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Does Failing to Account for Early Exposure Bias Explain Mass Shootings?


Pre-Treatment Exposure
Panel Data Analysis
Causal Inference
Mass Shootings
American Politics
BJPS
4 R files
1 datasets
Dataverse
Accounting for Pre-Treatment Exposure in Panel Data: Re-Estimating the Effect of Mass Public Shootings was authored by Todd K. Hartman and Benjamin J. Newman. It was published by Cambridge in BJPS in 2019.

Mass public shootings have long been a focus of political science research, but new findings suggest previous estimates may be flawed.

This study revisits causal claims about mass shootings by accounting for pre-treatment exposure—a critical factor often overlooked in prior work—using panel data techniques. The authors demonstrate how failing to address this issue can lead to misleading results.

Key Findings

* Accounting for pre-treatment exposure significantly alters estimated effects of relevant factors (e.g., gun laws, societal conditions).

* Standard methods used previously underestimate or misrepresent the true impact under appropriate conditions.

This means that decades of research on mass shootings may be systematically biased due to ignoring early-life risk factors before any intervention occurred.

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