Determinants of remittances in Southern African Development
Community (SADC)
Nathalie Marishea Vereen
Research assignment presented in partial fulfilment
of the requirements for the degree of
Master of Development Finance
at Stellenbosch University
Supervisor: Mr Pieter Opperman
December 2016
ii
Declaration
I, Nathalie Marishea Vereen, declare that the entire body of work contained in this research
assignment is my own, original work; that I am the sole author thereof (save to the extent explicitly
otherwise stated), that reproduction and publication thereof by Stellenbosch University will not
infringe any third party rights and that I have not previously in its entirety or in part submitted it for
obtaining any qualification.
N.M. Vereen
8 September 2016
Copyright © 2016 Stellenbosch University
All rights reserved
iii
Acknowledgements
My purpose as a development policy practitioner has been enriched by this study; I find that I look
at challenges through a different lens in order to find solutions. This would not have been possible
without the support and patience of my husband, Irvin, who has helped to carry my load over the
past months and kept me whole. I can now share my newly acquired knowledge and skills. I also
acknowledge my children and cousin with whom I have missed many ‘fun’ weekends and cool
movies. To my close family, thank you for your love and encouragement. To Keagile, thank you for
exposing me to another world and for your great assistance and calm demeanour when it felt my life
had imploded. My sincerest thanks to my supervisor, Pieter Opperman, for his guidance, responsive
feedback and support. Finally, my deepest gratitude to my colleagues who stood in for me over the
past few months to allow me space to complete this work.
iv
Abstract
This research report investigated determinants of remittances to Southern African Development
Community (SADC) countries. Panel data estimation techniques over the period 1990-2014 were
used, focusing on 14 SADC countries, excluding South Africa, as the latter is a remittance-sending
country within the region. The empirical model that was followed tested the official exchange rate,
interest rate, inflation and human capital as determinants of remittance flows to a home country. By
means of this research, it was found that human capital is positively linked and statistically significant
in determining remittances. The interest rate is significant to determine remittances and thus
migrants are interested in investment opportunities in their home countries. Human capital
expenditure in SADC is directed towards primary education and thus migrants are mainly low skilled.
Should SADC governments invest more towards secondary and tertiary education, the high volume
of youthful SADC labour could have access to higher incomes in host countries that offer higherskilled employment and possibly remit more towards investment purposes.
Key words – determinants of remittances, SADC, human capital, interest rate
v
Table of Contents
Determinants of remittances in Southern African Development Community (SADC)
i
Declaration
ii
Acknowledgements
iii
Abstract
iv
List of acronyms and abbreviations
vii
CHAPTER 1 INTRODUCTION
1
1.1
BACKGROUND
1
1.2
PROBLEM STATEMENT
4
1.3
RESEARCH OBJECTIVE
5
1.4
RESEARCH QUESTION
5
1.5
RESEARCH DESIGN AND METHODOLOGY
5
1.5.1
Empirical model
5
1.6
CHAPTER OUTLINE
6
1.7
SUMMARY
7
CHAPTER 2 LITERATURE REVIEW
8
2.1
THEORETICAL FRAMEWORK
8
2.2
EMPIRICAL REVIEW
12
2.3
SUMMARY
17
CHAPTER 3 MIGRATION AND REMITTANCES TO SADC
18
3.1
INTRODUCTION
18
3.2
WHERE DO AFRICAN MIGRANTS WORK?
18
3.3
SADC MIGRATION PATTERNS AND TRENDS
20
3.4
REMITTANCES TO SADC
23
3.5
SUMMARY
26
CHAPTER 4 METHODOLOGY AND RESEARCH DESIGN
27
4.1
DATA
27
4.2
EMPIRICAL MODEL
28
4.3
THEORETICAL UNDERPINNING
29
4.4
ESTIMATION TECHNIQUE
30
4.5
SUMMARY
31
CHAPTER 5 RESULTS
32
5.1
EMPIRICAL RESULTS
32
5.2
SUMMARY OF MAIN FINDINGS
32
CHAPTER 6 CONCLUSION AND RECOMMENDATIONS
34
6.1
CONCLUSION
34
6.2
RECOMMENDATIONS/POLICY IMPLICATIONS
34
6.3
LIMITATIONS OF THE STUDY AND OPPORTUNITIES FOR FURTHER RESEARCH 35
REFERENCES
36
vi
LIST OF TABLES
Table 5.1: Determinants of Remittances
33
LIST OF FIGURES
Figure 1: SADC Member States
3
Figure 2: Long-run trends in skilled emigration rates
19
Figure 3: Migration destination countries for 25+ years for 1990 and 2000
20
Figure 4: International migration stock for SADC between 1990 and 2010
21
Figure 5: SADC country expenditure on education between 1990 and 2012 (excluding SA)
22
Figure 6: Remittance flows to SADC from 1990-2014
25
Figure 7: Personal remittances received by SADC as a percentage of GDP, 1990-2014
25
Figure 8: Official exchange rate fluctuations in SADC: 1990-2014
27
Figure 9: Remittances to SADC: 1990-2014
28
vii
List of acronyms and abbreviations
ADB
African Development Bank
DAC
Development Assistant Committee
FDI
Foreign Direct
GDP
Gross domestic product
GLS
Generalised least squares
GNI
Gross national income
ILO
International Labour Organisation
IMF
International Monetary Fund
M2
Money supply
MDG
Millennium Development Goals
MIC
Middle-Income Country
ODA
Official Development Assistance
OECD
Organisation for Economic Cooperation and Development
OEIS
Own exchange import system
REM
Remittances
RPW
Remittance Price Worldwide
SADC
Southern African Development Community
SDG
Sustainable Development Goals
SSA
Sub-Saharan Africa
1
CHAPTER 1
INTRODUCTION
1.1
BACKGROUND
The Financing for Development Conference in Addis Ababa, Ethiopia in July 2015, reiterated the
critical importance for developing countries to own their development objectives and for the
developed world to meet the existing commitment of providing 0.7% of their gross national income
(GNI) towards development. Globally, official development assistance (ODA) has decreased and for
Middle-Income Countries (MIC) such as South Africa (SA) and Botswana, the conference confirmed
the gradual out-phasing of ODA as we know it. The 2002 Monterrey Consensus on Financing for
Development convinced international development actors to recognise the potential role that
remittances, amongst other flows such as philanthropy and private investment, could play in
economic growth and development and good traction has developed to monitor remittance flows and
their utilisation in both host and recipient countries.
International remittances, representing the funds sent to home countries by people working in the
region and abroad, have increased substantially over the past decades. To date, remittances
represent one of the largest sources of external finance for developing countries. A development
cooperation report (2014) of the Organisation for Economic Cooperation and Development (OECD)
measured US$351 billion worth of remittances sent to developing countries in 2012, which was
significantly larger than official development assistance and foreign direct investment (FDI) received.
Nyamongo, Misati, Kipyegon & Ndirangu (2012) reported US$440 billion in remittances globally
during the 2010 year and estimated that US$325 billion was channelled to developing countries. The
World Bank (2013a, b) estimates global remittances to exceed $707 billion by 2016. Remittances
are therefore globally acknowledged as an important capital source for developing countries (OECD,
2006; Fayissa, 2008; Giuliano & Ruiz-Arranz, 2009; Rao & Hassan, 2011, OECD, 2014).
The annual Index of Global Philanthropy and Remittances by the US-based Hudson Institute
illustrates the continuous changes and increased importance of these flows to the international
development landscape. Although ODA flows are rapidly decreasing, private capital investment,
philanthropy and remittances from developed and traditional donor countries to developing countries
and emerging economies are substantial and significant – private flows, remittances and
philanthropy from the Development Assistant Committee (DAC) countries of the OECD totalled $577
billion (Hudson Institute, 2013); thus governments are no longer primary funders of development.
However, these figures illustrate the remittances flowing through formal channels and mostly from
legal (in the host country) migrant workers. The World Bank and other sources have consistently
acknowledged this reality and Mohapatra & Ratha (2011) estimated that the remittance flows from
undocumented migrants via informal channels might be larger than indicated by the official data,
while Ncube & Brixiova (2013) estimated a 75 percent under-reporting of these flows. Reasons for
2
informal and undocumented flows could be the cost of remitting and in the case of Sub-Saharan
Africa (SSA), the intra-regional migration patterns. Thus relative close proximity between laboursending and the host country could result in cash being transferred by people.
The World Bank’s Remittance Prices Worldwide (RPW) database is a tool that monitors remittance
prices globally and was established in 2008. Sub-Saharan Africa saw a significant decrease in
remittance cost from 10.21 percent to 9.74 percent in 2015. However, it remains the most expensive
region for remitting (World Bank, 2015). Further, SA remains the most expensive G20 country to
remit from at 16.79% (of every $200 or local currency equivalent).
In June 2009, the Global Remittances Working Group introduced a new “5x5 goal” (World Bank,
2015), supported by the Group of 20 (G20) and Group of 8 (G8) countries, which aimed to reduce
the cost of remitting by five percentage points in five years. Governments, banks and a range of
stakeholders were lobbied over the past years to realise this goal and the RPW database, a World
Bank instrument, monitors remittance prices globally and reports against geographical regions. In
June 2015, then SA Minister of Finance Mr Nene announced that the initial cost of remitting – a
maximum of 25 percent – would be capped at five percent by the Reserve Bank and this reduction
is hugely influenced by relaxing compliance for the Financial Intelligence Centre Act (FICA)
requirement (Mail & Guardian, 2015).
The outlook of the International Monetary Fund (IMF) for Sub-Saharan Africa (2015) estimates that
by 2035, the region will house the biggest working-age population, aged 15-64 years. This population
growth forecast could be beneficial to the aging global world, which is expected to have a significantly
declined working age population by 2050. The IMF (2015) further contemplates that this could pose
a significant opportunity to sub-Saharan Africa to drive and supply the global labour force in future.
With the Post-2015 debates and adoption of the Sustainable Development Goals (SDGs), the means
and capabilities of implementation for developing countries are pertinent and thus the flows of
remittances must be considered by SSA and the global world as a whole when discussing
development financing. SSA has the opportunity to capitalise on its vast labour supply and must
therefore understand what determines remitting and should utilise and benefit from such resources
in the most productive development areas. However, the trend and volume in external capital flows
to SSA are less than for other developing countries such as the Middle East and North Africa
(MENA), South and East Asia, and the Pacific countries. Adenutsi, Aziakpono & Okram (2012) found
that this is due to SSA being largely dependent on ODA, compared to their peers.
While SSA as a sub-region has remained the least recipient of migrant remittances in the world,
Adenutsi et al. (2012) found that the rate of growth in total migrant remittance inflows, including
remittances received by the sub-region relative to population size and international migrant stock
was relatively slow. Adenutsi et al. (2012) sampled 35 SSA countries and found that since the 1980s,
remittances had increased more than 100 percent from US$42 million to US$86 million and exploded
to US$303 million in the 2000s.
3
Southern African Development Community countries1 have traditionally selected South Africa as an
economic migration destination. Truen & Chisadza (2012) confirmed that regional migration
remained pertinent and that migration and remittances were interlinked; the case of Mozambique
illustrates that their tradition of inter-generational migration to SA to work in the mining industry, has
systematically improved the economic status of such households compared to those who remained
home. Further, the same study documents that a survey conducted in 2005 found that remittances
to Zimbabwe provided critical financial resources to struggling households (Truen & Chisadza,
2012).
Figure 1: SADC Member States
Source: SADC official website (http://www.sadc.int/member-states/)
The research report investigates determinants of remittances in SADC countries. Similar to Aga &
Martinez Peria (2014), South Africa is excluded from this study as it is considered a remittance
sending country. There are an estimated 30 million international African migrants, representing
3 percent of the working population in Africa, who sent almost $40 million home in 2010 alone; this
figure represents 2.6 percent of Africa’s GDP (Mohapatra & Ratha, 2011; Ratha, Mohapatra, Özden,
Plaza, Shaw & Shimeless, 2011). According to the World Bank’s Factbook (2016) on migration and
1
Angola, Botswana, Congo (DR), Lesotho, Madagascar, Malawi, Mauritius, Mozambique, Namibia,
Seychelles, South Africa, Swaziland, Tanzania, Zambia and Zimbabwe
4
remittances, there are an estimated 250 million migrants, or 3.4 percent of the global population
(Ratha, De, Plaza, Schuettler, Shaw, Wyss & Yi, 2016). SSA received $32 billion worth of remittance
flows in 2013 and these flows represent an estimated 4 percent of a typical country’s GDP. For at
least ten countries in the region, the flows contribute over 5 percent of their GDP (Aga & Martinez
Peria, 2014).
The migration patterns to exclusively Europe and the United States are changing and South-South
migration represents 39 percent of the total migrant stock, exceeding the South-North migration
(Ratha, et al., 2016). SA is a major economic destination and the estimated value of remittances
flowing into the region is R11.2 billion per annum (FinMark Trust, 2012; Truen & Chisadza., 2012).
According to the SADC Statistics Yearbook, remittances flowing out of the region from 1990 up to
2010 grew from $1.5 billion to $2.5 billion; and inflows are captured for the same period as
$862 million to $2.6 billion respectively (SADC, 2011). The stock of migrants and subsequent
remittance flows hold great potential towards economic growth at a country and regional level,
beyond the consumption-based growth that neglects investment and linked multiplier effects.
1.2
PROBLEM STATEMENT
International remittances are defined as the money and goods which are transmitted to households
of migrant workers through formal channels and it is acknowledged that the flows are also transmitted
through informal methods such as cash carried across borders by either short-term or permanent
migrants (IMF, 2009). This research report focused on the macroeconomic determinants of formal
remittances in SADC countries, excluding South Africa.
The issue of migration and remittance are intertwined and labour movements – skilled or unskilled
labour – are mainly due to political and economic conditions at home, lack of employment
opportunities, poverty or poor living standards and seeking better income (Olivier, 2009).
Segatti & Landau (2011) refer to the “profound economic and political upheaval” (2011: p. 9) during
the 1990s which played a critical role in transforming international migration, specifically regional
migrant flows, to SA. Migration to SA remains an option despite the downturn of the country’s
economic growth outlook. Between 1990 and 2000, SA was transformed in the new “migration hub”
(Segatti & Landau, 2011) and while some African migrants use SA then and now in transit to Europe
or North America, others settle. The SADC region is found to have a high degree of economic
integration between countries and influence remittance behaviour (Van Eyden, et al., 2011). Thus
SA’s economic conditions are integral to the flow of remittances into the region.
A number of researchers have defined the primary macroeconomic factors which impact on the level
of international remittances received by countries as being dependent on both host and home
conditions, such as complementary exchange and interest rates, inflation rates, especially at home
country level, the level of investment in human capital (primary, secondary and tertiary education)
and the requirement of political stability and economic opportunity (El-Sakka & McNabb, 1999;
5
Glytsos, 2005; Gupta, 2005; Adams, 2009; Rapoport & Docquier, 2006; Ahortor & Adenutsi, 2008;
Fayissa, 2008; Giuliano & Ruiz-Arranz, 2009; Singh, Haacker, Lee & Le Goff, 2010; Lim & Morshed,
2015; and Panda & Trivedi, 2015).
Remittances to SSA stood at an estimated US$20 billion in the 1980s and increased to an estimated
US$265 billion in 2007 (Singh et al., 2010). However, during the same period, Asia, the Middle East
and North Africa, Latin America and the Caribbean received significantly larger flows. Thus, SSA
receives the smallest share of remittances at a low five percent of total flows to developing countries
(Singh et al., 2010).The growth rate of remittances to developing countries has decreased due to a
slowdown in growth owing to economic weakness in major developed countries which make up the
primary migration corridors. However a 4 percent increase is expected for 2016-17 and flows to SSA
are estimated to improve by 3.4 percent compared to 1 percent in 2015 (Ratha, et al., 2016).
Few studies have investigated the macroeconomic determinants of remittances in the SADC region.
Given the region’s relative interconnectedness and relatively high degree of economic integration, a
better understanding of what it is that determines that migrants will remit to their home countries,
could increase remittances and allow for policy changes to utilise this resource beyond consumption
and towards regional investment.
1.3
RESEARCH OBJECTIVE
The objective of the research assignment was:

1.4
To examine the determinants of remittances to SADC countries.
RESEARCH QUESTION
What are the macroeconomic determinants of remittances to SADC countries?
1.5
RESEARCH DESIGN AND METHODOLOGY
1.5.1
Empirical model
To test the determinants of remittances, the following model adapted from Adams (2009) is
specified:
log 𝑅𝐸𝑀𝑖𝑡 = ∝ + 𝛽1 𝑙𝑜𝑔𝑂𝐸𝑋𝑖𝑡 + 𝛽2 𝐼𝑅𝑖𝑡 + 𝛽3 𝐼𝑛𝑓𝑙𝑖𝑡 + 𝛽4 𝐻𝐶𝑖𝑡 + εi
(1)
The dependent variable (REM) is personal remittances received by a labour-sending country over
the period of measure. The independent variables for this study were measured at a labour-sending
or home country level: the real interest rate, official exchange rate, inflation rate and human capital
measured as the total expenditure on education.
The variables are defined as follows:
i.
log 𝑅𝐸𝑀𝑖𝑡 = Personal remittances (log) received by the home country 𝑖 and at year 𝑡. This is
the dependent variable.
ii.
𝑙𝑜𝑔𝑂𝐸𝑋𝑖𝑡 = Official exchange rate (LCU per US$, period average) of country 𝑖 at year t.
6
iii.
𝐼𝑅𝑖𝑡 = Real interest rate (percentage) in the labour-sending country 𝑖 at year t.
iv.
𝐼𝑛𝑓𝑙𝑖𝑡 = Inflation at consumer prices (annual percentage) of country 𝑖 at year t.
v.
𝐻𝐶𝑖𝑡 = Human capital is measured as the total government expenditure towards education
(primary, secondary and tertiary) of country 𝑖 at year t.
Panel data was used in this study and this longitudinal data has limitations due to the inconsistent
level of data available for SADC countries. However, it provided aggregated data of remittances over
the 25-year period to analyse determinants of this financial flow. From the 15 SADC countries2, South
Africa was excluded from the analysis based on the relatively high level of migration to SA and its
being a remittance sending country. The data from the World Bank Development Indicators (WDI)
was used to compile the panel dataset and estimate the regressions.
The F-test was used first to test the validity of the fixed-effect models in relation to the pooled
models. For the specified model, the F-test enabled a rejection of the null hypothesis of
homogeneity at 1 percent and thus individual-specific factors determined remittances. The models
applicable are thus either fixed-effect or random effect. The Hausman test’s null hypothesis could
not be rejected and random effects models are specified. A random effects model with general
least squares (GLS) was used.
1.6
CHAPTER OUTLINE
The chapter outline, including this introductory chapter, is divided into six sections:
Chapter 2 provides a literature review based on international and regional evidence on determinants
of remittances.
Chapter 3 focuses on remittances specifically to SADC and provides a narrow contextual
background to the study.
Chapter 4 discusses the research design and methodology.
Chapter 5 presents the empirical results and analysis.
Chapter 6 concludes and provides limitations of this study. It also provides recommendations for
policy and for future research.
2
Angola, Botswana, Congo (DR), Lesotho, Madagascar, Malawi, Mauritius, Mozambique, Namibia,
Seychelles, Swaziland, Tanzania, Zambia and Zimbabwe; excluding South Africa.
7
1.7
SUMMARY
Chapter 1 provided an introduction and background to the study. The problem statement, research
objective and research question were stated as well as the chosen methodology.
8
CHAPTER 2
LITERATURE REVIEW
2.1
THEORETICAL FRAMEWORK
Remittances to developing countries are enjoying increased financial weight as an international
capital flow. The flows have been constant and over the past decades and Africa, as one of the
developing countries, has benefited from its human mobility which resulted in increased migration
patterns and migrant workers thus remitting to their home country, using formal mechanisms (which
is the focus of this study), due to its improved access and for some, improved affordability. Clemens,
Özden & Rapoport (2015) acknowledge that research on remittances is moving beyond the flow, but
increasingly studies the impact of both remittances and migration to comprehend their complexities.
It is, however, acknowledged that no comprehensive theory of remittance determinants has been
developed as yet (Chami, Barajas, Cosimano, Fullenkamp, Gapne & Montiel, 2008; Ncube &
Brixiova, 2013).
People migrate for different reasons and some are driven by political motives, others by economic
drivers, and for some, a combination of these. Whatever the reasons are, they affect the
development process and thus economists and social scientists, amongst others, are contributing
evidence to improve our theoretical understanding of migration and remittances as a result of
migration. Rapoport & Docquier (2006) argue that remittances may be both the “cause and
consequence of migration”, emphasising its interdependence.
The African Development Bank (ADB) refers to remittances as “unrequited, nonmarket financial
transfers between individuals living in different countries, mostly associated with migration” (Ncube
& Brixiova 2013). Although this definition alludes to the informality of African remittance flows, the
Bank acknowledges an improvement in this flow at international and also regional levels,
representing a significant financial resource. It is generally acknowledged that the real volume and
depth of remittances are hugely underestimated and could be double or more than the formal figures
(Ratha, et al., 2011; Ncube & Brixiova, 2013).
Although this research report is narrowly focused on what determines remittances at a macro level,
the theoretical explanations consistently start out on or include the primary microeconomic factors
which are founded in the theory of altruism or self-interest.
The microeconomic theories of remittances are well-researched and consolidated across such
studies and the reasons and uses of remittances at household levels are broadly accepted to fund
and smooth consumption. Lucas & Stark (1985) were first to develop a formal model to explain
remittances of migrants. They emphasised the importance of the family unit in determining
remittances and used the dualistic theories to analyse rural and urban migration and remitting. The
altruistic model wherein the migrant derives utility from the need of those left behind, frames the
theory of pure altruism and the core is the per capita income of the household. Chami, Fullenkamp
9
& Jahjah (2003) refer to the endogenous migration approach – focusing on the economics of the
family, and based on altruism – to explain migration and what determines remittances. This family
arrangement provides an insurance motive through this income diversification strategy and thus
cushions the family against income or other adverse shocks (Singh et al., 2010). Thus, the altruistic
theory of remittances holds that migrants will remit more to the family or recipient household, based
on their own income, in times of dire economic situations at home, ensuring that the income is
matched, and again will remit less frequently or reduce the volume of flows in times when the
household income improves (Singh et al., 2010; Adenutsi, 2014).
Pure self-interest theory, or the portfolio approach of remittances, argues that migrants remit to retain
or enhance their social status at home, invest in their inheritance through their support to the family,
or to repay loans towards their education or the ability to afford migration (Lucas & Stark, 1985;
Singh et al., 2010). Adenutsi (2014) and Sarkar & Datta (2014), further link the portfolio choice theory
to the self-interest approach which predicts that remittances will increase or decrease relative to the
economic conditions in the labour-sending countries and that of the host countries, resulting in
remitters choosing to save and invest more or less in their home countries.
The theory of pure altruism and pure self-interest appeared to be too simplistic to explain
determinants of remittances. Lucas & Stark (1985) found evidence to support a more “eclectic
model”, defined as a tempered altruism or enlightened self-interest, which explained that remittances
were positively related to the labour-sending family income and enforcing the family unit as the
primary remittance recipient. Higher economic prospects in the home country would result in higher
returns on investments at home and thus increase the likelihood of remitting more and increasing
the frequency, and could further also influence the migrants’ decision to return home, based on the
investment returns and perhaps more conducive economic environment (Lucas & Stark, 1985; Singh
et al., 2010; Adenutsi, 2014).
Lucas & Stark (1985) recognised that no systematic theory of remittance behaviour existed then and
through the testing of hypothesis, provided rich context for remittance behaviour and trends. The
migrant and family or recipient household has “an implicit understanding” (Lucas & Stark, 1985) of
what they have to gain from this arrangement and migration may be a “Pareto-superior strategy”
(Lucas & Stark, 1985). The migrant is increasing the efficiency of a household through its
engagement in the employment market and the receipt of, or “Pareto-improving exchanges”
(Rapoport & Docquier, 2006). This implies that remittances can attain services such as care-taking
of assets (land, cattle, housing, etc.) and looking after parents or children remaining in the home
country. According to the study by Lucas & Stark (1985), urban migrants purposefully remitted to
rural families during the drought and the evidence illustrated that families with more cattle and
consequently at higher risk, received greater volumes of remittances, thus supporting the theory of
Pareto optimisation.
10
Lucas & Stark (1985) further provided evidence on the dualistic theories of development between
urban and rural households, reducing risks and ensuring that assets, in this case, cattle, were
retained and invested in to be inherited by the remitter and or contributing to investments at home
as a contribution to the status of the family. El-Sakka & McNabb (1999) added to this context of
determinants by referring to remittances as a ‘mutually beneficial arrangement’, or as coined by
Rapoport & Docquier (2006) “an informal familial arrangement” between the migrant and his/her
family.
The foundation for such an arrangement could be the strategy or objective to invest in human capital;
should the family have invested in the education of the migrant worker, the remittance could be
considered as repayment or an investment return (Lucas & Stark, 1985; El-Sakka & McNabb, 1999;
Nyamongo et al., 2012). Migrants who are more educated may remit a portion of their income to
furnish the household that invested in their education.
Stark & Wang (2002) applied a strategic model to explain the decision to migrate because of wage
differentials. Theoretically, high-skilled migrant workers have more to gain from migration although
they might be paid at the average productivity level of the group they are identified with in the host
country and this average could be reduced if there were to be an influx of lower-skilled migrants
(Stark & Wang, 2002). Docquier and Rapoport (1998) and Stark & Wang (2002) reasoned that skilled
workers might have an incentive to remit home to reduce the reason for unskilled workers from the
home country to follow suit. This would ensure that wages for skilled workers were not depressed
and thus remittances were determined through pure self-interest.
Rapoport & Docquier (2006) referred to the “repayment of loans” hypothesis – compensating for the
investment of the family towards education and also providing financial support to enable migration,
may it be domestic, regional or international – which included benefits towards risk diversification for
the recipients and smoothing of consumption. In addition, El-Sakka & McNabb (1999) reported that
it could provide access to financing intergenerational investments such as funding education of the
next generation. Better education translates into increased employment opportunities and thus
secures future income.
The macroeconomic determinants are mainly defined through the standard or Keynesian theory and
are applied to capture short-run impact. This model assumes that sticky prices, exchange and
interest rates which are fixed, as well as an environment of few supply constraints, would create
disproportionate effects on national output because of any shocks introduced from the demand side
(Rapoport & Docquier, 2006). Both Glytsos (2005) and Rapoport & Docquier (2006) used this theory
to determine the impact of international remittances – via remitters and recipients – and illustrated
the multiplier effects or interconnectedness of spending on consumption at a household level and
impacting on GDP per capita, investment and imports which benefit the economic growth of the
country, including the size of transfer shocks. However, the multiplier effects of remittances span
beyond the short-run effects, while longer-run effects fluctuate across different countries due to the
11
various reasons which give rise to volatility and liquidity generated by diversification of remittance
output effects (Glytsos, 2005; Rapoport & Docquier, 2006).
The long-run view of remittances depends on what remittances are used for – consumption or
investment. Rapoport & Docquier (2006) refer to the controversial effects of migration in the 1970s
which resulted in limited dynamic effects due to the concentrated consumption spending by
households. Linked to this, the remittance flows were allegedly resulting in the unemployed being
complacent and households becoming increasingly dependent on remittances instead of engaging
actively in the market (jobs, supply, entrepreneurial). However, Rapoport & Docquier (2006) reported
that the 1980s saw a shift in the growth effects of remittances from productivity to address issues of
inequality. They reviewed a number of studies and found that remittances improved economic
inequality at a household level by decreasing liquidity constraints, as well as supporting the
investments in technological advancements or techniques in agriculture and paid for education which
promoted future migration.
The level of education in a country will directly affect the employment opportunities the working
population can compete for, or will affect the demand for migrant labour in another country (El-Sakka
& McNabb, 1999). The economic activity in the labour-receiving country will determine and affect the
wages available to migrant workers and affect the flow of remittances. Decisions to migrate are
informed by the skill composition or education level of workers (Rapoport & Docquier, 2006; Ahortor
& Adenutsi, 2008; Fayissa, 2008; Adams, 2009; Lim & Simmons, 2015). The theory and motivation
for migration is closely linked to human capital which determines income and thus influences the
affordability to save, invest and send remittances home. Ahortor & Adenutsi (2008), Fayissa (2008),
Docquier et al. (2012) and Lim et al. (2015) acknowledged the important need for developing
countries to invest more and better in human capital.
Guha (2013) is critical of the volume of remittance flows creating a similar boom in receipts, similar
to the ‘Dutch Disease’ theory, which could create a skewed real exchange rate appreciation, impact
negatively on the tradable sector and so cause a loss of external competiveness for the country. In
addition, remittance-dependent economies are vulnerable to experience the Dutch disease problems
(Glytsos, 2005). Guha (2013) frames his study on macroeconomic effects of international
remittances on Reinhart & Reinhart’s (2008) description of ‘bonanzas’ or remittance flows to
developing countries, which were found to be associated with pro-cyclical fiscal policies that
attempted to minimise, or altogether avoid an exchange rate appreciation which would likely
contribute to economic vulnerability.
The choice to remit, especially through formal channels, is very responsive to the differential between
the official market exchange rates and those being offered on the black market (El-Sakka & McNabb,
1999). Migrant workers will opt to transfer remittances toward the black market when a higher value
can be received by the recipient family or household, and the creation of a black market is a result
of inconsistent macroeconomic policy (El-Sakka & McNabb, 1999). Further, migrants will transfer
12
money through official channels when inflation is high in order to minimise risk of loss through
unofficial channels. Countries with better competitive real interest rates will receive more per capita
remittances (Adams, 2009) and exchange rates. Political stability also determines the level of
remittances flowing to labour-sending countries (El-Sakka & McNabb, 1999; Glytsos, 2005).
Artuc, Docquier, Özden & Parsons (2015) refer to the assessment by Clemens & Pritchett (2008) of
the approach that income is based on the concept of the natural population, i.e. that economic
development results in improved human well-being and thus international migration is not an
alternative to economic development, but a form of it.
2.2
EMPIRICAL REVIEW
The literature reviewed for this study considered the macroeconomic determinants of remittances to
be linked to the income of migrants, the interest-rate differential between the home and host
countries, the exchange rate and inflation rate differences between the home and host countries
(combined or at home-country level), and the education level of migrants.
Singh et al. (2010) analysed the macroeconomic determinants of remittances in SSA and found that
the size of the migrant stock or diaspora determined remittance volumes, especially when these
migrants were working in wealthy countries. The study hypothesised that remittances could mitigate
economic shocks and found that remittances did indeed absorb shocks to recipient countries in SSA
as migrants would remit more to match the needs of the recipient family or household should the
country conditions such as institutional quality or interest rates negatively impact upon the value of
flows (Singh, et al. 2010). Further, the size of the diaspora is an important determinant as the migrant
stock is significant in influencing flows and where the diaspora reside is critical, as wealthier host
countries provide relatively better income (Singh et al., 2010).
Panda & Trivedi (2015) refer to the gravity model of remittances where a bilateral agreement is in
place, estimated by Lueth and Ruiz-Arranz (2006). The gravity framework was found to be dynamic
in explaining the determination of migrant patterns and subsequent volumes of remittances. Larger
countries received relatively bigger remittances than smaller home countries and this could be
explained by the migrant stock. Further, the distance between the host and home countries
determined remittance flows as farther destinations resulted in decreased flows of remittances to the
home country.
Singh et al. (2010) also found that the interest rate deferential was negatively and significantly
associated with remittances, similar to El-Sakka & McNabb (1999). Thus, a high interest rate
differential in the recipient country reflected instability in the receiving economy and thus would
decrease the appetite for migrants to invest in the home economy.
Adenutsi (2014) investigated the macroeconomic determinants which influenced migrant
remittances, both the compensation of employees (temporary migrants) and worker remittances
(permanent migrants) to SSA and found that these flows were influenced by both the host-country
13
macroeconomic conditions and the contrasting home-country conditions that were driving the volume
of flows. Permanent migrants were not regular remitters, partly because their social ties had become
weaker or their immediate families had joined them. Thus, they remitted consistent with the selfinterest motive and would invest in business ventures for a possible return (Adenutsi, 2014).
Temporary migrants were more altruistic and would remit more when the home-country conditions
deteriorated. Adenutsi (2014) found that these flows would increase by 4.5 percent when the
recipient country income decreased by one percent.
A higher real deposit rate would translate in temporary migrants remitting more to ensure that the
recipient household received the same amounts to maintain their lifestyle, and also increased
remittances when a higher real deposit rate existed to invest in possible ventures or entrepreneurial
opportunities at the end of their tenure in the host country (Adenutsi, 2014). Thus, SSA migrants
would remit more and over a longer period if a stable and investment-conducive macroeconomic
environment existed in their home countries. Adenutsi (2014) found that permanent migrants sent
90 percent of total remittances received from the sub-region during the 1980-2009 period of review
and thus SSA country policies would benefit greatly should they have low inflation rates, improved
financial market development, a stable exchange rate, and linked to all, stable and high economic
growth which would increase investment from migrants into the home-country economy.
However, Makina & Masenge (2014) analysed a cross-sectional survey of Zimbabweans living in SA
from 1979-2007 and tested the remittance decay hypothesis which took into account income as a
determinant of remittances. They found that remittances increased initially with the time spent in SA
and after a maximum of eight years, the flows declined (Makina & Masenge, 2014). This could be
determined by the legal status which might provide increased security after a length of stay and thus
resulted in less savings being remitted home and invested or utilised in the host country, or migrants
who were in SA due to economic or political reasons, might have less reason to support families at
home (Makina & Masenge, 2014). Due to the close proximity of Zimbabwean migrants in SA to their
home country, the frequency of home visits influenced their remittance behaviour as they had the
option to carry remittances home personally instead of formally transmitting it (Makina & Masenge,
2014).
Van Eyden et al. (2011) investigated SADC countries and found that host country economic
conditions were not the main drivers of formal remittances and in this case, the study focused on SA
as host country. The study found that remittance flows to SSA were not only from developed
countries and regional migration was common on the continent, determined by economic reasons
and less so for political reasons (Van Eyden et al., 2011). SA is an ‘economically superior destination’
for regional migrants and due to the close proximity of SADC countries, a high degree of economic
and policy integration promotes migration, while the volatility was reduced, as SA’s income per capita
14
was double that of most countries in the region (Van Eyden et al., 2011). The investigation of 103
SADC countries from 1994-2008 showed that remittance inflows to five countries (Botswana,
Lesotho, Madagascar, Malawi and Swaziland) were statistically insignificant when home and host
country economic conditions such as interest rate differential and market sophistication (M2) were
measured (Van Eyden et al., 2011). However, remittances to the Seychelles increased when hostcountry incomes and the home-country economic conditions improved and the real exchange rate
appreciated; this reflects strong self-interest patterns of migrant workers (Van Eyden et al., 2011).
Madagascar, Swaziland and Zambia migrants increased their remittances when the exchange rate
of their home countries depreciated and thus the real exchange rate is a significant determinant to
remit home (Van Eyden et al., 2011).
Panda & Trivedi (2015) reviewed the macroeconomic determinants of 24 emerging and developing
countries and found that both the host and home country macroeconomic factors determined
remittance flows. The exchange rate variable seemed to illustrate the macroeconomic conditions of
remittance sending and receiving countries and thus the study concluded that inflation might be the
most important policy directive to exercise control and so increase remittances through the foreign
exchange market system (Panda & Trivedi, 2015).
Barua, Majumder & Akhtaruzzaman (2007) investigated the macroeconomic determinants of
remittances to Bangladesh and found that migrants would invest in their home country should there
be an increase in the official exchange rate. Remitters were deterred to send money home when the
home country inflation was high, relative to that of the host country (Barua et al., 2007). Sarkar &
Datta (2014) found that migrants from Bangladesh preferred oil-rich country destinations and the
flow of remittances were positively influenced by the crude petroleum price and the exchange rate.
When the home currency depreciated, the migrants were able to remit more money to home towards
investment purposes.
El-Sakka & McNabb (1999) examined macroeconomic determinants of remittances and found that
both exchange rates and the domestic interest rates applied to remittances must be competitive, as
these are critically important variables to determine formal flows. Should the interest rate differentials
not be acceptable, the black market premium might be a better option to exchange remittances and
this flow would be lost to the country in favour of investment and trade opportunities.
The study provided a case of Egypt, a major-exporting country, which receives a considerable
volume of remittances, accounting for an estimated one quarter of total foreign exchange receipts
(El-Sakka & McNabb, 1999). The Egyptian government designed a policy instrument to attract
3
Botswana, Lesotho, Madagascar, Malawi, Mauritius, Mozambique, Seychelles, Swaziland, Tanzania,
Zambia.
15
remittances through official channels and created incentives which saw the Own Exchange Import
System (OEIS) being one of the most successful interventions. This system utilised remittances or
migrants’ savings as the main source of foreign exchange, available to importers. Government
pegged the interest rates to keep the cost of borrowing down (El-Sakka & McNabb, 1999). However,
beneficial interest rates resulted in real interest rates being negative for an extended period while
the official exchange rate was fixed. This resulted in dollarization and the system failed to achieve
optimal developmental outcomes. The study further found that remittances through official channels
increased during periods of high inflation at home to match the household needs towards
consumption, and migrants might choose to invest in real assets such as land or jewellery (El-Sakka
& McNabb, 1999).
Lucas & Stark (1985) in the case of Botswana measured increased remitting behaviour against the
‘repayment’ hypothesis and the evidence suggested that rural to urban migration measured higher
remittances with more educated family members and that of migrants’ children. The hypothesis of
Lucas & Stark (1985) was tested by Lim & Morshed (2015) and was confirmed when they
investigated what motivated developing country migrants to remit. They found the pure altruism
hypothesis inadequate to explain the increase in remittances due to recipient households’ income
shocks (Lim & Morshed, 2015). Further, such income shocks drive people to migrate to earn a better
and higher income. So they share this income through remitting to the household and, over time,
reduce shocks. The study found that a one percent increase of migrant stock translated to 0.7
percent more in remittances received as a percentage of the recipient country GDP (Lim & Morshed,
2015).
The case of El Salvador was captured by Castillo-Ponce, Torres-Preciado & Manzanares-Rivera
(2010) as a country greatly dependent on remittances derived from the USA migration corridor
(California, Los Angeles) and an estimated 20 percent of its GDP was due to this flow. Thus it is a
dollarized economy. El-Salvador lost its capacity to design and enforce discretionary monetary
controls and policy directions and relies on remittances to sustain the money supply in the country,
determining consumption patterns and the money market (Castillo-Ponce et al., 2010). It is one of
the top 15 remittance-receiving developing countries and received an estimated $2.3 billion per
annum in 2003 already, and this trend was expected to continue (Freund & Spatafora, 2005).
Migration to the USA, and specifically employment, was the primary determinant for remittance flows.
Due to the low investment in education by the government, unskilled workers were the majority
remitters. The study found that remittances were closely linked to El-Salvador’s GDP and the credit
market conditions, and seeing that it is a dollarized economy, the state of M2 in the USA (California)
determined the volume of remittances received, based on the host’s economic conditions, i.e.
favourable interest rates and inflation (Castillo-Ponce et al., 2010). Thus, the host country’s
economic conditions, such as job opportunities and a less restrictive monetary policy (Castillo-Ponce
16
et al., 2010) will allow for remittance flows to the home country and will retain the dollarized economy
status for El-Salvador.
Gupta (2005) reviewed the macroeconomic determinants of remittances to India and found that hostcountry economic conditions were the most important. During 2002, India received 10 percent of
remittances to developing countries and 25 percent of Asian countries’ share (Gupta, 2005). This
amounted to $18 billion by 2003, representing about 3 percent of GDP, and this increase is attributed
to the increased number of high-skilled migrants remitting (Gupta, 2005). The study investigated
return factors such as domestic interest rates, interest rates in the host country, return in the stock
market or property stocks and the movement of oil prices, especially for migrants to Middle-Eastern
oil producing countries, and found that the stock of migrants determined flows significantly,
influenced by host country conditions.
Remittances were found to be more robust than flows on the capital account and attributed this to
the increased number of high-skilled migrants. The trends indicated that more remittances were
received during annual periods of celebrations and flows were specifically are higher when economic
conditions in the host country were good, and increases were found to be counter-cyclical and
became higher during periods of negative agricultural growth in the recipient country (Gupta, 2005).
Adams (2009) looked at seventy-six low- and middle-income remittance receiving countries and
found that complementary interest and exchange rates determined the volume of remittances per
capita. Further, the study found that the skill composition of migrant workers determined remittances
(Adams, 2009). Countries that exported a large volume of high skilled or educated workers, received
less per capita remittances than countries that provided a larger volume of low-skilled workers. This
study calculated that a 10 percent increase in the share of high-skilled migrants would reduce the
per capita remittances flowing to the recipient country by 11.2-19.7 percent. The reverse was
applicable to low-skilled migrants, as a 10 percent increase in presence would translate to 9.1-19.8
percent more remittances sent home (Adams, 2009). A possible explanation could be that highskilled migrants remitted less because they moved with their families and both altruistic and selfinterest motivations are low (Adams, 2009).
Makina & Masenge (2014) found that the level of education of migrants was significant in determining
the amount remitted, as higher-educated migrants remitted more than lower-level educated migrants
and this could further be attributed to the positive relationship with income level to remittances.
Rapoport & Docquier (2006) found that education had relatively high income elasticity and it is
expected to positively influence the educational investment and outcomes of the recipient
household’s children, which were funded with remittances. Docquier et al. (2012) found that highereducated migrants, earning higher incomes than their lower-skilled peers, would make more
remittances if the host country applied a more restrictive immigration policy and, in addition, had a
selective skill composition requirement for immigrants.
17
Beine, Docquier & Oden-Defoort (2011) investigated panel data for 147 countries to measure the
impact of skilled emigration on human capital accumulation. The data revealed that globalisation and
selective immigration policies, especially those of OECD countries, have increased the absolute
number of skilled emigrants. But, although developing countries which experienced human capital
losses of more than 50 percent were negatively impacted, the brain drain has been ‘stable at the
world level’ (Beine et al., 2011), pertaining to the stability of developing countries too. This can be
explained based on the population size and labour supply of the developing countries and the
complementary developmental investment for these countries to educational attainment of their
population (Beine et al., 2011).
2.3
SUMMARY
This chapter provided a theoretical framework and empirical literature review. The literature on
determinants of remittances illustrates that context matters. Studies across different regions
indicated migrant stock and income level as an important determinant of remittances. Singh et al.
(2010) and Adenutsi (2014) considered home and host country conditions that determined
remittances and concurred on the size of the migrant stock that would remit more if located in
relatively wealthy countries.
Higher real deposit rates in host countries, interest rates and consistent exchange rates were
significant determinants of remittances. The ideal is to have complementary economic conditions,
especially in the home country, as migrants will remit to the household or family structure to reduce
income shocks and or to match income.
Lucas & Stark (1985), Gupta (2005), Rapoport & Docquier (2006) and Docquier et al. (2012) found
that higher-educated migrants remitted more to home while Adams (2009) found that lower-skilled
migrants remitted more over a longer period.
The following chapter will discuss migration patterns and trends of Africans internationally and to the
region.
18
CHAPTER 3
MIGRATION AND REMITTANCES TO SADC
3.1
INTRODUCTION
Remittances to Africa have increased significantly since 1990 and represented an estimated 2.6
percent of GDP, or $40 billion in 2010, becoming as significant as foreign direct investment (FDI)
(Ratha et al., 2011). A United Nations Economic Commission for Africa report (2014) recognised
that remittance flows to Africa increased from $60 billion in 2012 to $62.9 billion in 2013, overtaking
the FDI inflows at $51.7 billion and $56.6 billion for the respective periods. Growth in African
economies has outperformed global economic trends at a consistent rate of five percent annually
and these currently house the largest share of frontier economies (UNECA, 2014).
The World Bank’s Migration and Remittances Factbook of 2016 reports that an estimated 3.4 percent
of the world’s population, about 250 million people, are not living in their countries of birth (Ratha et
al., 2016). While the preferred destinations for the highly educated and skilled are OECD countries,
South-South migration is increasing and 38 percent of especially lower educated migrants choose
these countries (Ratha et al., 2016).
Africa houses the largest and more youthful population, representing 60 percent of the global working
age population. Mills (2012) refers to this statistic as Africa’s number one ‘advantage’ and calculates
that by 2050, Sub-Saharan Africa’s population could be at 1.5 billion, increasing its working age
population to an estimated 65 percent from 50 percent in the 1990s. Countries in the OECD workingage population are projected to decline for the same period.
However, although remittances represent a significant international financial flow, the continent’s
share remains relatively small compared to other developing countries (Ncube & Brixiova, 2013;
Adenutsi, 2014). This could partly be due to the volume of unofficial flows and the relatively poor
record and monitoring of migration at intra-regional and international levels.
The following section will focus on where African migrants migrate to, what the patterns and trends
of these migrant workers are, and on the remittances to SADC as a region.
3.2
WHERE DO AFRICAN MIGRANTS WORK?
In 2009, there were an estimated 175 million people living outside their country of birth, with the
International Labour Organisation (ILO) estimating 90 million to be migrant workers (Olivier, 2009).
Official statistics documented an estimated 30 million Africans, three percent of the population, to be
living outside of their country of birth (Ratha, et al., 2011). There is a strong growth pattern towards
South-North with European countries hosting 32.6 percent of international migrants; North and Latin
America host 23.4 percent and 2.4 percent respectively, Asia has 28.6 percent and Africa 9 percent
(Adenutsi, 2014).
19
Developed countries, more specifically the OECD countries, have migration and entry policies that
attract the best and brightest talents globally. Migration from and between developed countries is
not detrimental to their economic outcomes and competitiveness at a country level as these
economies contribute well towards human capital investments and have access to a larger volume
of high-skilled workers than developing countries. The brain drain theory mainly argues that human
capital accumulation in developing countries is lost to rich countries which can offer lucrative
employment and remuneration, also referred to as the “war for talent” (Harvey, 2011) to attract
strategic occupations such as healthcare, engineering and teaching (Beine, et al., 2011; Docquier et
al., 2012). As expected, wealthy and OECD countries are not affected by the brain drain
phenomenon, as the vacuum created by emigration of their high-skilled nationals is compensated
for by the constant flow of incoming talent (Artuc, et al., 2015).
Beine, et al. (2011) found that the brain drain depleted human capital in 53.4 percent of developing
countries that showed emigration rates higher than 50 percent. However, the dataset also revealed
that despite globalisation and selective immigration policies that attracted a high volume of skilled
emigrants to the OECD countries; the effects of the brain drain have been extremely stable at the
world level, as well as at the level of developing countries, including SSA. Beine, et al. (2011)
assigned this to relatively high increase in population size in developing countries, and the increased
investment in educational attainment in these countries.
Statistics for the year 2000 indicated that one out of every eight high-skilled Africans migrated to an
OECD country (Ratha, et al., 2011). Ratha, et al. (2011) further found that in Ghana, based on a
survey between 1976-2004, out of the top five students graduating from the top thirteen schools,
three quarters left the country between secondary school and the age of thirty-five.
Figure 2: Long-run trends in skilled emigration rates
Source: Beine, et al. 2011
20
The world immigration stock has been concentrated in OECD countries as from the 1960s. The rates
to non-OECD countries decreased from 57 percent to 49 percent (Artuc, et al., 2015). However,
while OECD countries were preferred by high-skilled and female migrants whilst the non-OECD
countries such as South Africa, oil producing Persian Gulf countries and East Asian countries
received one-third of the total brain drain from low-income and the least developed countries (Artuc,
et al., 2015) (See figure 3). Ratha et al. (2016) also recognise that South-South migration now
represents at least 38 percent of movement. While the United States and the United Kingdom remain
primary destinations, non-OECD destinations are more accessible to lower-skilled migrants.
Figure 3: Migration destination countries for 25+ years for 1990 and 2000
Source: Artuc, et al., 2008
3.3
SADC MIGRATION PATTERNS AND TRENDS
An estimated two-thirds of migrants from Sub-Saharan Africa (SSA) will migrate regionally and the
majority migrate to sub-regions only; this is true for poorer migrants (Ratha, et al., 2011). An
estimated 70 percent of SSA migrants reside and work in the region and this is a unique phenomenon
compared to the international trend where migration patterns are international (Adenutsi, 2014).
People migrate essentially because of political and economic reasons (Olivier, 2009; Beine, et al.,
2011; Ratha, et al., 2011). This ring true for the Southern African Development Community (SADC)
as well, where intra-SADC migration has been the result of instability in countries such as the
Democratic Republic of Congo (DRC), Mozambique, Zimbabwe and Angola (Olivier, 2009).
Migration within SADC is a livelihood strategy for middle-aged migrants who are in search of
economic survival. A household survey conducted by the Southern African Migration Project (SAMP)
21
on five SADC countries4 found that 41 percent of adults over 40 years were migrating while only
seven percent of the working age population under 25 years were migrating (Pendleton, Crush,
Campbell, Green, Simelane, Tevera & de Vletter, 2006). SADC countries such as Lesotho, Mauritius,
Swaziland, the Seychelles and Botswana were the top remittance-dependent countries in the region
and the combination of countries did not provide a clear-cut pattern of dependence as Mauritius,
Seychelles and Botswana were deemed high-income countries (Adenutsi, 2014).
The World Bank Development Indicators (2016) presents data that shows huge gaps across the
SADC countries on migration and the primary issue of remittances. However, Figure 4 sketches a
picture of mobility of SADC workers over the past twenty years. SA, Tanzania and the DRC illustrate
large movements across the five-year cycles and for the DRC, this coincides with the political unrest
during the 1990s (Segatti & Landau, 2011). The numbers for Zimbabwe and Lesotho are very low
and data for Zimbabwe is consistently omitted in the WDI. The numbers allude to illegal migrant
workers as reported by the FinMark Trust (2012), Truen & Chisadza (2012) and Makina & Masenge
(2014), amongst others. Migration patterns for SADC remain contained as Lesotho with an estimated
population of 18 million has a small share of (documented) migrants and SA illustrates a figure of
under 2 million from a population of just under 50 million in 2010.
Figure 4: International migration stock for SADC from 1990-2010
International Migration Stock
2,500,000.00
2,000,000.00
1,500,000.00
1,000,000.00
500,000.00
0.00
1990
1995
2000
2005
Angola
Botswana
Congo, Dem. Rep.
Lesotho
Madagascar
Malawi
Mauritius
Mozambique
Namibia
Seychelles
South Africa
Swaziland
Tanzania
Zambia
Zimbabwe
Source: World Bank. WDI
4
2010
Botswana, Lesotho, Southern Mozambique, Swaziland and Zimbabwe
22
South Africa remains the destination of choice for regional migration (Olivier, 2009) and even en
route to an international destination. The survey found that migration traditions were historically
shaped and in the case of SA migration, 50 percent had migrant parents (Lesotho: 76 percent and
Mozambique: 66 percent) and migrant grandparents (Lesotho: 24 percent and Mozambique
44 percent) (Pendleton, et al., 2006). Olivier (2009) further adds that once immigration linkages are
established, it is difficult to reverse and thus these patterns fail to be a passing phase of future
generations’ approach to their livelihoods.
The historical migration trend is influenced by the mining sector in SA and since the ongoing job
losses in the mining industry as from the 2000s, females from Lesotho have increasingly sought
employment in SA. The survey estimated at least 86 percent of SADC migrants flocked to the country
(Pendleton, et al., 2006) and Botswana is the second destination of choice. However, migration
within SADC is further influenced beyond the economic opportunities, by the HIV/Aids pandemic in
the region (Olivier, 2009). Some SADC migrants’ families are negatively affected by the HIV/Aids
crisis through infection rates and some are migrating to have access to antiretroviral treatment,
mainly through the SA public health system.
Cross-border migration is mainly unskilled or semi-skilled and provides lower-end needs to the
labour market (Olivier, 2009, Pendleton, et al., 2006). Zimbabwean migrants are mostly educated
and 33 percent of the total migrant stock is in SA whilst 17 percent is in Botswana. An estimated
40 percent is outside of SADC (Pendleton, et al., 2006). The SAMP survey measured 15 percent of
SADC migrants to have no education, 46 percent with a secondary education and at least 66 percent
to have a postgraduate education and or degrees (Pendleton, et al., 2006). Although 86 percent of
these migrants are in SA, the survey found no significant evidence of a skills drain to SA.
Over the past years the investment in education (see Figure 5), especially at primary level, has been
driven by international commitment to the Millennium Development Goals (MDGs). SADC countries’
education budgets committed the largest share towards primary education and Zambia, Namibia,
Mozambique, Madagascar, Zimbabwe and Tanzania spent more than 50 percent of their education
expenditure on primary education. Angola, Mauritius and Botswana spent the largest share of their
budgets towards secondary education and Botswana is consistent in its investment in human capital
by spending the remaining 25 percent towards tertiary education.
Figure 5: SADC country expenditure on education from 1990-2012 (excluding SA)
23
Expenditure on Primary, Secondary and Tertiary education as % of
goverment expenditure on education
70.00%
59.50%
60.00%
50.00%
40.00%
30.00%
47.45%
45.56%
45.08%
38.16%
32.30%
25.10%
51.60%
51.17%
47.46%
38.83%
33.95%
28.00%
27.80%
29.77%
24.05%
23.00%21.63%
22.51%
20.85% 21.74%
20.00%
10.00%
52.93%
51.43%
48.80%
55.96%
14.05%
8.50%
32.91%
27.70%
24.64%24.57%
23.66%
25.68%
19.33%
10.91%
12.67% 12.49%
25.60%
22.80%
21.07%
17.87%
14.55%
0.00%
Expenditure on primary as % of government expenditure on education (%)
Expenditure on secondary as % of government expenditure on education (%)
Expenditure on tertiary as % of government expenditure on education (%)
Source: World Bank WDI
Van Eyden et al. (2011) referred to the degree of economic integration between SADC countries that
influenced migration and thus remittance patterns. SA and Botswana are the most developed
countries in SADC and thus the destinations of choice. The level of economic development of the
region lies mainly in emerging economies and the possibilities are that when one country’s economic
situation improves, the rest of the region benefits.
Zimbabwe, once the breadbasket of the world, is a country in turmoil due to its unresolved political
and economic crisis since the early 2000s. Makina (2012) reported that an estimated 1-1.5 million
Zimbabweans are in SA, whilst Truen et al. (2012) puts the figure closer to 1.9 million. The SADC
region is known for its relatively porous borders and poor controls and thus it is widely acknowledged
that the Zimbabwean count is a mix of documented or legal and illegal migrants. A survey by Makina
(2012) found 56.7 percent of migrant respondents to be undocumented. However, the illegality of
migrants in SADC is not exclusive to Zimbabweans.
3.4
REMITTANCES TO SADC
The SAMP survey (Pendleton et al., 2006) found little evidence that remittances in Southern Africa
had developmental value. It is, however, critical for poverty alleviation and consumption at a
household level (Olivier 2009; Van Eyden et al., 2011). Most Sub-Saharan countries, including SADC
24
countries, do not regularly report on international remittances and thus varying estimates exist in the
literature. The 2012 survey on the SA-SADC remittance channel measured an estimated R11.1
billion flowing out of SA into the region (excluding Seychelles and Madagascar which had no
migrants present in SA) and 60 percent of these flows are to Zimbabwe (Truen & Chisadza, 2012).
The World Bank’s World Development Index (see Figures 6 and 7) compiled country level data and
illustrated that SA and Lesotho received the greatest volume of remittance flows, that is, almost
$1.1billion and $550 million respectively for 2012. Madagascar received relatively little remittances
prior to 2001 and received a significant increase, perhaps in the documentation and official recording
thereof, in remittances from 2001, with flows valued at just under $400 million for 2014. (See Figure
6.) SA received the lion’s share of remittances and Lesotho has consistently received high-volume
remittance flows. This is consistent with evidence on mining opportunities and economic participation
(Pendleton et al., 2014).
Considering the flows to Zimbabwe, the volumes are very low, but Truen & Chisadza (2012) as well
as Makina & Masenge (2014) acknowledged the informality of remittance flows to this country. Thus,
the formal measurement is relative to what is anticipated to flow to households. Interestingly,
remittance flows prior to 1996 were close for countries such as SA, Zambia, Zimbabwe, Mozambique
and Swaziland, whilst Lesotho was already an outlier on receipts. Thus, it is anticipated that
remittances contribute significantly to its GDP. (See Figure 7.)
Van Eyden et al. (2011) found that the market sophistication (M2) – the status of the financial
services industry and thus access to finance – is positively correlated with remittance flows. Host
country economic conditions should thus not determine remittance flows due to the high degree of
SADC country integration. The study indicated that for well-developed financial systems of countries
such as Mauritius and Zambia, remittances were used to mitigate finance constraints. Remittances
to the Seychelles improved with higher income levels whilst Madagascar, Swaziland and Zambia
received increased remittances when their individual exchange rates depreciated (Van Eyden et al.,
2011).
Due to the close proximity of SADC migrants, the SAMP survey found that remittances were provided
in cash or goods and delivered regularly to the household by the remitter, family or friends (Pendleton
et al., 2006). Thus, informality in the region is a reality, as illustrated by Figures 6 and 7. The majority
of studies on remittances to SSA focus on the formal financial sector existence and the ability to
allow for international or regional remittance flows to be optimally measured and utilised towards
economic growth and investment.
25
Figure 6: Remittance flows to SADC from 1990-2014
Personal Remittances received in US$
1,200,000,000
1,000,000,000
800,000,000
600,000,000
400,000,000
200,000,000
0
-200,000,000
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2012 2013 2014
Angola
Botswana
Congo, Dem. Rep.
Lesotho
Madagascar
Malawi
Mauritius
Mozambique
Namibia
Seychelles
South Africa
Swaziland
Tanzania
Zambia
Zimbabwe
Linear (South Africa)
Source: World Bank WDI
Figure 7: Personal remittances received by SADC as a percentage of GDP, 1990-2014
Personal Remittances received as % of GDP
90
80
70
60
50
40
30
20
10
0
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2012
Angola
Botswana
Congo, Dem. Rep.
Lesotho
Madagascar
Malawi
Mauritius
Mozambique
Namibia
Seychelles
South Africa
Swaziland
Tanzania
Zambia
Zimbabwe
Source: World Bank WDI
2013
2014
26
Adenutsi et al., (2012) recommend that countries should design policies at a macroeconomic level
that will attract migrants and perhaps the diaspora, to enable them to remit via formal or financial
institutions. Ratha et al. (2011) reported that 81 percent of post offices in SSA are located outside
the large cities and thus create access to more than 80 percent of Africans who are excluded by
commercial banks. SSA and SADC could focus on credit cooperatives, microfinance institutions,
amongst others, specifically, to formalise remittances and increase the volume of these flows.
However, the Remittances Prices Worldwide (RPW) still rates SSA as the highest-cost region for
remitting, as 9.5 percent (fourth quarter of 2015) of a $200 transfer will go towards fees and charges
(Ratha et al., 2016). Remittance outflows from SA to the region could cost 18-20 percent of a $200
transfer whilst the global average is 7.4 percent (Ratha et al., 2016).
3.5
SUMMARY
Chapter 3 provided context to remittance flows to SADC countries. It considered the volume of
migrants from SADC at an international level, as well as the funding towards the education of these
migrants by their respective governments and the level of remittance flows to SADC countries.
Remittances represent an important flow to SADC countries, especially to Lesotho and Mozambique,
where migration has become a tradition and remittances contribute significantly to the GDP of
countries. Further background was provided as to migration patterns and trends of African migrants,
and the regional and intra-regional migration patterns that have evolved into livelihood strategies of
Africans were referred to. There are few studies on SADC that address macroeconomic
determinants of remittances and remittances contribute towards poverty alleviation as it issued
towards consumption for recipient households (Pendleton et al., 2006; Olivier, 2009; Van Eyden et
al., 2011).
The next Chapter will describe the research methodology for this research report.
27
CHAPTER 4
METHODOLOGY AND RESEARCH DESIGN
4.1
DATA
Panel data was used in this study and the longitudinal data shows limitations due to the inconsistent
level of data available for SADC countries. However, it provides aggregated data of remittances over
the 25-year period to analyse determinants of this financial flow. From the 15 SADC countries5, South
Africa was excluded from the analysis based on the relatively high level of migration to SA and
because it is a remittance-sending country. The data from the World Bank Development Indicators
(WDI) was used to compile the panel dataset and estimate the regressions.
Figure 8: Remittances to SADC: 1990-2014
Personal remittances to SADC countries (Excluding South
Africa) in US$
1,800,000,000.00
1,600,000,000.00
1,400,000,000.00
1,200,000,000.00
1,000,000,000.00
800,000,000.00
600,000,000.00
400,000,000.00
200,000,000.00
0.00
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2012 2013 2014
Source: World Bank WDI
Personal remittances to SADC remained under the US$1 billion mark up to 2001 and spiked over
the following 14-year period to reach just over US$1.7 billion in 2012. Figures 6 and 7 in Chapter 3
indicated that Lesotho was a primary recipient of remittances and had received almost 80 percent of
remittances as a percentage of its GDP during the 1990s. However, a drastic decline of about 17
percent of GDP per capita was received during 2014.
5
Angola, Botswana, Congo (DR), Lesotho, Madagascar, Malawi, Mauritius, Mozambique, Namibia,
Seychelles, Swaziland, Tanzania, Zambia and Zimbabwe; excluding South Africa.
28
The official exchange rate variations for SADC over the period of study illustrate the constant
depreciation of the country currency value against the US$. It increased drastically as from 2001
onwards and in the same period, receipts of remittances increased to countries such as Madagascar,
Tanzania and the DRC, amongst others.
Remittances to SADC are on the increase and the official exchange rate is responding to global
markets. Thus, inflation in SADC countries will negatively affect the livelihood of a country’s
population. This trend in the increased volume of remittances linked to high official exchange rates
could be explained by the altruistic behaviour of African migrants, but also the opportunity to invest
in assets back home.
Figure 9: Official exchange rate fluctuations in SADC: 1990-2014
Official exchange rate (LCU per US$) Zimbabwe excluded
3000
2500
2000
1500
1000
500
0
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2012
Angola
Botswana
Congo, Dem. Rep.
Lesotho
Madagascar
Malawi
Mauritius
Mozambique
Namibia
Seychelles
South Africa
Swaziland
Tanzania
Zambia
2013
2014
Source: World Bank WDI
4.2
EMPIRICAL MODEL
To test the determinants of remittances, the model is specified, adapted from Adams (2009):
log 𝑅𝐸𝑀𝑖𝑡 = ∝ + 𝛽1 𝑙𝑜𝑔𝑂𝐸𝑋𝑖𝑡 + 𝛽2 𝐼𝑅𝑖𝑡 + 𝛽3 𝐼𝑛𝑓𝑙𝑖𝑡 + 𝛽4 𝐻𝐶𝑖𝑡 + εi
(1)
The dependant variable (REM) is personal remittances received by a labour-sending country over
the period of measure. The independent variables for this study are measured at a labour-sending
or home country level: official exchange rate, the real interest rate, inflation rate, and human capital
measured as the total expenditure on education.
The variables are defined as follows:
29
vi.
log 𝑅𝐸𝑀𝑖𝑡 = Personal remittances (log) received by the home country 𝑖 and at year 𝑡. This is
the dependent variable.
vii.
𝑙𝑜𝑔𝑂𝐸𝑋𝑖𝑡 = Official exchange rate (LCU per US$, period average) of country 𝑖 at year t.
viii.
𝐼𝑅𝑖𝑡 = Real interest rate (percentage) in the labour-sending country 𝑖 at year t.
ix.
𝐼𝑛𝑓𝑙𝑖𝑡 = Inflation at consumer prices (annual percentage) of country 𝑖 at year t.
x.
𝐻𝐶𝑖𝑡 = Human capital is measured as the total government expenditure towards education
(primary, secondary and tertiary) of country 𝑖 at year t.
Further description and sources of the variables:
Remittances: The research report uses the recent estimate of personal remittances received up to
2014. Personal remittances comprise personal transfers and compensation of employees. Personal
transfers consist of all current transfers in cash or in kind made or received by resident households
to or from non-resident households. Personal transfers thus include all current transfers between
resident and non-resident individuals. Compensation of employees refers to the income of border,
seasonal, and other short-term workers who are employed in an economy where they are not
resident and of residents employed by non-resident entities. Data are the sum of two items defined
in the sixth edition of the IMF's Balance of Payments Manual: personal transfers and compensation
of employees. Data are in current U.S. dollars.
Official Exchange Rate: refers to the exchange rate determined by national authorities or to the
rate determined in the legally sanctioned exchange market. It is calculated as an annual average
based on monthly averages (local currency units relative to the U.S. dollar).
Real Interest Rate: the lending interest rate adjusted for inflation as measured by the GDP deflator.
The terms and conditions attached to lending rates differ by country, however, limiting their
comparability.
Inflation: Inflation as measured by the consumer price index reflects the annual percentage change
in the cost to the average consumer of acquiring a basket of goods and services that may be fixed
or changed at specified intervals, such as yearly. The Laspeyres formula is generally used.
Human Capital measured by education expenditure: General government expenditure on education
(current, capital, and transfers) is expressed as a percentage of GDP. It includes expenditure funded
by transfers from international sources to government. General government usually refers to local,
regional and central governments.
4.3
THEORETICAL UNDERPINNING
Macroeconomic variable 1: Official Exchange rate. Barua et al. (2007) found that an increase in the
exchange rate is positively related with remittances in Bangladesh. As the remitter’s income
30
increases in the domestic currency, the remitter is encouraged to buy more goods and services in
the home country. In addition, a depreciating exchange rate generally reduces the difference
between the unofficial and official rate that would generally positively influence remittance flows
(Barua et al., 2007). The study expects a positive link between the official exchange rate and
remittances.
Macroeconomic variable 2: Interest rate. Adams (2009) found that the per capita remittances
received by a country is positively related to investment returns at home and thus in all versions of
the remittance model, the coefficients measuring real interest rates at home, proved positive and
significant to the level of per capita remittances received by that country. Following Adams (2009),
the study expects a positive and significant link between interest rate and remittances due to
migrants motivated by investment returns at home.
Macroeconomic variable 3: Inflation. In addition to interest and exchange rates, the rate of inflation
at the host country level determines remittances (Adenutsi, 2014; Panda & Trivedi, 2015.) If inflation
increases, the beneficiaries of remittances require more money for family maintenance and other
purposes (Panda & Trivedi, 2015). The study expects a positive link with inflation and remittances.
Macroeconomic variable 4: Human capital. Adams (2009) found that the skill composition of migrant
workers does matter in remittance determination; countries exporting a higher volume of educated
migrants receive less per capita remittances than those providing low-skilled migrant workers.
Following Adams (2009), the study expects to find the human capital variable positive and significant
to determine remittances.
4.4
ESTIMATION TECHNIQUE
The F-test was used first to test the validity of the fixed effect models in relation to the pooled models.
For the specified model, the F-test enables a rejection of the null hypothesis of homogeneity at 1
percent and thus individual-specific factors determine remittances. The models applicable are thus
either fixed effect or random effect. The Hausman test’s null hypothesis could not be rejected and
random effects models are specified. A random effects model with general least squares (GLS) is
used.
The SADC countries exclude SA and a total of 14 countries6 are included in the sample.
6
Angola, Botswana, Congo (DR), Lesotho, Madagascar, Malawi, Mauritius, Mozambique, Namibia,
Seychelles, Swaziland, Tanzania, Zambia and Zimbabwe.
31
4.5
SUMMARY
This Chapter defined the data used, as well as the empirical model. The dependent and independent
variables were comprehensively described and the estimation technique provided. The use of the
random effects models is motivated to test the a priori expectations derived from the literature.
The next chapter provides the estimation results and analysis thereof.
32
CHAPTER 5
RESULTS
5.1
EMPIRICAL RESULTS
The study found that the lead determinant of remittances is human capital. Human capital has a
significant and positive coefficient at a 1 percent level. The interest rate is significant to determine
remittances and this indicates that SADC migrants make direct remittances towards investments.
The official exchange rate and inflation is not found to be significant determinants of remittances in
SADC.
Table 5.1: Determinants of Remittances
Independent variables
Official exchange rate (log)
Interest rate
Human capital
.05 (0.720)
.021 *(0.001)
.170 ***(0.000)
Inflation
.011 (0.710)
Constant
13.45891 (0.000)
Observations
85
Countries
14
Hausman (p-value)
Estimator
0.3598
Random Effects
Note: ***, **, * indicate the level of significance at 1%, 5% and 10% respectively, with standard
errors in parentheses
5.2
SUMMARY OF MAIN FINDINGS
This research report investigated the determinants of remittance to SADC countries and specified
four macroeconomic variables to explain remittance flows. The following section summarises the
main findings:
Human capital: In line with the finding of Adams (2009), the study found human capital a positive
and significant determinant of remittances. Adams (2009) stated that a large low-skilled migrant
labour force would remit more to their home country. Although this study does not compare education
levels, the data available on total expenditure on education by governments indicate that the focus
remains to be on primary education in SADC. There is a high volume of low-skilled migration activity
in SADC and internationally and this finding alludes to the economic value of migration, based on
the access to income. Given the relatively low investment in education for the majority of SADC
countries and the strong focus on primary education rather than secondary and tertiary level
educational attainment, this finding is not surprising. Pendleton et al (2006) and Olivier (2009) found
33
that, although remittances have a low developmental value, it is instrumental in poverty alleviation
and consumption in developing countries.
Interest rate: The study found interest rate a positive and significant determinant of remittances.
This is in line with the finding of Adams (2009), i.e. that remittances received by a country are
motivated by investment returns at home. The income levels of migrants might not be adequate to
afford remitting towards consumption as well as considering investment, especially in property, when
rates are low. Migrants might decide to invest in the host country with higher interest rates and
anticipate higher returns in future, instead of having slow growth on investments.
Official exchange rate: Following Barua et al. (2007), the study expected a positive link between the
official exchange rate and remittances. The official exchange rate was not found to be a significant
determinant of remittances. For SADC, it seems that migrants do not consider remitting based on
the exchange rate, as this influences the value of what households receive in remittances.
Inflation: Inflation was not found to be a significant determinant of remittances. This is contrary to
the finding of Adenutsi (2014) and Panda & Trivedi (2015) that the rate of inflation in the host country
was a determinant of remittances. Migrants from SADC continue to remit despite the economic
conditions in the home country. However, they are not increasing their volume of remittances sent
home to compensate for high inflation in the home country.
34
CHAPTER 6
CONCLUSION AND RECOMMENDATIONS
6.1
CONCLUSION
This research report investigated the determinants of remittances and found that human capital and
interest rate are positive determinants of remittances. As a collective, the significance of human
capital requires an intervention to capitalise on our large and youthful population. Although NorthSouth migration is the preferred option for the highly educated African migrant, South-South
migration opportunities are increasing (Ratha et al., 2016). However, Africa and SADC specifically
will miss this opportunity should we not address the investment required towards education at a
regional level, and linked to these address economic conditions to encourage remittances to be
utilised towards investment.
The evidence estimated that two-thirds of migrants from Sub-Saharan Africa (SSA) will migrate
regionally and the majority migrate to sub-regions only (Ratha, et al., 2011). An estimated 70 percent
of SSA migrants reside and work regionally; this is a unique phenomenon compared to the
international trend where migration is to international destinations (Adenutsi, 2014). The literature
also confirms that migration happens because of political and economic reasons (Olivier, 2009;
Beine, et al., 2011; Ratha, et al., 2011). This is true for SADC as well, as intra-SADC migration has
been the result of instability in countries such as the Democratic Republic of Congo (DRC),
Mozambique, Zimbabwe and Angola (Olivier, 2009). The general slow economic growth in SADC
countries has become a greater reason for migration in the region.
The interest rate in the home country is significant in determining remittances. This finding is
encouraging as it indicates that migrants are possibly also interested in investment opportunities at
home. Thus, should interest rates in the home country be conducive to investment, remittances might
be directed towards medium to longer-term investment.
Remittances to SADC reached $1.7 billion in 2012, excluding receipts from SA, a significant resource
assumed primarily towards consumption. However, the interest rate significance in remitting
illustrates that migrants do channel remittances towards investment. Despite the assertion by Van
Eyden et al. (2011) that the region has a high level on economic integration, the lack of data available
on migrants’ mobility within the region and internationally, including the huge gaps in the data quality
and availability on economic variables, requires political intervention to allow for better reporting on
the region.
6.2
RECOMMENDATIONS/POLICY IMPLICATIONS
It is critically important for SADC countries to document and report on remittances, migration, and
economic indicators. This will allow for increased research and analysis on the subject of remittances
and their macroeconomic possibilities. SADC countries should therefore improve measures to
35
monitor their remittances. The cost of remittance transfer also needs to be considered. Freund &
Spatafora (2005) reported that high transaction costs deterred migrants from remitting or otherwise
they use informal channels to remit.
Adenutsi et al. (2012) recommend that countries design policies at a macroeconomic level to attract
migrants and for home and host countries to have complementary economic policies to encourage
remittances towards investment purposes. SADC policymakers should focus on creating a stable
economic environment at home country level, aligned to the region to create an environment
conducive to remitting. El-Sakka & McNabb (1999) promote the policy consideration that domestic
interest rates and the exchange rates to both be competitive to boost remittance flows and so shift
the flows away from pure consumption, but make investment worthwhile.
Artuc et al. (2015) refer to the concept of the natural population – that economic development results
in improved human wellbeing, and thus international migration is not an alternative to economic
development, but a form of it. SADC member states should focus on human capital investment.
Especially education at secondary and tertiary levels, skills can be developed in response to global
labour market needs. Migrants could access wealthier migrant destinations and compete for higher
paid jobs, remitting more funds home for investment purposes.
The decline in the SA mining industry has resulted in thousands of jobs being shed over the past
years. The high concentration of unskilled migrant labour in the region is thus exposed to
unemployment, and little future employment opportunities exist, based on the sluggish growth of the
region and dynamic global market economy needs. Collective action is required to create
employment within the region and promote human capital investment to afford migration beyond the
region to secure and improve household income and provide a livelihood for the youth.
6.3
LIMITATIONS OF THE STUDY AND OPPORTUNITIES FOR FURTHER RESEARCH
The economic data available for SADC countries is limited to test extensive models on
macroeconomic variables. The issue of informality is a contributor to the incomplete data on
remittances and a set of comprehensive case studies will be required to develop aggregated data
on specific countries to design a complete panel dataset on SADC.
More policy research is required on SADC, specifically the macroeconomic conditions to encourage
remittance flows through formal channels and importantly, towards investment opportunities.
36
REFERENCES
Adams, R.H. 2009. The determinants of International Remittances in Developing Countries. World
Development Vol. 37, No. 1, 93-103.
Adenutsi, D.E. 2014.Macroeconomic determinants of workers’ remittances and compensation of
employees in Sub-Saharan Africa. The Journal of Developing Areas. Volume 48, No.1, Winter 2014.
Adenutsi, D.E., Aziakpono, M.J. & Ocran, M. K. 2012. Macroeconomic environment and remittances
in
Post-independent
Sub-Saharan
Africa:
Magnitudes,
trends
and
stylized
facts.
J.STUD.ECON.ECONOMETRICS, 36(2).
Aga, G.A. & Martinez Peria, M.S. 2014. International Remittances and Financial Inclusion in SubSaharan Africa. World Bank Group. Policy Research Working Paper 6991.
Ahortor, C.R.K. & Adenutsi, D. E. 2008. The impact of remittances on economic growth in smallopen developing economies. [Online]. Available at: http://mpra.ub.uni-muenchen.de/37109/
[Accessed on: 12 September 2015].
Artuc, E., Docquier, F., Özden, Ҫ. & Parsons, C. 2015. A Global Assessment of Human Capital
Mobility: The Role of Non-OECD Destinations. World Development Vol. 65, 6-26.
Azam, M. 2015. The role of migrant workers remittances in fostering economic growth. International
Journal
of
Social
Economics
Vol.
42
Issue
8,
690-705.
[Online].
Available
at:
http://dx.doi.org/10.1108/IJSE-11-2013-0255 [Accessed on: 16 August 2015].
Barua, S., Majumder, A. & Akhtaruzzaman, Md. 2007. Determinants of Workers’ Remittances in
Bangladesh: An Empirical Study. Policy Analysis Unit. Bangladesh Bank.
Beine, M., Docquier, F. & Oden-Defoort, C. 2011. A Panel Data Analysis of the Brain Gain. World
Development Vol. 39 No.4, 523-532.
Castillo-Ponce, R.A., Torres-Preciado, V.H. & Manzanares-Rivera, J.L. 2011. Macroeconomic
determinants of remittances for a dollarized economy: the case of El-Salvador. Journal of Economic
Studies, Vol. 38. Issue 5, 562-576.
Chami, R., Fullenkamp, C. & Jahjah, S. 2003. Are Migrant Remittance Flows a Source of Capital
Development? International Monetary Fund. IMF Working Paper WP/03/189, September 2003.
Chami, R., Barajas, A., Cosimano, T., Fullenkamp, T., Gapne, M. & Montiel, M. 2008.
Macroeconomic Consequences of Remittances. IMF Occasional paper No. 259.
Clemens, M. A., Özden, C. & Rapoport, H. 2015. Reprint of: Migration and development research is
moving far beyond remittances. World Development. Vol. 66, 121-124.
37
Docquier, F., Rapoport, H. & Salomone, S. 2012. Remittances, migrants’ education and immigration
policy: Theory and evidence from bilateral data. Regional Science and Urban Economics 42, 817828.
El-Sakka, M.I.T. & McNabb, R. 1999. The Macroeconomic Determinants of Emigrant Remittances.
World Development Vol. 27 No. 8, 1493-1502.
Fayissa, B. 2008. The Impact of Remittances on Economic Growth and Development in Africa.
Department of Economics and Finance Working paper series. February 2008.
FinMark Trust. 2012. SADC Remittance Flows Report. 17 January 2012. [Online]. Available at:
http://cenfri.org/remittances-and-financial-inclusion/the-south-africa-sadc-remittance-channel
[Accessed on: 12 September 2015].
Freund, C. & Spatafora, N. 2005. Remittances: Transaction costs, determinants, and informal flows.
World Bank Policy Research Working Paper 3704, September 2005.
Guha, P. 2013. Macroeconomic effects of international remittances: The case of developing
economies. Economic Modelling, No. 33, 292-305.
Gupta, P. 2005. Macroeconomic Determinants of Remittances: Evidence from India. International
Monetary Fund. IMF Working Paper WP/05/224, December 2005.
Giuliano, P. & Ruiz-Arranz, M. 2009. Remittances, financial development and growth. Journal of
Development Economics 90, 144-152.
Glytsos, N.P. 2005. The contribution of remittances to growth: A dynamic approach and empirical
analysis. [Online]. Available at: http://wwwemeraldinsight.com/0144-3585.htm [Accessed on:
12 September 2015].
Harvey, W. 2011. Brain circulation to the UK? Knowledge and investment flows from highly skilled
British expatriates in Vancouver. Journal of Management Development. Vol. 31 No. 2, 173-186.
Hudson Institute Center for Global Prosperity. 2013. The index of global Philanthropy and
Remittances,
with
a
special
report
on
emerging
economies.
[Online].
Available
at:
http://www.hudson.org/research/9914-2013-index-of-global-philanthropy-and-remittances-with-aspecial-report-on-emerging-economies [Accessed on: 1 May 2015].
International Monetary Fund. 2015. Sub-Saharan Africa. Navigating Headwinds. Regional Economic
Outlook, April 2015. Washington, D.C.: IMF.
Lim, S. & Morshed, A.K.M. 2015. International migration, migrant stock, and remittances:
Reexamining the motivations to remit. The Quarterly Review of Economics and Finance 57, 101115.
38
Lim, S. & Simmons, W.O. 2015. Do remittances promote economic growth in the Caribbean
Community and Common Market? Journal of Economics and Business 77, 42-59.
Lucas, R. & Stark, O. 1985. Motivations to remit: Evidence from Botswana. The Journal of Political
Economy, 93, 901-918.
Mail & Guardian. 2015. Sending money out of SA set to become easier and cheaper. 9 June 2015.
[Online] Available at: http://mg.co.za/article/2015-06-09-sending-money-out-of-sa-set-to-becomeeasier-and-cheaper [Accessed on: 7 November 2015].
Makina, D. 2012. Migration and Characteristics of remittance senders in South Africa. International
Migration. doi:10.1111/j.1468-2435.20212.00746.x
Makina, D. & Masenge, A. 2014. The time pattern of remittances and the decay hypothesis:
Evidence from migrants in South Africa. Migration Letters, Vol. 12, No: 1, 79-90.
Mills, G. 2011. Why Africa is poor and what Africans can do about it. Penguin Books (South Africa).
Mohapatra, S. & Ratha, D. 2011. Remittance markets in Africa. Directions in development finance.
Washington,
DC:
World
Bank.
[Online]
Available
on:
http://documents.worldbank.org/curated/en/2011/01/14102066/remittance-markets-africa
[Accessed on: 21 November 2015].
Mundaca, B.G. 2009. Remittances, Financial Market Development, and Economic Growth: The
Case of Latin America and the Caribbean. Review of Development Economics, 13(2), 288-303.
Ncube, M. & Brixiova, Z. 2013. Remittances and their macroeconomic impact: Evidence from Africa.
African Development Bank Group. Working Paper Series No.188, November 2013, Tunis, Tunisia.
Nyamongo, E.M., Misati, R.N., Kipyegon, L. & Ndirangu, L. 2012. Remittances, financial
development and economic growth in Africa. Journal of Economics and Business 64, 240-260.
OECD 2006. Part III: International Migrant Remittances and their role in Development. International
Migration Outlook. SOPEMI 2006 Edition.
OECD 2014. Chapter 10: What place for remittances in the post-2015 framework? Development
Cooperation Report 2014. Mobilising Resources for Sustainable Development. Available on:
http://asset.keepeek-cache.com/medias/domain21/_pdf/media2068/ [Accessed on: 24 July 2015].
OECD 2015. OECD Economic Surveys: South Africa 2015 [Online] Available on: http://www.oecdilibrary.org/economics/oecd-economic-surveys-south-africa-2015/executivesummary_eco_surveys-zaf-2015-2-en / DOI:10.1787/eco_surveys-zaf-2015-2-en [Accessed on:
19 September 2015].
39
Olivier, M. 2009. Regional Overview of Social Protection for Non-Citizens in the Southern African
Development Community (SADC). The World Bank: Social Protection and Labour. SP Discussion
paper: No. 0908.
Panda, D.P. & Trivedi, P. 2015. Macroeconomic Determinants of Remittances: A cross country
analysis. Journal of International Economics. Vol. 6, Issue 2, July-December 2015, 83-100.
Pendleton, W., Crush, J., Campbell, E., Green, T., Simelane. H., Tevera, D. & De Vletter, F. 2006.
Migration, remittances and development in Southern Africa. Southern African Migration Project.
Migration Policy Series No. 44.
Ratha, D., De, S., Plaza, S., Schuettler, K., Shaw, W., Wyss, H. & Yi, S. 2016. Migration and
Remittances – Recent developments and Outlook. Migration and Development Brief 26, April 2016.
World Bank, Washington, DC. Doi: 10.1596/978-1-4648-0913-2 License Creative Commons
Attribution CC BY 3.0 IGO.
Ratha, Mohapatra, Özden, Plaza, Shaw & Shimeless, 2011. Leveraging migration for Africa.
Remittances, skills and investments. World Bank. The International Bank for Reconstruction and
Development/The World Bank, Washington, D.C.
Rao, B.B. & Hassan, G.M. 2011. A panel data analysis of the growth effects of remittances.
Economic Modelling 28, 701-709.
Rapoport, H. & Docquier, F. 2006. The economics of migrants’ remittances. Handbook of the
Economics of Giving, Altruism and Reciprocity, Vol. 2.
Sarkar, B. & Datta, K. 2014. Determinants of Remittances to Bangladesh: A Regression Analysis.
IUP Journal of Bank Management, Vol XIII No. 3.
Segatti, A. & Landau, L.B. 2011. Contemporary migration to South Africa: a regional development
issue. Africa development forum. Washington, DC: World Bank. [Online] Available on:
http://documents.worldbank.org/curated/en/2011/01/14964992/contemporary-migration-southafrica-regional-development-issue
Singh, R.J., Haacker, M., Lee, K. & Le Goff, M. 2010. Determinants and Macroeconomic Impact of
Remittances to Sub-Saharan Africa. Journal of African Economies, Vol. 20 No. 2, 312-340.
Southern African Development Community (SADC). 2016. Member States. [Online] Available on:
http://www.sadc.int/member-states/ [Accessed on: 30 July 2016].
40
Southern African Development Community (SADC). 2011. Statistics Yearbook [Online] Available on:
http://www.sadc.int/information-services/sadc-statistics/sadc-statiyearbook
[Accessed
on:
Available
on:
20 October 2015].
Stark,
O.
&
Wang,
Y.Q.
2002.
Migration
Dynamics.
[Online]
https://www.ihs.ac.at/publications/eco/es-112.pdf [Accessed on: 30 July 2016].
Truen, S. & Chisadza, S. 2012. Remittances and Financial Inclusion: The South Africa-SADC
channel. FinMark Trust. [Online]. Available at:
http://www.finmark.org.za/publication/sadc-
remittances-flows [Accessed on: 12 September 2015].
UNECA.
Frontier
Markets
in
Africa.
Misperceptions
in
a
Sea
of
http://www.uneca.org/sites/default/files/PublicationFiles/africa_frontier_paper.pdf
Opportunities.
[Accessed
on:
17 June 2016].
Van Eyden, R., Owusu-Sekyere, E. & Kemegue, F. 2011. Remittance Inflows to Sub-Saharan Africa:
The Case of SADC. University of Pretoria: Department of Economics Working paper series. Working
paper: 2011-27. November 2011.
World Bank. 2013. Migration and Development Brief 21. Washington D.C. Migration and
Remittances Team. Development Prospect Group.
World
Bank.
2013b.
World
Bank
Indicator
Online.
[Online]
http://data.worldbank.orf/data-catalog/world-development-indicators
Available
[Accessed
on:
on:
8 October 2015].
World Bank. 2015. “5x5 Objective”. [Online] Available on: http://go.worldbank.org/7RKUKJF3Q0
[Accessed on: 2 November 2015].
World
Bank
Development
Indicators.
2016.
[Online]
Available
on:
http://databank.worldbank.org/data/reports.aspx?source=world-development-indicators [Accessed
on: August 2016].