Notice bibliographique
Résumé
Citation (2014), "List of Contributors", Essays in Honor of Peter C. B. Phillips (Advances in Econometrics, Vol. 33), Emerald Group Publishing Limited, Bingley, pp. xiii-xvi. https://doi.org/10.1108/S0731-905320140000033025 Publisher: Emerald Group Publishing Limited Copyright © 2014 Emerald Group Publishing Limited Badi H. Baltagi Department of Economics and Center for Policy Research, Syracuse University, Syracuse, NY, USA; Department of Economics, Leicester University, Leicester, UK Yong Bao Department of Economics, Purdue University, West Lafayette, IN, USA Brendan K. Beare Department of Economics, University of California – San Diego, La Jolla, CA, USA Yoosoon Chang Department of Economics, Indiana University, Bloomington, IN, USA John Chao Department of Economics, University of Maryland, College Park, MD, USA Jin Seo Cho School of Economics, Yonsei University, Seoul, South Korea Thomas B. Fomby Department of Economics and Richard B. Johnson Center for Economic Studies, Southern Methodist University, Dallas, TX, USA Jiti Gao Department of Econometrics and Business Statistics, Monash University, Melbourne, Australia Eric Ghysels Department of Economics and Department of Finance, University of North Carolina – Chapel Hill, Chapel Hill, NC, USA Ryan Greenaway-McGrevy Department of Economics, University of Auckland, Auckland, New Zealand Chirok Han Department of Economics, Korea University, Seoul, South Korea Bruce E. Hansen Department of Economics, University of Wisconsin, Madison, WI, USA Javier Hidalgo Department of Economics, London School of Economics, London, UK Cheng Hsiao Department of Economics, University of Southern California, Los Angeles, CA, USA; WISE, Xiamen University, Xiamen, China; Department of Quantitative Finance, National Tsinghua University, Hsinchu Liang Hu Department of Economics, Wayne State University, Detroit, MI, USA Chihwa Kao Department of Economics, Center for Policy Research, Syracuse University, Syracuse, NY, USA Myungsup Kim Department of Economics, University of North Texas, Denton, TX, USA Maxwell King Department of Econometrics and Business Statistics, Monash University, Melbourne, Australia Jan F. Kiviet Division of Economics, Nanyang Technological University, Singapore; Republic of Singapore and University of Amsterdam, Amsterdam, The Netherlands Yong Li Hanqing Advanced Institute of Economics and Finance, Renmin University of China, Beijing, China Long Liu Department of Economics, College of Business, University of Texas at San Antonio, San Antonio, TX, USA Jungyoon Lee Department of Economics, New College of the Humanities, London, UK Esfandiar Maasoumi Department of Economics, Emory University, Atlanta, GA, USA Alex Maynard Department of Economics, University of Guelph, Guelph, Canada J. Isaac Miller Department of Economics, University of Missouri, Columbia, MO, USA Jerzy Niemczyk European Central Bank, Frankfurt, Germany Joon Y. Park Department of Economics, Indiana University, Bloomington, IN, USA Melinda Pitts Federal Reserve Bank of Atlanta, Atlanta, GA, USA Dongmeng Ren Department of Economics, University of Guelph, Guelph, Canada Yongcheol Shin Department of Economics and Related Studies, University of York, York, UK Kyungchul Song Vancouver School of Economics, University of British Columbia, Vancouver, Canada Donggyu Sul Department of Economics, University of Texas at Dallas, Richardson, TX, USA Yixiao Sun Department of Economics, University of California – San Diego, La Jolla, CA, USA Purevdorj Tuvaandorj Department of Economics, McGill University, CIREQ, CIRANO, Montreal, Canada Aman Ullah Department of Economics, University of California – Riverside, Riverside, CA, USA Igor Vaynman Department of Economics, University of California – San Diego, La Jolla, CA, USA Chi Wan Department of Accounting and Finance, University of Massachusetts, Boston, MA, USA Halbert White Department of Economics, University of California – San Diego, La Jolla, CA, USA Ke Wu Department of Economics, Emory University, Atlanta, GA, USA Zhijie Xiao Department of Economics, Boston College, Chestnut Hill, MA, USA Jun Yu School of Economics and Lee Kong Chian School of Business, Singapore Management University, Singapore, Republic of Singapore Tao Zeng Economics and Management School, Wuhan University, Wuhan, China Ru Zhang Department of Economics, University of California – Riverside, Riverside, CA, USA Victoria Zinde-Walsh Department of Economics, McGill University, CIREQ, CIRANO, Montreal, Canada Book Chapters Essays in Honor of Peter C. B. Phillips Advances in Econometrics Essays in Honor of Peter C. B. Phillips Copyright Page Dedication List of Contributors Introduction Asymptotic Moments of Autoregressive Estimators with a Near Unit Root and Minimax Risk Fixed-smoothing Asymptotics and Asymptotic F and t Tests in the Presence of Strong Autocorrelation Moment Approximation for Least-Squares Estimator in First-Order Regression Models with Unit Root and Nonnormal Errors On the Size Distortion from Linearly Interpolating Low-frequency Series for Cointegration Tests Testing for Cointegration in Markov Switching Error Correction Models Specification Testing in Parametric Trending Models with Unknown Errors Panel Macroeconometric Modeling ☆ This paper is dedicated to P. C. B. Phillips for his creative and lasting contributions to econometrics. Mean Average Estimation of Dynamic Panel Models with Nonstationary Initial Condition Efficient Estimation and Inference for Difference-In-Difference Regressions with Persistent Errors A CUSUM Test for Common Trends in Large Heterogeneous Panels Test of Hypotheses in a Time Trend Panel Data Model with Serially Correlated Error Component Disturbances Limit Theory and Inference About Conditional Distributions On the Limiting and Empirical Distributions of IV Estimators When Some of the Instruments are Actually Endogenous Testing the Equality of Two Positive-Definite Matrices with Application to Information Matrix Testing ☆ A glossary of notation and the program codes written in GAUSS for our simulations are available at: http://web.yonsei.ac.kr/jinseocho/research.htm Minimax Estimation of Nonregular Parameters and Discontinuity in Minimax Risk The Gap between the Conditional Wage Distributions of Incumbents and the Newly Hired Employees: Decomposition and Uniform Ordering Deviance Information Criterion for Comparing VAR Models Stable Limit Theory for the Variance Targeting Estimator Assessing the Power of Long-Horizon Predictive Tests in Models of Bull and Bear Markets Idiosyncratic Volatility, Expected Windfall, and the Cross-Section of Stock Returns
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,003 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,025 | 0,008 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».