Dear list,
I am trying to replicate an econometrics study that was orginally done in
Stata. (Blanton and Blanton. 2009. A Sectoral Analysis of Human Rights and FDI:
Does Industry Type Matter? International Studies Quarterley 53 (2):469 - 493.)
The model I try to replicate is in Stata given as
xtpcse total_FDI lag_total ciri human_cap worker_rts polity_4 market income
econ_growth log_trade fix_dollar fixed_xr xr_fluct lab_growth english, pairwise
corr(ar1)
According to the paper, this is an OLS regression with panel corrected standard
errors including a lagged dependent variable (lag_total is total_FDI t-1) and
controlling first order correlations within each panel (corr(ar1)).
The BIG QUESTION is how to replicate this line in R.
Econometrics is a new field to me, but a bit of searching showed that packages
like plm, nlme, pcse should be able to handle this kind of problem. In
particular, function gls() uses auto-correlation structure and pcse() corrects
the standard errors of the fitted model. Below is some code to show what I have
done, and some problems I ran into.
## setup and load data from web
library(foreign)
library(nlme)
library(pcse)
D <-
read.dta("http://umdrive.memphis.edu/rblanton/public/ISQ_data/blanton_isq08_data.dta";)
D[544,"year"] <- 2005 ## fixing an unexpected NA in the year column
## Model formula
form <- total_FDI ~ lag_total + ciri + human_cap + worker_rts + polity_4 +
market_size + income + econ_growth + log_trade + fixed_xr + fix_dollar +
xr_fluct + english + lab_growth
## Model 1: no auto-correlation
res1 <- gls(model=form, data=D,correlation=NULL,na.action=na.omit)
coefficients(res1)
## Model 2: with auto-correlation
corr <- corAR1(.1,~1|c_name)
res2 <- gls(model=form, data=D,correlation=corr,na.action=na.omit)
coefficients(res2)
Now, I know from the paper how the Stata coefficients looked like. For
example, for log_total it should be .852 and for market_size .21 (these were
the two significant ones). The result of Model1 is closer to this than the
result of Model 2, but there is still quite a gap.
The goal is to do OLS on panel data with AR(1) and PCSE - am I on the right
track here? More specifically:
Question 1: Auto-correlation
- how to specify the parameter 'value' in corAR1 (the .1 above is completely
arbitrary)
- Any other ideas how to translate Stata's corr(AR1) into R? (I'm not even
completely sure what Stata does there and didn't find any details in the online
manuals)
Question 2: PCSE
- the pcse function seems to work on objects of class 'lm' only. Any way to use
it for gls-objects?
Any help is greatly appreciated!
Florian
--
Florian Markowetz
Cancer Research UK
Cambridge Research Institute
Li Ka Shing Centre
Robinson Way, Cambridge, CB2 0RE, UK
phone: +44 (0) 1223 40 4315
email: florian.markow...@cancer.org.uk
web : http://www.markowetzlab.org
skype: florian.markowetz
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