Tarefa paper_repro.angrist_krueger_1991.tab5_c2.design

Veredito

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.

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_c1f07f1f nos detalhes

   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).

   Por que este é o caminho de referência: 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 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

   Todos os 1 números escritos na resposta foram conferidos contra as ferramentas e o enunciado (nenhum número sem lastro).

   Números encontrados: 0,08912
   Figuras citadas: call_c1f07f1f:coef.educ
   • ✓
     #0resposta com lastro

     Garante que todo número citado no texto veio de uma ferramenta ou do enunciado (sem cálculo mental do modelo).
   • ✓
     #1figura da resposta escolhida

     an answer figure: the effect of an estimator call the answer cites
   • ✓
     #2ferramenta chamadainfer.iv_2sls

     Exige que o resultado venha da ferramenta infer.iv_2sls.
   • ✓
     #3argumento igualy

     T3: the outcome the design question implies
   • ✓
     #4argumento igualendog[0]

     T3: the treatment the design question implies
   • ✓
     #5argumento igualy

     outcome: log weekly earnings (T3: recorded; a design question cannot state it)
   • ✓
     #6argumento igualendog

     the endogenous regressor: years of education (T3: recorded; a design question cannot state it)
   • ✓
     #7argumento igualinstruments

     the 30 quarter-of-birth by year-of-birth interactions (T3: recorded; a design question cannot state it)
   • ✓
     #8diagnósticon_obs

     (T3: recorded; a design question cannot state it)
   • ✓
     #9figura da resposta próxima

     software reference (T3: recorded; T3 pontua o desenho; a estimativa é registrada)
   • ✓
     #10figura da resposta próxima

     software reference, SE: recorded (T3)
   • ✓
     #11figura da resposta próxima

     published cell: recorded, never required on T2/T3
   • ✓
     #12figura da resposta próxima

     published cell, SE: recorded, never required on T2/T3

Valores esperados e de onde vêm

Verificações

Caminho de referência e caminho do agente

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

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"
      }

    Mensagens (formato neutro)Instruções do sistemaFerramentas oferecidas
35. 34Ferramenta
    infer.iv_2sls— Variáveis instrumentais por mínimos quadrados em dois estágios (MQ2E)v0.1.0call_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

    Chave	Valor	Valor bruto	Erro-padrão	IC
    coef.educ 2SLS effect of educ on lwklywge	0,0891155	0.08911545635097498	0,01611010.01611008909296629	0,0575401 – 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,
          "endog": "educ",
          "instrument": "qtr3_yob31",
          "p": 0.15933229029806595,
          "se": 0.05300644071083681,
          "t": 1.407323962515764
        },
        {
          "ci_high": 0.03424162010315075,
          "ci_low": -0.16756473077572898,
          "coef": -0.0666615553362891,
          "endog": "educ",
          "instrument": "qtr3_yob32",
          "p": 0.19537202922361283,
          "se": 0.05148196882650839,
          "t": -1.2948524863323534
        },
        {
          "ci_high": 0.16529951614557503,
          "ci_low": -0.04193078268328362,
          "coef": 0.06168436673114571,
          "endog": "educ",
          "instrument": "qtr3_yob33",
          "p": 0.24328643630286026,
          "se": 0.05286564936015529,
          "t": 1.1668137529326759
        },
        {
          "ci_high": 0.010053401807836357,
          "ci_low": -0.18969387761548934,
          "coef": -0.08982023790382648,
          "endog": "educ",
          "instrument": "qtr3_yob34",
          "p": 0.07795572238862243,
          "se": 0.05095668777353495,
          "t": -1.7626781062185883
        },
        {
          "ci_high": 0.14097507283865052,
          "ci_low": -0.05755117317398906,
          "coef": 0.04171194983233072,
          "endog": "educ",
          "instrument": "qtr3_yob35",
          "p": 0.4101611069011542,
          "se": 0.050645195079121214,
          "t": 0.823611198795179
        },
        {
          "ci_high": 0.05814454033296278,
          "ci_low": -0.14170703751405417,
          "coef": -0.04178124859054569,
          "endog": "educ",
          "instrument": "qtr3_yob36",
          "p": 0.41249689060607997,
          "se": 0.05098329490544008,
          "t": -0.8195085991997645
        },
        {
          "ci_high": 0.0881032721398109,
          "ci_low": -0.10572224710236647,
          "coef": -0.008809487481277793,
          "endog": "educ",
          "instrument": "qtr3_yob37",
          "p": 0.8585944794466445,
          "se": 0.04944601245674619,
          "t": -0.1781637596961748
        },
        {
          "ci_high": 0.05212658174333239,
          "ci_low": -0.13928127409497526,
          "coef": -0.043577346175821444,
          "endog": "educ",
          "instrument": "qtr3_yob38",
          "p": 0.3721559469809917,
          "se": 0.048829252521050644,
          "t": -0.8924434417060744
        },
        {
          "ci_high": -0.03281225527763924,
          "ci_low": -0.22172672894979428,
          "coef": -0.12726949211371677,
          "endog": "educ",
          "instrument": "qtr3_yob39",
          "p": 0.008270960685375651,
          "se": 0.04819317629058809,
          "t": -2.640819757268664
        }
      ],
      "reduced_form": [
        {
          "ci_high": -0.004492652873066976,
          "ci_low": -0.04594953453173596,
          "coef": -0.02522109370240147,
          "instrument": "qtr1_yob30",
          "p": 0.017090245340735215,
          "se": 0.010575890599581772,
          "t": -2.3847725602795897
        },
        {
          "ci_high": 0.013301871212669179,
          "ci_low": -0.030204501753712094,
          "coef": -0.008451315270521459,
          "instrument": "qtr1_yob31",
          "p": 0.44637870657334305,
          "se": 0.011098727701359456,
          "t": -0.7614670345940894
        },
        {
          "ci_high": 0.030199740090564895,
          "ci_low": -0.011687836549837443,
          "coef": 0.009255951770363726,
          "instrument": "qtr1_yob32",
          "p": 0.386384021795845,
          "se": 0.010685763383697658,
          "t": 0.8661947151557491
        },
        {
          "ci_high": 0.010399816274816594,
          "ci_low": -0.032401992668162294,
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    }

    Hashes SHA-256 e metadados de reprodução

    Digests dos dados

    asciiqob 654074d5953a60c49422fd28f157a9ede3a844493e1280ba284d386a05958cf7

    sha256 do resultado

    2f144bd7d7632da6a484a290783956e9cd90bf18136655a16b8fea99e04f6dbc

    Resultado mostrado ao modelo
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"
        ]
      }

    Mensagens (formato neutro)Instruções do sistemaFerramentas oferecidas
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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• época 1, tentativa 1passoupontuada(exibindo)

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