101 ECONOMIC DEVELOPMENT IN SUB-SAHARAH AFRICA AND ANALYSIS OF WAGNER`S LAW, 2005-2015 Choudhry Mohammad HANIF*

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ECONOMIC DEVELOPMENT IN SUB-SAHARAH AFRICA AND ANALYSIS OF WAGNER`S LAW, 2005-2015 Choudhry Mohammad HANIF*¹

Elsadig Musa AHMED Abstract

The paper empirically tests the validity of the Wagner’s law in selected Sub-Saharan Africa (SSA), divided into higher and lower income countries for the period 2005- 2014. Panel fixed effect model was used to investigate the relationship between public expenditure and economic growth following five identified framework in the econometric literature. It was found that the income elasticities from the Peacock, Goffman and Gupta versions of the Wagner’s law were positive and statistically significant. The impact of income on growth and vice versa in higher and lower income countries in Sub-Saharan Africa indicates that big government is a positive function of growth among the selected lower income countries. All the versions of Wagner’s law tested indicate that for lower income countries in SSA, there is a positive and statistically significant relationship (except in the case of the Mann’s version) between income and growth.

Keywords: Economic growth; public expenditure; Sub-Saharan Africa;

Wagner’s law 1. Introduction

The role and size of government in economic life is one of the most debated issues in the economic literature. It is not in contention that over the last century, the size of public expenditure in relation to national income or output has expanded for most of the developed and developing world. This had led to renewed interest in what the optimal size of government might be or whether expansion has bearing on spending. Several theories have been propounded and explain the relationship between growth and public expenditure, with vast amount of empirical investigations focused on the different formulations over time, across countries or group of countries.

Many factors contribute to a country’s economic growth, including its population size, economic structure, public expenditure and the age structure of its work force. An extensive literature has developed which examines the impact of public expenditure, on economic growth on the one hand; and the determinants and causes of public expenditure, on the other. As with most research, studies of economic development are not always consistent due to differences. Sub-Saharan Africa garners a lot of attention when strategies for stimulating economic growth or development are discussed due to the pervasive poverty in the region.

*¹Choudhry Mohammad HANIF, Department of Economics, Faculty of Social & Management Sciences, Bayero University, Kano, Nigeria. *Elsadig Musa AHMED

Faculty of Business, Multimedia University, Melaka, Malaysia, E-mail:

([email protected])

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First, the size and the composition of public expenditure on economic life come under a strong matrix of political, institutional and macroeconomic factors.

Second, the subject has witnessed increasing interest in recent years, as many governments have attempted to fight against various forms of economic crisis through increasing the quantum of expenditures. The relationship between government expenditure and economic growth has been largely investigated from the point of view of two important theories: the Wagner’s law and the Keynesian hypothesis (Ram, 1987; Courakis et al., 1993).

Applying the Wagner’s preposition on Sub-Saharan Africa is plausible given that basically it was conceived as applicable to countries in their early stages of development. In the light of this, a number of economists agree that the law is expected to be valid in developing economies. Sub-Saharan African countries are considered poor in the world. They face major challenges in attempts to achieve growth and reduce poverty, and to effectively integrate into the global economy (IMF, 2013). It faces monumental problems in virtually all aspects of economic life. It remains vulnerable to endogenous and exogenous shocks. Conflicts are prevalent, the political environment of many of the countries is fragile while diversification through investment in various sectors of the economy appears not forthcoming (Nkurunziza &

Bates, 2004; Basu et al., 2005).

According to Haggblade et al. (2004), Sub-Saharan Africa has the world’s fastest growing populations, which is estimated at 2.7% a year, contrasted with 2.2%

and 2% respectively for Latin America and Asia (Lelo & Makenzi, 2000). It is also the most diverse region in the world with over two thousand different indigenous languages (Kim & Kim, 2003).

In recent times however, some countries are showing signs of economic progress, reflecting the efforts of governments of most sub-Saharan African countries in restructuring their public expenditure. Economic growth rates are still not high enough to make a real difference in the persistent poverty bedevilling the region.

According to McKinley (2005), the rate of economic growth in SSA has improved in the last 10 to 15 years, although hitherto, it had the worst growth performance of any region globally. The poor performance of the sub-region was mainly occasioned by low investment, inappropriate policies and institutions and geographical constraints.

However, there has been marked improvement in growth from the 1990s, although it has not spread evenly across the countries. Between 1996 and 2005, fifteen SSA countries (i.e. Mozambique, Rwanda, Cape Verde, Uganda, Botswana, Ethiopia, Tanzania, Mauritania, Benin, Ghana, Senegal, Burkina Faso, Mali, Gambia and Cameroon) recorded annual growth rates of more than 4.5%. During the same period, thirteen SSA countries (i.e. Central African Republic, Guinea-Bissau, Kenya, Lesotho, Eritrea, Comoros, Seychelles, Cote d’Ivoire, Burundi, Sierra Leone, Swaziland, DRC Congo, and Zimbabwe) recorded growth rates of only 1.3% (World Bank, 2006).

Between 2010 and 2013, the rate of economic growth was maintained at a high level, between 5.3%-5.7%, with a small variation since then: from 5.3% (2010) to 5.2%

(2011) to 5.0% (2012) to 5.7% (2013) (OECD et al., 2012).

An investigation of the relationship between government spending and national income is very important for SSA, due largely to its implication for policy. As

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of 2015, countries in Europe such as Greece, Portugal and Italy are in recession and the imperative of stimulating their economies through extra fiscal measures has been stressed. Consequently the relationship between public expenditure and national income is critical for public deficit sustainability which is required if such economies are to exit the pigeon-hole of recession.

From the foregoing, the study examines public expenditure and economic growth focusing on sub-Saharan African countries. The study takes into account recent advances in econometric techniques and examines the relationships between public expenditure and GDP over the period of 2005-2014, with a view to determining the applicability of the Wagner’s Law.

Significance of the Study

This study is significant for three majors groups, namely academics, policy makers and the general public. For academics, this study closes some gaps in the existing literature on public expenditure-growth nexus. The first gap that this study fills in this respect is the examination of whether economies with higher levels of public expenditure experience more or less volatility in economic growth rates.

Although some studies have been conducted on Sub-Saharan Africa countries in which the countries were segregated into high and low income groups, such as those of Chen et al. (2014), such analysis used the Generalized Method of Moments (GMM) technique. This study further extends the investigation of the public spending-growth nexus by considering an alternative econometric technique, that of panel co-integration and causality. The study also augments the available empirical evidence on the role of public expenditure on economic growth, which is the object of a lively debate among both academics and policymakers.

In particular, the paper adds to the debate on the effects as well as direction of causal relationship by applying recent developments in the panel time series literature.

Finally, the study offers an additional advantage in terms of the span of the historical time series used in the analysis. Considering that Wagner’s law needs to be regarded as a long-run phenomenon, use of time series becomes more reliable than the use of cross-country data analyses, in terms of statistical inference and economic interpretation, consistent with the views of Henrekson (1992), Legrenzi (2000) and Florio and Collautti (2005).

2. Public Expenditure and Economic Growth Relationship

Many studies have considered the relation between public expenditure and economic growth. In the existing literature, some studies concentrate on a specific country, while others look at a panel of countries. Some studies examine the relationship between aggregate public expenditure and economic growth while some explore certain public expenditure components (e.g. education, military, health, etc) in relation to economic growth. The results vary from country to country. Whilst some researchers have been able to show that government expenditure leads to the growth of a country’s economy or certain public expenditure components leads to growth, other researchers think in quite the opposite way and argue that economic growth stimulates government expenditure. In principle, causation could run from public expenditure to economic growth or vice versa.

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The empirical evidence of the relationship between government size and economic growth is mixed. Folster and Henrekson (2001), Landau (1986), Grier and Tullock (1989) found a negative relationship between government size and economic growth. They maintain that higher government expenditure results in diminishing returns and crowd out private investment. Distortion in government expenditure may well results from increasing government size, and while government will require more taxes to sustain expenditure, this can progressively cause a lot of harm to the economy.

Ram (1986), Aschauer (1989) and, Kormendi and Meguire (1986) found a positive relationship between government size and economic growth and the conclusion reached was that higher government size improves the investment environment as it encourages private sector participation and protects private property.

Conflicting results to be pervasive in the study of the relationship between government size and economic growth, irrespective of the compositions of expenditure, the methodological tool used, the sample size and the stage of development of the countries investigated. The underlying factor appears to be that the effect of government spending on economic growth would depend essentially on the components of expenditure and fiscal adjustment, so that while investment tends to positively impact growth, the reverse is the case for consumption expenditure (Levine

& Renelt, 1992).

It is mostly likely that the nature of policy and policy mix impact the growth process. In this context, Barro (1990) extended the endogenous growth framework to account for tax-financed government services, and the finding is that there is a positive relationship when the share of government expenditure and the tax rate is low and a negative relationship when government size increases. This result was linked to rising inefficiencies brought about by the disincentive effect of higher tax rates on private capital accumulation. These results are supported by the empirical findings by Kneller et al. (1999) and Bleaney et al. (2001). Similarly, Grossman (1990), on a study comprising 48 developing and developed countries, showed that government size has both positive and negative impacts on economic growth (although the net-effect is positive), the former working through higher productivity and the latter through inefficient and distortionary public taxation.

On the part of fiscal adjustment, Park (2006) using a set of developed and developing countries did not find robust empirical results linking higher growth to the combination of productive public investment and lower taxes or lower growth to the combination of current government consumption and higher taxes. When combined with a lower budget deficit, government capital expenditure has a positive impact on economic growth for low-income economies (Gupta et al., 2005). In a similar study, Benos (2009) on a study of 14 countries in the European Union found that a reallocation of government spending components in favour of infrastructure and human capital stimulates growth. The findings by Donald and Shuanglin (1993) on a study conducted on 58 countries suggest that while government expenditures on education and defence have positive effect, welfare expenditure does not. It would be plausible to find that in low-income and developing countries, higher expenditure on health,

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education and capital projects would spur economic growth (Baldacci et al., 2008;

Ang, 2009).

The seeming contradiction and inconsistency in the empirical literature has been blamed on the true nature of the relationship in that rather than a linear one, it could well be non-linear, as found in Sheehey (1993).

It may well be that the effect that government size has on economic growth depends largely on the initial growth rate and size of spending, so that higher spending may reduce the growth rate subsequently.

It may be that higher growth rate does not favour higher public expenditure.

Chen et al. (2011) used the quantile regression methodology to explore the relationship between government size and economic growth for 24 Organisation for Economic Cooperation and Development (OECD) countries, and found that the degree of the effect varies through the quantiles, implying that at low growth rate, a rise in government size may be beneficial to economic growth, while at high growth rates, the reverse was found.

Guisan(2013) and (2018) analyses public expenditure in the context of macroeconometric models and presents a disequilibrium model from supply and demand sides in 6 OECD countries, having into account not only the primary inputs approach to supply (production function) but also intermediate inputs supply (with intersectoral relationships and effects of foreign trade).

She founds that the different components of Government Expenditure have different effects on real GDP per head, and that economic development from the supply side contributes very positively to increase both private and public expenditure and to social welfare.

The effects of Public Consumption may be positive from the demand side, and the effects of Public Investment may be positive from the demand side and/or from the supply side (increase of the stock of capital), provided that they do not have a negative effect on private consumption and investment, and do not lead to unsustainable foreign trade deficit, or other negative consequences on development.

Regarding other kinds of Government Expenditure (as transfers to enterprises, families or other groups), the effects usually affect more to the quality of social welfare than to production per capita. The most important conclusion from that study is that the effects should be analysed separately and that it is very important to foster economic policies addressed to increase the supply side, having into account not only investment but also the important positive impact of industry on other sectors, in the context. In Guisan(2017) it is included and analysis of the evolution of manufacturing in Sub- Saharan countries in comparison with other areas and World average.

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3. Economic Growth and Government Expenditure in Sub-Saharan Africa

From a historical perspective, the Gross Demostic Product (GDP) in Sub-Saharan Africa is presented in in Table 1 and Figure 1.

Fig. 1: Sub-Saharan Africa GDP Trend: current prices

In terms of government expenditure as a proportion of GDP, it has tended to be below 30% for SSA from 2000 to 2013 as indicated in Table 1.

Fig. 2: General Government Expenditure as a percentage of GDP

It can be seen in Table 1 that GDP and by extension economic activities in SSA has been rising over the period of investigation. From 341.666 billion dollars in 1980, it rose to 497.462 in 1997 and declined slightly between 1998 and 2002. From 2003, the figure experienced an upward trend so that as at 2013, the GDP was 1,607.46 billion dollars. This trend can be observed in Fig. 1. It can be concluded that in nominal terms, Sub-Saharan Africa has experienced relatively rising quantum of economic activities between 1980 and 2013. In economic growth terms, the experience in SSA within the period of investigation has been rather uneven.

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Table 1: Sub-Saharan Africa GDP (1980 – 2013) and Government Expenditure

Year

Gross domestic product, current prices (Billion $)

General government total expenditure (Percent of GDP)

1980 341.666

1981 332.079

1982 332.866

1983 285.698

1984 239.626

1985 221.77

1986 243.337

1987 266.656

1988 292.045

1989 294.537

1990 337.956

1991 344.037

1992 350.699

1993 348.453

1994 328.037

1995 421.122

1996 479.481

1997 497.462

1998 473.877

1999 354.951

2000 374.355 23.357

2001 349.67 25.843

2002 378.418 22.916

2003 481.388 24.313

2004 602.51 22.88

2005 708.103 22.925

2006 821.764 21.653

2007 958.326 23.716

2008 1,104.76 24.054

2009 1,043.69 25.559

2010 1,271.53 25.04

2011 1,455.07 25.248

2012 1,526.38 24.562

2013 1,607.46 23.937

Source: IMF (2014)

It can be observed from the second column of Table 2 1 and the associated Fig. 2 that in the last one decade, government expenditure as a component of GDP in SSA hovered between 22 present and 27 present. The years 2002, 2004 and 2006 experienced declining expenditure. The same is true for 2011 to 2013.

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4. Methodology

This section explains the data sources, description of variables, models explanation and estimation procedures involved in the study.

Classification of countries

High income countries: Botswana, Equatorial Guinea, Mauritius, Nigeria, South Africa

Low Income countries: Sierra Leone, Tanzania, Ethiopia, Madagascar, DR Congo Sources of Data and Variables Description

Annual data on real gross domestic product per capita, real gross domestic product, real government expenditure and nominal government expenditure per capital for the period 2005 to 2014 were employed in the study. Data covers 10 selected countries in Sub-Saharan Africa and were sourced from publicly acknowledged sources such as the World Development Indicators (World Bank, 2014), World Economic Outlook (IMF, 2014), and the various national accounts of the countries selected in Sub-Saharan Africa.

All the variables were transformed into logarithms in order to capture linear properties and to correct for heteroscedasticity, in line with the trend in the econometric literature. Consistent with the empirical literature, the dependent variable is government expenditure. The independent variable is GDP. The nature of both the regressor and the regressand (i.e. whether in real or nominal terms and whether on per capita basis) are stated depending on which version of the Wagner’s law was tested.

Model Specification

To test the validity of the Wagner’s law, the following models were estimated in this paper:

1 1

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t

GDP e

GE   

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

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e GDP GDP

GE

In the above specifications, GE is the log of real government expenditures, P is log of population, (GE/GDP) is the log of the share of government spending in total output, GDP/P is the log of the per capita real output, GE/P is the log of the per capita real government expenditures, GDP is the log of real GDP. Each of the above specifications related to a specific version of the Wagner’s law:

The first model (Equation 1) is the Peacock-Wiseman (1961) version;

The second model (Equation 2) is the Gupta (1967) version;

The third model (Equation 3) is the Goffman (1968) version;

the fourth model (Equation 4) is the Musgrave (1969) version;

while the fifth model (Equation 5) is the Mann (1980) version.

Model Estimation Procedures

Previous studies on aggregate (single) country data adopted Vector Auto- Regressive (VAR) econometric techniques while some authors based their studies on cross country or regional level data which investigate the relationship between public expenditure and economic growth. However, purely time series studies are constrained by small sample problems linked to the short time span of the data. While the first attempt of panel studies simply estimated either fixed or random effects models.

Recently issues have tackled issues of non-stationary panel data.

In this paper, to study the relationship between public expenditure and economic growth, an econometric model based on panel time series disaggregating the sub-region into high income and low income was used.

The steps or procedures taken in the paper are summarized as follows:

(i) A benchmark cross-country pooled OLS regressions incorporating all the countries in SSA;

(ii) Cross-country pooled OLS regressions reflecting group of countries categorised based on level of per capita income, in line with World Bank benchmarks (i.e. higher income countries and lower income countries). The Housman test was implemented to determine the most appropriate regression type (i.e. fixed or random effect) selected.

5. Empirical Results

In estimating a multivariate panel models involving both the short run and long run analysis, the need to investigate the behaviour as well as the times-series properties of the data used in estimation becomes imperative. This is carried out using unit roots and cointegration tests respectively.

The unit root test results are presented in Panels A and B of Table 2.

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Table 2: Panel Unit Root Test Results

Panel A: ADF-Fisher, PP-Fisher, and Im, Pesaran & Shin Tests^Ω Variable

ADF- Fisher χ² PP-Fisher χ² Im, Pesaran & Shin W- stat

No trend Trend No trend Trend No trend Trend

GDP 19.3284 26.0075 39.7395 27.5617 1.20781 -0.22036

GDP/P 14.5349 24.4064 24.0305 17.2485 2.13392 -0.16181

GE 23.3991 33.2559 50.2054 33.6746 0.54927 -0.73737

GE/GDP 27.7842 22.7246 23.0221 38.7617 -0.54413 0.12055

GE/P 26.1631 21.4256 50.0800 31.2239 -0.13738 -0.13819

∆GDP 38.9659^* 35.2050^** 57.8090^* 55.1808^* -2.11507^** -0.85905

∆GDP/P 41.3218^* 39.7353^* 45.5237^* 36.4563^** -2.39534^* -1.23319^***

∆GE 41.5370^* 29.5330^*** 60.6533^* 62.7913^* -2.40276^* -0.36264

∆GE/GDP 60.3928^* 44.0317^* 78.9853^* 59.3654^* -4.23031^* -1.41121^***

∆GE/P 49.8648^* 38.2430^* 56.2956^* 60.8915 -3.34138^* -1.11984 Panel B: Levin, Lin & Chu Test, and Breitung t-stat^Ф

Levin, Lin & Chu Breitung

Variable No trend Trend Trend

GDP -1.65356 -6.22948 0.45515

GDP/P -2.84892 -3.65136 1.07149

GE -4.01916 -8.53196 0.39064

GE/GDP -2.49954 2.94484 0.67740

GE/P -3.07420 -4.98350^* 1.38354

∆GDP -7.04869^* -10.4168^* -3.27618^*

∆GDP/P -7.95847^* -7.54187^* -4.55988^*

∆GE -6.45095^* -6.55665^* 0.91775

∆GE/GDP -7.45167^* -9.44442^* -0.93974

∆GE/P -7.25474^* -8.18954^* -1.09127

Note: the null hypothesis is that the variable is non-stationary. ^*, ^**and ^*** denote order of integration at 1%, 5% and 10% level respectively. ^Ω assumes individual unit root process under the null hypothesis; ^Ф assumes common unit root process under the null hypothesis.

Probabilities for Fisher tests are computed using an asymptotic Chi-square distribution while other tests assume asymptotic normality. Source: Author’s computations.

The results of ADF-Fisher test (implemented with a trend and no trend) in Panel A of Table 2 indicate that all the variables used in the study are not stationary in levels. In other words, they are integrated of the first order and thus have a unit root. The same can be said about the PP-Fisher tests which indicate that the variables are stationary in first difference. The ADF and PP-type test are thus consistent. In the Im, Pesaran &

Shin Tests, all the variables have a unit root except GDP which tends to indicate that it is neither stationary in levels or first difference.

In Panel B of Table 2, the assumption is that there is a common unit root process under the null hypothesis. All the variables tend to be stationary at first

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difference, when tests are conducted by when both a linear trend, and constant and a linear trend are included.

In the Breitung tests however, real GDP and real GDP per capita tend not be stationary whether in levels or first difference. A combination of the results in both panels of Table 2 suggests that the variables employed are integrated of order (1).

Consequently, the results are generally consistent. The test for long run equilibrium relationship shows that there exists a long-run relationship among the variables (the results are not presented to conserve space). In the presence of cointegration, estimations using the series in their levels are not out of place.

The long-run estimates are next presented, with a view to determining the relationship between public expenditure and economic growth, in addition to examining the impact of public expenditure on economic growth in Sub-Saharan Africa.

The estimated results in Tables 3 are consistent with the prediction of theory.

Consequently, the income elasticities from the Peacock, Goffman and Gupta versions were positive. However, it is only the Peacock estimate that exceeds unity while the Goffman and Gupta versions are less than unity. On the other hand, the estimated income elasticities of the Musgrave and Mann versions are in excess of zero, in line with a priori expectation.

Table 3: Long-run Estimates

Peacock-Wiseman GE GDP Std. Error t-Statistic

1 1.12639^* 0.0922588 2.2090

Gupta GE/P GDP/P Std. Error t-Statistic

1 0.677798^* 0.15873 4.2701

Goffman GE GDP/P Std. Error t-Statistic

1 0.509702^* 0.125168 4.0721

Musgrave GE/GDP GDP/P Std. Error t-Statistic

1 3.25579^* 1.18654 2.7439

Mann GE/GDP GDP Std. Error t-Statistic

1 0.0693956^** 0.034177 2.0305

Note: * and ** denote rejection of the null hypothesis at 1% and 5% level of significance respectively. Source: Authors’ computations

The implication of the estimated income elasticity in the Wagner’s laws tested is that a rise in the value of income (proxied by GDP) results in a more than proportionate rise in expenditure (in the case of the Peacock-Wiseman version) and less than proportionate in the case of the Goffman and Gupta versions respectively.

The result of the Musgrave’s version is particularly interesting. A 1% rise in real income is associated with about 3.3% increase in government share of GDP, implying that government spending tends to rise when there is a rise in the level of income in the economy.

It is also important to note that in all five versions of Wagner’s law tested, the income elasticity is statistically significant at the 1% level with the exemption of Mann’s version which is significant at the 5% level. In all cases, the conclusion is that government expenditures are income elastic in Sub-Saharan Africa.

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All the estimated versions were diagnosed for the most appropriate panel framework, namely whether fixed or random effects. In all cases, the results are in favour of the fixed effects.

A comparison of the impact of government expenditure between higher and lower income countries in Sub-Saharan Africa is next presented. Long run estimates for higher income countries are presented in Table 4 while for the corresponding lower income countries, the results are presented in Table 5.

Table 4: Long-run Estimates (Higher Income Countries)

1 1.16283^* 0.0491785 23.6450

1 −0.823366^*** 0.429378 −1.9176

1 −1.22096^* 0.25354 −4.8156

1 −0.0617221 0.093977 −0.6568

1 0.102216^*** 0.051394 1.9889

Note: ^*, ^** and^*** denote rejection of the null hypothesis at 1%, 1% and 5% level of significance respectively. Source: Authors' computations

Table 5: Long-run Estimates (Selected Lower Income Countries)

1 0.398897^*** 0.239494 1.6656

1 3.60303^* 0.582084 6.1899

1 2.57614^* 0.559574 4.6038

1 0.471278^* 0.150099 3.1398

1 0.0503923 0.0599781 0.8402

Note: ^*, ^**and ^*** denote rejection of the null hypothesis at 1%, 1% and 5% level of significance respectively. Source: Author’s computations.

A cursory examination of the results in Tables 5 and 6 indicates that in the long run, the impact of real income on government expenditure in higher income countries tend to be inversed in comparison with lower income countries in SSA.

Specifically, with the exemption of the Peacock-Wiseman, and the Mann’s versions which indicate a positive relationship between income and growth, the Gupta, Goffman and Musgrave versions indicate that there is an inverse relationship between income and public expenditure, in this study.

Nevertheless, a negative relationship between GE per capita and GDP per capita, in the Gupta version, does not happen in other groups of countries, because the increase of real GDP per capita usually increases consumption per capita (both private and public), and other components of Public Expenditure per capita, as seen in

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Guisan(2013) and other studies. Besides, It is surprising the negative result, in the Goffman version, between real GE and GDP per capita, because usually increases of GDP per capita correspond to countries with increase of real GDP and thus it implies increase of GE if, as usual, the percent of GE on GDP is rather stable. The negative result of the Musgrave version may hold in some countries, because although GE/P and GE increases, the percentage of GE on GDP may not always increase with GDP/P.

In contrast, all the versions of Wagner’s law tested indicate that for lower income countries in SSA, there is a positive and statistically significant relationship (except in the case of the Mann’s version) between income and growth. The implication is that incomes in lower income countries of SSA tend to induce higher government spending than in the higher income countries in the sub-region. It therefore is plausible to conclude that for poorer countries in the sub-region, higher growth (in real terms) is inextricably linked or associated with the growth in public spending. As such the crucial role of the public sector in galvanizing the economy is not in doubt.

6. Conclusion and Implications

In this study, the validity of Wagner’s Law was investigated for 10 selected countries in Sub-Saharan Africa. Five versions of the Wagner’s law in the empirical literature were tested, using annual time series real data for the period 2005-2014.

Panel cointegration techniques were used to investigate the interaction between growth and public expenditure. A long-run equilibrium relationship between national income and government expenditure was found. Irrespective of the version of the Wagner’s law tested, the empirical results suggest that there is a long-run equilibrium relationship between government expenditure and economic growth. This conclusion is corroborated by the individual cross section results, where in majority of cases, the null hypothesis of no cointegration is rejected.

The estimated long-run equations indicate that the income elasticities from the Peacock, Goffman and Gupta versions were are positive and statistically significant.

While the estimated Peacock model exceeds unity, the Goffman and Gupta versions are less than unity. On the other hand, the estimated income elasticities of the Musgrave and Mann versions are in excess of zero, in line with the expectation of theory.

With the exemption of the Peacock-Wiseman, and the Mann’s versions which indicate a positive relationship between income and growth, the Gupta, Goffman and Musgrave versions do not provide empirical support to that relation.

Importantly, all the versions of Wagner’s law tested indicate that for lower income countries in SSA, there is a positive and statistically significant relationship (except in the case of the Mann’s version) between income and growth. The implication is that incomes in lower income countries of SSA tend to induce higher government spending than in the higher income countries in the sub-region. It therefore is plausible to conclude that for poorer countries in the sub-region, higher growth (in real terms) is inextricably linked or associated with the growth in public spending. As such the crucial role of the public sector in galvanizing the economy is not in doubt.

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