cobbDouglasCalc {micEcon} | R Documentation |
Calculate the dependent variable of a Cobb-Douglas function.
cobbDouglasCalc( xNames, data, coef, 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 xNames
(in the same order);
if the elements of coef have names,
the element named a_0 is taken as intercept of the logged
equation
and the elements named a_1 , ..., a_n
are taken as coefficients of the independent variables
defined in argument xNames (numbered in that order). |
dataLogged |
logical. Are the values in data already logged? |
A vector containing the endogenous variable.
If the inputs are provided as logarithmic values
(argument dataLogged
is TRUE
),
the endogenous variable is returned as logarithm;
non-logarithmic values are returned otherwise.
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$time <- c(1:20) # estimate a Cobb-Douglas production function estResult <- translogEst( "qOutput", c( "qLabor", "land", "qVarInput", "time" ), germanFarms, linear = TRUE ) cobbDouglasCalc( c( "qLabor", "land", "qVarInput", "time" ), germanFarms, coef( estResult )[ 1:5 ] ) #equal to estResult$fitted