Do debit cards increase household spending? Evidence from a semiparametric causal analysis of a survey

TL;DR

This paper investigates whether debit cards causally increase household spending using semiparametric methods and survey data from Italy, finding significant positive effects on monthly expenditure.

Contribution

It introduces a new doubly-robust estimator for causal effects and applies semiparametric modeling with cross-validation in a household spending context.

Findings

Debit cards significantly increase household monthly spending.

The proposed estimator performs well in simulation studies.

Assumptions of overlap and unconfoundedness are validated in the analysis.

Abstract

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.