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

Almasri, Abdullah LU and Shukur, Ghazi (2003) In Journal of Applied Statistics 30(5). p.571-584
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... (More)
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. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Journal of Applied Statistics
volume
30
issue
5
pages
571 - 584
publisher
Carfax Publishing
external identifiers
  • wos:000181842100007
  • scopus:0037409940
ISSN
0266-4763
DOI
10.1080/0266476032000053682
language
English
LU publication?
yes
id
bbaaeb15-edaf-4d1c-9903-8f723468dbe3 (old id 315181)
date added to LUP
2007-08-02 10:48:13
date last changed
2018-08-19 04:08:49
@article{bbaaeb15-edaf-4d1c-9903-8f723468dbe3,
  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.},
  author       = {Almasri, Abdullah and Shukur, Ghazi},
  issn         = {0266-4763},
  language     = {eng},
  number       = {5},
  pages        = {571--584},
  publisher    = {Carfax Publishing},
  series       = {Journal of Applied Statistics},
  title        = {An illustration of the causality relation between government spending and revenue using wavelet analysis on Finnish data},
  url          = {http://dx.doi.org/10.1080/0266476032000053682},
  volume       = {30},
  year         = {2003},
}