Last data update: 2014.03.03
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R: SNQ Profit function: Hessian matrix
snqProfitHessian | R Documentation |
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.
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prices |
vector of netput prices at which the Hessian
should be calculated.
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weights |
vector of weights of prices for normalization.
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scalingFactors |
factors to scale prices (and quantities).
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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
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 )
Results
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