Tarefa paper_repro.fujiwara_2015.tab2_pa_valid98_c1.agent

Veredito

Pergunta feita ao analista

Fujiwara, T. (2015), 'Voting Technology, Political Responsiveness, and Infant Health: Evidence from Brazil', Table II, Panel A, column (1): estimate the jump in valid votes as a share of turnout in the 1998 state legislature elections at the threshold of 40,500 registered voters in 1996, above which municipalities voted electronically in the 1998 elections, as a sharp regression discontinuity. Use a local linear regression on each side of the threshold with a rectangular kernel (unweighted observations), the Imbens-Kalyanaraman bandwidth the paper reports for this outcome, 11,873 registered voters (use that bandwidth as given; do not recompute it), and heteroskedasticity-robust standard errors. Report the jump at the threshold.

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_d74ba263 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_d74ba263: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

     outcome
   • ✓
     #4argumento igualrunning

     running variable: registered voters, 1996
   • ✓
     #5argumento igualcutoff

     the electronic-voting threshold
   • ✓
     #6argumento igualbandwidth

     the paper's bandwidth for this column
   • ✓
     #7argumento igualkernel

     rectangular kernel: unweighted observations
   • ✓
     #8argumento igualpolynomial

     local linear
   • ✓
     #9diagnósticon_left

     Confere o diagnóstico "n_left" reportado pela ferramenta.
   • ✓
     #10diagnósticon_right

     Confere o diagnóstico "n_right" reportado pela ferramenta.
   • ✓
     #11figura da resposta próxima

     software reference
   • ✓
     #12figura da resposta próxima

     software reference, SE (the question states the convention)
   • ✓
     #13figura da resposta próxima

     published cell: recorded, never required on T2/T3
   • ✓
     #14figura da resposta próxima

     published cell, SE: recorded, never required on T2/T3

Valores esperados e de onde vêm

Verificações

Caminho de referência e caminho do agente

A chamada de referência ao lado da chamada que deu a resposta, argumento por argumento.

Trajetória

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

1. 0Início

   Fujiwara, T. (2015), 'Voting Technology, Political Responsiveness, and Infant Health: Evidence from Brazil', Table II, Panel A, column (1): estimate the jump in valid votes as a share of turnout in the 1998 state legislature elections at the threshold of 40,500 registered voters in 1996, above which municipalities voted electronically in the 1998 elections, as a sharp regression discontinuity. Use a local linear regression on each side of the threshold with a rectangular kernel (unweighted observations), the Imbens-Kalyanaraman bandwidth the paper reports for this outcome, 11,873 registered voters (use that bandwidth as given; do not recompute it), and heteroskedasticity-robust standard errors. Report the jump at the 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_3a5e3ce8referenceFim: 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"
     }

   Mensagens (formato neutro)Instruções do sistemaFerramentas oferecidas
3. 2Ferramenta
   infer.rdd— Regressão descontínua (RDD)v0.1.0call_d74ba263decidido 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_d74ba263

   Chave	Valor	Valor bruto	Erro-padrão	IC
   effect Jump in r_util98 at the cutoff of voters96	0,117944	0.11794391631664342	0,01512710.015127131953692786	0,0882953 – 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

   2a8b70e5e9926482477d3556f68bdf4ed763373389098ef100319c38f841b11a

   Resultado mostrado ao modelo
4. 3Turno do modelo
   call_d813e718referenceFim: 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_d74ba263:effect"
       ]
     }

   Mensagens (formato neutro)Instruções do sistemaFerramentas oferecidas
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_d74ba263:effect · Parada: answered

   Figura da resposta: call_d74ba263:effect = 0,1179440.11794391631664342 (se 0,01512710.015127131953692786)
7. 6Pontuação
   #0resposta com lastropassouobrigatóriaevery number backed
8. 7Pontuação
   #1figura da resposta escolhidapassouobrigatóriaanswer figure call_d74ba263: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 igualpassouobrigatóriainfer.rdd.bandwidth = 11873.0
14. 13Pontuação
    #7argumento igualpassouobrigatóriainfer.rdd.kernel = 'uniform'
15. 14Pontuação
    #8argumento igualpassouobrigatóriainfer.rdd.polynomial = 1
16. 15Pontuação
    #9diagnósticopassouobrigatória174 vs 174
17. 16Pontuação
    #10diagnósticopassouobrigatória91 vs 91
18. 17Pontuação
    #11figura da resposta próximapassouobrigatória0.1179439163 vs 0.11794391631644154
19. 18Pontuação
    #12figura da resposta próximapassouobrigatória0.01512713195 vs 0.015127131953666773
20. 19Pontuação
    #13figura da resposta próximapassouregistrada0.1179439163 vs 0.118
21. 20Pontuação
    #14figura da resposta próximapassouregistrada0.01512713195 vs 0.015

Épocas × verificações

Tentativas

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

• época 1, tentativa 1passoupontuada(exibindo)

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