What are the effects of trademarks on the U.S. economy? Evidence from comprehensive micro data on trademark registrations and outcomes for U.S. employer firms suggests that trademarks protect firm value and are linked to higher firm growth and marketing activity. Motivated by this evidence, trademarks are introduced in a general equilibrium framework to quantify their aggregate effects. Firms invest in product quality and engage in both informative and persuasive advertising to build a customer base subject to depreciation. Persuasive advertising induces a perception of higher quality. Firms can register trademarks to reduce customer depreciation and enhance product awareness. The model's predictions about trademark registrations, firm growth, and advertising expenditures align with the empirical evidence. The analysis shows that, compared to the counterfactual economy without trademarks, the U.S. economy with trademarks generates higher average product quality but lower variety, ultimately resulting in greater welfare and higher industry concentration. While informative advertising improves welfare, persuasive advertising reduces it. Nevertheless, the positive welfare impact of trademarks outweighs the negative effects of persuasive advertising.
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Information and Industry Dynamics
August 2010
Working Paper Number:
CES-10-16R
This paper develops a dynamic industry model in which firms compete to acquire customers over time by disseminating information about themselves under the presence of random shocks to their efficiency. The properties of the model's stationary equilibrium are related to empirical regularities on firm and industry dynamics. As an application of the model, the effects of a decline in the cost of information dissemination on firm and industry dynamics are explored.
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An Anatomy of U.S. Firms Seeking Trademark Registration
April 2018
Working Paper Number:
CES-18-22
This paper reports on the construction of a new dataset that combines data on trademark applications and registrations from the U.S. Patent and Trademark Office with data on firms from the U.S. Census Bureau. The resulting dataset allows tracking of various activity related to trademark use and protection over the life-cycle of firms, such as the first application for a trademark registration, the first use of a trademark, and the renewal, assignment, and cancellation of trademark registrations. Facts about firm-level trademark activity are documented, including the incidence and timing of trademark registration filings over the firm life-cycle and the connection between firm characteristics and trademark applications. We also explore the relation of trademark application filing to firm employment and revenue growth, and to firm innovative activity as measured by R&D and patents.
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Competition, Firm Innovation, and Growth under Imperfect Technology Spillovers
July 2024
Working Paper Number:
CES-24-40
We study how friction in learning others' technology, termed 'imperfect technology spillovers,' incentivizes firms to use different types of innovation and impacts the implications of competition through changes in innovation composition. We build an endogenous growth model in which multi-product firms enhance their products via internal innovation and enter new product markets through external innovation. When learning others' technology takes time due to this friction, increased competitive pressure leads firms with technological advantages to intensify internal innovation to protect their markets, thereby reducing others' external innovation. Using the U.S. administrative firm-level data, we provide regression results supporting the model predictions. Our findings highlight the importance of strategic firm innovation choices and changes in their composition in shaping the aggregate implications of competition.
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Asymmetric Learning Spillovers
April 1993
Working Paper Number:
CES-93-07
In this paper, I employ a linear-quadratic model of an industry characterized by learning by doing to examine the implications of asymmetric learning spillovers. Importantly, I show that distribution of spillover benefits can influence market structure in ways that can not be seen in models where spillovers are symmetric. If spillovers are asymmetric, a tradeoff between improved industry performance and increased market concentration can arise which does not occur when they are symmetric. This tradeoff leads to a policy dilemma; whether to promote static or dynamic efficiency in markets where learning is important.
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Learning and the Value of Relationships in International Trade
February 2016
Working Paper Number:
CES-16-11
How valuable are long-term supplier relationships? To address this question, this paper explores relationships between U.S. importers and their suppliers abroad. We establish several facts: almost half of U.S. imports involve relationships three years or older, relationship survival and traded quantity increase as a relationship ages, and long-term relationships were more resilient in the 2008-09 financial crisis. We present a model of importer learning and calibrate it using our data. We estimate large differences in the value of relationships across countries. Counterfactuals show that relationships are central to trade dynamics.
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Starting Up AI
March 2024
Working Paper Number:
CES-24-09R
Using comprehensive administrative data on business applications over the period 2004- 2023, we study business applications (ideas) and the resulting startups that aim to develop AI technologies or produce goods or services that use, integrate, or rely on AI. The annual number of new AI-related business applications is stable between 2004 and 2011, but begins to rise in 2012 with further increases from 2016 onward into the Covid-19 pandemic and beyond, with a large, discrete jump in 2023. The distribution of these applications is highly uneven across states and sectors. AI business applications have a higher likelihood of becoming employer startups compared to other applications. Moreover, businesses originating from these applications exhibit higher revenue, average wage, and labor share, but similar labor productivity and lower survival rate, compared to other businesses. While it is still early in the diffusion of AI, the rapid rise in AI business applications, combined with the better performance of resulting businesses in several key outcomes, suggests a growing contribution from AI-related business formation to business dynamism.
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Multinational Production and Innovation in Tandem
October 2024
Working Paper Number:
CES-24-64
Multinational firms colocate production and innovation by offshoring them to the same host country or region. In this paper, I examine the determinants of multinational firms' production and innovation locations. Exploiting plausibly exogenous variations in tariffs, I find complementarities between production and innovation within host countries and regions. To evaluate manufacturing reshoring policies, I develop a quantitative multicountry offshoring location choice model. I allow for rich colocation benefits and cross-country interdependencies and prove supermodularity of the model to solve this otherwise NP-hard problem. I find the effects of manufacturing reshoring policies are nonlinear, contingent upon firm heterogeneity, and they accumulate dynamically.
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Workers' Job Prospects and Young Firm Dynamics
January 2025
Working Paper Number:
CES-25-09
This paper investigates how worker beliefs and job prospects impact the wages and growth of young firms, as well as the aggregate economy. Building a heterogeneous-firm directed search model where workers gradually learn about firm types, I find that learning generates endogenous wage differentials for young firms. High-performing young firms must pay higher wages than equally high-performing old firms, while low-performing young firms offer lower wages than equally low-performing old firms. Reduced uncertainty or labor market frictions lower the wage differentials, thereby enhancing young firm dynamics and aggregate productivity. The results are consistent with U.S. administrative employee-employer matched data.
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The Intangible Divide: Why Do So Few Firms Invest in Innovation?
February 2025
Working Paper Number:
CES-25-15
Investments in software, R&D, and advertising have surged, nearing half of U.S. private nonresidential investment. Yet just a few hundred firms dominate this growth. Most firms, including large ones, regularly invest little in capitalized software and R&D, widening this 'intangible divide' despite falling intangible prices. Using comprehensive US Census microdata, we document these patterns and explore factors associated with intangible investment. We find that firms invest significantly less in innovation-related intangibles when their rivals invest more. One firm's investment can obsolesce rivals' investments, reducing returns. This negative pecuniary externality worsens the intangible divide, potentially leading to significant misallocation.
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Learning By Doing And Competition In The Early Rayon Industry
February 1993
Working Paper Number:
CES-93-04
In this paper, I derive a structural econometric model of learning by doing from a dynamic oligopoly game. Unlike previous empirical models, this model is capable of testing hypotheses concerning both the technological nature and behavioral implications of learning. I estimate the model with firm level data from the early U.S. rayon industry. The empirical results show that there were considerable differences across firms in both proprietary and spillover learning. The results also indicate that two of the three firms took their rival's reactions into account when choosing their strategies.
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