Relationship between Stocks of Construction Companies and the Gross Domestic Product in the US

There is a sizeable amount of research that investigates the relationship between the construction market and the economy. However, the impact of key companies in the construction market on the economic performance still requires more research. The goal of this research is to investigate the connection between the GDP, as a measure of the economic performance, and the stock prices of large publicly traded companies in the construction industry, in the U.S. This is achieved by analyzing the GDP, total construction spending (TTLCONS), S&P 500 Index (GSPC), and the stocks of large companies in the construction field. The analysis methods include: 1) statistical analysis using correlation analysis and Granger causality testing, and 2) vector auto-regression (VAR). Analysis is performed using R. Preliminary results show positive correlations between the GDP, TTLCONS, GSPC, and the stock prices. Granger causality testing showed a satisfactory causality of the stock prices on the GDP. A VAR model was developed and used to predict the GDP for the coming two years. In order to validate the VAR model, it was fitted for historical data before the year 2008 and tested for its ability to predict the 2008 economic crisis. The model correctly predicted the crisis within a satisfactory level of accuracy. This research proposes the significance of investigating the effect of key players in construction on the economy. It presents a new perspective on the relationship between the construction market and economic performance.