Download Remittances and Trade Balance: Evidence from

Remittances and Trade Balance: Evidence from the Middle East
and North Africa
Mohammad Reza Farzanegan
Tel.: +49 6421 2824955
Email: [email protected]
Sherif Maher Hassan
Tel.: +49/64212824965
Email: [email protected]
Address:
Philipps-University of Marburg, Center for Near and Middle Eastern Studies (CNMS)
Deutschhausstr. 12
35032 Marburg, Germany
Web: http://www.uni-marburg.de/cnms/wirtschaft
Abstract:
During 1992-2012, Middle East and North Africa (MENA) has the highest deficit in terms of non
oil external trade balance against other world regions, while during the same period it constitutes
the third largest in the world in terms of remittance received. This research investigates the relation
between remittance inflows and external trade balance in a group of 11 Labor abundant MENA
countries. Using difference GMM and fixed effects panel modeling covering period from 1992-2012,
we find that remittance inflows are accompanied by trade deficit via triggering imports led consumption
expenditures.
JEL classifications: D14, F22, F24
2015
1
1. Introduction
MENA region is the third largest region in terms of remittances share of GDP. These
flows constituted 1.7 percent on average of the region’s GDP during 1992-2012 (World
Development Indictors, 2014). Inflows of remittances to the region are driven by inflows to
Resource Poor Labor Abundant (RPLA) group of countries with remittances composing 10.19
percent of their GDP, compared to 1.87 percent for Resource Rich Labor Abundant (RRLA)
group, and 6.74 percent for a combined sample of the labor abundant (LA) countries in MENA
(Migration and development brief, 23; World Development Indictors, 2014)1.
According to World Bank indicators, MENA has the highest deficit in terms of non oil
external trade balance against other world regions during 1992-2012. Figure (A4) shows outlays
of external trade balance for our sample of countries during the same period, RPLA countries
have trade deficit of an average 13%, while the observed surplus in LA countries’ trade balance
is driven by oil exports of RRLA countries, however, in general a persistent trade deficit is
observed for LA-MENA countries.
Our research question is; to what extent does workers’ remittance inflows impact foreign
trade balance of LA-MENA countries. There is an urgency to better understand the dynamics of
the increasing flows of remittances as a source of foreign currency and catalyst of private savings
(Leon-Ledesma and Piracha 2001; Drinkwater et al. 2003) that contribute to liquidity of the
banking system and finance exports led domestic production (Kandi and Mirzaie, 2011; BouhgaHagbe, 2004).
MENA has a weak export structure which is concentrated in fuel and primary
commodities (El Wassal, 2012; Hadad, 2001), while imports are driven by food and
manufactured imports (World Development indictors, 2014). We reason the existence of trade
deficit in our sample to the weak industrial sector which fails to provide domestic substitutes for
imports of manufactured products (El Wassal, 2012; Hadad, 2001). The deteriorating prices of
primary commodities –which represent the largest component of our sample countries’ exportsrelative to imported manufactured products explains the prolonged trade deficit (Thirlwall, 1995;
El Wassal, 2012; Hadad, 2001). World Bank (2003) estimates’ show that just closing in half the
merchandise export gap could generate an additional 4 million jobs over five years and increase
women’s labor force participation at the same time.
A resilient trade deficit for a sustained period of time increases country’s debt levels, and
with a low sovereign credit rating, this would causes sources of future borrowing to dry up
(Shakur, 2012). Dependence on imported consumption and intermediate goods create additional
pressures by imported inflation to the existing high figures of inflation rate in MENA (Mim and
Ben Ali, 2011), also results in economic instability and stagnation of domestic economy
production capabilities (Shakur, 2012; Chaudhary and Qaisrani, 2002).
1
World Bank classifies MENA countries according to labor and resource abundance to three groups of countries,
(1)RPLA: Arab Republic of Egypt, Jordan, Lebanon, Morocco, and Tunisia; (2) RRLA: Algeria, Islamic Republic
of Iran, Iraq, Libya, Syrian Arab Republic, and Republic of Yemen; and (3) RRLI: Bahrain, Kuwait, Oman, Qatar,
Saudi Arabia, and United Arab Emirates who are also referred to as the Gulf Cooperation Council (GCC) countries.
Because of absence of data on remittances to GCC countries, also their distinctive economies that rely heavily on oil
exports, additionally, they are classified as labor importing economies, as per, we tend to exclude GCC countries
and limit our analysis to RRLA, RPLA, and a combined full sample of 11 countries that contains both resource poor
and resource rich labor abundant countries (LA).
2
One possible reason for trade deficit is existence of current account deficit, because of
what is known as “twin deficit Hypothesis” (CBO, 2009). A deficit may reflect the shortfall in
domestic national savings relative to investment tends (Elwel, 2007), however, LA-MENA
countries have been experiencing a liner increase in the current account balance in the last two
decades (World economic outlook, 2014). A trade deficit may also point to a highly productive
and growing economy, as some of manufactured imports can be used as intermediate inputs for
the production of future exports; nevertheless, MENA has the lowest share of manufactured
exports across the globe, with an average of 18% during 1992-2012 (World development
indicators, 2014).
Literature on MENA are limited and have mixed findings, for example, Kandil and
Mirzaie, (2011) using time series analysis find that export growth increases significantly with
remittance inflows in only two countries (Jordan and Tunisia) out of a sample of four LA
countries. El-Sakka and McNabb (1999) analyze how interest and inflation rates affect inflows of
remittances to Egypt, and they implicitly find that imports financed through remittances have
high income elasticity which suggests either that these imports are consumer durables and luxury
goods or that they are undertaken by higher income groups. Conversely, Bouhga-Hagbe (2004)
finds that in the case of Morocco, remittances receipts almost covered the trade deficit and
actually explains the observed surpluses of the external current account.
Our research contributes two fold to the literature. First, it expands on the small literature
concerned with studying remittances impact on MENA trade balance; to our knowledge this
research is the first panel study to include a full sample of LA-MENA countries in investigating
this specific field of analysis. Second, our research resembles studies by (Ramirez and Sharma,
2008; Giuliano and Ruiz-Arranz, 2006) to study how a developed financial sector and sizeable
domestic production affect the trade balance effects of remittances.
Our difference GMM and fixed effect panel modeling for 11 labor abundant MENA
countries covering period from 1992-2012, show that remittances exercise negative impact on our
sample trade balance via triggering import led consumption expenditures. Domestic production
and financial sectors interactions’ were positive but insignificant, this is explained by the fact
that most of the remittances are absorbed by consumption, and only small fraction is channeled
towards private savings, this in turn hinders the aptitude of domestic production and financial
sector to exert any effect.
The rest of the paper is organized as follows. In section 2 we discuss the relevant
literature on the trade balance effects of remittances. Section 3 outlines empirical methodology,
data selection and estimation result. In section 4 the findings of the research has been discussed
with recommendations.
2. Literature Review
Trade expansion, in the form of rising manufacturing exports, has been an important
source of growth in developing countries (De Silva and Jáuregui, 2004). MENA region is
characterized by weak industrial base; this could provide a partial explanation for the weak
export performance reflected by low share of manufactured exports as a percentage of
merchandise exports averaged around 18% over the period 1992-2012. Furthermore, prices of
primary exports relative to imported manufactured products have been deteriorating for at least a
century which explains the prolonged trade deficit (Thirlwall, 1995; El Wassal, 2012).
3
This demonstrates implicitly that LA countries’ merchandise exports are mostly primary
products, in addition to the binding domestic production capabilities for our sample of countries,
because of high and resilient official unemployment rates, weak quality of institutions (Page and
Van Gelder, 2001), low link between education system and manufacturing/industry (Makdisi et
al, 2007), low growth rates (Bhattacharya and Wolde, 2010), lack of infrastructure (Nabli, 2007);
this leaves no room for household consumption expenditures except to trigger imports. Figure
(A8) shows the existing negative correlation between house hold final consumption expenditures
in our sample of countries and external trade balance.
One way of correcting trade deficit is to trigger private savings and channel it towards
domestic investments to widen the pool of domestically manufactured products; remittances
could be a very good catalyst for triggering private savings (Kandil and Mirzaie, 2011; LeonLedesma and Piracha 2001; Drinkwater et al. 2003). The literature identifies two channels
through which remittances affect the receiving countries’ trade balance, exchange rate and
savings channels. Through the exchange rate channel, remittances inflow may be significant in
volume as to result in appreciation of the real exchange rate of the receiving economy, results in
reduction of foreign trade competitiveness, and adversely affect the trade balance as well as the
economic development of the receiving economy (Okodua and Olayiwola, 2013). They also
could generate a resource allocation from the tradable to the non-tradable sector (Dutch dieses)
(Amuedo-Dorantes and Pozo, 2004; Chami, et al, 2003).
This study is concerned with the saving channel. There are two factors which affect the
capacity of the savings channel, financial development (Brown, 2014) and domestic production
(OECD, 2006). When substantial fractions of remittances are saved by migrant’s families in
financial institutions; these deposits promote the ability of these institutions to finance domestic
production; if these investments are export-oriented there will be positive spillovers of
remittance inflows on exports (Kandil and Mirzaie, 2011; Bouhga-Hagbe, 2004). In another
scenario, remittance inflows may primarily finance consumption spending which might spur
domestic demand in recessions (Gopalan and Rajan, 2010; Taylor, 1996), however, if domestic
capacity constraints are binding, in other words, if the additional demand induced by remittances
cannot be neutralized by domestic output, the increase in consumption will be inflationary and
stimulate further increase in imports (OECD, 2006).
Regarding how financial sector affects the receiving country’s capacity to use
remittances, Giuliano and Ruiz-Arranz, 2006; Ramirez and sharma, (2008) imply that for
financially developed economies, remittances act as substitutes for financial sector variables
which are available, consequently people need not wait for remittances for investment purposes,
as per, their estimates showed that remittances have a positive and significant impact on growth
in less financially developed countries. Other studies like (Mundaca, 2005) do not observe the
marginal differences between financially developed and under developed economies on the
positive impact of remittances; for a sample of Latin American countries, he concludes that
remittances have a significant impact on growth, and this impact is amplified when the financial
sector variable is included in the model.
Remittances may also facilitate the development of the receiving country’s financial
sector, according to (Gupta, et al 2009), remittances foster banking outreach and depth through
excess cash balances that are held by migrant’s families and therefore by increasing the demand
for other banking services. Aggarwal, et al (2011) find that remittances can relax individuals’
credit constraints, and the consequent increase in credit to the private sector might be channeled
4
to finance government, anyhow, the immediate consumption of remittances hinder these
favorable spillovers.
Household budget surveys, which represent the best possible source of information about
how remittances are spent, are limited for MENA. Adams, (1991) conducts surveys for 1000
households in rural Egypt, show that more than 70% of remittances go into purchasing of
agricultural or building land, and around 12% are dedicated for consumption expenditures. IOM,
(2012) shows that remittances to Egypt are primarily channeled towards essential expenses and
consumption, however a small proportion of remittances -around 20%- are invested in real estate
and other forms of productive investments.
At regional scale, EIB, (2006) undertakes field studies on remittances’ usage across
alternative budget items on selected LA MENA countries. Table (1A) demonstrates that
everyday expenses absorb most of the income arising from remittances, while limited resources
are devoted to investments. Similarly, (Schramm, 2009; Mim and Ben Ali, 2008) argue that basic
consumption items (food, heat, and clothing) absorb most of the remittances in MENA.
An extra evidence for the consumption usage of remittances, is highlighted by Figure
(A7) which reports household private savings as a percentage of GDP per capita from 1992-2012
for our full sample of LA countries, private savings have not increased over the investigated
period, otherwise decreasing slightly in spite of the incrementing flows of remittances.
Moreover, Figure (A8) shows the zero regression line between remittances and private savings
for our sample of LA countries.
Domestic production capabilities are binding in our sample of countries, because of high
and resilient official unemployment rates, weak quality of institutions (Page and Van Gelder,
2001), low link between education system and manufacturing/industry (Makdisiet al, 2007), low
growth rates (Bhattacharya and Hodler, 2010) , lack of infrastructure (Nabli, 2007). This leaves
no room for remittances induced consumption expenditures, except to trigger imports of goods
and services (Loser et al, 2006).
When remittances induce an increase of imports and trade balance deficits in the
remittance-receiving country, this is known as “boomerang effect”, However as argued by
(OECD, 2006),
the propensity to import can also increase as a consequence of the general
development of the economy. For instance, in south European countries between 1960 and 1981
remittance-induced imports accounted for 1% in Spain and Italy, to maximums of 4.9% in Greece
and 6.2% in Portugal (Glytsos, 1993; Straubhaar, 1991). Jadhav, (2003) reasons the export of a
number of professional and business services to remittance inflows to India. Conversely, other
studies support the boomerang effects of remittances to Sub Saharan African (SSA) (Okodua and
Olayiwola, 2013), Nepal (Bhatta, 2013), and Latin America (Loser et al, 2006).
Literature on MENA are limited and have mixed findings, for example, Kandil and
Mirzaie, (2011) using time series analysis find that export growth increases significantly with
remittance inflows in only two countries (Jordan and Tunisia) out of a sample of four LA
countries. El-Sakka and McNabb (1999) analyze how interest and inflation rates affect inflows of
remittances to Egypt, and they implicitly find that imports financed through remittances have
high income elasticity which suggests either that these imports are consumer durables and luxury
goods or that they are undertaken by higher income groups. Conversely, Bouhga-Hagbe (2004)
found that in the case of Morocco, remittances receipts almost covered the trade deficit and
actually explains the observed surpluses of the external current account.
5
3. Empirical model
Our main prediction is that remittance flows have a dampening impact on trade balance
of LA MENA countries, via triggering consumption expenditures; and due to binding domestic
production, remittances-induced consumption expenditures are matched with larger imports of
goods and service. We test this hypothesized negative correlation conditioned to well-structured
financial sector (Ramirez and Sharma, 2008; Giuliano and Ruiz-Arranz, 2006), and strong
domestic production base (OECD, 2006). It is important to clarify here that the study is restricted
to the macroeconomic impact of remittances on the receiving economies and not on their
microeconomic impact.
This study is limited to 11 labor abundant MENA countries; we use panel data over
period 1992 to 2012 within three groups, RRLA, RPLA and full sample of LA2. For the sake of
consistency, we include RR countries to capture common shocks to external trade balance for all
LA countries, regardless of their economic structure composition. However, for this group, we
add natural resource rents in the control variables set, to ensure that oil exports don’t signify
misleading biasness to our estimates.
Our variables are reported as percentage of GDP. We use (T) trade balance (measured as
exports of goods and services minus imports of goods and services) as our dependent variable.
Our main independent variables are (REMIT) remittance inflows, (INV) we use gross fixed
capital formation as an indicator for domestic production, (FIN) domestic credit to private sector
is used as proxy for financial sector development, (HCO) Household final consumption
expenditures, and two interactions (REMIT*INV and REMIT*FIN). We commence with a
straightforward specification of our dependent variable (trade balance) in a linear function of our
main independent variables, besides set of control variables (X). The subscripts i denote the
country (11 countries), t the time period (1992-2012), are the observation-specific errors, and
are unobserved individual-specific effects.
To reduce the omitted variable bias, we have to control for other variables that might
affect trade balance. We include natural resource rents as percent of GDP to account for the
impact of natural resource exploitation which constitute large share of RR countries exports.
Nominal exchange rates of local currencies vis a vis US dollar is used to account for exchange
rate fluctuations and their impact on exports competitiveness (Majeed and Ahmed, 2006).
Secondary school enrollment rate as a proxy for human capital and the role of education, because
educational developments are likely to affect trade patterns because of their impact on
comparative advantage (WTO, 2013). Moreover, we take into consideration both the impact of
FDI and official aid flows that can encourage governments to improve the quality of
infrastructure and adopt FDI-led export growth strategies with twin objectives of capturing the
benefits of both FDI inflow and exports growth (Pfaffermayr 1996). And finally we include
2
Our sample contains the five largest recipients of remittances in MENA in 2013, Lebanon, Jordan, Yemen,
Morocco, and Egypt. For example in Egypt, remittance inflows are three times higher than the foreign exchange
revenue from the Suez Canal or tourism, and substantially higher than foreign direct investments (Migration and
development brief, 23). In Morocco, these flows are five times higher than official development aid and also exceed
FDI and revenues from tourism and the export of agricultural produce and phosphates (Haas, 2005).
6
inflation rate as a proxy for macroeconomic instability (Barro and Sala-i-Martin, 2004). Data are
sourced from the World Development indicator, (2014). Variables’ descriptive statistics and
definitions appear in Table (2A & 3A).
3-1. Methodology
Our model can be estimated using ordinary least squares (OLS). However, some of the
right-hand side variables may be endogenous to trade balance, because causality may run in both
directions, for instance, from trade balance to consumption and from trade balance to fixed
capital formation. Hence, using OLS to estimate our model would therefore lead to biased
results. Another problem arises when estimating our panel data is time-invariant country
characteristics, such as geography and demographics that may be correlated with the explanatory
variables.
One possible solution to this problem would be running the regression using first
difference (FD) estimator which wipes out many of the biases that arise from endogeneity and
omitted variables (Jeffrey, 2001). Another solution would be running the model using lag(s) of
explanatory variables. Such strategy according to (Bhattacharyya and Hodler, 2010) reduces the
reverse casual effect from the dependent variable on regressors. In other words, the lagged
measures are less likely to be endogenous than raw values. To decide the appropriate number of
lags, we use Akike Information Criterion (AIC) 3.
We estimate our equations, first by using country fixed effects panel modeling. There are
several merits of using country fixed effects in this analysis. First, such regressions focus on
within-country variation in the data which is a more appropriate approach to test our theoretical
predictions. Second, as mentioned by Baltagi (2008), country fixed effects assist in controlling
for unobserved heterogeneity that is constant over time and correlated with independent
variables, there are several time-invariant country characteristics that affect trade balance, which
increase the risk of omitted variable bias, for example geography, history, ethnicity, etc. Finally,
fixed time effects capture shocks common to all countries such as global business-cycle effects
(Bjorvtan, and Farzanegan, 2013). Moreover, we use cluster-robust standard errors that are
robust to heteroskedasticity and serial correlation.
For robustness, we take advantage of the panel nature of the data to use GMM estimators
that are based on differencing regressors to control for unobserved effects (Giuliano and RuizArranz, 2006). Difference Generalized Methods of Moments (GMM) developed by (Arellano
and Bover 1995; Blundell and Bond 1998); this method can eliminate any endogeneity that due
to the correlation of time-invariant country characteristics and explanatory variables (Baltagi et
al., 2009). Good instruments must possess the following two properties: (i) they must be highly
correlated with the endogenous explanatory variable (relevance condition); and (ii) orthogonal
with the error term/dependent variable (validity condition). We test the validity condition by
examining Hansen’s statistics with null hypothesis (H0: The excluded instruments are
uncorrelated with the endogenous explanatory variable). Also AR (1) and AR (2) tests with null
hypothesis of no autocorrelation, both are reported in estimation tables. We treat our main
3
AIC is a measure of the relative goodness of fit of a statistical model, for more information see Akike, (1974). We
estimate the model first by using 5 lags of each independent variable, and then we reduce the number of lags until
we observe the lowest AIC value at 1 lag.
7
independent variables as endogenous and use lags of each as internal instruments, other control
variables are treated as exogenous except for exchange rate and inflation, as one would observe
an obvious reverse causality from countries’ trade balance on domestic inflation and exchange
rates4.
3-2. Results
Tables (A4, A5 and A6) report estimates of our basic specification for our three groups of
countries (RPLA, RRLA, and LA). The first three equations at each table report fixed effects
estimations, while the fourth equation reports GMM estimation results. The dependant variable is
trade balance as % GDP. T-test probabilities are in parentheses. Robust standard errors are used
for all specifications. In fixed effects equations, we run the variables at first difference while
using one lag for all independent and control variables. In GMM, we use three lags of
endogenous variables as instruments.
3-2-1. Resource Poor-Labor Abundant (RPLA) countries (Egypt, Jordan, Lebanon,
Morocco, and Tunisia)
(4.1) shows that Remittances have a significant negative impact on trade balance, one
unit increase in REMIT; reduce TB (in other words, increase imports at expense of exports) by 0.231. This result is robust across other specifications that incorporate control variables, though
it become insignificant when we include the two interactions REMIT*DCR and REMI*FC.
GMM estimations in (4.4) reports slightly larger negative coefficient than fixed effects, one unit
increase in REMIT, increases trade deficit by 0.630. The highly significant negative coefficient
of (HCON) across all equations goes prior to our argument that consumption in MENA countries
is import driven, which exercise dampening impact on these countries’ trade balance.
(FIN) fails to explain trade balance movements. This is justifiable because financial
sector in MENA -except for GCC- incur crucial problems like public sector banks’ domination,
independent monetary policies, and weak quality of institutional; and since we are using
domestic credit to private sector as a proxy, latter reasons cause inefficient circulation of
financial funds to boost private sector participation rates. Moreover, private sector led growth in
MENA is stagnated (World Bank, 2009; Creane, et al. 2004).
Surprisingly, (INV) has a negative impact on (TB), its coefficient is robust across all
equations. Possible reasons are: first, domestic investments in general have a significant non
tradable component (Burstein et al. 2004). Second, Domestic investments in RPLA are not
diversified; they are heavily concentrated in services and construction sectors, while the
concentration of industry are in relatively narrow ranges of low productivity activities (OECD,
2006); On contrary, more than half of their exports are concentrated in three commodities most
of which are primary products: agriculture, crude materials or minerals (Hadad, 2001). Third,
MENA region is the lowest in terms of manufactured exports to other developing regions (Figure
A5)5; conclusively, one can’t observe a clear positive nexus between existing patterns of
4
Trade deficits might weaken the currency and trigger domestic inflation by the effect of “imported inflation”. For
more details about two way causality between trade balance, exchange and inflation rates, see for example (CBO,
2000)
5
For better understanding of trade performance, openness and diversity in MENA, see (Hadad, 2001; OECD, 2007).
8
domestic investments and non-oil exports. While for the domestic production countercyclical
impact on trade balance, one reason would be the increasing share of intermediate imports that
are used as inputs for domestic production, occurring because of lack of domestic capital goods;
this reveals high dependence of domestic market on foreign suppliers6.
Furthermore, we test our interactions of REMIT*INV and REMIT*FIN, and find that
they are non-significant. This can be explained by the fact that most of remittances are absorbed
by consumption expenditures that are imports driven, and those –if any- were saved, are either
non significant in terms of economic activity or invested in small scale non tradable projects that
have nearly no impact on the country’s trade balance (Ramirez and Sharma, 2008).
3-2-2. Resource Rich-Labor Abundant (RRLA) countries (Algeria, Iran, Iraq, Libya,
Syria, and Yemen)
For this group of countries we use natural resource rents in the control variables set, to
ensure that oil exports don’t signify misleading biasness to our estimates. Similar to RPLA
estimation results, (REMIT) remittances exercise negative impact on trade balance, according to
(5.1), one unit increase in remittances reduces trade surplus by 0.616, however this negative
coefficient is not robust across other equations; this result match our expectations as remittance
inflows for this group of countries is low, hence insignificant effect of remittance on trade
balance is unambiguous.
Similarly, (HCON) repress trade surplus by triggering imports. Financial sector proxy
fails to explain trade balance movements. (INV) is negative, and significant. Interactions are non
significant, except in (5.4) which shows a positive and significant interaction REMIT*INV,
anyhow with remittances being insignificant, we cannot conclude much from this interaction.
3-2-3. Full sample of Labor Abundant (LA) countries
(6.1, 6.2 and 6.3) report fixed effects estimations similar to previous tables, these
equations show that (REMIT) are significant and exercise countercyclical impact on our sample
trade balance. (6.3) includes a full list of control variables PLUS interactions, one unit increase
in (REMIT), increases trade deficit by 0.522. (HCON) are negative, highly significant and robust
across all equations. (INV) is significant, negative and robust. REMIT*INV is significant only in
(6.4), according to GMM estimations, one unit increase in this interaction, lead to a reduction in
the dampening impact of remittances on trade balance by 0.0219, begetting a net negative impact
of (-0.695+0.0219=-0.671).
4. Conclusion and policy recommendations
This research emphasizes the role of the incrementing flows of remittances to the MENA
region, especially Labor abundant MENA countries, to alleviate the persistent trade deficit.
Giving the weak industrial base, low share of manufactured exports, and the highly dependence
on finished and intermediate imported goods, these signal the deficiency of local economy to
provide domestic substitutes for imports of finished and manufactured products.
6
The use of imported intermediates for exports has been growing globally, for more details see (Ali and Dadush,
2011).
9
Remittances can spur private savings, and with channeling them towards domestic
investments the economy can widen the pool of domestically manufactured products. The latter
is known as saving channel. However, data provide countercyclical evidence for this
hypothesized argument, as household private savings have not increased during the investigated
period, which suggest that these remittances have induced consumption expenditures rather than
private savings. And giving the inability of domestic economy to match remittances inducedconsumption expenditures, this conclusively adds extra pressure to labor abundant MENA
countries’ trade balance via triggering imports.
Fixed effects and difference GMM panel modeling provide statistical evidence of the
negative correlation between remittances and trade balance via spurring household consumption
expenditures which in turn stimulate imports.
Therefore, in the light of these findings, Our sample of countries should pay close
attention towards: a) building alliances between domestic and international banks to leverage
local expertise and combine distributional networks, which results in facilitating the money
transfer through formal chances, by reducing costs and duration of the transfer; this would help
provide reliable figures for remittances entering the country, b) promoting financial services,
which targets repatriates outside the country, like saving incentives, interest rate premium on
migrant’s deposits, and the issuance of remittances back bonds, c) implementing policies that
facilitate investment use of remittances to foster their effect on growth. In this regard, a strong
cooperation between Diaspora groups, banks, and international financial institutions needs to be
instigated to develop cooperative pooling schemes. d) Promote exports led investments by applying
policies to attract foreign direct investments into exports sector, and provide local- instead of importedcapital goods and materials that are needed for export diversification via subsidizing their domestic
producers. finally e) organizing different schemes that sustain cultural, social and political bridges
with migrant’s abroad, for instance, ensuring their participation in elections, organizing on
regular schedules social and cultural events; this would likely contribute to sustainable
remittance flows and ensure that they remain strong in the future through intensifying the sense
of belonging for the migrants.
5. Bibliography
Adams, H. (1991). The Economic Uses and Impact of International Remittances in Rural Egypt.
Economic development and cultural change, 39(4): 695-722
Aggarwal, R. et al. (2011). Do Remittances Promote Financial Development?. Journal of
Development Economics, 96(2):255-264
Akaike, H. (1974). A New Look at the Statistical Model Identification. IEEE Transactions on
Automatic Control, 19(6):716-723
Ali, S. and Dadush, U. (2011). The Rise of Trade in Intermediates: Policy Implications. VOXEU
organization, February 9. Retrieved from http://www.voxeu.org/article/rise-trade-intermediatespolicy-implications
Amuedo-Dorantes, C. and Pozo, S. (2004). On the Use of Differing Money Transmission
10
Methods by Mexican Immigrants," Economic Working Papers at Centro de Estudios
Andaluces E2004/06, Centro de Estudios Andaluces.
Arellano, M., and Bover, O. (1995). Another look at the instrumental variable estimation of
error-components models. Journal of Econometrics 68: 29–51.
Baltagi, B. (2008). Econometric Analysis of Panel Data (4thed.). Publisher: Chichester:
Wiley.
Baltagi, B., et al. (2009). Financial development and openness: evidence from panel
data. Journal of Development Economics 89:285–296.
Barro, R., & Sala-i-Martin, X. (2004). Economic growth. 2nd edition. Cambridge, MA, U.S.A:
MIT Press.
Bhatta, G. (2013). Remittance and Trade Deficit Nexus in Nepal: A VECM Approach. NRB
Economic Review, Nepal Rastra Bank, Research Department, 25(1):37-50.
Bhattacharyya, S., and Hodler, R. (2010). Natural Resources, Democracy and Corruption.
European Economic Review, 54(4):608-621
Bjorvatn, K. and Farzanegan, M. (2013). Demographic transition in resource rich countries: a
blessing or a curse?. World Development 45, 337–351.
Blundell, R., and Bond, S. (1998). Initial Conditions and Moment Restrictions in Dynamic Panel
Data Models. Journal of Econometrics, 87:11-143.
Brown, R., et al. (2013). Migrants’ Remittances and Financial Development: Macro- and Micro-Level
Evidence of a Perverse Relationship. The World Economy, 36(5):636-660.
Bouhga-Hagbe, J. (2004). A Theory of Workers' Remittances with an Application to Morocco. IMF
Working Paper 04/194, Washington D. C., International Monetary Fund.
CBO (2000). Causes and Consequences of the Trade Deficit: an Overview. Congressional Budget Office.
Congressional budget office (CBO) (2000). Causes and Consequences of the Trade Deficit: An
Overview. Memorandum.
Chami, R., et al. (2003). Are Immigrant Remittance Flows a Source of Capital for Development?
International Monetary Fund Working Paper, 03/189. Washington, DC.
Chaudhary, M., and Qaisrani, A. (2002). Trade Instability, Investment and Economic Growth in
Pakistan. Pakistan Economic and Social Review, XL(1): 57-73.
Creane, S., et al. (2004). Evaluating Financial Sector Development in the Middle East and North
11
Africa: New Methodology and Some New Results. IMF Policy Working Paper
De Silva, S., and Juregui, C. (2004). Migration and Trade and in MENA Problems or Solutions?.
World Bank Working Paper Series No. 40:1-40
Drinkwater, S., et al. (2003). The Labor Market Effects of Remittances. Flowenla discussion
Paper No. 6, Hamburg Institute of International Economics, Hamburg.
EIB, )2006). Study On Improving The Efficiency Of Workers’ Remittances In Mediterranean
Countries. European investment bank, Rotterdam, The Netherlands. Retrieved from
http://www.eib.org/attachments/country/femip_workers_remittances_en.pdf
El Sakka, M., and McNabb, R. (1999). The Macroeconomic Determinants of Emigrant
Remittances. World Development, 27(8):1493-1502
El Wassal, K. (2012). The Impact of Trade Liberalization on Trade Balance in Arab Countries.
Journal of Economic and Social Research, 14(2):1-26
Elwel, C. (2007). The U.S. Trade Deficit: Causes, Consequences, and Cures. Congressional
research service (CRS) report No. RL31032.
Giuliano, P., and Ruiz-Arranz, M. (2009). Remittances, Financial Development and Growth.
Journal of Development Economics, 90(1):144-152
Glytsos, N. (1993). Measuring the Income Effects of Migrant Remittances: A Methodological
Approach Applied to Greece. Economic Development and Cultural Change, 42(1):131168
Gopalan, S. and Rajan, R. (2010). External Financing in South Asia: The Remittances Option.
United Nations Economic and Social Commission for Asia and the Pacific (ESCAP),
Policy
brief
No.
23.
Retrieved
from
http://www.unescap.org/sites/default/files/polbrief23.pdf
Gupta, S., et al. (2009). Effect of Remittances on Poverty and Financial Development in Sub
Saharan Africa. World Development, 37(1): 104-115.
Hadad, M. (2000). Export Competitiveness: Where Does the Middle East and North Africa
Region Stand?. Economic Research Forum (ERF), Working paper 2030.
Haas, H. (2007). Morocco's Migration Experience: A Transitional Perspective. International
Migration 45 (4): 39-70
IMF (2005). World Economic Outlook, International Monetary Fund, Washington DC.
12
IOM (2010). A Study on Remittances and Investment Opportunities for Egyptian Migrants.
Jeffery, A. (2001). Transnational migration in rural Oaxaca, Mexico: Dependency, development,
and the household. American Anthropologist, 103(4):954-967
Jadhav, N. (2003). Maximizing Development Benefits of Migrant Remittances: The Indian
Experience. Paper presented in a Joint DFID-World Bank Conference on Migrant
Remittances, London (October 9-10).
Kandil, M., and Mirzaie, I. (2008). The Impact of Capital and Remittance Flows on Economic
Performance in MENA Countries. Egyptian Research Forum (ERF), working paper No.
440.
León-Ledesma, M., and Piracha, M. (2001). International migration and the role of remittances
in Eastern Europe. University of Kent Discussion Paper, No. 01/13, Canterbury,
University of Kent.
Loser, C, et al (2006). The Macro Economic Impact of Remittances in Latin America -Dutch
Disease or Latin Cure?. Presented at the G-24 Technical Group meeting in Singapore on
September 13-14. Retrieved from http://www.g24.org/lose0906.pdf
Majeed, T., and Ahmad, E. (2006). Determinants of Exports in Developing Countries. Pakistan
Development Review, 45(4):1265-1274
Makdisi, S., et al. (2007). Determinants of Growth in the MENA Countries,” in Explaining
Growth in the Middle East, ed. by Jeffrey B. Nugent and Hashem Pesaran (Amsterdam;
Boston, Massachusetts: Elsevier).
Mankiw, G. (2006). Is the U.S. Trade Deficit a Problem?. Greg Mankiw Blog, March 31.
Retrieved from http://gregmankiw.blogspot.de/2006/03/is-us-trade-deficit-problem.html
Marchetta, F. (2011). The Impact of Migration on the Labor Markets in The Arab Mediterranean
Countries. Middle East Development Journal, 4(1):1-47
Mim, S. and Ben Ali, M (2012). Through Which Channels Can Remittances Spur Economic
Growth in MENA Countries?. Economics Discussion Papers, No 2012-8, Kiel Institute
for
the
World
Economy.
Retrieved
from
http://www.economicsejournal.org/economics/discussionpapers/2012-8
Mim, S, and Ben Ali, M. (2011). What Drives Inflation in MENA Countries?. International
Journal of Economics and Finance, 3(4):119-129
Mundaca, B. (2009). Remittances, Financial Market Development, and Economic Growth: The
13
Case of Latin America and the Caribbean. Review of Development Economics,
13(2):288-303
Nabli, K., (2007). Long-Term Economic Development Challenges and Prospects for the Arab
Countries,” in Breaking the Barriers to Higher Economic Growth: Better Governance and
Deeper Reforms in the Middle East and North Africa, edited by Mustapha K. Nabli
(Washington: The World Bank).
OECD (2006). International Migration Outlook. International Migrant Remittances and Their
Role of Development.
OECD (2007). MENA-OECD Investment Programme. Diversifying Mena Economies to
Improve Performance.
Okodua, H. and Olayiwola, W. (2013). Migrant Workers' Remittances and External Trade
Balance in Sub-Sahara African Countries. International Journal of Economics and
Finance; 5(3):134-142
Page, J. and Van Gelder, L. (2001). Missing Links: Institutional Capability, Policy Reform and
Growth in the Middle East and North Africa. in The State and Global Change: The
Political Economy of Transition in the Middle East and North Africa, edited by Hassan
Hakimian and Ziba Moshaver (London: Curzon Press, 2001)
Pfaffermayr, M. (1996) Foreign outward Direct Investment and Exports in Austrian
Manufacturing: Substitutes or Complements?. Weltwirtschaftliches Archive 132(2):501522.
Ramirez, M. and Sharma, H. (2008). Remittances and Growth in Latin America: A Panel Unit
Root and Panel Cointegration Analysis. Department of Economics, Trinity College,
Hartford, USA. Retrieved from http://ssrn.com/abstract=1148225
Schramm, C. (2009). Migration from Egypt, Morocco and Tunisia: Synthesis of Three Case
Studies. Background paper for Shaping the Future, The World Bank, Washington.
Shakur, S. (2012). Impact of Global Trade Liberalization on Regional Trade Balances.
International Journal of Economics and Finance, 4(1):48-55
Straubhaar, T. (1991). On the Economics of International Labor Migration. Gunter Steinmann
Weltwirtschaftliches Archive, Published by: Springer, Stuttgart.
Taylor, J., et al. (1996). International migration and national development. Population Index,
62(2):181-212
14
Thirlwall, P. (1999). Growth and Development. Great Britain: Macmillan, 6th Edition
World Bank, 2003. Trade, Investment and Development in the Middle East and North Africa:
Engaging with the World. World Bank, Washington, D.C
World Bank (2006). Global Economic Prospects: The Economic Implications of Remittances
and Migration. The World Bank.
World Bank (2009). From Privilege to Competition Unlocking Private-Led Growth in the
Middle East and North Africa. MENA development report.
WTO (2013). World Trade report.
World Bank, (2014). World Development indicators.
World Bank. Migration and development brief, various issues.
Appendix
3.5
3
2.5
2
1.5
1
0.5
0
Sub-Saharan
Africa
(developing
only)
World
South Asia
Middle East & Latin America &
East Asia &
North Africa (all Caribbean (all
Pacific (all
income levels) income levels) income levels)
Figure A1: Remittances received (% GDP). Selected world regions, average (1992-2012)
Source: world development indicators, (2014)
15
RRLA
RPLA
LA (Full sample)
0
2
4
6
8
10
12
Figure A2: Remittances received (%GDP). RRLA, RPLA, AND LA, average (1992-2012)
Source: world development indicators, (2014)
Notes: RPLA (Resource Poor Labor Abundant MENA) - LA (Labor Abundant MENA) - RRLA (Resource Rich
Labor Abundant MENA)
5
0
1992
1995
1998
2001
2004
2007
2010
-5
-10
-15
-20
-25
SSA
World
SAS
MENA
LCN
EAS
Figure A3: Non oil External trade balance (% GDP). Selected world regions (1992-2012)
Source: world development indicators, (2014)
Notes: Non oil External trade balance is calculated as (fuel exports- Exports of goods and services) minus imports of
goods and services. SSA (Sub Saharan Africa)-SAS (South Asia)- MENA(Middle East and North Africa)-LCN(Latin
America and Caribbean) -EAS (East Asia).
16
30
20
10
0
1992
1995
1998
2001
2004
2007
2010
-10
-20
-30
RPLA
RRLA
LA
Figure A4: External trade balance (% GDP). RPLA, RRLA, and LA (1992-2012)
Source: world development indicators, (2014)
Notes: External trade balance is calculated as exports minus imports of goods and services. RPLA (Resource Poor
Labor Abundant MENA)- RRLA (Resource Rich Labor Abundant MENA- LA (Labor Abundant MENA)
90
80
70
60
50
40
30
20
10
0
East Asia &
Pacific (all
income levels)
Latin America & Middle East &
Caribbean (all North Africa (all
income levels) income levels)
Manufactured exports(%Merchandise exports)
South Asia
Sub-Saharan
Africa (all income
levels)
World
Manufactured imports (%Merchandise imports
Figure A5: Manufactured exports gap (%Merchandise trade). Selected world regions, average (19922012)
Source: world development indicators, (2014)
Notes: Manufactured exports and imports comprise the following commodities: chemicals, basic manufactures,
machinery and transport equipment, miscellaneous manufactured goods. SSA (Sub Saharan Africa)-SAS (South
Asia)- MENA(Middle East and North Africa)-LCN(Latin America and Caribbean) -EAS (East Asia).
17
8
6
4
2
0
-2
1992
1995
1998
2001
2004
2007
2010
-4
-6
-8
Current account (%GDP)
Linear (Current account (%GDP))
Figure A6: Current Account balance (%GDP). LA MENA countries (1992-2012)
Source: World Economic Outlook, (2014)
Notes: LA (Labor Abundant MENA countries)
50
45
40
35
30
25
20
15
10
5
0
1992
1995
1998
2001
2004
LA
2007
2010
Linear (LA)
Figure A7: House Hold private savings (% GDP per capita). LA countries (1992-2012)
Source: world development indicators, (2014)
Notes: H.H private savings are calculated as the difference between GDP per Capita and HH final consumption
expenditures per capita. LA (Labor Abundant MENA countries)
18
30
Differenced TRADE
20
10
0
-10
-20
-30
-20
-10
0
10
20
30
Differenced HCON
Figure A8: Regression line between Household final consumption expenditures and trade balance. LA
countries (1992-2012)
Source: world development indicators, (2014) and author calculations
4,000
3,000
Differenced PS
2,000
1,000
0
-1,000
-2,000
-3,000
-8
-4
0
4
8
12
Differenced REMIT
Figure A9: Regression line between Household private savings and remittances. LA countries (19922012)
Source: world development indicators, (2014) and author calculations
19
Table A1. Usage of remittances in selected LA MENA countries (Percentage of remittances)
Daily expenses
Payment of
school fees
Building a
house
Investments
Other
Number of
interviews
Algeria
45
13
23
5
11
64
Egypt
43
12
18
15
12
31
Jordan
74
16
4
6
-
40
Lebanon
56
24
5
5
5
41
Morocoo
46
31
16
5
2
40
Syria
61
11
8
-
20
49
Source: EIB, (2006)
Table A2: Variables description
Variable
FIN
Definition
Domestic credit to private sector as a proxy for financial sector development
refers to financial resources provided to the private sector by financial
corporations, such as through loans, purchases of non-equity securities, and
trade credits and other accounts receivable, that establish a claim for
repayment
TB
Trade balance comprise of exports of goods and services minus imports of
goods and services
REMIT
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 nonresident
households
INV
Gross fixed capital formation (formerly gross domestic fixed investment)
includes land improvements (fences, ditches, drains, and so on); plant,
machinery, and equipment purchases; and the construction of roads, railways,
and the like, including schools, offices, hospitals, private residential
dwellings, and commercial and industrial buildings.
INF
Inflation rate (GDP deflator index)
FDI
Net Inflows of foreign direct investments
EXR
Exchange rate of local currency expressed as quantity notation relative to US
$
AID
Net official development assistance (ODA) consists of disbursements of
20
loans made on concessional terms (net of repayments of principal) and grants
by official agencies of the members of the Development Assistance
Committee (DAC), by multilateral institutions, and by non-DAC countries to
promote economic development and welfare in countries and territories in the
DAC list of ODA recipients.
RENT
Total natural resources rents are the sum of oil rents, natural gas rents, coal
rents (hard and soft), mineral rents, and forest rents. Capturing the degree of
utilization of these natural rents in the development of a business
environment
HCON
Household final consumption (formerly private consumption) is the market
value of all goods and services, including durable products (such as cars,
washing machines, and home computers), purchased by households. It
excludes purchases of dwellings but includes imputed rent for owneroccupied dwellings. It also includes payments and fees to governments to
obtain permits and licenses.
SCHO
Gross enrollment ratio is the ratio of total enrollment, regardless of age, to
the population of the age group that officially corresponds to the level of
education shown
Table A3. Descriptive statistics of key variables
Variables
Mean
R.
Poor
R.
Rich
6.98
10.29
3.73
7.392
7.329
5.83
26.68
26.68
25.4
0.003
2.85
0.003
-4.22
-14.6
5.66
16.82
13.81
12.95
45.83
-0.38
45.83
-64.4
-64.4
-25.6
63.16
72.79
54.37
16.27
12.67
14.15
124.64
124.64
89.51
22.46
54.83
22.46
40.92
59.46
12.82
27.12
17.34
8.79
91.76
91.76
37.27
1.266
22.27
1.266
23.69
24.14
21.03
6.067
4.59
7.04
38.23
36.65
38.23
2.91
15.61
2.91
L.A.
REMIT
TB
HCON
FIN
INV
St. deviation
R.
R.
LA
Poor Rich
21
Maximum
R.
R
LA
Poor
Rich
Minimum
R.
R.
LA
Poor Rich
Table A4: Trade balance effects of remittances. Resource Poor-Labor Abundant (RPLA) countries
(Egypt, Jordan, Lebanon, Morocco, and Tunisia), (1992-2012)
Dependant variable: Trade balance (%GDP)
Models
(4.1)
(4.2)
Fixed effects
fixed effects
-0.231
(0.0059)***
(4.3)
fixed effects
(4.4)
GMM
-0.135
(0.067)*
-0.438
(0.179)
-0.630
(0.064)*
-1.075
(0.000)***
-1.182
(0.000)***
-0.994
(0.047)**
-0.042
(0.0529)*
0.057
(0.208)
0.031
(0.589)
-0.096
(0.149)
-0.980
(0.000)***
-0.989
(0.000)***
-0.993
(0.000)***
-1.037
(0.000)***
REMIT*INV
0.0058
(0.309)
0.010
(0.553)
REMIT*FIN
0.0026
(0.404)
0.003
(0.188)
REMIT
INV
FIN
HCON
-0.911
(0.000)***
FDI
-0.043
(0.175)
-0.053
(0.109)
AID
0.026
(0.708)
0.045
(0.469)
SCHO
-0.023
(0.133)
-0.027
(0.087)*
INF
-0.029
(0.392)
-0.023
(0.513)
0.0127
(0.826)
EXR
0.017
(0.954)
0.052
(0.868)
0.320
(0.650)
Sargan-p value
(0.229)
(0.136)
AR(2)-p value
Observations
90
72
72
Instruments
72
36
Adj. R2
0.989
0.992
0.992
No. of
Countries
5
5
5
5
The method of estimation is fixed effects panel OLS and difference GMM. The constant term is included (not reported). t
Statistics probabilities shown in parenthesis are based on robust standard errors which are clustered at the country level.
Significantly different from zero at *90%, **95%, and *** 99% confidence. To reduce the reverse feedback effect from
22
dependent variable, we use one lag of all explanatory and control variables. We use three lags of each independent variable as
instruments, plus EXR and INF are treated as endogenous, the remaining control variables are listed as exogenous
Table A5: Trade balance effects of remittances. Resource Rich-Labor Abundant (RRLA) countries
(Algeria, Iran, Iraq, Libya, Syria, and Yemen), (1992-2012)
Dependant variable: Trade balance (%GDP)
Models
(5.1)
(5.2)
(5.3)
Fixed effects
Fixed effects
Fixed effects
-0.616
(0.000)***
0.065
(0.887)
-8.544
(0.293)
-4.338
(0.102)
-0.880
(0.000)***
-0.962
(0.000)***
-1.148
(0.007)***
-1.357
(0.000)***
0.124
(0.659)
0.013
(0.978)
0.084
(0.887)
0.104
(0.268)
-0.980
(0.000)***
-0.787
(0.006)***
-0.681
(0.066)*
-0.649
(0.016)**
REMIT*INV
0.363
(0.318)
0.191
(0.018)**
REMIT*FIN
-0.044
(0.877)
-0.132
(0.283)
REMIT
INV
FIN
HCON
(5.4)
GMM
RENTS
0.206
(0.022)**
0.157
(0.115)
INF
0.029
(0.652)
0.134
(0.409)
EXR
0.000
(0.099)*
0.000
(0.671)
0.000
(0.553)
FDI
0.273
(0.734)
0.161
(0.837)
0.000
(0.994)
AID
-1.469
(0.179)
-3.441
(0.230)
SCHO
-0.227
(0.073)*
-0.159
(0.143)
Sargan-p value
(0.223)
AR(2)-p value
(0.171)
Adj. R2
0.942
0.941
0.943
Observations
73
73
42
Instruments
42
23
23
No. of Countries
6
6
6
6
The method of estimation is fixed effects panel OLS and difference GMM. The constant term is included (not reported). RENTS
is added to the list of control variables to account for natural exports of these countries. t Statistics probabilities shown in
parenthesis are based on robust standard errors which are clustered at the country level. Significantly different from zero at
*90%, **95%, and *** 99% confidence. To reduce the reverse feedback effect from dependent variable, we use one lag of all
explanatory and control variables. We use three lags of each independent variable as instruments, plus EXR and INF are treated
as endogenous, the remaining control variables are listed as exogenous
\
Table A6: Trade balance effects of remittances. Labor Abundant countries, (1992-2012)
Dependant variable: Trade balance (%GDP)
Models
(6.1)
Fixed effects
(6.2)
Fixed effects
(6.3)
Fixed effects
(6.4)
GMM
REMIT
-0.415
(0.000)***
-0.178
(0.015)**
-0.522
(0.038)**
-0.695
(0.003)***
INV
-0.853
(0.000)***
-0.963
(0.000)***
-0.969
(0.000)***
-1.274
(0.000)***
FIN
-0.045
(0.157)
0.024
(0.553)
-0.031
(0.887)
-0.0659
(0.096)*
HCON
-0.983
(0.000)***
-0.870
(0.000)***
-0.681
(0.546)
-0.0735
(0.001)***
REMIT*INV
0.002
(0.796)
0.0219
(0.030)**
REMIT*FIN
0.005
(0.099)*
-0.024
(0.183)
FDI
0.020
(0.790)
-0.022
(0.765)
AID
-0.095
(0.596)
-0.062
(0.682)
RENTS
0.123
(0.057)*
0.128
(0.045)**
INF
0.009
(0.842)
0.009
(0.851)
EXR
0.000
(0.326)
0.000
(0.026)
-0.001
(0.580)
SCHO
-0.068
(0.387)
-0.055
(0.323)
-0.005
(0.846)
24
Sargan-p value
(0.746)
AR(2)-p value
(0.314)
Adj. R2
0.976
0.984
0.984
Observations
163
163
115
Instruments
No. of countries
115
51
11
11
11
11
The method of estimation is fixed effects panel OLS and difference GMM. The constant term is included (not reported). RENTS
is added to the list of control variables to account for natural exports of these countries. t Statistics probabilities shown in
parenthesis are based on robust standard errors which are clustered at the country level. Significantly different from zero at
*90%, **95%, and *** 99% confidence. To reduce the reverse feedback effect from dependent variable, we use one lag of all
explanatory and control variables. We use three lags of each independent variable as instruments, plus EXR and INF are treated
as endogenous, the remaining control variables are listed as exogenous
25