The paper analyses how the individuals' deposits influences the resources of Russian banks. We show that the depositors panic in the crisis has a serious effect on stability of both bank and national bank system. We show the tendencies how the volume and structure of individuals' deposits change; how to avoid the rash of withdrawals by individual depositors; and how the resources of Russian banks shrank because of such withdrawals happened in the period of the crisis. We also present our assessment of how the resources of Russian banks reduced because of the rash of withdrawals in the crisis.
We proposed the nonlinear dynamic model of the formation of the market prices of precious metals based on the econophysic considerations. This model is a system of three ordinary differential equations relating the time dependence of elasticity, variations of bid and ask prices; it is similar to the Lorenz system. The areas of the dynamic stochasticity in experimental data were found with the comparing of the experimental and the theoretical ask and bid prices. These areas are the precursors of the crisis mode in the form of dynamic chaos.
The conference was co-organised by the Center, the Department of Financial Law, Faculty of Law and Administration, University of Gdańsk, and the Department of Financial Law and Economics, Faculty of Law, Masaryk University in Brno. The cooperation of both departments has been ongoing for several years. On 24 November 2015, they signed a cooperation agreement. The Law faculties of both universities signed a similar agreement of broader scope as well. Since then, their cooperation has intensified and gradually evolved.
In 1921 Austria became the first interwar European country to experience hyperinflation. The League of Nations, among other actors, stepped in to help reconstruct the economy, but a decade later Austria’s largest bank, Credit-Anstalt, collapsed. Historians have correlated these events with the banking and currency crisis that destabilized interwar Europe—a narrative that relies on the claim that Austria and the global monetary system were the victims of financial interlopers. In this corrective history, Nathan Marcus deemphasizes the destructive role of external players in Austria’s reconstruction and points to the greater impact of domestic malfeasance and predatory speculation on the nation’s financial and political decline.
Consulting sources ranging from diplomatic dossiers to bank statements and financial analyses, Marcus shows how the League of Nations’ efforts to curb Austrian hyperinflation in 1922 were politically constrained. The League left Austria in 1926 but foreign interests intervened in 1931 to contain the fallout from the Credit-Anstalt collapse. Not until later, when problems in the German and British economies became acute, did Austrians and speculators exploit the country’s currency and compromise its value. Although some statesmen and historians have pinned Austria’s—and the world’s—economic implosion on financial colonialism, Marcus’s research offers a more accurate appraisal of early multilateral financial supervision and intervention.
Illuminating new facets of the interwar political economy, Austrian Reconstruction and the Collapse of Global Finance reckons with the true consequences of international involvement in the Austrian economy during a key decade of renewal and crisis.
The process of the IPO of banks in Russia is its infancy but the rapid growth is forecasted. This context raises the issue of the factors determining the floated banks stock value. The results of the research on 2007-2009 Russian data showed that the bank stock price is dependent on the macroeconomic indicators (such as the oil prices and the Dow Jones index volatility) and the some banking system indicators(the interbank interest rate, the bank’s ROA, and ROE). However, the results adjusted to the global financial crisis effect proved to exclude the ROE factor and showed the dependence of the stocks prices of the floated banks from the historic trend of the American economy. The models developed are of the practical application and can be used by the institutional as well as the private investors.
The Group of Eight (G8) has had extensive and even existential experience with financial crises (Kirton 2007). The groups creation was driven by financial crises created by and in the US, in the form of the Nixon Administration’s unilateral destruction of the Bretton Woods system of fixed exchange rates on August 15, 1971 and the imminent bankruptcy of New York City at the time of the first summit at Rambouillet in November 1975. Then came a succession of real and potential crises, notably Britain’s need for support from the International Monetary Fund (IMF) in the mid 1970s and Italy’s need in 1976, the developing countries debt crisis of the early 1980s, the American stock market plunge of October 1987, the attack on the European Monetary System (EMS), the Mexican peso crisis starting on December 20, 1994, the Asian-turned-global financial crisis of 1997–1999, the 9/11 terrorist attacks on America, the Enron–dot.com bust and the America-turned-global financial crisis from 2008 to now. Since the G8’s 1975 start, such crises have been created by others to afflict a vulnerable America, and been created by America to attack the rest of the world. In both cases such crisis have been conscious, calculated controlled and targeted, as on August 15, 1971 and September 11, 2001, and unco.nscious, uncalculated, uncontrolled and untargeted events characterized by contagion, complexity and uncertainty that no one can fully comprehend, as in the global crisis from 2008 until now.
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.