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Tarefa crb_papers.q051

crb_papersagentT2publicépoca 1, tentativa 1Execução: 20261015T171027Z-suite-crb_papers-naive-54c3f2

Veredito

falhouDecidida pela verificação 1: figura da resposta próxima, fora da tolerância.
0.1124380421 in [-0.3051840721, -0.04680777739]?

Família do método (das chamadas de ferramentas): ols (regression)

Pergunta feita ao analista

How did logged district capital expenditures per capita change in 2010 in districts holding a district head election that year versus districts that did not hold an election that year (restricting to districts without an election the year prior)?

Resposta

Estimativa ingênua (infer.ols): coef.election_year = 0,1124.

Valores esperados e de onde vêm

crb_papers.q051.gold

Fonte
CausalReasoningBenchmark, causal_queries.json, index 51 (revision edd0fe1c1d1c)
Tipo
benchmark_gold
Localização
causal_queries.json['51'].effect and .standard_error
Trecho
index 51: effect -0.175996, standard_error 0.0659123
Valor como publicado
-0.17599592472724762
Erro-padrão como publicado
0.06591232006923611
Valor
-0,175996-0.17599592472724762 (se 0,06591230.06591232006923611)
Conferido por
arquivo do benchmark · Read from the catalog at the pinned revision by scripts/freeze_crb_papers.py; the catalog states the value its estimation script prints.
Endereço
https://huggingface.co/datasets/syrgkanislab/CausalReasoningBenchmark/resolve/edd0fe1c1d1c5c0a4f0e3e67a50481ac679fb888/causal_queries.json
Licença
MIT
  • #2 figura da resposta próxima: -0,175996-0.17599592472724762 · relativa 0.000001 · absoluta 6.591232006923611e-8
  • #3 figura da resposta próxima: 0,06591230.06591232006923611 · relativa 0.000001 · absoluta 6.591232006923611e-8

crb_papers.q051.script

Fonte
CausalReasoningBenchmark reference estimation script for index 51
Tipo
software
Localização
solutions/research_papers/DiD/Pierskalla_Sacks_2018/question_1/estimation.py
Valor
—
Conferido por
arquivo do benchmark · sha256 of the script's 1713 bytes at the pinned revision; the reference path of the item is a transcription of this script into typed transforms and tool calls (never executed here).
Implementação
independente da ferramenta
sha256 da cópia lida
11a46d9801a93c40b86aad91174f865c708c588855bd17cafc41e8aa94c56132 (identifica a cópia lida, não um arquivo canônico)
Endereço
https://huggingface.co/datasets/syrgkanislab/CausalReasoningBenchmark/resolve/edd0fe1c1d1c5c0a4f0e3e67a50481ac679fb888/solutions/research_papers/DiD/Pierskalla_Sacks_2018/question_1/estimation.py
Licença
MIT

    Verificações

    Cada verificação, o que esperava, o que observou e a chamada que leu
    #VerificaçãoObrigatóriaResultadoEsperadoObservadoTolerânciaFonteChamada
    0resposta com lastro
    every number backed
    obrigatóriapassou—[]———
    1figura da resposta próxima
    0.1124380421 in [-0.3051840721, -0.04680777739]?
    obrigatóriafalhou[-0.3051840720629504,-0.04680777739154485]0,1124380.11243804212457445interval · [-0.3051840720629504, -0.04680777739154485]—call_09c7bb00
    2figura da resposta próxima
    0.1124380421 vs -0.17599592472724762
    registradafalhou-0,175996-0.175995924727247620,1124380.11243804212457445relativa 0.000001 · absoluta 6.591232006923611e-8crb_papers.q051.goldcall_09c7bb00
    3figura da resposta próxima
    0.04467788271 vs 0.06591232006923611
    registradafalhou0,06591230.065912320069236110,04467790.04467788270993699relativa 0.000001 · absoluta 6.591232006923611e-8crb_papers.q051.goldcall_09c7bb00

    Caminho de referência e caminho do agente

    A chamada de referência ao lado da chamada que deu a resposta, argumento por argumento.

    caminho de referência do item · benchmark_script

    Referência: infer.olsChamada do agente: infer.ols (call_09c7bb00)igual
    Argumentos da referência e do agente
    ArgumentoReferênciaAgente
    cluster"kode_neil"—diferente
    controls["TreatGroup","Post"][]diferente
    dataset"ref_panel""ds_0027"diferente
    fe—[]não fixado pela referência
    intercept—truenão fixado pela referência
    level—0,950.95não fixado pela referência
    se—"HC1"não fixado pela referência
    subset——não fixado pela referência
    weights——não fixado pela referência
    x["DiD"]["election_year"]diferente
    y"lcapital_exp_pc""lcapital_exp_pc"igual

    Trajetória

    Cada evento na ordem em que aconteceu: turnos do modelo, chamadas de ferramentas, guardas, transformações e pontuação.

    1. 0Início

      How did logged district capital expenditures per capita change in 2010 in districts holding a district head election that year versus districts that did not hold an election that year (restricting to districts without an election the year prior)?

      ds_0027 (agent)

      | Variable Name | Description | | --- | --- | | year | Calendar year of observation for the district-level fiscal and political records (2001–2012). | | kode_neil | Harmonized district identifier that tracks administrative units across boundary changes and splits to maintain longitudinal comparability. | | personnel_sh | Share of total realized district expenditures allocated to personnel (wages, salaries, allowances); expressed as a fraction between 0 and 1. | | capital_sh | Share of total realized district expenditures allocated to capital investment (e.g., infrastructure, equipment); expressed as a fraction between 0 and 1. | | ltotalexp_all_pc | Natural log of total realized district government expenditures per capita (rupiah per resident). | | lcapital_exp_pc | Natural log of realized district capital expenditures per capita (rupiah per resident). | | incumbency | Indicator for whether the sitting district head is a candidate in that year (1=yes, 0=no); relevant in years when district head elections are held. | | services_provision | Standardized index summarizing local service delivery (sanitation access, clean water access, school enrollment, skilled birth attendance, and road quality); higher values indicate better provision. | | lgdppc_l | Natural log of district GDP per capita from official statistics, lagged one year. | | lpop_l | Natural log of the district’s population, lagged one year. | | rev_total_pc2_l | Total district revenue per capita from all sources (including general transfers and revenue sharing), lagged one year; measured in rupiah per resident. | | rev_natural_pc_l | Shared natural resource revenues (intergovernmental revenue sharing tied to extractive resources) per capita, lagged one year; measured in rupiah per resident. | | poverty_pc_l | Fraction of the district population below the official poverty line, lagged one year (0–1 scale). | | gini_l | Gini index of consumption inequality from household survey data, lagged one year (0–100 scale; higher = more unequal). | | elected_leader_l | Indicator that the district head position is filled by direct popular election (1) versus selection by the local legislature (0), lagged one year; direct elections were rolled out beginning in 2005. | | golkar_share_all | Vote share of the Golkar party in the district’s legislative elections (compiled from 1999 and 2004 results); expressed as a fraction between 0 and 1. | | pdip_share_all | Vote share of the Indonesian Democratic Party of Struggle (PDI–P) in the district’s legislative elections (compiled from 1999 and 2004 results); expressed as a fraction between 0 and 1. | | enp_all | Effective number of parties in the district legislature (Laakso–Taagepera index); higher values indicate more fragmented party systems. | | election_year | Indicator that a district head election is held in the current calendar year (1=yes, 0=no); reflects the local executive election calendar. | | election_year_l | Indicator for the year immediately preceding a district head election (lead-up year; 1=yes, 0=no). | | election_year_lead1 | Indicator for the year immediately following a district head election (post-election year; 1=yes, 0=no). | Dataset Context: This panel assembles district-by-year information for Indonesia’s post-decentralization era, covering 2001–2012. Fiscal figures are realized (executed) budgets from the Ministry of Finance and use the national economic classification that separates outlays into capital investment, goods and services, and personnel. Revenue items distinguish general-purpose transfers and shared natural resource revenues alongside locally generated revenue. Where noted, variables are expressed per capita using contemporaneous district population counts, and several key covariates are provided in natural logs to reduce skew. Political characteristics capture the local partisan environment and institutional arrangements. District-level party vote shares are compiled from the 1999 and 2004 legislative elections to describe the baseline partisan landscape. The effective number of parties quantifies legislative fragmentation. Indonesia shifted from indirect selection of district heads by local legislatures (1999–2004) to direct popular elections beginning in 2005. The initial schedule of local executive contests was phased according to pre-existing appointment terms, producing staggered election years across districts. Indicators mark the election year itself as well as the years immediately before and after. Socioeconomic and service delivery measures come from official statistics agencies and large-scale household surveys (including Susenas). The services index combines access and quality proxies—sanitation, clean water, school enrollment, skilled birth attendance, and road conditions—standardized so that higher values indicate stronger provision. Inequality (Gini) and poverty rates are derived from household consumption data. Variables with the “_l” suffix are lagged one calendar year to reflect prior conditions relative to the current budget year. The administrative map of Indonesia evolved substantially during this period due to district proliferation. The dataset harmonizes identifiers to follow units through splits, yielding an unbalanced panel by design. Users should note that national statistical agencies implemented notable survey and weighting changes around 2011; while the panel extends through 2012, comparability for certain survey-based indicators across this redesign may warrant caution. District governments largely finance spending through intergovernmental transfers and shared revenues, as local borrowing was highly restricted during these years. Overall, the dataset provides a consolidated view of local public finance, political structure, and socioeconomic context during Indonesia’s early decentralization and direct local election era.

      file e02ae6b363d47cf0f76a5fc37d88e1f8ffc08c6b9f51eee68d0b5d6b12c2d727 · frame —
      ref_panel (reference)
      file e02ae6b363d47cf0f76a5fc37d88e1f8ffc08c6b9f51eee68d0b5d6b12c2d727 · frame —
      1. select {"columns":["lcapital_exp_pc","election_year","kode_neil","year"]}
      2. dropna {"columns":["lcapital_exp_pc","election_year","kode_neil","year"]}
      3. filter {"query":"year in [2009, 2010]"}
      4. merge {"how":"inner","on":["kode_neil"],"with":"ref_pre"}
      5. merge {"how":"inner","on":["kode_neil"],"with":"ref_post"}
      6. filter {"query":"t0 == 0 and (t1 == 1 or t1 == 0)"}
      7. derive {"args":{"cmp":"eq","column":"t1","value":1},"name":"TreatGroup","op":"indicator"}
      8. derive {"args":{"cmp":"eq","column":"year","value":2010},"name":"Post","op":"indicator"}
      9. derive {"args":{"columns":["TreatGroup","Post"]},"name":"DiD","op":"interaction"}
      ref_post (reference)
      file e02ae6b363d47cf0f76a5fc37d88e1f8ffc08c6b9f51eee68d0b5d6b12c2d727 · frame —
      1. select {"columns":["lcapital_exp_pc","election_year","kode_neil","year"]}
      2. dropna {"columns":["lcapital_exp_pc","election_year","kode_neil","year"]}
      3. filter {"query":"year == 2010"}
      4. select {"columns":["kode_neil","election_year"]}
      5. rename {"map":{"election_year":"t1"}}
      ref_pre (reference)
      file e02ae6b363d47cf0f76a5fc37d88e1f8ffc08c6b9f51eee68d0b5d6b12c2d727 · frame —
      1. select {"columns":["lcapital_exp_pc","election_year","kode_neil","year"]}
      2. dropna {"columns":["lcapital_exp_pc","election_year","kode_neil","year"]}
      3. filter {"query":"year == 2009"}
      4. select {"columns":["kode_neil","election_year"]}
      5. rename {"map":{"election_year":"t0"}}
    2. 1Turno do modelo
      call_7bf618b0naive-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_0027",
          "x": [
            "election_year"
          ],
          "y": "lcapital_exp_pc"
        }
    3. 2Ferramenta
      infer.olsv0.1.0call_09c7bb00decidido pelo modeloreexecutável

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

      Argumentos
      {
        "cluster": null,
        "controls": [],
        "dataset": "ds_0027",
        "fe": [],
        "intercept": true,
        "level": 0.95,
        "se": "HC1",
        "subset": null,
        "weights": null,
        "x": [
          "election_year"
        ],
        "y": "lcapital_exp_pc"
      }
      Figuras call_09c7bb00
      ChaveValorValor brutoErro-padrãoIC
      coef.election_year
      Coefficient on election_year in the regression of lcapital_exp_pc
      0,112438 0.112438042124574450,04467790.044677882709936990,02485 – 0,200026
      Diagnósticos
      • n_obs = 5.0465046
      • k = 22
      • r2 = 0,001312860.0013128572019270868
      • df_resid = 5.0445044
      • se_type = "HC1"
      • n_clusters = —
      Tabelas (1)
      {
        "coefficients": [
          {
            "ci_high": 12.95725482312203,
            "ci_low": 12.889751020657828,
            "coef": 12.923502921889929,
            "p": 0,
            "se": 0.017216541927267497,
            "t": 750.6445241144351,
            "term": "Intercept"
          },
          {
            "ci_high": 0.20002610079835967,
            "ci_low": 0.02484998345078923,
            "coef": 0.11243804212457445,
            "p": 0.011878832851659468,
            "se": 0.04467788270993699,
            "t": 2.516637658381395,
            "term": "election_year"
          }
        ]
      }
      • 1841 rows were dropped because one of 'lcapital_exp_pc', 'election_year' was missing
      Digests dos dados
      ds_0027 34e6aab5839bb0d13885f393ef3301fae7aaba436c2973fc095e08870341facd
      sha256 do resultado
      2d822184ddf27968745313fb2816c53944df24177a86716b6f9c811bb88e1fa7
    4. 3Turno do modelo
      call_921a668bnaive-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.election_year = 0,1124.",
          "caveats": [],
          "figure_refs": [
            "call_09c7bb00:coef.election_year"
          ]
        }
    5. 4Guarda
      resposta aceita
      Números encontrados
      0,1124
      Sem lastro
      —
      Não citados
      —
      1 nova(s) tentativa(s) restante(s)
    6. 5Resposta

      Estimativa ingênua (infer.ols): coef.election_year = 0,1124.

      Figuras citadas: call_09c7bb00:coef.election_year · Parada: answered
      Figura da resposta: call_09c7bb00:coef.election_year = 0,1124380.11243804212457445 (se 0,04467790.04467788270993699)
    7. 6Pontuação
      #0resposta com lastropassouobrigatóriaevery number backed
    8. 7Pontuação
      #1figura da resposta próximafalhouobrigatória0.1124380421 in [-0.3051840721, -0.04680777739]?
    9. 8Pontuação
      #2figura da resposta próximafalhouregistrada0.1124380421 vs -0.17599592472724762
    10. 9Pontuação
      #3figura da resposta próximafalhouregistrada0.04467788271 vs 0.06591232006923611

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    #0123
    Época 1passoufalhoufalhoufalhou

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