similar to: Heckman estimation

Dear all, I have uploaded a new package called micEcon (version 0.1-3) to CRAN (an early version of this package has been already presented at useR! 2004). It contains tools for microeconomic analysis and microeconomic modeling. These are for instance: - tools for demand analysis with the 'Almost Ideal Demand System' (AIDS): e.g. econometric estimation, calculation of price and

Dear all, I have uploaded a new package called micEcon (version 0.1-3) to CRAN (an early version of this package has been already presented at useR! 2004). It contains tools for microeconomic analysis and microeconomic modeling. These are for instance: - tools for demand analysis with the 'Almost Ideal Demand System' (AIDS): e.g. econometric estimation, calculation of price and

Dear All, we (Ott Toomet and I) would like to add functions for maximum likelihood (ML) estimations of generalized tobit models of type 2 and type 5 (*see below) in my R package for microeconomic analysis "micEcon". So far we have called these functions "tobit2( )" and "tobit5( )". Are these classifications well known? How are these functions called in other

Dear R Users: We have splitted up the micEcon package into three packages: a) Package "maxLik" provides tools for maximum likelihood estimations (see http://www.maxLik.org). b) Package "sampleSelection" provides tools for estimating Heckman-type sample selection/generalized tobit models (see http://www.sampleSelection.org). c) Package "micEcon" contains the

Dear R Users: We have splitted up the micEcon package into three packages: a) Package "maxLik" provides tools for maximum likelihood estimations (see http://www.maxLik.org). b) Package "sampleSelection" provides tools for estimating Heckman-type sample selection/generalized tobit models (see http://www.sampleSelection.org). c) Package "micEcon" contains the

Dear R Users: The functions of our "micEcon" package [1,2] can be subdivided into three categories: - microeconomic demand and firm models - sample selection models (mainly selection()) - routines for (likelihood) maximisation (e.g. maxLik(), maxNR(), maxBHHH()) (mainly used for ML estimation of sample selection models) Although sample selection models are often used in

Dear All, I would like to publish a function for 'heckit' estimations together with two examples from Greene's and Wooldridge's econometric textbooks. These examples use the dataset of Mroz (1987) that is also available in John Fox' "car" package. However, not all variables that are used in my examples are available in the "car" package. Therefore, I

Hello folks, I am trying to estimate the two-step Heckman regression model. I would like to make an adjustment for intragroup correlations. Stata can implement this with the "cluster" option, but I am really hoping to stick with R. It seems that the micEcon package is the primary source for this two-step regression model (i.e., heckit), but I can't find a way to make the

Hi, since nobody answered to my first message, I try to explain my problem more clearly and more general this time: I have a data set in my R package "micEcon", which has many variables (82). Therefore, I would like to avoid to describe all variables in the "\format" section of the documentation (.Rd file). However, doing this lets "R CMD check" complain about

Dear R users, the systemfit package contains functions for fitting systems of simultaneous equations by various estimation methods (e.g. OLS, SUR, 2SLS, 3SLS). Currently version 0.8 of systemfit is available on CRAN. However, shortly we will upload version 1.0, which is NOT BACKWARD COMPATIBLE. The changes that broke backward compatibility were necessary to make systemfit() more similar to

Dear R users, the systemfit package contains functions for fitting systems of simultaneous equations by various estimation methods (e.g. OLS, SUR, 2SLS, 3SLS). Currently version 0.8 of systemfit is available on CRAN. However, shortly we will upload version 1.0, which is NOT BACKWARD COMPATIBLE. The changes that broke backward compatibility were necessary to make systemfit() more similar to

Hi, I added a new function "predict.systemfit" to our package "systemfit" to make it closer to other packages (e.g. lm). Now "R CMD check" complains that the generic function "predict" has only the argument "object", while our function "predict.systemfit" has more arguments. However, the function "predict.lm" has also more

Dear R users, The authors of the systemfit package have released a new version of this package with substantial enhancements. The systemfit package contains functions for fitting simultaneous systems of linear equations using Ordinary Least Squares (OLS), Weighted Least Squares (WLS), Seemingly Unrelated Regressions (SUR), Two-Stage Least Squares (2SLS), Weighted Two-Stage Least Squares

Dear R users, The authors of the systemfit package have released a new version of this package with substantial enhancements. The systemfit package contains functions for fitting simultaneous systems of linear equations using Ordinary Least Squares (OLS), Weighted Least Squares (WLS), Seemingly Unrelated Regressions (SUR), Two-Stage Least Squares (2SLS), Weighted Two-Stage Least Squares

Hi, I would like to obtain the names of all objects that are provided as further arguments ("...") in a function call. I have created a minimal example that illustrates my wish (but isn't useful otherwise): f1 <- function( ... ) return( deparse( substitute( ... ) ) ) x1 <- 1 x2 <- 2 x3 <- 3 f1( x1, x2, x3 ) [1] "x1" However, I would like to obtain the

Hi, I was really happy when I saw that in R version 2.3.0 "R CMD check" works for packages whose package name is different from the directory name in which it is located (see http://cran.r-project.org/src/base/NEWS). Now, I can have branches of my packages in directories like "[...]/branches/<version number>/", while I had to use "[...]/branches/<version

Hi, I added the "tests" subdirectory and a test file (say "myTest.R") to our "systemfit" package. Up to now I create the "myTest.Rout.save" file with > R CMD BATCH --vanilla myTest.R myTest.Rout.save However, "R CMD check" reports two differences between myTest.Rout.save and the output of myTest.R: a) myTest.Rout.save contains following

Hi, I have a dataframe (say myData) and want to get a list (say myList) that contains a matrix for each row of the dataframe myData. These matrices are calculated based on the corresponding row of myData. Using a for()-loop to do this is very slow. Thus, I tried to use apply(). However, afaik apply() does only return a list if the matrices have different dimensions, while my matrices have

Hi, I did not find any web page about using R in economics and econometrics so far. However, this does not mean that there is none (searching with google for "R" and "economics" gives many pages about economics and a name like Firstname R. Lastname on it ;-)). Does anybody in the list does know such a web page? If not, I will be happy if you, Ajay, could build and

When using function heckit() from package ‘sampleSelection’, is there anyway to make t-tests for the coefficients using robust covariance matrix estimator? By “robust” I mean something like if a had an object ‘lm’ called “reg” and then used: > coeftest(reg, vcov = vcovHC(reg)). I’m asking this because in Stata we could use function heckman and then use vce option “robust”. We could do the