search for: dynformula

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 + capital rather than the complete model that is given in the paper: log(emp) ~ lag(log(emp), 1) + lag(log(emp), 2) + lag(log(wage), 2) + lag(log(wage), 3) + diff(capital, 2) +...

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 + capital rather than the complete model that is given in the paper: log(emp) ~ lag(log(emp), 1) + lag(log(emp), 2) + lag(log(wage), 2) + lag(log(wage), 3) + diff(capital, 2) +...

...and delta y's. I believe that pgmm operates by demanding that "firm" (i) and "year" (t) be the first two columns in the data set. library(plm) NF=20; NT=10 d= data.frame( firm= rep(1:NF, each=NT), year= rep( 1:NT, NF), x=rnorm(NF*NT) ); # the following fails, because dynformula magic is required; learned this the hard way # v=pgmm( x ~ lag(x), data=d, gmm.inst=~x, lag.gmm=c(2,99), transformation="ld" ) formula= dynformula( x ~ 1, list(1)); # this creates x ~ lag(x) v=pgmm( formula, data=d, gmm.inst=~x, lag.gmm=c(2,99), transformation="ld" ) Error...

...use Stata to analyze the UK Employment Data. I am trying to replicate Roodman's results for the UK Employment data using R instead of Stata but I am having limited success. Using: >library('plm') >data("EmplUK", package = "plm") >emp.plm <- plm(dynformula(emp ~ wage + capital + output, lag = list(2, 1, 2, 2), log = TRUE), EmplUK, effect = "time") >summary(emp.plm) I am able to perfectly replicate Roodman's "naive model" (on page 17) regressing Log(Employment) on its own first and second lags as well as current and...

...and (ugh!). I'm also adding the 'nomata' option to avoid complications, but this will be unnecessary on most systems (not on mine...). The system-GMM estimator (with robust SEs) in Stata is 'xtabond2 n nL1, gmm(L.(n)) nomata robust' whose R equivalent is: > sysmod<-pgmm( dynformula( log(emp) ~ 1, list(1)), data=EmplUK, gmm.inst=~log(emp), lag.gmm=c(2,99), + effect="individual", model="onestep", transformation="ld" ) > summary(sysmod, robust=TRUE) (note that although 'summary(sysmod)' does not report a constant, it's actually th...

...periods, but this should leave me with the first time period to use as an instrument. Below is my full code, along with 4 different pgmm attempts, with 4 different errors. My data is available here if anyone wants to try it: http://dl.dropbox.com/u/3053463/did_dpd.dta Also, likely unrelated, but dynformula has some strange behaviour dynformula(value~value, lag.form=list(value = 1),diff.form=list(TRUE)) Gives: diff(value) ~ diff(diff(value), 1) + diff(value, 1) Where I would have thought it would give this: diff(value) ~ diff(value, 1) Thanks for your time. library(foreign) library(plm) #Loading th...

...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 <- pgmm(dynformula(inv ~ value + capital, lag=list(1,1,1), log=T), data=Grunfeld, gmm.inst=~log(inv), lag.gmm=list(c(2,5)), model="twosteps") Error in solve.default(suml(A2)) : system is computationally singular: reciprocal condition number = 8.83721e-21 I read all the documentation available and tried...

...aring statements, because stata seemed able of running this and producing output. On the other hand, the exact NF number at which pgmm() dies does suggest that you are right. function( NF=7, NT=4 ) { d= data.frame( firm= rep(1:NF, each=NT), year= rep( 1:NT, NF), x=rnorm(NF*NT) ) lagformula= dynformula( x ~ 1, list(1) ) v=pgmm( lagformula, data=d, gmm.inst=~x, model="onestep", effect=NULL, lag.gmm=c(1,99), transformation="ld" ) } with NF=8, it works; and with NF=7, it dies. With NF=7, I have 28 data points in levels and 21 data points in differences, which are used to e...

It seems to only works for zoo or ts objects? I tried to run it for xts objects, and error message occurs. Once I coerce it to be an zoo object (by as.zoo), it works. Error message: Error in model.frame.default(formula = dynformula(PIh - PI ~ L(X, 0:i) + : variable lengths differ (found for 'L(X, 0:i)') In addition: Warning messages: 1: In zoo(coredata(x), order.by = index(x), ...) : some methods for ?zoo? objects do not work if the index entries in ?order.by? are not unique 2: In zoo(coredata(x), order.by = inde...

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, effect = "individual", model = "twosteps", transformation...

...to regress a dynamic panel model with pgmm function in the plm package, but it doesn't work. The error report is "Error in names(coefficients) <- c(namesX, namest) : 'names' attribute [13] must be the same length as the vector [5]". My command is: reg.gmm<-pgmm(dynformula(ln_per_co2ec~ln_per_realgdp+ln_per_realgdp2,lag .form=list(1,0,0), log.form=FALSE),data=co2new,effect="individual",model="twosteps", gmm.inst=~ln_per_co2ec,lag.gmm=list(c(99,2)),transformation="d") Could you guys give me some hints on this problem? Thank you in adv...

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 dynpanel<-pgmm(dynformula(form,list(1,1,1,1)),data=panel[1:2185,1:37],effect="twoways",model="onestep",index=c("Aktie","Datum"),gmm.inst=~PB,lag.gmm=list(c(2,12)),transformation="ld") Fehler in FUN(X[[1L]], ...) : Indizierung au?erhalb der Grenzen dim(panel) [1] 34086 3...

...I need to convert all my data into <ts> data and then compile it with ts.union to create a time series data frame in case there was a problem with using the <lag> operator on my data frame, but my panel entities are not time series data so this approach seemed flawed. I have also used dynformula but this also seemed to lead to the same outcome. If on the other hand I used a simple linear model, there was no problem. Example: > b.fetw<-lm(B~lag(B,k=1)+Ma+lag(Ma,k=1)+Pa+lag(Pa,k=1)+Ya+lag(Ya,k=1)+F+lag(F,k=1)+CS+R+lag(R,k=1)+G+I,data=b) > summary(b.fetw) Call: lm(formula = B ~ la...

...and (ugh!). I'm also adding the 'nomata' option to avoid complications, but this will be unnecessary on most systems (not on mine...). The system-GMM estimator (with robust SEs) in Stata is 'xtabond2 n nL1, gmm(L.(n)) nomata robust' whose R equivalent is: > sysmod<-pgmm( dynformula( log(emp) ~ 1, list(1)), data=EmplUK, gmm.inst=~log(emp), lag.gmm=c(2,99),  + effect="individual", model="onestep", transformation="ld" ) > summary(sysmod, robust=TRUE) (note that although 'summary(sysmod)' does not report a constant, it's actually th...