Long-Run Construction Cost Trends: Baumol’s Cost Disease and a Disaggregate Look at Building Material Price Dynamics
Publication: Journal of Construction Engineering and Management
Volume 144, Issue 7
Abstract
Decision-support tools for infrastructure planning assume that the real cost of construction (i.e., the cost of construction when adjusting for inflation) will remain constant over the life cycle of a facility. This paper is the first of its kind to evaluate the validity of this assumption by assessing the long-run (i.e., multidecade) nature of construction costs. This study begins by testing for the possibility that Baumol’s cost disease, a phenomenon found in some industries in which labor compensation growth outpaces productivity gains, thus giving way to real cost growth, afflicts the construction sector. To do so, a series of regression models are developed using historical macroeconomic data from the US Bureau of Economic Analysis on construction costs, compensation, productivity, and the price of intermediate and capital goods. Because construction cost growth is also closely tied to price changes for inputs, this research extracts long-run real price trends of important intermediate goods used in construction through time-series methods applied to publicly available data from the US Bureau of Labor Statistics and the US Geological Survey. The results of this study provide strong empirical evidence that Baumol’s cost disease is present within the construction sector, whereas the real price of most construction commodities has not exhibited a negative nor positive secular trend over the last century. These two findings suggest that, contrary to the conventional assumption found in current analytical frameworks, the real cost of construction will rise in the long run. This study’s contribution should motivate decision-makers to re-examine their existing decision-support tools, because the value of policies that reduce project completion times and increase the service life of facilities is potentially much higher than currently anticipated.
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Data Availability Statement
The data analyzed in this study are made available by the following agencies:
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US Bureau of Economic Analysis (https://www.bea.gov/itable/index.cfm)
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US Bureau of Labor Statistics (https://www.bls.gov/data/)
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US Geological Survey (https://minerals.usgs.gov/minerals/pubs/historical-statistics/)
Information about the Journal’s data sharing policy can be found here: http://ascelibrary.org/doi/10.1061/(ASCE)CO.1943-7862.0001263
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Published In
Journal of Construction Engineering and Management
Volume 144 • Issue 7 • July 2018
Copyright
©2018 American Society of Civil Engineers.
History
Received: Apr 25, 2017
Accepted: Jan 15, 2018
Published online: May 9, 2018
Published in print: Jul 1, 2018
Discussion open until: Oct 9, 2018
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