Мир. Вызовы глобального кризиса. Германия
The economic crisis of 2008-2009 highlighted new problems in the development of the German social market economy model and brought to the forefront the factors of its resilience that have ensured Germany's leadership positions in the EU. Changes in economic policy have affected in the ﬁrst place the energy and the ﬁnancial sectors. Shifts in the political landscape have led to the appearance of new political parties. These changes have affected the results of the 2013 elections, the liberal democrats failure to enter the Bundestag has made the winner - CDU - seek new coalition partners.
The analysis of competition policy during economic crisis is motivated by the fact that competition is a key factor in productivity levels. The latter, in turn, influences the scope and length of economic recession. In many Russian markets, buyers’ gains decline because of weak competition, since suppliers are reluctant to cut prices despite decreasing demand. Data on prices in Russia and abroad in the second half of 2008 show asymmetric price rigidity. At least two questions are important in an economic crisis: the “division of labor” between proactive and protective tools of competition policy and the impact of anticrisis policy on competition. Protective competition policy is insufficient in a transition economy, especially during a crisis, and it should be supplemented with well-designed industrial policy measures that do not contradict the goals of competition. The preferred tools of anticrisis policy are those that do not restrain competition.
We address the external effects on public sector efficiency measures acquired using Data Envelopment Analysis. We use the health care system in Russian regions in 2011 to evaluate modern approaches to accounting for external effects. We propose a promising method of correcting DEA efficiency measures. Despite the multiple advantages DEA offers, the usage of this approach carries with it a number of methodological difficulties. Accounting for multiple factors of efficiency calls for more complex methods, among which the most promising are DMU clustering and calculating local production possibility frontiers. Using regression models for estimate correction requires further study due to possible systematic errors during estimation. A mixture of data correction and DMU clustering together with multi-stage DEA seems most promising at the moment. Analyzing several stages of transforming society’s resources into social welfare will allow for picking out the weak points in a state agency’s work.