NextProf Seminar

Start Date: 
Monday, October 22, 2012 - 11:00am to 12:00pm
Presenter: 
Stephanie Vereen

Forecasting Skilled Labor Demand in the Construction Industry

Presenter: Ms. Stephanie Vereen Ph.D. Candidate North Carolina State University Monday, October 22, 11.00 AM Room 2355 GG Brown Abstract:

Ensuring an adequate supply of skilled laborers to meet demand and avoid potential shortages and surpluses has been an issue of concern to construction industry professional and researchers for quite some time. An inability to accurately predict impending skilled labor shortages coupled with the current record unemployment rates in the United States construction industry present challenges to identifying skilled labor recruitment and training needs. The research focuses on developing a forecasting model that is adequate for predicting skilled labor demand in the United States construction industry. Previous researchers have addressed long term labor supply needs, factors attributing to shortages, and labor demand forecasts in other countries. A web-based proprietary labor market forecasting tool for the United States has also been developed.

The presentation highlights progress to date including data collection, preliminary analysis and outcomes, and expected contributions to the construction industry. To this point, monthly data on labor demand, construction output, productivity, interest rate, material prices, and real wage have been collected from 1990 to 2005. Data collection from the Bureau of Labor Statistics, Census Bureau, and other sources has been challenging because collection methods have been updated over time and data categorizations have changed. The degree to which labor demand is related to the noted factors has been evaluated; other factors that drive construction output still need to be investigated. It is anticipated that the final forecast model can assist the construction industry, policy makers, and researchers in planning for future staffing, policy, and research to support a more balanced workforce for the industry, avoiding both severe shortages and surpluses.

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