An Analysis On Influence Of Housing Price To Aggregate Price Level Variation

When the year of2007passed, the consistent growth of China’s GDP came to an end. In a situation of high price level and the Subprime Crisis, the realty industry became a prime force to stable the economy. As the first sign of economic recovery emerged at the beginning of the year of2009, the realty industry developed rapidly, with a quantity of investment imbued. In2010, first-tier cities suffered a constant increase in housing price, which reflected the boom of realty industry. The year-on-year growth of new-estate-price indices of Beijing and Shanghai went on a level of10%for2seasons. Increases of housing price in adjacent cities were also in brew. However, under thorough macro-control efforts, the widespread trend of excessive prices terminated, In2011, new regulation policies came out of China central government and local government in quick succession, of which the National Eight Bills and tax on private estate were the most inexpensive. Soon, profiteering-attitude-driving purchase and hoarding for speculation were effectively dismissed. Furthermore, the supply-demand structure of estate market was improved and the tendency of housing price increasing was ceased. At the beginning of2012, business recession in China and a stable but slightly decreasing housing prices simulate the demand of private estate. At the end of2012, China’s estate market was in a resurgence, which was linked to the macro-economic revival, and housing prices in main first-tier and second-tier cities began to go up.In condition of housing prices’variation and ambiguous tendency, realty industry attracted more and more attention. Based on existent researches, the author will develop a threshold panel data model, which includes New Keynesian Philips Curve and estate price variable to make a representation of housing-price-to-price-level variation relations and regime effects. Moreover, shock factors such as second-handed estate prices, M2and interest rate are included too. Data in this paper ranges from July of2005to December of2012.The main content of this paper is as follows. The first chapter is the introduction, stating the background and value of the paper. The second chapter is an introduction to the history of Philips Curve. The third chapter is an introduction to threshold panel Model, where the threshold estimating procedure, the criteria to find the number of thresholds, slope parameter estimating procedure, some statistic characters and hypothesis tests of all parameters are introduced. In the fourth chapter, the author executes three regressions based on35-cities-data of China, in order to describe the regime effects of housing price to price level. A brief analysis is also given. The fifth chapter comes as conclusion, providing policy suggestions and declaring the shortcomings of this paper.The main conclusion is as follows. Firstly, Subprime Crisis and European Debt Crisis struck the economy of the whole world and China surely a victim. From change in output-gap structure, we know that China’s economy suffered a recession after these two crisis, following which may be a permanent economic transition-to bad sides. Secondly, as the structure of inflation-output relation changes, the modes of housing price explaining price level variation mismatch here and there. Besides main effects of parameter-based explanation shifting from new estate to second-handed estate, housing price regulation cannot be neglected either. Thirdly, from parameters of monetary policy variables, the short-term "housing price to price lever" mismatch will exist for a time, especially under the condition of conflicts of "economic growth stabilization" and "estate price suppressing".