prodest

Production Function Estimation in R

prodest (Rovigatti, 2017) implements most of the methods for production function estimation. The prodest package provides functions to simulate panel data, estimate the productivity, state and free variables parameters. Full description of the models, their issues and characteristics is available in Mollisi et al., 2017.

The latest stable version of prodest is available on CRAN at 'https://cran.r-project.org/package=prodest'.

The latest development version of prodest is available at 'https://github.com/GabrieleRovigatti/prodest/tree/master/prodest'.

Please cite prodest in publications:

Rovigatti, G. (2017).
prodest: Production Function Estimation in R.
R package.

Rovigatti, G. (2017).
Production Function Estimation in R: The prodest Package.
Working paper.

Installation: To install the latest stable version of prodest in R type install.packages("prodest").

Example: In R, type

require(prodest)

data(chilean) # Chilean data on production.

#we fit a model with two free (skilled and unskilled), one state (capital) and one proxy variable (electricity) with two different optimizers

LP.fit <- prodestLP(chilean$Y, fX = cbind(chilean$fX1, chilean$fX2), chilean$sX, chilean$pX, chilean$idvar, chilean$timevar, seed = 154673)

LP.fit.solnp <- prodestLP(chilean$Y, fX = cbind(chilean$fX1, chilean$fX2), chilean$sX, chilean$pX, chilean$idvar, chilean$timevar, opt = 'solnp')

#show results

summary(LP.fit)

summary(LP.fit.solnp)

#show results in .tex tabular format

printProd(list(LP.fit, LP.fit.solnp))