Tangible investment and labour productivity: Evidence from European manufacturing

Labour productivity is one of the key drivers for higher earnings and welfare standards in every economy. The problem of how to ensure the growth of labour productivity is especially relevant to less developed economies and forces justification of the factors affecting sustainable productivity growth. The purpose of this research is to test if the investment in tangible assets improves labour productivity in the European manufacturing industry and to reveal the countries with inefficient investment. The results show that with consideration of all European countries, a 1% increase in gross investment in tangible goods (G.I.T.G.) per person employed (P.E.) has a 0.0373% long-run effect on apparent labour productivity (A.L.P.). Considering various types of investments in tangibles, only an increase in gross investment in existing buildings and structures (G.I.E.B.S.) per P.E. and gross investment in machinery and equipment (G.I.M.E.) per P.E. caused growth of A.L.P. However, the impact of investment in assets on A.L.P. significantly differs among the countries and it is revealed that many European countries, which are characterised by low productivity, use investment inefficiently

The efficiency of structural support and impact on economic and social indicators

The economic and social cohesion is one of the economic objectives of the European Union. It is, therefore, important to analyse the impact of policies of the European Union on cohesion. The establishment of the common market still did not offer a solution for economic problems faced by the Member States. The economic and social cohesion is very important to strengthen the political and economic development of the Member States. This article includes the analysis of Lithuanian economic environment compared with the other Member States and the impact of EU structural funds on economic growth of the country. The detailed analysis of the correlation between funding and economic and social indicators of Lithuania showed that there is the significant direct relationship between the funding and the direct foreign investments per inhabitant. The significant correlation between EU support and other economic and social indicators was not found. Nevertheless the EU funding is undoubtedly useful and necessary to promote the economic growth. The efficiency of the use of EU funds is the largest problem and the task achieving the maximum benefit for the economics of Lithuania

Estimation of social discount rate for Lithuania

Purpose of the article: The paper seeks to analyse the problematics of estimation of the social discount rate (SDR). The SDR is the critical parameter of cost-benefit analysis, which allows calculating the present value of cost and the benefit of public sector investment projects. Incorrect choice of the SDR can lead to the realisation of ineffective public project or conversely, cost-effective project will be rejected. The relevance of this problem analysis is determined by discussions and different viewpoints of scientists on the choice of the most appropriate approach to determine the SDR and absence of methodically based the SDR on the national level of Lithuania. Methodology/methods: The research is performed by the scientific and methodical literature analysis, systematization, time series and regression analysis. Scientific aim: The aim of the article is to calculate the SDR based on the statistical data of Lithuania. Findings: The analysis of methods of SDR determination, as well as the researches performed by foreign researchers, allows stating that the social rate of time preference (SRTP) approach is the most appropriate. The SDR, calculated by the SRTP approach, reflects the main purpose of public investment projects, i.e. to enhance social benefit for society, the best. The analyses of SDR determination practice of the foreign countries shows that the SDR level should not be universal for all states. Each country should calculate the SDR based on its own data and apply it for the assessment of public projects. Conclusions: The calculated SDR for Lithuania using the SRTP approach varies between 3.5 % and 4.3 %. Although it is lower than 5 % that is offered by European Commission, this rate is based on the statistical data of Lithuania and should be used for the assessment of the national public projects. Application of the reasonable SDR let get the more accurate and reliable cost-benefit analysis of the public projects

Personnel Costs and Labour Productivity: The Case of European Manufacturing Industry

The objective of the article is to evaluate the impact of personnel costs on apparent labour productivity by employing the 1995–2018 panel data of the manufacturing industry in 27 European countries. The methods of independent samples t-test, correlation analysis, Granger causality test, unit root test, and ARDL were employed. The analysis shows that a long-term relationship exists among personnel costs and apparent labour productivity, and there are not significant differences among European countries concerning the impact of personnel costs on apparent labour productivity, but it varies in time. Companies often avoid increasing wages, as it decreases the profit of the company, and seek to increase the turnover in order to reduce the cost of goods sold. This research shows that growth of personnel costs does not necessarily mean lower profitability. The growth of personnel costs increases the gross operating rate if the turnover per person employed is stable. Turnover growth has a positive effect on apparent labour productivity, but a negative impact on the gross operating rate. Thus, the impact of turnover on apparent labour productivity is significantly lower than the impact of personnel costs on apparent labour productivity

Personnel Costs and Labour Productivity: The Case of European Manufacturing Industry

The objective of the article is to evaluate the impact of personnel costs on apparent labour productivity by employing the 1995–2018 panel data of the manufacturing industry in 27 European countries. The methods of independent samples t-test, correlation analysis, Granger causality test, unit root test, and ARDL were employed. The analysis shows that a long-term relationship exists among personnel costs and apparent labour productivity, and there are not significant differences among European countries concerning the impact of personnel costs on apparent labour productivity, but it varies in time. Companies often avoid increasing wages, as it decreases the profit of the company, and seek to increase the turnover in order to reduce the cost of goods sold. This research shows that growth of personnel costs does not necessarily mean lower profitability. The growth of personnel costs increases the gross operating rate if the turnover per person employed is stable. Turnover growth has a positive effect on apparent labour productivity, but a negative impact on the gross operating rate. Thus, the impact of turnover on apparent labour productivity is significantly lower than the impact of personnel costs on apparent labour productivity

EU framework programmes: positive and negative effects on member states' innovation performance

Research background: Seeking to ensure competitiveness in the global market, the EU is constantly improving its innovation policy. Compared to other EU initiatives, the Framework Programs for Research and Innovation (FPs) act as the main instrument with the longest history and the largest budget to boost member states' innovation performance. Despite the initial presumptions that these financial inflows should bring positive and constructive effects, the results significantly diverge across the countries with highly uneven and incoherent progress. Therefore, complex and reliable tools must be adopted to evaluate the long-term influence of EU investment and the reasons which distort the innovation performance in separate member states. Purpose of the article: The purpose of this article is to evaluate the influence of EU investment on its member states? innovation performance by using a redeveloped national innovative capacity framework and including technological, non-technological and commercial innovative output. Methods: Panel unit root tests were used to assess the time series stationarity. Autoregressive distributed lag models helped in calculating the long-term influence of EU investment on member states? innovation performance. Finally, by employing dummies, it was analysed how this influence varied over time and across different countries. Findings & value added: The findings provide evidence that EU investment exerts positive long-term influence on the technological innovative output proxied as total, business and higher education institutions? patent applications, as well as product and process innovations. The effects were also positive on trademarks and marketing, and organisational innovations. However, small but negative influence was found in the case of patent applications by the government sector and the exports of hi-tech products and knowledge-intensive services. These insights may serve in the designing process of the specific instruments and the future innovation policies, which would bring the maximum benefit for the society and economy

The Leading Indicators of the Economic Cycles in Lithuania

The identification of the leading indicators that precede economic events and predict the next phase of the economic cycle is undoubtedly an important issue seeking to protect a country against recession or other negative economic events. The literature analysis shows that leading indicators vary across the countries and time. Therefore the aim of this research is to analyse potential leading indicators and identify the best predictors of the economic cycles in Lithuania. Various economic, industrial, financial, real estate market indicators as well as consumer and business expectations are analysed in order to find out which indicators cause the changes in the growth rate of GDP. The analysis is based on Granger causality test and autoregressive distributed lag model. The research shows that economic indicators such as consumption expenditure of households, government debt, compensation of employees, unemployment and others are weak predictors of the growth rate of GDP. Volume index of intermediate goods production is the best predictor in the group of industry data as it holds predictive attributes even three years before the changes in economy. The same conclusion can be made considering two financial indicators, i.e. short-term interest rate and the value of stock market index. Real estate market data such as residential buildings permits and growth rate in house price index can also warn about the changes in the growth rate of GDP two years before. Nevertheless, consumer and business expectations are the most important for the prediction of the changes in the growth rate of GDP

The Impact of Socio-Economic Indicators on Sustainable Consumption of Domestic Electricity in Lithuania

Lithuania is one of the EU Member States, where the rate of energy consumption is comparatively low but consumption of electricity has been gradually increasing over the last few years. Despite this trend, households in only three EU Member States consume less electricity than Lithuanian households. The purpose of this research is to analyse the impact of socio-economic factors on the domestic electricity consumption in Lithuania, i.e., to establish whether electricity consumption is determined by socio-economic conditions or population’s awareness to save energy. Cointegration analysis, causality test and error-correction model were used for the analysis. The results reveal that there is a long run equilibrium relationship between residential electricity consumption per capita and GDP at current prices as well as the ratio of the registered unemployed to the working-age population. In consequence, the results of the research propose that improvement of living standards for Lithuanian community calls for the necessity to pay particular attention to the promotion of sustainable electricity consumption by providing consumers with appropriate information and feedback in order to seek new energy-related consumption practices