Download or read book Forecasting Performance of Bayesian Vector Autoregression Models written by Raluca Alina Cata and published by . This book was released on 2007 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Forecasting with Bayesian Vector Autoregressions with Time Variation in the Mean written by Marta Banbura and published by . This book was released on 2018 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt: We develop a vector autoregressive model with time variation in the mean and the variance. The unobserved time-varying mean is assumed to follow a random walk and we also link it to long-term Consensus forecasts, similar in spirit to so called democratic priors. The changes in variance are modelled via stochastic volatility. The proposed Gibbs sampler allows the researcher to use a large cross-sectional dimension in a feasible amount of computational time. The slowly changing mean can account for a number of secular developments such as changing inflation expectations, slowing productivity growth or demographics. We show the good forecasting performance of the model relative to popular alternatives, including standard Bayesian VARs with Minnesota priors, VARs with democratic priors and standard time-varying parameter VARs for the euro area, the United States and Japan. In particular, incorporating survey forecast information helps to reduce the uncertainty about the unconditional mean and along with the time variation improves the long-run forecasting performance of the VAR models.

Download or read book Specifying a Bayesian Vector Autoregression for Short run Macroeconomic Forecasting with an Application to Finland written by Christian C. Starck and published by . This book was released on 1991 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Data Analysis Machine Learning and Applications written by Christine Preisach and published by Springer Science & Business Media. This book was released on 2008-04-13 with total page 714 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data analysis and machine learning are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as web and text mining, marketing, medical science, bioinformatics and business intelligence. This volume contains the revised versions of selected papers in the field of data analysis, machine learning and applications presented during the 31st Annual Conference of the German Classification Society (Gesellschaft für Klassifikation - GfKl). The conference was held at the Albert-Ludwigs-University in Freiburg, Germany, in March 2007.

Download or read book Using Leading Indicators to Forecast U S Home Sales in a Bayesian Vector Autoregressive Framework written by Pami Dua and published by . This book was released on 1999 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper uses Bayesian vector autoregressive models to examine the usefulness of leading indicators in predicting U.S. home sales. The benchmark Bayesian model includes home sales, the price of homes, the mortgage rate, real personal disposable income, and the unemployment rate. We evaluate the forecasting performance of six alternative leading indicators by adding each, in turn, to the benchmark model. Out-of-sample forecast performance over three periods shows that the model that includes building permits authorized consistently produces the most accurate forecasts. Thus, the intention to build in the future provides good information with which to predict U.S. home sales. Another finding suggests that leading indicators with longer leads outperform the short-leading indicators.

Download or read book The Macroeconomic Forecasting Performance of Autoregressive Models with Alternative Specifications of Time varying Volatility written by Todd E. Clark (Economiste) and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Forecasting with Bayesian Vector Autoregressions written by K. R. Kadiyala and published by . This book was released on 1989 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Forecasting the Albanian Short term Inflation Through a Bayesian VAR Model written by Meri Papavangjeli and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In the context of the Bank of Albania's primary objective of achieving and maintaining price stability, generating accurate and reliable forecasts for the future rate of inflation is a necessity for its successful realization. This paper aims to enrich the Bank's portfolio of short-term inflation forecasting tools through the construction of a Bayesian vector autoregressive (BVAR) model, which unlike standard autoregressive vector (VAR) models, addresses the overparameterization problem, allowing for the inclusion of more endogenous variables, and in this way enabling a more comprehensive explanation of inflation. Several univariate models are estimated to forecast short-term inflation, such as: unconditional mean, random walk, autoregressive integrated moving average (ARIMA) models, and the best performing among them is used as a benchmark to evaluate the forecast performance of the BVAR model. In addition, an unrestricted VAR - the most commonly used tool to obtain projections of the main economic indicators - is constructed as an additional benchmark, based solely on the information that the data series provides. The results show that the BVAR approach, which incorporates more economic information, outperforms the benchmark univariate and the unrestricted VAR models in the different time horizons of the forecast sample, but the differences between models in terms of their forecast performance are not statistically significant.

Download or read book Bayesian VAR Models for Forecasting Irish Inflation written by Geoff Kenny and published by . This book was released on 1998 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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 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 BAYESIAN VECTOR AUTOREGRESSIVE MODELS FOR BUSINESS FORECASTING VAR BVAR written by Elizabeth Louise Rose and published by . This book was released on 1989 with total page 580 pages. Available in PDF, EPUB and Kindle. Book excerpt: forecast comparisons.

Download or read book Bayesian Vector Autoregressive Models for Business Forecasting written by Elizabeth Louise Rose and published by . This book was released on 1991 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Forecasting and Turning point Predictions in a Bayesian Panel VAR Model written by Fabio Canova and published by . This book was released on 2001 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Time Series Analysis by State Space Methods written by James Durbin and published by Oxford University Press. This book was released on 2001-06-21 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: State space time series analysis emerged in the 1960s in engineering, but its applications have spread to other fields. Durbin (statistics, London School of Economics and Political Science) and Koopman (econometrics, Free U., Amsterdam) extol the virtues of such models over the main analytical system currently used for time series data, Box-Jenkins' ARIMA. What distinguishes state space time models is that they separately model components such as trend, seasonal, regression elements and disturbance terms. Part I focuses on traditional and new techniques based on the linear Gaussian model. Part II presents new material extending the state space model to non-Gaussian observations. c. Book News Inc.

Download or read book Bayesian VARs Specification Choices and Forecast Accuracy written by Andrea Carriero and published by . This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper we discuss how the forecasting performance of Bayesian VARs is affected by a number of specification choices. In the baseline case, we use a Normal-Inverted Wishart (N-IW) prior that, when combined with a (pseudo-) iterated approach, makes the analytical computation of h-step ahead forecasts feasible and simple, in particular when using standard and fixed values for the tightness and the lag length. We then assess the role of the optimal choice of the tightness, of the lag length and of both; compare alternative approaches to h-step ahead forecasting (direct, iterated and pseudo-iterated); discuss the treatment of the error variance and of cross-variable shrinkage; and address a set of additional issues, including the size of the VAR, modeling in levels or growth rates, and the extent of forecast bias induced by shrinkage. We obtain a large set of empirical results, but we can summarize them by saying that we find very small losses (and sometimes even gains) from the adoption of specification choices that make BVAR modeling quick and easy. This finding could therefore further enhance the diffusion of the BVAR as an econometric tool for a vast range of applications.

Download or read book Univariate and Multivariate ARIMA Versus Vector Autoregression Forecasting written by Michael L. Bagshaw and published by . This book was released on 1987 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: