frontierQuad: Quadratic or Translog Frontiers

In frontier: Stochastic Frontier Analysis

Description

This is a convenient interface for estimating quadratic or translog stochastic frontier functions using frontier.

Usage

frontierQuad( yName, xNames, shifterNames = NULL, zNames = NULL,
   data, lrTests = FALSE, ... )

Arguments

yName	string: name of the endogenous variable.
xNames	a vector of strings containing the names of the X variables (exogenous variables of the production or cost function) that should be included as linear, quadratic, and interaction terms.
shifterNames	a vector of strings containing the names of the X variables that should be included as shifters only (not in quadratic or interaction terms).
zNames	a vector of strings containing the names of the Z variables (variables explaining the efficiency level).
data	a (panel) data frame that contains the data; if data is a usual data.frame, it is assumed that these are cross-section data; if data is a panel data frame (created with pdata.frame), it is assumed that these are panel data.
lrTests	logical. If TRUE, likelihood ratio tests are conducted to test the statistical significance of each X variable.
...	further arguments passed to frontier.

Value

frontierQuad returns a list of class frontierQuad (and frontier) containing the same elements as returned by frontier. If argument lrTest is set to TRUE, the returned object has a component lrTests that contains the results of likelihood-ratio tests of the statistical significance of each X variable.

Author(s)

Arne Henningsen

See Also

frontier.

Examples

   # example included in FRONTIER 4.1 (cross-section data)
   data( front41Data )
   front41Data$logOutput  <- log( front41Data$output )
   front41Data$logCapital <- log( front41Data$capital )
   front41Data$logLabour  <- log( front41Data$labour )

   # estimate the translog function
   translog <- frontierQuad( yName = "logOutput",
      xNames = c( "logCapital", "logLabour" ),
      data = front41Data )
   translog

   # estimate the same model using sfa()
   translog2 <- sfa( logOutput ~ logCapital + logLabour
      + I( 0.5 * logCapital^2 ) + I( logCapital * logLabour )
      + I( 0.5 * logLabour^2 ), data = front41Data )
   translog2
   all.equal( coef( translog ), coef( translog2 ),
      check.attributes = FALSE )

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/

Call:
frontierQuad(yName = "logOutput", xNames = c("logCapital", "logLabour"),      data = front41Data)

Maximum likelihood estimates
      a_0        a_1        a_2      b_1_1      b_1_2      b_2_2    sigmaSq  
 0.809280   0.391869   0.363922  -0.183240   0.005075   0.057687   0.189391  
    gamma  
 0.762324  

Call:
sfa(formula = logOutput ~ logCapital + logLabour + I(0.5 * logCapital^2) +      I(logCapital * logLabour) + I(0.5 * logLabour^2), data = front41Data)

Maximum likelihood estimates
              (Intercept)                 logCapital  
                 0.809280                   0.391869  
                logLabour      I(0.5 * logCapital^2)  
                 0.363922                  -0.183240  
I(logCapital * logLabour)       I(0.5 * logLabour^2)  
                 0.005075                   0.057687  
                  sigmaSq                      gamma  
                 0.189391                   0.762324  
[1] TRUE

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