translogCheckMono( xNames, data, coef, increasing =TRUE, strict =FALSE, dataLogged =FALSE, tol =10* .Machine$double.eps )## S3 method for class 'translogCheckMono'print( x,...)## S3 method for class 'translogCheckMono'summary( object,...)## S3 method for class 'summary.translogCheckMono'print( x,...)
Arguments
xNames: a vector of strings containing the names of the independent variables.
data: dataframe containing the data.
coef: vector containing all coefficients.
increasing: single logical value or vector of logical values of the same length as argument xNames
indicating whether it should be checked if the translog function is monotonically increasing (default, TRUE) or decreasing (FALSE) in the explanatory variables.
strict: logical. Check for strict (TRUE) or non-strict (default, FALSE) monotonicity?
dataLogged: logical. Are the values in data already logged?
tol: tolerance level for checking non-strict monotonicity: values between -tol and tol are considered to be zero (ignored if argument strict is TRUE).
x: an object returned by translogCheckMono or by summary.translogCheckMono.
object: an object returned by translogCheckMono.
...: currently not used.
Returns
translogCheckMono returns a list of class translogCheckMono
containing following objects: - obs: a vector indicating whether monotonicity is fulfilled at each observation.
exog: data frame indicating whether monotonicity is fulfilled for each exogenous variable at each observation.
increasing: argument increasing.
strict: argument strict.
Details
Function translogCheckMono internally calls function translogDeriv
and then checks if the derivatives have the sign specified in argument increasing.
Function translogCheckMono does not have an argument shifterNames, because shifter variables do not affect the monotonicity conditions of the eplanatory variables defined in Argument xNames. Therefore, translogCheckMono automatically removes all coefficients of the shifter variables before it calls translogDeriv.
See Also
translogEst, translogDeriv, and translogCheckCurvature
Author(s)
Arne Henningsen
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 translog production function estResult <- translogEst("qOutput", c("qLabor","land","qVarInput","time"), germanFarms )# check whether the production function is monotonically increasing# in all inputs test <- translogCheckMono( xNames = c("qLabor","land","qVarInput","time"), data = germanFarms, coef = coef( estResult )) test
summary( test )# check whether the production function is monotonically decreasing# in time and monotonically increasing in all other inputs test <- translogCheckMono( c("qLabor","land","qVarInput","time"), germanFarms, coef( estResult ), increasing = c(TRUE,TRUE,TRUE,FALSE)) test
summary( test )