By Sean O'Connor
Over the years this blog has looked at funding received by Irish sports clubs distributed by the Department of Transport, Tourism and Sport or its various different name groupings throughout the years. Various different pieces have examined different areas (here , here, here). Moreover, beyond this blog and within the academic literature Irish sports capital grant allocations have been focused on extensively. A common finding which tends to emerge amongst various studies is that those who control the purse strings tend to award their locality disproportionately. In essence the presence of pork barrel politics.
However, during my time reading various pieces on this topic I’ve never seen this data presented under the guise of the GINI coefficient. Developed by the Italian statistician and sociologist Corrando Gini, the Gini coefficient examines the measures of inequality amongst values of a frequency distribution. Most commonly what the measure is utilised for is the examination of income or wealth inequality. Its value can range from 0 to 1, where 1 would indicate that one person in the population controls all the income. Conversely a value of 0 would imply perfect equality, where the entire population has an equal spread of wealth or income. For example, according to the OECD Ireland’s GINI coefficient score in 2014 was 0.30 whereas in the United States for the same period it was 0.39. Therefore income was more unevenly distributed in the United States than Ireland.
This piece will look at inequality in the distribution of Ireland’s sports capital grants over the period 2002-2015. To begin, Table 1 presents the GINI coefficients for the entire country over the different years.
Over the years this blog has looked at funding received by Irish sports clubs distributed by the Department of Transport, Tourism and Sport or its various different name groupings throughout the years. Various different pieces have examined different areas (here , here, here). Moreover, beyond this blog and within the academic literature Irish sports capital grant allocations have been focused on extensively. A common finding which tends to emerge amongst various studies is that those who control the purse strings tend to award their locality disproportionately. In essence the presence of pork barrel politics.
However, during my time reading various pieces on this topic I’ve never seen this data presented under the guise of the GINI coefficient. Developed by the Italian statistician and sociologist Corrando Gini, the Gini coefficient examines the measures of inequality amongst values of a frequency distribution. Most commonly what the measure is utilised for is the examination of income or wealth inequality. Its value can range from 0 to 1, where 1 would indicate that one person in the population controls all the income. Conversely a value of 0 would imply perfect equality, where the entire population has an equal spread of wealth or income. For example, according to the OECD Ireland’s GINI coefficient score in 2014 was 0.30 whereas in the United States for the same period it was 0.39. Therefore income was more unevenly distributed in the United States than Ireland.
This piece will look at inequality in the distribution of Ireland’s sports capital grants over the period 2002-2015. To begin, Table 1 presents the GINI coefficients for the entire country over the different years.
For the earliest period where information was available the GINI coefficient stood at 0.56, with the distribution of grants becoming more equal throughout the years. This trend stopped in 2008 with a large spike in the score to 0.62. However, with the reintroduce of the sports capital grant process in 2012 we see a continued decrease year on year, where in 2015 it stood at 0.51. If we where to compare this to a countries income inequality, this value would rank alongside the likes of Brazil or Honduras in terms of unequal distribution. Similar to differences in years there may also be differences amongst counties and within counties during different periods. Therefore, Table 2 extends the analysis to calculate county and year specific GINI coefficients.
Initially, if we take an average of each GINI score over the entire period, Dublin, Cork and Limerick ranked first, second and third in terms of within county grant inequality over the period. Amongst these three counties, Limerick in 2008 recorded the highest GINI score with 0.76. In fact, Limerick had the most unequal distribution of grants in a number of years, 2003, 2007 and 2008. On the opposite end of the spectrum, Cavan over the entire period had the most even distribution of capital grants 0.34. Over the entire period and amongst all counties, Monaghan recorded the most equal distribution of grants in 2003 with a GINI score of 0.16.
Finally, what is interesting to look at is the ranking of GINI scores of the counties where the Minister of Sport was based. As was noted in the beginning from previous analysis, these counties tend to perform particularly well, relative to others. However, how do they rank in terms of the distribution of grants? Table 3 plots the ranks.
Finally, what is interesting to look at is the ranking of GINI scores of the counties where the Minister of Sport was based. As was noted in the beginning from previous analysis, these counties tend to perform particularly well, relative to others. However, how do they rank in terms of the distribution of grants? Table 3 plots the ranks.
Note: Values in bold indicate when Minister of Sport came from this county
What is interesting when examining the ordinal rankings of the data is it appears that the distribution of grants within a county become more equal towards the end of a Minister’s reign. Take for instance in both Kerry and Mayo, where in 2004 and 2005 Kerry ranked fourth and seventh in terms of within county grant inequality. However, for Minister O’Donoghue’s final announcement of grants the spread became much more equal within Kerry. A similar trend seemed to appear in Mayo, however, it is difficult to infer any conclusion from a descriptive examination of the data and a more empirical study would be necessary.
A follow up piece to this blog will examine the distribution of grants amongst different types of sports over the same period.
RSS Feed