TY - JOUR

T1 - Robust Estimation of Finite Horizon Dynamic Economic Models

AU - Jørgensen, Thomas Høgholm

AU - Tô, Maxime

PY - 2020

Y1 - 2020

N2 - We study an estimation approach that is robust to misspecifications of the dynamic economic model being estimated. Specifically, the approach allows researchers to focus on a particular sub-problem or sub-period of the optimizing agent’s finite horizon and thus alleviates the need for assumptions regarding expectation formation about the (distant) future. This is accomplished by approximating a pseudo terminal period policy- or value function non-parametrically rather than fully specifying the remaining economic environment anticipated by agents until the terminal period. We illustrate through two Monte Carlo experiments the superior robustness of the approximate estimator compared to a standard full solution estimator.

AB - We study an estimation approach that is robust to misspecifications of the dynamic economic model being estimated. Specifically, the approach allows researchers to focus on a particular sub-problem or sub-period of the optimizing agent’s finite horizon and thus alleviates the need for assumptions regarding expectation formation about the (distant) future. This is accomplished by approximating a pseudo terminal period policy- or value function non-parametrically rather than fully specifying the remaining economic environment anticipated by agents until the terminal period. We illustrate through two Monte Carlo experiments the superior robustness of the approximate estimator compared to a standard full solution estimator.

KW - C51

KW - C61

KW - C63

KW - Finite horizon dynamic programming

KW - Robust

KW - Structural estimation

U2 - 10.1007/s10614-019-09898-8

DO - 10.1007/s10614-019-09898-8

M3 - Journal article

AN - SCOPUS:85066141292

VL - 55

SP - 499

EP - 509

JO - Computational Economics

JF - Computational Economics

SN - 0927-7099

IS - 2

ER -