Examining the determinants of housing prices and the influence of the spatial–temporal interaction effect:The case of China during 2003–2016

The slowdown of the Chinese economy has been accompanied by a recent rapid rise in housing prices,which has put severe pressure on China's high-quality development.Therefore,understanding the impact of the spatial–temporal interaction effect on housing prices and their potential determinants is critical for formulating housing policies and achieving sustainable urbanization.This study empirically analyzed both of these based on four aspects—the financial market,housing market,housing supply,and housing demand—using 2006–2013 data of 285 prefecture-level(and above)Chinese cities and spatial econometric models.The results indicated that the housing prices of Chinese cities were heavily affected by the interaction effect of space and time,both at the national and regional levels;however,the influence of this interaction effect exhibited a significant spatial differentiation,and only consistently drove up housing prices in Eastern and Western China.Additionally,the regional results based on administrative and economic development levels revealed that wage and medical service levels in first-and second-tier cities had negatively affected the competitiveness and efficiency of the Chinese economy during the investigation period.These findings suggest the need for land supply systems based on the increasing population to prevent housing prices from rising too quickly as well as policies that consider regional variations,accompanied by corresponding supporting measures.

Measuring the Imbalance of Regional Development from Outer Space in China

We develop a statistical framework to use the data of night-time-lights(DN)from satellite to augment official GDP measures,and a non-linear substitution relationship between DN and GDP is given.In this paper,we take advantage of DN instead of GDP to measure the imbalance of regional development(IRD)in China by using the method of bi-dimensional decomposition under the population-weighted coefficient of variation.The method enables us to analyze the contributions of DN components to within-region and between-regions inequality under the framework which has been proposed,we can get the conclusion that the imbalance between-regions rather than within-region is the main reason for the influence of IRD for the whole country in China.

The impact of demographic changes on the unbalanced development of the national public pension system in China’s provinces

China’s public pension system is managed at the provincial level.In recent years,the development of public pension system in the provinces has become more unbalanced.The increase in the gap between the developed and less developed regions of China has become increasingly evident.Based on an analysis of changes to population structure in each province during the 20 year period 1995-2015,combined with research focused on public pension policy,this paper finds that there are great differences in the structure of population in each province with respect to age,type(the ratio of local residents to migrants),and quality(the proportion of the population with higher education).All of these are important factors that help to explain the unbalanced development of the public pension system.China’s developed regions have cumulative advantages in these three areas,and this study found that the gap between developed and less developed regions was growing.Among the three factors,the influences of population age and quality structure were a reflection of normal social phenomenon,while variations of population type structure in the provinces were largely a result of the way in which China’s public pension transfer policy is designed.In this paper,the author argues that if barriers to migration were removed,greater population mobility would help realize national management of the public pension system.