Tarefa causcibench_real.q127

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Pergunta feita ao analista

What is the effect of term limits on state expenditure per capita?

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Verificações

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Trajetória

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1. 0Início

   What is the effect of term limits on state expenditure per capita?

   keele_do_term_limits (agent)

   This dataset contains state-level panel data examining fiscal policy outcomes across U.S. states during a period of significant variation in legislative term limits. The data spans multiple decades, capturing the adoption and subsequent repeal of term limits across states. The term limits movement began in 1990 with California, Colorado, and Oklahoma, followed by a major wave in 1992 when eight additional states adopted restrictions. By 2000, twenty-one states had implemented term limits on state legislators. However, several states later repealed these limits through court decisions or legislative action. Currently, fifteen states maintain active term limits while six have repealed previously enacted restrictions. Variable description: exp_real_pc: real per capita expenditure tl_onset: whether a term limit was active in that year population: population popgrowth: relative population growth with respect to the previous year populationdensity: population density grants_real_pc: federal grants per capita gsp_real_inc: real gross state product per capita fedempciv_pc: federal employment per capita fedempmil_pc: federal military employment per capita govtempsandl_pc: state and local employment per capita seats_house: number of seats in the house of representatives seats_senate: number of seats in the senate unemployment: unemployment rate gopshare: share of votes for the republican party demcontrol: whether the state is controlled by the democratic party dividedgov: whether the state has a divided government squire_score: squire score initiatives: number of initiatives tel: whether the state has implemented tax and expenditure limitations debtlimit: whether the state has a debt limit year: year fips: state code (Federal Information Processing Standards code) state: state name, may contain spelling errors

   file 57dfc507d57b56b5790e4f71220a32a302ae01cc57be41652fbd60ce19e8ba99 · frame —
2. 1Turno do modelo
   call_f6a33eaereferenceFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache

   Texto visível

   causcibench_metadata_rule/1: did

   Chamadas pedidas

   • infer.ols

     {
       "controls": [
         "population",
         "popgrowth",
         "populationdensity",
         "grants_real_pc",
         "gsp_real_inc",
         "fedempciv_pc",
         "fedempmil_pc",
         "govtempsandl_pc",
         "seats_house",
         "seats_senate",
         "unemployment",
         "gopshare",
         "demcontrol",
         "dividedgov",
         "squire_score",
         "initiatives",
         "tel",
         "debtlimit"
       ],
       "dataset": "keele_do_term_limits",
       "fe": [
         "fips",
         "year"
       ],
       "x": [
         "tl_onset"
       ],
       "y": "exp_real_pc"
     }

   Mensagens (formato neutro)Instruções do sistemaFerramentas oferecidas
3. 2Ferramenta
   infer.olsv0.1.0call_90de0dc8decidido pelo modeloreexecutável

   Motivo: causcibench_metadata_rule/1: did

   Argumentos

   {
     "cluster": null,
     "controls": [
       "population",
       "popgrowth",
       "populationdensity",
       "grants_real_pc",
       "gsp_real_inc",
       "fedempciv_pc",
       "fedempmil_pc",
       "govtempsandl_pc",
       "seats_house",
       "seats_senate",
       "unemployment",
       "gopshare",
       "demcontrol",
       "dividedgov",
       "squire_score",
       "initiatives",
       "tel",
       "debtlimit"
     ],
     "dataset": "keele_do_term_limits",
     "fe": [
       "fips",
       "year"
     ],
     "intercept": true,
     "level": 0.95,
     "se": "HC1",
     "subset": null,
     "weights": null,
     "x": [
       "tl_onset"
     ],
     "y": "exp_real_pc"
   }

   Figuras call_90de0dc8

   Chave	Valor	Valor bruto	Erro-padrão	IC
   coef.tl_onset Coefficient on tl_onset in the regression of exp_real_pc	-5,55924	-5.559238248588588	3,218723.2187239380607915	-11,8738 – 0,755363

   Diagnósticos

   • n_obs = 1.3631363
   • k = 9393
   • r2 = 0,9235780.9235775439610645
   • df_resid = 1.2701270
   • se_type = "HC1"
   • n_clusters = —
   • fixed_effects = "fips (47 levels), year (29 levels)"

   Tabelas (1)

   {
     "coefficients": [
       {
         "ci_high": -5.27262357023173,
         "ci_low": -194.0497557398846,
         "coef": -99.66118965505817,
         "p": 0.0385207911901036,
         "se": 48.1124203994311,
         "t": -2.071423321206193,
         "term": "Intercept"
       },
       {
         "ci_high": 0.7553627341559048,
         "ci_low": -11.87383923133308,
         "coef": -5.559238248588588,
         "p": 0.08438279804490278,
         "se": 3.2187239380607915,
         "t": -1.7271559647758743,
         "term": "tl_onset"
       },
       {
         "ci_high": -0.0000021507801053412907,
         "ci_low": -0.000007628881489064911,
         "coef": -0.000004889830797203101,
         "p": 0.0004772313649846642,
         "se": 0.0000013961686658506498,
         "t": -3.502320970814692,
         "term": "population"
       },
       {
         "ci_high": 0.5578816310836541,
         "ci_low": -1.7164197889673354,
         "coef": -0.5792690789418407,
         "p": 0.31780786867328076,
         "se": 0.5796366582059279,
         "t": -0.9993658453810962,
         "term": "popgrowth"
       },
       {
         "ci_high": 0.37765881379895927,
         "ci_low": 0.08835813260077852,
         "coef": 0.2330084731998689,
         "p": 0.001613847830030332,
         "se": 0.07373221446726812,
         "t": 3.160199037603952,
         "term": "populationdensity"
       },
       {
         "ci_high": 0.0000011169272230152201,
         "ci_low": 6.374398296926654e-7,
         "coef": 8.771835263539428e-7,
         "p": 1.1998084226118369e-12,
         "se": 1.2220388549514508e-7,
         "t": 7.17803302898083,
         "term": "grants_real_pc"
       },
       {
         "ci_high": 0.0523975672548958,
         "ci_low": 0.031625034616737664,
         "coef": 0.04201130093581673,
         "p": 4.575781773150611e-15,
         "se": 0.0052941625479817015,
         "t": 7.9354006521452085,
         "term": "gsp_real_inc"
       },
       {
         "ci_high": 0.01974292124078359,
         "ci_low": -0.014824739402870352,
         "coef": 0.0024590909189566206,
         "p": 0.7801953110188954,
         "se": 0.008810038599472415,
         "t": 0.27912373949234254,
         "term": "fedempciv_pc"
       },
       {
         "ci_high": 0.010095810026358815,
         "ci_low": -0.02137544553115226,
         "coef": -0.005639817752396722,
         "p": 0.4820959934220905,
         "se": 0.008020877637446787,
         "t": -0.7031422254924206,
         "term": "fedempmil_pc"
       },
       {
         "ci_high": 0.03028725753410803,
         "ci_low": 0.012307054192219485,
         "coef": 0.021297155863163757,
         "p": 0.000003709865727539808,
         "se": 0.004582499437880874,
         "t": 4.647497757907503,
         "term": "govtempsandl_pc"
       },
       {
         "ci_high": 0.6104954912358547,
         "ci_low": 0.019012741068008043,
         "coef": 0.3147541161519314,
         "p": 0.03700056835986174,
         "se": 0.15074742585618042,
         "t": 2.087956821579298,
         "term": "seats_house"
       },
       {
         "ci_high": 2.622183968612376,
         "ci_low": -1.2055128338438252,
         "coef": 0.7083355673842754,
         "p": 0.46791406418955356,
         "se": 0.9755406049702443,
         "t": 0.7260954221437875,
         "term": "seats_senate"
       },
       {
         "ci_high": 4.1132028332950625,
         "ci_low": -0.032831852464846545,
         "coef": 2.0401854904151078,
         "p": 0.05373477947914511,
         "se": 1.0566733454380284,
         "t": 1.9307627084786347,
         "term": "unemployment"
       },
       {
         "ci_high": 41.841646508966605,
         "ci_low": -73.00832286565888,
         "coef": -15.58333817834614,
         "p": 0.5945559103557495,
         "se": 29.271077200430433,
         "t": -0.5323800716878635,
         "term": "gopshare"
       },
       {
         "ci_high": 7.6569656975384826,
         "ci_low": -4.5641523920388964,
         "coef": 1.5464066527497933,
         "p": 0.6196391428441786,
         "se": 3.1147182104049462,
         "t": 0.49648364580266285,
         "term": "demcontrol"
       },
       {
         "ci_high": 11.832696644383585,
         "ci_low": 2.261922848690163,
         "coef": 7.047309746536874,
         "p": 0.003928564513405139,
         "se": 2.439241909832789,
         "t": 2.8891393338760607,
         "term": "dividedgov"
       },
       {
         "ci_high": 88.49859916125413,
         "ci_low": 1.4770686627976275,
         "coef": 44.98783391202588,
         "p": 0.04272447145708398,
         "se": 22.17862095383983,
         "t": 2.028432426238704,
         "term": "squire_score"
       },
       {
         "ci_high": 18.888905716456527,
         "ci_low": -33.020068961245975,
         "coef": -7.065581622394723,
         "p": 0.5933870300831844,
         "se": 13.229708405319922,
         "t": -0.5340693389397393,
         "term": "initiatives"
       },
       {
         "ci_high": 4.04862330097067,
         "ci_low": -9.45887584310616,
         "coef": -2.705126271067745,
         "p": 0.4321389319643361,
         "se": 3.4425699230388687,
         "t": -0.7857868776939299,
         "term": "tel"
       },
       {
         "ci_high": -19.255719369288045,
         "ci_low": -78.87770022156202,
         "coef": -49.066709795425034,
         "p": 0.0012738685938721635,
         "se": 15.195472962442725,
         "t": -3.229034720847372,
         "term": "debtlimit"
       }
     ]
   }

   • dropped as collinear with the other regressors: ['fips[50]']

   Digests dos dados

   keele_do_term_limits 05bca1170ff33ca31ffea371b35a9489153b050608e2719369fc9accaa9127c8

   sha256 do resultado

   f7730a0c3e2c8a4df3f2c8bc4217cc25bbacd58678a614588f263ea335a098e0

   Resultado mostrado ao modelo
4. 3Turno do modelo
   call_15afe552referenceFim: 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.tl_onset = -5,559.",
       "caveats": [],
       "figure_refs": [
         "call_90de0dc8:coef.tl_onset"
       ]
     }

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

   Números encontrados

   -5,559

   Sem lastro

   —

   Não citados

   —

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

   Estimativa (infer.ols): coef.tl_onset = -5,559.

   Figuras citadas: call_90de0dc8:coef.tl_onset · Parada: answered

   Figura da resposta: call_90de0dc8:coef.tl_onset = -5,55924-5.559238248588588 (se 3,218723.2187239380607915)
7. 6Pontuação
   #0resposta com lastropassouobrigatóriaevery number backed
8. 7Pontuação
   #1figura da resposta próximapassouobrigatória-5.559238249 vs -5.559

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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