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Topics in Microeconometrics Professor William Greene Stern School of Business, New York University at Curtin Business School Curtin University Perth July 22-24, 2013. 4. Frontier Model Extensions. Model Extensions. Model Extensions. Simulation Based Estimators
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Topics in Microeconometrics Professor William Greene Stern School of Business, New York University at Curtin Business School Curtin University Perth July 22-24, 2013
Model Extensions • Simulation Based Estimators • Normal-Gamma Frontier Model • Bayesian Estimation of Stochastic Frontiers • A Discrete Outcomes Frontier • Similar Model Structures • Similar Estimation Methodologies • Similar Results
Functional Forms Normal-half normal and normal-exponential: Restrictive functional forms for the inefficiency distribution
Normal-Truncated Normal More flexible. Inconvenient, sometimes ill behaved log-likelihood function. MU=-.5 MU=0 MU=+.5
Normal-Gamma Very flexible model. VERY difficult log likelihood function. Bayesians love it. Conjugate functional forms for other model parts
Normal-Gamma Model z ~ N[-i + v2/u, v2]. q(r,εi) is extremely difficult to compute
Simulating the Log Likelihood • i = yi - ’xi, • i = -i - v2/u, • = v, and PL = (-i/) Fqis a draw from the continuous uniform(0,1) distribution.
Application to C&G Data This is the standard data set for developing and testing Exponential, Gamma, and Bayesian estimators.
Application to C&G Data Descriptive Statistics for JLMS Estimates of E[u|e] Based on Maximum Likelihood Estimates of Stochastic Frontier Models
Chanchala Ganjay Gadge CONTRIBUTIONS TO THE INFERENCE ON STOCHASTIC FRONTIER MODELS DEPARTMENT OF STATISTICS AND CENTER FOR ADVANCED STUDIES, UNIVERSITY OF PUNE PUNE-411007, INDIA