The Impact of the Housing Price Index,Cement and Steel Stocks Index on Taiwan Stocks Construction Index

• Main Authors: Yan-Kai Huang, 黃彥凱
• Other Authors: 謝德宗
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/322hz5

碩士 === 國立臺灣大學 === 經濟學研究所 === 106 === This thesis mainly distinguishes the revenue of housing price index, the cost of steel, cement stock index, market supply and demand factors(such as quantity of money and lending rate) to explore how to influence the construction of stock index, in order to provide information on investment in construction investment. Due to the fact that the variables in this paper are based on time-series data and may have stochastic trend, so we employ the unit root test and make them stationary. Then, explored the long term trend between each interpretation variables and construction index by Cointegration test, explored the leading or backward indicator between each interpretation variables and construction index by Granger Causality test, explored the short-term impact of variables on the construction stock index by Vector Error Correction Model, and finally proposes significant variables on the error correction model to establish a multiple regression to explore various factors for the impact of construction stock index. The result of our empirical research which is based on statistical methods are as follows as: (1) In the cointegration results, we find that Construction stock index, steel prices of H type and Cement stock index have positive long-term trends, Construction stock index and lending rate have negative long-term trend. (2) In the Granger Causality results, we find that Construction stock index synchronizes steel prices of H type, and leads rest of interpretation variables. (3) In the Vector Error Correction model results, we find that changes of the construction stock index is inversely affected by two-period-lag of Housing price index and M2 quantity of money, and positively affected by one-period-lag of cement stock index, steel price of H type, and real estate burden rate. (4) In the multiple regression results, we find that one-period-lag of cement stock index has positive influence on construction stock index, and one-period-lag of lending rate and two-period-lag of quantity of M2 have negative influence on construction stock index.