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Replication Package for: Star Firms, Information Spillovers, and Predictable Industry-Level Outcomes
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Replication Package for: Star Firms, Information Spillovers, and Predictable Industry-Level Outcomes

Vidhi Chhaochharia, Alok Kumar, Mehrshad Motahari and Ville Rantala
Harvard Dataverse
2026

Abstract

Business and Management Social Sciences
This replication package contains the SAS and Stata programs, pseudonymized data, and documentation needed to reproduce the empirical results in the paper "Star Firms, Information Spillovers, and Predictable Industry-Level Outcomes." The package includes code for constructing firm-level and industry-level datasets, estimating earnings growth and earnings surprise regressions, macro-outcome regressions (GDP and employment), dynamic panel GMM analyses, and portfolio construction for asset-pricing tests. Data sources used include CRSP, Compustat, I/B/E/S, LinkUp, BEA, BLS, patent data (Kogan et al. 2017), markup data (De Loecker et al. 2020), technology spillover scores (Bloom et al. 2013), vertical integration scores (Fresard et al. 2020), and Fama-French factors. All supplied datasets are pseudonymized (capped at 1,000 observations with pseudo variable values), except for industry code and linking tables (NAICS/BEA mappings). The analysis is conducted using SAS 9.4 and Stata/SE 18.0 on Windows 64-bit.
url
https://doi.org/10.7910/dvn/g9ukjbView
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