[R] problem with dynformula from plm package
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) + diff(capital, 3) And indeed, when I try to run a regression using that formula, it appears to not contain any lags or logs (output below). Any ideas? Thanks in advance, ~Owen -- Owen Powell http://center.uvt.nl/phd_stud/powell R library(plm) R data(EmplUK, package=plm) R a = dynformula(emp~wage+capital,log=list(capital=FALSE,TRUE),lag=list(emp=2,c(2,3)),diff=list(FALSE,capital=TRUE)) R testModel - plm(formula = a,data=EmplUK,model=within) [1] 10312 R summary(testModel) Oneway (individual) effect Within Model Call: plm(formula = a, data = EmplUK, model = within) Unbalanced Panel: n=140, T=7-9, N=1031 Residuals : Min. 1st Qu. Median 3rd Qu. Max. -17.1000 -0.3060 0.0137 0.3070 27.3000 Coefficients : Estimate Std. Error t-value Pr(|t|) wage-0.143626 0.032790 -4.3802 1.186e-05 *** capital 0.801495 0.064088 12.5062 2.2e-16 *** --- Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 1 Total Sum of Squares:5030.6 Residual Sum of Squares: 4207.8 F-statistic: 86.9179 on 2 and 889 DF, p-value: 2.22e-16 [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] problem with dynformula from plm package [RE-POST]
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) + diff(capital, 3) And indeed, when I try to run a regression using that formula, it appears to not contain any lags or logs (output below). Any ideas? Thanks in advance, ~Owen -- Owen Powell http://center.uvt.nl/phd_stud/powell R library(plm) R data(EmplUK, package=plm) R a = dynformula(emp~wage+capital,log=list(capital=FALSE,TRUE),lag=list(emp=2,c(2,3)),diff=list(FALSE,capital=TRUE)) R testModel - plm(formula = a,data=EmplUK,model=within) [1] 10312 R summary(testModel) Oneway (individual) effect Within Model Call: plm(formula = a, data = EmplUK, model = within) Unbalanced Panel: n=140, T=7-9, N=1031 Residuals : Min. 1st Qu. Median 3rd Qu. Max. -17.1000 -0.3060 0.0137 0.3070 27.3000 Coefficients : Estimate Std. Error t-value Pr(|t|) wage-0.143626 0.032790 -4.3802 1.186e-05 *** capital 0.801495 0.064088 12.5062 2.2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Total Sum of Squares:5030.6 Residual Sum of Squares: 4207.8 F-statistic: 86.9179 on 2 and 889 DF, p-value: 2.22e-16 __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] problem with dynformula from plm package [RE-POST]
Great! That did the trick, thanks David. To summarize for the list, to get dynformula to work (example): R a = dynformula(emp~wage+capital,log.form=list(capital=FALSE,TRUE),lag.form=list(emp=2,c(2,3)),diff.form=list(FALSE,capital=TRUE)) it might be necessary to use: R plm(formula = formula(a), data=EmplUK) rather than just: R plm(formula = a, data = EmplUK) ~Owen 2009/11/27 David Winsemius dwinsem...@comcast.net: You might also note that the authors hint on the help page that one might want to use the formula() operation on the result of dynformula. Following that path would have gotten us to a more successful conclusion. grun.fe - plm(formula = formula(a),data=EmplUK) grun.fe Model Formula: log(emp) ~ lag(log(emp), 1) + lag(log(emp), 2) + lag(log(emp), 1) + lag(log(emp), 2) + lag(log(wage), 2) + lag(log(wage), 3) + diff(capital, 2) + diff(capital, 3) Coefficients: lag(log(emp), 1) lag(log(emp), 2) lag(log(wage), 2) lag(log(wage), 3) diff(capital, 2) 0.8678675 -0.1936447 -0.1632724 0.3200785 0.0037612 diff(capital, 3) 0.0137866 -- David. On Nov 27, 2009, at 12:04 PM, Owen Powell wrote: Hi David, Thank you for the response. I forgot to mention that I'd already tried what (I think) you propose (adding .form to the end of the lag, log and diff) and I still see the same results (posted below). Specifically, I still see no lags, logs or diffs in my model. Any other ideas? ~Owen R rm(list = ls()) R options(prompt= R ) R library(plm) R data(EmplUK, package=plm) R EmplUK - plm.data(EmplUK, index = c(firm, year)) R log(emp)~lag(log(emp),1)+lag(log(emp),2)+lag(log(wage),2)+lag(log(wage),3)+diff(capital,2)+diff(capital,3) log(emp) ~ lag(log(emp), 1) + lag(log(emp), 2) + lag(log(wage), 2) + lag(log(wage), 3) + diff(capital, 2) + diff(capital, 3) R a = dynformula(emp~wage+capital,log.form=list(capital=FALSE,TRUE),lag.form=list(emp=2,c(2,3)),diff.form=list(FALSE,capital=TRUE)) R grun.fe - plm(formula = a,data=EmplUK,model=within) [1] 1031 2 R summary(grun.fe) Oneway (individual) effect Within Model Call: plm(formula = a, data = EmplUK, model = within) Unbalanced Panel: n=140, T=7-9, N=1031 Residuals : Min. 1st Qu. Median 3rd Qu. Max. -17.1000 -0.3060 0.0137 0.3070 27.3000 Coefficients : Estimate Std. Error t-value Pr(|t|) wage -0.143626 0.032790 -4.3802 1.186e-05 *** capital 0.801495 0.064088 12.5062 2.2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Total Sum of Squares: 5030.6 Residual Sum of Squares: 4207.8 F-statistic: 86.9179 on 2 and 889 DF, p-value: 2.22e-16 2009/11/27 David Winsemius dwinsem...@comcast.net On Nov 27, 2009, at 10:25 AM, Owen Powell wrote: 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)) Perhaps you could have read the help page for the current version of the package which says the argument have been modified. Using the current arguments: dynformula(emp~wage+capital,log.form=list(capital=FALSE,TRUE),lag.form=list(emp=2,c(2,3)),diff.form=list(FALSE,capital=TRUE)) log(emp) ~ lag(log(emp), 1) + lag(log(emp), 2) + lag(log(emp), 1) + lag(log(emp), 2) + lag(log(wage), 2) + lag(log(wage), 3) + diff(capital, 2) + diff(capital, 3) -- David Winsemius, MD 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) + diff(capital, 3) And indeed, when I try to run a regression using that formula, it appears to not contain any lags or logs (output below). Any ideas? Thanks in advance, ~Owen -- Owen Powell http://center.uvt.nl/phd_stud/powell R library(plm) R data(EmplUK, package=plm) R a = dynformula(emp~wage+capital,log=list(capital=FALSE,TRUE),lag=list(emp=2,c(2,3)),diff=list(FALSE,capital=TRUE)) snipped David Winsemius, MD Heritage Laboratories West Hartford, CT -- Owen Powell http://center.uvt.nl/phd_stud/powell David Winsemius, MD Heritage Laboratories West Hartford, CT -- Owen Powell http://center.uvt.nl/phd_stud/powell __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] problem with dynformula from plm package [RE-POST]
Hi David, Thank you for the response. I forgot to mention that I'd already tried what (I think) you propose (adding .form to the end of the lag, log and diff) and I still see the same results (posted below). Specifically, I still see no lags, logs or diffs in my model. Any other ideas? ~Owen R rm(list = ls()) R options(prompt= R ) R library(plm) R data(EmplUK, package=plm) R EmplUK - plm.data(EmplUK, index = c(firm, year)) R log(emp)~lag(log(emp),1)+lag(log(emp),2)+lag(log(wage),2)+lag(log(wage),3)+diff(capital,2)+diff(capital,3) log(emp) ~ lag(log(emp), 1) + lag(log(emp), 2) + lag(log(wage), 2) + lag(log(wage), 3) + diff(capital, 2) + diff(capital, 3) R a = dynformula(emp~wage+capital,log.form=list(capital=FALSE,TRUE),lag.form=list(emp=2,c(2,3)),diff.form=list(FALSE,capital=TRUE)) R grun.fe - plm(formula = a,data=EmplUK,model=within) [1] 10312 R summary(grun.fe) Oneway (individual) effect Within Model Call: plm(formula = a, data = EmplUK, model = within) Unbalanced Panel: n=140, T=7-9, N=1031 Residuals : Min. 1st Qu. Median 3rd Qu. Max. -17.1000 -0.3060 0.0137 0.3070 27.3000 Coefficients : Estimate Std. Error t-value Pr(|t|) wage-0.143626 0.032790 -4.3802 1.186e-05 *** capital 0.801495 0.064088 12.5062 2.2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Total Sum of Squares:5030.6 Residual Sum of Squares: 4207.8 F-statistic: 86.9179 on 2 and 889 DF, p-value: 2.22e-16 2009/11/27 David Winsemius dwinsem...@comcast.net On Nov 27, 2009, at 10:25 AM, Owen Powell wrote: 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)) Perhaps you could have read the help page for the current version of the package which says the argument have been modified. Using the current arguments: dynformula(emp~wage+capital,log.form=list(capital=FALSE,TRUE),lag.form=list(emp=2,c(2,3)),diff.form=list(FALSE,capital=TRUE)) log(emp) ~ lag(log(emp), 1) + lag(log(emp), 2) + lag(log(emp), 1) + lag(log(emp), 2) + lag(log(wage), 2) + lag(log(wage), 3) + diff(capital, 2) + diff(capital, 3) -- David Winsemius, MD 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) + diff(capital, 3) And indeed, when I try to run a regression using that formula, it appears to not contain any lags or logs (output below). Any ideas? Thanks in advance, ~Owen -- Owen Powell http://center.uvt.nl/phd_stud/powell R library(plm) R data(EmplUK, package=plm) R a = dynformula(emp~wage+capital,log=list(capital=FALSE,TRUE),lag=list(emp=2,c(2,3)),diff=list(FALSE,capital=TRUE)) snipped David Winsemius, MD Heritage Laboratories West Hartford, CT -- Owen Powell http://center.uvt.nl/phd_stud/powell __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] joint estimation of two poisson equations
Dear list members, Is there a package somewhere for jointly estimating two poisson processes? I think the closest I've come is using the SUR option in the Zelig package (see below), but when I try the poisson option instead of the SUR optioin I get an error (error given below, and indeed, reading the documentation of the Zelig package, I get the impression poisson was not meant to handle a system of equations). I think I could do it myself by constructing the likelihood function and then applying ML, but I'd prefer to avoid doing that unless it's entirely necessary. I'll post my solution to the list when I've worked it out. Regards, ~Owen # CODE FOR sur OPTION rm(list = ls()) library(Zelig) y1 = c(1,2,3,4) y2 = c(0,2,0,2) x = c(2,3,4,8) d = data.frame(cbind(y1, y2, x)) eq1 = y1 ~ x eq2 = y2 ~ x eqSystem = list (eq1, eq2) system_out = zelig(formula = eqSystem, model = sur, data = d) summary(system_out) - # ERROR FROM REPLACING sur WITH poisson Error in switch(mode(x), `NULL` = structure(NULL, class = formula), : invalid formula -- Owen Powell http://center.uvt.nl/phd_stud/powell __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] joint estimation of two poisson equations
Thanks Tirthankar, that did the trick. Here's the solution to my problem using the bivpois package: rm(list = ls()) library(bivpois) y1 = c(1,2,3,4,4,3) y2 = c(0,2,0,2,3,5) x1 = c(2,3,4,8,1,3) x2 = c(3,5,6,7,8,9) d = data.frame(cbind(y1, y2, x)) eq1 = y1 ~ x1 + x2 eq2 = y2 ~ x1 + x2 out = lm.pb(eq1, eq2, data = d, zeroL3 = TRUE) print(out) I couldn't find out how to get standard errors and p-values from the package, so I bootstrapped them. ~Owen 2009/4/13 Tirthankar Chakravarty tirthankar.chakrava...@gmail.com You should probably try the -bivpois- package: http://cran.r-project.org/web/packages/bivpois/index.html A very good discussion of multivariate Poissons, negative binomials etc. can be found in Chapter 7 of Rainer Winkelmann's book Econometric Analysis of Count Data (Springer 2008). Most of the likelihoods involved are fairly straightforward. T On Mon, Apr 13, 2009 at 9:32 AM, Owen Powell opow...@gmail.com wrote: Dear list members, Is there a package somewhere for jointly estimating two poisson processes? I think the closest I've come is using the SUR option in the Zelig package (see below), but when I try the poisson option instead of the SUR optioin I get an error (error given below, and indeed, reading the documentation of the Zelig package, I get the impression poisson was not meant to handle a system of equations). I think I could do it myself by constructing the likelihood function and then applying ML, but I'd prefer to avoid doing that unless it's entirely necessary. I'll post my solution to the list when I've worked it out. Regards, ~Owen # CODE FOR sur OPTION rm(list = ls()) library(Zelig) y1 = c(1,2,3,4) y2 = c(0,2,0,2) x = c(2,3,4,8) d = data.frame(cbind(y1, y2, x)) eq1 = y1 ~ x eq2 = y2 ~ x eqSystem = list (eq1, eq2) system_out = zelig(formula = eqSystem, model = sur, data = d) summary(system_out) - # ERROR FROM REPLACING sur WITH poisson Error in switch(mode(x), `NULL` = structure(NULL, class = formula), : invalid formula -- Owen Powell http://center.uvt.nl/phd_stud/powell __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- To every ù-consistent recursive class ê of formulae there correspond recursive class signs r, such that neither v Gen r nor Neg(v Gen r) belongs to Flg(ê) (where v is the free variable of r). -- Owen Powell http://center.uvt.nl/phd_stud/powell [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
