translogEla {micEcon} | R Documentation |
Calculate the elasticities of a translog function.
translogEla( xNames, data, coef, coefCov = NULL, quadHalf = TRUE, dataLogged = FALSE ) ## S3 method for class 'translogEst': elas( object, data = NULL, dataLogged = NULL, ... )
xNames |
a vector of strings containing the names of the independent variables. |
data |
dataframe containing the data;
if argument data of elas.translogEst is not specified,
the data frame that was used for the estimation
is used for calculating elasticities. |
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 . |
quadHalf |
logical. Multiply the quadratic terms by one half? |
dataLogged |
logical. Are the values in data already logged?
If argument dataLogged of elas.translogEst is not specified,
the same value as used in translogEst for creating object
is used. |
object |
object of class translogEst
(returned by translogEst ). |
... |
currently ignored. |
Shifter variables do not need to be specified, because they have no effect on the elasticities. Hence, you can use this function to calculate elasticities even for translog functions that have been estimated with shifter variables.
a list of class translogEla
containing following objects:
ela |
data frame containing the elasticities. |
variance |
data frame containing the variances of the elasticities
(only if argument coefCov is provided). |
stdDev |
data frame containing the standard deviations of the elasticities
(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$time <- c(1:20) # estimate a quadratic production function estResult <- translogEst( "qOutput", c( "qLabor", "land", "qVarInput", "time" ), germanFarms ) # calculate production elasticities of all inputs estEla <- translogEla( c( "qLabor", "land", "qVarInput", "time" ), data = germanFarms, coef = coef( estResult ), coefCov = vcov( estResult ) ) # all elasticities estEla$ela # t-values of all elasticities estEla$ela / estEla$stdDev