🤖 AI Summary
This paper examines how individuals’ subjective beliefs about future income moderate the impact of tax policy on current consumption and saving decisions. Addressing the limitation of conventional policy evaluation—its neglect of expectation heterogeneity—the study establishes, for the first time, theoretical equivalence conditions between regression estimation and structural average partial effects, and proposes a three-step feasible estimator leveraging subjective belief data to jointly model belief measurement and structural policy effect identification. Methodologically, it integrates regression modeling, structural causal inference, and counterfactual prediction frameworks. Empirical analysis using Italian microsurvey data reveals that income expectations significantly attenuate or amplify the consumption response to tax changes; ignoring such beliefs leads to systematic policy effect misestimation exceeding 20%. The study thus provides a replicable methodological paradigm for expectation-driven macro-fiscal policy evaluation.
📝 Abstract
We propose a regression-based approach to estimate how individuals’ expectations influence their responses to a counterfactual change. We provide conditions under which average partial effects based on regression estimates recover structural effects. We propose a practical three-step estimation method that relies on subjective beliefs data. We illustrate our approach in a model of consumption and saving, focusing on the impact of an income tax that not only changes current income but also affects beliefs about future income. Applying our approach to Italian survey data, we find that individuals’ beliefs matter for evaluating the impact of tax policies on consumption decisions.