Running head ETHICAL CONTRIBUTIONS 1 (Including a Runni.docx
Is there a secular trend in the public opinion of unions in Canada over time
1. UNIVERSITY OF WATERLOO
Department of Economics
Have Canadians Become More Anti-Union? An
Analysis of Public Opinion Poll Data Spanning
Three Decades.
Mark Vanspall
20278874
Econ 472-Senior Honours Essay
Mikal Skuterud
Dec 14, 2012
2. Abstract
This paper attempts to identify whether or not there is a secular trend in the public opinion
of unions in Canada. Determining whether or not there is a secular trend in the public opinion of
unions has important implications for both unions and governments as it could facilitate better
decision making. In the case of governments, public opinions could be assessed to estimate the
popularity and support of strike-breaking or anti-union legislation, while unions could assess
public opinion to try and determine the probability of success of strikes and other strategic
negotiation tactics.
Looking at public opinion poll data from the years 1976 – 2008 there is a clear increasing
trend in the public opinions of unions. In this paper OLS regression methods are used to attempt
to identify the determinants of the public’s decision making process of whether or not to support
unions. Determinants such as: age, geography, education, inflation rates, media coverage, union
density, strike activity and the gini coefficient are examined.
No identifiable secular trend emerges in the public opinion of unions over time; however,
several key variables have predictive power that reinforces a secular time trend in opinions; which
indicates that there could, in reality, be an increasing secular trend in public opinion from 1976-
2008. Further, inflation is identified as the biggest determinant of trends seen in this area.
3. 1
Have Canadians Become More Anti-Union? An Analysis of
Public Opinion Poll Data Spanning Three Decades.
1 Introduction
There are many reasons one may be interested in the public opinion of unions. For a
perspective union, formation and effectiveness can both be related to public opinion. Unions
require mandatory dues and as such must have a positive opinion within their membership to
form and continue operations. Public opinion of unions can be related to the success of general
bargaining and labour negotiations as a hostile climate can hurt solidarity and hamper the ability
of a union to achieve its goals (Bok and Dunlop 1970). Union density is falling over time and
union leaders are looking to maintain power and knowing public opinion trends could enable
more effective policy and growth plans (Poole 1981). Unions may need to develop new ways of
operating to be successful if the climate in which they operate is changing (Lewenza 2012).
Collective bargaining can be a drawn out process and involve the threat or use of strikes, and
public opinion could clearly be a deciding factor. The battle for public opinion can be easily seen
in the current NHL lockout as it is clearly important for both sides. In the 2004 – 2005 lockout
public opinion was identifiably skewed to the owner’s position and this helped pressure the
players into massive concessions (CBC 2012).
On the flip side, legislators and executives may take cues from public perceptions in how
they approach general bargaining and strikes. In Canadian legislation, certain industries have
been declared essential services, and can be denied the right to strike and are instead offered
binding interest arbitration (Treasury Board of Canada Secretariat). Given the political import of
4. 2
these decisions it is not unreasonable to expect that public opinions may dictate which services
are declared essential. The TTC strike of 2011 is a prime example of this. In many communities
public transportation while important for many people would not be considered essential. In
Toronto, where a much larger percentage of the population uses public transportation, Mayor
Ford had an easy time pushing for the essential designation and the Toronto Transit Commission
Labour Dispute Resolution Act was passed doing just that. From a policy standpoint many
government and public workers are unionized and public opinion is absolutely necessary for
leaders deciding on wages, in addition to decisions restricting the right to strike of certain
workers. Recent laws passed in Michigan limiting unions, in particular mandatory membership
and dues, have sparked protests and anger that also illustrates the clear link between legislative
decisions about unions and public perception (San Francisco Chronicle). Understanding
Canadian opinions about these issues and unions as a whole can help Canadian legislators if they
decide to enact similar measures, as Ontario Premier hopeful Tim Hudak promises to do if
elected (Globe and Mail).
2 Literature Review
Despite the obvious benefits of assessing the public opinion trends, very few studies
addressing unions are longitudinal in nature (Klandermans 1986). Previous research has
examined the trend of British public opinion over time, specifically between 1971 and 1981
using Gallup poll responses, and found they were generally stable (Martin and Little 1986).
Further research into a positive growth in public opinion in the Britain beyond 1979 found that
the tendency was due to the reduction of inflation and the volume of strikes (Bain and Edwards
1988). Strikes can be disruptive, and affect the lives of non-union members and possibly could
5. 3
be violent, providing a militant view of unions to independent observers. A study on declining
union density within the United States found that declining union density was highly correlated
with the decline of public opinion of unions (Lipset 1986). This could be argued either way
though as it could be that as union density falls there is less awareness of unions, or exposure to
union advertising, that leads to a decrease in public opinion, or that decreasing public opinion
causes a fall in union density.
With respect to the Canadian studies Riddell conducted a cross sectional comparison of
the years 1950-58 and 1976-82, again using the Gallup poll responses, and found that Canadian
public opinions are becoming less favourable (Riddell 1986). This poses the question of whether
this trend continues and whether it is time trend or reflective of different economic conditions
between the 50’s and late 70’s. Public opinions of unions do appear to be sensitive to economic
and socio-political changes (Johnston 1986). Lowe and Krahn conducted a cross-secional study
on Winnipeg and Edmonton for the years 1987 and 1981 and found that a negative view of
unions, specifically that they are too powerful, was not increasing over time. However, they did
suggest that the key causal agent for increasing support in Calgary as opposed to Winnipeg was
the result of poor economic performance and high unemployment. They also posited that
community studies could be of greater benefit than poll data for interpolating trends (Lowe and
Krahn 1989). While this paper is interested in Canadian opinions, it will be beneficial to look
into provincial data when possible to try and capture this sentiment.
Another purported determinant of the public opinion of unions is media coverage of
unions. This could be related to the level of strike activity as media coverage of strikes is biased
towards strike reporting (Schmidt 1993). It could be that this bias tends to negatively affect
public attitudes towards unions over time (Schmidt 1993). It may also be that media is more of a
6. 4
moderating influence and does not create this negative view (Duffy 1981). It is clear from
previous research examining the factors of public opinion in general and over time that there are
many contradicting conclusions depending on the country that is studied, the sources used, as
well as the timeframe observed. This may be because there are valid reasons to form an opinion
either way depending on the specific outcome being looked at. In the case of conflicting effects
of inflation it could be argued unions are a bad thing as they drive up the price level and cause
inflation, or that unions are good thing for workers as they enable quicker raise adjustments in
the case of rising price levels (Lowe and Krahn 1989). Another area with well-established
conflicting opinions is the social outcomes that could result from unions. People may view
unions as a tool to raise the standards of living of the lower ends of society, but at the end of the
day it may be that governments are a more effective means for addressing job concerns
(Johnston 1986).
3 Methodology
3.1 Initial Data
This paper will use survey responses to the question: “How much confidence do you have
in unions?” from the Gallup polls and the Canadian Election Survey to attempt to assess whether
there is a secular trend in the opinion of unions over time. When looking at an individual’s
support of unions, it may be important to note that an individual’s opinion of unions may vary
based on different aspects of the union activity (Furnham 1984). To account for this, several
macroeconomic variables, that may be viewed as outcomes of unions can also be examined. For
the timeframe of 1976 – 1989 the Gallup poll asked respondents “Do you think that labour
unions are a good thing or bad thing for Canada?” For the purpose of analysis only respondents
7. 5
who gave a definitive response have been included. For the period of 1991-2000 the Gallup poll
asked the question “Would you tell me how much confidence you, yourself, have in labour
unions – a great deal, quite a lot, some or very little. For the purposes of analysis a binary
variable, labeled supunion, was created with a value of 1, indicating support of unions, if the
respondent answered “a great deal” or “quite a lot”, and 0 otherwise. The trend in public opinion
based off this poll is therefore just identifying those who are decisive in their support for unions,
which may also indicate they believe strongly in most or all aspects of union behaviour. For the
time frame of 1993-2008 the mail back survey of the Canadian Election Study asked respondents
“How much confidence do you have in unions? – A great deal, quite a lot, not very much, or
none at all.” Again the dummy variable, supunion, was coded 1, indicating support, for
respondents who replied “a great deal” or “quite a lot”, and 0 otherwise. Because of the
difference in questions a variable, sample, is also included in all analysis to account for question
bias.
When regressing the dummy variable, supunion, on the intercept we can see an
interesting result. Sample1 is a dummy variable for the Gallup poll responses from 1976- 89
asking whether unions are good or bad for Canada. Sample2 is a dummy variable for the
responses to the Gallup poll from 91-2000, while Sample3 is a dummy variable for the responses
to the Canadian Election Study’s mail back survey. When discounting the level effects that are
caused by the form and coding of the question a clear trend can be seen of increasing support of
unions over time. This is surprising given that falling union density rate over time would be
expected to either be a cause or consequence of less favourable attitudes towards unions. This
leads to the question of whether a decrease in union density may in fact have the opposite effect.
It is also important to note that the observations are distributed roughly around .5. This supports
8. 6
the use of ordinary least squares linear regression as opposed to the maximum likelihood
regression model. All analysis in this paper is done using the OLS regressor.
By controlling for the variable “sample” in the regression model:
supunion = β 0 + β 1t + β2sample1 + β3 sample2 + ε
where sample1 and sample2 are dummy variables and t is a time index in which 1976 is 1.
we can identify the effect of time independent of the level effects caused by the question
differences. We can interpret β 2 and β3 as these level effects. The results from this regression are:
Table 1
Regression Results of Supunion on Time and Sample
y = 0.0154x - 29.935
R² = 0.5381
y = 0.0081x - 15.875
R² = 0.5089
y = 0.0034x - 6.4489
R² = 0.5373
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1970 1980 1990 2000 2010
Sample 1
sample 2
sample 3
Supunio
Supportof UnionsOverTime
Year
9. 7
Variable b St. Err. t
t
sample1
sample2
constant
N= 23292
R2= 0.1082
.0075855
.428482
-.0607189
.1241728
.0007236
.0153119
.0074989
.0185234
10.48
27.98
-8.10
6.70
*all R2 reported= adjusted R2
From this regression we can see a large time trend of .76 percentage point increase in the
probability of support for unions per year. This trend is also significant, meaning we can reject
the null hypothesis that the effect of time is zero at the 5% significance level, which is observed
in the high t statistic. However it could be argued that the time trend is in fact not linear. To test
this hypothesis we can estimate the models:
supunion = β 0 + β 1t + β2t2 + β3 sample1 + β4sample2 + ε (quadratic)
supunion = β 0 + β 1t + β2t2 + β3 t3+ β4sample1 + β5sample2 + ε (cubic)
supunion = β 0 + β 1t + β2t2 + β3 t3+ β4t4+ β5sample1 + β6 + ε (quartic)
Looking at the graph comparing the resulting time trends from these models:
10. 8
For regression results refer to Table 1 in appendix.
We can see that over the sample period 1976-2008 there is some variation between the
linear model as compared to the quadratic, cubic and quartic models. The associated R2 for these
models are: Quadratic = .1095, Cubic = .1099, Quartic = .1102. This variation is not too drastic,
and doesn’t account for much of the variation seen in the data and for the analytical purposes of
this paper, the linear model will be used.
3.2 Personal Attributes
Now that a significant time trend has been identified, the question becomes whether it is
well defined or if there is a significant omitted variable bias. Given the variable of interest is
time; it definitely could expected that elements, not yet introduced into the model, may be
correlated with the support of unions as well as with t. To truly identify if there is a unique time
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
1970 1980 1990 2000 2010
linear
quadratic
cubic
quartic
Regression of SupuniononTime
Year
11. 9
trend in the support of unions, the elements that affect people’s opinions of unions must also be
introduced into the model.
Age may be a determinant of whether a person supports a union or not. Young people,
under the age of 25 are much less likely to be members of unions (Bryson et al. 2005). As people
age they gain life experiences and knowledge that will affect their opinions on certain issues.
They may: become members of unions, join a non-unionized employer, become upper
management or know people who have had interactions with unions. These life experiences may
make an individual more supportive of unions or more cynical of unions as they age. Again it is
not unreasonable to expect that the relationship between age and the support of unions is non-
linear. People have very different needs as they age, a person working in their prime could have
a very different opinion than a retired person. To exam this relationship the following models
were regressed:
supunion = β 0 + β 1age + β 2sample1 + β3 sample2 + ε
supunion = β 0 + β 1age + β 2 age2 + β3 sample1 + β4sample2 + ε
supunion = β 0 + β 1age + β 2age2 + β3 age3+ β4sample1 + β5sample2 + ε
supunion = β 0 + β 1age + β 2age2 + β3 age3+ β4age4+ β5sample1 + β6 Sample2 + ε
Looking at the graph of the resulting age trends:
12. 10
For the regression results see Table 2 in appendix.
It is important to note that the age range of interest in this graph is age <85 as there are
very few instances of respondents over this age. Looking at the graph there is some variation
between the models but they are fairly close, especially over the prime age of individuals. The
R2 for the linear, quadratic, cubic, and quartic models are: .1095, .1109, .1118 and .1134
respectively. Therefore, in the final model only the linear age term will be included. The linear
age regression coefficient is -.0022 with a t statistic of -12.01 which allows us to reject the null
hypothesis that the effect of age on supunion is zero. This indicates that as people age they tend
to grow more cynical of unions due to life experience or changing values.
It may be that women and men have systematically different opinions about unions. This
may be a result of differing levels of union participation. It may be that women are less career-
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0 20 40 60 80 100 120
Linear
Quadratic
Cubic
Quartic
DifferentModelsforRegressing
supuniononage
Age
13. 11
oriented as they have children. To test this, a dummy variable, male, equaling 1 for men is
included in the regression.
It is reasonable to expect that respondents living in different locations have significantly
different opinions about unions. This could be a result of different economic conditions in the
provinces or varying levels of union density or activity. Different industries are more or less
prevalent in different geographical locations. It also could be a result of different taxation in
between provinces, and different levels of welfare in different geographical locations. It could
also be a result of different political tendencies across provinces, for example Alberta is
historically very conservative, and different political affiliations tend to have varying views on
unions. To test for differing opinions across provinces a dummy variable is included in the model
for each province. To avoid the dummy variable trap Ontario is chosen as the baseline and
excluded from the model, meaning all province coefficients will be a reflection of the difference
in opinion between that province and Ontario.
It is reasonable to expect that as one gains more education their opinion of unions will
change. This could be a result of a different likelihood of joining a union. It could also be that as
one gains more education they gain a better or simply new understanding of how unions affect
the economy. It could be that teachers and professors pass their views on to students. As students
enter university and college they specialize and these specializations could lead to unique
opinions about unions. To test for the effects of education, several dummy variables are included
in the model. Respondents are classified as having no high school education, high school
education, some post-secondary education, having completed college, or having a university
degree. Again to avoid the dummy variable trap those with no high-school are excluded from the
14. 12
model so that the coefficients on the other education variables can be interpreted as the
difference in opinions about unions than those with no highs school diploma.
It could be that being born in different periods will also lead to differing views on unions.
It may be that the differences in economic conditions and union activity during formative years
could lead to drastically different opinions of unions. It could be that living through different
historical events like war or political unrest may lead to differing values that may affect one’s
opinions of unions. To test for these effects dummy variables are created for respondents
depending on which decade they are born: before1920, 20s, 30s, 40s, 50s, 60s, 70s, or after 1980.
Those born before 1920 are omitted from the model so coefficients can be interpreted as the
difference in opinions about unions between the decade of birth and being born before 1920.
These periods were chosen so that there is a roughly equal amount of respondents born in each
period. These periods are somewhat arbitrary, for example there is not much difference in being
born between 1929 and 1930, but they will still provide insight as to whether cohort effects exist.
3.3 Macroeconomic Attributes
There are a variety of reasons we would expect the current unemployment rate to affect
public opinion of unions. A well known facet of unions is that they raise the wages above
equilibrium rates. Given this, it is reasonable to expect high unemployment would cause a
pervasive negative view of unions. However it has also been argued that during periods of high
unemployment workers may be more susceptible to bullying by management, so unions can
protect the interests of workers (Lowe and Krahn 1989). Provincial unemployment rates are used
in the regression analysis as one would expect that they would have a bigger effect on opinions,
as the majority of people are most concerned about the local job climate. Unemployment rates
15. 13
were obtained from the Labour Force Survey (LFS). Previous studies have posited that the union
density is a predictor of union rates (Lipset 1986). Union density rates were obtained from
stats.oecd.org. Union density is declining over time and this may be expected to lead to a more
negative view of unions. One would probably expect a union member to be more favourable of
unions as they have directly or indirectly chosen to join a union. Having a union member in
one’s household could also significantly affect ones opinion of unions. If one’s spouse is a union
member, they may get a higher level of pay as a result. It could be that union members with
negative experiences are affected the other way but there is little doubt that there will be an
identifiable effect. To test for this, respondents are given a dummy variable equal to 1 if they or
a member of their household is a member of a union.
It may be that current strike activity affects people’s support of unions. More labour
disputes and strikes could lead to views that unions are militant or ineffective, or they may
disrupt everyday activities of people leading to negative views (Bain and Edwards1988). To test
this, the number of strike hours lost per month per year in Canada, as obtained from the Labour
Force Survey (LFS) estimates, is included in the model.
It may be that people view the primary objective of unions should be to lift the bottom
members of society to higher earnings. One way we could model this is by looking at the Gini
coefficient. This is one measure of the dispersion of wealth with a higher score indicating a
greater disparity between the rich and poor. This is increasing over time as the coefficient
obtained when gini is regressed on time is .0018.
It could be that most people are not aware of the actual level of strikes. Therefore a better
measure of the effect of strike activity may be the effect of media coverage of strikes. To attempt
16. 14
to capture this effect, a measure of the number of articles in which strikes and unions appear in
the first paragraph of articles in the Globe and Mail was obtained through the Factiva periodicals
database. This measure labeled globeart is analyzed in the regression in addition to the number
of labour hours lost to strikes. Note this could not be obtained for 1976 so those observations are
dropped in subsequent analysis.
There are conflicting views on the effect of inflation on the support of unions. It could be
that unions cause inflation and therefore a higher inflation could lead to negative views (Bain
and Edwards 1988), or that unions help ensure livings standards in the case of inflation(Lowe
and Krahn 1989). It also may be that inflation concerns have decreased over time given that
Canada has maintained relatively stable inflation in recent history. To test this, provincial
inflation calculated from Consumer Price Indices (CPI) from Statistics Canada is included in the
model. Note inflation for the years 1978 and 1976 was not obtained so observations from that
year have been dropped.
It is human nature to be envious or jealous of those who are doing well. This may arise in
the case of unions if given two equivalent workers; the union member receives better pay or
benefits. This effect may be bigger if a less qualified union member gets paid more than a non-
union member. To test for this effect a measure of the union wage premium was constructed
using data from the Labour Force Survey (LFS) by subtracting the logarithm of the hourly wage
of non-union members from those covered by collective bargaining agreement. We could also
expect interaction effects between union and non-union members. Note that this was only
available starting in 1997.
4 Results
17. 15
Including the personal variables of age, gender, province, education and cohort into the model
leads to:
supunion = β0 + β1sample1 + β2sample2 + β3t + β4age + β5male + β6NFLD + β7PEI +
β8NS + β9NB + β10QUE+ β11MAN + β12SASK + β13ALB + β14BC + β15 HS +
β16SomePS + β17college + β18Uni + β1920s + β2030s + β2140s + β2250s + β2360s + β2470s
+ β25after1980 + ε
The results of this regression are:
Table 2
Results of supunion regressed on personal variables
Variable b St. Err. t
Sample1
Sample2
Time
Age
Male
NFLD
PEI
NS
NB
QUE
.4199226
-.0667914
.0097208
-.0039056
.0019385
.1144033
.0365501
.0247479
.0362482
.0702841
.0152863
.0075171
.0012035
.0009799
.0058605
.0192484
.0255508
.0166407
.0177458
.0076703
27.47
-8.89
8.08
-3.99
0.33
5.94
1.43
1.19
2.04
9.16
18. 16
MAN
SASK
ALB
BC
HS
Some Post-Secondary
College
University
20s
30s
40s
50s
60s
70s
After 1980
Constant
Obs= 23292
R2 = 0.1246
-.0062977
.0030781
-.0643011
.0223685
-.0244156
-.0416294
-.0399268
-.0421845
.0118766
-.0158691
-.0172754
-.0457343
-.0807569
-.0429485
.0025056
.3041292
.0149275
.0147711
.0107833
.0098577
.008603
.0099761
.009847
.0092722
.0189516
.0256307
.0340324
.0427245
.0514785
.0611867
.0735187
.0653449
-0.42
0.21
-5.96
2.27
-2.84
-4.17
-4.05
-4.55
0.63
-0.62
-0.51
-1.07
-1.57
-0.70
-0.03
4.65
Looking at the results of this regression there are a few interesting implications. First the
time coefficient .0097 has increased from .0076 in the regression of supunion on time alone after
the inclusion of these personal variables. The variation increased but the coefficient is still
significant at the 5% level. The R2 also increased from R2= 0.1082 to R2 = 0.1246. The negative
19. 17
effect of age on the support of unions leads to an increase in the effect of time, because of
Canada’s aging population. This aging population is reflected in the sample, if age is regressed
on time the coefficient is .2789. The results suggest that the effect of gender on the support of
unions is very small, and we cannot reject the null hypothesis that it is in fact zero at the 5%
significance level. The effects of the province of respondents are very straight forward and fall in
line with what might be expected. Newfoundland and Quebec are significantly more supportive
of unions than Ontario, while Alberta is significantly less supportive. While other provinces tend
to be more supportive of unions than Ontario, their opinions are fairly close and only in BC and
New Brunswick are we able to reject a null hypothesis of no effect at a 5% significance level.
The effect of education also seems to push the time trend higher as it is clear that
opinions of unions seem to drop a bit as one completes high-school and definitely drops if the
respondent completed at least some post-secondary education. Over time people are becoming
more educated, supported by a positive coefficient if education is regressed on time, and one
would expect this to drop the opinions of unions over time.
Finally the cohort effects are very small and the null hypothesis of zero effect cannot be
rejected for any decade. As previously stated the chosen cohorts are somewhat arbitrary but we
can still infer that there are no or very small cohort effects. Because of the insignificance of
gender and cohort they are excluded in further analysis. If the same regression is run without
these variables the time trend is very close although slightly smaller at .0089 with a t statistic of
12.15. See Table 3 appendix for full results.
Inclusion of unemployment leads to the model:
20. 18
supunion = β0 + β1sample1 + β2sample2 + β3t + β4age + β5NFLD + β6PEI + β7NS + β8NB
+ β9QUE + β10MAN + β11SASK + β12ALB + β13BC + β14HS + β15SomePS + β16college +
β17Uni + β18Unemployment
See Table 4 in Appendix for full results.
When this regression is run the coefficient on unemployment rates is -.0040 with a t
statistic of -2.09. This result can be interpreted as people are .40 percentage points less likely to
support unions given a one point increase in the provincial unemployment rate. We can reject the
null hypothesis that provincial unemployment rates, in fact, have no effect on people’s support of
unions. The inclusion of unemployment rates does reduce the time trend from .0088 to .0079
though this is still a rather significant time trend independent of the variables included in the
model thus far.
When union density is included in the regression model it leads to:
supunion = β0 + β1sample1 + β2sample2 + β3t + β4age + β5NFLD + β6PEI + β7NS + β8NB
+ β9QUE + β10MAN + β11SASK + β12ALB + β13BC + β14HS + β15SomePS + β16college +
β17Uni + β18Unemployment + β19uniondensity
See Table 5 in appendix for full regression results
When this regression is run the coefficient is surprisingly negative at -.0016 however the
t statistic is -0.79. As union density is falling over time in Canada, this reduced the effect of time
on union support to .0075. However we cannot reject the null hypothesis that the effect of union
density has no effect on the support of unions. Therefore because of this ambiguity a better
representation of the effect of the effect of falling union density may be the personal level
21. 19
variable of whether or not a member of the respondents household is a union member. The
falling union density over time is reflected in the respondents as household union membership
regressed on time produces a coefficient of -.0022. This leads to the model:
supunion = β0 + β1sample1 + β2sample2 + β3t + β4age + β5NFLD + β6PEI + β7NS + β8NB
+ β9QUE + β10MAN + β11SASK + β12ALB + β13BC + β14HS + β15SomePS + β16college +
β17Uni + β18Unemployment + β19HHUnionMembership
See Table 6 in appendix for full regression results
Not surprisingly, the estimates suggest that respondents with union members in their
household are strongly predisposed to be supportive of unions compared to non-union members.
The coefficient of household union membership is .1782 with a t statistic of 27.94. Here we can
easily reject the null hypothesis that this effect is in fact zero at the 5% significance level. This
positive trend reinforces the idea that there is a secular time trend in increasing support of
unions. The coefficient of time in this regression is .0091 with a t statistic of 10.88. It is also
worth noting the difference in the adjusted R2 statistics of these two models, as the union density
model was 0.1236 and the household union membership was 0.1520. This means this second
model fits the data significantly better. Therefore for further analysis on household union
membership and not union density will be included.
Inclusion of the number of labour hours lost to strikes leads to the model:
supunion = β0 + β1sample1 + β2sample2 + β3t + β4age + β5NFLD + β6PEI + β7NS + β8NB
+ β9QUE + β10MAN + β11SASK + β12ALB + β13BC + β14HS + β15SomePS + β16college +
β17Uni + β18Unemployment + β19HHUnionMembership + β20Strikehours
22. 20
For full regression results refer to Table 7 appendix.
Looking at the results the expected negative effect of more strikes on the opinions of
unions can be seen as the coefficient for strike hours is -.0000446 with a t statistic of -2.37.
Although this is an extremely small effect, it is per hour of labour so given high variation it could
have an impact on public opinions. This can be seen in the fact that we cannot reject the null
hypothesis that this effect is in fact zero at the 5% significance level. However the inclusion of
strike hours lowers the R2 slightly, meaning it does not make the model fit the data any better.
Including the gini measure, as recorded by Statistics Canada, leads to the model:
supunion = β0 + β1sample1 + β2sample2 + β3t + β4age + β5NFLD + β6PEI + β7NS + β8NB
+ β9QUE + β10MAN + β11SASK + β12ALB + β13BC + β14HS + β15SomePS + β16college +
β17Uni + β18Unemployment + β19HHUnionMembership + β20Strikehours + β21Gini
See Table 8 in appendix for complete regression results.
There is a large negative coefficient on Gini in this regression of -2.9928 with a t statistic
of -5.80, which can be viewed as an increasingly negative public view of unions as the dispersion
between the rich and poor increases. This increases the time trend significantly to .0135 with a t
statistic of 9.31. It is hard to identify the causal relationship here in the minds of the public. The
inclusion of Gini does increase the R2 a little, from .1522 to .1533. It may be that this is not a
consideration that the majority of people have when deciding on their support for unions and this
result is picking up spurious correlation. What is evident is that it is not reducing the secular
trend in public opinions over time.
23. 21
The poor predictive value of strike hours may be a reflection of a lack of knowledge in
the general public. To better capture this effect in the decision making process of the public,
strike hours is replaced with a measure of media coverage of strikes. This leads to the model:
supunion = β0 + β1sample1 + β2sample2 + β3t + β4age + β5NFLD + β6PEI + β7NS + β8NB
+ β9QUE + β10MAN + β11SASK + β12ALB + β13BC + β14HS + β15SomePS + β16college +
β17Uni + β18Unemployment + β19HHUnionMembership + β20globeart + β21Gini
For complete regression result see Table 9 in appendix.
Looking at the results, the coefficient of globeart is similar to that of strike hours, b= -
.0017 but with a higher t statistic of -4.35. It also has a much larger effect on the time coefficient
reducing it to .0072 with a t statistic of 3.69. This indicates that media does in fact have an effect
on the public opinion of unions. It must be noted that while a general result can be drawn from
this there is bound to be a high uncertainty with using one measure of media coverage. The
variations in articles may not necessarily reflect how much awareness the public has of strikes, as
the form of the paper changes over time. For example there are more sections and different
authors with different opinions. It is also interesting that the coefficient for Gini drastically
drops, to -1.1124 with a t statistic of -1.58 lending credence to the idea that this is not a
consideration of an average individual in their decision about whether or not to support unions.
Including provincial inflation leads to the model:
supunion = β0 + β1sample1 + β2sample2 + β3t + β4age + β5NFLD + β6PEI + β7NS + β8NB
+ β9QUE + β10MAN + β11SASK + β12ALB + β13BC + β14HS + β15SomePS + β16college +
β17Uni + β18Unemployment + β19HHUnionMembership + β20globeart + β21Gini +
β22provincialinflation
24. 22
For full regression results see Table 10 in appendix
The results of this regression are very interesting, the inflation coefficient is -.0075 with a
t statistic of -3.42. This implies that as inflation increases people become less supportive of
unions. The effect of provincial inflation on time is very suggestive. In this regression the
coefficient on time is .0017 which is significantly smaller than previous results. Perhaps more
telling is the t statistic for time, which is now 0.76, meaning one fails to reject the null hypothesis
that there is no secular trend in the support of unions over time. If globeart and gini are removed,
given their subjective nature, the time coefficient is still much smaller (see Table 11 in appendix
for complete results) at .0027 with a t statistic of 2.09. While the null hypothesis would not be
rejected at a 5% significance level in this regression, if one takes the idea of some negative
correlation between media coverage of strikes and public opinion of unions, which is reasonable
given the previous research into this relationship in the United States (Schmidt 1993), then the
null hypothesis of zero effect at the 5% significance level would likely be rejected. Also note that
the effect of the dropped variables is also negligible to these key results. If the initial regression
of supunion on sample and time is run without observations from 1976 and 1978 the time
coefficient increases from .0076 to .0077, implying that the effect of provincial inflation is
bigger than the effect of lost observations.
Including the measure of wage premium and accounting for interaction effects leads to the
model:
supunion = β0 + β1sample2 + β2t + β3age + β4NFLD + β5PEI + β6NS + β7NB+ β8QUE +
β9MAN + β10SASK+ β11ALB + β12BC + β13HS + β14SomePS + β15College +
25. 23
β16University+ β17Unemployment + β18HHUnionMembership + β19globeart + β20Gini +
β21provincialinflation + β22wagepremium + β23hhunion*wagepremium
For full regression results refer to Table 12 in appendix
Looking at the results of this regression one can see a very large coefficient on the union
premium of -.2615 which suggests that as the wage premium for union member grows the public
opinion of unions falls, and a large positive coefficient on the interaction effects of .0989
suggesting as the wage premium grows union members become more supportive of their unions.
However the t statistics for these coefficients are -1.09 and 1.39 respectively so the null
hypothesis that these effects are zero cannot be rejected at the 5% significance level. Because of
this fact combined with the severely reduced R2 of .0507 these variables will be left out of the
regression.
5 Conclusions
There is a clear trend of increasing support for unions in Canada from 1976 – 2008. After
analyzing components that could be incorporated in the decision process of how the public form
their opinions of unions the following model best represents the support of unions from 1976 to
2008.
supunion = β0 + β1sample1 + β2sample2 + β3t + β4age + β5NFLD + β6PEI + β7NS + β8NB
+ β9QUE + β10MAN + β11SASK + β12ALB + β13BC + β14HS + β15SomePS + β16college +
β17Uni + β18Unemployment + β19HHUnionMembership + β20globeart + β21Gini +
β22provincialinflation
Table 3
26. 24
The Results of the Ordinary Least Squares Regression
Variables b St. Err. t
Sample1
Sample2
T
Age
NFLD
PEI
NS
NB
QUE
MAN
SASK
ALB
BC
HS
Some post-secondary
College
University
Unemployment rates
HHunion
globeart
Gini
.4229384
-.0621281
.0016906
-.0017991
.2806546
.1983724
.0873261
.1087373
.1256822
-.0297746
-.0216571
-.0706928
.0247258
-.0313082
-.0374687
-.0602123
-.0606356
-.0224847
.1732808
-.0001787
-.2943564
.0206513
.0076367
.0022291
.000197
.0322291
.0316005
.0191287
.020947
.011332
.0156541
.0156258
.0114349
.0102153
.009017
.0102973
.010006
.0094446
.0029625
.006695
.0000432
.7499253
20.48
-8.14
0.76
-9.13
8.71
6.28
4.57
5.19
11.09
-1.90
-1.39
-6.18
2.42
-3.47
-3.64
-6.02
-6.42
-7.59
25.88
-4.13
-0.39
27. 25
Provincial Inflation
Constant
R2 = 0.1451
Obs= 20851
-.0074529
.6124605
.0021779
.2230462
-3.42
2.75
From these results there are three main conclusions that can be reached:
1. One cannot definitively state that the increasing public opinion is a secular trend over time, as
one cannot reject the null hypothesis that the time coefficient is not in fact zero.
2. While we cannot definitively state that there is an increasing secular public opinion of unions,
the majority of covariates analyzed had a clear impact on the support of unions that tended to
increase the secular time trend. This suggests that in reality there could be a secular increase in
the support of unions over time.
3. The biggest factor leading to the increasing support of unions appears to be the reduction and
stabilization of provincial inflation.
Further analysis of these regression results does provide some other useful insights. There
appears to be significant differences given geographical locations within Canada. People tend to
become less supportive of unions as they age, and as they receive more education. However the
type of education doesn’t appear to have a huge effect, suggesting this is a difference in life
experience and goals as opposed to a fundamental aspect of any particular education system. In
Canada, both the amount of education and the age of the population are increasing which
supports the idea of a secular trend of increasing support of unions from 1976 – 2008. People
tend to become more cynical of unions as unemployment increases; this may be a result of the
28. 26
fact unions raise the wage above equilibrium values. There does not appear to be a pervasive
opinion that unions are a tool for social equalization. This may be a result of well-defined legal
and political systems that are seen as better tools to reach these goals.
With respect to media coverage of unions it appears that the level of coverage of strikes over
time has affected people’s opinions of unions. This could be reflective of the decline of the
union’s social status. On the surface, looking at the big effect that union membership has on the
support of unions, the falling union density over time reinforces a secular time trend. However, it
may be that as union density has declined, people hear less about unions, there are fewer strikes
and people may believe unions have become less powerful and, therefore, worry less about
negative externalities that may arise, like corruption.
29. 27
Appendix
Table 1
Results of Supunion Regressed on Time
Variable b St. Err. t
t
t2
sample1
sample2
constant
R2= 0.1095
Obs= 23292
.0188369
-.0002834
.4708031
-.0722534
.0265434
.0020378
.000048
.0168957
.0077438
.0248172
9.24
-5.91
27.87
-9.33
1.07
t
t2
t3
sample1
sample2
constant
R2= 0.1099
Obs= 23292
.007967
.0006006
-.0000176
.4947763
-.0735191
.0323508
.0038819
.000273
5.35e-06
.0183971
.0077517
.0248747
2.05
2.20
-3.29
26.89
-9.48
1.30
t
t2
t3
-.0173958
.0038739
-.0001582
.0089008
.0010692
.0000447
-1.95
3.62
-3.54
32. 30
Sample1
Sample2
T
Age
NFLD
PEI
NS
NB
QUE
MAN
SASK
ALB
BC
HS
Some post-secondary
College
University
Constant
R2 = 0.1235
Obs= 23292
.4244988
-.0671639
.0088378
-.002602
.1134528
.0372681
.0247839
.0353604
.0711148
-.0066681
.0024748
-.0641586
.0225853
-.0263522
-.0410781
-.0445653
-.0454725
.2297021
.0152368
.0075063
.0007274
.00019
.0192512
0255611
.0166477
.017755
.007671
.0149351
.0147788
.0107886
.0098619
.0085644
.0099696
.009782
.0092064
.0214251
27.86
-8.95
12.15
-13.69
5.89
1.46
1.49
1.99
9.27
-.045
0.17
-5.95
2.29
-3.08
-4.12
-4.56
-4.95
10.72
Table 4
Regression Results From Inclusion of Provincial Unemployment Rates
33. 31
Variables b St. Err. t
Sample1
Sample2
T
Age
NFLD
PEI
NS
NB
QUE
MAN
SASK
ALB
BC
HS
Some post-secondary
College
University
Unemployment rates
Constant
R2 = 0.1236
Obs= 23292
.4064867
-.0668922
.0079165
-.0026077
.1471443
.0613827
.0357001
.0485352
.0820449
-.0107693
-.0032475
-.0683742
.0252959
-.0259398
-.0407324
-.0440578
-.0452419
-.0039857
.2778308
.0175047
.0075069
.0008505
.00019
.0251091
.0280433
.0174468
.0188398
.0092839
.0150624
.0150293
.0109748
.0099462
.0085661
.0085661
.0097843
.0092064
.0092064
.031454
23.22
-8.91
9.31
-13.72
5.86
2.19
2.05
2.58
8.84
-0.71
-0.22
-6.23
2.54
-3.03
-4.09
-4.50
-4.91
-2.09
8.83
34. 32
Table 5
Regression results when union density is included
Variables b St. Err. t
Sample1
Sample2
T
Age
NFLD
PEI
NS
NB
QUE
MAN
SASK
ALB
BC
HS
Some post-secondary
College
University
Unemployment rates
Union Density
.4059635
-.0666246
.0074682
-.0026066
.1337012
.0519019
.0310564
.0429064
.0774938
-.0090346
-.0007628
-.066701
.0242724
-.0259001
-.0407124
-.0439957
-.0450448
-.0023766
-.0016398
.0175172
.0075145
.0010214
.00019
.0302994
.0304873
.0184042
.0201336
.0109157
.0152207
.0153527
.0111761
.0100297
.0085663
.0099704
.0097847
.0097847
.0097847
.0020685
23.18
-8.87
7.31
-13.72
4.41
1.70
1.69
2.13
7.10
-0.59
-0.05
-5.97
2.42
-3.02
-4.08
-4.50
-4.89
-0.85
-0.79
35. 33
Constant
R2 = 0.1236
.3309864 .0740651 4.47
Table 6
Regression Results of Including Household Union Membership
Variables b St. Err. t
Sample1
Sample2
T
Age
NFLD
PEI
NS
NB
QUE
MAN
SASK
ALB
BC
HS
Some post-secondary
College
.4303811
-.052317
.0091174
-.0018927
.1172761
.0662348
.0364901
.0425793
.0692943
-.0146353
-.0073081
-.0596871
.0145939
-.0315564
-.036612
-.0566837
.01724
.0074027
.0008377
.0001887
.0247221
.0275857
.0171619
.0185333
.0091436
.014817
.0147845
.0108001
.0097912
.0084285
.0098085
.0096351
24.96
-7.07
10.88
-10.03
4.74
2.40
2.13
2.30
7.58
-0.99
-0.49
-5.53
1.49
-3.74
-3.73
-5.88
36. 34
University
Unemployment rates
Household union
membership
Constant
R2 = 0.1527
Obs= 23292
-.0549966
-.0032368
.1782362
.1617485
.0090627
.0018762
.0063804
.031218
-6.07
-1.73
27.94
5.18
Table 7
Regression Results When Labour Hours Lost to Strikes is Included in the Model
Variables b St. Err. t
Sample1
Sample2
T
Age
NFLD
PEI
NS
NB
QUE
MAN
SASK
.4349104
-.0531343
.0076466
-.0018819
.1468663
.0883411
.0466236
.0549597
.0791499
-.0184293
-.0125618
.017344
.00741
.0010427
.0001887
.0276969
.0291191
.0176854
.0192545
.010045
.0149019
.0149485
25.08
-7.17
7.33
-9.97
5.30
3.03
2.64
2.85
7.88
-1.24
-0.84
37. 35
ALB
BC
HS
Some post-secondary
College
University
Unemployment rates
HHunion
Strike hours
Constant
R2 = 0.1522
Obs= 23292
-.0636783
.0171395
-.0320167
-.0371473
-.0571846
-.0552182
-.0068496
.1780333
-.0000446
.234278
.0109296
.009849
.009849
.0098101
.0096364
.0090623
.0024178
.0063803
.0000188
.043726
-5.83
1.74
-3.80
-3.79
-5.93
-6.09
-2.83
27.90
-2.37
5.36
Table 8
Regression Results From Including Gini Coefficient
Variable b St.err. t
Sample1
Sample2
T
Age
NFLD
PEI
.4070361
-.0512435
.0134541
-.0018936
.1864314
.1151885
.0179857
.007412
.001445
.0001886
.0285056
.0294645
22.63
-6.91
9.31
-10.04
6.54
3.91
38. 36
NS
NB
QUE
MAN
SASK
ALB
BC
HS
Some post-secondary
College
University
Unemployment rates
HHunion
Strike hours
Gini
Constant
R2 = 0.1533
Obs= 23292
.0601283
.0722122
.0928176
-.0239618
-.0205839
-.0687433
.0199677
-.0328054
-.037782
-.0578585
-.0568523
-.0115263
.1783318
7.40e-06
-2.992812
1.15954
.0178257
.0194695
.0103108
.0149219
.0150019
.0109568
.0098542
.0084251
.0098039
.0096304
.0090604
.0025471
.0063761
.0000208
.5159567
.1653902
3.37
3.71
9.00
-1.61
-1.37
-6.27
2.03
-3.89
-3.85
-6.01
-6.27
-4.53
27.97
.36
-5.80
7.01
Table 9
Regression Results Replacing Strike Hours with Globeart
Variables b St. Err. t
40. 38
Obs= 22525
Table 10
Regression with Provincial Inflation Included
Variables b St. Err. t
Sample1
Sample2
T
Age
NFLD
PEI
NS
NB
QUE
MAN
SASK
ALB
BC
HS
Some post-secondary
College
University
.4229384
-.0621281
.0016906
-.0017991
.2806546
.1983724
.0873261
.1087373
.1256822
-.0297746
-.0216571
-.0706928
.0247258
-.0313082
-.0374687
-.0602123
-.0606356
.0206513
.0076367
.0022291
.000197
.0322291
.0316005
.0191287
.020947
.011332
.0156541
.0156258
.0114349
.0102153
.009017
.0102973
.010006
.0094446
20.48
-8.14
0.76
-9.13
8.71
6.28
4.57
5.19
11.09
-1.90
-1.39
-6.18
2.42
-3.47
-3.64
-6.02
-6.42
41. 39
Unemployment rates
HHunion
globeart
Gini
Provincial Inflation
Constant
R2 = 0.1451
Obs= 20851
-.0224847
.1732808
-.0001787
-.2943564
-.0074529
.6124605
.0029625
.006695
.0000432
.7499253
.0021779
.2230462
-7.59
25.88
-4.13
-0.39
-3.42
2.75
Table 11
Regression with provincial Inflation and Without Globeart and Gini
Variables b St. Err. t
Sample1
Sample2
T
Age
NFLD
PEI
NS
NB
QUE
MAN
.3921882
-.0642707
.0027159
-.0018018
.2338274
.1629527
.070827
.0904373
.1097074
-.0232088
.0187286
.0075776
.0013021
.0001971
.0312513
.0310935
.0189375
.0207295
.0110057
.015625
20.94
-8.48
2.09
-9.14
7.48
5.24
3.74
4.36
9.97
-1.49
42. 40
SASK
ALB
BC
HS
Some post-secondary
College
University
Unemployment rates
HHunion
Provincial Inflation
Constant
R2 = 0.1443
Obs= 20851
-.0132702
-.0651165
.0215151
-.0304537
-.0367433
-.059738
-.0594498
-.0169039
.1736293
-.0072063
.4172811
.0155707
.0114102
.0102107
.0090239
.010306
.0100146
.0094487
.0028117
.0067008
.0021436
.051631
-0.85
-5.71
2.11
-3.37
-3.57
-5.97
-6.29
-6.01
25.91
-3.36
8.08
Table 12
Regression Including Wage Premium and Wage Premuim*HHunion
Variables b St. Err t
Sample2
T
Age
NFLD
PEI
-.057269
.0072155
-.0010436
.1692896
.0874713
.0120779
.0079509
.0002978
.1094656
.1068876
-4.74
.91
-3.5
1.55
0.82
43. 41
NS
NB
QUE
MAN
SASK
ALB
BC
HS
Some post-secondary
College
University
Unemployment rates
HHunion
Globeart
gini
Provincial Inflation
Union premium
Union
premium*HHunion
Constant
R2 = 0.0507
Obs= 9714
-.0356566
.0531451
.0802219
-.0873228
-.0703859
-.0864481
-.0068095
-.051431
-.0546847
-.0787903
-.0703196
-.0138767
-.0960244
-.0001144
.1826176
-.0039215
-.2615254
.0988516
.955606
.0720631
.0782314
.036093
.055346
.05526
.0260757
.0178725
.0146563
.0160569
.0155808
.0145162
.0085385
. 1952469
.0001679
2.001193
.0099611
.2400441
. 0709162
.9822524
-0.49
0.68
2.22
-1.58
-1.27
-3.32
-0.38
-3.51
-3.41
-5.06
-4.84
-1.63
-0.49
-0.68
0.09
-.039
-1.09
1.39
0.97
44. 42
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