translogEst: Estimate a translog function
In micEcon: Microeconomic Analysis and Modelling

Description Usage Arguments Value Author(s) See Also Examples

Estimate a translog function.

   translogEst( yName, xNames, data, shifterNames = NULL,
      dataLogged = FALSE, ... )

   ## S3 method for class 'translogEst'
print( x, ... )

`yName`	a string containing the name of the dependent variable.
`xNames`	a vector of strings containing the names of the independent variables.
`data`	data frame containing the data (possibly a panel data frame created with `pdata.frame`).
`shifterNames`	a vector of strings containing the names of the independent variables that should be included as shifters only (not in quadratic or interaction terms).
`dataLogged`	logical. Are the values in `data` already logged? If `FALSE`, the logarithms of all variables (`yName`, `xNames`, `shifterNames`) are used except for shifter variables that are factors or logical variables.
`x`	An object of class `translogEst`.
`...`	further arguments of `translogEst` are passed to `lm` or `plm`; further arguments of `print.translogEst` are currently ignored.

a list of class translogEst containing following objects:

`est`	the object returned by `lm` or `plm`.
`nExog`	length of argument `xNames`.
`nShifter`	length of argument `shifterNames`.
`residuals`	residuals.
`fitted`	fitted values.
`coef`	vector of all coefficients.
`coefCov`	covariance matrix of all coefficients.
`r2`	R^2 value.
`r2bar`	adjusted R^2 value.
`nObs`	number of observations.
`model.matrix`	the model matrix.
`call`	the matched call.
`yName`	argument `yName`.
`xNames`	argument `xNames`.
`shifterNames`	argument `shifterNames`.
`dataLogged`	argument `dataLogged`.

Arne Henningsen

translogCalc, translogDeriv and quadFuncEst.

   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 )

   estResult
   summary( estResult )

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Estimated Translog function with 20 observations.
         a_0          a_1          a_2          a_3          a_4        b_1_1 
-133.4851620   24.5892366   19.9228713   34.6307963  -12.4674226  -16.8647382 
       b_1_2        b_1_3        b_1_4        b_2_2        b_2_3        b_2_4 
  14.3472829   -8.5911234   -3.5734031    0.2644969   -3.4684787   -1.1633161 
       b_3_3        b_3_4        b_4_4 
  -3.9096383    2.7933263   -0.2456535 
Estimated Translog function with 20 observations.
        Estimate Std. Error t value Pr(>|t|)  
a_0   -133.48516  165.54756 -0.8063  0.45668  
a_1     24.58924   66.49741  0.3698  0.72669  
a_2     19.92287   16.49954  1.2075  0.28124  
a_3     34.63080   55.32287  0.6260  0.55879  
a_4    -12.46742    5.22824 -2.3846  0.06280 .
b_1_1  -16.86474   19.10077 -0.8829  0.41769  
b_1_2   14.34728    8.76958  1.6360  0.16276  
b_1_3   -8.59112   10.55065 -0.8143  0.45251  
b_1_4   -3.57340    1.89984 -1.8809  0.11874  
b_2_2    0.26450    4.82223  0.0548  0.95838  
b_2_3   -3.46848    3.48959 -0.9939  0.36588  
b_2_4   -1.16332    1.54187 -0.7545  0.48456  
b_3_3   -3.90964    9.32307 -0.4194  0.69237  
b_3_4    2.79333    0.74993  3.7248  0.01364 *
b_4_4   -0.24565    0.15974 -1.5378  0.18471  
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
R-squared: 0.9982506     Adjusted R-squared: 0.9933521