1. Skills, Technology and Capital Intensity: Employment & Wage Shifts in post-apartheid South Africa Labour Market Intelligence Partnership Policy Roundtable Haroon Bhorat, Ben Stanwix, Sumayya Goga Development Policy Research Unit (DPRU) 24 January 2014

2. Outline Introduction Data Changing Employment Landscape – Sectoral and Skills-biased trends Skills-Biased Technological Change – A Decomposition Analysis Task-Based Wage Analysis – Quantile Regression Application to Occupational Tasks Conclusions

3. Introduction South Africa is an upper middle-income country: – Population 51 million – Resource rich, well-developed financial sector – GDP per capita US$7,507 (World Bank, 2012) – High unemployment (25%) – High poverty & inequality levels In post-apartheid period, continued skills-biased labour demand contributes to inequality & high unemployment rates

4. Key Questions How has structure of economy changed in 10-year period? Are employment shifts ‘skills-biased’? Do within- or between-sector shifts explain changes in employment? What has happened to wage returns across occupation task categories (& its link to technological and capital-intensive change)? What are the lessons for ‘inclusive growth’?

5. Data Labour Force Surveys (2001-2007) – Bi-annual Quarterly Labour Force Survey (2008-2011) Stratified random sample of ±30 000 dwellings Occupational and Industry codes (ISOC and SIC) Wage Data: – LFS: 2001-2007 – QLFS: 2010 and 2011 (annual)

6. Data Labour Force Surveys (2001-2007) – Bi-annual Quarterly Labour Force Survey (2008-2011) Stratified random sample of ±30 000 dwellings Occupational and Industry codes (ISOC and SIC) Wage Data: – LFS: 2001-2007 – QLFS: 2010 and 2011 (annual)

7. Real Quarterly Annualised GDP & Total Employment: Total & Percentage Change, 2001-2012 Source:SARB & StatsSA (LFS 2001-2007 and QLFS 2008-2012), Author’s Calculations

8. Main Sector Share of Real GDP, 1993 & 2012 Source:SARB, Quarterly Bulletin, Various issues and Authors’ Calculations

9. Gross Value Added and Employment Growth, by Sector: 2001-2012 Source:SARB, Quarterly Bulletin, Various issues and Authors’ Calculations

10. Employment Shifts by Main Sector, 2001-12 Source:StatsSA (LFS 2001 and QLFS 2012), Author’s Calculations Growth (2001-2012)Employment Shares Share of Change ( Δ E j / Δ E) Absolute Relative (% Δ E j /% Δ E) 20012012(2001-2012) Primary-719,232*-2.60.150.07-0.28 Agriculture-514,468*-2.70.100.04-0.20 Mining-204,764*-2.20.050.02-0.08 Secondary537,376*1.00.21 Manufacturing112,1490.30.140.120.04 Utilities10,7740.50.008 0.004 Construction414,453*2.50.050.070.16 Tertiary2,720,821*1.60.630.711.08 Trade513,572*0.90.21 0.20 Transport288,364*2.10.040.060.11 Financial782,108*2.80.090.130.31 Comm Serv1,041,524*2.10.170.220.42 Priv Hholds95,2530.40.090.080.04 Total2,497,763*1.0111

11. Employment Shifts by Sector-Skill Cells, 2001-2012 Source:StatsSA (LFS 2001 and QLFS 2012), Author’s Calculations Proportions Change in Prop Change in No 200120122001-2012 Primary High-Skilled0.030.080.0527,602 Med-Skilled0.540.37-0.17-571,229* Unskilled0.430.560.13-175,392* Total11-719,232* Secondary High-Skilled0.140.180.04188,518* Med-Skilled0.700.62-0.08136,140 Unskilled0.160.200.04214,002* Total11537,376* Tertiary High-Skilled0.270.290.02931,498* Med-Skilled0420.430.0081,214,349* Unskilled0.310.28-0.03576,288* Total112,720,821*

12. A Theory of Relative Labour Demand Shifts Relative Labour demand patterns driven at the sectoral level by two forces: – within-sector shifts (driven, for example, by technological change) – between-sector shifts (driven, for example, by trade flows and evolving product demand) Identifies relative demand shifts in net sectoral employment growth

13. Relative Labour Demand Shifts: A Decomposition Analysis Estimate using standard Katz & Murphy (1992) decomposition technique: The subscript k refers to occupation (or other groups) and j refers to sectors. The total relative demand shift for group k in the period under consideration is measured by or, where is group k’s share of total employment in sector j in the base year. is the change in total labour input in sector j between the two years. Derive within-sector shift as residual of total- and between-sector shifts.

14. Industry-Based Relative Demand Shift Measures, by Occupation: 2001-2012 Source:StatsSA (LFS 2001 and QLFS 2012), Author’s Calculations BetweenWithinTotal Share of Within in Total High-Skilled Managers0.9212.6313.3294.9% Professionals3.0315.0417.2087.4% Medium-Skilled Clerks1.5912.8814.0791.6% Service & Sales Workers1.9211.7513.2388.9% Skilled agric and fishery-0.55-19.60-20.4795.8% Craft & Trade Workers1.357.889.0187.4% Operators & Assembler0.191.631.8190.1% Unskilled Elementary Workers0.281.101.3780.1% Domestic Workers0.373.493.8391.1%

15. Real Wages Shifts by Occupational Tasks How have wages changed for those involved in specific tasks? Autor, Levy & Murnane (2003), Goos & Manning (2007), Acemoglu & Autor (2011) identify ‘occupational tasks’ as a key channel for wages shifts Relevant in face of capital deepening and skills-biased technological change Jobs requiring cognitive skill, creative problem-solving or face-to-face interaction are unlikely to be automated or threatened by international competition or technological change Routine tasks on an assembly line, for e.g. face high risks

16. From an Occupation- to a Task-based Measure of Skills Information and communication technology (ICT)-related jobs: High information content; likely to be affected by technological change through adoption of new technologies, or face global low-cost competition. Include activities such as getting information, analysing data, recording information, and often involve interaction with computers. In the SASCO codes this consists of occupations such as software engineers, computer programmers, typists, data entry, and so on. Automation/routinisation: Jobs routine in nature and potential to be automated; involving repeated tasks; structured work environments, and where the pace of the job is often determined by mechanical or technical equipment. These jobs could also potentially be at risk through increased trade and import penetration. They include occupations such as textile weavers, engravers, machine operators, and assemblers. Face-to-Face: Work that relies on face-to-face contact, such as establishing and maintaining personal relationships, working directly with the public, managing people, caring for others, teaching, and work requiring face-to-face discussions. Generally these are jobs that cannot be easily automated or replaced by a competing international firm. Such jobs range from room service attendants, food vendors, labour supervisors, travel guides, to therapists and teachers. On-Site: Jobs that require the worker to be present at the particular place of work, and usually include tasks involving physical work, controlling machines/processes, operating vehicles or mechanical equipment, inspecting equipment, constructing physical objects. Again, these jobs are not easily offshorable and are generally made up of construction workers, machine operators, drivers, mechanics, and various kinds of manual labourers. Decision-Making/Analytic: Work that requires non-routine decision-making abilities, usually tasks that involve creative thought, problem-solving, developing strategies, taking responsibility for outcomes and results. Such jobs cannot easily be automated and are usually at lower risk of being displaced by international competition. Occupations include artists, all types of professionals, managers, and other jobs generally considered to be high-skilled jobs.

17. Occupation Categories and Occupational Tasks, 2001 Source:StatsSA (LFS 2001 and QLFS 2012), Author’s Calculations LFS September 2001 ICTAutomatedFace-to-FaceOn-siteAnalytic Total LFS Totals No.ShareNo.ShareNo.ShareNo.ShareNo.Share Managers00.000 663 2270.198 6810.00663 2270.351 335 135663 945 Professionals77 9220.122 9860.00249 4900.0731 7760.00381 8610.20744 036485 829 Technicians178 6380.29205 1650.05531 8640.15134 1100.02671 2190.361 720 9961 176 031 Clerks368 9230.591 029 7700.26356 1390.10100 9980.0251 4810.031 907 3111 090 772 Service00.000 1 034 6430.29740 5260.1232 9930.021 808 1621 429 021 Skilled Agriculture Workers00.00283 4500.0700.00292 1280.0543 4640.02619 042520 699 Craft Workers00.00724 0150.1800.001 297 7630.2030 1340.022 051 9121 529 375 Operators and Assemblers00.00475 8690.1200.00878 2390.1400.001 354 1081 127 155 Elementary Workers00.001 311 6560.33673 7910.192 055 7140.3200.004 041 1622 252 554 Domestic Workers00.000 0 881 4110.1400.00881 411 Total625 48314 032 91213 509 15416 421 34411 874 380116 463 27711 156 792

18. Task Distributions, By Main Sector: 2001 Source:StatsSA (LFS 2001 and QLFS 2012), Author’s Calculations ICTAUTOFACEONSITEANALYTIC SectorNo.ShareNo.ShareNo.ShareNo.ShareNo.Share Primary Agriculture6 2520.011 054 4580.2623 6190.011 195 1430.1853 5430.03 Mining19 3380.03415 2100.1026 2150.01453 4090.0723 0240.01 Secondary Manufacturing104 6520.171 028 2470.25197 0300.05968 7290.15237 0790.12 Utilities7 1700.0140 0580.0119 5690.0168 8560.0115 7920.01 Construction7 2440.01223 5530.0538 7610.01586 4220.0936 1060.02 Tertiary Trade85 8400.14505 7610.121 566 3430.441 265 9330.19298 0410.16 Transport38 6650.06162 2190.04175 1220.05230 0250.04109 6990.06 Financial Services240 8450.38302 8980.07491 1640.14338 4580.05343 7880.18 Community Services114 7060.18378 8780.091 032 9460.29544 9780.08794 5820.41 Private HHs00006 5020898 6220.142350 Total624 71214 123 11513 582 89816 553 49511 917 2471 ICTAUTOFACEONSITEANALYTIC SectorNo.ShareNo.ShareNo.ShareNo.ShareNo.Share Primary Agriculture6 2520.011 054 4580.2623 6190.011 195 1430.1853 5430.03 Mining19 3380.03415 2100.1026 2150.01453 4090.0723 0240.01 Secondary Manufacturing104 6520.171 028 2470.25197 0300.05968 7290.15237 0790.12 Utilities7 1700.0140 0580.0119 5690.0168 8560.0115 7920.01 Construction7 2440.01223 5530.0538 7610.01586 4220.0936 1060.02 Tertiary Trade85 8400.14505 7610.121 566 3430.441 265 9330.19298 0410.16 Transport38 6650.06162 2190.04175 1220.05230 0250.04109 6990.06 Financial Services240 8450.38302 8980.07491 1640.14338 4580.05343 7880.18 Community Services114 7060.18378 8780.091 032 9460.29544 9780.08794 5820.41 Private HHs00006 5020898 6220.142350 Total624 71214 123 11513 582 89816 553 49511 917 2471

19. Estimation Strategy

20. Task Wage Premia, plotted by Quantiles: 2001-2011 Source:StatsSA (LFS 2001 and QLFS 2012), Author’s Calculations

21. Conclusions: Employment Employment driven by 2001-2008 growth Primary sector employment collapse – Agriculture (Impact of W m ) and Mining together losing over 700 000 jobs  Both employers of least-skilled workers Lacklustre employment growth in Manufacturing Growth within tertiary sectors such as financial services and community services – Public sector as a growing source of employment – Financial Services & Temporary Empl. Service Providers Employment gains in high- and medium-skilled occupations Decomposition Results: Technological change, increasing capital intensity: within-sector shifts dominate reasons for relative labour demand shifts in South Africa

22. Conclusions: Wages Jobs that involve automated or routine tasks have experienced a drop in wage levels (Agriculture, Mining and Manufacturing) Jobs involving face-to-face tasks and those with an ICT component have seen rising wages in general (largely Community, Trade & Financial Services) Onsite jobs saw falling returns at upper end of the distribution (Manufacturing, Agriculture) but stable returns at the lower end (Domestic Workers) Analytic jobs posted high and relatively stable wages (community and financial services) At the bottom of the distribution wages remained relatively stable or rose in all task categories. Impacts of minimum wages and collective bargaining outcomes

23. LMIP structure