I’m currently a Donald P. Jacobs Scholar in the finance department at the Kellogg School of Management at Northwestern University. I received my PhD from the MIT Sloan School of Management in May 2022.
PhD in Financial Economics, 2022
Massachusetts Institute of Technology
MS in Management Research, 2020
Massachusetts Institute of Technology
BS in Economics and Mathematics (magna cum laude), 2016
Brigham Young University
We develop a granular, occupation-specific measure of technological progress that relies only on textual descriptions of patent documents and the tasks performed by workers in an occupation. Our measure primarily identifies labor-saving innovations and is broadly available from the 19th century to the present. Examining the type of worker tasks most exposed to innovation, we find that while non-routine manual (physical) and routine-manual tasks have been highly exposed throughout the last 150 years, the innovations of the information technology revolution in the post-1980 period saw an increased relationship with cognitive tasks. Using a panel of administrative data on worker earnings, we show that the earnings of older and more highly-paid workers are more responsive to our technology exposure measure, a pattern consistent with skill displacement. Our calibrated model fits these facts and emphasizes the importance of movements in skill quantities, not just skill prices, for the link between technology and inequality.
Consistent with the exercise of market power, firms with high labor productivity have low labor shares, high profitability, and high market valuations without high investment rates. I quantify the economic value that firms of different productivity levels derive from their labor market power by estimating the effect of unanticipated firm-level labor demand shocks on wages and employment at publicly listed U.S. firms. Productive firms face lower labor supply elasticities on average, and still lower elasticities for skilled workers, who are disproportionately employed at more productive firms. Using a dynamic wage posting model in which firms face upward-sloping labor supply and adjustment costs in hiring, I estimate that firms in the top and bottom quartiles of labor productivity pay 62% and 94% of marginal product, despite the fact that adjustment costs temper the exercise of labor market power. Markdown differentials can explain three-fifths of the average spread in log labor shares between high- and low-labor productivity firms, and the evolution of these differentials can explain most of the change in the aggregate labor share in the 1991–2014 period. Holding constant equilibrium labor demand, I estimate that about a third of capital income for the typical firm stems from wage markdowns. Aggregate wage markdowns are worth two-fifths of total capital income.
Recent theory stresses the role of new job types (‘new work’) in counterbalancing the erosive effect of task-displacing automation on labor demand. Drawing on a novel inventory of eight decades of new job titles linked to United States Census microdata, we estimate that the majority of contemporary employment is found in new job tasks added since 1940 but that the locus of new task creation has shifted—from middle-paid production and clerical occupations in the first four post-WWII decades, to high-paid professional and, secondarily, low-paid services since 1980. We hypothesize that new tasks emerge in occupations where new innovations complement their outputs (‘augmentation’) or market size expands, while conversely, employment contracts in occupations where innovations substitute for labor inputs (‘automation’) or market size contracts. Leveraging proxies for output-augmenting and task-automating innovations built from a century of patent data and harnessing occupational demand shifts stemming from trade and demographic shocks, we show that new occupational tasks emerge in response to both positive demand shifts and augmenting innovations, but not in response to negative demand shifts or automation innovations. We document that the flow of both augmentation and automation innovations is positively correlated across occupations, yet these two faces of innovation have strongly countervailing relationships with occupational labor demand.
Stocks with similar characteristics but different levels of ownership by financial institutions have returns and risk premia that comove very differently with shocks to the risk-bearing capacity of financial intermediaries. After accounting for observable stock characteristics, excess returns on more intermediated stocks have higher betas on contemporaneous shocks to intermediary willingness to take risk and are more predictable by state variables that proxy for intermediary health. The empirical evidence supports the predictions of asset pricing models featuring financial intermediaries as marginal investors who face frictions that induce changes in their risk-bearing capacity. This suggests that such models are useful for explaining price movements not only in markets for complex financial assets, but also within asset classes where households face comparatively low barriers to direct participation.
TA: Spring 2019
TA: Spring 2019
TA: Fall 2015
TA: Spring 2014