Ekonomika 2012 91(1)

This article deals with the operations of alternative investment funds (AIF) and their legislation in Lithuania. Currently, the AIF registered in Lithuania face difficulties, since the majority of them are not able to attract investors and are forced to discontinue their operations. Nevertheless, the size of the AIF capital in Lithuania is consistently growing and contributes to the increasing share of capital among all investment funds. The legislation of AIF on the global scale before the financial and economic crisis in 2008 was rather weak; nevertheless,
currently this trend is changing, a new legislation is put in place in the EU and USA in order to tighten AIF legislation and to limit their operations. However, AIF registered in Lithuania are rather small; therefore, this trend will not have a significant influence on Lithuania.

 

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This article presents several approaches to estimating the probabilities of default for low default portfolios, their advantages and disadvantages, and provides exemplary calculations using data of one external credit register of Lithuania. The results show that three approaches seem to be most appropriate: those of K. Pluto and D. Tasche (2005) without correlation, and those of N. M. Kiefer (2006) and A. Forrest (2005) without correlation. The first one could be easily implemented by banks; however, if the ordinal ranking of obligors is incorrect, then the monotony of probabilities of default is not ensured. The same problem exists with the second approach. The A. Forrest (2005) approach without correlation ensures the monotony of default probabilities and allows estimating conservative PDs; however, it requires programming skills, otherwise iterative recalculation will be very time-consuming.

 

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Corporate social responsibility (CSR), understood as a concept of socially responsible business behaviour, is becoming one of the important and actual business practices. Globally more and more MNEs are engaging themselves into CSR activities and see CSR as part of their corporate strategy. This paper presents an analysis of existing CSR strategic options for international companies to choose, and reveals what influences international companies’ decision what strategy and instruments to choose for implementing in a host country or market. In particular, the implementation of CSR strategic options and instruments in Belarus are analysed. The concept of this paper is based on the integration of a theoretical idea and business management practices. Since the object of the research is complex, it required the application of different research methods, such as theory analysis, system analysis, meta-analysis, survey, content-analysis, and expert interview methods. The findings of the study could be useful for foreign companies deciding to enter the Belarusian market, make M&A with local companies, for local managers responsible for CSR at their company, as well for researchers interested in CSR implementation in Eastern Europe.

 

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The main idea of this study is to connect the possibilities of mining technology with the methodology of proactive management by social and economic systems. The permanent process of complication of all spheres of social life requires improving the management forms and methods. Modern methods of decision support, appropriate information technology make it possible to improve the classical approaches, one of which is proactive management. Taking into account the limits of classical methods, proactive management should be chosen as an appropriate mining technology that can automatically extract the new non-trivial knowledge from data in the form of patterns, relationships, laws, etc. This synthetic technology combines the latest achievements of artificial intelligence, mathematics, statistics, heuristic approaches, including Data Mining, OLAP and others. Using the mining technology enables: to implement data monitoring, preparation and analysis (collection and presentation of data, detection of situations), to identify problem situations (to recognize patterns of problem situations; to correlate the pattern of the current situation with patterns of problem situations; to determine the structure of the problem situation, to identify factors and relationships), to prioritize the problems, trends and challenges, their expectations, effects (to predict the situation development with managerial influence and without it), to pose the tasks (to analyze deviations in terms of activity; to define goals, criteria, operating conditions) and so on. The following models (using the methods of “nearest neighbour”, rules induction, causal networks, statistical methods, associations, neural networks, decision trees, etc.) can be used: cluster allocation situations, classification of patterns, models of situation identification, pattern recognition models, prediction models, optimization models, causal relationships models.

 

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The work includes an analysis of the main modern challenges in the sphere of the labour force migration in Ukraine. The development of governmental regulations of labour force migration will give Ukraine a chance to improve the quality of workforce coming from abroad and to avoid the quitting of scientists by making them able to be employed in Ukraine. Also, changes in migration policy will help to decrease the unemployment rate in the country. The influence of labor force migration on the country’s economic development is also measured. The necessity of changes in governmental regulation of labor force migration in Ukraine is described in the paper. The government should make several steps to stimulate the usage of local labor force instead of cheap and unqualified foreigners by national enterprises. The first step is to provide the “quality rate” of a foreigner to be employed. The second step is the governmental support of enterprises that will act according to the mentioned rules and carefully regard the professionalism of employees. Such enterprises should receive subsidies.

 

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Econometric models are widely used in economic policies of many states. They help to build a great variety of econometric systems for every country and take into account the specifics of each economy.
In this article, the structural macroeconomic models that describe the main aspects of the economic policy were applied. The interdependence between the level of inflation, the value of investment, savings, consumption, export and import transactions, taxes on the foreign trade were defined based on the analysis of the key macroeconomic parameters of Ukraine. After investigating all economic indicators, they were transformed into stationary time series for a correct use in the model. In addition, heteroscedasticity and autocorrelation of residuals were excluded in all econometric equations.
As a result, the research shows that a large share of black economy leads to a rather high level of inflation in the state, because its value is primarily determined by expectations of the population under such circumstances. The paper indicates that the further export growth leads to a lower consumption growth and also to a lower growth of savings. Such a situation indicates an insufficient development of the domestic market. Investment growth has been fund not to be directly linked to consumption increase and economic development in general. Unfortunately, the main sources of investment in Ukraine are the funds of enterprises and foreign sources. The analysis shows a need to encourage public involvement into investment processes. For example, the creation of public–private partnerships is especially useful while implementing infrastructural projects.

 

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In the face of economic crisis, Baltic governments had to choose between internal and actual devaluation. Eventually, the first path was chosen to tackle the external and domestic macroeconomic instability. The aim of this study was to evaluate the effectiveness of the internal devaluation policy in the Baltic economies. Using qualitative research methods and graphical analysis, we have evaluated whether the choice of internal devaluation or deflation was appropriate in the exceptional recession period and whether it helped to eliminate the imbalances of the boom period. Obviously, fiscal consolidation helped to ease the tensions and restore confidence in the markets. However, we believe that the internal devaluation policy was efficient only temporarily in Latvia and Lithuania. This policy was hampered by the sectorial mismatches between labour demand and supply, which resulted from a strong surge in unemployment. A. detailed cos–benefit analysis of the internal devaluation policy option requires a more formal econometric analysis which will be implemented in the future research.

 

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We investigate the structural disturbances underlying the business cycle in Lithuania in the bivariate time series framework. In the structural VAR model constructed productivity, hours of work and output fluctuations over the business cycle are composed of technology and non-technology shocks. We find that a technology shock has a persistent positive effect on all three variables. Non-technology disturbance has a long-term impact on working hours and output, but it has a negligible short-run effect on productivity.
Differently from Gali (1999), the study has revealed no significant correlation between productivity and working hours under the effects of technology shocks on Lithuanian data. In contrast with the results of developed countries, non-technology shocks result in a significant negative correlation between the working hours and labour productivity in Lithuania.
Historical decomposition of output, productivity and working hours series allows distinguishing four different episodes of Lithuanian economy during the analysed timeline. In 1999, negative technology shocks played the biggest role in pushing the output down. During the period 2001–2004, the real GDP growth was supported by productivity increase due to technology shocks; in 2005–2008, non-technology shocks and the higher working hours were fuelling output growth together with a positive impact of the technology shock on productivity growth. Finally, 2008–2011 is the period of negative technology and non-technology shocks.

 

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This article is focussed on the problem of economic-statistical calculations and includes an economic-statistical research of economic fluctuations. The author also discusses the rules for statistical identification of economic welfare, economic development features of Lithuania after it became a member of the European Union. The notion of specific economic indicators, their classification issues, and the role and place of economic indicators presenting a systemic view of the country’s economy through identification of economic activities and their development are also discussed.
The article deals also with the methodologies based on various statistical methods and offers a methodology for revealing the components of economic fluctuations. A common notion is that the methodologies using analytical time series smoothed with the least squares method for revealing economic fluctuation components are best. The author proposes a methodology for calculating and evaluating the components of economic fluctuations, based on gross domestic product data.

 

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This article stylizes the monetary policy features applied during the chairmanship of Mr. Alan Greenspan and condenses statistical discussion into the “low interest rate trap” in the U.S. economy. Data from the U.S. in the decade prior to the 2008 financial crisis are used. A monetarist solution to the “low interest rate trap” is provided. The paper challenges the theoretical discussion on the Keynes’ interest rate – output relationship, and poses the question whether difference in investment returns would present a different picture in output growth.

 

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