Hi all,
If I want to estimate the following regression in the attachment on Stata. How should I proceed? The coefficient associated with base year value added per worker (lnyit-1) instead of being the typical beta in a linear regression seems to follow an exponential distribution averaged by time period (T). In addition of estimating the regression, I would like to store the values of lambda in the coefficient.
I do apologize for attaching the equation from latex but I had a very hard time typing Greek letters in the forum. My apologies if I violated any rule
Thank you,
Hugo
If I want to estimate the following regression in the attachment on Stata. How should I proceed? The coefficient associated with base year value added per worker (lnyit-1) instead of being the typical beta in a linear regression seems to follow an exponential distribution averaged by time period (T). In addition of estimating the regression, I would like to store the values of lambda in the coefficient.
I do apologize for attaching the equation from latex but I had a very hard time typing Greek letters in the forum. My apologies if I violated any rule
Thank you,
Hugo
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input int(country year) str2 isic str3 isiccomb byte sourcecode long(Establishments Employment) double(Wages Output ValueAdded GrossFixed) 8 1988 "15" "15A" 3 . 28488 24784500 . 244666667 . 8 1989 "15" "15A" 3 . 33285 30767812 . 238593750 . 8 1990 "15" "15A" 3 . 34191 23603258 . 119101124 . 8 1988 "17" "17C" 3 . 61728 56789667 . 206666667 . 8 1989 "17" "17C" 3 . 65344 57339219 . 228125000 . 8 1990 "17" "17C" 3 . 73034 46971461 . 165056180 . 8 2015 "17" "17" 3 180 981 2487827 12673714 6424091 1471835 8 2016 "17" "17" 3 156 991 2483940 11053559 5398844 3079267 8 2017 "17" "17" 3 251 1449 4324097 18866499 8043661 4265323 8 2018 "17" "17" 3 220 1943 6658075 20270552 11732658 3342928 8 2015 "18" "18" 3 641 19550 44850538 129020866 78066323 14846257 8 2016 "18" "18" 3 732 23083 56807324 166284400 92327672 13371415 8 2017 "18" "18" 3 569 26203 70965575 200621327 121460957 24987406 8 2018 "18" "18" 3 670 27169 85073348 234125336 140356671 29669643 8 2015 "19" "19" 3 257 19203 46311372 159996364 80215989 27185890 8 2016 "19" "19" 3 301 21661 55504183 189140044 95804895 21274957 8 2017 "19" "19" 3 272 23206 67942905 216893367 114214945 23828715 8 2018 "19" "19" 3 240 25509 83712100 248543449 139532514 29623342 8 1988 "20" "20C" 3 . 31015 30028967 . 66333333 . 8 1989 "20" "20C" 3 . 32092 30099359 . 68281250 . 8 1990 "20" "20C" 3 . 32572 21315315 . 33595506 . 8 2015 "20" "20" 3 476 1167 2623992 24039043 6525976 3678136 8 2016 "20" "20" 3 433 1240 3292803 31106310 9290163 1225278 8 2017 "20" "20" 3 484 1568 4298908 35843829 14492024 8295550 8 2018 "20" "20" 3 461 1756 5898740 48810452 17186909 4120784 8 1988 "21" "21" 3 . 2346 2294383 . 9833333 . 8 1989 "21" "21" 3 . 2426 2237984 . 10781250 . 8 1990 "21" "21" 3 . 2486 1846899 . 6067416 . 8 2015 "21" "21" 3 96 2526 5782713 42169699 13001844 7126341 8 2016 "21" "21" 3 65 2526 6309605 45371109 15586727 2631275 8 2017 "21" "21" 3 69 2272 6045340 39277918 13140218 7212427 8 2018 "21" "21" 3 67 2447 7500752 52283022 16279411 8862000 8 1988 "22" "22" 3 . 2984 2464783 . 9000000 . 8 1989 "22" "22" 3 . 3105 2410250 . 6718750 . 8 1990 "22" "22" 3 . 3169 1952663 . 5393258 . 8 2015 "22" "22" 3 164 1198 5291698 59760883 30812508 3972631 8 2016 "22" "22" 3 202 1419 6334761 57656732 25808526 11936850 8 2017 "22" "22" 3 215 1376 6792611 51872376 25104954 8035264 8 2018 "22" "22" 3 224 1462 7991542 57913216 25697022 6880320 8 2015 "23" "23" 3 13 1365 9002280 19572405 3155203 340740 8 2016 "23" "23" 3 8 1258 6534636 10188586 2765475 308162 8 2017 "23" "23" 3 3 103 386230 9907641 2342569 361041 8 2018 "23" "23" 3 6 107 518571 9584295 2685455 9908401 8 1988 "24" "24B" 3 . 8388 9226800 . 64500000 . 8 1989 "24" "24B" 3 . 8507 8916391 . 69687500 . 8 1990 "24" "24B" 3 . 8808 6781169 . 38314607 . 8 2015 "24" "24" 3 102 1137 4167935 42901941 16830517 4048851 8 2016 "24" "24" 3 96 1055 4486779 40074914 13202570 18937914 8 2017 "24" "24" 3 86 1008 4903442 49118388 16280437 4114190 8 2018 "24" "24" 3 89 1028 5908000 52329323 17307292 7259987 8 2015 "25" "25" 3 120 989 2277320 38440507 8536388 5047710 8 2016 "25" "25" 3 128 1367 3239777 46658990 10967965 7389056 8 2017 "25" "25" 3 117 1589 4685139 46733837 12670025 9941226 8 2018 "25" "25" 3 117 1655 5528332 52338583 14362552 7991542 8 1988 "26" "26" 3 . 27748 30694567 . 32833333 . 8 1989 "26" "26" 3 . 28403 30363781 . 34843750 . 8 1990 "26" "26" 3 . 29254 22751090 . 25168539 . 8 2015 "26" "26" 3 724 4186 16713750 255765027 69937548 25418726 8 2016 "26" "26" 3 834 5171 19674964 258228726 71524151 13306745 8 2017 "26" "26" 3 809 5782 24114190 320705290 90268682 26675063 8 2018 "26" "26" 3 675 5573 26687862 357545123 94342796 32975530 8 1988 "27" "27" 3 . 8378 10036833 . 27166667 . 8 1989 "27" "27" 3 . 8849 10204000 . 28281250 . 8 1990 "27" "27" 3 . 9393 8181404 . 12808989 . 8 2015 "27" "27" 3 59 1150 6050801 168885540 31668868 5851806 8 2016 "27" "27" 3 65 1119 5416103 159142125 42049092 136254185 8 2017 "27" "27" 3 33 1083 5382032 299219144 63257767 19336692 8 2018 "27" "27" 3 23 1049 8000803 296761248 63376727 18057367 8 1988 "28" "28F" 3 . 56860 64251667 . 1.400e+08 . 8 1989 "28" "28F" 3 . 59148 62437969 . 1.450e+08 . 8 1990 "28" "28F" 3 . 59164 46666404 . 99887640 . 8 2015 "28" "28" 3 1019 4124 12167403 158182580 40843647 17546730 8 2016 "28" "28" 3 1396 5171 15783317 180872407 45904179 22199328 8 2017 "28" "28" 3 1541 5042 17682620 202006717 53618808 37481108 8 2018 "28" "28" 3 1182 5587 21826263 266971223 65497310 32308796 8 2015 "36" "36" 3 989 3924 9529321 76707562 23633007 4609888 8 2016 "36" "36" 3 968 4213 10886604 82114994 26797662 4514982 8 2017 "36" "36" 3 1043 4728 13249370 91057935 32107473 9235936 8 2018 "36" "36" 3 1028 5101 16251630 108436803 33420019 16427574 8 1988 "D" "D" 3 . 227935 230572167 . 8.010e+08 . 8 1989 "D" "D" 3 . 241159 234776766 . 830312500 . 8 1990 "D" "D" 3 . 252071 180069663 . 505393258 . 8 2015 "D" "D" 3 8431 73958 200267277 1543120257 508535664 168654484 8 2016 "D" "D" 3 9860 86437 241657772 1706377751 573558612 314203436 8 2017 "D" "D" 3 9346 92562 281905961 2022359362 698740554 286020151 8 2018 "D" "D" 3 8930 98872 346210653 2355321006 797228115 313142521 12 1967 "15" "15" 3 . 23520 46991529 448445026 146645980 . 12 1968 "15" "15" 3 . 23701 50232325 478017282 156368365 . 12 1969 "15" "15" 3 . 23595 53473120 509007385 166698399 . 12 1970 "15" "15" 3 . 24192 58131763 551745371 180674328 . 12 1971 "15" "15" 3 . 24245 60659874 595199565 200096160 . 12 1972 "15" "15" 3 . 26904 75884134 724247101 251533585 . 12 1973 "15" "15" 3 . 26285 91356582 916089484 320252770 . 12 1974 "15" "15" 3 . 27971 94002272 763738564 239909107 . 12 1975 "15" "15" 3 . 31880 113687925 910009804 286625236 . 12 1976 "15" "15" 3 . 35568 138814672 970982210 335989145 . 12 1977 "15" "15" 3 . 37405 161330852 1022485518 367033716 . 12 1978 "15" "15" 3 . 39238 240550695 1687132807 546660279 . 12 1979 "15" "15" 3 . 48082 314019247 2200729926 712901546 . 12 1980 "15" "15" 3 . 54570 370037395 2438598549 790108014 . end
Attached Files
Comment