Download or read book Bayesian Variable Selection for Nowcasting Economic Time Series written by Steven L. Scott and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We consider the problem of short-term time series forecasting (nowcasting) when there are more possible predictors than observations. Our approach combines three Bayesian techniques: Kalman filtering, spike-and-slab regression, and model averaging. We illustrate this approach using search engine query data as predictors for consumer sentiment and gun sales.
Download or read book Economic Analysis of the Digital Economy written by Avi Goldfarb and published by University of Chicago Press. This book was released on 2015-05-08 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is a small and growing literature that explores the impact of digitization in a variety of contexts, but its economic consequences, surprisingly, remain poorly understood. This volume aims to set the agenda for research in the economics of digitization, with each chapter identifying a promising area of research. "Economics of Digitization "identifies urgent topics with research already underway that warrant further exploration from economists. In addition to the growing importance of digitization itself, digital technologies have some features that suggest that many well-studied economic models may not apply and, indeed, so many aspects of the digital economy throw normal economics in a loop. "Economics of Digitization" will be one of the first to focus on the economic implications of digitization and to bring together leading scholars in the economics of digitization to explore emerging research.
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 Handbook of Bayesian Variable Selection written by Mahlet G. Tadesse and published by CRC Press. This book was released on 2021-12-24 with total page 491 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian variable selection has experienced substantial developments over the past 30 years with the proliferation of large data sets. Identifying relevant variables to include in a model allows simpler interpretation, avoids overfitting and multicollinearity, and can provide insights into the mechanisms underlying an observed phenomenon. Variable selection is especially important when the number of potential predictors is substantially larger than the sample size and sparsity can reasonably be assumed. The Handbook of Bayesian Variable Selection provides a comprehensive review of theoretical, methodological and computational aspects of Bayesian methods for variable selection. The topics covered include spike-and-slab priors, continuous shrinkage priors, Bayes factors, Bayesian model averaging, partitioning methods, as well as variable selection in decision trees and edge selection in graphical models. The handbook targets graduate students and established researchers who seek to understand the latest developments in the field. It also provides a valuable reference for all interested in applying existing methods and/or pursuing methodological extensions. Features: Provides a comprehensive review of methods and applications of Bayesian variable selection. Divided into four parts: Spike-and-Slab Priors; Continuous Shrinkage Priors; Extensions to various Modeling; Other Approaches to Bayesian Variable Selection. Covers theoretical and methodological aspects, as well as worked out examples with R code provided in the online supplement. Includes contributions by experts in the field. Supported by a website with code, data, and other supplementary material
Download or read book Bayesian Variable Selection for Time Series Regression with Application to Waste Water Monitoring written by Ian Roddis and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Jointness in Bayesian Variable Selection with Applications to Growth Regression written by and published by World Bank Publications. This book was released on with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Applied Bayesian Forecasting and Time Series Analysis written by Andy Pole and published by CRC Press. This book was released on 1994-09-01 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical in its approach, Applied Bayesian Forecasting and Time Series Analysis provides the theories, methods, and tools necessary for forecasting and the analysis of time series. The authors unify the concepts, model forms, and modeling requirements within the framework of the dynamic linear mode (DLM). They include a complete theoretical development of the DLM and illustrate each step with analysis of time series data. Using real data sets the authors: Explore diverse aspects of time series, including how to identify, structure, explain observed behavior, model structures and behaviors, and interpret analyses to make informed forecasts Illustrate concepts such as component decomposition, fundamental model forms including trends and cycles, and practical modeling requirements for routine change and unusual events Conduct all analyses in the BATS computer programs, furnishing online that program and the more than 50 data sets used in the text The result is a clear presentation of the Bayesian paradigm: quantified subjective judgements derived from selected models applied to time series observations. Accessible to undergraduates, this unique volume also offers complete guidelines valuable to researchers, practitioners, and advanced students in statistics, operations research, and engineering.
Download or read book Variable Selection in a Class of Bayesian Time Series Models written by Roberta Paroli and published by . This book was released on 2006 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Bayesian Econometric Methods written by Joshua Chan and published by Cambridge University Press. This book was released on 2019-08-15 with total page 491 pages. Available in PDF, EPUB and Kindle. Book excerpt: Illustrates Bayesian theory and application through a series of exercises in question and answer format.
Download or read book An Application of Bayesian Variable Selection to International Economic Data written by 田祥 and published by . This book was released on 2017 with total page 39 pages. Available in PDF, EPUB and Kindle. Book excerpt: GDP plays an important role in people's lives. For example, when GDP increases, the unemployment rate will frequently decrease. In this project, we will use four different Bayesian variable selection methods to verify economic theory regarding important predictors to GDP. The four methods are: g-prior variable selection with credible intervals, local empirical Bayes with credible intervals, variable selection by indicator function, and hyper-g prior variable selection. Also, we will use four measures to compare the results of the various Bayesian variable selection methods: AIC, BIC, Adjusted-R squared and cross-validation.
Download or read book Applied Economic Forecasting Using Time Series Methods written by Eric Ghysels and published by Oxford University Press. This book was released on 2018 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: Economic forecasting is a key ingredient of decision making in the public and private sectors. This book provides the necessary tools to solve real-world forecasting problems using time-series methods. It targets undergraduate and graduate students as well as researchers in public and private institutions interested in applied economic forecasting.
Download or read book Essays on Bayesian Time Series and Variable Selection written by Debkumar De and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Estimating model parameters in dynamic model continues to be challenge. In my dissertation, we have introduced a Stochastic Approximation based parameter estimation approach under Ensemble Kalman Filter set-up. Asymptotic properties of the resultant estimates are discussed here. We have compared our proposed method to current methods via simulation studies. We have demonstrated predictive performance of our proposed method on a large spatio-temporal data. In my other topic, we presented a method for simultaneous estimation of regression parameters and the covariance matrix, developed for a nonparametric Seemingly Unrelated Regression problem. This is a very flexible modeling technique that essentially performs a sparse high-dimensional multiple predictor(p), multiple responses(q) regression where the responses may be correlated. Such data appear abundantly in the fields of genomics, finance and econometrics. We illustrate and compare performances of our proposed techniques with previous analyses using both simulated and real multivariate data arising in econometrics and government. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/152793
Download or read book Introducing Monte Carlo Methods with R written by Christian Robert and published by Springer Science & Business Media. This book was released on 2010 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the main tools used in statistical simulation from a programmer’s point of view, explaining the R implementation of each simulation technique and providing the output for better understanding and comparison.
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.
Download or read book Economic Time Series written by William R. Bell and published by CRC Press. This book was released on 2018-11-14 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: Economic Time Series: Modeling and Seasonality is a focused resource on analysis of economic time series as pertains to modeling and seasonality, presenting cutting-edge research that would otherwise be scattered throughout diverse peer-reviewed journals. This compilation of 21 chapters showcases the cross-fertilization between the fields of time s
Download or read book The Economics of Digitization written by Shane M. Greenstein and published by . This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The increasing creation, support, use and consumption of digital representation of information touches a wide breadth of economic activities. This digitization has transformed social interactions, facilitated entirely new industries and undermined others and reshaped the ability of people - consumers, job seekers, managers, government officials and citizens - to access and leverage information. This important book includes seminal papers addressing topics such as the causes and consequences of digitization, factors shaping the structure of products and services and creating an enormous range of new applications and how market participants make their choices over strategic organization, market conduct, and public policies. This authoritative collection, with an original introduction by the editors, will be an invaluable source of reference for students, academics and practitioners with an interest in the economics of digitisation and the digital economy.
Download or read book Bayesian Variable Selection in Spatial Autoregressive Models written by and published by . This book was released on 2015 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt:
