Macro Roundup

“…This paper describes the stylized facts characterizing periods of exceptionally large capital inflows in a sample of 70 middle- and high-income countries over the last 35 years. We identify 155 episodes of large capital inflows and find that these events are typically accompanied by an economic boom and followed by a slump. Moreover, during episodes of large capital inflows capital and labor shift out of the manufacturing sector, especially if the inflows begin during a period of low international interest rates. However, accumulating reserves during the period in which capital inflows are unusually large appears to limit the extent of labor reallocation. Larger credit booms and capital inflows during the episodes we identify increase the probability of a sudden stop occurring during or immediately after the episode. In addition, the severity of the post-inflows recession is significantly related to the extent of labor reallocation during the boom, with a stronger shift of labor out of manufacturing during the inflows episode associated with a sharper contraction in the aftermath of the episode….”

Gianluca Benigo,, Nathan Converse, and Luca Fornaro, “Large Capital Inflows, Sectoral Allocation, and Economic Performance.” International Finance Discussion Papers, 2015, https://www.federalreserve.gov/econresdata/ifdp/2015/files/ifdp1132.pdf

“…In 1980, more than 80% of the country was white, and whites accounted for about eight in ten students at Harvard, Yale, and Princeton. Today, less than 65% of the country is white, and it's non-whites who now account for a majority at all three of those institutions….”

California: 40 percent white; 38 percent Hispanic 14 percent Asian; 6.6 percent black; 13.6 percent Asian.

Texas: 45 percent white; 38 percent Hispanic; 12 percent black; 4 percent Asian.

Michigan: 76 percent white; 14.2 percent black; 4.4 percent Hispanic; 2.4 percent Asian.

How America's Top Colleges Reflect (and Massively Distort) the Country's Racial Evolution

In the last 30 years, the country has become steadily more racially diverse -- and so have many American colleges. In 1980, more than 80% of the country was white, and whites accounted for about eight in ten students at Harvard, Yale, and Princeton. Today, less than 65% of the country is white, and it's non-whites who now account for a majority at all three of those institutions.

The four graphs below compare national racial composition averages in 1980, 1990, 2000, and 2010 to six elite universities: three top-flight private schools in the northeast -- Harvard, Yale, and Princeton -- and three top-flight public schools across the country -- the University of Michigan, the University of Texas, and the University of California, Berkeley.* (University data comes from the National Center for Education Statistics. National data comes from the Census.) It is notable that the data below starts in 1980, two years after the Supreme Court ruled in Regents of the University of California vs. Baake that race could not exclude a candidate but could serve as one of many factors in college admissions.

There are any number of conclusions various people could draw from the data -- the under-representation of blacks is, of course, striking; some might say the flattening out of Asians at elite private schools suggests an unofficial quota system -- but I'll let the graphs speak for themselves. This post isn't meant to be a polemic, but rather a starting point, a primary source.

Derek Thompson, “How America’s Top Colleges Reflect (and Massively Distort) the Country’s Racial Evolution,”The Atlantic, January 23, 2013, https://www.theatlantic.com/national/archive/2013/01/how-americas-top-colleges-reflect-and-massively-distort-the-countrys-racial-evolution/267415/

“…The share of births to unwed mothers stands at 40 percent—up from 5 percent in 1960. We estimate that nearly half of births start as an unwed pregnancy, including two-thirds of first births to women under 30….Three times as many births today are from unwed pregnancies than in the early 1960s, and only 9 percent of these pregnancies are followed by a shotgun marriage—down from 43 percent in the early 1960s…..”

Scott Winship, “Love, Marriage, And The Baby Carriage: The Rise In Unwed Childbearing.” Joint Economic Committee, December 2017, https://www.lee.senate.gov/public/_cache/files/3a6e738b-305b-4553-b03b-3c71382f102c/love-marriage-and-the-baby-carriage.pdf

New paper out that characterizes top incomes in the US (everyone from Auerbach to Zucman commented on draft) paper finds the super rich earn their money. as of 2014, most income at the top is non wage income, the primary source of which is business income. these profits accrue to working-age owners of closely-held, mid-market firms in skill-intensive industries. Private business profit falls by three-quarters after owner retirement or premature death!

“…Have the idle rich replaced the working rich at the top of the U.S. income distribution? Using tax data linking 11 million firms to their owners, this paper finds that entrepreneurs who actively manage their firms are key for top income inequality. Most top income is non-wage income, a primary source of which is private business profit. These profits accrue to working-age owners of closely-held, mid-market firms in skill-intensive industries. Private business profit falls by three-quarters after owner retirement or premature death. Classifying three-quarters of private business profit as human capital income, we find that most top earners are working rich: they derive most of their income from human capital, not physical or financial capital. The human capital income of private business owners exceeds top wage income and top public equity income. Growth in private business profit is explained by both rising productivity and a rising share of value added accruing to owners….”

Smith, Matthew, Danny Yagan, Owen Zidar, and Eric Zwick. January 2019. “Capitalists in the Twenty-First Century.” National Bureau of Economic Research.https://www.nber.org/papers/w25442

Summers’ core case for Secular Stagnation (2014)

“…In my remarks today, I want to take up these issues—secular stagnation, the idea that the economy re-equilibrates; hysteresis, the shadow cast forward on economic activity by adverse cyclical developments; and the significance of the zero lower bound for the relative efficacy of monetary and fiscal policies. I shall argue three propositions. First, as the United States and other industrial economies are currently configured, simultaneous achievement of adequate growth, capacity utilization, and financial stability appears increasingly difficult. Second, this is likely to be related to a substantial decline in the equilibrium or natural real rate of interest. Third, addressing these challenges requires different policy approaches than are represented by the current conventional wisdom….”

Summers, Lawrence. February 2014. US Economic Prospects: Secular Stagnation, Hysteresis, and the Zero Lower Bound. Business Economics.http://larrysummers.com/wp-content/uploads/2014/06/NABE-speech-Lawrence-H.-Summers1.pdf

“…In the postwar era, developed economies have experienced two substantial trends in the net capital share of aggregate income: a rise during the last several decades, which is well known, and a fall of comparable magnitude that continued until the 1970s, which is less well known. Overall, the net capital share has increased since 1948, but once disaggregated this increase turns out to come entirely from the housing sector: the contribution to net capital income from all other sectors has been zero or slightly negative, as the fall and rise have offset each other.Several influential accounts of the recent rise emphasize the role of increased capital accumulation, but this view is at odds with theory and evidence: it requires empirically improbable elasticities of substitution, and it presumes a correlation between the capital-income ratio and capital share that is not visible in the data. A more limited narrative that stresses scarcity and the increased cost of housing better fits the data. These results are clarified using a new, multisector model of factor shares….”

Matthew Rognlie, 2015. “Deciphering the Fall and Rise in the Net Capital Share: Accumulation or Scarcity?” Brookings Papers on Economic Activity.https://www.brookings.edu/bpea-articles/deciphering-the-fall-and-rise-in-the-net-capital-share/

"...Most investors in technology companies squander vast sums by reacting to short-term jitters or global jolts rather than concentrating on the staying power of those emerging enterprises on the right side of history. And for the founders and chief executives of all of the current billion-dollar “unicorns” there is another abiding message.Almost all of today’s technology juggernauts formed before about 2008 required smallish amounts of capital. Google, for example, consumed only $8m before turning profitable. Maybe this means that sooner or later a new class of company will come into vogue — a rare species known as the profitable unicorn....."

The writer is chairman of Sequoia Capital and co-author with Sir Alex Ferguson of ‘Leading’. Views expressed are his own. Sequoia Capital persons hold interests in certain companies mentioned

And for the founders and chief executives of all of the current billion-dollar “unicorns” there is another abiding message. Almost all of today’s technology juggernauts formed before about 2008 required smallish amounts of capital. Google, for example, consumed only $8m before turning profitable. Maybe this means that sooner or later a new class of company will come into vogue — a rare species known as the profitable unicorn.

Most investors in technology companies squander vast sums by reacting to short-term jitters or global jolts rather than concentrating on the staying power of those emerging enterprises on the right side of history.

Finally, a note about two other themes that jump out of this listing: patience and profits.

Woe betide the management of any western technology company that underestimates the challenge posed by the vast number of emerging Chinese competitors, fuelled by an ambition and work regimen that is hard to match in Europe and the US.

Perched in a clump as the fourth, fifth and sixth most valuable technology companies of the day are Alibaba, Tencent and Baidu. This threesome is now worth $409bn — testament not just to how much China has progressed in a decade and a half but a harbinger of the next several decades as the country places increasing emphasis on spawning its own technology.

Several of today’s most valuable technology companies did not even exist in 2000. Facebook, LinkedIn and Twitter together have a collective corporate history of only 33 years. Even Google and Salesforce were barely smudges on the horizon in 2000. These companies now have a combined value of about $850bn. Beyond some of the customised systems they operate in their own datacentres, and in Google’s case, some sideline activities such as its Nexus phones and Chrome notebooks, none of these companies sully their hands with anything as taxing as hardware. They have thrived from the artful deployment of software, in particular the “cloud based” variant, and — for Facebook, LinkedIn, Twitter (and Google’s YouTube service) — organising and collating the contributions of their users.

Now a word from sunnier climes. Fifteen companies that were together worth less than $10bn in 2000 are now among the world’s 50 top technology companies as measured by market capitalisation, with a combined worth of $2.1tn. (Had Amazon been included, rather than being classified as a retailer, this number would have swollen by another $250bn). Apple, which even in 2000 was viewed as little more than a curiosity, has risen in value from $6bn to $659bn. A few themes jump out of this listing: the power of novelty, the shift towards China, the benefits of patience and the virtues of capital efficiency.

For the class of 2000, the sharpest property price declines have been in the deteriorating neighbourhoods of systems, hardware and semiconductors. This is because of the continuing decline in the cost of computing, the rise of open-source software, the move to the “cloud” and the emergence of huge datacentres where companies such as Amazon, Google and Facebook are designing their own approaches.

In 2000, Nortel sported a market value of $209bn that, like those of its classmates, had been bloated by the enthusiasm of the era; it has since gone bankrupt. While other members of this corporate bracket have avoided that ignominy, their long-term stock charts present bleak pictures. Cisco’s market value has faded from $403bn to $144bn; Intel’s from $288bn to $161bn; and EMC’s from $218bn to $51bn.

Only one, Microsoft, has a market capitalisation that is higher than in 2000. One extraordinary aspect of this meltdown is that it did not occur, as some might suspect, in the much ballyhooed dotcom wonder companies of yesteryear. Instead it was a blight that affected most of what were once considered blue-chip technology holdings.

First, the bad news. The 15 technology companies with the largest market capitalisations in 2000 have been decimated — losing about $1.35tn, or roughly 60 per cent, of their combined market value.

The San Francisco-based buyout firm Francisco Partners recently published a delicious analysis relevant to anyone wondering about what the future holds for technology stocks. It is a bulletin in which both pessimists and optimists can find hope and it offers a helpful perspective for those wondering about the current valuations of technology companies.

The fall and rise of technology juggernauts

The fall and rise of technology juggernauts

https://next.ft.com/content/6b859714-99ba-11e5-9228-87e603d47bdc

Moritz, Michael, "The fall and rise of technology juggernauts,"Financial Times, December 4, 2015. Available at:https://next.ft.com/content/6b859714-99ba-11e5-9228-87e603d47bdc

chairmen of the top VC firm in the valley

James E. Bessen, "Information Technology and Industry Concentration," Boston Univ. School of Law, Law and Economics Research Paper, June 2019, https://papers.ssrn.com/sol3/papers.cfm"...It is sometimes argued that information technology “levels the playing field” by providing inexpensive tools to small and young firms. This paper finds that much of the impact of IT may be to tilt the playing field in favor of those firms who are able to use it most effectively. The use of IT systems is strongly associated with industry concentration across a wide range of sectors.Moreover, the magnitude of the link between industry IT systems use and concentration is large enough to account for much of the recent rise in industry concentration. Instrumental variable regressions provide some support for the notion that this relationship is causal, consistent with a view that IT generates a growing gap between the most productive firms and the rest.This view is further supported by evidence that IT systems use is associated with enhanced performance of the top firms within each industry. IT systems use is associated with relatively greater plant size among the top four firms, with relatively greater revenue per employee at these firms, and with higher firm operating margins, especially for the largest firms. These findings suggest that IT contributes to a widening productivity gap between the top firms and the rest, driving an increase in industry concentration. On the other hand, the observed increases in concentration are fairly modest. There are, of course, well known examples where IT facilitates highly concentrated markets as with Amazon’s dominance in e-commerce. These cases may be described as “winner-take-all” markets. But the markets in this study show much lower levels of concentration and relatively small increases. While economies of scale or network effects might be at play in the markets studied here, it appears that there are limits to such scale effects. These are “winnertake-a-bit-more” markets. Perhaps more narrowly defined markets would be more likely to exhibit “winner-take-all” competition, but the market definitions used here from the Economic Census (at the 6-digit NAICS and higher level of aggregation) are the markets that have raised concern about growing concentration. The findings of this paper suggest that much of the recent rise in industry concentration and much of the rise in firm operating margins can be attributed to the deployment of proprietary IT systems. A general decline in competition might also play a role in rising concentration and profits, but the evidence found here regarding competition is mixed. Merger and acquisition activity seems unrelated to industry concentration and the residual time trend in operating margins is negative once intangible investments are taken into account. On the other hand, greater Federal regulation is associated with higher operating margins, although this effect is substantially smaller than the role of IT systems.Overall, the analysis here suggests that the recent overall rise in industry concentration is not mainly the result of anticompetitive activity that should worry antitrust authorities. Indeed, IT systems use appears to bring real social economic benefits in terms of greater output per worker even if it does raise industry concentration. While there may be other reasons to question antitrust policies (see, for instance, Kwoka 2012), the general rise in industry concentration does not appear to raise troubling issues for antitrust enforcement at this point by itself. However, the evidence about the role of IT in raising industry concentration does broach another concern. Why aren’t the productivity gains from IT shared more broadly beyond the top firms? Increasingly, it seems, top performing firms utilize new technologies productively while their rivals do not. Concentration appears to be rising because of “barriers to technology” if not actually barriers to entry. More research is needed to understand exactly how IT is related to the growing productivity gap. Top firms might be able to use patents and trade secrets to prevent the spread of new knowledge. Or perhaps, instead, top firms are better able to recruit and develop talented managers and workers skilled at working with the new systems. Whatever the cause, the issue is important because the slow diffusion of new technologies might be related to sluggish aggregate productivity growth (Decker et al. 2017). Also, growing disparity in firm productivity might be related to growing inter-firm wage inequality. But the policies to address these issues, whether antitrust or other, depend very much on the diagnosis...."

“…. Between-firm wage dispersion is found to be significantly and positively correlated to the overall wage dispersion across workers and its evolution over time. Most of the between-firm wage variance is driven by differences in pay across firms within sectors rather than by differences in average wages across sectors. There has been a steady increase in wage inequality, measured as the 90-10 wage ratio, driven mainly by an increased dispersion in the lower tail (50-10 ratio); the divergence of the upper tail (90-50 ratio) only happens in the service sector and only since 2005…. Similarly, we find that dispersion in productivity, whether measured as real value added per worker (labour productivity) or as multi-factor productivity (MFP), has also significantly increased in the last decade. Most of the increase is driven by within-sector productivity differentials across firms, rather than by cross-sectoral differences. Similar dynamics of increase at the bottom throughout the entire period and at the top only after 2005 are also present in the productivity data, which might point to a link between the co-evolution of wage and productivity dispersions…. Wage dispersion is linked to increasing differences between high and low productivity firms, even controlling for the sectors’ skill composition. Firm-level correlation between wages and productivity is systematically weaker at the top and at the bottom of the productivity distribution….Both globalisation, as indicated by measures of greater openness, greater import penetration and greater export intensity at the sectoral level, and digitalisation, measured by more intense use of ICT capital at the sectoral level, are associated with higher wage divergence, and tend to strengthen the link between productivity and wage dispersion within sectors and countries over time….Finally, the report provides some preliminary analysis of the impact of policies and institutions on the link between wage inequality and productivity dispersion focusing on minimum wage, employment protection legislation, trade union density, and coordination in wage setting. The results point to a positive link between higher minimum wages, unionisation, EPL, coordination in wage setting, and reduced wage inequality, but usually accompanied by a weaker link between productivity and wages, especially for more centralised wage bargaining. On the contrary, over time, the minimum wage tends to strengthen the link between productivity and wage dispersion…”

Giuseppe Berlingieri, Patrick Blanchenay, and Chiara Criscuolo, “The Great Divergence,” Organisation for Economic Co-operation and Development (OECD), May 12, 2017, http://www.oecd-ilibrary.org/science-and-technology/the-great-divergence-s_953f3853-en

"... In Europe...Nearly half of workers toil in firms with fewer than 50 employee..."

Economist Staff, "Politicians in America and Europe scramble to help small firms,"The Economist, May 2, 2020, https://www.economist.com/finance-and-economics/2020/05/02/politicians-in-america-and-europe-scramble-to-help-small-firms
Politicians in America and Europe scramble to help small firms

Randy hathcock appeared to be out of options. The time had come for the owner of h&t Truss Mill, a construction company in Arkadelphia, Arkansas, to decide how many of his 16 employees to sack. The pandemic had led to orders drying up. Then a lifeline appeared. The Paycheck Protection Programme (ppp), a scheme administered by America’s Small Business Administration, promised enough to cover two-and-a-half months of wages. It was “an answer to our prayers”, says Mr Hathcock. If he retains his staff for two years, the $161,200 loan turns into a grant.

Voters abhor bail-outs when they involve airlines and Wall Street, but seem altogether happier to provide succour to the likes of Mr Hathcock and Main Street. Politicians in America and Europe have all the more reason to help: small and medium-sized businesses (smes) have been clobbered by the pandemic, even more so than their larger peers. Fully 60% of people who worked for businesses with fewer than ten employees in America at the start of the year have since been fired, according to one study. In Britain, seven in ten firms managed by their owners say they have lost over half their revenue.

Even as the share prices of listed titans have perked up—the s&p 500 index of large American stocks is up by 31% since its nadir on March 23rd—small firms are becoming ever more uncertain about their prospects. Most have cash buffers that stretch to weeks, not years. Roughly half of American entrepreneurs do not expect business to recover within two years, according to a survey by academics at Oxford, Princeton and Yale universities (see chart 1).

Schemes like theppp should help. But rich-country bail-out schemes that were put together in a rush are experiencing sharp teething pains. As a result, lifelines that are generous on paper have been less so in practice. Aid has not reached the most distressed firms, and has been hogged by larger smes savvy enough to navigate the bail-out bureaucracy, if not by even bigger businesses (see article).

America and Europe have adopted similar strategies to preserve the fabric of their economies. First help smes cut cash outgoings quickly, for example by delaying tax deadlines or even reversing past payments. Then find ways to lend or grant cash so that companies make it through the lockdown.

In Europe, the fastest way for businesses to cut costs has been to lay off workers temporarily. Britain and all members of the European Union now have temporary-unemployment schemes that allow firms to cut staff hours, sometimes to zero. Workers receive benefits in lieu of most of their salary. When lockdowns are lifted, they will go back to their old jobs. That limits the disruption to both their livelihoods and their employers’ prospects.

Such short-time working schemes, which originated in Germany and spread continent-wide after the global financial crisis, were once the purview of big firms, says Stefano Scarpetta of the oecd, a policy adviser to rich countries. Now they have been opened to smes. The take-up has been rapid. Nearly 11m French workers, or roughly half the salaried workforce, are temporarily unemployed. In Germany, more than 700,000 firms have applied.

America has no such federal scheme (though some states have smaller programmes in place). Hence theppp. But the $349bn originally allocated to the programme ran out just 13 days after it was launched on April 3rd. On April 27th a further $310bn approved by Congress became available; the demand crashed the Small Business Administration’s systems. “It’s been all hands on deck trying to get the loans approved,” says Darrin Williams, the boss of Southern Bancorp, a Mississippi-delta lender, which helped unlock theppp riches for Mr Hathcock. Even once firms’ applications have been approved, delays in receiving the cash are common.

European countries have also looked to direct cash to small firms—and faced similar delays. In Britain, Germany and Italy, among others, the smallest firms (or self-employed workers) have received handouts reasonably promptly. Bigger smes are entitled to low-interest loans, typically covering three months of payroll. Doling these out has proved tricky.

To ensure the money did not end up going to businesses with no hope of paying it back, bankers were roped in to assess potential recipients. Governments agreed to shoulder 70-90% of potential loan losses, limiting the downside for banks. Still, lending figures have underwhelmed. In Spain after five weeks only €13.4bn ($14.6bn) out of €100bn in state guarantees earmarked for smes have been tapped. Britain managed to allocate a meagre £4.1bn ($5.1bn) by April 28th. From early May it will join Germany in offering some loans that are completely underwritten by the state. Bankers can distribute cash without having to worry about the creditworthiness of the borrower.

There will still be suspicions that the money is flowing into the wrong pockets. A study by researchers at the University of Chicago finds that smes in the bits of America where activity had fallen most were only half as likely to receiveppp funds as those in the least-disrupted places.

In Europe, finding ways to help smes is economically essential. Nearly half of workers toil in firms with fewer than 50 employees (see chart 2). But many of the most troubled companies are in Spain or Italy, which have been hit especially hard by covid-19, and where governments have little fiscal space to fund large-scale bail-outs. That imbalance has raised complaints that firms in the European Union do not really compete in a single market.

Given the rush, it is perhaps not much of a surprise that neither America’s nor Europe’s schemes have achieved all that policymakers hoped. Europe’s short-timework schemes will preserve employment—but at huge cost, and at the risk of keeping employees in jobs that ought to disappear. America is now dishing out money more decisively, but unemployment there has soared (see Free Exchange), in no small part owing to Main Street’s woes. Back in January, roughly half of all small firms had at least three employees on their books. By April, a similar share had none.

“…This paper presents direct measures of capital costs, equal to the product of the required rate of return on capital and the value of the capital stock. The capital share, equal to the ratio of capital costs and gross value added, does not offset the decline in the labor share. Instead, a large increase in the share of pure profits offsets declines in the shares of both labor and capital. Industry data show that increases in concentration are associated with declines in the labor share….”

Simcha Barkai, “Declining Labor and Capital Shares,” London Business School, 2016, https://home.uchicago.edu/~barkai/doc/BarkaiDecliningLaborCapital.pdf

great paper, in short rolling back the technological frontier is hard, and getting harder!

Moore's law is a great example, Red Queens Run....

"...The striking fact, shown in Figure 4, is that research effort has risen by a factor of18 since 1971. This increase occurs while the growth rate of chip density is more or less stable: the constant exponential growth implied byMoore’s Law has been achieved only by a massive increase in the amount of resources devoted to pushing the frontier forward. Assuming a constant growth rate for Moore’s Law, the implication is that research productivity has fallen by this same factor of 18, an average rate of 6.8 percent per year. If the null hypothesis of constant research productivity were correct, the growth rate underlying Moore’s Law should have increased by a factor of 18 as well. Instead, it was remarkably stable.Put differently, because of declining research productivity, it is around 18 times harder today to generate the exponential growth behind Moore’s Lawthan it was in 1971...We find thatresearch productivity for the aggregate U.S. economy has declined by a factor of 41 since the 1930s, an average decrease of more than 5% per year... A key assumption of many endogenous growth models is that a constant number of researchers can generate constant exponential growth. We show that this assumption corresponds to the hypothesis that the total factor productivity of the idea production function is constant, and we proceed to measure research productivity in many different contexts.Our robust finding is that research productivity is falling sharply everywhere we look.Taking the U.S. aggregate number as representative,research productivity falls in half every 13 years — ideas are getting harder and harder to find. Put differently, just to sustain constant growth in GDP per person, the U.S. must double the amount of research effort searching for new ideas every 13 years to offset the increased difficulty of finding new ideas.This analysis has implications for the growth models that economists use in our own research, like those cited in the introduction. The standard approach in recent years employs models that assume constant research productivity, in part because it is convenient and in part because the earlier literature has been interpreted as being inconclusive on the extent to which this is problematic. We believe the empirical work we have presented speaks clearly against this assumption. A first-order fact of growth empirics is that research productivity is falling sharply. Future work in the growth literature should determine how best to understand this fact. One possibility is the semi-endogenous growth models discussed in the preceding section. These models have important implications. For example, they have a “Red Queen” prediction in which we have to run faster and faster to maintain constant exponential growth. If the growth rate of research inputs were to slow, this could cause economic growth itself to slow down. It is possible that this contributes to the global slowdown in productivity growth during the past fifteen years. One way in which the overall interpretation of the evidence in this paper could be wrong is if there is indeed declining research productivity in every sector, but the entire increase in aggregate R&D occurs in making quality/productivity improvements for individual varieties. The separate idea production function for producing new varieties could then exhibit constant research productivity if in fact the research going to create new varieties is not increasing over time. While this is conceptually possible, it seems unlikely. We do not have any growth models in the literature that suggest this could occur in an equilibrium in which there is population growth. Why, despite a growing population and constant research productivity, would the equilibrium allocation feature a constant number of researchers creating new varieties? Nevertheless, this loophole is one that future research may wish to consider. Alternatively, there are other possible explanations for declining research productivity. Incumbent firms may be shifting to “defensive” R&D to protect their market position, and this could cause research productivity to decline; Dinopoulos and Syropoulos (2007) provide a model along these lines. Or perhaps declines in basic research spending (potentially related to the U.S. decline in publicly-funded research as a share of GDP) have negatively impacted overall research productivity. Clearly this would have important policy implications. That one particular aspect of endogenous growth theory should be reconsidered does not diminish the contribution of that literature. Quite the contrary. The only reason models with declining research productivity can sustain exponential growth in living standards is because of the key insight from that literature: ideas are nonrival. And if research productivitywere constant, sustained growth would actually not require that ideas be nonrival; Akcigit, Celik and Greenwood (2016b) show that fully rivalrous ideas in a model with perfect competition can generate sustained exponential growth in this case. Our paper therefore clarifies that the fundamental contribution of endogenous growth theory is not that research productivity is constant or that subsidies to research can necessarily raise growth. Rather it is that ideas are different from all other goods in that they do not get depleted when used by more and more people. Exponential growth in research leads to exponential growth in At. And because of nonrivalry, this leads to exponential growth in per capita income...."

Nicholas Bloom, Charles Jones, John Van Reenen, Michael Webb, "Are Ideas Getting Harder to Find?" National Bureau of Economic Research, 6 September 2017, http://www.nber.org/papers/w23782

“…The fall of labor’s share of GDP in the United States and many other countries in recent decades is well documented but its causes remain uncertain. Existing empirical assessments typically rely on industry or macro data, obscuring heterogeneity among firms. In this paper, we analyze micro panel data from the U.S. Economic Census since 1982 and document empirical patterns to assess a new interpretation of the fall in the labor share based on the rise of “superstar firms.” If globalization or technological changes push sales towards the most productive firms in each industry, product market concentration will rise as industries become increasingly dominated by superstar firms, which have high markups and a low labor share of value-added. We empirically assess seven predictions of this hypothesis: (i) industry sales will increasingly concentrate in a small number of firms; (ii) industries where concentration rises most will have the largest declines in the labor share; (iii) the fall in the labor share will be driven largely by reallocation rather than a fall in the unweighted mean labor share across all firms; (iv) the between-firm reallocation component of the fall in the labor share will be greatest in the sectors with the largest increases in market concentration; (v) the industries that are becoming more concentrated will exhibit faster growth of productivity; (vi) the aggregate markup will rise more than the typical firm’s markup; and (vii) these patterns should be observed not only in U.S. firms, but also internationally. We find support for all of these predictions…..”

David Autor, David Dorn, Lawrence Katz, Christina Patterson, John Van Reenen, “The Fall of the Labor Share and the Rise of Superstar Firms,“ Quarterly Journal Of Economics, October 2019, https://economics.mit.edu/files/12979

“…China’s emergence as a great economic power has induced an epochal shift in patterns of world trade. Simultaneously, it has challenged much of the received empirical wisdom about how labor markets adjust to trade shocks. Alongside the heralded consumer benefits of expanded trade are substantial adjustment costs and distributional consequences. These impacts are most visible in the local labor markets in which the industries exposed to foreign competition are concentrated. Adjustment in local labor markets is remarkably slow, with wages and labor-force participation rates remaining depressed and unemployment rates remaining elevated for at least a full decade after the China trade shock commences. Exposed workers experience greater job churning and reduced lifetime income.At the national level, employment has fallen in U.S. industries more exposed to import competition, as expected, but offsetting employment gains in other industries have yet to materialize. Better understanding when and where trade is costly, and how and why it may be beneficial, are key items on the research agenda for trade and labor economists….”

Autor, David, David Dorn, and Gordon Hanson. “The China Shock: Learning from Labor Market Adjustment to Large Changes in Trade.” National Bureau Of Economic Research, January 2016, http://www.nber.org/papers/w21906

“….In this paper, we aim to bring the debate on the global productivity slowdown - which has largely been conducted from a macroeconomic perspective - to a more micro-level. We show that a particularly striking feature of the productivity slowdown is not so much a lower productivity growth at the global frontier, but rather rising labour productivity at the global frontier coupled with an increasing labour productivity divergence between the global frontier and laggard (non-frontier) firms. This productivity divergence remains after controlling for differences in capital deepening and mark-up behaviour, suggesting that divergence in measured multi-factor productivity (MFP) may in fact reflect technological divergence in a broad sense. This divergence could plausibly reflect the potential for structural changes in the global economy - namely digitalisation, globalisation and the rising importance of tacit knowledge - to fuel rapid productivity gains at the global frontier. Yet, aggregate MFP performance was significantly weaker in industries where MFP divergence was more pronounced, suggesting that the divergence observed is not solely driven by frontier firms pushing the boundary outward. We contend that increasing MFP divergence - and the global productivity slowdown more generally - could reflect a slowdown in the diffusion process.This could be a reflection of increasing costs for laggard firms of moving from an economy based on production to one based on ideas. But it could also be symptomatic of rising entry barriers and a decline in the contestability of markets. We find the rise in MFP divergence to be much more extreme in sectors where pro-competitive product market reforms were least extensive, suggesting that policy weaknesses may be stifling diffusion in OECD economies….”

Andrews, Dan, Chiara Criscuolo, and Peter Gal. “The Global Productivity Slowdown, Technology Divergence and Public Policy: A Firm Level Perspective.” Brookings Papers on Economic Activity, September 27, 2016.https://www.brookings.edu/wp-content/uploads/2016/08/andrews-et-al.pdf

“…This paper studies the effect of top tax rates on inventors' international mobility since 1977. We put special emphasis on “superstar” inventors, those with the most abundant and most valuable patents. We use panel data on inventors from the United States and European Patent Offices to track inventors' locations over time and combine it with international effective top tax rate data. We construct a detailed set of proxies for inventors' counterfactual incomes in each possible destination country including, among others, measures of patent quality and technological fit with each potential destination. Exploiting the differential impact of changes in the top tax rate on inventors of different qualities,we find that superstar top 1% inventors are significantly affected by top tax rates when deciding where to locate. The elasticity to the net-of-tax rate of the number of domestic superstar inventors is relatively small, around 0.03, while the elasticity of the number of foreign superstar inventors is around 1. Inventors who work in multinational companies are more likely to take advantage of tax differentials. On the other hand, if the company of an inventor has a higher share of its research activity in a given country, the inventor is less sensitive to the tax rate in that country….”

Ufuk Akcigit, Salomé Baslandze, Stefanie Stantcheva, "Taxation and the International Mobility of Inventors," National Bureau Of Economic Research, October 2015, https://www.nber.org/papers/w21024

this is a hell of a Churchill quote“,,, medal glitters, but it also creates a shadow….”

Philipp Ager, Leonardo Bursztyn, Hans-Joachim Voth, “Killer Incentives: Status Competition and Pilot Performance during World War II,”The National Bureau of Economic Research, December 2016, http://www.nber.org/papers/w22992

“…Fighter pilots in wartime are subject to substantial principal-agent problems. To fulfill their duty, they have to risk death. How can they be motivated to do so? We study the role of awards and of status competition. We collect and compile new, detailed data on monthly victory scores of over 5,000 German pilots during World War II.Our results suggest that awards may have been an important incentive. Crucially, we find evidence of status competition: When the daily bulletin of the German armed forces mentioned the accomplishments of a particular fighter pilots, his former peers perform markedly better. Outperformance is differential across skill groups. The best pilots try harder, score more, and die no more frequently when a former squadron peer is mentioned; average pilots try win only very few additional victories, but die at a markedly higher rate.Our results suggest that the incentive effects of nonfinancial rewards can beambiguous in settings where both risk and output affect aggregate performance….”

whole paper is interesting

“…Far from sudden “eureka” moments, innovation is nearly always a gradual process that proceeds by incremental steps. It is a team sport: There is no individual who can be credited with inventing the computer or the internet. The introduction of short-strawed wheat that revolutionized Asian agriculture in the 1960s, resulting in the defeat of famine, was driven by Manzoor Bajwa in Pakistan and M.S. Swaminathan in India. But they got the idea from Norman Borlaug in Mexico, who got it from Burton Bayles, who got it from Orville Vogel, who got it from Cecil Salmon, who got it from Gonjirô Inazuka in Japan, who got it from…at this point the trail runs cold. Once started, innovation is so inexorable it looks inevitable: 21 different people had the idea of the lightbulb independently. Many people besides the Google founders came up with search engines in the 1990s. Yet, paradoxically, innovation is impossible to predict. Almost nobody foresaw the usefulness and profitability of search engines. The first half of the 20th century brought dramatic changes in transport, the second half in communication. The switch was not the result of policy: Innovation cannot easily be forced…”

Matt Ridley, "Innovation Can’t Be Forced, but It Can Be Quashed,"Wall Street Journal, May 15, 2020, https://www.wsj.com/articles/innovation-cant-be-forced-but-it-can-be-quashed-11589555004

Innovation Can’t Be Forced, but It Can Be Quashed

The Covid-19 pandemic reveals that far from living in an age of incessant technological change, we have been neglecting innovation in exactly the areas where we most need it. Faced with a 17th-century plague, we are left to fall back mainly on the 17th-century response of quarantine and closing the theaters.

It is commonplace today to say that innovation is speeding up, but like much conventional wisdom, it is wrong. Some innovation is speeding up, certainly, but some is slowing down. Take speed itself. In my lifetime of more than sixty years, I have seen little or no improvement in the average speed of travel. Congestion on the roads and at airports has in many cases increased the scheduled travel time between two points. A modern airliner, with its high-bypass engines and less-swept wings, is designed to save fuel by going more slowly than a Boeing 707 did in the 1960s. The record for the fastest manned plane, 4,520 miles an hour, was set by the X-15 rocket plane in 1967 and remains unbroken. Boeing 747s are still flying half a century after they were launched. Concorde, the only supersonic passenger plane, is history.

Moreover, recent decades have seen innovation stalled or rejected in a number of technologies. Nuclear power has been unable to roll out plans for new reactor designs. Genetic modification of crops was effectively rejected by Europe. The flow of new pharmaceutical drugs has slowed to a trickle. Ride-sharing apps have been banned in many cities. As the investor Peter Thiel has pointed out, innovation is now largely a digital phenomenon, because bits are lightly regulated and atoms heavily regulated. On all sides we hear arguments that innovation threatens jobs, the environment, privacy and democracy.

Of immediate relevance to the current emergency, the development of vaccines has languished in the 21st century as an orphan technology, insufficiently encouraged by governments and ignored by the private sector. New vaccines are rarely profitable. By the time a company develops one for a new epidemic, the worst may be over. Last year Wayne Koff, president of the Human Vaccines Project, warned that the world was poorly prepared for a pandemic because vaccine development “is an expensive, slow and laborious process, costing billions of dollars, taking decades, with less than a 10% rate of success.”

It is not just vaccines. Throughout the economy, with the exception of the digital industry, the West is experiencing an innovation famine. The Austrian economist Joseph Schumpeter’s “perennial gale of creative destruction” has been replaced by the gentle breezes of rent-seeking. Two recent books argue that big companies in cozy cahoots with big government increasingly shy away from change, sheltered against competition by regulation and intellectual property rights. In “The Captured Economy” (2017), Brink Lindsey and Steven M. Teles make the case that to the extent that incomes have been stagnating and opportunities for social mobility drying up, the cause is not too much innovation but too little. In “The Innovation Illusion” (2016), Fredrik Erixon and Bjorn Weigel argue that Western economies have “developed a near obsession with precautions that simply cannot be married to a culture of experimentation.”

Innovation relies upon freedom to experiment and try new things, which requires sensible regulation that is permissive, encouraging and quick to give decisions. By far the surest way to rediscover rapid economic growth when the pandemic is over will be to study the regulatory delays and hurdles that have now been hastily swept aside to help innovators in medical devices and therapies, and to see whether such reforms could be applied to other parts of the economy too.

A big obstacle to innovation is the slow pace of regulatory licensing. One 2012 study found that a medical device takes around 21 months to get through the regulatory process in the U.S., from application to market, and 70 months in Germany. In the specific case of the Stratos implantable pacemaker, it took 14 months in the U.S., 40 months in France and 70 months in Italy.

There is nothing new about resistance to innovation. In 1662, William Petty, a pioneering economist, medical professor and land speculator, lamented that “the poor inventor runs the gauntloop of all petulant wits,” with everybody trying to stop him from succeeding. At the time, King Charles II, lobbied by the brewing industry, was trying to ban a novel drink called coffee because it caused fake news. “As for coffee, tea and chocolate,” the king pronounced, “I know no good they do; only the places where they are sold are convenient for persons to meet in, sit half day and discourse with all companies that come in of State matters, talking of news and broaching of lies.”

Hansom cab operators in London furiously denounced the introduction of the umbrella for offering shelter to rain-soaked pedestrians. Margarine was subjected to a decadeslong smear campaign from the dairy industry. Musicians’ unions delayed the playing of recorded music on the radio. The Horse Association of America for many years fought a rear-guard action against the tractor, and the natural-ice harvesting industry frightened people with scares about the safety of refrigerators. You may laugh, but the same happens today: Incumbent vested interests, overcautious regulators, opportunistic activists and rent-seeking patent holders combine to oppose or delay almost every innovation.

There is no good evidence that patents are helpful, let alone necessary, in encouraging innovation.

Surprisingly, there is no good evidence that patents are helpful, let alone necessary, in encouraging innovation. A 2002 study by Josh Lerner, an economist at Harvard Business School, looked at 177 cases of strengthened patent policy in 60 countries over more than a century, finding that “these policy changes did not spur innovation.” James Watt, Samuel Morse, Guglielmo Marconi, the Wright brothers and many others wasted the best years of their lives in court defending their intellectual property, when they might have been busy developing new devices.

The expiration of patents often results in a burst of innovation, as with 3-D printing, where the recent lapse of three key patents has resulted in notable improvements in quality and a drop in price. The historian Anton Howes, of the Royal Society of Arts in London, points out that the French government bought out Louis Daguerre’s patent for photography in 1839 and made the technology freely available, unleashing a burst of creative innovation. Dr. Howes argues, “As we look to fight coronavirus and any future pandemics, we should perhaps consider which patents—for antivirals, vaccines, ventilators and other hygienic equipment—might be bought out in order to remove…innovation bottlenecks.”

What is innovation and how is it best encouraged? Policy makers tend to assume it is the result of clever people having clever thoughts in ivory towers. But science is just as often the fruit as the seed of technology, and invention is different from innovation. To illustrate the difference, Charles Townes, who won the Nobel Prize for the physics behind the laser in 1964, was fond of telling the story of a beaver and a rabbit looking up at the Hoover Dam. “No, I didn’t build it myself,” says the beaver. “But it’s based on an idea of mine.” Discoverers and inventors often feel they get too little credit or profit from a good idea, forgetting just how much effort was needed to turn that idea into a workable, affordable innovation that actually delivered benefits to people.

Thomas Edison understood better than anybody that trial and error is the key to turning an invention into a useful innovation. In developing the nickel-iron battery, his employees undertook 50,000 experiments. Developing a new technology, he famously said, is 1% inspiration and 99% perspiration. Jeff Bezos makes the same point: “Being wrong might hurt you a bit, but being slow will kill you. If you can increase the number of experiments you try from a hundred to a thousand, you dramatically increase the number of innovations you produce.” It turns out that continuous tinkering to develop and refine a better product is much more important than protecting what you’ve already created.

Once started, innovation is so inexorable it looks inevitable, yet it’s nearly impossible to predict.

Far from sudden “eureka” moments, innovation is nearly always a gradual process that proceeds by incremental steps. It is a team sport: There is no individual who can be credited with inventing the computer or the internet. The introduction of short-strawed wheat that revolutionized Asian agriculture in the 1960s, resulting in the defeat of famine, was driven by Manzoor Bajwa in Pakistan and M.S. Swaminathan in India. But they got the idea from Norman Borlaug in Mexico, who got it from Burton Bayles, who got it from Orville Vogel, who got it from Cecil Salmon, who got it from Gonjirô Inazuka in Japan, who got it from…at this point the trail runs cold.

Once started, innovation is so inexorable it looks inevitable: 21 different people had the idea of the lightbulb independently. Many people besides the Google founders came up with search engines in the 1990s. Yet, paradoxically, innovation is impossible to predict. Almost nobody foresaw the usefulness and profitability of search engines. The first half of the 20th century brought dramatic changes in transport, the second half in communication. The switch was not the result of policy: Innovation cannot easily be forced.

Given this unpredictability, politicians should rethink the incentives for innovation. One option is to expand the use of prizes, to replace reliance on grants, subsidies and patents. Britain’s famous Longitude Prize, offered in 1714 for accurately measuring longitude at sea, elicited a solution from an unexpected direction: accurate and robust clocks made by a humble clockmaker, John Harrison. Similar serendipity happens today. One study of the online problem-sharing forum known as Innocentive, where organizations can reward crowdsourced solutions to problems that baffle them, found that “the further the focal problem was from the solvers’ field of expertise, the more likely they were to solve it.” Teflon, Kevlar and the Post-it Note are all examples of useful things developed by people looking for something completely different.

The Nobel Prize-winning economist Michael Kremer came up with a concept called the Advance Market Commitment that would fine-tune prizes as incentives to innovate. In 2007, the Gates Foundation committed $1.5 billion to a prize fund to find a vaccine for Pneumococcus bacteria for use in developing countries, where no pharmaceutical company could make money from it. But rather than just winning a lump sum for meeting the goal, companies were assured that if they succeeded, they would win a contract that paid out for 10 years at a good price. The prize money effectively topped up the sum received by the pharmaceutical firm for every vaccine sold. The result of the auction was three good vaccines, costing $2 per dose, which have been given to 150 million children, saving 700,000 lives.

The world would benefit from more innovation, and it need not be high-tech. Consider just one remarkable development that has saved millions of lives from malaria in recent decades: the insecticide-treated mosquito net.

In June 1983, in the West African country of Burkina Faso, a group of French and Vietnamese scientists together with African colleagues began an experiment. They installed mosquito nets in 36 huts specially equipped with mosquito traps. Half the nets were treated with the insecticide permethrin and half had holes torn in them to simulate the wear and tear of everyday life. For five months, volunteers slept in the huts, while every mosquito that entered or tried to leave the huts was collected, dead or alive. The results showed that the presence of a permethrin-treated net, whether intact or torn, repelled mosquitoes, reducing the number entering the huts by about 70% and increasing the rate at which the insects left the hut from 25% to 97%.

This simple, careful experiment proved to be a breakthrough in the control of malaria in Africa. Supported by the Gates Foundation, impregnated bednets first started to be used on a wide scale in 2003, and that very year malaria mortality began to decline. According to a recent study in the journal Nature, insecticide-treated mosquito nets account for 70% of the six million lives saved world-wide from malaria in recent years, twice as high a percentage as antimalarial drugs and insecticide sprays put together. Globally, the death rate from malaria has halved since 2003.

Dealing with Covid-19 has forcibly reminded governments of the value of innovation. But if we are to get faster vaccines and treatments—and better still, more innovation across all fields in the future—then innovators need to be freed from the shackles that hold them back.

“…We investigate the importance of Veblen effects on work hours, namely the manner in which a desire to emulate the consumption standards of the rich influences individuals’ allocation of time between labor and leisure. Our model of the choice of work hours captures Veblen effects by taking account of the influence of the consumption of the well-to-do on the marginal utility of consumption by the less well-off. The main result is that work hours are increasing in the degree of income inequality.We use data on work hours of manufacturing employees in ten countries over the period 1963-1998, along with three different measures of income inequality to explore this hypothesis. Using both OLS and country-fixed-effects estimates,we find that greater inequality predicts longer work hours. Its effects are large, and estimates are robust across a variety of specifications.Additional evidence suggests that while greater inequality may induce longer hours for conventional incentive reasons, this mechanism does not account for our results. We show that in the presence of Veblen effects, a social welfare optimum cannot be implemented by a flat tax on consumption but may be accomplished by more complicated (progressive) consumption taxes or by subsidizing the leisure of the rich….”

Samuel Bowles and Yongjin Park, “Emulation, Inequality, and Work Hours: Was Thorsten Veblen Right?”The Economic Journal, November 2005, http://onlinelibrary.wiley.com/doi/10.1111/j.1468-0297.2005.01042.x/abstract

“…We present new evidence on trends in intergenerational mobility in the U.S. using administrative earnings records. We find that percentile rank-based measures of intergenerational mobility have remained extremely stable for the 1971-1993 birth cohorts. For children born between 1971 and 1986, we measure intergenerational mobility based on the correlation between parent and child income percentile ranks. For more recent cohorts, we measure mobility as the correlation between a child's probability of attending college and her parents' income rank. We also calculate transition probabilities, such as a child's chances of reaching the top quintile of the income distribution starting from the bottom quintile. Based on all of these measures, we find that children entering the labor market today have the same chances of moving up in the income distribution (relative to their parents) as children born in the 1970s. However, because inequality has risen, the consequences of the "birth lottery" - the parents to whom a child is born - are larger today than in the past….”

Raj Chetty, Nathaniel Hendren, Patrick Kline, Emmanuel Saez, and Nicholas Turner, “Is the United States Still a Land of Opportunity? Recent Trends in Intergenerational Mobility.” National Bureau Of Economic Research, January 2014, http://www.nber.org/papers/w19844

“…We construct a model of household decision-making in which agents consume a private and a public good, interpreted as children's welfare. Children's utility depends on their human capital, which depends on the time their parents spend with them and on the parents' human capital. We first show that as returns to human capital increase, couples at the top of the income distribution should spend more time with their children.This in turn should reinforce assortative matching, in a sense that we precisely define. We then embed the model into a transferable utility matching framework with random preferences, a la Choo and Siow (2006), which we estimate using US marriage data for individuals born between 1943 and 1972. We find that the preference for partners of the same education has significantly increased for white individuals, particularly for the highly educated. We find no evidence of such an increase for black individuals. Moreover, in line with theoretical predictions, we find that the "marital college-plus premium" has increased for women but not for men….”

Pierre-André Chiappori, Bernard Salanié, and Yoram Weiss. “Partner Choice, Investment in Children, and the Marital College Premium,” American Economic Review, August 2017, https://www.aeaweb.org/articles

Research presented at Brooking's finds Chinese growth overstated by an average of 1.7% y/y btw 2008-2016. If true their GDP is 12% smaller then official figures suggests. two thoughts a) implications for their debt to GDP ratio ~30bps higher then we thought (see chart) b) their gross security spending as a % of GDP is prob really high

"....China’s national accounts are based on data collected by local governments. However, since local governments are rewarded for meeting growth and investment targets, they have an incentive to skew local statistics. China’s National Bureau of Statistics (NBS) adjusts the data provided by local governments to calculate GDP at the national level. The adjustments made by the NBS average 5% of GDP since the mid-2000s. On the production side, the discrepancy between local and aggregate GDP is entirely driven by the gap between local and national estimates of industrial output. On the expenditure side, the gap is in investment. Local statistics increasingly misrepresent the true numbers after 2008, but there was no corresponding change in the adjustment made by the NBS. Using publicly available data, we provide revised estimates of local and national GDP by re-estimating output of industrial, construction, wholesale and retail firms using data on value-added taxes. We also use several local economic indicators that are less likely to be manipulated by local governments to estimate local and aggregate GDP. The estimates also suggest that the adjustments by the NBS were insufficient after 2008. Relative to the official numbers, we estimate that GDP growth from 2008-2016 is 1.7 percentage points lower and the investment and savings rate in 2016 is 7 percentage points lower..."

Wei Chen, Xilu Chen, Chang-Tai Hsieh, and Zheng (Michael) Song, "A forensic examination of China’s national accounts," Brookings Paper's on Economic Activity, March 7, 2019, https://www.brookings.edu/bpea-articles/a-forensic-examination-of-chinas-national-accounts/

Michael Beckley, "China's Economy Is Not Overtaking America's,"Journal Of Applied Corporate Finance, May 18, 2020, https://www.aei.org/research-products/journal-publication/chinas-economy-is-not-overtaking-americas/

"...China’s economic growth over the past three decades has been spectacular, even miraculous. Yet the veneer of double-digit growth rates has masked gaping liabilities that limit China’s ability to close the wealth gap with the United States. China has achieved high growth at high costs, and now the costs are rising while growth is slowing. As I explain in a recent book, data that accounts for these costs reveal thatthe United States is several times wealthier than China, and the gap appears to be growing by trillions of dollars every year.1 This conclusion may surprise many people, given that China has a bigger GDP, a higher investment rate, larger trade flows, and a higher economic growth rate than the United States. How can China outproduce, outinvest, and outtrade the United States—and own nearly $1.2 trillion in U.S. debt—yet still have substantially less wealth?....The reason is that China’s economy is big but inefficient. It produces vast output but at enormous expense. Chinese businesses suffer from chronically high production costs, and China’s 1.4 billion people impose substantial welfare and security burdens. The United States, by contrast, is big and efficient. American businesses are among the most productive in the world; and with four times fewer people than China, the United States has much lower welfare and security costs. GDP and other standard measures of economic heft ignore these costs and create the false impression that China is overtaking the United States economically. In reality, China’s economy is barely keeping pace as the burden of propping up loss-making companies and feeding, policing, protecting, and cleaning up after one-fifth of humanity erodes China’s stocks of wealth.....China’s productivity growth has not only been unspectacular; it has been virtually nonexistent.5 By contrast, productivity improvements have accounted for roughly 20% of U.S. economic growth over the past decade, as it has for most of the past 100 years.6...China’s private sector is relatively efficient, but it is shackled to a bloated state sector that destroys nearly as much value as it creates.11... All told, more than one-third of China’s industrial capacity goes to waste and nearly two-thirds of China’s infrastructure projects cost more to build than they will ever generate in economic returns.12 Total losses from this waste are difficult to calculate, but the Chinese government estimates that it blew nearly $7 trillion on “ineffective investment” between 2009 and 2014.13...As just one example, China’s unused capacity in steelmaking exceeds the total combined steel production capacity of Japan, the United States, and Germany.10....The unsurprising result of all these burdens, plus the wasted investment highlighted above, has been a dramatic rise in China’s debt, from 100% of GDP in the 1990s to greater than 300% in 2019.19.... With a per capita income six times greater than China’s, the United States not only has more surplus wealth to pay down its debts it also has much lower interest rates....China’s household and corporate borrowers have been hit with rising interest rates that now consume 20% of China’s GDP.21 Roughly a quarter of China’s thousand biggest firms owe more money in interest than they earn in gross profits; and 45% of all new loans in China are being used to pay interest on old loans, a practice that analysts are calling “Ponzi finance.” Writing off these bad loans will cost China somewhere between $1.5 trillion and $10 trillion, with the latter figure nearly equal to China’s GDP.22 To put that number in context, consider that the United States spent 8% of its GDP writing off bad loans after the 2008 financial crisis.23.....Ultimately, the only way for China to solve its debt problem without gutting social spending is to increase its productivity, which in turn will require innovation. The Chinese government understands this well. Since 2007, it has tripled R&D spending, employed more scientists and engineers than any other country, and mounted the most extensive corporate espionage campaign in history......These moves, however, have yet to turn China into an innovation powerhouse. China produces only half the high-technology output and highly-cited scientific studies as the United States, holds five times fewer international patents, and pays more royalties for technology than it takes in.24...China is a major player in high-technology supply chains, but Chinese firms mainly focus on low-tech activities...For those reasons, Deloitte and Boston Consulting Group both argue that the United States increasingly rivals China as the world’s most cost-competitive manufacturing nation.33....China now leads the world in retractions of scientific studies due to fraud, one-third of Chinese scientists have admitted to plagiarizing or falsifying results (versus 2% of U.S. scientists), and nearly two-thirds of China’s R&D spending has been lost to corruption.35/////This culture of fraud extends throughout China’s economy.....According to the World Bank and the UN, human capital—the knowledge, skills, and labor embodied in a nation’s population—constitutes more than half of the wealth of most countries. Both organizations estimate that the U.S. stock of human capital is several times greater than China’s.38 China has four times the population of the United States, but the average American worker generates seven times the output of the average Chinese worker.39....China also loses 400,000 of its most highly educated workers every year to foreign countries in net terms, including thousands of scientists, engineers, and “inventors” (people that have registered at least one patent).52The United States, by contrast, nets one million workers annually from all foreign countries, including roughly 20,000 inventors and 15,000 scientists and engineers, 5,000 of whom come from China.....The U.S. workforce is not only better educated but also healthier than China’s. China loses 40% more years of productive life per capita on average from major ailments.53....China is aging more rapidly than any society in history. The number of Chinese aged 65 and older will more than triple by midcentury, from 130 million in 2015 to 400 million by 2050.63 Meanwhile China’s workforce will shrink by 212 million—about one-third of the current total. At that point, senior citizens will account for more than 30% of China’s population versus only 20% of the U.S. population.....The United States can feed its population with only 1% of its workforce in agriculture whereas China devotes 30% of its workforce to farming—and still depends on food imports to feed its population.64....Roughly one-third of China’s provinces and two-thirds of its major cities suffer from extreme water scarcity.67....The United States generates more than three times as much wealth from each gallon of water as China.68....The United States generates roughly 40% more wealth per unit of energy than China.76....American farmers produce 30% more food per hectare than Chinese farmers.....China must recognize that its economic engine is not strong enough to support grand ambitions for territorial conquest and regional hegemony. Its best option, therefore, is to become a responsible stakeholder in the existing international order. The United States, on the other hand, must recognize that China is nowhere close to dominating East Asia, let alone challenging the United States for global primacy. And so Instead of preparing for preventive war, the United States should reinforce the existing East Asian balance of power...."

Conference Board. 2013. “Departing CEO Age and Tenure.” The Conference Board, CEO Succession Practices.https://www.conference-board.org/retrievefile.cfm

"....This paper has set out methods, presented data and analyzed investment and sources of economic growth including intangibles for the European Union and the United States. Our data for investment cover the EU27 member countries and the US in 1995-2005, and for the EU15 economies, the US plus Czech Republic and Slovenia we add the years 2006-2009. Our growth accounting covered 14 EU countries plus the US. Despite the emerging parity in the contribution of intangible capital to European growth, for some countries in Europe, this stands against a backdrop of smaller rates of growth of labor productivity than typically experienced in the UK and US. And in most cases the shortfall can be attributed to lower multifactor productivity growth. This could result from structural factors orthogonal to intangible capital per se, such as a greater ability to 37 obtain financing for innovation in certain countries. It also could be associated with returns to scale or intangible capital deepening itself, as suggested by Figure 9, which shows a positive association between MFP growth and the contribution of intangible capital deepening (and one that is much stronger than that for tangible capital, figure 10).Figure 9 - Intangible Capital and Spillover Effects

We are, of course, conditioned to think in terms of spillovers from R&D because the topic is well researched, but spillovers occur whenever an investment in innovation by a firm or an industry creates a platform that spurs follow on innovations and new or expanded markets (think “apps” for mobile phones, or the “clusters” that form around a successful business). To better understand the spillovers that are suggested by Figure 5 suggests deeper study of the returns to specific intangible assets and channels through which the returns accrue. With the advent of the IT revolution and Internet technology, the spillover channels may be quite different than the “distance” models formulated and studied by Zvi Griliches some time ago (see Griliches 1992 for a review).

A deeper dive into such topics is the subject of a forthcoming companion paper (Corrado, Haskel, JonaLasinio 2012) 38 Figure 10 - Tangible Capital and Spillover Effects The harmonized estimates of intangible capital for Europe introduced in this paper are preliminary, but key advances were made that substantially enhance their usefulness in policy discussions. The new growth accounting results are the broadest available results for Europe to date. Although Europe invests less in intangibles than the US, intangibles account still account for between 1/5 and 1/4 of the average growth of market sector labor productivity in Europe. In addition to improved measurement, advanced countries need to build a deeper understanding of the returns to intangible assets and of the role intangibles play in the national and international innovation diffusion process..."

Corrado, Carol, Jonathan Haskel, Cecilia Jona-Lasinio, and Massimiliano Iommi. July 2012. “Intangible Capital and Growth in Advanced Economies: Measurement Methods and Comparative Results.” Institute for the Study of Labor (IZA).https://www.conference-board.org/pdf_free/workingpapers/EPWP%201203.pdf

“…We estimate the monetary return to attending a highly selective college using the College and Beyond (C&B) Survey linked to Detailed Earnings Records from the Social Security Administration (SSA). This paper extends earlier work by Dale and Krueger (2002) that examined the relationship between the college that students attended in 1976 and the earnings they self-reported reported in 1995 on the C&B follow-up survey. In this analysis, we use administrative earnings data to estimate the return to various measures of college selectivity for a more recent cohort of students: those who entered college in 1989. We also estimate the return to college selectivity for the 1976 cohort of students, but over a longer time horizon (from 1983 through 2007) using administrative data. We find that the return to college selectivity is sizeable for both cohorts in regression models that control for variables commonly observed by researchers, such as student high school GPA and SAT scores. However, when we adjust for unobserved student ability by controlling for the average SAT score of the colleges that students applied to, our estimates of the return to college selectivity fall substantially and are generally indistinguishable from zero. There were notable exceptions for certain subgroups. For black and Hispanic students and for students who come from less-educated families (in terms of their parents’ education), the estimates of the return to college selectivity remain large, even in models that adjust for unobserved student characteristics….”

Stacy Dale and Alan Krueger, “Estimating the Return to College Selectivity Over the Career Using Administrative Earnings Data.” National Bureau Of Economic Research, June 2011, http://www.nber.org/papers/w17159

Why Workers Without College Degrees Are Fleeing Big Cities

Last month the Census Bureau confirmed a confounding dynamic taking hold across the American landscape: Superstar cities, the nation’s economic powerhouses, hotbeds of opportunity at the cutting edge of technological progress, are losing people to other parts of the country.

Santa Clara County, Calif., home to most of Silicon Valley, lost 24,645 people to domestic migration, its ninth consecutive annual loss.

The trend is becoming widespread. Eight of the 10 largest metropolitan areas in the country, including those around New York, San Francisco, Los Angeles and Miami, lost people to other places in 2018. That was up from seven in 2016, five in 2013 and four in 2010. Migration out of the New York area has gotten so intense that its total population shrank in 2018 for the second year in a row.

As the chart above shows, 30 of the 44 largest counties, with populations above one million, recorded more domestic outflows than inflows of people in 2018.

This growing flow of people out of the hotbeds of innovation and economic activity underscores how lopsided the distribution of opportunity has become.

Places like Cupertino and Mountain View in Santa Clara County may still offer the best, most highly paid opportunities for the highly educated — lawyers and programmers seeking jobs at Apple or Google. The median family in that county makes $122,700 a year. In King County it is $105,512, way above the national median of $76,000.

The problem is that workers without a four-year college degree don’t earn anywhere near that much.

Consider janitors. In 1960, a janitor in the Deep South could more than double his income by moving to Santa Clara County, even after accounting for higher housing costs. Since then, janitors’ earnings have grown much more slowly in Silicon Valley and King County than in the Deep South. And this is upending the distribution of prosperity across the country.

The divergence of economic opportunity for workers on either side of college is not a new phenomenon. But we are only beginning to understand how it has reconfigured the rationale for migration: Moving to opportunity is not what it once was.

Forty or 50 years ago, someone with no more than a high school diploma had much better job opportunities in a big city than in a small town. Not only did those at the bottom of the wage scale — janitors, cashiers at 7-Eleven — make more money in dense urban centers, but these places also offered data entry, bookkeeping and other jobs that paid middle-class wages while requiring little or no college experience.

But as my colleagues Emily Badger and Quoctrung Bui noted recently in an article citing the work of the M.I.T. economist David Autor, big cities have lost their luster for workers without four-year college degrees. They will make no more in New York or San Francisco than they would in, say, small-town Alabama.

The clerical jobs that cities used to offer are largely gone, replaced by computer software or outsourced to other parts of the world. Moreover, the wage bump that big cities used to offer janitors and cashiers has mostly disappeared. Those who used to hold middle-income positions have dropped down the wage scale, competing for jobs at the bottom.

And even as big-city wages flatlined for workers without the requisite college degree, big-city housing prices soared ahead.

Rising rents affect everybody, of course. But housing sucks up a bigger share of the income of the poor. In 1960, housing absorbed 17 percent of a janitor’s household earnings in King County, compared with 9 percent of a lawyer’s, according to data from Mr. Ganong. By 2017, lawyers’ households had to pay almost 15 percent of their incomes. Janitors’ households had to pay 38 percent.

In the middle of the 20th century, rich urban clusters drew people from across the educational spectrum. Moving to the big city in search of a good job was as sound a decision for a worker who hadn’t completed high school as for someone with a college degree.

That attraction has faded even for the most-educated workers. Changes in the way the Census Bureau records domestic moves — in 1940 it asked people where they were five years ago; in 2016 it asked where they were the year before — reduces reported migration rates. Still, migration has subsided significantly over the last few decades. In 2016, more people with a bachelor’s degree or more left the nation’s richest metropolitan areas than arrived seeking opportunities there. Rising housing costs seem to deter them, too. For workers who haven’t cleared the college threshold, this is doubly true. For them, New York or Los Angeles or Seattle or San Francisco no longer makes sense.

It is not obvious how to turn big cities back into magnets of opportunity for the working class. Many of the jobs that offered a leg up to those without a college background no longer exist and won’t come back. But there are policies that could make a difference. Relaxing zoning regulations to make it easier to build could slow rising rents, ensuring that the housing supply keeps up with demand.

And yet the prospects do not look good. California lawmakers last week shelved Senate Bill 50, which would have forced cities to allow denser housing near public transit and removed density limits in wealthier areas close to job centers and good schools. The bill faced stiff opposition from many municipal governments and residents enamored with low-density living — not to mention rising property values.

The single-family-home ethos may eventually lose its grip on the politics of America’s superstar cities. Until then, it will make sense for those without a degree to look for opportunities elsewhere, in places like Kansas City or Des Moines or Las Vegas.

Eduardo Porter and Gilbert Gates, “Why Workers Without College Degrees Are Fleeing Big Cities,”New York Times, May 21, 2019, https://www.nytimes.com/interactive/2019/05/21/business/economy/migration-big-cities.html

Venture Funding of U.S. Startups Last Year Was Most Since 2000

The money spigots for U.S. startups opened last year to their widest since the peak of the dot-com boom in

Venture capitalists pumped $48.3 billion into U.S. startups in 2014, according to data today from the National Venture Capital Association and PricewaterhouseCoopers, the most since investors piled $105 billion into closely held companies in 2000. The 2014 total was up 61 percent from $30 billion in 2013 and was more than double the $20.4 billion invested in 2009.

The venture number caps what was a year of megadeal funding rounds and rising valuations for startups, especially in the technology industry. Mobile car-booking company Uber Technologies Inc. reeled in two financings that each exceeded $1 billion last year, ending with a valuation of $40 billion. Venture fundings of more than $500 million hit a six-year high last year, according to researcher CB Insights.

“I think we’re in an environment where there are a lot of things to celebrate, but we’re getting to the point of excessive in the amount of capital being raised and valuations,” said Joe Horowitz, managing general partner at Jafco Ventures.

The flood of money has renewed debate about whether Silicon Valley is in a bubble. Venture capitalists including Andreessen Horowitz’s Marc Andreessen, Benchmark’s Bill Gurley and Breyer Capital’s Jim Breyer have all cautioned in recent months that the good times may not last for startup fundraising

“When the market turns, and it will turn, we will find out who has been swimming without trunks on,” Andreessen said in a Twitter post in September. Bloomberg LP, the parent of Bloomberg News, is an investor in Andreessen Horowitz.

Other Investors

The NVCA and PricewaterhouseCoopers data doesn’t fully capture the amount of money being poured into U.S. startups because the survey only tracks investments from venture capitalists. Other types of investors have also increasingly started putting money into startups, including hedge funds, sovereign wealth funds and international companies. Last month, for example, Chinese Web company Baidu Inc. agreed to invest in San Francisco-based Uber.

Apart from Uber, other U.S. startups that benefited from the easy-money environment last year were virtual-reality startup Magic Leap Inc. and mobile messaging company Snapchat Inc., as well as media startup Vice Media, according to NVCA and PricewaterhouseCoopers data.

Bigger Numbers

Many of the startups taking in money are receiving larger funding amounts. The number of investing deals last year rose to 4,356 last year, up 3.9 percent from 2013, illustrating how more money flooded into a relatively constant number of companies, according to the NVCA and PricewaterhouseCoopers report.

“The inflow of capital and public market funds is very real and sizeable,” said Steve Harrick, general partner at Institutional Venture Partners. “The investment climate is very good in terms of opportunities.”

Venture capitalists last year paid particular attention to software startups, which accounted for 41 percent of total investments. It was the largest share the category has held since at least 1995, according to the data.

Among the most active venture firms in 2014 were New Enterprise Associates, Andreessen Horowitz, Kleiner Perkins Caufield & Byers, Google Ventures and Khosla Ventures, CB Insights said.

Even with the warnings from some venture capitalists, others said the rush of money is set to continue. Charles Kane, a senior lecturer at the Massachusetts Institute of Technology’s Sloan School of Management, said venture investors still need to deploy the huge amounts of funding they’ve raised.

“Next year will be bigger than the past year,” Kane said. “The venture capital firms that have gone out to raise money haven’t had trouble raising money.”

Eric Newcomer, “Venture Funding of US Startups Last Year Was Most Since 2000.” Bloomberg Businessweek, January 16, 2015, http://www.bloomberg.com/news/articles/2015-01-16/it-s-official-startup-funding-last-year-was-biggest-since-2000

“…Concentration has increased over the last 30 years or so in a variety of industries. This development has raised concern about weakened competition and resulting harm to consumers. Calls for tougher antitrust enforcement have become louder. There is also concern that rising concentration may be at least symptomatically related to declining business dynamism and lower productivity growth. There is, however, only sporadic evidence on these matters. This paper provides more systematic evidence on the interplay between concentration, prices and productivity across several hundred US manufacturing industries over two 15 year periods from 1982-2012. The consistent pattern is that high and rising concentration has been on average associated with better productivity growth.Rising concentration has also been associated with widening margins of price over input costs. On balance, the net price effects are trivial. Accordingly some skepticism about tougher merger policy may be warranted, since this would risk harm to productivity without benefiting consumers….”

Sam Peltzman, “Productivity and Prices in Manufacturing During an Era of Rising Concentration,” Social Science Research Network, May 10, 2018, https://papers.ssrn.com/sol3/papers.cfm

Research from FRBR, while market concentration has risen nationally, concentration of smaller markets as gone down. "...We have shown...that the increase in market concentration observed at the national level over the last 25 years is being shaped by enterprises expanding into new local markets. This expansion into local markets is accompanied by a fall in local concentration as firms open establishments in new locations. These observations are suggestive of more, rather than less, competitive markets...."Counterintuitively (figure 15) if you net out the largest firm, concentration is unchanged suggesting that either small business stay in business or when a big firm enters a market other big firms do as well.

"....Using U.S. NETS data, we present evidence that the positive trend observed in national product market concentration between 1990 and 2014 becomes a negative trend when we focus on measures of local concentration. We document diverging trends for several geographic definitions of local markets. SIC 8 industries with diverging trends are pervasive across sectors. In these industries, top firms have contributed to the amplification of both trends. When a top firm opens a plant, local concentration declines and remains lower for at least 7 years. Our findings, therefore, reconcile the increasing national role of large firms with falling local concentration, and a likely more competitive local environment....In this paper, we use the National Establishment Time Series (NETS) dataset to document four main facts regarding national and local product-market concentration in the U.S. economy between 1990 and 2014. Our first fact is that the observed positive trend in market concentration at the national level has been accompanied by a corresponding negative trend in average local market concentration.We measure concentration using the Herndahl-Hirschman index (HHI), but our findings hold for a variety of statistics..... The second fact shows that local concentration is falling across SIC 8 industries that together account for 78% of employment and 72% of sales.Furthermore, conditioning on industries where national concentration is rising, industries where local concentration has declined account for the majority of employment overall (72% of employment and 66% of sales) across all major sectors. The presence of these diverging trends is always large but more pronounced in services, retail trade, and FIRE relative to wholesale trade and manufacturing. This ordering is natural given that transport costs are less relevant in the latter two sectors. Together, these first two facts underscore an unmistakable decline in local concentration on average that is pervasive across all sectors..... Our third fact shows that among SIC 8 industries that exhibit this pattern, top firms have accelerated these trends. That is, excluding the top
firm in each industry (in terms of national sales in their SIC 8 industry in 2014), the national increase in concentration becomes naturally less pronounced.Perhaps more surprisingly, the decline in local concentration also becomes less pronounced.Put another way, large firms have materially contributed to the observed decline in local concentration. Among industries with diverging trends, large firms have become bigger but the associated geographic expansion of these firms, through the opening of more plants in new local markets, has lowered local concentration thus suggesting increased local competition. In the considerably smaller set of industries where we observe increases in both national and local concentration, top firms have also been responsible for both forms of concentration......Our fourth fact establishes that among industries with falling local concentration, the opening of a plant by a top firm is associated with a decline in local concentration at the time of the opening, and that this lower level of concentration persists for at least the next 7 years.This observation provides further evidence that in those industries, large enterprises do not enter and dominate the local market but instead lower its concentration, either by competing with the previous local monopolist or by simply adding one more establishment that grabs a proportional market share from other local establishments. In any case, the notion that entry by large firms eliminates local producers to the point of increasing concentration is certainly not supported in the vast majority of industries where most of U.S. employment resides...."

Rossi-Hansberg, Esteban, Pierre-Daniel Sarte, and Nicholas Trachter. April 17, 2019. “Diverging Trends in National and Local Concentration.” Federal Reserve Bank of Richmond.https://www.princeton.edu/~erossi/DTNLC.pdf

“…This paper calculates the effects of immigration on the wages of native US workers of various skill levels in two steps. In the first step we use labor demand functions to estimate the elasticity of substitution across different groups of workers. Second, we use the underlying production structure and the estimated elasticities to calculate the total wage effects of immigration in the long run. We emphasize that a production function framework is needed to combine own-group effects with cross-group effects in order to obtain the total wage effects for each native group. In order to obtain a parsimonious representation of elasticities that can be estimated with available data, we adopt alternative nested-CES models and let the data select the preferred specification. New to this paper is the estimate of the substitutability between natives and immigrants of similar education and experience levels. In the data-preferred model, there is a small but significant degree of imperfect substitutability between natives and immigrants which, when combined with the other estimated elasticities,implies that in the period from 1990 to 2006 immigration had a small effect on the wages of native workers with no high school degree (between 0.6% and +1.7%). It also had a small positive effect on average native wages (+0.6%) and a substantial negative effect (−6.7%) on wages of previous immigrants in the long run….”Ottaviano, Gianmarco, and Giovanni Peri. February 1, 2012. “Rethinking the Effect of Immigration on Wages.” Journal of the European Economic Association.https://academic.oup.com/jeea/article-abstract/10/1/152/2182016

“Does Deutschland Do Digital?” November 21, 2017. The Economist.https://www.economist.com/news/business/21678774-europes-biggest-economy-rightly-worried-digitisation-threat-its-industrial

Yet it would be unfair not to mention the “Bosch Start-up Platform” which the firm has recently set up in Ludwigsburg, a short drive away. It has already incubated a handful of firms. One has developed a wireless sensor to improve asparagus yields, another builds agricultural robots that kill weeds. Germany’s manufacturers are clearly changing. The question is whether they can do so fast enough.

Compare Silicon Valley and Germany’s equivalent for industrial firms, the region around Stuttgart, and the cultural differences are clear. Google’s campus in Mountain View offers about 30 different canteens with free food and generous opening hours. Visitors can see some self-driving cars, but the scenery is dominated by bicycles in primary colours which employees use to pedal between the many buildings. At Bosch in Gerlingen, employees all stream into a huge, centralised corporate cafeteria at lunchtime. And the most striking vehicles are green self-driving lawnmowers that keep the grass around the firm’s office block in perfect trim.

The engineering background of many managers also explains why they focus more on incremental improvements than on making drastic gains in their products’ functionality and ease of use. “Germans are really good at reducing theSpaltmass, the clearance between the parts of a car’s body,” says Christoph Keese, who was one of the Springer executives who spent a few months in Silicon Valley and has written an influential book about the experience. But the user interfaces for German products are a different matter. They are often so complex, says Mr Keese, that the word that appears most often on their displays isAnwenderfehler(“user error”).

Many employees, too, are not ready for the digital world. At German universities computer scientists are trained much like engineers, meaning they are focused on precision, explains Clemens Westerkamp of the University of Applied Sciences in Osnabrück. This mindset, he says, is a big advantage when building highly reliable systems, which are required in many industries. But it is a drawback in the world of software and data, where quick thinking and risk-taking are more important. “The battle for industrial platforms will be a fight between German precision and American speed,” says Mr Westerkamp.

A fourth and final hurdle relates to German corporate culture. Although German firms are no longer as hierarchical as they once were, they are still managed from the top down; risk-taking is discouraged. A key to developing successful platforms and services is to put them in the hands of autonomous teams—rather like internal startups—and to be prepared to shut projects down if they fail to take off. Many German giants now have “accelerators” to incubate new business ideas, but lots are just public-relations exercises. Only a few have gone as far as Klöckner, which has set up an incubator for internal startups in Berlin, far away from its headquarters in Duisburg, with the aim of digitising the firm’s entire supply chain.

Third, platforms are about sharing the data they gather. The best new services are often the result of combining information from different sources. But in Germany this can be difficult. One barrier is privacy: in addition to the country’s strict data-protection laws, there is a widespread suspicion of anything that smacks of monetising data. Even among younger Germans, nearly two-thirds worry that data generated by their cars will be sold on, according to a recent study by Deloitte, a consulting firm. Many Germans are wary of what has come to be calledPlattform-Kapitalismus, meaning the dominance of new markets by mighty foreign providers such as Google and Facebook (see chart 2). This is seen as somehow unfair and an example of American “cowboy capitalism”, which adds to the reluctance of German firms to create and promote their own platforms. Mittelstand firms too are reluctant to share data: they fear they could lose control of their intellectual property and thus their competitive edge.

Shy about sharingUser-unfriendly

Second, successful platforms tend to be “open”, meaning chiefly that their owners encourage other firms, including competitors, to build applications that run on them. Bosch, Trumpf, Siemens and others claim to be open, but it is not clear how welcoming they will be in practice. German bosses tend to think that they can offer all the necessary services themselves and do not like the idea of inviting others onto their platform. German carmakers could probably build the dominant operating system for vehicles if they overcame their rivalries. But it is unclear whether BMW, Daimler and VW’s Audi subsidiary will turn Here, the digital-maps business they are buying from Nokia, into a bona fide platform. Such proprietary thinking also makes German industrial firms reluctant to produce open-source software, or to give away other forms of intellectual property, in the way that Tesla, an American maker of electric cars, has done with its patents in an effort to spread its technology.

If that offers some comfort to German manufacturers, it only goes so far. First, platforms thrive when other firms, developers and customers make use of them. Most big IT companies have grown up managing such “ecosystems”, but this will not come easy to manufacturers. As Sangeet Paul Choudary, a technology analyst, puts it, they are steeped in “pipe thinking”: firms order supplies, fashion them into products and then send them towards customers. Now they must think more like a gardener, and maintain a park which attracts and retains other firms and customers, in order to flourish.

Yet the economics of the markets for industrial equipment, and the other business-to-business products many German firms make, are different, explains a report this month by Stiftung Neue Verantwortung, a think-tank, and other organisations. These markets move more slowly and are more complex. The expertise of incumbents is hard to replicate and, more important, in many cases they control access to the data their products generate. As a result, network effects are not as strong in these sorts of business.

Fortunately for many German industrial firms—and, for that matter, their counterparts in other countries—they have more time to adapt than consumer firms. In consumer markets, digital newcomers can quickly become dominant by exploiting the “network effects” in some technology platforms: the more people use them, the more apps and other offerings they generate, and the stronger they get versus any rivals. This is why German makers of cars and heating equipment look with trepidation at Google’s work on self-driving cars and intelligent thermostats.

The first aim of this bureaucracy is to produce templates and test beds for trying out innovative digital services, and to publicise interesting examples. Its second aim is to convince two groups of the need for change: the smaller among Germany’s Mittelstand firms, and the industrial trade unions, which, under the country’s “co-determination” model of labour relations, have a say in many management decisions. “Creating acceptance is key,” says Matthias Machnig, a senior official who leads the Industrie 4.0 effort at the ministry of economic affairs.

Does Deutschland do digital?

SINCE it was founded in 1923 Trumpf, a family-owned company based near Stuttgart, has had one main mission: making things that make things. It started out with motorised hand shears and other tools to work sheet metal. It then invented fabrication machines with a numerical-control system and later was among the first to use lasers to cut metal. A prime example of a firm from Germany’s industrial Mittelstand that has outgrown the label (which literally means “mid-sized trades”), the firm today has annual sales of €2.7 billion ($3.2 billion) and more than 10,000 employees worldwide.

Trumpf’s roots in metalworking and other hardware stand in stark contrast to what it is trying to achieve next: building a new business purely based on software and data. Unveiled last month, its online offering, called Axoom, connects machines built by Trumpf and others, and uses the data it collects from them to help customers organise their production—for instance, to warn them when they are running out of material or to order it directly from the supplier. Much like smartphones, Axoom will be able to run “apps” from other providers, such as software to schedule workloads, or to predict when machines will need a spare part.

The company’s attempt to redefine itself is emblematic of the leap that manufacturers, in Germany and everywhere else, now have to make. The much-discussed “internet of things” (IoT) is becoming a reality on factory floors: industrial machines and the products they make are increasingly packed with sensors and connected to the internet (see Schumpeter).

As a result, the rules in many industries, from construction equipment to cars, are changing: making things matters less and knowing things more. In many cases the successful companies will no longer be the ones that make the best products, but the ones that gather the best data and combine them to offer the best digital services. And the biggest winners of all may be those that control a “platform”, a layer of software that combines different kinds of devices, data and services, on top of which other firms can build their own offerings—just as Trumpf is trying to do with Axoom.

Mastering this sort of transformation ought to be on the agenda of any country with a big manufacturing base (see chart 1). But nowhere is the sense of urgency more developed than in Germany, where the fear that digitisation threatens its position as a leading industrial nation has been given added piquancy by Volkswagen’s recent emissions scandals. The first half of the battle to master the digital world was lost, according to Timotheus Höttges, the boss of Deutsche Telekom. “The question now is: how do we win the second half?”

Smart services do not have to be closely related to the principal use of the product. A high-end car, for instance, has the digital horsepower of 20 personal computers and generates 25 gigabytes of data per hour of driving, estimates Gabriel Seiberth of Accenture, a provider of IT and consulting services. Rather than just building vehicles, he argues, carmakers should be thinking about how to provide, and profit from, the entertainment and e-commerce services that could be offered on the screens inside a vehicle. “The car will become a central part of a person’s digital life,” says Mr Seiberth.

That strikes a particular chord in Germany. Some fear that its carmakers, which directly or indirectly employ one in seven workers nationwide, could be demoted to low-margin metal-bashers, while American tech giants make most of the money by providing the software and the in-car entertainment—and perhaps, in time, designing the cars themselves.

Apple and Google are pressing carmakers to install the operating systems they have designed for cars’ entertainment systems, which in practice will suck up all sorts of other data about the car and its occupants. Carmakers are realising that to give up this territory would risk their “sovereignty over the data” generated by their vehicles, in the words of Wilko Stark, Daimler’s strategy chief. They could end up like Samsung, whose profits from smartphones are limited by the fact that it depends on Android, Google’s mobile operating system.

It is not just German carmakers which worry about this sort of future, however. The American tech giants are also trying to establish platforms for the “smart home”, which collect data from appliances, heating systems and the like. “Whoever controls the platforms will rule the future,” declares Henning Kagermann, the head of Acatech, who coined the term “Industrie 4.0” for German industry’s collective efforts to make the transition to a digital, internet-connected future.

Despite such concerns, in some ways Germany’s industry seems well prepared for the rise of services and platforms. Its bosses are alive to the threat. Axel Springer, a publishing giant, started a trend among German firms by having some of its top people live in Silicon Valley for several months. The experience led the firm to invest in a consulting firm, gratingly called Hy!, which introduces old-economy executives to startups and helps them plan their digital transformation.

Some firms have already acted on the insight that digital platforms are crucial for their futures. One is Trumpf. Another is Klöckner, a metals trader, which has created a platform to connect steelmakers with construction firms and other customers. Germany’s engineering and manufacturing giants, too, have started to take platforms seriously: Bosch now offers an “IoT Suite” to help other companies create new services around connected devices. Deutsche Telekom has teamed up with other firms to establish Qivicon, a smart-home platform to rival Apple’s and Google’s.

The government is trying to help. It has taken the lead in Industrie 4.0, creating around it an unwieldy structure that ropes in everyone from trade associations and ministries to unions and academics. Only in a country with Germany’s corporatist tradition would an effort to make businesses more agile and responsive to change be so stuffed with steering committees, working groups and advisory boards.