Tarefa paper_repro.card_1995.ex15_4_iv.tool
paper_reprotoolT1publicépoca 1, tentativa 1Execução: 20261015T165744Z-suite-paper_repro-scripted-def9dfVeredito
Pergunta feita ao analista
Tarefa de ferramenta: nenhuma pergunta; a especificação de referência é chamada direto.
Valores esperados e de onde vêm
card_1995.ex15_4_iv.software
- Fonte
- linearmodels 7.0: the reference specification of card_1995 ex15_4_iv (infer.iv_2sls, figure 'coef.educ') on an independent code path
- Tipo
- software
- Localização
- card_1995: Wooldridge (2020), Example 15.4 'Using College Proximity as an IV for Education', Table 15.1 (dependent variable log(wage)), column IV, row educ
- Valor
- 0,131504
0.13150383624451933(se 0,05496370.054963672601153514) - Conferido por
- execução de software · IV2SLS(dependent=lwage, exog=[const, exper, expersq, black, smsa, south, smsa66, reg662, reg663, reg664, reg665, reg666, reg667, reg668, reg669], endog=['educ'], instruments=['nearc4']).fit(cov_type='unadjusted', debiased=True) on card (the file pinned at sha256 326dad817467b20d51bdfd015033e3e3e313931f51f812c38c0776249e7fd711); n_obs = 3010. 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: 0,131504
0.13150383624451933· relativa 0.000001 · absoluta 5.496367260115351e-8 - #1 figura próxima: 0,0549637
0.054963672601153514· relativa 0.000001 · absoluta 5.496367260115351e-8
card_1995.ex15_4_iv.paper
- Fonte
- Wooldridge, J. M. (2020). Introductory Econometrics: A Modern Approach, 7th edition. Boston: Cengage. Example 15.4 (Card 1995, 'Using Geographic Variation in College Proximity to Estimate the Return to Schooling', data set CARD).
- Tipo
- textbook
- Localização
- Wooldridge (2020), Example 15.4 'Using College Proximity as an IV for Education', Table 15.1 (dependent variable log(wage)), column IV, row educ
- Página
- 508
- Trecho
Table 15.1 educ IV .132 (.055)
- Valor como publicado
.132- Erro-padrão como publicado
.055- Valor
- 0,132
0.132(se 0,0550.055) log points of the hourly wage per year of schooling - Conferido por
- fonte primária · Read on 2026-10-15 from a copy of Chapter 15 of the 7th edition (Cengage, 2020) posted on a course page at huhuaping.com (64-page PDF of Chapters 15-16), with pdftotext and from the rendered page image. Table 15.1 on printed page 508: IV column, educ .132 (.055), observations 3,010; other controls smsa66, reg662 ... reg669. The text says the IV standard errors use a degrees-of-freedom adjustment. Data fact checked: CARD has 3,010 rows with no missing values in the variables used.
- sha256 da cópia lida
d4e2e31096d1e3ef19d9aa7f3d8d29a5dc11da66ecd8360ff195a462651d85df(identifica a cópia lida, não um arquivo canônico)- Endereço
https://www.cengage.com/c/introductory-econometrics-a-modern-approach-7e-wooldridge/9781337558860/- Licença
- Copyright Cengage; cited, not reproduced.
- #2 figura próxima: 0,132
0.132· published_cell d=3 · absoluta 0.000500001 - #3 figura próxima: 0,055
0.055· published_cell d=3 (the SE as printed) · absoluta 0.000500001
Verificações
| # | Verificação | Obrigatória | Resultado | Esperado | Observado | Tolerância | Fonte | Chamada |
|---|---|---|---|---|---|---|---|---|
| 0 | figura próxima 0.1315038362 vs 0.13150383624451933 | obrigatória | passou | 0,1315040.13150383624451933 | 0,1315040.13150383624470474 | relativa 0.000001 · absoluta 5.496367260115351e-8 | card_1995.ex15_4_iv.software | — |
| 1 | figura próxima 0.0549636726 vs 0.054963672601153514 | obrigatória | passou | 0,05496370.054963672601153514 | 0,05496370.054963672601175226 | relativa 0.000001 · absoluta 5.496367260115351e-8 | card_1995.ex15_4_iv.software | — |
| 2 | figura próxima 0.1315038362 vs 0.132 | obrigatória | passou | 0,1320.132 | 0,1315040.13150383624470474 | published_cell d=3 · absoluta 0.000500001 | card_1995.ex15_4_iv.paper | — |
| 3 | figura próxima 0.0549636726 vs 0.055 | obrigatória | passou | 0,0550.055 | 0,05496370.054963672601175226 | published_cell d=3 (the SE as printed) · absoluta 0.000500001 | card_1995.ex15_4_iv.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 | "card" | "card" | igual |
| endog | ["educ"] | ["educ"] | igual |
| exog | ["exper","expersq","black","smsa","south","smsa66","reg662","reg663","reg664","reg665","reg666","reg667","reg668","reg669"] | ["exper","expersq","black","smsa","south","smsa66","reg662","reg663","reg664","reg665","reg666","reg667","reg668","reg669"] | igual |
| instruments | ["nearc4"] | ["nearc4"] | igual |
| level | — | 0,950.95 | não fixado pela referência |
| se | "classical" | "classical" | igual |
| subset | — | — | não fixado pela referência |
| y | "lwage" | "lwage" | 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.
card(agent)Wooldridge's CARD data set (the R package wooldridge, served by Rdatasets): David Card's (1995) sample of men from the National Longitudinal Survey of Young Men, observed in 1976; one row per man (3,010 rows). Columns used here: lwage, log hourly wage in 1976; educ, years of schooling in 1976; nearc4, 1 if the man grew up near a four-year college in 1966; nearc2, 1 if near a two-year college in 1966; exper, years of experience (age - educ - 6); expersq, exper squared; black, 1 if black; smsa, 1 if living in an SMSA in 1976; south, 1 if living in the South in 1976; smsa66, 1 if living in an SMSA in 1966; reg661 to reg669, indicators of the region of residence in 1966; also age, fatheduc, motheduc, IQ, KWW, married, wage (cents per hour) and the family-background indicators momdad14, sinmom14, step14, south66, libcrd14, enroll, weight, id and rownames.
file326dad817467b20d51bdfd015033e3e3e313931f51f812c38c0776249e7fd711· frame — - 1Ferramenta
infer.iv_2slsv0.1.0call_fb828551decidido pelo códigoreexecutávelArgumentos
{ "cluster": null, "dataset": "card", "endog": [ "educ" ], "exog": [ "exper", "expersq", "black", "smsa", "south", "smsa66", "reg662", "reg663", "reg664", "reg665", "reg666", "reg667", "reg668", "reg669" ], "instruments": [ "nearc4" ], "level": 0.95, "se": "classical", "subset": null, "y": "lwage" }Figuras call_fb828551 Chave Valor Valor bruto Erro-padrão IC coef.educ 2SLS effect of educ on lwage0,131504 0.131503836244704740,0549637 0.0549636726011752260,0237335 – 0,239274 Diagnósticosfirst_stage_F.educ= 13,255813.255785330576108partial_r2.educ= 0,004407930.004407934102325983weak_instrument=falsen_obs= 3.0103010se_type="classical"n_clusters= —
Tabelas (3)
{ "coefficients": [ { "ci_high": 5.479516553400695, "ci_low": 1.8527852634542328, "coef": 3.666150908427464, "p": 0.00007538415974785308, "se": 0.9248295310138733, "t": 3.9641369414407985, "term": "Intercept" }, { "ci_high": 0.1546598064790368, "ci_low": 0.06188240572195053, "coef": 0.10827110610049366, "p": 0.000004922903208547169, "se": 0.023658571085405363, "t": 4.576400903911081, "term": "exper" }, { "ci_high": -0.001681030950206941, "ci_low": -0.0029888444048044374, "coef": -0.002334937677505689, "p": 3.1161246944085553e-12, "se": 0.00033349713755244625, "t": -7.001372469466829, "term": "expersq" }, { "ci_high": -0.04109124105905192, "ci_low": -0.25246025330930105, "coef": -0.1467757471841765, "p": 0.006504376545512747, "se": 0.05389985881009377, "t": -2.7231193258096242, "term": "black" }, { "ci_high": 0.1738897625009303, "ci_low": 0.04972685470035713, "coef": 0.11180830860064371, "p": 0.0004197459454284399, "se": 0.03166198833336174, "t": 3.5313103972953286, "term": "smsa" }, { "ci_high": -0.09117299500874089, "ci_low": -0.19817000636948712, "coef": -0.144671500689114, "p": 1.2266258857565786e-7, "se": 0.027284622963645526, "t": -5.302308955556272, "term": "south" }, { "ci_high": 0.06090028882943441, "ci_low": -0.023838079835042367, "coef": 0.01853110449719602, "p": 0.39119278809555685, "se": 0.021608588970484666, "t": 0.8575804983151744, "term": "smsa66" }, { "ci_high": 0.17466030000544155, "ci_low": 0.026875261834297726, "coef": 0.10076778091986964, "p": 0.007538241795889867, "se": 0.0376857165904629, "t": 2.6738984962109194, "term": "reg662" }, { "ci_high": 0.2204423366673024, "ci_low": 0.07607522011011421, "coef": 0.1482587783887083, "p": 0.000057840797772050855, "se": 0.03681413427830229, "t": 4.027224360837132, "term": "reg663" }, { "ci_high": 0.13566022759527543, "ci_low": -0.035866069886474596, "coef": 0.049897078854400416, "p": 0.25405688043284264, "se": 0.04373982315600082, "t": 1.1407700181237441, "term": "reg664" }, { "ci_high": 0.23855286385627722, "ci_low": 0.05399096224877149, "coef": 0.14627191305252435, "p": 0.001901645058086012, "se": 0.04706394912130858, "t": 3.107939639223742, "term": "reg665" }, { "ci_high": 0.2646849853540353, "ci_low": 0.06112089839772622, "coef": 0.16290294187588075, "p": 0.001716385181435308, "se": 0.05190957477135003, "t": 3.1382060553073585, "term": "reg666" }, { "ci_high": 0.2314381083788585, "ci_low": 0.03770631068276323, "coef": 0.13457220953081087, "p": 0.006486970827583493, "se": 0.04940230562501896, "t": 2.72400665977539, "term": "reg667" }, { "ci_high": 0.03325735213331668, "ci_low": -0.1994113382810437, "coef": -0.08307699307386351, "p": 0.161550835975611, "se": 0.05933135339638065, "t": -1.4002207655511092, "term": "reg668" }, { "ci_high": 0.1898006809461838, "ci_low": 0.0258277843270978, "coef": 0.10781423263664079, "p": 0.009971984091442317, "se": 0.041813678752432255, "t": 2.578444084649437, "term": "reg669" }, { "ci_high": 0.23927422232576134, "ci_low": 0.023733450163648154, "coef": 0.13150383624470474, "p": 0.016792621890736437, "se": 0.054963672601175226, "t": 2.392559121711473, "term": "educ" } ], "first_stage": [ { "ci_high": 0.4921785043603216, "ci_low": 0.147619375822603, "coef": 0.3198989400914623, "endog": "educ", "instrument": "nearc4", "p": 0.00027634008572957033, "se": 0.08786381779522222, "t": 3.640849534185134 } ], "reduced_form": [ { "ci_high": 0.07751371396063084, "ci_low": 0.006622161704650145, "coef": 0.04206793783264049, "instrument": "nearc4", "p": 0.020027629759561513, "se": 0.01807760095364329, "t": 2.3270752540957202 } ] }- Digests dos dados
card4ec4da8d7939f11a46d67bd248416cc7330bd0dddaddcd6c49c9872c5a427413- sha256 do resultado
e1da69862a73a9f1eb06f2e0388acd3b0ce16c11e3a46edc3319c298e95b578a
- 2Pontuação#0figura próximapassouobrigatória
0.1315038362 vs 0.13150383624451933 - 3Pontuação#1figura próximapassouobrigatória
0.0549636726 vs 0.054963672601153514 - 4Pontuação#2figura próximapassouobrigatória
0.1315038362 vs 0.132 - 5Pontuação#3figura próximapassouobrigatória
0.0549636726 vs 0.055
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
ae9d017580bdcafb527272d10d8d09b170e1c4bba76fb68b1e096863b8a31a7cO 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/card_1995.ex15_4_iv.paper.json | 1,7 KB | 11928adb67b420dff797a57ab90497bf42f5c52af08802879dc087a4a78f9c4a |
| sources/card_1995.ex15_4_iv.software.json | 1,4 KB | 15387377734a8e321b58ac40a638a9218ccc4eb7fcfb3b5f8447b00610139733 |
| specs/paper_repro.card_1995.ex15_4_iv.tool.json | 5,0 KB | e12cef96cd5173b41899913e5e0f1f1f80aba0362e7bdb08c35b4ab3e90f588e |
| traces/paper_repro.card_1995.ex15_4_iv.tool.e1.a1.jsonl | 6,7 KB | 3cdd938bebe6bbb8aab20cc66e76d0f28e0219fff8860b14e159c18f2c6ede90 |
| trajectories/paper_repro.card_1995.ex15_4_iv.tool.e1.a1.jsonl | 10,6 KB | e031b117c56413c7a4e87bdee86dcda10b3898c0a52505e6e1e3a3fed1c46e4b |