Research

Working Papers:

Slides

The U.S. economy has been experiencing an increase in productivity dispersion, which also co-moves with the rise of intangible capital. How would intangible capital lead to heterogeneous effect on productivity patterns? To explore this question, we introduce a new channel in which intangible capital meets skilled labor to operationalize its economic benefits, which requires economies of scale. Using firm-level measures of intangible capital and skill intensity, we document four related stylized facts: i) increasing productivity dispersion driven by large firms, particularly in intangible-intensive sectors, ii) a rise in intangible capital concentration among large firms, iii) higher skill intensity in large and intangible firms, and iv) higher productivity in large firms that exhibit higher levels of intangible capital and skill intensity. Based on these motivating facts, we build an empirical framework to quantify the effect of the intangible capital - skilled labor complementarity on firm-level productivity dynamics. We document that firms with higher intangible capital and skill intensity have higher productivity, which is amplified with firm size. To rationalize the reduced-form empirical evidence, we build a general equilibrium model with non-homothetic CES production technology to elucidate how the economies of scale shapes the complementarity within the firm-level production framework. Our calibrated model suggests that 80% of the complementarity between intangible capital and skilled labor over time is attributable to the economies of scale.

This study focuses on estimating the role of intangible capital on firms’ competitiveness. We use Lyft’s acquisition of Motivate, the biggest bike sharing company in the U.S. at the time, to evaluate the degree to which intangible capital affects the competition between Lyft and Uber. By acquiring Motivate, Lyft gained more consumer data as we interpret intangible capital, and bikes’ presence on the streets potentially helped Lyft build stronger brand salience. We estimate the effect of the acquisition on Lyft’s ridership by employing trip-level ride sharing data from New York City and using a difference-in-difference-in-differences model. We find that the acquisition helped Lyft increase its ridership by around 6%.

Work in Progress:

Scale up with Intangible Capital


Patents as Collateral: Innovative Financing for Innovation


Linking Real and Financial Connectedness, joint with Muhammed A. Yildirim (Harvard University & Koç University) and Kamil Yilmaz (Koç University)