Effect of Eco-compensation Schemes on Household Income Structures and Herder Satisfaction: Lessons From the Grassland Ecosystem Subsidy and Award Scheme in Inner Mongolia
Jing Zhang,
Colin Brown,
Guanghua Qiao and
Bao Zhang
Ecological Economics, 2019, vol. 159, issue C, 46-53
Abstract:
The Grassland Ecosystem Subsidy and Award Scheme (GESAS) is a key set of policy instruments designed to improve grassland condition and herder livelihoods in China. This paper uses a Structural Equation Modelling (SEM) approach to investigate the impacts of GESAS on livestock practices, herder incomes and employment, and overall herder satisfaction in Inner Mongolia. The findings reveal that more intensive use of on-farm inputs mediated the effects of lower stocking-rate under the scheme on on-farm income. Conversely, GESAS had a direct and negative impact on off-farm income. Overall the findings do highlight the incentive role of GESAS on herder decisions, but also indicate a level of dissatisfaction among herders as the level of compensation is insufficient to cover the extra effort expended by herders and does not meet the livelihood expectations of most herders.
Keywords: Eco-compensation; Grassland subsidy; Household income; Herder satisfaction; Inner Mongolia (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (18)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0921800918311893
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolec:v:159:y:2019:i:c:p:46-53
DOI: 10.1016/j.ecolecon.2019.01.006
Access Statistics for this article
Ecological Economics is currently edited by C. J. Cleveland
More articles in Ecological Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().