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Record W583086315

Panel data : theory and applications

2004· book· en· W583086315 on OpenAlexaboutno aff
Badi H. Baltagi

Bibliographic record

VenuePhysica eBooks · 2004
Typebook
Languageen
FieldEconomics, Econometrics and Finance
TopicFirm Innovation and Growth
Canadian institutionsnot available
Fundersnot available
KeywordsPanel dataEconometricsRandom effects modelHeteroscedasticityEstimatorEconomicsMathematicsStatistics
DOInot available

Abstract

fetched live from OpenAlex

B.H. Baltagi: Introduction.- J.H. Abbring, G.J. van den Berg: Analyzing the effect of dynamically assigned treatments using duration models, binary treatment models, and panel data models.- W. Greene: Convenient estimators for the panel probit model: Further results.- P. Contoyannis, A.M. Jones, N. Rice: Simulation-based inference in dynamic panel probit models: An application to health.- S. Karlsson, J. Skoglund: Maximum-likelihood based inference in the two-way random effects model with serially correlated time effects.- M.J.G. Bun: Testing poolability in a system of dynamic regressions with nonspherical disturbances.- B.H. Baltagi, G. Bresson, A. Pirotte: Tobin q: Forecast performance for hierarchical Bayes, shrinkage, heterogeneous and homogeneous panel data estimators.- C. Driver, K. Imai, P. Temple, G. Urga: The effect of uncertainty on UK investment authorisation: Homogeneous vs. heterogeneous estimators.- D. Hum, W. Simpson: Reinterpreting the performance of immigrant wages from panel data.- M. Gillman, M. Harris, L. Matyas: Inflation and growth: Explaining a negative effect.- L. Orea, S. Kumbhakar: Efficiency measurement using a latent class stochastic frontier model.- S. Kumbhakar: Productivity and technical change: Measurement and testing.- R. Chakir, A. Bousquet, N. Ladoux: Modeling corner solutions with panel data: Application to the industrial energy demand in France.- F. Peracchi: The European Community Household Panel: A review.- T.J. Knieser, Qi Li: Nonlinearity in dynamic adjustment: Semiparametric estimation of panel labor supply.- K. Hadri, C. Guermat, J. Whittaker: Estimation of technical inefficiency effects using panel data and doubly heteroscedastic stochastic production frontiers.- P. Egger, M. Pfaffermayr: The proper panel econometric specification of the gravity equation: A three-way model with bilateral interaction effects.- D. Parent: Employer-supported training in Canada and its impact on mobility and wages.- Ho Tsung-wu: A panel cointegration approach to the investment-saving correlation.- A. Aakvik: Estimating the employment effects of education for disabled workers in Norway.- B. Fitzenberger, C. Kurz: New insights on earnings trends across skill groups and industries in West Germany.

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)0.000
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.495
Threshold uncertainty score0.943

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.074
GPT teacher head0.239
Teacher spread0.166 · 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
GenreOther

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

Citations19
Published2004
Admission routes1
Has abstractyes

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