Abstract: Income to housing price ratio is the measurer of housing affordability,the indicator of bubbles in the real estate market,and one of the important indexes in subjectively measuring the well-being of citizens.As an important index of measuring whether the housing price matches residents’ income,the ratio of income to housing price has distinctive regional characteristics.Most of the studies of China’s housing affordability ignore the spatial effects of geography,lack of intuitive spatial and temporal patterns,and do not find the influencing factors of regional residential housing affordability from the perspective of geography.Therefore,it is of great theoretical and practical significance to explore the temporal and spatial evolution characteristics and influencing factors of China’s housing affordability from the perspective of geography.This paper takes the income to housing price ratio as the measurement index,explores the law of the evolution and influencing factors of the income to housing price ratio of 346 municipal units in mainland China from 2012 to 2017 with the Theil index,the σ coefficient,the spatial classification method,the Moran’ I index and the spatial regression model.The results show as follows: (1) From 2012 to 2017,the overall ranking of municipal unit income to housing price ratio in China is East>Central>Northeast>West.The relative and absolute differences are increasing,and the housing affordability is steadily increasing. (2) From 2012 to 2017,the spatial differentiation of the income to housing price ratio is significant.The spatial polarization effect is significantly enhanced in China.The regions with the lower-level ratios are mostly concentrated in the eastern part of China,the medium-level areas are mostly distributed in the central and northeastern part of China,and the higher-level areas are mostly distributed in the western part of China.The number of municipal research units in a reasonable range of the income to housing price ratio has increased significantly,accounting for 66.8% of the total in 2017.China’s income to housing price ratio has a significant spatial agglomeration,the Moran’ I index is gradually increasing.The number of income to housing price ratio increases in both HH and LL districts,and there is a positive correlation feature. (3) Per capita gross domestic product (X1),urbanization rate (X2),per capita real estate investment level (X5),and city size (X7) are the main influencing factors affecting China’s income to housing price ratio.From 2012 to 2017,the per capita GDP (X1) has a significant positive impact on the ratio in the eastern,central and western regions; the urbanization rate (X2) has a significant impact on the ratio in the northeast regions from 2014 to 2017 positively and in the east regions from 2016 to 2017 negatively; the industrialization level (X3, X4) has a significant negative impact on the ratio in the western regions from 2014 to 2017;the level of real estate investment (X5) has a significant negative impact on the ratio in the northeast and east regions; the per capita fiscal revenue (X6) has a significant negative impact on the ratio in the eastern regions from 2012 to 2017;the city size (X7) has a significant negative impact on the ratio in the northeast,east,central and western regions from 2012 to 2017.

Key words: income to housing price ratio, temporal and spatial evolution, affecting factors, China