WP/17/144

Migration and Remittances in Latin America and

the Caribbean: Engines of Growth and
Macroeconomic Stabilizers?

by Kimberly Beaton, Svetlana Cerovic, Misael Galdamez, Metodij Hadzi-Vaskov, Franz Loyola,
Zsoka Koczan, Bogdan Lissovolik, Jan Kees Martijn, Yulia Ustyugova and Joyce Wong

IMF Working Papers describe research in progress by the author(s) and are published
to elicit comments and to encourage debate. The views expressed in IMF Working Papers
are those of the author(s) and do not necessarily represent the views of the IMF, its
Executive Board, or IMF management.
 2

© 2017 International Monetary Fund WP/17/144

IMF Working Paper

Western Hemisphere Department

Migration and Remittances in Latin America and the Caribbean: Engines of

Growth and Macroeconomic Stabilizers?

Prepared by Kimberly Beaton, Svetlana Cerovic, Misael Galdamez, Metodij

Hadzi-Vaskov, Franz Loyola, Zsoka Koczan, Bogdan Lissovolik, Jan Kees
Martijn, Yulia Ustyugova and Joyce Wong1
Authorized for distribution by Krishna Srinivasan

June 2017

IMF Working Papers describe research in progress by the author(s) and are published to
elicit comments and to encourage debate. The views expressed in IMF Working Papers are
those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board,
or IMF management.

Abstract

Outward migration has been an important phenomenon for countries in Latin American
and the Caribbean (LAC), particularly those in Central America and the Caribbean. This
paper examines recent trends in outward migration from and remittances to LAC, as well
as their costs and benefits. For the home country, the negative impact from emigration on
labor resources and productivity seems to outweigh growth gains from remittances,
notably for the Caribbean. However, given emigration, remittance flows play key
financing and stabilizing roles in Central America and the Caribbean. They facilitate
private consumption smoothing, support financial sector stability and fiscal revenues, and
help reduce poverty and inequality, without strong evidence for harmful competitiveness
effects through shifts in the real exchange rate.

1 The project team on migration and remittances of the IMF’s Western Hemisphere Department, led by Jan Kees Martijn,
under the guidance of Krishna Srinivasan. The team gratefully acknowledges conversations with Ralph Chami, Nadeem
Ilahi, Daria Zakharova, Dilip Rathna, Sonia Plaza, and Supriyo De, as well as helpful comments and suggestions (including
on an accompanying Chapter of the Spring 2017 Regional Economic Outlook for the Western Hemisphere) from Alejandro
Werner, Valerie Cerra and many other IMF colleagues. We would like to thank Benjamin Hunt and Keiko Honjo in the
IMF’s Research Department for providing the FSGM simulation results, and Reza Yousefi and Serhan Cevik in the IMF’s
Fiscal Affairs Department for their analysis, summarized in Box 4 of this paper. We also thank Ke Wang for her
participation in our team at the start of our project.
 3

JEL Classification Numbers: F22, F24, O54

Keywords: International Migration, Remittances, Latin America, Caribbean

Author’s E-Mail Address: kbeaton@imf.org; scerovic@imf.org; mgaldamez@imf.org;

mhadzivaskov@imf.org; floyola@imf.org; zkoczan@imf.org; blissovolik@imf.org;
jmartijn@imf.org; yustyugova@imf.org; jwong2@imf.org
 4

Abstract ......................................................................................................................................2

I. Introduction ............................................................................................................................7

II. Stylized Facts about Migration and Remittances in LAC .....................................................8

A. Migration ...................................................................................................................8
B. Emigrant profiles .....................................................................................................13
C. Remittances .............................................................................................................14
D. Remittance channels and cost .................................................................................19

III. Empirical Evidence On Drivers and Macroeconomic Effects ...........................................22

A. What are the drivers of migration and remittances? ...............................................22
B. What explains the high cost of remittances? ...........................................................26
C. How do migration and remittances affect growth? .................................................28
D. Are remittances a macroeconomic stabilizer? ........................................................31
Do remittances facilitate consumption risk-sharing? .......................................31
Remittances and fiscal revenues ......................................................................37
Box 4. Remittances and their Effects During the Global Financial Crisis
(Continued) ......................................................................................................40
Remittances and financial stability ..................................................................41
Remittances and Competitiveness ...................................................................42
Remittances and inflation ................................................................................43
E. How do migration and remittances affect poverty and inequality? .........................45

IV. Macro-Model: The Impact of a U.S. Growth Shock .........................................................48

V. Conclusions and Policy Implications ..................................................................................52

References ................................................................................................................................76

Boxes
1. Brain Drain in Jamaica.........................................................................................................14
2. Who Sends Remittances? Evidence from U.S. Microdata ..................................................17
3. Smooth Operator: Remittances and Fiscal Policy ...............................................................37
4. Remittances and their Effects During the Global Financial Crisis ......................................39

Figures
1. Emigrants, Latin America and the Caribbean and Emerging Market Economies, 2015 .......8
2. Emigrants ...............................................................................................................................9
3. The Stock of LAC Emigrants ................................................................................................9
4. Immigrants ...........................................................................................................................10
5. Emitter and Receiver Countries in Latin America, 2015 .....................................................10
6. Intra-Regional Migration in LAC ........................................................................................11
7. Migration and Income Levels in LAC, 2015 .......................................................................12
8. Educational Attainment .......................................................................................................13
9. Married (Spouse Absent) Immigrants in the U.S.................................................................13
10. Remittances to Latin America and the Caribbean .............................................................15
 5

11. Remitters by Education ......................................................................................................16

12. Remittances, 2015 ..............................................................................................................16
13. LAC Emigrant Stocks and Remittances, 2015) .................................................................17
14. Characteristics of LAC Remittance Senders in the US .....................................................18
15. Remittance Channels .........................................................................................................19
16. Global Cost of Sending USD 200 in Remittances .............................................................20
17. Latin America: Product Impact of Withdrawal of Correspondent Banking ......................20
18. Cost of Sending USD 200 in Remittances, Latin America and the Caribbean..................22
19. Net Effect of Migration and Remittances on Growth: Short Term and Long Term
Effects ......................................................................................................................................31
20. Remittances and Natural Disasters ....................................................................................31
21. LAC: Remittances and Other Inflows................................................................................32
22. Remittances and Income Volatility ....................................................................................33
23. Remittances and Deviation from Perfect Risk Sharing .....................................................34
24. Portion of Total Risks Shared ............................................................................................36
25. Remittances and Household Income in Mexico ................................................................47
26. Gini Coefficients ................................................................................................................47
27. United States: Temporary Increase in Domestic Demand .................................................49
28. Dominican Republic: Temporary Increase in Domestic Demand in the U.S. ...................51
29. Jamaica: Temporary Increase in Domestic Demand in the U.S. .......................................52

Tables
1. Determinants of Migration Flows (IV Regressions) ............................................................24
2. Determinants of Remittances (IV Regressions) ...................................................................25
3. The Cost of Remittances: Determinants ..............................................................................28
4. Global Consumption Risk-Sharing (Panel Regressions) .....................................................35
5. Effects of Remittances on Revenue (IV Regressions) .........................................................39
6. Effects of Remittances on Non-Performing Loans ..............................................................42
7. Effects of Remittances on Inflation .....................................................................................45
8. Effects of Remittances and Migration on Poverty and Inequality (IV Regressions) ...........46

Annexes
I. Data .......................................................................................................................................54
II. Empirical strategy ...............................................................................................................63
III. Regression Tables ..............................................................................................................64

Annex Tables
1.1. Variables in Regressions ...................................................................................................57
1.2. Countries Included in the Study........................................................................................59
1.3. Remittance Corridors: Source and Recipient Countries ...................................................60
1.4. Characteristics of Immigrants Who Entered After Age 22, 2014 .....................................61
1.5. Top Occupations, Immigrants Who Entered After Age 22, 2014 ....................................62
2.1. Empirical Strategy ............................................................................................................63
3.1. Determinants of Migration Flows .....................................................................................64
3.2. Determinants of Remittances ............................................................................................66
3.3. Effects on Growth (FE Regressions) ................................................................................67
 6

3.4. Effects on Growth (IV Regressions) .................................................................................68

3.5. Global Consumption Risk Sharing ...................................................................................69
3.6. Regional Consumption Risk Sharing ................................................................................69
3.7. Regional Consumption Risk-Sharing (Panel Regressions)...............................................70
3.8. Effects on Revenue (FE Regressions)...............................................................................71
3.9. Effects on Revenue (IV Regressions) ...............................................................................71
3.10. Effects of Remittances on NPLs (FE Regressions) ........................................................72
3.11. Effects of Remittances on NPLs (IV Regressions) .........................................................73
3.12. Remittances and the Real Effective Exchange Rate (FE Regressions) ..........................74
3.13. Remittances and the Real Effective Exchange Rate (IV Regressions) ...........................74
3.14. Effects on Inflation (FE Regressions) .............................................................................75
3.15. Effects on Inflation (IV Regressions) .............................................................................75
 7

I. INTRODUCTION

Migration and remittances can have profound effects on human welfare and economic
development. Economic migration reflects people’s desire to improve their own and their
families’ wellbeing. As emigrants find higher-paying jobs abroad, productivity likely rises at
a global level. Likewise, the remittances emigrants send home can also improve the standard
of living, health, and education of the often-poor recipient households. However, for others
in the home country, and for the remaining population as a whole, the impact of outward
migration can be less benign, because the departure of people of prime working age, who
may also be relatively well-educated in some cases, can weaken the country’s economic
base.

Outward migration has been an important phenomenon for countries in Latin

American and the Caribbean (LAC), particularly those in Central America and the
Caribbean. In these two sub-regions, emigrants account for about 10 percent or more of the
population—compared with about 2 percent, on average, for emerging market and
developing countries. Emigrants typically represent the younger and more productive
segment of the population – an average emigrant is between 20-25 years old – and in some
instances (e.g. the Caribbean), emigrants are also the higher educated. Emigrants remit
substantial funds, averaging about 8 percent of GDP, to support family members back home.

Given their importance for the region, this paper examines recent trends in migration
and remittances, as well as the costs and benefits of these flows. Does the loss in
population associated with emigration hurt economic growth? Do remittances compensate for
this loss and function as engines of growth? Are remittances macroeconomic stabilizers and
do they help reduce poverty and inequality? Our study offers qualified positive answers to
each of these questions. The analysis focuses only on the consequences for countries in LAC
from where the emigrants originate and not on the effects on emigrants’ host countries.

The results presented in this paper underscore the profound and multifaceted
implications of migration and remittances for the LAC region. Five key messages arise
for LAC:

 Emigration and remittances, taken jointly, are not drivers of growth. While
emigration may reduce real per-capita economic growth (as a result of the decline in
labor resources and productivity), remittances can support investment and education and
foster commercial linkages. The negative impact of emigration on real per capita growth
seems to outweigh growth gains from remittances, notably for the Caribbean.

 Remittances are important macroeconomic stabilizers. Beneficial stabilizing effects

are particularly important for Central America and the Caribbean. Remittances in these
sub-regions represent one of the most important sources of external financing, facilitate a
smoothing of private consumption, and help boost financial sector soundness and fiscal
space.

 Remittances function as a channel to reduce poverty and inequality, since lower-

income households are more likely to receive them.
 8

 The effects of migration and remittances vary across LAC. Mexico stands out as a
special case, as it is the largest source of immigrants into the United States and an
important hub for emigrants from Central America. In contrast, for most South American
countries, emigration and remittances are less material and do not appear to act as
macroeconomic stabilizers. Even for those countries in South America that have seen
substantial outward migration, remittances tend to be relatively modest, and our analysis
does not reveal significant macroeconomic effects.

 Labor market developments and changes in host country policies can have a
significant impact on migration and remittances. With the majority of emigrants from
Central American, Mexico, and the Caribbean living in the United States, large shifts in
its economic cycle and policies could have particularly far-reaching regional
repercussions.

The paper is organized as follows. Section II reviews patterns of migration and remittances
in LAC and the demographic characteristics of emigrants and remittance senders. The paper
leverages on the US-centric nature of the region’s emigration patterns and the availability of
micro data for this country to examine the characteristics of emigrants and remittances
senders in the region’s main host country. This main channels through which remittances are
sent and their relative costs are also considered. Section III examines drivers of remittances
and migration, the determinants of the costs of remitting, and the impact of emigration and
remittances on growth and macroeconomic stability. We also look at remittances’ impact on
poverty and inequality, in particular using micro-data from remittance recipients in Mexico.
Section IV examines the offsetting effects of remittances and emigration jointly in a general
equilibrium setup to understand the channels through which they affect economies. Finally,
Section VI concludes.

II. STYLIZED FACTS ABOUT MIGRATION AND REMITTANCES IN LAC

A. Migration

Emigration has been important for many 30

Figure 1. Emigrants, Latin America and
countries in LAC over the past decades. 2 25 the Caribbean and Emerging Market
While the stock of emigrants is estimated at Economies, 2015
close to 5 percent of the population in LAC, 20
(Percent of total population)
there are significant differences across groups 15
of countries within the region (Figures 1, 2 10
and 3). Starting in the 1960s, emigration to
5
countries offering better economic
opportunities has been an important 0
DOM

HND

PER
COL

BRA
Central America
URY
MEX
SLV

PAR

PAN

EME
NIC

GTM
Caribbean

LAC

CRI
BOL
ECU

CHL

VEN
ARG

phenomenon for LAC. Violent conflict has

also resulted in emigration in several
countries, particularly in Central America
during the 1990s and the subsequent Sources: UNPD and Fund staff calculations.

2 For patterns of migration and remittances in Latin America, see Niimi and Özden (2008), OAS (2011), and ECLAC
(2014).
 9

deterioration in the security situation. Stocks

Figure 2. Emigrants
of emigrants are especially significant for the (Percent of population)
Caribbean, where about one-fifth of the 12
LAC Developing Asia Africa Middle East CIS
population lives abroad, as well as the 10
countries in Central America, Panama and the
8
Dominican Republic (CAPDR) and Mexico
(about 10 percent of the population). On the 6 5.2 5.3
4.7
4.2
other hand, emigration out of South America 4
3.1
3.6

is much more limited, averaging about 2 ½

2
percent of the population. However, some
0
South American countries such as Paraguay 1990 1995 2000 2005 2010 2015
and Uruguay have sizeable emigrant Sources: UNPD and IMF staff calculations.
populations living abroad that represent more
than 10 percent of their populations. Among other South American countries, Bolivia,
Colombia, and Ecuador also have sizable emigrant populations.

Emigration from LAC has traditionally been U.S.–centered. About two-thirds of all LAC
emigrants reside in the United States and this proportion has been rather stable over the past
two decades (Figure 3). Moreover, almost all Mexican and four-out-of-five CAPDR
emigrants live in the United States, while this share is smaller for the Caribbean (about half
of all emigrants). For the last group of countries emigration to Canada and Europe is quite
important as well. South America features a more diversified migration pattern, with intra-
regional migration as well as migration to Europe (especially Spain, reflecting historical and
linguistic ties).

Figure 3. The Stock of LAC Emigrants

…with the majority of emigrants destined to the United
An important share of LAC’s population has emigrated…
States.
Emigrants (% of total population) Emigrants to US (% of total emigrants)
25
120

20 100

Caribbean Mexico
80
15 Mexico CAPDR
CAPDR 60 LA
10 LAC LAC
LA 40
Caribbean
5 South America South America
20

0
0
1990 1995 2000 2005 2010 2015
1990 1995 2000 2005 2010 2015

Source: United Nations Population Division (UNPD).

Sources: UNPD Sources: UNPD

With a few exceptions, immigration has been much less important for LAC countries
than emigration, and immigration has mostly been intraregional. Overall, immigrants
account for close to 1.5 percent of the total LAC population in 2015, While CAPDR and the
Caribbean host more immigrants as a share of total population than Mexico and South
America, the differences across these groups of countries are less pronounced compared to
the case of emigration. Figure 6 (circle) shows the magnitude and patterns of interregional
 10

migration. Within South America, Figure 4. Immigrants

Immigrants (% of(%
totalof total population)
population)
4.5
important destinations for migrants have
4
been Argentina (mainly from Bolivia, 3.5
Chile, Paraguay, and Uruguay) and, 3 CAPDR

especially during the 1970s, Venezuela 2.5 Caribbean

(notably, from Colombia). Since the 2 LAC

economic crisis of the 1980s, migration 1.5 South America

1 LA
from South America to other regions has
0.5 Mexico
become more important—in particular to
0
the United States and Spain. In recent 1990 1995 2000 2005 2010 2015

years, Chile and Colombia have also Sources: UNPD

become notable destinations. Within the CAPDR region, a key pattern is the presence of
emigrants from Nicaragua in Costa Rica, with the other countries in the region showing more
diversified intra-regional migration patterns. For several countries in the region, such as
Costa Rica, Panama and the Dominican Republic, both inward and outward migration are
very important (Figure 5).

Figure 5. Emitter and Receiver Countries in Latin

America, 2015
Countries with significant immigration and emigration

Costa Rica

Argentina

Panama

Venezuela

Dominican Republic

Chile

Ecuador

Paraguay

Uruguay

0 2 4 6 8 10 12 14

Emigrants (% of population) Immigrants (% of population)

Source: UNPD.
Note: This chart depicts the countries in LAC for which
both the stock of emigrants and the stock of immigrants
represented at least 2 percent of the total population in
2015.
 11

Figure 6. Intra-Regional Migration in LAC

Source: OECD.
Note: The chart depicts stocks of intra-regional migrants in LAC in
2010. The colors indicate the migrants’ country of residence and the
flow roots indicate the migrants’ country of origin. Each country’s
share of the perimeter corresponds to the relative size of its migrants
(immigrants plus emigrants) in the region.

Higher-income countries in Latin America receive more immigrants and send less
emigrants, but the latter relationship is weaker for the Caribbean. Income differences
across countries constitute one of the key factors that explain the patterns of cross-border
migration (Figure 7).

 In 2015 the average stock of immigrants in countries of Latin America with GDP per
capita below 5,000 U.S. dollars represented about 1 percent of the total population,
compared with close to 5 percent for countries with GDP per capita above 10,000
U.S. dollars. On the other hand, emigration is much more present in countries with
lower incomes per capita. On average, about 10 percent of the population in countries
with GDP per capita below 5,000 U.S. dollars live as emigrants abroad, while
 12

corresponding figure is about 4 percent of the population in countries with GDP per
capita above 10,000 U.S. dollars.

 In contrast to Latin America, relative incomes do not seem to play a significant role
for emigration from the Caribbean, likely because emigration in this region is driven
also by natural disasters (Figure 7, lower right panel).

Figure 7. Migration and Income Levels in LAC, 2015

Latin America: Immigration and income levels Latin America: Emigration and income levels
10 25
9
Stock of immigrants (% of population)

8 20

Emigrants (% of population)
7
6 15
5
4 10
3
2 5
1
0 0
0 5 10 15 20 0 5 10 15 20
Sources: UNPD GDP per capita ($)
Sources: UNPD GDP per capita ($)

Caribbean: Immigration and income levels Caribbean: Emigration and income levels

40 80

70
Stock of immigrants (% of population)

35
60
Emigrants (% of population)

30

25 50

20 40

30
15
20
10
10
5
0
0
0 5 10 15 20 25
0 5 10 15 20 25
Sources: UNPD GDP per capita ($) Sources: UNPD GDP per capita ($)

Source: UNPD and IMF WEO.

 13

B. Emigrant profiles

Who are LAC’s emigrants? Micro data from the American Community Survey provide a
profile of LAC immigrants in the United States (Annex Table 1.4).3 While immigrants
typically enter the United States in their early 20s, immigrants from Mexico and CAPDR
countries tend to be younger at arrival Figure 8. Educational Attainment
and have lower levels of education (Immigrants who Entered after Age 22)
Less than high school High sch ool 1 year of college
compared with those from South 100%
2 years of college 4 years of college 5+ years of college
2.1 3.2 7.0
4.7
America and the Caribbean (Figure 8). 90% 2.0
5.1
7.8
3.6 10.4
12.8

8.9
Of the latter groups, 40 percent or 80%
24.3
7.7 19.1
70% 12.3
more have attended college (or 60% 28.9
6.4
12.6
beyond). Brain drain is a particular 50%
40% 44.6
challenge for the Caribbean (Box 1). 34.0
30% 61.9
Emigrants from Mexico and CAPDR 20%
47.7

are also more likely to be 10% 18.1 15.2

0%
undocumented and much less likely to Mexico Central America Caribbean Sou th America
become U.S. citizens than those from Source: 2008 American Community Survey.
the Caribbean and South America.

With lower levels of education on average, emigrants from Mexico and CAPDR tend to
work in lower-skilled occupations. Their employment is concentrated in construction,
maintenance, transportation, production, and food preparation, while emigrants from South
America and the Caribbean tend to be employed in office and administration, sales,
management, and health-related occupations (Annex Table 1.5). The higher-skilled
immigrants from South America and the Caribbean also earn more: their hourly wages are
almost 60 percent higher, on average, than those of immigrants from Mexico and CAPDR.

There is some evidence of family reunification for emigrants into the U.S. from CAPDR
10%
and Mexico. The proportion of households Figure 9. Married (Spouse Absent) Immigrants in the U.S.
(Percent, Born between 1957-1962)
in which the head is married but the head’s 9%

spouse is absent declines with the age of the 8%

Mexico
CAPDR
head of the household from about 9 percent Caribbean
South
7%
of households (for age 28) to around 6
percent of households (by age 50) for 6%

immigrants born in Mexico and CAPDR 5%

(Figure 9).4 For South America, the evidence
4%
is weaker, with the decline in
married/spouse-absent households taking 3%
28 30 32 38 40 42 44 46 48 50 52 54 56
place late in life and only to a small Age
Source: 2008 American Community Survey and Fund staff estimates.
magnitude. Like the trends noted above (and

3 For South American, and to a lesser extent Caribbean, migrants, these data may not be fully reflective of their
characteristics given the more diverse destination pattern.
4 While this trend could also be due to return migration at an early age, for the cohort under analysis and at those ages, return

migration was a relatively modest phenomenon throughout the 1990s and even around the crisis. According to ECLAC
(2014), for Mexico in 2010, the number of migrants who had returned during the previous 5 years amounted to only 7
percent of the total emigrant stock.
 14

likely driven by the different type of immigration), there is no compelling evidence for
family reunification among Caribbean immigrants.

Box 1. Brain Drain in Jamaica

Nearly half of Caribbean emigrants residing in the United States have at least a college
education, a ratio comparable to the U.S. native-born population (Figure 1.1, right). In
contrast, only one-quarter of other Latin American and Caribbean emigrants in the United
States have at least a college education.1 However, to truly examine brain drain from the home
country, educational levels of immigrants in the host country are not sufficient—attainment
levels in the home country are needed for comparisons. Very few countries in the Caribbean
publish household data that include detailed educational attainment; Jamaica, however, does.

In Jamaica, there is evidence of significant brain drain, especially among women. Among
Jamaican-born women living in the United States (who emigrated after the age of 22), 50
percent have at least a college education; this is double the attainment rate in the home
country, where only one-quarter of women have a college education (Figure 1.1, left).2 A
simple calculation implies that nearly one-third of all women with at least a college education
in Jamaica have emigrated, compared to about 13 percent of those with high school or less.
These patterns reflect the significant numbers of Jamaican nurses and healthcare practitioners
– 65 percent of Jamaican immigrants are in these sectors versus 7 percent in the United States-
born population. For men, the statistics are not as striking, but there is nevertheless evidence
of brain drain – while 21 percent of men in Jamaica are college educated, 37 percent of those
who migrated to the US have at least a college education.

Box Figure 1.1. Jamaican Educational Attainment

100 100
Educational Attainment of Jamaicans: Living in the
Educational Attainment 90 U.S. vs Living in Jamaica
(% of total population residing in the U.S.) 80
(U.S. data for 2012, Jamaica data for 2011)
80
Women (US)
Caribbean Rest of LAC 70 Men (US)
U.S. born Women (JAM)
60 60
Men (JAM)
50
40 40

30
20
20

10
0
0
HS or less College
HS or less College or more

Sources: 2008 American Community Survey and World Bank.

1
This difference is statistically significant at 99 percent.
2
This difference is statistically significant at 95 percent.

C. Remittances

LAC emigrants have maintained strong connections with their home countries, sending
home sizable remittances (Figure 10). Remittances to the region reached 1.4 percent of
regional output in 2015. As a share of GDP, remittance flows to CAPDR and Caribbean
 15

countries dwarf those received by their South American neighbors, consistent with their
larger migrant stocks, and also far exceed those received by Mexico (one of the largest
recipients worldwide in nominal terms) and emerging market economies on average.5 In four
countries—El Salvador, Haiti, Honduras, and Jamaica—remittances exceed 15 percent of
GDP.

Figure 10. Remittances to Latin America and the Caribbean

…but Central America and the Caribbean
Mexico receives the largest remittance flows to
receive more important flows compared to their
LAC…
output.
Remittances Remittances
(in billions of US dolalrs) (% of GDP)
80 700 12
Caribbean World
70 600 Caribbean
Mexico 10
60 Central America Mexico
500
Latin America nd the Caribbean 8 Central America
50
South America 400 Latin America nd the Caribbean
40 6
World (RHS) South America
300
30
4
200
20

100 2
10

0 0 0
1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013

Remittances received by the region are

Sources: World Bank
…with considerable heterogenity across Latin
Sources: World Bank and IMF WEO

comparable to those received by other regions America and the Caribbean.

of emerging market economies…
Remittances Remittances, 2015
(% of regional GDP) (% of GDP)
4 30

LAC Developing Asia 25

Africa Middle East
3 20
CIS

15
2
10

5
1
0
HTI

PER
MEX
PRY
VCT
BOL
GRD

URY

ARG
CHL
GUY
DOM

KNA
HND

ECU

COL

PAN
SLV

ATG
LAC avg.
JAM
GTM

C. American

BLZ

BRA
Caribbean

BRB

VEN
LCA

EME avg.
CRI
TTO

SUR
NIC

DMA

0
1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013

Sources: World Bank and IMF WEO Sources: World Bank and IMF WEO

Sources: World Bank and IMF WEO.

The remitting behavior of LAC immigrants in the United States varies with their
demographic characteristics (Box 2). About a third of LAC immigrants send remittances to
their home countries. This share is somewhat higher for CAPDR and falls with age. The
likelihood of remitting does not appear to relate to the immigrant’s income. Not surprisingly,

5Even for South American countries that have sizeable emigrant populations, remittances are very low compared to CAPDR
countries with comparable emigrant populations.
 16

60%
immigrants who are married but with an absent Figure 11. Remittance Senders by Education Level
(Percent of total remittance senders, by region)
spouse are the most likely to remit. On average, 50%
LAC immigrants who remit send about HS or less
40% College or more
US$2500 to their families on an annual basis.
Conditional on remitting, immigrants in the 30%
United States with lower levels of education
20%
and income tend to remit more as a share of
their income, while immigrants from the 10%

Caribbean send home much less than those

0%
from Central America (Figure 11). CAPDR MEX SOU CAR
Source: 2008 American Community Survey (remittances module).

Remittances to the region peaked at about 2 percent of regional output before the
global financial crisis. With LAC migrants residing mainly in the United States, the
epicenter of the crisis, remittances fell precipitously during and in the aftermath of the crisis–
more so than in other parts of the world. Emigrants from Mexico and CAPDR were
particularly hard hit by the global financial crisis because the crisis had a notably profound
effect on the industries in which they have traditionally been employed, such as construction
and building maintenance, sharply lowering remittances into these countries. Remittances to
the region have subsequently begun to recover, but remain below their precrisis peak.

LAC countries send very little in Figure 12. Remittances, 2015

(Percent of GDP)
remittances. Despite the importance of 30
intraregional migration, LAC countries are not
25
large senders of remittances, particularly when Inflow
Outflow
20
compared to the remittances they receive
(Figure 12). 15

10

The relationship between emigrants and 5

remittances is very different between Latin
0
America and the Caribbean. In general,
HTI

MEX
BOL

URY

ARG
HND

GUY
DOM

CHL
ECU

PAN
COL
JAM
SLV
GTM

BLZ

VEN
CRI

BRA
SUR
NIC

countries in which emigration is relatively more Sources: World Bank and IMF WEO
important are expected to receive higher overall
remittances. This is indeed the case for Latin American countries (Figure 13). However, this
result does not hold for the Caribbean. First, remittance flows into the Caribbean, on average,
are relatively low given the large stock of emigrants. Second, within the Caribbean, a larger
emigrant stock does not imply higher remittances. This may be linked to differences in
migration patterns, with Caribbean emigrants tending to migrate with their families, while
evidence of later family re-unification is more pronounced for CADPR emigrants.
Differences in remitting patterns may also be related to the time emigrants have been the host
country, as emigrants tend to remit less over time as their connections with their home
country diminish. For instance, Honduran emigrants may be sending relatively more
remittances than El Salvadoran emigrants because, on average, they have spent shorter time
in the host country.
 17

Figure 13. LAC Emigrant Stocks and Remittances, 2015

18 25
HND SLV
16
HTI
20
14

Remittances (% of GDP)
Remittances (% of GDP)

12
15 JAM
10 GTM NIC
8 GUY
DOM 10
6
KNA
4 BOL 5 BLZ BRB VCT DMA
ECU GRD
2 MEX PRY LCA ATG
BRA PER
CRIPAN COL TTO SUR
ARGVEN CHL URY 0
0
0 20 40 60 80 100 120
0 5 10 15 20 25 30
Emigrants (% of Population)
Emigrants (% of Population)

Source: UNPD, World Bank, and Fund staff calculations.

Box 2. Who Sends Remittances? Evidence from U.S. Microdata

Remittance senders tend to be young, and the likelihood drops with age. While over half
of CAPDR emigrants under 30 years old send remittances, this proportion drops to about 40
percent after age 40 (Figure 14). For Mexico and the Caribbean, similar declines also take
place, where the proportion of remitters dropping from about 40 and 30 percent, respectively,
at the younger ages, to 30 and 20 percent, respectively, after 50 years old. This is partly driven
by the family re-unification patterns which weaken home-country links: spouses and children
join the remitter in the US, while parents pass away in the home country.
Mexican men and Caribbean women emigrants are the biggest remitters. Out of all
remittance senders from Mexico, 58 percent are men whereas for the Caribbean, the same
proportion are women. This echoes the demographic characteristics of emigrants (Annex
Table 1.4). Caribbean emigrants tend to be women (particularly in teaching and healthcare
professions) who are attracted by opportunities in the United States. On the other hand,
Mexican emigrants tend to be men who engage in lower skilled jobs in the US, which
nevertheless provide a higher income than what they would have earned at home. For CAPDR
and South America, women and men are just as likely to remit.
Those married but whose spouse is absent are most likely to remit and in larger
amounts. This is not surprising as those people likely have spouses (and children) in the home
country who are the recipients of remittances. This pattern broadly holds for all sub-regions
except for CAPDR, where the likelihood to remit is very high across all marital states, but
especially so for widowed and separated. For CAPDR, this could partly reflect the heritage of
non-economic migration, whereupon those widowed due to wars emigrated to the US.
Conditional on remitting, wealthier Mexican households remit more but poorer
households remit a higher proportion of income. Gross amounts remitted remain at about
$2,500 for CAPDR and Mexican households at incomes below $100,000; the analogous
number for Caribbean and South America is much closer to $1,000. However, in Mexico’s
case, the amounts remitted increase significantly as household income levels reach $150,000.
For CAPDR, amounts remitted form a U-shape, where those with about US$20,000 and
US$100,000 of income a year remit the most. CAPDR and Mexican households with incomes
under $20,000 remit nearly 40 percent of their income. For Caribbean and South American
(and CAPDR/Mexico households earning above $30,000), remittances hover at about 10
percent of household income.
 18

Figure 14. Characteristics of LAC Remittance Senders in the US

Remitters from Mexico tend to be men, while
… and likelihood to remit declines with age.
those from Caribbean tend to be women…
CAPDR CAR
Remitters by Age
Remitters: by sex Male Female MEX SOU
100 (% of total)
60%
55%
80 50%
45%
60 40%
35%

40 30%
25%
58
50 50 20%
20 42
15%
10%
0 24 29 34 39 44 49 54 59
MEX CAPDR SOU CAR

Those with spouse absent or separated are

… and amounts remitted are higher.
most likely to remit…
Remitters by Marital Status Amounts Remitted
(% of total households) (conditional on remitting)
80% 10000
CAPDR CAR MEX SOU 9000 CAPDR CAR MEX SOU
70%
8000
60%
7000
50% 6000
40% 5000

30% 4000
3000
20%
2000
10% 1000
0% 0
Married - Married - Widowed Divorced Separated Never Married - Married - Widowed Divorced Separated Never
Spouse Spouse Married Spouse Spouse Married
Absent Present Absent Present

Amounts remitted increase with income among … but lower income households remit more as
immigrants from Mexico… proportion of income
12000 45
Amounts Remitted Amounts Remitted as Percent of Income
(Conditional on remitting) 40 (Conditional on remitting)
10000
35

30 CAPDR
8000 CAPDR CAR
CAR 25 MEX
MEX SOU
6000 20
SOU
15
4000
10

2000 5

0
0 < 12.5 < 20 < 30 < 40 <50 <60 < 75 < 100 < 150 150 +
< 12.5 < 20 < 30 < 40 <50 <60 < 75 < 100 < 150 150 + Income in thousands of '00 USD
Income in thousands of '00 USD Source: 2008 American Community Survey and Fund staff estimates.

Source: 2008 American Community Survey (remittances module).

 19

D. Remittance channels and cost

Emigrants primarily rely on banks and money transfer operators (MTOs) to send
remittances. MTOs in particular dominate formal remittance channels across all regions of
the world and within LAC (Figure 15).6,7 While the market for MTOs includes many smaller
operators, Western Union and MoneyGram are by far the largest players, operating in 99 and
92 percent of country corridors included in the World Bank’s Remittance Prices Worldwide
(RPW) database.

Figure 15. Remittance Channels

Remittances are primarily transmitted through
…including in LAC.
MTOs…
Remittance Channels Remittance Channels Latin America and the Caribbean
(2016Q3; in percent of total) (2016Q3; in percent of total)
100
90 100

80 90
80
70
70
60
60
50 50
40 40
30 30
20 20
10 10
0
0

HTI

PER
MEX

PRY
BOL

COL

DOM

GUY
HND

PAN
ECU

SLV
BRA

GTM

JAM
CRI

SUR
NIC
CUB
East Asia & Pacific Europe & Central Asia Latin America & Middle East & North South Asia Sub-Saharan Africa
Caribbean Africa

MTO Bank Bank/MTO MTO/Bank Post Office MTO Bank Bank/MTO MTO/Bank
Sources: World Bank, Remittance Prices Worldwide Sources: World Bank, Remittance Prices Worldwide

Source: World Bank, Remittances Prices Worldwide.

Despite advances in technology that facilitate financial transactions across countries,

remittances continue to be mainly transmitted in cash.8 Online transaction channels are
becoming increasingly available, as are mobile money, which could have positive effects on
the financial inclusion of households receiving remittances. For LAC in particular, online
channels have become more popular, while mobile remittance channels have been slower to
develop, particularly compared to Sub-Saharan Africa, as payment systems have not kept
pace with technology.

6 Informal remittance channels, whereby remittances enter a country through private unrecorded channels such as friends,
relatives or the migrant themselves, are also believed to be important; however, these channels are often unrecorded and
there is no data available to assess their importance (with some exceptions).
7 Data on remittance channels are from the World Bank’s Remittance Prices Worldwide database. The database includes

detail on distinct remittance channels by corridor and by remittance service provider. However, the database does not
include data on the magnitude of remittances transacted on each channel. Instead, the relative importance of each type of
channel is based on the percent of each type of channel in the total number of channels for each corridor.
8 Cash transfers typically occur with a migrant depositing cash at a local MTO or bank on the sending end and the recipient

receiving cash at their local bank branch or MTO.

 20

Sending remittances is costly. The global average cost of sending US$200 in remittances
remains substantial at 7.42 percent as of 2016Q3 (Figure 16).9 Remittance corridors with
larger remittances benefit from lower costs: Figure 16. Global Cost of Sending USD 200 in Remittances
the weighted average total cost, which (Percent)
10
accounts for the relative size of remittances Global Average
9 Latin America & the Caribbean
sent between countries, is lower than the Global Weighted Average

global average at 5.73 percent as of 2016Q3. 8

7.4
Banks are the most expensive channel for 7
migrants to send remittances, at 11.18 percent 6.2
6
in 2016Q3, while the cost of sending
5.7
remittances through MTOs reached 8.05 5

percent in 2016Q3.10 Mobile remittance

4
service providers are a low-cost option for 2011Q1 2012Q1 2013Q1 2013Q3 2014Q1 2014Q3 2015Q1 2015Q3 2016Q1 2016Q3
Source: World Bank, Remittances Prices Worldwide.
migrants, at 3.45 percent in 2016Q2, is below
the global average.

The cost of sending remittances to LAC is lower than to other regions, except for South
Asia, but, at 6.2 percent for a US$200 transaction, remains substantial (Figure 18).
These costs have declined significantly over the past decades—for example, by about 40
percent for flows to El Salvador, Colombia and Guatemala, and by 15 percent for Jamaica
over 2001-15 (Orozco, Porras, and Yansura 2016). Within LAC, the region’s largest
recipients of remittances benefit from lower transaction costs as do the dollarized economies,
with dollarization eliminating the cost of currency conversion. Costs remain relatively
elevated for Caribbean countries compared with those in Latin America. Remittance from the
United States are the most cost effective, likely reflecting competition among remittance-
service providers in the region’s most important remittances corridors. Within LAC, the cost
of remittances from the U.S. also varies by country, suggesting that characteristics of both
the migrants’ host and home country affect the cost of remittances.

The cost of remitting has come under Figure 17. Latin America: Product Impact of Withdrawal of
Correspondent Banking
upward pressure from the global (Percent of ASBA members reporting on impact)
withdrawal of correspondent banking 70

relationships. The withdrawal of global banks 60

from correspondent banking has 50

disproportionately affected MTOs given the 40

enhanced challenges they face to meet the 30

stringent know-your-customer anti-money 20

laundering/combating the financing of 10
terrorism standards.11 According to a survey 0
Remittances Correspondents Trade Finance Money Exchange Electronic Electronic Money Mobile Banking
carried out by the World Bank (World Bank Source: ASBA (2015)
Payment

9 The cost of sending remittances includes a transaction fee and a currency conversion fee, both typically paid by the sender,
although some remittance-service providers may also require the recipient to pay a fee.
10 The cost of sending remittances through post offices, the third main type of remittance service provider, is below the

global average at 6.36 percent in 2016Q3.

11 The withdrawal of global banks from correspondent banking has been linked to their cost-benefit analysis in response to

more rigorous prudential requirements and AML/CFT and tax transparency standards (Erbenová et al. 2016
 21

(2015b)), global banks have closed the correspondent bank accounts of MTOs, particularly
smaller MTOs, on a widespread basis, curtailing their ability to transmit remittances. Coming
under similar pressure, in some countries/regions, local banks have also faced challenges in
maintaining their correspondent banking relationships, with 60 percent of the Asociación de
Supervisores Bancarios de las Américas reporting that remittances to LAC have been
affected (Figure 17).12 Pressure on MTOs’ correspondent banking relationships may have
contributed to the observed slowing of the convergence between the global average cost of
sending remittances and the cost of sending remittances through MTOs.13

The high transaction costs of remittances reduce the money received by migrants’
families. Based on the US$68 billion in officially recorded remittances to LAC in 2015,
lowering the cost of remittances could significantly increase the funds received by migrants’
families back home. The United Nations has made lowering these transaction costs a
priority—reducing them to less than 3 percent and eliminating remittance corridors with
transaction costs higher than 5 percent by 2030 is a UN Sustainable Development Goal.
Existing efforts to lower remittances transaction costs have focused on enhancing
competition in the market for remittances-services providers, which continues to be
dominated by MTOs, and promoting the use of new payment technologies for sending
remittances. Enhanced use of online and mobile remittance channels offers particular
promise to further lower the cost of remittances as mobile remittances-service providers are
the most cost effective.

12 To prevent remittance flows from being disrupted by compliance issues, the Federal Reserve Bank of Atlanta has enabled
financial institutions to transfer funds through the FedGlobal Automated Clearing House. Remittances are channeled
through the U.S. domestic payment system to foreign financial institutions and regulation MTOs (Erbenová et al. 2016).
13 The International MTO Index from the World Bank’s RPW database tracks the prices of MTOs that are present in at least

85 percent of corridors covered in the World Bank’s RPW database. To date, the index has included only Western Union
and MoneyGram.
 22

Figure 18. Cost of Sending USD 200 in Remittances, Latin America and the Caribbean
LAC countries that receive the most remittances and
The cost of sending remittances to LAC is lower than
dollarized economies benefit from a lower cost of
in all regions with the exception of South Asia.
remittances.
Cost of Sending USD 200 in Remittances Cost of Sending USD 200 in Remittances: Latin America &
(in percent) the Caribbean
11 14
(in percent, by destination)
10
10 12
9

9 9.5 10 8
7
8 8.2 8 6
7.0 5
7 6
6.4 4
6 4 3
6.2
East Asia & Pacific Europe & Central Asia
2
5 Latin America & the Caribbean Middle East & North Africa
5.4 2 1
South Asia Sub-Saharan Africa
0
4 0

PER

HTI
MEX

PRY
BOL
PAN

DOM

GUY
ECU

HND

COL

JAM
SLV

GTM

BRA
SUR

CRI
NIC

CUB
2011Q1 2012Q1 2013Q1 2013Q3 2014Q1 2014Q3 2015Q1 2015Q3 2016Q1 2016Q3

Source: World Bank, Remittances Prices Worldwide. Source: World Bank, Remittance Prices Worldwide

The cost to send remittances to LAC varies by source …and within the main source market (the United
market… States) across LAC.
Cost of Sending USD 200 in Remittances to Latin Cost of Sending USD 200 in Remittances from the United
America and the Caribbean States: Latin America & the Caribbean
(in percent, by source country) (in percent, by destination)
14
10
12 9
8
10
7
8 6
5
6
4
4 3
2
2
1
0 0
CRI CHL PRT USA BRA ITA ESP GBR NLD DOM FRA CAN JPN ECU HND SLV PAN NIC MEX PER GTM HTI BRA COL CRI JAM DOM CUB GUY

Source: World Bank, Remittance Prices Worldwide Source: World Bank, Remittance Prices Worldwide

Sources: World Bank, Remittance Prices Worldwide.

III. EMPIRICAL EVIDENCE ON DRIVERS AND MACROECONOMIC EFFECTS

The empirical analysis in this chapter offers a quantitative assessment of the drivers of
migration and remittances in Latin America and the Caribbean, as well as of their
macroeconomic effects in the countries that the migrants are from and that receive the
remittances. The analyses typically (although not in every case) use cross-country panel
regressions, for standardized country groupings (in most cases the world, emerging markets,
LAC, and subgroups within LAC). The key regression results are presented in the main text,
while background tables (Annex III) present additional regressions.

A. What are the drivers of migration and remittances?

Migration and remittances could be affected by economic conditions in the home and
host countries as well as shocks and underlying structural factors. The drivers of
migration and remittances are examined using cross-country panel regressions. The baseline
regressions are ordinary least squares (OLS) regressions with country fixed effects to account
 23

for any time-invariant unobservable country characteristics.14 The baseline regressions are
complemented with an instrumental variables approach to mediate endogeneity concerns as
remittance and migration flows could affect growth, while also responding to it. Regional
averages of the endogenous variables are used as the main instruments. 15 A similar
instrumental variables approach was used by Chami and others (2008), looking at the effect
of remittances on growth. Niimi and Özden (2008) relied on passport costs as a share of GDP
per capita, the dependency ratio and the population density in each country as instruments for
migration, when examining the effect of migration on remittances. The determinants of
migration and remittances have been studied widely in the literature, for an empirical
analysis of Latin America see e.g. Fajnzylber and López (2008). The empirical specifications
in the first section, examining the drivers of migration and remittances can be expressed as:

𝑦𝑖𝑡 = 𝛼𝑖 + 𝜷𝑿𝒊𝒕 + 𝛾𝑍𝑖𝑡 , (1)

where 𝑦𝑖𝑡 is the dependent variable of interest: migration flows as a share of the home
population or remittances as a share of GDP , 𝛼𝑖 are country fixed effects, 𝑿𝒊𝒕 is a vector of
exogenous variables including the stock of emigrants as a share of the population16, structural
characteristics and economic conditions in the home country (per capita GDP in PPP terms,
inflation, age dependency ratio, share of rural population), economic conditions in the host
country (unemployment) and shocks (dummy variables for natural disasters and conflict).17
𝑍𝑖𝑡 is the endogenous variable, real GDP growth, instrumented using regional averages of
GDP growth and changes in the terms of trade. For additional details on the empirical
strategy and results of the robustness analysis of the instrument set and dependent variables
see Annex 2. A similar empirical approach is used in all following sections, with the
exception of the analysis of the cost of remittances and the effect of remittances on
consumption smoothing.

Emigration from LAC appears to increase with conflict in the home country. The
empirical results suggest that conflict in the home country (measured here as a dummy
variable) would increase migration flow out of the country by 0.03 percent of the population
in the same year (Table 1).18 This could result in large cumulative effects – by comparison,
average migration flows in the LAC region over the period 1980-2013 were about 0.4
percent of the population annually. While these regressions do not show responsiveness of
migration flows to current economic conditions in the home or host country (neither GDP
growth, inflation or unemployment), this could be driven in part by the data limitation that
data on migration is interpolated, thus artificially smoothing the series. Results are, however,
broadly similar when examining migration flows to the U.S., available at an annual
frequency (Annex Table 3.1). An alternative explanation could be that what matters for

14 Time fixed effects are not included as regressions include controls such as Hispanic unemployment in the United States.
15 The robustness of the results to alternative sets of instruments is considered and reported in Annex II.
16 Data on migration is only available at 5-year intervals and is interpolated to the annual frequency, as is standard practice

in this literature.
17 These are in line with the control variables typically used in the literature. Results are robust to adding alternative controls

such as further measures of economic conditions in the host countries.

18 The conflict variable is a broad concept of conflict, including internal conflict as well as the threat of conflict, from the

Correlates of War database.

 24

migration is large shocks to growth (likely picked up by the conflict variable), rather than
normal business cycle fluctuations.

Slower-moving ‘structural’ variables—including the level of development in the home

country--can account for only a small share of the observed decline in migration flows.
For the LAC region, migration flows have fallen over time, from an average of 0.6 percent of
the population in the 1980s to about 0.2 percent in the 2000s. Slower-moving ‘structural’
variables, such as an increasing level of development, a rising stock of migrants abroad,
falling age dependency ratios and increasing urbanization together could account only for
about a fifth of this decline. Lower levels of conflict in the 2000s relative to the 1980s also
contributed. While migration flows appear to be decreasing with the migrant stock already
abroad for the LAC region as a whole, this average hides important differences between
subgroups: in particular, while this also holds for the Caribbean, the opposite link holds for
Mexico and Central America, which are characterized more by network-based migration.

Table 1. Determinants of Migration Flows (IV Regressions)

Central
Latin America,
Emerging America and Latin South Panama,
World Carribbean Mexico
Markets the America America and the
Caribbean Dominican
Republic
Change in emigrants/population
Real per ccapita GDP growth -0.000780 0.000761 -0.000593 -0.00109 -0.00106 0.00298 0.00175 -0.00101
(0.00253) (0.00717) (0.00346) (0.00312) (0.00314) (0.0170) (0.00759) (0.00407)
Emigrants/population -0.00979*** 0.00521 -0.0102*** -0.000498 0.0341*** -0.0258*** 0.0583* 0.00153
(0.00148) (0.00387) (0.00255) (0.00326) (0.00801) (0.00714) (0.0322) (0.00239)
PPP GDP per capita -0.00192** 0.0337*** -0.00926*** -0.00696*** -0.00906*** -0.00419 0.0455 -0.0138***
(0.000793) (0.00539) (0.00198) (0.00256) (0.00270) (0.00405) (0.0327) (0.00515)
Unemployment in destination -0.00417* -0.00809 0.00121 -0.000397 0.00160 0.00671 0.0109 0.00291
(0.00222) (0.00662) (0.00221) (0.00221) (0.00284) (0.0134) (0.00828) (0.00276)
Inflation -0.00000871 -0.00168 -0.00000723 -0.00000747 0.00000462 0.000183 0.000842 -0.0000714
(0.0000102) (0.00132) (0.00000785) (0.00000767) (0.00000733) (0.00237) (0.000710) (0.000576)
Age dependency -0.00280*** 0.00108 -0.00186* -0.000714 0.00389* -0.00155 -0.123*** 0.00526***
(0.000654) (0.00173) (0.00105) (0.00122) (0.00208) (0.00261) (0.0248) (0.00108)
Rural population -0.0000389 0.0240*** -0.00794*** -0.00668*** -0.0206*** -0.00754*** 0.521*** -0.00865***
(0.00114) (0.00374) (0.00132) (0.00197) (0.00350) (0.00243) (0.117) (0.00250)
Natural disaster 0.0223*** 0.00807 -0.00173 0.00604 0.0350* 0.00200 . -0.0291**
(0.00786) (0.0187) (0.0121) (0.0152) (0.0203) (0.0205) . (0.0129)
War -0.00256 0.0230 0.0258** 0.0263** 0.00805 0.0171 0.0314 -0.000372
(0.00846) (0.0240) (0.0126) (0.0126) (0.0165) (0.0764) (0.0573) (0.0116)
Number of obs. 3232 669 736 563 313 173 33 217
Adjusted R2 0.870 0.819 0.783 0.660 0.463 0.896 0.629 0.917
 25

Table 2. Determinants of Remittances (IV Regressions)

Central
Latin America,
Emerging America and Latin South Panama,
World Carribbean Mexico
Markets the America America and the
Caribbean Dominican
Republic
Workers' remittances/GDP
Real per capita GDP growth 0.0328 0.181 0.101 0.0783 0.0720 0.308* 0.00198 0.255**
(0.147) (0.762) (0.0902) (0.0892) (0.108) (0.185) (0.0195) (0.103)
Change in LC/USD exchange rate -0.0434 -0.0212 -0.0432 -0.0355 0.0387 -0.0699**
(0.0672) (0.457) (0.0586) (0.0471) (0.0435) (0.0346)
Emigrants/population 0.0131 0.0268 0.371*** 0.229** 0.781*** 0.376*** -0.608*** 0.453***
(0.0528) (0.246) (0.0812) (0.0953) (0.285) (0.0671) (0.230) (0.117)
PPP GDP per capita -0.103*** -0.0240 -0.396*** -0.445*** 0.0919 -0.194** -0.140 0.0101
(0.0372) (0.205) (0.0670) (0.0958) (0.219) (0.0793) (0.183) (0.171)
Unemployment in destination (lagged) -0.0357 -0.0963 -0.136*** -0.131** -0.266* 0.121 -0.0132 -0.206***
(0.0578) (0.0823) (0.0505) (0.0593) (0.155) (0.113) (0.0428) (0.0764)
Inflation 0.0398 0.0121 0.0399 0.0329 -0.0352 0.0620 0.000847 0.0331
(0.0612) (0.0866) (0.0534) (0.0429) (0.0396) (0.0479) (0.00634) (0.0238)
Age dependency -0.0867*** 0.0249 -0.272*** -0.372*** 0.174 -0.0108 0.614*** -0.635***
(0.0171) (0.0725) (0.0321) (0.0363) (0.117) (0.0361) (0.124) (0.0528)
Rural population -0.126*** -0.0860 -0.0963** -0.0505 -0.0760 -0.102 -2.960*** 0.434***
(0.0312) (0.0805) (0.0445) (0.0710) (0.478) (0.0724) (0.363) (0.113)
Average age at entry 0.00758 0.0449 -0.0898*** -0.198*** 0.00338 0.0151 -0.300*** -0.185*
(0.0191) (0.0327) (0.0322) (0.0466) (0.0776) (0.0426) (0.0592) (0.106)
Female migration share -0.194** -0.300** -0.268 -0.386** 0.608 0.203 -1.366*** -1.991***
(0.0887) (0.132) (0.209) (0.193) (0.630) (0.171) (0.344) (0.494)
Natural disaster 0.257 0.323 0.623* 0.328 0.382 0.185 . 1.011*
(0.231) (0.287) (0.353) (0.473) (0.748) (0.400) . (0.551)
War -0.294 -0.522 -0.449 -0.504 0.144 -1.810** . -0.436
(0.184) (0.436) (0.337) (0.312) (0.408) (0.900) . (0.457)
Number of obs. 1413 511 486 356 174 214 24 158
Adjusted R2 0.812 0.823 0.844 0.825 . 0.779 0.954 0.888

Remittances to the LAC region also respond to shocks, and appear to be more
responsive to current economic conditions than migration flows. Remittances increase in
response to natural disasters and the effect is large: a natural disaster in the home country
would increase remittances by 0.6 percentage points of GDP, a large effect relative to the
sample average of remittances of 4 percent of GDP (Table 2, Annex Table 3.2). Remittances
are also linked to the business cycle of the destination country, in particular they fall with a
rise in Hispanic unemployment in the U.S., though the effect is smaller than that of natural
disasters (a 5 percentage point fall in unemployment would result in an effect of the same
magnitude). It should however be added that the apparent higher responsiveness of
remittances to economic conditions relative to migration could in part be driven by the
migration data limitation discussed above. While remittances do not appear to respond to the
conflict variable that was an important driver of migration, this could be due to data
limitations as the breakdown of formal remittance sending channels during times of conflict
could mean that remittances are less well-recorded during these periods. Remittances, which
are measured in U.S. dollars, appear to be fixed in that currency (as indicated by the absence
of a significant effect of dollar exchange rate movements), and are not responsive to inflation
or simple business cycle fluctuations in growth in the home country.

As for migration, slower-moving ‘structural’ variables play a much smaller role. The
average annual increase in the migrant stock abroad, the average annual decrease in age
dependency or a (hypothetical) fall in the age of entry by one year would lead to an increase
in remittances of about 0.1 ppt of GDP. The increase in the level of development would have
 26

an opposite effect of a similar magnitude, while increasing urbanization would increase

remittances, but the effect is an order of magnitude smaller.

B. What explains the high cost of remittances?

Transaction costs absorb a large portion of remittances, reducing the money received
by migrants’ families, yet little is known about the drivers of these costs. The
characteristics of the market for remittance service providers, including the degree of
competition and the volume of remittances sent, have been shown to lower transaction costs
(e.g. Orozco (2006) and Beck and Soledad Martínez Pería (2011)). However, little has been
done to understand the role of sending and receiving country characteristics for remittances
transaction costs, despite the observed heterogeneity of costs when considering the same
sending or receiving country. Beck and Soledad Martínez Pería (2011) show that these
characteristics can be important drivers of transaction costs –higher incomes levels in both
sending and receiving countries increase remittance transaction costs as does the receiving
countries’ access to remittance service providers.19

Our empirical strategy examines the determinants of the cost of remittances at the level
of remittance corridors. The approach follows the novel work of Beck and Soledad
Martínez Pería (2011), exploiting data on the cost of remittances at the corridor level to
conduct a bilateral analysis of the determinants of the cost of remittances. The cost of
remittances is analyzed as a function of characteristics of both the sending and receiving
countries:

𝐶𝑖𝑗 = 𝛽0 + 𝜷𝟏 𝑺𝒆𝒏𝒅𝒊𝒏𝒈𝒊 + 𝜷𝟐 𝑹𝒆𝒄𝒆𝒊𝒗𝒊𝒏𝒈𝒋 + 𝜷𝟑 𝑿𝒊𝒋 + 𝑢𝑖𝑗 (2)

where 𝐶𝑖𝑗 is the cost of sending $200 US dollars (in percent of the amount sent) from country
i to country j. 𝑋𝑖𝑗 captures characteristics of the remittance corridor that may affect the cost
of remittances. These include the degree of competition in market for remittance service
providers and the importance of banks in the market. For both sending and receiving
countries, the importance of the economic and financial development, the exchange rate
regime, and access to financial services are considered as potential determinants of the cost
of remittances. The analysis is cross-sectional and undertaken for 2015, given the short time
horizon for which data on the cost of remittances is available.20

The analysis exploits recent improvements in monitoring the cost of remittances made
by the World Bank through its RPW database. The RPW database provides data on the
cost of sending and receiving remittances at the level of individual remittance service
providers for the world’s major remittance corridors.21 Equation 2 is estimated using data for
288 country corridors including 34 sending countries and 91 receiving countries (Annex
Table 1.2).22 This significantly expands the number of corridors covered in Beck and Soledad
19 Proxied by the share of the rural population.
20 The RPW database is currently available from 2011-2016.2015 is the last year of annual data available.
21 An important caveat is that the database includes data only from formal providers of remittance services.
22 Remittances service providers operating in Russia and the former Soviet Republics are excluded since they operate based

on the integrated payment systems of the former USSR and are not comparable to RSPs which incur high costs when having
 27

Martínez Pería (2011)’s analysis, which included 119 corridors. The variables included in the
regression and their sources are summarized in Annex Table 1.1. The database also includes
data across all types of remittance service providers including the MTOs and banks that
dominant the market for remittance services. This allows us to conduct the analysis averaging
across all providers and separately for MTOs and banks to assess whether the determinants
differ by type of service provider given the observed heterogeneity in costs across providers
(see Section II.D).

Greater competition in the market for remittance service providers, captured by the
number of providers by corridor, lowers transaction costs within LAC as well as
worldwide (Table 3). This effect seems to stem from MTOs’ costs rather than banks. This is
consistent with the notion that for banks transmitting remittances is a marginal line of activity
but for MTOs is a primary business activity. A more important role for banks in the market
for remittance transactions increases costs, again consistent with the view that remittance
transactions are a marginal product for banks and they are therefore likely to offer less
competitive prices. The worldwide regressions also indicate that a larger migrant stock
reduces the cost of remittances, with a stronger effect for banks than for MTOs.23

For the worldwide sample, source and recipient country characteristics also affect the
cost of remittances. The source country’s level of economic development appears to be a
more important driver of the cost of remittances than the receiving country’s, with a higher
per capita income in the source country reducing transaction costs. This contradicts evidence
from Beck and Soledad Martínez Pería (2011), suggesting that the relationship may have
changed over time towards a more important role for efficiency gains in financial
intermediation supported by economic development contributing to lower costs. While the
sample size is relatively limited, this effect appears to reverse for LAC, perhaps reflecting
some idiosyncrasies for the region given the importance of the U.S. as a source market for
the region’s remittances. However, financial development in both the source and recipient
countries tends to increase transaction costs but financial access in rural areas, proxied by the
geographical dispersion of the population in the source or receiving country, is insignificant.
Despite dollarized LAC economies benefiting on average from lower remittance costs, there
is no evidence that the broad exchange rate regime (fixed vs. floating) of the recipient
country affects the cost of remittances.

to bridge the national payment systems in two countries. This follows the methodology used by the World Bank to calculate
the global average total cost of remittances. Similarly, remittances service providers that do not disclose the exchange rate
applied to the transaction and thus classified by the World Bank as non-transparent are excluded from the analysis.
23 Following Beck and Soledad Martínez Pería (2011), the migrant stock is included as a proxy for the flow of remittances as

the migrant stock is less likely to be endogenous to the cost variable. The results are robust to the inclusion of remittance
flows instead of the migrant stock.
 28

Table 3. The Cost of Remittances: Determinants

Full Sample LAC MTOs Banks Full Sample LAC MTOs Banks
(1) (2) (3) (4) (5) (6) (7) (8)
Per capita GDP receiving country (ln) 0.236 -0.234 0.782*** -0.255 0.0726 1.414 0.0726 0.0514
(0.351) (0.722) (0.00714) (0.741) (0.933) (0.303) (0.933) (0.984)
Per capita GDP source country (ln) -0.981** 1.607 -0.263 -1.211* -3.015*** 2.587** -3.015*** -4.514**
(0.0281) (0.182) (0.539) (0.0884) (0.00145) (0.0263) (0.00145) (0.0195)
Fixed exchange rate -0.0767 -0.632 0.0883 0.388 0.324 1.129 0.324 2.545
(0.853) (0.495) (0.842) (0.719) (0.614) (0.237) (0.614) (0.176)
Number of remittance service providers -0.0915*** -0.267*** -0.112*** 0.0425 -0.120*** -0.142* -0.120*** -0.0465
(0.00482) (0.00517) (0.000612) (0.538) (0.00483) (0.0545) (0.00483) (0.591)
Importance of banks in remittance corridor 4.748*** 4.153 -0.830 5.195* 2.331 6.091* 2.331 2.615
(in percent of total providers) (7.92e-06) (0.276) (0.427) (0.0660) (0.110) (0.0767) (0.110) (0.607)
Rural population receiving country (in percent of
total population) 0.0343 -0.0396 0.0343 0.109
(0.188) (0.515) (0.188) (0.156)
Rural population source country (in percent of
total population) -0.0633 -0.110 -0.0633 -0.0997
(0.139) (0.276) (0.139) (0.223)
Financial development index receiving country 6.713** -0.989 6.713** 19.96**
(0.0264) (0.736) (0.0264) (0.0470)
Financial development index source country 3.311** -4.430 3.311** 8.879**
(0.0493) (0.201) (0.0493) (0.0436)
Migrants (ln) -0.763*** 0.581 -0.673*** -1.295*** -0.949** 0.229 -0.949** -2.165**
(6.46e-06) (0.142) (0.000246) (0.000251) (0.0105) (0.707) (0.0105) (0.0153)
Constant 22.20*** -3.991 18.65*** 31.20*** 29.02*** -2.728 29.02*** 41.65***
(0) (0.608) (0) (3.52e-08) (2.74e-06) (0.785) (2.74e-06) (0.00173)

Observations 277 38 275 157 159 29 159 100

R-squared 0.292 0.291 0.137 0.201 0.308 0.535 0.308 0.277
Robust pval in parentheses
*** p<0.01, ** p<0.05, * p<0.1

C. How do migration and remittances affect growth?

Emigration and receipts of remittances are likely to have opposite effects on growth in
the home country. On the one hand, emigration is likely to have a negative effect on growth
in the home country as the departure of people of working age reduces the labor force. This
loss could be significant in case of brain drain, as the loss of high-skilled workers could
entail negative externalities for the broader economy, including less scope for innovation.
Accordingly, the negative effects of emigration would likely be most pronounced in the
Caribbean and South America, which tend to have relatively large share of high-skilled
emigrants. The receipt of remittances could also aggravate the decline in labor supply, as
recipients substitute labor income with remittance income. On the other hand, remittances
could have a positive effect on growth by providing financial resources for investment and
education and through migrant networks that can foster trade and investment.24 Such positive
effects would likely be largest in Mexico and CAPDR, which receive the most remittances as
a share of GDP.

It is difficult to empirically estimate the effect of emigration and remittances on per

capita growth. The existing literature has mostly focused on the role of remittances, and is
inconclusive. Looking at different samples of countries and time periods, different definitions
of remittances and varying control variables, some studies found positive effects of
remittances on growth, while others found negative or insignificant effects. Most studies
24For example, Edwards and Ureta (2003) find that remittances have a significant positive impact on schooling retention in
El Salvador.
 29

focused on the effects of remittances, but often did not control for migration, and did not
explicitly consider their joint effect. Chami, Fullenkamp, and Jahjah (2003) found that the
workers’ remittances–to–GDP ratio either was not significant or was negatively related to
growth, while annual changes in the workers’ remittances–to–GDP ratio were found to have
negative and significant effects on growth. IMF (2005) found no statistically significant
effect of total remittances on economic growth. AFD (2007) noted that (average or initial)
remittances had a positive and significant effect on growth, though the effect was no longer
significant when relying on instrumental variables estimation. Giuliano and Ruiz-Arranz
(200) looked at five-year averages for all variables to smooth out cyclical variations and did
not find remittances to be significantly related to growth. Catrinescu and others (2006)
introduced institutional variables as additional controls and found some evidence of a
positive relationship between growth and total remittances, although this relationship was not
very robust and relatively mild. World Bank (2006) found a consistently positive, though
small effects of remittances on GDP growth. Barajas and others (2009) found a positive and
significant effect only when the estimation excluded investment and in the absence of
country fixed effects. Chami and others (2008) found that when endogeneity is controlled
for the effect of remittances was negative and significant, though in many of the
specifications the effect was not significant.

In any case, two-way causality poses a serious problem. Emigration and remittances could
respond to economic conditions as well as affect them (in line with the channels described
above). Simple ordinary least squares panel regressions would overlook this two-way
causality. Some of the literature has thus tried to mitigate this concern by relying on
instrumental variables approach, though results remain inconclusive. This paper, in contrast,
aims to estimate a net effect of both emigration and remittances on growth, relying on OLS
as well as an instrumental variables approach. The instrumental variables approach used here
is closest to that in Barajas and others (2009) and Abdih and others (2009), though with the
crucial distinction that they do not control for migration stocks or migration flows.

The joint effect of migration and remittances on growth is examined here using a cross-
country panel fixed effects regression similar to equation (1). The dependent variable is
real per capita GDP growth.25 The exogenous growth determinants, 𝑿𝒊𝒕 , considered include
real GDP growth in the U.S., FDI as a share of GDP, export growth, change in the terms of
trade, country risk, the stock of emigrants as a share of the home population. The endogenous
growth determinants, 𝒁𝒊𝒕 , include the flow of migrants, remittances as a share of GDP,
government spending as a share of GDP, and M2 as a share of GDP. These endogenous
variables are instrumented using their regional averages, the share of rural population and
unemployment in the destination countries. Additional details on the estimation strategy can
be found in Annex 2.26

25 Effects on GNI, which includes remittances and may be more closely related to per capita welfare were also examined:
here, as for GDP, remittances still have a significant positive effect on growth, while the coefficients on migration are still
negative but no longer significant.
26 Regressions are estimated on the period 1980-2015 (unbalanced sample). IV regressions are implemented using 2SLS and

include country fixed effects but not time fixed effects as they include controls such as growth in the United States. First
stage F statistics exceed 10 for all specifications except the Caribbean, where sample sizes are particularly small. Results are
 30

As expected, our estimation results suggest that outward migration has a negative effect
on growth, and this seems most pronounced in the subregions experiencing brain drain
(Annex Table 3.4). Remittances seem to have positive (though not always statistically
significant) growth effects, that are largest in the high-remittance-receiving subregions. The
effects of migration and remittances are of a (perhaps surprisingly) large magnitude: an
increase in the migrant flow out of a LAC country by 0.1 percent of the population would
reduce growth by 1.4 percentage points, the effect of remittances on growth is almost one-
for-one. However, the instrumented regressions remove some of the variation in migration
and remittance flows that occurs in response to growth fluctuations and only pick up
exogenous variation. Simple OLS regressions with country fixed effects point to much
smaller effects, as expected: while remittances increase growth, they are likely acyclical or
counter-cyclical, thus mitigating the overall effect (Annex Table 3.3). However, these
separate effects are difficult to quantify with precision given that migration and remittances
are highly correlated (i.e. remittances cannot occur without migration). Furthermore,
estimates for South America conceal a large degree of heterogeneity within this subregion:
while emigration and remittances have limited importance for some countries, Paraguay and
Uruguay have large stocks of emigrants, and remittances are significant for Bolivia and
Ecuador. However, restricting the sample to these four countries does not materially change
the estimation results.27
Emigration and remittances together appear to have had a small and ambiguous effect
on real per capita GDP growth in the LAC region, but the effect has varied across sub-
regions, likely reflecting the different characteristics of migrants. Figure 19 shows the
estimated cumulative joint impact on growth of the actual increases in the stock of emigrants
and in remittances over 2003-2013, using the estimated coefficients and actual increases in
the stocks of emigrants and in remittances for each of the subregions over this period. Given
the complications due to two-way causality, the figure shows ranges rather than point
estimates.28 This joint or net effect has likely been negative for the Caribbean and South
America, with the former experiencing large emigrant outflows and both characterized by
brain drain and relatively smaller remittance receipts. On the other hand, the net impact
appears small and possibly positive for CAPDR countries, which receive much higher
remittances.29

robust to controlling for investment and lagged real GDP per capita. Unfortunately, information on ages and skill levels of
emigrants is not available for sufficiently long enough time periods to be included in the regressions; cross-sectional
variation in these factors would be mopped up by country fixed effects.
27 Results available upon request.
28 The ‘true’ joint effect of migration and remittances on per capita GDP growth is likely somewhere between the

instrumented effects (which try to remove all reverse causality effects, but only pick up variation in the instruments) shown
in the figure as the bottom of the range and the ordinary least squares effects (which confound some of the true effect with
reverse causality) corresponding with the top of the range.
29 The effect is around zero for Mexico, but this is not strictly comparable to other results as it is estimated purely from time

series variation and the data sample is particularly small. Most of this effect is driven by migration, with a much smaller
contribution from remittances (Annex Table 3.4), though these are difficult to separate empirically. The positive effect of
remittances on growth here is estimated while controlling for migrant stocks and migration flows, and is thus relative to the
counterfactual of ‘migration without remittances’. The positive effect of remittances on growth also holds up when
examining GNI instead of GDP.
 31

The net effect of migration and remittances Figure 19. Net Effect of Migration and Remittances on Growth,
Short Term and Long Term Effects
is likely to be more negative in the longer 4.00

term. To examine the net effect of emigration 2.00

0.00
and remittances over the longer term, the same
-2.00
specification is estimated using 5-year
-4.00
averages to allow for lag times and dynamic -6.00
effects. While the small sample size limits the -8.00 ST - IV
ST - FE
robustness of these regressions, the results -10.00 LT - IV
LT - FE
suggest that although the ordering of the -12.00
LAC Latin South Carribbean Mexico Central
subregions remains similar, the net effect is America America America,
Panama,
more negative in the longer term (Figure 19). Dom. Rep.
Notes: Based on coefficient estimates from fixed effects and instrumental variables
Accordingly, remittances (and migration) regressions, changes in migrant stocks and remittances as a percent of GDP in 2003-2013.
Short term refers to annual regressions, long term to 5-year averages.
appear unlikely to act as drivers of durable
growth.30

D. Are remittances a macroeconomic stabilizer?

Remittances are often seen as a source of economic stabilization, and this feature could
offer important benefits for migrants’ home countries even if emigration and
remittances may, on balance, have unclear or negative net implications for growth. The
analysis in this section suggests that remittances have indeed contributed to macroeconomic
stabilization within the LAC region. Beneficial effects are found especially for the Caribbean
and CAPDR, where they typically increase consumption smoothing, help generate fiscal
revenues, and support financial stability, while there appears to be little evidence of possible
adverse “Dutch disease” effects given that their impact on the real exchange rate and
inflation tends to be minor. In addition, whereas poorer households are more likely to
receive remittances, remittances can also help lower poverty as well as inequality – and all
the more so in the wake of negative shocks.

Do remittances facilitate consumption risk-sharing?

Figure 20. Remittances and Natural
Remittances can help smooth consumption in the 6
Disasters
home country as emigrants send additional funds t-1 natural disaster (t) t+1
Remittances (percent of GDP)

5
to cushion economic shocks. This stabilizing
property of remittances is illustrated in Figure 20, 4

which shows that remittances (as a share of GDP) 3

jump when a natural disaster hits the remittances-
2
recipient country.31 This effect appears to be
stronger for LAC than for emerging market and 1

developing economies in general, and seems to be 0

especially important for the Caribbean—the country EMDE LAC Caribbean

group that is particularly susceptible to large natural Source: Emergency Events Database and Fund staff calculations.

disasters—where the average remittance-to-GDP

30 It should be added that the overall welfare effect is likely to be positive for the migrants and their dependents in the home
country, even if the effect on GDP growth is negative.
31 For example, remittances in Grenada increased from 2 percent of GDP in 2003 to 4 percent of GDP in 2004, the year

Hurricane Ivan hit the island, and then normalized to the 2003 level in the following years.
 32

ratio increased from 4.4 percent of GDP in the years prior to natural disasters to 5.4 percent
in the years with natural disaster.

Remittance flows are relatively large, resilient and less volatile compared to other
sources of external financing.32 They are larger than any other external inflow for CAPDR
and the Caribbean (Figure 21). For South America, private capital inflows (excluding foreign
direct investment) have typically been larger than remittances, but remittances flows have
been a more stable source of external financing for all subregions in LAC. This relative
stability can be partly attributed to the lower
Figure 21. LAC: Remittances and Other Inflows
correlation of remittances to economic cycles in (Percent of GDP)
5
the recipient country. More generally,
33
Remittances
4
remittances are often found to be FDI
Non-FDI capital flow
countercyclical with respect to the recipient 3
Official aid
country business cycle (Spatafora, 2005; 2

Frankel, 2011; Bettin, Presbitero, and 1

Spatafora, 2015), though other studies indicate 0

that they can be countercyclical as well as -1

procyclical (Sayan, 2006; Chami et al., 2008) or -2

predominantly acyclical (De et al., 2016). As 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013

Sources: World Bank WDI, IMF BOPS and WEO

such, they have the potential to complement one
key role assigned to financial flows, namely to support aggregate consumption smoothing.

Remittances can foster consumption smoothing not only through their direct
countercyclicality, but also by supporting financial inclusion and access to credit.
Remittances allow recipients to save in good times and tap into these resources when
domestic income contracts. They also facilitate access to credit by strengthening borrowers’
capacity to repay. For instance, Guiliano and Ruiz-Arranz (2009) show that remittances
provide an alternative way to finance investment and help overcome households’ liquidity
constraints. In this way, households receiving remittances can vary the share of their receipts
used for consumption.

The resilience and possible countercyclical nature suggest that remittances can play a
similar role as financial flows for consumption smoothing through risk-sharing. The
usual argument states that as long as output fluctuations are not perfectly correlated across
countries, financial integration can help delink domestic consumption growth from domestic
output growth through the holding of foreign financial assets (Lewis, 1999; Kose, Prasad,
and Terrones, 2009).34 These conjectures are also related to the empirical evidence that
remittances contribute to reducing consumption instability (Combes and Ebeke, 2011) and
the findings in section III.A and Figure 20 that remittances increase significantly in response
to natural disasters affecting the recipient country. In this context, earlier empirical evidence
indicates that remittances indeed may help improve cross-country consumption risk-sharing
(Hadzi-Vaskov, 2006; Balli and Rana, 2015; De et al., 2016).

32 See Chami et al. (2008) and Balli and Rana (2015).

33 However, as demonstrated by the drop in remittances after the global financial crisis, economic cycles in remittance
source countries can have important implications for remittances (see Box 4).
34 For a review of the literature and findings on risk-sharing see Kose, Prasad, and Terrones (2009).
 33

We investigate the impact of remittances on consumption smoothing through several

methods. First, we explore their impact on overall income volatility. Second, we check
whether there is a relationship between average levels of remittances (as share of GDP) and
degree of consumption risk-sharing. Third, we formally test for the impact of remittances on
consumption risk-sharing using a standard approach employed in the literature.

Remittances seem to lower income volatility in the home country. Figure 22 demonstrates
that for most countries in the LAC region, overall income, including remittances, is less
volatile than domestic income (measured using international prices). In addition, this effect is
more important for countries in LAC than for EMDEs in general. Beyond the above-
mentioned countercyclicality of remittances, this stabilizing effect also reflects the finding
that remittances to LAC are typically set in terms of U.S. dollars. Hence, while, for example,
a sharp depreciation would reduce the value of domestic income in terms of international
prices, remittance income would cushion this effect even if it is not increased in terms of
U.S. dollars.

Figure 22. Remittances and Income Volatility

1. EMDE 2. LAC 3. Caribbean
1.5 1.5 1.5

Income volatility
Income volatility

Income volatility

1 1 1

0.5 0.5 0.5

0 0 0
0 0.5 1 1.5 0 0.5 1 1.5 0 0.5 1 1.5
GDP volatility GDP volatility GDP volatility

Sources: Fund staff calculations.

Note: Standard deviations of income (domestic income plus remittances) are plotted on the vertical axis and GDP standard deviations
are plotted on the horizontal axis. Dots below the 45-degree line indicate that remittances lower income volatility.

Higher remittances (as a share of GDP) are associated with more consumption
smoothing in the face of idiosyncratc shocks to output. Specifically, remittances help
delink country-specific consumption growth from country-specific output growth.
The relationship between idiosyncratic (country-specific) private consumption and
idiosyncratic (country-specific) output growth is estimated in a standard risk-sharing
specification for each country i as follows:

Δ𝑐̃𝑖𝑡 = 𝛽0 + 𝛽1 𝑅𝑖𝑡 + 𝛾1 Δ𝑦̃𝑖𝑡 + 𝜀𝑖𝑡 (3)

where Δ𝑐̃𝑖𝑡 = Δ𝑐𝑖𝑡 − Δ𝑐̅𝑡 , Δ𝑦̃𝑖𝑡 =Δ𝑦𝑖𝑡 − Δ𝑦̅𝑡

Δ𝑐𝑖𝑡 is real private consumption growth for country i at time t, Δ𝑦𝑖𝑡 is for real GDP growth
for country i at time t, Δ𝑐̅𝑡 and Δ𝑦̅𝑡 are the world variables, and Δ𝑐̃𝑖𝑡 and Δ𝑦̃𝑖𝑡 are the
idiosyncratic ones. In equation 3 the coefficient 𝛾1 measures the degree of consumption risk-
sharing: coefficient that is not significantly different from zero suggests perfect consumption
risk-sharing as idiosyncratic output shocks do not result in shocks to idiosyncratic
 34

consumption. Figure 23 shows the relationship between the degree of consumption

smoothing, as measured by 𝛾1 from the time series country-specific regressions from
equation (3), and 𝑅̅𝑖 – the average ratio of remittances to GDP for country i. Consumption-
growth correlations are lower for countries with higher levels of remittances. Again, these
effects seem relatively pronounced for LAC, particularly for the Caribbean.35 Besides the
high remittances-to-GDP ratios, the strong effects found for Caribbean countries likely
reflects their susceptibility to natural disasters and the countercyclical response of
remittances to such events.

Figure 23. Remittances and Deviation from Perfect Risk Sharing

1. EMDE 2. LAC 3. Caribbean
2.5 1.5
1.4
2 1.2
1
1
Slope coefficient

1.5 Slope coefficient

Slope coefficient
0.5 0.8
1
0.6
0.5 0 0.4
0 0.2
-0.5 0
-0.5
-0.2
-1 -1 -0.4
0 2 4 6 8 10 12 0 2 4 6 8 10 0 1 2 3 4 5 6
Average remittances (percent of GDP) Average remittances (percent of GDP)
Average remittances (percent of GDP)

Sources: Fund staff calculations.

Note: Slope coefficients obtained from time series country-specific regressions of idiosyncratic consumption growth on idiosyncratic
output growth are plotted on the vertical axis and average levels of remittances as a share of GDP are plotted on the horizontal axis. A
negative relationship suggests that higher average remittances are associated with lower deviations from perfect risk-sharing.

Finally, our more formal approach follows a standard risk-sharing specification. We

investigate the relationship between idiosyncratic (country-specific) private consumption and
idiosyncratic (country-specific) output growth, and the impact of remittances on this
relationship. We employ the following regression specification:36

Δ𝑐̃𝑖𝑡 = 𝛽0 + 𝛽1 𝑅𝑖𝑡 + 𝛾1 Δ𝑦̃𝑖𝑡 + 𝛾2 𝑅𝑖𝑡 Δ𝑦̃𝑖𝑡 + 𝛾3 𝐾𝐴𝑖𝑡 Δ𝑦̃𝑖𝑡 + 𝛾4 𝐹𝐼𝑖𝑡 Δ𝑦̃𝑖𝑡 + 𝜀𝑖𝑡 (4)
where Δ𝑐̃𝑖𝑡 = Δ𝑐𝑖𝑡 − Δ𝑐̅𝑡 , Δ𝑦̃𝑖𝑡 =Δ𝑦𝑖𝑡 − Δ𝑦̅𝑡

where Δ𝑐𝑖𝑡 is real private consumption growth for country i at time t, Δ𝑦𝑖𝑡 is for real GDP
growth for country i at time t, Δ𝑐̅𝑡 and Δ𝑦̅𝑡 are the world variables, and Δ𝑐̃𝑖𝑡 and Δ𝑦̃𝑖𝑡 are the
idiosyncratic ones, 𝑅𝑖𝑡 is the ratio of remittances to GDP, 𝐾𝐴𝑖𝑡 is the index of de jure capital
account openness from Chinn and Ito (2006) and 𝐹𝐼𝑖𝑡 stands for de facto indicators of
financial integration from Lane and Milesi-Ferretti (2007).

The degree of risk-sharing is captured by the coefficients in front of idiosyncratic

output. If the sum of the coefficients is not significantly different from zero, then
idiosyncratic consumption is independent of country-specific output fluctuations and
aggregate consumption risks are perfectly shared across countries. 𝛾2 measures the extent to
which remittances facilitate risk-sharing by delinking country-specific consumption from

35
The relationships are not statistically significant, however, and the sample sizes are quite limited.
36
The empirical specification follows Sorensen et al. (2007) and similar specifications that include remittances in Hadzi-
Vaskov (2006), and De et al. (2016).
 35

output. Hence, a significant negative value for the coefficient 𝛾2 would indicate that
remittances help lower deviations from perfect risk-sharing. In a similar vein, the coefficient
𝛾3 measures the extent to which other channels, such as financial integration, facilitate
consumption risk-sharing.

Estimation results suggest that remittances improve consumption risk-sharing. In line

with other studies in the literature, the results in Table 4 convey two main general
conclusions: consumption risk-sharing across countries is far from perfect as the coefficient
𝛾2 in front of idiosyncratic output growth is significantly different from zero for the world as
a whole, the emerging market and developing economies (EMDEs) and all subgroups of
EMDEs (with and without accounting for different indicators of financial indicators); and
remittances typically facilitate risk-sharing as the coefficient in front of the interaction terms
is generally negative and significant for several country groups37.

Remittances seem to be more important as a channel of risk-sharing for LAC than for
other emerging market regions. The coefficient in front of the interaction term is
significant and negative for LAC in all specifications. Moreover, LAC is the only region for
which this terms is significant in the baseline specification that accounts for financial
integration. 38 A closer look at the results for subgroups of countries within LAC shows that
the strength of this effect is primarily explained by the Caribbean.

Table 4. Global Consumption Risk-Sharing (Panel Regressions)

World EMDEs LAC SSA CIS EM Asia LA Caribbean
Remittances 0.000509 0.000513 -0.000278 -0.000226 0.000162 -2.73e-05 -2.31e-05 -0.00151
(0.480) (0.515) (0.806) (0.951) (0.914) (0.975) (0.974) (0.536)
Δŷ 0.867*** 0.895*** 0.999*** 0.815** 0.829*** 0.810*** 0.731*** 1.290***
(0) (0) (1.35e-09) (0.0119) (0.000207) (1.01e-06) (0) (0.000926)
Remittances*Δŷ -0.0298** -0.0298** -0.0428* -0.0309 0.0116 -0.00883 0.0222 -0.0718*
(0.0118) (0.0216) (0.0565) (0.519) (0.731) (0.551) (0.283) (0.0964)
Financial openness (de jure)*Δŷ -0.0557 -0.0493 -0.0302 0.0443 -0.360** 0.206*** -0.0364 0.0516
(0.140) (0.253) (0.648) (0.769) (0.0171) (0.00810) (0.305) (0.733)
Financial integration (de facto, FDI)*Δŷ 0.0826* 0.0989 -0.0215 0.399* -0.0424 -0.0791 -0.00519 -0.132
(0.0795) (0.122) (0.781) (0.0889) (0.917) (0.633) (0.865) (0.763)
Financial integration (de facto, portfolio)*Δŷ -0.244* -0.371** -0.149 -1.261* -1.254 -0.301 0.522** -0.217
(0.0745) (0.0171) (0.476) (0.0570) (0.510) (0.420) (0.0456) (0.809)
Constant -0.0126*** -0.0132*** -0.00750 -0.00765 0.0142 -0.00880 -0.0134*** 0.00222
(2.95e-05) (0.000443) (0.195) (0.483) (0.170) (0.191) (2.50e-05) (0.880)
Observations 2,373 2,012 679 439 84 279 395 284
R-Squared 0.118 0.113 0.094 0.114 0.308 0.177 0.365 0.053
Countries 138 117 29 36 7 16 17 12
Note: The table contains results from panel regressions with country-specific and time fixed effects. The dependent variable is idiosyncratic
real consumption growth, and Δŷ is idiosyncratic real output growth; both of them are calculated as differences between country-specific and
world growth rates. Remittances stands for remittances as a share of GDP, Financial openness (de jure) stands for the index of de jure capital
account openness from Chinn-Ito (2006), while Financial integration (de facto) refers to de facto financial integration measured by FDI and
equity portfolio and is retrieved from the updated and extended version of the dataset by Lane and Milesi-Ferretti (2007). P-values are
reported in parentheses, and significance at 10, 5, and 1 percent is denoted by *, **, and ***, respectively.

Remittances account for a significant portion of overall risks shared in LAC, and
especially in the Caribbean. Figure 24 compares the importance of remittances relative to
other channels of risk-sharing, such as de jure capital account openness and de facto financial

37Results from specifications without financial integration interaction terms are presented in the appendix.
38The coefficient for the countries from the Commonwealth of Independent State (CIS) is significantly negative and of
similar magnitude as for LAC in the preview specification, that excludes the financial integration terms.
 36

integration. The calculated portion of risks shared through alternative channels are based on
the estimation results of the risk-sharing specification (equation 4) presented in Table 4. 39
The estimates suggest that remittances account for a larger share of total risks shared in LAC
than in EMDEs in general. Moreover, remittances seem to be especially important for the
Caribbean, where they contribute more to risk-sharing than all other channels combined.
Besides the high remittance-to-GDP ratios in the Caribbean, these findings can also be
explained by the larger output fluctuations that the Caribbean countries face due to their
higher susceptibility to natural disasters.40 Further analysis sheds light on the consumption-
smoothing impact of remittances taking into account the fiscal stance and finds that
remittances and fiscal policy may act as substitutes (Box 3 and Beaton, Cevik and Yousefi
forthcoming).

0.6
Figure 24. Portion of Total Risks Shared
Rest
0.5 Remittances (BOPS)

0.4

0.3

0.2

0.1

0
EMDE LAC Caribbean
Note: Estimates about the portion of total risks shared are based on region-specific
coefficients obtained from panel regressions of idiosyncratic consumption growth on
idiosyncratic output growth and its interactions with indicators for remittances, capital
account openness index (Chinn -Ito) and de facto financial integration measures (Lane -
Milesi-Ferretti) over the period 1980-2011.

Focusing on regional rather than global risk-sharing, remittances also play an

important role for various sub-regions within LAC. One may argue that many
countries/regions are hindered in sharing risks globally due to numerous obstacles to trade
and financial integration. Hence, the more feasible option for them will be to share
macroeconomic risks within their regions, where obstacles to integration may be important.
Annex Tables 3.6 and 3.7 present findings from regressions that replace ‘the world’ with the
Western Hemisphere as the relevant aggregate in the definition of idiosyncratic growth
rates.41 These results imply that remittances in LAC are even more important for sharing
risks within the Hemisphere than globally – the coefficient in front of the interaction terms is
negative and statistically significant at 1 percent across all specifications.

39 The portion of risks shared through remittances is calculated as −𝛾2 ̅̅̅̅

𝑅𝑖𝑡 , where 𝛾2 is the region-specific coefficient in front
of the interaction term, and ̅̅̅̅
𝑅𝑖𝑡 is the corresponding region-specific average ratio of remittances to GDP.
40 The high sensitivity of idiosyncratic output to global output and regional output fluctuations is captured by coefficients

above unity in Tables 6 and 7, respectively.

41 The Western Hemisphere is chosen here due to the important trade and financial linkages across the countries of LAC,

Canada, and the U.S. Results from regressions that employ LAC as the relevant aggregate imply very similar conclusions
(results are available upon request).
 37

Box 3. Smooth Operator: Remittances and Fiscal Policy

The consumption-smoothing effect of workers’ remittances varies with the fiscal policy
stance and is pronounced in high-remittance countries. In related work, Beaton, Cevik,
and Yousefi (forthcoming), estimate the standard consumption risk-sharing equation for a
sample of 149 countries, and investigate the consumption smoothing impact of remittances
during periods of fiscal consolidations and fiscal shocks. Fiscal consolidation (expansion) is
defined as narrowing (widening) of the cyclically adjusted primary budget balance (CAPB),
and fiscal shock is measured as either narrowing or widening of CAPB of at least 1.5
percentage points, consistent with the definition of fiscal shocks proposed by Alesina and
Ardagna (2010). The empirical results indicate that the consumption-smoothing effect of
remittances is negligible during periods of fiscal expansion while they significantly help
stabilize consumption during periods of fiscal consolidation and fiscal shocks. These findings
are pronounced in high-remittance countries, those with remittances more than the median
level (1.5 percent of GDP) during 1990-2014. Furthermore, this pattern is observed
consistently regardless of the level of income and in most regional groups of countries
especially in the Latin America and the Caribbean. The study argues that households with
high remittance receipts can smooth consumption during economic austerity through various
channels: intertemporal savings, allocating higher proportion of remittances to consumption,
or temporarily receiving higher remittances from the family members abroad.
Box Figure 3.1. β2
(Consumption Smoothing of Remittances: Coefficient for R * ∆y)
Full Time Period Fiscal consolidation Fiscal expansion Fiscal shock
0

-1

-1.4
-2
-1.9
***
-2.4 **
-2.6
-3 **
-2.9
**
-3.5
-4 All Countries ***
High Rem. -4.2 **
-4.5
-5

The risk sharing equation is Δ𝑐̃𝑖𝑡 = 𝛽0 + 𝛾𝑅𝑖𝑡 + 𝛽1 Δ𝑦̃𝑖𝑡 + 𝛽2 𝑅𝑖𝑡 Δ𝑦̃𝑖𝑡 + 𝛾𝑿𝑖𝑡 + 𝛽3 𝑋𝑖𝑡 Δ𝑦̃𝑖𝑡 + ∆𝜀𝑖𝑡 , where Δ𝑐̃𝑖𝑡 = ∆𝑐𝑖𝑡 −
∆𝑐̅𝑡 𝑎𝑛𝑑 Δ𝑦̃𝑖𝑡 = ∆𝑦𝑖𝑡 − ∆𝑦̅𝑡 .
∆𝑐𝑖𝑡 (∆𝑐̅𝑡 ) denotes private consumption growth in country i (world) at time t, and ∆𝑦𝑖𝑡 (∆𝑦̅𝑡 ) is the real GDP per capita growth. 𝑅𝑖𝑡 represents
remittances as a share of GDP, and 𝑿𝑖𝑡 are standard control variables including financial openness and trade openness. A negative and
statistically significant 𝛽2 would imply that migrant remittances delink fluctuations in consumption from that in income, and hence smooth
consumption.

Remittances and fiscal revenues

Apart from the smoothing of private consumption, remittances can foster economic
stabilization through the fiscal accounts. Remittances can help raise fiscal revenues even
though they typically are not taxed directly, given that spending out of remittances is part of
 38

the base for indirect taxation.42 Furthermore, as documented above, remittances tend to
support short-term output growth (even if the joint effect including emigration may be
ambiguous), and thereby fiscal revenues. The associated increase in fiscal space, in turn,
enhances the scope for stabilization through countercyclical fiscal policies. Ebeke (2010) for
example, finds that remittances significantly increase both the level and stability of the
government revenue ratio in the remittance-receiving developing countries that have adopted
a VAT. Abdih and others (2012) conclude that, in a sample of 17 countries in the Middle
East, North Africa, and Central Asia, remittances are positively associated with the overall
tax ratio as well as with the share of sales and trade tax revenues. Largely reflecting their
potential revenue-supporting role, remittances are also believed to substantially contribute to
public debt sustainability (see Abdih and others (2009)). The fiscal role of remittances across
Latin American countries has not yet been explored and we aim to fill this gap.

As in other subsections, our preferred results are those of instrumental variable

regressions to control for endogeneity of remittances, but fixed effects regressions are
also run for robustness purposes. Based on equation (1), where the dependent variable,
𝑦𝑖𝑡 , is the revenue/GDP ratio, 𝛼𝑖 are country fixed effects, 𝑿𝒊𝒕 is a vector of exogenous
variables including level of real GDP per capita, real GDP growth in the U.S., FDI as a share
of GDP, the stock of emigrants as a share of the home population, and share of the rural
population (for a full list please see Annex 2) and 𝒁𝒊𝒕 are the endogenous variables:
remittances as a share of GDP and real per capita GDP growth, instrumented using their
regional averages, unemployment in the destination countries, and terms of trade changes
(for details see Annex II, Table 2.1). Additional controls that were used to check robustness
included those typically used in revenue regressions, such as the level of government debt as
percent of GDP, import growth, agriculture share, and sub-components of the institutional
quality variables relating to political risk, corruption, economic risk, government stability,
and law and order.

Remittances help mobilize fiscal revenues in LAC, particularly for large remittance-
receivers. A higher remittance-to-GDP ratio is associated with a higher revenue-to-GDP
ratio and the positive impact is significant for the Caribbean and CAPDR. In an instrumental
variable specification, a higher remittance-to-GDP ratio by 1 percentage point is associated
with an increased revenue/GDP ratio of 0.4 percentage point in Central America and 1.2
percentage point in the Caribbean (Table 5, Annex table 3.8). Robustness checks (which the
authors can provide upon request) confirm the positive sign of the coefficients for these two
groups of countries, but indicate some uncertainty with respect to their numerical values.43

Changes in remittances dynamics have significantly impacted revenue developments in

some country sub-groupings. Our estimates imply that, for example, the actual increase in

42 The few countries that tried to tax remittances directly later repealed these taxes. Examples include Vietnam, Tajikistan,
and the Philippines (see Ratha (2017)).
43 As with the above regressions on the determinants of growth, numerical estimates of the coefficients differ somewhat

between the ordinary least squares and instrumental variables regressions, as well as depending on the set of control
variables used. The effects of remittances on revenues are almost always positive and statistically significant from zero for
the two sub-groups of large remittance receivers. However, the coefficients seem to be more precisely estimated (e.g.,
falling within a relatively narrow range) for CAPDR and are more widely dispersed for the Caribbean.
 39

the remittance-to-GDP ratio since 2000 in CAPDR, which reflected continued substantial
emigration from the region to the United States, accounted for an increase in fiscal revenues
of 1 percent of GDP. Incidentally, the increase in the region’s revenue-to-GDP ratio since
2000 is fully concentrated in the group of five countries that are receiving significant
remittances (e.g., excluding Costa Rica and Panama).44 On the other hand, the drop in
remittances associated with the global financial crisis is estimated to have dented fiscal
revenues against the counterfactual (see Box 4)). Further regressions indicate that in the
Caribbean higher remittances have been associated with improved fiscal balances, while in
CAPDR they are associated with higher expenditures and no significant effect on fiscal
balances.45 This finding suggests that in CAPDR, revenues generated by remittances have
helped create scope for additional spending.

Table 5. Effects of Remittances on Revenue (IV Regressions)

Central America,
Latin America
Emerging South Panama, and the
World and the Latin America Carribbean Mexico
Markets America Dominican
Caribbean
Republic

Revenue/GDP
Remittances/GDP 1.152** 0.676 0.440 0.251 3.190 1.157** 1.303** 0.393**
(0.496) (0.749) (0.311) (0.489) (2.136) (0.558) (0.546) (0.156)
Number of obs. 2362 619 568 399 221 169 24 154
Adjusted R2 0.790 0.845 0.657 0.632 0.371 0.540 0.782 0.821

Box 4. Remittances and their Effects During the Global Financial Crisis
The global financial crisis saw a significant
Box Figure 4.1. Change in Remittance Flows,
contraction of remittance inflows to LAC 2008-2010 Relative to 2007
countries. Between 2007 and 2008–10, all key (Percentage points of GDP)
0.0
LAC country sub-groupings experienced a fall
-0.2
in remittance inflows, with the largest drop -0.4
observed in CAPDR countries (by about 1 -0.6
percent of GDP). This behavior of remittances -0.8
-1.0
contrasted with earlier indications that
-1.2
remittances could play a -1.4
stabilizing/countercyclical role for recipient LAC Latin South Carribbean Mexico CAPDR
America America
economies. This episode illustrated that
46
Source: World Bank and IMF WEO.
extensive reliance on remittances can be risky,
especially when most migrants reside in a single country.

44 Obviously, the cumulative increase in revenues reflected diverse, often country-specific, factors, including revenue
measures implemented by the authorities at various times. Still, the evidence of a link between remittances and fiscal
revenues in most CAPDR countries is extensive and includes high-frequency correlations in country-level time-series
regressions (not shown).
45 These results are however less robust to alternative specifications. Results available upon request.
46 See for example Chami and others (2008).
 40

Box 4. Remittances and their Effects During the Global Financial Crisis
(Continued)

The drop in remittances appears to have been mostly driven by an increase in

Hispanic unemployment in the U.S. The significant contraction in remittances inflows
during the crisis was followed by a recovery. This appears to be very closely related to the
increase in Hispanic unemployment in the U.S., which by itself can explain most of the
observed decline in remittances.

Box Figure 4.2. Hispanic Unemployment in the U.S. and Remittances

Effects of the Increase in U.S. Hispanic Unemployment on Remittances in
Hispanic Unemployment in the U.S. During the
LAC, 2008-2010 Relative to 2007
Global Financial Crisis 1.0
14
0.5
12
0.0
10
-0.5
8
-1.0
6
-1.5
4 Observed change Predicted change Predicted change (OLS)
-2.0
2 LAC Latin South Carribbean Mexico
Central
America America America,
0 Panama,
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Dom. Rep.
Note: Predicted change in remittances based on region-specific coefficients on U.S.
Source: Bureau of Labor and Statistics (BLS). Hispanic unemployment and a 5.4 ppt change in unemployment (2008-2010 relative to 2007).
Note: Hispanic unemployment rate in the U.S., period average. Lighter shaded bars are not statistically significant at the 10 percent level.

Sources: Bureau of Labor and Statistics (BLS) and Fund staff estimates.

The crisis period generally saw a weakening of revenues in the region, and
remittances are estimated to have played a
Box Figure 4.3. Effects on
role as revenue drivers. In particular,
Revenue/GDP
Box Figure Ratio Ratio,
3.2. Effects on Revenue/GDP
revenue-to-GDP dropped in LAC countries by 0.6
2008-10 vs. 2007
¾ percentage points between the average of 0.4

2007-08 and 2010. The extent and timing of 0.2

Percent of GDP

0
the changes to revenue/GDP ratio varied by -0.2
sub-regions. In CAPDR countries, the -0.4

revenue-to-GDP ratio fell by more than 1 -0.6

-0.8
percentage point in 2008-10 relative to the -1
2007 level. Our econometric analysis of the -1.2 Observed change

effects of remittances on fiscal variables -1.4

Central America Caribbean
suggests that slightly less than one-half of this
drop is explained by the fall in remittances. In the Caribbean countries, the ratio actually
increased compared to 2007 during 2008-10, but our analysis indicates that it could have
increased yet more if remittances did not decline. In other country subgroupings, factors
other than remittances, in particular commodity revenues, were the key drivers of overall
revenue trends.47
 41

Remittances and financial stability

The robust growth of remittances in recent years has occurred in parallel with
significant financial deepening in LAC. In this regard, remittances and financial sector
development have interacted significantly, and in a complex way. On the one hand, financial
sector advances have been instrumental in lowering the cost and facilitating an increase in
remittances, as well as channeling them through formal channels. On the other hand,
remittances are believed to have profoundly affected the financial sector, by altering bank
business models in many countries, and helping boost credit to the private sector (Aggarwal
and others (2010)). 48

The positive impact of remittances for financial sector development can go beyond the
associated increase in deposits and access to credit (Fajnzylber and Lopez 2008).
Remittances may also affect credit quality and financial stability. In theory, the impact of
remittances on credit quality is ambiguous. On the one hand, remittances could fuel
excessive private credit growth, which can worsen credit quality. On the other hand,
remittances can strengthen borrowers’ balance sheets and incomes and hence their capacity
to repay loans. In particular, remittances are relatively stable and can serve as collateral,
which, other things equal, decreases the riskiness of loans. Related to this, remittances can
also help banks better know and discriminate their clients, as banks often observe some of the
remittance flows. The existing empirical literature finds that the favorable effects of
remittances on credit quality dominate. Ebeke and others (2014) concluded that remittances
are negatively related to NPLs in a sample of developing countries in 2000-11, suggesting
that the “income-stabilizing” effect dominates the “risk-inducing” effect. A country-level
study of Moldova (see Clichici and Colsenicova (2014)) also finds a negative link between
remittances growth and NPLs in time series regressions.

The impact of remittances on credit quality is examined using a cross-country panel

fixed effects regression similar to equation (1). The dependent variable is the NPL ratio.
The exogenous determinants, 𝑿𝒊𝒕 , considered include the level of real GDP per capita, real
GDP growth in the U.S., FDI as a share of GDP, the stock of emigrants as a share of the
home population, and the share of the rural population (for a full list see Annex III,
Tables 3.10 and 3.11). The endogenous determinants, 𝒁𝒊𝒕 , include remittances as a share of
GDP, real per capita GDP growth, export growth, and a measure of country risk. Endogenous
variables are instrumented using their regional averages, unemployment in the destination
countries, and terms of trade percentage changes (for details see Annex II). Additional
controls included inflation, the unemployment rate, change in the nominal exchange rate,
loan interest rate, terms of trade percentage change, and the dummy variable for natural
disasters. Robustness checks included simple fixed effects regressions.

47 A similar impact of the GFC was observed in other parts of the world. Thus, Abdih and others (2012) estimate the impact
of the 2009 crisis and 2010 recovery on the tax revenues and conclude that some countries, particularly in the Caucasus and
the Central Asia region, suffered from an acute vulnerability to the business cycle in their main remittance-sending country,
Russia. For South American remittance receivers, the sharp slowdown in its economy, and especially the construction sector
seems to have had a pronounced negative effect (Maldonado and Hayem, 2013).
48 For example, securitization of remittance inflows is a common feature of bank business models in countries receiving

significant remittances, and in LAC countries was used in practice in Brazil, El Salvador, and Mexico among others (see
World Bank (2015a)).
 42

The results, in Table 6, indicate that the positive effect of remittances on credit quality
dominate for LAC. Higher remittances in LAC are associated with lower NPLs, though the
effect is only significant for CAPDR. Based on these results, an increase in the remittances-
to-GDP ratio for CAPDR by 1 percentage point would cause a drop in the NPL ratio by
almost 0.5 percentage points. The magnitude of the latter effect is similar to that found by
Ebeke et al. (2014). Sufficient observations were not available for the Caribbean. In South
America other determinants (terms-of-trade shocks and cyclical factors) seem to be more
important NPL drivers than remittances (which are small in most countries and restricting the
sample to a countries with relatively larger flows still did not reveal significant effects).
Table 6. Effects of Remittances on Non-Performing Loans
(IV Regressions)
Central America,
Latin America
Emerging Panama, and the
World and the
Markets Dominican
Caribbean
Republic

Nonperforming loans/total gross loans

Remittances/GDP -0.918** -3.975 -0.475 -.450**
(0.456) (2.553) (0.461) (.216)
Number of obs. 1257 303 272 94

Remittances and Competitiveness

Although remittances support stability through the above channels, these benefits may
be counteracted by risks to competitiveness. Remittance inflows are expected to boost
household spending, which in turn will put the pressure on nontradable prices and interest
rates, leading to real exchange rate appreciation.49 The existing economic literature typically
finds that remittances tend to appreciate the real exchange rate, though some studies do not
detect such an effect or find it to be very small. Some papers focus on the equilibrium REER
and long term effects, while others look more at the more imminent impact. Amuedo-
Dorantes and Pozo (2004) used a panel of 13 Latin American and Caribbean countries for
1979-98, and by applying an instrumental variables approach found that doubling of transfers
in the form of worker’s remittances results in real exchange rate appreciation of about 22
percent. Lopez et al. (2009) found a similar relation, for a larger sample of countries for
1993-2003. Hassan and Holmes (2013) estimate a long-run relationship using a panel
cointegration framework. They conclude that workers’ remittances contribute to long-run
real exchange rate appreciation in the case of high remittance countries. On the other hand,
Izquierdo and Montiel (2006) used time series methods and obtained mixed results for six
Central American countries over 1960-2004. They found no impact of remittances on
equilibrium exchange rate in cases of Honduras, Nicaragua and Jamaica, and a positive effect

49However, Barajas et al. (2012) explain how such an effect on the equilibrium REER depends critically on degree of
openness, factor mobility between domestic sectors, the cyclicality of remittances, the share of consumption in tradables,
and the sensitivity of a country’s risk premium to remittance flows.
 43

Guatemala, El Salvador and Dominican Republic. Barajas et al. (2010) show, using panel
cointegration techniques, that the appreciation effects tend to be small.

As in prior sections, we estimate a cross-country panel fixed effects regressions similar

to equation (1) to assess the impact of remittances on competitiveness. The dependent
variable is the real effective exchange rate (REER) expressed in log form. 50 The set of
controls, in addition to the remittances-to-GDP ratio, includes: the external terms of trade;
exports of goods and services (in percent of GDP); foreign direct investments (in percent of
GDP), real GDP growth; government spending (in percent of GDP); and the US interest rate.
Exogenous changes that raise demand for non-tradables and would be expected to result in
REER appreciation, include an increase in the external terms of trade and increases in
exports, FDI inflows, government spending, or real GDP growth. A higher US interest rate,
may result in capital outflows and a decline in domestic spending, and hence a depreciation
of the real exchange rate. To account for possible endogeneity we estimate the model using
instrumental variables and treat the remittances and export ratios as endogenous variables.
Reverse causality Could arise because remittances might respond to exchange rate
movements, for example if migrants sought to offset the impact of exchange rate movements.
We use as the instruments: per capita GDP and the unemployment rate in the host countries,
both weighted by share of emigrants from each remittance-receiving country. We estimated
a first stage regression of exports of goods and services ratio dependent on real exchange rate
and terms of trade, and then used residuals in the second stage regression for the real
exchange rate.

Our results do not point to a significant impact of remittances on the REER in LAC.
This outcome reflects large leakages of remittance inflows through imports given the small
size and relatively high openness of many countries. A significant (but small) effect is only
found for the CAPDR region (see Annex Table 3.12 for results) where a one percentage point
increase in the remittances-to-GDP ratio causes a 6 percent appreciation of the REER based
on estimates over 1980-2015 or 3.6 percent based on estimates over 1995-2015.51

Remittances and inflation

An inflationary effect of remittances is one of the theoretical priors in the literature.

This conclusion partly derives from the Dutch-disease effects, whereby the remittance-
induced appreciation of the real exchange rate occurs via rising domestic prices. The extent
of the effect would however depend on the exchange rate regime, with inflation effects in the
fixed exchange-rate regimes likely to be particularly pronounced, because of an absence of a
shock absorber that could adjust the relative prices between tradables and non-tradables
sectors more quickly. There are several other theoretical frameworks (cost-based pressures,
consumption-induced excess demand, and monetary expansion) that are also consistent with
the inflationary effects of remittances (see Narayan and others 2011). Empirical studies have
generally detected inflationary effects from remittance inflows. In a panel regression,

50 Remittances may affect external competitiveness through their impact on wages in the recipient economies, as noted in
IMF (2016). However, the lack of cross-country wage data prevents us from investigating this complementary channel, and
limits our analysis of external competitiveness to the CPI-based REER only.
51 As a robustness check, Annex Table 3.13 summarizes the simple fixed effects OLS estimates, showing more robust but

smaller effects.
 44

Narayan and others (2011) find a positive and significant effect of remittances across most
specifications for emerging market economies. Ball et al. (2012) also confirm such
inflationary effects in small open economies, emphasizing the dominance of fixed exchange
rate regimes driving those linkages. Country-level studies based on time series analysis also
find significant inflationary effects of remittances in several Asian countries, El Salvador
(Caceres and Saca (2006)), and Mexico (Balderas and Nath (2008)). Some of the country-
level studies focus on the food sub-components of the CPI to gauge the consumption-induced
demand effect. For example, IMF (2016) documents several stylized facts of a positive
correlation between remittances and food price inflation in Guatemala, which is suggestive of
the inflationary effect of remittances (although causal effects have not been formally tested).

Our methodology aims to strike a balance between the regressions that assessed the
overall macroeconomic impact of remittances and the literature specific to the
determinants of inflation. We estimate a cross country panel fixed effects regression similar
to equation (1) where the dependent variable is inflation, measured as the CPI-based inflation
rate. The vector of exogenous variables, 𝑿𝒊𝒕 , includes the level of real GDP per capita, U.S.
real GDP growth., FDI as a share of GDP, the stock of emigrants as a share of the home
population, and share of the rural population (see Annex II and Annex Table 3.14) and the
endogenous variables, 𝒁𝒊𝒕 , include remittances as a share of GDP (or a lagged change in
remittance/GDP ratio), real per capita GDP growth, export growth, and a measure of country
risk. Endogenous variables are instrumented using their regional averages, unemployment in
the destination countries, and terms of trade percentage changes (see Annex II). Additional
controls that were used to check robustness included contemporaneous and lagged changes in
the nominal exchange rate to the US dollar, the unemployment rate, terms of trade change,
overall fiscal balance, and lagged inflation. Also, robustness checks included simple fixed
effects regressions (Annex table 3.15).

Our results confirm remittance-induced inflationary pressures for the CAPDR and the
Caribbean (Table 7). We find that a lagged change in the remittance-to-GDP ratio is a more
significant determinant of inflation than the level of the same ratio, with significant positive
effects on inflation in two country sub-groupings: CAPDR and the Caribbean. We find that
the level of remittances is not a significant determinant of inflationary pressure, except in the
Caribbean countries. The result for the CAPDR and the Caribbean is consistent with the
prevalence of fixed or stabilized exchange rate regimes and limited credibility of monetary
frameworks in many countries in these regions. That said, we do not find a clear effect of a
fixed exchange rate regime dummy in influencing the results.
 45

Table 7. Effects of Remittances on Inflation

(IV Regressions)
Central America,
Latin Panama, and
Carribbean
America the Dominican
Republic
Inflation (Percent)
Lagged Change in Remittances/GDP 21 2.52** 3.37*
(20.34) (1.27) (1.97)
Number of obs. 532 73 198
Adjusted R2 0.981 - 0.275
Inflation (Percent)
Remittances/GDP 0.950 1.350*** 0.255
(11.62) (0.422) (0.417)
Number of obs. 473 75 198
Adjusted R2 0.984 0.242 0.264

E. How do migration and remittances affect poverty and inequality?

Earlier studies have typically found that remittances and migration tend to reduce
poverty, while their effects on inequality are more ambiguous. A number of studies have
examined the impact of international remittances on poverty and inequality in emerging and
developing countries (see e.g. Adams and Page 2005, Fajnzylber and López 2008). As
international remittances often represent significant shares of migrant household incomes,
and incomes earned working abroad are typically multiples of those earned at home, most
studies have found that remittances reduce poverty in home countries.52 The impact of
remittances on income inequality is more ambiguous depending on which part of the income
distribution migrants come from and whether remittances go to poorer or richer households.
While some studies found that migration and remittances increase inequality, others found
that it reduces it, that there was no significant effect, that the effect depended on where
remittances came from, or changed over time, from initially increasing inequality to later
reducing it as migration opportunities became more widely available.53

Remittances and migration do not appear to affect poverty and inequality at the macro
level in LAC. In line with the analysis in previous sections, we first rely on cross-country
panel regressions to examine the determinants of poverty (measured using two different
headcount measures) and inequality (measured here using the Gini coefficient). We examine
the effect of remittances and migration (both lagged to mitigate reverse causality), while
controlling for conditions in the home and host countries. While simple OLS regressions
(including country fixed effects) point to significant effects, instrumental variables results do

52See e.g. Acosta and others 2008, Loritz 2008, Taylor and others 2005 for studies of LAC countries.
53See e.g. Adams 2006, Adams and others 2008, Barham and Boucher 1998, Bouoiyour and Miftah 2014, Möllers and
Meyer 2014; Acosta and others 2008, Brown and Jimenez 2007, Gubert and others 2010, Loritz 2008, Margolis and others
2013, Mughal and Anwar 2012, Taylor and others 2005; Beyene 2014, Yang and Martinez 2005; Acharyaa and Leon-
Gonzalez 2013; Stark and others 1988.
 46

not indicate significant effects of remittances or migration. Unemployment appears to be a

key factor for both poverty and inequality, with strikingly robust effects. The results also
highlight the roles of common regional shocks for both poverty and inequality.

Table 8. Effects of Remittances and Migration on Poverty and Inequality

(IV Regressions)
Headcount (1.9 USD) Headcount (3.1 USD) Gini coefficient
Emerging Emerging Emerging
LAC LAC LAC
Markets Markets Markets
Remittances/GDP (lagged) 0.193 -0.639 0.344 -0.912 1.703* -0.921
(0.310) (1.666) (0.523) (2.338) (0.997) (2.582)
Change in emigrants/population (lagged) -0.644 0.690 -1.191 1.952 -4.036** -2.384
(0.581) (3.410) (0.982) (4.785) (1.708) (5.202)
Unemployment (lagged) 0.130* 0.245*** 0.375*** 0.362*** 0.450** 0.378***
(0.0663) (0.0701) (0.112) (0.0984) (0.200) (0.102)
Country risk -0.0786** -0.0515 -0.151** -0.103 -0.0690 -0.0757
(0.0361) (0.0746) (0.0610) (0.105) (0.101) (0.125)
Rural population 0.225*** 0.0946 0.331*** 0.151 0.278 -0.129
(0.0662) (0.269) (0.112) (0.378) (0.223) (0.419)
Poverty gap (World/LAC average) 0.159** 0.160** 0.309** 0.277** 0.536* 0.301***
(0.0793) (0.0771) (0.134) (0.108) (0.287) (0.116)
Number of obs. 180 290 180 290 179 289
Adjusted R2 0.662 0.613 0.738 0.697 0.760 0.520
Note: Lagged remittances are treated as endogenous and instrumented using regional migration flows (excluding own
country) and unemployment in the destination. *** denotes significant at 1 percent, ** at 5 percent, * at 10 percent.

Micro-level evidence for Mexico suggests that poorer households are much more likely
to receive remittances and that this pattern became more prominent during the global
financial crisis. To zoom into the drivers of these macro-level findings at a more
disaggregated level, Mexican household surveys are used to compare remittance-receiving
households with non-remittance-receiving households. The results suggest that about 5
percent of households received remittances in 2014; on average about US$290/month (mean;
US$140 median). Poorer households were much more likely to receive remittances, and this
increased further during the crisis and persisted to some extent even after. Remittance-
receiving households are poorer than non-remittance-receiving households, even when
including remittances. The average income of remittance receiving households would put
them in the 4th decile without remittances, in the 6th decile with remittances; non-remittance
receiving households would be on average in the 7th decile. The income gap between
households that did or did not receive remittances narrowed during the crisis when including
 47

remittance income – average income of those Figure 25. Remittances and Household
receiving remittances increased from 55 percent Income in Mexico
of non-remittance-receiving households’ income 10
Share of Households Receiving Remittances,
by Income Decile
in 2002 to 59 percent in 2008 – 8 (Percent)
2002
2008
consistent with their insurance role. However, 2014
6
the gap when excluding remittances has
widened, possibly due to increasing inequalities 4

in domestic opportunities. As may be expected, 2

for remittance-receiving households, remittances
0
constituted a larger share of income for lower-

Highest
Lowest

9
income households: almost 40 percent in the
bottom decile, in contrast with about 20 percent 50
Remittances as a Share of Household Income,
in the top decile, in 2002. However, households by Income Decile 2002
40 (Percent) 2008
across the distributions appear to have become 2014
less dependent on remittances over time, with the 30

possible exception of the very top, where 20

investment motives may be playing an
increasingly important role. As a result, and quite 10

strikingly, by 2014 remittances constituted a 0

similar share of income, around 20-25 percent,

Highes
Lowest

t
for (remittance-receiving) households across the 50000
Average Household Income
45000 Mean
income distribution. 40000 Median
(Nominal Mexican pesos in given year)
35000
30000
25000
This pro-poor pattern of remittances could 20000
15000
translate into remittances lowering inequality 10000
5000
even at the macro level. A simple comparison 0
hhs (including remittances)

hhs (including remittances)

hhs (including remittances)

Non-remittances

Non-remittances

Non-remittances
hhs (excluding remittances)

hhs (excluding remittances)

hhs (excluding remittances)

of Gini coefficients based on actual income
receiving hhs

receiving hhs

receiving hhs
Remittances-receiving

Remittances-receiving

Remittances-receiving
Remittances-receiving

Remittances-receiving
Remittance-receiving

(including remittances for remittance-receiving

households) and income excluding remittances
would suggest that remittances lower inequality.
This, however, is not a measure of the true 2002 2008 2014

effect, as ‘missing’ remittances would likely be Sources: INEGI and Fund staff calculations.
associated with behavioral responses affecting Figure 26. Gini Coefficients
0.5
income: hours or employment could be higher to 0.49
Income including remittances
Income excluding remittances
try and make up for ‘missing’ remittances, but it 0.48 Counterfactual income

is un clear ex ante how this would differ across 0.47

0.46
the income distribution. Propensity score 0.45
matching is thus used to construct counterfactual 0.44

incomes for remittance-receiving households, 0.43

0.42
providing an estimate of what their income 2002 2008 2014
would be once this behavioral response is taken Source: INEGI and Fund staff calculations.
Note: Counterfactual income uses actual income for non-remittance-receiving
into account, assuming that their income would households and an estimated counterfactual income for remittance-receiving
households based on propensity score matching, controlling for the same household
be similar to that of non-remittance-receiving characteristics as in the regressions above.

households with comparable (non-migration-

 48

related) characteristics.54 The resulting Gini coefficient is lower than that based on income
excluding remittances, but is still higher than that of actual income, suggesting that inequality
would be higher in the absence of remittances, even when taking the behavioral response into
account.

IV. MACRO-MODEL: THE IMPACT OF A U.S. GROWTH SHOCK55

This section presents a model-based analysis of migration and remittances based on a

version of the IMF’s Flexible System of Global Models (FSGM) complementing the
empirical work in previous sections. A general equilibrium model-based analysis helps
explore complex transmission channels and net economic effects of labor migration and
remittances. A model that provides a structural interpretation of labor and remittance flows
while capturing other structural features of the economies has an advantage of factoring in
multiple economic linkages in a consistent manner. It allows to trace how various shocks
propagate through the economies, explore the multiple channels, and distinguish the first-
and second-round effects.

The FSGM is routinely used in the IMF for simulation exercises as well as global and
regional spillover analysis. It represents a system of annual, multi-region, general
equilibrium models, combining both micro-founded and reduced form formulations of
various economic sectors. It has a fully articulated demand side, and some supply side
features. International linkages are modeled in aggregate for each country/region. The
models have full stock-flow consistency, public deficits cumulate into the level of public
debt, current account balances cumulate into the level of net foreign assets, and investment
cumulates into the level of the capital stock. There are endogenous rules governing the
operation of both monetary and fiscal policy. The theoretical foundations and dynamic
properties of the model are described in Andrle and others (2015) and Snudden (2017).

The key features of the remittance and labor migration channels in the FSGM are the
following:
 Household members of working age in their home country provide migrant labor to
foreign economies. When the workers travel abroad, they reduce the population of
their country and increase that of the foreign economy. Labor emigration could be
drawn from either the labor force or the non-participating population.
 Foreign workers are assumed to have full employment in the host economy.
Expatriate workers, however, have a lower level of productivity relative to native
workers which leads to lower wages compared to the natives. The share of foreign
labor in aggregate employed labor is explicitly modeled via fixed bilateral shares
from labor-exporting economies.

54 Of course, this counterfactual does not show what the income distribution would have been in the absence of the
migration that is behind the remittances.
55 We would like to thank Benjamin Hunt and Keiko Honjo in the IMF’s Research Department for providing the FSGM

simulation results.
 49

 Labor migration and remittances come hand in hand in the model. Foreign workers
remit a fixed share of their after-tax earnings to their home country. The cost of
sending remittances is explicitly modeled and remittance flows are net of cost.
 Remittances are received by liquidity constrained (LIQ) households of the home
economy. They increase their consumption under the assumption that all remittances
are spent. This is broadly consistent with empirical estimates and case studies
suggesting that remittances are primarily used for immediate consumption.
 Most of the model’s parameters have been estimated from the data using a range of
empirical techniques. The structural dynamics of remittances and migration in FSGM
are calculated to broadly match the key stylized facts of empirical estimates. The data
source for remittance flows is the World Bank Bilateral Remittances 2014.

With the United States accounting for over half of the remittance flows to the LAC, we
simulate an increase in domestic demand in the United States and its effect on the
remittance receiving economies. The increase in private investment and consumption in the
United States are calibrated to increase real GDP by one percentage point in the first year
relative to the baseline (Figure 27). Specifically, the increase in investment is about five
times larger than that of private consumption in percentage terms. Higher domestic private
demand leads to higher output, which raises aggregate labor demand by almost 0.5 percent
and puts upward pressure on real wages. The increased labor demand is partly met by an
inflow of foreign workers. Migrant labor increases by approximately 0.4 percent. As a result,
remittance outflows from the United States increase by 1.5 percent after the first year.

Figure 27. United States: Temporary Increase in Domestic Demand

Percent difference from baseline scenario
1.2 0.6
Real GDP Employed Labor
0.9 0.4
0.6
0.2
0.3
0.0 0.0
2016 2017 2018 2019 2020 2021 2022 2016 2017 2018 2019 2020 2021 2022
0.6 2.5
Foreign Employed Labor Remittances Sent by Foreign Workers
2.0
0.4
1.5
0.2 1.0
0.5
0.0 0.0
2016 2017 2018 2019 2020 2021 2022 2016 2017 2018 2019 2020 2021 2022
Source: Fund staff simulations.

The following counterfactual scenarios allow for exploring remittance and labor
migration effects versus the spillovers from the U.S. shock:

(1) the “basic” model with no new remittances or foreign labor flows;
(2) the model with remittances and foreign labor flows, where the expatriate workers
are pulled from the non-participating labor force of their home economy;
 50

(3) the model with remittances and foreign labor flows, where the expatriate workers
are pulled from participating and non-participating labor force.

Figure 28 for the Dominican Republic illustrates the net economic effects from a
positive U.S. shock on a remittance receiving economy.56

 Higher external demand significantly lifts exports, but puts upward pressure on
inflation, which makes the monetary authority raise the policy rate to return inflation
to target. As a result, private investment and consumption decline. The consumption
of the LIQ households, however, picks up in scenarios 2 and 3 by 0.2 and 0.1 pp,
respectively, supported by higher remittance inflows. This buffers the decline in
aggregate consumption, but also adds to import demand.

 In scenario 3, the benefits for private consumption from higher remittance income are
dampened by the loss of labor income of those who used to be employed but have
now emigrated (the increase in emigration from the Dominican Republic is 0.4
percent), but the latter impact appears to be relatively small.

As expected, the net effect of a significant positive shock to the domestic private
demand in the United States on the Dominican Republic economy is large and
positive. But taking into account the changes in relative prices and foreign demand in
the general equilibrium context, the net impact on GDP level does not vary much
across all three scenarios. Similar results hold for all the LA countries with different
levels of the remittance dependence.

 The simulations show that the REER dynamics differ very little across the scenarios.
This is consistent with the empirical results in section Remittances and the exchange
rate suggesting that there is no statistically significant impact of remittance inflow on
the REER.

 Remittances play the role of consumption smoothing, in line with the earlier
discussion. The LIQ households benefit the most from the remittance inflow. Their
disposable income increases, more than offsetting the negative impact of higher
interest rates on their consumption.

56We focus on the case of the Dominican Republic, as an example of a country that it is highly dependent on remittance
inflows (6.8 percent of GDP).
 51

Figure 28. Dominican Republic: Temporary Increase in Domestic Demand in the U.S.
Percent difference from baseline scenario
Scenario 1: No Remittances
Scenario 2: With Remittances from Non-Participating Labor Force
Scenario 3: With Remittances from a combination of Non-Participating and Participating Labor force

Real GDP 0.6

0.6 GDP per capita
0.4 0.4

0.2 0.2
0.0 0.0
-0.2 -0.2
2016 2017 2018 2019 2020 2021 2022 2016 2017 2018 2019 2020 2021 2022
0.6 0.1
Real GNP Real Consumption
0.3 0.0

0.0 -0.1

-0.3 -0.2
2016 2017 2018 2019 2020 2021 2022 2016 2017 2018 2019 2020 2021 2022

0.3 0.4
Real Consumption of LIQ Households Real Investment
0.2
0.0
0.1
0.0 -0.4

-0.1 -0.8
-0.2 -1.2
2016 2017 2018 2019 2020 2021 2022 2016 2017 2018 2019 2020 2021 2022

0.05
0.8 Contribution of Net Exports to GDP /1 Population
0.00
0.4

0.0 -0.05

-0.4 -0.10
2016 2017 2018 2019 2020 2021 2022 2016 2017 2018 2019 2020 2021 2022
0.5 1.6
Emigrating Labor Force Remittances Sent
0.4
1.2
0.3
0.8
0.2
0.1 0.4
0.0 0.0
2016 2017 2018 2019 2020 2021 2022 2016 2017 2018 2019 2020 2021 2022
0.4
Real Effective Exchange Rate 1.0 Policy Interest Rate /1
0.3 (+ appreciation)
0.2 0.6

0.1 0.2

0.0 -0.2
2016 2017 2018 2019 2020 2021 2022 2016 2017 2018 2019 2020 2021 2022
1/ Difference from baseline scenario in percentage points.
Source: Fund staff simulations.
 52

The magnitude of the effect on GDP per capita and GNP, however, depends on country
characteristics. For example, in case of Jamaica, the positive impact on GDP per capita is
more pronounced than in other remittance dependent countries, due to higher share of
emigrants in the total population (Figure 29). Still, the overall size of the effect is small.
Remittance inflows are positively translated to GNP, and in most countries partially offset
the negative contribution of net export. In the case of Jamaica, given the much higher share
of remittances in the overall economy (12 percent) real GNP is higher in scenarios 2 and 3.

Figure 29. Jamaica: Temporary Increase in Domestic Demand in the U.S.

Percent difference from baseline scenario
Scenario 1: No Remittances
Scenario 2: With Remittances from Non-Participating Labor Force
Scenario 3: With Remittances from a combination of Non-Participating and Participating Labor force
0.4 0.6
Real GDP Real GDP per capita
0.3
0.2 0.4
0.1 0.2
0.0
-0.1 0.0
-0.2 -0.2
2016 2017 2018 2019 2020 2021 2022 2016 2017 2018 2019 2020 2021 2022
0.6
Real GNP 0.9
0.4 Real GNP per capita
0.6
0.2
0.0 0.3
-0.2 0.0
-0.4 -0.3
-0.6 -0.6
-0.8
-0.9
2016 2017 2018 2019 2020 2021 2022
2016 2017 2018 2019 2020 2021 2022

Source: Fund staff simulations.

V. CONCLUSIONS AND POLICY IMPLICATIONS

The analysis in this paper confirms many findings of earlier studies. In line with earlier
studies, migration and remittances seem to respond to slow moving “structural” variables in
the home country, including weak growth, as well as with conflicts and natural disasters, but
not so much to cyclical movements. The types of emigrants vary across LAC sub-regions:
Caribbean countries face the most significant brain drain with nearly one half of them in the
US having a college education. Most remittances are still transmitted in cash and their cost
have gone up recently, albeit from a low base, likely due to changes in correspondent
banking relations.

While remittances are beneficial for the home country, the negative effects from
population loss cannot be ignored. For the home country, the negative impact from
emigration on labor resources and productivity seems to outweigh growth gains from
remittances, especially for the Caribbean. Thus, the net effect on per capita GDP growth
would be negative. However, given emigration (which can be perceived as a foregone cost),
remittance flows play key financing and stabilizing roles. They represent the most important
external flow for LAC and—in particular, for the Caribbean and CAPDR—facilitate private
 53

consumption smoothing, support financial sector stability and fiscal revenues, without strong
evidence for harmful competitiveness effects through shifts in the real exchange rate.
Nevertheless, open questions remain with regards to the effects of emigration and
remittances on the home country’s wages and labor supply. For example, the emigration of
workers, if they were previously employed, could drive up wages while at the same time,
remittances decrease labor supply and increase reservation wages for those who left behind.

Remittances merit policy support given their key financing and stabilizing roles. Policy
measures should focus on reducing the cost of remittances and facilitating formal
intermediation. Given the recent changes to CBRs, strengthening AML/CFT frameworks,
and exploring regional solutions for cooperation can help improve LAC countries’ regulatory
environment and keep formal financial channels open. Development and enhancements of
payments systems (including through new solutions like mobile money) and ensuring their
access for remittance-service providers would help foster competition and drive prices down.
At the same time, policy support should help control risks arising from the large dependence
on remittances, including via measures to enhance the financial sector’s resilience to
volatility and potential sudden stops of remittances. Educating consumers about the costs of
remittances can also help users make informed decisions and allow them to choose their best
option. Improving transparency on the cost of remittances, as the World Bank has done with
its Remittance Price Worldwide (RPW) database, can help in this regard.

Steps to curb brain drain can minimize negative effects from emigration. Since the type
of emigration linked to brain drain typically generates relatively little remittances, the net
effect for these countries can be especially negative. These findings support the case for
measures to retain potential emigrants, either through structural reforms that foster job
opportunities for the highly educated (e.g., the development of a medical tourism industry) or
measures to limit the subsidization of brain drain with public funds (e.g. through bonding
schemes whereby people who have benefitted from public funding for education must remain
in the home country for some years).

More generally, improvements in the business environment and strong institutions can
help raise productivity and thereby limit incentives for outward migration. Productivity
can also benefit from steps to promote return migration by skilled workers, for example
through the recognition of foreign qualifications and experience in professional regulations
and public sector hiring, or the provision of portable social security benefits. Effective
policies to improve the security situation in many Central American and some Caribbean
countries may also relieve key bottlenecks to productive use of remittances, including their
greater use for investment. Countries could also seek to leverage economic ties with
diasporas, which could bolster FDI and tourist receipts. Furthermore, policies can aim at
boosting labor supply, in particular by raising female labor market participation, to offset the
impact of emigration. The adverse impact of a real appreciation in case of a spike in
remittance inflows can be cushioned by steps to reduce labor and product market rigidities
and to support the provision of credit to firms.
 54

VI. ANNEX I. DATA

This section provides a short discussion of the two main variables of interest in this paper and
their sources, namely, measures of migrant stocks and remittance flows. In addition, a table
listing all the countries included in this study is provided together with a table of all variables
used in the empirical analysis and their sources. Lastly, this section contains a discussion on
migrant profile data including two tables with more detail on emigrant profiles.

A. Migration and Migrant Stocks Data

There are currently two major providers of migration data for use in cross-country analysis:57
The United Nations Population Division (UNPD) and the World Bank (WB). Both
institutions classify a migrant as an individual who is either born abroad or is a citizen of a
foreign country.

Trends in International Migrant Stock Database (TIMS)58 – UNPD

The UNPD calculates the international migrant stock using population censuses, population
registers, and other nationally representative surveys. These surveys are maintained in the
Global Migration Database. In most instances, the international migrant stock is equated with
the foreign-born population in these surveys. In addition, the estimate for the stock of
migrants is supplemented with information on country of citizenship, when available.

This methodology has some limitations as highlighted by the creators of the database.
Depending on the how citizenship is conferred, individuals may or may not be classified as
an immigrant. If citizenship is conferred on the basis of jus sanguinis, individuals born to
international migrants in the country of residence may be considered immigrants even though
they have never lived abroad. Conversely, if an individual born abroad decides to naturalize
in their country of residence, then they will not be included in the international migrant pool.

In addition to issues regarding classification of foreign-born/foreign-citizen populations in

the country censuses, there is also a problem regarding the timing of the surveys. The
database reports the migrant stocks from 1990-2015 in 5-year increments. In situations where
the country census does not fall within the reference years, the UNPD interpolates and
extrapolates using 2 or more censuses – adjusting for country-specific factors such as the
economic business cycle and changes in migration policies. In situations where there is only
one data point for a country, regional growth rates of the migrant stock and country-specific
assumptions are used as appropriate to estimate migrant stocks and the distribution of
country of origin59. Lastly, when a country has no available data, similar countries or group

57 The Organization for Economic Co-operation and Development (OECD) also produces migration statistics; however, the
coverage of destination countries is limited to OECD members only
58 United Nations, Department of Economic and Social Affairs, Population Division (2015). Trends in International Migrant

Stock: The 2015 Revision. (United Nations database, POP/DB/MIG/Stock/Rev.2015).

59 For example, the change in the total stock was relatively minor (under five per cent) using regional growth rates, the

distribution by origin at the start of the period was left constant.

 55

of countries are used as models to estimate the migrant stock, e.g. for the Democratic
People's Republic of Korea.

Global Bilateral Migration Database (GBM)60 -World Bank (WB)

Whenever data is available for both definitions, the WB prioritizes information based on
country of birth. They cite several reasons for this approach. First, place of birth is a more
appropriate measure of movement across country borders. Second, nationality can change but
birth-place cannot. Third, there is significant heterogeneity of naturalization rates across
countries that can affect classification.

The primary source of the WB are censuses found in the Global Migration Database of the
UNPD, with priority given to data with information on country of origin and gender.
However, the WB reports migrant stocks in destination countries from 1960-2010 in 10-year
intervals. One benefit of using longer intervals is the opportunity to use more census data in
between reporting years. Nonetheless, this database still faces similar data constraints in
several countries with only one or two census data points. In these instances, the WB relies
on the total stocks provided by the TIMS with the shares derived from the average bilateral
shares in available censuses. When data is missing completely, the WB relies on
interpolation to estimate the migrant stocks. The interpolation exercise relies on a propensity
measure defined as the likelihood that a particular destination country will accept migrants
from a specific origin region.

B. Remittances

In general, there are two ways to define remittances in the literature – narrow and broad.
Under the previous Balance of Payments Manual (BPM5), the narrow concept was defined as
simply workers’ remittances: current transfers by “migrants” (defined by a stay in the host
country for 1 year or more) who are employed in and considered residents in a host country.
The broad definition included worker’s remittances plus compensation of employees (wages
earned by individuals in countries other than those in which they are residents for work
performed for and paid by residents) and migrants’ transfers (contra-entries to the flow of
goods and changes to the capital accounts transfer items arising from the change of
residence). The World Bank’s migration and remittances database reported this broader
concept. The same data are available in STA’s database.

The introduction in 2009 of BPM6 created changes in the reporting framework and
corresponding definitional changes for categories associated with remittances. A new
category, personal transfers, has been introduced to replace workers’ remittances. Personal
transfers are defined as all current transfers in cash or in kind made or received by resident
households to or from nonresident households. This new category is closely related to the
“workers’ remittances but may potentially be a broader concept.61 The “workers’
60 Ozden C., Parsons C., Schiff M., Walmsley T. (2011). Where on Earth is everybody? The evolution of global bilateral
migration 1960–2000. World Bank Economic Review, 25, 12-56.
61 Personal transfers explicitly include “in kind” transfers and all kinds of individuals (whether related or unrelated

personally). Fortunately, both concepts match for most countries until the most recent years. The data for the last 2-3 years,
 56

remittances” concept continues to be reported as a supplementary item in BPM6.

Consequently, the narrower measure of remittances is now defined as personal transfers,
while the broader measure would be the sum of “personal transfers” included in the
secondary income account and “compensation of employees” in the primary income
account.62

C. Migrant Profiles

Given the U.S. centric nature of Latin American emigration, we developed a snapshot of
migrant profiles through an analysis of U.S. household level census data, provided by the
American Community Survey (ACS).63 The 2008 American Community Survey contained a
topical module on migration, including questions on monetary transfers, which allowed us to
produce a picture of remittance senders. In addition, because survey households are randomly
chosen, the ACS captures both documented and undocumented migrants, resulting in a more
holistic snapshot of migrants. One constraint of our analysis using this microdata is that for
South American and to a lesser extent, Caribbean migrants, this data may not be fully
reflective of their characteristics due to their more diverse destination patterns, e.g. Spain for
South American migrants and the U.K. and Canada for Caribbean migrants.

show that personal transfers are larger than worker’s remittances. The reason for the discrepancy is unclear but may be
attributed to the preliminary nature of the most recent estimates.
62 The concepts of “migrants’ transfers” and “migrant” more generally have been removed from the balance of payments

framework.
63 ACS data accessed via the Integrated Public Use Microdata Series (Ruggles, S., K. Genadek, R. Goeken, J. Grover, and

M. Sobek, 2015).
 57

Annex Table 1.1. Variables in Regressions

Variable Source Note
American Community
Average Age at Entry Survey
Hispanic Unemployment
Rate, U.S. Bureau of Labor Statistics
Chinn, Menzie D. and Hiro Ito
(2006). "What Matters for Financial
Development? Capital Controls,
Institutions, and Interactions," Journal
Capital Account Openness of Development Economics, Volume
Index Chinn-Ito Index 81, Issue 1, Pages 163-192 (October).
Dummy variable, 0 if no wars took
place in country during the year, 1 if a
War Corelates of War war took place.
Dummy variable, 0 if no natural
disasters occurred in country during the
Natural Disaster Emergency Events Database year, 1 if a natural disaster occurred.
Worker's Remittances, IMF: Balance of Payments
Credit/Debit Statistics
Foreign Direct Investment, IMF: Balance of Payments
Net Statistics
Gross Domestic Product, IMF: World Economic
Real Outlook Database
Gross Domestic Product, IMF: World Economic
Nominal Outlook Database
IMF: World Economic
Gross Domestic Product, PPP Outlook Database
Gross Domestic Product, Per IMF: World Economic
Capita Outlook Database
IMF: World Economic
Unemployment Rate Outlook Database
IMF: World Economic
Inflation Outlook Database Consumer Price Index, period average
IMF: World Economic
Total Exports Outlook Database National Accounts
General Government IMF: World Economic
Expenditure Outlook Database
Composite Political, Financial,
Economic Risk Rating for a Country.
Country Risk (Composite International Country Risk https://www.prsgroup.com/about-
Risk Index) Guide us/our-two-methodologies/icrg
 58

Annex Table 1.1 (Continued). Variables in Regressions

Exchange Rate Arrangements Entering
the 21st Century: Which Anchor Will
Reinhart & Rogoff; IMF Hold?, Ethan Ilzetzki, Carmen M.
Fixed Exchange Rate AREAER database. Reinhart and Kenneth S. Rogoff.
United Nations Population
Emigrants, Stocks Division
United Nations Population
Female Emigrants, Stocks Division
United Nations Population
Emigrants to U.S., Stocks Division
United Nations Population
Population Division
M2 to GDP Ratio WEO/IFS
Rural Population, Percent of
Total Population World Bank
Poverty Gap, 2011 PPP World Bank
Age Dependency Ratio,
Percent of Working-Age
Population World Bank
Remittances, Sent/Received World Bank

Change in Terms of Trade World Bank

Average Transaction Cost of World Bank: World
Remittances Development Indicators
Number of Remittance
Service Providers
Financial Development Index
Financial Openness
Trade Openness
 Annex Table 1.2. Countries Included in the Study
Latin America and the Caribbean
CAPDR Barbados Rest of Latin America
Costa Rica Belize Argentina
Dominican Republic Jamaica Bolivia (Plurinational State of)
El Salvador Dominica Brazil
Guatemala Guyana Chile
Honduras Haiti Colombia
Nicaragua Montserrat Ecuador
Panama Saint Kitts and Nevis Mexico
Caribbean Saint Lucia Paraguay
Anguilla Saint Vincent and the Grenadines Peru
Antigua and Barbuda Suriname Uruguay
Bahamas Trinidad and Tobago Venezuela (Bolivarian Republic of)
World
Afghanistan Guinea Philippines
Albania Guinea-Bissau Poland
Algeria Hungary Portugal
Armenia Iceland Qatar
Angola India Republic of Korea
Australia Indonesia Republic of Moldova
Austria Iran (Islamic Republic of) Romania
Azerbaijan Iraq Russian Federation
Bahrain Ireland Rwanda
Bangladesh Israel Samoa
Belarus Italy San Marino
Belgium Japan Sao Tome and Principe
Benin Jordan Saudi Arabia
Bhutan Kazakhstan Senegal
Bosnia and Herzegovina Kenya Serbia
Botswana Kiribati Seychelles
Brunei Darussalam Kuwait Sierra Leone
Bulgaria Kyrgyzstan Singapore
Burkina Faso Lao People's Democratic Republic Slovakia
Burundi Latvia Slovenia
Cabo Verde Lebanon Solomon Islands
Cambodia Lesotho South Africa
Cameroon Liberia South Sudan
Canada Libya Spain
Central African Republic Lithuania Sri Lanka
Chad Luxembourg Sudan
China Madagascar Swaziland
China, Hong Kong SAR Malawi Sweden
Comoros Malaysia Switzerland
Congo Maldives Syrian Arab Republic
Côte d'Ivoire Mali Tajikistan
Croatia Malta Thailand
Cyprus Marshall Islands Former Yugoslav Republic of Macedonia
Czech Republic Mauritania Timor-Leste
Democratic Republic of the Congo Mauritius Togo
Denmark Micronesia (Federated States of) Tonga
Djibouti Mongolia Tunisia
Egypt Montenegro Turkey
Equatorial Guinea Morocco Turkmenistan
Eritrea Mozambique Tuvalu
Estonia Myanmar Uganda
Ethiopia Namibia Ukraine
Fiji Nepal United Arab Emirates
Finland Netherlands United Kingdom
France New Zealand United Republic of Tanzania
Gabon Niger United States of America
Gambia Nigeria Uzbekistan
Georgia Norway Vanuatu
Germany Oman Vietnam
Ghana Pakistan Yemen
Greece Palau Zambia
Grenada Papua New Guinea
 60

Annex Table 1.3. Remittance Corridors: Source and Recipient Countries

Source Countries Recipient Countries
United Arab Emirates Afghanistan Morocco
Australia Angola Republic of Moldova
Austria Albania Madagascar
Belgium Netherlands Antilles Mexico
Brazil Bangladesh The former Yugoslav Republic of Macedonia
Canada Bulgaria Mali
Switzerland Bosnia and Herzegovina Myanmar
Chile Bolivia (Plurinational State of) Mozambique
Costa Rica Brazil Malawi
Czech Republic Botswana Malaysia
Germany China Nigeria
Dominican Republic Côte d'Ivoire Nicaragua
Spain Cameroon Nepal
France Democratic Republic of the Congo Pakistan
United Kingdom of Great Britain and Northern Ireland Colombia Panama
Ghana Cabo Verde Peru
Italy Costa Rica Philippines
Japan Dominican Republic Poland
Kenya Algeria Paraguay
Republic of Korea Ecuador Romania
Kuwait Egypt Rwanda
Malaysia Eritrea Sudan
Netherlands Ethiopia Senegal
Norway Fiji Sierra Leone
New Zealand Ghana El Salvador
Qatar Gambia Somalia
Saudi Arabia Guatemala Serbia
Senegal Guyana Suriname
Singapore Honduras Swaziland
Sweden Croatia Syrian Arab Republic
Thailand Haiti Togo
United Republic of Tanzania Hungary Thailand
United States of America Indonesia Tajikistan
South Africa India Tonga
Jamaica Turkey
Jordan United Republic of Tanzania
Kenya Uganda
Kyrgyzstan Ukraine
Cambodia Viet Nam
Kosovo Vanuatu
Lao People's Democratic Republic Samoa
Lebanon Yemen
Liberia South Africa
Sri Lanka Zambia
Lesotho Zimbabwe
Lithuania
 61

Annex Table 1.4. Characteristics of Immigrants Who Entered After Age 22,
201464
MEX CA CAR SOUTH AM.
Proportion female 52 55 59 58
Proportion married 69 55 54 66
Proportion in one adult hhs 17 22 24 19

Female Labor Force Participation 46 58 63 61

Male Labor Force Participation 79 81 68 81

Married Female LFP 44 58 67 61

Married Male LFP 81 82 71 82

Female Hourly Wage $9.06 $10.43 $17.56 $14.27

Male Hourly Wage $12.34 $13.33 $19.34 $21.05

Age (mean) 49 50 56 51
Years in US (mean) 17 17 22 17
Entry age (mean)* 20 21.7 24.5 24.5

Proportion citizens* 28.5 41.5 64.4 51.6

Family size* 4.1 3.5 3.0 3.2

Source: 2008 American Community Survey.
* Includes entire sample

64We choose age 22 in order to best reflect the group of people who emigrated to the US after completing all their education
(22 is the usual age for 4-year college completion).
 62

Annex Table 1.5 Top Occupations, Immigrants Who Entered After Age 22, 2014
Mexico South America
17% Building and Grounds Cleaning 12% Building and Grounds Cleaning
and Maintenance and Maintenance
14% Production 11% Office and Administrative
Support
14% Construction and Extraction 9% Sales and Related
11% Food Preparation and Serving 8% Management, Business, Science,
and Arts
10% Transportation and Material 7% Production
Moving
Central America Caribbean
20% Building and Grounds Cleaning 13% Healthcare Support
and Maintenance
12% Construction and Extraction 12% Office and Administrative
Support
11% Production 8% Healthcare Practitioners and
Technical
10% Transportation and Material 7% Personal Care and Service
Moving
8% Food Preparation and Serving 7% Building and Grounds Cleaning
and Maintenance
Source: 2008 American Community Survey.
 63

VII. ANNEX II. EMPIRICAL STRATEGY

Annex Table 2.1. Empirical Strategy

Dependent variables Exogenous controls Endogenous controls Instruments

Emigrants/population, per capita PPP GDP,

Emigrant flow (emigrant World/LAC average of
Determinants of unemployment in destination, inflation, age Real per capita GDP
stock/population - its lag); endogenous variable,
migration dependency, rural population, natural growth
emigrant flow to U.S. changes in terms of trade
disaster, war

Emigrants/population, per capita PPP GDP Real per capita GDP

remittances/GDP, workers' World/LAC average of
(robust to using logs), unemployment in growth, changes in
remittances/GDP (robust to endogenous variable,
Determinants of destination (lagged), inflation, age LC/USD exchange rate
using logs, changes in terms of trade
remittances dependency, rural population, average age at (latter not instrumented
remittances/population, (latter not used for the
entry, female migrant share, natural disaster, for the Caribbean
remittances/emigrants) Caribbean subsample)
war subsample)

Emigrant flow, World/LAC averages of

Effects of Real GDP growth in the US, FDI/GDP, export
Real per capita GDP remittances/GDP, govt endogenous variables, rural
remittances and growth, change in terms of trade, country risk,
growth spending/GDP, population, unemployment
migration emigrants/population
M2/GDP in destination

weighted GPD per capita in

terms of trade, FDI/GDP, real GDP growth, remittances/GDP, destination, weighted
REER (in log)
government spending/GDP, US interest rate export/GDP residuals unemployment in
destination
World/LAC averages for
Remittances/GDP, real
per capita PPP GDP, real GDP growth in US, endogenous variables,
per capita GDP growth,
Inflation FDI/GDP, emigrants/population, rural unemployment in
Effects of export growth, country
population destination and changes in
remittances and risk
terms of trade
migration
NPLs to total gross loans as above as above as above

World/LAC averages for

per capita PPP GDP, real GDP growth in US, endogenous variables,
Remittances/GDP, real
Revenue/GDP FDI/GDP, emigrants/population, rural unemployment in
per capita GDP growth
population destination and changes in
terms of trade
 64

VIII. ANNEX III. REGRESSION TABLES

Annex Table 3.1. Determinants of Migration Flows

Central
America,
Emerging South
World LAC Latin America Carribbean Mexico Panama, and
Markets America
the Dominican
Republic

Change in emigrants/population (FE regressions)

Real per capita GDP growth 0.00274* 0.0133*** 0.00911** 0.00177 0.000841 0.0171** 0.00176 -0.000696
(0.00156) (0.00477) (0.00357) (0.00160) (0.00119) (0.00667) . (0.00388)
Emigrants/population -0.00640 -0.0324*** -0.0222*** -0.000709 0.0325 -0.0178* 0.0583 0.00153
(0.0112) (0.0107) (0.00748) (0.0112) (0.0186) (0.00899) . (0.00572)
PPP GDP per capita -0.00391 0.00146 -0.0181* -0.00789 -0.00961 -0.0207 0.0455 -0.0141
(0.00394) (0.0238) (0.00957) (0.00803) (0.00726) (0.0195) . (0.0118)
Unemployment in destination -0.000196 0.00515 0.00168 0.000482 0.00211 -0.00145 0.0109 0.00306
(0.00584) (0.0135) (0.00696) (0.00163) (0.00262) (0.0180) . (0.00191)
Inflation 0.0000151 0.00271*** 0.00000172 -0.00000521 0.00000606 0.00536** 0.000842 -0.0000451
(0.0000172) (0.000902) (0.00000573) (0.00000477) (0.00000725) (0.00196) . (0.000988)
Age dependency 0.00812*** 0.00758 0.00865 -0.000730 0.00382 0.0133 -0.123 0.00528*
(0.00307) (0.00823) (0.00715) (0.00330) (0.00237) (0.0104) (0) (0.00263)
Rural population -0.0196*** -0.0141 -0.0264*** -0.00664 -0.0206* -0.0210** 0.521 -0.00873
(0.00568) (0.0139) (0.00706) (0.00519) (0.0107) (0.00859) . (0.00489)
Natural disaster 0.00716 -0.00723 -0.0285 0.00670 0.0356 -0.0386 . -0.0290
(0.0209) (0.0353) (0.0261) (0.0232) (0.0266) (0.0458) . (0.0172)
War 0.0184 0.119* 0.00786 0.0270* 0.00869 -0.0116 0.0314 -0.000246
(0.0176) (0.0711) (0.0329) (0.0136) (0.00886) (0.132) . (0.0140)
Number of obs. 4162 834 936 563 313 373 33 217
Change in emigrants to US/population (FE regressions)
Real per capita GDP growth 0.000110 -0.000573 -0.000154 -0.000212 -0.0000926 -0.00127 -0.000513 0.000655
(0.000166) (0.000849) (0.00141) (0.000613) (0.000173) (0.00280) (0) (0.00228)
Emigrants/population 0.000275 -0.00714* -0.0145 -0.00920 0.00381 -0.0162 -0.250 -0.0288*
(0.00279) (0.00378) (0.00897) (0.0153) (0.00260) (0.0110) (0) (0.0133)
PPP GDP per capita -0.000319 0.00120 0.00236 0.000775 0.000977* 0.00388 0.0201 -0.0101
(0.000290) (0.00259) (0.00235) (0.00246) (0.000522) (0.00507) . (0.00621)
Unemployment in destination -0.00536*** -0.00711** -0.00344* -0.000222 -0.000831* -0.00975** 0.00112 0.000788
(0.00150) (0.00332) (0.00177) (0.00172) (0.000394) (0.00348) . (0.00673)
Inflation 0.0000193 -0.000724 -0.000838 -0.000666* -0.000277* -0.00179 0.0127 -0.000365
(0.000164) (0.000572) (0.000778) (0.000369) (0.000132) (0.00238) . (0.00141)
Age dependency -0.000775 0.00198 0.00463* 0.00499 0.000786 0.00402 0.0288 0.00523
(0.00178) (0.00259) (0.00266) (0.00379) (0.00148) (0.00356) . (0.00551)
Rural population -0.00576** -0.00609 -0.00925** -0.00781 0.00327 -0.00546 -0.141 -0.0168
(0.00278) (0.00577) (0.00447) (0.00806) (0.00273) (0.00600) (0) (0.0138)
Natural disaster 0.00210 0.00474 -0.00260 0.00400 0.00274 -0.00585 . -0.0109
(0.00400) (0.0112) (0.0219) (0.0148) (0.00539) (0.0301) . (0.0267)
War 0.000892 0.00261 0.00534 0.00647 0.0166*** -0.0800 . -0.0234
(0.00261) (0.00787) (0.00771) (0.00667) (0.00500) (0.0624) . (0.0252)
Number of obs. 1717 396 290 180 100 110 10 70
Change in emigrants to US/population (IV regressions)
Real per capita GDP growth -0.000604 -0.00348 -0.00113 -0.000891 -0.000205 0.0221 -0.00183 -0.0000586
(0.00118) (0.00239) (0.00354) (0.00166) (0.000623) (0.0192) (0.00568) (0.00371)
Emigrants/population 0.000317 -0.00700*** -0.0146*** -0.00903* 0.00415 -0.0134 -0.415 -0.0289***
(0.000983) (0.00248) (0.00497) (0.00471) (0.00349) (0.0111) (0.831) (0.00901)
PPP GDP per capita -0.000269 0.000213 0.00229 0.000781 0.000940 0.00352 0.0295 -0.00967*
(0.000514) (0.00275) (0.00251) (0.00163) (0.000665) (0.00832) (0.0430) (0.00562)
Unemployment in destination -0.00588*** -0.00920*** -0.00403 -0.000526 -0.000870** 0.00910 0.00251 0.000363
(0.00138) (0.00266) (0.00264) (0.00124) (0.000414) (0.0161) (0.00645) (0.00328)
Inflation -0.0000449 -0.000868 -0.000886 -0.000734 -0.000285 -0.00222 0.00722 -0.000455
(0.000229) (0.000792) (0.000967) (0.000594) (0.000269) (0.00360) (0.0242) (0.00118)
Age dependency -0.000737 0.00195 0.00456*** 0.00494*** 0.000945 0.00809 0.0249 0.00513**
(0.000602) (0.00129) (0.00176) (0.00147) (0.00175) (0.00548) (0.0864) (0.00235)
Rural population -0.00578*** -0.00573** -0.00952*** -0.00770*** 0.00298 0.00484 -0.176 -0.0164***
(0.00114) (0.00288) (0.00293) (0.00268) (0.00316) (0.0113) (0.429) (0.00538)
Natural disaster 0.00242 0.00612 -0.00290 0.00367 0.00284 -0.00382 . -0.0121
(0.00398) (0.00748) (0.0114) (0.0113) (0.00398) (0.0250) . (0.0277)
War 0.000698 0.0000425 0.00358 0.00534 0.0163*** 0.00532 . -0.0224
(0.00516) (0.0124) (0.0195) (0.00973) (0.00320) (0.154) . (0.0297)
Number of obs. 1710 392 290 180 100 110 10 70
Note: The table contains results from panel regressions. The dependent variable is emigrant flows as percent of the population. See Annex 2.1 for further
methodological details.
Standard errors in parantheses; ***p<0.01; **p<0.05; *p<0.1.
65
 66

Annex Table 3.2. Determinants of Remittances 1/

Central
America,
Emerging South Panama, and
World LAC Latin America Carribbean Mexico
Markets America the
Dominican
Republic
Remittances/GDP (FE regressions)
Real per capita GDP growth 0.0520** 0.0506 0.00295 0.0148 -0.0105 -0.00755 0.00857 0.144*
(0.0248) (0.0483) (0.0274) (0.0361) (0.0168) (0.0468) . (0.0669)
Change in LC/USD exchange rate 0.00213*** 0.000983 -0.00453 -0.00415 -0.000317 -0.0415 0.00375 -0.0127
(0.000580) (0.000925) (0.00441) (0.00405) (0.00157) (0.0258) . (0.0184)
Emigrants/population 0.168 0.126 0.443** 0.300* 0.468 0.509* -0.525 0.580*
(0.115) (0.148) (0.208) (0.149) (0.321) (0.257) (0) (0.262)
PPP GDP per capita -0.0287 -0.195 -0.248** -0.302* -0.0455 -0.171* -0.140 0.0670
(0.0233) (0.203) (0.102) (0.145) (0.0592) (0.0857) (0) (0.127)
Unemployment in destination (lagged) -0.125*** -0.117 -0.121*** -0.144** -0.146* -0.0513 -0.0118 -0.221*
(0.0453) (0.0782) (0.0435) (0.0596) (0.0648) (0.0734) (0) (0.105)
Inflation -0.00189*** -0.000925 0.00435 0.00411 0.000469 0.0225 -0.00273 0.0312*
(0.000500) (0.0161) (0.00404) (0.00365) (0.00138) (0.0680) (0) (0.0135)
Age dependency -0.0460 -0.0173 -0.0440 -0.309** 0.119 0.0774 0.685 -0.585***
(0.0397) (0.0617) (0.0968) (0.128) (0.116) (0.109) . (0.126)
Rural population -0.0475 0.0253 -0.224*** 0.00855 -0.319 -0.136 -3.076 0.477**
(0.0671) (0.157) (0.0703) (0.0955) (0.254) (0.140) (0) (0.170)
Average age at entry -0.00200 0.0112 -0.0385 -0.186*** -0.0620*** 0.00589 -0.259 -0.166
(0.0215) (0.0324) (0.0411) (0.0567) (0.0133) (0.0167) (0) (0.131)
Female migration share -0.196 -0.293 0.161 -0.172 0.308 0.305 -1.383 -1.595
(0.241) (0.204) (0.231) (0.450) (0.412) (0.252) (0) (1.031)
Natural disaster 0.173 0.218 0.135 -0.108 -0.331 0.169 . 0.880**
(0.175) (0.201) (0.298) (0.566) (0.405) (0.325) . (0.337)
War -0.302 -0.989* -1.150* -0.689 0.134 -1.771 . -0.595
(0.183) (0.531) (0.579) (0.406) (0.116) (1.484) . (0.608)
Number of obs. 2401 690 627 397 210 230 24 163
Workers' remittances/GDP (FE regressions)

Real per capita GDP growth 0.0360** 0.0634* -0.000712 0.0252 -0.0166 -0.0184 0.00371 0.121
(0.0161) (0.0364) (0.0281) (0.0373) (0.0202) (0.0472) . (0.0646)
Change in LC/USD exchange rate 0.000174 0.0114* -0.00515 -0.00414 -0.000881 -0.0601 0.00282 -0.0113
(0.000979) (0.00612) (0.00463) (0.00393) (0.00206) (0.0415) . (0.0168)
Emigrants/population 0.0665 0.103 0.323 0.233 0.803** 0.377 -0.509 0.437
(0.105) (0.131) (0.236) (0.158) (0.327) (0.308) (0) (0.252)
PPP GDP per capita -0.0985** -0.175 -0.289** -0.362* -0.0695 -0.177 -0.0782 0.114
(0.0400) (0.143) (0.113) (0.189) (0.0725) (0.0972) (0) (0.115)
Unemployment in destination (lagged) -0.0875 -0.111 -0.117** -0.164** -0.147** -0.0181 -0.00248 -0.227**
(0.0533) (0.0797) (0.0520) (0.0649) (0.0612) (0.0903) (0) (0.0866)
Inflation -0.0000777 0.000986 0.00499 0.00414 0.000912 0.0490 -0.00172 0.0292*
(0.000945) (0.0167) (0.00420) (0.00351) (0.00182) (0.0819) (0) (0.0127)
Age dependency -0.0867* -0.0258 -0.115 -0.365** 0.194 0.0115 0.656 -0.631***
(0.0490) (0.0646) (0.0900) (0.132) (0.161) (0.0943) . (0.125)
Rural population -0.126* -0.00503 -0.223*** -0.0116 -0.443 -0.146 -2.922 0.473**
(0.0737) (0.140) (0.0721) (0.112) (0.327) (0.136) (0) (0.154)
Average age at entry 0.00550 0.0360 -0.0368 -0.175** -0.0547*** 0.00195 -0.292 -0.197
(0.0215) (0.0344) (0.0374) (0.0618) (0.0145) (0.0151) (0) (0.143)
Female migration share -0.378 -0.290 0.0797 -0.334 0.0955 0.269 -1.350 -1.974
(0.305) (0.216) (0.281) (0.500) (0.467) (0.300) (0) (1.047)
Natural disaster 0.231 0.403** 0.232 0.363 0.0262 0.180 . 0.840**
(0.234) (0.193) (0.322) (0.331) (0.328) (0.327) . (0.277)
War -0.187 -0.540 -1.088* -0.608 0.126 -1.678 . -0.419
(0.208) (0.407) (0.560) (0.390) (0.131) (1.555) . (0.605)
Number of obs. 1665 612 570 356 174 214 24 158
Workers' remittances/GDP (IV regressions)
Real per capita GDP growth 0.0328 0.181 0.101 0.0783 0.0720 0.308* 0.00198 0.255**
(0.147) (0.762) (0.0902) (0.0892) (0.108) (0.185) (0.0195) (0.103)
Change in LC/USD exchange rate -0.0434 -0.0212 -0.0432 -0.0355 0.0387 -0.0699**
(0.0672) (0.457) (0.0586) (0.0471) (0.0435) (0.0346)
Emigrants/population 0.0131 0.0268 0.371*** 0.229** 0.781*** 0.376*** -0.608*** 0.453***
(0.0528) (0.246) (0.0812) (0.0953) (0.285) (0.0671) (0.230) (0.117)
PPP GDP per capita -0.103*** -0.0240 -0.396*** -0.445*** 0.0919 -0.194** -0.140 0.0101
(0.0372) (0.205) (0.0670) (0.0958) (0.219) (0.0793) (0.183) (0.171)
Unemployment in destination (lagged) -0.0357 -0.0963 -0.136*** -0.131** -0.266* 0.121 -0.0132 -0.206***
(0.0578) (0.0823) (0.0505) (0.0593) (0.155) (0.113) (0.0428) (0.0764)
Inflation 0.0398 0.0121 0.0399 0.0329 -0.0352 0.0620 0.000847 0.0331
(0.0612) (0.0866) (0.0534) (0.0429) (0.0396) (0.0479) (0.00634) (0.0238)
Age dependency -0.0867*** 0.0249 -0.272*** -0.372*** 0.174 -0.0108 0.614*** -0.635***
(0.0171) (0.0725) (0.0321) (0.0363) (0.117) (0.0361) (0.124) (0.0528)
Rural population -0.126*** -0.0860 -0.0963** -0.0505 -0.0760 -0.102 -2.960*** 0.434***
(0.0312) (0.0805) (0.0445) (0.0710) (0.478) (0.0724) (0.363) (0.113)
Average age at entry 0.00758 0.0449 -0.0898*** -0.198*** 0.00338 0.0151 -0.300*** -0.185*
(0.0191) (0.0327) (0.0322) (0.0466) (0.0776) (0.0426) (0.0592) (0.106)
Female migration share -0.194** -0.300** -0.268 -0.386** 0.608 0.203 -1.366*** -1.991***
(0.0887) (0.132) (0.209) (0.193) (0.630) (0.171) (0.344) (0.494)
Natural disaster 0.257 0.323 0.623* 0.328 0.382 0.185 . 1.011*
(0.231) (0.287) (0.353) (0.473) (0.748) (0.400) . (0.551)
War -0.294 -0.522 -0.449 -0.504 0.144 -1.810** . -0.436
(0.184) (0.436) (0.337) (0.312) (0.408) (0.900) . (0.457)
Number of obs. 1413 511 486 356 174 214 24 158
Note: The table contains results from panel regressions. The dependent variables are remittances and workers' remittances as a percent of GDP. See Annex 2.1
for further methodological details.
Standard errors in parantheses; ***p<0.01; **p<0.05; *p<0.1.
1/ See Annex I for the concepts of "remittances" and the more narrow "worker's remittances."
 67

Annex Table 3.3. Effects on Growth (FE regressions)

Effects on short term growth, Real per capita GDP growth
Central
America,
Emerging Latin South Panama,
World LAC Carribbean Carribbean Mexico
Markets America America and the
Dominican
Republic
Change in emigrants/population 4.174*** 3.224*** 2.478** 4.288*** 2.848 2.360 2.295 9.630 12.85***
(1.582) (1.141) (0.937) (1.283) (2.472) (2.247) (1.767) . (2.982)
Remittances/GDP 0.0347 0.119 -0.0174 0.0406 -0.657 -0.159 -0.0620 0.923 0.129
(0.0659) (0.156) (0.0863) (0.117) (0.515) (0.129) (0.0793) . (0.0722)
Expenditure/GDP -0.0449 -0.0408 -0.0223 -0.00901 0.00965 -0.0404 -0.0310 0.706 -0.298
(0.0628) (0.0900) (0.0979) (0.126) (0.159) (0.0835) (0.0962) . (0.333)
M2/GDP -1.113 -4.694** 0.126 2.830 5.006 -4.087 -8.991** -19.49 -1.695
(0.714) (2.309) (2.988) (2.801) (4.296) (7.077) (3.973) (0) (9.707)
PPP GDP per capita 0.0897* 0.167 0.167 0.387*** 0.308** -0.671*** -0.0891 0.168 0.364***
(0.0475) (0.113) (0.164) (0.119) (0.116) (0.0290) (0.168) . (0.0770)
Real GDP growth in AEs/U.S. 0.589*** 0.599*** 0.537*** 0.659*** 0.561** 0.129 0.626** 0.927 0.739***
(0.0710) (0.104) (0.104) (0.111) (0.215) (0.128) (0.275) . (0.137)
FDI/GDP -0.00717 -0.00916 -0.0499 0.109 0.254 -0.151 -0.298** 0.362 -0.275*
(0.0117) (0.106) (0.145) (0.145) (0.202) (0.0882) (0.108) . (0.129)
Export growth 0.000329 0.0108 -0.0000634 -0.000131 -0.0000926 0.0640* 0.0435 -0.0565 0.00373
(0.000233) (0.0161) (0.000191) (0.000177) (0.000209) (0.0263) (0.0266) (0) (0.0346)
Change in terms of trade 0.0204** 0.0175 0.0485*** 0.0405*** 0.0392*** 0.0375 0.0239 0.247 0.0119
(0.00996) (0.0195) (0.0128) (0.0135) (0.0101) (0.0277) (0.0217) . (0.0256)
Country risk 0.210*** 0.328*** 0.133** 0.131** 0.173* 0.420** 0.387 0.0691
(0.0522) (0.0517) (0.0468) (0.0528) (0.0749) (0.0967) . (0.0773)
Emigrants/population 0.173 0.244 0.290 -0.0585 0.382 0.819** 0.0699 -0.282 0.179
(0.119) (0.202) (0.209) (0.274) (0.253) (0.245) (0.0468) (0) (0.386)
Number of obs. 1126 652 361 299 170 62 152 24 105
Effects on long term growth, Real per capita GDP growth
Central
America,
Emerging Latin South Panama,
World LAC Carribbean
Markets America America and the
Domican
Republic
Change in emigrants/population -1.182 2.442 -1.019 0.0418 -19.91*** 2.483 3.214
(1.261) (2.851) (1.644) (4.026) (5.106) (1.647) (10.64)
Remittances/GDP -0.00206 0.387* -0.339** -0.187 0.297 0.277 -0.349**
(0.0950) (0.208) (0.130) (0.136) (0.461) (0.163) (0.0935)
Expenditure/GDP 0.0243 -0.407 0.0253 0.0417 -0.134 0.0251 0.477**
(0.0491) (0.292) (0.0596) (0.102) (0.0781) (0.138) (0.128)
M2/GDP -0.559* 0.197 0.702 -0.640 -9.443** -11.33*** 2.788
(0.285) (8.092) (3.935) (3.957) (3.285) (2.577) (4.933)
PPP GDP per capita -0.0972* -0.452 -0.122 0.0538 0.221** 0.0107 -0.260**
(0.0553) (0.458) (0.148) (0.119) (0.0920) (0.111) (0.0753)
Real GDP growth in AEs/U.S. -0.0218 0.322 -0.662** -0.440* -0.882* -0.0577 -0.0942
(0.234) (0.688) (0.305) (0.240) (0.448) (0.499) (0.193)
FDI/GDP -0.0232 -0.0711 -0.373 -0.139 -0.00465 -0.239* -0.830**
(0.0156) (0.129) (0.266) (0.259) (0.289) (0.130) (0.251)
Export growth 0.000580 0.0665 0.00185*** 0.00168** -0.000321 0.168*** -0.0477
(0.000813) (0.0755) (0.000410) (0.000657) (0.000891) (0.0451) (0.0287)
Change in terms of trade 0.00308 -0.155 0.00917 0.0370 -0.185 -0.242* 0.248***
(0.0533) (0.158) (0.0742) (0.0684) (0.119) (0.133) (0.0555)
Country risk 0.139** 0.223 0.150*** 0.154*** 0.121* 0.0206
(0.0544) (0.231) (0.0452) (0.0464) (0.0606) (0.116)
Emigrants/population 0.0868 0.512 0.364** 0.218 1.820*** -0.0531 0.264
(0.0976) (0.349) (0.145) (0.274) (0.385) (0.0482) (0.299)
Number of obs. 270 53 83 67 39 37 23

Note: The table contains results from panel regressions. The dependent variable is real per capita GDP growth. See Annex 2.1 for further
methodological details.
Standard errors in parantheses; ***p<0.01; **p<0.05; *p<0.1.
 68

Annex Table 3.4. Effects on Growth (IV Regressions)

Effects on short term growth, Real per capita GDP growth
Central
America,
Emerging Latin South Panama,
World LAC Carribbean Carribbean Mexico
Markets America America and the
Dominican
Republic
Change in emigrants/population -5.066 -14.41** -13.97*** -19.68*** -33.63** 9.048 -27.14 -15.21 -6.108
(14.44) (6.935) (4.734) (6.869) (13.68) (5.695) (31.75) (16.59) (25.36)
Remittances/GDP -0.173 2.128*** 0.990*** 0.837* 1.220 -0.187 2.277 -1.212 0.0297
(0.857) (0.784) (0.305) (0.452) (1.461) (0.192) (2.018) (2.217) (0.241)
Expenditure/GDP 1.412 -0.287 0.179 0.901 0.405 -0.0586 -0.566 1.145** -1.291*
(1.283) (0.303) (0.352) (0.693) (0.390) (0.105) (0.516) (0.453) (0.716)
M2/GDP -48.45 15.23 -9.243 -42.78 -77.66** -9.721 -14.29 -68.29* 13.11
(41.83) (13.97) (10.17) (32.50) (34.53) (7.704) (13.52) (38.06) (32.58)
PPP GDP per capita 1.068 0.0899 0.199 0.242 0.740* -0.608*** 0.678 0.291 0.187
(0.913) (0.313) (0.280) (0.388) (0.448) (0.196) (0.722) (1.194) (0.243)
Real GDP growth in AEs/U.S. 0.837** 0.460** 0.577*** 0.636*** 0.507 0.197 0.561 1.279*** 0.769***
(0.355) (0.186) (0.163) (0.218) (0.309) (0.211) (0.459) (0.405) (0.177)
FDI/GDP -0.0184 0.343 0.297** 0.556** 0.538* -0.227 -0.154 1.043 -0.427
(0.0379) (0.226) (0.151) (0.270) (0.292) (0.152) (0.194) (0.774) (0.381)
Export growth 0.000981 -0.00882 -0.0000628 0.000557 0.000654 0.0665*** -0.0417 -0.0369* -0.0345
(0.00137) (0.0147) (0.000556) (0.000841) (0.000741) (0.0222) (0.0925) (0.0217) (0.0240)
Change in terms of trade 0.0414 0.0446 0.0400 0.0178 -0.0202 0.0379 0.00691 -0.00616 -0.0468
(0.0383) (0.0348) (0.0256) (0.0377) (0.0456) (0.0344) (0.0894) (0.185) (0.0653)
Country risk 0.141 0.220* 0.181*** 0.231*** 0.188* 0.462*** 0.647 0.0465
(0.126) (0.123) (0.0582) (0.0809) (0.104) (0.135) (0.418) (0.0990)
Emigrants/population -0.152 -0.662 -0.404 0.654 4.727*** 0.982** -0.172 0.551 0.755
(0.375) (0.482) (0.322) (0.575) (1.432) (0.410) (0.302) (1.326) (0.849)
Number of obs. 1126 277 361 299 170 62 152 24 105
Effects on long term growth, Real per capita GDP growth
Central
America,
Emerging Latin South Panama,
World LAC Carribbean
Markets America America and the
Domican
Republic
Change in emigrants/population 2.134 0.144 -10.06** -12.37** -22.46** 2.446* -3.948
(24.15) (5.031) (4.756) (5.271) (9.446) (1.249) (10.51)
Remittances/GDP 0.121 0.212 -0.427* -0.134 0.292 0.356*** -0.255*
(0.696) (0.347) (0.219) (0.244) (1.005) (0.128) (0.144)
Expenditure/GDP 0.253 0.530 0.446 0.273 -0.0535 0.122 0.979***
(0.359) (0.598) (0.312) (0.322) (0.113) (0.0914) (0.354)
M2/GDP -17.95 -12.99 10.24 -3.741 -20.21** -12.96*** -13.11
(60.09) (18.87) (8.029) (11.58) (8.034) (2.916) (11.92)
PPP GDP per capita 0.418 -0.522 -0.611* -0.182 0.267** 0.0123 -0.225
(1.898) (0.721) (0.317) (0.307) (0.134) (0.103) (0.162)
Real GDP growth in AEs/U.S. -0.0532 0.142 -1.047** -0.706 -0.959** -0.0780 -0.0559
(1.172) (0.730) (0.443) (0.440) (0.408) (0.421) (0.247)
FDI/GDP -0.0132 0.0865 -0.0609 0.0548 0.0966 -0.214** -1.034***
(0.0700) (0.185) (0.249) (0.256) (0.306) (0.0885) (0.266)
Export growth 0.0000535 0.0970 0.00245 0.00165 -0.000591 0.210*** -0.0390
(0.00283) (0.0701) (0.00167) (0.00158) (0.00106) (0.0465) (0.0277)
Change in terms of trade -0.0101 -0.180 -0.267 -0.122 -0.245 -0.242** 0.351***
(0.137) (0.176) (0.194) (0.177) (0.194) (0.0968) (0.129)
Country risk 0.0252 0.381 0.296*** 0.244*** 0.123 -0.0670
(0.464) (0.266) (0.100) (0.0800) (0.0765) (0.106)
Emigrants/population -0.159 0.479 0.0971 0.440 2.318*** -0.0665 -0.192
(0.597) (0.297) (0.270) (0.318) (0.428) (0.0485) (0.359)
Number of obs. 270 53 83 67 39 37 23

Note: The table contains results from panel regressions. The dependent variable is real per capita GDP growth. See Annex 2.1 for further
methodological details.
Standard errors in parantheses; ***p<0.01; **p<0.05; *p<0.1.
 69

Annex Table 3.5. Global Consumption Risk Sharing

World EMDE LAC SSA CIS EM Asia LA CAPDR Caribbean
Remittances/GDP 0.000852 0.000877 -0.000437 0.00196 0.00145 0.000634 0.000114 0.000166 -0.00164
(0.173) (0.197) (0.666) (0.499) (0.226) (0.532) (0.861) (0.811) (0.443)
Δŷ 0.910*** 0.918*** 0.867*** 1.079*** 0.870*** 0.551*** 0.847*** 0.581*** 0.862***
(0) (0) (0) (0) (1.49e-06) (1.54e-05) (0) (2.42e-06) (0.000172)
Remittances*Δŷ -0.0380*** -0.0388*** -0.0477** -0.0478 -0.0454** -0.00796 0.0148 0.0278 -0.0663*
(0.000216) (0.000579) (0.0183) (0.259) (0.0391) (0.670) (0.437) (0.217) (0.0639)
Constant -0.0127*** -0.0127*** -0.00741 -0.0156* 0.0149* -0.00286 -0.0132*** -0.00787 0.00168
(1.92e-06) (0.000104) (0.148) (0.0864) (0.0919) (0.636) (5.96e-06) (0.126) (0.892)
Observations 2,747 2,329 778 601 99 321 442 196 336
R-squared 0.110 0.103 0.091 0.098 0.251 0.071 0.350 0.222 0.046
Countries 143 121 30 36 7 16 17 7 13
Note: The table contains results from panel regressions with country-specific and time fixed effects. The dependent variable is idiosyncratic real
consumption growth, and Δŷ is idiosyncratic real output growth; both of them are calculated as differences between country-specific and world growth
rates. P-values are reported in parentheses, and significance at 10, 5, and 1 percent is denoted by *, **, and ***, respectively.

Annex Table 3.6. Regional Consumption Risk Sharing

LAC LA CAPDR Caribbean
Remittances/GDP 0.00181 -0.000120 0.000302 -0.00110
(0.240) (0.886) (0.716) (0.665)
Δŷ 1.080*** 1.059*** 1.002*** 1.260***
(0) (0) (0) (0)
Remittances*Δŷ -0.0346*** -0.100*** -0.0754*** -0.0732***
(3.86e-05) (0) (8.85e-08) (2.37e-10)
Constant -0.0138* -0.00453 -0.00512 -0.00209
(0.0628) (0.204) (0.380) (0.891)
Observations 602 455 200 173
R-squared 0.936 0.989 0.938 0.848
Countries 24 17 7 7
Note: The table contains results from panel regressions with country-
specific and time fixed effects. The dependent variable is idiosyncratic
real consumption growth, and Δŷ is idiosyncratic real output growth;
both of them are calculated as differences between country-specific
and growth rates for the Western Hemisphere. P-values are reported
in parentheses, and significance at 10, 5, and 1 percent is denoted by
*, **, and ***, respectively.
 70

Table 3.7. Regional Consumption Risk-Sharing (Panel Regressions)

LAC LA CAPDR Caribbean
Remittances/GDP 0.00148 0.000118 0.000887 -0.00140
(0.360) (0.894) (0.331) (0.620)
Δŷ 1.391*** 1.076*** 0.920*** 1.414***
(0) (0) (0) (2.23e-08)
Remittances*Δŷ -0.0484*** -0.0790*** -0.0787*** -0.0915***
(9.98e-08) (9.57e-08) (2.90e-05) (9.32e-06)
Financial openness (de jure)*Δŷ -0.0584*** -0.0221*** -0.0444* 0.0849
(1.26e-08) (3.81e-07) (0.0621) (0.608)
Financial integration (de facto, FDI)*Δŷ -0.845*** 0.0275** -0.0454** 0.0669
(1.95e-08) (0.0294) (0.0164) (0.909)
Financial integration (de facto, portfolio)*Δŷ1.716*** -0.472** 1.341*** -0.588
(1.47e-08) (0.0384) (0.00295) (0.610)
Constant -0.0147* -0.00594 -0.00784 -0.0103
(0.0591) (0.107) (0.183) (0.570)
Observations 517 408 210 135
R-Squared 0.946 0.990 0.990 0.881
Countries 23 17 7 6
Note: The table contains results from panel regressions with country-specific and time fixed
effects. The dependent variable is idiosyncratic real consumption growth, and Δŷ is idiosyncratic
real output growth; both of them are calculated as differences between country-specific growth
rates and aggregate growth rates for the Western Hemisphere. Financial openness (de jure)
stands for the index of de jure capital account openness from Chinn-Ito (2006), while Financial
integration (de facto) refers to de facto financial integration measured by FDI and equity portfolio
and is retrieved from the updated and extended version of the dataset by Lane and Milesi-Ferretti
(2007). P-values are reported in parentheses, and significance at 10, 5, and 1 percent is denoted by
*, **, and ***, respectively.
 71

Annex Table 3.8. Effects on Revenue (FE Regressions)

Central
America,
Latin America
Emerging Panama, and
World and the Latin America South America Carribbean Mexico
Markets the
Caribbean
Dominican
Republic
Revenue/GDP
Remittances/GDP -0.0308 0.0906 0.260** 0.273 1.126 0.193** 1.526 0.304**
(0.121) (0.0872) (0.0971) (0.195) (1.052) (0.0787) . (0.0969)
Real per capita GDP growth 0.0543 0.0295 0.0750 0.206** 0.239** -0.0539 0.111 0.0103
(0.0469) (0.0618) (0.0655) (0.0952) (0.0915) (0.0742) . (0.0563)
PPP GDP per capita 0.0831 0.513** 0.370** 0.352 0.511 0.427* 0.610 0.271
(0.0593) (0.226) (0.166) (0.393) (0.439) (0.215) . (0.300)
Real GDP growth in U.S. -0.0416 -0.108 -0.243*** -0.181 -0.246 -0.257*** -0.417 0.0421
(0.0868) (0.0854) (0.0866) (0.143) (0.171) (0.0839) (0) (0.0904)
FDI/GDP -0.00736 -0.00953 0.0593 0.150 -0.321 0.0124 -0.176 0.170*
(0.00972) (0.0195) (0.0579) (0.166) (0.315) (0.0408) (0) (0.0712)
Emigrants/population 0.000181 -0.0959 -0.0150 0.479 0.249 -0.0653 -2.819 0.318
(0.0711) (0.137) (0.120) (0.454) (0.895) (0.134) (0) (0.286)
Rural population -0.164* -0.0134 -0.0538 0.0788 0.0266 -0.256 -1.732 0.212
(0.0880) (0.103) (0.206) (0.329) (0.579) (0.210) (0) (0.314)
Number of obs. 3026 785 688 399 221 289 24 154
Note: The table contains results from panel regressions. The dependent variable is revenue as a percent of GDP. See Annex 2.1 for further methodological
details.
Standard errors in parantheses; ***p<0.01; **p<0.05; *p<0.1.

Annex Table 3.9. Effects on Revenue (IV Regressions)

Central America,
Latin America
Emerging Panama, and the
World and the Latin America South America Carribbean Mexico
Markets Dominican
Caribbean
Republic

Revenue/GDP
Remittances/GDP 1.152** 0.676 0.440 0.251 3.190 1.157** 1.303** 0.393**
(0.496) (0.749) (0.311) (0.489) (2.136) (0.558) (0.546) (0.156)
Real per capita GDP growth 0.0530 -0.447 0.450*** 0.361* 0.433* -0.559** 0.498** -0.372*
(0.445) (0.628) (0.174) (0.193) (0.234) (0.238) (0.237) (0.205)
PPP GDP per capita 0.100* 0.595*** 0.242** 0.284 0.678** 0.540*** -0.540 0.529**
(0.0520) (0.140) (0.114) (0.204) (0.307) (0.129) (0.852) (0.236)
Real GDP growth in U.S. 0.0758 0.250 -0.359** -0.249 -0.269 0.345 -0.879*** 0.239
(0.281) (0.403) (0.149) (0.176) (0.252) (0.281) (0.309) (0.164)
FDI/GDP 0.00649 -0.00714 0.209*** 0.200* -0.474* -0.0997 -0.473 -0.0268
(0.0104) (0.0221) (0.0755) (0.116) (0.268) (0.104) (0.381) (0.134)
Emigrants/population 0.0640 -0.0553 0.0264 0.493 -0.00295 -0.0777 -3.175*** 0.206
(0.0626) (0.0808) (0.0811) (0.362) (0.515) (0.0782) (0.816) (0.200)
Rural population -0.112** 0.0963 -0.0189 0.0707 0.521 -0.330 -3.510** 0.324***
(0.0542) (0.146) (0.0928) (0.120) (0.528) (0.205) (1.482) (0.119)
Number of obs. 2362 619 568 399 221 169 24 154
Note: The table contains results from panel regressions. The dependent variable is revenue as a percent of GDP. See Annex 2.1 for further methodological
details.
Standard errors in parantheses; ***p<0.01; **p<0.05; *p<0.1.
 72

Annex Table 3.10. Effects of Remittances on NPLs (FE Regressions)

Central America,
Latin America
Emerging Panama, and the
World and the
Markets Dominican
Caribbean
Republic
Nonperforming loans/total gross loans
Remittances/GDP -0.540*** -0.536** -0.204 -0.369***
(0.182) (0.256) (0.133) (0.049)
Real per capita GDP growth -0.297*** -0.402*** -0.240* -0.040
(0.0747) (0.0918) (0.121) (0.086)
Export growth 0.00166 -0.0274 -0.00133 0.0266**
(0.00332) (0.0383) (0.0150) (0.011)
Country risk -0.552*** -0.213 -0.377** -0.173
(0.0918) (0.316) (0.161) (0.183)
PPP GDP per capita -0.178** -1.053*** -0.470** 0.095
(0.0737) (0.255) (0.204) (0.112)
Real GDP growth in U.S. 0.329*** 0.801** 0.222 -0.151
(0.101) (0.310) (0.153) (0.111)
FDI/GDP 0.00202 0.157 0.265* 0.158
(0.00707) (0.0924) (0.136) (0.124)
Emigrants/population 0.340 1.174** -1.618** -0.142
(0.219) (0.490) (0.586) (0.180)
Rural population 0.583*** 0.0253 -0.333 0.160
(0.207) (0.378) (0.200) (0.083)
Number of obs. 1362 313 273 94
Note: The table contains results from panel regressions. The dependent variable is the ratio of
nonperforming loans to total gross loans. See Annex 2.1 for further methodological details.
Standard errors in parantheses; ***p<0.01; **p<0.05; *p<0.1.
 73

Annex Table 3.11. Effects of Remittances on NPLs (IV Regressions)

Central America,
Latin America
Emerging Panama, and the
World and the
Markets Dominican
Caribbean
Republic
Nonperforming loans/total gross loans
Remittances/GDP -0.918** -3.975 -0.475 -.450**
(0.456) (2.553) (0.461) (.216)
Real per capita GDP growth -1.509*** 1.657 -0.855*** 0.105
(0.315) (2.112) (0.290) (0.440)
Export growth 0.0327 -0.398 0.0480 0.045
(0.0362) (0.358) (0.0443) (0.074)
Country risk -0.179 -1.344 0.423 -0.348
(0.240) (1.194) (0.636) (0.216)
PPP GDP per capita -0.146* -1.306 -0.812 -0.292
(0.0824) (1.030) (0.497) (0.194)
Real GDP growth in U.S. 1.023*** 0.658 0.392 -0.359
(0.264) (1.111) (0.289) (0.588)
FDI/GDP -0.00842 0.0130 0.221 -0.023
(0.0141) (0.381) (0.388) (0.388)
Emigrants/population 0.439*** 0.973 0.0842 0.276*
(0.139) (0.652) (0.164) (0.157)
Rural population 0.148*** -0.301 -0.0323 0.148*
(0.0280) (0.247) (0.0650) (0.084)
Number of obs. 1257 303 272 94
Note: The table contains results from panel regressions. The dependent variable is the ratio of
nonperforming loans to total gross loans. See Annex 2.1 for further methodological details.
Standard errors in parantheses; ***p<0.01; **p<0.05; *p<0.1.
 74

Annex Table 3.12. Remittances and the Real Effective Exchange Rate (FE Regressions)
Central
Latin Central Latin America,
Emerging America Latin America, Emerging America Latin Panama,
Carribbean Carribbean
Markets and the America Panama, and Markets and the America and the
Caribbean the Domican Caribbean Domican
Republic Republic
log (REER) 1980-2015 log (REER) 1995-2015
Remittances/GDP 0.00842*** 0.0247*** 0.0266*** 0.0227*** 0.0120** 0.00159 0.00745* 0.00940** 0.00462 0.00240
(0.00290) (0.00646) (0.00680) (0.00551) (0.00531) (0.00149) (0.00384) (0.00427) (0.00451) (0.00517)
Terms of trade 0.00179*** 0.00241*** 0.00331*** 0.00221* -0.00119** 0.00185*** 0.00178*** 0.00234*** 0.00146 -0.000182
(0.000413) (0.000492) (0.000540) (0.00109) (0.000572) (0.000295) (0.000339) (0.000407) (0.00125) (0.000462)
exports of goods and services/GDP -0.00826*** -0.0125*** -0.0141*** -0.00976*** -0.00510** -0.00626*** -0.00942*** -0.0141*** -0.00375*** 0.000977
(0.000933) (0.000860) (0.00131) (0.00234) (0.00242) (0.00112) (0.00188) (0.00252) (0.00129) (0.00103)
FDI/GDP -0.000781 -0.00506** -0.00282 -0.00346 -0.00326 -0.000839* 2.52e-05 0.00844 0.00326 -0.00162
(0.000644) (0.00200) (0.00306) (0.00270) (0.00279) (0.000474) (0.00269) (0.00554) (0.00253) (0.00214)
Real GDP growth 8.58e-08 7.01e-06*** 5.64e-06* 0.000170** 6.03e-05 -0.00197 -0.000790 -0.00278 0.00182 0.000912
(5.61e-08) (2.52e-06) (3.02e-06) (6.64e-05) (0.000195) (0.00122) (0.00247) (0.00336) (0.00286) (0.00105)
Government spending/GDP 0.0118*** 0.00367 0.0106 0.0172*** -0.00599 0.00946*** 0.0124** 0.0138 0.0237*** -0.000480
(0.00272) (0.00279) (0.00663) (0.00569) (0.00605) (0.00252) (0.00476) (0.00961) (0.00779) (0.00266)
US interest rate 0.0129** 0.00900 0.0162* 0.00767 -0.00327 -0.00227 -0.000150 -0.00423 -0.00608 -0.00373
(0.00598) (0.00780) (0.00828) (0.00783) (0.00624) (0.00414) (0.00694) (0.00725) (0.00471) (0.00523)

Observations 1,534 707 509 209 198 1,143 506 329 133 177
Note: The table contains results from panel regressions. The dependent variable is the logged real exchange rate. See Annex 2.1 for further methodological
details.
Standard errors in parantheses; ***p<0.01; **p<0.05; *p<0.1.

Annex Table 3.13. Remittances and the Real Effective Exchange Rate (IV Regressions)
Central
Latin America,
Latin America
Emerging Latin Central America, Emerging America and Latin Panama,
and the Carribbean Carribbean
Markets America Panama, and Markets the America and the
Caribbean
the Domican Caribbean Domican
Republic Republic
log (REER) 1980-2015 log (REER) 1995-2015
Remittances/GDP -0.0438 0.0266 0.00838 0.0608*** 0.00315 -0.0642 -0.0227 -0.0375 0.0369* 0.00502
(0.0364) (0.0330) (0.0524) (0.0224) (0.0160) (0.0443) (0.0288) (0.0391) (0.0196) (0.0161)
Exports/GDP 0.000176 0.00105 -0.00115 -0.00920 0.00448 -0.00173 0.00171 0.00323 -0.0104* 0.00685
(0.00362) (0.00453) (0.00802) (0.00684) (0.00347) (0.00497) (0.00540) (0.00890) (0.00576) (0.00436)
Terms of trade 0.000590 0.00271** 0.00180 0.00336 0.00157 0.00142 0.00148 0.00101 0.00477 0.00170
(0.000978) (0.00135) (0.00196) (0.00225) (0.00138) (0.00117) (0.00135) (0.00168) (0.00291) (0.00138)
FDI/GDP -0.00732 0.00254 0.0125 -0.0474* -0.00341 -0.00662 0.00436 0.0297 -0.00624 -0.00307
(0.00789) (0.00766) (0.0172) (0.0261) (0.00506) (0.00888) (0.00845) (0.0193) (0.0247) (0.00504)
Real GDP growth -0.00456 -0.0113** -0.0193** 0.0119 -0.00289 -0.00302 -0.00981 -0.0261** -0.0194 -0.00260
(0.00603) (0.00487) (0.00910) (0.0102) (0.00553) (0.00733) (0.00605) (0.0108) (0.0167) (0.00549)
Government spending/GDP 0.0183** 0.0115 0.0237 -0.00811 -0.00303 0.0153 0.0228 0.0333 -0.00143 -0.00758
(0.00771) (0.0126) (0.0167) (0.0171) (0.0104) (0.00946) (0.0162) (0.0217) (0.0154) (0.0116)
US interest rate -0.0108 0.00480 -0.00952 0.00750 -0.000654 -0.0101 -0.00711 -0.0236 -0.00527 -0.00275
(0.00833) (0.0138) (0.0244) (0.0138) (0.00889) (0.00873) (0.0124) (0.0200) (0.0118) (0.00906)

Observations 236 121 82 33 39 210 106 68 28 38

Note: The table contains results from panel regressions. The dependent variable is the logged real exchange rate. See Annex 2.1 for further methodological details.
Standard errors in parantheses; ***p<0.01; **p<0.05; *p<0.1.
 75

Annex Table 3.14. Effects on Inflation (FE Regressions)

Central
America,
Latin America
Emerging Panama, and
World and the Latin America South America Carribbean Mexico
Markets the
Caribbean
Dominican
Republic
Inflation (percent)
Remittances/GDP 3.162 0.417** -0.111 0.0436 -6.852 0.711* 2.730 0.175
(2.123) (0.196) (0.562) (0.634) (4.038) (0.275) . (0.218)
Real per capita GDP growth -1.440 -0.597** -1.826* -1.583 -0.672 -0.146 1.959 -0.851*
(1.038) (0.265) (0.929) (1.054) (1.263) (0.236) . (0.357)
Export growth 0.414 0.278*** 1.223*** 1.224*** 1.227*** 0.121*** 0.494 0.167**
(0.309) (0.0808) (0.0383) (0.0387) (0.0396) (0.0243) . (0.0568)
Country risk -4.502* -0.362*** -0.117 -0.212 -1.734 0.313 -1.995 -0.196
(2.461) (0.0850) (0.687) (0.799) (2.019) (0.245) (0) (0.129)
PPP GDP per capita 0.365 0.281 0.957 0.974 -0.622 0.203 7.879 0.483
(0.745) (0.277) (1.284) (1.948) (3.007) (0.125) . (0.377)
Real GDP growth in U.S. 1.744 -0.301 -3.137** -3.810** -6.726** -0.445 -3.115 -0.787*
(1.941) (0.244) (1.280) (1.423) (2.462) (0.451) (0) (0.326)
FDI/GDP 0.0535 -0.145 -0.240 -0.106 -1.228 -0.0508 -1.635 -0.668**
(0.0856) (0.159) (0.741) (0.978) (2.201) (0.213) (0) (0.209)
Emigrants/population -1.980 -1.344*** -0.993 -3.884* -18.00* -1.325* 4.445 -0.986***
(1.893) (0.145) (0.705) (1.867) (8.869) (0.502) . (0.193)
Rural population 1.229 -0.135 -0.546 -1.442 -9.979* 0.248 14.82 0.444**
(1.325) (0.225) (0.827) (1.587) (4.571) (0.120) . (0.139)
Number of obs. 2572 521 585 473 245 112 30 198
Note: The table contains results from panel regressions. The dependent variable is average period inflation. See Annex 2.1 for further methodological
details.
Standard errors in parantheses; ***p<0.01; **p<0.05; *p<0.1.

Annex Table 3.15. Effects on Inflation (IV Regressions)

Central America,
Latin America
Emerging Panama, and the
World and the Latin America South America Carribbean Mexico
Markets Dominican
Caribbean
Republic

Inflation (percent)
Remittances/GDP 38.75 -2.444 6.797 0.950 17.48 1.350*** -10.17 0.255
(37.77) (2.751) (8.978) (11.62) (97.90) (0.422) (9.467) (0.417)
Real per capita GDP growth -40.63 8.666 -7.068* -5.043 -12.88 -0.817 1.412 0.144
(54.78) (12.69) (3.759) (4.245) (19.90) (0.506) (2.537) (0.759)
Export growth 0.717 -0.396 1.174*** 1.121*** 0.828** 0.148 0.722*** 0.370***
(0.737) (1.334) (0.115) (0.147) (0.367) (0.102) (0.167) (0.100)
Country risk -1.645 -2.206 -0.852 -1.480 -0.985 0.827*** -2.200 -0.123
(11.06) (2.754) (1.422) (1.656) (10.98) (0.236) (1.625) (0.135)
PPP GDP per capita 5.216 -19.59 5.313 4.132 16.91 -0.560 9.517** 0.0563
(5.529) (21.71) (3.435) (3.960) (24.17) (0.359) (3.961) (0.779)
Real GDP growth in U.S. 25.80 -2.837 -0.881 -2.305 -5.067 -0.238 -3.664 -1.362***
(32.07) (3.779) (2.811) (3.671) (13.55) (0.430) (3.434) (0.491)
FDI/GDP -0.0894 1.812 -1.149 -0.740 14.27 0.176 0.857 0.0735
(0.703) (4.149) (1.892) (2.462) (20.89) (0.246) (4.900) (0.414)
Emigrants/population -13.41 0.328 -5.243 -0.931 16.79 -0.425 12.21 -1.253***
(18.68) (2.058) (7.053) (10.78) (51.65) (0.594) (10.88) (0.471)
Rural population 4.465 -8.370 1.375 0.680 31.95 0.856*** 18.06** 0.187
(5.468) (9.580) (2.123) (2.775) (54.30) (0.272) (8.607) (0.348)
Number of obs. 1990 166 548 473 245 75 30 198
Note: The table contains results from panel regressions. The dependent variable is average period inflation. See Annex 2.1 for further methodological
details.
Standard errors in parantheses; ***p<0.01; **p<0.05; *p<0.1.
 76

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