Macro Roundup

New Rognlie looks at income distribution's impact on aggregate demand as of today. As of now they find that the marginal propensity to consume btw rich and poor is quite small: “…average MPC of the top 10% of income earners and that of the bottom 90% of earners is less than 0.1….”

Adrien Auclert and Matthew Rognlie, "Inequality and Aggregate Demand," Stanford University and Northwestern University, January 2020, http://mattrognlie.com/inequad.pdf

“…For temporary increases in inequality, in line with common intuition, we find that the key is the relationship between MPCs and income. But although the rich have lower MPCs than the poor, the gap is not large enough for realistic changes in the income distribution to have much effect on aggregate consumption. For instance, in both the data and our calibrated model,the gap between the average MPC of the top 10% of income earners and that of the bottom 90% of earners is less than 0.1. Hence, every additional 1% of overall income shifting from the bottom 90% to the top 10% (a larger-than-usual year on year change; see Piketty and Saez 2003) lowers aggregate consumption by no more than 0.1% of total income….We explore the transmission mechanism of income inequality to output. In the short run, higher inequality reduces output because marginal propensities to consume are negatively correlated with incomes, but this effect is quantitatively small in both the data and our model. In the long run, the output effects of income inequality are small if inequality is caused by rising dispersion in individual fixed effects, but can be large if it is the manifestation of higher individual income risk….We found that transitory income redistribution can lead to declines in both consumption and output, but that this effect is likely small. By contrast, we found that the long-run effect of income inequality, if it involves an increase in idiosyncratic income risk, can potentially be quite large….”

However they find that this could change going forward, “…we generally findoutput effects that are negative but small, with one notable exception: if inequality is caused by an increase in individual income risk, and monetary policy does not or cannot lower interest rates enough to offset it, then a large, long-lasting slump can ensue…”.

Chart fromTheEconomistreport on who is buying Treasuries and the state of play of the global savings glut/safe asset shortage,

“…Domestic investors have soaked up two-thirds of the extra government borrowing since 2016. Foreigners have bought the rest, equivalent to $800bn-worth of Treasuries. As a consequence, America is now an even bigger net borrower from the rest of the world. Its current-account deficit has widened to around 2.5% of gdp. It is no surprise that investors have an appetite for American debt. Policy uncertainty abounds, not least thanks to Mr Trump’s enthusiasm for threatening trade war. There are few other havens. Germany’s insistence on running super-tight fiscal policy means there is an undersupply of bunds, argues Brad Setser of the Council on Foreign Relations, a think-tank. Traders moan that the market for Japan’s government bonds is illiquid. Investors based in Europe appear to have been the most enthusiastic buyers (see chart). In part that reflects some countries’ large trade surpluses. In the past year Norway, a big oil exporter, has doubled its holdings. But that does not explain why Belgium, a country of 11m people, is one of the world’s biggest foreign buyers of Treasuries. Although official purchases by China look stable, some suspect that it is making some of its purchases through Belgian intermediaries….”

Economist Staff, “Investors at home and abroad are piling into American government debt,” The Economist, January 25, 2020, https://www.economist.com/finance-and-economics/2020/01/25/investors-at-home-and-abroad-are-piling-into-american-government-debt

Ed’s Comment: “…You don’t need to say “suggests that talent is the limiting constraint.” Your goal is to report factual with minimal opinion. Did they say “diminishing returns?” because 75-38 = 37 i.e., education contributed as much to inequality in the 17 years after 2000 as the 20 years before. That doesn’t seem like diminishing returns. I never trust katz to recognize that a college educated 60thpercentile person is no more productive than a 60thpercentile non-college grad from yesteryear because college, unfortunately, doesn’t teach those students anything useful. There should be no wage increase from education. In the past I thought he misinterpreted that. …”

“….The race between education and technology provides a canonical framework that does an excellent job of explaining U.S. wage structure changes across the twentieth century. The framework involves secular increases in the demand for more-educated workers from skill-biased technological change, combined with variations in the supply of skills from changes in educational access. We expand the analysis backwards and forwards. The framework helps explain rising skill differentials in the nineteenth and twenty-first centuries, but needs to be augmented to illuminate the recent convexification of education returns and implied slowdown in the growth of the relative demand for college workers. Increased educational wage differentials explain 75 percent of the rise of U.S. wage inequality from 1980 to 2000 as compared to 38 percent for 2000 to 2017….. The core findings are of a substantial positive secular trend in the relative demand for college workers and a strong negative impact of increases in the relative supply of college workers on the college wage premium.A 10 percent increase in the relative supply of college equivalents typically reduces the college wage premium by around 6 percent. The implication is that𝜎𝜎)3 is approximately 1.62 (using the estimate in col. 2 of Table A1), similar to other estimates in the literature, typically in the 1 to 2.5 range. Figure A1 plots the actual college wage premium….But the model’s results (see Table A1) divulge a puzzling slowdown in the trend demand demand growth for college equivalents starting in the early 1990s. Rapid and disruptive technological change from computerization, robots, and artificial intelligence is not to be found—though the impact of these technologies may not be well-captured by this two factor setup. The large rise in the college wage premium since 1980 is driven more by slower relative supply growth rather than by an acceleration in skill-biased technological change, or some other demand-side factor. A further comparison of the two periods, 1979 to 2017 and 1939 to 1979, illustrates the point (see Table A2). The log college wage premium increased by 0.274 from 1979 to 2017 (from 0.4 to 0.674, or by 0.072 per decade). Compare that to the change from 1939 to 1979, when the premium declined by 0.088 (by 0.022 per decade). The rate of growth of the log relative supply of college equivalents was 0.31 per decade (or 3.1 percent per annum) from 1939 to 1979. But it decreased to 0.213 per decade (2.13 percent per annum) from 1979 to 2017. The slowdown in relative supply growth accounts for 62 percent (0.058) of the 0.094 per decade increase in the growth rate of the college wage premium post-1979 relative to 1939 to 1979, under the assumption that𝜎𝜎)3 = 1.62. The implied acceleration in the growth of log relative demand for college equivalents of 0.058 per decade explains 38 percent (0.036) of the surge in the college wage premium….But most of the recent rise in wage inequality has occurred within, rather than between, education groups. In fact, the largest part of increased wage variance in the twenty -first century comes from rising inequality among college graduates. There is almost no change in wage inequality for non-college workers since 2000. Such a pattern is consistent with the continuing, rapid rise of the 90-50 wage differential and soaring top-end inequality, combined with stability in the 50-10 wage differential in the 2000s….”

They suggests that supply has driven down college wage premium and note the recent changes in wage inequality are driven by changes in the higher educational attainment group as properly trained talent (implicitly) not education drives compensation “…, the largest part of increased wage variance in the twenty -first century comes from rising inequality among college graduates. There is almost no change in wage inequality for non-college workers since 2000. Such a pattern is consistent with the continuing, rapid rise of the 90-50 wage differential and soaring top-end inequality, combined with stability in the 50-10 wage differential in the 2000s…”

New Autor/Goldin/Katz (implicitly) suggests that talent is the limiting constraint. Paper finds increased educational wage differentials ability to explain wage inequality has changed post 2000 (through 2017) when compared with the previous two decades (1980-2000), “…Increased educational wage differentials explain 75 percent of the rise of U.S. wage inequality from 1980 to 2000 as compared to 38 percent for 2000 to 2017….” Diminishing returns in all things.