Сравнительная политика (Nov 2016)
GDP PER CAPITA, PROTEST INTENSITY AND REGIME TYPE: A QUANTITATIVE ANALYSIS
Abstract
The study suggests that the relationship between per capita GDP and intensity of antigovernment demonstrations is not negative as tends to be believed; we are rather dealing with an inverted U-shaped relationship: the highest levels of antigovernment demonstration intensity are typical for countries with neither the lowest nor the highest values of GDP per capita, but rather with intermediate values of this indicator. Thus, for higher values of per capita GDP we observe a negative correlation between GDP per capita and the antigovernment demonstration intensity, and for lower values it is positive. This correlation is partly explained by the following points: (1) GDP growth in authoritarian regimes leads to increased pro-democracy movement, and hence to intensifi cation of the anti-government demonstrations. And since in our database (as well as in reality) authoritarian states constitute a very high percentage of the number of states with the lowest values of per capita income, the effect of the growth of internal pressure on authoritarian regimes towards democracy with economic growth to some extent (but no not completely) explains a strong correlation between GDP per capita and the intensity of antigovernment demonstrations for low and middle income countries. (2) In the range of per capita GDP up to $ 20000, the increase in per capita GDP is quite strongly correlated with a decrease in the proportion of authoritarian regimes and the increasing share of nonauthoritarian regimes (democratic and intermediate). The presence of non-authoritarian regimes in this range is signifi cantly positively correlated with the higher intensity of anti-government demonstrations. This is another mechanism that contributes to the presence of a strong positive correlation between GDP per capita and the intensity of anti-government demonstrations in the range of interest to us. At the same time we have done a further analysis that has shown that both of the above mechanisms do not explain the correlation in question to the full, which means the need to find additional mechanisms and factors.
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