arXiv subjects

Philipp Eisenhauer

Publications and source records attributed to Philipp Eisenhauer.

3 recordsLinked to original sources

arXiv2024

Sequential Choices, Option Values, and the Returns to Education

Using detailed Norwegian data on earnings, education and work histories, we estimate a dynamic structural model of education and sector choices that captures rich life-cycle patterns by ability. We validate the model against variation in education choices induced by a compulsory schooling reform. Our approach allows us to estimate the ex-ante returns to different education tracks across the life-cycle by individual ability and quantify the contribution of option values. We find substantial heterogeneity in returns and establish crucial roles for option values and re-enrollment in determining education choices and the impact of schooling policies.

econ.GN↗

arXiv2022

Structural models for policy-making: Coping with parametric uncertainty

The ex-ante evaluation of policies using structural econometric models is based on estimated parameters as a stand-in for the true parameters. This practice ignores uncertainty in the counterfactual policy predictions of the model. We develop a generic approach that deals with parametric uncertainty using uncertainty sets and frames model-informed policy-making as a decision problem under uncertainty. The seminal human capital investment model by Keane and Wolpin (1997) provides a well-known, influential, and empirically-grounded test case. We document considerable uncertainty in the models's policy predictions and highlight the resulting policy recommendations obtained from using different formal rules of decision-making under uncertainty.

econ.EM↗

arXiv2021

Robust decision-making under risk and ambiguity

Economists often estimate economic models on data and use the point estimates as a stand-in for the truth when studying the model's implications for optimal decision-making. This practice ignores model ambiguity, exposes the decision problem to misspecification, and ultimately leads to post-decision disappointment. Using statistical decision theory, we develop a framework to explore, evaluate, and optimize robust decision rules that explicitly account for estimation uncertainty. We show how to operationalize our analysis by studying robust decisions in a stochastic dynamic investment model in which a decision-maker directly accounts for uncertainty in the model's transition dynamics.

econ.EM↗