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1{2 "validation_errors": [],3 "doc_id": "jof_12821",4 "ontology_version": "1.0",5 "prompt_version": "1.0",6 "model": "claude-opus-5-5",7 "effort": "medium",8 "annotated_at": "2026-11-03T23:08:56+00:00",9 "source_sha256": "8ef34f94d1cb69fc5e1735f56a2dd14afec7ff5be98e68a43faa7ffd8948b87f",10 "parser": "pymupdf-jof-heuristics-1.3",11 "payload_chars": 32022,12 "usage": {13  "input": 10593,14  "output": 2469,15  "cache_read": 3968,16  "cache_write": 017 },18 "cost_usd": 0.092546,19 "request_id": "req_011CggqU1ZKgq8Gy1WyCxH3S",20 "annotation": {21  "genre": "empirical",22  "subfield": "household_finance",23  "subfield_secondary": "financial_intermediation_banking",24  "primary_method": "instrumental_variables",25  "identification": {26   "estimand": "Causal effect of a foreclosure on a resetting ARM on default and foreclosure probability among neighboring properties within 0.10 miles (foreclosure spillover)",27   "strategy": "IV/2SLS in which the within-month interest rate shock at ARM reset, driven by index choice (LIBOR vs Treasury) and lookback period, instruments for the foreclosure of the resetting loan; first stage, reduced form and IV estimates are contrasted with OLS",28   "key_assumptions": [29    "Within-month reset rate variation from index and lookback terms is unrelated to other determinants of loan performance",30    "Exclusion restriction: the resetting loan's rate shock affects neighbors' defaults only through its foreclosure",31    "Neighboring loans have different contract terms, so they are not directly hit by the same shock"32   ],33   "threats_addressed": [34    "Common local shocks such as a plant closure, addressed by showing effects are concentrated at very small distances",35    "Pre-existing neighborhood distress, addressed with a placebo on prior foreclosures",36    "Borrower selection into index type",37    "Demand versus supply in refinancing, addressed with mortgage inquiries"38   ],39   "causal_language_strength": 4,40   "uses_causal_claim": true41  },42  "abstract_moves": {43   "question": {44    "present": false,45    "sentence_index": -146   },47   "gap": {48    "present": false,49    "sentence_index": -150   },51   "method": {52    "present": true,53    "sentence_index": 054   },55   "results": {56    "present": true,57    "sentence_index": 158   },59   "magnitude": {60    "present": true,61    "sentence_index": 162   },63   "contribution": {64    "present": false,65    "sentence_index": -166   }67  },68  "introduction": {69   "moves": [70    {71     "paragraph_index": 0,72     "move": "motivation"73    },74    {75     "paragraph_index": 1,76     "move": "mechanism_or_theory_sketch"77    },78    {79     "paragraph_index": 1,80     "move": "literature_gap"81    },82    {83     "paragraph_index": 1,84     "move": "contribution_statement"85    },86    {87     "paragraph_index": 2,88     "move": "preview_of_approach"89    },90    {91     "paragraph_index": 2,92     "move": "identification_defense"93    },94    {95     "paragraph_index": 3,96     "move": "preview_of_results"97    },98    {99     "paragraph_index": 3,100     "move": "related_literature_positioning"101    },102    {103     "paragraph_index": 4,104     "move": "preview_of_approach"105    },106    {107     "paragraph_index": 5,108     "move": "identification_defense"109    },110    {111     "paragraph_index": 5,112     "move": "preview_of_results"113    },114    {115     "paragraph_index": 6,116     "move": "preview_of_results"117    },118    {119     "paragraph_index": 7,120     "move": "preview_of_results"121    },122    {123     "paragraph_index": 8,124     "move": "preview_of_results"125    },126    {127     "paragraph_index": 9,128     "move": "preview_of_results"129    },130    {131     "paragraph_index": 10,132     "move": "related_literature_positioning"133    },134    {135     "paragraph_index": 11,136     "move": "roadmap"137    }138   ],139   "contribution_paragraph_index": 1,140   "contribution_types": [141    "new_identification",142    "new_evidence",143    "new_data_or_measure"144   ],145   "roadmap_present": true,146   "literature_positioning_location": "inside_introduction"147  },148  "section_roles": [149   {150    "idx": 0,151    "role": "introduction"152   },153   {154    "idx": 1,155    "role": "data"156   },157   {158    "idx": 2,159    "role": "results"160   },161   {162    "idx": 3,163    "role": "results"164   },165   {166    "idx": 4,167    "role": "results"168   },169   {170    "idx": 5,171    "role": "robustness"172   },173   {174    "idx": 6,175    "role": "conclusion"176   }177  ],178  "results_presentation": {179   "economic_significance_discussed": true,180   "statistical_significance_language": "unclear",181   "magnitude_statements_in_intro": true182  },183  "robustness": {184   "location": "mixed",185   "types": [186    "placebo",187    "subsample",188    "falsification",189    "alternative_measure"190   ]191  },192  "tables": {193   "convention_notes": "Table notes state the regression equations (first stage, reduced form, 2SLS) and describe the samples (Deeds vs BlackBox). Heterogeneity and placebo tables reuse the main IV specification. Summary statistics are split by index type.",194   "units_stated_in_notes": true,195   "standard_errors_description": "unclear"196  },197  "figures": {198   "uncertainty_shown": "unclear"199  },200  "conclusion": {201   "bounded_claims": true,202   "policy_implications": true,203   "open_questions": false,204   "restates_contribution": true205  },206  "hedging": {207   "level": "moderate",208   "typical_devices": [209    "consistent with",210    "suggest",211    "likely reflects",212    "may help to explain",213    "potentially point to",214    "highly unlikely ex ante"215   ]216  },217  "claim_evidence": [218   {219    "claim": "A 100bp higher reset rate raises the 12-month foreclosure probability by about 2.5 points against an 8% baseline",220    "evidence_type": "table",221    "evidence_ref": "Table II; Figure 6"222   },223   {224    "claim": "Each instrumented foreclosure raises neighbor default probability by about 2.1%, or 0.3-0.6 additional foreclosures",225    "evidence_type": "table",226    "evidence_ref": "Table II, Table IV"227   },228   {229    "claim": "LIBOR-Treasury spread and lookback volatility produce sizable within-month payment differences",230    "evidence_type": "figure",231    "evidence_ref": "Figures 1-4"232   },233   {234    "claim": "Neighboring sale prices fall about 1-3% after a resetting ARM forecloses",235    "evidence_type": "figure",236    "evidence_ref": "Figure 7"237   },238   {239    "claim": "Neighbor refinancing falls by one-third while mortgage inquiries do not, indicating a bank supply response",240    "evidence_type": "table",241    "evidence_ref": "Table III; Figure 8"242   },243   {244    "claim": "Spillovers are strongest in areas with few prior foreclosures and are concentrated at short distances",245    "evidence_type": "table",246    "evidence_ref": "Table VI; Figure 10"247   },248   {249    "claim": "Tract-level foreclosure activity raises mortgage denials, citing collateral reasons",250    "evidence_type": "table",251    "evidence_ref": "Table VII; Figure 12"252   },253   {254    "claim": "Placebo: the instrument does not predict prior neighbor foreclosures",255    "evidence_type": "table",256    "evidence_ref": "Table IX"257   }258  ],259  "structural_summary": "The paper opens with crisis-scale motivation and lists candidate spillover channels. It then introduces two contract-detail instruments, previews first-stage, reduced-form and IV magnitudes, and walks through mechanism results (prices, refinancing supply, borrower learning) before aggregate HMDA evidence. Literature positioning sits inside the introduction, followed by a roadmap. The body covers data and strategy, main IV results, mechanisms, macro channels, and a short placebo robustness section. The conclusion restates the findings, favours an informational interpretation, and closes with bank-run analogies and policy implications.",260  "writing_profile_keywords": [261   "instrumental variables",262   "contract-detail instruments",263   "peer effects",264   "foreclosure spillovers",265   "mechanism decomposition",266   "single-author first person",267   "geocoded administrative data"268  ],269  "confidence": 0.8,270  "notes": "The roadmap labels Section V as the conclusion, but in the section list Section V is Robustness and VI is the Conclusion. The abstract is truncated and has no explicit gap or contribution sentence. Standard error treatment is not visible in the excerpts. Mechanism and macro sections were classified as results despite the rule-based robustness label."271 },272 "deterministic_checks": {273  "roadmap_regex": true,274  "contribution_regex_in_intro": true,275  "magnitude_in_abstract": true,276  "abstract_n_sentences": 4,277  "intro_n_paragraphs": 12,278  "intro_n_words": 1773,279  "causal_words_in_abstract": 1,280  "hedge_words_in_abstract": 0,281  "stars_mentioned": false,282  "clustered_se_mentioned": false,283  "internet_appendix_mentioned": false,284  "section_roles_rule": {285   "0": "introduction",286   "1": "data",287   "2": "other",288   "3": "robustness",289   "4": "robustness",290   "5": "robustness",291   "6": "conclusion"292  }293 },294 "schema_valid": true,295 "code_version": "87c73cd-dirty"296}
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