1{2 "validation_errors": [],3 "doc_id": "jof_12722",4 "ontology_version": "1.0",5 "prompt_version": "1.0",6 "model": "claude-opus-5-5",7 "effort": "medium",8 "annotated_at": "2026-11-03T23:04:47+00:00",9 "source_sha256": "ab134dba0b0dcf60c02a71704242bbbf70f97fa4dd2788ffbc422b0cbe1ec125",10 "parser": "pymupdf-jof-heuristics-1.3",11 "payload_chars": 22264,12 "usage": {13 "input": 8169,14 "output": 2172,15 "cache_read": 3968,16 "cache_write": 017 },18 "cost_usd": 0.07691,19 "request_id": "req_011Cggq9H7BDxjvv2Ve7dStn",20 "annotation": {21 "genre": "mixed_theory_empirical",22 "subfield": "asset_pricing",23 "subfield_secondary": "experimental finance / collateral and leverage",24 "primary_method": "survey_or_experiment",25 "identification": {26 "estimand": "Price spread between two assets with identical payoffs that differ only in whether they can be used as collateral, compared against model-implied equilibrium values",27 "strategy": "Controlled laboratory double-auction experiment implementing a collateral general equilibrium model. The two assets have identical payoffs, so the price spread isolates collateral value. Observed outcomes are compared to equilibrium benchmarks calibrated to elicited risk aversion.",28 "key_assumptions": [29 "Laboratory implementation faithfully represents the model economy",30 "Subjects have CRRA preferences, which allows the Holt-Laury elicitation to map choices to risk-aversion parameters",31 "Induced payoffs control subjects' valuations"32 ],33 "threats_addressed": [34 "Heterogeneity in risk aversion, handled through Holt-Laury elicitation and an equilibrium computed for different beta values",35 "Learning and convergence, addressed by comparing practice rounds, early paid rounds and late paid rounds",36 "Session-level differences, addressed with by-session tables and Wilcoxon tests"37 ],38 "causal_language_strength": 4,39 "uses_causal_claim": true40 },41 "abstract_moves": {42 "question": {43 "present": true,44 "sentence_index": 045 },46 "gap": {47 "present": false,48 "sentence_index": -149 },50 "method": {51 "present": true,52 "sentence_index": 153 },54 "results": {55 "present": true,56 "sentence_index": 257 },58 "magnitude": {59 "present": true,60 "sentence_index": 461 },62 "contribution": {63 "present": false,64 "sentence_index": -165 }66 },67 "introduction": {68 "moves": [69 {70 "paragraph_index": 0,71 "move": "motivation"72 },73 {74 "paragraph_index": 0,75 "move": "related_literature_positioning"76 },77 {78 "paragraph_index": 0,79 "move": "mechanism_or_theory_sketch"80 },81 {82 "paragraph_index": 1,83 "move": "preview_of_results"84 },85 {86 "paragraph_index": 2,87 "move": "related_literature_positioning"88 },89 {90 "paragraph_index": 2,91 "move": "tension_or_puzzle"92 },93 {94 "paragraph_index": 3,95 "move": "preview_of_results"96 },97 {98 "paragraph_index": 3,99 "move": "roadmap"100 }101 ],102 "contribution_paragraph_index": -1,103 "contribution_types": [104 "new_evidence",105 "new_theory_or_model"106 ],107 "roadmap_present": true,108 "literature_positioning_location": "inside_introduction"109 },110 "section_roles": [111 {112 "idx": 0,113 "role": "introduction"114 },115 {116 "idx": 1,117 "role": "theory"118 },119 {120 "idx": 2,121 "role": "empirical_design"122 },123 {124 "idx": 3,125 "role": "results"126 },127 {128 "idx": 4,129 "role": "conclusion"130 }131 ],132 "results_presentation": {133 "economic_significance_discussed": true,134 "statistical_significance_language": "p_values",135 "magnitude_statements_in_intro": false136 },137 "robustness": {138 "location": "within_results",139 "types": [140 "subsample",141 "sensitivity_to_parameters"142 ]143 },144 "tables": {145 "convention_notes": "Notes report descriptive statistics (means, medians, standard deviations in parentheses), both pooled and by session. Nonparametric Wilcoxon signed-rank and rank-sum tests are reported with p-values. Theory tables give equilibrium values across a range of risk-aversion parameters. Prices are in experimental currency units, and the notes describe the variables but do not consistently state units.",146 "units_stated_in_notes": false,147 "standard_errors_description": "none"148 },149 "figures": {150 "uncertainty_shown": "no"151 },152 "conclusion": {153 "bounded_claims": false,154 "policy_implications": false,155 "open_questions": false,156 "restates_contribution": true157 },158 "hedging": {159 "level": "low",160 "typical_devices": [161 "'seems to arise' when stating the mechanism",162 "'quantitatively close to' theoretical predictions",163 "'consistent with' the theory"164 ]165 },166 "claim_evidence": [167 {168 "claim": "The collateralizeable asset trades at a higher price than the identical noncollateralizeable asset, a significant deviation from the Law of One Price",169 "evidence_type": "table",170 "evidence_ref": "Tables VII, VIII; Figure 2"171 },172 {173 "claim": "Observed prices and spread are not statistically different from the model's predictions",174 "evidence_type": "table",175 "evidence_ref": "Table VIII"176 },177 {178 "claim": "Most buyers borrow the maximum and are collateral constrained, consistent with the theoretical mechanism",179 "evidence_type": "table",180 "evidence_ref": "Tables X, XI, XIII; Figure 3"181 },182 {183 "claim": "Final holdings match the theory: high-valuation agents hold the collateralized asset but share the other, so the allocation is not Pareto efficient",184 "evidence_type": "table",185 "evidence_ref": "Tables XV, XVI"186 },187 {188 "claim": "Prices, spread and constrained shares converge toward the collateral equilibrium across rounds",189 "evidence_type": "table",190 "evidence_ref": "Tables XVII, XVIII; Figures 5-8"191 },192 {193 "claim": "Attempts to arbitrage the price difference decline as the experiment progresses",194 "evidence_type": "table",195 "evidence_ref": "Table XIX"196 },197 {198 "claim": "In the model, collateral value raises the price of the leverageable asset, and the spread depends on risk aversion",199 "evidence_type": "equation_or_proof",200 "evidence_ref": "Section I; Tables II, III"201 }202 ],203 "structural_summary": "The paper motivates the question with the crisis and the theoretical literature on collateral value. It then builds a lab-implementable general equilibrium model with two identical assets, only one of which can serve as collateral. Next it describes the experimental design and procedures. Results begin by calibrating the theoretical benchmark to elicited risk aversion, then test prices, borrowing, constraint status, allocations and convergence across rounds, using nonparametric tests against the model's predictions. The conclusion restates the first-of-its-kind contribution and summarizes the findings.",204 "writing_profile_keywords": [205 "laboratory experiment",206 "theory-testing",207 "Law of One Price",208 "collateral value",209 "nonparametric tests",210 "convergence to equilibrium",211 "double auction"212 ],213 "confidence": 0.85,214 "notes": "Section II (experiment design) is mapped to empirical_design. No explicit contribution paragraph is visible in the intro excerpt; the conclusion claims to be the first lab study. 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