1{2 "validation_errors": [],3 "doc_id": "jof_12725",4 "ontology_version": "1.0",5 "prompt_version": "1.0",6 "model": "claude-opus-5-5",7 "effort": "medium",8 "annotated_at": "2026-11-03T23:04:26+00:00",9 "source_sha256": "3a4e568c585991e2adb22c50d5cabe140eb4cb1dcb7cab3ce83f3c9fa25d897e",10 "parser": "pymupdf-jof-heuristics-1.3",11 "payload_chars": 21212,12 "usage": {13 "input": 6963,14 "output": 2203,15 "cache_read": 3968,16 "cache_write": 017 },18 "cost_usd": 0.072706,19 "request_id": "req_011Cggq8BZX8HcirHFuhjYh9",20 "annotation": {21 "genre": "empirical",22 "subfield": "financial_intermediation_banking",23 "subfield_secondary": "political economy of finance; household finance (mortgages and foreclosures)",24 "primary_method": "reduced_form_regression",25 "identification": {26 "estimand": "Difference in the hazard of, and time to, foreclosure start for 90-day delinquent mortgages located in districts of House Financial Services Committee members versus other districts during 2009–2010.",27 "strategy": "Loan-level exponential hazard and accelerated-failure-time models that use committee membership as a political factor argued to be orthogonal to local economic conditions. Models include loan and zip-code controls and state-by-time fixed effects. Placebos use other committees and past periods, and delinquency onset is checked for self-selection.",28 "key_assumptions": [29 "Committee membership is not tied to districts and does not proxy for economic factors affecting servicers' foreclosure decisions",30 "No self-selection of members into the committee based on local delinquency conditions",31 "Controls and state-time fixed effects absorb local economic shocks"32 ],33 "threats_addressed": [34 "Servicer capacity constraints from differing delinquency volumes",35 "Self-selection into committee membership",36 "Spurious committee effects (placebo committees)",37 "Time-invariant district effects (past-period placebos)",38 "Stimulus-fund allocation as an alternative explanation",39 "Econometric model specification"40 ],41 "causal_language_strength": 3,42 "uses_causal_claim": true43 },44 "abstract_moves": {45 "question": {46 "present": false,47 "sentence_index": -148 },49 "gap": {50 "present": false,51 "sentence_index": -152 },53 "method": {54 "present": false,55 "sentence_index": -156 },57 "results": {58 "present": true,59 "sentence_index": 160 },61 "magnitude": {62 "present": true,63 "sentence_index": 264 },65 "contribution": {66 "present": false,67 "sentence_index": -168 }69 },70 "introduction": {71 "moves": [72 {73 "paragraph_index": 0,74 "move": "motivation"75 },76 {77 "paragraph_index": 0,78 "move": "mechanism_or_theory_sketch"79 },80 {81 "paragraph_index": 1,82 "move": "preview_of_results"83 },84 {85 "paragraph_index": 1,86 "move": "identification_defense"87 },88 {89 "paragraph_index": 2,90 "move": "preview_of_results"91 },92 {93 "paragraph_index": 3,94 "move": "contribution_statement"95 },96 {97 "paragraph_index": 3,98 "move": "robustness_mention"99 },100 {101 "paragraph_index": 4,102 "move": "roadmap"103 }104 ],105 "contribution_paragraph_index": 3,106 "contribution_types": [107 "new_evidence"108 ],109 "roadmap_present": true,110 "literature_positioning_location": "inside_introduction"111 },112 "section_roles": [113 {114 "idx": 0,115 "role": "introduction"116 },117 {118 "idx": 1,119 "role": "other"120 },121 {122 "idx": 2,123 "role": "data"124 },125 {126 "idx": 3,127 "role": "results"128 },129 {130 "idx": 4,131 "role": "robustness"132 },133 {134 "idx": 5,135 "role": "results"136 },137 {138 "idx": 6,139 "role": "conclusion"140 },141 {142 "idx": 7,143 "role": "appendix"144 },145 {146 "idx": 8,147 "role": "appendix"148 },149 {150 "idx": 9,151 "role": "appendix"152 },153 {154 "idx": 10,155 "role": "appendix"156 }157 ],158 "results_presentation": {159 "economic_significance_discussed": true,160 "statistical_significance_language": "unclear",161 "magnitude_statements_in_intro": true162 },163 "robustness": {164 "location": "main_text_section",165 "types": [166 "placebo",167 "alternative_sample_period",168 "alternative_specification",169 "subsample",170 "falsification"171 ]172 },173 "tables": {174 "convention_notes": "Table notes name the estimator (exponential hazard, maximum-likelihood AFT with right-censoring), the sample period, the sample definition and the binary committee variable. Separate tables cover placebos, delinquency, senior members and alternative models.",175 "units_stated_in_notes": false,176 "standard_errors_description": "unclear"177 },178 "figures": {179 "uncertainty_shown": "no_figures"180 },181 "conclusion": {182 "bounded_claims": true,183 "policy_implications": false,184 "open_questions": true,185 "restates_contribution": true186 },187 "hedging": {188 "level": "moderate",189 "typical_devices": [190 "'unlikely to be driven by'",191 "'conservatively estimate'",192 "'may be more effective'",193 "explicit statement of what the paper does not show",194 "'quite plausible' assumptions"195 ]196 },197 "claim_evidence": [198 {199 "claim": "Servicers delayed foreclosure starts on delinquent loans in districts of HFSC members.",200 "evidence_type": "table",201 "evidence_ref": "Table II"202 },203 {204 "claim": "Foreclosure starts take about half a month longer in committee districts than the roughly 12-month average elsewhere.",205 "evidence_type": "table",206 "evidence_ref": "Table III"207 },208 {209 "claim": "Delinquency onset does not differ between committee and noncommittee districts.",210 "evidence_type": "table",211 "evidence_ref": "Table V"212 },213 {214 "claim": "No comparable effect appears for the Transportation & Infrastructure or Armed Services committees, or for HFSC in past periods.",215 "evidence_type": "table",216 "evidence_ref": "Table IV"217 },218 {219 "claim": "The cost of delay (~$30M) is comparable to lobbying and an order of magnitude above PAC contributions to members.",220 "evidence_type": "descriptive_statistic",221 "evidence_ref": "Introduction paragraph 2; foreclosure cost estimates from prior literature"222 },223 {224 "claim": "Results hold under alternative periods and econometric models and for senior members.",225 "evidence_type": "table",226 "evidence_ref": "Tables VI, VII"227 }228 ],229 "structural_summary": "Opens with a political anecdote about foreclosure moratorium calls to motivate whether banks' foreclosure timing responds to political concerns. The introduction previews the main hazard result, uses null delinquency differences to rule out capacity constraints, and quantifies the cost of delay against lobbying and PAC spending. It then frames foreclosure delay as a novel in-kind political channel. The body moves through institutional background, loan-level data and hazard regressions, then a robustness section of placebos, self-selection checks and alternative methods. A welfare section tests borrowers' nonmortgage credit outcomes. The conclusion restates the findings, draws political-economy implications, notes assumptions, and leaves banks' returns as an open question.",230 "writing_profile_keywords": [231 "political economy",232 "hazard models",233 "placebo tests",234 "loan-level data",235 "anecdotal motivation",236 "cost comparison",237 "first-to-document claim"238 ],239 "confidence": 0.8,240 "notes": "Abstract is results-focused, with no explicit gap or method sentence. Standard-error treatment is not visible in the excerpts. Section V is labeled robustness by the rule, but it functions as welfare and mechanism analysis."241 },242 "deterministic_checks": {243 "roadmap_regex": true,244 "contribution_regex_in_intro": true,245 "magnitude_in_abstract": false,246 "abstract_n_sentences": 5,247 "intro_n_paragraphs": 5,248 "intro_n_words": 809,249 "causal_words_in_abstract": 0,250 "hedge_words_in_abstract": 0,251 "stars_mentioned": false,252 "clustered_se_mentioned": false,253 "internet_appendix_mentioned": false,254 "section_roles_rule": {255 "0": "introduction",256 "1": "literature",257 "2": "data",258 "3": "other",259 "4": "robustness",260 "5": "robustness",261 "6": "conclusion",262 "7": "appendix",263 "8": "appendix",264 "9": "appendix",265 "10": "appendix"266 }267 },268 "schema_valid": true,269 "code_version": "feb6c9e-dirty"270}