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Tarefa paper_repro.angrist_krueger_1991.tab5_c2.tool

paper_reprotoolT1publicépoca 1, tentativa 1Execução: 20261015T165744Z-suite-paper_repro-scripted-def9df

Veredito

passouPassou em todas as verificações obrigatórias.
Calculado pelo agente
coef.educ =0,08911550.08911545635097498
2SLS effect of educ on lwklywge
via infer.iv_2sls (call_263bb148)
Valor esperado (gabarito)
coef.educ =0,08911550.08911545635601215
linearmodels 7.0: the reference specification of angrist_krueger_1991 tab5_c2 (infer.iv_2sls, figure 'coef.educ') on an independent code path
Como foi validado
4 de 4 verificações obrigatórias aprovadas
relativa 0.000001 · absoluta 1.6110089092885403e-8

Pergunta feita ao analista

Tarefa de ferramenta: nenhuma pergunta; a especificação de referência é chamada direto.

Como o agente resolveu e como foi validado

Resumo passo a passo do que o agente executou, por que o caminho está correto e como cada verificação conferiu o resultado.

  1. 1Preparação da base de dados
    asciiqob— 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).
    Transformação "dummies" aplicada à base "asciiqob" (329509 → 329509 linhas). {"column":"yob","drop_first":false,"prefix":"yob"}
    Transformação "dummies" aplicada à base "asciiqob" (329509 → 329509 linhas). {"column":"qob","drop_first":false,"prefix":"qtr"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_1","yob_30"]},"name":"qtr1_yob30","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_1","yob_31"]},"name":"qtr1_yob31","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_1","yob_32"]},"name":"qtr1_yob32","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_1","yob_33"]},"name":"qtr1_yob33","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_1","yob_34"]},"name":"qtr1_yob34","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_1","yob_35"]},"name":"qtr1_yob35","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_1","yob_36"]},"name":"qtr1_yob36","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_1","yob_37"]},"name":"qtr1_yob37","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_1","yob_38"]},"name":"qtr1_yob38","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_1","yob_39"]},"name":"qtr1_yob39","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_2","yob_30"]},"name":"qtr2_yob30","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_2","yob_31"]},"name":"qtr2_yob31","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_2","yob_32"]},"name":"qtr2_yob32","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_2","yob_33"]},"name":"qtr2_yob33","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_2","yob_34"]},"name":"qtr2_yob34","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_2","yob_35"]},"name":"qtr2_yob35","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_2","yob_36"]},"name":"qtr2_yob36","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_2","yob_37"]},"name":"qtr2_yob37","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_2","yob_38"]},"name":"qtr2_yob38","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_2","yob_39"]},"name":"qtr2_yob39","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_3","yob_30"]},"name":"qtr3_yob30","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_3","yob_31"]},"name":"qtr3_yob31","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_3","yob_32"]},"name":"qtr3_yob32","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_3","yob_33"]},"name":"qtr3_yob33","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_3","yob_34"]},"name":"qtr3_yob34","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_3","yob_35"]},"name":"qtr3_yob35","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_3","yob_36"]},"name":"qtr3_yob36","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_3","yob_37"]},"name":"qtr3_yob37","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_3","yob_38"]},"name":"qtr3_yob38","op":"interaction"}
    Transformação "derive" aplicada à base "asciiqob" (329509 → 329509 linhas). {"args":{"columns":["qtr_3","yob_39"]},"name":"qtr3_yob39","op":"interaction"}
  2. 2Chamada que gerou a resposta finalinfer.iv_2sls(Variáveis instrumentais por mínimos quadrados em dois estágios (MQ2E))citada na respostacoincide com a referência
    Ver chamada call_263bb148 nos detalhes
    Argumentos principais
    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:
    0,950.95
    se:
    "classical"
    y:
    "lwklywge"
    Resultado calculado
    • coef.educ = 0,0891155 0.08911545635097498
      2SLS effect of educ on lwklywge
    Diagnósticos: first_stage_F.educ = 4,907074.907068900445309 (Wald F of the excluded instruments in the first stage for educ (classical (homoskedastic) standard errors); below 10: weak instrument, the estimate and its interval are unreliable) · partial_r2.educ = 0,0004466170.0004466165850589565 (share of the variation the instruments explain beyond the controls) · weak_instrument = true (at least one first-stage F is below 10) · overid_p = 0,6552610.6552608024512252 (Sargan test of the overidentifying restrictions (assumes homoskedastic errors)) · sargan = 25,439425.439387654762992 (n·R² of the structural residuals on the instruments) · sargan_df = 2929 · n_obs = 329.509329509 · se_type = "classical" (classical (homoskedastic) standard errors)
  3. 3Conferência de lastro e resposta final
    • #0figura próximacoef.educ
      software reference
    • #1figura próximacoef.educ
      software reference, SE
    • #2figura próximacoef.educ
      published cell
    • #3figura próximacoef.educ
      published cell, SE

Aprofundamento técnico para especialistas

Acesso direto às fontes primárias, tabela formal de verificações, comparação de argumentos, trajetória completa com prompts brutos e somas SHA-256.

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/
  • #0 figura próxima: 0,08911550.08911545635601215 · relativa 0.000001 · absoluta 1.6110089092885403e-8
  • #1 figura 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.
  • #2 figura próxima: 0,08910.0891 · published_cell d=4 · absoluta 0.000050001000000000005
  • #3 figura próxima: 0,01610.0161 · published_cell d=4 (the SE as printed) · absoluta 0.000050001000000000005
Especificação técnica do gabarito

Angrist, J. D. and Krueger, A. B. (1991). Does Compulsory School Attendance Affect Schooling and Earnings? Quarterly Journal of Economics 106(4): 979-1014. 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' (source angrist_krueger_1991.tab5_c2.paper); software reference angrist_krueger_1991.tab5_c2.software: linearmodels 7.0: the reference specification of angrist_krueger_1991 tab5_c2 (infer.iv_2sls, figure 'coef.educ') on an independent code path

Verificações

Cada verificação, o que esperava, o que observou e a chamada que leu
#VerificaçãoObrigatóriaResultadoEsperadoObservadoTolerânciaFonteChamada
0
figura próximacoef.educ
software reference
0.08911545635 vs 0.08911545635601215
obrigatóriapassou0,08911550.089115456356012150,08911550.08911545635097498relativa 0.000001 · absoluta 1.6110089092885403e-8angrist_krueger_1991.tab5_c2.software—
1
figura próximacoef.educ
software reference, SE
0.01611008909 vs 0.016110089092885405
obrigatóriapassou0,01611010.0161100890928854050,01611010.01611008909296629relativa 0.000001 · absoluta 1.6110089092885403e-8angrist_krueger_1991.tab5_c2.software—
2
figura próximacoef.educ
published cell
0.08911545635 vs 0.0891
obrigatóriapassou0,08910.08910,08911550.08911545635097498published_cell d=4 · absoluta 0.000050001000000000005angrist_krueger_1991.tab5_c2.paper—
3
figura próximacoef.educ
published cell, SE
0.01611008909 vs 0.0161
obrigatóriapassou0,01610.01610,01611010.01611008909296629published_cell d=4 (the SE as printed) · absoluta 0.000050001000000000005angrist_krueger_1991.tab5_c2.paper—

Caminho de referência e caminho do agente

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

a própria especificação da tarefa

Referência: infer.iv_2slsChamada do agente: infer.iv_2sls (call_263bb148)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

    Tarefa de ferramenta: nenhuma pergunta; a especificação de referência é chamada direto.

    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. 33Ferramenta
    infer.iv_2sls— Variáveis instrumentais por mínimos quadrados em dois estágios (MQ2E)v0.1.0call_263bb148decidido pelo códigoreexecutável
    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_263bb148
    ChaveValorValor brutoErro-padrãoIC
    coef.educ
    2SLS effect of educ on lwklywge
    0,08911550.089115456350974980,01611010.016110089092966290,0575401 – 0,120691
    Diagnósticos
    • first_stage_F.educ = 4,907074.907068900445309 (Wald F of the excluded instruments in the first stage for educ (classical (homoskedastic) standard errors); below 10: weak instrument, the estimate and its interval are unreliable)
    • partial_r2.educ = 0,0004466170.0004466165850589565 (share of the variation the instruments explain beyond the controls)
    • weak_instrument = true (at least one first-stage F is below 10)
    • overid_p = 0,6552610.6552608024512252 (Sargan test of the overidentifying restrictions (assumes homoskedastic errors))
    • sargan = 25,439425.439387654762992 (n·R² of the structural residuals on the instruments)
    • sargan_df = 2929
    • n_obs = 329.509329509
    • se_type = "classical" (classical (homoskedastic) standard errors)
    • n_clusters = — (errors not clustered)
    Derivação matemática e pressupostos
    coef.educ
    1. Coeficiente de educ por mínimos quadrados em dois estágios: lwklywge sobre as projeções dos regressores endógenos nos instrumentos ['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'] e os controles; resíduos com os valores observados de educ.→ 0,0891155 (0.08911545635097498)
    2. Erro-padrão clássico (homocedástico): a raiz da variância estimada do coeficiente.ep = √V_jj→ 0,0161101 (0.01611008909296629)
    3. Intervalo de 95% de confiança: a estimativa mais ou menos o valor crítico da distribuição t de Student com 329498 graus de liberdade vezes o erro-padrão.IC = β ± c · ep
    Pressupostos do estimador
    • the instruments affect the outcome only through the endogenous regressors (exclusion restriction)
    • the instruments are as good as randomly assigned given the controls
    • errors are independent and have the same variance for every observation
    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"
        },
        {
          "ci_high": 0.0320379781880583,
          "ci_low": 0.007361278581300101,
          "coef": 0.0196996283846792,
          "p": 0.001752238055046221,
          "se": 0.006295168981423545,
          "t": 3.1293247953805463,
          "term": "yob_35"
        },
        {
          "ci_high": 0.031046993897747763,
          "ci_low": 0.008483832447970862,
          "coef": 0.019765413172859313,
          "p": 0.0005950717820947613,
          "se": 0.0057559931573096966,
          "t": 3.4338840635622825,
          "term": "yob_36"
        },
        {
          "ci_high": 0.024005056575907437,
          "ci_low": 0.0034141737785028346,
          "coef": 0.013709615177205136,
          "p": 0.009056306404146239,
          "se": 0.005252853450906754,
          "t": 2.609936733498355,
          "term": "yob_37"
        },
        {
          "ci_high": 0.021481765608160248,
          "ci_low": 0.0024814511940856217,
          "coef": 0.011981608401122935,
          "p": 0.013439544603007553,
          "se": 0.004847090244759461,
          "t": 2.471917747782211,
          "term": "yob_38"
        },
        {
          "ci_high": 0.12069076674838888,
          "ci_low": 0.05754014595356108,
          "coef": 0.08911545635097498,
          "p": 3.1746317685400635e-8,
          "se": 0.01611008909296629,
          "t": 5.531655091211324,
          "term": "educ"
        }
      ],
      "first_stage": [
        {
          "ci_high": -0.24423101623545268,
          "ci_low": -0.4443099482623238,
          "coef": -0.34427048224888823,
          "endog": "educ",
          "instrument": "qtr1_yob30",
          "p": 1.5334104886584053e-11,
          "se": 0.05104129427339284,
          "t": -6.744940290990073
        },
        {
          "ci_high": 0.03329997025416202,
          "ci_low": -0.17667020336250389,
          "coef": -0.07168511655417092,
          "endog": "educ",
          "instrument": "qtr1_yob31",
          "p": 0.18080200278004172,
          "se": 0.05356460728591,
          "t": -1.3382925813595477
        },
        {
          "ci_high": -0.09210161848063765,
          "ci_low": -0.2942591678208908,
          "coef": -0.1931803931507642,
          "endog": "educ",
          "instrument": "qtr1_yob32",
          "p": 0.00017979988812732292,
          "se": 0.05157156158789376,
          "t": -3.7458705380003967
        },
        {
          "ci_high": 0.08420754559399626,
          "ci_low": -0.12236226572558334,
          "coef": -0.019077360065793546,
          "endog": "educ",
          "instrument": "qtr1_yob33",
          "p": 0.7173382253017675,
          "se": 0.05269715517146937,
          "t": -0.3620187845761012
        },
        {
          "ci_high": -0.04858890678595669,
          "ci_low": -0.2526220347339507,
          "coef": -0.15060547075995367,
          "endog": "educ",
          "instrument": "qtr1_yob34",
          "p": 0.0038102951969203416,
          "se": 0.052050032552731405,
          "t": -2.8934750541678658
        },
        {
          "ci_high": -0.06714195423790696,
          "ci_low": -0.27032296935537087,
          "coef": -0.16873246179663892,
          "endog": "educ",
          "instrument": "qtr1_yob35",
          "p": 0.0011327157087515853,
          "se": 0.05183265363483825,
          "t": -3.2553313396871673
        },
        {
          "ci_high": -0.08391769441429438,
          "ci_low": -0.2860284719644745,
          "coef": -0.18497308318938444,
          "endog": "educ",
          "instrument": "qtr1_yob36",
          "p": 0.00033383979192525557,
          "se": 0.05155962983337756,
          "t": -3.587556462045051
        },
        {
          "ci_high": -0.03889071440458361,
          "ci_low": -0.23848230110238802,
          "coef": -0.13868650775348582,
          "endog": "educ",
          "instrument": "qtr1_yob37",
          "p": 0.006454332685723027,
          "se": 0.05091696965759414,
          "t": -2.723777724521378
        },
        {
          "ci_high": 0.00598371111567067,
          "ci_low": -0.18889277267494778,
          "coef": -0.09145453077963855,
          "endog": "educ",
          "instrument": "qtr1_yob38",
          "p": 0.06582659390958243,
          "se": 0.04971411959948464,
          "t": -1.8396087774746919
        },
        {
          "ci_high": -0.016570143818348537,
          "ci_low": -0.21051088292701844,
          "coef": -0.11354051337268349,
          "endog": "educ",
          "instrument": "qtr1_yob39",
          "p": 0.021740170944274873,
          "se": 0.04947540571195907,
          "t": -2.2948879698673954
        },
        {
          "ci_high": -0.09622064831729407,
          "ci_low": -0.2962937332845743,
          "coef": -0.19625719080093418,
          "endog": "educ",
          "instrument": "qtr2_yob30",
          "p": 0.00012048696764349247,
          "se": 0.05103980265462924,
          "t": -3.845179263896192
        },
        {
          "ci_high": 0.02393777492354869,
          "ci_low": -0.18608624341832858,
          "coef": -0.08107423424738995,
          "endog": "educ",
          "instrument": "qtr2_yob31",
          "p": 0.13023226414765723,
          "se": 0.05357834338714136,
          "t": -1.5131903885413434
        },
        {
          "ci_high": -0.014849005578609714,
          "ci_low": -0.22017659422594396,
          "coef": -0.11751279990227684,
          "endog": "educ",
          "instrument": "qtr2_yob32",
          "p": 0.024868088109442684,
          "se": 0.05238025697371889,
          "t": -2.2434559639758422
        },
        {
          "ci_high": 0.04655037022906063,
          "ci_low": -0.16167160957612794,
          "coef": -0.05756061967353366,
          "endog": "educ",
          "instrument": "qtr2_yob33",
          "p": 0.2785323866265866,
          "se": 0.05311863292032035,
          "t": -1.0836238906953128
        },
        {
          "ci_high": 0.0327667680588367,
          "ci_low": -0.17256887894936285,
          "coef": -0.06990105544526307,
          "endog": "educ",
          "instrument": "qtr2_yob34",
          "p": 0.18206060751174122,
          "se": 0.05238231270824386,
          "t": -1.3344400396102047
        },
        {
          "ci_high": 0.07885479305820559,
          "ci_low": -0.12428181305671299,
          "coef": -0.022713509999253693,
          "endog": "educ",
          "instrument": "qtr2_yob35",
          "p": 0.6611659885451465,
          "se": 0.051821324641103915,
          "t": -0.43830431114139584
        },
        {
          "ci_high": -0.015112341127623857,
          "ci_low": -0.2187655125839801,
          "coef": -0.11693892685580198,
          "endog": "educ",
          "instrument": "qtr2_yob36",
          "p": 0.024395349632829442,
          "se": 0.05195310345127977,
          "t": -2.2508554655539332
        },
        {
          "ci_high": -0.027122489144994266,
          "ci_low": -0.22674491025101312,
          "coef": -0.1269336996980037,
          "endog": "educ",
          "instrument": "qtr2_yob37",
          "p": 0.01268273276767146,
          "se": 0.05092483569370037,
          "t": -2.492569646399585
        },
        {
          "ci_high": 0.07561511674869896,
          "ci_low": -0.12055176148365347,
          "coef": -0.022468322367477252,
          "endog": "educ",
          "instrument": "qtr2_yob38",
          "p": 0.6534481306223997,
          "se": 0.05004330669460792,
          "t": -0.44897757265704774
        },
        {
          "ci_high": -0.005827556820442725,
          "ci_low": -0.20043332424802487,
          "coef": -0.1031304405342338,
          "endog": "educ",
          "instrument": "qtr2_yob39",
          "p": 0.03776952239046919,
          "se": 0.04964505828747952,
          "t": -2.0773556138666733
        },
        {
          "ci_high": -0.03370087482664952,
          "ci_low": -0.2319307651982523,
          "coef": -0.1328158200124509,
          "endog": "educ",
          "instrument": "qtr3_yob30",
          "p": 0.008629813299590575,
          "se": 0.0505695930388139,
          "t": -2.6263968529568786
        },
        {
          "ci_high": 0.17848833058487334,
          "ci_low": -0.029293862224809827,
          "coef": 0.07459723418003177,
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    Hashes SHA-256 e metadados de reprodução
    Digests dos dados
    asciiqob 654074d5953a60c49422fd28f157a9ede3a844493e1280ba284d386a05958cf7
    sha256 do resultado
    80f8ddcfa234156daf98daa06bd85289cc726c39f6555b8c7f953444063ffb28
  35. 34Pontuação
    #0figura próximapassouobrigatória0.08911545635 vs 0.08911545635601215
  36. 35Pontuação
    #1figura próximapassouobrigatória0.01611008909 vs 0.016110089092885405
  37. 36Pontuação
    #2figura próximapassouobrigatória0.08911545635 vs 0.0891
  38. 37Pontuação
    #3figura próximapassouobrigatória0.01611008909 vs 0.0161

Épocas × verificações

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Época 1passoupassoupassoupassou

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sources/angrist_krueger_1991.tab5_c2.paper.json1,6 KB8d9c6073415af1c3ae4a4c5eb910af8b1a355fb7ea9b01e4eb354cef97cc68ed
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specs/paper_repro.angrist_krueger_1991.tab5_c2.tool.json8,4 KBe00a08ad73a2abdd238317518dabd187ddb02385b277220d781284919e555a8d
traces/paper_repro.angrist_krueger_1991.tab5_c2.tool.e1.a1.jsonl48,0 KB5c2a5d3b1b37d1002019cfb3d27f9fe72263f8082f3bd1d7578aa6a523dee5bf
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