A Linear Estimator for Factor-Augmented Fixed-T Panels With Endogenous Regressors
| Autor: | Vasilis Sarafidis, Artūras Juodis |
|---|---|
| Přispěvatelé: | Research programme EEF |
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: |
Statistics and Probability
Economics and Econometrics Moment condition 05 social sciences Urban water management Fixed T consistency Estimator Endogeny 01 natural sciences 010104 statistics & probability Factor (programming language) 0502 economics and business Moment conditions Econometrics Common factors 0101 mathematics Statistics Probability and Uncertainty computer Social Sciences (miscellaneous) 050205 econometrics Mathematics computer.programming_language Panel data |
| Zdroj: | Journal of business & economic statistics Journal of Business and Economic Statistics, 40(1), 1-15. AMER STATISTICAL ASSOC |
| ISSN: | 1537-2707 0735-0015 |
| Popis: | A novel method-of-moments approach is proposed for the estimation of factor-augmented panel data models with endogenous regressors when T is fixed. The underlying methodology involves approximating the unobserved common factors using observed factor proxies. The resulting moment conditions are linear in the parameters. The proposed approach addresses several issues which arise with existing nonlinear estimators that are available in fixed T panels, such as local minima-related problems, a sensitivity to particular normalization schemes, and a potential lack of global identification. We apply our approach to a large panel of households and estimate the price elasticity of urban water demand. A simulation study confirms that our approach performs well in finite samples. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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