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A multiple indicator solution approach to endogeneity in discrete-choice models for environmental valuation
Petr Mariel1, David Hoyos2, Alaitz Artabe3
1Department of Applied Economics III (Econometrics and Statistics), University of the Basque Country (UPV/EHU), Spain; Avda. Lehendakari Aguirre, 83. E48015 Bilbao, Spain.
The Science of the Total Environment
|May 16, 2018
Summary
The multiple indicator solution method effectively addresses endogeneity in discrete choice models for environmental valuation, offering parsimonious and implementable welfare estimates compared to hybrid models.
Area of Science:
- Environmental Economics
- Econometrics
- Discrete Choice Modelling
Background:
- Endogeneity poses significant challenges in discrete choice models, leading to inconsistent parameter estimates and biased welfare measures.
- Omitted explanatory variables are a common source of endogeneity in environmental valuation studies.
- Existing methods for addressing endogeneity can be complex or yield suboptimal results.
Purpose of the Study:
- To analyze the performance of the multiple indicator solution method for handling endogeneity in discrete choice models.
- To propose and demonstrate a factor analysis approach for selecting appropriate indicators.
- To compare the multiple indicator solution method with the hybrid choice modelling framework.
Main Methods:
- Application of the multiple indicator solution method to address endogeneity from omitted variables.
- Utilisation of factor analysis for indicator selection in discrete choice models.
- Comparative analysis with the hybrid choice modelling framework using empirical data.
Main Results:
- The multiple indicator solution method and the hybrid model approach yield comparable welfare estimates.
- The multiple indicator solution method is more parsimonious and significantly easier to implement.
- Factor analysis provides a practical procedure for indicator selection.
Conclusions:
- The multiple indicator solution method is a viable and efficient alternative for addressing endogeneity in discrete choice models for environmental valuation.
- Its parsimony and ease of implementation make it attractive for empirical applications.
- Further research should explore its performance with different endogeneity sources and indicator sets.
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