The Impact of Risk and Uncertainty on Remittances 
into Latin American Economies 

Bien Solomon 

Grand Valley State University • Grand Rapids , MI 

Abstract 

This study investigates the effects of exchange rate uncertainty and political 

risk, after controlling for the conventional macroeconomic detenninants, on remit-

tances transfers into eight Latin American countries during the period of 1990-2006. 

The results suggest that an increase in exchange rate uncertainty reduces remittances 

flows into these countries. Furthennore, an increase in political risk seems to have 

a negative but statistically insignificant impact on remittances transfers. Based on 

the findings of this paper, we can say that governments of the remittance receiving 

countries can influence the inflow of remittances by means of adopting appropriate 

macroeconomic policies to reduce exchange rate uncertainty and also by improving 

their political environments. 

Introduction 

Remittances have become an increasingly important and fast growing source 

of external finance for many developing countries.) By 2005, the total remittances 

inflows into developing countries reached $167 billion. This amount had more than 

doubled from its value of$58 billion in 1995 (United Nations Habitat, 2006). The in-

crease in remittances flows into developing regions is welcomed because remittances 

have a potentially significant impact on the recipient country's economy. First, remit-

tances are a more stable source of external finance as opposed to capital flows which 

tend to rise during favorable economic cycles and fall during less favorable ones. 

This acyclical nature of remittances exerts a stabilizing influence, and thus helps 

insulate vulnerable countries from economic shocks (Ratha, 2003; Global Economic 

Prospects, 2006). Moreover, remittances increase the recipient country's foreign ex-

change reserves and promote economic growth if households use remittances for in-

vestment. If they are used for consumption, they can also generate positive multiplier 

effects, offsetting some of the output losses that a developing country may suffer 

from emigration of its highly skilled workers (Ratha, 2003). 

By 2005, Latin America and the Caribbean (LAC) were the largest remit-

tances destination in the world, with inflows around $53.6 billion . This amount 

exceeded, for the third consecutive year, the combined flows of all net Foreign Di-



100 Journal of Business Strategies 

rect Investment (FDI) and Official Development Assistance (ODA) to the region 

(Inter-American Development Bank, 2006). Because of their increasing volume and 

their potential to reduce poverty and enhance economic growth, remittances are 

receiving growing attention from policymakers in the developing countries of Latin 

America. 

There is a wide range of important issues related to remittances. In this study, 

we focus on a very important issue, namely, the determinants of remittances to 

Latin American countries. Assuming that remittances have a positive effect on the 

recipient economy, what are the determinants of remittances into Latin American 

economies? The remittances literature is divided into two broad categories. The 

first category of determinants deals with microeconomic determinants of remit-

tances such as the social and demographic characteristics of migrants and their 

families, while the second category considers macroeconomic variables of the host 

(sending) as well as home (receiving) countries. Our study fits into the second cat-

egory as we investigate the macroeconomic determinants of remittances into nine 

Latin American countries. 2 

Generally, studies that investigate the determinants of remittances assume 

that migrants are risk neutral in their preferences with respect to risk and return 

in that they do not include risk variables in their regressions (Higgins et aI., 2004). 

However, remittances for investment would be influenced by risk and return consid-

erations. Ratha (2003) reviews cross-country studies on remittances and reveals that 

remittances are affected by the investment climate in recipient countries in the same 

manner that capital flows are; though to a lesser degree. Therefore, determinants of 

remittances in an investing framework would have to include rates of return to in-

vestment and the risk of investing in the home (receiving) country such as political 

risk and/or exchange rate uncertainty. However, to our knowledge, only one study 

(Higgins et aI., 2004) has considered risk variables as determinants of remittances 

and no study has used the rate of return to investment measure that we use in this 

study. 3 We employ a measure of political risk that captures multiple facets of risk 

faced by investors in the Latin American countries. We use the political risk index 

from the International Country Risk Guide (ICRG) that measures the combined ef-

fects of political and institutional instabilities faced by investors. We also include a 

GARCH measure of exchange rate uncertainty to investigate the exchange rate risk 

faced by investors. These risk variables are included in addition to the traditional 

determinants used by other studies. Thus, this paper contributes to the literature 

by filling a long-standing void in exploring the links between remittances, risk and 

return in Latin America. 



Volume 26, Number 1 101 

The rest of the paper is organized as follows. Section 2 discusses some basic 

facts about remittances inflows into Latin American countries and provides a brief 

literature review. The sources of data and the variables used in the study are dis-

cussed in Section 3. Section 4 outlines the empirical methodologies and discusses the 

empirical findings. Conclusions and policy implications are included in Section 5. 

Facts About Remittances to Latin America and Brief 
Literature Review 

Facts about Remittances to Latin America 

In 1995, the share of remittances going to Latin America and the Caribbean 

accounted for 23.2% of the total world remittances, but by the year 2005 this share 

had increased to 31% ,making it the largest remittance recipient region in the world. 

In dollar terms, LAC received about $53.6 billion in remittance transfers in 2005. 

Out of the $53.6 billion sent, an estimated $20 billion were sent to Mexico, nearly 

$6.4 billion were destined to Brazil, and about $4.1 billion were sent to Colombia 

(Inter-American Development Bank, 2006). In most Latin American countries, re-

mittances have exceeded official development assistance and other capital inflows 

such as FDI (see Table 1). 

Table 1 

Remittances (for 2003) Relative to Foreign Direct Investment (FDI) and GDP, 

and Remittances per Capita 

Country Remi % FOI Remi%GOP Remi. Per Capita 

Argentina 15% 0 .09% 6.42 

Bolivia 835% 1.05% 10.73 

Brazil 46% 0.33% 11.43 

Colombia 111% 3.40% 68.64 

Mexico 178% 2.26% 130.96 

Nicaragua 270% 10.44% 80.87 

Peru 117% 1.49% 31.68 

Venezuela 18% 0.5% 10.23 

Source : Inter-American Development Bank (2006) 

Some key factors could explain the tremendous growth seen in remittances 

inflows into Latin American countries over the last decade. One of the most impor-



102 Journal of Business Strategies 

tant reasons has been the increase in emigration of workers from Latin American 

countries to regions with demand for labor such as the u.s. and Western Europe. 
The Inter American Development Bank estimates that in 2005 over 25 million Latin 

American born adults were living outside their countries of origin. Out of these 25 

million migrants, approximately 65% send money home on a regular basis. The 

amount of money they send typically ranges between $100 and $300 a month (lnter-

American Development Bank, 2006). 

The main source of remittances to Latin America is the U.S. as about 75% 

($40 billion) of Latin American remittances originate in the U.S. The next largest 

source of remittances is Western Europe with a share of almost 15% (about $7.5 

billion). 

Brief Literature Review 

There is a wide range of important issues related to remittances. In this study, 

we focus on the macroeconomic determinants of remittances to Latin American 

countries. However, much of the remittances literature has focused on the micro-

economic determinants of remittances (for example, see Lucas & Stark, 1985; Rus-

sell, 1986; Djajic, 1989; Hoddinot, 1992; Durand et al., 1996; Ilahi & Jafarey, 1999; 

Agarwal & Horowitz, 2002). The studies that have recognized the importance of the 

macroeconomic determinants of remittances include Straubharr (1986), Faini (1994), 

EI-Sakka and McNabb (1999), Chami et al., (2003), Higgins et al., (2004), and Var-

gas-Silva and Huang (2006). These studies investigate the impacts of home (receiv-

ing) and host (sending) country variables such as inflation, income, exchange rates, 

wage levels, interest rates, and interest rate differentials on remittances flows. Studies 

have found mixed evidence on the impacts of these variables on remittances flows. 

For example, a higher host country interest rate compared to the home coun-

try rate (a high premium) is expected to discourage remittances flows. However, 

Straubhaar (1986), using data of remittances from Germany to Turkey, finds that 

interest rate differentials between the host and home countries have no effect on 

remittance flows. Similarly, Elbadawi and Rocha (1992), using data from Western 

Europe and North Africa, find the interest rate differential to have no significant 

impact on remittances. In contrast, Katselli and Glytsos (1986), and EI-Sakka and 

McNabb (1999) argue that interest rates and interest rate differentials significantly 

affect remittances inflows into Greece and Egypt respectively. 

The real exchange rate (XR) also has the potential to affect remittances. 

Many studies have investigated the impact of exchange rates on remittances. These 



Volume 26, Number 1 103 

studies have found exchange rates to be important in explaining remittances flows 

(see Chandavarkar, 1980; Amuedo-Dorantes & Pozo, 2004; Higgins et ai., 2004). 

Most studies expect the depreciation of the real exchange rate to encourage the flow 

of remittances from the host to home country (see Higgins et ai., 2004). Interset-

ingly, Amuedo-Dorantes and Pozo (2004) also find that surges in workers' remit-

tances may contribute to real exchange rate appreciation . Furthermore, Higgins et 

al. (2004) show that exchange rate volatility (a measure of risk) is an important 

determinant of remittances. 

The macroeconomic variables mentioned above have also been used to test 

the altruistic versus self-interest motive for remitting. If downturns in the receiving 

economy prompt workers to increase remittances to their home countries, then their 

motives can be thought of as altruistic. If, on the other hand, immigrant workers are 

self-interested, remittances will respond positively to economic conditions in the 

receiving country. Faini (1994) and Glytsos (1997), using income to measure the 

economic condition of the receiving country, find that workers motives are altruistic 

because downturns in the home economy prompt workers to increase the amount 

they remit. In contrast, Higgins et al. (2004) find evidence for the investment or self-

interest hypothesis since they find favorable economic conditions at home increase 

remittances inflows into the home country. This paper investigates if risk and return 

variables, in addition to the conventional macroeconomic determinants, have a role 

in determining remittances flows into Latin American countries. 

Data Description 

Our analysis covers nine Latin American countries between 1990 through 

2006.4 The variables used in this study are annual in frequency; however, the ex-

change rates used to generate the conditional variances are monthly. 5 The data 

sources for our variables are the World Development Indicators (WDI), the Inter-

national Financial Statistics (IFS) CD-ROM, the U.S. Census data, the Immigra-

tion and Naturalization Services (INS) statistical yearbook, and the International 

Country Risk Guide (ICRG). All variables except the political risk indicators, were 

retrieved from the World Bank's World Development Indicators (WDI) and the In-

ternational Financial Statistics (IFS) CD-ROM. The political risk indicators were 

taken from the ICRG dataset. 

It should be noted that some problems exist in the measurement of remit-

tances. One of the problems is that there is no consensus on the boundaries of the 

phenomenon under study. That is, should only workers' remittances be counted, 



104 Journal of Business Strategies 

or should compensation of employees and migrant transfers be included as well 

(Ratha, 2003)? In this study, we use the definition of migrant remittances used by 

The World Bank, which is the sum of workers' remittances, compensation of em-

ployees, and migrant transfers. 

Another problem arises because many types of informal remittances flows 

go unrecorded due to weakness in data collection (Jongwanich, 2007). For exam-

ple, money transfers through informal channels such as family members are rarely 

documented. If remittances sent through informal channels are included in official 

remittances data, total remittances could be as much as 50% higher than the official 

record (World Bank, 2006). However, the collection of remittances data is improv-

ing. For example, Ratha (2003) shows that countries such as Mexico have improved 

their system of unrecorded portion of remittances which has significantly increased 

the remittances statistics. 

Another potential problem arises because the available data on remittance 

flows does not identify the source (host) country of these flows. However, remit-

tances literature identifies macroeconomic variables in the sending as well as the 

receiving country as being important determinants of remittances. To incorporate 

both the sending and receiving countries' macroeconomic variables, we use data 

from Latin American countries since 75% of Latin American remittances are sent 

from the u.s. For this reason, for Latin American countries, it is reasonable to as-
sume that the error is relatively small. 

In order to investigate the determinants of remittances into Latin American 

countries, we use the following variables:, the share of remittances in GOP (REMG), 

the stock of immigrants in the US. (for each Latin American country) (IMMI), per 

capita income of each of the nine Latin American countries (Y), median Hispanic 

income in the U.S. (MHI), real exchange rate (XR), rate of return to investment 

(RR), exchange rate uncertainty (GARCH), and political risk (POLRISK).6 

The median Hispanic income in the u.s. (MHI) is used to measure economic 
well being of migrants in the host (sending) country.7 An increase in the income of 

migrants (i.e. an improvement in their well-being) is expected to increase remit-

tances sent by these migrants to their native countries. Other studies have used the 

host country's GOP as well as the unemployment rate of the host country in order to 

measure the economic well being of migrants in the sending country. 

The per capita incomes (Y) of the nine Latin American countries are used 

to measure the economic well-being of the home (receiving) countries. The home 

country's GDP per capita may affect remittances either positively or negatively. 

However, the stock of immigrants (IMMI) in the host country is expected to have 



Volume 26, Number 1 105 

a positive relationship with remittances flows, that is, an increase in the number of 

immigrants in the host country will increase the money sent back home. The real 

exchange rate (XR) also has the potential to affect remittances. The depreciation of 

the real exchange rate is expected to encourage the flow of remittances from the host 

. to home country (Higgins et ai., 2004). Some studies highlight the fact that some 

governments in developing countries have devalued the exchange rates in order to 

encourage remittances inflows (Wahba, 1991). 

In addition to the variables mentioned above, measures for rate of return 

(RR) to investment, macroeconomic uncertainty (GARCH), and political risk 

(POLRISK) are included in our regressions. Most studies take account of the RR by 

using the interest rate differentials between the host and home countries. However, 

we take account of RR by using log ofthe inverse of the real GOP per capita. 8 This 

substitution is made since market interest rates for most of the selected years are not 

available. In addition, the reported interest rates in many of these countries do not 

reflect true asset returns (Higgins et ai., 2004). Therefore we use our measure of the 

rate of return to investment. This variable is expected to have a positive relationship 

with remittances inflows if the motive to remit is for investment. On the other hand, 

GARCH measures of the real exchange rates are used to proxy exchange rate uncer-

tainty.9 Increases in exchange risk will decrease the level of remittances assuming 

that a part of these flows in fact are private investment flows made by immigrants 

(Higgins et aI., 2004). 

The overall political risk indices (POLRISK) for each home country are used 

to proxy the political risk prevailing in the countries. The ICRG provides a compos-

ite political risk index (for each country) that is made up of particular components 

of political instability as well as home country institutional quality. The unpredict-

ability and volatility in the political environment of the home country increases the 

perceived risk and uncertainty experienced by the migrant. As a result, a negative 

relationship between political risk and remittances inflows is to be expected. 

Estimation Methodology and Results 

Exchange Rate Uncertainty Specification and Results 

The ARCH/GARCH measure of uncertainty involves obtaining the variance 

of the unpredictable part of the series. Unlike the ad-hoc measures of uncertainty 

such as rolling variances, the ARCH/GARCH approach is obtained on the basis of an 

estimated econometric model. This method captures volatility in each period more 



106 Journal of Business Strategies 

accurately. The ARCH model characterizes the distribution of the stochastic error 

conditional on the realized values of the set of variables that may include lagged 

values of the conditional variance. The generalized ARCH model, the GARCH (p, 

q) model, is specified as follows: 

Yt = f(x t; 8) + et e/ 'I't.1 ~D(O, h/ ) (4.1.1) 

q P 

h 1 = a + ~a.E l + ~8h 1 (4.1.2) 
I 0 ~ I I -I k.J , I-I 

i= 1 ;= 1 

where f (x
t
; 8) refers to the conditional mean, x

t 
is a vector of explanatory variables 

that may include lagged y,'s, 8 is a Mxl vector of parameters, 'l't-I is the information 

set that contains all the information available through time t-l , and e
t 

is the error 

term which follows, conditional on 'l't-I' a D-distribution. That is, the conditional 

errors have zero mean and time varying variance, h/- The conditional variance 
follows a GARCH process as in (4_1.2). The conditional variance, h/ , the proxy for 
uncertainty, is the one period ahead forecast variance based on the past information. 

It is a function of three terms: the mean level of volatility a o' the ARCH term £,./ 
and the GARCH term h 1 . 10. 11 

,-I 

To generate measures of uncertainty, monthly real exchange rates for each 

of the countries were used. Before estimation of our ARCH/GARCH models, we 

conducted some preliminary data analysis such as checking for the presence of unit 

roots. The results from the Augmented Dickey Fuller (ADF) Test for unit roots sug-

gest that the log of the real exchange rates for all the countries under consideration 

are l(l) processes . That is, the real exchange rate for each country has a unit root 

in levels while they are difference stationary. As a result, to ensure the stationarity 

of our variables, we use the first differences to fit ARCH/GARCH models and to 

generate the conditional variances. 

Argentina, Boliva, Colombia, Nicaragua, and Venezuela had fixed exchange 

rate regimes during a portion of our period of study. Therefore, in order to account 

for this fact , we include dummy variables in the GARCH estimations. The dummy 

variable for each country is defined as I if the country had a fixed exchange rate 

regime during the period of study, and 0 otherwise. 

Table 2 presents the coefficients of the GARCH (p, q) estimation. As can be 

seen from Table 2, the coefficients of the GARCH (p, q) have the expected theoreti-

cal signs. Figure 1 shows a plot of exchange rate uncertainty (h,) for each country in 

our study. Once the monthly exchange rate uncertainty measures (h,) are obtained, 



Volume 26, Number 1 107 

they are aggregated to produce annual series, and included into our regressions. 

Table 2 

ARCH/GARCH Models of the Log Difference of Exchange Rates (Monthly) 

AR MA 
Countries Process Process C ~ A2 ~1 

Argentina AR(8) MA(2) 0.0019 1.0025 
(0.0257)*** 

Bolivia AR(1) MA(1) 0.0005 0.3610 0.3184 
(0.0010) (0.0431) *** (0.0950)*** 

Brazil AR(3) 0.0182 0.4123 
(0.0082)*** (0.1268)*** 

Colombia AR(3) 0.0012 1.0430 
(0.0001)*** (0.2001)*** 

Chile AR(3) 0.0008 0.1863 0.0957 
(0.0008) (0.4855)*** (0.1449)*** 

Mexico AR(3) 0.1900 0.2592 0.5799 
(0.0035)*** (0.0385)*** (0.0514)*** 

Nicaragua AR(3) 0.0101 0.1239 0.6000 
(0.0026)*** (0.0031) *** (0.0083)*** 

Peru AR(3) 0.0100 0.4452 0.7181 
(0.0005)*** (0.0584)*** (0.0119) *** 

Venezuela AR(3) 0.0047 1.0001 
(0.0049)*** (0.0037)*** 



108 Jour nal of Business Strategies 

Figure 1 

Conditional Variances of the Exchange Rates 
05 ,----- - ------ --, '.0.,,------- - - ----- ---, 

OB 

os 

02 
02 

00 
·.2 

"2 
IE .. '" " .. .. .. OJ .. .. (Ii 

[ --~~~.wa 

." 

." 
00; 

.ro 

.... 

.. " 
0; .. 90 " .. .. " ro .. .. .. 

1- Brad CodiortII ~~ 
0 " .... 
0.'" 

0.003 

0.00 

.. '" ."" 

.., ... 
0.(1)1 

.., .. 

.... ,000 .. .. 90 92 .. .. .. ro .. .. '" 
CcDrtiII ~1cnII V..w-o. ] 

2. '.2,---------- --- - - - -, 

, .. ' .0 
LO .. 
05 '5 

o. ~~,~ 0 .. 
.. , .. .. 90 " .. .. .. ro '" .. .. 

~O::n::Ii:nllVIfWI: . -1 

•• 

'" 
.2 

., 
0.0 

.. , 
II! ... III 92 .. .. .. <Xl '" .. 06 

~OTdt~V""" .. =:1 



Volume 26, Number 1 

Estimation Methodology and Results for the Determinants of 
Remittances 

109 

In this paper, the Arellano-Bond dynamic panel GMM estimator is the meth-

od of choice. Using this estimator has many advantages. First, it includes the lagged 

dependent variable as an additional regressor and therefore addresses the problem 

of autocorrelation of the residuals. In addition, it deals with the fact that some of the 

control variables are endogenous. For example, remittances may increase the home 

country's capital stock and boost GOP growth rates in addition to boosting GOP per 

capita. As a result, in order to take the endogeneity issue into account, we employ 

this instrumental variable type approach, namely Arellano-Bond dynamic panel 

generalized method of moments (GMM). 

One of the basic assumptions for applying the Arellano-Bond estimator is 

no second-order serial correlation in the residuals of the differenced specification. 

Therefore, before we employ the Arellano-Bond GMM dynamic panel estimator, 

we have to test for second order serial correlation of our residuals. In addition, the 

overall appropriateness of the instruments is verified by the Sargan test of over-

identifying restrictions. 

Before estimation we also check for the stationarity properties of our vari-

ables. A Fisher type test for panel unit root is first applied to examine the null 

of a unit root in the variables under consideration. The Fisher test combines the 

p-values of unit root tests for each cross section i as proposed by Maddala & Wu 

(1999) and Choi (2001). Based on the p-values of individual unit root tests, Fisher's 

test assumes that all series are non-stationary under the null hypothesis against the 

alternative that at least one series in the panel is stationary. The results suggest that 

4 of the variables (namely, Y, RR, GARCH, and IMMI) are 1(1) processes. That is, 

these variables have a unit root in levels while they are difference stationary.12 As a 

result, to ensure the stationarity of our variables, we use the first differences in our 

regression. All the remaining variables are 1(0) processes. The results are reported 

in Table 3. 

Our model specification uses remittances share in GOP as the dependent 

variable. All the variables included are in real terms and, therefore, we do not in-

clude the home and host country inflation rates. Thus, the model to be estimated is 

as follows: 

REMG it = ~o + ~lMHIit_ l + ~2LlYit_! + ~3LlGARCHit_! + ~4LlRRit_! + ~5XRit_1 + 
P

6
POLRISKit _! + PflIMMl it _! + Cjt (4.2.1) 



110 Journal of Business Strategies 

where, is the country specific fixed-effect. The right-hand variables are as defined 

in Section 3.13 

Table 3 

Fisher Test for panel unit root 

Variable 

REMG 

Median Hispanic Income (MHI) 

Exchange Rates (XR) 

GOP per capita (Y) 

Rate of Return to Investment (RR) 

Uncertainty (GARCH) 

Political Risk (POLRISK) 

Immigrant Stock (IMMI) 

Notes : Ho: Series non-stationary 

t Statistic 
69.2808 

79.7396 

68.4213 

0.5272 

15.9693 

16.2994 

30.3325 

19.4291 

p-value 

0.0000 

0.0000 

0.0000 

1.0000 

0.5947 

0.5717 

0.0343 

0.4490 

Tables 4 shows the Arellano-Bond dynamic panel GMM estimation results 

with robust standard errors. This table shows that all of the variables have their ex-

pected signs and are mostly significant. For example, the coefficient for growth of 

the median Hispanic income (MHI), which measures the economic well-being of a 

migrant, is significant. This result is to be expected because a migrant's income is 

an important determinant for the money they send back home. The result implies 

that as the income of migrants in the U.S. increases; they are more likely to increase 

the remittances they send to their home countries. This is supportive of previous 

studies that show remittances respond directly to the ability of the remitter to send 

earnings home (Loser et aI., 2006). For comparison with other studies, we used the 

U.S. GOP as well as U.S. unemployment rate to measure the economic well being of 

migrants in the U.S. The results, though not significant, show that U.S. unemploy-

ment is negatively related to remittances inflows into Latin American countries. 

This is consistent with previous studies such as Higgins et al. (2007). 



Volume 26, Number 1 

Table 4 

Arellano-Bond Dynamic Panel GMM Estimation Results 

Using Remittances per Immigrant 

Dependent Variable: Remittances per GDP 

Variable (1) 

Lagged Rem ittances per GOP 0.4476 
(0.0678)*** 

Median Hispanic Income (MHI) 0 .7795 
(0.2182) *** 

Exchange Rates (XR) -0.0088 
(0.0210) 

GOP per capita (Y) 0.0131 
(0.0101) 

Rate of Return to Investment (RR) 0.1301 
(0 .3107) 

Uncertainty (GARCH) -2 .0028 
(0.8741 )*** 

Political Risk (POLRISK) -0.2586 
(0.1015)*** 

Immigrant Stock (IMMI) 0.0089 
(0.0051 )* 

Observations 144 

Countries 8 

Sargan Test 0.2724 

Second Order Serial Correlation Test 0.1590 

111 

Notes : Standard Errors are in parenthesis and ***, ** and * denote significance at 0.01 , 
0.05 , and 0.10 levels respectively. The null hypothesis for the Sargan test is that the in-
struments are valid (p-values are reported above) . The null- hypothesis for the second 
order serial correlation test is that the errors don't exhibit second order serial correlation 
(reported above are the p-values) 

The estimated coefficient of the growth of the GDP per capita (Y) of the 

home countries indicates that this variable is positively (but not significantly) re-

lated to remittances. The result suggests that a higher growth of income in home 

country increases remittances sent home by immigrants. That is, remittances in-

crease when economic activity in the home country accelerates and they decrease 

when economic conditions worsen. This result is contrary to the commonly held 

belief that remittances are used to smooth out fluctuations in economic activity. In 

our case, immigrants choose to keep more of their money in the host country during 



112 Journal of Business Strategies 

periods of economic trouble in the home country due to a possible loss of confidence 

in their country's economic situation. 

In addition, a change in the rate of return to investment is positively related 

to remittances inflows into the selected Latin American countries. A few studies 

have attributed these results to the investment motive to remit. A high rate of return 

to investment and high income in the home country would both encourage more 

investment (see, for example, Higgins et aI., 2004). This in turn would increase re-

mittances for investment purposes. However, the estimated coefficient is not statis-

tically significant. Furthermore, as expected, the growth of the immigrants (IMMI) 

in the host country shows an increase in the money sent back home. 

The coefficient for real exchange rate return (XR) is not significant. How-

ever, it indicates that remittances tend to increase when the exchange rate depreci-

ates. This result shows that remitters choose to send more to their home country 

when the currency oftheir home country depreciates. This is because exchange rate 

depreciations permit the remitter to buy more home currency with a given level of 

host currency thereby getting 'more credit for the transfer' (Amuedo-Dorantes & 

Pozo, 2007; Higgins et aI., 2004; Wahba, 1991). 

One of the main variables of interest, namely, the exchange rate uncertainty 

(GARCH) is significant. This result indicates that as exchange rate volatility in-

creases, the level of remittances per immigrant decreases. The result supports the 

hypothesis that uncertainty in the exchange rate lowers the level of remittances 

sent for investment purposes (for similar results, see Higgins et aI., 2004). The mi-

grant will ignore investing opportunities in the home country if he/she expects a 

high variability of the exchange rate. In addition, exchange rate volatility would re-

duce remittances because exchange rate volatility decreases confidence in the home 

country's financial system. 

Similarly, the political risk (POLRISK) is found to be negatively and sig-

nificantly related to remittances inflows. This result shows that when the political 

situation in the home country worsens remittances flow decrease. Immigrants may 

choose to keep more of their money in the host country during periods of political 

turmoil in the home country due to lack of belief in their country's political sys-

tem. 

Concluding Remarks 

The Latin America and the Caribbean region is the largest remittances des-

tination in the world. By 2005, remittances inflows exceeded the combined flows 



Volume 26, Number 1 113 

of all net FDI to the Latin American countries (Inter-American Development Bank, 

2006). Because of their increasing volume and their potential to reduce poverty, 

remittances are and should be receiving growing attention from policymakers in 

the region. There is a wide range of important issues related to remittances. In this 

study, we focus on investigating the macroeconomic determinants of remittances to 

nine Latin American countries. 

The empirical evidence presented in this paper shows that for the period of 

1990-2006, macroeconomic variables of the host as well as home countries affected 

remittances inflows. Host country variables such as median Hispanic income in 

the U.S. significantly affected remittances inflows. In addition, the results show 

that home country risk variable such as exchange rate uncertainty is an important 

determinant of remittances to Latin American countries. An increase in political 

risk seems to have a negative but insignificant impact on remittances. Based on the 

findings of this paper, we can say that governments of the home countries can influ-

ence the inflow of remittances by stabilizing their currency and by improving their 

institutional and political environments. Because government institutions and po-

litical instability matter for the manner in which remittances are used, governments 

should try to encourage remittances to be utilized for productive investment and 

thereby economic growth. The best way for these countries' governments to ensure 

that remittances contribute to positive economic growth is to foster better quality of 

institutions, political stability, and stable currency. 

Notes 

I. Remittances are the portion of international migrant workers' earnings sent back 

from the country of employment to the country of origin. World Bank defines inter-

national flows of remittances as the sum of three items, namely, worker remittances, 

income (compensation) of migrant workers, and migrant savings (the net wealth of 

migrants when they return home). 

2. The countries included in this study are: Argentina, Bolivia, Brazil, Chile, Co-

lombia, Mexico, Nicaragua, Peru, and Venezuela. These countries were chosen due 

to data availability. 

3. Most studies take account of the return to investment by using the interest rate 

differentials between the host and home countries. In this study, we use the inverse 

of the log of GOP per capita to account for the rate of return to investment. For 

an explanation on how to construct this rate of return to investment variable, see 

Aseidu, 2002. This substitution is made since market interest rates for most of the 



114 Journal of Business Strategies 

selected years are not available. In addition, the reported interest rates in many of 

these countries do not reflect true asset returns (Higgins et ai, 2004). 

4. The selection of the LAC was based on data availability. 

5. We aggregate the monthly conditional variances into annual frequency to obtain 

our annual volatility measures. 

6. The stock of immigrants in the US. for each of the sample country was con-

structed from US. Census data and annual data on US. immigration flows from 

each of the sample countries. 

7. Most studies use US. GDP to measure the economic well being of the migrants. 

However, MHI more closely maps the US. income of this group. MHI measures 

income of Hispanic households (migrant and US. nationals) in the US (Loser et ai, 

2006). 

8. For explanations of how to construct this variable see Asiedu (2002). 

9. We use the real rather than the nominal exchange rate, since uncertain price levels 

as well as exchange rates are relevant for long-term investments. All real exchange 

rates used in this chapter are bilateral exchange rates vis-a-vis the U.S. dollar. The 

real exchange rates are calculated by multiplying the ratio of prices in the United 

States relative to national prices by the nominal exchange rates. Thus an increase in 

the real exchange rate index would indicate an appreciation of the US. dollar. 

10. The ARCH term is the lag of squared errors from the mean equation or news 

about volatility from the previous period. 

11. To ensure a well-defined process, all the parameters in the infinite order AR 

representation must lie outside the unit circle. For a GARCH (1,1) process this will 

be the case if a
l 

and 01 are non-negative. It is also required that a
l 
+ 01 > 1 for co-

variance stationarity. 

12. The results for the differenced variables' unit root tests are available upon re-

quest. 

13. The variables with the presence of unit roots have been first-differenced. There-

fore they are in growth terms. 



Volume 26, Number 1 115 

References 
Agarwal, R., & Horowitz, A. (2002). Are international remittances altruism or insur-

ance? Evidence from Guyanna using multiple-migrant households. World De-
velopment, 30, 2033-2044. 

Amuedo-Dorantes, c., & Pozo, S. (2007). Remittances and the macro economy: The 
case of small island developing states. San Diego State University, Department 
of Economics. Working Papers 0018. 

Amuedo-Dorantes, C., & Pozo, S. (2004). Worker's remittances and the real ex-
change rate: A paradox of gifts. World Development, 32, 1407-1417. 

Asiedu, E. (2002). On the determinants of foreign direct investment to developing 
countries: Is Africa different? World Development, 30(1), 107-119. 

Chami, R., Fullenkamp, c., & Jahjah, S. (2003). Are immigrant remittance flows a 
source of capital for development? IMF Working Paper 03/189. 

Chandavarkar, A. G. (1980). Use of migrants' remittances in labor-exporting coun-
tries. Finance and Development, 17,6-39. 

Choi, 1. (2001). Unit root tests for panel data. Journal of International Money and 
Finance, 20(2), 249-272. 

Djajic, S. (1989). Migrants in a guest-worker system: A utility maximizing approach. 
Journal of Development Economics, 31,327-339. 

Durand, J., Kandell, w., Parrado, E., & Massey, D. S. (1996). International migra-
tion and development in Mexican communities. Demography, 33(2), 249-64. 

Elbadawi, I., & Rocha, R. (1992). Determinants of expatriate workers' remittances 
in North Africa and Europe. World Bank Working Paper Series 1038. 

El-Sakka, M., & McNabb, R. (1999). The macroeconomic determinants of migrant 
remittances. World Development, 27, 1493-1502. 

Faini, R. (1994). Workers remittances and the real exchange rate: A quantitative 
framework. Journal of Population Economics, 7,235-245. 

Global Economics Prospects (2006). 

Glytsos, N. P. (1997). Remitting behavior of "temporary" and "permanent" migrants: 
The case of Greeks in Germany and Australia. Labour, 11, 409-435. 

Hoddinott, J. (1992). Modeling remittance flows to Kenya. Journal of African Econ-
omies, 1, 206-232. 

Higgins, M. L., Hysenbegasi, A., & Pozo, S. (2004). Exchange-rate uncertainty and 
workers' remittances. Applied Financial Economics, 14, 403-411. 



116 Journal of Business Strategies 

Ilahi, N ., & Jafarey, S. (1999). Guestworker migration, remittances and the extended 
family: Evidence from Pakistan. Journal of Development Economics, 2,485-512. 

Inter-American Development Bank (2006). 

International Country Risk Guide (ICRG) (2006). 

Jongwanich, J. (2007). Workers' remittances, economic growth and poverty in devel-
oping Asia and Pacific countries. UNESCAP Working Paper (WP/07/01). 

Katseli, L. T., & Glytsos, N. (1986). Theoretical and empirical determinants of In-
ternational Labour Mobility: A Greek-German perspective. Centre for Econom-
ic Policy Research Working Paper 148. 

Loser, C., Lockwood, C., Minston, A., & Balcazar, L. (2006). The macro-economic 
impact of remittances in Latin America: Dutch disease or Latin cure? Inter-
American Dialogue. 

Lucas, R., & Stark, O. (1985). Motivations to remit: Evidence from Botswana. The 
Journal of Political Economy, 93,901-918. 

Maddala, G., & Wu, S. (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. 

Ratha, D. (2003). Worker's remittances: An important and stable source of external 
development finance. Global Development Finance, 157-172. 

Russell, S. (1986). Remittances from international migration: A review in perspec-
tive. World Development, 14,677-696. 

Straubhaar, T. (1986). The determinants of workers' remittances: The case of Tur-
key. Weltwirtschaflliches Archiv, 122, 728-740. 

United Nations Habitat (2006). 

Vargas-Silva, c., & Huang, P. (2006). Macroeconomic determinants of workers' re-
mittances: Host versus home country's economic conditions. Journal of 1nter-
national Trade & Economic Development, Taylor and Francis Journals, 15( 1), 
81-99. 

Wahba, S. (1991). What determines workers' remittances? A framework for exam-
ining flows from migrant workers, with a focus on Egypt's experience in the 
1980s. Finance & Development, 28(4),41-4. 

World Bank (2006). 



Volume 26, Number 1 117 

Biographical Sketch of Author 

Bien Solomon was born in Addis Ababa, Ethiopia and started her college 

education at Addis Ababa University in 1996-97. At the end of her first year, she 

transferred to Lawrence University in Appleton, WI where she received her B.A. 

in 2000. She received her M.A. in Economics in 2004 and her Ph.D. in economics 

in 2007 from Western Michigan University. Currently, she has a visiting position at 

Grand Valley State University. 



118 Journal of Business Strategies 


	The Impact of Risk and Uncertainty on Remittances into Latin American Economies