Benchmark wealth capital stock estimations across China's 344 prefectures: 1978 to 2012

- A prefecture-level wealth capital stock dataset for China from 1978 to 2012
- The wealth capital stock dataset is of great value for economic exposure analysis of disaster losses.
- Provincial-specific depreciation rates and capital deflators are constructed.
- The accumulated wealth capital stock for Mainland China reached RMB 152 trillion by 2012.
- A total of 60% of China's wealth capital stock is distributed within 22% of China's prefectures.

Measures of wealth ('net') capital stock (WKS) can be used for measuring economic exposure to natural disasters and thus are essential for disaster risk management in terms of both quick loss estimation during emergency responses and post-disaster planning for recovery and reconstruction. Today, the improved availability of statistical data and the progress of capital stock estimation methods have made it possible to produce datasets of WKS on the prefecture level. By applying the perpetual inventory method (PIM) to estimate prefecture-level WKS in China from 1978 to 2012, this paper aims to illustrate both the methodology for generating the WKS dataset and the utility of the WKS as a useful indicator of economic exposure to potential hazards. The estimation results indicate that the accumulated WKS for Mainland China had reached RMB 152 trillion by 2012, and it has maintained an average annual growth rate of 14% since 1990. Spatially, the uneven distribution of WKS is distinct, with approximately 47% being concentrated in the eastern economic region, and approximately 60% to 22% of China's prefectures. Methodologically, the dataset can easily be extended to more recent years with available data. Furthermore, a systematic sensitivity analysis indicates that the depreciation rate is the most important parameter for WKS estimates. Notwithstanding certain limitations, the paper concludes that such WKS estimates, in particular with its finer spatial resolution, offer a useful baseline for quick disaster loss estimation.