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Carpenter, N and Bausman, D C (2016) Project Delivery Method Performance for Public School Construction: Design-Bid-Build versus CM at Risk. Journal of Construction Engineering and Management, 142(10).
Chang, C and Chen, S (2016) Transitional Public–Private Partnership Model in China: Contracting with Little Recourse to Contracts. Journal of Construction Engineering and Management, 142(10).
Chen, C, Wang, Q, Martek, I and Li, H (2016) International Market Selection Model for Large Chinese Contractors. Journal of Construction Engineering and Management, 142(10).
Choi, J O, O’Connor, J T and Kim, T W (2016) Recipes for Cost and Schedule Successes in Industrial Modular Projects: Qualitative Comparative Analysis. Journal of Construction Engineering and Management, 142(10).
Choi, K and Lee, H W (2016) Deconstructing the Construction Industry: A Spatiotemporal Clustering Approach to Profitability Modeling. Journal of Construction Engineering and Management, 142(10).
de Castro e Silva Neto, D, Cruz, C O, Rodrigues, F and Silva, P (2016) Bibliometric Analysis of PPP and PFI Literature: Overview of 25 Years of Research. Journal of Construction Engineering and Management, 142(10).
Duzkale, A K and Lucko, G (2016) Exposing Uncertainty in Bid Preparation of Steel Construction Cost Estimating: I. Conceptual Framework and Qualitative C-I-V-I-L Classification. Journal of Construction Engineering and Management, 142(10).
Duzkale, A K and Lucko, G (2016) Exposing Uncertainty in Bid Preparation of Steel Construction Cost Estimating: II. Comparative Analysis and Quantitative C-I-V-I-L Classification. Journal of Construction Engineering and Management, 142(10).
Gwak, H, Son, S, Park, Y and Lee, D (2016) Exact Time–Cost Tradeoff Analysis in Concurrency-Based Scheduling. Journal of Construction Engineering and Management, 142(10).
Harper, C M, Molenaar, K R and Cannon, J P (2016) Measuring Constructs of Relational Contracting in Construction Projects: The Owner’s Perspective. Journal of Construction Engineering and Management, 142(10).
Moret, Y and Einstein, H H (2016) Construction Cost and Duration Uncertainty Model: Application to High-Speed Rail Line Project. Journal of Construction Engineering and Management, 142(10).
Namian, M, Albert, A, Zuluaga, C M and Jaselskis, E J (2016) Improving Hazard-Recognition Performance and Safety Training Outcomes: Integrating Strategies for Training Transfer. Journal of Construction Engineering and Management, 142(10).
Poshdar, M, González, V A, Raftery, G M, Orozco, F, Romeo, J S and Forcael, E (2016) A Probabilistic-Based Method to Determine Optimum Size of Project Buffer in Construction Schedules. Journal of Construction Engineering and Management, 142(10).
Ramaji, I J and Memari, A M (2016) Product Architecture Model for Multistory Modular Buildings. Journal of Construction Engineering and Management, 142(10).
Salas, R and Hallowell, M (2016) Predictive Validity of Safety Leading Indicators: Empirical Assessment in the Oil and Gas Sector. Journal of Construction Engineering and Management, 142(10).
Sveikauskas, L, Rowe, S, Mildenberger, J, Price, J and Young, A (2016) Productivity Growth in Construction. Journal of Construction Engineering and Management, 142(10).
- Type: Journal Article
- Keywords: Productivity; Construction industry; Statistics; Regulations; Quantitative methods;
- ISBN/ISSN: 0733-9364
- URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001138
- Abstract:
Measuring productivity growth in construction has been a classic challenge, largely because reliable output deflators are scarce. This paper reports first results from a Bureau of Labor Statistics research group convened to measure construction productivity better. Results show that labor productivity growth has been positive, and fairly substantial, in all four industries where reliable deflators now exist. Shifts of labor between construction industries reduce productivity growth by 0.4% a year. Regulation is a significant negative effect on productivity, but reduces productivity growth by only 0.1% a year. Undocumented immigrants are important in construction, and often work off the books, but reasonable allowance for their increased presence reduces productivity growth by only 0.1% a year. The influences examined are not sufficient to explain why productivity growth is so much lower in construction than elsewhere. Later work will measure productivity growth in a broader range of industries, including some industries representing contractors. However, this further work requires access to restricted Census microdata, and so will take several years more to complete.