Tarefa crb_papers.q004

Veredito

Pergunta feita ao analista

How much did state policy liberalism change, by the governor's first year in office, in states that elected a Democratic governor in 2003 relative to comparable states that remained under Republican governors?

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

   How much did state policy liberalism change, by the governor's first year in office, in states that elected a Democratic governor in 2003 relative to comparable states that remained under Republican governors?

   ds_0002 (agent)

   | Variable Name | Description | | --- | --- | | year | Calendar year of the observation (1936–2014). Each row represents a state-year in the panel. | | Policy | Continuous, standardized index summarizing the ideological orientation of a state’s policy outputs in that year. The score is estimated from nearly 150 statutory and regulatory indicators spanning domains such as social welfare, taxation, labor, civil rights, women’s rights, morality laws, family planning, environment, religion, criminal justice, and drug policy. Higher values indicate a more liberal policy orientation. The scale is standardized to be comparable across states and years (centered roughly at 0 with a typical standard deviation near 1). | | sen_dem_control | Indicator (0/1) that the Democratic Party held a majority of seats in the state senate (upper chamber) in that year, based on official election returns and chamber composition. For Nebraska’s nonpartisan unicameral legislature, this variable is generally coded as missing. | | hs_dem_control | Indicator (0/1) that the Democratic Party held a majority of seats in the state house/lower chamber in that year, based on official election returns and chamber composition. For Nebraska, typically coded as missing due to nonpartisan unicameral structure. | | Policy_L1 | One-year lag of the policy index (value from t−1). Included to capture persistence and gradualism in state policy change over time. | | Policy_L2 | Two-year lag of the policy index (value from t−2). Provides an additional look-back to characterize medium-run policy momentum. | | South11 | Indicator (0/1) for membership in the traditional 11-state U.S. South: AL, AR, FL, GA, LA, MS, NC, SC, TN, TX, VA. Useful for distinguishing long-standing regional political and institutional contexts. | | gov_dem | Indicator (0/1) that the sitting governor was affiliated with the Democratic Party for the relevant portion of the calendar year, as compiled from official administrative records and election data. | | gov_dem_X_hs_dem | Product term (0/1) equal to 1 when both gov_dem = 1 and hs_dem_control = 1 in the same year; 0 otherwise. Encodes concurrent Democratic control of the governorship and the lower chamber. | | gov_dem_X_sen_dem | Product term (0/1) equal to 1 when both gov_dem = 1 and sen_dem_control = 1 in the same year; 0 otherwise. Encodes concurrent Democratic control of the governorship and the upper chamber. | | both_dem | Indicator (0/1) that Democrats controlled both legislative chambers in that year (hs_dem_control = 1 and sen_dem_control = 1). | | full_dem | Indicator (0/1) that Democrats held a “trifecta” in that year: governorship plus majorities in both legislative chambers. | | state | Numeric state identifier for the panel unit. Codes map to U.S. states included in the panel; Nebraska’s unicameral, nonpartisan legislature is handled specially for chamber-control variables. | Dataset Context: This dataset is an annual, state-year panel that tracks the ideological orientation of U.S. state policies alongside the party composition of key state institutions from the mid-1930s through the early 2010s. The central measure is a dynamic policy index that pools information from nearly 150 codings of enacted state statutes and regulatory provisions. The underlying source material includes historical statutory compilations, administrative records, and archival policy datasets, covering areas such as safety-net programs, taxation structures, labor and employment regulations, civil and voting rights, women’s rights, morality and family policy, environmental regulation, religion in public institutions, criminal justice, and drug laws. Because most policy indicators are dichotomous (present/absent) and some are continuous (e.g., benefit levels), the index is estimated using a modeling approach that accommodates mixed data types and allows comparability over time. Scores are standardized so that higher values represent more liberal policy bundles, facilitating interpretation across decades when the national policy environment shifted. Party control variables are constructed from state election returns and official chamber rosters, identifying which party held the governor’s office and whether Democrats held majorities in the state house and senate in each year. Nebraska’s unique nonpartisan unicameral legislature is typically excluded from chamber-majority coding or marked as missing for those fields. The dataset also includes composite indicators for concurrent control across branches (e.g., both chambers, or governorship plus both chambers) and simple product terms that register simultaneous control by party across institutions. Coverage spans 1936–2014, a period that includes major institutional realignments, changes in party competition, and significant waves of policy innovation at the state level. The inclusion of lagged versions of the policy index reflects the empirical regularity that state policy changes are often incremental and path dependent. A regional flag for the traditional 11-state South is provided to facilitate analyses that account for historically distinct political and legal environments in that region. Together, these features make the file a versatile panel for describing long-run patterns in state policy content and the composition of state political institutions.

   file cde09ab5c48545fe73a7e45bba4331903448516e4a49ebe1e1c8b00723f91b7e · frame —

   ref_g0 (reference)

   file cde09ab5c48545fe73a7e45bba4331903448516e4a49ebe1e1c8b00723f91b7e · frame —

   1. select {"columns":["year","state","Policy","gov_dem","Policy_L1","Policy_L2"]}
   2. derive {"args":{"cmp":"gt","column":"gov_dem","value":0.5},"name":"gov_dem","op":"indicator"}
   3. derive {"args":{"column":"gov_dem","default":0,"keep_unmapped":false,"mapping":[{"source":1,"target":1}]},"name":"gov_dem","op":"map"}
   4. dropna {"columns":["year","state","Policy","gov_dem"]}
   5. filter {"query":"year == 2002"}
   6. select {"columns":["state","gov_dem"]}
   7. rename {"map":{"gov_dem":"g0"}}

   ref_g1 (reference)

   file cde09ab5c48545fe73a7e45bba4331903448516e4a49ebe1e1c8b00723f91b7e · frame —

   1. select {"columns":["year","state","Policy","gov_dem","Policy_L1","Policy_L2"]}
   2. derive {"args":{"cmp":"gt","column":"gov_dem","value":0.5},"name":"gov_dem","op":"indicator"}
   3. derive {"args":{"column":"gov_dem","default":0,"keep_unmapped":false,"mapping":[{"source":1,"target":1}]},"name":"gov_dem","op":"map"}
   4. dropna {"columns":["year","state","Policy","gov_dem"]}
   5. filter {"query":"year == 2003"}
   6. select {"columns":["state","gov_dem"]}
   7. rename {"map":{"gov_dem":"g1"}}

   ref_panel (reference)

   file cde09ab5c48545fe73a7e45bba4331903448516e4a49ebe1e1c8b00723f91b7e · frame —

   1. select {"columns":["year","state","Policy","gov_dem","Policy_L1","Policy_L2"]}
   2. derive {"args":{"cmp":"gt","column":"gov_dem","value":0.5},"name":"gov_dem","op":"indicator"}
   3. derive {"args":{"column":"gov_dem","default":0,"keep_unmapped":false,"mapping":[{"source":1,"target":1}]},"name":"gov_dem","op":"map"}
   4. dropna {"columns":["year","state","Policy","gov_dem"]}
   5. filter {"query":"year in [2002, 2003]"}
   6. merge {"how":"inner","on":["state"],"with":"ref_g0"}
   7. merge {"how":"inner","on":["state"],"with":"ref_g1"}
   8. filter {"query":"g0 == 0 and (g1 == 1 or g1 == 0)"}
   9. derive {"args":{"cmp":"eq","column":"year","value":2003},"name":"Post","op":"indicator"}
   10. derive {"args":{"cmp":"eq","column":"g1","value":1},"name":"TreatGroup","op":"indicator"}
   11. derive {"args":{"columns":["TreatGroup","Post"]},"name":"TreatGroup_Post","op":"interaction"}
2. 1Turno do modelo
   call_05f2358enaive-olsFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache

   Texto visível

   Linha de base ingênua: regressão do resultado no tratamento, sem controles.

   Chamadas pedidas

   • infer.ols

     {
       "dataset": "ds_0002",
       "x": [
         "gov_dem"
       ],
       "y": "Policy"
     }

   Mensagens (formato neutro)Instruções do sistemaFerramentas oferecidas
3. 2Ferramenta
   infer.olsv0.1.0call_be59c957decidido pelo modeloreexecutável

   Motivo: Linha de base ingênua: regressão do resultado no tratamento, sem controles.

   Argumentos

   {
     "cluster": null,
     "controls": [],
     "dataset": "ds_0002",
     "fe": [],
     "intercept": true,
     "level": 0.95,
     "se": "HC1",
     "subset": null,
     "weights": null,
     "x": [
       "gov_dem"
     ],
     "y": "Policy"
   }

   Figuras call_be59c957

   Chave	Valor	Valor bruto	Erro-padrão	IC
   coef.gov_dem Coefficient on gov_dem in the regression of Policy	-0,154302	-0.1543024516209968	0,03100780.031007753286602834	-0,215095 – -0,0935095

   Diagnósticos

   • n_obs = 3.9043904
   • k = 22
   • r2 = 0,006280170.006280167993056307
   • df_resid = 3.9023902
   • se_type = "HC1"
   • n_clusters = —

   Tabelas (1)

   {
     "coefficients": [
       {
         "ci_high": 0.13312915747750606,
         "ci_low": 0.04341078306431639,
         "coef": 0.08826997027091123,
         "p": 0.00011623977565694068,
         "se": 0.022880661443021613,
         "t": 3.8578417188998153,
         "term": "Intercept"
       },
       {
         "ci_high": -0.09350951462468195,
         "ci_low": -0.21509538861731164,
         "coef": -0.1543024516209968,
         "p": 6.762339798583586e-7,
         "se": 0.031007753286602834,
         "t": -4.976253848345229,
         "term": "gov_dem"
       }
     ]
   }

   • 46 rows were dropped because one of 'Policy', 'gov_dem' was missing

   Digests dos dados

   ds_0002 3dd8fb457073ac61d9d41273bd6c182d894366d9601588c9a90bd54929af231f

   sha256 do resultado

   db691e699e1ade23f5e02348399d0cd32983c091f259c617c192e907991c6fec

   Resultado mostrado ao modelo
4. 3Turno do modelo
   call_6f8e5eb5naive-olsFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache

   Chamadas pedidas

   • submit_answer (meta-ferramenta)

     {
       "answer": "Estimativa ingênua (infer.ols): coef.gov_dem = -0,1543.",
       "caveats": [],
       "figure_refs": [
         "call_be59c957:coef.gov_dem"
       ]
     }

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

   Números encontrados

   -0,1543

   Sem lastro

   —

   Não citados

   —

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

   Estimativa ingênua (infer.ols): coef.gov_dem = -0,1543.

   Figuras citadas: call_be59c957:coef.gov_dem · Parada: answered

   Figura da resposta: call_be59c957:coef.gov_dem = -0,154302-0.1543024516209968 (se 0,03100780.031007753286602834)
7. 6Pontuação
   #0resposta com lastropassouobrigatóriaevery number backed
8. 7Pontuação
   #1figura da resposta próximafalhouobrigatória-0.1543024516 in [-0.03580010641, 0.118411916]?
9. 8Pontuação
   #2figura da resposta próximafalhouregistrada-0.1543024516 vs 0.04130590477377359
10. 9Pontuação
    #3figura da resposta próximafalhouregistrada0.03100775329 vs 0.039339801624083896

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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