Abstract
The conventional equation of economic well-being with the gross domestic product (GDP) has dominated policy thinking for at least 50 years. However, a variety of authors have pointed to the social and environmental costs of economic development and called for more comprehensive and more representative measures of progress to be developed. Therefore, a variety of ‘adjusted’ indicators have been developed. The robustness and reliability of these indicators is still a contentious issue. But these attempts raise important questions about sustainable development and pose an important challenge to conventional thinking about the relationship between economic progress, well-being and sustainability. The Genuine Progress Indicator (GPI) is one of the indicators of measuring sustainable development. Apply it to Liaoning Province, this paper evaluates Liaoning’s GPI from 1978 to 2011. GPI, Per Capita GPI and GDP of Liaoning are compared with each other. It is concluded that GDP and Per Capita GDP of Liaoning grow much faster than GPI and Per Capita GPI. Grouped all components of GPI into three categories (economy, environment and Social), it shows that social and environmental development lags behind economic growth in Liaoning. This paper is till now a unique application of GPI indicator in Liaoning and China’s provincial level and also contribution to the continuing development of the methods and results for the Index of Genuine Progress Indicator (GPI). Policy implications are given finally.
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Acknowledgments
This work was financially supported by Major Program of China National Social Science Foundation (13&ZD171), China National Social Science Foundation(15BTJ001), Program for New Century Excellent Talents in University (NCET), Research Program of Dongbei University of Finance and Economics (DUFE2015Y13), National Statistical Science and Research Program(2013LY099). The paper has been improved as a result of comments from two anonymous referees. Remaining errors are the author’s responsibility.
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Hou, Y. Calculating a GPI for Liaoning Province of China. Soc Indic Res 134, 263–276 (2017). https://doi.org/10.1007/s11205-016-1415-1
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DOI: https://doi.org/10.1007/s11205-016-1415-1