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Dlm With Markov Switching And The Application In Business Cycle Analysis
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Book Synopsis DLM with Markov Switching and the Application in Business Cycle Analysis by : Yuqing Zheng (Researcher in statistics)
Download or read book DLM with Markov Switching and the Application in Business Cycle Analysis written by Yuqing Zheng (Researcher in statistics) and published by . This book was released on 2014 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Advances in Markov-Switching Models by : James D. Hamilton
Download or read book Advances in Markov-Switching Models written by James D. Hamilton and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of state-of-the-art papers on the properties of business cycles and financial analysis. The individual contributions cover new advances in Markov-switching models with applications to business cycle research and finance. The introduction surveys the existing methods and new results of the last decade. Individual chapters study features of the U. S. and European business cycles with particular focus on the role of monetary policy, oil shocks and co movements among key variables. The short-run versus long-run consequences of an economic recession are also discussed. Another area that is featured is an extensive analysis of currency crises and the possibility of bubbles or fads in stock prices. A concluding chapter offers useful new results on testing for this kind of regime-switching behaviour. Overall, the book provides a state-of-the-art over view of new directions in methods and results for estimation and inference based on the use of Markov-switching time-series analysis. A special feature of the book is that it includes an illustration of a wide range of applications based on a common methodology. It is expected that the theme of the book will be of particular interest to the macroeconomics readers as well as econometrics professionals, scholars and graduate students. We wish to express our gratitude to the authors for their strong contributions and the reviewers for their assistance and careful attention to detail in their reports.
Book Synopsis Markov-Switching Vector Autoregressions by : Hans-Martin Krolzig
Download or read book Markov-Switching Vector Autoregressions written by Hans-Martin Krolzig and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contributes to re cent developments on the statistical analysis of multiple time series in the presence of regime shifts. Markov-switching models have become popular for modelling non-linearities and regime shifts, mainly, in univariate eco nomic time series. This study is intended to provide a systematic and operational ap proach to the econometric modelling of dynamic systems subject to shifts in regime, based on the Markov-switching vector autoregressive model. The study presents a comprehensive analysis of the theoretical properties of Markov-switching vector autoregressive processes and the related statistical methods. The statistical concepts are illustrated with applications to empirical business cyde research. This monograph is a revised version of my dissertation which has been accepted by the Economics Department of the Humboldt-University of Berlin in 1996. It con sists mainly of unpublished material which has been presented during the last years at conferences and in seminars. The major parts of this study were written while I was supported by the Deutsche Forschungsgemeinschajt (DFG), Berliner Graduier tenkolleg Angewandte Mikroökonomik and Sondeiforschungsbereich 373 at the Free University and Humboldt-University of Berlin. Work was finally completed in the project The Econometrics of Macroeconomic Forecasting founded by the Economic and Social Research Council (ESRC) at the Institute of Economies and Statistics, University of Oxford. It is a pleasure to record my thanks to these institutions for their support of my research embodied in this study.
Book Synopsis Dynamic Factor Markov Switching Model and Its Applications in Business Cycles by : Chengxuan Yu
Download or read book Dynamic Factor Markov Switching Model and Its Applications in Business Cycles written by Chengxuan Yu and published by . This book was released on 2001 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis How Well Do Markov Switching Models Describe Actual Business Cycles? by : Penelope A. Smith
Download or read book How Well Do Markov Switching Models Describe Actual Business Cycles? written by Penelope A. Smith and published by . This book was released on 2004 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Identification and Normalization in Markov Switching Models of "business Cycles" by :
Download or read book Identification and Normalization in Markov Switching Models of "business Cycles" written by and published by . This book was released on 2004 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Check on the Robustness of Hamilton's Markov Switching Model Approach to the Economic Analysis of the Business Cycle by : Michael D. Boldin
Download or read book A Check on the Robustness of Hamilton's Markov Switching Model Approach to the Economic Analysis of the Business Cycle written by Michael D. Boldin and published by . This book was released on 1998 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This note explores the robustness of Hamilton's (Econometrica, 1989) two-regime Markov switching model framework for capturing business-cycle patterns. Applying his exact specification to a revised version of real GNP, I find parameter estimates that are similar to those he reported only when I use the same sample period (1952-1984) and a particular set of starting values for the maximum likelihood procedure. Two other local maxima exist that have higher likelihood values, and neither correspond to the conventional recession-expansion dichotomy. In fact, when the sample period is extended, there is no longer a local maximum near the parameter set reported by Hamilton. Exploring the model and data further, I reject cross-regime restrictions of Hamilton specification but also find that relaxing these restrictions increases the number of local maxima. However, a parsimonious three-regime model for GNP growth is more robust and plausible, especially when each regime is required to last more than one quarter.
Book Synopsis The Markov-switching Model as Applied to the UK and US Business Cycles by : Fida Hussain
Download or read book The Markov-switching Model as Applied to the UK and US Business Cycles written by Fida Hussain and published by . This book was released on 2000 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Okun's Law Across the Business Cycle and During the Great Recession by : Rui M. Pereira
Download or read book Okun's Law Across the Business Cycle and During the Great Recession written by Rui M. Pereira and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Markov-Switching Models with Evolving Regime-Specific Parameters by : Yunjong Eo
Download or read book Markov-Switching Models with Evolving Regime-Specific Parameters written by Yunjong Eo and published by . This book was released on 2015 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we relax the assumption of constant regime-specific mean growth rates in Hamilton's (1989) two-state Markov-switching model of the business cycle. We introduce a random walk hierarchical prior for each regime-specific mean growth rate and impose a cointegrating relationship between the mean growth rates in recessionary and expansionary periods. By applying the proposed model to postwar U.S. real GDP growth (1947:Q4-2011:Q3), we uncover the evolving nature of the regime-specific mean growth rates of real output in the U.S. business cycle. Additional features of the postwar U.S. business cycle that we uncover include: i) a steady decline in the long-run mean growth rate of real output over the postwar sample and ii) an asymmetric error-correction mechanism when the economy deviates from its long-run equilibrium.
Book Synopsis Duration Dependent Markov-Switching Vector Autoregression by : Matteo M. Pelagatti
Download or read book Duration Dependent Markov-Switching Vector Autoregression written by Matteo M. Pelagatti and published by . This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Duration dependent Markov-switching VAR (DDMS-VAR) models are time series models with data generating process consisting in a mixture of two VAR processes. The switching between the two VAR processes is governed by a two state Markov chain with transition probabilities that depend on how long the chain has been in a state. In the present paper we analyze the second order properties of such models and propose a Markov chain Monte Carlo algorithm to carry out Bayesian inference on the model's unknowns. Furthermore, a freeware software written by the author for the analysis of time series by means of DDMS-VAR models is illustrated. The methodology and the software are applied to the analysis of the U.S. business cycle.
Book Synopsis Bayesian Methods and Markov Switching Models for the Analysis of U.S. Postwar Business Cycle Fluctuations by : Jie Li
Download or read book Bayesian Methods and Markov Switching Models for the Analysis of U.S. Postwar Business Cycle Fluctuations written by Jie Li and published by . This book was released on 2010 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation consists of five chapters addressing analytically and empirically U.S. Postwar business cycle fluctuations. Markov Switching models and Bayesian estimation methods are used to investigate United States macroeconomic dynamics in the last 60 years. Chapter 1 introduces the structure of this dissertation. Chapter 2 proposes a dynamic stochastic general equilibrium (DSGE) model with Markov Switching and heteroskedastic shocks to examine the role of agents' beliefs separately from changes in monetary policy in explaining inflation fluctuations. Bayesian analysis is conducted with Markov Switching to support regime switches in the private sector, in the implementation of monetary policy and in the volatility of shocks in the U.S. Postwar economy, which are related to the "Great Inflation", the "Great Moderation" and the 2008 financial crisis. A counterfacutal analysis found that if agents maintained a weak response to macroeconomic dynamics over time, there would be lower inflation during the "Great Inflation". In addition, irrespectively to monetary policy regimes, supply shocks are the main driver of inflation fluctuations, while demand shocks are the main source of changes in the output gap. However, when agents maintain a higher risk aversion towards consumption with a higher slope in the Phillips curve, demand shocks also play a role in driving inflation, even though supply shocks are still the main driver of inflation. Chapter 3 emphasizes on the monetary policy with an investigation on the assumption that policymakers commit to a Taylor rule, using a time-varying inflation-unemployment dynamic model on U.S. economy. This chapter is based on the conjecture that potential policymakers' misperception may be originated from unobserved deviations of unemployment from its natural rate. Five processes are proposed for policymakers' belief under commitment to inflation and unemployment and compare them with a baseline autoregressive process without commitment. The models are estimated using Bayesian techniques. Empirical results are as follows: First, policymakers' belief is very persistent even when it commits to a Taylor-type policy rule. Second, the run-up of U.S. inflation around 1980 can be mostly attributed to policymakers' misperception while the peak surge of inflation in 1974 is possibly a result of non-policy shocks. Third, models with commitment dominate models without commitment, especially in periods of large oscillations in inflation. In particular, when policymakers are committed to respond to a Taylor-type policy rule, the average loss function is considerably reduced over time, thus effectively lessening potential misperceptions. Chapter 4 introduces a simple version of adaptive expectation to a dynamic stochastic general equilibrium (DSGE) model to evaluate the goodness of fitness and forecasting performance on U.S. macroeconomic indicators. Analytical maximum likelihood estimation results represent a DSGE model with adaptive expectation outperforms a DSGE model with rational expectation. In addition to providing a better fit of inflation and output gap in the U.S. Postwar macro economy, a DSGE model with adaptive expectation also leads to redundant lagged inflation in fitting inflation dynamics. Chapter 5 concludes and proposes future extension.
Book Synopsis Special Issue on Advances in Regime-switching Models for Business Cycle Research and Financial Analysis by :
Download or read book Special Issue on Advances in Regime-switching Models for Business Cycle Research and Financial Analysis written by and published by . This book was released on 2002 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Dynamic Linear Models with R by : Giovanni Petris
Download or read book Dynamic Linear Models with R written by Giovanni Petris and published by Springer Science & Business Media. This book was released on 2009-06-12 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: State space models have gained tremendous popularity in recent years in as disparate fields as engineering, economics, genetics and ecology. After a detailed introduction to general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis. Whenever possible it is shown how to compute estimates and forecasts in closed form; for more complex models, simulation techniques are used. A final chapter covers modern sequential Monte Carlo algorithms. The book illustrates all the fundamental steps needed to use dynamic linear models in practice, using R. Many detailed examples based on real data sets are provided to show how to set up a specific model, estimate its parameters, and use it for forecasting. All the code used in the book is available online. No prior knowledge of Bayesian statistics or time series analysis is required, although familiarity with basic statistics and R is assumed.
Book Synopsis Nonlinear Time Series Analysis by : Ruey S. Tsay
Download or read book Nonlinear Time Series Analysis written by Ruey S. Tsay and published by John Wiley & Sons. This book was released on 2018-09-14 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive resource that draws a balance between theory and applications of nonlinear time series analysis Nonlinear Time Series Analysis offers an important guide to both parametric and nonparametric methods, nonlinear state-space models, and Bayesian as well as classical approaches to nonlinear time series analysis. The authors—noted experts in the field—explore the advantages and limitations of the nonlinear models and methods and review the improvements upon linear time series models. The need for this book is based on the recent developments in nonlinear time series analysis, statistical learning, dynamic systems and advanced computational methods. Parametric and nonparametric methods and nonlinear and non-Gaussian state space models provide a much wider range of tools for time series analysis. In addition, advances in computing and data collection have made available large data sets and high-frequency data. These new data make it not only feasible, but also necessary to take into consideration the nonlinearity embedded in most real-world time series. This vital guide: • Offers research developed by leading scholars of time series analysis • Presents R commands making it possible to reproduce all the analyses included in the text • Contains real-world examples throughout the book • Recommends exercises to test understanding of material presented • Includes an instructor solutions manual and companion website Written for students, researchers, and practitioners who are interested in exploring nonlinearity in time series, Nonlinear Time Series Analysis offers a comprehensive text that explores the advantages and limitations of the nonlinear models and methods and demonstrates the improvements upon linear time series models.
Book Synopsis Regime-Switching Models by : Simon van Norden
Download or read book Regime-Switching Models written by Simon van Norden and published by . This book was released on 2000 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper is a user's guide to a set of Gauss procedures developed at the Bank of Canada for estimating regime-switching models. The procedures can estimate relatively quickly a wide variety of switching models and so should prove useful to the applied researcher. Sample program listings are included. FRENCH VERSION La presente etude constitue un guide d'utilisation d'un ensemble de procedures de Gauss mises au point a la Banque du Canada en vue de l'estimation des modeles a changement de regime. Ces procedures permettent d'estimer de facon assez rapide une vaste gamme de modeles a changement de regime et devraient s'averer utiles pour la recherche appliquee. Des echantillons de programmes sont inclus dans l'etude.
Book Synopsis Monte Carlo Simulation and Finance by : Don L. McLeish
Download or read book Monte Carlo Simulation and Finance written by Don L. McLeish and published by John Wiley & Sons. This book was released on 2011-09-13 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Monte Carlo methods have been used for decades in physics, engineering, statistics, and other fields. Monte Carlo Simulation and Finance explains the nuts and bolts of this essential technique used to value derivatives and other securities. Author and educator Don McLeish examines this fundamental process, and discusses important issues, including specialized problems in finance that Monte Carlo and Quasi-Monte Carlo methods can help solve and the different ways Monte Carlo methods can be improved upon. This state-of-the-art book on Monte Carlo simulation methods is ideal for finance professionals and students. Order your copy today.
