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Topics in Microeconometrics Professor William Greene Stern School of Business, New York University PowerPoint Presentation
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Topics in Microeconometrics Professor William Greene Stern School of Business, New York University

Topics in Microeconometrics Professor William Greene Stern School of Business, New York University

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Topics in Microeconometrics Professor William Greene Stern School of Business, New York University

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  1. Topics in Microeconometrics Professor William Greene Stern School of Business, New York University at Curtin Business School Curtin University Perth July 22-24, 2013

  2. 4. Frontier Model Extensions

  3. Model Extensions

  4. 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

  5. Functional Forms Normal-half normal and normal-exponential: Restrictive functional forms for the inefficiency distribution

  6. Normal-Truncated Normal More flexible. Inconvenient, sometimes ill behaved log-likelihood function. MU=-.5 MU=0 MU=+.5

  7. Normal-Gamma Very flexible model. VERY difficult log likelihood function. Bayesians love it. Conjugate functional forms for other model parts

  8. Normal-Gamma Model z ~ N[-i + v2/u, v2]. q(r,εi) is extremely difficult to compute

  9. Normal-Gamma Frontier Model

  10. 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.

  11. Application to C&G Data This is the standard data set for developing and testing Exponential, Gamma, and Bayesian estimators.

  12. Application to C&G Data Descriptive Statistics for JLMS Estimates of E[u|e] Based on Maximum Likelihood Estimates of Stochastic Frontier Models

  13. Inefficiency Estimates

  14. Tsionas Fourier Approach to Gamma

  15. A 3 Parameter Gamma Model

  16. Discrete Outcome Stochastic Frontier

  17. 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