Insider power, outside ineffectiveness and wage setting institutions: evidence from Australia.
Insider-outsider theories have been advanced to explain a range of phenomena, principally the persistence of unemployment. This paper uses data from the Australian Workplace Industrial Relations Survey 1995, and regional labour force survey data, to test this model. The paper also examines how enterprise bargaining influences the relative power positions of insiders and outsiders. The paper finds provisional support for the insider-outsider distinction, and for the idea that enterprise level wage bargaining enhances insider power at the expense of outsiders.
Insider-outsider models have been advanced to explain a range of phenomena, principally the persistence of unemployment. The first purpose of this paper is to provide an empirical test of this theory using Australian micro-data. The second purpose is to examine the relationship between wage setting institutions and insider power. Specifically, the paper seeks to establish whether enterprise level wage setting facilitates or restrains insider power. Analysis of the Australian experience is well suited to this task, since this economy has been moving from a centralised, at times corporatist, wage setting system to one based at the enterprise, over the past two decades. The result is a hybrid system of centralised and decentralised elements.
A considerable body of international evidence exists testing the insider-outsider theory. While the evidence is far from unidirectional, it is reasonable to say that there is considerable support for the insider-outsider distinction in the international evidence, particularly in the micro-data studies. The evidence from aggregate data studies is more mixed. One reason for this is that research based on aggregate data invariably has to rely on only a small number of observations. Several Australian researchers have found support, in various ways, for the theory using aggregate data. These include Gregory (1987), Watts and Mitchell (1990), Flatau, Lewis and Rushton (1990), Flatau, Lewis and Rushton (1991), Kenyon (1990) and Groenewold and Taylor (1992). (1) The research reported in this paper can be seen as complementing these aggregate data studies.
There also exists a large body of international empirical evidence examining the impact of wage setting institutions on insiders and outsiders. This evidence is quite mixed. I argue in section 3 that this is due to the inherent limitations of intercountry comparisons, the favourite method for testing these ideas. The Australian experience allows for an analysis of a single country which has undergone a rich and diverse experience with wage setting institutions in recent years. Australian researchers, including Chapman and Gruen (1990), Flatau, Lewis and Rushton (1990), Flatau, Kenyon, Lewis and Rushton (1991) and Kenyon (1990), all used aggregate data to find evidence to support the view that Australia's experiment with corporatist wage setting in the 1980s had the effect of restraining insider power. This paper complements this previous research by using micro-data to examine how enterprise bargaining impacts on insider power and outsider ineffectiveness.
Achieving the two objectives of this paper is facilitated by the availability of the Australian Workplace Industrial Relations Survey 1995 (AWIRS 1995). This survey provides a rich, nationally representative, snapshot of a labour market with centralised and decentralised elements. The paper is organised as follows. In the next section, the insider-outsider model is outlined briefly (2). In section 3, Australia's wage setting institutions and their connection to this topic are discussed. Section 4 discusses data and methodology. Section 5 contains a description and discussion of the key variables employed in the empirical analysis. Section 6 discusses an important issue to do with collinearity in this study. Section 7 discusses several econometric issues, including the estimation procedures employed. Section 8 presents and discusses the results. The evidence suggests that the insider-outsider model fits the Australian labour market. It is also found that insider influences are strongest, and outsider influences weakest, where wages are set at the enterprise level. Section 9 contains the conclusion.
2. The Insider-Outsider Theory
All insider-outsider models share the idea that insiders are protected, when wages are set, from competition by outsiders. Insiders are usually employed workers; outsiders are usually the unemployed. The main implication of this is that wage outcomes, particularly in the aftermath of a negative shock to employment, may prevent a rapid return to the pre-shock employment level. Three broad approaches can be identified in the literature.
The first approach is most commonly associated with the names of Blanchard and Summers (1986, 1987). In this approach the ability of insiders to ignore outsiders in wage setting is simply assumed. This approach is best seen as an extension of the microeconomic trade union literature. In the union literature, the interests of employed and unemployed union members are equally important when the union bargains over wages. The main innovation in the Blanchard and Summers model is to assume that unemployed union members lose membership of the union (the insider group), and become outsiders. This means that their interests are no longer taken into account when the union bargains over wages in subsequent bargaining rounds.
This emphasis on 'membership rules' creates the possibility of persistence in unemployment. This is so since unanticipated shocks, which cause a change in actual employment, will then alter the size of the insider group in whose interest wages will be set in the future. Unanticipated contractions in employment tend to generate upward wage movements, since any future level of labour demand has to be divided between a smaller, and as such more secure, insider group. Of course this wage behaviour tends to make the original contraction in employment persistent.
The second approach is associated with the work of Lindbeck and Shower (1988, 2001). This approach is also capable, under the right assumptions, of generating the predictions of the Blanchard and Summers model. The major contribution of Lindbeck and Shower is to explain the source of insider power, rather than simply assuming it. They argue that insider power comes from a range of turnover costs. These costs mean that the firm's incumbent workforce cannot be costlessly exchanged for unemployed outsiders. These turnover costs create a rent to be bargained over, and therefore, the possibility of wage outcomes that make it unprofitable for employers to employ outsiders. These costs include hiring, training and firing costs. Firing costs include direct costs such as severance pay, but may also include more amorphous considerations, such as the negative morale impact of turnover on remaining employees. Models combining turnover costs and membership rules can explain unemployment persistence.
Lindbeck and Snower extend the basic insider-outsider model by exploring asymmetric membership rules in which insider status is acquired and lost at different rates. The short-term unemployed, for instance, may retain insider status. In contrast, the newly employed can be assumed to require several periods of continuous employment before they are considered insiders. Altering the rules that govern membership of the insider group in ways such as this can produce interesting modifications to the predictions of the basic model.
The final approach, associated with Layard, Nickell and Jackman (1991), identifies the long-term unemployed as outsiders. A number of ideas make up the 'outsider ineffectiveness hypothesis'. Long-term unemployment could result in skill atrophy, and or, demoralisation. Either or both of these will diminish the ability of the long-term unemployed to compete in the labour market. In addition, employers may use unemployment duration as a screening mechanism. Under this scenario employers interpret long-term unemployment as a signal that a potential employee has already been found wanting. These ideas lead to the conclusion that the long-term unemployed are marginalised in relation to wage outcomes.
Under these conditions past employment shocks could have a persistent impact on unemployment. This is so since the actual history of shocks to employment determines, in part, the current duration composition of unemployment, and hence the number of long-term unemployed in any given pool of unemployed. The larger the proportion of total unemployment that is long-term, all other things being equal, the more favourable are wage setting conditions for insiders. This may in turn generate wage outcomes that are inimical to future employment growth, thereby making the effect of past shocks persistent.
3. The Role of Wage Setting Institutions
The second purpose of this paper is to examine the impact of wage setting institutions on insider power and outsider ineffectiveness. Since the work of Bruno and Sachs (1985), Calmfors and Driffill (1988) and Layard, Nickell and Jackman (1991), much has been written about the impact of wage setting institutions on economic outcomes. A central theme in this literature is a belief that the level at which wage determination occurs is crucial to unemployment outcomes. Calmfors and Driffill's (1988) famous 'hump hypothesis' held that either centralized (national), or decentralized wage setting (firm or enterprise), would produce lower unemployment outcomes than would be obtained under more intermediate, industry level bargaining.
According to Calmfors and Driffill, decentralised bargaining resulted in favourable unemployment outcomes due to the absence of market power at the level of the firm or enterprise. On the other hand, centralised bargaining could also produce favourable unemployment outcomes. This was because wage setters would not be able to escape the adverse unemployment consequences of their wage setting behaviour. This would induce them to strive for wage outcomes consistent with low unemployment. On the other hand, when wages are set at an intermediate level, wage setters can generate and share in local rents. The costs associated with this activity are spread across the entire community, and hence have a negligible impact on those responsible for them.
Calmfors notes that a competitive labour market model underpins the hump hypothesis. He has stated that this model should be '... regarded only as a benchmark case that needs to be modified by bringing more considerations into the analysis' (Calmfors, 1993, p. 10). He discusses six other considerations including the fact that the benchmark model '... did not consider the insider-outsider issue' (Calmfors, 1993, p. 11, original underline). While Calmfors does not present a formal model in relation to this, he speculates that incorporating insider-outsider considerations into the benchmark model would strengthen the case for centralisation. This is because he believes that the unemployed are more likely to remain attached to the insider group if wages are set at a centralized, rather than a decentralised level. In other words, if insider power is present when wages are set in a decentralised manner, this weakens the argument in favour of decentralised wage setting as a way to produce good unemployment outcomes. Fritzenberger and Franz (1999) present a theoretical model that supports Calmfors's intuition.
Empirical support for Calmfors's intuition can also be found in some Australian research using aggregate data. Flatau, Lewis and Rushton (1990), Flatau, Kenyon, Lewis and Rushton (1991), Kenyon (1990) and Chapman and Gruen (1990) all produce evidence to suggest that Australia's adoption of a corporatist style Prices and Incomes Accord in the early 1980s had the effect of 'enfranchising' unemployed outsiders. These studies suggest that the Accord did this by limiting the ability of insiders to exploit wage setting power at the local level. Groenewold and Taylor (1992), on the other hand, while finding evidence in favour of the role of insiders in wage setting, found no evidence that the Accord moderated this power.
At the international level, the substantial body of empirical evidence on this issue is quite inconclusive. One reason is that this literature relies heavily on inter-country comparisons as a way to test ideas about the impact of wage setting institutions on economic outcomes. These inter-country comparisons involve ranking countries with the aid of some index of how corporatist or centralised their institutions are. Calmfors and Driffill (1988) discuss how these rankings are heavily dependent on exactly what institutional feature is trying to be captured, as well as on the idiosyncrasies of individual countries. They also provide an illustration of how the results of inter-country studies are quite sensitive to the particular ranking employed (see Calmfors and Driffill, 1988, Table 5, p. 29).
Freeman (1998) also discusses the problems inherent in inter-country studies. He notes that the general problem is that since the number of institutions that differ among countries can be large, it can be difficult to interpret which institutional differences are driving the relevant economic outcomes. In addition, identical institutions may operate differently in different countries, because of other differences in the institutional arrangements (Freeman, 1998, p. 5). In this paper I undertake an empirical examination of whether insider power is enhanced or restrained by enterprise level bargaining. Moreover, the recent Australian experience offers a way to do this that avoids the need to make inter-country comparisons.
The data used in the empirical analysis undertaken in this paper were collected in late 1995 and early 1996. Table 1 reveals the hybrid nature of the Australian wage setting system at this time. It indicates that by 1996 the Australian workforce had become evenly divided between three different approaches to the determination of wages. Approximately one third was covered, fully or in part, by decentralised enterprise bargains. A similar proportion remained entirely dependent on awards that were regulated primarily at the industry level. The remaining one third of the workforce was covered by some type of individual arrangement (ACIRRT, 1999, p. 77).
4. Data and Methodology
This study uses data from two sources. One is the 1995 Australian Workplace Industrial Relations Survey (AWIRS 1995). The other is unpublished Labour Force Survey data provided by the Australian Bureau of Statistics. The AWIRS 1995 data are described and summarised in Morehead et al. (1997). The primary task of AWIRS 1995 was '... to provide a comprehensive and statistically reliable database on workplace relations in Australia' (Morehead et al., 1997, p. 1). AWIRS 1995 is rich in information about the characteristics of the sampled workplaces and their employees.
Workplaces in the Defence industry and the Agriculture, Forestry and Fishing industries are not included in the survey. In addition, workplaces with fewer than five employees were excluded from the survey. AWIRS 1995 also contained a small workplace survey that collected information on workplace characteristics for workplaces with between 5-19 employees. No information was collected on employees at these small workplaces. Hence these workplaces have been ignored in the analysis conducted in this paper.
The original sample consisted of 19,155 employees and 2001 workplaces. All non-commercial and Public Sector workplaces and employees were eliminated from the sample. This was done in the belief that the insider-outsider model is meant to apply to workers and workplaces that are directly subject to market forces and the profit motive. This decision cost almost 40 per cent of the sample. In the case of some of the variables used in the study, 'missing' or 'no response' rates where as high as 50 per cent. Once all cases with missing observations are eliminated, the sample used in the analysis consists of 4001 employees spread across 444 workplaces.
This large loss of observations could raise questions as to the representativeness of the final sample. Appendix 1 presents the means and standard deviations of variables used in this study. With the exception of the unionisation rates, all variables reported in Appendix 1 have means and standard deviations that are reasonable, and consistent, when applicable, with those obtained from other cross section data sets. The high unionisation rates in the samples used in this study are most likely due to the exclusion of small workplaces which tend to have relatively low unionisation rates.
As discussed below, various unemployment measures are used to capture insider-outsider influences. These variables are constructed from unpublished Labour Force Survey data, provided by the Australian Bureau of Statistics. The data are used to construct a total unemployment rate, a short-term unemployment rate and a long-term unemployment proportion for each state and territory, cross-referenced on a metropolitan/non-metropolitan basis. (3) The unemployment variables are presented in Appendix 2.
The empirical analysis is conducted by estimating a cross-section log wage equation that includes insider-outsider proxy variables among the regressors. The equation estimated has the following form:
ln[W.sub.ij] = [beta] + [X.sub.ij][[beta].sub.1] + [Z.sub.j][[beta].sub.2] + [IO.sub.j][[beta].sub.3] + [[epsilon].sub.ij] (1)
i=1,... ...,[N.sub.j] j=1,... ...,J
[W.sub.ij] = the wage of worker i at workplace j.
Xij = a set of employee specific human capital and job characteristics. These include the following: potential experience, tenure at current workplace, whether the employee is from a non-English speaking home, whether the employee is disabled, their occupation, education, whether the employee is casual, and whether the employee is on a fixed term contract. These variables are fully defined in Appendix 1 under the heading 'Individual Variables'.
[X.sub.ij] = a set of variables describing the workplace at which each individual is employed. The variables include the following: workplace size, union density, occupational composition of the workplace, industry, the degree of product market competition faced by the workplace, whether the workplace operates primarily in export markets, whether the workplace faces competition from imported goods, percentage of the workplace workforce that is female, a measure of labour intensity, whether the workplace is foreign or Australian owned. All these variables are fully defined in Appendix 1 under the heading 'Workplace Variables'.
[IO.sub.j] = the insider-outsider proxy variables at each workplace. These variables are discussed in the next section, and are also fully described in Appendix 1 under the heading 'Insider-Outsider Variables'. [[epsilon].sub.ij] = a disturbance term. Nj is the number of observations for workplace j, and J is the number of workplaces.
The wage equation is estimated over the full sample of observations in order to ascertain whether the insider-outsider distinction is relevant for Australia. The sample is then purged of all workplaces that have neither (i) a registered or unregistered written enterprise agreement nor (ii) a verbal enterprise agreement in operation. The regression models are re-estimated by using the enterprise bargaining sub-sample. In this way, it is possible to gain some insight into how enterprise bargaining influences the positions of insiders and outsiders.
Two significant complications need to be acknowledged. First, awards, individual contracts and enterprise agreements do not necessarily represent substitutes for each other. Awards and enterprise agreements, in particular, are frequently used in conjunction with one another. The data permit the identification of those workplaces that have a written or verbal enterprise bargain in place. This does not mean that other mechanisms to set wages are not also used at these workplaces. When a workplace is denoted as an enterprise bargaining workplace, this needs to be kept in mind. It does not mean that all wages are set at that workplace by enterprise bargaining. Second, within the workplaces that engage in enterprise bargaining, there was a tendency towards pattern bargaining at the time the data were collected. This practice implies that wages were not necessarily determined in a fully decentralised manner at these workplaces.
These complications should bias the results of this study towards finding no difference in insider power, and outsider ineffectiveness, between the full sample of workplaces and the sub-sample of enterprise bargaining workplaces. In fact, my results suggest that once non-enterprise bargaining workplaces are purged from the data, insider power increases. Such a result would be unlikely if enterprise bargaining actually serves to reduce insider power. At the very least my findings suggest that we need to take seriously the possibility that decentralised wage setting does not restrict insider power, notwithstanding the complications just mentioned.
5. Description and Discussion of Key Variables
The dependent variable is the log hourly wage. The theory is tested by estimating three separate specifications that include different combinations of the insider-outsider proxy variables. Each of the three specifications includes an insider proxy variable that is drawn from the AWIRS 1995 data. This variable, called 'employment change' (EC), is a dummy variable equal to one if employment change at the workplace in the proceeding twelve months was positive and zero if employment change was zero or negative. This variable attempts to capture a basic implication of the Blanchard and Summers (1986, 1987) model. The implication is that wages move inversely with the size of the firm's insider group, with the latter being the firm's current employees. If this is the case, the coefficient on 'employment change' should be significant and negative. The first specification also includes a variable measuring the total unemployment rate (TU) in the region in which each worker is employed. If the unemployed are outsiders, then variation in the total unemployment rate will not have a statistically significant impact on log hourly wages. Thus the first specification can be written as:
lln[W.sub.ij] = [beta] + [X.sub.ij][[beta].sub.1] + [Z.sub.j][[beta].sub.2] + [EC.sub.j][[beta].sub.3] + [TU.sub.j][[beta].sub.4] + [[epsilon].sub.ij]
A second specification of the model aims to test the outsider ineffectiveness hypothesis. This is done by including, along with the total regional unemployment rate, a variable to capture the proportion of total regional unemployment that is long-term (LTUP). The expectation is that, in this specification, the coefficient on the variable for the total regional unemployment rate will be significant and negative. The coefficient on the long-term unemployment proportion is expected to be significant and positive. Such an outcome would be consistent with the idea that the long-term unemployed create more favourable wage setting conditions for insiders. In other words, insiders cannot ignore all of the unemployed, just those that are long-term unemployed. (4) Flatau, Lewis and Rushton (1990), Flatau, Kenyon, Lewis and Rushton (1991) and Kenyon (1990) use this approach to test the insider-outsider distinction in the 1980s with Australian aggregate data. Thus the second specification can be written as:
lln[W.sub.ij] = [beta] + [X.sub.ij][[beta].sub.1] + [Z.sub.j][[beta].sub.2] + [EC.sub.j][[beta].sub.3] + [TU.sub.j][[beta].sub.4] + [LTUP.sub.j][[beta].sub.5] + [[epsilon].sub.ij]
A third specification is employed in the analysis to test an alternative formulation of the outsider ineffectiveness hypothesis, and or, membership rules approach. In some versions of the insider-outsider model, insider status is not lost the instant a worker becomes unemployed. Rather it is assumed that an insider needs to be unemployed for a period of time before he or she becomes an outsider. Under this scenario it might be reasonable to assume that the short-term unemployed (STU) remain attached to the insider group, while only those with longer unemployment durations are ignored in wage setting. (5)
Alternatively, the short-term unemployed may not belong to the insider group as such. They may, however, be actual or perceived substitutes for employed insiders. This could be the case if the short-term unemployed retain labour market contacts and skills, which longer durations of unemployment tend to erode. On either account, an increase (decrease) in the short-term unemployment rate may induce employed insiders to decrease (increase) wage demands. Thus the third specification can be written as:
ln[W.sub.ij] = [beta] + [X.sub.ij][[beta].sub.1] + [Z.sub.j][[beta].sub.2] + [EC.sub.j][[beta].sub.3] + [STU.sub.j][[beta].sub.6] + [[epsilon].sub.ij]
Three potentially important limitations of the unemployment variables used in the three specifications should be noted. First, it is a premise of this study that insider-outsider influences can manifest themselves at the regional level. In other words, it is assumed that regional variation in turnover costs, and/or membership rules, and/or the factors underpinning outsider ineffectiveness can explain, at least in part, the variation observed in the regional unemployment data used in this study. This is a strong assumption in view of the nature of Australian industrial relations and labour market practices, which would tend to place a limit on the required variation.
Second, under the membership rules version of the insider-outsider model, it is implied that the short-term unemployed may be insiders because they have recently been part of the insider group, i.e., recently employed. This ignores the reality that some of the short-term unemployed will have come from outside the labour force. There is little that can be done about this except to acknowledge that it introduces the possibility of measurement error into the estimations.
On the other hand, the duration of the unemployment based insider-outsider model is not subject to this limitation. In this version the short-term unemployed are insiders, not because they have recently been employed, but because they have not been unemployed for long. How they managed to arrive at this state of short-term unemployment (i.e., from employment or from outside the unemployment pool) is not relevant.
Third, as already noted, the AWlRS 1995 data employed in this study only enable the location of workplaces to be identified by state and territory, cross-referenced on a metropolitan non-metropolitan basis. This means that the size and nature of these regional dimensions is potentially problematic since the impact of unemployment on wages will be constrained to be the same for workers in geographically distinct regions such as Cape York and South West Queensland. The result of this is the potential introduction of measurement error, which could bias upwards the standard errors. Apart from acknowledging the potential problem, there is little that can be done about it. It is a problem imposed by the nature of the data set. (6)
This study finds in favour of the insider-outsider theory and of the role of enterprise bargaining in disenfranchising the long-term unemployed. Given the three limitations discussed in the previous paragraphs, we should be prudent to regard the results of this paper as offering provisional support for these ideas.
As noted previously, each regression also contains a large number of control variables. These variables control for a range of individual employee and workplace characteristics. They are, by and large, standard inclusions in wage equations of the kind estimated in this study. Appendix 1 includes a description of these variables. For efficiency of exposition, they are not discussed in this paper.
6. Regional Dummies, Regional Unemployment Rates and Collinearity
The earnings regressions include three different unemployment measures. These are proxies for the insider-outsider influences that are central to this study. As just discussed, these unemployment rates are regional rates. In fact, there are 14 regions identifiable in AWIRS 1995, one for the metropolitan area of each state, one for the non-metropolitan area of each state, and one for each Territory. In addition to regional unemployment, other regional factors will influence wages. Regional influences on wages that are not directly related to unemployment, but which may be correlated with unemployment, need to be controlled for. Failure to do this may result in omitted variable bias. The estimated coefficients on the unemployment variables will register the impact on earnings of omitted but correlated regional influences, in addition to the impact of regional unemployment.
The rationale for including regional dummies to control for regional fixed effects in addition to unemployment is clear enough. Including 14 regional dummies, corresponding to the 14 regions for which unemployment rates have been defined, along with 14 regional unemployment rates would, however, result in perfect collinearity. On the other hand, omitting the regional dummies may result in omitted variables bias. These issues have been dealt with as follows in this study. Along with 14 regional unemployment rates, 8 regional dummy variables have been included, one for each state and territory. This eliminates perfect collinearity, enabling the coefficients to be estimated. It does not, of course, eliminate collinearity entirely.
To gauge the impact of collinearity and omitted variables bias on the results, the following strategy has been adopted. Each regression has been estimated with regional dummy variables. The regressions have been re-estimated without them. The regressions have also been estimated without regional dummy variables, but with a variable to capture median house prices in each region. This third specification omits full controls for regional influences, but controls for housing cost differences, a major contributor to regional differences. These experiments confirm that the specification which includes regional dummy variables is superior to the other specifications. For brevity, only those regressions with regional dummy variables are reported and discussed in this paper. Complete results from all regressions are available upon request.
7. Estimation and other Econometric Issues
In order to estimate equation (1) using ordinary least squares (OLS), it must be assumed that the random disturbances are independently distributed. As discussed in Wooden (2001) and Wooden and Bora (1999), this may be appropriate in a sample in which individuals are selected at random from the population of employees. But in the case of AWIRS 1995, the employee sample was not drawn at random from the population of employees. Rather, a random sample of workplaces was taken, and then the employee sample was drawn from these workplaces.
A group of individuals from the same workplace are likely to have characteristics that are more similar than a group of individuals sampled from the population at large. This could result from any of a number of factors. Workers from a given workplace, for instance, could share a particular 'workplace culture' which impacts on their productivity. Many of these common characteristics are unlikely to be measurable, and hence controlled for. As a result they will be registered in the error term with the result that there will be a correlation in the errors. Greene (1991) shows that, under the circumstances just described, the error structure is given as follows:
[[epsilon].sub.ij] = [[micro].sub.ij] + [[lambda].sub.j]
This error term has two components. The first component [[micro].sub.ij] varies independently across individuals both within and across workplaces. The second component [[lambda].sub.j] varies across workplaces but is constant for workers within the same workplace. This error structure describes the random effects model and the efficient estimator is feasible Generalised Least Squares (Wooden, 2001; Wooden and Bora, 1999; and Greene, 1991).
Given that much of the data in AWIRS 1995 are grouped, we might expect that heteroscedasticity could be a problem in the regressions. An examination of residual plots, and the Breusch-Pagan-Godfrey test (neither reported in this paper), indicate that this is indeed the case. The presence of heteroscedasticity means that the standard errors from the random effects regressions are not efficient. An estimator using a procedure such as White's (1980) is not available for the random effects model. In an attempt to compensate for this, OLS regressions with the t-ratios corrected using White's (1980) procedure are also estimated and reported. If the results from the OLS and random effects regressions are qualitatively similar, the conclusion is drawn that the econometric difficulties just discussed are not of practical importance. The results suggest that this is the case. The OLS and random effects estimates, reported in Tables 1 and 2 below, are quantitatively and qualitatively very similar.
Measurement error also results from the fact that the employee earnings variable reported in AWIRS 1995 is grouped into 23 categories. The usual practice of allocating midpoints to each earnings category has been followed in this research. The top and bottom pay categories are open-ended. They have been closed somewhat arbitrarily. Sensitivity tests show that the findings are not sensitive to the end points chosen.
8. Discussion of Results
The research undertaken in this paper has generated a large volume of regression output. Most of this output is not directly relevant to the task of testing the insider-outsider theory. Accordingly, the coefficient estimates and t-ratios for the insider-outsider variables have been extracted from the regression output and reported in Table 2. The focus of this section is on discussing the estimates on these insider-outsider variables. As already noted in section 5, for the sake of brevity the estimates relating to all the other individual and workplace variables are not discussed in this paper. I note that the results for the non insider-outsider variables are reasonable, and consistent with expectations. This can also be seen from Appendix 3, which provides complete results for the specification that includes the long-term unemployment proportion. It is also apparent from Table 2 that the OLS and random effects estimates are qualitatively similar. For the sake of brevity in what follows, only the OLS results are discussed. (7)
The examination turns first to the results from the full sample reported in Panel A. Column 1A shows that variation in the total unemployment rate in the region in which a worker works does not have a statistically significant impact on wages. This could be viewed as evidence that the unemployed are outsiders. The results reported in column 2A are from the specification that includes the long-term unemployment proportion, in addition to the total unemployment rate. The estimated coefficient on the long-term unemployment proportion is positive and significant at the one per cent significance level. It can also be seen that once the long-term unemployment proportion is included, the total unemployment rate becomes significant, also at the one per cent significance level. These results support the version of the insider-outsider theory in which the long-term unemployed are outsiders. The insignificance of the total unemployment rate in column 1A was probably the result of omission of a relevant variable, namely the long-term unemployment proportion.
Column 3A provides additional evidence in favour of the idea that the long-term unemployed are outsiders. The specification reported in this column includes the short-term unemployment rate as an insider variable. The negative and significant coefficient estimate on this variable implies that the short-term unemployed are attached to the insider group, or are considered to be viable substitutes for incumbent insiders. The insider variable 'employment change' fails to achieve significance in any of the regressions reported in Panel A. Taken together, the three specifications reported in Panel A provide a compelling case for the idea that the long-term unemployed are outsiders in local labour markets.
The next step in the analysis involves purging the sample of all workplaces that do not have either a written or verbal enterprise agreement in place. The results reported in Panel B are for the sub-sample of workplaces at which there is a written or verbal enterprise bargain in operation.
The same qualitative comments apply to the results reported in Panel B as were made in relation to the results from Panel A. The total unemployment rate is not statistically significant when entered by itself. This can be seen in column 1A from Panel B. Column 2A shows that once the long-term unemployment proportion has been entered, the total unemployment rate becomes significant at one per cent. In addition the coefficient on the long-term unemployment proportion is significant at one per cent and has a positive sign. This is interpreted as meaning that the long-term unemployed are outsiders. The results from Panel B also support the idea that the short-term unemployed either remain attached to the insider group, or are viable substitutes for insiders; probably because they have only been unemployed for a short time. The insider variable 'employment change' is never significant.
The R-squared statistics reported in both panels are generally around 0.45. These are very high for analysis that uses cross-section data. The reported F values indicate that each regression is significant overall at the one per cent significance level. In the full sample, the size of the coefficient on the long-term unemployment proportion suggests that for each one per cent increase in the proportion of total unemployment that is long-term, insiders can raise their wages by 0.33 per cent. Given that during periods of high unemployment the long-term proportion has reached as high as 30 per cent, we may regard this as an economically significant result, and suggesting that this is an important mechanism for unemployment persistence. The size of the elasticity of insider wages with respect to the long-term unemployment proportion rises to 0.43 when the enterprise bargaining sub-sample is considered. These results suggest that enterprise bargaining is not an antidote to insider power. On the contrary, these results suggest that enterprise bargaining allows a given increase in the 'density of outsiderness' to be transformed into a bigger increase in wages for insiders than was the case in the full sample.
It is well known that the long-term unemployment proportion rises, with a lag, along with the actual unemployment rate (Chapman, 1993). The finding that there exists an insider effect, that seems to be related to unemployment duration, implies that insider power is a latent force at work in the Australian labour market. The research reported in this paper suggests that in the aftermath of a rise in unemployment the subsequent rise in long-term unemployment may create conditions favourable to the exercise of insider power. This will then make the return to lower levels of unemployment a more protracted process than would be the case in the absence of that insider power. It is beyond the scope of this paper to attempt to determine whether unemployment might have fallen more rapidly, from the highs of the early 1990s to its current low level, had a more centralized wages system been maintained throughout this period. At the very least, the research reported here suggests that such an idea is worth consideration and further exploration.
Previous Australian research, using aggregate data, indicates that the insider-outsider distinction is a relevant one for the Australian labour market. In addition, this aggregate data research has produced convincing evidence that centralised wage fixing under the Accord had the effect of 'enfranchising' unemployed outsiders. The Accord did this; it has been suggested, by limiting the ability of insiders to exploit wage setting power at the local level. This paper has attempted to establish the presence of insider-outsider influences in the Australian labour market using micro-data. In addition, the paper examined whether enterprise bargaining had any impact on the relative labour market positions of insiders and outsiders.
We find that the insider-outsider distinction was relevant in the full sample and in the sample of workplaces that engaged in enterprise bargaining. In addition, the paper found evidence that insiders are strongest, and outsiders weakest, where workplaces engage in enterprise bargaining. A reasonable conclusion is that enterprise bargaining does not reduce insider power. Several limitations of the study were discussed in the paper. It is perhaps prudent to consider the results presented here as offering provisional support for the insider-outsider theory and for the role of enterprise bargaining in shifting power towards insiders at the expense of outsiders in regional labour markets.
Appendix 1 Variable definitions; Means and Standard Deviations (Note: The first number in each cell is the mean, the number beneath is the standard deviation) Full Enterprise Variable Definition Sample Bargains Log hourly pay Log of gross pay per week 2.72 2.77 divided by hours worked 0.40 0.41 each week. Workplace Variables Active union Dummy variable: Equals 1 if the senior delegate from the union with most 0.48 0.62 members spends one hour 0.50 0.49 or more each week on union activities, and either a general meeting of members is held at least once every six months, a union committee exists and meets regularly with management, or delegates meet with management at least once a month. Unionisation Rate Proportion of employees 0.62 0.63 at workplace who are 0.29 0.27 union members. 20-49 (omitted Dummy variable: equals 1 0.13 0.10 category) if 20-49 employees at 0.34 0.29 workplace. 50-99 Dummy variable: equals 1 0.21 0.19 if 50-99 employees at 0.41 0.39 workplace. 100-199 Dummy variable: equals 1 0.27 0.25 if 100-199 employees at 0.44 0.43 workplace. 200-499 Dummy variable: equals 1 0.24 0.27 if 200-499 employees at 0.43 0.45 workplace. 500-1000 Dummy variable: equals 1 0.11 0.14 if 500-1000 employees at 0.32 0.35 workplace. 1000+ Dummy variable: equals 1 0.04 0.05 if 1000 or more employees 0.19 0.22 at workplace. Labour intensity Labour costs as a 2.39 2.32 proportion of total 1.11 1.09 costs. The variable is measured as a scale going from 1 to 6 representing less to more labour intensive. Foreign Dummy variable: Equals 1 0.23 0.30 if workplace is majority 0.42 0.46 foreign owned. Import competing Dummy variable: Equals 1 0.40 0.46 if workplace faces import 0.49 0.50 competition for it's major product or service. Export Dummy variable: Equals 1 0.12 0.14 if more than 50% of main 0.32 0.34 product or service is exported. % Managers Managers as a percentage 5.59 5.38 of total employment at 4.72 4.80 workplace. % Professionals Professionals as a 4.40 5.04 percentage of total 7.90 8.31 employment at workplace. % Tradespeople Tradespeople as a 14.47 15.28 percentage of total 19.43 18.97 employment at workplace. % Clerical Clerical as a percentage 11.87 12.28 of total employment at 16.04 15.52 workplace. % Salespeople Salespeople as a 18.85 12.22 percentage of total 31.24 24.82 employment at workplace. % Plant and mach Plant and machine 18.58 21.22 operators operators as a percentage 24.79 25.02 of total employment at workplace. % Labourers Labourers as a percentage 18.45 20.52 of total employment at 23.54 24.72 workplace. % Para-prof (omit- Para-professionals as a 7.76 8.03 ted category) percentage of total 14.71 14.27 employment at workplace. Competition in Dummy variable: equals 1 0.58 0.55 product market if firm has many competi- 0.49 0.49 tors in product market, equals zero if firm has few or no competitors. % Female Percentage of workplace 34.95 29.57 workforce which is 27.47 24.75 female. Individual Variables Male Dummy variable: Equals 1 0.62 0.68 if employee is male. 0.48 0.47 Experience Age--(years at school + 19.26 20.03 5), 11.96 11.62 Tenure Years employed at 6.77 7.27 workplace. 7.08 7.31 Non-English Dummy variable: Equals 1 0.06 0.07 Speaking home if employee comes from a 0.25 0.25 non-English speaking home. Disabled Dummy variable: Equals 1 0.08 0.08 if a health condition or 0.23 0.27 - disability exists which is likely to last beyond six months. Plant and machine Dummy variable: Equals 1 0.16 0.18 operators if employed in 0.36 0.38 occupational group, Plant and Machine Operators and Drivers. Sales Dummy variable: Equals 1 0.17 0.12 if employed in 0.38 0.32 occupational group, Sales and Personal Services. Clerks Dummy variable: Equals 1 0.14 0.14 if employed in 0.34 0.34 occupational group, Clerks. Tradesperson Dummy variable: Equals 1 0.14 0.15 if employed in 0.35 0.36 occupational group, Tradesperson and Apprentices. Para-prof Dummy variable: Equals 1 0.08 0.09 if employed in 0.27 0.28 occupational group, Para-professionals. Professional Dummy variable: Equals 1 0.07 0.08 if employed in 0.26 0.28 occupational group, Professionals. Manager Dummy variable: Equals 1 0.07 0.07 if employed in 0.25 0.26 occupational group, Managers. Other occupation Dummy variable: Equals 1 0.01 0.01 if not able to be 0.08 0.07 classified in the other occupational categories Labourers (omitted Dummy variable: Equals 1 0.17 0.17 category) if employed in occu- 0.37 0.37 pational group, Labourers and Related Workers. Primary education Dummy variable: Equals 1 0.03 0.03 if attended primary 0.17 0.18 school but not secondary school. Some secondary Dummy variable: Equals 1 0.34 0.33 if attended, but did 0.48 0.47 not complete secondary school. Skilled vocational Dummy variable: Equals 1 0.16 0.18 if highest educational 0.37 0.39 level is skilled vocational qualification. Associate diploma Dummy variable: Equals 1 0.86 0.09 if highest educational 0.28 0.29 attainment is Associate diploma /advanced certificate. Degree Dummy variable: Equals 1 0.09 0.09 if highest educational 0.29 0.29 attainment is undergraduate degree or a diploma. Postgraduate Dummy variable: Equals 1 0.04 0.04 if highest educational 0.19 0.20 attainment is a Postgra- duate degree or diploma. Basic vocational Dummy variable: Equals 1 0.04 0.04 if highest educational 0.19 0.19 level is basic vocational qualification. Completed secondary Dummy variable: Equals 1 0.21 0.19 school (omitted if completed not higher 0.41 0.39 category) than secondary school. Fixed term contract Dummy variable: Equals 1 0.07 0.07 if employment contract 0.25 0.25 ends on a fixed date. Casual Dummy variable: Equals 1 0.13 0.09 if not entitled to both 0.34 0.29 paid holiday or sick leave. School * Years of formal schooling 230.10 239.60 Experience times potential experi- 139.90 136.10 ence Insider-Outsider Variables Short-term Log short-term unemploy- 1.39 1.39 unemployed ment rate. Regional 0.15 0.15 unemployed for less than or equal to 13 weeks, as a percentage of regional labour force. Total unemployed Log regional unemploy- 2.29 2.29 ment rate. Regional 0.10 0.10 unemployed as a percen- tage of regional labour force. Long-term Proportion of regional unemployed unemployment that is 3.49 3.49 long-term. Log of regio- 0.22 0.22 nal long-term unem- ployment, expressed as a percentage of total unemployment in the region. Employment change Dummy variable: Equals 1 0.54 0.53 if employment change at 0.49 0.50 workplace was positive in proceeding 12 months. Location Dummies NSW Dummy variable: Equals 1 0.33 0.31 if workplace is in 0.47 0.46 New South Wales. ACT Dummy variable: Equals 1 0.01 0.05 if workplace is in the 0.08 0.07 Australian Capital Territory. TAS Dummy variable: Equals 1 0.03 0.32 if workplace is in 0.17 0.18 Tasmania. NT Dummy variable: Equals 1 0.000 if workplace is in the 0.03 NA Northern Territory. QLD Dummy variable: Equals 1 0.18 0.20 if workplace is in 0.39 0.40 Queensland. SA Dummy variable: Equals 1 0.09 0.91 if workplace is in 0.28 0.29 South Australia. WA Dummy variable: Equals 1 0.08 0.70 if workplace is in 0.27 0.26 Western Australia. VIC (omitted Dummy variable: Equals 1 0.29 0.29 category) if workplace is in 0.45 0.45 Victoria. Appendix 2 Regional Unemployment Rates Used in this Study Long-term Region Total Short-term Unemployment Unemployment Unemployment Proportion Rate (Per Cent) Rate (Per Cent) (Per Cent) NSW Met 9.07 3.88 34.63 NSW Non Met 10.76 4.23 40.05 Victoria Met 10.49 3.68 38.61 Victoria Non Met 9.87 4.00 34.89 Queensland Met 8.58 4.75 21.60 Queensland Non Met 10.73 4.86 26.41 South Australia Met 11.29 3.93 35.38 South Australia 8.07 2.00 43.24 Non Met Western Australia 9.34 4.74 22.60 Met Western Australia 7.59 2.66 20.46 Non Met Tasmania Met 13.25 5.45 41.45 Tasmania Non Met 11.09 2.78 44.09 Northern Territory 8.89 4.72 21.78 Australian Capital 8.83 4.59 17.33 Territory NOTES: Short-term unemployment is 13 weeks or less. Long-term unemployment is 52 weeks or more. The data were provided by the Australian Bureau of Statistics and are based on unpublished Labour Force Survey (6203.0) data. Appendix 3 Complete results for the specifications reported in columns 2A and 2B of Table 2 OLS and Random Effects Estimates. Dependent Variable is Log Hourly Wage. Workplace level OLS RE variables Full Sample Full Sample Unionisation rate 0.093 ** 0.093 ** * active (3.998) (2.956) Unionisation 0.036 (#) 0.035 rate * (1-active) (1.643) (1.169) Foreign owned 0.045 ** 0.037 * (3.772) (1.979) Product market -0.001 -0.005 competition (-0.123) (-0.319) Shiftworking 0.018 ** 0.017 ** (5.246) (3.397) Female -0.001 ** -0.001 * (-2.835) (-2.186) Workplace size (20-49 omitted) 50-99 0.040 * 0.044 (#) (2.040) (1.888) 100-199 0.055 ** 0.063 * (2.678) (2.574) 200-499 0.079 ** 0.088 ** (3.747) (3.377) 500-1000 0.101 ** 0.097 ** (4.331) (3.284) 1000+ 0.122 ** 0.077 ** (3.334) (2.796) Labour intensity -0.003 -0.0006 (-0.722) (-0.095) Import competing -0.027 * -0.031 (#) (-2.362) (-1.825) Exporter 0.063 ** 0.076 ** (3.443) (2.869) Occupational Composition of Workplace. (Para-prof omitted) % managers 0.001 0.001 (1.462) (0.907) professionals 0.003 * 0.002 (#) (2.230) (-1.922) tradespeople -0.0007 -0.0009 (-1.132) (-1.202) clerical 0.0004 0.0001 (0.703) (0.155) % salespeople -0.0003 -0.0007 (-0.555) (-0.840) % plant and machine -0.0007 -0.0009 operators (-1.373) (-1.335) % labourers -0.002 ** -0.002 ** (-3.741) (-3.381) Individual level variables Male -0.0001 -0.0003 (-0.007) (-0.012) Experience 0.027 ** 0.026 ** (6.757) (6.620) Experience squared -0.0003 ** -0.0003 ** (-5.508) (-5.683) Male * experience 0.008 ** 0.007 ** (2.788) (2.725) Male * experience -0.0001 (#) -0.0001 (#) squared (-1.820) (-1.692) Non-English -0.068 ** -0,068 ** Speakinghome (-3.555) (-3.303) Tenure 0.010 ** 0.010 ** (4.537) (5.771) Tenure squared -0.0002 * -0.0002 ** (-2.363) (-3.606) Casual 0.040 * 0.048 ** (2.220) (2.973) Fixed term -0.092 ** -0.082 ** contract (-4.389) (-4.152) Disabled -0.040 ** -0.034 (#) (-2.625) (-1.924) Occupation (labourers omitted) Plant and machine 0.116 ** 0.101 ** operators (6.024) (5.480) Sales 0.047 * 0.041 * (2.441) (2.084) Clerk 0.095 ** 0.086 ** (5.168) (4.427) Tradesperson 0.125 ** 0.115 ** (5.979) (5.536) Para-prof 0.217 ** 0.199 ** (8.867) (8.459) Professional 0.288 ** 0.272 ** (8.398) (10.080) Manager 0.358 ** 0.341 ** (15.29) (14.30) Other occupation 0.190 * 0.159 ** (2.159) (2.675) Education (completed secondary school omitted) Primary education -0.212 ** -0.185 ** (-3.774) (-3.577) Some secondary -0.067 ** -0.065 ** (-4.053) (-3.984) Skilled vocational 0.008 0.005 (0.414) (0.259) Associate diploma 0.106 ** 0.109 ** (4.961) (5.183) Degree 0.156 ** 0.153 ** (6.347) (6.749) Postgraduate 0.222 ** 0.221 ** (6.004) (6.555) Basic vocational -0.074 * -0.072 * (-2.196) (-2.564) Schooling * -0.0008 ** -0.0007 ** experience (-3.870) (-3.660) Insider Outsider Variables Total unemployment -0.220 ** -0.217 (#) rate (-3.196) (-1.929) Long-term 0.334 ** 0.325 * unemployed (3.805) (2.363) proportion Employment change 0.0004 -0.004 (0.004) (-0.279) Location (VIC omitted) NSW 0.006 0.0009 (0.486) (0.050) ACT 0.178 * 0.154 (2.083) (1.250) TAS -0.040 -0.056 (-1.389) (-1.210) NT 0:306 * 0.294 (2.007) (1.531) QLD 0.136 ** 0.125 * (3.337) (2.040) SA -0.026 -0.026 (-1.418) (-0.930) WA 0.132 ** 0.118 (#) (2.722) (1.653) Industry dummies (Manufacturing omitted) Mining 0.232 ** 0.208 ** (7.432) (5.577) Electricity and 0.015 0.001 Gas (0.588) (0.038) Construction 0.105 ** 0.106 * (3.029) (2.167) Retail -0.103 ** -0.109 * (-3.418) (-2.414) Accommodation -0.101 ** -0.102 * (-3.489) (-2.397) Transport -0.040 -0.041 (-1.562) (-1.179) Communications 0.090 ** 0.086 * (3.192) (2.151) Finance 0.073 (#) 0.065 (1.960) (1.179) Property 0.004 0.002 (0.079) (0.041) Wholesale 0.018 0.037 (0.604) (0.888) Education -0.185 * -0.178 (#) (-2.357) (-1.647) Government -0.187 -0.246 * (-1.412) (-2.312) Personal Services 0.027 0.028 (0.719) (0.444) Health 0.017 0.004 (0.322) (0.072) Recreation -0.025 -0.025 (-0.645) (-0.522) CONSTANT 1.563 ** 1.633 ** (5.619) (4.67) Workplace level OLS RE variables EB Sample EB Sample Unionisation rate 0.081 * 0.082 (#) * active (2.440) (1.869) Unionisation 0.001 0.004 rate * (1-active) (0.056) (1.101) Foreign owned 0.050 ** 0.041 (#) (3.498) (1.903) Product market 0.006 0.003 competition (0.455) (1.170) Shiftworking 0.019 ** 0.018 ** (4.280) (2.703) Female -0.001 * -0.001(#) (-2.220) (-1.880) Workplace size (20-49 omitted) 50-99 0.048 (#) 0.048 (1.658) (1.481) 100-199 0.078 ** 0.083 * (2.669) (2.452) 200-499 0.099 ** 0.105 ** (3.335) (2.995) 500-1000 0.125 ** 0.119 ** (3.987) (3.138) 1000+ 0.135 ** 0.084 * (2.884) (2.502) Labour intensity -0.006 -0.0001 (-0.095) (-1.981) Import competing -0.039 ** -0.042 * (-2.660) (-1.975) Exporter 0.046 * 0.059 (#) (2.195) (1.879) Occupational Composition of Workplace. (Para-prof omitted) % managers 0.0004 0.0004 (0.327) (0.201) professionals 0.003 * 0.002 (#) (1.963) (1.792) tradespeople -0.001 -0.001 (-1.548) (-1.326) clerical -0.0004 -0.0006 (-0.574) (-0.536) % salespeople -0.0009 -0.001 (-1.137) (-0.932) % plant and machine -0.0009 -0.0009 operators (-1.511) (-1.106) % labourers -0.002 ** -0.002 ** (-4.161) (-3.174) Individual level variables Male 0.043 0.041 (1.185) (1.153) Experience 0.033 ** 0.031** (6.685) (6.270) Experience squared -0.0004 ** -0.0004 ** (-6.161) (-5.754) Male * experience 0.001 0.001 (0.532) (0.424) Male * experience 0.0000 0.0000 squared (0.340) (0.426) Non-English -0.078 ** -0.077 ** Speakinghome (-3.303) (-3.357) Tenure 0.012 ** 0.012** (3.994) (5.117) Tenure squared -0.0002* -0.0002 ** (-2.259) (-3.396) Casual -0.017 -0.006 (-0.678) (-0.283) Fixed term -0.091 ** -0.079 ** contract (-3.646) (-3.316) Disabled -0.057 ** -0.048 * (-3.121) (-2.235) Occupation (labourers omitted) Plant and machine 0.119 ** 0.107 ** operators (5.161) (4.958) Sales 0.063 * 0.062 * (2.438) (2.289) Clerk 0.101 ** 0.095 ** (4.309) (3.928) Tradesperson 0.127 ** 0.120 ** (4.804) (4.711) Para-prof 0.207 ** 0.192 ** (7.108) (6.727) Professional 0.249 ** 0.238 ** (6.335) (7.284) Manager 0.352 ** 0.345 ** (12.48) (11.67) Other occupation 0.433 ** 0.412 ** (3.058) (4.750) Education (completed secondary school omitted) Primary education -0.221 ** -0.187 ** (-3.058) (-3.023) Some secondary -0.049 * -0.042 * (-2.457) (-2.051) Skilled vocational 0.026 0.028 (1.033) (1.155) Associate diploma 0.145 ** 0.148 ** (5.311) (5.652) Degree 0.224 ** 0.214 ** (7.168) (7.129) Postgraduate 0.283 ** 0.274 ** (6.163) (6.604) Basic vocational -0.063 -0.062 (#) (-1.469) (-1.794) Schooling * -0.0009 ** -0.0008 ** experience (-3.489) (-3.252) Insider Outsider Variables Total unemployment -0.321 ** -0.324 * rate (-3.596) (-2.221) Long-term 0.427 ** 0.451 * unemployed (3.776) (2.541) proportion Employment change 0.001 -0.004 (0.106) (-0.252) Location (VIC omitted) NSW 0.007 0.006 (0.425) (0.247) ACT 0.334 ** 0.339 * (2.661) (1.958) TAS -0.056 (#) -0.089 (-1.709) (-1.514) NT N/A N/A QLD 0.189 ** 0.195 * (3.624) (2.424) SA -0.020 -0.022 (-0.854) (-0.614) WA 0.180 ** 0.182 (#) (2.806) (1.926) Industry dummies (Manufacturing omitted) Mining 0.229 ** 0.199 ** (5.892) (4.489) Electricity and 0.047 0.029 Gas (1.568) (0.622) Construction 0.148 ** 0.138 * (3.050) (1.984) Retail -0.071 (#) -0.083 (-1.670) (-2.443) Accommodation -0.165 ** -0.167 * (-3.880) (-2.443) Transport -0.008 -0.013 (-0.268) (-0.308) Communications 0.102 ** 0.092 (#) (3.153) (1.889) Finance 0.043 0.041 (0.911) (0.548) Property 0.027 0.025 (0.334) (0.310) Wholesale 0.040 0.050 (1.185) (1.110) Education -0.275 ** -0.261 (#) (-2.696) (-1.702) Government -0.183 -0.244 * (-1.359) (-2.184) Personal Services 0.058 0.047 (1.386) (0.700) Health -0.073 -0.078 (-0.938) (-0.947) Recreation -0.048 -0.046 (-0.835) (-0.639) CONSTANT 1.450 ** 1.398 ** (4.023) (2.764) Notes, **, *, (#), indicates significance at 1%, 5% and 10% respectively. The t-ratios (in brackets) in the OLS regressions have been corrected for heteroskedastic error structures using White's (1978) procedure.
* I am grateful to Bill Junor, Roger Tonkin and Bruce Chapman for comments on the research that went into this paper. I also express my gratitude to participants at a seminar at the Australian Centre for Industrial Relation Research and Training, University of Sydney, for helpful comments; and to two anonymous referees of this journal for their very insightful comments. Any errors are mine. Address for correspondence: Dr Michael Dobbie, Economics Department, Macquarie University, New South Wales, Australia, 2109. Email: firstname.lastname@example.org
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(1.) Indeed, Gregory (1987) is considered to be one of the first tests of this theory.
(2.) Sanfey (1995) provides a detailed survey of the theory. The outline given in this paper is both brief and informal.
(3.) There is no metropolitan/non-metropolitan split for the Australian Capital Territory and the Northern Territory.
(4.) The long-term unemployed have experienced 52 weeks or more of continuous unemployment.
(5.) The short-term unemployed have been unemployed for 13 weeks or less. Testing this alternative specification is also justified by the fact that in economics we often use poorly measured and crude proxies. It is prudent to test alternative versions of the same model when possible.
(6.) I am grateful to Bruce Chapman for pointing out the second and third of these limitations in relation to the unemployment variables used in this study.
(7.) It is acknowledged that this discussion of the random effects model, the problem of heteroscedasticity and the decision to estimate OLS regressions using White's (1980) procedure follows Wooden (2001) and Wooden and Bora (1999).
Michael Dobbie, Macquarie University.
Table 1: Mechanisms for Regulating Wages in 1996 Form of regulation % of employees Awards only 35-40 Awards and Registered Enterprise Agreements 30-40 Enterprise Agreements only 5-10 Individual arrangements 30-35 Source: ACIRRT, 1999, p. 77. Table 2: OLS and Random Effects Estimates. Dependent Variable is Log Hourly Wage. OLS 1A RE 1B OLS 2A PANEL A Insider-Outsider Variables Full Sample, N=4001 Total unemployment -0.045 -0.045 -0.220 ** rate (-0.731) (-0.528) (-3.196) Long-term unemployed 0.334 ** proportion (3.805) Short-term unemployed rate Employment change 0.0009 -0.003 0.0004 (0.089) (-0.261) (0.040) R-squared 0.437 Adjusted R-squared 0.427 Model F 58.64 ** PANEL B Enterprise Bargains, N=2746 Total unemployment -0.099 -0.084 -0.321 ** rate (-1.260) (-0.748) 0.427 ** Long-term unemployed 0.427 ** proportion (3.776) Short-term unemployed rate Employment change 0.004 -0.001 0.001 (0.317) (-0.072) (0.106) R-squared 0.435 Adjusted R-squared 0.420 Model F 43.72 ** RE 2B OLS 3A PANEL A Insider-Outsider Variables Full Sample, N=4001 Total unemployment -0.217 (#) rate (-1.929) Long-term unemployed 0.325* proportion (2.363) Short-term unemployed -0.108 ** rate (-2.742) Employment change -0.004 0.002 (-0.279) (0.265) R-squared 0.439 0.438 Adjusted R-squared 0.428 0.428 Model F 58.31 ** 58.38 ** PANEL B Enterprise Bargains, N=2746 Total unemployment -0.324 * rate (-2.221) Long-term unemployed 0.451* proportion (2.541) Short-term unemployed -0.164 ** rate (-3.093) Employment change -0.004 0.007 (-0.252) (0.513) R-squared 0.437 0.436 Adjusted R-squared 0.422 0.421 Model F 43.79 ** 43.88 ** RE 3B PANEL A Insider-Outsider Variables Full Sample, N=4001 Total unemployment rate Long-term unemployed proportion Short-term unemployed -0.109 (#) rate (-1.842) Employment change -0.002 (-0.164) R-squared Adjusted R-squared Model F PANEL B Enterprise Bargains, N=2746 Total unemployment rate Long-term unemployed proportion Short-term unemployed -0.180* rate (-2.246) Employment change 0.0009 (0.0457) R-squared Adjusted R-squared Model F Notes: **, *, (#), indicates significance at 1%, 5% and 10% respectively. The t-ratios in brackets in the OLS regressions have been corrected for heteroscedastic error structures using White's (1980) procedure. Each regression reported in this table contains approximately 50 other control variables, the coefficient estimates for which have not been reported here.
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|Title Annotation:||CONTRIBUTED ARTICLE|
|Publication:||Australian Bulletin of Labour|
|Date:||Dec 1, 2006|
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