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  5. Innovation, Spillovers, and Global/Spatial Dynamics
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Innovation, Spillovers, and Global/Spatial Dynamics

Paper Session

Sunday, Jan. 4, 2026 10:15 AM - 12:15 PM (EST)

Philadelphia Marriott Downtown, Room 414
Hosted By: Korea-America Economic Association & American Economic Association
  • Chair: Yoonseok Lee, Syracuse University

From Research to Development: How Globalization Shapes Corporate Innovation

Chan Kim
,
International Monetary Fund

Abstract

I show that globalization has shifted U.S. corporate innovation from scientific research to commercial development. Analyzing data from publicly traded firms, I find that substantial tariff reductions at export destinations following the “Uruguay Round” led U.S. firms to focus on a narrower range of technologies, reducing their emphasis on scientific research. To explain these findings, I develop a multi-product firm model that distinguishes between research and development. Globalization—represented by expanded market size or lower trade costs—reallocates profits toward products for which firms hold a competitive advantage. Consequently, firms increasingly prioritize developing core products over broader research. The model embeds a crucial welfare trade-off:
development increases the supply of high-productivity products, but research enhances the overall innovation efficiency of the economy through knowledge spillovers. Calibration to U.S. manufacturing firms shows that allowing separate decisions on research versus development amplifies the productivity gains from globalization but reduces welfare gains. The welfare-maximizing
policy suggests that research subsidies should exceed development subsidies, particularly after globalization, to counteract the decline in research share.

Connected Trade Flows: How Spillovers Reshape Global Trade and Amplify Pair-Specific Heterogeneity?

Hanbat Jeong
,
Macquarie University
Jieun Lee
,
Emory University

Abstract

This paper introduces a novel spatial interaction model and estimation method for international trade flows. These flows are typically captured through Origin-Destination (OD) flows, which represent directional movements or forces between locations, and are commonly analyzed using gravity-type equations. However, traditional gravity models have critical limitations: (1) they fail to account for the interconnectedness of trade flows arising from interactions among countries, resulting in spillover effects and pair-specific heterogeneity, and (2) they assume all cross-sectional units are equally influential, overlooking the influence of dominant units. To this end, we propose a spatial interaction model with microfoundations that explicitly incorporates various interactions, capturing spillover effects across trade flows and pair-specific heterogeneity. Our estimation approach employs a Poisson maximum likelihood estimator tailored for the conditional expectation of trade levels. We further adjust standard errors to account for unknown correlation structures among trade pairs and heteroskedasticity, explicitly addressing the influence of dominant units to ensure robust statistical inference. Monte Carlo simulations demonstrate the estimator’s consistency and reasonable nominal coverage.
In our empirical application, we suspect different structures and sources of spillover effects across the following four phases: Phase 1 (1986, trade liberalization), Phase 2 (1997, NAFTA implementation), Phase 3 (2000s, emergence of the China trade shock), and Phase 4 (recent period, expansion of global supply chains). We identify variations in spillover patterns among trade pairs across these phases. We investigate whether differences in spillover mechanisms lead to varying effects of trade policies, such as tariffs or free trade agreements. Our impact analysis further addresses several critical questions, including how country-specific shocks—such as economic restructuring or changes in trade policy—affect international trade flows, and how geopolitical conflicts between two countries influence third-party nations. Finally, we examine how risks originating from dominant economies propagate, potentially causing welfare losses for consumers.

Heterogeneous Innovation and Growth under Imperfect Technology Spillovers

Karam Jo
,
Pennsylvania State University
Seula Kim
,
Pennsylvania State University and IZA

Abstract

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. Importantly, the shift in innovation composition reduces aggregate growth, as creative destruction contributes more to growth. Using U.S. administrative firm-level data, we provide regression results supporting the model predictions.

Powering Intelligence: Data Centers and Spatial Welfare

Sungwan Hong
,
University of Pittsburgh

Abstract

The construction of hyperscale data centers is driven by U.S. states offering cheap electricity. Using proprietary data on data center locations and power capacities, I first empirically show the stark geographic concentration of capacity additions. I then build a quantitative spatial model integrating AI/datacenters to study the economic implications of this boom.
JEL Classifications
  • O3 - Innovation; Research and Development; Technological Change; Intellectual Property Rights
  • D8 - Information, Knowledge, and Uncertainty