remittances, investment and growth in sub-saharan africa
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Remittances, investment andgrowth in sub-Saharan AfricaEmmanuel K.K. Lartey aa Department of Economics , California StateUniversity , Fullerton , CA , USAPublished online: 14 Nov 2011.
To cite this article: Emmanuel K.K. Lartey (2013) Remittances, investment andgrowth in sub-Saharan Africa, The Journal of International Trade & EconomicDevelopment: An International and Comparative Review, 22:7, 1038-1058, DOI:10.1080/09638199.2011.632692
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© 2013 Taylor & Francis
The Journal of International Trade & Economic Development, 2013Vol. 22, No. 7, 1038–1058, http://dx.doi.org/10.1080/09638199.2011.632692
Remittances, investment and growth in sub-Saharan Africa
Emmanuel K.K. Lartey*
Department of Economics, California State University, Fullerton, CA, USA
(Received 1 February 2011; final version received 11 October 2011)
Several studies have examined the impact of remittances on economicgrowth, yet the results remain largely inconclusive. I present an analysisof the relationship between remittances and per capita growth, andinvestigate whether the impact of remittances on growth is throughcapital accumulation or other mechanisms. Using data for sub-SaharanAfrican countries and dynamic empirical models, I find that there is apositive relationship between remittances and growth, as well as apositive interaction effect between remittances and financial depth ongrowth. The findings also reveal threshold values for two mainindicators of financial development, above which the total effect ofremittances on growth is positive. The results further provide evidencefor the existence of an investment channel through which remittancesaffect growth, and indirect evidence that remittances contribute towardsa stable macroeconomic environment, and hence, growth, through aconsumption smoothing effect.
Keywords: economic growth of open economies; developing countries;growth; remittances; panel data
JEL Classifications: F43 O10
Introduction
Remittances have become an important source of foreign capital, exceedingthe inflow of foreign aid and other private capital inflows in many countries.They currently represent about one-third of total financial flows to thedeveloping world. Although the flow of remittances to Africa in general andsub-Saharan Africa in particular has been small relative to globalremittances flows, both the sub-region and the continent have alsoexperienced a tremendous growth in remittances in recent years. Recordedremittances to Africa increased from approximately US$4.9 billion in 1990to an estimated US$50 billion in 2007. Sub-Saharan Africa featuredprominently is this trend over the period, exhibiting an increase fromUS$1.8 billion in 1990 to US$9 billion in 2005, a figure which more than
*Email: [email protected]
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The Journal of International Trade & Economic Development 1039
Remittances, investment and growth in sub-Saharan Africa
Emmanuel K.K. Lartey*
Department of Economics, California State University, Fullerton, CA, USA
(Received 1 February 2011; final version received 11 October 2011)
Several studies have examined the impact of remittances on economicgrowth, yet the results remain largely inconclusive. I present an analysisof the relationship between remittances and per capita growth, andinvestigate whether the impact of remittances on growth is throughcapital accumulation or other mechanisms. Using data for sub-SaharanAfrican countries and dynamic empirical models, I find that there is apositive relationship between remittances and growth, as well as apositive interaction effect between remittances and financial depth ongrowth. The findings also reveal threshold values for two mainindicators of financial development, above which the total effect ofremittances on growth is positive. The results further provide evidencefor the existence of an investment channel through which remittancesaffect growth, and indirect evidence that remittances contribute towardsa stable macroeconomic environment, and hence, growth, through aconsumption smoothing effect.
Keywords: economic growth of open economies; developing countries;growth; remittances; panel data
JEL Classifications: F43; O10
Introduction
Remittances have become an important source of foreign capital, exceedingthe inflow of foreign aid and other private capital inflows in many countries.They currently represent about one-third of total financial flows to thedeveloping world. Although the flow of remittances to Africa in general andsub-Saharan Africa in particular has been small relative to globalremittances flows, both the sub-region and the continent have alsoexperienced a tremendous growth in remittances in recent years. Recordedremittances to Africa increased from approximately US$4.9 billion in 1990to an estimated US$50 billion in 2007. Sub-Saharan Africa featuredprominently is this trend over the period, exhibiting an increase fromUS$1.8 billion in 1990 to US$9 billion in 2005, a figure which more than
*Email: [email protected]
doubled to about US$19 billion in 2007. The estimated US$19 billion inremittances received in 2007 represented about 2.4% of gross domesticproduct (GDP) for the sub-region then, reflecting an increase of 1.8% withrespect to the 2006 estimate. Relative to GDP, remittance flows to sub-Saharan Africa is higher than the average for all developing countries basedon 2009 estimates.
There has, however, been a limited amount of research on remittances insub-Saharan Africa. The aim of this article is, thus, two fold: firstly, toexamine the impact of remittances on investment, and secondly, to analyzethe effect of remittances on growth, focusing on sub-Saharan Africa.
The extant literature has provided evidence that high levels of remittancesare associated with lower poverty indicators and high growth rates (Adamsand Page 2005; Acosta et al. 2008). Remittances also, it has been found,finance investment in human capital, smooth consumption and have multipliereffects through increased household expenditures (Gupta, Pattillo and Wagh2009). Other studies have revealed that rising levels of remittances could beharmful to the long-run growth of recipient economies through anappreciation of the real exchange, and resource allocation from the tradableto the nontradable sector, i.e. the Dutch disease phenomenon (Amuedo-Dorantes and Pozo 2004; Acosta et al. 2009). The potential effect ofremittances on investment has been addressed also in the literature, althoughto a lesser extent. A couple of avenues through which remittances affectinvestment positively, and hence growth, have been identified. Remittances canincrease investments by alleviating credit constraints in developing countries,and thereby positively affect economic growth. It has been argued that theeffect of remittances through this channel would be greater for countries with arelatively underdeveloped financial system. Remittances, it has also beendetermined, could enhance investment by minimizing the volatility ofconsumption, giving rise to a stable macroeconomic environment conducivefor investment activities (Singh, Markus and Kyung-woo 2009).
The existing studies addressing both of these issues have predominantlyfocused on developing countries in general, or countries in other sub-regions. This article contributes to the literature by investigating therelationship between remittances and investment in sub-Saharan Africa.Secondly, it adds to the literature by appealing to different dynamics in theremittances-economic growth relationship in sub-Saharan Africa. Thisshould provide insight into whether remittances to the sub-region enhancegrowth through capital accumulation or other mechanisms.
Based on data for 36 countries and estimates from dynamic empiricalmodels, the results reveal that there is a positive relationship betweenremittances and growth, as well as a positive interaction effect betweenremittances and financial depth on growth. The findings also suggest thereare threshold values for two main indicators of financial development, abovewhich the total effect of remittances on growth is positive. Furthermore, the
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findings are indicative of the existence of an investment channel throughwhich remittances affect growth, and provide indirect evidence thatremittances contribute towards a stable macroeconomic environment, andhence economic growth, through a consumption smoothing effect.
Related literature
Several empirical studies have analyzed the impact of remittances oneconomic growth in recipient countries, yet the results remain largelyinconclusive. Remittances can have negative impact on growth by reducinglabor supply or labor force participation. Chami, Connel and Samir (2005)show that where such effects are dominant, remittances do have adeleterious effect on recipient economies. Another way in which remittancescould adversely impact long-run growth is through the Dutch disease effect(Amuedo-Dorantes and Pozo 2004; Lartey et al. 2008). On the other hand,remittances can also increase economic growth either through an increase ininvestment or some other mechanism. For instance even where remittancesgo towards consumption rather than investment, they could indirectlyenhance growth by smoothing consumption, thereby contributing to a stablemacroeconomic environment, which could foster investment. Chami,Hakura and Montiel (2009) provide some evidence in support of the roleof remittances as automatic stabilizer. Other research that examine therelationship between remittances and investment, either in the case whereremittances act as substitutes for, or as complements to financial depth,show that remittances positively impact growth. Studies that are closelyrelated to this article include Guliano and Ruiz-Arranz (2009), Singh,Markus and Kyung-woo (2009) and Bjuggren, Dzansi and Shukur (2010).
Guliano and Ruiz-Arranz (2009) in a study with global scope, examinethe effect of the interaction between financial depth and remittances ongrowth. They find that coefficients on the interaction terms are all negative,whereas coefficients for financial depth and remittances were positive,suggesting that remittances substitute for financial depth. They also find aninvestment channel through which remittances promote growth in lessfinancially developed countries. Singh, Markus and Kyung-woo (2009)investigate the determinants of remittances in sub-Saharan Africa and theeffects of remittances on growth. Although their findings on the relationshipbetween remittances and growth are mixed, one robust result identified isthat adverse effects of remittances on growth is dominant in sub-SaharanAfrica, and is explainable by the moral hazard argument, that remittancesreduce labor supply and consequently, growth. Bjuggren, Dzansi andShukur (2010) study the effect of remittances on investment. They argue thatremittances affect investment either directly, or indirectly through betterinstitutional framework or more developed financial sector; a high qualityinstitutional framework promotes use of remittances towards investment
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findings are indicative of the existence of an investment channel throughwhich remittances affect growth, and provide indirect evidence thatremittances contribute towards a stable macroeconomic environment, andhence economic growth, through a consumption smoothing effect.
Related literature
Several empirical studies have analyzed the impact of remittances oneconomic growth in recipient countries, yet the results remain largelyinconclusive. Remittances can have negative impact on growth by reducinglabor supply or labor force participation. Chami, Connel and Samir (2005)show that where such effects are dominant, remittances do have adeleterious effect on recipient economies. Another way in which remittancescould adversely impact long-run growth is through the Dutch disease effect(Amuedo-Dorantes and Pozo 2004; Lartey et al. 2008). On the other hand,remittances can also increase economic growth either through an increase ininvestment or some other mechanism. For instance even where remittancesgo towards consumption rather than investment, they could indirectlyenhance growth by smoothing consumption, thereby contributing to a stablemacroeconomic environment, which could foster investment. Chami,Hakura and Montiel (2009) provide some evidence in support of the roleof remittances as automatic stabilizer. Other research that examine therelationship between remittances and investment, either in the case whereremittances act as substitutes for, or as complements to financial depth,show that remittances positively impact growth. Studies that are closelyrelated to this article include Guliano and Ruiz-Arranz (2009), Singh,Markus and Kyung-woo (2009) and Bjuggren, Dzansi and Shukur (2010).
Guliano and Ruiz-Arranz (2009) in a study with global scope, examinethe effect of the interaction between financial depth and remittances ongrowth. They find that coefficients on the interaction terms are all negative,whereas coefficients for financial depth and remittances were positive,suggesting that remittances substitute for financial depth. They also find aninvestment channel through which remittances promote growth in lessfinancially developed countries. Singh, Markus and Kyung-woo (2009)investigate the determinants of remittances in sub-Saharan Africa and theeffects of remittances on growth. Although their findings on the relationshipbetween remittances and growth are mixed, one robust result identified isthat adverse effects of remittances on growth is dominant in sub-SaharanAfrica, and is explainable by the moral hazard argument, that remittancesreduce labor supply and consequently, growth. Bjuggren, Dzansi andShukur (2010) study the effect of remittances on investment. They argue thatremittances affect investment either directly, or indirectly through betterinstitutional framework or more developed financial sector; a high qualityinstitutional framework promotes use of remittances towards investment
and a more developed financial sector channels remittances into investmentactivities. They find that there is a direct and positive relationship betweenremittances and investment, and that institutional quality and level offinancial development interact inversely with remittances, hence remittancesincrease investment more in less financially developed countries, and whereinstitutional quality is lower.
This article adds to the literature by studying remittances and how theyaffect investment in sub-Saharan Africa, different from Bjuggren, Dzansi andShukur (2010) who focus on a broader group of developing countries. I alsoexamine whether remittances affect growth in the sub-region, counter toGuliano and Ruiz-Arranz (2009) whose study possesses a global scope. On theexamination of the relationship between remittances and growth, I followclosely, Singh, Markus and Kyung-woo (2009) but with an alternativeapproach. In contrast to that study, I use a different estimation method, thegeneralized method of moments (GMM) system estimator, as well as differentmeasures of financial development. The goal is to exploit a potential advantageof the GMM system estimator, in that it combines a difference estimator withan estimator in levels in a system; and the inclusion of the levels equationallows the use of information on cross-country differences, which is otherwiseimpossible when using an estimator in first differences, such as fixed-effect two-stage least squares.1 Moreover, the use of different measures of financial depthwould provide additional insight to the interaction effect of remittances andfinancial development on growth in sub-Saharan Africa.
Flow of remittances to sub-Saharan Africa
There has been a substantial increase in remittance flows to emerging marketeconomies, from US$30 billion in 1990 to about US$338 billion in 2008.Remittances as a share of GDP for the continent hovered in the range,1.5%–2%, over the period, 1999–2008. It is estimated that Africa receivesonly about 4% of global remittances, being the least share of all developingcountries (Gupta, Pattillo and Wagh 2009). Sub-Saharan Africa in turn,receives the lowest share of remittances to the continent. Nevertheless, therehas been a steady and significant increase in the flow of remittances into thesub-region in recent years. Remittances increased by about 100% between2000 and 2005, from US$4.5 billion to about US$9 billion, and areestimated to be about US$21 billion in 2009.2
Figure 1 shows the consistent increase in the flow of remittances to thesub-region, both in relation to GDP as well in absolute currency units. Asthe figure depicts, in absolute terms, the steepest increase in remittancesoccurred between 2005 and 2007. Also, when measured as a percentage ofGDP, remittances have generally exhibited an upward trend since 1990,peaking in 2009 at 2.5%. Figure 2 compares remittances as a share of GDPfor sub-Saharan Africa to that for all developing countries, and shows that it
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Figure 1. Flow of remittances to sub-Saharan Africa.Source: WDI (2010).
Figure 2. Remittances (percentage of GDP).Source: World Development Indicators (2010).
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Figure 1. Flow of remittances to sub-Saharan Africa.Source: WDI (2010).
Figure 2. Remittances (percentage of GDP).Source: World Development Indicators (2010).
has been greater for the sub-region since 2007. Sub-Saharan Africa receivedon average about 6% of total remittance flows to developing countriesbetween 2005 and 2009, attaining a high of about 7% in 2009.3 This is arelatively small share in absolute terms, but relative to GDP, many countriesare attracting about the same level of remittances, and in several cases, evenhigher than some major recipient countries in Asia and Latin America.
Remittance flows to sub-Saharan Africa are unevenly distributed. In2004 for instance, of the 10 highest ranked recipients, Nigeria and Sudanreceived US$2.75 billion and US$1.4 billion, respectively, whereas Mali andTogo received US$154 million and US$149 million, respectively. The majorrecipients in 2009 included Nigeria with US$9.5 billion, Sudan with US$3billion, Kenya with US$1.7 billion and Senegal with US$1.3 billion. Whenexpressed relative to GDP, for the same year, the main recipients includedLesotho at 28%, Togo at 12%, Senegal and Cape Verde at 10% and Liberiaat 6% (Tables 1 and 2).
Table 1. Remittances – highest ranked recipients in sub-Saharan Africa (in US$).
Ranking Country Millions (US$) Percent of GDP
1 Nigeria 9,585 62 Sudan 3,059 63 Kenya 1,686 64 Senegal 1,276 105 South Africa 902 06 Uganda 694 47 Lesotho 491 288 Mali 424 59 Togo 329 12
10 Ethiopia 301 1
Source: World Development Indicators (2010).
Table 2. Remittances – highest ranked recipients in sub-Saharan Africa (relative toGDP).
Ranking Country Percent of GDP Millions (US$)
1 Lesotho 28 4912 Togo 12 3293 Senegal 10 12764 Cape Verde 10 1495 The Gambia 9 656 Guinea-Bissau 7 307 Nigeria 6 95858 Sudan 6 30599 Kenya 6 1686
10 Liberia 6 55
Source: World Development Indicators (2010).
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Remittances have been frequently compared to other sources of foreigncapital in developing countries, particularly Official Development Assistance(ODA) and Foreign Direct Investment (FDI), and have exceeded both FDIand ODA in many of these countries. In 2007, remittances were estimated tobe twice as large as ODA, and about two-thirds of FDI inflows todeveloping countries. On the contrary, they have lagged behind ODA andFDI in sub-Saharan Africa (Figures 3 and 4). In 2008, remittances wereabout US$20 billion, representing about half of ODA, and FDI was aboutUS$35 billion. Moreover, as a share of GDP, FDI has dominatedremittances over an extended period of time. This observation notwith-standing, remittances still remain an important source of external finance tothese countries. The sheer magnitude of the flow of remittances to the sub-region in recent years, and the fact that they are a different type of foreignprivate capital with potential effects on investment and economic growth,makes it an essential subject of interest to policy makers.
Empirical analysis
Data and model specification
The data set contains annual observations for 36 sub-Saharan Africancountries, spans the period 1990–2008, and comes from databases of theInternational Monetary Fund (IMF) and the World Bank.4 Table 3provides some basic descriptive statistics for the dependent variables, GDPper capita growth rate and investment as a percentage of GDP, as well as themain control set and the explanatory variable of interest, remittances as apercentage of GDP. Between the two dependent variables, GDP growth rateis highly variable across countries over the period under consideration, withvalues ranging between about 750% to about 35%, and a mean of about4%, whereas investment/GDP has values in the range 1.25%–4.25%, with amean of about 3%. Table 4 presents the correlation matrix for the samegroup of variables, and reveals a positive association between remittancesand investment, and also between remittances and GDP growth rate. It alsoshows that investment is positively correlated with GDP growth rate, butcontrary to expectation, a negative correlation between per capita growthrate and a pair of financial development indexes, namely total private creditas a percentage of GDP and deposit money bank assets as a percentage ofGDP.
I estimate two main equations. The first is an empirical growth modelthat characterizes the relationship between remittances and growth, withGDP per capita growth as the dependent variable. The set of controlvariables in the growth model include investment, financial developmentindicator (private credit, bank assets, M2), government expenditure, tradeopenness, population growth and inflation; with remittances, and aninteraction term of remittances and financial development indicator, being
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Remittances have been frequently compared to other sources of foreigncapital in developing countries, particularly Official Development Assistance(ODA) and Foreign Direct Investment (FDI), and have exceeded both FDIand ODA in many of these countries. In 2007, remittances were estimated tobe twice as large as ODA, and about two-thirds of FDI inflows todeveloping countries. On the contrary, they have lagged behind ODA andFDI in sub-Saharan Africa (Figures 3 and 4). In 2008, remittances wereabout US$20 billion, representing about half of ODA, and FDI was aboutUS$35 billion. Moreover, as a share of GDP, FDI has dominatedremittances over an extended period of time. This observation notwith-standing, remittances still remain an important source of external finance tothese countries. The sheer magnitude of the flow of remittances to the sub-region in recent years, and the fact that they are a different type of foreignprivate capital with potential effects on investment and economic growth,makes it an essential subject of interest to policy makers.
Empirical analysis
Data and model specification
The data set contains annual observations for 36 sub-Saharan Africancountries, spans the period 1990–2008, and comes from databases of theInternational Monetary Fund (IMF) and the World Bank.4 Table 3provides some basic descriptive statistics for the dependent variables, GDPper capita growth rate and investment as a percentage of GDP, as well as themain control set and the explanatory variable of interest, remittances as apercentage of GDP. Between the two dependent variables, GDP growth rateis highly variable across countries over the period under consideration, withvalues ranging between about 750% to about 35%, and a mean of about4%, whereas investment/GDP has values in the range 1.25%–4.25%, with amean of about 3%. Table 4 presents the correlation matrix for the samegroup of variables, and reveals a positive association between remittancesand investment, and also between remittances and GDP growth rate. It alsoshows that investment is positively correlated with GDP growth rate, butcontrary to expectation, a negative correlation between per capita growthrate and a pair of financial development indexes, namely total private creditas a percentage of GDP and deposit money bank assets as a percentage ofGDP.
I estimate two main equations. The first is an empirical growth modelthat characterizes the relationship between remittances and growth, withGDP per capita growth as the dependent variable. The set of controlvariables in the growth model include investment, financial developmentindicator (private credit, bank assets, M2), government expenditure, tradeopenness, population growth and inflation; with remittances, and aninteraction term of remittances and financial development indicator, being
Figure 3. Remittances and FDI (sub-Saharan Africa).Source: World Development Indicators (2010).
Figure 4. Capital inflows to sub-Saharan Africa.Source: World Development Indicators (2010).
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the variables of interest here. The second is a model specification thatdescribes the relationship between remittances and investment, whereinvestment is the dependent variable. The control set for the investmentequation comprises financial development indicator (private credit, bankasset, M2), FDI, interest rate (lending rate), trade openness and GDPgrowth rate, with remittances as the variable of interest.5
Estimation and results
I estimate dynamic models using the GMM estimator suggested by Arellanoand Bond (1991), and Blundell and Bond (1998) which is designed toaddress potential endogeneity issues. This technique reduces omittedvariable biases in static panel models, the omitted variable being the oneperiod lag of the dependent variable; and accounts for endogeneity due tothe introduction of lagged dependent variable as a regressor. Each of theestimated equations is of the form:
yi; t � yi; t�1 ¼ ðf� 1Þyi; t�1 þ b0xit þ ai þ eit
where y is the dependent variable, x is a set of regressors, a is a country-specific effect which is unobservable, and e is an error term.
I employ the GMM system estimator which combines an estimator infirst-differences with an estimator in levels. The inclusion of a levels equationallows the use of information on cross-country differences, which isotherwise impossible to exploit using the difference estimator.6 The validityof instruments underpins the consistency of the GMM estimator, and Iaddress this by employing two specification tests; a test of over-identifyingrestrictions and a test for second-order serial correlation in the error term.The main regressions satisfy both the Sargan test of over-identifyingrestrictions where applicable, as well as the serial correlation test.
Table 3. Descriptive statistics.
Mean SD Min Max
Investment/GDP 2.94 0.39 1.25 4.26Remittances/GDP 0.06 1.76 75.64 5.42Interest rate 2.17 0.87 73.17 3.89GDP growth 3.78 5.06 750.25 35.22Trade openness 4.20 0.50 2.38 5.65Private credit/GDP 72.07 0.82 74.20 0.49Assets/GDP 71.81 0.78 73.99 0.09FDI 0.25 1.74 78.92 3.79GDP Inflation 11.79 16.58 718.19 159.27
Note: Statistics are based on the log of variables except for GDP growth and inflation.
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the variables of interest here. The second is a model specification thatdescribes the relationship between remittances and investment, whereinvestment is the dependent variable. The control set for the investmentequation comprises financial development indicator (private credit, bankasset, M2), FDI, interest rate (lending rate), trade openness and GDPgrowth rate, with remittances as the variable of interest.5
Estimation and results
I estimate dynamic models using the GMM estimator suggested by Arellanoand Bond (1991), and Blundell and Bond (1998) which is designed toaddress potential endogeneity issues. This technique reduces omittedvariable biases in static panel models, the omitted variable being the oneperiod lag of the dependent variable; and accounts for endogeneity due tothe introduction of lagged dependent variable as a regressor. Each of theestimated equations is of the form:
yi; t � yi; t�1 ¼ ðf� 1Þyi; t�1 þ b0xit þ ai þ eit
where y is the dependent variable, x is a set of regressors, a is a country-specific effect which is unobservable, and e is an error term.
I employ the GMM system estimator which combines an estimator infirst-differences with an estimator in levels. The inclusion of a levels equationallows the use of information on cross-country differences, which isotherwise impossible to exploit using the difference estimator.6 The validityof instruments underpins the consistency of the GMM estimator, and Iaddress this by employing two specification tests; a test of over-identifyingrestrictions and a test for second-order serial correlation in the error term.The main regressions satisfy both the Sargan test of over-identifyingrestrictions where applicable, as well as the serial correlation test.
Table 3. Descriptive statistics.
Mean SD Min Max
Investment/GDP 2.94 0.39 1.25 4.26Remittances/GDP 0.06 1.76 75.64 5.42Interest rate 2.17 0.87 73.17 3.89GDP growth 3.78 5.06 750.25 35.22Trade openness 4.20 0.50 2.38 5.65Private credit/GDP 72.07 0.82 74.20 0.49Assets/GDP 71.81 0.78 73.99 0.09FDI 0.25 1.74 78.92 3.79GDP Inflation 11.79 16.58 718.19 159.27
Note: Statistics are based on the log of variables except for GDP growth and inflation.
Table
4.
Correlationmatrix.
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
Investm
ent/GDP
1.00
Rem
ittances/GDP
0.34
1.00
Interest
rate
70.07
70.14
1.00
GDPgrowth
0.16
0.04
0.08
1.00
Tradeopenness
0.50
0.39
0.02
0.00
1.00
Private
credit/G
DP
0.20
0.13
70.10
70.10
0.14
1.00
Assets/GDP
0.26
0.20
70.10
70.05
0.32
0.88
1.00
FDI
0.37
0.13
0.07
0.12
0.55
70.4
0.13
1.00
GDPInflation
70.14
70.10
70.47
70.13
70.06
70.13
70.20
70.11
1.00
Note:Statisticsare
basedonthelogofvariablesexceptforGDPgrowth
andinflation.(1)Investm
ent/GDP,(2)Rem
ittances/GDP,(3)Interest
rate,(4)
GDPgrowth,(5)Tradeopenness,(6)Private
credit/G
DP,(7)Assets/GDP,(8)FDI,(9)Inflation.
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1048 E.K.K. Lartey
Remittances and growth
Table 5 reports results from the preliminary regressions examining theimpact of the exogenous component of remittances on growth. I estimateboth the standalone effect of remittances, as well as the interaction effectwith financial development. Private credit as a percentage of GDP, depositmoney bank assets as a percentage of GDP, and liquid liabilities of thefinancial system as a percentage of GDP (M2/GDP) represent the indicatorsof financial development. The coefficient on remittances in specificationsthat exclude the interaction term are negative and statistically insignificant.In those regressions, each financial development index is incorporated at atime, all of them showing negative and statistically significant coefficients. Inthe model specifications with the interaction term however, the results varyacross indexes. In the model with private credit, the coefficient onremittances is positive and statistically significant, likewise the interactionterm. The specification with bank assets shows a statistically insignificantcoefficient for remittances, alongside coefficients for bank assets and theinteraction term that are insignificant. The third specification showsremittances with an insignificant coefficient, M2/GDP with a negative andstatistically significant, and the interaction term with a coefficient close tozero.
The preliminary estimations, therefore, reveal that the impact ofremittances on growth is sensitive to the model specification, in terms ofthe choice of financial development index and the inclusion of theinteraction term. Given that remittances exhibit a positive relationshipwith per capita growth only in a specification that includes an interactionterm, and coupled with the theoretical arguments in favor of the role of thefinancial sector in enhancing the effects of remittances, I further examine thisrelationship focusing on a specification that accounts for the interactionterm, using the preferred pair of financial development indicators,7 privatecredit and bank assets and the one-step GMM estimator.8
The results, as presented in Table 6, show that remittances enter allestimations using private credit positively, but is only significant in one,whereas the interaction term is consistently positive and statisticallysignificant (columns 1–3). In the equation that features bank assets,however, remittances show a positive and significant coefficient, evenwhen the set of control variables is altered.9 The interaction term is alsopositive and significant in all estimations (columns 4–6). The results indicatethat there is a positive relationship between remittances and growth, and apositive interaction effect between remittances and financial depth ongrowth, with the coefficient on remittances between 1.5 and 2.7, and that onthe interaction terms across all specifications with values between 0.74 and1.1. These estimates suggest that the effect of remittances on growth ispositive, and increases with the level of financial development.
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The Journal of International Trade & Economic Development 1049
Remittances and growth
Table 5 reports results from the preliminary regressions examining theimpact of the exogenous component of remittances on growth. I estimateboth the standalone effect of remittances, as well as the interaction effectwith financial development. Private credit as a percentage of GDP, depositmoney bank assets as a percentage of GDP, and liquid liabilities of thefinancial system as a percentage of GDP (M2/GDP) represent the indicatorsof financial development. The coefficient on remittances in specificationsthat exclude the interaction term are negative and statistically insignificant.In those regressions, each financial development index is incorporated at atime, all of them showing negative and statistically significant coefficients. Inthe model specifications with the interaction term however, the results varyacross indexes. In the model with private credit, the coefficient onremittances is positive and statistically significant, likewise the interactionterm. The specification with bank assets shows a statistically insignificantcoefficient for remittances, alongside coefficients for bank assets and theinteraction term that are insignificant. The third specification showsremittances with an insignificant coefficient, M2/GDP with a negative andstatistically significant, and the interaction term with a coefficient close tozero.
The preliminary estimations, therefore, reveal that the impact ofremittances on growth is sensitive to the model specification, in terms ofthe choice of financial development index and the inclusion of theinteraction term. Given that remittances exhibit a positive relationshipwith per capita growth only in a specification that includes an interactionterm, and coupled with the theoretical arguments in favor of the role of thefinancial sector in enhancing the effects of remittances, I further examine thisrelationship focusing on a specification that accounts for the interactionterm, using the preferred pair of financial development indicators,7 privatecredit and bank assets and the one-step GMM estimator.8
The results, as presented in Table 6, show that remittances enter allestimations using private credit positively, but is only significant in one,whereas the interaction term is consistently positive and statisticallysignificant (columns 1–3). In the equation that features bank assets,however, remittances show a positive and significant coefficient, evenwhen the set of control variables is altered.9 The interaction term is alsopositive and significant in all estimations (columns 4–6). The results indicatethat there is a positive relationship between remittances and growth, and apositive interaction effect between remittances and financial depth ongrowth, with the coefficient on remittances between 1.5 and 2.7, and that onthe interaction terms across all specifications with values between 0.74 and1.1. These estimates suggest that the effect of remittances on growth ispositive, and increases with the level of financial development. T
able
5.
Rem
ittancesandgrowth
–preliminary
regressions(G
MM
system
estimator-tw
ostep).
Regressors
(1)
(2)
(3)
(4)
(5)
(6)
Investm
ent/GDP
3.403***
4.777***
5.003***
4.893***
8.644***
7.925***
(.001)
(.000)
(.000)
(.003)
(.000)
(.000)
Rem
ittances/GDP
70.136
2.972***
70.057
0.599
70.213
70.157
(.309)
(.004)
(.428)
(.509)
(.123)
(.162)
Private
credit/G
DP
73.450***
74.087***
(.001)
(.000)
Private
credit*Rem
it1.023***
(.003)
Assets/GDP
73.028**
72.303
(.016)
(.343)
Assets*Rem
it0.413
(.229)
M2/G
DP
70.368***
70.384***
(.000)
(.000)
M2*Rem
it70.000*
(.059)
Govt.expenditure
71.661
71.676
72.040*
72.951*
0.939
1.132
(.185)
(.351)
(.073)
(.097)
(.663)
(.445)
Tradeopenness
3.586
2.975
2.712
1.818
71.268
71.380
(.106)
(.132)
(.163)
(.476)
(.415)
(.386)
Populationgrowth
1.096***
1.391***
0.488
0.838*
70.905*
70.999**
(.024)
(.020)
(.180)
(.068)
(.057)
(.040)
GDPInflation
70.027**
70.021
70.021
70.021
70.003
70.000
(.016)
(.181)
(.125)
(.226)
(.765)
(.943)
Observations
472
472
468
468
535
535
Countries
30
30
30
30
34
34
Sargantest
(0.999)
(0.998)
(0.999)
(0.998)
(0.997)
(0.999)
Serialcorrelationtest
(0.357)
(0.312)
(0.409)
(0.341)
(0.100)
(0.100)
Note:Dependentvariable:GDPgrowth.p-values
are
inparenthesis.***Significantat1%
level,**5%
level,*10%
level.
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1050 E.K.K. LarteyTable
6.
Rem
ittancesandgrowth
–robust
regressions.
Regressors
(1)
(2)
(3)
(4)
(5)
(6)
Investm
ent/GDP
3.430*
4.096
2.386
3.667**
4.434*
3.366
(.067)
(.137)
(.327)
(.050)
(.095)
(.223)
Rem
ittances/GDP
1.663
1.931
2.736**
1.531**
1.701*
2.213**
(.122)
(.151)
(.042)
(.047)
(.069)
(.023)
Private
credit/G
DP
73.455***
74.861***
75.451***
(.006)
(.005)
(.000)
Private
credit*Rem
it0.773*
0.742*
1.105*
(.073)
(.100)
(.062)
Assets/GDP
73.824***
75.127***
75.602***
(.002)
(.004)
(.000)
Assets*Rem
it0.907***
0.841**
1.105**
(.011)
(.031)
(.043)
Govt.expenditure
70.781
73.073
0.254
70.394
73.188
70.102
(.610)
(.254)
(.913)
(.822)
(.253)
(.965)
Tradeopenness
5.212***
4.738**
5.057***
4.678**
(.005)
(.021)
(.009)
(.026)
Inflation
70.016
70.015
70.020
70.018
(.676)
(.705)
(.619)
(.641)
Populationgrowth
1.674
1.373
70.391
1.333
0.982
71.028
(.122)
(.192)
(.611)
(.316)
(.467)
(.353)
Termsoftrade
73.240
73.590
(.153)
(.146)
CPIInflation
0.019
0.016
(.650)
(..687)
Observations
472
472
430
468
468
426
Countries
30
30
29
30
30
29
Serialcorrelationtest
(0.410)
(0.354)
(0.177)
(0.453)
(.411)
(.183)
Note:Dependentvariable:GDPgrowth.p-values
are
inparentheses.***Significantat1%
level,**5%
level,*10%
level.(1)and(4)–one-step
(robust)with
alllagsofinstruments;(2)and(5)–one-step
(robust)withmaxim
um
2periodlagsofinstruments;(3)and(6)–one-step
(robust)withmaxim
um
2period
lagsofinstruments
(differentcontrolset);Nosargantest
statistic
forone-step
(robust)in
stata.
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Table
6.
Rem
ittancesandgrowth
–robust
regressions.
Regressors
(1)
(2)
(3)
(4)
(5)
(6)
Investm
ent/GDP
3.430*
4.096
2.386
3.667**
4.434*
3.366
(.067)
(.137)
(.327)
(.050)
(.095)
(.223)
Rem
ittances/GDP
1.663
1.931
2.736**
1.531**
1.701*
2.213**
(.122)
(.151)
(.042)
(.047)
(.069)
(.023)
Private
credit/G
DP
73.455***
74.861***
75.451***
(.006)
(.005)
(.000)
Private
credit*Rem
it0.773*
0.742*
1.105*
(.073)
(.100)
(.062)
Assets/GDP
73.824***
75.127***
75.602***
(.002)
(.004)
(.000)
Assets*Rem
it0.907***
0.841**
1.105**
(.011)
(.031)
(.043)
Govt.expenditure
70.781
73.073
0.254
70.394
73.188
70.102
(.610)
(.254)
(.913)
(.822)
(.253)
(.965)
Tradeopenness
5.212***
4.738**
5.057***
4.678**
(.005)
(.021)
(.009)
(.026)
Inflation
70.016
70.015
70.020
70.018
(.676)
(.705)
(.619)
(.641)
Populationgrowth
1.674
1.373
70.391
1.333
0.982
71.028
(.122)
(.192)
(.611)
(.316)
(.467)
(.353)
Termsoftrade
73.240
73.590
(.153)
(.146)
CPIInflation
0.019
0.016
(.650)
(..687)
Observations
472
472
430
468
468
426
Countries
30
30
29
30
30
29
Serialcorrelationtest
(0.410)
(0.354)
(0.177)
(0.453)
(.411)
(.183)
Note:Dependentvariable:GDPgrowth.p-values
are
inparentheses.***Significantat1%
level,**5%
level,*10%
level.(1)and(4)–one-step
(robust)with
alllagsofinstruments;(2)and(5)–one-step
(robust)withmaxim
um
2periodlagsofinstruments;(3)and(6)–one-step
(robust)withmaxim
um
2period
lagsofinstruments
(differentcontrolset);Nosargantest
statistic
forone-step
(robust)in
stata.
I estimate threshold values of private credit and bank assets to ascertainthe level of financial development above which remittances have a positiveeffect on growth.10 Based on results from model specifications given incolumns 3 and 6 of Table 6, the threshold values are 72.48 and 72 forprivate credit and bank assets, respectively, both of which are below theirrespective mean values. Given that the variables are expressed in logarithmicform, these estimates become 0.08 and 0.135 for private credit and bankassets, respectively. This implies that in order for the total effect ofremittances on growth to be positive, private credit must be at least 8% ofGDP, or deposit money bank assets should be at least 13.5% of GDP incountries where there is some degree of financial development.
Remittances and investment
The results from estimating different specifications of the investmentequation are presented in Table 7. I estimate two variants of the model,using each of the three financial development indicators at a time, with andwithout FDI. The coefficient on remittances is consistently positive andstatistically significant across all specifications, whether I control forfinancial development only or both financial development and FDI. Thecoefficient estimates range between 0.03 and 0.04 approximately, whichmeans that when the percentage of remittances to GDP goes up by 1 point,per capita growth rises by at least 0.03%.
There is, therefore, a positive relationship between the exogenouscomponent of remittances and investment, which suggests that there is aninvestment channel through which remittances affect growth. The elasticityof investment with respect to per capita growth rate is positive andsignificant, likewise the effect of trade openness on investment. The laggeddependent variable (one-period lag of investment) enters all equations with apositive and significant coefficient, whereas FDI shows a positive coefficientbut only significant in the specification with M2/GDP. The interest rate(lending rate) is insignificant in all regressions. It is noteworthy that allfinancial development indicators are statistically insignificant across allspecifications.
Analysis of the results
The main results from the various specifications of the growth model(Tables 5 and 6) reveal that there is a positive relationship betweenremittances and growth, and a positive interactive effect betweenremittances and financial depth on growth. These suggest that an increasein remittances lead to an increase in per capita growth, and this effect isincreasing in the level of financial development. The findings, thus, provideevidence in favor of the complementarity of remittances and financial
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1052 E.K.K. Lartey
Table
7.
Rem
ittancesandinvestm
ent–GMM
system
estimator(one-step
robust).
Regressors
(1)
(2)
(3)
(4)
(5)
(6)
Investm
ent/GDP(7
1)
0.597***
0.603***
0.661***
0.669***
0.662***
0.663***
(.000)
(.000)
(.000)
(.000)
(.000)
(.000)
Rem
ittances/GDP
0.036*
0.038**
0.034*
0.034**
0.029**
0.029**
(.064)
(.037)
(.052)
(.048)
(.046)
(.050)
Private
credit/G
DP
0.090
0.084
(.146)
(.234)
Assets/GDP
0.019
70.001
(.769)
(.989)
M2/G
DP
0.000
70.000
(.839)
(.843)
FDI
0.013
0.019
0.024**
(.251)
(.162)
(.040)
Interest
rate
0.028
0.011
0.028
0.010
0.010
70.000
(.167)
(.675)
(.177)
(.700)
(.547)
(.998)
GDPgrowth
0.009*
0.009
0.009*
0.008
0.008*
0.007
(.062)
(.116)
(.074)
(.131)
(.099)
(.195)
Tradeopenness
0.321**
0.301**
0.346**
0.328**
0.313**
0.300**
(.032)
(.053)
(.022)
(.032)
(.037)
(.046)
Observations
288
263
286
261
327
301
Countries
28
28
28
28
31
31
Serialcorrelationtest
(0.342)
(0.741)
(0.746)
(0.341)
(0.763)
(0.897)
Note:Dependentvariable:Investm
ent/GDP.p-values
are
inparentheses.***Significantat1%
level,**5%
level,*10%
level.
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Table
7.
Rem
ittancesandinvestm
ent–GMM
system
estimator(one-step
robust).
Regressors
(1)
(2)
(3)
(4)
(5)
(6)
Investm
ent/GDP(7
1)
0.597***
0.603***
0.661***
0.669***
0.662***
0.663***
(.000)
(.000)
(.000)
(.000)
(.000)
(.000)
Rem
ittances/GDP
0.036*
0.038**
0.034*
0.034**
0.029**
0.029**
(.064)
(.037)
(.052)
(.048)
(.046)
(.050)
Private
credit/G
DP
0.090
0.084
(.146)
(.234)
Assets/GDP
0.019
70.001
(.769)
(.989)
M2/G
DP
0.000
70.000
(.839)
(.843)
FDI
0.013
0.019
0.024**
(.251)
(.162)
(.040)
Interest
rate
0.028
0.011
0.028
0.010
0.010
70.000
(.167)
(.675)
(.177)
(.700)
(.547)
(.998)
GDPgrowth
0.009*
0.009
0.009*
0.008
0.008*
0.007
(.062)
(.116)
(.074)
(.131)
(.099)
(.195)
Tradeopenness
0.321**
0.301**
0.346**
0.328**
0.313**
0.300**
(.032)
(.053)
(.022)
(.032)
(.037)
(.046)
Observations
288
263
286
261
327
301
Countries
28
28
28
28
31
31
Serialcorrelationtest
(0.342)
(0.741)
(0.746)
(0.341)
(0.763)
(0.897)
Note:Dependentvariable:Investm
ent/GDP.p-values
are
inparentheses.***Significantat1%
level,**5%
level,*10%
level.
development in enhancing growth. Arguably, well-functioning financialintermediaries mobilize savings and facilitate transactions, allowing thetransfer of funds from savers to investors at lower costs, and hence mayserve to channel remittances into high-return projects, thereby enhancingeconomic growth.
Credit constraints are essential to the growth prospects of developingcountries, and studies have shown that access to credit is a significantproblem facing entrepreneurs in developing countries (Giuliano and Ruiz-Arranz 2009). In this context, the results from the estimated investmentequations suggest that independent of the financial system, remittances dorelax such credit constraints by providing funds that are allocated towardproductive investments (Table 7), ultimately leading to an increase ingrowth.
The observation that remittances are positive and significant in thegrowth equations, even when controlling for both investment and financialdevelopment; coupled with the result that remittances exhibit a positive andsignificant relationship with investment, are indicative of the existence of aninvestment channel for the effect of remittances on growth, as well as someother mechanism through which remittances influence growth.
The positive standalone effect of remittances on growth potentiallycaptures the consumption smoothing effect, providing anecdotal evidencefor remittances as an automatic stabilizer; that remittances contributetowards a stable macroeconomic environment in the sub-region by financingconsumption during economic downturns which in turn fosters investment.This also suggests the existence of multiplier effects associated with anincrease in consumption levels following remittances inflows.11
The estimated negative coefficient that captures the relationship betweenfinancial development and growth is contrary to what is typically observedin the literature. This is not at all puzzling, however, given that such anoutcome is possible under certain conditions. A negative effect of financialdevelopment on growth can be explained by the notion that thedevelopment of the banking sector for instance, may lead to lower savingsrate, decrease investment and consequently, adversely impact growth. Suchan effect can be caused by financial repression or where financialliberalization is too fast and characterized by poor regulatory system(De Gregorio and Guidotti 1995). Nevertheless, the results still show thatfinancial development is complementary to remittances in enhancinggrowth. Thus, where the exogenous component of financial developmentmay have a negative effect on growth, it may still help mobilize funds fromremittance flows plausibly because remittances are a different kind of capitalinflows with inherently different dynamics.12 Different from the results fromthe growth equations, financial development is not significant in theinvestment equations, and bears a coefficient that is close to zero when M2/GDP is used.
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1054 E.K.K. Lartey
In terms of the relationship between remittances and growth, the keyobservation from these results stand in sharp contrast to those in Singh,Markus and Kyung-woo (2009), who find that there is a negative effect ofremittances on growth in sub-Saharan Africa, suggesting that the negativeeffects through reduced labor force participation and real exchange rateappreciation are dominant. They mention, however, that it is possibleremittances could reduce the volatility of consumption or alleviate creditconstraints, which is what the findings in this study indicate.13
Secondly, the results also differ in comparison to those in Guliano andRuiz-Arranz (2009) who find that the interaction coefficient is negative,suggesting that remittances substitute for financial development. They alsoonly observe a positive coefficient on remittances when investment isdropped as an explanatory variable, which contradicts the findings here. Inaddition, their threshold estimation shows that remittances impact growthpositively only in countries with low financial development, as opposed tothe results here, where the threshold is at a lower bound. It is important tomention again, that Guliano and Ruiz-Arranz (2009) utilize data from abroader sample of developing countries, and which covers a different timeperiod. Nonetheless, this study is corroborative of theirs with respect to thegeneral observation of the existence of an investment channel through whichremittances promote growth. The estimated relationship between remit-tances and investment is also consistent with the results in Bjuggren, Dzansiand Shukur (2010).
Policy implication
The existing literature provides inconclusive evidence on the effects ofremittances on growth in developing economies in general. Such evidence iseven more limited for sub-Saharan Africa. This study provides valuableempirical observation on the interaction effect of remittances and financialsector development on economic growth, and on both the direct and indirecteffects of the exogenous component of remittances on growth throughcapital accumulation and macroeconomic stability.
The estimates presented in Table 6 indicate that a 1% increase in theshare of remittances to GDP will lead to an increase in per capita growth inthe range 1.5%–2.7%. They also suggest that a unit increase in the measureof financial development raises the marginal effect of remittances on growthby a value in the range, 0.74%–1.1%. Furthermore, the estimates presentedin Table 7 imply that a 1% increase in the ratio of remittances to GDPwould lead to an increase in investment by between 0.03% and 0.04%.These results, to a considerable extent, provide some answers to animportant question that has dominated the literature; that is whetherremittances could serve as capital, and hence alleviate financial constraints.Entrepreneurs in developing countries encounter significant hurdles in
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In terms of the relationship between remittances and growth, the keyobservation from these results stand in sharp contrast to those in Singh,Markus and Kyung-woo (2009), who find that there is a negative effect ofremittances on growth in sub-Saharan Africa, suggesting that the negativeeffects through reduced labor force participation and real exchange rateappreciation are dominant. They mention, however, that it is possibleremittances could reduce the volatility of consumption or alleviate creditconstraints, which is what the findings in this study indicate.13
Secondly, the results also differ in comparison to those in Guliano andRuiz-Arranz (2009) who find that the interaction coefficient is negative,suggesting that remittances substitute for financial development. They alsoonly observe a positive coefficient on remittances when investment isdropped as an explanatory variable, which contradicts the findings here. Inaddition, their threshold estimation shows that remittances impact growthpositively only in countries with low financial development, as opposed tothe results here, where the threshold is at a lower bound. It is important tomention again, that Guliano and Ruiz-Arranz (2009) utilize data from abroader sample of developing countries, and which covers a different timeperiod. Nonetheless, this study is corroborative of theirs with respect to thegeneral observation of the existence of an investment channel through whichremittances promote growth. The estimated relationship between remit-tances and investment is also consistent with the results in Bjuggren, Dzansiand Shukur (2010).
Policy implication
The existing literature provides inconclusive evidence on the effects ofremittances on growth in developing economies in general. Such evidence iseven more limited for sub-Saharan Africa. This study provides valuableempirical observation on the interaction effect of remittances and financialsector development on economic growth, and on both the direct and indirecteffects of the exogenous component of remittances on growth throughcapital accumulation and macroeconomic stability.
The estimates presented in Table 6 indicate that a 1% increase in theshare of remittances to GDP will lead to an increase in per capita growth inthe range 1.5%–2.7%. They also suggest that a unit increase in the measureof financial development raises the marginal effect of remittances on growthby a value in the range, 0.74%–1.1%. Furthermore, the estimates presentedin Table 7 imply that a 1% increase in the ratio of remittances to GDPwould lead to an increase in investment by between 0.03% and 0.04%.These results, to a considerable extent, provide some answers to animportant question that has dominated the literature; that is whetherremittances could serve as capital, and hence alleviate financial constraints.Entrepreneurs in developing countries encounter significant hurdles in
having very limited access to credit, which reduces investments. Remittancescould therefore be viewed as an essential source of finance for investmentand consequently, growth in the sub-region. The flow of remittances to sub-Saharan Africa has been consistently on the rise. Notwithstanding, with theemergence of this evidence in support of an investment-enhancing role ofremittances, policy makers can facilitate the inflow of remittances throughmeasures that would result in more effective and relatively inexpensivemoney transfer systems.
The findings reveal that remittances are channeled into investmentprojects, independent of the financial system. There remains, even so, animportant role for financial intermediaries, following the observation thatfinancial development increases the marginal effect of remittances ongrowth. Financial intermediaries provide avenues for mobilization anddirection of funds from savers to borrowers, whether firms or households,who in turn may channel these funds into growth-enhancing activities.Policy makers should, therefore, aim at improving the financial infra-structure of their economies, in order to take advantage of some of the well-documented benefits of better quality financial systems.
An important insight from the results that should also serve as a guidefor policy design in the sub-region is that on average, the positive effects ofremittances seemingly dominate any potentially negative impact that mayexist. In other words, policy should focus less on, but not neglect addressingissues like real exchange rate appreciation and the concomitant lessening ofinternational competitiveness where they exist, and more on mechanismsthat enhance the inflow of remittances, and foster the development andoperation of the financial sector.
Conclusion
In this article, I present an analysis of the relationship between remittancesand per capita growth in a sample of 36 sub-Saharan African countries. Ialso investigate whether the impact of remittances on growth is throughcapital accumulation. I estimate separately, variants of a dynamic growthequation and an investment equation; and based on data from the samplecountries, I find that there is a positive relationship between remittances andgrowth, as well as a positive interaction effect between remittances andfinancial depth on growth. The positive isolated impact of remittances ongrowth suggests there are other mechanisms through which remittancesinfluence growth, and the positive interaction term suggests that the effect ofremittances on growth increases as the level of financial development rises.14
The findings also reveal threshold values for the two main indicators offinancial development, total credit to the private sector and deposit moneybank assets, above which the total effect of remittances on growth ispositive. I further find that an increase in the exogenous component of
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remittances leads to an increase in investment, suggesting that independentof the financial system, remittances contribute towards funding productiveinvestments, and hence enhance economic growth. The results, therefore,provide evidence for the presence of an investment channel through whichremittances affect growth. Furthermore, they provide indirect evidence thatremittances contribute towards a stable macroeconomic environment andeconomic growth through a consumption smoothing effect, indicative of theexistence of other mechanisms through which remittances affect growth inthe sub-region.
Notes
1. Singh, Markus and Kyung-woo (2009) employ a fixed-effect two-stage leastsquares method to estimate their empirical models.
2. All the figures and other estimates reported for remittances are based onworkers’ remittances and compensation of employees received, from the WorldBank’s World Development Indicators (WDI).
3. The estimates represent the author’s computations using data from WDI.4. The countries are Benin, Botswana, Burkina Faso, Cameroon, Cape Verde,
Comoros, Republic of Congo, Cote d’Ivoire, Eritrea, Ethiopia, Gabon, TheGambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Madagascar,Malawi, Mali, Mauritania, Mauritius, Mozambique, Namibia, Niger, Nigeria,Rwanda, Sao Tome and Principe, Senegal, Seychelles, Sierra Leone, SouthAfrica, Sudan, Swaziland, Tanzania, and Togo.
5. The set of control variables for the growth equation is selected from a large setof variables used in the literature to explain per capita economic growth, whileclosely following Singh, Markus and Kyung-woo (2009). For the investmentequation, the choice is made following Guliano and Ruiz-Arranz (2009) andBjuggren, Dzansi and Shukur (2010). Detailed definitions of all variables areprovided in the appendix.
6. These estimators have been widely applied and discussed in a number ofstudies. See Arellano and Bond (1991) and Blundell and Bond (1998) for detailson the GMM difference and system estimators.
7. Private credit is the preferred measure, and is equal to the value of credit byfinancial intermediaries to the private sector only, and improves on othermeasures of financial development. In order to provide additional robustnesschecks, I choose to use bank assets, rather than M2/GDP, which arguably hassome shortcomings (Levine, Loayza and Beck 2000).
8. Following Bond, Hoeffler and Temple (2001), I use the one step GMMestimator with standard errors that are both robust and reliable for finitesample inference, and consider this to be the preferred estimator.
9. To test the robustness of the results, I introduce the terms of trade and CPIinflation to replace trade openness and GDP inflation as control variables inspecifications presented in columns 3 and 6 in Table 6.
10. The approach involves taking the derivative of the growth equation withrespect to each of the two variables and setting it equal to zero. I use the modelspecifications in columns 3 and 6 of Table 6. The resultant equations are asfollows: DGROWTH
DREMITTANCES ¼ 2:736þ 1:105� credit ¼ 0, and DGROWTHDREMITTANCES ¼
2:213þ 1:105� assets ¼ 0.11. This would be consistent with the two main hypotheses on the motivation to
remit; altruistically motivated remittances that tend to increase during
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The Journal of International Trade & Economic Development 1057
remittances leads to an increase in investment, suggesting that independentof the financial system, remittances contribute towards funding productiveinvestments, and hence enhance economic growth. The results, therefore,provide evidence for the presence of an investment channel through whichremittances affect growth. Furthermore, they provide indirect evidence thatremittances contribute towards a stable macroeconomic environment andeconomic growth through a consumption smoothing effect, indicative of theexistence of other mechanisms through which remittances affect growth inthe sub-region.
Notes
1. Singh, Markus and Kyung-woo (2009) employ a fixed-effect two-stage leastsquares method to estimate their empirical models.
2. All the figures and other estimates reported for remittances are based onworkers’ remittances and compensation of employees received, from the WorldBank’s World Development Indicators (WDI).
3. The estimates represent the author’s computations using data from WDI.4. The countries are Benin, Botswana, Burkina Faso, Cameroon, Cape Verde,
Comoros, Republic of Congo, Cote d’Ivoire, Eritrea, Ethiopia, Gabon, TheGambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Madagascar,Malawi, Mali, Mauritania, Mauritius, Mozambique, Namibia, Niger, Nigeria,Rwanda, Sao Tome and Principe, Senegal, Seychelles, Sierra Leone, SouthAfrica, Sudan, Swaziland, Tanzania, and Togo.
5. The set of control variables for the growth equation is selected from a large setof variables used in the literature to explain per capita economic growth, whileclosely following Singh, Markus and Kyung-woo (2009). For the investmentequation, the choice is made following Guliano and Ruiz-Arranz (2009) andBjuggren, Dzansi and Shukur (2010). Detailed definitions of all variables areprovided in the appendix.
6. These estimators have been widely applied and discussed in a number ofstudies. See Arellano and Bond (1991) and Blundell and Bond (1998) for detailson the GMM difference and system estimators.
7. Private credit is the preferred measure, and is equal to the value of credit byfinancial intermediaries to the private sector only, and improves on othermeasures of financial development. In order to provide additional robustnesschecks, I choose to use bank assets, rather than M2/GDP, which arguably hassome shortcomings (Levine, Loayza and Beck 2000).
8. Following Bond, Hoeffler and Temple (2001), I use the one step GMMestimator with standard errors that are both robust and reliable for finitesample inference, and consider this to be the preferred estimator.
9. To test the robustness of the results, I introduce the terms of trade and CPIinflation to replace trade openness and GDP inflation as control variables inspecifications presented in columns 3 and 6 in Table 6.
10. The approach involves taking the derivative of the growth equation withrespect to each of the two variables and setting it equal to zero. I use the modelspecifications in columns 3 and 6 of Table 6. The resultant equations are asfollows: DGROWTH
DREMITTANCES ¼ 2:736þ 1:105� credit ¼ 0, and DGROWTHDREMITTANCES ¼
2:213þ 1:105� assets ¼ 0.11. This would be consistent with the two main hypotheses on the motivation to
remit; altruistically motivated remittances that tend to increase during
recessions, and self-interested remittances that target investment opportunities(Acosta et al. 2009).
12. For example, financial development may lower domestic savings coming fromdomestic income, and hence decrease growth, but at the same time, becauseremittances supplement domestic incomes, the presence of a developed bankingsystem could aid mobilization of these funds for growth enhancing purposes.
13. It should be noted that I use a different estimation technique which possesses aclear advantage in allowing exploitation of country-specific effects. The mainfinancial development indicators I use also vary from those in Singh, Markusand Kyung-woo (2009). Moreover, the time period I consider (1990–2008) hasthree more observations per country relative to that study. The set of countriesare identical, however.
14. Ball et al. (2008) study how exchange rate regimes matter for macroeconomiceffects of remittances. There is also a vast literature on the effect of exchangerate regimes and growth. The effect of the interaction between exchange rateregimes, financial development and remittances in the sub-region would,therefore, be an interesting subject of research in the future.
References
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Acosta, P., E.K.K. Lartey, and F. Mandelman. 2009. Remittances and Dutchdisease. Journal of International Economics 79: 102–16.
Adams, R., and J. Page. 2005. Do international migration and remittances reducepoverty in developing countries? World Development 33, no. 10: 1645–69.
Amuedo-Dorantes, C., and S. Pozo. 2004. Workers’ remittances and the realexchange rate: A paradox of gifts. World Development 32, no 8: 1407–17.
Arellano, M., and S. Bond. 1991. Some tests of specification for panel data: MonteCarlo evidence with an application for employment equations. Review ofEconomic Studies 58: 277–97.
Ball, Christopher P., M. Cruz-Zuniga, C. Lopez, and J.A. Reyes. 2008. Remittances,inflation and exchange rate regimes in small open economies. EconomicsWorking Paper no. WP 2008-03, University of Cincinnati.
Bjuggren, P.-O., J. Dzansi, and G. Shukur. 2010. Remittances and investment.Working Paper Series no. 216, CESIS Electronic.
Blundell, R., and S. Bond. 1998. Initial conditions and moment restrictions indynamic panel data models. Journal of Econometrics 87:115–43.
Bond, Stephen R., Hoeffler, Anke, and Temple, Jonathan R.W. 2001. GMMestimation of empirical growth models. Economics Papers 2001-W21, EconomicsGroup, Nuffield College, University of Oxford.
Chami, Ralph, Connel Fullenkamp, and Samir Jahjah. 2005. Are immigrantremittance flows a source of capital for development? International MonetaryFund (IMF) Staff Paper in 52 (1).
Chami, R., D. Hakura, and P. Montiel. 2009. Remittances: An automatic outputstabilizer? IMF Working Papers: 91/2009, International Monetary Fund.
De Gregorio, J., and P. Guidotti. 1995. Financial development and economicgrowth. World Development 23: 433–448.
Giuliano, P., and M. Ruiz-Arranz. 2009. Remittances, financial development andgrowth. Journal of Development Economics 90: 144–152.
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Gupta, Sanjeev, Catherine A. Pattillo, and Smita Wagh. 2009. Effect of remittanceson poverty and financial development in sub-Saharan Africa.World Development37, no 1: 104–15.
Lartey, Emmanuel K.K., Federico S. Mandelman, and Pablo A. Acosta. 2008.Remittances, exchange rate regimes, and the Dutch disease: A panel dataanalysis. Working Paper 2008-12, Federal Reserve Bank of Atlanta.
Levine, R., N. Loayza, and T. Beck. 2000. Financial intermediation and growth:Causality and causes. Journal of Monetary Economics 46: 31–77.
Singh, Raju J., Markus Haacker, and Kyung-woo Lee. 2009. Determinants andmacroeconomic impact of remittances in sub-Saharan Africa, IMF workingPaper WP/09/216, IMF, Washington DC.
Appendix
Definitions and data sources
Remittances (% GDP): Percentage of workers’ remittances, compensation ofemployees, and migrant transfers credit (US$) over GDP in current (US$) (WorldBank Data – WDI).
M2: Money and quasi money (M2) as % of GDP (World Bank Data – WDI).Deposit money bank assets: Claims on domestic real nonfinancial sector by Deposit
money banks as a share of GDP (Financial Structure database-Beck andDemirguc-Kunt 2009).
Private credit: Credit to private sector by deposit money banks and other financialinstitutions as a share of GDP (Financial Structure database-Beck and Demirguc-Kunt 2009).
Terms of Trade: Index of the relative price of a country’s exports of goods andservices with respect to imports (World Economic Outlook Database, IMF).
Trade Openness: Sum of exports and imports of goods and services as % of GDP(World Bank Data – WDI).
Foreign direct investment (FDI): Foreign direct investment, net inflows (% of GDP)(World Bank Data – WDI.
Government expenditure growth: General government final consumption expenditure(% of GDP) (World Bank Data – WDI).
Investment: Gross capital formation (formerly gross domestic investment) (% ofGDP) (World Bank Data – WDI).
GDP growth: GDP per capita growth (annual %) (World Bank Data – WDI).GDP inflation: Inflation, GDP deflator (annual %) (World Bank Data – WDI).CPI inflation: Inflation, consumer prices (annual %) (World Bank Data – WDI).Population growth: Population growth (annual %) (World Bank Data – WDI).Interest rate: Lending interest rate (%) (World Bank Data – WDI).
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