Union and Nonunion
Sanford M. Jacoby and Daniel J.B. Mitchell*
many purposes, the economic impact of unions
better measured by
the proportion of union wages in total payrolls rather than by the proportion
of unionized employees in the overall workforce.
use recently available
Current Population Survey data to generate estimates of the former.
also show that published data
the Survey on median union and
nonunion wages produce substantially larger estimates of the union1
nonunion wage differential than figures based on mean wages. Finally,
we note that the Bureau of Labor Statistics’ Employment Cost Index
gives undue weight to the union sector because of
workforce is often used as
key index of union strength and influence. For
many years, estimates of the unionization rate were based on membership
estimates obtained from unions by the
Bureau of Labor Statistics
(BLS). More recently, the BLS has shifted to representation estimates from
the Current Population Survey (CPS) as its primary data source
has also been the source of widely used estimates of
union versus nonunion wage levels based on annual estimates of union and
nonunion median “usual weekly earnings” for full-time employees.
For some purposes, the proportion
employees who are union-represented
is an appropriate measure of union influence. If, for example, union political
issue, a count of union workers is an important piece
information. But in other cases, the proportion of total payrolls (or total
compensation) covered by collective bargaining is the more relevant statistic.
In particular, when investigating the influence
union wage settlements in
The authors’ affiliations are, respectively, Anderson Graduate School of Management, University of
Angeles and Institute of Industrial Relations and Anderson Graduate School of
Management, University of California at
2 (Spring 1988).
1988 Regents of the University
an aggregate wage index, the correct and appropriate union weights are
based on payrolls or compensation, not on employment. Despite the
importance of payroll-based weights for assessing the economic impact of
unions, we know of no previously published calculations of such weights.
In this paper, we use data now available from the
to calculate these
estimated payroll weights for commonly used indexes, such as average hourly
earnings and compensation per hour. Union importance in these indexes
is shown to be understated by traditional employment weights. The
understatement is caused by two factors: union workers earn more than
nonunion workers and they work longer hours. We also show that for some
purposes, the published
data on union/nonunion pay differentials are
misleading, owing to the
use of median rather than mean pay measures.
much-quoted estimate of a roughly one-third wage gap between
union and nonunion pay in the mid-eighties is substantially overstated
because the use
medians reduces the effect on the ratio of highly paid
Finally, we note that the union-sector weights in the Employment Cost
Index, an index intended by the
eventually to become the key indicator
of wage change, are too large.
When aggregate wage changes occur, some of the change stems from the
unionized sector of the economy and some from the nonunion. Determining
the source of wage change can be important in an overall assessment of the
economy, particularly with regard to inflation. In periods when unions are
perceived as strong, it often is assumed that wage inflation stems from
bargaining demands. Thus, the federal anti-inflation wage controls mounted
in the early seventies frequently were rationalized by, and focused on,
seemingly excessive union settlements. Similarly, during periods when unions
are perceived as weak-as in the eighties-wage moderation may be attributed
to union concession bargaining.
full assessment of the union impact on aggregate wages must take
the possibility of union-to-nonunion wage influences, such as
spillovers, patterns, and threat effects. However, before such assessments
can be attempted,
simple question must be asked: “If union wages were
to rise by
affecting nonunion wages, how much would
!The authors would like to thank Maury Pearl, who acted as research assistant on this project, and
Schwenk and others at the
Labor Statistics who assisted in providing necessary data
and technical information. They also wish to thank two anonymous referees.
aggregate wages rise?” What is involved here is the basic arithmetic of the
direct union effect on the wage index, i.e., the weight of the union sector
in the index. Indirect effects, such as spillovers, must be added to the direct
effect before the full impact of union settlements on aggregate wage change
will emerge. But the indirect effects are secondary, and common sense
suggests that the direct impacts will dominate, especially in the short run.
Thus, it is the direct effects we seek.
Aggregate wage indexes, such as the monthly average hourly earnings
series and the quarterly compensation per hour index, are computed by
dividing the total payroll (or total compensation bill) by the number of
employee hours. If union wages were to rise by
per cent, the direct effect
on these indexes would be determined by the union weight in payrolls
compensation, not by the union weight in employment. The payroll or
compensation weights will be identical to the employment weights only if,
on average, union and nonunion workers receive the same level of hourly
pay and work the same number of hours per period. In general, neither of
these assumptions is valid. Union workers tend to earn higher pay than
nonunion workers and they tend to work longer hours.
The empirical generalizations of higher pay and longer hours for
union workers do not involve any complex standardizations for worker
characteristics. It is the gross (unstandardized) observations that are relevant.
Even if unions have no causal impact on pay and hours, the fact that
unionized workers are paid more and work longer hours than do nonunion
workers gives the union sector added weight in aggregate wage indexes.
Beginning in the eighties, the Current Population Survey has been used
regularly to obtain data on earnings and unionization. This information is
researchers in published form and on computer tapes. In
this study, we take advantage of these CPS data to estimate the appropriate
union-sector weights in the indexes of compensation per hour and average
Our calculations combine data from the CPS earnings files for
1983 and 1984. These files were compiled by the BLS for outgoing rotation
groups within the CPS sample. They are the same sources the BLS uses to
produce its annual tables on union membership, representation, and union
versus nonunion earnings (BLS, 1982a; Flaim, 1986; Adams, 1986).
Data reported below have been restricted to private, nonagricultural
employees; all self-employed persons have been removed. In order to enhance
JACOBY AND DANIEL
comparability to the establishment-based data reported in the average hourly
estimates include 14- and
part-time workers are also included except where indicated. Neither 14-15
year olds nor part-timers appear in the published BLS tables on union/
nonunion earnings differences. Thus, the definitions adopted in this paper
are better suited for calculating union payroll or compensation weights than
those underlying the published tables. Finally, for purposes of the
computations described below, unionized employees are defined as those
by unions; nonmembers who are in collective bargaining
units are counted as unionized employees.
In the discussion that follows, we refer to two samples drawn from the
CPS tapes: the “global” sample (meant to simulate compensation per hour)
sample (meant to simulate average hourly earnings). The
global sample includes all wage and salary earners remaining after application
the restrictions and definitions noted above. The
sample was derived
by taking the global sample and excluding from it those occupations that
are not included in the payroll data used to generate the
managers, supervisors, and certain other classifications.2 For
observations in the global sample, and
Union/Nonunion Pay Ratio: Means
When the BLS codes the
censors some data values. In particular,
wage and salary workers reporting weekly earnings of
or more are
value of earnings of
Because the BLS only reports median
figures for usual weekly earnings, its published tables are unaffected by this
truncation of the upper tail of the earnings distribution. However, since it
is essential to use means rather than medians to calculate payroll weights-the
objective of this study-estimates of the upper tails had to be reconstructed.
The upper tails
the earnings distribution were assumed to follow the
Pareto di~tribution.~ Methodology following BLS practice was
used for the estimations of the upper tails.4 Pareto factors were calculated
The AHE series includes only production workers in mining and manufacturing, construction workers
in the construction industry, and nonsupervisory workers in all other industries
the Pareto constant and d is the lower limit of the interval to which the Pareto distribution is
assumed valid. When x is not
than d, the conditional mean of the open-ended interval-the Pareto
factor-is then (MA-l)(x*), where x*
of the open-ended interval.
has developed a maximum likelihood estimator for
applied in this study. See West (n.d.).
’In a Pareto distribution, the probability of
individual whose income exceeds
for each industry/union-status distribution presented below, and these factors
were used to compute the needed earnings means and payroll weights.
The upper panel of Table 1 compares the median weekly earnings figures
the BLS with the median and mean earnings figures computed
directly from the merged 1983-1984 files.5 There is a noteworthy discrepancy
between mean and median earnings, especially for nonunion workers. A
high-earning employees fall into the nonunion category. Not
surprisingly, a lesser proportion of unionized workers are very high earners.
The extreme nonunion values have little impact on medians but carry larger
weight in means.
Labor market analysts who rely on the published BLS tables for estimates
of union/nonunion wage differentials should do
with caution. The median
differential is substantially larger than the estimated mean differential (38
per cent vs. 12 per cent). Thus, users cannot assume that calculated union/
nonunion differentials are insensitive to the measure of central tendency
employed. To the contrary, Table 1 demonstrates that medians and means
are not interchangeable.
Analysts who use the BLS tables probably want to know what the average
union worker earns compared with the average nonunion worker. The
clearly a substantial overstatement
to that question. Generally, medians will be relatively insensitive to changes
in the distribution profile.
is possible-though we cannot verify it-that
this insensitivity is responsible for the failure of the BLS published
differentials to reflect the union wage concessions of the eighties.6
shows that the unionlnonunion wage differential
to the sample’s occupational specifications. When occupational definitions
are changed to match those used in the AHE series-chiefly by eliminating
managers and supervisors-the median earnings differential is raised to
per cent, and the mean is boosted to 29 per cent.
could be argued that
the AHE figures in Table 1 are derived from a sample that approximates
the potential union membership base and thus constitutes a more realistic
measure of uniodnonunion earnings differences. However, even for this
restricted sample, a significant meadmedian gap remains for nonunion
divides the earnings distribution into ranges and applies an interpolation technique in the
range in which the median is located to produce its median estimate. In contrast, the
the median presented
are calculated directly from the two-year distribution vithout
an interpolation technique. There appears to be little practical difference between direct
estimation and estimation by interpolation.
wage concessions were concentrated among above-median union workers, they would not pull down
the union median. Freeman
reports an absence
an apparent concession impact using
His analysis was based on regression coefficients estimated across individual workers and not on medians,
however, which may suggest other difficulties with the
Freeman’s paper does not report how he
dealt with the truncated ends of the union and nonunion earnings distributions.
JACOBY AND DANIEL
MEDIAN WEEKLY EARNINGS
PRIVATE, NONAGRICULTURAL WAGE
BLS-published Medians and means calculated from
Global sample AHE sample
1983 1984 Median Mean Median Mean
Union $391 $404 $400 $410 $390 $399
Nonunion 287 302 290 367 250 310
nonunion 1.36 1.34 1.38 1.12 1.56 1.29
Full-time and part-time employees
combined, 1983- 1984
Global sample AHE sample
Median Mean Median Mean
$380 $391 $365 $378
Nonunion 236 304 200 252
nonunion 1.61 1.28 1.83 1.50
Population Survey (see description in text).
workers, a discrepancy which again reflects the weight of the upper tail
the nonunion earnings distribution.
The lower panel of Table
includes part-time workers in both the global
samples. Thus, the lower panel is more comprehensive than the
tables on union vs. nonunion earnings published by the
are paid less than full-time workers, often on an hourly, and certainly on a
weekly basis. They are also heavily nonunion.
result of these differences, absolute earnings are reduced for both
the union and nonunion groups (relative to the upper panel), but the
comparatively greater for nonunion workers. This comparative
effect raises the weekly unionhonunion earnings differential. For example,
Measurement of Compensation
the global median differential increases from
per cent for full-time workers
per cent for full- and part-time workers combined. The same type of
meadmedian discrepancies that characterized full-time workers are again
observed when part-timers are included in the analysis.
presents employment and payroll weights for full- and part-time
workers. Aggregate weights are shown together with weights for industrial,
occupational, and demographic groups. The reported payroll weights were
calculated by multiplying the estimated mean weekly earnings figures by
their corresponding employment levels and then dividing the union payroll
by the total (union plus nonunion) payroll for each classification shown.
Employment weights are simply the proportion of individuals in a specific
category who were represented by unions.
The top line of Table
shows that unions represented
per cent of
private, nonagricultural wage and salary workers in
these unionized workers earned about
per cent of total payrolls in those
years. The discrepancy between employment weights and payroll weights
reflects the earnings differential between unionized and nonunion workers.
could be anticipated from the exclusion of higher-earning occupations,
the gap between employment and payroll weights is larger for the
per cent vs.
per cent) than for the global sample
Disaggregated weights and reverse pay differentials.
When finer breakdowns
are examined, it can be seen that the employment weight is usually less
than the payroll weight. Reverse cases occur only when mean earnings for
nonunion workers in a grouping exceed mean union earnings. Since the
earnings data are
i.e., not standardized for employee characteristics,
such reverse differentials can occur even if unions raise the wages of their
members. Cases in which the union payroll weight is
employment weight can be found among workers in the finance, insurance,
and real estate industry, the mining industry, and among managers and
indicates that the gap between global
employment and payroll weights for males is relatively small when compared
example, in the case
managers and professionals, unionized workers might be nurses and
engineers, while nonunion workers might be doctors, lawyers, and executives.
SANFORD M. JACOBY AND DANIEL
Employment weight Payroll weight
Full time only
10 12 14
33 35 40 44
with the corresponding gap for females. In fact, for full-time workers only,
the male gap
negative in the global sample.
finding for males is a
case of the “tail wagging the distribution”; well-paid, unorganized, male
managers and supervisors dominate the global male payroll weights. When
these workers are removed, as in the
sample, a positive gap appears.
The female earnings distribution is less skewed; there are proportionately
fewer highly paid nonunion women than men. Nevertheless, the global
unionhonunion wage differential does not exist only because of the union/
nonunion wage gap among female workers.
the aggregate level, unionized
men count heavily in total payroll weights; there are more of them, and they
earn more (on average) than unionized women. Thus, the disproportionate
presence of males contributes to the aggregate unionhonunion wage gap
which reflects male/female wage differentials as well as union/nonunion
differences within the two sex groups.
There is a parallel situation with regard to the two age
groups presented in Table
Taken separately, the gap between the
employment weight and the payroll weight for the global sample is evident
only for younger workers (those less than
years old). But, on average,
younger workers earn substantially less than older workers and are less likely
to be unionized. The gap between employment weights and payroll weights
for the overall global sample reflects both unionhonunion age differentials
across age groups and age-related wage differences.
Perhaps the most striking feature of Table
blacks’ pay which comes from the union sector: Over a
third of the black payroll in
even for the global sample, was set
by collective bargaining. This confirms the widespread conclusion in the
union-impact literature that union wage-setting is very important for black
workers (see Freeman and Medoff,
The second row of Table
shows that adding
part-time workers to the sample has little effect on union payroll weights.
This result may seem surprising since Table
demonstrated that adding
part-time workers raises the union/nonunion earnings differential substan-
tially. Why isn’t that boost in earnings differentials reflected in the payroll
This seeming paradox is easily explained. When payroll weights are
calculated, the addition of part-time workers greatly increases the total
number of nonunion individuals in the denominator of the weight. The
“body count” effect of part-timers on nonunion payrolls offsets their wage
depressing effect. In contrast, within the union sector, part-timers add few
bodies but have
sufficient wage-depressing effect to drag down the union
payroll relative to the nonunion.
SANFORD M. JACOBY AND DANIEL J.
Union Impact on Fringe Benefits
Previous studies have found that, in addition to raising wages, unions
increase expenditures on most kinds of fringe benefits. The union “fringe
effect” often is larger than the union wage effect (Freeman and Medoff,
Unfortunately, fringe benefits such as pension plans, health and life
insurance, and similar programs are not included in the
data on usual
weekly earnings. Employer-paid payroll taxes, e.g., for Social Security, are
also omitted. Yet, a complete account of the union weight in total
Compensation must include fringe benefits and payroll taxes.
Although an adjustment for fringe benefits
is needed, the actual results obtained are not likely to be highly sensitive to
the precise technique used. National income account data suggest that the
average ratio (union plus nonunion) of total compensation to wages in the
private sector was about
Of course, if both union and
nonunion workers had the same
ratio, the union payroll weight-adjusted
total compensation basis-could be unaffected; the weight would remain
per cent global estimate of Table
It is simple arithmetic,
alternative assumptions about the union compensation-to-
wage ratio, given the
total ratio and the
per cent union payroll weight.
The payroll weight adjusted for unionhonunion compensation differences
will increase by only about
percentage points for each added
point increase in assumed union compensation impact. That
if the union
compensation-to-wage ratio were
per cent union
payroll weight would rise to
per cent on a compensation basis.
the compensation-adjusted union payroll
weight would be
per cent.8 Thus, even in the absence of good data on
union versus nonunion total compensation, substantial errors in estimating
global compensation (as opposed to payroll) weights are not likely.
One possibility for adjusting
payroll data to a total compensation basis, given the relative insensitivity of
the results, is to use an “average” effect found in the union-impact literature
The difficulty with that approach is that the literature
typically involves methodology specifically designed to extract the “pure”
union effect from the gross unionhonunion differential. We seek the gross
differential, not the pure effect.
A second possibility
to use information from the biennial
global payroll weight
cent means that there
on expenditures for employee compensation. These surveys were discontinued
in the mid-seventies, however, and the outdated data raise obvious difficulties.
Moreover, the unionlnonunion breakdown in the published surveys applied
only to “nonoffice” workers rather than to all employees. Still, since the
surveys purport to measure approximately what we need, it is worth
examining their data.
In 1968, according to the
survey, the ratio of total compensation
(wages, fringes, and payroll taxes) to wages was 1.23 in the union
sector and 1.15 in the nonunion ~ector.~ Subsequently, the ratio pairs
(union:nonunion) were 1.25:1.16 in 1970, 1.28:1.18 in 1972, and 1.32:1.20
in 1974 (the final year for which unionhonunion data were published). If
ratios of this magnitude prevailed in 1983-1984, the global payroll weights
shown on Table
would have been boosted by about
percentage point on
a total compensation basis, i.e., from
per cent to 23 per cent,
It is possible that the union impact on compensation (relative to wages)
grew from the mid-seventies until the 1983-1984 period on which Table
is based. That union wages relative to nonunion wages rose during those
years is well known. But there is no direct measurement available.
alternative to direct measurement, we can combine the national income data
cited above and a crude regression technique to factor out the union/
The national income accounts include data on wages and salaries
(corresponding roughly to earnings in the
and total compensation on
detailed industry basis. Thus, it is possible to calculate the ratio
total annual employee compensation to total annual payrolls for each two-
digit industry in 1983-1984.
Unfortunately, national income data do not
differentiate between union and nonunion compensation. However,
industry regression with
as the dependent variable and the industry-level
union payroll weights as the independent variable will yield a rough-and
probably upward biased-estimate of the union compensation impact.
Labor Statistics (1971, p.
Wages are defined as “pay
Related data cited below are from
Bureau of Labor Statistics (1973, 1975, 1977).
“’National income data on compensation, wages and salaries, and employment appear annually in the
usually in the July issue, and in various supplements.
The issues regarding interpretation of the coefficient are analogous to those involved in cross-sectional
union wage impact studies, as discussed extensively in Lewis (1963) and in Mitchell (1980). If union
values are infleenced by the unionization measure, biases will result. Since union
bargaining strength is likely to increase as the unionization measure rises, there probably will be an
upward bias in the coefficient. We did try various regression specifications using R, as the dependent
variable and union payroll weights
as the unionization measure; none yielded impressive results.
For example, across 57 industries drawn from the national income accounts and matched with
data, the following regression was estimated: log(R,)
.17P,, where both coefficients are
significant at the 5 per cent level but
regression suggests that for nonunion workers,
and for union workers, 1.37.
When applied to the national income data for
yields an estimated union compensation-to-wage ratio of almost
nonunion ratio in the
this (undoubtedly too high)
estimate is used to adjust the
per cent global union weight of Table
it raises that weight to about
per cent. It seems reasonable to assume,
therefore, that the global weight on a total compensation basis would be
per cent and
The CPS did not collect data on union vs. nonunion wages during much
of the period of declining unionization, i.e., the period from the mid-fifties
to the present. However, it is possible to use alternative data sources to
make rough estimates of the time path of the union weight in payrolls.
Specifically, we used national income account data on wages and salaries per
employee for industries with above-average and below-average unionization
trends for these two industry groupings were assumed to track
general union and nonunion pay trends, respectively. These data were
benchmarked to the
CPS-based payroll estimates (discussed
earlier) to produce comparable estimates for selected two-year periods
beginning in the mid-fifties. The results are graphed in Figure
The Figure permits comparison of the union employment and payroll weights
over the estimation.
shows that union payroll weights typically have been
percentage points above employment weights. And, based on the discussion
in the previous section, another roughly
percentage points should be added
to adjust the data to
total compensation basis. Thus, the importance of the
union sector in aggregate pay setting has been chronically understated by the
traditional employment-based unionization rate.
On the other hand, although union wages generally rose relative to nonunion
wages during the period from the mid-fifties through the seventies, the widening
union pay advantage only partially offset the downward pull
unionization rate. And, in the eighties, the widening uniodnonunion pay trend
reflected in the national income account data has reversed, intensifying the
decline of the union payroll and compensation weights.
I2Unionization rates used to divide industries into the two groupings were taken from
Labor Statistics (1972, Table
and applied to 1970. Forty industries were used (see Appendix). The
benchmarking technique involved linking the national-income-based percentage pay changes between
each two-year period appearing in Figure
and the 1983-1984 period for which we had estimates of
union and nonunion pay from the
earlier period union pay was estimated to
per cent of union pay in 1983-1984,
implicit union wage of .75 times the 1983-1984 level of pay
was assumed. Union and nonunion employment estimates of pay levels in each period could be
union payroll weights using BLS estimates of private union membership.
Union weights: Employment and Payroll
1953-1954 1958-1959 1963-1964 1968-1969 1973-1974 1978-1979 1983-1984
Beginning in the mid-seventies, the
has made available the
Employment Cost Index (ECI) as a measure of wage rate change. Initially,
the ECI was confined to private wages and salaries. During the eighties,
however, the index was expanded to include benefit and payroll taxes and
state and local government. Unlike the older compensation per hour and
average hourly earnings series, the ECI is published with a uniodnonunion
breakdown. The availability
these comparative data suggest that this index
might be a good source of information on union payroll and compensation
weights-a possibility reinforced by the
touting of the ECI as the best
wage and compensation
I3According to the
was developed because alternative wage indexes
“...were found to
fragmented, limited in industrial and occupational coverage, insufficiently timely
subject to influences unrelated to the basic trend in employee compensation.”
methodology precludes an accurate tracking of payroll
and compensation weights. To obtain information on wage change for the
tracks ajixed sample ofestablishments. The
based on fixed employment weights, t00.l~ Until the mid-
eighties, the base period for the
was 1970. Thus, the relative shrinkage
in employment in industries
which unions were concentrated after 1970
was not reflected in the
The shift toward nonunion production
industries was also not reflected because of the fixed sample of
establishments. Most of this shift occurred as new establishments, which
were nonunion, replaced older union establishments. The newer establish-
ments were not permitted to enter the sample.
Until the mid-eighties, the proportion
union employees in the
about one-third, well above estimates from other sources, and reflecting the
upward biases just cited. Given the overestimate of union employment,
payroll and compensation weights for the union sector in the
the mid-eighties, the base year for the
was moved to
1980 and new establishments were included in the sample. These alterations
dropped the unionization rate embedded in the index to about
one-fourth, still too high, because
the trends of the eighties persist, i.e.,
shift toward industries which have
historically had low unionization rates and a shift within industries toward
nonunion production, the
will continue to place excessive weight on
the union sector.16
The proportion of workers represented by unions has traditionally been
used as a measure
unions in wage setting. However,
preferable measure is the percentage of the total national payroll located in
the union sector.
union workers receive identical rates of pay and worked
the same number of hours, there would be no discrepancy between these
measures. But, in fact, the pay and hours differences produce payroll or
compensation weights for union workers which are higher than their
ECI methodology, see
(1982a, 1986) and Wood (1982).
will make available the payroll and compensation weights for the ECI but prefers that
they not be published. Hence, we cite
the employment weights in the text.
should be noted that if the
and nonunion components are used separately
uniodnonunion pay differentials;
example, the overweighting of the
overall index has
periods when union and
wage-change trends diverge,
the overweighting will have only a small effect on the overall ECI.
When presenting these findings to labor market analysts, we have often
been told that “everyone knows” that payroll weights
employment weights-should be used for judging the union sector impact
on wage indexes. Perhaps that is
Specific statements in the literature
recognizing this fact are hard to find, however.17 Moreover, until the
data became available, estimates of the type we have presented could not
have been made readily. Now that data are available, analysts of the union
effect on general wage movements ought to be using payroll-based weights.
It would be helpful if the CPS methodology omitted the truncation of
reported usual weekly earnings at the $1,000 level. Median estimates would
not be effected, but means (which we have shown differ substantially from
medians) would become available directly. Similarly, if the establishment
survey-on which average hourly earnings are based-included information
on the union status of the sampled establishments, union payroll weights
could be calculated and reported. Finally,
revival of the survey of union
versus nonunion benefits practices would assist in estimating union weights
in total compensation.
Industries Used to Calculate Pay Trends
Above- and Below- Average Unionization Rates
Industries with below-average unionization had unionization rates (union
members as a percentage
wage and salary workers)
20.8 per cent,
where 20.8 per cent is the private, nonagricultural average unionization rate
in 1970. These industries are marked with a “(B)” in the listing below. All
other industries had above-average unionization.
Forestry and fishing
Lumber and wood products
Furniture and fixtures
Stone, clay, and glass products
Machinery except electrical
the extent that researchers have devoted their efforts to developing union weights, those efforts
employment weights, not payroll weights. See,
example, Freeman and
Motor vehicles and parts
Other transportation equipment
Miscellaneous manufacturing industries
Food and kindred products
Apparel and other textile products
Paper and allied products
Printing and publishing
Chemicals and allied products
Petroleum and coal products
Rubber and miscellaneous plastics products
Leather and leather products
Other public utilities
Banking and other financial services (B)
Insurance and real estate
Health services (B)
Welfare and religious services
Other professional services
“New Data on Union Members and Their Earnings,”
Employmenr and Earnings,
Union Wage Concessions in Standard Data Sets,”
Medoff. “New Estimates of Private Sector Unionism
the United States,”
What Do Unions Do?
Union Relative Wage Effects: A
Chicago, IL: University
Unionism and Relative Wages in the United States: An Empirical Inquiry.
and Labor Relations Review,
Mitchell, Daniel J.B.
Unions, Wages, and Inflation.
Washington, DC: Brookings Institution, 1980.
Economics and Informarion Theory.
Amsterdam: North Holland Publishing, 1967.
Bureau of Labor Statistics.
Bulletin 2239. Washington, DC: GPO,
Handbook of Methods,
Bulletin 2134-1. Washington, DC: GPO, 1982a.
Technical Description of the Quarten) Data on Weekly Earnings from the Current Population
Selected Earnings and Demographic Characteristics of Union Members,
1970. Report 417. Washington,
Employee Compensation in the Pnvare Nonfarm Economy.
Bulletins 1722, 1770, 1873, 1963, for 1968,
the Mean from Censored Income Data,” unpublished paper,
Wood, G. Donald
“Estimation Procedures for the Employment
Monthly Labor Review,
Bulletin 2113. Washington, DC: GPO, 1982b.
DC: GPO, 1972.
1970, 1972, and 1974, respectively. Washington, DC: GPO, 1971, 1973, 1975, 1977.
Bureau of Labor Statistics, Office of Research and Evaluation, n.d.
CV (May, 1982), 40-42.