Intangible Capital Meets Skilled Labor: The Implications for U.S. Business Dynamism (with Yusuf Ozkara) The U.S. economy has been experiencing a decline in aggregate productivity growth and an increase in productivity dispersion, which also co-moves with the rise of intangible capital. How would intangible capital lead to heterogeneous impacts on productivity patterns? To explore this question, we introduce a new channel in which intangible capital meets skilled labor to internalize 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, especially in intangible intensive sectors, ii) rising intangible capital concentration by large firms, iii) increasing number of skilled workers in large intangible firms, and iv) higher intangible-skill complementarity in large firms. Based on these motivating facts, we build an empirical framework to quantify the effects of the intangible capital - skilled labor complementarity on firm-level productivity dynamics. We find that complementarity brings higher productivity in large firms, whereas it has no effect on small firms. Hence, large firms' surge in intangible capital combined with skilled labor accounts for an increasing trend in productivity dispersion. We build a general equilibrium model that includes heterogeneous firms subject to adjustment costs investing in tangible and intangible capital, and hiring skilled and unskilled labor to discipline our reduced-form evidence. Consistent with the empirical insights, our model delivers that an increase in asset intangibility increases the skilled premium and productivity dispersion by replacing unskilled labor with skilled labor. The model also provides predictions, that are empirically tested, on the implications of intangible capital in the linkage between firm-level investment dynamics and labor reallocation. Intangible Capital and Competition in Ride Sharing: The Case of Lyft-Motivate Merger (with Hasan Tosun) 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%.