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1{2 "validation_errors": [],3 "repairs": [4  "hoisted tables.figures -> figures",5  "hoisted tables.conclusion -> conclusion",6  "hoisted tables.hedging -> hedging",7  "hoisted tables.claim_evidence -> claim_evidence"8 ],9 "doc_id": "jof_12900",10 "ontology_version": "1.0",11 "prompt_version": "1.0",12 "model": "claude-opus-5-5",13 "effort": "medium",14 "annotated_at": "2026-11-03T23:26:54+00:00",15 "source_sha256": "f37dbb22f2499faa93a32eed5eb6241fb26e28d5f0ed6739729ad53810016d6b",16 "parser": "pymupdf-jof-heuristics-1.3",17 "payload_chars": 21270,18 "usage": {19  "input": 7173,20  "output": 2263,21  "cache_read": 3968,22  "cache_write": 023 },24 "cost_usd": 0.074746,25 "request_id": "req_011CggqtCrPoWtU55iEzQ87w",26 "annotation": {27  "genre": "mixed_theory_empirical",28  "subfield": "financial_intermediation_banking",29  "subfield_secondary": "structural estimation of asymmetric information in credit markets / macro-finance (credit crunch)",30  "primary_method": "structural_estimation",31  "identification": {32   "estimand": "Magnitude of the information gap (incumbent lenders' private information) and its contribution to the decline in lending during the 2007-2009 crisis",33   "strategy": "Two-stage discrete-choice model of renewal and new relationship formation. Bank lending-capacity shocks separate private from common information. Renewers serve as a benchmark, and the second stage uses non-renewing firms while correcting for selection on common information.",34   "key_assumptions": [35    "Bank shocks to lending ability are unrelated to unobservable borrower characteristics",36    "Distribution of borrower unobservables and the lending rule are common across lenders up to a matching error orthogonal to the previous lender's shock"37   ],38   "threats_addressed": [39    "Confounding of private information with common information unobservable to the econometrician",40    "Mechanical selection of non-renewing firms on common information",41    "Matching errors (Monte Carlo)"42   ],43   "causal_language_strength": 3,44   "uses_causal_claim": true45  },46  "abstract_moves": {47   "question": {48    "present": true,49    "sentence_index": 050   },51   "gap": {52    "present": false,53    "sentence_index": -154   },55   "method": {56    "present": true,57    "sentence_index": 258   },59   "results": {60    "present": true,61    "sentence_index": 362   },63   "magnitude": {64    "present": false,65    "sentence_index": -166   },67   "contribution": {68    "present": true,69    "sentence_index": 270   }71  },72  "introduction": {73   "moves": [74    {75     "paragraph_index": 0,76     "move": "motivation"77    },78    {79     "paragraph_index": 0,80     "move": "policy_or_broader_implication"81    },82    {83     "paragraph_index": 1,84     "move": "contribution_statement"85    },86    {87     "paragraph_index": 1,88     "move": "preview_of_approach"89    },90    {91     "paragraph_index": 1,92     "move": "preview_of_results"93    },94    {95     "paragraph_index": 2,96     "move": "preview_of_approach"97    },98    {99     "paragraph_index": 3,100     "move": "mechanism_or_theory_sketch"101    },102    {103     "paragraph_index": 4,104     "move": "identification_defense"105    },106    {107     "paragraph_index": 5,108     "move": "preview_of_results"109    },110    {111     "paragraph_index": 5,112     "move": "tension_or_puzzle"113    },114    {115     "paragraph_index": 6,116     "move": "related_literature_positioning"117    },118    {119     "paragraph_index": 7,120     "move": "related_literature_positioning"121    },122    {123     "paragraph_index": 8,124     "move": "related_literature_positioning"125    }126   ],127   "contribution_paragraph_index": 1,128   "contribution_types": [129    "new_evidence",130    "new_identification",131    "new_method",132    "new_theory_or_model"133   ],134   "roadmap_present": false,135   "literature_positioning_location": "inside_introduction"136  },137  "section_roles": [138   {139    "idx": 0,140    "role": "introduction"141   },142   {143    "idx": 1,144    "role": "data"145   },146   {147    "idx": 2,148    "role": "data"149   },150   {151    "idx": 3,152    "role": "theory"153   },154   {155    "idx": 4,156    "role": "results"157   },158   {159    "idx": 5,160    "role": "conclusion"161   },162   {163    "idx": 6,164    "role": "appendix"165   }166  ],167  "results_presentation": {168   "economic_significance_discussed": true,169   "statistical_significance_language": "confidence_intervals",170   "magnitude_statements_in_intro": false171  },172  "robustness": {173   "location": "mixed",174   "types": [175    "subsample",176    "alternative_measure",177    "other"178   ]179  },180  "tables": {181   "convention_notes": "Probit tables report marginal effects ×100. Second-stage estimates use nonlinear least squares on non-renewers with bootstrapped 95% CIs. Notes define renewal via lead-lender overlap, the crisis-exposure construction, and sample restrictions. Counterfactual lending is computed with the information gap set to zero.",182   "units_stated_in_notes": true,183   "standard_errors_description": "bootstrap"184  },185  "structural_summary": "The introduction motivates the work with relationship stickiness and its aggregate fragility, then states the main contribution: a first direct estimate of the information gap. It frames the key challenge of separating private from common information and sketches the comparison with renewers and a three-layer-information discrete-choice model. Identifying assumptions are stated, followed by a negative quantitative result contrasted with the prevailing view, and an alternative covenant channel is proposed. Related literature is discussed inside the introduction. The body moves from data and bank-shock measurement to the model and identification, then to two-stage estimation, aggregate counterfactuals, bias from naive models, policy, and generalizability. A short conclusion restates the method and finding.",186  "writing_profile_keywords": [187   "structural discrete choice",188   "adverse selection",189   "identification of private vs common information",190   "negative result",191   "bank shocks",192   "first-person singular",193   "quantification",194   "syndicated loans"195  ],196  "confidence": 0.8,197  "notes": "Single-authored. The main finding is a null/small-magnitude result. Robustness via subsamples (Table AIV), alternative bank shocks (Fig A2) and Monte Carlo (Fig A3) sits in the appendix. Section 2 heading appears to be a parsing fragment of Section I.",198  "figures": {199   "uncertainty_shown": "unclear"200  },201  "conclusion": {202   "bounded_claims": true,203   "policy_implications": false,204   "open_questions": false,205   "restates_contribution": true206  },207  "hedging": {208   "level": "moderate",209   "typical_devices": [210    "'appears to be' qualifiers on the main finding",211    "'unlikely to explain'",212    "explicit statement of maintained assumptions",213    "'a likely friction' for alternative mechanisms",214    "confining the conclusion to the syndicated loan market"215   ]216  },217  "claim_evidence": [218   {219    "claim": "Lending relationships in the syndicated market are very sticky; few firms form new relationships relative to renewals",220    "evidence_type": "descriptive_statistic",221    "evidence_ref": "Table I"222   },223   {224    "claim": "Lender crisis exposure lowers renewal probability with the existing lender",225    "evidence_type": "table",226    "evidence_ref": "Table II"227   },228   {229    "claim": "Estimated information gap is small",230    "evidence_type": "table",231    "evidence_ref": "Table III"232   },233   {234    "claim": "Information gap explains little of the aggregate post-crisis lending decline",235    "evidence_type": "table",236    "evidence_ref": "Table IV"237   },238   {239    "claim": "Naive models ignoring common information greatly overstate the friction's effect",240    "evidence_type": "table",241    "evidence_ref": "Table V"242   },243   {244    "claim": "Reduced-form patterns consistent with the inference hypothesis are mostly driven by common information",245    "evidence_type": "table",246    "evidence_ref": "Table AIII; Figure 6"247   },248   {249    "claim": "Bank shocks matter for firm borrowing in this market",250    "evidence_type": "prior_literature",251    "evidence_ref": "Chodorow-Reich (2014)"252   }253  ]254 },255 "deterministic_checks": {256  "roadmap_regex": false,257  "contribution_regex_in_intro": true,258  "magnitude_in_abstract": false,259  "abstract_n_sentences": 5,260  "intro_n_paragraphs": 9,261  "intro_n_words": 1297,262  "causal_words_in_abstract": 0,263  "hedge_words_in_abstract": 1,264  "stars_mentioned": false,265  "clustered_se_mentioned": false,266  "internet_appendix_mentioned": true,267  "section_roles_rule": {268   "0": "introduction",269   "1": "other",270   "2": "other",271   "3": "other",272   "4": "empirical_design",273   "5": "conclusion",274   "6": "appendix"275  }276 },277 "schema_valid": true,278 "code_version": "87c73cd-dirty"279}
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