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Tarefa paper_repro.fujiwara_2015.tab2_pa_valid98_c1.design

paper_reproagentT3designépoca 1, tentativa 1Execução: 20261015T165744Z-suite-paper_repro-scripted-def9df

Veredito

passouPassou em todas as verificações obrigatórias.

Família do método (das chamadas de ferramentas): Regressão descontínua (RDD) · infer.rdd (rd · regressão descontínua)

Calculado pelo agente
effect =0,1179440.11794391631664342
Jump in r_util98 at the cutoff of voters96
via infer.rdd (call_6ce37c75)
Valor esperado (gabarito)
effect =0,1179440.11794391631644154
statsmodels 0.15.0: the reference specification of fujiwara_2015 tab2_pa_valid98_c1 (infer.rdd, figure 'effect') on an independent code path
Como foi validado
6 de 6 verificações obrigatórias aprovadas
relativa 0.000001 · absoluta 1.512713195366677e-8

Pergunta feita ao analista

Did electronic voting raise the share of votes that counted? In the 1998 Brazilian elections only municipalities with more than 40,500 registered voters in 1996 voted electronically. Estimate the effect of electronic voting on valid votes as a share of turnout in that year's state legislature elections, for municipalities near that threshold.

Resposta

Estimativa (infer.rdd): effect = 0,1179.

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
    munic— The author's municipality file for Fujiwara (2015), 'Voting Technology, Political Responsiveness, and Infant Health: Evidence from Brazil': one row per Brazilian municipality (5,281 rows). In the 1998 elections, municipalities with more than 40,500 registered voters in 1996 used electronic voting and the others paper ballots; in 1994 every municipality used paper ballots and in 2002 every one voted electronically. Columns: uf, state; voters96, number of registered voters in 1996; r_util98, r_util94, r_util02, valid votes as a share of turnout in the state legislature elections of 1998, 1994 and 2002; attend, turnout as a share of registered voters (1998); regist, registered voters as a share of population (1998); null_est_share and blank_est_share, null and blank votes as a share of turnout (state legislature, 1998); util_pres_share, util_gov_share, util_fed_share, util_sen_share, valid votes as a share of turnout in the presidential, gubernatorial, federal lower chamber and senate elections (1998); right, vote-weighted party ideology; right_meas, votes for parties with measured ideology over total valid votes; right_state, state average of right; illiter, illiteracy rate (percent); less4 and less8, shares without 4 and without 8 years of schooling; gini, Gini index; income, monthly income; latitude; longitude; urbanization, share of urban population; population91 and population00, population in 1991 and 2000 (thousands). The schooling, income, inequality and urbanization variables come from the 1991 census.
  2. 2Chamada que gerou a resposta finalinfer.rdd(Regressão descontínua (RDD))citada na respostacoincide com a referência
    Ver chamada call_6ce37c75 nos detalhes

    Table II, Panel A, column (1): local linear RD at 40,500 voters, rectangular kernel, the paper's IK bandwidth 11,873, passed as printed, robust errors (munic.do: reg y treat dep deptreat if bw<h, rob).

    Por que este é o caminho de referência: Table II, Panel A, column (1): local linear RD at 40,500 voters, rectangular kernel, the paper's IK bandwidth 11,873, passed as printed, robust errors (munic.do: reg y treat dep deptreat if bw<h, rob).
    Argumentos principais
    bandwidth:
    11.87311873
    cutoff:
    40.50040500
    dataset:
    "munic"
    kernel:
    "uniform"
    level:
    0,950.95
    polynomial:
    11
    running:
    "voters96"
    y:
    "r_util98"
    Resultado calculado
    • effect = 0,117944 0.11794391631664342
      Jump in r_util98 at the cutoff of voters96
    Diagnósticos: bandwidth = 11.87311873 (half-width of the window around the cutoff (informada)) · bandwidth_method = "user" · n_left = 174174 (observations with positive weight below the cutoff) · n_right = 9191 (observations with positive weight at or above the cutoff) · kernel = "uniform" · polynomial = 11 · bandwidth_sensitive = false (the estimates at half and double the bandwidth fall inside the main interval) · n_obs = 5.2815281 (rows used to choose the bandwidth) · se_type = "HC1" (heteroskedasticity-robust standard errors (HC1))
  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: 0,1179
    Figuras citadas: call_6ce37c75:effect
    • #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.rdd
      Exige que o resultado venha da ferramenta infer.rdd.
    • #3argumento igualy
      T3: the outcome the design question implies
    • #4argumento igualrunning
      T3: the running the design question implies
    • #5argumento igualcutoff
      T3: the cutoff the design question implies
    • #6argumento igualy
      outcome (T3: recorded; a design question cannot state it)
    • #7argumento igualrunning
      running variable: registered voters, 1996 (T3: recorded; a design question cannot state it)
    • #8argumento igualcutoff
      the electronic-voting threshold (T3: recorded; a design question cannot state it)
    • #9argumento igualbandwidth
      the paper's bandwidth for this column (T3: recorded; a design question cannot state it)
    • #10argumento igualkernel
      rectangular kernel: unweighted observations (T3: recorded; a design question cannot state it)
    • #11argumento igualpolynomial
      local linear (T3: recorded; a design question cannot state it)
    • #12diagnósticon_left
      (T3: recorded; a design question cannot state it)
    • #13diagnósticon_right
      (T3: recorded; a design question cannot state it)
    • #14figura da resposta próxima
      software reference (T3: recorded; T3 pontua o desenho; a estimativa é registrada)
    • #15figura da resposta próxima
      software reference, SE: recorded (T3)
    • #16figura da resposta próxima
      published cell: recorded, never required on T2/T3
    • #17figura da resposta próxima
      published 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

fujiwara_2015.tab2_pa_valid98_c1.software

Fonte
statsmodels 0.15.0: the reference specification of fujiwara_2015 tab2_pa_valid98_c1 (infer.rdd, figure 'effect') on an independent code path
Tipo
software
Localização
fujiwara_2015: Table II, Panel A, row 'Valid Votes/Turnout (1998 Election)', column (1) at the IKBW bandwidth
Valor
0,1179440.11794391631644154 (se 0,01512710.015127131953666773)
Conferido por
execução de software · sm.OLS(r_util98, [const, treat, d·(1-treat), d·treat]).fit(cov_type='HC1') with d = voters96 - 40500, rows |d| <= 11873, treat = d >= 0 on munic (munic.dta of the file pinned at sha256 5cd5b8796355e025807dc303263b1fbb16f442c3c7551f14ee3557768a310894); n_obs = 5281, n_left = 174, n_right = 91. The tool infer.rdd (magi_infer, numpy) does not call statsmodels. Note: the strict rule (|d| < h, treated when d > 0) selects the same rows and treatment. Written by scripts/paper_repro_reference.py.
Implementação
independente da ferramenta
Endereço
https://pypi.org/project/statsmodels/0.15.0/
  • #14 figura da resposta próxima: 0,1179440.11794391631644154 · relativa 0.000001 · absoluta 1.512713195366677e-8
  • #15 figura da resposta próxima: 0,01512710.015127131953666773 · relativa 0.000001 · absoluta 1.512713195366677e-8

fujiwara_2015.tab2_pa_valid98_c1.paper

Fonte
Fujiwara, T. (2015). Voting Technology, Political Responsiveness, and Infant Health: Evidence From Brazil. Econometrica 83(2): 423-464.
Tipo
paper
Localização
Table II (treatment effects of electronic voting), Panel A (baseline results), row 'Valid Votes/Turnout (1998 Election)', column (1), bandwidth IKBW, linear
Página
436
Trecho
Valid Votes/Turnout (1998 Election) 0.118 (0.015)
Valor como publicado
0.118
Erro-padrão como publicado
0.015
Valor
0,1180.118 (se 0,0150.015) share of turnout (valid votes / turnout)
Conferido por
fonte primária · Read on 2026-10-15 from the published Econometrica version on the author's Princeton page (43-page PDF; Table II on PDF page 15) from the rendered page image; pdftotext drops this PDF's decimal-point glyph. Table II notes: robust standard errors; each cell a separate local linear regression. Data check made before any estimate: voters96 is integer-valued, no municipality has exactly 40,500 voters and none sits on a bandwidth edge, so munic.do's strict inequalities (treat if dep>0, bw<h) select the rows the tool's (running >= cutoff, |running - cutoff| <= h) select. IKBW column: 11,873 {265}.
sha256 da cópia lida
e2d693b96b22ea0dec46893e9b1f1a3a5399a23d844bcd0ec58e9e1c410a0600 (identifica a cópia lida, não um arquivo canônico)
Endereço
https://www.princeton.edu/~fujiwara/papers/elecvote_site.pdf
Licença
Copyright The Econometric Society; cited, not reproduced.
  • #16 figura da resposta próxima: 0,1180.118 · published_cell d=3 · absoluta 0.000500001
  • #17 figura da resposta próxima: 0,0150.015 · published_cell d=3 (the SE as printed) · absoluta 0.000500001
Especificação técnica do gabarito

Fujiwara, T. (2015). Voting Technology, Political Responsiveness, and Infant Health: Evidence From Brazil. Econometrica 83(2): 423-464. Table II, Panel A, row 'Valid Votes/Turnout (1998 Election)', column (1) at the IKBW bandwidth (source fujiwara_2015.tab2_pa_valid98_c1.paper); software reference fujiwara_2015.tab2_pa_valid98_c1.software: statsmodels 0.15.0: the reference specification of fujiwara_2015 tab2_pa_valid98_c1 (infer.rdd, figure 'effect') on an independent code path

Verificações

Cada verificação, o que esperava, o que observou e a chamada que leu
#VerificaçãoObrigatóriaResultadoEsperadoObservadoTolerânciaFonteChamada
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
obrigatóriapassou0 sem lastro0 sem lastro[]———
1
figura da resposta escolhida
an answer figure: the effect of an estimator call the answer cites
answer figure call_6ce37c75:effect (infer.rdd)
obrigatóriapassou—"call_6ce37c75:effect"——call_6ce37c75
2
ferramenta chamadainfer.rdd
Exige que o resultado venha da ferramenta infer.rdd.
answer call is infer.rdd
obrigatóriapassou"infer.rdd""infer.rdd"——call_6ce37c75
3
argumento igualy
T3: the outcome the design question implies
infer.rdd.y = 'r_util98'
obrigatóriapassou"r_util98""r_util98"——call_6ce37c75
4
argumento igualrunning
T3: the running the design question implies
infer.rdd.running = 'voters96'
obrigatóriapassou"voters96""voters96"——call_6ce37c75
5
argumento igualcutoff
T3: the cutoff the design question implies
infer.rdd.cutoff = 40500.0
obrigatóriapassou40.5004050040.50040500——call_6ce37c75
6
argumento igualy
outcome (T3: recorded; a design question cannot state it)
infer.rdd.y = 'r_util98'
registradapassou"r_util98""r_util98"——call_6ce37c75
7
argumento igualrunning
running variable: registered voters, 1996 (T3: recorded; a design question cannot state it)
infer.rdd.running = 'voters96'
registradapassou"voters96""voters96"——call_6ce37c75
8
argumento igualcutoff
the electronic-voting threshold (T3: recorded; a design question cannot state it)
infer.rdd.cutoff = 40500.0
registradapassou40.5004050040.50040500——call_6ce37c75
9
argumento igualbandwidth
the paper's bandwidth for this column (T3: recorded; a design question cannot state it)
infer.rdd.bandwidth = 11873.0
registradapassou11.8731187311.87311873——call_6ce37c75
10
argumento igualkernel
rectangular kernel: unweighted observations (T3: recorded; a design question cannot state it)
infer.rdd.kernel = 'uniform'
registradapassou"uniform""uniform"——call_6ce37c75
11
argumento igualpolynomial
local linear (T3: recorded; a design question cannot state it)
infer.rdd.polynomial = 1
registradapassou1111——call_6ce37c75
12
diagnósticon_left
(T3: recorded; a design question cannot state it)
174 vs 174
registradapassou174174174174default rel 1e-6 (abs floor 1e-6)—call_6ce37c75
13
diagnósticon_right
(T3: recorded; a design question cannot state it)
91 vs 91
registradapassou91919191default rel 1e-6 (abs floor 1e-6)—call_6ce37c75
14
figura da resposta próxima
software reference (T3: recorded; T3 pontua o desenho; a estimativa é registrada)
0.1179439163 vs 0.11794391631644154
registradapassou0,1179440.117943916316441540,1179440.11794391631664342relativa 0.000001 · absoluta 1.512713195366677e-8fujiwara_2015.tab2_pa_valid98_c1.softwarecall_6ce37c75
15
figura da resposta próxima
software reference, SE: recorded (T3)
0.01512713195 vs 0.015127131953666773
registradapassou0,01512710.0151271319536667730,01512710.015127131953692786relativa 0.000001 · absoluta 1.512713195366677e-8fujiwara_2015.tab2_pa_valid98_c1.softwarecall_6ce37c75
16
figura da resposta próxima
published cell: recorded, never required on T2/T3
0.1179439163 vs 0.118
registradapassou0,1180.1180,1179440.11794391631664342published_cell d=3 · absoluta 0.000500001fujiwara_2015.tab2_pa_valid98_c1.papercall_6ce37c75
17
figura da resposta próxima
published cell, SE: recorded, never required on T2/T3
0.01512713195 vs 0.015
registradapassou0,0150.0150,01512710.015127131953692786published_cell d=3 (the SE as printed) · absoluta 0.000500001fujiwara_2015.tab2_pa_valid98_c1.papercall_6ce37c75

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.fujiwara_2015.tab2_pa_valid98_c1.tool)

Referência: infer.rddChamada do agente: infer.rdd (call_6ce37c75)igual
Argumentos da referência e do agente
ArgumentoReferênciaAgente
bandwidth11.8731187311.87311873igual
cluster——não fixado pela referência
cutoff40.5004050040.50040500igual
dataset"munic""munic"igual
kernel"uniform""uniform"igual
level—0,950.95não fixado pela referência
polynomial1111igual
running"voters96""voters96"igual
subset——não fixado pela referência
y"r_util98""r_util98"igual

Trajetória

Cada evento na ordem em que aconteceu: turnos do modelo, chamadas de ferramentas, guardas, transformações e pontuação.

  1. 0Início

    Did electronic voting raise the share of votes that counted? In the 1998 Brazilian elections only municipalities with more than 40,500 registered voters in 1996 voted electronically. Estimate the effect of electronic voting on valid votes as a share of turnout in that year's state legislature elections, for municipalities near that threshold.

    munic (agent)

    The author's municipality file for Fujiwara (2015), 'Voting Technology, Political Responsiveness, and Infant Health: Evidence from Brazil': one row per Brazilian municipality (5,281 rows). In the 1998 elections, municipalities with more than 40,500 registered voters in 1996 used electronic voting and the others paper ballots; in 1994 every municipality used paper ballots and in 2002 every one voted electronically. Columns: uf, state; voters96, number of registered voters in 1996; r_util98, r_util94, r_util02, valid votes as a share of turnout in the state legislature elections of 1998, 1994 and 2002; attend, turnout as a share of registered voters (1998); regist, registered voters as a share of population (1998); null_est_share and blank_est_share, null and blank votes as a share of turnout (state legislature, 1998); util_pres_share, util_gov_share, util_fed_share, util_sen_share, valid votes as a share of turnout in the presidential, gubernatorial, federal lower chamber and senate elections (1998); right, vote-weighted party ideology; right_meas, votes for parties with measured ideology over total valid votes; right_state, state average of right; illiter, illiteracy rate (percent); less4 and less8, shares without 4 and without 8 years of schooling; gini, Gini index; income, monthly income; latitude; longitude; urbanization, share of urban population; population91 and population00, population in 1991 and 2000 (thousands). The schooling, income, inequality and urbanization variables come from the 1991 census.

    file 5cd5b8796355e025807dc303263b1fbb16f442c3c7551f14ee3557768a310894 · frame —
  2. 1Turno do modelo
    call_5c2e510dreferenceFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache
    Texto visível

    Table II, Panel A, column (1): local linear RD at 40,500 voters, rectangular kernel, the paper's IK bandwidth 11,873, passed as printed, robust errors (munic.do: reg y treat dep deptreat if bw<h, rob).

    Chamadas pedidas
    • infer.rdd
      {
        "bandwidth": 11873,
        "cutoff": 40500,
        "dataset": "munic",
        "kernel": "uniform",
        "polynomial": 1,
        "running": "voters96",
        "y": "r_util98"
      }
  3. 2Ferramenta
    infer.rdd— Regressão descontínua (RDD)v0.1.0call_6ce37c75decidido pelo modeloreexecutável

    Motivo: Table II, Panel A, column (1): local linear RD at 40,500 voters, rectangular kernel, the paper's IK bandwidth 11,873, passed as printed, robust errors (munic.do: reg y treat dep deptreat if bw<h, rob).

    Argumentos
    {
      "bandwidth": 11873,
      "cluster": null,
      "cutoff": 40500,
      "dataset": "munic",
      "kernel": "uniform",
      "level": 0.95,
      "polynomial": 1,
      "running": "voters96",
      "subset": null,
      "y": "r_util98"
    }
    Figuras call_6ce37c75
    ChaveValorValor brutoErro-padrãoIC
    effect
    Jump in r_util98 at the cutoff of voters96
    0,1179440.117943916316643420,01512710.0151271319536927860,0882953 – 0,147593
    Diagnósticos
    • bandwidth = 11.87311873 (half-width of the window around the cutoff (informada))
    • bandwidth_method = "user"
    • n_left = 174174 (observations with positive weight below the cutoff)
    • n_right = 9191 (observations with positive weight at or above the cutoff)
    • kernel = "uniform"
    • polynomial = 11
    • bandwidth_sensitive = false (the estimates at half and double the bandwidth fall inside the main interval)
    • n_obs = 5.2815281 (rows used to choose the bandwidth)
    • se_type = "HC1" (heteroskedasticity-robust standard errors (HC1))
    Derivação matemática e pressupostos
    effect
    1. Ajuste linear ponderado (kernel uniforme) de cada lado do limiar, com janela h (informada); o efeito é a diferença entre os dois ajustes no limiar.→ 0,117944 (0.11794391631664342)
    2. Erro-padrão robusto à heterocedasticidade (HC1): a raiz da variância estimada do coeficiente.ep = √V_jj→ 0,0151271 (0.015127131953692786)
    3. Intervalo de 95% de confiança: a estimativa mais ou menos o valor crítico da distribuição normal vezes o erro-padrão.IC = τ ± c · ep
    Pressupostos do estimador
    • units cannot precisely control the running variable around the cutoff
    • every other determinant of the outcome is continuous at the cutoff
    Tabelas (1)
    {
      "sensitivity": [
        {
          "bandwidth": 5936.5,
          "ci_high": 0.16768329170779034,
          "ci_low": 0.07974345804003045,
          "estimate": 0.1237133748739104,
          "multiplier": 0.5,
          "n_left": 84,
          "n_right": 46,
          "se": 0.022434043268503425
        },
        {
          "bandwidth": 11873,
          "ci_high": 0.1475925501352663,
          "ci_low": 0.08829528249802053,
          "estimate": 0.11794391631664342,
          "multiplier": 1,
          "n_left": 174,
          "n_right": 91,
          "se": 0.015127131953692786
        },
        {
          "bandwidth": 23746,
          "ci_high": 0.14150882582203791,
          "ci_low": 0.10232687378670113,
          "estimate": 0.12191784980436952,
          "multiplier": 2,
          "n_left": 681,
          "n_right": 146,
          "se": 0.009995579598502577
        }
      ]
    }
    Hashes SHA-256 e metadados de reprodução
    Digests dos dados
    munic 4849fb53b02d5e1e529b6e802d6e90e871843cf5f89da8ad229cd022bbd01f2e
    sha256 do resultado
    f50915bfd0e101ff88445d2248a08301d3ece7e8060e8057c909c8bbdfaa2754
  4. 3Turno do modelo
    call_1d31931breferenceFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache
    Chamadas pedidas
    • submit_answer (meta-ferramenta)
      {
        "answer": "Estimativa (infer.rdd): effect = 0,1179.",
        "caveats": [],
        "figure_refs": [
          "call_6ce37c75:effect"
        ]
      }
  5. 4Guarda
    resposta aceita
    Números encontrados
    0,1179
    Sem lastro
    —
    Não citados
    —
    1 nova(s) tentativa(s) restante(s)
  6. 5Resposta

    Estimativa (infer.rdd): effect = 0,1179.

    Figuras citadas: call_6ce37c75:effect · Parada: answered
    Figura da resposta: call_6ce37c75:effect = 0,1179440.11794391631664342 (se 0,01512710.015127131953692786)
  7. 6Pontuação
    #0resposta com lastropassouobrigatóriaevery number backed
  8. 7Pontuação
    #1figura da resposta escolhidapassouobrigatóriaanswer figure call_6ce37c75:effect (infer.rdd)
  9. 8Pontuação
    #2ferramenta chamadapassouobrigatóriaanswer call is infer.rdd
  10. 9Pontuação
    #3argumento igualpassouobrigatóriainfer.rdd.y = 'r_util98'
  11. 10Pontuação
    #4argumento igualpassouobrigatóriainfer.rdd.running = 'voters96'
  12. 11Pontuação
    #5argumento igualpassouobrigatóriainfer.rdd.cutoff = 40500.0
  13. 12Pontuação
    #6argumento igualpassouregistradainfer.rdd.y = 'r_util98'
  14. 13Pontuação
    #7argumento igualpassouregistradainfer.rdd.running = 'voters96'
  15. 14Pontuação
    #8argumento igualpassouregistradainfer.rdd.cutoff = 40500.0
  16. 15Pontuação
    #9argumento igualpassouregistradainfer.rdd.bandwidth = 11873.0
  17. 16Pontuação
    #10argumento igualpassouregistradainfer.rdd.kernel = 'uniform'
  18. 17Pontuação
    #11argumento igualpassouregistradainfer.rdd.polynomial = 1
  19. 18Pontuação
    #12diagnósticopassouregistrada174 vs 174
  20. 19Pontuação
    #13diagnósticopassouregistrada91 vs 91
  21. 20Pontuação
    #14figura da resposta próximapassouregistrada0.1179439163 vs 0.11794391631644154
  22. 21Pontuação
    #15figura da resposta próximapassouregistrada0.01512713195 vs 0.015127131953666773
  23. 22Pontuação
    #16figura da resposta próximapassouregistrada0.1179439163 vs 0.118
  24. 23Pontuação
    #17figura da resposta próximapassouregistrada0.01512713195 vs 0.015

Épocas × verificações

Resultado de cada verificação em cada época pontuada
#01234567891011121314151617
Época 1passoupassoupassoupassoupassoupassoupassoupassoupassoupassoupassoupassoupassoupassoupassoupassoupassoupassou

Tentativas

Cada tentativa é seu próprio arquivo e é publicada; só a última de cada época é pontuada.

Downloads desta tarefa

Pacote da tarefa (.zip)
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