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Minimum Wage Enforcement in South Africa: Measurement and Determinants

Literature › Works

Natasha Mayet (2010). Minimum Wage Enforcement in South Africa: Measurement and Determinants. Dissertation, Masters in Applied Economics, School of Economics, University of Cape Town (supervisor: Haroon Bhorat). University of Cape Town.
Type thesis
Scope Post-1994 South African economy
Method econometric
Period studied 2001–2007
Regions South Africa, nine provinces and district councils
Themes labour markets wages, agriculture land, inequality poverty unemployment, transition post apartheid, methods data sources
Citation key mayet2010

Argument

The thesis measures employer non-compliance with South Africa's post-1999 sectoral minimum wage determinations. It applies Kanbur's index of violation (an FGT-style measure) to the September 2001 and 2007 Labour Force Surveys, with each worker's statutory minimum mapped by sector, occupation, area and hours. Violation is very high: 55% of covered workers in 2001 and 45% in 2007 were paid below the minimum. Probit, OLS and quantile regressions show that violation depends on individual, firm and contractual, sectoral and spatial factors. Labour inspector density lowers the probability and depth of violation, and local unemployment raises both, with unemployment having the largest effect. It also finds that minima are high relative to median wages (the Kaitz index), and that high Kaitz values go with more violation.

Evidence and method

Statistics South Africa September 2001 and 2007 Labour Force Surveys, the 2000 Income and Expenditure Survey (used for geographic mapping), Department of Labour Employment Conditions Commission sectoral determinations, Department of Labour data on labour inspectors by province (2009), and Municipal Demarcation Board area data. Samples are about 6,900 covered workers for the probit and about 3,000 violated workers for the OLS and quantile regressions.

Findings

  • Overall violation fell between 2001 and 2007 but remained very high. (p. 30)

    The estimates in the last row of Table 1 show that in South Africa V0 was 55% in 2001 and 45% in 2007.

  • Violation varies widely by sector, with Security worst and Civil Engineering lowest in 2007. (p. 30)

    This ranged from a low of 9 % in the Civil engineering sector to a high of 67 % among Security workers.

  • Farm worker violation fell sharply after the 2002 determination but stayed very high. (p. 31)

    The figures for Farm workers in turn yield a decline in violation from 78% to 55%.

  • Minimum wages are set high relative to the median wage. (p. 36)

    the K1 Kaitz ratio for South Africa, estimated as the ratio of the mean minimum wage to the overall median wage, was 0.70, and subsided to 0.61 in 2007.

  • Labour inspector density significantly reduces the probability of violation. (p. 47)

    In all three specifications, namely specifications II, III, and IV, the results from the inspector density variable are negative and statistically significant at the 1% level.

  • Local unemployment raises the probability of violation, consistent with surplus labour accepting sub-minimum pay. (p. 48)

    The coefficient for the unemployment rate in the district council was positive and highly significant (1% level of significance) in all the specifications where included

  • Small and medium firms are more likely to violate than large firms. (p. 48)

    Employees in small and medium-sized enterprises (less than 20 workers) were more likely to be violated than those in large firms with 50 employees or more.

  • Race and gender affect whether a worker is violated, but not how deep the violation is. (p. 51)

    while race and gender play a significant role in determining whether an individual is violated or not, they are irrelevant in determining the extent and degree of this violation

  • More inspectors also reduce the depth of violation. (p. 56)

    a 1% increase in the density of labour inspectors significantly lowers the depth of violation by 1.2% for the individual.

  • The effect of unemployment on depth of violation is large and grows across the violation distribution. (p. 64)

    A 1% rise in the unemployment rate results in an increase in the depth of violation of between 4.4% (at the lowest percentile), to 33.7 % (at the 85th percentile).

  • The sector with the highest violation also has the highest Kaitz values, which suggests that high floors combined with weak enforcement drive non-compliance. (p. 67)

    A noteworthy example is the Security sector which recorded the highest measures for violation in 2007, and ironically also the highest Kaitz values.