{"text": "{\"genre\":\"empirical\",\"subfield\":\"asset_pricing\",\"subfield_secondary\":\"market_microstructure; experimental finance\",\"primary_method\":\"survey_or_experiment\",\"identification\":{\"estimand\":\"Treatment effects of exogenous information-network structure (none, complete, circle, core-periphery) on signal acquisition, volume, liquidity, information aggregation, price informativeness and profits\",\"strategy\":\"Between-session laboratory treatments that randomly vary the information network, analyzed with ordered probit and OLS regressions on treatment dummies, using standard errors clustered at subject level\",\"key_assumptions\":[\"Network structure is exogenous and assigned by design\",\"Information sharing is automatic, perfect and nonstrategic\",\"Subjects in different sessions are comparable\"],\"threats_addressed\":[\"Endogenous network formation (removed by imposing exogenous networks)\",\"Within-subject dependence (handled by clustering)\"],\"causal_language_strength\":4,\"uses_causal_claim\":true},\"abstract_moves\":{\"question\":{\"present\":true,\"sentence_index\":0},\"gap\":{\"present\":false,\"sentence_index\":-1},\"method\":{\"present\":true,\"sentence_index\":0},\"results\":{\"present\":true,\"sentence_index\":1},\"magnitude\":{\"present\":false,\"sentence_index\":-1},\"contribution\":{\"present\":false,\"sentence_index\":-1}},\"introduction\":{\"moves\":[{\"paragraph_index\":0,\"move\":\"motivation\"},{\"paragraph_index\":0,\"move\":\"literature_gap\"},{\"paragraph_index\":1,\"move\":\"preview_of_approach\"},{\"paragraph_index\":2,\"move\":\"mechanism_or_theory_sketch\"},{\"paragraph_index\":2,\"move\":\"preview_of_results\"},{\"paragraph_index\":3,\"move\":\"preview_of_results\"},{\"paragraph_index\":4,\"move\":\"preview_of_results\"},{\"paragraph_index\":4,\"move\":\"tension_or_puzzle\"},{\"paragraph_index\":4,\"move\":\"related_literature_positioning\"}],\"contribution_paragraph_index\":1,\"contribution_types\":[\"new_evidence\"],\"roadmap_present\":false,\"literature_positioning_location\":\"inside_introduction\"},\"section_roles\":[{\"idx\":0,\"role\":\"introduction\"},{\"idx\":1,\"role\":\"empirical_design\"},{\"idx\":2,\"role\":\"results\"},{\"idx\":3,\"role\":\"other\"},{\"idx\":4,\"role\":\"conclusion\"}],\"results_presentation\":{\"economic_significance_discussed\":true,\"statistical_significance_language\":\"stars_and_tstats\",\"magnitude_statements_in_intro\":true},\"robustness\":{\"location\":\"none_seen\",\"types\":[]},\"tables\":{\"convention_notes\":\"Tables pair period-average descriptive statistics, reported with standard deviations, with regression tables. The regressions use treatment dummies against a nonnetworked baseline and include a period control. Standard errors are clustered by subject and reported in parentheses, with stars marking significance. Notes define each dependent variable precisely.\",\"units_stated_in_notes\":true,\"standard_errors_description\":\"clustered\"},\"figures\":{\"uncertainty_shown\":\"mixed\"},\"conclusion\":{\"bounded_claims\":true,\"policy_implications\":false,\"open_questions\":true,\"restates_contribution\":true},\"hedging\":{\"level\":\"moderate\",\"typical_devices\":[\"on average\",\"typically\",\"explicit design simplifications acknowledged\",\"might not be as strong\"]},\"claim_evidence\":[{\"claim\":\"Signal acquisition probability and quantity fall as a trader's number of network connections rises.\",\"evidence_type\":\"table\",\"evidence_ref\":\"Tables II, III, IV; Figure 2\"},{\"claim\":\"Information sharing raises trading volume and improves liquidity.\",\"evidence_type\":\"table\",\"evidence_ref\":\"Table V\"},{\"claim\":\"Prices aggregate more of the available information with sharing, and aggregation rises with network density.\",\"evidence_type\":\"table\",\"evidence_ref\":\"Table VI; Figures 3-4\"},{\"claim\":\"Price informativeness about the true state does not improve with social communication.\",\"evidence_type\":\"table\",\"evidence_ref\":\"Table IX; Figures 5-6\"},{\"claim\":\"Net earnings are higher under sharing because of savings on signal costs.\",\"evidence_type\":\"table\",\"evidence_ref\":\"Tables X, XIII\"},{\"claim\":\"Prices support semi-strong but not strong-form efficiency.\",\"evidence_type\":\"prior_literature\",\"evidence_ref\":\"Discussion; Page and Siemroth (2018)\"}],\"structural_summary\":\"The introduction opens with the rational-expectations literature on costly information and flags the absence of social networks as an open question. It then describes the exogenous-network setup and frames a trade-off between richer information sets and free-riding. Results are previewed sequentially: crowding out of acquisition, then liquidity, aggregation, informativeness and earnings, with a counter-to-conventional-wisdom point on forecasting quality. A design section presents the lab procedures and the four network treatments. A long results section is organized by outcome, using regressions on treatment dummies. A discussion section links the findings to market efficiency, and a short conclusion restates the findings and lists extensions.\",\"writing_profile_keywords\":[\"laboratory experiment\",\"information networks\",\"free-riding\",\"treatment comparisons\",\"price efficiency\",\"outcome-by-outcome results\"],\"confidence\":0.82,\"notes\":\"Experimental asset-market paper with no equations shown. No explicit robustness section is visible in the excerpts. An Internet Appendix exists, but its contents are not shown.\"}", "json": {"genre": "empirical", "subfield": "asset_pricing", "subfield_secondary": "market_microstructure; experimental finance", "primary_method": "survey_or_experiment", "identification": {"estimand": "Treatment effects of exogenous information-network structure (none, complete, circle, core-periphery) on signal acquisition, volume, liquidity, information aggregation, price informativeness and profits", "strategy": "Between-session laboratory treatments that randomly vary the information network, analyzed with ordered probit and OLS regressions on treatment dummies, using standard errors clustered at subject level", "key_assumptions": ["Network structure is exogenous and assigned by design", "Information sharing is automatic, perfect and nonstrategic", "Subjects in different sessions are comparable"], "threats_addressed": ["Endogenous network formation (removed by imposing exogenous networks)", "Within-subject dependence (handled by clustering)"], "causal_language_strength": 4, "uses_causal_claim": true}, "abstract_moves": {"question": {"present": true, "sentence_index": 0}, "gap": {"present": false, "sentence_index": -1}, "method": {"present": true, "sentence_index": 0}, "results": {"present": true, "sentence_index": 1}, "magnitude": {"present": false, "sentence_index": -1}, "contribution": {"present": false, "sentence_index": -1}}, "introduction": {"moves": [{"paragraph_index": 0, "move": "motivation"}, {"paragraph_index": 0, "move": "literature_gap"}, {"paragraph_index": 1, "move": "preview_of_approach"}, {"paragraph_index": 2, "move": "mechanism_or_theory_sketch"}, {"paragraph_index": 2, "move": "preview_of_results"}, {"paragraph_index": 3, "move": "preview_of_results"}, {"paragraph_index": 4, "move": "preview_of_results"}, {"paragraph_index": 4, "move": "tension_or_puzzle"}, {"paragraph_index": 4, "move": "related_literature_positioning"}], "contribution_paragraph_index": 1, "contribution_types": ["new_evidence"], "roadmap_present": false, "literature_positioning_location": "inside_introduction"}, "section_roles": [{"idx": 0, "role": "introduction"}, {"idx": 1, "role": "empirical_design"}, {"idx": 2, "role": "results"}, {"idx": 3, "role": "other"}, {"idx": 4, "role": "conclusion"}], "results_presentation": {"economic_significance_discussed": true, "statistical_significance_language": "stars_and_tstats", "magnitude_statements_in_intro": true}, "robustness": {"location": "none_seen", "types": []}, "tables": {"convention_notes": "Tables pair period-average descriptive statistics, reported with standard deviations, with regression tables. 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It then describes the exogenous-network setup and frames a trade-off between richer information sets and free-riding. Results are previewed sequentially: crowding out of acquisition, then liquidity, aggregation, informativeness and earnings, with a counter-to-conventional-wisdom point on forecasting quality. A design section presents the lab procedures and the four network treatments. A long results section is organized by outcome, using regressions on treatment dummies. A discussion section links the findings to market efficiency, and a short conclusion restates the findings and lists extensions.", "writing_profile_keywords": ["laboratory experiment", "information networks", "free-riding", "treatment comparisons", "price efficiency", "outcome-by-outcome results"], "confidence": 0.82, "notes": "Experimental asset-market paper with no equations shown. No explicit robustness section is visible in the excerpts. 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