Dear Statalist,
I am doing research on using nighttime light (radiances per area) to predict real regional GDP (random effect model). I have a dataset of 34 provinces in Indonesia for the period 2012-2020 (quarterly data). My mentor suggested I include time fixed effects (i.qdate) and province fixed effects (i.id) as dummies. But when I do so, the significance of my interest variable (ln_nli) become insignificance. Here's my result before and after adding the time and provinces dummy:


. xtreg . xtreg ln_pdrb ln_nli, re ro

Random-effects GLS regression Number of obs = 1,122
Group variable: id Number of groups = 34

R-sq: Obs per group:
within = 0.3997 min = 33
between = 0.5016 avg = 33.0
overall = 0.4384 max = 33

Wald chi2(1) = 164.50
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000

(Std. Err. adjusted for 34 clusters in id)
------------------------------------------------------------------------------
| Robust
ln_pdrb | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
ln_nli | .1363934 .0106343 12.83 0.000 .1155505 .1572363
_cons | 17.57819 .1798055 97.76 0.000 17.22578 17.9306
-------------+----------------------------------------------------------------
sigma_u | .82280392
sigma_e | .09782348
rho | .98606209 (fraction of variance due to u_i)
------------------------------------------------------------------------------

. xtreg ln_pdrb ln_nli i.qdate i.id, re ro

Random-effects GLS regression Number of obs = 1,122
Group variable: id Number of groups = 34

R-sq: Obs per group:
within = 0.8764 min = 33
between = 1.0000 avg = 33.0
overall = 0.9985 max = 33

Wald chi2(33) = .
corr(u_i, X) = 0 (assumed) Prob > chi2 = .

(Std. Err. adjusted for 34 clusters in id)
------------------------------------------------------------------------------
| Robust
ln_pdrb | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
ln_nli | .0071749 .0078816 0.91 0.363 -.0082727 .0226225
|
qdate |
210 | .0281132 .0042352 6.64 0.000 .0198124 .036414
211 | .0285663 .012437 2.30 0.022 .0041903 .0529424
212 | .024168 .0056676 4.26 0.000 .0130597 .0352764
213 | .0488249 .0062365 7.83 0.000 .0366016 .0610482
214 | .0875023 .0052677 16.61 0.000 .0771778 .0978268
215 | .0941612 .0085182 11.05 0.000 .0774657 .1108566
216 | .0838755 .006852 12.24 0.000 .0704458 .0973053
217 | .1006991 .0076502 13.16 0.000 .085705 .1156933
218 | .1361169 .007639 17.82 0.000 .1211449 .151089
219 | .1439286 .0098438 14.62 0.000 .1246351 .1632221
220 | .1285819 .0110317 11.66 0.000 .1069601 .1502037
221 | .1559425 .0115845 13.46 0.000 .1332374 .1786476
222 | .1867966 .0139732 13.37 0.000 .1594097 .2141835
223 | .1943102 .0125887 15.44 0.000 .1696368 .2189835
224 | .1819726 .013399 13.58 0.000 .1557111 .2082341
225 | .2012336 .0149958 13.42 0.000 .1718423 .2306248
226 | .2399893 .0161248 14.88 0.000 .2083854 .2715933
227 | .2516112 .0159806 15.74 0.000 .2202897 .2829326
228 | .226623 .0141486 16.02 0.000 .1988923 .2543537
229 | .2448326 .0168339 14.54 0.000 .2118388 .2778264
230 | .2867302 .0181616 15.79 0.000 .2511341 .3223263
231 | .2939583 .0181339 16.21 0.000 .2584166 .3295001
232 | .2795545 .0158775 17.61 0.000 .2484351 .3106738
233 | .3027815 .018904 16.02 0.000 .2657303 .3398327
234 | .3326927 .0195459 17.02 0.000 .2943834 .371002
235 | .3371736 .0176719 19.08 0.000 .3025373 .3718099
236 | .3191344 .0178491 17.88 0.000 .2841509 .3541179
237 | .3431905 .0197575 17.37 0.000 .3044666 .3819144
238 | .378396 .0190506 19.86 0.000 .3410574 .4157345
239 | .3853209 .0203378 18.95 0.000 .3454596 .4251822
240 | .3490189 .0190272 18.34 0.000 .3117262 .3863116
241 | .3074161 .02012 15.28 0.000 .2679816 .3468506
|
id |
2 | 1.349615 .0033258 405.80 0.000 1.343097 1.356134
3 | .2081012 .0001396 1490.41 0.000 .2078276 .2083749
4 | 1.35338 .0031468 430.08 0.000 1.347212 1.359547
5 | .080414 .0020315 39.58 0.000 .0764323 .0843958
6 | .8071257 .0031772 254.04 0.000 .8008985 .8133529
7 | -1.094362 .0033559 -326.10 0.000 -1.100939 -1.087784
8 | .5555607 .0047317 117.41 0.000 .5462867 .5648347
9 | -.9177501 .0002953 -3108.17 0.000 -.9183288 -.9171714
10 | .273506 .0109266 25.03 0.000 .2520903 .2949218
11 | 2.518404 .03778 66.66 0.000 2.444356 2.592451
12 | 2.349943 .0151691 154.92 0.000 2.320212 2.379674
13 | 1.945931 .0119341 163.06 0.000 1.922541 1.969321
14 | -.3214616 .0144193 -22.29 0.000 -.349723 -.2932003
15 | 2.446185 .0140759 173.79 0.000 2.418597 2.473773
16 | 1.158497 .0175069 66.17 0.000 1.124184 1.19281
17 | .1139387 .013109 8.69 0.000 .0882455 .1396319
18 | -.3446538 .0030191 -114.16 0.000 -.3505712 -.3387365
19 | -.6924587 .0047129 -146.93 0.000 -.7016958 -.6832216
20 | -.0098659 .0049347 -2.00 0.046 -.0195378 -.0001941
21 | -.3577425 .0049798 -71.84 0.000 -.3675027 -.3479824
22 | 1.333831 .002178 612.41 0.000 1.329562 1.3381
23 | 1.334234 .0017355 768.79 0.000 1.330832 1.337635
24 | -.8315154 .0046088 -180.42 0.000 -.8405486 -.8224823
25 | -.4790523 .0026143 -183.24 0.000 -.4841762 -.4739284
26 | -.3125605 .0025476 -122.69 0.000 -.3175537 -.3075674
27 | .7999971 .0031723 252.18 0.000 .7937795 .8062147
28 | -.4333453 .0034614 -125.19 0.000 -.4401296 -.4265611
29 | -1.630576 .0010813 -1508.04 0.000 -1.632696 -1.628457
30 | -1.477908 .0055417 -266.69 0.000 -1.48877 -1.467047
31 | -1.512727 .0054251 -278.84 0.000 -1.52336 -1.502094
32 | -.7831341 .0059699 -131.18 0.000 -.794835 -.7714333
33 | -.7823274 .0068561 -114.11 0.000 -.7957651 -.7688898
34 | .1184597 .0086356 13.72 0.000 .1015342 .1353851
|
_cons | 17.0143 .0191901 886.62 0.000 16.97669 17.05191
-------------+----------------------------------------------------------------
sigma_u | 0
sigma_e | .04505634
rho | 0 (fraction of variance due to u_i)
------------------------------------------------------------------------------

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