Tarefa paper_repro.stock_watson_fatalities.tab10_1_c3.design
paper_reproagentT3designépoca 1, tentativa 1Execução: 20261015T165744Z-suite-paper_repro-scripted-def9dfVeredito
Família do método (das chamadas de ferramentas): Regressão linear por mínimos quadrados ordinários (MQO) · infer.ols (ols · regressão linear)
coef.beertax =-0,63998-0.6399799857068672coef.beertax =-0,63998-0.6399799857068721Pergunta feita ao analista
Do higher beer taxes reduce traffic deaths? Using the panel of 48 U.S. states over 1982-1988, estimate the effect of the real beer tax on the traffic fatality rate (deaths per 10,000 residents), controlling for the states' unobserved characteristics that do not change over time and for nationwide changes that affect all states alike.
Estimativa (infer.ols): coef.beertax = -0,6400.
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
fatalities— 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).Transformação "derive" aplicada à base "fatalities" (336 → 336 linhas).{"args":{"left":"fatal","right":"pop"},"name":"fatal_per_pop","op":"ratio"}Transformação "derive" aplicada à base "fatalities" (336 → 336 linhas).{"args":{"column":"fatal_per_pop","factor":10000},"name":"frate","op":"scale"} - 2Chamada que gerou a resposta finalVer chamada call_4fca7863 nos detalhes
infer.ols(Regressão linear por mínimos quadrados ordinários (MQO))citada na respostacoincide com a referênciaStock and Watson Table 10.1, column (3): the traffic fatality rate on the real beer tax with state and year fixed effects, errors clustered by state.
Por que este é o caminho de referência: Stock and Watson Table 10.1, column (3): the traffic fatality rate on the real beer tax with state and year fixed effects, errors clustered by state.Argumentos principais- cluster:
"state"- dataset:
"fatalities"- fe:
["state","year"]- intercept:
true- level:
- 0,95
0.95 - se:
"HC1"- x:
["beertax"]- y:
"frate"
Resultado calculadocoef.beertax= -0,63998-0.6399799857068672Coefficient on beertax in the regression of frate
Diagnósticos:n_obs= 336336(observations used) ·k= 5555(parameters estimated, fixed-effect dummies included) ·r2= 0,9089270.9089266435995828·df_resid= 281281·se_type="cluster"(cluster-robust standard errors (CR1) by 'state') ·n_clusters= 4848(48 clusters of 'state') ·fixed_effects="state (48 levels), year (7 levels)"(absorbed as dummies; their coefficients are not tabulated) - 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:-0,6400Figuras citadas:call_4fca7863:coef.beertax- #0resposta com lastroGarante que todo número citado no texto veio de uma ferramenta ou do enunciado (sem cálculo mental do modelo).
- #1figura da resposta escolhidaan answer figure: the effect of an estimator call the answer cites
- #2uma entreacceptable tools: the reference tool and its alternatives
- #3argumento igual
yT3: the outcome the design question implies - #4argumento igual
x[0]T3: the treatment the design question implies - #5argumento igual
yT3: the outcome the design question implies - #6argumento igual
x[0]T3: the treatment the design question implies - #7argumento igual
youtcome: traffic deaths per 10,000 residents (T3: recorded; a design question cannot state it) - #8argumento igual
festate and year fixed effects (T3: recorded; a design question cannot state it) - #9argumento igual
clustererrors clustered by state (T3: recorded; a design question cannot state it) - #10diagnóstico
n_obs(T3: recorded; a design question cannot state it) - #11figura da resposta próximasoftware reference (T3: recorded; T3 pontua o desenho; a estimativa é registrada)
- #12figura da resposta próximasoftware reference, SE: recorded (T3)
- #13figura da resposta próximapublished cell: recorded, never required on T2/T3
- #14figura da resposta próximapublished cell, SE: recorded, never required on T2/T3
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
stock_watson_fatalities.tab10_1_c3.software
- Fonte
- statsmodels 0.15.0: the reference specification of stock_watson_fatalities tab10_1_c3 (infer.ols, figure 'coef.beertax') on an independent code path
- Tipo
- software
- Localização
- stock_watson_fatalities: Table 10.1, column (3) (state and time effects, clustered standard errors), row 'Beer tax'
- Valor
- -0,63998
-0.6399799857068721(se 0,3857870.385786721792343) - Conferido por
- execução de software · sm.OLS(frate, add_constant(['beertax']), fe dummies ['state', 'year']; 55 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/
- #11 figura da resposta próxima: -0,63998
-0.6399799857068721· relativa 0.000001 · absoluta 3.8578672179234303e-7 - #12 figura da resposta próxima: 0,385787
0.385786721792343· relativa 0.000001 · absoluta 3.8578672179234303e-7
stock_watson_fatalities.tab10_1_c3.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, column (3) (state and 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 (3): −0.64 (0.36)
- Valor como publicado
−0.64- Erro-padrão como publicado
0.36- Valor
- -0,64
-0.64(se 0,360.36) 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.
- #13 figura da resposta próxima: -0,64
-0.64· published_cell d=2 · absoluta 0.0050000010000000004 - #14 figura da resposta próxima: 0,36
0.36· published_cell d=2 (the SE as printed) · absoluta 0.0050000010000000004
Especificação técnica do gabarito
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. Table 10.1 (drunk driving laws and traffic deaths). Table 10.1, column (3) (state and time effects, clustered standard errors), row 'Beer tax' (source stock_watson_fatalities.tab10_1_c3.paper); software reference stock_watson_fatalities.tab10_1_c3.software: statsmodels 0.15.0: the reference specification of stock_watson_fatalities tab10_1_c3 (infer.ols, figure 'coef.beertax') on an independent code path
Verificações
| # | Verificação | Obrigatória | Resultado | Esperado | Observado | Tolerância | Fonte | Chamada |
|---|---|---|---|---|---|---|---|---|
| 0 | resposta com lastro Garante que todo número citado no texto veio de uma ferramenta ou do enunciado (sem cálculo mental do modelo). every number backed | obrigatória | passou | 0 sem lastro | 0 sem lastro[] | — | — | — |
| 1 | figura da resposta escolhida an answer figure: the effect of an estimator call the answer cites answer figure call_4fca7863:coef.beertax (infer.ols) | obrigatória | passou | — | "call_4fca7863:coef.beertax" | — | — | call_4fca7863 |
| 2 | uma entre acceptable tools: the reference tool and its alternatives tool_called(infer.ols): ok | tool_called(infer.fe): answer call is infer.ols | obrigatória | passou | [{"abs_tol":null,"bind":"answer_call","column":null,"failure_class":null,"field":"value","interval":false,"key":null,"kind":"tool_called","min_lre":null,"note":"","open_interval":false,"rel_tol":null,"required":true,"source_id":null,"table":null,"tool":"infer.ols","value":null,"weight":1,"where":null},{"abs_tol":null,"bind":"answer_call","column":null,"failure_class":null,"field":"value","interval":false,"key":null,"kind":"tool_called","min_lre":null,"note":"","open_interval":false,"rel_tol":null,"required":true,"source_id":null,"table":null,"tool":"infer.fe","value":null,"weight":1,"where":null}] | "infer.ols" | — | — | call_4fca7863 |
| 3 | argumento igual yT3: the outcome the design question implies infer.ols.y = 'frate' | obrigatória | passou | "frate" | "frate" | — | — | call_4fca7863 |
| 4 | argumento igual x[0]T3: the treatment the design question implies infer.ols.x[0] = 'beertax' | obrigatória | passou | "beertax" | "beertax" | — | — | call_4fca7863 |
| 5 | argumento igual yT3: the outcome the design question implies not applicable: the answer call is infer.ols, not infer.fe | obrigatória | passou | "frate" | — | — | — | call_4fca7863 |
| 6 | argumento igual x[0]T3: the treatment the design question implies not applicable: the answer call is infer.ols, not infer.fe | obrigatória | passou | "beertax" | — | — | — | call_4fca7863 |
| 7 | argumento igual youtcome: traffic deaths per 10,000 residents (T3: recorded; a design question cannot state it) infer.ols.y = 'frate' | registrada | passou | "frate" | "frate" | — | — | call_4fca7863 |
| 8 | argumento igual festate and year fixed effects (T3: recorded; a design question cannot state it) infer.ols.fe = ['state', 'year'] | registrada | passou | ["state","year"] | ["state","year"] | — | — | call_4fca7863 |
| 9 | argumento igual clustererrors clustered by state (T3: recorded; a design question cannot state it) infer.ols.cluster = 'state' | registrada | passou | "state" | "state" | — | — | call_4fca7863 |
| 10 | diagnóstico n_obs(T3: recorded; a design question cannot state it) 336 vs 336 | registrada | passou | 336336 | 336336 | default rel 1e-6 (abs floor 1e-6) | — | call_4fca7863 |
| 11 | figura da resposta próxima software reference (T3: recorded; T3 pontua o desenho; a estimativa é registrada) -0.6399799857 vs -0.6399799857068721 | registrada | passou | -0,63998-0.6399799857068721 | -0,63998-0.6399799857068672 | relativa 0.000001 · absoluta 3.8578672179234303e-7 | stock_watson_fatalities.tab10_1_c3.software | call_4fca7863 |
| 12 | figura da resposta próxima software reference, SE: recorded (T3) 0.3857867218 vs 0.385786721792343 | registrada | passou | 0,3857870.385786721792343 | 0,3857870.38578672179234064 | relativa 0.000001 · absoluta 3.8578672179234303e-7 | stock_watson_fatalities.tab10_1_c3.software | call_4fca7863 |
| 13 | figura da resposta próxima published cell: recorded, never required on T2/T3 -0.6399799857 vs -0.64 | registrada | passou | -0,64-0.64 | -0,63998-0.6399799857068672 | published_cell d=2 · absoluta 0.0050000010000000004 | stock_watson_fatalities.tab10_1_c3.paper | call_4fca7863 |
| 14 | figura da resposta próxima published cell, SE: recorded, never required on T2/T3 0.3857867218 vs 0.36 | registrada | falhou | 0,360.36 | 0,3857870.38578672179234064 | published_cell d=2 (the SE as printed) · absoluta 0.0050000010000000004 | stock_watson_fatalities.tab10_1_c3.paper | call_4fca7863 |
Caminho de referência e caminho do agente
A chamada de referência ao lado da chamada que deu a resposta, argumento por argumento.
a tarefa T1 do mesmo alvo (paper_repro.stock_watson_fatalities.tab10_1_c3.tool)
| Argumento | Referência | Agente | |
|---|---|---|---|
| cluster | "state" | "state" | igual |
| controls | [] | [] | igual |
| dataset | "fatalities" | "fatalities" | igual |
| fe | ["state","year"] | ["state","year"] | 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
Do higher beer taxes reduce traffic deaths? Using the panel of 48 U.S. states over 1982-1988, estimate the effect of the real beer tax on the traffic fatality rate (deaths per 10,000 residents), controlling for the states' unobserved characteristics that do not change over time and for nationwide changes that affect all states alike.
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 - 3Turno do modelo
call_7150652freferenceFim:tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cacheTexto visívelStock and Watson Table 10.1, column (3): the traffic fatality rate on the real beer tax with state and year fixed effects, errors clustered by state.
Chamadas pedidasinfer.ols{ "cluster": "state", "controls": [], "dataset": "fatalities", "fe": [ "state", "year" ], "x": [ "beertax" ], "y": "frate" }
- 4Ferramenta
infer.ols— Regressão linear por mínimos quadrados ordinários (MQO)v0.1.0call_4fca7863decidido pelo modeloreexecutávelMotivo: Stock and Watson Table 10.1, column (3): the traffic fatality rate on the real beer tax with state and year fixed effects, errors clustered by state.
Argumentos
{ "cluster": "state", "controls": [], "dataset": "fatalities", "fe": [ "state", "year" ], "intercept": true, "level": 0.95, "se": "HC1", "subset": null, "weights": null, "x": [ "beertax" ], "y": "frate" }Figuras call_4fca7863 Chave Valor Valor bruto Erro-padrão IC coef.beertax Coefficient on beertax in the regression of frate-0,63998 -0.63997998570686720,385787 0.38578672179234064-1,41608 – 0,136123 Diagnósticosn_obs= 336336(observations used)k= 5555(parameters estimated, fixed-effect dummies included)r2= 0,9089270.9089266435995828df_resid= 281281se_type="cluster"(cluster-robust standard errors (CR1) by 'state')n_clusters= 4848(48 clusters of 'state')fixed_effects="state (48 levels), year (7 levels)"(absorbed as dummies; their coefficients are not tabulated)
Derivação matemática e pressupostos
coef.beertax- Coeficiente de beertax na regressão por mínimos quadrados ordinários de frate, efeitos fixos de state, year.→ -0,63998 (-0.6399799857068672)
- Erro-padrão robusto por conglomerado (CR1): a raiz da variância estimada do coeficiente.
ep = √V_jj→ 0,385787 (0.38578672179234064) - Intervalo de 95% de confiança: a estimativa mais ou menos o valor crítico da distribuição t de Student com 47 graus de liberdade vezes o erro-padrão.
IC = β ± c · ep
Pressupostos do estimador- the conditional mean of the outcome is linear in the regressors
- errors are independent across clusters of 'state' and may be correlated within them
Tabelas (1)
{ "coefficients": [ { "ci_high": 4.806427061916114, "ci_low": 2.216322623371488, "coef": 3.5113748426438014, "p": 0.0000017820972417412704, "se": 0.6437471485183183, "t": 5.454587023376746, "term": "Intercept" }, { "ci_high": 0.13612279218177825, "ci_low": -1.4160827635955127, "coef": -0.6399799857068672, "p": 0.1037964594597914, "se": 0.38578672179234064, "t": -1.658895834293002, "term": "beertax" } ] }Hashes SHA-256 e metadados de reprodução
- Digests dos dados
fatalitiesfbec03347d8ac47966e488772a52693f33319d956e744370f990665ce749914e- sha256 do resultado
609984de8b85083b92d7f9b8c34fc0fc7a982612711848732fa4568d1528b6fb
- 5Turno do modelo
call_75c62da5referenceFim:tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cacheChamadas pedidassubmit_answer(meta-ferramenta){ "answer": "Estimativa (infer.ols): coef.beertax = -0,6400.", "caveats": [], "figure_refs": [ "call_4fca7863:coef.beertax" ] }
- 6Guardaresposta aceita
- Números encontrados
- -0,6400
- Sem lastro
- —
- Não citados
- —
1 nova(s) tentativa(s) restante(s) - 7Resposta
Estimativa (infer.ols): coef.beertax = -0,6400.
Figuras citadas:call_4fca7863:coef.beertax· Parada:answeredFigura da resposta:call_4fca7863:coef.beertax= -0,63998-0.6399799857068672(se 0,3857870.38578672179234064) - 8Pontuação#0resposta com lastropassouobrigatória
every number backed - 9Pontuação#1figura da resposta escolhidapassouobrigatória
answer figure call_4fca7863:coef.beertax (infer.ols) - 10Pontuação#2uma entrepassouobrigatória
tool_called(infer.ols): ok | tool_called(infer.fe): answer call is infer.ols - 11Pontuação#3argumento igualpassouobrigatória
infer.ols.y = 'frate' - 12Pontuação#4argumento igualpassouobrigatória
infer.ols.x[0] = 'beertax' - 13Pontuação#5argumento igualpassouobrigatória
not applicable: the answer call is infer.ols, not infer.fe - 14Pontuação#6argumento igualpassouobrigatória
not applicable: the answer call is infer.ols, not infer.fe - 15Pontuação#7argumento igualpassouregistrada
infer.ols.y = 'frate' - 16Pontuação#8argumento igualpassouregistrada
infer.ols.fe = ['state', 'year'] - 17Pontuação#9argumento igualpassouregistrada
infer.ols.cluster = 'state' - 18Pontuação#10diagnósticopassouregistrada
336 vs 336 - 19Pontuação#11figura da resposta próximapassouregistrada
-0.6399799857 vs -0.6399799857068721 - 20Pontuação#12figura da resposta próximapassouregistrada
0.3857867218 vs 0.385786721792343 - 21Pontuação#13figura da resposta próximapassouregistrada
-0.6399799857 vs -0.64 - 22Pontuação#14figura da resposta próximafalhouregistrada
0.3857867218 vs 0.36
Épocas × verificações
| # | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Época 1 | passou | passou | passou | passou | passou | passou | passou | passou | passou | passou | passou | 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
4f48cd12e9d9a2eea0ece2ae3b0cca00a60a9aa38618eb3ed890e349075ee697O 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.