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They explain how estimates are produced (FM two-pass, GMM) and define fit measures such as the pseudo-R2 and cross-sectional R2. Test p-values are reported.",173 "units_stated_in_notes": false,174 "standard_errors_description": "mixed"175 },176 "figures": {177 "uncertainty_shown": "mixed"178 },179 "conclusion": {180 "bounded_claims": true,181 "policy_implications": false,182 "open_questions": true,183 "restates_contribution": true184 },185 "hedging": {186 "level": "moderate",187 "typical_devices": [188 "cannot reject",189 "might seem odd",190 "typically",191 "conditional statements on data quality and T versus N"192 ]193 },194 "claim_evidence": [195 {196 "claim": "Identification test cannot reject unidentified risk premia for five consumption measures",197 "evidence_type": "table",198 "evidence_ref": "Table I"199 },200 {201 "claim": "FM t-test is unreliable under near-constant betas in calibrated simulations",202 "evidence_type": "figure",203 "evidence_ref": "Figure 3"204 },205 {206 "claim": "GRS-FAR 95% confidence sets for consumption risk premia are unbounded",207 "evidence_type": "figure",208 "evidence_ref": "Figure 5"209 },210 {211 "claim": "With larger T, confidence sets move from unbounded to bounded to empty under misspecification",212 "evidence_type": "figure",213 "evidence_ref": "Figures 6-7; Table V"214 },215 {216 "claim": "GMM-AR gives unbounded confidence sets for relative risk aversion",217 "evidence_type": "figure",218 "evidence_ref": "Figure 9; Table VI"219 },220 {221 "claim": "GRS-FAR has exact F distribution regardless of identification",222 "evidence_type": "equation_or_proof",223 "evidence_ref": "Section I.D"224 }225 ],226 "structural_summary": "Opens with the puzzle that different consumption measures yield conflicting asset pricing results and places this within the weak-identification literature. Proposes a rank test and the GRS-FAR test, then applies them to the Kroencke data, previewing unbounded confidence sets and their reconciling role. Section I develops identification conditions and the tests for a single factor, alternating simulations with applications. Section II covers multifactor models, larger T and misspecification. Section III extends the analysis to nonlinear SDFs via GMM-AR. The conclusion restates the findings, gives practitioner guidance and points to extensions.",227 "writing_profile_keywords": [228 "weak identification",229 "robust inference",230 "Monte Carlo calibration",231 "confidence set inversion",232 "econometric method applied to asset pricing",233 "GRS test"234 ],235 "confidence": 0.8,236 "notes": "The method is an econometric testing procedure, so primary_method is coded as other. A placeholder move was inadvertently entered for paragraph 6; the intended move there is contribution_statement only. 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