Макроэкономика : учебник для бакалавриата и специалитета
The welfare analysis of the monetary policy has been in the centre of macroeconomics since the Great Depression. Empirical observations of the Phillips curve suggest that prices are sticky in the short run and, therefore, the monetary policy may be used to smooth the business cycle and increase social welfare.
In an open economy where foreign shocks may be passed into the domestic economy the task of the monetary policy becomes even more complicated. Under high pass-through of exchange rate onto the domestic prices, monetary policy stops to be independent and should adjust to exchange rate shocks. Such a policy of smoothing exchange rate fluctuations is common in western economies (e.g. [Parsley, Popper, 1998]).
The problem of optimal monetary policy is extremely relevant for Russia. Although the monetary authority claims that inflation targeting is the main goal of the monetary policy, empirical finding suggest that the real exchange rate targeting is of major importance [Vdovichenko, Voronina, 2004]. Due to the rising flow of petrodollars, Rouble is experiencing significant real appreciation recently. But the fear to loose exports makes the monetary authority respond to this real appreciation by accumulating dollar reserves and increasing the money supply, thus preventing the nominal appreciation. Such policy leads to high inflation and benefits of some interested groups at the expense of others. That is why the optimal degree of intervention is in the centre of all political and economic discussions nowadays.
Recent empirical literature finds that prices are more sticky downwards than upwards. This effect it called «asymmetric price rigidity» and may result from money illusion of workers, collusive behaviour of firms or search behaviour of consumers. Therefore, in this paper we propose a model in which we assume downward price rigidity and determine the optimal monetary policy in case of positive and negative exchange rate shocks. We claim that while depreciation of the domestic currency should be accompanied by a significant rise in the interest rate, its appreciation of the same size should be accompanied by a much smaller cut in the interest rate. Then we test this claim on the Russian data.
The paper examines the structure, governance, and balance sheets of state-controlled banks in Russia, which accounted for over 55 percent of the total assets in the country's banking system in early 2012. The author offers a credible estimate of the size of the country's state banking sector by including banks that are indirectly owned by public organizations. Contrary to some predictions based on the theoretical literature on economic transition, he explains the relatively high profitability and efficiency of Russian state-controlled banks by pointing to their competitive position in such functions as acquisition and disposal of assets on behalf of the government. Also suggested in the paper is a different way of looking at market concentration in Russia (by consolidating the market shares of core state-controlled banks), which produces a picture of a more concentrated market than officially reported. Lastly, one of the author's interesting conclusions is that China provides a better benchmark than the formerly centrally planned economies of Central and Eastern Europe by which to assess the viability of state ownership of banks in Russia and to evaluate the country's banking sector.
The paper examines the principles for the supervision of financial conglomerates proposed by BCBS in the consultative document published in December 2011. Moreover, the article proposes a number of suggestions worked out by the authors within the HSE research team.
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.