Dear Nick (statalisters),
Thank you for your time. Let me be more clear this time.
I would like to examine the autoregressive properties of abnormal earinings (=residual income) (first order abnormal earnings autoregression). So I want to use a pooled analysis with one lag, i.e. residual_income (i, t+1) = b0 + b1 * residual_income(i, t) + e(i, t+1), where i is a specific company ("name" as identifier) and t is the year of the observation ("year"). What I want to get is a fade rate b1 , which describes the reversal of residual_income. b1 should be one single value in order to predict future residual incomes in another sample ( i.e. residual_income next year equals b1 times residual income this year). I expect b1 to be about 0.7 (b0=0).
When I say the regression should run over every two consecutive years for a company I mean that the regression should ignore cases, in which there is more than one year between two observations, because b1 should be the fade rate of residual_income from one year to the following year.
The identifier for company is "name" and the year is given by "year". I used:
tsset name year
.panel variable: name, 1000 to 270705
.time variable: year, 1974 to 2006, but with gaps
rollreg residual_income l.residual_income, move(2) stub(a)
.sample may not contain gaps
r(198);
Well, I don't know whether my idea is an appropiate way to solve this problem and to get one single b1. Perhaps someone can help me, whether this is an appropiate way to solve this problem and to get one single value of b1 and how to get rid of the gaps (because -rollreg-from SSC does not support gaps in the data).
Thanks for your consideration.
Greg B.
-------- Original-Nachricht --------
> Datum: Mon, 20 Oct 2008 13:37:03 +0100
> Von: "Nick Cox" <[email protected]>
> An: [email protected]
> Betreff: st: RE: regression: fade rate residual income
> I think you have problems at various levels.
>
> The most obvious is that -rollreg- from SSC [please remember to explain
> where user-written programs you discuss come from] does not support data
> with gaps. When you -tsset- your data you should have seen a comment
> that your data include gaps.
>
> The next is what you are trying to do. If I read this correctly, you
> want to look at regressions for pairs of values within each panel. That
> gives you at most two distinct data points and you should be able to
> solve for the coefficients directly. You will get perfect fits, except
> when points coincide when regression will be indeterminate. Also, there
> is no question of an error term.
>
> On the other hand, I doubt that I am reading you correctly.
>
> You posted on this topic a week ago. In response both Michael Hanson and
> I hinted that you may need to explain what you expect in more detail to
> get better answers.
>
> Nick
> [email protected]
>
> [email protected]
>
> I would like to run a regression on residual_income. I have yearly
> observations of residual income for firms. The year is given in variable
> "year", the identifier for firm is "name".
>
> I'd like to run the regression residual_income(year) = b0 + b1 *
> residual_income(year-1) + e The regression should run on
> "residual_income" over every two consecutive years ("year") within each
> identifier "name" (whenever there are values for at least two
> consecutive years for a given name).
>
> I used the following:
>
> drop if missing(residual_income)
> tsset name year
> rollreg residual_income l.residual_income, move(2) stub(a)
>
> I hope this command will do what I want but unfortunately Stata always
> says:
> sample may not contain gaps
> r(198);
>
> What might be the problem?
>
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