The Impact of Unionization Threat on Non-union Wage Rages in Canada

THE IMPACT OF UNIONIZATION THREAT ON NON-UNION WAGE

RATES IN CANADA

BY

JOEY YI ZUO

OCTOBER 2007

i

Abstract

In an effort to reduce the workers’ benefits from joining the union, employers increase wages

of their non-union workers when facing an increased threat of unionization (Rosen, 1969).

This paper presents novel evidence regarding the effect of the threat of unionization on wage

rates in Canada for the period between 1998 and 2006. Drawing on the insights provided by

nine consecutive annual Canadian Labor Force Surveys, I find that the threat of unionization

has a larger positive effect on the non-union wages compared to the threat’s effect on the

union wages and, hence, has an inverse effect on the union-wage gap. Further, the analysis

by sectors suggests that these results hold for the private sector only and do not extend to the

public sector. Importantly, I find that the results are sensitive to the definition of the

unionization threat and to the list of explanatory variables included in the estimation model.

ii

TABLE OF CONTENTS

1. INTRODUCTION - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -1

2. LITERATURE REVIEW - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 3

3. THEORETICAL FRAMEWORK - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 5

4. METHODOLOGICAL APPROACH - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -7

4.1. Predicated Probability of Union Membership as a Measure of Unionization Threat- 7

4.2. Industry Union Density as a Measure of Unionization threat- - - - - - - - - - - - - - - - -9

4.3. Analysis by Private and Public Sector- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -9

4.4. Potential Problems- - - - - - - - - - - - - - - - - - - - - - - - - - - - - -- - - - - - - - - - - - - - -10

5. DESCRIPTION OF DATA AND VARIABLES - - - - - - - - - - - - - - - - - - - - - - - - - 11

6. RESULTS - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 11

6.1. Determinants of Union Membership in Canada, 1998-2006- - - - - - - - - - - - - - - - -11

6.2. Effect of the Unionization Threat on Non-union Wage Rates- - - - - - - - - - - - - - - -13

6.3. An Analysis of Unionization Threat in Private and Public Sectors - - - - - - - - - - - - 15

6.4. An alternative Measure for Unionization Threat - - - - - - - - - - - - - - - - - - - - - - - - 16

7. CONCLUSIONS- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -16

8. REFERENCES - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -18

9. APPENDICES - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 21

Appendix A Variable Description and Review of Literature on the Union Threat Effects-21

Appendix B Estimation Results- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 24

Appendix C Graphs- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 44

iii

LIST OF TABLES

Table 1: Description of variables - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 21

Table 2: Review of literature on the union threat effects - - - - - - - - - - - - - - - - - - - - - -22

Table 3: Determinants of union membership in Canada, 1998-2006 (all sample) - - - - - 24

Table 4: Effect of predicted probability of unionization on union/non-union wage rates,

1998 -2006 (all sample)- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 26

Table 5: Effect of union density on union/non-union wage rates, 1998-2006 (all sample)

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - -- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 29

Table 6: Determinants of union membership in Canada, 1998-2006 (Public Sector)

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -- - - - - - - - - - - - - - - - - - - - - - - - - - - - - 31


1998-2006 (Public Sector) - - - - - - - - - - - - - - - - - - - - - - - - - -- - - - - - - - - - - - - - - 33

Table 8: Effect of union density on union/non-union wages, 1998- 2006 (Public Sector)

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -- - - - - - - - - - - - - - - - - - - - - - - - - - - - - 36

Table 9: Determinants of union membership in Canada, 1998- 2006 (Private Sector)

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - -- - - - - - - - - - - - - - - - - - - - - - - - - - - - - -38


1998- 2006 (Private Sector) - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -40

Table 11: Effect of union density on union/non-union wage rates, 1998 – 2006

(Private Sector) - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -- - - - - - - - - - - - - - - - - -42

iv

LIST OF FIGURES

Figure 1: Union membership in Canada (1998-2006) - - - - - - - - - - - - - - - - - - - - - -44 Figure 2: Effect of predicted probability of unionization on the non-union/union wages

and the union-wage gap, for the whole sample, by year- - - - - - - - - - - - - - - - - - - - -45

Figure 3: Effect of predicted probability of unionization on the non-union/union wages

and the union-wage gap, for the public sector, by year- - - - - - - - - - - - - - - - - - - - - 46

Figure 4: Effect of predicted probability of unionization on the non-union/union wages

and the union-wage gap, for the private sector, by year - - - - - - - - - - - - - - - - - - - - -47

Figure 5: Effect of industry union density on the non-union/union wages and the union-

wage gap, for the whole sample, by year. - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -48


wage gap, for the private sector, by year- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 49


wage gap, for the public sector, by year- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -50

1

1. Introduction

Union membership in Canada has declined from approximately 55% to 30%, since the

1980s, according to Blanchflower (2006). The decline can be attributed to decreasing union

membership in the private sector. In contrast, union membership in the public sector has

increased in the past decade. Over the last decade private firms have responded to the threat

of unionization most notably by subcontracting, outsourcing, and even plant-closings. The

retail giant Wal-Mart, for example, recently closed its store in Jonquiere, Quebec after the

store became unionized (Bianco 2006). In this paper I am interested in assessing whether the

unionization threat in Canada justifies such severe reactions on the part of firms.

My analysis draws on the seminal work by Rosen (1969). Rosen suggests that the

ability of unions to negotiate higher wages increases with the extent of unionization; that is,

as the proportion of employed workers who are union members in an industry or occupation

increases. In particular, Rosen notes that as the extent of unionization increases “[the

possibility] for output or product substitution against unionized firms is reduced”. Moreover,

to avoid an increase in wage rates that follow unionization, employers are expected to

increase the wages of their current non-union employees in an attempt to reduce the

employees’ benefits from joining the union. This increase in non-union wages is likely

greater when the non-union employees have similar attributes to those of the union members

or in industries (occupations or cities) with substantial union presence. The literature refers to

this phenomenon as the effect of the unionization threat on non-union wages.

Several studies tested these predictions (e.g., Kahn 1978; Moore et al. 1985; Podgursky

1986). Despite the wide interest, the empirical evidence on the unionization threat effect

remains an unsettled question. Using firm-level data, Leue and Tremblay (1993), for instance,

2

found no significant effect of unionization threat on non-union wages. Freeman and Medoff

(1981) found that in manufacturing, the unionization threat has a strong positive effect on

union wages, but no or a weak effect on non-union wages. While the literature on the

unionization threat effect primarily draws on the U.S. data, Canadian studies tend to focus on

identifying the wage gap between union and non-union workers. The estimates range from

9.5% in Kumar and Stengos (1985), to between 16% and 51% in MacDonald and Evans

(1981), and 34.7% in Chaykowski and Slotsve (2002). To my knowledge, no study has

examined the effect of unionization threat on wage rates in Canada.

This paper attempts to fill this gap in the literature by providing evidence that pertains

to the unionization threat effect on the non-union wages and the union-wage gap. Using data

from the Canadian Labor Force Surveys between 1998 and 2006, I build on prevalent

approach in the literature and construct industry-level union density as my proxy for the

threat of unionization. I expand on this initial approach by constructing an alternative

measure following Farber’s (2005) methodology. This alternative measure for the threat of

unionization is constructed as the predicted probability of union membership, a function of

worker-, job-, and firm-specific attributes. I proceed to regress wages of non-union workers

on these alternate unionization threat variables while controlling for a wide set of observable

worker-, job-, and firm-characteristics. In addition, I extend on Farber’s (2005) study by

examining separately the effect of the threat of unionization in the private and public sectors.

My results are consistent with the hypothesis that the threat of unionization is directly

related to an increase in non-union wages in the private sector, but not in the public sector.

The magnitudes of the threat effects in my study are somewhat similar to those in the related

literature that draws on the U.S. data. The estimated threat effect in the non-union private

3

sector in Canada is between 14.9% and 21.9% (from 1998 to 2006), as compared to 20% in

the Farber’s (2005) study which draws on the U.S. data. Importantly, I find that my results

are sensitive to the list of explanatory variables and to the definition of the unionization

threat. In Section 2, a review of the literature on the unionization threat effect is provided.

Section 3 provides a brief description of the theoretical framework that motivates my

empirical analysis. Section 4 focuses on methodology and Section 5 on data description.

Results are presented in Section 6. Section 7 concludes.

2. Literature Review

Economists have been long concerned with assessing the effect unions have not only on

wages of union workers but also on wages of non-union workers. Some argued that the effect

of unions on the non-union wages (i.e., the unionization threat effect) results from a desire by

the non-union employers to avoid unionization; as higher wages reduce the benefits to

unionization. Rosen (1969), for instance, argued that we should observe a positive

relationship between the non-union wages and the extent of union organization (or the

percent of unionized workers in the industry) at lower levels of union organization. This

prediction is supported by Moore et al. (1985). The authors found that the unionization

density in an industry with fewer union members has a positive effect on non-union wages.

Corneo and Lucifora (1997) and Kahn (1978) reported similar findings.

Podgursky (1986) extended the argument and found that non-union wages at medium-

sized firm increase with the union threat. Pearce (1990) also suggested that the effect of

unionization threat increases with firm size in the non-union sector. Farber (2005)

documented that stronger evidence in favour of the union threat effects could be found in

4

deregulated industries. However, some studies report that no significant threat effect is found.

Freeman and Medoff (1981), for instance, found that in manufacturing, the threat has a

strong positive effect on union wages, but no or weak effect on non-union wages. Leue and

Tremblay (1993) also claimed that no significant effect was found of the effects of either the

percentage organized or the firm-level predicted threat of unionization on non-union wages.

Another strand of literature has provided findings of the unionization threat’s effect on

wage dispersion. Belman and Heywood (1990), for instance, have shown that the percentage

organized in the union reduces union wage dispersion but has a weak effect on non-union

wages. According to findings in Neumark and Wachter (1995), at the industry (city) level, an

increase in the percentage organized in the union reduced (increased) the non-union industry

(city) wage differential. Kahn and Curme (1987), on the other hand, found that an increase in

the percentage organized in unions decreased the dispersions of non-union wages.

The reviewed papers tend to use different measures of the threat of unionization (see

Appendix A Table 2). The most common measure for the unionization threat is an industry-

level or occupation-level union density. For example, Podgursky (1986) uses the proportion

of production workers who are covered by union contracts in an industry as a measure of the

union threat. Kahn and Curme (1987) and Moore et al. (1985) use both industry-level and

occupation-level union membership rates. Neumark and Wachter (1995) employ the city-

level union density rate as an explanatory variable in the wage regression. Farber (2005), on

the other hand, uses the predicted probability of being a union member as a measure of the

threat. Unlike the industry-level union density, Farber’s measure allows the threat of

unionization to differ not only across industries, but also across workers who are employed in

the same industry but differ in their age, attained education, marital status, gender, etc.

5

In this paper, I follow Farber’s (2005) approach. I use repeated cross-sectional data

from 1998 to 2006 for Canada to construct the predicted probability of union membership. I

also construct an alternative measure, industry-level union density, in an attempt to infer how

sensitive the results are to the definition of the union threat measure. Using both measures I

can, therefore, better understand why related literature has found remarkably different

evidence for the effect of unionization threat on non-union wages. In addition, a separate

analysis for the public sector and the private sector is provided. I am interested in the latter

distinction, since it is more likely that employers in a private sector are confronted with

decisions stipulated in a theoretical framework of profit maximization. In contrast, employers

in the public sector may be pursuing other goals such as ensuring stable employment.

Overall, my analysis contributes in four respects to the related literature. Namely, I: (1)

estimate the effect of unionization threat on non-union and union wage rates in Canada over

an extended period of time; (2) identify the threat effect on the wage gap between union and

non-union workers; (3) examine both the union and the non-union wage responses to the

unionization threat separately in the public and private sectors; (4) measure the threat effect

with the predicted probability of union membership and the industry-level union density.

3. Theoretical Framework

Following Farber’s (2005) methodology, I let ),( βαP denote the probability of

unionization, where NNU WWW /)( −=α denotes the union wage gap ( 0 1α< < ), UW the

union wages, NW the non-union wages, andβ the index of the threat of unionization for a

given union-wage gap ( 0 1β< < ). I assume that 0Pα > , 0Pβ > , 0Pαα > , 0Pαβ > , and

6

0Pββ > . Note that 0>αβP implies that, the marginal effect of an increase in the union-wage

gap on the probability of unionization increases in magnitude as the threat β increases.

Let the expected wage be denoted as ( )E W . Hence, the expected wage is a weighted

average of the union wage and the non-union wage rates with weights representing the

probability of unionization ( P ) and the probability of non-unionization (1 P− ), respectively.

Using the above introduced notation, the expected wage can be written as:

( )( ) ( ) (1 )N N UN U N N N N N

N

PW W WE W W P W W W W PW W PW

α α−= + − = + = + = + . (1)

Employers who employ non-unionized workers choose NW in order to minimize )(WE . The

optimal NW solves the first order condition obtained by setting the derivative of

the )(WE with respect to NW to zero: (1 ) (1 ) 0P Pαα α− − − = . The effect of the threat of

unionization on the non-union wage rate can be obtained by taking the derivative of this first-

order condition with respect toβ :

2

(1 )( )(1 )

N N U

U

P PW W WP P Wβ αβ

α αα

α αβ α β

+ −∂ ∂ ∂= +

∂ + + ∂ ∂. (2)

If 0/ ≥∂∂ βUW , one gets:

2

(1 )/ 0

( )(1 )N U

U

P PW WWP Pβ αβ

α αα

α αβ

β α β+ −∂ ∂

= + ∂ ∂ > ≥∂ + + ∂

. (3)

Since 0,0,0,0,0 >>>>> ββαβααβα PPPPP , 0 1α< < it follows that 0)1)(()1(2 >

++

−+

ααα

ααα

αββ

PPPP

.

The comparative statistics’ results in (2) and (3) are central to this study that aims to

estimate the effect of the threat of unionization on the non-union wage. The result suggests

that an increase in the likelihood of unionization (β ) has: (1.) a positive effect on the non-

7

union wage ( 0NWβ

∂>

∂); (2.) a nonnegative effect on the union wage such

that 0N UW Wβ β

∂ ∂> ≥

∂ ∂; and (3.) a negative effect on the union-wage gap or the union wage

premium. This paper tests empirically these three predictions by drawing on the data

collected from nine annual labor force surveys in Canada from 1998 to 2006.

4. Methodological Approach

To test these predictions I use two measures for the threat of unionization (β ). In the

next two sections I describe how these two measures are constructed. My third approach to

testing the model’s prediction explores one of the model’s assumptions; i.e., that employers

minimize their wage costs. While this assumption may be valid for employers in the private

section, it may not be a good description of the employers’ decisions in the public sector. I

explore this conjecture by examining separately the effect of unionization threat on non-

union wages for workers in the private sector and for workers in the public sector.

4.1. Predicated Probability of Union Membership as a Measure of Unionization Threat

My first approach to estimating the unionization threat’s effect on the non-union wage

rates follows Farber (2005). In the first step, I estimate the predicted probability of union

membership by running a probit regression for each year:

( 1| ) ( ' )i i iProb Union X Xφ η= = . (4)

In this equation, ( )Φ ⋅ denotes a standard normal cumulative distribution function, η is a

vector of coefficients I wish to estimate, and Xi is a vector of worker and firm characteristics,

8

industry and province dummies (See Appendix A, Table 1 for detailed explanation of

variables). The threat of unionization assigned to worker i in my sample is defined as follows:

)'( ii Xthreat∧∧

= ηφ . (5)

In the second step, I use the threat variable, ithreat∧

, as an independent variable in the

wage regression. I estimate separately the wage regression for the sample that consists solely

of non-union workers and in a sample that consists solely of union workers. In particular, an

econometric specification for the union wage equation can be written as:

0 1ln( ) 'iUiU U U U iU iUwage threat Xδ δ γ ε∧

= + + + . (6)

Similarly, the wage regression I estimate for the non-union workers is:

0 1ln( ) 'iNiN N N N iN iNwage threat Xδ δ γ ε∧

= + + + . (7)

In equations (6) and (7), iUthreat∧

is the predicted probability of being a union member

for a worker in the sample of union workers, and iNthreat∧

is the predicted probability of

being a union member for a worker in the sample of non-union workers. Hence, unionization

threat is measured by the extent the non-union employees have similar attributes to those of

the union members. XiU is a vector containing other explanatory variables in the union sample;

XiN is a vector containing other explanatory variables in the non-union sample; Uγ and Nγ are

vectors of estimated coefficients for the control variables; 0Uδ and 0Nδ are the constants, δ 1U

and δ1N are the coefficients on the threat effects; and iUε and iNε are the residuals in the

sample of union workers and the sample of non-union workers, accordingly.

Theory suggests that non-union firms are expected to increase wage rates for their non-

union workers when faced with the unionization threat. In particular, a positive correlation

9

between the threat of unionization and the non-union wage rates is expected. Specifically, we

expect 1 0Nδ > . We also expect that 1 1 0N Uδ δ> ≥ , due to the results derived in (3).

4.2. Industry Union Density as a Measure of Unionization Threat

In my second approach, I consider an alternative measure of unionization threat,

following the approach prevalent in existing literature (e.g., Podgursky 1986; Kahn and

Curme 1987). This measure for the threat of unionization is the industry-level union density.

In particular, this alternative measure is constructed, for each year, in the following manner:

,j altnumber of workers employed in industry j who are union membersthreat

number of workers employed in industry j

∧

= . (8)

In the second step, I run a regression of the logarithmic value of hourly wage on the

alternative measure of the union threat, controlling for various worker and firm specific

attributes. Hence, I estimate the following equation for the sample of union workers:

0 1ln( ) 'iU UAlt UAlt iUAlt iUAlt iUAltwage threat Xδ δ γ ε∧

= + + + . (9)

And similarly for non-union workers:

0 1ln( ) 'iN NAlt NAlt iNAlt iNAlt iNAltwage threat Xδ δ γ ε∧

= + + + . (10)

Theory suggests that 1 0NAltδ > , and 1 1 0NAlt UAltδ δ> ≥ .

4.3. Analysis by Private and Public Sector

The motivation for my third approach stems from the assumption that is necessary to

generate the central prediction—a positive effect of the threat of unionization on non-union

wage rates. Note that in deriving the main results, I assume that employers minimize the

expected wage costs. While this assumption is most likely valid for employers in the private

10

sector it may not be valid for employers in the public sector. I therefore follow my first

approach by using only the sample of workers who were employed in the private sector at the

time of a survey. I then compare the results to those obtained based on the sample of workers

who were employed in the public sector. Due to the abovementioned differences in the

maximization problem across employers in the public and private sectors, I expect that the

relation between the unionization threat and the non-union wages is likely to be stronger for

the sample of workers in the private sector.

4.4. Potential Problems

The first potential problem with the above models is the likely heteroscedasticity and

autocorrelation. When the variance of regression residuals depends on the explanatory

variables, serious consequences may occur for OLS and probit estimators. Although the OLS

estimators remain unbiased, the estimated standard errors are wrong. As a result, inferences

and hypotheses tests cannot be relied on. In the probit models, “the maximum likelihood

estimators are inconsistent and the covariance matrix is inappropriate” (Green, 2003; page

679). Therefore, I choose to compute and report heteroscedasticity-robust standard errors.

In addition, in the probit model, the coefficients cannot be interpreted as marginal

effects. Hence, I choose to compute and report marginal effects, which are a non-linear

combination of the regression coefficients. The marginal effects are obtained by calculating

the derivative of the outcome probability with respect to the control variables.

Autocorrelation might be another problem because nine years of data is used in the second

step. I decided to include indicator variables for each year. I also included interaction terms

that allow for the effect of various explanatory variables on wage to differ across years.

11

5. Description of Data and Variables

My analysis draws on monthly Labor Force Surveys (LFS) conducted by Statistics

Canada. I use data collected every January from the year 1998 to 2006. The overall pooled

sample consists of 432,574 observations after I drop observations because of missing

information on union membership or control variables. Among workers in my final sample

291,596 (67.4%) are non-union members and the rest 140,978 (32.6%) are union members;

112,767 (26.1%) are in the public sector and 319,807 (73.9%) in the private sector.

The choice of the independent variables is based on the review of the literature on

determinants of wages. Most importantly, the human capital theory suggests that the

workers’ productivity increases with the worker’s ability and acquired skills (Becker, 1993).

Wages are thereby expected to be correlated with the workers’ attained education (e.g.,

number of years spent in school) and other components of the workers’ human capital (age,

for instance, may measure acquired work experience). Other variables such as demographic

and industry characteristics which might affect the worker’s wage are also included, as

suggested by Lewis (1986). My choice of explanatory variables draws also on Belman and

Heywood (1990) who used race, gender, marital status, education, employment status,

location or region, and industry in their analysis of the effect of unionization on wage

dispersion. Following Farber’s (2005) model, other variables which might affect the worker’s

decision to join the union, such as firm size are also included.

6. Results

6. 1. Determinants of Union Membership in Canada, 1998-2006

The first step to assessing the effect of the threat of unionization on wages of union and

12

non-union workers entails constructing the measure for the unionization threat. As described

in Section 4.1., I estimate the probit model in order to obtain the predicted probability of

becoming a union member. The estimates are reported in Appendix B, Tables 3, 6, and 9.

Table 3 presents the results for the whole sample, while Tables 6 and 9 report results for

workers employed in the public sector and those employed in the private sector, respectively.

The marginal effects instead of the original coefficients are reported.

The results based on the most recent survey in 2006 suggest that both worker-specific

and employer-specific characteristics significantly affect the likelihood of being a union

member. The characteristics associated with a worker that are positively associated with the

likelihood of union membership are gender (male workers are more likely to be union

members) and age (older workers are more likely to be union members). Workers who are

married or have higher attained education, on the other hand, are less likely to be union

members. Firm characteristics also matter in terms of explaining the worker’s propensity to

join the union. For instance, employment in the public sector increases the probability of

being a union member by approximately 36.7% in 2006. Also, there exists a positive

correlation between the firm size and the probability of being a union member. The larger

the firm is, the higher the probability for the worker to become a union member. For instance,

workers employed in a firm with more than five hundred employees are 35.8% more likely to

be union members compared to those in the firm with less than 20 employees in 2006.

In addition, residents of Quebec, British Columbia, Manitoba, and Saskatchewan are

more likely to be union members, as compared to the Albertans. Moreover, industry

dummies are all significant in determining the probability of unionization. The results

suggest that the workers in industries that require lower skills or more labor work are more

13

likely to be unionized. Exceptions are the industries which are highly unionized from the

early days of unionization, for example, health care, education, and public administration.

Similar results, in terms of magnitude and sign, to those found in 2006 are found across

all nine years. However, differences are also found for some explanatory variables. For

instance, in 2000, workers residing in New Foundland, Nova Scotia, and British Columbia

were more likely to be union members compared to Albertan workers. In 1998, married

workers were more likely to be unionized than the unmarried workers. After 1999, the

marital status was negatively associated with the likelihood of union membership.

Separate results for public and private sectors are reported in Tables 6 and 9. For the

private sector, the estimates on major independent variables are similar, in terms of the

magnitudes and the signs, to the ones obtained from the whole sample. For workers in the

public sector, the estimates are different from those in the whole sample; for example, being

male decreases the probability of joining the union, whereas being married increases the

probability of being a union member.

6.2. The Effect of the Unionization Threat on Non-union Wage Rates

I start by analyzing results of the first approach in Section 4. In particular, this approach

uses the predicted probability obtained from the probit model as a measure for the threat of

unionization. The results are presented in Table 4 in Appendix B. Figure 2 in Appendix C

plots the main results reported in Table 4 based on the full sample. In particular, the Figure

plots the estimated coefficients of the threat effect on both the union and non-union wages by

year, organized in the following four panels. Panel A depicts the estimated marginal effects

of the threat effect on wages of union and non-union workers from the regression without the

14

industry and province dummies; Panel B reports the results in which province dummies are

included; in Panel C, controls for the industry are added; and finally, Panel D presents results

from in which the province and industry dummies are included.

As shown in Panel A in Figure 2, Appendix C, the estimates of marginal effects of the

predicted probability of unionization on non-union wages are approximately 30%. The

lowest estimate is at 29.5% in 1998 and the highest is at 34.9% in 2006. Compared to the

effects on non-union wage, those on the union wages are slightly higher, whereas the highest

effect is at 39.5% in 1998 and the lowest at 36% in 2001. In Panel B, in Figure 2, by

including the province dummies to wage regression, the estimated marginal effect of the

predicted probability of unionization on the non-union wages (ranges from 29.3 to 41.8%) is

still smaller compared to the effect on the union wages (ranges from 46.5 to 56.4%); but

effects still have an increasing trend. Figure 2 Panel C adds the industry dummies to the list

of explanatory variables in the wage regressions. The union threat effect on non-union wages

(ranges from 15.1% to 26.9 %) is now higher than that on the union wages (ranges from -2.5

to 23.2%), both showing a decreasing trend.

Finally, in Panel D, Figure 2, by controlling for both province and industry

characteristics, the threat effects are reduced. The estimates of marginal effects of the

unionization threat on the non-union and union wages are decreasing over the period from

27.3% to 24.8%; for instance, an increase in the probability of being a union member will

increase non-union wages by 27.3% in 1998 and by 24.8% in 2006. The threat effect on

union wages is at a lower range, decreasing from 25.9% and 13.2%. The results in both Panel

C and D are consistent with the theory’s predictions.

15

6.3. An Analysis of Unionization Threat in Private and Public Sectors

Estimation results for workers in the public and private sector are presented in Tables 7

and 10, and plotted in Figures 3 and 4. In the private sector, the threat effects on the non-

union wage range from 21.9% in 1998 to 14.9% in 2006. The within- and between-province

variation for the non-union wages is 39.3% to 40.6%, whereas the within- and between-

province and within-industry variation is 33.1% to 12.5%. The threat effects on the union

wages are smaller after controlling for industry. Figure 3 in the Appendix C suggests that

there is a decreasing trend in the threat effects in Panels C and D.

In the public sector, with the full set of control variables, an increase in the probability

of being a union member is estimated to increase non-union wages by 12% to 9%, and 14%

to 11% increase in union wages from 1998 to 2006 (see Figure 4 and Table 7). However,

with fewer controls in the wage regressions, the effects of unionization threat on the wages of

workers in the public sector (both unionized and non-unionized) are ambiguous, because the

signs on the coefficient of the threat are both positive and negative. One explanation for the

observed pattern is as follows. Namely, the private sector aims to minimize the expected

costs of wage payments, so the effects of unionization threat on wages are clear-cut. The

maximization problem for employers in the public sector is more ambiguous. Therefore, the

effect of unionization threat on the public workers’ wage rates cannot be determined.

In conclusion, using the predicted probability of becoming a union member as a

measure of the threat of unionization, I find that the threat effects on union and non-union

wages are both positive. However, the threat effects are higher for non-union workers in the

private sector, but not in the public sector. Importantly, I find this evidence to be sensitive to

the set of control variables that I include when estimating the wage regression.

16

6.4. An alternative Measure for Unionization Threat

In this section, I discuss the results obtained by using as an alternative measure of the

unionization threat. In particular, I use as a measure for the unionization threat an industry-

level union density. The results are reported in Tables 5, 8, and 11, for the full sample, for

workers in the public sector, and for workers in the private sector, respectively. The main

results as they pertain to the unionization threat effect on the union and the non-union wage

rates are depicted in Figures 5 through 7, for the full sample, the sample of workers in the

public sector, and the sample of workers in the private sector, respectively.

The alternative measure for the threat of unionization gives different results in terms of

the magnitude and sign of the threat effects over the years, as compared to the results

obtained when the threat measure was inferred from the probit model. The difference is

particularly pronounced for Panel D (see Figures 5 through 7 in the Appendix). For the whole

sample in Panel D, the threat effects on the non-union wages are greater than the effects on

the union workers only after 2002. Moreover, the threat effects turn negative after 2002. This

finding suggests that with an increase in the unionization threat, the wage rates actually

decrease. For the private sector, the threat effects on the non-union wage are greater then the

effects on the union wage only for 1998 and 1999 fro Panel D. The effects become negative

after 1999. The threat effects on non-union wage rates of public workers are only greater than

that on the union workers in 2000. The effects are negative throughout the nine year period.

7. Conclusion

Using both the predicted probability of being a union member and the industry-level

union density as measures for the threat of unionization, I provide evidence that suggests that

17

the threat of unionization can have a positive impact on wages of non-union workers in

Canada. In particular, an increase in the probability of being a union member is estimated to

result in a 14.9% increase in wages of non-union workers in the private sector, and 10.6% for

non-union workers in 2006 in Canada. The difference between these two percentage terms

measures the effect of the unionization threat on the union-wage gap.

The result supports the theoretical prediction that the threat of unionization has a

positive effect on the non-union wages in private sectors, and a positive or close to negligible

effect on that in public sectors. Further, the results can help explain why the threat of

unionization may tend to result in plant closures mostly in private sectors. More importantly,

though, my findings are shown to be very sensitive to the list of explanatory variables

included in the wage regressions as well as to the definition of the threat of unionization.

Upon restricting the sample to public and private sector, the results show that the threat

effects on the private sector are driving the results reported for the whole sample.

The results in this paper are of importance for several reasons. To my understanding of

the literature, this paper is the first study of the union threat effects on non-union wage rates

in Canada. While a growing literature has explored the union threat effect for the United

States and several European countries, studies using Canadian data have been thus far

restricted to estimating the union wage premium. The results obtained in this paper are

consistent with the theory for certain specifications but not for others. Hence, the conflicting

results reported in related literature regarding the union threat effect on the non-union wage

rates are reaffirmed in this study as well. Overall, the main conclusion I draw from my

analysis is that the effects of unionization threat are not clear cut.

18

References

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Dispersion of Wages”, The Review of Economics and Statistics, Vol. 72, No. 1, pp.

148-153.

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reference to education, Chicago and London: University of Chicago Press. Third

Edition, pp. 390.

Bianco, A. (2006) “No Union Please, We Are Wal-Mart”, Business Week, Feb.13, 2006.

Accessed at www.businessweek.com/magazine/content/06_07/b3971115.htm.

Blanchflower, D. (2006) “A Cross-Country Study of the Union Membership”, IZA

Working Paper. Accessed at http://ideas.repec.org/p/iza/izadps/dp2016.html.

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Corneo, G., and Lucifora, C. (1997) “Wage Information Under the Union Threat Effects:

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Farber, H. (2005) “Non-union Wage Rates and the Threat of Unionization”, Industrial

and Labor Relations Review, Vol. 58, No. 3, pp. 335-352.

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and Non-union Wages”, Review of Economics and Statistics, Vol. 63, No. 4, pp.

561-572.

Greene, W. H. (2003) Econometric Analysis. New Jersey: Prentice Hall. Fifth Edition.

19

Kahn, L., and Curme, M. (1987) “Union and Non-union Wage Dispersion”, The Review

of Economics and Statistics, Vol. 69, No. 4, pp. 600-607.

Kahn, L. M. (1978) “The Effect of Unions on the Earnings of Non-union Workers”,

Industrial and Labor Relations Review, Vol. 31, No. 2, pp. 205-216.

Kumar, P., and Stengos, T. (1985) “Measuring the Union Relative Wage Impact: A

Methodological Note”, Canadian Journal of Economics, Vol. 18, No. 1, pp. 182-

189.

Lewis, H. (1986) Union Relative Wage Effects: A Survey. Chicago: University of

Chicago Press, 1986.

Leue, C., and Tremblay, C. H. (1993) “A New Econometric Model of the Union Threat

Effects”, Applied Economics, Vol. 25, No. 10, pp. 1329-1336.

MacDonald, G., and Evans, J. C. (1981) “The Size and Structure of Union-Non-union

Wage Differentials in Canada”, Canadian Journal of Economics, Vol. 14, No. 2,

pp. 216-231.

Moore, W. J., and Newman, R. J., and Cunningham, J. (1985) “The Effect of the Extent

of Unionism on Union and Non-union Wages”, Journal of Labor Research, Vol.

6, No. 1, pp. 21-44.

Neumark, D., and Wachter, M. (1995) “Union Effects on Non-union Wages: Evidence

form Panel Data on Industries and Cities”, Industrial and Labor Relations Review,

Vol. 49, No. 2, pp. 20-38.

Pearce, J. (1990) “Tenure, Unions, and the Relationship between Employer Size and

Wages”, Journal of Labor Economics, Vol. 8, No. 2, pp. 251-269.

20

Podgursky, M. (1986) “Unions, Establishment Size, and Intra-Industry Threat Effects”,

Industrial and Labor Relations Review, Vol. 39, No. 2, pp. 277-284.

Rosen, S. (1969) “Trade Union Power, Threat Effects and the Extent of Organization”,

The Review of Economic Studies, Vol. 36, No. 2, pp. 185-196.

21

Appendix A

Table 1: Description of variables

1 The public sector includes employees in public administration at the federal, provincial and municipal levels, as well as in Crown corporations, liquor control boards and other government institutions such as schools (including universities), hospitals and public libraries. The private sector comprises all other employees and self-employed owners of businesses, and self-employed persons without businesses.

Variable Name Description

Hrlyearn Hourly wage before taxes and other deductions, including tips, commissions and bonuses (inferred from questions 205-209 in the Labor Force Survey).

Unionmbr Union status dummy is set to 1 if the worker is a union member and 0 otherwise (inferred from question 220 in the Labor Force Survey).

Public Public sector dummy is set to 1 if the worker works in the public sector and 0 otherwise (inferred from question 115 in the Labor Force Survey).1

Age15-24, Age 25-34, Age 35-44, Age 45-54

A set of age dummies indicating which age group the worker (i.e., the survey’s respondent) belongs to at the time of the survey (inferred from question ANC_Q03 in the Labor Force Survey).

Male Gender dummy is set to 1 if male and 0 otherwise (inferred from question Q01in the Labor Force Survey).

Married Marital status dummy is set to 1 if married and 0 otherwise (inferred from question MSNC_Q01 in the Labor Force Survey).

Hisch, Post, Univg

A set of dummy variables that identify the highest attained level of schooling at the time of the survey: 1 if no high school or grades<12 is the excluded group; 1 if high school graduates ( Hisch), some postsecondary (Post), university graduate (Univg) (inferred from question EDQ01-04 in the Labor Force Survey)

Nfld, pei, ns, nb, que, ont, man, sask, bc

A set of provincial dummies that identify survey respondent’s residence: New Foundland, P.E.I, Nova Scotia, New Brunswick, Quebec, Ontario, Manitoba, Saskatchewan, British Columbia.

Firmsize

A set of dummy variables that identify the size of a firm (in number of employees) at which a survey respondent worked at the time of the survey (inferred from question Q240 in the Labor Force Survey). The number of employees at all locations, in four categories: it is 1 if less than 20 employers, 2 if 20 to 99 employers, 3 if 100 to 500 employers, 4 if more than 500 employers.

In02, In03, In04, In05, In06, In07, In08, In09, In10, In11, In12, In13, In14, In15, In16, In17, In18

A set of industry dummy variables indicating the industry the worker works in: accordingly, the dummy variables represent Forestry, Fishing, Mining, Oil and Gas; Utilities; Construction; Manufacturing - durables; Manufacturing - non-durables; Wholesale Trade; Retail Trade; Transportation and Warehousing; Finance, Insurance, Real Estate and Leasing; Professional, Scientific and Technical Services; Management, Administrative and Other Support; Educational Services; Health Care and Social Assistance; Information, Culture and Recreation; Accommodation and Food Services; Other services; Public Administration (inferred from question 115 in the Labor Force Survey).

22

Table 2: Review of literature on the union threat effects

Author Period Country Survey Proxy for the Threat of Unionization Findings

Yi Zuo (this paper)

1998-2006 Canada Labor Force

Surveys

- Predicted probability of union membership as a function of worker, job, and firm characteristics

- Industry union density

- The union threat effect on non-union wage rate found in private sector only

- Results are sensitive to definition of the unionization threat and to a set of explanatory variables

Farber 1978-2002 U.S. CPS

- Predicted probability of being a union member as a function of worker, job, and firm characteristics

- The effect of the threat of unionization on the non-union wages is sensitive to set of explanatory variables

Pearce 1990 U.S. CPS - Industry-level percentage of employed with union membership

- The effect of industry-level unionization increases with firm size in the non-union sector

Leue and Tremblay

1979-1980 U.S. EOPP

- The percentage of three-digit industry employment organized in unions

- The probability that a firm is organized by a union

- No significant effect found of percentage organized and the predicted threat of unionization on non-union wages

Neumark and Wachter

1973-1989 U.S. CPS

- Industry-level percentage of employed organized in unions

- City-level percentage of employed organized in unions

- At the industry level, an increase in the percentage organized reduces the non-union industry wage differential

- At the city level, an increase in the percentage organized in union increases the non-union city wage differential

Moore, Newman, and Cunningham

1973-1979 U.S. CPS

- Industry-level union membership rate - Occupation-level union membership

rate

- Unionization in an industry with fewer union members has a significant positive wage effect on non-union workers

- Unionization within an occupation has no wage effect on non-union workers

Podgursky 1979 U.S. CPS - Proportion of an industry’s production workers covered by union contracts

- Large and small non-union employers tend to respond less to the union threat

- Wage at medium-sized non-union employers increases with the union threat

23

Table 2 (Continued)

Author Period Country Survey Proxy for the Threat of Unionization Findings

Freeman and Medoff

1973-1975 U.S. CPS and EEC - Industry-level percentage of employed

covered by collective agreement

- Non-union workers in highly organized markets receive higher wages than those in less unionized industries

- In manufacturing, the threat has a strong positive effect on union wages, but no or a weak effect on non-union wages

Kahn 1967 U.S. SEO - Industry-level union membership rate - Occupation-level union membership

rate

- For occupations which are not organized unionization threat has strong impact on non-union wages

- For occupations which are highly unionized, the within occupation-industry union effect on non-union wages is negative

Rosen 1958 U.S. Census of Manufactures

- Three union dummies based on the percentage organized in union

- Non-union workers with below-median earnings receive higher wages with unionization, except for managers and professionals

Heywood and Belfield 1997 U.K. Labor Force

Survey - Industry-level union coverage - Non-union workers with below-median earnings receive

higher wages with unionization, except for managers and professionals

Corneo and Lucifora 1990 Italy Fedemecanica

Survey - Firm-level union density - Threat effects are strongly correlated with union density - Threat effects on wages are significant with an

intermediate level of union density Abbreviation used in Table 2: CPS - Current Population Survey; EOPP - Employment Opportunity Pilot Project; EEC - Expenditures for Employee Compensation Surveys; SEO - Survey of Economic Opportunity.

24

Appendix B Estimation Results

Table 3: Determinants of union membership in Canada, 1998 – 2006 (all sample)

Dataset: Canadian Labor Force Survey Sample: All observations: Analysis by year 2006 2005 2004 2003 2002 2001 2000 1999 1998 Marginal

effect (S.E.)

Marginal effect (S.E.)








Variable name: (1) (2) (3) (4) (5) (6) (7) (8) (9) Public 0.367 0.399 0.361 0.387 0.393 0.323 0.332 0.319 0.303 (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** Male 0.045 0.030 0.046 0.035 0.046 0.050 0.052 0.060 0.051 (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** Married -0.013 -0.011 0.001 -0.014 -0.005 -0.006 -0.013 0.000 0.011 (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000) (0.000)*** Age base category: Age 55 + … … … … … … … … … … … … … … … … … … Age between 15 and 24 -0.117 -0.098 -0.101 -0.119 -0.121 -0.130 -0.153 -0.120 -0.136 (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.001)*** (0.001)*** Age between 25 and 34 -0.028 -0.047 -0.029 -0.039 -0.050 -0.050 -0.050 -0.030 -0.028 (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.001)*** (0.001)*** (0.001)*** Age between 35 and 44 0.001 -0.008 -0.005 -0.012 -0.002 -0.006 -0.008 0.008 -0.001 (0.000) (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.001)*** (0.001)*** (0.001)*** (0.001)** Age between 45 and 54 0.032 0.018 0.022 0.026 0.015 0.022 0.018 0.030 0.039 (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** High school dropout (excluded group) … … … … … … … … … … … … … … … … … … 11 to 13 years of schooling/graduate -0.009 -0.020 -0.020 -0.022 -0.005 -0.022 -0.014 -0.012 -0.027 (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** At least some postsecondary diploma -0.043 -0.034 -0.041 -0.043 -0.020 -0.032 -0.026 -0.036 -0.041 (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** University: bachelors or graduate degree -0.122 -0.122 -0.141 -0.132 -0.123 -0.130 -0.118 -0.123 -0.139 (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)***

25

Table 3 (Continued)

Dataset: Canadian Labor Force Survey Sample: All observations: Analysis by year 2006 2005 2004 2003 2002 2001 2000 1999 1998 Marginal

effect (S.E.)









Variable name: (1) (2) (3) (4) (5) (6) (7) (8) (9) … … … … … … … … … Firm with less than 20 employees (base) … … … … … … … … …

Firm with 20-99 employees 0.187 0.226 0.221 0.208 0.228 0.207 0.216 0.233 0.234 (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** Firm with 100-500 employees 0.343 0.368 0.382 0.376 0.351 0.364 0.384 0.385 0.371 (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** Firm with more than 500 employees 0.358 0.374 0.383 0.394 0.394 0.382 0.399 0.409 0.396 (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** Additional control variables: Industry X X X X X X X X X Province X X X X X X X X X Observations 50085 49634 46846 49461 48268 48485 46963 47036 45798 Pseudo R-squared 0.316 0.316 0.313 0.323 0.326 0.314 0.303 0.318 0.305

Robust standard errors in parentheses *significant at 10%; ** significant at 5%; *** significant at 1%

26

Table 4: Effect of predicted probability of unionization on union/non-union wage rates, 1998 – 2006 (all sample)

Dataset: Canadian Labor Force Survey Panel A-No control for

industry or province Panel B-Control for

province Panel C-Control for

industry

Panel D-Control for both industry and

province Sample: Non-union

workers Union

workers Non-union

workers Union

workers Non-union

workers Union

workers Non-union

workers Union

workers Coefficient

(S.E.) Coefficient

(S.E.) Coefficient

(S.E.) Coefficient

(S.E.) Coefficient

(S.E.) Coefficient

(S.E.) Coefficient

(S.E.) Coefficient

(S.E.) Variable name: (1) (2) (3) (4) (5) (6) (7) (8) The threat of unionization in 2006 0.349 0.376 0.418 0.564 0.151 -0.025 0.248 0.132 (0.017)*** (0.019)*** (0.017)*** (0.021)*** (0.022)*** (-0.026) (0.025)*** (0.049)*** The threat of unionization in 2005 0.338 0.375 0.398 0.548 0.182 0.003 0.264 0.142 (0.015)*** (0.016)*** (0.016)*** (0.018)*** (0.019)*** (-0.022) (0.021)*** (0.040)*** The threat of unionization in 2004 0.370 0.394 0.415 0.553 0.210 0.041 0.278 0.165 (0.014)*** (0.015)*** (0.014)*** (0.017)*** (0.017)*** (0.019)** (0.019)*** (0.035)*** The threat of unionization in 2003 0.326 0.376 0.360 0.514 0.197 0.068 0.249 0.171 (0.013)*** (0.014)*** (0.013)*** (0.015)*** (0.015)*** (0.017)*** (0.016)*** (0.029)*** The threat of unionization in 2002 0.315 0.366 0.341 0.486 0.214 0.085 0.257 0.168 (0.013)*** (0.013)*** (0.013)*** (0.014)*** (0.015)*** (0.016)*** (0.016)*** (0.027)*** The threat of unionization in 2001 0.321 0.360 0.345 0.480 0.236 0.112 0.274 0.192 (0.013)*** (0.014)*** (0.013)*** (0.015)*** (0.015)*** (0.017)*** (0.016)*** (0.029)*** The threat of unionization in 2000 0.329 0.380 0.340 0.485 0.261 0.161 0.283 0.222 (0.014)*** (0.015)*** (0.014)*** (0.016)*** (0.017)*** (0.019)*** (0.018)*** (0.035)*** The threat of unionization in 1999 0.324 0.374 0.333 0.456 0.268 0.193 0.287 0.235 (0.015)*** (0.016)*** (0.015)*** (0.018)*** (0.018)*** (0.022)*** (0.020)*** (0.040)*** The threat of unionization in 1998 0.295 0.395 0.293 0.465 0.269 0.232 0.273 0.259 (0.016)*** (0.019)*** (0.016)*** (0.021)*** (0.021)*** (0.026)*** (0.023)*** (0.049)*** Public sector -0.003 -0.099 0.024 -0.092 -0.026 -0.047 -0.003 -0.026 -0.009 (0.008)*** (0.009)*** (0.009)*** (0.011)** (0.011)*** (-0.012) (-0.019) Male 0.250 0.174 0.252 0.170 0.217 0.137 0.219 0.138 (0.003)*** (0.004)*** (0.003)*** (0.004)*** (0.003)*** (0.005)*** (0.003)*** (0.005)*** Married 0.099 0.045 0.105 0.048 0.085 0.038 0.091 0.042 (0.004)*** (0.004)*** (0.004)*** (0.004)*** (0.004)*** (0.004)*** (0.004)*** (0.004)*** Age base category: Age 55 + … … … … … … … … … … … … … … … …

27

Table 4 (Continued)




industry



workers Union

workers Non-union

workers Union

workers Non-union

workers Union

workers Non-union

workers Union

workers Coefficient

(S.E.) Coefficient

(S.E.) Coefficient

(S.E.) Coefficient

(S.E.) Coefficient

(S.E.) Coefficient

(S.E.) Coefficient

(S.E.) Coefficient

(S.E.) Variable name: (1) (2) (3) (4) (5) (6) (7) (8) Age between 15 and 24 -0.367 -0.39 -0.358 -0.364 -0.321 -0.374 -0.313 -0.358 (0.008)*** (0.012)*** (0.008)*** (0.012)*** (0.008)*** (0.011)*** (0.008)*** (0.013)*** Age between 25 and 34 -0.105 -0.123 -0.095 -0.110 -0.103 -0.129 -0.094 -0.118 (0.008)*** (0.008)*** (0.007)*** (0.008)*** (0.007)*** (0.008)*** (0.007)*** (0.008)*** Age between 35 and 44 0.017 -0.033 0.025 -0.022 0.008 -0.039 0.016 -0.030 (0.008)** (0.007)*** (0.007)*** (0.007)*** (-0.007) (0.007)*** (0.007)** (0.007)*** Age between 45 and 54 0.042 -0.001 0.050 0.005 0.037 -0.003 0.045 0.004 (0.008)*** (-0.007) (0.008)*** (-0.007) (0.008)*** (-0.007) (0.007)*** (-0.007) High school dropout (excluded group) … … … … … … … … … … … … … … … … 11 to 13 years of schooling/graduate 0.153 0.123 0.141 0.111 0.136 0.123 0.125 0.109 (0.005)*** (0.006)*** (0.004)*** (0.006)*** (0.004)*** (0.006)*** (0.004)*** (0.006)*** At least some postsecondary diploma 0.251 0.206 0.241 0.203 0.217 0.203 0.209 0.197 (0.004)*** (0.006)*** (0.004)*** (0.005)*** (0.004)*** (0.006)*** (0.004)*** (0.006)*** University: bachelors or graduate degree 0.554 0.463 0.531 0.458 0.495 0.453 0.476 0.443 (0.006)*** (0.007)*** (0.006)*** (0.007)*** (0.007)*** (0.008)*** (0.007)*** (0.011)***

… … … … … … … … Firm with less than 20 employees (base) … … … … … … … …

Firm with 20-99 employees 0.067 -0.081 0.058 -0.092 0.062 -0.029 0.053 -0.031 (0.005)*** (0.012)*** (0.005)*** (0.012)*** (0.005)*** (0.013)** (0.005)*** (0.015)** Firm with 100-500 employees 0.087 -0.094 0.075 -0.113 0.072 -0.029 0.062 -0.033 (0.006)*** (0.013)*** (0.006)*** (0.013)*** (0.006)*** (0.014)** (0.007)*** (-0.021) Firm with more than 500 employees 0.123 -0.057 0.107 -0.09 0.114 0.012 0.100 -0.001 (0.005)*** (0.013)*** (0.005)*** (0.013)*** (0.006)*** (-0.015) (0.007)*** (-0.025)

28

Table 4 (Continued)




industry



workers Union

workers Non-union

workers Union

workers Non-union

workers Union

workers Non-union

workers Union

workers Coefficient

(S.E.) Coefficient

(S.E.) Coefficient

(S.E.) Coefficient

(S.E.) Coefficient

(S.E.) Coefficient

(S.E.) Coefficient

(S.E.) Coefficient

(S.E.) Variable name: (1) (2) (3) (4) (5) (6) (7) (8) Additional control variables: Industry X X X X Province X X X X Year X X X X X X X X Interaction terms with year X X X X X X X X Constant 2.039 2.453 2.082 2.464 2.001 2.403 2.043 2.425 (0.007)*** (0.012)*** (0.008)*** (0.013)*** (0.013)*** (0.038)*** (0.013)*** (0.039)*** Observations 291596 140978 291596 140978 291596 140978 291596 140978 Adjusted R-squared 0.412 0.328 0.443 0.362 0.472 0.375 0.499 0.407

Robust standard errors in parentheses * significant at 10%; ** significant at 5%; *** significant at 1%

29

Table 5: Effect of union density on union/non-union wage rates, 1998 – 2006 (All sample)

Dataset: Canadian Labor Force Survey Panel A Panel B Panel C Panel D Sample: Non-union

workers Union

workers Non-union

workers Union

workers Non-union

workers Union

workers Non-union

workers Union

workers Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient

(S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) Variable name: (1) (2) (3) (4) (5) (6) (7) (8) Industry-level union density in 2006 0.234 0.373 0.279 0.337 -0.167 -0.206 -0.132 -0.204 (0.001)*** (0.001)*** (0.013)*** (0.017)*** (0.153) (0.145) (0.148) (0.142) Industry-level union density in 2005 0.251 0.340 0.291 0.320 -0.101 -0.153 -0.071 -0.145 (0.001)*** (0.001)*** (0.013)*** (0.015)*** (0.127) (0.117) (0.124) (0.114) Industry-level union density in 2004 0.271 0.331 0.313 0.325 -0.069 -0.118 -0.046 -0.107 (0.001)*** (0.001)*** (0.012)*** (0.016)*** (0.103) (0.101) (0.100) (0.098) Industry-level union density in 2003 0.235 0.350 0.277 0.301 -0.065 -0.070 -0.046 -0.060 (0.001)*** (0.001)*** (0.012)*** (0.014)*** (0.082) (0.081) (0.080) (0.079) Industry-level union density in 2002 0.224 0.324 0.282 0.308 -0.023 -0.020 -0.009 -0.009 (0.001)*** (0.001)*** (0.012)*** (0.014)*** (0.064) (0.069) (0.062) (0.066) Industry-level union density in 2001 0.235 0.331 0.299 0.286 0.016 0.020 0.028 0.035 (0.001)*** (0.001)*** (0.012)*** (0.015)*** (0.055) (0.065) (0.052) (0.062) Industry-level union density in 2000 0.260 0.326 0.297 0.317 0.034 0.057 0.038 0.084 (0.001)*** (0.001)*** (0.012)*** (0.016)*** (0.055) (0.074) (0.052) (0.071) Industry-level union density in 1999 0.273 0.284 0.296 0.239 0.077 0.086 0.081 0.108 (0.001)*** (0.001)*** (0.012)*** (0.016)*** (0.069) (0.084) (0.066) (0.081) Industry-level union density in 1998 0.254 0.347 0.270 0.295 -0.167 -0.206 -0.132 -0.204 (0.001)*** (0.001)*** (0.013)*** (0.016)*** (-0.088) (0.103)* (-0.085) (0.099)** Public sector 0.020 -0.002 0.039 0.005 0.068 0.034 0.087 0.056 (0.000)*** (0.000)*** (0.007)*** -0.005 (0.008)*** (0.006)*** (0.008)*** (0.006)*** Male 0.237 0.183 0.262 0.192 0.228 0.152 0.230 0.153 (0.000)*** (0.000)*** (0.003)*** (0.004)*** (0.003)*** (0.004)*** (0.003)*** (0.004)*** Married 0.091 0.049 0.104 0.050 0.086 0.037 0.092 0.042 (0.000)*** (0.000)*** (0.004)*** (0.004)*** (0.004)*** (0.004)*** (0.004)*** (0.004)*** Age base category: Age 55 + … … … … … … … … … … … … … … … … Age between 15 and 24 -0.399 -0.432 -0.381 -0.438 -0.351 -0.412 -0.342 -0.400 (0.000)*** (0.001)*** (0.008)*** (0.011)*** (0.007)*** (0.011)*** (0.007)*** (0.010)*** Age between 25 and 34 -0.107 -0.137 -0.103 -0.129 -0.113 -0.138 -0.103 -0.129 (0.000)*** (0.001)*** (0.007)*** (0.008)*** (0.007)*** (0.008)*** (0.007)*** (0.007)***

30

Table 5 (Continued)

Panel A Panel B Panel C Panel D Sample: Non-union

workers Union

workers Non-union

workers Union

workers Non-union

workers Union

workers Non-union

workers Union


(S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) Variable name: (1) (2) (3) (4) (5) (6) (7) (8) Age between 35 and 44 0.020 -0.028 0.024 -0.024 0.007 -0.039 0.015 -0.029 (0.000)*** (0.000)*** (0.007)*** (0.007)*** -0.007 (0.007)*** (0.007)** (0.007)*** Age between 45 and 54 0.046 0.014 0.055 0.017 0.044 0.006 0.051 0.012 (0.000)*** (0.000)*** (0.008)*** (0.007)** (0.008)*** (-0.007) (0.007)*** (0.007)* High school dropout (excluded group) … … … … … … … … … … … … … … … … 11 to 13 years of schooling/graduate 0.161 0.117 0.136 0.098 0.132 0.117 0.121 0.104 (0.000)*** (0.000)*** (0.004)*** (0.006)*** (0.004)*** (0.006)*** (0.004)*** (0.006)*** At least some postsecondary diploma 0.255 0.196 0.232 0.188 0.211 0.194 0.204 0.188 (0.000)*** (0.000)*** (0.004)*** (0.006)*** (0.004)*** (0.006)*** (0.004)*** (0.005)*** University: bachelors or graduate degree 0.524 0.385 0.496 0.384 0.467 0.416 0.449 0.404 (0.000)*** (0.000)*** (0.006)*** (0.007)*** (0.006)*** (0.007)*** (0.006)*** (0.007)***

… … … … … … … … Firm with less than 20 employees (base) … … … … … … … …

Firm with 20-99 employees 0.083 -0.034 0.080 -0.017 0.087 0.014 0.079 0.016 (0.000)*** (0.001)*** (0.004)*** (-0.012) (0.004)*** (-0.012) (0.004)*** (-0.011) Firm with 100-500 employees 0.129 -0.013 0.124 0.018 0.124 0.046 0.115 0.048 (0.000)*** (0.001)*** (0.005)*** (-0.011) (0.005)*** (0.011)*** (0.005)*** (0.011)*** Firm with more than 500 employees 0.193 0.055 0.180 0.075 0.186 0.108 0.172 0.103 (0.000)*** (0.001)*** (0.004)*** (0.010)*** (0.004)*** (0.011)*** (0.004)*** (0.010)*** Additional control variables: Industry X X X X Province X X X X Year X X X X X X X X Interaction terms with year X X X X X X X X Constant 2.06 2.399 2.029 2.358 2.004 2.362 2.031 2.346 (0.000)*** (0.001)*** (0.009)*** (0.014)*** (0.013)*** (0.038)*** (0.014)*** (0.038)*** Observations 291596 140978 291596 140978 291596 140978 291596 140978 Adjusted R-squared 0.403 0.340 0.446 0.360 0.472 0.375 0.498 0.406


31

Table 6: Determinants of union membership in Canada, 1998 – 2006 (Public Sector)

Dataset: Canadian Labor Force Survey Sample: All observations: Analysis by year 2006 2005 2004 2003 2002 2001 2000 1999 1998

Marginal effect

Marginal effect

Marginal effect

Marginal effect

Marginal effect

Marginal effect

Marginal effect

Marginal effect

Marginal effect

(S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) Variable name: (1) (2) (3) (4) (5) (6) (7) (8) (9) Male -0.046 -0.052 -0.037 -0.053 -0.046 -0.027 -0.039 -0.005 -0.035 (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** Married 0.016 -0.005 0.005 -0.012 0.003 0.000 -0.011 -0.005 0.047 (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (-0.001) (0.001)*** (0.001)*** (0.001)*** Age base category: Age 55 + … … … … … … … … … … … … … … … … … … Age between 15 and 24 -0.234 -0.212 -0.168 -0.244 -0.295 -0.287 -0.354 -0.26 -0.317 (0.001)*** (0.002)*** (0.002)*** (0.002)*** (0.002)*** (0.002)*** (0.002)*** (0.002)*** (0.002)*** Age between 25 and 34 0.033 0.007 0.036 -0.004 -0.031 0.008 0.008 0.056 -0.011 (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** Age between 35 and 44 0.044 0.045 0.030 -0.005 0.017 0.028 0.024 0.079 0.011 (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** Age between 45 and 54 0.042 0.021 0.040 0.026 0.010 0.017 0.029 0.075 0.06 (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** High school dropout (excluded group) … … … … … … … … … … … … … … … … … … 11 to 13 years of schooling/graduate 0.027 0.031 0.031 0.006 0.069 0.027 0.016 0.003 0.028 (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** At least some postsecondary diploma 0.007 0.032 0.035 0.015 0.064 0.049 0.012 0.034 0.03 (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** University: bachelors or graduate degree -0.059 -0.049 -0.053 -0.067 -0.012 -0.047 -0.082 -0.038 -0.059 (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** Firm with less than 20 employees (base) … … … … … … … … … … … … … … … … … … Firm with 20-99 employees 0.136 0.166 0.160 0.172 0.165 0.189 0.225 0.205 0.207 (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** Firm with 100-500 employees 0.236 0.229 0.251 0.249 0.226 0.262 0.307 0.273 0.285 (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)***

32

Table 6 (Continued)


Marginal effect

Marginal effect

Marginal effect

Marginal effect

Marginal effect

Marginal effect

Marginal effect

Marginal effect

Marginal effect

(S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) Variable name: (1) (2) (3) (4) (5) (6) (7) (8) (9) Firm with more than 500 employees 0.415 0.426 0.451 0.482 0.423 0.439 0.498 0.454 0.431 (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** Additional control variables: X X X X X X X X X Industry X X X X X X X X X Province X X X X X X X X X Observations 13081 12913 12569 12849 12512 12568 12193 12030 12054 Pseudo R-squared 0.097 0.090 0.088 0.092 0.104 0.094 0.102 0.099 0.101 Robust standard errors in parentheses * Significant at 10%; ** significant at 5%; *** significant at 1%.

33

Table 7: Effect of predicted probability of unionization on union/non-union wage rates, 1998 – 2006 (Public Sector) Dataset: Canadian Labor Force Survey Panel A-No control for



industry Panel D-Control for both

industry and province Sample: Non-union

workers Union

workers Non-union

workers Union

workers Non-union

workers Union

workers Non-union

workers Union

workers Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Variable name: (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (1) (2) (3) (4) (5) (6) (7) (8) The threat of unionization in 2006 -0.276 -0.324 -0.262 -0.281 -0.250 -0.250 0.113 0.099 (0.059)*** (0.036)*** (0.069)*** (0.042)*** (0.075)*** (0.043)*** (-0.121) (-0.074) The threat of unionization in 2005 -0.355 -0.274 -0.348 -0.222 -0.290 -0.240 0.066 0.106 (0.054)*** (0.034)*** (0.063)*** (0.040)*** (0.066)*** (0.038)*** (-0.107) (-0.065) The threat of unionization in 2004 -0.260 -0.142 -0.260 -0.071 -0.200 -0.124 0.134 0.215 (0.050)*** (0.035)*** (0.056)*** (0.039)* (0.058)*** (0.038)*** (-0.089) (0.058)*** The threat of unionization in 2003 -0.284 -0.144 -0.302 -0.107 -0.187 -0.118 0.114 0.160 (0.044)*** (0.032)*** (0.048)*** (0.034)*** (0.051)*** (0.034)*** (-0.076) (0.050)*** The threat of unionization in 2002 -0.351 -0.202 -0.368 -0.150 -0.230 -0.177 0.073 0.092 (0.041)*** (0.029)*** (0.045)*** (0.031)*** (0.047)*** (0.030)*** (-0.07) (0.045)** The threat of unionization in 2001 -0.229 -0.188 -0.247 -0.084 -0.116 -0.201 0.183 0.112 (0.043)*** (0.032)*** (0.047)*** (0.035)** (0.050)** (0.034)*** (0.073)** (0.049)** The threat of unionization in 2000 -0.333 -0.198 -0.351 -0.109 -0.200 -0.173 0.078 0.084 (0.044)*** (0.030)*** (0.049)*** (0.033)*** (0.052)*** (0.032)*** (-0.077) (0.049)* The threat of unionization in 1999 -0.202 -0.113 -0.238 -0.040 -0.055 -0.116 0.205 0.115 (0.049)*** (0.033)*** (0.055)*** (-0.038) (-0.058) (0.037)*** (0.088)** (0.058)** The threat of unionization in 1998 -0.317 -0.109 -0.339 0.005 -0.151 -0.106 0.141 0.144 (0.056)*** (0.035)*** (0.066)*** (-0.043) (0.069)** (0.039)*** (-0.108) (0.067)** Public Sector 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) Male 0.211 0.117 0.206 0.118 0.188 0.101 0.190 0.103 (0.011)*** (0.005)*** (0.011)*** (0.005)*** (0.011)*** (0.005)*** (0.011)*** (0.006)*** Married 0.092 0.031 0.100 0.037 0.084 0.028 0.087 0.034 (0.012)*** (0.005)*** (0.012)*** (0.005)*** (0.012)*** (0.005)*** (0.012)*** (0.005)*** Age base category: Age 55 + … … … … … … … … … … … … … … … … Age between 15 and 24 -0.551 -0.412 -0.560 -0.376 -0.489 -0.410 -0.410 -0.333 (0.028)*** (0.020)*** (0.030)*** (0.021)*** (0.031)*** (0.021)*** (0.040)*** (0.027)***

34

Table 7 (Continued)




industry Panel D-Control for both industry and


workers Union

workers Non-union

workers Union

workers Non-union

workers Union

workers Non-union

workers Union

workers Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) Variable name: (1) (2) (3) (4) (5) (6) (7) (8) Age between 25 and 34 -0.195 -0.142 -0.189 -0.136 -0.199 -0.144 -0.194 -0.139 (0.022)*** (0.010)*** (0.021)*** (0.010)*** (0.022)*** (0.010)*** (0.022)*** (0.010)*** Age between 35 and 44 0.005 -0.034 0.009 -0.029 -0.009 -0.038 -0.013 -0.036 (-0.020) (0.010)*** (-0.020) (0.009)*** (-0.021) (0.010)*** (-0.021) (0.009)*** Age between 45 and 54 0.091 0.016 0.093 0.014 0.078 0.015 0.066 0.008 (0.021)*** (0.010)* (0.021)*** (-0.009) (0.021)*** (-0.010) (0.021)*** (-0.010) High school dropout (excluded group) … … … … … … … … … … … … … … … … 11 to 13 years of schooling/graduate 0.220 0.152 0.211 0.130 0.213 0.151 0.197 0.129 (0.021)*** (0.010)*** (0.020)*** (0.010)*** (0.021)*** (0.010)*** (0.020)*** (0.010)*** At least some postsecondary diploma 0.364 0.268 0.352 0.251 0.355 0.269 0.330 0.248 (0.018)*** (0.009)*** (0.017)*** (0.008)*** (0.018)*** (0.009)*** (0.018)*** (0.009)*** University: bachelors or graduate degree 0.611 0.498 0.587 0.481 0.633 0.501 0.623 0.495 (0.019)*** (0.009)*** (0.019)*** (0.009)*** (0.020)*** (0.010)*** (0.020)*** (0.010)*** Firm with less than 20 employees (base) … … … … … … … … … … … … … … … … Firm with 20-99 employees 0.220 0.059 0.231 0.030 0.176 0.066 0.097 -0.004 (0.024)*** (0.021)*** (0.026)*** (-0.022) (0.026)*** (0.022)*** (0.036)*** (-0.027) Firm with 100-500 employees 0.289 0.109 0.301 0.060 0.233 0.118 0.125 0.019 (0.028)*** (0.022)*** (0.033)*** (0.024)** (0.032)*** (0.024)*** (0.048)*** (-0.034) Firm with more than 500 employees 0.378 0.143 0.386 0.082 0.297 0.146 0.170 0.032 (0.029)*** (0.022)*** (0.034)*** (0.025)*** (0.034)*** (0.024)*** (0.054)*** (-0.037)

35

Table 7 (Continued) Dataset: Canadian Labor Force Survey Panel A-No control for



industry Panel D-Control for both

industry and province Sample: Non-union

workers Union

workers Non-union

workers Union

workers Non-union

workers Union

workers Non-union

workers Union

workers Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) Variable name: (1) (2) (3) (4) (5) (6) (7) (8) Additional control variables: Industry X X X X Province X X X X Year X X X X X X X X Interaction terms with year X X X X X X X X Constant 2.171 2.489 2.149 2.419 2.646 2.516 2.503 2.401 (0.036)*** (0.027)*** (0.038)*** (0.028)*** (0.225)*** (0.109)*** (0.251)*** (0.103)*** Observations 31790 80977 31790 80977 31790 80977 31790 80977 Adjusted R-squared 0. 417 0.273 0.441 0 .313 0.434 0. 286 0. 459 0. 325

Robust standard errors in parentheses. * Significant at 10%; ** significant at 5%; *** significant at 1%

36

Table 8: Effect of union density on union/non-union wages, 1998 – 2006 (Public Sector)


workers Union

workers Non-union

workers Union

workers Non-union

workers Union

workers Non-union

workers Union


(S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) Variable name: (1) (2) (3) (4) (5) (6) (7) (8) Industry-level union density in 2006 -0.066 -0.211 -0.069 -0.154 -0.474 -0.292 -0.436 -0.266 (0.005)*** (0.003)*** (-0.071) (0.044)*** (0.183)*** (0.096)*** (0.177)** (0.093)*** Industry-level union density in 2005 -0.017 -0.146 -0.005 0.002 -0.456 -0.230 -0.414 -0.188 (0.005)*** (0.003)*** (-0.085) (-0.052) (0.194)** (0.108)** (0.187)** (0.104)* Industry-level union density in 2004 0.043 0.003 0.061 0.077 -0.182 -0.087 -0.154 -0.047 (0.004)*** (-0.003) (-0.066) (0.045)* (-0.121) (-0.078) (-0.117) (-0.074) Industry-level union density in 2003 -0.182 -0.002 -0.154 0.000 -0.430 -0.141 -0.370 -0.120 (0.006)*** (-0.004) (0.093)* (-0.054) (0.158)*** (-0.092) (0.153)** (-0.090) Industry-level union density in 2002 -0.096 -0.028 -0.023 0.057 -0.240 -0.102 -0.217 -0.063 (0.005)*** (0.003)*** (-0.071) (-0.050) (0.128)* (-0.082) (0.123)* (-0.079) Industry-level union density in 2001 0.145 -0.055 0.043 -0.090 -0.105 -0.256 -0.062 -0.224 (0.005)*** (0.004)*** (-0.078) (-0.055) (-0.154) (0.093)*** (-0.151) (0.091)** Industry-level union density in 2000 -0.356 -0.165 -0.319 -0.144 -0.338 -0.227 -0.311 -0.174 (0.007)*** (0.004)*** (0.092)*** (0.052)*** (0.194)* (0.102)** (0.188)* (0.098)* Industry-level union density in 1999 0.010 0.006 -0.131 0.018 -0.081 -0.007 -0.078 -0.006 (0.006)* (0.004)* (-0.089) (-0.052) (-0.202) (-0.114) (-0.198) (-0.110) Industry-level union density in 1998 -0.122 0.348 -0.217 0.227 -0.185 0.159 -0.127 0.184 (0.007)*** (0.004)*** (0.099)** (0.054)*** (-0.264) (-0.138) (-0.260) (-0.132) Male 0.198 0.114 0.214 0.117 0.190 0.102 0.187 0.101 (0.001)*** (0.000)*** (0.010)*** (0.005)*** (0.011)*** (0.005)*** (0.011)*** (0.005)*** Married 0.090 0.030 0.095 0.037 0.081 0.028 0.089 0.036 (0.001)*** (0.000)*** (0.012)*** (0.005)*** (0.012)*** (0.005)*** (0.012)*** (0.005)*** Age base category: Age 55 + … … … … … … … … … … … … … … … … Age between 15 and 24 -0.491 -0.385 -0.466 -0.371 -0.454 -0.372 -0.454 -0.371 (0.002)*** (0.001)*** (0.023)*** (0.017)*** (0.024)*** (0.018)*** (0.023)*** (0.017)*** Age between 25 and 34 -0.215 -0.143 -0.188 -0.133 -0.196 -0.144 -0.191 -0.139 (0.001)*** (0.001)*** (0.021)*** (0.010)*** (0.022)*** (0.010)*** (0.021)*** (0.010)***

37

Table 8 (Continued)


workers Union

workers Non-union

workers Union

workers Non-union

workers Union

workers Non-union

workers Union


(S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) Variable name: (1) (2) (3) (4) (5) (6) (7) (8) Age between 35 and 44 -0.013 -0.029 0.004 -0.026 -0.008 -0.040 -0.006 -0.033 (0.001)*** (0.001)*** (-0.020) (0.009)*** (-0.02) (0.009)*** (-0.020) (0.009)*** Age between 45 and 54 0.080 0.015 0.079 0.015 0.075 0.011 0.075 0.013 (0.001)*** (0.001)*** (0.020)*** (0.009)* (0.021)*** (-0.009) (0.020)*** (-0.009) High school dropout (excluded group) … … … … … … … … … … … … … … … … 11 to 13 years of schooling/graduate 0.214 0.148 0.206 0.131 0.212 0.149 0.199 0.130 (0.001)*** (0.001)*** (0.020)*** (0.010)*** (0.021)*** (0.010)*** (0.020)*** (0.009)*** At least some postsecondary diploma 0.352 0.258 0.343 0.250 0.351 0.263 0.335 0.251 (0.001)*** (0.001)*** (0.017)*** (0.008)*** (0.018)*** (0.009)*** (0.017)*** (0.008)*** University: bachelors or graduate degree 0.592 0.480 0.602 0.476 0.639 0.505 0.615 0.488 (0.001)*** (0.001)*** (0.019)*** (0.009)*** (0.019)*** (0.010)*** (0.019)*** (0.009)*** Firm with less than 20 employees (base) … … … … … … … … … … … … … … … … Firm with 20-99 employees 0.146 -0.002 0.140 0.030 0.144 0.031 0.142 0.035 (0.001)*** (-0.001) (0.018)*** (0.018)* (0.019)*** (0.019)* (0.018)*** (0.018)** Firm with 100-500 employees 0.187 0.047 0.175 0.064 0.194 0.074 0.188 0.070 (0.001)*** (0.001)*** (0.018)*** (0.017)*** (0.018)*** (0.017)*** (0.018)*** (0.016)*** Firm with more than 500 employees 0.258 0.078 0.246 0.088 0.256 0.099 0.242 0.088 (0.001)*** (0.001)*** (0.015)*** (0.016)*** (0.015)*** (0.017)*** (0.015)*** (0.016)*** Additional control variables: Industry X X X X Province X X X X Year X X X X X X X X Interaction terms with year X X X X X X X X Constant 2.224 2.239 2.216 2.247 2.691 2.292 2.660 2.280 (0.005)*** (0.003)*** (0.081)*** (0.048)*** (0.297)*** (0.169)*** (0.303)*** (0.159)*** Observations 31790 80977 31790 80977 31790 80977 31790 80977 Adjusted R-squared 0. 410 0. 264 0. 440 0. 313 0. 433 0. 285 0. 459 0. 325


38

Table 9: Determinants of union membership in Canada, 1998 – 2006 (Private Sector)


Marginal effect

Marginal effect

Marginal effect

Marginal effect

Marginal effect

Marginal effect

Marginal effect

Marginal effect

Marginal effect

(S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) Variable name: (1) (2) (3) (4) (5) (6) (7) (8) (9) Male 0.057 0.043 0.054 0.047 0.054 0.055 0.060 0.059 0.060 (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** Married -0.017 -0.008 0.002 -0.010 -0.006 -0.007 -0.010 0.001 0.000 (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)** (0.000) Age base category: Age 55 + … … … … … … … … … … … … … … … … … … Age between 15 and 24 -0.075 -0.060 -0.067 -0.071 -0.067 -0.08 -0.091 -0.078 -0.083 (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** Age between 25 and 34 -0.037 -0.044 -0.037 -0.035 -0.038 -0.049 -0.047 -0.042 -0.024 (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** Age between 35 and 44 -0.015 -0.021 -0.014 -0.012 -0.007 -0.016 -0.014 -0.016 -0.006 (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** Age between 45 and 54 0.016 0.010 0.010 0.015 0.012 0.016 0.010 0.005 0.019 (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.001)*** High school dropout (excluded group) … … … … … … … … … … … … … … … … … … 11 to 13 years of schooling/graduate -0.006 -0.013 -0.014 -0.013 -0.007 -0.014 -0.010 -0.004 -0.021 (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** At least some postsecondary diploma -0.029 -0.024 -0.031 -0.031 -0.016 -0.026 -0.019 -0.029 -0.033 (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** University: bachelors or graduate degree -0.090 -0.090 -0.106 -0.095 -0.098 -0.097 -0.089 -0.097 -0.107 (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** Firm with less than 20 employees (base) … … … … … … … … … … … … … … … … … … Firm with 20-99 employees 0.139 0.167 0.170 0.149 0.162 0.148 0.150 0.168 0.170 (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** Firm with 100-500 employees 0.276 0.301 0.317 0.302 0.274 0.296 0.304 0.315 0.299 (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)*** (0.001)***

39

Table 9 (Continued)


Marginal effect

Marginal effect

Marginal effect

Marginal effect

Marginal effect

Marginal effect

Marginal effect

Marginal effect

Marginal effect

(S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) Variable name: (1) (2) (3) (4) (5) (6) (7) (8) (9) Firm with more than 500 employees 0.275 0.289 0.303 0.304 0.307 0.305 0.321 0.335 0.327 (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** (0.000)*** Additional control variables: X X X X X X X X X Industry X X X X X X X X X Province X X X X X X X X X Observations 37004 36721 34277 36612 35756 35917 34770 35006 33744 Pseudo R-squared 0.191 0.180 0.200 0.201 0.202 0.208 0.206 0.214 0.209

Robust standard errors in parentheses * significant at 10%; ** significant at 5%; *** significant at 1%.

40

Table 10: Effect of predicted probability of unionization on union/non-union wage rates, 1998 – 2006 (Private Sector)


workers Union

workers Non-union

workers Union

workers Non-union

workers Union

workers Non-union

workers Union


(S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) Variable name: (1) (2) (3) (4) (5) (6) (7) (8) The threat of unionization in 2006 0.406 0.531 0.460 0.752 0.125 -0.101 0.149 0.106 (0.020)*** (0.029)*** (0.021)*** (0.031)*** (0.025)*** (0.037)*** (0.028)*** (0.061)* The threat of unionization in 2005 0.403 0.568 0.444 0.814 0.186 -0.053 0.185 0.147 (0.020)*** (0.029)*** (0.020)*** (0.031)*** (0.024)*** (-0.035) ** (0.026)*** (0.055)*** The threat of unionization in 2004 0.413 0.551 0.432 0.764 0.183 -0.001 0.166 0.159 (0.018)*** (0.026)*** (0.018)*** (0.027)*** (0.020)*** (-0.029) *** (0.022)*** (0.043)*** The threat of unionization in 2003 0.399 0.501 0.403 0.697 0.204 -0.004 0.164 0.132 (0.018)*** (0.025)*** (0.018)*** (0.026)*** (0.019)*** (-0.027)* (0.021)*** (0.038)*** The threat of unionization in 2002 0.388 0.509 0.385 0.683 0.243 0.035 0.191 0.143 (0.018)*** (0.025)*** (0.018)*** (0.025)*** (0.019)*** (-0.026) ** (0.020)*** (0.036)*** The threat of unionization in 2001 0.364 0.520 0.360 0.678 0.237 0.110 0.181 0.200 (0.017)*** (0.024)*** (0.017)*** (0.025)*** (0.019)*** (0.026)*** (0.020)*** (0.037)*** The threat of unionization in 2000 0.427 0.539 0.392 0.666 0.311 0.162 0.221 0.211 (0.018)*** (0.025)*** (0.018)*** (0.026)*** (0.020)*** (0.029)*** (0.021)*** (0.042)*** The threat of unionization in 1999 0.406 0.511 0.388 0.620 0.297 0.183 0.22 0.216 (0.018)*** (0.025)*** (0.018)*** (0.026)*** (0.022)*** (0.032)*** (0.023)*** (0.049)*** The threat of unionization in 1998 0.393 0.482 0.346 0.597 0.331 0.176 0.219 0.197 (0.019)*** (0.028)*** (0.019)*** (0.029)*** (0.024)*** (0.037)*** (0.026)*** (0.059)*** Male 0.243 0.248 0.248 0.239 0.213 0.208 0.221 0.213 (0.004)*** (0.007)*** (0.004)*** (0.007)*** (0.004)*** (0.008)*** (0.004)*** (0.010)*** Married 0.100 0.063 0.106 0.063 0.086 0.0490 0.092 0.049 (0.004)*** (0.007)*** (0.004)*** (0.007)*** (0.004)*** (0.006)*** (0.004)*** (0.006)*** Age base category: Age 55 + … … … … … … … … … … … … … … … … Age between 15 and 24 -0.356 -0.405 -0.351 -0.369 -0.311 -0.400 -0.313 -0.381 (0.008)*** (0.015)*** (0.008)*** (0.015)*** (0.008)*** (0.015)*** (0.008)*** (0.016)*** Age between 25 and 34 -0.091 -0.116 -0.083 -0.095 -0.089 -0.126 -0.084 -0.110 (0.008)*** (0.012)*** (0.008)*** (0.012)*** (0.008)*** (0.011)*** (0.008)*** (0.012)***

41

Table 10 (Continued)


workers Union

workers Non-union

workers Union

workers Non-union

workers Union

workers Non-union

workers Union


(S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) Variable name: (1) (2) (3) (4) (5) (6) (7) (8) Age between 35 and 44 0.022 -0.034 0.03 -0.018 0.012 -0.043 0.019 -0.029 (0.008)*** (0.011)*** (0.008)*** (0.010)* (0.008) *** (0.010)*** (0.008)*** (0.010)*** Age between 45 and 54 0.034 -0.008 0.044 0.003 0.029 -0.015 0.039 -0.002 (0.009)*** (-0.011) (0.008)*** (-0.011) (0.008)*** (-0.01) (0.008)*** (-0.01) High school dropout (excluded group) … … … … … … … … … … … … … … … … 11 to 13 years of schooling/graduate 0.150 0.117 0.137 0.102 0.131 0.111 0.119 0.095 (0.005)*** (0.008)*** (0.005)*** (0.008)*** (0.005)*** (0.008)*** (0.004)*** (0.008)*** At least some postsecondary diploma 0.245 0.173 0.235 0.169 0.208 0.153 0.199 0.146 (0.004)*** (0.007)*** (0.004)*** (0.007)*** (0.004)*** (0.007)*** (0.004)*** (0.007)*** University: bachelors or graduate degree 0.560 0.378 0.530 0.384 0.476 0.303 0.445 0.289 (0.007)*** (0.016)*** (0.007)*** (0.016)*** (0.007)*** (0.017)*** (0.007)*** (0.020)*** Firm with less than 20 employees (base) … … … … … … … … … … … … … … … … Firm with 20-99 employees 0.062 -0.100 0.056 -0.115 0.057 -0.023 0.058 -0.026 (0.005)*** (0.015)*** (0.005)*** (0.015)*** (0.005)*** (-0.015) (0.005)*** (-0.017) Firm with 100-500 employees 0.078 -0.141 0.072 -0.169 0.063 -0.04 0.071 -0.04 (0.006)*** (0.016)*** (0.006)*** (0.016)*** (0.006)*** (0.017)** (0.007)*** (0.023)* Firm with more than 500 employees 0.102 -0.09 0.096 -0.133 0.099 0.046 0.112 0.04 (0.005)*** (0.015)*** (0.005)*** (0.016)*** (0.007)*** (0.019)** (0.007)*** (-0.028) Additional control variables: Industry X X X X Province X X X X Year X X X X X X X X Interaction terms with year X X X X X X X X Constant 2.031 2.409 2.087 2.477 2 2.357 2.044 2.384 (0.008)*** (0.017)*** (0.009)*** (0.019)*** (0.013)*** (0.042)*** (0.013)*** (0.043)*** Observations 259806 60001 259806 60001 259806 60001 259806 60001 Adjusted R-squared 0.392 0.367 0.425 0.405 0.461 0.447 0.489 0.475


42

Table 11: Effect of union density on union/non-union wage rates, 1998 – 2006 (Private Sector)


workers Union

workers Non-union

workers Union

workers Non-union

workers Union

workers Non-union

workers Union


(S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) Variable name: (1) (2) (3) (4) (5) (6) (7) (8) Industry-level union density in 2006 0.399 0.797 0.510 0.768 -0.198 -0.142 -0.183 -0.172 (0.001)*** (0.003)*** (0.022)*** (0.048)*** (0.137) *** (-0.203) (0.133) ** (-0.199) Industry-level union density in 2005 0.380 0.695 0.501 0.754 -0.127 -0.056 -0.119 -0.069 (0.001)*** (0.003)*** (0.022)*** (0.045)*** (-0.110) (-0.160) (0.107) ** (-0.157) Industry-level union density in 2004 0.374 0.740 0.478 0.801 -0.130 0.018 -0.123 -0.004 (0.001)*** (0.002)*** (0.021)*** (0.043)*** (0.074)* (-0.109) (0.072)* (-0.107) Industry-level union density in 2003 0.342 0.652 0.474 0.680 -0.086 -0.046 -0.087 -0.061 (0.001)*** (0.003)*** (0.020)*** (0.041)*** (-0.053) (-0.08) (0.052)* (-0.078) Industry-level union density in 2002 0.253 0.430 0.318 0.453 -0.027 -0.003 -0.027 -0.017 (0.001)*** (0.002)*** (0.015)*** (0.029)*** (0.028) (-0.042) (0.027) ** (-0.041) Industry-level union density in 2001 0.350 0.679 0.450 0.704 -0.025 0.043 -0.022 0.029 (0.001)*** (0.003)*** (0.019)*** (0.040)*** (-0.05) (-0.075) (-0.048) (-0.073) Industry-level union density in 2000 0.324 0.539 0.408 0.579 -0.026 0.023 -0.029 0.027 (0.001)*** (0.002)*** (0.019)*** (0.038)*** (-0.069) (-0.096) (-0.067) (-0.094) Industry-level union density in 1999 0.386 0.577 0.486 0.593 0.051 0.043 0.052 0.030 (0.001)*** (0.002)*** (0.019)*** (0.037)*** (-0.096) (-0.135) (-0.093) (-0.131) Industry-level union density in 1998 0.355 0.499 0.429 0.575 0.066 0.043 0.064 0.047 (0.001)*** (0.002)*** (0.020)*** (0.038)*** (-0.123) (-0.173) (-0.119) (-0.168) Male 0.233 0.243 0.256 0.267 0.231 0.232 0.233 0.234 (0.000)*** (0.000)*** (0.003)*** (0.006)*** (0.004)*** (0.008)*** (0.003)*** (0.007)*** Married 0.089 0.066 0.103 0.063 0.086 0.046 0.092 0.048 (0.000)*** (0.000)*** (0.004)*** (0.007)*** (0.004)*** (0.006)*** (0.004)*** (0.006)*** Age base category: Age 55 + … … … … … … … … … … … … … … … … Age between 15 and 24 -0.394 -0.447 -0.376 -0.457 -0.343 -0.434 -0.333 -0.415 (0.001)*** (0.001)*** (0.008)*** (0.014)*** (0.008)*** (0.014)*** (0.008)*** (0.013)*** Age between 25 and 34 -0.101 -0.142 -0.099 -0.137 -0.104 -0.142 -0.094 -0.125 (0.000)*** (0.001)*** (0.008)*** (0.011)*** (0.008)*** (0.011)*** (0.008)*** (0.011)***

43

Table 11 Continued


workers Union

workers Non-union

workers Union

workers Non-union

workers Union

workers Non-union

workers Union


(S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) (S.E.) Variable name: (1) (2) (3) (4) (5) (6) (7) (8) Age between 35 and 44 0.020 -0.036 0.022 -0.031 0.007 -0.047 0.016 -0.033 (0.000)*** (0.001)*** (0.008)*** (0.011)*** -0.008 (0.010)*** (0.008)** (0.010)*** Age between 45 and 54 0.035 0.011 0.045 0.015 0.033 -0.010 0.042 0.003 (0.001)*** (0.001)*** (0.008)*** (-0.011) (0.008)*** (-0.010) (0.008)*** (-0.010) High school dropout (excluded group) … … … … … … … … … … … … … … … … 11 to 13 years of schooling/graduate 0.161 0.122 0.133 0.094 0.126 0.105 0.116 0.090 (0.000)*** (0.001)*** (0.005)*** (0.008)*** (0.005)*** (0.008)*** (0.004)*** (0.007)*** At least some postsecondary diploma 0.254 0.182 0.229 0.163 0.200 0.141 0.193 0.136 (0.000)*** (0.000)*** (0.004)*** (0.007)*** (0.004)*** (0.007)*** (0.004)*** (0.007)*** University: bachelors/graduate degree 0.531 0.322 0.497 0.301 0.437 0.256 0.419 0.245 (0.000)*** (0.001)*** (0.007)*** (0.016)*** (0.007)*** (0.015)*** (0.007)*** (0.015)*** Firm with less than 20 employees (base) … … … … … … … … … … … … … … … … Firm with 20-99 employees 0.076 -0.050 0.072 -0.051 0.083 0.008 0.075 0.006 (0.000)*** (0.001)*** (0.005)*** (0.015)*** (0.005)*** -0.014 (0.004)*** (-0.014) Firm with 100-500 employees 0.120 -0.074 0.114 -0.052 0.118 0.019 0.108 0.020 (0.000)*** (0.001)*** (0.005)*** (0.014)*** (0.005)*** -0.014 (0.005)*** (-0.014) Firm with more than 500 employees 0.182 0.030 0.166 0.040 0.179 0.129 0.166 0.125 (0.000)*** (0.001)*** (0.004)*** (0.013)*** (0.004)*** (0.013)*** (0.004)*** (0.013)*** Additional control variables: Industry X X X X Province X X X X Year X X X X X X X X Interaction terms with year X X X X X X X X Constant 2.058 2.368 2.029 2.351 2.004 2.334 2.033 2.327 (0.001)*** (0.001)*** (0.009)*** (0.020)*** (0.014)*** (0.043)*** (0.014)*** (0.042)*** Observations 259806 60001 259806 60001 259806 60001 259806 60001 Adjusted R-squared 0.385 0.353 0.429 0.397 0.460 0.446 0.488 0.475


44

Appendix C

45

Figure 2: Effect of predicted probability of unionization on the non-union/union wages and the union-wage gap, for the whole sample, by year.

Panel (B) No Control for Industry

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

1998 1999 2000 2001 2002 2003 2004 2005 2006

Threat Effect (Non-Union)

Threat Effect (Union)

Panel (C) No Control for Province

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

1998 1999 2000 2001 2002 2003 2004 2005 2006



P anel (A ) N o C o ntro l fo r Industry no r fo r P ro vince

-0.1

00.1

0.20.3

0.40.5

0.6

1998 1999 2000 2001 2002 2003 2004 2005 2006



46

Figure 3: Effect of predicted probability of unionization on the non-union/union wages and the union-wage gap, for the public sector, by year.

Panel (A) No control for industry; nor for province

-0.45

-0.35

-0.25

-0.15

-0.05

0.05

0.15

0.25

1998 1999 2000 2001 2002 2003 2004 2005 2006



Panel (D) Control for industry and province

-0.45

-0.35

-0.25

-0.15

-0.05

0.05

0.15

0.25

1998 1999 2000 2001 2002 2003 2004 2005 2006



Panel (B) No control for industry

-0.45

-0.35

-0.25

-0.15

-0.05

0.05

0.15

0.25

1998 1999 2000 2001 2002 2003 2004 2005 2006



Panel ( C ) No control for province

-0.45

-0.35

-0.25

-0.15

-0.05

0.05

0.15

0.25

1998 1999 2000 2001 2002 2003 2004 2005 2006



47

Figure 4: Effect of predicted probability of unionization on the non-union/union wages and the union-wage gap, for the private sector, by year.


-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1998 1999 2000 2001 2002 2003 2004 2005 2006




-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1998 1999 2000 2001 2002 2003 2004 2005 2006



Panel ( C ) No control for province

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1998 1999 2000 2001 2002 2003 2004 2005 2006

Threat Effect(Non-Union)Threat Effect(Union)

Panel (A) No control for industry; nor for province

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1998 1999 2000 2001 2002 2003 2004 2005 2006



48

Figure 5: Effect of industry union density on the non-union/union wages and the union-wage gap, for the whole sample, by year.

Panel (C) No control for province

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

1998 1999 2000 2001 2002 2003 2004 2005 2006



Panel (A) No Control for industry; nor for province

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

1998 1999 2000 2001 2002 2003 2004 2005 2006




-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

1998 1999 2000 2001 2002 2003 2004 2005 2006




-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

1998 1999 2000 2001 2002 2003 2004 2005 2006

Threat Effect (Non-Union)Threat Effect (Union)

49

Figure 6: Effect of industry union density on the non-union/union wages and the union-wage gap, for the private sector, by year.

Panel (A) NO control for industry; nor province

-0.25

-0.05

0.15

0.35

0.55

0.75

0.95

1998 1999 2000 2001 2002 2003 2004 2005 2006




-0.25

-0.05

0.15

0.35

0.55

0.75

0.95

1998 1999 2000 2001 2002 2003 2004 2005 2006



Panel (C) No control for province

-0.25

-0.05

0.15

0.35

0.55

0.75

0.95

1998 1999 2000 2001 2002 2003 2004 2005 2006




-0.25

-0.05

0.15

0.35

0.55

0.75

0.95

1998 1999 2000 2001 2002 2003 2004 2005 2006

Threat Ef fect (Non-Union)

Threat Ef fect (Union)

50

Figure 7: Effect of industry union density on the non-union/union wages and the union-wage gap, for the public sector, by year.

Panel (A) No Control for industry; nor for province

-0.6-0.5-0.4-0.3-0.2-0.1

00.10.20.30.4

1998 2000 2002 2004 2006




-0.6

-0.5-0.4

-0.3

-0.2-0.1

0

0.1

0.20.3

0.4

1998 1999 2000 2001 2002 2003 2004 2005 2006



Panel (C) No Control for province

-0.6

-0.5-0.4

-0.3

-0.2-0.1

0

0.1

0.20.3

0.4

1998 1999 2000 2001 2002 2003 2004 2005 2006




-0.6

-0.5-0.4

-0.3

-0.2-0.1

0

0.1

0.20.3

0.4

1998 1999 2000 2001 2002 2003 2004 2005 2006

