Full Citation
Title: SNAP Enrollment Cycles: New Insights from Heterogeneous Panel Models with Cross-Sectional Dependence
Citation Type: Miscellaneous
Publication Year: 2022
ISBN:
ISSN:
DOI: 10.22004/AG.ECON.322367
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PMCID:
PMID:
Abstract: The Supplemental Nutrition Assistance Program (SNAP) has grown rapidly over the past two decades. A large body of literature relies on state-level macro (aggregate) panel data on SNAP caseloads and implements traditional two-way fixed effects (TWFE) estimators to isolate the causal impact of economic conditions on SNAP enrollment. This empirical strategy implicitly assumes slope parameter homogeneity and ignores the possibility of cross-sectional dependence in the error term. The latter could feasibly arise in macro panel data if the unobserved common shocks have different effects on SNAP participation across US states. This study empirically evaluates the appropriateness of these two assumptions by adopting a more general common factor model that allows for both slope heterogeneity and cross-sectional dependence in the error term. Comparing results across different estimators, we find that TWFE estimators yield spuriously much larger estimates of the impact of the economy. This result is largely driven by TWFE assuming cross-sectional independence of error terms, while imposing a common slope assumption across states is less problematic for identification. Our counterfactual simulations confirm our main findings, implying the importance of carefully accounting for time-varying unobserved heterogeneity when analyzing the predictors of SNAP enrollment using state-level macro panel data.
Url: https://ageconsearch.umn.edu/record/322367
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Authors: Valizadeh, Pourya; Fischer, Bart L.; Bryant, Henry L.
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Data Collections: IPUMS CPS
Topics: Health, Methodology and Data Collection
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