Tarefa paper_repro.cheng_hoekstra_2013.tab5_pb_c1.agent

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Pergunta feita ao analista

Cheng and Hoekstra (NBER Working Paper 18134, 2012; published in the Journal of Human Resources, 2013), 'Does Strengthening Self-Defense Law Deter Crime or Escalate Violence? Evidence from Expansions to Castle Doctrine', Table 5, Panel B, column (1): in the state panel for 2000-2010, estimate by unweighted ordinary least squares the effect of castle doctrine laws on the log homicide rate, with state fixed effects and year fixed effects and no other controls. As in the paper, the law is measured as the fraction of each year in which it was in effect. Report the coefficient on the castle doctrine law.

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1. 0Início

   Cheng and Hoekstra (NBER Working Paper 18134, 2012; published in the Journal of Human Resources, 2013), 'Does Strengthening Self-Defense Law Deter Crime or Escalate Violence? Evidence from Expansions to Castle Doctrine', Table 5, Panel B, column (1): in the state panel for 2000-2010, estimate by unweighted ordinary least squares the effect of castle doctrine laws on the log homicide rate, with state fixed effects and year fixed effects and no other controls. As in the paper, the law is measured as the fraction of each year in which it was in effect. Report the coefficient on the castle doctrine law.

   castle (agent)

   The state-year panel of Cheng and Hoekstra (2013), 'Does Strengthening Self-Defense Law Deter Crime or Escalate Violence? Evidence from Expansions to Castle Doctrine', as distributed with Cunningham's Causal Inference: The Mixtape: one row per U.S. state and year, 2000-2010 (550 rows: 50 states, 11 years). Columns used most: state, the state's name; sid, a numeric state id; year; cdl, the castle doctrine law variable as the paper codes it: the fraction of the year in which the state's castle doctrine (stand-your-ground) law was in effect, 0 before adoption and 1 in full years after it; post, 1 in every year from the adoption year on (any part of the year); effyear and treatment_date, the year the law took effect (missing for states that never adopted one); homicide, the homicide rate per 100,000 residents (FBI Uniform Crime Reports), and l_homicide its natural log; murder and l_murder, the murder rate and its log; population; popwt, the state's average population over 2000-2010 (constant within a state), the weight the paper's weighted regressions use; northeast, midwest, south, west, census region indicators; r20001 to r20104, region-by-year indicators named r20<two-digit year><region 1-4> (for example r20063 is region 3 in 2006); trend_1 to trend_51, state-specific linear trends; lead1 to lead9 and lag0 to lag5, event-time indicators relative to adoption; other crime rates (robbery, assault, burglary, larceny, motor) and their logs (l_robbery and so on); and the time-varying controls of the paper (police, unemployrt, income, poverty, prisoner, lagprisoner, exp_subsidy, exp_pubwelfare, and the shares of black and white men aged 15-24 and 25-44).

   file 804633c161827b6c0824f86f239046386d1a8266a866f83bf5ddb2aa762a5f29 · frame —
2. 1Turno do modelo
   call_690e1d33referenceFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache

   Texto visível

   Table 5, Panel B, column (1): the Panel A column (1) regression without population weights, errors clustered by state.

   Chamadas pedidas

   • infer.ols

     {
       "cluster": "sid",
       "controls": [],
       "dataset": "castle",
       "fe": [
         "sid",
         "year"
       ],
       "weights": null,
       "x": [
         "cdl"
       ],
       "y": "l_homicide"
     }

   Mensagens (formato neutro)Instruções do sistemaFerramentas oferecidas
3. 2Ferramenta
   infer.olsv0.1.0call_f2136d83decidido pelo modeloreexecutável

   Motivo: Table 5, Panel B, column (1): the Panel A column (1) regression without population weights, errors clustered by state.

   Argumentos

   {
     "cluster": "sid",
     "controls": [],
     "dataset": "castle",
     "fe": [
       "sid",
       "year"
     ],
     "intercept": true,
     "level": 0.95,
     "se": "HC1",
     "subset": null,
     "weights": null,
     "x": [
       "cdl"
     ],
     "y": "l_homicide"
   }

   Figuras call_f2136d83

   Chave	Valor	Valor bruto	Erro-padrão	IC
   coef.cdl Coefficient on cdl in the regression of l_homicide	0,0877014	0.08770138490539615	0,06689910.06689912458805584	-0,0467374 – 0,22214

   Diagnósticos

   • n_obs = 550550
   • k = 6161
   • r2 = 0,9105470.9105468478338682
   • df_resid = 489489
   • se_type = "cluster"
   • n_clusters = 5050
   • fixed_effects = "sid (50 levels), year (11 levels)"

   Tabelas (1)

   {
     "coefficients": [
       {
         "ci_high": 2.035267779456797,
         "ci_low": 1.8549305947048351,
         "coef": 1.945099187080816,
         "p": 9.62431952152882e-41,
         "se": 0.04486947824097916,
         "t": 43.350162813000196,
         "term": "Intercept"
       },
       {
         "ci_high": 0.222140209063177,
         "ci_low": -0.0467374392523847,
         "coef": 0.08770138490539615,
         "p": 0.1959855599903869,
         "se": 0.06689912458805584,
         "t": 1.3109496640716034,
         "term": "cdl"
       }
     ]
   }

   Digests dos dados

   castle 6a9af2b4a14b985d82e0f3aea93c535c24cfc2497c4d9f07242bac5f84ae11c1

   sha256 do resultado

   c170f7d3b43c525a115590d2303905a9cc75249d3f5f035c5a7b351a4cefdad9

   Resultado mostrado ao modelo
4. 3Turno do modelo
   call_0843cec0referenceFim: 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.cdl = 0,08770.",
       "caveats": [],
       "figure_refs": [
         "call_f2136d83:coef.cdl"
       ]
     }

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

   Números encontrados

   0,08770

   Sem lastro

   —

   Não citados

   —

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

   Estimativa (infer.ols): coef.cdl = 0,08770.

   Figuras citadas: call_f2136d83:coef.cdl · Parada: answered

   Figura da resposta: call_f2136d83:coef.cdl = 0,08770140.08770138490539615 (se 0,06689910.06689912458805584)
7. 6Pontuação
   #0resposta com lastropassouobrigatóriaevery number backed
8. 7Pontuação
   #1figura da resposta escolhidapassouobrigatóriaanswer figure call_f2136d83:coef.cdl (infer.ols)
9. 8Pontuação
   #2ferramenta chamadapassouobrigatóriaanswer call is infer.ols
10. 9Pontuação
    #3argumento igualpassouobrigatóriainfer.ols.y = 'l_homicide'
11. 10Pontuação
    #4argumento igualpassouobrigatóriainfer.ols.x = ['cdl']
12. 11Pontuação
    #5argumento igualpassouobrigatóriainfer.ols.weights = None
13. 12Pontuação
    #6diagnósticopassouobrigatória550 vs 550
14. 13Pontuação
    #7figura da resposta próximapassouobrigatória0.08770138491 vs 0.08770138490539588
15. 14Pontuação
    #8figura da resposta próximapassouregistrada0.06689912459 vs 0.06689912458805553
16. 15Pontuação
    #9figura da resposta próximapassouregistrada0.08770138491 vs 0.0877
17. 16Pontuação
    #10figura da resposta próximafalhouregistrada0.06689912459 vs 0.0638

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• época 1, tentativa 1passoupontuada(exibindo)

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