). Country comparison. CIA Factbook. Retrieved Sept. 14, 2014, from http://www.indexmundi.com/factbook/compare/estonia.lithuania/economy Invest Lithuania. (2014). Foreign direct investment in Lithuania: tendencies and prospectss. ISSUU. Retrieved Sept. 09, 2014, from http://issuu.com/invest_lithuania/docs/tiesiogines-uzsienioinvesticijos-l Ivestors’ Forum Tax Group. (2011). Favourable and clear Lithuanian tax system for everybody. Investors’ Forum. Retrieved Sept. 12, 2014, from http
Tanja Zdolšek Draksler and Karin Širec
: An institutional perspective on new ventures and the business plan. Journal of Business Venturing , 24, 27–45. https://doi.org/10.1016/j.jbusvent.2007.10.003 Kiggundu, M. N. (2002). Entrepreneurs and Entrepreneurship in Africa: What is Known and What Needs to be Done. Journal of developmental Entrepreneurship , 7 (3). Kvedaraite, N. (2014). Reasons and Obstacles to Starting a Business: Experience of Students of Lithuanian Higher Education Institutions. Management – Journal of Contemporary Management Issues, 19 (1), 1–16. Kyndt, E. in Baert
.4232/1.11004 FKTK (2015). Valsts fondēto pensiju shēmas līdzekļu pārvaldīšana - ceturkšņa pārskati par 2005-2015. Retrieved August 20, 2015, from http://www.fktk.lv/lv/statistika/pensiju-fondi/ceturksna-parskati.html Holzmann, R., Hinz, R. P. & Dorfman, M. (2008). Pension Systems and Reform Conceptual Framework. Social Protection Discussion Paper 0824. Medaiskis, T. & Jaunkauskiene, D. (2013). ASISP country document 2013. Pensions, health and long-term care. Lithuania. Retrieved August 20, 2015, from http://socialprotection.eu/files_db/1334/LT
Angelina Bekasova, Biruta Sloka and Tatjana Muravska
Studies, 33(4), 412-430. https://doi.org/10.1080/01629770200000201 Hospers, G. J. (2004). Regional Economic Change in Europe: a Neo-Schumpeterian Vision. New Brunswick, London: Transaction Publishers. Iannuzzi, A. (2012). The Making and Marketing of Sustainable Brands. Boca Raton/London/New York: CRC Press. Invest Lithuania. (2016). Let’s Talk Lithuania. Retrieved from http://www.investlithuania.com/letstalk-lithuania/lifestyle/ Investment and Development Agency of Latvia - LIAA. (2016). About. Retrieved
Natalia Scacun and Irina Voronova
The article represents the bibliometric analysis of risk assessment in Baltic countries relying on scientific database. The purpose of this analysis is to study trends and development of scientific research when evaluating financial risks as well as reveal resources with high impact to apply content analysis that could be used for future research on the topic. The applied investigation methods were chosen based on the analysis of existing scientometric data: the number and dynamics of published documents; their subject area and type; territory/country; source title; affiliation; authors; h-index; citation overview followed by search results as well as adopting search references to reveal the used and cited documents. The authors also present the applied deduction of trends between enterprise death rate in Latvia, Lithuania, and Estonia and the number of documents in the referenced period. This study demonstrates that the amount of research increased significantly when countries face rises in enterprise death rates.
Scott William Hegerty
For centuries, Estonia, Latvia, and Lithuania have enjoyed historic and economic ties with their Nordic neighbors in the Baltic Sea region. While the period since 1991 has been one of increased integration with the European Union, trade linkages with Finland and Sweden are particularly strong for Estonia and Latvia, respectively. This study addresses these connections by applying time-series econometric techniques, with the goal of highlighting where regional connections are strongest. Strong Nordic-Baltic linkages, while providing evidence that historical factors are still important, might also suggest that integration with the rest of the EU is relatively weak. Using quarterly data from 1994 to 2014 for Baltic, Nordic, and other partner countries, business cycles are modeled for output, consumption, and investment. Common regional cycles are also extracted via Principal Components Analysis for the three Baltic countries and for the Nordic countries of Denmark, Finland, Norway, and Sweden. Cross-correlation functions are then generated for various cycle pairs to assess whether any are “synchronized.” One key finding is that the Nordic region has two possible consumption cycles that behave in very different ways, suggesting that this region does not behave as a coherent whole. Norway and Denmark drive one cycle, while Sweden and Finland drive the other. Another key result is that each Baltic country behaves differently from one another. While regional differences are quite large - making it harder to describe this as a single “region” at all - Estonia does show significant connections to Finland, its historic and linguistic neighbor.
Recent rapid development of the Baltic stock markets raises the question about stock market integration level in these countries. Some empirical aspects of the Baltic stock market integration have been analysed in the scientific literature, however, a comprehensive analysis on the Baltic stock market integration level is still missing. The aim of the paper is to assess the regional integration level of the Baltic stock markets. The research object is stock markets in the Baltic countries. The following research and statistical methods have been applied in this study: the systemic and comparative analysis of the scientific literature, Spearman’s correlation coefficient, dynamic conditional correlation generalized autoregressive conditional heteroskedasticity model, Granger causality test, generalized impulse response analysis, Johansen cointegration test, autoregressive distributed lag model and error correction model. The main findings of this empirical study are (a) all three Baltic stock markets are closely related markets, (b) however, the Latvian stock market is more isolated at the regional level comparing to other two Baltic stock markets (c) whereas Estonian and Lithuanian stock markets are more interrelated.
The aim of this paper is to assess if and how a concept of accounting quality differs from perspectives of various types of organisations affected by the accounting harmonisation process. Accounting harmonisation is commonly associated with worldwide adoption of IFRS by public interest companies. However, in the EU this process is much broader and also involves efforts to harmonise accounting standards for non-listed companies and public sector organisations. Analysis of the previous scientific research revealed that accounting quality was commonly assessed from IFRS users’ perspective and approximated with the quality of financial statements. However, based on the interviews with experts of Lithuanian accounting market, the concept of accounting quality for small and medium companies and public sector institutions is ambiguous and still needs to be clarified. Definition of accounting quality only as the quality financial statements is too narrow as financial disclosure is not that important for such companies. For non-listed companies and public sector organisations, other aspects and factors, such as qualification of accountants, supervision of accounting and reporting, overall and managers’ perspective on importance of accounting, have more importance while defining accounting quality.
Vladimirs Rojenko and Aleksandrs Dahs
Human capital, affected by the demographic determinants, nowadays becomes a novel driver of change and regional development. Changes in the modern economy determine the future leading role of human capital, especially its creative dimension in the development of modern, sustainable competitive advantages of countries and regions. Considering the negative demographical tendencies in the Baltic States, the aim of this paper is to analyse and forecast the development of creative potential in Lithuania, Latvia and Estonia. Our methodology is based on the estimation of a regression model describing the relations between Global Creativity Index (GCI) and its components with the available demographic data in 28 European Union member countries. Model estimation results indicate a particular importance of population age composition for all GCI components, while education attainment levels appear to be highly significant for the technology and talent components. Using the estimated model parameters, authors elaborate a simple forecast for the three Baltic States using the current demographic projections, while outlining the strengths and potential weaknesses of each country in the long-term perspective.
Ilze Zariņa, Irina Voronova and Gaida Pettere
The study gives an overview of the Baltic non-life insurance market. The purpose of the research is to summarise stability statistics on solvency ratios, risk profiles and capital surplus, which was contained in Solvency and Financial Condition reports (SFCR) in 2016 published first time by non-life insurance companies in European Union and Baltic market (Latvia, Estonia, and Lithuania). Solvency II came into effect in 2016, and these reports have been prepared using the new requirements of the Solvency II framework. All non-life insurance companies are required to have eligible own funds at least equal to solvency capital requirement (SCR) in order to avoid supervisory intervention (own funds divided by SCR are required to be at least 100 %). The SCR is based on well known risk measure value at risk with 99.5 % confidence level over a one-year time horizon. Baltic non-life insurance companies were strong capitalized (median 155 %) in 2016. It means that all Baltic companies can survive even if 1 in 200 years events have occurred although Baltic solvency coverage ratio is lower than the median ratio in European Union (209 %). For Latvian non-life insurance market, solvency ratio median is the lowest in European Union comparing by countries. The authors have analysed the historical development of the market and have calculated financial ratios, Gini’s concentration index, as well as dissimilarity index. The authors have investigated the current and future internal and external risks and issues for the Baltic non-life insurance market, such as political environment, low-yield environment, and market competition due to new mergers and acquisitions (M&A) activities, and a new rule for accounting for insurance companies IFRS17.