Topics in identification, limited dependent variables, partial observability, experimentation, and flexible modeling. Part A
Título:
Topics in identification, limited dependent variables, partial observability, experimentation, and flexible modeling. Part A
ISBN:
9781789732436
9781789732412
PRODUCTION_INFO:
Bingley, U.K. : Emerald Publishing Limited, 2019.
©2019
Descrição Física:
1 online resource (xi, 318 pages).
Série:
Advances in econometrics ; 40, Part A
Advances in econometrics ; v. 40, pt. A.
Nota Geral:
Includes index.
Conteúdo:
Foreword / Ivan Jeliazkov and Justin L. Tobias -- 1. An interview with Dale Poirier / Ivan Jeliazkov, Dale J. Poirier and Justin L. Tobias -- 2. Macroeconomic nowcasting using Google probabilities / Gary Koop and Luca Onorante -- 3. Sentiment-based overlapping community discovery / Fulya Ozcan -- 4. Violence in the decond intifada : a demonstration of Bayesian generative cognitive modeling / Percy Mistry and Michael D. Lee -- 5. A Bayesian model for activation and connectivity in task-related fMRI data / Zhe Yu, Raquel Prado, Steve C. Cramer, Erin B. Quinlan and Hernando Ombao -- 6. Robust estimation of ARMA models with near root cancellation / Timothy Cogley and Richard Startz -- 7. A simple efficient moment-based estimator for the stochastic volatility model / Md. Nazmul Ahsan and Jean-Marie Dufour -- 8. A new approach to modeling endogenous gain learning / Eric Gaus and Srikanth Ramamurthy -- 9. How sensitive are VAR forecasts to prior hyperparameters? an automated sensitivity analysis / Joshua C.C. Chan, Liana Jacobi and Dan Zhu -- 10. Stein-like shrinkage estimation of panel data models with common correlated effects / Bai Huang, Tae-Hwy Lee and Aman Ullah -- 11. Predictive testing for granger causality via posterior simulation and cross validation / Gary J. Cornwall, Jeffrey A. Mills, Beau A. Sauley and Huibin Weng -- 12. New evidence on the effect of compulsory schooling laws / Theodore F. Figinski, Alicia Lloro and Phillip Li.
Resumo:
Volume 40 in the Advances in Econometrics series features twenty-three chapters that are split thematically into two parts. Part A presents novel contributions to the analysis of time series and panel data with applications in macroeconomics, finance, cognitive science and psychology, neuroscience, and labor economics. Part B examines innovations in stochastic frontier analysis, nonparametric and semiparametric modeling and estimation, A/B experiments, big-data analysis, and quantile regression. Individual chapters, written by both distinguished researchers and promising young scholars, cover many important topics in statistical and econometric theory and practice. Papers primarily, though not exclusively, adopt Bayesian methods for estimation and inference, although researchers of all persuasions should find considerable interest in the chapters contained in this work. The volume was prepared to honor the career and research contributions of Professor Dale J. Poirier. For researchers in econometrics, this volume includes the most up-to-date research across a wide range of topics.
LANGUAGE:
Inglês