{"call_id":"call_df3c12dd","run_id":"20261015T171027Z-suite-crb_papers-naive-54c3f2/crb_papers.q089/e1a1","step":"analysis","kind":"llm","name":"llm.analyst.scripted","version":"","code_version":"2925aeab2262","inputs":{"tools":["calc__annuity","calc__breakeven","calc__combine","calc__discount","calc__fiscal_impact","core__atkinson","core__equivalent_variation","core__fgt","core__gini","core__indirect_incidence","core__kakwani","core__mvpf","core__palma","core__quantile_shares","core__reynolds_smolensky","core__scale_effect","core__theil","core__welfare_change","data__cite","data__describe","data__siconfi","data__sidra","evidence__pool_dl","infer__ate","infer__density_test","infer__did_2x2","infer__did_staggered","infer__event_study","infer__fe","infer__fisher_exact","infer__iv_2sls","infer__linear_hypothesis","infer__mde","infer__neyman","infer__ols","infer__power","infer__randomization_inference","infer__rdd","infer__sample_size","infer__twfe","infer__wald_late","submit_answer"],"exemplars":[]},"input_digest":"","dataset_digests":{},"result":null,"outputs":null,"output_digest":"","params_versions":[],"sources":[],"started_at":"2026-10-15T17:10:29.967487Z","duration_ms":0.0,"error":null,"decided_by":"model","rationale":"","cached":false,"informed_by":[],"model":"naive-ols","prompt":"# Role\nYou are MAGI's economist. A municipal analyst in Brazil asks a question; you answer it by choosing registered tools and their arguments. The tools compute every number. Your job is to recognise how the data were generated, pick the tool whose design matches, read what it reports, and say what the result means for the analyst.\n\n# Rules\n1. You never compute a number. Every number in your answer must have been stated by a tool call in this run (a figure, its standard error or interval, a diagnostic, a table cell) or written in the question. No mental arithmetic: for a ratio, difference, sum, product, percent change or share of figures already computed, call calc.combine; to restate a log-point coefficient as a percent or an effect in standard deviations, call core.scale_effect.\n2. Before estimating, work out the design: how units came to be treated (a lottery, an offer with partial take-up, a threshold of a running variable, a policy that started on one date or on different dates, self-selection), what a row is, and which columns hold the outcome, treatment, unit, time, running variable, instrument, cluster and survey weight. Call data.describe when the columns are unclear. Then choose the tool whose \"Use when\" matches and heed its \"Avoid when\".\n3. Read the diagnostics, warnings and \"Check after\" items a result returns before you trust a figure. If a diagnostic says the design fails — a weak instrument, sorting at the cutoff, few clusters, non-parallel pre-trends — say so plainly and do not present the estimate as causal.\n4. If no tool fits the design, or the data cannot identify what is asked, decline and say what is missing. Never invent a design, a column or a number.\n5. A tool that errors or declines returns its reason; fix the arguments and call again, or choose another tool.\n6. Before each tool call, write one sentence on why this tool and these arguments fit the design. It is recorded as your rationale.\n7. Finish with submit_answer. Write the answer in the language of the question (Portuguese: decimal comma), short and direct: the estimate with its uncertainty, the design that identifies it, and what could undermine it. List in figure_refs every figure you quote, as ':' (each tool result carries its call_id), and put diagnostics that limit the conclusion in caveats. Write numbers as the tools stated them; do not quote rule-of-thumb thresholds as numbers.\n\n# Datasets\nPass a dataset's id as the `dataset` argument.\n{\n \"id\": \"ds_0058\",\n \"rows\": 3950,\n \"description\": \"| Variable Name | Description |\\n|----------------------------|------------------------------------------------------------------------------------------------------|\\n| Unnamed: 0 | Row index |\\n| abb | State postal abbreviation |\\n| year | Calendar year |\\n| Policy | Annual state policy liberalism score (composite measure across policy domains) |\\n| hs_dem_per_2pty | Democratic share of the two-party vote in state house elections |\\n| sen_dem_per_2pty | Democratic share of the two-party vote in state senate elections |\\n| sen_dem_control | Indicator that Democrats control the state senate |\\n| election_year | Indicator for a gubernatorial election year |\\n| hs_dem_control | Indicator that Democrats control the state house |\\n| hs_dem_in_sess | Number of Democratic members seated in the state house |\\n| hs_rep_in_sess | Number of Republican members seated in the state house |\\n| hs_tot_in_sess | Total number of seats in the state house |\\n| sen_tot_in_sess | Total number of seats in the state senate |\\n| demprop2 | - |\\n| hs_elections_this_year | Indicator that the state held house elections in this year |\\n| sen_elections_this_year | Indicator that the state held senate elections in this year |\\n| gov_party | Party of the sitting governor (e.g., D/R) |\\n| sen_dem_prop_all_centered | Democratic seat share in the state senate, centered |\\n| hs_dem_prop_all_centered | Democratic seat share in the state house, centered |\\n| house_bins | Time-period bin label for house analyses (four-era scheme) |\\n| senate_bins | Time-period bin label for senate analyses (three-era scheme) |\\n| StPO | State postal abbreviation (duplicate) |\\n| Year | Calendar year (duplicate) |\\n| StateHouseDivergence | Ideological distance between Democratic and Republican medians in the state house |\\n| StateSenateDivergence | Ideological distance between Democratic and Republican medians in the state senate |\\n| DemControl | Share of major state institutions (governor, house, senate) held by Democrats |\\n| MassPartisanDivergence | Distance between average Democratic and Republican identifiers’ economic policy views in the state |\\n| Era4 | Four-era categorical label |\\n| Era3 | Three-era categorical label |\\n| StateHouseDivergence_L1 | One-year lag of StateHouseDivergence |\\n| StateSenateDivergence_L1 | One-year lag of StateSenateDivergence |\\n| MassPartisanDivergence_L1 | One-year lag of MassPartisanDivergence |\\n| MassPartisanDivergence_L2 | Two-year lag of MassPartisanDivergence |\\n| Policy_L1 | One-year lag of Policy |\\n| Policy_L2 | Two-year lag of Policy |\\n| Policy_L3 | Three-year lag of Policy |\\n| Policy_L4 | Four-year lag of Policy |\\n| DemControl_L1 | One-year lag of DemControl |\\n| DemControl_L2 | Two-year lag of DemControl |\\n| Policy_D1 | One-year change in Policy |\\n| Policy_D2 | Two-year change in Policy |\\n| Policy_D3 | Three-year change in Policy |\\n| Policy_D4 | Four-year change in Policy |\\n| hs_cont_alt | - |\\n| sen_cont_alt | - |\\n| South11 | Indicator for the 11 former Confederate states |\\n| StateLegDivergence | Ideological distance between party medians in the combined state legislature |\\n| StateLegDivergence_L1 | One-year lag of StateLegDivergence |\\n| DemGov | Indicator that the governor is a Democrat |\\n| DemPropGov0 | Democratic two-party vote share in the most recent gubernatorial election |\\n| DemMarginGov | Democratic two-party vote margin in the gubernatorial election |\\n| DemWinGov | Indicator that the Democrat won the gubernatorial election |\\n| DemSeatShareHouse | Democratic seat share in the state house |\\n| DemSeatShareSenate | Democratic seat share in the state senate |\\n| DemControlHouse | Indicator that Democrats hold a majority in the state house |\\n| DemControlSenate | Indicator that Democrats hold a majority in the state senate |\\n| GovLib | Policy liberalism series aligned to gubernatorial election timing |\\n| GovLibL1 | One-year lag of GovLib |\\n| GovLibL2 | Two-year lag of GovLib |\\n| GovLibL3 | Three-year lag of GovLib |\\n| GovLibL4 | Four-year lag of GovLib |\\n| GovLibL12 | Twelve-year lag of GovLib |\\n| GovLibP1 | One-year lead of GovLib |\\n| GovLibP2 | Two-year lead of GovLib |\\n| GovLibP3 | Three-year lead of GovLib |\\n| GovLibP4 | Four-year lead of GovLib |\\n| GovLibP12 | Twelve-year lead of GovLib |\\n| GovLibD1 | One-year change in GovLib |\\n| GovLibD2 | Two-year change in GovLib |\\n| GovLibD3 | Three-year change in GovLib |\\n| GovLibD4 | Four-year change in GovLib |\\n| GovLibD12 | Twelve-year change in GovLib |\\n| GovLibDL1 | One-year lag of the first difference of GovLib |\\n| GovLib.fe0 | - |\\n| GovLib.fe1 | - |\\n| GovLib.fe2 | - |\\n| GovLib.1 | - |\\n| GovLib.2 | - |\\n| GovLib.1L1 | - |\\n| GovLib.1L2 | - |\\n| GovLib.2L1 | - |\\n| GovLib.2L2 | - |\\n| GovLib.fe0L1 | - |\\n| GovLib.fe0L2 | - |\\n| GovLib.fe1L1 | - |\\n| GovLib.fe1L2 | - |\\n| GovLib.fe2L1 | - |\\n| GovLib.fe2L2 | - |\\n| GovLib.1P1 | - |\\n| GovLib.1P2 | - |\\n| GovLib.2P1 | - |\\n| GovLib.2P2 | - |\\n| GovLib.fe0P1 | - |\\n| GovLib.fe0P2 | - |\\n| GovLib.fe1P1 | - |\\n| GovLib.fe1P2 | - |\\n| GovLib.fe2P1 | - |\\n| GovLib.fe2P2 | - |\\n\\nData Description: \\nThis dataset assembles annual, state-level information on policy outputs, party control, election results, and ideological measures for the U.S. states over a long historical period. The core outcome is a yearly score of state policy liberalism derived from a broad set of substantive policy indicators spanning social welfare, taxation, labor, civil rights, criminal justice, and other domains. Complementing this are chamber composition measures (seat counts, seat shares, majority indicators), gubernatorial party and election results, and time-indexed transformations such as lags and differences that structure the panel.\\n\\nThe data were compiled by combining the dynamic state policy liberalism series with state legislative returns and composition data, gubernatorial election outcomes, measures of elite ideological positions in state legislatures, and mass public ideology by party within states. The panel covers 1936–2014 (with some variables available for shorter ranges), includes identifiers for states and eras, and provides both chamber-specific and combined-legislature indicators of partisan divergence. Variables with suffixes like _Lk, Dk, and Pk denote k-year lags, k-year differences, and k-year leads, respectively, offering analysts ready-to-use time-aligned series.\\n\",\n \"columns\": {\n \"Unnamed: 0\": \"int64\",\n \"abb\": \"str\",\n \"year\": \"int64\",\n \"Policy\": \"float64\",\n \"hs_dem_per_2pty\": \"float64\",\n \"sen_dem_per_2pty\": \"float64\",\n \"sen_dem_control\": \"float64\",\n \"election_year\": \"float64\",\n \"hs_dem_control\": \"float64\",\n \"hs_dem_in_sess\": \"float64\",\n \"hs_rep_in_sess\": \"float64\",\n \"hs_tot_in_sess\": \"float64\",\n \"sen_tot_in_sess\": \"float64\",\n \"demprop2\": \"float64\",\n \"hs_elections_this_year\": \"float64\",\n \"sen_elections_this_year\": \"float64\",\n \"gov_party\": \"float64\",\n \"sen_dem_prop_all_centered\": \"float64\",\n \"hs_dem_prop_all_centered\": \"float64\",\n \"house_bins\": \"str\",\n \"senate_bins\": \"str\",\n \"StPO\": \"str\",\n \"Year\": \"int64\",\n \"StateHouseDivergence\": \"float64\",\n \"StateSenateDivergence\": \"float64\",\n \"DemControl\": \"float64\",\n \"MassPartisanDivergence\": \"float64\",\n \"Era4\": \"str\",\n \"Era3\": \"str\",\n \"StateHouseDivergence_L1\": \"float64\",\n \"StateSenateDivergence_L1\": \"float64\",\n \"MassPartisanDivergence_L1\": \"float64\",\n \"MassPartisanDivergence_L2\": \"float64\",\n \"Policy_L1\": \"float64\",\n \"Policy_L2\": \"float64\",\n \"Policy_L3\": \"float64\",\n \"Policy_L4\": \"float64\",\n \"DemControl_L1\": \"float64\",\n \"DemControl_L2\": \"float64\",\n \"Policy_D1\": \"float64\",\n \"Policy_D2\": \"float64\",\n \"Policy_D3\": \"float64\",\n \"Policy_D4\": \"float64\",\n \"hs_cont_alt\": \"float64\",\n \"sen_cont_alt\": \"float64\",\n \"South11\": \"int64\",\n \"StateLegDivergence\": \"float64\",\n \"StateLegDivergence_L1\": \"float64\",\n \"DemGov\": \"float64\",\n \"DemPropGov0\": \"float64\",\n \"DemMarginGov\": \"float64\",\n \"DemWinGov\": \"float64\",\n \"DemSeatShareHouse\": \"float64\",\n \"DemSeatShareSenate\": \"float64\",\n \"DemControlHouse\": \"float64\",\n \"DemControlSenate\": \"float64\",\n \"GovLib\": \"float64\",\n \"GovLibL1\": \"float64\",\n \"GovLibL2\": \"float64\",\n \"GovLibL3\": \"float64\",\n \"GovLibL4\": \"float64\",\n \"GovLibL12\": \"float64\",\n \"GovLibP1\": \"float64\",\n \"GovLibP2\": \"float64\",\n \"GovLibP3\": \"float64\",\n \"GovLibP4\": \"float64\",\n \"GovLibP12\": \"float64\",\n \"GovLibD1\": \"float64\",\n \"GovLibD2\": \"float64\",\n \"GovLibD3\": \"float64\",\n \"GovLibD4\": \"float64\",\n \"GovLibD12\": \"float64\",\n \"GovLibDL1\": \"float64\",\n \"GovLib.fe0\": \"float64\",\n \"GovLib.fe1\": \"float64\",\n \"GovLib.fe2\": \"float64\",\n \"GovLib.1\": \"float64\",\n \"GovLib.2\": \"float64\",\n \"GovLib.1L1\": \"float64\",\n \"GovLib.1L2\": \"float64\",\n \"GovLib.2L1\": \"float64\",\n \"GovLib.2L2\": \"float64\",\n \"GovLib.fe0L1\": \"float64\",\n \"GovLib.fe0L2\": \"float64\",\n \"GovLib.fe1L1\": \"float64\",\n \"GovLib.fe1L2\": \"float64\",\n \"GovLib.fe2L1\": \"float64\",\n \"GovLib.fe2L2\": \"float64\",\n \"GovLib.1P1\": \"float64\",\n \"GovLib.1P2\": \"float64\",\n \"GovLib.2P1\": \"float64\",\n \"GovLib.2P2\": \"float64\",\n \"GovLib.fe0P1\": \"float64\",\n \"GovLib.fe0P2\": \"float64\",\n \"GovLib.fe1P1\": \"float64\",\n \"GovLib.fe1P2\": \"float64\",\n \"GovLib.fe2P1\": \"float64\",\n \"GovLib.fe2P2\": \"float64\"\n }\n}\n\n# Question\nAmong states with gubernatorial elections decided near 50-50, what is the average effect of electing a Democratic rather than a Republican governor on the one-year change in state policy liberalism?","response":"Linha de base ingênua: regressão do resultado no tratamento, sem controles.\ninfer__ols({\"dataset\": \"ds_0058\", \"y\": \"GovLibD1\", \"x\": [\"DemWinGov\"]})","tokens_in":0,"tokens_out":0,"meta":{"turn_call_id":"call_df3c12dd","text":"Linha de base ingênua: regressão do resultado no tratamento, sem 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