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Spatial Variation and Factors Impacting Grassland Circulation Price in Inner Mongolia, China

Jing Zhang () and Colin Brown ()
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Jing Zhang: School of Agriculture and Food Sciences, The University of Queensland, Brisbane 4072, Australia
Colin Brown: School of Agriculture and Food Sciences, The University of Queensland, Brisbane 4072, Australia

Sustainability, 2018, vol. 10, issue 12, 1-15

Abstract: As the circulation of grassland use rights in China increases, relatively little is known about the factors that influence circulation price. This paper examines the spatial distribution of grassland circulation prices and the impact of various attributes on grassland circulation prices in Inner Mongolia Autonomous Region (IMAR). Spatial autocorrelation tests and quantile regression methods are applied to data from an online land-circulation website covering the period from January to October 2017. The spatial analysis found that grassland circulation price does vary greatly throughout IMAR but that no significant spatial autocorrelation is evident. The quantile regression analysis revealed significant, though varied, quantile effects across the price distribution indicating that local market structures, strong demand for grazing land in desert steppe, high demand of poor herders for smaller plots, and high demand of richer herders for larger plots all play an important role in determining circulation prices. These nuanced findings should enable policy makers, grassland users, and other grassland actors to better understand how grassland price is determined with respect to a range of factors across the quantiles of price as well as the spatial pattern of price characteristics. This information and understanding are a crucial step in improving grassland circulation.

Keywords: grassland circulation; price distribution; spatial autocorrelation; quantile regression (search for similar items in EconPapers)
JEL-codes: Q Q0 Q2 Q3 Q5 Q56 O13 (search for similar items in EconPapers)
Date: 2018
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