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CONSTRUCTION INDUSTRY PRODUCTIVITY

CONSTRUCTION INDUSTRY PRODUCTIVITY: Its History and Future Direction

(By Preston H. Haskell)

December, 2004 Abstract: Extant data on construction industry productivity are conflicting and incomplete, and no aggregate productivity measures are maintained by either government or industry. This research, covering a period of 37 years through 2003 and using two distinct methodologies, finds that aggregate productivity has increased approximately 33 percent during that period, which is substantially below that of U.S. industry generally. The author makes observations and recommendations for the acceleration of productivity growth and the rationalization and standardization of productivity measurement within the construction industry. Introduction This paper analyzes and reports on long-term trends in construction industry productivity between the years 1966 to 2003, and the particular segment studied is the U.S. building construction industry. In contrast to many previous studies, it is concerned with overall, aggregate productivity, i.e., both labor and non-labor (principally materials and equipment). As in other research, productivity is defined as aggregate output divided by aggregate input at one or more given points in time. The purpose of this paper is threefold: · To establish and document aggregate productivity increases during the study period · To identify the sources of productivity growth and their quantitative contributions to aggregate productivity · To identify areas where potential exists for increased productivity, which may then be pursued to increase industry productivity and profitability Background Despite the immense size and importance of the construction industry to the U.S. economy, construction productivity is one of its most controversial and least understood factors. Productivity in the construction industry is largely unmeasured, and those measures that do exist are contradictory and conflicting. For example, the Bureau of Labor Statistics does not maintain an official productivity index for the construction industry, the only major industry so treated. Many measurements and studies of productivity at the aggregate level show long-term declines1 while others consistently show improvement.2 Yet another major study found that it cannot be determined if productivity has increased, decreased or remained constant.3 Clearly, there is lack of agreement and understanding in this field. The principal reason for such divergence of data and lack of understanding is the absence of a consistent measure of aggregate output. Other industries can readily measure output, such as tons of steel or bushels of wheat or numbers of automobiles. The construction industry, however, has no such easily recognizable output measurement. At the task level, output may be measured in cubic yards of excavation, square feet of formwork, or cubic yards of concrete placement, but none of these provides a recognizable and workable measure of aggregate output. Input, on the other hand, is more easily measured. Almost all researchers use man-hours or constant dollars as a measure of labor input, and chained or constant dollars as a measure of non-labor input. Because real

wages in the industry have declined during the study period, labor dollars and labor man-hours cannot be used interchangeably without adjustment for this decline.4 Methodology For purposes of this paper, aggregate productivity is determined using constant dollars as the input (for both labor and non- labor expenditures) and square feet of building area adjusted for quality changes as the measure of aggregate output. Task productivity is determined using labor man-hours as input and production units as output. Because this paper deals only with building construction, other sectors of the construction industry are of necessity not considered, because their output is not measurable in building area. However, building construction represents over 82% of the entire industry,5 so that the scope of this paper corresponds to the dominant share of the construction industry. Moreover, materials and methods in the nonbuilding sector (chiefly transportation and utilities) are so different that it merits an approach to productivity measurement distinct from that of this paper. The study period for this paper, 1966 to 2003, is chosen for several reasons: (1) it is of sufficient length to overcome short-term fluctuations in pricing and other conditions, (2) it corresponds generally with the study periods of other researchers, particularly Teicholz,6 (3) it corresponds to the personal industry experience of the author and most of the individual sources consulted, and (4) the year 2003 is the latest date for which full statistical data are available. However, by using 2003 as the ending year, the recent sharp runup in prices of significant construction commodity materials is excluded; if the year 2004 were included, productivity metrics would be somewhat diminished. In the sections which follow, two distinct and independent methodologies are used to determine productivity changes. The first approach is an output-based one, in which real costs, in dollars per square foot for several buildings types, further adjusted for enhancements in quality and content, are compared over the study period. The second approach, termed the input-based approach, constructs a model based upon observable changes in labor productivity at the task level, changes in real materials costs, and changes in costs of tools and equipment utilized at the jobsite.* In seeking the most appropriate inflation factor for conversion of current dollars to constant dollars, both broad measures of cost change and industry-specific cost indices were considered. These tend to diverge from one another from time to time, but in comparing the Bureau of Labor Statistics (BLS) Consumer Price Index from the year 1966 to 2003, and the Engineering News Record Building Cost Index for the same period, an extraordinary agreement was found. Both indices increased by a factor of 5.68 between 1966 and 2003.7 This factor is therefore used throughout this paper to adjust costs between these two years. For periods in between the beginning and ending years, the BLS Consumer Price Index is used. Finally, it should be noted that the quantitative data used herein are, in many cases, inexact estimates, gathered from sources having varying degrees of accuracy. While every attempt has been made to verify and refine these data, they remain estimates, but ones whose accuracy is, in the author’s opinion, adequate for the broad conclusions reached herein.

• The use of the words “input” and “output” in this context should not be confused with the use of those words in the definition of productivity.

Output-Based Approach This approach compares unit costs, in dollars per square foot, of buildings constructed in 1966 with comparable buildings constructed in 2003. The latter costs are then deflated to 1966 costs, using the factor of 5.68.

Table 1. Changes in Unit Costs of Construction 1966-20038

Building Type Cost/s.f. 1966

Cost/s.f. 2003

2003 Cost Adjusted to

1966

1966-2003 Change

Market Weight*

Weighted Change

Warehouse $4.30 $21.00 $3.70 (14.0%) .04 .56% Retail $13.00 $63.33 $11.15 (14.3%) .20 2.86% Office $18.50 $91.00 $16.02 (13.4%) .21 2.81% Multifamily Residential

$8.90 $45.50 $8.09 (11.1%) .55 6.11%

Total 12.34% The data in Table 1 show that real construction costs per square foot have decreased by approximately 12.3%. This figure, however, does not reflect the increases in quality and content mandated by codes, higher life cycle expectancy, sustainability, energy conservation, security, accessibility, and higher quality expectations generally, during the study period. Therefore adjustments to unit costs must be made in order to obtain qualitative comparability. These adjustments are shown in Table 2.

Table 2. Impact of Quality Improvements Upon Unit Costs9

Category 37-Year

Cost Impact Occupant safety requirements, including fire protection sprinklers, fireproofing, fire resistant materials, exitway enhancements, etc.

3.1%

Code-mandated improvements in seismic and windstorm resistance 1.6% Improvements due to better life-cycle cost expectancy, especially in building envelope materials and construction and interior finishes and equipment

3.3%

Sustainability enhancements such as stormwater catchment, recycling and reuse, environmentally friendly materials, pollution reduction (green buildings), increased landscaping

2.7%

Impact fees, offsite improvements, and concurrency 1.2% Accessibility compliance (ADA) 1.3% Enhanced security features 1.0% Improved energy efficiency 2.8% Indoor air quality, mold prevention, asbestos remediation 1.6%

Total 18.6%

__________________________ * There is not provision in this table for single-family residential construction due to the absence of reliable data over the study period. This paper therefore uses multifamily residential as a proxy for all residential, and gives it weight reflective of all residential construction. Similarly, retail and office are overweighted as proxies for institutional and other commercial buildings, and warehouse is similarly weighted to include light manufacturing buildings.

The quantitative decrease in unit cost from Table 1 (13%) is combined with the qualitative increase in the product from Table 2 (17.6%) to obtain a total productivity increase using the following formula:

PT = [(1+PN) x (1+PL)] -1

where PT = total productivity increase, PN = quantitative productivity increase, and PL = qualitative productivity increase. Using this formula,

PT = (1.123 x 1.186) -1 = 0.332 or 33.2%

Total productivity increase using real unit area costs adjusted for quality is thus found to be approximately 33.2%. We now turn to the alternative, input-derived methodology.

Input-Based Approach The input-based approach studies the effect of (1) observable increases in labor productivity, offset by increases in capital costs and (2) documented decreases in real materials costs. Examination of labor productivity was undertaken in three broad categories: general construction, which includes earthwork, sitework, structure, building envelope, and finishes; mechanical construction, including HVAC, plumbing and fire protection; and electrical construction. Estimates of task productivity increases are multiplied by weighting factors. A weighting factor represents the estimated portion of the labor force which is affected by that particular task improvement. The products of productivity increases multiplied by weights are then totaled to obtain aggregate productivity, expressed as a percent of total labor expenditure in that category. Table 3 displays labor task productivity gains in the general construction category.

Table 3. Labor Task Productivity Increases – General Construction10

Task

Task Productivity

Increase

Task Weight

Weighted Increase

Machine excavation and trenching in lieu of hand excavation, power compaction in lieu of hand tamping.

250%

.02

5.0%

Motorized screeds, power floating and troweling machines, and concrete pumps

150%

.05

7.5%

Gang forms, table forms, and tunnel forms. 110% .01 1.1% Widespread use of motorized, compressed air, and cordless hand tools.

100%

.25

2.5% Prefabricated roof trusses and stud walls replacing joist-and-rafter roofs and handassembled walls.

125%

.01

1.3%

Less materials handled/worked due to higher strength materials 15% .10 1.5% Computerized transits and levels. 100% .01 1.0% Lightweight manlifts and scissors lifts in lieu of ladders and scaffolds. 100% .02 2.0% Motorized scaffolds in lieu of hand-erected ones for exterior masonry and envelope trades.

25% .

.01

0.3%

Laser level instruments for interior finish trades 20% .04 0.8%

Single ply membrane and seam welding roof materials vs. multi-ply built-up

125%

.02

2.5%

High-strength adhesives for joining, anchoring and adhering vs. mechanical fasteners

75%

.02

1.5%

Water based paint vs. oil based paint, other easier-to-use finish materials

30%

.01

0.3%

Enhanced on-site communications using handheld telephones 20% .10 2.0% Less restrictive work rules, greater flexibility in labor assignment, multitasking

20%

.35

7.0%

Miscellaneous NOC 4.0% Total 40.3% Table 3 demonstrates that overall labor productivity has increased by approximately 40% in the general construction category. Using similar methodology, Tables 4 and 5 analyze labor productivity increases in the mechanical and electrical construction categories.

Table 4. Labor Task Productivity Increases – Mechanical Construction11

Task

Task

Productivity Increase

Task Weight

Weighted Increase

Offsite prefabrication of piping assemblies 50% .04 2.0% PVC pipe replacing lead-joint cast iron soil pipe 150% .05 7.5% CPVC pipe replacing copper and steel water pipe 70% .06 4.2% Victaulic couplings replacing threaded fittings 75% .03 2.3% Sheet metal ductwork fabricated offsite in factory conditions 75% .08 6.0% High density polyethylene pipe and heat-fusion joints replacing steel pipe and threaded joints

100%

.03

3.0%

Computerized detailed layouts of piping, ductwork and equipment (CAD) 20% .30 6.0% Enhanced jobsite communication through extensive use of hand-held telephones

20%

.10

2.0%

Factory-built “package” chillers, boilers and other major equipment 75% .03 2.3% Machine welding replacing hand welding on large steel piping 75% .03 2.3% Operator-friendly hydraulic cranes, high-reach lifts, less hand hoisting 50% .06 3.0% More flexible, less restrictive division of labor 20% .40 8.0% Electronic DDC controls replacing pneumatic 150% .02 3.0% Miscellaneous NOC 3.0% Total 54.6%

Table 5. Labor Task Productivity Increases – Electrical Construction12

Task

Task

Productivity Increase

Task Weight

Weighted Increase

Improved tools and equipment, including cable pullers, power threaders, hoisting equipment, power scaffolds, high-reach lifts, one-shot conduit benders

60%

.12

7.2%

Precut and prespooled cable, lighter insulation, pneumatic pull lines replacing fishtape

50%

.08

4.0%

PVC conduit, including rolled PVC and Smurf, replacing metal 200% .07 14.0% “Relock” lighting system, prewired modules 100% .02 2.0% High-temperature plenum cables replacing wire in conduit 150% .02 3.0% Flexible metal-clad cable replacing wire in conduit 200% .03 6.0% 277-volt and 480-volt distribution replacing 120/240-volt

60%

.04

2.4%

More efficient, higher-output equipment, e.g. lighting and motors 60% .02 1.2% Computerized controls and solid state energy management systems replacing open-contact relays and associated field labor

150%

.03

4.5%

Wireless devices for security and sensing replacing wired ones 200% .01 2.0% Computerization of supervisory and management functions, including purchasing, estimating, cost control, detailed layouts and conflict avoidance

75%

.10

7.5%

More sophisticated personnel due to increased training, use of semiskilled labor

15%

.80

12.0%

Enhanced on-site communications using hand-held telephones 20% .10 2.0% Miscellaneous NOC 3.0% Total 70.8% There is a clear spread in labor productivity gains among the three categories, with electrical construction showing greatest gains, approximately 71%. This is understandable: electrical is the most technology- intense of the three, and has also benefited significantly from the widely admired NECA-IBEW collaboration which has driven craft training and competencies to the highest among the construction trades. Mechanical construction is second to electrical with a labor productivity increase of approximately 54%, and general construction is farther behind, at approximately 40%. Mechanical construction typically represents 16% of total labor, electrical approximately 12%, and general construction the remainder, 72%.13 The productivity increases for each category are blended to obtain aggregate labor productivity increase using the following formula:

PL = (0.72 x PG) + (0.16 x PM) + (0.12 x PE) where PL = total labor productivity increase, and PG, PM, and PE = categorical labor productivity increases for general, mechanical, and electrical construction respectively. Using this formula,

PL = (0.72 x 0.403) + (0.16 x 0.546) + (0.12 x 0.708) = 0.463, or 46.3%

Because labor productivity increases are principally the result of automation and mechanization, resulting from new or improved tools and equipment, the increased cost of such equipment must be subtracted from the productivity increase.* Otherwise stated, there is a tradeoff between labor savings and equipment costs which must be accounted for.

The cost of power tools and capital equipment used or consumed at the jobsite increased from approximately 5% of total construction cost in 1966 to approximately 9% in 2003,14 a figure which would be higher were it not for significant decreases in the real costs of tools and equipment. This difference must be subtracted from the labor productivity gain. But labor, including benefits, is only approximately 33% of jobsite costs in building construction;15 as seen above, the value of tools and construction equipment utilized constitutes 9%; materials account for the remainder, 58%. Thus it is necessary to determine the changes in materials costs, using methodologies similar to those used for labor costs. The author’s research of cost changes in major categories of construction materials is found in Table 6. Here again, significant gains are observed through price decreases, quality improvements, and/or substitution of lower-cost or higher quality materials.

Table 6. Selected Construction Materials Cost Changes 1966-200315

Material 1966

Price or Index

2003 Price or Index

2003 Real

37-Year Change

Weight Weighted Value

Concrete 13.10 72.10 12.69 (.03) .09 (.027) Structural Steel 8.25 25.30 4.32 (.48) .10 (.048) Reinforcing Steel and Mesh 8.20 25.60 4.51 (.45) .02 (.009) Aggregates and Stone (.30) .03 (.009) Masonry (.15) .04 (.006) Gypsum and Plaster Products 45.6 155 27.3 (.40) .03 (.016) Wood 40 145 25.5 (.34) .11 (.038) Plastics/Thermoplastics/Elastomerics/ Composites

11.20 29.53 5.20 (.54) .12 (.065)

Glass/Aluminum Products (.40) .04 (.020) Paints, coatings, floor/wall coverings (.45) .04 (.014) Light and Sheet Metals, Piping 50 155 27.2 (.46) .06 (.028) Electrical Materials (.45) .05 (.015) Manufactured Products – Mechanical 159 595 104 (.35) .09 (.035) Manufactured Products – Electrical (.33) .04 (.013) Manufactured Products – Other (.35) .10 (.035) All Other Materials (.40) .04 (.016) Total 1.0 (.364) __________________________ *The cost of equipment at the jobsite may be measured in several ways: rental expense, original cost minus salvage or resale value, or depreciation expense for the duration of utilization. In general economic terms, all three produce approximately the same result. The foregoing table indicates that, on a weighted basis, real costs of materials for building construction have declined approximately 36.4% during the 37-year study period.

Finally, to arrive at the aggregate productivity increase, the three components of change – labor and benefits, materials and capital – are combined using the following formula:

PT = (0.33 x PL) – ? C + (0.58 x PM)

where PT = total productivity increase, PL = total labor productivity increase, ? C = change in capital equipment costs expressed as a percentage of total construction cost, and PM = material cost improvement. Using this formula,

PT = (0.33 x 0.463) – 0.04 + (0.58 x 0.364) = 0.324 or 32.4% This input-derived increase of 32.4% corresponds closely to the output-based one of 33.2%, which used real unit costs adjusted for content and quality enhancements. Conclusions Two independent methodologies demonstrate that total construction productivity has increased during the past 37 years, on the order of 33 percent, or 0.78% per year. We are receiving more building for less money than we did 37 years ago, and moreover, the product is qualitatively superior. These improvements are the result of increased productivity made possible by mechanization, automation, prefabrication, less costly and easier-to-use materials, and lower level of real wages (which, unlike the other drivers, is not a good thing). The industry has transferred tasks from the field to the shop, automated many of the tasks in the field, benefited from lower cost materials, and taken advantage of labor-saving materials. This level of productivity improvement, however, is less than one-half that of U.S. nonagricultural productivity gains during the same period, which averaged 1.75% annually between 1966 and 2003.17 Much of this differential is due to the inherent nature of the construction industry: its products are mostly one of a kind and largely handcrafted, while other industrial products are factory-based and assembly line-produced. The industry is highly fragmented, both vertically and horizontally. Finally, industrial manufacturers benefit from the research and development activity which they fund, whereas in the fragmented construction industry, research is nearly nonexistent because architects and engineers have neither the resources nor incentive to fund research, and constructors have little ability to influence innovation in architectural, engineering, or product design. But productivity gains in construction can and must continue. In the author's view, the potential for further productivity enhancements falls into five categories: Information technology. This is the area in which the greatest labor productivity improvements will occur in the near term. Visualization and 4D immersion technology 12 will drive planning and scheduling. Handheld computers will assist supervisors with layout and interpretation of drawings (“pocket CAD”), and serve as computerized timecards for labor cost and payroll reporting. Digital cameras linked to offices of the project manager and architect-engineer will display field conditions and problems, leading to rapid and accurate decisionmaking and problem solving. Wireless strain gauges imbedded in concrete pours will permit more rapid form removal. RFID technology will improve logistics, track materials locations, and better control tools and equipment. Project delivery. The continued integration of design, fabrication, and construction will enhance productivity through faster and more accurate decision making and communications, through cost-based design decisions, through design innovation, through enhanced interoperability, and through shortening of the project delivery

cycle. Additionally, when both designers and constructors have a stake in the outcome, they can and will invest more in research and development. Automation and prefabrication. This has been the chief source of recent labor productivity gains and will continue. Among tasks ripe for increased productivity are, for example, fusion-welded reinforcing bar cages and mats, premanufactured spaces such as bathrooms and kitchens, and at-grade erection of roof structures followed by jacking into place. Robotics and telerobotics will make the ir way from the factory floor to the construction site. Tools and equipment will continue to increase in efficiency, userfriendliness and performance, and will decrease in real cost. Workforce development. Craft recruitment, training and retention have been uneven across the industry, particularly as unionization of the building trades declined. In recent years, the National Center for Construction Education and Research and employer-based programs have begun to close the training gap, which will lead to higher productivity through better trained and multitask-capable craftsmen. Enlightened, productivity-oriented employers will recognize the value of recruitment and retention initiatives, including higher wages, gainsharing, and emphasis upon advancement and promotion. Materials. Lower cost, higher quality, substitute, and easier-to-use materials have played an important role in aggregate productivity gains. The competitive nature of the U.S. economy ensures that these gains will continue, but they can be accelerated through greater collaboration among manufacturers, designers and constructors. From the foregoing discussion, it is also evident that accurate and accepted standards for measuring construction industry productivity are much needed. It is the author's opinion that an appropriate standard, at the very least, would be the one explicated in the output-based approach above: real unit area cost adjusted for quality enhancements. The Bureau of Labor Statistics, in collaboration with representatives from the industry, should develop a weighted "basket" of unit costs representative of the building construction industry. These costs would be periodically surveyed, and adjusted for quality enhancements, in much the same fashion as the Consumer Price Index is constructed. A more ambitious but worthwhile pursuit would be a system of national productivity measurements at the task level, then aggregated in a fashion similar to the input-based approach above. While this would require greater resources for data-gathering and analysis, it would provide much more detail as to the sources and degrees of productivity change than the simpler output-based methodology. In any case, having sophisticated productivity measurements for the building construction industry would result in several benefits. They would serve to identify the value of new labor practices, technologies, materials and project delivery methods. They would permit comparison of productivity improvements across regions of the country, identifying those with superior methodologies and sharing that knowledge industry wide. They would identify areas in which research and development should be undertaken to greatest advantage. Most importantly, they would position the construction industry, long known for inferior and inconsistent profitability, to emulate the productivity, and therefore profitability, of other U.S. industries.

Source Information Acknowledgements Support, encouragement and assistance in the preparation of this paper came from numerous sources. Harvey M. Bernstein, as president of the Civil Engineering Research Foundation and now vice president for industry analytics of McGraw-Hill Construction, provided the initial stimulus for undertaking the project. Janice L. Tuchman, editor- inchief of Engineering News Record and a long time reporter on productivity issues in her own right, provided news coverage of my efforts and made available members of her editorial and research staff, particularly Debra Rubin and Tim Grogan, to provide valuable historical cost information. Professor Paul M. Goodrum of the University of Kentucky furnished to me the considerable body of published research undertaken by him and his colleagues, and others in the academic community. For providing highly informative and practical labor productivity data, I am indebted to three leading industry figures, H. E. “Buck” Autrey of Miller Electric Company, and William W. Gay and Henry H. Beckwith of W. W. Gay Mechanical Contractors. I was also provided immeasurable support and information by my Haskell Company colleagues, in particular chief executive Steve Halverson who stimulated and encouraged me throughout the process. Others who provided quantitative data, and reviewed drafts of this paper and made valuable suggestions for its improvement, include David Engdahl, Greg Ferrell, Bob Soulby, Joe Varon and Boyd Worsham. To all of them I extend deep appreciation. Abbreviations BLS – Bureau of Labor Statistics, U.S. Department of Labor DOC – U.S. Department of Commerce ENR – Engineering News Record magazine THC – The Haskell Company, Architects-Engineers-Contractors Source Notes 1. Research of Paul M. Teicholz reported in ENR December 13, 1999 “Viewpoint: Reverse Productivity Declines” and updated and reported in ENR May 12, 2003 “Accurate Measures are Elusive”; Allen, S. G., Why Construction Industry Productivity is Declining, The Review of Economics and Statistics, November, 1985; Stokes, H., An Examination of the Productivity Decline in the Construction Industry, The Review of Economics and Statistics, November, 1981. 2. Goodrum, Paul M. and Haas, Carl T., Partial Factor Productivity and Equipment Technology Change at Activity Level in U. S. Construction Industry, Journal of Construction Engineering and Management, December 1, 2002; Allmon, Eric, Haas, Carl T., Bocherding, John D. and Goodrum, Paul M., U. S. Construction Labor Productivity Trends, 1970-1998, Journal of Construction Engineering and Management, March/April, 2000. 3. Rojas, Eddy M. and Aramvareekul, Peerapong, Is Construction Labor Productivity Really Declining?, Journal of Construction Engineering and Management, January/February, 2003. 4. BLS reports that average hourly wages for employees of general contractors, expressed in 1990 dollars, declined from $16.00 in 1968 to $13.75 in 1998 but peaked at $17.80 in 1972. This profile reflects very accurately the steep runup in union wages from the late 1960s to the early 1970s, which collapsed in the recession and open shop movement of the mid-1970s. The author’s observations and THC records, which are based upon both union and open-shop labor, show that

real hourly wages have experienced similar decline. 5. DOC, Economics and Statistics Administration, Annual Value of Construction Put-in-Place from 1994-2003, August, 2004. 6. Teicholz, op. cit. 7. The BLS Consumer Price Index increased from 97.2 in 1966 to 551.1 in 2003, a factor increase of 5.68. The ENR Building Cost Index increased from 650 to 3693 over the same period, again a factor increase of 5.68. 8. The cost figures are taken from THC records reflecting average total costs for similar buildings in each building type, generally in the southeastern U.S. The market weights are derived from DOC, op. cit. A description of each building type follows: Warehouse: Truck-height floor, 24-foot clear height, tilt-up concrete walls with architectural exterior finish, 15 f.c. lighting, heating and ventilation. Retail: National retail chain stores (drug, variety and discount department stores) in community malls, including proportionate sitework. Office: Three-story suburban office with normal sitework, interior tenant finishes to typical standard. Multifamily Residential: Two-story garden apartments, wood and brick exterior, typical interior finishes with kitchen and laundry appliances, parking and sitework, no covered garages. 9. Author’s experience and THC cost records. 10. Author’s experience, THC records, Allmon et al., op. cit., and Goodrum and Haas, op. cit. 11. Author’s interviews with Henry H. Beckwith and William W. Gay, cost records of W. W. Gay Mechanical Contractors, Inc., and author’s observations.

12. Author’s interviews with H. E. Autrey, cost records of Miller Electric Company, and author’s observations. These data pertain primarily to nonresidential construction, but similar changes

have taken place in residential construction including, for example, substitution of plastic slipthrough boxes for steel and clamp connectors, plastic snap connectors in lieu of steel clamps, lighter nonmetallic cables, and push-on device terminals. 13. Author’s experience and THC records. 14. THC cost records and author’s experience. 15. Interviews with Gay and Autrey supra, THC cost records, and author’s observations.

16. ENR Materials Price Indexes, BLS Producer Price Indexes, THC cost records, and author’s observations. Where quality improvements have occurred during the study period (e.g., 60 ksi

structural and reinforcing steel vs. 40ksi), a price reduction is applied to the 2003 value. Where a material did not exist in 1966 (e.g., thermoplastic polyolefin roofing membrane), the price of a

material which it substantially replaced is used. Where a price or index did not exist in 1996 but did no later than 1982, the later price is adjusted to 1966 using the CPI. 17. BLS, Private Nonfarm Business: Productivity and Related Indexes 1948-2003.