Dear Salaam,
if I ever get you right (and I'm not sure I do), you are confusing the
residuals with the fixed effects. What you **would** probably be
computing, if you used square brackets like in
>
0.59081533*ADOP[200001]+0.04263590*PE[200002]-0.03717528*WOR[200002]+2.6
6677[200002]
(and amended the last index in your expression, which was wrong...) is
the **fitted value** for '200002'. The difference between this and
ADOP[200002] is the residual: should be ar1$residuals[200002].
Otherwise, your estimation results look "technically" OK to me. Sorry,
if I misunderstood your post.
HTH,
Giovanni
------------------------------
Message: 156
Date: Thu, 15 Jul 2010 13:15:36 +0800
From: Salaam Batur <swordlight20 at gmail.com>
To: r-help at r-project.org
Subject: [R] I can't figure out my plm model. Any ideas?
Message-ID:
<AANLkTil-Py06oRQSu-lMdDxcRE2x34TTMQuCsXncA1I9 at mail.gmail.com>
Content-Type: text/plain
Dear R users,
I am using plm packege in R to build my model, but from the result I
can't
quite figure out what it is... Can anyone tell me why? Am I missing
something?
R Results:
*> ar1<-plm(formula=ADOP~lag(ADOP,1)+PE+WOR,
+ data=well,
effect="time",model="within")> summary(ar1)*
Oneway (time) effect Within Model
Call:
plm(formula = ADOP ~ lag(ADOP, 1) + PE + WOR, data = well, effect
"time",
model = "within")
Unbalanced Panel: n=135, T=1-119, N=10972
Residuals :
Min. 1st Qu. Median 3rd Qu. Max.
-25.9000 -0.8950 -0.0627 0.7210 25.4000
Coefficients :
Estimate Std. Error t-value Pr(>|t|)
lag(ADOP, 1) 0.59081533 0.00598959 98.640 < 2.2e-16 ***
PE 0.04263590 0.00087449 48.755 < 2.2e-16 ***
WOR -0.03717528 0.00072192 -51.495 < 2.2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05
'.' 0.1 ' ' 1
Total Sum of Squares: 148890
Residual Sum of Squares: 42814
F-statistic: 8960.98 on 3 and 10850 DF, p-value: < 2.22e-16
*> summary(fixef(ar1, effect="time"))
* Estimate Std. Error t-value Pr(>|t|)
200002 2.66677 0.22335 11.9397 < 2.2e-16 ***
200003 2.42303 0.22340 10.8464 < 2.2e-16 ***
200004 2.49954 0.21370 11.6964 < 2.2e-16 ***
200005 2.61619 0.21305 12.2799 < 2.2e-16 ***
200006 3.21967 0.21451 15.0094 < 2.2e-16 ***
200007 1.72400 0.21028 8.1986 2.220e-16 ***
200008 2.58108 0.21009 12.2854 < 2.2e-16 ***
200009 2.59461 0.21566 12.0309 < 2.2e-16 ***
200010 2.69361 0.21605 12.4676 < 2.2e-16 ***
200011 2.35014 0.22084 10.6419 < 2.2e-16 ***
200012 2.33155 0.22047 10.5751 < 2.2e-16 ***
200101 2.92930 0.21892 13.3808 < 2.2e-16 ***
200102 2.58167 0.22187 11.6361 < 2.2e-16 ***
200103 3.13288 0.21851 14.3377 < 2.2e-16 ***
200104 2.32652 0.21682 10.7303 < 2.2e-16 ***
200105 2.93256 0.21576 13.5918 < 2.2e-16 ***
200106 2.49128 0.21177 11.7640 < 2.2e-16 ***
200107 2.33528 0.21472 10.8759 < 2.2e-16 ***
200108 2.38340 0.21325 11.1767 < 2.2e-16 ***
200109 2.58050 0.21202 12.1709 < 2.2e-16 ***
..........so
on....................................................................
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05
'.' 0.1 ' ' 1>
########################################################################
ADOP(200002)=0.59081533*ADOP(200001)+0.04263590*PE(200002)-0.03717528*WO
R(200002)+2.66677
(Feb2000)
....and so on...
*It should look like this, right? When I put the data to this model, the
right hand side and left one is not equal. What did I miss? *
[[alternative HTML version deleted]]
------------------------------
Giovanni Millo
Research Dept.,
Assicurazioni Generali SpA
Via Machiavelli 4,
34132 Trieste (Italy)
tel. +39 040 671184
fax +39 040 671160
Ai sensi del D.Lgs. 196/2003 si precisa che le informazi...{{dropped:13}}