Lower Taxation Leads to Higher Economic Growth Within the European Union - Case Study Example

Lower taxation leads to higher economic growth within the European Union Name: Date: Course Professor: Introduction The European Union (EU) was formed by members of the European community in 1993 following the ratification of the Maastricht treaty. The major aim was to forge a closer economic and political union (IBP 2013 p 247). The formation of the EU led to the establishment of a central European bank and enactment of the Euro (a common currency for the region). Its membership is drawn from Austria, Belgium, Bulgaria, Cyprus, the Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, the Netherlands, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, and the UK. One of its major aims was to come up with a common market which was free of barrier amongst the member states. Amongst the member states, it there is free movement of goods, services, persons and capital. Economic growth refers to the expansion in an economy on the basis of changes that occur in the gross domestic product. It is the positive increase in the market value of the goods and services that an economy produces. Economic growth is commonly measured in inflation adjusted terms (real terms) to cater for the effect of inflation on the prices of the goods and services that are produced. The EU does not determine the rates of taxation for its member states. Each state has the prerogative to decide on the suitable tax rate for their economy. It takes proper functioning of a tax system to realize economic growth. A good tax system should be embrace sound national tax policies that are suitable for growth and fiscal sustainability (International Monetary Fund. 2012 p. 29). It should also aim at avoiding and correcting the imbalances in macroeconomic functioning which may impede economic growth. The impact of tax on economic growth has not been easy to compare, this is due to lack of direct statistics. This difficulty is also propagated by persistent fluctuations in the variables that compose the data base. Inter-jurisdiction variations have also made it an uphill task to come up with clear-cut ways of conducting the analysis between the EU member states. Types of taxes Total taxes are presumed to be made up of taxes charged on production activities, imports, current taxes on income and wealth, capital taxes, actual compulsory social contributions (Viitala, 2005 p. 127). It would be summarized that it is made up of indirect taxes, direct taxes and social contributions that are received by the general government and the institutions of the EU. Real (payable) taxes are deemed to be the difference between total taxes and the actual compulsory social contributions (Richelle etal 2013 p 100 -106). Indirect taxes are majorly linked to production and imports. They are compulsory levies on production units due to production and or importation of goods and services or the use of factors of production. Indirect taxes include: VAT, import duties, excise duties, taxes on services like transport, insurance tax on production, also included are taxes that enterprises incur as a result of engaging in production like professional fees. Direct taxes include taxes on income and wealth together with taxes on inheritances and gifts (Viitala, 2005 p. 129) It was in the interest of the question to analyze the relationship between low tax rate and economic growth. Lower taxation would be the independent variable while higher economic growth would be the dependant variable being determined by the rate of taxation. Because of the close relationship that exists between economic growth and poverty and income inequalities, I will carry out my economic analysis based on the statistics from the European Union on poverty and the rates of taxation. Most of the literature that analyses economic growth between countries is most often based on gross domestic product.GDP only highlights in monetary terms the comparative richness between countries and fails to take cognizance of the distribution of income within the country. GDP does not also acknowledge the non monetary factors that are key determinants of the kind of life that is led by the population.014 edition Another basis for the assessment of the performance of the tax systems is the Lisbon Assessment Framework (LAF) (Marlier & Natali 2010 p. 259). The framework comprised of a national implementation grid, database for labor reforms, assessment tools for key reform drivers and a macro modeling exercise (p 259). A member state is presumed to be a poor performer if the bench mark puts it among the last poor performers. A member state is considered to be significantly worse if it falls at -0.4 deviations below the EU average. This approach is however a bit restrictive if compared to the weighted GDP approach (Barro, 2008 p 19 - 22). However a more elaborate approach that engages several indicators need to be put in place to critically come up with whether a member state is facing challenges in a particular area of taxation. This approach basing on LAF does not take into account the member states specificities and is therefore prone to wrong judgment because a country may be above LAF minus but still face challenges in a specific tax area. Countries which appear to be doing well according to this scale may also need some little policy adjustments. Table 1. EU member states included in EU-SILC longitudinal files (UDB Release 2008-1), and their persistent poverty rates in 2007 State % poverty State % poverty Austria (AT) 5.6 Cyprus (CY) 10.5 Belgium (BE) 9.0 Czech Republic (CZ) 3.9 Finland (FI) 6.7 Estonia (EE) 13.3 Ireland (IE) 12.2 Hungary (HU) 7.5 Italy (IT) 11.9 Latvia (LV) 12.2 Luxembourg (LU) 8.4 Lithuania (LT) 10.4 Netherlands (NL) 5.8 Poland (PL) 10.3 Norway (NO) 5.4 Slovenia (SI) 7.8 Portugal (PT) 13.1 Slovakia (SK) 4.9 Spain (ES) 11.0 Sweden (SE) 3.0 United Kingdom (UK) 8.4 Source: (Stephen and Philippe 2013 p 10). Based on the above statistics, the countries with the highest percentage poverty will be classified as experiencing low economic growths. On the other hand, the states with low poverty would be classified as undergoing high economic growth. This follows the presumed inverse relationship between economic growth and poverty levels. The assumption here therefore will be that states like Sweden at 3%, Czech Republic at 3.9%, Slovakia at 4.9% are the best performing states in terms of economic growth. According to this data, the worst performing economies in terms of low economic growth will be Estonia 13.3%, Portugal 13.1%, Ireland and Latvia at 12.2%. According to data that is available from Eurostat (taxation trends in the European Union) 2014, the percentage taxation for the states captured in the above data with low and high poverty levels were as follows Table 2: Low poverty (High Economic growth) states states Poverty % Total taxes including SSC as % of GDP Total tax excluding SSC as % of GDP Sweden 3 47.3 38.0 Czech Republic 3.9 35.9 20.2 Slovakia 4.9 29.3 17.6 Table 3: High poverty states (Low economic growth rates) States Poverty % Total taxes including SSC as % of GDP Total tax excluding SSC as % of GDP Latvia 12.2 30.6 21.9 Portugal 13.1 32.8 24.3 Estonia 13.3 31.4 21.0 Source: Eurostat 2014 pp 174 -175 (taxation trends in the European Union). The data in columns 3 & 4 are only extracts; the full table will be attached towards the end of the paper. CORRELATION AND REGRESSION In trying to assess the characteristics of tax wage, employment and unemployment rate in the EU, Primož Dolenc and Suzana Laporšek utilized a linear regression analysis with panel-correlated sample of 27 EU member states during the periods 1999 and 2008. The following regression model was used in the study. EGi t =α+ β.TWi t +Ԓ.macroenocomic control matrixi t + e i t where EG – employment growth, TW – tax wedge, macroeconomic control variables, e – error, i, t – country and time. It is worth noting that the regression model consisted of a panel-corrected standard error method so as to control contemporaneously correlated and panel heteroskedastic errors. Regression Table Studied group of countries Employment growth Coefficient S.E Z p>IZI EU-27 Tax wedge -0.043 0.009 -4.75 0.000 Potential GDP growth 0.354 0.124 2.85 0.004 Inflation rate -0.099 0.041 -2.41 0.016 Constant 2.047 0.545 3.76 0.000 R-squared 0.199 Source: (Dolenc and Laporšek, 2010, p.12). According to the regression analysis, an increase in tax wage by 1% decreases the employment growth in the EU-27 by around 0.04%, all factors held constant. Since employment was one of the determinant of economic growth, it is arguable right to conclude that high tax rate reduce the rate of economic growth as per the regression results above. Conclusion based on the data. The data in table 2 shows that where the percentage tax is high relative to GDP like in Sweden is the state which recorded the lowest rate of poverty indicator in the year 2007.This goes against the theory which states that lower taxation leads to high economic growth. This is true for both the categories of taxes. Considering the states which recorded the highest poverty indicators, Latvia which ranked third on the basis of poverty had a tax rate inclusive of SSC of 30.6%. This also contravened the fact that low tax rates lead high economic growths. Based on the data above it is not true that lower taxation rates would lead to higher economic growth which would be indicated by low poverty percentage levels. It is then justified to claim that there are a lot of other macro-economic factors that play crucial roles in determining economic growth apart from tax rates. The jurisdictional differences in terms of policies on taxation also make it difficult to compare growth in different states using the same indicators. Formulae Growth based on GDP. GDPcy - GDPby x 100% where GDPcy means GDP for the current year GDPby GDPby means GDP for the base year. Tax Rates Total taxes x 100% GDP References American Heritage Dictionary of the English Language,(2011) Fifth Edition. Houghton Mifflin Harcourt Publishing Company. Published by Houghton Mifflin Harcourt Publishing Company. Barro, R. J. (2008). Macroeconomics: a modern approach. Mason, Thomson. Bjork, Gordon J. (1999). The Way It Worked and Why It Won’t: Structural Change and the Slowdown of U.S. Economic Growth. Westport, CT; London: Praeger.. Current poverty. Centre for Analysis of Social Exclusion, London School of Economics Houghton Street, London . Eurostat statistical books, (2014).taxation trends in the European Union. Publications Office of the European Union, Luxembourg IBP,(2013). European Union Economic Partnership Agreements Handbook Volume 1 CARIFORUM …washington D.C International Monetary Fund. (2012). Philippines technical assistance report on road map for a pro. [S.l.], International Monetary Fu. Marlier, E. & Natali, D. (2010). Europe 2020: towards a more social EU? Bruxelles, P.I.E. Peter Lang. Richelle, I., Schön, W., & Traversa, E. (2013). Allocating taxing powers within the European Union. Berlin, Springer. http://dx.doi.org/10.1007/978-3-642-34919-5. Stephen P. J and Philippe V. K, (2013). The relationship between EU indicators of persistent and Taxation papers, (2012).Tax reforms in EU member states: Tax policy challenges for economic growth and fiscal sustainability. Working paper No. 34. Viitala, T. (2005). Taxation of investment funds in the European union. Amsterdam, International Bureau of Fiscal Documentation. Dolenc, P and Laporšek, S. (2010). Tax Wedge On Labour And Its Effect On Employment Growth In The European Union. 1 ed. London: PRAGUE ECONOMIC PAPERS. Read More