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Time-series Econometrics: Cointegration and Autoregressive Conditional Heteroskedasticity

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Author Info
Committee, Nobel Prize (Nobel Prize Committee)
Abstract

Advanced information on the Bank of Sweden Prize in Economic Sciences in Memory of Alfred Nobel, 2003. Empirical research in macroeconomics as well as in financial economics is largely based on time series. Ever since Economics Laureate Trygve Haavelmo's work it has been standard to view economic time series as realizations of stochastic processes. This approach allows the model builder to use statistical inference in constructing and testing equations that characterize relationships between economic variables. This year's Prize rewards two contributions that have deepened our understanding of two central properties of many economic time series - nonstationarity and time-varying volatility - and have led to a large number of applications

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File URL: http://nobelprize.org/nobel_prizes/economics/laureates/2003/ecoadv.pdf
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Publisher Info
Paper provided by Nobel Prize Committee in its series Nobel Prize in Economics documents with number 2003-1.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length: 31 pages
Date of creation: 08 Oct 2003
Date of revision:
Handle: RePEc:ris:nobelp:2003_001

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Web page: http://www.nobelprize.org/

For technical questions regarding this item, or to correct its listing, contact: (Christian Zimmermann).

Related research
Keywords: time-series; cointegration;

Find related papers by JEL classification:
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions

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This page was last updated on 2009-12-17.


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