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Pedersen index

From Wikipedia, the free encyclopedia

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]

What the index means

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"The net change within the electoral party system resulting from individual vote transfers" [2]

Construction of the Index

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The Pedersen index is calculated as

  

where is the percentage of votes for political party at election and is the value for the next election. To calculate the index, the percentage gains of the winning parties must be determined. The resulting index will be between 0 (no parties gained, and thus no parties lost either) and 100 (all the parties from the last election were reduced to zero votes), because for every gain there is an equal (in terms of percentage of votes) loss. In other words, the index is equal to the net percentage of voters who changed their votes. ("Net percentage," because if the only change is a Party A voter switching to Party B, and a Party B voter switching to Party A, there is no net volatility.) The index can also be constructed by summing the absolute values of all gains and all losses, and dividing this total by two.

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.

Example

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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 Blue Orange Fuchsia
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

Countries

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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
 Argentina 2011 25.1
 Austria 2010 7.3
 Australia 2010 7.3
 Bolivia 2009 35.9
 Brazil 2010 18.2
 Bulgaria 2009 39.9
 Chile 2009 13.9
 Colombia 2010 15.9
 Costa Rica 2010 29.0
 Czech Republic 2010 27.7
 Dominican Republic 2010 32.3
 Ecuador 2009 33.0
 Estonia 2011 32.5
 El Salvador 2012 15.5
 Germany 2009 8.3
 Honduras 2009 7.8
 Hungary 2010 25.1
 Israel 2009 20.9
 India 2009 25.1
 Italy 2008 15.2
 Japan 2009 14.2
 Latvia 2011 36.4
 Lithuania 2012 39.7
 Macedonia 2011 32.0
 Malaysia 2008 13.7
 Mexico 2009 21.0
 Mongolia 2008 24.3
 Netherlands 2010 13.4
 Paraguay 2008 25.6
 Romania 2008 36.9
 Sweden 2009 8.4
 Singapore 2011 10.8
 South Korea 2012 29.3
 Taiwan 2012 16.9
 Thailand 2010 27.2
 Trinidad and Tobago 2011 25.1
 United Kingdom 2010 7.6
 United States 2010 3.4
 Uruguay 2009 14.6
 Venezuela 2010 34.5

References

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  1. ^ Pedersen's paper
  2. ^ W. Ascher and S. Tarrow, 'The Stability of Communist Electorates: Evidence from a Longitudinal Analysis of French and Italian Aggregate Data', American Journal of Political Science, 19/3 (1975), 48o-i.
  3. ^ Emanuele, Vincenzo. "Dataset of Electoral Volatility and its internal components in Western Europe (1945-2015)." (2015).
  4. ^ a b "Institutionalization of party systems: a cross-regional approach using the Weighted Volatility Index, Eduardo Olivares Concha, Prepared for the Political Studies Association 64th Annual International Conference, Manchester, 2014" (PDF).