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Within-dealer variation comes from dealer fixed effects and state-specific centrality based on tax-segmented state markets. Additional tests address alternative channels: adverse selection, bond riskiness and inventory.",28 "key_assumptions": [29 "Conditional on controls, centrality is not a proxy for dealer size or unobserved dealer quality.",30 "Central dealers do not systematically intermediate a priori riskier or more illiquid bonds.",31 "State tax segmentation creates local submarkets in which state-specific centrality varies independently of aggregate dealer attributes."32 ],33 "threats_addressed": [34 "dealer size / scale effects",35 "bond riskiness and illiquidity selection",36 "inventory risk channel",37 "asymmetric information / adverse selection",38 "time-invariant dealer heterogeneity (dealer fixed effects)"39 ],40 "causal_language_strength": 2,41 "uses_causal_claim": false42 },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": 259 },60 "magnitude": {61 "present": true,62 "sentence_index": 263 },64 "contribution": {65 "present": true,66 "sentence_index": 467 }68 },69 "introduction": {70 "moves": [71 {72 "paragraph_index": 0,73 "move": "motivation"74 },75 {76 "paragraph_index": 0,77 "move": "literature_gap"78 },79 {80 "paragraph_index": 0,81 "move": "preview_of_approach"82 },83 {84 "paragraph_index": 1,85 "move": "preview_of_results"86 },87 {88 "paragraph_index": 1,89 "move": "mechanism_or_theory_sketch"90 },91 {92 "paragraph_index": 2,93 "move": "other"94 },95 {96 "paragraph_index": 3,97 "move": "identification_defense"98 },99 {100 "paragraph_index": 3,101 "move": "preview_of_results"102 },103 {104 "paragraph_index": 4,105 "move": "robustness_mention"106 },107 {108 "paragraph_index": 4,109 "move": "identification_defense"110 },111 {112 "paragraph_index": 5,113 "move": "preview_of_results"114 },115 {116 "paragraph_index": 5,117 "move": "related_literature_positioning"118 },119 {120 "paragraph_index": 5,121 "move": "contribution_statement"122 }123 ],124 "contribution_paragraph_index": 5,125 "contribution_types": [126 "new_evidence",127 "new_data_or_measure"128 ],129 "roadmap_present": false,130 "literature_positioning_location": "both"131 },132 "section_roles": [133 {134 "idx": 0,135 "role": "introduction"136 },137 {138 "idx": 1,139 "role": "literature"140 },141 {142 "idx": 2,143 "role": "data"144 },145 {146 "idx": 3,147 "role": "results"148 },149 {150 "idx": 4,151 "role": "results"152 },153 {154 "idx": 5,155 "role": "results"156 },157 {158 "idx": 6,159 "role": "results"160 },161 {162 "idx": 7,163 "role": "robustness"164 },165 {166 "idx": 8,167 "role": "conclusion"168 },169 {170 "idx": 9,171 "role": "appendix"172 },173 {174 "idx": 10,175 "role": "appendix"176 },177 {178 "idx": 11,179 "role": "appendix"180 },181 {182 "idx": 12,183 "role": "appendix"184 }185 ],186 "results_presentation": {187 "economic_significance_discussed": true,188 "statistical_significance_language": "unclear",189 "magnitude_statements_in_intro": true190 },191 "robustness": {192 "location": "main_text_section",193 "types": [194 "alternative_specification",195 "subsample",196 "alternative_measure",197 "falsification",198 "other"199 ]200 },201 "tables": {202 "convention_notes": "Long descriptive table notes state the estimator (panel OLS with state and month fixed effects, Probit, Tobit), point to Appendix D for control definitions, define the centrality index as a first principal component, and report markups in percent. Tables progress from univariate tier sorts to multivariate regressions and then subsample tests.",203 "units_stated_in_notes": true,204 "standard_errors_description": "unclear"205 },206 "figures": {207 "uncertainty_shown": "no"208 },209 "conclusion": {210 "bounded_claims": false,211 "policy_implications": true,212 "open_questions": false,213 "restates_contribution": true214 },215 "hedging": {216 "level": "moderate",217 "typical_devices": [218 "'consistent with' theory predictions",219 "'suggests that'",220 "framing of results as tests of hypotheses derived from models"221 ]222 },223 "claim_evidence": [224 {225 "claim": "The interdealer network has a stable core-periphery structure with a small set of hubs and thousands of peripheral dealers.",226 "evidence_type": "figure",227 "evidence_ref": "Figure 1, Figure 2, Table II"228 },229 {230 "claim": "Central dealers charge investors higher round-trip markups than peripheral dealers.",231 "evidence_type": "table",232 "evidence_ref": "Table IV, Table V"233 },234 {235 "claim": "Central dealers sell more directly to end customers and are associated with shorter intermediation chains.",236 "evidence_type": "table",237 "evidence_ref": "Table VI, Table VII"238 },239 {240 "claim": "Central dealers prearrange fewer trades and unwind inventory faster, implying more immediacy.",241 "evidence_type": "table",242 "evidence_ref": "Table VIII, Table XIII"243 },244 {245 "claim": "Investors turn more to central dealers in stress times.",246 "evidence_type": "table",247 "evidence_ref": "Table IX"248 },249 {250 "claim": "The adverse-selection component of markups is lower for central dealers.",251 "evidence_type": "table",252 "evidence_ref": "Table X"253 },254 {255 "claim": "State-specific centrality affects markups more than aggregate centrality and adds explanatory power beyond dealer fixed effects.",256 "evidence_type": "table",257 "evidence_ref": "Table XIV"258 }259 ],260 "structural_summary": "The introduction motivates the role of dealers in OTC markets and notes how little empirical work exists for lack of data. It previews the regulatory data, the main results, a state-segmentation identification refinement, tests ruling out alternative explanations, and the contribution relative to the literature. A separate section then derives hypotheses from network models. The paper next describes the data and the round-trip chain construction. Successive results sections cover network structure, the centrality premium in markups, search efficiency, and execution speed and stress-time trading. A section on alternative theories (adverse selection, riskiness, inventory, local information, subsamples) follows. The conclusion restates the cost–speed trade-off and the systemic role of central dealers.",261 "writing_profile_keywords": [262 "hypothesis-driven empirics",263 "theory-motivated tests",264 "network centrality",265 "regulatory audit trail data",266 "alternative explanations section",267 "OTC market microstructure",268 "descriptive-then-multivariate tables"269 ],270 "confidence": 0.8,271 "notes": "Section VII is labelled 'theory' by the role rule but functions as robustness/alternative explanations, so it was assigned robustness. Standard error treatment and significance notation are not visible in the excerpts. 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