quadFuncCalc {micEcon}

Calculate dependent variable of a quadratic function

Description

Calculate the dependent variable of a quadratic function.

Usage

quadFuncCalc( xNames, data, coef, shifterNames = NULL, 
   homWeights = NULL )

Arguments

xNames

a vector of strings containing the names of the independent variables.

data

dataframe or a vector with named elements containing the data.

coef

vector containing all coefficients: if there are n exogenous variables in xNames and m shifter variables in shifterNames, the n+1 alpha coefficients must have names a_0, ..., a_n, the n*(n+1)/2 beta coefficients must have names b_1_1, ..., b_1_n, ..., b_n_n, and the m delta coefficients must have names d_1, ..., d_m (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).

shifterNames

a vector of strings containing the names of the independent variables that should be 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).

Value

a vector containing the endogenous variable.

Author(s)

Arne Henningsen

See Also

quadFuncEst and quadFuncDeriv.

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( "qOutput", c( "qLabor", "land", "qVarInput", "time" ),
      germanFarms )

   quadFuncCalc( c( "qLabor", "land", "qVarInput", "time" ), germanFarms,
      coef( estResult ) )
   #equal to estResult$fitted