Tarefa paper_repro.card_krueger_1994.tab3_r3_ciii.agent

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Pergunta feita ao analista

Card and Krueger (1994), 'Minimum Wages and Employment: A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania', Table 3, row 3, column (iii): New Jersey raised its minimum wage from $4.25 to $5.05 per hour on April 1, 1992, while Pennsylvania's did not change. Using all available observations in each survey wave (February-March 1992, before the rise, and November-December 1992, after it), estimate the difference in differences of mean full-time-equivalent employment per restaurant: the change in the New Jersey mean minus the change in the Pennsylvania mean, where full-time-equivalent employment counts full-time employees and managers in full and each part-time worker as half a full-time worker. Report the difference in differences.

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
   njmin_long— The survey of fast-food restaurants (Burger King, KFC, Roy Rogers, Wendy's) in New Jersey and eastern Pennsylvania used by Card and Krueger (1994), 'Minimum Wages and Employment': New Jersey's minimum wage rose from $4.25 to $5.05 per hour on April 1, 1992; Pennsylvania's did not change. Each restaurant was interviewed in February-March 1992 (wave 1, before the rise) and again in November-December 1992 (wave 2, after it). One row per restaurant and wave (410 restaurants, two rows each); the employment of a wave is missing when the restaurant gave no employment data in that wave. Columns: store, a unique restaurant id (the sheet number, plus 1000 for New Jersey restaurants, because one sheet number is used by one restaurant in each state); sheet, the survey's sheet number; wave, 1 or 2; wave2, 1 for the second wave (after the rise) and 0 for the first; nj, 1 for a restaurant in New Jersey and 0 for one in Pennsylvania; fte, full-time-equivalent employment in that wave (full-time employees plus managers and assistant managers plus half the part-time employees, the authors' definition; restaurants closed for good in wave 2 report zero employees); chain, 1 Burger King, 2 KFC, 3 Roy Rogers, 4 Wendy's; co_owned, 1 if company-owned; southj, centralj, northj, 1 for southern, central and northern New Jersey; pa1, pa2, 1 for the northeast suburbs of Philadelphia and for Easton and nearby areas; shore, 1 on the New Jersey shore; wage_st, starting wage in wave 1 ($ per hour); status2, status of the second interview (0 refused, 1 answered, 2 closed for renovations, 3 closed permanently, 4 closed for highway construction, 5 closed by a mall fire).
   Transformação "derive" aplicada à base "njmin_long" (410 → 410 linhas). {"args":{"column":"emppt","factor":0.5},"name":"pt_half1","op":"scale"}
   Transformação "derive" aplicada à base "njmin_long" (410 → 410 linhas). {"args":{"columns":["empft","nmgrs","pt_half1"]},"name":"fte1","op":"sum"}
   Transformação "derive" aplicada à base "njmin_long" (410 → 410 linhas). {"args":{"column":"emppt2","factor":0.5},"name":"pt_half2","op":"scale"}
   Transformação "derive" aplicada à base "njmin_long" (410 → 410 linhas). {"args":{"columns":["empft2","nmgrs2","pt_half2"]},"name":"fte2","op":"sum"}
   Transformação "derive" aplicada à base "njmin_long" (410 → 410 linhas). {"args":{"column":"state","factor":1000},"name":"state_k","op":"scale"}
   Transformação "derive" aplicada à base "njmin_long" (410 → 410 linhas). {"args":{"columns":["sheet","state_k"]},"name":"store","op":"sum"}
   Transformação "rename" aplicada à base "njmin_long" (410 → 410 linhas). {"map":{"state":"nj"}}
   Transformação "select" aplicada à base "njmin_long" (410 → 410 linhas). {"columns":["store","sheet","chain","co_owned","nj","southj","centralj","northj","pa1","pa2","shore","wage_st","status2","fte1","fte2"]}
   Transformação "reshape_long" aplicada à base "njmin_long" (410 → 820 linhas). {"id":["store"],"j":"wave","stubs":["fte"]}
   Transformação "derive" aplicada à base "njmin_long" (820 → 820 linhas). {"args":{"cmp":"eq","column":"wave","value":2},"name":"wave2","op":"indicator"}
2. 2Chamada que gerou a resposta finalinfer.did_2x2(Diferenças em diferenças (2 grupos × 2 períodos))citada na respostacoincide com a referência

   Ver chamada call_ffa7e5d1 nos detalhes

   Table 3, row 3, column (iii): the New Jersey minus Pennsylvania change in mean FTE employment over all available observations of each wave (the difference of the four group means; check.sas: EMPTOT = EMPPT*.5 + EMPFT + NMGRS), errors clustered by restaurant.

   Por que este é o caminho de referência: Table 3, row 3, column (iii): the New Jersey minus Pennsylvania change in mean FTE employment over all available observations of each wave (the difference of the four group means; check.sas: EMPTOT = EMPPT*.5 + EMPFT + NMGRS), errors clustered by restaurant.
   Argumentos principais

   cluster:

   "store"

   dataset:

   "njmin_long"

   level:

   0,950.95

   post:

   "wave2"

   treated:

   "nj"

   y:

   "fte"

   Resultado calculado

   • did = 2,75361 2.7536057829805816
     Difference-in-differences effect on fte
   Diagnósticos: design = "stacked" (stacked rows: treated × post interaction) · n_obs = 794794 · se_type = "cluster" (cluster-robust standard errors (CR1) by 'store') · parallel_trends = "untestable" (with two periods parallel trends cannot be tested; the estimate rests on assuming them) · n_clusters = 410410 (410 clusters of 'store')
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: 2,754
   Figuras citadas: call_ffa7e5d1:did
   • ✓
     #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.did_2x2

     Exige que o resultado venha da ferramenta infer.did_2x2.
   • ✓
     #3argumento igualy

     outcome: full-time-equivalent employment
   • ✓
     #4argumento igualtreated

     the treated group: New Jersey restaurants
   • ✓
     #5argumento igualpost

     after the rise: the second wave
   • ✓
     #6diagnósticon_obs

     Confere o diagnóstico "n_obs" reportado pela ferramenta.
   • ✓
     #7figura da resposta próxima

     software reference
   • ✓
     #8figura da resposta próxima

     software reference, SE: recorded, not required (the question does not state the convention)
   • ✗
     #9figura da resposta próxima

     published cell: recorded, never required on T2/T3
   • ✗
     #10figura 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

   Card and Krueger (1994), 'Minimum Wages and Employment: A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania', Table 3, row 3, column (iii): New Jersey raised its minimum wage from $4.25 to $5.05 per hour on April 1, 1992, while Pennsylvania's did not change. Using all available observations in each survey wave (February-March 1992, before the rise, and November-December 1992, after it), estimate the difference in differences of mean full-time-equivalent employment per restaurant: the change in the New Jersey mean minus the change in the Pennsylvania mean, where full-time-equivalent employment counts full-time employees and managers in full and each part-time worker as half a full-time worker. Report the difference in differences.

   njmin_long (agent)

   The survey of fast-food restaurants (Burger King, KFC, Roy Rogers, Wendy's) in New Jersey and eastern Pennsylvania used by Card and Krueger (1994), 'Minimum Wages and Employment': New Jersey's minimum wage rose from $4.25 to $5.05 per hour on April 1, 1992; Pennsylvania's did not change. Each restaurant was interviewed in February-March 1992 (wave 1, before the rise) and again in November-December 1992 (wave 2, after it). One row per restaurant and wave (410 restaurants, two rows each); the employment of a wave is missing when the restaurant gave no employment data in that wave. Columns: store, a unique restaurant id (the sheet number, plus 1000 for New Jersey restaurants, because one sheet number is used by one restaurant in each state); sheet, the survey's sheet number; wave, 1 or 2; wave2, 1 for the second wave (after the rise) and 0 for the first; nj, 1 for a restaurant in New Jersey and 0 for one in Pennsylvania; fte, full-time-equivalent employment in that wave (full-time employees plus managers and assistant managers plus half the part-time employees, the authors' definition; restaurants closed for good in wave 2 report zero employees); chain, 1 Burger King, 2 KFC, 3 Roy Rogers, 4 Wendy's; co_owned, 1 if company-owned; southj, centralj, northj, 1 for southern, central and northern New Jersey; pa1, pa2, 1 for the northeast suburbs of Philadelphia and for Easton and nearby areas; shore, 1 on the New Jersey shore; wage_st, starting wage in wave 1 ($ per hour); status2, status of the second interview (0 refused, 1 answered, 2 closed for renovations, 3 closed permanently, 4 closed for highway construction, 5 closed by a mall fire).

   file 41a29aec6b489658b20030d044a2b20a5f5a04b871cde41df057afd6013ba587 · frame —

   1. derive {"args":{"column":"emppt","factor":0.5},"name":"pt_half1","op":"scale"}
   2. derive {"args":{"columns":["empft","nmgrs","pt_half1"]},"name":"fte1","op":"sum"}
   3. derive {"args":{"column":"emppt2","factor":0.5},"name":"pt_half2","op":"scale"}
   4. derive {"args":{"columns":["empft2","nmgrs2","pt_half2"]},"name":"fte2","op":"sum"}
   5. derive {"args":{"column":"state","factor":1000},"name":"state_k","op":"scale"}
   6. derive {"args":{"columns":["sheet","state_k"]},"name":"store","op":"sum"}
   7. rename {"map":{"state":"nj"}}
   8. select {"columns":["store","sheet","chain","co_owned","nj","southj","centralj","northj","pa1","pa2","shore","wage_st","status2","fte1","fte2"]}
   9. reshape_long {"id":["store"],"j":"wave","stubs":["fte"]}
   10. derive {"args":{"cmp":"eq","column":"wave","value":2},"name":"wave2","op":"indicator"}
2. 1Transformação
   njmin_long · derive {"args":{"column":"emppt","factor":0.5},"name":"pt_half1","op":"scale"}

   410 → 410 linhas

   Frame antes → depois: 23992890fd66 → 8509ad26d6da
3. 2Transformação
   njmin_long · derive {"args":{"columns":["empft","nmgrs","pt_half1"]},"name":"fte1","op":"sum"}

   410 → 410 linhas

   Frame antes → depois: 8509ad26d6da → a007c15bc5d2
4. 3Transformação
   njmin_long · derive {"args":{"column":"emppt2","factor":0.5},"name":"pt_half2","op":"scale"}

   410 → 410 linhas

   Frame antes → depois: a007c15bc5d2 → d9ae72d01975
5. 4Transformação
   njmin_long · derive {"args":{"columns":["empft2","nmgrs2","pt_half2"]},"name":"fte2","op":"sum"}

   410 → 410 linhas

   Frame antes → depois: d9ae72d01975 → 6328c90ff4e6
6. 5Transformação
   njmin_long · derive {"args":{"column":"state","factor":1000},"name":"state_k","op":"scale"}

   410 → 410 linhas

   Frame antes → depois: 6328c90ff4e6 → d497fb988f6b
7. 6Transformação
   njmin_long · derive {"args":{"columns":["sheet","state_k"]},"name":"store","op":"sum"}

   410 → 410 linhas

   Frame antes → depois: d497fb988f6b → b4da454f129f
8. 7Transformação
   njmin_long · rename {"map":{"state":"nj"}}

   410 → 410 linhas

   Frame antes → depois: b4da454f129f → 1398628b36ae
9. 8Transformação
   njmin_long · select {"columns":["store","sheet","chain","co_owned","nj","southj","centralj","northj","pa1","pa2","shore","wage_st","status2","fte1","fte2"]}

   410 → 410 linhas

   Frame antes → depois: 1398628b36ae → 5da0564e9bdb
10. 9Transformação
    njmin_long · reshape_long {"id":["store"],"j":"wave","stubs":["fte"]}

    410 → 820 linhas

    Frame antes → depois: 5da0564e9bdb → e431f1f5da32
11. 10Transformação
    njmin_long · derive {"args":{"cmp":"eq","column":"wave","value":2},"name":"wave2","op":"indicator"}

    820 → 820 linhas

    Frame antes → depois: e431f1f5da32 → 1400ae8f1887
12. 11Turno do modelo
    call_0ff5a97dreferenceFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache

    Texto visível

    Table 3, row 3, column (iii): the New Jersey minus Pennsylvania change in mean FTE employment over all available observations of each wave (the difference of the four group means; check.sas: EMPTOT = EMPPT*.5 + EMPFT + NMGRS), errors clustered by restaurant.

    Chamadas pedidas

    • infer.did_2x2

      {
        "cluster": "store",
        "controls": [],
        "dataset": "njmin_long",
        "post": "wave2",
        "treated": "nj",
        "y": "fte"
      }

    Mensagens (formato neutro)Instruções do sistemaFerramentas oferecidas
13. 12Ferramenta
    infer.did_2x2— Diferenças em diferenças (2 grupos × 2 períodos)v0.1.0call_ffa7e5d1decidido pelo modeloreexecutável

    Motivo: Table 3, row 3, column (iii): the New Jersey minus Pennsylvania change in mean FTE employment over all available observations of each wave (the difference of the four group means; check.sas: EMPTOT = EMPPT*.5 + EMPFT + NMGRS), errors clustered by restaurant.

    Argumentos

    {
      "cluster": "store",
      "controls": [],
      "dataset": "njmin_long",
      "level": 0.95,
      "post": "wave2",
      "treated": "nj",
      "y": "fte"
    }

    Figuras call_ffa7e5d1

    Chave	Valor	Valor bruto	Erro-padrão	IC
    did Difference-in-differences effect on fte	2,75361	2.7536057829805816	1,306611.3066070124191203	0,185102 – 5,32211

    Diagnósticos

    • design = "stacked" (stacked rows: treated × post interaction)
    • n_obs = 794794
    • se_type = "cluster" (cluster-robust standard errors (CR1) by 'store')
    • parallel_trends = "untestable" (with two periods parallel trends cannot be tested; the estimate rests on assuming them)
    • n_clusters = 410410 (410 clusters of 'store')

    Derivação matemática e pressupostos

    did

    1. Variação da média do grupo tratado menos a variação da média do grupo de comparação.DiD = (ȳ_T1 − ȳ_T0) − (ȳ_C1 − ȳ_C0)→ 2,75361 (2.7536057829805816)
    2. Erro-padrão robusto por conglomerado (CR1): a raiz da variância estimada do coeficiente.ep = √V_jj→ 1,30661 (1.3066070124191203)
    3. Intervalo de 95% de confiança: a estimativa mais ou menos o valor crítico da distribuição t de Student com 409 graus de liberdade vezes o erro-padrão.IC = DiD ± c · ep

    Pressupostos do estimador

    • without the policy the treated group's outcome would have changed as much as the comparison group's (parallel trends)
    • no other change hit one group and not the other between the two periods

    Tabelas (1)

    {
      "means": [
        {
          "group": "treated",
          "mean": 20.439408099688475,
          "n": 321,
          "period": "before"
        },
        {
          "group": "treated",
          "mean": 21.02742946708464,
          "n": 319,
          "period": "after"
        },
        {
          "group": "comparison",
          "mean": 23.33116883116883,
          "n": 77,
          "period": "before"
        },
        {
          "group": "comparison",
          "mean": 21.165584415584416,
          "n": 77,
          "period": "after"
        }
      ]
    }

    • 26 rows were dropped because one of 'fte', 'nj', 'wave2', 'store' was missing
    • with two periods parallel trends cannot be tested

    Hashes SHA-256 e metadados de reprodução

    Digests dos dados

    njmin_long 1400ae8f1887d40b00dd9de85c9853d6ae2c0ce54e44bee458c94220f44a4803

    sha256 do resultado

    d3233bae4042236e443ab73bd96d9c6c77decc9bc53febb9b26dd73e8e5a6e61

    Resultado mostrado ao modelo
14. 13Turno do modelo
    call_8dc807e5referenceFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache

    Chamadas pedidas

    • submit_answer (meta-ferramenta)

      {
        "answer": "Estimativa (infer.did_2x2): did = 2,754.",
        "caveats": [],
        "figure_refs": [
          "call_ffa7e5d1:did"
        ]
      }

    Mensagens (formato neutro)Instruções do sistemaFerramentas oferecidas
15. 14Guarda
    resposta aceita

    Números encontrados

    2,754

    Sem lastro

    —

    Não citados

    —

    1 nova(s) tentativa(s) restante(s)
16. 15Resposta

    Estimativa (infer.did_2x2): did = 2,754.

    Figuras citadas: call_ffa7e5d1:did · Parada: answered

    Figura da resposta: call_ffa7e5d1:did = 2,753612.7536057829805816 (se 1,306611.3066070124191203)
17. 16Pontuação
    #0resposta com lastropassouobrigatóriaevery number backed
18. 17Pontuação
    #1figura da resposta escolhidapassouobrigatóriaanswer figure call_ffa7e5d1:did (infer.did_2x2)
19. 18Pontuação
    #2ferramenta chamadapassouobrigatóriaanswer call is infer.did_2x2
20. 19Pontuação
    #3argumento igualpassouobrigatóriainfer.did_2x2.y = 'fte'
21. 20Pontuação
    #4argumento igualpassouobrigatóriainfer.did_2x2.treated = 'nj'
22. 21Pontuação
    #5argumento igualpassouobrigatóriainfer.did_2x2.post = 'wave2'
23. 22Pontuação
    #6diagnósticopassouobrigatória794 vs 794
24. 23Pontuação
    #7figura da resposta próximapassouobrigatória2.753605783 vs 2.7536057829805793
25. 24Pontuação
    #8figura da resposta próximapassouregistrada1.306607012 vs 1.3066070124191145
26. 25Pontuação
    #9figura da resposta próximafalhouregistrada2.753605783 vs 2.76
27. 26Pontuação
    #10figura da resposta próximafalhouregistrada1.306607012 vs 1.36

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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