This paper discusses a series of Monte Carlo experiments designed to evaluate the empirical properties of heterogeneous-agent macroeconomic models in the presence of sampling variability. The calibration procedure leads to the welfare analysis being conducted with the wrong parameters. The ability of the calibrated model to correctly predict the welfare changes induced by a set of policy experiments is assessed. The results show that, for the economy and the policy reforms under analysis, the model always predict the right sign of the welfare effects. Quantitatively, the maximum errors made in evaluating a policy change are very small for some reforms (in the order of 0.05 percentage points), but bigger for others (in the order of 0.5 pp). Finally, having access to better data, in terms of larger samples, does lead to sizable increases in the precision of the welfare effects estimates.
Monte Carlo Heterogeneous Agents Incomplete Markets, Ex-ante Policy Evaluation Welfare