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Tarefa paper_repro.angrist_krueger_1991.tab5_c2.design

paper_reproagentT3designépoca 1, tentativa 1Execução: 20261015T165744Z-suite-paper_repro-scripted-def9df

Veredito

passouPassou em todas as verificações obrigatórias.

Família do método (das chamadas de ferramentas): iv (two-stage least squares)

Pergunta feita ao analista

Is the earnings gain from schooling causal? For men born in the United States in 1930-1939, observed in the 1980 Census, estimate the causal effect of a year of education on log weekly earnings, using a source of variation in schooling that is unrelated to ability or family background.

Resposta

Estimativa (infer.iv_2sls): coef.educ = 0,08912.

Valores esperados e de onde vêm

angrist_krueger_1991.tab5_c2.software

Fonte
linearmodels 7.0: the reference specification of angrist_krueger_1991 tab5_c2 (infer.iv_2sls, figure 'coef.educ') on an independent code path
Tipo
software
Localização
angrist_krueger_1991: Table V (OLS and TSLS estimates of the return to education for men born 1930-1939: 1980 Census), column (2) TSLS, row 'Years of education'
Valor
0,08911550.08911545635601215 (se 0,01611010.016110089092885405)
Conferido por
execução de software · IV2SLS(dependent=lwklywge, exog=[const, yob_30, yob_31, yob_32, yob_33, yob_34, yob_35, yob_36, yob_37, yob_38], endog=['educ'], instruments=['qtr1_yob30', 'qtr1_yob31', 'qtr1_yob32', 'qtr1_yob33', 'qtr1_yob34', 'qtr1_yob35', 'qtr1_yob36', 'qtr1_yob37', 'qtr1_yob38', 'qtr1_yob39', 'qtr2_yob30', 'qtr2_yob31', 'qtr2_yob32', 'qtr2_yob33', 'qtr2_yob34', 'qtr2_yob35', 'qtr2_yob36', 'qtr2_yob37', 'qtr2_yob38', 'qtr2_yob39', 'qtr3_yob30', 'qtr3_yob31', 'qtr3_yob32', 'qtr3_yob33', 'qtr3_yob34', 'qtr3_yob35', 'qtr3_yob36', 'qtr3_yob37', 'qtr3_yob38', 'qtr3_yob39']).fit(cov_type='unadjusted', debiased=True) on asciiqob (asciiqob.txt of the file pinned at sha256 0b6c505e52fd6c9f6194c356c91688acf2f8937b5023a84e754e942c9a2f2dcc, after its 32 declared transforms); n_obs = 329509. The tool infer.iv_2sls (magi_infer, numpy) does not call linearmodels. Written by scripts/paper_repro_reference.py.
Implementação
independente da ferramenta
Endereço
https://pypi.org/project/linearmodels/7.0/
  • #9 figura da resposta próxima: 0,08911550.08911545635601215 · relativa 0.000001 · absoluta 1.6110089092885403e-8
  • #10 figura da resposta próxima: 0,01611010.016110089092885405 · relativa 0.000001 · absoluta 1.6110089092885403e-8

angrist_krueger_1991.tab5_c2.paper

Fonte
Angrist, J. D. and Krueger, A. B. (1991). Does Compulsory School Attendance Affect Schooling and Earnings? Quarterly Journal of Economics 106(4): 979-1014.
Tipo
paper
Localização
Table V (OLS and TSLS estimates of the return to education for men born 1930-1939: 1980 Census), column (2) TSLS, row 'Years of education'
Página
1000
Trecho
Years of education 0.0891 (0.0161)
Valor como publicado
0.0891
Erro-padrão como publicado
0.0161
Valor
0,08910.0891 (se 0,01610.0161) log points of weekly earnings per year of education
Conferido por
fonte primária · Read on 2026-10-15 from the JSTOR copy of the QJE article on a WWU course page; Table V on PDF page 23 (printed page 1000), from the rendered page image. Notes: 'Instruments are a full set of quarter-of-birth times year-of-birth interactions'; chi-square [dof] 25.4 [29], i.e. 30 excluded instruments. The authors' posted 'QOB Table V.do' instruments EDUC with QTR1-QTR3 times YR20-YR29 (30 interactions) and includes YR20-YR28; its posted log QOB_V.log prints .0891155 (.0161098) on 329,509 rows.
sha256 da cópia lida
30ae8da0ac7b02e59084b9d21c23843cc39dfe031e9489bf95c41ec6762887b2 (identifica a cópia lida, não um arquivo canônico)
Endereço
https://doi.org/10.2307/2937954
Licença
Copyright of the publisher; cited, not reproduced.
  • #11 figura da resposta próxima: 0,08910.0891 · published_cell d=4 · absoluta 0.000050001000000000005
  • #12 figura da resposta próxima: 0,01610.0161 · published_cell d=4 (the SE as printed) · absoluta 0.000050001000000000005

Verificações

Cada verificação, o que esperava, o que observou e a chamada que leu
#VerificaçãoObrigatóriaResultadoEsperadoObservadoTolerânciaFonteChamada
0resposta com lastro
every number backed
obrigatóriapassou—[]———
1figura da resposta escolhida
answer figure call_c1f07f1f:coef.educ (infer.iv_2sls)
obrigatóriapassou—"call_c1f07f1f:coef.educ"——call_c1f07f1f
2ferramenta chamada
answer call is infer.iv_2sls
obrigatóriapassou—"infer.iv_2sls"——call_c1f07f1f
3argumento igual
infer.iv_2sls.y = 'lwklywge'
obrigatóriapassou"lwklywge""lwklywge"——call_c1f07f1f
4argumento igual
infer.iv_2sls.endog[0] = 'educ'
obrigatóriapassou"educ""educ"——call_c1f07f1f
5argumento igual
infer.iv_2sls.y = 'lwklywge'
registradapassou"lwklywge""lwklywge"——call_c1f07f1f
6argumento igual
infer.iv_2sls.endog = ['educ']
registradapassou["educ"]["educ"]——call_c1f07f1f
7argumento igual
infer.iv_2sls.instruments = ['qtr1_yob30', 'qtr1_yob31', 'qtr1_yob32', 'qtr1_yob33', 'qtr1_yob34', 'qtr1_yob35', 'qtr1_yob36', 'qtr1_yob37', 'qtr1_yob38', 'qtr1_yob39', 'qtr2_yob30', 'qtr2_yob31', 'qtr2_yob32', 'qtr2_yob33', 'qtr2_yob34', 'qtr2_yob35', 'qtr2_yob36', 'qtr2_yob37', 'qtr2_yob38', 'qtr2_yob39', 'qtr3_yob30', 'qtr3_yob31', 'qtr3_yob32', 'qtr3_yob33', 'qtr3_yob34', 'qtr3_yob35', 'qtr3_yob36', 'qtr3_yob37', 'qtr3_yob38', 'qtr3_yob39']
registradapassou["qtr1_yob30","qtr1_yob31","qtr1_yob32","qtr1_yob33","qtr1_yob34","qtr1_yob35","qtr1_yob36","qtr1_yob37","qtr1_yob38","qtr1_yob39","qtr2_yob30","qtr2_yob31","qtr2_yob32","qtr2_yob33","qtr2_yob34","qtr2_yob35","qtr2_yob36","qtr2_yob37","qtr2_yob38","qtr2_yob39","qtr3_yob30","qtr3_yob31","qtr3_yob32","qtr3_yob33","qtr3_yob34","qtr3_yob35","qtr3_yob36","qtr3_yob37","qtr3_yob38","qtr3_yob39"]["qtr1_yob30","qtr1_yob31","qtr1_yob32","qtr1_yob33","qtr1_yob34","qtr1_yob35","qtr1_yob36","qtr1_yob37","qtr1_yob38","qtr1_yob39","qtr2_yob30","qtr2_yob31","qtr2_yob32","qtr2_yob33","qtr2_yob34","qtr2_yob35","qtr2_yob36","qtr2_yob37","qtr2_yob38","qtr2_yob39","qtr3_yob30","qtr3_yob31","qtr3_yob32","qtr3_yob33","qtr3_yob34","qtr3_yob35","qtr3_yob36","qtr3_yob37","qtr3_yob38","qtr3_yob39"]——call_c1f07f1f
8diagnóstico
329509 vs 329509
registradapassou329.509329509329.509329509default rel 1e-6 (abs floor 1e-6)—call_c1f07f1f
9figura da resposta próxima
0.08911545635 vs 0.08911545635601215
registradapassou0,08911550.089115456356012150,08911550.08911545635097498relativa 0.000001 · absoluta 1.6110089092885403e-8angrist_krueger_1991.tab5_c2.softwarecall_c1f07f1f
10figura da resposta próxima
0.01611008909 vs 0.016110089092885405
registradapassou0,01611010.0161100890928854050,01611010.01611008909296629relativa 0.000001 · absoluta 1.6110089092885403e-8angrist_krueger_1991.tab5_c2.softwarecall_c1f07f1f
11figura da resposta próxima
0.08911545635 vs 0.0891
registradapassou0,08910.08910,08911550.08911545635097498published_cell d=4 · absoluta 0.000050001000000000005angrist_krueger_1991.tab5_c2.papercall_c1f07f1f
12figura da resposta próxima
0.01611008909 vs 0.0161
registradapassou0,01610.01610,01611010.01611008909296629published_cell d=4 (the SE as printed) · absoluta 0.000050001000000000005angrist_krueger_1991.tab5_c2.papercall_c1f07f1f

Caminho de referência e caminho do agente

A chamada de referência ao lado da chamada que deu a resposta, argumento por argumento.

a tarefa T1 do mesmo alvo (paper_repro.angrist_krueger_1991.tab5_c2.tool)

Referência: infer.iv_2slsChamada do agente: infer.iv_2sls (call_c1f07f1f)igual
Argumentos da referência e do agente
ArgumentoReferênciaAgente
cluster——não fixado pela referência
dataset"asciiqob""asciiqob"igual
endog["educ"]["educ"]igual
exog["yob_30","yob_31","yob_32","yob_33","yob_34","yob_35","yob_36","yob_37","yob_38"]["yob_30","yob_31","yob_32","yob_33","yob_34","yob_35","yob_36","yob_37","yob_38"]igual
instruments["qtr1_yob30","qtr1_yob31","qtr1_yob32","qtr1_yob33","qtr1_yob34","qtr1_yob35","qtr1_yob36","qtr1_yob37","qtr1_yob38","qtr1_yob39","qtr2_yob30","qtr2_yob31","qtr2_yob32","qtr2_yob33","qtr2_yob34","qtr2_yob35","qtr2_yob36","qtr2_yob37","qtr2_yob38","qtr2_yob39","qtr3_yob30","qtr3_yob31","qtr3_yob32","qtr3_yob33","qtr3_yob34","qtr3_yob35","qtr3_yob36","qtr3_yob37","qtr3_yob38","qtr3_yob39"]["qtr1_yob30","qtr1_yob31","qtr1_yob32","qtr1_yob33","qtr1_yob34","qtr1_yob35","qtr1_yob36","qtr1_yob37","qtr1_yob38","qtr1_yob39","qtr2_yob30","qtr2_yob31","qtr2_yob32","qtr2_yob33","qtr2_yob34","qtr2_yob35","qtr2_yob36","qtr2_yob37","qtr2_yob38","qtr2_yob39","qtr3_yob30","qtr3_yob31","qtr3_yob32","qtr3_yob33","qtr3_yob34","qtr3_yob35","qtr3_yob36","qtr3_yob37","qtr3_yob38","qtr3_yob39"]igual
level—0,950.95não fixado pela referência
se"classical""classical"igual
subset——não fixado pela referência
y"lwklywge""lwklywge"igual

Trajetória

Cada evento na ordem em que aconteceu: turnos do modelo, chamadas de ferramentas, guardas, transformações e pontuação.

  1. 0Início

    Is the earnings gain from schooling causal? For men born in the United States in 1930-1939, observed in the 1980 Census, estimate the causal effect of a year of education on log weekly earnings, using a source of variation in schooling that is unrelated to ability or family background.

    asciiqob (agent)

    Joshua Angrist's minimal extract of the 1980 Census used by Angrist and Krueger (1991), 'Does Compulsory School Attendance Affect Schooling and Earnings?' (asciiqob.txt in asciiqob.zip): one row per man born in the United States in 1930-1939, from the 5 percent public-use sample of the 1980 Census (329,509 rows). Columns: lwklywge, the log of weekly earnings in 1979; educ, years of education; yob, year of birth (30 for 1930 to 39 for 1939); qob, quarter of birth (1 to 4); pob, state of birth (census code). Added by the declared transforms: yob_30 to yob_39, one indicator per year of birth; qtr_1 to qtr_4, one indicator per quarter of birth; and qtr1_yob30 to qtr3_yob39, thirty columns, each the product of the indicator for quarter of birth 1, 2 or 3 and the indicator for one year of birth (qtr2_yob35 is 1 for men born in the second quarter of 1935).

    file 0b6c505e52fd6c9f6194c356c91688acf2f8937b5023a84e754e942c9a2f2dcc · frame —
    1. dummies {"column":"yob","drop_first":false,"prefix":"yob"}
    2. dummies {"column":"qob","drop_first":false,"prefix":"qtr"}
    3. derive {"args":{"columns":["qtr_1","yob_30"]},"name":"qtr1_yob30","op":"interaction"}
    4. derive {"args":{"columns":["qtr_1","yob_31"]},"name":"qtr1_yob31","op":"interaction"}
    5. derive {"args":{"columns":["qtr_1","yob_32"]},"name":"qtr1_yob32","op":"interaction"}
    6. derive {"args":{"columns":["qtr_1","yob_33"]},"name":"qtr1_yob33","op":"interaction"}
    7. derive {"args":{"columns":["qtr_1","yob_34"]},"name":"qtr1_yob34","op":"interaction"}
    8. derive {"args":{"columns":["qtr_1","yob_35"]},"name":"qtr1_yob35","op":"interaction"}
    9. derive {"args":{"columns":["qtr_1","yob_36"]},"name":"qtr1_yob36","op":"interaction"}
    10. derive {"args":{"columns":["qtr_1","yob_37"]},"name":"qtr1_yob37","op":"interaction"}
    11. derive {"args":{"columns":["qtr_1","yob_38"]},"name":"qtr1_yob38","op":"interaction"}
    12. derive {"args":{"columns":["qtr_1","yob_39"]},"name":"qtr1_yob39","op":"interaction"}
    13. derive {"args":{"columns":["qtr_2","yob_30"]},"name":"qtr2_yob30","op":"interaction"}
    14. derive {"args":{"columns":["qtr_2","yob_31"]},"name":"qtr2_yob31","op":"interaction"}
    15. derive {"args":{"columns":["qtr_2","yob_32"]},"name":"qtr2_yob32","op":"interaction"}
    16. derive {"args":{"columns":["qtr_2","yob_33"]},"name":"qtr2_yob33","op":"interaction"}
    17. derive {"args":{"columns":["qtr_2","yob_34"]},"name":"qtr2_yob34","op":"interaction"}
    18. derive {"args":{"columns":["qtr_2","yob_35"]},"name":"qtr2_yob35","op":"interaction"}
    19. derive {"args":{"columns":["qtr_2","yob_36"]},"name":"qtr2_yob36","op":"interaction"}
    20. derive {"args":{"columns":["qtr_2","yob_37"]},"name":"qtr2_yob37","op":"interaction"}
    21. derive {"args":{"columns":["qtr_2","yob_38"]},"name":"qtr2_yob38","op":"interaction"}
    22. derive {"args":{"columns":["qtr_2","yob_39"]},"name":"qtr2_yob39","op":"interaction"}
    23. derive {"args":{"columns":["qtr_3","yob_30"]},"name":"qtr3_yob30","op":"interaction"}
    24. derive {"args":{"columns":["qtr_3","yob_31"]},"name":"qtr3_yob31","op":"interaction"}
    25. derive {"args":{"columns":["qtr_3","yob_32"]},"name":"qtr3_yob32","op":"interaction"}
    26. derive {"args":{"columns":["qtr_3","yob_33"]},"name":"qtr3_yob33","op":"interaction"}
    27. derive {"args":{"columns":["qtr_3","yob_34"]},"name":"qtr3_yob34","op":"interaction"}
    28. derive {"args":{"columns":["qtr_3","yob_35"]},"name":"qtr3_yob35","op":"interaction"}
    29. derive {"args":{"columns":["qtr_3","yob_36"]},"name":"qtr3_yob36","op":"interaction"}
    30. derive {"args":{"columns":["qtr_3","yob_37"]},"name":"qtr3_yob37","op":"interaction"}
    31. derive {"args":{"columns":["qtr_3","yob_38"]},"name":"qtr3_yob38","op":"interaction"}
    32. derive {"args":{"columns":["qtr_3","yob_39"]},"name":"qtr3_yob39","op":"interaction"}
  2. 1Transformação
    asciiqob · dummies {"column":"yob","drop_first":false,"prefix":"yob"}
    329509 → 329509 linhas
    Frame antes → depois: 845a36d4dcec → d4b277b4997b
  3. 2Transformação
    asciiqob · dummies {"column":"qob","drop_first":false,"prefix":"qtr"}
    329509 → 329509 linhas
    Frame antes → depois: d4b277b4997b → 2c53c053bf00
  4. 3Transformação
    asciiqob · derive {"args":{"columns":["qtr_1","yob_30"]},"name":"qtr1_yob30","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: 2c53c053bf00 → cf52bf944241
  5. 4Transformação
    asciiqob · derive {"args":{"columns":["qtr_1","yob_31"]},"name":"qtr1_yob31","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: cf52bf944241 → c572825a7957
  6. 5Transformação
    asciiqob · derive {"args":{"columns":["qtr_1","yob_32"]},"name":"qtr1_yob32","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: c572825a7957 → f423f0515e53
  7. 6Transformação
    asciiqob · derive {"args":{"columns":["qtr_1","yob_33"]},"name":"qtr1_yob33","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: f423f0515e53 → 53a56d68c9d1
  8. 7Transformação
    asciiqob · derive {"args":{"columns":["qtr_1","yob_34"]},"name":"qtr1_yob34","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: 53a56d68c9d1 → 4a3cff9083bb
  9. 8Transformação
    asciiqob · derive {"args":{"columns":["qtr_1","yob_35"]},"name":"qtr1_yob35","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: 4a3cff9083bb → 373b8fd4038e
  10. 9Transformação
    asciiqob · derive {"args":{"columns":["qtr_1","yob_36"]},"name":"qtr1_yob36","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: 373b8fd4038e → e7e4772d7f72
  11. 10Transformação
    asciiqob · derive {"args":{"columns":["qtr_1","yob_37"]},"name":"qtr1_yob37","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: e7e4772d7f72 → 493704cb4202
  12. 11Transformação
    asciiqob · derive {"args":{"columns":["qtr_1","yob_38"]},"name":"qtr1_yob38","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: 493704cb4202 → 459fa0f19579
  13. 12Transformação
    asciiqob · derive {"args":{"columns":["qtr_1","yob_39"]},"name":"qtr1_yob39","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: 459fa0f19579 → 85c2fdc43e1d
  14. 13Transformação
    asciiqob · derive {"args":{"columns":["qtr_2","yob_30"]},"name":"qtr2_yob30","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: 85c2fdc43e1d → 221b8d8c4186
  15. 14Transformação
    asciiqob · derive {"args":{"columns":["qtr_2","yob_31"]},"name":"qtr2_yob31","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: 221b8d8c4186 → 318603958de3
  16. 15Transformação
    asciiqob · derive {"args":{"columns":["qtr_2","yob_32"]},"name":"qtr2_yob32","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: 318603958de3 → 069525d0a1fe
  17. 16Transformação
    asciiqob · derive {"args":{"columns":["qtr_2","yob_33"]},"name":"qtr2_yob33","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: 069525d0a1fe → 64ef72351a15
  18. 17Transformação
    asciiqob · derive {"args":{"columns":["qtr_2","yob_34"]},"name":"qtr2_yob34","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: 64ef72351a15 → 0c272ae20586
  19. 18Transformação
    asciiqob · derive {"args":{"columns":["qtr_2","yob_35"]},"name":"qtr2_yob35","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: 0c272ae20586 → 7856b1936015
  20. 19Transformação
    asciiqob · derive {"args":{"columns":["qtr_2","yob_36"]},"name":"qtr2_yob36","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: 7856b1936015 → 06252be82053
  21. 20Transformação
    asciiqob · derive {"args":{"columns":["qtr_2","yob_37"]},"name":"qtr2_yob37","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: 06252be82053 → 4a442f63e865
  22. 21Transformação
    asciiqob · derive {"args":{"columns":["qtr_2","yob_38"]},"name":"qtr2_yob38","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: 4a442f63e865 → 1a895d8e4ad2
  23. 22Transformação
    asciiqob · derive {"args":{"columns":["qtr_2","yob_39"]},"name":"qtr2_yob39","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: 1a895d8e4ad2 → 7fd62953f64c
  24. 23Transformação
    asciiqob · derive {"args":{"columns":["qtr_3","yob_30"]},"name":"qtr3_yob30","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: 7fd62953f64c → fbb95e831358
  25. 24Transformação
    asciiqob · derive {"args":{"columns":["qtr_3","yob_31"]},"name":"qtr3_yob31","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: fbb95e831358 → 3c39c77165ba
  26. 25Transformação
    asciiqob · derive {"args":{"columns":["qtr_3","yob_32"]},"name":"qtr3_yob32","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: 3c39c77165ba → 7e4ccc705689
  27. 26Transformação
    asciiqob · derive {"args":{"columns":["qtr_3","yob_33"]},"name":"qtr3_yob33","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: 7e4ccc705689 → e14e138d365d
  28. 27Transformação
    asciiqob · derive {"args":{"columns":["qtr_3","yob_34"]},"name":"qtr3_yob34","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: e14e138d365d → efea1aed1a08
  29. 28Transformação
    asciiqob · derive {"args":{"columns":["qtr_3","yob_35"]},"name":"qtr3_yob35","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: efea1aed1a08 → 889c869c49df
  30. 29Transformação
    asciiqob · derive {"args":{"columns":["qtr_3","yob_36"]},"name":"qtr3_yob36","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: 889c869c49df → 4690bc1fd2a9
  31. 30Transformação
    asciiqob · derive {"args":{"columns":["qtr_3","yob_37"]},"name":"qtr3_yob37","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: 4690bc1fd2a9 → 73cf0a1d91c6
  32. 31Transformação
    asciiqob · derive {"args":{"columns":["qtr_3","yob_38"]},"name":"qtr3_yob38","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: 73cf0a1d91c6 → adbbeec74207
  33. 32Transformação
    asciiqob · derive {"args":{"columns":["qtr_3","yob_39"]},"name":"qtr3_yob39","op":"interaction"}
    329509 → 329509 linhas
    Frame antes → depois: adbbeec74207 → 654074d5953a
  34. 33Turno do modelo
    call_102473e2referenceFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache
    Texto visível

    Table V, column (2): 2SLS of the log weekly wage on years of education, instrumented by the 30 quarter-of-birth (1-3) by year-of-birth interactions, with nine year-of-birth dummies (the authors' 'QOB Table V.do': ivregress 2sls, classical errors).

    Chamadas pedidas
    • infer.iv_2sls
      {
        "dataset": "asciiqob",
        "endog": [
          "educ"
        ],
        "exog": [
          "yob_30",
          "yob_31",
          "yob_32",
          "yob_33",
          "yob_34",
          "yob_35",
          "yob_36",
          "yob_37",
          "yob_38"
        ],
        "instruments": [
          "qtr1_yob30",
          "qtr1_yob31",
          "qtr1_yob32",
          "qtr1_yob33",
          "qtr1_yob34",
          "qtr1_yob35",
          "qtr1_yob36",
          "qtr1_yob37",
          "qtr1_yob38",
          "qtr1_yob39",
          "qtr2_yob30",
          "qtr2_yob31",
          "qtr2_yob32",
          "qtr2_yob33",
          "qtr2_yob34",
          "qtr2_yob35",
          "qtr2_yob36",
          "qtr2_yob37",
          "qtr2_yob38",
          "qtr2_yob39",
          "qtr3_yob30",
          "qtr3_yob31",
          "qtr3_yob32",
          "qtr3_yob33",
          "qtr3_yob34",
          "qtr3_yob35",
          "qtr3_yob36",
          "qtr3_yob37",
          "qtr3_yob38",
          "qtr3_yob39"
        ],
        "se": "classical",
        "y": "lwklywge"
      }
  35. 34Ferramenta
    infer.iv_2slsv0.1.0call_c1f07f1fdecidido pelo modeloreexecutável

    Motivo: Table V, column (2): 2SLS of the log weekly wage on years of education, instrumented by the 30 quarter-of-birth (1-3) by year-of-birth interactions, with nine year-of-birth dummies (the authors' 'QOB Table V.do': ivregress 2sls, classical errors).

    Argumentos
    {
      "cluster": null,
      "dataset": "asciiqob",
      "endog": [
        "educ"
      ],
      "exog": [
        "yob_30",
        "yob_31",
        "yob_32",
        "yob_33",
        "yob_34",
        "yob_35",
        "yob_36",
        "yob_37",
        "yob_38"
      ],
      "instruments": [
        "qtr1_yob30",
        "qtr1_yob31",
        "qtr1_yob32",
        "qtr1_yob33",
        "qtr1_yob34",
        "qtr1_yob35",
        "qtr1_yob36",
        "qtr1_yob37",
        "qtr1_yob38",
        "qtr1_yob39",
        "qtr2_yob30",
        "qtr2_yob31",
        "qtr2_yob32",
        "qtr2_yob33",
        "qtr2_yob34",
        "qtr2_yob35",
        "qtr2_yob36",
        "qtr2_yob37",
        "qtr2_yob38",
        "qtr2_yob39",
        "qtr3_yob30",
        "qtr3_yob31",
        "qtr3_yob32",
        "qtr3_yob33",
        "qtr3_yob34",
        "qtr3_yob35",
        "qtr3_yob36",
        "qtr3_yob37",
        "qtr3_yob38",
        "qtr3_yob39"
      ],
      "level": 0.95,
      "se": "classical",
      "subset": null,
      "y": "lwklywge"
    }
    Figuras call_c1f07f1f
    ChaveValorValor brutoErro-padrãoIC
    coef.educ
    2SLS effect of educ on lwklywge
    0,0891155 0.089115456350974980,01611010.016110089092966290,0575401 – 0,120691
    Diagnósticos
    • first_stage_F.educ = 4,907074.907068900445309
    • partial_r2.educ = 0,0004466170.0004466165850589565
    • weak_instrument = true
    • overid_p = 0,6552610.6552608024512252
    • sargan = 25,439425.439387654762992
    • sargan_df = 2929
    • n_obs = 329.509329509
    • se_type = "classical"
    • n_clusters = —
    Tabelas (3)
    {
      "coefficients": [
        {
          "ci_high": 5.145673344398731,
          "ci_low": 4.322726441555527,
          "coef": 4.734199892977129,
          "p": 1.6197733596808568e-112,
          "se": 0.2099385209000278,
          "t": 22.550410818753665,
          "term": "Intercept"
        },
        {
          "ci_high": 0.0790234823803597,
          "ci_low": 0.03803067580515462,
          "coef": 0.05852707909275716,
          "p": 2.186943635875741e-8,
          "se": 0.010457502361582108,
          "t": 5.5966594191524175,
          "term": "yob_30"
        },
        {
          "ci_high": 0.06653789078443655,
          "ci_low": 0.03275366055223902,
          "coef": 0.049645775668337784,
          "p": 8.402007890648315e-9,
          "se": 0.008618552788994342,
          "t": 5.760337829772777,
          "term": "yob_31"
        },
        {
          "ci_high": 0.05632558371941518,
          "ci_low": 0.0246679027865398,
          "coef": 0.04049674325297749,
          "p": 5.322127727975817e-7,
          "se": 0.008076057747117086,
          "t": 5.014419723216272,
          "term": "yob_32"
        },
        {
          "ci_high": 0.05126430317091755,
          "ci_low": 0.022198787603013116,
          "coef": 0.03673154538696533,
          "p": 7.280376625482111e-7,
          "se": 0.007414781350340894,
          "t": 4.953827179985098,
          "term": "yob_33"
        },
        {
          "ci_high": 0.04647324297768207,
          "ci_low": 0.01900535082607492,
          "coef": 0.0327392969018785,
          "p": 0.0000029807256524072373,
          "se": 0.007007218364425381,
          "t": 4.6722244404557305,
          "term": "yob_34"
        },
        {
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          "coef": 0.0196996283846792,
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          "t": 3.1293247953805463,
          "term": "yob_35"
        },
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          "coef": 0.019765413172859313,
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          "se": 0.0057559931573096966,
          "t": 3.4338840635622825,
          "term": "yob_36"
        },
        {
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          "coef": 0.013709615177205136,
          "p": 0.009056306404146239,
          "se": 0.005252853450906754,
          "t": 2.609936733498355,
          "term": "yob_37"
        },
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          "ci_high": 0.021481765608160248,
          "ci_low": 0.0024814511940856217,
          "coef": 0.011981608401122935,
          "p": 0.013439544603007553,
          "se": 0.004847090244759461,
          "t": 2.471917747782211,
          "term": "yob_38"
        },
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          "coef": 0.08911545635097498,
          "p": 3.1746317685400635e-8,
          "se": 0.01611008909296629,
          "t": 5.531655091211324,
          "term": "educ"
        }
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      "first_stage": [
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          "coef": -0.34427048224888823,
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          "instrument": "qtr1_yob30",
          "p": 1.5334104886584053e-11,
          "se": 0.05104129427339284,
          "t": -6.744940290990073
        },
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        },
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          "coef": -0.1931803931507642,
          "endog": "educ",
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      "reduced_form": [
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        },
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          "t": -0.7614670345940894
        },
        {
          "ci_high": 0.030199740090564895,
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          "t": 0.8661947151557491
        },
        {
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        },
        {
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        },
        {
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        },
        {
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        {
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        {
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        {
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    }
    Digests dos dados
    asciiqob 654074d5953a60c49422fd28f157a9ede3a844493e1280ba284d386a05958cf7
    sha256 do resultado
    2f144bd7d7632da6a484a290783956e9cd90bf18136655a16b8fea99e04f6dbc
  36. 35Turno do modelo
    call_dd1273aareferenceFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache
    Chamadas pedidas
    • submit_answer (meta-ferramenta)
      {
        "answer": "Estimativa (infer.iv_2sls): coef.educ = 0,08912.",
        "caveats": [],
        "figure_refs": [
          "call_c1f07f1f:coef.educ"
        ]
      }
  37. 36Guarda
    resposta aceita
    Números encontrados
    0,08912
    Sem lastro
    —
    Não citados
    —
    1 nova(s) tentativa(s) restante(s)
  38. 37Resposta

    Estimativa (infer.iv_2sls): coef.educ = 0,08912.

    Figuras citadas: call_c1f07f1f:coef.educ · Parada: answered
    Figura da resposta: call_c1f07f1f:coef.educ = 0,08911550.08911545635097498 (se 0,01611010.01611008909296629)
  39. 38Pontuação
    #0resposta com lastropassouobrigatóriaevery number backed
  40. 39Pontuação
    #1figura da resposta escolhidapassouobrigatóriaanswer figure call_c1f07f1f:coef.educ (infer.iv_2sls)
  41. 40Pontuação
    #2ferramenta chamadapassouobrigatóriaanswer call is infer.iv_2sls
  42. 41Pontuação
    #3argumento igualpassouobrigatóriainfer.iv_2sls.y = 'lwklywge'
  43. 42Pontuação
    #4argumento igualpassouobrigatóriainfer.iv_2sls.endog[0] = 'educ'
  44. 43Pontuação
    #5argumento igualpassouregistradainfer.iv_2sls.y = 'lwklywge'
  45. 44Pontuação
    #6argumento igualpassouregistradainfer.iv_2sls.endog = ['educ']
  46. 45Pontuação
    #7argumento igualpassouregistradainfer.iv_2sls.instruments = ['qtr1_yob30', 'qtr1_yob31', 'qtr1_yob32', 'qtr1_yob33', 'qtr1_yob34', 'qtr1_yob35', 'qtr1_yob36', 'qtr1_yob37', 'qtr1_yob38', 'qtr1_yob39', 'qtr2_yob30', 'qtr2_yob31', 'qtr2_yob32', 'qtr2_yob33', 'qtr2_yob34', 'qtr2_yob35', 'qtr2_yob36', 'qtr2_yob37', 'qtr2_yob38', 'qtr2_yob39', 'qtr3_yob30', 'qtr3_yob31', 'qtr3_yob32', 'qtr3_yob33', 'qtr3_yob34', 'qtr3_yob35', 'qtr3_yob36', 'qtr3_yob37', 'qtr3_yob38', 'qtr3_yob39']
  47. 46Pontuação
    #8diagnósticopassouregistrada329509 vs 329509
  48. 47Pontuação
    #9figura da resposta próximapassouregistrada0.08911545635 vs 0.08911545635601215
  49. 48Pontuação
    #10figura da resposta próximapassouregistrada0.01611008909 vs 0.016110089092885405
  50. 49Pontuação
    #11figura da resposta próximapassouregistrada0.08911545635 vs 0.0891
  51. 50Pontuação
    #12figura da resposta próximapassouregistrada0.01611008909 vs 0.0161

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