{"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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{"arguments":{"cluster":null,"dataset":"autor_china_syndrome","endog":["d_tradeusch_pw"],"exog":["t2"],"instruments":["d_tradeotch_pw_lag"],"level":0.95,"se":"HC1","subset":null,"y":"d_sh_empl_mfg"},"attempt":1,"cached":false,"call_id":"call_35778d9b","card_version":"0.1.0","code_version":"2925aeab2262","dataset_digests":{"autor_china_syndrome":"dff483b164debe4f7940c1b62d049aa15131912009e244d7aecab186f60327ff"},"decided_by":"model","duration_ms":17.70579209551215,"epoch":1,"error":null,"event":"tool","informed_by":[],"input_digest":"932cfd224a41209497d1e8d09c132cda999d7a6bc61f848d5a9d6dc8d2459775","llm_name":"infer__iv_2sls","output_digest":"b3835d37c24cd43d96da6014e0a2a5b1d1c918fe9aa139529c16d4db6823cf2a","rationale":"causcibench_metadata_rule/1: iv","replay_class":"replayed","result":{"assumptions":["the instruments affect the outcome only through the endogenous regressors (exclusion restriction)","the instruments are as good as randomly assigned given the controls","errors are independent across observations; their variance may differ"],"call_id":"call_35778d9b","datasets":{},"diagnostics":[{"flag":false,"name":"first_stage_F.d_tradeusch_pw","note":"Wald F of the excluded instruments in the first stage for d_tradeusch_pw (heteroskedasticity-robust standard errors (HC1))","value":51.56145914069501},{"flag":false,"name":"partial_r2.d_tradeusch_pw","note":"share of the variation the instruments explain beyond the controls","value":0.46298812988549665},{"flag":false,"name":"weak_instrument","note":"every first-stage F is at least 10","value":false},{"flag":false,"name":"n_obs","note":"","value":1444},{"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":-0.3681782751365685,"ci_level":0.95,"ci_low":-0.8749733490814211,"derivation":{"note_pt":"","steps":[{"formula":"\u03b2 = \u03c1 / \u03c0","result":-0.6215758121089948,"terms":[{"note":"forma reduzida","symbol":"\u03c1","unit":"","value":-0.5389958133083622},{"note":"primeiro est\u00e1gio","symbol":"\u03c0","unit":"","value":0.867144124349948}],"text_pt":"Com um instrumento e um regressor end\u00f3geno, o MQ2E \u00e9 a raz\u00e3o entre o coeficiente de d_tradeotch_pw_lag na forma reduzida (d_sh_empl_mfg sobre d_tradeotch_pw_lag e os controles) e no primeiro est\u00e1gio (d_tradeusch_pw sobre d_tradeotch_pw_lag e os controles).","unit":""},{"formula":"ep = \u221aV_jj","result":0.12917824069875605,"terms":[{"note":"diagonal da matriz de covari\u00e2ncia","symbol":"V_jj","unit":"","value":0.016687017870025755}],"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":-0.6215758121089948},{"note":"quantil 0.975","symbol":"c","unit":"","value":1.96161161200012},{"note":"","symbol":"ep","unit":"","value":0.12917824069875605}],"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 1441 graus de liberdade vezes o erro-padr\u00e3o.","unit":""}]},"key":"coef.d_tradeusch_pw","label":"2SLS effect of d_tradeusch_pw on d_sh_empl_mfg","se":0.12917824069875605,"unit":"","value":-0.6215758121089948}],"notes":"","reason":"","status":"ok","tables":{"coefficients":[{"ci_high":0.11641955290747832,"ci_low":-0.5437871324843294,"coef":-0.21368378978842553,"p":0.20436156483465448,"se":0.16828170300201287,"t":-1.2697981181345044,"term":"Intercept"},{"ci_high":-0.051299538639999254,"ci_low":-0.8484407356217173,"coef":-0.44987013713085827,"p":0.026978757222309684,"se":0.2031852768675569,"t":-2.214088264988309,"term":"t2"},{"ci_high":-0.3681782751365685,"ci_low":-0.8749733490814211,"coef":-0.6215758121089948,"p":1.6531087415123596e-06,"se":0.12917824069875605,"t":-4.811768675178903,"term":"d_tradeusch_pw"}],"first_stage":[{"ci_high":1.104031387249036,"ci_low":0.6302568614508601,"coef":0.867144124349948,"endog":"d_tradeusch_pw","instrument":"d_tradeotch_pw_lag","p":1.1079723089122809e-12,"se":0.12076155210844738,"t":7.180630831667577}],"reduced_form":[{"ci_high":-0.3776723394103266,"ci_low":-0.7003192872063979,"coef":-0.5389958133083622,"instrument":"d_tradeotch_pw_lag","p":7.783686691322959e-11,"se":0.08224027269778712,"t":-6.553915686649532}]},"tool":"infer.iv_2sls","version":"0.1.0","warnings":[]},"result_for_model_ref":"07534828e88d40849a30b164f2bef53371865def26cfbabe45c1aba5a260af18","result_sha256":"c7c02a6c4304034d0c683c2c0c3d482f0c659a63b4e30bb73e63802a6501c420","run_id":"20261015T171059Z-suite-causcibench_real-scripted-ded01d","seq":2,"synthetic":false,"task_id":"causcibench_real.q044","timestamp":"2026-10-15T17:11:00.796483Z","tool_id":"infer.iv_2sls","turn_id":"call_e55cedc3"}
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{"answer":"Estimativa (infer.iv_2sls): coef.d_tradeusch_pw = -0,6216.","answer_figure":{"call_id":"call_35778d9b","ci_high":-0.3681782751365685,"ci_low":-0.8749733490814211,"formatted":-0.6215758121089948,"key":"coef.d_tradeusch_pw","ref":"call_35778d9b:coef.d_tradeusch_pw","se":0.12917824069875605,"tool_id":"infer.iv_2sls","unit":"","value":-0.6215758121089948},"attempt":1,"caveats":[],"epoch":1,"event":"answer","figure_refs":["call_35778d9b:coef.d_tradeusch_pw"],"run_id":"20261015T171059Z-suite-causcibench_real-scripted-ded01d","seq":5,"stopped":"answered","task_id":"causcibench_real.q044","timestamp":"2026-10-15T17:11:00.816305Z"}
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