Input–output efficiency of the housing provident fund in China: temporal-spatial variations and influencing factors

The input–output efficiency of China’s Housing Provident Fund (HPF) program has received increasing academic attention in recent years. However, few studies have been conducted to examine its temporal-spatial variations and influencing factors. To fill the gaps, this study first used a DEA model to measure the input–output efficiency of HPF of 287 Chinese cities from 2015 to 2020, and then employed the Tobit regression model to determine the main influencing factors. Results indicate: (1) China's HPF input–output efficiency grew consistently from 2015 to 2020, remaining relatively high even during the Covid-19 outbreak. (2) HPF's efficiency displays notable spatial variation, with values higher in the eastern region and large cities compared to the western/central areas and medium/small cities. (3) Macroeconomic factors, housing market conditions, and HPF management elements significantly influence HPF efficiency, yet specific impacts vary; some factors (e.g., housing prices, capital investment intensity, fund utilization level) are positive, while others (housing price-to-income ratios, commercial housing loan interest rates, number of contributing employees) are negative. This study enhances understanding of HPF efficiency over time and space in China, offering insights for policy reform and system enhancement.