{"call_id":"call_5c2e510d","run_id":"20261015T165744Z-suite-paper_repro-scripted-def9df/paper_repro.fujiwara_2015.tab2_pa_valid98_c1.design/e1a1","step":"analysis","kind":"llm","name":"llm.analyst.scripted","version":"","code_version":"62cdbe0860ad","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":"2026-10-15T16:57:55.887993Z","duration_ms":0.0,"error":null,"decided_by":"model","rationale":"","cached":false,"informed_by":[],"model":"reference","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\": \"munic\",\n \"rows\": 5281,\n \"description\": \"The author's municipality file for Fujiwara (2015), 'Voting Technology, Political Responsiveness, and Infant Health: Evidence from Brazil': one row per Brazilian municipality (5,281 rows). In the 1998 elections, municipalities with more than 40,500 registered voters in 1996 used electronic voting and the others paper ballots; in 1994 every municipality used paper ballots and in 2002 every one voted electronically. Columns: uf, state; voters96, number of registered voters in 1996; r_util98, r_util94, r_util02, valid votes as a share of turnout in the state legislature elections of 1998, 1994 and 2002; attend, turnout as a share of registered voters (1998); regist, registered voters as a share of population (1998); null_est_share and blank_est_share, null and blank votes as a share of turnout (state legislature, 1998); util_pres_share, util_gov_share, util_fed_share, util_sen_share, valid votes as a share of turnout in the presidential, gubernatorial, federal lower chamber and senate elections (1998); right, vote-weighted party ideology; right_meas, votes for parties with measured ideology over total valid votes; right_state, state average of right; illiter, illiteracy rate (percent); less4 and less8, shares without 4 and without 8 years of schooling; gini, Gini index; income, monthly income; latitude; longitude; urbanization, share of urban population; population91 and population00, population in 1991 and 2000 (thousands). The schooling, income, inequality and urbanization variables come from the 1991 census.\",\n \"columns\": {\n \"uf\": \"str\",\n \"voters96\": \"float32\",\n \"illiter\": \"float32\",\n \"less4\": \"float32\",\n \"less8\": \"float32\",\n \"gini\": \"float32\",\n \"income\": \"float32\",\n \"latitude\": \"float32\",\n \"longitude\": \"float32\",\n \"right_state\": \"float32\",\n \"right\": \"float32\",\n \"right_meas\": \"float32\",\n \"null_est_share\": \"float32\",\n \"blank_est_share\": \"float32\",\n \"util_pres_share\": \"float32\",\n \"util_gov_share\": \"float32\",\n \"util_fed_share\": \"float32\",\n \"util_sen_share\": \"float32\",\n \"r_util98\": \"float32\",\n \"r_util02\": \"float32\",\n \"r_util94\": \"float32\",\n \"attend\": \"float32\",\n \"regist\": \"float32\",\n \"urbanization\": \"float32\",\n \"population91\": \"float32\",\n \"population00\": \"float32\"\n }\n}\n\n# Question\nDid electronic voting raise the share of votes that counted? In the 1998 Brazilian elections only municipalities with more than 40,500 registered voters in 1996 voted electronically. Estimate the effect of electronic voting on valid votes as a share of turnout in that year's state legislature elections, for municipalities near that threshold.","response":"Table II, Panel A, column (1): local linear RD at 40,500 voters, rectangular kernel, the paper's IK bandwidth 11,873, passed as printed, robust errors (munic.do: reg y treat dep deptreat if bw