Tarefa paper_repro.angrist_krueger_1991.tab5_c2.tool
paper_reprotoolT1publicépoca 1, tentativa 1Execução: 20261015T165911Z-suite-paper_repro-baseline-8b4f85Veredito
coef.educ =0,08911550.08911545635097498coef.educ =0,08911550.08911545635601215Pergunta 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.
- 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"} - 2Chamada que gerou a resposta finalVer chamada call_09096d9b nos detalhes
infer.iv_2sls(Variáveis instrumentais por mínimos quadrados em dois estágios (MQ2E))citada na respostacoincide com a referênciaArgumentos 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:
- 0,95
0.95 - se:
"classical"- y:
"lwklywge"
Resultado calculadocoef.educ= 0,08911550.089115456350974982SLS 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) - 3Conferência de lastro e resposta final
- #0figura próxima
coef.educsoftware reference - #1figura próxima
coef.educsoftware reference, SE - #2figura próxima
coef.educpublished cell - #3figura próxima
coef.educpublished 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
- 0,0891155
0.08911545635601215(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: 0,0891155
0.08911545635601215· relativa 0.000001 · absoluta 1.6110089092885403e-8 - #1 figura próxima: 0,0161101
0.016110089092885405· 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
- 0,0891
0.0891(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: 0,0891
0.0891· published_cell d=4 · absoluta 0.000050001000000000005 - #3 figura próxima: 0,0161
0.0161· 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
| # | Verificação | Obrigatória | Resultado | Esperado | Observado | Tolerância | Fonte | Chamada |
|---|---|---|---|---|---|---|---|---|
| 0 | figura próxima coef.educsoftware reference 0.08911545635 vs 0.08911545635601215 | obrigatória | passou | 0,08911550.08911545635601215 | 0,08911550.08911545635097498 | relativa 0.000001 · absoluta 1.6110089092885403e-8 | angrist_krueger_1991.tab5_c2.software | — |
| 1 | figura próxima coef.educsoftware reference, SE 0.01611008909 vs 0.016110089092885405 | obrigatória | passou | 0,01611010.016110089092885405 | 0,01611010.01611008909296629 | relativa 0.000001 · absoluta 1.6110089092885403e-8 | angrist_krueger_1991.tab5_c2.software | — |
| 2 | figura próxima coef.educpublished cell 0.08911545635 vs 0.0891 | obrigatória | passou | 0,08910.0891 | 0,08911550.08911545635097498 | published_cell d=4 · absoluta 0.000050001000000000005 | angrist_krueger_1991.tab5_c2.paper | — |
| 3 | figura próxima coef.educpublished cell, SE 0.01611008909 vs 0.0161 | obrigatória | passou | 0,01610.0161 | 0,01611010.01611008909296629 | published_cell d=4 (the SE as printed) · absoluta 0.000050001000000000005 | angrist_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
| Argumento | Referência | Agente | |
|---|---|---|---|
| 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 | — | 0,950.95 | não 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.
- 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).
file0b6c505e52fd6c9f6194c356c91688acf2f8937b5023a84e754e942c9a2f2dcc· frame —dummies{"column":"yob","drop_first":false,"prefix":"yob"}dummies{"column":"qob","drop_first":false,"prefix":"qtr"}derive{"args":{"columns":["qtr_1","yob_30"]},"name":"qtr1_yob30","op":"interaction"}derive{"args":{"columns":["qtr_1","yob_31"]},"name":"qtr1_yob31","op":"interaction"}derive{"args":{"columns":["qtr_1","yob_32"]},"name":"qtr1_yob32","op":"interaction"}derive{"args":{"columns":["qtr_1","yob_33"]},"name":"qtr1_yob33","op":"interaction"}derive{"args":{"columns":["qtr_1","yob_34"]},"name":"qtr1_yob34","op":"interaction"}derive{"args":{"columns":["qtr_1","yob_35"]},"name":"qtr1_yob35","op":"interaction"}derive{"args":{"columns":["qtr_1","yob_36"]},"name":"qtr1_yob36","op":"interaction"}derive{"args":{"columns":["qtr_1","yob_37"]},"name":"qtr1_yob37","op":"interaction"}derive{"args":{"columns":["qtr_1","yob_38"]},"name":"qtr1_yob38","op":"interaction"}derive{"args":{"columns":["qtr_1","yob_39"]},"name":"qtr1_yob39","op":"interaction"}derive{"args":{"columns":["qtr_2","yob_30"]},"name":"qtr2_yob30","op":"interaction"}derive{"args":{"columns":["qtr_2","yob_31"]},"name":"qtr2_yob31","op":"interaction"}derive{"args":{"columns":["qtr_2","yob_32"]},"name":"qtr2_yob32","op":"interaction"}derive{"args":{"columns":["qtr_2","yob_33"]},"name":"qtr2_yob33","op":"interaction"}derive{"args":{"columns":["qtr_2","yob_34"]},"name":"qtr2_yob34","op":"interaction"}derive{"args":{"columns":["qtr_2","yob_35"]},"name":"qtr2_yob35","op":"interaction"}derive{"args":{"columns":["qtr_2","yob_36"]},"name":"qtr2_yob36","op":"interaction"}derive{"args":{"columns":["qtr_2","yob_37"]},"name":"qtr2_yob37","op":"interaction"}derive{"args":{"columns":["qtr_2","yob_38"]},"name":"qtr2_yob38","op":"interaction"}derive{"args":{"columns":["qtr_2","yob_39"]},"name":"qtr2_yob39","op":"interaction"}derive{"args":{"columns":["qtr_3","yob_30"]},"name":"qtr3_yob30","op":"interaction"}derive{"args":{"columns":["qtr_3","yob_31"]},"name":"qtr3_yob31","op":"interaction"}derive{"args":{"columns":["qtr_3","yob_32"]},"name":"qtr3_yob32","op":"interaction"}derive{"args":{"columns":["qtr_3","yob_33"]},"name":"qtr3_yob33","op":"interaction"}derive{"args":{"columns":["qtr_3","yob_34"]},"name":"qtr3_yob34","op":"interaction"}derive{"args":{"columns":["qtr_3","yob_35"]},"name":"qtr3_yob35","op":"interaction"}derive{"args":{"columns":["qtr_3","yob_36"]},"name":"qtr3_yob36","op":"interaction"}derive{"args":{"columns":["qtr_3","yob_37"]},"name":"qtr3_yob37","op":"interaction"}derive{"args":{"columns":["qtr_3","yob_38"]},"name":"qtr3_yob38","op":"interaction"}derive{"args":{"columns":["qtr_3","yob_39"]},"name":"qtr3_yob39","op":"interaction"}
- 1Transformação
asciiqob·dummies{"column":"yob","drop_first":false,"prefix":"yob"}329509 → 329509 linhasFrame antes → depois:845a36d4dcec→d4b277b4997b - 2Transformação
asciiqob·dummies{"column":"qob","drop_first":false,"prefix":"qtr"}329509 → 329509 linhasFrame antes → depois:d4b277b4997b→2c53c053bf00 - 3Transformação
asciiqob·derive{"args":{"columns":["qtr_1","yob_30"]},"name":"qtr1_yob30","op":"interaction"}329509 → 329509 linhasFrame antes → depois:2c53c053bf00→cf52bf944241 - 4Transformação
asciiqob·derive{"args":{"columns":["qtr_1","yob_31"]},"name":"qtr1_yob31","op":"interaction"}329509 → 329509 linhasFrame antes → depois:cf52bf944241→c572825a7957 - 5Transformação
asciiqob·derive{"args":{"columns":["qtr_1","yob_32"]},"name":"qtr1_yob32","op":"interaction"}329509 → 329509 linhasFrame antes → depois:c572825a7957→f423f0515e53 - 6Transformação
asciiqob·derive{"args":{"columns":["qtr_1","yob_33"]},"name":"qtr1_yob33","op":"interaction"}329509 → 329509 linhasFrame antes → depois:f423f0515e53→53a56d68c9d1 - 7Transformação
asciiqob·derive{"args":{"columns":["qtr_1","yob_34"]},"name":"qtr1_yob34","op":"interaction"}329509 → 329509 linhasFrame antes → depois:53a56d68c9d1→4a3cff9083bb - 8Transformação
asciiqob·derive{"args":{"columns":["qtr_1","yob_35"]},"name":"qtr1_yob35","op":"interaction"}329509 → 329509 linhasFrame antes → depois:4a3cff9083bb→373b8fd4038e - 9Transformação
asciiqob·derive{"args":{"columns":["qtr_1","yob_36"]},"name":"qtr1_yob36","op":"interaction"}329509 → 329509 linhasFrame antes → depois:373b8fd4038e→e7e4772d7f72 - 10Transformação
asciiqob·derive{"args":{"columns":["qtr_1","yob_37"]},"name":"qtr1_yob37","op":"interaction"}329509 → 329509 linhasFrame antes → depois:e7e4772d7f72→493704cb4202 - 11Transformação
asciiqob·derive{"args":{"columns":["qtr_1","yob_38"]},"name":"qtr1_yob38","op":"interaction"}329509 → 329509 linhasFrame antes → depois:493704cb4202→459fa0f19579 - 12Transformação
asciiqob·derive{"args":{"columns":["qtr_1","yob_39"]},"name":"qtr1_yob39","op":"interaction"}329509 → 329509 linhasFrame antes → depois:459fa0f19579→85c2fdc43e1d - 13Transformação
asciiqob·derive{"args":{"columns":["qtr_2","yob_30"]},"name":"qtr2_yob30","op":"interaction"}329509 → 329509 linhasFrame antes → depois:85c2fdc43e1d→221b8d8c4186 - 14Transformação
asciiqob·derive{"args":{"columns":["qtr_2","yob_31"]},"name":"qtr2_yob31","op":"interaction"}329509 → 329509 linhasFrame antes → depois:221b8d8c4186→318603958de3 - 15Transformação
asciiqob·derive{"args":{"columns":["qtr_2","yob_32"]},"name":"qtr2_yob32","op":"interaction"}329509 → 329509 linhasFrame antes → depois:318603958de3→069525d0a1fe - 16Transformação
asciiqob·derive{"args":{"columns":["qtr_2","yob_33"]},"name":"qtr2_yob33","op":"interaction"}329509 → 329509 linhasFrame antes → depois:069525d0a1fe→64ef72351a15 - 17Transformação
asciiqob·derive{"args":{"columns":["qtr_2","yob_34"]},"name":"qtr2_yob34","op":"interaction"}329509 → 329509 linhasFrame antes → depois:64ef72351a15→0c272ae20586 - 18Transformação
asciiqob·derive{"args":{"columns":["qtr_2","yob_35"]},"name":"qtr2_yob35","op":"interaction"}329509 → 329509 linhasFrame antes → depois:0c272ae20586→7856b1936015 - 19Transformação
asciiqob·derive{"args":{"columns":["qtr_2","yob_36"]},"name":"qtr2_yob36","op":"interaction"}329509 → 329509 linhasFrame antes → depois:7856b1936015→06252be82053 - 20Transformação
asciiqob·derive{"args":{"columns":["qtr_2","yob_37"]},"name":"qtr2_yob37","op":"interaction"}329509 → 329509 linhasFrame antes → depois:06252be82053→4a442f63e865 - 21Transformação
asciiqob·derive{"args":{"columns":["qtr_2","yob_38"]},"name":"qtr2_yob38","op":"interaction"}329509 → 329509 linhasFrame antes → depois:4a442f63e865→1a895d8e4ad2 - 22Transformação
asciiqob·derive{"args":{"columns":["qtr_2","yob_39"]},"name":"qtr2_yob39","op":"interaction"}329509 → 329509 linhasFrame antes → depois:1a895d8e4ad2→7fd62953f64c - 23Transformação
asciiqob·derive{"args":{"columns":["qtr_3","yob_30"]},"name":"qtr3_yob30","op":"interaction"}329509 → 329509 linhasFrame antes → depois:7fd62953f64c→fbb95e831358 - 24Transformação
asciiqob·derive{"args":{"columns":["qtr_3","yob_31"]},"name":"qtr3_yob31","op":"interaction"}329509 → 329509 linhasFrame antes → depois:fbb95e831358→3c39c77165ba - 25Transformação
asciiqob·derive{"args":{"columns":["qtr_3","yob_32"]},"name":"qtr3_yob32","op":"interaction"}329509 → 329509 linhasFrame antes → depois:3c39c77165ba→7e4ccc705689 - 26Transformação
asciiqob·derive{"args":{"columns":["qtr_3","yob_33"]},"name":"qtr3_yob33","op":"interaction"}329509 → 329509 linhasFrame antes → depois:7e4ccc705689→e14e138d365d - 27Transformação
asciiqob·derive{"args":{"columns":["qtr_3","yob_34"]},"name":"qtr3_yob34","op":"interaction"}329509 → 329509 linhasFrame antes → depois:e14e138d365d→efea1aed1a08 - 28Transformação
asciiqob·derive{"args":{"columns":["qtr_3","yob_35"]},"name":"qtr3_yob35","op":"interaction"}329509 → 329509 linhasFrame antes → depois:efea1aed1a08→889c869c49df - 29Transformação
asciiqob·derive{"args":{"columns":["qtr_3","yob_36"]},"name":"qtr3_yob36","op":"interaction"}329509 → 329509 linhasFrame antes → depois:889c869c49df→4690bc1fd2a9 - 30Transformação
asciiqob·derive{"args":{"columns":["qtr_3","yob_37"]},"name":"qtr3_yob37","op":"interaction"}329509 → 329509 linhasFrame antes → depois:4690bc1fd2a9→73cf0a1d91c6 - 31Transformação
asciiqob·derive{"args":{"columns":["qtr_3","yob_38"]},"name":"qtr3_yob38","op":"interaction"}329509 → 329509 linhasFrame antes → depois:73cf0a1d91c6→adbbeec74207 - 32Transformação
asciiqob·derive{"args":{"columns":["qtr_3","yob_39"]},"name":"qtr3_yob39","op":"interaction"}329509 → 329509 linhasFrame antes → depois:adbbeec74207→654074d5953a - 33Ferramenta
infer.iv_2sls— Variáveis instrumentais por mínimos quadrados em dois estágios (MQ2E)v0.1.0call_09096d9bdecidido pelo códigoreexecutávelArgumentos
{ "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_09096d9b Chave Valor Valor bruto Erro-padrão IC coef.educ 2SLS effect of educ on lwklywge0,0891155 0.089115456350974980,0161101 0.016110089092966290,0575401 – 0,120691 Diagnósticosfirst_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= 2929n_obs= 329.509329509se_type="classical"(classical (homoskedastic) standard errors)n_clusters= — (errors not clustered)
Derivação matemática e pressupostos
coef.educ- 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)
- Erro-padrão clássico (homocedástico): a raiz da variância estimada do coeficiente.
ep = √V_jj→ 0,0161101 (0.01611008909296629) - 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": 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}, { "ci_high": 0.0019509568391937425, "ci_low": -0.03719261964483328, "coef": -0.017620831402819767, "instrument": "qtr3_yob39", "p": 0.07763242078595874, "se": 0.009985753052530064, "t": -1.7645971525758115 } ] }Hashes SHA-256 e metadados de reprodução
- Digests dos dados
asciiqob654074d5953a60c49422fd28f157a9ede3a844493e1280ba284d386a05958cf7- sha256 do resultado
be4f586efda7f19f27051cd5a3b2057c3eda32fe715c0b33b12b05db9ae978d7
- 34Pontuação#0figura próximapassouobrigatória
0.08911545635 vs 0.08911545635601215 - 35Pontuação#1figura próximapassouobrigatória
0.01611008909 vs 0.016110089092885405 - 36Pontuação#2figura próximapassouobrigatória
0.08911545635 vs 0.0891 - 37Pontuação#3figura próximapassouobrigatória
0.01611008909 vs 0.0161
Épocas × verificações
| # | 0 | 1 | 2 | 3 |
|---|---|---|---|---|
| Época 1 | passou | passou | passou | passou |
Tentativas
Cada tentativa é seu próprio arquivo e é publicada; só a última de cada época é pontuada.
- época 1, tentativa 1passoupontuada(exibindo)
Downloads desta tarefa
a24d5898e3c4ec8e1dc385e0fcabe1631ec1c26c31d93c456081320a778c3566O hash de um zip é só de transporte: o que ancora a integridade é o RUN_SHA256SUMS que vai dentro dele, cópia exata do SHA256SUMS da execução.
| Arquivo | Tamanho | sha256 |
|---|---|---|
| sources/angrist_krueger_1991.tab5_c2.paper.json | 1,6 KB | 8d9c6073415af1c3ae4a4c5eb910af8b1a355fb7ea9b01e4eb354cef97cc68ed |
| sources/angrist_krueger_1991.tab5_c2.software.json | 1,8 KB | b8954244a39ca124742b066b2790b2cf9b2017049c274fd73ea94cbc11a91f9d |
| specs/paper_repro.angrist_krueger_1991.tab5_c2.tool.json | 8,4 KB | e00a08ad73a2abdd238317518dabd187ddb02385b277220d781284919e555a8d |
| traces/paper_repro.angrist_krueger_1991.tab5_c2.tool.e1.a1.jsonl | 48,0 KB | 053f4794208297ed010fed4026045d0513a1ca9e389f5d104c49102ec8098ddf |
| trajectories/paper_repro.angrist_krueger_1991.tab5_c2.tool.e1.a1.jsonl | 44,3 KB | 424fd76befc56b423d0834cdc2b5580a44088b8b889f753f6d2409a9e30ec9ba |