期刊
ANNALS OF APPLIED STATISTICS
卷 8, 期 4, 页码 2485-2508出版社
INST MATHEMATICAL STATISTICS
DOI: 10.1214/14-AOAS784
关键词
Causal inference; potential outcomes; payment instruments; power series; propensity score; overlap; unconfoundedness
资金
- Divn Of Social and Economic Sciences
- Direct For Social, Behav & Economic Scie [1155697] Funding Source: National Science Foundation
Motivated by recent findings in the field of consumer science, this paper evaluates the causal effect of debit cards on household consumption using population-based data from the Italy Survey on Household Income and Wealth (SHIW). Within the Rubin Causal Model, we focus on the estimand of population average treatment effect for the treated (PATT). We consider three existing estimators, based on regression, mixed matching and regression, propensity score weighting, and propose a new doubly-robust estimator. Semiparametric specification based on power series for the potential outcomes and the propensity score is adopted. Cross-validation is used to select the order of the power series. We conduct a simulation study to compare the performance of the estimators. The key assumptions, overlap and unconfoundedness, are systematically assessed and validated in the application. Our empirical results suggest statistically significant positive effects of debit cards on the monthly household spending in Italy.
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