Knowledge that Transforms

We introduce a simple method of recovering attention costs from choice data. Our method rests on a precise analogy with production theory. Costs of attention determine consumer demand and consumer welfare, just as a competitive firm’s technology determines its supply curve and profits. We implement our recovery method experimentally, outline applications, and link our work to the broader literature on inattention and mistaken decisions.

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.

Macro-finance analyses commonly link firms’ borrowing constraints to the liquidation value of physical assets. For U.S. nonfinancial firms, we show that 20% of debt by value is based on such assets (asset-based lending in creditor parlance), whereas 80% is based predominantly on cash flows from firms’ operations (cash flow–based lending). A standard borrowing constraint restricts total debt as a function of cash flows measured using operating earnings (earnings-based borrowing constraints). These features shape firm outcomes on the margin: first, cash flows in the form of operating earnings can directly relax borrowing constraints; second, firms are less vulnerable to collateral damage from asset price declines, and fire sale amplification may be mitigated. Taken together, our findings point to new venues for modeling firms’ borrowing constraints in macro-finance studies.

This article estimates the effect of environmental regulation on firm productivity using a spatial regression discontinuity design implicit in China's water quality monitoring system. Because water quality readings are important for political evaluations and the monitoring stations only capture emissions from their upstream regions, local government officials are incentivized to enforce tighter environmental standards on firms immediately upstream of a monitoring station, rather than those immediately downstream. Exploiting this discontinuity in regulation stringency with novel firm-level geocoded emission and production data sets, we find that immediate upstream polluters face a more than 24% reduction in total factor productivity (TFP), and a more than 57% reduction in chemical oxygen demand emissions, as compared with their immediate downstream counterparts. We find that the discontinuity in TFP does not exist in nonpolluting industries, only emerged after the government explicitly linked political promotion to water quality readings, and was predominantly driven by prefectural cities with career-driven leaders. Linking the TFP estimate with the emission estimate, a back-of-the-envelope calculation indicates that China's water regulation efforts between 2000 and 2007 were associated with an economic cost of more than 800 billion Chinese yuan.

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 study the role of gender in the evaluation of economic research using submissions to four leading journals. We find that referee gender has no effect on the relative assessment of female- versus male-authored papers, suggesting that any differential biases of male referees are negligible. To determine whether referees as a whole impose different standards for female authors, we compare citations for female- and male-authored papers, holding constant referee evaluations and other characteristics. We find that female-authored papers receive about 25% more citations than observably similar male-authored papers. Editors largely follow the referees, resulting in a 1.7 percentage point lower probability of a revise and resubmit verdict for papers with female authors relative to a citation-maximizing benchmark. In their desk rejection decisions, editors treat female authors more favorably, though they still impose a higher bar than would be implied by citation maximization. We find no differences in the informativeness of female versus male referees or in the weight that editors place on the recommendations of female versus male referees. We also find no differences in editorial delays for female- versus male-authored papers.

We analyze a unique episode in the history of monetary economics, the 2016 Indian “demonetization.” This policy made 86% of cash in circulation illegal tender overnight, with new notes gradually introduced over the next several months. We present a model of demonetization where agents hold cash both to satisfy a cash-in-advance constraint and for tax evasion purposes. We test the predictions of the model in the cross-section of Indian districts using several novel data sets including: the geographic distribution of demonetized and new notes for causal inference; night light activity and employment surveys to measure economic activity including in the informal sector; debit/credit cards and e-wallet transactions data; and banking data on deposit and credit growth. Districts experiencing more severe demonetization had relative reductions in economic activity, faster adoption of alternative payment technologies, and lower bank credit growth. The cross-sectional responses cumulate to a contraction in aggregate employment and night lights–based output due to the the cash shortage of at least 2 percentage points and of bank credit of 2 percentage points in 2016Q4 relative to their counterfactual paths, effects that dissipate over the next few months. Our analysis rejects monetary neutrality using a large-scale natural experiment, something that is still rare in the vast literature on the effects of monetary policy.

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.