Tarefa paper_repro.ccft_2017.senate_h16794.agent

Veredito

Pergunta feita ao analista

Calonico, Cattaneo, Farrell and Titiunik (2017), 'rdrobust: Software for Regression-discontinuity Designs', the U.S. Senate example (data of Cattaneo, Frandsen and Titiunik 2015): estimate the incumbency advantage as a sharp regression discontinuity, the jump at a Democratic lead of zero in the Democratic party's share of the votes in the next election for the same seat, where the running variable is the Democratic lead over the strongest opponent in the current election, in percentage points. Use a local linear regression on each side of zero with kernel weights that fall linearly from one at zero to nothing at the bandwidth, and the bandwidth h = 16.79369 percentage points that Calonico, Cattaneo and Titiunik (2014) selected for this example (use it as given; do not recompute it). Report the conventional point estimate of the jump.

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
   senate— U.S. Senate elections, 1914-2010, the extract of the data of Cattaneo, Frandsen and Titiunik (2015) that ships with the rdrobust package as its illustration: one row per state and Senate election (1,390 rows). Columns: state, state code; year, year of the election; margin, the Democratic party's margin of victory in that election, in percentage points (negative when the Democratic candidate lost); vote, the Democratic party's vote share, in percent, in the next election for the same Senate seat (missing for some rows); class, the seat's Senate class (1, 2 or 3); termshouse and termssenate, terms the Democratic candidate had served in the House and in the Senate; population, the state's population.
2. 2Chamada que gerou a resposta finalinfer.rdd(Regressão descontínua (RDD))citada na respostacoincide com a referência

   Ver chamada call_eb385e88 nos detalhes

   rdrobust's Senate example at the bandwidth h = 16.79369 that Calonico, Cattaneo and Titiunik (2014) selected: local linear, triangular kernel, cutoff 0; the conventional point estimate (rdrobust's own errors are nearest-neighbour based; the tool's are HC1).

   Por que este é o caminho de referência: rdrobust's Senate example at the bandwidth h = 16.79369 that Calonico, Cattaneo and Titiunik (2014) selected: local linear, triangular kernel, cutoff 0; the conventional point estimate (rdrobust's own errors are nearest-neighbour based; the tool's are HC1).
   Argumentos principais

   bandwidth:

   16,793716.79369

   cutoff:

   00

   dataset:

   "senate"

   kernel:

   "triangular"

   level:

   0,950.95

   polynomial:

   11

   running:

   "margin"

   y:

   "vote"

   Resultado calculado

   • effect = 7,4253 7.425304341122355
     Jump in vote at the cutoff of margin
   Diagnósticos: bandwidth = 16,793716.79369 (half-width of the window around the cutoff (informada)) · bandwidth_method = "user" · n_left = 343343 (observations with positive weight below the cutoff) · n_right = 310310 (observations with positive weight at or above the cutoff) · kernel = "triangular" · polynomial = 11 · bandwidth_sensitive = false (the estimates at half and double the bandwidth fall inside the main interval) · n_obs = 1.2971297 (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: 7,425
   Figuras citadas: call_eb385e88: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: the Democratic vote share in the next election for the seat
   • ✓
     #4argumento igualrunning

     running variable: the Democratic margin of victory
   • ✓
     #5argumento igualcutoff

     a margin of zero
   • ✓
     #6argumento igualbandwidth

     the bandwidth the example fixes
   • ✓
     #7argumento igualkernel

     rdrobust's default kernel
   • ✓
     #8argumento igualpolynomial

     local linear (p = 1)
   • ✓
     #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: recorded, not required (the question does not state 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

   Calonico, Cattaneo, Farrell and Titiunik (2017), 'rdrobust: Software for Regression-discontinuity Designs', the U.S. Senate example (data of Cattaneo, Frandsen and Titiunik 2015): estimate the incumbency advantage as a sharp regression discontinuity, the jump at a Democratic lead of zero in the Democratic party's share of the votes in the next election for the same seat, where the running variable is the Democratic lead over the strongest opponent in the current election, in percentage points. Use a local linear regression on each side of zero with kernel weights that fall linearly from one at zero to nothing at the bandwidth, and the bandwidth h = 16.79369 percentage points that Calonico, Cattaneo and Titiunik (2014) selected for this example (use it as given; do not recompute it). Report the conventional point estimate of the jump.

   senate (agent)

   U.S. Senate elections, 1914-2010, the extract of the data of Cattaneo, Frandsen and Titiunik (2015) that ships with the rdrobust package as its illustration: one row per state and Senate election (1,390 rows). Columns: state, state code; year, year of the election; margin, the Democratic party's margin of victory in that election, in percentage points (negative when the Democratic candidate lost); vote, the Democratic party's vote share, in percent, in the next election for the same Senate seat (missing for some rows); class, the seat's Senate class (1, 2 or 3); termshouse and termssenate, terms the Democratic candidate had served in the House and in the Senate; population, the state's population.

   file def1fc6b8ae5af273f2140aa449c81b3ecfe1d0f325aa80ceccb0d9638a2ad44 · frame —
2. 1Turno do modelo
   call_59cb1d91referenceFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache

   Texto visível

   rdrobust's Senate example at the bandwidth h = 16.79369 that Calonico, Cattaneo and Titiunik (2014) selected: local linear, triangular kernel, cutoff 0; the conventional point estimate (rdrobust's own errors are nearest-neighbour based; the tool's are HC1).

   Chamadas pedidas

   • infer.rdd

     {
       "bandwidth": 16.79369,
       "cutoff": 0,
       "dataset": "senate",
       "kernel": "triangular",
       "polynomial": 1,
       "running": "margin",
       "y": "vote"
     }

   Mensagens (formato neutro)Instruções do sistemaFerramentas oferecidas
3. 2Ferramenta
   infer.rdd— Regressão descontínua (RDD)v0.1.0call_eb385e88decidido pelo modeloreexecutável

   Motivo: rdrobust's Senate example at the bandwidth h = 16.79369 that Calonico, Cattaneo and Titiunik (2014) selected: local linear, triangular kernel, cutoff 0; the conventional point estimate (rdrobust's own errors are nearest-neighbour based; the tool's are HC1).

   Argumentos

   {
     "bandwidth": 16.79369,
     "cluster": null,
     "cutoff": 0,
     "dataset": "senate",
     "kernel": "triangular",
     "level": 0.95,
     "polynomial": 1,
     "running": "margin",
     "subset": null,
     "y": "vote"
   }

   Figuras call_eb385e88

   Chave	Valor	Valor bruto	Erro-padrão	IC
   effect Jump in vote at the cutoff of margin	7,4253	7.425304341122355	1,49791.497901791714546	4,48947 – 10,3611

   Diagnósticos

   • bandwidth = 16,793716.79369 (half-width of the window around the cutoff (informada))
   • bandwidth_method = "user"
   • n_left = 343343 (observations with positive weight below the cutoff)
   • n_right = 310310 (observations with positive weight at or above the cutoff)
   • kernel = "triangular"
   • polynomial = 11
   • bandwidth_sensitive = false (the estimates at half and double the bandwidth fall inside the main interval)
   • n_obs = 1.2971297 (rows used to choose the bandwidth)
   • se_type = "HC1" (heteroskedasticity-robust standard errors (HC1))

   Derivação matemática e pressupostos

   effect

   1. Ajuste linear ponderado (kernel triangular) de cada lado do limiar, com janela h (informada); o efeito é a diferença entre os dois ajustes no limiar.→ 7,4253 (7.425304341122355)
   2. Erro-padrão robusto à heterocedasticidade (HC1): a raiz da variância estimada do coeficiente.ep = √V_jj→ 1,4979 (1.497901791714546)
   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": 8.396845,
         "ci_high": 12.665187371055993,
         "ci_low": 4.845539163400076,
         "estimate": 8.755363267228034,
         "multiplier": 0.5,
         "n_left": 217,
         "n_right": 175,
         "se": 1.9948448719814
       },
       {
         "bandwidth": 16.79369,
         "ci_high": 10.361137905260883,
         "ci_low": 4.489470776983827,
         "estimate": 7.425304341122355,
         "multiplier": 1,
         "n_left": 343,
         "n_right": 310,
         "se": 1.497901791714546
       },
       {
         "bandwidth": 33.58738,
         "ci_high": 9.455366988625087,
         "ci_low": 5.051427501358595,
         "estimate": 7.253397244991841,
         "multiplier": 2,
         "n_left": 499,
         "n_right": 488,
         "se": 1.1234745949426124
       }
     ]
   }

   • 93 rows were dropped because one of 'vote', 'margin' was missing

   Hashes SHA-256 e metadados de reprodução

   Digests dos dados

   senate e1181ed0f741b1485e582b1110d74d93e57241b2b9bfa1ed59f2cd80ab0b165e

   sha256 do resultado

   314298f0ca13c04932bd228b4d321bc2a2a90712721d31d5bd2c84f7ba5031fb

   Resultado mostrado ao modelo
4. 3Turno do modelo
   call_42ad367ereferenceFim: 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 = 7,425.",
       "caveats": [],
       "figure_refs": [
         "call_eb385e88:effect"
       ]
     }

   Mensagens (formato neutro)Instruções do sistemaFerramentas oferecidas
5. 4Guarda
   resposta aceita

   Números encontrados

   7,425

   Sem lastro

   —

   Não citados

   —

   1 nova(s) tentativa(s) restante(s)
6. 5Resposta

   Estimativa (infer.rdd): effect = 7,425.

   Figuras citadas: call_eb385e88:effect · Parada: answered

   Figura da resposta: call_eb385e88:effect = 7,42537.425304341122355 (se 1,49791.497901791714546)
7. 6Pontuação
   #0resposta com lastropassouobrigatóriaevery number backed
8. 7Pontuação
   #1figura da resposta escolhidapassouobrigatóriaanswer figure call_eb385e88:effect (infer.rdd)
9. 8Pontuação
   #2ferramenta chamadapassouobrigatóriaanswer call is infer.rdd
10. 9Pontuação
    #3argumento igualpassouobrigatóriainfer.rdd.y = 'vote'
11. 10Pontuação
    #4argumento igualpassouobrigatóriainfer.rdd.running = 'margin'
12. 11Pontuação
    #5argumento igualpassouobrigatóriainfer.rdd.cutoff = 0.0
13. 12Pontuação
    #6argumento igualpassouobrigatóriainfer.rdd.bandwidth = 16.79369
14. 13Pontuação
    #7argumento igualpassouobrigatóriainfer.rdd.kernel = 'triangular'
15. 14Pontuação
    #8argumento igualpassouobrigatóriainfer.rdd.polynomial = 1
16. 15Pontuação
    #9diagnósticopassouobrigatória343 vs 343
17. 16Pontuação
    #10diagnósticopassouobrigatória310 vs 310
18. 17Pontuação
    #11figura da resposta próximapassouobrigatória7.425304341 vs 7.425304341122386
19. 18Pontuação
    #12figura da resposta próximapassouregistrada1.497901792 vs 1.497901791714553
20. 19Pontuação
    #13figura da resposta próximapassouregistrada7.425304341 vs 7.4253
21. 20Pontuação
    #14figura da resposta próximafalhouregistrada1.497901792 vs 1.4954

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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