Abstract We show that newly hired workers earn higher wages in response to higher firm leverage. Consistent with compensating differential models, these higher wages appear to reflect compensation for the risk of earnings losses in the event of financial distress. For tenured workers, increases in leverage are not associated with higher wages. Our findings suggest that the wage costs of debt and optimal capital structure for a firm depend on expected employee turnover, as well as on the firm’s future growth and hiring plans. Variation in local labor market conditions also significantly affects the relationship between firm leverage and employee pay. (JEL G32, G33, J21, J31, J61) Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

This paper describes the balance sheet adjustments of debt and equity financed firms over time in an economy subject to taste shocks. A model is developed that describes a representative firm with a stochastic diminishing returns technology and a set of financial contracts that resolve a conflict-of-interest problem between differentially risk-averse bondholders and stockholders. The contractual resolution of this conflict-of-interest problem between the two agents is shown to shape certain stylized facts of business cycles ignored in Keynesian and Classical models. Changes in investor risk aversion and equity valuations trigger real investment decisions that can cause business cycles. Bond covenants then have the firm adjusting its financing decisions so as to offset any risk-shifting associated with the investment decisions. Stockholders manage the asset side of the firm’s balance sheet while bondholders (regulators in the case of banks) manage the financing side. In this way the welfare of both investors is coalesced over the business cycle. A similar type of analysis accounts for the age distribution of workers, and the size distribution of firms over the business cycle. Evidence presented here and elsewhere fails to reject these predictions for the U.S. non-financial and financial corporate sectors.

There is a long-standing debate about the extent to which economic theory should inform econometric modeling and estimation. This debate is particularly evident in the program/policy evaluation literature, where reduced-form (experimental or quasi-experimental) and structural modeling approaches are often viewed as rival methodologies. Reduced-form proponents criticize the assumptions invoked in structural applications. Structural modeling advocates point to the limitations of reduced-form approaches in not being able to inform about program impacts prior to implementation or about the costs and benefits of program designs that deviate from the one that was implemented. In this paper, we argue that there is a new emerging view of a natural synergy between these two approaches, that they can be melded to exploit the advantages and ameliorate the disadvantages of each. We provide examples of how data from randomized controlled trials (RCTs), the exemplar of reduced form practitioners, can be used to enhance the credibility of structural estimation. We also illustrate how the structural approach complements experimental analyses by enabling evaluation of counterfactual policies/programs. Lastly, we survey many recent studies that combine these methodologies in various ways across different subfields within economics. (JEL C21, C52, C53, H24, I38, J13, R38)

Abstract We test whether measures of influence on regulators affect stress-test outcomes. The large trading banks—those most plausibly Too Big to Fail—face the toughest tests. Supervisory stress tests have a greater effect on large trading banks’ portfolios; the large banks respond by making more conservative (initial) capital plans; and, despite their more conservative capital plans, the large banks still fail their tests more frequently than other banks. In contrast, while we find little evidence that political or regulatory connections affect the quantitative element of the stress tests, these connected banks do face less scrutiny under its qualitative dimension.

We present the first quantitative analysis of the impact of ending de jure segregation of Mexican American schoolchildren in the United States by examining the effects of the 1947 Mendez v. Westminster court decision on long-run educational attainment for Hispanics and non-Hispanic Whites in California. Our identification strategy relies on comparing individuals across California counties that vary in their likelihood of segregating and across birth cohorts that vary in their exposure to the Mendez court ruling based on school start age. Results point to a significant increase in educational attainment for Hispanics who were fully exposed to school desegregation. (JEL H75, I24, J13, J15, K10, N32, R23)

ABSTRACT Reward systems based on balanced scorecards often connect pay to an index, that is, a weighted sum of multiple performance measures. We show that such an index contract may indeed be optimal if performance measures are nonverifiable so that the contracting parties must rely on self‐enforcement. Under commonly invoked assumptions (including normally distributed measurements), we show that the weights in the index reflect a tradeoff between distortion and precision for the measures. The efficiency of the contract improves with higher precision of the index measure, because this strengthens incentives, and correlations between measurements may for this reason be beneficial. There is a caveat, however, because the index contract is not necessarily optimal for very precise measurements, although it is shown to be asymptotically optimal. We also consider hybrid measurements, and show that the principal may want to include verifiable performance measures in the relational index contract in order to improve incentives, and that this has noteworthy implications for the formal contract.

The financial intermediation wedge of the banking sector used to co-move positively with the federal funds rate, but the post-GFC era saw a disconnect between them. We develop a flexible price dynamic general equilibrium with banks’ liquidity creation to offer an explanation. In a corridor system, the financial wedge and policy rate are shown to co-move, and the pass-through of monetary policy onto both inflation and output obtains. However, the post-GFC floor system obviates the need for the financial wedge to cover the cost of obtaining reserves, so the wedge and the policy rate indeed disconnect in equilibrium; furthermore, we show that the disconnect obstructs monetary expansions from generating inflation. In this environment, tightening bank capital requirement leads to disinflationary pressure. Money-financed fiscal expansions that subsidise non-bank sectors’ borrowing costs improve output and reduce default risks but increase inflation. The model uses banks’ liquidity creation via credit extension to provide a rationale for both the pre-pandemic disinflation and the post-pandemic inflation. The results hold both on the dynamic paths and in the steady state, and the role of money enlarges the Taylor rule determinacy region.

Mammography guidelines have weakened in response to evidence that mammograms diagnose breast cancers that would never eventually cause symptoms, a phenomenon called "overdiagnosis." Given concerns about overdiagnosis, instead of recommending mammograms, US guidelines encourage women aged 40-49 to get them as they see fit. To assess whether these guidelines target women effectively, I propose an approach that examines mammography behavior within an influential clinical trial that followed participants long enough to find overdiagnosis. I find that women who are more likely to receive mammograms are healthier and have higher socioeconomic status. More importantly, I find that the 20-year level of overdiagnosis is at least 3.5 times higher among women who are most likely to receive mammograms. At least 36% of their cancers are overdiagnosed. These findings imply that US guidelines encourage mammograms among healthier women who are more likely to be overdiagnosed by them. Guidelines in other countries do not.

Abstract We show how to use commuting flows to infer the spatial distribution of income within a city. A simple workplace choice model predicts a gravity equation for commuting flows whose destination fixed effects correspond to wages. We implement this method with cell phone transaction data from Dhaka and Colombo. Model-predicted income predicts separate income data, at the workplace and residential level, and by skill group. Unlike machine learning approaches, our method does not require training data, yet it achieves comparable predictive power. We show that hartals (transportation strikes) in Dhaka reduce commuting more for high model-predicted wage and high skill commuters.