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An analogue model of phase-averaging procedures

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This paper considers the statistical and econometric effect that fixed n-period phase-averaging has on time series generated by some simple dynamic processes. We focus on the variance and autocorrelation of the data series and of the disturbance term for levels and difference equations involving the phase-average data. Further, we examine the effect of phase-averaging on the erogeneity of variables in those equations and the implications phase-averaging has for conducting statistical inference. ; To illustrate our analytical results, we investigate claims by Friedman and Schwartz in their 1982 book Monetary Trends in the United States and the United Kingdom about what the properties of phase-average data and the relationships between those data ought to be. We present certain features of the observed series on velocity, examine how well our analytical model captures them, and contrast them with Friedman and Schwartz's predictions. While our model is an extremely simplified characterization of the phase-averaging adopted by Friedman and Schwartz, it does offer several insights into the likely consequences of their approach.

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  • Julia Campos & Neil R. Ericsson & David F. Hendry, 1987. "An analogue model of phase-averaging procedures," International Finance Discussion Papers 303, Board of Governors of the Federal Reserve System (U.S.).
  • Handle: RePEc:fip:fedgif:303
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    Cited by:

    1. Neil R. Ericsson & John S. Irons & Ralph W. Tryon, 2001. "Output and inflation in the long run," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 241-253.
    2. Granger, C. W. J. & Siklos, Pierre L., 1995. "Systematic sampling, temporal aggregation, seasonal adjustment, and cointegration theory and evidence," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 357-369.
    3. Yamin Ahmad & Ivan Paya, 2014. "Temporal Aggregation of Random Walk Processes and Implications for Asset Prices," Working Papers 14-01, UW-Whitewater, Department of Economics.
    4. Neil R. Ericsson, David F. Hendry & Kevin M. Prestiwch, "undated". "The UK Demand for Broad Money over the Long run," Economics Papers W29, Economics Group, Nuffield College, University of Oxford.
    5. Michael D. Bordo & Lars Jonung & Pierre Siklos, 1993. "The Common Development of Institutional Change as Measured by Income Velocity: A Century of Evidence from Industrialized Countries," NBER Working Papers 4379, National Bureau of Economic Research, Inc.
    6. Mamingi Nlandu, 2017. "Beauty and Ugliness of Aggregation over Time: A Survey," Review of Economics, De Gruyter, vol. 68(3), pages 205-227, December.
    7. Marcellino, Massimiliano, 1999. "Some Consequences of Temporal Aggregation in Empirical Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 129-136, January.
    8. Rajaguru GULASEKARAN & Tilak ABEYSINGHE, 2002. "The Distortionary Effects Of Temporal Aggregation On Granger Causality," Departmental Working Papers wp0204, National University of Singapore, Department of Economics.
    9. Neil R. Ericsson & David F. Hendry & Hong-Anh Tran, 1993. "Cointegration, seasonality, encompassing, and the demand for money in the United Kingdom," International Finance Discussion Papers 457, Board of Governors of the Federal Reserve System (U.S.).
    10. Hendry, David F & Ericsson, Neil R, 1991. "An Econometric Analysis of U.K. Money Demand in 'Monetary Trends in the United States and the United Kingdom' by Milton Friedman and Anna Schwartz," American Economic Review, American Economic Association, vol. 81(1), pages 8-38, March.
    11. Ahmad Yamin S & Paya Ivan, 2020. "Temporal aggregation of random walk processes and implications for economic analysis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(2), pages 1-20, April.
    12. Edward Nelson, 2012. "The correlation between money and output in the United Kingdom: resolution of a puzzle," Finance and Economics Discussion Series 2012-29, Board of Governors of the Federal Reserve System (U.S.).
    13. Ericsson Neil R., 2016. "Testing for and estimating structural breaks and other nonlinearities in a dynamic monetary sector," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 377-398, September.

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