Job Market Paper

Endogenous Firm Structure and Worker SpecializationPDF

Abstract: What tasks must be performed to produce a good? Which occupations are well suited to do those tasks? And what are the aggregate productivity gains from reorganizing firms to use the optimal mix of occupations to complete those tasks. I use Brazilian administrative data to document several new facts about how firms systematically vary the types of workers that they choose to hire as they grow larger. Bigger firms hire more distinct occupations, and systematically vary the average skill level of their workers, along the cognitive, manual, and interpersonal dimensions, with larger firms hiring a set of workers whose skills are more dispersed than at small firms. I then develop a structural model of how firms choose which types of workers to hire, and how they assign tasks to those workers. I propose a novel identification strategy for how to indirectly infer the (multi-dimensional) distribution of skill requirements for tasks that firms face and show how one can estimate the distribution of tasks that firms face using only cross-sectional data on which occupations firms choose to hire, and in what proportion, across the firm size distribution. I estimate this model using Brazilian manufacturing firms, and show that more than 1/3 of the variance in firm level TFP is due to firm’s endogenous choices of which types of workers to hire (and how specialized those workers should be). I find gains from increasing firm specialization are bounded at around 1.3% of output, the costs to shutting down worker specialization within the firm are large, leading to a 9.6% decrease in total output.

In Progress

Credit Access and the Earnings Mobility of Workers and Entrepreneurs with Carter Braxton, Kyle Herkenhoff, and Gordon Phillips

Abstract: Does greater access to credit increase the earnings mobility of workers and entrepreneurs? Has the expansion of consumer credit contributed to the increase in earnings inequality? We answer the first question by linking individual credits reports to administrative earnings data for workers as well as entrepreneurs. We answer the second question by developing a tractable labor sorting model with human capital accumulation. We link TransUnion credit reports to the LEHD on scrambled social security numbers. We stratify individuals based on credit scores (the marginal cost of credit), and credit limits (the stock of credit), and we document their lifecycle earnings mobility patterns from 1998 to 2008. We instrument access to credit using house price variation and credit account ages in 1998. We find that credit access has an insignificant effect on earnings mobility among initially low earning households. We find that credit access has significant positive significant effect on the earnings mobility of high earning households. We find similar results for entrepreneurial income, with those who have initially high entrepreneurial earnings benefiting the most from credit access. We estimate our model to match these facts, and then we counterfactually shut down credit markets. We find that credit access, while welfare improving, significantly increases measured wage and entrepreneurial income inequality.


Do Long-Haul Truckers Undervalue Future Fuel Savings?Journal Link

Do Long-Haul Truckers Undervalue Future Fuel Savings? Jacob Adenbaum and John J. Stevens Energy Economics (June 2019) vol. 81, pp. 1148-1166

Abstract: The U.S. federal government enacted fuel efficiency standards for medium and heavy trucks for the first time in September 2011. Rationales for using this policy tool typically depend upon frictions existing in the marketplace or consumers being myopic, such that vehicle purchasers undervalue the future fuel savings from increased fuel efficiency. We measure by how much long-haul truck owners undervalue future fuel savings by employing recent advances to the classic hedonic approach to estimate the distribution of willingness-to-pay for fuel efficiency. We find significant heterogeneity in truck owners’ willingness to pay for fuel efficiency, with the elasticity of fuel efficiency to price ranging from 0.51 at the 10th percentile to 1.33 at the 90th percentile, and an average of 0.91. Combining these results with estimates of future fuel savings from increases in fuel efficiency, we find that long-haul truck owners’ willingness-to-pay for a 1 percent increase in fuel efficiency is, on average, just 29.8% of the expected future fuel savings. These results suggest that introducing fuel efficiency standards for heavy trucks might be an effective policy tool to raise medium and heavy trucks’ fuel economy.