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William Greene Stern School of Business New York University. Stochastic Frontier Models. 0 Introduction 1 Efficiency Measurement 2 Frontier Functions 3 Stochastic Frontiers 4 Production and Cost 5 Heterogeneity 6 Model Extensions 7 Panel Data 8 Applications.

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William greene stern school of business new york university

William Greene

Stern School of Business

New York University

Stochastic Frontier Models

0 Introduction

1 Efficiency Measurement

2 Frontier Functions

3 Stochastic Frontiers

4 Production and Cost

5 Heterogeneity

6 Model Extensions

7 Panel Data

8 Applications


Deterministic frontier programming estimators
Deterministic Frontier: Programming Estimators



Statistical problems with programming estimators
Statistical Problems with Programming Estimators

  • They do correspond to MLEs.

  • The likelihood functions are “irregular”

  • There are no known statistical properties – no estimable covariance matrix for estimators.

  • They might be “robust,” like LAD.

    • Noone knows for sure.

    • Never demonstrated.


An orthodox frontier model with a statistical basis
An Orthodox Frontier Modelwith a Statistical Basis


Extensions
Extensions

  • Cost frontiers, based on duality results:

    ln y = f(x) – u  ln C = g(y,w) + u’

    u > 0. u’ > 0. Economies of scale and

    allocative inefficiency blur the relationship.

  • Corrected and modified least squares estimators based on the deterministic frontiers are easily constructed.



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