Structural models for policy-making: Coping with parametric uncertainty

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

Collaborators: Janos Gabler, Lena Janys


Uncertainty quantification and robust decision-making: Initiating a transdisciplinary research program

Computational models play an ever-increasing role in informing decisions. Domain-expertise is essential for developing models tailored to their intended application and the available data. However, the shared need to calibrate models to data and enable model-informed decisions creates many transdisciplinary research opportunities. Uncertainty, for example, is a major challenge across scientific domains. However, in practice, we often display incredible certitude when analyzing our models’ implications and disregard the uncertainties involved. Consequently, we accept fragile findings as facts, dueling certitudes stifle constructive debate, and we do not identify gaps in our knowledge. We bring together a transdisciplinary research team from economics, epidemiology, and finance to address these shortcomings.


Eckstein-Keane-Wolpin models: An invitation or transdisciplinary collaboration

We present background material on a class of structural microeconometric models to facilitate transdisciplinary collaboration in their future development. We describe the economic framework, mathematical formulation, and calibration procedures for the so-called Eckstein-Keane-Wolpin (EKW) models. We provide an exemplifying analysis of the seminal model outlined in Keane & Wolpin (1997) and present our group’s ensemble of research codes that allow for its specification, simulation, and calibration. We summarize our efforts drawing on research outside economics to address the computational challenges in applying EKW models and improve their results’ reliability and interpretability.