THE EFFICIENCY FORECAST OF RURAL HUMAN RESOURCES USE BY THE DATA ENVELOPMENT ANALYSIS APPROACH
Journal: Scientific Papers Series ?Management, Economic Engineering and Rural Development” (Vol.14, No. 4)Publication Date: 2015-04-01
Authors : Dorel MIHAI; Ion DONA;
Page : 165-168
Keywords : efficiency; forecast; rural human resources;
- THE EFFICIENCY FORECAST OF RURAL HUMAN RESOURCES USE BY THE DATA ENVELOPMENT ANALYSIS APPROACH
- DATA ENVELOPMENT ANALYSIS APPROACH ON THE EFFICIENT USE OF RURAL HUMAN RESOURCES IN AGRICULTURE, INDUSTRY AND CONSTRUCTIONS DURING 2006-2013
- Technical Efficiency Analysis of Potato Farming in Kerinci Regency-Indonesia (Approach Data Envelopment Analysis Method)
- Evaluating the Technical Efficiency of Rural Cooperatives in Sistan and Baluchestan Province of Iran Using Fuzzy Data Envelopment Analysis (FDEA) Model
- FARM EFFICIENCY MEASUREMENT OF PADDY PRODUCTION IN NORTHERN SRI LANKA USING DATA ENVELOPMENT ANALYSIS (DEA) APPROACH
Abstract
The structure of rural human resources (from agriculture, industry, constructions) represents the most important production factor in order to achieve economic growth (high GDP). In terms of efficiency, it is more important to assess the way in which the combination of human resources between these three branches contributes to GDP formation. To do this assessment for the period 2013-20120, we applied the nonparametric method of DEA (Data Envelopment Analysis). This method enables ranking regions based on a series of inputs (rural population occupied in agriculture, industry and constructions) and outputs (rural gross domestic product). The data regarding the rural human resources are retrieved from the Amigo data base, the rural GDP Eurostat and the analysis was performed by MAXDATA 6.3 Beta program. The results revealed that, by 2020, if maintaining the 2006-2013 trends, the average technical efficiency will decrease by 5.4%, only the Central and the South-West regions will be performing well and the North-East and North-West regions will become more inefficient. Our results reveal that, in the majority of regions, there is a clear need to reduce the population from agriculture, to increase the population from industry and constructions, and to increase de productivity, to ensure real economic growth.
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