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Regression over Timescale Decompositions: A Sampling Analysis of Distributional Properties

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  • James Ramsey

Abstract

In two previous papers, Ramsey and Lampart demonstrated that regression analyses between timescale decompositions provided important insight into the properties of economic relationships. The idea in those papers was that the relationship between any two variables, say consumption and income, was the union of the individual relationships between consumption and income at each timescale and that the regression relationship might, differ across timescales. This paper is dedicated to discovering the approximate distributional properties of the regression estimators and of the residuals in the context of such models. Sampling procedures are used to verify the distributional properties of the regression estimators at each timescale and those of the residuals. This analysis is necessary to provide the appropriate distributional information required to specify tests of hypotheses and confidence intervals.

Suggested Citation

  • James Ramsey, 1999. "Regression over Timescale Decompositions: A Sampling Analysis of Distributional Properties," Economic Systems Research, Taylor & Francis Journals, vol. 11(2), pages 163-184.
    • Handle: RePEc:taf:ecsysr:v:11:y:1999:i:2:p:163-184
    DOI: 10.1080/09535319900000012
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    Citations

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    Cited by:

    1. Ramsey, James B. & Gallegati, Marco & Gallegati, Mauro & Semmler, Willi, 2010. "Instrumental variables and wavelet decompositions," Economic Modelling, Elsevier, vol. 27(6), pages 1498-1513, November.
    2. Bašta, Milan & Helman, Karel, 2013. "Scale-specific importance of weather variables for explanation of variations of electricity consumption: The case of Prague, Czech Republic," Energy Economics, Elsevier, vol. 40(C), pages 503-514.
    3. Gallegati Marco & Gallegati Mauro & Ramsey James B. & Semmler Willi, 2016. "Productivity and unemployment: a scale-by-scale panel data analysis for the G7 countries," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 477-493, September.
    4. Connor Jeff & Rossiter Rosemary, 2005. "Wavelet Transforms and Commodity Prices," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(1), pages 1-22, March.
    5. KimHiang Liow & Xiaoxia Zhou & Qiang Li & Yuting Huang, 2019. "Dynamic interdependence between the US and the securitized real estate markets of the Asian-Pacific economies," Journal of Property Investment & Finance, Emerald Group Publishing Limited, vol. 37(1), pages 92-117, January.
    6. Gallegati, Marco & Ramsey, James B., 2013. "Bond vs stock market's Q: Testing for stability across frequencies and over time," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 138-150.
    7. P. Lakshmi & M. Thenmozhi, 2018. "Impact of foreign institutional investor trades in Indian equity and debt market: a three-dimensional analysis," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 45(3), pages 225-233, September.
    8. Jianhua Xu & Yaning Chen & Weihong Li & Qin Nie & Chunan Song & Chunmeng Wei, 2014. "Integrating Wavelet Analysis and BPANN to Simulate the Annual Runoff With Regional Climate Change: A Case Study of Yarkand River, Northwest China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(9), pages 2523-2537, July.
    9. Fernandez Viviana P, 2005. "The International CAPM and a Wavelet-Based Decomposition of Value at Risk," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(4), pages 1-37, December.
    10. Lin, Fu-Lai & Chen, Yu-Fen & Yang, Sheng-Yung, 2016. "Does the value of US dollar matter with the price of oil and gold? A dynamic analysis from time–frequency space," International Review of Economics & Finance, Elsevier, vol. 43(C), pages 59-71.
    11. Jia, Xiaoliang & An, Haizhong & Fang, Wei & Sun, Xiaoqi & Huang, Xuan, 2015. "How do correlations of crude oil prices co-move? A grey correlation-based wavelet perspective," Energy Economics, Elsevier, vol. 49(C), pages 588-598.
    12. Antonis Michis, 2015. "Multiscale Analysis of the Liquidity Effect in the UK Economy," Computational Economics, Springer;Society for Computational Economics, vol. 45(4), pages 615-633, April.
    13. Liow, Kim Hiang & Huang, Yuting & Song, Jeonseop, 2019. "Relationship between the United States housing and stock markets: Some evidence from wavelet analysis," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    14. Rothman Philip, 2016. "Introduction to Studies in Nonlinear Dynamics & Econometrics Issue in Honor of James B. Ramsey," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 343-346, September.

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