Using the plm
package in R to fit a fixed-effects model, what is the correct syntax to add a lagged variable to the model? Similar to the 'L1.variable' command in Stata.
Here is my attempt adding a lagged variable (this is a test model and it might not make sense):
library(foreign)
nlswork <- read.dta("http://www.stata-press.com/data/r11/nlswork.dta")
pnlswork <- plm.data(nlswork, c('idcode', 'year'))
ffe <- plm(ln_wage ~ ttl_exp+lag(wks_work,1)
, model = 'within'
, data = nlswork)
summary(ffe)
R output:
Oneway (individual) effect Within Model
Call:
plm(formula = ln_wage ~ ttl_exp + lag(wks_work), data = nlswork,
model = "within")
Unbalanced Panel: n=3911, T=1-14, N=19619
Residuals :
Min. 1st Qu. Median 3rd Qu. Max.
-1.77000 -0.10100 0.00293 0.11000 2.90000
Coefficients :
Estimate Std. Error t-value Pr(>|t|)
ttl_exp 0.02341057 0.00073832 31.7078 < 2.2e-16 ***
lag(wks_work) 0.00081576 0.00010628 7.6755 1.744e-14 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Total Sum of Squares: 1296.9
Residual Sum of Squares: 1126.9
R-Squared: 0.13105
Adj. R-Squared: -0.085379
F-statistic: 1184.39 on 2 and 15706 DF, p-value: < 2.22e-16
However, I got different results compared what Stata produces.
In my actual model, I would like to instrument an endogenous variable with its lagged value.
Thanks!
For reference, here is the Stata code:
webuse nlswork.dta
xtset idcode year
xtreg ln_wage ttl_exp L1.wks_work, fe
Stata output:
Fixed-effects (within) regression Number of obs = 10,680
Group variable: idcode Number of groups = 3,671
R-sq: Obs per group:
within = 0.1492 min = 1
between = 0.2063 avg = 2.9
overall = 0.1483 max = 8
F(2,7007) = 614.60
corr(u_i, Xb) = 0.1329 Prob > F = 0.0000
------------------------------------------------------------------------------
ln_wage | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
ttl_exp | .0192578 .0012233 15.74 0.000 .0168597 .0216558
|
wks_work |
L1. | .0015891 .0001957 8.12 0.000 .0012054 .0019728
|
_cons | 1.502879 .0075431 199.24 0.000 1.488092 1.517666
-------------+----------------------------------------------------------------
sigma_u | .40678942
sigma_e | .28124886
rho | .67658275 (fraction of variance due to u_i)
------------------------------------------------------------------------------
F test that all u_i=0: F(3670, 7007) = 4.71 Prob > F = 0.0000