quadFuncDeriv {micEcon} | R Documentation |
Calculate the derivatives of a quadratic function.
quadFuncDeriv( xNames, data, coef, coefCov = NULL, homWeights = NULL, quadHalf = TRUE )
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 ,
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). |
coefCov |
optional covariance matrix of the coefficients:
the row names and column names must be the same as the names
of coef . |
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 ). |
quadHalf |
logical. Multiply the quadratic terms by one half? |
Shifter variables do not need to be specified, because they have no effect on the partial derivatives. Hence, you can use this function to calculate partial derivatives even for quadratic functions that have been estimated with shifter variables.
a list of class quadFuncDeriv
containing following objects:
deriv |
data frame containing the derivatives. |
variance |
data frame containing the variances of the derivatives
(only if argument coefCov is provided). |
stdDev |
data frame containing the standard deviations of the derivatives
(only if argument coefCov is provided). |
Arne Henningsen
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$time <- c(1:20) # estimate a quadratic production function estResult <- quadFuncEst( "qOutput", c( "qLabor", "land", "qVarInput", "time" ), germanFarms ) # compute the marginal products of the inputs margProducts <- quadFuncDeriv( c( "qLabor", "land", "qVarInput", "time" ), germanFarms, coef( estResult ), vcov( estResult ) ) margProducts$deriv