Knowledge that Transforms

This article argues that accounting for capital-embodied technology greatly increases the importance of capital in explaining cross-country differences in agricultural labor productivity. To do so, we draw on a novel data set of agricultural capital prices. We document that new capital is more expensive in richer countries, both in absolute terms and relative to old capital. A model of endogenous adoption of capital of different quality links these price differences to the path of capital-embodied technology. In particular, our model recovers the level of embodied technology from the price of new capital and the growth rate of embodied technology from the price of new capital relative to old capital. We then measure the stocks of quality-adjusted capital in agriculture for a sample of 16 countries at different stages of development. We find that adjusting for differences in quality almost doubles the importance of capital in accounting for cross-country differences in agricultural labor productivity: from 21% to 37%. In addition, improvements in capital quality have been an important source of agricultural labor productivity growth over the past 25 years, accounting for 21% and 35% of the productivity growth in poor and rich countries, respectively.

We evaluate a randomized outreach study in which the IRS sent informational letters to 3.9 million households that paid a tax penalty for lacking health insurance coverage under the Affordable Care Act. Drawing on administrative data, we study the effect of this intervention on taxpayers’ subsequent health insurance enrollment and mortality. We find the intervention led to increased coverage during the subsequent two years and reduced mortality among middle-aged adults over the same time period. The results provide experimental evidence that health insurance coverage can reduce mortality in the United States.

A widely held view is that openness to international trade leads to higher GDP volatility, as trade increases specialization and hence exposure to sector-specific shocks. We revisit the common wisdom and argue that when country-wide shocks are important, openness to international trade can lower GDP volatility by reducing exposure to domestic shocks and allowing countries to diversify the sources of demand and supply across countries. Using a quantitative model of trade, we assess the importance of the two mechanisms (sectoral specialization and cross-country diversification) and provide a new answer to the question of whether and how international trade affects economic volatility.

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

We provide a continuous-time “risk-centric” representation of the New Keynesian model, which we use to analyze the interactions between asset prices, financial speculation, and macroeconomic outcomes when output is determined by aggregate demand. In principle, interest rate policy is highly effective in dealing with shocks to asset valuations. However, in practice monetary policy faces a wide range of constraints. If these constraints are severe, a decline in risky asset valuations generates a demand recession. This reduces earnings and generates a negative feedback loop between asset prices and aggregate demand. In the recession phase, average beliefs matter because they not only affect asset valuations but also determine the strength of the amplification mechanism. In the ex ante boom phase, belief disagreements (or heterogeneous asset valuations) matter because they induce investors to speculate. This speculation exacerbates the crash by reducing high-valuation investors’ wealth when the economy transitions to recession, which depresses (wealth-weighted) average beliefs. Macroprudential policy that restricts speculation in the boom can Pareto improve welfare by increasing asset prices and aggregate demand in the recession.

We study the causal impact of religiosity through a randomized evaluation of an evangelical Protestant Christian values and theology education program delivered to thousands of ultrapoor Filipino households. Six months after the program ended, treated households have higher religiosity and income; no statistically significant differences in total labor supply, consumption, food security, or life satisfaction; and lower perceived relative economic status. Exploratory analysis suggests that the income treatment effect may operate through increasing grit. Thirty months after the program ended, significant differences in the intensity of religiosity disappear, but those in the treatment group are less likely to be Catholic and more likely to be Protestant, and there is some mixed evidence that their consumption and perceived relative economic status are higher.

We study the sources of racial disparities in income using anonymized longitudinal data covering nearly the entire U.S. population from 1989 to 2015. We document three results. First, black Americans and American Indians have much lower rates of upward mobility and higher rates of downward mobility than whites, leading to persistent disparities across generations. Conditional on parent income, the black-white income gap is driven by differences in wages and employment rates between black and white men; there are no such differences between black and white women. Hispanic Americans have rates of intergenerational mobility more similar to whites than blacks, leading the Hispanic-white income gap to shrink across generations. Second, differences in parental marital status, education, and wealth explain little of the black-white income gap conditional on parent income. Third, the black-white gap persists even among boys who grow up in the same neighborhood. Controlling for parental income, black boys have lower incomes in adulthood than white boys in 99% of Census tracts. The few areas with small black-white gaps tend to be low-poverty neighborhoods with low levels of racial bias among whites and high rates of father presence among blacks. Black males who move to such neighborhoods earlier in childhood have significantly better outcomes. However, less than 5% of black children grow up in such areas. Our findings suggest that reducing the black-white income gap will require efforts whose impacts cross neighborhood and class lines and increase upward mobility specifically for black men.

Despite decades of research, the consistent estimation of structural forward-looking macroeconomic equations remains a formidable empirical challenge because of pervasive endogeneity issues. Prominent cases—the estimation of Phillips curves, Euler equations, or monetary policy rules—have typically relied on using predetermined variables as instruments, with mixed success. In this work, we propose a new approach that consists in using sequences of independently identified structural shocks as instrumental variables. Our approach is robust to weak instruments and is valid regardless of the shocks’ variance contribution. We estimate a Phillips curve using monetary shocks as instruments and find that conventional methods substantially underestimate the slope of the Phillips curve.

We study how long-lived rational agents learn from repeatedly observing a private signal and each others’ actions. With normal signals, a group of any size learns more slowly than just four agents who directly observe each others’ private signals in each period. Similar results apply to general signal structures. We identify rational groupthink—in which agents ignore their private signals and choose the same action for long periods of time—as the cause of this failure of information aggregation.

We provide evidence that financial market risk perceptions are important drivers of economic fluctuations. We introduce a novel measure of risk perceptions: the price of volatile stocks (PVSt), defined as the book-to-market ratio of low-volatility stocks minus the book-to-market ratio of high-volatility stocks. PVSt is high when perceived risk directly measured from surveys and option prices is low. Using our measure, we show that high perceived risk is associated with low risk-free interest rates, a high cost of capital for risky firms, and future declines in output and real investment. Perceived risk as measured by PVSt falls after positive macroeconomic news. These declines are predictably followed by upward revisions in perceived risk, indicating that fluctuations in investor risk perceptions are not fully rational.