Estimation of Structural Models Using Experimental Data From the Lab and the Field

Behavioral economics provides a framework for understanding non-classical preferences and belief formation, while experimental approaches allow for the estimation of structural models. The combination of behavioral and experimental economics provides a natural setting for the estimation of structural models, with examples covering outcome-based preferences, belief-dependent preferences, and risk preferences. This Element aims to facilitate the adoption of structural modelling by providing Stata codes to replicate some of the empirical illustrations.

Format: Paperback / softback
Length: 75 pages
Publication date: 09 February 2023
Publisher: Cambridge University Press

Behavioral economics offers a comprehensive framework for understanding and modeling non-classical preferences and belief formation, which can be employed to estimate structural models of decision-making. At the same time, experimental approaches enable researchers to manipulate exogenously various aspects of the decision-making environment. The interplay between behavioral and experimental economics creates a fertile ground for estimating structural models. This Element will explore examples that support the following arguments:
1. Experimental data enables researchers to estimate structural models under weaker assumptions, simplifying their estimation process.
2. Many popular models in behavioral economics can be estimated without the need for advanced programming skills, thanks to readily available software tools.
3. Experimental methods serve as valuable tools for validating structural models, providing empirical evidence to support their validity.
4. This Element aims to promote the adoption of structural modeling by offering Stata codes that replicate some of the empirical illustrations presented. Examples covered include estimation of outcome-based preferences, belief-dependent preferences, and risk preferences.
By leveraging the strengths of behavioral economics and experimental methods, researchers can gain a deeper understanding of decision-making processes and develop more accurate structural models that can inform policy and practice.

ISBN-13: 9781009362634