snqProfitImposeConvexity: Imposing Convexity on a SNQ Profit function

Description

Imposing Convexity on a Symmetric Normalized Quadratic (SNQ) Profit function.

Usage

snqProfitImposeConvexity( estResult, rankReduction = 0,
   start = 10, optimMethod = "BFGS", control = list( maxit=5000 ),
   stErMethod = "none", nRep = 1000, verbose = 0 )

Arguments

estResult

object returned by snqProfitEst.

rankReduction

an integer specifying the reduction of the rank of the $\beta$ matrix.

start

starting values of the triangular Cholesky matrix.

optimMethod

method to be used by optim.

control

list of control parameters passed to optim.

stErMethod

method to compute standard errors, either 'none', 'resample', 'jackknife' or 'coefSim' (see details).

nRep

number of replications to compute the standard errors if stErMethod is either 'resample' or 'coefSim'.

verbose

an integer idicating the verbose level.

Value

a list of class snqProfitImposeConvexity containing the same objects as an object of class snqProfitEst and additionally the objects:
mindistobject returned by . sim{results of the simulation to obtain the standard errors of the estimated coefficients.}
Koebel, B., M. Falk and F. Laisney (2000), Imposing and Testing Curvature Conditions on a Box-Cox Cost Function. Discussion Paper No. 00-70, ZEW, Mannheim, ftp://ftp.zew.de/pub/zew-docs/dp/dp0070.pdf.
Koebel, B., M. Falk and F. Laisney (2003), Imposing and Testing Curvature Conditions on a Box-Cox Cost Function. Journal of Business and Economic Statistics, 21, p. 319-335.
snqProfitEst.
[object Object]
data( germanFarms ) germanFarms$qOutput <- germanFarms$vOutput / germanFarms$pOutput germanFarms$qVarInput <- -germanFarms$vVarInput / germanFarms$pVarInput germanFarms$qLabor <- -germanFarms$qLabor priceNames <- c( "pOutput", "pVarInput", "pLabor" ) quantNames <- c( "qOutput", "qVarInput", "qLabor" ) estResult <- snqProfitEst( priceNames, quantNames, "land", data = germanFarms ) estResult # Note: it is NOT convex in netput prices estResultConvex <- snqProfitImposeConvexity( estResult ) estResultConvex # now it is convex
models

Details

The procedure proposed by Koebel, Falk and Laisney (2000, 2003) is applied to impose convexity in prices on an estimated symmetric normalized quadratic (SNQ) profit function. The standard errors of the restricted coefficients can be either calculated by bootstrap resampling ('resampling'), jackknife ('jacknife') or by simulating the distribution of the unrestricted coefficients using its variance covariance matrix ('coefSim').