New evidence based on household surveys F. Rycx & S.Kampelmann ULB/DULBEA What do we and what don t we know about minimum wages in Europe? Expert conference organised by the European Trade Union Institute (ETUI) 12 December 2011
Outline Context and research objectives 1 Context and research objectives 2 3 4
Statistical blanks in data on European minimum wage sector
Statistical blanks in data on European minimum wage sector Extant surveys cover limited number of countries (often the same)
Statistical blanks in data on European minimum wage sector Extant surveys cover limited number of countries (often the same) Statistical panoramas of minimum wage earners are outdated (and partial)
Statistical blanks in data on European minimum wage sector Extant surveys cover limited number of countries (often the same) Statistical panoramas of minimum wage earners are outdated (and partial) Few efforts to disaggregate the group of minimum wage earners
Statistical blanks in data on European minimum wage sector Extant surveys cover limited number of countries (often the same) Statistical panoramas of minimum wage earners are outdated (and partial) Few efforts to disaggregate the group of minimum wage earners Limits of conventional indicators (e.g. Kaitz index)
Research objectives
Research objectives 1 Literature review: concepts, mechanisms, statistics
Research objectives 1 Literature review: concepts, mechanisms, statistics 2 Measurement of minimum wage bite for a set of European countries
Research objectives 1 Literature review: concepts, mechanisms, statistics 2 Measurement of minimum wage bite for a set of European countries 3 Discussion of empirical findings in light of widening wage distributions, high unemployment, increasing poverty, precariousness of employment, and fiscal austerity
Ce salaire horaire minimum correspond au niveau le plus bas applicable, à savoir à la fonction de manoeuvre ordinaire. CCT relative au salaire horaire minimum conclue le 27 juin 2007 au sein de la Commission Paritaire de l industrie chimique.
Tariflöhne sind Mindestlöhne. WSI Tariflohndatenbank
Typology of minimum wage systems
Typology of minimum wage systems Type 1 A single statutory minimum wage fixed at national level with no subsequent differentiation:
Typology of minimum wage systems Type 1 A single statutory minimum wage fixed at national level with no subsequent differentiation: clean cut system
Typology of minimum wage systems Type 1 A single statutory minimum wage fixed at national level with no subsequent differentiation: clean cut system Type 2 Many different minimum wages exist (specific sectors, regions, occupations, etc):
Typology of minimum wage systems Type 1 A single statutory minimum wage fixed at national level with no subsequent differentiation: clean cut system Type 2 Many different minimum wages exist (specific sectors, regions, occupations, etc): fuzzy system
Qualitative features of minimum wage systems
Qualitative features of minimum wage systems Main mechanism regulating minimum wages (government agencies, tripartite commissions, sectoral bargaining. etc.)
Qualitative features of minimum wage systems Main mechanism regulating minimum wages (government agencies, tripartite commissions, sectoral bargaining. etc.) Extension mechanism (erga omnes laws, selective extension laws, etc.)
Qualitative features of minimum wage systems Main mechanism regulating minimum wages (government agencies, tripartite commissions, sectoral bargaining. etc.) Extension mechanism (erga omnes laws, selective extension laws, etc.) Exempted categories of workers (civil servants, apprentices, etc)
Qualitative features of minimum wage systems Main mechanism regulating minimum wages (government agencies, tripartite commissions, sectoral bargaining. etc.) Extension mechanism (erga omnes laws, selective extension laws, etc.) Exempted categories of workers (civil servants, apprentices, etc) Differentiation of minimum rates (reduced rates for younger workers, people with disabilities, etc.)
Classification of EU-SILC countries Clean cut system Fuzzy system Nordic FI, DK, NO, SE, IS Anglo-saxon UK, IE Western continental LU, NL AT, BE, DE Southern CY, ES (?), PT GR, IT Centr. & Eastern CZ, BG, EE, HU, LT, LV, PL, RO, SI
Selection of countries for in-depth study
Selection of countries for in-depth study Reflect international diversity of minimum wage systems Geographic balance Sufficiently large EU-SILC sample to allow for statistical inference
Classification of EU-SILC countries
Classification of EU-SILC countries Clean cut system Fuzzy system Nordic FI, DK, NO, SE, IS Anglo-saxon UK, IE Western continental LU, NL AT, BE, DE Southern CY, ES, PT GR, IT Centr. & Eastern CZ, BG, EE, HU, LT, LV, PL, RO, SI
Classification of EU-SILC countries Clean cut system Fuzzy system Nordic FI, DK, NO, SE, IS Anglo-saxon UK, IE Western continental LU, NL, FR AT, BE, DE Southern CY, ES, PT GR, IT Centr. & Eastern CZ, BG, EE, HU, LT, LV, PL, RO, SI
Translating the minimum wage systems into code
Translating the minimum wage systems into code EU-SILC and GSOEP datasets; wave 2008 (earnings 2007)
Translating the minimum wage systems into code EU-SILC and GSOEP datasets; wave 2008 (earnings 2007) Gross hourly earnings
Translating the minimum wage systems into code EU-SILC and GSOEP datasets; wave 2008 (earnings 2007) Gross hourly earnings Additional variables to reflect differentiation (age, educational activity, labour market experience, occupation, disability status, sector... )
Countries with Type 1 systems ( clean cut ) BG, HU, PL, RO ES UK, IE
Countries with Type 2 systems ( fuzzy ) BE DE
Descriptive statistics (9 European countries, 2007)
Descriptive statistics (9 European countries, 2007) Level of minimum wages, share of minimum earners, and Kaitz indices per country
Descriptive statistics (9 European countries, 2007) Level of minimum wages, share of minimum earners, and Kaitz indices per country Individual characteristics of employees below and above minimum wages
Descriptive statistics (9 European countries, 2007) Level of minimum wages, share of minimum earners, and Kaitz indices per country Individual characteristics of employees below and above minimum wages Job characteristics of employees below and above minimum wages
Descriptive statistics (9 European countries, 2007) Level of minimum wages, share of minimum earners, and Kaitz indices per country Individual characteristics of employees below and above minimum wages Job characteristics of employees below and above minimum wages Distribution of minimum wage earners according to sector of activity
Descriptive statistics (9 European countries, 2007) Level of minimum wages, share of minimum earners, and Kaitz indices per country Individual characteristics of employees below and above minimum wages Job characteristics of employees below and above minimum wages Distribution of minimum wage earners according to sector of activity Household characteristics of employees below and above minimum wages
Weighted Kaitz index Clean cut systems : Hungary 57.0 11.5 UK 53.2 9.5 Ireland 52.6 9.2 Poland 47.5 8.9 Romania 44.4 4.9 Bulgaria 41.0 5.8 Spain 39.9 3.8 Fuzzy systems : Belgium 59.6 11.4 Germany 57.8 (19.0) Share of minimum earners
Logit model predicting likelihood of earning the minimum wage
Logit model predicting likelihood of earning the minimum wage Dependent variable: minimum wage dummy
Logit model predicting likelihood of earning the minimum wage Dependent variable: minimum wage dummy Independent variables: temporary work contract, part time, job change, tenure, occupational category, age, sex, education, firm size, sector of activity
Logit model predicting likelihood of earning the minimum wage Dependent variable: minimum wage dummy Independent variables: temporary work contract, part time, job change, tenure, occupational category, age, sex, education, firm size, sector of activity Separate individual-level regression for each of the nine countries
Descriptive statistics and logit regression:
Descriptive statistics and logit regression: Minimum wage earners on average younger, more feminine, less educated
Descriptive statistics and logit regression: Minimum wage earners on average younger, more feminine, less educated Proportion with temporary work contracts and part time work is on average higher among minimum wage earners
Descriptive statistics and logit regression: Minimum wage earners on average younger, more feminine, less educated Proportion with temporary work contracts and part time work is on average higher among minimum wage earners Size of effects differs across countries
Other results:
Other results: Minimum wage earners tend to live in bigger households, have lower disposable family income, and higher risk of poverty
Summary of results so far
Summary of results so far Updated, extended, and improved statistics on minimum wages
Summary of results so far Updated, extended, and improved statistics on minimum wages Diversity of minimum wage systems; co-existence of different rates in (almost) all countries
Summary of results so far Updated, extended, and improved statistics on minimum wages Diversity of minimum wage systems; co-existence of different rates in (almost) all countries Sign of effects for socio-demographic variables often similar across countries, but size of effects differ
Summary of results so far Updated, extended, and improved statistics on minimum wages Diversity of minimum wage systems; co-existence of different rates in (almost) all countries Sign of effects for socio-demographic variables often similar across countries, but size of effects differ Extensive infra-national variations in rates and employment spikes, notably among sectors of activity
Improve regression analysis: additional controls, interpretation of cross-country differences...
Improve regression analysis: additional controls, interpretation of cross-country differences... Compare Kaitz indices for sub-groups (age, gender, occupation, educational attainment, contract type etc.)
Improve regression analysis: additional controls, interpretation of cross-country differences... Compare Kaitz indices for sub-groups (age, gender, occupation, educational attainment, contract type etc.) Compare our results with other sources (OECD)
Improve regression analysis: additional controls, interpretation of cross-country differences... Compare Kaitz indices for sub-groups (age, gender, occupation, educational attainment, contract type etc.) Compare our results with other sources (OECD) Extend analysis to other countries (France, Italy, Nordic countries... )
Improve regression analysis: additional controls, interpretation of cross-country differences... Compare Kaitz indices for sub-groups (age, gender, occupation, educational attainment, contract type etc.) Compare our results with other sources (OECD) Extend analysis to other countries (France, Italy, Nordic countries... ) Contextualize and interpret results
Thank you very much for your attention.