Download 1. Driving factors of male employment in African countries

1. Driving factors of male employment
in African countries
John C. Anyanwu1,2
Abstract
The issue of employment is currently one of the greatest development challenges
facing countries globally, including those in Africa. In 2011, the global male
employment-to-population was estimated at about 72.7% compared to the
female employment-to-population ratio of only 47.9%. For Africa as a whole,
the employment-to-population ratio for males was estimated at about 69.2%
compared to a ratio for females of only 39.2%. In addition to analyzing the
characteristics of male employment in Africa, this paper empirically studies its
key drivers (proxied by the male employment-to-population ratio for the age
group 15–64 over the period 1991–2009), using cross-sectional data. The results suggest that for all-Africa estimation, quadratic (squared) levels of real per
capita GDP, greater access to credit by the private sector, more education, and
higher male share of the population increase male employment while higher level
of real GDP per capita, higher government consumption expenditure, urban
share of the population, and being a net oil-exporting country tend to lower it.
In Sub-Saharan Africa, our results indicate that higher domestic investment,
greater access to credit by the private sector, more education, and higher male
share of the population increase male employment, while higher government
consumption expenditure, greater openness of the economy, urban share of the
population, and being a net oil-exporting country tend to lower it. However,
North Africa presents a different picture. The North Africa sample results indicate
that while the quadratic (squared) element of democracy, greater access to credit
by the private sector, inflation, and greater openness of the economy increase male
employment; the level of real GDP per capita, the level of democracy, increased
inflow of foreign direct investment, and being a net oil-exporting country tend
to lower male employment in the subregion. The policy implications of these
results are discussed.
Key words: Male employment-to-population ratio; female employment-topopulation ratio; determinants; Sub-Saharan Africa; North Africa.
JEL classification: J16, J21, J64, J68, I32, C33, E24, O55.
1. Professor John C. Anyanwu is a Lead Research Economist in the Development
Research Department, Chief Economist Complex, The African Development Bank
(AfDB), Temporary Relocation Agency, BP 323, 1002 Tunis-Belvedere, Tunisia. Email:
[email protected].
2. The views expressed here are those of the author and in no way reflect those of the
AfDB or its Executive Directors.
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Journal statistique africain, numéro 16, mai 2013
1. Driving factors of male employment in African countries
Résumé
La question de l’emploi est actuellement l’un des grands défis au développement
que doivent relever les pays du monde, y compris ceux d’Afrique. En 2011,
tandis que le ratio emploi masculin-population était estimé à 72,7 % au niveau
mondial, le ratio emploi féminin-population plafonnait à 47,9 % seulement.
Dans toute l’Afrique, le ratio emploi masculin-population n’est que de 69,2 %
alors que le ratio emploi féminin-population s’établit à 39,2 %. L’article analyse les caractéristiques de l’emploi chez les hommes en Afrique et en étudie
empiriquement les principaux déterminants (sur le ratio emploi masculinpopulation du groupe d’âge 15–64 ans et sur la période 1991–2009) à partir
d’une base de données transversale. Nos résultats montrent que, sur l’ensemble
de l’Afrique, des niveaux quadratiques de PIB réel par habitant, un plus grand
accès au crédit pour le secteur privé, un meilleur niveau d’éducation et une proportion plus importante d’hommes dans la population améliorent la situation
de l’emploi chez les hommes ; par contre, la situation a tendance à se dégrader
avec l’accroissement du PIB réel par habitant, l’augmentation des dépenses de
consommation du gouvernement, une plus forte proportion de citadins dans la
population et le fait que le pays soit exportateur net de pétrole. Nos résultats se
présentent comme suit : en Afrique subsaharienne, la situation de l’emploi chez les
hommes s’améliore en fonction d’un certain nombre de facteurs – augmentation
des investissements dans le pays, facilité d’accès au crédit pour le secteur privé,
qualité du système éducatif, forte proportion d’hommes dans la population – et
a tendance à se dégrader lorsque les dépenses de consommation du gouvernement
sont élevées, l’économie plus ouverte, la proportion de citadins plus importante
dans la population totale, et quand le pays est un exportateur net de pétrole. En
Afrique du Nord cependant, l’élément quadratique de la démocratie, un plus
grand accès au crédit de la part du secteur privé, l’inflation, ainsi qu’une ouverture accrue de l’économie améliorent la situation de l’emploi chez les hommes,
mais celle-ci se dégrade avec le niveau du PIB réel par habitant, le niveau de
démocratie et l’afflux accru d’investissements étrangers directs, et lorsque le
pays est un exportateur net de pétrole. L’auteur examine les conséquences de ces
résultats en termes de politiques.
Mots clés : Ratio emploi masculin–population ; ratio emploi féminin–population ; déterminants ; Afrique ; Afrique sub-saharienne ; Afrique du Nord.
Classification JEL : J16, J21, J64, J68, I32, C33, E24, O55.
The African Statistical Journal, Volume 16, May 2013
13
John C. Anyanwu
1.INTRODUCTION
The issue of employment has grown in prominence on national and global
development agendas in recent times, given its socio-economic cum political
implications. Though the employment challenge has its own dimensions,
it scourges countries worldwide regardless of their stage of socio-economic
development. Thus, employment is currently a global policy issue: employment increases economic growth; promotes political and social stability; positively affects progress toward the Millennium Development Goals (MDGs)
and poverty reduction generally. It also leads to greater social equality and
more efficient resource allocation; increased productive potential; and low
dependency ratio (Anyanwu 2012; Anyanwu and Erhijakpor 2012; World
Bank 2012a). In 2011, the male employment-to-population ratio, globally,
was estimated at about 72.7% compared to a female employment-to-population ratio of only 47.9%. For Africa as a whole, the male employmentto-population ratio was estimated at about 69.2% compared to a female
employment-to-population ratio of only 39.2%. While estimates for SubSaharan Africa stood at 70.4% (male) to 58.8% (female), the gender gap
was more pronounced in North Africa. Women in North Africa faced an
employment rate of only 19.6% (compared to the global average of 47.9%),
the second lowest of all regions and subregions in the world – and against a
figure of 68% for the men in the subregion during the same year.
What factors are driving male employment in Africa and its key components? In addition to analyzing the characteristics of male employment in
Africa, this paper empirically studies the key drivers (proxied by the male
employment-to-population ratio for the age group 15–64 over the period
1991–2009), using cross-sectional data. It also draws out important policy
implications for African countries. The model is estimated by feasible generalized least squares (FGLS) method, with subregional and oil-fixed effects.
A deeper understanding of the key determinants of male employment in
Africa is crucial for implementing effective policies to make Africa’s labor
market more inclusive and promote gender equality in employment so as
to reap its benefits in the shortest time possible.
The next section of the paper summarizes the evidence on the characteristics
of male employment-to-population ratios, an indicator of how effectively
a country utilizes its male productive potential. The third section reviews
some relevant empirical literature. The fourth section presents the model
and data, while section five presents the cross-country regressions of the key
determinants of male employment for the entire continent, Sub-Saharan Africa
and North Africa. The last section concludes with policy recommendations.
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Journal statistique africain, numéro 16, mai 2013
1. Driving factors of male employment in African countries
2.
CHARACTERISTICS OF MALE EMPLOYMENT IN AFRICA
Low employment is a global problem
As noted above, the employment problem is currently a global phenomenon.
Figure 1 demonstrates the relationship between male (malesq22012) and
female employment ratios in OECD countries during the second quarter
of 2012. It shows that the problem is most acute in countries like Greece,
Spain, Hungary and Italy, for both male and female employment – and
also Turkey for female employment. However, the problem is also serious
in Belgium, France, the Euro Area and EU generally, among others. Yet,
employment, including for males, is critical for economic development (see
Figure 2 for the positive correlation between male employment (empmrnew)
and economic growth in Africa, for example).
80
Figure 1: Relationship between male and female employment ratios
in OECD countries, Q2-2012
Switzerland
70
Korea
Norway
New Zealand
Chile
Australia
Netherlands
Japan
Canada
Israel
OECD - Total Austria
United States
G7
Czech Republic
United Kingdom
Sweden
Luxembourg Germany Denmark
Estonia
Slovak Republic Finland
European Union
Poland
Slovenia
Euro area Portugal
France
Belgium
Ireland
Italy
Hungary
60
Turkey
50
Male employment ratio in Q2 2012
Iceland
Mexico
Greece
30
Spain
40
50
60
Female employment ratio in Q2 2012
malesq22012
70
Fitted values
Source: OECD database.
The African Statistical Journal, Volume 16, May 2013
15
John C. Anyanwu
80
70
60
Burkina Faso
Ethiopia
Madagascar
Nigeria São Tomé & Príncipe
Eritrea
Seychelles
Benin
Togo
Zimbabwe
Uganda
Central African Republic
Cape Verde
Burundi Côte d’Ivoire Gambia
Malawi
Namibia
Guinea
Tunisia
Chad
Comoros
Cameroon Mauritius
South Africa
Guinea...Bissau
Angola
Swaziland
Congo. Dem. Rep.
Ghana Mozambique
Zambia
Egypt
Libya
Kenya
Botswana
Congo. Rep.
Algeria
Equatorial Guinea
Rwanda
Liberia
Mali
Lesotho
Tanzania
Gabon
Niger
Mauritania
50
Male employment ratio
90
Figure 2: Positive correlation between male employment ratios and
economic growth in Africa, 1991–2011
Sudan
0
5
10
Real GDP Growth Rate
(mean) empmrnew
15
20
Fitted values
Sources: ILO and World Bank databases, ILO (2012a), World Bank (2012b).
Male employment ratio relatively high in Africa but far below that of
South Asia; however, it fell in all regions between 1991 and 2011
In 2011, the South Asia region recorded the highest average male employment ratio (at about 78.5%) (Figure 3). While the male employment ratio
for the whole of Africa was relatively high at 69.3%, that of Sub-Saharan
Africa was slightly higher, at 70.8%. Africa’s performance was pulled down
slightly by North Africa’s average of only 67.8%. However, as the figure
shows, male employment ratios fell between 1991 and 2011 in all regions.
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Journal statistique africain, numéro 16, mai 2013
1. Driving factors of male employment in African countries
Figure 3: Male employment ratios by global regions, 1991 and 2011
South-East Asia
& the Pacific
Developed Economies
& European Union
Sub-Saharan Africa
East Asia
Africa
World
Latin America &
the Caribbean
South Asia
Middle East
North Africa
0
20
2011
40
60
80
100
1991
Sources: ILO database, ILO (2012a).
Figure 4 presents the average employment ratio for men and women in
African countries in 1991 and 2011. It shows that employment was significantly higher for men. For the continent as a whole in 2011, the male
employment ratio stood at about 69%, compared to 39% for women (1.8
times higher than for women). However, these average figures hide huge
disparities between North Africa and Sub-Saharan Africa (Figure 5). In
addition, there is greater gender inequality in employment in North Africa
than in Sub-Saharan Africa, across all age groups (Figures 6 and 7).
The African Statistical Journal, Volume 16, May 2013
17
John C. Anyanwu
Figure 4: Male and female
employment ratios in Africa,
1991 & 2011
Figure 5: Male and female
employment ratios in North
Africa & Sub-Saharan Africa,
2011
80
80
70
70
60
60
50
50
40
40
30
30
20
20
10
10
0
1991
2011
0
Females (age 15+) Males (age 15+)
Females (age 15+)
North Africa
Males (age 15+)
Sub-Saharan Africa
Sources: ILO database, ILO (2012a)
Figure 6: Male and female
employment ratios in North
Africa, 1991 & 2011
Figure 7: Male and female
employment ratios in SubSaharan Africa, 1991 & 2011
100
100
80
80
60
60
40
40
20
20
0
1991
2011
0
1991
2011
Females (age 15+)
Males (age 15+)
Females (age 15+)
Males (age 15+)
Females (age 25+)
Males (age 25+)
Females (age 25+)
Males (age 25+)
Females (age 15-24)
Males (age 15-24)
Females (age 15-24)
Males (age 15-24)
Sources: ILO database, ILO (2012a, b).
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Journal statistique africain, numéro 16, mai 2013
1. Driving factors of male employment in African countries
As Figure 8 demonstrates, the average male employment-to-population ratio
in North Africa (57%) is far greater than that for women (18%). This huge
gender gap in employment in North African countries largely explains the
generally low levels of employment ratios in the subregion. For the African
continent as a whole, the employment ratio averaged 45% for males against
38% for females between 1991 and 2011. In Sub-Saharan Africa, the employment ratio averaged 71.3% for males compared to 57.3% for females.
In 2011, the employment ratio in North Africa was 68% for men, compared to just 20% for women, aged 15 and above. In Sub-Saharan Africa
in the same year, the employment ratio was 71% for men, compared to
59% for women.
Male adult employment ratios are also higher than those for the youth,
but much more so in North Africa, where it stands at more than double
that of the youth male (Figure 9). Indeed, in 2011, while the ratio of male
adult–to-youth employment in Sub-Saharan Africa was 1.7, it was 2.2 in
North Africa.
Figure 8: Male and female employment ratios in Africa’s major
subregions, 1991–2011 (%)
80
70
60
50
40
30
20
North Africa – females
Sub-Saharan Africa – females
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
10
North Africa – Males
Sub-Saharan Africa – Males
Sources: ILO database, ILO (2012).
The African Statistical Journal, Volume 16, May 2013
19
John C. Anyanwu
Substantial variation in male employment ratios across African
countries
There were substantial variations in male employment ratios across African
countries between 1991 and 2011. Figure 10 also shows that a number of
smaller African economies have relatively higher male and female employment ratios compared to richer, oil-exporting and North African economies.
Figure 9: Male adult and youth employment ratios in Africa, 1991–
2011
100
80
60
40
North Africa – male youth
North Africa – male adult
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
20
Sub-Saharan Africa – male youth
Sub-Saharan Africa – male adult
Sources: ILO database, ILO (2012a, b).
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Journal statistique africain, numéro 16, mai 2013
1. Driving factors of male employment in African countries
60
70
80
Burkina Faso
Ethiopia
Madagascar
Equatorial
Guinea
Nigeria
São Tomé & Príncipe
Seychelles
Benin
Eritrea
Togo
Central African Republic Zimbabwe
Uganda
Côte d’Ivoire
Burundi
Gambia
Malawi
Cape Verde
Namibia
Chad
Mauritius
Tunisia
Guinea
Comoros
Cameroon
Guinea...Bissau
South Africa
Swaziland
Zambia
Angola
Mozambique
Ghana
Egypt
Kenya
Congo. Dem. Rep.
Libya
Botswana
Congo. Rep.
Somalia
Rwanda
Algeria
Mali
Liberia
Lesotho
Tanzania
Gabon
Mauritania
Niger
50
Male employment ratio
90
Figure 10: Relationship between average male and female
employment ratios in African countries, 1991–2011
Sudan
0
20
40
Female employment ratio
(mean) empmrnew
60
80
Fitted values
Sources: ILO database, ILO (2012a).
Falling male employment trend in Africa generally
Male employment has fallen generally since 1991 across the continent, but
the decline has been dramatic in some countries. These include Niger, Benin, Rwanda, Lesotho, Kenya, and Burundi (Figure 11). A similar picture
is evident in the OECD countries between 2009 and 2012 (Figure 12).
The African Statistical Journal, Volume 16, May 2013
21
John C. Anyanwu
Ethiopia
Burkina
Faso
São Tomé
& Príncipe
Ethiopia
African Republic
Guinea...Bissau
Uganda Central
Malawi
Madagascar
Burkina
Côte d’Ivoire
Guinea
Namibia
Benin
Swaziland
Faso
Equatorial Guinea
Burundi
Zimbabwe
Comoros
Tunisia
Chad
EritreaGambiaNigeria São Tomé
Angola
Libya
Mauritius
Seychelles
&
Príncipe
Togo Cape Verde
Zambia
Egypt South Africa
Central African Republic
Botswana
Guinea...Bissau
Ghana
Cameroon
Uganda
Malawi
Congo. Rep.
Côte d’Ivoire
Mozambique
Guinea
Namibia
Benin
Swaziland
Somalia
Congo.
Dem.
Rep.
Burundi
Comoros
Tunisia
Chad
Algeria
Gambia
Kenya
Mali
Angola
Libya
Mauritius
Cape Verde
Liberia
Zambia
Egypt South Africa
Botswana
Ghana
Cameroon
Rwanda
Congo. Rep.
Mozambique
TanzaniaSomalia
Congo. Dem. Rep.
Algeria
Kenya
Lesotho
Mali
Gabon Liberia
Madagascar
Equatorial Guinea
Nigeria
Eritrea
Seychelles
Togo
60
70
80
70
80
90
Zimbabwe
50
60
Mauritania
Sudan
Mauritania
50
Male employment
ratio in 2010
Male employment
ratio in 2010
90
Figure 11: Male employment ratios did not generally increase
between 1991 and 2010 in African countries
50
Sudan
Rwanda
Tanzania
Niger
60
Niger
50
Lesotho
80
90
empmrnew2010
Fitted values
60
70
80
Male employment ratio in 1991
90
Gabon
70
Male employment ratio in 1991
Sources: ILO database, ILOempmrnew2010
(2012a).
Fitted values
80
70 80
Mexico
OECD - Total
60 70
50 60
50
Norway Iceland
Korea
New Zealand
Mexico
Netherlands
Japan
Australia
Turkey
Male employment ratio in Q4 2009
Spain
50
Chile
Canada
Austria
Norway
United
States
United Kingdom
Korea
Czech Republic
Luxembourg
G7
Germany
Australia
New Zealand
Chile
OECD
Total
Denmark
Sweden
Netherlands
Estonia
Japan
Slovak Republic
Canada
Poland
TurkeyUnion Austria
Finland
European
Israel
United
States
Slovenia
Euro area
United Kingdom
Czech Republic
PortugalG7
Luxembourg
Belgium
Germany
France
IrelandSweden
Denmark
Hungary
Estonia
Slovak Republic
Poland
Italy
Finland
European Union
Slovenia
Euro area
Spain
Portugal
Belgium
Greece
France
Ireland
Hungary
55Italy
60
65
70
Israel
50
Male employment
ratio in Q2
2012
Male employment
ratio
in Q2 2012
Figure 12: OECD countries: Male employment ratios on a decline
Iceland
between 2009 and 2012
55
malesq22012Greece
Fitted values
60
65
70
Male employment ratio in Q4 2009
malesq22012
75
75
Fitted values
Sources: OECD database, ILO (2012a).
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Journal statistique africain, numéro 16, mai 2013
1. Driving factors of male employment in African countries
Overall, a substantial gender inequality persists in African countries. As
shown in the distribution of the difference between average male and female
employment ratios (malefemalediffemp) between 1991 and 2011, the gap
between the two is not symmetrical but positively distributed, indicating
gendered social exclusion (Figure 13).
100
0
50
Frequency
150
Figure 13: Distribution of average male minus female employment
ratios in Africa, 1991 and 2011
0
20
malefemalediffemp
40
60
Source: ILO database, ILO (2012a).
3.
REVIEW OF THE LITERATURE
The literature suggests that the key determinants of male employment
relate to a country’s stage of economic development, access to credit by the
private sector, globalization, demographic factors, macroeconomic factors,
education, cultural and social norms, perceptions and expectations, and
political systems.
It is hypothesized that as countries develop, the male labor force participation generally increases. Böserup (1970) suggests that men’s greater access
to education and technologies leads to their displacing women from the
labor force during the early stages of a country’s development. However,
as development increases and women gain more access to education and
technologies, the female labor force participation increases.
The African Statistical Journal, Volume 16, May 2013
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John C. Anyanwu
Another well-established hypothesis for this phenomenon focuses on income
and substitution effects. As development occurs, households’ unearned
incomes rise, reducing the incentive for women to work outside the home.
The negative impact of rising incomes on women’s labor force participation
is termed the “income effect,” since greater household income implies that
households are able to afford more female leisure time. On the other hand,
the “substitution effect” works in the opposite direction – as female wages
rise, more women have the incentive to enter the labor market (Goldin
1995; Mammen and Paxson 2000; Bloom et al. 2009; Chaudhuri 2009;
Tam 2011). The stylized U-shaped curve holds for overall male employment in African countries. It can be seen in Figure 14, which depicts the
relationship between economic development (as captured by real GDP per
capita) and the male employment ratio across African countries between
1991 and 2011.
80
70
60
Male employment ratio
90
Figure 14: Africa: U-shaped correlation between male employment
ratio and GDP per capita, 1991–2011
Ethiopia
Burkina Faso
Madagascar
Nigeria
Benin
Eritrea
Central African Republic Togo
Zimbabwe
Uganda
Côte d’Ivoire
Burundi
Gambia
Cape Verde
Malawi
Guinea
Namibia
Chad
Comoros
Guinea...Bissau
Cameroon
Swaziland
Ghana
Zambia
Angola
Egypt
Mozambique
Kenya
Congo. Rep.
Congo. Dem. Rep.
Liberia
Rwanda
Mali
Equatorial Guinea
Seychelles
Tunisia
Mauritius
South Africa
Libya
Botswana
Algeria
Lesotho
Tanzania
Gabon
50
Niger
Mauritania
Sudan
5
6
7
Log of Real GDP Per Capita
(mean) empmrnew
8
9
Fitted values
Sources: ILO and World Bank databases, ILO (2012a), World Bank (2012b).
The male employment ratio in Africa partly reflects the natural resource endowment structure, being low in fossil fuel-rich and mineral-rich economies.
For example, Algeria, Egypt, Libya, and Sudan have very low employment
ratios relative to their income levels. The same applies to countries like
Gabon, Mauritania, and Tanzania, among others.
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Journal statistique africain, numéro 16, mai 2013
1. Driving factors of male employment in African countries
Recent empirical work reveals that foreign direct investment (FDI) and
international trade can generate employment opportunities for both men
and women (Richards and Gelleny 2007; see also ILO 2012c). According to
Oostendorp (2009), in the long term, FDI may increase male employment
at the expense of females; alternatively, women may be pushed down the
production chain into subcontracting work. Furthermore, FDI may widen
the gender gap as technical training is offered primarily to men, thereby
“improving male technical knowledge and reducing women’s access to technology and employment” (Parpart et al. 2000). Also, by benefiting men,
FDI may reinforce existing gender inequalities (Ward 1984; Ernesto 2011).
Policies designed to increase trade and FDI inflows reduce state revenues,
and therefore reduce the government’s capacity to provide social services.
Because women are often the key beneficiaries of these services, economic
integration can act against men’s employment in many dimensions.
In a recent study, Tseloni, Tsoukis, and Emmanouilides (2011) reveal a greater
participation of women in paid employment than men in more populous
countries, with a greater share of women in their populations, more equal
income distribution, and higher growth rates. However, such countries
also evince a lower level of economic development, democracy ratings or
international capital mobility (i.e., current account surplus or deficit/GDP).
The banking sector is the key conduit for financial intermediation in an
economy. Thus, access to credit by the private sector enhances the productive
capacity of businesses. Businesses and enterprises with adequate credit access
have greater potential to grow in terms of sales, revenues, and operations; to
expand investments; and to create more employment. Indeed, greater access
to credit by the private sector fosters growth because it means that fewer
firms will be financially constrained and more investment projects will be
undertaken. This in turn should foster employment and economic growth.
Financial development also contributes to building and improving productivity of assets held by poor people, creating opportunities for entrepreneurship
and new investments, improving efficiencies in product and factor markets,
while stimulating private sector development and job creation (see Gandelman and Rasteletti 2012). Also, as IFC (2012) notes, improving access to
finance helps firms expand their operations, which can have a positive effect
on the quality and number of jobs created. The effects tend to be greatest
for smaller firms. In a recent review of seven evaluations that focused on
the provision of loans and advisory services to MSMEs and households, the
IFC (2012) found that private sector access to credit has mainly positive
The African Statistical Journal, Volume 16, May 2013
25
John C. Anyanwu
effects on job creation. The report concludes that increasing access to loans
helped firms to expand, facilitating the hiring of more workers.
According to the findings of Niemi and Lloyd (1981), inflation has an independent, positive impact on female labor force participation. As a result
of women’s lower cash holdings relative to men, it is posited that it possible
that women are less adversely affected than men by increases in inflation
(Cardoso 1992).
Another macroeconomic variable is domestic investment. Domestic investment is a key source of employment, wealth creation and innovation.
Without it, countries are unable to spur the growth of their economies or
to sustain the reduction of poverty over the long term. Where domestic
investment is low, the productive capacity of the economy fails to increase.
This results in lower rates of economic growth, fewer opportunities for the
poor to improve their livelihoods, and lower rates of job creation. As the
ILO (2011) shows, investment growth has a strong and positive effect on
employment creation. The results show that a 1 percentage point increase
in the investment growth rate produces a 0.12 percentage point increase in
employment growth. In addition, results from ILO (2012c) show that both
private and public investment rates positively and strongly affect employment.
The literature on the relationship between government consumption expenditure and employment focuses on the transmission mechanisms and the
results of policy actions. According to the real business cycle (RBC) model,
an increase in government consumption expenditure (financed by current
or future lump-sum taxes) has a negative wealth effect which should lead
to a decline in consumption and hence a rise in labor supply. The rise in
labor supply leads, in equilibrium, to a lower real wage, higher employment
and higher output (Ramey 2011a, 2011b; Wilson 2012). However, the
New Keynesian models differ in that they generally assume some degree of
stickiness, that is, that wages and prices do not adjust instantly to economic
shocks (Christiano, Eichenbaum, and Rebelo 2011).
Earlier, the Keynesian IS-LM model had asserted that consumption rises in
response to an increase in government consumption expenditure. According to the proponents of this position, consumers exhibit non-Ricardian
behavior in the IS-LM model and consumption is a function of current
disposable income. Thus, the impact of an increase in government consumption expenditure depends on how the government consumption expenditure
is financed, with the fiscal multiplier increasing in line with the extent of
deficit financing (see Wilson 2012). Indeed, Wilson (2012) concluded that
26
Journal statistique africain, numéro 16, mai 2013
1. Driving factors of male employment in African countries
though the impact depends on the environment in which expenditures are
made, the effects of government investment are potentially greater than
other types of government expenditure, a finding which was also attested
by Kehoe and Serra-Puche (1982).
Aiyagari, Christiano, and Eichenbaum (1990) also find that persistent
changes in government consumption have contemporaneous employment
and output effects which are larger than those due to transitory changes.
Fatás and Mihov (2002) maintain that increases in government consumption
lead to increases in employment. Also, the ILO (2012c) finds that government expenditures on public wages and salaries, social benefits, and social
transfers positively and significantly affect employment, while government
expenditures on interest payments significantly reduce employment.
As Sakellariou (2011) explains, changes in educational attainment and in the
demographic profile of the population, explain changes in the female–male
gap in labor force participation, especially in rural communities. Changes
in education and literacy help to explain the variation in male and female
labor force participation within a country (Ogawa and Akter 2007; World
Bank 2010; Gallaway and Bernasek 2004) and in employment in US multinational enterprises (MNEs) in Africa (Asiedu 2004).
Campa et al. (2011) analyze the extent to which the gender culture affects
the gender gap in employment. They show that the index of gender culture,
based on firms’ attitudes as well as female literacy and education, is significant in explaining the gender gap in employment in Italian provinces. As
Forsythe et al. (2000) have noted, “rapid development is particularly likely
to be accompanied by greater gender rigidity in a country with a tradition of patriarchal institutional arrangements.” Indeed, Böserup (1970),
Moghadam (1994), Shukri (1996), Psacharopoulos and Tzannatos (1989)
have found that Muslim and Latin American countries – i.e. countries with
strong socio-religious views about women’s role in the public sphere and the
workplace – are more likely to be characterized by entrenched patriarchal
institutions (see also Antecol 2000; Fernández 2010; Fernández and Fogli
2005; Fernández, Fogli, and Olivetti 2004).
In addition, the seminal work by Hegre et al. (2001) supports a quadratic
relationship between democracy and employment. Democracy could also
unleash women’s labor market potential and open up the decision-making
process to the less privileged, including women, resulting in redistributive
policies that would benefit these groups. Democracy could also increase
women’s employment by increasing expenditures on social programs. We
The African Statistical Journal, Volume 16, May 2013
27
John C. Anyanwu
therefore expect that democracy will not have significant positive effect on
male employment.
4.
THE MODEL AND DATA
This section focuses on the econometric analyses of the determinants of
male employment in Africa. We use the cross-sectional time series data
covering 48 African countries to empirically study the key drivers of male
employment in the continent during the period 1991 to 2009. The variable
that proxies male employment (male employment-to-population ratio for
the age group 15-64 over the period) was used as dependent variable. The
level of economic development, along with other control variables, acted
as independent variables.
Independent Variables
Level of economic development
To control for the level of economic development, we include a nation’s real
gross domestic product (GDP) per capita measured in terms of constant
2000 dollars. We also include the square of real GDP per capita in order
to determine whether a non-monotonic relationship exists between development and male employment. The quadratic term tests Böserup’s (1970)
assertion that the gap between men and women increases at intermediate
levels of economic development but subsequently narrows after a nation
has achieved a certain level of economic development.
We also include economic growth (real GDP growth rate) separately to
control for the possibility that an economic decline or slowdown might have
adverse effects on male employment independent of the level of development.
Institutionalized democracy
It has been hypothesized that democracy increases equity in gender relations as women and men become empowered through the political process.
This is because it is assumed that democratic regimes have greater respect
for human rights, relative to authoritarian regimes. We use the measure
democracy from the Polity IV Project, in which a country’s level of democracy is ranked along a 21-point spectrum, ranging from -10 for fully
institutionalized autocracies to +10 for fully institutionalized democracies,
based on research conducted at the Center for International Development
and Conflict Management, University of Maryland. Since it is intuitively
plausible that democratic countries encourage male employment, we expect
28
Journal statistique africain, numéro 16, mai 2013
1. Driving factors of male employment in African countries
that increasing levels of democracy will act to increase women’s employment
more than men’s. Democracy is fitted as a quadratic function for capturing
possible average across country non-linear effects.
Access to credit by the private sector
As noted earlier, access to credit by the private sector enhances the productive capacity of businesses, leading to greater potential to grow in terms
of sales, revenues, and operations. Moreover it expands investments and
creates more employment. We therefore include banking system’s credit to
the private sector as a percentage of GDP. The higher the value of credit to
the private sector, the more resources firms have at their disposal for investment, expansion and entrepreneurship, all of which increase employment.
Macroeconomic factors
Three indicators are used to measure macroeconomic conditions: (i) the
inflation rate (percentage change in CPI), (ii) domestic investment rate, and
(iii) government consumption expenditure relative to GDP. With respect
to inflation’s effect on employment, the current literature is inconclusive.
Some experts contend that inflation hurts women more than men, since
women are disproportionately represented among the poor and thus unable to protect their consumption levels in the presence of rising inflation.
However, others assert that inflation will not harm women as much as men
due to their lower cash holdings; further still, others contend that inflation
may actually benefit women by increasing labor force participation. We
expect inflation to have a negative effect on men’s employment.
The second indicator of macroeconomic condition is a nation’s domestic
investment measured as a percentage of GDP. The higher the value of
investment rate, the more resources a government and the private sector
ostensibly have at their disposal to spend on economic and social programs,
including investments for employment creation.
The third macroeconomic condition is government consumption expenditure measured as a percentage of GDP. The higher the value of government
consumption expenditure, the less resources the government has at its
disposal to spend on economic and social programs, including investments
for employment creation for both men and women.
Demographic factors
To measure the effect of key demographic variables on men’s employment,
three indicators are used: (i) population growth rate, (ii) ratio of male to
female population of those aged 15 to 64, and (iii) the share of urban areas
The African Statistical Journal, Volume 16, May 2013
29
John C. Anyanwu
to total population. Increasing population growth is expected to narrow the
gender equality in employment. Inclusion of the sex population ratio ensures
that changes in the population ratio due to changes in the sex population
ratio are properly accounted for. In light of the above, the population sex
ratio is expected to have a positive effect on the male employment. More
specifically, increases in the male–female population ratio, a measure of
labor supply, are expected to lead to increases in male employment. Thus,
the higher the proportion of men in a nation’s population, the higher will
be the employment of men. On the other hand, living in an urban area is
associated with an increase in access to labor markets and formal employment opportunities. Men, like their female counterparts, have access to more
economic opportunities in urban areas than in rural areas. This is because
urban labor markets offer a wide variety of occupations, from manufacturing and services to clerical activities. Thus, increased urbanization rate is
expected to lead to higher levels of male employment.
Globalization
In order to control for the effect of globalization on male employment,
trade openness of the economy and foreign direct investment (FDI) are
included as explanatory variables and are measured as a percentage of GDP.
A nation’s openness to trade is defined as the sum of net exports of goods
and services as a percentage of GDP. An increase in openness is hypothesized
to augment male labor force participation thereby increasing male employment. In addition, if the export sector is primarily capital intensive, then
male employment is expected to decrease as a result of differential access
to productive resources.
As authors like Oostendorp (2009) have argued, FDI is assumed to be
positively associated with higher employment, especially for women. On
the other hand, some authors have argued that FDI can have a positive
effect on male employment by serving to reinforce existing gender inequalities in the access to the labor market and the gender division of labor.
Indeed, in the predominantly agricultural nations of Africa, men have a
greater advantage in producing export crops, compared with women who
predominately produce crops for subsistence and local consumption. According to this hypothesis, greater access to export channels through FDI
would further widen the gender gap. Many African countries are today
blessed with abundant natural resources, which have been attracting huge
FDI. However, most natural resources sectors such as minerals, are enclave
and capital-intensive sectors, and operate to the advantage of men, thus
widening the gender gap in employment.
30
Journal statistique africain, numéro 16, mai 2013
predominantlypredominantly
agricultural nations
of Africa,
menofhave
a greater
advantage
in producing
agricultural
nations
Africa,
men have
a greater
advantage export
in producing
crops,
compared
with
women
who
predominately
produce
crops
for
subsistence
and
local
crops,
compared
with
women
who
predominately
produce
crops
for
subsistence
and
ter advantage in producing export
consumption.
According
to
this
hypothesis,
greater
access
to
export
channels
through
FDI
would
consumption.
According
to
this
hypothesis,
greater
access
to
export
channels
through
FDI
crops for subsistence
and local
1. Driving factors of male employment in African countries
further
widen
the gender
gap.
African
countries
are today
blessed
with abundant
natural
further
widen
theMany
gender
gap. Many
African
countries
are today
blessed with
abundant
xport channels through
FDI
would
resources,natural
which
have been
attracting
hugeattracting
FDI. However,
mostHowever,
natural resources
sectors
such assectors s
resources,
which
have been
huge FDI.
most natural
resources
day blessed with abundant
are as
enclave and
sectors, and operate
theoperate
advantage
of men,
thus of me
minerals,
arecapital-intensive
enclave and capital-intensive
sectors,toand
to the
advantage
st natural resourcesminerals,
sectors such
widening
the
gender
gap
in
employment.
widening
the
gender
gap
in
employment.
ate to the advantage of men, thus
Level of general education
Education tends to broaden one’s views, reduce ethnocentricity, and increase one’s
flexibility
to one’s
accept
newreduce
customs
andreduce
norms.
As increase
such, the
level
Education
tends
to broaden
views,
ethnocentricity,
and
one’s
flexibility
to flexib
Education
tends
to broaden
one’s views,
ethnocentricity,
and
increase
one’s
of
education
attained
by
the
general
population
plays
an
important
role
accept
new customs
and customs
norms. As
the As
level
of education
attained
by the
general
accept
new
andsuch,
norms.
such,
the level of
education
attained
by the g
y, and increase one’s
flexibility
to
in increasing
access
toplays
the an
labor
market
and
employment
opportunities.
population
plays
an
important
role
in
increasing
access
to
the
labor
market
and
employment
population
important
role
in
increasing
access
to
the
labor
market
and
emplo
ducation attained by the general
Indeed, menopportunities.
with higher
levels
of education
are
more
likely
to enter
the likely
opportunities.
Indeed,
men
with
higher
levels
of
education
are
more
likely
to
enter
the
labor
Indeed,
men
with
higher
levels
of
education
are
more
to
enter
the
he labor market and employment
labor market,
especially
in
urban
areas,
which
may
reflect
their
higher
wage
market,
especially
in
urban
areas,
which
may
reflect
their
higher
wage
premiums
and
higher
market, especially in urban areas, which may reflect their higher wage premiums and
re more likely to enter the labor
premiums cost
and
opportunity
cost
of(see
being
inactive
(see
also2007).
Ogawa
opportunity
ofhigher
being inactive
(see also
Ogawa
and
Akter
2007).
opportunity
cost
of being
inactive
also
Ogawa
and
Akter
igher wage premiums
and higher
and Akter 2007).
007).
Level of general
education
Level
of general education
Subregional and
oil effects and oil effects
Subregional
Subregional and oil effects
We
five
subregional
to capture
subregional
effects.
In
addition,
We
include
the fivedummies
subregional
dummies
to capture
subregional
effects.
addition, to c
We include
includethethe
five
subregional
dummies
to capture
subregional
effects.
In toIncapture
the
effects
of
net
oil exporters,
we exporters,
add
two oil
dummies
representing
oil dummies
exporters
net oil and
effects
of net
oil
weexporters,
add two
dummies
representing
net and
oil exporters
addition,
tothe
capture
the
effects
of net
we addnet
two
nal effects. In addition,
to capture
importers.
importers.
representing
net oil exporters and net oil importers.
nting net oil exporters
and net oil
The
TheModel
Model The Model
Based on the above review and following the frameworks posited by Tseloni,
Based on the Based
above on
review
and following
the following
frameworks
by Tseloni,
and Tsouk
the above
review and
the posited
frameworks
positedTsoukis
by Tseloni,
Tsoukis and Emmanouilides
(2011),
Choudhry,
Marelli,
and Signorelli
Emmanouilides
(2011),
Choudhry,
Marelli,
and
Signorelli
(2012),
and
Eastin
and
Prakash
Emmanouilides
(2011),
Choudhry,
Marelli,
and
Signorelli
(2012),
and
Eastin
and P
posited by Tseloni,
Tsoukis
andEastin and Prakash (2013), the relationship that we want to
(2012),
and
(2013),
the
relationship
that
we
want
to
estimate
can
be
written
as:
(2013),
the
relationship
that
we
want
to
estimate
can
be
written
as:
(2012), and Eastin
and Prakash
estimate
can be written as:
Kommentar [SJ3]: In the equation
as:
below, if possible, position the2(1) further
2
1ME
log(
 log( credit
 4 (democ
log MEit   i log
log(it rgdp
rgdp
democit2)it 
)  5 (demo
it ) log(
 i itright,
1level
 the
) 
rgdp
credit itit)) 45((democ
2 log(
it )
3 log(
it ) 
to
with
the right
hand2 3 rgdp it ) 
2
margin.
X it it)   7 ( Z it )   it
 5(democ
)   4 (democit )  
) 7( Zit6)( 
6 ( X it ) it 
(i  1,...., N ; t (i1
,.....,
T ),........
(1)
1,....,
N ; t  .......(
1,.....,1T) ),...............(1)
where
is the
measure
male
countryini at
time
t; ii is
atime
fixed
effect
ME isofthe
measure
maleinemployment
in
country
i at
time t;
ai
a fixed effect ref
i is reflecting
whereME
ME
iswhere
the
measure
of employment
maleofemployment
country
at
time
differences
between
countries;

1
is
the
elasticity
of
male
employment
with
respect
realrespect
time
differences
between
countries;

1
is
the
elasticity
of
male
employment
a fixed
effect reflecting time differences between countries; b1 is the towith
me t; i is a fixed is
effect
reflecting
capitatoincome
in 2000,
rgdp;in22000,
is
thergdp;
male
elasticity
respectintowith
quadratic
elasticity
ofreal
male
employment
with
respect
capitawith
income
per
capita
income
employment
2 isto
thereal
maleper
employment
elasticity
respect to qu
e employment withper
respect
2000,
rgdp;
b2
is
the
male
employment
elasticity
with
respect
to
quadreal
per
capita
GDP;

3
is
the
coefficient
of
access
to
credit
by
the
private
sector,
credit;

4
is the
real
per
capita
GDP;

3
is
the
coefficient
of
access
to
credit
by
the
private
sector,
credit; 
elasticity with respect to quadratic
ratic
real
per
capita
GDP;
b3
is
the
coefficient
of
access
to
credit
by
the
coefficient
of
democracy,
domec;

5
is
the
coefficient
of
the
quadratic
of
democracy;
X
is
the
coefficient of democracy, domec; 5 is the coefficient of the quadratic of democracy; X
the private sector, credit; 4 is the
private
sector,
credit;
b4 inflation
is including
the coefficient
of(inf),
democracy,
domec;
b5 (%
is(inv),
control
variables,
including
(inf),inflation
domestic
investment
of GDP)
trade (inv)
control
variables,
domestic(%
investment
of GDP)
quadratic of democracy; X is the
the
coefficient
of
the
quadratic
of
democracy;
X
is
the
control
variables,
openness
(open),
foreign
direct
investment
(%
of
GDP)
(fdi),
primary
school
enrollment
ratio
openness
(open),
foreign
direct
investment
(%
of
GDP)
(fdi),
primary
school
enrollmen
tment (% of GDP) (inv), trade
including
inflation
(inf
),
domestic
investment
(%
of
GDP)
(inv),
trade
(educ),
urban
population
share
(urban),
population
growth
rate
(popg),
male–female
population
(educ), urban population share (urban), population growth rate (popg), male–female pop
, primary school enrollment ratio
openness
(open),
e (popg), male–female
population
foreign direct investment (% of GDP) (fdi), primary
school enrollment ratio (educ), urban population share (urban), population Page
growth
| 18 rate (popg), male–female population ratio (popratio); Z
represents subregional and oil effects dummies used as fixed effects; and
e is an error term that includes errors in the male employment measure.
We use the North African dummy with its separate estimation to check
if indeed, North Africa is different.
The African Statistical Journal, Volume 16, May 2013
31
Page | 18
Pa
John C. Anyanwu
Data for these variables are largely drawn from the World Bank’s WDI
Online database, except as indicated in Appendix 1. The Feasible Generalized Least Squares (FGLS) regressions with subregional and oil fixed-effects
were estimated to investigate the determinants of male employment. Table
1 provides detailed descriptions of the raw dataset.
Table 1: Descriptive statistics of main regression variables (excluding
dummies), 1991–2009
Variable
Observations
Mean
Standard
Deviation
931
960
950
895
916
877
950
942
962
623
1007
1007
988
966
71.77
1065.43
19.40
15.82
-3.57
92.66
20.78
75.10
3.88
36.72
38.23
2.33
1.03
3.93
10.04
1573.73
21.60
8.00
23.17
1175.11
11.13
38.56
9.45
26.36
17.31
1.14
0.06
7.68
Male employment ratio
Real GDP per capita
Credit to private sector-GDP
Govt consumption expd-GDP
Democracy
Inflation
Domestic investment-GDP
Openness
FDI-GDP
Education
Urban population share
Population growth
Male–female population ratio
Economic Growth
Note: These are raw data before the log and other transformations.
Source: Author’s calculations.
5.
RESULTS AND ANALYSIS
Table 2 presents the results of estimating the male employment equation (1).
Level of economic development
In our model, the coefficient associated with real GDP per capita is found
to be negative and statistically significant in the all-Africa and North Africa
samples. To test the hypothesis that real GDP per capita has a non-monotonic
relationship with male employment, the squared real GDP per capita is
included as an explanatory variable. The quadratic term is positive in sign
and significant at the 1 percent level in only the all-Africa sample.
32
Journal statistique africain, numéro 16, mai 2013
1. Driving factors of male employment in African countries
Table 2: FGLS estimates of the determinants of male employment
(with subregional and oil-fixed effects)
Variable
Africa
Sub-Saharan Africa
North Africa
Real GDP per capita
Real GDP per capita2
Democracy
Democracy2
Inflation
Govt. consumption
expd-GDP
Domestic investmentGDP
Openness
FDI-GDP
Education
Urban population share
Population growth
Male-female population
ratio
Credit to private sectorGDP
Net oil exporters
Net oil importers
North Africa
Southern Africa
Central Africa
East Africa
West Africa
Real GDP Growth
Constant
-14.993 (-3.32***)
1.127 (3.39***)
0.036 (1.58)
1.344 (1.92)
-9.729 (-3.17***)
0.030 (1.31)
-0.00001 (-0.03)
0.0001 (0.17)
-2.081 (-2.62**)
0.446 (2.07**)
0.200 (2.61**)
-0.379 (-5.52***)
-0.476 (-6.87***)
-0.083 (-0.39)
0.035 (0.76)
-0.007 (-0.52)
0.027 (0.36)
0.124 (7.07***)
-0.254 (-5.59***)
-0.968 (-1.52)
0.079 (1.65*)
-0.025 (-1.80*)
0.087 (1.15)
0.114 (6.59***)
-0.338 (-7.90***)
-0.548 (-0.85)
-0.087 (-0.95)
0.146 (3.52***)
-0.246 (-1.62*)
0.176 (2.72**)
0.586 (1.39)
-0.905 (-0.35)
0.216 (2.59**)
0.260 (3.11**)
-0.137 (-1.17)
0.080 (4.14***)
-8.210 (-7.42***)
0.067 (3.29***)
-11.771 (-9.86***)
0.198 (6.36***)
-11.425 (-1.75*)
-5.558 (-3.25***)
5.079 (3.22***)
-5.220 (-3.15**)
0.729 (0.44)
0.066 (0.83)
105.389 (6.08***)
12.881 (8.28***)
-1.000 (-0.78)
6.227 (4.89***)
0.022 (0.28)
44.431 (5.16***)
0.019 (0.16)
99.162 (3.16**)
Log likelihood
Wald chi2
Prob > chi2
N
-2008.122
287.47
0.0000
569
-1803.161
317.52
0.0000
512
-106.5155
1219.41
0.0000
57
Note: t-values are in parentheses; ***= 1% significant level; **=5% significant level; *=10%
significant level.
These results provide evidence of a U-shaped relationship between real GDP
per capita and male employment in Africa as a whole. Thus, these results
suggest that although higher levels of real GDP per capita are negatively
The African Statistical Journal, Volume 16, May 2013
33
John C. Anyanwu
associated with male employment, the effect is not constant. Rather, above
a certain point, higher levels of real GDP per capita act to increase male
employment, holding other factors constant. This relationship suggests
that the marginal effect of real GDP per capita exhibits increasing returns
for male employment. This finding supports Böserup’s (1970) assertion of
a curvilinear relationship but this U-shaped relationship contradicts the
findings of Tseloni, Tsoukis, and Emmanouilides (2011), and Eastin and
Prakash (2013). We note, however, that real GDP per capita (both level and
quadratic) is not significantly related to male employment in Sub-Saharan
Africa, while the quadratic element is not significant in the North Africa
sample – hence was dropped.
Institutionalized democracy
Institutionalized democracy is negative and statistically significant only in
the North African sample, against earlier findings such as those of Tseloni,
Tsoukis, and Emmanouilides (2011), and Eastin and Prakash (2013). The
quadratic term included to determine whether democracy has a nonlinear
effect on male employment is positive in sign and statistically significant in
the North African sample also, indicating a U-shaped relationship between
democracy and male employment in North Africa, holding other factors
constant. Institutionalized democracy (both level and quadratic) does not
significantly affect male employment in Africa as a whole, nor in Sub-Saharan
Africa – hence the quadratic term was dropped in both results.
Access to credit by the private sector
The credit variable has a positive and statistically significant effect on male
employment in the all-African, Sub-Saharan African and North African
estimations. These results are consistent with the findings of IFC (2012),
thus underscoring the huge role of access to finance in employment creation in Africa.
Macroeconomic factors
It is only in North Africa that rising inflation is found to be positively
associated with increasing levels of male employment. This is consistent
with some of the results of Eastin and Prakash (2013). This finding may be
linked to the fact that a reduction in real wages increases male labor force
participation, as men enter the workforce in greater numbers to supplement
household earnings.
As shown in Table 2, a nation’s domestic investment rate is found to be
positively and significantly associated with male employment only in the
Sub-Saharan African estimation. Its effect is insignificant in the all-African
34
Journal statistique africain, numéro 16, mai 2013
1. Driving factors of male employment in African countries
and North African estimations. This could be attributed to wastages, inefficiency, and corruption associated with investment projects in many African
countries. Indeed, investment in white-elephant, unproductive activities,
remains a development challenge confronting the continent.
Related to the issue of wastages is that of government consumption expenditures in Africa. Our results show that government consumption expenditures
negatively and significantly affect male employment in both the all-African
and Sub-Saharan African estimations. These results are also in conformity
with the crowding-out theories prevalent in the literature.
Globalization
Trade openness is negative in sign and statistically significant in the SubSaharan African estimation but it is positive and statistically at the 1 percent level in the North African case. The North African results support the
view that increasing levels of exports relative to imports may increase male
employment and that an external market orientation may further enhance
job opportunities for men. This suggests that labor-intensive export sectors
dominate the capital-intensive sectors in North Africa, while the opposite
is likely to be the case in Sub-Saharan Africa.
On the other hand, the FDI–GDP ratio was found to have a positive but
insignificant effect on male employment in both the all-African and SubSaharan African estimations. However, it has a negative but statistically
significant effect on male employment in North Africa. Our findings,
therefore, do not support the proposition that the inflow of foreign direct
investment enhances male employment in Africa. In fact, we found that it
lowers male employment in North Africa.
Education
The education variable has a positive and statistically significant effect
on male employment in the all-African, Sub-Saharan African, and North
African estimations. This is consistent with Asiedu’s findings (2004). This
supports the hypothesis that education tends to broaden one’s awareness
of cultures and social norms that exist in industrial countries where both
men and women are in most circumstances entitled to the same freedoms
and opportunities.
Demographic factors
Increasing urbanization rates are found to be negatively and highly significantly associated with falling male employment in the all-African and
Sub-Saharan African estimations. As seen in Table 2, this effect is statistically
The African Statistical Journal, Volume 16, May 2013
35
John C. Anyanwu
significant at the 1 percent level in both cases. However, the variable is positive but insignificant in the North African case.
Furthermore, our results suggest that rising population growth rates have
a negative but statistically insignificant effect on male employment in all
three sample groups.
The ratio of male to female population has a positive and statistical significant effect on male employment in the all-African and Sub-Saharan African
samples. Thus, the higher the proportion of men in a nation’s total population, the higher the level of male employment in that country. However,
in North Africa, the male-to-female population ratio has a negative but
insignificant effect on male employment.
Economic growth
In view of the various arguments about the effects of growth or development, we also entered the real GDP growth, in addition to real GDP per
capita. The results show that real GDP growth was insignificant for three
samples: all-Africa, Sub-Saharan Africa, and North Africa. These results
were consistent with those of the ILO (2011) for developing economies.
Subregional and oil effects
The subregional fixed effects, which shift the intercepts, imply that Southern African countries, followed by those in East Africa, have lower male
employment compared to Central and West Africa.
Our results also show that net oil-exporting countries generally have systematically lesser male employment compared to net oil-importing countries in
Africa. This suggests that, holding other factors constant, net oil-exporting
countries experience lower levels of male employment than net oil-importing
countries. In this sense, our results also suggest that oil-exporting nations
have failed to fully utilize their huge oil revenues to create adequate jobs
for their citizens.
6.
CONCLUSION AND POLICY RECOMMENDATIONS
Our empirical estimates, using available cross-sectional data over the period
1991 and 2009 suggest that in the all-African estimation, quadratic levels of
real per capita GDP, greater access to credit by the private sector, more education, and higher male share of the population increase male employment
while higher level of real GDP per capita, higher government consumption
36
Journal statistique africain, numéro 16, mai 2013
1. Driving factors of male employment in African countries
expenditure, urban share of the population, and being a net oil-exporting
country tend to lower it. In Sub-Saharan Africa, our results indicate that
higher domestic investment, greater access to credit by the private sector,
more education, and a higher male share of the population increase male
employment while higher government consumption expenditure, greater
openness of the economy, urban share of the population, and being a net
oil-exporting country tend to lower it. However, North Africa is different. The North African results indicate that while the quadratic element
of democracy, greater access to credit by the private sector, inflation, and
greater openness of the economy increase male employment; the level of
real GDP per capita, the level of democracy, increased inflow of foreign
direct investment, and being a net oil-exporting country tend to lower male
employment in the subregion.
What are the implications of these results for African countries? Given our
finding that government consumption expenditure reduces male employment across Africa and that domestic investment is not male employmentpromoting in the overall sample and particularly in North Africa, achieving
investment effectiveness must remain an active goal of governments. All
actors, from governments to civil society, must share responsibility for making investment more productive, efficient and effective, and for preventing
one of its main breakdowns: corruption. Political will and good governance, strengthening accountability and transparency, as well as enlarging
civil society space as a “watch dog” are critical in this direction. Attention
should be paid to the design, implementation, and monitoring and evaluation phases of projects and programs. At the design stage, the aim should
be to create achievable and quantifiable targets and to have all-stakeholder
ownership through the collaboration of governments, the private sector,
civil society, and other development agencies. All stakeholders must follow
through to ensure that projects and programs are implemented as designed.
Also, stakeholders must ensure that those projects and programs are regularly
monitored and evaluated against indicators established in the design phase
and agreed on by the development partners.
Productive and efficient domestic investment requires the development of
coordinated, objective, and transparent processes for decision-making based
on thorough and rigorous cost-benefit analysis. Adoption of high-level best
practice principles to inform the development of these processes will help
African governments to achieve this. Those broad principles should include
the following key elements: a nationally coordinated approach to the development of significant strategic projects and programs; the promotion
of competitive markets; decision-making based on rigorous cost-benefit
The African Statistical Journal, Volume 16, May 2013
37
John C. Anyanwu
analysis to ensure the highest economic and social benefits to the nation over
the long term; a commitment to transparency at all stages of the decisionmaking and project implementation processes; and a public sector financial
management regime with clear accountabilities and responsibilities.
To reduce waste, fraud, and corruption, all African countries should embrace and fully implement Transparency International’s (2009) “Integrity
Pacts,” which embody rights and obligations to the effect that neither side
in contracts will pay, offer, demand or accept bribes, or collude with competitors to obtain the contract, or while carrying it out. At the same time,
efforts to reform the fiscal system for consolidation by both the executive
and legislative arms of government are imperative to reduce government
consumption expenditure to avoid waste, corruption and crowding out
resources for public sector investment and employment creation.
The current study suggests that, holding other factors constant, increasing
levels of FDI are associated with decreasing male employment in North Africa
while having an insignificant effect in the other samples. Thus, to promote
male employment and ensure men have complete access to productive
resources, African countries should regulate the inflow of foreign capital to
ensure labor-intensive industries are not displaced by globalization. Further,
to protect against threats to individual basic rights, the government should
mandate that MNCs adhere to core labor standards, as provided by the
International Labor Organization (ILO). Since labor-intensive employment
represents a viable channel through which job-seekers are able to realize gains
in real wages and social capital, the protection of these industries should be
a policy priority for African countries.
We find that access to credit by the private sector is essential to increasing
men’s employment across the countries of Africa. African governments should
start encouraging entrepreneurship and access to financing, for both men
and women. The continent needs entrepreneurs ready and able to exploit
new opportunities. Men and women need training in entrepreneurship and
to be encouraged to take risks and start businesses and subsequently become
employers themselves (WEF 2012a, 2012b); however, some deliberate and
focused credit targeting will be of immense help in this direction. In fact,
the promotion of domestic investment through improved credit conditions
for small and medium enterprises, for example, would yield significant gains
in employment.
Effective policies that invest in the human capital of the workforce are needed.
Policies that promote the upskilling, better training and education for the
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Journal statistique africain, numéro 16, mai 2013
1. Driving factors of male employment in African countries
low-skilled workforce are imperative. Educational reforms that conform
to industry needs will also help to address the skills mismatches existing in
many African countries.
African governments need to dialogue with large employers as to how best
to create employment for the men (and women) through strategic skills
planning, skills development, and skills matching. Addressing the skills
mismatch in the short-run will require improved training programs and
closer links between tertiary and vocational educational institutions on the
one hand, and the private sector on the other. Training programs should
include on-the-job initiatives targeting those already working, as well as
graduates with a general education who lack specific work skills. In addition,
governments need to develop innovative public–private partnerships and
the opportunities for collaboration among large employers, governments
and other relevant stakeholders such as higher and vocational educational
institutions to transform institutional structures and strengthen the region’s
economy (Ncube and Anyanwu 2012).
Indeed, stronger university–industry linkages are essential. This can be
achieved by including private sector representatives in national education
and training policy bodies and on academic boards involved in curriculum
development. No doubt, this will also facilitate private sector funding for
research, scholarships, internships, and apprenticeships. Our results also
point to the need for enhanced government efforts, not just to increase
human capital, especially for the men, but more importantly to reform the
educational curriculum for better quality education and skills.
We have shown in this study that being a net oil-exporting country decreases
men’s employment in Africa. Thus, efficient management of oil and other
natural resources in Africa requires actions throughout the value chain.
In particular, a new natural resources management framework is needed for
better governance, sectoral linkages, economic growth and human, capacity
and infrastructure development – with strong parliamentary legislation,
oversight, and representation throughout the resources value chain.
Key effective natural resources management practices will require the following measures:
•
Enhanced good governance, especially as it relates to the way public money
is spent, is a crucial factor in turning a natural resource boom into an
opportunity for growth and development, job creation, and gender
The African Statistical Journal, Volume 16, May 2013
39
John C. Anyanwu
•
•
•
•
•
•
equality in Africa. Prioritizing the public investment management
system is imperative. Checks and balances need to be maximized
through parliaments.
Integrating the extractive sector into national development frameworks –
Revenue optimization needs to be integrated with the downstream sector.
Value-addition and natural resources–industry linkages are paramount.
There are many opportunities for improving positive linkages between
the natural resources sector and development initiatives.
Reinforcing institutional capacity and building strong and capable
institutions.
Sound fiscal policy and diversification of the economy, while using windfall
taxes to protect against reneging on taxation.
Full disclosure of terms of natural resources contracts is needed, as well as
activating third-party brokers such as development partners (e.g. AfDB)
and NGOs to ease information availability and reduce information
asymmetry.
African natural resource-rich countries should stop the practice of
entering into bilateral development agreements with extractive companies
for generous concessions in extraction contracts. Consequently, all contracts
and terms should be legislated in the substantive law and implemented
as such.
EITI adherence: African countries’ company and financial laws should
be reformed to require all extractive companies to use the EITI template
in their annual financial reports by law.
Without doubt, sustainable inclusive growth and development as well as
inclusive governance should be the basis for policymakers and leaders in
Africa to bridge the transformation between pain of current unemployment
time bomb, especially in North Africa and net oil-exporting countries, and
the promise of the future.
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1. Driving factors of male employment in African countries
APPENDIX 1: Description of Variables
Variable
Source
Employment ratios
World Bank/International Labor
Organization (ILO) database
World Development Indicators
World Development Indicators
Polity IV Project
World Development Indicators
World Development Indicators
World Development Indicators
World Development Indicators
World Development Indicators
World Development Indicators
World Development Indicators
World Development Indicators
Per capita GDP (constant 2000 US dollar)
Credit to the private sector
Democracy
Trade openness ((imports + exports)/GDP)
School enrollment rate
Inflation (annual percentage change in CPI)
Urban population ratio
Population
Domestic investment
FDI
Government consumption expenditures
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The African Statistical Journal, Volume 16, May 2013
45
2. Alcohol consumption patterns:
Do neighborhoods matter?
A multilevel analysis of alcohol consumption
patterns in Uganda
Nazarius Mbona Tumwesigye,1 Richard Muwonge, 2 and Rogers Kasirye3
Abstract
This paper presents a re-analysis of data on patterns of alcohol consumption with
adjustment for cluster effects. The outcomes of interest were the consumption of
alcohol at least three times a week and consuming 12 or more drinks in a single
day. Multilevel regression analysis was applied using STATA V.10. Results show
that there is a significant variation in the likelihood of drinking frequently at
village level (p<0.01), but that this is confounded by the average proportion of
drinkers. The variation in the likelihood of heavy drinking remained significant
after controlling for background characteristics of respondents and village-level
prevalence of drinking and unemployment. Cluster effects have an influence on
the frequency and amount of alcohol consumption but their inclusion in statistical
models does not affect the influence of established factors. Cluster analysis provides
information on other correlates of frequent and heavy alcohol consumption.
Key words: cluster effects, village effects, logistic regression, intracluster correlation, multilevel models, rho.
Résumé
Cet article présente une nouvelle analyse des données sur les schémas de consommation d’alcool, avec ajustement pour effets de grappe, et compare ces résultats avec
ceux de la précédente analyse. Les résultats concernent la consommation régulière
d’alcool au moins trois fois par semaine et l’absorption de douze boissons ou plus en
une seule et même journée. L’analyse de régression multi-niveaux a été appliquée
à l’aide de STATA V.10. Les résultats révèlent l’existence d’une variation significative dans la probabilité de boire fréquemment au niveau du village (p<0.01),
mais cette variation se perd dans la proportion moyenne des consommateurs. La
variation dans la probabilité d’une forte consommation d’alcool reste significative
après neutralisation de certains facteurs comme le niveau d’instruction des personnes
1. Department of Epidemiology and Biostatistics, School of Public Health, Makerere
University College of Health Sciences, Mulago Hill, P. O. Box 7072, Kampala, Uganda.
Tel: +256-782-447771, e-mail: [email protected]
2. International Agency for Research on Cancer (IARC), 150 cours Albert Thomas,
69008 Lyon, France. Email: [email protected]
3. Uganda Youth Development Link, P.O. Box 12659, Kampala, Uganda. Email:
­[email protected]
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Journal statistique africain, numéro 16, mai 2013