STATISTICAL INDICATORS FOR MONITORING IMPLEMENTATION OF ENVIRONMENTAL MEASURES
Journal: Scientific Papers Series ?Management, Economic Engineering and Rural Development” (Vol.14, No. 2)Publication Date: 2015-04-01
Authors : Crina TURTOI; Camelia TOMA; Camelia GAVRILESCU;
Page : 331-334
Keywords : agri-environmental indicators; agricultural policy; rural development;
Abstract
Most agri-environmental indicators subscribe to the general principles of sustainable development, in which economic, social and environment are interrelated. Measuring sustainable development must be based on indicators that indicate: (i) the pressure of society on the environment, (ii) the resulting environmental conditions (particularly changes) and (iii) response to human activities, especially in terms of socio- economic decisions, respectively the agricultural and agri-environmental policies adopted. These indicators must be consensual and should provide a representative picture of the three dimensions of sustainable development: society, economy and environment. Equally, it is necessary that they should be very clear, robust and reliable in statistical terms and they should derived from the best data sources, harmonized in terms of methodology with international standards. Agrienvironmental indicators must guaranty comparability for EU Member States and provide the opportunity for comparability in accordance with the methodologies used by the United Nations and the OECD. At the same time, the selected indicators must be able to be collected timely and easily to be revised and update further on. In Romania, the design of the system of indicators to monitor sustainable development is closely linked to the objectives and targets set out in : (i) National Strategy for Sustainable Development of Romania Horizons 2013- 2020-2030 (ii) Reports on the millennium development goals (iii) Development Strategy of Romania "Horizon 2025". The paper aims both at defining statistical indicators for monitoring implementation of agri-environmental measures and identifying possible sources of data for quantifying them.
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