similar to: Heckman regression / adjustment for standard errors?

Displaying 20 results from an estimated 1000 matches similar to: "Heckman regression / adjustment for standard errors?"

2005 Apr 20
2
heckit / tobit estimation
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
2009 Jan 27
2
Need help on running Heckman Correction Estimation using R
Team, I am trying to resolve the self-selection bias of a sample in an experiment and would like to run the Heckman Correction Estimation using R. Can someone help me with the R-Code... I tried searching for the discussion, but not successful. Thanks in advance, Best, Kishore/.. http://kaykayatisb.blogspot.com [[alternative HTML version deleted]]
2004 Aug 25
0
Heckman estimation
Hi, I wrote a function to perform a two-step Heckman (also known as "heckit") estimation. This function is mainly a wrapper function to "glm" (1st step probit estimation) and "lm" (2nd step OLS estimation). Though this function is not perfect yet, it is IMHO already very useful. Since there were some questions about Heckmann estimation in this list, I would like
2007 Aug 30
1
Data simulation with R
Hi, I am currently on a placement here at GSK for my studies, and I'm working on Heckman Models. I have to make simulations, in order to see whether these models are efficient or not. I have to generate a dataset under the following constraints: - outcome is 0 or 1 - one control group, one treatment group, there must be no treatment effect - generate one continuous variable and one
2011 Jul 11
1
Robust vce for heckman estimators
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
2004 Aug 19
1
sample selection problem, inverse mills ratio (Heckman, Lewbel, ...)
-----Ursprüngliche Nachricht----- Von: Wildi Marc, wia Gesendet: Mittwoch, 18. August 2004 10:11 An: r-help@lists.R-project.org Betreff: Hi Does anybody know from an R-package devoted to sample selection problems (Heckman's lambda, Lewbel, ...)? Thanks and best regards Marc Wildi [[alternative HTML version deleted]]
2009 Jul 12
2
Heckman Selection MOdel Help in R
Hi Saurav! On Sun, Jul 12, 2009 at 6:06 PM, Pathak, Saurav<s.pathak08 at imperial.ac.uk> wrote: > I am new to R, I have to do a 2 step Heckman model, my selection equation is > below which I was successful in running but I am unable to proceed further, > > > > I have so far used the following command > > glm(formula = s ~ age + gender + gemedu + gemhinc + es_gdppc +
2007 Oct 30
2
Splitting up the micEcon package?
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
2004 Aug 25
1
License for including datasets in packages
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
2006 Feb 27
2
heckit with a probit
Hi I have data for voting behaviour on two (related) binary votes. I want to examine the second vote, running separate regressions for groups who voted different ways on the first vote. As the votes are not independent, I guess that there is an issue with selection bias. So, I think I would like to fit a heckit style model but with a binary dependent variable - so, in effect, two successive
2005 Feb 21
0
New package for microeconomics: micEcon
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
2005 Feb 21
0
New package for microeconomics: micEcon
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
2006 Nov 30
2
AIC for heckit
Hi, I have used the heckit function in micEcon. Now I would like to evaluate the fit of the probit part of the model but when I enter AIC(sk$probit) I get this error Error in logLik(object) : no applicable method for "logLik" How can I then get the AIC for this model? Side question: If you know - from the top of your head - some link to readings dealing with evaluating the
2005 Aug 16
1
Fwd: Documenting data sets with many variables
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
2009 Jul 11
2
Heckman Selection Model/Inverse Mills Ratio
I have so far used the following command glm(formula = s ~ age + gender + gemedu + gemhinc + es_gdppc + imf_pop + estbbo_m, family = binomial(link = "probit")) My question is 1. How do i discard the non significant selection variables (one out of the seven variables above is non-significant) and calculate the Inverse Mills Ratio of the significant variables 2. I need the inverse
2008 May 29
1
package for stochastic frontier models?
I need to estimate maximum tree crown radius and am looking for a package to prepare stochastic frontier models in R. I have not found any package references on Nabble R help, google, or R help. Any tips on a package for this? With regards, Aaron Trowbridge Researcher BV Research Centre Smithers B.C. -- View this message in context:
2008 Mar 07
0
Packages micEcon, sampleSelection, and maxLik
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
2008 Mar 07
0
Packages micEcon, sampleSelection, and maxLik
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
2004 Nov 29
3
systemfit - SUR
Hello to everyone, I have 2 problems and would be very pleased if anyone can help me: 1) When I use the package "systemfit" for SUR regressions, I get two different variance-covariance matrices when I firstly do the SUR regression ("The covariance matrix of the residuals used for estimation") and secondly do the OLS regressions. In the manual for "systemfit" on page
2003 Feb 20
2
is.numeric
Hi, I have a vector, which contains both strings and numbers, e.g. > foo <- c("str1",1234,"str2",0.9876) I want to know if a distinct element of the vector is a string or a number and took "is.numeric", but > is.numeric(foo[2]) [1] FALSE because R treats the numbers in a mixed vectors as strings: > foo [1] "str1" "1234"