NORC at the University of Chicago
Longitudinal Analysis of Strike Activity
Author(s): David Card
Source: Journal of Labor Economics, Vol. 6, No. 2 (Apr., 1988), pp. 147-176
Published by: The University of Chicago Press on behalf of the Society of Labor
Economists and the NORC at the University of Chicago
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Longitudinal Analysis of
Strike Activity
David Card, Princeton University
This article presents an empirical study of strike activity in a panel of
contract negotiations for some 250 firm-and-union pairs. Evidence is
presented on two sources of variation in dispute rates: changes in the
characteristics of the collective bargaining agreement that affect subsequent
strike outcomes and the effects of lagged strikes on the inci
dence and duration of subsequent disputes. Strike probabilities are
significantly affected by the duration and expiration month of the
previous agreement. Dispute rates are also increased by the occurrence
of a short strike during the previous negotiations and reduced by the
occurrence of a long strike.
I. Introduction
The growing availability of data on collective bargaining settlements in
the union sector has generated widespread interest in the empirical analy
of strikes.1 In contrast to earlier studies based on the aggregate number o
I am grateful to Wayne Vroman for making available his contract data and to
Sheena McConnell and Joe Tracy for access to their data on strikes. Thanks to
John Abowd, Rebecca Blank, and George Jakubson for comments on earlier drafts.
' Recent studies include papers by Gramm (1986, 1987), Gunderson, Kervin, and
Reid (1986), McConnell (1986), Schnell and Gramm (1987), Tracy (1986, 1987),
[Journal of Labor Economics, 1988, vol. 6, no. 2]
? 1988 by The University of Chicago. All rights reserved.
0734-306X/88/0602-0003$01 .50
147
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148 Card
strikes, re
of strike outcomes.2 This article focuses on the time-series variation in
bargaining-pair-specific strike outcomes. Evidence is presented from a panel
of collective bargaining agreements on two sources of variation: changes
in the characteristics of the collective bargaining agreement that affect
subsequent strike outcomes and the effects of lagged strike outcomes on
the incidence and duration of subsequent disputes.
The first part of this article addresses the question of whether bargaining
parties can vary the probability of future work stoppages by their choice
of contract characteristics. I concentrate on three aspects of the preceding
contract: the expiration month of the contract; the duration of the contract;
and the provision of a limited reopening clause, which restricts subsequent
negotiations to a small number of issues (usually wages). The empirical
analysis shows that strike probabilities are higher following a long contract
and lower in limited reopening situations. Strike probabilities are also higher
following expirations in summer and fall, relative to winter and spring.
The second part of the article addresses the question of whether strike
probabilities and durations are affected by preceding strike outcomes.
Contrary to the findings of previous researchers, there is no evidence of
state dependence in strike incidence.3 The absence of simple state dependence,
however, is the product of two competing effects: an increase in
strike probabilities following a strike of less than 14 days' duration and a
decrease in strike probabilities following a longer work stoppage. In contrast
to the effects of lagged strike outcomes on subsequent strike probabilities,
the effects on subsequent durations are small and imprecisely
measured.
II. Data Description
The data in this study represent strike outcomes for contract negotiat
of 253 bargaining pairs during the period from 1955 to 1979. Contract
terms and strike information were originally collected from the Bureau of
Labor Statistics' monthly publication, Current Wage Developments (CWD),
by Wayne Vroman.4 Vroman's data set contains information on some 300
collective bargaining situations covering 1,000 or more workers. For purand
S. Vroman (1986). Earlier studies include Farber (1978), Mauro (1982), and
Swidinsky and Vanderkamp (1982). Much of the recent empirical and theoretical
literature on strikes is summarized by Kennan (1986).
2 Among the aggregate studies are papers by Ashenfelter and Johnson (1969),
Pencavel (1970), Kaufman (1982), and Abbott (1984).
3 Mauro (1982) and Schnell and Gramm (1987) both report evidence that strike
probabilities are reduced following a strike in the previous negotiation.
4 I am grateful to Wayne Vroman for making these data available. A further
description of the sample is presented in W. Vroman (1982).
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Strike Activity 149
poses of this article however, I have focused on bargaining pairs with
complete information on at least seven consecutive agreements. The resulting
sample contains 2,543 contracts, or an average of 10 contracts per
bargaining pair.
Table 1 presents a cross-tabulation of the data by industry. With the
exception of contracts for seven bargaining pairs in transportation, communications,
and public utilities, the contracts are drawn from the manufacturing
sector.5 The coverage within two-digit manufacturing industries
is irregular and reflects Vroman's original interest in "pattern" bargaining
and wage determination. The data set contains single-employer contracts
covering multiple establishments (such as the Autoworkers' agreements
with General Motors, Ford, and Chrysler), multiple-employer agreements
(such as the Distillery Workers' agreements with the Winery Employers
Association of California), and single-establishment agreements (such as
the Machinist's agreements with Morse Chain). The average number of
workers covered by each contract is 13,000.
The contract sample is "unbalanced" in the sense that there are different
numbers of contracts for each bargaining pair. Contracts in the textile
industry, for example, tend to be short. As a result, there is an average
of 14 contracts per bargaining pair from this industry over the 24-year
sample period. Most contracts in the transportation equipment industry,
in contrast, run for 3 years. As a result, there are approximately eight
contracts for each bargaining pair in the sample from this industry.
In addition to fixed-duration noncontingent contracts, the sample contains
a variety of alternative contract forms, including fixed-duration
contracts with contingent cost-of-living wage-adjustment formulas (approximately
25% of the sample), contracts with scheduled wage-reopening
provisions (approximately 7.5% of the sample), and contracts with contingent
wage-reopening provisions (approximately 1% of the sample).6
Since wage-reopenings place the parties at risk of a strike, I have defined
each reopening as a new contract. The impact of reopener clauses on strike
probabilities is analyzed in the next section.
Even in the absence of explicit reopening provisions, most long-term
'The nonmanufacturing bargaining pairs are: Class I Railroads and the Railroad
Engineers; Class I Railroads and the Brotherhood of Railroad and Airline Clerks;
Trucking Employers Incorporated and the Teamsters (National Master Freight
Agreement); New York Shipping Association and the Longshoremen; Pacific Maritime
Association and the Longshoremen; United Airlines and the Machinists; and
ATT (Longlines Division) and the Communication Workers.
6 A reopening clause states that the parties will open an ongoing agreement for
purposes of renegotiating a limited number of contract issues (often only wages):
see Bureau of National Affairs (1986, sec. 36.2). Most reopener clauses in the sample
specify a fixed date for reopening. A small number specify reopening contingent
on a specific event (e.g., discontinuation of wage and price controls; wage adjustments
in contracts at other firms; inflation rates above a certain maximum).
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Strike Activity 151
labor contracts can
the parties, and many contracts are automatically extended past their
scheduled expiration date unless one party or the other files a formal notice
of intent to terminate the contract and put the pair at risk of strike.7 Approximately
1% of contracts in the sample were reopened earlier than 3
months before their scheduled expiration date, and another 6% ran more
than 3 months past their scheduled expiration date before a new contract
was reached or a strike was declared. While these facts introduce some
ambiguity into the notion of a contract expiration date, I have adopted
the convention of dating expirations by the earlier of the expiration date
of the preceding contract and the actual renegotiation date of the next
contract, as reported in Current Wage Developments.8
The third and fourth columns of table 1 contain information on the
probability and mean duration of strikes by industry. For most of the
contracts in the sample, the source of strike information is the contract
listing in Current Wage Developments.9 For contract expirations after 1970,
however, strike information is also available from an exhaustive listing of
major strikes assembled by Sheena McConnell and Joseph Tracy.10
McConnell and Tracy's data include local-issue strikes associated with the
ratification of multiestablishment master contracts, as well as more widespread
disputes. For comparability with the CWD definition of contract
strikes, however, I restricted attention to disputes involving at least 70%
of workers covered by each contract." The McConnell-Tracy strike listings
7 See ibid., sec. 36.2. A small number of contracts in the sample from the textile
industry specify an indefinite contract duration, although these contracts all reopened
at regular 12- or 24-month intervals.
8 An interesting issue for further research is the question of when and why the
parties continue to operate under the terms of the old contract.
9 The original source of the strike information in CWD is the contract report
filed by firms at the request of the Bureau of Labor Statistics (BLS), in connection
with their ongoing analysis of wage changes in contracts with 1,000 or more workers.
For contracts negotiated between 1960 and 1970 I checked the CWD strike information
against contract information reported in the Monthly Labor Review's monthly
summary of recent developments in industrial relations. I found only three examples
of strikes reported in the Review that were not recorded in CWD.
10 McConnell and Tracy's strike listings were assembled from three sources: a
weekly BLS in-house newsletter entitled "Industrial Relations Facts"; a BLS data
tape listing strikes recorded from published newspaper reports; and a Bureau of
National Affairs' data tape listing strikes from published media and other sources.
The Bureau of National Affairs' data are only available after 1970; for this reason
McConnell and Tracy began their merged strike listings in that year. A further
description of their data is provided by McConnell (1986).
" The precise definition of a strike in Current Wage Developments is unclear. It
is clear, however, that the BLS does not report local-issue strikes in CWD. The
question of whether local-issue strikes should be treated differently from more
general disputes is an important issue for further research.
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152 Card
contribute
data for co
some 20% of strikes associated with contract renegotiations are missing
from the CWD listings. The added strikes are shorter than the strikes in
CWD (27 vs. 48 days) but are more or less evenly distributed over time
and across industries. Assuming that 20% of actual strikes are randomly
missing from the CWD listing prior to 1970, the true probability of strikes
in the data set is 14.1/%.
For purposes of a longitudinal analysis, it is convenient to work with a
fixed number of contract expirations per bargaining pair. To this end, I
have extracted a balanced sample of contracts based on the six most recent
negotiations for each bargaining pair. Strike probabilities and durations
for this sample of 1,518 contracts are presented in the right-hand columns
of table 1. The pattern of strike probabilities and durations across industries
is similar between the total sample and the balanced subsample, although
strike probabilities are somewhat higher in the subsample. This reflects
the fact that the subsample contains relatively fewer contracts from the
1950s and early 1960s, when strike probabilities were relatively low. By
the same token, underreporting of strikes is less significant in the subsample
since relatively fewer of the contract expirations in the subsample occurred
before 1970 (39.7% vs. 63.2%). Assuming that 20% of strikes prior to 1970
are unreported, the true probability of strikes in the balanced sample
is 17.8%.
The simple averages in table 1 show considerable variation across industries
in both the probability and duration of strikes. Strikes are more
likely in durable than nondurable manufacturing and are most frequent
in the rubber and nonelectrical machinery industries.12 There is a weak
positive rank-order correlation across industries between strike probabilities
and the conditional duration of strikes (.21), although the correlation falls
to zero if the apparel industry is ignored. The longest strikes are in lumber
and wood products, primary metals, and fabricated metals, while the
shortest strikes are in apparel, petroleum refining, and instruments.
Some additional insight into the distribution of strike lengths is provided
by table 2, which gives the weekly settlement rates for 244 strikes drawn
from the balanced sample of contract expirations. Over 95% of these strikes
are settled in 20 weeks or less. The average weekly settlement rate during
the first 20 weeks is 13.8%. With only two exceptions, the individual weekly
12 Industry average strike probabilities from larger samples of agreements are
presented by McConnell (1986) and Gramm (1987). McConnell's data include 4,592
agreements in the manufacturing sector from the period 1970-81. Gramm's data
include 3,812 agreements from the period 1971-80. The correlation coefficients
between the industry strike probabilities in the fifth column of table 1 and those
presented by McConnell and Gramm are .91 and .73, respectively.
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Strike Activity 153
Table 2
Empirical Hazard Rate of Strike Settlement*
No. of Ongoing Fraction Settled t-Ratio for Test of
Week Strikes in Week Constant Hazardt
1 244 .127 -.50
2 213 .197 2.50
3 171 .181 1.64
4 140 .136 -.08
5 121 .165 0.87
6 101 .069 -2.00
7 94 .117 -.59
8 83 .169 .81
9 69 .159 .52
10 58 .086 -1.14
11 53 .189 1.07
12 43 .070 -1.30
13 40 .275 2.51
14 29 .069 -1.08
15 27 .111 -.41
16 24 .042 -1.37
17 23 .130 -.11
18 20 .200 .80
19 16 .125 -.15
20 14 .143 .05
* Calculated from 2
weeks there were 1
t t-ratio for the h
rate over the first
is 29.58 with a mar
settlement rat
test statistic f
ability value of
of strikes after only a few weeks is relatively small. Recent studies by
Kennan (1980, 1985) and Harrison and Stewart (1986), using much larger
sample sizes, conclude that strike settlement rates tend to decrease with
the duration of the strike. While there is no evidence of this phenomenon
in table 2, it is difficult to draw firm conclusions because of the relatively
small sample size.
The tabulation of strike probabilities by 5-year interval in table 1 shows
considerable time-series variation in aggregate and industry-specific strike
propensities. Figure 1 presents average annual strike probabilities for 1961-
79 from the balanced subsample of 1,518 contracts. Actual probabilities
and strike durations by year are recorded in table Al. The figure shows
both the probability of strikes associated with contract expirations in each
year and an adjusted probability that controls for the industry composition
of contract expirations. These adjusted probabilities represent estimated
year effects from a linear probability model that includes two-digit industry
controls. Both series show relatively low strike probabilities in the early
1960s, followed by sharply higher strike probabilities from 1965 to 1970,
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154 Card
30-
28-
26-
24-
22-
20-
18-
16-
14-
12-
10-
8
6
4-
2-
0
1960 1962 1964 1966 1968 1970 1972 1974 1976 1978
YEAR
O adjusted + Unadjusted
FIG. 1.-Strike probabilities by year
and lower but widely varying strike prob
Since the focus of this article is on the lo
activity, in the empirical analysis reported b
aggregate strike propensities with a series of
both ordinary and fixed-effect probability
varying component of strike activity is wel
step function, with steps at 1965, 1971, and 1
captures the relatively low strike probabilit
and the relatively high strike probabilities f
III. The Effects of Contract Characteristics
on Strike Incidence
In this section I analyze the effects of three characteristics of collective
bargaining agreements on the probability of strikes: the seasonal timing
13 Susan Vroman (1986) has investigated the effects of a variety of macroeconomic
variables on the probability of strikes in this data set. Her results suggest that
unemployment rates, past inflation rates, and wage and price controls all effect the
probability of strikes. She does not, however, compare the explanatory power of
her probit regressions to regressions with unrestricted year effects. The likelihood
ratio test statistic of the four-step time function against an unrestricted specification
of the year effects in a logistic regression that includes two-digit industry effects
has a probability value of 16%.
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Strike Activity 155
of contract expiration
the length of time bet
of contract characteri
the nonrandom incide
gaining pairs. The fact
contracts that expire in December, for example, does not imply that a
bargaining pair who traditionally negotiate in June could reduce the probability
of a work stoppage by scheduling their negotiations in December.
To control for unobserved heterogeneity in strike propensities across bargaining
pairs, I use three alternative estimation strategies. The first strategy
is to model heterogeneity across industries using a series of two-digit industry
effects. The second estimation strategy is a conditional logistic
regression-the direct analogue of a fixed-effects estimator for logistic
probability models. The third strategy is a first-differenced version of the
linear probability model. In all cases, the empirical analysis accounts for
random underreporting of strikes among expirations prior to 1970.
A. Seasonality of Expirations
It is widely acknowledged that there is a strong seasonal pattern in
measures of aggregate strike activity.14 Only recently, however, has it been
possible to decompose this pattern of seasonality into the seasonal component
of expirations and the seasonal component of strike probabilities.15
Evidence in Gramm (1987, table 3) based on a large sample of manufacturing
and nonmanufacturing contracts suggests that monthly strike probabilities
vary widely. Her data analysis does not address the question of
whether this seasonal variation is due to the monthly composition of contract
expirations, however, or to an intrinsic seasonal effect. Indeed, the
year-to-year variation in relative monthly strike probabilities in Gramm's
data suggests that compositional effects may be an important component
of seasonal variation in strike probabilities.16
In an effort to isolate intrinsic seasonal variation in strike probabilities,
table 3 presents estimated month effects from several models that control
for the composition of expirations. For reference, the first two columns
of the table report the fraction of expirations in each month and the associated
raw strike probabilities. Column 3 of table 3 reports estimated
14 Kennan (1986, sec. 11) provides a brief summary of the evidence on seasonality,
starting with the study by Yoder (1938).
15 Aggregate measures of strike incidence or duration include intracontract strikes.
Evidence reported by Flaherty (1983) shows that these strikes also have a seasonal
pattern.
16 For example, the rank-order correlation between monthly strike probabilities
in 2 consecutive years in Gramm's data is typically less than .25 and is in many
cases negative.
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Strike Activity 157
month effects from
for heterogeneity. In order to incorporate the assumption that 20% of
strikes associated with expirations before 1970 are unreported, I assume
that the probability of an observed strike is
pit = (1 - .2Dit)pit (1)
where pin is the predicted probability of a
the ith pair in the absence of any underre
variable for expirations prior to January
in the absence of underreporting is given
formula
logit(pi') log[pi'/(l- = xit3 (2)
where xit represents a vector of indicators for expiration month, a
a Vector of month effects with the normalization that the effect for
is zero.
The estimates in column 3 show significantly different strike prob
depending on the expiration month of the preceding contract. The
lihood-ratio test associated with the hypothesis that strike prob
are constant across months is reported in the last row of the table
highly significant.
The fourth column of table 3 introduces two-digit industry cont
a four-step function of time as additional covariates of strike activ
Comparing the estimates in the third and fourth columns of the table,
there are only small differences between the estimated month effects. These
results suggest that the monthly pattern of strike probabilities is not simply
an artifact of the industry distribution of contract expirations. In fact, the
monthly pattern of strike probabilities is very similar with and without
industry controls.
The fifth column of table 3 contains estimated month effects from a
conditional logit model of strike incidence.18 This model permits a separate
fixed effect for each bargaining pair in the data set. Specifically, the prob-
17 The main effect of the adjustment for unreported strikes is to change the
estimated year effects in the specification for pa*, the probability of strikes in the
absence of underreporting. Comparing estimated logistic regression models that
include industry effects and time-period effects with and without the correction of
underreporting prior to 1970, the year effects for time periods before 1970 are .20.25
higher in the corrected model. The industry effects are very similar between
specifications.
18 This model is described in Chamberlain (1980), who also provides references
to earlier work.
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158 Card
ability of
to be giv
logit(pW) = ai + XiA (3)
where xit represents a vector of year and month indic
a fixed pair-effect. As a consequence of the function
probability model, the pair-effects are eliminated by
lihood of the sequence of strike indicators for the it
Yi2, *.., Yi6) conditional on the total number of st
pair in the sample. Since the number of strikes is a s
the pair-effect in the logistic probability model, con
the pair-effect from the likelihood while permitting estimation of the
coefficients associated with the time-varying determinants of strike prob-
abilities."9
Unfortunately, the addition of the simple underreporting model described
by equation (1) to strike probability model (3) leads to a probability model
for observed strike outcomes that no longer satisfies the necessary conditions
for the conditional logit model. The fixed-effects specification can
be combined with an approximation to the underreporting model, however,
that leads to a workable conditional likelihood.20 I have therefore used
this approximate correction for underreporting of strikes prior to 1970 to
compute the estimates in column 5 of table 3. These estimates are less
precise than the conventional logit estimates in column 4 and indicate a
somewhat different seasonal pattern. The conditional logit estimates, in
fact, suggest that the monthly effects can be divided into just two "seasons":
a low strike probability season from December to May and a high strike
probability season from June to November. The likelihood ratio test for
the hypothesis that strike probabilities are constant from December to
May and from June to November has a marginal significance level of .38.
The estimated month effect for June-November in this simple 2-season
model is .96, with a standard error of .28. Assuming an average strike
19 Note that bargaining pairs who never strike, or who strike in every negotiation,
do not contribute to the conditional likelihood.
20 Specifically, I consider the approximate formula for the probability of an observe
strike:
eai + X,,o - yDi
pit-l + ea+xil3YDu,
where y = .256 is chosen to approximate the behavior of the true model a
sample mean strike probability. This model is clearly amenable to a condit
likelihood formulation. The approximation is also relatively precise, at leas
values of the individual effects that give rise to predicted strike probabilities b
2% and 30%.
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Strike Activity 159
probability of 15%, th
probabilities between expirations in summer and fall, on one hand, and
winter and spring, on the other.
The conditional logit estimation scheme relies very heavily on the functional
form of the logistic distribution function. As a check on the results
in column 5, consider an alternative linear-probability specification
p= = ai + Xi (4)
where, as before, ai represents a
a vector of year and month indic
from the objection that the pred
interval, it is particularly conven
noring underreporting) it implie
Ayit = AxitP + pits
where Ayit = yit - yit - 1 represe
the (t - 1)st and tth negotiation,
of differences in the covariates,
This first-differenced linear pro
easily with the underreporting m
combined model are presented in
comparable with the estimated co
the month effects and their standard errors have been multiplied by a
factor of [pF(1 - f)f1, where f represents the sample average strike probability.
AssumingP = .145, the normalizing factor in column 6 is 8.0.
The estimated month effects from the linear probability model are generally
similar to the estimates from the conditional logit model, although
the point estimates for March, May, August, and December differ somewhat
21 The combined linear-probability and underreporting model implies that the
probability of an observed strike is
pit = (1 - .2Dit)(ai + xito),
where Dit is an indicator for expirations prior to 1970. A suitable regression equation
for observed strike outcomes is
Yi Yzt - I
1 - .2D5t 1 - .2Dit1 = AxItl + nit,
where tit is a residual with expected value equal to 0. Note that tit is
heteroscedastic. The standard errors for the differenced linear prob
are therefore estimated by the White (1980) procedure.
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160 Card
between
linear probability specification are constant from December to May and
from June to November has a marginal significance level of .37 (virtually
identical to the significance level of the test on the conditional logit coefficients).
Assuming a 2-season model, the linear probability specification
implies a 15-percentage point increase in the probability of strikes between
June and November relative to expirations in December-May, with a standard
error of .05.
Both the conditional logit and first-differenced linear probability specifications
therefore indicate that strike probabilities are significantly higher
in summer and fall relative to expirations between December and May.
Since both specifications control for bargaining-pair specific heterogeneity,
these results suggest that contract negotiators can vary the likelihood of
subsequent work stoppages by varying the expiration dates of their contracts.
There is, however no evidence that the duration of strikes varies by
the expiration date of the previous contract.22 These findings raise an interesting
puzzle: why do negotiators schedule expirations in high strike
probability months? The interpretation of strikes as unproductive accidents
(Reder and Neumann 1980; Siebert and Addison 1981) implies that bargainers
should schedule negotiations when the expected costs due to work
stoppages are lowest. Assuming that marginal strike costs do not vary by
season, the results in table 3 clearly reject this interpretation. More detailed
evidence on the seasonal variation in strike costs is obviously required for
a definitive test.23
B. Reopeners and Contract Duration
Table 4 presents estimates of the effects of two additional contract characteristics
on strike probabilities: the length of time since the last negotiation
and the provision for a limited contract reopening. As is the case for the
expiration month, both of these characteristics are determined in the preceding
contract negotiation. Time since the last negotiation is simply the
duration of the preceding contract. A limited reopening is a provision of
22 The mean and median duration for strikes associated with expirations between
December and May are 45.3 and 28, respectively. The mean and median duration
for strikes associated with expirations between June and November are 45.4 and
28, respectively.
23 In an effort to check if seasonality in strike probabilities varies significantly
by region, I fit separate first-differenced linear probability models of strike incidence
to 61 bargaining pairs in southern and western states and 99 pairs in northern
states (the remaining bargaining situations are multistate). Neither subsample rejected
a 2-season model based on December-May and June-November. The estimated
increase in the probability of strikes for expiration in June-November was
13 percentage points for the northern pairs, and 23 percentage points for the southern-western
pairs, with standard errors of 8% and 9%, respectively.
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Strike Activity 161
Table 4
Effects of Reopener Status and Previous Contract Duration
on Strike Incience
Ordinary Logit
No Industry Industry Conditional First-differenced
or Year and Year Logit with Linear Probability
Effects Effects Year Effects with Year Effects
1. Reopener -1.68 -1.70 -1.43 -.69
(.73) (.92) (.76) (.28)
2. Previous contract
duration
(months) .052 .043 .043 .039
(.009) (.010) (.013) (.012)
NoTE.-Standard errors are in parentheses. Mo
See notes to table 3.
the previous contract that restric
set of contract issues, with the u
collective agreement are to remai
these characteristics affect strik
gaining parties can control the li
the question of how the parties choose among the menu of contract al-
ternatives.
The estimates in table 4 are obtained from models that exclude seasonal
effects, although as a practical matter the estimates are not much different
when seasonal effects are included since the distribution of reopening provisions
and contract lengths is more or less independent of expiration
month. The first row of the table presents the estimated coefficient of a
dummy variable for a limited reopening.25 The second row presents the
estimated coefficient of the duration (in months) of the previous contract.
In cases where new contract or a strike was reached prior to the expiration
date of the preceding contract, the duration of the previous contract is
defined as the period of time between its effective date and the date of the
next contract or strike.
The first column of the table contains the estimated effects of these two
variables with no heterogeneity controls. The estimates show that strike
24 According to Bureau of National Affairs (1986, sec. 36.2), most reopening
provisions are limited to wages, fringe benefits, and cost-of-living wage adjustments.
The courts have ruled that a reopening agreement limited to "wages" does not
preclude negotiation over "compensation" more broadly defined. See Meltzer (1977,
pp. 712-18).
25 I have counted as "reopenings" only those negotiations that are identified as
reopening in the preceding contract and whose reopening date is specified in the
preceding contract. By this definition, the data set contains 91 reopeners (6% of
contract negotiations), mostly in textile, apparel, and chemical industries.
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162 Card
probabilit
higher fo
introduce
logistic re
while the
the two r
estimator
strike pro
estimates
opening p
probabilit
are 9%-101% lower in reopening situations and about 6% higher for negotiations
following a 3-year, as compared to a 2-year, contract.27
These results suggest two conclusions. First, the commitment to limited
negotiations implied by a reopener clause actually reduces the probability
of disputes. Second, increases in contract length, while reducing the number
of opportunities for disputes, lead to a higher probability of disputes in
each negotiation. In fact, the estimates in table 4 suggest that the expected
number of disputes per period of time is approximately constant, whether
bargaining occurs at 1-, 2-, or 3-year intervals.28
The finding that expected strike losses per year are independent of contract
length yields some support for the "accident" interpretation of strikes.
On the margin, there is apparently no advantage to shortening or lengthening
contract duration in order to avoid costly work stoppages. The findings
that strike probabilities increase with contract duration and decrease
in reopener situations are also roughly consistent with the notion that
strike probabilities increase with the degree of uncertainty associated with
26 The probabilities of strikes among reopenings is 2%. Strike probabilities by
the duration of the preceding contract are as follows: less than 18 months-7.1 1%;
18-29 months-9.93%; 30-41 months-20.91%; and 42 months and longer-
29.73%.
27 I have also estimated the effect of previous contract length by grouping contracts
into 1-year (less than 18 months), 2-year (18-29 months), 3-year (30-41 months),
and longer (over 42 months) contracts. Relative to a 1-year contract, the estimated
effects and associated standard errors from a differenced linear probability model
are 2-year contract: -.01 (.03); 3-year contract: .06 (.03); 4-year or longer contract:
.26 (.09).
28 For example, the average probability of strikes among 2-year (i.e., 19-32 month)
contracts is approximately 10%. The expected number of disputes per year on a
2-year bargaining cycle is therefore .05. The estimates in table 4 suggest that the
probabilities of strikes in 1- and 3-year bargaining cycles are 4% and 16%, respectively.
These probabilities imply .04 and .053 expected disputes per year, bargaining
annually and triennially. Mean strike duration following a 1-year contract is slightly
shorter than mean strike duration following 2- or 3-year contracts: 32.5 vs. 45.6
and 46.8 days, respectively.
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Strike Activity 163
the bargainers' inform
gotiations, on the one
trade-offs between al
tiations over wages, o
game. This characteri
information are less l
same token, it may b
about each other deca
contract negotiations.
strike probabilities is
sociated with less fre
IV. The Longitudinal Structure of Strike Activity
A. Models of Strike Incidence
This section presents and analyzes the pattern of strike incidence over
time within bargaining pairs. Using information on six contract negotiations
for each bargaining pair, I first test the hypothesis that strike probabilities
are related to previous strike incidence. Contrary to the findings
of Mauro (1982) and Schnell and Gramm (1987), there is no evidence of
either positive or negative state dependence in strike incidence, controlling
for heterogeneity in underlying strike propensities. The absence of state
dependence in strike incidence, however, masks an important dependence
of strike probabilities on the duration of lagged strike outcomes. Specifically,
I find that strike probabilities are significantly increased by a relatively
short strike in the preceding negotiation and significantly reduced by a
relatively long strike in the preceding negotiation.
Some simple evidence on the extent of state dependence in strike incidence
is presented in table 5. This table presents a frequency distribution
of the alternative strike histories represented in the sample of six negotiations
for each of the 253 bargaining pairs, together with the predicted
frequencies generated by two simple models of strike incidence. The first
column of the table describes the relevant strike history: the strike history
"000000," for example, represents the occurrence of no strikes in six negotiations.
The next column gives the number of bargaining pairs with
each history. For simplicity, I have not displayed the actual distributions
of bargaining pairs among histories with three or four strikes in six negotiations.
Since strikes are relatively rare events, the number of pairs in
the individual cells with more than three strikes is typically one or zero.
There are no pairs with five strikes in six negotiations, and only one pair
(the Autoworkers and Allis Chalmers) with six strikes.
The third and fourth columns of table 5 present the predicted numbers
of bargaining pairs with each strike history (or group of histories) from
two alternative models: an ordinary logistic regression model of strike
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Table 5
Actual and Predicted Strike Histories: Last Six Contracts for Each Pair
Predicted No. (absolute
t-statistics)*
Ordinary
Actual Logit with
No. Industry Conditional
Strike History of Pairs Effects Logit
No strikes:
1. 000000 118 105.8 (3.07) 118 (...)
One strike:
2. 100000 12 10.7 (.43) 8.1 (1.49)
3. 010000 8 13.3 (1.56) 9.9 (.66)
4. 001000 17 17.3 (.09) 15.6 (.42)
5. 000100 9 13.9 (1.41) 10.8 (.59)
6. 000010 9 12.0 (.95) 10.20 (.41)
7. 000001 11 13.4 (.81) 11.49 (.41)
8. Total of 6 cases 66 80.7 (2.20) 66.0 (...)
Two strikes:
9. 110000 1 2.17 (.82) 1.6 (.49)
10. 011000 5 3.6 (.80) 3.1 (1.11)
11. 001100 3 4.2 (.61) 4.3 (.66)
12. 000110 2 2.9 (.53) 2.6 (.39)
13. 000011 8 2.7 (3.34) 2.4 (3.69)
14. 101000 2 2.8 (.48) 2.2 (.11)
15. 010100 1 2.8 (1.08) 2.3 (.88)
16. 001010 2 3.5 (.84) 3.4 (.81)
17. 000101 2 3.2 (.71) 3.0 (.60)
18. 100100 3 2.2 (.52) 1.7 (1.04)
19. 010010 1 2.5 (.95) 2.0 (.75)
20. 001001 4 4.0 (.02) 3.9 (.03)
21. 100010 0 2.0 (1.43) 1.5 (1.23)
22. 010001 2 2.8 (.47) 2.3 (.21)
23. 100001 2 2.2 (.15) 1.6 (.28)
24. Total of 15 cases 38 43.4 (1.06) 38 (-..)
Three strikes:
25. Total of 20 cases 24 17.1 (2.06) 24 (...)
Four strikes:
26. Total of 15 cases 6 5.0 (.49) 6 (...)
Five strikes:
27. Total of 6 cases 0 .9 (1.05) 0 (-..)
Six strikes:
28. 111111 1 .1 (3.21) 1 ( )
29. Goodness of fit for table
uncorrected for parameter
estimation (probability value)t 74.47 (.15) 49.35 (.75)
NoTE.-See Section IV A of text for explanation of strike histories.
* Predicted number represents the expected number of pairs w
estimated parameters. The number in parentheses represents the
test that the predicted and actual number of pairs are equal. t-St
estimation.
t Goodness-of-fit statistic for the overall table (64 elements) treat
constants.
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Strike Activity 165
incidence with industr
year effects.29 Both o
no state dependence in strike incidence. A comparison of the predicted
frequencies under these simple models to the actual frequencies of the
alternative strike histories therefore provides a simple test for the presence
of state dependence.
A comparison of the actual cell frequencies to the predicted frequencies
generated by the ordinary logit model with year and industry effects suggests
that the model does a relatively good job of predicting the various
alternatives. The absolute t-statistics for the difference between the predicted
and actual cell frequencies are presented in parentheses beside each predicted
cell frequency, and an overall goodness-of-fit statistic is presented
in the last row of the table.30 Apart from the cells with no strikes and six
strikes, and the "000011" cell, the individual t-statistics are relatively small.
There is very little evidence that the model systematically over- or underpredicts
cells associated with significant state-dependence effects. For example,
negative state dependence (as reported by Mauro [1982] and Schnell
and Gramm [1987]) would show up in this table as significant overprediction
of cells with two consecutive strikes. The results in rows 9-13, by
comparison, show a tendency to underpredict these cells, at least among
histories with two strikes in six negotiations.
A similar conclusion emerges from an examination of the goodness of
fit of the conditional logit model. By construction, the conditional logit
model fits the number of observations with each strike total exactly. Looking
at the individual strike histories, the only significant outlier under the
conditional logit specification is the "000011" history; otherwise, the
goodness of fit to the individual cells and the overall table are acceptable
by conventional standards.31 Again, the fit of the model does not indicate
any significant state dependence in strike incidence.
A close inspection of the individual strike histories, however, suggests
that the absence of state dependence in strike incidence is the product of
two offsetting effects: a tendency for increased strike probabilities following
29 The models incorporate the corrections for underreporting of strikes prior to
1970 discussed in the preceding section.
30 The t-statistics and the overall goodness-of-fit statistic are not corrected for
the estimation of the industry and year effects in the logit model. A suitable correction
is suggested by Heckman (1984) (see also D. Moore [1977]). The impact of
this correction on the individual t-statistics in column 3 of table 5 is trivial. The
overall goodness-of-fit statistic, however, increases to 83.55 (with a probability
value of .04) when this correction is applied. The derivation of the corrected and
uncorrected goodness-of-fit statistics is described in an earlier version of this article
(Card 1986).
31 The eight bargaining pairs with the "000011" strike history are apparently
unrelated (i.e., are drawn from different industries and different time periods).
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166 Card
Table 6
Probability of Strikes Conditional on Preceding Strike Outcome
Previous Strike Outcome
1-7 8-14 15-28 29-42 43 Day
No Day Day Day Day or Longer
Strike Strike Strike Strike Strike Strike
1. Probability of strike 13.9 40.0 47.5 24.4 18.5 19.0
2. Mean strike duration 47.3 41.2 37.0 47.5 33.4 39.8
3. Number of contracts 1,291 35 40 41 27 84
(% of sample) (85.05) (2.31) (2.64) (2.70) (1.78) (5.53)
NOTE.-Sample cross-tabulation of strike outcomes by previous
relatively short disputes and a tendency for r
following relatively long disputes. Some simple evidence is presented in
table 6, which describes the probability and duration of strikes conditional
on the length of the preceding strike. The first row of the table reveals a
sharp difference between the effects of shorter strikes and longer strikes
on the probability of subsequent disputes. In contrast to this finding, a
simple model of state dependence implies that the probability of a subsequent
dispute depends only on the occurrence of a strike and not on its
length. Despite the variation in strike probabilities by lagged strike length,
the mean strike durations in the second row of table 6 show no significant
variation by lagged strike length.
In order to investigate the apparent dependence of strike probabilities
on lagged strike outcomes, a statistical model is required that permits both
unobserved heterogeneity in strike propensities and potential state dependence
in consecutive strike outcomes. A convenient model is a randomeffects
logit specification
logit(plzt) = ai + Xit, + 2: 8kylt- 1 X(5)
k
where pe represents the probability of a strike at the tth negotiation for
the ith bargaining pair in the absence of underreporting, xit represents a
vector of time effects, yU - is an indicator for a strike in the kth duration
class in the preceding negotiation, ak represents a vector of state dependence
effects, and ai represents a randomly distributed individual effect. A simple
model for the distribution of the random effects is a point-mass distribution
with a small number of mass points.32 The mass points and associated
probabilities, together with the parameters {P, 61, 62, ... } can be estimated
32 A similar model was proposed by Card and Sullivan (1987) as a description
of individual employment probabilities.
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Strike Activity 167
jointly by conventi
sample strike outco
Estimation results
table 7.34 For refer
of the model with
of-fit statistic repor
effects model with
relatively good fit
conventional logit m
model has 14 fewer
table of strike hist
bution of random e
likelihood (from goodness
of fit to t
The second column
in the log-odds of a
This specification c
As the results in ta
pendence. The point
consistent with the
slightly underpredi
The models in colum
on future strike p
dispute. As suggeste
guishes between 1-1
on the other, is ade
two weeks duratio
3 Ignoring underrepo
strike indicators (y1,
negotiation, is
z {fJ a (tkYt[1 lput (a4)] Y}k,
k=1 t
where pa (a) is the probability of a dispute c
a2, ..., a1 are the mass points of the distri
associated probability weights. In principle,
distribution of the presample strike outcome
of the parameters-see Heckman (1981). In ot
Canadian contracts (Card 1987), however, I have experimented with alternative
methods of handling the initial conditions and found relatively small differences
between them.
3 The likelihood of observed strike outcomes is corrected for 20% random underreporting
of strikes prior to 1970. No correction is made for the effect of underreporting
on the distribution of the lagged strike outcome indicators.
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0
ON ten O ON 0en 0
*4, vI(/) (Ncr~(NI Nre CA 00E
E ~ ~~~~~~C en CD ".1 en '.to .I r, "n
M-~ 0 ,,0 .o c,
s rO e1st (NJ - .
$ ; E~~~~~~~~~~~'_
.H NeN 0000 o sDO G 0
0~~~~~~~~~~~~~0
-0 U
C C d
o; o o
' X ~
ZH.
0 ~ ~ ~ ~ ~~~~~~~0
o~~~~~~~~~~~~~~
'.4 I~~~~~~~~~~~. I
2 o ~ ~ 4
0 00~~~~~~~
o ~~~~~~~~~~~~~o0 0
0 I~~~~~~~~~0
0 >0
U U .- 0~~~~~~~4 r;1
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Strike Activity 169
probability of a subsequent dispute, longer strikes actually reduce the
probability of a subsequent dispute. As a check that these results are not
biased by imperfect heterogeneity controls, the model in column 6 of table
7 introduces a set of industry effects. In order to reduce the number of
parameters in the model, two-digit industries were grouped according to
their estimated effects in a conventional logit model of strike incidence.35
The results with the grouped industry variables further strengthen the
conclusion that lagged strike outcomes affect current strike probabilities,
with shorter strikes increasing the likelihood of future disputes and longer
strikes reducing the likelihood of future disputes.
B. Models of Strike Incidence and Duration
In view of the impact of strike duration on subsequent strike outcomes,
this section presents a more detailed analysis of the duration and incidence
of strikes over time within bargaining pairs. The analysis is based on a
model that describes strike outcomes in terms of only three possibilities:
no strike; a strike for less than 2 weeks; and a strike for longer than 2
weeks. While this simple three-outcome model of strike activity is obviously
incomplete, the results of the last section suggest that the distinction between
short and long strikes is very useful in longitudinal models of strike
incidence. The three-outcome case is therefore a natural starting point
for studying the joint determination of strike incidence and duration
over time.
In order to describe the distribution of bargaining outcomes between
no strikes, short strikes, and long strikes, consider a pair of indicator variables
yit and zit, where Yit = 1 if a strike occurs in the tth negotiation for
the ith bargaining pair, and 0 otherwise, and zit = 1 if the strike lasts for
longer than two weeks, and 0 otherwise. Let pt and qt represent the
probability of a strike and the conditional probability of a long strike,
respectively, ignoring underreporting of strikes. Suppose that
logit(pW) = ai + Xitp + 8i(yit-i - zit - 1) + 82Zit- 1, (6a)
logit(q t) = yi + xit0 + pi(yit - Zit- ) + P2Zit-5 1 (6b)
where ai and yi are individual effects, xit is a vector of control variates (for
example, year and/or industry effects), and P and 0 are conformable vectors
of parameters. Finally, assume that yit and zit are independent, conditional
The four groups are a low strike-probability group (apparel, lumber and wood),
a moderate strike-probability group (primary metals, fabricated metals, electrical
machinery, transportation equipment), a high strike-probability group (rubber,
nonelectrical machinery), and a base group (all other industries).
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170 Card
on ci, yi,
of a shor
in negot
probabil
Given v
(6a) and
of strike outcomes over time. The two equations describe a first-order
Markov model of transitions between three alternative states: no strikes;
strikes of less than 14 days; and strikes of more than 14 days. Following
the approach in the previous section, I treat the joint distribution of ai and
Yi as a discrete distribution with a small number (two or three) of mass
points. I also condition the estimation and inference on the observed strike
outcomes for each bargaining pair in the immediate presample period.
Table 8 presents estimation results for the trinomial outcome model of
strikes implied by equations (6a) and (6b). The first column of the table
presents estimates based on a two mass-point bivariate distribution of individual
effects. Apart from individual effects, the only covariates of strike
activity are a step-function of time. For simplicity, the time effects in equations
(6a) (the incidence equation) and (6b) (the conditional duration equation)
are restricted to be proportional: 0 = hi. The estimated proportionality
constant 4 is reported in the fifth row of the table.
The estimated effects of previous work stoppages on the probability of
a strike are presented in the first two rows of the table. The point estimates
are very similar to the estimates in table 7, with about the same level of
precision. The estimated effects of short and long strikes in the preceding
contract on the conditional probability of a long strike in the current
negotiation are reported in the third and fourth rows of table 8. The point
estimates suggest that a long strike is more likely if there was a long strike
in the previous contract and less likely if the previous contract was settled
peacefully, although the estimates are relatively imprecise.
The second column of the table presents estimation results for a three
mass-point model of the distribution of individual effects. Overall, the
results are very similar to the two mass-point specification, and the likelihood
of the sample is not significantly improved.
The hypothesis that lagged strikes do not affect the probability of short
or long strikes is addressed in the third column of the table. Comparing
the likelihood and parameter estimates to those in the second column,
there is very little evidence against the hypothesis. While lagged strike
36 The assumption of independence between yit and zit is not particularly restrictive
if the distribution of the individual effects ai and yi is flexible.
37 In the event of a short strike in (t - 1), yit- I = 1 and zit I = 0, so logit(p*) is
increased by 61. In the event of a long strike in t - 1, yit - and zit = 1, s5
logit(p*) is increased by 62.
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Strike Activity 171
Table 8
Trinomial Outcome Model of Strike Probability and Duration
Random Effects Logit Model*
2 Mass
2 Mass 3 Mass 3 Mass Points and
Points Points Points 4 Industry
(1) (2) (3) Effectst
Effect of previous strike on
strike probability:
1. 0-14-day strike 1.08 1.04 1.11 1.01
(.36) (.34) (.35) (.35)
2. 15-day or longer
strike -.44 -.51 -.49 -.69
(.29) (.29) (.29) (.30)
Effect of previous strike on
probability of long strike:
3. 0-14-day strike .13 .17 .00 .00
(.46) (.48) (.) ( )
4. 15-day or longer
strike .44 .37 .00 .00
(.58) (.57) ( G
5. Relative time-effect on
probability of long strike 1.49 1.53 1.60 1.45
(.58) (.57) (.61) (.53)
6. Log likelihood -771.34 -771.03 -771.34 -749.92
7. Goodness of fit for
strike outcome table
(probability value)t 56.17 55.68 55.21 55.85
(.72) (.73) (.75) (.73)
NOTE.-Standard errors are in parentheses.
* All models include a four-step time function
strike. The coefficient in row 5 gives the relative
longer than 14 days.
t Model includes four grouped industry effec
equations. The industry effects are restricted to
relative effect of the industry variables in the d
t Goodness of fit to 64-element table of strik
estimation of the parameters in the model.
activity apparently influences the
probability of continuing a strike
previous strike outcomes. Some ca
preting these results since the nu
and strike duration is apparently
is probably required to fully analy
and particularly the effects of lag
3 For example, the R2 in a regression
two-digit industry effects and time
such an equation are jointly significa
3 The number of consecutive strikes i
among 42 bargaining pairs).
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172 Card
The four
specificat
in equati
dustry ef
different
time eff
which pl
effect on
increases
preceding negotiation. Overall, the estimates for the incidence equation
imply that strike probabilities increase 10-12 percentage points following
a relatively short strike and decrease 6-9 percentage points following a
longer work stoppage. The estimates for the duration equation, while relatively
imprecise, indicate that previous strike outcomes do not affect the
relative likelihood of short or long disputes.41
These findings are consistent with a very simple dynamic model in which
the probability of strikes depends positively on a state variable whose value
is unaffected by short strikes but is significantly reduced by the occurrence
of a long dispute.42 In such a model, the occurrence of a short strike signals
a high level of the state variable and an increased probability of further
strikes. The occurrence of a long strike, in contrast, reduces the probability
of further strikes by reducing the level of the state variable. There is a
variety of interpretations of the state variable in such a model: as an index
of union members' wealth, for example; or, alternatively, as a general index
of worker discontent. In the absence of more complete information, however,
it is impossible to distinguish between these various interpretations.
The pattern of state dependence in strike probabilities also bears an
40 This is consistent with results from a simple cross-sectional logit model of
short and long strike durations. In such a model, none of the industry effects is
individually significant, and the probability value of the test for the hypothesis that
the industry effects are jointly equal to zero is .12.
41 Some additional evidence on the weak relation between lagged strike outcomes
and strike durations is provided by the pattern of average strike durations by the
number of strikes in six negotiations. These average durations are 52 days for one
strike; 40 days for two strikes; 45 days for three strikes; 56 days for four strikes;
and 16 days for six strikes.
42 Suppose, e.g., that the occurrence of a strike is governed by a latent variable
Yt = Ywt + ut, where wt represents the state variable and ut represents an error
term. Suppose further that wt follows a first-order process wt - w - C - c + vt,
where ct measures the effect of a dispute on the state variable and vt is another
error term. Finally, suppose that costs are measured by strike length and that strike
duration is a random variable equal to 1 with probability q and k (O < k < 1) with
probability 1 - q. Under suitable assumptions, this model generates a steady-state
transition matrix in which lagged short strikes increase the probability of future
strikes and lagged long strikes reduce the probability of future strikes.
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Strike Activity 173
interesting relation to the literature on judging winners and losers of
strikes.43 Studies from a number of different countries and time periods
have concluded that unions are more likely to win short strikes than long
ones.44 If the impression of union victory is related to the union's willingness
to engage in subsequent work stoppages, then this pattern of wins and
losses by strike duration is consistent with the pattern of state dependence
observed in tables 7 and 8.
V. Conclusions
This article has presented evidence on two aspects of strike activity
associated with the renegotiation of union contracts: the effects of endogenously
determined contract characteristics on the probability of disputes
and the effects of lagged strike outcomes on future strike incidence and
duration. Although the evidence is based on a relatively small sample of
bargaining pairs drawn mainly from the manufacturing sector, the findings
suggest a number of conclusions and avenues for further research.
First, strike probabilities are significantly affected by contract characteristics
determined in earlier negotiations. Strikes are more likely following
a longer contract than a shorter one and are less likely in limited reopening
situations. Strike probabilities are also affected by the expiration month
of the preceding contract, with expirations in summer and fall leading to
an increased likelihood of disputes. The effects of contract duration and
reopening provisions are potentially consistent with the hypothesis that
strike probabilities increase with increases in the bargainers' uncertainty
about each other. Uncertainty may be expected to increase with the length
of time between negotiations and decrease when bargaining is restricted
to a smaller number of issues. The effect of the monthly timing of negotiations
is less easily explained. Judging by the duration of disputes, marginal
strike costs are not much different in summer and fall than in winter and
spring. A simple model of negotiator behavior based on the hypothesis
that the parties try to minimize expected losses due to work stoppages
cannot readily explain the predominance of scheduled expirations in high
strike probability months.
Second, strike probabilities are significantly affected by preceding strike
outcomes. Relative to strike probabilities after a peaceful settlement of the
most recent contract negotiation, strike probabilities are 10 percentage
points higher if the contract was settled after 1-14 day strike and 5-7
percentage points lower if the contract was settled after a longer work
43 This literature is reviewed by Kennan (1986, pp. 1113-14).
44 For example, H. Moore (1911, p. 119) presents contingency tables of the union
success rate against strike duration for disputes in Germany (from 1899 to 1905)
and France (from 1890 to 1905). Both tables show declining union success rates
with the length of the strike.
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174 Card
stoppage. The effects of previous strike outcomes on subsequent strike
durations are less precisely estimated and are not significantly different
between negotiations that ended peacefully and those that ended in shorter
or longer strikes.
This pattern of state dependence is not consistent with the simple model
of learning proposed by Schnell and Gramm (1987).45 Rather, it suggests
that any dynamic model of strike propensities must carefully distinguish
between the effects of relatively short strikes, on one hand, and longer
strikes, on the other. It also suggests that one should distinguish between
disputes of various lengths in investigating the effects of strikes on other
aspects of the collective bargaining agreement, including wage outcomes.
Appendix
Table Al
Strike Characteristics by Year: Sample of Six Contracts for Each Pair
Strike Probability (%)
Adjustd for Average
Adjusted for Strike Strikes Longer
No. of Industry Duration than 2 Weeks
Year Contracts Unadjusted Composition* Days (%)
1960 and
earlier 10 30.0 23.2 52.7 100.0
1961 26 15.4 6.8 11.0 25.0
1962 42 7.1 2.6 21.0 33.3
1963 40 2.5 .9 35.0 100.0
1964 71 11.3 7.6 20.1 50.0
1965 86 18.6 17.0 20.5 43.8
1966 65 13.9 15.9 23.0 55.5
1967 92 26.1 24.5 79.3 75.0
1968 92 25.0 23.7 47.0 86.9
1969 79 17.7 19.3 38.4 78.7
1970 92 23.9 23.6 64.1 86.4
1971 111 12.6 11.9 38.9 71.4
1972 68 11.8 14.9 23.6 25.0
1973 104 13.5 14.0 26.6 57.1
1974 135 18.5 19.3 31.7 64.0
1975 81 8.6 11.9 68.4 57.1
1976 95 17.9 18.6 52.7 76.5
1977 126 15.1 15.3 63.2 100.0
1978 66 16.7 19.8 50.0 72.0
1979 37 5.4 8.3 57.5 50.0
* Estimated year effects from
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