snqProfitFixEla {micEconSNQP} | R Documentation |
Fixed Factor Elasticities of SNQ Profit function
Description
Calculates the Fixed Factor Elasticities of a Symmetric Normalized Quadratic (SNQ) profit function.
Usage
snqProfitFixEla( delta, gamma, quant, fix, weights,
scalingFactors = rep( 1, length( weights ) ) )
Arguments
delta |
matrix of estimated |
gamma |
matrix of estimated |
quant |
vector of netput quantities at which the elasticities should be calculated. |
fix |
vector of quantities of fixed factors at which the elasticities should be calculated. |
weights |
vector of weights of prices used for normalization. |
scalingFactors |
factors to scale prices (and quantities). |
Note
A fixed factor elasticity is defined as
E_{ij} = \frac{ \displaystyle \frac{ \partial q_i }{ q_i } }
{ \displaystyle \frac{ \partial z_j }{ z_j } } =
\frac{ \partial q_i }{ \partial z_j } \cdot \frac{ z_j }{ q_i }
Thus, e.g. E_{ij}=0.5
means that if the quantity of fixed factor j
(z_j
) increases by 1%, the quantity of netput i (q_i
) will
increase by 0.5%.
Author(s)
Arne Henningsen
See Also
snqProfitEst
and snqProfitEla
.
Examples
# just a stupid simple example
snqProfitFixEla( matrix(1:6/6,3,2 ), matrix(4:1/4,2 ), c(1,1,1), c(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$time <- c( 0:19 )
priceNames <- c( "pOutput", "pVarInput", "pLabor" )
quantNames <- c( "qOutput", "qVarInput", "qLabor" )
fixNames <- c( "land", "time" )
estResult <- snqProfitEst( priceNames, quantNames, fixNames, data=germanFarms )
estResult$fixEla # price elasticities at mean quantities of netputs
# and fixed factors
# fixed factor elasticities at the last observation (1994/95)
snqProfitFixEla( estResult$coef$delta, estResult$coef$gamma,
estResult$data[ 20, quantNames ], estResult$data[ 20, fixNames ],
estResult$weights, estResult$scalingFactors )
}