micEcon (version 0.5-22)

quadFuncEla: Elasticities of a Quadratic Function

Description

Calculate elasticities of a quadratic function.

Usage

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

quadHalf

logical. Multiply the quadratic terms by one half?

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.

Value

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

See Also

quadFuncEst, quadFuncDeriv, and quadFuncCalc.

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 )