Which is really the bigger economy between Nigeria and South Africa?

Which is really the bigger economy between Nigeria and South Africa?

 

The Da Vinci Institute, South Africa

 

Basheer Oshodi

October, 2016

oshodibasheer@gamil.com

 

Which is really the bigger economy between Nigeria and South Africa?

Nigeria rebased her GDP in April 2014 and overtook South Africa. In August 2016 South Africa overtook Nigeria and regained the position of Africa’s largest economy. Nigeria’s GDP before the 2014 rebasing covered three major sectors – agriculture, crude oil and gas, and trade which constituted 85% of the GDP. Now, these only covered 54% while new sectors received significant share of the GDP. They include telecommunications, real estate, manufacturing, construction, and entertainment. A visit to Johannesburg or any city in South Africa demonstrate superior infrastructure when compared to Nigeria. More so, South Africa’s manufacturing sector seem much more organized than that of Nigeria, at least from the surface. This study seeks to examine development indicators between 1986 and 2014 for both countries and truly examine their competitive advantages. More specifically the variables include GDP; GDP deflector; GNI; agriculture value added (annual % growth); industry value added (annual % growth); trade (% of GDP); telecommunication investment with private participation (current US$); manufacturing value added (annual % growth); GDP deflator (base year varies by country); total unemployment (% of total labour force); FDI; inflation, consumer price (annual %); official exchange rate (LCU per US$ period average; and international tourism, expenditure (current US$).

Ordinary least squares and analysis of variance is used as estimation techniques while the performance of the results of models is evaluated using statistics: t-test, p-value, F Stat, the coefficient of multiple determination and Durbin-Watson. This research is expected to create a path for other methodologies in determining preferred ways to measure southern economies with consideration to social ontology.

Keywords: GDP, competitive advantage, regression analysis

JEL Classification: Political Economy

  • Introduction

Just as South Africa joined the BRIC countries, Nigeria was recognized first as the next 11, and then as a MINT country. Large population became a strength for Nigeria only where productivity rises, or else, demographics can be a burden (O’Neill 2013:36). While Nigeria suffers from migrant brain drain, South Africa was exposed to terminal brain drain caused by HIV-AIDS (Mazrui 2006:285). And, while Nigeria still attributes low growth and development to colonization, South Africa blames the apartheid regime for poor education and unemployment among its black population. South Africa however looks and feels much more developed than Nigeria in terms of overall organization, sound infrastructure and matured financial system. So when Nigeria’s GDP overtook that of South Africa in 2014 one was sure such gap may be somewhat artificial. As Nigeria’s GDP per capita is $2,294 that of South Africa’s is $10,960 meaning living standard is much better in South Africa. Of what use then is Nigeria’s high GDP and GNI? Can development indicators really determine the developmental prospects of southern economies? How come then that overall economic growth and development is slow when compared with other BRIC and MINT countries and indeed very far off from the Asian Newly Industrializing Countries (ANICs) such as Hong Kong, Singapore, Taiwan and South Korea, including Malaysia? It is these burning issues that spurred this research, first by asking which the bigger economy between Nigeria and South Africa is by running a regression of one dependent variable and several independent variables over a 29 year period. And, then, by deducing the economy with greater prospect on the one hand, and qualitatively examining the real path necessary to achieving real development and industrialization.

2.0     Nigeria’s colonialism, neopatrimonial governance and uncoordinated growth

The British brought together 500 tribes and languages, indeed the most set of diverse cultures under one country called Nigeria in 1914. Prior to this, the country was traced to prehistoric settlers living around the eastern part as early as 11,000 BC while several ancient African civilizations formed base in the region. Islam reached the region from the north in the 11 century and British forces captured Lagos in the west of the country in 1951 after several slave trade expeditions by the Portuguese since 1472. Lagos at that time was the main centre from which the Portuguese exploited other African coast. Nigeria became a British protectorate in 1901, amalgamated the north and south through a common treasury in 1914 and gave independence to the country in 1960. Kohli (2004:291-292) observed that “the British did nothing of the sort and instead ran Nigeria on the cheap”. He argued further that the British adopted an indirect rule approach that resulted in poorly formed state which shaped patrimonial, personalistic and localized pattern of rule resulting in failed centralize authority. Thus, soon after Nigeria became a republic in 1963 the military junta launched their first bloody coup d’etat in 1966 and then the eastern people formed the Republic of Biafra in 1967 leading to a three year civil war. Tribes, religious groups, political cronies and entrepreneurs pursued self-interest and adopted predatory state capture approach to ruin the politico-economic infrastructure of the country. Institutionalized corruption, eagerness to bite from the national cake and scramble for natural resources impacted negatively on state enterprises, institutions and even the private sector. However, population grew from 42 million in 1960 to 178 million in 2014 and it is expected to hit 440 million by 2050. Out of sub-Saharan Africa’s 90 gigawatts of power generation capacity, Nigeria only has 3 gigawatts (African Progress Report, 2015:16) despite being the largest producer of oil in Africa and 6th in the world. When Nigeria’s GDP hit USD568b in 2014 after the rebasing one can only wonder such economic growth without proper coordination of state, market, people and value (Oshodi 2014:206). This growth is certainly not inclusive since more than 120 million people are in poverty (NBS 2012). Nigeria is expected to become the 20th largest economy by 2020 and the 7th top growth market in 2050 (O’Neill 2013; Oshodi 2015). This research opines that the country is dragging development growth and development potential due to gross coordination gaps. Kohli (2004:21) compared the GDP of Nigeria, Brazil, Korea and India in 1960 and found them on same level. While South Korea galloped far ahead of others, Nigeria remained much behind India and Brazil. Where then is South Africa?

3.0     Radical apartheid and the renaissance of development in South Africa

More recently, ‘homo naledi’ was found 30 miles northwest of Johannesburg and the region is now termed the ‘Cradle of Humankind’. The fossil of these human-like species is evidence that they inhibited the land for more than 100,000 years. In 1488 the Portuguese explored the coastline of South Africa while trying to find their way to the Far East under the leadership of Bartolomeu Dias. In 1497 Da Gama proceeded with this expedition, gave the name Natal to the coastal region and later found his way to India. On the other hand the Zulu people of South Africa are port of the Nguni tribe and formed a potent state in 1818 under Shaka and united the fragmented black socio-political tribes into an empire. Gold and diamonds were discovered in the 19th century which led the Boer settlers and the British to fight over this buoyant mining industry. The British defeated the Anglo-Boer in the 1899-1902 war which led to the creation of South Africa as a British territory – thus unifying the four separate British colonies of Cape Colony, Natal Colony, Transvaal Colony and Orange River Colony through the South African Ace of 1909. Like fifteen other African countries, South Africa gained her independence in 1961. Meanwhile, the white Afrikaners had always dominated South African politics since 1948 and nursed their political agenda called ‘apartheid’ meaning separateness. Indeed a deepening radical cleavage of Euro-South Africans on the one side and Black, Indian and other South Africans of colour on the other side (Mazrui 2006:28). The assassination of Prime Minister Hendrik F. Verwoerd got Prime Minister Balthahazar J. Vorster into power who continued the apartheid regime. In December 1966 the United Nations tagged apartheid as ‘crime against humanity’. While 91 member states voted in favour of this declaration in 1973, South Africa, Portugal, the United States and United Kingdom voted against it. Apartheid continued to showcase consistent brutality of black South Africans and behold Nelson Mandela was released from prison in 1990 after 27 years. He later became president in 1997 under the African National Congress (ANC) and reconciled the nation. Decades after the collapse of apartheid, over half of the South African population still live in poverty while socio-economic progress had since slowed down. Poverty, unemployment and inequality became a normal situation while violent protest and xenophobia became a way of life. Though South Africa is seen as the most developed country in Africa, the reality however is that the institutional infrastructure laid down by the British and the Afrikaner is eroding rather too quickly.

4.0     Research methodology and model specifications

The methodology of the study emphasizes the aims and objectives; research questions; the choice of the research design and strategies; data requirement and sources; the nature and types of data collected; the data processing; and the parameters to be estimated. The section also specifies the model, vital concepts and terms used were equally defined and described for the purpose of further illustrating the phenomena under study. The research design adopted for this work is the experimental research design since it combines the theoretical consideration with empirical observation.

4.1     Research aim and objectives

The primary aim of this study is to determine the bigger economy between Nigeria and South Africa by examining some development indicators over a 29-year period. The specific objectives are:

  • To determine the country with greater developmental prospect.
  • To give an insight as to how both economies can achieve real development and industrialization.

4.2     Research questions       

This study seeks to achieve the research aim by answering the following questions:

  1. How do we determine the country with greater developmental prospect?
  2. How can both economies achieve real development and industrialization?

4.3     Data requirement and sources

The study covered the economic growth measurement in Nigeria and South Africa. The analysis was conducted using time series data for 1986 – 2015 which is a period of thirty (30) years. The choice of 1986 may have been due to the fact that the structural adjustment programme was heavily promoted at that period. Data for 2015 were hardly adequately available at this time which led to the usage of just 29 years which ranges from 1986-2014. The data were mainly obtained from the publications of the Central Bank of Nigeria (CBN), World Bank, and United Nation.

4.4     Parameters estimated

The empirical study used a simulation approach to investigate the bigger economic in the case study countries. The E-view is preferred because it enables one to correct the serial correlation in the data. The non-stationary variables were lagged before running the Ordinary Least Square. The performance of the results of models is evaluated using the following statistics: t-test, p-value, F Stat, the coefficient of multiple determination and Durbin-Watson.

4.5     Methods of data analysis

The research makes use of the Ordinary Least Square of estimation of method alongside descriptive statistics measures through the use of trend analysis in order to reflect the movement of the variable in question. The regression is run through the use of Economic View (E-View) software computer package (version 7.0) which regressed the dependent variables on the independent variable.    

4.7     Model specification

To evaluate the economic growth over the period, the following regression is being used: Y = αi, + βGDPi + εi, where Y is the log real GPD per capita and ε is error term. For the purpose of this research, the above model specification is adopted and built upon. The research analyses economic growth within the context of GDP = Gross Domestic Product-(Real Gross Domestic Product); AGRI= Agriculture value added, EXG= Foreign exchange rate, FDI= Foreign Direct Investment, GDD= GDP Deflator, GNI= Gross National Income, IFR = Interest Rate, IND= Industry value added, INT= International tourism, MVD= Manufacturing value added, Telecom Investment private participation, TRD= Trade % of GDP, UMP= Unemployment (% of total labor force) EEP = Education Expenditure, HEP = Health Expenditure and EXD = External debt stocks, total (DOD, current US$).

The model could therefore be specified as follows in the form:

GDP=f(AGRI, EXG, FDI, GDD, GNI, IFR, IND, INT, MVD, TCI, TRD, UMP, EEP, HEP, EXD)………………………………………………………………………………………….1

GDP=a0+a1AGRIC+a2EXG+a3FDI+a4GDD+a5GNI+a6IFR+a7IND+a8INT+a9MVD+a10TCI+a11TRD+a12UMP+ a13 EEP + a14 HEP + a15 EXD……………………………………………………………………….…..2

Where GDP = Gross Domestic Product-(Real Gross Domestic Product); AGRI= Agriculture value added, EXG= Foreign exchange rate, FDI= Foreign Direct Investment, GDD= GDP deflator, GNI= Gross national income, IFR = Interest Rate, IND= Industry value added, INT= International tourism, MVD= Manufacturing value added, Telecom Investment private participation, TRD= Trade % of GDP, UMP= Unemployment (% of total labor force) EEP = Education Expenditure, HEP = Health Expenditure and EXD = External debt stocks, total (DOD, current US$) = a0, a1, a2, a3, a4, a5, a6. a7, a8, a9, a10, a11, a12, a13, a14, a15….. at= Error term. From the specified model equation above, dependent variable is GDP i.e. endogenous variable and the exogenous variables are AGRI, EXG, FDI, GDD, GNI, IFR, IND, INT, MVD, TCI, TRD, UMP, HEP, EEP, EXD). This aspect defines the theoretical expectations about the signs and magnitudes of the parameters of the specified function. The apriori expectations are determined by the principles of economic theory guiding the economic relationship among the variables under study.

4.8      Estimation techniques

The technique that is used in the study for the processing of the data is OLS via View (E-View) software computer package. The empirical study used a simulation approach to investigate the bigger economic amongst the two countries. The performance of the results of models is evaluated using the following statistics: t-test, p-value, F Stat, the coefficient of multiple determination and Durbin-Watson.

 

The traditional test of significance of the parameter estimates is the standard error test, which is equivalent to the student’s t–test. The correlation coefficient (R) shows the relationship between the variables. The relationship could be of a direct, indirect or an outright zero correlation. The Durbin Watson test was conducted to verify the autocorrelation of the variables. The standard error is obtained by taking the inverse of the variance of the estimate. The standard errors for the estimate of ρ, ß and þis dealt with in this project, while the standard error for the estimates δ, Øand ∂ are left out.  The coefficient of determination (R2) is used to determine the overall significance of the regression model i.e. to determine the extent to which the variations in the dependent variable can be attributed to changes in the explanatory variable.

4.9     Data presentation and interpretation

4.9.1     Presentation for Nigeria

Dependent Variable: GDP    
Method: Least Squares    
Date: 07/29/16   Time: 22:54    
Sample (adjusted): 1987 2013    
Included observations: 27 after adjustments  
         
         
Variable Coefficient Std. Error t-Statistic Prob.  
         
         
C -2.92E+10 2.50E+10 -1.167872 0.2675
AGRI 7960954. 1.73E+08 0.045889 0.9642
EEP 53.04414 26.22906 2.022343 0.0681
EXD 0.429766 0.386300 1.112519 0.2896
EXG 40413978 1.16E+08 0.349516 0.7333
FDI -0.062183 0.167012 -0.372325 0.7167
GDD 64589936 2.47E+08 0.261179 0.7988
GNI 0.575159 0.211845 2.714999 0.0201
HEP 5.69E+08 8.59E+08 0.662688 0.5212
IFR 43058569 1.21E+08 0.356116 0.7285
IND -98565830 2.94E+08 -0.335647 0.7435
INT 1.260692 1.180182 1.068218 0.3083
MVD -5.05E+08 5.14E+08 -0.982982 0.3467
TCI 0.924190 4.081944 0.226409 0.8250
TRD 82525624 2.19E+08 0.376744 0.7135
UMP 1.06E+09 1.34E+09 0.791830 0.4452
         
         
R-squared 0.999012     Mean dependent var 1.19E+11
Adjusted R-squared 0.997665     S.D. dependent var 1.47E+11
S.E. of regression 7.11E+09     Akaike info criterion 48.49377
Sum squared resid 5.56E+20     Schwarz criterion 49.26167
Log likelihood -638.6658     Hannan-Quinn criter. 48.72210
F-statistic 741.5291     Durbin-Watson stat 1.885192
Prob(F-statistic) 0.000000      
         
         

Source: Author’s calculations using E-views 7

         

4.9.1.1     Results for Nigeria

Given the above empirical result, the functional model can be estimated as GDP= 2.82×1010+a1AGRI+a2EEP+a3EXD+a4EXG+a5GNI+a6FDI+a7GDD+a8GNI+a9HEP+a10IFR+

a11IND+a12INT+ a13MVD+ a14TRD+ a15UMP

GDP=a0+7960954AGRI+53.04414EEP+0.429766EXD+40413978EXG-0.062183FDI-64589936GDD+0.575159GNI+5.69x108HEP+43058569IFR-98565830IND+1.260692INT-5.05X108MVD+0.924190+82525624TRD+1.06x109UMP.

Therefore;

Ho: ao= a1 = a2  = a3  = a= a5 = a6 = a7 = a8 = a9 = a10 = a1 a121 = a13 = a14 = a15= ak meaning that the dependent variable indicators are not statistically insignificant.

H1: ao= a1 = a2  = a3  = a= a5 = a6 = a7 = a8 = a9 = a10 = a1 a121 = a13 = a14 = a15= ak meaning that the dependent variable indicators are statistically significant

Where N = 29 and K= 16

T 0.05 with V= N– k = 29 – 16 = 13 where T0.05 = 2.16

In taking decision, the T-calculated is compared with theoretical T as shown below:

Parameters T* Observations Decisions
a0 (C) -1.167872 T* < T 0.05 accept the null hypothesis
a1(AGRI) 0.045889 T* < T 0.05 accept the null hypothesis
a2 (EEP) 2.022343 T* < T 0.05 accept the null hypothesis
a3 (EXD) 1.112519 T* < T 0.05 accept the null hypothesis
a(EXG) 0.349516 T* < T 0.05 accept the null hypothesis
a5 (FDI) -0.372325 T* >T 0.05 accept the alternative hypothesis
a6(GDD) 0.261179 T* < T 0.05 accept the null hypothesis
a7(GNI) 2.714999 T* < T 0.05 accept the alternative hypothesis
a8(HEP) 0.662688 T* < T 0.05 accept the null hypothesis
a9(IFR) 0.356116 T* < T 0.05 accept the null hypothesis
a10(IND) -0.335647 T* < T 0.05 accept the null hypothesis
a11(INT) 1.068218 T* < T 0.05 accept the null hypothesis
a12(MVD) 0.982982 T* < T 0.05 accept the null hypothesis
a12(INT) 0.226409 T* < T 0.05 accept the null hypothesis
a12(TRD) 0.376744 T* < T 0.05 accept the null hypothesis
a12(UMP) 0.791830 T* < T 0.05 accept the null hypothesis

Based on the stated decision, the null hypothesis was accepted in relatively all of the variables and the alternative hypothesis was accepted where necessary.

The F-Test is used in testing the overall validity of the working model.

Decision Rule – Reject the null hypothesis (overall model is not statistically significant) if the Calculated F-Statistic is greater than the F-ratio at 5% level of significance; otherwise, accept the alternative hypothesis (overall model is statistically significant).

F-Statistic (F*) = 741.5291

F-ratio from F 0.05 table with the formula

V1 = k-1 and V2 = n-k; where V1 and V2 are degrees of freedom.

V1 = 16– 1 = 15

V2 = 29 – 16 = 13 

F 0.05 at V1 = 15 and V2 = 13 which becomes F 0.05(15,13)

Comparing the calculated F-Statistic with the F-ratio, it is observed that F* is greater than the F-ratio (741.5291> 2.60) and also the prob (F-statistic) is less than 0.05 which is (0.000000). The alternative hypothesis is therefore accepted and we conclude that the overall model is statistically significant.

4.9.1.2     The statistical significance of the parameter estimate

The statistical significance of the parameter estimate is verified by the adjusted R squared, the standard error test; the F-statistic and the Durbin-Watson statistics.

  1. The value of the adjusted R-squared (R2) for the model is very high, pegged at 99%. It implies that agriculture value added, industry’s value added, trade (%) of GDP, telecom Investment in private participation in private companies, manufacturing value added, GDP deflator, unemployment (total % of labor force of Nigeria), foreign direct investment, Inflation (consumer prices of Nigeria), GDP, official exchange rate, international tourism in terms of expenditure of Nigeria, education expenditure, health expenditure and external debt explained about 99% systematic variations in real GDP has served as a measure of economic growth over the observed years in the Nigerian economy while the remaining 1% variation is explained by other determining variables outside the model. This result shows a goodness of fit of the regression analysis conducted.
  2. For the model, when compared half of each coefficient with its standard error, it was found that the standard errors are greater than half of the values of the coefficients of the variables in some variables and less than half in some variables. For instance the standard error of GDP which is 2.50 x 1010 is greater than half coefficient of the variable which is -2.92×1010. Hence the variable is not statistically significant. The agricultural value added 1.73 x 108 standard error is greater than half coefficient of the variable 7960954. It can be seen that the standard error of the external debt with value 0.386300 is greater than half coefficient of the variable 0.429766. Also, the official exchange rate 1.16 x 108 is greater than the 40413978 coefficient of the variable. The foreign direct investment, the gross domestic deflator, health expenditure, inflation rate, industry value added, internal tourism, manufacturing value added, telecommunication investment, trade % of GDP, unemployment all have their respective standard errors 0.16701, 2.47×108, 8.59×108, 1.21×108, 2.94×108, 1.180182, 5.94×108, 4.081944, 2.19×108, 1.34×109 greater than half their coefficients

However, the educational expenditure with standard error 26.22906 and gross national income with standard error 0.211845 are less than half coefficient of the variable which makes them statistically significant. This shows that a high percentage of the estimated variables are not statistically significant and that a low percentage of the estimated value which includes GNI alone is statistically significant among the estimated variables measuring the economic growth in Nigeria.

  1. The F statistic of 741.5291 with prob (Fstatistic) of 0.0000 which is greater than the 0.05 known p value shows significance at 5% level and this is an indication that the explanatory variables are determinants of economic growth.
  1. The value of Durbin Watson for the model depict that there is a serial auto-correlation as reflected in the value of Durbin-Watson statistics of 885192 among the explanatory variables in the model.

 

In summary, the econometric test applied in this study shows relationships from different points of view as some were significant and others were not statistically significant but that does not depict a loophole in the analytical process and has helped in understanding the level and the form of association between the dependent and the independent variables which are significant predictors of the economic growth of Nigeria.

 

4.9.2     Presentation of results for South Africa

Dependent Variable: GDP    
Method: Least Squares    
Date: 07/30/16   Time: 00:30    
Sample (adjusted): 1996 2013    
Included observations: 18 after adjustments

 

 
         
         
Variable Coefficient Std. Error t-Statistic Prob.  
         
         
C 1.74E+11 5.60E+11 0.309944 0.7859
EEP 8.122892 16.98660 0.478194 0.6797
AGRI 63444396 5.78E+08 0.109788 0.9226
IND 1.34E+09 7.67E+09 0.174673 0.8774
MVD 4.65E+08 4.42E+09 0.105063 0.9259
EXD 0.098502 1.951251 0.050482 0.9643
EXG 7.80E+08 1.31E+10 0.059648 0.9579
FDI 5.165447 3.627756 1.423868 0.2905
GDD 86440211 1.77E+09 0.048861 0.9655
GNI -0.083864 0.171957 -0.487703 0.6740
HEP -1.22E+10 2.80E+10 -0.436427 0.7051
IFR -1.03E+09 2.00E+09 -0.512139 0.6595
INT 23.65134 29.67434 0.797030 0.5090
TCI -18.54572 28.61530 -0.648105 0.5834
TRD 41834567 2.59E+09 0.016149 0.9886
UMP 1.11E+09 2.77E+09 0.402669 0.7262
         
         
R-squared 0.999539     Mean dependent var 2.28E+11
Adjusted R-squared 0.996080     S.D. dependent var 1.00E+11
S.E. of regression 6.28E+09     Akaike info criterion 47.53961
Sum squared resid 7.89E+19     Schwarz criterion 48.33105
Log likelihood -411.8565     Hannan-Quinn criter. 47.64873
F-statistic 288.9718     Durbin-Watson stat 2.877817
Prob(F-statistic) 0.003454      
         
         

 

Given the above empirical result, the functional model is estimated below.

GDP=1.74×1011+a1AGRIC+a2EXG+a3FDI+a4GDD+a5GNI+a6IFR+a7IND+a8INT+a9MVD+a10TCI+a11TRD+a12UMP+ a13EEP+ a14HEP+ a15EXD

GDP=a0+8.122892EEP+63444396AGRI+1.34×109IND+4.65×108MVD+0.098502EXD+

7.80×108EXG+5.165447FDI+3.54×108GDDGDD-0.887339GNI-1.22X1010HEP-1.03x 109IFR+23.65134INT-18.54572TCI+41834567TRD+1.11×109UMP.

Therefore:

Ho: ao= a1 = a2  = a3  = a= a5 = a6 = a7 = a8 = a9 = a10 = a1 a121 = a13 = a14 = a15= ak meaning that the dependent variable indicators are not statistically insignificant.

H1: ao= a1 = a2  = a3  = a= a5 = a6 = a7 = a8 = a9 = a10 = a1 a121 = a13 = a14 = a15= ak meaning that the dependent variable indicators are statistically significant

Where N = 29 and K= 16

T 0.05 with V= N– k = 29 – 16 = 13 where T0.05 = 2.16

In taking decision, the T-calculated is compared with theoretical T as shown below:

Parameters T* Observations Decisions
a0 (C) 0.309944 T* < T 0.05 accept the null hypothesis
a1(EEP) 0.478194 T* < T 0.05 accept the null hypothesis
a2 (AGRI) 0.109788 T* < T 0.05 accept the null hypothesis
a3 (IND) 0.174673 T* > T 0.05 accept the null hypothesis
a(MVD) 0.105063 T* < T 0.05 accept the null hypothesis
a5 (EXD) 0.050482 T* >T 0.05 accept the alternative hypothesis
a6 (EXG) 0.059648 T* < T 0.05 accept the null hypothesis
a7(FDI) 1.423868 T* < T 0.05 accept the null hypothesis
a8(GDD) 0.048861 T* < T 0.05 accept the null hypothesis
a9 (GNI) -0.487703 T* < T 0.05 accept the null hypothesis
a10 (HEP) -0.436427 T* < T 0.05 accept the null hypothesis
a11  (IFR) -0.512139 T* < T 0.05 accept the null hypothesis
a12 (INT) 0.797030 T* < T 0.05 accept the null hypothesis
a13 (TCI) -0.648105 T* < T 0.05 accept the null hypothesis
a14 (TRD) 0.016149 T* < T 0.05 accept the null hypothesis
a14 (UMP) 0.402669 T* < T 0.05 accept the null hypothesis

Based on the stated decision, the null hypothesis was accepted in relatively all of the variables and the alternative hypothesis was accepted where necessary.

The F-Test is used in testing the overall validity of the working model.

Decision Rule – Reject the null hypothesis (overall model is not statistically significant) if the calculated F-Statistic is greater than the F-ratio at 5% level of significance; otherwise, accept the alternative hypothesis (overall model is statistically significant).

F-Statistic (F*) = 288.9718

F-ratio from F 0.05 table with the formula

V1 = k-1 and V2 = n-k; where V1 and V2 are degrees of freedom.

V1 = 16– 1 = 15

V2 = 29 – 16 = 13

F 0.05 at V1 = 12 and V2 = 16which becomes F 0.05(15,13)

Comparing the calculated F-Statistic with the F-ratio, it is observed that F* is greater than the F-ratio (288.9718> 2.42) and also the prob (F-statistic) with value 0.003454is less than 0.05. The alternative hypothesis is therefore accepted and we conclude that the overall model is statistically significant.

4.9.2.1     The statistical significance of the parameter estimate

The statistical significance of the parameter estimate is verified by the adjusted R squared, the standard error test; the F-statistic and the Durbin-Watson statistics.

  • The value of the adjusted R-squared (R2) for the model is very high, pegged at 99%. It implies that agriculture value added, industry’s value added, trade (%) of GDP, Telecom Investment in private participation in private companies, manufacturing value added, GDP deflator, unemployment (total % of labor force of Nigeria), Foreign direct investment, Inflation (consumer prices of South Africa), GDP, official exchange rate, International tourism, education expenditure, health expenditure and external debt of South Africa explained about 99% systematic variations in real GDP which has served as a measure of economic growth over the observed years in the South African economy while the remaining 1% variation is explained by other determining variables outside the model. This result shows a goodness of fit of the regression analysis conducted based on the adjusted R-squared value obtained.
  • From the presented E-view result, a comparison of half the value of the coefficient with its standard error, it was found that the standard errors of all variables are greater than half of the values of the coefficients of the variables. For instance the standard error of educational expenditure which is 98660 is greater than half coefficient of the variable which is 8.122892. The agricultural value added is 5.78×108 is greater than half the coefficient 63444396. Hence the variable is not statistically significant. Overall, the industry value added, the manufacturing value added, the external debt, exchange rate, foreign direct investment, gross domestic deflator, gross national income, health expenditure, inflation rate, internal tourism, telecommunication investment, trade % of GDP and unemployment rate all have their standard errors greater than half of their coefficients. This shows that the estimated variables are not statistically significant.
  1. The F statistic of 9718 with prob (Fstatistic) of 0.0000 which is greater than the 0.05 known p value shows significance at 5% level and this is an indication that the explanatory variables are determinants of economic growth.
  2. In addition to the value of the Durbin Watson model the results depict no serial auto-correlation problems as reflected in the value of Durbin-Watson statistics of 88 among the explanatory variables in the model.

In summary, the econometric test applied in this study shows relationships and their significance. Overall, none of the variables were statistically significant, perhaps due to the irregularities in the data obtained and non-availability of data for most years. However based on the generally significance of the variables by the F value, it can be seen that all the presented variables are major drivers of the economic growth of South Africa.

5.0     Comparison between the economic growth of Nigeria and South Africa

Nigeria rebased her GDP in April 2014 and overtook South Africa. In August 2016 South Africa overtook Nigeria and regained the position of Africa’s largest economy, at least, in dollar terms. At the end of August 2016 the rand recorded gains of over 13.3 per dollar while the naira weakened by 2.7 percent. Thus, Nigeria’s GDP value of USD510 has suddenly become USD296 billion since the naira has lost 42 percent compared to South Africa economy which only contracted from the assessed USD370 billion to USD310 billion (The Guardian, 2016). The analysis below examines in further details the performance of the various indicators in this study over a 29 year period.

5.1     Agricultural produce

South Africa is one of world’s largest producers of chicory roots; grapefruit; cereals; green maize and maize; castor oil seed; pears; sisal; fibre crops (Liebenberg and Pardey, 2010). In Nigeria agriculture suffers from years of mismanagement, misappropriation of agricultural funds, inconsistent and poorly conceived government policies, neglect and the lack of basic infrastructure (Ariyo 1999:159-173). The sector however still accounts for over 26.8% of GDP and two-thirds of employment. Before the discovery of oil in 1956, Nigeria was well known in her agrarian economy through which cash crops like cocoa, palm produce, rubber, timber, ground nuts, were exported. Nigeria now struggles to produce only 20% of what its population requires and relay on food importation.

The various reforms on agriculture made by the government in 2010 kept Nigeria ahead of South Africa in terms of exports of agricultural products by introducing agricultural incentives and the introduction of various farm mechanization process and equipment. Overall, Nigeria has better agricultural value added annual % growth than South Africa. This shows that Nigeria has been more prosperous in its agricultural sector than South Africa within the range of the 29 years considered.

5.2     Official exchange rate

Based on the data collected over the 29 year period, the value of the Nigerian currency was 1.75 naira to a dollar in 1986 to 158.55 in June 2015. The naira has been further devalued and exchanged for 300-320 for a dollar in July 2016. This then jumped to 381-420 naira to a dollar in August 2016. This study shows that South Africa has better official exchange rate than Nigeria.

5.3     Foreign direct investments

Nigeria received about 6% of Africa’s total FDI for new projects and 11% of capital invested since 2007. South Africa has great potential to strongly appeal to foreign investors compared to other countries in the world. However, its record in terms of attracting FDI thus far has been relatively poor although it has been improving due to its huge investments in infrastructure owing to the global financial crisis of 2008-2009. This led to a decline in FDI, investment flows recovered. They increased significantly in 2013 (ZAR 80 billion), but diminished again in 2014 (ZAR 62 billion). They are mostly concentrated in the telecommunications sector. However the country is the third largest FDI recipient in Africa, after Nigeria and Mozambique, and the largest FDI provider (Ruxanda & Muraru 2010:45-57).

Globally, South Africa occupies the 15th position among the most attractive economies for transnational companies for 2013-2014. In addition to structural issues in the electricity supply and logistics sectors, incessant industrial strikes which regularly affect production can also prove discouraging to investors. Therefore from the research conducted, Nigeria has been attracting more investors into the various sectors of its economy and as such is the biggest in Africa in terms of FDI and South Africa is said to be the third.

5.4     GDP deflator

Considering the variable GDP deflator, GDP deflator (base year varies by country) in Nigeria was 126.69 as of 2013 which is its highest value over the past 53 years, while its lowest value was 0.03 in 1960. GDP deflator (annual %) in South Africa was 87.5% in 2013, according to the data garnered from World Bank while that of Nigeria was measured at 94% in 2014. Over all, this research revealed that Nigeria has higher GDP deflator than South Africa.

 

5.5     Gross national income

The GNI of Nigeria experienced a 30% increase between 2005 and 2006. However, South Africa had a GNI of over 75 billion in the year 1986 which was about 79% greater than that of Nigeria at a time Nigeria was implementing the Structural Adjustment Program. The GNI of South Africa had been superseding that of Nigeria until 2012 when the GNI of Nigeria upbeat that of South Africa by 12% and has been taking the frontline since then. Nigeria is keeping up with South Africa in terms of the GNI but overall South Africa has a higher GNI value than Nigeria.

5.6     Inflation rate

The highest inflation rate Nigeria ever experienced in the 29 years computed data for this study is 72.8% which occurred in 1995 while that of South Africa was 18.7% and took place in 1986. The increment in the inflation rate has been as a result of the continuous increase in the exchange rate which has negative effect on international trade and overall economic development. Notably, inflation generally is known to have a negative effect on the economy of any country and must therefore be brought to the barest minimum level to improve the economy (Gillman Harris, and Matya, 2004). This research shows that Nigeria is experiencing more inflation and consumer prices increase than South Africa.

5.7     Industry value added (annual % growth)

This research has revealed that Nigeria is experiencing more industry value added than South Africa thus making it possess more contribution of a private industry or government sector to its overall GDP. This then means more compensation of employees, more taxes on production and imports less subsidies, and gross operating surplus than South Africa.

5.8     International tourism

In 2011, more than 2 million tourists visited Nigeria. The various international church crusades and conferences coupled with foreign investors on business tourism make the bulk of the tourists and spent the equivalent of US$3.7 million and this figure is expected to rise by 10 percent increase year by year (Njoku, 2003). South Africa offers both domestic and international tourists a wide variety of options, among others the natural landscape and game reserves, diverse cultural heritage and highly regarded wines. South Africa has been the most dominant in the area of tourism between the two countries but in the year 2007, Nigeria recorded over US$6.7 billion in the area of tourism while South Africa recorded over US$5.2 billion in the same year. This study however shows that South Africa supersedes Nigeria in the area of tourism.

5.9     Manufacturing value added

The Manufacturing sector is now Nigeria’s major economic growth driver and it is growing strongly despite power deficit. Nigeria produces 3 gigawatt of electricity while South Africa produces 45 gigawatt allowing cheaper production. The South African manufacturing industry’s contribution to the economy provides 13.3% of jobs and 15% of GDP. An interesting African story is that South African automotive industry accounts for about 10% of the country’s manufacturing exports, contributes 7.5% to the country’s GDP and employs around 36,000 people. Annual production in 2007 was 535,000 vehicles, out of a global production of 73 million units in the same year. Vehicle exports were in the region of 170,000 units in 2007, exported mainly to Japan (about 29% of the value of total exports), Australia (20%), the UK (12%) and the US (11%). However, the South African manufacturing sector contributed 15.2% to its GDP in 2013, making it the third-largest contributor to the nation’s economy. It has made lots of income from its Agro-processing, chemicals, information and communication, technology, textiles and metals aside the automotive. Data analysed however shows that Nigeria has more value added than South Africa.

5.10     Telecommunication investment

In December 2004, Nigeria had 1.5 million internet users, a penetration rate of 1.3% and constituted about 5.6% of the total number of African internet users. Africa itself only boasts of 1.5% of global internet users even though it has 14% of the world’s inhabitants. Private investment in ICTs also rose from an almost zero value to about US$4 billion between 1999 and 2003 (Ndukwe, 2005).

On the other hand, South Africa recorded over US$1.5 billion telecom investment participation in the year 2013 while Nigeria recorded over US$2.1 billion thus accruing over 26% more than South Africa. However, based on the data collected for the investigation of telecom investment participation between the two countries, it can be inferred that South Africa has more telecommunication investment participation than Nigeria but Nigeria has been experiencing more telecommunication investment since 2008 which is gradually overtaking South Africa.

5.11     Trade % of GDP

The variable trade % of GDP between Nigeria and South African shows that in 2005 Nigeria posted a US$26 billion trade surplus, corresponding to almost 20% of gross domestic product. In 2005, Nigeria had a positive current account balance of US$9.6 billion and has expanded its trade relations with other developing countries such as India. Nigeria is the largest African crude oil supplier to India. It annually exports 400,000 barrels per day (64,000 m3/d) to India valued at US$10 billion annually while almost 90% of South Africa’s exports to rest of Africa go to the SADC economies.

In the year 2013, South Africa recorded 64% percent trade % of GDP which was more than twice that of Nigeria’s trade % of GDP value of 31%. This then revealed that South Africa’s trade % of GDP superseded that of Nigeria by 52% in that year.

5.12     Unemployment

South Africa is projected to have the 8th highest unemployment rate in the world in 2015. It has been observed that more than 61 million jobs have been lost since the start of the global crisis in 2008 and projections show that unemployment will continue to rise. In Nigeria, more than 30 million Nigerians are unemployed while the National Bureau of Statistics observed that unemployment stood at 6.4% for the final quarter of 2014 and increased to 7.5%       for the first three months of 2015. However, based on the data collected for this research, it is evident that South Africa has a higher record of unemployment than Nigeria which has been negatively impacting on its economic growth.

5.13     Educational expenditure

In the area of educational expenditure, the educational expenditure of Nigeria is far behind that of South Africa. In the year 2014 based on the data collected, it was revealed that the South African education expenditure exceeded that of Nigeria by 64% as education is seen as a necessary tool that can help economic development (World Bank, 2008). The education expenditure of South Africa exceeds that of Nigeria which has positively impacted on the educational level of both countries putting South Africa’s education ahead of Nigeria.

5.14     Health expenditure

Considering the health expenditure of both countries, the health expenditure of South Africa evidently exceeds that of Nigeria. In the year 1995, the health expenditure of South Africa exceeded that of Nigeria by 36 percent. Based on the data garnered, it was clearly shown that in the year 2014 the health expenditure of South Africa exceeded that of Nigeria by 38 percent. Health expenditure of South Africa exceeds that of Nigeria, thus the former has adequately provided for health equipment, employment of quality doctors and health professionals more than later.

5.15     External debt

The external debt figures of both South Africa and Nigeria have clearly shown that South Africa has lots of external debts when compared to Nigeria. The highest external debt record of Nigeria from the Structural Adjustment Programme (SAP) up to 2014 has been US$39.9 billion (World Bank, 1996) while South Africa is known to have continued to have an increased external debt extending to over US$144 billion in the year 2014 making its debt exceed that of Nigeria  by 74% in that year. South Africa, thus, generally have more external debt than Nigeria.

5.16     Construction industry

Although data was not available for the construction and entertainment for this research work. It is important to discuss this based on the observational study. According to the report, infrastructure (construction and operation) will overtake oil and gas to become the third largest contributor (nearly 16%) to the GDP, after trade (17%) and agriculture (16%) in Nigeria. Excluding real estate, McKinsey estimates that US$839bn would need to be invested in infrastructure through 2030 to allow the economy to reach its full potential. The bulk of this investment would be in power and transportation systems, with significant need in telecommunications and water infrastructure.  This would raise the size of the construction industry in 2030 by USD39bn over the 2013 level. The Nigerian construction industry in 2008 and 2009 was the 8th largest contributor to the country’s GDP. It contributed between 1.56 per cent and 1.80 per cent to the country’s GDP respectively between 2010 and 2013 (National Bureau of Statistics, 2012).

However, South Africa’s construction industry faced a challenging year in 2014, troubled with labour unrest, substantial delays on some of the country’s major construction projects, as well as recent setbacks in the economy. The market capitalization of the heavy construction and building materials and fixtures companies saw mixed results in the year 2014. South Africa used to edge out Nigeria in the area of construction but recent observations have shown that Nigeria has now superseded South Africa in this regard.

5.17     The entertainments industry

The Nigerian entertainment industry is ranked third, globally, in terms of quality of production and gross earnings. Nollywood is ranked third globally in gross earnings and the revenue the film industry has generated in the last three years was between US$300m and US$800m. In South Africa, the entertainment industry generated about US$90.6m revenue in 2010 thus, the revenue increased to $102.7m in 2012.

It may be observed that data for both the construction and entertainment industry are hardly available which may have limited the scope of this study. However, it is believed that the Nigerian entertainment is bigger than the South African entertainment and has ascribed lots of international fame to its name.

  • Findings leading to economy with greater prospects

The findings from this study helps to determine the country with more prospects. Nigeria’s GDP exceed that of South Africa as at the end of 2014 but South Africa commands better GDP per-capita than Nigeria.  The agricultural value added of Nigeria is greater than that of South Africa even though Nigeria is still under producing and unable to feed its population. South Africa has better exchange rate than Nigeria as it was revealed that the Nigerian currency –the Naira has been suffering from devaluation in the past and the 2016 devaluation has been the worst in the country’s history when compared to the South African Rand. This devaluation of Nigerian currency made the South African GDP to become bigger than that of Nigeria in third quarter of 2016. Nigeria, though has a higher GDP deflator value than South Africa over the period examined.

Nigeria has better FDI than any other African country and has attracted more foreign investors into various areas of its economy while South Africa is ranked third in this indicator. The Inflation, consumer prices of Nigeria is greatly higher than that of South Africa. Nigerian is be experiencing increment in consumer price levels which makes South Africa better than Nigeria in that indicator. Again, Nigeria’s population and energized population may have contributed to this. South Africa remains a much better tourist attraction when compared to Nigeria and the country’s political stability, sound infrastructure and weather gives it much more advantage over Nigeria in the area of tourism.

Nigeria has a higher industry value added than South Africa and also possess more manufacturing value added than South Africa. In the area of telecommunication, investment private participation in South Africa has performed better than Nigeria. Findings however shows that more investors are entering into the Nigerian telecom sector and it has more internet service providers than South Africa. Projections shows that Nigeria would soon overtake South Africa in its telecom investment private participation.

The trade % of GDP of South Africa is greater than that of Nigeria as South Africa involves in more export rather than import. Data from the trade % of GDP of 2013 and 2014 revealed that South Africa’s trade % of GDP for the two years superseded that of Nigeria by 52%. South Africa has huge problems of unemployment when compared with Nigeria. This study observed South Africa has more education expenditure than Nigeria which has helped improved its educational level in the continent and has placed it ahead of every other African country. This indeed seem a major prospect for South Africa since future generation are expected to propel productivity unlike Nigeria with largely poor investment in education especially in the Northern part of the country.

Health expenditure is another very important investment that South Africa has made with much more sophisticated health facilities than Nigeria. It however suffers from the brain drain caused by HIV-AIDS. Infant mortality, malaria and other preventable diseases still kills many Nigerians. While Nigeria has tried to manage its external debt profile, South Africa has extreme external debt. One may, though, argue that South Africa has maximized these resources more effectively than Nigeria which still suffers from poor governance and ineffective institutions.

7.0     Developing a strategic path to economic growth and development

Nigeria had about the same GDP with Korea, Brazil and India in 1960 (Kohli 2004). It will take the whole of Africa till 2050 to become as larger as Brazil and India in GDP terms (O’Neill 2013:37-38). What then would Nigeria and South Africa do to become like South Korea learning from the miracles of Asian Tigers? South Korea achieved inclusive growth and development such that inequality, poverty and unemployment remained very low (Hwang 2014:196-198 in Ohno and Ohno 2014; Kohli 2004; Evans 1995). Malaysia on the other hand was as poor as many African countries in the 60s and embarked on a unique industrialization path built on political will, civil service efficiency and integrity, and public sector efficiency and integrity which is referred to as the ‘conceptual framework of triangle of hope’ (Jegathesan and Ono 2014:191). They also pursued ‘the quadrant strategy’ which is hinged on: the creation of attractive environment for general and specific sectors; identification of projects and industries with both comparative and competitive advantage; promotion of national image to attract foreign investment; and implementation of projects within the country that would create wealth and provide jobs within the country (Jegathesan and Ono 2014: 189-194). One may then “totally reject the classical economic notion of comparative advantage, because if focuses exclusively on economic advantage, in isolation of nature, culture and society” (Lessem 2015:4; Lessem et al 2014)) Malaysia and Korea clearly moved away from Nigeria and South Africa’s resource-dependent economy. Rather than see comparative advantage in commodities, Malaysia and Korea quickly perfected manufacturing in the 80s and 90s and became knowledge-based economies thereby paying even greater attention to services without necessarily declining in agriculture and manufacturing which allowed them to build competitive advantage strategies. Korea developed such unique cohesive-capitalist state where a relationship is established with state and capital in a growth-oriented, collaborative, and export-oriented manner (Kohil 2004:85). This Japanese state-led developmental path sometime distort market force mechanism (Oshodi 2014:124-125) by building a global trade regime and neighborhood externalities where the state play a catalyst role (Jegathesan and Ono 2014: 213 )aimed at rapid industrialization. Between Nigeria and South Africa, it would have been interesting to see the Japanese ‘operation of international division of labour either as offshore producers or as vendors of components’ (Jegathesan and Ono 2014: 213). Just like the way the Malaysian practically shared their industrialization experience with Zambia while the Koreans through the International Development Exchange Programme (IDEP) provided technical developmental assistance to Rwanda, South Africa and Nigeria may also consider such. Korea, like a developmental laboratory converted Rwanda’s land-lock attribute and ethnic diversity to strength, then, Nigeria’s ethno-linguistic diversity can indeed become strength. More so, South Africa’s unemployed black population and declining commodity prices can translate to wealth creation. Ineffective institutions and unguided privatization due to neo-patrimonial rent seeking behavior have greatly affected the ability of Nigeria to industrialize rapidly. In South Africa, post-apartheid government have allowed much corruption to reduce the country’s developmental speed while government agencies misplace priorities. One can then learn from the Korean International Cooperation Agency (KOICA) as cloned in Rwanda as Rwanda Development Board (RDB) where all state-owned enterprises were redesigned rather than quickly selling these massive enterprises to political cronies because the Washington Consensus has called for privatization and neo-liberalization.  Again, Rwanda created an ‘embedded autonomy (Evans 1995) through the Office of the President and the Institute of Policy Analysis and Research. Even though this study has examined developmental indicators for Nigeria and South Africa, what become more important is not the bigger economy between the two countries but the ability of these sleeping giants to innovate and quickly achieve sincere economic development rather than mere empty growth of indicators that has not positively touched the lives of its peoples.

8.0        Conclusion

This research shows that South Africa has a more healthy economy than Nigeria considering the variables considered. The study covered 1986 and 2014 using the ordinary least square to analyze development indicators. It was also found that both countries have their unique area of specialization and dominance as related to economic growth. Both economies rely heavily on commodity exports. In Nigeria, oil and gas transactions constitute more than 95% of its foreign income and South Africa’s commodities make up 65% of exports. South Africa is however more dynamic and has diversifying its manufacturing industry and automobile industry which has bolstered its economy.

Nigeria’s GDP in 2015 was seen at USD522 billion while South Africa’s GDP was USD350 billion. However economic growth is not only decided with the GDP variable alone but with other determinants of economic growth. Although a major part of Nigeria having a larger GDP when revealed was due to its much larger population of 182 million people compared to South Africa’s 54.9 million. The population of Nigeria hence surpasses available resources which make South Africa wealthier than Nigeria per capita. The Nigerian people are however energized with huge entrepreneurial zeal when compared with any country in Africa.

Whichever economy is bigger, the more prosperous one may be view in the area of a country’s ability to quickly create wealth through rapid industrialization.   Both countries have done little in learning from fast growing economies like South Korea, Singapore and Malaysia. South Africa and Nigeria have indeed not pursued well-articulated development plan aimed at building a true cohesive-capitalist state while ensuring that poverty, unemployment and inequality are minimized. More so, weak institutions, state and market capture, and unarticulated gaps needs to be addressed in order to truly feel like a member of the BRICS or MINT. A more symbiotic relationship between the two countries in terms of trade, industrialization and knowledge-based economy need to be further harmonized.

 

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Basheer Oshodi (Ph.D.)

Co-founder, Centre for Integral Socio-Economic Research (CISER) Nigeria, an affiliate of Trans4m Centre for Integral Development, Geneva; Adjunct lecturer, University of Lagos, Nigeria; Group Head, Non-Interest Banking, Sterling Bank, Nigeria; Member, Nigeria Security and Exchange Commission (SEC)  Alternative Finance Product Master Plan Committee; Member, International Atlantic Economic Society (IAES); Member, American Economic Association (AEA).

Mailing address: 12 Peony House, Primewaterview 2, Lekki 1, Lagos, Nigeria

Email: oshodibasheer@gmail.com

Phone numbers: +234 7069640663, +234 8185092955