Compensation and Working Conditions Spring 1998 28

Occupational Pay by

Establishment Size

Occupational earnings for workers vary considerably depending

on the size of the establishment employing them. Typically the

larger the establishment, the higher the earnings. This relationship was especially true for blue-collar occupations in private

industry. This relationship not only held when looking at variation in earnings by establishment size but also when taking into

account other characteristics such as industry and region.

BY ROBERT W.VAN GIEZEN

Robert W. Van Giezen is an economist in the Division of Compensation Data Analysis and Planning, Bureau of Labor Statistics. Telephone

(202) 606-6205. Albert E. Schwenk, also of the

Division of Compensation Data Analysis and

Planning, assisted with the regression analysis.

Recent articles in Compensation and Working Conditions(CWC) have examined national data from the Occupational

Compensation Survey (OCS) and reviewed, in depth, aspects of the survey not treated in the national summary bulletin. The CWC articles have

highlighted occupational pay differences among the Nation’s four regions,

goods- versus service-producing industries, metropolitan versus

nonmetropolitan areas, and private

industry versus State and local governments.1 One of the topics not covered is the difference in occupational

earnings among establishments of different sizes. This article, using the

recently published 1995 national data,

examines in more detail earnings by

different establishment size categories.2 This article also makes use of

regression analysis to better isolate the

effect of establishment size.

The surveys

The Bureau of Labor Statistics

(BLS) surveys specific occupations in

its OCS program, producing detailed

locality pay data for selected occupations. National data are obtained by

sampling 90 metropolitan and 70

nonmetropolitan areas. Surveys cover

establishments in the continental

United States employing 50 workers

or more in all industries, as classified

by the Standard Industrial Classification Manual, excluding agriculture,

the Federal Government, private

households, and the self-employed.

In the goods-producing sector, an

establishment is defined as a single

physical location where industrial operations are performed. In the serviceproducing sector, an establishment is

defined as all locations of a company

in the area within the same industry

division. In government, an establishment is typically defined as all locations of a government entity.

 Over 64 million workers in more

than a quarter of a million establishments are represented in the 4 establishment size categories. Establishments employing fewer than 500

workers comprised over 90 percent of

the total number of establishments and

represented nearly half the workers.
29 Compensation and Working Conditions Spring 1998

Establishments of 2,500 workers or

more comprised fewer than 1 percent

of all establishments, and represented

over one-fifth of all workers. (See table

1.)

Professional and administrative

occupations

Earnings of professional and administrative workers showed very little

variation by establishment size. (See

table 2.) Earnings for professional

occupations ranged from 1 percent

below the national average in establishments with fewer than 500 workers to 3 percent above the average in

establishments of 1,000 to 2,499 workers. Earnings for administrative occupations were within 3 percent of

each other – from 1 percent below for

the 2 establishment size categories

below 1,000 workers to 2 percent

above for workers in establishments

with 1,000 to 2,499 workers.3

Relative earnings by size of establishment followed the same pattern

among private industry and governments. The most notable exception

was workers in State and local governments in establishments with 1,000

to 2,499 workers, where professional

workers enjoyed a 13-percent advantage over their counterparts in smaller

establishments.

Among eight individual occupations studied separately, most were

generally clustered around the national

average. (See table 3.) For example,

earnings were clustered for the three

most populous jobs as follows: Computer systems analysts, level II (2 percent), engineers, level IV (4 percent),

and accountants, level III (4 percent).

An earnings differential of 10 percent

among personnel specialists, level III

was the largest found among any of

the occupations when a comparison

was made by size of establishment.

Individual professional and administrative occupations chosen for comparison were the most populated ones

within each job series, and they represented the middle (or journey-level)

position within the range. All of the

jobs selected were in an occupation

that was classified into at least four,

and as many as eight, work levels.

Technical and protective service

occupations

Earnings for technical and protective service occupations were generally higher in larger establishments.

Relative earnings for technical workers ranged from 3 percent below the

national average in the smallest establishments to 6 percent above in establishments with 2,500 workers or

more. Among protective service workers, a 40-percent earnings differential

was found between the largest and

smallest establishment size categories.

(See table 2.)

Similar patterns were found where

comparisons could be made within

industry divisions, private industry for

technical workers and State and local

government for protective service occupations. Earnings differentials between the smallest and largest establishment size categories were 10

percent for technical workers and 35

percent for protective service workers.

Earnings for the 4 technical occupations studied separately were higher

in the 2 establishment size categories

with 1,000 workers or more and lower

in the 2 size categories with fewer than

1,000 workers. (See table 3.) For the

most populous job, engineering technicians, level IV, earnings ranged from

$732 per week in establishments with

500 to 999 workers to $808 in establishments with 2,500 workers or more.

The largest differential, 16 percent,

was found among civil engineering

technicians, level III, ranging from

$553 per week in establishments with

500 to 999 workers to $644 a week in

establishments with 1,000 to 2,499

workers.

Earnings for corrections officers

ranged from $337 a week in establishments with fewer than 500 workers to

$620 a week in establishments with

2,500 workers or more, a differential

of nearly 84 percent. For the most

populous protective service occupation, police officers, level I, the 2 same

establishment categories (fewer than

500 and 2,500 or more) earned $598

and $743, respectively, a 24-percent

differential. Nearly all of protective

service occupations studied—corrections officers, firefighters, and police

officers—are State and local government employees.

Office clerical occupations

The earnings pattern of office clerical workers generally followed those

of other white-collar workers. Earnings were higher as establishment size

category advanced, ranging from 2

percent below the national average in

establishments with fewer than 500

workers to 4 percent above the national average in establishments

with 2,500 workers or more. The

all industry pattern generally held

Table 1. Number of establishments and workers within the scope of the survey1 and

the number studied by establishment size, November 1995

All establishments .... 267,494 17,899 64,098,451 14,642,070

Establishment size

 by number of

 workers: .................

 50-499 ..................... 245,512 12,821 31,239,407 2,139,211

 500-999 ................... 13,116 2,164 9,005,366 1,505,303

 1,000-2,499 ............. 6,515 1,734 9,598,356 2,652,215

 2,500 or more .......... 2,351 1,180 14,255,322 8,345,341

Studied

Number of establishments Number of workers in

 establishments Establishment size

Within the scope

of the survey

Within the scope

of the survey Studied

1

 The “workers within the scope of the survey”

estimates provide a reasonably accurate description of the size and composition of the labor force

included in the survey. Estimates are not intended,

however, for comparison with other statistical series to measure employment trends or levels since:

(1) planning of wage surveys requires establishment data compiled considerably in advance of the

payroll period studied; and (2) establishments employing fewer than 50 workers are excluded from

the scope of the survey.
 Compensation and Working Conditions Spring 1998 30

All industries

 All establishments ................................... 100 100 100 100 100 100 100

 Establishment size by number

 of workers:...........................................

 50-499 ................................................ 99 99 97 80 98 92 92

 500-999 .............................................. 100 99 98 96 98 98 103

 1,000-2,499 ........................................ 103 102 102 - 102 104 116

 2,500 or more ..................................... 100 101 106 112 104 115 131

Private industry

 All establishments ................................... 100 100 100 - 100 100 100

 Establishment size by number

 of workers:

 50-499 ................................................ 99 99 97 - 99 92 92

 500-999 .............................................. 99 99 99 - 99 98 104

 1,000-2,499 ........................................ 102 101 101 - 103 105 116

 2,500 or more ..................................... 101 102 107 - 105 119 136

State and local governments

 All establishments ................................... 100 100 100 100 100 100 100

 Establishment size by number

 of workers:

 50-499 ................................................ 98 - - 82 96 91 -

 500-999 .............................................. 98 94 - 95 96 95 85

 1,000-2,499 ........................................ 111 107 - - 102 102 -

 2,500 or more ..................................... 99 100 101 111 101 106 117

Technical Protective

services Clerical Establishment size Professional Administrative

MaintenanceMaterial

movement

1

 Pay relatives indicate establishment size pay as a percent of the national pay for that occupational group and industry group. For example, pay

for material movement workers in establishments with 2,500 workers or more

in private industry was 36 percent higher than the national average in private

industry for this occupational group.

NOTE: Dashes indicate that data did not meet publication criteria.

for private industry and State and local governments.

Among one of the most populous

clerical occupations, secretaries,

level III, earnings were nearly identical in all establishment size categories, varying only by $3 from the

mean of $547 per week. The occupation with the widest variation was

key entry operators, level I, with a

28-percent variation in earnings between establishments with 2,500

workers or more and all other establishment size categories.

Maintenance and material movement occupations

Blue-collar workers showed a wide

variation in earnings between small

and large establishments. Earnings

ranged from 8 percent below the national average for maintenance and

material movement workers in establishments with fewer than 500 workers to 15 percent and 31 percent above

the national average, respectively, for

comparable workers in establishments

of 2,500 workers or more. (See table

2.) Similar earning patterns were observed in private industry and State

and local governments.

In all but 1 of the 14 maintenance

and material movement occupations

studied separately (maintenance

pipefitter was the exception), earnings

increased as employment size rose.

(See table 4.) Maintenance electronics technician, level II, with only a 9-

percent pay advantage, had the smallest disparity in earnings. Among other

maintenance occupations, the pay disparity ranged up to 39 percent for

maintenance mechanics, machinery.

General maintenance worker, maintenance machinist, and tool and die

maker all averaged a 32-percent pay

disparity in earnings between the

smallest and largest size category. The

average disparity between earnings in

the smallest to largest establishment

size category for the eight maintenance occupations was 26 percent.

A similar pattern was found for

material movement occupations. The

pay disparity for workers in the largest employment size category to the

smallest ranged from 31 percent for

shipping/receiving clerks and tractortrailer truckdrivers to 66 percent for

material handling laborers. Comparable pay disparities for other occupations were: Forklift operators (62 percent); guards, level I (52 percent); and

janitors (43 percent). For the six occupations studied, the average disparity was 48 percent.

Conclusion

Workers in larger establishments

generally enjoyed a pay advantage

over workers in smaller establishments. However, this pay advantage

varied among different occupations.

The smallest pay advantages were

found among white-collar workers in

professional, administrative, and

clerical occupations. The largest pay

disparities were found among bluecollar workers.

Table 2. Pay relatives1 by establishment size, selected occupational groups, November 1995
31 Compensation and Working Conditions Spring 1998

Table 3. Average weekly pay and relative pay levels1 by establishment size, selected white-collar occupations, November 1995

Professional

Accountant III ................................. 74,378 $797 (100) $789 (99) $805 (101) $818 (103) $797 (100)

Attorney III ...................................... 13,353 1,249 (100) 1,306 (105) 1,216 (97) 1,313 (105) 1,206 97)

Engineer IV..................................... 200,421 1,149 (100) 1,148 (100) 1,134 (99) 1,178 (103) 1,140 (99)

Administrative

Budget analyst III ............................ 4,167 846 (100) 802 (95) 814 (96) 837 (99) 860 (102)

Buyer/contracting specialist II ......... 32,573 651 (100) 636 (98) 652 (100) 686 (105) 665 (102)

Computer programmer III ............... 43,003 774 (100) 762 (98) 754 (97) 790 (102) 787 (102)

Computer systems analyst II .......... 99,218 926 (100) 923 (100) 920 (99) 935 (101) 926 (100)

Personnel specialist III.................... 47,496 791 (100) 767 (97) 759 (96) 830 (105) 833 (105)

Technical

Computer operator II ...................... 32,754 440 (100) 420 (95) 430 (98) 453 (103) 470 (107)

Drafter III ........................................ 25,598 622 (100) 601 (97) 599 (96) 689 (111) 676 (109)

Engineering technician IV ............... 39,626 767 (100) 751 (98) 732 (95) 746 (97) 808 (105)

Civil engineering technician III ........ 20,329 582 (100) 582 (100) 553 (95) 644 (111) 575 (99)

Protective Services

Corrections officer .......................... 248,640 517 (100) 337 (65) 485 (94) - 620 (120)

Firefighter ....................................... 111,814 677 (100) 575 (85) 667 (99) 665 (98) 760 (112)

Police officer I ................................. 345,834 688 (100) 598 (87) 666 (97) 680 (99) 743 (108)

Clerical

Accounting clerk II .......................... 173,548 372 (100) 359 (97) 378 (102) 384 (103) 413 (111)

General clerk III .............................. 186,633 422 (100) 399 (95) 391 (93) 433 (103) 438 (104)

Key entry operator I ........................ 64,065 349 (100) 324 (93) 327 (94) 326 (93) 418 (120)

Personnel assistant III .................... 16,084 502 (100) 474 (94) 490 (98) 521 (104) 541 (108)

Secretary III .................................... 147,865 547 (100) 548 (100) 545 (100) 550 (101) 545 (100)

Switchboard operator-receptionist .. 105,519 348 (100) 345 (99) 360 (103) 380 (109) 359 (103)

Word processor II ........................... 24,732 489 (100) 482 (99) 458 (94) 490 (100) 496 (101)

All establishments Average pay and relative pay level by establishment size

Occupation and pay level2

Number of

workers

Average pay

(mean) Fewer than 500 500-999 1,000-2,499 2,500or more

1 Relative pay levels, shown in parenthesis, indicate the relative pay of different establishment size categories as a percent of all establishment pay in the United States.

For example, average pay for accountants, level III in establishments with fewer than 500

workers is 1 percent lower than the national average for that job. 2 Occupations in the Occupational Compensation Survey program are divided into

work levels based on duties and responsibilities. The number of levels varies by occupation, as does the degree of difficulty and responsibility. Work levels among different

occupations are not necessarily equal. For example, attorneys levels I through IV equate

to accountants levels III to VI. In addition, the work levels studied are not intended to

represent all workers in a specific occupation. The duties and responsibilities of an

establishment’s top engineers, for example, may exceed those of the highest level of

engineers in the survey. 3 Single-level occupation.

3

3

3

Table 4. Average hourly pay and relative pay levels1 by establishment size, selected blue-collar occupations, November 1995

Maintenance

General maintenance worker3 ....................... 132,302 $10.31 (100) $9.63 (93) $10.67 (103) $11.96 (116) $12.73 (123)

Maintenance electrician3 ............................... 112,426 18.41 (100) 16.53 (88) 16.98 (92) 18.53 (101) 20.56 (112)

Maintenance electronics technician II ............ 74,624 17.84 (100) 17.23 (97) 17.31 (97) 17.90 (100) 18.83 (106)

Maintenance machinist3 ................................ 29,948 16.82 (100) 15.47 (92) 16.64 (99) 16.97 (101) 20.37 (121)

Maintenance mechanic, machinery3 .............. 149,579 16.43 (100) 14.63 (89) 16.39 (100) 17.04 (104) 20.30 (124)

Maintenance mechanic, motor vehicle3 ......... 101,964 15.69 (100) 14.66 (93) 15.35 (100) 16.66 (106) 17.83 (116)

Maintenance pipefitter3 ................................. 25,214 20.01 (100) 19.09 (95) 18.27 (91) 19.27 (96) 21.01 (105)

Tool and die maker3 ...................................... 55,162 18.75 (100) 16.41 (88) 17.41 (93) 19.16 (102) 21.68 (116)

Material movement

Forklift operator3 ........................................... 186,415 11.28 (100) 10.28 (91) 11.29 (100) 12.36 (110) 16.66 (148)

Material handling laborer3 ............................. 123,808 8.84 (100) 7.91 (89) 9.26 (105) 11.16 (126) 13.12 (148)

Shipping/receiving clerk3 .............................. 108,313 10.24 (100) 9.82 (96) 10.56 (103) 11.06 (108) 12.84 (125)

Truckdriver, tractor-trailer3 ............................. 184,854 14.07 (100) 13.17 (94) 15.19 (108) 16.83 (120) 17.27 (123)

Guard I ......................................................... 319,009 7.01 (100) 6.31 (90) 7.30 (104) 8.13 (116) 9.60 (137)

Janitor3 ......................................................... 908,513 7.83 (100) 6.82 (87) 8.07 (103) 8.59 (110) 9.76 (125)

Occupation and pay level2

All establishments

Number of

workers

Average pay and relative pay level by establishment size

2,500

or more Fewer than 500 500-999 Average pay

(mean) 1,000-2,499

1 Relative pay levels, shown in parenthesis, indicate the relative pay of different

establishment size categories as a percent of all establishment pay. For example,

average pay for general maintenance workers in establishments with 2,500 or more

workers is 23 percent higher than the national average for that job. 2 Occupations in the Occupational Compensation Survey program are divided into

work levels based on duties and responsibilities. The number of levels varies by

occupation, as does the degree of difficulty and responsibility. Work levels among

different occupations are not necessarily equal. 3 Single-level occupations.
 Compensation and Working Conditions Spring 1998 32

Introduction

The Bureau has published several

studies that demonstrated a mixed relationship between establishment size

and wages. William R. Bailey and

Albert E. Schwenk in 1980 used information from 34 narrowly defined

manufacturing industries (3- or 4-digit

Standard Industrial Classification

codes) from the Bureau’s Industry

Wage program. They found that “there

are considerable differences among industries in the degree to which earnings vary by size of establishment. The

size differential is widespread, but not

universal.”4

Martin E. Personick and Carl B.

Barsky, using data from the Bureau’s

March 1980 National Survey of Professional, Administrative, and Clerical Pay, studied the effects of corporate size on white-collar pay levels.

They found a “tendency for the wage

differential to decline with increasing

skill level.”5

Other Bureau studies have demonstrated that compensation costs, both

wages and benefits, are also related

strongly to the size of establishment.6

Background

Comparing the average earnings of

workers by size of establishment, as

done earlier in this study, gives an indication of how size is related to earnings, but it does not show whether size

itself, or other important establishment

and occupational characteristics, are

important factors in explaining pay

differences. To better isolate the effect of establishment size on occupational pay, a series of regression equations were generated. In the

regressions, the average earnings of a

selected number of jobs were the dependent variable, while size of establishment, region, and metropolitan

characteristic were independent variables. Because of the different definition used to measure establishment

size in the goods- and the service-producing sectors, separate regression

equations were run for each.

The constant related to workers

employed in an establishment with

fewer than 500 workers in the South

and in a nonmetropolitan area.

The impact of more detailed industry variables was also tested. Within

the goods-producing sector, construction and manufacturing divisions were

independent variables, with mining included in the constant. Similarly, in

the service-producing sector, regressions were run with transportation and

utilities; wholesale trade; retail trade;

and finance, insurance, and real estate

as independent variables. The impact

of services was included in the constant. These regressions, while demonstrating that industry was significantly related to earnings, also showed

that the inclusion of industry in the

estimating equation had little effect on

the coefficients of the size of establishment variables. For that reason, these

regressions were not included in the

analysis.

However, other variables which

have an important impact on earnings

were not available. Variables such as

unionization and demographic characteristics such as sex and race were

unavailable and not included in the

analysis. It is possible that establishment size is a proxy for these or other

variables.

Results

The ability of the regression equations to explain the variation in earnings was much better for blue-collar

and protective service occupations

than for white-collar workers. For

example, the variables in the regression equation explained less than 3

percent of the variability for engineers,

level IV, but 64 percent of the variability in wages for corrections officers. (See tables 5 through 9.)

An important reason for the small

explanatory power of some of the equations (as measured by the R2

) is the

manner in which they are specified.

The focus on narrow occupations reduces considerably the range of earnings and the ability of the regression

equation to explain the variations. For

example, engineer IV is the most

populous of the occupation’s eight levels, but still represents only 30 percent

of all engineers within the United

States. Within the same level, pay for

higher skilled occupations such as engineer, varies less than for blue-collar

jobs because the labor market is national rather than local.

Regression findings generally followed those of occupational averages

for workers grouped by characteristic.

Earnings did not always rise consistently with establishment size. For

example, holding other variables constant, the regression equation estimates that computer systems analysts,

level II, in the goods-producing sector

averaged nearly $34 per week less in

establishments with 500 to 999 workers than in establishments with fewer

than 500 workers. Similarly, engineers, level IV, in the goods-producing sector averaged $15 per week less

when making a comparable comparison.7 (See tables 5 and 7.)

Regression analysis showed that

earnings of workers in establishments

with 2,500 workers or more were generally higher than in smaller establishments. Accounting clerks, level II, in

the largest establishment category averaged $65 per week more in goodsproducing and $18 per week more in

the service-producing sector than comparable workers in establishments with

fewer than 500 workers.

Among blue-collar workers, those

employed by establishments with

2,500 workers or more enjoyed a significant premium over those in establishments with 50 to 499 workers.

(See tables 6 and 8.) For example, in

the goods-producing sector, forklift

operators and janitors earned over $5

an hour more when comparing earnings among these establishment size

categories. (See chart.)

Percentage differences in earnings

among size classes were found to be

much larger for blue-collar than for

white-collar jobs. Janitors in the largest establishment category enjoyed

nearly a 50- and 25-percent advantage

Regression Analysis
33 Compensation and Working Conditions Spring 1998

over the smallest establishment size

category in goods- and service-producing establishments, respectively. Similarly, a comparison for forklift operators between comparable establish- ment

size categories found a 50- and 38-percent pay differential, respectively.

In contrast, for accounting clerks,

level II, the percentage difference in

earnings between the largest and

smallest establishment size category

was only 17 percent higher in goodsproducing and 5 percent higher in service-producing industries. Among

engineers, level IV, the earnings difference in goods-producing industries

between any of the establishment size

categories was only three percent.

Earnings of corrections officers and

police officers, level I, did not rise consistently with establishment size.

Earnings in establishments with 500

to 2,499 employees were lower than

in establishments both smaller and

larger in size. However, the pattern

of the largest establishments enjoying

a significant pay advantage held true.

Corrections officers and police officers, level I, employed in establishments

with 2,500 workers or more enjoyed a

$35 and $28 per week advantage, respectively, over employees in establishments with fewer than 500 workers.

Conclusion

Establishment size has a significant effect on earnings for most of the

occupations studied for comparison,

even after other establishment and occupational characteristics were taken

into account. However, other variables

are also important factors in determining pay. Among those studied, region

and metropolitan character were found

to be significant. Other variables, such

as unionization, may also have an impact, but data were not available for

this study. The results of this study on

establishment size, however, were consistent with earlier studies. The importance of establishment size was

more significant among blue-collar

and clerical occupations, a finding

consistent with Personick and Barsky.

As Bailey and Schwenk determined,

however, the impact of establishment

size “is widespread, but not universal.”

1

 See the national bulletin, Occupational

Compensation Survey: National Summary,

1994, Bulletin 2479, Bureau of Labor Statistics,

June 1996. Also see John E. Buckley, “Occupational Pay Across Regions in 1994,” Compensation and Working Conditions, June 1996, pp. 35-

38; Robert W. Van Giezen, “Occupational Pay in

Private Goods- and Service-Producing Industries,”

Compensation and Working Conditions, June

1996, pp. 29-34; Elizabeth Dietz and Jordan

Pfuntner, “Do Urban Workers Earn More than

Their Country Cousins?”, Compensation and

Working Conditions, June 1996, pp. 39-41; and

John E. Buckley, “Pay in Private Industry and

State and Local Governments, 1994,” Compensation and Working Conditions, September 1996,

pp. 22-26. 2

 For more extensive data from the surveys

and a more complete discussion of the scope of

the Occupational Compensation Survey program,

the computation of pay relatives, and the occupation definitions used in the survey, see Occupational Compensation Survey: National Summary, 1995, Bulletin 2487, Bureau of Labor Statistics, May 1997. 3

 Pay relatives indicate establishment size pay

as a percent of national pay for occupational and

industry groups. For example, the differences in

earnings between occupational groups and individual occupations discussed in this analysis are

compiled by dividing the higher pay relatives by

the lower pay relative. The pay advantage for an

occupational group with earnings 25 percent above

the national average compared to a group 10 percent below the national average is 39 percent. 4

 William R. Bailey and Albert E. Schwenk,

“Wage Rate Variation by Size of Establishment,”

Industrial Relations, Spring 1980, pp. 192-198. 5

 Martin E. Personick and Carl B. Barksy,

“White-collar Pay Levels Linked to Corporate

Work Force Size,” Monthly Labor Review, May

1982, pp. 23-28. The diminishing of the size effect as skill level increased was also found by

Charles Brown and James Medoff, “The Employer Size-Wage Effect,” Journal of Political

Economy, October 1989, pp. 1027-1059. 6

 These studies defined small establishments

as those employing 100 to 499 workers and medium and large establishments as those employing 500 workers or more. For more information

on size of establishment and employee benefits,

see Thomas P. Burke and John D. Morton, “How

Firm Size and Industry Affect Employee Benefits,”

Monthly Labor Review, December 1990, pp. 35-

43. See also Wayne Shelly, “Compensation Cost

Levels by Establishment Size,” Compensation

and Working Conditions, August 1991, pp. 1-8. 7

 The regression results for engineers, level

IV, correspond with those found for overall engineers. See Kenneth J. Hoffmann, “Analyzing

Wage Patterns of Engineers and Secretaries,”

Compensation and Working Conditions, Fall

1997, pp. 22.

—ENDNOTES—
 Compensation and Working Conditions Spring 1998 34

Constant....................................................... 14.0471 .190 8.7491 .128 6.5111 .156

Establishment size by number of workers:

 500-999 ....................................................... -1.3301 .174 .051 .128 -.5761 .182

 1,000-2,499 ................................................. .5831 .208 1.4611 .157 1.5971 .210

 2,500 or more .............................................. 2.7831 .208 5.6391 .278 5.2221 .258

Region:

 Northeast .................................................... 1.5631 .223 1.8521 .180 1.5031 .198

 Midwest ....................................................... 2.7361 .162 1.9361 .119 3.6921 .159

 West ............................................................ 2.6971 .239 .8231 .179 .332 .211

Metropolitan character:

 Metropolitan area ........................................ 2.8641 .180 1.1961 .115 2.0321 .161

R2 .................................................................. .3279 .2557 .3315

Adjusted R2 ................................................... .3256 .2538 .3299

1

 Significant at the 1 percent level.

Table 5. Regression results for selected white-collar occupations in the goods-producing sector, by independent variable,

November 1995

Constant....................................................... 1,120.7611 3.702 902.1481 8.195 337.9031 2.291

Establishment size by number of workers:

500-999 ....................................................... -15.1491 2.230 -33.9841 4.507 10.4691 2.705

1,000-2,499 ................................................. 6.6171 2.291 32.0531 4.314 24.9711 4.053

2,500 or more .............................................. 10.9151 2.493 46.7631 4.659 65.3411 10.531

Region:

Northeast .................................................... -34.4051 2.536 8.3261 4.869 33.5841 3.019

Midwest ....................................................... -10.1031 2.119 26.5521 4.236 -.295 2.331

West ............................................................ 24.5821 2.312 3.3011 4.570 20.6241 2.986

Metropolitan character:

Metropolitan area......................................... 35.6641 3.481 22.9131 8.026 24.5981 2.349

R2 .................................................................. .0229 .04691 .0980

Adjusted R2 ................................................... .0227 .0459 .0965

Parameter

estimate

Standard

error

Standard

error

Parameter

estimate

Parameter

estimate

Standard

error

Engineer IV Computer systems analyst II Accounting clerk II

Independent variable

1

 Significant at the 1 percent level.

Maintenance electrician

Independent variable

Forklift operator Janitor

Parameter

estimate

Standard

error

Parameter

estimate

Parameter

estimate

Standard

error

Standard

error

Table 6. Regression results for selected blue-collar occupations in the goods-producing sector, by independent variable,

November 1995
35 Compensation and Working Conditions Spring 1998

Table 7. Regression results for selected white-collar occupations in the service-producing sector, by independent variable,

November 1995

Constant....................................................... 1,157.8421 6.536 884.6701 13.225 297.7321 2.408

Establishment size by number of workers:

 500-999 ....................................................... 16.0191 4.412 15.8111 2.677 13.6601 2.151

 1,000-2,499 ................................................. 46.1761 3.438 -.719 2.327 3.767 2.110

 2,500 or more .............................................. 47.3101 5.386 1.865 2.688 18.2531 3.066

Region:

 Northeast .................................................... -6.834 3.741 25.7221 2.433 37.9121 1.863

 Midwest....................................................... -21.9971 3.769 24.9441 2.392 4.0132 1.739

 West ............................................................ 9.6771 3.837 70.4211 2.871 30.0461 1.726

Metropolitan character:

 Metropolitan area ........................................ -7.809 6.441 12.274 13.155 54.5121 2.348

R2 .................................................................. .0233 .0323 .1119

Adjusted R2 ................................................... .0227 .0320 .1114

1

 Significant at the 1 percent level.

2

 Significant at the 5 percent level.

Table 8. Regression results for selected blue-collar occupations in the service-producing sector, by independent variable,

November 1995

Constant....................................................... 15.9591 .281 10.0701 .238 5.2151 .042

Establishment size by number of workers:

 500-999 ....................................................... -.9551 .260 2.8201 .244 .2971 .034

 1,000-2,499 ................................................. -.261 .210 2.0511 .267 1.0711 .034

 2,500 or more .............................................. .7231 .237 4.4391 .396 1.6801 .055

Region:

 Northeast .................................................... 1.9441 .223 2.1771 .211 3.1581 .031

 Midwest....................................................... 2.8821 .205 1.5571 .216 .8261 .032

 West ............................................................ 2.9331 .263 1.6741 .229 1.1171 .034

Metropolitan character:

 Metropolitan area ........................................ .8071 .264 -.5552 .244 .2041 .040

R2 .................................................................. .1639 .1837 .2910

Adjusted R2 ................................................... .1602 .1804 .2908

1 Significant at the 1 percent level.

2 Significant at the 5 percent level.

Engineer IV Computer systems analyst II

Independent variable

Accounting clerk II

Parameter

estimate

Standard

error

Standard

error

Standard

error

Parameter

estimate

Parameter

estimate

Independent variable

Maintenance electrician Forklift operator Janitor

Standard

error

Parameter

estimate

Parameter

estimate

Standard

error

Parameter

estimate

Standard

error
 Compensation and Working Conditions Spring 1998 36

Table 9. Regression results for selected protective service occupations in all industries, by independent variable,

November 1995

Constant ............................................................. 281.8331 5.855 310.5351 21.209

Establishment size by number of workers:

 500-999 ............................................................. -22.5161 5.765 -23.1681 4.478

 1,000-2,499 ....................................................... -3.782 4.655 -10.6122 4.785

 2,500 or more .................................................... 35.4041 5.616 28.0541 5.280

Region:

 Northeast.......................................................... 238.0541 4.204 196.3911 3.810

 Midwest ............................................................ 94.4361 5.009 106.5051 4.000

 West ................................................................. 260.1691 5.862 243.5721 4.129

Metropolitan character:

 Metropolitan area .............................................. 48.5641 3.929 142.8901 4.341

Industry:

 State and local government .............................. 108.2361 7.408 133.6991 20.758

R2 ........................................................................ .6424 .3815

Adjusted R2 ......................................................... .6417 .3810

1

 Significant at the 1 percent level.

2

 Significant at the 5 percent level.

Corrections officer Police officer I

Independent variable Parameter

estimate

Standard

error

Parameter

estimate

Standard

error

No te: Wo rke rs in large e stab lis hme nts are defin ed a s emp loy ed in estab lishm ents

w ith 25 00 o r mo re emp loy ee s. The pay ad van tag e of the se wo rke rs is c om pa red

to w ork ers in e stablish me ts with 50 to 4 9 9 wo rke rs.

Elect rician

Forklift operator

Janitor

$0 $1 $2 $3 $4 $5 $6

St raight-t ime hourly earnings

 G ood s-produci ng Service-produci ng 

Regression results on the pay advantage of selected blue-collar workers in large

establishments by industry, November 1995

NOTE: Workers in large establishments are defined as employed in establishments with 2,500 or more

employees. The pay advantage of these workers is compared to workers in establishments with 50 to 499

workers.

Pay advantage (in straight-time hourly earnings)

Forklift operator

Janitor

Electrican

Goods-producing Service-producing