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Big Wins, Small Net Gains: Direct and Spillover Effects of First Industry Entries in Puerto Rico

Jorge A. Arroyo

arXiv 22 Nov 2025 · General Economics

arXiv:2511.19469 · PDF · DOI · OpenAlex · Extracted main text

Abstract

I study how first sizable industry entries reshape local and neighboring labor markets in Puerto Rico. Using over a decade of quarterly municipality--industry data (2014Q1--2025Q1), I identify “first sizable entries” as large, persistent jumps in establishments, covered employment, and wage bill, and treat these as shocks to local industry presence at the municipio--industry level. Methodologically, I combine staggered-adoption difference-in-differences estimators that are robust to heterogeneous treatment timing with an imputation-based event-study approach, and I use a doubly robust difference-in-differences framework that explicitly allows for interference through pre-specified exposure mappings on a contiguity graph. The estimates show large and persistent direct gains in covered employment and wage bill in the treated municipality--industry cells over 0--16 quarters. Same-industry neighbors experience sizable short-run gains that reverse over the medium run, while within-municipality cross-industry and neighbor all-industries spillovers are small and imprecisely estimated. Once these spillovers are taken into account and spatially robust inference and sensitivity checks are applied, the net regional 0--16 quarter effect on covered employment is positive but modest in magnitude and estimated with considerable uncertainty. The results imply that first sizable entries generate substantial local gains where they occur, but much smaller and less precisely measured net employment gains for the broader regional economy, highlighting the importance of accounting for spatial spillovers when evaluating place-based policies.

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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Shahn, Zach and Zivich, Paul N. and Renson, Audrey (2024) Structural Nested Mean Models Under Parallel Trends with Interference1.00086100%
2Callaway, Brantly and Sant'Anna, Pedro H. C (2021) Difference-in-Differences with Multiple Time Periods1.00085100%
3Roth, Jonathan and Sant'Anna, Pedro H. C. and Bilinski, Alyssa and P… (2023) What's trending in difference-in-differences? A synthesis of the recent econometrics literature1.00055100%
4Xu, Ruonan (2023) Difference-in-Differences with Interference0.95014786%
5Sävje, Fredrik (2023) Causal Inference with Misspecified Exposure Mappings: Separating Definitions and Assumptions0.9285480%
6Liu, Lan and Hudgens, Michael\,G. and Saul, Bradley and Clemens, Joh… (2019) Doubly Robust Estimation in Observational Studies with Partial Interference0.92843100%
7Rambachan, Ashesh and Roth, Jonathan (2023) A More Credible Approach to Parallel Trends0.92843100%
8Aronow, Peter M. and Eckles, Dean and Samii, Cyrus and Zonszein, Ste… (2020) Spillover Effects in Experimental Data0.8746567%
9Baker, Andrew and Callaway, Brantly and Goodman-Bacon, Andrew and Cu… (2025) Difference-in-Differences Designs: A Practitioner's Guide0.84333100%
10Della Vigna, Stefano and Imbens, Guido W. and Kim, Woojin and Ritzwo… (2025) Using Multiple Outcomes to Adjust Standard Errors for Spatial Correlation0.84333100%

Showing the top 10 of 44 scored citations.