Monthly Archives: June 2015

Which country has the most illiberal democracy in the world?

The most recent edition of Freedom House’s Freedom in the World noted a “disturbing decline in global freedom in 2014.” A driver of this appears to have been not necessarily a shift to totalitarian dictatorships, but a more relative illiberalization of democracies. For example, in one NBER working paper, Sergei Guriev and Daniel Treisman note that:

“in recent decades, a less carnivorous form of authoritarian government has emerged, one better adapted to the globalized media and sophisticated technologies of the 21st Century. From the Peru of Alberto Fujimori to the Hungary of Viktor Orban, illiberal regimes have managed to consolidate power without isolating their countries from the world economy or resorting to mass killings.”

Economists Dani Rodrik and Sharun Mukhand further point out the relative scarceness of liberal democracies around the world. In November 2014, Joseph Stiglitz told an audience at the Central European University that “[t]he conscious development of a learning society, essential for shared prosperity, can only be achieved in a liberal democracy”. 

So what is a liberal democracy? The answer to that question is could probably fill a bookshelf by itself. The simplest definition, as given by Wikipedia is the following:

“Liberal democracy is a form of government in which representative democracy operates under the principles of liberalism, i.e. protecting the rights of the individual, which are generally enshrined in law.”

Rodrik and Mukhand tie this a bit more to matters conducive to economic development:

“Liberal democracy rests on three distinct sets of rights: property rights, political rights, and civil rights. The first set of rights protects owners and investors from expropriation. The second ensures that groups that win electoral contests can assume power and choose policies to their liking – provided these policies do not violate the other two sets of rights. Finally, civil rights guarantee equal treatment before the law and equal access to public services such as education.”

These sound like fairly straightforward definitions, but when it comes to measurement, it quickly becomes complicated. Freedom House, for example, explicitly calculates values for “political rights” and “civil rights” for all individual countries each year, yet these are also measures used for “democracy”, not just “liberal democracy”. So is more “democracy” the same as more “liberal democracy”? (Also, for measures of “expropriation” from other sources it is not always clear if it’s from the perspective of a foreign investor or a domestic one.)

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How Turkey’s social conservatives won the day for HDP

(Note: This post has been updated to 1) add Istanbul to the provinces where Kurdish parties were active in 2011, 2) adding the other large cities Ankara, Izmir, Bursa, and Adana to the neighborhood-level analysis, and 3) adding graph of partial correlation between Refah vote share in 1995 and HDP vote swing in 2015.)

Given yesterday’s tumultuous election in Turkey, I thought it might be a good idea illustrate using the data available what just happened.

There’s the obvious: AKP lost about 10 percentage points of its vote share, and the Kurdish-and-what-not HDP received around 13 percentage points, pushing it above the ten percent threshold, allowing it to take seats in parliament – as far as I know, the first time a political party with such a clear pro-Kurdish constituency has done so. This means AKP’s seats in parliament fell from the 327 it won in 2011 down to 258.

Then there’s what it all means, which there’s no way I can discuss in one post. Instead I want to focus specifically here on the HDP and what kind of electorate brought it above the ten percent threshold.

Some herald Demirtaş. the HDP, and its electoral success as the comeback of the left or liberalism (here and here), noting amongst others his supportive stance toward the LGBT community as well as his background as a human rights lawyer. It is not for nothing that many refer to him as “Kurdish Obama”.

A following question is then to what extent HDP’s electoral success is a manifestation of the voting power of progressives and liberals in Turkey?

Despite talk of “borrowed votes”, i.e. strategic voting by (I assume) predominantly traditional CHP supporters, an initial look at the election suggests that what pushed HDP into parliament was a shift among traditional right-wing voters – the socially conservative Kurdish communities in the East and some living in the large cities who abandoned the AKP for the HDP.

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Pandora’s Ballot Box and Turkey: Kurdish edition

I recently (finally) had the chance to take a look at the Turkish presidential elections data from August 2014, with the aim of comparing some of the measures of election irregularities I documented from the earlier local elections in March of the same year. The analysis from those elections were essentially a snapshot of potential irregularities with little to say about how this evolved over time.

What I focused on last year was the rather peculiar degree with which the share of invalid ballots appeared to be positive correlated, at the ballot-box level within voting stations, with AKP vote shares (or rather the vote share difference between the AKP and the largest opposition party). Now, with the presidential elections data, I can compare how this correlation differs between that election and the local elections. As for the interpretation of the correlations, here’s what I wrote in April last year:

“An obvious question mark in the analysis is to what extent any correlation represents systematic mistakes, not systematic fraud. Suppose the AKP has a higher support among the illiterate who are more likely to make mistakes when voting. In this case, we would not be surprised if there was a correlation between invalid ballots and AKP support. An explanation would be that those more likely vote for the AKP are also those more likely to make voting mistakes and have their ballots declared invalid. Given the large difference across districts in the large cities in Ankara and Istanbul, one can easily imagine this as a plausible explanation for the simple unconditional correlations.

It is here that the fixed effects used in the previous analysis becomes crucial, i.e.  including fixed effects (FEs) to regressions of vote shares on invalid ballots control for all factors that vary across the FEs. Adding FEs for districts (Ilce) means we’re only looking at variation across ballot boxes within districts, whereas adding FEs for voting station means only looking at variation across ballot boxes within voting stations.

When doing this, although voters going to the same station to vote may still differ along several characteristics, it is much more difficult to argue that this systematically affect their likelihood of making mistakes in voting. The strength of the FEs is thus not that they control for everything, but that they reduce these differences to the point where it is less likely that the remaining differences represent an competing explanation for the correlation.

Furthermore, to the extent that this represent fraud, one would expect the relationship between AKP’s vote share and invalid ballots to be stronger in races with significant competition and less likely in races where the AKP was safe. (For the obvious reason that there is little return to engaging in fraud in races where you’re expected to win without fraud.)”

Below I show such correlations between the AKP’s vote share and the invalid share of ballots, with red representing the August presidential elections and blue representing the local elections. These are essentially the same kind of graphs as the first set of ones I posted here, the main difference being that I now from the start subtract the voting station means from the ballot-box level data. Another difference is that instead of plotting the raw voting data (which, with large amounts of data, makes graphs overly crowded and visually less attractive) I’m plotting equal-sized binned means – essentially a scatterplot of grouped data, with groups made up of equally large number of observations (see here for an easy way to implement such grouped scatterplots in Stata).

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