A Panel Unit-Root Tests and Panel Cointegration ...

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DEPARTMENT OF E CONOMICS AND FINANCE WORKING P APER SERIES • MARCH 2012

Financial Development and Remittances in Africa and the Americas: A Panel Unit-Root Tests and Panel Cointegration Analysis Bichaka Fayissa* Middle Tennessee State University Christian Nsiah Black Hills State University Abstract

In view of the sizable increase in recorded migrant workers’ remittances to developing countries from $70 billion in 2000 to $167 in 2005, this study investigates the long-run relationship between remittances and financial services development (FSD) and control variables including exchange rate (ERS), the size of migrant stock (MSK), the domestic per capita income (DPC) in the receiving country and foreign per capita income (FPC) in the main host country. We use a newly developed panel fully modified OLS (PFMOLS) on annual panel data over the 1985-2007 period for 44 countries consisting of 25 from Africa and 19 from the Americas. It is found that financial development, exchange rate stability, and the size of migrant stock have positive and statistically significant effect on remittances in both regions and in each of the regions. The study has important policy implications for the role of the financial services development through domestic credit expansion by the banking industry as well as increased competition among money transfer operations and exchange rate stability in order to promote the continuation of remittance inflows as a major source of economic growth in Africa and the Americas. The study also shows that there are regional differences in the impact and magnitude of the determinants of remittances.

Key Words: Workers’ Remittances, Transaction Cost Factors, Per Capita income, Unit-Root tests, Error Correction Model, PFMOOLS, Panel Data, Africa and the Americas JEL Classification: E21 F21, G22, J61, O16 *Correspondences: Bichaka Fayissa, Department of Economics and Finance, Middle Tennessee State University, Murfreesboro, TN 37132, U. S.A. Tel (615)898-2385, Fax (615) 898-5596; Email: [email protected]

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Financial Development and Remittances in Africa and the Americas: A Panel Fully Modified OLS Analysis Abstract In view of the sizable increase in recorded migrant workers’ remittances to developing countries from $70 billion in 2000 to $167 in 2005, this study investigates the long-run relationship between remittances and financial services development (FSD) and control variables including exchange rate (ERS), the size of migrant stock (MSK), the domestic per capita income (DPC) in the receiving country and foreign per capita income (FPC) in the main host country. We use a newly developed panel panel fully modified OLS (PFMOLS) on annual panel data over the 1985-2007 period for 44 countries consisting of 25 from Africa and 19 from the Americas. It is found that financial development, exchange rate stability, and the size of migrant stock have positive and statistically significant effect on remittances in both regions and in each of the regions. The study has important policy implications for the role of the financial services development through domestic credit expansion by the banking industry as well as increased competition among money transfer operations and exchange rate stability in order to promote the continuation of remittance inflows as a major source of economic growth in Africa and the Americas. The study also shows that there are regional differences in the impact and magnitude of the determinants of remittances.

. I. Introduction Recent studies by the World Bank (2006) and Freund and Spatafora (2008) indicate that recorded flows of workers’ remittances have increased from about $70 billion in 2000 to $167 billion in 2005. For many developing countries, remittances represent a major part of international capital flows, surpassing foreign direct investment (FDI), export revenues, and foreign aid (Giuliano and Ruiz-Arranz, 2005). Figures 1, 2, and 3 below depict the financial flows in the form of remittances, overseas development assistance (ODA), and foreign direct investment (FDI) for African countries and the Americas as a group and for each of the two regions of this study. Since many developing countries rely on remittance inflows for poverty reduction, consumption smoothing, and investment for profit motives, a study of the factors which promote remittance inflows to these areas such as financial services development, exchange rate stability, and the size of migrant stock, or impede (transaction costs) is relevant and important. In a recent study, Freund and Spatafora (2008) discuss that the determinants of transaction cost factors including the financial services development (FSD), remittances to a dollarized economy (RDE),

3 and competition in the financial services (CFS) and how they tend to reduce the transaction costs of remittances resulting in the increased flow of remittances as a key source of growth in the developing countries. On the other hand, they observe that the existence of weak institutions and business risk tend to increase the transaction costs and reduce the amount of money remitted to developing countries using cross-sectional and panel data. In this study, we are interested in exploring the long-run relationship between remittances and their determinants including the financial services development (FSD) and other control variables such as exchange rate stability (ERS), the size of migrant stock (MSK), the domestic per capita income of the receiving country (DPC), and the foreign per capita income of a major host country (FPC) such as the U.S. or the major OECD countries. The main objective of this study is, therefore, to estimate the long-run relationship between international workers’ remittances (REM) and its determinants including the financial services development (FSD), the exchange rate stability (ERS) in receiving country, the size of the migrant stock (MSK the domestic per capita income of the receiving country (DPC), and the foreign per capita income (FPC) in the host country as control variables for Africa and the Americas. The study makes important contributions to the existing literature on three fronts. First, it utilizes rich panel data covering two key regions of the world (Africa and the Americas) which heavily rely on remittances as one of the major sources of their economic growth as a group and/or individually. Secondly, we use a newly developed panel unit-root tests, cointegration tests, and Panel Fully Modified OLS (PFMOLS to establish the longrun relationship between remittances and the transaction cost factors (FSD, ERS, and MSK) and the domestic and foreign per capita income as control variables (DPC and FPC, respectively). Thirdly, the study provides a unified comparative analysis of the relative impact of the financial services development and other control variables (ERS, MSK, DPC, FPC) on remittances in Africa and the Americas. The findings suggest that the financial services development (FSD), the exchange rate stability (ERS), and increases in the size of migrant (MSK) have positive and statistically significant effect on remittances in both regions as a group and individually.

4 The rest of this paper is organized as follows. The next section gives a brief review of the literature. Section 3 describes the data and methodology. The empirical results are presented in section 4. The final section draws conclusion based on the results.

2. A Review of Selected Literature A recent joint study by the World Bank and the Central Bank of Kenya suggests that money sent to Africa by those living abroad is estimated at $21 billion and is expected to grow by two percent in 2010. While such sizable financial inflows represent a significant share of the gross domestic product (GDP) for many African countries, however, it is not as high as for the other regions of the world such as Latin American, or Asian countries (Otieno, 2010). For instance, remittances to the Philippines in Asia and Mexico in Latin America alone were roughly the same as those received by the whole of sub-Saharan Africa in 2010. The top ten recipients of remittances in Africa in 2010 include Nigeria (US$10 billion), Sudan (US$3.2 billion), Kenya (US$1.8 billion), Senegal (US$1.2 billion), South Africa (US$1.0 billion), Uganda (US$0.8 billion), Lesotho (US$0.5 billion), Ethiopia (US$387 million), Mali (US$385 million), and Togo (US$302 million). Many studies have investigated the microeconomic impact of remittances on economic growth. Based on household survey data from various African countries, few empirical studies have investigated the role of remittances in reducing poverty (Lucas and Stark, 1985; Adams, 1991; Sander, 2004; Azam and Gubert, 2005; Adam and Page, 2005; Adam, 2006). One theoretical strand suggests that workers’ remittances are mainly used for consumption purposes and, hence, have minimal impact on investment and may, in fact, reduce the incentive of the recipients to work. In other words, remittances are widely viewed as compensatory transfers between family members who lost skilled workers due to migration. Other studies by Stark and Lucas (1988), Taylor (1992), Faini (2002), and Adams and Page (2005) find a positive relationship between remittances and economic growth based on 113 countries. Focusing on the experience of 101 developing countries, however, recent studies by Chami et al. (2005) and IMF (2005) find negative and no impact of remittances on economic growth.

5 Stahl and Arnold (1986), however, argue that the use of remittances for consumption may have a positive effect on growth because of their possible multiplier effect by stimulating business development in the recipient countries. Moreover, remittances respond to investment opportunities in the home country as much as to charitable or insurance motives. Many migrants invest their savings in small businesses, real estate or other assets in their own country because they know local markets better than in their host countries, or probably expecting to return in the future. In about two-thirds of developing countries, remittances are mostly profit-driven and increase when economic conditions improve back home. Such external monetary flows are particularly used for investment where the financial sector does not meet the credit needs of local entrepreneurs (Institute of Development Studies, id21 insights, #60, January, 2006). Using panel data set of developing Asia and the Pacific countries during the period 1993-2003, Jongwanich (2007) finds that remittances constitute the largest foreign exchange earnings and represent more 10 percent of GDP. A recent study by Vargas-Silva, et al. (2009), using panel data for more than 20 countries in the Asian region for 1988–2007, also finds that remittances positively affect home country real gross domestic product (GDP) per capita growth, i.e. a 10% increase in remittances as a share of GDP leads to a 0.9–1.2% increase in GDP growth. Nsiah and Fayissa (2011) also find that remittances have a positive and significant effect on economic growth using panel unit-root tests, cointegration tests, and Panel Fully Modified OLS (PFMOLS) on annual panel data from 1985–2007 for 64 countries consisting of 29 from Africa, 14 from Asia, and 21 from Latin America and the Caribbean region. According to a World Bank study (2008), Latin America and the Caribbean countries received around US$50 billion in remittances in 2005. This represents about 70 percent of foreign direct investment (FDI) and is almost 8 times more than official development assistance (ODA) to the region. In terms of sheer volume, Mexico outpaces the pack in the region with over US$25 billion, followed by Brazil (US$7.2 billion), Colombia (US$4.8 billion), Guatemala (US$4.3 billion), El Salvador (US$3.8 billion), the Dominican Republic (US$3.1 billion), Peru (US$2.9 billion), Ecuador (US$2.8 billion), and Honduras (US$2.7 billion), according to the IDB (Grogg, 2009). However, as shown in Figure 2, on a per capita basis, El Salvador gets the most, followed by the Dominican Republic, Honduras, Guatemala, and

6 Mexico rounding up the top five recipients in that order. Using a large cross-country panel dataset, the Acosta et al. (2008) find that remittances in Latin American and Caribbean (LAC) countries have increased economic growth and reduced inequality and poverty. While Giuliano and Arranz (2009) find that remittances pave the way for financial development leading to economic growth, Amuedo-Durantes and Pozo (2004) and Chami, et al. (2005) argue that remittances may have a deleterious effect on economic growth otherwise known as the “Dutch disease” by reducing labor force participation incentives of the recipients. Thus, we cannot, a priori, predict the direction or the size of the impact of remittances on the economic growth based on the above discussions. In spite of their significant role on economic growth, however, only few studies have considered the factors which either have positive, or negative effect on remittances including the financial services development, exchange rate stability, and the size of migrant stock (Freund and Spatafora, 2008). Our study attempts to fill the gap in the empirical literature with respect to the determinants of remittances by using the proxies of transaction costs including the financial services development, exchange rate stability, and the size of migrant stock (Freund and Spatafora, 2008). The effect of income on remittances with a particular emphasis on the cyclicality of remittances has been investigated by Aggarwal and Spatapora (2005) and Sayan (2006) while the Fiani (2006) study focuses on the variation of remittance inflows by the different levels of migrant education. Using cross sectional and panel data, Fruend and Spatapora (2008) expand the previous studies by considering the size of migrant stock and transaction costs. They find that a rise in transaction costs is due to less developed financial services and exchange rate volatility will reduce the inflow of remittances to developing countries.. The altruistic and investment motives of remittances have been investigated by Johnson and Whitelaw (1974) and Lucas and Stark (1985). They argue that the altruistic motive of remittances is aimed at supporting recipients for consumption smoothing and compensating them against catastrophic events. This implies that remittances are negatively related with the economic conditions of real GDP growth and employment in the home country (Freund and Spataporta, 2008). On the other hand, the

7 investment motive of remittances focuses on taking advantage of high returns or other opportunities in the home country, implying that remittances are positively related to the economic conditions and investment opportunities in the home country Lin (2011). The impact of the exchange rate on remittances is less obvious since migrants may decide to send a fixed amount of money in the currency of their host, or in the local currency, compensating for the effects of exchange rates. Browne and Mineshima (2007) find that remittances to the Pacific region depend on the rate of real GDP growth in the remitting countries, the distance to remitting countries, and whether the home and remitting countries share common language. In addition, they find close links between remittances and the aggregate stock of migrants with the implication that there is economics of scale as the size migrant stock increases and unit transaction costs decease. Chamon et al. (2005) find that exchange rate depreciation in the receiving country is positively related with remittances. On the other hand, Bourdet and Flack (2003), Amuedo-Dorantes and Pozo (2004) find that remittance inflows may result in an appreciation of the equilibrium real exchange rate. Consequently, the impact of real exchange rate on remittances cannot be predicted a priori. The next section highlights the methodology and data of the study.

3. Methodology and Data 3.1 Methodology: Panel Fully Modified Ordinary Least Squares Test (PFMOLS) We employ an autoregressive distributive lag (ARDL) dynamic panel specification in the following form: (5)

where r it, i= 1…..,N, t=1…..T, denotes remittances of the ith country in period t, respectively. Xit is a K*1 vector of explanatory variables;

are scalars and

are a K*1 vector of coefficients. If the

variables in equation (5) are I(1) and cointegrated, then the error term is an I(0) process for all of our groups i. An important feature of variables that are cointegrated is their responsiveness to deviations from

8 the long-run state, suggesting an error-correcting model where the short-run dynamics (shocks) of our variables will adjust to the long-run equilibrium are influenced by deviations from long-run equilibrium. This allows us to re-parameterize equation (5) into an error correction model written as:

(6)

where

denotes the error-correcting speed of adjustment term. If

=0, then there is no evidence for a

long-run relationship between the dependent variable and our regressors. The parameter

is expected

to be significantly negative under the previous assumption that the variables return to a long-run equilibrium. The vector

is of particular importance because it contains the long-run relationships

(elasticities) between the per capita income and our variables.1 We employ the pooled-mean estimator for the dynamic panel data advocated by Pesaran, et al. (1998 & 1999) in estimating the long-run worker remittance elasticity of growth. They propose a maximum likelihood type “pooled-mean group” (PMG) estimator which combines pooling and averaging individual regression coefficients in equation (6). In this case, one could use a conditional error correction framework where long-run elasticities are constrained to be the same, but short-run dynamics are allowed to vary over the cross-sections. The PMG estimators have two key advantages over other commonly used estimators in the literature. First, compared to the static fixed-effects estimator, the PMG estimator allows for dynamics while the static fixed-effects model does not. In comparison to the dynamic fixed- effects estimator, the PMG estimator has an advantage because it allows the short-run dynamics (shocks) and error variances to differ across cross-sections. Secondly, another pertinent advantage of the PMG is that the underlying auto-regressive distributed lag (ARDL) structure dispenses with the importance of the unit root pretesting of the variables in question. As long as there is a unique vector which defines the long-run 1

9 relationship among our variables of interest, it is of no consequence if the variables are either I(1), or I(0) since the PMG estimates of an ARDL specification will yield consistent estimates. 2 3.2 Data We employ an annual panel dataset for 44 countries for the period between 1985 and 2007. The countries include 25 from Africa and 19 from the Americas. Using annual data is important for our analysis because they help us to circumvent problems associated with seasonality (Vanegas & Croes, 2003). They also help us not to make an unwarranted assumption of homogeneity among the countries in the sample. All data come from the World Bank’s 2010 World Development Indicators Dataset, except for the foreign per capita income which is also taken from Dumont et al. (2010). The data description and summary statistics are provided in Tables 1 and 2 below. 4. Empirical Results of Panel Fully Modified OLS (PFMOLS) Estimation Tests

Having established that the variables are stationary and exhibit long-run cointegration in the previous sub-sections, we now estimate the long-run impact of financial services development and the control variables on workers’ remittances in Africa and the Americas using the Panel Fully Modified Ordinary Least Squares (PFMOLS) estimator. The choice of the PFMOLS over Ordinary Least Squares (OLS) estimators is based on the fact that it has the dual advantage of correcting for both serial correlation and potential endogeneity problems that arise when the OLS estimators are used. We estimate three models, one for our whole sample and one each for the two regions under consideration. Table 6 present the results of our PFMOLS estimations. The negative and significant values of the

parameter for all our models indicate that there is a

long-run relationship between our variables. Our estimated long-run impact of financial services development and the control variables are consistent with the theoretical expectations for the region as a whole and this long-run relationship is statistically significant for all determinants of remittances. The 2

Reverse causality is not a problem since the variables are I(1) in which case there exists the superconsistent property.

10 coefficients of the financial services development (FSD) and exchange rate stability (ERS) are found to be positive and statistically significant for both regions and for each region, individually. The migrant sock variable has positive and statistically significant effect on remittances in both regions as a group and in the Americas, while for Africa it is positive, but statistically insignificant. The coefficient of the domestic per capita income (DPC) is positive and statistically significant for both regions and Africa, suggesting that this variable is pro-cyclical meaning that remittance inflows are directly related to the state of the domestic the economy, i.e. remittances will increase as the domestic income rises. In the case of the Americas, however, remittances are countercyclical, meaning that they tend to slow down when the domestic economy improves, although the coefficient of domestic per capita income is insignificant. The responsiveness of remittances to the main host country in both regions and the Americas is greater than one (i.e., a 1% increase in the main host income will increase remittances by 1.4% and 2.4% in both regions and the Americas, respectively). In other words, an increase in the main host income will increase migrant workers’ wages which allows them to send home more money. For the African region, however, remittances are found to be countercyclical to the main host income, but are less responsive to the increase in the host country income. Moreover, the coefficient of the migrant stock has the expected sign and statistically significant for both regions as a group and the Americas. The coefficient of migrant stock for Africa is, however, positive but statistically insignificant. This finding may be driven by the fact that migration from Africa, relative to from other regions of the world may be slow due to the immigration policies of host countries toward people from Africa, or also the fact that migrants from Africa are more likely to attempt to invest more of their acquired wealth in the host country when economic conditions are better in the host country than repatriate their acquired additional income to their home countries. The results presented indicate that the financial services development variable, (FSD), exchange rate stability (ERS), and the migrant stock (MSK) have a positive and significant long-run effect on remittances in our overall sample and in each of the regions Our results also indicate that the long-run impact of financial services development on remittances may depend on the geographical location of the countries in the study. These geographical differences may be caused by the differences in the dynamics

11 of the financial services development. For example, countries in Latin America and Caribbean may enjoy better financial services that facilitate efficient transmission of remittances in comparison to countries in Africa. Furthermore, expectations and culture of the senders and recipients of remittances while similar in one region may differ from one region to the other. For example, remittances may be largely used for investment purposes in one region, whereas it may be used mainly for current consumption supplementation in the other, thus having a significantly positive long-run impact in the region where it is largely used for investments, and either a negative, insignificant, or slightly positive impact on the longrun economic growth in areas where it is used largely to supplement consumption. Comparatively, our results indicate that a 10% improvement in the financial services development will lead to a 6.3 percent and 2.81percent long-run increase in remittances in Africa and the Americas, respectively. These results indicate that financial services development contribute more to the long-run increase in remittances to Africa than to the Americas, suggesting that there are differences in the financial services development in the recipient regions (more in the Americas less in Africa). Another important finding of the study is that exchange rate stability has a positive and statistically significant in both regions.

5. Conclusions and Policy Implications This study investigates whether there is a long-run stable relationship between remittances and the financial services development and other salient control variables such as the exchange rate stability, the migrant stock, the domestic and foreign per capita income in Africa and the Americas. We use annual panel data spanning over the 1985-2007 period and recently developed panel unit root tests (Choi, 2001) and error correction model by Westerlund (2007) and Pedroni (2004) to test the stationarity and cointegration of the panel data series, respectively. We also use Panel Fully Modified OLS, Autoregressive Distributed Lag Model (ARDL) model to determine the long-run relationship between the measure of remittances and the financial services development indicators and other control variables.

12 Overall, all our findings are consistent with other studies that have investigated the impact of financial services development on remittances. However, our findings are much more reliable because we use a superior dataset covering a larger group of countries and a longer time series, and also due to the fact that we employ newer and better estimation methodologies. The results indicate that the financial services development do, indeed, have a statistically significant long-run impact on the increased inflow of remittances by reducing the constraining cost of remittances to both regions, but especially to Africa. Freund and Spatafora (2008) find that high transaction costs significantly reduce recorded remittances: a one percentage point reduction in transaction costs increases recorded remittances by 14-23%. In an era when there is a strong opposition to the disbursement of the traditional sources of development financing in the form of foreign aid, foreign direct investment (FDI), and private transfers, remittances serve as a life line for development projects. In terms of policy implications, governments in these regions may find it very productive to implement policies which promote financial services development and exchange rate stability in order to ensure the external flow of resources in the form of remittances for the expressed purpose of poverty reduction, consumption smoothing, and the profit motive of private investment.

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14 Dumont, J., Spielvogel, Gilles, and Sarah Widmaier (2010). "International Migrants in Developed, Emerging and Developing Countries: An Extended Profile", OECD Social, Employment and Migration Working Papers No. 113. Freund, C. and N. Spatafora,. (2008). “Remittances, transaction costs, and informality,” Journal of Development Economics, 86: 356-366. Freund, Garcia-Fuentes, Pablo A. and P. Lynn Kennedy. (2009). “Remittances and economic growth in Latin America and the Caribbean: the impact of the human capital development,” Southern Agricultural Economics Association, 2009 Annual Meeting, January 31-February 3, 2009, Atlanta, Georgia Giuliano, P. and M. Ruiz-Arranz. (2005). Remittances, financial development, and growth, IMF 05/ 234, IMF Washington DC. Giuliano, P. and M. Ruiz-Arranz, 2009, “Remittances, financial development, and growth,” Journal of Development Economics, 90 (1): 144-152 Grogg, Patricia, 2009, “Latin America: remittances drop will hurt poor,” May 29, 2009, http://ipsnews.net/news.asp?idnews=47032. Gupta, Sanjeev, Catherine Pattillo, and Smita Wagh, (2007). “Making remittances work for Africa,” Finance & Development, 44, No. 2 (June, 2007): 1-9. Hadri, K. (1999). Testing for stationarity in heterogeneous panel data. Econometrics Journal, 3: 148161. Im, K. S., H. Pesaran, and Y. Shin (2003). Testing for unit roots panels, Journal of Econometrics 54: 159178. Institute of Development Studies, (2006). http://www.id21.org/insights/insights60/art03.html IMF, 2005, World Economic Outlook, International Monetary Fund, Washington DC. Johnson, G. E. and W. E. Whitelaw, (1974) Urban-rural income transfers in Kenya: an estimated remittances function, Economic Development and Cultural Change, 22: 473-479. Jongwanich, Juthathip, 2007, Workers’ Remittances, Economic Growth, and Poverty in Developing Asia and Pacific Countries, United nations Economic and Social Commission for Asia and the Pacific (UNESCAP), Working Paper 07/01 Levin, A., C. F. Lin, and J. Chu (2002). Unit root tests in panel data: asymptotic and finite-sample properties. Journal of Econometrics, 108: 1-24. Lin , H. H. ( 2011). Determinants of Remittances: Evidence from Tonga, IMF WP/11/18 Maddala, G. S., and S. Wu (1999). A comparative study of unit root tests with panel data and a new simple test. Oxford Bulletin of Economics and Statistics, 61: 631-652.

15 Newey, W. K. and K. D. West (1994). Automatic lag selection in covariance matrix estimation. Review of Economic Studies 61: 631–654. Nsiah, C. and B. Fayissa, (2011), Remittances and economic growth in Africa, Asia, and Latin American- Caribbean countries: a panel unit root and panel cointegration analysis, Journal Economics and Finance, 35, DOI: 10.1007/s12197-011-9195-6

Otieno, Jeff. (2010). Remittances to Africa to rise by 2 percent this year, The East African, October 20, 2010. Pedroni, P. (2004). Panel cointegration: Asymptotic and finite sample properties of pooled time series tests with an application to the ppp hypothesis. Econometric Theory, 20: 597–625. Pesaran, M. H., Y. Shin, and R. P. Smith (1997). Estimating long-run relationships in dynamic heterogeneous panels. DAE Working Papers Amalgamated Series 9721. Pesaran, M. H., Y. Shin, and R. P. Smith (1999). Pooled mean group estimation of dynamic heterogeneous panels. Journal of the American Statistical Association 94: 621-634. Pesaran, M., M. Hashem, and Y. Shin (1998). An autoregressive distributed lag modeling Approach to Cointegration Analysis. In Econometrics and Economic Theory in the 20 th Century: The Ragnar Frisch Centennial Symposium, edi. By Steinar Strom. Cambridge, Massachusetts, Cambridge University Press. Pesaran, M., M. Hashem, Y. Shin, and R. Smith (1999). Pooled estimation of long-run relationships in dynamic heterogeneous panels. Journal of the American Statistical Association, 94: 621-634. Ruiz-Arranz, M., (2006). Boosting economic growth. Institute of Development Studies http://www.id21.org/insights/insights60/art03.html Stahl, Charles W. and Fred Arnold. 1986. “Overseas workers’ remittances in Asian development.” International Migration Review 20(4): 899-925. Stark, O. and R. Lucas. 1988. Migration, remittances, and the family, Economic Development and Cultural Change, 36(3): 465-481. Stata 11 Hanbook (2009). StataCorp. Stata: Release 11. Statistical Software. College Station, Texas: StataCorp LP. Stock, James (1987) Asymptotic properties of least squares estimators of cointegrating vectors. Econometrica, 55. 1035-1056. Taylor, J.E. (1992). Remittances and inequality reconsidered: direct, indirect, and inter-temporal effects, Journal of policy Modeling, 14 (2):187-208. Vargas-Silva, Carlos, Shikha Jha, and Guntur Sugiyarto, (2009). Remittances in Asia: Implications for the fight against poverty and the pursuit of economic growth, ADB Economics Working Paper Series

16 Vanegas, M., Sr., and R.R. Croes (2003). Growth, development and tourism in a small economy: Evidence from Aruba. International Journal of Tourism Research, 5: 315–330. Westerlund, J. (2007). Testing for error correction in panel data. Oxford Bulletin of Economics and Statistics 69: 709–748. World Bank, 2008, Remittances and Development: Lessons from Latin America edited by Pablo Fajnzylber and J. Humberto Lopez http://siteresources.worldbank.org/INTLAC/Resources/Remittances_and_Development_Report.p df World Bank. (2006). Global Economic Prospects in 2006. Economic Implications of remittances and migration, World bank, Washington DC

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Table 1: Data description and sources Variable Description Workers' remittances and compensation of employees, received (millions of Remittances nominal US dollars).

Sources 2010 World Development Indicators Data Set

Domestic Per Capita Income (Constant 2000 US$)

2010 World Development Indicators Data Set

Foreign Per Capita Income

Main Host Country Per Capita Income (Constant 2000 US$)

2011 World Development Indicators Data Set & Jean-Christophe et al. (2010)

Financial Development

Percent of domestic credit provided by banking industry

2010 World Development Indicators Data Set

Exchange Rate

Nominal Exchange rate (Local Currency per US $)

2010 World Development Indicators Data Set

Total Migrant Stock in Foreign Countries

2010 World Development Indicators Data Set

Domestic Per Capita Income

Migrant Stock

Note: We use an unbalanced panel data set which covers the time period from 1985 to 2007 comprising of 44 countries in two regions of the world (29 from Africa and19 from the Americas).

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Table 2: Summary statistics by region Area All Regions

Variable

# of Countries 44

Remittances Domestic Per Capita Income Foreign Per Capita Income Financial Development Exchange Rate Migrant Stock Africa

Observations

Mean

Std. Dev.

Min

Max

1263 1274 1276 1250 1262 1305

661.00 1,607.77 17,475.74 43.74 228.69 270,171.80

1,990.00 1,543.79 12,732.83 31.65 686.56 414,181.40

1.00 102.29 139.97 0.00 0.00 1,777.00

27,100.00 9,469.14 38,205.94 222.64 11,786.80 2,371,277.00

731 723 725 701 720 754

489.00 714.90 10,631.53 36.96 195.60 366,851.80

1,140.00 725.16 10,196.25 33.87 282.93 490,674.20

1.00 102.29 139.97 0.00 0.00 5,747.00

9,980.00 3,763.82 38,205.94 220.12 2,142.30 2,371,277.00

532 551 551 549 542 551

897.00 2,779.35 26,481.29 52.40 272.65 137,872.80

2,740.00 1,550.11 9,797.24 26.15 994.45 216,212.50

1.00 402.01 3,966.50 5.72 0.00 1,777.00

27,100.00 9,469.14 38,205.94 222.64 11,786.80 111,283.00

25

Remittances (REM) Domestic Per Capita Income (DPC) Foreign Per Capita Income (FPC) Financial Development (FSD) Exchange Rate (ERS) Migrant Stock (MSK) Americas

19

Remittances (REM) Domestic Per Capita Income (DPC) Foreign Per Capita Income(FPC) Financial Development(FSD) Exchange Rate (ERS) Migrant Stock (MSK)

19

Table 3: Panel fully modified ordinary least squares model (PFMOLS)

DPC FPC FSD ERS MSK Φ # of countries

All Regions 3.159*** (0.455) 1.428*** (0.260) 0.734*** (0.107) 0.580*** (0.045) 0.301*** (0.058) -0.232 *** (0.037) 44

Africa 0.555** (0.252) -0.513** (0.244) 0.629*** (0.111) 0.664*** (0.066) 0.052 (0.113) -0.260*** (0.057) 25

Latin America & Caribbean -0.301 (0.285) 2.397*** (0.377) 0.281*** (0.125) 0.614*** (0.059) 0.805*** (0.188) -0.301*** (0.048) 19

Note: *, **, *** denotes significance at the 10%, 5% and the 1% levels of confidence respectively. The numbers in parenthesis are the standard errors

20 Figure 1: 2007 Top 10 Recipients of Remittances in Billions of US $

$38.67

$40.00

$32.83

$35.00 $30.00

$26.88

$25.00 $20.00

$16.30

$15.00 $9.22

$10.00

$7.66

$6.56

$6.17

$6.00

$5.50

$5.00

$0.00

Figure 2: 2007 Top 10 Per Capita Recipients of Remittances in US $ $800

$749

$731

$700 $600

$573

$500

$400 $300 $200 $100 $0

$350

$343

$321

$282

$258

$222

$221

$184

21

Figure 3: 2007 Foreign inflows to Africa in Billions of Dollars

60

51.09

50 36.84

38.25

40 30 20

10 0 Remittances

ODA

FDI

Reference for the data main host country: Dumont, Jean-Christophe, Spielvogel, Gilles, and Sarah Widmaier (2010). "International Migrants in Developed, Emerging and Developing Countries: An Extended Profile", OECD Social, Employment and Migration Working Papers No. 113.

22

Appendix List of Countries by Region Africa 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

Americas Algeria Benin Burkina Faso Cameroon Cape Verde Comoros Cote d'Ivoire Egypt, Arab Rep. Ethiopia Gambia, The Ghana Kenya Lesotho Madagascar Mali Morocco Mozambique Nigeria Rwanda Senegal South Africa Sudan Swaziland Togo Tunisia

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

Belize Bolivia Brazil Colombia Costa Rica Dominica Dominican Republic Ecuador El Salvador Grenada Haiti Honduras Jamaica Mexico Panama Paraguay St. Kitts and Nevis St. Lucia St. Vincent and the Grenadines