Abstract
In recent years, domestic housing prices have slowed down due to the weak economic growth, the implementation of real estate tax, as well as the impact of the decline in trading volume of houses. However, to solve this situation, the domestic real estate authorities launched a related policy, including housing tax base downward adjustment, to amend the urban renewal regulations and to accelerate the reconstruction of urban old buildings, etc. It is said the policies are likely to help the real estate market to recover. Take the whole world in view, there are many factors to affect the world economy. For example, the Withdrawal of the United Kingdom from the European Union, the Fed’s rate-raising campaign, geopolitical risk. If the economic growth rate is generally expected to be better than last year in the next half year, but it changes as the international economic situation and global financial markets change. Those are the factors which will still affect the domestic housing market. It can be seen that the real estate itself is not uniform, but also impacted by the macroeconomic variables, so when we analyze the real estate prices, if we can discharge the difference of real estate conditions themselves, then we can analyze the scale of each the macroeconomic variable on the impact of housing prices. Many literatures pointed out that the relationship between housing prices and the macroeconomic variables is strong. Therefore, this study is based on the housing price data of Taipei City, Xinbei City, Taichung City, Tainan City and Kaohsiung City. During the period from 2012 AD to 2016 AD, the data were used as in-samples, and take the information from January to April in the year of 2017 as out-sample data. The main purpose of this thesis is to find out the factors that affect the real estate price changes from the macroeconomic side, so that the people and the government can grasp the information in advance to help making decisions. Further, we forecast real estate prices and expect to find a model to predict reasonable future prices.