snqProfitCalc: Calculations with the SNQ Profit function

Description

Calculation of netput quantities and profit with the Symmetric Normalized Quadratic (SNQ) Profit function.

Usage

snqProfitCalc( priceNames, fixNames, data, weights,
      scalingFactors = rep( 1, length( weights ) ), coef,
      quantNames = NULL, form = 0 )

Arguments

priceNames

a vector of strings containing the names of netput prices.

fixNames

an optional vector of strings containing the names of the quantities of (quasi-)fix inputs.

data

a data frame containing the data.

weights

vector of weights of the prices for normalization.

quantNames

optional vector of strings containing the names of netput quantities.

scalingFactors

factors to scale prices (and quantities).

coef

a list containing the coefficients alpha, beta, delta and gamma.

form

the functional form to be estimated (see snqProfitEst).

Value

a data frame: the first n columns are the netput quantities, the last column is the profit.

References

Diewert, W.E. and T.J. Wales (1987) Flexible functional forms and global curvature conditions. Econometrica, 55, p. 43-68.

Diewert, W.E. and T.J. Wales (1992) Quadratic Spline Models for Producer's Supply and Demand Functions. International Economic Review, 33, p. 705-722.

Kohli, U.R. (1993) A symmetric normalized quadratic GNP function and the US demand for imports and supply of exports. International Economic Review, 34, p. 243-255.

Examples

Run this code

data( germanFarms )
   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 )
   snqProfitCalc( priceNames, fixNames, estResult$data, estResult$weights,
      estResult$scalingFactors, estResult$coef )