Hi there,
How can I generate and run regression to control industry*year fixed effect in STATA?
Thank you in advance!
How can I generate and run regression to control industry*year fixed effect in STATA?
Thank you in advance!
. use "https://www.stata-press.com/data/r17/nlswork.dta" (National Longitudinal Survey of Young Women, 14-24 years old in 1968) . g year_industry=year*ind_code (341 missing values generated) . xtset idcode year_industry repeated time values within panel r(451); . xtset idcode Panel variable: idcode (unbalanced) . xtreg ln_wage c.age##c.age i.year_industry, fe vce(cluster idcode) Fixed-effects (within) regression Number of obs = 28,169 Group variable: idcode Number of groups = 4,694 R-squared: Obs per group: Within = 0.1828 min = 1 Between = 0.2075 avg = 6.0 Overall = 0.1719 max = 15 F(170,4693) = . corr(u_i, Xb) = 0.0913 Prob > F = . (Std. err. adjusted for 4,694 clusters in idcode) ------------------------------------------------------------------------------- | Robust ln_wage | Coefficient std. err. t P>|t| [95% conf. interval] --------------+---------------------------------------------------------------- age | .065437 .0060477 10.82 0.000 .0535807 .0772933 | c.age#c.age | -.0008458 .0000988 -8.56 0.000 -.0010395 -.0006522 | year_industry | 69 | -.2151244 .1116532 -1.93 0.054 -.4340171 .0037684 70 | .0936565 .1078587 0.87 0.385 -.1177972 .3051102 71 | .1750703 .121042 1.45 0.148 -.0622288 .4123694 72 | -.0621015 .1347583 -0.46 0.645 -.326291 .202088 73 | .1320197 .0746783 1.77 0.077 -.0143847 .2784242 75 | .2561939 .0792523 3.23 0.001 .1008221 .4115656 77 | .1449438 .0965875 1.50 0.134 -.0444131 .3343007 78 | .1407521 .0941516 1.49 0.135 -.0438292 .3253334 80 | .1988352 .1110053 1.79 0.073 -.0187873 .4164577 82 | -.001926 .0890316 -0.02 0.983 -.1764697 .1726177 83 | .1192486 .10569 1.13 0.259 -.0879536 .3264507 85 | .1415818 .1263064 1.12 0.262 -.106038 .3892016 87 | .2050909 .119643 1.71 0.087 -.0294655 .4396473 88 | .1717386 .1045222 1.64 0.100 -.033174 .3766512 136 | .5208783 .058937 8.84 0.000 .4053342 .6364225 138 | .4446881 .0569746 7.81 0.000 .332991 .5563851 142 | .2988656 .1012043 2.95 0.003 .1004575 .4972736 144 | .3230389 .0714804 4.52 0.000 .1829037 .4631741 146 | .3913242 .0817845 4.78 0.000 .2309881 .5516603 150 | .1523785 .1628553 0.94 0.349 -.1668944 .4716513 154 | .3331075 .1345977 2.47 0.013 .0692329 .5969821 156 | .3589759 .2197103 1.63 0.102 -.0717594 .7897112 160 | .3489823 .1502397 2.32 0.020 .054442 .6435227 164 | .5490549 .139797 3.93 0.000 .2749872 .8231226 166 | .4259425 .1126494 3.78 0.000 .2050968 .6467882 170 | -.0707755 .1499249 -0.47 0.637 -.3646987 .2231478 174 | .2156787 .084263 2.56 0.011 .0504836 .3808738 176 | .9085235 .378261 2.40 0.016 .1669543 1.650093 204 | .0248326 .1711965 0.15 0.885 -.310793 .3604582 207 | .389997 .1414865 2.76 0.006 .112617 .667377 210 | .300939 .1150671 2.62 0.009 .0753536 .5265245 213 | .2779948 .118374 2.35 0.019 .0459261 .5100635 216 | .2902304 .1073506 2.70 0.007 .0797729 .5006879 219 | .2870798 .0851122 3.37 0.001 .1202199 .4539397 225 | .1741011 .0807504 2.16 0.031 .0157923 .3324099 231 | .1664301 .0943804 1.76 0.078 -.0185999 .3514601 234 | .234718 .1611553 1.46 0.145 -.081222 .550658 240 | .1545278 .106733 1.45 0.148 -.0547189 .3637745 246 | .2096142 .1062506 1.97 0.049 .0013132 .4179152 249 | .2180392 .1049774 2.08 0.038 .0122342 .4238443 255 | .288641 .0893613 3.23 0.001 .1134508 .4638311 261 | .233504 .0980585 2.38 0.017 .0412632 .4257447 264 | .4492036 .1315862 3.41 0.001 .1912328 .7071743 272 | .3238391 .0574558 5.64 0.000 .2111987 .4364794 276 | .3785699 .057292 6.61 0.000 .2662507 .4908891 280 | .3467667 .0570678 6.08 0.000 .2348869 .4586464 284 | .3439252 .0573162 6.00 0.000 .2315585 .4562919 288 | .3074104 .0581815 5.28 0.000 .1933472 .4214736 292 | .3198939 .0583272 5.48 0.000 .2055451 .4342426 300 | .2682323 .0584968 4.59 0.000 .153551 .3829136 308 | .2856677 .0600966 4.75 0.000 .1678501 .4034852 312 | .3132106 .0607554 5.16 0.000 .1941014 .4323197 320 | .2749739 .0615764 4.47 0.000 .1542553 .3956925 328 | .2839539 .0627965 4.52 0.000 .1608433 .4070645 332 | .2911078 .0639795 4.55 0.000 .165678 .4165377 340 | .2994247 .0631475 4.74 0.000 .175626 .4232235 345 | .2862553 .0700038 4.09 0.000 .149015 .4234956 348 | .3196252 .0672787 4.75 0.000 .1877274 .451523 350 | .2686098 .065238 4.12 0.000 .1407127 .396507 352 | .3754444 .069154 5.43 0.000 .2398702 .5110187 355 | .3124303 .0649669 4.81 0.000 .1850647 .4397959 360 | .3851681 .0648817 5.94 0.000 .2579695 .5123667 365 | .3776866 .0660637 5.72 0.000 .2481708 .5072025 375 | .3521591 .0683131 5.16 0.000 .2182333 .4860848 385 | .4133773 .0683242 6.05 0.000 .2794298 .5473248 390 | .4452066 .0693982 6.42 0.000 .3091536 .5812597 400 | .4452914 .0754288 5.90 0.000 .2974155 .5931672 408 | .0745872 .0598057 1.25 0.212 -.0426601 .1918345 410 | .3830289 .0760436 5.04 0.000 .2339478 .53211 414 | .1303118 .0591092 2.20 0.028 .01443 .2461936 415 | .4577505 .0739948 6.19 0.000 .312686 .6028151 420 | .0815238 .058331 1.40 0.162 -.0328323 .1958799 425 | .5283037 .0768345 6.88 0.000 .3776719 .6789354 426 | .0971294 .0575936 1.69 0.092 -.0157812 .21004 432 | .1094456 .0587149 1.86 0.062 -.0056632 .2245544 435 | .5619322 .0746805 7.52 0.000 .4155233 .7083412 438 | .113441 .0590082 1.92 0.055 -.0022427 .2291247 440 | .58528 .0787695 7.43 0.000 .4308548 .7397051 450 | .0363949 .0601823 0.60 0.545 -.0815906 .1543805 462 | .0814815 .0606352 1.34 0.179 -.0373919 .200355 468 | .1126424 .0617441 1.82 0.068 -.0084049 .2336898 476 | .1567416 .0643039 2.44 0.015 .0306757 .2828075 480 | .1424003 .0634375 2.24 0.025 .018033 .2667677 483 | .1816016 .0643259 2.82 0.005 .0554926 .3077105 490 | .2366809 .0615478 3.85 0.000 .1160183 .3573434 492 | .1087102 .0634867 1.71 0.087 -.0157536 .2331739 497 | .2674618 .0610082 4.38 0.000 .1478571 .3870666 498 | .0721726 .065511 1.10 0.271 -.0562596 .2006048 504 | .2679617 .0603997 4.44 0.000 .1495499 .3863735 510 | .1128694 .0661898 1.71 0.088 -.0168936 .2426325 511 | .2291164 .0617936 3.71 0.000 .107972 .3502608 522 | .0998189 .0686988 1.45 0.146 -.0348631 .2345009 525 | .2080324 .0607094 3.43 0.001 .0890135 .3270513 528 | .1921288 .0726317 2.65 0.008 .0497365 .3345211 539 | .2128163 .0620517 3.43 0.001 .0911659 .3344668 544 | .3441324 .0904516 3.80 0.000 .1668048 .52146 546 | .2272568 .0638271 3.56 0.000 .1021257 .3523879 552 | .2077733 .0861652 2.41 0.016 .0388489 .3766976 560 | .1992018 .0643654 3.09 0.002 .0730155 .3253882 568 | .1799161 .0767435 2.34 0.019 .0294628 .3303695 574 | .1883749 .0648068 2.91 0.004 .061323 .3154267 576 | .1763003 .0676455 2.61 0.009 .0436834 .3089173 581 | .2075204 .0690782 3.00 0.003 .0720947 .3429461 584 | .2029434 .0705781 2.88 0.004 .0645773 .3413096 595 | .2904191 .0682749 4.25 0.000 .1565683 .4242699 600 | .0948139 .0895537 1.06 0.290 -.0807534 .2703811 609 | .311109 .072125 4.31 0.000 .1697102 .4525078 612 | -.2016842 .0688974 -2.93 0.003 -.3367554 -.066613 616 | .3460607 .0717121 4.83 0.000 .2054713 .4866502 621 | -.0894246 .0738252 -1.21 0.226 -.2341567 .0553075 624 | .2110704 .0768438 2.75 0.006 .0604204 .3617204 630 | -.1303852 .0681089 -1.91 0.056 -.2639106 .0031401 639 | -.0520332 .0655822 -0.79 0.428 -.1806051 .0765387 640 | .0759073 .077653 0.98 0.328 -.0763291 .2281436 648 | -.0617995 .0721231 -0.86 0.392 -.2031947 .0795957 656 | .1519032 .0690321 2.20 0.028 .0165679 .2872385 657 | -.1022863 .0714177 -1.43 0.152 -.2422985 .0377259 664 | .1164675 .0768336 1.52 0.130 -.0341624 .2670973 675 | -.0263705 .0677073 -0.39 0.697 -.1591085 .1063676 680 | .2180718 .0757426 2.88 0.004 .0695809 .3665628 690 | .0476264 .1774924 0.27 0.788 -.300342 .3955948 693 | .0233201 .068779 0.34 0.735 -.1115191 .1581592 696 | .1346823 .0776851 1.73 0.083 -.017617 .2869816 700 | .1453541 .1265886 1.15 0.251 -.1028191 .3935273 702 | .0461645 .071808 0.64 0.520 -.0946128 .1869419 704 | .2121431 .0904798 2.34 0.019 .0347602 .3895259 710 | .2347147 .195053 1.20 0.229 -.1476807 .6171101 720 | .0638993 .0738622 0.87 0.387 -.0809053 .2087039 730 | .056443 .1336928 0.42 0.673 -.2056578 .3185437 738 | .0007804 .0722979 0.01 0.991 -.1409575 .1425183 747 | -.0160618 .0739343 -0.22 0.828 -.1610077 .1288841 748 | .1566492 .0598366 2.62 0.009 .0393413 .2739571 750 | .1980612 .1388667 1.43 0.154 -.0741827 .4703051 759 | .2326681 .0573945 4.05 0.000 .120148 .3451882 765 | .0777132 .0774555 1.00 0.316 -.074136 .2295624 770 | .1902657 .0579382 3.28 0.001 .0766796 .3038518 780 | .2793512 .1183474 2.36 0.018 .0473346 .5113677 781 | .2423313 .0579311 4.18 0.000 .1287591 .3559035 783 | .0246129 .0816038 0.30 0.763 -.1353689 .1845946 792 | .2001163 .058371 3.43 0.001 .0856817 .3145509 800 | .0751097 .1026684 0.73 0.464 -.1261686 .276388 803 | .2006384 .0582127 3.45 0.001 .0865142 .3147626 816 | .2058093 .0715488 2.88 0.004 .0655401 .3460786 820 | .0972962 .0968806 1.00 0.315 -.0926351 .2872276 825 | .1499924 .0581145 2.58 0.010 .0360607 .2639241 828 | .3183524 .0663448 4.80 0.000 .1882854 .4484195 830 | .2714865 .123515 2.20 0.028 .029339 .5136339 840 | .2897824 .0653262 4.44 0.000 .1617123 .4178524 847 | .1406452 .0600245 2.34 0.019 .022969 .2583214 850 | .3091407 .1937094 1.60 0.111 -.0706206 .688902 852 | .3350374 .0634987 5.28 0.000 .2105502 .4595245 858 | .1582583 .0604261 2.62 0.009 .0397947 .2767218 864 | .3458952 .0657406 5.26 0.000 .2170127 .4747777 870 | .0496647 .1212348 0.41 0.682 -.1880124 .2873418 876 | .3093225 .0669572 4.62 0.000 .1780549 .4405901 880 | .1103371 .0614934 1.79 0.073 -.0102188 .230893 900 | .2392429 .063221 3.78 0.000 .1152999 .3631858 902 | .1204948 .0630098 1.91 0.056 -.003034 .2440235 913 | .1512673 .063606 2.38 0.017 .0265696 .275965 924 | .2719516 .0629627 4.32 0.000 .1485151 .395388 935 | .1785435 .0649804 2.75 0.006 .0511514 .3059357 936 | .2324864 .0633571 3.67 0.000 .1082768 .3566961 957 | .2001202 .0668775 2.99 0.003 .069009 .3312315 960 | .2549316 .0665642 3.83 0.000 .1244345 .3854286 968 | .2437592 .0685375 3.56 0.000 .1093935 .378125 984 | .24743 .0682748 3.62 0.000 .1135793 .3812807 996 | .3289204 .0708963 4.64 0.000 .1899303 .4679104 1020 | .3364812 .069853 4.82 0.000 .1995365 .473426 1044 | .3476649 .0704221 4.94 0.000 .2096046 .4857253 1056 | .4229399 .0732641 5.77 0.000 .2793079 .5665718 | _cons | .3212618 .0994659 3.23 0.001 .1262619 .5162618 --------------+---------------------------------------------------------------- sigma_u | .38240507 sigma_e | .29083786 rho | .6335389 (fraction of variance due to u_i) ------------------------------------------------------------------------------- .
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