The South African National 
Minimum Wage

An analytical look into the effects on macroeconomic variables and income inequality

This essay was originally written in 2015 as my entry into the 2015 Nedbank Budget Speech Competition where I made the Top 20 in South Africa.

This essay will serve as an investigation into how the implementation of a national minimum wage will affect macroeconomic variables, such as employment, GDP growth, and income inequality as well as finding the link between the macroeconomic variables and inequality. Focusing on empirical evidence from various studies conducted in both developed and emerging economies, I will seek to find whether the traditional consensus has any validity in predicting the changes to the above-mentioned variables and whether the results from previous studies and investigations provide a clear indication as to the correct course of action for the South African Government.

Traditional View on the Effects of a Minimum Wage:
A minimum wage is described as a wage fixed by legal authority or by contract as the least that may be paid either to employed persons generally or to a particular category of employed persons. In a report by the Development Policy Research Unit of South Africa (2008) they outline that the objective of a minimum wage is to redistribute incomes and lift low-income workers out of poverty by raising wages of workers.

Some of the advantages of a minimum wage listed in Borrington and Simpson (2014) are that it will encourage more workers to seek out employment which will lead to a decrease in the shortage of labour. It will also lead to an increase in the wages of low-income workers with the aim that they spend more money and stimulate growth in the economy. A major disadvantage of a minimum wage, from a macroeconomic perspective, is that it can cause inflationary pressures within an economy as a result of firms increasing their prices to compensate them for the higher wages they will be forced to pay.

The effects that a minimum wage has at an industry level, assuming competitive markets, is that the imposition of minimum or floor wage into the labour market will cause the quantity of labour demanded by firms to fall commensurately with an increase in the supply of workers entering the industry. The result is a surplus of workers who are effectively unemployed at the minimum wage. According to the standard labour supply-labour demand framework, set out in Blanchard (2014), the unemployed are willingly unemployed as the workers would rather be unemployed and wait for employment opportunities that pay the minimum wage.
For that reason, I believe that it would be of more practical use to employ a wage setting (WS)-price setting (PS) relationship to analyse the macroeconomic effects of a national minimum wage.

The WS-PS model differs from the standard labour supply-labour demand model in some important elements. In the standard model wages are taken as given at the number of worker willing to work at that rate, whereas in in the WS-PS model the wages that correspond to a given level of employment in the WS relation is derived from the bargaining process between workers and firms or unilateral wage setting on the part of firms, if they are assumed to have monopolistic or monopsonistic market power. The WS-PS model makes allowances for the fact that the degree of competition within the goods market has an effect on the PS relation whereas the standard labour model assumes perfectly competitive markets (Blanchard, et al., 2014).

In the model, Blanchard sets out the price-setting function as a horizontal line as a function of markup. He also includes an upward sloping wage-setting function which relates employment to real wages as well as the labour supply, assumed to be fixed at some point. The point of intersection of wage-setting and price-setting schedules is called the natural rate of employment. The area to the left of the natural rate of employment is the total number of the population employed in the economy and the area to the right indicates the total number unemployed. (See figure 1)

A minimum wage will lead to an increase in firms cost of production. The firms will respond by increasing their markup in order to keep their profits unchanged. The increase in the markup leads the PS function to shift downwards along the WS function leading to an increase in the level of unemployment and an equivalent decrease in employment (See figure 2).

It is known that for every natural rate of employment there is a corresponding natural rate of output as described in the Keynesian model of aggregate demand (AD)-aggregate supply (AS). In the model, the WS-PS relations are captured in the aggregate supply function. Following on from the process above, there is a direct relationship between the decrease in employment and a simultaneous shrinkage in national income (GDP) along with a rise in the price level, assuming a closed economy to ignore the effects on international trade and financial flows. This rise in the price level leads to inflationary pressures that will be felt by consumers in terms of rising CPI.

So, therefore, what we see is that all else equal the implementation of a national minimum wage should lead to a decrease in employment and national income or GDP, and then through the multiplier effect, we should notice a rise in consumption leading to growth in employment and GDP in the second round.

Empirical Evidence of the Macroeconomic Effects of a Minimum Wage:
In Brazil, a National Minimum Wage was implemented which saw the minimum wage increased in real terms by 81% between the years 2003 through 2010. In that time span, approximately 17 million jobs were created leading to increased incomes which stimulated GDP growth in Brazil through an increase in domestic consumption from -0.5% in 2003, to 9.1% in 2010. During the seven-year period, Brazil witnessed unemployment fall to 6.1% from 11.6% (Nkabinde, n.d.). Loman (2014) said that the results in Brazil did not follow widely held economic theory that a minimum wage should lead to an increase in unemployment.

There have been many other studies conducted by prominent economists into the employment effects of a minimum wage. The famous study conducted by Card and Krueger (1994) into the employment effects of a minimum wage in the fast-food industry in New Jersey and Pennsylvania found no relationship between a rise in the minimum wage and a reduction in employment.

A review of research into minimum wages by Neumark and Wascher (2006) found that a minimum wage has only a moderate effect on employment. They concluded that a minimum wage does not lead to the large scale unemployment that the traditional model suggests. Nielsen (2012), echoed a similar result in that a rise in the minimum wage leads stimulates the income of the lowest wage workers with only negligible effects on employment.
These contradictory results have led to many economists to argue for the implementation of a minimum wage as a means to boost growth and as Schmitt (2013) reports, “the minimum wage has little or no discernible effect on the employment prospects of low-wage workers.”

There are, however, some economists who still believe in the traditional model like Meer and West (2015) who wrote that the minimum wage profoundly affects employment through a reduction in the rate of long-run job growth.

Income Inequality, the South African Gini Coefficient, and its relationship to GDP Growth:
Income inequality is a major issue in this day in age especially in countries such as South Africa and Brazil who have a history of extremely high unemployment and low levels of education and service delivery. A measure of income distribution as calculated by Statistics South Africa is the Gini coefficient. It specifically excludes the impact that government policies like access to free housing and basic services have on low-income households (Bosch, et al., 2010).

The Gini coefficient ranges between 0 and 1, with 0 demonstrating perfect equality and 1 demonstrating perfect inequality. 
A common measure of the Gini coefficient is the Lorenz curve. The Gini coefficient is calculated as the area between the Lorenz curve and a hypothetical line of perfect equality expressed as a percentage. (See figure 3)

In his book, The Price of Inequality, Joseph Stiglitz (2012) says, commonly, countries that are more equal have Gini coefficients of 0.3 or below, whereas countries that are perceived as the most unequal societies have Gini coefficients or 0.5 or above. The latest Gini coefficient measure for South Africa taken in 2011 was 0.65 (Worldbank, 2014) which puts us on the side of “most unequal” according to Stiglitz (2012).

When compared to the Gini coefficients of other countries, South Africa ranks among the worst in the world along with Brazil in a survey conducted by OECD (2013). (See figure 4)

From this evidence, we can see that South Africa and Brazil rank similarly in terms of income inequality as measured by the Gini coefficient. However, various authors dispute the Gini coefficient as an accurate measurement of inequality. Bosch and others (2014) say that the South African Gini coefficient is measured in terms of per capita income which frequently results in them being higher when compared to other countries because they are weighted by household size and then multiplied by the household weight. They make reference to the fact that different countries and institutions employ various methodologies and standards when calculating Gini coefficients which may yield substantial differences between the Gini coefficients for South Africa and those of its peers.

Stiglitz (2012) concedes that the Gini coefficient is “an imperfect measure of inequality”, but goes on to say that it is useful for international comparisons.
The relationship between GDP growth and income inequality has economists divided. There are some that argue that income inequality can boost economic growth due to increased innovation and entrepreneurship resulting from inequality. On the other hand, another group of economists believe that inequality is harmful to economic growth in that is hinders the development of human capital, as well as leading to political and economic instability which will discourage investment, all else equal. (Hong, et al., 2014)

Empirical Evidence of the Effect that a Minimum Wage has on Inequality and its Relationship with GDP Growth:
Studies into the effect that the minimum wage has on inequality has been explored in numerous academic articles. Golan and others (2001) used regression analysis and found that the minimum wage was statistically significant, and while holding other variables and factors constant, that an increase in the minimum wage leads to a reduction in welfare. The authors concluded that other studies unsuccessfully controlled for macroeconomic and demographic variables, which they believe may have contributed to the ambiguous results about the minimum wage’s effects on inequality.

A similar conclusion was drawn by Neumark and Wascher (1997) in that the authors found that minimum wages reduce both efficiency and equity, reporting that generally, the minimum wage led to an increase in the income inequality amongst low-income earning families and that it decreased the proportion of families earning incomes that put them just above the poverty line.

Card and Krueger (1995) explored the effects of a federal minimum wage rise in the United States from 1989 to 1991 and found that it significantly compressed income distribution.
Another study conducted by Neumark, Schweitzer, and Wascher (1999) led to a conclusion the unemployment caused by a minimum wage increase is focused amongst low-earning worker’s families. These results proposed that while some families are aided by a minimum wage it generally leads to an increase in the percentage of families below the poverty line.

When looking at Brazil’s National Minimum Wage policy Loman (2014) wrote that Brazil was able to reduce its traditionally high levels of inequality and poverty through social policies such as an increased minimum wage.
Ostry, Berg, and Tsangarides (2014) conducted a comprehensive analysis of the relationship between inequality, redistribution, growth focusing on medium and long term growth as well the length of the growth periods. The authors found that the narrowing of inequality had been strong determinate of the rate of medium-term growth as well as the duration of the growth period.

As can be concluded from the above evidence, there is no validity in the traditional consensus about the effects that a minimum wage has on economic variables such as employment, GDP growth, and income inequality. Most authors reported mixed results in terms of an employment effect as well as ambiguous changes in income distribution arising from different measurements and sample groups. There also appears to be an indirect relationship between inequality and GDP growth as reported in one study.
Isolating Brazil’s national minimum wage results, we see how they contradicted the traditional consensus, policymakers in South Africa should not rush to point out that all national minimum wage policies will have the same effects. The results did show a positive employment effect, however, in terms of income inequality, the results say that we should not expect that this policy will lift people out of poverty.

With a fragile economy as a result of the weakening rand, widening trade deficit, and energy crisis, South African policymakers will need to focus a lot of their time and resources on the implementation process of the national minimum wage, if the country is to have any hopes of reducing its inequality and setting the economy on the road to recovery.

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