Can housing price regulation improve R&D performance in universities? Evidence from China

The house property tax pilot policy (HPTPP) introduced in 2011 has resulted in the redistribution of R&D resources. However, few studies have focused on the impacts of this policy. In this paper, we use the heterogeneous stochastic frontier analysis method to measure the R&D total factor productivity (TFP) growth rate of Chinese universities. Then, the difference-in-differences (DID) method is employed to examine the impact of the HPTPP on R&D performance. Furthermore, a series of robustness tests are conducted on the estimated results, including: a parallel trend test, by advancing the introduced time of policy; a reduction of the self-selection bias, by adopting the propensity score matching (PSM); and an interference elimination of the house-purchasing restriction policy. Finally, based on the extensive margin and the intensive margin, we investigate the mechanisms of the HPTPP on R&D performance. The results show that the R&D TFP of Chinese universities displays a downward trend. After reducing self-selection bias, the HPTPP exerts no significant effect on R&D TFP growth rate of Shanghai's universities, but the HPTPP does reduce the R&D TFP growth rate of universities located in Chongqing. This conclusion remains robust after changing the matching ratio of the PSM strategy and eliminating the interference of the house-purchasing restriction policy. For Shanghai's universities, the effects of the HPTPP on extensive margin (i.e., factor input scale) and intensive margin (quantity of efficient factors) are not clear, resulting in an uncertain impact on R&D TFP growth rate. However, for Chongqing, the negative effect on the scale of factor input leads to a decline in R&D TFP growth rate of universities. Therefore, when restraining housing prices, the government should prevent the negative effect on R&D investment and attract high-end talent through preferential conditions.