A Quantitative Assessment of the Rurality and an Efficiency Analysis of Emigration in Romania

In Romania, as in many other Eastern European countries, the early 1990s were marked by a significant emigration from the countryside as a consequence of the transition from a centralised economy to an open one and due to key changes in the political framework. The permanent emigration has predominantly been concentrated in rural areas where multiple socio-economic variables such as GDP per capita, unemployment, and public financial subsidies aimed at supporting people at risk of severe deprivation and poverty have all had a direct effect on rural depopulation. The rurality is a complex theoretical construct comprising many items and variables and is, therefore, difficult to define in a concise manner. The aim of this paper is to assess the evolution of emigration in Romania between 2001 and 2016 through a quantitative approach, estimating an index of rurality for the same period composed of a set of socio-economic variables having a direct or indirect nexus to it. In the first phase of research, a matrix of correlation and a multiple regression model has been used in order to estimate the direct links among all investigated variables. Following the quantitative methodology, in the second phase Partial Least Square Structural Equation Modelling (PLS-SEM) has been used in order to assess the main cause-effect relationships among a few selected endogenous variables and a set of socio-economic items. Furthermore, using a non-parametric Data Envelopment Analysis (DEA) output-oriented model, this research has assessed the efficiency in terms of permanent emigration from Romania estimated as an output to minimise and not as an output to maximise, as investigated by traditional efficiency approaches. In terms of efficiency, financial subsidies allocated by national authorities and the level of per capita Gross Domestic Product have acted directly on the level of emigration. The index of rurality in 2016 has been influenced in particular by he pluriactivity in farms in terms of agritourism, the dimension of farms in terms of land capital endowment, and the level of GDP per capita.

JEL Classification: Q10; Q18

Clasters and Correlations among the Eu Member States Regarding Agri-Food Foreign Trade

The European Union has a significant role in international trade but this is largely in the area of industrial goods. However, in the case of some agricultural commodities the EU applies tariffs, bans, or different restrictive measures; it manages foreign trade in agricultural goods with many countries all over the world. On the other hand the member states do not contribute to the total trade of the EU to the same extent. In this study, a comparative analysis was performed in relation to the member states by means of data of Eurostat and Faostat. First, a multivariable correlation analysis was carried out in order to find the interrelation between the trade features of each country. In the second part of the study, a cluster analysis was carried out with almost the same component as in the foregoing, also in terms of the EU member states. It can be ascertained that the date of EU accession of a Member State as well as getting EU agricultural subsidies do not affect the agricultural foreign trade of the member states. Countries with significant agricultural production also export food commodities in larger quantities. Countries that have significant exports extra-EU also have larger imports in the case of both basic commodities and prepared food as well. As a result of the cluster analysis, it can be stated that the member states can be divided into specific groups according to the three examined aspects (food trade features, exports of commodities, imports of commodities). The following typical country groups can be divided as follows: non-trade countries, countries with larger trade extra-EU, agri-food exporter and importer countries, non-agri-food exporter and importer countries, primary commodity exporters and importers, and last but not least processed food exporters and importers as well.

JEL Classification: F10