This paper studies the effect of competition on firm innovation by developing a discrete-time endogenous growth model where multi-product firms do two types of innovation subject to friction in technology spillovers. Firms improve their existing products through internal innovation while entering others' product markets through external innovation. We introduce a novel friction, which we label as imperfect technology spillovers, which refer to frictions in learning others' technology in the process of external innovation. In contrast to existing models, this friction allows incumbent firms to defend themselves from competitors by building technological barriers through internal innovation. Using firm-level data from the U.S. Census Bureau integrated with firm-level patent data, we find regression results consistent with the model predictions. Our counterfactual analysis shows that rising competition by foreign firms leads domestic incumbent firms to undertake (i) more (less) internal innovation for the products in which they have (do not have) a technological advantage, and (ii) less external innovation. This compositional change in firm innovation affects overall innovation in the aggregate economy in different directions depending on the costs of external innovation, suggesting different policy implications. Specifically, the shift in innovation composition in response to rising competition decreases overall innovation in the U.S., but would increase overall innovation in an economy with high external innovation costs.

(Previous Version: "Defensive Innovation and Firm Growth in the U.S.: Impact of International Trade" [Paper] [Technical Appendix])

This paper shows that increasing foreign competition contributed to the recent decline in business dynamism in the U.S. by changing firms' innovation decisions. I first present the results of industry-level regressions using a generalized difference-in-difference identification strategy. I find that rising competition from China substantially lowered the U.S. young firm activities, startup rates, and employment growth of high-growth firms in the 2000s. I then develop a two-country model of firm innovation and show that increasing competitive pressure by foreign firms leads to the decline in high-growth firm activities and startup rates in the U.S. by inducing innovation-intensive and thus fast-growing firms to invest more in innovation for their own product improvement (internal innovation) for defensive reasons. Since these innovative incumbents build technological barriers and become better at protecting their own markets, all types of firms find it difficult to enter others' markets through innovation for business takeover (external innovation). Thus, the startup rate falls, and all firms reduce their investment in external innovation for entering new product markets. Because business takeover makes firms grow faster than their own product improvement by requiring firms to hire a new set of workers to produce new products, this change in innovation patterns cuts the employment growth of innovation-intensive firms.

Do firms seek a better product match and grow by dropping existing products and adding new ones? How does this behavior vary over the firm life-cycle and business cycle? This paper investigates a "product match-quality ladder" channel empirically by using a detailed product-firm level administrative database for the U.S. manufacturing sector and documents salient features of product switching by firms. We newly estimate the match quality of product-firm pairs and obtain the following set of results: i) young firms are less likely to drop products with low match quality than mature firms; ii) dropping low match-quality products can increase the likelihood of adding products and the quality of products added subsequently, and iii) has a positive impact on firm performance and growth. These indicate that proper product switching is important for young firms to climb up the product match-quality ladder and achieve fast growth. Lastly, we further look into cyclical variations of the channel and find that iv) the product switching pattern of young firms gets even more pronounced in recessions. This provides a potential source accounting for procyclical young firm activities.

We use the U.S. patent data merged with firm-level datasets to establish new facts about the role of mega firms in generating “novel patents”—innovations that introduce new combinations of technology components for the first time. While the importance of mega firms in novel patents had been declining until about 2000, it has strongly rebounded since then. The timing of this turnaround coincided with the ascendance of firms that newly became mega firms in the 2000s, and a shift in the technological contents, characterized by increasing integration of Information and Communication Technology (ICT) and non-ICT components. Mega firms also generate a disproportionately large number of “hits”—novel patents that lead to the largest numbers of follow-on patents (subsequent patents that use the same combinations of technology components as the first novel patent)—and their hits tend to generate more follow-on patents assigned to other firms when compared to hits generated by non-mega firms. Overall, our findings suggest that mega firms play an increasingly important role in generating new technological trajectories in recent years, especially in combining ICT with non-ICT components.

This paper constructs a patent assignee-firm longitudinal bridge between U.S. patent assignees and firms using firm-level administrative data from the U.S. Census Bureau. We match granted patents applied between 1976 and 2016 to the U.S. firms recorded in the Longitudinal Business Database (LBD) in the Census Bureau. Building on existing algorithms in the literature, we first use the assignee name, address (state and city), and year information to link the two datasets. We then introduce a novel search-aided algorithm that significantly improves the matching results by 7% and 2.9% at the patent and the assignee level, respectively. Overall, we are able to match 88.2% and 80.1% of all U.S. patents and assignees respectively. We contribute to the existing literature by 1) improving the match rates and quality with the web search-aided algorithm, and 2) providing the longest and longitudinally consistent crosswalk between patent assignees and LBD firms.