data( germanFarms )
# output quantity:
germanFarms$qOutput <- germanFarms$vOutput / germanFarms$pOutput
# quantity of variable inputs
germanFarms$qVarInput <- germanFarms$vVarInput / germanFarms$pVarInput
# a time trend to account for technical progress:
germanFarms$time <- c(1:20)
# estimate a quadratic production function
estResult <- translogEst( "qOutput", c( "qLabor", "land", "qVarInput", "time" ),
germanFarms )
# compute the Hessian matrices (with "fitted" output)
hessians <- translogHessian( c( "qLabor", "land", "qVarInput", "time" ),
germanFarms, coef( estResult ) )
hessians[[ 1 ]]
# compute the Hessian matrices (with observed output)
hessiansObs <- translogHessian( c( "qLabor", "land", "qVarInput", "time" ),
germanFarms, coef( estResult ), "qOutput" )
hessiansObs[[ 1 ]]
# compute the bordered Hessian matrices
borderedHessians <- translogHessian( c( "qLabor", "land", "qVarInput", "time" ),
germanFarms, coef( estResult ), bordered = TRUE )
borderedHessians[[ 1 ]]
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