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Regular version of the site

Laboratory for Qualitative and Quantitative Methods of Analysis of Political Regimes

Laboratory сompleted its work

Laboratory for Qualitative and Quantitative Methods of Analysis of Political Regimes was founded in 2009 on the basis of Basic Research Program at Higher School of Economics. First, the Laboratory was established for the realization of Basic Research Projects concerned with governance, state capacity and regime transformation. From 2010 till 2013 the Laboratory was run by Prof. Andrei Melville. In 2014 Prof. Andrei Akhremenko became the director of the Laboratory.

The key research field of the Laboratory has been always related with political regimes, regime peculiarities, causes and consequences of regime transformations. Prerequisites of democracy have been a source of intensive debate in the social sciences. Though being studied for millennia the concept of the state provokes waves of debates every time it acquires new attributes under internal and external pressures. The “third wave of democratization” gave rise to a variety of regimes. Some 30 years ago the former communist countries displayed immense similarities but today their trajectories of political and economic development are very different from each other and can be classified into distinct groups. Thus exploring the relationship between stateness/state capacity and the trajectories of political development became the research grounds for the Laboratory’s activity.

Interactions of stateness, governance (good governance and good enough governance), state capacity and institutional quality have become one of the mainstreams in contemporary political science. Thus, the topicality of the basic analyzed concepts is to be found in the context of comparative institutional analysis. In this case it is quite important to understand the conditions of institution transplantation and the ideas of how to make this process more effective and efficient. Therefore, the next step in the Laboratory’s agenda has touched the concepts of efficiency and effectiveness, interactions between efficiency and quality of governance and the comparison of efficiency level in various regime types.

The current research project was launched in 2014 and has been prolonged for 2015. The main goal of the research is to explore theoretically and empirically the impact of feedback loops between the state and the society within the fields of budget redistribution and stable economic growth in democratic, hybrid and autocratic political regimes.

One of the key objectives for the 2016 stage is finding fundamental factors that make political systems resilient against suboptimal policy. The results achieved in 2015 allow us to narrow down the search boundaries to regime characteristics closely connected to total factor productivity (TFP). TFP turned out to be the central factor connecting political institutions and economic growth, as the 2015 stage has shown. The upcoming new research aims at a deeper understanding of TFP via empirical studies.

The key feature of the Laboratory concept and of the current project is the implementation of a set of advanced quantitative methods (formal modeling, game-theoretical modeling and statistical and econometric methods of data analysis). The core idea is the combination of theoretical, formal theoretical and empirical analysis. Therefore, the Laboratory promotes the integration of various methodological approaches in political science, economics, mathematical modeling and statistics. Political science is represented by the new institutionalism, comparative analysis of political regimes and by theories of democratic / autocratic rule. Economics allows for the use of macroeconomic models and public capital theories. Dynamic mathematical models are investigated analytically (using the theory of differential equations) and with the help of numerical experiments. Game-theoretical models are studied via analytical search for Nash- and Markov equilibrium. The empirical analysis is represented by the set of advanced statistical and econometric methods (regression analysis, causal inferences and spatial econometric models).