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Productivity assessment of the real estate industry in China: a DEA-Malmquist index

Productivity assessment of the real estate industry in China: a DEA-Malmquist index The high-quality development of the real estate industry is crucial to the transformation of China's economy. However, few studies apply the productivity to explore the development path of the real estate industry in China. To fill this gap, this study mainly investigates the total factor productivity (TFP) of the real estate industry of 30 sample provinces in mainland China from 2007 to 2016.Design/methodology/approachThe Malmquist index is applied to estimate the productivity (i.e. TFP) of the real estate industry, based on the data envelopment analysis (DEA). Then, the truncated tobit regression analysis explores the external influencing factors on the TFP of the real estate industry.FindingsThrough empirical analysis, it is found that the high-quality development of the real estate industry depends on the technological innovation by the real estate enterprises and the targeted policies by the provincial government. Moreover, the development of the real estate industry has a positive correlation with the growth of China's economy but a negative correlation with the development of other industries.Practical implicationsTFP mainly reveals the development status of the provincial real estate industry and identifies the driving force for exploring the high-quality development mode of the real estate sector. Furthermore, the fluctuation rule of TFP can be applied to predict the development trend of the real estate industry in the future.Originality/valueAs an application, this study measures the TFP of the Chinese real estate industry in different provinces and periods. The results have meaningful policy implications for policymakers regulating the real estate industry. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Engineering Construction & Architectural Management Emerald Publishing

Productivity assessment of the real estate industry in China: a DEA-Malmquist index

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References (45)

Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
0969-9988
DOI
10.1108/ecam-07-2020-0561
Publisher site
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Abstract

The high-quality development of the real estate industry is crucial to the transformation of China's economy. However, few studies apply the productivity to explore the development path of the real estate industry in China. To fill this gap, this study mainly investigates the total factor productivity (TFP) of the real estate industry of 30 sample provinces in mainland China from 2007 to 2016.Design/methodology/approachThe Malmquist index is applied to estimate the productivity (i.e. TFP) of the real estate industry, based on the data envelopment analysis (DEA). Then, the truncated tobit regression analysis explores the external influencing factors on the TFP of the real estate industry.FindingsThrough empirical analysis, it is found that the high-quality development of the real estate industry depends on the technological innovation by the real estate enterprises and the targeted policies by the provincial government. Moreover, the development of the real estate industry has a positive correlation with the growth of China's economy but a negative correlation with the development of other industries.Practical implicationsTFP mainly reveals the development status of the provincial real estate industry and identifies the driving force for exploring the high-quality development mode of the real estate sector. Furthermore, the fluctuation rule of TFP can be applied to predict the development trend of the real estate industry in the future.Originality/valueAs an application, this study measures the TFP of the Chinese real estate industry in different provinces and periods. The results have meaningful policy implications for policymakers regulating the real estate industry.

Journal

Engineering Construction & Architectural Management – Emerald Publishing

Published: Apr 4, 2023

Keywords: Data envelopment analysis; Chinese real estate industry; DEA-Malmquist index; Regression analysis

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