quadFuncEla function

Elasticities of a Quadratic Function

Calculate elasticities of a quadratic function.

quadFuncEla( xNames, data, coef, yName = NULL, 
   shifterNames = NULL, homWeights = NULL )

## S3 method for class 'quadFuncEst'
elas( object, data = NULL, yObs = FALSE, ... )

Arguments

• xNames: a vector of strings containing the names of the independent variables.

• data: dataframe or a vector with named elements containing the data; if argument data of elas.quadFuncEst is not specified, the data frame that was used for the estimation is used for calculating elasticities.

• coef: vector containing all coefficients.

• yName: an optional string containing the name of the dependent variable. If it is NULL, the dependent variable is calculated from the independent variables and the coefficients.

• shifterNames: an optional vector of strings containing the names of the independent variables that are included as shifters only (not in quadratic or interaction terms).

• homWeights: numeric vector with named elements that are weighting factors for calculating an index that is used to normalize the variables for imposing homogeneity of degree zero in these variables (see documentation of quadFuncEst).

• object: object of class quadFuncEst

  (returned by quadFuncEst).

• yObs: logical. Use observed values of the endogenous variable. If FALSE (default) predicted values calculated by quadFuncCalc are used.

• ``: currently ignored.

Returns

A data.frame of class quadFuncEla, where each column corresponds to one of the independent variables.

See Also

quadFuncEst, quadFuncDeriv, and quadFuncCalc.

Author(s)

Arne Henningsen

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)

   # estimate a quadratic production function
   estResult <- quadFuncEst( yName = "qOutput", 
      xNames = c( "qLabor", "land", "qVarInput", "time" ),
      data = germanFarms )

   # compute the partial production elasticities with "fitted" output
   elaFit <- quadFuncEla( xNames = c( "qLabor", "land", "qVarInput", "time" ),
      data = germanFarms, coef = coef( estResult ) )
   elaFit
   # same as
   elaFit2 <- elas( estResult )
   all.equal( elaFit, elaFit2 )

   # compute the partial production elasticities with observed output
   elaObs <- quadFuncEla( xNames = c( "qLabor", "land", "qVarInput", "time" ),
      data = germanFarms, coef = coef( estResult ), yName = "qOutput" )
   elaObs
   # same as
   elaObs2 <- elas( estResult, yObs = TRUE )
   all.equal( elaObs, elaObs2 )