Working Papers

Abstract: I study how the interaction between large acquirers and small targets shapes upper tail firm size inequality via acquisition and innovation. Empirically, I compile a new dataset, tracking dynamic ownership of public and private firms, along with their patents from in-house development or acquisitions. I identify three innovation channels through which acquisitions drive firm growth: (i) acquirers develop more innovations using target firms' patents; (ii) acquirers use acquisitions to expand into new areas; (iii) acquisitions shield acquirers’ innovations from becoming technologically obsolete. Using firm random growth theories, I derive the dynamics of firm size distribution based on the dynamics of individual firms, modeling the growth of acquiring firms as a jump-diffusion process consistent with the empirically uncovered innovation channels. I find that acquisitions increase stationary firm size inequality and lead to a faster rise in inequality at the upper tail of firm size distributions.

"Firm Dynamics and Innovation: Evidence from Decomposing Top Sales Shares

Abstract: What do changes in top sales shares signal about changes in firm dynamics? I use an accounting decomposition to identify two sources of top sales share growth: (i) incumbent top firms grow bigger; (ii) new top firms replace old top firms. Over the 1950-2019 period, incumbent top firms contribute about four times as much as new top firms to the growth of sales share accrued to the top 0.01% firms in the US economy. I then build an analytical framework to estimate a firm dynamics process in which firms grow in response to an own innovation shock and shrink at the impact of a creative destruction shock using the empirical decomposition terms of top share growth. I find that own innovation is the major force that drives top sales share growth. The decline in the top sales shares in the 1980s is associated with a higher aggregate productivity growth, while the rise in the top sales shares since the late 1990s implies a slightly lower productivity growth.

"Employment during the COVID-19 Pandemic: Collapse and Early Recovery" (with Tam Mai)

Abstract: We use monthly Current Population Survey data to document employment changes during the COVID-19 pandemic at the occupation, industry, and metropolitan statistical area (MSA) levels. Over March-April 2020, jobs losses are larger for occupations with higher physical proximity or lower work-from-home feasibility, especially for lower-paying occupations. Nonessential industries also see greater declines in employment. Such occupational and industrial susceptibility to COVID-19 contributes to the variation in employment changes across MSAs: Employment shrinks more for MSAs with larger pre-crisis fractions of workers employed in occupations with higher infection risk. Over April-June 2020, occupations and industries that are hit harder recoup more jobs, but the recovery is only partial. Moreover, the gains are concentrated in lower-paying occupations and a few industries. Taken together, these abrupt changes in employment following the COVID-19 outbreak are unprecedented and potentially have longterm implications for occupational inequality and regional disparity.

"Income Inequality and Mortgage Credit Allocation"

Abstract: This paper studies how income inequality at the Metropolitan Statistical Area (MSA) level affect mortgage credit allocation along the income distribution of households within MSAs. I find that MSAlevel income inequality has heterogeneous effect on household-level mortgage debt accumulation. Two measures of inequality, the ratio of 95th-to-80th percentile (p95/p80) and the ratio of 80th-to-50th percentile (p80/p50) of household income, exhibit significant impact. With respect to credit approval along the income distribution, high p95/p80 inequality works more in favor of low-income households while high p80/p50 inequality benefits high-income households more.

Work in Progress 

"Scientific Breakthroughs, Entrepreneurial Finance and Firm Dynamics

Abstract: Access to frontier technology is a major driver of modern economic growth. I seek to understand how entrepreneurial finance promotes the diffusion of frontier knowledge developed in the academia by funding startups that make use of new technologies. I then track how such advanced technologies spread into large firms via acquisitions or via the usage of Corporate Venture Capital (CVC). I empirically identify scientific breakthroughs by performing text analyses on academic research papers and patent documents. One such key scientific breakthrough that I have identified is CRISPR-Cas9. The discovery of the revolutionary gene-editing tool CRISPR-Cas9 in 2012 has resulted in the establishment of a growing list of VC- funded startups wielding this unique powerful tool to solve complex problems in healthcare, agriculture and clean energy. 


Publications (in Biomedical Science, from previous PhD study)