Productivity In the U.S. Services Sector

Barry Bosworth

The Brookings Institution

Labor Productivity, Nonfarm Business

60

80

100

120

140

1970 1975 1980 1985 1990 1995 2000

year

ind

ex

1.4 percent trend growth1973-75

2.4 percent trend growth1995-2001

Growth in Labor Productivity and Wage Rates

80

100

120

140

160

180

1980 1985 1990 1995 2000

Year

Ind

ex,

1980

= 1

00

Labor Productivity

Real Hourly WageOutput Price

Real Hourly Wage -Consumption price

Exploration of resurgence in growth of labor productivity

• Work undertaken with Jack Triplett

• Emphasize a new industry data set developed by BEA and BLS

• Measure labor and multifactor productivity at the level of 54 industries (29 services) for the period of 1987-2001.

Basic Summary (1)

• Post-1995 labor productivity growth (gross output concept) of service-producing industries exceeded that of goods-producing industries.

1987-95 1995-2001 ChangeLabor ProductivityPrivate Nonfarm Business 1.0 2.5 1.5

Goods-Producing Industries 1.8 2.3 0.5Service Producing Industries 0.7 2.6 1.8

Trend Growth Rates

Summary (2)

• Similarly, growth of MFP in service-producing industries exceeds that of goods-producing after 1995

1987-95 1995-2001 ChangeMulti-factor ProductivityPrivate Nonfarm Business 0.6 1.4 0.9

Goods-Producing Industries 1.2 1.3 0.1Service Producing Industries 0.3 1.5 1.1

trend growth rates

Summary (3)• Strong MFP gains in IT-producing

industries are offset by weak performance in other goods-producing industries.

• Results for service-producing industries are very diverse.– Five industries (wholesale, retail, finance, real

estate, and health) represent 130 percent of the increase in aggregate MFP.

– Twelve of twenty-nine industries have negative MFP changes after 1995.

Comparison with Nonfarm Aggregate

ValuePeriod Value Labor Added Multi-factor

Added per Worker Productivity

1987-1995 2.9 1.5 1.4 0.91995-2001 3.8 1.5 2.3 1.1

Change 0.9 0.0 0.9 0.2

1987-1995 2.9 1.7 1.1 0.71995-2001 4.3 1.9 2.3 1.3

Change 1.4 0.2 1.2 0.5

Bureau of Labor Statistics

Industry Aggregate (BEA/BLS Data)

• Significantly greater post-1995 acceleration– Labor Productivity

• 1.2 vs 0.9

– MFP

• 0.5 vs 0.2

– Larger acceleration reflects lower productivity growth in 1987-95

– Same growth in 1995-2001.

Post- 2001 update

• New NAICS data through 2003 shows a second surge of labor productivity growth in 2001-2003 (value-added concept only).

• Acceleration in both goods-producing and service-producing industries.

• No new information on MFP

Trends in Labor Productivity, 1977-2003annual percent change

1977-87 1987-95 1995-00 2000-03Nonfarm business

output 3.3 3.0 4.7 2.0hours 2.0 1.5 2.2 -1.7labor productivity 1.3 1.5 2.5 3.8

Chain value-added outputPrivate goods-producing industries 2.6 2.3 4.0 -0.8Private services-producing industries 3.7 3.0 4.2 2.8

HoursPrivate goods-producing industries 0.2 0.2 1.1 -4.2Private services-producing industries 3.1 2.2 2.4 -0.3

Labor ProductivityPrivate goods-producing industries 2.4 2.1 2.9 3.5Private services-producing industries 0.6 0.8 1.7 3.1

Industry Data converted to NAICS basis.

Industry Detail

• Gross Output and Value Added• Inputs: labor, capital, intermediate inputs• Least-squares trends for sub-periods to

eliminate cycles.• Partition labor productivity growth into

contribution of growth in IT and non-IT capital per worker, purchased inputs, and multifactor productivity.

Contribution to the AggregateConvert industry data based on gross output to

aggregate value added

• Labor productivity aggregated with value-added weights.

• Large reallocation terms among industries with different levels of labor productivity and intermediate input intensities.

• Aggregation of individual industries accounts for only half of acceleration in nonfarm productivity after 1995

Contribution to Aggregate (2)

• MFP aggregated with Domar weights

• take effect of indirect contribution to lower intermediate input costs in other industries.– Inclusion of intermediate inputs scales down

MFP relative to value-added concept.

– weights exceed 100 percent (187%)

• Reallocation terms are small

• Service-producing industries account for – _three-fourths of post-1995 growth in aggregate

labor productivity. and

– all of the acceleration in labor productivity and MFP relative to 1987-95.

– Cross-industry correlation of post-1995 acceleration of Q/L and MFP is only 0.33.

• Large contribution of IT-producing sectors to MFP is offset by declines in other goods-producing industries

Contribution of IT Capital

• Increased IT capital per worker was a large contributor to post-1995 resurgence of labor productivity– 80 percent of the increased contribution was in

services

– 1995 stock of IT capital is correlated with cross-industry changes in labor productivity

– No correlation with distribution of MFP gains

Consistency with other studies

• Is resurgence in MFP limited to IT-producing industries?– Common interpretation of Oliner-Sichel

(Gordon) -- Yes

– Triplett-Bosworth -- No

• Sources of Differences– Income versus expenditure side estimates of

nonfarm (larger total change)

– Bottom-up versus top-down

Conclusions

• The productivity resurgence has been large and extends far beyond IT-producing sectors.

• The service-producing sectors account for a dominant portion of the improvements in:– labor productivity,

– MFP, and

– the contribution of IT capital.

The Case of Retail Trade

Output Measurement

• Gross margin versus sales– BLS - Sales

– BEA - Gross Margin (real values projected with sales)

• Gross margin assumes separability– Shifts in value added between retailer and manufacturer

– Sales closer to production function concept

– Lack of price deflator for margin or cost-of-goods sold

Output Measurement (2)

• Sales concept may credit retail with productivity gains that should more properly be assigned to other sectors of the economy– 1998 BLS detailed industries (Brookings workshop)

– Example of computer stores

– Combines improvements inside the box with increased sale of boxes.

– BEA projects real value of margin with sales

Output and Productivity GrowthSelected Sub-sectors

Industry 1987-95 1995-2001 1987-95 1995-2001Retail Trade 3.0 4.8 2.0 3.6

Electronics and appliance stores 13.3 18.8 11.5 14.7General merchandise stores 4.9 6.2 2.9 5.1

Department stores 4.2 2.7 1.0 1.6Other 6.6 11.9 6.1 10.9

Miscellaneous store retailers 6.4 4.7 4.5 3.1Nonstore retailers 6.8 12.9 5.6 12.4

Electronic shopping, mail-order 13.8 21.6 8.9 16.3

Output Output per hour

Output Measurement (3)

• Researchers generally favor sales concept– Quantity of goods and quality of services (store

format) inextricably linked

– Economies of scale

– How to quantify store services

– Paper by Foster et al suggests all productivity improvements are due to shifts in store formats

– Still requires measure of purchased inputs

Retail Price Indexes

• Shifts in store formats (Outlet substitution)– Identical products sold in different store formats are

different products

– Differences in prices are linked out in construction of CPI

– Example of Walmart

• Input price indexes– Feasibility

– BLS gross margin price index

General Merchandise

• Walmart not well captured in classification system– Split across categories

– MGI study stressed importance of management innovations, intensive IT, and economies of scale.

– Spread to other retail categories

Alternative Output and Productivity Measures

A n n u a l p e rc e n t c h a n g e1 9 8 7 -9 5 1 9 9 5 -2 0 0 1

O u tp u tB E A o u tp u t 2 .9 4 .9B E A v a lu e a d d e d 2 .9 6 .8B L S o u tp u t 3 .0 4 .8

E m p lo y m e n tB E A 1 .7 1 .7B L S 1 .1 1 .3

L a b o r p ro d u c tiv ityB E A 1 .2 3 .2B E A v a lu e a d d e d 1 .1 5 .0

C o n tr ib u t io n o f :In te rm e d ia te in p u ts 0 .5 -0 .1C a p ita l 0 .3 0 .3

IT c a p ita l 0 .1 0 .3M u lt i- fa c to r p ro d u c t iv ity

B E A o u tp u t 0 .4 3 .0B E A v a lu e a d d e d 0 .6 4 .5

E-Commerce

• Example of early innovations by Census Bureau to measure output– Growing at about 15 percent annually

– enormous economies of scale in the provision of information.

– Business-to-Business e-commerce