View source: R/cobbDouglasDeriv.R
cobbDouglasDeriv | R Documentation |
Calculate the derivatives of a Cobb-Douglas function.
cobbDouglasDeriv( xNames, data, coef, coefCov = NULL, yName = NULL, dataLogged = FALSE )
xNames |
a vector of strings containing the names of the independent variables. |
data |
data frame containing the data. |
coef |
vector containing the coefficients:
if the elements of the vector have no names,
the first element is taken as intercept of the logged equation
and the following elements are taken as coefficients of
the independent variables defined in argument |
coefCov |
optional covariance matrix of the coefficients
(the order of the rows and columns must correspond
to the order of the coefficients in argument |
yName |
an optional string containing the name of the dependent
variable.
If it is |
dataLogged |
logical. Are the values in |
a list of class cobbDouglasDeriv
containing following objects:
deriv |
data frame containing the derivatives. |
variance |
data frame containing the variances of the derivatives
(only if argument |
Arne Henningsen
cobbDouglasCalc
, translogDeriv
.
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$time <- c(1:20) # estimate a Cobb-Douglas production function estResult <- translogEst( "qOutput", c( "qLabor", "qVarInput", "land", "time" ), germanFarms, linear = TRUE ) # compute the marginal products of the inputs (with "fitted" Output) margProducts <- cobbDouglasDeriv( c( "qLabor", "qVarInput", "land", "time" ), data = germanFarms, coef = coef( estResult )[1:5], coefCov = vcov( estResult )[1:5,1:5] ) margProducts$deriv # t-values margProducts$deriv / margProducts$variance^0.5 # compute the marginal products of the inputs (with observed Output) margProductsObs <- cobbDouglasDeriv( c( "qLabor", "qVarInput", "land", "time" ), data = germanFarms, coef = coef( estResult )[1:5], yName = "qOutput", coefCov = vcov( estResult )[1:5,1:5] ) margProductsObs$deriv # t-values margProductsObs$deriv / margProductsObs$variance^0.5
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