translogProdFuncMargCost {micEcon}

Marginal Costs of Translog Production Function

Description

Calculate the marginal costs of the output from a translog production function.

Usage

translogProdFuncMargCost( yName, xNames, wNames, data, coef,
   dataLogged = FALSE )

Arguments

yName

a single character string containing the name of the output quantity.

xNames

a vector of strings containing the names of the input quantities.

wNames

a vector of strings containing the names of the input prices.

data

dataframe containing the data.

coef

vector containing all coefficients: if there are n inputs in xNames, the n+1 alpha coefficients must have names a_0, ..., a_n and the n*(n+1)/2 beta coefficients must have names b_1_1, ..., b_1_n, ..., b_n_n (only the elements of the upper right triangle of the beta matrix are directly obtained from coef; the elements of the lower left triangle are obtained by assuming symmetry of the beta matrix).

dataLogged

logical. Are the values in data already logged?

Value

A vector containing the marginal costs of producing the output.

Author(s)

Arne Henningsen and Geraldine Henningsen

See Also

translogEst, translogCalc, translogDeriv, translogEla and translogCostEst.

Examples

   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)

   # generate (artificial) prices
   germanFarms$pLand <- 200 + 15 * germanFarms$time
   germanFarms$pTime <- 1

   # estimate a single-output translog production function
   estResult <- translogEst( "qOutput", c( "qLabor", "land", "qVarInput", "time" ),
      germanFarms )

   # compute the marginal costs of producing the output
   margCost <- translogProdFuncMargCost( yName = "qOutput",
      xNames = c( "qLabor", "land", "qVarInput", "time" ),
      wNames = c( "pLabor", "pLand", "pVarInput", "pTime" ),
      data = germanFarms, coef = coef( estResult ) )