metadata: authors: 0: author: Dadam,Vincent
1: author: Hanusch,Marek
2: author: Viegi,Nicola
count: South Africa
docna: 0: docna: Why South Africa Is Cheap for the Rich and
            Expensive for the Poor : Reconsidering the Balassa-Samuelson Effect
docty: Policy Research Working Paper
subtopic: Construction Industry,Common Carriers Industry,Food & Beverage Industry,Plastics & Rubber Industry,Business Cycles and Stabilization Policies,General Manufacturing,Pulp & Paper Industry,Textiles, Apparel & Leather Industry,Mining & Extractive Industry (Non-Energy),International Trade and Trade Rules,Food Security
teratopic: Industry,International Economics and Trade,Agriculture,Macroeconomics and Economic Growth
abstracts: cdata!: This paper investigates cross-sectoral
            productivity differentials in South African industry and
            their distributional consequences. The analysis shows that
            typically, traded sectors have experienced low productivity
            growth over the past decade, while skill intensive service
            sectors have had significant productivity growth. This is
            the inverse of the traditional Balassa-Samuelson sectoral
            transformation hypothesis, where high wages in
            high-productivity traded sectors increase wages throughout
            the economy, thus increasing prices on non-traded goods and
            revaluing the country's real exchange rate. Instead,
            the higher productivity of non-traded sectors experienced in
            South Africa induces a devaluation of the real exchange rate
            and a contraction of the traded sectors. The results of the
            estimation show evidence of this "inverse"
            Balassa-Samuelson effect for agriculture and manufacturing
            and in particular mining. This "inverse"
            Balassa-Samuelson effect has important distributional
            consequences: the high-productivity sectors are associated
            with cheaper goods and services for wealthy households. This
            in turn burdens poor households, which are more dependent on
            traded goods, with higher prices, which are a consequence of
            low productivity and high markups.
geo_reg_key: 517195,517191
repnme: repnme: Why South Africa Is Cheap for the Rich and
            Expensive for the Poor : Reconsidering the Balassa-Samuelson Effect
display_title: Why South Africa Is Cheap for the
            Rich and Expensive for the Poor : Reconsidering the
            Balassa-Samuelson Effect
listing_relative_url: /research/2019/07/31265291/south-africa-cheap-rich-expensive-poor-reconsidering-balassa-samuelson-effect
topicv3: Agriculture and Food Security m1326205 435,Mining Services m1326410 1701,Manufacturing Sectors m1326521 1281,Trade m1326924 698,Mining Sector m1327113 554
publishtoextweb_dt: 2019-07-22T00:00:00Z
historic_topic: Industry,International Economics and Trade,Agriculture,Macroeconomics and Economic Growth
no_of_pages: 29
author_keys: 0: author_key: 1045860
1: author_key: 1576242
model_extractions: Policy Research Working Paper 8942 Why South Africa Is Cheap for the Rich and Expensive for the Poor Reconsidering the Balassa-Samuelson Effect _Vincent Dadam Marek Hanusch Nicola Viegi_ Macroeconomics, Trade and Investment Global Practice July 2019
Policy Research Working Paper 8942

# **Abstract**

This paper investigates cross-sectoral productivity differentials in South African industry and their distributional consequences. The analysis shows that typically, traded sectors have experienced low productivity growth over the past decade, while skill intensive service sectors have had significant productivity growth. This is the inverse of the traditional Balassa-Samuelson sectoral transformation hypothesis, where high wages in high-productivity traded sectors increase wages throughout the economy, thus increasing prices on non-traded goods and revaluing the country’s real exchange rate. Instead, the higher productivity of non-traded sectors experienced in South Africa induces a devaluation of the real exchange rate and a contraction of the traded sectors. The results of the estimation show evidence of this “inverse” Balassa-Samuelson effect for agriculture and manufacturing and in particular mining. This “inverse” Balassa-Samuelson effect has important distributional consequences: the high-productivity sectors are associated with cheaper goods and services for wealthy households. This in turn burdens poor households, which are more dependent on traded goods, with higher prices, which are a consequence of low productivity and high markups.

This paper is a product of the Macroeconomics, Trade and Investment Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at mhanusch@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
Why South Africa Is Cheap for the Rich and Expensive for the Poor: Reconsidering the Balassa-Samuelson Effect<sup>_∗_</sup> Vincent Dadam,<sup>_†_</sup> Marek Hanusch,<sup>_‡_</sup> Nicola Viegi<sup>_§_</sup>

> _∗_ The authors would like to thank Sebastien Dessus, Ha Nguyen, and Max Rudibert Steinbach for valuable comments.

> _†_ University of Pretoria email:dadamvince@yahoo.fr

> _‡_ World Bank, email:mhanusch@worldbank.org

> _§_ University of Pretoria and ERSA, email: nicola.viegi@up.ac.za
# **Key Points**

- **South Africa’s real exchange rate depreciation is large and persistent.** The persistent deviation from the law of one price is only partly explained by a traditional BalassaSamuelson effect. Nevertheless, the Balassa-Samuelson analysis directs attention toward differentials in sectoral productivity.

- **Productivity in the traded sector is inversely related to the degree of openness of the economy** . The intuition of modern trade theory is that countries with high barriers to entry in international markets and low competitiveness in the domestic economy will have larger deviations from the law of one price. South Africa shows all the characteristics of a relatively closed economy, with high barriers to entry in international markets, and quite protected internal sectors.

- **Low productivity growth in the manufacturing and mining sectors is coupled with growing productivity in some service sectors, especially the ones with high skill intensity** . The picture of traded goods stagnation is matched by dynamism in some service sectors. The increase in productivity in some service sectors makes the services relatively cheaper than goods in less productive sectors. This is reflected by sectoral differences in rates.

- **The Balassa-Samuelson logic is reversed.** The increase in productivity in the service sector has a spillover effect into the goods sector in the form of an increase in wages: this logic is reflected in the increase in the unit labor cost in the manufacturing sector being largely decoupled from productivity increases.

- **Firms in the traded sectors reduce employment or require protection from external competition.** Firms in the manufacturing sector will respond to the increase in labor costs either by reducing their labor force or by demanding higher levels of protection against competition from more productive external competitors. The negative spiral of low productivity and low competitiveness is thus self-reinforcing, with the increasingly monopolistic nature

2
of the traded goods sector reducing productivity, thus limiting access to international markets.

- **The process is reinforced when considering sectoral skill intensity.** The service sectors that have experienced greater productivity growth are also the most skill-intensive. Skills are therefore rewarded by increasing productivity and increasing the skill premium. Low-skilled workers in the high-productivity service sectors benefit as well with an increase in wages. The manufacturing sector will instead shrink and become more inward oriented.

- **Intersectoral productivity differences have distributional consequences.** Inflation will be lower in the sectors that have a larger weight in higher income groups while the poor will be burdened by the price of low productivity and high mark-ups in the inward-looking production sectors.

- **Increasing productivity in the traded sector is a necessary condition for a rebalancing of the economy.** To achieve inclusive growth the South African economy requires significant growth in traded sector productivity. This can be achieved by reducing the barriers to entry of South African firms in the international value chain (by promoting integration in international value chains, supporting exports to reduce the “gravity” effect on trade costs, and by reducing barriers to entry in the domestic market).

- **Reducing the skill constraint would drive a reduction of the skill premium and rebalance intersectoral distribution of skills.** This is a priority not only to improve the productivity dynamic in the country, but also to deal with long-term distributional issues. Skills are the most important commodity to import and in which to invest.

3
# **1 Introduction**

It is well known that the difference in price levels across countries correlates with the difference in income levels. The main explanation for this observation, illustrated in Figure (1), is generally found in the Balassa-Samuelson effect (Balassa (1964), Samuelson (1964)) that links the differences in income levels with differences in productivity in the traded sector.

<!-- Start of picture text --> South Africa<br>0 .5 1 1.5<br>Relative Real Per Capita Income Relative to the US<br>2<br>1.5<br>1<br>.5<br>Relative Price Level (PPP/XR) to the US<br>0<br><!-- End of picture text --> Figure 1: Price Level and Income Level (source; Penn World Tables) In its original formulation, it states that a country will experience an appreciation of the equilibrium real exchange rate (i.e. an increase of home prices relative to foreign prices) when an increase in productivity in the _traded_ sector leads to an increase in local wages in _any_ (i.e. traded and non-traded) sector. The generalized increase in wages induces an increase in prices in non-traded sectors and thus an increase in the general level of prices.

The Balassa-Samuelson analysis then offers a guidance to understanding the process of sectoral changes during episodes of growth convergence in a small open economy, that is benefiting from productivity spillovers from global trade integration (Cravino and Haltenhof, 2017).

4
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is a reflection of complex inter-sectoral dynamics. High transport costs and other barriers to entry reduce the productivity dynamics in the traded sectors. Domestic firms operate for the domestic market with low productivity and high mark-ups, affecting the distribution of rents between capital and labor (Fedderke et al., 2018). Few sectors, especially the service sectors, finance and insurance, have seen positive productivity dynamics, driven by technological innovation and liberalization after the 1990’s.

The biggest effect of this increase in productivity of the service sectors is reflected in a change of the relative prices and an increase of the relative size, with resources moving from the lowproductivity to the high-productivity sectors. This reinforced the relative weakness of low-productivity sectors, which find it even more difficult to enter international markets.

The logic of the Balassa-Samuelson effect is reversed: technical and efficiency innovations in nontraded sectors increase their productivity, thus putting upward pressure on economy-wide wages. This increase in wages has spillover effects in the traded sector, which is a price taker on the world market. The increase in labor costs induces a contraction of the use of labor in the traded sector and possibly an overall contraction of the sector. The real exchange rate remains depreciated; more resources are invested in the non-traded sectors; and non-traded goods become relatively less expensive than the internationally determined prices of tradeable goods. This dynamic has sectoral and distributional effects that are the focus of this paper.

Th relative price changes have important distributional effects in a very unequal society. The main productivity gains are made in the sectors servicing mainly the top end of the income distribution, making the economy relatively cheaper for them and more expensive for the poor. A rebalancing of productivity dynamics is important not only for growth but also from the perspective of equity.

The paper is organized as follows: in the next section we review the sectoral productivity dynamic in South Africa and link it to recent literature on the endogeneity of the Balassa-Samuelson effect when considering trade costs and barriers to entry in the traded sectors (Ghironi and Melitz, 2005). Section 3 presents a simple empirical analysis to show the relationship between relative sectoral productivity dynamics and the relative size of the sectors. Finally in section 4 we assess 6
the distributional consequences of the observed productivity dynamics. In particular, we look at the relationship between the real exchange rate and inequality in the country and how productivity growth in the traded sector might also require social rebalancing.

# **2 Balassa-Samuelson in South Africa: Some preliminary observations**

The traditional Balassa-Samuelson analysis is based on an exogenous definition of the traded and non-traded sectors often identified as goods and services. The problem is that a strict definition of traded and non-traded sectors conflicts with a simple observation: in all sectors, the proportion of firms that do not trade internationally represents the vast majority of the firms, with maybe the exception of the mining sector. Consider, for example, the following table from (Edwards et al., 2018) The table shows that almost 70% of all manufacturing firms in South Africa do not trade. This is possible if we consider a world with heterogeneous firms, with different levels of productivity, producing heterogeneous products which do not have perfect substitutes. Less productive firms can survive because they are partly protected from external competition. This observation is not specific to South Africa: the literature shows that in the United States only 21% of manufacturing plants export and there is a lot of switching from traded to non-traded goods in the same plants.

Moreover, in principle all sectors have traded components. The following graph shows the proportion of sectoral product exported for primary, secondary, and tertiary sectors in South Africa in

||2009|2010|2011|2012|2013|Average|
|---|---|---|---|---|---|---|
|Exporter only|6.2|7.2|7.1|7.1|7.2|7.0|
|Exporter and importer|16.3|17.7|17.2|17.9|15.9|17.0|
|Importer only|9.2|8.4|8.2|7.7|7.7|8.2|
|Non-trader|68.4|66.6|67.5|67.2|69.2|67.8|
|Total|100.0|100.0|100.0|100.0|100.0|100.0|

Table 1: Manufacturing Firm Engagement in International Trade, (Share of firms, %)(source (Edwards et al., 2018)) 7
<!-- Start of picture text --> 50<br>47.7226<br>45<br>40<br>35<br>32.9596<br>30<br>SM 25<br>20<br>15)<br>10.9112<br>10<br>6.5172<br>5<br>2.4687<br>3 =0.9771 = mz1.6286<br>Primary Manufacturing Construction Trade, catering and Transport, storage and Finance and insurance Community, social and<br>accommodation communication personal services<br>services<br><!-- End of picture text -->
the country should decrease relative to the rest of the world in order to keep labor employed. This will cause the relative prices of non-traded goods in any sector to reduce, thus depreciating the real exchange rate.

In normal circumstances, the lower relative labor cost should increase the export profitability of home firms, thus reducing the profit cut-off point that makes entering the export market convenient for home firms (only the most productive firms export). This is constrained by what determines the fixed cost of entry in the export market: the higher the cost of entry (both of national firms in the export market and foreign firms in the domestic), intended as physical, regulatory and economic (volatility and market structure), the larger the distance between national and international prices, as the economy will have a much larger proportion of less productive non-trading firms.

The logic of Balassa-Samuelson is maintained at the level of each individual sector: assume that labor has the same price across sectors, but the productivity of firms is differentiated: trading firms are more productive as a necessary condition to access the international market as they have to pay the cost of entry in the international market; non-trading firms are less productive but survive because they do not have to pay the fixed cost of entry in the international market. Wages will be higher the larger is the number of high productive firms in the market. The least productive firms will cover the increase in wages, due to the high productive firms, by increasing prices, thus replicating the Balassa-Samuelson inflation effect of productivity catch up.

The most important implication of the Balassa-Samuelson effect in the South African context is that the difference in prices across countries reflects differences in productivity levels, as they are reflected in differences in wage levels. The first observation is therefore that the South African real exchange rate is depreciated because of dismal productivity performances that have characterized this economy over the past 20 years.

In practice, the Balassa-Samuelson reasoning focuses our attention on the role of productivity in the export sectors as the source of productivity growth and wage increases. Either in the traditional perfect competitive framework or in the most recent models of monopolistic competition we need to first consider the sectoral composition of South Africa’s traded sector. As far as trading in goods is concerned, the following graph from the Atlas of Economic Complexity shows the composition 9
<!-- Start of picture text -->
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<!-- Start of picture text --> 110.00<br>105.00 -<br>100.00<br>95.00<br>90.00 -<br>85.00<br>80.00<br>75.00 ~<br>70.00<br>65.00<br>650.00, ppgp<br>1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016<br>=——Primary (SIC 1-2) = Secondary (SIC 3-5) <=Tertiary (SIC 6 - 9)<br><!-- End of picture text -->
<!-- Start of picture text --> 120.00<br>110.00 —<br>—_— 2 a<br>100.00 -— #.<br>7 —7~<br>90.00 a= 7<br>og 7<br>—- %<br>80.00 - es<br>60.0070.00 -— LZ<br>50.00 ~ : r —<br>1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016<br>=— Trade(SIC6) —=Trasport(SIC7)= <=<=Finance (SIC8) ——Community (SIC 9)<br><!-- End of picture text -->
<!-- Start of picture text --> 2505<br>230<br>"|<br>190<br>170<br>150<br>110=<br>00 | Price index of services relative to GDP deflator<br>70 | T T (2010=100)T T T T t T T T T T T T T T TM—T T T T T T 1<br>FPFSPS OSTM& & FPPHPS&S PPO& SOW SSPMYAV NTM& SO© SPNPAvo BPOD FPPHr OHbe PPLPo BP— oP© PPSY OTMid PPPMP© oh6 © PFWwW os FW”© &@ SaO GrAY grm® ©<br><!-- End of picture text -->
to be perfectly mobile across sectors. Regarding labor, this assumption has important implications in terms of the evolution of wages. In particular, perfect cross-sectoral mobility implies that in the long run wages between sectors are equal. In the alternative scenario, the incentive is that employees will change sectors until growing labor supply in the sector where earnings are high, combined with decreasing labor supply in the other sector would level the wages in the economy. We assume for simplicity perfect competition across sectors and that produce goods and services using a Cobb-Douglas production function with constant returns to scale. Thus, production in the traded and non-traded sector is done using the following two production function, one for each sector: To investigate how divergent productivity dynamics between traded and non-traded sector explains for cross-sectoral inflation differential, we begin with the following two production functions, one for each sector: where _Yt,T_ and _Yt,N_ are the output produced in the trade and non-traded sectors, _At,T_ and _At,N_ are the total factor productivity in the two sectors, _Lt,T_ and _Lt,N_ denotes the labor input, _Kt,T_ and _Kt,N_ are the capital inputs, _αT_ and _αN_ are labor elasticities of output.Firms in each sector face a standard profit maximization problem: in which _Pt,T_ and _Pt,N_ denote the level of price in each sector, _wt,T_ and _wt,N_ denote wages in the traded and non-traded sector respectively, and _rt_ is the cost of capital.

Computing the first order conditions, we have: 14
<!-- Start of picture text --> ()<br>(—)<br>JQ<br>_ (—)<br>(—)<br>/<br>(—) (—)<br><!-- End of picture text -->
sectoral relationship between price differential and productivity differential. We estimate 11 using South African sectoral data. In particular, we assume that agriculture, mining and manufacturing are typically traded sectors, broadly guided by the observations in Figure 3. The rest are treated as non-traded sectors as listed in Table (2).

|**Tradable sector**|**Non-tradable sector**|
|---|---|
|Agriculture|Electricity, gas and water|
|Mining|Construction|
|Manufacturing|Trade, catering and accommodation ser-<br>vices|
||Transport, storage and communication|
||Finance, insurance, real estate and busi-|
||ness services|
||Community, social and personal services|
||sectors|

Table 2: Traded and non-traded sectors Prices are defined as indices of output prices. labor productivity on the other hand is calculated as the ratio of total output (which also includes intermediary output) to total employment per sector. Our data covers the period 1993 to 2017 and were collected from Quantec Research.

As a baseline scenario we begin by conducting a fixed effects estimation of equation (11). The results are reported in Table (3) The results are broadly in line with expectations. We find a positive relationship between sectoral price differential and the difference in productivity between traded and non-traded sectors. In particular, it confirms the intuition that an increase in productivity in non-traded sectors reduces prices of the non-traded relative to traded sectors, thus devaluing the country real exchange rate.

The baseline specification in Table (3) can be improved statistically by taking into consideration the data generating process in the panel, which shows indication of non stationarity in the series. We therefore use the Pool Mean Estimator of Pesaran et al. (1999) to re-estimate the relationship in equation (11) while considering both the long run relationship and the adjustment dynamics. The results are summarized in Table (4).

16
||(1)|(2)|(3)|
|---|---|---|---|
||Agriculture|Manufacturing|Mining|
||_pt,N −pt,Agr_|_pt,N −pt,Man_|_pt,N −pt,Min_|
|_at,Agr −at,N_|0.268***<br>(11.36)|||
|_at,Man −at,N_||0.445***<br>(8.64)||
|_at,Min −at,N_|||1.463***<br>(14.87)|
|Constant|0.134***|-0.161***|-0.257***|
||(8.82)|(-10.23)|(-9.35)|
|_N_|150|150|150|

_t_ statistics in parentheses * _p <_ 0 _._ 05, ** _p <_ 0 _._ 01, *** _p <_ 0 _._ 001 Table 3: Fixed Effect Estimates The statistical analysis confirms the presence of a Baumol-Bowen effect for all traded sectors, with robust long run coefficients in line with the baseline regression in table 3 and a strong short adjustment mechanism for agriculture and manufacturing. The price effect of productivity differential is particularly strong in the case of mining which is also the sector with the highest proportion of exported output, between 70% and 80% of mined value. This suggests that the relationship between sectoral productivity and relative prices at the basis of the Balassa-Samuelson effect is particularly evident for the sector that is more clearly a traded sector and a price taker in the international market. The strong relationship between productivity differential and price differential in mining is obtained by excluding from the panel the electricity sector which is an important input in the mining industry. The electricity sector in South Africa is a public monopoly with price controls; it has had exponential increases in prices in a short period to cover large infrastructure expenditure and debt servicing, but which were not justified by a change in productivity, thus distorting the underlying relationship.

For the manufacturing and agriculture sector, the relationship between the productivity differential and price differential is less pronounced quantitatively, probably reflecting the imperfect 17
||(1)|(2)|(3)|
|---|---|---|---|
||Agriculture|Manufacturing|Mining|
||_pt,N −pt,Agr_|_pt,N −pt,Man_|_pt,N −pt,Min_|
|Long Run||||
|_aAgr −aN_|0.180***<br>(8.17)|||
|_aMan −aN_||0.119**<br>(2.83)||
|_aMin −aN_|||1.162***<br>(3.45)|
|Short Run||||
|Error Correction|-0.489***|-0.403***|-0.0986***|
||(-7.01)|(-6.28)|(-4.45)|
|∆_aAgr −aN_|0.115***<br>(4.86)|||
|∆_aMan −aN_||0.0763<br>(0.71)||
|∆_aMin −aN_|||0.399*<br>(2.39)|
|Constant|0.0294**<br>(2.70)|-0.0274*<br>(-2.38)|-0.0553*<br>(-2.30)|
|_N_|120|120|120|

_t_ statistics in parentheses * _p <_ 0 _._ 05, ** _p <_ 0 _._ 01, *** _p <_ 0 _._ 001 Table 4: Pool Mean Regression Estimation classification of these two sectors as traded sectors. In the manufacturing sector, there is evidence of a long-term relationship, evidence of adjustment dynamics but an insignificant short term relationship. Although the short-run coefficient estimate is of the expected sign, it remains statistically insignificant, independently of the specification. In the long run we find a significant but relatively weaker than in agriculture. In particular, an increase of 1 percentage point in the difference between traded and manufacturing sector labor productivity raises the price differential between non-traded and manufacturing sector by 0.11 percentage point in the long run. For comparison, Konopczak and Tor ́oj (2010) using manufacturing sector as traded sector and similar non-traded sectors for 18
Poland, find a coefficient of 0.2 using a Fully Modified Ordinary Least Square (FMLOS) and 0.19 using a Dynamic Ordinary Least Square (DOLS).

The finance sector has a particular place in the debate about South Africa economic transformation (Rodrik (2008), Fedderke (2014)). Its size is disproportionate relative to the size of the economy and it has experienced a significant wave of innovation and integration in the international capital markets after 1994. It is therefore instructive to isolate the effect of increasing productivity of the financial sector on the relative prices. The results are displayed in Table (5).

||(1)|(2)|(3)|
|---|---|---|---|
||Agriculture|Manufacturing|Mining|
||_pt,N −pt,Agr_|_pt,N −pt,Man_|_pt,N −pt,Min_|
|∆_aAgr −aF in_|0.177***<br>(3.81)|||
|∆_aMan −aF in_||0.426***<br>(5.26)||
|∆_aMin −aF in_|||1.560***<br>(10.03)|
|Constant|0.0675*|-0.175***|-0.343***|
||(2.40)|(-6.40)|(-6.97)|
|_N_|25|25|25|

_t_ statistics in parentheses * _p <_ 0 _._ 05, ** _p <_ 0 _._ 01, *** _p <_ 0 _._ 001 Table 5: Sectoral Effect of Finance Productivity The results are qualitatively in line with the general results, but the effects are quantitatively much larger for manufacturing and mining. For manufacturing, an increase in the difference in productivity of 1 % will increase the price differential between manufacturing and finance by almost half of a per cent. For mining, the change in relative prices is even stronger, with the change in productivity differential increasing the price differential by more than one to one.

19
# **4 Real Exchange Rate and Inequality**

The relationship between differences in productivity and difference in prices illustrated above can have strong distributional consequences in a very unequal society, where consumption baskets a very heterogeneous across income groups. Inequality is the defining characteristic of the South African economy. Whatever measure of inequality is used, South Africa comes always at the top of any inequality index, which is a reflection of both its history and of the structural changes after the end of apartheid.

Although South Africa’s real exchange rate is in line with comparable countries, the economy is considered expensive for the majority of the population. This is often the main explanation for strong downward rigidity of wages even in the presence of an extraordinarily high unemployment rate. The affordability of the South African economy, defined as the ability of the majority of the population to access goods and services, given the prevalent income, is a combination of relative price distribution and the level of income inequality. The South African economy is very unequal and the dynamic of productivity, as will be illustrated in the next sections, increases the burden on the poorest part of the population, who are more dependent on good produced in the less productive part of the economy.

Following Leibbrandt et al. (2016), we investigate the expenditure categories that have promoted a gap between the inflation rates of poor and non-poor households. The methodology is explained in detail in the appendix. Focusing on the period 2009-2017 and using the 2014/2015 Living Conditions of Households in South Africa, we assess price changes from the CPI basket of goods and services to which poor households were overexposed. These are typically items from the CPI basket for which inflation rates for poor households exceeded those of richer households during the period considered. Our results are consistent with the findings of Leibbrandt et al. (2016) while using a different dataset and a different and more recent time period, demonstrating that this evidence is a constant distributional issues over the last 20 years. Figure 8 plots the average annual percentage change in price relative to the ratio of weights of the bottom 4 deciles relative to the top 6 deciles. The horizontal line in the graph is the average inflation rate during the period considered, while 20
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consumption basket of upper income households (in the left-high quadrant of figure 8) are water, primary and secondary education and to a lesser extent, medical services.

These findings are in line with Leibbrandt et al. (2016) which further emphasizes that the living conditions of poor households have not significantly improved, given that our study focuses on a more recent sample period. Furthermore, this analysis shows that while the South African economy is relatively cheap, the cost of goods and services used by the poorest part of the population is relatively high and is increasing. This difference is made more dramatic if we consider the highly skewed distribution of income and the very low level of participation in the labor market.

The final characteristic of the South African economy that needs to be considered is the very high skill premium driven by the skill intensity of the public sector and part of the service sector, in particular finance. Because of the skill intensity in the service sector, and the relatively closed nature of the traded sector, the productivity in the service sector is growing faster than the productivity in the traded sector.

If this is the case, this would reduce the prices of services relative to the prices of goods by increasing wages in the traded sectors by more than the sector increase in productivity. This would not only reinforce the depreciation of the real exchange rate, but also it would penalize households with a consumption basket with a higher content of traded goods.

# **5 Conclusion**

The paper has discussed the role of sectoral productivity differential in explaining internal price dynamics and external real exchange rate evaluation. The increased productivity differential between non-traded and traded sectors in favor of the non-traded sector reinforces inequalities in the country, increases wage differentials between skilled and unskilled workers and moves resources away from low-skilled manufacturing jobs towards high-skilled service jobs.

Therefore, achieving inclusive growth in South Africa requires an increase in productivity and wages in the traded sectors. Bringing down barriers to entry, integrating South African firms into regional and international value chains, and promoting competition among firms to boost their 22
competitiveness are likely to reach that goal. Additionally, the South African labor market displays a significant shortage of skilled workers. Addressing this issue will essentially boost productivity dynamics across sectors while at the same time reducing the skill premium and rebalancing the distribution of skills across sectors.

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