Working Papers
Joint with Matin Safshekan, GWU.
We develop measures of R&D-driven uncertainty at the firm and aggregate level - the "fog of innovation." R&D is associated with a rise in
firm-level uncertainty with a lifecycle of 3-4 years. While aggregate uncertainty behaves like a negative supply shock, R&D-driven uncertainty
measured using forecast errors behaves like a positive supply shock.
Joint with Geyue Sun, GWU, Xiao Liu, UC Davis and Tomas Williams, GWU.
We develop new high frequency measures of capital controls with granularity regarding their intensity, direction, target and other dimensions of
heterogeneity using Artificial Intelligence. We also provide a new way to generate such measures using Artificial Intelligence that is significantly
less resource-intensive than alternative measures.
Joint with Naixin Zhang, GWU.
We develop measures of the political power of different industries based on the locations where they are based and the power of representatives
of those locations. We find that powerful industries are more likely to be the beneficiaries of industrial policy interventions.
Click here for an AI-generated presentation. Click here for a Highlighted 2026 AEA Highlighted Poster Video.
Joint with Matin Safshekan, GWU.
We develop measures of R&D-driven uncertainty at the firm and aggregate level - the "fog of innovation." R&D is associated with a rise in
firm-level uncertainty with a lifecycle of 3-4 years. While aggregate uncertainty behaves like a negative supply shock, R&D-driven uncertainty
measured using forecast errors behaves like a positive supply shock.
Joint with Geyue Sun, GWU, Xiao Liu, UC Davis and Tomas Williams, GWU.
We develop new high frequency measures of capital controls with granularity regarding their intensity, direction, target and other dimensions of
heterogeneity using Artificial Intelligence. We also provide a new way to generate such measures using Artificial Intelligence that is significantly
less resource-intensive than alternative measures.
Joint with Naixin Zhang, GWU.
We develop measures of the political power of different industries based on the locations where they are based and the power of representatives
of those locations. We find that powerful industries are more likely to be the beneficiaries of industrial policy interventions.
Click here for an AI-generated presentation. Click here for a Highlighted 2026 AEA Highlighted Poster Video.
- Robots and Inequality Between and Within Occupations
Joint with Rodimiro Rodrigo and Yun Zhang, GWU.
We show that automation is related to decreasing inequality within occupations, but increased inequality across occupations. We also show that a standard model of wage-posting accounts for these findings as long as it is the highest-productivity firms that automate, as found by the literature.
- Minimum Wage, Informality and Non-Compliance
Joint with Jinho Kim, Cardiff Business School.
We study the effect of the minimum wage in Indonesian household and firm level panel data. A higher minimum wage increases non-compliance, raises the wage distribution and brings people from the informal sector into the formal sector, while also rationing out marginal workers, consistent with an extension of the Burdett-Mortensen (1998) framework. We calibrate the model economy and find that the minimum wage has a negative overall impact on the size of the formal workforce.
Work in Progress
- Rule of Law and Firm Performance: Evidence from Vietnam
- Firm Credit and Loan Guarantees
- Uncertainty and Investment Specific Technical Change
