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Some simple tests for non-lineair time series models
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Year: 1978 Publisher: Louvain-la-Neuve UCL. CORE

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Calibration techniques and econometrics.
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The econometric analysis of recurrent events in macroeconomics and finance
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ISBN: 9780691167084 0691167087 Year: 2016 Publisher: Princeton, New Jersey Princeton University Press

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The global financial crisis highlighted the impact on macroeconomic outcomes of recurrent events like business and financial cycles, highs and lows in volatility, and crashes and recessions. At the most basic level, such recurrent events can be summarized using binary indicators showing if the event will occur or not. These indicators are constructed either directly from data or indirectly through models. Because they are constructed, they have different properties than those arising in microeconometrics, and how one is to use them depends a lot on the method of construction.xml_char_ref(d;) This book presents the econometric methods necessary for the successful modeling of recurrent events, providing valuable insights for policymakers, empirical researchers, and theorists. It explains why it is inherently difficult to forecast the onset of a recession in a way that provides useful guidance for active stabilization policy, with the consequence that policymakers should place more emphasis on making the economy robust to recessions. The book offers a range of econometric tools and techniques that researchers can use to measure recurrent events, summarize their properties, and evaluate how effectively economic and statistical models capture them. These methods also offer insights for developing models that are consistent with observed financial and real cycles


Book
The econometric analysis of recurrent events in macroeconomics and finance
Authors: ---
ISBN: 9781400880935 1400880939 9780691167084 0691167087 Year: 2016 Publisher: Princeton, NJ : Princeton University Press,

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The global financial crisis highlighted the impact on macroeconomic outcomes of recurrent events like business and financial cycles, highs and lows in volatility, and crashes and recessions. At the most basic level, such recurrent events can be summarized using binary indicators showing if the event will occur or not. These indicators are constructed either directly from data or indirectly through models. Because they are constructed, they have different properties than those arising in microeconometrics, and how one is to use them depends a lot on the method of construction.This book presents the econometric methods necessary for the successful modeling of recurrent events, providing valuable insights for policymakers, empirical researchers, and theorists. It explains why it is inherently difficult to forecast the onset of a recession in a way that provides useful guidance for active stabilization policy, with the consequence that policymakers should place more emphasis on making the economy robust to recessions. The book offers a range of econometric tools and techniques that researchers can use to measure recurrent events, summarize their properties, and evaluate how effectively economic and statistical models capture them. These methods also offer insights for developing models that are consistent with observed financial and real cycles.This book is an essential resource for students, academics, and researchers at central banks and institutions such as the International Monetary Fund.


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Alternative Models For Conditional Stock Volatility
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Year: 1990 Publisher: Cambridge, Mass. National Bureau of Economic Research

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The econometrics of the new Keynesian policy model: introduction
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Year: 2004 Publisher: Oxford Blackwell

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Issues in adopting DSGE models for use in the policy process
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Year: 2006 Publisher: Prague CNB

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On econometric analysis of structural systems with permanent and transitory shocks and exogenous variables
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Year: 2007 Publisher: Munich CESifo

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Alternative Models For Conditional Stock Volatility
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Year: 1989 Publisher: Cambridge, Mass. National Bureau of Economic Research

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This paper compares several statistical models for monthly stock return volatility. The focus is on U.S. data from 1834-19:5 because the post-1926 data have been analyzed in more detail by others. Also, the Great Depression had levels of stock volatility that are inconsistent with stationary models for conditional heteroskedasticity, We show the importance of nonlinearities in stock return behavior that are not captured by conventional ARCH or GARCH models. We also show the nonstationariry of stock volatility, even over the 1834-1925 period.

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