search for: baltagi

...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 degrees of freedom etc.. Some authoritative commentators (Baltagi) stress the advantages of imposing even an uncertain homogeneity hypothesis over resorting to heterogeneous techniques with uncertain small-sample properties (especially if data are not in the thousands...) on grounds of efficiency. Others (Pesaran) support the opposite strategy on grounds of consi...

Dear List, I am using the output of a ML estimation on a random effects model with first-order autocorrelation to make a further conditional test. My model is much like this (which reproduces the method on the famous Grunfeld data, for the econometricians out there it is Table 5.2 in Baltagi): library(Ecdat) library(nlme) data(Grunfeld) mymod<-lme(inv~value+capital,data=Grunfeld,random=~1|firm,correlation=co rAR1(0,~year|firm)) Embarrassing as it may be, I can find the autoregressive parameter ('Phi', if I get it right) in the printout of summary(mymod) but I am utterly un...

...s"), model = c("within", "random", "ht", "between", "pooling", "fd"), random.method = c("swar", "walhus", "amemiya", "nerlove", "kinla"), inst.method = c("bvk", "baltagi"), index = NULL, ...) { nframe <- length(sys.calls()) is.a.list <- class(formula)[1] == "list" if (is.a.list) { plmlist <- match.call(expand.dots = FALSE) plmlist[[1]] <- as.name("plm.list") plmlist <- eval(plmlist, sys...

...f Business and Economic Statistics). Extensive examples are provided with the data sets, reproducing many of the analyses in the books/papers they were taken from. In particular, all data sets from the following books with many of the associated examples are provided: o "Econometrics" (Baltagi, 2002) o "Econometric Analysis" (Greene, 2003) o "Introduction to Econometrics" (Stock & Watson, 2007) Until the book becomes available in autumn 2008, we will add vignettes to the package reproducing the examples from our book. Best wishes, Z ______________________...

...f Business and Economic Statistics). Extensive examples are provided with the data sets, reproducing many of the analyses in the books/papers they were taken from. In particular, all data sets from the following books with many of the associated examples are provided: o "Econometrics" (Baltagi, 2002) o "Econometric Analysis" (Greene, 2003) o "Introduction to Econometrics" (Stock & Watson, 2007) Until the book becomes available in autumn 2008, we will add vignettes to the package reproducing the examples from our book. Best wishes, Z ______________________...

Hi r-programmers, I performe Breusch-Pagan tests (bptest in package lmtest) to check the homoscedasticity of the residuals from a linear model and I carry out carry out White's test via bptest (formula, ~ x * z + I(x^2) + I(z^2)) include all regressors and the squares/cross-products in the auxiliary regression. But what can I do if I want find coefficient and p-values of variables x, z, x*z,

...t; and "lme4". See section 7 of the vignette for more details on these packages. The "plm" package deals with panel data econometrics. Good books on the topic of panel data econometrics are: Wooldridge J (2002), Econometric Analysis of Cross{Section and Panel Data. MIT press and Baltagi B (2001), Econometric Analysis of Panel Data. 3rd edition. John Wiley and Sons ltd but these books do not have any R code (or any other code for that matter). The classic reference for mixed models in R is the book by Pinheiro and Bates: Pinheiro J, Bates D (2000). Mixed{E_ects Models in S and S-p...

Hello, Is there a way to perform a White test (testing heteroscedasticity) under R? Best regards, Afrae Hassouni

Hi all, what indicates the parameter theta in the summary of a random effect panel model estimated with the plm function? example: data("Produc", package = "plm") zz <- plm(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp, model="random", data = Produc, index = c("state","year")) summary(zz) Effects: var std.dev

Hi guys, I am afraid I am stuck with an estimation problem. I have two variables, X and Y. Y is explained by the weighted sum of n lagged values of X. My aim is to estimate the two parameters c(alpha0,alpha1) in: Yt = Sum from j=1 to n of ( ( alpha0 + alpha1 * j ) * Xt-j ) Where Xt-j denotes the jth lag of X. I came up with this approach because I thought it would be a good idea to estimate

Dear all &nbsp; I wish to carry out sigma- and beta-convergence analysis in respect of panel data [wherein current value of one of the variables needs be regressed upon suitably transformed lagged values of another variable(s)]. I am quite new to the R-language and am not very much aware of the availbaility of suitable package(s)/ code in the language. Can any one help me in letting me know of

Dear listserv members, In Croissant (2008) “Panel Data Econometrics in R: The plm Package” the authors seem to indicate that the nlme package for R cannot correctly handle unbalanced panel data: “Moreover, economic panel datasets often happen to be unbalanced (i.e., they have a different number of observations between groups), which case needs some adaptation to the methods and is not

Dear R users, I wish to manually demean a panel over time and entities. I tried to code the Wansbeek and Kapteyn (1989) transformation (from Baltagi's book Ch. 9). As a benchmark I use both the pmodel.response() and model.matrix() functions in package plm and the results from using dummy variables. As far as I understood the transformation (Ch.3), Q%*%y (with y being the dependent variable) should yield the demeaned series. However, ......

dear readers---I struggled with how to do nice fixed-effects regressions in large economic samples for a while. Eventually, I realized that nlme is not really what I needed (too complex), and all I really wanted is the plm package. so, I thought I would share a quick example. ################ sample code to show fixed-effects models? in R # create a sample panel data set with firms and years

Hi All, I am doing econometric modeling of panel data (fixed effects). We currently use Eviews to do this, but I have discovered a bug in Eviews 7 and am exploring the use of R to build panel data models / longitudinal data models. I looked at the plm package but do not see how I can incorporate AR terms in the model using the plm package. I have an Eviews model with two AR terms, AR(1) and

Dear all R users, I have a small doubt about panel data analysis. My basic understanding on Panel data is a type of data that is collected over time and subjects. Vector Autoregressive Model (VAR) model used on this type of data. Therefore can I say that, one of statistical tools used for analysis of panel data is VAR model? If you clarify my doubt I will be very grateful. Thanks and regards,