(Previous Version: "Competition, Firm Innovation, and Growth under Imperfect Technology Spillovers"  [SSRN])

We study how frictions in learning others’ technology, termed "imperfect technology spillovers," impact firm innovation strategies and the aggregate economy through changes in innovation composition. We develop an endogenous growth model that generates strategic innovation decisions, where multi-product firms improve their products via own-innovation and enter new product markets through creative destruction under learning frictions. In our model, firms with technological advantages intensify own-innovation as learning frictions enable them to protect their markets from competitors, thereby reducing creative destruction of rivals. This pattern gets more pronounced when competitive pressure increases exogenously. Using U.S. administrative firm-level data, we provide regression results supporting the model predictions.

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

In this paper, I show that increasing foreign competition contributed to the recent decline in U.S. business dynamism by changing firms' innovation decisions. Using industry-level regressions with a generalized difference-in-difference identification strategy, I first show that rising competition from China substantially reduced young firm activities, startup rates, and employment growth of high-growth firms in the U.S. in the 2000s. I then develop a two-country model of firm innovation and show that increasing competitive pressure by foreign firms reduces high-growth firm activities and startup rates in the U.S. by inducing innovation-intensive and thus fast-growing firms to focus more on innovation for their product improvement (internal innovation) for defensive reasons. As these incumbents build technological barriers to better protect their markets, firms find it harder to enter others’ markets through innovation for business takeover (external innovation). As a result, the startup rate declines, and firms reduce investment in external innovation for entering new product markets. Since business takeover makes firms grow faster than they would through 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.