Zhang Chen

RESEARCH PAPERS

• Economic Growth and the Rise of Large Firms [2023 WP] [Latest Draft] 

Revise and Resubmit, Econometrica

I document that the right tail of the firm size distribution systematically thickens with economic development. To rationalize this fact, I develop a parsimonious idea search model in which both aggregate growth and the firm size distribution are endogenously determined. The model features an asymptotic balanced growth path along which Gibrat’s law holds at each date, and the right tail of the firm size distribution thickens monotonically toward Zipf’s law. The model also implies that policies favoring large firms can improve welfare by better utilizing the diffusion externalities arising from idea search.

• Export by Cohort [July 2023]

Using Chinese customs data, we document that, in a destination market, firms entering later tend to perform better at the same age. We interpret this fact through the lens of structural models of new exporter dynamics, among which two competing theories stand out: learning about demand and customer accumulation. We show that the relationship between sales lifecycle and cohort is informative about the main driver of post-entry exporter growth. A major class of demand learning models `a la Jovanovic (1982) predict flatter lifecycles for later cohorts, which are inconsistent with the parallel lifecycles seen in the data. On the other hand, we show analytically that customer accumulation models can generate parallel lifecycles. Guided by the qualitative analysis, we build a tractable customer base accumulation model with advertising, estimate it structurally and validate its capability to replicate the empirical cross-cohort exporter lifecycles. The model estimates suggest that rising foreign demand is the primary driver of the cohort effect: the increase in the initial customer base explains over 90% of the sales gains for later cohorts.

• Knowledge Diffusion Through Networks  [Dec 2019] 

How do geography and other barriers to the free flow of information shape the rate of knowledge diffusion? To address this question, we develop an empirical model of product discrete choice with Bayesian learning on a social network. Estimating this model using monthly data on the cholesterol-drug prescription decisions of over 50,000 U.S. physicians during January 2000 through December 2010, we find that the evolution of product choice efficiency is highly responsive to network structure changes, particularly targeted friction reductions that strengthen the strongest bilateral links.