1. Technology and Labor Displacement: Evidence from Linking Patents with Worker-Level Data

(with Leonid Kogan, Lawrence Schmidt and Bryan Seegmiller)

We develop separate measures of workers’ exposure to labor-saving and labor-augmenting technologies based on textual analysis of patent documents and the tasks performed by workers in an occupation. Using administrative data on earnings of individual workers in the US, we show that these exposure measures are both negatively related to earnings of incumbent workers. Exposure to labor-saving technologies is associated with significant declines in average earnings and a higher likelihood of job loss for all worker types. By contrast, exposure to labor-augmenting technologies is associated with earnings declines for only certain types of workers: white collar workers, older workers, and workers that are paid more relative to their peers. In contrast to these effects on incumbents, we find a positive overall effect of labor-augmenting technologies on total worker compensation, employment, and the labor share. We interpret the sign and magnitudes of these effects through a model that also allows for skill displacement.

[Paper] [ Slides]

 

2. Time Variation in Risk Premia, Labor Market Dynamics, and Income Risk

American Economic Review, Revise and Resubmit

We provide both theory and evidence that time-variation in risk premia results in time-varying idiosyncratic income risk for workers. Using administrative data on worker earnings from the United States, we show that increases in risk premia lead to lower worker earnings for workers at the bottom of the income distribution; these declines are primarily driven by job separations. This pattern lies in sharp contrast to productivity shocks, which mainly affect earnings for workers at the top of the income distribution. We build an equilibrium model of labor market search that quantitatively replicates these facts. The model generates endogenous time-variation in income risk in response to changes in risk premia and matches several stylized features of the data regarding unemployment and income risk over the business cycle.

[Paper][Slides]

 

3. Intangible Capital, Non-rivalry, and Growth

(with Nicolas Crouzet, Janice Eberly, and Andrea Eisfeldt)

We provide an answer as to why growth may slow even in the face of technological improvements. Our focus is on the role of intangible assets. Intangible assets are distinct from physical capital in that they are comprised by information that requires a storage medium. A reduction in replication costs for intangible assets enables them to be less rivalrous in use, stimulating growth. However, we show how limits to excludability create a countervailing force that limits growth. This paper subsumes the working paper A model of intangible capital.

[Paper (ver. 10/2022)]

 

4. Technological Change and Occupations over the Long Run

(with Leonid Kogan, Lawrence Schmidt and Bryan Seegmiller)

We construct occupation-specific indicators of technological change that span two centuries (1850-2010) using textual analysis of patent documents and occupation task descriptions. We find strong evidence that much of technical change has been displacive of labor during this period.

[Under Revision, new version coming soon]

 

5. Technological Innovation and Labor Income Risk

(with Leonid Kogan, Lawrence Schmidt and Jae Song)

Using administrative data, we examine how labor income risk depends on innovation shocks.

[Under Revision, new version coming soon]

 

6. Evaluation and Learning in R&D Investment

(with Alex Frankel, Danielle Li and Joshua Krieger)

[Paper (ver. 12/2022)]