A Discussion on the Economy of South Africa: Past, Present, and Future

By: Brian Williams


Good economic news has recently come out of South Africa, as the country experienced 3.1% GDP growth in the fourth quarter of 2017, and is now projected by the World Bank to exceed an earlier projection and have GDP growth reach 1.4% in 2018. While this is certainly something to take pride in, South Africa has some lofty goals for their future economic growth, as the government’s ambition is to achieve a 5% growth rate in the coming years. This post will analyze the historical growth of South Africa to gain a better understanding of future growth prospects for the Rainbow Nation.

Government Policy Analysis

In order to sustain and even improve growth, Paul Noumba Um, South Africa’s World Bank Director, acknowledged that GDP growth in his country is being challenged by unemployment, inequality, and poverty.[1] The GINI Coefficient, a measure of the inequality of a country with values between 0 and 100%, is very high in South Africa relative to other countries at 63. This means that a small percentage of the population owns a large proportion of the wealth.[2]

GINI index
The GINI Index of South Africa and important countries

     The South African Department of Trade and Industry highlights that companies will have a large pool of both semiskilled and unskilled workers to potentially employ as a major draw for investment, which would reduce the high inequality prevalent in the country, as well as help grow the economy with more people working.[3] To reduce poverty and close the inequality gap, Julie Schaffner’s textbook on Development Economics describes government policies that take into account the financial constraints the poor are faced with, such as bringing markets into remote areas whose inhabitants are commonly poor due to their large proximity away from financial centers, along with policies that “explicitly create new assets owned or used by the poor,” as the most effective. These policies perform multiple tasks, as they promote a reduction in inequality along with promoting growth in the economy with equal success to policies targeting those with average income.[4]

 BRICS Analysis

To get a better picture of South Africa’s future, it’s past economic progress can be a useful guide. BRICS is an acronym used to group the countries of Brazil, Russia, India, China, and South Africa together. First established by Goldman Sachs economist Jim O’Neil in 2001 to identify strong, growing economies, BRICS has advanced into “a new and promising political-diplomatic entity, far beyond the original concept tailored for the financial markets,” with Summits between member countries held annually and group decisions made often.[5] In his paper Divergence, Big Time, Lant Pritchett studied the average growth rates of 17 currently high-income countries from three different time periods. Divergence in this case is defined as the state when the GDP per capita of wealthy countries increases quicker than the GDP per capita of other countries, creating a greater divide between the two groups.[6] The table below presents a similar study to Pritchett’s, conducted with data for the BRICS countries over three different time periods.

GDP Growth Rate.png
Growth Rates of BRICS countries over 3 different time periods

One observation from this analysis is how South Africa has fallen from having the highest GDP per capita to having the fourth highest of the BRICS countries. Couple that with their consistently low average growth rates relative to the other countries (1.80, -0.467, and 1.586), and it becomes a signal that South Africa is diverging away from countries like Brazil, China, and Russia in terms of economic growth per capita.

OECD Analysis

The economies of the BRICS countries are often thought of as less developed relative to the advanced economies of the world, which are typically considered to be the OECD countries. Pritchett defines the OECD countries as European countries, their offshoots, and Japan. In his work, Pritchett estimated “that from 1870 to 1990, the ratio of per capita incomes between the richest and the poorest countries increased by roughly a factor of five,” which is a signal that divergence had occurred between the “developed” OECD countries and the other “less developed” countries.[7] By comparing the adjusted income per capita of South Africa and the OECD member countries, as shown in graph below, it becomes apparent that the divergence Pritchett discussed has occurred here as well.

Income per capita divergence.png
Income per Capita Divergence between OECD countries and South Africa

Numerically, the World Bank estimates that in 1971, the adjusted income per capita in South Africa was 728.245, while for OECD member countries it was 2,547,569. Had convergence occurred between these two countries, it would be expected that this gap of approximately 350% would have been reduced by today as South Africa’s economy would have grown faster than the OECD member’s economies, but this is not what happened. In fact, the current adjusted income per capita of South Africa is estimated to be 4,258.973, while this statistic for OECD member countries is now approximately 30,785,193, over 700% greater than South Africa’s. This exceeds Pritchett’s estimation and shows a high degree of divergence between South Africa and the developed OECD countries.[8]

Future Growth Potential

Even with the positive news of growth for the South African economy, the government still believes that higher growth rates can be achieved. Taking a step back, it may be ideal for the South African Government to decide if this goal is actually feasible and sustainable. One calculation that can help determine a countries future growth is based off of the observations from a graph included in the 1997 paper On the Evolution of the World Income Distribution penned by Charles Jones. Jones compared a countries 1960 GDP per worker to that of the United States and found that for most countries, those that had a GDP per worker greater than 15% of the United State’s converged, or grew towards the same value, whereas those with a GDP per worker less than that figure saw divergence.[9] For our experiment, we will compare South Africa’s 2016 GDP per worker to that of the United States use that to determine if convergence or divergence will occur in the future. No assumptions were made about the countries in Jones paper, as he simply observed a result from the raw data. The table below describes this relationship between South Africa and the Untied States, the reference country.

Jones analysis.png
Analyzing South Africa’s potential for future growth

Dividing 13614.28556 by 114512.8955 yields the approximation that South Africa’s ratio is 11.889% that of the United States. This is below the 15% threshold Jones observed for divergence, so if his findings hold than South Africa should be expected to further diverge away from the United States. As a result, with this evaluation, South Africa will not achieve their target goal of 5% growth, as they will be expected to grow slower than the United States, a country that averages around 2% growth annually.


[1] Winning, Alexander. “World Bank Raises South Africa 2018 Growth Forecast.”

[2] GINI Index-South Africa. Raw data. The World Bank.

[3] “Why Invest in South Africa.” Trade, Exports & Investment.

[4] Schaffner, Julie. Development Economics: Theory, Empirical Research, and Policy Analysis.

[5] Rachid, Biatriz. “Information about BRICS.”

[6] Pritchett, Lant. “Divergence, Big Time.”

[7] Pritchett, Lant. “Divergence, Big Time.”

[8] Income per Capita-South Africa and OECD countries. Raw data. The World Bank.

[9] Jones, Chad. “On the Evolution of the World Income Distribution.”

Source Articles:




Violent Crime and Risk Aversion

A Look at the paper by Ryan et al. on the impact of violent crime on risk aversion with evidence from the Mexican Drug War

By Ken Varghese


With the election of President Calderon in 2006, Mexico experienced a brief decrease in crime followed by a much more significant rise in violent crime. President Calderon’s efforts in the new War on Drugs removed the heads of the prominent Mexican cartels, however, this only led to more chaos. Groups fractured into smaller cells to fill in the vacancies left by the original cartels. The number of cartels in Mexico rose from six in 2006 to sixteen in 2011 and violence spread over the country as a result. The nature of crime in Mexico also changed as gangs sought more ways to find funds, including methods that impacted the citizenry more directly, such as extortion, kidnapping and auto theft. Citizens easily became targets for more brutal crime such as executions if they refused to cooperate.

In their paper “Impact of Violent Crime on Risk Aversion: Evidence from the Mexican Drug War,” Ryan Brown, Verónica Montalva, Duncan Thomas and Andrea Velásquez, analyze data from this period to gain insight into the ways exposure to violent local crime can effect risk preferences in individuals. The authors believe that, given the increasing brutality of crimes in Mexico and the heightened visibility of violent crime due to media coverage, the population living in affected areas would have been significantly psychologically impacted. They state that this may have a number of possible outcomes such as changing an individual’s perception of how risky their environment and future are or leading individuals to make risk averse decisions as a result of fear of victimization.

The Data

The authors used the Mexican Family Life Survey (MxFLS) to obtain data about local populations. The baseline survey collected data from a period in 2002 and included 8,440 households and 35,600 individuals in 16 states throughout the country. The first follow up survey (MxFLS2) in 2005 and 2006 occurred during a period of relatively stable levels of violent crime, and the second follow-up survey (MxFLS3) in 2009 and 2010 occurred after a major rise in violent crime. Using these three surveys allowed the authors to examine the impacts of different levels of violence on the same individuals over an extended period of time. A trait of the MxFLS that makes this analysis possible, is its low levels of attrition (loss of participants), with 89% of the original respondents being contacted again for the first follow up and 87% for the second follow up. The surveys allowed for the gauging of risk preferences by having respondents decide between sure outcomes and gambles that resulted in either an attractive or unattractive outcome. The differences between the expected values of the gambles and the values of the sure options were used to rank the level of risk aversion. This individual-level data from the MxFLS is combined with monthly municipality-specific homicide data from the National Institute of Statistics and Geography (INEGI) in order to measure how risk preferences vary as the level of local violent crime changes over time. The monthly homicide rate (the primary data used from INEGI) for the period studied can be seen in figure 1 below.

Figure 1 blog

Brown et al. 2017

Analysis and Results

The authors’ primary calculations suggest that an increase of 1 homicide per 10,000 people resulted in a 5% increase in risk aversion in MxFLS3 (compared to the average per capita expenditure from MxFLS2). Table 1 shows how the overall risk aversion distribution changed from MxFLS2 to MxFLS3. Surprisingly, the authors also found that the risk attitudes of households in the lowest quartile of per capita expenditure are not effected by homicide rate like those in other quartiles. This could be because of a variety of reasons, such as the possibility that the change in violence was greater in high income neighborhoods than in low income neighborhoods. The authors also state that it is possible (if fear as a result of violence is what drives the risk preference change) that the worst off individuals may already be past the point where increased local violence no longer significantly impacts their risk preferences. It is also possible that the used measure is noisier for these individuals.

table 1 blog

Brown et al. 2017

It also noteworthy that the influence of violence crimes significantly reduced the earnings of self-employed men and the labor market participation of self-employed women. This finding led the authors to explore whether the primary fear impacting risk preference was financial in nature. In looking at the data, they found that the risk attitudes of the self-employed are not more strongly impacted by local violence than other participants. However, further analysis revealed that risk aversion was more than double the size among participants in the population who were fearful of victimization during the escalation of violence. This provides evidence suggesting that local violent crime is impacting risk attitudes through the fear of victimization rather than increased financial hardship.

How Does This Relate to Development Economics?

As the authors state, there is evidence that increased risk aversion is negatively correlated with involvement in riskier but more profitable investment decisions, occupational choices and migration. This suggests that increased levels of risk aversion as a result of exposure to violent crime can negatively impact household wealth accumulation and can hurt a country’s economic development in the long-term. As such, level of exposure to violent crime and statistics such as local homicide rates should be seen as closely tied to inequality and economic growth. The impact on household wealth accumulation and on willingness to take riskier but more profitable financial decisions can deepen inequality and diminish growth in the long term. Similarly, the authors also mention that the violent crimes impacted self-owned businesses negatively. This is somewhat relevant to the field of microfinance, as some programs find effectiveness primarily in enabling individuals to have more choice by allowing them the option of self-employment. If self-employment becomes less profitable as a result of violent crime, these forms of microfinance will be less successful in affected communities.


Brown, Ryan, Verónica Montalva, Duncan Thomas and Andrea Velásquezv (2017). Impact of Violent Crime on Risk Aversion: Evidence from the Mexican Drug War, NBER Working Paper No. 23181 (2017): retrieved from http://nber.org/papers/w23181

Schaffner, Julie (2014). Development Economics: Theory, Empirical Research, and Policy Analysis. Hoboken, NJ: Wiley.


Credit Markets in Bulgaria: Meaning and Consequences of Greater Debt for Fewer People

A post about the discrepancies of the credit market in Bulgaria – specifically about the misuse of microcredit for consumption instead of investment.
By: Angelina Shtereva

In the beginning of March 2017, the chairwoman of the Association of Collection Agencies in Bulgaria (AKAB) Rayna Mitkova announced that over the last year, fewer Bulgarians have borrowed, but loan amounts have increased by 22% on average. The article “Fewer Bulgarians Become Indebted, Debt Amount Grows” states that the decrease in borrowers may be a result of the improving economic conditions, however the average debtor is still a 30-year-old male with a temporary or a seasonal job, who borrows for consumption of luxury goods such as mobile phones, laptops, and TVs, according to the article. So, what are the implications of borrowing to satisfy the need for impulse purchases? Should this type of borrowing be automatically attached to the label of a “risky borrower”?

Is Saving Possible and is Working Worth It?

To answer these questions and understand the situation a little bit better, we must explore the socio-economic environment in which the average Bulgarian lives. As mentioned in “Industry in Bulgaria Has One of the Highest Profit Rates in Europe”, a Bulgarian pharmacist receives EUR 536 on average, while a Spanish counterpart gets about EUR 3480. Both countries are members of the European Union but choices for the Bulgarian are limited for financial reasons, even though the output supplied is higher in Bulgaria, according to the article.

With this tight budget constraint, the Bulgarian has very little disposable income left over after paying taxes and other expenses like rent/mortgage, car loans, food, and bills. This is why purchasing laptops and mobile phones is considered a luxury in Bulgaria and the average person needs to borrow in order to obtain what would be considered normal goods in other member states of the European Union. Looking at the general form of the consumer’s utility function in the two-period model, we notice something else.

u(c) + β(u(c’))

The discount factor, β, must be very close to zero because of impulse purchases of consumption goods in the current period. This indicates that Bulgarians on average value consumption today more than consumption tomorrow. The reasons for this preference may range from the uncertainty of the job market to a negative outlook for the future and mistrust of the government as seen in the protests of 2012 (Ivancheva). This may also be the reason why employment decreased by 10% between 2012 and 2016. The substitution effect leads us to think that the opportunity cost of employment is greater than that of leisure, meaning the same level of utility can be achieved by staying at home and not working. Without the right incentives from the government and the free markets, the Bulgarian consumer is caught in a vicious cycle of not being able to save due to an inadequate ratio of wages to prices, leading to more impulse borrowing for consumption. Since the consumer has to repay any borrowing today in the future period, financial stability decreases as time goes on.

Macroeconomic Effects on Microcredit

The situation is exacerbated in some areas by the consequences of the Great Recession in 2008. While 9 of the 28 regions in Bulgaria have reached and surpassed their GDP levels of 2008, all of these regions include big metropolitan areas where economic downturns have always been overcome more easily than in the rest of the country. According to “Bulgaria Overcomes Consequences of Economic Crisis Due To Fast Growth of 9 Regions” the wealth gap among different regions in Bulgaria is growing and the same trend is seen between wealth in Bulgaria and in Europe on average. Education and the labor market are hit especially hard by this disparity. With this in mind it is easier to understand why this macroeconomic situation forces more Bulgarians to move abroad, leading to a negative population growth and a stagnant economy in 19 out of 28 regions.

One of these 19 unsuccessful regions is the Northwestern region in Bulgaria, which is also the poorest one in Europe. Its largest city, Russe, also has the lowest amount of borrowers in the country. Could this be due to lack of education about the potential benefits of borrowing or due to the absence of microcredit in this more rural region? It is understandable that poorer people who knowingly borrow for consumption, often try to stay as far away from loans as possible. These people have to repay what they borrow with high interest rates, decreasing their financial freedom. On the other hand, lenders sometimes face adverse selection in these regions when giving out loans – they do not know if the borrower in front of them is “safe” or “risky”, leading to uncertainty of repayment. However, because some regions are knowingly poorer than others, meaning investment will be low regardless of number of loans given out, the lenders spike up the interest rates because of the high likelihood of borrowing for consumption and because of the generally non-entrepreneurial culture in Bulgaria. In this sense, almost all borrowers are seen as risky in some areas, which probably discourages the safe types from borrowing at least to some level.

Will There be an End to Risky Borrowing for Consumption?

So, overall can we really label all borrowing for consumption as “risky”? Could different approaches like group lending increase production and well-being in rural areas? The truth is that the asymmetries of the Bulgarian credit market are simply extensions of flaws in other areas. Based on my own knowledge of the political atmosphere in Bulgaria, I can safely say that the government rarely incentivizes domestic production, especially in the poorer regions. So even with the existence of microcredit, people might still be unwilling to take up the opportunity to invest in a small business or in agriculture.

However, even with so many roadblocks, I believe that at least the mindset of some Bulgarians is changing. There is a light at the end of the tunnel for those who have the option to borrow and the education and willingness to do so. According to “Fewer Bulgarians Become Indebted…” highly educated people have increased their borrowing over the past year. While the article does not go into detail as to why that might be, it may be safe to assume that at least a small fraction of these educated borrowers will invest the money in small or medium enterprises, giving a much needed boost to output and GDP.

Works Cited

“Bulgaria Overcomes Consequences of Economic Crisis Due To Fast Growth of 9 Regions.”Novinite.com – Sofia News Agency. Novinite JSC, 29 Nov. 2016. Web. 07 Apr. 2017.

“Fewer Bulgarians Become Indebted, Debt Amount Grows.” Novinite.com – Sofia News Agency. Novinite JSC, 14 Mar. 2017. Web. 07 Apr. 2017.

“Industry in Bulgaria Has One of the Highest Profit Rates in Europe.” Novinite.com – Sofia News Agency. Novinite JSC, 30 Mar. 2017. Web. 07 Apr. 2017.

Ivancheva, Mariya. “The Bulgarian Wave of Protests, 2012-2013.” CritCom. Council for European Studies, 7 Oct. 2013. Web. 11 Apr. 2017.

Insurance – How Uganda Will Quadruple Its Coffee Industry

An analysis explaining how an innovative style of insurance policy can lead to farmers’ confidence in coffee to rise.


The government of Uganda is promoting growth of its coffee industry by nearly 400%. Aiming to increase production of coffee from four million bags to twenty million bags, the government is investing in irrigation and subsidizing coffee seedlings to increase interest in growing coffee, a crop often seen risky by farmers because of the unpredictable nature of rainfall in Uganda. NUCAFE, the National Union of Coffee Agribusiness and Farm Enterprises, is promoting crop insurance as a tool to increase interest in growing coffee. Justus Lyatuu of The Observer, writes of NUCAFE’s foray into crop insurance.

Coffee is extremely reliant on moisture and rainfall to successfully grow and mature to a  crop fit for harvest. A slight decrease in rainfall could cause mass coffee crop failure, leading farmers to stray from growing the risky crop. Nearly 65% of crop losses in Uganda are due to drought, and the farmers’ inability to accurately predict weather and effectively mitigate the risks associated with weather leads farmers to devote their resources to growing less risky and less valuable crops.

NUCAFE is encouraging farmers to grow coffee through the offering of crop insurance, which will function to reduce the risk carried by farmers from investing in the production of coffee. Farmers will pay 5% of their expected yield of harvest in the beginning of the grow, and in the event of crop failure due to weather events such as drought, the insurance policies will pay out to farmers near the expected yield of the harvest. Not only does this promote the growth of coffee by mitigating many of the risks of doing so, NUCAFE also will offer education and access to weather information from NASA to allow farmers to more accurately predict weather and mitigate losses from drought.

Index Insurance, How Can It Promote Increased Confidence in Risky Crops?

Index insurance is an emerging form of insurance beginning to become available to those in the agriculture industry, that offers policies to farmers based on weather indexes. Farmers will pay premiums to the insurer, who will in turn, pay out to the farmer in the event of weather conditions suitable for crop failure are met. For example, if the agreed upon conditions for the weather index insurance policy state that if below 15 inches of rain falls in the grow period, then the insurance policy will pay out to the farmer.

Pre-existing forms of crop insurance were structured so the farmer pays premiums to the insurer, and if the crop fails, then the insurance policy pays out near equal to the crop loss.

Index insurance has many advantages over standard crop insurance policies. Because index insurance uses publicly available data to determine if conditions for crop failure are met, transaction costs for index insurance are significantly lower than standard insurance, where claims often result in the insurer needing to inspect the farm themselves, increasing transaction costs. Lowered transaction costs are essential for financial products, and create suitable conditions for private insurers to exist in the marketplace as well as allowing small farmers to afford insurance. When transaction costs are minimized, the cost associated with the financial product is as close as possible to the cost to the insurer of paying out to policyholders. Not only does this increase potential profit margins for insurers, it keeps the cost of insurance low for farmers. Index insurance’s low transaction costs mean the product’s adoption might be possible without governmental and NGO financial support, which otherwise would be required to supplement insurers operating at a loss.

Index insurance protects insurers from moral hazard. With standard crop insurance, the policy may provide a better outcome to the farmer if the crop fails, tempting the farmer to intentionally sabotage their crop. They may have a policy that pays out more than the expected yield of their harvest, or they may be able to make the same amount of money with a failed harvest without having to put in effort to grow the crops. Because index insurance pays out when uncontrollable weather conditions are met, farmers don’t benefit from a failed harvest, it actually still serves the farmers best when they always strive for a successful harvest, since payouts aren’t determined with the outcome of the crop, but instead based on growing conditions.

Because index insurance determines if payout conditions are met based on weather data, it isn’t always effective in protecting the farmer from risk. If the farmer’s crop fails even when there has been 15 inches of rainfall in the grow season, the farmer has a failed crop and no payout from his insurance policy. If somehow the farmer’s crop succeeds when there has been less than 15 inches of rainfall in the grow season, he receives a payout even when his crop succeeded. So, while index insurance protects insurers from moral hazard, it often can result in ineffective risk mitigation for the farmers.

Index Insurance in Uganda

With the implementation of weather index insurance in Uganda for coffee farmers, coffee farmers can invest their resources to growing coffee without having to bear the risk of crop failure. Policies aimed to protect farmers from drought would pay out to farmers when drought conditions have been met. Since drought is the leading cause of crop loss in coffee agriculture, insurance policies that pay out when drought conditions occur mitigates the risk of low rainfall to coffee farmers, the largest drawback to growing coffee instead of safer crops.

Works Cited

Lyatuu, Justus. “Coffee Farmers Urged to Embrace Insurance.” The Observer. N.p., 10 Mar. 2017. Web. 11 Apr. 2017. <http://www.observer.ug/business/51694-coffee-farmers-urged-to-embrace-insurance.html&gt;.

Hellmuth M.E., Osgood D.E., Hess U., Moorhead A. and Bhojwani H. (eds) 2009. Index insurance and climate risk: Prospects for development and disaster management. Climate and Society No. 2. International Research. Institute for Climate and Society (IRI), Columbia University, New York, USA.

Leiva, Oscar. Hands of María Del Socorro López López. Digital image. Coffeelands. Catholic Relief Services, 9 Nov. 2015. Web. 17 Apr. 2017.