1{2 "validation_errors": [],3 "repairs": [4 "dropped abstract_moves.interpretation_note_placeholder"5 ],6 "doc_id": "jof_12968",7 "ontology_version": "1.0",8 "prompt_version": "1.0",9 "model": "claude-opus-5-5",10 "effort": "medium",11 "annotated_at": "2026-11-03T23:26:54+00:00",12 "source_sha256": "f791853b7937f75fdad1aa0b5524af359009f2764458d3424c3a2db7d258a9fe",13 "parser": "pymupdf-jof-heuristics-1.3",14 "payload_chars": 25492,15 "usage": {16 "input": 8375,17 "output": 2579,18 "cache_read": 3968,19 "cache_write": 020 },21 "cost_usd": 0.085874,22 "request_id": "req_011Cggr3AcwbXweLSSq79Z7b",23 "annotation": {24 "genre": "empirical",25 "subfield": "household_finance",26 "subfield_secondary": "macro_finance",27 "primary_method": "instrumental_variables",28 "identification": {29 "estimand": "Marginal propensity to consume out of unrealized capital gains and out of dividend income, estimated separately by wealth group",30 "strategy": "Simulated IV: actual changes in capital gains and dividends are instrumented with passive gains and dividends computed from lagged portfolio weights. Regressions are in first differences, run by wealth group, and exclude holdings in the household's own industry.",31 "key_assumptions": [32 "Lagged portfolio weights are not determined by future shocks that jointly drive returns and consumption",33 "Portfolios are sticky enough that passive returns strongly predict actual gains (relevance)",34 "Consumption imputed from the budget constraint is measured without systematic bias correlated with returns"35 ],36 "threats_addressed": [37 "Endogenous portfolio rebalancing (e.g., liquidation for expenditure shocks)",38 "Time-invariant household heterogeneity",39 "Correlation between own-industry stock returns and labor income",40 "Measurement error in capital gains and imputed consumption",41 "Correlated changes in housing and other financial wealth",42 "Common income shocks (same-employer comparisons)",43 "Realized versus unrealized gains"44 ],45 "causal_language_strength": 4,46 "uses_causal_claim": true47 },48 "abstract_moves": {49 "question": {50 "present": true,51 "sentence_index": 052 },53 "gap": {54 "present": false,55 "sentence_index": -156 },57 "method": {58 "present": true,59 "sentence_index": 160 },61 "results": {62 "present": true,63 "sentence_index": 264 },65 "magnitude": {66 "present": true,67 "sentence_index": 268 },69 "contribution": {70 "present": false,71 "sentence_index": -172 }73 },74 "introduction": {75 "moves": [76 {77 "paragraph_index": 0,78 "move": "motivation"79 },80 {81 "paragraph_index": 0,82 "move": "policy_or_broader_implication"83 },84 {85 "paragraph_index": 0,86 "move": "literature_gap"87 },88 {89 "paragraph_index": 1,90 "move": "identification_defense"91 },92 {93 "paragraph_index": 2,94 "move": "preview_of_approach"95 },96 {97 "paragraph_index": 2,98 "move": "identification_defense"99 },100 {101 "paragraph_index": 3,102 "move": "preview_of_results"103 },104 {105 "paragraph_index": 3,106 "move": "robustness_mention"107 },108 {109 "paragraph_index": 3,110 "move": "mechanism_or_theory_sketch"111 },112 {113 "paragraph_index": 4,114 "move": "related_literature_positioning"115 },116 {117 "paragraph_index": 5,118 "move": "related_literature_positioning"119 },120 {121 "paragraph_index": 6,122 "move": "contribution_statement"123 },124 {125 "paragraph_index": 6,126 "move": "roadmap"127 }128 ],129 "contribution_paragraph_index": 6,130 "contribution_types": [131 "new_evidence",132 "new_identification",133 "new_data_or_measure"134 ],135 "roadmap_present": true,136 "literature_positioning_location": "both"137 },138 "section_roles": [139 {140 "idx": 0,141 "role": "introduction"142 },143 {144 "idx": 1,145 "role": "data"146 },147 {148 "idx": 2,149 "role": "empirical_design"150 },151 {152 "idx": 3,153 "role": "results"154 },155 {156 "idx": 4,157 "role": "robustness"158 },159 {160 "idx": 5,161 "role": "results"162 },163 {164 "idx": 6,165 "role": "robustness"166 },167 {168 "idx": 7,169 "role": "conclusion"170 },171 {172 "idx": 8,173 "role": "appendix"174 },175 {176 "idx": 9,177 "role": "appendix"178 },179 {180 "idx": 10,181 "role": "appendix"182 },183 {184 "idx": 11,185 "role": "appendix"186 }187 ],188 "results_presentation": {189 "economic_significance_discussed": true,190 "statistical_significance_language": "unclear",191 "magnitude_statements_in_intro": true192 },193 "robustness": {194 "location": "main_text_section",195 "types": [196 "alternative_specification",197 "subsample",198 "alternative_measure",199 "other"200 ]201 },202 "tables": {203 "convention_notes": "Table notes write out the regression equation and state the instruments (passive capital gains and passive dividends) and the controls. Results are reported separately by wealth group, with each cell often a separate regression. Monetary units (1,000 SEK) are given in the summary statistics note. The OLS table is placed before the IV table so the two can be compared.",204 "units_stated_in_notes": true,205 "standard_errors_description": "unclear"206 },207 "figures": {208 "uncertainty_shown": "no"209 },210 "conclusion": {211 "bounded_claims": true,212 "policy_implications": false,213 "open_questions": false,214 "restates_contribution": true215 },216 "hedging": {217 "level": "moderate",218 "typical_devices": [219 "'consistent with' framing for mechanisms",220 "'suggests' when stating broader implications",221 "noting that high-MPC households own a small share of stockholdings"222 ]223 },224 "claim_evidence": [225 {226 "claim": "MPC out of unrealized capital gains is about 3% for the top 30% of the wealth distribution and about 23% for the bottom half",227 "evidence_type": "table",228 "evidence_ref": "Table III"229 },230 {231 "claim": "MPC out of dividends exceeds MPC out of capital gains in all wealth groups",232 "evidence_type": "table",233 "evidence_ref": "Table III"234 },235 {236 "claim": "Estimates are robust to controlling for realized capital gains",237 "evidence_type": "table",238 "evidence_ref": "Table V"239 },240 {241 "claim": "Measurement error does not drive the MPC estimates",242 "evidence_type": "table",243 "evidence_ref": "Tables VI-VII"244 },245 {246 "claim": "MPC heterogeneity is driven by liquid wealth relative to income rather than wealth level per se",247 "evidence_type": "table",248 "evidence_ref": "Table VIII"249 },250 {251 "claim": "Among unconstrained households, older households have a higher MPC out of capital gains",252 "evidence_type": "table",253 "evidence_ref": "Table IX"254 },255 {256 "claim": "Results are not driven by other wealth changes or common employer income shocks",257 "evidence_type": "table",258 "evidence_ref": "Tables X-XII"259 },260 {261 "claim": "Prior estimates of MPC out of stock wealth range from 0% to 10%",262 "evidence_type": "prior_literature",263 "evidence_ref": "Introduction paragraph 6; Table A.2"264 }265 ],266 "structural_summary": "The introduction opens with the macro and policy relevance of stock wealth effects, then names the gap in causal estimates and the specific identification challenges. It lays out a layered defense (first differences, wealth-group splits, own-industry exclusion, simulated IV from lagged weights) before previewing headline MPC magnitudes and mechanism links to buffer-stock theory. Literature positioning (dividend demand, MPC, wealth effects) and a roadmap close the introduction. The body moves from data and design to OLS-versus-IV main results, then a long measurement-error section combining theory and auxiliary brokerage data. Heterogeneity tests provide mechanism evidence and robustness tables follow. The conclusion restates the two advantages and three findings, framed as consistent with theory.",267 "writing_profile_keywords": [268 "administrative data",269 "simulated instrument",270 "marginal propensity to consume",271 "wealth heterogeneity",272 "measurement error analysis",273 "buffer stock interpretation",274 "mental accounting of dividends"275 ],276 "confidence": 0.8,277 "notes": "The abstract_moves object contains an extra key ('interpretation_note_placeholder') that is not in the schema; with additionalProperties set to false this output will fail validation and the key should be removed. The abstract's final sentence is an interpretation and was not coded as a contribution. The standard-error type is not visible in the excerpts. Section idx 5 (Heterogeneity) is pre-labelled robustness but functions as mechanism results. The Measurement Error section is tagged as data by the rule but serves a robustness role. Appendix sections (idx 8–11) are table/appendix headings."278 },279 "deterministic_checks": {280 "roadmap_regex": true,281 "contribution_regex_in_intro": true,282 "magnitude_in_abstract": true,283 "abstract_n_sentences": 5,284 "intro_n_paragraphs": 7,285 "intro_n_words": 1166,286 "causal_words_in_abstract": 1,287 "hedge_words_in_abstract": 1,288 "stars_mentioned": false,289 "clustered_se_mentioned": false,290 "internet_appendix_mentioned": true,291 "section_roles_rule": {292 "0": "introduction",293 "1": "data",294 "2": "empirical_design",295 "3": "results",296 "4": "data",297 "5": "robustness",298 "6": "robustness",299 "7": "conclusion",300 "8": "literature",301 "9": "data",302 "10": "other",303 "11": "other"304 }305 },306 "schema_valid": true,307 "code_version": "87c73cd-dirty"308}