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2012 | 6 | nr 2 | 40--57
Tytuł artykułu

The Analysis of Nonstationary Time Series Using Regression, Correlation and Cointegration

Autorzy
Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
There are simple well-known conditions for the validity of regression and correlation as statistical tools. We analyse by examples the effect of nonstationarity on inference using these methods and compare them to model based inference using the cointegrated vector autoregressive model. Finally we analyse some monthly data from US on interest rates as an illustration of the methods. (original abstract)
Rocznik
Tom
6
Numer
Strony
40--57
Opis fizyczny
Twórcy
  • Universities of Copenhagen and CREATES Aarhus, Denmark
Bibliografia
  • Anderson, T. W. (1951). Estimating linear restrictions on regression coefficients for multivariate normal distributions. Annals of Mathematical Statistics, 22, 327-351.
  • Davidson, R., & MacKinnon, J. G. (2004). Econometric Theory and Methods. New York, NY: Oxford University Press.
  • Dennis, J., Johansen, S., & Juselius, K. (2005). CATS for RATS: Manual to Cointegration Analysis of Time Series, Evanston, IL: Estima.
  • Dickey D. A., & Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica, 49, 1057-1072.
  • Engle R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation and testing. Econometrica, 55, 251-276.
  • Giese, J. V. (2008). Level, slope, curvature: characterizing the yield curve in a cointegrated VAR model. Economics: The Open-Access, Open-Assessment E-Journal, 2(2008-28), 1-21.
  • Granger, C. W. J. (1981). Some properties of time series data and their use in econometric model specification. Journal of Econometrics, 16(1), 121-130.
  • Granger, C. W. J., & Newbold, P. (1974). Spurious regressions in econometrics. Journal of Econometrics, 2, 111-120.
  • Haavelmo, T. (1943). Statistical implications of a system of simultaneous equations. Econometrica, 11, 1-12.
  • Hall, P., & Heyde, C. C. (1980). Martingale Limit Theory and its Application. New York, NY: Academic Press.
  • Johansen, S. (1988). Statistical analysis of cointegration vectors. Journal of Economic Dynamics and Control, 12, 231-254.
  • Johansen, S. (1996). Likelihood-based Inference in Cointegrated Vector Autoregressive Models. New York, NY: Oxford University Press.
  • Johansen, S. (2006). Cointegration: a survey. In T. C. Mills & K. Patterson (Eds.), Palgrave Handbook of Econometrics: Volume 1, Econometric Theory (16, pp. 17-34). New York, NY: Palgrave Macmillan.
  • Juselius, K. (2006).The Cointegrated VAR Model: Econometric Methodology and Macroeconomic Applications. New York, NY: Oxford University Press.
  • Phillips, P. C. B. (1986). Understanding Spurious Regressions in Econometrics. Journal of Econometrics, 33, 311-340.
  • Phillips, P. C. B. (1991). Optimal inference in cointegrated systems. Econometrica, 59, 283-306.
  • Sober, E. (2001). Venetian sea levels, British bread prices and the principle of the common cause. British Journal for the Philosophy of Sciences, 52, 331-346.
  • Stock, J. H., & Watson, M. W. (2003). Introduction to Econometrics. Boston, MA: Addison Wesley.
  • Yule, U. (1926). Why do we sometimes get nonsense-correlations between time series? - A study in sampling and the nature of time series. Journal of the Royal Statistical Society, 89, 1-63.
Typ dokumentu
Bibliografia
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Identyfikator YADDA
bwmeta1.element.ekon-element-000171258829

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