Frontier and Efficiency Analysis: Stochastic Frontier Analysis and Data Envelopment Analysis

LIMDEP and NLOGIT are the only programs that provide tools for both stochastic frontier analysis and data envelopment analysis.

Stochastic Frontier Analysis

Model frameworks for production or cost

  • Corrected OLS
  • Normal-half normal
  • Normal-truncated normal
  • Normal-exponential
  • Normal-gamma
  • Normal-Rayleigh
  • Semiparametric LOWESS
  • Sample selection

Mean of the one sided (inefficiency) component

  • E[U] = zero mean, the standard case
  • E[U] = nonzero constant mean
  • E[U] = a'z

Variance of the one sided (inefficiency) component

  • Var[U] = homoscedastic
  • Var[U] = exp(c'z) (heteroscedastic)

Variance of the firm specific (symmetric) component

  • Var[v] = homoscedastic
  • Var[v] = exp(d'w) (heteroscedastic)

Doubly heteroscedastic

Estimates of inefficiency measures automatically computed with all formulations

Partial effects of environmental variables on inefficiency

Stochastic frontier analysis using LIMDEP and NLOGIT

Panel data formulations

  • Random effects in specifications
    • Pitt and Lee time invariant
    • True random effects
  • Fixed effects
    • Schmidt and Sickles
    • True fixed effects in production or cost function
    • Truncation model with fixed effects
    • Fixed effects in mean of one sided component
    • Fixed effects in variance of one sided component
    • Method of moments for TFE
  • Random parameters
  • Generalized true random effects
  • Latent class
  • Zero inefficiency latent class
  • Sample selection
  • Battese and Coelli panel data models

Data Envelopment Analysis

Data envelopment analysis (DEA) using LIMDEP and NLOGIT

Analysis in parallel with stochastic frontier estimation and analysis (the only package available that has both of these methods in one program)

  • Input and output oriented inefficiency – retained in the data set for further analysis
  • Constant, increasing or nonincreasing returns to scale
  • Economic and allocative inefficiency
  • Bootstrapped confidence intervals for efficiency scores
  • Malmquist total factor productivity indexes for panel data
  • Listing of ‘peer’ firms with results