similar to: (no subject)

Dear Ivo, dear list, (see: Message: 70 Date: Thu, 26 Mar 2009 21:39:19 +0000 From: ivowel at gmail.com Subject: [R] pgmm (Blundell-Bond) sample needed) I think I finally figured out how to replicate your supersimple GMM example with pgmm() so as to get the very same results as Stata. Having no other regressors in the formula initially drove me crazy. This was a case where simpler models are

Dear Limin, might be just about anything. Could you please provide a reproducible example? Best, Giovanni ----------------- Original message ---------------------- Message: 51 Date: Mon, 17 May 2010 10:36:03 +0800 (CST) From: ??? <dlmsos at 163.com> To: r-help at r-project.org Subject: [R] pgmm function Message-ID: <b2cba0.35fc.128a41e3684.Coremail.dlmsos at 163.com> Content-Type:

Hello, I've been trying to fit Arrellano-Bond model with pgmm but I am getting very strange errors. I've looked around and found no reference to them. I've specified the model in dozens of different ways, and each seems to give me a new kind of error. This leads me to believe this has to do with the way the data is specified, but I can't see anything thats wrong with. My

Dear R Experts--- Sorry for all the questions yesterday and today. I am trying to use Yves Croissant's pgmm function in the plm package with Blundell-Bond moments. I have read the Blundell-Bond paper, and want to run the simplest model first, d[i,t] = a*d[i,t-1] + fixed[i] + u[i,t] . no third conditioning variables yet. the full set of moment conditions recommended for system-GMM,

Good day fellow R users: I have routinely received the following message when attempting to estimate a GMM model for a somewhat square panel (N = 20, T = 9-27, Obs = 338) using the pgmm function in the plm package: Error in function (..., deparse.level = 1) : number of rows of matrices must match (see arg 2) So far, I am not wedded to a particular GMM model but what I have used thus far is

Dear Helen, bootstrapped standard errors are currently not supported in 'plm'. Cheers, Giovanni ------------------------------ Original Message: Date: Wed, 22 Apr 2009 23:23:26 -0700 (PDT) From: Helen Chen <96258011 at nccu.edu.tw> Subject: [R] question of plm package To: r-help at r-project.org Message-ID: <23190943.post at talk.nabble.com> Content-Type: text/plain;

dear giovanni--- thanks for answering on r-help to me as well as privately. I very much appreciate your responding. I read the plm vignette. I don't have the book, so I can't consult it. :-(. I am going to post this message now (rather than just email it privately), because other amateurs may have similar questions in the future, and find this message and your answers via google.

Hi list, has anyone succeeded in using pgmm() on any dataset besides Arellano/Bond's EmplUK, as shown in the vignette? Whatever I try, I eventually get a runtime error because of a singular matrix at various points in pgmm.diff() (which gets called by pgmm()). For example, when estimating a "dynamic" version of the Grunfeld data: data(Grunfeld, package="Ecdat") grun

Dear Sir or Madam: I am Shaojuan Liao, the 3rd year Ph.D. student from Econ Department, Virginia Tech. I don't know whether it is appropriate to ask you questions on the command pgmm. But I don't know how to deal with the case where all X are exogenous and all T time periods' X can be used as the instrument. Problem 1: I know when X are predetermined, such as Z=[y1,X1,X2, 0,

Hello, although I searched for a solution related to my problem I didn?t find one, yet. My skills in R aren?t very large, however. For my Diploma thesis I need to run a GMM estimation on a dynamic panel model using the "pgmm" - function in the plm-Package. The model I want to estimate is: "Y(t) = Y(t-1) + X1(t) + X2(t) + X3(t)" . There are no "normal" instruments

Dear, I built the generalized method of moments model to estimate the sales rank in the bookstore using plm package in R. The equation is: data1.gmm <- pgmm(dynformula(lnsales_rank ~ ln_price + avg_ham_rate + avg_spam_rate + num_of_ham+ num_of_spam + ship_code2 +ship_code3 +ship_code4+ ship_code5+ ship_code6 + ship_ code7, lag = list(0, 0, 0, 0,0,0,0,0,0,0,0,0), log =FALSE), data=data,

Hi, I want to estimate a dynamic paneldata model with the following code, but unfortenately I received the error message below. form<-PB~Activity+Solvency+Cap_Int

Hi! I am looking for some insight with this situation: what to do or how to analyze when our models fitted with pgmm never pass Sargant test? With my current dataset, I've been fitting different models and with all possible combinations of lagged instruments, with all possible lag order combinations, but no model passes Sargan test. I can not give up gmm here as I have autocorrelation and

Hello Cecilia, nice hearing from you again. I must restate a couple of my old hints, though ;^) 1) please always put the authors c/c, as we are not guaranteed to browse through the r-help every day 2) please provide reproducible examples. As example(pooltest) keeps working fine, as do some other cases I tried (Grunfeld data etc.), I don't know what the problem is but evidently your data are

Hello. This is to get you started with data.frames, next time please - read the posting guide - see the documentation, especially the builtin "R data import/export" manual form the help menu ## begin R examples, paste into console ## data(mtcars) # builtin database class(mtcars) # what it is mtcars # print it out... head(mtcars) # ...better: see first rows fm <- mpg~hp+wt

Hello. Not an easy question at all, and it has little to do with software, alas! Veeeeeery loosely speaking: if the homogeneity hypothesis is rejected, then, depending on data availability, you may still be able to treat the data like a panel by: a) ignoring the results of the poolability test b) allowing the coefficients to vary. Of course, a) requires some courage while b) requires more

Dear list, dear Cecilia and Daniel, sorry for coming in ten days late, I've been very busy lately so I came across this email only today. This is just to make some points clearer re: fixed effects and r2 in package 'plm', to both you and the list. In particular, to make you aware of some additional features. Please see my comments below, with '##'. Best, Giovanni

Dear sir,    How to do bilinear time series in R?Is there any functions or packages?  thank you! -----Sincerely yours Kuangnan Fang 方匡南 敬上 department of statistics ,Economics school,Xia men University. Fujian Province (361005) China Mobile Phone：15860721915 SKYPE: ruiqwy MSN Messenger: ruiqwy@hotmail.com QQ:39863401 --- 09年3月31日，周二, r-help-request@r-project.org

Dear Carlos, please refrain from posting the same question umpteen times. Please consider that code is hard to read and people might not have the time to run your simulation etc. etc.. As I told you privately in response to your message on 18/1, > Re: generating correlated effects, I tried this only once, but I > didn't get it right. Simulations using this are, e.g., Hansen (2007)

Hello. Just a quick follow-up, for other 'plm' users on the list: - the problem turned out to be logs of zero values hidden in the big dataset - trying log(xx) would not reveal the problem, because log(0)=-Inf is a valid result in log() while it is an invalid input to plm() --> it is always advisable to try lm(yourformula, yourdata) as a first diagnostic check when plm(yourformula,