THE EFFECT OF REMITTANCES ON POPULATION HEALTH: AN ANALYSIS OF

REMITTANCES, HEALTH OUTCOMES, AND HEALTH EXPENDITURES

A Thesis submitted to the Faculty of the

Graduate School of Arts and Sciences

of Georgetown University

in partial fulfillment of the requirements for the

degree of Master of Public Policy

By

Andrea Thoumi, M.Sc.

Washington, DC

April 10, 2016

ii

Copyright 2016 by Andrea Thoumi

All Rights Reserved

iii

THE EFFECT OF REMITTANCES ON POPULATION HEALTH: AN ANALYSIS OF

REMITTANCES, HEALTH OUTCOMES, AND HEALTH EXPENDITURES

Andrea Thoumi, M.Sc.

Thesis Advisor: Andreas Kern, Ph.D.

ABSTRACT

While the search for alternative health financing mechanisms to fund national

health systems is not a new international development challenge, fiscal pressures to

identify alternative sources of revenue for health are growing. Today, low- and middle-

income countries are facing a dual burden of infectious and chronic diseases.

Remittances, or the money that migrants send back to their households, have been found

to positively impact certain health outcomes, including infant mortality and under-5

mortality; however, it is less clear if health spending is the channel leading to this

outcome. This study uses data from the World Development Indicators database between

1995-2011 to explore the two-part question of whether remittances are associated with

health spending and if health spending is associated with the positive health outcomes

that result from higher levels of remittances. The study uses a multivariate analysis and a

dynamic GMM approach. The key findings suggest that remittances are not significantly

associated with a reduction in government health spending, but are positively associated

with certain health outcomes, such as infant mortality rate and under-5 mortality rate.

Policy implications include increasing public health spending to raise total health

spending, implementing policy reforms to facilitate the transfer of remittances, and

creating alternative routes to increase household consumption.

iv

To Ines and Charlie

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Table of Contents

Introduction ......................................................................................................................... 1

Chapter 1: Literature Review and Conceptual Framework ................................................ 4

Effect of Remittances on Health Outcomes .................................................................... 4

Effect of Remittances on Health Spending ..................................................................... 5

Effect of Remittances on Public Goods Provision .......................................................... 6

Theoretical Considerations and Hypothesis .................................................................... 7

Chapter 2: Empirical Analysis ............................................................................................ 9

Chapter 3: Results ............................................................................................................. 11

Chapter 4: Policy Implications.......................................................................................... 14

Chapter 5: Conclusions and Limitations ........................................................................... 16

References ......................................................................................................................... 24

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List of Tables

Table 1: Description of World Development Indicators ....................................................... 19

Table 2: Descriptive Statistics (1995-2011) ............................................................................. 20

Table 3: Effects of Remittances (USD) on Health Outcomes ............................................... 21

Table 4: Effect of Public Health Spending (% of Government Expenditure) on Health

Outcomes ....................................................................................................................................... 22

Table 5: Effect of Remittances on Health Spending Measures ........................................... 23

1

Introduction

While the search for alternative health financing mechanisms to fund national

health systems is not a new international development challenge, fiscal pressures to

identify alternative sources of revenue for health are growing.1-3 As low- and middle-

income countries (LMICs) continue to battle infectious diseases and preventable

maternal, child and newborn mortality rates, these countries are undergoing

epidemiological transitions. Driven by aging populations, improved technologies, and

globalization, LMICs are facing a greater burden of non-communicable diseases, such as

cardiovascular disease and diabetes, which are increasingly common causes of mortality

and morbidity.4 Along with the changing needs of populations, efforts to expand

universal health coverage schemes continue to exert pressure on national health accounts,

which are comprised of public and private health expenditures.3 Furthermore, many

factors beyond health expenditure determine health outcomes, higher health spending

reduces adverse health outcomes, including infant mortality rate and under-5 mortality

rate.5,6 Thus, identifying innovative sources to cover rising health spending needs and to

improve population health is relevant and timely.

Theoretically, one funding source that has been identified as a potentially

innovative health financing tool for domestic mobilization of health care expenditures is

the transfer of remittances.3 Remittances are the private transfers of money from a

migrant to family members remaining in the country of origin. In 2015, remittance

financial flows accounted for over $600 billion globally.7 As these cash transfers occur

formally through banks or informally through other channels, this estimate is an

underestimated amount. Compared to other capital inflows, such as foreign direct

2

investment (FDI) and official development assistance (ODA) that are tied to specific

projects, remittances offer relative flexibility and stability to remittance-receiving

households by smoothing income and consumption and increasing the household’s ability

to allocate funding to their specific needs.8-10 For example, for top remittance-receiving

countries, remittances can represent 20 to 40 percent of national gross domestic product

(GDP);7 for remittance-receiving households, remittances can account for up to 50

percent of the household’s income and act as a tool to reduce poverty and income

inequality.11,12 Nevertheless, remittances may also create inflation, increase corruption,

lower governance and increase dependency on an external labor market.13-17 Despite

these potentially challenging macroeconomic effects, many countries and the

international community have argued in favor of using remittances for fostering

economic development.16,18,19

Studies have shown the positive impact of remittances on health outcomes,

including lowering infant mortality rates, increasing infant birth weight, household health

spending, and health knowledge, and equalizing access to care.10,20-23 Despite the positive

effects on health indicators at the micro level, the global evidence on the effect of

remittances on health spending at the macro level is mixed. Some evidence indicates that

remittances can increase corruption and lower political demand for change, resulting in a

government decreasing its social spending.14,24,25 Other studies suggest that the

government will increase accountability instead.15 To date, few studies have analyzed the

effect of remittances on public health expenditures or the exact channel between

remittances and improvements in health outcomes.24,26,27 Therefore, do remittances have

3

an effect on public health spending and through which channel do remittances affect

health outcomes?

The purpose of this paper is to expand the literature around remittances, public

health spending and health outcomes. The two-part study includes an analysis of whether

public health spending is the channel through which remittances are positively affecting

infant mortality rate, under-5 mortality rate, and maternal mortality ratio and if

remittances impact public health spending. The study analysis is based on static and

dynamic (GMM) estimation techniques that are used to model the impact of remittances

on health outcomes and health spending. The use of dynamic estimation techniques

minimizes endogeneity bias – especially reverse causality between remittances and health

spending measures – that might threaten the statistical validity of the analytical results.

This study contributes to the literature by providing preliminary evidence that remittances

will not significantly reduce public health spending suggesting that the results could

mitigate concerns that remittances negatively affect social spending.

While the literature suggests that remittances will likely decrease public health

spending, the data show that there is no effect. Furthermore, the data confirm that

remittances have a positive impact on health, though remittances do not affect maternal

mortality ratio. This is likely because maternal mortality ratio reflects the functional

status of the health care system whereas other health outcome measures, such as infant

mortality rate and under-5 mortality rate, depend on many social determinants of health

beyond health services. Lastly, the data show that raising overall health expenditure, not

other health spending measures, will affect infant mortality rate and under-5 mortality

rate.

4

Chapter 1: Literature Review and Conceptual Framework

Global evidence shows the impact of remittances spans from reducing national

poverty levels to improving economic and social development outcomes, including health

and education.11,18,19,28 Studies have shown that remittances generally have a positive

effect on health outcomes, including reducing infant mortality rate and infant birth

weight, improving child health and increasing overall health spending.20,21,29 Moreover,

remittances have been found to counter the initially negative effect on health of having a

parent leave a household.30 Other studies have suggested that there may be a negative

effect on public health spending because the government may begin to engage in a public

moral hazard knowing that households are now receiving more income from abroad,

which could be invested in health through the private sector.24

Effect of Remittances on Health Outcomes

Overall, studies show the effect of remittances on infant mortality rate is positive.

Kanaiaupuni and Donato (1999) found that migration in Mexico initially had a disruptive

effect on community and family life, increasing infant mortality rate; however, overtime

this effect positively impacted infant mortality rate as communities experienced long-

term migration patterns. Other studies further support the positive association between

remittances and health outcomes. Zhunio, Vishwasrao and Chiang (2012) found that a

1% increase in remittances per capita increased life expectancy by 0.03% and reduced

infant mortality rate by 0.15% in Mexico. Duryea, Lopez Cordova, Olmedo (2005)

posited that this positive association is partly due to improved housing conditions. Others

have found a differential effect between migrant households compared to non-migrant

households that are due in part to the influx of money to spend on more nutritional food,

5

medical care, and improved housing. For example, infants born in migrant households are

3% less likely to die than in non-migrant households and are approximately 5% less

likely to be born underweight.20 As more households receive remittances, infant mortality

rate declines further.27

Effect of Remittances on Health Spending

Studies have shown a mixed effect of remittances on health care spending at the

household- and government-level. On the one hand, Amuedo-Dorantes and Pozo (2009)

estimated that a 100 Mexican peso increase in remittances in Mexico augments

household health expenditure by 5 or 6 Mexican pesos, though the effect of remittances

will differ depending on the amount of remittances received. Similarly, in Ecuador, an

increase of $10 resulted in a private health spending increase of 5%.22 Cen Camal (2012)

found an additional household level effect. Specifically, Mexican households use

remittances to pay off health related debt, suggesting that remittances can be used at the

household level to prevent catastrophic health payments that can push a household further

into poverty.

In addition to the positive correlation between remittances and private health

spending, the literature indicates differences depending on the level of remittances

received. Amuedo-Dorantes, Sainz and Pozo (2007) found that higher income remittance-

receiving households spend 7% of remittances on health compared to 4% in lower

income remittance-receiving households. Others estimates suggest that households that

do not have access to formal health insurance will spend 11% of remittances on health

compared to 8% for households with formal health insurance.31

6

Effect of Remittances on Public Goods Provision

Despite the positive effects of remittances on household health spending, the

evidence on the effect of remittances at the macro-level is mixed. While there is general

consensus that remittances will change the local political economies in home countries,

including altering the way that tax revenues are allocated, studies have found that

remittances have a mixed effect on corruption and governance, key determinants of the

provision of public goods. Ahmed (2012) noted that a 3 percentage point increase in

remittances increases corruption by 1 point on a corruption index. Abdih et al (2008)

found a similar negative association between remittances and corruption, indicating the

potential for governments to free ride based on the availability of remittances to

substitute their provision of public goods.32 In contrast, Tyburski (2012) found that

remittances have the potential to counter corruption by increasing government

accountability. The relationship between remittances and governance is relevant to health

outcomes given that the positive effect of higher health spending on health outcomes is

dampened in low governance environments.33

These results on overall government indicators suggest that the effect of

remittances on health spending may be mixed. Indeed, while Naanwaab and Yeboah

(2013) found that a 10% increase in remittances is associated with a 0.30% increase in

health spending as percent of GDP, Ebeke (2012) argued that remittances reduce health

spending in countries with poor governance structures. A recent study exploring the

effect of remittances on social spending found that the stabilizing effect of remittances at

the household level lowered the public’s demand on the government to provide social

7

services.25 These findings suggest the potentially downward effect of remittances on

health spending.

Theoretical Considerations and Hypothesis

Remittance-receiving households use remittances for a variety of reasons

spanning immediate consumption to long-term investments for human development, such

as education and health. Often times, migrants cite increasing health care spending as a

primary reason for sending remittances; however, households may use remittances to buy

common household items, such as clothing, food or electronics, or to invest in physical

infrastructure or social development, such as education.8,29,34 The lag in spending on

social development is likely due to effects that materialize in the long-term. In other

words, a remittance-receiving household can receive immediate benefits, or higher utility,

by purchasing durable goods, whereas the impact of a better education or better health

access may occur in the long-term.

Remittances are sent to households through two main mechanisms: formal and

informal. The formal exchange of remittances is through banks, credit unions and the use

of money transfer organizations (MTO), such as Western Union or MoneyGram.

Formally remitting money can be expensive due to high transaction costs and asymmetric

information between the bank and the sender. Other challenges include fear of interacting

with the formal financing system or that the financial system in the home country is

inadequate.35,36

Assuming the migrant household can access a bank to receive the remittances, the

decision on how to use the remittance will be the responsibility of the head of household

in the home country. Often times, the primary reason a migrant cites for remitting may

8

not coincide with the primary use of the remittances. For example, nearly half of Mexican

remitters have cited health care spending as a primary reason for sending money to

families, which aligns with altruistic, insurance and investment theories that explain why

immigrants transfer remittances home.11 However, households are more likely to use

remittances to buy common household items, such as clothing, food or electronics, or

invest in physical infrastructure or social development, such as education.10 Households

will likely spend remittances on immediate basic consumption needs, followed by

investments, which can include home construction or human capital. Therefore, while the

implications on direct health spending are limited, household investments (e.g., improved

housing conditions or social standing) due to the higher budgetary constraint could have a

greater impact on health outcomes.

The health implications of the informal exchange channel depend on whether the

remittances are intended to support the community or the individual household. Migrants

may form hometown associations (HTA) to send money back home to a community.

Money pooled through HTAs could be used to build a health clinic for a local community

with matching funds from the municipal government.37 While the HTA is creating a

public good that can positively impact the population’s health, an individual household

may benefit more if the informal mechanism is at the individual household level. As the

money is directly tied to the migrant’s household, instead of the community, the

household could receive more direct benefits than if the informal channel is community-

based. An additional benefit to the individual household level mechanism is that

knowledge may be transferred more easily, especially if the migrant is travelling back

home and relaying health knowledge that may have been acquired abroad.

9

The determinants for health outcomes include social standing, income, education,

living conditions, and access to health systems.38 Regardless of whether the intended use

of remittances aligns with the actual household expenditure, remittances can increase a

household’s standard of living by increasing their consumption budget line. It is through

this expansion of the budget line that households may be able to invest more money in

factors that affect health. This can include improvements in housing and living

conditions, higher direct out-of-pocket spending on health services, or improved access to

food and nutrition. It is possible that households may seek services through the private

sector as they now have higher purchasing power to spend on health care.

Based on the theory posited in the literature, the main hypotheses of this paper are

that remittances will result in the government lowering public health spending and that

the channel through which remittances is impacting health outcomes is indirect. The

government may lower public spending on health care if they perceive this higher out-of-

pocket spending as a substitute to government spending. Furthermore, as higher

remittance levels implies that the country has a higher migrant stock, there may also be

less public pressure to reform behaviors, such as corruption or lower social spending.15,25

Moreover, as households receive remittances, they will likely increase their household

consumption, which will have a greater impact on health outcomes, such as infant

mortality rate and under-5 mortality rate, that are a function of social determinants of

health.

Chapter 2: Empirical Analysis

The analysis follows a two-step approach. First, the effect of remittances on

health outcomes and health spending are analyzed. Second, an empirical model studying

10

the effects of health spending on actual health outcomes is developed as a complementary

tool. This second stage of analysis allows a more detailed exploration of the two key

questions: whether and through which channels remittances impact selected health

outcomes. The basic multivariate specification is the following:

The central dependent variable in the model, HealthExpi,t, is health spending (all

measures included in Table 1) for a country, i, at a time, t. The main independent

variable, remittances (measures included in Table 1), is lagged, t-1, to minimize the threat

of reverse causality and to capture the lagged adjustment of public health expenditures.

Furthermore, remittances and health spending measures are logged. Controls are denoted

through Xi,t and country and time fixed effects are captured using ut and Θt . All data are

from the World Bank’s World Development Indicators (WDI) dataset, a multisectoral,

multi-country panel dataset that spans over 200 countries over 50 years. To ensure

overlap between the independent variable, remittances, and the dependent variable,

public health expenditure, the time period for this study is 1995-2011. Table 1 describes

the variables, short form and source of the selected variables used in the model. Table 2

describes the number of observations and other summary statistics for the variables

included in the model.

Other controls included in the model were GDP per capita, GDP growth rate,

urban population rate and life expectancy. As the selected model specification was

relatively small, country and time fixed effects (fe) were used to eliminate the potential

for omitted variable bias in a multivariate analysis. To control for the potential of reverse

causation, a dynamic panel approach was used. Other studies have used instrumental

11

variables to achieve this same goal.24 The same approach was used for the analyses using

health outcome data, including infant mortality rate, under-5 mortality rate and maternal

mortality ratio. Sensitivity analyzes were also conducted by geographic region (i.e.,

Africa, Asia, Americas, Europe) and income group (i.e., Low, Middle).

Chapter 3: Results

Remittances and Health Outcomes: In a year and time fixed effect model

including GDP per capita, the percentage of urban population, and GDP growth as

controls, remittances (in USD) have a statistically significant effect on infant mortality

rate and under-5 mortality rate (Table 3). On average, a one percent increase in

remittances is associated with a reduction of 1.015 infant deaths per 1,000 live births.

Similarly, including time-varying and country-varying controls, a one percent increase in

remittances is associated with a 1.699 under-5 deaths per 1,000. In contrast, there is no

statistically significant association between remittances and maternal mortality ratio.

These relationships hold when robustness checks were conducted using a different

measure of remittances (as percent of GDP) (Appendix A7) or regional and economic

variation (Appendix A8). The GMM model shows the same statistical association;

however, the relationship is somewhat smaller. The GMM model eliminates the problems

due to reverse causality (e.g., improved health could create a larger migrant pool, which

could, in turn, increase remittances) and serial correlation between health outcomes and

remittances (e.g., health outcomes may remain relatively constant over time). Overall, the

results indicate that remittances improve health the results indicate that remittances

improve health outcomes. Separate analyses on the relationship between health spending

and health outcomes are used to isolate the channels through which remittances operate.

12

Health Spending and Health Outcomes: In a year and time fixed effect model

including GDP per capita, the percentage of urban population, and GDP growth as

controls, public health expenditure (as % of government expenditure) has a statistically

significant effect on maternal mortality ratio but does not have a statistically significant

effect on IMR and under-5 mortality rate (Table 4). On average, a one-unit increase in the

log of the percent of public health expenditure (% of government expenditure) is

associated with a reduction of 81 maternal deaths per 100,000 live births. The GMM

model shows a different statistical association where only under-5 mortality rate has a

statistically significant effect. These relationships vary when robustness checks were

conducted using different measures of public health expenditure (Appendix A3, A4, A5)

or regional and economic variation (Appendix A9). For example, main findings from

robustness checks using differing measures of health expenditure show the following:

First, on average, a one percent increase in expenditure per capita is associated

with a reduction of 2.335 infant deaths per 1,000 live births. There is no statistical

association with under-5 mortality rate or maternal mortality ratio or in the GMM model

(Appendix A3). Second, on average, a one unit increase in the log of the percent of public

health expenditure (% of GDP) is associated with a reduction of 3.785 under-5 deaths per

1,000 and a reduction of 7.325 maternal deaths per 100,000 live births. There is no

statistical association with infant mortality rate or in the GMM model (Appendix A4).

Third, on average, a one unit increase in the log of the percent of public health

expenditure (% of total health expenditure) is associated with a reduction of 4.628 under-

5 deaths per 1,000 and 122.2 maternal deaths per 100,000 live births. There is no

statistical association with IMR or in the GMM model (Appendix A5).

13

Other robustness checks focused on the effect of household consumption,

government consumption and development assistance show the following (Appendix

A10). First, on average, a one-unit increase in the log of the percent of household

consumption, as percent of GDP, is associated with a reduction of 5.603 maternal deaths

per 100,000 live births and a reduction of 2.906 infant deaths per 1,000 live births. There

is no statistically significant association between household consumption and under-5

mortality rate. Second, on average, a one-unit increase in the log of the percent of

government consumption as percent of GDP is associated with a reduction of 5.425

under-5 deaths per 1,000 and reduction of 3.99 infant deaths per 1,000 live births. There

is no statistically significant association between government consumption and maternal

mortality ratio. Lastly, there is no statistically significant association between

development assistance and the three selected health outcomes.

Remittances and Health Spending: In a year and time fixed effect model including

GDP per capita, the percentage of urban population, and GDP growth as controls,

remittances (in USD) have a statistically significant effect on expenditure per capita

(Table 5). On average, a one percent increase in remittances is associated with a

reduction of $18 in health expenditure per capita. There is no other statistically

significant effect on other health expenditure measures. The GMM model shows a

statistically significant effect on public health expenditure as percent of government

expenditure. On average, a one percent increase in remittances is associated with a 0.2

unit reduction in the log of public health expenditure as percent of government

expenditure. There is no other statistically significant effect on other health expenditure

measures.

14

Chapter 4: Policy Implications

The key findings from this analysis suggest that remittances are not significantly

associated with a reduction in government health spending, but are positively associated

with certain health outcomes, such as infant mortality rate and under-5 mortality rate.

Instead of inducing moral hazard, as the literature suggests, it appears that the

government does not change their spending patterns based on remittance levels. While

the results on remittances and health outcomes are consistent with the literature (e.g.,

remittances have an effect on health outcomes), remittances do not appear to have a

significant association with health spending measures, including out-of-pocket payments

or expenditure per capita. This indicates that the channel through which remittances

impact health outcomes is not likely through direct health spending.

Robustness checks analyzing household and government consumption strengthen

the case that remittances primarily impact health outcomes through more stable and

enhanced household consumption. Remittances increase the amount of disposable income

at the household level, which may be invested in improving housing conditions or

increase availability of food. These channels appear to have a stronger impact than direct

health spending.

Unlike infant mortality rate and under-5 mortality rate, which are associated with

many social determinants of health, such as housing, food access, nutrition and family

security, maternal mortality reflects direct access to health services. The results for

maternal mortality support the hypothesis that maternal mortality ratio will not be driven

by remittances, and instead, depend on the health system overall.

15

Based on the results from this study, governments should consider the following

interrelated policy solutions, which weigh the positive effects of remittances against the

potentially adverse macroeconomic effects:

First, the data on health spending and health outcomes suggest that total

health spending should increase. If migrants are spending more money on non-health

services and durable goods, such as food or improvements to living conditions, then

policy makers should respond by investing in public health expenditure to increase total

health spending. This policy recommendation is also aligned with the World Health

Organization’s (WHO) efforts to increase universal coverage for health and reduce

reliance on out-of-pocket spending, or the money that people spend on health care

services directly. The data show that out-of-pocket payments do not have a statistically

significant effect on health outcomes, which indicates that they should not be promoted

as a measure to improve health outcomes.

Second, governments should implement policy reforms to make it easier for

migrants to send remittances back home. Remittances appear to have a sustained and

consistent relationship on key health outcomes, such as infant mortality rate and under-5

mortality. This positive effect suggests that governments should open the channels

through which remittances flow to increase the disposable income available to

households, especially those who heavily rely on remittances as part of their household

income. To account for potential negative effects, or the flow of illicit money without

oversight, the international community should increase efforts toward improving

government and regulatory frameworks. While making it easier for migrants to send

money home can help at the household level, remittances are comprised of many sources

16

of funding, suggesting that more comprehensive financial channels should be in place to

maximize the benefits of remittances and reduce the potentially negative consequences.

Third, although governments should promote remittances for household

consumption, national governments should consider alternative routes to increase

household consumption. For example, governments can create or continue to invest in

social protection programs that increase the availability of cash to program eligible

households. In doing so, these types of programs can increase household consumption,

which appears to be a driving force behind the reductions in mortality rates. This policy

measure could be implemented in conjunction with the first recommendation regarding

increasing total health spending.

Chapter 5: Conclusions and Limitations

As governments consider the policy recommendations described above, policy

makers should consider the inherent trade-off regarding remittances. While increasing

remittances and maintaining a stable flow of household consumption can increase health

outcomes, remittances can also produce negative macroeconomic consequences, such as

inflation or higher exchange rates. Facilitating the flow of remittances to benefit

households could also inadvertently lead to the higher flow of illicit funds. Furthermore,

the effect of remittances on chronic diseases, such as diabetes, remains unknown. A

future study on the effect of remittances on chronic diseases, such as diabetes, which tend

increase over time with lifestyle changes, would likely result in another negative outcome

associated with remittances.

In light of this policy trade-off, policy makers should reform remittance policy

within a more comprehensive framework to mitigate the concerns. More work should be

17

directed toward improving financial regulation and governance to facilitate the growth of

remittances in low- and middle-income countries, but maximizing the beneficial effects.

Furthermore, governments should increase health spending to complement the higher

household consumption to increase health outcomes, such as infant mortality rate and

under-5 mortality rate, and improve health outcomes, such as maternal mortality ratio,

that primarily depend on the existing health system instead of social determinants of

health.

The main limitations of this study were the following. First, the time period used

was determined based on the availability of health spending data, which only began to be

collected on an international level in 1995. Therefore, the effect of remittances and health

outcomes used in this study was restricted to a 20-year time period. Second, remittances

are underreported given that these data only capture formally recorded remittances.

Others have also noted inconsistency in data reporting across countries.21 Third, there is

missing data across the three areas of interest: remittances, health outcomes and health

spending. Therefore, it is possible that the results may change over time or when a more

complete dataset is available.

The international community and many national governments have been using

remittances as a tool for development for some time. While this study supports that

remittances should continue to be used to increase household consumption, it is important

that governments do not rely on remittances as the sole mechanism for health

improvements. It is evident that remittances can be a driving force to improve health

outcomes, especially those that rely on social determinant of health, but remittances fall

short of being a panacea for all health problems. Long-standing health issues such as

18

maternal mortality ratio and the growing burden of chronic diseases will require other

solutions that go beyond increasing household consumption. Therefore, governments in

developing countries, along with partners in international health funding institutions,

should continue to identify innovative ways to use remittances and other funding sources

more effectively.

19

Table 1: Description of World Development Indicators

Variable Short form Type Source (as described in WDI)

Personal remittances, received (current

US$)

Remitusd Independent

World Bank estimates based on IMF balance of payments data,

and World Bank and OECD GDP estimates

Personal remittances, received (% of GDP) Remitgdp Independent World Bank estimates based on IMF balance of payments data,

and World Bank and OECD GDP estimates

Health expenditure, public (% of GDP) exppubGDP Dependent

WHO Global Health Expenditure database

Health expenditure, public (% of

government expenditure)

exppubGOVEXP Dependent WHO Global Health Expenditure database

Health expenditure, public (% of total

health expenditure)

expPUBTHE Dependent WHO Global Health Expenditure database

Health expenditure, total (% of GDP) expGDP Dependent WHO Global Health Expenditure database

Health expenditure per capital (current $) expCAP Dependent WHO Global Health Expenditure database

GDP per capita (current US$) gdpCAP Control

World Bank, International Comparison Program database

Urban population (% of total) urbanPOP Control

World Bank

GDP growth (% annual) gdpgro Control

World Bank

Life expectancy at birth, total (years) Lifexpect Control/Dependent

UNPD and others

Mortality rate, under-5 (per 1,000) mortund5 Dependent UN Inter-agency for Child Mortality Estimation

Maternal mortality ratio (modeled

estimate, per 100,000 live births)

Maternmort Dependent UN Inter-agency

Mortality rate, infant (per 1,000 live births) Imr Dependent

UN Inter-agency for Child Mortality Estimation

20

Table 2: Descriptive Statistics (1995-2011)

Variable N Mean SD Min Max

Remitusd 2786 1.66 e+09 4.17e +09 0.00 6.88e+10

Remitgdp 2725 4.06 6.85 0.00 61.99

exppubGDP 3184 3.70 2.35 0.00 21.11

exppubGOVEXP 3180 11.09 4.63 0.00 42.38

expPUBTHE 3181 57.22 20.34 0.39 99.98

expGDP 3184 6.28 2.69 0.00 22.19

expCAP 3182 674.344 1276.119 0 9120.81

gdpCAP 3479 10727.47 18016.55 64.81 1.94e+05

urbanPOP 3726 55.32 24.47 7.21 100.00

gdpgro 3434 4.076798 5.748358 -47.553 106.2798

Lifexpect 3318 67.83558 10.10695 31.239 85.16341

Maternmort 517 163.9222 275.7378 0 2100

mortund5 3438 50.78365 53.0938 2.2 278.9

imr 3438 35.42693 32.18131 1.7 153.1

21

Table 3: Effects of Remittances (USD) on Health Outcomes

Infant Mortality Rate Under-5 Mortality Rate Maternal Mortality

(1) (3) (4) (5) (1) (3) (4) (5) (1) (3) (4) (5)

ln_remitusd -3.960*** -1.435*** -1.052*** -0.143** -6.407*** -2.441*** -1.699*** -0.289** -16.33*** -3.191 -0.268 -0.847

(-0.561) (-0.41) (-0.293) (-0.0569) (-1.013) (-0.749) (-0.517) (-0.121) (-5.863) (-5.549) (-5.072) (-1.528)

gdpCAP

0.000400*** 8.02e-06**

0.000697*** 2.93E-05

0.00229 -0.000243

(-0.0000831) (-0.00000367)

(-0.000151) (-0.0000208)

(-0.00276) (-0.000315)

urbanPOP

-0.462*** 0.00623*

-0.789** 0.00915

4.469 -0.0171

(-0.171) (-0.00332)

(-0.357) (-0.00655)

(-2.954) (-0.109)

gdpgro

-0.0369 -0.00979

-0.0176 0.00741

-1.504 -0.104

(-0.0338) (-0.0102)

(-0.0638) (-0.0718)

(-1.055) (-0.392)

lifexpect

-2.113*** -0.0166

-4.237*** -0.236

-29.78*** -0.676

(-0.287) (-0.0213)

(-0.621) (-0.183)

(-5.771) (-0.505)

imr/mortund5/maternmort

0.970***

0.921***

0.904***

(-0.00599)

-0.0366

(-0.0505)

Year

X X

x X

x x

Country

X X

x X

x x

Constant 109.6*** 67.55*** 221.8*** 3.662** 170.6*** 104.6*** 408.0*** 23.27 531.9*** 200.3 1,890*** 0

(-11.74) (-7.826) (-21.29) (-1.78) (-21.22) (-14.45) (-44.34) (-15.06) -122.7 -126.9 -329.1 0

Obs 2,556 2,556 2,460 2,460 2,556 2,556 2,460 2,460 432 432 420 145

# countries 171 171 170 170 171 171 170 170 131 131 127 49

chi2 49.79

258234 40.03

129318 7.753

225657

hansenp

0.795

0.463

0.697

sarganp

0.468

1

0.714

R-squared 0.501 0.715 0.398 0.64 0.16 0.349

Notes: Robust standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; Models (1): Simple OLS; (2): OLS + year fixed effect; (3): OLS + year and country fixed effect; (4): Fixed effect; (5): GMM

22

Table 4: Effect of Public Health Spending (% of Government Expenditure) on Health Outcomes

Infant Mortality Rate Under-5 Mortality Rate Maternal Mortality

(1) (3) (4) (5) (1) (3) (4) (5) (1) (3) (4) (5)

ln_exppubGOVEXP -4.164** 0.289 -0.364 -0.147 -8.116** -1.051 -2.516 -0.692* -83.54*** -80.14** -81.88** 5.591

(-1.932) (-1.298) (-1.132) (-0.174) (-3.602) (-2.503) (-1.962) (-0.418) (-29.63) (-35.11) (-35.67) (-5.875)

gdpCAP

0.000395*** 1.05e-05***

0.000693*** 3.24e-05**

0.00483* -0.000315

(-0.0000683) (-0.00000308)

(-0.000125)

(-0.0000159)

(-0.00261)

(-0.000325)

urbanPOP

-0.332** 0.00443

-0.620* 0.00601

4.442 0.0503

(-0.158) (-0.00307)

(-0.326) (-0.00592)

(-2.909) (-0.0809)

Gdpgro

-0.02 -0.0106*

-0.0144 -0.00616

-1.127 0.0845

(-0.0483) (-0.00594)

(-0.0825) (-0.0375)

(-1.16) (-0.339)

Lifexpect

-2.189*** -0.0370**

-4.343*** -0.24

-27.00*** -0.615

(-0.269) (-0.0171)

(-0.558) (-0.164)

(-5.539) (-0.544)

imr/mortund5/maternmort

0.969***

0.927***

0.913***

(-0.00566)

(-0.0324)

(-0.0473)

Constant 44.13*** 41.89*** 202.2*** 2.843** 68.01*** 64.16*** 380.9*** 19.66 412.3*** 315.7*** 1,871*** 0

(-5.078) (-3.046) (-18.24) (-1.377) (-9.463) (-5.944) (-36.66) (-12.75) (-73.93) (-102.2) (-332.3) 0

Obs 3,178 3,178 2,961 2,961 3,178 3,178 2,961 2,961 488 488 471 155

# countries 190 190 185 185 190 190 185 185 150 150 142 51

chi2 4.644

435108 5.078

186883 7.95

163396

Hansenp

0.0683

0.275

0.619

Sarganp

0

0.974

0.145

R-squared 0.486 0.699 0.395 0.642 0.182 0.337

Notes: Robust standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; Model 1: Simple OLS; Model 2: OLS + year fixed effect; Model 3: OLS + year and country fixed effect; Model 4: Fixed effect; Model 5: GMM

23

Table 5: Effect of Remittances on Health Spending Measures

exppubGOVEXP expcap exppubGDP expOOPthe

Model 4 Model 5 Model 4 Model 5 Model 4 Model 5 Model 4 Model 5

ln_remitusd 0.0543 0.260* ln_remitusd -18.87** 1.96 ln_remitusd -0.0166 0.0515 ln_remitusd -0.0666 0.064

(-0.115) (-0.139) (-8.798) (-5.555) (-0.0339) (-0.0324) (-0.456) (-0.313)

gdpCAP 2.36E-05 2.24e-05*** gdpCAP 0.101*** 0.00223 gdpCAP 1.50E-05 1.06e-05*** gdpCAP 6.65E-05 -3.04e-05***

(-0.0000211)

(-0.00000635)

(-0.00577)

(-0.00181)

(-0.00001)

(-0.00000232)

(-0.0000453)

(-0.00000924)

urbanPOP -0.0558 -0.00496 urbanPOP 1.155 0.260** urbanPOP 0.00934 9.79E-05 urbanPOP -0.284 -0.00225

(-0.0646) (-0.00604) (-6.521) (-0.104) (-0.0201) (-0.0012) (-0.207) (-0.00685)

Gdpgro -0.0411** -0.0115 gdpgro -1.061 1.220** gdpgro -0.0121** 0.00207 gdpgro 0.0341 -0.0202

(-0.0184) (-0.0152) (-1.03) (-0.48) (-0.00486) (-0.00281) (-0.0399) (-0.0282)

Lifexpect 0.058 -0.00637 lifexpect -1.633 0.348 lifexpect 0.0122 -0.00213 lifexpect -0.0706 -0.0038

(-0.153) (-0.0152) (-2.992) (-0.396) (-0.0388) (-0.00358) (-0.176) (-0.0338)

exppubGOVEXP

0.779*** expCAP

1.022*** exppubGDP

0.890*** expOOPTHE

0.940***

(-0.0274)

(-0.0196)

(-0.0159)

(-0.0133)

Year X Year X Year x

Country X Country X Country x

Constant 8.433 -1.681 Constant 237.3 -89.38 Constant 2.245 -0.503 Constant 55.85*** 1.827

(-11.34) (-1.821) (-411.5) (-79.66) (-2.961) (-0.43) (-19.12) (-3.32)

Obs 2,303 2,303 Obs 2,303 2,303 Obs 2,305 2,305 Obs 2,305 2,305

# countries 168 168 # countries 168 168 # countries 168 168 # countries 168 168

chi2

2295 chi2

259681 chi2

13380 chi2

50334

Hansenp

0.495 hansenp

0.442 hansenp

0.0872 hansenp

0.227 Sarganp

1.97E-05 sarganp

0.18 sarganp

5.57E-06 sarganp

0.0122

R-squared 0.091 R-squared 0.844 R-squared 0.212 R-squared 0.059

Notes: Robust standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; Model 1: Simple OLS; Model 2: OLS + year fixed effect; Model 3: OLS + year and country fixed effect; Model 4: Fixed effect; Model 5: GMM

24

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