Construction Productivity: A Proposed Model to Improve Construction Price Indices in the United States

摘要

The U.S. Census Bureau accounts for 60 to 80 percent of change in home prices through its hedonic indices (Census Bureau 2005b), however knowledge of reliability problems led the Census Bureau to cease its production of yearly adjusted construction output. The ability to accurately measure construction inflation is critical in developing reliable industry productivity measures. Typically, macroeconomic studies involving industry aggregated output measures have shown a decline in construction productivity (Stokes 1981, BRT 1983, Allen 1985, and Teicholtz 2000), while micro studies involving activity based data have shown an increase (Allmon et al. 2000 and Goodrum et al. 2002). A dominant theory to explain these opposing results is that current measurements of construction inflation do not adequately consider the change in quality and amenities provided in modern structures as compared to when the measurements were first established (Rosefielde and Mills 1979, Pieper 1990, Gullickson and Harper 2002). The U.S. Census Bureau New One-Family Houses under Construction Price Index is one of the industry's major measurements of construction inflation. Previous research suggests that omitted quality variables in the Census' price index leads to an omitted variable bias which overestimates construction inflation, leading to both an underestimate of construction industry output and productivity. This paper, as part of an ongoing study, examines the process for implementation of private sector data as well as statistical variable selections in an effort to improve model accuracy. The current hedonic regression model used by the Census Bureau to estimate this price index is based predominately on factors that have not changed since its inception in 1963. Implementation of Bayesian Information Criteria variable selection coupled with an alternative data source in the form of the Multiple Listing Service data from the Board of Realtors indicated improvements are possible. This paper examines these two instruments and explains the process of implementation.