lrtest.frontier: Likelihood Ratio test for Stochastic Frontier Models

In frontier: Stochastic Frontier Analysis

Description

Testing parameter restrictions in stochastic frontier models by a Likelihood Ratio test.

Usage

   ## S3 method for class 'frontier'
lrtest( object, ... )

Arguments

object	a fitted model object of class frontier.
...	further fitted model objects of class frontier.

Details

If lrtest.frontier is called with only one argument/object (i.e. argument ... is not used), it compares the fitted model to a corresponding model without inefficiency (i.e. estimated by OLS).

If lrtest.frontier is called with more than one argument/object (i.e. argument ... is used), it consecutively compares the fitted model object object with the models passed in ....

The test statistic is 2 * ( logLik( mu ) - logLik( mr ) ), where mu is the unrestricted model and mr is the restricted model.

If a Frontier model (estimated by ML) is compared to a model without inefficiency (estimated by OLS), the test statistic asymptotically has a mixed χ^2 distribution under the null hypothesis (see Coelli, 1995).

If two Frontier models (estimated by ML) are compared, the test statistic asymptotically has a χ^2 distribution with j degrees of freedom under the null hypothesis, where j is the number of restrictions.

Value

An object of class anova, which contains the log-likelihood value, degrees of freedom, the difference in degrees of freedom, likelihood ratio Chi-squared statistic and corresponding p value. See documentation of lrtest in package "lmtest".

Author(s)

Arne Henningsen

References

Coelli, T.J. (1995), Estimators and Hypothesis Tests for a Stochastic: A Monte Carlo Analysis, Journal of Productivity Analysis, 6, 247-268.

See Also

sfa, lrtest

Examples

# rice producers in the Philippines (panel data)
data( "riceProdPhil" )
library( "plm" )
riceProdPhil <- pdata.frame( riceProdPhil, c( "FMERCODE", "YEARDUM" ) )

# Error Components Frontier with truncated normal distribution
# and time effects (unrestricted model)
mu <- sfa( log( PROD ) ~ log( AREA ) + log( LABOR ) + log( NPK ),
   truncNorm = TRUE, timeEffect = TRUE, data = riceProdPhil )

# Error Components Frontier with half-normal distribution
# without time effects (restricted model)
mr <- sfa( log( PROD ) ~ log( AREA ) + log( LABOR ) + log( NPK ),
   data = riceProdPhil )

## compare the two models by an LR-test
lrtest( mu, mr )

## compare each of the models to a corresponding model without inefficiency
lrtest( mu )
lrtest( mr )

Example output

Loading required package: micEcon

If you have questions, suggestions, or comments regarding one of the 'micEcon' packages, please use a forum or 'tracker' at micEcon's R-Forge site:
https://r-forge.r-project.org/projects/micecon/
Loading required package: lmtest
Loading required package: zoo

Attaching package: 'zoo'

The following objects are masked from 'package:base':

    as.Date, as.Date.numeric


Please cite the 'frontier' package as:
Tim Coelli and Arne Henningsen (2013). frontier: Stochastic Frontier Analysis. R package version 1.1. http://CRAN.R-Project.org/package=frontier.

If you have questions, suggestions, or comments regarding the 'frontier' package, please use a forum or 'tracker' at frontier's R-Forge site:
https://r-forge.r-project.org/projects/frontier/
Loading required package: Formula
Likelihood ratio test

Model 1: mu
Model 2: mr
  #Df  LogLik Df  Chisq Pr(>Chisq)
1   8 -84.407                     
2   6 -86.430 -2 4.0473     0.1322
Likelihood ratio test

Model 1: OLS (no inefficiency)
Model 2: Error Components Frontier (ECF)
  #Df   LogLik Df Chisq Pr(>Chisq)    
1   5 -104.907                        
2   8  -84.407  3    41  2.298e-09 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Likelihood ratio test

Model 1: OLS (no inefficiency)
Model 2: Error Components Frontier (ECF)
  #Df  LogLik Df  Chisq Pr(>Chisq)    
1   5 -104.91                         
2   6  -86.43  1 36.953  6.051e-10 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

frontier documentation built on April 19, 2020, 3:54 p.m.