This analysis features an assessment of the Gross Value Added on the holdings covered by a measure entitled “Setting up of young farmers” (Measure 112) or “Modernisation of agricultural holdings” (Measure 121), including its growth in 2009 and 2010, and a projection on its further growth in 2013. In every case, the calculations were made using fixed prices. The study was based on Polish FADN data. For the purposes of the analysis, two panel groups were distinguished among farms keeping accounts continuously in the years 2008, 2009, and 2010. The first group comprised agricultural holdings benefitting only from Measure 112 or only from Measure 121. The second group, on the other hand, included farm owners eligible for support under Measures 112 or 121, who did not receive support in 2008. It has been established that the holdings benefitting in 2008 from Measure 112 or Measure 121 were characterised by greater production potential and a significant increase in GVA than the other farms.
The emergence of a new list of priority sectors of the economy, which the Government declares, conditions the need for calculating the volume of investment resources, which must be involved by the state in these industries to support their development in the short term. The implementation of such prediction requires the use of advanced methods of economic-mathematical modelling that will be effective in conditions of the limited availability of statistical data. This task was implemented due to: the developing an approach to the qualitative and quantitative assessment of the relationship between investment in fixed assets and gross value added in 33 economic activities in Ukraine, test of its effectiveness on data from the German economy, constructing a series of predictions to 2016 on the basis of the data obtained to priority economic activities. By a two-parameter exponential smoothing the scenarios of optimistic, average and pessimistic forecasts were formed. The obtained results will enable one to determine the amount of investment in fixed assets, which should be involved by the state in the priority economic activities until 2016 for their intensive development.
Climate change is a serious threat to sustainable development (SD). A Decomposition Analysis (DA) of the data on Greenhouse Gas (GHG) emissions in the European Union (EU) in 2008 – 2014 was carried out using the Log-Mean Divisia Index Method (LMDI). To detect the factors behind de/coupling of GHG emissions from Gross Value Added (GVA) in the EU-28, changes of GHG emissions were divided into three effects. The negative intensity effect showed the highest absolute magnitude in the overall period 2008 – 2014 and the two partial periods 2008 – 2011 and 2011 – 2014. The composition effect also helped reduce GHG emissions, but to a lesser extent. The scale effect boosted increases of GHG emissions except for two years, 2009 and 2012, which was related to the effects of the economic crisis. Transportation and storage along with the Agriculture, forestry and fishing activities should be addressed more significantly in relation to GHG emissions.
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