The Pedersen index is a measure of political volatility in party systems. It was described by Mogens Pedersen in a paper published in 1979 entitled The Dynamics of European Party Systems: Changing Patterns of Electoral Volatility.[1]
"The net change within the electoral party system resulting from individual vote transfers"[2]
The Pedersen index is calculated as
V=
1 | |
2 |
n | |
\sum | |
i=1 |
|pi,t-pi,t+1|,
where
pi,t
i
t
pi,t+1
The political volatility measured by the Pedersen index differs from the political volatility when parliamentary seats are considered due to the differing seats-to-votes ratios. The Pedersen index can overestimate the political volatility for countries with newly formed parliamentary groups made of previously existing political parties. Other measures[3] differ in their estimates of political volatility.
Assume that in the first election the Blue Party won 65%, the Orange Party won 25%, and the Fuchsia Party won 10%. Furthermore, assume that in the second election the Blue Party won 65%, the Orange Party won 15%, and the Fuchsia Party won 20%.
Election\Party | ||||
---|---|---|---|---|
1st | 65% | 25% | 10% | |
2nd | 65% | 15% | 20% | |
Gain/Loss | 0 | -10 | 10 |
The index would be equal to Blue gains (none) plus Orange's loss (10% since we do not consider sign differences) plus Fuchsia gains (10%). We then multiply it by 1/2 or divide by 2 for a total volatility of 10%.
If all three parties had disappeared in the next election, and been replaced by the Red Party (75%) and the Black Party (25%), the volatility would have been 100%: The first three lose all (100%) + the Red Party gaining 75% and the Black Party 25% since the previous election (when they both received no votes.) 100+100 = 200 -> divide by 2 = 100
The Pedersen indices for individual countries[4] are listed below, only the last available index is shown. The Pedersen index tends to decrease for some countries with increasing number of consecutive elections.[4]
Country | Year | Pedersen index | |
---|---|---|---|
2011 | 25.1 | ||
2010 | 7.3 | ||
2010 | 7.3 | ||
2009 | 35.9 | ||
2010 | 18.2 | ||
2009 | 39.9 | ||
2009 | 13.9 | ||
2010 | 15.9 | ||
2010 | 29.0 | ||
2010 | 27.7 | ||
2010 | 32.3 | ||
2009 | 33.0 | ||
2011 | 32.5 | ||
2012 | 15.5 | ||
2009 | 8.3 | ||
2009 | 7.8 | ||
2010 | 25.1 | ||
2009 | 20.9 | ||
2009 | 25.1 | ||
2008 | 15.2 | ||
2009 | 14.2 | ||
2011 | 36.4 | ||
2012 | 39.7 | ||
2011 | 32.0 | ||
2008 | 13.7 | ||
2009 | 21.0 | ||
2008 | 24.3 | ||
2010 | 13.4 | ||
2008 | 25.6 | ||
2008 | 36.9 | ||
2009 | 8.4 | ||
2011 | 10.8 | ||
2012 | 29.3 | ||
2012 | 16.9 | ||
2010 | 27.2 | ||
2011 | 25.1 | ||
2010 | 7.6 | ||
2010 | 3.4 | ||
2009 | 14.6 | ||
2010 | 34.5 |