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REPS
7,3 Migrants’ remittances and economic
growth in Egypt: an empirical
analysis from 1980 to 2017
154 Rasha Qutb
Department of Economics, Faculty of Commerce, Damanhour University,
Received 21 October 2018 Damanhour, Egypt
Revised 25 May 2019
21 August 2019
10 January 2020
7 June 2020
9 June 2020 Abstract
9 July 2020
11 October 2020
Purpose – Migrants’ remittances to Egypt have increased considerably in both size and importance over the
15 November 2020 past 40 years. This increase has made Egypt one of the top remittance recipients in the world and the leading
Accepted 5 January 2021 recipient country in the Middle East. As migrant remittances are one of Egypt’s main sources of foreign
capital, this study aims to identify the impact of these remittances on economic growth.
Design/methodology/approach – The study collects annual data on migrant remittances sent to Egypt
during the period 1980–2017. The study uses the Augmented Dickey–Fuller test and Johnsen’s Co-integration
test to establish long-run relationships between variables. Then, a vector error correction model (VECM) is
used to combine long-run and short-run dynamics, and a Granger causality test is performed. Finally,
diagnostic tests of the VECM are conducted.
Findings – Results reveal that migrants’ remittances to Egypt are countercyclical in the sense that they
have a long-term negative impact on economic growth. These results are determined by the Granger causality
between migrants’ remittances, inflation rate and imports.
Practical implications – The study can help policymakers to develop appropriate policies to turn
migrants’ remittances into a reliable source of capital that could result in a stable economic growth.
Originality/value – Although various empirical studies have examined the growth effect of remittances,
most of them are based on cross-country data. This study contributes to the field by attempting to close a gap
in the literature by empirically analyzing the impact of remittances on a single country over a long period.
Keywords Egypt, Economic growth, Granger causality, Johansen co-integration,
Migrants’ remittances, Vector error correction model, Remittances inflows
Paper type Research paper

1. Introduction
Over the past three decades or more, migrant remittance inflows to developing economies
have been considered an important economic development tool because of their impact on
the overall growth of the recipient economies (Aggarwal et al., 2006, p. 1). Remittance
inflows to developing economies have been growing and have become the second main
source of foreign exchange after foreign direct investment (FDI); therefore, they represent a
major source of international capital flows, exceeding official development assistance and

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pp. 154-176
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e-ISSN: 2631-3561 legalcode
p-ISSN: 2356-9980
DOI 10.1108/REPS-10-2018-0011 JEL classification – F24, O4, C22
export revenues as far back as 1997. They have also exceeded private debt and portfolio Economic
equity flows in recent years (Giuliano and Ruiz-Arranz, 2005, p. 5; Kamuleta, 2014, p. 1). The growth in
role that migrants’ remittances play in the growth of global capital flows has attracted
much attention due to its stable growth despite financial crises and economic declines. This
Egypt
stability helps to reduce income inequalities and volatility, alleviate poverty, prevent crises
that would otherwise occur in the balance of payment and boost the recipient country’s
economic growth rate (Ratha, 2013, p. 1; Datta and Sarkar, 2014, p. 2).
Broadly defined, remittances are the transfers of cash from migrants working abroad to 155
individuals in their home country through official and unofficial channels (Zohry, 2007,
p. 46; Naga, 2015, p. 21; Karagoz, 2009, p. 1893). Recipients can use the remitted funds in
various ways but usually invest the money or spend it on living expenses, education and
health care (Karagoz, 2009, p. 1891).
As remittances have been a reliable source of foreign exchange for developing
economies, they can have a potential impact on the growth of those economies because they
can influence consumption, investment, savings, poverty and income distribution (Rao and
Hassan, 2012, p. 351; Rahman, 2014, p. 140). However, the increased consumption that
results from migrant remittances may also have negative macroeconomic effects (Adam,
1991; Wahba, 2007; Glytsos, 2002, p. 6; World Bank Group, 2006; Rao and Hassan, 2012,
p. 352; Rahman, 2014, p. 141; Stratan and Chistruga, 2012; Goschin, 2014, p. 56).
In 2017, global remittances reached $613bn, which represented a 7% growth rate from
2016 to 2017 (World Bank Report, 2018). Officially recorded remittances sent to low- and
medium-income countries reached $466bn in 2017 amounting to three-quarters of total
global remittances and representing an increase of approximately 8.5% from the $429bn
recorded in 2016. This considerable growth in remittances among developing and developed
economies can be attributed to many factors including the acceleration of labor migration
and ongoing improvement in real wages paid to migrants around the world (Center for
Social and Economic Research, 2012, p. 6). Furthermore, transaction costs decreased as
technological improvements have created faster, lower-cost mechanisms to facilitate
international payments between individuals (Giuliano and Ruiz-Arranz, 2005; World Bank
Group, 2006; Abu Siddique and Selvanathan, 2010).
Remittance inflows to the MENA region increased by 9.3% in 2017; reaching $53bn;
$24.7bn of that total was sent to Egypt, making it one of the top ten remittance recipient
countries in the world. Therefore, it is important to analyze the impact of migrants’
remittances on economic growth, as such remittances are among the major sources of
foreign capital inflows to the Egyptian economy. ’This study tests the hypothesis that –
“remittance inflows to the Egyptian economy could promote economic growth along with
other types of foreign capital inflows, mainly international development aid and Foreign
Direct Investment (FDI)”. The study covers the period between 1980 and 2017 and uses
“Johansen’s co-integration test” – within VECM to test the hypothesis. Granger causality
test is used to explore the causal relationship between migrants’ remittances and economic
growth.
Although various empirical studies have examined the effect of migrants’ remittances on
economic growth; most of them use data across multiple countries, rather than focusing on
an individual country. This study uses data for a single country that is one of the top
recipients of migrants’ remittances globally, thereby contributing to the literature by
empirically analyzing the effect of remittances for a specific country over a long period.
Thus, the study can help policymakers develop appropriate policies to convert the
potential for economic growth represented by migrants’ remittances into a reliable source of
capital that results in stable economic growth.
REPS This study’s findings reveal that migrants’ remittances have a negative impact on
7,3 economic growth in Egypt, and that the effect of the remittances on the economy is
countercyclical because they lead to the increase in imports, which consequently fuels
inflation.
The remainder of the study is organized as follows. The next section reviews the history
of migrants’ remittances in Egypt and demonstrates the possible investment opportunities
156 they represent. The third section discusses the potential effects of migrants’ remittances on
economic growth in the recipient country and offers a review of the literature. The fourth
section provides the empirical model, data sources and results of the study. The final section
offers conclusions.

2. Egyptian migrants’ remittances

2.1 Historical background and potential investment opportunities
Emigration from Egypt began in the mid-1970s, triggered by many factors including
poverty, persistent high unemployment, rapid population growth and the oil boom in the
countries around the Arabian Gulf that led to an increasing demand for imported labor
(Zohry, 2007, p. 1). The positive side of the growth in Egyptian emigration was the increase
of migrants’ remittances to Egypt, which became a vital component of the country’s
national income. By the mid-1990s, Egyptian migrants’ remittances had become one of the
country’s main sources of foreign exchange, even exceeding revenues from the Suez Canal
(International Organization for Migration, 2010, 7:20).
Figure 1 displays the evolution of Egyptian migrants’ remittances during the period from
1980 to 2017, which rose from $2.7bn in 1980 to $24.7bn in 2017. Despite being private
capital inflows, migrants’ remittances in Egypt have been noticeably influenced by changes
in the country’s political and economic conditions over this period, except during the decade
of the 1980s, which was characterized by relative stability. For instance, the remarkably
high levels of Egyptian migrants’ remittances in 1992 and 1993, which reached $6.1bn and
$5.66bn, respectively, reflected conditions in the period immediately following the first Gulf
War.
Separately, the period following the sharp devaluation of the Egyptian pound in 2004
witnessed an unusually high level of migrants’ remittances that reached an average of
$6.6bn over the period 2004–2008. In spite of the international financial crisis in 2008–2009
that resulted in a 10% decrease of annual migrants’ remittances globally, Egypt ranked
seventh in the top remittance recipient countries in 2009, after India, China, Mexico,
Philippines, Poland and Nigeria (Ratha et al., 2008, p. 3; Ratha et al., 2009). There was a
noticeable increase in Egyptian migrants’ remittances during the period from 2010 through
2017, reaching an average of $18.13bn (a 98% growth rate). This increase covered the period
that included the 2011 Revolution and the second devaluation of the Egyptian pound in
2016. It is worth noting that average annual migrants’ remittances to Egypt between 1980
and 2017 were nearly $7.6bn.

30
US $ (Billion)

20
Figure 1.
10
Total Egyptians’
0
remittances
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017

during the period

(1980–2017)
Source: UNCTAD
The importance of migrants’ remittances to Egypt can be evaluated based on its share of the Economic
country’s gross domestic product (GDP). Figure 2 shows the steady growth in the growth in
importance of Egyptian migrants’ remittances as a share in Egypt’s GDP from 1980 to 2017.
With the exception of the periods from 1980 to 1982 and from 1989 to 1991, as well as the
Egypt
year 2017 (during which Egyptian migrants’ remittances were the country’s second largest
source of foreign exchange and represented 17.3% of its GDP), the share of the Egyptian
migrants’ remittances inflows in the country’s GDP was generally less volatile and
157
represented a much larger share of international capital flows than other sources, including
official development assistance and FDI.
Following the devaluation of the Egyptian pound in 2016 through the end of 2017,
remittances to Egypt reached US$29bn, jumping by 16.2%. This may be an indicator of the
success of liberalizing the exchange rate and of the subsequent severe devaluation of the
pound that encouraged Egyptians to transfer more funds through legal channels [1].
Although the size of remittances was significant, its share of GDP was less than that of
FDI for the fiscal year 2017, due to reforms and incentives created by the Egyptian
Government to stimulate investment prospects in the country. In 2018, remittances were the
second largest factor in reducing the government’s deficit, as they increased by $3bn
between 2017 and 2018.
The Egyptian economy’s current account deficit fell sharply to $3.4bn in 2018, compared
to $9.4bn in 2017, a decrease of 64%. This reduction is largely attributed to significant
improvements in key sources of national income, especially Egyptian migrants’
remittances. This suggests that the Egyptian economy could capitalize on these growth-
driven inflows by making them a reliable source of capital.
Although the economy receives a considerable portion of Egyptian migrants’ remittances,
they are the second source of migrant household income after labor income, both of which
alleviate poverty. The majority of these remittances is used for housing and everyday
consumption expenses instead of investment, which can have a negative effect on the country’s
economic growth (Center for Social and Economic Research, 2012, p. 7; International
Organization for Migration, 2010, p. 11).One of the reasons individuals do not invest a
significant portion of remittances can be attributed to the average Egyptians’ low awareness of
the government’s investment program.

30

25 workers' Remiances
inflows (as % of GDP)

20
% of GDP

FDI inflows (as % of GDP)

15

10
Net Official Development
Assistance inflows (as % of Figure 2.
5
GDP) Remittances, FDI
inflows and ODA (as
0 YEAR a % of GDP) in Egypt
1980 1985 1990 1995 2000 2005 2010 2014 2017
during the period
(1980–2017)
Source: WDI, Migration and Remittances Fact-book and GAFI
REPS The largest number of Egyptian migrants resides in the Kingdom of Saudi Arabia (KSA),
7,3 whereas a smaller and wealthier group live in the USA. Combined, these are the largest
source of migrants’ remittances to Egypt. Therefore, Egyptians who live in KSA and the
USA need more attention from policymakers who should try to encourage Egyptian
migrants there to direct remittances into productive investments in Egypt. Moreover, the
main concern of migrants when sending remittances to their families in their home country
158 is to transfer enough money to address basic daily needs. Many of Egypt’s migrants do not
invest in the country for a number of reasons, including individual financial difficulties, lack
of easy access to cash or credit, the risky investment climate in Egypt and a lack of
awareness of the government’s investment programs (International Organization for
Migration, 2010, p. 57).
The government has taken several positive steps to improve the investment environment
in Egypt and to overcome critical obstacles that impede investment, including changing and
amending several laws and creating a “one-stop-shop” for investors. Guidelines have also
been designed to help small enterprises gain access to capital more like large-scale
businesses. Even with these changes in laws and policies, some existing laws would have to
be modified to improve the investment environment for small-scale investors such as
migrant families, to help them invest their remittances in a productive way (International
Organization for Migration, 2010, p. 58). A family’s decision to invest is determined by not
only the money that remains after meeting their basic needs but also the overall economic
environment.

3. Migrants’ remittances and economic growth

3.1 Theoretical background
For relatively small and developing countries, migrant remittances are considered the
“second pillar” of financing the development process along with other sources of foreign
capital, because the steady growth of remittances helps to lessen the volatility of output and
thereby stimulates the rate of economic growth (Rao and Hassan, 2012, p. 351; Datta and
Sarkar, 2014, p. 2).
Moreover, remittances can help developing countries to address a number of challenges,
including shortages in foreign exchange reserves, problems in the balance of trade, the
limited impact of foreign aid and borrowing difficulties, by providing a constant and reliable
source of foreign currency, which in turn stabilizes the economies of the migrants’ home
countries (Ratha, 2005; Lopez-Cordova and Olmedo, 2006; Glytsos, 2002, p. 6; Ratha, 2013,
p. 71; Tahir et al., 2015). Moreover, remittances help to reduce current account deficits by
inducing investment (Daianu, 2001; Terry et al., 2004; Abu Siddique and Selvanathan, 2010).
Remittance inflows can also play a role in reducing official development assistance, can
act as an alternative to debt, thereby helping to alleviate poverty, and can improve the
creditworthiness of the receiving countries (Ratha, 2013, p. 2). Furthermore, remittances
improve the development of the financial sector, which in turn augments the growth in
output by easing credit restrictions for investments (Aggarwal et al., 2006; Giuliano and
Ruiz-Arranz, 2005; Rao and Hassan, 2012, p. 352).
Empirical studies have recorded different effects of remittance inflows on
macroeconomic variables in the home country. Migrants’ remittances stimulate economic
growth directly in their home economies through two main approaches. The first is the
family approach, referring to the temporary effect of migrants’ remittances on the economy
through increased consumption. In this case, when economic conditions in migrants’ home
countries are poor, they send money to their families out of concern about their welfare
(Carling, 2004; Lueth and Ruiz-Arranz, 2006; Singh et al., 2011, pp. 315–316, Goschin, 2014, p. 56;
OECD, 2006). As remittances are less prone to cyclical variations than other capital inflows, Economic
migrants from poor countries may actually increase their remittances when economic conditions growth in
decline (Center for Social and Economic Research, 2012, p. 7); therefore, remittances can help to
reduce income inequality and poverty in the recipient countries by alleviating the true impact of
Egypt
a recession and losses related to other disasters (Quibria, 1997; Taylor, 1999; Adams and Page,
2003; Docquier and Rapoport, 2003; Yang, 2008, p. 3; Datta and Sarkar, 2014, p. 2) [2].
The second approach is the permanent impact of savings and investment; this supply-
side impact can be called “the portfolio approach” (Carling, 2004; Rahman, 2014, p. 140; 159
Goschin, 2014, p. 56; OECD, 2006).) . In this approach, remittances are one form of foreign
capital where migrants send money to their families in their home country for the purpose of
investment (Ratha, 2003, p. 3; Leon-Ledesma and Piracha, 2004). Both Chandavarkar (1980)
and Carling (2005) note that only a small proportion of remittances are productively
invested, which is a source of disappointment among policymakers.
It is worth noting that even if remittances are not invested, remittance-based
consumption can enhance economic growth because it indirectly raises employment and
production through the multiplier effect, injecting capital into the economy through
consumption (Aggarwal et al., 2006; Stahl and Arnold, 1986; Rapoport and Docquier, 2005,
p. 48). Therefore, if remittances are invested they can contribute to economic growth, and if
they are consumed they can generate a positive multiplier effect in the economy (Ratha,
2003, p. 3).
According to Barajas et al. (2009), there are three channels through which remittances
can affect economic growth: first, by directly investing in capital accumulation; second, by
labor inputs through labor force contributions; and third, by affecting total factor
productivity growth (Rahman, 2014, p. 141). Furthermore, Glytsos (2005) suggests that
remittances can promote economic growth by increasing imports of capital goods. On the
other hand, many studies have found that increased consumption due to remittances can
have negative macroeconomic impacts on home countries. For example, Wahba (2007)
found that remittance inflows to Syria and Egypt caused higher inflation, which in turn
negatively affected economic growth. Adams (1991) found a high increase in property
values (mainly the price of land) attributable to remittances (Goschin, 2014, p. 56).
In the same manner, Stahl and Arnold (1986), Rahman et al. (2006) and Abu Siddique and
Selvanathan (2010) pointed out that remittances do not contribute to economic growth
because of them lead to unproductive consumption spending, i.e. spending on consumption
instead of investing in productive assets. Remittances may also have an indirect negative
impact on the real exchange rate. The increase in remittances can cause the real exchange to
appreciate, which adversely affects growth, leading to what is known as the Dutch disease
(Rao and Hassan, 2012, p. 352). In the end, the net effects of migrants’ remittances on
economic growth can be measured by analyzing both direct and indirect multiplier effects
on macroeconomic variables.

3.2 Literature Review

Remittances remained a vital source of financing for development in recipient economies,
due to their stability during periods of economic crises and their being the second largest
source of foreign capital after FDI. Therefore, a large portion of the previous literature on
remittances focused on their contribution as a source of foreign capital for economic
development in migrants’ home countries (Ratha and Prabal, 2012; Goschin, 2014, p. 55).
While the remittances–growth nexus has been empirically tested to a significant extent in
the literature, there is a substantial debate among economists regarding the impact of
remittances on economic growth of migrants’ home countries.
REPS Most previous studies have found that remittances have a positive impact on the
7,3 economies of recipient countries. For instance, Giuliano and Ruiz-Arranz (2005) found that
migrants’ remittances had the potential to influence growth through the multiplier effects of
increased consumption and decreased liquidity constraints. Analyzing panel data for 36
African countries over the period 1980–2004, Fayissa and Nsiah (2010) found that
remittance inflows had a positive impact on the economic growth of migrants’ home
160 countries by providing an alternative way to finance investment and helping to alleviate
cash constraints.
The same conclusion was reached in Rahman (2007), which re-examined the effect of
remittances, exports and FDI on the actual GDP of the recipient countries of Bangladesh,
Sri Lanka, India and Pakistan for the period 1976–2006, by applying autoregressive
distributed lag (ARDL) model.
Using a panel data set of MENA countries, (Algeria, Egypt, Jordan, Lebanon, Libia,
Morocco, Oman, Syria and Tunisia), Yaseen (2012) examined the effect of remittances on
economic growth through two channels, financial development and institutions. Findings
indicated that institutions and financial development both played an important role in how
remittances affect economic growth during the period 2000–2010. Using a production
function framework, Waqas (2013) found a link between workers’ remittances and economic
growth in Pakistan between 1991 and 2012.
Similarly, Goschin (2014) found remittances have a positive influence as a source of capital
flow for both absolute and relative GDP growth in CEE countries during the period from
1995 to 2011. By applying an ARDL model to analyze time series data covering the period
1977–2013 in Pakistan, Tahir et al. (2015) found that remittances promoted economic growth
alongside other external determinants such as imports and FDI. More recently, Comes et al.
(2018) investigated the combined effect of FDI and migrants’ remittances on economic growth
using data for seven Eastern and Central European countries with a per capita GDP of less
than 25,000 Euros. Their findings showed a positive impact for both FDI and remittances on
GDP, but the influence of FDI was greater. Other studies that showed remittances have a
positive impact on economic growth include Leon-Ledesma and Piracha (2004), Lueth and Ruiz-
Arranz (2006), Mundaca (2009), Abu Siddique and Selvanathan (2010), Ahmed et al. (2011),
Bugamelli and Paternò (2009), Khathlan (2012), Shafiq et al. (2012), Driffield and Jones (2013),
Datta (2014), Nwaogu and Ryan (2015) and Olayungbo and Quadri (2019).
However, other researchers have noted that migrants’ remittances could have a negative
impact on economic growth in the migrants’ home countries. For example, Jahjah et al.
(2003) discovered that remittances reduced work incentives for the recipients. Additionally,
they clarified that the effect of remittances on GDP for a large panel of countries translated
into labor reduction the migrants’ home countries, as remittances could reduce work
incentives for the recipients, leading to reductions in the workforce, especially with respect
to skilled workers.
Analyzing data collected from 101 developing countries, Chami et al. (2005) concluded
that the funds emigrants sent back home were only “compensatory transfers” that provided
support to poor families during difficult times but were not profit-promoting capital flows.
Hence, remittances resulted in fewer work incentives and created moral hazard problems
that had a negative impact on economic growth.
A World Bank study conducted in 2006 also showed that large remittances undermined
long-term economic growth in 22% of recipient countries because the inflows resulted in
exchange rate appreciation and a reduction in subsequent exports. The negative impact of
migrants’ remittances on economic growth was particularly notable in small economies
where reliance on migrants’ remittances was high. Singh et al. (2011) found that remittances
were countercyclical and proposed the hypothesis that remittances can work as a shock Economic
absorber. Finally, in some studies, such as Spatafora (2005), Barajas et al. (2009), Naga (2015) growth in
and Njangang et al. (2018), remittance inflows were found to have an insignificant effect on
economic growth.
Egypt
In summary, migrants’ remittances could, theoretically, have a positive impact on
economic growth in the recipient economy by acting as a source of capital that induces
investments and compensates for the workforce loss due to emigration. However, migrants’
remittances could have a negative impact on economic growth because they may lead to 161
increased demand for high-priced “non-tradable goods”, which may then lead to inflation.
Furthermore, remittance-based consumption can increase inflation and reduce work
incentives. Finally, remittances can have an insignificant impact on economic growth
because of recipients are unaware of how they could invest the money. This literature
review indicates that the impact of remittance inflows on the economic growth of the
Egyptian economy cannot be predicted from previous studies

4. Empirical model of economic growth with remittances

4.1 Theoretical model and data description
This study empirically examines the impact of migrants’ remittances, as a source of capital,
on the economic growth of Egypt alongside other sources of foreign capital such as official
development assistance (ODA) and FDI. The study is carried out within “the traditional
neoclassical growth model”; it focuses on the period 1980–2017. The study is based on many
previous empirical studies such as Fayissa and Nsiah (2010), Driffield and Jones (2013),
Tahir et al. (2015) and Olayungbo and Quadri (2019). The adopted function is established as
follows:

EGt ¼ f ð REMt ; FDIt ; ODAt ; Tradet Þ

Where t is time trend, EGt, REMt, FDIt, ODAt and Tradet are economic growth, remittance
inflows, FDI, official development assistance and Trade openness respectively. The
empirical model of the study is as follows:

EGt ¼ a0 þ a1 REMt; þ a2 FDIt þ a3 ODAt þ a4 Tradet þ « (1)

By taking the natural logarithm for our variables, the impact of outliers is minimized and
elasticity coefficients of variables are obtained. Thus, the structural form of the main
estimated model can be represented in a double-log function as follows:

ln EGt ¼ b 0 þ b 1 ln REMt þ b 2 ln FDIt þ b 3 ln ODAt þ b 4 ln Tradet þ « t

Where the endogenous variables include the natural logarithm of real GDP per capita (Ln
EGt), the natural logarithm of remittances as a percentage of GDP (Ln REMt), the natural
logarithm of FDI inflows as a percentage of GDP (Ln FDIt), the natural logarithm of net
official development assistance as a percentage of GDP (Ln ODAt) and the natural logarithm
of trade openness measured by summing of imports and exports as a percentage of GDP (Ln
Tradet). Note that both variables (Ln FDIt), and (Ln ODAt) capture the impact of other
sources of external exchange.
The study follows the next three steps; first, the “Augmented Dickey-Fuller” test is used
to check stationarity on every single variable to avoid “spurious regression”; second, in
order to ensure the long-run “equilibrium” relationship among variables Johansen’s Co-
REPS integration test is employed; and third to combine both long and short-run dynamics, VECM
7,3 is conducted. The “structural” form for the economic growth equation is given as:

D Ln EGt ¼ b 0 þ b 1 DLn EGt ðtiÞ þ b 2 D Ln REMðtiÞ þ b 3 DLn FDIðtiÞ þ b 4 DODAðtiÞ

þ b 5 Ln TradeðtiÞ þ l ECMt1 þ « t
162 Where:

ECMt1 ¼ Ln EGt ðt1Þ  a0 – a1 Ln REMðt1Þ  a2 Ln FDIðt1Þ  a3 ODAðt1Þ  a4 Ln Tradeðt1Þ

Here the “short-run dynamics” of the variables in the “ECM” are represented by the series in
differences while the long-run relations of the variables in levels.
The “speed of adjustment coefficient” l ‘, which is expected to be negative, represents
the amount of “correction” of the period (t – 1) disequilibrium that happens in period t. This
test is applied when all variables are appeared to be purely integrated at the first difference.
Also, the Granger causality test is conducted between GDP and remittances (Granger, 1981;
Brooks, 2008). Finally, the diagnostic Tests of the Model is conducted to ensure that the
model is stable and adequately passes the econometric pathology for residual serial
correlation, “Lagrange Multiplier test,” normality of residuals; “normality test Jarque-Bera,”
and “heteroscedasticity” test, and this is shown by the p-value.

4.2 Data sources and empirical results

4.2.1 Data sources. The data for the variables of interest are collected from various
sources. Data about total exports and total imports are gathered from the Central
Agency for Public Mobilization and Statistics. Data about GDP per capita, annual
inflation rate and net international development aids are obtained from “World
Development Indicators” database. Additionally, FDI inflows are obtained from general
authority for investment and free zones. Finally, data series about workers ‘remittance
inflows are obtained from “Migration and Remittances Fact-book.”

4.3 Stationarity analysis

Prior to testing of cointegration, a “unit root” test for each variable is conducted using
“Augmented Dickey-Fuller” test. The stationarity test results shown by Table 1 reveal that
all the variables are non-stationary at levels, while they are all stationary at the “first
difference.” Thereby, Johansen Co-integration test is conducted to check the long-run
relationship.

4.4 Analysis of the results

4.4.1 Johansen co-integration test. The test results, as shown in Table 2, assert that there is a
long-run relation between variables according to the values of “Trace statistics” and “Max-
Eigen statistics” introduced by Johansen (1988, 1992) and Johansen and Juselius (1988),
which test the null hypothesis that “the number of co-integrated variables are less than/or
equal r” co-integrating vectors.” Hence the hypothesis of existing at least one co-integrated
vector between the variables can’t be rejected.
The “trace” test statistics indicates “one co-integration” equation at a 5% significance
level. Therefore, Co-integration indicates that there is a “linear combination” of non-
stationarity variables that are stationarity and that they have to be included in VECM.
 Critical value Probability*
(t- statistic) (1%) level (5%) level Co-integration
At first At first At first At first Co-integration degree
Variables At level difference At level difference At level difference At level difference degree (at level) (at first difference)

Ln EGt 0.9 2.16 3.6 2.6 2.9 1.95 0.74 0.03 I(1) I(0)
Ln REMt 1.3 5.0 3.6 2.6 2.9 1.95 0.64 0.000 I(1) I(0)
Ln FDIt 2.5 5.1 3.6 2.6 2.9 1.95 0.12 0.000 I(1) I(0)
Ln ODAt 2.4 4.5 3.6 2.6 2.9 1.95 0.16 0.000 I(1) I(0)
Ln Tradet 1.3 2.4 3.6 2.6 2.9 1.95 0.57 0.015 I(1) I(0)

Note: *MacKinnon (1996) one-sided p-values

results
Table 1.
growth in

163
Egypt

Fuller unit root test

Augmented Dickey–
Economic
REPS 0.05 0.05
7,3 Hypothesized Trace Critical Max-Eigen Critical
No. of CE(s) Eigenvalue statistic value Prob.** statistics Value Prob.** Result

None *(r = 0) 0.690764 76.57588 69.81889 0.0131 42.25142 33.87687 0.0040 Reject H0
At most 1(r # 1) 0.438220 34.32446 47.85613 0.4842 20.75922 27.58434 0.2910 Accept H0
At most 2(r # 2) 0.185426 13.56524 29.79707 0.8641 7.383223 21.13162 0.9373 Accept H0
164 At most 3(r # 3) 0.157089 6.182014 15.49471 0.6740 6.152160 14.26460 0.5938 Accept H0
At most 4(r # 4) 0.000829 0.029853 3.841466 0.8628 0.029853 3.841466 0.8628 Accept H0
Table 2.
Johansen co-integration Notes: Trace test and Max-eigenvalue test indicates 1 cointegrating eqn(s) at the 0.05 level; *denotes
test rejection of the hypothesis at the 0.05 level; **MacKinnon-Haug-Michelis (1999) p-values

4.4.2 Vector error correction model. Variables can either have short or long-run effects. This
study utilizes a vector error correction model (VECM) to disaggregate these effects.
Before discussing the short-run and long-run results of the VECM, The diagnostic tests are
used to make sure of the reliability of the model. The results of diagnostic tests indicate that the
“VECM” sufficiently passes the econometric pathology for residual serial correlation using
“Lagrange Multiplier” test, normality of residuals through “normality Jarque-Bera” test and for
homoscedasticity when using the “VEC Residual Heteroskedasticity” test. This is indicated by
the “p-value” given within the square brackets. The result of the diagnostic test of the model is
given in Table 3. Additionally, the stability test of the VECM model is checked by the inverse
roots of the characteristic auto-regression polynomial graph as indicated by Figure 3.
According to Lutkepohl (1991), the estimated model is stationarity as all roots have modulus
less than one and lie inside the unit circle.
4.4.2.1 Long-term results. The estimated long-term relationship between variables are
shown in Table 4 [3] (Table 5).
These results reveal that the estimated long-term impact of a 1% increase in annual
workers’ remittances as a percentage of growth in per capita GDP is approximately []
0.24%, which means that an increase in remittances causes a decline in GDP per capita
growth. This negative impact is consistent with the result in Chami et al. (2005), who found
that remittances do not serve as a source of economic growth and is therefore negatively
correlated with GDP growth, implying that the money emigrants send back home can be
classified as “compensatory transfers” that provide support to poor families during periods
of financial difficulties, but are not profit-driven capital flows. For instance, many workers
lost their jobs, especially in tourism and other strategic sectors during the economic
slowdown in 1991–1992, which was associated with the implementation of Egypt’s

Test Null hypothesis

Jarque-Bera (JB) There is a normal distribution Jarque-Bera: 5.319

Prob. 0.86
Serial Correlation LM Tests No serial correlation LM st: 21.8
Prob. 0.64
Table 3. White (CH-sq) No conditional heteroskedasticity Chi-sq: 486.04
Diagnostic tests of Prob. 0.4146
the error correction
model Source: Computed by using E-Views packages
 Inverse Roots of AR Characteristic Polynomial Economic
1.5 growth in
Egypt
1.0

0.5
165
0.0

–0.5

–1.0
Figure 3.
Checking the stability
–1.5 of VECM
–1.5 –1.0 –0.5 0.0 0.5 1.0 1.5

The dependent variable: LNEGt

Regressors Coefficient Standard Error t-statistics

LNREMt 0.242357 0.03709 6.56634***

LNFDIt 0.094125 0.02241 4.19974*** Table 4.
LNODAt 0.136915 0.03248 4.21560***
LNTRADEt 0.498246 0.04259 11.6975***
Long-run
CONSTANT 8.229450 relationship of the
variables estimated
Note: ***Significant at 1% using VECM

Lag LogL LR FPE AIC SC HQ

0 96.04598 NA 0.000262 5.943881 6.168346 6.020430

1 70.19552 273.8095* 6.59e-08 2.364442 1.017654* 1.905149
2 95.46177 34.18375 7.18e-08 2.380104 0.089009 1.538066
3 117.1030 22.91424 1.16e-07 2.182529 1.408907 0.957746
4 165.9692 37.36830 5.37e-08* 3.586426* 1.127335 1.978898* Table 5.
Optimal lag length
Note: *Indicates lag order selected by the criterion selection

Economic Reform and Structural Adjustment Program, followed by a period of privatization

policy adoption. The same happened after the 2009 financial crisis, and in the period that
followed the 2011 revolution. During these times of economic difficulties, remittances served
as compensatory transfers. As Wahba (2007) observes, a majority of these remittances are
spent on housing and consumption expenditures, rather than on productive investments;
therefore, they do not benefit the country’s economic progress as a whole.
Similar to the results in Eltahir (2013), the findings here reveal a positive effect of trade
openness on economic growth. Moreover, these results reveal a significant positive effect of
FDI inflows on economic growth, consistent with the result in Wang and Swain (1997),
REPS Chang (2007) and Maningi and Martin (2018)). The results also match those of Burnside and
7,3 Dollar (2000) who show that official development aid has a positive impact on growth [4].
4.4.2.2 Short-term results. Table 6 presents the results of the “short-run dynamics,”
where the estimated coefficients of the model show the immediate and lagged impacts of
remittances D(Ln REM), FDI D(Ln FDI), official development assistance, D(Ln ODA) and
imports, D(Ln M), on the growth of GDP per capita D(Ln EG).
166 The estimates of short-term effects estimates from the first model indicate that the
temporary impact of the previous two periods of remittances on GDP per capita is
insignificant, while the effect of third lag GDP/capita is negative and significant.
Similarly, both one- and three- period lagged ODA have a significant negative impact on
GDP per capita, while the impact of two periods lagged ODA is insignificant.
Therefore, the short-term effect of remittances, FDI and trade openness appear to be
largely insignificant in terms of their impact on GDP per capita in Egypt over the period
studied.
Lastly, the speed of adjustment coefficient in the model (l = 0.91) is significant,
asserting the existence of a long-term relationship between variables in the model. This
estimated value represents the speed of adjustment of short-term GDP per capita
toward its long-run (average) equilibrium level, which means that approximately 91%
of the previous deviation of the previous period’s GDP per capita, (yt–1), from its
equilibrium value will be corrected in the current period (because the sign of l is
negative). Thus, it takes approximately 13 months for GDP per capita to return to its
“equilibrium” level.
4.4.3 Granger – causality. In this section we test for causality between remittances and
GDP. As there is co-integration among the variables of concern (remittances and real GDP)
as indicated in Table 7, we run a pairwise “Granger-causality” test [5]. Based on the results,
we conclude there is bidirectional causality from GDP to remittances; such causality
indicates that growth in remittance inflows is derived from economic conditions in the
recipient economy and can be either countercyclical or procyclical [6]. There is also causality

Error Correction Coefficient S.E t-statistics

CointEq1 (D(LNEG) 0.123345 0.03414 3.61265**

D(LNEG(1)) 0.134107 0.17581 0.76280
D(LNEG(2)) 0.177314 0.18278 0.97012
D(LNEG(3)) 0.370490 0.16800 2.20533**
D(LNREM(1)) 0.013711 0.01283 1.06870
D(LNREM(2)) 0.004012 0.01314 0.30521
D(LNREM(3)) 0.001898 0.01230 0.15440
D(LNFDI(1)) 0.001567 0.00459 0.34166
D(LNFDI(2)) 0.000973 0.00425 0.22903
D(LNFDI(3)) 0.004420 0.00349 1.26559
D(LNODA(1)) 0.013196 0.00584 2.26015**
D(LNODA(2)) 0.006088 0.00655 0.92928
D(LNODA(3)) 0.012548 0.00632 1.98525**
Table 6. D(LNTRADE(1)) 0.016755 0.02234 0.74991
D(LNTRADE(2)) 0.010409 0.02113 0.49264
Short-run D(LNTRADE(3)) 0.000305 0.02455 0.01241
relationship of the C 0.026166 0.00606 4.31963***
variables estimated
using VECM Notes: *Significance at 10%, **significance at 5%, ***significant at 1%
that runs from remittances to real GDP, which implies a potential impact of remittances on Economic
economic growth, and that the causal relationship can be positive (if remittances are directed growth in
toward investment projects) or negative (if remittances are directed toward imports of
consumption goods). This is one possible explanation of the negative impact of remittances
Egypt
on the Egyptian economy.
In an attempt to find a possible economic explanation for the negative long-term effect of
remittances on GDP per capita, we examine a Granger causality test [7] (Table 8) where new
variables are introduced in addition to the main variables; these include the inflation rate
167
(Inflation) and imports (LnM) [8]. The results of the “pairwise Granger-causality” test as
shown in Table 9, reveal that:
 A unidirectional Granger causality runs from remittances to imports.
 A unidirectional Granger causality runs from remittances to inflation.
 A unidirectional Granger causality runs from the inflation rate to imports.

Cointegration Test – Engle–Granger

Equation: UNTITLED
Specification: REM RGDP C
Cointegrating equation deterministics: C
Null hypothesis: Series are not cointegrated
Automatic lag specification (lag = 1 based on Schwarz Info Criterion maxlag = 9)
Table 7.
Value Prob.*
Engle-Granger tau-statistic 1.566319 0.7378
Co-integration test
Engle-Granger z-statistic 11.69075 0.2162 for the variables
(remittances, real
Note: *MacKinnon (1996) p-values GDP)

Cointegration Test – Engle-Granger

Specification: LNREM inflaion lnimports C
Cointegrating equation deterministics: C
Null hypothesis: Series are not cointegrated
Automatic lag specification (lag = 0 based on Schwarz Info Criterion, maxlag = 8)
Table 8.
Value Prob.*
Engle–Granger tau-statistic 1.886675 0.7826
Cointegration test for
Engle–Granger z-statistic 6.989778 0.7684 the variables
(remittances,
Note: *MacKinnon (1996) p-values inflation, imports)

Null Hypothesis Obs F-statistic Prob.

LM does not Granger Cause INFLATION 36 1.41616 0.2579

INFLATION does not Granger Cause LM 6.90255 0.0033 Table 9.
LNREM does not Granger Cause INFLATION 36 4.00898 0.0283 Pairwise Granger
INFLATION does not Granger Cause LNREM 1.14636 0.3309 causality results
LNREM does not Granger Cause LM 36 4.19523 0.0244 between remittances,
LM does not Granger Cause LNREM 1.13539 0.3343 inflation and imports
REPS These three Granger causality results assert a negative impact of remittances on growth
7,3 because remittances are countercyclical, as shown in many studies such as Böhnin (1975),
Rempel and Lobdell (1978), Oberoi and Singh (1980), and Stahl and Arnold (1986). In the case of
Egypt, for example, an increase in remittances can have an adverse effect on economic growth
if the increase motivates either unproductive spending or an increase in imported consumption
goods, due to the imitation effect. If this effect expands, it can reduce savings and investment,
168 hence decreasing the growth rate of the recipient economy. Therefore, and in accordance with
El-Sakka and McNabb (1999), remittances may have a low multiplier impact on growth when
used to finance imports, and may consequently result in a high income elasticity of demand
(Table 10).
Additionally, this negative impact of remittances on economic growth is reinforced by
the fact that they may lead to inflation. The Granger causality test reveals a unidirectional
causality running from remittances to inflation and from inflation to imports.
In summary, remittance inflows have not been able to stimulate economic growth and
therefore have not led to development in the Egyptian economy for a number of reasons,
including the remittances’ potential impact on inflation generated by a remittance-induced
increase in demand and an unresponsive domestic supply [9]. A steady increase in
remittances results in widening the monetary base in the economy and hence increases
household demand, which in turn increases pressure on the prices of non-tradable goods.
The subsequent increase in the general price level can cancel the positive impacts of
remittances on growth and widens the gap between sending and receiving countries since
the receiving countries suffer losses in the form of inflation and in rising imports, and the
sending countries may reap most or all of the benefits. The results of this study are similar
to results in the existing literature, such as Stahl (1982), Feiler (1987), Looney (1989), Adams
(1991), Wahba (2007), Glytsos (2002), World Bank Group (2006), Jahjah et al. (2003), Chami
et al. (2005), Barajas et al. (2009), Gjini (2013), Datta (2014) and Datta and Sarkar (2014).
In Egypt, migrants’ remittances have fueled inflation leading to higher imports. Those
who receive remittances can become highly dependent on the “easy money,” which many
encourage them to reduce their work efforts or participation in the labor market. Such
attitudes reflect a “moral hazard” problem that can negatively affect growth rates.
Furthermore, consistent with findings in Chami et al. (2005) and the IOM’s survey
(International Organization for Migration, 2010), a significant share of remittances in Egypt
is spent on everyday expenses and thus do not act as factor in the country’s capital. The
results are reinforced by the “one- way” causality that runs from remittances to import
growth, as increased remittances raises household incomes that motivates imports of
consumer goods, thereby decelerating growth in the local economy. These results run
counter to the widely held views that remittances stimulate growth rates (see, for example,
Leon-Ledesma and Piracha, 2004; Mundaca, 2009; and Bugamelli and Paternò, 2009).
Indeed, Egypt’s inability to use remittances to contribute to economic growth results in
the “Dutch disease” phenomenon, in which the increase in individuals’ income resulting
from migrants’ remittances boosts consumption of non-tradable commodities, especially

Null Hypothesis Obs F-statistic Prob.

Table 10.
REM does not Granger Cause RGDP 36 2.89841 0.0702
Pairwise Granger
RGDP does not Granger Cause REM 5.79816 0.0073
causality results
between remittances Note: The variables tested are on their second difference (dd)
and real GDP Source: Computed by using E-views packages
in the real estate sector, which increases inflation. Moreover, the positive effect that Economic
remittances have on the recipient’s income may allow those individuals in the home country growth in
to decrease their own work efforts, causing a decline in labor supply and productivity.
4.4.4 Impulse response functions (IRFs). The “IRFs” show the shock effects on the
Egypt
“adjustment path” of the model variables. This helps show the size of the impact of the
shock plus the rate at which the shock happens (Hill et al., 2011, pp. 505–507).
Figure 4 shows that, following an impulse in remittances, GDP per capita does not show
any response in the first and the second period then it declines slightly in the third period.
169
Again, GDP per capita does not show any noticeable response upon innovation in
remittances in the fourth period, then shows a gradual decline in the fifth and sixth periods.
After that, the response rises until the tenth period. Thereby it can be concluded that shocks

Response to Cholesky One S.D. Innovations

Response of LNEG to LNEG Response of LNEG to LNREM
0.04 0.04

0.03 0.03

0.02 0.02

0.01 0.01

0.00 0.00

–0.01 –0.01
1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10

Response of LNEG to LNFDI Response of LNEG to LNODA

0.04 0.04

0.03 0.03

0.02 0.02

0.01 0.01

0.00 0.00

–0.01 –0.01
1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10

Response of LNEG to LNTRADE

0.04

0.03

0.02

0.01

0.00
Figure 4.
–0.01 Impulse response
1 2 3 4 5 6 7 8 9 10
REPS to remittances will have a negative impact on GDP per capita on the short run and long run
7,3 as indicated by accumulated IRFS (Figure 5).
Following a one standard deviation shock in official development aid, GDP per capita
starts to rise in the second and third periods. Then, the response declines sharply till the
ninth period and is followed by non- noticeable response in GDP per capita to innovation in
remittances in the tenth period. Thereby it can be inferred from the accumulated response
170 that shocks to remittances on will have a positive impact on GDP per capita as the response
is in the positive region in most of the periods.
Following an innovation in trade openness, GDP per capita does not show any response
in the first period but shows a sharp rise until the seventh period and is followed by a
gradual rise from the eighth period until the tenth period. Thereby, it can be concluded that
shocks to trade openness will have a positive impact.

Accumulated Response to Cholesky One S.D. Innovations

Accumulated Response of LNEG to LNEG Accumulated Response of LNEG to LNREM
0.25 0.25

0.20 0.20

0.15 0.15

0.10 0.10

0.05 0.05

0.00 0.00

–0.05 –0.05
1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10

Accumulated Response of LNEG to LNFDI Accumulated Response of LNEG to LNODA

0.25 0.25

0.20 0.20

0.15 0.15

0.10 0.10

0.05 0.05

0.00 0.00

–0.05 –0.05
1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10

Accumulated Response of LNEG to LNTRADE

0.25

0.20

0.15

0.10

0.05
Figure 5.
0.00
Accumulated impulse
response –0.05
1 2 3 4 5 6 7 8 9 10
Following an impulse in FDI, GDP per capita does not show any response for the first Economic
period; it starts to rise sharply until the fourth period. After that, there is no response in growth in
GDP per capita to an impulse in FDI in the fifth period. Next, GDP per capita rises Egypt
gradually in the following innovation in FDI until the eighth period. Again, GDP per
capita does not show any response in the ninth period, and it then rises slightly in the
tenth period. The accumulated response function concludes a positive impact of FDI on
GDP per capita. 171
5. Conclusion and recommended policies
Remittances are one of the positive spillover effects of the migration process, and at least
partly compensate for the loss of skilled labor in developing countries. Migrants’
remittances are among the main source of foreign exchange for many developing economies,
and their value has increased in importance for several decades. As a source of capital,
migrants’ remittances can directly increase economic development, and remittance-based
consumption can enhance economic growth by indirectly raising employment levels and
output. While policymakers increasingly recognize the potential effects of remittances on
economic growth, the net growth impact of those remittances is still controversial.
Egypt is among the top remittance recipient countries in the world and is the leading
country in the Middle East region. Thereby, it is worthy to examine the influence of
remittances in enhancing economic growth and as a source of international capital flows,
along with FDI and ODA, over a long period.
This study examined the impact of remittance inflows on the economic growth of Egypt
on time series data from 1980 to 2017 using the Johansen co-integration technique and
VECM. Additionally, Granger causality test was used to explore the causal relationship
between GDP and remittances to identify whether remittances are procyclical or
countercyclical. To clarify the results, another test was conducted to show the causal
relationships between remittances, imports and the inflation rate. The main result is the
significant negative effect of remittances on GDP per capita growth, as a large proportion of
these inflows stimulate consumption by family members rather than investment in the
economy. This negative effect on growth is supported by the Granger causality tests that
reveals causal relationships running from remittances to imports and from remittances to
inflation.
We conclude that Egypt can learn important lessons from the experiences of other
countries that have succeeded in encouraging their migrants to send remittances to be
invested in productive projects. Policymakers in the Egyptian Government should develop
guidelines concerning appropriate policies and procedures to promote the use of remittances
for investment in the local economy. These guidelines should be based on realistic
objectives, tools and time frames that could help to overcome the obstacles that Egyptian
families face when they consider the possibility of investing in Egypt. Enhancing the
positive effect of remittances on economic growth will require adopting effective policies
that may include the following:
 encouraging social financial institutions and credit unions to attract, channel and
administer remittances by providing attractive credit opportunities;
 reducing transaction costs associated with remittances, improving the technology
used in money transfers and the diffusion of information regarding the types of
transfer channels available, as well as establishing voluntary codes of conduct for
fair transfers;
REPS  developing remittance-related products (i.e. savings and insurance products that
7,3 contribute to social safeguard for households); and
 improving migrants’ access to financial services in their home countries as well as
in their sending countries by providing ID cards for migrants and allowing
domestic banks to operate overseas.

172 Furthermore, incentives should be given to attract migrant remittances (e.g. tax exemption)
if remittances are directed into strategic sectors that have the potential for productive
investment in the home countries. This would help to generate employment and stimulate
economic growth.

Notes
1. The decision to float the Egyptian pound was intended to attract foreign inflows and to smother
the black market for the US dollar, encouraging people to use their hard currency through the
banking system.
2. This opinion was true until the international financial crisis of 2008/2009 that resulted in a
notable but temporary drop in the overall value of remittances, especially in developing
economies, after decades of robust progress. This was because the crisis simultaneously hit
many sending and receiving countries. It also had an uneven effect on sectors that included many
migrants’ traditional jobs in sectors such as construction and travel (Ratha et al., 2008, p. 1).
3. To find the optimal lag length (in this case, three), a vector auto-regression analysis is first run on
levels; the appropriate lag length is then chosen according to the Akaike Information Criteria (a
four-lag period as indicated in Table 5). This lag length minus one is used in the VECM as we
lose one degree of freedom for differencing.
4. In fact, foreign aid acts as a form of income that is transferred from developed to developing
countries; its capability to generate growth depends on how it is assigned and invested.
5. To obtain real GDP, data about nominal GDP is collected from government sources, which is
then deflated using the wholesale price index (base year = 2010).
6. Countercyclical remittances serve as a compensatory transfer during difficult economic times in
the home country, thereby working as a shock absorber (Gupta, 2005; Singh et al., 2010; Laniran
and Adeniyi, 2015, pp. 3-4). On the other side, procyclical remittances are those that increase
under favorable economic conditions in the migrant’s home country (Laniran, and Adeniyi, 2015,
p. 4).
7. The pairwise Granger causality test is conducted after running the co-integration test between
remittances, inflation and imports to ensure the long-run relationship between them. This is
shown in Table 8 in the Appendix.
8. Imports variable is measured as imports as a percentage of GDP.
9. Inflation could rise to call off the positive effect of migrants’ remittances on economic growth
broadening the gap among sending and recipient countries; as the latter bear losses in the form of
inflation and uprising imports, whereas the former reap all the benefits.

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Corresponding author
Rasha Qutb can be contacted at: rasha_qutb@yahoo.com

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