Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/120767
Title: 

Does the EU environment benefits from agri-environmental measures? A spatial econometric analysis

Authors: 
Reinhard, Stijn
Linderhof, Vincetn
Year of Publication: 
2012
Series/Report no.: 
52nd Congress of the European Regional Science Association: "Regions in Motion - Breaking the Path", 21-25 August 2012, Bratislava, Slovakia
Abstract: 
This paper analyses the impact of agri-environmental measures (AEM), the most important measure of the EU Rural Development Program (RDP) measures. Of the total public RDP budget, almost a quarter is allocated to this measure (35 billion euro including EU and national contribution). The measure is offered in all 27 EU Member States. Highest farmer uptake is found in extensive agricultural regions (mountainous areas, grassland areas), whereas low implementation occurs in prime agricultural regions. AEM are contracts between farmers and the governing authority, in which farmers commit themselves to adopt environmentally friendly farming practices that go beyond usual good agricultural practice. EU-wide environmental impact indicators are not readily available therefore we constructed two indicators (i) High Natural Value (HNV) farmland indicator at NUTS2 level, (capturing agricultural biodiversity change) and (ii) nitrogen balance (capturing change in water quality). These indicators are used in a joint production function that resembles the joint production of agricultural produce and biodiversity/landscape, incorporating the environmentally detrimental emissions of nutrients. Data were collected from Eurostat and other sources. The spending on the agri-environmental measures is not uniformly distributed over the NUTS 2 regions in the EU. The spatial analyses of nitrogen surplus and HNV-farmland showed the presence of spatial dependencies. Based on the spatial dependency tests of the classical regression model, a spatial error model is estimated. In the current version we relate the entire array of AEM to one impact indicators. Data on spending disaggregated to the various activities would improve the econometric estimation.
Subjects: 
Rural Development Program
spatial data analyses
spatial econometrics
environmental economics
agriculture
JEL: 
C21
L83
O18
Document Type: 
Conference Paper

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