Research

Job Market Paper:

Intangible Capital Meets Skilled Labor: The Implications for U.S. Business Dynamism

joint with Yusuf Ozkara (Boston College)

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. To rationalize the reduced-form empirical evidence, we build a general equilibrium model of heterogeneous firms subject to adjustment costs investing in tangible and intangible capital, and hiring skilled and unskilled labor. Consistent with the empirical evidence, 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 generates testable predictions on the role of intangibility in the relation between investment dynamics and labor reallocation.

Working Papers:

Intangible Capital and Competition in Ride Sharing: The Case of Lyft-Motivate Merger

joint with Hasan K. Tosun (University of Minnesota)

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%.

Linking Real and Financial Connectedness

joint with Muhammed Ali Yildirim (Koc University) and Kamil Yilmaz (Koc University)

We investigate the relationship between the fundamental and market values of U.S. industry-portfolio returns. In particular, we first map and compare how real and financial connectedness in industry networks behave and co-move over time. Second, we use ordinary least squares regression analysis to quantify whether the real linkages between industries predict the industry-portfolio financial connectedness. We have four different real economic network measures constructed by: (i) the flow of specialized inputs; (ii) employment; (iii) patent holdings; and (iv) geographic proximity/co-agglomeration. We use the Diebold-Yilmaz connectedness index methodology on industry-portfolio returns to estimate the industry-portfolio financial connectedness, which uses variance decompositions of vector auto-regressions. Using techniques from graph theory, we first find that several industries form observable clusters in real economic networks, whereas such clustering is not observed in financial networks. Second, industries with higher GDP shares (make values) in real economic networks are not the biggest drivers of the financial connectedness, which could prove that dynamics of financial and production markets have subtle differences. Our empirical findings suggest that industry-portfolio financial connectedness and the explanatory power of each real economic network on financial connectedness display heterogeneous patterns. During tranquil times, each real economy linkage has a higher explanatory power on determining financial connectedness. However, during times of turmoil, industry-portfolio financial connectedness is not an inter-industry phenomenon; instead, each industry portfolio becomes more susceptible to the overall financial environment.

Work in Progress:

Patents as Collateral: Innovative Financing for Innovation

During the Great Recession, innovation activity in the U.S. experienced a collapse, which coincided with a deterioration in financing conditions and a historic decline in house prices. Motivated by these facts, I explore a causal channel of local consumer demand through house prices on firms' innovation dynamism. In that regard, I investigate how innovative firms try to smooth out the negative demand shock by using their tangible and intangible assets. I find that innovation activity in non-tradable firms declined in response to a housing crisis, and this effect was amplified with financial frictions. As key evidence, I document that by using their intangible capital, patents in the context of this study, as collateral, some firms relaxed financial frictions and were able to mitigate the negative demand shock. The big picture takeaway suggests that firms' intellectual property is a protective entity and a valuable asset for the financing of innovation when they face negative economic shocks.

Scale up with Intangible Capital

This paper investigates the role of scalable intangible capital in the U.S. productivity dynamics. I argue that big firms produce scalable intangible capital to become the front-runner and leave laggards behind. I use a novel approach to measure the scalability of intangible capital based on large-scale patent data and empirically investigate the association between the scalability of intangible capital and productivity dynamics. I find that scalable intangible capital enhances firm-level productive capacity, which is complementary to firm size. I document a set of evidence that bigger firms use their scalable intangible capital to spill over their knowledge capital within the firm boundary. In contrast, the knowledge does not diffuse to other firms as scalable intangible capital becomes firm-specific and challenging to be reverse-engineered. As a result, scalable intangible capital from which frontier and giant firms disproportionately benefit accounts for the facts on higher productivity dispersion in the U.S. economy.

Adjusting Innovation: Firm-Level Responses to Trade Shocks

joint with Ari Boyarsky (Columbia Business School)

Many studies document various effects of trade shocks on firm and industry-level outcomes that generate winners and losers. However, there is a diverse set of evidence on which forces, in particular, lead to failure and success stories. This paper aims to contribute to this discussion by investigating the adjustments in firm-level innovation strategy in response to trade shocks. We plan to measure the firm adjustments in i) quality upgrading, ii) patenting activities, iii) process and product innovation, and iv) inventor composition. We aim to use large-scale patent data from the USPTO to investigate these adjustments using patent text-mining techniques. We decompose the total effect of trade shocks on the firm-level adjustments into four main underlying channels: 1) Direct effects at the exposed firms, 2) Indirect effects on other firms, which are captured through the network of patent citations, 3) Within and across industry reallocation effects, which are captured through inventor mobility, 4) Demand effects to capture the general equilibrium forces. This decomposition aims to answer the following questions: In high trade exposure industries, do we observe quality upgrading from productive firms that try to adapt to the changing business environment? Do we see large reallocation within and across industries with varying trade exposures? Can we quantify static loss (such as an increase in unemployment and decline in investment) but dynamic gain (such as quality upgrading and human capital reallocation) in industries with differential trade exposures? Thereby investigating how heterogeneity in firm-level responses to trade shocks may inform the trade policy decisions.

Global Intangibles with Local Humans: The Role of Multinational Companies

joint with Ivan Kirov (Analysis Group)

U.S. multinationals (MNC) have experienced a dramatic increase in overseas R&D expenditures, which implies that they create an ''intellectual value chain'' besides the global value chain. How would MNCs achieve this success story? What are key differences in innovation patterns between MNCs and domestic firms in host countries? How do MNCs benefit from local knowledge in host countries? Do MNCs spill over their know-how to other domestic firms in host countries? We plan to address these questions based on our argument that MNCs combine the local talent pool available in host countries with their global intangible to engage in frontier innovations. We aim to merge the universal coverage of patenting activities through the private database PatSnap with the administrative firm-level data on the operations of multinational firms from the Bureau of Economic Analysis (BEA). It enables us to track all the patenting activities and inventor networks of U.S. multinational companies (MNC) and their global investment in intangible capital. We aim to identify to what extent intangible capital (such as R&D, organizational business capital, and software) accumulated at the headquarter of U.S. MNCs boosts the knowledge spillover from local inventors and test the hypothesis that domestic firms at host countries are not able to benefit from U.S. MNCs because intangible capital at the U.S. headquarters is hard to be reverse-engineered. If the hypothesis comes true, we will document the asymmetric effects of trade linkages through the interaction of U.S. MNCs' global intangible capital and local inventors at host countries.