search for: fgls

When using the PLM package (version 1.2-8), I encounter the probem that calling the FGLS estimator evokes strange behavior, when choosing the "random" effects model. After calling the PGGLS function to estimate FGLS, PLM gives me a warning, stating that the "random" model has been replaced with the "pooling" model. I would, however, really like to estimate...

I have a VAR model with five macro-economic variables, y[1], y[2], y[3], y[4], y[5]. They are related to each other in following manner. y[1,t] = alpha[1,0] + beta[1,1, 1]*y[1,t-1]+............+beta[1,1, 12]*y[1,t-12] + beta[1,2, 1]*y[2,t-1]+............+beta[1,2, 12]*y[2,t-12] + e[1,t] y[2,t] = alpha[2,0] + beta[2,2, 1]*y[2,t-1]+............+beta[2,2, 12]*y[2,t-12] + e[2,t] y[3,t] = alpha[3,0]

I am fitting a reduced form VAR model using VAR in the vars library. I have several endogenous variables, and two exogenous variables. I would like to explore the effects of a shock to one of the exogenous variables on one of the endogenous variables. Using irf in the vars library only calculates the irf for the endogenous variables, this is obviously by design, is there some theoretical

I'm new to R and some what new to the world of stats. I got frustrated with excel and found R. Enough of that already. I'm trying to test and correct for Heteroskedasticity I have data in a csv file that I load and store in a dataframe. > ds <- read.csv("book2.csv") > df <- data.frame(ds) I then preform a OLS regression: > lmfit <- lm(df$y~df$x) To

...alue = 0.0006329 >> >> From the above, if I'm interpreting this correctly, there is >> Heteroskedasticity present. To correct for this, I need to calculate >> robust error terms. > > That is one option. Another one would be using WLS instead of OLS - or > maybe FGLS. As the model just has one regressor, this might be > possible and result in a more efficient estimate than OLS. I thought that WLS (which I guessing is a weighted regression) is really only useful when you know or at least have an idea of what is causing the Heteroskedasticity? I'm not fa...

...<B89F0CE41D45644A97CCC93DF548C1C30A76F0E6 at GBHENXMB02.corp.amvescap.net> Content-Type: text/plain; charset="us-ascii" Hello Megh, in principle you can do OLS on an equation-per-equation basis. However, in this case the estimator might be asymptotically inefficient. One can use FGLS instead. This is outlined for instance in: Helmut Luetkepohl, 2007. "Econometric Analysis with Vector Autoregressive Models," Economics Working Papers ECO2007/11, European University Institute. http://cadmus.iue.it/dspace/bitstream/1814/6918/1/ECO-2007-11.pdf Incidentally, you can also...