similar to: ivreg and structural change

Good day, For lack of a better solution (or perhaps I am ignorant to something more elegant), I have been bootstrapping panel data by hand so to speak and I would like to know if there is a way to define multiple variables in a loop using the loop variable. I found a post (here: https://stat.ethz.ch/pipermail/r-help/2002-October/026305.html ) that discussed naming multiple variables but it

I want to estimate the following fixed effect model: y_i,t = alpha_i + beta_1 x1_t + beta_2 x2_i,tx2_i,t = gamma_i + gamma_1 x1_t + gamma_2 Z1_i + gamma_3 Z2_i I can use ivreg from AER to do the iv regression. fm <- ivreg(y_i,t ~ x1_t + x2_i,t | x1_t + Z1_i + Z2_i, data = DataSet) But, I'm not sure how can I add the fixed effects. Thanks! [[alternative HTML

Dear friends, I am trying to understand and implement instrumental variables regression using R. I found a small (simple) example here which purportedly illustrates the mechanics (using 2-stage least-squares): http://www.r-bloggers.com/a-simple-instrumental-variables-problem/ Basically, here are the R commands (reproducible example) from that site: # ------ begin R library(AER)

Sounds like that was fixed on trunk also, in 0e8608b (I get the same on Windows.) On Tue, Jul 7, 2020 at 8:10 AM Neil Nelson via llvm-dev <llvm-dev at lists.llvm.org> wrote: > > Uploaded Ubuntu 20.04 > > sha256sum clang+llvm-10.0.1-rc3-x86_64-unknown-linux-gnu.tar.xz > 9a2b573b69a4c3d62d7a4accd9b164044cd5e8fbe68b056716c72cd0f81a134d > > FAIL: LLVM ::

Dear R-Helpers, I need to compute cross-correlation on two signals wich may contain missing values. One cannot pass "Na.action=na.pass" to the ccf() function. So, I wrote a naive function of my own (see below). Unsurprisingly, this function is not very fast. Do you think that it is possible to do better, or should I accept my fate ? Bruno. my_ccf <- function (X, Y,

Hi, I've tagged LLVM 10.0.1-rc3. This will hopefully be the last release candidate, please test it out and report results on this thread. Thanks, Tom

I am using 32-bit R 3.1.2 on Windows 7. I recently conducted an `R CMD check --as-cran` on a recently-developed package and received only the 'New submission' note. Research on StackOverflow and on R-devel suggested this could be ignored. I also used devtools::build_win() and received no notes or warnings, other than the one mentioned previously. Lastly, I conducted an `R CMD check` with

Dear John Fox, Christian Kleiber, and Achim Zeileis, I am attempting to run various independent variable parameters to assess their suitability. Unfortunately, I hit a snag and couldn't get the tests to run properly. When I used ivreg, I got an error message saying: "Error in eval(predvars, data, env) : object 'WageInequality' not found." Can you please help? Model:

Kelis, thanks for your interest. It's hard to say what exactly goes wrong based on the information you provide. However, I would recommend that you first process the data: - Store all variables as the appropriate types (numeric, factor, etc.) in the data frame. Then you don't have to put these things into the model formula. - Employ variable names without spaces, then you don't

Hi there, I hope to build a model Y ~ X1 + X2 + X3 + X4 with X1 has two instrumental variable A and B, and X2 has one instrumental variable A. I have searched the R site and mailling list, and known that the tsls() from sem package and ivreg() from AER package can deal with instrumental variable regression, however, I don't know how to formula the model. Any suggestion will be really

Dear R-listers, I want to reperfrom a poisson distribution test that presented in a recent-published biological research paper (Plant Physiology 2008, vol 148, pp. 1189-1200). That test is about the occurrence number of a kind of gene in separate chromosomes. For instance: The observed gene number in chromosome A is 36. The expected gene number in chromosome A is 30. Then, the authors got a

I'm trying to fit a nested mixed model using lmer and have some questions about the output and my model formulations. I have replicate measures on Lines which are strictly nested within Populations. (a) So if I want to fit a model where Line is a random effect and Populations are fixed and the random Line effect is constant across Populations, I have: measure_ijk = mu + P_i + L_ij +

Dear all, I am using the Instrumental Variable approach to estimate the causal effects of TWO endogenous variables in a Mendelian Randomization study. As long as point estimation is concerned, I have no problem: both "ivreg" in library "AER" and "tsls" in library "sem" do the job perfectly. The problems begin when I try to obtain confidence intervals for

I have upgraded R (from 3.6 to 4.0) and RStudio (from 1.1 to 1.2.5) a few days ago, and Ubuntu from 18.04 to 20.04 yesterday. Since then, R sometimes never terminates when executing certain commands: ivreg (from package AER), summary (of a logit regression) and logitmfx (from package mfx). Sometimes these commands run fine, but most of the time I have to kill the process because R won't

Dear All, I have already posted before on the list about data mining and it has proved very useful. I have now a training dataset consisting of N objects of M<<N different kinds (actually, M is usually 3 to 5, whereas N is of the order of 1000). Every object has its own label L_i, i=1...N, that is known. For each of these objects I measure some property in time (let's say I measure it

Hello, I am trying to replicate the "missing example" of a TSLS estimation in Epple & McCallum (link below) http://wpweb2.tepper.cmu.edu/facultyadmin/upload/ppaper_32774807225408_Epple-McCallum93.pdf According to them, the commands are in: http://www.tepper.cmu.edu/faculty-research/faculty-pages/dennis-epple/simultaneous-equation-econometrics/index.aspx They use the Stata's

I need your help because I am having difficulties to finalize an econometric model.By the way, I want to calculate the standard error with delta method in a 2sls model with interactions under R.I want to determine the total effect of the institutions (Institutions + D_MinMond * Institutions) on logYLby summing the estimated parameters of (Institutions) and (D_MinMond * Institutions);D_MinMond is a

Hi All, I am using R 2.11.0 on a Ubuntu machine. I estimated a model using "tsls" from the package "sem". Is there a way to get Newey West standard errors for the parameter estimates? When estimating the model by OLS, I used "NeweyWest" from the package "sandwich" to get HAC standard errors. But, I am not able to use the same method with the results of the

On 3 January 2015 at 13:49, Steven Ranney wrote: | I am using 32-bit R 3.1.2 on Windows 7. | | I recently conducted an `R CMD check --as-cran` on a recently-developed | package and received only the 'New submission' note. Research on | StackOverflow and on R-devel suggested this could be ignored. I also used | devtools::build_win() and received no notes or warnings, other than the one |

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