Occupa al Compensation

Earnings in
Consolidated
Metropolitan
Statistical Areas

BY KENNETH J, HOFFMANN

The Bureau of Labor Statistics has surveyed Metropoli-
tan Statistical Areas since 1948, beginning with the first
locality wage survey of occupations. In late 1995, how-
ever, BLS began converting to surveys of Consolidated Met-
ropolitan Areas. This article discusses the two area defini-
tions, the reasons for the change, and the effect the change
has had on survey results.

A Metropolitan Statistical Area (MSA) is defined by the
Office of Management and Budget as a city with 50,000 or
more inhabitants, or a Census Bureau-defined urbanized
area with at least 50,000 inhabitants and a total metropoli-
tan population of at least 100,000 (75,000 in New England).
The geographic area of an MSA is usually defined in terms
of counties. For example, the Green Bay, Wisconsin MSA
is defined as Brown County. In New England, the area is
defined in terms of cities and towns.

A Consolidated Metropolitan Statistical Area (CMSA)
consists of adjoining MSA’s having a combined population
of 1 million or more. When combined into a CMSA, each
component metropolitan area is referred to as a Primary
Metropolitan Statistical Area (PMSA). For example, the
Dallas-Forth Worth CMSA consists of the Dallas PMSA
and the Fort Worth PMSA. This article compares earnings
in PMSA’s to earnings in CMSA’s. No freestanding MSA's
were included in this study.

Presently there are 18 CMSA’s in the United States, made
up of 73 PMSA’s. Seven of the CMSA’s consist of only 2
PMSA’s each; at the other extreme, the Boston-Worcester-
Lawrence CMSA consists of 10 PMSA’s. Three PMSA’s
(Chicago, Houston, and Milwaukee) account for at least 90
percent of the employment within their respective CMSA,

Kenneth J. Hoffmann is an economist in the Division of Compensation
Data Analysis and Planning, Bureau of Labor Statistics. Telephone (202)
606-6201.

65 Compensation and Working Conditions Spring 1998

whereas four PMSA’s in the New York-Northern New Jer-
sey-Long Island CMSA (Danbury, Dutchess County, New-
burg, and Waterbury) account for only about 1 percent
each.'

This study includes 12 CMSA’s and compares their av-
erage earnings to those of 17 PMSA’s within them. For
nine of the CMSA'’s, data are available for only the largest
PMSA. For one of the CMSA’s, data are available for two
PMSA’s, and for the other two CMSA’s, data are available
for three PMSA’s.”

The chief reason that the Bureau converted from the study
of PMSA’s to CMSA’s was that the President’s Pay Agent,
which uses Bureau survey data to recommend adjustments
to Federal white-collar workers’ wages, requested that the
Bureau provide these data at the CMSA level?

Another reason for the change was to make more effi-
cient use of funds. Funding for occupational wage surveys
was reduced and it became necessary to produce less costly
survey results that represented large numbers of workers
without any loss in data reliability. In most cases, aCMSA
can be surveyed for little more than the cost of surveying
the largest PMSA in the area, and the data then represent
all PMSA’s in the area.

The change was made with the realization that users
might have data less specific to their geographic location,
but the altemative would have been that many users would
have no data relating to their location.

Comparing earnings

If wage comparisons are made between PMSA’s and
CMSA’s for individual occupations, the results sometimes
show considerable variation. For example, average wages
of the lowest level of material handling laborers studied in
the Denver PMSA in December 1994 were $9.50 an hour.
The follow-up study of the Denver CMSA in January 1996
reported an average of $7.50, over 20 percent lower. Like-


wise, the relationship between PMSA and CMSA earings
varied among occupations. The average for janitors in the
Cleveland PMSA was 5 percent below the CMSA average,
whereas light truckdrivers in the PMSA earned 3 percent
more. In the same area, level-6 engineers earned 5 percent
less in the PMSA, whereas level-4 engineers earned slightly
more in the PMSA, ©

Therefore, occupations and levels were combined into
three major categories: White collar, protective service, and
blue collar. The white-collar category was divided into four
subcategories: Professional, administrative, technical, and
clerical. The blue-collar category was broken into two sub-.
categories: maintenance and toolroom, and material move-
ment and custodial.*

The average wage for a particular category was com-
puted for the CMSA by multiplying the average wage for
each occupation in that category by the CMSA employment
for that occupation. These products were then summed for
the category and divided by the total employment of all
occupations in that category. The average for the PMSA
categories were similarly computed using PMSA occupa-
tional earnings times CMSA (not PMSA) employment. This
eliminated differences between category averages caused
by different distributions of workers among occupations in
the two areas.

Payroll reference dates of the surveys ranged from July
1994 to November 1996. For areas where the PMSA was
surveyed prior to the CMSA, the PMSA averages were up-
dated using the Bureau’s Employment Cost Index. The
PMSA category averages were then divided by the CMSA
averages and the results multiplied by 100 to reflect PMSA
earings as a percent of CMSA earnings.

Findings

Earnings in PMSA’s were more often above their respec-
tive CMSA earnings than they were below. (See table 1.)
However, the patterns were different when making com-
parisons for the white-collar categories than they were when
making comparisons for the protective service and blue-
collar categories. For the overall white-collar category and
each of its four subcategories, PMSA earnings were more
often below the CMSA earnings than above. The opposite
was true for the protective service and blue-collar catego-
ries where they were more often above. In addition, the
protective service and blue-collar categories showed larger
differences between the PMSA and CMSA earnings than
did the white-collar categories. Standard deviations, which
measure dispersion from the average, ranged from | to 2
percent for the white-collar categories; and 2 to 4 percent
for the protective service and blue-collar categories.

The material movement and custodial category gener-
ally showed more variation among areas than the other cat-
egories, The variation ranged from earnings 5 percent be-
low the CMSA average in Cleveland, to 11 and 12 percent
above in Seattle and Portland, respectively. The occupa-

tions that contributed most to this variation were janitors
and truckdrivers. Janitor averages vary widely depending
on the proportion of the workers employed by janitorial ser-
vices, whereas the proportion of workers covered by union
‘agreements heavily influences truckdriver averages.

Average earnings in a PMSA were nearer to the CMSA
average when the PMSA made up a large proportion of the
CMSA as opposed to when they made up a smaller portion.
Three of the PMSA’s studied had over 90 percent of their
MSA's nonagricultural employment. Within two PMSA’s,
Houston and Milwaukee, average earnings were within 2
percent of CMSA earnings for all occupational categories.
In the third area, Chicago, earnings were within 3 percent
for all categories except the maintenance and toolroom cat-
egory, which had PMSA earnings 8 percent above the
CMSA.

Four of the PMSA’s had between 80 and 90 percent of
their CMSA employment. In three of these, Cincinnati,
Denver, and Philadelphia, earnings were within 5 percent
of the CMSA average. In the fourth, Portland, Oregon,
earnings were very near the CMSA in all but the material
movement and custodial category, where they were 12 per-
cent above the CMSA average. This raised the average for
the overall blue-collar category 8 percent above that of the
CMSA category.

The pattern for the four PMSA’s with between 65 and
80 percent of the CMSA employment was very similar to
the above four. Earnings in Cleveland and Dallas were
within 5 percent for all categories. In the Boston PMSA,
averages were within 3 percent for all categories except the
protective service category where earnings were 12 percent
higher in the PMSA than in the CMSA. In Seattle, aver-
ages were within 2 percent except for material movement
and custodial workers who earned 11 percent more in the
PMSA, raising the average for all blue-collar workers to 8
percent above the CMSA.

Three of the six areas making up the San Francisco-
Oakland-San Jose CMSA each had roughly 30 percent of
the CMSA employment. All occupational categories were
within 4 percent of the CMSA average earnings in San Fran-
cisco and Oakland. In San Jose, administrative workers
earned 6 percent less than the CMSA average, whereas cus-
todial workers earned 8 percent more.

Lawrence and Worcester made up only 8 and 5 percent,
respectively, of the Boston CMSA employment, and Gary
provided 6 percent of the Chicago CMSA employment.
Although they constituted only small parts of their CMSA’s,
their averages were reasonably close to the CMSA aver-
ages. For Gary, all categories were within 4 percent; for
Lawrence all were within 6 percent; and for Worcester all
were within 9 percent.

In summary, PMSA averages for individual occupations
varied considerably from their respective CMSA averages,
but when occupations were grouped, they were never more
than 12 percent from the average.

Compensation and Working Conditions Spring 1998 66


—ENDNOTES—

' Proportionate employment sizes used in this analysis are based on De-
cember 1992 total nonasicataral employment, which was used inthe prob-
ability selection of the areas.

? ‘The areas studied were: Boston-Worcester-Lawrence CMSA, with the
Boston PMSA, Lawrence PMSA, and Worcester PMSA; Chicago-Gary-
Kenosha CMSA, with the Chicago PMSA, and Gary PMSA; Cincinnati-
Hamilton CMSA, with the Cincinnati PMSA; Cleveland-Akron CMSA, with
the Cleveland PMSA; Dallas-Fort Worth CMSA, with the Dallas PMSA;
Denver-1 ‘CMSA, with the Denver PMSA; Houston-Galveston-
Brazoria CMSA, with the Houston PMSA; Milwaukee-Racine CMSA, with
the Milwaukee-Waukesha PMSA; Philadelphia-Wilmington-Atlantic City
CMSA, with the Philadelphia PMSA; Portland-Salem CMSA, with the Port-
land-Vancouver PMSA; San Francisco-Oakland-San Jose CMSA, with the
‘San Francisco PMSA, Oakland PMSA, and San Jose PMSA; and Seattle-
‘Tacoma-Bremerton CMSA, with the Seattle-Bellevue-Everett PMSA.

2 The Federal Employees Pay Comparability Act of 1990 calls for the
Bureau of Labor Statistics to conduct “an annual appropriate survey” to be
used in setting locality pay rates for Federal General Schedule (white-collar)

workers. Under the act, the President appoints an agent to make recommen-
dations tohim. Presently the President’s Pay Agent consists of the Director of
the Office of Personnel Management, the Director of the Office of Manage-
ment and Budget, and the Secretary of Labor.

“ The occupations studied were as follows: Professional-accountant, public
accountant, attorney, and engineer, Administrative-budget analyst, buyer!
‘contracting specialist, computer programmer, computer systems analyst, com-

tenance machinery mechanic, maintenance motor vehicle mechanic, mainte-
nance pipefitter, skilled multi-craft maintenance worker, and tool and die
maker, Material movement and custodial-guard, janitor, material movement
and storage worker, and truckdriver.

Table 1. Earnings in Primary Metropolitan Statistical Areas as a percent of earnings in Consolidated Metropolitan

Statistical Areas, 1994-06 -
{Earnings in Consolidated Metropolitan Statistical Areas = 100)
White collar Pro- Blue collar
PMSA Protes- | Adminis tective Mainte-

All ‘sional trative echnical Clerical | service All nance Custodia!
100 100 100 7 100 112 101 103 100
101 101 102 99 102 103 103 108 101
100 99 99 100 101 101 101 103 100
100 100 100 98 100 102 98 101 Ey
100 98 102 99 104 103 102 104 100
99 101 7 104 5 101 102 104 101
96 - 96 101 96 - 97 98 97
100 100 100 101 101 100 100 99 100
99 99 99 101 98 105 105 104 106
100 100 100 100 100 99 101 102 100
100 101 99 101 98 102 100 99 100
99 100 100 97 100 98 100 9 100
101 102 101 9 100 102 108 99 2
99 99 99 100 97 101 104 104 103
97 - 94 99 98 - 102 99 108
100 102 99 102 100 100 108 102 WW
94 - 3 91 L) - 100 8 105
1.31 117 2.07 182 228 3.36 3.08 277 4.75

NOTE: Dashes indicate data do not meet publication criteria.

67 Compensation and Working Conditions Spring 1998