From 34c22079d60015e570ce52342df00c796357e758 Mon Sep 17 00:00:00 2001 From: bahadirbusra <75804477+bahadirbusra@users.noreply.github.com> Date: Tue, 15 Dec 2020 17:26:31 +0300 Subject: [PATCH 1/9] Add files via upload --- ikt533-main/2020-fall/analysis/1920-29.txt | 248 +++++++++++++ ikt533-main/2020-fall/analysis/1930-39.txt | 248 +++++++++++++ ikt533-main/2020-fall/analysis/README.md | 3 + ikt533-main/2020-fall/analysis/TabloIII.txt | 325 ++++++++++++++++++ .../analysis/regresyon kodlar\304\261.txt" | 182 ++++++++++ .../2020-fall/analysis/\305\237ekil V.txt" | 17 + ikt533-main/2020-fall/data/clean/README.md | 3 + 7 files changed, 1026 insertions(+) create mode 100644 ikt533-main/2020-fall/analysis/1920-29.txt create mode 100644 ikt533-main/2020-fall/analysis/1930-39.txt create mode 100644 ikt533-main/2020-fall/analysis/README.md create mode 100644 ikt533-main/2020-fall/analysis/TabloIII.txt create mode 100644 "ikt533-main/2020-fall/analysis/regresyon kodlar\304\261.txt" create mode 100644 "ikt533-main/2020-fall/analysis/\305\237ekil V.txt" create mode 100644 ikt533-main/2020-fall/data/clean/README.md diff --git a/ikt533-main/2020-fall/analysis/1920-29.txt b/ikt533-main/2020-fall/analysis/1920-29.txt new file mode 100644 index 0000000..cdee69a --- /dev/null +++ b/ikt533-main/2020-fall/analysis/1920-29.txt @@ -0,0 +1,248 @@ +. use "C:\Users\kenan\Desktop\NEW7080 (1).dta" + +. rename v1 AGE + +. +. rename v2 AGEQ + +. +. rename v4 EDUC + +. +. rename v5 ENOCENT + +. +. rename v6 ESOCENT + +. +. rename v9 LWKLYWGE + +. +. rename v10 MARRIED + +. +. rename v11 MIDATL + +. +. rename v12 MT + +. +. rename v13 NEWENG + +. +. rename v16 CENSUS + +. +. rename v18 QOB + +. +. rename v19 RACE + +. +. rename v20 SMSA + +. +. rename v21 SOATL + +. +. rename v24 WNOCENT + +. +. rename v25 WSOCENT + +. +. rename v27 YOB + + +********** YOB dummies ********** +. replace YOB=YOB-1900 if YOB >=1900 +(247199 real changes made) + + +. foreach i of numlist 0/9 { +. gen YR`i'=0 +. replace YR`i'=1 if YOB==20+`i' | YOB==30+`i' | YOB==40+`i' +. } +(95545 real changes made) +(93948 real changes made) +(101493 real changes made) +(101445 real changes made) +(101851 real changes made) +(102153 real changes made) +(111229 real changes made) +(120407 real changes made) +(117529 real changes made) +(118034 real changes made) + + +********** QOB dummies *********** + +. foreach i of numlist 1/4 { +. gen QTR`i'=0 +. replace QTR`i'=1 if QOB==`i' +. } +(262019 real changes made) +(255733 real changes made) +(280749 real changes made) +(265133 real changes made) + +********** QOB*YOB dummies ******** + +. foreach j of numlist 1/3 { +. foreach i of numlist 0/9 { +. gen QTR`j'YR`i'=QTR`j'*YR`i' +. } +. } + +********** Select Particular Men Born ******** + +. gen COHORT=2029 + +. +. replace COHORT=3039 if YOB<=39 & YOB >=30 +(329509 real changes made) + +. +. replace COHORT=4049 if YOB<=49 & YOB >=40 +(486926 real changes made) + +. +. replace AGEQ=AGEQ-1900 if CENSUS==80 +(816435 real changes made) + +. +. gen AGEQSQ= AGEQ*AGEQ + +*********************************************** + +. keep if COHORT < 2030 +(816435 observations deleted) + +********** Start Regression ******** + +. +. ivregress 2sls LWKLYWGE (EDUC=QTR1) + +Instrumental variables (2SLS) regression Number of obs = 247199 + Wald chi2(1) = 10.69 + Prob > chi2 = 0.0011 + R-squared = 0.1689 + Root MSE = .59373 + +------------------------------------------------------------------------------ + LWKLYWGE | Coef. Std. Err. z P>|z| [95% Conf. Interval] +-------------+---------------------------------------------------------------- + EDUC | .0715133 .0218682 3.27 0.001 .0286525 .1143741 + _cons | 4.333248 .251341 17.24 0.000 3.840629 4.825867 +------------------------------------------------------------------------------ +Instrumented: EDUC +Instruments: QTR1 + +. +. ivregress 2sls LWKLYWGE YR0-YR8 RACE MARRIED SMSA NEWENG MIDATL ENOCENT WNOCENT SOATL ESOCEN +> T WSOCENT MT AGEQ AGEQSQ (EDUC = QTR1YR0-QTR1YR9 QTR2YR0-QTR2YR9 QTR3YR0-QTR3YR9 YR0-YR8) +note: QTR3YR7 dropped due to collinearity +note: QTR3YR9 dropped due to collinearity + +Instrumental variables (2SLS) regression Number of obs = 247199 + Wald chi2(23) =33602.65 + Prob > chi2 = 0.0000 + R-squared = 0.2065 + Root MSE = .58017 + +------------------------------------------------------------------------------ + LWKLYWGE | Coef. Std. Err. z P>|z| [95% Conf. Interval] +-------------+---------------------------------------------------------------- + EDUC | .1007151 .033412 3.01 0.003 .0352289 .1662014 + YR0 | -.0679547 .0667052 -1.02 0.308 -.1986944 .0627851 + YR1 | -.0669484 .0610922 -1.10 0.273 -.1866869 .05279 + YR2 | -.0659506 .0528911 -1.25 0.212 -.1696152 .0377141 + YR3 | -.0600541 .0470548 -1.28 0.202 -.1522798 .0321716 + YR4 | -.0525386 .0402208 -1.31 0.191 -.1313698 .0262927 + YR5 | -.0342587 .0322616 -1.06 0.288 -.0974903 .0289728 + YR6 | -.0247798 .0257555 -0.96 0.336 -.0752597 .0257001 + YR7 | -.009527 .0166432 -0.57 0.567 -.042147 .023093 + YR8 | .002424 .0095616 0.25 0.800 -.0163164 .0211643 + RACE | -.2270556 .0775561 -2.93 0.003 -.3790626 -.0750485 + MARRIED | .2803622 .0140991 19.89 0.000 .2527284 .307996 + SMSA | -.1163201 .0198307 -5.87 0.000 -.1551876 -.0774526 + NEWENG | -.0201888 .0149986 -1.35 0.178 -.0495854 .0092079 + MIDATL | .0008335 .0157854 0.05 0.958 -.0301053 .0317722 + ENOCENT | .0423372 .0250246 1.69 0.091 -.0067101 .0913844 + WNOCENT | -.1236594 .0201894 -6.12 0.000 -.1632299 -.0840888 + SOATL | -.069971 .0371848 -1.88 0.060 -.1428518 .0029098 + ESOCENT | -.1571906 .0555523 -2.83 0.005 -.2660712 -.04831 + WSOCENT | -.1165475 .0383975 -3.04 0.002 -.1918051 -.0412899 + MT | -.1220909 .0085495 -14.28 0.000 -.1388476 -.1053341 + AGEQ | .1170356 .066147 1.77 0.077 -.01261 .2466813 + AGEQSQ | -.0011772 .0007361 -1.60 0.110 -.0026199 .0002654 + _cons | .9994293 1.594642 0.63 0.531 -2.126012 4.12487 +------------------------------------------------------------------------------ +Instrumented: EDUC +Instruments: YR0 YR1 YR2 YR3 YR4 YR5 YR6 YR7 YR8 RACE MARRIED SMSA NEWENG + MIDATL ENOCENT WNOCENT SOATL ESOCENT WSOCENT MT AGEQ AGEQSQ + QTR1YR0 QTR1YR1 QTR1YR2 QTR1YR3 QTR1YR4 QTR1YR5 QTR1YR6 + QTR1YR7 QTR1YR8 QTR1YR9 QTR2YR0 QTR2YR1 QTR2YR2 QTR2YR3 + QTR2YR4 QTR2YR5 QTR2YR6 QTR2YR7 QTR2YR8 QTR2YR9 QTR3YR0 + QTR3YR1 QTR3YR2 QTR3YR3 QTR3YR4 QTR3YR5 QTR3YR6 QTR3YR8 + +. +. reg LWKLYWGE EDUC + + Source | SS df MS Number of obs = 247199 +-------------+------------------------------ F( 1,247197) =50948.11 + Model | 17917.6603 1 17917.6603 Prob > F = 0.0000 + Residual | 86935.3595247197 .351684525 R-squared = 0.1709 +-------------+------------------------------ Adj R-squared = 0.1709 + Total | 104853.02247198 .424166133 Root MSE = .59303 + +------------------------------------------------------------------------------ + LWKLYWGE | Coef. Std. Err. t P>|t| [95% Conf. Interval] +-------------+---------------------------------------------------------------- + EDUC | .0801112 .0003549 225.72 0.000 .0794156 .0808068 + _cons | 4.23443 .00425 996.33 0.000 4.2261 4.24276 +------------------------------------------------------------------------------ + +. +. reg LWKLYWGE EDUC RACE MARRIED SMSA NEWENG MIDATL ENOCENT WNOCENT SOATL ESOCENT WSOCENT MT +> YR0-YR8 AGEQ AGEQSQ + + Source | SS df MS Number of obs = 247199 +-------------+------------------------------ F( 23,247175) = 3203.50 + Model | 24078.2095 23 1046.87868 Prob > F = 0.0000 + Residual | 80774.8103247175 .326791991 R-squared = 0.2296 +-------------+------------------------------ Adj R-squared = 0.2296 + Total | 104853.02247198 .424166133 Root MSE = .57166 + +------------------------------------------------------------------------------ + LWKLYWGE | Coef. Std. Err. t P>|t| [95% Conf. Interval] +-------------+---------------------------------------------------------------- + EDUC | .0701242 .0003547 197.69 0.000 .0694289 .0708194 + RACE | -.2979528 .0043445 -68.58 0.000 -.3064679 -.2894376 + MARRIED | .2927938 .0037449 78.18 0.000 .2854539 .3001337 + SMSA | -.1343204 .0025648 -52.37 0.000 -.1393473 -.1292935 + NEWENG | -.0327575 .0059551 -5.50 0.000 -.0444293 -.0210856 + MIDATL | -.0131056 .0041123 -3.19 0.001 -.0211657 -.0050456 + ENOCENT | .019735 .0040477 4.88 0.000 .0118016 .0276683 + WNOCENT | -.1414505 .0054026 -26.18 0.000 -.1520395 -.1308615 + SOATL | -.1037686 .0044283 -23.43 0.000 -.112448 -.0950893 + ESOCENT | -.2077598 .0058935 -35.25 0.000 -.219311 -.1962087 + WSOCENT | -.1513879 .0050702 -29.86 0.000 -.1613254 -.1414505 + MT | -.1268288 .0067059 -18.91 0.000 -.1399723 -.1136853 + YR0 | -.0178908 .037649 -0.48 0.635 -.0916818 .0559002 + YR1 | -.0207608 .033957 -0.61 0.541 -.0873157 .0457941 + YR2 | -.027055 .0310488 -0.87 0.384 -.0879098 .0337997 + YR3 | -.0260209 .0284315 -0.92 0.360 -.0817458 .029704 + YR4 | -.0244832 .0256729 -0.95 0.340 -.0748014 .0258349 + YR5 | -.0134015 .0225105 -0.60 0.552 -.0575216 .0307185 + YR6 | -.0088009 .0186642 -0.47 0.637 -.0453823 .0277804 + YR7 | -.0016045 .0140087 -0.11 0.909 -.0290612 .0258521 + YR8 | .0055357 .0088062 0.63 0.530 -.0117241 .0227955 + AGEQ | .1162067 .0651707 1.78 0.075 -.0115261 .2439395 + AGEQSQ | -.0012505 .000721 -1.73 0.083 -.0026636 .0001626 + _cons | 1.534505 1.461947 1.05 0.294 -1.330872 4.399882 +------------------------------------------------------------------------------ + +. save "C:\Users\kenan\Desktop\1920-29.dta" +file C:\Users\kenan\Desktop\1920-29.dta saved + diff --git a/ikt533-main/2020-fall/analysis/1930-39.txt b/ikt533-main/2020-fall/analysis/1930-39.txt new file mode 100644 index 0000000..ca600b5 --- /dev/null +++ b/ikt533-main/2020-fall/analysis/1930-39.txt @@ -0,0 +1,248 @@ +. use "C:\Users\kenan\Desktop\NEW7080 (1).dta" + +. rename v1 AGE + +. +. rename v2 AGEQ + +. +. rename v4 EDUC + +. +. rename v5 ENOCENT + +. +. rename v6 ESOCENT + +. +. rename v9 LWKLYWGE + +. +. rename v10 MARRIED + +. +. rename v11 MIDATL + +. +. rename v12 MT + +. +. rename v13 NEWENG + +. +. rename v16 CENSUS + +. +. rename v18 QOB + +. +. rename v19 RACE + +. +. rename v20 SMSA + +. +. rename v21 SOATL + +. +. rename v24 WNOCENT + +. +. rename v25 WSOCENT + +. +. rename v27 YOB + + +********** YOB dummies ********** + +. replace YOB=YOB-1900 if YOB >=1900 +(247199 real changes made) + +. +. foreach i of numlist 0/9 { +. gen YR`i'=0 +. replace YR`i'=1 if YOB==20+`i' | YOB==30+`i' | YOB==40+`i' +. } +(95545 real changes made) +(93948 real changes made) +(101493 real changes made) +(101445 real changes made) +(101851 real changes made) +(102153 real changes made) +(111229 real changes made) +(120407 real changes made) +(117529 real changes made) +(118034 real changes made) + + +********** QOB dummies *********** +. foreach i of numlist 1/4 { +. gen QTR`i'=0 +. replace QTR`i'=1 if QOB==`i' +. } +(262019 real changes made) +(255733 real changes made) +(280749 real changes made) +(265133 real changes made) + +********** QOB*YOB dummies ******** + +. foreach j of numlist 1/3 { +. foreach i of numlist 0/9 { +. gen QTR`j'YR`i'=QTR`j'*YR`i' +. } +. } + + +********** Select Particular Men Born ******** + +. gen COHORT=2029 + +. +. replace COHORT=3039 if YOB<=39 & YOB >=30 +(329509 real changes made) + + +. replace COHORT=4049 if YOB<=49 & YOB >=40 +(486926 real changes made) + +. +. replace AGEQ=AGEQ-1900 if CENSUS==80 +(816435 real changes made) + +. +. gen AGEQSQ= AGEQ*AGEQ + +********************************* +. keep if COHORT>3000 & COHORT <3040 +(734125 observations deleted) + + +********** Start Regression ******** + +. ivregress 2sls LWKLYWGE (EDUC = QTR1) + +Instrumental variables (2SLS) regression Number of obs = 329509 + Wald chi2(1) = 18.14 + Prob > chi2 = 0.0000 + R-squared = 0.0946 + Root MSE = .64591 + +------------------------------------------------------------------------------ + LWKLYWGE | Coef. Std. Err. z P>|z| [95% Conf. Interval] +-------------+---------------------------------------------------------------- + EDUC | .101995 .0239489 4.26 0.000 .055056 .148934 + _cons | 4.597477 .3058276 15.03 0.000 3.998066 5.196888 +------------------------------------------------------------------------------ +Instrumented: EDUC +Instruments: QTR1 + +. +. ivregress 2sls LWKLYWGE YR0-YR8 RACE MARRIED SMSA NEWENG MIDATL ENOCENT WNOCENT SOATL ESOCEN +> T WSOCENT MT AGEQ AGEQSQ (EDUC = QTR1YR0-QTR1YR9 QTR2YR0-QTR2YR9 QTR3YR0-QTR3YR9 YR0-YR8) +note: QTR3YR7 dropped due to collinearity +note: QTR3YR9 dropped due to collinearity + +Instrumental variables (2SLS) regression Number of obs = 329509 + Wald chi2(23) =30391.57 + Prob > chi2 = 0.0000 + R-squared = 0.1648 + Root MSE = .62037 + +------------------------------------------------------------------------------ + LWKLYWGE | Coef. Std. Err. z P>|z| [95% Conf. Interval] +-------------+---------------------------------------------------------------- + EDUC | .0599538 .0289847 2.07 0.039 .0031449 .1167628 + YR0 | .0924769 .0479925 1.93 0.054 -.0015868 .1865406 + YR1 | .0877543 .04306 2.04 0.042 .0033581 .1721504 + YR2 | .0808838 .0373007 2.17 0.030 .0077757 .1539918 + YR3 | .077101 .0324569 2.38 0.018 .0134867 .1407153 + YR4 | .0687472 .0274257 2.51 0.012 .0149939 .1225005 + YR5 | .0522657 .0232105 2.25 0.024 .006774 .0977574 + YR6 | .0442982 .0184254 2.40 0.016 .0081852 .0804113 + YR7 | .0317478 .0134627 2.36 0.018 .0053614 .0581341 + YR8 | .0213825 .0083434 2.56 0.010 .0050298 .0377352 + RACE | -.2626229 .0458025 -5.73 0.000 -.3523942 -.1728516 + MARRIED | .2486184 .0072577 34.26 0.000 .2343937 .2628432 + SMSA | -.1797344 .0305301 -5.89 0.000 -.2395722 -.1198965 + NEWENG | -.1152549 .0176329 -6.54 0.000 -.1498148 -.080695 + MIDATL | -.0549901 .0201773 -2.73 0.006 -.0945368 -.0154434 + ENOCENT | .0124712 .0310095 0.40 0.688 -.0483063 .0732486 + WNOCENT | -.110213 .021887 -5.04 0.000 -.1531108 -.0673153 + SOATL | -.1429483 .0320871 -4.46 0.000 -.2058379 -.0800587 + ESOCENT | -.169947 .048758 -3.49 0.000 -.265511 -.074383 + WSOCENT | -.1063998 .027931 -3.81 0.000 -.1611436 -.051656 + MT | -.0928902 .0090208 -10.30 0.000 -.1105708 -.0752097 + AGEQ | -.074122 .0625828 -1.18 0.236 -.1967821 .0485381 + AGEQSQ | .0007428 .000712 1.04 0.297 -.0006528 .0021384 + _cons | 6.817046 1.361268 5.01 0.000 4.149009 9.485082 +------------------------------------------------------------------------------ +Instrumented: EDUC +Instruments: YR0 YR1 YR2 YR3 YR4 YR5 YR6 YR7 YR8 RACE MARRIED SMSA NEWENG + MIDATL ENOCENT WNOCENT SOATL ESOCENT WSOCENT MT AGEQ AGEQSQ + QTR1YR0 QTR1YR1 QTR1YR2 QTR1YR3 QTR1YR4 QTR1YR5 QTR1YR6 + QTR1YR7 QTR1YR8 QTR1YR9 QTR2YR0 QTR2YR1 QTR2YR2 QTR2YR3 + QTR2YR4 QTR2YR5 QTR2YR6 QTR2YR7 QTR2YR8 QTR2YR9 QTR3YR0 + QTR3YR1 QTR3YR2 QTR3YR3 QTR3YR4 QTR3YR5 QTR3YR6 QTR3YR8 + +. +. reg LWKLYWGE EDUC + + Source | SS df MS Number of obs = 329509 +-------------+------------------------------ F( 1,329507) =43782.56 + Model | 17808.8293 1 17808.8293 Prob > F = 0.0000 + Residual | 134029.041329507 .40675628 R-squared = 0.1173 +-------------+------------------------------ Adj R-squared = 0.1173 + Total | 151837.871329508 .460801773 Root MSE = .63777 + +------------------------------------------------------------------------------ + LWKLYWGE | Coef. Std. Err. t P>|t| [95% Conf. Interval] +-------------+---------------------------------------------------------------- + EDUC | .070851 .0003386 209.24 0.000 .0701874 .0715147 + _cons | 4.995182 .0044644 1118.88 0.000 4.986432 5.003932 +------------------------------------------------------------------------------ + +. +. reg LWKLYWGE EDUC RACE MARRIED SMSA NEWENG MIDATL ENOCENT WNOCENT SOATL ESOCENT WSOCENT MT +> YR0-YR8 AGEQ AGEQSQ + + Source | SS df MS Number of obs = 329509 +-------------+------------------------------ F( 23,329485) = 2831.65 + Model | 25059.716 23 1089.55287 Prob > F = 0.0000 + Residual | 126778.155329485 .384776711 R-squared = 0.1650 +-------------+------------------------------ Adj R-squared = 0.1650 + Total | 151837.871329508 .460801773 Root MSE = .6203 + +------------------------------------------------------------------------------ + LWKLYWGE | Coef. Std. Err. t P>|t| [95% Conf. Interval] +-------------+---------------------------------------------------------------- + EDUC | .0632378 .0003393 186.37 0.000 .0625728 .0639028 + RACE | -.2574534 .0040414 -63.70 0.000 -.2653745 -.2495323 + MARRIED | .2478785 .0031666 78.28 0.000 .2416721 .2540849 + SMSA | -.1762903 .0028655 -61.52 0.000 -.1819066 -.1706741 + NEWENG | -.1133571 .0055121 -20.57 0.000 -.1241606 -.1025536 + MIDATL | -.0527515 .0041003 -12.87 0.000 -.060788 -.0447151 + ENOCENT | .0159563 .0039398 4.05 0.000 .0082343 .0236782 + WNOCENT | -.1077988 .0050041 -21.54 0.000 -.1176066 -.0979909 + SOATL | -.1393424 .0041035 -33.96 0.000 -.1473852 -.1312996 + ESOCENT | -.1644554 .0053262 -30.88 0.000 -.1748945 -.1540163 + WSOCENT | -.1032796 .0046703 -22.11 0.000 -.1124333 -.0941258 + MT | -.0921064 .0057895 -15.91 0.000 -.1034536 -.0807593 + YR0 | .0888003 .0353575 2.51 0.012 .0195006 .1581001 + YR1 | .0844662 .0318107 2.66 0.008 .0221182 .1468142 + YR2 | .0782175 .0289405 2.70 0.007 .021495 .13494 + YR3 | .0749617 .0263998 2.84 0.005 .0232189 .1267045 + YR4 | .0671941 .0237537 2.83 0.005 .0206374 .1137507 + YR5 | .0510923 .0207714 2.46 0.014 .010381 .0918035 + YR6 | .0435516 .017206 2.53 0.011 .0098284 .0772748 + YR7 | .0313043 .0128806 2.43 0.015 .0060588 .0565499 + YR8 | .0211243 .0080257 2.63 0.008 .0053942 .0368545 + AGEQ | -.0759683 .060413 -1.26 0.209 -.194376 .0424394 + AGEQSQ | .0007702 .0006694 1.15 0.250 -.0005418 .0020822 + _cons | 6.80081 1.353582 5.02 0.000 4.147828 9.453792 +------------------------------------------------------------------------------ + +. save "C:\Users\kenan\Desktop\1930-39.dta" +file C:\Users\kenan\Desktop\1930-39.dta saved + diff --git a/ikt533-main/2020-fall/analysis/README.md b/ikt533-main/2020-fall/analysis/README.md new file mode 100644 index 0000000..a95755e --- /dev/null +++ b/ikt533-main/2020-fall/analysis/README.md @@ -0,0 +1,3 @@ +# `2020-fall/analysis` klasörü + +Bu klasörde analizlerin gerçekleÅŸtirildiÄŸi kodlar yer almalıdır. OluÅŸturulan her bir dosya için bu README.md dosyası güncellenmelidir. diff --git a/ikt533-main/2020-fall/analysis/TabloIII.txt b/ikt533-main/2020-fall/analysis/TabloIII.txt new file mode 100644 index 0000000..31e0d89 --- /dev/null +++ b/ikt533-main/2020-fall/analysis/TabloIII.txt @@ -0,0 +1,325 @@ +use "C:\Users\kenan\Desktop\NEW7080 (1).dta" + +rename v1 AGE +rename v2 AGEQ +rename v4 EDUC +rename v5 ENOCENT +rename v6 ESOCENT +rename v9 LWKLYWGE +rename v10 MARRIED +rename v11 MIDATL +rename v12 MT +rename v13 NEWENG +rename v16 CENSUS +rename v18 QOB +rename v19 RACE +rename v20 SMSA +rename v21 SOATL +rename v24 WNOCENT +rename v25 WSOCENT +rename v27 YOB + + +. ********** YOB dummies ********** + +. replace YOB=YOB-1900 if YOB >=1900 +(247199 real changes made) + +. +. foreach i of numlist 0/9 { +. gen YR`i'=0 +. replace YR`i'=1 if YOB==20+`i' | YOB==30+`i' | YOB==40+`i' +. } + +(95545 real changes made) +(93948 real changes made) +(101493 real changes made) +(101445 real changes made) +(101851 real changes made) +(102153 real changes made) +(111229 real changes made) +(120407 real changes made) +(117529 real changes made) +(118034 real changes made) + +. +********** QOB dummies *********** + +. foreach i of numlist 1/4 { + 2. +. gen QTR`i'=0 + 3. +. replace QTR`i'=1 if QOB==`i' + 4. +. } +(262019 real changes made) +(255733 real changes made) +(280749 real changes made) +(265133 real changes made) + + +********** QOB*YOB dummies ******** + +. foreach j of numlist 1/3 { + 2. +. foreach i of numlist 0/9 { + 3. +. gen QTR`j'YR`i'=QTR`j'*YR`i' + 4. +. } + 5. +. } + +. +. ********** Select Particular Men Born ******** + +. gen COHORT=2029 + +. +. replace COHORT=3039 if YOB<=39 & YOB >=30 +(329509 real changes made) + +. +. replace COHORT=4049 if YOB<=49 & YOB >=40 +(486926 real changes made) + +. +. replace AGEQ=AGEQ-1900 if CENSUS==80 +(816435 real changes made) + +. +. gen AGEQSQ= AGEQ*AGEQ + + +********** Panel A ******** + +. sum LWKLYWGE if QTR1==1 & COHORT==2029 + + Variable | Obs Mean Std. Dev. Min Max +-------------+-------------------------------------------------------- + LWKLYWGE | 62628 5.148471 .6548401 -.0198026 8.503235 + +. +. sum LWKLYWGE if QTR1!=1 & COHORT==2029 + + Variable | Obs Mean Std. Dev. Min Max +-------------+-------------------------------------------------------- + LWKLYWGE | 184571 5.15745 .6500542 -.0198026 8.947976 + +. +. sum EDUC if QTR1==1 & COHORT==2029 + + Variable | Obs Mean Std. Dev. Min Max +-------------+-------------------------------------------------------- + EDUC | 62628 11.3996 3.390094 0 18 + +. +. sum EDUC if QTR1!=1 & COHORT==2029 + + Variable | Obs Mean Std. Dev. Min Max +-------------+-------------------------------------------------------- + EDUC | 184571 11.52515 3.350032 0 18 + +. +. +. +. reg LWKLYWGE QTR1 if COHORT==2029 + + Source | SS df MS Number of obs = 247199 +-------------+------------------------------ F( 1,247197) = 8.89 + Model | 3.76989393 1 3.76989393 Prob > F = 0.0029 + Residual | 104849.25247197 .424152599 R-squared = 0.0000 +-------------+------------------------------ Adj R-squared = 0.0000 + Total | 104853.02247198 .424166133 Root MSE = .65127 + +------------------------------------------------------------------------------ + LWKLYWGE | Coef. Std. Err. t P>|t| [95% Conf. Interval] +-------------+---------------------------------------------------------------- + QTR1 | -.0089789 .0030117 -2.98 0.003 -.0148818 -.0030759 + _cons | 5.15745 .0015159 3402.17 0.000 5.154479 5.160421 +------------------------------------------------------------------------------ + +. +. reg EDUC QTR1 if COHORT==2029 + + Source | SS df MS Number of obs = 247199 +-------------+------------------------------ F( 1,247197) = 65.29 + Model | 737.149176 1 737.149176 Prob > F = 0.0000 + Residual | 2791131.65247197 11.2911227 R-squared = 0.0003 +-------------+------------------------------ Adj R-squared = 0.0003 + Total | 2791868.8247198 11.294059 Root MSE = 3.3602 + +------------------------------------------------------------------------------ + EDUC | Coef. Std. Err. t P>|t| [95% Conf. Interval] +-------------+---------------------------------------------------------------- + QTR1 | -.1255553 .0155391 -8.08 0.000 -.1560115 -.0950991 + _cons | 11.52515 .0078214 1473.53 0.000 11.50982 11.54048 +------------------------------------------------------------------------------ + +. +. sureg (eq1: LWKLYWGE QTR1 ) (eq2: EDUC QTR1 ) if COHORT==2029 + +Seemingly unrelated regression +---------------------------------------------------------------------- +Equation Obs Parms RMSE "R-sq" chi2 P +---------------------------------------------------------------------- +eq1 2.5e+05 1 .6512674 0.0000 8.89 0.0029 +eq2 2.5e+05 1 3.360213 0.0003 65.29 0.0000 +---------------------------------------------------------------------- + +------------------------------------------------------------------------------ + | Coef. Std. Err. z P>|z| [95% Conf. Interval] +-------------+---------------------------------------------------------------- +eq1 | + QTR1 | -.0089789 .0030117 -2.98 0.003 -.0148818 -.003076 + _cons | 5.15745 .0015159 3402.18 0.000 5.154479 5.160421 +-------------+---------------------------------------------------------------- +eq2 | + QTR1 | -.1255553 .015539 -8.08 0.000 -.1560113 -.0950993 + _cons | 11.52515 .0078214 1473.54 0.000 11.50982 11.54048 +------------------------------------------------------------------------------ + +. +. nlcom ratio: [eq1]_b[QTR1]/[eq2]_b[QTR1] + + ratio: [eq1]_b[QTR1]/[eq2]_b[QTR1] + +------------------------------------------------------------------------------ + | Coef. Std. Err. z P>|z| [95% Conf. Interval] +-------------+---------------------------------------------------------------- + ratio | .0715133 .0218682 3.27 0.001 .0286525 .1143741 +------------------------------------------------------------------------------ + +. +. reg LWKLYWGE EDUC if COHORT==2029 + + Source | SS df MS Number of obs = 247199 +-------------+------------------------------ F( 1,247197) =50948.11 + Model | 17917.6603 1 17917.6603 Prob > F = 0.0000 + Residual | 86935.3595247197 .351684525 R-squared = 0.1709 +-------------+------------------------------ Adj R-squared = 0.1709 + Total | 104853.02247198 .424166133 Root MSE = .59303 + +------------------------------------------------------------------------------ + LWKLYWGE | Coef. Std. Err. t P>|t| [95% Conf. Interval] +-------------+---------------------------------------------------------------- + EDUC | .0801112 .0003549 225.72 0.000 .0794156 .0808068 + _cons | 4.23443 .00425 996.33 0.000 4.2261 4.24276 +------------------------------------------------------------------------------ + +. + + +********** Panel B ******** + +. sum LWKLYWGE if QTR1==1 & COHORT==3039 + + Variable | Obs Mean Std. Dev. Min Max +-------------+-------------------------------------------------------- + LWKLYWGE | 81671 5.891596 .6809133 -2.341806 10.5321 + +. +. sum LWKLYWGE if QTR1!=1 & COHORT==3039 + + Variable | Obs Mean Std. Dev. Min Max +-------------+-------------------------------------------------------- + LWKLYWGE | 247838 5.902695 .6781127 -2.341806 10.5321 + +. +. sum EDUC if QTR1==1 & COHORT==3039 + + Variable | Obs Mean Std. Dev. Min Max +-------------+-------------------------------------------------------- + EDUC | 81671 12.68807 3.309801 0 20 + +. +. sum EDUC if QTR1!=1 & COHORT==3039 + + Variable | Obs Mean Std. Dev. Min Max +-------------+-------------------------------------------------------- + EDUC | 247838 12.79688 3.271337 0 20 + +. +. reg LWKLYWGE QTR1 if COHORT==3039 + + Source | SS df MS Number of obs = 329509 +-------------+------------------------------ F( 1,329507) = 16.42 + Model | 7.56705738 1 7.56705738 Prob > F = 0.0001 + Residual | 151830.304329507 .460780207 R-squared = 0.0000 +-------------+------------------------------ Adj R-squared = 0.0000 + Total | 151837.871329508 .460801773 Root MSE = .67881 + +------------------------------------------------------------------------------ + LWKLYWGE | Coef. Std. Err. t P>|t| [95% Conf. Interval] +-------------+---------------------------------------------------------------- + QTR1 | -.0110989 .0027388 -4.05 0.000 -.0164669 -.0057309 + _cons | 5.902695 .0013635 4329.00 0.000 5.900022 5.905367 +------------------------------------------------------------------------------ + +. +. reg EDUC QTR1 if COHORT==3039 + + Source | SS df MS Number of obs = 329509 +-------------+------------------------------ F( 1,329507) = 67.57 + Model | 727.393312 1 727.393312 Prob > F = 0.0000 + Residual | 3546940.27329507 10.7643852 R-squared = 0.0002 +-------------+------------------------------ Adj R-squared = 0.0002 + Total | 3547667.66329508 10.76656 Root MSE = 3.2809 + +------------------------------------------------------------------------------ + EDUC | Coef. Std. Err. t P>|t| [95% Conf. Interval] +-------------+---------------------------------------------------------------- + QTR1 | -.1088179 .0132376 -8.22 0.000 -.1347633 -.0828725 + _cons | 12.79688 .0065904 1941.75 0.000 12.78397 12.8098 +------------------------------------------------------------------------------ + +. +. sureg (eq1: LWKLYWGE QTR1 ) (eq2: EDUC QTR1 ) if COHORT==3039 + +Seemingly unrelated regression +---------------------------------------------------------------------- +Equation Obs Parms RMSE "R-sq" chi2 P +---------------------------------------------------------------------- +eq1 3.3e+05 1 .6788059 0.0000 16.42 0.0001 +eq2 3.3e+05 1 3.280902 0.0002 67.57 0.0000 +---------------------------------------------------------------------- + +------------------------------------------------------------------------------ + | Coef. Std. Err. z P>|z| [95% Conf. Interval] +-------------+---------------------------------------------------------------- +eq1 | + QTR1 | -.0110989 .0027388 -4.05 0.000 -.0164668 -.0057309 + _cons | 5.902695 .0013635 4329.01 0.000 5.900022 5.905367 +-------------+---------------------------------------------------------------- +eq2 | + QTR1 | -.1088179 .0132376 -8.22 0.000 -.1347631 -.0828727 + _cons | 12.79688 .0065904 1941.76 0.000 12.78397 12.8098 +------------------------------------------------------------------------------ + +. +. nlcom ratio: [eq1]_b[QTR1]/[eq2]_b[QTR1] + + ratio: [eq1]_b[QTR1]/[eq2]_b[QTR1] + +------------------------------------------------------------------------------ + | Coef. Std. Err. z P>|z| [95% Conf. Interval] +-------------+---------------------------------------------------------------- + ratio | .101995 .0239489 4.26 0.000 .055056 .148934 +------------------------------------------------------------------------------ + +. +. reg LWKLYWGE EDUC if COHORT==3039 + + Source | SS df MS Number of obs = 329509 +-------------+------------------------------ F( 1,329507) =43782.56 + Model | 17808.8293 1 17808.8293 Prob > F = 0.0000 + Residual | 134029.041329507 .40675628 R-squared = 0.1173 +-------------+------------------------------ Adj R-squared = 0.1173 + Total | 151837.871329508 .460801773 Root MSE = .63777 + +------------------------------------------------------------------------------ + LWKLYWGE | Coef. Std. Err. t P>|t| [95% Conf. Interval] +-------------+---------------------------------------------------------------- + EDUC | .070851 .0003386 209.24 0.000 .0701874 .0715147 + _cons | 4.995182 .0044644 1118.88 0.000 4.986432 5.003932 +------------------------------------------------------------------------------ diff --git "a/ikt533-main/2020-fall/analysis/regresyon kodlar\304\261.txt" "b/ikt533-main/2020-fall/analysis/regresyon kodlar\304\261.txt" new file mode 100644 index 0000000..f07f02f --- /dev/null +++ "b/ikt533-main/2020-fall/analysis/regresyon kodlar\304\261.txt" @@ -0,0 +1,182 @@ + +***********ÖDEVE AÝT BÜTÜN KODLAR******** + +use "C:\Users\kenan\Desktop\NEW7080 (1).dta" + +rename v1 AGE +rename v2 AGEQ +rename v4 EDUC +rename v5 ENOCENT +rename v6 ESOCENT +rename v9 LWKLYWGE +rename v10 MARRIED +rename v11 MIDATL +rename v12 MT +rename v13 NEWENG +rename v16 CENSUS +rename v18 QOB +rename v19 RACE +rename v20 SMSA +rename v21 SOATL +rename v24 WNOCENT +rename v25 WSOCENT +rename v27 YOB + +replace YOB=YOB-1900 if YOB >=1900 +foreach i of numlist 0/9 { +gen YR`i'=0 +replace YR`i'=1 if YOB==20+`i' | YOB==30+`i' | YOB==40+`i' +} + +foreach i of numlist 1/4 { +gen QTR`i'=0 +replace QTR`i'=1 if QOB==`i' +} + +foreach j of numlist 1/3 { +foreach i of numlist 0/9 { +gen QTR`j'YR`i'=QTR`j'*YR`i' +} +} + +gen COHORT=2029 +replace COHORT=3039 if YOB<=39 & YOB >=30 +replace COHORT=4049 if YOB<=49 & YOB >=40 +replace AGEQ=AGEQ-1900 if CENSUS==80 +gen AGEQSQ= AGEQ*AGEQ + +******1920-1929 dönemi***** + +keep if COHORT < 2030 +ivregress 2sls LWKLYWGE (EDUC=QTR1) +ivregress 2sls LWKLYWGE YR0-YR8 RACE MARRIED SMSA NEWENG MIDATL ENOCENT WNOCENT SOATL ESOCENT WSOCENT MT AGEQ AGEQSQ (EDUC = QTR1YR0-QTR1YR9 QTR2YR0-QTR2YR9 QTR3YR0-QTR3YR9 YR0-YR8) +reg LWKLYWGE EDUC +reg LWKLYWGE EDUC RACE MARRIED SMSA NEWENG MIDATL ENOCENT WNOCENT SOATL ESOCENT WSOCENT MT YR0-YR8 AGEQ AGEQSQ + +******1930-1939 dönemi***** + +keep if COHORT>3000 & COHORT <3040 +ivregress 2sls LWKLYWGE (EDUC = QTR1) +ivregress 2sls LWKLYWGE YR0-YR8 RACE MARRIED SMSA NEWENG MIDATL ENOCENT WNOCENT SOATL ESOCENT WSOCENT MT AGEQ AGEQSQ (EDUC = QTR1YR0-QTR1YR9 QTR2YR0-QTR2YR9 QTR3YR0-QTR3YR9 YR0-YR8) +reg LWKLYWGE EDUC +reg LWKLYWGE EDUC RACE MARRIED SMSA NEWENG MIDATL ENOCENT WNOCENT SOATL ESOCENT WSOCENT MT YR0-YR8 AGEQ AGEQSQ + + +**********Tablo III KODLARI******** +sum LWKLYWGE if QTR1==1 & COHORT==2029 +sum LWKLYWGE if QTR1!=1 & COHORT==2029 +sum EDUC if QTR1==1 & COHORT==2029 +sum EDUC if QTR1!=1 & COHORT==2029 + +reg LWKLYWGE QTR1 if COHORT==2029 +reg EDUC QTR1 if COHORT==2029 +sureg (eq1: LWKLYWGE QTR1 ) (eq2: EDUC QTR1 ) if COHORT==2029 +nlcom ratio: [eq1]_b[QTR1]/[eq2]_b[QTR1] +reg LWKLYWGE EDUC if COHORT==2029 +sum LWKLYWGE if QTR1==1 & COHORT==3039 +sum LWKLYWGE if QTR1!=1 & COHORT==3039 +sum EDUC if QTR1==1 & COHORT==3039 +sum EDUC if QTR1!=1 & COHORT==3039 +reg LWKLYWGE QTR1 if COHORT==3039 +reg EDUC QTR1 if COHORT==3039 +sureg (eq1: LWKLYWGE QTR1 ) (eq2: EDUC QTR1 ) if COHORT==3039 +nlcom ratio: [eq1]_b[QTR1]/[eq2]_b[QTR1] +reg LWKLYWGE EDUC if COHORT==3039 + + +*****Figure V- 1930-1939 dönemi için yatay eksende doðum çeyreklerinin ve yýllarýn, dikey eksende ise o çeyrekte doðanlarýn eðitim seviyelerinin ortalamalarýnýn +yer aldýðý çizgi grafiði. + +use "C:\Users\kenan\Desktop\ak91.dta" +tab qob, gen(q) +gen age = ((79 - yob)*4 + 5 - qob)/4 +gen age2 = age^2 +collapse s lnw q*, by(age) +gen yob = 80-age + +label var s "Years of education" +label var lnw "Log Weekly Earnings" +label var age "Age" +label var yob "Year of Birth" +twoway (line s yob) (scatter s yob if q4 == 1) (scatter s yob if q1 == 1) (scatter s yob if q2 == 1) (scatter s yob if q3 == 1, msym(Oh)) + +************************************** +************************************* + +***Zayýf araç deðiþkeni testleri*** + + +use "C:\Users\kenan\Desktop\ak91.dta" + +****Tablo 6.4.***************** + +tab qob, gen(q) +gen age = ((79 - yob)*4 + 5 - qob)/4 +gen age2 = age^2 +matrix T = J(6,3,.) + +reg lnw q4, robust +mat T[1,1] = _b[_cons] +mat T[1,2] = (_b[_cons] + _b[q4]) +mat T[1,3] = _b[q4] +mat T[2,3] = _se[q4] + +reg s q4, robust +mat T[3,1] = _b[_cons] +mat T[3,2] = (_b[_cons] + _b[q4]) +mat T[3,3] = _b[q4] +mat T[4,3] = _se[q4] + +ivregress 2sls lnw (s = q4), robust +mat T[5,3] = _b[s] +mat T[6,3] = _se[s] +matrix list T + +ssc install mat2txt +mat2txt, matrix(T) saving("C:\Users\kenan\Desktop\Tablo64.xlsx") title(Table 6.4) replace + +*****TABLO 6.5.******************************* + +sort q4 +by q4: sum lnw s +reg lnw q4, robust +reg s q4, robust + +****OLS(1)**** +reg lnw s, robust +outreg2 s using "C:\Users\kenan\Desktop\Table64.xls", replace bdec(3) sdec(3) noaster word +reg s q4 +testparm q4 +local F = r(F) + +***2SLS(2)**** +ivregress 2sls lnw (s = q4), robust +outreg2 s using "C:\Users\kenan\Desktop\Table64.xls", append bdec(3) sdec(3) noaster word addstat(F-stat, `F') + +****OLS(3)**** +reg lnw s i.yob, robust +outreg2 s using "C:\Users\kenan\Desktop\Table64.xls", append bdec(3) sdec(3) noaster word +reg s q4 i.yob +testparm q4 +local F = r(F) + +****2SLS(4)**** +ivregress 2sls lnw (s = q4) i.yob, robust +outreg2 s using "C:\Users\kenan\Desktop\Table64.xls", append bdec(3) sdec(3) noaster word addstat(F-stat, `F') +reg s q2 q3 q4 i.yob +testparm q2 q3 q4 +local F = r(F) + +****2SLS(5)***** +ivregress 2sls lnw (s = i.qob) i.yob, robust +outreg2 s using "C:\Users\kenan\Desktop\Table64.xls", append bdec(3) sdec(3) noaster word addstat(F-stat, `F') + + + + + + + + + + diff --git "a/ikt533-main/2020-fall/analysis/\305\237ekil V.txt" "b/ikt533-main/2020-fall/analysis/\305\237ekil V.txt" new file mode 100644 index 0000000..4f32061 --- /dev/null +++ "b/ikt533-main/2020-fall/analysis/\305\237ekil V.txt" @@ -0,0 +1,17 @@ + +*****Figure 1- 1930-1939 dönemi için yatay eksende doðum çeyreklerinin ve yýllarýn, dikey eksende ise o çeyrekte doðanlarýn eðitim seviyelerinin ortalamalarýnýn +yer aldýðý çizgi grafiði. + + +use "C:\Users\kenan\Desktop\ak91.dta" +tab qob, gen(q) +gen age = ((79 - yob)*4 + 5 - qob)/4 +gen age2 = age^2 +collapse s lnw q*, by(age) +gen yob = 80-age + +label var s "Years of education" +label var lnw "Log Weekly Earnings" +label var age "Age" +label var yob "Year of Birth" +twoway (line s yob) (scatter s yob if q4 == 1) (scatter s yob if q1 == 1) (scatter s yob if q2 == 1) (scatter s yob if q3 == 1, msym(Oh)) diff --git a/ikt533-main/2020-fall/data/clean/README.md b/ikt533-main/2020-fall/data/clean/README.md new file mode 100644 index 0000000..b396275 --- /dev/null +++ b/ikt533-main/2020-fall/data/clean/README.md @@ -0,0 +1,3 @@ +# `2020-fall/data/clean` klasörü + +Bu klasörde deÄŸiÅŸtirilmiÅŸ veri dosyaları ve bunlara iliÅŸkin kod dosyaları yer almalıdır. From 74b0e68a8cf21e909916b3b3dee212ea38d57bba Mon Sep 17 00:00:00 2001 From: bahadirbusra <75804477+bahadirbusra@users.noreply.github.com> Date: Thu, 17 Dec 2020 23:05:39 +0300 Subject: [PATCH 2/9] =?UTF-8?q?=C4=B0lk=C3=96dev?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Büsra bahadir --- 2020-fall/analysis/busrabahadir.do | 172 +++++++++++++++++++++++++++++ 1 file changed, 172 insertions(+) create mode 100644 2020-fall/analysis/busrabahadir.do diff --git a/2020-fall/analysis/busrabahadir.do b/2020-fall/analysis/busrabahadir.do new file mode 100644 index 0000000..86768e9 --- /dev/null +++ b/2020-fall/analysis/busrabahadir.do @@ -0,0 +1,172 @@ +use "C:\Users\kenan\Desktop\NEW7080 (1).dta" +rename v1 AGE +rename v2 AGEQ +rename v4 EDUC +rename v5 ENOCENT +rename v6 ESOCENT +rename v9 LWKLYWGE +rename v10 MARRIED +rename v11 MIDATL +rename v12 MT +rename v13 NEWENG +rename v16 CENSUS +rename v18 QOB +rename v19 RACE +rename v20 SMSA +rename v21 SOATL +rename v24 WNOCENT +rename v25 WSOCENT +rename v27 YOB +**********YOB dummies ********** +replace YOB=YOB-1900 if YOB >=1900 +foreach i of numlist 0/9 { +gen YR`i'=0 +replace YR`i'=1 if YOB==20+`i' | YOB==30+`i' | YOB==40+`i' +} +**********QOB dummies *********** +foreach i of numlist 1/4 { +gen QTR`i'=0 +replace QTR`i'=1 if QOB==`i' +} +********** QOB*YOB dummies ******** +foreach j of numlist 1/3 { +foreach i of numlist 0/9 { +gen QTR`j'YR`i'=QTR`j'*YR`i' +} +} +********** Select Particular Men Born ******** +gen COHORT=2029 +replace COHORT=3039 if YOB<=39 & YOB >=30 +replace COHORT=4049 if YOB<=49 & YOB >=40 +replace AGEQ=AGEQ-1900 if CENSUS==80 +gen AGEQSQ= AGEQ*AGEQ +******************* +**************Cevap a)********** +*********Tablo III KODLARI******** +********** Panel A******** +sum LWKLYWGE if QTR1==1 & COHORT==2029 +sum LWKLYWGE if QTR1!=1 & COHORT==2029 +sum EDUC if QTR1==1 & COHORT==2029 +sum EDUC if QTR1!=1 & COHORT==2029 + +reg LWKLYWGE QTR1 if COHORT==2029 +reg EDUC QTR1 if COHORT==2029 +sureg (eq1: LWKLYWGE QTR1 ) (eq2: EDUC QTR1 ) if COHORT==2029 +nlcom ratio: [eq1]_b[QTR1]/[eq2]_b[QTR1] +reg LWKLYWGE EDUC if COHORT==2029 +********** +********** Panel B*********** +sum LWKLYWGE if QTR1==1 & COHORT==3039 +sum LWKLYWGE if QTR1!=1 & COHORT==3039 +sum EDUC if QTR1==1 & COHORT==3039 +sum EDUC if QTR1!=1 & COHORT==3039 +reg LWKLYWGE QTR1 if COHORT==3039 +reg EDUC QTR1 if COHORT==3039 +sureg (eq1: LWKLYWGE QTR1 ) (eq2: EDUC QTR1 ) if COHORT==3039 +nlcom ratio: [eq1]_b[QTR1]/[eq2]_b[QTR1] +reg LWKLYWGE EDUC if COHORT==3039 + +********Cevap b)********* +******1920-1929 dönemi için******** +keep if COHORT < 2030 +ivregress 2sls LWKLYWGE (EDUC=QTR1) +ivregress 2sls LWKLYWGE YR0-YR8 RACE MARRIED SMSA NEWENG MIDATL ENOCENT WNOCENT SOATL ESOCENT WSOCENT MT AGEQ AGEQSQ (EDUC = QTR1YR0-QTR1YR9 QTR2YR0-QTR2YR9 QTR3YR0-QTR3YR9 YR0-YR8) +reg LWKLYWGE EDUC +reg LWKLYWGE EDUC RACE MARRIED SMSA NEWENG MIDATL ENOCENT WNOCENT SOATL ESOCENT WSOCENT MT YR0-YR8 AGEQ AGEQSQ + +******1930-1939 dönemi için******** + +keep if COHORT>3000 & COHORT <3040 +ivregress 2sls LWKLYWGE (EDUC = QTR1) +ivregress 2sls LWKLYWGE YR0-YR8 RACE MARRIED SMSA NEWENG MIDATL ENOCENT WNOCENT SOATL ESOCENT WSOCENT MT AGEQ AGEQSQ (EDUC = QTR1YR0-QTR1YR9 QTR2YR0-QTR2YR9 QTR3YR0-QTR3YR9 YR0-YR8) +reg LWKLYWGE EDUC +reg LWKLYWGE EDUC RACE MARRIED SMSA NEWENG MIDATL ENOCENT WNOCENT SOATL ESOCENT WSOCENT MT YR0-YR8 AGEQ AGEQSQ +******************************* +*********Cevap d********** +use "C:\Users\kenan\Desktop\NEW7080 (1).dta" +rename v4 EDUC +rename v5 ENOCENT +rename v6 ESOCENT +rename v9 LWKLYWGE +rename v10 MARRIED +rename v11 MIDATL +rename v12 MT +rename v13 NEWENG +rename v16 CENSUS +rename v18 QOB +rename v19 RACE +rename v20 SMSA +rename v21 SOATL +rename v24 WNOCENT +rename v25 WSOCENT +rename v27 YOB +********** YOB dummies ********** +replace YOB=YOB-1900 if YOB >=1900 +foreach i of numlist 0/9 { +gen YR`i'=0 +replace YR`i'=1 if YOB==20+`i' | YOB==30+`i' | YOB==40+`i' +} +********** QOB dummies *********** +foreach i of numlist 1/4 { +gen QTR`i'=0 +replace QTR`i'=1 if QOB==`i' +} +********** QOB*YOB dummies ******** +foreach j of numlist 1/3 { +foreach i of numlist 0/9 { +gen QTR`j'YR`i'=QTR`j'*YR`i' +} +} +********** Select Particular Men Born ******** +gen COHORT=2029 +replace COHORT=3039 if YOB<=39 & YOB >=30 +replace COHORT=4049 if YOB<=49 & YOB >=40 +*********** +keep if COHORT>3000 & COHORT <3040 +*********Sekil V************** +tab QOB, gen(Q) +gen AGE=((79-YOB)*4+5-QOB)/4 +gen AGE2=AGE^2 +collapse EDUC LWKLYWGE Q*, by(AGE) +gen YOB = 80-AGE +label var EDUC "Years of education" +label var LWKLYWGE "Log Weekly Earnings" +label var AGE "age" +label var YOB "Year of Birth" +twoway (line EDUC YOB) (scatter EDUC YOB if Q1 == 1) (scatter EDUC YOB if Q2 == 1) (scatter EDUC YOB if Q3 == 1) (scatter EDUC YOB if Q4 == 1, msym(Oh)) +********************* +***********Cevap c)ZAYIF ARAÇ DEGISKEN****** +sort Q1 +by Q1: sum LWKLYWGE EDUC +reg LWKLYWGE Q1, robust +reg EDUC Q1, robust +*****COLUMN 1******* +reg LWKLYWGE EDUC, robust +outreg2 EDUC using "C:\Users\kenan\Desktop\Table64.xls", replace bdec(3) sdec(3) noaster word +********************* +*****FIRST STAGE**** +reg EDUC Q1 +testparm Q1 +local F = r(F) +*******COLUMN 2***** +ivregress 2sls LWKLYWGE (EDUC= Q1), robust +outreg2 EDUC using "C:\Users\kenan\Desktop\Table5.xls", append bdec(3) sdec(3) noaster word addstat (F-stat, `F') +****COLUMN 3*****0 +reg LWKLYWGE EDUC i.YOB, robust +outreg2 EDUC using "C:\Users\kenan\Desktop\Table5.xls", append bdec(3) sdec(3) noaster word +********************** +******FIRST STAGE***** +reg EDUC Q1 i.YOB +testparm Q1 +local F = r(F) +********COLUMN 4******* +ivregress 2sls LWKLYWGE (EDUC = Q1) i.YOB, robust +outreg2 s using "C:\Users\kenan\Desktop\Table5.xls", append bdec(3) sdec(3) noaster word addstat(F-stat, `F') +************************** +*****FIRST STAGE***** +reg EDUC Q2 Q3 Q4 i.YOB +testparm Q2 Q3 Q4 +local F = r(F) +********COLUMN 5******* +ivregress 2sls LWKLYWGE (EDUC = i.QOB) i.YOB, robust +outreg2 s using "C:\Users\kenan\Desktop\Table5.xls", append bdec(3) sdec(3) noaster word addstat(F-stat, `F') From f85c10a987d75590c3d58391ed71dd985804ad52 Mon Sep 17 00:00:00 2001 From: bahadirbusra <75804477+bahadirbusra@users.noreply.github.com> Date: Thu, 17 Dec 2020 23:42:54 +0300 Subject: [PATCH 3/9] Delete 1920-29.txt --- ikt533-main/2020-fall/analysis/1920-29.txt | 248 --------------------- 1 file changed, 248 deletions(-) delete mode 100644 ikt533-main/2020-fall/analysis/1920-29.txt diff --git a/ikt533-main/2020-fall/analysis/1920-29.txt b/ikt533-main/2020-fall/analysis/1920-29.txt deleted file mode 100644 index cdee69a..0000000 --- a/ikt533-main/2020-fall/analysis/1920-29.txt +++ /dev/null @@ -1,248 +0,0 @@ -. use "C:\Users\kenan\Desktop\NEW7080 (1).dta" - -. rename v1 AGE - -. -. rename v2 AGEQ - -. -. rename v4 EDUC - -. -. rename v5 ENOCENT - -. -. rename v6 ESOCENT - -. -. rename v9 LWKLYWGE - -. -. rename v10 MARRIED - -. -. rename v11 MIDATL - -. -. rename v12 MT - -. -. rename v13 NEWENG - -. -. rename v16 CENSUS - -. -. rename v18 QOB - -. -. rename v19 RACE - -. -. rename v20 SMSA - -. -. rename v21 SOATL - -. -. rename v24 WNOCENT - -. -. rename v25 WSOCENT - -. -. rename v27 YOB - - -********** YOB dummies ********** -. replace YOB=YOB-1900 if YOB >=1900 -(247199 real changes made) - - -. foreach i of numlist 0/9 { -. gen YR`i'=0 -. replace YR`i'=1 if YOB==20+`i' | YOB==30+`i' | YOB==40+`i' -. } -(95545 real changes made) -(93948 real changes made) -(101493 real changes made) -(101445 real changes made) -(101851 real changes made) -(102153 real changes made) -(111229 real changes made) -(120407 real changes made) -(117529 real changes made) -(118034 real changes made) - - -********** QOB dummies *********** - -. foreach i of numlist 1/4 { -. gen QTR`i'=0 -. replace QTR`i'=1 if QOB==`i' -. } -(262019 real changes made) -(255733 real changes made) -(280749 real changes made) -(265133 real changes made) - -********** QOB*YOB dummies ******** - -. foreach j of numlist 1/3 { -. foreach i of numlist 0/9 { -. gen QTR`j'YR`i'=QTR`j'*YR`i' -. } -. } - -********** Select Particular Men Born ******** - -. gen COHORT=2029 - -. -. replace COHORT=3039 if YOB<=39 & YOB >=30 -(329509 real changes made) - -. -. replace COHORT=4049 if YOB<=49 & YOB >=40 -(486926 real changes made) - -. -. replace AGEQ=AGEQ-1900 if CENSUS==80 -(816435 real changes made) - -. -. gen AGEQSQ= AGEQ*AGEQ - -*********************************************** - -. keep if COHORT < 2030 -(816435 observations deleted) - -********** Start Regression ******** - -. -. ivregress 2sls LWKLYWGE (EDUC=QTR1) - -Instrumental variables (2SLS) regression Number of obs = 247199 - Wald chi2(1) = 10.69 - Prob > chi2 = 0.0011 - R-squared = 0.1689 - Root MSE = .59373 - ------------------------------------------------------------------------------- - LWKLYWGE | Coef. Std. Err. z P>|z| [95% Conf. Interval] --------------+---------------------------------------------------------------- - EDUC | .0715133 .0218682 3.27 0.001 .0286525 .1143741 - _cons | 4.333248 .251341 17.24 0.000 3.840629 4.825867 ------------------------------------------------------------------------------- -Instrumented: EDUC -Instruments: QTR1 - -. -. ivregress 2sls LWKLYWGE YR0-YR8 RACE MARRIED SMSA NEWENG MIDATL ENOCENT WNOCENT SOATL ESOCEN -> T WSOCENT MT AGEQ AGEQSQ (EDUC = QTR1YR0-QTR1YR9 QTR2YR0-QTR2YR9 QTR3YR0-QTR3YR9 YR0-YR8) -note: QTR3YR7 dropped due to collinearity -note: QTR3YR9 dropped due to collinearity - -Instrumental variables (2SLS) regression Number of obs = 247199 - Wald chi2(23) =33602.65 - Prob > chi2 = 0.0000 - R-squared = 0.2065 - Root MSE = .58017 - ------------------------------------------------------------------------------- - LWKLYWGE | Coef. Std. Err. z P>|z| [95% Conf. Interval] --------------+---------------------------------------------------------------- - EDUC | .1007151 .033412 3.01 0.003 .0352289 .1662014 - YR0 | -.0679547 .0667052 -1.02 0.308 -.1986944 .0627851 - YR1 | -.0669484 .0610922 -1.10 0.273 -.1866869 .05279 - YR2 | -.0659506 .0528911 -1.25 0.212 -.1696152 .0377141 - YR3 | -.0600541 .0470548 -1.28 0.202 -.1522798 .0321716 - YR4 | -.0525386 .0402208 -1.31 0.191 -.1313698 .0262927 - YR5 | -.0342587 .0322616 -1.06 0.288 -.0974903 .0289728 - YR6 | -.0247798 .0257555 -0.96 0.336 -.0752597 .0257001 - YR7 | -.009527 .0166432 -0.57 0.567 -.042147 .023093 - YR8 | .002424 .0095616 0.25 0.800 -.0163164 .0211643 - RACE | -.2270556 .0775561 -2.93 0.003 -.3790626 -.0750485 - MARRIED | .2803622 .0140991 19.89 0.000 .2527284 .307996 - SMSA | -.1163201 .0198307 -5.87 0.000 -.1551876 -.0774526 - NEWENG | -.0201888 .0149986 -1.35 0.178 -.0495854 .0092079 - MIDATL | .0008335 .0157854 0.05 0.958 -.0301053 .0317722 - ENOCENT | .0423372 .0250246 1.69 0.091 -.0067101 .0913844 - WNOCENT | -.1236594 .0201894 -6.12 0.000 -.1632299 -.0840888 - SOATL | -.069971 .0371848 -1.88 0.060 -.1428518 .0029098 - ESOCENT | -.1571906 .0555523 -2.83 0.005 -.2660712 -.04831 - WSOCENT | -.1165475 .0383975 -3.04 0.002 -.1918051 -.0412899 - MT | -.1220909 .0085495 -14.28 0.000 -.1388476 -.1053341 - AGEQ | .1170356 .066147 1.77 0.077 -.01261 .2466813 - AGEQSQ | -.0011772 .0007361 -1.60 0.110 -.0026199 .0002654 - _cons | .9994293 1.594642 0.63 0.531 -2.126012 4.12487 ------------------------------------------------------------------------------- -Instrumented: EDUC -Instruments: YR0 YR1 YR2 YR3 YR4 YR5 YR6 YR7 YR8 RACE MARRIED SMSA NEWENG - MIDATL ENOCENT WNOCENT SOATL ESOCENT WSOCENT MT AGEQ AGEQSQ - QTR1YR0 QTR1YR1 QTR1YR2 QTR1YR3 QTR1YR4 QTR1YR5 QTR1YR6 - QTR1YR7 QTR1YR8 QTR1YR9 QTR2YR0 QTR2YR1 QTR2YR2 QTR2YR3 - QTR2YR4 QTR2YR5 QTR2YR6 QTR2YR7 QTR2YR8 QTR2YR9 QTR3YR0 - QTR3YR1 QTR3YR2 QTR3YR3 QTR3YR4 QTR3YR5 QTR3YR6 QTR3YR8 - -. -. reg LWKLYWGE EDUC - - Source | SS df MS Number of obs = 247199 --------------+------------------------------ F( 1,247197) =50948.11 - Model | 17917.6603 1 17917.6603 Prob > F = 0.0000 - Residual | 86935.3595247197 .351684525 R-squared = 0.1709 --------------+------------------------------ Adj R-squared = 0.1709 - Total | 104853.02247198 .424166133 Root MSE = .59303 - ------------------------------------------------------------------------------- - LWKLYWGE | Coef. Std. Err. t P>|t| [95% Conf. Interval] --------------+---------------------------------------------------------------- - EDUC | .0801112 .0003549 225.72 0.000 .0794156 .0808068 - _cons | 4.23443 .00425 996.33 0.000 4.2261 4.24276 ------------------------------------------------------------------------------- - -. -. reg LWKLYWGE EDUC RACE MARRIED SMSA NEWENG MIDATL ENOCENT WNOCENT SOATL ESOCENT WSOCENT MT -> YR0-YR8 AGEQ AGEQSQ - - Source | SS df MS Number of obs = 247199 --------------+------------------------------ F( 23,247175) = 3203.50 - Model | 24078.2095 23 1046.87868 Prob > F = 0.0000 - Residual | 80774.8103247175 .326791991 R-squared = 0.2296 --------------+------------------------------ Adj R-squared = 0.2296 - Total | 104853.02247198 .424166133 Root MSE = .57166 - ------------------------------------------------------------------------------- - LWKLYWGE | Coef. Std. Err. t P>|t| [95% Conf. Interval] --------------+---------------------------------------------------------------- - EDUC | .0701242 .0003547 197.69 0.000 .0694289 .0708194 - RACE | -.2979528 .0043445 -68.58 0.000 -.3064679 -.2894376 - MARRIED | .2927938 .0037449 78.18 0.000 .2854539 .3001337 - SMSA | -.1343204 .0025648 -52.37 0.000 -.1393473 -.1292935 - NEWENG | -.0327575 .0059551 -5.50 0.000 -.0444293 -.0210856 - MIDATL | -.0131056 .0041123 -3.19 0.001 -.0211657 -.0050456 - ENOCENT | .019735 .0040477 4.88 0.000 .0118016 .0276683 - WNOCENT | -.1414505 .0054026 -26.18 0.000 -.1520395 -.1308615 - SOATL | -.1037686 .0044283 -23.43 0.000 -.112448 -.0950893 - ESOCENT | -.2077598 .0058935 -35.25 0.000 -.219311 -.1962087 - WSOCENT | -.1513879 .0050702 -29.86 0.000 -.1613254 -.1414505 - MT | -.1268288 .0067059 -18.91 0.000 -.1399723 -.1136853 - YR0 | -.0178908 .037649 -0.48 0.635 -.0916818 .0559002 - YR1 | -.0207608 .033957 -0.61 0.541 -.0873157 .0457941 - YR2 | -.027055 .0310488 -0.87 0.384 -.0879098 .0337997 - YR3 | -.0260209 .0284315 -0.92 0.360 -.0817458 .029704 - YR4 | -.0244832 .0256729 -0.95 0.340 -.0748014 .0258349 - YR5 | -.0134015 .0225105 -0.60 0.552 -.0575216 .0307185 - YR6 | -.0088009 .0186642 -0.47 0.637 -.0453823 .0277804 - YR7 | -.0016045 .0140087 -0.11 0.909 -.0290612 .0258521 - YR8 | .0055357 .0088062 0.63 0.530 -.0117241 .0227955 - AGEQ | .1162067 .0651707 1.78 0.075 -.0115261 .2439395 - AGEQSQ | -.0012505 .000721 -1.73 0.083 -.0026636 .0001626 - _cons | 1.534505 1.461947 1.05 0.294 -1.330872 4.399882 ------------------------------------------------------------------------------- - -. save "C:\Users\kenan\Desktop\1920-29.dta" -file C:\Users\kenan\Desktop\1920-29.dta saved - From 039f9e00037f3abec6ec029f19ffe066b4055a7e Mon Sep 17 00:00:00 2001 From: bahadirbusra <75804477+bahadirbusra@users.noreply.github.com> Date: Thu, 17 Dec 2020 23:44:38 +0300 Subject: [PATCH 4/9] Delete 1930-39.txt --- ikt533-main/2020-fall/analysis/1930-39.txt | 248 --------------------- 1 file changed, 248 deletions(-) delete mode 100644 ikt533-main/2020-fall/analysis/1930-39.txt diff --git a/ikt533-main/2020-fall/analysis/1930-39.txt b/ikt533-main/2020-fall/analysis/1930-39.txt deleted file mode 100644 index ca600b5..0000000 --- a/ikt533-main/2020-fall/analysis/1930-39.txt +++ /dev/null @@ -1,248 +0,0 @@ -. use "C:\Users\kenan\Desktop\NEW7080 (1).dta" - -. rename v1 AGE - -. -. rename v2 AGEQ - -. -. rename v4 EDUC - -. -. rename v5 ENOCENT - -. -. rename v6 ESOCENT - -. -. rename v9 LWKLYWGE - -. -. rename v10 MARRIED - -. -. rename v11 MIDATL - -. -. rename v12 MT - -. -. rename v13 NEWENG - -. -. rename v16 CENSUS - -. -. rename v18 QOB - -. -. rename v19 RACE - -. -. rename v20 SMSA - -. -. rename v21 SOATL - -. -. rename v24 WNOCENT - -. -. rename v25 WSOCENT - -. -. rename v27 YOB - - -********** YOB dummies ********** - -. replace YOB=YOB-1900 if YOB >=1900 -(247199 real changes made) - -. -. foreach i of numlist 0/9 { -. gen YR`i'=0 -. replace YR`i'=1 if YOB==20+`i' | YOB==30+`i' | YOB==40+`i' -. } -(95545 real changes made) -(93948 real changes made) -(101493 real changes made) -(101445 real changes made) -(101851 real changes made) -(102153 real changes made) -(111229 real changes made) -(120407 real changes made) -(117529 real changes made) -(118034 real changes made) - - -********** QOB dummies *********** -. foreach i of numlist 1/4 { -. gen QTR`i'=0 -. replace QTR`i'=1 if QOB==`i' -. } -(262019 real changes made) -(255733 real changes made) -(280749 real changes made) -(265133 real changes made) - -********** QOB*YOB dummies ******** - -. foreach j of numlist 1/3 { -. foreach i of numlist 0/9 { -. gen QTR`j'YR`i'=QTR`j'*YR`i' -. } -. } - - -********** Select Particular Men Born ******** - -. gen COHORT=2029 - -. -. replace COHORT=3039 if YOB<=39 & YOB >=30 -(329509 real changes made) - - -. replace COHORT=4049 if YOB<=49 & YOB >=40 -(486926 real changes made) - -. -. replace AGEQ=AGEQ-1900 if CENSUS==80 -(816435 real changes made) - -. -. gen AGEQSQ= AGEQ*AGEQ - -********************************* -. keep if COHORT>3000 & COHORT <3040 -(734125 observations deleted) - - -********** Start Regression ******** - -. ivregress 2sls LWKLYWGE (EDUC = QTR1) - -Instrumental variables (2SLS) regression Number of obs = 329509 - Wald chi2(1) = 18.14 - Prob > chi2 = 0.0000 - R-squared = 0.0946 - Root MSE = .64591 - ------------------------------------------------------------------------------- - LWKLYWGE | Coef. Std. Err. z P>|z| [95% Conf. Interval] --------------+---------------------------------------------------------------- - EDUC | .101995 .0239489 4.26 0.000 .055056 .148934 - _cons | 4.597477 .3058276 15.03 0.000 3.998066 5.196888 ------------------------------------------------------------------------------- -Instrumented: EDUC -Instruments: QTR1 - -. -. ivregress 2sls LWKLYWGE YR0-YR8 RACE MARRIED SMSA NEWENG MIDATL ENOCENT WNOCENT SOATL ESOCEN -> T WSOCENT MT AGEQ AGEQSQ (EDUC = QTR1YR0-QTR1YR9 QTR2YR0-QTR2YR9 QTR3YR0-QTR3YR9 YR0-YR8) -note: QTR3YR7 dropped due to collinearity -note: QTR3YR9 dropped due to collinearity - -Instrumental variables (2SLS) regression Number of obs = 329509 - Wald chi2(23) =30391.57 - Prob > chi2 = 0.0000 - R-squared = 0.1648 - Root MSE = .62037 - ------------------------------------------------------------------------------- - LWKLYWGE | Coef. Std. Err. z P>|z| [95% Conf. Interval] --------------+---------------------------------------------------------------- - EDUC | .0599538 .0289847 2.07 0.039 .0031449 .1167628 - YR0 | .0924769 .0479925 1.93 0.054 -.0015868 .1865406 - YR1 | .0877543 .04306 2.04 0.042 .0033581 .1721504 - YR2 | .0808838 .0373007 2.17 0.030 .0077757 .1539918 - YR3 | .077101 .0324569 2.38 0.018 .0134867 .1407153 - YR4 | .0687472 .0274257 2.51 0.012 .0149939 .1225005 - YR5 | .0522657 .0232105 2.25 0.024 .006774 .0977574 - YR6 | .0442982 .0184254 2.40 0.016 .0081852 .0804113 - YR7 | .0317478 .0134627 2.36 0.018 .0053614 .0581341 - YR8 | .0213825 .0083434 2.56 0.010 .0050298 .0377352 - RACE | -.2626229 .0458025 -5.73 0.000 -.3523942 -.1728516 - MARRIED | .2486184 .0072577 34.26 0.000 .2343937 .2628432 - SMSA | -.1797344 .0305301 -5.89 0.000 -.2395722 -.1198965 - NEWENG | -.1152549 .0176329 -6.54 0.000 -.1498148 -.080695 - MIDATL | -.0549901 .0201773 -2.73 0.006 -.0945368 -.0154434 - ENOCENT | .0124712 .0310095 0.40 0.688 -.0483063 .0732486 - WNOCENT | -.110213 .021887 -5.04 0.000 -.1531108 -.0673153 - SOATL | -.1429483 .0320871 -4.46 0.000 -.2058379 -.0800587 - ESOCENT | -.169947 .048758 -3.49 0.000 -.265511 -.074383 - WSOCENT | -.1063998 .027931 -3.81 0.000 -.1611436 -.051656 - MT | -.0928902 .0090208 -10.30 0.000 -.1105708 -.0752097 - AGEQ | -.074122 .0625828 -1.18 0.236 -.1967821 .0485381 - AGEQSQ | .0007428 .000712 1.04 0.297 -.0006528 .0021384 - _cons | 6.817046 1.361268 5.01 0.000 4.149009 9.485082 ------------------------------------------------------------------------------- -Instrumented: EDUC -Instruments: YR0 YR1 YR2 YR3 YR4 YR5 YR6 YR7 YR8 RACE MARRIED SMSA NEWENG - MIDATL ENOCENT WNOCENT SOATL ESOCENT WSOCENT MT AGEQ AGEQSQ - QTR1YR0 QTR1YR1 QTR1YR2 QTR1YR3 QTR1YR4 QTR1YR5 QTR1YR6 - QTR1YR7 QTR1YR8 QTR1YR9 QTR2YR0 QTR2YR1 QTR2YR2 QTR2YR3 - QTR2YR4 QTR2YR5 QTR2YR6 QTR2YR7 QTR2YR8 QTR2YR9 QTR3YR0 - QTR3YR1 QTR3YR2 QTR3YR3 QTR3YR4 QTR3YR5 QTR3YR6 QTR3YR8 - -. -. reg LWKLYWGE EDUC - - Source | SS df MS Number of obs = 329509 --------------+------------------------------ F( 1,329507) =43782.56 - Model | 17808.8293 1 17808.8293 Prob > F = 0.0000 - Residual | 134029.041329507 .40675628 R-squared = 0.1173 --------------+------------------------------ Adj R-squared = 0.1173 - Total | 151837.871329508 .460801773 Root MSE = .63777 - ------------------------------------------------------------------------------- - LWKLYWGE | Coef. Std. Err. t P>|t| [95% Conf. Interval] --------------+---------------------------------------------------------------- - EDUC | .070851 .0003386 209.24 0.000 .0701874 .0715147 - _cons | 4.995182 .0044644 1118.88 0.000 4.986432 5.003932 ------------------------------------------------------------------------------- - -. -. reg LWKLYWGE EDUC RACE MARRIED SMSA NEWENG MIDATL ENOCENT WNOCENT SOATL ESOCENT WSOCENT MT -> YR0-YR8 AGEQ AGEQSQ - - Source | SS df MS Number of obs = 329509 --------------+------------------------------ F( 23,329485) = 2831.65 - Model | 25059.716 23 1089.55287 Prob > F = 0.0000 - Residual | 126778.155329485 .384776711 R-squared = 0.1650 --------------+------------------------------ Adj R-squared = 0.1650 - Total | 151837.871329508 .460801773 Root MSE = .6203 - ------------------------------------------------------------------------------- - LWKLYWGE | Coef. Std. Err. t P>|t| [95% Conf. Interval] --------------+---------------------------------------------------------------- - EDUC | .0632378 .0003393 186.37 0.000 .0625728 .0639028 - RACE | -.2574534 .0040414 -63.70 0.000 -.2653745 -.2495323 - MARRIED | .2478785 .0031666 78.28 0.000 .2416721 .2540849 - SMSA | -.1762903 .0028655 -61.52 0.000 -.1819066 -.1706741 - NEWENG | -.1133571 .0055121 -20.57 0.000 -.1241606 -.1025536 - MIDATL | -.0527515 .0041003 -12.87 0.000 -.060788 -.0447151 - ENOCENT | .0159563 .0039398 4.05 0.000 .0082343 .0236782 - WNOCENT | -.1077988 .0050041 -21.54 0.000 -.1176066 -.0979909 - SOATL | -.1393424 .0041035 -33.96 0.000 -.1473852 -.1312996 - ESOCENT | -.1644554 .0053262 -30.88 0.000 -.1748945 -.1540163 - WSOCENT | -.1032796 .0046703 -22.11 0.000 -.1124333 -.0941258 - MT | -.0921064 .0057895 -15.91 0.000 -.1034536 -.0807593 - YR0 | .0888003 .0353575 2.51 0.012 .0195006 .1581001 - YR1 | .0844662 .0318107 2.66 0.008 .0221182 .1468142 - YR2 | .0782175 .0289405 2.70 0.007 .021495 .13494 - YR3 | .0749617 .0263998 2.84 0.005 .0232189 .1267045 - YR4 | .0671941 .0237537 2.83 0.005 .0206374 .1137507 - YR5 | .0510923 .0207714 2.46 0.014 .010381 .0918035 - YR6 | .0435516 .017206 2.53 0.011 .0098284 .0772748 - YR7 | .0313043 .0128806 2.43 0.015 .0060588 .0565499 - YR8 | .0211243 .0080257 2.63 0.008 .0053942 .0368545 - AGEQ | -.0759683 .060413 -1.26 0.209 -.194376 .0424394 - AGEQSQ | .0007702 .0006694 1.15 0.250 -.0005418 .0020822 - _cons | 6.80081 1.353582 5.02 0.000 4.147828 9.453792 ------------------------------------------------------------------------------- - -. save "C:\Users\kenan\Desktop\1930-39.dta" -file C:\Users\kenan\Desktop\1930-39.dta saved - From f8e6be1c2cd8ca93a090bc7c10137c3c59d12b2c Mon Sep 17 00:00:00 2001 From: bahadirbusra <75804477+bahadirbusra@users.noreply.github.com> Date: Thu, 17 Dec 2020 23:45:09 +0300 Subject: [PATCH 5/9] Delete TabloIII.txt --- ikt533-main/2020-fall/analysis/TabloIII.txt | 325 -------------------- 1 file changed, 325 deletions(-) delete mode 100644 ikt533-main/2020-fall/analysis/TabloIII.txt diff --git a/ikt533-main/2020-fall/analysis/TabloIII.txt b/ikt533-main/2020-fall/analysis/TabloIII.txt deleted file mode 100644 index 31e0d89..0000000 --- a/ikt533-main/2020-fall/analysis/TabloIII.txt +++ /dev/null @@ -1,325 +0,0 @@ -use "C:\Users\kenan\Desktop\NEW7080 (1).dta" - -rename v1 AGE -rename v2 AGEQ -rename v4 EDUC -rename v5 ENOCENT -rename v6 ESOCENT -rename v9 LWKLYWGE -rename v10 MARRIED -rename v11 MIDATL -rename v12 MT -rename v13 NEWENG -rename v16 CENSUS -rename v18 QOB -rename v19 RACE -rename v20 SMSA -rename v21 SOATL -rename v24 WNOCENT -rename v25 WSOCENT -rename v27 YOB - - -. ********** YOB dummies ********** - -. replace YOB=YOB-1900 if YOB >=1900 -(247199 real changes made) - -. -. foreach i of numlist 0/9 { -. gen YR`i'=0 -. replace YR`i'=1 if YOB==20+`i' | YOB==30+`i' | YOB==40+`i' -. } - -(95545 real changes made) -(93948 real changes made) -(101493 real changes made) -(101445 real changes made) -(101851 real changes made) -(102153 real changes made) -(111229 real changes made) -(120407 real changes made) -(117529 real changes made) -(118034 real changes made) - -. -********** QOB dummies *********** - -. foreach i of numlist 1/4 { - 2. -. gen QTR`i'=0 - 3. -. replace QTR`i'=1 if QOB==`i' - 4. -. } -(262019 real changes made) -(255733 real changes made) -(280749 real changes made) -(265133 real changes made) - - -********** QOB*YOB dummies ******** - -. foreach j of numlist 1/3 { - 2. -. foreach i of numlist 0/9 { - 3. -. gen QTR`j'YR`i'=QTR`j'*YR`i' - 4. -. } - 5. -. } - -. -. ********** Select Particular Men Born ******** - -. gen COHORT=2029 - -. -. replace COHORT=3039 if YOB<=39 & YOB >=30 -(329509 real changes made) - -. -. replace COHORT=4049 if YOB<=49 & YOB >=40 -(486926 real changes made) - -. -. replace AGEQ=AGEQ-1900 if CENSUS==80 -(816435 real changes made) - -. -. gen AGEQSQ= AGEQ*AGEQ - - -********** Panel A ******** - -. sum LWKLYWGE if QTR1==1 & COHORT==2029 - - Variable | Obs Mean Std. Dev. Min Max --------------+-------------------------------------------------------- - LWKLYWGE | 62628 5.148471 .6548401 -.0198026 8.503235 - -. -. sum LWKLYWGE if QTR1!=1 & COHORT==2029 - - Variable | Obs Mean Std. Dev. Min Max --------------+-------------------------------------------------------- - LWKLYWGE | 184571 5.15745 .6500542 -.0198026 8.947976 - -. -. sum EDUC if QTR1==1 & COHORT==2029 - - Variable | Obs Mean Std. Dev. Min Max --------------+-------------------------------------------------------- - EDUC | 62628 11.3996 3.390094 0 18 - -. -. sum EDUC if QTR1!=1 & COHORT==2029 - - Variable | Obs Mean Std. Dev. Min Max --------------+-------------------------------------------------------- - EDUC | 184571 11.52515 3.350032 0 18 - -. -. -. -. reg LWKLYWGE QTR1 if COHORT==2029 - - Source | SS df MS Number of obs = 247199 --------------+------------------------------ F( 1,247197) = 8.89 - Model | 3.76989393 1 3.76989393 Prob > F = 0.0029 - Residual | 104849.25247197 .424152599 R-squared = 0.0000 --------------+------------------------------ Adj R-squared = 0.0000 - Total | 104853.02247198 .424166133 Root MSE = .65127 - ------------------------------------------------------------------------------- - LWKLYWGE | Coef. Std. Err. t P>|t| [95% Conf. Interval] --------------+---------------------------------------------------------------- - QTR1 | -.0089789 .0030117 -2.98 0.003 -.0148818 -.0030759 - _cons | 5.15745 .0015159 3402.17 0.000 5.154479 5.160421 ------------------------------------------------------------------------------- - -. -. reg EDUC QTR1 if COHORT==2029 - - Source | SS df MS Number of obs = 247199 --------------+------------------------------ F( 1,247197) = 65.29 - Model | 737.149176 1 737.149176 Prob > F = 0.0000 - Residual | 2791131.65247197 11.2911227 R-squared = 0.0003 --------------+------------------------------ Adj R-squared = 0.0003 - Total | 2791868.8247198 11.294059 Root MSE = 3.3602 - ------------------------------------------------------------------------------- - EDUC | Coef. Std. Err. t P>|t| [95% Conf. Interval] --------------+---------------------------------------------------------------- - QTR1 | -.1255553 .0155391 -8.08 0.000 -.1560115 -.0950991 - _cons | 11.52515 .0078214 1473.53 0.000 11.50982 11.54048 ------------------------------------------------------------------------------- - -. -. sureg (eq1: LWKLYWGE QTR1 ) (eq2: EDUC QTR1 ) if COHORT==2029 - -Seemingly unrelated regression ----------------------------------------------------------------------- -Equation Obs Parms RMSE "R-sq" chi2 P ----------------------------------------------------------------------- -eq1 2.5e+05 1 .6512674 0.0000 8.89 0.0029 -eq2 2.5e+05 1 3.360213 0.0003 65.29 0.0000 ----------------------------------------------------------------------- - ------------------------------------------------------------------------------- - | Coef. Std. Err. z P>|z| [95% Conf. Interval] --------------+---------------------------------------------------------------- -eq1 | - QTR1 | -.0089789 .0030117 -2.98 0.003 -.0148818 -.003076 - _cons | 5.15745 .0015159 3402.18 0.000 5.154479 5.160421 --------------+---------------------------------------------------------------- -eq2 | - QTR1 | -.1255553 .015539 -8.08 0.000 -.1560113 -.0950993 - _cons | 11.52515 .0078214 1473.54 0.000 11.50982 11.54048 ------------------------------------------------------------------------------- - -. -. nlcom ratio: [eq1]_b[QTR1]/[eq2]_b[QTR1] - - ratio: [eq1]_b[QTR1]/[eq2]_b[QTR1] - ------------------------------------------------------------------------------- - | Coef. Std. Err. z P>|z| [95% Conf. Interval] --------------+---------------------------------------------------------------- - ratio | .0715133 .0218682 3.27 0.001 .0286525 .1143741 ------------------------------------------------------------------------------- - -. -. reg LWKLYWGE EDUC if COHORT==2029 - - Source | SS df MS Number of obs = 247199 --------------+------------------------------ F( 1,247197) =50948.11 - Model | 17917.6603 1 17917.6603 Prob > F = 0.0000 - Residual | 86935.3595247197 .351684525 R-squared = 0.1709 --------------+------------------------------ Adj R-squared = 0.1709 - Total | 104853.02247198 .424166133 Root MSE = .59303 - ------------------------------------------------------------------------------- - LWKLYWGE | Coef. Std. Err. t P>|t| [95% Conf. Interval] --------------+---------------------------------------------------------------- - EDUC | .0801112 .0003549 225.72 0.000 .0794156 .0808068 - _cons | 4.23443 .00425 996.33 0.000 4.2261 4.24276 ------------------------------------------------------------------------------- - -. - - -********** Panel B ******** - -. sum LWKLYWGE if QTR1==1 & COHORT==3039 - - Variable | Obs Mean Std. Dev. Min Max --------------+-------------------------------------------------------- - LWKLYWGE | 81671 5.891596 .6809133 -2.341806 10.5321 - -. -. sum LWKLYWGE if QTR1!=1 & COHORT==3039 - - Variable | Obs Mean Std. Dev. Min Max --------------+-------------------------------------------------------- - LWKLYWGE | 247838 5.902695 .6781127 -2.341806 10.5321 - -. -. sum EDUC if QTR1==1 & COHORT==3039 - - Variable | Obs Mean Std. Dev. Min Max --------------+-------------------------------------------------------- - EDUC | 81671 12.68807 3.309801 0 20 - -. -. sum EDUC if QTR1!=1 & COHORT==3039 - - Variable | Obs Mean Std. Dev. Min Max --------------+-------------------------------------------------------- - EDUC | 247838 12.79688 3.271337 0 20 - -. -. reg LWKLYWGE QTR1 if COHORT==3039 - - Source | SS df MS Number of obs = 329509 --------------+------------------------------ F( 1,329507) = 16.42 - Model | 7.56705738 1 7.56705738 Prob > F = 0.0001 - Residual | 151830.304329507 .460780207 R-squared = 0.0000 --------------+------------------------------ Adj R-squared = 0.0000 - Total | 151837.871329508 .460801773 Root MSE = .67881 - ------------------------------------------------------------------------------- - LWKLYWGE | Coef. Std. Err. t P>|t| [95% Conf. Interval] --------------+---------------------------------------------------------------- - QTR1 | -.0110989 .0027388 -4.05 0.000 -.0164669 -.0057309 - _cons | 5.902695 .0013635 4329.00 0.000 5.900022 5.905367 ------------------------------------------------------------------------------- - -. -. reg EDUC QTR1 if COHORT==3039 - - Source | SS df MS Number of obs = 329509 --------------+------------------------------ F( 1,329507) = 67.57 - Model | 727.393312 1 727.393312 Prob > F = 0.0000 - Residual | 3546940.27329507 10.7643852 R-squared = 0.0002 --------------+------------------------------ Adj R-squared = 0.0002 - Total | 3547667.66329508 10.76656 Root MSE = 3.2809 - ------------------------------------------------------------------------------- - EDUC | Coef. Std. Err. t P>|t| [95% Conf. Interval] --------------+---------------------------------------------------------------- - QTR1 | -.1088179 .0132376 -8.22 0.000 -.1347633 -.0828725 - _cons | 12.79688 .0065904 1941.75 0.000 12.78397 12.8098 ------------------------------------------------------------------------------- - -. -. sureg (eq1: LWKLYWGE QTR1 ) (eq2: EDUC QTR1 ) if COHORT==3039 - -Seemingly unrelated regression ----------------------------------------------------------------------- -Equation Obs Parms RMSE "R-sq" chi2 P ----------------------------------------------------------------------- -eq1 3.3e+05 1 .6788059 0.0000 16.42 0.0001 -eq2 3.3e+05 1 3.280902 0.0002 67.57 0.0000 ----------------------------------------------------------------------- - ------------------------------------------------------------------------------- - | Coef. Std. Err. z P>|z| [95% Conf. Interval] --------------+---------------------------------------------------------------- -eq1 | - QTR1 | -.0110989 .0027388 -4.05 0.000 -.0164668 -.0057309 - _cons | 5.902695 .0013635 4329.01 0.000 5.900022 5.905367 --------------+---------------------------------------------------------------- -eq2 | - QTR1 | -.1088179 .0132376 -8.22 0.000 -.1347631 -.0828727 - _cons | 12.79688 .0065904 1941.76 0.000 12.78397 12.8098 ------------------------------------------------------------------------------- - -. -. nlcom ratio: [eq1]_b[QTR1]/[eq2]_b[QTR1] - - ratio: [eq1]_b[QTR1]/[eq2]_b[QTR1] - ------------------------------------------------------------------------------- - | Coef. Std. Err. z P>|z| [95% Conf. Interval] --------------+---------------------------------------------------------------- - ratio | .101995 .0239489 4.26 0.000 .055056 .148934 ------------------------------------------------------------------------------- - -. -. reg LWKLYWGE EDUC if COHORT==3039 - - Source | SS df MS Number of obs = 329509 --------------+------------------------------ F( 1,329507) =43782.56 - Model | 17808.8293 1 17808.8293 Prob > F = 0.0000 - Residual | 134029.041329507 .40675628 R-squared = 0.1173 --------------+------------------------------ Adj R-squared = 0.1173 - Total | 151837.871329508 .460801773 Root MSE = .63777 - ------------------------------------------------------------------------------- - LWKLYWGE | Coef. Std. Err. t P>|t| [95% Conf. Interval] --------------+---------------------------------------------------------------- - EDUC | .070851 .0003386 209.24 0.000 .0701874 .0715147 - _cons | 4.995182 .0044644 1118.88 0.000 4.986432 5.003932 ------------------------------------------------------------------------------- From 22dd2f22a5c3add0ca8c09713abe4221fc66dff8 Mon Sep 17 00:00:00 2001 From: bahadirbusra <75804477+bahadirbusra@users.noreply.github.com> Date: Thu, 17 Dec 2020 23:45:41 +0300 Subject: [PATCH 6/9] =?UTF-8?q?Delete=20regresyon=20kodlar=C4=B1.txt?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../analysis/regresyon kodlar\304\261.txt" | 182 ------------------ 1 file changed, 182 deletions(-) delete mode 100644 "ikt533-main/2020-fall/analysis/regresyon kodlar\304\261.txt" diff --git "a/ikt533-main/2020-fall/analysis/regresyon kodlar\304\261.txt" "b/ikt533-main/2020-fall/analysis/regresyon kodlar\304\261.txt" deleted file mode 100644 index f07f02f..0000000 --- "a/ikt533-main/2020-fall/analysis/regresyon kodlar\304\261.txt" +++ /dev/null @@ -1,182 +0,0 @@ - -***********ÖDEVE AÝT BÜTÜN KODLAR******** - -use "C:\Users\kenan\Desktop\NEW7080 (1).dta" - -rename v1 AGE -rename v2 AGEQ -rename v4 EDUC -rename v5 ENOCENT -rename v6 ESOCENT -rename v9 LWKLYWGE -rename v10 MARRIED -rename v11 MIDATL -rename v12 MT -rename v13 NEWENG -rename v16 CENSUS -rename v18 QOB -rename v19 RACE -rename v20 SMSA -rename v21 SOATL -rename v24 WNOCENT -rename v25 WSOCENT -rename v27 YOB - -replace YOB=YOB-1900 if YOB >=1900 -foreach i of numlist 0/9 { -gen YR`i'=0 -replace YR`i'=1 if YOB==20+`i' | YOB==30+`i' | YOB==40+`i' -} - -foreach i of numlist 1/4 { -gen QTR`i'=0 -replace QTR`i'=1 if QOB==`i' -} - -foreach j of numlist 1/3 { -foreach i of numlist 0/9 { -gen QTR`j'YR`i'=QTR`j'*YR`i' -} -} - -gen COHORT=2029 -replace COHORT=3039 if YOB<=39 & YOB >=30 -replace COHORT=4049 if YOB<=49 & YOB >=40 -replace AGEQ=AGEQ-1900 if CENSUS==80 -gen AGEQSQ= AGEQ*AGEQ - -******1920-1929 dönemi***** - -keep if COHORT < 2030 -ivregress 2sls LWKLYWGE (EDUC=QTR1) -ivregress 2sls LWKLYWGE YR0-YR8 RACE MARRIED SMSA NEWENG MIDATL ENOCENT WNOCENT SOATL ESOCENT WSOCENT MT AGEQ AGEQSQ (EDUC = QTR1YR0-QTR1YR9 QTR2YR0-QTR2YR9 QTR3YR0-QTR3YR9 YR0-YR8) -reg LWKLYWGE EDUC -reg LWKLYWGE EDUC RACE MARRIED SMSA NEWENG MIDATL ENOCENT WNOCENT SOATL ESOCENT WSOCENT MT YR0-YR8 AGEQ AGEQSQ - -******1930-1939 dönemi***** - -keep if COHORT>3000 & COHORT <3040 -ivregress 2sls LWKLYWGE (EDUC = QTR1) -ivregress 2sls LWKLYWGE YR0-YR8 RACE MARRIED SMSA NEWENG MIDATL ENOCENT WNOCENT SOATL ESOCENT WSOCENT MT AGEQ AGEQSQ (EDUC = QTR1YR0-QTR1YR9 QTR2YR0-QTR2YR9 QTR3YR0-QTR3YR9 YR0-YR8) -reg LWKLYWGE EDUC -reg LWKLYWGE EDUC RACE MARRIED SMSA NEWENG MIDATL ENOCENT WNOCENT SOATL ESOCENT WSOCENT MT YR0-YR8 AGEQ AGEQSQ - - -**********Tablo III KODLARI******** -sum LWKLYWGE if QTR1==1 & COHORT==2029 -sum LWKLYWGE if QTR1!=1 & COHORT==2029 -sum EDUC if QTR1==1 & COHORT==2029 -sum EDUC if QTR1!=1 & COHORT==2029 - -reg LWKLYWGE QTR1 if COHORT==2029 -reg EDUC QTR1 if COHORT==2029 -sureg (eq1: LWKLYWGE QTR1 ) (eq2: EDUC QTR1 ) if COHORT==2029 -nlcom ratio: [eq1]_b[QTR1]/[eq2]_b[QTR1] -reg LWKLYWGE EDUC if COHORT==2029 -sum LWKLYWGE if QTR1==1 & COHORT==3039 -sum LWKLYWGE if QTR1!=1 & COHORT==3039 -sum EDUC if QTR1==1 & COHORT==3039 -sum EDUC if QTR1!=1 & COHORT==3039 -reg LWKLYWGE QTR1 if COHORT==3039 -reg EDUC QTR1 if COHORT==3039 -sureg (eq1: LWKLYWGE QTR1 ) (eq2: EDUC QTR1 ) if COHORT==3039 -nlcom ratio: [eq1]_b[QTR1]/[eq2]_b[QTR1] -reg LWKLYWGE EDUC if COHORT==3039 - - -*****Figure V- 1930-1939 dönemi için yatay eksende doðum çeyreklerinin ve yýllarýn, dikey eksende ise o çeyrekte doðanlarýn eðitim seviyelerinin ortalamalarýnýn -yer aldýðý çizgi grafiði. - -use "C:\Users\kenan\Desktop\ak91.dta" -tab qob, gen(q) -gen age = ((79 - yob)*4 + 5 - qob)/4 -gen age2 = age^2 -collapse s lnw q*, by(age) -gen yob = 80-age - -label var s "Years of education" -label var lnw "Log Weekly Earnings" -label var age "Age" -label var yob "Year of Birth" -twoway (line s yob) (scatter s yob if q4 == 1) (scatter s yob if q1 == 1) (scatter s yob if q2 == 1) (scatter s yob if q3 == 1, msym(Oh)) - -************************************** -************************************* - -***Zayýf araç deðiþkeni testleri*** - - -use "C:\Users\kenan\Desktop\ak91.dta" - -****Tablo 6.4.***************** - -tab qob, gen(q) -gen age = ((79 - yob)*4 + 5 - qob)/4 -gen age2 = age^2 -matrix T = J(6,3,.) - -reg lnw q4, robust -mat T[1,1] = _b[_cons] -mat T[1,2] = (_b[_cons] + _b[q4]) -mat T[1,3] = _b[q4] -mat T[2,3] = _se[q4] - -reg s q4, robust -mat T[3,1] = _b[_cons] -mat T[3,2] = (_b[_cons] + _b[q4]) -mat T[3,3] = _b[q4] -mat T[4,3] = _se[q4] - -ivregress 2sls lnw (s = q4), robust -mat T[5,3] = _b[s] -mat T[6,3] = _se[s] -matrix list T - -ssc install mat2txt -mat2txt, matrix(T) saving("C:\Users\kenan\Desktop\Tablo64.xlsx") title(Table 6.4) replace - -*****TABLO 6.5.******************************* - -sort q4 -by q4: sum lnw s -reg lnw q4, robust -reg s q4, robust - -****OLS(1)**** -reg lnw s, robust -outreg2 s using "C:\Users\kenan\Desktop\Table64.xls", replace bdec(3) sdec(3) noaster word -reg s q4 -testparm q4 -local F = r(F) - -***2SLS(2)**** -ivregress 2sls lnw (s = q4), robust -outreg2 s using "C:\Users\kenan\Desktop\Table64.xls", append bdec(3) sdec(3) noaster word addstat(F-stat, `F') - -****OLS(3)**** -reg lnw s i.yob, robust -outreg2 s using "C:\Users\kenan\Desktop\Table64.xls", append bdec(3) sdec(3) noaster word -reg s q4 i.yob -testparm q4 -local F = r(F) - -****2SLS(4)**** -ivregress 2sls lnw (s = q4) i.yob, robust -outreg2 s using "C:\Users\kenan\Desktop\Table64.xls", append bdec(3) sdec(3) noaster word addstat(F-stat, `F') -reg s q2 q3 q4 i.yob -testparm q2 q3 q4 -local F = r(F) - -****2SLS(5)***** -ivregress 2sls lnw (s = i.qob) i.yob, robust -outreg2 s using "C:\Users\kenan\Desktop\Table64.xls", append bdec(3) sdec(3) noaster word addstat(F-stat, `F') - - - - - - - - - - From ffb9f599564a45af763f7aae58a5d369232770bc Mon Sep 17 00:00:00 2001 From: bahadirbusra <75804477+bahadirbusra@users.noreply.github.com> Date: Thu, 17 Dec 2020 23:46:15 +0300 Subject: [PATCH 7/9] =?UTF-8?q?Delete=20=C5=9Fekil=20V.txt?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../2020-fall/analysis/\305\237ekil V.txt" | 17 ----------------- 1 file changed, 17 deletions(-) delete mode 100644 "ikt533-main/2020-fall/analysis/\305\237ekil V.txt" diff --git "a/ikt533-main/2020-fall/analysis/\305\237ekil V.txt" "b/ikt533-main/2020-fall/analysis/\305\237ekil V.txt" deleted file mode 100644 index 4f32061..0000000 --- "a/ikt533-main/2020-fall/analysis/\305\237ekil V.txt" +++ /dev/null @@ -1,17 +0,0 @@ - -*****Figure 1- 1930-1939 dönemi için yatay eksende doðum çeyreklerinin ve yýllarýn, dikey eksende ise o çeyrekte doðanlarýn eðitim seviyelerinin ortalamalarýnýn -yer aldýðý çizgi grafiði. - - -use "C:\Users\kenan\Desktop\ak91.dta" -tab qob, gen(q) -gen age = ((79 - yob)*4 + 5 - qob)/4 -gen age2 = age^2 -collapse s lnw q*, by(age) -gen yob = 80-age - -label var s "Years of education" -label var lnw "Log Weekly Earnings" -label var age "Age" -label var yob "Year of Birth" -twoway (line s yob) (scatter s yob if q4 == 1) (scatter s yob if q1 == 1) (scatter s yob if q2 == 1) (scatter s yob if q3 == 1, msym(Oh)) From f570b6825519608a4b841a352e3df1dc64b056b9 Mon Sep 17 00:00:00 2001 From: bahadirbusra <75804477+bahadirbusra@users.noreply.github.com> Date: Mon, 21 Dec 2020 00:19:51 +0300 Subject: [PATCH 8/9] =?UTF-8?q?Son=C3=96dev?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Ä°lkÖdevim --- 2020-fall/report/busraa.png | Bin 0 -> 56167 bytes "2020-fall/report/\303\266dev1.tex" | 240 ++++++++++++++++++ .../2020-fall/analysis/busrabahadir.do | Bin 0 -> 7538 bytes 3 files changed, 240 insertions(+) create mode 100644 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@@ +\documentclass[a4paper]{article} +\input{head} +\begin{document} + +%------------------------------- +% TITLE SECTION +%------------------------------- + +\fancyhead[C]{} +\hrule \medskip % Upper rule +\begin{minipage}{0.295\textwidth} +\raggedright +\footnotesize +Büşra Bahadir \hfill\\ + +\end{minipage} +\begin{minipage}{0.4\textwidth} +\centering +\large +ÖDEV 1\\ +\normalsize +EMEK EKONOMÄ°SÄ°-Ä°KT 533\\ +\end{minipage} +\begin{minipage}{0.295\textwidth} +\raggedleft +\today\hfill\\ +\end{minipage} +\medskip\hrule +\bigskip + +%------------------------------- +% CONTENTS +%------------------------------- + + +a) 3 adet doÄŸum çeÄŸreÄŸi kukla deÄŸiÅŸkeni oluÅŸturuyoruz.EÄŸitimin ücretler üzerindeki etkisi analiz edilirken doÄŸum çeyrekleri eÄŸitim için enstrüman deÄŸiÅŸken olarak kullanılır. Dolayısyla doÄŸum çeyrekleri enstrüman deÄŸiÅŸken iken enstrüman deÄŸiÅŸkenin eÄŸitim üzerindeki etkisini test eden regresyon birinci aÅŸama (first stage) olacaktır. Bu tahminin katsayısı 0 olmaz.Yani enstrüman biraz açıklayıcı güce sahiptir. Ä°ndirgenmiÅŸ form (reduced form) ise ücretler ve enstrüman deÄŸiÅŸken doÄŸum çeyrekleri arasındaki iliÅŸkiyi tahminleyen modeldir. +\item +Birinci aÅŸama tahminleri Tablo 3 deki Panel A ve Panel B deki ikinci sütundaki 3. kolondaki doÄŸum ceyreÄŸinin eÄŸitim üzerindeki etkisini inceleyen tahmindir. [-0.1256(0.0155) ve -0.1088(0.0132)]. +Ä°ndirgenmiÅŸ form tahminleri ise enstrüman deÄŸiÅŸken doÄŸum çeyreÄŸinin ücretler üzerindeki regresyonundan bulduÄŸumuz Panel A ve Panel B ' deki ilk sütundaki 3.kolondaki tahminlerdir. [-0.00898(0.00301) ve -0.01110(0.00274)]. Ä°ndirgenmiÅŸ form katsayılarını alıp birinci aÅŸama katsayılarına bölersek Wald tahminlerini elde ederiz. Wald tahmini, ilk çeyrekle diÄŸer 3 çeyrek arasındaki ĕgitimdeki genel farkla tanımlanır +. +\item +\item +\item +\begin{table}[h!] +\centering +\begin{tabular}{@{}lccc@{}} +\toprule +\multicolumn{4}{l}{PANEL A: WALD ESTIMATES FOR 1970 CENSUS - MEN BORN 1920-1929} \\ \midrule + & \begin{tabular}[c]{@{}c@{}}(1)\\ Born in \\ 1st quarter \\ of year\end{tabular} & \begin{tabular}[c]{@{}c@{}}(2)\\ Born in 2nd, \\ 3rd, or 4th\\ quarter of year\end{tabular} & \begin{tabular}[c]{@{}c@{}}(3)\\ Difference\\ (std. error)\\ (1)-(2)\end{tabular} \\ \midrule +ln (wkly. wage) & 5.1484 & 5.1574 & \begin{tabular}[c]{@{}c@{}}-.00898\\ (.00301)\end{tabular} \\ +Education & 11.3996 & 11.5252 & \begin{tabular}[c]{@{}c@{}}-.1256\\ (.0155)\end{tabular} \\ +Wald est. of return to education & & & \begin{tabular}[c]{@{}c@{}}.0715\\ (.0219)\end{tabular} \\ +OLS return to education & & & \begin{tabular}[c]{@{}c@{}}.0801\\ (.0004)\end{tabular} \\ \midrule +\multicolumn{4}{l}{PANEL B: WALD ESTIMATES FOR 1980 CENSUS - MEN BORN 1930-1939} \\ \midrule + & \begin{tabular}[c]{@{}c@{}}(1)\\ Born in \\ 1st quarter \\ of year\end{tabular} & \begin{tabular}[c]{@{}c@{}}(2)\\ Born in 2nd,\\ 3rd, or 4th \\ quarter of year\end{tabular} & \begin{tabular}[c]{@{}c@{}}(3)\\ Difference\\ (std. error)\\ (1)-(2)\end{tabular} \\ \midrule +ln (wkly. wage) & 5.8916 & 5.9027 & \begin{tabular}[c]{@{}c@{}}-.01110\\ (.00274)\end{tabular} \\ +Education & 12.6881 & 12.7969 & \begin{tabular}[c]{@{}c@{}}-.1088\\ (.0132)\end{tabular} \\ +Wald est. of return to education & & & \begin{tabular}[c]{@{}c@{}}.1020\\ (.0239\end{tabular} \\ +OLS return to education & & & \begin{tabular}[c]{@{}c@{}}.0709\\ (.0003)\end{tabular} \\ \bottomrule +\end{tabular} + +\end{table} +\\ +\\ +\\ +\\ +\\ +\\ +\\ +\\ +\\ + +\newpage +b) Wald tahmini enstrüman deÄŸiÅŸkenin özel bir durumu gibidir. +Bu durumda Wald tahmini, bir bireyin yılın ilk çeyreÄŸinde doÄŸup doÄŸmadığını gösteren bir kukla deÄŸiÅŸkenin eÄŸitim için bir araç olarak kullanıldığı ve hiçbir kontrol deÄŸiÅŸkeninin bulunmadığı araç deÄŸiÅŸkenlere eÅŸdeÄŸerdir. TSLS tahminleri iki önemli açıdan Wald tahminlerinden farklılık gösterir. Ä°lk olarak, TSLS tahminleri kontrol deÄŸiÅŸkenleri içerir. Ä°kincisi, TSLS modelleri, her yıl doÄŸumun her çeyreÄŸindeki eÄŸitimdeki varyasyonlarla tanımlanırken, Wald tahmini, ilk çeyrek ile yılın geri kalanı arasındaki eÄŸitimdeki genel farkla tanımlanır. +\item +\item +AÅŸağıdaki tablolar her iki dönem (1920-29 ve 1930-39) için aynı araç deÄŸiÅŸken kullanarak yapılmış, herhangi bir kontrol deÄŸiÅŸkeni kullanılmayan 2SLS tahminlerini (Wald Tahmini), bütün ırk, bölge kuklaları, doÄŸum yılı kuklaları ve yaÅŸ deÄŸiÅŸkeni kullanılarak yapılmış 2SLS tahminlerini, herhangi bir kontrol deÄŸiÅŸkeni kullanılmadan yapılmış OLS tahminlerini ve bütün kontrol deÄŸiÅŸkenlerin birlikte kullanıldığı OLS tahminlerini içermektedir. +EÄŸitim yılı için doÄŸum çeyrekleri enstrüman deÄŸiÅŸken olarak kullanılmıştır. her iki dönem için birinci dönem için 1970, ikinci dönem için 1980 nüfus sayımı verileri kullanılarak aynı tahminler yapılmış ve aÅŸağıdaki iki tabloda ayrı ayrı sunulmuÅŸtur. Tablolardaki birinci sütun ve üçüncü sütunlar OLS tahminlerini, ikinci ve dördüncü sütunlar 2SLS tahminlerini göstermektedir. +\item +Ä°lk tablo 1970 nüfus sayımı verileri kullanılarak yapılmış 1920-29 dönemine ait tahminleri içermektedir. Tabloya bakıldığında herhangi bir kontrol deÄŸiÅŸkeni kullanılmadan yapılmış OLS ve 2SLS tahminlerinin (1. ve 2. sütun) a şıkkında oluÅŸturulan OLS ve Wald tahminleri ile aynı olduÄŸu görülecektir. Kontrol deÄŸiÅŸkenleri eklenerek yapılmıs OLS ve 2SLS tahminlerinde ise yaÅŸ dışında bütün açıklayıcı deÄŸiÅŸkenler istatistiki olarak anlamlı bulunmuÅŸtur. OLS tahmininde kontrol deÄŸiÅŸkenleri eklendiÄŸinde eÄŸitimin katsayısı düşerken 2SLS taminlerinde bu katsayı artmıştır. DoÄŸum yılı kuklaları ücret eÅŸitliklerine dahil edildiÄŸinden, eÄŸitimin etkisi her doÄŸum yılı içinde doÄŸum çeyrekleri arasındaki eÄŸitimdeki farklılıkler (varyasyon) olarak tanımlanır. Bu yüzden 3. ve 4. sütunlar ilk 2 sütunu tekrar ederler doÄŸum yılı kuklalarını da dahil ederler. Bunlara ek olarak diÄŸer bütün kontrol deÄŸiÅŸkenleri de kullanılmıştır. + +\item + + +\begin{table}[htbp]\centering +\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi} + +\begin{tabular}{l*{4}{c}} +\hline\hline +Independent Variables &\multicolumn{1}{c}{\begin{tabular}[c]{@{}l@{}}(1)\\ OLS\end{tabular}}&\multicolumn{1}{c}{\begin{tabular}[c]{@{}l@{}}(2)\\ TSLS)\end{tabular}}&\multicolumn{1}{c}{\begin{tabular}[c]{@{}l@{}}(3)\\ OLS\end{tabular}}&\multicolumn{1}{c}{\begin{tabular}[c]{@{}l@{}}(4)\\ TSLS\end{tabular}}\\ +\hline +Years of education & 0.0802\sym{***}& 0.0715\sym{***}& 0.0701\sym{***}& 0.1007\sym{**} \\ + & (0.0004) & (0.0219) & (0.0004) & (0.0334) \\ +[1em] +Race(1 = black) & & & -0.298\sym{***}& -0.227\sym{**} \\ + & & & (0.0043) & (0.0776) \\ +[1em] +SMSA (1 = center city) & & & -0.134\sym{***}& -0.116\sym{***}\\ + & & & (0.0026) & (0.0198) \\ +[1em] +Married (1 = married) & & & 0.293\sym{***}& 0.280\sym{***}\\ + & & & (0.0037) & (0.0141) \\ +8 Region of residence dummies & No & No & Yes& Yes\\ + & & & & \\ +[1em] +9 Region of residence dummies & No & No & Yes& Yes\\ + & & & & \\ +[1em] +Age & & & 0.116 & 0.117 \\ + & & & (0.0652) & (0.0661) \\ +[1em] +Age-squared & & & -0.00125 & -0.00118 \\ + & & & (0.0007) & (0.0007) \\ +\hline +Observations & 247199 & 247199 & 247199 & 247199 \\ +\hline\hline +\multicolumn{9}{l}{\footnotesize Standard errors in parentheses}\\ +\multicolumn{9}{l}{\footnotesize \sym{*} \(p<0.05\), \sym{**} \(p<0.01\), \sym{***} \(p<0.001\)}\\ +\end{tabular} +\end{table} +\end{landscape} +\clearpage +Ä°kinci tablo ise 1980 nüfus sayımı verileri kullanılarak yapılmış 1930-39 dönemine ait tahminleri içermektedir. Birinci tabloda yapılmış olan tahminlerin aynısı bu tabloda yapılmıştır. Bu dönemde kontrol deÄŸiÅŸkenleri eklendiÄŸinde OLS ve TSLS tahminlerine ait eÄŸitim deÄŸiÅŸkenine ait katsayıların (3. ve 4. sütunda) azaldığı görülmektedir. Bu tabloda da önceki tablo ile aynı ÅŸekilde yaÅŸ dışındaki bütün kontrol deÄŸiÅŸkenleri istatistiki olarak anlamlıdır. + +\begin{landscape} +\begin{table}[htbp]\centering +\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi} + +\begin{tabular}{l*{4}{c}} +\hline\hline +Independent Variables &\multicolumn{1}{c}{\begin{tabular}[c]{@{}l@{}}(1)\\ OLS\end{tabular}}&\multicolumn{1}{c}{\begin{tabular}[c]{@{}l@{}}(2)\\ TSLS\end{tabular}}&\multicolumn{1}{c}{\begin{tabular}[c]{@{}l@{}}(3)\\ OLS\end{tabular}}&\multicolumn{1}{c}{\begin{tabular}[c]{@{}l@{}}(4)\\ TSLS\end{tabular}}\\ +\hline +Years of education & 0.0709\sym{***}& 0.1020\sym{***}& 0.0632\sym{***}& 0.0600\sym{*} \\ + & (0.0003) & (0.0239) & (0.0003) & (0.0290) \\ +[1em] +Race(1 = black) & & & -0.257\sym{***}& -0.263\sym{***}\\ + & & & (0.0040) & (0.0458) \\ +[1em] +SMSA (1 = center city) & & & -0.176\sym{***}& -0.180\sym{***}\\ + & & & (0.0029) & (0.0305) \\ +[1em] +Married (1 = married) & & & 0.248\sym{***}& 0.249\sym{***}\\ + & & & (0.0032) & (0.0073) \\ +[1em] +8 Region of residence dummies & No & No & Yes& Yes\\ + & & & & \\ +[1em] +9 Region of residence dummies & No & No & Yes& Yes\\ + & & & & \\ +Age & & & -0.0760 & -0.0741 \\ + & & & (0.0604) & (0.0626) \\ +[1em] +Age-squared & & & 0.0008 & 0.0007 \\ + & & & (0.0007) & (0.0007) \\ +\hline +Observations & 329509 & 329509 & 329509 & 329509 & \\ +\hline\hline +\multicolumn{9}{l}{\footnotesize Standard errors in parentheses}\\ +\multicolumn{9}{l}{\footnotesize \sym{*} \(p<0.05\), \sym{**} \(p<0.01\), \sym{***} \(p<0.001\)}\\ +\end{tabular} +\end{table} +\end{landscape} +\item +\item +\item + +c) Zayıf bir enstrüman deÄŸiÅŸken , enstrümanı olarak kullanıldığı deÄŸiÅŸkenle yüksek düzeyde iliÅŸkili olmayan bir enstrümandır, bu nedenle bu enstrümanla iliÅŸkili ilk aÅŸama katsayısı küçüktür veya kesin olarak tahmin edilmez.Bu gibi birçok araç deÄŸiÅŸkenle yapılan 2SLS tahminleri, aynı modelin OLS tahminlerine benzer olma eÄŸilimindedir. 2SLS, OLS'ye yakın olduÄŸunda, ikincisindeki seçilim yanlılığı konusunda endiÅŸelenmenize gerek olmadığı sonucuna varmanız doÄŸaldır, ancak bu sonuç yersiz olabilir. Sonlu örneklem sapması (finite sample bias) nedeniyle, birçok zayıf IV kullanılarak yapılan 2SLS tahminleri, ilginin nedensel iliÅŸkisi hakkında size çok az ÅŸey söyler. +\item +Sonlu örneklem sapması ne zaman endiÅŸelenmeye deÄŸer? Birçok enstrümanla kurulan bütün ilk aÅŸama tahminlerinin sıfır olduÄŸu ortak hipotezini test eden ilk aÅŸama F istatistiÄŸine odaklanılır. Popüler bir genel kurala göre, bunu ortadan kaldırmak için F deÄŸerinin en az 10 olması gerekmektedir. 2SLS'ye bir alternatif olarak LIML modeli sonlu örneklem sapmasından daha az etkilenmektedir. EÄŸer tek bir nedensel etkiyi tahmin etmek için tek bir enstrüman kullanılırsa birçok zayıf araç deÄŸiÅŸken problemi azaltilabilir.Ä°ndirgenmiÅŸ form tahminleri sınırlı örneklem sapmasından etkilenmeyen OLS tahminleri olduÄŸundan dikkatle incelenmesi gerekmektedir. Küçük ve anlamlı ölçüde sıfırdan farklı olmayan indirgenmiÅŸ form tahminleri en azından eldeki verilerde, ilgili nedensel iliÅŸkinin zayıf veya var olmadığına dair güçlü ve tarafsız bir ipucu saÄŸlar. Çoklu indirgenmiÅŸ form katsayıları ayrıca bir F testi kullanılarak birlikte test edilmelidir. +\item +AÅŸağıdaki tabloda ilk iki sütun B şıkkında 1920-29 için yapılan IV tahminlerinin birinci aÅŸama F istatistiklerini göstermektedir. 3. ve 4. sütunda 1930-39 dönemine ait IV tahminlerinin F istatistikleri mevcuttur. Burada bütün kontrol deÄŸiÅŸkenleri eklenerek yapılan IV tahminlerinin birinci aÅŸama F istatistiklerinin daha düşük olduÄŸunu 2. ve 4. sütundan görebiliriz. Aynı ÅŸekilde bu tahminlerde standard hataların daha düşük olduÄŸunu da görüyoruz. +DoÄŸum çeyreÄŸi kukla deÄŸiÅŸken IV konusuna, ek enstrümanlar ve kontrol deÄŸiÅŸkenleri eklemek için 2SLS' i kullanabiliriz. +\item + \item + \item + \\ + + \\ \\ + \item + + +\item + +\item +\item +\\ + +\begin{table} +\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi} +\begin{tabular}{l*{5}{c}} +\hline\hline + &\multicolumn{1}{c}{\begin{tabular}[c]{@{}l@{}}(1920-1929)\\ + TSLS\end{tabular}}&\multicolumn{1}{c}{\begin{tabular}[c]{@{}l@{}}(1920-1929)\\ TSLS\end{tabular}}&\multicolumn{1}{c}{\begin{tabular}[c]{@{}l@{}}(1930-1939)\\ TSLS\end{tabular}}&\multicolumn{1}{c}{\begin{tabular}[c]{@{}l@{}}(1930-1939)\\ TSLS\end{tabular}}\\ +\hline + +\item +Years of education & .102\sym{}& .067\sym{}& .071\sym{}& .0805\sym{} & & \\ + & (.0219) & (.0152) & (.0240) & (.0164) & \\ + \\ +[1em] +First-stage F-statistic & 65 & 57,2 & 67 & 58 & & + & & & & & \\ +[1em] +Instruments & Quarter 1 & Quarter 1 & Quarter 1 & Quarter 1 & + & & & & & \\ +[1em] + \\ +[1em] +All control variables & No & Yes & No & Yes & & & \\ + & & & & & \\ +\hline +\multicolumn{9}{l}{}\\ +\multicolumn{9}{l}{\footnotesize } +\end{tabular} +\end{table} + \item + Peki bu doÄŸum çeyreÄŸi enstrümanları birinci aÅŸama, bağımsızlık ve dışlanmış kısıtlılık gerekliliklerini nasıl hesaplar? Bu tabloda sunulan büyük F istatistikleri güçlü bir ilk aÅŸamanın göstergeleridir. + Büyük bir birinci aÅŸama F istatistiÄŸi, zayıf araçlardan kaynaklanan yanlılığın bu baÄŸlamda bir sorun olma ihtimalinin düşük olduÄŸunu göstermektedir. Yukarıda da bahsettiÄŸim üzere eÄŸer F istatistiÄŸi 10 dan büyükse zayıf araç deÄŸiÅŸkenden söz edemeyiz. Araç deÄŸiÅŸkenin güçlü olduÄŸu sonucuna varırız. + \item + \clearpage + d)1930-39 dönemi için yatay eksende doÄŸum çeyreklerinin ve yılların, dikey eksende ise o çeyrekte doÄŸanların eÄŸitim seviyelerinin ortalamalarının yer aldığı çigi grafik aÅŸağıda sunulmuÅŸtur. + + \begin{figure}[ht!] +\centering + +\includegraphics[width=150mm]{busraa.png} +\label{overflow} +\end{figure} +\end{document} +\bigskip +\ + +%------------------------------------------------ + +\bigskip + +%------------------------------------------------ + +\end{document} diff --git a/ikt533-main/2020-fall/analysis/busrabahadir.do b/ikt533-main/2020-fall/analysis/busrabahadir.do new file mode 100644 index 0000000000000000000000000000000000000000..f927342eaf3b341d68484555d05a580d826471ea GIT binary patch literal 7538 zcmeIuF#!Mo0K%a4Pi+Tph(KY$fB^#r3>YwAz<>b*1`HT5V8DO@0|pEjFkrxd0R!K_ E03C7w0RR91 literal 0 HcmV?d00001 From 5f623f93de214b92a8207687448317090f3eeee3 Mon Sep 17 00:00:00 2001 From: bahadirbusra <75804477+bahadirbusra@users.noreply.github.com> Date: Mon, 21 Dec 2020 00:26:33 +0300 Subject: [PATCH 9/9] =?UTF-8?q?Do=20dosyas=C4=B1?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Ödevim --- .../analysis/busrabahadir\303\226dev.do" | 344 +++++++++--------- 1 file changed, 172 insertions(+), 172 deletions(-) rename 2020-fall/analysis/busrabahadir.do => "2020-fall/analysis/busrabahadir\303\226dev.do" (96%) diff --git a/2020-fall/analysis/busrabahadir.do "b/2020-fall/analysis/busrabahadir\303\226dev.do" similarity index 96% rename from 2020-fall/analysis/busrabahadir.do rename to "2020-fall/analysis/busrabahadir\303\226dev.do" index 86768e9..33204f5 100644 --- a/2020-fall/analysis/busrabahadir.do +++ "b/2020-fall/analysis/busrabahadir\303\226dev.do" @@ -1,172 +1,172 @@ -use "C:\Users\kenan\Desktop\NEW7080 (1).dta" -rename v1 AGE -rename v2 AGEQ -rename v4 EDUC -rename v5 ENOCENT -rename v6 ESOCENT -rename v9 LWKLYWGE -rename v10 MARRIED -rename v11 MIDATL -rename v12 MT -rename v13 NEWENG -rename v16 CENSUS -rename v18 QOB -rename v19 RACE -rename v20 SMSA -rename v21 SOATL -rename v24 WNOCENT -rename v25 WSOCENT -rename v27 YOB -**********YOB dummies ********** -replace YOB=YOB-1900 if YOB >=1900 -foreach i of numlist 0/9 { -gen YR`i'=0 -replace YR`i'=1 if YOB==20+`i' | YOB==30+`i' | YOB==40+`i' -} -**********QOB dummies *********** -foreach i of numlist 1/4 { -gen QTR`i'=0 -replace QTR`i'=1 if QOB==`i' -} -********** QOB*YOB dummies ******** -foreach j of numlist 1/3 { -foreach i of numlist 0/9 { -gen QTR`j'YR`i'=QTR`j'*YR`i' -} -} -********** Select Particular Men Born ******** -gen COHORT=2029 -replace COHORT=3039 if YOB<=39 & YOB >=30 -replace COHORT=4049 if YOB<=49 & YOB >=40 -replace AGEQ=AGEQ-1900 if CENSUS==80 -gen AGEQSQ= AGEQ*AGEQ -******************* -**************Cevap a)********** -*********Tablo III KODLARI******** -********** Panel A******** -sum LWKLYWGE if QTR1==1 & COHORT==2029 -sum LWKLYWGE if QTR1!=1 & COHORT==2029 -sum EDUC if QTR1==1 & COHORT==2029 -sum EDUC if QTR1!=1 & COHORT==2029 - -reg LWKLYWGE QTR1 if COHORT==2029 -reg EDUC QTR1 if COHORT==2029 -sureg (eq1: LWKLYWGE QTR1 ) (eq2: EDUC QTR1 ) if COHORT==2029 -nlcom ratio: [eq1]_b[QTR1]/[eq2]_b[QTR1] -reg LWKLYWGE EDUC if COHORT==2029 -********** -********** Panel B*********** -sum LWKLYWGE if QTR1==1 & COHORT==3039 -sum LWKLYWGE if QTR1!=1 & COHORT==3039 -sum EDUC if QTR1==1 & COHORT==3039 -sum EDUC if QTR1!=1 & COHORT==3039 -reg LWKLYWGE QTR1 if COHORT==3039 -reg EDUC QTR1 if COHORT==3039 -sureg (eq1: LWKLYWGE QTR1 ) (eq2: EDUC QTR1 ) if COHORT==3039 -nlcom ratio: [eq1]_b[QTR1]/[eq2]_b[QTR1] -reg LWKLYWGE EDUC if COHORT==3039 - -********Cevap b)********* -******1920-1929 dönemi için******** -keep if COHORT < 2030 -ivregress 2sls LWKLYWGE (EDUC=QTR1) -ivregress 2sls LWKLYWGE YR0-YR8 RACE MARRIED SMSA NEWENG MIDATL ENOCENT WNOCENT SOATL ESOCENT WSOCENT MT AGEQ AGEQSQ (EDUC = QTR1YR0-QTR1YR9 QTR2YR0-QTR2YR9 QTR3YR0-QTR3YR9 YR0-YR8) -reg LWKLYWGE EDUC -reg LWKLYWGE EDUC RACE MARRIED SMSA NEWENG MIDATL ENOCENT WNOCENT SOATL ESOCENT WSOCENT MT YR0-YR8 AGEQ AGEQSQ - -******1930-1939 dönemi için******** - -keep if COHORT>3000 & COHORT <3040 -ivregress 2sls LWKLYWGE (EDUC = QTR1) -ivregress 2sls LWKLYWGE YR0-YR8 RACE MARRIED SMSA NEWENG MIDATL ENOCENT WNOCENT SOATL ESOCENT WSOCENT MT AGEQ AGEQSQ (EDUC = QTR1YR0-QTR1YR9 QTR2YR0-QTR2YR9 QTR3YR0-QTR3YR9 YR0-YR8) -reg LWKLYWGE EDUC -reg LWKLYWGE EDUC RACE MARRIED SMSA NEWENG MIDATL ENOCENT WNOCENT SOATL ESOCENT WSOCENT MT YR0-YR8 AGEQ AGEQSQ -******************************* -*********Cevap d********** -use "C:\Users\kenan\Desktop\NEW7080 (1).dta" -rename v4 EDUC -rename v5 ENOCENT -rename v6 ESOCENT -rename v9 LWKLYWGE -rename v10 MARRIED -rename v11 MIDATL -rename v12 MT -rename v13 NEWENG -rename v16 CENSUS -rename v18 QOB -rename v19 RACE -rename v20 SMSA -rename v21 SOATL -rename v24 WNOCENT -rename v25 WSOCENT -rename v27 YOB -********** YOB dummies ********** -replace YOB=YOB-1900 if YOB >=1900 -foreach i of numlist 0/9 { -gen YR`i'=0 -replace YR`i'=1 if YOB==20+`i' | YOB==30+`i' | YOB==40+`i' -} -********** QOB dummies *********** -foreach i of numlist 1/4 { -gen QTR`i'=0 -replace QTR`i'=1 if QOB==`i' -} -********** QOB*YOB dummies ******** -foreach j of numlist 1/3 { -foreach i of numlist 0/9 { -gen QTR`j'YR`i'=QTR`j'*YR`i' -} -} -********** Select Particular Men Born ******** -gen COHORT=2029 -replace COHORT=3039 if YOB<=39 & YOB >=30 -replace COHORT=4049 if YOB<=49 & YOB >=40 -*********** -keep if COHORT>3000 & COHORT <3040 -*********Sekil V************** -tab QOB, gen(Q) -gen AGE=((79-YOB)*4+5-QOB)/4 -gen AGE2=AGE^2 -collapse EDUC LWKLYWGE Q*, by(AGE) -gen YOB = 80-AGE -label var EDUC "Years of education" -label var LWKLYWGE "Log Weekly Earnings" -label var AGE "age" -label var YOB "Year of Birth" -twoway (line EDUC YOB) (scatter EDUC YOB if Q1 == 1) (scatter EDUC YOB if Q2 == 1) (scatter EDUC YOB if Q3 == 1) (scatter EDUC YOB if Q4 == 1, msym(Oh)) -********************* -***********Cevap c)ZAYIF ARAÇ DEGISKEN****** -sort Q1 -by Q1: sum LWKLYWGE EDUC -reg LWKLYWGE Q1, robust -reg EDUC Q1, robust -*****COLUMN 1******* -reg LWKLYWGE EDUC, robust -outreg2 EDUC using "C:\Users\kenan\Desktop\Table64.xls", replace bdec(3) sdec(3) noaster word -********************* -*****FIRST STAGE**** -reg EDUC Q1 -testparm Q1 -local F = r(F) -*******COLUMN 2***** -ivregress 2sls LWKLYWGE (EDUC= Q1), robust -outreg2 EDUC using "C:\Users\kenan\Desktop\Table5.xls", append bdec(3) sdec(3) noaster word addstat (F-stat, `F') -****COLUMN 3*****0 -reg LWKLYWGE EDUC i.YOB, robust -outreg2 EDUC using "C:\Users\kenan\Desktop\Table5.xls", append bdec(3) sdec(3) noaster word -********************** -******FIRST STAGE***** -reg EDUC Q1 i.YOB -testparm Q1 -local F = r(F) -********COLUMN 4******* -ivregress 2sls LWKLYWGE (EDUC = Q1) i.YOB, robust -outreg2 s using "C:\Users\kenan\Desktop\Table5.xls", append bdec(3) sdec(3) noaster word addstat(F-stat, `F') -************************** -*****FIRST STAGE***** -reg EDUC Q2 Q3 Q4 i.YOB -testparm Q2 Q3 Q4 -local F = r(F) -********COLUMN 5******* -ivregress 2sls LWKLYWGE (EDUC = i.QOB) i.YOB, robust -outreg2 s using "C:\Users\kenan\Desktop\Table5.xls", append bdec(3) sdec(3) noaster word addstat(F-stat, `F') +use "C:\Users\kenan\Desktop\NEW7080 (1).dta" +rename v1 AGE +rename v2 AGEQ +rename v4 EDUC +rename v5 ENOCENT +rename v6 ESOCENT +rename v9 LWKLYWGE +rename v10 MARRIED +rename v11 MIDATL +rename v12 MT +rename v13 NEWENG +rename v16 CENSUS +rename v18 QOB +rename v19 RACE +rename v20 SMSA +rename v21 SOATL +rename v24 WNOCENT +rename v25 WSOCENT +rename v27 YOB +**********YOB dummies ********** +replace YOB=YOB-1900 if YOB >=1900 +foreach i of numlist 0/9 { +gen YR`i'=0 +replace YR`i'=1 if YOB==20+`i' | YOB==30+`i' | YOB==40+`i' +} +**********QOB dummies *********** +foreach i of numlist 1/4 { +gen QTR`i'=0 +replace QTR`i'=1 if QOB==`i' +} +********** QOB*YOB dummies ******** +foreach j of numlist 1/3 { +foreach i of numlist 0/9 { +gen QTR`j'YR`i'=QTR`j'*YR`i' +} +} +********** Select Particular Men Born ******** +gen COHORT=2029 +replace COHORT=3039 if YOB<=39 & YOB >=30 +replace COHORT=4049 if YOB<=49 & YOB >=40 +replace AGEQ=AGEQ-1900 if CENSUS==80 +gen AGEQSQ= AGEQ*AGEQ +******************* +**************Cevap a)********** +*********Tablo III KODLARI******** +********** Panel A******** +sum LWKLYWGE if QTR1==1 & COHORT==2029 +sum LWKLYWGE if QTR1!=1 & COHORT==2029 +sum EDUC if QTR1==1 & COHORT==2029 +sum EDUC if QTR1!=1 & COHORT==2029 + +reg LWKLYWGE QTR1 if COHORT==2029 +reg EDUC QTR1 if COHORT==2029 +sureg (eq1: LWKLYWGE QTR1 ) (eq2: EDUC QTR1 ) if COHORT==2029 +nlcom ratio: [eq1]_b[QTR1]/[eq2]_b[QTR1] +reg LWKLYWGE EDUC if COHORT==2029 +********** +********** Panel B*********** +sum LWKLYWGE if QTR1==1 & COHORT==3039 +sum LWKLYWGE if QTR1!=1 & COHORT==3039 +sum EDUC if QTR1==1 & COHORT==3039 +sum EDUC if QTR1!=1 & COHORT==3039 +reg LWKLYWGE QTR1 if COHORT==3039 +reg EDUC QTR1 if COHORT==3039 +sureg (eq1: LWKLYWGE QTR1 ) (eq2: EDUC QTR1 ) if COHORT==3039 +nlcom ratio: [eq1]_b[QTR1]/[eq2]_b[QTR1] +reg LWKLYWGE EDUC if COHORT==3039 + +********Cevap b)********* +******1920-1929 dönemi için******** +keep if COHORT < 2030 +ivregress 2sls LWKLYWGE (EDUC=QTR1) +ivregress 2sls LWKLYWGE YR0-YR8 RACE MARRIED SMSA NEWENG MIDATL ENOCENT WNOCENT SOATL ESOCENT WSOCENT MT AGEQ AGEQSQ (EDUC = QTR1YR0-QTR1YR9 QTR2YR0-QTR2YR9 QTR3YR0-QTR3YR9 YR0-YR8) +reg LWKLYWGE EDUC +reg LWKLYWGE EDUC RACE MARRIED SMSA NEWENG MIDATL ENOCENT WNOCENT SOATL ESOCENT WSOCENT MT YR0-YR8 AGEQ AGEQSQ + +******1930-1939 dönemi için******** + +keep if COHORT>3000 & COHORT <3040 +ivregress 2sls LWKLYWGE (EDUC = QTR1) +ivregress 2sls LWKLYWGE YR0-YR8 RACE MARRIED SMSA NEWENG MIDATL ENOCENT WNOCENT SOATL ESOCENT WSOCENT MT AGEQ AGEQSQ (EDUC = QTR1YR0-QTR1YR9 QTR2YR0-QTR2YR9 QTR3YR0-QTR3YR9 YR0-YR8) +reg LWKLYWGE EDUC +reg LWKLYWGE EDUC RACE MARRIED SMSA NEWENG MIDATL ENOCENT WNOCENT SOATL ESOCENT WSOCENT MT YR0-YR8 AGEQ AGEQSQ +******************************* +*********Cevap d********** +use "C:\Users\kenan\Desktop\NEW7080 (1).dta" +rename v4 EDUC +rename v5 ENOCENT +rename v6 ESOCENT +rename v9 LWKLYWGE +rename v10 MARRIED +rename v11 MIDATL +rename v12 MT +rename v13 NEWENG +rename v16 CENSUS +rename v18 QOB +rename v19 RACE +rename v20 SMSA +rename v21 SOATL +rename v24 WNOCENT +rename v25 WSOCENT +rename v27 YOB +********** YOB dummies ********** +replace YOB=YOB-1900 if YOB >=1900 +foreach i of numlist 0/9 { +gen YR`i'=0 +replace YR`i'=1 if YOB==20+`i' | YOB==30+`i' | YOB==40+`i' +} +********** QOB dummies *********** +foreach i of numlist 1/4 { +gen QTR`i'=0 +replace QTR`i'=1 if QOB==`i' +} +********** QOB*YOB dummies ******** +foreach j of numlist 1/3 { +foreach i of numlist 0/9 { +gen QTR`j'YR`i'=QTR`j'*YR`i' +} +} +********** Select Particular Men Born ******** +gen COHORT=2029 +replace COHORT=3039 if YOB<=39 & YOB >=30 +replace COHORT=4049 if YOB<=49 & YOB >=40 +*********** +keep if COHORT>3000 & COHORT <3040 +*********Sekil V************** +tab QOB, gen(Q) +gen AGE=((79-YOB)*4+5-QOB)/4 +gen AGE2=AGE^2 +collapse EDUC LWKLYWGE Q*, by(AGE) +gen YOB = 80-AGE +label var EDUC "Years of education" +label var LWKLYWGE "Log Weekly Earnings" +label var AGE "age" +label var YOB "Year of Birth" +twoway (line EDUC YOB) (scatter EDUC YOB if Q1 == 1) (scatter EDUC YOB if Q2 == 1) (scatter EDUC YOB if Q3 == 1) (scatter EDUC YOB if Q4 == 1, msym(Oh)) +********************* +***********Cevap c)ZAYIF ARAÇ DEGISKEN****** +sort Q1 +by Q1: sum LWKLYWGE EDUC +reg LWKLYWGE Q1, robust +reg EDUC Q1, robust +*****COLUMN 1******* +reg LWKLYWGE EDUC, robust +outreg2 EDUC using "C:\Users\kenan\Desktop\Table64.xls", replace bdec(3) sdec(3) noaster word +********************* +*****FIRST STAGE**** +reg EDUC Q1 +testparm Q1 +local F = r(F) +*******COLUMN 2***** +ivregress 2sls LWKLYWGE (EDUC= Q1), robust +outreg2 EDUC using "C:\Users\kenan\Desktop\Table5.xls", append bdec(3) sdec(3) noaster word addstat (F-stat, `F') +****COLUMN 3*****0 +reg LWKLYWGE EDUC i.YOB, robust +outreg2 EDUC using "C:\Users\kenan\Desktop\Table5.xls", append bdec(3) sdec(3) noaster word +********************** +******FIRST STAGE***** +reg EDUC Q1 i.YOB +testparm Q1 +local F = r(F) +********COLUMN 4******* +ivregress 2sls LWKLYWGE (EDUC = Q1) i.YOB, robust +outreg2 s using "C:\Users\kenan\Desktop\Table5.xls", append bdec(3) sdec(3) noaster word addstat(F-stat, `F') +************************** +*****FIRST STAGE***** +reg EDUC Q2 Q3 Q4 i.YOB +testparm Q2 Q3 Q4 +local F = r(F) +********COLUMN 5******* +ivregress 2sls LWKLYWGE (EDUC = i.QOB) i.YOB, robust +outreg2 s using "C:\Users\kenan\Desktop\Table5.xls", append bdec(3) sdec(3) noaster word addstat(F-stat, `F')