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Hello Molnar
Since I cannot replicate the problem you are referring to. For the record, asreg does not do any extrapolation. If the dependent variable is missing, it shall create missing output.
Please identify any unexpected results in the following code and the results shown below the code.
*Create some dummy data
set obs 100
gen company_id = _n
expand 20
bys company_id : gen year = _n + 1980
gen dep_var = uniform()
gen x1 = uniform()
gen x2 = uniform()
gen x3 = uniform()
replace dep_var = . in 10
*rolling window regression
asreg dep_var x1 x2 x3, window(year 5) by(company_id )
*Note that the results are missing for observation 5 as I set the dep_var equal to missing in observation 10
. list company_id year dep_var x1 x2 x3 _b_x1 _b_x2 _b_x3 _b_cons in 1/20
+-----------------------------------------------------------------------------------------------------------------+
| compan~d year dep_var x1 x2 x3 _b_x1 _b_x2 _b_x3 _b_cons |
|-----------------------------------------------------------------------------------------------------------------|
1. | 1 1981 .9472316 .4128598 .722326 .5578895 . . . . |
2. | 1 1982 .0522234 .7549242 .5103776 .7870066 . . . . |
3. | 1 1983 .9743183 .552299 .8967206 .7550112 . . . . |
4. | 1 1984 .9457484 .5891278 .3083104 .3083135 . . . . |
5. | 1 1985 .1856478 .697482 .909019 .1549393 -3.0732114 -.33335542 .01013383 2.6870112 |
|-----------------------------------------------------------------------------------------------------------------|
6. | 1 1986 .9487334 .4505732 .3013251 .9282259 -3.6761877 -.03146574 -.21259752 3.002839 |
7. | 1 1987 .8825376 .3878326 .1245625 .0175663 -1.0323297 -.3133134 .40717164 1.3231022 |
8. | 1 1988 .9440776 .4846907 .2986447 .337576 1.1819022 -1.4298679 .25653229 .63017369 |
9. | 1 1989 .0894259 .4338235 .3440744 .758045 13.829088 -6.3155436 .27149413 -3.7996463 |
10. | 1 1990 . .8449519 .6950497 .3233008 . . . . |
|-----------------------------------------------------------------------------------------------------------------|
11. | 1 1991 .9484983 .4248196 .3894849 .6740687 2.953628 -.73021252 -.22957358 -.18853085 |
12. | 1 1992 .1121626 .2664079 .2287498 .327188 2.3396352 6.3272919 -2.740214 -.93388601 |
13. | 1 1993 .4809064 .5369344 .9809995 .649418 3.8529128 -.62252069 -.68318142 -.4848008 |
14. | 1 1994 .9763448 .3829168 .1949201 .9513145 -2.8998911 .73232787 1.7772335 .19997632 |
15. | 1 1995 .1254975 .0192644 .8068066 .2702817 -.05386859 -.11403092 1.3741806 -.18383902 |
|-----------------------------------------------------------------------------------------------------------------|
16. | 1 1996 .7655026 .0001751 .4510984 .3024662 -1.1119095 -.02674897 1.5406791 .00390702 |
17. | 1 1997 .0358593 .1630308 .9948465 .944969 .89422509 -1.0497158 -.30523184 1.1898735 |
18. | 1 1998 .0702359 .7856113 .7915192 .5903638 -.28049067 -1.3305861 .1390848 1.2473779 |
19. | 1 1999 .2101787 .177225 .2381918 .0603619 -.36437884 -.75992844 .31518871 .68711351 |
20. | 1 2000 .6616006 .0859762 .7393021 .1151739 -.54199642 .46124685 -.71506168 .47141122 |
+-----------------------------------------------------------------------------------------------------------------+