The measurement, assessment, and effective mitigation of energy intensity compose a foremost objective of contemporary energy policy. Although the European Union (EU) Member States have been experiencing the convergence in energy efficiency indicators, Lithuania, acceded to the EU in 2004, still remains peculiar with relatively high energy intensity. Our study, therefore, is aimed at analyzing the energy intensity trends in Lithuanian economy as a whole as well as in separate economic sectors. The investigation covers the period of 1995–2009. The Logarithmic Mean Divisia Index was applied for decomposition analysis. Our analysis has shown that energy efficiency falls during economic downturn. In order to facilitate these challenges the Lithuanian Government as well as business should opt for increasing energy efficiency in the most problematic sectors of transport and services. In addition, the analysis of legal acts, namely National Energy Efficiency Programme for 2006–2010 and Energy Efficiency Action plan for 2010–2016, was taken into consideration. Some suggestions, thus, were offered for successful implementation of strategic goals outlined in the aforementioned strategic documents.
The measurement, assessment, and effective mitigation of energy intensity compose a foremost objective of contemporary energy policy. This is because energy is the main intermediate resource for socio-economic development in any country (Tolon-Becerra et al., 2010, Omer, 2008). Consequently, the appropriate energy use enables to resolve the problems of economic competitiveness, energy security, and environmental sustainability (Ang et al., 2010).
Although the European Union (EU) Member States have been experiencing the convergence in energy efficiency indicators (Mulder and de Groot, 2011, Markandya et al., 2006), Lithuania, acceded to the EU in 2004, still remains peculiar with relatively high energy intensity (Baležentis et al., 2010, Streimikiene et al., 2008). Furthermore, many EU strategic documents (Streimikiene and Šivickas, 2008) as well as the new strategy Europe 2020(European Commission, 2010) stressed the importance of the energy efficiency in the EU. More specifically, the so called 20/20/20 targets, namely reduction of greenhouse gas emissions (by 20%), increase of share of the renewable energy (20%), and increase of energy efficiency thus saving up to 20% in the energy consumption, implied the need for elaborating appropriate policy measures aimed at achieving the aforementioned aims by 2020 (Tolon-Becerra et al., 2010). It is, hence, important to analyze the energy intensity in Lithuania and in other transition countries.
A number of studies on energy intensity in Lithuania have been carried out (Streimikiene et al., 2007, Streimikiene et al., 2008, Streimikiene and Šivickas, 2008, Klevas and Minkstimas, 2004). These studies, however, did not offer a decomposition analysis of energy consumption changes. Indeed, the volume of gross value added created in the Lithuanian economy has doubled since 1995, whereas the energy consumption remained virtually at the same level (Statistics Lithuania, 2011). These findings suggest that the Lithuanian economy has undergone some transformations, both intensive and extensive. Our study, therefore, is aimed at analyzing the energy intensity trends in Lithuanian economy as a whole as well as in separate economic sectors. The investigation covers the period of 1995–2009. The effects of policies and measures implemented in separate sectors of economy are assessed in terms of energy savings. The decomposition analysis allows investigating the effect of policies and measures in terms of energy intensity decrease of the whole economy and its separate sectors.
To analyze and understand diachronic changes in economic, environmental, or other socio-economic indicators, it is essential to assess the main factors that underlie these developments (Hoekstra and van den Bergh, 2003). The two methods are widely applied for decomposition of indicator changes, namely structural decomposition analysis (SDA) and index decomposition analysis (IDA). The SDA is based on input–output model (Hoekstra and van den Bergh, 2003), whereas IDA uses aggregate data at the sectoral level. Meanwhile, IDA is widely applied in energy related studies (Cornillie and Fankhauser, 2004, Ang, 2005, Hatzigeorgiou et al., 2008, Zha et al., 2009, Duro and Padilla, 2011). The IDA will be applied in this study. Ang (2004) presented an overview of IDA methods. The IDA methods can be generally divided into those based on Laspeyres index and those based on Divisia index. The former group of methods encompasses arithmetic mean Divisia index (AMDI), Laspeyres-based parametric Divisia method, logarithmic mean Divisia index I and II. Ang et al. (2009) report logarithmic mean Divisia index I (henceforth referred to as LMDI) method being robust and convenient to apply. LMDI method, therefore, is applied in this study. Moreover, both additive and multiplicative forms of LMDI are employed.
This paper is hence organized in the following way. Section 2 presents the overview of Lithuanian energy sector and comparison of energy intensity trends with neighboring countries. Section 3 analyses Lithuanian policies and measures to promote energy use efficiency and their effects on energy savings. Section 4 presents the basics of LMDI method. The following Section 5 describes the trends of energy consumption in various sectors of economy of Lithuania during 1995–2009. Section 6 brings forward the IDA of energy consumption changes in Lithuania. Finally, Conclusions present results and findings of performed analysis together with policy recommendations in the field of energy efficiency.
2. Lithuanian energy sector
The closure of Ignalina NPP marked the turning point for the Lithuanian energy sector. After shut down of Ignalina NPP at the end of 2009, Lithuania became dependent on electricity import. Augutis et al. (2011) presented a study on this particular issue. Natural gas consumption in its energy mix has increased for the production of electricity (Lithuania is totally dependent on imported natural gas from Russia) and the price of electricity for customers has increased by more than 30%. Against the background of the economic and financial crisis, the closure of Ignalina NPP is an additional factor, which has affected Lithuania's economic growth—the closure of Ignalina NPP alone has reduced Lithuanian GDP growth by at least by 1% in 2010. The biggest risk for Lithuania after the closure of Ignalina NPP is the increased dependency on energy imports, whether it is electricity or the means for electricity production—natural gas.
The closure of Ignalina NPP led to the revision of the main Lithuanian energy policy. It is clear that the closure strengthened the development of other energy infrastructure projects in Lithuania, but Ignalina NPP is not the only reason for these changes. The Baltic Energy Market Interconnection Plan (BEMIP), endorsed on 17 June 2009, is another essential factor driving energy infrastructure projects further. The BEMIP, an initiative of the European Commission with 8 participating Baltic Sea states, is an unprecedented step in EU energy policy. It creates an energy policy agenda both for generation and interconnection for the Baltic Sea region. As an umbrella for the development of energy projects, the BEMIP is itself an indirect consequence of the closure of Ignalina NPP, which highlighted the energy vulnerability of the Baltic states and created a demand for coordinated efforts in the implementation of energy projects. The plans to build new nuclear power plant (Visaginas NPP) together with Latvia, Estonia, and Poland in 2020 seem quite real as strategic investor will be selected in 2011.
The energy mix development is presented in Table 1. 2010 was the first year without nuclear power. Currently more than half of electricity needs to be imported. In the field of renewable energy resources Lithuania seeks to achieve the target of 23% of renewable energy in final energy consumption in 2020. For the electricity sector this means at least 20% (60% heat; 10% transport). A clear framework should be helpful and the most economically feasible technical solutions. In particular, the RES-Directive has fixed a renewable energy target for electricity of 7% of gross electricity consumption by 2010.
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