Estimating housing vacancy rates in rural China using power consumption data

Village hollowing is a growing policy problem globally, but accurately estimating housing vacancy rates is difficult and costly. In this study, we piloted the use of power consumption data to estimate the vacancy rate of rural housing. To illustrate the method used, we took power consumption data in 2014 and 2017 in an area of rural China to analyze the change in housing vacancies. Results indicated that the rural vacancy rates were 5.27% and 8.69%, respectively, while underutilization rates were around 10% in 2014 and 2017. Second, there was significant spatial clustering of vacant rural housing, and the hotspots were mainly distributed in western mountainous areas, whereas villages near urban areas had lower vacancy rates. Third, rural vacancies increased from 2014 to 2017. Compared with other methods, our method proved to be accurate, very cost-effective and scalable, and it can offer timely spatial and temporal information that can be used by policymakers to identify areas with significant village hollowing issues. However, there are challenges in setting the right thresholds that take into consideration regional differences. Therefore, there is also a need for more studies in different regions in order to scale up this method to the national level.