This paper presents the bayesian approach to analyze small sample elasticity distributions with locally regular flexible functional forms. It is known that for a translog cost function these are t student conditional on factor shares, otherwise they are a nonlinear combination of parameters and predictive, whose distributional properties cannot be analytically derived. However a simple Monte Carlo composition method can be used to approximate moments even with inequality constraints such as monotonicity and concavity. This approach is applied to the well known Berndt-Wood data set.

Appraising elasticities in small samples. A bayesian approach

GREGORI, TULLIO
1994

Abstract

This paper presents the bayesian approach to analyze small sample elasticity distributions with locally regular flexible functional forms. It is known that for a translog cost function these are t student conditional on factor shares, otherwise they are a nonlinear combination of parameters and predictive, whose distributional properties cannot be analytically derived. However a simple Monte Carlo composition method can be used to approximate moments even with inequality constraints such as monotonicity and concavity. This approach is applied to the well known Berndt-Wood data set.
Bayesian Analysis, Flexible Functional Forms, Inequality Constraints, Monte Carlo methods.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11368/2843579
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