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An illustration of the causality relation between government spending and revenue using wavelet analysis on Finnish data

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  • Abdullah Almasri
  • Ghazi Shukur

Abstract

Quarterly data for the period 1960:1 to 1997:2, conventional tests, a bootstrap simulation approach and a multivariate Rao's F-test have been used to investigate if the causality between government spending and revenue in Finland was changed at the beginning of 1990 due to future plans to create the European Monetary Union (EMU). The results indicate that during the period before 1990, the government revenue Granger-caused spending, while the opposite happened after 1990, which agrees better with Barro's tax smoothing hypothesis. However, when using monthly data instead of quarterly data for almost the same sample period, totally different results have been noted. The general conclusion is that the relationship between spending and revenue in Finland is still not completely understood. The ambiguity of these results may well be due to the fact that there are several time scales involved in the relationship, and that the conventional analyses may be inadequate to separate out the time scale structured relationships between these variables. Therefore, to investigate empirically the relation between these variables we attempt to use the wavelets analysis that enables us to separate out different time scales of variation in the data. We find that time scale decomposition is important for analysing these economic variables.

Suggested Citation

  • Abdullah Almasri & Ghazi Shukur, 2003. "An illustration of the causality relation between government spending and revenue using wavelet analysis on Finnish data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(5), pages 571-584.
    • Handle: RePEc:taf:japsta:v:30:y:2003:i:5:p:571-584
    DOI: 10.1080/0266476032000053682
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    Cited by:

    1. el Alaoui, Abdelkader O. & Dewandaru, Ginanjar & Azhar Rosly, Saiful & Masih, Mansur, 2015. "Linkages and co-movement between international stock market returns: Case of Dow Jones Islamic Dubai Financial Market index," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 36(C), pages 53-70.
    2. Hacker, R. Scott & Karlsson, Hyunjoo Kim & Månsson, Kristofer, 2014. "An investigation of the causal relations between exchange rates and interest rate differentials using wavelets," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 321-329.
    3. Benhmad, François, 2013. "Dynamic cyclical comovements between oil prices and US GDP: A wavelet perspective," Energy Policy, Elsevier, vol. 57(C), pages 141-151.
    4. Haiyun Xu, 2016. "Economic policy uncertainty and housing returns in Germany: Evidence from a bootstrap rolling window," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 34(2), pages 309-332.
    5. Cifter Atilla & Ozun Alper, 2008. "Estimating the Effects of Interest Rates on Share Prices in Turkey Using a Multi-Scale Causality Test," Review of Middle East Economics and Finance, De Gruyter, vol. 4(2), pages 68-79, April.
    6. Cifter, Atilla & Ozun, Alper, 2007. "Estimating the Effects of Interest Rates on Share Prices Using Multi-scale Causality Test in Emerging Markets: Evidence from Turkey," MPRA Paper 2485, University Library of Munich, Germany.
    7. Benhmad, François, 2012. "Modeling nonlinear Granger causality between the oil price and U.S. dollar: A wavelet based approach," Economic Modelling, Elsevier, vol. 29(4), pages 1505-1514.
    8. Tiwari, Aviral Kumar, 2012. "Decomposing Time-Frequency Relationship between Interest Rates and Share Prices in India through Wavelets," MPRA Paper 39693, University Library of Munich, Germany.
    9. Månsson, Kristofer & Shukur, Ghazi & Sjölander, Pär, 2010. "A New Ridge Regression Causality Test in the Presence of Multicollinearity," HUI Working Papers 37, HUI Research.
    10. Heni Boubaker, 2016. "A Comparative Study of the Performance of Estimating Long-Memory Parameter Using Wavelet-Based Entropies," Computational Economics, Springer;Society for Computational Economics, vol. 48(4), pages 693-731, December.
    11. Stelios Bekiros, 2014. "Timescale Analysis with an Entropy-Based Shift-Invariant Discrete Wavelet Transform," Computational Economics, Springer;Society for Computational Economics, vol. 44(2), pages 231-251, August.
    12. Cengiz KARATAS & Gazanfer UNAL & Adil YILMAZ, 2017. "Co-movement and Forecasting Analysis of Major Real Estate Markets by Wavelet Coherence and Multiple Wavelet Coherence," Chinese Journal of Urban and Environmental Studies (CJUES), World Scientific Publishing Co. Pte. Ltd., vol. 5(02), pages 1-18, June.
    13. Dewandaru, Ginanjar & Bacha, Obiyathulla Ismath & Masih, A. Mansur M. & Masih, Rumi, 2015. "Risk-return characteristics of Islamic equity indices: Multi-timescales analysis," Journal of Multinational Financial Management, Elsevier, vol. 29(C), pages 115-138.
    14. A. Khalifa & S. Hammoudeh & E. Otranto, 2012. "Volatility Spillover, Interdependence, Comovements across GCC, Oil and U.S. Markets and Portfolio Management Strategies in a Regime-Changing Environment," Working Paper CRENoS 201209, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    15. Adil Yilmaz & Gazanfer Unal, 2016. "Co-movement analysis of Asian stock markets against FTSE100 and S&P 500: Wavelet-based approach," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 3(04), pages 1-19, December.
    16. Atilla Cifter & Alper Ozun, 2008. "Multiscale Systematic Risk: an Application on the ISE-30," Istanbul Stock Exchange Review, Research and Business Development Department, Borsa Istanbul, vol. 10(38), pages 1-24.
    17. Xiaojie Xu, 2018. "Causal structure among US corn futures and regional cash prices in the time and frequency domain," Journal of Applied Statistics, Taylor & Francis Journals, vol. 45(13), pages 2455-2480, October.
    18. Yousefi, Shahriar & Weinreich, Ilona & Reinarz, Dominik, 2005. "Wavelet-based prediction of oil prices," Chaos, Solitons & Fractals, Elsevier, vol. 25(2), pages 265-275.
    19. Yilmaz, Adil & Unal, Gazanfer & Karatasoglu, Cengiz, 2016. "Wavelet Based Analysis Of Major Real Estate Markets," MPRA Paper 74083, University Library of Munich, Germany.
    20. Alzahrani, Mohammed & Masih, Mansur & Al-Titi, Omar, 2014. "Linear and non-linear Granger causality between oil spot and futures prices: A wavelet based test," Journal of International Money and Finance, Elsevier, vol. 48(PA), pages 175-201.
    21. Chiara Perricone, 2018. "Wavelet analysis for temporal disaggregation," CEIS Research Paper 444, Tor Vergata University, CEIS, revised 29 Oct 2018.
    22. Almasri, Abdullah & Shukur, Ghazi, 2006. "Clustering Using Wavelet Transformation," CAFO Working Papers 2006:3, Linnaeus University, Centre for Labour Market Policy Research (CAFO), School of Business and Economics.
    23. Masih, Mansur & Alzahrani, Mohammed & Al-Titi, Omar, 2010. "Systematic risk and time scales: New evidence from an application of wavelet approach to the emerging Gulf stock markets," International Review of Financial Analysis, Elsevier, vol. 19(1), pages 10-18, January.
    24. Xiaojie Xu, 2018. "Intraday price information flows between the CSI300 and futures market: an application of wavelet analysis," Empirical Economics, Springer, vol. 54(3), pages 1267-1295, May.

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