CSESTUDY: Stata module to provide Efficient Inference for Cross-Sectional Event Studies

Jonathan Cohn (), Travis Johnson (), Zack Liu and Malcolm Wardlaw
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Jonathan Cohn: University of Texas at Austin
Travis Johnson: University of Texas at Austin

Statistical Software Components from Boston College Department of Economics

Abstract: csestudy implements the time-series approach to cross-sectional event study inference described in Cohn, Johnson, Liu, and Wardlaw (2026), "Past is Prologue: Inference from the Cross Section of Returns Around an Event," Journal of Financial Economics 180, 104278. Standard event study methodologies typically fail to account for the cross-correlation structure in stock returns across firm characteristics, and clustering standard errors by industry does not address this. The command benchmarks the event-period coefficient against a distribution of the same relationship estimated on pre-event days, using either OLS or GLS with a PCA-based covariance estimator. Rejection criteria are reported as a parametric z-score and a p-value from the empirical CDF of pre-event coefficients.

Language: Stata
Requires: Stata version 14
Keywords: event study; cross sectional data; corporate finance (search for similar items in EconPapers)
Date: 2026-04-20
Note: This module should be installed from within Stata by typing "ssc install csestudy". The module is made available under terms of the MIT license (https://opensource.org/licenses/MIT).
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http://fmwww.bc.edu/repec/bocode/c/csestudy.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/c/csestudy.mata program code (text/plain)
http://fmwww.bc.edu/repec/bocode/c/csestudy.sthlp help file (text/plain)

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