similar to: pgmm (Blundell-Bond) sample needed)

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,

Hello, I am switching to R from Stata and I am having particular trouble with the transition from Stata's 'xtabond' and 'ivreg' commands to the "plm" package. I am trying to replicate some of the dynamic panel data work using the UK Employment data in Arellano and Bond (1991) and available as 'EmplUK' under the 'plm' package. I have been

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,    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

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

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 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,

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, 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'm a pgmm (plm) user and would like to know if a orthogonal transformation is available, as in Stata xtabond2. Can someone help me? Thanks! Kinds regards, Eva [[alternative HTML version deleted]]

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, 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,

Dear Hao-pang, it is impossible to really tell the problem without a reproducible example. Just guessing: this looks like you have too many regressors. In GMM, lags of variables are used as instruments, so you might have more regressors than observations. Try reducing the 'lag' argument (which, by default, uses all lags available). Of course, the first observation to make would be that

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

Dear R-Users, I am using pgmm in the plm package to estimate a dynamic models with panel data. Besides the lagged dependent variable, I also have some other endogenous variables. Does the pgmm have an argument that allows me to specify these endogenous variables and their instruments? I didn't find this argument in the description and online. Thank you very much for your help!

Dear Sir, I am using the package pgmm you build in panel regression. However, I found that when T is 10, N=30, the error would show as following: system is computationally singular: reciprocal condition number But the similar code works well on Stata, so I wonder how I can optimize the algorithm, for example , the inverse matrix optimization ? And I have checked my data as well, no

Hello, I am using {plm} to estimate panel models. I want to estimate a model that includes fixed effects for time and individual, but has a random individual effect for the coefficient on the independent variable. That is, I would like to estimate the model: Y_it = a_i + a_t + B_i * X_it + e_it Where i denotes individuals, t denotes time, X is my independent variable, and B (beta) is the

Hello list, I'm following the paper (http://www.jstatsoft.org/v27/i02/paper) on how to use "plm" to run panel regressions, and am having trouble with what I believe should be something very basic. When I run the command (p.9 in the paper): R> dynformula(emp~wage+capital,log=list(capital=FALSE,TRUE),lag=list(emp=2,c(2,3)),diff=list(FALSE,capital=TRUE)) I see: emp ~ wage +

I am trying to generate a set of data points from a Gaussian mixture model. My mixture model is represented by a data frame that looks like this: > gmm weight mean sd 1 0.3 0 1.0 2 0.2 -2 0.5 3 0.4 4 0.7 4 0.1 5 0.3 I have written the following function that generates the appropriate data: gmm_data <- function(n, gmm) { c(rnorm(n*gmm[1,]$weight, gmm[1,]$mean,