Coping with unobservables in estimating production functions: An example with US banking data
This paper (i) derives a number of properties of a newly specified multi-input-single-output (MISO) production function with a derived error term, and (ii) using iteratively rescaled generalized least squares, presents estimates of the cross-sectionally varying coefficients of a multi-input-multi-ou...
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Elsevier
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/17a0a8ceb2b640bb973fd2c8e2538cbd |
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| Sumario: | This paper (i) derives a number of properties of a newly specified multi-input-single-output (MISO) production function with a derived error term, and (ii) using iteratively rescaled generalized least squares, presents estimates of the cross-sectionally varying coefficients of a multi-input-multi-output (MIMO) production function with a derived error term based on newly derived conditions for estimating the total effects of its regressors on its dependent variable, when an unknown number of unobserved inputs is potentially involved in production. The results indicate that for the years 2008, 2009, and 2010, the coefficient estimates do not contain simultaneous-equations biases, bank heterogeneity is not pronounced, and non-transaction accounts turn out to be the dominant input. |
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