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The Determinants of Trade Union Density in Cross-Country Comparisons: Theortical Opulance and Empirical Destitution Bernd Brandl University of Vienna Department of Industrial Sociology 1 st TURI network Conference: The future of trade union structures and strategies

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October 20081st TURI network Conference2 Researcher offer a number of determinants which possibly explain differences in the level of trade union density across countries and shifts over time From a macro-perspective (socio-)economic, political and institutional factors are used to explain differences in trade union density across countries and over time Empirical studies (usually) use aggregate pooled time series to investigate the empirical relevance of determinants on basis of different models Results of empirical studies are mixed regarding the relevance of specific determinants Introductory remarks and motivation

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October 20081st TURI network Conference3 The heterogeneity in empirical results is unsatisfactory for researchers and policy makers as there is uncertainty about what determinants are really important The aim of this paper is to investigate systematically the empirical relevance of determinants in explaining variations of trade union density across countries and over time using a Bayesian Model Averaging approach The work allows the identification of variables that are robust in explaining trade union density, i.e. provide explanatory power independent of what (specific) theory or model is used! Introductory remarks and motivation

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October 20081st TURI network Conference4 Contents I.Determinants of trade union density II.The empirical relevance of determinants and model uncertainty III.Bayesian Model Averaging and robust determinants IV.Summary and conclusions

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I.Determinants of trade union density

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October 20081st TURI network Conference6 I. Determinants of trade union density Trade union density: A country comparison Averages from 1970 to 2000. Source: OECD

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October 20081st TURI network Conference7 I. Determinants of trade union density Trade union density: A country comparison Shifts over time from 1970 to 2000. Source: OECD

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October 20081st TURI network Conference8 Literature is rich in offering theories and models that explain trade union density (across countries and in time) Literature is also reach in specifying determinants (factors, variables) that explain differences in trade union membership across countries and changes over time: Institutional determinants (number of union trade unions, organization of trade unions...) Economic determinants (unemployment rate, business cycle …) Socio-economic determinants (demographic characteristics, structure of the economy, education of population, religion …) Political determinants (Corporatism, political orientation of government …) I. Determinants of trade union density

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October 20081st TURI network Conference9 Analyzed variables in cross-country studies I. Determinants of trade union density

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October 20081st TURI network Conference10 Analyzed variables in cross-country studies I. Determinants of trade union density

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October 20081st TURI network Conference11 Analyzed variables in cross-country studies I. Determinants of trade union density

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October 20081st TURI network Conference12 Analyzed variables in cross-country studies I. Determinants of trade union density

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October 20081st TURI network Conference13 Analyzed variables in cross-country studies I. Determinants of trade union density

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October 20081st TURI network Conference14 Analyzed variables in cross-country studies I. Determinants of trade union density

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October 20081st TURI network Conference15 Analyzed variables in cross-country studies I. Determinants of trade union density

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October 20081st TURI network Conference16 Analyzed variables in cross-country studies I. Determinants of trade union density

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October 20081st TURI network Conference17 Analyzed variables in cross-country studies I. Determinants of trade union density

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October 20081st TURI network Conference18 Analyzed variables in cross-country studies I. Determinants of trade union density

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October 20081st TURI network Conference19 Analyzed variables in cross-country studies I. Determinants of trade union density

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October 20081st TURI network Conference20 Analyzed variables in cross-country studies I. Determinants of trade union density

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October 20081st TURI network Conference21 Analyzed variables in cross-country studies I. Determinants of trade union density

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October 20081st TURI network Conference22 Analyzed variables in cross-country studies I. Determinants of trade union density

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October 20081st TURI network Conference23 Analyzed variables in cross-country studies I. Determinants of trade union density

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October 20081st TURI network Conference24 Analyzed variables in cross-country studies I. Determinants of trade union density

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October 20081st TURI network Conference25 Analyzed variables in cross-country studies I. Determinants of trade union density

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October 20081st TURI network Conference26 I. Determinants of trade union density Analyzed variables in cross-country studies 76 Variables + 67 Interaction terms (variables) = 143 Regressors There are much more other variables which are reasonable! Further lags Further interactions

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II.The empirical relevance of determinants and model uncertainty

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October 20081st TURI network Conference28 (Usually) theoretical literature offers testable predictions and can used as a basis for empirical studies: Unfortunately, not only predictions of theories are differing, but also the results of empirical studies are heterogeneous. One reason for the heterogeneity: Estimation of different models! Depending on what combination of regressors the investigator chooses to put into his regression different significant determinants of union density are achieved! II. The empirical relevance of determinants and model uncertainty

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October 20081st TURI network Conference29 Examples: II. The empirical relevance of determinants and model uncertainty

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October 20081st TURI network Conference30 A phenomenon that can be observed in empirical studies: One study (based on a specific theoretical model) concludes that a specific variable has no significant influence Another study (based on a slightly different specification) concludes that the same variable has a significant positive influence Another study (based again on a slightly different specification) concludes that the same variable has a significant negative influence Reasons for estimating different models or for the existence of model uncertainty Theories are different (and competing) Theory is not precise enough in offering the true model so that empirical researchers have to check alternative specifications Small sample size (number of observations limited) so that a selection has to be made II. The empirical relevance of determinants and model uncertainty

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October 20081st TURI network Conference31 Comments on model uncertainty: Model uncertainty is pervasive in social science There is (almost) no theory in social science that is strong enough to dictate a single model specification All models are wrong, some are useful Box (1979) The typical case is one in which a number of variables are plausible predictors The problem is how to decide which specification to use Bayesian model averaging is (at least) an interesting approach in this context II. The empirical relevance of determinants and model uncertainty

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III.Bayesian Model Averaging and robust determinants

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October 20081st TURI network Conference33 Bayesian Model Averaging (BMA) Bayesian statisticians reject idea of a single, true estimate Instead: each parameter has a distribution! It is not believed that any of the models is actually correct – all models are used as proxies for some unknown underlying model BMA provides a coherent mechanism for accounting for model uncertainty as probabilities to different possible models are attached The idea of BMA is to average across several models instead of selecting one model It takes the K variables and runs a regression on all 2 K subsets of the K variables, before averaging over all these models III. Bayesian Model Averaging and robust determinants

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October 20081st TURI network Conference34 Bayesian Averaging of Classical Estimates (BACE) Sala-i-Martin, Doppelhofer and Miller, AER, 2004 The BACE approach constructs estimates by averaging weighted OLS coefficients across models The weights given to individual regressions have a Bayesian justification similar to the BIC Advantages of the BACE approach: In contrast to a standard Bayesian approach that requires the specification of a prior distribution for all parameters, BACE requires the specification (assumption) of only one prior hyper-parameter: the expected model size (= 7). The interpretation of estimates is straightforward: the weights applied to different models are proportional to the logarithm of the likelihood function corrected for degrees of freedom. III. Bayesian Model Averaging and robust determinants

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October 20081st TURI network Conference35 Determinants of trade union density – BACE results Dependent variable(s): Share of trade union members in relation to the total number of employees (i.e. trade union density) Yearly percentage change (Source and definition: OECD) Cross-country panel data set (balanced): OECD countries (Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Ireland, Italy, Japan, Netherlands, New Zealand, Norway, Portugal, Spain, Sweden, Switzerland, UK, USA) Time: 1970 to 2000 (missing values!) 55 (theoretically grounded) variables: Number of trade unions; strike activity; Ghent-System; participation of unions in socio-economic policy making; centralization of wage bargaining, unemployment rate, trade openness, … III. Bayesian Model Averaging and robust determinants

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October 20081st TURI network Conference36 Determinants of differences in the level across countries Robust determinants - Level (# 15): Number of union confederations (-) Ghent-System (+) Inflation (+) Union activities in policy-making (+) Business activities in policy-making (-) Centralisation of bargaining level (-) Yearly change of wage and salary earner; Extension practice; Closed/Union shop practice, Bargaining governability, Change of compensation per employee, change of wage rates, change of unit labour costs, change in productivity III. Bayesian Model Averaging and robust determinants

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October 20081st TURI network Conference37 Determinants of trade union density Robust Determinants - Change (# 10): Ghent-System (+) Left parties in government (+) GDP growth (-) Trade openness (-) Change in total labour force (-) Change in unemployment rate (+) Change in productivity (+); Population growth (-), Change employment share (-), one period lagged change in union density (+) III. Bayesian Model Averaging and robust determinants

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IV.Summary and conclusions

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October 20081st TURI network Conference39 What we already knew! Trade union density is different in different countries Trade union density is declining in many countries There are a lot of theories and studies available which aimed to explain differences in the level of trade union density and the decline over time We also knew that some theories and studies are saying this and some are saying that I knew that that this is not satisfactory at least I have the impression that the current state of research is unsatisfactory because we do not know what to do after reading all these studies IV. Summary and conclusions

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October 20081st TURI network Conference40 What do we know now? We still do not know which theory is the true one But we know that some theories are explaining trade union density better than other theories And there are variables which are robustly and highly correlated with trade union density and there are variables that are not correlated with trade union density These variables are of GENERAL relevance (not only specifical)! For the problem at hand the paper showed that: Only 15 variables (out of 55) are robustly correlated with the level of union density Only 10 variables (out of 55) are robustly correlated with the change IV. Summary and conclusions

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October 20081st TURI network Conference41 What do we know now? We still do not know which theory is the true one But we know that some theories are explaining trade union density better than other theories And there are variables which are robustly and highly correlated with trade union density and there are variables that are not correlated with trade union density These variables are of GENERAL relevance (not only specifical)! For the problem at hand the paper showed that: Only 15 variables (out of 55) are robustly correlated with the level of union density Only 10 variables (out of 55) are robustly correlated with the change In fact: Only few determinants are able to explain trade union density BUT: These few determinants are able to provide us an instrument for changing the situation, i.e. policy makers (for example trade unions) may use these few variables to increase the number of members in trade unions! The general relevance allows a very high degree of certainty that something can be changed! IV. Summary and conclusions

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October 20081st TURI network Conference42 The relevance of these (few) variables for trade unions Trade union density (memberships) varies with the business cycle Variables: in particular unemployment, inflation and economic growth hard to use as a policy instrument for trade unions Trade union density depends on country specific traditions (i.e. Ghent system) and on global economic trends traditions and global trends are also hard to use a policy tool (instrument) IV. Summary and conclusions

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October 20081st TURI network Conference43 The relevance of these (few) variables for trade unions There are two determinants that might be considered by trade unions to increase their memberships: Centralisation of collective bargaining Trade unions should bargain collective agreements on the right level, i.e. not too central and not too decentralized There is an optimal level of bargaining in between Number of union confederations The more united and integrated unions are the more members they have! It is not easy to unify different trade unions because of different traditions but it is possible because trade unionists are the ones who are able to change the situation IV. Summary and conclusions

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October 20081st TURI network Conference44 FINAL REMARKS THERE ARE DEFENITELY NO EASY WAYS (NO EASY INSTRUMENTS) FOR TRADE UNIONS TO INCREASE THEIR MEMBER SHARES BUT THERE ARE WAYS! The analysis identified ways and instruments that can be used and which are (extremely) empirically relevant. There might be other ways (country specific ways) but the two ways identified by this work will work with a high probability! IV. Summary and conclusions

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