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Foundations and Trends® in Econometrics Ser.: Short-Term Forecasting for Empirical Economists : A Survey of the Recently Proposed Algorithmsa Survey of the Recently Proposed Algorithms by Maximo Camacho, Gabriel Perez-Quiros and Pilar Poncela (2013, Trade Paperback)
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About this product
Product Identifiers
PublisherNow Publishers
ISBN-101601987420
ISBN-139781601987426
eBay Product ID (ePID)240140813
Product Key Features
Number of Pages74 Pages
Publication NameShort-Term Forecasting for Empirical Economists : A Survey of the Recently Proposed Algorithmsa Survey of the Recently Proposed Algorithms
LanguageEnglish
SubjectEconometrics
Publication Year2013
TypeTextbook
Subject AreaBusiness & Economics
AuthorMaxiMo Camacho, Gabriel Perez-Quiros, Pilar Poncela
SeriesFoundations and Trends® in Econometrics Ser.
FormatTrade Paperback
Dimensions
Item Height0.2 in
Item Weight4.2 Oz
Item Length9.2 in
Item Width6.1 in
Additional Product Features
Intended AudienceScholarly & Professional
Table Of Content1. Introduction 2. Short-term Forecasting: The Evil is in the Details 3. Models 4. An Empirical Example 5. Conclusion References
SynopsisThe economic shocks brought about by the Great Recession triggered drastic reactions by policy makers and private agents alike. Such dramatic economic consequences have lead economics agents to acknowledge the need for new tools to monitor economic developments in real time, and learn early detection methods to foresee downturns and recoveries. Short-term Forecasting for Empirical Economists seeks to close the gap between research and applied short-term forecasting. The authors review some of the key theoretical results and empirical findings in the recent literature on short-term forecasting, and translate these findings into economically meaningful techniques to facilitate their widespread application to compute short-term forecasts in economics, and to monitor the ongoing business cycle developments in real time. Short-term Forecasting for Empirical Economists is divided into five sections. Section 1 outlines what forecasting frameworks are surveyed and why. Section 2 introduces the notation and main characteristics of the data for short term forecasting. Section 3 reviews the main models used for this purpose and addresses the role of the number of series in factor models. Section 4 illustrates the forecasting performance of the different models reviewed in Section 3 through an empirical application. Finally, Section 5 reviews the main results and proposes some lines for further research., The economic shocks brought about by the Great Recession triggered drastic reactions by policy makers and private agents alike. Such dramatic economic consequences have lead economics agents to acknowledge the need for new tools to monitor economic developments in real time, and learn early detection methods to foresee downturns and recoveries Short-term Forecasting for Empirical Economists seeks to close the gap between research and applied short-term forecasting. The authors review some of the key theoretical results and empirical findings in the recent literature on short-term forecasting, and translate these findings into economically meaningful techniques to facilitate their widespread application to compute short-term forecasts in economics, and to monitor the ongoing business cycle developments in real time. Short-term Forecasting for Empirical Economists is divided into five sections. Section 1 outlines what forecasting frameworks are surveyed and why. Section 2 introduces the notation and main characteristics of the data for short term forecasting. Section 3 reviews the main models used for this purpose and addresses the role of the number of series in factor models. Section 4 illustrates the forecasting performance of the different models reviewed in Section 3 through an empirical application. Finally, section 5 reviews the main results and proposes some lines for further research., Seeks to close the gap between research and applied short-term forecasting. Reviews some of the key theoretical results in recent literature on short-term forecasting, translates these findings into economically meaningful techniques to facilitate their widespread application to compute short-term forecasts in economics
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