Reference

NATL INST. OF STAND & TECH

NBS

Publications

it of Commerce

u of Standards

AlllDS T7ME1E

NBS Technical Note 1172

Productivity

Measurement for the

Construction Industry

IGU

. U5753

1172

1963
NATIONAL BUREAU OF STANDARDS

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HATIONAL BUREAU OF STANDARDS UERApy

fi'^5 ftrJJ^CtfJ i^^ APR 8 1983

fir

Productivity IVIeasurement for the

Construction industry

,\ i

Stephen F. Weber

Barbara C. Lippiatt

Center for Applied Mathematics

National Engineering Laboratory

l^tional Bureau of Standards

Washington, DC 20234

Prepared for: Center for Building Technology

National Bureau of Standards

Washington, DC 20234

U.S. DEPARTMENT OF COMMERCE, Malcolm Baldrige, Secretary

NATIONAL BUREAU OF STANDARDS, Ernest Ambler, Director

Issued February 1983
National Bureau of Standards Technical Note 1 1 72

Natl. Bur. Stand. (U.S.), Tech. Note 1 172, 39 pages (Feb. 1983)

CODEN: NBTNAE

U.S. GOVERNMENT PRINTING OFFICE

WASHINGTON: 1983

For sale by the Superintendent of Documents, U.S. Government Printing Office, Washington, DC 20402

Price $4.50

(Add 25 percent for other than U.S. mailing)
ABSTRACT

The fundamental concept underlying all productivity measures is a comparison of

the output of a production process, an enterprise, an industry, or an economy

with the corresponding factors of production (inputs) required to genera;te that

output. Productivity measures are formulated as a ratio of output to one or more of the inputs. This report evaluates alternative productivity measures

and concludes that the comprehensive Total Factor Productivity (TFP) method is

preferred to the Single Factor Productivity method. To combine the multiple

components in the denominator of a TFP index, a weighting system based on relative factor cost shares is recommended. A measurable index of the instantaneous

rate of change in TFP between two time periods is derived from a general production function. The report also investigates the specific data requirements for

implementing this TFP measure in the construction industry. An annotated

bibliography is included.

Key words: construction industry; economics; index; input; output; productivity

measurement; single factor productivity; total factor productivity.

iii
PREFACE

This research was funded by the NBS Center for Building Technology. The authors

wish to thank Michael Boehtn for his assistance in searching for literature on productivity. Philip Schoech of Laurits R. Christensen Associates, Inc. deserves

thanks for his advice on methods of quantifying inputs and outputs for measuring

industry productivity. Through their comments and helpful suggestions, the

following NBS reviewers contributed significantly to this final report: Robert

Chapman, James Gross, Harold Marshall, Mary Natrella, Fred Ruddair, and Richard

Wright.

iv
TABLE OF CONTENTS

Page

ABSTRACT iii

PREFACE ^ iv

LIST OF TABLES vi

1

INTRODUCTION 1

2. COMPONENTS OF PRODUCTIVITY INDEXES 2

2 .

OUTPUT 2 2.2 LABOR INPUT 3

2.3 MATERIALS INPUT 3

2.4 CAPITAL INPUT 3

3. SINGLE FACTOR PRODUCTIVITY MEASUREMENT 6

3.1 CONSTRUCTION INDUSTRY STATISTICS 6

3.1.1 Productivity Indexes 6

3.1.2 Labor and Materials Requirements Studies 8

3.2 LIMITATIONS OF SINGLE FACTOR PRODUCTIVITY MEASURES 8

4. TOTAL FACTOR PRODUCTIVITY MEASUREMENT 12

4 .MEASUREMENT METHOD 12

4.2 APPLICATION TO CONSTRUCTION INDUSTRIES 15

APPENDIX: ANNOTATED BIBLIOGRAPHY ON PRODUCTIVITY MEASUREMENT A-1

A.l PRODUCTIVITY MEASUREMENT METHODS A-1

A. 2 PRODUCTIVITY IN THE CONSTRUCTION INDUSTRY A-4

A. 3 PRODUCTIVITY MEASUREMENT CASE STUDIES A-9
LIST OF TABLES

Page

3.1 Annual Index Values for Output per Employee Hour in the U.S.

Construction Industry, 1947-1979 (1967 = 100) 7

3.2 Annual Rates of Growth for Output per Employee Hour in the U.S.

Construction Industry, by Beginning and Ending Year of Period,

1947-1979 (Percent) 9

3.3 Single Factor Productivity Measurement: An Illustration 11

4.1 Hypothetical Industry Data for Two Time Periods 14

4.2 Hypothetical Data on Output and Input Quantities, Input Prices,

and Cost Shares of an Industry for Two Time Periods 16

4.3 Data Available in the 1977 Census of Construction 17

4.4 Standard Industrial Classification (SIC) Titles for Construction

Industries 19

vi
1 . INTRODUCTION

This report sununarlzes the results of an investigation into methods for

measuring productivity and their application to the U.S. construction industry.

The fundamental concept underlying all productivity measures is a comparison of

the output of a production process, an industry, or an economy with the corre- sponding factors of production (inputs) required to generate that output. The

output and inputs of production thus constitute the basic components of every

productivity measure. Typically, productivity measures are formulated as a ratio of output to one or more of the inputs. Methods of deriving quantitative

measures of these output and input components of productivity indexes are discussed in section 2. If only one of the inputs is used in the denominator,

then the ratio is a single factor productivity measure. A common example of

this type of measure is output per labor hour. Single factor productivity

measures will be discussed in section 3. If all of the inputs are used, then

the r^tio is a total factor productivity measure. The main problem in developing a total factor productivity ratio concerns the proper weighting system to use when combining the individual input components into an index to serve as the denominator. In section 4, a mathematical model of the production processis used to develop the theoretically appropriate weighting system for combining

input components. In addition to discussing these two basic types of productivity measures and their application to the construction industry, this report

provides an annotated bibliography on productivity measurement. The three

parts of this bibliography found in the Appendix deal with general productivity

measurement methods, productivity in the construction industry, and case studies

of productivity measurement.
2. COMPONENTS OF PRODUCTIVITY INDEXES

The development of both single and total factor productivity indexes requires

accurate measures of output and input quantities. Ideally, these components

of productivity indexes are denominated in physical units of measurement. Such

data become less available, however, as levels of economic activity become more

aggregated. Thus, one typically uses quantity indexes that are obtained by

deflating to their constant dollar equivalent, the current dollar values corre- sponding to the physical quantities in order to correct for price changes.

Other measurement considerations that apply to all components include:

(1) development of an appropriate weighting system if heterogeneous items

comprise a single component; (2) adjustment for changes in component quality

over time; and (3) inclusion of new outputs and inputs introduced into the

production process. •'^

2 . 1 OUTPUT

It is easier to establish meaningful measures of the quantity of output for

industries and processes, the more homogeneous that output is. For example', a figure for bushels of wheat produced is more meaningful than is the number of

buildings constructed. If meaningful quantity data are not available, the

appropriate dollar measure of output is receipts plus increases (minus

decreases) in the value of finished good inventories.'^ Since the contract con- struction industry does not hold inventories, but rather receives payment based

upon completion (or progress toward completion) of work, the value of receipts

need not be adjusted for inventory changes. On the other hand, such an adjustment should be made to receipts of Operative Builders, who are defined as "builders primarily engaged in construction of single family houses and other

buildings for sale on their own account rather than as contractors. "^ When

measuring industry productivity, it is important to exclude from the output measure receipts for subcontracted construction work, in order to avoid double

counting.^ In addition, receipts for nonconstruction activities such as architectural services and mortgage banking should be excluded, unless these

activities are the object of the productivity measurement.

If output is to be measured by receipts (and inventory changes), this figure

should be deflated with an index of output prices rather than of input costs.

^ Component measurement issues are also discussed in studies by the National

Research Couucil (see Appendix, subsection A.l), Adam and Dogramaci,

Greenberg, Kendrick and Creamer, and Siegel (see Appendix, subsection A. 3),

2

3

Memorandum by Philip E. Schoech, Laurits R. Christensen Associates, Madison,

WI, May 27, 1981.

U.S. Office of Management and Budget, Standard Industrial Classification

Manual: 1972 (Washington, DC: U.S. Government Printing Office, 1972), p. A7,

^ When measuring the productivity of construction projects, however, revenues

that cover subcontracted work could be included in the output measure.
Input cost indexes do not provide the necessary adjustments for possible changes

in profit margins (i.e., output prices) nor in productivity itself. ^ For example, suppose receipts increased solely as a result of increased output prices,

while output quantities, input quantities and input prices remained constant.

The input cost index used to deflate receipts would leave them unchanged. As a result, productivity would appear to increase, although the ratio of real output

to real input had not changed. Conversely, suppose productivity had actually

increased through an increase in output quantities while input quantities

remained constant. If output prices were constant while input prices increased,

then the use of an input cost index to deflate receipts would incorrectly

diminish the measured productivity increase.

2.2 LABOR INPUT

Labor input can be denominated in labor hours actually worked adjusted for

changes in the mix of labor categories employed. Hours worked (hours paid less

holiday and leave hours) is preferred over hours paid as the measure of labor

hours because productivity indexes are meant to deal with technological relationships between output and inputs. An hour paid but not worked simply raises

the compensation paid for each hour actually worked. Changes in the labor mix

can be accounted for by weighting the number of hours worked for each labor

category by the value of its contribution to output. If we assume a competitive labor market, so that each labor category is paid a wage equal to its

marginal contribution to output, then we can weight hours worked of each labor

category by the corresponding average hourly earnings.

A measure of labor input equivalent to that of weighted labor hours can be

obtained by deflating total labor compensation with an index of average hourly

earnings. This index should be weighted to reflect the relative size of each

labor category, the weights varying in accordance with the labor mix."^

2.3 MATERIALS INPUT

Materials input refers to all inputs not classified as labor or capital. In

dollar terms, it is the value of output minus the value that is added to purchased goods and services by a firm's production processes. Since the materials

used by one firm are the outputs produced by other firms, materials measurement

issues are similar to those discussed -for output in subsection 2.1.

2.4 CAPITAL INPUT

Capital input is by far the most difficult component of productivity indexes to

quantify. Unlike materials, measurable quantities of which are completely

^ H. Kerable Stokes, Jr., "An Examination of the Productivity Decline in the

Construction Industry," The Review of Economics and Statistics , Vol. 63,

No. 4 (November 1981), pp. 495-502.

2 John W. Kendrick and Daniel Creamer, Measuring Company Productivity; Handbook

with Case Studies , Studies in Business Economics, No. 89 (New York: National

Industrial Conference Board, Inc., 1965), pp. 33-36.
consumed during the current time period, capital provides a flow of services

that extends beyond the current period. Moreover, although capital is similar

to labor in that both provide a service flow, service prices and service price

indexes can be readily observed for labor but not for capital. Thus, data are rarely available that can directly measure capital's contribution to production

over the relevant time periods. Real (i.e., constant dollar) capital input

must therefore be derived by one of several alternative estimating procedures.

In general, these procedures arrive at real capital input by multiplying real

capital stock by a ratio that reflects the value of capital services per period

per unit of capital stock. The differences in these procedures include whether

they use stock measures that are gross or net of depreciation, whether they

adjust estimated stocks for rates of utilization, and whether they adjust for

capital quality change.

Real capital stock can be' estimated using the perpetual inventory method. As

implemented by Caves, Christensen, and Swanson,! this method cumulates, by

capital type, a lengthy time series of investment expenditures that has been

deflated by an investment price index and adjusted for real .capital depreciation. Real net capital stocks are then estimated by adding these cumulated,

adjusted investment expenditures to an observation of real capital stock at

the beginning of the time series and then summing across capital types. A less

rigorous estimate of net capital stocks can be obtained by converting book values of capital stocks to market values by applying a standard ratio of book-tomarket value for each capital type.^ Alternatively, a measure of gross capital

stock can be obtained by transforming book values into constant dollar

acquisition prices by taking the age profile of capital into account. -^

Unit costs of capital services are typically estimated by some measure of the

real rates of return to capital types. An important issue here is the appropriate role for depreciation allowances. Another issue is whether to weight

annual estimates of capital stocks by a single base-year rate of return, or by the real rate of return relevant for each year.

There is some question as to the proper treatment of rented capital. Since

rental payments are made to other firms in return for their services during

the current period, rented capital can be considered a materials input. Alternatively, it can be treated as capital, and deflated rental payments can be

used to reflect real rented capital input.

D. W. Caves, L. R. Christensen, and J. A. Swanson, "Productivity in U.S.

Railroads, 1951-1974," Discussion Paper #7909 (Madison, WI: University

of Wisconsin, Madison, April 1979), pp. A5-A8.

2 Memorandum of Philip E. Schoech, May 27, 1981.

o

-* National Research Council, Panel to Review Productivity Statistics,

Measurement and Interpretation of Productivity (Washington, DC: National

Academy of Sciences , 1979) , p. 130.
All components of a given productivity index must be measured consistently.

First, the output and input measures must reflect the same economic activity.

If the output measure excludes some activity of the firm (e.g., force account

construction!), then th6 inputs that contribute to that activity should be

excluded from the input measure(s). Secondly, all indexes used to construct

component measures must have the same base year, the year in which the index

is set at 100.0. Finally, every effort should be made to collect component

data from the same source to ensure comparability.

! Force account construction is defined as "...construction work performed by

an establishment primarily engaged in some business other than construction,

for its own account and use and by its own employees...." U.S. Office of

Management and Budget, Standard Industrial Classification Manual; 1972 , p. 46.
3. SINGLE FACTOR PRODUCTIVITY MEASUREMENT

Single factor productivity (SFP) Indexes measure the ratio of output to one

input, usually labor. These single factor indexes require a limited amount of

data, are relatively easy to calculate, and are widely used. In many cases,

however, they inaccurately represent the course of technological change. This

section summarizes information relevant to SFP in the construction industry,

and then illustrates the shortcomings of SFP measures.

3.1 CONSTRUCTION INDUSTRY STATISTICS

Data relevant to construction industry single factor productivity measurement

are available in two basic forms: (1) productivity indexes, and (2) studies of

labor and materials requirements. Each will be discussed in turn.

3.1.1 Productivity Indexes

The Bureau of Labor Statistics (BLS) publishes an annual bulletin entitled

Productivity Indexes for Selected Industries . The 1979 edition (Bulletin 2054

released 12/79) of this annual series included 88 industries and designated

them by Standard Industrial Classification (SIC) number. Although this publication includes neither the construction industry as a whole nor its various

segments, a number of construction-related industries are explicitly included,

such as: sawmills and planing mills, general (SIC 2421), veneer and plywood

(SIC 2435, 2436), hydraulic cement (SIC 3241), structural clay products

(SIC 325), clay construction products (SIC 325, 3253, 3259), and concrete products (SIC 3271, 3272). For each of these industries the bulletin publishes

time-series indexes of output per employee and output per employee hour going

back to the 1950' s.

In addition to these published data on productivity, BLS can make available

unpublished data in the same form for 549 other Industries. Of these industries

at least 50 are related to the construction industry, ranging from prefabricated

wood buildings and structural wood members (SIC 2452), to flat glass (SIC 3211),

mineral wool (SIC 3296), and construction machinery (SIC 3531).

Besides this information on construction-related industries, the BLS can make

available on an unpublished basis some data on the construction industry taken

as a whole. Computer print-outs of time series index numbers (1967 = 100)

going back to 1947 are available for a number of key variables describing the

construction industry. These annual statistics include: total output in

constant dollars, total output in current dollars, compensation paid to all

employees, number of employees, number of hours paid, nonlabor payments, nominal compensation per hour, real compensation per hour, unit labor costs, unit

nonlabor payments, implicit price deflator, average weekly hours, and most

importantly for those concerned with productivity, output per employee and

output per employee hour. An example of these annual index series is presented

in table 3.1 for output per employee hour in the construction industry. The

print-outs also present, in a matrix format, the annual rates of growth derived

from these time series index numbers for every pairwise combination of years

throughout the entire time series. An example of these unpublished computer
Table 3.1 Annual Index Values for Output per Employee Hour in the U.S.

Construction Industry, 1947-1979 (1967 = 100)

Year

1947

1948

1949

1950

1951

1952

1953

1954

1955

1956

1957

1958

1959

1960

1961

1962

1963

Index

55..2 59,.6 59..9 63..2 64..2 65,.6 68..8 72..1 72..3 72..3 74..6 80,.3 81..8

84..9 87..0

88,.3 88..5

Year

1964

1965

1966

1967

1968

1969

1970

1971

1972

1973

1974

1975

1976

1977

1978

1979

Index

93.1

95.7

96.3

100.0

103.6

94.0

89.4

86.2

84.6

80.1

77.2

78.4

81.3

79.9

74.3

68.9

Source: U.S. Department of Labor, Bureau of Labor Statistics,
print-outs is given in table 3.2. To find the rate of growth for any given

period, read down the left-hand column stopping at the beginning year of the

period. Then read across that row to the column corresponding to the ending

year of the period of interest. The number thus found at the intersection of

the beginning year row and the ending year column is the annual rate of growth

in percent between those two years. For example, output per labor hour

declined by 2.2 percent annually during the nine year period from 1970 to 1979.

Each rate of growth shown in table 3.2 represents the slope coefficient, multiplied by 100, of the least squares regression of the natural logarithm of the

output per employee hour index on the year index, for all the years in each

period. The algebraic expression for this slope coefficient is

n n n

n Z i In P^ - [ Z i)( E In P^)

i=l i=l i=l , n n

n Z i2 - ( Z i)2

i=l i=l

where i = 1,2,..., n, the year index for each year in the period, including

the beginning and ending years; and

Pjl^ = annual index (1967 = 100) for the i year, of output per employee

hour in the U.S. construction industry, as presented in table 3.1.

3.1.2 Labor and Materials Requirements Studies

Another useful source of information related to productivity in the

construction industry is a series of studies on the labor and materials requirements for various construction Industry sectors. •' Each sector is devoted to a specific type of construction project. The project types that have been

studied include: civil works construction, college housing construction,

Federally aided highways. Federal office buildings, hospitals, private multifamily housing, private singlefamily housing, public housing, schools, and sewer works. These studies present data on the number of onsite and off site

employee hours used in a sample of projects per $1000 of total contract cost.

Some of these studies also report employee hours per square foot of floor area.

3.2 LIMITATIONS OF SINGLE FACTOR PRODUCTIVITY MEASURES

y

One purpose of measuring productivity is to determine whether and to what

extent technological change has occurred over time in a production process, an individual firm or plant, an industry, or even an entire economy. Alternatively, productivity measures may be used to compare two processes, firms,

industries, or economies at the same point in time to determine which entity is

technologically superior. Both purposes involve the comparison of technologies.

For example, see Robert J. Prier, "Labor Requirements Decline for Public

Housing Construction," Monthly Labor Review , Vol. 103, No. 12 (December 1980),

pp. 40-44.

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0) x: M-l

l-i 3 O I-l CO

M-lO 01 Mj U

X • 3

01 /^

—

m

•C3 o • C O r~i *

1-1 •-H

p

CD o h M r-l JD

CO XI CO

(L I-- CO

J

X -o c

0) <V 01 •a 4J s c c 4-1 iH 0) I-l 01 CO rH 0) a

CO

M 0) 3 a o C

12 0) •

CO CO en
Technology is here to be interpreted in the broad sense as the entire process

required in transforming inputs to outputs. Thus technological change may

arise from innovations in equipment, organization, information, or management.

In certain very restricted situations, SFP measures are able to confirm the

occurrence of technological change. For example, if only one input such as labor is reduced while output and all the other inputs remain unchanged, then

the resulting increase in labor productivity (output per labor hour) would be

sufficient to confirm that technological change has occurred. Similarly, if

all inputs remain unchanged or decrease while output increases, then all of the

SFP measures would increase. In this case, any one of these measures would

confirm the occurrence of technological change. Neither of these restrictive

situations in which SFP successfully tests for technological change permits

more than one input quantity to change. In practice, however, most changes in

technology require the substitution of one input for another, so that SFP

indexes are rarely useful in measuring technological change.

The hypothetical example in table 3.3 serves to illustrate the ambiguities that

result when SFP measures are used to identify technological change. Column 3

indicates that while quantities of output, labor input, and materials input

have all increased from period 1 to period 2, the use of capital has declined.

Column 4 presents the SFP measure for each input, derived by dividing the index

of change for output (i.e., 1.100) by that input's index of change. A value

less than one indicates a decline in productivity, equal to one no change, and

greater than one an increase in productivity. Thus, in this example, labor

productivity has declined, materials productivity has remained constant, and

capital productivity has increased. If one measured labor productivity only, a technological setback would be indicated, whereas if capital were selected

instead, one would conclude that a positive technological change had occurred.

In fact, the actual cause of the SFP changes may not have been technological

change at all. For example, another common cause of SFP changes is a mere shift

in relative prices, which in turn leads to substitution between inputs. ^ Thus,

in this illustration, labor productivity may have fallen and capital productivity risen simply because the price of labor fell relative to the price of

capital, causing substitution of labor for capital. Alternatively, the

measured changes in SFP may have arisen from some combination of technological

and relative price changes. This potential ambiguity in SFP indexes suggests

that a broader measure of technological change is needed. Such a measure is

discussed in the next section.

^ Edv/in Mansfield, Microeconomics: Theory and Applications , 3rd edition (New

York: W.W. Norton and Company, 1979), pp. 516-517.

10
Table 3.3 Single Factor Productivity Measurement: An Illustration

Quant tty^ Index of

Productivity Period 1 Period 2 Change

Component (1) (2) (3)=(2)/(l)

Output 500 550 1.100

Input

Labor 130 150 1.154

Materials 100 110 1.100

Capital 80 70 0.875

Single Factor

Productivity Measure

(4)=1. 100/(3)

n/a

0.95

1.00

1.26

^ Quantities can be denominated either in physical units of measurement or in

quantity index numbers derived by dividing current dollar values by their

appropriate price indexes, as discussed in section 2.

11
4. TOTAL FACTOR PRODUCTIVITY MEASUREMENT

As demonstrated in the previous section, SFP measures are ambiguous because

they only take account of one factor of production. The value of the SFP

measure of a given production process or entire Industry depends critically on which single factor of production is taken into account. Consequently, what is

required for most analysis is a productivity index that takes account of all

major inputs in the production process. Such a comprehensive index of productivity is usually referred to as a total factor productivity (TFP) index.

4.1 MEASUREMENT METHOD

Although several theoretical approaches to measuring the TFP of industries and

individual firms have been developed, ^ the present discussion focuses on the

TFP measurement method developed and applied to the railroad industry by Caves,

Chrlstensen, and Swanson.2 The measurement procedure proposed by Caves et al.

has been selected because it avoids restrictive assumptions about the form of

the underlying production function selected to represent an Industry or firm.

A production function shows the maximum obtainable output rates for all possible

sets of input usage rates and, by definition, specifies a particular technology.

Caves e_t al . begin by assuming that output Y is produced by combining a set of

inputs X. according to a general implicit production function:

f (Y; Xi, X2, . . ., X^; T) = 0, (4.1)

where T is time, which allows for shifts over time in the production function.

Such shifts in the production function are equivalent to changes in technology,

which could represent changes In productivity. Using a duality theorem

developed by McFadden,^ the following unique cost function corresponding to

the production function given by eq (4.1) can be specified:

C = g (Y; Wi, W2, . . ., W^; T)

,

(4.2)

1 The four basic approaches to measuring TFP are summarized briefly in an article by W. Erwin Diewert, "The Theory of Total Factor Productivity

Measurement in Regulated Industries," in Thomas G. Cowing and Rodney E.

Stevenson, eds.. Productivity Measurement in Regulated Industries (New York;

Academic Press, 1981), pp. 17-44.

2 Douglas W. Caves, Laurlts R. Chrlstensen, and Joseph A. Swanson,

"Productivity in U.S. Railroads, 1951-1974," The Bell Journal of Economics , Vol. 11, No. 1 (Spring 1980), pp. 166-181.

^ The production function employed by Caves et^ al. is more general than that

specified in eq (4.1) in that the former allows for more than one output.

^ D. L. McFadden, "Cost Revenue and Profit Functions," in M. A. Fuss and D. L,

McFadden, eds., Production Economics: A Dual Approach to Theory and

Applications (Amsterdam: North Holland, 1978).

12
where W^ is the price of input X^ and C is total cost:

n

C = Z W^Xj^. (4.3)

i=l

By taking the natural logarithm of the cost function, eq (4.2), and totally

differentiating with respect to time, Caves et^ al • allocate the rate of growth

of cost among changes in the output level, changes in input prices, and shifts

in the cost function (i.e., productivity changes in the opposite direction),

respectively:

din C ^ ain g din Y ^ ^ 31n g ^^^ ^i ^ 31n g /^ ^n

dT 31n Y dT ±=i 31n Wi dT 3T *

Following Shephard's lemma, ^ it can be shown that the first partial derivative

of the logarithm of the cost function with respect to the logarithm of each

input price is equal to the cost share of that input:

3ln W^ C ^*

where S± represents the cost share of the ith input. This useful characteristic

of the cost function can be illustrated with the hypothetical data in table 4.1.

Since the price of input i has increased by $1 between 1981 and 1982, if we hold

output, technology, all input quantities, and all other prices constant, then

total cost will increase by $200. Using 1981 as the base year, the continuous

partial derivative, 31n g/31n W^^, can be approximated with discrete data by the

ratio of the percentage change in total cost to the percentage change in the

price of input i, that is, [(10,200 - 10,000)/10,000]/ [(11 - 10)/ 10] = 0.2.

Consequently, 31n g/31n Wj^ = S-j^, since the cost share of input i in the base

year is [ ( 10)(200)]/10,000 = 0.2.2

1 Ronald W. Shephard, Cost and Production Functions (Princeton: Princeton

University Press, 1953), reprinted as Vol. 194 of the series, "Lecture Notes

in Economics and Mathematical Systems," M. Beckmann and H. B. Kiinzi, eds.,

(New York: Springer-Verlag, 1981). As originally formulated by Shephard

(pp. 10-11), this fundamental result states that the factor quantities that

minimize the total cost of a production process are equal to the first partial derivatives of the cost function with respect to factor prices:

3g/3Wj^'= X^. Multiplying both sides of this equation by the ratio W^/C, and

noting that C = g and 3Z/Z = 31nZ, yields eq (4.5).

Alternatively, if 1982 is considered the base year, 31n g/31n W. is

approximated by [(10,000 - 10, 200)/10,200] / [( lO-lD/ll ] = 0.217, and the

cost share of input i in the base year is also [ (11)(200)]/10,200 = 0.217.

13
Table 4.1 Hypothetical Industry Data for Two Time Periods

Symbol Definition 1981 1982

Wi Price of Input i ($/Unit) 10 11

X^ Quantity of Input i 200 200

C Total Production Cost ($) 10,000 10,200

Caves .et^ al^« take the total derivative of the natural logarithm of eq (4,3)

with respect to time and obtain:

ji ^ ^ w.x. din W. ^ W.X. din X. din C _

J 11 1 + Z 11

dT i=i C dT i=i C dT

(4.6)

Substitution of eq (4.6) into eq (4.4) and further substitution of eq (4.5)

into the result yields the following expression for productivity change:

- 31n g = 91n g

ain Y

din Y _ dT

^ din X.

z s • i

9T 1=1 ^ dT

(4.7)

If the production process -exhibits the economic property known as constant

returns to scale, this equation can be further simplified. Constant returns

to scale means that an increase (decrease) in the quantities used of all inputs

by the same proportion will lead to an increase (decrease) in output by exactly

the same proportion. That is, any percentage change in inputs will lead to an equal percentage change in output. ^ Furthermore, if input markets are competitive, then the firm cannot influence input prices. As a result, the given percentage change in inputs will lead to the same percentage change in total cost.

Therefore, the percentage change in total cost is equal to the percentage

change in output, and the partial derivative 31n g/91n Y can be assumed to be

equal to one. The equation for productivity change then becomes :2

^ For a given industry and time period, this assumption may be valid only over

a limited range of output levels.

2 This definition of the change in TFP derived here following Caves ^t^ al. is

identical to that used by Leo Sveikauskas in a recent study of the effect of

technological inputs on industry TFP. See "Technological Inputs and Multifactor Productivity Growth," Review of Economics and Statistics , Vol. 63,

No. 2 (May 1981), pp. 275-282.

14
_ 31n g ^ din Y _ ^ g. 1 (4.8)

3T dT ^^1 ^ dT

In order to apply this index to discrete (e.g., annual) data. Caves et al.

recommend the use of first differences in natural logarithms and of beginning

and end-of-period averages for the input cost shares. Implementing this recommendation for eq (4.8), one obtains the following formula for measuring the rate

of growth in TFP compounded continuously over the time period T-1 to T:^

^ 1 TFP Growth Rate = In Y„ - In Y„ , - E ± (S. ^^ + S. ^ ,)(ln X. „ -In X. „ ,). (4.9)

i=l ^ '

The application of eq (4.9) can be illustrated with the hypothetical data

in table 4.2. The right-hand side of eq (4.9) would be evaluated in the

following manner:

In 110 - In 100 - i (0.082 + 0.115) (In 30 - In 40)

2 - i (0.150 + 0.115) (In 40 - In 30)

2 - 1 (0.768 + 0.770) (In 2200 - In 2000) = 0.0122.

This means that the continuous rate of growth in TFP between these two periods

is approximately 1.2 percent. Since the data are given as annual values for

successive years, this result is interpreted as a continuous annual rate of

productivity increase of 1.2 percent.

4.2 APPLICATION TO CONSTRUCTION INDUSTRIES

Equation (4.9) could be applied to measure the changes in TFP for individual

industries within the construction sector as well as for the sector as a whole.

Every five years beginning with 1967, the Census of Construction Industries has • been conducted. The most recent Census (1977) includes detailed information on employment, receipts, costs, and assets for the approximately

1.2 million establishments engaged in construction in the United States. ^ A

construction establishment is an office or other place of business where such

construction-related activities as estimating, bidding, scheduling, purchasing.

1 This formula can be equivalently written as

In (Y^/Y^_^) - J^I (S.^^ + S,^^_pin(X.^^/X.^^_^).

For an excellent summary of the 1977 Census results and for more detailed

descriptions of the variables included in the Census, see Abraham Goldblatt

and Patrick MacAuley, "The 1977 Census of Construction—A Wealth of Economic

Data," Construction Review , January 1981, pp. 4-12.

15
Table 4.2 Hypothetical Data on Output and Input Quantities, Input Prices,

and Cost Shares of an Industry for Two Time Periods

1981 1982

Price Cost Price Cost

Symbol Variable Quant

1

ty ($/Unit) Share Quantity ($/Unit) Share

Y Output 100 — — 110 — —

Xl Labor 40 15 0.115 30 16 0.082

X2 Capital 30 20 0.115 40 22 0.150

X3 Materials 2000 2 0.770 2200 2.05 0.768

16
Table 4.3 Data Available in the 1977 Census of Construction

Type of data Totals*

State and

industry

totals^

By

employ- ment

size

By

receipts

size

By

type of

construction

Assets and depreciation: Gross book value—total , Structures, machinery and equipment , Accumulated depreciation—total, structures, machinery and

equipment

Net value—total, structures, machinery and equipment

Depreciation charges—total, strucrures, machinery and equipment

Capital expenditures:

Total capital expenditures

New structures, machinery and equipment

Used structures, machinery and equipment

Communication services, payments for Employees:

All employees—average number ....'.

Construction workers—average number

Other employees—average number

Employer costs for fringe benefits—legally required and voluntary

expenditures

Establishments, number of:

All With payroll . . . Without payroll Materials and Energy:

Materials, components, supplies, and fuels Selected power, fuels, and lubricants

Payroll:

First quarter, all employees

Annual:

All employees

Construction workers : Other employees

Proprietors and working partners:

All establishments Establishments with payroll Establishments without payroll Receipts:

All business receipts:

All establishments Establishments with payroll Establishments without payroll Construction receipts, total For work subcontracted in from others Other business receipts and land receipts Net construction receipts Value added

Rental payments:

Total For machinery and equipment

For structures Repairs to structures and related facilities Repairs to machinery and equipment

Specialization within State Sub-contracting

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes Yes

Yes

Yes

Yes

Yes Yes

Yes

Yes Yes

Yes

Yes

Yes

Yes Yes

Yes

Yes

Yes Yes

Yes Yes

Yes

Yes Yes

Yes

Yes

Yes Yes Yes

Yes

Yes

Yes

Yes

Yes

Yes Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes Yes

Yes

Yes

Yes

Yes

Yes

Yes

1 For each four-digit industry at the national level, or for the entire construction industry for each state.

2 For each four-digit industry in each state.

Source: Abraham Goldblatt and Patrick MacAuley, "The 1977 Census of Construction—

A

Wealth of Economic Data," Construction Review, January 1981, p. 5.

17
and supervising are conducted. Table 4.3 provides a list of the categories of

data collected in the 1977 Census and indicates the level of detail available

for each category.

The data on Net Construction E.eceipts , Construction Worker Payroll, and

Materials and Energy make possible the derivation of quantity indexes for output, and for labor and materials which could be used in eq (4.9). This derivation would require the development and application of appropriate price and cost

indexes to convert these current dollar Census values to corresponding quantity

indexes, as explained in section 2. An appropriate quantity index for capital

input is not as readily available. The perpetual inventory method for determining the real capital stock used in construction cannot be applied because the

Census data do not go back far enough. The less regions approach based on the

Gross Book V-alue data in the Census could be employed, provided an estimate of

the average ratio of book-to-market value can be developed for the construction

industry. Once real capital stocks have been estimated, they can be converted

to real capital input by multiplying by the rea/ rate of return to capital in

the construction industry. The Rental Payments data could be deflated by an appropriate cost index and used to reflect real rented capital input.

Once the resulting data on all relevant input and output quantities have been

obtained, eq (4.9) could be used to calculate estimates of TFP growth for the

two five-year intervals between the years for which the Census of Construction

Industries has been conducted: 1967, 1972, and 1977. These five-year estimates of TFP growth could be derived for the entire construction sector of the

United States or of individual states. In addition, these estimates could be

derived for individual construction industries at the four-digit Standard

Industrial Classification (SIC) level, as listed in table 4.4. ^ For example,

individual TFP growth estimates could be developed for Plumbing, Heating and

Air Conditioning Contractors (SIC 1711) and for Roofing and Sheet Metal Work

Contractors (SIC 1761). Alternatively, TFP growth estimates could be developed

for groups of construction industries at the two- or three-digit SIC level. An

example of a three-digit group of construction Industries would be General

Building Contractors-Residential Buildings (SIC 152); an example of a two-digit

industry group would be Construction-Special Trade Contractors (SIC 17).

1 The definitions of some four-digit construction industries (e.g., General

Contractors - Single-Family Houses (SIC 1521) have changed considerably

between Censuses. For these industries it would not be possible to derive the

five-year TFP growth estimates based on Census data.

18
Table 4.4 Standard Industrial Classification (SIC) Titles for

Construction Industries

SIC

- SIC

Industry titles Industry titles code code

15 BUILDIIMG CONSTRUCTION-GENERAL CONSTRUCTION-SPECIAL TRADE

CONTRACTORS AND OPERATIVE BUILDERS CONTRACTORS-Continued

152 General Building Contractors— Residential Buildings 172 Painting, Paper Hanging, and Decorating

1521 General Contractors— Single-Family Houses 1721 Painting, Paper Hanging, and Decorating

1522 General Contractors-Residential Buildings, Other

Than Single-Family 173 Electrical Work

1731 Electrical Work

153 Operative Builders 1531 Operative Builders 174 Masonry, Stonework. Tile Setting, and Plastering

1741 Masonry, Stone Setting, and Other Stonework

154 General Building Contractors- Nonresidential

Buildings

1742 Plastering, Drywall, Acoustical and Insulation Work

1743 Terrazzo, Tile, Marble, and Mosaic Work

1541 General Contractors— Industrial Buildings and

Warehouses 175 Carpentering and Flooring

1542 General Contractors— Nonresidential Buildings, 1751 Carpentering

Other Than Industrial Buildings and Warehouses

1752 Floor Laying and Other Floorwork, Not Elsewhere

Classified 16 CONSTRUCTION OTHER THAN BUILDING

CONSTRUCTION-GENERAL CONTRACTORS 176 Roofing and Sheet Metal Work

1761 Roofing and Sheet Metal. Work

161 Highway and Street Construction, Except Elevated Highways 177 Concrete Work

1611 Highway and Street Construction, Except Elevated Highways1771 Concrete Work

178 Water Well Drilling

162 Heavy Construction, Except Highway and Street Construction

1781 Water Well Drilling

1622 Bridge, Tunnel, and Elevated Highway Construction 179 Miscellaneous Special Trade Contractors 1623 Water, Sewer, Pipe Line, Communication and Power 1.791 Structural Steel Erection

Line Construction 1793 Glass and Glazing Work

1629 Heavy Construction, Not Elsewhere Classified 1794 Excavating and Foundation Work

1795 Wrecking and Demolition Work

17 CONSTRUCTION-SPECIAL TRADE 1796 Installation or Erection of Building Equipment, Not CONTRACTORS Elsewhere Classified 1799 Special Trade Contractors, Not Elsewhere Classified 171 Plumbing, Heating (Except Electric), and Air Conditioning

1711 Plumbing, Heating (Except Electric), and Air Conditioning 6552 Subdividers and Developers, Except Cemeteries

Source: U.S. Department of Commerce, Bureau of the Census, 1977 Census of

Construction Industries, Washington, D.C., 1980.

19

APPENDIX A. ANNOTATED BIBLIOGRAPHY ON PRODUCTIVITY MEASUREMENT

A.l PRODUCTIVITY MEASUREMENT METHODS

Caves, Douglas W.; Christensen, Laurits R. ; and Swanson, Joseph A.,

"Productivity in U.S. Railroads, 1951-1974," The Bell Journal of Economics , Vol. 11, No. 1 (Spring 1980), pp. 166-181. Includes 21 bibliographical

references.

This article develops estimates of U.S. railroad total factor productivity by

using methods based on the neoclassical theory of production. The authors find

that railroad productivity grew at the average annual rate of 1.5 percent per

year during the 1951-1974 period. Using conventional measurement procedures

for comparison, they find productivity growth of 3.6 percent per year. The

lower estimate of 1.5 percent is the result of using procedures which better

represent the railroad production process. These include using (1) estimated

cost elasticities of the outputs, rather than revenue shares, as output weights,

(2) actual cost shares, rather than national income shares, as input weights

and (3) input and output weights which change annually.

Diewert, W. Erwin, "The Theory of Total Factor Productivity Measurement in

Regulated Industries," in Productivity Measurement in Regulated Industries

(edited by Thomas G. Cowing and Rodney E. Stevenson). New York: • Academic

Press, 1981, pp. 17-44. The book includes 13 pages of bibliographical

references.

This paper reviews those aspects of duality theory that are relevant to the

measurement of total factor productivity (TFP) for a competitive firm. Four

alternative approaches are presented: (i) the econometric estimation of

production and cost functions; (ii) the use of Divisia indexes; (iii) the use

of exact index numbers; and (iv) nonparametric methods for measuring technical

progress. Each of these approaches is then applied to the special case of a rate-of-return regulated firm, and the necessary assumptions required for each

case, regulated as well as competitive, are derived. The informational

requirements for measuring TFP for a regulated firm using each of three

different approaches —(ii), (iii), and (iv) —are also derived.

Gold, Bela, "Improving Industrial Productivity and Technical Capabilities:

Needs, Problems, and Suggested Policies," in- Productivity Analysis: A Range of

Perspectives (edited by Ali Dogramaci). Boston: Martinus Nijhoff Publishing,

1981, pp. 86-132. Includes 29 bibliographical references.

The author first reviews the objectives of policies to accelerate progress in

industrial productivity and technical capabilities. He then discusses the sources and prospective effects of productivity and technological gains. This

is followed by examination of the considerations confronted by those deciding

whether to increase or decrease resource commitments to such improvement programs. The final focus is on the policy implications of such considerations.

Key findings emphasize that productivity changes have generally been inadequately measured, that the relative importance of the factors affecting them

has changed substantially since World War II, that such primary determinants

A-1
u^_fer among Industries, and the the effects of productivity increases are often widely at variance with expectations.

Gorman, John A., "Nonfinancial. Corporations : New Measures of Output and Input,"

Survey of Current Business , Vol. 52 (March 1972), pp. 21-27, 33. No references.

This article presents data that provide a basis for studying productivity and

costs of nonfinancial corporations. Specifically, the data consist of annual

estimates of nonfinancial corporations' output, of capital stocks and inputs,

of labor inputs consistent with the Bureau of Economic Analysis compensation

and employment series, of combined labor and capital inputs, and of profits.

The output, profit, and stock estimates are based on the assumption of

consistent depreciation practices. Total factor productivity is estimated, as well as the partial productivity of labor and capital separately. Also, rates

of return to capital stock are calculated, relating property income to the

capital stock valued at current replacement cost.

Mark, Jerome A., "Productivity Measurement," in Productivity; Prospects for

Growth (edited by Jerome M. Rosow). New York: Van Nostrand Reinhold Company,

1981, pp. 54-75. Includes 11 bibliographical references in footnotes.

To provide a basis for understanding the present status and future direction

of productivity measurement, this chapter examines the productivity measures

currently available, some of their limitations, how they can be improved, and

what attempts are being made to improve them. The examination traces the

available measures of the Federal Government as well as those of the principal

private researchers in the field, summarizes the conceptual bases of the indicators , and points out some of the more fundamental differences in approaches

employed.

Nadiri, M. Ishaq, "Some Approaches to the Theory and Measurement of Total

Factor Productivity: A Survey," Journal of Economic Literature , Vol. 8, No. 4

(December 1970), pp. 1137-1177. Includes 155 bibliographical 'references.

This survey concentrates on some basic theoretical hypotheses and empirical

evidence regarding the measurement and determinants of total factor productivity change in the U.S. economy. Section I comprises a preliminary review of

the indices of productivity, some empirical evidence, and a brief discussion of

the forces which may govern the behavior of productivity changes. Section II

briefly covers the problems of aggregation underlying the aggregate production

function, and some theoretical issues on the nature of technical change and

problems of its diffusion. The next two sections are devoted to the calculation

of technical change based on the aggregate production function. In the final

section, the author concludes that an important contribution towards understanding the determinants of technological change has been made by the theories

of endogenous technological change and the attempts to explain the production

and transmission of new knowledge. Further, the formulation of more general

forms of the production function via cost functions has served to widen the

scope of research in a new direction.

A-2
National Research Council, Panel to Review Productivity Statistics, Measurement

and Interpretation of Productivity . Washington, D.C.: National Academy of

Sciences, 1979, 449 pp. Includes 7 pages of bibliographical references.

This work provides a survey of productivity theory and ten papers on specific

topics related to productivity. The survey consists of nine chapters, four of

which are particularly useful for those interested in productivity measurement.

Chapter 3 reviews the basic concept of a production function and derives some

of the statistical formulas used in productivity measurement. Chapters 5 and

6 contain a discussion of shortcomings in existing measures and possible ways

of improving them. Chapter 5 discusses the measurement of output, the numerator of the productivity ratio. The first part of this chapter establishes

criteria for the inclusion or exclusion of specific types of activity in the

measure of output used in measuring productivity; the second part discusses

the measurement of inputs (labor, capital services, and intermediate inputs),

one or more of which make up the denominator of the productivity ratio. The

problems in measuring labor input include the appropriate concept of hours of

work and whether labor input should be differentiated by some measure of its

composition, such as skill, experience, or education. The problems of mea- suring the input of capital services include the treatment of depreciation,

obsolescence, and changes in inventories. Chapter 8 considers measures of

productivity at the level of the individual plant or company. It examines the

special uses, data requirements, and other issues associated with company-level

measures.

Siegel, Irving H. , Productivity Measurement: An Evolving Art , Studies in

Productivity: Highlights of the Literature, Study No. 16. Scarsdale, NY:

Work in America Institute, Inc., 1980, 34 pp. Includes 8 pages of bibliographical references.

This publication guides the reader towards a better understanding of the field

of productivity measurement by providing an overview of outstanding research,

abstracts of the literature, and an extensive bibliography. The overview

encompasses the development, state, and future direction of productivity

measurement. It concludes that classical problems of concept, quantification,

weighting, quality adjustment, deflation, and data supply persist. While

improvements are still sotlght in the measurement of labor input, the frontiers

are extended to the measurement of capital and intermediate inputs. Despite

the progress made in methodology and the generation of statistics, experts

remain unable to account for the recent slowdown of labor productivity growth

at the national level. Finally, the value of published productivity statistics

could be enhanced by a fuller awareness of their nature, limitations, actual

content, and structure.

A-3
A. 2 PRODUCTIVITY IN THE CONSTRUCTION INDUSTRY

Adrian, James J., and Boyer , LeRoy T. , "Modeling Method-Productivity," Journal

of the Construction Division, Proceedings of the American Society of Civil

Engineers , Vol. 102, No. COl (March 1976), pp. 157-168. Includes 5 bibliographical references.

This paper focuses on the development of a productivity model that provides a typical construction firm with a means of measuring, predicting, and improving

the productivity of a given construction method. Method productivity parameters

are addressed by documenting productivity delays. Although the model may not

recognize every construction method productivity parameter and may not always

result in the development of optimal construction method productivity, it does

provide the potential for local optimization for a given construction method.

Alfeld, Louis E., Research for Building Construction Productivity — Report on

the June 2, 1981 Conference, NBS-GCR-81-331 . Washington, D.C.: National Bureau

of Standards, August 1981, 16 pp. No references.

The conference was held to identify major research needs to improve commercial

construction productivity. A consensus emerged around six primary research

topics: (1) develop a "family" of micro measures of construction productivity

to assist individual firms in decision-making, (2) improve macro measures of

productivity to assist in understanding regional and aggregate industry trends,

(3) develop the methods needed to extend computer applications to all phases of

construction decision-making, (4) identify and develop methods to expedite the

regulatory process, (5) measure the relationships between occupant-user productivity and building design, and (6) produce the knowledge of physical properties of buildings needed to reduce risks of building failures and lower costs

of designing for building safety. Conferences further agreed that the private

sector, not government, must take the initiative to formulate and conduct

research. However, government should support and conduct some research.

Business Roundtable, Measuring Productivity in Construction , Construction

Industry Cost Effectiveness Project Report A-1. New York: The Business

Roundtable, 1982, 21 pp. Includes 11 bibliographical references.

This report reviews current construction productivity measurement procedures and

proposes a program intended to provide systems for measuring productivity in

construction at the aggregate industry, industry segment, and site levels, as well as to collect and disseminate construction productivity data on a national

basis. The major conclusions are that greater use of site productivity measurement systems is needed, present construction statistics and aggregate productivity measurement systems are inadequate, and that existing owner/contractor

data can be used to derive a series of productivity indexes that would allow

owners to compare the performance of their projects with similar projects.

Cassimatis, Peter J., "Time Trends of Productivity in Construction," Chapter 6

of Economics of the Construction Industry , Studies in Business Economics No.

111. New York: National Industrial Conference Board, Inc., 1969, pp. 76-88.

Includes 7 pages of bibliographical references.

A-4
This chapter is concerned with the definition of construction industry

productivity measurement that can be developed from the available data, and with

an evaluation of the trend in overall productivity in the construction industry.

Labor productivity is measured from 1947 to 1967. The average annual increase

in output per labor hour was nearly 3.0 percent during this period. This rate

is well below that of most other industries and of the national economy. Total

factor productivity is also measured, although less reliably because of the

limitations of data, and found to have increased about 1.5 percent per year.

Cremeans, J. E. , "Productivity in the Construction Industry," Construction

Review , Vol. 27, No. 5 (May/June 1981), pp. 4-6. Includes 5 bibliographical

references

.

This article discusses a number of hypotheses that have been proposed to

explain the significant decline in construction Industry labor productivity in

the 1970 's. These hypotheses suggest that the measured decline in productivity

is due to errors in the measurement or deflation of output, a decline in the

capital-labor ratio, a change in the age-sex composition of the labor force, a shift towards non-union construction, an increase in government regulation, or cyclical effects. Only one of the hypotheses—the increased proportion of

younger, less experienced workers —is found to be supported by the available

data. The author concludes that the latest data available (1979) indicates

that labor productivity in the construction industry had indeed fallen

significantly and continues to fall.

Judson, Arnold S. , "New Productivity Improvement Strategies for the

Engineering/Construction Industry," Proceedings of the Conference on the Civil

Engineer's Role in Productivity in the Construction Industry , Vol. 1. New

York: American Society of Civil Engineers, 1976, pp. 49-67. No references.

The author argues that managers in the engineering/construction industry

have demonstrated little capability of achieving total factor productivity

improvement that is substantial and lasting. This is due to the use of traditional strategies that are no longer workable, strategies that require a topdown approach. Existing opportunities for productivity improvement in the

industry are discussed, as are barriers to such productivity improvement.

Desirable characteristics and examples of new productivity improvement

strategies are then proposed. Examples of new approaches include productivity bargaining, quality of worklife, and continuous productivity improvement strategies. The author then explains the multi-phase process for

implementing any specific new approach.

Kellogg, Joseph C. ; Howell, George E.; and Taylor, Donald C. , "Hierarchy Model

of Construction Productivity," Journal of the Construction Division , Proceedings of the American Society of Civil Engineers , Vol. 107, No. CGI

(March 1981), pp. 137-152. Includes 1 bibliographical reference.

This paper relates the efforts of a group of construction professionals to

analyze the construction industry's productivity problem, and proposes a tool,

for continuing analysis—the Hierarchy Model. This model addresses total

factor productivity at five distinct construction industry levels: (1) policy

A-5
formation; (2) program management; (3) planning/design; (4) project management/

administration; and (5) site construction. The primary role of the hierarchy

model is to provide a cognitive map to solve the problem of construction industry fragmentation and a vehicle for the "total study" of total factor productivity in the industry.

Koch, Janet A. and Moavenzadeh, Fred, "Productivity and Technology in

Construction," Journal of the Construction Division , Proceedings of the

American Society of Civil Engineers , Vol. 105, No. C04 (December 1979),

pp. 351-366. Includes 11 bibliographical references.

This article focuses on the role of technology in the highway sector of the

construction industry and its influence on productivity and price. It takes a case-study approach that entails recording the inputs required for, and influences impacting, the various tasks of production for alternative means of producing a given output. The data are used to synthesize a production isoquant

for the product, which is subject to further economic analysis. The authors

find that there have been substantial gains in both labor and capital productivity and efficiency in highway construction over the past 50 years in the

United States, resulting in a certain offsetting of factor price increases.

Nevertheless, if trends of the past are indicative of the future, then gains

in efficiency can be expected to be less than previous gains. They conclude

that new means of accomplishing technology change in the construction industry

are clearly needed for the future.

NAHB Research Foundation, Inc., A Pilot Study on Productivity in Residential • Construction . Prepared for the Department of Housing and Urban Development,

Washington, D.C., July 1971, 44 pp. Includes 15 bibliographical references.

This pilot study identifies factors affecting total factor productivity in

residential construction that pertain to the industry, the individual firm,

and the worker. It also develops a detailed housing cost model to aid in

Identifying the relative amount of potential productivity gain opportunities.

It then lists those factors affecting productivity that are believed to offer

the important or most likely opportunities for productivity gains. Finally,

three related short term studies are recommended to rank productivity gain

opportunities and to define the most appropriate longer range research to lead

to the achievement of both the largest and most likely productivity gains.

National Commission on Productivity and the Construction Industry Collective

Bargaining Commission, Measuring Productivity in the Construction Industry

(Conference Proceedings). Washington, D.C., September 14, 1972, 79 pp.

Includes a few bibliographical references in footnotes.

This collection of papers from a 1972 conference includes the following works

of particular interest: Mark and Ziegler, "Measuring Labor Requirements for

Different Types of Construction," Behman, "Measuring Trends in Output per

Manhour for Specific Craft Occupations," and Johnson, Grimm, and Thompson,

"Measuring Mason Productivity." An appendix summarizes European and American

studies on productivity trends in the construction industry.

A-6
National Electrical Contractors Association, Inc. , and Mechanical Contractors

Association of America, Inc.-, Effects of Job Schedule Delays on Construction

Costs . Washington, D.C. , August 1980, 38 pp. No references.

This 1980 survey of mechanical and electrical projects shows that significant

delays in construction progress and distortions in planned schedules are not

commonplace and cannot be anticipated in bids. When they do occur, they have a devastating effect on construction costs, particularly labor costs, of electrical and mechanical specialty contractors. Delay-related factors account for

nearly 90 percent of the total labor cost overrun experienced by these contractors on projects with schedule problems. Contractors report that the most significant effects of schedule problems are related to productivity of the work

force. Loss of momentum and productive rhythm is the greatest of these effects,

followed by the need for redundant mobilization and demobilization in various

job areas, and by demoralization of employees.

Rosefielde, Steven and' Mills, Daniel Quinn, "Is Construction Technologically

Stagnant?," in The Construction Industry: The Balance Wheel of the Economy

(edited by Julian E. Lange and Daniel Quinn Mills). Lexington, MA: Lexington

Books, D.C. Heath and Company, 1979, pp. 83-111. Includes 3 pages of

bibliographical references in footnotes.

Government statistics suggest that the construction industry is technologically

stagnant. They seem to show a slow rate of productivity growth, rapid cost

inflation, and limited growth in the industry's output. This chapter analyses

these statistics by examining the definitions used in compiling them, the ways

in which statistics are collected, and their tecchnical meaning. The analysis

shows that construction is not a technologically stagnant sector of the economy,

but one characterized by continuous and large-scale change. Yet these changes,

generally of a socially beneficial nature, result in low measured rates of

advance in labor productivity and actual decreases in capital productivity.

Ruff, Edwin R. (Ed.). Proceedings of the Conference on Construction

Productivity Improvement . Austin, TX: Department of Civil Engineering,

University of Texas at Austin, 1980. No references

Session III of this conference is devoted to methods of productivity

measurement that are applicable to the construction site. One paper discusses

unit cost- analysis as a method of controlling field labor productivity. Other

field methods discussed in this session include work sampling, craftsmen

questionnaires, and foreman delay surveys.

Stokes, H. Kemble, Jr., "An Examination of the Productivity Decline in the

Construction Industry," The Review of Economics and Statistics , Vol. 63, No. 4

(November 1981), pp. 495-502. Includes 10 bibliographical references.

Labor productivity in the construction industry increased annually by 2.4

percent between 1950 and 1968, but between 1968 and 1978 labor productivity

declined annually by 2.8 percent. This article addresses seven possible

explanations for these trends in construction industry labor productivity:

(1-) the measurement of real output, (2) shifts in the composition of

A-7
construction Industry output, (3) changes in capital per worker, (4)

demographic changes in the workforce, (5) economies of scale, (6) regional

shifts, and (7) changes in work rules or practices. The results indicate that

only 25 percent of the deterioration in labor productivity is explained by these

factors. The major contributing factor has been the slower growth in capital

per worker. While other factors make a contribution to explaining recent productivity trends, the magnitudes are very small. There has been much speculation in the literature that the productivity problem was merely a measurement

problem, that real output was understated, but no conclusive evidence was found to support that hypothesis. The labor productivity declines in the

construction industry during the past decade are real.

Thompson, Bruce E. and Chapman, Robert E., Productivity in Residential

Construction: An Annotated Bibliography , NBSIR 80-2150. Washington, D.C.:

National Bureau of Standards, February 1981, 52 pp.

This report presents a state-of-the-art review of the technical literature

related to one or more of the factors affecting productivity in residential

construction. Particular emphasis is placed on identifying potential sources

of variation between the level of productivity in new housing construction

versus that in housing renovation. Although this report focuses on the

residential sector, emphasis is also placed on topics such as construction

management and cost control which apply even to a greater extent to the

nonresidential residential sector. The references have been categorized so that articles dealing with specific productivity and construction topics can

be easily identified. The categories emphasized in this report are: general

productivity/productivity measurement; construction productivity; residential

rehabilitation/renovation; construction/housing costs; construction cost

estimation and control; economics of construction; and building codes and

regulations.

Woodhead, W. D. , "Productivity Factors in System Housing." Commonwealth

Scientific and Industrial Research Organization, Division of Building Research,

Melbourne, Australia, 1979. Includes 7 bibliographical references.

This monograph reports on research which measured labor requirements per square

meter for eight alternative designs of single-family housing in Australia.

Three of the designs were conventional and five were innovative. The data were

derived from on-site observations. Labor requirement data are provided for the

entire building on a gross and net floor area basis, as well as for selected

building systems. The determinants of variations in labor requirements are also discussed.

A-8
A. 3 PRODUCTIVITY MEASUREMENT CASE STUDIES

Adam, Nabil R. and Dogramaci , All, eds.. Productivity Analysis at the

Organizational Level , Studies in Productivity Analysis, Volume III, Boston:

Martinus Nijhoff Publishing, 1981, 181 pp. Includes bibliographical references

after each chapter.

This is a collection of original papers on productivity analysis at the

organizational level. The book is divided into three parts: perspectives on productivity measurement, a range of studies at the micro level, and some productivity issues in public organizations. The first two parts are useful to

those interested in private sector, firm-level productivity measures. The

first chapter in part I discusses different methods for constructing partial

productivity ratio measures, as well as alternative methods of measuring a given choice of inputs and outputs. Also presented in this chapter is a brief

history of company-based productivity studies that go back to the turn of the

century. The next chapter discusses a number of problems in the measurement of

labor inputs, capital inputs, and outputs. Part I ends with an example of

labor and total factor productivity measurement for a specific industry (food

retailing) . Part II begins with a chapter that develops a set of models to

analyze the complex interrelationships between a multitude of labor productivity components. The next chapter provides an algorithm to solve an operations research problem in the area of human resources and labor productivity.

Another chapter develops the design of an experiment for productivity-related

ratio analysis in an organization. Finally, the last two chapters of part II

deal with issues related to industrial economics and address the question of

whether larger firms tend to have higher labor productivity.

Bailey, David and Hubert, Tony (Eds.). Productivity Measurement; An

International Review of Concepts, Techniques, Programmes, and Current Issues . Westmead, U.K.: Gower Publishing Company Limited, 1980. No references.

The papers published in this volume were originally presented in 1979 at one

of a series of conferences sponsored by the European Association of National

Productivity Centres. The major focus of these papers is on productivity

measurement at the level of the firm. The approaches discussed include

financial ratios, labor productivity, and a new method called resource allocation strategist (REALST) which measures the contributions to profit

variance of differences in capacity utilization, efficiency, and resource

costs. A number of inter-firm case studies are presented from various

countries.

Cocks, Douglas L. , "The Measurement of Total Factor Productivity for a Large

U.S. Manufacturing Corporation," Business Economics (September 1974), pp. 7-20.

Includes 16 bibliographical references in footnotes.

This article ' outlines a specific methodology for the measurement of total

factor productivity for an individual firm that allows a direct comparison with

all U.S. nonfinancial manufacturing corporations. The methodology is based on

a study completed by the U.S. Department of Commerce, Bureau of Economic

Analysis (see subsection A.l —John A. Gorman). This methodology is applied to

A-9
a large, fairly diversified U.S. manufacturer—Eli Lilly and Company. Then an approach for treating research and development as a capital input is presented.

The author finds that this alternative treatment of research and development

as a capital input has virtually no effect on Lilly's total factor productivity

measure.

Craig, Charles E. and Harris, R. Clark, "Total Productivity Measurement at the

Firm Level," Sloan Management Review , Vol. 14, No. 3 (Spring 1973), pp. 13-29.

Includes 6 bibliographical references.

This article describes a theoretical framework for firm-level productivity

measurement that is particularly suitable for supporting the corporate management decision process. The model is described as a service flow model. Physical inputs are converted to dollar equivalents which are remunerations for

services provided by those inputs. The return to capital is the residual left

when all other input factors have been paid for their services. This methrod

differs from others in its treatment of capital and the use of all inputs and

outputs. A lease service concept of capital is used rather than a physical

consumption concept. Also, all revenue items are included as outputs and all

cost or expense items are inputs. A case study from the manufacturing industry

is used to demonstrate the method and to point out some of the difficulties in

making the actual calculations.

Eilon, Samuel; Gold, Bela; and Soesan, Judith, Applied Productivity Analysis

for Industry . Elmsford, NY: Pergamon Press, Inc., 1976, 151 pp. Includes

bibliographical references after each chapter.

This book is divided into three parts. The first part is devoted to a discussion of the current concept of productivity and its definitions, and to

a literature survey of various prevailing approaches to the problem. It then

proceeds to propose a framework for productivity analysis and an array of

management-control ratios and also to indicate how problems of measurement can

be overcome in practical situations. The second part describes five case studies from the manufacturing industry to illustrate how the proposed methodology

can be applied in various situations involving different levels of complexity

and aggregation. In the third part, various problems encountered during the

case studies in measurement and analysis are reviewed and suggestions are made

as to how they can be overcome. Then the use of the model for planning purposes

is discussed through sensitivity tables, deterministic appraisals, and risk

simulation. The concluding chapter suggests that the methodology employed in

this book can be applied to various industries,

Greenberg, Leon, A Practical Guide to Productivity Measurement . Washington,

D.C.: The Bureau of National Affairs, Inc., 1973, 71 pp. Includes 15

bibliographical references.

This guide to company productivity measurement is directed primarily to the

company manager. It concentrates on the measurement of labor productivity

trends, dealing with other types of measures and the measurement of levels of

productivity only briefly. It begins with simple types of production and moves through more complex production simulations. Examples are given to illustrate

A-10
the methods of calculation. Guidelines are offered for measuring productivity

in service industries. Government productivity statistics for the economy,

major industry sectors, and individual industries are also discussed.

Hines , William W. , "Guidelines for Implementing Productivity Measurement,"

Industrial Engineering , (June 1976), pp. 40-43. Includes 9 bibliographical

references.

This paper presents a brief review of productivity measurement methods and

case studies at the level of the firm. Specific measurement problems are discussed and guidelines are presented for industrial engineers to implement a regular program of total factor productivity measurement for their companies.

Katzell, Raymond A.; Bienstock, Penney and Raerstein, Paul H. , A Guide to

Worker Productivity Experiments in the United States, 1971-1975 , prepared for

Work in America Institute, Inc. New York: New York University Press, 1977,

186 pp. Includes an annotated bibliography of 103 references.

In this book, three psychologists summarize and analyze 103 case studies

designed to improve the productivity of workers. The experiments under review

were performed in the United States and reported in publications issued from

1971 through 1975. Although based predominantly on experience in business and

industry, nearly one third of the case studies were performed in nonprofit

agencies, and the case studies involve workers from a wide range of occupations

and levels. This literature indicates that the improvement of worker performance is attainable through strategies already within our grasp. The

limitations of many of the experiments, however, raise questions about the

validity or generalizability of their findings.

Kendrick, John W. and Creamer, Daniel, Measuring Company Productivity;

Handbook with Case Studies , Studies in Business Economics, No. 89, New York:

National Industrial Conference Board, Inc., 1965, 120 pp. Includes 11

bibliographical references.

This report discusses the value of company productivity measures and the

technical difficulties that are involved in the estimating procedures. The

first chapter, which is designed primarily for the general executive, presents

the meaning and uses of company measures of productivity. The body of the

report is devoted to the problems and procedures of estimating. A section of case studies follows which shows how six major companies have measured

company productivity. The case studies include two uses of labor productivity

measures —"Measuring Labor Productivity in the General Oil Company: and

"Measuring Labor Productivity by Sub-components" —and four uses of total

productivity measures —"Measuring Labor and Capital Productivity: A Short-cut

Method," "Measuring Total Productivity at the Divisional Level of and Equipment

Manufacturer," "Total Productivity Measurement at the Midwest Manufacturing

Company," and "Total Factor Productivity Measure at a Durable Goods Manufacturing Company." These cases are meant to demonstrate that such measures can

be implemented in practice.

A-11
Kraus , Jerome, "Productivity and Profit Models of the Firm," Business Economics , Vol. 13, No. 4 (September 1978), pp. 10-14. Includes 5 bibliographical references in footnotes.

This paper presents a model for forecasting profits of a firm based on a modified income statement and the use of single factor productivity measures.

The major modification is to convert the bottom line of the traditional income

statement (i.e., income after taxes) into an appropriate measure of firm output,

such as sales adjusted for inventory change. The purpose of the model is to

permit the forecasting of profits to be based on economic variables, such as prices, sales volume, and productivity.

Litton Systems, Inc., Productivity Measurement Model Users Manual , Report No.

PRR-70-2. Prepared for Department of the Navy, Bureau of Naval Personnel,

Washington, D.C., July 15, 1969, 31 pp. No references.

This users' manual provides operating instructions, definitions, assumptions,

and computer program documentation for the Productivity Measurement Model

(PMM). The PPM computes productivity indices for large, decentralized

industrial organizations. Specifically, the model develops comparable labor

productivity measures for both lower and higher organizational levels. Then

aggregate productivity indices for the entire organization are formed by a weighted average process.

Nadiri, M. Ishaq, and Schankerraan, M. A., "The Structure of Production,

Technological Change, and the' Rate of Growth of Total Factor Productivity in

the U.S. Bell System," in Productivity Measurement in Regulated Industries

(edited by Thomas G. Cowing and Rodney E. Stevenson). New York: Academic

Press, 1981, pp. 219-247. The book includes 13 pages of bibliographical

references.

The objectives of this preliminary study are threefold. The first is to analyze

empirically the production structure of the Bell System at the aggregate level.

Particular attention is focused on the pattern of substitution among the factor

inputs and the degree to which the aggregate production function is characterized by economics of scale. In this connection, the authors explore the role

of research and development in the Bell System as an input in the production

process, and its interaction with the traditional inputs. Second, they examine

the impact of external technological change on the production structure of the

Bell System. The issues here include not only the rate of such change, but

also its factor bias. The third objective is to explore the interrelationships

between economies internal to the Bell System and external technical change in

determining the rate of growth of total factor productivity (TFP). Specifically, the authors propose and illustrate a methodology for decomposing the

observed growth of TFP into a part related to scale economies and a part

induced by technical change. These three objectives are addressed by first

estimating an aggregate translog cost function for the Bell System, using

annual data for the period 1947-1976. The implied estimate of scale economies

is then used to explore the sources of TFP growth.

A-12
Siegel, Irving H. , Company Productivity; Measurement for Improvement . Kalamazoo, Michigan: W.E. Upjohn Institute for Employment Research, 1980,

88 pp. Includes bibliographical references in footnotes.

The purpose of this book is to assist managers in tracking their company's

productivity over time. Chapters deal with the benefits of measuring company

productivity, definitions of productivity, and methods for establishing a com- pany measurement program. The final chapter offers some examples of company

productivity measurement. The examples cover both single and total factor

productivity. An appendix summarizes a number of productivity measurement

methods.

A-13
NBS-n4A (REV. 2-8C) U.S. DEPT. OF COMM. BIBLIOGRAPHIC DATA

SHEET (See instructions)

1. PUBLICATION OR

REPORT NO. NBS TN 1172

2. Performing Organ. Report No. 3. Publication Date

February 1983

4. TITLE AND SUBTITLE

PRODUCTIVITY MEASUREMENT FOR THE CONSTRUCTION INDUSTRY

5. AUTHOR(S)

Stephen F. Weber and Barbara C. Lippiatt

6. PERFORMING ORGANIZATION f /f jo/ nt or other than N BS. see instructions)

NATIONAL BUREAU OF STANDARDS

DEPARTMENT OF COMMERCE

WASHINGTON, D.C. 20234

7. Contract/Grant No.

8. Type of Report & Period Covered

Final

9. SPONSORING ORGANIZATION NAME AND COMPLETE ADDRESS (Street. City. State. ZIP)

National Bureau of Standards

Department of Commerce

Washington. D.C. 20234

10. SUPPLEMENTARY NOTES

j~ ! Document describes a computer program; SF-185, FlPS Software Summary, is attached.

11. ABSTRACT (A 200-word or less factual summary of most si gnificant information. If document includes a si gnificant

bibliography or literature survey, mention it here)

The fundamental concept underlying all productivity measures is a comparison of the

output of a production process, an enterprise, an industry, or an economy with the

corresponding factors of production (inputs) required to generate that output.

Productivity measures are formulated as a ratio of output to one or more of the

inputs. This report evaluates alternative productivity measures and concludes that

the comprehensive Total Factor Productivity (TFP) method is preferred to the Single

Factor Productivity method. To combine the multiple components in the denominator

of a TFP index, a weighting system based on relative factor cost shares is recommended.

A measurable index of the instantaneous rate of change in TFP between two time- periods

is derived from a general production function. The report also investigates the

specific data requirements for implementing this TFP measure in the construction

industry. An annotated bibliography is included.

12. KEY WORDS (Six to twelve entries; alphabetical order; capitalize only proper names; and separate key words by semicolons)

construction industry; economics; index; input; output; productivity measurement;

single factor productivity; total factor productivity.

13. AVAILABILITY

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