Union Incidence in the Public and Private Sectors

Union Incidence in the Public and Private SectorsAuthor(s): Chris RobinsonSource: The Canadian Journal of Economics / Revue canadienne d'Economique, Vol. 28, No. 4b(Nov., 1995), pp. 1056-1076Published by: Wiley on behalf of the Canadian Economics AssociationStable URL: http://www.jstor.org/stable/136135 .

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Union incidence in the public and private sectors CHRIS ROBINSON University of Western Ontario and Economic Research Center / NORC

Abstract. Union density in the public sector is approximately twice the level of that in the private sector in both Canada and the United States. Canadian data are particularly useful for analysing differences between the public and private sectors because of several industries that have a substantial overlap of ownership between sectors. Sectors therefore may be compared while holding the industry constant. Evidence is presented suggesting that union cost factors, as related to the size of the 'plants,' are important in explaining the high density in the public sector. Employee characteristics appear to play no role. The connection between wage differentials and public sector unionism is also addressed.

Incidence de la syndicalisation dans les secteurs public et prive. L'intensite de syndicalisation est deux fois plus grande dans le secteur public que dans le secteur prive tant aux Etats-Unis qu'au Canada. Les donnees canadiennes permettent de faire une analyse utile des diff6rences entre secteurs a cause du fait que plusieurs industries chevauchent les deux secteurs. On peut donc comparer les secteurs pour une meme industrie. Les resultats suggerent que les cofuts d'operation des syndicats, par rapport a la taille des etablissements, sont importants pour expliquer la plus forte intensite de syndicalisation dans le secteur public. Les caracteristiques des employes ne semblent jouer aucun r6le. On examine aussi le rapport entre les ecarts de salaires et le syndicalisme militant du secteur public.

I. INTRODUCTION

Public sector unionization has grown substantially in both Canada and the United States in the last two decades. u.s. researchers (e.g., Freeman 1986) have drawn attention to the dramatic contrast in the experience of unions between the public

Funding for this research was provided in part by the Center for the Study of the Economy and the State, University of Chicago. Helpful comments were received on earlier versions of this paper from members of the center and from seminar participants at the University -of Chicago, York University, University of Toronto, University of British Columbia, and University of Windsor.

Canadian Journal of Economics Revue canadienne d'Economique, XXViII, No. 4b November novembre 1995. Printed in Canada Imprime au Canada

0008-4085 / 95 / 1056-76 $1.50 ? Canadian Economics Association



Union incidence 1057

and private sectors. The public sector unions have flourished at a time when private sector unionism was in decline. In Canada a similar contrast emerges, though in a less dramatic form. As a result of these different growth patterns, in both countries the level of public sector unionization is at least twice the private sector unionization rate. Two related questions emerge. First, why is the current incidence of unionization higher in the public sector than in the private sector? Second, why have the growth rates in the two sectors been so different over the last few decades? Both questions relate to the analysis of union incidence. A satisfactory analysis would provide a consistent explanation for these related incidence phenomena. The present paper deals with the first question.

The original empirical work in the paper utilizes Canadian data, which have an important advantage over u.s. data for the public-private union incidence question in that they contain important industries that have substantial overlap of ownership between public and private sectors. Their use permits, therefore, a more natural experiment of varying the form of ownership while holding the 'industry' constant.

The structure of the paper is as follows. In section ii the current incidence of unionization by industry and public and private sectors in Canada is presented. It shows a high level of public sector unionization even within a single industry category. Various approaches to explaining union incidence are discussed in section iII, together with a very brief review of existing evidence on the effects of variables typically used to explain incidence in North America. In section iv recent Canadian data are used to assess explanations of the pattern of industrial and public-private sector union incidence. Some conclusions are presented in section v.

II. CURRENT UNION INCIDENCE BY INDUSTRY AND SECTOR

Union incidence by industry and sector was computed using the 1984 Survey of Union Membership, conducted as a special supplement to the December 1984 Labour Force Survey. The relevant question in the survey is 'Was [the person] a member of a union or other group which bargains collectively with [the person's main employer]?' The sample was restricted to individuals who were currently employed paid workers less than seventy years of age. In the total sample of 35,915, 2,207 workers had missing union and wage data. The final sample imposed a positive wage restriction, resulting in a sample size of 33,708. The sample design includes weights used in the standard Labour Force Surveys which oversample, for example, the smaller provinces. The unionization rates reported in table 1 are computed both with and without the weighting. The results show dramatically higher unionization in the public sector (71.87 per cent) than in the private sector (27.57 per cent). There are some major industries that have a high degree of overlap between public and private sectors. These industries are Transportation, Communication, Education and Related Services, and Health and Welfare Services. Other industries that exhibit a moderate degree of overlap (more than 10 per cent of the industry owned by each sector and at least fifty workers in the sample per sector) are Electric Power, Water and Gas Utilities, Insurance Carriers, and Insurance Agencies and



1058 Chris Robinson

Real Estate. In each of these 'overlapping industries' the public sector unionization is substantially in excess of that of the private sector. This finding suggests that the difference in public and private sector unionization cannot be explained solely by differences in the industrial mix of the two sectors.

The importance of the difference in the industrial mix is addressed further in table 2. Table 1 shows that the high public section unionization rate is not due simply to high unionization rates in the government administration sector. Public Administration, comprising Federal, Provincial, and Local Administration, shows unionization rates lower than the public sector average. In table 2, the unionization rates in industries other than public administration are compared for the two sectors. The first row of the table shows a public sector unionization rate almost three times that of the private sector. In the second row the unionization rates are recalculated assuming that both sectors had the same industrial mix as the public sector. The difference between the two sectors is reduced from 0.4734 to 0.3218 - a reduction of one-third.

The evidence from tables 1 and 2 together indicates that there is an important role for industry characteristics to play in explaining union incidence, including the difference between public and private sectors. In table 1 the correlation between unionization rates in the public and private sectors is 0.7294. In table 2 the difference between public and private sector unionization is reduced by one-third when industry characteristics are 'held constant,' assuming that industry characteristics are the same within the two-digit codes employed in the data. This is not an in- nocuous assumption, since the two-digit categories are fairly broad. If the public sector is involved in subsets of the category that have different characteristics than those of the private sector, the above assessment of the importance of industrial mix will be biased. A distinction can be made here between changes in the observed characteristics of the industry caused by the differences in ownership - for example, firm or plant size and difference due to the public sector's specializing in different subsets of the two-digit industry. In the former case the industry characteristics themselves should not be held constant in assessing the effect of public sector ownership on unionization.

III. EXPLANATIONS OF UNION INCIDENCE

Most of the theoretical literature on unions permits only two levels of union incidence: zero or 100 per cent. The traditional monopoly models deal with industries that are 100 per cent unionized. The efficient-bargains model is generally set in the context of a union facing a single firm with monopoly power (see, e.g., McDonald and Solow 1981; MaCurdy and Pencavel 1987). If the firm facing a downward- sloping demand curve is considered to be the industry, this model also deals with 100 per cent unionization cases. If the efficient-bargains assumption is taken to mean the assumption that unions face many competitive firms, as in the monopoly model, but can set the employment level as well as the wage, subject to zero profit for the firms, it can be shown that again 100 per cent unionization will result (MacDonald and Robinson 1992).




TABLE 1 Union incidence, 1984

Private sector Public sector

Industry Weighted Unweighted N Weighted Unweighted N

Agriculture 0.0234 0.0250 521 - - 0 Forestry, Fishing, and Trapping 0.3488 0.3095 294 0.5864 0.5581 43

Forestry 0.3436 0.2863 255 0.5552 0.5000 28 Fishing and Trapping 0.4140 0.4615 39 0.6571 0.6667 15

Minning (excluding Services) 0.4061 0.4385 561 0.4013 0.6122 49 Metal Mines 0.5579 0.6212 198 * * 3 Mineral Fuels 0.1829 0.2257 257 0.2732 0.4348 23 Non-Metal Mines 0.7339 0.6905 84 0.7960 0.8261 23 Quarries and Sandpits 0.3122 0.3182 22 - - 0 (Services Incidental to Mining) 0.0261 0.0359 223 - - 0

Manufacturing Industries 0.4482 0.4489 5678 0.7137 0.7818 55 Food and Beverage 0.4742 0.4678 962 * * 1 Tobacco Products 0.4330 0.4118 17 - 0 Rubber and Plastic Products 0.4143 0.3167 221 - - 0 Leather 0.3483 0.3333 78 - - 0 Textiles 0.5407 0.5724 152 - 0 Clothing 0.3212 0.3540 322 - - 0 Wood 0.5204 0.4979 484 * * 1 Furniture and Fixtures 0.4156 0.3521 142 - - 0 Paper and Allied Industries 0.7325 0.7613 465 * * 3 Printing, Publishing, Allied 0.2624 0.2206 399 - - 0 Primary Metal 0.5580 0.5987 314 0.8559 0.8333 12 Metal Fabricating 0.4050 0.3950 344 * * 2 Machinery 0.3616 0.3391 233 * * 4 Transportation Equipment 0.6671 0.6210 533 0.9649 0.9500 20 Electrical Products 0.3331 0.3483 379 - - 0 Nonmetallic Mineral Products 0.4747 0.4400 150 - - 0 Petroleum and Coal Products 0.2241 0.2394 71 * * 4 Chemical and Chemical Products 0.2539 0.2926 229 * * 8 Miscellaneous Manufacturing 0.2777 0.2514 183 - - 0

Construction (excluding Service) 0.3918 0.3295 1393 - - 0 General Contractors 0.3612 0.2905 630 - - 0 Special Trades Contractors 0.4152 0.3617 763 - - 0 (Services Incidental to Construction) 0.1723 0.1818 11 - - 0

Transportation 0.3638 0.3433 903 0.8296 0.8435 639 Storage 0.3065 0.3065 62 - - 0 Communication 0.6068 0.5414 399 0.7548 0.7689 502 Electric Power, Gas, and Water Utilities 0.4109 0.3600 75 0.6888 0.6793 343 Trade 0.1196 0.1057 5967 0.5287 0.5488 82

Wholesale Trade 0.1273 0.1280 1445 0.0755 0.1250 16 Retail Trade 0.1172 0.0986 4522 0.5961 0.6515 66

Finance 0.0545 0.0551 1507 0.5010 0.4737 171 Finance Industries 0.0573 0.0558 878 0.1523 0.2813 32 Insurance Carriers 0.0485 0.0496 282 0.7812 0.8113 53 Insurance Agencies and Real Estate 0.0533 0.0576 347 0.4547 0.3372 86



1060 Chris Robinson

TABLE 1 (Concluded)

Private sector Public sector

Industry Weighted Unweighted N Weighted Unweighted N

Education and Related Services 0.4284 0.4439 633 0.7970 0.7888 2277 Health and Welfare Services 0.5071 0.5070 2493 0.7070 0.6915 1099 Religious Organizations 0.0248 0.0299 268 - - 0 Other Service 0.0896 0.0740 4500 0.3945 0.3889 36

Amusement and Recreational Services 0.1238 0.0961 281 0.1920 0.2222 18 Services to Business Management 0.0587 0.0514 1011 * * 8 Personal Services 0.0706 0.0522 517 * * 3 Accommodation and Food Services 0.0969 0.0750 2094 * * 5 Miscellaneous Services 0.1263 0.1173 597 * * 2

Federal Administration - - 0 0.6795' 0.6846 1021 Provincial Administration - - 0 0.6843 0.7027 1073 Local Administration - - 0 0.6384 0.5700 826

TOTAL** 0.2759 0.2566 25492 0.7187 0.7151 8216

SOURCE: Survey of Union Membership, 1984, microtape. Household Surveys Division, Statistics Canada

NOTES 1. Sample restrictions were currently employed paid workers with positive wage rates, under seventy

years of age. 2. The file includes weights designed to make each individual represent the relevant number of indi-

viduals with the observations characteristics in the population. Major departures from randomness follow from oversampling the smaller provinces.

*Not computed, owing to small number of cases -**The private total includes five cases coded as 'other government offices.'

TABLE 2 The effect of industrial mix on the difference in public and private sector unionization

Unionization rates excluding public administration

Public sector Private sector Difference

Unadjusted 0.7493 0.2759 0.4734 Adjusted* 0.7493 0.5275 0.3218

*Assuming public sector industrial mix

Because of the lack of theories permitting partial unionization, most discussions of industrial incidence have taken a probabilistic form. The question typically posed is 'Is the probability of unionization higher in this industry?' rather than 'Is the level of unionization higher in this industry, given existence?' This is similar to the distinction in labour supply studies between participation and hours of work.




The existence of unions in an industry and the extent of their coverage are related but are not the same issues. Factors relevant for one may not have the same effect or even be relevant for the other. Of particular interest in the present context is the pattern for public sector unions, which at one point did not exist but, given existence, have a higher-than-average coverage. It is not clear that the industries currently without unions would not have a higher-than-average equilibrium level of coverage should factors relevant to existence change.

Some recent papers that do deal explicitly with both union coverage and existence are Lazear (1983) and MacDonald and Robinson (1992). Lazear's model assumes that firms differ in their ability to resist unions and that unions and finns are asymmetrically informed about individual firm abilities. The presumed differences among firms permit both unions and non-union firms to exist in an otherwise competitive environment. In essence the model is one in which the price of the labour input has two components: the actual wage, and a union-imposed cost which varies across firms. The marginal union and non-union firms pay the same total price and hence can coexist. Lazear's predictions are stated primarily in terms of the probability of an equilibrium's occurring which includes the presence of a union. The extent of coverage, however, is explicitly predicted to be inversely related to union operating costs.

An alternative model, in the spirit of the monopoly union approach, is provided in MacDonald and Robinson (1992). It deals with union power that arises from the union's size relative to competitive firms in an industry. Given free entry of firms, the union firms have to be protected from unlimited entry - a requirement that must hold whether coverage is or is not complete. Given this power to protect its union firms, incomplete union coverage as an equilibrium outcome depends only on whether it pays for the union to let some non-union firms operate.

The size of the union (or union incidence in the industry) is determined largely by the costs of operating the union. As is the case of firm size limits, the factor that may limit the size of unions is increasing costs of operating with size. Costs are assumed to take the form

C(N,L) = C(N,N) (1)

where N is the number of unionized firms in the industry, 1 is the number of union workers at an individual firm, and L is total union membership in the industry. C(-) is assumed to be montonically increasing and strictly convex, reflecting the assumption that for a given total membership (L) costs are lower when union membership is concentrated in fewer locations.

The existence of C(-) yields incomplete union coverage under a variety of specifications of the union objective function. (See MacDonald and Robinson 1992 for some general conditions). Operating costs thus play an important role in deter- mining not only the probability of the existence of a union, but also the level of (potentially) partial coverage, given existence. Given the form of C(.), these costs are reflected in the number of workers, 1, at each location (plant size as measured



1062 Chris Robinson

by employment). The (employment) size of the plants or firms depends on the technology of the firms, reflected in a conventional profit function 7r(p, w; et), and a (downward-sloping) labour demand function l(p, w; a) = -air(p, w; ct/lw, where p is the price of the output, w is the union wage, and et indexes the technology. Unionized firms make zero profits in the equilibrium, with p = p(w) equal to the minimum average cost of the unionized firms. Thus plant size, l(p(W),W;O) =

l(w; et), depends on the union wage and technology.' Industries may vary in a variety of dimensions: technology (et), skill levels, the

cost function C(-) a union would face, etc. Consider variation in et such that at a given w some industries have a larger plant size (1) than others. Which industries will be most attractive to a monopoly union? General results depend on the objective function of the union (does it care about location size apart from its cost aspect?) For any objective function where the union cares only about the union wage, total union employment and its costs as given in (1), the union is better off in the industry whose technology results in a large plant size. For example, if the union maximizes net rents its objective function would be

R = (w - w7v)Nl(w; t) - C(N,Nl(w, ex)), (2)

where wv is the alternative (competitive) wage. Suppose there are two technologies et1 and Ot2 such that l(w; a,) < l(w; a2) for all w, and let (w ,N1) maximize R for cx1:

RMax(alt) = (wi - v)ATl(wi; c,) - C)(Ni N l(wi; ex)).

The union can always do better than this with ct2 by choosing the same wage (w1) and a value of N2 > N1 that holds L constant, in which case the revenue, (w, - fv-)L stays the same, but the costs, C(N2,L), fall. (A similar argument applies in the case of firms in the same industry that differ in size (cx) to show that within an industry the union firms will be the large ones.)

The question addressed above, of which industries are more attractive to unions, relates to the existence of unions in an industry rather than their equilibrium coverage. This is the same question addressed by the standard monopoly union models that stress the 'benefits' to unions in industries where the Marshallian industry labour demand is inelastic. There remains the further question: given that a union will operate in a particular industry, what will be its equilibrium level of coverage? Here the monopoly model formally implies 100 per cent for all industries. If costs for the union are introduced, however, as in the model referenced earlier, predictions may also be derived concerning industrial incidence. In essence, a larger plant size that prevents cost rising with membership as fast as they otherwise would results in greater union coverage. This result requires stronger assumptions than those used above, since the scale of the union operation must increase relative to the number

1 For simplicity, factors other than labour have been suppressed. They can be incorporated in the technology parameter, a.




of non-union workers in the industry, which does not follow automatically from total union 'profits' being higher.

Union incidence questions do not appear to have received as much attention in the empirical literature as, for example, the related issue of union differentials. Hirsch and Addison (1986) survey studies of union incidence by industry and note that there has been relatively little empirical work in this area. They note further that most of the work is restricted to the manufacturing sector. They report some evidence of a positive effect on unionization of industry concentration and capital intensity, rationalized primarily on inelasticity of labour demand grounds. More evidence is available on firm or establishment size and unionization where a positive relation is also found. The arguments for this relationship are based primarily on lower organization or operating costs for the unions.

Freeman and Medoff (1984) discuss evidence on industrial incidence in a widely cited book dealing with their 'two faces' theory of unionism.2 However, they do not make specific predictions from their theory to explain the observed industrial pattern. Instead they note the marked differences by industry and conclude that the 'tendency for unionism to proliferate in sectors with certain technological and market characteristics implies that workers' needs for unionism, management's opposition to it, and unions' efforts to extend it are not random but rather result from fundamental characteristics of these industries' (32-3).

Many u.s. researchers have noted substantial variation by geographic area in union density - in particular, the low rate of unionization in the south. In this connection several recent studies have been done on the effects of right-to-work laws, which vary geographically. It is well documented that in the states with right- to-work laws the level of unionization is low. There is much less agreement on the interpretation of the observed relationship. Recent work by Wessels (1981), Moore (1980), and Farber (1984) suggests that the right-to-work laws have little direct impact on unionization, with the correlation reflecting primarily more fundamental factors that are associated with passage of the laws.

There is a great deal of evidence from microdata to show that part-time workers and women are less likely to be union members than other workers (see, e.g., Lee 1978; Antos, Chandler, and Mellow 1980; Freeman and Medoff 1979; Robinson and Tomes 1984; Hirsch and Berger 1984). Similarly, there is strong evidence that union workers are more experienced and have longer job tenure. The causality for this relation, however, is subject to dispute. A similar causation problem arises

2 Freeman and Medoff (1984) argue that there are 'two faces' of unionism. In the monopoly view (which includes the efficient-bargains case) they note that the industry must be 100 per cent unionized for the union to survive if the industry is competitive in the standard. sense, though less than complete coverage could occur if firms differed in their costs or more generally were non- competitive. However, they contrast this view with the 'collective voice' face of unions which permits unions to exist in competitive environments by providing contract gains (broadly inter- preted). These gains arise, it is argued, essentially from providing contract mechanisms alternative to those available in the absence of unions, including contract enforcement mechanisms. These are not mutually exclusive aspects of unionism but are presumed to operate together as 'two faces' of unionism.



1064 Chris Robinson

from the use of the union wage differential, either as a proxy for the benefits to be obtained from unionization (hence making it more likely), or, as more recently argued, as a cost factor to the employer (making employers' 'resistance' more likely). Indeed, in many models of unions the wage differential will be an endoge- nous variable to be explained by the underlying 'technological' parameters rather than an explanatory variable itself. The covariation in the wage differential and union incidence that is induced by variation in the underlying exogenous variables may be positive or negative depending on which exogenous variables are most important in inducing the covariation. This issue has a considerable history going back to the debate over spillover effects reducing the non-union wage vs. threats effects increasing it (see, e.g., Rosen 1969).

This brief review indicates several factors that may be important in explaining incidence questions. A number of them have been used to try to explain recent time series phenomena, for example, the decline in u.s. private sector unionism. In a companion paper (Robinson 1991) the cost emphasis of the model of incomplete union coverage discussed above was used as the basis for a study of the Canadian disaggregated manufacturing time series cross-section patterns and, in particular, the contrast with the u.s. pattern. Evidence was presented there for an important role of union costs, as proxied by plant size, in explaining the Canadian cross-section and time series pattern, as well as Canada/United States differences. In the next section this cost emphasis is examined for its possible importance in explaining public-private sector differences.

IV. EXPLAINING THE CURRENT PATTERN OF UNION INCIDENCE IN THE

PUBLIC AND PRIVATE SECTORS

In both Canada and the United States incidence questions for the public sector have been dominated in recent years by the puzzle of public sector union growth. (See, e.g., Freeman 1986.) What is equally a puzzle, however, is the level or organization in the public sector given its characteristics. Suppose it is true, as Freeman (1986) argues, that 'the growth in public sector unionism in the past two decades can be traced, in large part, to the passage of laws (executive orders) that have sought to bring the private sector industrial relations model to the public sector' (42). The question remains: why, when the u.s. public sector unions are in essentially the same legal framework as private sector unions, is their equilibrium level of organization so high relative to the average in the private sector? In terms of the characteristics of the employees - particularly the high proportion of white-collar workers - the public sector should have had a low level of organization.

1. Differences in Industry Characteristics The evidence in section ii shows that even holding 'industry' constant, public sector unionization rates are higher. As noted, however, the industry categories are relatively broad, leaving the possibility of different industry characteristics across




public and private sectors even within measured industry categories.3 The main industry characteristic noted earlier as relevant for the union problem is firm or establishment size. The larger plant sizes are assumed to be associated with lower union costs. Most studies of this issue are confined to the manufacturing sector because of data availability. Since there is no public sector manufacturing, this approach cannot shed light on public-private differences. The approach used here utilizes size data available from two recent individual worker level surveys that cover both public and private sectors.

Data on 'company' size by industry and by public-private sector are available from the Quality of Life (QoL) survey used earlier in union studies by Robinson and Tomes (1984) and Robinson (1989). The 1981 questionnaire for this survey included the question: 'In total, how many people are employed by the company (or government) [at which the respondent worked] as a whole?' The responses were coded by the interviewer into the categories: less than 5, 5-9, 10-29, 30- 49, 50-99, 100-199, 200-499, 500 and over. Union data for 1981, comparable to the 1984 Union Membership Survey, were computed from the 1981 Work History Survey carried out as a supplement to the regular Labour Force Survey in 1982. One problem with these data is the relatively small size of the QOL survey (approximately 3,400 individuals) for computing disaggregated industry data on company size. An alternative source for the size data is a set of questions on the Labour Market Activity surveys relating to number of employees working for the respondent's employer. Unfortunately, all but one of the size questions have their answers suppressed on the microtape that was released from the first (1986) LMAS because of confidentiality requirements. The answers to a question similar to that of the QOL

are, however, reported for the categories: less than 19, 20-99, 100-499, and 500 and over. (The question was 'In total about how many persons were employed at all locations [of the respondent's employer] in Canada?') The standard tape release does not distinguish between public and private sector workers; however, on request Statistics Canada has made available a tape with the public-private categories in the 'class of worker' variable equivalent to that used in the 1981 Work History Survey and the 1984 Union Membership Survey. The LMAS largely overcomes the small sample size problem of the QOL data for the size variable and contains union data equivalent to those in the 1984 UMS.

Table 3 reports the unweighted data by public and private sectors for unionization rates and company size for the overlapping industries. The unionization rates were computed in the same way as the unweighted rates in table 1. The measure of company size is the percentage of individuals reporting that 500 or more employees work for their employer. Of the seven overlapping industries, three had to be omitted

3 There is some ambiguity in what constitutes an 'industry' in the data which complicates the empirical analysis of the coverage issue. It is assumed that, at the level of industry aggregation dealt with in the 1984 Union Membership Survey, the figures represent an average of several 'theoretical industries.' Thus the observation that table 1 shows no industry with 100 per cent unionization does not rule out the possibility of the existence of such unions. Instead, high rates of unionization may be associated with a larger fraction of the observed industry being made up of 100 per cent unionized theoretical industries.



1066 Chris Robinson

TABLE 3 Company size and unionization in the public and private sectors: overlapping industriesa 1981 and 1986 (numbers in parenthese indicate the sample size for the calculation of the industry percentage)

Public sector Private sector

Percentage Percentage employed Percentage Percentage employed union in large companiesb union in large companies

1981 Data (QOL and WHS)

Trans 0.82 (704) 0.83 (42) 0.37 (1136) 0.36 (61) Comm 0.71 (516) 0.91 (34) 0.53 (356) 0.71 (45) Educ 0.75 (2318) 0.72 (112) 0.42 (640) 0.50 (58) Health 0.69 (781) 0.69 (97) 0.50 (2438) 0.29 (93)

1986 Data (LMAS)

Trans 0.84 (545) 0.80 (429) 0.32 (992) 0.32 (845) Comm 0.81 (411) 0.95 (349) 0.48 (438) 0.66 (377) Educ 0.77 (2330) 0.40 (1987) 0.40 (921) 0.34 (841) Health 0.73 (963) 0.41 (890) 0.50 (2757) 0.28 (2505)

Electric 0.74 (368) 0.83 (312) 0.50 (76) 0.37 (59) Insurance

Carrier 0.66 (68) 0.69 (61) 0.07 (244) 0.55 (196) Insurance

Agency 0.34 (68) 0.24 (51) 0.05 (471) 0.16 (400)

a As indicated in the text, these are industries with more than 10 per cent of the industry owned by each sector and at least fifty workers in the 1984 UMS in each sector.

b Companies (or government agencies) employing more than 500 workers

for the 1981 data because of the very small sample sizes for computing company size in the QOL data. The 1981 data are reported in the top half of the table. The sample sizes used in calculating the industry percentages are given in parentheses. The uniformly larger unionization rate in the public sectors of these industries is matched by a uniformly larger company size. Results for all the overlapping industries are presented for 1986, where the sample sizes used in computing the company size variable is much larger. Again, size is uniformally higher in the public sector of the industry. The only substantial difference is a lower estimated size variable for the Education and Health industries in the 1986 data relative to that in the 1981 data, for the public sector. The additional three industries for which industry percentages could be computed from the larger 1986 data set confirm the pattern in the other industries: company size and unionization are larger in the public sector of the industry.

The results of table 3 suggest an important role for plant size in explaining differences between public and private sector union incidence. The analysis was pursued further by testing for the significance of the effects of size in a regression framework that is not restricted to the overlapping industries. The 1986 data contain thirty-one industry/sectors for which at least 300 workers are available for




computation of the industry/sector aggregates. For 1981, data could be constructed for all but one of these industries, though the sample sizes for the size of employer variable are much smaller. The analysis reported in table 4 uses the thirty industry/sectors common to both 1981 and 1986.

The observations in table 4 are public or private sectors of industries disaggregated to the same level as reported in table 1. A dummy variable (PUBLIC) indicates whether the observation is for a public or private sector of the industry. (The data include eight public and twenty-two private sector observations.) Columns 1-4 refer to 1981; columns 5-8 report the equivalent regressions for 1986. Column 1 reports a simple regression of the percentage unionized in the industry/sector on the percentage of workers in the public sector of the industry. This yields an estimate for the average unionization rate in the private sector of 28.3 per cent and in the public sector of 69.3 per cent, the public ownership making an estimated difference of 41 percentage points on the unionization rate. Although these observations are from a subset of the universe for the unionization rates in table 1 and are unweighted by size of industry/sector, they produce estimates of the sector unionization rates that are very similar. Recalculating the rates for table 1 using the comparable individual level data in the 1981 Work History Survey yields an estimated private sector unionization rate of 26.0 per cent and a public sector rate of 69.2 per cent - an estimated difference of 43.2 percentage points.

Columns 2-4 use various measures of employer size as controls (see notes to the table for definitions). In all specifications the effects of size are statistically significant and dramatically reduce the estimated effect of public sector status. In the absence of size controls the estimated public ownership effect is 50-100 per cent larger. The analysis is repeated for 1986 in columns 5-8. The estimates (column 5) for the average private and public sector unionization rates are 26.7 per cent and 72.9 per cent, respectively. Recalculating the rates as in table 1 for 1986 using the LMAS yields private and public sector rates of 25.0 per cent and 71.0 per cent, respectively. Again the unweighted data for the subset of industry/sectors employed in table 4 reproduced very closely the estimates from the full-sample individual data. Controlling for size in columns 6-8 has the same effect as in the 1981 data, reducing the effect of public ownership by as much as a half.

The analysis was repeated using larger samples of industries and including controls for average individual characteristics (percentage female and percentage production workers) and showed the same pattern. These results suggest that differences in (measured) individual characteristics are not important in explaining public-private sector differences in union incidence. By contrast, there appears to be an important role for industry characteristics, such as size, to play in explaining the incidence of unionization not only across industries, but also across public and private sectors. The harder question remains of why public sector operations, even within the same industry, tend to be larger.

2. Differences in individual characteristics A variety of individual characteristics has been used as proxies for both union



1068 Chris Robinson

TABLE 4 Regression analysis of employer size and differences across industries in public and private sector unionization rates dependent variable: percentage unionized in the industry

1981 1986

1 2 3 4 5 6 7 8

Public 0.410 0.206 0.267 0.228 0.462 0.317 0.282 0.237 (5.44) (2.01) (3.63) (2.78) (6.05) (4.10) (4.44) (3.67)

Percentage Large 0.438 0.427 (2.67) (3.45)

Percentage Small -0.552 -1.005 -6.627 -1.341 (3.69) (2.24) (5.36) (3.56)

(Percentage Small)2 0.724 0.879 (1.13) (1.98)

Constant 0.283 0.151 0.438 0.488 0.267 0.139 0.501 0.596 (7.26) (2.48) (8.25) (7.05) (6.77) (2.78) (9.67) (8.65)

R2 0.513 0.615 0.676 0.691 0.567 0.699 0.790 0.818 N 30 30 30 30 30 30 30 30

NOTES: The data used in table 4 were as follows:

Variable Definition and source

1981 data Percentage unionized Unweighted unionization rate for the industry/sector from the 1981 Work

History Survey (Paid Employees) Public Dummy variable equal to 1 if the observation is for the public sector of an

industry as coded in the 1981 Work History Survey (Paid Worker Government Business or Government Non-Business).

Percentage large (small) Unweighted proportion of individuals in the industry/sector from the 1981 Quality of Life Survey that worked for a company or government that employed 500 or more people (less than ten people).

1986 data Percentage unionized Unweighted unionization rate for the industry/sector from the 1986 Labour

Market Activity Survey (Paid Employees) Public Dummy variable equal to one if the observation was for the public sector of

an industry as coded by request by Statistics Canada for the 1986 LMAS. Percentage large (small) Unweighted proportion of individuals in the industry/sector from the 1981

LMAS that worked for a company or government that employed 500 or more people. (less than twenty people)

The data for the two years were quite similar:

Standard Mean deviation

Variable 1981 1986 1981 1986

Percentage union 0.392 0.390 0.257 0.276 Public 0.267 0.267 0.450 0.450 Percentage large 0.426 0.391 0.281 0.281 Percentage small 0.212 0.297 0.221 0.245




TABLE 5 Individual characteristics by sector within overlapping industriesa

Transportation Communication Education Health

Public Private Public Private Public Private Public Private

Age (years) 15-19 0.013 0.053 0.018 0.020 0.015 0.035 0.016 0.028 35-64 0.613 0.504 0.524 0.4i9 0.655 0.491 0.521 0.497 65-69 0.000 0.006 0.004 0.000 0.004 0.002 0.001 0.004

Tenure (years) 0-1 0.116 0.287 0.100 0.165 0.166 0.253 0.169 0.209 6-10 0.216 0.150 0.249 0.243 0.211 0.177 0.264 0.219 11- 0.546 0.267 0.448 0.393 0.416 0.265 0.236 0.227

University degree 0.036 0.033 0.084 0.098 0.540 0.524 0.175 0.134 Part time 0.017 0.114 0.124 0.050 0.167 0.209 0.201 0.274 Male 0.908 0.817 0.572 0.559 0.422 0.507 0.171 0.170

Region Atlantic 0.318 0.192 0.175 0.248 0.237 0.197 0.286 0.187 Quebec 0.141 0.148 0.120 0.218 0.171 0.193 0.023 0.213 Ontario 0.125 0.204 0.169 0.261 0.190 0.194 0.109 0.216 Prairies 0.335 0.333 0.510 0.143 0.313 0.341 0.475 0.306

a The estimates presented are the means of dummy variables defined as 1 if the individual has the relevant characteristics.

costs (some types of employees are assumed more costly to organize) and benefits (some employees have greater attachment to the market and thus a longer pay-off period to any wage gain). A possible explanation for some of the differences in public and private sector unionization may therefore be differences in individual characteristics. The results in table 4 did not provide any evidence for the importance of individual characteristics. To pursue this point further, an analysis using the individual level data was undertaken. In order to hold industry characteristics constant as far as possible, only data on the major overlapping industries were used. In table 5 the means of dummy variables defined on individual characteristics for each sector are presented by industry. Inspection of table 5 shows that within an industry the public sector workers tend to be older, have more tenure, have less part-time status. They are also more likely to be male. Although the differences do not appear to be very large, these characteristics traditionally have been associated with a higher probability of union status. An attempt was therefore made to correct for these differences in characteristics in computing the difference between public and private sector unionization.

A linear probability model of union status was estimated (not reported here) for each sector within each overlapping industry. A major feature is that within industries individual characteristics do not operate in the same way as they do across industries. In particular, within the overlapping industries being male is associated with a higher probability of union status in Transportation, but a lower probability of



1070 Chris Robinson

TABLE 6 Unionization rates in overlapping industries by public and private sector

Transportation Communication Education Health

Rates unadjusted for individual characteristics

Public sector 0.8435 0.7689 0.7888 0.6915 Private sector 0.3433 0.4514 0.4439 0.5070 Difference 0.5002 0.2275 0.3449 0.1845

Rates assuming public sector individual characteristics

Public sector 0.8435 0.7689 0.7888 0.6915 Private sector 0.4540 0.4480 0.4964 0.4987 Difference 0.3895 0.3209 0.2924 0.1928

NOTE: These rates use the unweighted data.

union status in the other three major overlapping industries. In table 6 unionization rates are calculated with and without controls for individual characteristics. In the top half of the table the unionization rates for each of the major overlapping industries, using unweighted data, are presented and the differences between public and private unionization rates are calculated. In the lower half of the table the private sector unionization rate is predicted from the linear probability model using the private sector coefficients but the public sector individual characteristics. The difference between the sector unionization rates is again calculated. While the difference is reduced for Transportation and Education, it is increased for the other two sectors. Moreover, even in the industries where the difference is reduced, it remains substantial. Thus, there is still a major portion of the difference between public and private sector unionization that is unexplained by differences in the industries unionized or in the characteristics of the individuals in the two sectors.

3. Differences in wage gains As noted in section iii, the relation between the union wage differential and union coverage is theoretically ambiguous. Arguments advanced to explain high public sector unionization via the 'benefits' of high wage differentials are thus subject to criticism. Nevertheless, there has been a substantial amount of research on the relative .size of union differentials in the public sector stimulated by the observed organizations successes in this sector (see, e.g., Baugh and Stone 1982; Ashen- felter 1971; Ehrenberg 1973; Bartel and Lewin 1981; Gyourko and Tracy 1988; Moulton 1990). There has also been some recent work on explaining cross-country and time series patterns of unionization, using observations on wage differentials (Blanchflower and Freeman 1990).

Public sector differentials may be different from private sector differentials for a variety of reasons. The reason offered in the literature is the possibility of a less elastic demand for labour in the public sector, though this claim is rejected by




Freeman (1986).4 In the present context, comparing public and private sectors of the same industry, alternative arguments are necessary. It is possible, for example, that public sector employees are in local monopoly situations regarding their industry relative to the private sector.

The wage differentials calculated to explain union incidence in the previous literature typically have been obtained by estimating a standard oLs log wage equation. There is considerable evidence, however, that the endogeneity of union status bi- ases the estimates of the union differential (see, for e.g., Duncan and Leigh 1985, Robinson 1989).5 This issue will be examined using alternative estimators. The specification of the wage equation is complicated by an important difference between the public and private sectors discussed in the previous sections. The public sector was shown to have a much higher level of union coverage, even within an industry. The potential effect of coverage on wages complicates the calculation or interpretation of union differentials in the two sectors. Earlier research on Canadian data (Robinson and Tomes 1984) suggests that the large value of the percentage of organized workers (pow) in the public sector is a major contribution to the high earnings in that sector. Should the differential be calculated holding Pow constant, as for any other regressor in the wage equation? The answer depends on the structure underlying the relation between coverage and wage differentials. A case could be made for evaluating the public sector at its actual level of Pow and comparing it with the private sector at the private sector level of Pow and comparing it with the private sector at the private sector level of Pow, since this will be the wage difference at the equilibrium. Unfortunately, in the data there is very little overlap in the public and private sector distribution for Pow, making it hard to separate the effects of Pow and public sector status. The data set employed was the 1986 wave of the Labour Market Activity Survey for which public sector status was made available to the author by Statistics Canada. 15,841 hourly paid workers were used for the estimation. Table 7 contains some descriptive statistics on the data set by public and private sector. The basic oLs estimating equation is

ln Wi = Xi3 + 6,Ui + bpPi + bUiPi +YUipowi + -i, (3)

where Wi is the hourly wage of individual i; Ui and Pi are dummy variables indicating union membership and public section status, respectively; Powi is the percentage of organized workers in the individual's industry/sector; and Xi is a vector of exogenous regressors: Region, Schooling, Age, Sex, Tenure, Firm Size, and the Pow. Differentials implied by the estimated coefficients of equation (3) are presented in table 8.

In panel A differentials are computed at the total sample mean for all regressors. The oLs estimates (col. 1) show no difference in the size of the union differential

4 Freeman argues that public sector budget constraints act like elastic product demand curves, that local public sector monopolies are neutralized in the long run by mobility, and that 'essential' workers are usually prohibited from striking.

5 Gyourko and Tracy (1988) also allow for endogeneity of their government sector choice.



1072 Chris Robinson

TABLE 7 Data definition and descriptive statistics

Mean

Public Private Name Definition (N = 2516) (V= 1332)

Variables in the wage equation Atlantic Dummy variable equal to 1 if resident in Atlantic Province 0.239 0.198 Quebec Dummy variable equal to 1 if resident in Quebec 0.107 0.148 Ontario Dummy variable equal to 1 if resident in Ontario 0.169 0.243 Prairies Dummy variable equal to 1 if resident in prairie province 0.398 0.304 ED1 Dummy variable equal to 1 if none or elementary education 0.083 0.111 ED2 Dummy variable equal to 1 if post-secondary certificate

or diploma 0.321 0.238 ED3 Dummy variable equal to 1 if university education 0.146 0.057 Age Mid-point (actual years) of coded age category 38.982 34.104 Male Dummy variable equal to 1 if male 0.500 0.523 Tenure Actual years of tenure 8.017 5.107 Size Number of people working for respondent's company

(mid-point of coded category) 348.092 211.702 Union Dummy variable equal to 1 if union member 0.702 0.262

Dependent variable LN(Wage) Natural logarithm of hourly wage in cents 7.000 6.675

Variables excluded from the wage equation Married Dummy variable equal to 1 if married 0.734 0.600 PTime Dummy variable equal to 1 if part time 0.252 0.295 AVsize Fraction of people in companies with 500+ employees

in respondent's industry 0.547 0.301

Cumulative distribution of the percentage of organized workers Public Private

0-4.9 0.0 3.3 5-9.9 0.0 23.4 10-14.9 0.0 52.3 15-19.9 0.0 53.3 20-24.9 0.0 53.8 25-29.9 0.0 58.5 30-34.9 1.1 71.2 35-39.9 1.1 72.9 40-44.9 1.1 75.1 45-49.9 1.1 82.4 50-54.9 1.1 94.0 55-59.9 14.7 96.3 60-64.9 23.7 98.3 65-69.9 24.4 98.3 70-74.9 63.3 100.0 75-79.9 63.3 80-84.9 78.7 85-89.9 100.0

NOTES 1. The wage equation also included the square of AGE and a dummy variable set for the percentage of

organized workers. 2. The computations were performed using the microdata tape for the Labour Market Activity Survey,

1986 wave, supplied by Statistics Canada. The computations are solely the responsibility of the author. 3. The omitted region is British Columbia; the omitted education category is some or completed high

school.




TABLE 8 Union and public sector wage differentials, 1986

Estimation method

(1) (2) (3) OLS IV IM

A. Evaluated at sample mean values for all regressors Union differential

Public sector workers 0.2920 0.5410 0.6132 Private sector workers 0.2907 0.5965 0.6179

Public sector differential Union workers -0.0758 -0.0980 -0.0846 Non-union workers -0.0768 -0.0655 -0.0819

B. Evaluated at respective sector (public or private) means for POW Union differential

Public sector workers 0.2567 0.3024 0.6758 Private sector workers 0.2975 0.6479 0.6063

Public sector differential Union workers 0.0631 -0.0874 -0.0007 Non-union workers 0.0976 0.1145 -0.0422

NOTES 1. The estimated differentials were calculated as e'n WA-In WB - 1, where ln WA

and ln WB are the predicted log wages for the two categories of workers, A and B, being employed for the relevant comparison.

2. In panel A predicted log wages are evaluated at the total sample means for all regressors for both components of each comparison.

3. In panel B predicted log wages for public (private) sector workers are computed using the public (private) sector sample mean for POW and the total sample mea for the remaining regressors.

(29%) between the public and private sectors. The estimated public sector differentials are negative. In panel B, using the separate (public or private) sector means when computing the differentials, the results show similar-sized union differentials with only a small difference emerging between public and private sector union wage differences. The public sector differentials themselves are markedly different from before, however, being positive instead of negative. This finding is similar to the results on an earlier data set analysed in Robinson and Tomes (1984), where Pow could also be held constant. There it was argued that previously measured positive public sector differentials found in earlier work (e.g., Smith 1977; Gunderson 1979) may have been largely due to the greater equilibrium level of unionization in the public sector.

The two measures of public sector differentials address different questions. The adjusted differential (holding Pow constant) look at what the difference between public and private sector wages would be in the absence of effects due to differential unionism. The unadjusted differential measures the difference made by being in the public sector, taking as part of the public sector's characteristics that it is more highly unionized. Theoretically, the role of Pow has often been specified



1074 Chris Robinson

as indicating the strength of the union itself on the one hand, and the strength of the 'threat effect' on the other (Rosen 1969). The relation between Pow and union strength, though, is complicated. Presumably in competitive industries with elastic supplies there would be no threat effect. Within manufacturing, Freeman and Medoff (1981) report evidence against threat effects. The wage equations estimated here, however, show positive effect of Pow for both union and non-union workers. One explanation may be that at least a subset of the industries are not competitive. An alternative explanation is that Pow is capturing industry effects common to both union and non-union workers. To be consistent with the positive effect of Pow, this explanation would also have to assume that the highly unionized industries were those with the largest industry-compensating differentials.

There remains the problem of the sensitivity of the estimates of the wage differentials to the endogeneity of union status. This question was addressed by computing alternative instrumental variable (iv) and Inverse Mills Ratio (IM) estimators. The specification for these estimators is similar to Robinson (1989). The primary departure from that common specification was the treatment of firm size. Since size differs markedly between the sectors, it was not excluded from the wage equations. Instead, the individuals' wages were allowed to depend on the size that they reported at their own location, but not on the average size in their industry given their own location size. Both measures of size, however, were assumed to affect union costs and hence the probability of unionization. The results are presented in columns (2) and (3) in table 8.

The results for the union differential show that 'corrected' estimates tend to raise the union differential. This pattern is common in the literature (see Robinson 1989 for details). The relative pattern for the union differentials in the two sectors again provides no strong evidence of larger differentials for the public sector. In panel A, apart from being larger than the OLS estimates, the union differentials remain similar in the public and private sectors. The public sector differentials are essentially the same as the oLs estimates. In panel B, for the union differential the only significant change is the evidence of a larger union differential in the private sector from the iv estimator. For the public sector differentials the iv and IM estimators show a similar direction of change between panels A and B as exhibited by the oLs estimates, but the change is less marked. While the oLs estimates change from negative to positive when Pow is not held constant, the iv and IM estimates change from negative to either positive or less negative. It remains important, therefore, to treat the role of union coverage carefully when analysing public sector differentials.

V. CONCLUDING REMARKS

The fact that the public sector has a much higher level of unionization than the private sector, in both Canada and the United States, is something of a puzzle. Before the legislative changes of the 1960s the low level of unionization in the public sector was 'explained' in terms of its large proportion of women and white- collar workers - groups whose unionization rates were low anyway. Now the public




sector has a rate of unionization that is twice that of the private sector without much change in its female and white-collar make-up. The legislative changes made it possible for unions to form - but the question remains why, having formed, do they have such a high rate relative to the private sector?

Evidence presented above suggests that union cost factors, as related to the size of the 'plants' in which people work, can play an important role in an explanation of public-private sector differences. This finding is consistent with the evidence on plant size in explaining differences within the private sector as well as across time in the private sector (Robinson 1991). Evidence for the importance of individual characteristics in this issue suggests that they have little, if any role to play. Finally, the connection between wage differentials and public sector unionism was briefly addressed. Freeman and Medoff (1984) report lower union differentials in the public sector as the standard finding in the literature (though they argue that the public sector union effect may be underestimated for various reasons). This finding has damaged the hypothesis that the public sector provided an attractive target for unions because of larger benefits obtainable because of, for example, a presumed less elastic demand for labour in the public sector. The results obtained in this study are consistent with the earlier results, showing no evidence of larger union differentials in the public sector. Examination of wage differences between public and private sector workers provides evidence for an important role for the very high level of union coverage in the public sector in explaining public sector differentials. The evidence suggests that if coverage was the same in the public and private sectors, public sector differentials would actually be negative.

REFERENCES

Antos, J.R., M. Chandler, and W. Mellow (1980) 'Sex differences in union membership.' Industrial and Labor Relations Review 33, 162-9

Ashenfelter, 0. (1971) 'The effect of unionization on wages in the public sector: The case of fire fighters. Industrial and Labor Relations Review 24, 191-202

Bartel, A., and D. Lewin (1981) 'Wage and unionism in the public sector: the case of police.' Review of Economics and Statistics 63, 53-9

Baugh, W.H., and J.A. Stone (1982) 'Teachers, unions and wages in the 1970s: unionism now pays.' Industrial and Labor Relations Review 35, 368-76

Blanchflower, D., and R. Freeman (1990) 'Going different ways: unionism in the u.s. and other advanced O.E.C.D. countries.' NBER Working Paper No. 3342

Duncan, G., and D. Leigh (1985) 'The endogeneity of union status: an empirical test.' Journal of Labor Economics 3, 385-402

Ehrenberg, R.G. (1973) 'Municipal government structure, unionization and the wages of fire fighters.' Industrial and Labor Relations Review 27, 36-48

Farber, H.S. (1984) 'Right to work laws and the extent of unionization.' Journal of Labor Economics 2, 319-52

Freeman, R.B. (1986) 'Unionism comes to the public sector.' Journal of Economic Litera- ture 24, 41-86

Freeman, R.B., and J.L. Medoff (1979) 'New estimates of private sector unionism in the United States.' Industrial and Labor Relations Review 32, 143-74 (1981) 'The impact of the percent organized on union and nonunion wages.' Review of Economics and Statistics 64, 561-72



1076 Chris Robinson

- (1984) What Do Unions Do? (New York: Basic Books) Gyourko, J., and J. Tracy (1988) 'An analysis of pubic- and private-sector wages, allowing

for endogoneous choices of both government and union states.' Journal of Labour Economics 6, 229-53

Gunderson, M. (1979) 'Earnings differentials between public and private sectors.' This Journal 12, 228-42

Hirsch, B.T., and J.T. Addison (1986) The Economic Analysis of Unions (Boston: Allen & Unwin)

Hirsch, B.T., and M.C. Berger (1984) 'Union membership determination and industry characteristics.' Southern Economic Journal 50, 665-79

Lazear, E.P. (1983) 'A competitive theory of monopoly unionism.' American Economic Review 73, 631-43

Lee, L.F. (1978) 'Unionism and wages rates: a simultaneous equations model with quali- tative and limited dependent variables.' International Economic Review 19, 415-34

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

MaCurdy, T.E., and J. Pencavel (1986) 'Testing between competing models of wage and employment determination in unionized markets.' Journal of Political Economy 94, S3-39

MacDonald, G., and C. Robinson (1992) 'Unionism in a competitive industry.' Journal of Labor Economics, forthcoming

McDonald, I.M., and R.M. Solow (1981) 'Wage bargaining and employment.' American Economic Review 71, 896-908

Moore, W.J. 'Membership and wage impact of right to work laws.' Journal of Labor Research 1, 349-68

Moulton, B. (1990) 'A reexamination of the federal-private wage differential in the United States.' Journal of Labor Economics 8, 270-93

Robinson, C. (1989) 'The joint determination of union status and union wage effects: some tests of alternative models.' Journal of Political Economy 97, 639-67

-(1991) 'Explaining patterns of unionization: Canada and the United States.' Mimeo. Robinson, C., and N. Tomes (1984) 'Union wage differentials in the public and private

sectors: a simultaneous equations specification.' Journal of Labor Economics 2, 106- 27

Rosen, S. (1969) 'Trade union power, threat effects and the extent of organization.' Re- view of Economic Studies 36, 185-96

Smith, S. (1977) Equal Pay in the Public Sector: Fact or Fantasy? (Princeton, NJ: Indus- trial Relations Section, Princeton University)

Wessels, W.J. (1981) 'Economic effects of right to work laws.' Journal of Labor Research 2, 55-75



Documents

Union Incidence in the Public and Private Sectors