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Stochastic Frontier Models

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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Stochastic Frontier Models

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  1. 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

  2. Deterministic Frontier: Programming Estimators

  3. Estimating Inefficiency

  4. 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.

  5. An Orthodox Frontier Modelwith a Statistical Basis

  6. 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.

  7. Data Envelopment Analysis

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