Sergio wrote:
> I am estimating a standard linear model for a panel of the type:
> y(i,t) = b0 + b1x(i,t) + b2z(i,t) +...+ u(i,t)
> I want to see how does the coefficient b1 change over the whole range of another
> variable k not included in the model.
>
> Can I use something similar to a rolling regression even if my variable k is not
> time?
Yes, but you need to know how to access the coefficients from your
last model. Here's an example of how to do what you want, which
includes Baum/Schaffer/Stillman's -ivreg2- routine, downloadable from
SSC:
. webuse grunfeld
. tsset company year
. qui ivreg2 invest mvalue kstock time, bw(2) robust small
. g asif = _b[_cons]+_b[kstock]*kstock
. tab year, sum(asif)
| Summary of asif
year | Mean Std. Dev. Freq.
------------+------------------------------------
1935 | -35.35167 15.416683 10
1936 | -32.719774 16.340199 10
1937 | -26.372769 17.793016 10
1938 | -18.287618 23.054527 10
1939 | -14.717041 25.525124 10
1940 | -13.990398 25.112402 10
1941 | -10.003932 26.990851 10
1942 | -4.0298757 30.221506 10
1943 | -1.8618989 30.831515 10
1944 | -2.2220107 32.547093 10
1945 | -.61733065 34.569687 10
1946 | 2.5791901 38.816106 10
1947 | 19.008229 52.989957 10
1948 | 28.102447 61.844248 10
1949 | 35.926864 67.380231 10
1950 | 40.387872 72.122879 10
1951 | 45.280042 78.06703 10
1952 | 58.360062 89.718207 10
1953 | 75.884266 110.04284 10
1954 | 93.62981 136.78561 10
------------+------------------------------------
Total | 11.949223 66.644863 200
-tab-, and other programs using it as its basis, can be used in other
ways to get what you want, but that's left for you to explore.
> I have another question as well,
> I am also estimating a simple linear model for a panel of countries using GLS to
> take into account autoregression; but as I need to use country dummies I
> proceed as follows
> xi: xtgls y x1... xn i.country, [options]
>
> can anybody tell me if this way of proceeding is correct? Because I am basically
> trying to use fixed effects (my country dummies) with a procedure that
> estimates random effecta models only (the xtgls command)
I'd start with the FE model using -xtreg, fe- and assessing the
correlation between the RHS variables and the 'idiosyncratic' error
term u_i. If corr(u_i, Xb) = 0, you can proceed to an RE model via
-xtreg, re- or -xtgls-. If it's not 0, estimates and standard errors
obtained from models assuming REs will not be reliable.
--
Clive Nicholas
[Please DO NOT mail me personally here, but at
<[email protected]>. Thanks!]
"Courage is going from failure to failure without losing enthusiasm."
-- Winston Churchill
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