# st: RE: Time trend in fixed effects modle

 From "Rodrigo Alfaro A." <[email protected]> To <[email protected]> Subject st: RE: Time trend in fixed effects modle Date Tue, 15 Apr 2008 13:18:53 -0400

```Rita,

Suppose that you have a way to deal with your "missings at random". In
that scenario you have 10 ids and 19 years (obs=190), and you are
estimating the model with ids and year dummies, other covariates, and
interactions between ids and years. How many degree of freedom you have?

If you think that the missings are at random, maybe you could deal with
them using a multiple imputation procedure, such as the one available in
-ice-. You could be in the scenario above.

I do not know what is the purpose of your model, but from time-series
point of view it could be nice to have a long serie, then keep the
provinces for the full sample sounds a good idea. On the other hand,
keep the complete sample gives you 5 years and 10 ids... which is few
obs but maybe enough for your goal.

Rodrigo.

-----Mensaje original-----
De: [email protected]
[mailto:[email protected]] En nombre de rita luk
Enviado el: Martes, 15 de Abril de 2008 12:09 p.m.
Para: [email protected]
Asunto: st: Time trend in fixed effects modle

Hi Statalist,

Have a question on the design matrix of a fixed effects model.

I have cigarette sales and price data for a panel of ten provinces. Some
provinces have data for 19 years
(1981-1999) while other have data for 14 years (1981-1989, 1995-1999.
missing at random).

I regress sales on price, other provincial level covariates, provincial
and year dummy variables, and provincial specific time trends. My
question is on the last item.

To create provincial specific time trends variables, I create a time
trend variable, and interact it with provincial dummy variables. For a
province with full data, value of the trend variable are 1, 2, 3,... 19
corresponding to years 1981 to 1999.

For a province with only 14 data points, the trend value for 1981 to
1989 are the same as above. However, I do not know the proper way for
values of 1995 and thereafter. I can think of 2 possible ways:

Year			Way I			Way II
1981 			1			1
1982 to 1988		skip here		skip
1989			9			9
(1990-1994)		missing data	missing data
1995			15			10
1996			16			11
1997			17			12
1998			18			13
1999			19			14

Which way of coding is correct? Does the coding depend on the research
question in hand? I have searched on some fixed effects model with
unbalanced panel and unequal spacing, and found nothing said on this.

Thanks very much for all of your help.

Rita Luk
Research Officer
Ontario Tobacco Research Unit
University of Toronto
(416) 535-8501 x4727

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