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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. 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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