Tarefa paper_repro.stock_watson_fatalities.tab10_1_c2.tool
paper_reprotoolT1publicépoca 1, tentativa 1Execução: 20261015T183517Z-suite-paper_repro-gemini-0cda63Veredito
Pergunta feita ao analista
Tarefa de ferramenta: nenhuma pergunta; a especificação de referência é chamada direto.
Valores esperados e de onde vêm
stock_watson_fatalities.tab10_1_c2.software
- Fonte
- statsmodels 0.15.0: the reference specification of stock_watson_fatalities tab10_1_c2 (infer.ols, figure 'coef.beertax') on an independent code path
- Tipo
- software
- Localização
- stock_watson_fatalities: Table 10.1 (Regression analysis of the effect of drunk driving laws on traffic deaths), column (2) (state effects, no time effects, clustered standard errors), row 'Beer tax'
- Valor
- -0,655874
-0.6558737221504346(se 0,3148480.31484759309473803) - Conferido por
- execução de software · sm.OLS(frate, add_constant(['beertax']), fe dummies ['state']; 49 independent columns).fit(cov_type='cluster', groups=state) on fatalities (the file pinned at sha256 ae265c1b14b4a023179b3af5db33b6a659ccf804987f26e8349826d4083ee149, after its 2 declared transforms); n_obs = 336. The tool infer.ols (magi_infer, numpy) does not call statsmodels. Written by scripts/paper_repro_reference.py.
- Implementação
- independente da ferramenta
- Endereço
https://pypi.org/project/statsmodels/0.15.0/
- #0 figura próxima: -0,655874
-0.6558737221504346· relativa 0.000001 · absoluta 3.1484759309473804e-7 - #1 figura próxima: 0,314848
0.31484759309473803· relativa 0.000001 · absoluta 3.1484759309473804e-7
stock_watson_fatalities.tab10_1_c2.paper
- Fonte
- Stock, J. H. and Watson, M. W. (2015). Introduction to Econometrics, 3rd edition (update) or later; the edition of the reproduced table is not confirmed. Boston: Pearson.
- Tipo
- textbook
- Localização
- Table 10.1 (Regression analysis of the effect of drunk driving laws on traffic deaths), column (2) (state effects, no time effects, clustered standard errors), row 'Beer tax'
- Página
- slide 66 of the NTU reproduction (book page not read)
- Trecho
Table 10.1, Beer tax, column (2): −0.66 (0.29)
- Valor como publicado
−0.66- Erro-padrão como publicado
0.29- Valor
- -0,66
-0.66(se 0,290.29) deaths per 10,000 residents per dollar of real beer tax per case - Conferido por
- fonte secundária · The book itself was not read (not public). Secondary reproduction read on 2026-10-15: Ming-Ching Luoh's course slides 'Regression with Panel Data' (National Taiwan University, 2022; panel.pdf, sha256 72404054...), slide 66, an image of the book's Table 10.1 'Regression Analysis of the Effect of Drunk Driving Laws on Traffic Deaths' (dependent variable: traffic fatality rate, deaths per 10,000), read from the page rendered at 220 dpi. The table's layout (95% intervals in brackets, a 'Clustered standard errors?' row) suggests the 3rd edition; neither slide names an edition. The same deck's slide 35 prints an equation with a non-clustered standard error, -.66 (.20), edition not stated; the cells here are the table's clustered ones.
- sha256 da cópia lida
724040543bc392d0119d830d39ae5aabbbb08e847c66f33e9bfe56c64734b344(identifica a cópia lida, não um arquivo canônico)- Desvio conhecido
- convenção de erro-padrãoRecorded before this track's software-reference run and before any dry run on this target; from the stated conventions. Table 10.1 reports errors clustered by state with the convention of Stata's xtreg/areg-style panel output, where the absorbed state effects (nested in the clusters) are not counted in K; infer.ols, by its card, puts fixed effects in as dummies and applies the CR1 correction G/(G-1)·(N-1)/(N-K) with the dummies counted in K, so its clustered SE is larger by about sqrt((N-1)/(N-K)). The research probe of 2026-10-14 (research-papers.md sections 2.4 and 3.21) found 0.3148 against the printed 0.29 for column (2). The printed SE (and, for safety, the printed cell) is therefore a se_convention deviation: recorded, counted in replication fidelity, non-required on T1.
- Endereço
https://homepage.ntu.edu.tw/~luohm/metrics2022s/panel.pdf- Licença
- Copyright Pearson Education; cited, not reproduced.
- #2 figura próxima: -0,66
-0.66· published_cell d=2 · absoluta 0.0050000010000000004 - #3 figura próxima: 0,29
0.29· published_cell d=2 (the SE as printed) · absoluta 0.0050000010000000004
Verificações
| # | Verificação | Obrigatória | Resultado | Esperado | Observado | Tolerância | Fonte | Chamada |
|---|---|---|---|---|---|---|---|---|
| 0 | figura próxima -0.6558737222 vs -0.6558737221504346 | obrigatória | passou | -0,655874-0.6558737221504346 | -0,655874-0.6558737221504309 | relativa 0.000001 · absoluta 3.1484759309473804e-7 | stock_watson_fatalities.tab10_1_c2.software | — |
| 1 | figura próxima 0.3148475931 vs 0.31484759309473803 | obrigatória | passou | 0,3148480.31484759309473803 | 0,3148480.3148475930947355 | relativa 0.000001 · absoluta 3.1484759309473804e-7 | stock_watson_fatalities.tab10_1_c2.software | — |
| 2 | figura próxima -0.6558737222 vs -0.66 | obrigatória | passou | -0,66-0.66 | -0,655874-0.6558737221504309 | published_cell d=2 · absoluta 0.0050000010000000004 | stock_watson_fatalities.tab10_1_c2.paper | — |
| 3 | figura próxima 0.3148475931 vs 0.29 | registrada | falhou | 0,290.29 | 0,3148480.3148475930947355 | published_cell d=2 (the SE as printed) · absoluta 0.0050000010000000004 | stock_watson_fatalities.tab10_1_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 | "state" | "state" | igual |
| controls | [] | [] | igual |
| dataset | "fatalities" | "fatalities" | igual |
| fe | ["state"] | ["state"] | igual |
| intercept | — | true | não fixado pela referência |
| level | — | 0,950.95 | não fixado pela referência |
| se | — | "HC1" | não fixado pela referência |
| subset | — | — | não fixado pela referência |
| weights | — | — | não fixado pela referência |
| x | ["beertax"] | ["beertax"] | igual |
| y | "frate" | "frate" | 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.
fatalities(agent)Stock and Watson's traffic fatalities panel (R package AER, Fatalities; Ruhm 1996): one row per U.S. state (the 48 contiguous states) and year, 1982-1988 (336 rows). Columns: rownames, a row number; state, two-letter state code; year; spirits, spirits consumption; unemp, unemployment rate; income, per capita personal income (1987 dollars); emppop, employment to population ratio; beertax, tax on a case of beer (1988 dollars); baptist and mormon, percent of residents Southern Baptist and Mormon; drinkage, minimum legal drinking age; dry, percent of residents in dry counties; youngdrivers, percent of drivers aged 15-24; miles, average miles per driver; breath, jail, service, 'yes' for a preliminary breath test law, mandatory jail sentence and mandatory community service; fatal, number of vehicle fatalities; nfatal and sfatal, night-time and single-vehicle fatalities; fatal1517, fatal1820, fatal2124 and their night-time counterparts, fatalities by age group; afatal, alcohol-involved fatalities; pop, population; pop1517, pop1820, pop2124, population by age group; milestot, total vehicle miles (millions); unempus and emppopus, national unemployment rate and employment ratio; gsp, growth of gross state product. Columns built from the book's definition: fatal_per_pop, fatal divided by pop; frate, the traffic fatality rate, deaths per 10,000 residents (fatal_per_pop times 10,000).
fileae265c1b14b4a023179b3af5db33b6a659ccf804987f26e8349826d4083ee149· frame —derive{"args":{"left":"fatal","right":"pop"},"name":"fatal_per_pop","op":"ratio"}derive{"args":{"column":"fatal_per_pop","factor":10000},"name":"frate","op":"scale"}
- 1Transformação
fatalities·derive{"args":{"left":"fatal","right":"pop"},"name":"fatal_per_pop","op":"ratio"}336 → 336 linhasFrame antes → depois:63bcb8c60f68→4658e9b711d9 - 2Transformação
fatalities·derive{"args":{"column":"fatal_per_pop","factor":10000},"name":"frate","op":"scale"}336 → 336 linhasFrame antes → depois:4658e9b711d9→fbec03347d8a - 3Ferramenta
infer.olsv0.1.0call_fcd01130decidido pelo códigoreexecutávelArgumentos
{ "cluster": "state", "controls": [], "dataset": "fatalities", "fe": [ "state" ], "intercept": true, "level": 0.95, "se": "HC1", "subset": null, "weights": null, "x": [ "beertax" ], "y": "frate" }Figuras call_fcd01130 Chave Valor Valor bruto Erro-padrão IC coef.beertax Coefficient on beertax in the regression of frate-0,655874 -0.65587372215043090,314848 0.3148475930947355-1,28927 – -0,0224821 Diagnósticosn_obs= 336336k= 4949r2= 0,9050150.905014685169608df_resid= 287287se_type="cluster"n_clusters= 4848fixed_effects="state (48 levels)"
Tabelas (1)
{ "coefficients": [ { "ci_high": 4.506126847112231, "ci_low": 2.449133366231346, "coef": 3.4776301066717887, "p": 1.6311977618807354e-8, "se": 0.5112472177306856, "t": 6.802247496051376, "term": "Intercept" }, { "ci_high": -0.022482063471447655, "ci_low": -1.289265380829414, "coef": -0.6558737221504309, "p": 0.04270329712149496, "se": 0.3148475930947355, "t": -2.083146692352458, "term": "beertax" } ] }- Digests dos dados
fatalitiesfbec03347d8ac47966e488772a52693f33319d956e744370f990665ce749914e- sha256 do resultado
6284c3f10e835ed90b17b750bc0fff8f3746720f11e08606641344cd8d3792c5
- 4Pontuação#0figura próximapassouobrigatória
-0.6558737222 vs -0.6558737221504346 - 5Pontuação#1figura próximapassouobrigatória
0.3148475931 vs 0.31484759309473803 - 6Pontuação#2figura próximapassouobrigatória
-0.6558737222 vs -0.66 - 7Pontuação#3figura próximafalhouregistrada
0.3148475931 vs 0.29
Épocas × verificações
| # | 0 | 1 | 2 | 3 |
|---|---|---|---|---|
| Época 1 | passou | passou | passou | falhou |
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
5cf6a1f8f7d035bba48f3b59be8642745109cc41082743161926ed349e47f91cO 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/stock_watson_fatalities.tab10_1_c2.paper.json | 2,8 KB | 3916f74ed2d41b56ebbd3b560d86c61cdf2c1250bcabea353b4337ac72db4b70 |
| sources/stock_watson_fatalities.tab10_1_c2.software.json | 1,4 KB | 02029cb3ca03fede940432b021201deb6d05816b437bb39cf1bc49c8505eb36e |
| specs/paper_repro.stock_watson_fatalities.tab10_1_c2.tool.json | 6,6 KB | 3a5e3b1a4f63415f31637de80ed0312aaf238c00e116f9fbdba8a07afae31101 |
| traces/paper_repro.stock_watson_fatalities.tab10_1_c2.tool.e1.a1.jsonl | 5,4 KB | 1cf6138fae76d75c33ee92524751da4af00d0a9cc3f05a5d957ee421851882db |
| trajectories/paper_repro.stock_watson_fatalities.tab10_1_c2.tool.e1.a1.jsonl | 9,5 KB | b3be6bb4ee3e4dae53c921c629d8779ec41450e7484230466355955124b91655 |