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1{2 "validation_errors": [],3 "doc_id": "jof_12604",4 "ontology_version": "1.0",5 "prompt_version": "1.0",6 "model": "claude-opus-5-5",7 "effort": "medium",8 "annotated_at": "2026-11-03T23:01:06+00:00",9 "source_sha256": "860c930fc2afa26d0bb367bd471d774e67eac4db8c400b203876d2c222d80e6a",10 "parser": "pymupdf-jof-heuristics-1.3",11 "payload_chars": 19925,12 "usage": {13  "input": 6821,14  "output": 2166,15  "cache_read": 3968,16  "cache_write": 017 },18 "cost_usd": 0.071398,19 "request_id": "req_011CggpsTJQAJL9BoHfCssfc",20 "annotation": {21  "genre": "empirical",22  "subfield": "financial_intermediation_banking",23  "subfield_secondary": "corporate_finance",24  "primary_method": "reduced_form_regression",25  "identification": {26   "estimand": "Equilibrium sorting between borrower bank-dependence and lender capital, plus counterfactual crisis loan supply under alternative matching assignments",27   "strategy": "Cross-sectional and within-bank regressions of lender capital on borrower characteristics; lead-versus-participant and revolver-versus-term-loan contrasts to narrow mechanisms; Fox (2016) semiparametric matching estimator for counterfactual matchings; Khwaja-Mian style crisis lending regressions",28   "key_assumptions": [29    "Lack of an S&P rating proxies for bank dependence",30    "Lead arrangers monitor while participants bear default risk without monitoring",31    "Each quarter is an independent matching market with one-to-one matching to a single lead arranger",32    "Observed matches reflect pairwise stability (maximum score)"33   ],34   "threats_addressed": [35    "Mechanism ambiguity across competing theories, via lender roles and loan types",36    "Time-invariant bank heterogeneity, via within-bank variation",37    "Inconsistency of bootstrap for maximum score, via an alternative CI construction"38   ],39   "causal_language_strength": 2,40   "uses_causal_claim": false41  },42  "abstract_moves": {43   "question": {44    "present": true,45    "sentence_index": 046   },47   "gap": {48    "present": false,49    "sentence_index": -150   },51   "method": {52    "present": false,53    "sentence_index": -154   },55   "results": {56    "present": true,57    "sentence_index": 158   },59   "magnitude": {60    "present": false,61    "sentence_index": -162   },63   "contribution": {64    "present": true,65    "sentence_index": 266   }67  },68  "introduction": {69   "moves": [70    {71     "paragraph_index": 0,72     "move": "motivation"73    },74    {75     "paragraph_index": 0,76     "move": "literature_gap"77    },78    {79     "paragraph_index": 0,80     "move": "preview_of_results"81    },82    {83     "paragraph_index": 0,84     "move": "contribution_statement"85    },86    {87     "paragraph_index": 1,88     "move": "policy_or_broader_implication"89    },90    {91     "paragraph_index": 1,92     "move": "preview_of_approach"93    },94    {95     "paragraph_index": 2,96     "move": "mechanism_or_theory_sketch"97    },98    {99     "paragraph_index": 2,100     "move": "tension_or_puzzle"101    },102    {103     "paragraph_index": 3,104     "move": "preview_of_results"105    },106    {107     "paragraph_index": 4,108     "move": "other"109    },110    {111     "paragraph_index": 5,112     "move": "related_literature_positioning"113    },114    {115     "paragraph_index": 5,116     "move": "contribution_statement"117    }118   ],119   "contribution_paragraph_index": 5,120   "contribution_types": [121    "new_evidence"122   ],123   "roadmap_present": false,124   "literature_positioning_location": "inside_introduction"125  },126  "section_roles": [127   {128    "idx": 0,129    "role": "introduction"130   },131   {132    "idx": 1,133    "role": "theory"134   },135   {136    "idx": 2,137    "role": "data"138   },139   {140    "idx": 3,141    "role": "results"142   },143   {144    "idx": 4,145    "role": "empirical_design"146   },147   {148    "idx": 5,149    "role": "results"150   },151   {152    "idx": 6,153    "role": "conclusion"154   }155  ],156  "results_presentation": {157   "economic_significance_discussed": true,158   "statistical_significance_language": "unclear",159   "magnitude_statements_in_intro": true160  },161  "robustness": {162   "location": "within_results",163   "types": [164    "alternative_specification"165   ]166  },167  "tables": {168   "convention_notes": "Notes open by stating the dependent variable and sample, then define key variables (market equity ratio as bank capital, unrated borrower as bank-dependent). Spreads are given in basis points. The counterfactual table states its estimation window.",169   "units_stated_in_notes": true,170   "standard_errors_description": "unclear"171  },172  "figures": {173   "uncertainty_shown": "unclear"174  },175  "conclusion": {176   "bounded_claims": true,177   "policy_implications": true,178   "open_questions": false,179   "restates_contribution": true180  },181  "hedging": {182   "level": "moderate",183   "typical_devices": [184    "evidence suggests",185    "consistent with / inconsistent with",186    "explicit caveat that directional statements are descriptive only",187    "external validity discussion",188    "not isolating a specific channel"189   ]190  },191  "claim_evidence": [192   {193    "claim": "Unrated (bank-dependent) firms borrow from lead arrangers with about 1.8 points higher equity capital than rated firms do.",194    "evidence_type": "table",195    "evidence_ref": "Table III"196   },197   {198    "claim": "Sorting by capital holds for lead arrangers but not for participants, favoring monitoring and relationship explanations over risk management.",199    "evidence_type": "table",200    "evidence_ref": "Table V"201   },202   {203    "claim": "Borrowers of poorly capitalized banks were more likely to issue bonds after the 2008 crisis.",204    "evidence_type": "figure",205    "evidence_ref": "Figure 2"206   },207   {208    "claim": "High-capital banks earn a spread premium when lending to small or bank-dependent firms.",209    "evidence_type": "table",210    "evidence_ref": "Table VII"211   },212   {213    "claim": "Observed matching mitigates crisis loan supply cuts for bank-dependent firms relative to counterfactual assignments.",214    "evidence_type": "table",215    "evidence_ref": "Table X"216   },217   {218    "claim": "Competing banking theories predict opposite sortings, making the question an empirical one.",219    "evidence_type": "prior_literature",220    "evidence_ref": "Introduction paragraph 2; Section I"221   }222  ],223  "structural_summary": "The introduction moves from the known effects of banking relationships to the unexplored question of what determines them. It previews the headline sorting result with magnitudes and draws out its aggregate implication for credit cyclicality. It then sets competing theoretical predictions against each other, adds an interpretive caveat, and closes with literature positioning. The body follows: a conceptual framework of rival hypotheses, data construction, regression evidence (cross-section, within-bank, mechanism tests via lender roles and loan types, pricing), and a semiparametric matching model used for crisis counterfactuals. The conclusion restates the findings, discusses external validity, and spells out implications for the credit channel.",224  "writing_profile_keywords": [225   "stylized fact",226   "two-sided matching",227   "competing hypotheses",228   "mechanism narrowing",229   "counterfactual",230   "credit channel",231   "first-person singular"232  ],233  "confidence": 0.8,234  "notes": "Single-author paper. The section labeled '1' continues the matching model section (a parsing artifact). Standard-error conventions are not visible in the excerpts; the matching model uses a non-bootstrap confidence interval construction."235 },236 "deterministic_checks": {237  "roadmap_regex": false,238  "contribution_regex_in_intro": true,239  "magnitude_in_abstract": false,240  "abstract_n_sentences": 3,241  "intro_n_paragraphs": 6,242  "intro_n_words": 979,243  "causal_words_in_abstract": 0,244  "hedge_words_in_abstract": 0,245  "stars_mentioned": false,246  "clustered_se_mentioned": false,247  "internet_appendix_mentioned": false,248  "section_roles_rule": {249   "0": "introduction",250   "1": "theory",251   "2": "data",252   "3": "other",253   "4": "theory",254   "5": "other",255   "6": "conclusion"256  }257 },258 "schema_valid": true,259 "code_version": "feb6c9e-dirty"260}
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