The Impacts of Remittances on Human Capital and Labor Supply in Developing Countries

The Impacts of Remittances on Human Capital and Labor Supply in Developing Countries SeyedSoroosh Azizi Department of Economics, Northern Illinois University (NIU) October 25, 2017 Abstract This study investigates the impacts of workers remittances on human capital and labor supply by using data for 125 developing countries from 1990 to 2015. This topic is almost unexplored at the aggregate level, mainly due to endogeneity of remittances and the difficulty in finding instruments to resolve this issue. To address the endogeneity of remittances, I estimate bilateral remittances and use them to create weighted average remittance-sending countries indicators. These weighted indicators are used as instruments for remittances. Results obtained in this study indicate that remittances raise per capita out-of-pocket health expenditures and reduce undernourishment prevalence, depth of food deficit, and child mortality rate. Remittances also raise school enrollment, school completion rate, and private school enrollment. Although there is no difference on the impact of remittances on the health outcome of boys and girls, remittances raise the educational investment in girls more than in boys. Further, remittances decrease the female labor force participation rate but do not affect male labor force participation rate. Keywords: Migration; Remittances; Health; Education; Human capital; labor supply, Developing countries. JEL Classification Numbers: D64, F22, F24, O15. E-mail address: sazizi1@niu.edu. 1

1 Introduction In the past few years, many researchers have examined the impact of remittances on human capital or labor supply in a specific country or region. The primary barrier in evaluating the impact of remittances on human capital for all developing country is endogeneity of remittances. Remittances are endogenous to the education, health outcome, and labor supply of those left behind. Reverse causality, common factors affecting both remittances and human capital, and measurement error are among the sources of endogeneity. Finding instruments to overcome endogeneity of remittances in one country is easier than finding valid and strong instruments for remittances in all developing countries. To address the endogeneity of remittances, this research uses a novel instrumental variable (IV) approach by incorporating five economic indicators of the remittance-sending countries as instruments: per capita Gross National Income (GNI), unemployment rate, real interest rate, real exchange rate, and labor force participation rate. Since each remittance-receiving country has many different countries as the sources of remittances, building the instruments requires knowing the bilateral remittances to calculate the weighted average indicators of the host countries. Because bilateral remittances are not generally available, I estimate them and use them as weights to build the instruments. This estimation strategy allows me to utilize 5 valid and strong instruments, which are related to remittance-sending countries, to investigate the impacts of workers remittances on human capital and labor supply in remittance-receiving countries. I also use this IV approach to study gender-specific impacts of remittances on health, education, and labor supply in developing countries. The results obtained in this paper show that remittances contribute to more out-of-pocket health expenditure, less undernourishment prevalence, less depth of food deficit, and less child mortality rate. They also raise the school enrollment, school completion rates, and private school enrollment. As a robustness check, this paper investigates the overall impact of remittances on Human Development Index (HDI) and shows that remittances increase HDI. Another contribution of this paper is showing the gender-specific effect of remittances. Remittances increase gender parity index. Although there is no difference on the impact of remittances on the health outcome of boys and girls, remittances raise education investment on girls slightly more than on boys. Also, remittances do not affect male labor force participation in the developing remittance-receiving countries, but they decrease female labor force participation. Between 1990 and 2015, the number of individuals living outside their countries of birth grew from 153 million people to 244 million people, which corresponds to 2.87% of the world population in the year 1990 and 3.32% of the world population in the year 2015 (United Nations). The total amount of remittances received has risen from $68 billion in 1990 to $553 billion in 2

2015. The average amount of money each migrant remitted in 2011 constant dollars has risen from $688 in 1990 to $2,128 in 2015. These amounts include only remittances that have been sent through official channels (the World Bank, United Nations, author s calculations). This surge in the value of remittances has attracted the attention of many researchers. Many topics and questions related to remittances interest economists. Some of these questions are as followings: how do remittances affect recipient households and countries? Do they increase investment, either human capital or physical capital investment, or do they primarily fund higher consumption? What are the impacts of remittances on human capital, especially on education and health, in developing countries? What are the impacts of remittances on children left behind? If the remittances improve human capital in developing countries is there a difference between their effect on the sexes? Remittances can lift budget constraints and help children in remittance-receiving households to go to school or have a better health outcome. While remittances can benefit households by lifting liquidity constraints, migration of a family member can have a negative impact on the household s well-being. Migration of a productive family member may have disruptive effects on the life of the household. These observations lead to a fundamental development question: do remittances to developing countries contribute to higher investment in human capital? This research examines this question by exploring the major factors influencing education and health outcomes in developing countries. This paper addresses three main questions: To what extent can the remittances to developing countries improve health and education outcome in terms of nutrition adequacy, mortality rates, school attendance, and educational attainment? If remittances improve human capital in developing countries, is there any difference between their effect on two genders? What is the impact of remittances on labor force participation for men and women? Answering these questions is crucial to evaluate the overall effect of workers remittances on developing countries because as major components of human capital, health and education impact the long-run economic growth. The rest of the paper is arranged as follows. Background and literature review is provided in section 2. Section 3 discusses the data used in this paper. Section 4 is devoted to the econometric model. Section 5 presents empirical results, and Section 6 some conclusions. 2 Background Early studies on impacts of remittances on human capital (both health and education), financial development, poverty and inequality, and exchange rates did not consider the endogeneity of remittances. However, most of the recent studies about the impact of remittances 3

on different aspects of remittance-receiving households and countries recognize the endogeneity of remittances and include different methodologies to resolve the problem of endogeneity of remittances. The traditional and most popular method to address the endogeneity of remittances is to use instrumental variables. While the instruments must be strong, the bigger challenge to the researchers is to find valid (i.e. not correlated with the error term) instruments. Generally, three categories of instruments are used by different authors: instruments related to remittancereceiving countries, instruments related to remittance-sending countries, and instruments related to cost of remittances. Not many papers have addressed the endogeneity of remittances in the aggregate level. Adams and Page (2005) is one of the first studies which addresses endogeneity of remittances in the country-level. They use three instrumental variables to account for endogeneity of the impact of remittances on poverty. The first instrument is the distance (miles) between the four major remittance-sending areas and remittance-receiving countries. The second instrument used by them is education, specifically the percentage of the population over age 25 that has completed secondary education. This variable is correlated with education, and it is not a valid instrument in this research. The third variable used by them is government stability. The effect of government stability on remittances can be positive (if migrants have investment incentive, they remit more if their home countries are more stable) or negative (if migrants have altruistic purposes, they remit more if their home countries are less stable). Government stability also can be correlated with educational attainment or health outcome. This section is divided into three parts. First, I provide a summary of papers which study the effects of remittances oh health. Then, papers which investigate the impacts of remittances on education are reviewed. Lastly, papers which examine the impacts of remittances on labor supply are summarized. Due to the importance of endogeneity issue, I pay special attention to the instruments used by different authors. 2.1 Remittances and Health Researchers who studied the impact of remittances on health outcome mainly focused on three health measurements: health expenditures, nutrition status, and child mortality rates. In the following, I briefly discuss papers who consider the impacts of remittances on these three aspects of health outcome. Note that health expenditure is not an aspect of health outcome perse, but it has a strong impact on health outcome. Ambrosius and Cuecuecha (2013) test the assumption that remittances are a substitute for credit by comparing the response to health-related shocks using Mexican household panel data. They find that while the occurrence of serious health shocks that required hospital treatment 4

doubled the average debt burden of exposed households compared to the control group, households with a parent, child, or spouse in the US did not increase their debts due to health shocks. They use weighted linear regression to address the endogeneity problem. Valero-Gil (2008) find a statistically significant effect of remittances on the household health expenditure shares. The author uses the percentage of return migration between 1995-2000 at the municipal level as an instrument for remittance. Amuedo-Dorantes and Pozo (2009) find that international remittances raise health care expenditures among remittance-receiving households in Mexico. They select two variables to be included as instruments: the road distance to the US border (from the capital of the Mexican state in which the household resides) and US wages in Mexican emigrant destination states. Their results suggest that 6 Pesos of every 100 Peso increment in remittance income are spent on health. Ponce, Olivie, and Onofa (2011) study the impact of remittances on health outcomes in Ecuador, and they do not find significant impacts on long-term child health variables. However, they find that remittances have an impact on health expenditures. They use historic state-level migration rates as an instrument for current migration shocks. Some researchers have used different measurements of nutrition status as the factor representing health outcome. Food security level, household food consumption, child nutritional status, and low birth weight are some of the measurements of nutrition status. In the following, I introduce four of these papers. Generoso (2015) shows that the diversification of income sources, through the reception of remittances, constitutes one of the main ways of coping with the negative impact of climate hazards on the food security level of rural households situated in this region. Combes et al. (2013) explore the role of remittances and foreign aid inflows during food price shocks. They conclude remittance and aid inflows dampen the effect of the positive food price shock and food price instability on household consumption in vulnerable countries. Anton (2010) analyzes the impact of remittances on the nutritional status of children under 5 years old in Ecuador in 2006. Using an instrumental variables strategy, the study finds a positive and significant effect of remittance income on short-term and middle-term child nutritional status. The study uses the number of Western Union offices per 100,000 people at province level as the instrument. Frank and Hummer (2002) find that membership in a migrant household provides protection from the risk of low birth weight among Mexican-born infants largely through the receipt of remittances. They did not account for endogeneity in remittances. Many researchers have used child and infant mortality rates as the factor representing health outcome. Reducing child mortality rate is one of the United Nations Sustainable Development Goals (SDG). The goal is by 2030 end preventable deaths of newborns and children under 5 years of age, with all countries aiming to reduce neonatal mortality to at least as low as 12 per 1,000 live births and under-5 mortality to at least as low as 25 per 1,000 live births. In the 5

following, some of these studies are discussed. Terrelonge (2014) examines how remittances and government health spending improve child mortality in developing countries and concludes remittances reduce mortality through improved living standards from the relaxation of households budget constraints. Chauvet et al. (2012) consider the respective impact of aid, remittances and medical brain drain on child mortality rate. Their results show that remittances reduce child mortality while medical brain drain increases it. Health aid also significantly reduces child mortality but its impact is less robust than the impact of remittances. Kanaiaupuni and Donato (1999) consider the effects of village migration and remittances on health outcomes in Mexico and conclude higher rates of infant mortality in communities experiencing intense U.S. migration. On the other hand, mortality risks are low when remittances are high. Zhunio, Vishwasrao and Chiang (2012) study the effect of international remittances on aggregate educational and health outcomes using a sample of 69 low- and middle-income countries. They find that remittances play an important role in improving primary and secondary school attainment, increasing life expectancy and reducing infant mortality. 2.2 Remittances and Education To investigate the impact of remittances on the education of those left behind, most of the researchers rely on school attendance as the main indicator of education. Many authors also examined the impact of remittances on child labor. The common belief is that if remittances decrease child labor, then they increase children s education. While school attendance frequently used to measure investment on education, it represents the quantity of education and fails to capture the quality of education. Some researchers have used private school enrollment to demonstrate the quality of education. As Bouoiyour et al. (2016) state, parents invest in the education of their children if they believe such investment generates a higher rate of return than the return on savings. Some parents in low-income households invest too little in the education of their children because they cannot afford to finance educational investments regardless of such returns. Therefore, it is expected that the reduction of these liquidity constraints will make education more accessible to children of poor families. Therefore, financial transfers from family members can lift the budget constraints and allow parents to invest in the education of their children to the extent that is optimal for them. On the other hand, as Amuedo-Dorantes and Pozo (2010) state, the presence of family members abroad may induce changes in school attendance of children in migrants households for a variety of reasons. Children may have less time to devote to schooling because they engage in market activities to earn income to defray migration-related expenses of households. 6

Alternatively, children may leave school to implement necessary household chores that the absent migrant no longer attends to. Finally, if children get encouraged to migrate in the future, they may drop out of school if the origin country s education is not generally well-recognized in the destination. Among researchers who consider the impact of remittances on education and addressed the issue of endogeneity of remittances, two instruments are used frequently. Some studies who recognize the endogeneity of migration and remittances, use migration networks as the instrument for them. Many studies have used economic indicators of remittance-sender countries as instruments for remittances. Following papers have used migration networks as the instrument for remittances. Bouoiyour et al. (2016) use the history of migration networks and remittances costs as instruments to address the endogeneity of remittances. They find that the receipt of remittances in rural areas of southern Morocco has a significant positive effect on school attendance, especially for boys. Acharya and Leon-Gonzalez (2014) explore the effects of the migration and remittance on the educational attainment of Nepalese children. Their results indicate that remittances help severely credit-constrained households enroll their children in school and prevent dropouts. Also, remittances help households that face less severe liquidity constraints increase their investment in the quality of education. By using migration networks as instruments, they gain the similar results. Acosta (2011) studies the effects of remittance receipt on child school attendance and labor in El Salvador. The paper uses El Salvadorian municipal-level migrant networks and the number of international migrants who returned two or more years ago as instruments to address the endogeneity of remittances. The author concludes insignificant overall impact of remittances on schooling; a strong reduction of child wage labor in remittance-recipient households; and an increase in unpaid family work activities for children in those households. Moreover, while girls seem to increase school attendance after remittance receipts by reducing labor activities, boys, on average, do not benefit from higher education. Alcaraz et al. (2012) study the effects of remittances from the U.S. on child labor and school attendance in recipient Mexican households. They use distance to the U.S. border along the 1920 rail network as an instrument for the membership in the remittancerecipient group. By using the differences-in-differences method, they find that the negative shock on remittance receipts in 2008-2009 caused a significant increase in child labor and a significant reduction of school attendance. Salas (2014) investigates the effect of international migration on children left behind in Peru. Historical department-level migration rate is used as an instrument for remittances shocks. The model analyzes the role of international remittances on the investment decision between sending children to a public school or to a private school and finds that international remittances have a positive effect on the likelihood to send children to private schools. 7

As stated by Salas (2014) the common belief is that private schools provide better education compared to that provided by public schools. Besides increasing school enrollment, remittances can affect the choice of school type. The main limitation to access private education in developing countries is its cost. Remittances can lift the budget constraints and allow parents to invest in the quality of education of their children, as well as its quantity. While using migration networks to address the endogeneity of migration allows us to assess the impact of migration on educational attainment, it is not the best possible instrument if we are interested in impacts of remittances on educational attainment. Using economic indicators of remittance-sending countries is more useful if we want to evaluate the impacts of remittances on investment in education. Following studies use economic indicators of remittance-sending countries to address the endogeneity of remittances. Calero and Sparrow (2009) investigate how remittances affect human capital investments through relaxing resource constraints. They use information on source countries of remittances and regional variation in the availability of bank offices that function as formal channels for receiving remittances. They show that remittances increase school enrollment and decrease the incidence of child work, especially for girls and in rural areas. Besides increasing school enrollment, remittances affect the choice of school type. Remittances lead to a net substitution from the public to private schooling, hence increasing the quality of human capital investments in children. Bargain and Boutin (2015) explore the effects of remittance receipt on child labor in Burkina Faso. They instrument remittances using economic conditions in remittance-sending countries. They conclude while remittances have no significant effect on child labor on average, they reduce child labor in long-term migrant households, for whom the disruptive effect of migration is no longer felt. Fajnzylber and Lopez (2007) argue in 11 Latin American countries with the exception of Mexico, children of remittances-receiving families are more likely to remain in school. The positive effect of remittances on education tends to be larger when parents are less educated. They use two external instruments based on the real output per capita of the countries where remittances originate. Amuedo-Dorantes et al. (2010) address the endogeneity of remittance receipt and find that the receipt of remittances by the households in Haiti lifts budget constraints and raises the children s likelihood of being schooled, and the disruptive effect of household out-migration imposes an economic burden on the remaining household members and reduces children s school attendance. They use two variables as instruments: weekly earnings of workers in the United States who are similar to potential Haitian remitters, and unemployment in those geographic areas in which the household is likely to have migrant networks. Some other papers use other instrumental variables or do not address the endogeneity of remittance. Bansak and Chezum (2009) examine the impact of remittances on educational at- 8

tainment of school-age children in Nepal, focusing on differences between girls and boys. They use past literacy rates and political unrest by the district as instrumental variables to address the endogeneity. Their results indicate that positive net remittances increase the probability of young children attending schools. Yang (2008) concludes that favorable shocks in the migrants exchange rates (appreciation of the host county s currency versus Philippine peso) lead to enhanced human capital accumulation in origin households. Child schooling and educational expenditure rise, while child labor falls. Edwards and Ureta (2003) examine the effect of remittances from abroad on households schooling decisions using data for El Salvador. They examine the determinants of school attendance and find that remittances have a large and significant effect on school retention. The main issue with their paper is that they did not recognize the problem of endogeneity. Acosta and Lopez (2007) explore the impact of remittances on poverty, education, and health in eleven Latin American countries. While remittances tend to have positive effects on education for all Latin American Countries with the exception of Jamaica and the Dominican Republic, the impact is often restricted to specific groups of the population (e.g. the positive effect of remittances on education tends to be larger when parents are less educated). 2.3 Remittances and Labor Supply Researchers who study the impact of remittances on labor supply in remittance-receiving countries mainly focus on two aspects of labor supply: labor force participation rate and hours worked per week. As argued by Cox-Edwards and Rodriguez-Oreggia (2009), an important concept underlying the labor force participation decision is the notion of the reservation wage. The reservation wage is the lowest wage rate at which a worker would be willing to accept a particular type of job. A job offer involving the same type of work and the same working conditions, but at a lower wage rate, would be rejected by the worker. An increase in the reservation wage would reduce the probability that an individual participates in the labor force. One of the determinants of the reservation wage is non-labor income, which for an individual is a function of her own assets and the amount of income of other household members. The higher the level of income of the rest of the household (e.g. remittances), the higher the reservation wage of the individual, and the lower the probability that he or she participates in the labor force. Many researchers have looked at remittances as an additional non-labor income for recipient households and hypothesized that the presence of remittances would lead to a reduction in labor force participation among recipient household members. In studying the impact of migration and remittances on labor supply in recipient-households and receiving-countries, migration and remittances might be endogenous. Migration and remittances might be correlated with the error term due to different factors. Reverse causality, 9

omitted variable bias (uncontrolled common factors affecting both migration and remittances and labor supply) and measurement errors are among the potential sources of endogeneity. Many researchers use instrumental variables to address the endogeneity of migration and remittances. Particularly migration network is used frequently to address the endogeneity of migration and remittances. In the following, I review some papers which used this approach. Nguyen and Purnamasari (2011) apply an instrumental variable estimation method, using historical migration networks as instruments for migration and remittance receipts and find that, in Indonesia, migration reduces the working hours of remaining household members. Hanson (2007), based on rural households in Mexico in 2000, concludes individuals are less likely to participate in the labor force if their household either has sent migrants abroad or received remittances from abroad. The author also finds that women from high-migration states become less likely to work relative to women from low-migration states. The author argues that the unobserved characteristics of households that affect labor supply are also likely to affect whether households choose to send migrants abroad, and uses historical states emigration rates as one of the approaches to address endogeneity issue. Acosta (2006) controls for household wealth and uses selection correction techniques and concludes that, in El Salvador, remittances are negatively related to adult female labor supply. However, on average adult male labor force participation remains unaffected. The author recognizes the endogeneity issue and uses the village migrant networks and the number of international migrants who returned two or more years ago as instruments for remittance receipts. Many authors use other instruments to address the endogeneity of remittances. For example, Amuedo-Dorantes and Pozo (2006) assess the impact of remittances on Mexicans labor supply. They instrument remittances with information on the per capita count of Western Union offices in the state. They conclude while overall male labor supply does not vary because of changes in remittance income, its composition by type of employment does. Unlike men, the overall female labor supply appears to decrease due to changes in remittance income, although only in rural areas. Acosta et al. (2008) conclude in all 10 Latin American and Caribbean countries, remittances have a reducing effect on the number of hours worked per week. This negative effect is present both in urban and rural areas. Afterward, remittances are instrumented with the share of remittance-receiving households in the country interacted with household characteristics that affect their likelihood to migrate. After instrumenting for endogeneity, their negative impact on labor force participation ceases to be significant in a number of cases. They also find that the reductions in labor supply caused by remittances tend to be much smaller among individuals with higher levels of schooling. Some researchers use other methods to address the endogeneity of remittances or they do not address this problem at all. Cox-Edwards and Rodriguez-Oreggia (2009) use propensity 10

score matching to separate persistent from sporadic remittances. They find limited evidence of labor force participation effects of persistent remittances. This implies that remittances are an integral part of household s income generation strategy. Acosta, Lartey, and Mandelman (2009) find that in El Salvador an increase in remittance flows leads to a decline in labor supply. Kim (2007)studies the reasons of coexistence of high unemployment rates with increasing real wages in Jamaica. The author concludes that households with remittance income have higher reservation wages and reduce labor supply by moving out of the labor force. Funkhouser (2006) uses longitudinal data from the 1998 and 2001 in Nicaragua to examine the impact of the emigration of household members on the household labor market integration and poverty. The author concludes that households with emigrant had a reduction in labor income than otherwise similar households. 3 Data This study examines 125 developing (poor and middle-income) countries from the six major developing world regions: Latin America and the Caribbean, sub-saharan Africa, the Middle East and North Africa, East Asia and the Pacific, South Asia, and Europe and Central Asia. The income and regional classification in this paper follow the convention of the World Bank. This panel of countries is sufficiently diverse, which means that these results are internationally applicable. The annual data has a time span of 1990 to 2015. All dollar values in this paper are constant 2011 US dollars. Data on remittances come from the International Monetary Fund (IMF), which has defined remittances as the sum of two components: personal transfers (workers remittances) and compensation of employees. The World Bank has adopted the same definition. Compensation of employees refers to the income of border, seasonal, and other short-term workers who are employed in an economy where they are not resident and of residents employed by nonresident entities. Being present for one year or more in a territory or intending to do so is sufficient to qualify as being a resident of that economy (IMF, 2009). Between 1990 and 2015, personal transfers constituted 66% of remittances, and compensation of employees constituted 34% of remittances. In the year 2015, these ratios were 65% and 35% respectively. As Chami, Hakura, et al. (2009) and Chami, Fullenkamp, et al. (2009) show, this aggregation is not appropriate since two different types of transfers have different properties and respond differently to economic shocks. Thus, I follow Combes et al. (2013) in using only workers remittances as the measure of remittances. Therefore, the narrow definition of remittances (workers remittances) used in this paper to record remittances. Remittances are divided by remittance-receiving countries populations and converted in constant 2011 international dollars. The income variable in 11

equation (1) is per capita Gross Domestic Product (GDP) in constant 2011 international dollars adjusted for purchasing power parity (PPP). In this paper, I report the impacts of remittances on two type of human capital: health outcomes and educational attainment. After investigating the impacts of remittances on health outcomes and educational attainment, as a robustness check I examine the effect of remittances on HDI. finally, I estimate the impact of workers remittances on labor force participation. Six health measurements are examined in this research: Per capita out-of-pocket health expenditure, undernourishment prevalence, depth of food deficit, under 5 mortality rate, infant mortality rate, and neonatal mortality rate. Although per capita out-of-pocket health expenditure is not a measure of health, because it has a direct effect on health outcomes, is included as one of health outcome measurements. Five explanatory variables are employed in health regressions as the covariates: Population over 65, urban total ratio, newborns protected against tetanus, and per capita health expenditure. Data for all of the dependent and explanatory variables except remittances come from World Development Indicators (World Bank), while remittances data are from the IMF. Nine educational measurements are chosen in this paper: pre-primary gross enrollment rate, primary gross enrollment rate, secondary gross enrollment rate, tertiary gross enrollment rate, percent of children out of primary school, enrollment rate in private primary, secondary compliment rate, primary compliment rate, and gender parity index for primary education. Data on all of the dependent and explanatory variables except remittances come from World Development Indicators. Two new explanatory variables are employed in this section: Labor force participation and government expenditures on education as a percentage of GDP. Table 1 describes all dependent and explanatory variables alongside their descriptive statistics. Table 2 provides descriptive statistics for gender-specific variables. Except for remittances and HDI, data on all variables are from the world development indicators. Remittance data are from IMF. HDI data are from United Nations Development Programme (UNDP). This study uses 5 instruments to address endogeneity of workers remittances: weighted average per capita GNI, unemployment rate, real interest rate, real exchange rate, and labor force participation rate of the remittance-sending countries. Data on GNI and populations are from United Nations. Data on unemployment rate, real interest rate, and labor force participation rate are from world development indicators. Real interest rates are defined as lending interest rate adjusted for inflation as measured by the GDP deflator. Real exchange rates are defined as nominal exchange rates (units of host country currency per US dollar: e.g., 1.2 Euro/Dollar) multiplied by US Price Index, divided by host country s price index. Therefore, a rise in nominal or real exchange rates means a real depreciation in the host country s currency. Exchange rates data are from the IMF, and GDP deflator data are from the United Nations. 12

Table 1: Descriptive Statistics Variable Description N Mean SD Min Max Per capita GDP Per capita GDP (constant 2011 US$ adjusted for PPP) 3357 6065 5238 247 40015 Per capita Remittance Per capita remittance (constant 2011 US$ adjusted for PPP) 2268 107.4 174.1 0 1577 Per capita out of pocket Any outlay by households to health practitioners divided 2635 112 116.6 0.11 841 health expenditure by total population (constant 2011 US$ adjusted for PPP) Prevalence of The percentage of the population whose food intake is 2625 20.47 14.33 5 80.8 undernourishment insufficient to meet dietary energy requirements Depth of food deficit How many calories would be needed to lift the 2540 149 119.6 1 744 undernourished from their status. Neonatal mortality rate The number of neonates dying before reaching 3562 24.84 14.01 1.9 73.1 28 days of age per 1,000 live births in a given year. Infant mortality rate The number of infants dying before reaching 3562 48.32 32.98 3.4 171 one year, per 1,000 live births in a given year. Under 5 mortality rate The number of newborns dying before reaching 3562 69.95 56.85 4.6 328 age five per 1,000 live births in a given year. Population over 65 Population ages 65 and above as a percentage 3456 5.07 2.99 1.6 20 of the total population Urban total ratio The ratio of people living in urban areas to total population 3584 44.92 20.3 0 91.8 Food production index Food crops that are considered edible and contain nutrients 3204 94.49 26.16 0 301 Newborns protected The percentage of births by women of child-bearing 2510 72.07 18.51 5 99 against tetanus age who are immunized against tetanus. Per capita health The sum of public and private health expenditures divided 2635 329.7 322.4 5.94 2475 expenditure by total population (constant 2011 US$ adjusted for PPP) Gross enrollment The ratio of total enrollment in pre-primary, regardless 2179 39.92 30.41 0.23 159.6 ratio, pre-primary of age, to the population of the pre-primary age group. Gross enrollment The ratio of total enrollment in primary, regardless 2790 99.59 20.91 20.3 165.7 ratio, primary of age, to the population of the primary age group. Gross enrollment The ratio of total enrollment in secondary, regardless 2222 60.8 28.36 5.13 129 ratio, secondary of age, to the population of the secondary age group. Gross enrollment The ratio of total enrollment in tertiary, regardless 1915 20.45 19.04 0 119.8 ratio, tertiary of age, to the population of the tertiary age group. Out of school rate The percentage of primary-school-age children who 1800 15.6 17.62 0 80.85 at primary age are not enrolled in primary or secondary school Enrollment in private The ratio of enrollment in private primariy schools to the 2070 12.17 16.54 0 99.25 primary schools rate total number of students enrolled in primary education. Primary completion The ratio of new entrants in the last grade of primary 2036 79.54 25.04 13.93 185 rate education to the population at the entrance age. Lower secondary Gross intake ratio to the last grade of 1688 60.46 29.18 0 207 completion rate lower secondary education. Primary gender The ratio of girls to boys enrolled at primary level 2692 0.93 0.11 0 1.26 parity index in public and private schools. Labor force The proportion of the population ages 15 and older 3354 63.84 11.58 38.15 90.6 participation that is economically active Gov expenditures General (local, regional, and central) government 1491 4.33 2.34 0.49 44.3 on education expenditure on education as a percentage of GDP. Human Development Summary measure of average achievement in key 3013 0.57 0.14 0.19 0.83 Index (HDI) dimensions of human development N indicates the number of country-year observations. Time span is from 1990 to 2015. 13

Table 2: Gender-specific Descriptive Statistics Variable N Mean SD Min Max Male infant mortality rate 548 50.57 35.4 3.8 181.9 Female infant mortality rate 548 42.36 30.71 2.9 157.7 Male under 5 mortality rate 548 71.25 58.79 4.9 332.4 Female under 5 mortality rate 548 62.49 54.24 3.9 323.9 Male pre-primary enrollment rate 2020 39.82 30.9 0.26 158.82 Female pre-primary enrollment rate 2020 39.63 30.74 0.2 161.97 Male primary enrollment rate 2692 102.41 19.64 20.74 168.12 Feale primary enrollment rate 2692 96.4 23.32 0 163.02 Male secondary enrollment rate 2043 61.32 26.42 5.64 132.6 Female secondary enrollment rate 2043 59.97 30.8 0 130.06 Male tertiary enrollment rate 1641 19.86 16.74 0 92.32 Female tertiary enrollment rate 1641 22.61 23.19 0 150.71 Male primary completion rate 1898 80.53 23.4 14.62 183.06 Female primary completion rate 1898 77.89 27.57 6.35 187.65 Male lower secondary completion rate 1558 59.94 27.53 0 206.88 Female lower secondary completion rate 1558 59.93 31.26 0 206.31 Male human developmen index 858 0.632 0.122 0.304 0.828 Female human developmen index 856 0.578 0.145 0.118 0.813 Male labor force participation rate 3354 76.76 8.08 43.76 93.7 Female labor force participation rate 3354 51.12 18.72 9.24 90.8 N indicates the number of country-year observations. Time span is from 1990 to 2015. Data on out-of-pocket health expenditures and total expenditure on health cover years between 1995 to 2014. The share of out-of-pocket health expenditures in total expenditure on health in developing countries has fluctuated in recent years. In 1995 and 2014 it was 40.8% and 36.2% respectively. However, there has been a stable increasing trend in the amount per capita total health expenditure and per capita out-of-pocket health expenditure: they went up from $131.4 and $53.6 in the year 1995 (expressed in constant 2011 US dollars adjusted for PPP) to $530.3 and $191.9 in the year 2014 respectively. In recent years there has been a remarkable decline in undernourishment prevalence, depth of food deficit, and child mortality rate across the developing world. Undernourishment prevalence data cover years 1991 to 2015. Undernourishment prevalence went down from 23.7% in the year 1991 to 12.67% in the year 2015. Depth of food deficit data cover years 1992 to 2015. Depth of food deficit decreased from 175.6 kilocalories in the year 1992 to 91.9 kilocalories in the year 2015. In 1990, neonatal, infant, and under 5 mortality rates per 1000 live births were 39.3, 69.1, 99.7 respectively. In 2015, neonatal, infant, and under 5 mortality measures declined to 20.8, 34.6, and 46.4 respectively, in the developing world. As UNDP states, HDI is a summary measure of average achievement in key dimensions of 14

human development: a long and healthy life, being knowledgeable, and having a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions. The health dimension is assessed by life expectancy at birth, the education dimension is measured by the mean of years of schooling for adults aged 25 years and more, and expected years of schooling for children of school age. The standard of living dimension is measured by gross national income per capita. The HDI uses the logarithm of income, to reflect the diminishing importance of income with increasing GNI. The scores for the three HDI dimension indices are then aggregated into a composite index using geometric mean. Data on HDI is adopted from UNDP. While HDI data cover years 1990 to 2015, male and female HDI data cover years 2000, 2005, and 2010 to 2015. In recent years there has been a slight but smooth and stable decreasing trend in labor force participation rate in developing countries. In 1990, total, male, and female average labor force participation rate in developing countries were 68.1%, 82.7%, and 53.4% respectively. In 2015, total, male, and female average labor force participation rate in developing countries were 63.5%, 77.9%, and 48.9% respectively. 4 Econometric Model I use the panel data method to analyze how workers remittances affect human capital investment in the developing world. The relationship that I want to estimate can be written as log(h it ) = β 0 + β 1 log(r it ) + β 2 log(i it ) + X itγ + δ i + e it (1) for i = 1,..., N and t = 1,..., T i where H is a measure of health, education, HDI, or labor supply in country i at time t, β 0 is the intercept, R it is the per capita remittances received by country i at year t, I it is the mean per capita income of country i at year t, X it is a vector of other variables that potentially affect H it, δ i is region dummy 1 and e it is the error term. Since all variables are in logarithm, β 1 can be interpreted as elasticity of human capital with respect to per capita remittances, β 2 can be interpreted as elasticity of human capital with respect to per capita income, and β 3 can be interpreted as elasticity of human capital with respect to other variables included in the regression. Some of the variables used in the regression models, like per capita GDP, are non-stationary in the level, but they are first-difference stationary. Since there are non-stationary variables in 1 The reason that region dummies are used in this research rather than country dummies is that for many countries, there is just one year of data available, and for using country-specific effect, those countries had to be dropped from the regression. To avoid dropping those countries, I used region-specific effects rather that country-specific effect. 15

the regression models, the results of the regressions might be spurious. To check whether the results of the regressions are spurious or not, for the regressions with non-stationary dependent variables, I implement panel cointegration tests. If cointegrations exist, then it can be concluded that the error term is stationary, which means the results of the regressions are not spurious. Two tests are used to check whether panel cointegrations exist: Kao Residual Cointegration Test proposed by Kao (1999) (also known as residual-based Augmented Dicky Fuller test) and Johansen Fisher Panel Cointegration Test proposed by Johansen (1988). In both tests, the null hypothesis is that cointegration does not exist. I implemented both tests for all models with non-stationary dependent variables and all p-values were less than 0.05. Therefore, Based on the results of both tests, the null hypothesis is rejected, which means that cointegration relationship exists among the variables. In other words, the error terms are stationary, and the results of the regressions are not spurious. Another econometric issue that arises here is that the error terms are autocorrelated and also they do not have constant variance, which means the existence of Heteroskedasticity. To overcome Autocorrelation and Heteroskedasticity, Newey-West Heteroskedasticity and Autocorrelation Consistent (HAC) standard errors are used. Remittances may be endogenous to the education or health outcomes in the remittancereceiving countries. The endogenous relationship between workers remittances received and schooling decisions or health outcome can be explained by three reasons. First, there exists a reverse causality between human capital (educational attainment and health outcome) and remittances. An individual may decide to migrate and send remittances because he or she has school-age or sick and undernourished children, and in turn, remittances affect educational investment or health outcome by loosening liquidity constraints. The decision to live outside the country and send remittances is simultaneously determined with the expenditure on health and education. Second, there exist unobserved characteristics included in the error terms that may be correlated with both the decision to send remittances and the decision to send children to a school or how much the household spends on their nutrition and health (e.g. ability or ambition). Third, measurement error is another source of endogeneity. Officially recorded remittances do not include remittance in kind, unofficial transfers through kinship or through informal means such as hawala operators, friends, and family members. The negative impact of transactions costs on remittances encourages migrants to remit through informal channels when costs are high. Transfer costs are higher when financial systems are less developed. Evidence from household surveys also show a sizable informal sector (Freund and Spatafora, 2008). Since poor countries usually are less financially developed, migrants from poor countries are more likely to remit through informal channels. because income is also correlated with human capital investment, measurement error is also one of the sources of endogeneity. Therefore, least squares estimates of the impact of remittances may be biased as remittance 16

is endogenous. The traditional way, which is followed in this paper, is to resolve the endogeneity problem by using instrumental variables. In the following, the instruments suggested by other researchers are discussed and then I introduce the instruments that are used in this paper. Three kinds of instruments are possible to use. First, variables related to remittance-receiving countries. The main problem with using theses instruments is that they can easily be correlated with education, health or labor supply of the same country in a way other than through remittances or covariates. Therefore, they can be invalid instruments. Second, variables related to the cost of remittances (e.g. the number of branches of Western Union). These instruments are usually strong and valid buy data on these variables are mainly unavailable for most of developing countries. The third category is variables related to remittance-sending countries. Since these variables are not related to remittance-receiving countries, after controlling for some covariates, they are valid and strong. However, the main problem is that each remittance-receiving country receives remittances from many remittance-sending countries, and due to lack of information on bilateral remittances, the weights of remittance-sending countries are unknown. Aggarwal et al. (2006) use economic conditions in the top remittance-source countries as instruments for the remittances flows. They argue economic conditions in the remittance-source countries are likely to affect the volume of remittance flows that migrants are able to send, but are not expected to affect the dependent variables in the remittance receiving countries in ways other than through its impact on remittances or covariates. However, Because bilateral remittance data are largely unavailable they identify the top remittance-source countries for each country in the sample, using 2000 bilateral migration data. The dataset identifies the top five OECD countries that receive the most migrants from each remittance-recipient country. They assume that these countries account for the all of the remittance flows sent to the remittancerecipient countries. They construct three instruments by multiplying the per capita GDP, the real GDP growth, and the unemployment rate, in each of the top five remittance-source countries by the share of migration to each of these five countries. The technique used in this paper is similar to Aggarwal et al. (2006). However, I use an estimation of bilateral remittances and use them as weights of remittance-source countries. In this research, I introduce five instruments that are correlated with remittances and uncorrelated with the dependent variables unless through explanatory variables. Workers remittances, by definition, are money sent by migrants from host countries (remittance-sending countries) to their home countries (remittance-receiving countries). The value of remittances hinges on both host and home economic variables. Since the dependent variables belong to the home countries, in order to ensure the instruments are valid, we should select some economic variables from the host countries. Five variables used in this research as instruments are per capita GNI, unemployment rate, real interest rates, real exchange rate (versus US Dollars), and labor force 17