Learn R Programming

micEconSNQP (version 0.6-10)

snqProfitHessian: SNQ Profit function: Hessian matrix

Description

Returns the Hessian (substitution) matrix of a Symmetric Normalized Quadratic (SNQ) Profit Function.

Usage

snqProfitHessian( beta, prices, weights,
   scalingFactors = rep( 1, length( weights ) ) )

Arguments

beta

matrix of the \(beta\) coefficients.

prices

vector of netput prices at which the Hessian should be calculated.

weights

vector of weights of prices for normalization.

scalingFactors

factors to scale prices (and quantities).

See Also

snqProfitEst, snqProfitEla and snqProfitHessianDeriv.

Examples

Run this code
# NOT RUN {
# just a stupid simple example
snqProfitHessian( matrix(101:109,3,3), c(1,1,1), c(0.4,0.3,0.3) )

# now with real data
if( requireNamespace( 'micEcon', quietly = TRUE ) ) {
   data( germanFarms, package = "micEcon" )
   germanFarms$qOutput   <- germanFarms$vOutput   / germanFarms$pOutput
   germanFarms$qVarInput <- -germanFarms$vVarInput / germanFarms$pVarInput
   germanFarms$qLabor    <- -germanFarms$qLabor
   germanFarms$time <- c( 0:19 )
   priceNames <- c( "pOutput", "pVarInput", "pLabor" )
   quantNames <- c( "qOutput", "qVarInput", "qLabor" )

   estResult <- snqProfitEst( priceNames, quantNames, c("land","time"), data=germanFarms )

   estResult$hessian  # the Hessian at mean prices and mean quantities

   # Hessian at the last observation (1994/95)
   snqProfitHessian( estResult$coef$beta, estResult$data[ 20, priceNames ],
      estResult$weights, estResult$scalingFactors )
}
# }

Run the code above in your browser using DataLab