Download or read book Bayesian Inference for Structural Vector Autoregressions Identified by Markov switching Heteroskedasticity written by Helmut Lütkepohl and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Structural Vector Autoregressions with Markov Switching written by Aleksei Netšunajev and published by . This book was released on 2013 with total page 79 pages. Available in PDF, EPUB and Kindle. Book excerpt: Structural vector autoregressions are of great importance in applied macroeconometric work. The main di culty associated with structural analysis is to identify unique shocks of interest. In a conventional approach this is done via zero or sign restrictions. Heteroskedasticity is proposed for use in identi cation. Under certain assumptions when volatility of shocks changes over time, unique shocks can be obtained. Then formal testing of the restrictions and impulse response analysis can be performed. In this thesis I show how identi cation via heteroskedasticity can be used in di erent contexts. In the rst chapter I analyze the dynamics of trade balances in response to macroeconomic shocks. I show that identifying restrictions, which are known in the literature, are rejected for two out of seven countries. Partially identi ed models fail to provide enough information to fully identify shocks. The second chapter, coauthored with my supervisor, demonstrates how one can bene t from identi cation via heteroskedasticity when sign restrictions are used. The approach is illustrated with a model of the crude oil market. It is shown that shocks identi ed via previously known sign restrictions are in line with the properties of the data. Use of tighter restrictions uncovers that the approach can be discriminative. The third chapter reconsiders the con icting results in the debate on the e ects of technology shocks on hours worked. Using six ways of identifying technology shocks, I nd that not all of them are supported by the data. There is no clear-cut evidence in favor of positive reaction of hours to technology shocks. However, it is plausible for real wage and disentangled investment-speci c and neutral technology shocks, even though conventional identi cation of the latter shocks is rejected.

Download or read book Bayesian Inference on Fully and Partially Identified Structural Vector Autoregressions written by Jetro Anttonen and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We show that under standard assumptions the elements of the impact matrix of the structural vector autoregression (SVAR) are always at least set identified and bounded by the standard deviations of the corresponding reduced form errors. This result facilitates valid Bayesian inference without additional restrictions when only some (or none) of the columns of the impact matrix are point identified due to non-Gaussianity or heteroskedasticity. Moreover, the properties of the shocks can be assessed to find out which of them (if any) are point identified. We expand identification results put forth in the previous literature to models where all or part of the structural shocks are orthogonal but mutually dependent. To exploit deviations from Gaussianity, we propose using versatile error distributions and discuss their implementation in Bayesian analysis. Simulation results and an empirical application to U.S. fiscal policy lend support to the usefulness of efficiently accounting for non-Gaussianity.

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.

Download or read book Structural Vector Autoregressive Analysis written by Lutz Kilian and published by Cambridge University Press. This book was released on 2017-11-23 with total page 757 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the econometric foundations of structural vector autoregressive modeling, as used in empirical macroeconomics, finance, and related fields.

Download or read book Structural Vector Autoregressions with Markov Switching written by Helmut Herwartz and published by . This book was released on 2011 with total page 37 pages. Available in PDF, EPUB and Kindle. Book excerpt: In structural vector autoregressive (SVAR) analysis a Markov regime switching (MS) property can be exploited to identify shocks if the reduced form error covariance matrix varies across regimes. Unfortunately, these shocks may not have a meaningful structural economic interpretation. It is discussed how statistical and conventional identifying information can be combined. The discussion is based on a VAR model for the US containing oil prices, output, consumer prices and a shortterm interest rate. The system has been used for studying the causes of the early millennium economic slowdown based on traditional identication with zero and long-run restrictions and using sign restrictions. We find that previously drawn conclusions are questionable in our framework.

Download or read book Methods for Inference in Large Multiple Equation Markov Switching Models written by Christopher A. Sims and published by . This book was released on 2014 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt: The inference for hidden Markov chain models in which the structure is a multiple-equation macroeconomic model raises a number of difficulties that are not as likely to appear in smaller models. One is likely to want to allow for many states in the Markov chain without allowing the number of free parameters in the transition matrix to grow as the square of the number of states but also without losing a convenient form for the posterior distribution of the transition matrix. Calculation of marginal data densities for assessing model fit is often difficult in high-dimensional models and seems particularly difficult in these models. This paper gives a detailed explanation of methods we have found to work to overcome these difficulties. It also makes suggestions for maximizing posterior density and initiating Markov chain Monte Carlo simulations that provide some robustness against the complex shape of the likelihood in these models. These difficulties and remedies are likely to be useful generally for Bayesian inference in large time-series models. The paper includes some discussion of model specification issues that apply particularly to structural vector autoregressions with a Markov-switching structure.

Download or read book Markov Switching Vector Autoregressive Models written by Matthieu Droumaguet and published by . This book was released on 2012 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation has for prime theme the exploration of nonlinear econometric models featuring a hidden Markov chain. Occasional and discrete shifts in regimes generate convenient nonlinear dynamics to econometric models, allowing for structural changes similar to the exogenous economic events occurring in reality. The first paper sets up a Monte Carlo experiment to explore the finite-sample properties of the estimates of vector autoregressive models subject to switches in regime governed by a hidden Markov chain. The main finding of this article is that the accuracy with which regimes are determined by the Expectation Maximixation algorithm shows improvement when the dimension of the simulated series increases. However this gain comes at the cost of higher sample size requirements for models with more variables. The second paper advocates the use of Bayesian impulse responses for a Markovswitching Vector Autoregressive model. These responses are sensitive to the Markovswitching properties of the model and, based on densities, allow statistical inference to be conducted. Upon the premise of structural changes occurring on oil markets, the empirical results of Kilan (2009) are reinvestigated. The effects of the structural shocks are characterized over four estimated regimes. Over time, the regime dynamics are evolving into more competitive oil markets, with the collapse of the OPEC. Finally, the third paper proposes a method of testing restrictions for Granger noncausality in mean, variance and distribution in the framework of Markov-switching VAR models. Due to the nonlinearity of the restrictions derived by Warne (2000), classical tests have limited use. Bayesian inference consists of a novel Block Metropolis-Hastings sampling algorithm for the estimation of the restricted models, and of standard methods of computing posterior odds ratios. The analysis may be applied to financial and macroeconomic time series with changes of parameter values over time and heteroskedasticity.

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.

Download or read book Markov Switching Structural Vector Autoregressions written by Juan Francisco Rubio-Ramirez and published by . This book was released on 2014 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper develops a new and easily implementable necessary and sufficient condition for the exact identification of a Markov-switching structural vector autoregression (SVAR) model. The theorem applies to models with both linear and some nonlinear restrictions on the structural parameters. We also derive efficient MCMC algorithms to implement sign and long-run restrictions in Markov-switching SVARs. Using our methods, four well-known identification schemes are used to study whether monetary policy has changed in the euro area since the introduction of the European Monetary Union. We find that models restricted to only time-varying shock variances dominate the other models. We find a persistent post-1993 regime that is associated with low volatility of shocks to output, prices, and interest rates. Finally, the output effects of monetary policy shocks are small and uncertain across regimes and models. These results are robust to the four identification schemes studied in this paper.

Download or read book Markov switching Structural Vector Autoregressions written by and published by . This book was released on 2005 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "This paper develops a new and easily implementable necessary and sufficient condition for the exact identification of a Markov-switching structural vector autoregression (SVAR) model. The theorem applies to models with both linear and some nonlinear restrictions on the structural parameters. We also derive efficient MCMC algorithms to implement sign and long-run restrictions in Markov-switching SVARs. Using our methods, four well-known identification schemes are used to study whether monetary policy has changed in the euro area since the introduction of the European Monetary Union. We find that models restricted to only time-varying shock variances dominate the other models. We find a persistent post-1993 regime that is associated with low volatility of shocks to output, prices, and interest rates. Finally, the output effects of monetary policy shocks are small and uncertain across regimes and models. These results are robust to the four identification schemes studied in this paper."--Federal Reserve Bank of Atlanta web site.

Download or read book Structural Vector Autoregressions with Markov Switching written by Markku Lanne and published by . This book was released on 2009 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Structural Vector Autoregressive Analysis written by Lutz Kilian and published by Cambridge University Press. This book was released on 2017-11-23 with total page 758 pages. Available in PDF, EPUB and Kindle. Book excerpt: Structural vector autoregressive (VAR) models are important tools for empirical work in macroeconomics, finance, and related fields. This book not only reviews the many alternative structural VAR approaches discussed in the literature, but also highlights their pros and cons in practice. It provides guidance to empirical researchers as to the most appropriate modeling choices, methods of estimating, and evaluating structural VAR models. The book traces the evolution of the structural VAR methodology and contrasts it with other common methodologies, including dynamic stochastic general equilibrium (DSGE) models. It is intended as a bridge between the often quite technical econometric literature on structural VAR modeling and the needs of empirical researchers. The focus is not on providing the most rigorous theoretical arguments, but on enhancing the reader's understanding of the methods in question and their assumptions. Empirical examples are provided for illustration.

Download or read book The Oxford Handbook of Bayesian Econometrics written by John Geweke and published by Oxford University Press. This book was released on 2011-09-29 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian econometric methods have enjoyed an increase in popularity in recent years. Econometricians, empirical economists, and policymakers are increasingly making use of Bayesian methods. This handbook is a single source for researchers and policymakers wanting to learn about Bayesian methods in specialized fields, and for graduate students seeking to make the final step from textbook learning to the research frontier. It contains contributions by leading Bayesians on the latest developments in their specific fields of expertise. The volume provides broad coverage of the application of Bayesian econometrics in the major fields of economics and related disciplines, including macroeconomics, microeconomics, finance, and marketing. It reviews the state of the art in Bayesian econometric methodology, with chapters on posterior simulation and Markov chain Monte Carlo methods, Bayesian nonparametric techniques, and the specialized tools used by Bayesian time series econometricians such as state space models and particle filtering. It also includes chapters on Bayesian principles and methodology.

Download or read book On Using Markov Switching Time Series Models to Verify Structural Identifying Restrictions and to Assess Public Debt Sustainability written by Anton Stoyanov Velinov and published by . This book was released on 2013 with total page 111 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first paper in this thesis deals with the issue of whether there are bubble components in stock prices. This is joint research with Wenjuan Chen (Free Universtiy Berlin). We investigate existing bivariate structural vector autoregressive (SVAR) models and test their identifying restriction by means of a Markov switching (MS) in heteroskedasticity model. We use data from six different countries and find that, for five of the country models, the structural restriction is supported at the 5% level. Accordingly, we label the two structural shocks as fundamental and non-fundamental. This paper illustrates the virtue of being able to test structural restrictions in order to justify the relevant shocks of interest. The second paper proceeds in the spirit if the first paper. In particular, five trivariate structural VAR or vector error correction (VEC) versions of the dividend discount model are considered, which are widely used in the literature. A common structural parameter identification scheme is used for all these models, which claims to be able to capture fundamental and non-fundamental shocks to stock prices. A MS-SVAR/SVEC model in heteroskedasticity is used to test this identification scheme. It is found that for two of the five models considered, the structural identification scheme appropriately classifies shocks as being either fundamental or non-fundamental. These are models which use real GDP and real dividends as proxies of real economic activity. The findings are supported by a series of robustness tests. Results of this paper serve as a good guideline when conducting future research in this field. The third thesis paper addresses the question of how sustainable a government's current debt path is by means of a Markov switching Augmented Dickey-Fuller (MS-ADF) model. This model is applied to the debt/GDP series of 16 different countries. Stationarity of this series implies that public debt is on a sustainable path and hence, the government's present value borrowing constraint holds. The MS specification also allows for unit root and explosive states of the debt/GDP process. Two different criteria are used to test the null hypothesis of a unit root in each state. The countries with a sustainable debt path are found to be Finland, Norway, Sweden, Switzerland and the UK. The model indicates that France, Greece, Ireland and Japan have unsustainable debt trajectories. The remaining seven countries, (Argentina, Germany, Iceland, Italy, Portugal, Spain and the US) are all found to have uncertain debt paths. The model is robust to the sample size and number of states used. It is shown that this model is an improvement to existing models investigating this subject.

Download or read book Bayesian Multivariate Time Series Methods for Empirical Macroeconomics written by Gary Koop and published by Now Publishers Inc. This book was released on 2010 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Multivariate Time Series Methods for Empirical Macroeconomics provides a survey of the Bayesian methods used in modern empirical macroeconomics. These models have been developed to address the fact that most questions of interest to empirical macroeconomists involve several variables and must be addressed using multivariate time series methods. Many different multivariate time series models have been used in macroeconomics, but Vector Autoregressive (VAR) models have been among the most popular. Bayesian Multivariate Time Series Methods for Empirical Macroeconomics reviews and extends the Bayesian literature on VARs, TVP-VARs and TVP-FAVARs with a focus on the practitioner. The authors go beyond simply defining each model, but specify how to use them in practice, discuss the advantages and disadvantages of each and offer tips on when and why each model can be used.

Download or read book The Markov switching Vector Error Correction Model written by Lukas Frei and published by . This book was released on 2008 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: