Recent Developments in Bayesian Econometrics and Their Applications
Description
The original contributions on Bayesian econometrics gathered in this book pay tribute to Sune Karlsson, celebrating his significant work in time series econometrics and its applications in macroeconomics and finance. The volume consists of both methodological and empirical studies by leading experts in the field, with particular attention paid to Bayesian vector autoregressive (VAR) models and forecasting. It addresses forecasting with Bayesian VARs as a research field, mixed-frequency and high-dimensional Bayesian VARs, various forms of Bayesian VARs with stochastic volatility, forecast combination, analysis of time-varying parameter models in the frequency domain, and portfolio analysis in a Bayesian framework. Presenting cutting-edge research and providing valuable insights into the field of Bayesian econometrics, the book will appeal to researchers, practitioners in the banking sector, and government authorities.
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Persons
Stepan Mazur is an Associate Professor in Statistics at the School of Business, Örebro University, Sweden. He holds a PhD in Economics from European University Viadrina Frankfurt (Oder) and previously worked as a PostDoc at Lund University and Aarhus University. He has also been a Visiting Assistant Professor in Statistics at Linnaeus University. His research focuses on multivariate statistics with applications in macro- and financial economics.
Pär Österholm is a Professor of Economics at the School of Business, Örebro University, Sweden. He holds a PhD in Economics from Uppsala University and previously was a Division Head at the National Institute of Economic Research. He has also been a Visiting Researcher at the Board of Governors of the Federal Reserve System and the International Monetary Fund, a Senior Economist at Sveriges Riksbank and the National Institute of Economic Research, and a member of the Swedish Fiscal Policy Council. His research interests include macro-finance, forecasting and monetary policy.
Content
- Forecasting with Bayesian Vector Autoregressions Revisited.- Large Bayesian Tensor VARs with Stochastic Volatility.- Measuring Sub-Regional Economic Activity: Missing Frequencies and Missing Data.- VAR Models with Fat Tails and Dynamic Asymmetry.- International Transmission of Macroeconomic Uncertainty in Small.- Modeling Local Predictive Ability using Power-Transformed Gaussian Processes.- Spectral Domain Likelihoods for Bayesian Inference in Time-Varying Parameter Models.- Bayesian Regularization of the Tangency Portfolio.- Predictive Decision Synthesis for Portfolios: Betting on Better Models.