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Record W1527863737

Wealth Inequality, Stock Market Participation, and the Equity Premium

2012· article· en· W1527863737 on OpenAlexaff
Jack Favilukis

Bibliographic record

VenueSSRN Electronic Journal · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic theories and models
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEconomicsStock marketInequalityEquity premium puzzleCounterfactual thinkingEquity (law)Precautionary savingsIncomplete marketsMonetary economicsLabour economicsNational wealthConsumption (sociology)Economic inequalityInterest rateRisk premiumMarket liquidityFinanceMicroeconomics
DOInot available

Abstract

fetched live from OpenAlex

The last 30 years saw substantial increases in wealth inequality and in stock market participation, smaller increases in consumption inequality and the fraction of indebted households, a decline in interest rates and in the expected equity premium, as well as a prolonged stock market boom. Understanding the causes of these trends is crucial for many questions in finance and economics. In an incomplete markets, overlapping generations model we show that these trends can be jointly explained by the observed rise in wage inequality, as well as a decrease in participation costs and a loosening of borrowing constraints. Once we account for these changes, we show that the observed pattern of stock prices played a major role in increasing wealth inequality because stockholders, who tend to be wealthy, benefit most from a bull market. Crucially, these phenomena must be considered jointly; studying one independently leads to counterfactual predictions about others. For example, a loosening of credit standards is expected to raise, rather than lower interest rates through decreased precautionary savings as well as vastly increase the fraction of households in debt; an increase in labor inequality is (somewhat counterintuitively) expected to lower rather than raise wealth inequality, again through precautionary savings; increased stock market participation should also lower wealth inequality.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.105
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.039
GPT teacher head0.282
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2012
Admission routes1
Has abstractyes

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