Memo on benchmarks for national minimum wage

Transcription

1 Memo on benchmarks for national minimum wage The Labour and Community Constituencies of the Nedlac Wage Inequality Technical Task Team, negotiating the institution of a national minimum wage, requested the National Minimum Wage Research Initiative to provide statistical information on benchmarks for setting a national minimum wage. A summary is given on pages 1 4, followed by detailed information on the data sources and treatment of the data. Three key indicators may be useful in providing guidance for setting a national minimum wage in South Africa. 1 Summary 1.1 Labour market ratios Labour market indicators specifically the ratios between minimum wages and mean (or average) wages, and between minimum wages and median wages (the midpoint) can be instructive. International comparisons show that for different country groups the typical ratios of minimum- to- mean wages sit between 45% and 50%; with the middle- income country average of 48% most instructive for South Africa. These ratios are shown in Table 1 and Figure 1; the latter includes the full sample used. South Africa falls well below this international average with a minimum- to- mean ratio of 36% according to updated information from Rani et al. (2013). 1 The average minimum- to- median wage ratios are between 65% and 80% for all country groups with the average for middle- income countries sitting at 80%; these ratios are shown in Table 2 and Figure 2. South Africa sits below this at 74%. Table 1 Minimum- to- mean wage ratios, various country groups Average Median 2 No. of obs. 3 All available countries Developing countries Middle- income countries Source: ILO (2016), Global Wage Database 1 This figures for South Africa use sectoral determinations. Rani et al. at the ILO consider these estimates more accurate then the older information in the ILO Global Wage Database. 2 The median within the two tables refers to the level in the middle of all the ratios for that set of ratios. 3 Refers to the number of countries within that country group. 1

2 Table 2 Minimum- to- median wage ratios, various country groups Average Median No. of obs. All available countries Developing countries Middle- income countries Source: ILO (2016), Global Wage Database Figure 1 Minimum- to- mean wage ratios (all countries) Malawi Botswana Kazakhstan Russia Mauritius Azerbaijan Mongolia Mexico Jamaica Latvia Viet Nam Tanzania Armenia India Czech Republic Belarus China South Korea Estonia Romania Jordan United States Croatia Brazil Tajikistan Slovakia Ethiopia Ukraine Kenya Bulgaria Moldova Japan Egypt Taiwan, China Costa Rica Hungary Poland Sri Lanka Cyprus Luxembourg Dominican Republic Panama Canada Lithuania Serbia Hong Kong, China Nicaragua Israel Slovenia Ireland Cuba Belgium United Kingdom Portugal France Malta Peru Syria Australia Albania Ecuador Oman New Zealand Chad Netherlands Thailand Madagascar El Salvador Argentina Bolivia Indonesia Lebanon Lesotho Pakistan Fiji Guatemala Philippines Ratio Source: ILO (2016), Global Wage Database Figure 2 Minimum- to- median ratios (all countries) Mexico Czech Republic United States Uruguay Poland Slovakia Lithuania Japan Armenia South Korea Canada Cyprus Malta Brazil United Kingdom Moldova Latvia Israel New Zealand Australia Costa Rica Portugal Venezuela Peru Panama Colombia Ecuador Argentina Turkey Honduras Philippines Ratio Source: ILO (2016), Global Wage Database 2

3 Table 3 takes the ratios for middle- income countries above and calculates what these would equate to in South Africa using data from the previous section. Depending on how mean and median wages in South Africa are defined, 48% of the mean wage is between R4 355 and R5 161 per month and 80% of the median wage is between R3 428 and R3 918 per month. These are given in April 2015 rands. Table 3 Percentage of mean and median wages for South Africa (Feb 2016) 48% of Mean 80% of Median All full- time employees Formal ex. agriculture ex. domestic work Source: LMDSA 2014 dataset, own calculations and Finn (2015) 1.2 Current collective bargaining minima Current collective bargaining may also be useful as a benchmark. In fact the request for this data arises from a government proposal to consider this as a benchmark for the NMW. Using data from the Department of Labour (DoL 2015, supplemented by data from the Public Service Co- ordinating Bargaining Council, PSCBC 2014), Table 4 gives the weighted and unweighted averages for bargaining council agreement minima (weighted according to the number of workers covered). 4 We see that the private sector weighted average for bargaining council agreements is R4 355 per month which rises to R5 747 per month when the public sector is included. We check the robustness of these figures by using data given in Appendix C of the DPRU NMW report (DPRU 2016) and the results are extremely similar (see Section 3.3 for a discussion of this). Using weighted averages is certainly more appropriate if one wishes to benchmark a national minimum wage against the current levels of collective bargaining agreements in South Africa. By way of illustration: it would be peculiar to give equal weight to the Building Industry Bargaining Council for Kimberley which impacts an estimated 496 workers and the Metal and Engineering Industries Bargaining Council (National) which covers workers. Table 4 Current collective bargaining levels from Department of Labour (2015) Bargaining councils Unweighted average Unweighted median Weighted average - private sector Weighted average - public and private sector According to the Department of Labour (DoL 2015) the average and median level of the sectoral determinations is just above R2 700 per month. 3

4 Using detailed data provided by the Labour Research Service (LRS 2016) which compiles all available wage agreements including both bargaining councils and bilateral agreements we isolate 450 agreements with 2015 data. In each we use the lowest minimum wage specified. The ability to weight the data is very limited (given insufficient coverage data) and so the weighted means and medians should be viewed with caution. Despite this, the data is not dissimilar from that in Table 4, with Table 5 showing averages between approximately R4 300 and R Table 5 Current minimum wage levels from Labour Research Services (2015) Unweighted Mean Median Bargaining councils Bargaining councils and bilaterals Weighted Bargaining councils Bargaining councils and bilaterals A rounded- off summary of the most important data is given on page Workers basic needs Arguably the most important, and most neglected, benchmark is workers needs as outlined by the ILO and discussed here in terms of poverty measures. Updating the figures in Finn (2015) to February 2016 rands we see that the preferred individual poverty line is R1 386 which equates to R5 544 for a family of four and corresponds to a working- poor line of R These serve as indicators as to the needs of workers and their dependents. Table 6 Updated poverty lines (February 2016) Apr- 15 Feb- 16 Individual poverty line Household poverty line (family 4) Working poor line Source: Updated from Finn (2015) using NIDS Wave 3 and LMDSA datasets For technical notes on these lines see Finn (2015). 4

5 1.4 Conclusion If we extract the most important data and round it off to the nearest R50 the benchmarks are: Poverty lines Household poverty line (family of 4) Working poor line Ratios Min/Average Min/Median Middle- income countries' ratio South African rand equivalent Collective bargaining averages Average Source 5 Bargaining councils (private sector) unweighted DoL and DPRU Bargaining councils (all) unweighted DoL and DPRU Bargaining councils and bilaterals agreements (all) unweighted LRS Bargaining councils (private sector) weighted DoL and DPRU Bargaining councils (all) weighted DoL and DPRU The relevant benchmarks congregate between R3 500 and R See discussion in Section 3.3 regarding DPRU data. 5

6 2 Technical notes on labour market ratios The figures and tables for international comparisons use the latest available data (between 2009 and 2013) in the ILO s Global Wage Database. The number of observations for each country group is given. The figures are different from those in DPRU (2016) given DPRU s (unreferenced) replacement of the ILO data with other data and their (also unexplained) sample selection. We use all countries for which there is available data but remove outliers. Outliers for minimum- to- median ratios are those in which the ratio is less than 0.1; this results in one removal. Outliers for minimum- to- mean ratios are those where the ratio is less than 0.1 or greater than 2; this results in six removals. South Africa is also excluded in both series. Given the difficulty in establishing the level of the minimum wage in countries where there are multiple minima the data should be viewed with caution. However, given that this is the most comprehensive data source available and has a large sample size, the average ratios we highlight are credible indicators, and are certainly the most accurate available for a large sample set. Rani et al. (2013) have collected more detailed data for a sample of 11 developing countries. In this sample, the average minimum- to- mean ratio is 0.51 and the average minimum- to- median ratio is 0.74 (excluding South Africa), both very similar to the ratios in the GWD (the raw data as well as updated data for India and South Africa were provided by the authors of Rani et al. 2013). 6

7 3 Technical notes on collective bargaining data There is no comprehensive database with collective bargaining minima. This report uses information provided by the Department of Labour (DoL) and by the Labour Research Service (LRS), supplemented by data from other collective Bargaining Councils and the DPRU. 6 The LRS data is the most comprehensive database including bilateral collective bargaining agreements. However, there are still gaps in the data. 7 Note: All results are reported in 2015 rands. 3.1 Department of Labour Data The DoL s report Minimum Wage in South Africa, June 2015, Version 2, contains useful statistics but is incomplete Data available Two tables on collective bargaining agreements are given and explained as follows (page 4): Table 1 presents minimum wages for a number of Bargaining Council collective agreements, arranged by three skill levels. The skill levels are determined by selecting wages attached to low paying occupational categories (e.g. General worker), middle level categories (e.g. Artisan) and high level categories (e.g. Factory manager). Figures for the number of employees covered by the collective agreements are also included. All information is up to March The information in the table is derived from a system used by the Department of Labour to capture wage information from collective agreements. Table 2 gives the lowest minimum wage contained in every bargaining council agreement. As many agreements as possible have been included, including agreements between parties to the council which have not been extended by the Minister. The table also contains information on job category and hours of work in the agreements. Two further tables in the document list minimum wages for sectoral determinations and limited minima in the mining sector. 6 We are grateful to the LRS for making their full database available to us. We thank George Mthethwa, Edward Cottle and Trenton Elsey for their assistance. The LRS database could serve as the basis for an official database of the NMW competent authority if BC indicators are used when setting the NMW. 7 The researchers who compiled this report are happy to make available the original excel/csv files (with permission from DoL and LRS) as well as the Stata do files. There may be ways of improving the techniques used and we are very open to collaboration in this regard. 7

8 In Table 1: There are 27 BCs listed; All BCs listed have minimum wages for unskilled workers given; All but two BC listed give the number of workers affected. 8 In Table 2: There are 37 BCs listed; All the BCs listed in Table 1 appear in Table 2 although the Public Sector which appears as a single BC in Table 1 is split into five BCs in Table 2; In addition there are 6 BCs listed that do not appear in Table 1; Five BCs in Table 2 do not list monthly minimum wages Assessment of data Key weaknesses in the data: The data does not include all BCs in Table 1; Completed data is not given for certain BCs; 9 There are no advantages to Table 1, because Table 2: Includes all the BCs in Table 1 and others; Now includes the numbers of workers affected, extracted from Table 1; Predominately includes the actual minima for the lowest paid worker and not the unskilled category Cleaning the data Adjustments made to Table 2: We have transposed the number of workers covered by the BC from Table 1 to Table 2. This covers 25 BCs; We have used the minimum wage given in Table 1 for the Motor Ferry Industry Bargaining Council of South Africa (National) in Table 2 as this was one of those that did not list a minimum; We have used the lowest minima given; Where there are multiple lowest minima for a single BC, for example for Area A, B, C etc., we have used the median. The number of workers covered by the Public Sector agreements is not given and is taken from information provided by the Public Service Co- ordinating Bargaining Council These are: Bargaining Council for the New Tyre Manufacturing Industry and Public Service. 9 In Table 2 (the more completed data set) data on wages and the number of workers covered is missing from: Transnet Bargaining Council (National), Amanzi Bargaining Council, Bargaining Council for the Canvas Goods Industry (Witwatersrand & Pretoria), South African Local Government Bargaining Council. In addition, the numbers of workers covered is missing from: National Bargaining Council for the Sugar Manufacturing and Refining Industry, National Bargaining Council for the Wood and Paper Sector, New Tyre Manufacturing Industry 10 content/uploads/vote/vote- weight- pscbc pdf 8

9 We have supplemented the data with data requested from Bargaining Councils directly Output Table 2 Unweighted average R Unweighted median R Unweighted average - private sector R Weighted average - private sector R Weighted average - public and private sector R Robustness checks We conducted a number of checks to assess the robustness of the data outputs provided. The first is to remove any private sector BC data that we included that were not provided by the DoL; the results are extremely similar, differing by as little as R1 and by as much as R68. The second is to use data given in Appendix C of the DPRU report, Investigating the feasibilty of a national minimum wage for South Africa, which lists the lowest minimum in each BC agreement. 12 The DPRU also includes some BC minima that are not given by the DoL (if we updated the DoL data with these the output does not alter significantly). The weighting is done using the numbers of workers provided by DoL and PSCBC. The output is: DPRU data (with corrections) Unweighted average R Unweighted median R Unweighted average - private sector R Weighted average - private sector R Weighted average - public and private sector R For instance the Bargaining Council for the Canvas Goods Industry (Witwatersrand & Pretoria). Including or excluding these BCs makes extremely little difference to end results. 12 Some corrections were made to the data. For example, the DPRU lists the minimum for the Bargaining Council for the Canvas Goods Industry (Witwatersrand & Pretoria) as R but the agreement shows a minimum of R The DPRU lists the minimum for the Metal and Engineering Industries Bargaining Council (National) as R For this BC they note that they used the minimum for Rate 1(a) Project Labour Agreement workers. The BC agreement ties this level to the lowest level in the Civil Engineering Bargaining Council. The DPRU lists the Civil Engineering Bargaining Council rate as not R The 2014/15 agreement gives this rate as R25.18 per hours which is R per month (it is possible the DPRU updated this to 2015/16 to get the R ). We therefore change the original R to R (the results do not differ much when using R ). 9

10 The output is remarkably similar, differing (for the averages) by as little as R1 and as much as R40. The only significant difference is the median. 3.4 Labour Research Service Data Working with the LRS data is more complex Data available For 2015 the LRS lists 603 agreements for bargaining councils, bilateral agreements and sectoral determinations that are associated with 2015 minimum wages Cleaning the data At times more than one category of worker is included, e.g. under the bargaining council of Food Retail, Retail, Catering & Allied Trade minima are given for General Assistant, Watchman and Catering Assistant. o We keep only the lowest in such cases. 61 observations are dropped. Certain BCs have detailed regional differentiation, e.g. Electrical and Hairdressing. o We calculate a median for these regional minima (this is what the LRS does to some data before inputting it). 13 Where different bilateral agreements were made by the same company for different regions / factories these were kept as is, i.e. the multiple minima remained (this affects very few companies). Many mining agreements list minima for both Surface and Underground workers. Surface workers minima are consistently lower. We report results including only Surface minima. In certain instances it is not clear what the distinction between two observations are. 14 Dropping other variables: o One direct duplicate exists and is dropped. 15 o In one instance a farm wage which was reduced by the inclusion of in- kind benefits was dropped. 16 o The novice category from Sibanye Gold was dropped (2 observations). 13 This means keeping a single observation for those agreements and the others being dropped. 67 observations were dropped. Two bilateral agreements were included in this process in error (each with two observations), the code should be improved to avoid this but the impact is immaterial. 14 For example: Laundry, Cleaning & Dyeing (Other) WC, Laundry, Cleaning & Dyeing D/C (WC) 15 Hairdressing & Cosmetology Trade (Alberton) Division 105 Alberton 16 Bloubank Estates cc (Workers living on the farm) was dropped by Bloubank Estates cc (Workers living in town) was kept. 10

11 A few spelling corrections were made to the raw data. We drop sectoral determinations. This leaves us with 450 agreements. 84 Bargaining Councils 366 Bilaterals Weighting the data The LRS data does include Estimated Total Workforce and Estimated Union Membership. However, amongst our 450 agreements only 14 have an Estimated Total Workforce value and only 165 have an Estimated Union Membership value. Our weighted results below are reported using the Estimated Union Membership as a weight for those 178 agreements. It should be noted that large BCs, like the public sector, do not have Estimated Union Membership. These weighted results should be viewed with extreme caution but, irrespective, it is very likely that given proper weighting the means and medians would be higher than the unweighted data Assessment of data Key strengths: The data contains a large number of bargaining council and bilateral agreements even once cleaned. Key weaknesses: The absence of comprehensive statistics on the number of workers affected by each agreement makes weighting very difficult. The weighted results below should be viewed with great caution Output Unweighted Mean Median Bargaining Councils Bargaining Councils and Bilaterals Weighted Bargaining Councils Bargaining Councils and Bilaterals

12 4 References DoL, Minimum wages in South Africa. Department of Labour, Government of the Republic of South Africa. DPRU, Investigating the feasibilty of a national minimum wage for South Africa. University of Cape Town: Development Policy Research Unit. Finn, A., A national minimum wage in the context of the South Africa labour market. University of the Witwatersrand, Working Paper Series No. 1. ILO, Global Wage Database. LRS, AWARD Database. PSCBC, Public Service Co- ordinating Bargaining Council Membership Statistics. Public Service Co- ordinating Bargaining Council. Rani, U., Belser, P., Oelz, M., and Ranjbar, S., Minimum wage coverage and compliance in developing countries. International Labour Review, 152 (3 4),