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1{2 "validation_errors": [],3 "doc_id": "jof_12522",4 "ontology_version": "1.0",5 "prompt_version": "1.0",6 "model": "claude-opus-5-5",7 "effort": "medium",8 "annotated_at": "2026-11-03T22:59:17+00:00",9 "source_sha256": "583feee465b88ccc5bebcb9ca367adf20c06c6c6c8ea43662c0bb8017cf71117",10 "parser": "pymupdf-jof-heuristics-1.3",11 "payload_chars": 21627,12 "usage": {13  "input": 7041,14  "output": 2274,15  "cache_read": 3968,16  "cache_write": 017 },18 "cost_usd": 0.074438,19 "request_id": "req_011CggpjPkMd3HEbAgrGHxnf",20 "annotation": {21  "genre": "empirical",22  "subfield": "household_finance",23  "subfield_secondary": "financial_intermediation_banking",24  "primary_method": "regression_discontinuity",25  "identification": {26   "estimand": "Effect of an information-free credit rating downgrade on consumers' subsequent borrowing, borrower actions and market exit, plus the share of the post-default credit decline attributable to the credit-reporting downgrade itself.",27   "strategy": "Regression discontinuity around Peru's 'rule of twenty' rating-alignment regulation. The running variable is an exchange-rate-adjusted debt share, so currency movements push a bank's share across the 20% threshold. Complete-default outcomes are then decomposed by interacting default with the expected exogenous classification change.",28   "key_assumptions": [29    "Currency movements are exogenous to individual consumers",30    "No manipulation of the running variable around the 20% threshold",31    "Borrowers just above and just below the threshold are comparable",32    "Threshold crossing affects outcomes only through the rating alignment"33   ],34   "threats_addressed": [35    "Endogeneity of current-month balance changes (handled by using lagged, exchange-rate-adjusted balances)",36    "Covariate balance around the threshold",37    "Density manipulation (McCrary test)",38    "Placebo sample of borrowers with homogeneous loan ratings who should be unaffected"39   ],40   "causal_language_strength": 4,41   "uses_causal_claim": true42  },43  "abstract_moves": {44   "question": {45    "present": true,46    "sentence_index": 047   },48   "gap": {49    "present": false,50    "sentence_index": -151   },52   "method": {53    "present": true,54    "sentence_index": 155   },56   "results": {57    "present": true,58    "sentence_index": 159   },60   "magnitude": {61    "present": true,62    "sentence_index": 363   },64   "contribution": {65    "present": false,66    "sentence_index": -167   }68  },69  "introduction": {70   "moves": [71    {72     "paragraph_index": 0,73     "move": "motivation"74    },75    {76     "paragraph_index": 0,77     "move": "tension_or_puzzle"78    },79    {80     "paragraph_index": 1,81     "move": "preview_of_approach"82    },83    {84     "paragraph_index": 1,85     "move": "preview_of_results"86    },87    {88     "paragraph_index": 2,89     "move": "identification_defense"90    },91    {92     "paragraph_index": 3,93     "move": "preview_of_results"94    },95    {96     "paragraph_index": 4,97     "move": "related_literature_positioning"98    },99    {100     "paragraph_index": 4,101     "move": "contribution_statement"102    },103    {104     "paragraph_index": 5,105     "move": "preview_of_results"106    },107    {108     "paragraph_index": 5,109     "move": "mechanism_or_theory_sketch"110    },111    {112     "paragraph_index": 6,113     "move": "related_literature_positioning"114    },115    {116     "paragraph_index": 6,117     "move": "policy_or_broader_implication"118    },119    {120     "paragraph_index": 7,121     "move": "roadmap"122    }123   ],124   "contribution_paragraph_index": 4,125   "contribution_types": [126    "new_evidence",127    "new_identification"128   ],129   "roadmap_present": true,130   "literature_positioning_location": "inside_introduction"131  },132  "section_roles": [133   {134    "idx": 0,135    "role": "introduction"136   },137   {138    "idx": 1,139    "role": "data"140   },141   {142    "idx": 2,143    "role": "empirical_design"144   },145   {146    "idx": 3,147    "role": "results"148   },149   {150    "idx": 4,151    "role": "conclusion"152   }153  ],154  "results_presentation": {155   "economic_significance_discussed": true,156   "statistical_significance_language": "stars_and_tstats",157   "magnitude_statements_in_intro": true158  },159  "robustness": {160   "location": "within_results",161   "types": [162    "placebo",163    "alternative_specification",164    "falsification"165   ]166  },167  "tables": {168   "convention_notes": "Notes give the observation level (client-bank-month), the sample definition, and the equation estimated. Later tables point back to the baseline specification of Table IV. Stars mark significance levels. Outcomes are measured at 12-, 24- and 36-month horizons. Some variables are stated in soles.",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    "suggest",185    "may",186    "appears to",187    "potentially",188    "in our sample"189   ]190  },191  "claim_evidence": [192   {193    "claim": "Complete default is associated with medium-term reductions in borrowing in a random sample of the full data set",194    "evidence_type": "table",195    "evidence_ref": "Table III"196   },197   {198    "claim": "Exchange-rate-adjusted share predicts actual crossing of the 20% threshold",199    "evidence_type": "table",200    "evidence_ref": "Table IV, Figure 1"201   },202   {203    "claim": "Borrowers just above and below the threshold look similar on observables, with no density manipulation",204    "evidence_type": "figure",205    "evidence_ref": "Table V, Figures 2-3"206   },207   {208    "claim": "Crossing the threshold produces a moderate-duration rating downgrade only for borrowers with heterogeneous ratings",209    "evidence_type": "table",210    "evidence_ref": "Table VI, Figure 4"211   },212   {213    "claim": "Shocked borrowers see lower loan balances, less new financing and fewer new relationships for three years",214    "evidence_type": "table",215    "evidence_ref": "Table VII, Figure 5"216   },217   {218    "claim": "Shocked borrowers pay down judicial-collection loans and zero out credit cards",219    "evidence_type": "table",220    "evidence_ref": "Table VIII, Figure 6"221   },222   {223    "claim": "Shocked borrowers are more likely to exit the consumer loan market at two- and three-year horizons",224    "evidence_type": "table",225    "evidence_ref": "Table IX, Figure 7"226   },227   {228    "claim": "The reporting downgrade accounts for 25-65% of the post-default credit decline",229    "evidence_type": "table",230    "evidence_ref": "Tables X-XI"231   }232  ],233  "structural_summary": "Opens from the macro debate on weak post-2008 recovery and household borrowing constraints, then asks why negative credit events have lasting effects. Establishes a descriptive default–credit association first. It then uses a regulatory threshold combined with currency-driven variation as an RD to isolate information-free downgrades. The design is validated through first stage, covariate balance, density and placebo checks. Effects are traced on financing, borrower actions and broader outcomes, and the paper ends with a decomposition of the post-default decline. Policy implications about macro-contingent credit-history forgiveness close both the introduction and the conclusion.",234  "writing_profile_keywords": [235   "regression discontinuity",236   "regulatory threshold",237   "credit reporting",238   "consumer credit",239   "Peru",240   "exchange rate variation",241   "decomposition",242   "policy implication"243  ],244  "confidence": 0.85,245  "notes": "Standard-error type is not visible in the excerpts. Robustness checks are embedded in results subsections rather than a separate section. An Internet Appendix exists, but its content is not visible."246 },247 "deterministic_checks": {248  "roadmap_regex": true,249  "contribution_regex_in_intro": false,250  "magnitude_in_abstract": true,251  "abstract_n_sentences": 6,252  "intro_n_paragraphs": 8,253  "intro_n_words": 1114,254  "causal_words_in_abstract": 1,255  "hedge_words_in_abstract": 1,256  "stars_mentioned": true,257  "clustered_se_mentioned": false,258  "internet_appendix_mentioned": false,259  "section_roles_rule": {260   "0": "introduction",261   "1": "data",262   "2": "empirical_design",263   "3": "results",264   "4": "conclusion"265  }266 },267 "schema_valid": true,268 "code_version": "feb6c9e-dirty"269}
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