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Valuing Agricultural Landscape: Lithuanian Case Study Using a Contingent Valuation Method

Anastasija Novikova (), Lucia Rocchi () and Bernardas Vaznonis ()
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Anastasija Novikova: Research Institute for Bioeconomy, Vytautas Magnus University, LT-53361 Kaunas District, Lithuania
Lucia Rocchi: Department of Agricultural, Food and Environmental Sciences, University of Perugia, 74-06121 Perugia, Italy
Bernardas Vaznonis: Research Institute for Bioeconomy, Vytautas Magnus University, LT-53361 Kaunas District, Lithuania

Sustainability, 2019, vol. 11, issue 9, 1-13

Abstract: This study analyses Lithuanian residents’ willingness to pay (WTP) for the agricultural landscape in Lithuania. Since it is a part of the European Union, the agriculture is supported by the Common Agricultural Policy (CAP). According to CAP, agri-environmental schemes focus on the maintenance and improvement of agricultural landscape. Under these measures, Lithuanian farmers receive payments for the creation of agricultural landscape services. Therefore, understanding the demand of such agricultural landscape services, as received by the society, may help policymakers better allocate the funds. The present study has revealed that Lithuanian residents are concerned about the maintenance and preservation of the agricultural landscape. Moreover, they demand provision of the agricultural landscape services. Application of the contingent valuation method has shown that the median WTP of 23.59 €/year per family for agricultural landscape services, which is influenced by socioeconomic characteristics. The findings of the present study provide quantitative information about the demand for agricultural landscape services, which could be used to improve the agri-environmental policy, substantiating the internalization of positive and negative externalities (e.g., agricultural landscape services) to the performance of farmers.

Keywords: contingent valuation; willingness to pay; agricultural landscape; Lithuania (search for similar items in EconPapers)
JEL-codes: Q Q0 Q2 Q3 Q5 Q56 O13 (search for similar items in EconPapers)
Date: 2019
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