Global Majority E-Journal

Volume 8, Number 2(December 2017)

Global Majority E-Journal

About the Global Majority E-JournalThe Global Majority E-Journal is published twice a year and freely available online at: http://www.american.edu/cas/economics/ejournal/. The journal publishes articles that discuss critical issues for the lives of the global majority. The global majority is defined as the more than 80 percent of the world’s population living in low- and middle-income countries. The topics discussed reflect issues that characterize, determine, or influence the lives of the global majority: poverty, population growth, youth bulge, urbanization, lack of access to safe water, climate change, agricultural development, etc. The articles are based on research papers written by American University (AU) undergraduate students (mostly freshmen) as one of the course requirements for AU’s General Education Course: Econ-110—The Global Majority.

EditorDr. Bernhard G. Gunter, Assistant Professor, Economics Department, American University; Washington, DC; and President, Bangladesh Development Research Center (BDRC), Falls Church, VA, United States. The editor can be reached at gunter@american.edu.

Cover DesignBased on an animated GIF (Graphics Interchange Format) available as Wikimedia Commons, created in 1998 by Christian Janoff, showing the “Globe” demonstration as it can be found on the Commodore REU 1700/1750 test/demo disk; please see:http://en.wikipedia.org/wiki/File:Globe.gif.

ISSN 2157-1252

Copyright © 2017 by the author(s) for the contents of the articles.

Copyright © 2017 by American University for the journal compilation.All rights reserved. No part of this publication may be reproduced, stored or transmitted in any form or by any means without the prior permission in writing from the copyright holder. American University, the editor and the authors cannot be held responsible for errors or any consequences arising from the use of information contained in this journal. The views and opinions expressed are those of the authors and should not be associated with American University.

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Global Majority E-Journal

Volume 8, Number 2 (December 2017)

Contents

Muslim Baby-Boom? Examining Fertility in Bangladesh and LebanonKendell Lincoln 66

Climate Change and Natural Disastersin India and BrazilJoseph Bisaccia 81

Leave the Knot Untied: Education and Child Marriagein Bangladesh and BoliviaEmily Lytle 95

Effects of Climate Change on Agriculture in Guatemala and HondurasKarissa Waddick 109

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Global Majority E-Journal, Vol. 8, No. 2 (December 2017), pp. 66-80

Muslim Baby-Boom? Examining Fertility in Bangladesh and Lebanon

Kendell Lincoln

AbstractWhile fertility has long been understood as under the influence of many factors, the effects of cultural circumstances, namely religion, are understudied. As fertility rates remain high in the developing world and many majority Muslim countries, the need for further analysis becomes evident as high fertility rates seem to hold back growth and development. This article uses Bangladesh and Lebanon as case studies to examine the evolution of fertility rates over time and to what degree religion remains a determinant for fertility rates.

I. IntroductionThe effect of fertility on population growth is logical: fertility has a direct relationship to population growth, as births per woman are together with the death rate the key factors determining the growth rate of a population. Economists, development theorists, and public health interventionists have long identified the key contributors to fertility as socioeconomic status, education levels, access to contraceptives, and cultural and religious values. Fertility patterns among Muslim women emerge regardless of country of origin. Rooted in history, culture, and habits, religion offers a lens to examine fertility.

This article adopts that lens, and applies religion and culture as another institution for examining fertility beyond socioeconomic and developmental determinants in two pre-dominantly Muslim countries: Bangladesh and Lebanon.

Following this introduction, the next section provides a brief review of the literature on previous research done on fertility in Bangladesh and Lebanon. The literature review section is followed by some socio-economic empirical background for Bangladesh and Lebanon in section III. The fourth section examines first the evolution of fertility rates and other population statistics over time, and discusses then how religion, unmet need for contraceptives, and unwanted pregnancies are related to each other in Bangladesh and Lebanon. Building on an explanation for high fertility rates put forward by Wyshak (1999), the discussion section examines the correlation between fertility and access rates to water and sanitation in Bangladesh and Lebanon. The last section provides some conclusions and recommendations.

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II. Brief Literature ReviewAccording to Yurtseven (2015), fertility rates in Muslim countries remain largely understudied. While this seems true for Lebanon, there actually is a relatively large literature on fertility in Bangladesh. This brief literature review summarizes three studies that have examined Lebanon’s fertility and four recent studies examining Bangladesh’s fertility.

II.1. Studies Focusing on Lebanon

Beydoun (2001) concluded that illiterate women in Lebanon end up supplying an excess number of children, which is mediated by the shorter lactation period of more educated women (triggered by a higher access of more educated women to breast milk substitutes). She also finds that educated husbands demand more children, while educated women demand ‘child quality’ as they expect both material and opportunity costs of having a child to coincide with the norms and values of their social class. Their lower supply of births with increased economic well-being is primarily attributed to a higher use of modern contraceptive methods.

Khawaja (2003) describes the lack of fertility decline in Lebanon, despite favorable social conditions as “a demographic puzzle”. One explanation centers around the Palestinian-Israeli conflict and the influx of Palestinian refugees. The article goes on to detail the Lebanese piece of this puzzle, describing the environment and economic systems that contribute to its abnormally high fertility rate. Khawaja continued to examine fertility trends among women based on a number of determinants: refugee status, education, as well as proximate determinants such as marriage proportions, contraceptive prevalence, sterility, abortion, sexual behavior, and breastfeeding.

Tfaily, Khawaja and Kaddour (2009) examine differentials in fertility between Christians and Muslims in three socio-economically poor communities in Greater Beirut and Lebanon using data from the 2002–2003 Urban Health Survey. They find that both Christian and Muslim women are controlling their fertility but that the decline in fertility among Christian women has been underway for some time, while that for Muslim women is a more recent phenomenon. They assert that these differences in marital fertility by religious affiliation persist after controlling for differences in socio-economic conditions, religiosity, and cultural capital. Tfaily, Khawaja and Kaddour (2009) also discuss context-specific explanations of the religious fertility differences taking Lebanon’s social, economic, historic and political context into account.

II.2. Recent Studies Focusing on Bangladesh

Duvendack and Palmer-Jones (2017) first state the “Bangladesh paradox” of improved wellbeing despite low economic growth over the last four decades has been claimed as a paradigmatic case of the spread of both modern family planning programs and microfinance leading to women’s empowerment and fertility reduction. They then examine the links between microfinance, empowerment and fertility reduction and come to the conclusion that these links are fraught with problems, and far from robust. They suggest that the claimed causal links between microfinance and family planning via women’s empowerment needs to be examined further.

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Hernández-Julián, Mansour and Peters (2014) examine the effects of malnutrition on birth and fertility outcomes based on the evidence from the 1974 Bangladesh famine. They find that women who were pregnant during the famine were less likely to have male children. Moreover, children who were in utero during the most severe period of the Bangladesh famine were more likely to die within one month of birth compared with their siblings who were not in utero during the famine. Hernández-Julián, Mansour and Peters (2014) also estimate the impacts of the famine on subsequent pregnancy outcomes. Controlling for pre-famine fertility, they find that women who were pregnant during the famine experienced a higher number of stillbirths in the post-famine years. This increase appears to be driven by an excess number of male stillbirths.

Islam and Nesa (2009) focus on the fertility transition in Bangladesh through educational differentials. Their results show that fertility declined considerably with women's education. The illiterate and poor women had the highest fertility rate, whereas secondary-educated rich woman had the lowest fertility. This relationship also held even after controlling the other factors such as place of residence, region, and household wealth status. All of the factors included in the study showed significant effect on the children ever born. For example, the fertility rate was found to be higher among rural women than urban women. Based on these findings, Islam and Nesa (2009) suggest that compulsory free higher education is necessary to bring a further reduction of fertility in Bangladesh.

Rahman and Roy (2015) discuss the determinants of unwanted fertility in Bangladesh. Posing the question of whether sex preference and unmet need are dominant, the study aims to investigate the ultimate determinants of high unwanted fertility. While the national fertility rates have been decreasing steadily since the 1970s, researchers have identified a large percentage of births to be unintended. The socio-economic development is considered the main cause of fertility transition, but Rahman and Roy describe other factors contributing to Bangladesh’s unique fertility situation. Unmet need, sex preference, age at first marriage, religion, women’s completed years of schooling, and couples’ desire for children are discussed and upheld as variables determining fertility.

III. Empirical Background Figure 1 shows the geographical location of the two countries. Bangladesh is a South Asian country, while Lebanon is located in the Middle East. With 90 percent and 54 percent of the population considering themselves to be of Muslim faith, respectively,1 both are pre-dominantly Muslim countries, though neither country’s government is considered to be dominated by religious beliefs.

In terms of land area, Bangladesh is (with 130,170 square km) about 13 times larger than Lebanon (10,230 square km). Based on official population statistics, Bangladesh is currently about 35 times more populated than Lebanon. Bangladesh has currently about 161 million people, while Lebanon’s official population is about 4.6 million. As stated in Francis (2017), during the last six years, about 1.5 million Syrians poured into Lebanon. However, most of these

1 Respectively, https://en.wikipedia.org/wiki/Freedom_of_religion_in_Bangladesh and https://en.wikipedia.org/wiki/Religion_in_Lebanon.

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refugees are not considered legal residents.0 Hence, they are typically not reflected in Lebanon’s official population data. Including these 1.5 million Syrian refugees, Lebanon’s population would be close to 6 million people. In 2017, Bangladesh also experienced an influx of refugees. The UN-led Inter-Sector Coordination Group (ISCG) reported on October 22, 2017 that an estimated 603,000 refugees from Rakhine, Myanmar had crossed the border into Bangladesh since August 25, 2017.0

Figure 1: Geographic Location of Bangladesh and Lebanon

Source: Created by author based on Google Maps (2017).

Figure 2: Population (in millions), 1970-2015

0 See Francis (2017).0 As reported by PressTV, available at: http://www.presstv.com/Detail/2017/10/22/539540/Myanmar-Bangladesh-Rohingya-UN.

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Source: Created by author based on World Bank (2016).

As Figure 3 shows, Lebanon is about six times richer than Bangladesh in terms of purchasing power parity (PPP)-adjusted GDP per capita. In 1990, Bangladesh’s GDP per capita was $1,290, while that of Lebanon was $7,734 (which is almost exactly six times that of Bangladesh). Lebanon’s GDP per capita grew then very quickly during the early 1990s, though it started to stagnate and even decrease slightly from 1996 to 2006. In 2006, Lebanon’s GDP per capita was once again nearly six times that of Bangladesh. Both countries experienced relatively high growth rates during the subsequent four years, after which Lebanon’s GDP per capita once again started to stagnate. In 2014, Bangladesh’s GDP per capita was $2,979, while that of Lebanon was $16,659. Bangladesh was a low-income country until it got reclassified by the World Bank in 2015 as a lower-middle income country, while Lebanon is currently classified as an upper-middle income country.

Figure 3: PPP-adjusted GDP per capita, 1990-2014

Source: Created by author based on World Bank (2016).

Bangladesh and Lebanon also made solid progress in increasing life expectancy. Figure 4 shows the growing life expectancy for both Bengali and Lebanese populations from 1970 to 2015. During these 45 years, Bangladesh added 24.5 years of life expectancy, while Lebanon added 13.5 years. Hence, in 2015, Bangladesh’s life expectancy stood at 72.0 years, while that of Lebanon was 79.6 years. The data scope for poverty headcounts is limited, but the most recent totals as percent of population are as follows: In 2010, poverty affected 31.5 percent of Bangladesh’s population (based on national poverty lines). In 2012, although considerably less, still 27 percent of Lebanon’s total population faced poverty based on their national poverty lines.0

0 World Bank (2016).

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Figure 4: Total life expectancy at birth, Bangladesh and Lebanon, 1970 to 2015

Source: Created by author based on World Bank (2016).

Figure 5: Adult literacy rate (percent of population, 15 years and older), all available data

Source: Created by author based on World Bank (2016).

Even though we have only one year of observation for Lebanon’s adult literacy rate, Figure 5 seems to indicate that Lebanon is also far better off than Bangladesh in terms of literacy. Bangladesh has doubled its adult literacy rate from 1981 to 2013 (from about 30 percent to 60 percent), but still lacks at least 30 percentage points behind Lebanon, which already had a literacy rate of nearly 90 percent in 2007.

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Finally, as Figure 6 shows, Lebanon is a highly urbanized country (with nearly 90 percent of its population living in urban areas), while most of Bangladesh’s population live in rural areas. Bangladesh is however experiencing rapid urbanization. While less than ten percent of Bangladesh’s people lived in urban areas in 1970, by 2015, nearly 35 percent of Bangladesh’s people had urbanized. The conclusion drawn from Figures 3 to 6 is that despite considerable progress, Bangladesh is still a considerably less developed and less urbanized country than Lebanon.

Figure 6: Share of Urban Population (in percent of total), 1970-2015

Source: Created by author based on World Bank (2016).

IV. DiscussionBangladesh and Lebanon experience changes in their fertility rates that originate in a variety of inter-related sources, including religious and social norms that influence marriage age and the desire for children, socio-economic factors like income and education, as well as the availability and acceptability of modern contraceptives. This discussion section will first provide some basic information on the evolution of population growth, total fertility rates, crude birth rates, and adolescent fertility rates. It will then focus on the intersection of religion, unmet need for contraceptives, and unwanted fertility that contribute to fertility rates. Building on the hypothesis of Wyshak (1999), that not having access to clean water for hygienic purposes and for convenient coping with menstruation is associated with higher fertility, we will then review the evolution of access to safe water and sanitation.

IV.1. Evolution of Population Growth, Fertility and Birth Rates

Despite the fact that most refugees are not counted in the official population figures, Figure 7 shows that Lebanon has highly volatile population growth rates. Bangladesh also experienced rapid changes in population growth rates in most the 1970s, but then experienced a steady

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decline in the population growth rates from a high of 2.8 percent in 1978 to a low of 1.1 percent in 2009, after which it increased slightly and seems to have then stabilized at around 1.2 percent.

Figure 7: Population Growth (in percent), 1970-2015

Source: Created by author based on World Bank (2016).

Figures 8 and 9 depict the total fertility rates and the crude birth rates, respectively, of Bangladesh and Lebanon. We show these two graphs next to each other to better see the similarly between them. While Bangladesh had far higher fertility and birth rates than Lebanon in 1970, both have declined steadily for Bangladesh, catching nearly up with Lebanon’s fertility and birth rates in 2015. These low fertility rates in both countries seem to indicate that the influence of religion (which typically keeps fertility rates high) has largely disappeared in both countries.

Figures 8 and 9: Total Fertility Rates and Birth Rates, 1970 to 2015

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0

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Source: Created by author based on World Bank (2016).

IV.2. Religion, Adolescent Fertility, and Contraceptive Prevalence

While development theorists have long recognized that fertility exists on a divide at socioeconomic and demographic development levels, the changing fertility occurring with modernization does not follow the traditional indexes such as female autonomy, literacy, or presence in the workforce. Rather, it follows alterations in the value of children in the class-specific family economy.0 The KAP-gap, known for knowledge, attitude, and practice, highlights the more complex nature of family planning and fertility, and reveals a gap in these three areas.0 Greenhalgh (1990) stresses that a political economy of fertility directs attention to the embeddedness of community institutions in structures and processes.

For Lebanon and Bangladesh, the indirect relationship between the economic progress and fertility has been illustrated in Figure 3 (showing increases in GDP per capita) and Figure 8 (showing declining fertility rates). Logically this makes sense, as children present an economic burden that, particularly in a developing country, prevents a household from reaching their full economic potential. Child rearing contributes mostly to reduced female economic prospects, as a mother’s domestic tasks greatly increases her time-poverty and prevents her from undertaking paid work.

But new lines of analysis examine religious affiliation as a determinant of fertility in Muslim women. Hence, it can be expected that more religious Lebanese and Bengali women will experience higher fertility rates than less religious women. Figure 10 shows that religious and cultural norms still influence at what age girls get married in Bangladesh, resulting in relatively high adolescent birth rates, shown in Figure 11. The connection between the age a woman is married and her fertility is well-understood and logical. Lebanon sees less women entering marriage before the age of 18, which contributes to a lower adolescent fertility rate.

0 Greenhalgh (1990).0 Casterline and Sinding (2000).

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Figure 10: Women who were first married by age 18 (% of women ages 20-24)

Source: Created by author based on World Bank (2016).

Figure 11: Adolescent Fertility Rates (births per 1,000 women ages 15-19), 1970-2015

Source: Created by author based on World Bank (2016).

According to Casterline and Sinding (2000), roughly one-fifth of all births in the developing world are unwanted. Furthermore, Casterline and Sinding (2000, p. 700) explain: “Social scientists who have studied the relationship between attitudes, motivation, and behavior have long recognized that strongly held preferences will often not have direct behavioral counterparts because of obstacles to the implementation of those preferences”, such as cultural norms originating in religion.

Yurtseven (2015) notes that contraceptive prevalence is an important determinant of fertility, and offers insights into the lack of Muslim women utilizing contraceptives. As cited by Yurtseven

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(2015, p. 167), “Campbell et al. (2013) assert that if women’s mobility is restricted due to group norms and practices, women’s exposure rate to new ideas and innovations, including contraceptives, decreases. In addition to this, opposition from husbands may decrease the use of contraceptives thereby increasing fertility in patriarchal settings. Muslim women’s traditional primary role of wife and mother strengthens the position against contraceptive use (Espesito and DeLong-Bas, 2001).” He also comments on Sharia law as a powerful force among Islamic states that gives political and social importance to marriage, with the basic objective to bring up healthy and faithful children.

Figure 12 shows the modern contraceptive prevalence rate (as percent of all women ages 15-49) in Bangladesh and Lebanon. The limited data, especially for Lebanon, seems to indicate that women in Bangladesh have a higher prevalence rate of modern contraceptive use than Lebanese women, especially as the percentage of Lebanese women using modern contraceptives has decreased from 2000 to 2004. While the decline in use in Lebanon is consistent with the decline in their GDP per capita during this period, it is inconsistent with Lebanon’s higher level of income and development compared to Bangladesh. Furthermore, the Lebanese data is also inconsistent with Khawaja (2003), who reported that 58 percent of married Lebanese women use modern contraceptives.

While the World Bank (2016) contains no data for unwanted fertility in Lebanon, Figure 13 displays Bengali women’s total fertility rate compared to their wanted fertility rate for all available years with data for both variables. The available data clearly shows that wanted fertility is consistently below the total fertility, and hence, there is a significant amount of unwanted fertility. Rahman and Roy (2015) report that in Bangladesh, the proportion of more religious women experiencing unwanted birth is, with 18 percent, almost double than that of others.

Figure 12: Contraceptive prevalence, modern methods (% of women ages 15-49)

Source: Created by author based on World Bank (2016).

Figure 13: Total Fertility and Wanted Fertility in Bangladesh, all available years

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Source: Created by author based on World Bank (2016).

IV.3. Access to Water and Sanitation

Wyshak (1999) draws an interesting connection between fertility and access to clean water. Establishing feminine hygiene as a public health concern, she poses (p. 155): “Because of the unavailability of means to cope with 10 or 12 menstrual cycles per year, women may, consciously or unconsciously, have more pregnancies and prolong their post-partum amenorrhea through breast feeding.” Here, menstrual cycles are contributing to high fertility rates by incentivizing women of reproductive age to prevent their cycles. Whether or not these subsequent pregnancies are unwanted or not is unknown, but Wyshak’s findings support her hypothesis that not having access to water for hygienic purposes and for convenient coping with menstruation is associated with higher fertility. We will reexamine her hypothesis based on the latest data for Bangladesh and Lebanon.

Figures 14 and 15 display the access rates to improved water sources and sanitation facilities in Bangladesh and Lebanon. Combined with the previously shown (see Figure 8) lower fertility in Lebanon than in Bangladesh, the data remains consistent with Wyshak’s assertions as Lebanon, which has consistently higher access rates to safe water and sanitation than Bangladesh, also has consistently lower fertility rates.

Figures 14 and 15: Access to Improved Water and Sanitation (in percent of total pop.) in Bangladesh and Lebanon

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6065707580859095

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Source: Created by author based on World Bank (2016).

However, to investigate Wyshak’s hypothesis more carefully, Figure 16 shows the evolution of access rates for safe water and sanitation in Bangladesh next to the evolution of Bangladesh’s fertility rates. The same three time series are then provided for Lebanon in Figure 17. Despite showing simple correlations, which do not prove a hypothesis, the Bangladeshi data is consistent with Wyshak’s hypothesis as access to improved water and sanitation is increasing continuously, while fertility rates continuously decrease. In the case of Lebanon, the situation is a bit more complicated as access to water and sanitation are not directly related to each other. The access rates to improved water increase in Lebanon from 1998 to 2011, after which they stabilize at close to 100 percent, while the access rate to improved sanitation facilities is initially stable at around 83 percent (from 1998 to 2002), then declines slowly to about 81 percent (from 2002 to 2011), and remains then again stable (from 2011to 2015). From 1998 to 2009, Lebanon’s fertility rate is negatively correlated to Lebanon’s access rate to improved water; the relationship is however less clear after 2009. There is certainly no stable correlation between Lebanon’s access rate to improved sanitation and Lebanon’s fertility rate.

Figure 16: Access to Improved Water, Access to Improved Sanitation, and Fertility Rates in Bangladesh

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Source: Created by author based on World Bank (2016).

Figure 17: Access to Improved Water, Access to Improved Sanitation, and Fertility Rates in Lebanon

Source: Created by author based on World Bank (2016).V. Conclusion and RecommendationsWe have shown that neither Bangladesh nor Lebanon are currently experiencing particularly high fertility rates. Yet, it is undeniable that cultural and religious factors still influence fertility rates in both countries, at least through limiting access to or the use of modern contraceptives. Greenhalgh (1990) referred to a homegrown version of political economy and cultural history, which becomes imperative in understanding Lebanon’s and Bangladesh’s fertility rates. She also asserts that from practices originating in patriarchy to teachings regarding contraceptives, fertility exists as a microscopic piece of behavior artificially extracted from the larger kinship and family contexts of which it is an integral part. Rahman and Roy (2015) emphasize that the

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elimination of unwanted births leads not only to substantial reductions in fertility and population growth, but it also upholds the individual right of women to determine their lives. Yurtseven (2015) emphasized that most of the variability in fertility is captured by a country’s norms about fertility, and Bangladesh and Lebanon are no exceptions. He comes to the conclusion that even with improving socioeconomic conditions, the convergence of the fertility rates of majority Muslim countries with that of western countries may not occur quickly.

Recommendations for combating unwanted fertility must originate in addressing the cultural roots of unmet need for family planning. Some proposed interventions display the cultural competency necessary to combat the complex social, political, and religious issue of unwanted pregnancy amongst Muslim women. As over 40 percent of Muslim women report not using any form of contraceptives, urgency arises to curb fertility rates and provide women economic and social opportunity by decreasing their childrearing burden. Yurtseven (2015) recommends that special attention be given to Muslim women in providing family planning services, ensuring that a variety of options are made available to them based on cultural and access implications. Due to the possible correlation between access to improved water/sanitation and fertility (as was suggested by Wyshak (1999)), these interventions should also include an emphasis on supplying clean water and sanitation to women.

In any case, no single intervention will solve the fertility crisis, which remains an issue as long as there is unwanted fertility. Rather, interventions must exercise social competency to address the specific needs of Muslim women, taking into account their cultural history and barriers to use modern contraceptives, such as women’s lack of power. Still, some specific interventions like providing education to women, encouraging girls to getting married later, and providing access to improved water and sanitation, can be highly effective for lowering fertility rates. These recommendations extend beyond Bangladesh and Lebanon to populations across the world facing similar intersections of culture, religion, development, and fertility.

ReferencesBeydoun, May A. (2001). Marital Fertility in Lebanon: A Study Based on the Population and

Housing Survey. Social Science & Medicine, Vol. 53, No. 6 (September), pp. 759–771.

Duvendack, Maren and Richard Palmer-Jones (2017). Micro-Finance, Women’s Empowerment and Fertility Decline in Bangladesh: How Important Was Women’s Agency? Journal of Development Studies, Vol. 53, No. 5, pp. 664–683.

Campbell, Martha; Ndola Prata; and Malcolm Potts (2013). The Impact of Freedom on Fertility Decline. Journal of Family Planning and Reproductive Health Care, Vol. 39, No. 1, pp. 44–50.

Casterline, John B. and Steven W. Sinding (2000). Unmet Need for Family Planning in Developing Countries and Implications for Population Policy. Population and Development Review, Vol. 26, No. 4 (December), pp. 691–723.

Esposito, John L. and Natana J. DeLong-Bas (2001). Women in Muslim Family Law (Syracuse, NY: Syracuse University Press).

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Francis, Ellen (2017). Hostility grows towards Syrian refugees in Lebanon. Reuters, World News, August 28, 2017; available at: https://www.reuters.com/article/us-lebanon-refugees-tension/hostility-grows-towards-syrian-refugees-in-lebanon-idUSKCN1B8128.

Greenhalgh, Susan (1990). Toward a Political Economy of Fertility: Anthropological Contributions. Population and Development Review, Vol. 16, No. 1 (March), pp. 85–106.

Hernández-Julián, Rey; Hani Mansour; and Christina Peters (2014). The Effects of Intrauterine Malnutrition on Birth and Fertility Outcomes: Evidence from the 1974 Bangladesh Famine. Demography, Vol. 51, No. 5, pp. 1775–1796.

Islam, Sabina and Mossamet Kamrun Nesa (2009). Fertility Transition in Bangladesh: The Role of Education. Proceedings of the Pakistan Academy of Sciences, Vol. 46, No. 4 (December), pp. 195–201; available at: https://www.researchgate.net/publication/228652514_Fertility_transition_in_Bangladesh_The_role_of_education

Khawaja, Marwan (2003). The Fertility of Palestinian Women in Gaza, the West Bank, Jordan and Lebanon. Population, Vol. 58, No. 3, pp. 273–302.

Rahman, Mahfuzur and Tapan Kumar Roy (2015). Determinants of Unwanted Fertility in Bangladesh: Whether Sex Preference and Unmet Need are Dominant? Romanian Journal of Population Studies, Vol. 9, No. 1 (January-June), pp. 81–103.

Tfaily, Rania; Marwan Khawaja; and Afamia Kaddour (2009). Christian-Muslim Fertility Differences in Poor Settings in Greater Beirut, Lebanon. Paper presented at the 26th International Population Conference of the International Union for the Scientific Study of Population (IUSSP) in Marrakesh, Morocco (September 27-October 2); preliminary draft available at: http://iussp2009.princeton.edu/papers/93343.

World Bank (2016). World Development Indicators / Global Development Finance Database (Washington, DC: The World Bank); as posted on the World Bank website: http://data.worldbank.org/data-catalog/ (downloaded on June 28, 2016).

Wyshak, Grace (1999). New Insights into the Determinants of the Total Fertility Rate, Infant Mortality Rate and Life Expectancy. International Journal of Sustainable Development and World Ecology, Vol. 6, No. 3, pp. 155–166.

Yurtseven, Caglar (2015). The Socioeconomic Determinants of Fertility Rates in Muslim Countries: A Dynamic Panel Data Analysis. Economics and Sociology, Vol. 8, No. 4, pp. 165–178; available at: http://www.economics-sociology.eu/files/17_184_Yurtseven.pdf.

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Global Majority E-Journal, Vol. 8, No. 2 (December 2017), pp. 81-94

Climate Change and Natural Disastersin India and Brazil

Joseph Bisaccia

AbstractThis article looks at the effects that climate change has on the developing world based on recent experiences in Brazil and India. Both of these countries have vastly growing economies, but climate change and the natural disasters that it causes are hindering further progress. Based on a UNICEF report by Cabral et al. (2009), millions of deaths of children and adolescents in Brazil are a result of climate change. Similarly, a World Bank report by Hallegatte et al. (2016) concluded that climate change could negate India’s progress, as it may push almost 50 million people into extreme poverty over the next 15 years. This article analyzes the effects that climate change had on Brazil and India, focusing on floods, droughts and food production.

I. Introduction Although climate change from greenhouse gas emissions is an international issue, its environmental effects hit the developing world much harder than the rest of the world. The developing world is geographically and socioeconomically more vulnerable to natural hazards from global warming than the industrialized world. Brazil and India are two countries within the developing world that are experiencing poverty reduction and economic development, but climate change is impeding further progress.

While Brazil and India have many similarities with regards to the impact of climate change, there is a major difference in the source of greenhouse gas emissions in these two countries. After China, India leads the developing world in greenhouse gas emissions from burning fossil fuels, while Brazil leads the developing world in emissions from deforestation and other land use. With that being said, although deforestation and a loss of biodiversity are major issues, this article will only address deforestation to the extent of its effect on Brazil’s development. In both countries, the majority of the population living in urban and rural areas are suffering from natural hazards and a subsequent shortage of agricultural products.

Following this introduction, the next section covers a brief review of the literature. The subsequent section provides an empirical background of the countries in question. The

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discussion section will focus on two major effects of climate change in these two countries (floods and droughts) as well as examine the impacts of climate change on agriculture and forestry. The final section will be the conclusion, which summarizes the main points and poses some potential solutions to the issue.

II. Brief Literature Review Given the serious implications of climate change in developing countries, there is a relatively large literature examining various effects of climate change in Brazil and India. This brief literature review focuses on four recent contributions, two for each country. Cabral et al. (2009) and Marengo (2009) focus on Brazil, while Hayden (2016) and World Bank (2013a) focus on India. In each case, the authors look at the current situation of the country and assess the effects that climate change is having on the country as well as what can be done to reduce these effects.

Based on data for the early 2000s, Cabral et al. (2009) ranked Brazil among the four largest polluters in the world, representing five percent of the global emissions. Unlike most other countries, whose main source for greenhouse gas emission is the burning of fossil fuels, in Brazil 75 percent of emissions occur in land-use activities such as deforestation and burning for agriculture use. They examine how growing rates of desertification and deforestation in Brazil are driving the country into poverty. Finally, Cabral et al. (2009) provide a number of proposals for the construction of another world, especially through the participation of children and adolescents.

Hayden (2016) explains the present and future dangers that India faces due to climate change and suggests that solar fuel can help alleviate some of the problems that the India people will face. The article details that 44 percent of India’s energy came from coal in 2013. The article describes the assertions of Prime Minister Narenda Modi, who has pledged to source 40 percent of the country’s electricity from renewable and low-carbon sources by 2030. Although this plan will help lower carbon emissions in the cities and more wealthy areas of India, we also need to keep in mind that 300 million Indians live currently without electricity.

Marengo (2009) illustrates the growing frequency and intensity of natural disasters in Brazil, especially in the second half of the 20th century and into the 21st century. The article explicates the consequences and implications of extreme weather events, such as floods and landslides, and how they will affect the future of Brazil’s economy. Marengo (2009) states that climate studies have projected that precipitation is expected to increase in the southern, western Amazonia and the coastal regions of Brazil, while lower rainfall is to be expected in the remaining regions. In addition to this, the article describes that by 2030, the dominant pattern of rainfall shows a reduction in rainfall in areas such as the tropical regions, but also shows a pattern of increasing rainfall in southern Brazil. Ultimately, this article illuminates the increasing frequency of extreme weather events and how they could potentially affect many of Brazil’s people, businesses and companies, which affects the entirety of the economy overall. Marengo (2009) suggests that the insurance industry plays a vital role in contributing to the efforts against global warming by offering innovative cost solutions and green investments.

A Press Release by the World Bank (2013a) focuses on the implications climate change has on India, based on a report written for the World Bank by the Potsdam Institute for

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Climate Impact Research and Analytics.0 The press release states that the warming climate poses a significant risk to India’s agriculture and water resources. Basing its analysis on the Potsdam Institute’s prediction that the world would warm four degrees above pre-industrial levels by the end of this century, the press release declares that India will be affected more than any other country due to its geographic location, its already high poverty rate, and its high population. The press release concludes with offering prospects for the future, where the World Bank has partnered with the government of India to support rural livelihood projects and the development of environmentally sustainable hydropower.

III. Empirical BackgroundIn 2015, India and Brazil were, respectively, the second and fifth most populous countries in the world. As illustrated in Figure 1, in 1970, the population of Brazil was 96 million while the population of India was 554 million. As of 2014, the population of each country has more than doubled. The population of Brazil in 2014 was 206 million people and the population of India was 1.3 billion. Though both countries’ population growth has declined by half overtime, India’s average annual population growth is with currently 1.2 percent higher than that of Brazil’s 0.9 percent. Given that Brazil has nearly three times the amount of land mass as India but one-sixth of the population, Brazil’s population density is currently 25 people per square km, while India’s is 441 people per square km.0

Figure 1: Total Population (in millions), 1970-2015

Source: Created by the author based on the World Bank (2016).

0 See Adams et al. (2013).0 The data of this paragraph is based on World Bank (2016).

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Figure 2 depicts the evolution of Gross Domestic Product (GDP) per capita of India and Brazil in the constant 2011 international $ adjusted for purchasing power parity (PPP). While Brazil’s GDP per capita was more than five times that of India in 1990, it was slightly less than three times that of India in 2014. As is clearly visible in Figure 2, Brazil’s GDP per capita has started to stagnate in recent years while that of India continued to grow, which can be partially explained by the different impact the 2008 international recession had on these two countries. Although both countries have overall experienced positive GDP per capita growth over the past two decades, it does not take into account the loss or lack in GDP per capita growth due to health issues, natural disasters, and the loss of agriculture and forests from greenhouse gas emissions.

Figure 2: GDP per capita, PPP (constant 2011 international $), 1990-2014

Source: Created by the author based on the World Bank (2016).

Though data on the incidence of poverty is available for only selected years, it is clear that both India and Brazil have made tremendous progress over the past 30 years with reducing poverty. Brazils’ poverty headcount ratio at $1.90 a day (2011 PPP) was 3.66 percent as of 2014, which is a tenth of what it was in 1983.0 As of 2011, India’s poverty headcount ratio was at 21.23 percent, which is 30 percentage points less than it was in 1983.0

Figure 3 depicts the life expectancy at birth in India and Brazil from 1990 to 2014. While Brazil’s average life expectancy has consistently been higher than that of India, both countries have experienced a similar increase in average life expectancy over the past two decades. In 1990, Brazil’s average life expectancy was 65 years while that of India was 58 years, making a difference of 7 years in Brazil’s favor. In 2015, Brazil’s average life expectancy was 74 years, while India’s was 68 years, making a difference of 6 years in Brazil’s favor.

0 World Bank (2016). 0 World Bank (2016).

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Figure 3: Average Life Expectancy at Birth (in years), 1970-2015

Source: Created by the author based on the World Bank (2016).

Figure 4 depicts the adult literacy rates of Brazil and India from 2000 to 2015. Brazil’s literacy rates are consistently higher than those of India. As of 2015, Brazil’s literacy rate was 93 percent, while India’s was 72 percent. Given that India’s adult literacy rate was slightly less than 41 percent in 1981, while that of Brazil stood at 75 percent in 1980, it makes sense that India’s average adult literacy rate has been growing much faster than that of Brazil.

Figure 4: Adult Literacy Rate of Population 15+ Years (both sexes, %), all available years

Source: Created by the author based on the World Bank (2016).

Figure 5 shows the 15 countries with the highest CO2 emissions in 2015. India, which emitted 2,274 million tons of CO2 in 2015, ranked third; while Brazil, which emitted 515 million tons of CO2 in 2015, ranked 12th. It should be stressed that these are the total emissions by country, not adjusted for population size.

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Figure 5: Top 15 Countries of CO2 Emissions in 2015 (in millions of tons)

Source: World Bank (undated), Global Carbon Atlas, available at: http://www.globalcarbonatlas.org/en/CO2-emissions.

Figure 6 depicts the increase in CO2 emissions per capita in Brazil and India from 1970-2011 (the last year the World Bank (2016) has data for this indicator for both countries). In 1970, an average person in Brazil emitted 0.98 tons of CO2, about three times as much as an average person in India (0.35 tons of CO2). Brazil’s CO2 per capita emission doubled between 1970 and 2011, while that of India increased more than five times. In other words, by 2011, India has nearly caught up with Brazil in terms of CO2 per capita. This makes sense as with socio-economic development, especially an increase in GDP per capita, it is normal to see an increase in CO2 emissions per capita. Yet, as already stated in the Introduction, most of Brazil’s emissions comes from deforestation and other land use, while the main source of India’s CO2 emissions is from burning fossil fuels or industrialization more generally.

Figure 6: CO2 Emissions (Metric ton per capita), 1970-2011

Source: Created by the author based on the World Bank (2016).

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IV. DiscussionAs the last section has shown, both India and Brazil have made tremendous progress over the past few decades. Economists predict similar progress in the future, but climate change may be standing in the way of such progress. The frequency and severity of natural disasters has increased tremendously and scientists believe that climate change is to blame.

In Brazil, where an average of 12 disasters took place per year in the first half of the 20 th century, the number of disasters reached an all-time high of 350 in 2004.0 Similarly, the high impact poverty scenario of climate change by Hallegatte et al. (2016) identifies India as one of the most vulnerable countries to climate change in the world. This assertion was supported by the World Development Report 2014, which stated that 57.3 percent of India’s rural population experienced a poverty shock from a natural disaster (drought or flood) within the past year.0 This section will address the two main types of natural disasters caused by climate change, floods and droughts, and will then examine how climate change has impacted agriculture and food production in Brazil and India.

IV.1. Flooding

India’s monsoon season has been greatly effected by inconstant floods. Three quarters of India’s rainfall occurs within a four-month span, causing almost every river to flood and disperse heavy discharge around the 34 million hectors of land liable to floods. While it is normal for India to experience seasonal floods in the form of monsoons, the floods have been anything but normal as of recently. Between 1900-1980, India experienced 52 medium and perilous floods, and from 1980-2013 India experienced 201 of these types of floods. The areas that are liable to flood and that are most affected by floods account for 55 percent of India’s population, 46 percent of land area, and the majority of impoverished individuals.0

The most recent floods of November and December 2015 killed over 500 people and displaced 1.8 million more.0 Hayden (2016) asserts that this type of flooding is expected to increase over time as it has been predicted that major monsoons, which have historically occurred every 100 years, are set to occur every 10 years by 2020. These torrential monsoons/rains have also increased the intensity and frequency of landslide disasters in the mountains, specifically in the Himalayas, which effects 15 percent of India’s land area and accounts for 30 percent of land-slide deaths worldwide.0

These floods also greatly affect coastal regions in India. Not only are low-lying coastal cities exposed to rising sea levels, but coastal cities like Mumbai are also very susceptible to cyclonic storms and flooding. In July of 2005, an unexpected flood killed 500 people and took a toll on low-income and impoverished peoples with their losses estimated at $245 million.0 In addition, tropical cyclones over the coastal regions of India have increased by 20 percent in the last two decades with five cyclones between 2011-2013 causing significant physical and economic damage to the cities of Odisha, Andhra Pradesh and Tamil Nadu.0 0 Cabral et al. (2009), p. 8. 0 World Bank (2013b). 0 The data in this paragraph is based on Mishra (2014), p. 5.0 Hayden (2016). 0 Mishra (2014), p. 5.0 Hallegatte et al. (2016), p. 106. 0 Mishra (2014), p. 5.

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Figure 7 shows the projected percentage change in precipitation during the wet season (June, July and August) in India by 2071–99 relative to 1951–80 for the case of further increases in global greenhouse gas emissions (the so-called RCP 8.5 scenario). The scale on right goes from plus 30 percent (the dark turquoise at the top) to minus 30 percent (the dark brown at the bottom). It clearly shows a significant increase in the projected precipitation during the wet season, which is very likely to increase flooding.

Figure 7: Projected Increase in Precipitation during the Wet Season

Source: Adams et al. (2013), Figure 5.6, bottom right chart, p. 115.

Brazil has experienced similar forms of flooding in which experts name climate change as the culprit. Since the 1950s, Brazil has experienced random and severe floods in the Amazon and coastal regions. Although there have been numerous floods within the past 30 years, which have caused significant damage, the most catastrophic natural disaster in Brazil’s history occurred in 2008. In Southern Brazil, heavy rainfall affected Santa Catarina State causing severe flooding and deadly mudslides, which affected 1.5 million people, resulted in 120 casualties and left 69,000 people homeless.0 Mudslides and flooding caused by the storms blocked almost all the highways in the region and cut off water and electricity to thousands of homes. Ultimately, there were 120 causalities and 69,000 individuals were left homeless.

Since the 2008 disaster, the Amazon and Northeast Brazil regions have experienced intense rainfall and floods, setting record high water-levels in Rio Negro. These floods killed 44 people and left 376,000 people homeless as of July 2009.0 Attributed to the changing air and water temperature and pressure from CO2 emissions, these floods have separated entire villages and communities, which have prevented over 400,000 children from going to school.0 Brazil’s deforestation has allowed floods to travel farther and reach villages and cities taking thousands of people from their homes.

0 Marengo (2009), p. 7. 0 Marengo (2009), p. 11.0 Marengo (2009), p. 11.

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IV.2. Droughts

Both countries have also experienced more severe droughts in recent years, which are considered to be a result of climate change. While floods and heavy rainfall have accompanied monsoon season in India in the past 50 years, monsoon rains have been lacking in 2015, causing more than 2,000 deaths in the southern states of Telangana and Andhra Pradesh.

In the northern states like Punjab and Haryana, fights erupted over ownership of river waters. Water availability in India’s 91 reservoirs was at its lowest in a decade, with stocks at 29 percent of their total storage capacity.0 The 2015 drought was combined with a heat wave that hit 118 degrees Fahrenheit in May 2015. Elderly people and homeless individuals were the most vulnerable to this drought and heat wave, with 900 of the victims from the city of Andhra Pradesh being elderly or low-income.0

In the subsequent year, the Indian government reported that 330 million people spread across 256 districts were affected by another severe drought in April 2016, with temperatures reaching 120 degrees Fahrenheit.0 These recent droughts were intensified by the melting and total disappearance of many glaciers in the Himalayas, which constitute a large majority of the India’s fresh water reserves.0

Figure 8: Projected Increase in Precipitation during the Dry Season

Source: Adams et al. (2013), Figure 5.6, center right chart, p. 115.

Figure 8 shows the projected percentage change in precipitation during the dry season (December, January, and February) in India by 2071–99 relative to 1951–80 for the case of further increases in global greenhouse gas emissions (the so-called RCP 8.5 scenario). It clearly shows a significant less precipitation during the dry season, which is very likely to increase droughts.

0 BBC (2016).0 Hallegatte et al. (2016), p. 119.0 BBC (2016).0 Mishra (2014), p. 13.

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Brazil has experienced a similar drought pattern in recent years. While, Brazil’s Amazon region has become accustomed to perilous and frequent droughts due to El Nino since the early 1900s, in 2005 the most intense drought of the past one-hundred years occurred in the southwest region of the amazon which has been attributed to anomalously warm conditions in the North Atlantic. The Amazon River and its tributaries reached historic low levels, suspending navigation and isolating hundreds of small villages that relied on the rivers.0 As the rainforest dried, serious wildfires broke out damaging hundreds of thousands of hectares of forests. This implies an about 300 percent increase in forest fires from the dry season of the previous year.0 The lack of water and the unsafe condition created by the smoke caused Brazil to declare a state of public calamity in September of 2005.

Unlike the droughts in the past, which have affected the Amazon region, the drought of 2014 hit the northeast region of Brazil, which contains a quarter of the country’s population. 700 cities declared a state of emergency, including the cities of Rio de Janeiro and Sao Paulo. The main water supply of Sao Paulo, which experienced the worst effects of the drought, ran on emergency reserves with a third of the water that it usually contained. The poor living in the slums of Sao Paulo, which constitute a large majority of the city’s population, experienced the drought worst, with numerous death and injuries occurring due to fights over water. Marengo, Torres and Alves (2017) predicted that there will be longer and hotter drought periods in the future.

IV.3. Impact of Climate Change on Agriculture and Food Production

Figure 9 depicts the share of agriculture to GDP for India and Brazil from 1970 to 2012. During this time span, agriculture has decreased by over half in both countries agriculture accounting for 5.2 percent of Brazil’s GDP and 17.0 percent of India’s as of 2015. India has historically and still does rely heavily on agriculture in comparison to Brazil.

Figure 9: Agriculture, Value Added (percent of GDP), 1970-2014

Source: Created by the author based on the World Bank (2016).

0 Marengo (2009), p. 10. 0 Marengo (2009), p. 10.

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Although the World Bank (2016) data shows that agriculture accounts currently for only about five percent of Brazil’s GDP, this data has limitations. The World Bank (2016) metadata clarifies that in developing countries a large share of agricultural output is either not exchanged (because it is consumed within the household) or not exchanged for money. Hence, this data may not account for individuals living below the poverty line in the northeast Amazon villages and the southwest rural slums that live off their land and survive through bartering. Furthermore, the share of agriculture does not account for farm inputs, such as farm machinery, seed supply, and workers.

In any case, Brazil’s GDP is – with 2.4 trillion U.S. dollars as of 2014 – the 8 th largest in the world.0 Therefore, Brazil’s agricultural sector amounts to more than 100 billion U.S. dollars a year. Cabral et al. (2009, p. 5) lists Brazil as one of the largest food producers in the world, with “agribusiness” accounting for 33 percent of Brazil’s GDP, 42 percent of the country’s exports, and employing 37 percent of its labor force.

Although the share of agriculture in GDP has decreased in Brazil and India, Figure 10 shows that food production has overall increased during the last four decades. The index, which is set to 100 for the food production during the years 2004-2006, shows very similar increases for Brazil and India, especially since the early 2000s. In 2012, Brazil had increased its food production by 36.7 percent compared to 2004-2006, while India increased its food production by 38.8 percent compared to 2004-2006. Given that the populations of both Brazil and India have also increased from 2004-2006 to 2012, the food production per capita has increased less, though it has still been positive.0

Figure 10: Food Production index (2004-2006 = 100), 1970-2012

Source: Created by the author based on the World Bank (2016).

0 World Bank (2016).0 Based on calculations by the author from population data provided by World Bank (2016), Brazil’s population increased by 7.4 percent from 2004-2006 to 2012, while India’s population increased by 10.4 percent during the same time period. In other words, per capita food production increased by 29.3 percent in Brazil and by 28.4 percent in India during 2004-2006 to 2012.

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While per capita food production has increased in both countries, Figure 11 shows that the percentage of arable land to total land has started to decrease in India since the mid-1980s. It will only be a matter of time that Brazil will also be faced with a decrease in arable land, especially as deforestation should end.

Figure 11: Arable Land in India and Brazil (percent of land area), 1970-2012

Source: Created by the author based on the World Bank (2016).

While the decrease in arable land in India may seem relatively small, it can have serious implications in the event of a natural catastrophe. Growing more food on less land means that a single natural disaster can destroy more food and therefore effect a larger amount of the population. And experts are aware of this growing issue. The World Bank (2013a) predicts a 2-degree increase in temperature by 2040, which, with 60 percent of cropland being rain-fed, would lead to a 12 percent decrease in crop production and 63 million people would no longer be able to meet their caloric demand. Additionally, childhood stunting is supposed to increase by 35 percent by 2050, resulting from a decrease in food production.0

Brazil does not seem to be as vulnerable to natural disasters as India. However, a report by the Wharton School of the University of Pennsylvania (2007) asserts that recent droughts across Brazil could reduce the grain production by half in the next century. The report predicts that if the temperature rises even a single degree, grain crops like coffee (which account for 5 percent of Brazil’s agriculture business) will see a 90 percent decline in production, costing the government over $600 million.0 Similarly, a separate UNICEF study found that climate change may cause agricultural losses of $7.4 billion in grain crops in Brazil, in 2020.0 And there is evidence that these changes in temperature and drought have already had a tremendous impact on Brazil’s economy. Soy production dropped by over 10 percent in 2006 and caused significant damage to the economy as soy is important to various food chains of domestic animals.0 V. Conclusion0 World Bank (2013a).0 Wharton School of the University of Pennsylvania (2007). 0 See Cabral et al. (2009).0 Wharton School of the University of Pennsylvania (2007.

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While Brazil and India have some of the fastest growing economies in the world, further progress is contingent on immediate mitigation. Climate change from greenhouse gas emissions is hindering significant progress in India and Brazil. Brazil and India have been greatly affected by drought and flooding over the past century. In both countries, droughts and floods have taken many lives and displaced many more. With many individuals in both countries being isolated by either floods or droughts, individuals no longer have access to food, water, health services, or education. While human development has increased significantly over the past 50 years, these natural disasters are and will continue to prevent further progress. With projected temperatures increases of 2-3 degrees by 2050, natural disasters will become more frequent and intense.

The World Bank’s high impact scenario from its 2016 report on climate change and poverty differentiates between a poverty scenario and a prosperity scenario. In the poverty scenario, climate change would push 50 million people into poverty in India. In the prosperity scenario, climate change would push two million of India’s people into poverty.0

Similarly, the impoverished peoples living in the low-lying slums of Brazil’s major cities are extremely vulnerable to extreme weather events. One major natural catastrophe, like the drought of 2014, could kill thousands of people and displace many more. Given that both India and Brazil still rely on agriculture, these frequent natural disasters will not only continue to hurt the agricultural sector but will also result in broader economic damages.

Rapid, inclusive, and climate-informed development is required to remove the long-term threat that climate change creates for poverty eradication. Steps have been taken in both countries to help solve this global issue such as Brazil’s Terra Legal program formal process of recognizing indigenous lands and granting land titles to about 300,000 smallholders conditional on compliance with the Brazilian Forest Code, or India’s ratification of the Paris agreement to limit the Earth’s warming to less than two degrees Celsius. While progress and acknowledgements are being made a predicted increase in the frequency and severity of natural disasters might make the path to further development longer and more difficult to persist.

ReferencesAdams, Sophie; Florent Baarsch; Alberte Bondeau; Dim Coumou; Reik Donner; Katja Frieler;

Bill Hare; Arathy Menon; Mahe Perette; Franziska Piontek; Kira Rehfeld; Alexander Robinson; Marcia Rocha; Joeri Rogelj; Jakob Runge; Michiel Schaeffer; Jacob Schewe; Carl-Friedrich Schleussner; Susanne Schwan; Olivia Serdeczny; Anastasia Svirejeva-Hopkins; Marion Vieweg; and Lila Warszawski (2013). Turn Down the Heat: Climate Extremes, Regional Impacts, and the Case for Resilience (Washington DC: The World Bank); available at: http://documents.worldbank.org/curated/en/975911468163736818/Turn-down-the-heat-climate-extremes-regional-impacts-and-the-case-for-resilience-full-report.

BBC (2016). India Drought: 330 Million People Affected. BBC News Story of April 20, 2016; available at: http://www.bbc.com/news/world-asia-india-36089377.

Cabral, Antonio Carlos; Fabio Atanasio de Morais; Ida Pietricovosky de Oliveira; and Roshni Basu (2009). Climate Change and Children in the Brazilian Amazon Region. Brasília, Brazil: UNICEF Brazil; available at:

0 Hallegatte et al. (2016), p. 33.

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https://www.unicef.org/sitan/files/SITAN_Climate_Change_and_Children_in_the_Brazilian_Amazon_Region.pdf.

Hallegatte, Stephane; Mook Bangalore; Laura Bonzanigo; Marianne Fay; Tamaro Kane; Ulf Narloch; Julie Rozenberg; David Treguer; and Adrien Vogt-Schilb (2016). Shock Waves: Managing the Impacts of Climate Change of Poverty (Washington, DC: The World Bank Group); available at: https://openknowledge.worldbank.org/bitstream/handle/10986/22787/9781464806735.pdf.

Hayden, Michael Edison (2016). How Climate Change is Hitting India (Queens, NY: National Geographic); available at: http://yearsoflivingdangerously.com/learn/news/how-climate-change-is-hitting-india/.

Marengo, Jose A. (2009). Climate Change, Extreme Weather and Weather Events in Brazil. In: Lilia Giannotti (ed.) Climate Change and Extreme Events in Brazil (Rio de Janeiro, Brazil: Fundação Brasileira para o Desenvolvimento Sustentável (FBDS), pp. 5-19.

Marengo, Jose A.; Roger Rodrigues Torres; and Lincoln Muniz Alves (2017). Drought in Northeast Brazil—Past, Present, and Future. Theoretical and Applied Climatology, Vol. 129, No. 3-4 (August), pp. 1189-1200.

Mishra, Ashutosh (2014). An Assessment of Climate Change-Natural Disaster Linkage in Indian Context. Geology and Geoscience, Vol. 26, No. 5 (July), pp. 1-15.

Rocha, Jan (2016). Climate Change Worsens NE Brazil’s Drought (Sao Paulo, Brazil: Climate News Network, October 2); available at: http://climatenewsnetwork.net/climate-change-worsens-ne-brazils-drought/.

Wharton School of the University of Pennsylvania (2007). Global Warming and its Impact on Brazilian Agriculture. Philadelphia, Pennsylvania: Wharton University of Pennsylvania, Knowledge@Wharton; available at: http://knowledge.wharton.upenn.edu/article/global-warming-and-its-impact-on-brazilian-agriculture/.

World Bank (2013a). Warming Climate in India to Pose Significant Risk to Agriculture, Water Resources, Health, says World Bank Report. Washington, DC: The World Bank, Press Release of June 19, 2013; available at: http://www.worldbank.org/en/news/press-release/2013/06/19/warming-climate-india-pose-significant-risk-agriculture-water-resources-health-says-world-bank-report.

World Bank (2013b). World Development Report 2014: Risk and Opportunity — Managing Risk for Development (Washington, DC: The World Bank); available at: http://siteresources.worldbank.org/EXTNWDR2013/Resources/8258024-1352909193861/8936935-1356011448215/8986901-1380046989056/WDR-2014_Complete_Report.pdf.

World Bank (2016). World Development Indicators / Global Development Finance Database (Washington, DC: The World Bank); as posted on the World Bank website: http://data.worldbank.org/data-catalog/ (downloaded on June 28, 2016).

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Global Majority E-Journal, Vol. 8, No. 2 (December 2017), pp. 95-108

Leave the Knot Untied: Education and Child Marriage in Bangladesh and Bolivia

Emily Lytle

Abstract

This article looks at education and child marriage in Bangladesh and Bolivia. More specifically, it examines how education can prevent girls from marrying when they are still children. While Bangladesh and Bolivia are both developing countries, they are very different in terms of income per capita, culture and the prevalence of child marriage. Therefore, this article will analyze the roots of these differences as well as some similar explanations for child marriage in Bangladesh and Bolivia. It will also look at what policies and initiatives have been successful to reduce child marriage in Bolivia and Bangladesh.

I. Introduction

Child marriage and lack of education are mutually detrimental. When girls marry before they turn 18-years-old, they are more likely to drop out of school, which then limits their career potential as well as their self-empowerment to make decisions and have a voice within family and society. Similarly, when girls do not go to school or drop out early, they are more prone to child marriage because they no longer have an escape from societal expectations to become a wife and mother. Schurmann (2009, p. 505) writes: “As an intervention, increasing access to secondary educations has great potential to counter social exclusion for girls whose traditional gender responsibilities have kept them from full economic and social participation.”

Both Bolivia and Bangladesh have made considerable progress in achieving the Millennium Development Goal (MDG) of promoting gender equality and empowering women. However, the fact that the majority of girls in Bangladesh and just under a fifth of girls in Bolivia are married as children shows that the goal has not been achieved completely. Thus, it is important to look at

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the factors that are driving child marriage—such as poverty, access to education, and cultural expectations—to uncover the differences between the degree of child marriage in the two countries.

To best examine the interrelationship between child marriage and education in Bolivia and Bangladesh, this article will first lay out the core differences between the countries in relation to GDP per capita, life expectancy at birth, and the percentages of people living below $1.90-a-day and $3.10-a-day. Beyond that primary background, this article mainly aims to compare access to education, cultural implications, and the level of poverty, ultimately arguing that those factors influence child marriage and social progress for girls in both Bolivia and Bangladesh.

II. Brief Literature ReviewWhile it has become widely recognized that empowering young girls through education can decrease birth rates, as well as the chances of maturing too fast through child marriage, the topic spans a wide variety of articles. Schurmann (2009) and Bates, Maselko and Schuler (2007) analyze the educational programs targeting girls in Bangladesh, while Reid and Miller (2012) take a similarly analytical approach in researching gender equity in Bolivian school systems. Zapata, Contreras and Kruger (2011) focus on examining Bolivia’s school systems when it comes to the work-school decision. Though focusing neither on Bangladesh nor Bolivia, UNICEF (2005) details the state of the world’s children, using many examples from Bangladesh and Bolivia.

● Schurmann (2009) reviews the Female Secondary School Stipend Project in Bangladesh, a program to increase the enrollment of girls in secondary schools. Schurmann digs deeper to explain how this project could delay marriage and childbearing. She also looks at the factors that contribute to the exclusion of girls from secondary schooling in Bangladesh, such as: harassment, poverty, and premature marriage and childbirth. Thus, she offers a perspective on the current and future progressive education policies affecting girls in Bangladesh, focusing on an analysis of the Female Secondary School Stipend Project.

● Reid and Miller (2012) examine the Bolivian education system, especially in relation to recent national educational reform law that mandated gender equity. They describe Bolivian culture as a basis to the institutional and structural limitations upon Bolivian girls in school and in other aspects of their lives. Through in-depth interviews and observation, the article examines the effectiveness of reforming gender equity in Bolivian schools. Reid and Miller offer information about progressive leanings in Bolivian education through a more sociological lens.

● Zapata, Contreras and Kruger (2011) analyze the effect of the work-school choice in Bolivia, in which children and their families are forced to choose between going to

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school or working to support their families’ incomes. The article concludes that girls, especially indigenous girls, are most vulnerable to being excluded. The authors also recognize the greater impact of not educating girls, noting that education can empower girls and lower birth rates. The article emphasizes how cultural distinctions influence the degree to which girls are educated in Bolivia.

● Bates, Maselko and Schuler (2007) focuses on women in Bangladesh and tests the hypothesis that daughters of women with more education marry later and that daughters-in-law of more educated women initiate childbearing at a slower rate. They support this hypothesis by explaining that the traditional setting of many communities in rural Bangladesh requires that parents decide the age of marriage, with influence from mothers-in-law. Their study analyzes data from a 2002 survey in six villages in rural Bangladesh.

● UNICEF (2005) provides an extensive report on the state of the world’s children, illustrating the difference between children being excluded and children being invisible. Exclusion refers to issues such as not receiving an education, health services and food, while invisibility refers to children disappearing due to premature entry into adult roles, such as marriage. While being excluded and being invisible are not necessarily mutually exclusive, they are conceptually different problems and hence, policy interventions to address exclusion and invisibility have a different focus.

III. Empirical Background

Despite being a resource-rich country—gas makes up 50 percent of exports—Bolivia is still considered one of the least-developed countries in the world due to “state-oriented policies that deter investment and growth,” according to the World Factbook.0 In 1982, Bolivia established democratic civilian rule, facing issues such as poverty, social unrest, illegal drug production, as well as a disastrous economic crisis. Into the 1990s, economic reforms brought about increased private investment, economic growth, and reduced poverty rates. However, the few years before the current socialist president Evo Morales was elected (on December 18, 2005) were marked by instability in all senses: politics, race, and violence. When the global recession hit in 2009, Bolivia maintained the highest growth rate in South America and has averaged 5.3 percent growth each year after that, especially growing rapidly in between 2010 and 2013 when commodity prices were high. However, the subsequent decline in oil prices caused Bolivian growth rates and revenue to decline. One of the biggest challenges facing Bolivia and its economy, on top of continuing social unrest, is a lack of foreign investment.0

0 U.S. Central Intelligence Agency (undated), The World Factbook, Bolivia; Section on Economy.0 Most of this paragraph is based on information provided by the U.S. Central Intelligence Agency’s World Factbook for Bolivia.

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Similar to Bolivia’s large share of gas exports, more than 80 percent of Bangladesh’s exports are ready-made garments (RMG). The RMG sector continues to grow despite fatal factory accidents, strikes, and political unrest. After becoming independent in 1971, the country faced series of military coups, and a constant struggle for power between the Bangladesh Nationalist Party (BNP) and the Awami League (AL). The country returned to democratic rule in 2008, when Prime Minister Sheikh Hasina was elected. The period that followed buckled under the global recession, poor infrastructure, corruption, insufficient power supplies, and slow implementation of economic reforms. Today, more than half of the GDP of Bangladesh comes from the services sector, but most Bangladeshis still work in agriculture, specifically on rice fields. The economy continues to grow at an average of 6 percent each year due to the RMG industry and remittances from Bangladeshis who work overseas. 0

The influence of Bolivia’s rich resources and economic reform in the 1990s can be seen in Figure 1. The figure also shows the considerable difference in the level of GDP per capita between Bangladesh and Bolivia. In 1990, Bangladesh had a GDP per capita (based on purchasing power parity (PPP)) of $1,290, while that of Bolivia was with $3,707 about three times that of Bangladesh. In 2014, Bangladesh’s GDP per capita had reached $2,979, while that of Bolivia reached $ 6,325, which is only slightly more than twice that of Bangladesh. In other words, while the nominal gap between Bangladesh and Bolivia has increased, in relative terms, Bangladesh’s GDP per capita grew faster during the last 25 years than that of Bolivia.

Figure 1: GDP per capita (constant 2011 international $), 1990-2014

Source: Created by author based on World Bank (2016).

0 This paragraph is based mostly on information provided by the U.S. Central Intelligence Agency’s World Factbook for Bangladesh.

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While Bolivia is much richer than Bangladesh, Bangladesh has a higher life expectancy than Bolivia, though the gap between the two countries is relatively small. As Figure 2 shows, both countries have made considerable progress over the last 45 years. Bangladesh has increased its life expectancy by 24.5 years, while Bolivia’s life expectancy has increased by 23.1 years.

Figure 2: Life Expectancy at Birth (Years)

Source: Created by author based on World Bank (2016).

Consistent with Bangladesh’s much lower GDP per capita, Figures 3 and 4 show that poverty, measured at the international poverty lines of $1.90-a-day and $3.10-a-day, is far more common in Bangladesh than in Bolivia. Figures 3 and 4 also show that Bangladesh has made considerable progress with reducing poverty, while the level of poverty in Bolivia has been volatile during 1990 to 2013. The figures show how Bolivia’s poverty overall increased in the early 2000s before decreasing again in 2006, which coincides with a period marked by instability and violence.

Figure 3: Percent of Population below $1.90 a day (2011 PPP)

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Source: Created by author based on World Bank (2016).

Figure 4: Percent of Population living below $3.10 a day (2011 PPP)

Source: Created by author based on World Bank (2016).

IV. DiscussionThe level of poverty can be an indication that children prematurely enter into adult roles, such as child marriage. According to UNICEF (2005), poverty and inequality frequently cause children to be excluded and become invisible. Invisibility refers to children not getting the attention they

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need because they have taken on adult roles. For examples, many girls are married and have children, hence, they are considered to be mothers, no longer children themselves.

Although influencing factors, poverty and inequality cannot justify or explain child marriage. Instead, one must focus on each country and examine the ways that the country’s policies and culture has perpetuated child marriage. We will also review how both countries have made considerable progress in gender equality. To accomplish this, the discussion section will compare education’s role in delaying marriage; the influence of cultures related to female empowerment like purdah and marianismo; and the direct implications of poverty in delaying marriages, often due to a lack of investment in education.

Each step of the discussion will show the interconnectedness of education and child marriage, tied by the strings of government shortcomings, access to educational and non-national resources, cultural ideologies, and financial burdens. The first subsection provides some information on legal age for marriage, the evolution of adolescent fertility, and teenage pregnancies. The second subsection focuses on child marriage and education. The third subsection focuses on cultural factors and female empowerment, while the fourth subsection examines the influence of poverty on education and child marriage.

IV.1. Legal Age for Marriage and Adolescent Fertility

Although marriage is illegal until a girl turns 18 years-old in Bangladesh, inconsistent birth registration and a lack of enforcement contribute to a culture in which over half of Bangladeshi women are married before they reach age 18. As shown in Table 9 of UNICEF (2014, p. 84), between 2005 and 2013, 29 percent of Bangladeshi girls were married by age 15, and 65 percent were married before age 18.

In the case of Bolivia, three percent of Bolivia’s girls were married by age 15 between 2005 and 2013, and 22 percent were married before they were 18 years old. In Bolivia, the legal age to get married is 21 years of age. However, most men are allowed to get married at 16 years and woman as early as 14 years, if they have parental consent.

Figure 5 shows the adolescent fertility rates (defined as births per 1,000 women ages 15-19) for Bangladesh and Bolivia from 1970-2014. It shows that Bangladesh had a much higher adolescent fertility rate than Bolivia in the 1070s, but it decreased rapidly since the early 1980s, and nearly reached Bolivia’s adolescent fertility rates by 2014. In Bolivia, there has been no progress with reducing adolescent fertility from 1970 to 1998. Only from 1998 onwards has Bolivia been able to moderately reduce its adolescent fertility rate. As of 2014, the adolescent fertility rate was 83.5 births per 1,000 women ages 15-19 in Bangladesh, while it was 71.1 births per 1,000 women ages 15-19 in Bolivia.

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Figure 5: Adolescent Fertility Rates in Bangladesh and Bolivia, 1970-2014

Source: Created by author based on World Bank (2016).

Despite that Bangladesh’s adolescent fertility rates are approaching those of Bolivia, Figure 6 shows that there is still a big difference in terms of the percent of teenage pregnancies in the two countries. Although Bangladesh has a better depreciating rate than Bolivia in recent years, Bolivia’s overall percentage of girls who are pregnant in their teenage years is much lower than in Bangladesh.

Figure 6: Teenage Pregnancies

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Source: Created by author based on World Bank (2016).

IV.3. Education Delays Marriage and Childbearing

When looking at literature on the topic, the correlation between marriage and childbearing is almost taken for granted. Due to the cultural stigma around marriage and childbearing, newly-wed females tend to have a child very soon after marrying because religion and community standards strongly prohibit extramarital relations. There is also the cultural idea that remains: the primary purpose of women should be to care for their children. Reid (2012) recognizes this trend of domestic expectations for women in Bolivia, too. Furthermore, Bates, Maselko and Schuler (2007) raise that mothers and mothers-in-law have a large influence over when their children have children of their own.

Schurmann (2009) describes the ways in which Bangladesh has attempted to combat high rates of child marriage and adolescent fertility. She reviews the Female Secondary School Stipend Project (FSP), which was launched in 1994 with the primary aim of delaying marriage and decreasing fertility. The program attempts to accomplish this by paying tuition-fees and providing monthly stipends for unmarried rural girls until the tenth grade. One of the requirements of the FSP is to stay unmarried. Hence, more girls are expected to wait until they finish school to marry.

Figure 7 shows the overall percentages of female students from 1970 to 2013 in Bangladesh and Bolivia. While Bangladesh has not made any progress in the 1970s, the percentage of secondary students who are female have sharply increased from 1981 until 2002. During 2002-2013, more than half of the secondary students were actually female; that is, the number of female secondary students is exceeding that of the number of male secondary students in Bangladesh. With about 40 percent of female secondary students in the 1970s, Bolivia started with much higher percentages of female secondary students than Bangladesh, but has made relatively little progress over time. Nevertheless, Bolivia nearly reached parity in male and female secondary

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students in the last few years. Reid (2012) explains that Bolivia has made significant movements toward gender equality with the passing of The Bolivian Educational Reform and localized efforts to create gender-sensitive environments.

Figure 7: Percentage of Secondary Students Who Are Female

Source: Created by author based on World Bank (2016).

Combining the information provided in Figures 5 and 7, it seems clear that education has contributed to reducing adolescent fertility rates in both, Bangladesh and Bolivia. It is also clear that Bangladesh’s Female Secondary School Stipend Project (FSP) has contributed to the high female secondary enrollments. However, the decline in Bangladesh’s adolescent fertility rates started at least a decade before the implementation of the FSP.

Schurmann (2009) reports that continuing girls’ education in Bangladesh is more frequently viewed as marriage capital, rather than human capital. In other words, many families support increasing a girl’s education not to empower her to enter the workforce or develop skills that will help her later in life, but instead to improve her likeliness of marrying a man of high stature. A big part of these cultural thoughts in Bangladesh emerges from the role of poverty in identifying gender roles and expectations for young women, which will be discussed more below.

IV.3. Cultural Factors and Female Empowerment

Culture plays a substantial role keeping girls out of schools and increasing their likeliness of succumbing to child marriage in both Bangladesh and Bolivia. Schurmann (2009) and Reid (2012) identify ways that young women are limited by gendered expectations, respectively in Bangladesh and Bolivia.

In Bangladesh, women are “sequestered to the domestic sphere” through traditional practice of purdah, in which women are secluded and completely covered by clothing when around men

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who are not blood-related (Schurmann). Even though that the legal age for getting married in Bangladesh is currently 18 years, Schurmann (2009) explains that girls are traditionally considered eligible for marriage as soon as they start menstruation.

While Bolivia’s numbers for child marriages are considerably lower than those for Bangladesh, child marriage remains a cultural problem, which Reid (2012) refers to as marianismo. While machismo (a strong, almost aggressive, male dominance) prevails as a way of thinking in much of Latin America, marianismo is another way of identifying the role of a woman. As Reid (2012) describes it, being a woman means being a mother. For example, Reid uses a specific example in which the girls that attend school watch their teacher juggle a child while she teaches. These girls learn from a young age that their primary role should be a caretaker.

Girls Not Brides0 explains that there is a proverb in Bangladesh “Khuritay Buri”, which translates to “Bengali girls become old when they turn 20.” Therefore, families believe they must marry their children off early because their culture supports that girls as young as 15-years-old are ready for marriage. The example of Rubi, a 19-year-old Bangladesh girl featured in a post on Girls Not Bride’s website, illustrates the pressure parents put on their daughters to get married.

In any case, Bangladesh’s sharp decline in adolescent fertility has been influenced by a slight shift of ideologies concerning women and marriage, as well as the above reported gender-equality within Bangladeshi schools. Girls now also have more access to resources from organizations like Girls Not Brides to fight the pressures of marrying early. Girls Not Brides has worked to be the voice of young women in Bangladesh, especially as the Child Marriage Restraint Act of 2017 passed in February 2017. This law would uphold that a girl must be 18-years-old to marry; however, Girls Not Brides and others have argued against the act because it allows exceptions to this rule in special cases, which are not defined. Girls Not Brides and others have argued that evidence from global experience has shown that requiring parental and court consent does not protect girls from child marriage. Girls Not Brides Bangladesh expects that these requirements could be widely abused and effectively eliminate a minimum age of marriage in Bangladesh.

Figure 8 demonstrates that women have been given more opportunities in both countries to become involved in government. With exception of 1990, Bolivia’s women always had a higher representation in national parliament than Bangladeshi women, though the difference was sometimes marginal. But in 2014 and 2015, Bolivia has visibly surpassed not only Bangladesh in the percentage of seats held by women in national parliament, but Bolivia’s women have also surpassed Bolivia’s men in parliament. The explanation behind this sharp increase is not clear. The cultural traditions of machismo and marianismo perpetuate ideas that limit a women’s agency in daily life; however, something must have changed in the minds of many Bolivians that women leadership would spike to such an extent as shown in Figure 8.

0 Girls Not Brides is a global partnership of more than 800 civil society organizations committed to ending child marriage and enabling girls to fulfil their potential; Girls Not Brides was initiated in September 2011 by The Elders, a group of independent global leaders working together for peace and human rights. For further information, see: https://www.girlsnotbrides.org/.

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Though less steady, women have also increased their representation in Bangladesh’s parliament. In 1990 and from 1997-2000, Bangladeshi women had nearly ten percent of the parliamentary seats. It then declined to below five percent from 2002 to 2004, which is quite significant, though an explanation for such a sharp decrease is not clear. Fortunately, despite some volatility, the representation of Bangladeshi women in parliament increased again in 2005, and during 2009-2015, reached or nearly reached 20 percent.

Figure 8: Parliament Seats Held by Women

Source: Created by author based on World Bank (2016).

While administrative policy or other legal decisions could play a role, there must have been a significant cultural shift towards women parliamentarians in both countries. In addition to women in government, Bates, Maselko and Schuler (2007) measure a women’s empowerment by the agency she has in making small or large purchases, her involvement in major decisions, and her freedom from family domination.

IV.4. Influence of Poverty on Education and Child Marriage

In addition to culture-centered female empowerment, poverty acts as a significant driver of child marriage. Concerning Bangladesh, Schurmann (2009) recognizes that younger girls require a lower dowry, so marrying their child off as soon as possible may seem like the best option for a low-income family. Therefore, the decision to get married is largely driven by the needs of the

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family. Similarly, Bates, Maselko and Schuler (2007) state that Bangladeshi parents often make the decisions about marriage and childbearing.

Schurmann (2009) also explains that many families in Bangladesh view education in terms of profit. When it comes to educating young girls, many poor families conclude that, even if the female child can use the advantages of her education to attain a good job and earn a significant sum of money, that money would just transfer to her husband’s family after marriage. Because the parents of girls do not view education as economical, these girls have even less opportunity of being enrolled in school.

Due to the parents’ cultural perspective on marriage as a way out of poverty, many do not understand the immense benefits of delaying marriage and prolonging education. According to Psacharopoulos and Patrinos (2002), girls who attend an extra year of primary school boost their future earnings by 15 percent, a percentage that increases with the more time spent in school. However, women succeeding in the workplace is not common in Bangladesh, especially in the rural regions, so these statistics do not offer much realistic hope for many poor families.

Bolivia, on the other hand, has an income per capita that is more than double that of Bangladesh, and a lot less Bolivians live below $1.90 or $3.10 a day, as the Empirical Background section demonstrates. That difference in income and poverty levels helps explain why only 22 percent of Bolivian girls are married by their eighteenth birthday, while 52 percent of 18-year-olds are married in Bangladesh.

Further supporting the correlation between poverty and child marriage, there is a strong correlation between income per capita of a country and the age at which females get married for the first time. So, countries with lower incomes per capita, like Bangladesh, will have more first marriages at a young age in comparison with countries who have higher incomes. In fact, Girls Not Brides reports that girls from poor families are more than three times as likely to marry before 18, compared with girls from wealthier families.0

Figure 9 provides a map that visualizes the prevalence of child marriage across the world, while Figure 10 shows GDP per capita around the globe. Comparing Figure 9 with Figure 10 shows that child marriage is correlated with the overall income per capita. Due to many intertwining factors, such as education and other policy reforms, the correlation between GDP per capita and child marriage is not perfect. However, it is notable that the countries marked by the three darkest blue shades in Figure 10 (which are countries with GDP per capita above $17,000) have either no data available on child marriage or child marriage is not widely practiced.

Figure 9: Percentage of women aged 20–24, who were married before age 18

0 See https://www.girlsnotbrides.org/why-does-it-happen/.

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Source: UNICEF global databases, 2007, based on MICS, DHS and other national surveys, 1987–2006; as posted at https://www.unicef.org/progressforchildren/2007n6/index_41848.htm;

arrows identifying Bangladesh and Bolivia added by author.

Figure 10: GDP per capita Across the World (PPP, constant 2011 international $)

Source: World Bank (2016); arrows identifying Bangladesh and Bolivia added by author.

V. Conclusion

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In Bangladesh, 52 percent of girls get married by the age of 18. In Bolivia, 18 percent of girls get married by the age of 18. At the basis of this article is the question: why does the current percent of child marriages in Bangladesh surpass the percent of child marriages in Bolivia by such a large margin?

A simple answer to this question does not readily appear as too many factors influence the age at which a girl gets married. Based on the data provided in the Empirical Background section, it is clear that Bangladesh has a much lower GDP per capita than Bolivia, and poverty is far more common in Bangladesh than in Bolivia. On the other hand, life expectancy is actually higher in Bangladesh than in Bolivia. In Figure 5, we then showed that Bangladesh and Bolivia seem to be almost at par when it comes to adolescent fertility rates. Yet, Figure 6 has shown the teenage pregnancy is about twice in Bangladesh than in Bolivia. On the other hand, Figure 7 showed that Bangladesh has recently surpassed Bolivia in the percentage of female students in secondary education. Yet, Figure 8 has shown that the presentation of women is now much higher in Bolivia than in Bangladesh.

Beyond the numbers, many differences arise regarding cultural norms. Behind the looming issue of child marriage, for both countries, is a social infrastructure that cannot be swayed by government interference. The traditions of purdah and marianismo, in Bangladesh and Bolivia respectively, and families’ ideas about investing in their female children, overpower the child’s wish to continue her education and delay marriage. What separates Bangladesh and Bolivia then, is their unique culture.

To be clear, this article is not calling for cultural assimilation or termination. Instead, it is important that policy-makers and outside interventionist organizations, such as Girls Not Brides, understand the implications of child marriage. Bangladesh remains a much poorer country than Bolivia, and without significantly lowering the number of people living on a mere $3.10 a day, the effects of poverty will continue to influence child marriage and perpetuate a culture of female submission. In any case, in order to eliminate child marriages, Bangladesh and Bolivia must continue to balance economic progression with increased human development and female empowerment.

References

Asadullah, M. Niaz and Zaki Wahhaj (2017). Bangladesh’s New Child Marriage Law Swings in the Wrong Direction. The Conversation, University of Kent (March 8, 2017); available at: www.theconversation.com/bangladeshs-new-child-marriage-law-swings-in-the-wrong-direction-72282.

Bates, Lisa M.; Joanna Maselko; and Sidney Ruth Schuler (2007). Women’s Education and the Timing of Marriage and Childbearing in the Next Generation: Evidence from Rural Bangladesh. Studies in Family Planning, Vol. 38, No. 2 (June), pp. 101-112.

Reid, Julie A. and Amy Chasteen Miller (2014). ‘We understand better because we have been

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mothers’: teaching, maternalism, and gender equality in Bolivian education. Gender and Education, Vol. 26, No. 6, pp. 688-704.

Schurmann, Anna T. (2009). Review of the Bangladesh Female Secondary School Stipend Project Using a Social Exclusion Framework. Journal of Health, Population and Nutrition, Vol. 27, No. 4 (August), pp. 505-517.

United States, Central Intelligence Agency (CIA) (undated). The World Factbook: Bangladesh. Internet Resource of the U.S. Central Intelligence Agency; available at: available at: https://www.cia.gov/library/publications/the-world-factbook/geos/bg.html.

United States, Central Intelligence Agency (CIA) (undated). The World Factbook: Bolivia. Internet Resource of the U.S. Central Intelligence Agency; available at: available at: https://www.cia.gov/library/publications/the-world-factbook/geos/bl.html.

United Nations Children’s Fund (UNICEF) (2005). The State of the World’s Children 2006: Excluded and Invisible (New York, NY: United Nations Children’s Fund (UNICEF)); available at: http://www.unicef.org/sowc06/pdfs/sowc06_fullreport.pdf.

United Nations Children’s Fund (UNICEF) (2014). The State of the World’s Children 2015: Reimagine the Future: Innovation for Every Child , Executive Summary (New York, NY: United Nations Children’s Fund (UNICEF); available at: https://www.unicef.org/publications/files/SOWC_2015_Summary_and_Tables.pdf.

World Bank (2016). World Development Indicators / Global Development Finance database (Washington, DC: The World Bank); as posted on the World Bank website: http://data.worldbank.org/data-catalog/ (downloaded on June 28, 2016).

Zapata, Daniela; Dante Contreras; and Diana Kruger (2011). Child Labor and Schooling in Bolivia: Who’s Falling Behind? The Role of Domestic Work, Gender, and Ethnicity. World Development, Vol. 39, No. 4 (April), pp. 588-599.

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Global Majority E-Journal, Vol. 8, No. 2 (December 2017), pp. 109-120

Effects of Climate Change on Agriculture in Guatemala and Honduras

Karissa Waddick

AbstractThis article looks at the impact of climate change in Guatemala and Honduras. Both countries rely on agriculture as a main source of income, hence they are highly vulnerable to climate change. Indeed, both countries have already been severely affected by past weather-related disasters that were induced by climate change. Guatemala and Honduras have started to adapt to climate change by farming more efficiently and conserving water. However, much more needs to be done to cope with long-term increase in temperatures and the increasingly volatile environment, which could strip away the agricultural livelihoods of the still many poor people in both countries.

I. Introduction

Though climate change may seem like a far off issue to some, it is already negatively affecting regions, like Central America. Since the 1990s, countries in Central America including Guatemala and Honduras have experienced an increasing number of natural disasters, increasing temperatures and a decreasing amount of rainfall. These countries have also been bombarded with an increasing amount of flooding and high winds because of their locations between the Atlantic and Pacific Oceans. These weather events, thought to be caused by climate change, are negatively affecting the agricultural production in Central America.

This is an especially big problem for countries like Guatemala and Honduras because a large portion of their gross domestic product (GDP) is from agriculture. Both countries produce large amounts of coffee, corn and beans. Like many countries in the Global Majority, the poor in the rural regions of these countries depend on the agricultural production of these products for their livelihoods. However, the increasing number of storms and changing temperatures/rainfall have forced many of the rural farmers to change techniques, move locations or abandon farming all together.

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This article discusses the ways climate change has affected both Guatemala and Honduras. It compares the agricultural production in each country including what crops they produce, who produces it and how they produce it. The article then looks at the effects of climate change on the production and specifically, the ways it has decreased the production. Lastly, it discusses how both Guatemala and Honduras are adapting their production techniques to combat the effects of climate change.

II. Literature ReviewThere is a lot of literature about the effects of climate change on agriculture in Honduras and Guatemala. Much of the literature discusses how the location of the two countries and their topographies have exacerbated the effects of climate change. Scholars have studied how major weather events like Hurricane Mitch,0 along with precipitation and temperature change, have affected agriculture and how or if these countries have adapted. Most of the literature also discuss ways each country is trying to combat the negative impacts of climate change.

Díaz-Ambrona et al. (2012) describe how an increase in temperatures and a decrease in precipitation will lead to a decrease in the production of both corn and beans. Though both of these crops will be affected, the article suggests that the production of corn will be most affected. Crop yields will be most affected in low land areas, where yields could be reduced by as much as 22 percent. Yields may increase at higher elevations where the temperature will be cooler. However, available agricultural land in the mountain regions is scarce. Because of these factors, the article argues that there is high uncertainty about the future of maize and corn yields. The article provides suggestions to reduce the effect of climate change.

McSweeney and Coomes (2011) discuss the ways Hurricane Mitch provided rural communities in Honduras with a window of opportunity. While climate-related disasters like Hurricane Mitch can leave developing countries vulnerable, McSweeney and Coomes argue that in this case, the hurricane allowed the Tawahka community to re-build and better prepare itself for future disasters. The article says that the hurricane forced the community to replant crops and rebuild housing away from low-land flood areas. Land was also reallocated in a way that benefited the rural poor. This region has is now less affected by similar future climate-related events.

Lloyd (2015) summarized the main reasons for why Honduras is most vulnerable to the effects of climate change, focusing on the economic impact of climate change on Honduras. She points out that 60 percent of Honduras’s GDP is agricultural, with coffee, corn and beans being the main crops. A decrease in agricultural production due to climate change would have a huge economic impact on the country, especially in rural regions where the poor depend on agriculture. To combat the effect of climate change, Lloyd suggests encouraging environmentally friendly farming, supporting diversification and educating local populations about climate change.

0 Hurricane Mitch, which hit Central America in late October and early November 1998, was the second-deadliest Atlantic hurricane on record, killing at least 19,325 people.

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In a news report for The Guardian, Felicity Lawrence (2017) summarizes how climate change imperils Guatemala’s food security. Because Guatemala lies in between the Atlantic and Pacific Ocean, it is hardest hit by tropical storms. Further, increasing temperatures and changing rain patterns have decreased crop yields for smallholder farmers. Farmers are seeking other crops to produce and other ways to make a living but some of these tactics are exacerbating the effects of climate change. For example, people have begun cutting down forests to make room for new farmland. This is increasing the emission of carbon dioxide and making the problem worse.

A contribution to the Climate Change Adaptation Portal of the United Nations Development Program (UNDP) (2015) discusses ways Guatemala can incorporate climate change risk management strategies into their agricultural activities. It describes four main projects as part of the community based adaptation program. These projects include a soil recovery and conservation, reforestation and farming techniques. The goal of these projects is to decrease the vulnerability of Western Guatemala to future hurricanes, earthquakes and droughts.

III. Empirical Background0

Guatemala and Honduras are both lower-middle income countries in Central America. Within Central America, Guatemala is with about 16 million people the most populous country, while Honduras is with about 9 million people the second most populous country. Guatemala has the largest economy in Central America, with its top exports being edible fruits, nuts, coffee, tea and precious stones/metals. Despite being the second most populous country in Central America, the Honduran economy is the fourth largest as the less populous but richer Costa Rica and El Salvador have a larger GDP than Honduras.

Like many countries in Latin America, Guatemala and Honduras struggle with high income inequality, corruption and political instability. After a 36 year-long civil war ended in 1996, Guatemala adopted a representative government. Honduras had various military coups throughout its past, the latest in 2009. Since the 2010 inauguration of President Lobo, political stability has been partly restored, though the controversial re-election of President Juan Orlando Hernandez on November 26, 2017 has increased uncertainty and polarization in Honduran politics.

Figure 1: PPP-adjusted GDP per capita, 1990-2014

0 Most of the information provided in this section is based on World Bank (2016, 2017a, and 2017b).

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Source: Created by author based on World Bank (2016).

Figure 1 shows that Guatemala has a much higher GDP per capita (adjusted for purchasing power parity, PPP) than Honduras. Guatemala’s GDP per capita increased from $5,159 in 1990 to 7,112 in 2014 (which implies a cumulative increase of 37.8 percent over 24 years), while Honduras increased its GDP per capita during the same period from $3,205 to $4,683 (which implies a cumulative increase of 46.1 percent).

Figure 2 compares the life expectancy at birth of Guatemala and Honduras. While the differences between the two countries were small in the early 1970s, Guatemala fell behind subsequently and was only able to catch up partly in the last decade. As of 2015, Guatemala’s life expectancy was 72.0 years, while that of Honduras was 73.3 years. It should be pointed out that even though Guatemala has a higher GDP per capita than Honduras, in terms of life expectancy, Honduras is doing better than Guatemala.

Figure 2: Life expectancy at birth, total (years), 1990-2015

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Source: Created by author based on World Bank (2016).

Though data for literacy is available for only a few years, Figure 3 shows that Guatemala also has a lower literacy rate than Honduras. In 2001, Honduras had a literacy rate of 80.0 percent, while Guatemala’s was 69.1 percent in 2002. For 2013, which is last year such data was available for both countries, Guatemala had an adult literacy rate of 77.0 percent, while that of Honduras was 85.5 percent.

Figure 3: Adult literacy rate (percent), all available years

Source: Created by author based on World Bank (2016).

IV. Discussion

IV.1. Evidence of Climate Change

Both Honduras and Guatemala are listed among the top nations affected by climate change. Based on the long-term climate risk index (CRI), Honduras has been the most affected country from 1996 to 2015, while Guatemala has been the 9th most affected country.0

One of the main reasons for these countries’ high vulnerability is their location. Both countries lie on a thin strip of land between the Atlantic and Pacific Oceans. Guatemala lies mainly on the Pacific Ocean where Honduras lies mainly on the Atlantic Ocean. Neither country has a buffer from the harsh weather events that the tropical oceans cause. These weather events include hurricanes, flooding as well as droughts. According to Baptiste (2014), a reporter for the Latin Correspondent, Honduras saw 60 extreme weather events and averaged 329 climate change-related deaths per year between 1996 and 2011. Both countries are also threatened by frequent volcanic eruptions and earthquakes.

0 As stated by Kreft et al. (2017, p. 3): “The Climate Risk Index indicates a level of exposure and vulnerability to extreme events, which countries should understand as warnings in order to be prepared for more frequent and/or more severe events in the future.”

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Climate researchers have concluded that the increasing amount and strength of storms, floods and droughts are largely due to a changing and more volatile climate. In addition to many deaths, the recent storms have also caused a great deal of destruction to the economies of both countries. Jose Luis Rivera, the coordinator of Guatemala’s Climate Change Unit, said that natural disasters have had serious consequences for the country: loss of infrastructure due to landslides and floods, loss of harvest causing food shortages and loss of natural space.0 When these storms flood the shores, they destroy the crops and farms that were once there. The people that worked on those farms are forced to move further inland.

Guatemala and Honduras are also extremely affected by climate change because it has changed the duration of their seasons. Normally, both countries have a rainy season that lasts from May to October and a dry season that lasts from November to April. However, in recent years the rainy season has not started until June. Because of the shift in seasons, a greater amount of rain falls in a shorter period of time. A document of the Adaptation Fund (2015) states that in Honduras this could be resulting in a greater frequency or intensity of both floods and droughts. These floods and droughts can ruin crops and destroy land. The changing seasons also affect the way the different crops grow. The next section will explore how the changing seasons and extreme weather events affect agriculture in each country.

IV.2. Climate Change Affecting Agriculture

Though Guatemala and Honduras rely both on agriculture, climate change has affected their agricultural outputs differently. Guatemala’s main agricultural exports are coffee, bananas, sugar and cardamom. Coffee and bananas are also the two biggest agricultural exports from Honduras. Eakin et al. (2006) examine the recent coffee crisis caused by climate change in Mexico, Guatemala and Honduras. Figure 4 shows the value added by agriculture as percent of GDP for all available years. While the data availability is too limited to say much about Guatemala, the high volatility for Honduras’s agricultural output is an indication of some problems. The downward secular trend of the share of agriculture is not necessarily a problem, as growing country is typically undergoing a structural transformation away from agriculture and towards industry and services, the very sharp declines of some years are likely reflecting shocks to the agricultural sector.

Figure 4: Agriculture, value added (percent of GDP)

0 As reported by Bevan (2013).

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Source: Created by author based on World Bank (2016).

To better assess such agricultural shocks, Figure 5 provides the data for the food production index, for which there is data for both countries from 1970 to 2015. The food production index includes food products that are edible. It excludes coffee and tea because these products are not edible in their natural form.

Figure 5: Food Production Index, 1970-2014

Source: Created by author based on World Bank (2016).

Excluding some minor volatility, Guatemala’s food production index has been steadily increasing since 1970. Though also trending upwards, Honduras’s food production index shows three clear declines: one in the early 1970s, one in the late 1990s, and one from 2008 to 2009.

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The very sharp decline from 1998 to 1999 has been due to Hurricane Mitch, which is actually also clearly visible in Figure 4 above. The overall increase in food production in Guatemala and Honduras can be linked to modernizations in the agricultural sector, especially the adoption of new technologies.

Climate change has decreased the amount of available agricultural land in both Honduras and Guatemala. Large storms like Hurricane Mitch flood neighborhoods by the shores, destroy homes, and ruin crops. An article written by Kendra McSweeney and Oliver Coomes (2011) discusses the devastating effects of Hurricane Mitch on one region of Honduras. They assert that some whole communities had to move further inland because of the destruction Hurricane Mitch caused. Focusing on the impact of Hurricane Mitch on the largest Tawahka community of Krausirpi (a village on Honduras’ Caribbean coast) McSweeney and Coomes (2011, p. 5203) write: “Ninety-five percent of the flood-plain’s 125 ha of cacao orchards were buried or washed away, and with them all income from cacao sales.”

Flooding of agricultural orchards and fields like this is common. Due to various climate-change induced impacts, salinization, and other land degradations, the total land available for agriculture in both Guatemala and Honduras has decreased over the years. Figure 6 shows the total amount of land available for agriculture in both Honduras and Guatemala.

Figure 6: Arable Land (millions of hectares), 1970-2014

Source: Created by author based on World Bank (2016).

In Guatemala, the amount of arable land grew at a slow pace from 1970 to 2002, but has since been on an overall declining trend, despite two sharp increases in 2003 and 2007. In Honduras, the availability of arable land increased slightly from 1970 to 1977, after which it decreased slightly until 1988. Following a few years of increase and subsequent decrease in the early and mid-1990s, there has been a very sharp decline in the amount of arable land from 1998 to 1999. Incidentally, this is when Hurricane Mitch devastated Honduras.

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Increasing temperatures and the changing seasons have negative impacts on some crops. Crops like coffee and fruit (that are central to both Honduras and Guatemala) depend on a specific sequence of seasons. Because these seasons have been affected by climate change, the output of these products has been hurt. “Melons in the South of Honduras are now requiring more water to grow as temperatures are soaring and the vegetables in the mountains are struggling with the opposite, becoming sick with fungi due to the cold.”0

The vegetables in the mountains of Honduras are not the only crops infected with fungus. In Guatemala, a fungus called La Roya, has taken a hold of the coffee plants. NPR reporter Carrie Kahn (2014) writes that more than 70 percent of Guatemalan coffee crops are infected with La Roya, which has caused the loss of “100,000 jobs and a 15 percent drop in coffee output over the past two years”. Like the fungus affecting the vegetable crops in the mountains, La Roya has flourished because of the changing temperatures. Unlike the vegetable crops, La Roya thrives in warmer temperatures. Anyway, the changing temperatures across the region have allowed all types of fungus to grow. Climate change has reduced agricultural output because of fungi like La Roya and because of storm-induced flooding. People in both Honduras and in Guatemala have been forced to change the way they farm because of climate change.

IV.3. Deforestation: Exacerbating the Problem

The loss of arable land on the shores has led people in both countries to move inward. However, when they move inward, they typically have to cut down forests to make land available for farming. Figure 7 shows the amount of forest area in millions of square miles for each country from 1990 to 2015. It shows that the amount of forest area has been steadily decreasing in both, Guatemala and Honduras. The main reason for these decreases in forest area (especially in Honduras) is due to deforestation, which occurs mostly to create more farmland. Ironically, people are creating more farmland because climate change has negatively impacted the amount of crop they get on their previous land. Cutting down trees provides more farmland, but it also worsens the problem of climate change because cutting down trees releases carbon dioxide (CO2) into the air.

Figure 7: Forest Area (millions of hectares), 1990-2015

0 Llyod (2015).

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Source: Created by author based on World Bank (2016).

There is of course no direct correlation between the impact of climate change on a country and that country’s CO2 emissions as the impact of climate change is determined by global emissions and those emissions have much longer-term implications. However, given the topic of this article, it is still interesting to see how CO2 emissions have evolved over time in Guatemala and Honduras. Excluding the negative impact the world economic crisis of 2008/2009 had on output, the trends of total emissions, shown in Figure 8, are clearly upward. Controlling for GDP (in constant 2005 US$), Figure 9 shows that CO2 emissions have remained relatively stable in both countries from 1970 to around 1990, after which they increased until they turned highly volatile from 2005 to 2011, likely related to the recent world economic crisis.

Figures 8 and 9: Total CO2 emissions and CO2 emissions controlled for GDP

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Source: Created by author based on World Bank (2016).

IV.4. How Are Honduras and Guatemala Adapting?

The effects of climate change in Honduras and Guatemala are exacerbated because both countries are highly vulnerable and have poor infrastructure. Nonetheless, both countries have put in place adaptation strategies to combat the effects of climate change.

Honduras’ main climate adaptation strategies involve water resource management. Increasing temperatures and decreasing rainfall mean that water levels in Honduras will decrease. Water is needed for everything, especially for agricultural production. Given the negative impact of climate change on water availability, Honduras is working on a) enhancing the quality of its irrigation system and b) improving water management more generally, which includes everything from water storage to water conservation.0

While Guatemala also has policies for water management, many of their climate change adaptation policies focus on soil recovery and forest conservation techniques. These strategies are aimed at protecting Guatemala against extreme weather events. As mentioned in the previous section, extreme weather events erode the soil on the shore where crops are planted. When crops are destroyed because of extreme weather events, people are forced to move inland. And, when people move inland they often have to cut down trees to clear the land. In order to prevent deforestation, Guatemala is working on protecting the soil and plants around existing forests. While replanting trees and adding soil, Guatemala is also attempting to add nutrients to the ground. They hope that these initiatives will also increase crop yields.0

0 Adaptation Fund (2015).0 United Nations Development Program (UNDP), Climate Change Adaptation Portal (2015).

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While these adaptation plans are helpful, the implementation of the plans is more important. Because both countries are struggling with other problems, such as inequality and political corruptness, the necessary resources are not being allocated to implement climate change adaptation. In order for these countries to improve their situation, they must follow the steps set up and allocate the proper resources to deal with climate change.

V. ConclusionThis article examined the impacts of climate change on the agriculture of both Guatemala and Honduras. Generally, climate change has caused an increase in extreme weather events, an increase in temperatures, and a decrease in precipitation. Both Honduras and Guatemala are listed among the top ten countries most affected by climate change during 1996 to 2015.

Extreme weather events and changing temperatures are not good for any nation. However, they are especially harmful to nations that depend on agriculture, like Guatemala and Honduras do. The extreme weather events destroy crops and permanently destroy farmland. Changing temperatures and rainfall also negatively impact crop yields. Decreasing crop yields means less money for mostly already poor farmers, which greatly hinder their livelihoods. In countries where agriculture makes up a significant portion of GDP, these climate change related affects are a big problem.

Based on the data provided in this article, it is easy to see how much climate change has impacted Honduras and Guatemala within the last 20 years. However, we have also shown that within the last 10-15 years Guatemala and Honduras have begun to adapt to climate change. Both countries have begun to farm more efficiently and have begun to conserve water. They have also started planting different types of crops and have begun to diversify their economies.

While most of these initiatives have produced positive outcomes, they have not done enough to combat the eminent effects of climate change. As temperatures continue to rise and rainfall becomes less common, the agricultural industries in countries like Guatemala and Honduras will suffer. The amount of people living in poverty in both countries could increase as agricultural livelihoods are stripped away.

It is too late to reverse the effects of climate change. But there is still time to stop these effects from getting worse. International initiatives like the Paris Climate Agreement are good places to start. Agreements like this help hold nations accountable for their greenhouse gas emissions. Beyond mitigation, more adaptation initiatives that help countries already facing the effects of climate change, like Honduras and Guatemala, are needed. As the most vulnerable countries to climate change are overall also the least developed, these countries have to allocate many of their resources towards poverty reduction and addressing inequality. Therefore, it is important for the international community to help these countries to adapt to their changing environments.

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