Labor Market

Highlights We are shifting our U.S. recession call from late-2019 to 2020. A cheap dollar and fiscal support will give the Fed more scope to raise rates before monetary policy moves into restrictive territory. The fiscal impulse will fall sharply in 2020. By then, financial conditions will be tighter and economic imbalances will be more pronounced. As is usually the case, a downturn in the U.S. will infect the rest of the world. Emerging markets with large current account deficits and high debt levels are most vulnerable. A cyclical overweight to global equities is still appropriate, but long-term investors should begin to scale back risk exposure. Feature Records Are Meant To Be Broken The NBER Business Cycle Dating Committee, which contrary to popular belief does not serve as a matchmaking service for lonely-heart economists, estimates that the current economic expansion is going on nine years. If it makes it to July 2019, it will be the longest in history (Chart 1). Considering that records begin in 1854 - encompassing 33 business cycles - that will be an impressive achievement. Chart 1Nine Years And Still Going Strong There is an old adage that says "Expansions do not die of old age. They are murdered by the Fed." A year or so ago, it looked like the Fed would pull the trigger sometime in 2019. Now, however, it looks more likely that the deed will be committed in 2020. Two things have changed since the start of last year. First, the real trade-weighted dollar has fallen by 8%. According to the Fed's SIGMA macroeconomic model, this should boost growth by about 0.3% over the next two years. Chart 2U.S. Fiscal Policy Has Become##BR##Much More Stimulative Second, U.S. fiscal policy has become much more stimulative, a point very much in keeping with our Geopolitical Strategy team's long-standing view that age of austerity is giving way to a new age of populism.1 My colleague Mark McClellan estimates that the U.S. fiscal impulse will reach 0.8% of GDP in 2018 and 1.3% of GDP in 2019, up from -0.4% and 0.3%, respectively, in the IMF's October 2017 projections (Chart 2). Mark's calculations incorporate the CBO's assessment of the tax cuts, the recent Senate deal to raise the caps on defense and nondefense expenditures, and $45 billion in hurricane relief. He assumes some delay between when the bill is passed and when the spending takes place. According to the Congressional Budget Office, a little more than half of the expenditures in the 2013 and 2015 spending bills occurred in the same year the funding was authorized. These fiscal measures will cause the federal budget deficit to swell by about 2.3 percentage points to 5.6% of GDP in FY2019. Even that may be an understatement, as this does not include any additional infrastructure spending nor the possible restoration of "earmarks"- the widely criticized practice that allows members of Congress to add appropriations to unrelated bills to fund what often turn out to be politically motivated projects in their districts - which could add a further $25 billion in annual spending. Meanwhile, federal government revenue is coming in below target, which the Office of Management and Budget (OMB) has attributed to lower-than-expected taxable income from pass-through businesses and capital gains realizations. This problem could worsen over the next few years as creative accountants find new loopholes to exploit in the recently passed tax bill. Too Much, Too Late All this stimulus is arriving when the economy least needs it. The unemployment rate currently stands at 4.1%, 0.5 points below the level the Fed regards as consistent with full employment. It has been stuck at that number for four straight months, largely because job growth in the Household survey (which the unemployment rate is based on) has lagged the Establishment survey by a considerable margin. Given the underlying strength in GDP growth, it is likely the job gains in the Household survey will rebound strongly over the course of 2018, taking the unemployment rate down to 3.5% by year-end, well below the Fed's end-2018 projection of 3.9%. A lower-than-projected unemployment rate will permit the Fed to raise rates four times this year, one more hike than currently implied by the dots. The Fed will probably also hike rates three or four times next year. Yet, even those additional rate hikes will not come close to offsetting all the fiscal stimulus coming down the pike. In the absence of a sustained increase in productivity or labor force growth - neither of which appear forthcoming - the economy will continue to overheat. Inflation is a highly lagging indicator. It typically does not peak until well after a recession has begun and does not bottom until well after it has ended (Chart 3). The Fed knows this perfectly well, but has chosen to let the economy run hot for fear that a premature tightening will sow the seeds for a deflationary spiral. Chart 3Inflation Is A Lagging Indicator By the time the next recession rolls around, inflation will be higher and financial and economic imbalances will be greater. The fiscal impulse will also fall back towards zero in 2020 as the budget deficit stabilizes at an elevated level. It is the change in the budget balance that is correlated with GDP growth. If output is already being constrained by a lack of spare capacity going into late-2019, the subsequent decline in the fiscal impulse in 2020 could push growth below trend, leading to rising unemployment. And, as we have often noted, once unemployment starts rising, it keeps rising. There has never been a case in the post-war era where the unemployment rate has risen by more than one-third of a percentage point that was not associated with a recession (Chart 4). Chart 4Even A Small Uptick In The Unemployment Rate Is Bad News For The Business Cycle A recent IMF report highlighted that changes in U.S. financial conditions strongly influence growth abroad.2 As the U.S. falls into a recession, equity prices will tumble and credit spreads will widen. Financial conditions will tighten, transmitting the downturn to the rest of the world. Emerging markets with large current account deficits and high debt levels will be the most vulnerable. The only saving grace is that interest rates will be higher in 2020 than they would have been if the recession had begun in 2019. This will give the Fed a bit more scope to ease monetary policy again. As discussed last week, this will likely set the stage for a stagflationary episode following the recession.3 For Now, Leading Indicators Look A-Okay While our baseline view is that the next recession will occur in 2020, this is more of an educated guess than a firm prediction. Many things, including an overly aggressive Fed, a sharp appreciation in the dollar, and a variety of political shocks, could cause the recession to occur sooner than anticipated. As such, we continue to watch a wide swathe of data to help guide our investment recommendations. The good news is that right now, none of our favorite leading economic indicators such as the level of ISM manufacturing new orders minus inventories, capital goods orders, initial unemployment claims, and building permits are flashing red (Chart 5). Many of these indicators appear in The Conference Board's LEI, which is still rising at a healthy 5.5% y/y pace. Historically, a decisive break below zero in the year-over-year change in the LEI has been a reliable recession indicator (Chart 6). We are still far from that point. Chart 5U.S. Leading Indicators Looking A-OKAY Chart 6U.S. LEI Is Not Flashing Red The same goes for leading financial variables such as credit spreads and the yield curve. The yield curve has inverted in the lead-up to every recession over the past 50 years (Chart 7). The fact that the 10-year/3-month slope has steepened by 30 basis points since the start of the year gives us some comfort that the next recession is still some time away. Chart 7An Inverted Yield Curve Has Often Been A Harbinger Of A Recession Keep An Eye On Credit Credit spreads remained well contained during the recent bout of market turbulence but we continue to watch them closely. Credit typically starts to underperform before equities do, which makes it a good leading indicator for the stock market. This is likely to be especially the case over the next two years. If there is one area where financial imbalances have accumulated to worrying levels, it is in the corporate debt arena. This month's issue of the Bank Credit Analyst estimates that the interest coverage ratio for U.S. companies would drop from 4 to 2½ if interest rates were to increase by 100 basis points across the corporate curve.4 This would take the coverage ratio to the lowest level in the 30-year history of our sample (Chart 8). Consumer staples, tech, and health care would be the most affected. Chart 8U.S. Interest Coverage Ratio##BR##Breakdown By Sector (I) Chart 8U.S. Interest Coverage Ratio##BR##Breakdown By Sector (II) We currently maintain an overweight to equities and spread product but expect to move to neutral later this year and to underweight sometime in 2019. Long-term investors should consider paring back exposure to both asset classes already, given that valuations have become stretched. The Dollar And The Return Of "Twin Deficits" Bigger budget deficits will drain national savings. Since the current account balance is simply the difference between what a country saves and what it invests, the U.S. current account deficit is likely to increase. How the emergence of these twin deficits will affect the dollar is a tough call. Historically, there is no clear relationship between the sum of the fiscal and current account balance and the value of the trade-weighted dollar (Chart 9). In the early 1980s, the twin deficits exploded on the back of the Reagan tax cuts and the military buildup, but the dollar strengthened. In contrast, the dollar weakened in the early 2000s, a period when the twin deficits rose in response to the Bush tax cuts, the Iraq War, and a decline in the household saving rate from the booming housing market. Much depends on what happens to real interest rates. If investors come to believe that persistently large budget deficits will lead to higher inflation, long-term real yields could decline, pushing the dollar lower. In contrast, if investors conclude that the Fed will raise rates by enough to keep inflation from spiraling upwards, real yields could rise. U.S. real yields have gone up across all maturities since the start of the year. As a result, real rate differentials have widened between the U.S. and its developed market peers (Chart 10). However, some of the increase in U.S. real rates has been due to a rising term premium, with the rest reflecting an upward revision to the expected path of policy rates. The latter is good for the dollar. The former is not, because it means that investors are starting to worry about the ability of the market to absorb the increasing supply of Treasurys. Meanwhile, rising interest rates threaten to put further pressure on the U.S. current account deficit. The U.S. net international investment position has deteriorated from -10% of GDP to -40% of GDP since 2007 (Chart 11). The U.S. owes the rest of the world about 68% of GDP in debt - almost all of which is denominated in dollars - but holds only 23% of GDP in foreign debt. Thus, a synchronized increase in global bond yields would cause U.S. net interest payments to rise. If yields in the U.S. increase more than elsewhere, net payments would rise even more. Chart 9Twin Deficits And The Dollar:##BR##No Clear-Cut Relationship Chart 10Real Rate Differentials Have##BR##Widened Between The U.S. And Its DM Peers Chart 11Deterioration In U.S. Net##BR##International Investment Position America's status as a major net external debtor could also constrain the extent to which the dollar appreciates. If the greenback were to strengthen, the dollar value of U.S. external assets would decline, as would the dollar value of interest or dividend payments that the U.S. receives from abroad. This would result in a deterioration in the current account balance and in a worsening in the U.S. net international investment position. Some Positives For The Greenback While the discussion above is bearish for the dollar, it needs to be put into some context. The U.S. current account deficit stands at 2.3% of GDP, down from almost 6% of GDP in 2006 (Chart 12). Much of the improvement in the U.S. balance of payments can be traced back to the plunge of almost 70% in net oil imports, a development that is likely to be permanent given the shale boom. Furthermore, the U.S. trade balance should benefit over the coming quarters from the lagged effects of a weaker dollar. And while we estimate that the primary income balance will deteriorate by about 0.6% of GDP over the next two years, it should still remain in positive territory and above the levels from a decade ago (Chart 13). Chart 12U.S. Balance Of Payments:##BR##Improvement Due To Sinking Oil Imports Chart 13Primary Income Balance Will Decline,##BR##But Will Remain In Positive Territory On the fiscal side, the projected rise in U.S. government debt levels at a time when the economy is booming is concerning. Nevertheless, the U.S. debt profile still compares favorably to countries such as Japan and Italy, two economies with worse growth prospects than the U.S. Italian 30-year bond yields are actually lower than in the United States. If one of the two countries is going to have a debt crisis over the next decade, our guess is that it will be Italy and not the U.S. A Cresting In Global Growth Could Help The Dollar Our preferred explanation for why the dollar began to weaken in 2017 focuses on the role of global growth as well as on technical factors. Chart 14USD Is A Momentum Winner Strong global growth - especially when concentrated outside the U.S., as was the case last year - tends to hurt the dollar. There are a number of reasons for this. First, a robust global economy pushes up natural resource prices, which boosts the terms of trade for commodity-exporting economies. Second, manufacturing represents a smaller share of the U.S. economy than it does in most other countries. Since manufacturing activity is quite cyclically-sensitive, faster global growth benefits economies such as Germany, Sweden, Japan, China, and Korea more than the U.S. Third, stronger global growth tends to boost risk appetites. This has translated into large inflows into EM funds and peripheral European debt markets. The latter have also seen an ebbing of political risk, which has translated into sharply lower sovereign spreads. The acceleration in global growth came at a time when long dollar positions had reached elevated levels. As those positions were unwound, the dollar began to tumble. At that point, the strong upward momentum that fueled the dollar rally following the U.S. presidential election was replaced by downward momentum. The U.S. dollar is one of the most momentum-driven currencies out there (Chart 14). Weakness led to even more weakness. It is impossible to know when the dollar's downward momentum will exhaust itself. What can be said is that speculative positioning has become increasingly dollar bearish. This raises the odds of a short-covering dollar rally (Chart 15). Chart 15Speculative Positioning Has Gotten Increasingly Dollar Bearish Perhaps more importantly, global growth may be peaking. China's economy has slowed, as gauged by the Li Keqiang index, which combines electricity production, freight traffic, and bank lending (Chart 16). Growth in Europe and Japan has also likely reached top velocity. U.S. financial conditions have eased sharply relative to the rest of the world (Chart 17). This, in conjunction with an easier U.S. fiscal policy, suggests that the composition of global growth will shift back towards the U.S. over the coming months. If this were to happen, the dollar could recoup some its losses. Chart 16Chinese Economy##BR##Has Slowed Chart 17U.S. Financial Conditions Have##BR##Eased Sharply Relative To ROW Peter Berezin, Chief Global Strategist Global Investment Strategy peterb@bcaresearch.com 1 Please see Geopolitical Strategy Special Report, "Constraints & Preferences Of The Trump Presidency," dated November 30, 2016. 2 Please see "Getting The Policy Mix Right," IMF Global Financial Stability Report, April 2017. 3 Please see Global Investment Strategy Weekly Report, "A Structural Bear Market In Bonds," dated February 16, 2018. 4 Please see The Bank Credit Analyst, "Leverage And Sensitivity To Rising Rates: The U.S. Corporate Sector," dated February 22, 2018. Available at bca.bcaresearch.com. Tactical Global Asset Allocation Recommendations Strategy & Market Trends Tactical Trades Strategic Recommendations Closed Trades

Special Report

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 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 Slide 2 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 Slide 4 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 Slide 6 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 Slide 8 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 Slide 10 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 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 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 Slide 14 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 Slide 16 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 Slide 18 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 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

Highlights Market participants should be asking why yields are higher, and not worry about how much they have climbed. While the bond market has begun to price in higher inflation (via the move in the TIPS breakeven rate), wage and price inflation remains muted for now. Sentiment has deteriorated more than valuations or technicals as the S&P 500 climbed to fresh all-time highs in December and January. Our U.S. Equity Strategy service downgraded small caps to neutral from overweight. Feature Chart 1The January Jobs Report Keeps The Fed##BR##On Track For Gradual Hikes This Year Last week marked Janet Yellen's final FOMC meeting and the first week in many years that the U.S. Treasury and equity markets worried about inflation. The strongest year-over-year reading in average hourly earnings in 9 years (+2.9% in January) added to the market's inflation concerns (Chart 1). The 10-year Treasury yield climbed 15 bps to 2.84%, while the S&P 500 moved lower by 2.5% as of midday on Friday, February 2. It was the worst week for the stock market since September 2016. Individual investor sentiment on the equity market has surged recently, and valuations are at extremes. However, BCA's technical indicator for U.S. stocks is not at an extreme. BCA's stance is that while the risk/reward for stocks over bonds has narrowed, it is too soon to call an end to the bull market. However, we are monitoring real yields closely. At 2.13% on Friday morning, February 2, the 10-year TIPS breakeven yield was still below the 2.4 to 2.5% range where markets should begin to worry about the Fed falling behind the curve. While the acceleration in average hourly earnings in January cements the case for continued gradual Fed rate hikes this year, inflation is not about to spiral higher. Wage inflation remains muted, and patience is still required as market participants await signs of a pickup in broader measures of consumer price inflation. The market is now fully priced for three rate hikes this year. Also, longer-term rate expectations have moved close to the Fed's estimate of the terminal rate. It would be reasonable to expect some short-term pause to recent near-relentless uptrend in rate expectations. For the market to price tightening beyond the Fed's dots, the economy and inflation would need to outperform the Fed's forecasts (which are 2.5% GDP growth, 1.9% core inflation and 3.9% unemployment for 2018). For now at least, it's not clear that is the case. Why Rates Are Rising Matters The relentless increase in 10-year Treasury yields spooked investors early last week, but it is too soon for equity investors to worry about an overly aggressive Fed. At 2.84%, the 10-year Treasury yield is above the FOMC's view of the neutral Fed funds rate, and has moved nearly 80 bps higher since early September. Market participants should be asking why yields are higher, and not worry about how much they have climbed. Chart 2Breaking Down The Rise In Yields BCA's U.S. Bond Strategy service noted in mid-January1 that in the current environment, it is useful to split the nominal 10-year yield into its two main components - the compensation for inflation protection and the real yield (Chart 2). The 10-year TIPS breakeven inflation rate has moved from 1.66% last June to 2.13% late last week, but is still too low. Historically, the 10-year TIPS breakeven rate has traded in a range between 2.4 and 2.5% when inflation is well-anchored near the Fed's 2% target. BCA's stance is that inflation will move back to the Fed's target soon. The implication is that there is still another 25 to 35 bps of upside in the 10-year breakeven rate. The reason why this threshold is important is because a rise in inflation expectations to that level would be a signal that the FOMC will need to become more aggressive in slowing economic growth. This could occur even if actual inflation is below the 2% target, as long as it is rising toward the target. This will be especially true if the unemployment rate is heading to 3.5%, as we suspect. BCA's U.S. Bond strategists' model of real yields2 projects that real yields will rise 4 bps by the end of the year to 0.61%, but it could be more depending on how quickly the Fed wants to slow growth. Bottom Line: BCA expects that the nominal Treasury yield should move into a range between 3.0 and 3.25% by the time inflation reaches the Fed's target. BCA's stance is that risk assets will get into trouble once inflation expectations rise above 2.4%. Bond yields will presumably be moving higher along with inflation expectations. However, investors should not ignore higher Treasury yields rates. That said, equity investors do not need to be too concerned until inflation expectations hit that 2.4% threshold. Inflation itself may not be at 2% as this occurs, but if inflation is climbing and the unemployment rate is still falling, then the market will believe that the Fed is behind the curve. That is a bearish environment for equities. Inflation: Still A Waiting Game While the bond market has begun to price in higher inflation (via the move in the TIPS breakeven rate), wage and price inflation remains muted for now. Chart 3 illustrates various measures of wage inflation. Panel 1 shows that the Employment Cost Index (ECI) is in a clear uptrend. The acceleration in the wages and salaries component of ECI is broad-based across geography and industry (Chart 4, panel 1). Moreover, at 86%, the percentage of states reporting unemployment rates below NAIRU suggests that wage gains are imminent (Chart 4, panels 2 and 3). Chart 3Most Wage Metrics Are Rolling Over Chart 4The Employment Cost Index Is In A Definitive Uptrend... Although the year-over-year increase in average hourly earnings accelerated to 2.9% in January, many other wage indicators have stalled out recently (Chart 3, panel 4). The Atlanta Fed Wage Tracker rolled over recently along with weekly usual earnings (Chart 3, panels 2 and 3). In short, despite a robust global economy, a U.S. economy running above its long term potential and the unemployment rate (4.1% in January) below NAIRU (4.6%), labor shortages are not yet strong enough to push up wage inflation. Chart 5Shift Towards Service Economy Led##BR##To Shift Away From Capacity Utilization That said, the historical evidence suggests that once the labor market tightens, inflation eventually does accelerate. However, wages do not always lead inflation at bottoms and may be a lagging indicator in this cycle.3 In long economic cycles (1980s and 1990s), wage inflation was a lagging indicator. BCA recommends that investors should monitor a broad range of inflation indicators. Most of these indicators show that inflation pressures are building, but only gradually. The low readings on manufacturing capacity utilization suggest low odds of a rapid acceleration in inflation. Furthermore, the shift in composition of the U.S. economy in the past three decades suggests that the metric is no longer an accurate measure of wage or price bottlenecks in the economy (Chart 5, panels 1 and 2). Manufacturing capacity utilization hit a post WWII low in mid-2009 at 63.5%, before recovering to a well below average 75%-76% range for the past half-decade. In December 2017, utilization hit a 9-year high at 77%. Chart 5, (panels 3 and 4) shows that prior to 1980, inflation accelerated and the output gap closed as utilization breached 80%. Since early 1990s, the relationship is not as clear. Is 5% The Magic Number On Rates? History suggests that rising rates are not an impediment to higher stock prices, as long as rates remain below 5%. Chart 6 is a reminder that the 10-year yield and stock prices climbed together in the 1950s. The rise in yields in the 50s primarily reflected better economic growth rather than fears of inflation. Nonetheless, investors are concerned that a rise in yields will flip the positive correlation between bond yields and stock prices. Table 1 shows that since 1980, long treasury yields and stock prices move in the same direction until the 10-year moves above 5%. Chart 7 shows the relationship between the level of nominal bond yields and stock to bond yield correlations back to 1874. Moreover, since 1980, a move from 2 to 3% on the 10-year is accompanied by an average gain for the S&P 500 of 1.2%, with a median move of 1.8%. On average, the S&P 500 posts a modest decline (24 bps) as the 10-year Treasury elevates from 3 to 4%, but the median return (98 bps) is still positive. Our July 2016 Special Report provides an in-depth discussion of the impact of rates and inflation on equity prices. Historically, even the move from 4 to 5% on the 10-year is not an impediment to higher stock prices.4 Moreover, in a 2016 report our Global ETF Strategy service provides a detailed overview of equity returns in various phases of the Fed cycle.5 Chart 6Stock Can Rise##BR##With Bond Yields Table 13-Year Correlation* Between Stock Prices##BR##And Bond Yield Level (1980-2018) BCA's stance is that the stock-to-bond ratio will climb this year. However, the risk/reward embedded in that stance has shifted given the move in both bond yields and stock prices in the past few months. Our U.S. bond strategists peg fair value for the 10-year Treasury yield at 3.0%, just 18 bps above the yield last Friday morning. Chart 8 illustrates this point across three time horizons given our view of fair value on the 10-year Treasury yield (3.0%). Our analysis assumes a 1.75% annualized dividend yield on the S&P 500. Panel 1 illustrates that the ratio between now and mid-year will remain positive if stocks are flat. The same holds true though September 2018 and year end. Just a 5% drop in the S&P 500 by year-end 2018 signals a localized peak in the stock-to-bond ratio. Declines of 10 or 20% indicate a reversal of the uptrend in stocks versus bonds that has been in place since early 2016. Chart 7Stock To Bond Correlations Remain Positive With Nominal Yields Below 4.25% Chart 8Scenarios For Stock-To-Bond Ratio Bottom Line: BCA's view is that Treasury yields will top out at around 3 to 3.25% in this cycle, as inflation returns to the Fed's 2% target. Our base case is that stocks will do well in 2018, and will not be subject to concerns over an aggressive Fed until 2019. However, investors should closely monitor the 10-year TIPs spread, as noted above. We do not expect to breech 2.4% this year, but the timing is unclear. Moreover, we may take profits on our overweight stance well before the market senses the Fed is behind the curve, earlier than that, especially given stretched valuation and stretched market sentiment. Seismic Sentiment Shift Rising rates are not the only concern for U.S. equities. In late November, we noted6 that our technical and sentiment indicators are not flashing red as in previous bear markets, but neither are they giving an all-clear for U.S. equity investors. Sentiment levels are a bigger concern than technical indicators, and investors should monitor both for signs of an equity sell-off. These indicators have become even more stretched since we highlighted them in November and more clearly since the most recent equity market lull in late August 2017. BCA's technical indicator deteriorated since our late November report, but remains below levels that, in the past, have preceded bear markets (Chart 9, panel 1). The S&P 500 is testing the top end of the recovery trend channel in place since 2009 (Panel 2). A break above that level suggests more upside to stocks. However, a definitive failure to breakout may signal a period of consolidation for equities. BCA's equity valuation metric pushed further into extreme overvalued territory. Stretched valuations say more about medium- and long-term returns than near-term performance.7 However, the shift in the equity sentiment indicators we track is notable. BCA's investor sentiment composite index is at an all-time high (Chart 10, panel 1). Moreover, the surge in sentiment is led by individual investors and advisors who serve them (panels 2 and 4). Traders are a bit more complacent. Furthermore, individuals' optimism toward stocks is at an all-time high in surveys conducted by the Conference Board and the University of Michigan (Chart 11, panels 1 and 2). Chart 9Technical Picture For##BR##Equities Still Looks OK Chart 10Investor Sentiment##BR##Is Flashing Red Chart 11Surge In Consumer Optimism##BR##Toward Year Ahead Returns For Equities A similar survey from Yale University suggests that consumers' expectations about future equity market returns remains subdued. However, this may be due to the fact that the Yale survey is only available to December, and thus misses the equity 'melt up' in January that followed the news of the U.S. tax cuts. The other surveys mentioned are up to January. Notably, the Yale panel includes wealthy individual investors and a sample of institutions. The respondents in the Michigan and Conference Board surveys are more representative of the average U.S. household. Despite elevated attitudes toward equities, readings from the Fed's Flow of Funds on household ownership of stocks suggest that individuals may still have room in their portfolios for equities. Chart 12 shows that as of Q3 2017, equity holdings as a share of total household financial assets remains below prior peaks. As the U.S. stock market soared in the late 1990s, equities accounted for 31% of assets at the peak. Just before the global financial crisis, the figure was 23%. Today, equities account for just 25% of households' financial portfolios. The bottom panel of Chart 12 illustrates that individuals have allocated away from debt securities in the past half-decade. Chart 12Household Holdings Of Equities Still Below Prior Peaks Bottom Line: Sentiment has deteriorated more than valuations or technicals as the S&P 500 climbed to fresh all-time highs in December and January. While we are sticking with our stance that stocks will beat bonds in 2018, we are concerned about small caps. BCA's U.S. Equity Strategy service notes8 that rising interest rates and a flattening yield curve, coupled with increasing relative indebtedness and lack of relative profit growth, signal that the time is right to shift from overweight to neutral on U.S. small caps. John Canally, CFA, Senior Vice President U.S. Investment Strategy johnc@bcaresearch.com 1 Please see BCA Research's U.S. Bond Strategy Weekly Report "The Long And Short Of It", published January 23, 2018. Available at usbs.bcaresearch.com. 2 Please see BCA Research's U.S. Bond Strategy Weekly Report "Ill Placed Trust?", published December 19, 2017. Available at usbs.bcaresearch.com. 3 Please see BCA Research's The Bank Credit Analyst "Monthly Report", published September 2017. Available at bca.bcaresearch.com. 4 Please see BCA Research's U.S. Investment Strategy Special Report "Stock-To-Bond Correlation: When Will Good News Be Bad News?", published July 6, 2015. Available at usis.bcaresearch.com. 5 Please see BCA Research's Global ETF Strategy Special Report "Equity Factors And The Fed Funds Rate Cycle", published December 21, 2016. Available at getf.bcaresearch.com. 6 Please see BCA Research's U.S. Investment Strategy Weekly Report "Technically Speaking", published November 27, 2017. Available at usis.bcaresearch.com. 7 Please see BCA Research's Global Asset Allocation Special Report "What Returns Can You Expect?", published November 15, 2017. Available at gaa.bcaresearch.com. 8 Please see BCA Research's U.S. Equity Strategy Weekly Report "Too Good To Be True?", published January 22 , 2018. Available at uses.bcaresearch.com.

Special Report

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 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 Chart 3Global Robot Usage By Industry (2016) 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) Chart 5Stock Of Robots By Country (II) (2016) 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 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 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 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 Chart 10U.S.: Unit Labor Costs Vs. Robot Density 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 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 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 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 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 Chart 16Japan: 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.

Special Report

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 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 Chart II-3Global Robot Usage By Industry (2016) 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) Chart II-5Stock Of Robots By Country (II) (2016) 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 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 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 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 Chart II-10U.S.: Unit Labor Costs Vs. Robot Density 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 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 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 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 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 Chart II-16Japan: 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.

Dear Client, This is our final publication for the year. We will be back on January 5th. On behalf of the entire Global Investment Strategy team, I would like to wish you a Merry Christmas, Happy Holidays, and a Prosperous New Year! Best regards, Peter Berezin, Chief Global Strategist Highlights Global bonds have sold off in recent days, but the spread between long-term and short-term Treasury yields remains well below where it was at the start of the year. A flatter Treasury yield curve suggests that the ongoing U.S. business-cycle expansion is getting long in the tooth. Nevertheless, three factors dilute the potentially bearish message from the curve. First, the yield curve has flattened largely because short-term rate expectations have risen thanks to better economic data. Second, both the 10-year/2-year and 10-year/3-month spreads are still above levels that have foreshadowed poor returns for risk assets in the past. This is particularly true for equities. Third, a structurally low term premium has distorted the signal from the yield curve. The U.S. yield curve is likely to steepen over the next six months, before flattening again in the lead-up to a recession in late-2019. We reveal the One Number that will kill bitcoin. Feature A Harbinger Of Recession? The U.S. yield curve has steepened in recent days, but is still much flatter than it was at the start of the year. The 10-year/3-month spread currently stands at 113 bps, down 84 bps year-to-date. The 10-year/2-year spread has fallen from 125 bps to 62 bps. Numerous academic studies have highlighted the importance of the yield curve as a leading indicator of recessions.1 In fact, every U.S. recession over the past 50 years has been preceded by an inverted yield curve (Chart 1). Chart 1An Inverted Yield Curve Has Often Been A Harbinger Of A Recession The converse has generally been true as well: Most inversions in the yield curve have coincided with a recession. The only two exceptions were in 1967 - when credit conditions tightened and industrial production decelerated, but the U.S. still managed to avoid succumbing to a recession - and in 1998, when the yield curve briefly inverted during the LTCM crisis. Considering that recessions and equity bear markets typically overlap (Chart 2), it is not surprising that investors have begun to fret about what a flatter yield curve may mean for their portfolios. Chart 2Recessions And Bear Markets Usually Overlap Don't Worry... Yet Chart 3U.S. Growth Expectations Revised Higher We would not be as dismissive of a flatter yield curve as Fed Chair Yellen was during her December press conference. Policymakers and investors alike have been too quick to downplay the signal from the yield curve in the past. In 2006, they blamed the "global savings glut" for dragging down long-term yields. In 2000, they argued that the federal government's budget surplus was reducing the supply of long-term bonds. In both cases, the bond market turned out to be seeing something more ominous than they were. That said, there are three reasons why we would discount some of the more bearish interpretations of what a flatter yield curve is telling us. First, the flattening of the yield curve has occurred mainly because of an increase in short-term rate expectations, rather than a decrease in long-term bond yields. The increase in rate expectations has been largely driven by stronger growth data. The economic surprise index has surged far into positive territory and analysts are now scrambling to revise up their 2018 and 2019 U.S. GDP growth projections (Chart 3). The Fed now sees growth of 2.5% in 2018 and an unemployment rate of 3.9% by the end of next year. Back in September, the Fed expected growth of 2.1% and an unemployment rate of 4.1%. Second, our research suggests that the slope of the yield curve only becomes worrisome for the economy when it falls to extremely low levels. This conclusion is reinforced by the New York Fed's Yield Curve Recession Model, which uses the difference between 10-year and 3-month Treasury rates to estimate the probability of a U.S. recession twelve months ahead.2 The model's current recession probability stands at a modest 11% (Chart 4). The last three recessions all began when the implied probability was over 25%. Chart 4NY Fed's Yield Curve Model Suggests That The Probability Of A Recession Is Still Quite Low Third, the slope of the yield curve is weighed down by a structurally low term premium. The term premium measures the additional return investors can expect to receive by locking in their money in a 10-year Treasury note instead of rolling over a short-term Treasury bill for an entire decade. Historically, the term premium has been positive. Over the past few years, however, it has often been negative - meaning that investors have been willing to pay a premium to take on duration risk. Many commentators have attributed this peculiar state of affairs to central bank asset purchases, which they claim have artificially depressed long-term bond yields. There is some truth to this, but we think there is an even more important reason: Bonds today provide a good hedge against bad economic news. When fears of an economic slowdown mount, equities tend to sell off, while bond prices rise. This differs from the circumstances that existed in the 1970s and 1980s, when bad economic news usually meant higher inflation. To the extent that long-term bonds now serve as insurance policies against recessions, investors are more willing to accept the lower yields that they offer. Empirically, one can see this in the shift of the correlation between equity returns and bond yields. It was strongly negative up until the mid-1990s. Now it is strongly positive (Chart 5). A low term premium implies that the slope of the yield curve should be structurally flatter. That is exactly what we see today. Chart 6 shows that the 10-year/3-month spread would be well above its long-term average if the term premium were removed from the picture. This implies that investors have little to fear from the shape of today's yield curve, at least over the next six-to-twelve months. Chart 5Bond Prices Now Tend To Rise When Equity Prices Go Down Chart 6Stripping Out The Term Premium,##BR##The Yield Curve Is Not So Flat Rising Odds Of A Recession In Late-2019 Beyond then, things start to get dicey. The Fed's end-2018 unemployment rate projection of 3.9% is 0.7 percentage points below its long-term estimate of the unemployment rate. This means that at some point in the future, the Fed will need to lift interest rates above their "neutral" level in order to push the unemployment rate up to its equilibrium level. That's a risky gambit. There has never been a case in the post-war era where the unemployment rate has risen by more than one-third of a percentage point without a recession ensuing (Chart 7). Modern economies are subject to feedback loops. Once economic conditions begin to deteriorate, households cut back on spending. This leads to less hiring and even less spending. Bad economic news begets worse news. Chart 7Even A Small Uptick In The Unemployment Rate Is Bad News For The Business Cycle Implications For Equities And Credit A flatter Treasury yield curve suggests that the U.S. business cycle is entering the home stretch. Nevertheless, as we pointed out two weeks ago, the 7th-to-8th innings of business-cycle expansions are often the juiciest for equity investors (Table 1).3 Table 1Too Soon To Get Out Chart 8 shows that the term spread today is still at levels that have signaled positive equity returns in the past. In fact, today's term spread is close to levels that prevailed in the second half of the 1990s, a period that coincided with the greatest bull market in American history. This message is echoed by our forthcoming MacroQuant model, which continues to flag upside risks for stocks over the next 6-to-12 months (Chart 9). Chart 8Current Term Spread Is Still Pointing##BR##To Positive Equity Returns Chart 9MacroQuant Still Positive##BR##On The Stock Market Globally, we favor euro area and Japanese equities (in local-currency terms) in the developed market sphere due to our expectation that the euro and yen will depreciate somewhat next year. Both the euro area and Japan also have greater exposure to cyclical sectors. This fits with our bias towards owning cyclicals over defensive stocks. Today's term spread is a bit more worrying for corporate credit. As our bond strategists have noted, a flatter yield curve is consistent with lower, though still positive, monthly excess returns for high-yield bonds (Chart 10).4 Again, the second half of the 1990s provides a potentially useful template: Despite a sizzling stock market, high-yield spreads actually widened as corporations loaded up on debt (Chart 11). The deterioration in our Corporate Health Monitor over the past five years suggests that a similar dynamic may be afoot (Chart 12). Chart 10Junk Monthly Excess Returns##BR##And The Yield Curve Chart 11Second Half Of 1990s: When High-Yield Spreads##BR##Rose With Stock Prices Chart 12Corporate Health Has##BR##Been Deteriorating Yield Curve Should Steepen Over The Coming Months Of course, much depends on what happens to the yield curve going forward. We suspect that it will flatten again towards the end of next year. However, it is likely to steepen over the next six months. U.S. GDP growth will remain above trend next year, as wages start to rise more briskly and firms boost capital spending to meet rising demand for their products. Fiscal policy should also help. Tax cuts will lift growth by 0.2%-to-0.3% in 2018. Higher disaster relief efforts following the hurricanes and a pending agreement to raise caps on discretionary spending will also translate into increased federal government spending. Investors have largely overlooked this source of fiscal stimulus, but increased spending will contribute almost as much to growth next year as lower taxes. Unfortunately, all this additional growth, coming at a time when the output gap is all but closed, is likely to stoke inflationary pressures. Our Pipeline Inflation Pressure Index has risen sharply since early 2016, while the ISM prices paid index has shot up. The New York Fed's Underlying Inflation Gauge has accelerated to an 11-year high of 3% (Chart 13). Historically, rising inflation expectations have led to a steeper yield curve (Chart 14). The implication is that investors should favor inflation-linked securities over government bonds. Chart 13U.S. Inflation Pressure Are Building Chart 14Rising Inflation Expectations Lead To A Steeper Yield Curve The One Number That Will Kill Bitcoin In a normal world, most reasonable people would regard a flatter yield curve and continued weak inflation readings as evidence that fiat money was, if anything, doing too good a job as a store of value. However, nothing is normal or reasonable about bitcoin.5 Chart 15Governments Will Want Their Cut:##BR##U.S. Seigniorage Revenue No one knows when the bitcoin bubble will burst. Only a tiny fraction of the public owns the virtual currency. The value of all bitcoin in circulation represents 0.35% of global GDP. At its peak in 1996, the value of all pyramid scheme assets in Albania amounted to almost half of GDP. Never underestimate the lure of easy money. While we do not know where the price of bitcoin will be ten months from now, we do have a good guess of where it will be ten years from today. And that price is zero, or thereabouts. When the U.S. Treasury issues a $100 bill, it gains the ability to buy $100 of goods and services with it. The government's cost is whatever it pays to print the bill, which is next to nothing. This so-called "seigniorage revenue" is set to reach $100 billion this year (Chart 15). That is the number that will kill bitcoin. There is no way the U.S. government will forsake this revenue in order to make room for bitcoin and other cryptocurrencies. Not when there are entitlements to pay and gaping budget deficits to finance. A variety of other countries have a love-hate relationship with bitcoin, partly because of their "the enemy of my enemy is my friend" attitude towards the dollar. But that will change when they see their tax bases eroding as more commerce gets done in the anonymous world of cryptocurrencies. Bitcoin's days are numbered. The only question is who will be holding the bag when the party ends. Peter Berezin, Chief Global Strategist peterb@bcaresearch.com 1 Please see Jonathan H. Wright, "The Yield Curve And Predicting Recessions," FEDs Working Paper No. 2006-7, May 3, 2006; Michael Owyang, "Is the Yield Curve Signaling a Recession?"Federal Reserve Bank Of St. Louis, March 24, 2016; and Arturo Estrella and Mishkin, Frederic S., "The Yield Curve as a Predictor of U.S. Recessions," Federal Reserve Bank Of New York, (2:7), June 1996. 2 Please see "The Yield Curve As A Leading Indicator: Probability of U.S. Recession Charts," Federal Reserve Bank Of New York. 3 Please see Global Investment Strategy Weekly Report, "When To Get Out," dated December 8, 2017. 4 Please see U.S. Bond Strategy, "Proactive, Reactive Or Right?" dated December 12, 2017. 5 Please see European Investment Strategy Weekly Report, "Bitcoins And Fractals," dated December 21, 2017; Technology Sector Strategy Special Report, "Cyber Currencies: Actual Currencies Or Just Speculative Assets?" dated December 12, 2017; Global Investment Strategy Special Report, "Bitcoin's Macro Impact," dated September 15, 2017; and Technology Sector Strategy Special Report, "Blockchain And Cryptocurrencies," dated May 5, 2017. Tactical Global Asset Allocation Recommendations Strategy & Market Trends Tactical Trades Strategic Recommendations Closed Trades

Watching The Warning Signals Recommended Allocation Two of the three indicators we have focused on all year as reliable signals of recession (and, therefore, of the timing for reducing exposure to risk assets) have wobbled in the past month. But, for now, we are not too concerned about this, and continue to argue that the current bull market has maybe another year to run, until a possible 2019 recession starts to get priced in. Global growth indicators are showing no signs of slowdown, with the Global Manufacturing PMI at 53.5, and 26 of the 29 markets for which Markit runs its survey returning a PMI above 50 - close to the highest percentage on record (Chart 1). However, the flattening yield curve in the U.S. has raised concerns: the gap between the yield on two-year and 10-year Treasuries has fallen to less than 60 bps (Chart 2). But a flattening yield curve is not unusual when the Fed is tightening policy, and historically the curve has needed to invert before it became a recession signal. Also of concern was a jump in early November in high-yield spreads, which have also been a good lead indicator for recession (Chart 3). The rise was caused by poor earnings from lowly-rated telecoms companies, which triggered a sell-off in junk bond ETFs. But the rise in spreads remains insignificant, and has mostly reversed since. Chart 1Global Growth Looks Fine... Chart 2But Should We Worry About The Yield Curve... Chart 3...And Rising Credit Spreads? BCA's macro view, as laid out in detail in our recent 2018 Outlook,1 is that the strong growth that has been a positive for risk assets this year will slowly become a negative next year as it is increasingly accompanied by rising inflation. Two-thirds of countries globally now have unemployment below the NAIRU (Chart 4). In the U.S., employment has reached a level at which the Philips Curve has historically been "kinky", associated with an acceleration in wage growth (Chart 5). Upside surprises in inflation will mean that the Fed will hike three or four times next year (compared to the market's expectation of only 1½ hikes), 10-year bond yields will rise to above 3%, and the dollar will appreciate. Chart 4Unemployment Is Below Nairu In Most Places Chart 5The 'Kinky' U.S. Philips Curve What are the implications of this scenario for portfolio construction? We continue to recommend an overweight on risk assets on the 12-month time horizon, as we would expect equities to outperform bonds until Fed policy tightens above the neutral level (which is still about five rate hikes away, as long as core PCE inflation picks up to 2%, as we expect - Chart 6). However, the risks to this scenario are rising. The Fed could stubbornly push ahead with rate hikes even if inflation remains subdued. Chinese growth could slow if the authorities misjudge the timing of structural reforms. Our geopolitical strategists argue that, while investors overestimated political risks at the start of 2017, now they are underestimating the risks (North Korea, NAFTA renegotiation, China trade issues, Italian elections).2 With valuations stretched, small shocks could trigger a disproportionate negative market reaction. More risk-averse investors, therefore, might choose to reduce exposure now, at the risk of leaving some money on the table. Equities: If global equities have further upside, as we believe, higher beta markets such as the euro zone (average beta to global equities over the past 20 years: 1.2) and Japan (beta: 0.9) are likely to continue to outperform. Both have central banks that remain accommodative, our models suggest further upside for earnings growth into next year (Chart 7), and valuations are less stretched than in the U.S. While EM equities are also high beta, we think they are likely to lag next year: higher U.S. interest rates, a stronger U.S. dollar, potential slowdown in China, and sluggish domestic demand in most major emerging economies all represent significant headwinds. Chart 6How Long Until Rates Above Neutral? Chart 7Euro and Japan Earnings Have Upside Fixed Income: A combination of higher inflation and a more aggressive Fed is not a positive environment for government bonds. We expect the yield curve to steepen over the next six months, as the market prices in higher inflation and fiscal deficits (after the U.S. tax cut), but to resume flattening mid next year, as the Fed pushes ahead with rates hikes, and worries about the risk of a policy error emerge. For now, we remain underweight duration, and prefer inflation-linked over nominal bonds. For spread product, while valuations are stretched, we see some attractiveness. As long as the global expansion continues, U.S. investment grade bonds should see a carry pickup over Treasuries of around 100 bps, and high-yield bonds one of around 250 bps (adjusting for likely defaults) - even if we don't assume further spread contraction. In a world of continuing low rates, that remains alluring. Currencies will continue to be driven by relative monetary policy. While we see the Fed tightening more than the market expects, the ECB will not raise rates until late 2019, since underlying inflationary pressures in the euro zone are much weaker. This is largely in line with what the futures market is pricing in. Interest rate differentials (and an unwind of the current large speculative long-euro positions) should cause some weakness of the euro versus the dollar. We expect the Bank of Japan to stick to its 0% target for 10-year JGBs, which means that the yen will also weaken, to below 120 to the dollar, if U.S. interest rates rise in line with our forecasts (Chart 8). Emerging market currencies have already fallen by 1.3% since early September as U.S. rates rose, and amid signs of economic weakness in some emerging economies. We expect this to continue. Chart 8Yen Is Driven By U.S. Rates Chart 9China Is What Matter For Metals Commodities: Our energy strategists recently raised their target for Brent and WTI crude to an average over the next two years of $65 and $63 respectively, with risk of upside surprises in the event of geopolitical disruptions (Venezuela, Kurdistan etc.). They see the OPEC agreement being extended possibly to December 2018, and argue that backwardation of the oil curve (futures prices lower than spot) and rising extraction costs will delay the response of shale oil producers to the higher price. The outlook for industrial commodities depends, as always, on China, which now comprises greater demand for base metals than the rest of the world put together (Chart 9). The risk of a slowdown in Chinese infrastructure spending next year makes us wary on metals such as iron ore, and markets such as Australia and Brazil. Garry Evans, Senior Vice President Global Asset Allocation garry@bcaresearch.com 1 Please see The Bank Credit Analyst Special Report, "2018 Outlook - Policy And The Markets On A Collision Course," dated 20 November 2017, available at bca.bcaresearch.com 2 Please see Geopolitical Strategy Weekly Report, "From Overstated To Understated Risks," dated 22 November 2017, available at gps.bcaresearch.com GAA Asset Allocation

Highlights The BCA earnings model shows that S&P 500 EPS growth is peaking and should decelerate through 2018. Synchronous global growth remains in place in 2017 and will persist into 2018, providing a tailwind for U.S. growth, equity markets and, ultimately, inflation. The labor market continues to tighten, which suggests that wage pressures should accelerate soon. Is another "Great Moderation" at hand? Feature Uncertainty around the GOP tax plan led to a weaker dollar last week, but U.S. equities and Treasuries were little changed. The tax plan could fail if enough Republican voters turn against it. BCA's Geopolitical Strategy team notes1 that as long as President Trump remains more popular with Republican voters than his Republican peers in Congress, he will be able to force the tax plan through both the Senate and the House. Moreover, we could even see some Democrats in the Senate supporting these tax changes. Ahead of the OPEC meeting on November 30, the weaker dollar along with the ongoing political turmoil boosted oil prices. Closer to home, corporate profits for Q3 2017 and guidance for Q4 2017 and beyond remains supportive for risk assets, although BCA expects S&P 500 earnings growth to peak in the next couple of quarters on a 4-quarter moving average basis. Global growth remains supportive for S&P 500, U.S. economic growth, and ultimately, higher inflation. Meanwhile, investors are still asking when price and wage inflation will turn higher toward the Fed's 2% forecast. BCA's answer: Be patient. In the final section of this week's report, we examine whether the recent period of low economic and financial market volatility will persist and herald a return to the Great Moderation. Q3 Earnings Season: Margins Still Expanding EPS and sales growth in Q3 ran well ahead of consensus expectations as forecasted in our October 2 preview. Moreover, the counter-trend rally in profit margins is still in place. Over 90% of companies have reported results so far, with 72% beating consensus EPS projections, just above the long-term average of 69%. Furthermore, 67% have posted Q3 revenues that topped expectations, which exceeded the long-term average of 55%. The surprise factor for year-over-year results in Q3 stands at 5% for EPS and 1% for sales. These compare favorably with the average EPS (4%) and sales (1%) in the past five years. We anticipate the secular mean-reversion of margins to re-assert itself in the S&P data, perhaps beginning early in 2018. Margins tend to peak halfway through late-cycle periods.2 Nonetheless, the results imply that Q3 will be another quarter of margin expansion. Earnings growth (Q3 2017 versus Q3 2016) is solid at 8%, and in revenues, 5%. Strength in earnings and revenues is broad based (Table 1). Earnings per share increased in Q3 2017 versus Q3 2016 in 8 of the 11 sectors. The 7.3% year-over-year drop in the financial sector is attributed to the impact of the hurricanes on the insurance and reinsurance industries. Excluding those industries, financial EPS is up by 6% from a year ago. EPS results are particularly impressive in energy (162%), and strong in technology (24%), healthcare (8%), and materials (7%). These sectors likewise experienced significant sales gains (17%, 10%, 4%, and 9%, respectively). Corporate managements are more focused on the message in Washington than on the President (Chart 1). Trump's name was mentioned only twice in the Q3 earnings calls held through November 10, doubling the total in Q2. CEOs and CFOs have cited Trump's name at least once in each earnings season since Q2 2016. The zenith in mentions occurred immediately after Trump took office in early 2017. Table 1S&P 500:##BR##Q3 2017 Results* Chart 1Managements Focused On The Message##BR##Not The Man In DC In contrast, "tax" and "reform" have appeared 13 times so far in Q3 conference calls, most often in a positive light. There were only five mentions in Q2 when investors were skeptical that a tax plan would pass this year. In the Q4 2016 reporting season following the November election, tax and reform were cited 16 times. BCA's Geopolitical Strategy service has consistently expected a tax package to pass by the end of Q1 2018.3 We are encouraged by the upward trajectory of EPS estimates for 2017 and 2018 (Chart 2). It is odd that the recent downtick in 2017 EPS is mirrored by an uptick in the 2018 projection. The divergence can be explained by the effect of the hurricanes on the financial sector's earnings in 2017 and the probable snapback in early 2018. Analysts expect 2019 EPS growth to slow from the anticipated 2018 clip, which matches BCA's view. However, unlike estimates for 2017 and 2018, we anticipate that EPS estimates for 2019 will move lower throughout 2018 and 2019, ahead of a recession in late 2019.4 Bottom Line: The BCA earnings model shows that S&P 500 EPS growth is peaking and should decelerate through 2018 to a level commensurate with 3 ½-4% nominal GDP growth (Chart 3). Margins will crest in 2018. Accordingly, BCA believes that the earnings backdrop will remain a tailwind for the equity market, albeit a smaller tailwind. This forecast excludes any encouraging effect on growth from tax cuts, which would be positive for EPS and the S&P 500 price index in the short term, but would bring forward Fed rate hikes. BCA expects growth outside the U.S. to remain robust, an additional support for EPS growth in the coming quarters. Chart 2Stability In '17 & '18 EPS Estimates, But '19 Likely To Move Lower Chart 3Strong EPS Growth Ahead,##BR##Will Start To Slow Soon Global Growth Update Synchronous global growth remains in place in 2017 and will persist into 2018,5 providing a tailwind for U.S. growth, equity markets and, ultimately, inflation. Global real GDP estimates continue to move higher, a welcome departure from the past when estimates slid relentlessly lower (Chart 4). Since the start of 2017, GDP estimates for this year have increased from 2.6% to 3.2%, while 2018 forecasts have accelerated from 2.8% to 3%. The 2019 growth projection is steady at 2.9%. This upward trajectory for 2017 and 2018 has occurred despite a recalibration by many major central banks away from accommodative policies. The improving growth forecasts could be short-circuited by aggressive central bank actions, a worldwide trade war, or escalating tensions in Northeast Asia (or a combination of all three). Falling oil prices would also challenge a quickening of world growth, but BCA's stance is that oil prices will move up significantly in the coming year.6 Chart 4Global Growth Estimates Accelerating Global leading indicators are on the upswing. The most recent update of our Global Leading Indicator (excluding the U.S.) was the strongest since 2010 when it slowed after a sharp rebound from the 2007-2009 financial crisis. Moreover, the global LEI diffusion index turned positive after a worrisome dip below 50% earlier this year. It will be a warning sign for wide-reaching growth if the diffusion index moves back below 50% (Chart 5). Industrial production (IP) overseas is expanding at nearly three times the U.S. rate (Chart 6). This suggests that U.S. economic activity will be pulled up by foreign demand. Additionally, G3 capital goods orders are climbing at the fastest pace since 2014. A stronger dollar may dampen U.S. exports and earnings, but this will be a modest offset, rather than something that derails the recovery in U.S. industrial production. Chart 5Global LEI's Pointing Higher Chart 6Supports For Global Growth In Place Global growth is important to large cap U.S. equities because 43% of S&P 500 sales in 2016 came from outside the U.S. (Table 2). Remarkably, this figure moved lower in the past 5 years and 10 years. In 2012, 47% of S&P 500 sales came from outside the U.S.; in 2007, it was only 1% less. The drop in overseas sales since 2012 masks shifts by region. In 2016, 8% of S&P 500 sales were to Asia, up 100 bps from 2012. Europe, excluding the U.K., accounted for 6% sales in 2016 and the U.K., a mere 1%. These numbers dropped from the 2012 figures of 10% and 2% respectively. While Standard and Poor's does not separate out sales to China, that country represents a large portion of sales to Asia, which makes China and Europe the two most important regions for overseas sales. In contrast, only 3% of S&P 500 sales are made in Canada and Mexico. Table 2Most S&P 500 Sales Go To Asia And Europe While BCA's European strategists remain upbeat about growth prospects in the Eurozone,7 our outlook on China is more sanguine. BCA's Geopolitical Strategy service notes that Chinese politics have shifted from tailwind to headwind for global growth in the wake of China's 19th National Party Congress.8 Meanwhile, BCA's China Investment Strategy states that the weak external demand environment faced by China in 2015 was a function of severe dislocations in the commodity and currency markets that probably will not recur in the coming 6-12 months. While Chinese export growth will moderate in the coming year, the absence of these shocks is an important factor supporting a gradual deceleration.9 Moreover, China's economic momentum is on the upswing. Real-time measures of economic activity such as electricity production, excavator sales, and railway freight traffic, all are expanding at double-digit rates, albeit down from recent peaks (Chart 7). Various price indexes also show a broadly based pickup in inflation to levels that will unnerve the authorities. Nonetheless, economic growth will slow in 2018 as policymakers continue to pare back stimulus. BCA does not foresee a substantial downturn in growth next year, but it could be hard on base metals prices. Bottom Line: Improving economic activity outside the U.S. is a tailwind for both domestic economic growth and profits of U.S. firms with significant foreign business. Moreover, surging world growth is a precondition for higher inflation. BCA's Global Fixed Income Strategy service notes10 that 68% of OECD nations have unemployment rates under the organization's assessment of "global NAIRU", which has not occurred since before the Great Recession when inflation expanded in both the goods and service sectors (Chart 8). Solid foreign demand will help the economy hit the Fed's GDP target and support the central bank's additional but gradual tightening stance. Stay overweight U.S. equities and remain short duration. BCA's view that inflation is poised to turn higher also supports our duration call. Chart 7China: Healthy Growth Indicators Chart 8NAIRU Is Not Dead Yet Still Waiting For Wage Inflation Table 3Inflation Reacts With A Lag The labor market continues to tighten, which suggests that wage pressures should accelerate soon. Given that inflation is a lagging indicator, investors must remain patient. Table 311 illustrates the time lag from when full employment is reached to the turning point for consumer price inflation. During long expansions, the gap is 26 months. The U.S. unemployment rate dipped below NAIRU 12 months ago in November 2016. The implication is that investors (and the Fed) are too eager as they wait for inflation's inflection point. BCA approaches wage growth - or the lack of it - in another way. Like inflation, wage growth takes time to materialize in protracted recoveries. Charts 9 and 10 provide updates on inflation and its leading indicators that we published in August 2017. These charts reiterate that price pressures take time to emerge in "slow burn" expansions. Chart 11 shows that the ECI has trended higher since 2009, matching increases in quit rates, NFIB compensation plans, and the Conference Board's measure of jobs hard to get less jobs easy to get. Moreover, the top panel of Chart 11 shows that the ECI gains are widespread and at 73%, the percentage of states reporting unemployment rates below NAIRU suggests that wage gains are imminent (Chart 12). Chart 9In the 80s And 90s Wage Growth Did Not##BR##Provide And Early Warning On Inflation Chart 10Patience Is Required On##BR##Inflation In Long Cycles Chart 11Labor Market Is Tight Enough##BR##To Push Up Inflation Chart 1270%+ Of States Have Unemployment Rates Below NAIRU The Atlanta Fed Wage Tracker,12 which is not compromised by compositional shifts in the labor market, stabilized in the past few months after rolling over in the spring and early summer. Moreover, the Tracker remains in a distinct uptrend; at 3.6% year-over-year, it is at the lower end of the 3.3% to 4.3% year-over-year range in place before the global financial crisis (Chart 13, panel 2). Chart 13Wage Pressures Mounting Bottom Line: Wage inflation is on the upswing as the output gap turns positive for the first time in a decade and the unemployment rate moves even further below NAIRU. A persistent buildup in wages will allow the Fed to bump up rates in December and three times again next year. This supports BCA's underweight stance on duration. That said, a sudden surge in consumer price or wage inflation would trigger a more aggressive response from the Fed, and a signal of "the beginning of the end" for the recent return of the Great Moderation. Great Moderation, Interrupted? The Great Recession was eight years ago, but investors are now ruminating about the return of the Great Moderation era (mid-1980s to mid-2007), when subdued macroeconomic volatility often coincided with low market volatility. Then, as now, inflation was muted and stable, but unlike today, economic growth was much faster in a long expansion phase with two mild recessions (Chart 14). There have been many studies rationalizing the Great Moderation, which was observed in most advanced economies (G7 countries and Australia) roughly at the same time though not fully synchronized (Chart 15).The phenomenon13 was initially forged in 2002 by Stock and Watson and then publicized by former Fed Chair Bernanke14 in a 2004 speech.15 Chart 14Return Of The Great Moderation? Chart 15The Great Moderation: A Global Phenomenon Too! Three main causes were identified: Structural changes in the economy: improvement in inventory management as the U.S. moved away from a manufacturing-based economy towards a service-based economy, the latter less volatile. Financial innovations, for example, increased credit availability to households through the rise of securitization, allowing consumption to be more balanced; Higher efficacy of monetary policy: increased transparency and predictability of FOMC actions, which augmented the Fed's credibility to tame inflation (price stability) and foster full employment; Good Luck (smaller shocks): post mid-1980s (and up to the global financial crisis-GFC), the economy did not experience outsized shocks such as the surge in oil prices in the 1960s and the 1970s. Most investors and/or economists agree that structural changes and better monetary policy were significant drivers of the decline in macroeconomic volatility. Good luck also seems to have been a factor and there is empirical research to support it. The persistence and length of the current expansion is an indication that good luck still plays a role, with investors taking on risk and becoming complacent. That said, there does not seem to be a consensus on the single most important driver of the "Great Moderation". Interestingly, complacency in the financial markets creates vulnerability at the late stage in this expansion. It has caught the Fed's attention as evidenced in the September 19-20 FOMC minutes: "Broad U.S. equity price indexes increased over the intermeeting period. One-month-ahead option-implied volatility of the S&P 500 index - the VIX - remained at historically low levels despite brief spikes associated with increased investor concerns about geopolitical tensions and political uncertainties." Since Chair Yellen took office in February 2014, this is the most direct reference about low volatility and therefore, complacency in the financial markets. Chart 16Back To Low Correlations Among Stocks The November 2017 Bank Credit Analyst Monthly Report16 discussed complacency in the context of a return of the Great Moderation. BCA believes significant complacency is signaled by the good news already discounted in equity prices, the depressed level of the VIX and the decline this year in risk asset correlations. Moreover, large institutional investors are reportedly selling volatility and thus, dampening implied volatility across asset classes. The "Great Moderation" in macro volatility is also contributing to low correlations among stocks (Chart 16). The idea is that low perceived macroeconomic volatility during the "Great Moderation" had diminished the dispersion of growth and inflation forecasts, thereby trimming the variance of interest rate projections. This allowed equity investors to focus on alpha rather than beta, given less uncertainty about the macro outlook. The focus on alpha contributed to the decline in stock price correlation. Today, dispersion in the outlooks for growth and interest rates have returned to pre-Lehman levels, helping to explain the low levels of implied volatility and correlation in the equity market (Chart 17). Some of the reduced dispersion can be justified by the fundamentals. The onset of a broadly based global expansion has calmed lingering fears that the world economy is constantly teetering on the edge of the abyss. Investor uncertainty regarding economic policy has also moderated (bottom panel). Historically, implied volatility tended to fall when global industrial production was strong and global earnings were rising in a broad swath of countries (Chart 18). Our U.S. Equity Sector Strategy service points out that, during the later stages of the cycle, equity sector correlations tend to drop. The lower correlations occur as earnings fundamentals become more important performance drivers, and sector differentiation generates alpha.17 Similarly, the VIX can fluctuate at low levels for an extended time when global growth is broadly based. Chart 17A Less Uncertain Macro Outlook? Chart 18Broad-Based Growth Lowers Implied Volatility Still, the current readings of equity market correlation and the VIX are unnerving given a plethora of potential geopolitical crises and the pending unwinding of the Fed's balance sheet. Moreover, any meaningful pickup in inflation would upset the 'low vol' applecart. Table 4 shows the drop in the S&P 500 index during non-recessionary periods when the VIX surges by more than 10% in a 13-week period. The equity price index fell by an average of 7% during those nine episodes, with a range of -3.6 to -18.1%. Table 4Episodes When VIX Spiked Bottom Line: Longer expansions and shorter recessions, alongside the decline in market volatility, may stay for a while, the result of the perceived return to the Great Moderation. Risk assets are thus vulnerable because a lot of good news is discounted. Nonetheless, we would view any pullback in equities as a healthy correction rather than the beginning of a bear market. If the next recession is not expected before 2019 (our base case), then it is too early for the equity market to begin to discount the next bear market because profits will continue to expand well into 2018. Stay overweight stocks versus bonds in the next 12 months. John Canally, CFA, Senior Vice President U.S. Investment Strategy johnc@bcaresearch.com Mark McClellan, Senior Vice President The Bank Credit Analyst markm@bcaresearch.com Jizel Georges, Senior Analyst jizelg@bcaresearch.com 1 Please see BCA Research's Geopolitical Strategy Weekly Report, "Tax Cuts Are Here... So Much for Populism," November 8, 2017. Available at gps.bcaresearch.com. 2 Please see BCA Research's U.S. Investment Strategy Weekly Report, "The Late Cycle View," October 16, 2017. Available at usis.bcaresearch.com. 3 Please see BCA Research's Geopolitical Strategy Weekly Report, "Xi Jinping: Chairman Of Everything," October 25, 2017. Available at gps.bcaresearch.com. 4 Please see BCA Research's Global Investment Strategy Weekly Report, "Strategy Outlook Fourth Quarter 2017: Goldilocks And The Recession Bear," October 4, 2017. Available at gis.bcaresearch.com. 5 Please see BCA Research's U.S. Investment Strategy Weekly Report, "Synchronicity," September 25, 2017. Available at usis.bcaresearch.com. 6 Please see BCA Research's Commodity & Energy Strategy Weekly Report, "Still Some Upside In The Nickel Market," November 2, 2017. Available at ces.bcaresearch.com. 7 Please see BCA Research's European Investment Strategy Weekly Report, "The Great Resynchronization," September 21, 2017. Available at eis.bcaresearch.com 2017. 8 Please see BCA Research's Geopolitical Strategy Special Report, "China: Party Congress Ends ... So What?," November 1, 2017. Available at gps.bcaresearch.com. 9 Please see BCA Research's China Investment Strategy Weekly Report, "China's Economy - 2015 Vs. Today (Part I): Trade," October 26, 2017. Available at cis.bcaresearch.com. 10 Please see BCA Research's Global Fixed Income Strategy Weekly Report, "Have Bond Yields Peaked For The Cycle? No," September 12, 2017. Available at gfis.bcaresearch.com. 11 Please see The Bank Credit Analyst Monthly Report, November 2017. Available at bca.bcaresearch.com. 12 https://www.frbatlanta.org/chcs/wage-growth-tracker.aspx?panel=1 13 Peter M. Summers, "What Caused the Great Moderation" Some Cross-Country Evidence", 2005, Federal Reserve Bank of Kansas City www.kansascityfed.org/ROkYZ/OcgaZ/Publicat/econrev/PDF/3q05summ.pdf 14 James H. Stock and Mark W. Watson, "Has the Business Cycle Changed? Evidence and Explanations", August 2003 https://www.kansascityfed.org/publicat/sympos/2003/pdf/Stockwatson2003.pdf 15 Governor Ben S. Bernanke, "The Great Moderation," Washington, DC, February 20, 2004, https://www.federalreserve.gov/boarddocs/speeches/2004/20040220/ 16 Please see The Bank Credit Analyst Monthly Report, November 2017. Available at bca.bcaresearch.com. 17 Please see BCA Research's U.S. Equity Strategy Weekly Report, "Later Cycle Dynamics," published October 23, 2017. Available at uses.bcaresearch.com.

Highlights The so-called 'Silver Tsunami' of retiring baby boomers will continue to be a drag on aggregate wage growth for some time. We would strongly bet against the two further rate hikes that the Bank of England has flagged for this tightening cycle. Overweight U.K. 10-year gilts versus German 10-year bunds; and underweight GBP/EUR. The global inflation mini-cycle will turn down in early 2018. Approaching the year end, use technical opportunities to trim exposure to commodities, commodity equities and commodity currencies. Feature Last week, the Bank of England pointed out that "some of the softness in recent pay outturns had related to the composition of employment, with the number of low-paid jobs growing disproportionately."1 Separately, a recent study by the Federal Reserve Bank of San Francisco described the exact same phenomenon in the United States. "The drag on wage growth reflects changes in workforce composition."2 The San Francisco Fed study highlighted two paradoxes. The first paradox is that for continuously full-time employed workers, wages are actually rising quite strongly. For the continuously employed, pay is growing close to the rate seen at the previous economic peak in 2007 (Chart I-2). Chart of the WeekThe Inflation Mini-Cycle Will Turn Down In Early 2018 Chart I-2Will The Real Wage Inflation Please Stand Up However, the entry of new and returning workers to full-time employment continues to depress aggregate wage growth - because new entrants generally earn less than workers who are leaving full-time employment. This creates the second paradox. Strong job growth can actually pull down average wages in the economy and slow the pace of aggregate wage growth. Solving The Wage Puzzle According to the San Francisco Fed, this 'composition effect' is exceptionally pronounced right now because of the large-scale exit of higher-paid baby boomers from the labour force. This has depressed aggregate wage growth by 2 percentage points, a sizeable effect relative to the normal expected wage gains. Furthermore, with so many of the baby boomer generation still approaching retirement, "the so-called Silver Tsunami will continue to be a drag on aggregate wage growth for some time." A second very important factor is at play. The current wave of technological progress is having its most disruptive impact on middle-income jobs. As we explained in Why Robots Will Kill Middle Incomes,3 "high-level reasoning - such as logic and algebra - requires very little computation, but supposedly low-level sensorimotor skills - such as mobility and perception - require vast computational resources." The upshot is that when baby boomers retire, automation and Artificial Intelligence (AI) are replacing many of the jobs that the boomers occupied in high-income and middle-income sectors such as Finance and Manufacturing, rather than opening up these formerly lucrative career paths to new entrants. Therefore, new entrants are flooding into industry sectors which AI cannot yet disrupt but which are traditionally much lower paid with limited prospects for advancement - sectors like Food Services and Drinking Places and Administrative and Support Services (Table I-1). Table I-1Which Sectors Are Creating The Most Jobs? In summary, for the continuously employed, wages are rising healthily. But for aggregate wage growth, the composition effect from retirements and new entrants is an exceptionally strong headwind. What does this mean for overall inflation? The study concludes that as long as the economy can keep its wage bill low by replacing retiring staff with AI and with lower-paid workers, "labour cost pressures for higher price inflation could remain muted for some time." Given that the next wave of AI is just about to hit us, we expect these conditions to hold true in all developed economies for at least the next five years. Solving The U.K. Productivity Puzzle Chart I-3Since The Global Financial Crisis U.K. ##br##Productivity Has Stagnated But the San Francisco Fed study does also carry a warning about a latent inflationary threat. If productivity growth is slowing, "continued increases in unit labour costs could be hiding behind low readings on measures of aggregate wage growth." This seems to be a particular worry in the U.K. Since the global financial crisis, serial disappointments in productivity growth have concerned the Bank of England (Chart I-3). However, the Bank need not worry. We would like to present a very simple explanation for the U.K.'s so-called 'productivity puzzle'. Big clues come from comparing and contrasting the economic recoveries of 1993-2000 with 2009-17. At the very beginning of the two recoveries, productivity growth evolved in the same way. But then it took drastically different paths. Through the late 1990s, productivity growth accelerated, whereas through the 2010s productivity has stagnated. Why? A plausible explanation comes from the mirror-image patterns in self-employment. At the very beginning of the two recoveries, self-employment evolved in the same way. But through the late 1990s self-employment fell by 300,000, whereas through the 2010s self-employment has increased by a million, accounting for 30% of all jobs created (Chart I-4, Chart I-5, Chart I-6, Chart I-7). Furthermore, there is a tell-tale pattern. Whenever self-employment has picked up most sharply - for example, 2011-13 and 2015 - productivity growth has taken a big hit. Chart I-41990s Recovery: ##br##Self-Employment Fell Chart I-52010s Recovery: Self-Employment ##br##Has Risen Sharply Chart I-6Compare And Contrast: ##br##The Pattern of Self-Employment... Chart I-7...And Productivity...##br##Are Mirror-Images What's going on? Contrary to popular belief, the self-employed are not innovative entrepreneurs, who might typically boost productivity. The Office for National Statistics itself has poured cold water on the increased innovation thesis, claiming that "while there has been an increase in the number of people who are self-employed there has been a reduction in the number of employees who work for the self-employed." Given that these new self-employed work for themselves with no employees of their own, the idea that they are innovative entrepreneurs is a long way from the truth. In reality, the new model army of self-employed consists of former employees in sectors like journalism, media and technology who are now freelancing. And this provides a simple explanation for the productivity puzzle. Job creation that is skewed to self-employment depresses productivity growth. The reason is that the army of self-employed have to carry out tasks in which they have no specialism, and in which they are therefore much less productive. For example, a freelance journalist must spend time managing her IT gremlins, accounts, sales pitches, and so on, rather than focussing entirely on her special skill of writing powerful news stories. This makes her much less productive as a freelancer than as an employee. However, this hit to productivity eventually abates in one of two ways: freelancers gradually become more adept at the new tasks they must undertake; or more likely, they switch back to employee jobs in which they are much more productive. Combining the messages from the first two sections, the Bank of England need not fear labour cost pressures for higher price inflation. Furthermore, with Brexit negotiations progressing at a snail's pace, U.K. based companies are getting increasingly nervous about what their future international trading relationships will look like. So we would strongly bet against the two further rate hikes that the Bank of England has flagged for this tightening cycle. The investment conclusion is to overweight U.K. 10-year gilts versus German 10-year bunds; and underweight GBP/EUR. The Inflation Mini-Cycle Will Turn Down In Early 2018 Last week, we reviewed our mini-cycle framework for the global economy. To recap, the acceleration and deceleration of global bank credit flows - as measured in the global credit impulse - exhibits a remarkably regular wave like pattern with each half-cycle lasting about 8 months. As the current mini-upswing started in May, we are likely more than half way through the mini-upswing - with an expected end around January/February 2018. At which point, the cycle will enter a mini-downswing. The mini-cycle framework is so powerful that it also perfectly explains the mini-cycles in commodity price inflation - specifically, metals - and unsurprisingly, in overall inflation too. To anybody who still doubts the existence of these remarkably regular mini-cycles, the Chart of the Week and Chart I-8 should put the doubts to rest once and for all. Chart I-8Metal Price Inflation Also Exhibits Remarkably Regular Mini-Cycles Make no mistake. The mini-cycle in commodity prices and overall inflation will turn down in early 2018. So as we approach the year end, use technical opportunities to trim exposure to commodities, commodity equities and commodity currencies. Dhaval Joshi, Senior Vice President Chief European Investment Strategist dhaval@bcaresearch.com 1 From the Monetary Policy Summary and minutes of the Monetary Policy Committee meeting ending on November 1, 2017. 2 From the SF Fed blog 'The Good News on Wage Growth' August 14. 2017. 3 Please see the European Investment Strategy Special Report 'Why Robots Will Kill Middle Incomes' August 10, 2017 available at eis.bcaresearch.com. Fractal Trading Model* The near 20% rally in Japan's Nikkei 225 since early September has taken its 65-day fractal dimension to its lower bound, suggesting a likelihood of a trend-change. So our recommended trade this week is short Nikkei 225 / long Eurostoxx50 with a profit target / stop loss set at 3%. We now have six open trades. For any investment, excessive trend following and groupthink can reach a natural point of instability, at which point the established trend is highly likely to break down with or without an external catalyst. An early warning sign is the investment's fractal dimension approaching its natural lower bound. Encouragingly, this trigger has consistently identified countertrend moves of various magnitudes across all asset classes. Chart I-9 The post-June 9, 2016 fractal trading model rules are: When the fractal dimension approaches the lower limit after an investment has been in an established trend it is a potential trigger for a liquidity-triggered trend reversal. Therefore, open a countertrend position. The profit target is a one-third reversal of the preceding 13-week move. Apply a symmetrical stop-loss. Close the position at the profit target or stop-loss. Otherwise close the position after 13 weeks. Use the position size multiple to control risk. The position size will be smaller for more risky positions. * For more details please see the European Investment Strategy Special Report "Fractals, Liquidity & A Trading Model," dated December 11, 2014, available at eis.bcaresearch.com Fractal Trading Model Recommendations Equities Bond & Interest Rates Currency & Other Positions Closed Fractal Trades Trades Closed Trades Asset Performance Currency & Bond Equity Sector Country Equity Indicators Bond Yields Chart II-1Indicators To Watch - Bond Yields Chart II-2Indicators To Watch - Bond Yields Chart II-3Indicators To Watch - Bond Yields Chart II-4Indicators To Watch - Bond Yields Interest Rate Chart II-5Indicators To Watch -##br## Interest Rate Expectations Chart II-6Indicators To Watch -##br## Interest Rate Expectations Chart II-7Indicators To Watch -##br## Interest Rate Expectations Chart II-8Indicators To Watch - ##br##Interest Rate Expectations