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With profits rising and productivity slowing in the face of near-zero interest rates, advocates of income redistribution have conveniently seized on the hypothesis that an increase in crony capitalism and monopoly rents have increased income inequality and slowed middle- and working-class wage growth (Barkai, 2016; De Loecker et al., 2018; Gutierrez and Philippon, 2019; Reich, 2015). If cronyism misallocates resources, theoretically, policy-makers can redistribute income without significantly slowing growth and diminishing prosperity.

By providing no alternative explanation for rising income inequality, proponents of free markets leave such claims largely unaddressed. Their beliefs that higher taxes, more regulation, diminished incentives, and growing government slow growth do not explain the outsized success of so-called superstar companies and the top 0.1 percent. Their reluctance to blame trade with low-wage economies, low-skilled immigration, or technological innovation for slowing low-skilled wage growth leaves charges of increased cronyism unanswered.

Counterevidence of Growing Cronyism

If America’s income inequality—the high-wage economy with the most income inequality—is solely the result of misallocated resources, US productivity growth should have slowed relative to other high-wage economies with more equally distributed income. Instead, America’s productivity has grown faster than that (p.263) of other high-wage economies since the early 1990s—the opposite of this hypothesis’ prediction (OECD “GDP per Hour Worked,” 2019)— despite these economies enjoying unearned gains from the outsized contribution of American innovation, defense expenditures, and pharmaceutical pricing.

Company and industry evidence are also inconsistent with growing cronyism. Market share leaders in consolidating sectors who have invested more than competitors, chiefly in information technology, research, and development, and other intangible assets, have largely driven US productivity growth (Autor et al., 2019; Manyika et al., 2018). These leaders have gained share and are more global in scope (Autor et al., 2019; Manyika et al., 2018). Increased industry consolidation correlates with increased investment in information technology and intangible assets, greater patent intensity, faster productivity growth, and declining labor share (Autor et al., 2019; Bessen, 2019; Manyika et al., 2018). These company and industry trends are common across all high-wage economies despite different antitrust regimes and bargaining strengths of labor unions (Autor et al., 2019). Prices have not risen significantly, and output has expanded faster in increasingly consolidated sectors than in the rest of the economy (Ganapati, 2019; Peltzman, 2018; Autor, 2019). None of this evidence is indicative of oligopolistic behavior, but rather that leaders and followers are competing fiercely. Counterfactual arguments—chiefly whether companies should have borrowed and invested more when profits were high, interest rates were low, and market values exceeded replacement costs—are addressed later in this chapter.

While consolidation has occurred across all industry sectors, it has largely occurred at levels of concentration below levels that antitrust experts view as anticompetitive (Shapiro, 2017). Ironically, consolidation has largely occurred in fragmented and geographically decentralized sectors, such as retail, restaurants, and wholesale distribution, where expansion by national competitors into local markets has increased competition (Hsieh et al., 2016; Rossi-Hansberg et al., 2019). No surprise, McKinsey Global Institute finds that so-called superstar effects—the growing success of the most successful companies—account for less than 20 percent of the decline in labor’s share of gross domestic product (GDP) (Manyika et al., 2019), of which only a portion would be unearned.

Rising North American profitability largely stems from the growth of idea-intensive companies with near-zero marginal costs and with profitability twice that of capital-intensive companies with emerging market competitors who have squeezed their profits (Dobbs et al., 2015). But the high-tech sector has been in turmoil, the opposite of cronyism. Excluding Microsoft, the 15 largest NASDAQ technology companies at the peak of the internet bubble have lost almost 60 percent of their market value. Meanwhile, half of today’s largest 15 NASDAQ companies, with a combined market capitalization of $3.5 trillion, were worth less than $100 billion in 2000 (Moritz, 2017). With turnover like that, it is hard to see cronyism at work. Instead, competitive advantages derived from intellectual property have been surprisingly fragile and short-lived.

(p.264) More broadly, nearly half of so-called superstar companies have lost their superstar status in a single business cycle over the past 30 years (Manyika et al., 2018). Nor does there appear to be any erosion in the contestability of market leadership (Manyika et al., 2018).

Were cronyism rising, we should also expect to see an increasingly entrenched status quo. We see the opposite, as Gerald Auten and David Splinter have shown in Chapter 5 of this volume. The turnover of the Fortune 500 (Foster and Kaplan, 2001), CEO tenures (Conference Board, 2013), and the Forbes 400 richest Americans (Kaplan and Rauh, 2013) have also increased. Today, the Forbes 400 richest Americans are increasingly self-made entrepreneurs, not heirs (Kaplan and Rauh, 2013). Most top 0.1 percent earners are undiversified working-age owners of closely held midmarket, skill-intensive businesses that lose almost all of their profits when the owner retires or dies (Smith et al., 2019).

Evidence of rising cronyism is lacking. The largest and most successful companies invest more, produce more innovation, grow faster, pay higher wages, and provide more spillover benefits than the rest of the economy (Atkinson and Lind, 2018; Autor et al., 2019; Babina and Howell, 2019; Moretti, 2019). We are fortunate to have them. It would be reckless for the United States, or any other economy, to dismantle its hard-won success given the lack of compelling evidence supporting rising cronyism.

Consequences of a Constrained Supply of Properly Trained Talent

Given that income inequality has risen worldwide concurrent with the commercialization of information technology, growing international trade, immigration, and other structural trends, such as the decline of marriage, hypotheses for growing inequality must address these factors. Information technology has opened a window of investment opportunities to create new technology, deploy the technology to gather better information, and use the information to make better decisions and produce innovation. With investment opportunities exceeding the supply of properly trained talent needed to capitalize on them, the 80th to 99th percentile’s share of pretax income has increased modestly (Congressional Budget Office [CBO], 2019; Blau and Kahn, 2005; Benzell and Brynjolfsson, 2019). So have returns to education in America relative to other high-wage economies (Organisation for Economic Cooperation and Development (OECD) Education at a Glance, 2019).

At the same time, trade with low-wage economies and low-skilled immigration have provided an unconstrained supply of low-skilled labor. Aging demographics and slowing population growth, especially in high-wage economies, have also reduced the need to expand capacity with existing technology and, (p.265) together with trade surpluses (Conard, 2016), flooded markets with risk-averse savings (Summers, 2014). A significant decline in the cost of capital goods further reduces savings constraints (Summers, 2014; International Monetary Fund [IMF], 2015). As a result, properly trained talent, rather than savings and low-skilled labor, now constrains growth. Declining research productivity (Bloom et al., 2017; Gordon, 2016), the end of one-time productivity gains from saturating high-wage populations with education, and the failure of other high-wage economies to contribute their share of innovation, exacerbate constraints on the supply of talent.

Constraints on the supply of talent are particularly acute in the United States. On an OECD-administered academic skills test, 8.5 percent of adult Americans score at the highest numeracy levels, and 28.7 percent score at the lowest skill levels. America has 0.3 high-scoring adults for every low-scoring adult. In contrast, 14.2 percent of German adults score at the highest levels and 18.4 percent score at the lowest. Astonishingly, Germany has nearly three times more high-scoring adults per low-scoring adult than the United States. Scandinavia has more than four times as many. Japan has nearly eight times as many (OECD “Survey of Adult Skills,” 2019). America has half as much talent per capita as the other most successful high-wage economies and twice the supervisory needs. Cross-country comparisons that fail to account for these enormous differences—comparisons of wages and productivity as information magnifies the value of skill, for example—produce grossly distorted conclusions.

A constrained supply of properly trained talent has cascading consequences. Markets have logically dedicated a greater share of properly trained talent to increasing the productivity of constrained talent. Previously, talented workers created mass-market products produced by domestic blue-collar consumers—an allocation of talent that benefited the middle and working classes. Now they create information and information technologies, such as spreadsheets, for decision-makers and innovators. This reallocation of talent disproportionately increases the productivity of the most productive workers and consumes talent that would otherwise increase the productivity of domestic lesser-skilled workers. This slows low-skilled productivity growth and growth elsewhere in the economy.

When the supply of low-skilled labor is unconstrained, increases in high-skilled productivity disproportionately raise low-skilled employment rather than low-skilled wages. This spreads constrained talent over a greater supply of labor, which slows low-skilled productivity and wage growth further. Since the early 1980s, US employment, excluding offshore workers, has grown twice as fast as in Germany and France and three times faster than in Japan (OECD “Labour Force,” 2019). Today more than 42 million foreign-born adults live in the United States (Radford, 2019). Low-skilled immigrants, offshore workers, and properly trained talent have been the chief beneficiaries of this growth.

(p.266) When the window of investment opportunities exceeds the constrained supply of talent, additional high-skilled productivity disproportionately increases investment to raise high-skilled productivity rather than expanding high-skilled resources devoted to raising low-skilled productivity, especially when insights that make high-skilled workers more productive are harder for competitors to copy than innovative uses for low-skilled labor.

A constrained supply of properly trained talent not only limits the discovery of investment-worthy ideas, it also increases risk by restricting the supply of engineers and managers tasked with reducing costs and risks. The allocation of a constrained supply of talent to attractive investment opportunities created by the advent of information technology increases the risk of other investments. Higher risks consume investors’ and talent’s willingness and capacity to bear risk. This occurs even more when the creation of valuable information-related innovation is riskier than other investment opportunities, and even when those risks are unsystematic, since a large portion of risk-takers—entrepreneurs, for example—do not enjoy the luxury of diversification. Limits on the economy’s willingness and capacity to take risk lower interest rates in the face of an unconstrained supply of risk-averse savings.

The advent of information technology has opened a window of investment opportunities that has constrained the supply of properly trained talent at a time when trade with low-wage economies, low-skilled immigration, trade deficits, and aging demographics have relieved constraints to low-skilled labor and capital. The economy has logically allocated an increasing share of talent to raising the productivity of constrained resources, namely talent. This allocation of talent slows the growth of low-skilled productivity and other endeavors not aligned with increasing high-skilled productivity.

Value of Returns Exceeding the Cost of Capital

Unlike investments that expand capacity using existing technology, hard-won innovation bubbles up unpredictably from a large pool of costly failure. The prospect of returns greater than the cost of capital is the chief justification for risk-taking. If innovations were easy to copy, investors would wait for others to innovate, and the rate of innovation would grind to halt.

Fortunately, information-related innovations have captured first-mover advantages and other economies of scale that are difficult for competitors to duplicate, even more so when talent constrains growth and slows the convergence of followers to the technological frontier, which we have seen (Andrews et al., 2016; Manyika et al., 2018). Increasingly clever patenting strategies may have also slowed followers (Akcigit and Ates, 2019). Consistent with these economics, returns exceeding the cost of capital are confined to the most successful companies (Manyika et al., 2018).

(p.267) A larger economy increases the value of success, which spurs increased risk-taking when success captures excess returns. As the economy grows larger relative to the individuals who compose it, success will grow larger relative to the incomes of median workers—teachers, truck drivers, and nurses—whose wages are constrained by the number of customers they can serve.

At the same time, information-derived innovation scales with less cost and investment than the capital- and low-skilled labor-intensive manufacturing of yesteryear. Successful information technology startups, such as Google and Facebook, have scaled to economy-wide success without much need for investors or labor. When the production of intangible assets requires risk-taking and success produces excess returns, lower costs and larger payoffs for success can spur increased risk-taking. This holds even if the value of innovation is declining relative to the economy and productivity growth is slowing. Consistent with the growing need to take risk, the success of companies has grown increasingly dispersed (Berlingieri et al., 2017).

Improbable success limits talent’s ability to capture excess returns unless talented workers bear the cost of failure. Rather than demanding premium pay, properly trained workers have accepted less pay to gain valuable exposure to the technological frontier (Tambe et al., 2019). In addition to more interesting and prestigious work, this exposure provides invaluable on-the-job training, a network of valuable relationships with brilliant colleagues, and valuable ideas that increase the likelihood of entrepreneurial success (Babina and Howell, 2019; Moretti, 2019). Talented workers have also shared risk by accepting equity in lieu of pay, which has distorted traditional measures of labor’s share of GDP (Eisfeldt et al., 2019). Uncertain returns, rising equity grants, pay-for-performance, and entrepreneurialism have concentrated returns extracted by talent in a small group of successful risk-takers. As such, rising income inequality is largely confined to the top sliver of success—the 0.1 percent or 0.01 percent (Auten and Splinter, 2018; Gold, 2017).

Successful risk-taking has gradually built institutions at the technological frontier. In turn, exposure to the technological frontier has increased the expected value of success for talented and well-trained risk-takers (Babina and Howell, 2019; Moretti, 2019). In America, fewer restrictions on creative destruction, economies of scale afforded by a larger economy and common language, and greater R&D defense spending increase the payoff and likelihood of successful risk-taking.

With higher expected payoffs, talented Americans have received better training, worked longer hours (Bowles and Park, 2005; Kuhn and Lozano, 2008; OECD “Hours Worked,” 2019), and taken more entrepreneurial risk than their counterparts in Europe and Japan. A larger pool of determined risk-takers has produced a greater number of outsized successes.

The share of talented risk-takers and the productivity of America’s most productive workers are far greater than many economists realize. Despite having (p.268) fewer than half as many high-scorers per capita as other high-wage economies, American entrepreneurs have produced six times as many startups valued at more than $1 billion than has Europe (CB Insights, 2019)—a broad indication of risk-taking and innovativeness. Similarly, the market values of America’s high-tech companies—an indication of the productivity of its workers at the technological frontier—are astonishingly high compared to German manufacturing companies (“Does Deutschland Do Digital?” 2017). Only in America have the returns been high enough to spur a substantial increase in risk-taking. Fortunately, the rest of the world benefits from America’s success.

Advocates of income redistribution insist that the ongoing success of Silicon Valley in the face of a higher California tax rate indicates that higher payoffs for risk-taking do not increase risk-taking significantly (Hacker and Pierson, 2017; Krugman, 2019), despite a host of evidence to the contrary (Akcigit et al., 2015, 2018; Moretti and Wilson, 2017; Moretti and Wilson, 2019; Rauh, 2019). They disregard the amplifying effect of Silicon Valley on the expected payoff for risk-taking, which overwhelms small differences in state tax rates (Babina and Howell, 2019; Moretti, 2019) and they ignore critical long-term effects that are near-impossible to measure, such as gradual increases in training and risk-taking. Given the higher expected payoffs afforded by proximity to Silicon Valley, and the resulting increase in risk-taking and innovation that Silicon Valley and America enjoy relative to Europe and Japan, it is hard to believe after-tax payoffs do not affect the willingness of people to take risk.

The commercialization of the internet in the 1990s similarly raised expected payoffs for successful innovation far in excess of tax increases and motivated increased risk-taking, as evidenced by the rising number of internet startups. Armies of Hollywood aspirants, increased aggressiveness of World War II fighter pilots in the face of others’ success (Ager et al., 2016), and swelling participation in state lotteries as payoffs rise all suggest that the value of fame and fortune spurs individuals to take risk.

When risk-taking produces success, high ex-post returns to success are hardly evidence of unearned profits. Ex-ante returns are the relevant measure of whether profits have been earned. Since 2000, venture capital—an indicator of returns to innovation more broadly—has been mediocre at best (Ivashina and Lerner, 2019), especially given the unsystematic risks faced by entrepreneurs and employees.

For the same reason, high ex-post rewards for successful risk-takers will not necessarily motivate increased investment or risk-taking, especially when competitors already inhabit previously unoccupied niches. Good fortune does not prove additional risks are worth taking. Expected ex-ante returns drive behavior. When success entails risk, we cannot conclude that the high ex-post stock market values relative to replacement costs should have increased investment but for rising cronyism.

(p.269) As the productivity of researchers and innovators declines, expected ex-ante returns and risk-taking will decline unless the payoffs for success increase. With research productivity declining as investment has continued unabated, we should celebrate rising payoffs for successful risk-taking as good fortune.

There is ample evidence of the declining productivity of researchers and innovators. Not only has the growth of multifactor productivity slowed, but the productivity of researchers also appears to be declining as science grows increasingly complex (Bloom et al., 2017). Additional economy-wide productivity gains from general-purpose information technology, such as artificial intelligence, have proved difficult to create (Brynjolfsson et al., 2018; Gordon, 2016). While the growth of education in the rest of the world has increased the number of scientists, engineers, and business executives searching for and implementing innovation, so far, the United States alone—where properly trained talent is constrained—has predominately driven the technological frontier. Growing payoffs for success are critical for spurring investment in the face of declining research productivity.

While productivity growth has slowed, there appears to be no significant slowdown in the advancement of the technological frontier (Andrews et al., 2016). Instead, venture capital investment and investment by Facebook, Apple, Microsoft, Google, Amazon, and others in Silicon Valley now exceed their 2000 peak (Frothy.com, 2014; National Venture Capital Association, 2019.). Without rising payoffs for successful risk-taking, investment would decline as research productivity has declined. Fortunately, Google cannot afford to neglect investment in quantum computing because the consequences of someone else’s success are too risky. Redistributing the value of success eliminates the incentive to make risky investments.

More broadly, while investment in capital goods slowed relative to GDP in the aftermath of the financial crisis, it has not slowed over the long term when economists properly adjust tangible investment for the disproportionate deflation in the price of capital goods (Summers, 2014; IMF, 2015). As the economy has shifted from capital intensity to knowledge intensity, investment has shifted from plant and equipment to salaries of properly trained talent tasked with designing a better future (Corrado et al., 2012; Haskel and Westlake, 2018). When economists account for these changes, there has been no downward trend in investment relative to GDP. Failed risk-taking also washes away accumulated investment, leaving true investment understated.

Skeptics point to declining startups as evidence of declining risk-taking (Decker et al., 2014) and slowing productivity growth, even though productivity growth can slow for a litany of unrelated reasons and investment will continue if the returns for success are large enough. While the number of startups has declined, high-potential US startups—chiefly high-tech startups—have neared their 2000 peak, a peak that was far above trend line (Guzman and Stern, 2019). Consolidation in the retail, restaurant, and distribution sectors curtailed the (p.270) vast number of mom-and-pop startups that largely allocate demand between competing firms and do little to advance the technological frontier and grow productivity. With its thirst for talent, the economy gobbles up, trains, and redeploys potential “mom-and-pop” talent, leaving a vacuum of startups in its wake (US Bureau of Labor Statistics “National Business Employment Dynamics Data by Firm Size Class,” 2019).

Improbable innovations bubble up unpredictably from a large pool of failure. Outsized rewards are sine qua non for risk-taking. As research productivity declines, we need higher returns to motive the risk-taking that produces it. We do not need outsized returns to motive success per se; we need them to motive a large pool of failure.

Success produces institutional capabilities—the expertise, economies of scale, and returns—needed to explore and advance the technological frontier. Exploration of the frontier produces valuable spillover that benefits the rest of the economy. Spillover raises the rewards for risk-taking, which motivates further risk-taking.

Given the failure of Europe and Japan to innovate during this time when information technology is transforming the economy and a constrained supply of talent slows growth, it would be reckless to confiscate outsized rewards for success, whether from companies or individuals. The argument that outsized returns were unexpected ex ante ignores the armies of American risk-takers who have followed in the wake of the success of Bill Gates, Steve Jobs, and others like them. Redistributing the ownership of future cash flows to consumers will not only demotivate risk-taking, but it will also diminish the amount of risk and investment owners demand businesses take. Less risk-taking and investment will slow growth and diminish prosperity.

Reconciliation with Low Interest Rates

One of the better arguments for rising cronyism questions why profits in excess of the rental cost of capital—chiefly assets times the real interest rate—have risen since the 1980s. Leaving aside the difficulty of subtracting the unreproducible profits of successful risk-takers from the broader pool of business profits, some say that rising cronyism may have allowed increased profits.

Historical evidence, however, runs contrary to this argument. Excess profits as a share of GDP were higher in the 1950s and 1960s, when industry consolidation was lower than it is today. They reached their lowest point in the 1970s and 1980s, when real interest rates soared, and they have risen as interest rates have fallen (Karabarbounis and Neiman, 2018; Rognlie, 2018). Rather than being correlated with rising cronyism, excess profits have been inversely correlated with interest rates. Low interest rates, rather than rising cronyism, appear to give (p.271) rise to excess profits. The same pattern occurred in real estate where there should be little, if any, ability to diminish competition (Karabarbounis et al., 2018).

When rates fell after the 1980s and excess profits grew, one might have expected increased borrowing to strengthen competition. An alternative version of the argument asks why business did not borrow more when real interest rates fell and profits were robust unless cronyism prevented it. A glut of savings, a constrained supply of talent, and excess returns for successful risk-taking provide a more plausible explanation than rising cronyism for why business did not borrow more.

Secular stagnation argues that aging demographics slow growth and increase savings relative to a diminished need for capacity-expanding investment (Summers, 2014). Savings in excess of investment reduce interest rates and slow growth.

Trade deficits add to the glut of savings. Manufacturing-driven economies with aging demographics and more domestic savings than their demand for investment—namely China, Germany, and Japan—deploy otherwise unneeded savings by running trade surpluses, largely with the United States, to avoid employment and wage declines.

Had the domestic demand for savings pulled offshore savings into the US economy via trade deficits, interest rates would have risen as trade deficits rose. For decades, real interest rates have fallen as trade deficits have risen (Federal Reserve Board “10-Year Treasury Constant Maturity Rate,” 2019; OECD “Balance of Payments: Current Account Balance as a % of GDP,” 2019). This indicates that an increase in the supply of offshore savings has fueled trade deficits.

Reluctance to displace workers catches surplus exporters in a vicious cycle. Manufacturing productivity gains—gains exporters need to remain competitive—require larger trade surpluses to achieve a given level of employment. Interest rates must fall to equilibrate the supply and demand for savings. Otherwise, rising currency exchange rates will render the price of their exports unattractive. While trade deficits have declined (OECD “Balance of Payments: Current Account Balance as a % of GDP,” 2019), so far, near-zero interest rates have not fully deterred offshore savers.

Rather than export precious risk-bearing capital, surplus exporters have bought low-risk US government-guaranteed debt, displacing domestic risk-averse savers. With an increasing share of manufacturing capacity moving offshore, America has little need for risk-averse savings best suited for low-risk capacity expansion. Innovation-driven growth needs risk-bearing capital willing to suffer significant losses, which surplus exporters have been reluctant to provide.

With its constrained supply of properly trained talent preoccupied with more productive endeavors—namely, capitalizing on risky information-related opportunities—business has had limited appetite for bearing the additional risk of borrowing and investing risk-averse savings. Risk-averse savings flowed into (p.272) real estate (Rognlie, 2015) and through real estate to “subprime consumption” prior to the financial crisis as homeowners borrowed against the rising value of their homes and consumed the proceeds (Mian and Sufi, 2015). At the same time, Germany financed Greek consumption. China built empty apartment buildings (Poon, 2019). Japan financed fiscal deficits. Since the crisis, US fiscal deficits and the resulting increase in low-risk government-guaranteed debt have largely consumed proceeds from the repayment of mortgage debt (Federal Reserve Board “Financial Stability Report,” 2019).

Business’ failure to take the risks to borrow and invest this flood of risk-averse savings is hardly evidence of rising cronyism, especially when, at every point in the economic cycle, business borrowing had already reached historical highs relative to GDP (Federal Reserve Board “Financial Stability Report,” 2019). With an abundant supply of risk-averse savings relative to the demand for low-risk investment, growth has been lackluster and real interest rates have remained low while the valuation of well-positioned companies with hard-to-replicate capabilities near the technological frontier have soared.

Structural Trends Slowing Low-Skilled Productivity Growth

Were the success of superstar companies and the 0.1 percent not growing concurrently with the slowing growth of lesser-skilled wages, claims that the success of one comes at the expense of the other would be less persuasive. While the allocation of constrained talent to producing innovation rather than raising low-skilled productivity likely contributes to the relative slowing of low-skilled productivity growth, structural changes independent of information technology, chiefly an increase in the supply of low-skilled labor and its substitutes, have slowed the growth of lesser-skilled wages relative to GDP in high-wage economies.

The growth of information disproportionately increases high-skilled productivity. Algebraically, this slows low-skilled wage growth relative to GDP, even if low-skilled workers are better off from otherwise faster growth.

The allocation of constrained talent to endeavors other than increasing the productivity of low-skilled workers slows low-skilled productivity growth. This is especially acute in the United States given the skew of its demographics toward low-skilled workers (OECD “Survey of Adult Skills,” 2019) and America’s outsized success producing innovation.

As high-wage economies have automated and offshored manufacturing and shifted employment to domestic services, properly trained talent has migrated to expert-based services. Talented workers have increasingly clustered in companies largely composed of high-paid workers, such as Microsoft and Goldman Sachs (Song et al., 2018), with the know-how to magnify the productivity of the most (p.273) productive workers. Meanwhile, companies such as Apple and General Motors have increasingly outsourced low-skilled labor to companies with a preponderance of low-paid workers. This sorting has produced large shifts in the allocation of skill between companies.

A large share of low-skilled workers now works in the low-skilled service sector where, aside from distribution, productivity growth has been significantly slower (Remes et al., 2018) without the capital-intensive centralized “command and control” structure of manufacturing. With less than 9 percent of the US workforce left in manufacturing, faster manufacturing productivity growth contributed less to the productivity growth of lower-skilled workers (US Bureau of Labor Statistics “All Employees: Manufacturing,” 2019; US Bureau of Labor Statistics “Manufacturing Sector: Real Output,” 2019).

Dividing companies that predominately produce information, such as media, finance, and information technology, with their largely white-collar workforces, from companies that predominately produce physical products, reveals large differences in productivity growth and levels of investment in information technology. The information-oriented companies have invested substantially more in information technology and grown productivity 2.7 percent per year over the past 15 years. The physical labor-oriented companies have invested less in information technology and have only improved productivity 0.7 percent per year (Mandel and Swanson, 2017). The latter group includes logistics, distribution, and manufacturing—sectors where productivity has grown substantially faster than the economy as a whole (Mandel and Swanson, 2017; Remes et al., 2018). Thus the productivity of the rest of this group—sectors that have added workers—has grown more slowly than 0.7 percent per year. These differences surely reflect differences in the productivity of high-skilled knowledge workers and low-skilled workers more broadly and are directionally consistent with other estimates of differences in high- and low-skilled productivity growth (Lazear, 2019).

At the same time, disproportionate increases in the supply of low-skilled labor from automation, trade with low-wage economies, and low-skilled immigration increase the relative supply of lower-skilled workers. An increase in the supply of low-skilled labor lowers the marginal product of labor and spreads constrained talent over a greater number of low-skilled workers, which slows low-skilled productivity growth. An increasing share of talent must be devoted to engineering and maintaining automation for example. The arrival of low-skilled immigrants spreads constrained talent, a portion of which is devoted to low-skilled supervision, over a greater number of workers. Even with balanced trade, high-wage economies largely buy low-skilled offshore labor and sell high-skilled labor to the rest of the world. This puts downward pressure on low-skilled wages and upward pressure on high-skilled wages. On net, talented engineers at companies such as Apple and Ford Motor Company increasingly design products and factories that employ offshore workers.

(p.274) Low-skilled domestic workers disproportionately bear more of the cost and enjoy less of the benefits from trade with low-wage economies and low-skilled immigration. To the extent that lower priced goods offset the downward pressure that trade and immigration put on wages, low-skilled workers bear most of the cost of lower wages but capture only 40 percent of the benefits from lower prices. The top 20 percent of earners capture 40 percent of the benefits. Retirees capture 15 percent, and the non-working poor capture 5 percent of the benefits (Conard, 2016, see Figure 10.1). The disproportionate sharing of costs and benefits increases income inequality.

Trade deficits add to the supply of low-skilled labor. They also add substantially to the glut of risk-averse savings. Prior to the financial crisis, the incremental supply of offshore savings indirectly funded increased consumption through increased mortgage lending (Federal Reserve Board “Financial Stability Report,” 2019; Mian and Sufi, 2015). The pressure to consume the large influx of risk-averse savings to maximize employment and wages indirectly destabilized the banking system (Conard, 2012; Reinhart and Rogoff, 2009)—a naturally unstable equilibrium—which led to the financial crisis and deep recession. Deleveraging by fearful businesses and households (Federal Reserve Board “Financial Stability Report,” 2019) in the wake of the financial crisis produced the slowest recovery since the Great Depression. With employers firing marginal, easy-to-replace, low-skilled workers first and rehiring them last, no group has paid a more painful price (Aaronson et al., 2019; Benigo et al., 2015).

When properly trained talent constrains growth, and low-skilled workers are displaced by trade, high-skilled entrepreneurs may never arrive to reemploy workers at high wages, especially if the talent has moved to Silicon Valley and outsourced their blue-collar work to China. Research finds that many towns that have lost manufacturing have been slow to recover lost wages (Autor et al., 2016). The productivity of the rural economy and smaller cities is no longer converging with large cities (Ganong and Shoag, 2017; Giannone, 2017; Winship, 2019). Both are indications that the talent necessary for growth in an information-driven economy has moved away.

Trade with low-wage economies also makes it more difficult for rural Americans to ship their production competitively to faster growing urban economies. Onshore producers cannot compete without productivity gains that minimize domestic labor. Urban migration of talent and trade with low-wage economies isolates rural blue-collar Americans, leaving them with fewer benefits from trade. With less supervisory talent, rural blue-collar service sector productivity has slowed to a crawl.

Soaring real estate prices and other urban costs preclude blue-collar Americans from following high-skilled Americans who are flocking to a handful of fast growth cities—San Francisco, New York, Los Angeles, Boston, and Seattle—at the technological frontier (Erdmann, 2019; Hsieh and Moretti, 2019). Half of American employment gains since 2010 have come from just 20 cities (p.275) (Muro and Whiton, 2018). Low-skilled wages in these cities are two to three times higher than wages in the rest of the country (Moretti, 2010). But landlords have captured a large share of those gains through higher rents (Hornbeck and Moretti, 2018). For the first time, low-skilled after-rent wages are lower in larger cities than elsewhere (Hoxie et al., 2019).

Native-born middle-class workers are now moving away from coastal cities (Ganong and Shoag, 2017; Autor, 2019). Low-skilled immigrants willing to accept low after-rent wages have replaced them. Workers end up sorted by geography, with lesser-skilled Americans precluded from earning higher after-rent wages in faster growing cities filled with high-skilled workers (Clark and Cummins, 2018). We should expect workers to be less supportive of growth that excludes them.

Advocates of low-skilled immigration often ask, “Without low-skilled immigrants, who will do the jobs Americans do not want to do?” This argument ignores the effect of price on the demand for low-skilled labor or the effect of supply on the marginal product of low-skilled labor. If the supply of low-skilled labor were smaller, Chileans would grow fruit for America and, with higher low-skilled wages, the demand for low value-added tasks like landscaping would decline. Farmers might lose their investments, but these shifts would increase the marginal product of domestic low-skilled labor. In turn, low-skilled wages would rise, albeit in a smaller economy with slower growth. It is not hard to see why some workers may prefer that.

Yes, the supply of domestic labor—low-skilled immigrants in the case of America—creates its own demand, but at what marginal product of labor? An unconstrained supply of low-skilled labor will drive the shadow price of labor down to the marginal product of unskilled workers serving unskilled workers.

The value of consumer surpluses derived from an abundant supply of lower-skilled labor may be greater than the foregone wages of low-skilled workers. But, in that case, we should not blame the misallocation of resources or the success of the most productive workers for the slow growth of low-skilled wages relative to GDP. Instead, we should recognize that the productivity of high-skilled workers, especially the productivity of the most productive workers, has put upward pressure on the demand for low-skilled labor.

Other structural trends also slow low-skilled productivity growth. Governments have increased spending as a share of GDP, reduced investment, expanded income redistribution, and increased regulations. These policies slow reported productivity growth.

Onetime gains from testing, sorting, and saturating the population with productivity-enhancing education have waned. Further low-skilled productivity gains from education have been difficult to achieve (US Department of Education “Long-Term Trend Mathematics Assessments,” 2019). With more women investing in higher education, men and women meet and marry through education or subsequent employment, so some children are increasingly (p.276) differentiated through their parents’ educational levels. (Chiappori et al., 2017; Greenwood et al., 2014).

Some proponents of income redistribution insist that the determination of upper income parents, who spend their incomes on tutoring and similar efforts to give their children advantages, blocks the rest of the population from valuable income-enhancing educational opportunities (Reeves, 2017). But this hypothesis does not square with the evidence. Rich, well-prepared students now compete more fiercely for fewer admission slots at prestigious schools (Thompson 2013). Meanwhile, less prestigious universities, where admissions have expanded to meet demand, offer curriculum at all levels of difficulty (e.g., engineering at state universities). Research shows that getting an education and earning an academic credential are akin to running a marathon: your time matters more than which marathon you run (Dale and Krueger, 2011). There is no reduction in the opportunity for any student to earn academic training and credentials at every level of difficulty.

Weakening of the family, religion, community, and respect for authority also undermines productivity growth. Today, 40 percent of American children are born out of wedlock (Winship 2017). Children raised without responsible fathers have achieved less income mobility (Chetty et al., 2014). The weakening of families disproportionately afflicts low-skilled workers.

No surprise, a recent study finds US incomes are more widely dispersed among 25-year-olds than they were in the past and that median 25-year-old incomes have drifted downward. The study also finds lifetime incomes grow similarly across the income spectrum as they have historically and concludes that the wider dispersion of 25-year-old incomes is the chief driver of lifetime income inequality (Guvenen et al., 2017).

Whether or not lower-skilled workers are net beneficiaries of trade, trade deficits, or low-skilled immigration, it seems likely that each of these factors has contributed to income inequality by slowing the growth of lower-skilled wages relative to GDP. Moreover, rising trade, trade deficits, and low-skilled immigration have occurred at a time when information technology constrained the supply of talent. Automation, trade with low-wage economies and low-skilled immigration have spread talent devoted to increasing low-skilled productivity even thinner. Structural factors, such as the saturation of education, assortative mating, the breakdown of the family, and employment shifting from manufacturing to services, have slowed low-skilled productivity growth further.

Conclusion and Recommendations

Each economic era presents its own set of opportunities and challenges. With the advent of information technology, global trade, trade deficits, and low-skilled immigration, properly trained talent, rather than savings or lower-skilled labor, (p.277) now constrains growth. To succeed, the economy must allocate resources appropriately. Where talent previously created products and jobs for lesser-skilled workers, it now creates information to increase the productivity of decision-makers and innovators.

Given the disruption to established businesses that has occurred over the past three decades, it is hard to believe that cronyism has been the predominant driver of increased income inequality. Income inequality and profits have risen across all high-wage economies concurrently with the increased use of information technology, low-skilled immigration, trade with low-wage economies, trade deficits, and structural factors that slow low-skilled productivity growth. Productivity in the United States—the country with the most income inequality—has grown faster than other high-wage economies despite a much smaller share of high-scoring workers. A growing economy relative to the workers who compose it, a reduction in the cost of achieving economy-wide success in today’s information-intensive economy, and increased risk-taking to achieve lottery-like success provide a more consistent explanation for the growing success of the 0.1 percent and superstar companies than does growing cronyism.

An abundance of evidence indicates that growing inequality stems from free enterprise logically rationing constrained resources, as one should expect. Blaming cronyism and unearned rents for income inequality conveniently suggests that high-wage economies can redistribute income without slowing growth. If inequality stems from the logical allocation of resources, we should expect income redistribution to slow growth and reduce prosperity by diminishing the expected payoffs for hard work and successful risk-taking. That is a dangerous outcome given the impending cost of retiring baby boomers, workforce demographics shifting toward lesser-skilled workers, and the growing military threat of China.

Advocates of redistribution point to the competitiveness of Scandinavia to dismiss these concerns (Krugman, 2018). But an abundance of high test-scorers allows Scandinavia to remain competitive despite lower high-skilled productivity than the United States. A more homogeneous Scandinavian workforce with higher scores and greater earning potential than the US workforce also reduces redistribution’s disincentives for low-potential earners to work. Scandinavia’s results do not indicate that the heavy hand of income redistribution will not erode competitiveness elsewhere.

Despite having half as much talent and nearly twice as many low-skilled workers per capita as the next most successful high-wage economies, chiefly northern European economies, no other economy comes close to producing the innovation, prosperity, and demand for middle- and working-class workers as the US economy. Without benefiting from the disproportionate contribution of American-made innovation, those economies would be poorer and slower growing, even more so if they had America’s demographics and resulting shortage of high-skilled supervision.

(p.278) In truth, evidence supporting cronyism as the driver of inequality is lacking. Income redistribution is a riskier policy than its advocates admit, given the success of the United States relative to Europe and Japan.

To accelerate lower-skilled wage growth without slowing growth overall, economic policy must increase the expected payoff for success and raise the ratio of high- to low-skilled workers. If education is unable to produce further improvements, increasing high-skilled immigration will be the only realistic opportunity for improving the ratio of high- to low-skilled workers before the baby boomers retire. Reducing subsidies for studying curriculum where the supply of students far exceeds the demands of customers may ease constraints to properly trained talent, but the results are likely to be small and gradual. Reengineering poorly designed regulations and taxes that lower returns to successful risk-taking may gradually increase the productivity of high-skilled workers, but they will also increase income inequality. Perhaps inequality is a small price to pay for greater prosperity.

In the meantime, education, the media, and government support must prepare lesser-skilled people for success in a lightly supervised service economy that offers a wide variety of opportunities but where the safety net snares vulnerable people. While innovation and trade are essential to long-term growth and competitiveness, tax policy must recognize that low-skilled workers in high-wage economies bear a disproportionate share of the costs of trade, trade deficits, fiscal deficits, and low-skilled immigration while receiving only a portion of the benefits. Many of today’s policies slow the growth of lesser-skilled wages relative to GDP. We can do better.