Tarefa qrdata_socsci.381

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Pergunta feita ao analista

We would like to reduce the confounding bias due to different fast-food chains and the location of restaurants. We only consider Burger King restaurants, and focus on the Burger King restaurants located in northern and southern NJ that are near PA, while excluding those in the Jersey shore and central New Jersey. What is the difference in the proportion of full-time Burger King employees in NJ (northern and southern only) and PA? Please round to the nearest thousandth.

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Trajetória

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1. 0Início

   We would like to reduce the confounding bias due to different fast-food chains and the location of restaurants. We only consider Burger King restaurants, and focus on the Burger King restaurants located in northern and southern NJ that are near PA, while excluding those in the Jersey shore and central New Jersey. What is the difference in the proportion of full-time Burger King employees in NJ (northern and southern only) and PA? Please round to the nearest thousandth.

   minwage (agent)

   Two social science researchers examined the impact of raising the minimum wage on employment in the fast-food industry. In 1992, the state of New Jersey (NJ) in the United States raised the minimum wage from $4.25 to $5.05 per hour. Did such an increase in the minimum wage reduce employment as economic theory predicts? As discussed above, answering this question requires inference about the NJ employment rate in the absence of such a raise in the minimum wage. Since this counterfactual outcome is not observable, we must somehow estimate it using observed data. One possible strategy is to look at another state in which the minimum wage did not increase. For example, the researchers of this study chose the neighboring state, Pennsylvania (PA), on the grounds that NJ’s economy resembles that of Pennsylvania, and hence the fast-food restaurants in the two states are comparable. Under this cross-section comparison design, therefore, the fast-food restaurants in NJ serve as the treatment group receiving the treatment (i.e., the increase in the minimum wage), whereas those in PA represent the control group, which did not receive such a treatment. To collect pretreatment and outcome measures, the researchers surveyed the fast-food restaurants before and after the minimum wage increase. Specifically, they gathered information about the number of full-time employees, the number of part-time employees, and their hourly wages, for each restaurant. The CSV file minwage.csv contains this data set. Variable Description chain: name of the fast-food restaurant chain location: location of the restaurants (centralNJ, northNJ, PA, shoreNJ, southNJ) wageBefore: wage before the minimum-wage increase wageAfter: wage after the minimum-wage increase fullBefore: number of full-time employees before the minimum-wage increase fullAfter: number of full-time employees after the minimum-wage increase partBefore: number of part-time employees before the minimum-wage increase partAfter: number of part-time employees after the minimum-wage increase

   file 3c3a97cca6fdd96f6856f7856b5f8bc786a31d1a9be78c9f610ef3070783e970 · frame —

   minwage_props (reference)

   file 3c3a97cca6fdd96f6856f7856b5f8bc786a31d1a9be78c9f610ef3070783e970 · frame —

   1. derive {"args":{"columns":["fullAfter","partAfter"]},"name":"totalAfter","op":"sum"}
   2. derive {"args":{"left":"fullAfter","right":"totalAfter"},"name":"fullPropAfter","op":"ratio"}
   3. derive {"args":{"columns":["fullBefore","partBefore"]},"name":"totalBefore","op":"sum"}
   4. derive {"args":{"left":"fullBefore","right":"totalBefore"},"name":"fullPropBefore","op":"ratio"}
   5. derive {"args":{"left":"fullPropAfter","right":"fullPropBefore"},"name":"fullPropChange","op":"diff"}
   6. derive {"args":{"cmp":"ne","column":"location","value":"PA"},"name":"nj","op":"indicator"}
2. 1Transformação
   minwage_props · derive {"args":{"columns":["fullAfter","partAfter"]},"name":"totalAfter","op":"sum"}

   358 → 358 linhas

   Frame antes → depois: 55dec890a044 → 808a12f40fca
3. 2Transformação
   minwage_props · derive {"args":{"left":"fullAfter","right":"totalAfter"},"name":"fullPropAfter","op":"ratio"}

   358 → 358 linhas

   Frame antes → depois: 808a12f40fca → 891fe31e6dd3
4. 3Transformação
   minwage_props · derive {"args":{"columns":["fullBefore","partBefore"]},"name":"totalBefore","op":"sum"}

   358 → 358 linhas

   Frame antes → depois: 891fe31e6dd3 → fc02f54744c1
5. 4Transformação
   minwage_props · derive {"args":{"left":"fullBefore","right":"totalBefore"},"name":"fullPropBefore","op":"ratio"}

   358 → 358 linhas

   Frame antes → depois: fc02f54744c1 → 590bda545f53
6. 5Transformação
   minwage_props · derive {"args":{"left":"fullPropAfter","right":"fullPropBefore"},"name":"fullPropChange","op":"diff"}

   358 → 358 linhas

   Frame antes → depois: 590bda545f53 → 3ab27676376a
7. 6Transformação
   minwage_props · derive {"args":{"cmp":"ne","column":"location","value":"PA"},"name":"nj","op":"indicator"}

   358 → 358 linhas

   Frame antes → depois: 3ab27676376a → 67fcfadd313b
8. 7Turno do modelo
   call_45d51969referenceFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache

   Texto visível

   The same difference over Burger King restaurants in northern NJ, southern NJ and PA.

   Chamadas pedidas

   • infer.ols

     {
       "dataset": "minwage_props",
       "subset": "chain == 'burgerking' and location in ['northNJ', 'southNJ', 'PA']",
       "x": [
         "nj"
       ],
       "y": "fullPropAfter"
     }

   Mensagens (formato neutro)Instruções do sistemaFerramentas oferecidas
9. 8Ferramenta
   infer.olsv0.1.0call_45a3c1f1decidido pelo modeloreexecutável

   Motivo: The same difference over Burger King restaurants in northern NJ, southern NJ and PA.

   Argumentos

   {
     "cluster": null,
     "controls": [],
     "dataset": "minwage_props",
     "fe": [],
     "intercept": true,
     "level": 0.95,
     "se": "HC1",
     "subset": "chain == 'burgerking' and location in ['northNJ', 'southNJ', 'PA']",
     "weights": null,
     "x": [
       "nj"
     ],
     "y": "fullPropAfter"
   }

   Figuras call_45a3c1f1

   Chave	Valor	Valor bruto	Erro-padrão	IC
   coef.nj Coefficient on nj in the regression of fullPropAfter	0,0314985	0.03149853475090858	0,05407670.05407670844470241	-0,0755881 – 0,138585

   Diagnósticos

   • n_obs = 120120
   • k = 22
   • r2 = 0,002823980.002823975749484564
   • df_resid = 118118
   • se_type = "HC1"
   • n_clusters = —

   Tabelas (1)

   {
     "coefficients": [
       {
         "ci_high": 0.4131433610366152,
         "ci_low": 0.229452334200419,
         "coef": 0.3212978476185171,
         "p": 2.411459821685738e-10,
         "se": 0.046380245671683654,
         "t": 6.927471878715765,
         "term": "Intercept"
       },
       {
         "ci_high": 0.13858513981597825,
         "ci_low": -0.0755880703141611,
         "coef": 0.03149853475090858,
         "p": 0.5613555973312575,
         "se": 0.05407670844470241,
         "t": 0.582478772411199,
         "term": "nj"
       }
     ]
   }

   Digests dos dados

   minwage_props 67fcfadd313ba1d19f472b3dfda49f69f3c7884474526b8969637c189accc2da

   sha256 do resultado

   38c5bdd018ba0427747e9a114b52734c912e1a9e1ad6eccbeba295fa178408f2

   Resultado mostrado ao modelo
10. 9Turno do modelo
    call_565c9e4dreferenceFim: 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.nj = 0,03150. Caminho de referência inferido à mão.",
        "caveats": [],
        "figure_refs": [
          "call_45a3c1f1:coef.nj"
        ]
      }

    Mensagens (formato neutro)Instruções do sistemaFerramentas oferecidas
11. 10Guarda
    resposta aceita

    Números encontrados

    0,03150

    Sem lastro

    —

    Não citados

    —

    1 nova(s) tentativa(s) restante(s)
12. 11Resposta

    Estimativa (infer.ols): coef.nj = 0,03150. Caminho de referência inferido à mão.

    Figuras citadas: call_45a3c1f1:coef.nj · Parada: answered

    Figura da resposta: call_45a3c1f1:coef.nj = 0,03149850.03149853475090858 (se 0,05407670.05407670844470241)
13. 12Pontuação
    #0resposta com lastropassouobrigatóriaevery number backed
14. 13Pontuação
    #1figura da resposta próximafalhouobrigatória0.031 in (0.03104, 0.03296)?

Épocas × verificações

Tentativas

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

• época 1, tentativa 1falhoupontuada(exibindo)

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