Macro Roundup

Local Labor Supply

"... Figure 7 reports estimation results for population headcounts. In Figure 7a, we find negative but insignificant impacts of trade exposure on the size of the working-age population, though the point estimates grow as the time interval lengthens. The next three panels of the figure make clear that these negative effects are driven by one age group, those 25 to 39 years old. For adults ages 18 to 24 and 40 to 64, the impact of greater import competition on population headcounts is negative but small and highly imprecisely estimated for all time differences. The finding of no net impact of trade exposure on CZ populations is consistent with Faber et al. (2019), while the greater responsiveness of younger adults echoes Bound and Holzer (2000), who show that less-experienced workers are more relatively more mobile in the face of adverse shocks. For the 2000-2019 time difference, the coefficient estimate of􀀀5:89 (t-value=􀀀2:52) indicates that when comparing CZs at the 25th and 75th percentiles of trade exposure, the more-exposed CZ would have a􀀀3:89 (􀀀5:89 ) percentage-point larger decrease in headcounts for this age group. For comparison, the 75th- 25th percentile difference in population growth across CZs for individuals ages 25 to 39 over 2000 to 2019 was 20:96 (= 16:08 + 4:84) percentage points. Cross-CZ spillovers transmitted via net migration appear to be modest and concentrated on a narrow age group....The impact of trade exposure on the total working-age population is negative for both the 2000-2010 ( =􀀀2:42, t-value =􀀀1:92) and 2000-2019 ( =􀀀3:47, t-value=􀀀1:84) time differences, and marginally significant in each case. When we examine the impact on the native-born population, we find a smaller and much less precisely estimated effect: the impact coefficient for 2000 to 2019 is􀀀0:75 (t-value =􀀀0:79). This contrasts with impacts on the foreignborn, for which greater import competition significantly reduces population headcounts over 2000 to 2019 ( =􀀀 6:79, t-value =􀀀2:05). When looking at age subgroups within these populations, we see negative significant impacts of import competition on native-born workers ages 25 to 39 ( =􀀀5:03, t-value =􀀀2:29), which aligns with the results in Figure 7, and on foreign-born workers ages 40 to 64 ( =􀀀12:70, t-value =􀀀2:08). Whereas native-born labor-supply responses are strongest for younger workers, for the foreign-born they are strongest for older workers…”

"... Estimation results appear in Figure 8, where outcomes are in terms of log income and transfers relative to the total population of a CZ, except for total labor compensation, which is relative to wage and salary employment.39 The impact of exposure to import competition on personal income per capita in Figure 8a is negative at all time horizons and precisely estimated for most time differences from 2000 to 2014 forward. Negative effects reach their peak for the 2000 to 2015 time difference, for which the impact coefficient is􀀀3:64 (t-value =􀀀2:55)…”

"... Figure 9 presents estimates in which we divide the sample of CZs into groups based on whether the share of the college-educated in their working-age populations was above or below the population weighted national median in 2000. There are 336 CZs in the former group and 386 in the latter group.We consider four outcomes: the manufacturing employment-population ratio, the total wage and salary employment-population ratio, the log working-age population, and log personal income per capita. To keep the time horizon the same across outcomes, we evaluate time differences from 2001 to 2002 to 2001 to 2019. To control the false discovery rate when evaluating differences in coefficient estimates across sample splits, we compute and display minimal Benjamin-Hochberg q-values based on the number hypotheses being tested. Although both higher and lower-educated CZs experienced declines in manufacturing employment, the negative impacts of trade exposure on overall employment in Figure 5 are concentrated in CZs with relatively few college-educated workers, as shown in Figures 9a and 9b. These results are consistent with those in Bloom et al. (2019), who study the 1992 to 2012 time period. For the 2001 to 2019 horizon, the first two figures show that in less-educated CZs, a one percentage point increase in import penetration over 2000 to 2012 predicts a 1:74 (t-value =􀀀4:07) percentage point decrease in the manufacturing employment-population ratio and a 2:47 (t-value =􀀀3:59) percentage point decrease in the total wage and salary employment-to-population ratio. Across all CZs (see Figure 5), trade-induced changes in manufacturing and total employment-population ratios are very similar at long horizons, indicating that employment impacts on non-manufacturing employment are null. For CZs with relatively few college workers, the substantially larger impact on total employment than on manufacturing employment reveals a negative impact of trade exposure on non-manufacturing employment, as shown in Appendix Figure A17. Despite manufacturing job losses being compounded by non-manufacturing losses in these CZs, there is no effect of trade exposure on the log working-age population (Figure 9c). It thus appears that more trade-impacted CZs with fewer college-educated workers did not experience differential out-migration, though they did experience larger declines in personal income per capita, as shown in Figure 9d. Since economically-motivated migration would tend to mitigate the local disemployment effects of trade exposure, one interpretation of these results is that the lack of migration is both symptom and cause of the slow adjustment process. In CZs with more-educated working-age populations, the pattern of adjustment is qualitatively different. Impacts of trade exposure on manufacturing employment (Figure 9a) are negative, but somewhat smaller and less precisely estimated. Impacts on the total wage and salary employment population ratio are small and imprecise for short time differences and then become large, positive, and marginally significant for long time differences. For the 2001-2016 time difference and beyond, we easily reject that impact coefficients for wage and salary employment-population are the same in more- versus less-educated CZs. This trade-induced increase in the total employment-population ratio must imply a corresponding positive impact of trade exposure on the non-manufacturing population ratio, as seen in Appendix Figure A17. As critically, more-educated CZs adjusted to adverse trade shocks in part through net outmigration. For all time differences except 2001 to 2006, we reject that impact coefficients on the working-age population are equal for more versus less-educated CZs. At the 2001 to 2019 time difference in more-educated CZs, a one percentage point increase in import penetration is predicted to cause a 9:13 (t-value =􀀀3:31) percentage point decrease in the working-age population, or an annual population decline of approximately one-half a percentage point. The impact coefficient on log non-manufacturing employment at the 2001 to 2019 time difference of 6:04 (t-value = 2:37, Appendix Figure A17b) implies that more of the increase in the non-manufacturing employment population ratio occurred through the out-migration of labor rather than through greater job growth. Like less-educated CZs, more-educated CZs also see negative impacts of trade exposure on personal income per capita (Figure 9d). Distinct from less-educated CZs, these impacts reach their maximum negative value for the 2001 to 2012 time difference and then diminish over time, becoming close to zero for the 2001 to 2016 horizon and beyond…”

David Autor, David Dorn and Gordon Hanson, "On the Persistence of the China Shock," Brookings Papers On Economic Activity, September 9, 2021, https://www.brookings.edu/wp-content/uploads/2021/09/On-the-Persistence-of-the-China-Shock_Conf-Draft.pdf

David Autor returns to the China stock and finds the initial impact of the China shock has been persistent though stopped intensifying a decade ago, "...We evaluate the duration of the China trade shock and its impact on a wide range of outcomes, building on analyses in Autor et al. (2013a) and Acemoglu et al. (2016). This shock plateaued in 2010, enabling study of its effects for nearly a decade past its culmination. Adverse impacts of import competition on manufacturing employment, employment-population ratios, and income per capita in more trade-exposed U.S. commuting zones are present out to 2019. Reductions in population headcounts, which indicate net out-migration, register only for foreignborn workers and the native-born 25-39 years old, implying that exit from work is a primary means of adjustment. More negatively affected regions see larger increases in the uptake of government transfers, but these transfers primarily take the form of Social Security and Medicare benefits and replace only a small fraction of lost personal income. Adverse outcomes are more acute in regions that initially had fewer college-educated workers and were more industrially specialized. Impacts are qualitatively—but not quantitatively—similar to those caused by the decline of employment in coal production since the 1980s, indicating that the China trade shock holds lessons for other episodes of localized job loss. Import competition from China induced shocks to income per capita across local labor markets that are much larger than the spatial heterogeneity of income effects predicted by standard quantitative trade models. Even using higher-end estimates of the consumer benefits of rising trade with China, a substantial fraction of commuting zones appears to have suffered absolute declines in real average incomes...."

Autor also did an exercise looking at the China shock relative to the collapse in demand for coal and the housing bust and finds that the China trade shock was different, "...In summary, we observe that Chinese import competition, the fall in demand for coal, and the Great Recession each reduced employment and labor incomes as these shocks unfolded. CZs with greater shock exposure did not experience large declines in population in any of these cases, suggesting that migration did not disperse the local impacts of these shocks. CZ more exposed to the Great Recession eventually experienced a substantial recovery of their employment rates, and faster population growth. Those with greater exposure to the China or coal shocks instead endured persistently depressed employment rates and labor income levels, combined with a slow decline in population. The comparison with the coal shock in particular indicates that the China shock’s long-lasting impact on CZ labor market conditions and the sluggish population response to depressed local labor market conditions was not without precedent. However, the large magnitude of the China shock, which had a sizable impact on many local labor markets in the US, sets it apart from shocks such as the decline of the coal sector whose impact was more limited in scope. As the United States prepares for potentially more job loss due to the ongoing energy transformation and expected changes in oil and gas production, the failure of local labor markets to adjustment successfully to the coal and China trade shocks reminds us that the adjustment process is typically slow and sclerotic, unlike the textbook model of frictionless labor market adjustment..."
The basic story, "...The first wave of China shock research found that greater import competition caused localized job loss in manufacturing, declines in earnings for low-wage workers, and greater economic distress across a wide range of outcomes. The primary mechanism of adjustment to trade exposure was exit from work, rather than increased employment in non-manufacturing or migration to other regions. The impacts of rising import competition, originally documented for 1991 through 2007, are manifest out to 2019, nearly two decades after China’s accession to the WTO in 2001 and nine years after the plateau of China’s export surge. More trade-impacted CZs suffered durable increases in joblessness and decreases in personal income per capita that are not close to being offset by government transfers. The resulting economic distress appears to be most acute in local labor markets that lacked abundant supplies of college-educated workers—consistent with the dearth of human capital hypothesis—and that were narrowly specialized in labor-intensive manufacturing—consistent with the reverse agglomeration hypothesis. For CZs such as North Hickory, North Carolina, the consequences of the China trade shock have been profound and long-lasting….”
"...In more trade-exposed regions, we find that negative effects on manufacturing employment continue to build well beyond the culmination of the trade shock itself. Adverse impacts persist out to 2019, nearly a decade after the shock reached peak intensity. Although the trade shock did generate modest net out-migration, this occurred only among the foreign-born and native-born adults ages 25 to 39. Impacts of the trade shock thus appear to be long-lasting and to entail suppressed participation in work, which is evident in declines in wages and salaries and personal income in trade-exposed regions. Income losses are only minimally offset by the increased uptake of government transfers, which also remain elevated to the end of the analytic window. Why has the China trade shock had such enduring consequences? One explanation is that the shock itself never stopped intensifying. We find little support for this idea. China’s spectacular manufacturing export growth slowed dramatically in the last decade, by which point China’s reform driven boom had run its course and the government had begun to rollback reforms (Lardy, 2019; Brandt et al., 2020; Brandt and Lim, 2020). Export growth also did not simply move en masse from China to other nearby countries. Whether we look at the U.S. market presence of China alone or combined with Vietnam and other Southeast Asian nations, to which China has begun to offshore some labor-intensive activities, the trade shock reached peak intensity around 2010 and stabilized thereafter. Although the China trade shock did not unwind, it did plateau, letting us examine its consequences for nearly a decade beyond its full expression...."

"...We conduct preliminary analyses of two other explanations for why trade-exposed labor markets suffered long-lasting hardship. One hypothesis is that many traditional manufacturing regions were poorly positioned to recover from job loss because of a dearth of college-educated workers, who are in high demand by sectors that are expanding nationally (Glaeser et al., 1995; Diamond, 2016; Bloom et al., 2019). A second is that specialization in a narrow set of industries left these regions exposed to industry-specific shocks that, once industry decline initiated, would set in motion a process that is self-reinforcing (e.g., Dix-Carneiro and Kovak, 2017). We find some support for both the dearth-of human- capital and reverse-agglomeration hypotheses. We also discuss other mechanisms that may be at work, though we do not provide a definitive, mono-causal explanation..."

"...China’s post-2010 slowdown is also apparent when we compare its trade performance to the U.S., which is helpful for defining the shock facing U.S. manufacturing industries. A simple method to evaluate China’s relative export success is to use the Balassa (1965) measure of revealed comparative advantage (RCA), which is the ratio of a country’s share of world exports in a particular sector to its share of world exports of all goods.13 In Figure 2, we show the gap between the log China and log U.S. RCA for manufacturing and non-manufacturing. China began with a modest comparative advantage in manufacturing over the U.S. in 1991—as indicated by a China-U.S. manufacturing versus all goods export differential of just 2.0 percentage points in that year. By 2011, its manufacturing-versus-all goods export differential over the U.S. had leaped to 13.1 percentage points, before falling and rising over the ensuing eight years. After 2010, the China-U.S. relative RCA exhibits little trend. By construction, China’s RCA in non-manufacturing compared to the U.S. exhibits approximately the inverse pattern, dropping steadily through the 1990s and 2000s and then remaining at negative levels after 2011. China’s comparative disadvantage in non-manufacturing relative to the U.S. reflects the success of U.S. firms in exporting agricultural products, certain mineral products, and oil and gas, to the rest of the world, as well as market forces in China that have concentrated factors of production in manufacturing at the expense of other sectors. Even though China’s export growth in manufacturing slowed after 2010, it still could have contributed to overall U.S. manufacturing import growth by offshoring production to other low wage countries. Chinese firms have been active in building industrial parks for export production in Southeast Asia, and in Vietnam in particular. To investigate this possibility, in Figure 3 we plot shares of U.S. imports and import penetration in the U.S. market for China alone and for China combined with low-income countries in Southeast Asia. We select these countries—Cambodia, Indonesia, Laos, Myanmar, Philippines, Vietnam—based on their per capita GDP in 2010 being less than that of China. We also add neighboring Bangladesh to this group because in recent decades multinational companies from Asia have expanded apparel factories in the country (Heath and Mobarak, 2015). Figure 3 underscores that China’s exports to the U.S. dwarf those of Southeast Asia. In 2010, China accounted for 23.4% of U.S. manufacturing imports, whereas the Southeast Asian nations accounted for just 2.6%. In 2018, these figures were only modestly changed, at 23.6% and 3.8%, respectively. Although Southeast Asian countries did gain a larger share of U.S. imports, the increase over the 2010 to 2018 period was just 1.2 percentage points. Import penetration, shown in Figure 3b, tells a similar story. Whether we look at China alone or combined with low-income Southeast Asian nations, its U.S. market presence largely stabilized after 2010..."

Evidence, "...This section presents our main empirical results for the impact of trade exposure on U.S. commuting zones. We use equation (2) to estimate how the 2000-2012 trade shock affected CZs over2000 to 2019, focusing on three sets of outcomes. The first are ratios of manufacturing employment, non-manufacturing employment, total wage and salary employment, and unemployment to the working-age population (defined as individuals ages 18 to 64 years old). We measure employment using the Bureau of Economic Analysis’ (BEA) Regional Economic Information System (REIS), unemployment using Local Area Unemployment Statistics (LAUS), and population using the National Vital Statistics System, where we aggregate data from the county to the CZ level. Trade shock impacts on these outcomes reveal the direct consequences on manufacturing employment, and the magnitude of labor reallocations to unemployment, non-employment, and other sectors. A second set of outcomes are population headcounts, overall and by nativity and age-based subgroups, which reveal whether exposure to import competition led to net reductions in the resident population (e.g., due to out-migration). A third set of outcomes are per capita personal income, labor compensation, and government transfers, overall and by program type, which reveal the impact of trade shocks on average income and its components, and allow us to quantify the degree to which government transfers offset income losses caused by trade exposure. We measure income, earnings, and government transfers using county-level data from the REIS. For most series, we use 2000 as the initial year.Summary statistics on outcome and control variables are reported in Appendix Tables A1 and A2; Appendix A.2 contains further details on data sources and variable construction…”

Employment Outcomes

"... Figure 5 shows the cumulative impact of trade exposure for progressively longer time differences (1 to 18 years)....The results for manufacturing employment in Figure 5a show a negative effect of trade exposure that builds quickly and then stabilizes.... As one moves past 2012, the negative effect of greater import competition on manufacturing employment continues to grow, even though the trade shock itself no longer appears to be intensifying. Given a decadalized increase in import penetration over 2000 to 2012 of 0:89 percentage points (Table 1),the implied reduction in the manufacturing employment share over 2001 to 2019 is􀀀1:59 (=􀀀1:790:89) percentage points, relative to the overall 2001-2019 change in the manufacturing employment share of􀀀2:68 percentage points (Appendix Table A1). Alternatively, when comparing CZs at the 25th and 75th percentiles of trade exposure, the latter would be predicted to have a reduction in its manufacturing employment share that is 1:18 (=􀀀1:79 ) percentage points larger than in the former over 2001 to 2019. This compares to the 25th-75th percentile differential change in the manufacturing-employment-share of􀀀2:17 (=􀀀3:79 + 1:62) percentage points for the same period. Exposure to import competition from China thus appears to account for a large share of net manufacturing job loss in US commuting zones after 2000.29 Those losing jobs in manufacturing may move into other sectors, into unemployment, or out of the labor force. Simultaneously, they may move to another commuting zone.30 In Figure 5b, we consider the impact of exposure to import competition on the CZ share of the working-age population employed in non-manufacturing industries. Impact coefficient estimates are close to zero at all time intervals and are imprecisely estimated (e.g., the impact coefficient for the 2001-2019 period is 0:05, t-value= 0:06). We see no evidence that on net non-manufacturing sectors absorbed local workers released from manufacturing due to the China trade shock.31 The wide standard error bounds in Figure 5b are suggestive of heterogeneity across CZs in how non-manufacturing absorbs displaced manufacturing workers, a possibility we explore in section 4.4. The fall in manufacturing employment and absence of offsetting job gains in non-manufacturing imply a decline in total wage and salary employment in trade-exposed CZs, confirmed by Figure 5c. Decreases in the employment-population ratio are comparable in magnitude to those for manufacturing employment. The effect reaches its maximum value for the 2001 to 2017 period: the impact coefficient of􀀀1:91 (t-value=􀀀2:70) compares to􀀀1:88 (t-value=􀀀5:89) for manufacturing employment at the same horizon. The impact attenuates modestly late in the period, ending at􀀀1:74 (t-value=􀀀2:35) over 2001 to 2019, which is close to the manufacturing impact at this horizon. At long time horizons, much of the net absorption of manufacturing job loss is through increases in nonemployment. Amior and Manning (2018) argue that changes in the local employment-population ratio summarize changes in local average real income. By this logic, the China trade shock would have substantially altered the distribution of well-being across CZs, a possibility we explore in more detail below through our analysis of personal income per capita. Figure 6a maps the actual change in wage and salary employment-population ratios across CZs for the 2001 to 2019 time period. While the national employment rate barely changed over this period (+0.19 percentage points), the map reveals considerable variation across space, with lower employment growth in parts of the South, Midwest and Northeast, and faster employment growth in the Great Plains and some of the Western and Northeastern coastal areas. In Figure 6b, we map the implied impact of the China trade shock (as measured in (1) for 2000 to 2012) on changes in employment-population ratios for the same 2001 to 2019 time period. A visual comparison between Figure 6’s two panels shows a striking correlation, as many of the CZs that lost employment overall (in panel a) were also more adversely affected by the trade shock (in panel b).This correlation suggests that the China shock had an important influence on the differential employment growth across U.S. regions in the last two decades. The top 5% of CZs in terms of implied reductions in employment-population ratios, which are listed in Appendix Table A4, include a preponderance of locations that in 2000 were relatively highly specialized in manufacturing and had relatively few college-educated workers. In 2000, 33 of the 38 most exposed CZs had a manufacturing employment share above 25 percent, relative to the population-weighted median of 15.4%, and 33 of 38 had a college-educated share of the working-age population below 20 percent, relative to the national population-weighted median of 23.4%. The distinctiveness of trade-impacted commuting zones motivates the heterogeneity analysis we undertake in section 4.4..."

“…One way American firms have improved their moats in recent times is through creeping consolidation. The Economist has divided the economy into 900-odd sectors covered by America’s five-yearly economic census. Two-thirds of them became more concentrated between 1997 and 2012 (see charts 2 and 3). The weighted average share of the top four firms in each sector has risen from 26% to 32%....These data make it possible to distinguish between sectors of the economy that are fragmented, concentrated or oligopolistic, and to look at how revenues have fared in each case. Revenues in fragmented industries—those in which the biggest four firms together control less than a third of the market—dropped from 72% of the total in 1997 to 58% in 2012. Concentrated industries, in which the top four firms control between a third and two-thirds of the market, have seen their share of revenues rise from 24% to 33%. And just under a tenth of the activity takes place in industries in which the top four firms control two-thirds or more of sales. This oligopolistic corner of the economy includes niche concerns—dog food, batteries and coffins—but also telecoms, pharmacies and credit cards….”

Economist Staff, "Too much of a good thing,"The Economist, March 26, 2016, https://www.economist.com/briefing/2016/03/26/too-much-of-a-good-thing

Too much of a good thing

AMERICA’S airlines used to be famous for two things: terrible service and worse finances. Today flyers still endure hidden fees, late flights, bruised knees, clapped-out fittings and sub-par food. The profit bit of the picture, though, has changed a lot. Last year America’s airlines made $24 billion—more than Alphabet, the parent company of Google. Even as the price of fuel, one of airlines’ main expenses, collapsed alongside the oil price, little of that benefit was passed on to consumers through lower prices, with revenues remaining fairly flat. After a bout of consolidation in the past decade the industry is dominated by four firms with tight financial discipline and many shareholders in common. And the return on capital is similar to that seen in Silicon Valley.

What is true of the airline industry is increasingly true of America’s economy as a whole. Profits have risen in most rich countries over the past ten years but the increase has been biggest for American firms. Coupled with an increasing concentration of ownership, this means the fruits of economic growth are being hoarded. This is probably part of the reason that two-thirds of Americans, including a majority of Republicans, have come to believe that the economy “unfairly favours powerful interests”, according to polling by Pew, a research outfit. It means that when Hillary Clinton and Bernie Sanders, the Democratic contenders for president, say that the economy is “rigged”, they have a point.

Opportunities

An intense burst of consolidation will boost their profits more. Since 2008 American firms have engaged in one of the largest rounds of mergers in their country’s history, worth $10 trillion. Unlike earlier acquisitions aimed at building global empires, these mergers were largely aimed at consolidating in America, allowing the merged companies to increase their market shares and cut their costs. The companies in question usually make no pretence of planning to pass the savings they make this way on to their customers; take their estimates of the synergies involved at face value and profits in America will rise by a further 10% or so.

Profits are an essential part of capitalism. They give investors a return, encourage innovation and signal where resources should be invested. Their accumulation allows investment in bold new ventures. Countries where profits are too low—Japan, for instance—can slip into morbid torpor. Firms that ignore profits, such as China’s state-run enterprises, lurch around like aimless zombies, as likely to destroy value as to create it.

But high profits across a whole economy can be a sign of sickness. They can signal the existence of firms more adept at siphoning wealth off than creating it afresh, such as those that exploit monopolies. If companies capture more profits than they can spend, it can lead to a shortfall of demand. This has been a pressing problem in America. It is not that firms are underinvesting by historical standards. Relative to assets, sales and GDP, the level of investment is pretty normal. But domestic cash flows are so high that they still have pots of cash left over after investment: about $800 billion a year.

High profits can deepen inequality in various ways. The pool of income to be split among employees could be squeezed. Consumers might pay too much for goods. In a market the size of America’s prices should be lower than in other industrialised economies. By and large, they are not. Though American companies now make a fifth of their profits abroad, their naughty secret is that their return-on-equity is 40% higher at home.

Most explanations of America’s high profits draw on national-accounts data which show that the fall in the share of output going to workers over the past decade is equivalent to about 60% of the rise in domestic pre-tax profits. Scholars typically have three explanations for this: technology, which has allowed firms to replace workers with machines and software; globalisation, which has made it easier to shift production to lower cost countries; and a decline in trade-union membership.

None of these accounts, though, explain the most troubling aspect of America’s profit problem: its persistence. Business theory holds that firms can at best enjoy only temporary periods of “competitive advantage” during which they can rake in cash. After that new companies, inspired by these rich pickings, will pile in to compete away those fat margins, bringing prices down and increasing both employment and investment. It’s the mechanism behind Adam Smith’s invisible hand.

In America that hand seems oddly idle. An American firm that was very profitable in 2003 (one with post-tax returns on capital of 15-25%, excluding goodwill) had an 83% chance of still being very profitable in 2013; the same was true for firms with returns of over 25%, according to McKinsey, a consulting firm. In the previous decade the odds were about 50%. The obvious conclusion is that the American economy is too cosy for incumbents.

In 1998, Joel Klein, who ran the antitrust operation at the Department of Justice (DoJ), declared that “our economy is more competitive today than it has been in a long, long time.” He may well have been right. In the post-war boom American firms grew into mighty conglomerates; in the 1960s J.K. Galbraith, a left-leaning economist, predicted the rise of a symbiotic “industrial state” in which large companies worked closely with the government. But in the 1980s deregulation opened some industries, such as telecoms and railways, to competition. And a new doctrine of shareholder value led big firms, such as RJR Nabisco, to be broken-up and sprawling conglomerates to become focused. In the 1990s American firms faced a wave of competition from low-cost competitors abroad (and, reciprocally, focused their energy on expanding overseas).

Since then the pendulum seems to have swung back. Huge companies, long the focus of American worries about competition, have not actually got any bigger. In 2014 the top 500 listed firms made about 45% of the global profits of all American firms, as they did in the late 1990s. Instead they, and other companies, have become more focused. The strategy can be seen as an amalgam of the philosophies of two deeply influential business figures. Jack Welch, the boss of General Electric for two decades at the end of the 20th century, advised companies to get out of markets which they did not dominate. Warren Buffett, the 21st century’s best-known investor, extols firms that have a “moat” around them—a barrier that offers stability and pricing power.

These data make it possible to distinguish between sectors of the economy that are fragmented, concentrated or oligopolistic, and to look at how revenues have fared in each case. Revenues in fragmented industries—those in which the biggest four firms together control less than a third of the market—dropped from 72% of the total in 1997 to 58% in 2012. Concentrated industries, in which the top four firms control between a third and two-thirds of the market, have seen their share of revenues rise from 24% to 33%. And just under a tenth of the activity takes place in industries in which the top four firms control two-thirds or more of sales. This oligopolistic corner of the economy includes niche concerns—dog food, batteries and coffins—but also telecoms, pharmacies and credit cards.

Concentration does not of itself indicate collusion. Other factors at play might include regulations that keep competitors out. Business spending on lobbying doubled over the period as incumbents sought to shape regulations in ways that suited them. The rising importance of intangible assets, particularly patents, has meant that an ability to manage industry regulators and the challenges of litigation is more valuable than ever.

The ability of big firms to influence and navigate an ever-expanding rule book may explain why the rate of small-company creation in America is close to its lowest mark since the 1970s (although an index of startups run by the Kauffman Foundation has shown flickers of life recently). Small firms normally lack both the working capital needed to deal with red tape and long court cases, and the lobbying power that would bend rules to their purposes. A lack of lobbying clout and legal savvy may also help explain foreign firms’ loss of momentum. In the 1990s adventurers from abroad piled into America, with the share of output from foreign-owned subsidiaries rising steadily. But foreign firms seem to have lost their mojo. Since 2003 their contribution has been flat at about 6% of private business output.

Another factor that may have made profits stickier is the growing clout of giant institutional shareholders such as BlackRock, State Street and Capital Group. Together they own 10-20% of most American companies, including ones that compete with each other. Claims that they rig things seem far-fetched, particularly since many of these funds are index trackers; their decisions as to what to buy and sell are made for them. But they may well set the tone, for example by demanding that chief executives remain disciplined about pricing and restraining investment in new capacity. The overall effect could mute competition.

Quantifying the effect of the corporate America’s defences is tricky. Profits are not the whole picture. In some industries—banking is a case in point—rent-seeking will result in high pay to an employee elite instead. But one can get a crude sense of what is going on by dividing the profits all firms generate into the “bog-standard” and the “exceptional”. Over the past 50 years return on capital has averaged about 10% (excluding goodwill) and that is what investors tend to demand, so let that represent bog-standard profits. The excess on top of that—which may reflect brilliant innovations, wise historic investments in intangible assets such as brands, or, perhaps, a lack of competition—is the exceptional bit. For S&P 500 firms these exceptional profits are currently running at about $300 billion a year, equivalent to a third of taxed operating profits, or 1.7% of GDP.

I love you, you pay my rent

About a quarter of America’s abnormal profits are spread across a wide range of sectors. Returns on capital, concentration and prices have risen in many pockets of the economy. The cable television industry has become more tightly controlled, and many Americans rely on a monopoly provider; prices have risen at twice the rate of inflation over the past five years. Consolidation in one of Mr Buffett’s favourite industries, railroads, has seen freight prices rise by 40% in real terms and returns on capital almost double since 2004. The proposed merger of Dow Chemical and DuPont, announced last December, illustrates the trend to concentration. After combining, the companies plan to split into three specialist companies each of which will have a higher share of its market than either original company had before the deal. They say the plan will yield $3 billion in cost savings. Since 2008 American mergers have sought to remove recurring annual costs of about $150 billion from industrial ledgers. Few firms that are not regulated utilities have public plans to pass these gains on to consumers.

Concentration is contagious. As firms become more powerful those elsewhere on associated chains of customers and suppliers bulk up in response. Google now dominates internet searches for flights and hotels. This has led Expedia, the leading internet travel-agent, to beef up by buying two of its main rivals over the past two years. The spectre of very big online travel sites dominating the purchase of hotel rooms has led the hotel firms to consolidate, too, with Marriott agreeing to buy Starwood this month. (A Chinese firm, Anbang, may make a counter-bid).

Roughly another quarter of abnormal profits comes from the health-care industry, where a cohort of pharmaceutical and medical-equipment firms make aggregate returns on capital of 20-50%. The industry is riddled with special interests and is governed by patent rules that allow firms temporary monopolies on innovative new drugs and inventions. Much of health-care purchasing in America is ultimately controlled by insurance firms. Four of the largest, Anthem, Cigna, Aetna and Humana, are planning to merge into two larger firms.

The rest of the abnormal profits are to be found in the technology sector, where firms such as Google and Facebook enjoy market shares of 40% or more. By Silicon Valley’s account such penetration reflects the popularity and inventiveness of the products on offer, some of which are free to consumers. Today’s dominant firms could be tomorrow’s Nokia or Blackberry: Apple now trades on just 11 times earnings, suggesting investors expect it to decline. Firms such as Uber and Airbnb are a rare source of disruption in the economy, competing fiercely with incumbents.

But many of these arguments can be spun the other way. Alphabet, Facebook and Amazon are not being valued by investors as if they are high risk, but as if their market shares are sustainable and their network effects and accumulation of data will eventually allow them to reap monopoly-style profits. (Alphabet is now among the biggest lobbyists of any firm, spending $17m last year.) A fall from grace in the tech world is not as bad as you might imagine. Microsoft’s operating profits today are twice what they were in 2000, when Mr Klein was prosecuting it in an antitrust trial. And the “sharing economy” startups that are being so highly rated by some investors mostly seek to dominate their markets. The large mountains of cash they are burning today can only be justified if they eventually mature to enjoy very high market shares and margins.

In the past, periods of high and stable profits have ended. Just three years after Mr Galbraith made his 1967 prediction of a cosy, collaborative business world, it was already toast: profits had collapsed by a third relative to GDP as recession struck. Today’s profits, too, may be more vulnerable than they look. If wages finally pick up it could crimp margins. The earnings-per-share of listed firms have fallen slightly in the past few quarters, though a strong dollar and declining oil revenues explain much of that. Some observers of the stockmarket argue that it is already signalling more decline. The gap between the real yield on equities and that on government bonds suggests that either firms are riskier than ever, bond yields are freakishly low, or that profits face a cyclical downturn.

Even so, it is hard to identify a mechanism by which profits might fall to more normal levels. Investors and managers continue to place extraordinarily high profit multiples on businesses with “moats”. The cable television industry is supposedly under pressure from the likes of Netflix and Amazon Prime. Yet in 2015 Charter Communications, a cable company, bought Time Warner Cable for $79 billion, or 26 times its free cash flow, which implies that it believes it will be in a position to raise prices. When Heinz (part-controlled by Mr Buffett) bought Kraft Foods in 2015, it paid 31 times the free cash flow and promptly slashed spending to boost margins, suggesting it felt the threat from rival makers of cheese slices was rather small.

Antitrust, but verify

Perhaps antitrust regulators will act, forcing profits down. The relevant responsibilities are mostly divided between the DoJ and the Federal Trade Commission (FTC), although some industries, such as railways and telecoms, also have their own regulators. The DOJ and FTC are busy trying to police the mergers-and-acquisition boom. Rather than contest every deal they select cases that set new precedents and argue them in court: of the 15,000 deals between 2005-14, about 3% have been subject to close scrutiny.

Together the two bodies have roamed far and wide. The DoJ has blocked domestic deals, such as the takeover by AT&T of T-Mobile USA in 2011, and cross-border combinations that would have caused concentration in global industries, such as the merger of two chipmakers, Applied Materials and Tokyo Electron, in 2015. The FTC spends a big chunk of its time looking at health care. It has blocked hospital mergers and fought “pay-for-delay” deals in which pharmaceutical firms try to stop generic competitors from launching rival products when patents expire. The DoJ is casting a beady eye over the airlines.

Yet the system suffers two limitations. One is constitutional. The two bodies’ job is to police infringements of a well-established and mature body of law through the courts. This leaves them admirably free of overt political interference and lobbying but it also limits their scope. Lots of important subjects are beyond their purview. They cannot consider whether the length and security of patents is excessive in an age when intellectual property is so important. They may not dwell deeply on whether the business model of large technology platforms such as Google has a long-term dependence on the monopoly rents that could come from its vast and irreproducible stash of data. They can only touch upon whether outlandishly large institutional shareholders with positions in almost all firms can implicitly guide them not to compete head on; or on why small firms seem to be struggling. Their purpose is to police illegal conduct, not reimagine the world. They lack scope.

The second limitation is intellectual. America’s antitrust apparatus has gone through periods of leniency (1915-35) and stridency (1936-72). By the 1980s the Chicago school of free-market thought was ascendant. Its insistence that the efficiency benefits of big mergers should not be dismissed had a big influence on the courts. Antitrust guidelines which held that any deal involving a firm with a market share of 35% or more should be considered suspect on principle have been set aside in favour of a more granular approach, with regulators looking ever more closely at the specific effects of a deal. To work out if a deal lowers consumers’ level of choice or lets firms hike prices they will study micro-markets in specific regions.

Who does not prefer the rifle to the blunderbuss, the scalpel to the axe? Such sophistication allows regulators to demand clever remedies, such as the disposal of subsidiaries. But with their heads deep in data and court rulings that set fine precedents, the scientists of antitrust are able to sidestep some troubling questions. If markets are truly competitive, why do so many companies now claim they can retain the cost synergies that big deals create, not pass them on to consumers? Why do investors believe them? Why have returns on capital risen almost everywhere?

These legal and intellectual limitations of the antitrust apparatus raise the question of competition to the political sphere—currently, alas, a realm well supplied with blunderbusses and axes wielded haphazardly and at the wrong targets. Americans’ mistrust of their economic system and the companies that make so much money in it has so far been channelled into calls for protectionism and government intervention. Free trade should be limited. Health-care firms should be more regulated. Foreign firms—particularly Chinese ones—should be discriminated against. Wages should be forced up. Taxes on companies should be raised.

Memories of the future

Nowhere has the alternative approach been articulated. It would aim to unleash a burst of competition to shake up the comfortable incumbents of America Inc. It would involve a serious effort to remove the red tape and occupational-licensing schemes that strangle small businesses and deter new entrants. It would examine a loosening of the rules that give too much protection to some intellectual-property rights. It would involve more active, albeit cruder, antitrust actions. It would start a more serious conversation about whether it makes sense to have most of the country’s data in the hands of a few very large firms. It would revisit the entire issue of corporate lobbying, which has become a key mechanism by which incumbent firms protect themselves.

Large firms no longer employ all that many people in America: the domestic employee base of the S&P 500 is only around a tenth of total American employment. New firms would invest more, employ more staff, and force incumbents to invest more in order to compete. If this sounds pie in the sky, consider the shale revolution over the past decade. Although the industry is now suffering from low oil prices, it is a rare example of entrepreneurial spirit taking on a stodgy industry to the benefit of all. A new commitment to competition could be the source of optimism that America is desperately searching for. After all, it is only a healthy dollop of greed and a belief in a better future that prompts people to start from scratch and try to cross the moat that has been dug around corporate America.