Экономика России. Ежемесячный обзор
Вып. 1: На грани предсказуемости. М.: Sberbank CIB, 2016.
Евгений Гавриленков, Антон Струченевский, Сергей Коныгин
Under the general editorship: Евгений Гавриленков
Евгений Гавриленков, Антон Струченевский, Сергей Коныгин М.: Sberbank CIB, 2015.
Added: Aug 13, 2015
Гимпельсон В. Е. Проблемы рынка труда. WP3. Высшая школа экономики, 2002. № 01.
Added: Mar 26, 2013
Smirnov S. V., Kondrashov N. V. Economics. EC. Высшая школа экономики, 2017. No. 169.
Regional statistics published by the Russian Federal State Statistics Service (Rosstat) are reviewed in terms of quality, and radical disagreement between “month-on-month” and “year-on-year” monthly statistics is identified. In view of this, an original method is proposed for estimating the level of Regional Economic Activity (REA), based on monthly official regional statistics in five key sectors of the Russian economy: industry, construction, retail trade, wholesale trade, and paid services for the population. This method transforms current “year-on-year” growth rates into specially constructed dichotomous variables, which eliminate the excessive volatility and inaccuracy of the initial time series. On these grounds, REA indices are estimated for all Russian constituent entities for the period from January 2005 to May 2017. Composite REA indices for all five economic sectors, eight federal districts, and Russia as a whole are then calculated. Methods for visualising multidimensional regional data are also proposed. They allow us to track the regional peculiarities of the Russian economy and to discern the current phase of the business cycle more accurately and without any additional lag. Several illustrative examples for the possible application of these indices in real time monitoring and analyses are provided.
Added: Aug 9, 2017
Евгений Гавриленков, Антон Струченевский, Сергей Коныгин М.: Sberbank CIB, 2016.
Added: Aug 11, 2016
Хасянова С. Ю., Егоров Ф. В. В кн.: Современные проблемы в области экономики, менеджмента, бизнес-информатики, юриспруденции и социально- гуманитарных наук. Материалы IV научно- практической конференции студентов и преподавателей НФ ГУ-ВШЭ. Н. Новгород: Нижегородский государственный технический университет им. Р.Е. Алексеева, 2006. С. 32-36.
Added: Dec 16, 2012
Мазин А. Л., Мазина Анна Александровна Человек и труд. 2011. № 2. С. 11-16.
Added: Nov 17, 2011
Евгений Гавриленков, Антон Струченевский, Сергей Коныгин Вып. 10: Пессимистичные бюджетные прогнозы угрожают инвестициям. М.: Sberbank CIB, 2015.
Added: Aug 11, 2016
Антон Струченевский Cbonds Review. 2013. № 9.
Added: Feb 12, 2014
Смирнов С. В. Экономическое обозрение ЕврАзЭс+. 2007. № 1. С. 11-14.
Added: Dec 18, 2014
Российский финансовый кризис: почему девальвация рубля сопровождалась дефолтом по государственному долгу?
Shpringel V. K. Исследования по экономике и финансам. WP9. Высшая школа экономики, 2005. No. 03.
Using an original currency crisis model we show that mistakes in monetary and fiscal policy could explain the origins and roots of the Russian financial crisis of 1998. A combination of high interest rates with high sensitivity of inflation rate to the rate of currency depreciation, low duration of debt and low GDP monetization together resulted in exchange rate appreciation and rapid accumulation of domestic-currency debt. When the debt became too high to service, investors started to flee. Protective interest rate hike by the monetary authorities was counterproductive, accelerating the approach of the crisis via the growth in the debt-servicing payments and GDP contraction. The budget restriction of 3% of GDP, used in EC countries, was too loose for Russia in the pre-crisis period.
Added: Mar 18, 2013
Экономика и управление: проблемы и перспективы развития. Сборник научных статей по итогам международной научно-практической конференции г.Волгоград 15-16 ноября 2010 г.
Ч. 1. Волгоград: Волгоградское научное издательство, 2010.
Added: Jan 18, 2013
Anisimova A. I., Muradyan P. A., Vernikov A. V. SSRN Working Paper Series. Social Science Research Network, 2011. No. 1919817.
This empirical paper adds to competition and industrial organization literature by exploring the interplay between industry structure and competitiveness on local, rather than nation-wide, markets. We use micro-level statistical data for banks in two Russian regions (Bashkortostan and Tatarstan) to estimate Herfindahl-Hirschman index, Lerner index, and Panzar-Rosse model. We estimate Panzar-Rosse model in two ways: via the widely used price-equation that accounts for scale effects and then via a revenue-equation that disregards scale effects as suggested by Bikker et al. (2009). We find both regional markets to be ruled by monopolistic competition, although estimation by revenue-equation does not reject monopoly hypothesis for Tatarstan. Existence of sizeable locally-owned and operated institutions does not necessarily lead to higher competitiveness of the given regional market, and the results from non-structural methods of estimation suggest that bank competition in Bashkortostan is stronger than in Tatarstan. Going further away from aggregated analysis we compute Lerner indices in two product segments of Tatarstan – retail and corporate loans – and find that retail segment is significantly more competitive. Local banks exert more market power in corporate loans, while federal branches – in retail loans.
Added: May 14, 2012
Added: Feb 22, 2013
Трунин П. В., Дробышевский С. М., Евдокимова Т. В. М.: Издательский дом «Дело» РАНХиГС, 2012.
Added: Mar 26, 2013
Яковлев А. А. Общественные науки и современность. 2008. № 4. С. 21-37.
Added: Sep 22, 2012
Penikas H. I. Financial Economics. FE. Высшая школа экономики, 2012. No. 03.
The Basel Committee of Banking Supervision initiated a discussion on the most efficient practices to prevent bank managers from excessive risk-taking. This paper proposes a game-theoretical approach, describing the decision-making process by a bank manager who chooses his own level of risk and effort. If the level of risk implies the variability of the future outcome, the amount of effort applied affects the probability of a positive outcome. Although effort is unobserved for the bank’s stakeholders, the risk level is under control, and is associated with certain indicators such as capital adequacy ratio or leverage level. The risk-neutral utility function of a bank manager and a binary game outcome of gaining profit or loss for a bank are assumed. Starting from the general incentive contract scheme having the fixed and variable parts of remuneration, it is proposed that differentiating the variable part of remuneration is sufficient to motivate bank managers to make fewer risky decisions. More precisely, the variable part of remuneration (e.g. the share of the bank’s profit) needs to be higher in proportion to the higher variance of outcome for the high -risk outcome case to stimulate a bank manager to opt for lower-risk decisions in place of higher-risk situations.
Added: May 3, 2012
Уринсон Я. М. Вестник Европы. 2014. № 38-39.
Added: Feb 5, 2018
Penikas H. I., Titova Y. Financial Economics. FE. Высшая школа экономики, 2012. No. 02.
In this paper we elaborate a simple model that allows for the predicting of possible reactions from financial institutions to more stringent regulatory measures introduced by the Basel Committee on Banking Supervision (BCBS) in regard to global systemically important banks (G-SIBs). The context is framed by a 2011 BCBS document that proposes higher capital requirements for global systemically important banks. We attempt to analyze bank interactions in an oligopolistic market that is subject to demand constraints on loan amounts and additional loss absorbency requirements introduced by the regulator. We distinguish between the bank’s announced funding cost that determines both the loan amount issued and the market interest rate, and the bank’s true funding cost that has a direct impact on retained earnings. We conclude that in a two-stage game both banks will announce the highest funding cost, thus reducing the amount of loans granted (in line with the regulator’s objective), but at the expense of a higher cost of borrowing established in the market. If the game is repeated, then both banks also choose lower loan amounts in the periods prior to the last one in which the declared funding cost is the lowest possible. It should be noted that the designated outcome also coincides with the findings of the Monetary Economic Department of the Basel Committee on Banking Supervision.
Added: May 3, 2012
Added: Jun 24, 2011