{"attempt":1,"datasets":{"autor_china_syndrome":{"description_shown":"This study assembles a commuting-zone panel for 1990-2007 to quantify how changes in Chinese import exposure relate to U.S. local labor-market outcomes, merging County Business Patterns, Census/ACS, and trade data to track employment, wages, nonemployment, and transfer receipts across places and time. The unit of observation is the commuting zone-year, with baseline characteristics recorded at the start of each period and subsequent changes measured over decade-length intervals.\nVariables include:\nczone: Commuting zone identifier\nstatefip: State FIPS code for the commuting zone\ncity: City/metropolitan label linked to the commuting zone\nyr: Calendar year of observation\nt2: Time-period indicator (e.g., 1990-2000 vs. 2000-2007 window)\ntimepwt48: Period weight used for aggregating across time intervals\nreg_midatl: Mid-Atlantic region dummy\nreg_encen: East North Central region dummy\nreg_wncen: West North Central region dummy\nreg_satl: South Atlantic region dummy\nreg_escen: East South Central region dummy\nreg_wscen: West South Central region dummy\nreg_mount: Mountain region dummy\nreg_pacif: Pacific region dummy\nl_popcount: Log working-age population count at baseline\nl_no_workers_totcbp: Log total employment (CBP) at baseline\nl_shind_manuf_cbp: Baseline share employed in manufacturing industries (CBP)\nl_sh_popedu_c: Baseline share of population with college education\nl_sh_popfborn: Baseline share of foreign-born population\nl_sh_empl_f: Baseline female employment share\nl_sh_routine33: Baseline share in routine-task occupations\nl_task_outsource: Baseline task offshorability index (higher = more offshorable)\nl_sh_empl: Baseline employment-to-population share\nl_sh_empl_mfg: Baseline manufacturing employment share\nl_sh_empl_mfg_m: Baseline male manufacturing employment share\nl_sh_empl_mfg_f: Baseline female manufacturing employment share\nl_sh_empl_mfg_edu_nc: Baseline manufacturing share, non-college\nl_sh_empl_mfg_edu_c: Baseline manufacturing share, college\nl_sh_empl_mfg_age1634: Baseline manufacturing share, ages 16-34\nl_sh_empl_mfg_age3549: Baseline manufacturing share, ages 35-49\nl_sh_empl_mfg_age5064: Baseline manufacturing share, ages 50-64\nl_sh_empl_nmfg: Baseline nonmanufacturing employment share\nl_sh_empl_nmfg_m: Baseline male nonmanufacturing employment share\nl_sh_empl_nmfg_f: Baseline female nonmanufacturing employment share\nl_sh_empl_nmfg_edu_nc: Baseline nonmanufacturing share, non-college\nl_sh_empl_nmfg_edu_c: Baseline nonmanufacturing share, college\nl_sh_empl_nmfg_age1634: Baseline nonmanufacturing share, ages 16-34\nl_sh_empl_nmfg_age3549: Baseline nonmanufacturing share, ages 35-49\nl_sh_empl_nmfg_age5064: Baseline nonmanufacturing share, ages 50-64\nl_sh_unempl: Baseline unemployment share\nl_sh_unempl_m: Baseline male unemployment share\nl_sh_unempl_f: Baseline female unemployment share\nl_sh_unempl_edu_nc: Baseline unemployment share, non-college\nl_sh_unempl_edu_c: Baseline unemployment share, college\nl_sh_unempl_age1634: Baseline unemployment share, ages 16-34\nl_sh_unempl_age3549: Baseline unemployment share, ages 35-49\nl_sh_unempl_age5064: Baseline unemployment share, ages 50-64\nl_sh_nilf: Baseline not-in-labor-force share\nl_sh_nilf_m: Baseline NILF share, male\nl_sh_nilf_f: Baseline NILF share, female\nl_sh_nilf_edu_nc: Baseline NILF share, non-college\nl_sh_nilf_edu_c: Baseline NILF share, college\nl_sh_nilf_age1634: Baseline NILF share, ages 16-34\nl_sh_nilf_age3549: Baseline NILF share, ages 35-49\nl_sh_nilf_age5064: Baseline NILF share, ages 50-64\nl_sh_ssadiswkrs: Baseline share on SSDI (disabled workers)\nl_avg_lnwkwage_mfg: Baseline log average weekly wage in manufacturing\nl_avg_lnwkwage_nmfg: Baseline log average weekly wage in nonmanufacturing\nl_trans_totindiv_pc: Baseline per-capita total individual transfers\nl_trans_totmed_pc: Baseline per-capita total Medicare transfers\nl_trans_fedinc_pc: Baseline per-capita federal income assistance\nl_trans_othinc_pc: Baseline per-capita other income assistance\nl_trans_unemp_pc: Baseline per-capita unemployment benefits\nl_trans_taaimp_pc: Baseline per-capita Trade Adjustment Assistance payments\nl_trans_totedu_pc: Baseline per-capita education-related transfers\nl_trans_ssaret_pc: Baseline per-capita Social Security retirement\nl_trans_ssadis_pc: Baseline per-capita Social Security disability\nl_avg_hhincsum_pc_pw: Baseline per-worker average household total income per capita\nl_avg_hhincwage_pc_pw: Baseline per-worker average household wage income per capita\nl_tradeusch_pw: Baseline U.S. imports-from-China exposure per worker\nl_tradeotch_pw: Baseline China exports to other high-income markets exposure per worker\nd_tradeusch_pw: Change in U.S. imports-from-China exposure per worker\nd_tradeotch_pw_lag: Lagged change in China-to-others exposure per worker\nlnchg_popworkage: Log change in working-age population\nlnchg_popworkage_edu_c: Log change in working-age population, college\nlnchg_popworkage_edu_nc: Log change in working-age population, non-college\nlnchg_popworkage_age1634: Log change, ages 16-34\nlnchg_popworkage_age3549: Log change, ages 35-49\nlnchg_popworkage_age5064: Log change, ages 50-64\nd_popcount: Change in population count\nd_sh_empl: Change in employment-to-population share\nd_sh_empl_mfg: Change in manufacturing employment share\nd_sh_empl_nmfg: Change in nonmanufacturing employment share\nd_sh_empl_mfg_m: Change in male manufacturing employment share\nd_sh_empl_nmfg_m: Change in male nonmanufacturing employment share\nd_sh_empl_mfg_f: Change in female manufacturing employment share\nd_sh_empl_nmfg_f: Change in female nonmanufacturing employment share\nd_sh_empl_mfg_edu_nc: Change in manufacturing share, non-college\nd_sh_empl_nmfg_edu_nc: Change in nonmanufacturing share, non-college\nd_sh_empl_mfg_edu_c: Change in manufacturing share, college\nd_sh_empl_nmfg_edu_c: Change in nonmanufacturing share, college\nd_sh_empl_mfg_age1634: Change in manufacturing share, ages 16-34\nd_sh_empl_nmfg_age1634: Change in nonmanufacturing share, ages 16-34\nd_sh_empl_mfg_age3549: Change in manufacturing share, ages 35-49\nd_sh_empl_nmfg_age3549: Change in nonmanufacturing share, ages 35-49\nd_sh_empl_mfg_age5064: Change in manufacturing share, ages 50-64\nd_sh_empl_nmfg_age5064: Change in nonmanufacturing share, ages 50-64\nd_sh_empl_edu_c: Change in overall employment share, college\nd_sh_empl_edu_nc: Change in overall employment share, non-college\nd_sh_unempl: Change in unemployment share\nd_sh_unempl_m: Change in male unemployment share\nd_sh_unempl_f: Change in female unemployment share\nd_sh_unempl_edu_nc: Change in unemployment share, non-college\nd_sh_unempl_edu_c: Change in unemployment share, college\nd_sh_unempl_age1634: Change in unemployment share, ages 16-34\nd_sh_unempl_age3549: Change in unemployment share, ages 35-49\nd_sh_unempl_age5064: Change in unemployment share, ages 50-64\nd_sh_nilf: Change in not-in-labor-force share\nd_sh_nilf_m: Change in NILF share, male\nd_sh_nilf_f: Change in NILF share, female\nd_sh_nilf_edu_nc: Change in NILF share, non-college\nd_sh_nilf_edu_c: Change in NILF share, college\nd_sh_nilf_age1634: Change in NILF share, ages 16-34\nd_sh_nilf_age3549: Change in NILF share, ages 35-49\nd_sh_nilf_age5064: Change in NILF share, ages 50-64\nd_sh_ssadiswkrs: Change in SSDI recipient share\nd_avg_lnwkwage: Change in log average weekly wage (overall)\nd_avg_lnwkwage_c: Change in log average weekly wage, college\nd_avg_lnwkwage_nc: Change in log average weekly wage, non-college\nd_avg_lnwkwage_m: Change in log average weekly wage, male\nd_avg_lnwkwage_f: Change in log average weekly wage, female\nd_avg_lnwkwage_c_m: Change in log average weekly wage, college males\nd_avg_lnwkwage_c_f: Change in log average weekly wage, college females\nd_avg_lnwkwage_nc_m: Change in log average weekly wage, non-college males\nd_avg_lnwkwage_nc_f: Change in log average weekly wage, non-college females\nd_avg_lnwkwage_mfg: Change in log average weekly wage in manufacturing\nd_avg_lnwkwage_mfg_c: Change in log manufacturing wage, college\nd_avg_lnwkwage_mfg_nc: Change in log manufacturing wage, non-college\nd_avg_lnwkwage_nmfg: Change in log average weekly wage in nonmanufacturing\nd_avg_lnwkwage_nmfg_c: Change in log nonmanufacturing wage, college\nd_avg_lnwkwage_nmfg_nc: Change in log nonmanufacturing wage, non-college\nlnchg_no_empl: Log change in number employed\nlnchg_no_empl_mfg: Log change in manufacturing employment count\nlnchg_no_empl_nmfg: Log change in nonmanufacturing employment count\nlnchg_no_empl_mfg_edu_nc: Log change in manufacturing employment, non-college\nlnchg_no_empl_nmfg_edu_nc: Log change in nonmanufacturing employment, non-college\nlnchg_no_empl_mfg_edu_c: Log change in manufacturing employment, college\nlnchg_no_empl_nmfg_edu_c: Log change in nonmanufacturing employment, college\nlnchg_no_unempl: Log change in number unemployed\nlnchg_no_nilf: Log change in number not in labor force\nlnchg_no_ssadiswkrs: Log change in number receiving SSDI\nlnchg_trans_totindiv_pc: Log change in per-capita total transfers\nlnchg_trans_totmed_pc: Log change in per-capita Medicare transfers\nlnchg_trans_fedinc_pc: Log change in per-capita federal income assistance\nlnchg_trans_othinc_pc: Log change in per-capita other income assistance\nlnchg_trans_unemp_pc: Log change in per-capita unemployment benefits\nlnchg_trans_taaimp_pc: Log change in per-capita TAA payments\nlnchg_trans_totedu_pc: Log change in per-capita education transfers\nlnchg_trans_ssaret_pc: Log change in per-capita Social Security retirement\nlnchg_trans_ssadis_pc: Log change in per-capita Social Security disability\nd_trans_totindiv_pc: Change in per-capita total transfers\nd_trans_totmed_pc: Change in per-capita Medicare transfers\nd_trans_fedinc_pc: Change in per-capita federal income assistance\nd_trans_othinc_pc: Change in per-capita other income assistance\nd_trans_unemp_pc: Change in per-capita unemployment benefits\nd_trans_taaimp_pc: Change in per-capita TAA payments\nd_trans_totedu_pc: Change in per-capita education transfers\nd_trans_ssaret_pc: Change in per-capita Social Security retirement\nd_trans_ssadis_pc: Change in per-capita Social Security disability\nrelchg_avg_hhincsum_pc_pw: Relative change in per-worker average household total income per capita\nrelchg_avg_hhincwage_pc_pw: Relative change in per-worker average household wage income per capita\nrelchg_avg_hhincbusinv_pc_pw: Relative change in per-worker average household business/investment income per capita\nrelchg_avg_hhinctrans_pc_pw: Relative change in per-worker average household transfer income per capita\nrelchg_avg_hhincrest_pc_pw: Relative change in per-worker average household residual income per capita\nrelchg_med_hhincsum_pc_pw: Relative change in per-worker median household total income per capita\nrelchg_med_hhincwage_pc_pw: Relative change in per-worker median household wage income per capita\nd_avg_hhincsum_pc_pw: Change in per-worker average household total income per capita\nd_avg_hhincwage_pc_pw: Change in per-worker average household wage income per capita\nd_avg_hhincbusinv_pc_pw: Change in per-worker average household business/investment income per capita\nd_avg_hhinctrans_pc_pw: Change in per-worker average household transfer income per capita\nd_avg_hhincrest_pc_pw: Change in per-worker average household residual income per capita\nd_med_hhincsum_pc_pw: Change in per-worker median household total income per capita\nd_med_hhincwage_pc_pw: Change in per-worker median household wage income per capita\nd_tradex_usch_pw: Change in exposure to U.S. exports to China per worker\nd_tradex_otch_pw_lag: Lagged change in exposure to China's exports to other high-income markets per worker\nd_tradeusch_netinput_pw: Change in net trade exposure per worker using input linkages\nd_inputotch_pw_lag: Lagged change in input-based China-to-others exposure per worker\nd_netimpusch_pw: Change in net imports-from-China exposure per worker\nd_expotch_pw_lag: Lagged change in exposure to Chinese exports per worker\nd_traderes_pw_lag: Lagged change in residual trade exposure per worker\nd_nettradefactor_usch_io: Change in factor-based net trade exposure (U.S.-China, input-output weighted)\nd_tradefactor_otch_lag_io: Lagged change in factor-based China-to-others exposure (IO weighted)\nd_expfactor_otch_lag_io: Lagged change in factor-based China export exposure (IO weighted)\nd_tradeuschlw_pw: Change in low-wage-weighted U.S. import exposure per worker\nd_tradeotchlw_pw_lag: Lagged change in low-wage-weighted China-to-others exposure per worker\nd_tradeuschce_pw: Change in consumption-expenditure-weighted U.S. import exposure per worker\nd_tradeotchce_pw_lag: Lagged change in consumption-expenditure-weighted China-to-others exposure per worker\nd_tradeusce_pw: Change in U.S. consumption-weighted import exposure per worker\nd_tradeotce_pw_lag: Lagged change in others' consumption-weighted China exposure per worker\nd_tradeushi_pw: Change in high-income-weighted U.S. import exposure per worker\nd_tradeothi_pw_lag: Lagged change in high-income-weighted China-to-others exposure per 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{"attempt":1,"attempts":[],"call_id":"call_6bc2b405","epoch":1,"event":"model","finish_reason":"tool_use","latency_ms":0.0,"model_reported":"naive-ols","model_requested":"naive-ols","provider":"scripted","request":{"config":{},"contents_refs":[],"messages_refs":["e2cb1f71c462ff5b25166ed23fa2c7ee5affe75c6a5bf6a17ea7fc65acc10aa4"],"system_stable_ref":"433a6877aa6a378bbd4b7e2752e484d8cb7499c562d68222be231f62ff2fa420","system_task_ref":"c396d5c9dae3880983b7979d303093904108b840320d8d72cdee6250aabe47ad","tools_ref":"52ab03d8ec104abb85572294bf8a469d75c5de9e74d6042caabff8017adc572b"},"response":{"text":"Linha de base ing\u00eanua: regress\u00e3o do resultado no tratamento, sem controles.","thoughts":null,"tool_calls":[{"args":{"dataset":"autor_china_syndrome","x":["d_tradeusch_pw"],"y":"d_sh_empl_mfg"},"llm_name":"infer__ols","tool_id":"infer.ols","vendor_id":"script_1"}]},"response_id":null,"run_id":"20261015T171142Z-suite-causcibench_real-naive-d6494d","seq":1,"task_id":"causcibench_real.q044","timestamp":"2026-10-15T17:11:43.842757Z","usage":{"cached":0,"input":0,"output":0,"thoughts":0},"vendor":false}
{"arguments":{"cluster":null,"controls":[],"dataset":"autor_china_syndrome","fe":[],"intercept":true,"level":0.95,"se":"HC1","subset":null,"weights":null,"x":["d_tradeusch_pw"],"y":"d_sh_empl_mfg"},"attempt":1,"cached":false,"call_id":"call_97cacab7","card_version":"0.1.0","code_version":"2925aeab2262","dataset_digests":{"autor_china_syndrome":"dff483b164debe4f7940c1b62d049aa15131912009e244d7aecab186f60327ff"},"decided_by":"model","duration_ms":5.239375168457627,"epoch":1,"error":null,"event":"tool","informed_by":[],"input_digest":"b5e3e868b3c6860c6c81f00c654ba1205533cbb3e5d43e6231ee8bc5136f2054","llm_name":"infer__ols","output_digest":"07df53cda924bcb23a8b48c7f0db12d5db70a1cea2c546f83fce6413c4ac31e3","rationale":"Linha de base ing\u00eanua: regress\u00e3o do resultado no tratamento, sem controles.","replay_class":"replayed","result":{"assumptions":["the conditional mean of the outcome is linear in the regressors","errors are independent across observations; their variance may differ"],"call_id":"call_97cacab7","datasets":{},"diagnostics":[{"flag":false,"name":"n_obs","note":"observations used","value":1444},{"flag":false,"name":"k","note":"parameters estimated, fixed-effect dummies included","value":2},{"flag":false,"name":"r2","note":"","value":0.15107686836275547},{"flag":false,"name":"df_resid","note":"","value":1442},{"flag":false,"name":"se_type","note":"heteroskedasticity-robust standard errors (HC1)","value":"HC1"},{"flag":false,"name":"n_clusters","note":"errors not clustered","value":null}],"figures":[{"ci_high":-0.24379575434494308,"ci_level":0.95,"ci_low":-0.5104576830228664,"derivation":{"note_pt":"","steps":[{"formula":"","result":-0.37712671868390474,"terms":[{"note":"","symbol":"n","unit":"observa\u00e7\u00f5es","value":1444.0},{"note":"","symbol":"k","unit":"par\u00e2metros","value":2.0}],"text_pt":"Coeficiente de d_tradeusch_pw na regress\u00e3o por m\u00ednimos quadrados ordin\u00e1rios de d_sh_empl_mfg.","unit":""},{"formula":"ep = \u221aV_jj","result":0.06797015334229951,"terms":[{"note":"diagonal da matriz de covari\u00e2ncia","symbol":"V_jj","unit":"","value":0.00461994174537571}],"text_pt":"Erro-padr\u00e3o robusto \u00e0 heterocedasticidade (HC1): a raiz da vari\u00e2ncia estimada do coeficiente.","unit":""},{"formula":"IC = \u03b2 \u00b1 c \u00b7 ep","result":null,"terms":[{"note":"","symbol":"\u03b2","unit":"","value":-0.37712671868390474},{"note":"quantil 0.975","symbol":"c","unit":"","value":1.9616104684581679},{"note":"","symbol":"ep","unit":"","value":0.06797015334229951}],"text_pt":"Intervalo de 95% de confian\u00e7a: a estimativa mais ou menos o valor cr\u00edtico da distribui\u00e7\u00e3o t de Student com 1442 graus de liberdade vezes o erro-padr\u00e3o.","unit":""}]},"key":"coef.d_tradeusch_pw","label":"Coefficient on d_tradeusch_pw in the regression of d_sh_empl_mfg","se":0.06797015334229951,"unit":"","value":-0.37712671868390474}],"notes":"","reason":"","status":"ok","tables":{"coefficients":[{"ci_high":-0.6593024525771742,"ci_low":-1.1495827730001305,"coef":-0.9044426127886523,"p":7.41013329682227e-13,"se":0.12496882747784228,"t":-7.237345752875975,"term":"Intercept"},{"ci_high":-0.24379575434494308,"ci_low":-0.5104576830228664,"coef":-0.37712671868390474,"p":3.425167646475188e-08,"se":0.06797015334229951,"t":-5.548416476047722,"term":"d_tradeusch_pw"}]},"tool":"infer.ols","version":"0.1.0","warnings":[]},"result_for_model_ref":"1273392c668fa5c03bdac921eb16a05d05002b97c0f5ae983e7f0b9f6e6caf41","result_sha256":"1b68d7d24f56d71c51615f7ed090eada65408df2abb11820003b8c671864e44b","run_id":"20261015T171142Z-suite-causcibench_real-naive-d6494d","seq":2,"synthetic":false,"task_id":"causcibench_real.q044","timestamp":"2026-10-15T17:11:43.845779Z","tool_id":"infer.ols","turn_id":"call_6bc2b405"}
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{"answer":"Estimativa ing\u00eanua (infer.ols): coef.d_tradeusch_pw = -0,3771.","answer_figure":{"call_id":"call_97cacab7","ci_high":-0.24379575434494308,"ci_low":-0.5104576830228664,"formatted":-0.37712671868390474,"key":"coef.d_tradeusch_pw","ref":"call_97cacab7:coef.d_tradeusch_pw","se":0.06797015334229951,"tool_id":"infer.ols","unit":"","value":-0.37712671868390474},"attempt":1,"caveats":[],"epoch":1,"event":"answer","figure_refs":["call_97cacab7:coef.d_tradeusch_pw"],"run_id":"20261015T171142Z-suite-causcibench_real-naive-d6494d","seq":5,"stopped":"answered","task_id":"causcibench_real.q044","timestamp":"2026-10-15T17:11:43.885892Z"}
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