Tables

The Appendix tables provide additional information on each African economy’s macroeconomic and operating environments

Download tables

Methodology

RMB Investment Attractiveness Rankings – The methodology

We believe that the decision to invest is typically based on two key considerations: economic activity (specifically market size and growth) and the business environment. These factors form the basis of our methodology.

The structural DNA of the RMB Investment Attractiveness Rankings

Source: RMB Global Markets

Economic activity

The economic activity variable aims to measure the economic performance of a country by assessing both the size and forecasted growth rates.

Market size: The market size of each economy is converted to US dollars to ensure that there is a common unit of measurement between all the countries. Rather than multiplying the respective sizes of each economy by their prevailing exchange rate, we standardised the variables by using the purchasing power parity method. This ensures that the unit measures the real rather than nominal value of an economy.

A score ranging from zero to ten is allocated to the market size variable, using the ranking method. Market sizes can differ significantly, especially after national accounts are rebased, resulting in several outliers. However, the ranking method isn’t affected by outliers and allows us to track the country rankings over time.

Growth: The real growth variable measures the average growth rate in the size of the economy over a five-year forecast period after adjusting for inflation. However, this unit can be quite volatile from year to year, subjecting the economic activity variable to large fluctuations. In order to overcome some of the challenges, we standardised the variable using the z-score method to identify exceptional GDP growth by some countries and extreme outliers that could distort our scoring process. We then used the rescaling method to widen the range of the observed growth rates lying within a small interval, as most of the rates were clustered around the mean.

The rescaled variables are multiplied by ten, and then allocated to the respective countries.

The overall economic activity score is then calculated by simply aggregating the two variables, with the best possible score being ten and the worst score being zero.

Operating environment methodology

The operating environment scoring is arguably the most subjective. Our estimate uses the same four sources as in previous years: the World Bank’s Doing Business Report, the Heritage Foundation’s Index of Economic Freedom, the World Economic Forum’s (WEF) Global Competitiveness Report and Transparency International’s Corruption Perceptions Index, which are surveyed at different times of the year. We have used these four as they are highly regarded, have long histories, and contain a mix of hard and subjective data, but acknowledge that there are many other indices that could be used.

It could also be argued that some indices overlap or that certain indices should be given higher weights. However, we have found that most assessments of business operating conditions tend to be highly correlated: countries where corruption is high will also have prohibitive bureaucracy, less economic freedom and be perceived as being less competitive. Quite simply, it would probably not make much difference which indices are included or with which weights. Individual indices will have their own idiosyncrasies, but taking an equally weighted average of four indices helps smooth individual anomalies. To combine the indices, we adjusted each of their scales so that the best possible score is ten and the worst possible score is zero.

Aggregate score

The composite investment attractiveness score is an equally weighted, linearly aggregated index, comprising the operating and economic activity variables. Equal weights are allocated to both variables. A linear aggregation method is used because all the composites use the same measurement unit. It therefore rewards variables based on their weights, unlike geometric aggregation, which rewards variables with high scores. This means that countries with low scores would benefit much more from the linear aggregation method than geometric aggregation.

While we believe our methodology is strong, it only provides a general overview of the attractiveness of each country rather than a specific rating that will be relevant to each company or each sector. We still highly recommend that individual companies look at the factors that are relevant to their particular businesses.

Alternative rankings

The alternative index rankings use a linear aggregation method, with unequal weights. Since the alternative ranking caters for investors who may place greater emphasis on the economic environment or the operating climate when making their investment decision, the weights are changed accordingly to reflect this. A weight of 60% is allocated to the emphasised variable, while a 40% weight is allocated to the other variable.

To emphasise the importance of political rights and civil liberties, we have incorporated the scorings of Freedom House’s Freedom in the World Index to our operating environment scoring by weighting them equally against the standardised scores of the existing global surveys. We then aggregate this five-factor operating environment index with the economic activity score to augment our main methodology with socio-political risk.

Retail rankings

In Chapter 3, we calculate a retail ranking score, where we take into consideration GDP per capita, population size and growth, average annual growth forecast (2019-2024), forecasted average annual urbanisation growth (2020-2025), domestic competition and household final consumption.

We recognize that not all these variables carry the same level of importance for retail companies when they are considering investing in various African markets. Therefore, we give a 25% weighting to domestic competition and household final consumption each and give an equal 10% weight to the remaining macroeconomic variables.

We first rank all countries across each of the seven variables. We then aggregate these individual rankings to arrive at a score. Using these aggregate scores, we rank the 38 countries for which we have data.

Sources and other information

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RMB Global Markets Contacts

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Celeste Fauconnier celeste.fauconnier@rmb.co.za 
Nema Ramkhelawan-Bhana nema.ramkhelawan-bhana@rmb.co.za
Neville Mandimika neville.mandimika@rmb.co.za 

Contributing authors
Chris Mabanga chris.mabanga@rmb.co.za
Daniel Kavishe dkavishe@fnbnamibia.com.na
Editorial and data analysis
Nonjabulo Dladla nonjabulo.dladla@rmb.co.za
Mandy Brennan mandy.brennan@rmb.co.za
Giselle Willcox giselle.willcox@rmb.co.za 
Claudell Van Aswegen claudell.vanaswegen@rmb.co.za

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