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Efficiency Measurement

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Presentation on theme: "Efficiency Measurement"— Presentation transcript:

1 Efficiency Measurement
William Greene Stern School of Business New York University

2 Session 2 Frontier Functions

3 Deterministic Frontier: Programming Estimators

4 Estimating Inefficiency

5 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 estimates. They might be “robust,” like LAD. Noone knows for sure. Never demonstrated.

6 An Orthodox Frontier Model with a Statistical Basis

7 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.

8 Data Envelopment Analysis

9 Methodological Problems with DEA
Measurement error Outliers Specification errors The overall problem with the deterministic frontier approach

10 DEA and SFA: Same Answer?
Christensen and Greene data N=123 minus 6 tiny firms X = capital, labor, fuel Y = millions of KWH Cobb-Douglas Production Function vs. DEA (See Coelli and Perelman (1999).)

11

12 Comparing the Two Methods.

13 Total Factor Productivity


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