Jing,

> Does the insignificance of
> the [lagged] d.v. mean error correction model is not approriate?  If
yes, can I

Yes, I'm afraid it does. More exactly, it means you (seem) still (to)
have non-stationarity in that specification. What you'd like is for that
coefficient to be negative and highly significant (say t>=4). The basic
idea of the ECM approach (I am assuming you are following the version of
it Beck, Political Analysis volume 3, popularized to political science)
is that somewhere in your right-hand-side you have sufficient
cointegrating factors such that the dependent variable net of
(controlling for) those cointegrating relationships is stationary. I.e.,
the left-hand-side is non-stationary, but it moves in equilibrium with
some combination of your right-hand-side variables such that if you take
left-hand-side minus that combination of right-hand-side terms, i.e. net
of the equilibrium relationship, the remainder is stationary.

My first line of advice for someone in your situation would be to ask
whether you could think of any further information, i.e., explanators,
that you could place on the RHS to explain the level of school
enrolments better. My guess is that enrollment actually is
non-stationary, unlike a lot of things that political scientists have
worried about that about, but that it definitely ought to be
cointegrated with an appropriate set of RHS explanators. It's
non-stationary because it's a demographic thing, basically, so shocks at
time t (say to birth rates) will multiply exponentially forward b/c
those higher or lower birth numbers then create permanent change in pool
having more or fewer births next period & so on exponentially, without
any reason to expect mean-reversion that I can see. So, have you got
sufficient demographic controls in your models? Any other important
explanators you may be neglecting?

Some quick-and-easy possible fixes--atheoretical ones, so I don't like
them much, but quick & easy & maybe effective, so maybe consider them if
you haven't already:
* Do you have fixed effects included for these 6 countries? If not, and
if you don't have cross-sectional heterogeneity sufficiently modeled
otherwise (i.e. the preferable way: theoretically), then your lag
coefficients are biased upward (dynamics estimated as too slow,
incorrectly increasing the degree to which they look nonstationary). So,
try 'em if you don't already have 'em.
* (A little less atheoretical, so less distasteful) Do you have any
lagged changes of the dependent variable on the right-hand side? These
would capture any kind of "momentum", as opposed to level, "stickyness",
and, again, if such exists & you do not have it modeled, it might be
biasing your estimates of the level dynamics. (Might, might not, depends
on what's actually happening in your short time-series.) Try 'em if you
don't already have 'em.
* (This one is at least as atheoretical as the country (dumb) dummies,
so I don't like it either, but, it is easy, so...) Have you tried
including a linear (or other-shape) trend? Once again, if there is one &
you don't have it sufficiently explained & accounted in your existing
right-hand-side (i.e., in the far-preferable theoretical way!), then
your dynamic estimates are likely biased upward (too sticky) and so the
left-hand-side variable incorrectly appears more nonstationary than it
is. Try 'em if you don't already have 'em.


Hope this helps, and Good luck!
Rob


************************************************************************
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Robert (Rob) J. Franzese, Jr.                  US Mail:   (ISR Room
4256)
Assoc. Prof. Political Science                              P.O. Box
1248
The University of Michigan                       Ann Arbor, MI
48106-1248
Research Assoc. Prof.                        TeleComm:
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Director, EITM: Empirical Implications of Theoretical Models,
                2006 Summer Institute, University of Michigan, Ann Arbor
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> -----Original Message-----
> From: Political Methodology Society [mailto:[log in to unmask]]
On
> Behalf Of Jing Chen
> Sent: Friday, May 19, 2006 9:26 AM
> To: [log in to unmask]
> Subject: [POLMETH] a question on error correction model
>
> Dear Political Methodologists,
>
> I'm studying determinants of gross school enrolment. The data is
> unbalanced panel data consisting of 6 countries and about 25 years of
> each. My choice of model is error correction model since school
> enrolment is not stationary. I used OLS with PCSEs. My estimation for
> primary and secondary school enrolment look fine. However, in the
model
> for tertiary school enrolment, the coefficient for the lagged d.v.
comes
> out as insigificant and positive.  I then logged tertiary school
> enrolment since it is skewed; the coefficient for the lagged d.v. now
> becomes negative now but still insignificant. Does the insignificance
of
> the d.v. mean error correction model is not approriate?  If yes, can I
> still interpretate other coefficients the regular way?  Any advice is
> greatly appreciated.
>
> Best,
>
> Jing Chen
> PhD Candidate
> Political Science Department
> Rutgers, the State University of New Jersey
>
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