Macro Roundup

Core of their employment argument, “…. how much the stock market reflects the economy is an empirical question. Employment is a reliable benchmark for the state of the economy.Employment data for the whole economy is available for our sample period, does not depend on accounting rules, and is collected by the Federal government irrespective of whether a firm is public or not. For public corporations, employment is available for most corporations annually since the early 1970s. We find that, from 1973 to 2019, the percentage of employees working for public firms is highest at the start of the sample period and falls sharply in the 1980s. At the beginning of that period, more than 41.4 percent of non-farm workers in the private sector work for public firms, but in 2019, that percentage is 29.0 percent. In 2019, the percentage of non-farm workers in the private sector working for public firms is the lowest for our sample period for industrial firms and for all firms, including financial firms, it is the lowest except for 1989 and 1990. We create a measure of unrepresentativeness to capture how poorly market capitalization proxies for a firm’s contribution to employment over time. For each firm, we measure the absolute value of the difference between the firm’s market capitalization as a share of the market capitalization of the stock market and the firm’s employment share among public firms defined as the firm’s employment divided by the employment of all stock market firms. The measure of unrepresentativeness is proportional to the sum of these differences. Intuitively, it is the difference between a portfolio that holds the stock market and a portfolio with weights equal to the employment weights of firms. The unrepresentativeness measure increases as the two portfolios differ more. We call this measure our employment unrepresentativeness measure. This measure follows a w-shape, with its lowest values in the 1980s and 1990s and its highest values in the 1970s, around 2000, and in the recent past. The stock market is more unrepresentative at the end of our sample period with respect to employment than at any time except around the year 2000. Another way to show that market capitalizations are not instructive about firms’ contribution to employment is to estimate how much of the variation in market capitalizations can be explained by variation in employment. We find that from 1973 to 2019 a firm’s employment never explains as little of its market capitalization as in 2019. In most years in the 1970s and early 1980s, firm employment explains more than 50% of the variation in market capitalization. In each of the last four sample years but one, firm employment explains less than 20% of the variation in market capitalization…”

Core of their value added argument, “…Assessing a firm’s contribution to GDP is more fraught with difficulties. A firm’s value added depends on the total compensation it pays to its employees. However, most firms do not disclose how much they pay to their employees separately…. we find that the contribution of public firms to GDP is higher in the 1970s than in the 2000s.This result is insensitive to the approximations we make. Using the same approach to measure unrepresentativeness as with employment, we construct a measure of unrepresentativeness for value added. The stock market’s unrepresentativeness for value added follows a w-shape with unrepresentativeness high early in the sample period, around 2000, and late in the sample period. In contrast to employment, the unrepresentativeness at the end of the sample period is less than at the beginning of the sample period….We find that variation in value-added best explains the variation in market capitalization in the late 1970s and early 1980s. While employment explains less of the variation in market capitalization in the 2010s than in the 1970s, the same is not the case for value added. The variation in value-added explains the variation in market capitalization less well at the end of the sample period than in a number of years, but it explains it better than in the period from 1988 (1991 for industrial firms) to 2003…”

Conclusions, “….we examine how listed firms contribute to the economy over time and how their market capitalization is related to their contribution to the economy. We find that stock market firms as a group contribute less to employment and to GDP than in the 1970s. Since 1973, industrial stock market firms never contribute as little to employment as they do in 2019 and all firms on the stock market contribute less than in 2019 only two years.Though the contribution to GDP of stock market firms is less in recent years than in the 1970s, the decline in contribution to GDP is less than the decline in contribution to employment. Our estimates for the contribution of listed firms to GDP come with some important caveats. Listed firms generally do not disclose their employment expenses, so that we have to approximate them using approaches developed in the recent literature. Further, though listed firms disclose employment, they do not generally disclose separately domestic and foreign employment. As a result, our estimates of employment and value added for listed firms are estimates for worldwide employment and worldwide value added of these firms. To the extent that foreign activities of firms increase over time, our estimates likely understate the decrease in the contribution of listed firms to the US economy. It is well-known that the relative importance of investments in intangible capital has increased over time. These investments are mostly expensed under GAAP. Though we can adjust firm income for investment in intangible capital, we cannot adjust employment for employees who work on projects that increase invested capital. If we adjust income for investment in intangible capital, our conclusions about the evolution of the contribution of value added of listed firms to GDP are unchanged. We measure how representative the market capitalization of firms is of their contribution to the economy. We find that our measure of unrepresentativeness follows a w shape for both employment and value added: the measure is high in the 1970s, around 2000, and at the end of the sample period.For labor, unrepresentativeness increases over time, but not for value added. We also find that the relation between firm market capitalization and firm employment collapses during our sample period. In the 1970s, employment explains 50.7% on average of the variation in market capitalization across firms. In the 2010s, it explains 21.8% on average.A firm’s value added explains much more its market capitalization than its employment. This is true throughout our sample period. Strikingly, there is no consistent degradation in the ability of value added to explain the variation in market capitalization across firms. In the 1970s, value added explains 68.2% of the variation in market capitalization in average. In the 2010s, it explains 67.7%.Perhaps not surprisingly, the top market capitalization firm evolves in the same way as the market as a whole. In the 1950s, the top market capitalization firm was the top employer in the country. In the 2010s, it is the 40th. However, the top market capitalization firm is in the top ten of firms by value added in the 2010s as in the 1970s. The evolution we document is largely the result of the decline of manufacturing in the US. Not all firms are equally suited to be public firms. Small firms and service firms are much less likely to be listed on stock exchanges. Over our sample period, employment by the manufacturing industry falls sharply in importance while employment by the service industries grows dramatically in importance. A large fraction of the employees of manufacturing firms work for public firms. A small fraction of employees of service firms work for public firms. As a result, the fraction of employees working for public firms falls….”

This was a very interesting factoid (see their Table 5 below), “…. Strikingly, from 1950 to 2019, only seven distinct firms have the top market capitalization in at least one year. Only two of these firms, General Motors and AT&T, ever have the largest number of employees in the US. The percentage of US non-farm payrolls represented by the largest market capitalization firm declines steadily over time, so that it is at its lowest in the 2000s. The percentage of US GDP represented by the largest market capitalization firm is also lower in the 2000s than before 1980. The contribution of the top market capitalization firm to the economy in 2019 is a fraction of GM’s contribution in 1953. …”

They find representativeness is worst when the market is most highly valued and worsens over time for employment, but not for value added. “…we measure the extent to which a firm’s market capitalization reflects its concurrent contribution to the economy. We show a strong downward trend in the extent to which a firm’s market capitalization reflects its concurrent contribution to employment. With value added, market capitalizations are least instructive about a firms’ contemporaneous contribution to GDP around 2000, but market capitalizations appear to be as instructive about firms’ contribution to GDP in the 1970s as in the 2010s…..In the 1970s, employment explains 50.7% on average of the variation in market capitalization across firms. In the 2010s, it explains 21.8% on average.A firm’s value added explains much more its market capitalization than its employment. This is true throughout our sample period. Strikingly, there is no consistent degradation in the ability of value added to explain the variation in market capitalization across firms. In the 1970s, value added explains 68.2% of the variation in market capitalization in average. In the 2010s, it explains 67.7%...”

New NBER argues that there is a declining correlation btw a firm's share of employment and its share of stock market value.

“…Our data, which range from 1980 to 2016, allow us to characterize responsiveness in a more recent period than most of the literature, and our event-study approach enables us to estimate effects over different time horizons and test for dynamic effects. We then build a simple framework to relate these state-level effects to a policy-relevant elasticity at the national level, which is the state-level realization response after removing migration effects and accounting for average state taxes and a minor aggregation adjustment term. We find that this policy-relevant elasticity of realizations with respect to capital gains tax rates over a ten year period is approximately -0.3 to -0.5 depending on the specification, and that the estimates are larger in absolute value in the short and medium run than in the long run….This paper uses an event study approach to estimate the effect of capital gains taxation on realizations at the state level, and then develops a framework for determining revenue-maximizing rates at the federal level. We find that the elasticity of revenues with respect to the tax rate over a ten-year period is -0.5 to -0.3,indicating that capital gains tax cuts do not pay for themselves, and that a 5 percentage point rate increase would yield $18 to $30 billion in annual federal tax revenue. Our long-run estimates yield revenue-maximizing capital gains tax rates of 38 to 47 percent….”

Their takeaway, “….We highlight three implications of these elasticity estimates. First, these estimates are well below an elasticity of one in absolute value, which indicates that capital gains tax cuts do not pay for themselves. We formallytest and reject the null of an elasticity of -1.0. Second, these estimates suggest thatraising capital gains tax rates by 5 percentage points (in the current regime with unlimited deferral and step-up-basis at death) would yield 18 to 30 billion in annual tax revenue, which is roughly twice the amount suggested based on recent estimates from the Joint Committee on Taxation (JCT), which according to Gravelle (2020) currently uses an elasticity of -0.7 to score proposals.1 Third, ourlong-run elasticity estimates correspond to point estimates for the revenue-maximizing capital gains tax rates of 38 to 47 percent….”

Current state of capital gains taxes, “…Table 1 provides summary statistics. On average, state capital gains tax rates are 4 percent, but they range from 0 to 15 percent in our sample. Figure 1 plots the maximum federal tax rate over time. The current maximum capital gains tax rate is 23.8 percent. Combining both tax rates and accounting for interactions and phase-outs results in an effective keep rate of 75 percent on average, indicating that a dollar of realized capital gains amounts to 75 cents after taxes….”

Worth noting from Owen Zidar (Capitalists in the Twenty-First Century) looks at the impact of changes in treatment of capital gains on the state level to estimate a the revenue-maximizing rates for federal level. They estimate a Federal “…revenue-maximizing capital gains tax rates of 38 to 47 percent…”

Economist Staff, "How the American economy did under Donald Trump,"The Economist, October 14, 2020, https://www.economist.com/united-states/2020/10/14/how-the-american-economy-did-under-donald-trump

In terms of low skilled wage growth, “…The lot of working-class Americans, however, definitely improved in 2017-19.Comparing household incomes between countries is difficult, certainly for recent years. But though there is some dispute about the reliability of the data gathered in 2020, where the pandemic made it difficult for researchers to conduct surveys, there is clear evidence of an acceleration in the growth of America’s median household income from 2017 onwards (see chart 7). A tight labour market also helped raise the wage growth of the lowest-paid Americans, relative to others, to a degree not seen since Bill Clinton was president (see chart 8)…”

In terms of labor markets, “…America’s labour-market performance is similarly nuanced. Though Mr Trump particularly likes to boast about monthly employment figures, it is hard to make the case that in 2017-19 the jobs machine was whirring. Jobs growth was slower than it had been during Mr Obama’s second term. In 2009-16 America’s unemployment rate fell relative to the average for other g7 economies (see chart 6). Under Mr Trump unemployment did fall to the lowest since the 1960s, but this was not internationally exceptional. America’s improvement relative to employment in other countries stopped under Mr Trump...”

In terms of beating forecasts, “….another way to look at this question is to assess whether America in 2017-19 exceeded or fell short of economists’ expectations (see chart 2). In October 2012 the imf forecast that in the subsequent four years (those of Mr Obama’s second term), the American economy would grow by an annual average of 3%. In fact that proved to be too optimistic; it actually grew by closer to 2% a year. But the imf was too pessimistic in its projections for 2017-19, released shortly before the election of 2016. In those years America outperformed the forecasts….”

In terms of GDP, “…GDP growth was somewhat faster in 2017-19 than it was in either Barack Obama’s first or second term, according to official data. America also did well relative to other countries. The world economy peaked in 2017. In 2018 it slowed but America accelerated. In 2019 America slowed too, but stayed ahead of others…”

The Economistreviews America’s relative economic performance versus the G6 and concludes, “…in 2017-19, the American economy performed marginally better than expected….”