Forecasting skilled construction labor demand ensures that the construction industry can train and supply an adequate workforce. Crucial to developing reliable forecasts is the collection of accurate and consistent data on which to base projections. This article summarizes research efforts to formally identify and collect quality economic and construction industry data intended for use in a labor forecast model. The methodology used to collect data for five key independent variables (interest rate, material price, construction output, productivity, and real wage) and a dependent variable (labor demand) from a variety of data sources is discussed. An assessment of the availability and quality of the data is made, and recommendations are given on how it can be improved. With these recommendations, more extensive data collection can be undertaken to produce accurate and consistent data. Doing so will provide the construction industry with more meaningful skilled labor data to support accurate forecasts for planning, recruitment, and retention efforts. This article fills a significant void in addressing construction industry data.
AgapiouA.PriceA.McCafferR. (1995). Planning future construction skill requirements: Understanding labor resource issues. Construction Management and Economics, 13, 149-161.
2.
AllenP. G.FildesR. (2001). Econometric forecasting. In Scott ArmstrongJ. (Ed.), Principles of forecasting: A handbook for researchers and practitioners (pp. 301-356). Norwell, MA: Kluwer Academic.
3.
AllmonE.HaasC. T.BorcherdingJ. D.GoodrumP. M. (2000). U.S. construction labor productivity trends, 1970-1998. Journal of Construction Engineering and Management, 119(2), 97-429.
The Business Roundtable. (1983). More construction for the money: Summary report of the construction industry cost effectiveness project (Technical report). New York, NY: Author.
12.
ChanA. P. C.ChiangY. H.MakS. W. K.ChoyL. H. T.WongJ. M. W. (2006). Forecasting the demand for construction skills in Hong Kong. Construction Innovation, 6, 3-19.
13.
CoughlinJ. F. (2009). Longevity, lifestyle, and anticipating the new demands of aging on the transportation system. Public Works Management & Policy, 13, 201-311.
GoodrumP. M.ZhaiD.YasinM. F. (2009). Relationship between changes in material technology and construction productivity. Construction Management and Economics, 20, 417-428.
16.
IbbsW. (2012). Construction change: Likelihood, severity, and impact on productivity. Journal of Legal Affairs and Dispute Resolution in Engineering and Construction, 4(3), 67-73.
17.
JacobsE. E. (Ed.). (2007). Handbook of U.S. labor statistics: Employment, earnings, prices, productivity, and other labor data (10th ed.). Lanham, MD: Berman Press.
18.
KeslingB. (2013). “Flour challenged by shortage of skilled labor amid US shale boom”. Retrieved from http://hydrocarbonprocessing.com/
19.
PriceW. (2002). Innovation in public finance implications for the nation’s infrastructure. Public Works Management & Policy, 7(1), 63-78.
20.
PryorF. L.SchafferD. L. (1999). Who’s not working and why: Employment, cognitive skills, wages, and the changing U.S. labor market. Cambridge, UK: Cambridge University Press.
21.
RojasE.AramvareekulP. (2003). Is construction labor productivity really declining?Journal of Construction Engineering and Management, 129(1), 41-46.
22.
RosenfeldY.WarszawskiA. (1993). Forecasting methodology of national demand for construction labor. Construction Management and Economics, 11(1), 18-29.
23.
RSMeans. (1990-2012). Building construction cost data. Kingston, MA: Author.
24.
SongL.AbouRizkS. (2008). Measuring and modeling labor productivity using historical data. Journal of Construction Engineering and Management, 134, 786-794.
UwakwehB. O.MaloneyW. F. (1991). Conceptual model for manpower planning for the construction industry in developing countries. Construction Management and Economics, 9, 451-465.
WhitesideJ.II. (2006). Construction productivity. In AACE International Transactions (pp. 8.1-8.8). AACE International.
31.
WongJ. M. W.ChanA. P. C.ChiangY. H. (2007). Forecasting construction manpower demand: A vector error correction model. Building and Environment, 42, 3030-3041.
