- Email: [email protected]
Attitudes towards unions and union membership
Economics Letters North-Holland
ATIITUDES
TOWARDS
Virginia CHRISTIE
UNIONS
15 December 21 February
AND UNION MEMBERSHIP
* and Paul MILLER
The University of Western Australia, Received Accepted
263
30 (1989) 263-268
Nedlands,
*
Western Australia,
6009 Australig
1988 1989
This paper argues that the conventional treatment of the attitudes of workers in union status models is poorly motivated. One result is that the model may be incapable of tracking large changes in union membership, if these derive from shifts in attitudes.
1. Introduction Trade union membership has declined in many Western countries in recent years. In Britain the percent of the workforce unionised has fallen from 55 percent in 1979 to around 40 percent in 1987 [Towers (1988)]. In Australia, the union membership rate has declined from 49 percent in 1982 to 46 percent in 1987. The reasons for the trade union decline have not been understood, due to the lack of understanding of the determinants of trade union membership. Many studies that have examined the union membership decision have been based on Lee’s (1978) model. One of the key aspects of this model is the individual’s receptivity of unions, and this provides the focus of the current paper. The evidence presented suggests that existing union membership studies that have rationalised the inclusion of personal characteristics variables in the estimating equation on the grounds that they reflect the attitudes of workers may have an unsound basis. This has probably contributed to the poor understanding of changes over time in the union membership decision. The paper is structured as follows. Section 2 provides a brief outline of Lee’s (1978) model of union membership. Section 3 presents an application of this model using Australian data. The feature of the empirical analysis is the use of direct information on union sentiment in the estimating equation. Section 4 summarises the main findings.
2. Modelling the union membership
decision
In Lee’s (1978) model, individual i will join a union if (Ki-
0)
W,i)/W,i>pi,
where Wui represents the union wage, Wni the non-union wage and P, the reservation wage. The reservation wage (P,) depends upon the monetary and non-monetary costs associated with unionisa* We are grateful
0165-1765/89/$3.50
to Ken Clements
and Paul Volker for helpful
0 1989, Elsevier Science Publishers
comments.
B.V. (North-Holland)
264
V. Christie, P. Miller / Attitudes
towards unions and union membership
tion (C,), the characteristics of individual i (X,) that affect his receptivity of unions, and an error term (cl,) reflecting unobservable factors. This is summarised by the following equation: P, =
cc; + px, + Cl,
(2)
)
where eli - N(0, u,“,). The costs associated with union membership (C,) are divided into two parts. The first is associated with the characteristics of the worker (X,) and the second with the attributes of industry (2,). Both are observable variables. The cost function also includes unobservable factors, which are represented by the normally distributed residual cZ,. Thus, c,
=
Yl
+
Y2x,
+
Y36
+
E2r.
Eqs. (l), (2), and (3) may be used to derive eq. (4). This indicates that an individual will join a union if
Alternatively, and index I, may be defined as I,
=
-aYl
+
s,
[ ( wu,
-
wnj)/W,,]
-
(P
+
W2)
xj
-
aY3zi - vi.
(5)
It is convenient to rewrite the index function (5) in the following form which is used in estimation: I,=
-f_~y,+6,(lnW,~-lnW,,)-(/3+ay~)X,-ay,Z~-v~.
(6)
Then, an individual joins a union if 1, > 0. The important feature of eq. (6) is that the personal of workers may characteristics (X;) capture two types of influences. First, the characteristics influence the union membership decision via the cost function [eq. (3)]. Lee (1978) suggests that after deciding to join a union, the individual must then secure employment. The selectiveness of firms in this regard is assumed to vary with variables such as education, marital status, experience and sex. The second route through which individual characteristics (X,) may affect the reservation wage (P,) is by altering the individual’s receptivity of unions [eq. (2)]. In previous studies [e.g., Lee (1978), Robinson and Tomes (1984), Simpson (1985)] it has been assumed that a strong correlation exists between workers’ attitudes towards trade unions and their individual characteristics (X,). For example, attitudes towards unions may vary with marital status. Job security and satisfactory conditions of employment are usually key priorities to married couples, especially those with family commitments. As a major role of trade unions is to protect the working conditions and rights of the employees, the married might be expected to hold favourable attitudes towards trade unions. The extent to which attitudes towards trade unions vary with personal characteristics may, however, be minimal. For example, cross-tabulations of responses to the question: ‘How good a job would you say that trade unions are doing for the country as a whole?’ with marital status, labour market experience, qualifications and sex revealed very little relationship within a bivariate framework. Table 1, which lists the relevant data for sex, is illustrative. These figures show only a slight difference between the distribution of responses. If the considerable difference in union membership rates between males and females derives from differences in attitudes towards unions, then this evidence suggests that individual characteristics may contribute a very poor proxy for the individual’s receptivity of unions [i.e., for the second term, PX,, in eq. (2)]. In the present study, Lee’s model is therefore estimated using two approaches. First, previous studies
V, Christie, P. Miller / Aftifudes Table 1 Attitudes
towards
trade union
Attitude
Very good Fairly good Not very good No good at all
activity
in Australia
(percentage
towards unions and union membership
265
distribution).
Sex Males
Females
2.9 35.7 37.2 24.2
1.5 33.8 42.4 22.3
will be followed, and individual characteristics used to reflect attitudes in the reservation wage equation. Second, actual attitudinal information is included in the equation representing Pi. Comparison of the two equations indicates the extent to which the conventional approach provides an adequate representation of workers’ attitudes. When the direct attitudinal information is included in the estimating equation, the coefficients on XL yield -(dye rather than the composite -(/3 + cry,) in the general model. Clearly then, the alternative model permits a better focus on the ‘costs’ and ‘attitudinal’ aspects of the trade union membership decision. Finally, it can be noted that theoretical arguments propose /3 > 0, thus - cuy, > - (/_I + ay,). This implies that when the attitudinal information is included in the estimating equation, the values of coefficients on the other variables should yield higher values than when the attitude variable is excluded from the specification.
3. Empirical analysis The data are drawn from the 1984 Australian National Social Science Survey. ’ The survey covers 3012 respondents, and is representative of the Australian population aged 18 years and above. The analyses are limited to those employed individuals having valid information on the economic, background and attitudinal information used in the statistical models. The purged data set consists of 1316 cases. Information on anti-trade union sentiment is derived from four questions. These sought information on the degree of confidence respondents have in trade unions, their opinion of the type of job trade unions are doing for the country, their concern for the power of trade unions, and their sympathies (or otherwise) for strikers. A scale variable is derived from responses to these questions to summarise the respondent’s opposition to trade unions [see Kelley (1988)]. Statistical models are estimated on data pooled across male and female respondents, and in this sense the study parallels that by Robinson and Tomes (1984). Precise definitions of all variables are presented in Christie (1988). A general specification of the index, I, was used, with qualifications, experience, marital status, sex, occupation, and State of residence included. The expected wage gain (In I?$; - In IV,,i) was computed from conventional human capital earnings functions, estimated separately for union and non-union members, and corrected for sample selection bias using the methods outlined in Heckman (1979). = ’ These data are available through the Social Science Data Archive at the Australian National University. ’ The following variables are included in the wage equation: education, qualifications, labour market experience and its square, marital status, sex, region, occupation and State of residence. It is noted that not all the variables that enter the wage equation can be included in the structural union status equation. The (over)identifying restrictions are provided by the exclusion of education and region. These restrictions are supported by the appropriate likelihood ratio tests.
266
V. Christie, P. Miller / Attitudes towards unions and union membership
Table 2 Logit estimates
of union membership
model:
Structural
Variable
Logit estimate
t-statistics
Constant
-0.823
b
form (dependent
variable:
log odds of union
membership).
a
Marginal effect
Logit estimate
1.58
- 0.192
0.531
0.94
0.124
0.026 0.319 0.198 0.722
0.17 0.89 0.74 2.66
- 0.006 0.074 0.046 0.168
0.110 0.430 0.222 0.923
0.71 1.16 0.80 3.28
0.026 0.100 0.052 0.215
Experience: Experience (EXP) EXP squared/l00
0.056 - 0.086
2.41 1.90
0.013 - 0.020
0.068 - 0.107
2.86 2.29
0.016 - 0.025
Marital status: Single Others
- 0.039 -0.151
0.22 0.62
- 0.009 - 0.035
-0.135 - 0.025
0.74 0.10
- 0.031 - 0.059
Sex: Female
-
0.501
3.24
-0.117
- 0.440
2.79
- 0.102
Indwy: Agriculture Mining Manufacturing Utility Construction Wholesale trade Transport Finance Public administration Other industries
- 2.190 - 0.484 - 0.768 0.322 - 1.025 - 1.416 0.137 -0.800 0.620 - 0.714
2.87 1.01 3.30 0.72 3.16 4.81 0.49 3.05 2.41 2.32
- 0.510 -0.113 - 0.179 0.075 - 0.239 - 0.330 0.032 -0.186 0.144 - 0.166
- 1.785 - 0.625 - 0.786 0.112 - 0.924 - 1.398 0.126 - 0.694 0.630 - 0.635
2.24 1.26 3.26 0.25 2.76 4.62 0.44 2.59 2.39 2.00
-0.183 - 0.146 -0.183 0.026 0.215 - 0.326 0.029 -0.162 0.147 - 0.148
Occupation: Professional Administration Clerical Sales Service Agriculture
-
0.519 0.917 0.456 1.460 0.869 1.426
2.25 3.34 2.00 4.27 3.15 1.94
-
-
0.561 0.802 0.381 1.376 0.895 1.785
2.36 2.82 1.63 3.95 3.18 2.30
-0.131 - 0.187 - 0.089 - 0.321 - 0.209 - 0.416
Stare of residence: Queensland S. Australia Tasmania Victoria W. Australia N. Territory A.C.T.
0.004 0.278 0.839 0.285 - 0.507 -0.158 - 0.822
0.02 1.17 3.65 1.42 1.82 0.13 1.59
0.001 0.065 0.196 0.066 -0.118 - 0.037 - 0.192
- 0.081 0.341 0.894 0.254 - 0.525 -0.289 - 1.019
0.37 1.40 3.77 1.22 1.84 0.24 1.92
- 0.019 0.079 0.208 0.059 - 0.122 - 0.067 0.237
1.682
1.94
0.392
2.345
2.60
0.547
- 0.028
7.85
0.006
Education: Trade certificate Higher degree Degree Diploma
Inw,-In& Anti-union Chi-squared Sample size
attitude
E
_c 211.90 1316
’ The omitted categories for the categorical production-type work in the communication b Absolute value of asymptotic r-statistics. ’ Variable not entered.
0.121 0.214 0.106 0.340 0.202 0.332
_c
t-statistics
b
Marginal effect
277.27 1316
variables define the control group as unqualified, industry and who live in New South Wales.
married
males who work in
V. Christie, P. Miller / Attitudes
towards unions and union membership
261
The union membership model is estimated using a logit model. As an assurance that each variable category is significant, likelihood ratio tests were conducted on different variable groupings. The specification adopted passed these tests. Table 2 presents the estimates. The left-hand set of estimates excludes the attitudinal information, while the second set of estimates includes this information. The three columns for each set of results list, respectively, the estimated coefficients, the asymptotic ‘t ’ statistics, and the marginal effects, calculated as NJ/ax= U(1 - U)/3. Several conclusions may be drawn from these results. First, the estimates are generally consistent with previous Australian studies of trade union membership [e.g., Crocket and Hall (1987)] and with the overseas literature. For example, variables such as qualifications have little impact on the union membership decision, a finding consistent with Hirsch and Addison (1986). The coefficient on the union/non-union wage differential is positive and statistically significant. In the equation which includes the union attitude variable, the estimated coefficient is 2.34 (implying an elasticity of 1.04) with t = 2.60. This result is consistent with findings reported by both Robinson and Tomes (1984) and Lee (1978). Second, workers’ attitudes have an important influence upon the union membership decision, as indicated by the high level of statistical significance of this variable (t = 7.85). As outlined above, when the attitudinal information is excluded from the estimating equation, the coefficients on the X, variables should be larger than when the union sentiment variable is included in the model. However, it can be concluded from the results of table 2 that, whilst there is a tendency for the theoretical prediction to be borne out by the evidence, the addition of the union attitude factor has little perceptible impact on the estimated coefficients of other variables. This has two possible interpretations. First, the variables in the equation omitting direct information on attitudes are dominated by the impact of cost of organisation rather than attitudes (i.e., (my, is considerably larger than p). Second there may be little correlation between attitudes and the Xi variables. The notion of a weak relationship between attitudes and individual characteristics is supported by a regression of the attitude variable on the individual characteristics listed in table 2. Consequently, standard statistical results relating to omitted variables bias suggest that the exclusion of an attitude variable from the union status equation will not greatly alter other empirical findings. The implications of these findings for applications of union membership models can now be canvassed. The results of table 2 suggest that the conventional specification of the union status model is, in part, poorly motivated. This prompts the conclusion that the model will be largely incapable of tracking the large changes in union membership that have occurred, if these derive from shifts in attitudes. This opens up the doors to investigate this position, using more detailed data and methodology, for a comprehensive understanding of the effects the attitude variable has upon the union membership decision.
4. Conclusion As an extension to the conventional trade union membership studies, this paper incorporates the attitudes of workers towards unions into the estimating equation, rather than allowing these to be indirectly represented by individual characteristics such as age, sex, marital status, experience and location. This modification of the basic Lee model led to the important conclusion that attitudes are a major determinant of trade union membership. The inclusion of the union sentiment variable has little impact upon other coefficients in the equation. However, the results suggest that conventional models will be unable to explain the recent declines in unionisation in most Western countries, if these declines are related to shifts in attitudes towards union activity.
268
K Christie, P. Miller / Attitudes
towardr unions and union membership
References Christie, Virginia, 1988, Union wage effects and the probability of union membership, Unpublished dissertation (Department of Economics, The University of Western Australia, Nedlands). Crockett, Geoff and Ken Hall, 1987, Salaried professionals and union membership: An Australian perspective, The Journal of Industrial Relations 29, 49-65. Heckman, James J., 1979, Sample selection bias as a specification error, Econometrica 47, 153-161. Hirsch, Barry T. and John T. Addison, 1986, The economic analysis of unions, new approaches and evidence (Allen and Unwin, Boston, MA). Kelley, Jonathan, 1988, Political ideology in Australia, in: Jonathan Kelley and Clive Bean, eds., Society and politics in Australia: Analyses from the National Social Science Survey (Allen and Unwin, Sydney). Kelley. Jonathan, R.G. Cushing and B. Headey, 1987, Australian National Social Science Survey, 1984 (Users Guide and Data File) (Social Science Data Archives, The Australian National University, Canberra). Lee, Lung-Fei, 1978, Unionism and wage rates: A simultaneous equations model with qualitative and limited dependent variables, International Economic Review 19, 415-434. Robinson, Chris and Nigel Tomes, 1984, Union wage differentials in the public and private sectors: A simultaneous equations specification, Journal of Labor Economics 2, 106-217. Simpson, Wayne, 1985, The impact of unions on the structure of Canadian wages: An empirical analysis with microdata, Canadian Journal of Economics 18, 164-181. Tower, B., 1987, Trends and developments in industrial relations, after Blackpool: The wider questions, Industrial Relations Journal 18, 239-243.
ATIITUDES
TOWARDS
Virginia CHRISTIE
UNIONS
15 December 21 February
AND UNION MEMBERSHIP
* and Paul MILLER
The University of Western Australia, Received Accepted
263
30 (1989) 263-268
Nedlands,
*
Western Australia,
6009 Australig
1988 1989
This paper argues that the conventional treatment of the attitudes of workers in union status models is poorly motivated. One result is that the model may be incapable of tracking large changes in union membership, if these derive from shifts in attitudes.
1. Introduction Trade union membership has declined in many Western countries in recent years. In Britain the percent of the workforce unionised has fallen from 55 percent in 1979 to around 40 percent in 1987 [Towers (1988)]. In Australia, the union membership rate has declined from 49 percent in 1982 to 46 percent in 1987. The reasons for the trade union decline have not been understood, due to the lack of understanding of the determinants of trade union membership. Many studies that have examined the union membership decision have been based on Lee’s (1978) model. One of the key aspects of this model is the individual’s receptivity of unions, and this provides the focus of the current paper. The evidence presented suggests that existing union membership studies that have rationalised the inclusion of personal characteristics variables in the estimating equation on the grounds that they reflect the attitudes of workers may have an unsound basis. This has probably contributed to the poor understanding of changes over time in the union membership decision. The paper is structured as follows. Section 2 provides a brief outline of Lee’s (1978) model of union membership. Section 3 presents an application of this model using Australian data. The feature of the empirical analysis is the use of direct information on union sentiment in the estimating equation. Section 4 summarises the main findings.
2. Modelling the union membership
decision
In Lee’s (1978) model, individual i will join a union if (Ki-
0)
W,i)/W,i>pi,
where Wui represents the union wage, Wni the non-union wage and P, the reservation wage. The reservation wage (P,) depends upon the monetary and non-monetary costs associated with unionisa* We are grateful
0165-1765/89/$3.50
to Ken Clements
and Paul Volker for helpful
0 1989, Elsevier Science Publishers
comments.
B.V. (North-Holland)
264
V. Christie, P. Miller / Attitudes
towards unions and union membership
tion (C,), the characteristics of individual i (X,) that affect his receptivity of unions, and an error term (cl,) reflecting unobservable factors. This is summarised by the following equation: P, =
cc; + px, + Cl,
(2)
)
where eli - N(0, u,“,). The costs associated with union membership (C,) are divided into two parts. The first is associated with the characteristics of the worker (X,) and the second with the attributes of industry (2,). Both are observable variables. The cost function also includes unobservable factors, which are represented by the normally distributed residual cZ,. Thus, c,
=
Yl
+
Y2x,
+
Y36
+
E2r.
Eqs. (l), (2), and (3) may be used to derive eq. (4). This indicates that an individual will join a union if
Alternatively, and index I, may be defined as I,
=
-aYl
+
s,
[ ( wu,
-
wnj)/W,,]
-
(P
+
W2)
xj
-
aY3zi - vi.
(5)
It is convenient to rewrite the index function (5) in the following form which is used in estimation: I,=
-f_~y,+6,(lnW,~-lnW,,)-(/3+ay~)X,-ay,Z~-v~.
(6)
Then, an individual joins a union if 1, > 0. The important feature of eq. (6) is that the personal of workers may characteristics (X;) capture two types of influences. First, the characteristics influence the union membership decision via the cost function [eq. (3)]. Lee (1978) suggests that after deciding to join a union, the individual must then secure employment. The selectiveness of firms in this regard is assumed to vary with variables such as education, marital status, experience and sex. The second route through which individual characteristics (X,) may affect the reservation wage (P,) is by altering the individual’s receptivity of unions [eq. (2)]. In previous studies [e.g., Lee (1978), Robinson and Tomes (1984), Simpson (1985)] it has been assumed that a strong correlation exists between workers’ attitudes towards trade unions and their individual characteristics (X,). For example, attitudes towards unions may vary with marital status. Job security and satisfactory conditions of employment are usually key priorities to married couples, especially those with family commitments. As a major role of trade unions is to protect the working conditions and rights of the employees, the married might be expected to hold favourable attitudes towards trade unions. The extent to which attitudes towards trade unions vary with personal characteristics may, however, be minimal. For example, cross-tabulations of responses to the question: ‘How good a job would you say that trade unions are doing for the country as a whole?’ with marital status, labour market experience, qualifications and sex revealed very little relationship within a bivariate framework. Table 1, which lists the relevant data for sex, is illustrative. These figures show only a slight difference between the distribution of responses. If the considerable difference in union membership rates between males and females derives from differences in attitudes towards unions, then this evidence suggests that individual characteristics may contribute a very poor proxy for the individual’s receptivity of unions [i.e., for the second term, PX,, in eq. (2)]. In the present study, Lee’s model is therefore estimated using two approaches. First, previous studies
V, Christie, P. Miller / Aftifudes Table 1 Attitudes
towards
trade union
Attitude
Very good Fairly good Not very good No good at all
activity
in Australia
(percentage
towards unions and union membership
265
distribution).
Sex Males
Females
2.9 35.7 37.2 24.2
1.5 33.8 42.4 22.3
will be followed, and individual characteristics used to reflect attitudes in the reservation wage equation. Second, actual attitudinal information is included in the equation representing Pi. Comparison of the two equations indicates the extent to which the conventional approach provides an adequate representation of workers’ attitudes. When the direct attitudinal information is included in the estimating equation, the coefficients on XL yield -(dye rather than the composite -(/3 + cry,) in the general model. Clearly then, the alternative model permits a better focus on the ‘costs’ and ‘attitudinal’ aspects of the trade union membership decision. Finally, it can be noted that theoretical arguments propose /3 > 0, thus - cuy, > - (/_I + ay,). This implies that when the attitudinal information is included in the estimating equation, the values of coefficients on the other variables should yield higher values than when the attitude variable is excluded from the specification.
3. Empirical analysis The data are drawn from the 1984 Australian National Social Science Survey. ’ The survey covers 3012 respondents, and is representative of the Australian population aged 18 years and above. The analyses are limited to those employed individuals having valid information on the economic, background and attitudinal information used in the statistical models. The purged data set consists of 1316 cases. Information on anti-trade union sentiment is derived from four questions. These sought information on the degree of confidence respondents have in trade unions, their opinion of the type of job trade unions are doing for the country, their concern for the power of trade unions, and their sympathies (or otherwise) for strikers. A scale variable is derived from responses to these questions to summarise the respondent’s opposition to trade unions [see Kelley (1988)]. Statistical models are estimated on data pooled across male and female respondents, and in this sense the study parallels that by Robinson and Tomes (1984). Precise definitions of all variables are presented in Christie (1988). A general specification of the index, I, was used, with qualifications, experience, marital status, sex, occupation, and State of residence included. The expected wage gain (In I?$; - In IV,,i) was computed from conventional human capital earnings functions, estimated separately for union and non-union members, and corrected for sample selection bias using the methods outlined in Heckman (1979). = ’ These data are available through the Social Science Data Archive at the Australian National University. ’ The following variables are included in the wage equation: education, qualifications, labour market experience and its square, marital status, sex, region, occupation and State of residence. It is noted that not all the variables that enter the wage equation can be included in the structural union status equation. The (over)identifying restrictions are provided by the exclusion of education and region. These restrictions are supported by the appropriate likelihood ratio tests.
266
V. Christie, P. Miller / Attitudes towards unions and union membership
Table 2 Logit estimates
of union membership
model:
Structural
Variable
Logit estimate
t-statistics
Constant
-0.823
b
form (dependent
variable:
log odds of union
membership).
a
Marginal effect
Logit estimate
1.58
- 0.192
0.531
0.94
0.124
0.026 0.319 0.198 0.722
0.17 0.89 0.74 2.66
- 0.006 0.074 0.046 0.168
0.110 0.430 0.222 0.923
0.71 1.16 0.80 3.28
0.026 0.100 0.052 0.215
Experience: Experience (EXP) EXP squared/l00
0.056 - 0.086
2.41 1.90
0.013 - 0.020
0.068 - 0.107
2.86 2.29
0.016 - 0.025
Marital status: Single Others
- 0.039 -0.151
0.22 0.62
- 0.009 - 0.035
-0.135 - 0.025
0.74 0.10
- 0.031 - 0.059
Sex: Female
-
0.501
3.24
-0.117
- 0.440
2.79
- 0.102
Indwy: Agriculture Mining Manufacturing Utility Construction Wholesale trade Transport Finance Public administration Other industries
- 2.190 - 0.484 - 0.768 0.322 - 1.025 - 1.416 0.137 -0.800 0.620 - 0.714
2.87 1.01 3.30 0.72 3.16 4.81 0.49 3.05 2.41 2.32
- 0.510 -0.113 - 0.179 0.075 - 0.239 - 0.330 0.032 -0.186 0.144 - 0.166
- 1.785 - 0.625 - 0.786 0.112 - 0.924 - 1.398 0.126 - 0.694 0.630 - 0.635
2.24 1.26 3.26 0.25 2.76 4.62 0.44 2.59 2.39 2.00
-0.183 - 0.146 -0.183 0.026 0.215 - 0.326 0.029 -0.162 0.147 - 0.148
Occupation: Professional Administration Clerical Sales Service Agriculture
-
0.519 0.917 0.456 1.460 0.869 1.426
2.25 3.34 2.00 4.27 3.15 1.94
-
-
0.561 0.802 0.381 1.376 0.895 1.785
2.36 2.82 1.63 3.95 3.18 2.30
-0.131 - 0.187 - 0.089 - 0.321 - 0.209 - 0.416
Stare of residence: Queensland S. Australia Tasmania Victoria W. Australia N. Territory A.C.T.
0.004 0.278 0.839 0.285 - 0.507 -0.158 - 0.822
0.02 1.17 3.65 1.42 1.82 0.13 1.59
0.001 0.065 0.196 0.066 -0.118 - 0.037 - 0.192
- 0.081 0.341 0.894 0.254 - 0.525 -0.289 - 1.019
0.37 1.40 3.77 1.22 1.84 0.24 1.92
- 0.019 0.079 0.208 0.059 - 0.122 - 0.067 0.237
1.682
1.94
0.392
2.345
2.60
0.547
- 0.028
7.85
0.006
Education: Trade certificate Higher degree Degree Diploma
Inw,-In& Anti-union Chi-squared Sample size
attitude
E
_c 211.90 1316
’ The omitted categories for the categorical production-type work in the communication b Absolute value of asymptotic r-statistics. ’ Variable not entered.
0.121 0.214 0.106 0.340 0.202 0.332
_c
t-statistics
b
Marginal effect
277.27 1316
variables define the control group as unqualified, industry and who live in New South Wales.
married
males who work in
V. Christie, P. Miller / Attitudes
towards unions and union membership
261
The union membership model is estimated using a logit model. As an assurance that each variable category is significant, likelihood ratio tests were conducted on different variable groupings. The specification adopted passed these tests. Table 2 presents the estimates. The left-hand set of estimates excludes the attitudinal information, while the second set of estimates includes this information. The three columns for each set of results list, respectively, the estimated coefficients, the asymptotic ‘t ’ statistics, and the marginal effects, calculated as NJ/ax= U(1 - U)/3. Several conclusions may be drawn from these results. First, the estimates are generally consistent with previous Australian studies of trade union membership [e.g., Crocket and Hall (1987)] and with the overseas literature. For example, variables such as qualifications have little impact on the union membership decision, a finding consistent with Hirsch and Addison (1986). The coefficient on the union/non-union wage differential is positive and statistically significant. In the equation which includes the union attitude variable, the estimated coefficient is 2.34 (implying an elasticity of 1.04) with t = 2.60. This result is consistent with findings reported by both Robinson and Tomes (1984) and Lee (1978). Second, workers’ attitudes have an important influence upon the union membership decision, as indicated by the high level of statistical significance of this variable (t = 7.85). As outlined above, when the attitudinal information is excluded from the estimating equation, the coefficients on the X, variables should be larger than when the union sentiment variable is included in the model. However, it can be concluded from the results of table 2 that, whilst there is a tendency for the theoretical prediction to be borne out by the evidence, the addition of the union attitude factor has little perceptible impact on the estimated coefficients of other variables. This has two possible interpretations. First, the variables in the equation omitting direct information on attitudes are dominated by the impact of cost of organisation rather than attitudes (i.e., (my, is considerably larger than p). Second there may be little correlation between attitudes and the Xi variables. The notion of a weak relationship between attitudes and individual characteristics is supported by a regression of the attitude variable on the individual characteristics listed in table 2. Consequently, standard statistical results relating to omitted variables bias suggest that the exclusion of an attitude variable from the union status equation will not greatly alter other empirical findings. The implications of these findings for applications of union membership models can now be canvassed. The results of table 2 suggest that the conventional specification of the union status model is, in part, poorly motivated. This prompts the conclusion that the model will be largely incapable of tracking the large changes in union membership that have occurred, if these derive from shifts in attitudes. This opens up the doors to investigate this position, using more detailed data and methodology, for a comprehensive understanding of the effects the attitude variable has upon the union membership decision.
4. Conclusion As an extension to the conventional trade union membership studies, this paper incorporates the attitudes of workers towards unions into the estimating equation, rather than allowing these to be indirectly represented by individual characteristics such as age, sex, marital status, experience and location. This modification of the basic Lee model led to the important conclusion that attitudes are a major determinant of trade union membership. The inclusion of the union sentiment variable has little impact upon other coefficients in the equation. However, the results suggest that conventional models will be unable to explain the recent declines in unionisation in most Western countries, if these declines are related to shifts in attitudes towards union activity.
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References Christie, Virginia, 1988, Union wage effects and the probability of union membership, Unpublished dissertation (Department of Economics, The University of Western Australia, Nedlands). Crockett, Geoff and Ken Hall, 1987, Salaried professionals and union membership: An Australian perspective, The Journal of Industrial Relations 29, 49-65. Heckman, James J., 1979, Sample selection bias as a specification error, Econometrica 47, 153-161. Hirsch, Barry T. and John T. Addison, 1986, The economic analysis of unions, new approaches and evidence (Allen and Unwin, Boston, MA). Kelley, Jonathan, 1988, Political ideology in Australia, in: Jonathan Kelley and Clive Bean, eds., Society and politics in Australia: Analyses from the National Social Science Survey (Allen and Unwin, Sydney). Kelley. Jonathan, R.G. Cushing and B. Headey, 1987, Australian National Social Science Survey, 1984 (Users Guide and Data File) (Social Science Data Archives, The Australian National University, Canberra). Lee, Lung-Fei, 1978, Unionism and wage rates: A simultaneous equations model with qualitative and limited dependent variables, International Economic Review 19, 415-434. Robinson, Chris and Nigel Tomes, 1984, Union wage differentials in the public and private sectors: A simultaneous equations specification, Journal of Labor Economics 2, 106-217. Simpson, Wayne, 1985, The impact of unions on the structure of Canadian wages: An empirical analysis with microdata, Canadian Journal of Economics 18, 164-181. Tower, B., 1987, Trends and developments in industrial relations, after Blackpool: The wider questions, Industrial Relations Journal 18, 239-243.