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Highlights Key Portfolio Highlights Our portfolio positioning remains firmly behind cyclicals over defensives, driven principally by our key 2018 investment themes: synchronized global capex growth (Chart 1A) and higher interest rates on the back of a pickup in inflation (Chart 1B). The positioning has been lifted by synchronized global growth and a soft U.S. dollar (Chart 1C), while the key risk to our portfolio of a hard landing in China looks to be mitigated (Chart 1D). A return of volatility, spurred on by Fed tightening (Chart 1E), caused an SPX pullback in February, and while the market pushed through that rough patch, it has since been replaced with fears of a trade war, exacerbated by musical chairs in the Trump administration (Chart 1F). Our buy-the-dip strategy remains appropriate on a cyclical time horizon (Chart 1G), given a dearth of evidence of a recession in the next year. SPX forward EPS estimates still show near-20% increases this calendar year (corroborated by our EPS growth model, Chart 1H) which should underpin outsized equity returns in the absence of a major valuation rerating. Still, the return of volatility warrants a review of our macro, valuation and technical indicators. The best combination in our review is S&P financials (Overweight) with an elevated and accelerating cyclical macro indicator (CMI), fed by both of our key capex growth and rising interest rate themes, combined with a modest undervaluation. The worst combination is S&P telecom services (Underweight, high-conviction), whose CMI recently touched a 30-year low as sector deflation hit acute levels. Valuations make the sector look cheap, but every indication is that telecoms are a value trap. Chart 1AGlobal Trade Is Rising... Global Trade Is Rising... Global Trade Is Rising... Chart 1B...But So Too Is Inflation ...But So Too Is Inflation ...But So Too Is Inflation Chart 1CA Weaker Dollar Is A Boon To Growth A Weaker Dollar Is A Boon To Growth A Weaker Dollar Is A Boon To Growth Chart 1DSoft Landing In China Seems Likely Soft Landing In China Seems Likely Soft Landing In China Seems Likely Chart 1EThe Return Of Vol May Spoil The Party... The Return Of Vol May Spoil The Party... The Return Of Vol May Spoil The Party... Chart 1F...And Policy Uncertainty Doesnt Help ...And Policy Uncertainty Doesnt Help ...And Policy Uncertainty Doesnt Help Chart 1GBuy The Dip Has Worked Out Nicely Buy The Dip Has Worked Out Nicely Buy The Dip Has Worked Out Nicely Chart 1HHeed The Message From A Booming EPS Model Heed The Message From A Booming EPS Model Heed The Message From A Booming EPS Model Feature S&P Financials (Overweight) Our financials cyclical macro indicator (CMI, Chart 2) has climbed to new cyclical highs with significant upward momentum, driven by broad improvement in virtually all of its underlying components. More than any other variable, rising yields and the accompanying higher price of credit are a boon to financials. Higher interest rates is one of BCA's key themes for 2018 and an ongoing selloff in the bond market bodes well for profits in the heavyweight banks sub-index and should deliver the next up leg in bank stocks performance (top panel, Chart 3). Another of BCA's key themes for 2018 is a global capex upcycle; higher demand for capital goods should drive outsized capital formation in the year to come. Our U.S. commercial banks loans and leases model echoes this positive outlook, pointing to the best loan growth of the past 30 years (middle panel, Chart 3). Lastly, a low unemployment rate drives both expanding consumer credit and much better credit quality. At present, the unemployment rate is testing all-time lows, sending an unambiguously positive message for financials profitability (bottom panel, Chart 3). Despite the much-improved cyclical outlook and a revival of overall animal spirits, our valuation indicator (VI) suggests that financials are modestly undervalued. At this point in the cycle, we would expect a modest overvaluation; the implication is that financials should be a core portfolio overweight. Our technical indicator (TI) has approached overbought levels several times over the course of this bull market, though history suggests it can stay at elevated levels for a considerable time. Chart 2S&P Financials (Overweight) S&P Financials (Overweight) S&P Financials (Overweight) Chart 3RS1 Rising Yields Are A Boon To Financials Earnings RS1 Rising Yields Are A Boon To Financials Earnings RS1 Rising Yields Are A Boon To Financials Earnings S&P Industrials (Overweight) Our industrials CMI (Chart 4) has gone vertical and is very near its all-time high. A combination of a supportive currency, a recovery in commodity prices and synchronized global growth are responsible for the rise. A falling U.S. dollar and capital goods producers' top line growth acceleration have historically moved hand-in-hand as this group is one of the most international of the S&P 500. The trade-weighted U.S. dollar has fallen by more than 10% from its most recent peak at the end of 2016 which suggests U.S. industrials should have a leg up in sales for the year to come (top panel, Chart 5). The slide in the U.S. dollar is coming at an opportune time; global growth is remarkably synchronized (and remains a key BCA theme for 2018) and has proven an excellent harbinger of industrials margins (bottom panel, Chart 5). Overall, an expanding top line and widening margins imply solid relative EPS gains. Our valuation gauge is near the neutral zone, where it has been for much of the past 3 years as the market has failed to capture the sector's outlook strength. Our TI echoes the neutral message, having unwound a significant overbought position at the beginning of last year. Chart 4S&P Industrials (Overweight) S&P Industrials (Overweight) S&P Industrials (Overweight) Chart 5Global Euphoria Should Lift Industrials Global Euphoria Should Lift Industrials Global Euphoria Should Lift Industrials S&P Energy (Overweight) Our energy CMI (Chart 6) has maintained its upward trajectory after bouncing off all-time lows last year. Importantly, the relative share performance does not yet reflect the drastically improved cyclical conditions, underpinning our overweight recommendation. Falling oil inventories and rising prices (top and second panel, Chart 7) combined with solid gains in domestic production underlie the CMI recovery. Our key themes for 2018 of a global capex expansion and synchronized global growth should be the most important drivers for energy stocks this year. With respect to the former, the capex intentions from the Dallas Fed survey hit their highest level in a decade, which usually presages domestic oil patch expansion and energy stock outperformance (third panel, Chart 7) With respect to global growth, emerging markets/Chinese demand is the swing determinant of overall oil demand, and non-OECD demand has been moving higher for most of the past year (bottom panel, Chart 7). Our VI has retreated far into undervalued territory, a result of the aforementioned failure of stocks to react to the enticing macro outlook. The TI too is in deeply oversold levels, suggesting that an oversold bounce could soon occur at a time when valuations are so appealing. Chart 6S&P Energy (Overweight) S&P Energy (Overweight) S&P Energy (Overweight) Chart 7Energy Share Prices Have Trailed Oils Recovery Energy Share Prices Have Trailed Oil's Recovery Energy Share Prices Have Trailed Oils Recovery Energy Share Prices Have Trailed Oil's Recovery Energy Share Prices Have Trailed Oils Recovery S&P Consumer Staples (Overweight) Our consumer staples CMI (Chart 8) has turned up recently, following a two year decline. Strong employment gains and positive retail sales are the key pillars underlying the modest recovery. The euphoric consumer continues to push our consumer staples EPS model higher, now pointing to the best earnings growth of the past 5 years (middle panel, Chart 9). Overall industry exports are expanding at a healthy clip as a consequence of a softening U.S. dollar and robust European and rebounding emerging markets demand. Deflating raw food commodity prices are offsetting rising energy and labor input costs, heralding a sideways move to margins. Sell side analysts are also currently penciling in a lateral profit margin move (bottom panel, Chart 9). Investors have been vehemently avoiding staples stocks during the board market's uninterrupted run up, and have put our positioning offside. However, in the context of our cyclical over defensive portfolio bent we refrain from putting all our eggs in one basket, and prefer to keep consumer staples as our sole defensive sector overweight. Further, our VI is waving a green flag as consumer staples are now nearly two standard deviations below their 30-year mean valuation. Technical conditions too are completely washed out, signaling widespread bearishness, which is positive from a contrary perspective. Chart 8S&P Consumer Staples (Overweight) S&P Consumer Staples (Overweight) S&P Consumer Staples (Overweight) Chart 9Robust Consumer Confidence Bodes Well Robust Consumer Confidence Bodes Well Robust Consumer Confidence Bodes Well S&P Utilities (Neutral) Our utilities CMI (Chart 10) has spent the last decade in a long-term downtrend, albeit one with periodic countertrend moves. The key underlying factors are natural gas prices and relative spending on utilities, both of which have been retreating since 2008 (middle panel, Chart 11). Encouragingly, the sector's wage bill has slowed from punitively high levels, though pricing power has followed it down, implying muted margin changes (bottom panel, Chart 11). Like other defensive sectors, utilities have underperformed cyclical sectors in the last year; utilities equities trade as fixed income proxies, and a rising interest rate environment is punitive. As a result of the underperformance and relatively constant earnings, valuations have collapsed to the neutral zone. We reacted by booking solid gains and upgrading to a benchmark allocation earlier this year; synchronized global growth and higher interest rates are headwinds for this niche defensive sector and prevent us from lifting positions further. Our TI has fallen steeply over the past year and is now closing in on two standard deviations below the 30-year average. Chart 10S&P Utilities (Neutral) S&P Utilities (Neutral) S&P Utilities (Neutral) Chart 11Pricing Is Falling But Margins Look Neutral Pricing Is Falling But Margins Look Neutral Pricing Is Falling But Margins Look Neutral S&P Real Estate (Neutral) Our real estate CMI (Chart 12) has been in decline since its most recent peak at the end of 2016. This is confirmed by a darkened outlook for REITs; rents have crested while the vacancy rate found its nadir in 2016, suggesting further rent weakness on the horizon (top panel, Chart 13). Further, bankers appear less willing to extend commercial real estate credit, despite recent stability in underlying prices; declines in credit availability will directly impact REIT valuations (bottom panel, Chart 13). Our VI is consistent with BCA's Treasury bond indicator (not shown), indicating that both are at fair value. Our TI is starting to firm from extremely oversold levels, a positive indication for both 12- and 24-month relative performance. Chart 12S&P Real Estate (Neutral) S&P Real Estate (Neutral) S&P Real Estate (Neutral) Chart 13Peaking Rents and Tight Credit Are Headwinds Peaking Rents and Tight Credit Are Headwinds Peaking Rents and Tight Credit Are Headwinds S&P Materials (Neutral) Our materials CMI (Chart 14) has maintained its downward trajectory, largely due to the ongoing Fed tightening cycle. The heavyweight chemicals component of the materials index typically sees earnings (and hence stock prices) underperform as rates are moving higher (top panel, Chart 15). BCA's view remains that a sizable selloff in the bond markets is the most likely scenario in 2018, representing a substantial headwind to sector performance. Still, the news is not all negative. Exceptionally strong global demand growth has revitalized chemicals prices (bottom panel, Chart 15). Combined with the industry's relatively newfound restraint, capacity has not overextended and the resulting productivity gains bode well for earnings growth. Despite the improving outlook, valuations have been retreating for much of the past year and our VI has fallen back to the neutral zone. Our TI has been hovering near the neutral line for the past year, though a recent hook downward indicates a loss of momentum and downside relative performance risks. Chart 14S&P Materials (Neutral) S&P Materials (Neutral) S&P Materials (Neutral) Chart 15Rising Rates Are Offset By Improving Demand Rising Rates Are Offset By Improving Demand Rising Rates Are Offset By Improving Demand S&P Consumer Discretionary (Underweight) Our consumer discretionary CMI (Chart 16) has fallen back after reaching highs earlier in 2017, though remains elevated relative to the long term trend. Rising interest rates (top panel, Chart 17) are more than offsetting higher home prices and real wage growth, both have which have recently stalled. This rising short-term interest rate backdrop is not conducive to owning the extremely interest rate-sensitive equities that fall into the S&P consumer discretionary index. Both the household financial obligation ratio and household debt service payments have bottomed and are actually increasing. A higher interest rate backdrop will sustain the upward pressure on both and likely weigh on consumer discretionary relative share prices (third and bottom panels, Chart 17). This underpins our recent downgrade to a below benchmark allocation. Elevated valuations support our negative thesis as our valuation indicator has been rising recently out of the neutral zone. Our TI has fully recovered from oversold levels, and is now well into overbought territory, though historically this indicator has been excessively volatile. Chart 16S&P Consumer Discretionary (Underweight) S&P Consumer Discretionary (Underweight) S&P Consumer Discretionary (Underweight) Chart 17Higher Borrowing Costs Bode Ill For Consumer Discretionary Higher Borrowing Costs Bode Ill For Consumer Discretionary Higher Borrowing Costs Bode Ill For Consumer Discretionary S&P Health Care (Underweight) Our health care CMI (Chart 18) rolled over last year and has been treading water at these lower levels, driven by weak fundamentals in the key pharmaceuticals sector. Poor pricing power, a soft spending backdrop and a depreciating U.S. dollar have been pressuring the sector and keeping a tight lid on the CMI (top and second panels, Chart 19). Other non-pharma indicators are mixed as lower healthcare consumer spending is offset by a tick up in overall pricing power. Relative valuations have fallen deep into undervalued territory and are approaching one standard deviation below the 25 year average. Our TI too has reversed course and is well into oversold territory. However, the message from our health care earnings model is that sector earnings will continue to decelerate; this environment in not conducive for a sector re-rating (bottom panel, Chart 19). Chart 18S&P Health Care (Underweight) S&P Health Care (Underweight) S&P Health Care (Underweight) Chart 19Pharma Pricing Power Continues To Collapse Pharma Pricing Power Continues To Collapse Pharma Pricing Power Continues To Collapse S&P Telecommunication Services (Underweight) Our telecom services CMI (Chart 20), after moving sideways for much of the past decade, has recently fallen to a new 30-year low. Extreme deflation continues to reign in the beleaguered sector as relative consumer outlays on telecom services have nosedived (top panel, Chart 21) which is broadly matched by melting selling prices (middle panel, Chart 21) as demand contracts. This is reflected in our S&P telecom services revenue growth model, which remains deep in contractionary territory (bottom panel, Chart 21). The sector remains chronically cheap, exacerbated by the recent sell-off, and is currently as cheap as it has ever been. Still, given the brutal operating environment, we think such valuations have created a value trap. Our Technical Indicator has sunk but, like the VI, cycles deep in the sell zone have not proven reliable indicators that a relative bounce is in the offing. We recently downgraded the sector to underweight and added it to our high-conviction underweight list based on the factors noted above.1 Chart 20S&P Telecommunication Services (Underweight) S&P Telecommunication Services (Underweight) S&P Telecommunication Services (Underweight) Chart 21Telecom Services Remain A Value Trap Telecom Services Remain A Value Trap Telecom Services Remain A Value Trap S&P Technology (Underweight, Upgrade Alert) The technology CMI (Chart 22) has been falling for the past three years, driven by ongoing relative pricing power declines and new order weakness. However, the sector has proven resilient, at least until recently, as a handful of stocks (the FANGs, excluding the consumer discretionary components) and the red-hot semiconductor group have provided support. Still, market euphoria aside, tech stocks thrive in a disinflationary/deflationary environment and suffer during inflationary periods; inflation is gradually rising after a prolonged disinflationary period (bottom panel, Chart 23). Valuations, while still in the neutral zone, have reached their highest level in a decade. This may prove risky should inflation mount faster than expected; a de-rating phase in technology would likely follow. Our TI is extremely overbought, though it has been at this high level for several years. Chart 22S&P Technology (Underweight, Upgrade ALert) S&P Technology (Underweight, Upgrade ALert) S&P Technology (Underweight, Upgrade ALert) Chart 23Inflation Is No Friend To Tech Inflation Is No Friend To Tech Inflation Is No Friend To Tech Size Indicator (Neutral Small Vs. Large Caps) Our size CMI (Chart 24) has fallen back to the boom/bust line. Keep in mind that this CMI is not designed as a directional trend predictor, but rather as a buy/sell oscillator; the current message is neutral. Small company business optimism is near modern highs, as pricing and consumption vigor push domestic revenues higher (top panel, Chart 25). A smaller government footprint, i.e. fewer regulatory hurdles, and tax relief will disproportionately benefit SMEs. Earlier this year, we downgraded our recommendation on small caps vs. large caps to a neutral allocation, based on a deterioration in small cap margins and too-high leverage.2 Recent NFIB surveys would suggest this move was prescient; firms reporting planned labor compensation increases have steadied near a two decade high, while price increases are trailing far behind (middle panel, Chart 25). With "quality of labor" having overtaken "taxes" as the single most important problem facing businesses, labor compensation growth seems likely to continue moving up at an elevated pace and small cap margins should likely continue to trail large cap peers (bottom panel, Chart 25). Valuations have improved and small caps are relatively undervalued, though our TI echoes a neutral message. Chart 24Size Indicator (Neutral Small Vs. Large Caps) Size Indicator (Neutral Small Vs. Large Caps) Size Indicator (Neutral Small Vs. Large Caps) Chart 25Small Businesses Remain Exceptionally Confident Small Businesses Remain Exceptionally Confident Small Businesses Remain Exceptionally Confident Chris Bowes, Associate Editor chrisb@bcaresearch.com 1 Please see BCA U.S. Equity Strategy Weekly Report, "Manic-Depressive?" dated February 12, 2018, available at uses.bcaresearch.com. 2 Please see BCA U.S. Equity Strategy Weekly Report, "Too Good To Be True?" dated January 22, 2018, available at uses.bcaresearch.com.

Highlights With North Korean diplomacy on track, Taiwan is the country most exposed to U.S.-China trade and strategic tensions. The Taiwanese public supports the status quo; however, a majority sees itself as exclusively Taiwanese, and the desire for independence may grow over time. Domestic political changes in mainland China and in the United States are also conducive to greater geopolitical tensions affecting Taiwan. Beijing will likely refrain from excessive pressure in the lead-up to Taiwan's November local elections ... but an independence-leaning outcome could change that. Stay overweight Taiwan within Emerging Market portfolios, but be prepared to downgrade if latent geopolitical risks begin to materialize. Feature The decision by the United States to toughen its enforcement of trade rules with China marks a shift that will have lasting ramifications.1 The U.S. is concerned not only about the trade imbalance but also the national security risk posed by China's economic might and increasing technological prowess. Hence President Donald Trump has imposed trade measures on China despite Chinese President Xi Jinping's cooperation on North Korea. Xi has enforced sanctions on the North and thus forced Kim Jong Un to the negotiating table, even getting him to consider denuclearization (Chart 1). Global financial markets may "climb the wall of worry" about the latest tariffs because the Trump administration has moderated its rhetoric in practice, notably by choosing to prosecute China in the World Trade Organization. However, the protectionist shift in U.S. policy is a lasting one. American power is declining relative to China, and the two countries no longer share the same economic interdependency that acted as a deterrent to conflict in the past (Chart 2).2 Chart 1China Gives Kim To Trump China Gives Kim To Trump China Gives Kim To Trump Chart 2Structural Increase In U.S.-China Tensions Structural Increase In U.S.-China Tensions Structural Increase In U.S.-China Tensions Taiwan is the country that is most exposed to both trade and strategic tensions between the U.S. and China (Chart 3). Indeed, BCA's Geopolitical Strategy has held since January 2016 that Taiwan is a potential geopolitical black swan.3 Does this warrant shifting to an underweight stance in EM portfolios? Not yet. But it is a left tail risk that investors should have on their radar. Taiwan Is Filled With Dry Powder There are three reasons to suspect that Taiwan geopolitical risk is understated. First, Chinese President Xi Jinping has consolidated power and made himself into Chairman Mao Zedong's peer in the Communist Party's ideological hierarchy. He is in power indefinitely. Xi has also followed his predecessor Jiang Zemin, in the 1990s, in taking a tough approach to security and defense. Implicitly he wants to make sure that unification occurs by 2049, but some argue that he wants to achieve it within his lifetime, namely by 2035. The Taiwanese public is resolutely opposed to any timetable. The fundamental risk is that economic slowdown could disappoint the aspirations of a big and ambitious middle class, which could force Xi to pursue nationalism and foreign aggression as a way to maintain domestic control (Chart 4). Beijing is still unlikely to attack Taiwan other than as a last resort, due to the American alliance system protecting it: this remains a hard constraint for now. But aggressive economic sanctions and military posturing with the intention to coerce Taiwan are much more likely than investors realize today. Chart 3Taiwan's Economy As Well As Security On The Line Taiwan's Economy As Well As Security On The Line Taiwan's Economy As Well As Security On The Line Chart 4China's Stability Vulnerable To Growth Slowdown China's Stability Vulnerable To Growth Slowdown China's Stability Vulnerable To Growth Slowdown Second, Taiwan's independence-leaning Democratic Progressive Party (DPP) has gained control of every level of government on the island - the presidency, the legislature, the municipalities - since the large-scale, anti-mainland "Sunflower" protests of 2014. President Tsai Ing-wen, who replaced the outspokenly pro-China President Ma Ying-jeou, is vocally uncomfortable with the status quo. She has refused to positively affirm the "1992 Consensus," which holds that there is only "One China" but two interpretations. Beijing sees this idea as the basis of smooth cross-strait relations. Tsai has not in practice tried to break the status quo, but she is clearly interested in enhancing Taiwan's autonomy. Moreover, a youthful "Third Force" has emerged in Taiwanese politics, with the backing of former presidents Lee Teng-hui and Chen Shui-bian, arguing for independence and the right to hold popular referendums on the question of sovereignty. Any success of this movement will provoke a massive response from China. Third, U.S. President Trump has suggested in several poignant ways that his tougher approach to China will entail a more robust American guarantee of Taiwan's security. While he has promised Xi to uphold the "One China policy," he is actively upgrading diplomatic and possibly naval relations with Taiwan and considering more substantial arms sales to Taiwan.4 His negotiation style suggests that he is not afraid to touch this "third rail" in Sino-American relations. Moreover, in the wake of the 1995-96 Third Taiwan Strait Crisis, and again in the wake of the Global Financial Crisis, a hugely important shift in Taiwanese national identity accelerated. Today the public mostly identifies solely as Taiwanese, as opposed to both Taiwanese and Chinese (Chart 5). This trend has abated somewhat since the DPP rose to full control in 2014-16, but a 55% majority still sees itself as exclusively Taiwanese. Among the youth, that number is 70%. This dynamic raises the possibility that a political independence movement could one day emerge. Beijing, at any rate, is watching with great concern. Of course, this shift in national identity does not imply that Taiwanese want to declare independence for the state of Taiwan anytime soon. Only about 22% want the country to move toward formal independence, and only 5% want to declare independence today. Whereas 69% are comfortable maintaining the status quo for a long time (Chart 6). The Taiwanese want to preserve their de facto independence and continue to prosper. But support for independence has grown faster than support for the status quo since the 1994 consensus. The status quo barely, if at all, holds majority support if one removes from its ranks those who eventually want to see the country declare independence. And younger cohorts have larger majorities than older cohorts in favor of independence. Chart 5Majority Of Taiwanese Are Exclusively Taiwanese ... Taiwan Is A Potential Black Swan Taiwan Is A Potential Black Swan Chart 6... Yet Majority Support Status Quo For Now Taiwan Is A Potential Black Swan Taiwan Is A Potential Black Swan The point is that there is a lot of "dry powder" in Taiwanese public opinion that could be ignited against China in the event of a change of circumstances, i.e. another military crisis or economic shock. Essentially, China is worried that someday this national identity could be weaponized. Chart 7China Gains Leverage Over Time China Gains Leverage Over Time China Gains Leverage Over Time How will China respond to the situation? So far it has not overreacted. Xi Jinping has launched more intimidating military drills and has hardened his rhetoric - including in key reports at the 2017 party congress and this year's National People's Congress. His administration has also pursued policies to emphasize its dominance, such as setting up new air traffic routes over the strait that Taiwan claims violate its rights.5 Nevertheless, the cross-strait status quo has not yet changed in any fundamental way that would suggest relations are about to explode. And this is fitting because the status quo is beneficial to the mainland, having created a vast imbalance of economic influence over Taiwan (Chart 7). This imbalance gives China the ability to use economic coercion to dissuade Taiwan's leaders from trying anything too daring. This year, in particular, there is reason to think that Xi Jinping may want to limit any provocations. Taiwan will hold local elections on November 24, an opportunity for the pro-China Kuomintang (KMT) to at least begin to claw back the political stature it has lost (Chart 8). A good showing in 2018 is essential for the KMT if it is to rebuild momentum for the 2020 general election. Tsai's and the DPP's approval ratings have fallen precipitously since her inauguration (Chart 9). Xi may deem that saber-rattling would be counterproductive by giving Tsai and the DPP a foil, when in fact the tide is already working against them. If the KMT's performance is abysmal in the November elections, then Beijing faces a problem. Its strategy of gaining influence over Taiwan through economic integration has not prevented the emergence of an exclusively Taiwanese identity. So far Beijing has not given up on this strategy but that might become a concern if the Xi administration treads softly this year and yet the DPP broadens its control of local offices. Worse still for Beijing would be sweeping gains for outspoken, pro-independence candidates, since China cannot expel them from the legislature as easily as it did their peers in Hong Kong. Chart 8Kuomintang Needs A Win In 2018 Taiwan Is A Potential Black Swan Taiwan Is A Potential Black Swan Chart 9DPP Only Leads KMT By A Little Now Taiwan Is A Potential Black Swan Taiwan Is A Potential Black Swan Bottom Line: Political changes in China, Taiwan, and the United States are conducive to souring relations across the strait. Moreover, Taiwanese national identity is dry powder that Beijing fears could be exploited by independence-leaning politicians - potentially with American backing from an aggressive President Trump. This three-way dynamic means that Taiwanese geopolitical risk is understated, despite the fact that these powers are all familiar with the dynamics and Beijing may not want to overly provoke voters ahead of local elections, knowing that heavy-handedness in 1995-96 encouraged Taiwanese uniqueness. Macro Backdrop And Trade Tensions Undermine DPP The problem for President Tsai and the ruling DPP, as local elections approach, is that the Taiwanese economy faces headwinds as Chinese and Asian trade slows down and as the Trump administration converts its protectionist rhetoric into action. Since last year, China has tightened financial conditions and regulation and has cracked down on corruption in the financial sector. The result is a slump in broad money supply that is now pointing to a drop in EM and Taiwanese exports (Chart 10). Indeed, a cyclical slowdown is emerging in Taiwan: The short-term loans impulse is weakening which suggests that Taiwanese export growth will slow further (Chart 11, top panel). The basis for this relationship is that short-term loans are used by Taiwanese businesses to fund their working capital needs as well as purchase inputs to fill their export orders. Further, broad money is also weak (Chart 11, bottom panel). Chart 10China Slowdown Spells Trouble For Taiwan bca.gps_sr_2018_03_30_c10 bca.gps_sr_2018_03_30_c10 Chart 11Taiwanese Money/Credit Growth Slowing Taiwanese Money/Credit Growth Slowing Taiwanese Money/Credit Growth Slowing The manufacturing sector is slowing, with the shipments-to-inventories ratio weak and manufacturing PMI dipping sharply (Chart 12). Worryingly, the new orders, export orders, and electronic-sector employment components of the manufacturing PMI are approaching a precarious level. Various prices of semiconductors are also starting to show signs of weakness globally which does not bode well for a market that relies heavily on this trade. The semiconductor shipment-to-inventory ratio has rolled over (Chart 13). Taiwanese exports to ASEAN are also slowing, which signifies that final demand for semiconductors is softening, as ASEAN economies lie at the final stage of the semiconductor supply chain process. Chart 12Manufacturing Indicators Rolling Over Manufacturing Indicators Rolling Over Manufacturing Indicators Rolling Over Chart 13Softness In Key Semiconductor Exports Softness In Key Semiconductor Exports Softness In Key Semiconductor Exports Further, global trade tensions have the potential to harm global growth and especially heavily trade-exposed economies like Taiwan. Taiwan is not guaranteed to benefit from the U.S.'s more aggressive posture toward China. Theoretically, if the U.S. imposes tariffs on goods from China that can be substituted by Taiwan, then Taiwan will benefit. But in practice, the U.S. is using tariffs as a threat to force China to open its market more to U.S. exports. One way that Beijing may respond is by purchasing American goods instead of goods that come from American allies like Taiwan. Beijing has already attempted this strategy by offering to increase imports of American semiconductors at the expense of Taiwan and South Korea. At the moment there are no details on how much of an increase China is proposing. In Table 1 we show several scenarios to assess the damage that could be inflicted on Taiwan if China substituted away from it. The impact on Taiwan's exports is not negligible. For instance, under the benign scenario, if U.S.'s share of semiconductor exports to China rise from 4%6 to 10%, then Taiwan's share of semiconductor exports to China would drop from 15% to 12%. That would amount to a $4 billion loss for Taiwan, approximately, which represents 1.4% share of its total exports and 4% of its overall semiconductor exports. This analysis assumes that the trade losses resulting from China's shift to its semiconductor import mix would harm Taiwan somewhat more than Korea. The latter holds a competitive advantage on Taiwan as Korea designs and manufactures unique semiconductors that are not as easily substitutable. At any rate, the damage to Taiwan's geopolitical and trade outlook would be more concerning than the loss of revenue. Table 1China's Trade Concessions To U.S. Could Impose Costs On U.S. Allies Taiwan Is A Potential Black Swan Taiwan Is A Potential Black Swan It is unlikely that the Trump administration is willing to accept such a deal, which is flagrantly designed to appease the U.S. at the expense of its allies. But the exercise illustrates a broader dynamic in which U.S. negotiations with China threaten to disrupt trade relationships and supply chains that have benefited Taiwan in recent decades. The result will be greater uncertainty and a higher potential for negative shocks. Chart 14China Punishes Taiwan For 2016 Election China Punishes Taiwan For 2016 Election China Punishes Taiwan For 2016 Election Moreover, the Trump administration has not entirely exempted allies from trade pressure. For instance, Taiwan has appreciated the dollar a bit in response to the threat of punishment for currency manipulation from the U.S. Washington has also just secured assurances from South Korea that it will not competitively depreciate the won. If agreements like these stand, and yet China makes less robust or less permanent agreements regarding its own currency, South Korea and Taiwan could suffer marginal losses of competitiveness. Taiwan is also exposed to coercive economic measures from China. Since Tsai's election, Beijing has made a notable effort to reduce tourist travel to Taiwan, which is reflected in tourism and flight data (Chart 14). Given the context of political tensions, the risk of discrete sanctions will persist and could flare up at any time if an incident occurs that aggravates the distrust between the two governments. How will investors know if Taiwanese geopolitical risk is about to spike upwards? At the moment, geopolitical risk is subdued, according to a proxy based on USD/JPY and USD/KRW exchange rates and relative Taiwanese/American inflation (Chart 15). This indicator tracks well with previous cross-strait crises. It even jumped upon the heightened tensions around the 2016 election of Tsai, and her controversial phone call with Donald Trump after his election. At the moment it suggests that cross-strait tensions have subsided significantly, despite the cutoff in formal diplomatic communication. However, the low point of the measure, and the underlying political factors outlined in the previous section, suggest that it should rise going forward. Chart 15Taiwanese Geopolitical Risk Likely To Rise From Here Taiwanese Geopolitical Risk Likely To Rise From Here Taiwanese Geopolitical Risk Likely To Rise From Here In the short run, it will be important to watch the Trump administration's handling of diplomatic visits and arms sales to Taiwan. Trump's signing of the Taiwan Travel Act has elevated diplomatic exchanges in a way that is mostly symbolic but could still spark an episode of heightened tension with China that would result in economic sanctions. An unprecedented naval port call could turn into an incident. At the same time, the U.S. guarantees Taiwan's security and in token of that guarantee periodically provides Taiwan with weapons packages. Beijing, for its part, always protests these sales, more or less vigorously depending on the military capabilities in question. The currently slated one is not too big but there is a rumor that it will include F-35 stealth fighter jets; other surprises could occur. Traditionally, the biggest spikes in sales have fallen under Democratic, not Republican, administrations. However, Trump may change that. There is a consensus in Washington that policy toward China should get tougher. The Taiwan Travel Act, upgrading diplomatic ties, passed with unanimous consent in both the House and Senate. Taiwanese governments have a record of increasing military spending when Republican presidents sit in Washington. And the first DPP government, under Chen Shui-bian from 2000-08, marked a clear upturn in Taiwanese military spending growth (Chart 16). If the Trump administration decides to sell Taiwan weapon systems that make a qualitative difference in the military balance, it will raise tensions with Beijing and likely prompt economic sanctions against Taiwan. Chart 16Arms Sales Could Reemerge As An Irritant Arms Sales Could Reemerge As An Irritant Arms Sales Could Reemerge As An Irritant In the long run, there are three key negotiations taking place in the region that could increase Taiwanese geopolitical risk: U.S.-China trade negotiations: Taiwan has benefited from China's engagement with the U.S., and with the West more broadly, and stands to suffer if they disengage. That would herald rising strategic tensions that would put Taiwan's trade and security in jeopardy. Geopolitical risk would go up. North Korean diplomacy: Kim Jong Un has met with Xi Jinping and formally agreed to hold bilateral summits with Presidents Trump and Moon Jae-in of South Korea. He has also indicated that denuclearization is on the table. If the different parties enter onto a path towards a peace treaty and denuclearization, then Taiwan might worry that the U.S. will eventually remove troops from the peninsula - far-fetched but not out of the question. Taiwan would fear abandonment and could attempt to entangle the U.S. For its part, China could believe that cooperation on North Korea requires the U.S. to give China greater sway over Taiwan. Geopolitical risk would go up. The South China Sea: These sea lanes are vital to Taiwan as well as China, South Korea, and Japan. If the U.S. washes its hands of the matter, ceding China a maritime sphere of influence, Taiwan will face both greater supply risk and greater anxiety about American commitment to its security. Beijing might be emboldened to pressure Taiwan, or Taiwan might act out to try to secure American support. Geopolitical risk would go up. Bottom Line: Taiwan's economy is entering a cyclical slowdown on the back of China's slowdown and rollover in the semiconductor industry. At the same time, trade tensions emanating from the U.S.-China negotiations and political tensions emanating from the other side of the strait suggest that Taiwan's geopolitical risk premium will rise. Over the short term, Taiwan's local elections, the referendum movement, or U.S. diplomacy or arms sales could provide a catalyst for a cross-strait crisis. Over the long term, significant changes in U.S.-China relations, North Korea, or the South China Sea could put Taiwan in a more precarious position. Investment Conclusions While the absolute outlook for Taiwanese stock prices is negative, the potential downside in share prices in U.S. dollar terms is lower than for the EM benchmark. BCA's Emerging Markets Strategy recommends that EM-dedicated investors remain overweight Taiwanese risk assets relative to the EM benchmark. First, the epicenter of China's slowdown is capital spending in general and construction in particular. Various Chinese industrial activity indicators have already begun decelerating. This is negative for industrial commodity prices and countries that produce them. Taiwan is less exposed to China's construction slump than many other EM economies. Second, China's spending on technology will not slow much. As a part of its ongoing reforms, Beijing will encourage more investment in technology as well as upgrading industries across the value-added curve. Hence, China's tech spending will outperform its expenditure on construction and infrastructure. Taiwan is poised to benefit from this relative shift in China's growth priorities. Third, there are no fresh credit excesses in Taiwan like in some other EMs. Taiwan's banking system worked out bad assets extensively following the credit excesses of the 1980s-90s. Hence it is less vulnerable than its peers in the developing world. Finally, Taiwan has an enormous current account surplus of 14% of GDP and, contrary to many other EMs, foreign investors hold few Taiwanese local bonds. When outflows from EM occur, the Taiwanese currency will fall under less pressure and its financial system under much less stress. This will allow Taiwanese stocks to act as a low-beta defensive play. Crucially, despite some appreciation to appease Trump, the Taiwanese dollar is among the cheapest currencies in EM (Chart 17). Chart 17Cheap Taiwanese Dollar Removes Risk Cheap Taiwanese Dollar Removes Risk Cheap Taiwanese Dollar Removes Risk As for heightened geopolitical risk, BCA's Geopolitical Strategy would note that while we view Taiwan as a potential "black swan," nevertheless tail risks are not the proper basis for an investment strategy. We will continue to monitor the situation so that we can alert clients when a major, market-relevant deterioration in cross-strait relations appears imminent, based largely on the factors highlighted above. If the DPP remains dominant after the local elections later this year, or if "Third Forces" make notable gains, we would suspect that the Xi administration will shift to using more sticks than carrots. This could include economic sanctions and military saber-rattling. The question then will be whether Beijing (or Washington or Taipei) attempts a material change to the status quo. Ultimately - from a bird's eye point of view - a war is more likely in the wake of Xi Jinping's elimination of term limits, consolidation of power, and the secular slowdown in China's economy and rise of Chinese nationalism. But we see no reason to fear such a catastrophic outcome in the near term. Matt Gertken, Associate Vice President Geopolitical Strategy mattg@bcaresearch.com Ayman Kawtharani, Associate Editor ayman@bcaresearch.com 1 Please see BCA Geopolitical Strategy Weekly Report, "We Are All Geopolitical Strategists Now," dated March 28, 2018, available at gps.bcaresearch.com. 2 Please see BCA Geopolitical Strategy Special Report, "Sino-American Conflict: More Likely Than You Think, Part II," dated November 6, 2015, available at gps.bcaresearch.com. 3 Please see BCA Geopolitical Strategy Special Report, "Taiwan's Election: How Dire Will The Straits Get?" dated January 13, 2016, and "Scared Yet? Five Black Swans For 2016," dated February 10, 2016, available at gps.bcaresearch.com. 4 Trump began, as president-elect, by holding an unprecedented telephone call with the Taiwanese president. His administration has since requested a new $1.4 billion arms package, opened legal space for port calls (including potentially naval port calls) in the 2018 Defense Authorization Act, and for higher-level diplomatic meetings via the Taiwan Travel Act, which became public law on March 16, 2018. 5 Please see BCA Geopolitical Strategy Weekly Report, "Watching Five Risks," dated January 24, 2018, available at gps.bcaresearch.com. Military drills have involved symbolic shows, like sailing China's only operational aircraft carrier along the mid-line of the Taiwan Strait, as well as more poignant maneuvers, like drilling north and south of Taiwan simultaneously. As for rhetoric, Xi omitted from his 2017 party congress speech any reference to hopes that the Taiwanese "people" would bring about unification; in his speech after the March National People's Congress, he warned of the "punishment of history" for those who would promote secession. 6 Shown as the average of 2015 and 2017.

Highlights Several economic and financial market indicators point to a budding downtrend in Chinese capital spending and its industrial sector. The recent underperformance of global mining, chemicals and machinery/industrials corroborate that capital spending in China is starting to slump. Shipments-to-inventory ratios for Korea and Taiwan also point to a relapse in Asian manufacturing. This is occurring as our global growth sentiment proxy sits on par with previous peaks, and investor positioning in EM and commodities is overextended. Stay put on EM. Markets with currency pegs to the U.S. dollar, such as the Gulf states and Hong Kong, will face tightening local liquidity. Share prices in these markets have probably topped out. Feature On the surface, EM equities, currencies and local bond and credit markets are still trading well. However, there are several economic indicators and financial variables that herald negative surprises for global and Chinese growth. In particular: China's NBS manufacturing PMI new orders and backlogs of orders have relapsed in the past several months. Chart I-1 illustrates the annual change in new orders and backlogs of orders to adjust for seasonality. The measure leads industrial profits, and presently foreshadows a slowdown going forward. Furthermore, the average of NBS manufacturing PMI, new orders, and backlog orders also points to a potential relapse in industrial metals prices in general as well as mainland steel and iron ore prices (Chart I-2). The message from Charts I-1 and I-2 is that the recent weakness in iron ore and steel prices could mark the beginning of a downtrend in Chinese capital spending. While supply cuts could limit downside in steel prices, it would be surprising if demand weakness does not affect steel prices at all.1 Chart I-1China: Slowdown Has Further To Run China: Slowdown Has Further To Run China: Slowdown Has Further To Run Chart I-2Industrial Metals Prices Have Topped Out Industrial Metals Prices Have Topped Out Industrial Metals Prices Have Topped Out Although China's money and credit have been flagging potential economic weakness for a while, the recent manufacturing PMI data from the National Bureau of Statistics finally confirmed an impending deceleration in industrial activity and ensuing corporate profit disappointment. Our credit and fiscal spending impulses continue to point to negative growth surprises in capital spending. The latter is corroborated by the weakening Komatsu's Komtrax index, which measures the average hours of machine work per unit in China (Chart I-3). In both Korea and Taiwan, the overall manufacturing shipments-to-inventory ratios have dropped, heralding material weakness in both countries' export volumes (Chart I-4). Chart I-3Signs Of Weakness In Chinese Construction Signs Of Weakness In Chinese Construction Signs Of Weakness In Chinese Construction Chart I-4Asia Exports Are Slowing Asia Exports Are Slowing Asia Exports Are Slowing Notably, global cyclical equity sectors that are leveraged to China's capital spending such as materials, industrials and energy have all recently underperformed the global benchmark (Chart I-5). Some of their sub-sectors such as machinery, mining and chemicals have also begun to underperform (Chart I-6). Chart I-5Global Cyclicals Have ##br##Begun Underperforming... Global Cyclicals Have Begun Underperforming... Global Cyclicals Have Begun Underperforming... Chart I-6...Including Machinery ##br##And Chemical Stocks ...Including Machinery And Chemical Stocks ...Including Machinery And Chemical Stocks Among both global and U.S. traditional cyclicals, only the technology sector is outperforming the benchmark. However, we do not think tech should be treated as a cyclical sector, at least for now. In brief, the underperformance of global cyclical equity sectors and sub-sectors following last month's equity market correction corroborate that China's capital spending is beginning to slump. Notably, this is occurring as our global growth sentiment proxy rests on par with its previous apexes (Chart I-7). Previous tops in this proxy for global growth sentiment have historically coincided with tops in EM EPS net revisions, as shown in this chart. Chart I-7Global Growth Sentiment: As Good As It Gets Global Growth Sentiment: As Good As It Gets Global Growth Sentiment: As Good As It Gets All told, we may be finally entering a meaningful slowdown in China that will dampen commodities prices and EM corporate earnings. The latter are still very strong but EPS net revisions have rolled over and turned negative again (Chart I-8). Chart I-8EM EPS Net Revisions Have Plummeted EM EPS Net Revisions Have Plummeted EM EPS Net Revisions Have Plummeted EM share prices typically lead EPS by about nine months. In 2016, EM stocks bottomed in January-February, yet EPS did not begin to post gains until December 2016. Even if EM corporate profits are to contract in the fourth quarter of this year, EM share prices, being forward looking, will likely begin to wobble soon. Poor EM Equity Breadth There is also evidence of poor breadth in the EM equity universe, especially compared to the U.S. equity market. First, the rally in the EM equally-weighted index - where all individual stocks have equal weights - has substantially lagged the market cap-weighted index since mid 2017. This suggests that only a few large-cap companies have contributed a non-trivial share of capital gains. Second, the EM equal-weighted stock index's and EM small-caps' relative share prices versus their respective U.S. counterparts have fallen rather decisively in the past six weeks (Chart I-9, top and middle panels). While the relative performance of market cap-weighted indexes has not declined that much, it has still rolled over (Chart I-9, bottom panel). We compare EM equity performance with that of the U.S. because DM ex-U.S. share prices themselves have been rather sluggish. In fact, DM ex-U.S. share prices have barely rebounded since the February correction. Third, EM technology stocks have begun underperforming their global peers (Chart I-10). This is a departure from the dynamics that prevailed last year, when a substantial share of EM outperformance versus DM equities was attributed to EM tech outperformance versus their DM counterparts and tech's large weight in the EM benchmark. Chart I-9EM Versus U.S. Equities: Relative ##br##Performance Is Reversing EM Versus U.S. Equities: Relative Performance Is Reversing EM Versus U.S. Equities: Relative Performance Is Reversing Chart I-10EM Tech Has Started ##br##Underperforming DM Tech EM Tech Has Started Underperforming DM Tech EM Tech Has Started Underperforming DM Tech Finally, the relative advance-decline line between EM versus U.S. bourses has been deteriorating (Chart I-11). This reveals that EM equity breadth - the advance-decline line - is substantially worse relative to the U.S. Chart I-11EM Versus U.S.: Relative Equity Breadth Is Very Poor EM Versus U.S.: Relative Equity Breadth Is Very Poor EM Versus U.S.: Relative Equity Breadth Is Very Poor Bottom Line: Breadth of EM equity performance versus DM/U.S. has worsened considerably. This bodes ill for the sustainability of EM outperformance versus DM/U.S. We continue to recommend an underweight EM versus DM position within global equity portfolios. Three Pillars Of EM Stocks EM equity performance is by and large driven by three sectors: technology, banks (financials) and commodities. Table I-1 illustrates that technology, financials and commodities (energy and materials) account for 66% of the EM MSCI market cap and 75% of MSCI EM total (non-diluted) corporate earnings. Therefore, getting the outlook of these sectors right is crucial to the EM equity call. Table I-1EM Equity Sectors: Earnings & Market Cap Weights EM: Disguised Risks EM: Disguised Risks Technology Four companies - Alibaba, Tencent, Samsung and TSMC - account for 17% of EM and 58% of EM technology market cap, respectively. This sector can be segregated into hardware tech (Samsung and TSMC) and "new concept" stocks (Alibaba and Tencent). We do not doubt that new technologies will transform many industries, and there will be successful companies that profit enormously from this process. Nevertheless, from a top-down perspective, we can offer little insight on whether EM's "new concept" stocks such as Alibaba and Tencent are cheap or expensive, nor whether their business models are proficient. Further, these and other global internet/social media companies' revenues are not driven by business cycle dynamics, making top-down analysis less imperative in forecasting their performance. We can offer some insight for technology hardware companies such as Samsung and TSMC. Chart I-12 demonstrates that semiconductor shipment-to-inventory ratios have rolled over decisively in both Korea and Taiwan. In addition, semiconductor prices have softened of late (Chart I-13) Together, this raises a red flag for technology hardware stocks in Asia. Chart I-12Asia's Semiconductor Industry Asia's Semiconductor Industry Asia's Semiconductor Industry Chart I-13Semiconductor Prices: A Soft Spot? Semiconductor Prices: A Soft Spot? Semiconductor Prices: A Soft Spot? Finally, Chart I-14 compares the current run-up in U.S. FANG stocks (Facebook, Amazon, Netflix and Google) with the Nasdaq mania in the 1990s. An equal-weighted average stock price index of FANG has risen by 10-fold in the past four and a half years. Chart I-14U.S. FANG Stocks Now ##br##And 1990s Nasdaq Mania U.S. FANG Stocks Now And 1990s Nasdaq Mania U.S. FANG Stocks Now And 1990s Nasdaq Mania A similar 10-fold increase was also registered by the Nasdaq top 100 stocks in the 1990s over eight years (Chart I-14). While this is certainly not a scientific approach, the comparison helps put the rally in "hot" technology stocks into proper historical perspective. The main take away here is that even by bubble standards, the recent acceleration in "new concept" stocks has been too fast. That said, it is impossible to forecast how long any mania will persist. This has been and remains a major risk to our investment strategy of being negative on EM stocks. In sum, there is little visibility in EM "new concept" tech stocks. Yet Asia's manufacturing cycle is rolling over, entailing downside risks to tech hardware businesses. Putting all this together, we conclude that it is unlikely that EM tech stocks will be able to drive the EM rally and outperformance in 2018 as they did in 2017. Banks We discussed the outlook for EM bank stocks in our February 14 report,2 and will not delve into additional details here. In brief, several countries' banks have boosted their 2017 profits by reducing their NPL provisions. This has artificially boosted profits and spurred investors to bid up bank equity prices. We believe banks in a number of EM countries are meaningfully under-provisioned and will have to augment their NPL provisions. The latter will hurt their profits and constitutes a major risk for EM bank share prices. Energy And Materials The outlook for absolute performance of these sectors is contingent on commodities prices. Industrial metals prices are at risk of slower capex in China. The mainland accounts for 50% of global demand for all industrial metals. Oil prices are at risk from traders' record-high net long positions in oil futures, according to CFTC data (Chart I-15, top panel). Traders' net long positions in copper are also elevated, according to the data from the same source (Chart I-15, bottom panel). Hence, it may require only some U.S. dollar strength and negative news out of China for these commodities prices to relapse. Chart I-15Traders' Net Long Positions In ##br##Oil And Copper Are Very Elevated Traders' Net Long Positions In Oil And Copper Are Very Elevated Traders' Net Long Positions In Oil And Copper Are Very Elevated How do we incorporate the improved balance sheets of materials and energy companies into our analysis? If and as commodities prices slide, share prices of commodities producers will deflate in absolute terms. However, this does not necessarily mean they will underperform the overall equity benchmark. Relative performance dynamics also depend on the performance of other sectors. Commodities companies could outperform the overall equity benchmark amid deflating commodities prices if other equity sectors drop more. In brief, the improved balance sheets of commodities producers may be reflected in terms of their relative resilience amid falling commodities prices but will still not preclude their share prices from declining in absolute terms. Bottom Line: If EM bank stocks and commodities prices relapse as we expect, the overall EM equity index will likely experience a meaningful selloff and underperform the DM/U.S. benchmarks. Exchange Rate Pegs Versus U.S. Dollar With the U.S. dollar depreciating in the past 12 months, pressure on exchange rate regimes that peg their currencies to the dollar has subsided. These include but are not limited to Hong Kong, Saudi Arabia and the United Arab Emirates (UAE). As a result, these countries' interest rate differentials versus the U.S. have plunged (Chart I-16). In short, domestic interest rates in these markets have risen much less than U.S. short rates. This has kept domestic liquidity conditions easier than they otherwise would have been. However, maneuvering room for these central banks is narrowing. In Hong Kong, the exchange rate is approaching the lower bound of its narrow band (Chart I-17). As it touches 7.85, the Hong Kong Monetary Authority (HKMA) will have no choice but to tighten liquidity and push up interest rates. Chart I-16Markets With U.S. Dollar Peg: ##br##Policymakers' Maneuvering Window Is Closing Markets With U.S. Dollar Peg: Policymakers' Maneuvering Window Is Closing Markets With U.S. Dollar Peg: Policymakers' Maneuvering Window Is Closing Chart I-17Hong Kong: Interest ##br##Rates Are Heading Higher Hong Kong: Interest Rates Are Heading Higher Hong Kong: Interest Rates Are Heading Higher In Saudi Arabia and the UAE, the monetary authorities have used the calm in their foreign exchange markets over the past year to not match the rise in U.S. short rates (Chart I-18A and Chart I-18B). However, with their interest rate differentials over U.S. now at zero, these central banks will have no choice but to follow U.S. rates to preserve their currency pegs.3 Chart I-18ASaudi Arabian Interest Rates Will Rise The UAE Interest Rates Will Rise The UAE Interest Rates Will Rise Chart I-18BThe UAE Interest Rates Will Rise Saudi Arabian Interest Rates Will Rise Saudi Arabian Interest Rates Will Rise If U.S. interest rates were to move above local rates in Saudi Arabia and the UAE, those countries' currencies will come under considerable depreciation pressure because capital will move from local currencies into U.S. dollars. Hence, if U.S. short rates move higher, which is very likely, local rates in these and other Gulf countries will have to rise if their exchange rate pegs are to be preserved. Neither the Hong Kong dollar nor Gulf currencies are at risk of devaluation. The monetary authorities there have enough foreign currency reserves to defend their respective pegs. Nevertheless, the outcome will be domestic liquidity tightening in the Gulf's and Hong Kong's banking system. In addition, potentially lower oil prices will weigh on Gulf bourses and China's slowdown will hurt growth and equity sentiment in Hong Kong. All in all, equity markets in Gulf countries and Hong Kong have probably seen their best in terms of absolute performance. Potential negative external shocks and higher interest rates due to Fed tightening have darkened the outlook for these bourses. Bottom Line: Local liquidity in Gulf markets and Hong Kong is set to tighten. Share prices in these markets have probably topped out. However, given these equity markets have massively underperformed the EM equity benchmark, they are unlikely to underperform when the overall EM index falls. Hence, we do not recommend underweighting these bourses within an EM equity portfolio. For asset allocators, a neutral or overweight allocation to these bourses is warranted. Arthur Budaghyan, Senior Vice President Emerging Markets Strategy arthurb@bcaresearch.com 1 Please see Emerging Markets Strategy Special Report "China's "De-Capacity" Reforms: Where Steel & Coal Prices Are Headed," dated November 22, 2017; the link is available on page 16. 2 Please see Emerging Markets Strategy Special Report "EM Bank Stocks Hold The Key," dated February 14, 2018; the link is available on page 16. 3 Please see BCA's Frontier Markets Strategy Special Report "United Arab Emirates: Domestic Tailwinds, External Headwinds," dated March 12, 2018. The link is available on fms.bcaresearch.com. Equity Recommendations Fixed-Income, Credit And Currency Recommendations

Highlights Portfolio Strategy Synchronized global capex growth and higher interest rates are two key themes that will continue to dominate this year. Three high-conviction calls are levered to the former theme and two to the latter. A special situation completes our sextet. Reinstate the S&P construction machinery & heavy truck index to the high-conviction overweight list. We also reiterate our high-conviction underweight call in the newcomer S&P telecom services sector. Recent Changes S&P Construction Machinery & Heavy Truck - Add back to high-conviction overweight list. Table 1 Semblance Of Calm Semblance Of Calm Feature Chart 1Market Bounced Smartly Market Bounced Smartly Market Bounced Smartly Equities regained their footing last week, as volatility took a breather. There are high odds that the technical, mostly-sentiment driven, pullback that we have been flagging since January 22nd is nearly over, as the market smartly bounced off the 200-day moving average (top panel, Chart 1).1 A consolidation/absorption phase is looming and, according to our "buy the dip" cycle-on-cycle analysis, a retest of the recent lows is likely before the market gets out of the woods (please refer to Chart 1 from last week's publication). While inflation expectations, crude oil prices and financial conditions are all tightly linked with and weighing on the S&P 500 (second and third panels, Chart 1), a number of tactical high-frequency financial market indicators suggest that the cyclical SPX bull market remains intact. First, SPX e-mini futures positioning is an excellent leading indicator of market momentum, and the current message is positive (net speculative positions are advanced by 40 weeks, Chart 2). Second, bond market internal dynamics suggest that this mini "risk off" episode is an isolated one and not a precursor to a real tremor. The high yield bond ETF outperformed the long dated Treasury bond ETF (bottom panel, Chart 3). It would be unprecedented for an equity market downdraft to morph into a fully blown bear market without junk bonds sinking compared with the ultimate risk free asset. Even when adjusted for its lower duration, the high yield bond ETF remained resilient versus the 3-7 year Treasury bond ETF (top panel, Chart 3). Chart 2Futures Positioning... Futures Positioning... Futures Positioning... Chart 3...Junk Bonds... ...Junk Bonds... ...Junk Bonds... Third, the calmness in the TED spread corroborates the message from the bond market. Were a systemic risk to materialize, the TED spread should have widened and not come in as it did in the past two weeks (Chart 4). Put differently, quiet interbank markets are a healthy sign. Chart 4...And TED Spread All Flashing Green Semblance Of Calm Semblance Of Calm Finally, relative valuations have corrected not only on an absolute basis (please refer to the bottom panel of Chart 2A from last week's Report), but also controlled for equity market volatility. In fact, Chart 5 shows that both the VIX-adjusted Shiller P/E and the 12-month forward P/E have returned to the neutral zone. Meanwhile, two key macro indicators we track are also flashing green. Chart 6 shows momentum in money velocity or how fast "one unit of currency is used to purchase domestically-produced goods and services".2 Historically, velocity of M2 money stock has been positively correlated with stock market momentum. The recent spike in this indicator suggests that the longevity of the business cycle remains intact, and investors with a cyclical (9-12 month) investment horizon should start "buying the dip", as we suggested on February 8th.3 Another yield curve-type macro indicator confirms this buoyant business cycle message: real GDP growth is easily outpacing real interest rates, as per the 10-year TIPS market (Chart 7). In other words, real rates are not yet restrictive enough to choke off GDP growth, despite the recent 35bps increase. Were this spread to plunge below the zero line, it would predict recession. Thus, the recent widening underscores that recession is not imminent. Chart 5Valuations Return To Earth Valuations Return To Earth Valuations Return To Earth Chart 6Money Velocity... Money Velocity... Money Velocity... Chart 7...And Yield Curve Emit Bullish Signal ...And Yield Curve Emit Bullish Signal ...And Yield Curve Emit Bullish Signal Under such a backdrop, the upshot is that earnings will remain upbeat in 2018 and continue to underpin equity prices. This week we revisit our 2018 high-conviction call list and reinstate one sector to the overweight column. Chart 8Both Themes Remains Intact Both Themes Remains Intact Both Themes Remains Intact The Themes Two key BCA themes formed the cornerstone of our 2018 high conviction call list: Synchronized global capex upcycle Higher interest rates Last autumn, we started to articulate the synchronized global capital spending macro theme4 that, despite still flying under the radar, will likely dominate this year. Both advanced and emerging economies are simultaneously expanding gross fixed capital formation (middle panel, Chart 8). As a result, we reiterate our cyclical over defensive portfolio bent,5 and continue to tie three high-conviction overweight calls to this theme. Similarly, late last year we started to highlight BCA's U.S. Bond Strategy view of a higher 10-year yield on the back of rising inflation expectations for 2018 (bottom panel, Chart 8). Back in late-November we posited that if BCA's constructive crude oil view pans out then inflation and rates may get an added boost. Two high-conviction calls remain levered to this theme. Finally, a special situation rounds up our call this year. But before we update the call list and make a small tweak, a quick housekeeping note is in order. Taking The Tally Early this year, we added trailing stops to our high-conviction call list as a risk management tool. The goal was to help protect profits as a number of our calls were showing outsized gains for such a short time span. Our tactically souring view of the overall market also compelled us to introduce this risk management metric. As a result of the recent careening in the SPX, half of our calls got stopped out with lofty double digit gains since inception a mere two and a half months ago. Namely, our speculative underweights in the S&P semi equipment and S&P homebuilders registered gains of 20% and 10%, respectively. The high-conviction underweight in the S&P utilities sector got called at an 18% gain, and our high-conviction overweight call in the S&P construction machinery & heavy truck (CMHT) index got stopped out at the 10% mark. (Please refer to page 15 for the closed trades table). Last week we added the S&P telecom services sector as a high-conviction underweight replacing the S&P utilities sector, and now that the worst is likely behind us, we are reinstating the S&P CMHT index to the high-conviction overweight list. Anastasios Avgeriou, Vice President U.S. Equity Strategy anastasios@bcaresearch.com Construction Machinery & Heavy Truck (Overweight, Capex Theme) The capex upcycle is underpinning machinery stocks. Not only are expectations for overall capital outlays as good as they get (Chart 9), but there are also tentative signs that even the previously moribund mining and oil & gas complexes will be capex upcycle participants. While we are not calling for a return to the previous cycle's peak, even a modest renormalization of capital spending plans in these two key machinery client segments would rekindle industry sales growth. Recent news of oil majors accelerating their capex plans is a step in the right direction. This machinery end-demand improvement is not only a U.S. phenomenon, but also a global one. The middle panel of Chart 9 shows Caterpillar's global machinery sales to dealers hitting a decade high. Tack on the drubbing in the U.S. dollar and related commodity price inflation and the ingredients are in place for a global machinery export boom. While most of the countries we track enjoy a sizable rebound in machinery orders, Japan's machine tools orders have surged to an all-time high confirming that machinery global end demand is brisk (bottom panel, Chart 9). Finally, our machinery EPS model is firing on all cylinders, underscoring that the earnings-led recovery has more running room (fourth panel, Chart 9). Reinstate the S&P CMHT index to the high-conviction overweight list. The ticker symbols for the stocks in this index are: BLBG: S5CSTF - CAT, CMI, PCAR. Energy (Overweight, Capex Theme) The S&P energy sector is a key beneficiary of our synchronized global capex theme. The Dallas Fed manufacturing outlook survey is firing on all cylinders and, given the importance of oil to the state of Texas, it serves as an excellent gauge for oil activity. Importantly, the capital expenditures part of the survey hit its highest level in a decade, and capex intentions in the coming six months are also probing multi-year highs. The overall message is that the budding recovery in energy capital budgets will likely gain steam (second panel, Chart 10). Following the late-2015/early-2016 drubbing in oil prices, energy projects ground to a halt and only now are green shoots appearing (middle panel, Chart 10). Recent news that Exxon Mobil would bump domestic capital spending up to $50bn over the next five years is encouraging. New projects/investments comprise 70% of this figure. OECD oil stocks are receding steadily and so are U.S. crude oil inventories. OPEC 2.0 remains in place and will likely balance the oil market by continuing to constrain supply. Our Commodity & Energy Strategy service is still penciling in higher oil prices for 2018. On the demand side, emerging markets/Chinese demand is the key determinant of overall oil demand, and the news on this front is encouraging and consistent with BCA's synchronized global growth theme: following the recent lull, non-OECD demand is growing anew by roughly 1.5mn bbl/day. The upshot is that S&P energy relative revenues will climb out of the recent trough (bottom panel, Chart 10). The ticker symbols for the stocks in this index are: BLBG: S5ENRS - XLE: US. Chart 9Construction Machinery & Heavy Truck ##br##(Overweight, Capex Theme) Construction Machinery & Heavy Truck (Overweight, Capex Theme) Construction Machinery & Heavy Truck (Overweight, Capex Theme) Chart 10Energy (Overweight, Capex Theme) Energy (Overweight, Capex Theme) Energy (Overweight, Capex Theme) Software (Overweight, Capex Theme) The S&P software index is another clear capex upcycle beneficiary. If software commands a larger slice of the overall capital spending pie as we expect, then industry profits should enjoy a healthy rebound (second panel, Chart 11). Small business sector plans to expand keep on hitting fresh recovery highs, underscoring that software related outlays will likely follow them higher. Rebounding bank loan growth also corroborates the upbeat spending message and signals that businesses are beginning to loosen their purse strings (Chart 11). Reviving animal spirits suggest that demand for software upgrades will stay elevated. CEO confidence is pushing decade highs (middle panel, Chart 11). Such ebullience is positive for a pickup in software outlays. It has also rekindled software M&A activity, and pushed take out premia higher. Meanwhile, the structural pull from the proliferation of cloud computing and software-as-a-service has served as a catalyst to raise the profile of this more defensive and mature tech sub-sector. Tax reform is another bonus for this group that benefits from cash repatriation, which will likely result in increased shareholder friendly activities. The ticker symbols for the stocks in this index are: BLBG: S5SOFT-MSFT, ORCL, ADBE, CRM, ATVI, INTU, EA, ADSK, RHT, SYMC, SNPS, ANSS, CDNS, CTXS, CA. Banks (Overweight, Higher Interest Rates Theme) The S&P banks index remains a core overweight portfolio holding and there are high odds of additional relative gains in the coming quarters beyond the current 10% relative return mark since the November 27th, 2017 inception. All three key drivers of bank profits, namely price of credit, loan growth and credit quality, are simultaneously moving in the right direction. On the price front, BCA expects the 10-year yield will continue to rise more quickly than is discounted in the forward curve. Our U.S. bond strategists think that inflation expectations have more room to run, likely pushing the 10-year Treasury yield close to 3.25% (top panel, Chart 12). C&I and consumer loans, two large credit categories, are both forecast to reaccelerate in the coming months. The ISM remains squarely above the 50 boom/bust line and consumer confidence is still buoyant. Our credit growth model captures these positive forces and is sending an unambiguously positive message for loan reacceleration in the coming months (third panel, Chart 12). Finally, credit quality remains pristine despite some pockets of weakness in auto loans (especially subprime) and credit card debt. At this stage of the cycle, with a closed unemployment gap, NPLs will remain muted. The ticker symbols for the stocks in this index are: BLBG: S5BANKX - WFC, JPM, BAC, C, USB, PNC, BBT, STI, MTB, FITB, CFG, RF, KEY, HBAN, CMA, ZION, PBCT.  Chart 11Software (Overweight, Capex Theme) Software (Overweight, Capex Theme) Software (Overweight, Capex Theme) Chart 12Banks (Overweight, Higher Interest Rates Theme) Banks (Overweight, Higher Interest Rates Theme) Banks (Overweight, Higher Interest Rates Theme) Telecom Services (Underweight, Higher Interest Rates Theme) We downgraded the S&P telecom services index to underweight and added it to the high-conviction underweight list last week, filling the void left by the S&P utilities sector.6 Three main reasons are behind our dislike for this fixed income proxy sector: BCA's 2018 rising interest rate theme, both our Cyclical Macro Indicator (CMI) and our sales model send a distress signal, and a profit margin squeeze is looming. The top panel of Chart 13 shows that high dividend yielding telecom services stocks and the 10-year yield are nearly perfectly inversely correlated. In fact, telecom services stocks are prime beneficiaries of disinflation/deflation and vice versa. BCA's bond market view remains that the 10-year yield will continue to rise likely piercing through 3% and weigh heavily on this fixed income proxied sector. Our CMI has melted and relative consumer outlays on telecom services have also taken a nosedive (second & third panels, Chart 13), warning that revenue growth will be hard to come by for telecom carriers. In fact, while nearly all of the GICS1 sectors have come out of the top line growth lull of late-2015/early-2016, telecom services sales growth has relapsed. Worrisomely, our S&P telecom services revenue growth model remains deep in contractionary territory, waving a red flag (bottom panel, Chart 13). Finally, still steeply deflating selling prices are a major headwind for the sector's top and bottom line growth prospects and coupled with a still expanding wage bill, suggest that a profit margin squeeze is looming. The ticker symbols for the stocks in this index are: VZ, T, CTL. Pharmaceuticals (Underweight, Special Situation) Weak pricing power fundamentals, a soft spending backdrop, a depreciating U.S. dollar and deteriorating industry operating metrics will sustain downward pressure on pharma stocks. Industry selling prices remain soft (Chart 14). In the context of a bloated industry workforce, the profit margin outlook darkens significantly. If the Trump administration also manages to clamp down on the secular growth of pharma selling price inflation, as we expect, then industry margins will remain under chronic downward pressure. Our dual synchronized global economic and capex growth themes bode ill for this safe haven index. Nondiscretionary health care outlays jump in times of duress and underwhelm during expansions. Currently, the elevated ISM manufacturing index is signaling that pharma profits will underwhelm in the coming months as the most cyclical parts of the economy flex their muscles (the ISM survey is shown inverted, second panel, Chart 14). A depreciating currency is also synonymous with pharma profit sickness (bottom panel, Chart 14). While pharma exports should at least provide some top line growth relief during depreciating U.S. dollar phases, they are still contracting (middle panel, Chart 14), warning that global pharma demand is ill. Finally, even on the operating metric front, the outlook is dark. Pharma industrial production is nil and our productivity proxy remains muted, warning that the valuation derating phase is far from over. The ticker symbols for the stocks in this index are: BLBG: S5PHAR - JNJ, PFE, MRK, BMY, AGN, LLY, ZTS, MYL, PRGO. Chart 13Telecom Services ##br##(Underweight, Higher Interest Rates Theme) Telecom Services (Underweight, Higher Interest Rates Theme) Telecom Services (Underweight, Higher Interest Rates Theme) Chart 14Pharmaceuticals ##br##(Underweight, Special Situation) Pharmaceuticals (Underweight, Special Situation) Pharmaceuticals (Underweight, Special Situation) 1 Please see BCA U.S. Equity Strategy Weekly Report, "Too Good To Be True?" dated January 22, 2018, available at uses.bcaresearch.com. 2 https://fred.stlouisfed.org/series/M2V 3 Please see BCA U.S. Equity Strategy Insight, "Buy The Dip," dated February 8, 2018, available at uses.bcaresearch.com. 4 Please see BCA U.S. Equity Strategy Weekly Report, "Invincible," dated November 6, 2017, available at uses.bcaresearch.com. 5 Please see BCA U.S. Equity Strategy Special Report, "Top 5 Reasons To Favor Cyclicals Over Defensives," dated October 16, 2017, available at uses.bcaresearch.com. 6 Please see BCA U.S. Equity Strategy Weekly Report, "Manic Depressive?" dated February 12, 2018, available at uses.bcaresearch.com. Current Recommendations Current Trades Size And Style Views Favor value over growth. Stay neutral small over large caps (downgrade alert).

Highlights Despite having the largest negative return of major markets during the global equity market correction, China's investable stock selloff appears to be normal after controlling for its risk characteristics. Taken together, the association between the global correction and volatility/valuation should be viewed as a sharp reduction in complacency in the market. Several factors make us cautious about China's outsized tech sector exposure in a world of reduced complacency. We recommend that investors retain cyclical exposure to investable Chinese stocks while neutralizing exposure to the tech sector. Feature Chart 1An Average Size, But Very Rapid, ##br##Global Selloff An Average Size, But Very Rapid, Global Selloff An Average Size, But Very Rapid, Global Selloff Global equities have sold off quite sharply since the end of January, having declined a total of 9% in US$ terms from their January 26 high to last Friday's close (Chart 1). BCA addressed the rout in a Special Report last week,1 and noted that strong economic growth and positive earnings surprises are likely to keep the global equity bull market intact, a view largely supported by this week's stock market behavior. Still, the report also highlighted that investors need to adjust to the fact that realized volatility is likely to sustainably rise, even if forward-looking volatility measures (such as the VIX in the U.S.) are currently too elevated. More generally, we equate the return of volatility with a reduction in complacency, and in this week's report we explore the implications of lower complacency for investors with an overweight allocation towards Chinese equities. Our judgement is that the complacency risk for China's ex-tech equity market is low, but that the same cannot be said for China's technology stocks. We conclude by recommending two trades that investors can employ to retain cyclical exposure to investable Chinese stocks, but with a neutralized exposure to the tech sector. Normal Underperformance For China Chart 2At First China Appears To Be Among ##br##The Worst Performers... After The Selloff: A View From China After The Selloff: A View From China At first blush, China's investable stock market fared quite poorly during the global stock market correction. Chart 2 lists 21 major country stock markets by the magnitude of their decline in US$ terms and highlights that China's selloff ranks at the very top of the list. But a simple comparison of stock market performance is misleading, as it fails to adjust for the different degrees of riskiness that are normally observed across global equity markets. For example, it is well known that emerging market equities have tended to be high beta relative to global stocks over the past decade, and we noted in a recent Special Report that Chinese investable stocks have become high beta even relative to emerging markets. In order to properly compare the performance of these markets during the global stock market selloff, we rely on the concept of "abnormal return" that is often employed in event study analysis. This approach involves calculating a counterfactual "normal" return for each market based on its rolling 1-year alpha and beta versus global stocks prior to the selloff, and then comparing it to the actual return. This difference, the "abnormal return" of each market, is shown in Chart 3, which highlights that China's performance during the selloff was perfectly normal after controlling for its risk characteristics. In fact, Chart 3 shows that many equity markets outperformed on a risk-adjusted basis, highlighting that the magnitude of the selloff in global stocks could actually have been worse. As for the underlying cause of the selloff, we showed in last week's Special Report that a crowded "short volatility" trade was undoubtedly a driving force: Chart 4 highlights that net long speculative positions on the VIX had fallen to a new low over the past six months, a circumstance that has now completely reversed. But Chart 5 shows that valuation also appears to have been a factor contributing to the selloff, by presenting the abnormal returns shown in Chart 3 as a function of the difference between the market's 12-month forward P/E and that of the global benchmark. While the fit is somewhat loose, the chart confirms that markets with higher (lower) forward P/E ratios were more likely to have negative (positive) abnormal returns over the two-week period. Chart 3...But Not After Adjusting##br## For Riskiness After The Selloff: A View From China After The Selloff: A View From China Chart 4The Low-Vol Trade Contributed ##br##To The Speed Of The Selloff... The Low-Vol Trade Contributed To The Speed Of The Selloff... The Low-Vol Trade Contributed To The Speed Of The Selloff... Taken together, the association between the selloff and volatility/valuation should be viewed as a sharp reduction in complacency in the market. While this does not necessarily bode poorly for global equities over the coming 6-12 months, there are some potential implications to explore for China's investable stock market. Chart 5...But Valuation Was Also A Factor After The Selloff: A View From China After The Selloff: A View From China Complacency Risk And Chinese Stocks The sharp reversal in global markets raises the question of whether Chinese equities are complacent about some looming risk. The obvious candidate for complacency risk in China would be focused on its economy, and the potential for a more substantial economic slowdown than is currently expected by market participants. However, we are unconvinced that Chinese ex-tech stocks are somehow neglecting the risks facing China's economy over the coming year. First, we have noted in previous reports that Chinese investable ex-tech stocks are extremely cheap versus global ex-tech stocks, highlighting that investors have priced in a degree of structural risk. Second, recent economic data releases from China do not suggest that the pace of the ongoing economic slowdown is accelerating, suggesting that there is no basis to expect a severe downturn over the coming year. But we acknowledge that the same cannot be said for China's tech sector. While Chinese tech stocks are not stretched on a technical basis (either versus the investable benchmark or versus global tech stocks), several observations make us cautious about China's outsized tech exposure in a world of reduced complacency: First, the growth rates of IBES 12-month trailing and forward earnings growth for global technology stocks are currently at the 80th and 85th percentiles, respectively (Chart 6). This suggests that a substantial amount of fundamental improvement has already been priced in to global tech stocks, raising the risk of earnings disappointment over the coming year. Given that China's tech sector weight (42%) is considerably above that of the global benchmark (18%), a global tech selloff would cause China's investable stock market to underperform even if Chinese tech performance is in line with that of the global tech sector. Second, relative to global technology stocks, the growth rates of China's 12-month trailing and forward earnings growth are also quite elevated, at the 80th and 70th percentiles, respectively (Chart 6 panel 2). This suggests that the tech earnings exuberance observed globally is even worse in China. Third, Chart 7 highlights that China's tech sector has been responsible for pushing our relative composite valuation indicator for China into overvalued territory over the past year. Relative to global ex-tech, China's ex-tech stocks are still significantly cheap; relative to global tech, China's tech stocks are significantly overvalued. Last, we have noted in past reports that China's tech sector appears to be a domestic consumer play, and thus unlikely to significantly underperform over the coming year. However, we also noted in last week's report on China's housing market that the optimism of the consumer sector may be somewhat unfounded if it is based on expectations of future gains in employment and/or income.2 While we do not expect a broad-based retracement in China's consumer sector, even a moderate decline in consumer confidence could spark a non-trivial selloff in Chinese tech stocks given the stretched fundamental picture highlighted above. Chart 6Tech Earnings Growth##br## Is Significantly Stretched Tech Earnings Growth Is Significantly Stretched Tech Earnings Growth Is Significantly Stretched Chart 7Tech Stocks Have Pushed China ##br##Into Overvalued Territory Tech Stocks Have Pushed China Into Overvalued Territory Tech Stocks Have Pushed China Into Overvalued Territory Investment Recommendations Given our observations about the complacency risk facing Chinese tech sector stocks, we are making the following changes to our investment recommendations: We are closing our overweight MSCI China Free versus the emerging markets benchmark trade for a 31% relative return. This has been a core trade for BCA's China Investment Strategy service and has provided investors with significant outperformance since its initiation in May 2012. We are opening two new trades as a replacement for the closed China / EM position: 1) long MSCI China investable ex-technology / short MSCI All Country World ex-technology, and 2) long MSCI China investable value / short All Country World value. These two new trades are a slight variation of a single theme, which is to retain cyclical exposure to investable Chinese stocks while neutralizing exposure to the tech sector. While style indexes such as value and growth normally do not have such a stark sector orientation, Chart 8 highlights that the relative performance of China value vs global value looks very similar to our internally-calculated ex-technology indexes for both markets. This is because MSCI's China growth index is almost entirely made up of tech sector stocks, meaning that a relative value play effectively mimics an ex-tech position. As a final point, we noted above that it is difficult to see how Chinese ex-tech equities are complacent about the ongoing slowdown in China's economy. Chart 9 supports this view by presenting a model for China's investable ex-tech 12-month trailing earnings in US$ terms, based on the Li Keqiang index. The model fit has been tight over the past decade, and is currently forecasting roughly 10% earnings growth over the coming year. This would clearly represent a significant deceleration from current levels, but it is still a decent earnings result that signals Chinese ex-tech stocks are attractive on a risk/reward basis given the sizeable valuation discount that is levied on China relative to global stocks. Chart 8China Ex-Tech And Value:##br## Similar Performance Vs Global China Ex-Tech And Value: Similar Performance Vs Global China Ex-Tech And Value: Similar Performance Vs Global Chart 9Positive Ex-Tech Earnings Growth Likely, ##br##Even With A Slowing Economy Positive Ex-Tech Earnings Growth Likely, Even With A Slowing Economy Positive Ex-Tech Earnings Growth Likely, Even With A Slowing Economy We remain alert to the possibility of a further, more pronounced slowdown in China's economy, but barring that Chinese ex-tech stocks appear to be a solid buy over the coming 6-12 months. Jonathan LaBerge, CFA, Vice President Special Reports jonathanl@bcaresearch.com 1 Please see Global Investment Strategy Special Report, "The Return Of Vol", dated February 6, 2018, available at gis.bcaresearch.com. 2 Please see China Investment Strategy Weekly Report, "Is China's Housing Market Stabilizing?", dated February 8, 2018, available at cis.bcaresearch.com. Cyclical Investment Stance Equity Sector Recommendations

Dear Client, This Special Report is the full transcript and slides of a presentation I recently gave at the London School of Economics symposium: 'Will I Work For AI, Or Will AI Work For Me?' The presentation pulls together several years of research analyzing the impact of current technological advances on work, the economy and society. I hope you find the presentation insightful and provocative, especially the narrative surrounding Slide 12. Dhaval Joshi Slide 2 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Feature Good afternoon Thank you very much for the invitation to speak here at the London School of Economics. The specific question you asked me was: will we be able to work in the future? (Slide 1). To which my answer is yes, an emphatic yes. I'm very optimistic that we will be able to work in the future. And one reason I'm saying this is, imagine that we had this symposium 100 years ago. I suspect we might have had exactly the same fears that we have right now (Slide 2). Slide 1 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Slide 2 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Specifically, at the start of the 20th century, about 35% of all jobs were on farms and another 6% were domestic servants. At the time, you could probably also have said, "Well, these jobs aren't going to exist." More or less half of the jobs that existed at that time were going to disappear - and disappear they did. So we'd have thought there would be mass unemployment. Of course, there wasn't mass unemployment, because just as jobs were destroyed, we had an equivalent job creation (Slide 3). For example, at the start of the 20th century, less than 5% of people worked in professional and technical jobs. But by the end of the century, these jobs employed a quarter of the workforce. I guess what I'm saying is that we're very conscious of job destruction because we can see existing jobs being destroyed. But we're not very conscious of job creation, because in real time, it's difficult to visualize or imagine where these new jobs will be. In essence, what we saw in the 20th century was one major segment of employment basically collapsed from very significant to insignificant. While another segment surged from insignificant to very significant (Slide 4). Slide 3 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Slide 4 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? As you all know, there is an economic thesis that underlies this. It's called Say's Law, derived by French economist Jean-Baptiste Say in 1803. In simple terms, it says that new supply creates new demand. Think about it like this: why would you replace a human with a machine? You would only do that if it increases your productivity, right? Otherwise, it does not make sense to replace a human with any sort of machine, including AI. But because you have increased productivity, you then have extra income to spend on new goods and services. Now if those goods and services are being supplied by a machine, then you can redeploy humans to satiate new desires, desires that do not even exist at the time. In economic terms, the producer of X - as long as his products are demanded - is able to buy Y (Slide 5). The question is, what is Y? Y is the new product or service. Let me give you some examples (Slide 6). In the 19th century, we had the advent of railways. And then someone thought. "Hang on a minute. We have this way of moving things around much faster, and we've got all these people who live hundreds of miles from the coast who might want to eat fresh fish." So this was the birth of the frozen food industry. But you could not have the frozen food industry without railways. What I'm saying is that entrepreneurs will seize the new technology to satiate a desire. Or even create a new desire because maybe the people in the middle of the country never thought they could eat fresh sea fish. Until someone came along and said, "you can eat fresh fish now." Slide 5 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Slide 6 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Another example is, as technology improved the health and longevity of your teeth someone thought. "Well, hang on a minute. Maybe there's a desire to make teeth look beautiful." And we created this whole new industry called the dental cosmetics industry. We know this because prior to the 1960s, there was no job called dental technician or dental hygienist. A third example is, let's say that we have more advanced healthcare and pharmaceuticals, so humans are living longer and healthier lives. Well, then you can sort of ask. "Hang on a minute. Don't you want your dog to live the same long and healthy life that you're living?" And this is behind the explosion of the pet care industry that we're seeing at the moment. So while one segment of the economy will employ less, a new segment will come along to replace it. In the 20th century we saw farm work disappearing but professional work rising. Today, we are seeing manufacturing and driving jobs disappearing but healthcare work rising (Slide 7). Which does raise a pretty obvious question (Slide 8). Is there anything really different this time around? Slide 7 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Slide 8 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Well, the answer is yes, there is a subtle but crucial difference this time around. To see the difference, we have to look more closely at where jobs are being destroyed, and where they are being created. As you can see, the mega-sectors losing a lot of jobs are manufacturing, the auto industry, and finance (Slide 9). While on the other side of the ledger, we have job creation in health, social work and education. But now, let's look in a little more detail. Where, specifically, are the jobs being created? For this we have to look at the United States data which is much more granular than in Europe. Here are the top five subsectors of job creation this decade (Slide 10). At the top of the list is food services and drinking places, which is just a euphemistic way of describing bartenders, waitresses, and pizza delivery boys. We also have a lot of new administrative jobs and care workers. What is the common link in this job creation? Answer: these are predominantly low-income jobs. Slide 9 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Slide 10 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? So it is true that we have an enormous amount of job creation in the last decade or so, and the policymakers keep boasting about it, they say, "Well look, the unemployment rate in the U.S. is at a record low, the unemployment rate in the UK is at a record low, the unemployment rate in Germany is at a record low. We're creating loads and loads of jobs." The trouble is that these are predominantly low-income jobs. Meanwhile the job destruction is in middle-income jobs in manufacturing and finance. This means what we're seeing in the labour market is called a 'negative composition effect' - a hollowing out of middle incomes. So while we're getting loads and loads of job creation, it is not translating into wage inflation at an aggregate level. I think one of the reasons is a concept called Moravec's paradox. Professor Hans Moravec is an expert in robotics and Artificial Intelligence, and he noticed this paradox (Slide 11). He said, "Look. For AI, the things that we think are difficult are actually easy." By easy, he means they're doable. Let me give you some specific examples. Say someone could speak five languages fluently and translate between them at ease. We would think that person is a genius, a real rare specimen, and the economy would value this person extremely highly, probably pay that person hundreds of thousands of pounds at a minimum. But actually, AI can translate across five languages quite easily, and even something like Google Translate, which we all use, does a reasonably good first stab at translating from one language to another. Slide 11 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Or consider something like insurance underwriting. Pricing an insurance premium from lots of data on a risk. AI can do that extremely well, much better than a human can. Or medical diagnosis. Figuring out what's wrong with a patient from very detailed medical data. Again, AI beats humans hands down on that. What I'm saying is, these skills that we thought were difficult transpired not to be that difficult for AI, because they just amount to narrow-frame pattern recognition and repetition of algorithms. Whereas, the second part of Moravec's paradox is that AI finds the easy things very hard. Things that we think are really innate, we don't even give them a second thought like walking up some stairs, cleaning a table, moving objects around, and cleaning around them. Actually, AI finds these things incredibly difficult, almost impossible. We have a false sense of what is difficult and what is easy. The main reason is that the things that we find innate took millions and millions of years of human brain evolution for us to find them innate. And as AI is in essence trying to replicate the human brain, only now are we recognizing that things that we find innate are actually incredibly complex. If it took millions and millions of years to evolve the sensorimotor skills that allow us to walk up some stairs, recognize subtle emotional signals, and respond appropriately, then obviously AI is going to find it very, very difficult to replicate those innate human skills. Conversely, the brain's ability to do calculus, construct a grammatical structure for a language, or play chess only evolved relatively recently. So AI can do them very easily. Which brings me to quite a profound thought. If there's one thing that I want you to remember from this presentation it is this (Slide 12). Might we have completely misvalued the human brain? Might we have grossly overvalued things that are actually quite easy? And might we have undervalued things which are actually very, very difficult? And what AI is now doing is correcting this huge error. In which case, the next decade could be extremely disruptive as AI corrects this economic misvaluation of our skills. Slide 12 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? This might also explain the mystery as to why there is no wage inflation when the Phillips curve says there should be. The Phillips curve makes a simple relationship between the unemployment rate and wage pressures. And the folks at the Federal Reserve and Bank of England, they're sort of getting really perplexed. They're saying, "Look, unemployment is so low. Where is this wage inflation? It's going to kick in any time now." In fact, there's a bit of a paradox going on. For the people who are continuously employed in the same job, there has been pretty good wage inflation - at sort of three, four percent (Slide 13). But when you take the negative composition effect into account, then suddenly there's this big gap because what's happening is that the well-paid jobs are disappearing to be replaced by lower-paid jobs. So even if you give the bartender making thirty thousand a big pay rise to thirty-five thousand. Even if you hire two of them, but you're losing a finance job paying over a hundred thousand, then at the aggregate level, you won't see much wage inflation. And this problem, I think, continues for the next few years, minimum. It means that you will not get the wage pressures that a lot of economists think you're going to get from the low unemployment rate. Because you have to look at the quality of the jobs as well as the quantity. I think there is another disturbing impact from a societal perspective. Look again at where the jobs are being lost and where they're being created, and look at the percentage of male employees (Slide 14). Job destruction is occurring in sectors that are male-dominated, whereas job creation is occurring in sectors that are female-dominated. Slide 13 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Slide 14 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? AI is good at narrow-frame pattern recognition and repetition of algorithms and functions - jobs like driving, which are typically male-dominated. Whereas jobs that require emotional input, emotional understanding, and empathy in the 'caring sectors' are typically female-dominated. So if you're a male, you're in trouble. You're in a lot of trouble. Obviously, there'll be re-training, so all the guys who were driving trucks will have to retrain as nurses, or as essential carers. But if you're a female, things are looking okay. You can see that in the data (Slide 15). Female labour force participation is in a very clear uptrend. Male participation is flat to down. This varies by country by country, and in the U.S., it's catastrophic for males, especially young males. Young male participation in the U.S. is really falling off a cliff at the moment. I think the other thing to say from a societal perspective is that the so-called 'Superstar Economy' is booming - both superstar individuals and superstar firms. One way of seeing this is in this index called 'the cost of living extremely well' calculated every year by Forbes (Slide 16). Whereas the ordinary CPI includes the cost of bread and milk, the CPI index for the extremely rich includes the cost of Petrossian caviar and Dom Perignon champagne. And a Learjet 70, a Sikorsky S-76D helicopter. I think there's a pedigree racehorse in there too. Anyway, we're seeing the CPI for the extremely rich rising at a dramatically faster pace than the CPI for society as a whole. So it would seem that superstar individuals and superstar firms are really thriving. Slide 15 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Slide 16 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Let's explain this dynamic in terms of a superstar we all recognise - Roger Federer. Roger Federer was unknown initially, but as he went up the tennis rankings and became a superstar, his income grew exponentially. The other aspect is, how long can he stay a superstar? Because all superstars are eventually displaced by a new superstar. So there's two aspects to the dynamics of superstar incomes (Slide 17). First, how exponential is your income growth? And second, how long do you stay a superstar? What I'm saying is that the rise of AI, by hollowing out the middle jobs, actually allows a few superstars to have this exponential rise in their income. Let's think about it in terms of the legal profession. The top lawyer will be in huge demand. Technology really boosts him. Not just AI, but things like the internet, the fact that social media will reinforce his position, whereby everyone will know who he is. Even if he can't service you directly, he will have a team with his brand on it. And he can stay there for longer before he is displaced. So this is the mechanism by which technology can increase income inequality by hollowing out the middle. In the legal profession, the assistant lawyer who just checks a document for simple legal principle, well the machine can do that. But the guy who knows all the oddities, who knows all the loopholes that can win you the case, the machine won't be able to do that. Essentially what I'm saying is that the technological revolution - it's not just AI, it's technology in aggregate, including the internet and social media, and so on - it increases the rate of income growth for a few superstar individuals and firms. And it increases their longevity (Slide 18). And these are the two drivers for the Pareto distribution of incomes. You can actually go through the mathematics of this to show that it does increase the polarization of incomes. Slide 17 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Slide 18 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Let's sum up (Slide 19). First of all, yes, we will be able to work in the future. I don't think there's any doubt about that because there will be new jobs created, the nature of which we can only guess because we're going to get new industries to satiate our new desires. However, in the coming years, middle-income work will suffer high disruption because of Moravec's Paradox. Some things that we thought were difficult are actually quite easy for AI. But things like gardening, plumbing, nursing, and childcare are very difficult for machines to replicate. Which means that low-income work will suffer much less disruption and, of course, low-income work will get paid better over time - though the gap is so large at the moment that it's preventing overall wage inflation from kicking in. And that, I think, will persist for the next few years at a minimum. Slide 19 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Men are going to suffer much more disruption than women because of the nature of the job destruction versus the job creation. And the final point is that superstars will thrive. All of this has a lot of implications for how we respond as a society, and maybe we will need some support mechanisms in this period of disruption. I think the most intense disruption will be in the next decade. After that we will reach a new equilibrium once we have actually corrected this misvaluation of the brain, this misvaluation of what it is that makes us truly human. Thank you very much. Dhaval Joshi, Senior Vice President Chief European Investment Strategist dhaval@bcaresearch.com

Risk management is important in tumultuous times. Our long held strategy of how to navigate choppy waters during a tactical correction has been to book gains in pair trades and thus de-risk the portfolio, and institute trailing stops to the high-flyers in our high-conviction call list. Two additional high-conviction underweight calls got stopped out recently with hefty gains for our portfolio: 10% for our underweight call on homebuilders and 20% for our underweight call in semi equipment stocks. We are obeying both stops and taking profits by removing them from the high-conviction underweight list. Nevertheless, the spiking lumber prices, surging interest rates and tax reform trifecta is still, at the margin, weighing on homebuilders. Therefore, we continue to recommend an underweight stance in this niche consumer discretionary industry. Similarly, while our underweight conviction level is not as high for semiconductor equipment stocks as on November 27, 2017, we continue to recommend a below benchmark allocation to this highly cyclical industry. Rising interest rates, a key BCA theme for 2018 is working against last year's stellar performers with growth stocks (semi equipment equities included) suffering a valuation derating. Bottom Line: Crystalize profits of 20% and 10% in chip equipment and homebuilding stocks, respectively, and remove from the high-conviction underweight list. We continue to recommend a below benchmark allocation in both indexes. The ticker symbols for the stocks in the S&P semi equipment and S&P homebuilders indexes are: AMAT, LRCX, KLAC, and LEN, DHI, PHM, respectively. Housekeeping In Turbulent Times Housekeeping In Turbulent Times

Dear Client, In addition to this Special Report written by my colleagues Mark McClellan and Brian Piccioni, we are sending you an abbreviated weekly report. Best regards, Peter Berezin, Chief Global Strategist Global Investment Strategy Highlights Media reports warn of a "Robot Apocalypse" that is already laying waste to jobs and depressing wages on a broad scale. Technological advance in the past has not prevented improving living standards or led to ever rising joblessness over the decades, but pessimists argue that recent advances are different. The issue is important for financial markets. If structural factors such as automation are holding back inflation by more than in previous decades, then the Fed will have to proceed very slowly in raising rates. We see no compelling evidence that the displacement effect of emerging technologies is any stronger than in the past. Robot usage has had a modest positive impact on overall productivity. Despite this contribution, overall productivity growth has been dismal over the past decade. If automation is increasing 'exponentially' and displacing workers on a broad scale as some claim, one would expect to see accelerating productivity growth, robust capital spending and more violent shifts in occupational shares. Exactly the opposite has occurred. Periods of strong growth in automation have historically been associated with robust, not lackluster, wage gains, contrary to the consensus view. The Fed was successful in meeting the 2% inflation target on average from 2000 to 2007, when the impact of the IT revolution on productivity (and costs) was stronger than that of robot automation today. This and other evidence suggest that it is difficult to make the case that robots will make it tougher for central banks to reach their inflation goals than did previous technological breakthroughs. For investors, this means that we cannot rely on automation to keep inflation depressed irrespective of how tight labor markets become. Feature Recent breakthroughs in technology are awe-inspiring and unsettling. These advances are viewed with great trepidation by many because of the potential to replace humans in the production process. Hype over robots is particularly shrill. Media reports warn of a "Robot Apocalypse" that is already laying waste to jobs and depressing wages on a broad scale. In the first in our series of Special Reports focusing on the structural factors that might be preventing central banks from reaching their inflation targets, we demonstrated that the impact of Amazon is overstated in the press. We estimated that E-commerce is depressing inflation in the U.S. by a mere 0.1 to 0.2 percentage points. This Special Report tackles the impact of automation. We are optimistic that robot technology and artificial intelligence will significantly boost future productivity, and thus reduce costs. But, is there any evidence at the macro level that robot usage has been more deflationary than technological breakthroughs in the past and is, thus, a major driver of the low inflation rates we observe today across the major countries? The question matters, especially for the outlook for central bank policy and the bond market. If structural factors are indeed holding back inflation by more than in previous decades, then the Fed will have to proceed very slowly in raising rates. However, if low inflation simply reflects long lags between wages and the tightening labor market, then inflation may suddenly lurch to life as it has at the end of past cycles. The bond market is not priced for that scenario. Are Robots Different? A Special Report from BCA's Technology Sector Strategy service suggested that the "robot revolution" could be as transformative as previous General Purpose Technologies (GPT), including the steam engine, electricity and the microchip.1 GPTs are technologies that radically alter the economy's production process and make a major contribution to living standards over time. The term "robot" can have different meanings. The most basic definition is "a device that automatically performs complicated and often repetitive tasks," and this encompasses a broad range of machines: From the Jacquard Loom, which was invented over 200 years ago, on to Numerically Controlled (NC) mills and lathes, pick and place machines used in the manufacture of electronics, Autonomous Vehicles (AVs), and even homicidal robots from the future such as the Terminator. Our Technology Sector report made the case that there is nothing particularly sinister about robots. They are just another chapter in a long history of automation. Nor is the displacement of workers unprecedented. The industrial revolution was about replacing human craft labor with capital (machines), which did high-volume work with better quality and productivity. This freed humans for work which had not yet been automated, along with designing, producing and maintaining the machinery. Agriculture offers a good example. This sector involved over 50% of the U.S. labor force until the late 1800s. Steam and then internal combustion-powered tractors, which can be viewed as "robotic horses," contributed to a massive rise in output-per-man hour. The number of hours worked to produce a bushel of wheat fell by almost 98% from the mid-1800s to 1955. This put a lot of farm hands out of work, but these laborers were absorbed over time in other growing areas of the economy. It is the same story for all other historical technological breakthroughs. Change is stressful for those directly affected, but rising productivity ultimately lifts average living standards. Robots will be no different. As we discuss below, however, the increasing use of robots and AI may have a deeper and longer-lasting impact on inequality. Strong Tailwinds Chart 1Robots Are Getting Cheaper Robots Are Getting Cheaper Robots Are Getting Cheaper Factory robots have improved immensely due to cheaper and more capable control and vision systems. As these systems evolve, the abilities of robots to move around their environment while avoiding obstacles will improve, as will their ability to perform increasingly complex tasks. Most importantly, robots are already able to do more than just routine tasks, thus enabling them to replace or aid humans in higher-skilled processes. Robot prices are also falling fast, especially after quality-adjusting the data (Chart 1). Units are becoming easier to install, program and operate. These trends will help to reduce the barriers-to-entry for the large, untapped, market of small and medium sized enterprises. Robots also offer the ability to do low-volume "customized" production and still keep unit costs low. In the future, self-learning robots will be able to optimize their own performance by analyzing the production of other robots around the world. Robot usage is growing quickly according to data collected by the International Federation of Robotics (IFR) that covers 23 countries. Industrial robot sales worldwide increased to almost 300,000 units in 2016, up 16% from the year before (Chart 2). The stock of industrial robots globally has grown at an annual average pace of 10% since 2010, reaching slightly more than 1.8 million units in 2016.2 Robot usage is far from evenly distributed across industries. The automotive industry is the major consumer of industrial robots, holding 45% of the total stock in 2016 (Chart 3). The computer & electronics industry is a distant second at 17%. Metals, chemicals and electrical/electronic appliances comprise the bulk of the remaining stock. Chart 2Global Robot Usage Global Robot Usage Global Robot Usage Chart 3Global Robot Usage By Industry (2016) The Impact Of Robots On Inflation The Impact Of Robots On Inflation As far as countries go, Japan has traditionally been the largest market for robots in the world. However, sales have been in a long-term downtrend and the stock of robots has recently been surpassed by China, which has ramped up robot purchases in recent years (Chart 4). Robot density, which is the stock of robots per 10 thousand employed in manufacturing, makes it easier to compare robot usage across countries (Chart 5, panel 2). By this measure, China is not a heavy user of robots compared to other countries. South Korea stands at the top, well above the second-place finishers (Germany and Japan). Large automobile sectors in these three countries explain their high relative robot densities. Chart 4Stock Of Robots By Country (I) Stock Of Robots By Country (I) Stock Of Robots By Country (I) Chart 5Stock Of Robots By Country (II) (2016) The Impact Of Robots On Inflation The Impact Of Robots On Inflation While the growth rate of robot usage is impressive, it is from a very low base (outside of the automotive industry). The average number of robots per 10,000 employees is only 74 for the 23 countries in the IFR database. Robot use is tiny compared to total man hours worked. In the U.S., spending on robots is only about 5% of total business spending on equipment and software (Chart 6). To put this into perspective, U.S. spending on information, communication and technology (ICT) equipment represented 35-40% of total capital equipment spending during the tech boom in the 1990s and early 2000s.3 Chart 6U.S. Investment In Robots U.S. Investment In Robots U.S. Investment In Robots The bottom line is that there is a lot of hype in the press, but robots are not yet widely used across countries or industries. It will be many years before business spending on robots approaches the scale of the 1990s/2000s IT boom. A Deflationary Impact? As noted above, we view robotics as another chapter in a long history of technological advancements. Pessimists suggest that the latest advances are different because they are inherently more threatening to the overall job market and wage share of total income. If the pessimists are right, what are the theoretical channels though which this would have a greater disinflationary effect relative to previous GPT technologies? Faster Productivity Gains: Enhanced productivity drives down unit labor costs, which may be passed along to other industries (as cheaper inputs) and to the end consumer. More Human Displacement: The jobs created in other areas may be insufficient to replace the jobs displaced by robots, leading to lower aggregate income and spending. The loss of income for labor will simply go to the owners of capital, but the point is that the labor share of income might decline. Deflationary pressures could build as aggregate demand falls short of supply. Even in industries that are slow to automate, just the threat of being replaced by robots may curtail wage demands. Inequality: Some have argued that rising inequality is partly because the spoils of new technologies over the past 20 years have largely gone to the owners of capital. This shift may have undermined aggregate demand because upper income households tend to have a high saving rate, thereby depressing overall aggregate demand and inflationary pressures. The human displacement effect, described above, would exacerbate the inequality effect by transferring income from labor to the owners of capital. 1. Productivity It is difficult to see the benefits of robots on productivity at the economy-wide level. Productivity growth has been abysmal across the major developed countries since the Great Recession, but the productivity slowdown was evident long before Lehman collapsed (Chart 7). The productivity slowdown continued even as automation using robots accelerated after 2010. Chart 7Productivity Collapsed Despite Automation Productivity Collapsed Despite Automation Productivity Collapsed Despite Automation Some analysts argue that lackluster productivity is simply a statistical mirage because of the difficulties in measuring output in today's economy. We will not get into the details of the mismeasurement debate here. We encourage interested clients to read a Special Report by the BCA Global Investment Strategy service entitled "Weak Productivity Growth: Don't Blame The Statisticians." 4 Our colleague Peter Berezin makes the case that the unmeasured utility accruing from free internet services is large, but so was the unmeasured utility from antibiotics, radio, indoor plumbing and air conditioning. He argues that the real reason that productivity growth has slowed is that educational attainment has decelerated and businesses have plucked many of the low-hanging fruit made possible by the IT revolution. Cyclical factors stemming from the Great Recession and financial crisis are also to blame, as capital spending has been slow to recover in most of the advanced economies. Some other factors that help to explain the decline in aggregate productivity are provided in Appendix 1. Nonetheless, the poor aggregate productivity performance does not mean that there are no benefits to using robots. The benefits are evident at the industrial level, where measurement issues are presumably less vexing for statisticians (i.e., it is easier to measure the output of the auto industry, for example, than for the economy as a whole). Chart 8 plots the level of robot density in 2016 with average annual productivity growth since 2004 for 10 U.S. manufacturing industries (robot density is presented in deciles). A loose positive relationship is apparent. Chart 8U.S.: Productivity Vs. Robot Density The Impact Of Robots On Inflation The Impact Of Robots On Inflation Academic studies estimate that robots have contributed importantly to economy-wide productivity growth. The Centre for Economic and Business Research (CEBR) estimated that labor productivity growth rises by 0.07 to 0.08 percentage points for every 1% rise in the rate of robot density.5 This implies that robots accounted for roughly 10% of the productivity growth experienced since the early 1990s in the major economies. Another study of 14 industries across 17 countries by the Centre for Economic Performance (CEP) found that robots boosted annual productivity growth by 0.36 percentage points over the 1993-2007 period.6 This is impressive because, if this estimate holds true for the U.S., robots' contribution to the 2½% average annual U.S. total productivity growth over the period was 14%. To put the importance of robotics into historical context, its contribution to productivity so far is roughly on par with that of the steam engine (Chart 9). It falls well short of the 0.6 percentage point annual productivity contribution from the IT revolution. The implication is that, while the overall productivity performance has been dismal since 2007, it would have been even worse in the absence of robots. What does this mean for inflation? According to the "cost push" model of the inflation process, an increase in productivity of 0.36% that is not accompanied by associated wage gains would reduce unit labor costs (ULC) by the same amount. This should trim inflation if the cost savings are passed on to the end consumer, although by less than 0.36% because robots can only depress variable costs, not fixed costs. There indeed appears to be a slight negative relationship between robot density and unit labor costs at the industrial level in the U.S., although the relationship is loose at best (Chart 10). Chart 9GPT Contribution To Productivity The Impact Of Robots On Inflation The Impact Of Robots On Inflation Chart 10U.S.: Unit Labor Costs Vs. Robot Density The Impact Of Robots On Inflation The Impact Of Robots On Inflation In theory, divergences in productivity across industries should only generate shifts in relative prices, and "cost push" inflation dynamics should only operate in the short term. Most economists believe that inflation is a purely monetary phenomenon in the long run, which means that central banks should be able to offset positive productivity shocks by lowering interest rates enough that aggregate demand keeps up with supply. Indeed, the Fed was successful in meeting the 2% inflation target on average from 2000 to 2007, when the impact of the IT revolution on productivity (and costs) was stronger than that of robot automation today. Also, note that inflation is currently low across the major advanced economies, irrespective of the level of robot intensity (Chart 11). From this perspective, it is hard to see that robots should take much of the credit for today's low inflation backdrop. Chart 11Inflation Vs. Robot Density The Impact Of Robots On Inflation The Impact Of Robots On Inflation 2. Human Displacement A key question is whether robots and humans are perfect substitutes. If new technologies introduced in the past were perfect substitutes, then it would have led to massive underemployment and all of the income in the economy would eventually have migrated to the owners of capital. The fact that average real household incomes have risen over time, and that there has been no secular upward trend in unemployment rates over the centuries, means that new technologies were at least partly complementary with labor (i.e., the jobs lost as a direct result of productivity gains were more than replaced in other areas of the economy over time). Rather than replacing workers, in many cases tech made humans more productive in their jobs. Rising productivity lifted income and thereby led to the creation of new jobs in other areas. The capital that workers bring to the production process - the skills, know-how and special talents - became more valuable as interaction with technology increased. Like today, there were concerns in the 1950s and 1960s that computerization would displace many types of jobs and lead to widespread idleness and falling household income. With hindsight, there was little to worry about. Some argue that this time is different. Futurists frequently assert that the pace of innovation is not just accelerating, it is accelerating 'exponentially'. Robots can now, or will soon be able to, replace humans in tasks that require cognitive skills. This means that they will be far less complementary to humans than in the past. The displacement effect could thus be much larger, especially given the impressive advances in artificial intelligence. However, Box 1 discusses why the threat to workers posed by AI is also heavily overblown in the media. The CEP multi-country study cited above did not find a large displacement effect; robot usage did not affect the overall number of hours worked in the 23 countries studied (although it found distributional effects - see below). In other words, rather than suppressing overall labor input, robot usage has led to more output, higher productivity, more jobs and stronger wage and income growth. A report by the Economic Policy Institute (EPI)7 takes a broader look at automation, using productivity growth and capital spending as proxies. Automation is what occurs as the implementation of new technologies is incorporated along with new capital equipment or software to replace human labor in the workplace. If automation is increasing 'exponentially' and displacing workers on a broad scale, one would expect to see accelerating productivity growth, robust capital spending, and more violent shifts in occupational shares. Exactly the opposite has occurred. Indeed, the report demonstrates that occupational employment shifts were far slower in the 2000-2015 period than in any decade in the 1900s (Chart 12). Box 1 The Threat From AI Is Overblown Media coverage of AI/Deep Learning has established a consensus view that we believe is well off the mark. A recent Special Report from BCA's Technology Sector Strategy service dispels the myths surrounding AI.8 We believe the consensus, in conjunction with warnings from a variety of sources, is leading to predictions, policy discussions, and even career choices based on a flawed premise. It is worth noting that the most vocal proponents of AI as a threat to jobs and even humanity are not AI experts. At the root of this consensus is the false view that emerging AI technology is anything like true intelligence. Modern AI is not remotely comparable in function to a biological brain. Scientists have a limited understanding of how brains work, and it is unlikely that a poorly understood system can be modeled on a computer. The misconception of intelligence is amplified by headlines claiming an AI "taught itself" a particular task. No AI has ever "taught itself" anything: All AI results have come about after careful programming by often PhD-level experts, who then supplied the system with vast amounts of high quality data to train it. Often these systems have been iterated a number of times and we only hear of successes, not the failures. The need for careful preparation of the AI system and the requirement for high quality data limits the applicability of AI to specific classes of problems where the application justifies the investment in development and where sufficient high-quality data exists. There may be numerous such applications but doubtless many more where AI would not be suitable. Similarly, an AI system is highly adapted to a single problem, or type of problem, and becomes less useful when its application set is expanded. In other words, unlike a human whose abilities improve as they learn more things, an AI's performance on a particular task declines as it does more things. There is a popular misconception that increased computing power will somehow lead to ever improving AI. It is the algorithm which determines the outcome, not the computer performance: Increased computing power leads to faster results, not different results. Advanced computers might lead to more advanced algorithms, but it is pointless to speculate where that may lead: A spreadsheet from 2001 may work faster today but it still gives the same answer. In any event, it is worth noting that a tool ceases to be a tool when it starts having an opinion: there is little reason to develop a machine capable of cognition even if that were possible. Chart 12U.S. Job Rotation Has Slowed The Impact Of Robots On Inflation The Impact Of Robots On Inflation The EPI report also notes that these indicators of automation increased rapidly in the late 1990s and early 2000s, a period that saw solid wage growth for American workers. These indicators weakened in the two periods of stagnant wage growth: from 1973 to 1995 and from 2002 to the present. Thus, there is no historical correlation between increases in automation and wage stagnation. Rather than automation, the report argues that it was China's entry into the global trading system that was largely responsible for the hollowing out of the U.S. manufacturing sector. We have also made this argument in previous research. The fact that the major advanced economies are all at, or close to, full employment supports the view that automation has not been an overwhelming headwind for job creation. Chart 13 demonstrates that there has been no relationship between the change in robot density and the loss of manufacturing jobs since 1993. Japan is an interesting case study because it is on the leading edge of the problems associated with an aging population. Interestingly, despite a worsening labor shortage, robot density among Japanese firms is falling. Moreover, the Japanese data show that the industries that have a high robot usage tend to be more, not less, generous with wages than the robot laggard industries. Please see Appendix 2 for more details. Chart 13Global Manufacturing Jobs Vs. Robot Density The Impact Of Robots On Inflation The Impact Of Robots On Inflation The bottom line is that it does not appear that labor displacement related to automation has been responsible in any meaningful way for the lackluster average real income growth in the advanced economies since 2007. 3. Inequality That said, there is evidence suggesting that robots are having important distributional effects. The CEP study found that robot use has reduced hours for low-skilled and (to a lesser extent) middle-skilled workers relative to the highly skilled. This finding makes sense conceptually. Technological change can exacerbate inequality by either increasing the relative demand for skilled over unskilled workers (so-called "skill-biased" technological change), or by inducing companies to substitute machinery and other forms of physical capital for workers (so-called "capital-biased" technological change). The former affects the distribution of labor income, while the latter affects the share of income in GDP that labor receives. A Special Report appearing in this publication in 2014 focused on the relationship between technology and inequality.9 The report highlighted that much of the recent technological change has been skill-biased, which heavily favors workers with the talent and education to perform cognitively-demanding tasks, even as it reduces demand for workers with only rudimentary skills. Moreover, technological innovations and globalization increasingly allow the most talented individuals to market their skills to a much larger audience, thus bidding up their wages. The evidence suggests that faster productivity growth leads to higher average real wages and improved living standards, at least over reasonably long horizons. Nonetheless, technological change can, and in the future almost certainly will, increase income inequality. The poor will gain, but not as much as the rich. The fact that higher-income households tend to maintain a higher savings rate than low-income households means that the shift in the distribution of income toward the higher-income households will continue to modestly weigh on aggregate demand. Can the distribution effect be large enough to have a meaningful depressing impact on inflation? We believe that it has played some role in the lackluster recovery since the Great Recession, with the result that an extended period of underemployment has delivered a persistent deflationary impulse in the major developed economies. However, as discussed above, stimulative monetary policy has managed to overcome the impact of inequality and other headwinds on aggregate demand, and has returned the major countries roughly to full employment. Indeed, this year will be the first since 2007 that the G20 economies as a group will be operating slightly above a full employment level. Inflation should respond to excess demand conditions, irrespective of any ongoing demand headwind stemming from inequality. Conclusions Technological change has led to rising living standards over the decades. It did not lead to widespread joblessness and did not prevent central banks from meeting their inflation targets over time. The pessimists argue that this time is different because robots/AI have a much larger displacement effect. Perhaps it will be 20 years before we will know the answer. But our main point is that we have found no evidence that recent advances in robotics and AI, while very impressive, will be any different in their macro impact. There is little evidence that the modern economy is less capable in replacing the jobs lost to automation, although the nature of new technologies may be affecting the distribution of income more than in the past. Real incomes for the middle- and lower-income classes have been stagnant for some time, but this is partly due to productivity growth that is too low, not too high. Moreover, it is not at all clear that positive productivity shocks are disinflationary beyond the near term. The link between robot usage and unit labor costs over the past couple of decades is loose at best at the industry level, and is non-existent when looking across the major countries. The Fed was able to roughly meet its 2% inflation target in the 1990s and the first half of the 2000s, despite IT's impressive contribution to productivity growth during that period. For investors, this means that we cannot rely on automation to keep inflation depressed irrespective of how tight labor markets become. The global output gap will shift into positive territory this year for the first time since the Great Recession. Any resulting rise in inflation will come as a shock since the bond market has discounted continued low inflation for as far as the eye can see. We expect bond yields and implied volatility to rise this year, which may undermine risk assets in the second half. Mark McClellan Senior Vice President The Bank Credit Analyst Brian Piccioni Vice President Technology Sector Strategy Appendix 1 Why Is Productivity So Low? A recent study by the OECD10 reveals that, while frontier firms are charging ahead, there is a widening gap between these firms and the laggards. The study analyzed firm-level data on labor productivity and total factor productivity for 24 countries. "Frontier" firms are defined to be those with productivity in the top 5%. These firms are 3-4 times as productive as the remaining 95%. The authors argue that the underlying cause of this yawning gap is that the diffusion rate of new technologies from the frontier firms to the laggards has slowed within industries. This could be due to rising barriers to entry, which has reduced contestability in markets. Curtailing the creative-destruction process means that there is less pressure to innovate. Barriers to entry may have increased because "...the importance of tacit knowledge as a source of competitive advantage for frontier firms may have risen if increasingly complex technologies were to increase the amount and sophistication of complementary investments required for technological adoption." 11 The bottom line is that aggregate productivity is low because the robust productivity gains for the tech-savvy frontier companies are offset by the long tail of firms that have been slow to adopt the latest technology. Indeed, business spending has been especially weak in this expansion. Chart 14 highlights that the slowdown in U.S. productivity growth has mirrored that of the capital stock. Chart 14U.S. Capex Shortfall Partly To Blame For Poor Productivity U.S. Capex Shortfall Partly To Blame For Poor Productivity U.S. Capex Shortfall Partly To Blame For Poor Productivity Appendix 2 Japan - The Leading Edge Japan is an interesting case study because it is on the leading edge of the problems associated with an aging population. The popular press is full of stories of how robots are taking over. If the stories are to be believed, robots are the answer to the country's shrinking workforce. Robots now serve as helpers for the elderly, priests for weddings and funerals, concierges for hotels and even sexual partners (don't ask). Prime Minister Abe's government has launched a 5-year push to deepen the use of intelligent machines in manufacturing, supply chains, construction and health care. Indeed, Japan was the leader in robotics use for decades. Nonetheless, despite all the hype, Japan's stock of industrial robots has actually been eroding since the late 1990s (Chart 4). Numerous surveys show that firms plan to use robots more in the future because of the difficulty in hiring humans. And there is huge potential: 90% of Japanese firms are small- and medium-sized (SME) and most are not currently using robots. Yet, there has been no wave of robot purchases as of 2016. One problem is the cost; most sophisticated robots are simply too expensive for SMEs to consider. This suggests that one cannot blame robots for Japan's lack of wage growth. The labor shortage has become so acute that there are examples of companies that have turned down sales due to insufficient manpower. Possible reasons why these companies do not offer higher wages to entice workers are beyond the scope of this report. But the fact that the stock of robots has been in decline since the late 1990s does not support the view that Japanese firms are using automation on a broad scale to avoid handing out pay hikes. Indeed, Chart 15 highlights that wage deflation has been the greatest in industries that use almost no robots. Highly automated industries, such as Transportation Equipment and Electronics, have been among the most generous. This supports the view that the productivity afforded by increased robot usage encourages firms to pay their workers more. Looking ahead, it seems implausible that robots can replace all the retiring Japanese workers in the years to come. The workforce will shrink at an annual average pace of 0.33% between 2020 and 2030, according to the Japan Institute for Labour Policy and Training. Productivity growth would have to rise by the same amount to fully offset the dwindling number of workers. But that would require a surge in robot density of 4.1, assuming that each rise in robot density of one adds 0.08% to the level of productivity (Chart 16). The level of robot sales would have to jump by a whopping 2½ times in the first year and continue to rise at the same pace each year thereafter to make this happen. Of course, the productivity afforded by new robots may accelerate in the coming years, but the point is that robot usage would likely have to rise astronomically to offset the impact of the shrinking population. Chart 15Japan: Earnings Vs. Robot Density The Impact Of Robots On Inflation The Impact Of Robots On Inflation Chart 16Japan: Where Is The Flood Of Robots? Japan: Where Is The Flood Of Robots? Japan: Where Is The Flood Of Robots? The implication is that, as long as the Japanese economy continues to grow above roughly 1%, the labor market will continue to tighten and wage rates will eventually begin to rise. 1 Please see Technology Sector Strategy Special Report "The Coming Robotics Revolution," dated May 16, 2017, available at tech.bcaresearch.com 2 Note that this includes only robots used in manufacturing industry, and thus excludes robots used in the service sector and households. However, robot usage in services is quite limited and those used in households do not add to GDP. 3 Note that ICT investment and capital stock data includes robots. 4 Please see BCA Global Investment Strategy Special Report "Weak Productivity Growth: Don't Blame The Statisticians," dated March 25, 2016, available at gis.bcaresearch.com 5 Centre for Economic and Business Research (January 2017) "The Impact of Automation." A Report for Redwood. In this report, robot density is defined to be the number of robots per million hours worked. 6 Graetz, G., and Michaels, G. (2015): "Robots At Work." CEP Discussion Paper No 1335. 7 Mishel, L., and Bivens, J. (2017): "The Zombie Robot Argument Lurches On," Economic Policy Institute. 8 Please see BCA Technology Sector Strategy Special Report "Bad Information - Why Misreporting Deep Learning Advances Is A Problem," dated January 9, 2018, available at tech.bcaresearch.com 9 Please see The Bank Credit Analyst, "Rage Against the Machines: Is Technology Exacerbating Inequality?" dated June 2014, available at bca.bcaresearch.com. 10 OECD Productivity Working Papers, No. 05 (2016) "The Best Versus the Rest: The Global Productivity Slowdown, Divergence Across Firms and the Role of Public Policy." 11 Please refer to page 8.

Highlights U.S. equities 'melted up' in January as tax cuts made the robust growth/low inflation sweet spot even sweeter. Ominously, recent market action is beginning to resemble a classic late cycle blow-off phase. The fundamentals supporting the market will persist through most of the year, before an economic downturn in the U.S. takes hold in 2019. The repatriation of overseas corporate cash will also flatter EPS growth this year via buyback and M&A activity. The S&P 500 could return 14% or more this year. Unfortunately, the consensus now shares our upbeat view for 2018. Valuation is stretched and many indicators suggest that investors have become downright giddy. This month we compare valuation across the major asset classes. U.S. equities are the most overvalued, followed by gold, raw industrials and EM assets. Oil is still close to fair value. Long-term investors should already be scaling back on risk assets. Investors with a 6-12 month horizon should stay overweight equities versus bonds for now, but a risk management approach means that they should not try to squeeze out the last few percentage points of return. In terms of the sequencing of the exit from risk, the most consistent lead/lag relationship relative to previous tops in the equity market is provided by U.S. corporate bonds. For this reason, we are likely to take profits on corporates before equities. EM assets are already at underweight. We still see a window for the U.S. dollar to appreciate, although by only about 5%. A lot of good news is discounted in the euro, peripheral core inflation is slowing and ECB policymakers are getting nervous. Monetary policy remains the main risk to a pro-cyclical investment stance, although not because of the coming change in the makeup of the FOMC. The economy and inflation should justify four Fed rate hikes in 2018 no matter the makeup. The bond bear phase will continue. Feature Chart I-1Investors Are Giddy Investors Are Giddy Investors Are Giddy U.S. equities 'melted up' in January as tax cuts made the robust growth/low inflation sweet spot even sweeter. Ominously, though, recent market action is beginning to resemble the classic late cycle blow-off phase. Such blow-offs can be highly profitable, but also make it more difficult to properly time the market top. Our base case is that the fundamentals supporting the market will persist through most of the year, before an economic downturn in the U.S. takes hold in 2019. Unfortunately, the consensus now shares our upbeat view for 2018 and many indicators suggest that investors have become downright giddy (Chart I-1). These indicators include investor sentiment, our speculation index, and the bull-to-bear ratio. Net S&P earnings revisions and the U.S. economic surprise index are also extremely elevated, while equity and bond implied volatility are near all-time lows. From a contrarian perspective, these observations suggest that a lot of good news is discounted and that the market is vulnerable to even slight disappointments. It is also a bad sign that our Revealed Preference Indicator moved off of its bullish equity signal in January (see Section III for more details). Meanwhile, central banks are beginning to take away the punchbowl as global economic slack dissipates. This is all late-cycle stuff. Equity valuation does not help investors time the peak in markets, but it does tell us something about downside risk and medium-term expected returns. The Shiller P/E ratio has surged above 30 (Chart I-2). Chart I-3 highlights that, historically, average total returns were negligible over the subsequent 10-year period when the Shiller P/E was in the 30-40 range. Granted, the Shiller P/E will likely fall mechanically later this year as the collapse of earnings in 2008 begins to drop out of the 10-year EPS calculation. Nonetheless, even the BCA Composite Valuation indicator, which includes some metrics that account for extremely low bond yields, surpassed +1 standard deviations in January (our threshold for overvaluation; Chart I-2, bottom panel). An overvaluation signal means that investors should be biased to take profits early. Chart I-2BCA Valuation Indicator Surpasses One Sigma BCA Valuation Indicator Surpasses One Sigma BCA Valuation Indicator Surpasses One Sigma Chart I-3Expected Returns Given Starting Point Shiller P/E February 2018 February 2018 As we highlighted in our 2018 Outlook Report, long-term investors should already be scaling back on risk assets. We recommend that investors with a 6-12 month horizon should stay overweight equities versus bonds for now, but we need to be vigilant in terms of scouring for signals to take profits. A risk management approach means that investors should not try to get the last few percentage points of return before the peak. U.S. Earnings And Repatriation Before we turn to the timing and sequence of our exit from risk assets, we will first update our thoughts on the earnings cycle. Fourth quarter U.S. earnings season is still in its early innings, but the banking sector has set an upbeat tone. S&P 500 profits are slated to register a 12% growth rate for both Q4/2017 and calendar 2017. Current year EPS growth estimates have been aggressively ratcheted higher (from 12% growth to 16%) in a mere three weeks on the back of Congress' cut to the corporate tax rate.1 U.S. margins fell slightly in the fourth quarter, but remain at a high level on the back of decent corporate pricing power. A pick-up in productivity growth into year-end helped as well. Our short-term profit model remains extremely upbeat (Chart I-4). The positive profit outlook for the first half of the year is broadly based across sectors as well, according to the recently updated EPS forecast models from BCA's U.S. Equity Sector Strategy service.2 The repatriation of overseas corporate cash will also flatter EPS growth this year via buyback and M&A activity. Studies of the 2004 repatriation legislation show that most of the funds "brought home" were paid out to shareholders, mostly in the form of buybacks. A NBER report estimated that for every dollar repatriated, 92 cents was subsequently paid out to shareholders in one form or another. The surge in buybacks occurred in 2005, according to the U.S. Flow of Funds accounts and a proxy using EPS growth less total dollar earnings growth for the S&P 500 (Chart I-5). The contribution to EPS growth from buybacks rose to more than 3 percentage points at the peak in 2005. Chart I-4Profit Growth Still Accelerating Profit Growth Still Accelerating Profit Growth Still Accelerating Chart I-5U.S. Buybacks To Lift EPS U.S. Buybacks To Lift EPS U.S. Buybacks To Lift EPS We expect that most of the repatriated funds will again flow through to shareholders, rather than be used to pay down debt or spent on capital goods. Cash has not been a constraint to capital spending in recent years outside of perhaps the small business sector, which has much less to gain from the tax holiday. A revival in animal spirits and capital spending is underway, but this has more to do with the overall tax package and global growth than the ability of U.S. companies to repatriate overseas earnings. Estimates of how much the repatriation could boost EPS vary widely. Most of it will occur in the Tech and Health Care sectors. Buybacks appear to have lifted EPS growth by roughly one percentage point over the past year. We would not be surprised to see this accelerate by 1-2 percentage points, although the timing could be delayed by a year if the 2004 tax holiday provides the correct timeline. This is certainly positive for the equity market, but much of the impact could already be discounted in prices. Organic earnings growth, and the economic and policy outlook will be the main drivers of equity market returns over the next year. We expect some profit margin contraction later this year, but our 5% EPS growth forecast is beginning to look too conservative. This is especially the case because it does not include the corporate tax cuts. The amount by which the tax cuts will boost earnings on an after-tax basis is difficult to estimate, but we are using 5% as a conservative estimate. Adding 2% for buybacks and 2% for dividends, the S&P 500 could provide an attractive 14% total return this year (assuming no multiple expansion). Timing The Exit Chart I-6Timing The Exit (I) Timing The Exit (I) Timing The Exit (I) That said, we noted in last month's Report and in BCA's 2018 Outlook that this will be a transition year. We expect a recession in the U.S. sometime in 2019 as the Fed lifts rates into restrictive territory. Equities and other risk assets will sniff out the recession about six months in advance, which means that investors should be preparing to take profits sometime during the next 12 months. Last month we discussed some of the indicators we will watch to help us time the exit. The 2/10 Treasury yield curve has been a reliable recession indicator in the past. However, the lead time on the peak in stocks was quite extended at times (Chart I-6). A shift in the 10-year TIPS breakeven rate above 2.4% would be consistent with the Fed's 2% target for the PCE measure of inflation. This would be a signal that the FOMC will have to step-up the pace of rate hikes and aggressively slow economic growth. We expect the Fed to tighten four times in 2018. We are likely to take some money off the table if core inflation is rising, even if it is still below 2%, at the time that the TIPS breakeven reaches 2.4%. We will also be watching seven indicators that we have found to be useful in heralding market tops, which are summarized in our Scorecard Indicator (Chart I-7). At the moment, four out of the seven indicators are positive (Chart I-8): State of the Business Cycle: As early signals that the economy is softening, watch for the ISM new orders minus inventories indicator to slip below zero, or the 3-month growth rate of unemployment claims to rise above zero. Monetary and Financial Conditions: Using interest rates to judge the stance of monetary policy has been complicated by central banks' use of their balance sheet as a policy tool. Thus, it is better to use two of our proprietary indicators: the BCA Monetary Indicator (MI) and the Financial Conditions Indictor. The S&P 500 index has historically rallied strongly when the MI is above its long-term average. Similarly, equities tend to perform well when the FCI is above its 250-day moving average. The MI is sending a negative signal because interest rates have increased and credit growth has slowed. However, the broader FCI remains well in 'bullish' territory. Price Momentum: We simply use the S&P 500 relative to its 200-day moving average to measure momentum. Currently, the index is well above that level, providing a bullish signal for the Scorecard. Sentiment: Our research shows that stock returns have tended to be highest following periods when sentiment is bearish but improving. In contrast, returns have tended to be lowest following periods when sentiment is bullish but deteriorating. The Scorecard includes the BCA Speculation Indicator to capture sentiment, but virtually all measures of sentiment are very high. The next major move has to be down by definition. Thus, sentiment is assigned a negative value in the Scorecard. Value: As discussed above, value is poor based on the Shiller P/E and the BCA Composite Valuation indicator. Valuation may not help with timing, but we include it in our Scorecard because an overvalued signal means investors should err on the side of getting out early. Chart I-7Equity ScoreCard: Watch For A Dip Below 3 Equity ScoreCard: Watch For A Dip Below 3 Equity ScoreCard: Watch For A Dip Below 3 Chart I-8Timing The Exit (II) Timing The Exit (II) Timing The Exit (II) We demonstrated in previous research that a Scorecard reading of three or above was historically associated with positive equity total returns in subsequent months. A drop below three this year would signal the time to de-risk. Table I-1Exit Checklist February 2018 February 2018 To our Checklist we add the U.S. Leading Economic index, which has a good track record of calling recessions. However, we will use the LEI excluding the equity market, since we are using it as an indicator for the stock market. It is bullish at the moment. Our Global LEI is also flashing green. Table I-1 provides a summary checklist for trimming equity exposure. At the moment, 2 out of 9 indicators are bearish. Cross Asset Valuation Comparison Clients have asked our view on the appropriate order in which to scale out of risk assets. One way to approach the question is to compare valuation across asset classes. Presumably, the ones that are most overvalued are at greatest risk, and thus profits should be taken the earliest. It is difficult to compare valuation across asset classes. Should one use fitted values from models or simple deviations from moving averages? Over what time period? Since there is no widely accepted approach, we include multiple measures. More than one time period was used in some cases to capture regime changes. Table I-2 provides out 'best guestimate' for nine asset classes. The approaches range from sophisticated methods developed over many years (i.e. our equity valuation indicators), to regression analysis on the fundamentals (oil), to simple deviations from a time trend (real raw industrial commodity prices and gold). Table I-2Valuation Levels For Major Asset Classes February 2018 February 2018 We averaged the valuation readings in cases where there are multiple estimates for a single asset class. The results are shown in Chart I-9. Chart I-9Valuation Levels For Major Asset Classes February 2018 February 2018 U.S. equities stand out as the most expensive by far, at 1.8 standard deviations above fair value. Gold, raw industrials and EM equities are next at one standard deviation overvalued. EM sovereign bond spreads come next at 0.7, followed closely by U.S. Treasurys (real yield levels) and investment-grade corporate (IG) bonds (expressed as a spread). High-yield (HY) is only about 0.3 sigma expensive, based on default-adjusted spreads over the Treasury curve. That said, both IG and HY are quite expensive in absolute terms based on the fact that government bonds are expensive. Oil is sitting very close to fair value, despite the rapid price run up over the past couple of months. This makes oil exposure doubly attractive at the moment because the fundamentals point to higher prices at a time when the underlying asset is not expensive. Sequencing Around Past S&P 500 Peaks Historical analysis around equity market peaks provides an alternative approach to the sequencing question. Table I-3 presents the number of days that various asset classes peaked before or after the past major five tops in the S&P 500. A negative number indicates that the asset class peaked before U.S. equities, and a positive number means that it peaked after. Table I-3Asset Class Leads & Lags Vs. Peak In S&P 500 February 2018 February 2018 Unfortunately, there is no consistent pattern observed for EM equities, raw industrials, U.S. cyclical stocks, Tech stocks, or small-cap versus large-cap relative returns. Sometimes they peaked before the S&P 500, and sometime after. The EM sovereign bond excess return index peaked about 130 days in advance of the 1998 and 2007 U.S. equity market tops, although we only have three episodes to analyse due to data limitations. Oil is a mixed bag. A peak in the price of gold led the equity market in four out of five episodes, but the lead time is long and variable. The most consistent lead/lag relationship is given by the U.S. corporate bond market. Both investment- and speculative-grade excess returns relative to government bonds peaked in advance of U.S. stocks in four of the five episodes. High-yield excess returns provided the most lead time, peaking on average 154 days in advance. Excess returns to high-yield were a better signal than total returns. This leading relationship is one reason why we plan to trim exposure to corporate bonds within our bond portfolio in advance of scaling back on equities. But the 'return of vol' that we expect to occur later this year will take a toll on carry trades more generally. We are already underweight EM equities and bonds. This EM recommendation has not gone in our favor, but it would make little sense to upgrade them now given our positive views on volatility and the dollar. An unwinding of carry trades will also hit the high-yielding currencies outside of the EM space, such as the Kiwi and Aussie dollar. Base metal prices will be hit particularly hard if the 2019 U.S. recession spills over to the EM economies as we expect. We may downgrade base metals from neutral to underweight around the time that we downgrade equities, but much depends on the evolution of the Chinese economy in the coming months. Oil is a different story. OPEC 2.0 is likely to cut back on supply in the face of an economic downturn, helping to keep prices elevated. We therefore may not trim energy exposure this year. As for equity sectors, our recommended portfolio is still overweight cyclicals for now. Our synchronized global capex boom, rising bond yield, and firm oil price themes keep us overweight the Industrials, Energy and Financial sectors. Utilities and Homebuilders are underweight. Tech is part of the cyclical sector, but poor valuation keeps us underweight. That said, our sector specialists are already beginning a gradual shift away from cyclicals toward defensives for risk management purposes. This transition will continue in the coming months as we de-risk. We are also shifting small caps to neutral on earnings disappointments and elevated debt levels. The Dollar Pain Trade Market shifts since our last publication have largely gone in our favor; stocks have surged, corporate bonds spreads have tightened, oil prices have spiked, bonds have sold off and cyclical stocks have outperformed defensives. One area that has gone against us is the U.S. dollar. Relative interest rate expectations have moved in favor of the dollar as we expected at both the short- and long-ends of the curve. Nonetheless, the dollar has not tracked its historical relationship versus both the yen and euro. The Greenback did not even get a short-term boost from the passage of the tax plan and holiday on overseas earnings. Perhaps this is because the lion's share of "overseas" earnings are already held in U.S. dollars. Reportedly, a large fraction is even held in U.S. banks on U.S. territory. Currency conversion is thus not a major bullish factor for the U.S. dollar. The recent bout of dollar weakness began around the time of the release of the ECB Minutes in January which were interpreted as hawkish because they appeared to be preparing markets for changes in monetary policy. The European debt crisis and economic recession were the reasons for the ECB's asset purchases and negative interest rate policy. Neither of these conditions are in place now. The ECB is meeting as we go to press, and we expect some small adjustments in the Statement that remove references to the need for "crisis" level accommodations. Subsequent steps will be to prepare markets for a complete end to QE, perhaps in September, and then for rates hikes likely in 2019. The key point is that European monetary policy has moved beyond 'peak stimulus' and the normalization process will continue. Perhaps this is partly to blame for euro strength although, as mentioned above, interest rate differentials have moved in favor of the dollar. Does this mean that the dollar has peaked and has entered a cyclical bear phase that will persist over the next 6-12 months? The answer is 'no', although we are less bullish than in the past. We believe there is still a window for the dollar to appreciate against the euro and in broader trade-weighted terms by about 5%. First, a lot of euro-bullish news has been discounted (Chart I-10). Positive economic surprises heavily outstripped that in the U.S. last year, but that phase is now over. The euro appears expensive based on interest rate differentials, and euro sentiment is close to a bullish extreme. This all suggests that market positioning has become a negative factor for the currency. Chart I-10Euro: A Lot Of Bullish News Is Discounted EURO: A Lot Of Bullish News Is Discounted EURO: A Lot Of Bullish News Is Discounted Second, the chorus of complaints against the euro's strength is growing among European central bankers, including Ewald Nowotny, the rather hawkish Austrian central banker. Policymakers' concerns may partly reflect the fact that peripheral inflation excluding food and energy has already weakened to 0.6% from a high of 1.3% in April last year (Chart I-10, fourth panel). Third, U.S. consumer price and wage inflation have yet to pick up meaningfully. The dollar should receive a lift if core U.S. inflation clearly moves toward the Fed's 2% target, as we expect. The FOMC would suddenly appear to have fallen behind the curve and U.S. rate expectations would ratchet higher. Chart I-10, bottom panel, highlights that the euro will weaken if U.S. core inflation rises versus that in the Eurozone. The implication is that the Euro's appreciation has progressed too far and is due for a pullback. As for the yen, the currency surged in January when the Bank of Japan (BoJ) announced a reduction in long-dated JGB purchases. This simply acknowledged what has already occurred. It was always going to be impossible to target both the quantity of bond purchases and the level of 10-year yield simultaneously. Keeping yields near the target required less purchases than they thought. The market interpreted the BoJ's move as a possible prelude to lifting the 10-year yield target. It is perhaps not surprising that the market took the news this way. The economy is performing extremely well; our model that incorporates high-frequency economic data suggests that real GDP growth will move above 3% in the coming quarters. The Japanese economy is benefiting from the end of a fiscal drag and from a rebound in EM growth. Nonetheless, following January's BoJ policy meeting, Kuroda poured cold water on speculation that the BoJ may soon end or adjust the YCC. Recent speeches by BoJ officials reinforce the view that the MPC wants to see an overshoot of actual inflation that will lower real interest rates and thereby reinforce the strong economic activity that is driving higher inflation. Only then will officials be convinced that their job is done. Given that inflation excluding food and energy only stands at 0.3%, the BoJ is still a long way from the overshoot it desires. On the positive side, Japan's large current account surplus and yen undervaluation provide underlying support for the currency. Balancing the offsetting positive and negative forces, our foreign exchange strategists have shifted to neutral on the yen. The Euro remains underweight while the dollar is overweight. Similar to our dollar view, we still see a window for U.S. Treasurys to underperform the global hedged fixed-income benchmark as world bond yields shift higher this year. European government bonds will also sell off, but should outperform Treasurys. JGBs will provide the best refuge for bondholders during the global bond bear phase, since the BoJ will prevent a rise in yields inside of the 10-year maturity. Our global bond strategists upgraded U.K. gilts to overweight in January. Momentum in the U.K. economy is slowing, as a weaker consumer, slower housing activity, and softer capital spending are offsetting a pickup in exports. With the inflationary impulse from the 2016 plunge in the Pound now fading, and with Brexit uncertainty weighing on business confidence, the Bank of England will struggle to raise rates in 2018. FOMC Transition Monetary policy remains the main risk to a pro-cyclical investment stance, although not because of the coming change in the makeup of the FOMC. An abrupt shift in policy is unlikely. There was some support at the December 2017 FOMC meeting to study the use of nominal GDP or price level targeting as a policy framework, but this has been an ongoing debate that will likely continue for years to come. The Fed will remain committed to its current monetary policy framework once Powell takes over. Table I-4 provides a summary of who will be on the FOMC next year, including their policy bias. Chart I-11 compares the recent FOMC makeup with the coming Powell FOMC (voting members only). The hawk/dove ratio will not change much under Powell, unless Trump stacks the vacant spots with hawks. Table I-4Composition Of The FOMC February 2018 February 2018 Chart I-11Composition Of Voting FOMC Members 2017 Vs. 2018 February 2018 February 2018 In any event, history shows that the FOMC strives to avoid major shifts in policy around changeovers in the Fed Chair. In previous transitions, the previous path for rates was maintained by an average of 13 months. Moreover, Powell has shown that he is not one to rock the boat during his time on the FOMC. It will be the evolution of the economy and inflation, not the composition of the FOMC, that will have the biggest impact on markets at the end of the day. Recent speeches reveal that policymakers across the hawk/dove spectrum are moving modesty toward the hawkish side because growth has accelerated at a time when unemployment is already considered to be below full-employment by many policymakers. The melt-up in equity indexes in January did little to calm worries about financial excesses either. The Fed is struggling to understand the strength of the structural factors that could be holding down inflation. This month's Special Report, beginning on page 21, focusses on the impact of robot automation. While advances on this front are impressive, we conclude that it is difficult to find evidence that robots are more deflationary than previous technological breakthroughs. Thus, increased robot usage should not prevent inflation from rising as the labor market continues to tighten. The macro backdrop will likely justify the FOMC hiking at least as fast as the dots currently forecast. The risks are skewed to the upside. The median Fed dot calls for an unemployment rate of 3.9% by end-2018, only marginally lower than today's rate of 4.1%. This is inconsistent with real GDP growth well in excess of its supply-side potential. The unemployment rate is more likely to reach a 49-year low of 3.5% by the end of this year. As highlighted in last month's Report, a key risk to the bull market in risk assets is the end of the 'low vol/low rate' world. The selloff in the bond market in January may mark the start of this process. Conclusions We covered a lot of ground in this month's Overview of the markets, so we will keep the conclusions brief and focused on the risks. Our key point is that the fundamentals remain positive for risk assets, but that a lot of good news is discounted and it appears that we have entered a classic blow-off phase. This will be a transition year to a recession in the U.S. in 2019. Given that valuation for most risk assets is quite stretched, and given that the monetary taps are starting to close, investors must plan for the exit and keep an eye on our timing checklist. The main risk to our pro-cyclical portfolio is a rise in U.S. inflation and the Fed's response, which we believe will end the sweet spot for risk assets. Apart from this, our geopolitical strategists point to several other items that could upset the applecart this year:3 1. Trade China has cooperated with the U.S. in trying to tame North Korea. Nonetheless, President Trump is committed to an "America First" trade policy and he may need to show some muscle against China ahead of the midterm elections in November in order to rally his base. It is politically embarrassing to the Administration that China racked up its largest trade surplus ever with the U.S. in Trump's first year in office. A key question is whether the President goes after China via a series of administrative rulings - such as the recently announced tariffs on solar panels and white goods - or whether he applies an across-the-board tariff and/or fine. The latter would have larger negative macroeconomic implications. 2. Iran On January 12, President Trump threatened not to waive sanctions against Iran the next time they come due (May 12), unless some new demands are met. Pressure from the U.S. President comes at a delicate time for Iran. Domestic unrest has been ongoing since December 28. Although protests have largely fizzled out, they have reopened the rift between the clerical regime, led by Supreme Leader Ayatollah Ali Khamenei, and moderate President Hassan Rouhani. Iranian hardliners, who control part of the armed forces, could lash out in the Persian Gulf, either by threatening to close the Straits of Hormuz or by boarding foreign vessels in international waters. The domestic political calculus in both Iran and the U.S. make further Tehran-Washington tensions likely. For the time being, however, we expect only a minor geopolitical risk premium to seep into the energy markets, supporting our bullish House View on oil prices. 3. China Last month's Special Report highlighted that significant structural reforms are on the way in China, now that President Xi has amassed significant political support for his reform agenda. The reforms should be growth-positive in the long term, but could be a net negative for growth in the near term depending on how deftly the authorities handle the monetary and fiscal policy dials. The risk is that the authorities make a policy mistake by staying too tight, as occurred in 2015. We are monitoring a number of indicators that should warn if a policy mistake is unfolding. On this front, January brought some worrying economic data. The latest figures for both nominal imports and money growth slowed. Given that M2 and M3 are components of BCA's Li Keqiang Leading Indicator, and that nominal imports directly impact China's contribution to global growth, this raises the question of whether December's economic data suggest that China is slowing at a more aggressive pace than we expect. For now, our answer is no. First, China's trade numbers are highly volatile; nominal import growth remains elevated after smoothing the data. Second, China's export growth remains buoyant, consistent with a solid December PMI reading. The bottom line is that we are sticking with our view that China will experience a benign deceleration in terms of its impact on DM risk assets, but we will continue to monitor the situation closely. Mark McClellan Senior Vice President The Bank Credit Analyst January 25, 2018 Next Report: February 22, 2018 1 According to Thomson Reuters/IBES. 2 Please see U.S. Equity Sector Strategy Special Report "White Paper: Introducing Our U.S. Equity Sector Earnings Models," dated January 16, 2018, available at uses.bcaresearch.com 3 For more information, please see BCA Geopolitical Strategy Weekly Report "Upside Risks In U.S., Downside Risks In China," dated January 17, 2018, available at gps.bcaresearch.com. Also see "Watching Five Risks," dated January 24, 2018. II. The Impact Of Robots On Inflation Media reports warn of a "Robot Apocalypse" that is already laying waste to jobs and depressing wages on a broad scale. Technological advance in the past has not prevented improving living standards or led to ever rising joblessness over the decades, but pessimists argue that recent advances are different. The issue is important for financial markets. If structural factors such as automation are holding back inflation by more than in previous decades, then the Fed will have to proceed very slowly in raising rates. We see no compelling evidence that the displacement effect of emerging technologies is any stronger than in the past. Robot usage has had a modest positive impact on overall productivity. Despite this contribution, overall productivity growth has been dismal over the past decade. If automation is increasing 'exponentially' and displacing workers on a broad scale as some claim, one would expect to see accelerating productivity growth, robust capital spending and more violent shifts in occupational shares. Exactly the opposite has occurred. Periods of strong growth in automation have historically been associated with robust, not lackluster, wage gains, contrary to the consensus view. The Fed was successful in meeting the 2% inflation target on average from 2000 to 2007, when the impact of the IT revolution on productivity (and costs) was stronger than that of robot automation today. This and other evidence suggest that it is difficult to make the case that robots will make it tougher for central banks to reach their inflation goals than did previous technological breakthroughs. For investors, this means that we cannot rely on automation to keep inflation depressed irrespective of how tight labor markets become. Recent breakthroughs in technology are awe-inspiring and unsettling. These advances are viewed with great trepidation by many because of the potential to replace humans in the production process. Hype over robots is particularly shrill. Media reports warn of a "Robot Apocalypse" that is already laying waste to jobs and depressing wages on a broad scale. In the first in our series of Special Reports focusing on the structural factors that might be preventing central banks from reaching their inflation targets, we demonstrated that the impact of Amazon is overstated in the press. We estimated that E-commerce is depressing inflation in the U.S. by a mere 0.1 to 0.2 percentage points. This Special Report tackles the impact of automation. We are optimistic that robot technology and artificial intelligence will significantly boost future productivity, and thus reduce costs. But, is there any evidence at the macro level that robot usage has been more deflationary than technological breakthroughs in the past and is, thus, a major driver of the low inflation rates we observe today across the major countries? The question matters, especially for the outlook for central bank policy and the bond market. If structural factors are indeed holding back inflation by more than in previous decades, then the Fed will have to proceed very slowly in raising rates. However, if low inflation simply reflects long lags between wages and the tightening labor market, then inflation may suddenly lurch to life as it has at the end of past cycles. The bond market is not priced for that scenario. Are Robots Different? A Special Report from BCA's Technology Sector Strategy service suggested that the "robot revolution" could be as transformative as previous General Purpose Technologies (GPT), including the steam engine, electricity and the microchip.1 GPTs are technologies that radically alter the economy's production process and make a major contribution to living standards over time. The term "robot" can have different meanings. The most basic definition is "a device that automatically performs complicated and often repetitive tasks," and this encompasses a broad range of machines: From the Jacquard Loom, which was invented over 200 years ago, on to Numerically Controlled (NC) mills and lathes, pick and place machines used in the manufacture of electronics, Autonomous Vehicles (AVs), and even homicidal robots from the future such as the Terminator. Our Technology Sector report made the case that there is nothing particularly sinister about robots. They are just another chapter in a long history of automation. Nor is the displacement of workers unprecedented. The industrial revolution was about replacing human craft labor with capital (machines), which did high-volume work with better quality and productivity. This freed humans for work which had not yet been automated, along with designing, producing and maintaining the machinery. Agriculture offers a good example. This sector involved over 50% of the U.S. labor force until the late 1800s. Steam and then internal combustion-powered tractors, which can be viewed as "robotic horses," contributed to a massive rise in output-per-man hour. The number of hours worked to produce a bushel of wheat fell by almost 98% from the mid-1800s to 1955. This put a lot of farm hands out of work, but these laborers were absorbed over time in other growing areas of the economy. It is the same story for all other historical technological breakthroughs. Change is stressful for those directly affected, but rising productivity ultimately lifts average living standards. Robots will be no different. As we discuss below, however, the increasing use of robots and AI may have a deeper and longer-lasting impact on inequality. Strong Tailwinds Chart II-1Robots Are Getting Cheaper Robots Are Getting Cheaper Robots Are Getting Cheaper Factory robots have improved immensely due to cheaper and more capable control and vision systems. As these systems evolve, the abilities of robots to move around their environment while avoiding obstacles will improve, as will their ability to perform increasingly complex tasks. Most importantly, robots are already able to do more than just routine tasks, thus enabling them to replace or aid humans in higher-skilled processes. Robot prices are also falling fast, especially after quality-adjusting the data (Chart II-1). Units are becoming easier to install, program and operate. These trends will help to reduce the barriers-to-entry for the large, untapped, market of small and medium sized enterprises. Robots also offer the ability to do low-volume "customized" production and still keep unit costs low. In the future, self-learning robots will be able to optimize their own performance by analyzing the production of other robots around the world. Robot usage is growing quickly according to data collected by the International Federation of Robotics (IFR) that covers 23 countries. Industrial robot sales worldwide increased to almost 300,000 units in 2016, up 16% from the year before (Chart II-2). The stock of industrial robots globally has grown at an annual average pace of 10% since 2010, reaching slightly more than 1.8 million units in 2016.2 Robot usage is far from evenly distributed across industries. The automotive industry is the major consumer of industrial robots, holding 45% of the total stock in 2016 (Chart II-3). The computer & electronics industry is a distant second at 17%. Metals, chemicals and electrical/electronic appliances comprise the bulk of the remaining stock. Chart II-2Global Robot Usage Global Robot Usage Global Robot Usage Chart II-3Global Robot Usage By Industry (2016) February 2018 February 2018 As far as countries go, Japan has traditionally been the largest market for robots in the world. However, sales have been in a long-term downtrend and the stock of robots has recently been surpassed by China, which has ramped up robot purchases in recent years (Chart II-4). Robot density, which is the stock of robots per 10 thousand employed in manufacturing, makes it easier to compare robot usage across countries (Chart II-5, panel 2). By this measure, China is not a heavy user of robots compared to other countries. South Korea stands at the top, well above the second-place finishers (Germany and Japan). Large automobile sectors in these three countries explain their high relative robot densities. Chart II-4Stock Of Robots By Country (I) Stock Of Robots By Country (I) Stock Of Robots By Country (I) Chart II-5Stock Of Robots By Country (II) (2016) February 2018 February 2018 While the growth rate of robot usage is impressive, it is from a very low base (outside of the automotive industry). The average number of robots per 10,000 employees is only 74 for the 23 countries in the IFR database. Robot use is tiny compared to total man hours worked. Chart II-6U.S. Investment In Robots U.S. Investment in Robots U.S. Investment in Robots In the U.S., spending on robots is only about 5% of total business spending on equipment and software (Chart II-6). To put this into perspective, U.S. spending on information, communication and technology (ICT) equipment represented 35-40% of total capital equipment spending during the tech boom in the 1990s and early 2000s.3 The bottom line is that there is a lot of hype in the press, but robots are not yet widely used across countries or industries. It will be many years before business spending on robots approaches the scale of the 1990s/2000s IT boom. A Deflationary Impact? As noted above, we view robotics as another chapter in a long history of technological advancements. Pessimists suggest that the latest advances are different because they are inherently more threatening to the overall job market and wage share of total income. If the pessimists are right, what are the theoretical channels though which this would have a greater disinflationary effect relative to previous GPT technologies? Faster Productivity Gains: Enhanced productivity drives down unit labor costs, which may be passed along to other industries (as cheaper inputs) and to the end consumer. More Human Displacement: The jobs created in other areas may be insufficient to replace the jobs displaced by robots, leading to lower aggregate income and spending. The loss of income for labor will simply go to the owners of capital, but the point is that the labor share of income might decline. Deflationary pressures could build as aggregate demand falls short of supply. Even in industries that are slow to automate, just the threat of being replaced by robots may curtail wage demands. Inequality: Some have argued that rising inequality is partly because the spoils of new technologies over the past 20 years have largely gone to the owners of capital. This shift may have undermined aggregate demand because upper income households tend to have a high saving rate, thereby depressing overall aggregate demand and inflationary pressures. The human displacement effect, described above, would exacerbate the inequality effect by transferring income from labor to the owners of capital. 1. Productivity It is difficult to see the benefits of robots on productivity at the economy-wide level. Productivity growth has been abysmal across the major developed countries since the Great Recession, but the productivity slowdown was evident long before Lehman collapsed (Chart II-7). The productivity slowdown continued even as automation using robots accelerated after 2010. Chart II-7Productivity Collapsed Despite Automation Productivity Collapsed Despite Automation Productivity Collapsed Despite Automation Some analysts argue that lackluster productivity is simply a statistical mirage because of the difficulties in measuring output in today's economy. We will not get into the details of the mismeasurement debate here. We encourage interested clients to read a Special Report by the BCA Global Investment Strategy service entitled "Weak Productivity Growth: Don't Blame The Statisticians." 4 Our colleague Peter Berezin makes the case that the unmeasured utility accruing from free internet services is large, but so was the unmeasured utility from antibiotics, radio, indoor plumbing and air conditioning. He argues that the real reason that productivity growth has slowed is that educational attainment has decelerated and businesses have plucked many of the low-hanging fruit made possible by the IT revolution. Cyclical factors stemming from the Great Recession and financial crisis are also to blame, as capital spending has been slow to recover in most of the advanced economies. Some other factors that help to explain the decline in aggregate productivity are provided in Appendix II-1. Nonetheless, the poor aggregate productivity performance does not mean that there are no benefits to using robots. The benefits are evident at the industrial level, where measurement issues are presumably less vexing for statisticians (i.e., it is easier to measure the output of the auto industry, for example, than for the economy as a whole). Chart II-8 plots the level of robot density in 2016 with average annual productivity growth since 2004 for 10 U.S. manufacturing industries (robot density is presented in deciles). A loose positive relationship is apparent. Chart II-8U.S.: Productivity Vs. Robot Density February 2018 February 2018 Academic studies estimate that robots have contributed importantly to economy-wide productivity growth. The Centre for Economic and Business Research (CEBR) estimated that labor productivity growth rises by 0.07 to 0.08 percentage points for every 1% rise in the rate of robot density.5 This implies that robots accounted for roughly 10% of the productivity growth experienced since the early 1990s in the major economies. Another study of 14 industries across 17 countries by the Centre for Economic Performance (CEP) found that robots boosted annual productivity growth by 0.36 percentage points over the 1993-2007 period.6 This is impressive because, if this estimate holds true for the U.S., robots' contribution to the 2½% average annual U.S. total productivity growth over the period was 14%. To put the importance of robotics into historical context, its contribution to productivity so far is roughly on par with that of the steam engine (Chart II-9). It falls well short of the 0.6 percentage point annual productivity contribution from the IT revolution. The implication is that, while the overall productivity performance has been dismal since 2007, it would have been even worse in the absence of robots. What does this mean for inflation? According to the "cost push" model of the inflation process, an increase in productivity of 0.36% that is not accompanied by associated wage gains would reduce unit labor costs (ULC) by the same amount. This should trim inflation if the cost savings are passed on to the end consumer, although by less than 0.36% because robots can only depress variable costs, not fixed costs. There indeed appears to be a slight negative relationship between robot density and unit labor costs at the industrial level in the U.S., although the relationship is loose at best (Chart II-10). Chart II-9GPT Contribution To Productivity February 2018 February 2018 Chart II-10U.S.: Unit Labor Costs Vs. Robot Density February 2018 February 2018 In theory, divergences in productivity across industries should only generate shifts in relative prices, and "cost push" inflation dynamics should only operate in the short term. Most economists believe that inflation is a purely monetary phenomenon in the long run, which means that central banks should be able to offset positive productivity shocks by lowering interest rates enough that aggregate demand keeps up with supply. Indeed, the Fed was successful in meeting the 2% inflation target on average from 2000 to 2007, when the impact of the IT revolution on productivity (and costs) was stronger than that of robot automation today. Also, note that inflation is currently low across the major advanced economies, irrespective of the level of robot intensity (Chart II-11). From this perspective, it is hard to see that robots should take much of the credit for today's low inflation backdrop. Chart II-11Inflation Vs. Robot Density February 2018 February 2018 2. Human Displacement A key question is whether robots and humans are perfect substitutes. If new technologies introduced in the past were perfect substitutes, then it would have led to massive underemployment and all of the income in the economy would eventually have migrated to the owners of capital. The fact that average real household incomes have risen over time, and that there has been no secular upward trend in unemployment rates over the centuries, means that new technologies were at least partly complementary with labor (i.e., the jobs lost as a direct result of productivity gains were more than replaced in other areas of the economy over time). Rather than replacing workers, in many cases tech made humans more productive in their jobs. Rising productivity lifted income and thereby led to the creation of new jobs in other areas. The capital that workers bring to the production process - the skills, know-how and special talents - became more valuable as interaction with technology increased. Like today, there were concerns in the 1950s and 1960s that computerization would displace many types of jobs and lead to widespread idleness and falling household income. With hindsight, there was little to worry about. Some argue that this time is different. Futurists frequently assert that the pace of innovation is not just accelerating, it is accelerating 'exponentially'. Robots can now, or will soon be able to, replace humans in tasks that require cognitive skills. This means that they will be far less complementary to humans than in the past. The displacement effect could thus be much larger, especially given the impressive advances in artificial intelligence. However, Box II-1 discusses why the threat to workers posed by AI is also heavily overblown in the media. The CEP multi-country study cited above did not find a large displacement effect; robot usage did not affect the overall number of hours worked in the 23 countries studied (although it found distributional effects - see below). In other words, rather than suppressing overall labor input, robot usage has led to more output, higher productivity, more jobs and stronger wage and income growth. A report by the Economic Policy Institute (EPI)7 takes a broader look at automation, using productivity growth and capital spending as proxies. Automation is what occurs as the implementation of new technologies is incorporated along with new capital equipment or software to replace human labor in the workplace. If automation is increasing 'exponentially' and displacing workers on a broad scale, one would expect to see accelerating productivity growth, robust capital spending, and more violent shifts in occupational shares. Exactly the opposite has occurred. Indeed, the report demonstrates that occupational employment shifts were far slower in the 2000-2015 period than in any decade in the 1900s (Chart II-12). Box II-1 The Threat From AI Is Overblown Media coverage of AI/Deep Learning has established a consensus view that we believe is well off the mark. A recent Special Report from BCA's Technology Sector Strategy service dispels the myths surrounding AI.8 We believe the consensus, in conjunction with warnings from a variety of sources, is leading to predictions, policy discussions, and even career choices based on a flawed premise. It is worth noting that the most vocal proponents of AI as a threat to jobs and even humanity are not AI experts. At the root of this consensus is the false view that emerging AI technology is anything like true intelligence. Modern AI is not remotely comparable in function to a biological brain. Scientists have a limited understanding of how brains work, and it is unlikely that a poorly understood system can be modeled on a computer. The misconception of intelligence is amplified by headlines claiming an AI "taught itself" a particular task. No AI has ever "taught itself" anything: All AI results have come about after careful programming by often PhD-level experts, who then supplied the system with vast amounts of high quality data to train it. Often these systems have been iterated a number of times and we only hear of successes, not the failures. The need for careful preparation of the AI system and the requirement for high quality data limits the applicability of AI to specific classes of problems where the application justifies the investment in development and where sufficient high-quality data exists. There may be numerous such applications but doubtless many more where AI would not be suitable. Similarly, an AI system is highly adapted to a single problem, or type of problem, and becomes less useful when its application set is expanded. In other words, unlike a human whose abilities improve as they learn more things, an AI's performance on a particular task declines as it does more things. There is a popular misconception that increased computing power will somehow lead to ever improving AI. It is the algorithm which determines the outcome, not the computer performance: Increased computing power leads to faster results, not different results. Advanced computers might lead to more advanced algorithms, but it is pointless to speculate where that may lead: A spreadsheet from 2001 may work faster today but it still gives the same answer. In any event, it is worth noting that a tool ceases to be a tool when it starts having an opinion: there is little reason to develop a machine capable of cognition even if that were possible. Chart II-12U.S. Job Rotation Has Slowed February 2018 February 2018 The EPI report also notes that these indicators of automation increased rapidly in the late 1990s and early 2000s, a period that saw solid wage growth for American workers. These indicators weakened in the two periods of stagnant wage growth: from 1973 to 1995 and from 2002 to the present. Thus, there is no historical correlation between increases in automation and wage stagnation. Rather than automation, the report argues that it was China's entry into the global trading system that was largely responsible for the hollowing out of the U.S. manufacturing sector. We have also made this argument in previous research. The fact that the major advanced economies are all at, or close to, full employment supports the view that automation has not been an overwhelming headwind for job creation. Chart II-13 demonstrates that there has been no relationship between the change in robot density and the loss of manufacturing jobs since 1993. Japan is an interesting case study because it is on the leading edge of the problems associated with an aging population. Interestingly, despite a worsening labor shortage, robot density among Japanese firms is falling. Moreover, the Japanese data show that the industries that have a high robot usage tend to be more, not less, generous with wages than the robot laggard industries. Please see Appendix II-2 for more details. Chart II-13Global Manufacturing Jobs Vs. Robot Density February 2018 February 2018 The bottom line is that it does not appear that labor displacement related to automation has been responsible in any meaningful way for the lackluster average real income growth in the advanced economies since 2007. 3. Inequality That said, there is evidence suggesting that robots are having important distributional effects. The CEP study found that robot use has reduced hours for low-skilled and (to a lesser extent) middle-skilled workers relative to the highly skilled. This finding makes sense conceptually. Technological change can exacerbate inequality by either increasing the relative demand for skilled over unskilled workers (so-called "skill-biased" technological change), or by inducing companies to substitute machinery and other forms of physical capital for workers (so-called "capital-biased" technological change). The former affects the distribution of labor income, while the latter affects the share of income in GDP that labor receives. A Special Report appearing in this publication in 2014 focused on the relationship between technology and inequality.9 The report highlighted that much of the recent technological change has been skill-biased, which heavily favors workers with the talent and education to perform cognitively-demanding tasks, even as it reduces demand for workers with only rudimentary skills. Moreover, technological innovations and globalization increasingly allow the most talented individuals to market their skills to a much larger audience, thus bidding up their wages. The evidence suggests that faster productivity growth leads to higher average real wages and improved living standards, at least over reasonably long horizons. Nonetheless, technological change can, and in the future almost certainly will, increase income inequality. The poor will gain, but not as much as the rich. The fact that higher-income households tend to maintain a higher savings rate than low-income households means that the shift in the distribution of income toward the higher-income households will continue to modestly weigh on aggregate demand. Can the distribution effect be large enough to have a meaningful depressing impact on inflation? We believe that it has played some role in the lackluster recovery since the Great Recession, with the result that an extended period of underemployment has delivered a persistent deflationary impulse in the major developed economies. However, as discussed above, stimulative monetary policy has managed to overcome the impact of inequality and other headwinds on aggregate demand, and has returned the major countries roughly to full employment. Indeed, this year will be the first since 2007 that the G20 economies as a group will be operating slightly above a full employment level. Inflation should respond to excess demand conditions, irrespective of any ongoing demand headwind stemming from inequality. Conclusions Technological change has led to rising living standards over the decades. It did not lead to widespread joblessness and did not prevent central banks from meeting their inflation targets over time. The pessimists argue that this time is different because robots/AI have a much larger displacement effect. Perhaps it will be 20 years before we will know the answer. But our main point is that we have found no evidence that recent advances in robotics and AI, while very impressive, will be any different in their macro impact. There is little evidence that the modern economy is less capable in replacing the jobs lost to automation, although the nature of new technologies may be affecting the distribution of income more than in the past. Real incomes for the middle- and lower-income classes have been stagnant for some time, but this is partly due to productivity growth that is too low, not too high. Moreover, it is not at all clear that positive productivity shocks are disinflationary beyond the near term. The link between robot usage and unit labor costs over the past couple of decades is loose at best at the industry level, and is non-existent when looking across the major countries. The Fed was able to roughly meet its 2% inflation target in the 1990s and the first half of the 2000s, despite IT's impressive contribution to productivity growth during that period. For investors, this means that we cannot rely on automation to keep inflation depressed irrespective of how tight labor markets become. The global output gap will shift into positive territory this year for the first time since the Great Recession. Any resulting rise in inflation will come as a shock since the bond market has discounted continued low inflation for as far as the eye can see. We expect bond yields and implied volatility to rise this year, which may undermine risk assets in the second half. Mark McClellan Senior Vice President The Bank Credit Analyst Brian Piccioni Vice President Technology Sector Strategy Appendix II-1 Why Is Productivity So Low? A recent study by the OECD10 reveals that, while frontier firms are charging ahead, there is a widening gap between these firms and the laggards. The study analyzed firm-level data on labor productivity and total factor productivity for 24 countries. "Frontier" firms are defined to be those with productivity in the top 5%. These firms are 3-4 times as productive as the remaining 95%. The authors argue that the underlying cause of this yawning gap is that the diffusion rate of new technologies from the frontier firms to the laggards has slowed within industries. This could be due to rising barriers to entry, which has reduced contestability in markets. Curtailing the creative-destruction process means that there is less pressure to innovate. Barriers to entry may have increased because "...the importance of tacit knowledge as a source of competitive advantage for frontier firms may have risen if increasingly complex technologies were to increase the amount and sophistication of complementary investments required for technological adoption." 11 The bottom line is that aggregate productivity is low because the robust productivity gains for the tech-savvy frontier companies are offset by the long tail of firms that have been slow to adopt the latest technology. Indeed, business spending has been especially weak in this expansion. Chart II-14 highlights that the slowdown in U.S. productivity growth has mirrored that of the capital stock. Chart II-14U.S. Capex Shortfall Partly To Blame For Poor Productivity U.S. Capex Shortfall Partly To Blame For Poor Productivity U.S. Capex Shortfall Partly To Blame For Poor Productivity Appendix II-2 Japan - The Leading Edge Japan is an interesting case study because it is on the leading edge of the problems associated with an aging population. The popular press is full of stories of how robots are taking over. If the stories are to be believed, robots are the answer to the country's shrinking workforce. Robots now serve as helpers for the elderly, priests for weddings and funerals, concierges for hotels and even sexual partners (don't ask). Prime Minister Abe's government has launched a 5-year push to deepen the use of intelligent machines in manufacturing, supply chains, construction and health care. Indeed, Japan was the leader in robotics use for decades. Nonetheless, despite all the hype, Japan's stock of industrial robots has actually been eroding since the late 1990s (Chart II-4). Numerous surveys show that firms plan to use robots more in the future because of the difficulty in hiring humans. And there is huge potential: 90% of Japanese firms are small- and medium-sized (SME) and most are not currently using robots. Yet, there has been no wave of robot purchases as of 2016. One problem is the cost; most sophisticated robots are simply too expensive for SMEs to consider. This suggests that one cannot blame robots for Japan's lack of wage growth. The labor shortage has become so acute that there are examples of companies that have turned down sales due to insufficient manpower. Possible reasons why these companies do not offer higher wages to entice workers are beyond the scope of this report. But the fact that the stock of robots has been in decline since the late 1990s does not support the view that Japanese firms are using automation on a broad scale to avoid handing out pay hikes. Indeed, Chart II-15 highlights that wage deflation has been the greatest in industries that use almost no robots. Highly automated industries, such as Transportation Equipment and Electronics, have been among the most generous. This supports the view that the productivity afforded by increased robot usage encourages firms to pay their workers more. Looking ahead, it seems implausible that robots can replace all the retiring Japanese workers in the years to come. The workforce will shrink at an annual average pace of 0.33% between 2020 and 2030, according to the Japan Institute for Labour Policy and Training. Productivity growth would have to rise by the same amount to fully offset the dwindling number of workers. But that would require a surge in robot density of 4.1, assuming that each rise in robot density of one adds 0.08% to the level of productivity (Chart II-16). The level of robot sales would have to jump by a whopping 2½ times in the first year and continue to rise at the same pace each year thereafter to make this happen. Of course, the productivity afforded by new robots may accelerate in the coming years, but the point is that robot usage would likely have to rise astronomically to offset the impact of the shrinking population. Chart II-15Japan: Earnings Vs. Robot Density February 2018 February 2018 Chart II-16Japan: Where Is The Flood Of Robots? Japan: Where Is The Flood OF Robots? Japan: Where Is The Flood OF Robots? The implication is that, as long as the Japanese economy continues to grow above roughly 1%, the labor market will continue to tighten and wage rates will eventually begin to rise. 1 Please see Technology Sector Strategy Special Report "The Coming Robotics Revolution," dated May 16, 2017, available at tech.bcaresearch.com 2 Note that this includes only robots used in manufacturing industry, and thus excludes robots used in the service sector and households. However, robot usage in services is quite limited and those used in households do not add to GDP. 3 Note that ICT investment and capital stock data includes robots. 4 Please see BCA Global Investment Strategy Special Report "Weak Productivity Growth: Don't Blame The Statisticians," dated March 25, 2016, available at gis.bcaresearch.com 5 Centre for Economic and Business Research (January 2017): "The Impact of Automation." A Report for Redwood. In this report, robot density is defined to be the number of robots per million hours worked. 6 Graetz, G., and Michaels, G. (2015): "Robots At Work." CEP Discussion Paper No 1335. 7 Mishel, L., and Bivens, J. (2017): "The Zombie Robot Argument Lurches On," Economic Policy Institute. 8 Please see BCA Technology Sector Strategy Special Report "Bad Information - Why Misreporting Deep Learning Advances Is A Problem," dated January 9, 2018, available at tech.bcaresearch.com 9 Please see The Bank Credit Analyst, "Rage Against The Machines: Is Technology Exacerbating Inequality?" dated June 2014, available at bca.bcaresearch.com 10 OECD Productivity Working Papers, No. 05 (2016): "The Best Versus the Rest: The Global Productivity Slowdown, Divergence Across Firms and the Role of Public Policy." 11 Please refer to page 27. III. Indicators And Reference Charts As we highlight in the Overview section, the earnings backdrop for the U.S. equity market remains very upbeat, as highlighted by the rise in the net earnings revisions and net earnings surprises indexes. Bottom-up analysts will likely continue to boost after-tax earnings estimates for the year as they adjust to the U.S. tax cut news. Our main concern is that a lot of good news is now discounted. Our Technical Indicator remains bullish, but our composite valuation indicator surpassed one sigma in January, which is our threshold of overvaluation. From these levels of overvaluation, the medium-term outlook for equity total returns is negligible. Our speculation index is at all-time highs and implied volatility is low, underscoring that investors are extremely bullish. From a contrary perspective, this is a warning sign for the equity market. Our Monetary Indicator has also moved further into 'bearish' territory for equities, although overall financial conditions remain positive for growth. It is also disconcerting that our Revealed Preference Indicator (RPI) shifted to a 'sell' signal for stocks, following five straight months on a 'buy' signal. This occurred because investors may be buying based on speculation rather than on a firm belief in the staying power of the underlying fundamentals. For now, though, our Willingness-to-Pay indicator for the U.S. rose sharply in January, highlighting that investor equity inflows are very strong and are favoring U.S. equities relative to Japan and the Eurozone. This is perhaps not surprising given the U.S. tax cuts just passed by Congress. The RPI indicators track flows, and thus provide information on what investors are actually doing, as opposed to sentiment indexes that track how investors are feeling. Our U.S. bond technical indicator shows that Treasurys are close to oversold territory, suggesting that we may be in store for a consolidation period following January's surge in yields. Treasurys are slightly cheap on our valuation metric, although not by enough to justify closing short duration positions. The U.S. dollar is oversold and due for a bounce. EQUITIES: Chart III-1U.S. Equity Indicators U.S. Equity Indicators U.S. Equity Indicators Chart III-2Willingness To Pay For Risk Willingness To Pay For Risk Willingness To Pay For Risk Chart III-3U.S. Equity Sentiment Indicators U.S. Equity Sentiment Indicators U.S. Equity Sentiment Indicators Chart III-4Revealed Preference Indicator Revealed Preference Indicator Revealed Preference Indicator Chart III-5U.S. Stock Market Valuation U.S. Stock Market Valuation U.S. Stock Market Valuation Chart III-6U.S. Earnings U.S. Earnings U.S. Earnings Chart III-7Global Stock Market And Earnings: ##br##Relative Performance Global Stock Market And Earnings: Relative Performance Global Stock Market And Earnings: Relative Performance Chart III-8Global Stock Market And Earnings: ##br##Relative Performance Global Stock Market And Earnings: Relative Performance Global Stock Market And Earnings: Relative Performance FIXED INCOME: Chart III-9U.S. Treasurys And Valuations U.S. Treasurys and Valuations U.S. Treasurys and Valuations Chart III-10U.S. Treasury Indicators U.S. Treasury Indicators U.S. Treasury Indicators Chart III-11Selected U.S. Bond Yields Selected U.S. Bond Yields Selected U.S. Bond Yields Chart III-1210-Year Treasury Yield Components 10-Year Treasury Yield Components 10-Year Treasury Yield Components Chart III-13U.S. Corporate Bonds And Health Monitor U.S. Corporate Bonds And Health Monitor U.S. Corporate Bonds And Health Monitor Chart III-14Global Bonds: Developed Markets Global Bonds: Developed Markets Global Bonds: Developed Markets Chart III-15Global Bonds: Emerging Markets Global Bonds: Emerging Markets Global Bonds: Emerging Markets CURRENCIES: Chart III-16U.S. Dollar And PPP U.S. Dollar And PPP U.S. Dollar And PPP Chart III-17U.S. Dollar And Indicator U.S. Dollar And Indicator U.S. Dollar And Indicator Chart III-18U.S. Dollar Fundamentals U.S. Dollar Fundamentals U.S. Dollar Fundamentals Chart III-19Japanese Yen Technicals Japanese Yen Technicals Japanese Yen Technicals Chart III-20Euro Technicals Euro Technicals Euro Technicals Chart III-21Euro/Yen Technicals Euro/Yen Technicals Euro/Yen Technicals Chart III-22Euro/Pound Technicals Euro/Pound Technicals Euro/Pound Technicals COMMODITIES: Chart III-23Broad Commodity Indicators Broad Commodity Indicators Broad Commodity Indicators Chart III-24Commodity Prices Commodity Prices Commodity Prices Chart III-25Commodity Prices Commodity Prices Commodity Prices Chart III-26Commodity Sentiment Commodity Sentiment Commodity Sentiment Chart III-27Speculative Positioning Speculative Positioning Speculative Positioning ECONOMY: Chart III-28U.S. And Global Macro Backdrop U.S. And Global Macro Backdrop U.S. And Global Macro Backdrop Chart III-29U.S. Macro Snapshot U.S. Macro Snapshot U.S. Macro Snapshot Chart III-30U.S. Growth Outlook U.S. Growth Outlook U.S. Growth Outlook Chart III-31U.S. Cyclical Spending U.S. Cyclical Spending U.S. Cyclical Spending Chart III-32U.S. Labor Market U.S. Labor Market U.S. Labor Market Chart III-33U.S. Consumption U.S. Consumption U.S. Consumption Chart III-34U.S. Housing U.S. Housing U.S. Housing Chart III-35U.S. Debt And Deleveraging U.S. Debt And Deleveraging U.S. Debt And Deleveraging Chart III-36U.S. Financial Conditions U.S. Financial Conditions U.S. Financial Conditions Chart III-37Global Economic Snapshot: Europe Global Economic Snapshot: Europe Global Economic Snapshot: Europe Chart III-38Global Economic Snapshot: China Global Economic Snapshot: China Global Economic Snapshot: China Mark McClellan Senior Vice President The Bank Credit Analyst

Media reports warn of a "Robot Apocalypse" that is already laying waste to jobs and depressing wages on a broad scale. Technological advance in the past has not prevented improving living standards or led to ever rising joblessness over the decades, but pessimists argue that recent advances are different. The issue is important for financial markets. If structural factors such as automation are holding back inflation by more than in previous decades, then the Fed will have to proceed very slowly in raising rates. We see no compelling evidence that the displacement effect of emerging technologies is any stronger than in the past. Robot usage has had a modest positive impact on overall productivity. Despite this contribution, overall productivity growth has been dismal over the past decade. If automation is increasing 'exponentially' and displacing workers on a broad scale as some claim, one would expect to see accelerating productivity growth, robust capital spending and more violent shifts in occupational shares. Exactly the opposite has occurred. Periods of strong growth in automation have historically been associated with robust, not lackluster, wage gains, contrary to the consensus view. The Fed was successful in meeting the 2% inflation target on average from 2000 to 2007, when the impact of the IT revolution on productivity (and costs) was stronger than that of robot automation today. This and other evidence suggest that it is difficult to make the case that robots will make it tougher for central banks to reach their inflation goals than did previous technological breakthroughs. For investors, this means that we cannot rely on automation to keep inflation depressed irrespective of how tight labor markets become. Recent breakthroughs in technology are awe-inspiring and unsettling. These advances are viewed with great trepidation by many because of the potential to replace humans in the production process. Hype over robots is particularly shrill. Media reports warn of a "Robot Apocalypse" that is already laying waste to jobs and depressing wages on a broad scale. In the first in our series of Special Reports focusing on the structural factors that might be preventing central banks from reaching their inflation targets, we demonstrated that the impact of Amazon is overstated in the press. We estimated that E-commerce is depressing inflation in the U.S. by a mere 0.1 to 0.2 percentage points. This Special Report tackles the impact of automation. We are optimistic that robot technology and artificial intelligence will significantly boost future productivity, and thus reduce costs. But, is there any evidence at the macro level that robot usage has been more deflationary than technological breakthroughs in the past and is, thus, a major driver of the low inflation rates we observe today across the major countries? The question matters, especially for the outlook for central bank policy and the bond market. If structural factors are indeed holding back inflation by more than in previous decades, then the Fed will have to proceed very slowly in raising rates. However, if low inflation simply reflects long lags between wages and the tightening labor market, then inflation may suddenly lurch to life as it has at the end of past cycles. The bond market is not priced for that scenario. Are Robots Different? A Special Report from BCA's Technology Sector Strategy service suggested that the "robot revolution" could be as transformative as previous General Purpose Technologies (GPT), including the steam engine, electricity and the microchip.1 GPTs are technologies that radically alter the economy's production process and make a major contribution to living standards over time. The term "robot" can have different meanings. The most basic definition is "a device that automatically performs complicated and often repetitive tasks," and this encompasses a broad range of machines: From the Jacquard Loom, which was invented over 200 years ago, on to Numerically Controlled (NC) mills and lathes, pick and place machines used in the manufacture of electronics, Autonomous Vehicles (AVs), and even homicidal robots from the future such as the Terminator. Our Technology Sector report made the case that there is nothing particularly sinister about robots. They are just another chapter in a long history of automation. Nor is the displacement of workers unprecedented. The industrial revolution was about replacing human craft labor with capital (machines), which did high-volume work with better quality and productivity. This freed humans for work which had not yet been automated, along with designing, producing and maintaining the machinery. Agriculture offers a good example. This sector involved over 50% of the U.S. labor force until the late 1800s. Steam and then internal combustion-powered tractors, which can be viewed as "robotic horses," contributed to a massive rise in output-per-man hour. The number of hours worked to produce a bushel of wheat fell by almost 98% from the mid-1800s to 1955. This put a lot of farm hands out of work, but these laborers were absorbed over time in other growing areas of the economy. It is the same story for all other historical technological breakthroughs. Change is stressful for those directly affected, but rising productivity ultimately lifts average living standards. Robots will be no different. As we discuss below, however, the increasing use of robots and AI may have a deeper and longer-lasting impact on inequality. Strong Tailwinds Chart II-1Robots Are Getting Cheaper Robots Are Getting Cheaper Robots Are Getting Cheaper Factory robots have improved immensely due to cheaper and more capable control and vision systems. As these systems evolve, the abilities of robots to move around their environment while avoiding obstacles will improve, as will their ability to perform increasingly complex tasks. Most importantly, robots are already able to do more than just routine tasks, thus enabling them to replace or aid humans in higher-skilled processes. Robot prices are also falling fast, especially after quality-adjusting the data (Chart II-1). Units are becoming easier to install, program and operate. These trends will help to reduce the barriers-to-entry for the large, untapped, market of small and medium sized enterprises. Robots also offer the ability to do low-volume "customized" production and still keep unit costs low. In the future, self-learning robots will be able to optimize their own performance by analyzing the production of other robots around the world. Robot usage is growing quickly according to data collected by the International Federation of Robotics (IFR) that covers 23 countries. Industrial robot sales worldwide increased to almost 300,000 units in 2016, up 16% from the year before (Chart II-2). The stock of industrial robots globally has grown at an annual average pace of 10% since 2010, reaching slightly more than 1.8 million units in 2016.2 Robot usage is far from evenly distributed across industries. The automotive industry is the major consumer of industrial robots, holding 45% of the total stock in 2016 (Chart II-3). The computer & electronics industry is a distant second at 17%. Metals, chemicals and electrical/electronic appliances comprise the bulk of the remaining stock. Chart II-2Global Robot Usage Global Robot Usage Global Robot Usage Chart II-3Global Robot Usage By Industry (2016) February 2018 February 2018 As far as countries go, Japan has traditionally been the largest market for robots in the world. However, sales have been in a long-term downtrend and the stock of robots has recently been surpassed by China, which has ramped up robot purchases in recent years (Chart II-4). Robot density, which is the stock of robots per 10 thousand employed in manufacturing, makes it easier to compare robot usage across countries (Chart II-5, panel 2). By this measure, China is not a heavy user of robots compared to other countries. South Korea stands at the top, well above the second-place finishers (Germany and Japan). Large automobile sectors in these three countries explain their high relative robot densities. Chart II-4Stock Of Robots By Country (I) Stock Of Robots By Country (I) Stock Of Robots By Country (I) Chart II-5Stock Of Robots By Country (II) (2016) February 2018 February 2018 While the growth rate of robot usage is impressive, it is from a very low base (outside of the automotive industry). The average number of robots per 10,000 employees is only 74 for the 23 countries in the IFR database. Robot use is tiny compared to total man hours worked. Chart II-6U.S. Investment In Robots U.S. Investment in Robots U.S. Investment in Robots In the U.S., spending on robots is only about 5% of total business spending on equipment and software (Chart II-6). To put this into perspective, U.S. spending on information, communication and technology (ICT) equipment represented 35-40% of total capital equipment spending during the tech boom in the 1990s and early 2000s.3 The bottom line is that there is a lot of hype in the press, but robots are not yet widely used across countries or industries. It will be many years before business spending on robots approaches the scale of the 1990s/2000s IT boom. A Deflationary Impact? As noted above, we view robotics as another chapter in a long history of technological advancements. Pessimists suggest that the latest advances are different because they are inherently more threatening to the overall job market and wage share of total income. If the pessimists are right, what are the theoretical channels though which this would have a greater disinflationary effect relative to previous GPT technologies? Faster Productivity Gains: Enhanced productivity drives down unit labor costs, which may be passed along to other industries (as cheaper inputs) and to the end consumer. More Human Displacement: The jobs created in other areas may be insufficient to replace the jobs displaced by robots, leading to lower aggregate income and spending. The loss of income for labor will simply go to the owners of capital, but the point is that the labor share of income might decline. Deflationary pressures could build as aggregate demand falls short of supply. Even in industries that are slow to automate, just the threat of being replaced by robots may curtail wage demands. Inequality: Some have argued that rising inequality is partly because the spoils of new technologies over the past 20 years have largely gone to the owners of capital. This shift may have undermined aggregate demand because upper income households tend to have a high saving rate, thereby depressing overall aggregate demand and inflationary pressures. The human displacement effect, described above, would exacerbate the inequality effect by transferring income from labor to the owners of capital. 1. Productivity It is difficult to see the benefits of robots on productivity at the economy-wide level. Productivity growth has been abysmal across the major developed countries since the Great Recession, but the productivity slowdown was evident long before Lehman collapsed (Chart II-7). The productivity slowdown continued even as automation using robots accelerated after 2010. Chart II-7Productivity Collapsed Despite Automation Productivity Collapsed Despite Automation Productivity Collapsed Despite Automation Some analysts argue that lackluster productivity is simply a statistical mirage because of the difficulties in measuring output in today's economy. We will not get into the details of the mismeasurement debate here. We encourage interested clients to read a Special Report by the BCA Global Investment Strategy service entitled "Weak Productivity Growth: Don't Blame The Statisticians." 4 Our colleague Peter Berezin makes the case that the unmeasured utility accruing from free internet services is large, but so was the unmeasured utility from antibiotics, radio, indoor plumbing and air conditioning. He argues that the real reason that productivity growth has slowed is that educational attainment has decelerated and businesses have plucked many of the low-hanging fruit made possible by the IT revolution. Cyclical factors stemming from the Great Recession and financial crisis are also to blame, as capital spending has been slow to recover in most of the advanced economies. Some other factors that help to explain the decline in aggregate productivity are provided in Appendix II-1. Nonetheless, the poor aggregate productivity performance does not mean that there are no benefits to using robots. The benefits are evident at the industrial level, where measurement issues are presumably less vexing for statisticians (i.e., it is easier to measure the output of the auto industry, for example, than for the economy as a whole). Chart II-8 plots the level of robot density in 2016 with average annual productivity growth since 2004 for 10 U.S. manufacturing industries (robot density is presented in deciles). A loose positive relationship is apparent. Chart II-8U.S.: Productivity Vs. Robot Density February 2018 February 2018 Academic studies estimate that robots have contributed importantly to economy-wide productivity growth. The Centre for Economic and Business Research (CEBR) estimated that labor productivity growth rises by 0.07 to 0.08 percentage points for every 1% rise in the rate of robot density.5 This implies that robots accounted for roughly 10% of the productivity growth experienced since the early 1990s in the major economies. Another study of 14 industries across 17 countries by the Centre for Economic Performance (CEP) found that robots boosted annual productivity growth by 0.36 percentage points over the 1993-2007 period.6 This is impressive because, if this estimate holds true for the U.S., robots' contribution to the 2½% average annual U.S. total productivity growth over the period was 14%. To put the importance of robotics into historical context, its contribution to productivity so far is roughly on par with that of the steam engine (Chart II-9). It falls well short of the 0.6 percentage point annual productivity contribution from the IT revolution. The implication is that, while the overall productivity performance has been dismal since 2007, it would have been even worse in the absence of robots. What does this mean for inflation? According to the "cost push" model of the inflation process, an increase in productivity of 0.36% that is not accompanied by associated wage gains would reduce unit labor costs (ULC) by the same amount. This should trim inflation if the cost savings are passed on to the end consumer, although by less than 0.36% because robots can only depress variable costs, not fixed costs. There indeed appears to be a slight negative relationship between robot density and unit labor costs at the industrial level in the U.S., although the relationship is loose at best (Chart II-10). Chart II-9GPT Contribution To Productivity February 2018 February 2018 Chart II-10U.S.: Unit Labor Costs Vs. Robot Density February 2018 February 2018 In theory, divergences in productivity across industries should only generate shifts in relative prices, and "cost push" inflation dynamics should only operate in the short term. Most economists believe that inflation is a purely monetary phenomenon in the long run, which means that central banks should be able to offset positive productivity shocks by lowering interest rates enough that aggregate demand keeps up with supply. Indeed, the Fed was successful in meeting the 2% inflation target on average from 2000 to 2007, when the impact of the IT revolution on productivity (and costs) was stronger than that of robot automation today. Also, note that inflation is currently low across the major advanced economies, irrespective of the level of robot intensity (Chart II-11). From this perspective, it is hard to see that robots should take much of the credit for today's low inflation backdrop. Chart II-11Inflation Vs. Robot Density February 2018 February 2018 2. Human Displacement A key question is whether robots and humans are perfect substitutes. If new technologies introduced in the past were perfect substitutes, then it would have led to massive underemployment and all of the income in the economy would eventually have migrated to the owners of capital. The fact that average real household incomes have risen over time, and that there has been no secular upward trend in unemployment rates over the centuries, means that new technologies were at least partly complementary with labor (i.e., the jobs lost as a direct result of productivity gains were more than replaced in other areas of the economy over time). Rather than replacing workers, in many cases tech made humans more productive in their jobs. Rising productivity lifted income and thereby led to the creation of new jobs in other areas. The capital that workers bring to the production process - the skills, know-how and special talents - became more valuable as interaction with technology increased. Like today, there were concerns in the 1950s and 1960s that computerization would displace many types of jobs and lead to widespread idleness and falling household income. With hindsight, there was little to worry about. Some argue that this time is different. Futurists frequently assert that the pace of innovation is not just accelerating, it is accelerating 'exponentially'. Robots can now, or will soon be able to, replace humans in tasks that require cognitive skills. This means that they will be far less complementary to humans than in the past. The displacement effect could thus be much larger, especially given the impressive advances in artificial intelligence. However, Box II-1 discusses why the threat to workers posed by AI is also heavily overblown in the media. The CEP multi-country study cited above did not find a large displacement effect; robot usage did not affect the overall number of hours worked in the 23 countries studied (although it found distributional effects - see below). In other words, rather than suppressing overall labor input, robot usage has led to more output, higher productivity, more jobs and stronger wage and income growth. A report by the Economic Policy Institute (EPI)7 takes a broader look at automation, using productivity growth and capital spending as proxies. Automation is what occurs as the implementation of new technologies is incorporated along with new capital equipment or software to replace human labor in the workplace. If automation is increasing 'exponentially' and displacing workers on a broad scale, one would expect to see accelerating productivity growth, robust capital spending, and more violent shifts in occupational shares. Exactly the opposite has occurred. Indeed, the report demonstrates that occupational employment shifts were far slower in the 2000-2015 period than in any decade in the 1900s (Chart II-12). Box II-1 The Threat From AI Is Overblown Media coverage of AI/Deep Learning has established a consensus view that we believe is well off the mark. A recent Special Report from BCA's Technology Sector Strategy service dispels the myths surrounding AI.8 We believe the consensus, in conjunction with warnings from a variety of sources, is leading to predictions, policy discussions, and even career choices based on a flawed premise. It is worth noting that the most vocal proponents of AI as a threat to jobs and even humanity are not AI experts. At the root of this consensus is the false view that emerging AI technology is anything like true intelligence. Modern AI is not remotely comparable in function to a biological brain. Scientists have a limited understanding of how brains work, and it is unlikely that a poorly understood system can be modeled on a computer. The misconception of intelligence is amplified by headlines claiming an AI "taught itself" a particular task. No AI has ever "taught itself" anything: All AI results have come about after careful programming by often PhD-level experts, who then supplied the system with vast amounts of high quality data to train it. Often these systems have been iterated a number of times and we only hear of successes, not the failures. The need for careful preparation of the AI system and the requirement for high quality data limits the applicability of AI to specific classes of problems where the application justifies the investment in development and where sufficient high-quality data exists. There may be numerous such applications but doubtless many more where AI would not be suitable. Similarly, an AI system is highly adapted to a single problem, or type of problem, and becomes less useful when its application set is expanded. In other words, unlike a human whose abilities improve as they learn more things, an AI's performance on a particular task declines as it does more things. There is a popular misconception that increased computing power will somehow lead to ever improving AI. It is the algorithm which determines the outcome, not the computer performance: Increased computing power leads to faster results, not different results. Advanced computers might lead to more advanced algorithms, but it is pointless to speculate where that may lead: A spreadsheet from 2001 may work faster today but it still gives the same answer. In any event, it is worth noting that a tool ceases to be a tool when it starts having an opinion: there is little reason to develop a machine capable of cognition even if that were possible. Chart II-12U.S. Job Rotation Has Slowed February 2018 February 2018 The EPI report also notes that these indicators of automation increased rapidly in the late 1990s and early 2000s, a period that saw solid wage growth for American workers. These indicators weakened in the two periods of stagnant wage growth: from 1973 to 1995 and from 2002 to the present. Thus, there is no historical correlation between increases in automation and wage stagnation. Rather than automation, the report argues that it was China's entry into the global trading system that was largely responsible for the hollowing out of the U.S. manufacturing sector. We have also made this argument in previous research. The fact that the major advanced economies are all at, or close to, full employment supports the view that automation has not been an overwhelming headwind for job creation. Chart II-13 demonstrates that there has been no relationship between the change in robot density and the loss of manufacturing jobs since 1993. Japan is an interesting case study because it is on the leading edge of the problems associated with an aging population. Interestingly, despite a worsening labor shortage, robot density among Japanese firms is falling. Moreover, the Japanese data show that the industries that have a high robot usage tend to be more, not less, generous with wages than the robot laggard industries. Please see Appendix II-2 for more details. Chart II-13Global Manufacturing Jobs Vs. Robot Density February 2018 February 2018 The bottom line is that it does not appear that labor displacement related to automation has been responsible in any meaningful way for the lackluster average real income growth in the advanced economies since 2007. 3. Inequality That said, there is evidence suggesting that robots are having important distributional effects. The CEP study found that robot use has reduced hours for low-skilled and (to a lesser extent) middle-skilled workers relative to the highly skilled. This finding makes sense conceptually. Technological change can exacerbate inequality by either increasing the relative demand for skilled over unskilled workers (so-called "skill-biased" technological change), or by inducing companies to substitute machinery and other forms of physical capital for workers (so-called "capital-biased" technological change). The former affects the distribution of labor income, while the latter affects the share of income in GDP that labor receives. A Special Report appearing in this publication in 2014 focused on the relationship between technology and inequality.9 The report highlighted that much of the recent technological change has been skill-biased, which heavily favors workers with the talent and education to perform cognitively-demanding tasks, even as it reduces demand for workers with only rudimentary skills. Moreover, technological innovations and globalization increasingly allow the most talented individuals to market their skills to a much larger audience, thus bidding up their wages. The evidence suggests that faster productivity growth leads to higher average real wages and improved living standards, at least over reasonably long horizons. Nonetheless, technological change can, and in the future almost certainly will, increase income inequality. The poor will gain, but not as much as the rich. The fact that higher-income households tend to maintain a higher savings rate than low-income households means that the shift in the distribution of income toward the higher-income households will continue to modestly weigh on aggregate demand. Can the distribution effect be large enough to have a meaningful depressing impact on inflation? We believe that it has played some role in the lackluster recovery since the Great Recession, with the result that an extended period of underemployment has delivered a persistent deflationary impulse in the major developed economies. However, as discussed above, stimulative monetary policy has managed to overcome the impact of inequality and other headwinds on aggregate demand, and has returned the major countries roughly to full employment. Indeed, this year will be the first since 2007 that the G20 economies as a group will be operating slightly above a full employment level. Inflation should respond to excess demand conditions, irrespective of any ongoing demand headwind stemming from inequality. Conclusions Technological change has led to rising living standards over the decades. It did not lead to widespread joblessness and did not prevent central banks from meeting their inflation targets over time. The pessimists argue that this time is different because robots/AI have a much larger displacement effect. Perhaps it will be 20 years before we will know the answer. But our main point is that we have found no evidence that recent advances in robotics and AI, while very impressive, will be any different in their macro impact. There is little evidence that the modern economy is less capable in replacing the jobs lost to automation, although the nature of new technologies may be affecting the distribution of income more than in the past. Real incomes for the middle- and lower-income classes have been stagnant for some time, but this is partly due to productivity growth that is too low, not too high. Moreover, it is not at all clear that positive productivity shocks are disinflationary beyond the near term. The link between robot usage and unit labor costs over the past couple of decades is loose at best at the industry level, and is non-existent when looking across the major countries. The Fed was able to roughly meet its 2% inflation target in the 1990s and the first half of the 2000s, despite IT's impressive contribution to productivity growth during that period. For investors, this means that we cannot rely on automation to keep inflation depressed irrespective of how tight labor markets become. The global output gap will shift into positive territory this year for the first time since the Great Recession. Any resulting rise in inflation will come as a shock since the bond market has discounted continued low inflation for as far as the eye can see. We expect bond yields and implied volatility to rise this year, which may undermine risk assets in the second half. Mark McClellan Senior Vice President The Bank Credit Analyst Brian Piccioni Vice President Technology Sector Strategy Appendix II-1 Why Is Productivity So Low? A recent study by the OECD10 reveals that, while frontier firms are charging ahead, there is a widening gap between these firms and the laggards. The study analyzed firm-level data on labor productivity and total factor productivity for 24 countries. "Frontier" firms are defined to be those with productivity in the top 5%. These firms are 3-4 times as productive as the remaining 95%. The authors argue that the underlying cause of this yawning gap is that the diffusion rate of new technologies from the frontier firms to the laggards has slowed within industries. This could be due to rising barriers to entry, which has reduced contestability in markets. Curtailing the creative-destruction process means that there is less pressure to innovate. Barriers to entry may have increased because "...the importance of tacit knowledge as a source of competitive advantage for frontier firms may have risen if increasingly complex technologies were to increase the amount and sophistication of complementary investments required for technological adoption." 11 The bottom line is that aggregate productivity is low because the robust productivity gains for the tech-savvy frontier companies are offset by the long tail of firms that have been slow to adopt the latest technology. Indeed, business spending has been especially weak in this expansion. Chart II-14 highlights that the slowdown in U.S. productivity growth has mirrored that of the capital stock. Chart II-14U.S. Capex Shortfall Partly To Blame For Poor Productivity U.S. Capex Shortfall Partly To Blame For Poor Productivity U.S. Capex Shortfall Partly To Blame For Poor Productivity Appendix II-2 Japan - The Leading Edge Japan is an interesting case study because it is on the leading edge of the problems associated with an aging population. The popular press is full of stories of how robots are taking over. If the stories are to be believed, robots are the answer to the country's shrinking workforce. Robots now serve as helpers for the elderly, priests for weddings and funerals, concierges for hotels and even sexual partners (don't ask). Prime Minister Abe's government has launched a 5-year push to deepen the use of intelligent machines in manufacturing, supply chains, construction and health care. Indeed, Japan was the leader in robotics use for decades. Nonetheless, despite all the hype, Japan's stock of industrial robots has actually been eroding since the late 1990s (Chart II-4). Numerous surveys show that firms plan to use robots more in the future because of the difficulty in hiring humans. And there is huge potential: 90% of Japanese firms are small- and medium-sized (SME) and most are not currently using robots. Yet, there has been no wave of robot purchases as of 2016. One problem is the cost; most sophisticated robots are simply too expensive for SMEs to consider. This suggests that one cannot blame robots for Japan's lack of wage growth. The labor shortage has become so acute that there are examples of companies that have turned down sales due to insufficient manpower. Possible reasons why these companies do not offer higher wages to entice workers are beyond the scope of this report. But the fact that the stock of robots has been in decline since the late 1990s does not support the view that Japanese firms are using automation on a broad scale to avoid handing out pay hikes. Indeed, Chart II-15 highlights that wage deflation has been the greatest in industries that use almost no robots. Highly automated industries, such as Transportation Equipment and Electronics, have been among the most generous. This supports the view that the productivity afforded by increased robot usage encourages firms to pay their workers more. Looking ahead, it seems implausible that robots can replace all the retiring Japanese workers in the years to come. The workforce will shrink at an annual average pace of 0.33% between 2020 and 2030, according to the Japan Institute for Labour Policy and Training. Productivity growth would have to rise by the same amount to fully offset the dwindling number of workers. But that would require a surge in robot density of 4.1, assuming that each rise in robot density of one adds 0.08% to the level of productivity (Chart II-16). The level of robot sales would have to jump by a whopping 2½ times in the first year and continue to rise at the same pace each year thereafter to make this happen. Of course, the productivity afforded by new robots may accelerate in the coming years, but the point is that robot usage would likely have to rise astronomically to offset the impact of the shrinking population. Chart II-15Japan: Earnings Vs. Robot Density February 2018 February 2018 Chart II-16Japan: Where Is The Flood Of Robots? Japan: Where Is The Flood OF Robots? Japan: Where Is The Flood OF Robots? The implication is that, as long as the Japanese economy continues to grow above roughly 1%, the labor market will continue to tighten and wage rates will eventually begin to rise. 1 Please see Technology Sector Strategy Special Report "The Coming Robotics Revolution," dated May 16, 2017, available at tech.bcaresearch.com 2 Note that this includes only robots used in manufacturing industry, and thus excludes robots used in the service sector and households. However, robot usage in services is quite limited and those used in households do not add to GDP. 3 Note that ICT investment and capital stock data includes robots. 4 Please see BCA Global Investment Strategy Special Report "Weak Productivity Growth: Don't Blame The Statisticians," dated March 25, 2016, available at gis.bcaresearch.com 5 Centre for Economic and Business Research (January 2017): "The Impact of Automation." A Report for Redwood. In this report, robot density is defined to be the number of robots per million hours worked. 6 Graetz, G., and Michaels, G. (2015): "Robots At Work." CEP Discussion Paper No 1335. 7 Mishel, L., and Bivens, J. (2017): "The Zombie Robot Argument Lurches On," Economic Policy Institute. 8 Please see BCA Technology Sector Strategy Special Report "Bad Information - Why Misreporting Deep Learning Advances Is A Problem," dated January 9, 2018, available at tech.bcaresearch.com 9 Please see The Bank Credit Analyst, "Rage Against The Machines: Is Technology Exacerbating Inequality?" dated June 2014, available at bca.bcaresearch.com 10 OECD Productivity Working Papers, No. 05 (2016): "The Best Versus the Rest: The Global Productivity Slowdown, Divergence Across Firms and the Role of Public Policy." 11 Please refer to page 27.