snqProfitHessian: SNQ Profit function: Hessian matrix

In micEconSNQP: Symmetric Normalized Quadratic Profit Function

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).

Author(s)

Arne Henningsen

See Also

snqProfitEst, snqProfitEla and snqProfitHessianDeriv.

Examples

# 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 )
}

micEconSNQP documentation built on June 21, 2022, 5:07 p.m.