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Record W2148117946 · doi:10.1002/jae.768

Semiparametric estimation of lifetime equivalence scales

2005· article· en· W2148117946 on OpenAlex
Krishna Pendakur

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Applied Econometrics · 2005
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomics of Agriculture and Food Markets
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsEquivalence (formal languages)EconomicsEconometricsParametric statisticsSemiparametric modelCommodityEstimationEngel curveNonparametric statisticsMathematicsStatisticsPrice index

Abstract

fetched live from OpenAlex

Abstract Pashardes ( 1991 ) and Banks et al. ( 1994 ) use parametric methods to estimate lifetime equivalence scales. Their approaches put parametric restrictions on the differences in within‐period expenditure needs across household types, the intertemporal allocation of expenditure, and the shapes of commodity demand equations. This paper puts parametric structure only on the differences in within‐period expenditure needs across household types. This implies structure on the intertemporal allocation of expenditure, but leaves the shapes of commodity demand equations unrestricted. Semiparametric methods are used to estimate within‐period and lifetime equivalence scales with Canadian expenditure data, and to test the restrictions imposed on within‐period expenditure functions. Estimated lifetime equivalence scales are similar in size to those estimated by Banks et al. ( 1994 ) and exhibit equal lifetime costs for first and second children. Copyright © 2005 John Wiley & Sons, Ltd.

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.

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)0.002
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 score0.262
Threshold uncertainty score0.929

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.210
Teacher spread0.188 · 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