Tarefa paper_repro.lmb_2004.tab1_c3.agent

Veredito

Pergunta feita ao analista

Lee, Moretti and Butler (2004), 'Do Voters Affect or Elect Policies? Evidence from the U.S. House', Table I, column (3): in the paper's close-elections sample, the House elections at time t in which the Democratic candidate's share of the two-party vote was strictly between 48 and 52 percent, estimate the difference in the probability that the Democratic candidate wins the seat's next election (t+1) between districts where the Democratic candidate's share at t was strictly between 50 and 52 percent and districts where it was strictly between 48 and 50 percent. Estimate it as the coefficient of a regression of an indicator of a Democratic win at t+1 on an indicator of a Democratic win at t, with no other regressors. Report that difference.

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Trajetória

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1. 0Início

   Lee, Moretti and Butler (2004), 'Do Voters Affect or Elect Policies? Evidence from the U.S. House', Table I, column (3): in the paper's close-elections sample, the House elections at time t in which the Democratic candidate's share of the two-party vote was strictly between 48 and 52 percent, estimate the difference in the probability that the Democratic candidate wins the seat's next election (t+1) between districts where the Democratic candidate's share at t was strictly between 50 and 52 percent and districts where it was strictly between 48 and 50 percent. Estimate it as the coefficient of a regression of an indicator of a Democratic win at t+1 on an indicator of a Democratic win at t, with no other regressors. Report that difference.

   lmb (agent)

   U.S. House elections and roll-call voting, the extract of the data of Lee, Moretti and Butler (2004), 'Do Voters Affect or Elect Policies? Evidence from the U.S. House', distributed with the causaldata R package: one row per district and congressional session (13,588 rows). Each row pairs a district's election with the one before it for the same seat. Columns: rownames, the row number; state, ICPSR state code; district, district code; id, an election identifier; score, the adjusted ADA voting score of the district's representative in the session that follows the row's election (0 to 100, higher means a more liberal roll-call record); year, year of the election; demvoteshare, the Democratic candidate's share of the two-party vote in the row's election; democrat, 1 if the Democratic candidate won the row's election; lagdemvoteshare, the Democratic share of the two-party vote in the previous election for the same seat; lagdemocrat, 1 if the Democratic candidate won that previous election. In the paper's notation the previous election is time t and the row's election, and the session after it, are time t+1.

   file 58cf9d8ef80b2871a96c00844fae975051a5aac443dff3d317fe92ffd6a516b7 · frame —
2. 1Turno do modelo
   call_4c1d3383referenceFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache

   Texto visível

   Table I, column (3): the difference in the probability of a Democratic win at t+1 between districts the Democrat won and lost at t, among elections with the Democratic share at t strictly between 48 and 52 percent (915 observations), as the coefficient of a regression on the win indicator; heteroskedasticity-robust errors.

   Chamadas pedidas

   • infer.ols

     {
       "controls": [],
       "dataset": "lmb",
       "fe": [],
       "se": "HC1",
       "subset": "lagdemvoteshare > 0.48 and lagdemvoteshare < 0.52",
       "x": [
         "lagdemocrat"
       ],
       "y": "democrat"
     }

   Mensagens (formato neutro)Instruções do sistemaFerramentas oferecidas
3. 2Ferramenta
   infer.olsv0.1.0call_1d90f670decidido pelo modeloreexecutável

   Motivo: Table I, column (3): the difference in the probability of a Democratic win at t+1 between districts the Democrat won and lost at t, among elections with the Democratic share at t strictly between 48 and 52 percent (915 observations), as the coefficient of a regression on the win indicator; heteroskedasticity-robust errors.

   Argumentos

   {
     "cluster": null,
     "controls": [],
     "dataset": "lmb",
     "fe": [],
     "intercept": true,
     "level": 0.95,
     "se": "HC1",
     "subset": "lagdemvoteshare > 0.48 and lagdemvoteshare < 0.52",
     "weights": null,
     "x": [
       "lagdemocrat"
     ],
     "y": "democrat"
   }

   Figuras call_1d90f670

   Chave	Valor	Valor bruto	Erro-padrão	IC
   coef.lagdemocrat Coefficient on lagdemocrat in the regression of democrat	0,484329	0.48432871476349737	0,02893220.02893215206729027	0,427547 – 0,54111

   Diagnósticos

   • n_obs = 915915
   • k = 22
   • r2 = 0,2347720.2347717230713633
   • df_resid = 913913
   • se_type = "HC1"
   • n_clusters = —

   Tabelas (1)

   {
     "coefficients": [
       {
         "ci_high": 0.2811938149509847,
         "ci_low": 0.2023226685654988,
         "coef": 0.24175824175824176,
         "p": 4.715920282942519e-31,
         "se": 0.02009388689657253,
         "t": 12.031432395465465,
         "term": "Intercept"
       },
       {
         "ci_high": 0.5411099640233312,
         "ci_low": 0.42754746550366346,
         "coef": 0.48432871476349737,
         "p": 4.618711084163874e-55,
         "se": 0.02893215206729027,
         "t": 16.740155161532673,
         "term": "lagdemocrat"
       }
     ]
   }

   Digests dos dados

   lmb 6f2fbc93d91c4156cab244ba7581cc8eae45210626f97f85ac8b2d366e4cbc20

   sha256 do resultado

   76ed0f6ef69f3b30cdf11d85c7bf8f52f40de0e8e80b3853a9eefed10bbaafcb

   Resultado mostrado ao modelo
4. 3Turno do modelo
   call_f482756ereferenceFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache

   Chamadas pedidas

   • submit_answer (meta-ferramenta)

     {
       "answer": "Estimativa (infer.ols): coef.lagdemocrat = 0,4843.",
       "caveats": [],
       "figure_refs": [
         "call_1d90f670:coef.lagdemocrat"
       ]
     }

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

   Números encontrados

   0,4843

   Sem lastro

   —

   Não citados

   —

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

   Estimativa (infer.ols): coef.lagdemocrat = 0,4843.

   Figuras citadas: call_1d90f670:coef.lagdemocrat · Parada: answered

   Figura da resposta: call_1d90f670:coef.lagdemocrat = 0,4843290.48432871476349737 (se 0,02893220.02893215206729027)
7. 6Pontuação
   #0resposta com lastropassouobrigatóriaevery number backed
8. 7Pontuação
   #1figura da resposta escolhidapassouobrigatóriaanswer figure call_1d90f670:coef.lagdemocrat (infer.ols)
9. 8Pontuação
   #2ferramenta chamadapassouobrigatóriaanswer call is infer.ols
10. 9Pontuação
    #3argumento igualpassouobrigatóriainfer.ols.y = 'democrat'
11. 10Pontuação
    #4argumento igualpassouobrigatóriainfer.ols.x = ['lagdemocrat']
12. 11Pontuação
    #5argumento igualpassouobrigatóriainfer.ols.controls = []
13. 12Pontuação
    #6argumento igualpassouobrigatóriainfer.ols.fe = []
14. 13Pontuação
    #7diagnósticopassouobrigatória915 vs 915
15. 14Pontuação
    #8figura da resposta próximapassouobrigatória0.4843287148 vs 0.4843287147634966
16. 15Pontuação
    #9figura da resposta próximapassouregistrada0.02893215207 vs 0.02893215206729024
17. 16Pontuação
    #10figura da resposta próximapassouregistrada0.4843287148 vs 0.48
18. 17Pontuação
    #11figura da resposta próximafalhouregistrada0.02893215207 vs 0.02

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Tentativas

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• época 1, tentativa 1passoupontuada(exibindo)

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