ENERGY AND WOMEN’S ECONOMIC EMPOWERMENT: RETHINKING THE BENEFITS OF IMPROVED COOKSTOVE USE IN RURAL INDIA
A Thesis submitted to the Faculty of the Graduate School of Arts and Sciences Of Georgetown University in partial fulfillment of the requirements for the degree of Master of Public Policy in Public Policy
By
Rabea I. Sheikh, B.A.
Washington, DC April 8, 2014
Copyright 2014 by Rabea I. Sheikh All Rights Reserved
ii
ENERGY AND WOMEN’S ECONOMIC EMPOWERMENT: RETHINKING THE BENEFITS OF IMPROVED COOKSTOVE USE IN RURAL INDIA
Rabea I. Sheikh, B.A.
Thesis Advisor: Andrew Wise, Ph.D.
ABSTRACT
International development organizations have recently ramped up efforts to promote the use of improved cookstoves (ICS) in developing countries, aiming to reduce the harmful environmental and public health impacts of the burning of biomass for cooking and heating. I hypothesize that ICS use also has additional benefits--economic and social benefits--that can contribute to women’s economic empowerment in the developing world. To explore the relationship between ICS use and women’s economic empowerment, I use Ordinary Least
Squares and Logit models based on data from the India Human Development Survey (IHDS) to analyze differences between women living in households that use ICS and those living in homes that use traditional cookstoves. My regression results reveal that ICS use has a statistically significant and negative effect on the amount of time women and girls spend on fuel collection and a statistically significant and positive effect on the likelihood of women’s participation in side businesses, but does not have a statistically significant effect on the likelihood of lost productivity. My analysis shows promise that in addition to health and environmental benefits, fuel-efficient cooking technologies can also have social and economic impacts that are especially beneficial to women. It is my hope that the analysis provided in this paper will be used to further the dialogue about the importance of women’s access to modern energy services in the fight to improve women’s living standards in the developing world.
iii
ACKNOWLEDGEMENTS
The research and writing of this thesis is dedicated my wonderful family, friends, co-workers, and evening program classmates for their limitless patience, support, and help along the way. I would like to express my sincere gratitude to Dr. Andrew Wise for his guidance, crucial feedback, and continuous optimism about my topic and Mike Barker for all his help with my regressions and for re-teaching me how to use STATA. For taking the time to share their insights and advice, I would also like to thank Genevieve Smith, Doris Bartel, Douglas F. Barnes, Jacob Moss, and many others in the sustainable energy and development communities. I would also like to thank Ali and Omer for their boundless encouragement and essential edits and my amazing parents for their undying love, support, and guidance – I would be lost without you all. Last, but in no way least, I thank my incredible husband and partner, Rory. Without your patience, generosity, creativity, persistence, endless help, and infinite love none of this would have been possible. We made it, Ro!
Many thanks, Rabea I. Sheikh
iv
TABLE OF CONTENTS
I. INTRODUCTION ...... 1
II. BACKGROUND AND LITERATURE REVIEW ...... 5
III. THEORETICAL FRAMEWORK ...... 22
IV. EMPIRICAL MODELS ...... 24
V. DATA AND DESCRIPTIVE STATISTICS ...... 32
VI. FINDINGS AND ANALYSIS ...... 39
VII. CONCLUSION AND POLICY RECOMMENDATIONS ...... 52
REFERENCES ...... 60
v
I. INTRODUCTION
In many countries around the world, women are tasked with the responsibility of running the household. This is especially true in rural communities in developing nations where women’s responsibilities include taking care of children, cleaning the home, subsistence farming, pumping water, and cooking meals. Households in rural areas often employ the use of traditional cookstoves that run on biomass, the collection of which is another duty bestowed on women. The often physically demanding and time-intensive nature of biomass collection leaves little time for women to pursue other activities, such as furthering their education, participating in community- based activities, and economic activities—activities that can contribute to women’s economic empowerment and thereby, the eventual eradication of global poverty.
Improved cookstoves (ICS) that are designed to fuel efficient are being developed and promoted by various non-governmental organizations (NGOs), governments, and private development organizations as more environmentally-friendly alternatives to the heavy-exhaust producing, biomass-intensive, traditional cookstoves currently used in many of these households.
Many of the studies that have been conducted on ICS technologies have focused on the health benefits of using fuel-efficient technologies, as well as their potential for mitigating environmental degradation. In this paper, I go one step further and analyze the potential economic benefits of ICS to determine whether the use of these technologies can contribute to an improvement in women’s economic standing in rural communities.
My hypothesis in this study is that using improved cookstoves yields economic and social benefits that contribute to women’s economic advancement in developing nations. This hypothesis is based on the theory that as compared to traditional cookstoves, fuel-efficient cooking technologies are more energy-efficient—which contributes to timesavings—and emit
1 lower amounts of harmful toxins—which contributes to improved health. In particular, I propose that ICS use has the potential to reduce (1) “‘time poverty’, the absence of discretionary time women can dedicate to personal interests, paid labor, education, or other endeavors” and (2) lost productivity due to the incidence of debilitating diseases caused by harmful indoor air pollution
(IAP) (Gill, Brooks, McDougall, Patel, & Kes, 2010). Together, the timesaving and health benefits of ICS use provide women with resources and access to opportunities necessary to succeed and advance economically (Golla, Malhotra, Nanda, & Mehra, 2011).
It is my aim in this thesis to raise awareness about the importance engendering energy programs by incorporating the needs and preferences of women in energy development projects.
The concept of engendered energy suggests that men and women in rural communities use energy differently. Men generally use energy outside of the household whereas women typically use energy within the household for cooking and other household chores (ENERGIA.org, n.d.).
Many international development agencies committed to the overarching goal of eradicating global poverty have invested heavily in the development and promotion of sustainable energy technologies—technologies that allow access to modern energy services, contribute to economic growth, and are environmental sustainability. Unfortunately, many of these organizations have employed a gender-neutral approach to the design and implementation phases of their sustainable energy projects and as a result, have failed to incorporate the needs and preferences of the audience that they should be targeting – women. Incorporating women’s needs into these programs is essential for their success—“[b]ecause women are particularly well-placed to identify solutions for their own problems, engaging them at key points throughout the design and implementation process ensures the technology will be used and will create results meaningful to businesses as well as to individual women” (Gill et al., 2010). The failure to understand women’s
2 perspectives has proven to be an obstacle in the quest to improve economic development and eradicate rural poverty.
There has been a significant effort to detail the environmental and health benefits of ICS use in the developing world. However, research on social and economic benefits, especially pertaining to women, is not as robust. The purpose of this thesis is to contribute to the slowly growing body of work on the impact of ICS use. My analysis is based on data collected in the
India Human Development Survey 2005 (IHDS) and focuses on women in rural communities in
India where there has been a sustained effort at both the federal and local government levels to promote fuel efficient cooking technologies. Through this study, I hope to show that there is an important link between the use of improved stoves and women’s economic empowerment, which is essential for the reduction of global poverty.
To determine the impact of ICS use on women’s economic empowerment, I employ the conceptual framework on measuring women’s economic empowerment designed by the
International Center for Research on Women (ICRW) and the U.K. Department for International
Development as shown below (Golla et al., 2011):
Figure 1: Women’s Economic Empowerment: Two Necessary Inter-Related Components
Source: International Center for Research on Women (ICRW) (Golla et al., 2011).
3
There are two components to economic empowerment in this framework– power and agency, and economic advancement. In this paper I focus on the economic advancement component of the framework and argue that ICS use can provide women with “resources to compete in markets, as well as fair and equal access to economic institutions” needed to succeed and advance economically (Golla et al., 2011). To understand this relationship, I will analyze differences between populations that use ICS and those who continue to rely on traditional cooking methods. I will use three sets of regressions to assess the impact of ICS use on women’s economic empowerment in rural India. In the first set of regressions, I explore the timesaving aspect of the use of ICS by examining the amount of time women and girls dedicate to fuel collection. In the second regression, I analyze the impact of the health benefits of ICS use on women’s productivity. In this model, I use the probability of having to miss a day of work due to illness as a measure of women’s productivity which is a proxy that accounts for a change in women’s livelihood. In the third regression, I evaluate the influence of ICS use on the likelihood of women participating in a secondary business, which is used as a proxy for changing business practices. It is my hope that the analysis provided in this paper will be used to further the dialogue about the importance of women’s access to modern energy services in the fight to improve women’s living standards in the developing world.
In section II of this paper I provide background on the importance of the use of improved cooking technologies and the link between access to modern energy sources and sustainable international development. This background section is followed a literature review which includes relevant case studies that illustrate the benefits of improved cooking technologies that are currently being used in many developing nations. In section III, I discuss the theory behind the frameworks used to assess the impact of ICS use on women’s economic empowerment.
4
Section IV explains the empirical models that I use to measure changes in women’s economic empowerment that result from the use of fuel-efficient cookstoves. In Section V, I provide an overview of the data and descriptive statistics used in my analysis. Section VI is a discussion of the findings and analysis for each of the three models. Finally, Section VII is the concluding section of this report that includes a discussion about my hypothesis and the results obtained through my empirical analysis. This section concludes with an analysis of policy implications related to the use of improved cooking technologies and recommendations for sustainable energy projects that may be carried out in the future in developing communities.
II. BACKGROUND AND LITERATURE REVIEW
In this section, I discuss the adverse effects of inefficient cooking technologies
(traditional cookstoves/cooking methods) and highlight the need for improved cooking technologies. I then provide background on energy access in the developing world and discuss the connection between women’s economic empowerment and the eradication of poverty. Next, I describe the efforts to promote fuel-efficient cooking technologies in India. After describing
India’s ICS programs, I discuss the benefits of ICS usage as found in case studies and experiments that have been conducted all over the world.
There is a growing gap between the provision of basic energy services in developed and developing nations. Basic energy services include “heating for cooking, illumination for home or business use, mechanical power for pumping or grinding, communication, and cooling for refrigeration,” in other words, “energy services are the benefits that energy carriers produce for human well-being” (Modi, McDade, Lallement, & Saghir, 2005). Currently there are about 1.5 billion people in the world who lack access to basic energy services (Legros, Havet, Bruce, &
5
Bonjour, 2009). One-and-a-half billion people cannot switch on a light after the sun sets to read or do homework; turn on the heat to warm their homes when the temperature drops; or use mechanical appliances such as refrigerators to keep food from spoiling, grinders to process grains, and water pumps retrieve clean drinking water. Many of these 1.5 billion people also lack access to electric stoves and instead rely on primitive cooking methods for daily sustenance.
According to the International Energy Agency (IEA), in 2009 2.7 billion people (around 40% of the world’s population) “relied on the traditional use of biomass for cooking” (IEA, 2011). The consumption of biomass leads to “more than 1 billion tons of carbon dioxide (CO2) emitted into the atmosphere” (Akbar, Barnes, Eil, & Gnezditskaia, 2011). Much of this consumption occurs in rural communities in developing nations—in fact, India alone accounts for 27% of the worldwide population dependent on biomass (also called solid fuel) (Barnes, Kumar, &
Openshaw, 2012). The use of biomass has been linked to a host of problems including premature death related to respiratory infections, environmental degradation, climate change, and loss in social and economic productivity.
Cooking Methods
Traditional cooking typically involves placing a pot on top of an open fire contained by stones. Biomass and/or biofuel, meaning “living or recently living matter, plant or animal [which has traditionally consisted of] wood, charcoal, crop wastes, and animal dung,” is required to ignite the flame used in this cooking process (Manuel, 2003). This biomass is typically collected from surrounding areas—forests, farm plots, and so forth—and is usually a cost-free fuel.
However, traditional stoves are frequently inefficient. The design of traditional cookstoves contributes to the “free escape of flames and combustion gases around the pan without any heat transfer” (Manibog, 1984). The inefficiency of traditional cooking methods contributes to longer
6 cooking times which requires additional of biomass (Malinksi, 2008). The smoke that results from this cooking process is often highly toxic and contains fine particulate matter (PM),
“carbon monoxide, nitrous oxides, formaldehyde, and polycyclic organic matter, including carcinogens such as benzo[a]pyrene” (Manuel, 2003). The release of these chemicals within homes leads to increased indoor air pollution (IAP) levels, which has been linked to many serious respiratory infections including acute respiratory infections (ARI), chronic obstructive pulmonary disease (COPD), tuberculosis (TB), asthma, and even cancer (Smith, 2000).
Lab and field testing has shown that some ICS technologies have more efficient combustion, require less biomass, and reduce cooking times (Barnes et al., 2012). The basic definition of an improved cook stove is a stove that has been designed to consume less biofuel for combustion and improve fuel efficiency (Zhang, 2009). Generally ICS “have walls that create a barrier concentrating the fire, while conserving heat and reducing fuelwood use” (Holmes,
2010). In some cases, ICS consume less than 50% of the fuel used by traditional cookstoves
(Zhang, 2009). The improved efficiencies of ICS are usually measured by the controlled cooking test (CCT), the water boiling test (WBT), and the kitchen performance test (KPT).1 Scientists have used these three tests in the ICS development process to produce modern cooking technologies. By employing this testing process, scientists and engineers have discovered that fuel-efficient stoves can “[operate on] about one fifth of the energy of the open fire method”
(Ayoub & Brunet, 1996).
1 The WBT compares the amount of time needed to boil water in an ICS versus the amount of time needed using a traditional stove. In the CCT, a local meal is prepared by a stove distributing agency in the same way that it would be prepared in a local household, using the same pots, pans, fuels and practices. With the KPT, meals are selected and prepared in-home by every-day users on improved and traditional stoves. The WBT is generally conducted in a lab, whereas the CCT and KPT are usually conducted in the field, and as such, are more reliable tests of performance (Johnson, 2012). 7
The promotion of improved cook stove technologies accelerated in the 1970s as awareness grew about the hazardous pollution caused by the burning of biomass. Many agencies developing these stoves aimed to create fuel-efficient models to reduce the need for firewood, preventing deforestation and reducing drudgery (Kumar, Kumar, & Tyagi, 2013). Unfortunately, this wave of ICS dissemination programs was not as successful as hoped—in 1984 it was reported that “[f]ewer than 100,000 stoves have been distributed worldwide, of which 10%-20%
[had] fallen into disuse and another 20%-30% [were] used only intermittently” (Manibog, 1984).
Many initial ICS programs were top down government efforts that produced “inconsistent efficiency measurements and large discrepancies between laboratory and field performances”
(Gifford, 2010). This was especially true in the case of India’s National Program on Improved
Chulhas (NPIC).2
Access to Modern Energy and Poverty
The reduction and eventual eradication of poverty is tied to access to modern energy services. Energy is a fundamental requirement for many household activities—cooking, heating, lighting, irrigation, etc. (Cecelski, 2000a). Income plays a significant role in determining the type of energy source used—higher income earning individuals “generally use more efficient and more convenient sources of energy such as gas and electricity, while poor people use less efficient and less convenient sources such as fuelwood and human energy” (Cecelski, 2000a).
There has been a significant effort to promote rural electrification—the expansion of electricity access to rural communities. While some poor households have gained access to basic electric services through these efforts, many still cannot afford to use electric facilities to prepare meals and continue to rely on primitive cooking technologies. This is primarily because poor people
“often pay more for [energy services] both absolutely (paying higher unit prices) and relatively
2 Chulha is the name for stove in Hindi. 8
(as a percentage of their income) than do the non-poor” (Cecelski, 2000a). In this way “[p]overty influences and determines energy choices of households” (Cecelski, 2000a). This is especially true in India, where 69 percent of the population relies on wood and dung for fuel (Legros et al.,
2009).
Eradicating Poverty through Women’s Economic Empowerment – the Millennium
Development Goals
In September 2000, world leaders gathered at the United Nations (UN) Millennium
Summit and adopted the United Nations Millennium Declaration. From the Declaration came a list of eight international development goals known as the Millennium Development Goals
(MDGs). These goals include the eradication of extreme poverty and hunger, achieving universal primary education, promoting gender equality and empowering women, reducing child mortality rates, improving maternal health, combating HIV/AIDS, malaria, and other diseases, and ensuring environmental sustainability. Having access to modern energy services is fundamental to the achievement of these goals. Without access to sustainable energy, the “energy poor”— those who are both impoverished and lack modern energy access—will continue to depend on inefficient and unreliable energy services. This lack of access perpetuates the cycle of poverty. In this paper I will focus on the MDGs that relate specifically to achieving women’s economic advancement by the use of modern cooking technologies.
MDG 1: Eradicate Extreme Poverty and Hunger
Improved cooking technologies can contribute to the eradication of extreme poverty and hunger, a problem that is more acutely experienced by women and children in developing nations. Access to clean fuels and/or more fuel-efficient appliances has been shown to reduce the
“large share of household income spent on cooking” (Modi et al., 2005). In countries where
9 biomass is a scarce resource, many households dedicate a significant amount of their earnings to purchasing firewood. Families living in camps for internally displaced persons (IDPs) in the
Northern Darfur region experience extreme hunger as a consequence of wood scarcity and the high costs of fuelwood (Galitsky, Gadgil, Jacobs, & Lee, 2006). Those who cannot afford to purchase firewood, LPG, or kerosene resort to foraging for biomass and, as is the case in many developing countries, the “management of non-commercial fuels falls on women's shoulders”
(Parikh, 1995).
The time and labor required of women for biomass drudgery takes away from any discretionary time and human energy that could be spent on other activities, including income- generating opportunities. Improved cooking technologies typically require less biomass than traditional cookstoves, thereby alleviating some of the time and labor constraints associated with traditional cook stove use. In this way, ICS use can help curb the problem of time poverty that affects so many women in developing nations. Alleviating time poverty is essential for the achievement of economic growth and education as women with more time can learn and develop new skills to expand their economic prospects (Gill et al., 2010). This in turn could contribute to a reduction in poverty generally.
MDG 2: Achieve Universal Primary education
ICS use can also contribute to the achievement of universal primary education. Women and girls are often responsible for the collection of biomass (particularly firewood). To ensure adequate fuel supply, many girls are removed from school to help their relatives forage for biomass. The fuel-efficiency of many ICS technologies reduces the need for vast amounts of biofuel for combustion. Biomass drudgery for ICS thus requires less time and labor, thereby reducing the need to take girls out of school. In fact, studies have shown that the “conditions for
10 women’s education become favourable if the drudgery of their household chores is reduced, if not eliminated, with efficient and clean energy sources and/or devices for cooking” (Batliwala,
2003).
MDG 3: Promote Gender Equality and Women’s Empowerment
The time and labor saving nature of many fuel-efficient cooking technologies may also permit women and girls a respite from “survival activities” such as foraging for biomass, cooking, managing the household, etc. (Modi et al., 2005). This saved time can be spent enjoying social activities, including community gatherings which provide a forum for the exchange of ideas, and economic endeavors, like operating or participating in micro-enterprises. Participating in social or economic endeavors improves women’s productivity and may lead to “local income generation through improved agricultural development and non-farm employment” (Modi et al.,
2005).
The timesaving aspect of fuel-efficient technologies can also reduce the risk and threat of physical violence that women face while foraging for biomass. In August 2006 the International
Rescue Committee (IRC) in Darfur reported “200 assaults [on women gathering firewood] in a five-week period from a single [(IDP)] camp [and] Médecins sans Frontières reported over 200 cases per month [in the same region] in 2005” (Patrick, 2007). Because the “amount of firewood needed to cook the same amount of food is less, [with fuel-efficient alternatives] stove users can collect firewood less often and their risk of attack is therefore reduced” (Patrick, 2007). Gender based violence results in women feeling vulnerable and afraid. These reactions are a barrier to economic advancement—abused and traumatized women may feel too vulnerable outside their homes to participate in income generating activities.
11
MDG 5: Improve Maternal Health
The procurement and use of biomass, herein referred to collectively as the “biomass cycle”, includes inherent risks to women’s health. These risks are present in the procurement, carrying, and combustion stages of the biomass cycle (Wickramasinghe, 2003). In the procurement stage, women sometimes travel significant distances to collect biomass. Women are exposed at this stage to the risk of rape and assault, snakebites, cuts and bruises, and other dangers to their health and wellbeing. In the carrying stage women often transport the acquired materials on their heads, known as “headloading”. Headloading usually results in joint- and chest-pain, headaches, and stress injuries (Wickramasinghe, 2003). The third and final stage of the cycle, combustion, is likely the most harmful stage of biomass acquisition. In the combustion phase biomass is burned, typically inside the home. There is significant evidence that cooking with large amounts of biomass produces harmful gasses that have adverse health effects on household occupants, especially for those doing majority of the cooking. Studies show that prolonged IAP exposure can cause several diseases that have been linked to premature death. In
2000, the WHO “estimated that about 420 thousand premature deaths were caused annually in
India by household fuel air pollution” (Venkataraman, Sagar, Habib, Lam, & Smith, 2010).3
Many studies that have attempted to prove that ICS use can mitigate some of the harmful health effects of biomass combustion. According to scientific research on the health effects of
IAP exposure, “[p]articles less than 10 microns in diameter (PM10), and particularly those less than 2.5 microns in diameter (PM 2.5), [have been shown to] penetrate deeply into the lungs and appear to have the greatest potential for damaging human health” (Manuel, 2003). In one study,
World Bank Energy Economist Yabei Zhang proposed that “[i]f an average household with both
3 This data point comes from the WHO’s “Comparative Quantification of Health Risks: Global and Regional Burden of Disease Attributable to Selected Major Risk Factors” report (Ezzati, Lopez, Rodgers, & Murray, 2004). 12 primary and secondary traditional stoves switches the primary stove to an improved stove, the
PM 2.5 mean concentration is estimated to decline by 0.443 mg/m3 or 58 [percent]” (Zhang,
2009). While Zhang’s estimate was not statistically significant, her hypothesis on the connection between ICS use and reduced IAP levels in Indian households speaks to the potential health benefits for women who use ICS technologies.
MDG 7: Ensure Environmental Sustainability
Firewood harvesting also contributes significantly to environmental degradation. Many people who use traditional stoves harvest unsustainable levels of fuelwood, which adds pressure on biomass resources and contributes to “erosion, reduced soil fertility, and desertification”
(Modi et al., 2005). Furthermore, the burning of millions of tons of biomass every year significantly contributes to climate change, as “more than 1 billion tons of carbon dioxide (CO2)
[are] emitted [from inefficient cookstoves] into the atmosphere” (Akbar, et al., 2011). The impact of biomass combustion on the environment has a direct impact on women engaged in biomass collection. For example, extreme droughts resulting from climate change can make it difficult to grow crops, the byproduct of which is often used for fuel. These types of changes in the global environment are forcing women to travel further distances to collect fuel. In 2006, women in South Darfur needed to travel about 3 hours one way to get to fuel-gathering areas, whereas in 2005 they traveled about 2 hours one way to collect biofuel (Galitsky et al., 2006).
ICS developers hoping to reduce the burden of substantial biomass consumption and combustion on the environment have designed fuel-efficient cookstoves that require less fuel than traditional open-fire stoves, mitigating some of the harmful pollution caused by biomass consumption. The use of fuel-efficient stoves “can make exploitation of natural resources more sustainable…reduce greenhouse gas (GHG) emissions… [and encourage] better natural resource
13 management” (Modi et al., 2005). In this way, ICS use can contribute to environmental sustainability.
Women’s Economic Empowerment
Women’s economic empowerment is a necessary condition for alleviating global poverty.
Evidence from development literature “confirms that women’s improved economic status produces many positive economic and welfare outcomes for children, families, and societies”
(Gill et al., 2010). Economically empowered women are better able to advocate for and advance their rights, promote business and market growth, and they often invest their earned income in their children and families, which has been shown to have a significant effect on public health, education, and community welfare (Golla et al., 2011). Empowering women essentially
“provid[es] a route to sustainable development” (Golla et al., 2011).
To encourage economic advancement for women, it is imperative to include women in the discussion on sustainable energy development. Women in the developing world are generally responsible for energy procurement and management, and the effort required for these tasks are generally unaccounted for in national labor and energy use statistics. Furthermore, because household labor and productivity are not captured in GDP statistics, the value of women’s socio- economic contributions is often overlooked in national accounting measures. Because women’s domestic efforts are unaccounted for in many national statistics, “gender is still commonly viewed predominantly as a political [rather than an economic issue]” (Cecelski, 2000a). As a result, energy development programs, which are generally focused on economic improvements, have had a particularly strong gender bias. Women and men use energy in different ways, and it would be useful for successful development for researchers to generate more qualitative and quantitative information on disaggregated energy use (Cecelski, 2000b). This information will
14 allow for the customization of reliable and affordable energy service delivery programs that contribute to economic productivity and cater to the needs of both men and women. A gender- focused energy approach can “contribute to a dramatic improvement in living standards if they are directed preferentially towards the needs of women” (Batliwala, 2003).
Improved Cookstoves in India
India’s launched the National Program on Improved Chulhas (NPIC) in 1983 under the auspices of the Ministry for New and Renewable Energy (MNRE). The objectives of the NPIC were: “(i) reduction of deforestation and smoke through fuel wood conservation; (ii) reduction in the drudgery tasks to be performed by women and children; (iii) [reduction in] health hazards due to exposure to smoke; and (iv) [encouraging] employment in the rural areas” (Kumar et al.,
2013). The NPIC failed to accomplish its ambitious objectives. One of the main reasons for the failure of the program was the government’s sole focus on the dissemination of clean cookstoves. While the program met the government’s dissemination target, officials conducted very little follow on the maintenance of stoves and did not address the complaints from the
‘beneficiaries’ of the program. As a result, many of the ICS recipients “continue[d] to use their traditional stoves for daily cooking,” frequently keeping their ICS in the corner or outside the home (Sinha, 2002). The program also suffered because of the government-designed subsidization scheme, which offered rural households an ICS at subsidized price; “[i]t was expected that use of the stove would convince the rural user of the benefits of continuing with the use of the improved stove[,] which she was [then] expected to buy in the open market”
(Sinha, 2002). While officials developed this scheme to give poor customers the ability to purchase ICS technologies, due to deficient assessments the NPIC failed to account for the fact that “[m]any rural households [still] could not afford, or were not willing to pay for the highly
15 subsidized improved cook stove[s]” (Sinha, 2002). Many of the families who received the subsidized stove stopped using the stoves after they broke—shelf life of the stoves was typically two to five years—and reverted to their sturdier, easier to fix traditional stoves. It was also later discovered that the “proportion of harmful emissions [was] even higher for most ‘improved’ stoves than for traditional ones, so that the improved stoves seem[ed] to have an enhanced health hazard associated with their use” (Hanbar & Karve, 2002). Furthermore, the use of chimneys to reduce IAP levels also proved problematic as chimneys “transfer[ed] the pollution outdoor[s],” which contributed to “substantial human exposure” (Venkataraman et al., 2010). As a result of these discoveries (among others), India dismantled the NPIC in 2002.
In 2009, India formed the National Biomass Cook Stove Initiative (NCI) to again try to curb the harmful effects of traditional cooking in the nation. The goal of the NCI was to
“provid[e] energy service comparable to clean sources such as LPG but using the same solid biomass fuels commonly used today” (Venkataraman et al., 2010). The NCI incorporated lessons from the NPIC into its framework—for example, developers knew that “[t]o achieve reliable long-term high performance, stoves must use either advanced ceramics or metal alloys as well as other components (such as blowers), which must be made in centralized manufacturing facilities with good quality control and other modern mass production techniques” (Venkataraman et al.,
2010). Additionally, officials within the Ministry of New and Renewable Energy (MNRE) now also understand that ICS technologies should have “high-combustion-efficiency and low- emissions advanced-combustion devices that do not produce any significant pollution in the first place” (Venkataraman et al., 2010). According to their study on the implications of GHG emissions, Smith, et al., 2000, found that in India traditional cookstoves “achieve combustion efficiencies of 84-90% meaning that 6-16% of the energy in the fuel is not converted to heat, but
16 retained in a large range of produce of incomplete combustion” (Venkataraman et al., 2010).
Under the NCI, new combustion-efficient cookstoves are being manufactured to capture energy lost in the combustion process, and these stoves are now being disseminated to meet the goals of the program.
The NCI model also restructured the subsidization of ICS technologies and applied a more decentralized approach to cook stove dissemination. The NCI encourages private and/or non-profit entrepreneurs to develop cookstoves that are fuel-efficient and match the demands of the end users, a feature missing in the NPIC program. These and other lessons from the NPIC are being used to promote ICS usage in rural communities in India, where according to the National
Family Health Survey (NFHS-3), in 2005, “90% of rural households used biomass as their primary cooking fuel” (Venkataraman et al., 2010). The population dependent on biomass is expected to grow if the NCI and other local ICS initiatives fail to promote the adoption of clean cooking technologies.
ICS Programs in the Developing World
The above background section details the potential benefits of the use of modern cooking technologies. In this section I will discuss the available research on ICS use in the developing world. While many of the case studies reviewed in this section do not specifically address women’s economic empowerment, they do demonstrate the time, cost, and health saving benefits of ICS use. These benefits can contribute to women’s economic advancement and thereby empowerment.
Time and Cost Saving Benefits of ICS use
In their analysis on improved cook stove use in the Purépecha region in Mexico, Garcia-
Frapolli, et al., find that most of the economic benefits of ICS use come from household
17 fuelwood savings and saved healthcare costs. This study analyzes the savings associated with the distribution of over 1,500 Pastari improved cookstoves in Mexico’s Purépecha region, where
“80% of the residences use fuelwood as their primary energy source” (Garcia-Frapolli, et al.,
2010).4 To determine the savings from ICS use, the authors of this study construct a cost-benefit analysis (CBA) of the Pastari stove. According to their analysis, “[h]ouseholds using the Pastari cook stove saved a total of 40.6 hours/year due to better health[,] 24 hours/year from reduced acute respiratory diseases, 9.9 hours/year from avoided eye diseases, and 6.7 hours/year from the reduction of burn episodes in the kitchen” (Garcia-Frapolli, 2010). Taken together, savings on firewood and improved health “constituted 53% and 28% of the overall [economic] benefit” of
ICS use (Garcia-Frapolli, 2010). Through this analysis, Garcia-Fapolli, et al., suggest that there is a “shadow price” associated with the amount of time saved when using an ICS and there is potential for these timesavings to be translated into income generating activities, which may improve living standards for women.5
As in the Purépecha ICS study, the use of improved cook stove technology is shown to reduce spending on fuelwood and time spent foraging for biomass in the southern Darfur region in Sudan. In a study by the Lawrence Berkeley National Laboratory (LBNL), three metal ICS
(called Tara stoves) are tested against traditional three stone fire stoves in an IDP camp. It is estimated that IDPs typically spend about 200 Sudanese Dinar (SDD) ($0.90) a day for fuelwood. Through survey analysis, the LBNL team predicts that the use of the modified Tara stove saves families “about 36,500 SDD (about $160) annually…leading to a substantial increase in their disposable income that they [can] spend on other necessities (better nutrition, clothing,
4 The Pastari stove is an improved cookstove developed by the Interdisciplinary Group of Rural and Appropriate Technology (GIRA) in Mexico (Garcia-Frapolli, et al., 2010). 5 A shadow price is the true economic price (or opportunity cost) of an activity that does not have a defined market price (The Economist). In this case the shadow price accounts for timesavings from ICS use. 18
[and] improved shelters)” (Galitsky et al., 2006).6 It is also estimated that if the IDP camp adopted ICS universally, about 260 million kilograms of fuelwood would be saved annually
(Galitsky et al., 2006). These income savings from ICS use can translate into more food for
IDPs. Instead of spending endless hours searching for fuel and/or spending a substantial portion of their income on fuel, IDPs can use income saved on sustenance. In this way, ICS use can promote MDG 1, eradicating extreme poverty and hunger.
Another example of the potential benefits of ICS use is found in a recent field study sponsored by the U.S. Environmental Protection Agency (EPA), conducted in the peri-urban neighborhoods of Kolhapur, Maharashtra, India. In this study, a kitchen performance test is used to test household stove performance and determine fuel savings that result from the use of clean and improved cooking technologies. Researchers discovered through this testing that “homes with traditional biomass stoves required approximately double the energy [needed] for cooking compared to those [homes] using LPG and/or a combination of LPG/Oorja” (Johnson, et al.,
2013).7 While this study does not directly address the cost savings associated with energy savings, the fuel consumption estimates in the analysis do highlight significant findings on household energy consumption patterns and imply that there may be substantial environmental and economic benefits of transitioning from traditional stove use to more environmentally friendly LPG and improved cookstoves.
Health Benefits
Cooking with biomass increases IAP levels, which has many negative consequences for biomass cook stove users. Using a 2000 to 2003 survey of 1,638 rural households in Bangladesh,
Pitt, et al., establish that prolonged proximity to traditional cookstoves is correlated with a
6 The Tara stove is a modified fuel-efficient stove developed by Development Alternatives in New Delhi, India. 7 The Ooorja is an improved cook stove developed by First Energy, India. 19 significant increase in respiratory illnesses. The estimates in the study indicate that “a four hour per day increase in the time spent cooking - notably the difference between the average hours spent by women and by men - is associated with a 10.8 percentage point increase in the probability of reporting a respiratory symptom” (Pitt, Rosenzwieg, & Hassan, 2005). This correlation between time spent cooking and respiratory problems is significant because it proves the harmful consequences of prolonged IAP exposure. While many improved cookstoves do consume biomass, it has been shown that ICS use can reduce IAP levels, meaning ICS technologies can mitigate some of the harmful effects of inefficient biomass combustion.
In their study on the impact of ICS on women’s health in rural communities in Honduras,
Clark, et al., use a cross-sectional analysis to quantify household pollution levels. Through this assessment they discovered that “[w]omen with the improved stoves had 63% lower personal
PM2.5 concentrations, 73% lower indoor PM2.5 concentrations, and 90% lower indoor carbon monoxide levels as compared to women with traditional stoves” (Clark, et al., 2010). While this study is successful in showing that ICS use can reduce IAP, it also reveals that lower PM levels in Honduras are still significantly higher than PM levels in developed countries. This finding proves while ICS technologies will not eliminate pollution, their use can help reduce the burden of disease associated with traditional cooking.
In a study by Oregon’s Aprovecho Research Center (ARC), researchers use a controlled cooking test to measure differences between toxin emissions from ICS and traditional cookstoves in Tamil Nadu, India. The performance of three different Rocket stoves, “[a] single pot stove, a double pot stove, and a double pot stove with a chimney [is] compared to both the open fire and traditional stoves” used in the region (MacCarty, Still, Ogle, & Drouin, 2008).8 ARC found that
"[w]hen emissions released into the room were compared for the chimney stove, a 40%
8 The Rocket Stove is a fuel-efficient cook stove designed by the Aprovecho Research Center in the 1980s. 20 improvement was seen over the traditional chimney stove, while an 84% improvement was seen in IAP as compared to the three-stone fire" (MacCarty et al., 2008). This study also shows that the improved Rocket stoves require less firewood to cook meals than traditional stoves—Rocket stoves "used an average of about 1.5 kilos of firewood to cook the standard meal, while the traditional stoves used an average of 2.2 kilos" (MacCarty et al., 2008). The findings in this study support the positive public health and potential economic benefits of ICS use found in the other studies discussed in this section.
In his study on India’s national burden of disease (NBD) attributable to IAP, Kirk Smith calculates the annual health effects of IAP exposure (Smith, 2000). Impoverished individuals who continually experience poor health are often unable to participate in physically demanding activities and are therefore restricted in their labor market opportunities (Duflo, Greenstone, &
Hanna, 2008). Because of their limited economic prospects, these individuals and their families remain in the “poverty trap”—“because members of the household are both financially disadvantaged and in poor health, the household remains both in poverty and in poor health”
(Duflo et al., 2008). Smith finds that 1.6 to 2.0 billion days of work are lost annually due to diseases caused by IAP exposure. Smith’s research on IAP related NBD is one of the only studies that attempts to address the effect of air pollution on productivity and poverty (Duflo et al., 2008).
There are many studies on the public health and cost- and timesaving benefits of ICS use.
However, I did not find any studies that specifically address the relationship between ICS use women’s economic empowerment. This likely results from not having a unified standard for measuring economic or social benefits of ICS technologies. Field-tested results on ICS programs are also sparse. It is my objective in this thesis to contribute to the growing understanding that
21 energy development programs can contribute to women’s empowerment, and I hope to strengthen my claim by studying the relationship between ICS use and women’s economic advancement. I address this connection by examining the potential timesavings for women, their likelihood of having to take a sick day from work, and their probability of participating in secondary businesses. These variables are used as proxies for indicators of women’s economic advancement in rural India as explained in the following section in which I develop my theoretical framework.
III. THEORETICAL FRAMEWORK
Based on my review of sustainable energy development literature and ICS case studies, I use the following theoretical frameworks to test my hypothesis that using improved cooking technologies contributes to women’s economic empowerment in the developing world:
Women’s Economic Empowerment (Time savings) = f (Energy Source, Time, Region Differences, Education and Exposure, ε) (1)
Women’s Economic Empowerment (Productivity Savings) = f (Energy Source, Ability to Work, Physical Home Characteristics, Health, ε) (2)
Women’s Economic Empowerment (Participation in Secondary Business) = f (Energy Source, Income Assistance, Education, ε) (3)
In each of these equations, changes in economic empowerment are measured using different indicators for women’s economic advancement. In the first equation, changes in timesaving are measured to illustrate the effect of ICS use on reducing time poverty. In the second equation, the relationship between ICS use and productivity savings is used as a proxy for improved livelihood, an impact indicator of women’s economic advancement. In the third equation, the relationship between participation in a side business and ICS use is modeled. In this equation, participation in a side business is a proxy for changes in business practices, another
22 indicator of women’s economic advancement. It is my hope that together, these three different economic empowerment frameworks will support my hypothesis that ICS use can increase women’s economic empowerment in rural communities in the developing world.
In each equation, Energy Source means the type of cooking technology used within the household, including access to and use of improved cooking technologies; in this case, improved cookstoves (or chulhas) with chimneys. The reference category for ICS is traditional chulhas with no chimneys, three-stone open fire stoves, and stoves that do not run on biomass fuel.
In the first equation, other factors that influence women’s economic empowerment are the amount of extra or free time women have to devote to activities outside household chores
(Time); place of residence, such as urban or rural, city or village settings, regional specifications including monthly consumption per capita, and caste and/or religion of the head of the household
(Regional Differences); and primary or secondary schooling and exposure to media (Education and Exposure).
In the second equation, factors that may influence a woman’s productivity include women’s health and wellbeing (Health); a woman’s ability to participate in daily activities
(Ability to Work); and physical characteristics of the home, e.g., location of the cook stove and the home’s construction materials (Physical Home Characteristics).
In the third equation, income assistance including government and/or non-profit or NGO aid (Income Assistance) and education (Education) are assumed to influence women’s economic prospects. In each of the three equations listed above, the symbol “ε” is used to reflect the measurement error that may be present in my variables of interest in the equations.
I employ these frameworks to understand the economic benefits of ICS use in an attempt to add to the growing body of work on the benefits of access to modern energy services in the
23 developing world. Many ICS program studies have shown that fuel-efficient cooking technologies do yield some cost-savings for biomass users. In this thesis, I go a step further and predict that the cost-savings from ICS use can translate into higher rates of productivity and entrepreneurship among women, both of which lead to greater economic empowerment.
IV. EMPIRICAL MODELS
To test the theoretical frameworks discussed above, I will use three different sets of regressions that each measure a different facet of women’s economic empowerment. The first regression will analyze the potential timesavings for women and girls who use fuel-efficient cooking technologies. The second regression will examine the probability of lost productivity due to illness for traditional and improved cook stove users. The third regression will analyze if there is a difference in the likelihood of a woman’s participation in a secondary business in households that use traditional cookstoves and households that use improved stoves.
Model 1 – Time Spent Collecting Fuel
To determine whether ICS have a timesaving effect for women, I first analyze the amount of time women and girls spend collecting fuel in households that have traditional and modern cooking technologies. Because the dependent variable in this analysis is a continuous variable, I use an ordinary least squares (OLS) model to assess the relationship between ICS use and fuel collection rates:
Time Spent Collecting Fuel = β0 + β1Impoved Cookstoves + β2Cooking Fuel + β3Education + B4Exposure to Mass Media + β5Stove Use + β6Region + μ (4)
In this model the dependent variable, Time Spent Collecting Fuel, represents the amount of time (in minutes) women and girls spend collecting fuel in a week. I will run four different regressions based on this model to determine the effect, if any, of ICS use on women’s economic
24 empowerment—in this case represented by the amount of time women and girls save during fuel collection duties. The first two regressions measure the number of minutes per week women over the age of 15 spend collecting fuel. The third and fourth regressions measure the number of minutes per week girls under the age of 15 spend collecting fuel.9
Improved Cookstoves is the key independent variable of interest in this model. The purpose of this model is to demonstrate the timesaving nature of improved cooking technologies.
Given my hypothesis that improved cooking technologies can contribute to women’s economic empowerment because saved time reduces time poverty, I anticipate that the sign for ICS will be negative (Gill et al., 2010). This would indicate that the amount of time per week that women who live in households that use ICS spend collecting fuel is lower than the amount of time women who live in households that do not use ICS spend collecting fuel.
To account for other factors that might affect the relationship between the time that women spend collecting fuel and use of modern cooking technologies, I include several control variables in the model. These include the different types of energy sources used in the home, education and familiarity with mass media, and the household’s geographic location and the religion or culture of the inhabitants of the household. The first control variable, Cooking Fuel, represents the type of fuel a household uses for cooking. Cooking Fuel consists of three indicator variables – CookWood, CookDung, and CookCrop, each of which account for whether a household uses firewood, dung, or crop residue for cooking fuel respectively. I anticipate a positive sign for all three indicator variables given that women who live in households that rely on these materials for cooking will have to spend more time searching for these fuels than women who live in households that do not use these materials.
9 The IHDS Questionnaire asks how many minutes per week women over the age of 15 and girls under the age of 15 spend collecting fuel. It is not clear from the survey documentation which category 15-year-old girls fall into (women over age 15 or girls under age 15). 25
The second set of control variables used in this model account for the influence that education and exposure to mass media might have on the relationship between improved cooking technologies and timesavings. The Education variable accounts for women’s schooling— whether or not they have attended school and/or college. The Exposure control accounts for familiarity with new ideas and information discussed in the mass media. The more exposure women have to mass media, the better informed they may be about various government or NGO initiatives to eradicate extreme poverty. The women who fall into this category have a higher percentage chance of having knowledge about improved cook stove initiatives that are being promoted under the NCI. I anticipate that the sign for both variables will be negative. Women who are better informed are more likely to have and use ICS than women who are not exposed to mass media and therefore are less likely to be aware of ICS promotion efforts. Similarly, women who have attended school and/or college may be more aware of the benefits of ICS technologies.
In addition, women who attended school or college may spend less time collecting fuel because they are involved in other types of work—work that may require a higher level of education.
Both of these controls are likely to influence the relationship between ICS use and the amount of time spent collecting fuel.
The next control in the model, Stove Use, accounts for the amount of time that stoves are used within a household. Stove Use measures the number of hours a stove is used within a household on a given day. I anticipate that the sign for the stove use variable will be positive. I base this assumption on the fact that stoves require fuel for consistent combustion, meaning a stove that is used for a longer period of time will require more fuel for continued energy production. Women and girls living in households that have greater stove use will probably
26 spend more time collecting fuel than women and girls who live in homes that use their stoves for shorter periods of time.
The last control variable included in all of three of the empirical models in this paper is
Region. The Region control accounts for regional attributes that may influence fuel collection rates; for example, a household’s religion and a household’s monthly consumption per capita.
Taken together, these regional characteristics may account for cultural differences that could influence ICS use and the time women/girls spend collecting fuel in the various Indian states.
According to a UNICEF report on its Global Initiative on Out-of-School Children, “[g]irls in rural areas [in India], particularly those from Scheduled Castes and Scheduled Tribes in India have higher rates of [school] exclusion” (UNICEF, 2014). My Region variable captures the effects these types of cultural differences may have on the time women and girls spend collecting fuel. I also included this regional control in my analysis to account for climate differences in the various regions in India. For example, women who live in more arid regions in northern India may have to travel further distances to collect firewood and crop residue than women who live in southern temperate zones where biomass may be more abundant. Unfortunately, the IHDS does not include a section on the different climate types or vegetation patterns in India. The only way to control for these differences was to include the various states in my Region control.
I will use this regression model to assess the relationship between ICS and fuel collection times for women and girls. Together, these regressions will provide evidence of the timesaving benefits of ICS use for women in India.
Model 2 – Women’s Health and Productivity
The second regression in my analysis will analyze the relationship between ICS use and women’s productivity. In this model, I propose that women who use traditional, heavy-exhaust
27 producing cooking technologies are more likely to experience debilitating illnesses than women who use ICS technologies. As such, women who use traditional cooking technologies are less productive than women who use ICS. To assess my hypothesis about women’s productivity, I use a woman’s inability to perform work due to illness as my dependent variable. In this case, the ability to continue working is used as a proxy for the improvement in a woman’s livelihood, an indicator that measures the impact of improved cookstove use. Healthier women are less likely to have to take time off from their routine activities and therefore are more productive members of their households. These women are also more likely to be able to participate in economic opportunities that improve both their and their families’ livelihoods.
In this model, my dependent variable is a binary variable; therefore, I use the following
Logit model to assess the difference between the predicted probabilities of having to take time off from work due to an illness for women who live in households with ICS and those who live in households without ICS.
Inability to Work Due to Illness = β0 + β1Improved Cookstoves + β2Awareness of IAP Harm + β3Physical Household Characteristics + β4Health Status + β5Region + μ (5)
The dependent variable in this analysis, Inability to Work Due to Illness, is an indicator variable that accounts for whether or not a person was unable to perform her usual activities
(work, school, domestic work) in the last 30 days because of an illness.
The primary independent variable of interest is this model is Improved Cookstoves, which is the same key variable of interest used in Model 1 above. Model 2 is used to measure the difference between the likelihood of incapacitation due to illness in households that use ICS and households that employ traditional cooking technologies. In accordance with my hypothesis that the use of ICS contributes to women’s economic empowerment, I anticipate that the sign on the
28
Improved Cookstoves variable will be negative. This would indicate that using ICS improves women’s health, and in turn increases their prospects for participation in economic or social activities that may yield fiduciary gains.
I have also included different control variables in this model that may influence the relationship between improved cooking technologies and the likelihood of being unable to perform work. The first control included in the model is Awareness of IAP Harm. I anticipate that the sign for the Awareness of IAP Harm variable is positive. Common sense dictates that knowing about the negative consequences of IAP would be reason enough to induce people to switch to cleaner cooking technologies. However, despite having this knowledge, many people are not likely to adopt clean cooking technologies. For many people, cooking methods are steeped in years of traditions that have been passed down for generations. As a result, household members grow accustomed to their food having a particular taste. Unfortunately, the amount of and type of fuel used for cooking influences this taste. According to many ICS test-users, new cooking technologies that consume less fuel often alter the taste of food, which is a significant problem for many women (Lambe and Atteridge, 2012). These types of consequences may discourage the adoption of ICS technologies despite the technology’s health benefits.
The Health Status control in this model accounts for a person’s current health status, which could influence the relationship between the inability to perform work and ICS use.
Healthier individuals—in this case, individuals who do not smoke—and individuals who are not pregnant are less likely to be unable to perform routine activities. Therefore, I anticipate that the sign for Health Status will be negative, showing that individuals with better health are less likely to take time off from work than individuals with poor health.
29
The last control in this model, Physical Household Characteristics, accounts for the influence certain household characteristics may have on a person’s likelihood of being sick and unable to work. This includes the location of the cook stove—indoor vs. outdoor—and the home’s construction material. I anticipate that the sign for this variable will be negative.
Cooking indoors increases indoor air pollution, which has been linked to higher incidence of TB and asthma which can both cause severe debilitation (International Institute for Population
Sciences and Macro International, 2007). Additionally, certain building materials, particularly mud, have been linked to poor ventilation, thereby increasing indoor air pollution (Dasgupta,
Huq, Khaliquzzaman, Pandey, & Wheeler, et al., 2004).10 This means certain physical household characteristics can increase the probability of a person being sick and unable to perform daily activities.
Model 3 – Operating a Side Business
In my third and final empirical model, I analyze the relationship between improved cooking technologies and the likelihood of having or participating in a secondary (or side) business. In this model, my dependent variable is Side Business, which is a binary variable that accounts for whether or not a household operates or participates in a side business. Because my dependent variable is an indicator variable, I will use the following Logit regression model to determine the difference between the predicted probabilities of having a side business for women who live in households that use ICS and women who live in homes that do not use ICS:
Side Business = β0 + β1Improved Cookstoves + β2Income Assistance + β3Education + β4Region + μ (6)
10 This study was conducted in Bangladesh and noted that the “soil has low sand content and mud walls and floors are frequently re-coated with fresh mud to prevent cracking [which] creates an effective seal that permits almost no ventilation” especially when compared to other common building materials in the area (Dasgupta, et al., 2004).
30
As with Models 1 and 2, the key independent variable of interest in Model 3 is Improved
Cookstoves. I anticipate that the sign on Improved Cookstoves will be positive. Using the findings from Model 1 and 2, I hope to further my argument that the timesaving and productivity benefits of ICS technologies allow women to be more involved in other activities which may include owning or participating in side businesses. In this way, women may have the opportunity to become more actively involved in income generating activities, which may lead to a change in community business practices—having more women involved in businesses is an indicator of women’s economic advancement, which contributes to economic empowerment.
The first control in this model, Income Assistance, accounts for any payments that the household has received from NGOs, charities, government income assistance programs, and/or household income generating activities (renting of land). I anticipate that the sign for Income
Assistance will be positive. Income assistance programs may involve microfinance lending or business investment seed money, which encourages entrepreneurship. These assistance programs may also contribute to a household’s disposable income, which can be used to invest in a side business. Not having income assistance will likely reduce the probability of having a side business.
The second control variable in this model is Education, which is the same variable used in Model 1. I anticipate that the sign for Education will be positive; attending school, or living with household members who have attended school, will encourage the exchange of ideas and may influence a woman’s decision to start up a side business. I next detail the data I use to estimate these models.
31
V. DATA AND DESCRIPTIVE STATISTICS
The data used in this thesis come from the India Human Development Survey 2005
(IHDS). The IHDS is a national survey that spans a wide array of human development topics including education, health, socio-economic status, and gender relations at the household and individual level. India’s National Council of Applied Economic Research (NCAER) and the
University of Maryland, College Park developed and executed the IHDS between November
2004 and October 2005. The surveyors administered the IHDS survey in “all states and union territories of India (with the exception of Andaman Nicobar and Lakshadwee),” and collected data on 41,554 households in 1,503 villages and 971 urban neighborhoods across India (Desai, et al., 2008). The surveying agencies used stratified random sampling methodology to draw a sample of households. The collaborating institutions trained pairs of local administrators—one male and one female—who then gathered information for the IHDS by conducting two one-hour, face-to-face interviews with household heads for the Household Questionnaire and with ever- married female household occupants between the ages of 15 to 49 for the Women’s
Questionnaire.
To assess the impact of fuel-efficient cooking technologies on women’s empowerment, I combined data from the household- and individual-level surveys. I then removed all data for households in urban/urban slum areas, as my hypothesis is focused specifically on rural energy users. The descriptive statistics for key variables of interest in my analysis are listed in Table 1 below.
32
Table 1: Descriptive Statistics Variable Observations Mean* Min Max Fuel Collection (Minutes/Week) TFuelCollectWOM 100,501 250.407 0 3,600 TFuelCollectWOMMiss 88,266 285.117 1 3,600 TFuelCollectGirl 70,544 28.894 0 1,340 TFuelCollectGirlMiss 11,611 175.547 1 1,340 Inability to Perform Daily Activities Due to Illness UnabletoWork* 135,315 16,673 0 1 Household Side Business SideBus* 135,315 22,661 0 1 Gender Female* 135,315 66,504 0 1 Male* 135,315 68,811 0 1 Stove Use StoveUseLow* 135,315 38,560 0 1 StoveUseMed* 135,315 61,545 0 1 StoveUseHigh* 135,315 35,210 0 1 Stove Type ICS* 135,315 5,892 0 1 TradCookStove * 135,315 121,464 0 1 NoBiomassStove* 135,315 6,755 0 1 Fuel Type CookWood* 135,315 128,721 0 1 CookDung* 135,315 73,135 0 1 CookCrop* 135,315 25,792 0 1 Education and Exposure AttenSchool* 135,315 80,527 0 1 AttenColl* 135,315 4,144 0 1 WomWatchEducShow* 135,315 33,074 0 1 KnowIAPHarm* 135,315 94,410 0 1 Physical Household Characteristics CookIndoors* 135,315 102,518 0 1 MudWalls* 135,513 53,899 0 1 Health and Well Being NotPregnant* 135,315 107,272 0 1 NoSmoke* 135,315 7,609 0 1 Income Assistance NoNGOAssit* 135,315 135,284 0 1 NoGovAssist* 135,315 135,097 0 1 NoLandRentOut* 135,315 62,509 0 1 *represents a binary variable where 1 indicates the presence of a condition and 0 indicates the absence of the condition. Binary variable means are listed as the number of observations where the value equals 1. Source: India Human Development Survey 2005.
In the table above, variables marked with an asterisk are indicator variables, meaning if a condition is present the value of the variable is one and if the condition is absent the value is zero. For example, a household uses an improved cook stove if the value of the ICS variable is
33 one and does not if the value is zero. The first six variables in Table 1 are dependent variables that I use in my analysis of the impact of improved cooking technologies on women’s empowerment. The first two dependent variables, TFuelCollectWOM and
TFuelCollectWOMMiss, are continuous variables that measure the number of minutes per week women over the age of 15 spend collecting fuel. For the purpose of this thesis I generated the
TFuelCollectWOM variable using the observations in variable FU11B from the Women’s
Questionnaire and created a new variable, TFuelCollectWOMMiss. For this latter variable, observations coded as zero in the original data for the minutes per week women spend collecting fuel were recoded as missing and thus dropped from my regressions. I created this variable to account for any downward or upward bias that may influence my estimates—downward where surveyors recorded that women spent zero minutes per week collecting fuel, and upward in the cases where surveyors coded as missing observations listed as zero. My theory is that some of the zero minute responses are actually missing observations, but it is impossible to tell which observations are missing and which are truly zero. By reporting results for both regressions the reader can see upper and lower bounds for the estimates.
The next two dependent variables, TFuelCollectGIRL and TFuelCollectGIRLMiss, account for the number of minutes per week girls under the age of 15 spent per week collecting fuel and were created from variable FU11D. As in the women’s fuel collection variables, the girl variables are continuous, and observations coded as zero have been similarly recoded to account for bias from coding errors.
The next dependent variable, UnabletoWork, is an indicator variable that equals one if a person was unable to do usual activities (work, school, domestic work) in the last 30 days due to illness and equals zero if the person did not have to take time off from usual activities due to
34 illness in the last 30 days. The UnabletoWork indicator variable is based on variable SM10 from the Short-term Morbidity section of the Women’s Questionnaire. SM10 is a continuous variable that measures the number of days a person was unable to do his/her usual activities in the last 30 days. To assess the relationship between ICS use and women’s economic empowerment (in this case, measured by differences in productivity), I transformed SM10 into an indicator variable. In doing so, I hope to capture the difference between the likelihood of having to take time off from usual activities for women who use traditional and improved cookstoves.
The last dependent variable in the table above, SideBus, is an indicator variable that I created to measure whether or not a household operates or participates in a secondary business.
The SideBus variable is a combination of variables NF1A, NF10A, and NF19A, from the
Household Questionnaire. Variables NF1A, NF10A, and NF19A contain observations for only those respondents who report having or participating in a secondary business. The observations in these variables account for the different industry codes applied to the household’s secondary business, including retail trade in textiles, food/food articles, beverages, and so forth. SideBus equals one if the household runs a secondary business and zero if a household does not have a secondary business.
The remaining variables listed in Table 1 are control variables used in my three empirical models. The first set of controls, StoveUseLow, StoveUseMed, and StoveUseHigh, account for the amount of time that stoves are used within a household. These three control variables were derived from the FU3 variable, a continuous variable, which measures the number of hours a day a stove was burned in a household. StoveUseLow is an indicator variable that accounts for those households that use their stoves for two or less hours a day and is the reference category for the medium and high stove use indicator variables. StoveUseMed includes households that use their
35 stoves for three to four hours a day, and StoveUseHigh measures those households that use their stoves for five or more hours a day.
The next section of controls contains my key independent variable of interest, improved cookstoves. The three indicator variables in the Stove Type category come from ordinal variable
FU4, which asks what type of chulha the household uses. Households that use improved cookstoves are coded as one for the ICS indicator variable, and households that use traditional cooking methods (traditional chulhas without chimneys or open fire stoves) are coded as one for the TradCookStove variable. Unfortunately, the IHDS does not account for households that use multiple cookstoves—improved and open fire stoves or ICS and non-biomass consuming stoves—which is often the case in households that use ICS technologies (Johnson, et al., 2013).
Instead, the survey data only lists households as using one technology. Because many of the households surveyed for the IHDS probably used both improved and traditional cookstoves, the estimates achieved in my analysis may not reflect the true impact of ICS use on women’s economic empowerment. For example, the ICS coefficient estimates for my fuel collection regressions might be downwardly biased—women living in households that only use improved cookstoves might spend even fewer minutes per week collecting fuel than women who live in households that use both traditional and improved cookstoves.
Fuel type is the next category in Table 1, which I use in my regression analysis for Model
1. This set of indicator variables accounts for the type of fuel a household uses. The three indicator variables in this category come from the ordinal variables, FU5, FU6, and FU7 in the
Women’s survey. For these variables, households were asked whether wood, dung, or crop residue was used for mainly cooking, mainly lighting, mainly heating, a combination of the categories, or was not used at all in the household. For the purpose of this study, I created
36
CookWood, CookDung, and CookCrop to account for those households that use the respective materials for mainly cooking or combined use.
The Education and Exposure category contains indicator variables that measure a person’s level of education and exposure to mass media. AttenSchool comes from the Household
Questionnaire variable ED3A, which asks if a given household member has ever attended school. AttenSchool equals one if a household member did attend school and zero if that household member did not attend school. Similarly, AttenColl is derived from variable ED11A, which asks if a given household member ever attended college or a technical/vocational school.
WomWatchEducShow is an indicator variable based on ordinal variable MM5B which asked how often women watched news, talk shows, educational, or agricultural shows. The
WomWatchEducShow variable equals one if the respondent sometimes or regularly watched these shows and zero if the respondent never watched the shows. The last variable in the
Education and Exposure category, KnowIAPHarm in an indicator variable based on ordinal variable HB4 which asks respondents if smoke from wood/dung burning traditional chulhas is good for a person’s health, harmful for health or doesn’t really matter. KnowIAPHarm accounts for those respondents who stated that stove exhaust is harmful for health and is marked as zero for those respondents who believe smoke is good for their health and those who do not believe that smoke matters for health.
I use the next set of variables in the table in my second empirical model where the influence of different household characteristics on the likelihood of being unable to work is captured. CookIndoor is derived from the ordinal variable SA2, which asks respondents if cooking is done outdoors, in a separate kitchen or in the living area. CookIndoor combines both indoor values (in a separate kitchen and in living area) to equal one and equals zero if cooking is
37 conducted outdoors. MudWalls comes from the predominant wall type ordinal variable, HQ4.
MudWalls equals one if the home’s walls are made out of mud or un-burnt bricks and zero if the walls are made of other materials.
The next category of control variables accounts for a person’s current health status. The first control in the category, NotPregnant, is an indicator variable derived from variable FP1 which asks respondents if they are currently pregnant. NotPregnant equals one if the respondent is not pregnant and zero if the respondent is pregnant. NoSmoke comes from ordinal variable
TO2, which asks how often household members smoke cigarettes, bidis, or hukkah. NoSmoke equals one for those households in which household members never smoke and zero for households with smoking occupants. Both of these variables are used as controls in Model 2.
The final set of control variables are categorized under Income Assistance. All three variables in this category are indicator variables used to determine whether or not a household has received income assistance. Both NoNGOAssist and NoGovAssist come from survey questions 8.12 and 8.13, which ask if anyone in the household has participated in NGO or charity assistance and/or government income generation programs. Individuals in households that have not received income assistance from the government or NGOs are captured under the
NoNOGAssist and NoGovAssist indicator variables. The final variable in this category,
NoLandRentOut, is an indicator variable that equals one if a household has not rented or sharecropped out any of its land and zero if it has. NoLandRentOut is derived from continuous variable FM6A, which measures the total units of agricultural land that the household has rented or sharecropped out.
38
VI. FINDINGS AND ANALYSIS
To determine the effect of ICS use on women’s economic empowerment, I employ regression analysis on three different measures of women’s economic advancement. I first explore the time saving aspect of the use of improved cookstoves using theoretical framework number one. In this equation I separately regress my independent variables on four different continuous variables (TFuelCollectWOM, TFuelCollectWOMMiss, TFuelCollectGIRL, and
TFuelCollectGIRLMiss), each of which account for the number of minutes per week women and girls spend collecting fuel. I then employ theoretical framework number two using a logistic model to examine the effect of ICS use on women’s productivity, which is used as a proxy for the economic advancement output indicator, women’s participation in various activities. In this case, the logistic estimation allows me to determine the predicted probability of women having to abstain from their usual activities due to illness (UnabletoWork) in households that use improved cooking technologies and households that rely on traditional cookstoves. In my final regression, I apply another logistic model to the third theoretical framework to assess the relationship between ICS use and the likelihood of women participating in a secondary business.
In this regression the binary variable, SideBus, represents household members who participate in or operate a side business. In this case, the likelihood of participating in a secondary business is used as a proxy for the economic advancement outcome indicator, changes in business practice.
Table 2 lists diagnostic statistics for the models detailed above. As shown in Table 2, F- and Chi2-statistics for all models are highly statistically significant (p<0.01). The R2 and pseudo-
R2 statistics, which capture the amount of variance in the models, are consistent across regression techniques. In the OLS regressions, independent variables account for between 21 to 54 percent of the variation in the time spent collecting fuel. Across the two logistic regressions, only five to
39 seven percent of the variation in predicted probabilities is attributable to independent variables used in the models. Coefficient estimates and standard errors for the fuel collection, productivity, and secondary business regressions are listed in Tables 3, 4, and 5, respectively.
Table 2: Diagnostic Statistics for Models of Women’s Economic Empowerment Model R2 & Number of F-Statistic or Pseudo-R2 Observations Chi2 - Statistic Min/Week Women collect fuel 0.39 100,449 90.61*** (F) Min/Week Women collect fuel (Missing) 0.40 88,220 62.29*** (F) Min/Week Girls collect fuel 0.21 70,513 57.41*** (F) Min/Week Girls collect fuel (Missing) 0.54 11,611 31.81*** (F) Unable to Work Due to Illness 0.045 66,457 2062.46*** (Chi2) Side Business 0.073 66,401 3982.32*** (Chi2) *** indicates 99% confidence that the regression is statistically significant Notes: Source – IHDS 2005.
40
41
ICS Use and Time
Table 3 presents coefficient estimates for ICS use, household fuel type, education and exposure, and stove use, for the number of minutes per week women and girls spend collecting fuel. The findings in Table 3 show that ICS use has a statistically significant effect on time spent on fuel procurement. In all models, coefficient estimates for the key independent variable, ICS, are also expectedly negative, suggesting that the use of ICS contributes to time-savings for women and girls. The magnitude of the effect of ICS use on fuel collection is also important to consider – according to the regression results, women who live in households that use cookstovesICS spend fewer minutes per week collecting fuel, on average, than women who live in households that use traditional, open fire, or non-biomass consuming cooking technologies
(about 21 and 16 fewer minutes per week for regressions 1 and 2, respectively). Put another way, women in households with fuel-efficient cookstoves may save up to one hour and 24 minutes per month that they would otherwise spend collecting fuel.
Similarly, girls who live in households that use ICS may spend between 11 and 46 fewer minutes per week collecting fuel than girls from households that use traditional or non-biomass consuming cooking methods. This means girls in ICS-using households may be able to save up to three hours per month on fuel collection. The less time girls spend collecting fuel, the more time they can dedicate to other activities, most importantly staying in school to further their education. Women and girls who live in households that employ improved cooking technologies have the benefit of extra saved minutes per week—minutes that can be used for educational, social, or economic activities. The results for the OLS regressions suggest ICS use can contribute to economic advancement—in this particular case, fuel-efficient cooking technologies are shown to reduce the time women and girls spend on fuel drudgery.
42
In each of the four models above, eight binary demographic and control variables are used to account for other factors that may influence the relationship between ICS use and the time women and girls spend collecting fuel. The first set of controls reflect the influence that the type of fuel used in a household may have on fuel collection. In all four regressions, cooking with wood and dung has a statistically significant effect on time spent procuring fuel. Cooking with crop residue, on the other hand, has a statistically significant effect on fuel collection in only three of the four models. Consistent with my predictions, in three of the models cooking with wood is shown to increase the amount of time women and girls spend gathering fuel.
Coefficient estimates in the first, second, and fourth models reveal that cooking with wood increases the amount of time per week women and girls spend gathering fuel by 45, 39, and 21 minutes, respectively. Cooking with wood is shown to have the opposite effect in the third regression which measures the number of minutes per week girls spend on fuel collection—in this case, results indicate that girls who live in households that use wood for fuel spend less time per week on fuel collection than girls who live in household that do not use fuel wood. A likely explanation for this result is that wood is often very heavy and younger girls who may not be as able to carry large supplies may be precluded from wood procurement. Another factor that may have contributed to this result is the possible measurement error associated with coding the number of minutes spent collecting fuel as zero instead of missing.
Cooking with dung is mostly shown to have a negative effect on time spent collecting fuel; however, in the third regression, using dung is shown to increase the amount of time that girls spend collecting fuel by six additional minutes per week. This result may reflect the influence of travel distance on fuel procurement—because animal dung is typically collected on
43 local farms, younger girls may be more engaged in dung collection than with more strenuous wood collection.
In three of the models, cooking with crop residue is shown to increase the number of minutes per week women and girls spend collecting fuel. The inverse relationship between fuel collection and crop residue use reflected in the first regression, however, shows that women who live in households that use crop residue for fuel spend 47 fewer minutes per week, on average, collecting fuel than women who live in households where crop residue is not used for fuel.
The next set of demographic variables in the models account for the effect of education on fuel collection time and ICS use. Having a household member who has attended school has a statistically significant effect on fuel collection time in the first and third models, where observations listed as zero were not recoded as missing. Coefficient estimates for the
AttenSchool variables in these models suggest that women who live with household members who have attended school spend about four fewer minutes per week collecting fuel as compared to women with no household members who attended school. By contrast, girls who live in households where someone has attended school spend four more minutes per week on average collecting fuel than girls from households where no occupants have attended school. This result may reflect societal gendered norms—as is the case in many traditional households, boys are usually kept in school and encouraged to pursue educational aspirations, whereas girls are sometimes pulled out of school and made to assist with household responsibilities (UNICEF,
2014).
Having a household member who has attended college is also, for the most part, shown to have a statistically significant and negative effect on fuel collection times. In the first three models, living with college-educated household members is shown to decrease the amount of
44 time women and girls spend collecting fuel by 16, 12, and six minutes per week, respectively. In the fourth regression, which measures the time girls spend collecting fuel and where observations coded as zero were recorded as missing, however, girls with college-educated relatives are shown to spend more time collecting fuel supplies than girls with non-college-educated relatives.
This coefficient estimate does not reflect a statistically significant effect on fuel collection times.
The negative correlation between higher education and fuel collection times makes sense— college-educated household members are more likely to encourage the pursuit of education, which involves staying in school and studying (Gill et al., 2010). Furthermore, women who have attended college may be more inclined to work for pay, and may have access to higher paying jobs, and as such, spend less of their time foraging for fuel.
The next control used in the models, having women in the household who sometimes or regularly watch educational programming, has a statistically significant effect on the time spent collecting fuel in all four models. In three of the models, watching educational programming has a negative effect on the time spent collecting fuel. This relationship reflects that women and girls who live in households where women sometimes or regularly watch informational shows spend less time collecting fuel. What is most interesting about these results is that having women in the household who sometimes or regularly watch the news, talk shows, or other educational TV seems to have a very strong influence on the amount of time girls spend collecting fuel— according to results from the second regression, girls can save up to three and a half hours a month on drudgery. One factor that is not accurately captured in this regression and could be influencing these results is household affluence—affluent households are more likely to own a
TV and household members in these homes are more likely to have the time to watch educational
TV shows than less affluent households. Furthermore, affluent households are also less likely to
45 depend on cooking methods that require collected biomass—these households are more likely to have the resources to purchase wood or crop-fuel, LPG, or kerosene and are therefore, less likely to send young girls into the fields to gather fuel. Regression results in the second model reflect a positive effect on fuel collection. This positive influence in this estimate could be the result of the imprecise measurement in the time spent collecting fuel variable particularly the coding of zero or missing values.
The last set of control variables account for the relationship between household stove use and time spent collecting fuel. In all four models, medium to high stove use has a statistically significant effect on fuel collection times. In three out of the four models, coefficient estimates reflect an expectedly positive relationship between fuel collection and sustained stove use. In this case, women and girls who live in households that burn stoves for three to four hours per day
(medium stove use) and five or more hours per day (high stove use) spend more time per week collecting fuel than women and girls who live in households that use their stoves for only one to two hours a day. Stove use results in the fourth model, however, are inconsistent with my predictions. An explanation for these results could be that girls under the age of 15 might not be as able to collect the significant amount of biomass needed for higher energy production, therefore older women and, in some cases, boys might be more actively involved in the biomass procurement phase in households that use their stoves for 3 or more hours a day.
The findings in Table 3 are consistent with my predictions about the timesaving benefits of ICS use. Results from the OLS regressions reveal that ICS use has a statistically significant and negative effect on the amount of time women and girls spend on fuel collection. Women in many developing countries are often saddled the burden of household responsibilities leaving very little “discretionary time [to] dedicate to personal interests, paid labor, education, or other
46 endeavors” (Gill et al., 2010). As demonstrated, improved cooking technologies can alleviate some of the time poverty faced by women. In order to achieve economic empowerment, women need the resource of time and the fuel-efficient cook stove is one development initiative that can help in the provision of this invaluable resource.
ICS Use and Productivity
After analyzing the potential time-saving benefits of ICS use, I shift my focus to another facet of economic advancement—women’s participation in activities. To explore the effect of
ICS use on women’s participation I use a logit model with the binary dependent variable, inability to work which accounts for women who were unable to perform daily activities due to illness. Regression results for this model are shown in Table Four below:
Table 4: Logit Regression Model – Probability of Inability to Perform Work Due to Illness Variable Coefficient Standard Error AME ICS -0.02 0.07 -0.002 Cook Indoor -0.07** 0.03 -0.008 Mud Walls 0.08*** 0.03 0.009 Understands IAP Harm 0.03 0.03 0.004 Not Pregnant -0.14*** 0.03 -0.016 Non-Smoking HH 0.22*** 0.06 0.027 ** indicates 95% confidence, *** indicates 99% confidence Notes: Source – IHDS 2005; Regional controls (COPC, Geographic Location, Religious affiliation not shown).
As demonstrated by the regression results listed in Table 4, after controlling for various health and demographic factors, it appears that in this particular model improved cookstoves do not have a statistically significant effect on changing the likelihood of a woman being unable to perform routine activities. This result may have to do with the data itself—survey respondents may have underestimated the number of days they were unable to perform routine activities or have not been comfortable reporting this information for fear of either losing their current jobs or because they did not understand the survey question fully. Additionally, the data collected does not account for households that used traditional and improved cookstoves. Furthermore, it is not
47 clear when the data for this survey was collected—more specifically, during which season the data was gathered. In the IHDS, respondents were questioned about the number of days they were unable to work during the last month and their response may have differed based on the month that the survey was conducted. For example, some survey respondents may have been ill and unable to work during the rainy monsoon season but completely healthy in the spring or summer. The lack of significance in this model could also be attributed to the general scope of the dataset. Because my dataset does not focus solely on ICS users but a broad swath of households, only some of which use improved cookstoves, it is difficult to analyze the changes in women’s productivity based on ICS use. What is reassuring, however, is that the coefficient estimate for ICS is negative and not positive, as such, there is the possibility that ICS use can reduce the probability of incapacitation and this possibility warrants further investigation.
The regression results also indicates that not being pregnant, living in a home built with mud walls, living with non-smokers, and cooking indoors each have a statistically significant effect on the probability of being unable to work. As is consistent with my predictions, not being pregnant reduces the likelihood of a woman having to abstain from usual activities and living in a home constructed of mud increases the likelihood of being unable to work due to illness. Using the Average Marginal Effects (AME) method to estimate the magnitude of the logit coefficients reveals that women who are not pregnant are about two percentage points less likely to have to take time off from work due to illness than women who are pregnant.11 This finding, although slight, is not surprising given that women who are pregnant are generally not able to perform as many activities as women who are not pregnant. The AME method also shows that women who live in mud-walled homes are about one percentage point more likely to take time off from work
11 The Average Marginal Effects (AME) method is used to compute an average marginal effect—an average change in the predicted probability [P(Y=1)] related to a change in a covariate. AME calculations used in this thesis were performed on Stata using the margins command (Stata 13 Reference Manual, Margins). 48 due to illness than women who live in homes made out of other construction materials. This finding is somewhat more surprising given the poor-ventilation properties of mud (Dasgupta, et al., 2004). This result could be related to survey response error – survey takers were asked to note observed housing characteristics and may not have accurately recorded building materials.
Coefficient estimates for CookIndoor and NoSmoke, on the other hand, are not consistent my predictions. According to the average marginal effects results, women who live in households where the cooking is done indoors are less likely to abstain from typical duties than women who live in households where the cooking is done outdoors by about one percentage point. This is inconsistent with previous findings that indicate that indoor cooking contributes to an increase IAP, which has been linked to debilitating respiratory illnesses and could be related to the data issues discussed earlier. Additionally, the AME method reveals that living in non- smoking homes increases the likelihood of a woman being incapacitated by about three percentage points. This may again have something to do with the way the answers for the survey questions were collected – some respondents may have been confused about the questions or may have been reluctant to report their smoking habits to the survey administrators.
The findings in Table 4 are not consistent with my predictions about the relationship between ICS use and women’s productivity. Results from the logit regression reveal that ICS use has does not have a statistically significant effect on likelihood of a woman being unable to perform her routine activities due to illness although due to the potential data errors discussed above, this premise still warrants exploration. Many studies have established that traditional cooking methods pose great health risks to household occupants, particularly women who often spend countless hours hovered over cookstoves. In using this model, I hoped to highlight the connection between the health benefits of fuel-efficient cooking technologies and women’s
49 economic advancement by showing that improved health related to ICS use could translate into increased productivity and therefore, an improvement in women’s livelihood. The idea behind this hypothesis was that women who are not consistently fighting respiratory infections are more able to participate in various activities, which is an indicator of women’s economic advancement. Despite these results, it is still important to explore the impact of ICS use women’s ability to perform work.
ICS Use and Changing Business Practices
My final model involves exploring women’s economic empowerment through the relationship between ICS use and changing business practices. In this model, a logistic regression is used to determine the likelihood of women who use improved cooking technologies participating in a secondary business. Regression results for this model are shown in Table 5 below:
Table 5: Logit Regression Model – Probability of Participating in a Secondary Business
Variable Coefficient Standard Error AME ICS 0.24*** 0.06 0.033 No NGO Assistance -1.18 0.89 -0.203 No Govt. Assistance 0.23 0.38 0.028 No Land Rented Out -0.22*** 0.02 -0.028 HH Member Attend School 0.31*** 0.02 0.040 *** indicates 99% confidence Notes: Source – IHDS 2005; Regional controls (COPC, Geographic Location, Religious affiliation not shown).
The regression results listed in Table 5 are, for the most part, consistent with my predictions about the relationship between the use of improved cookstoves and the likelihood of a woman operating or participating in a secondary business. The coefficient on my key variable of interest, ICS, is highly statistically significant (p<0.01) and reflects a positive relationship between ICS use and the probability of participating in a side business. The AME method reveals
50 that women who use improved cooking technologies are about three percentage points more likely to participate in a secondary business than women who use traditional cooking technologies. Although a three-percentage point difference in the likelihood of participating in a secondary business is not a significant result, this finding is still important in that it reflects the potential for fuel-efficient technologies to contribute to women’s economic empowerment.
Increased participation in businesses allows women to develop new skills, potentially earn an income, and influence business practices and workplace policies and all of these factors contribute to women’s economic advancement. The fuel-efficient nature of improved cookstoves allows women to have more time to dedicate to other activities and these activities may include secondary businesses, which could be income-generating opportunities.
The variables, NoLandRentOut and AttenSchool also have a statistically significant effect on the likelihood of a woman participating in a side business. The direction of these relationships is also in line with my predictions. According to AME results, the likelihood of women operating or participating in a secondary business is about four percentage points higher for women who live with, or are themselves, school-educated household than women who do not live with school-educated household members. Attending school allows for the exchange of ideas and the building of relationships and these factors may influence a woman’s decision to participate in or start up a side business. Women who have attended school, or are related to people who have, are more likely to have a better understanding and recognition of the different economic or social opportunities available in their communities, and as such, are more likely to take advantage of these opportunities. On the other hand, regression results depict an inverse relationship between renting out land and the likelihood of women participating in a secondary business. The direction of this relationship is consistent with my prediction—the likelihood of participating in a side
51 business is reduced by about three percentage points for women who live in homes that do not receive rental income. This is not a surprising finding—households that are not collecting rental income probably have fewer opportunities to invest in new ventures. Another plausible reason for this result is that households that own land are more likely to have additional resources including other valuable assets and, in some cases, extra time that can be dedicated to side projects. Households that do not have these assets are less likely to have the resources to start a new business or may not have the additional time to taken on a second job.
The findings in Table 5 support my hypothesis that ICS use can contribute to women’s changing business practices, a factor crucial for economic advancement. The decision to start a small business is a complicated matter so the low pseudo-R2 statistic and small predicted probabilities in this model are not surprising. These statistics reveal that there are unaccounted for factors that also influence a woman’s decision to join or start a new business. Despite these statistics, however, regression results reveal that ICS use has some influence on changing business practices. Without a dataset that is designed to specifically target ICS users it is difficult to conclude that ICS use is the solely responsible for any one difference but it is apparent from the models used in this analysis that the use of fuel-efficient technologies, has the potential contribute to women’s economic empowerment.
VII. CONCLUSION AND POLICY RECOMMENDATIONS
The purpose of this study was to understand how ICS use contributes to women’s economic empowerment in rural communities in India. Economic empowerment, according to the ICRW, has two components: power and agency, and the “ability to succeed and advance economically” (Golla et al., 2011). In this paper I focused on the latter component: economic
52 advancement. In this context, I hypothesized that ICS use could contribute to economic advancement by providing women the “resources to compete in markets, as well as [more] fair and equal access to economic institutions” (Golla et al., 2011). To support my hypothesis I use three different sets of regressions—one on the potential timesavings associated with ICS use, one on the likelihood of women losing productivity by being unable to work due to illness, and one on the potential for women to own or participate in a side business.
The regression results from the fuel collection models showed that ICS use has a statistically significant effect on the amount of time women and girls spend collecting fuel.
While my results did show a timesavings benefit, it is not possible to conclude from this analysis that the time saved per week is spent on socially or economically productive activities.
Nonetheless, having additional time to devote to anything other than backbreaking biomass drudgery is significant for women’s economic empowerment. Women and girls in the developing world “bear a disproportionate burden of household and family responsibilities, such as cooking, cleaning, and fetching fuel or water, as well as child and elder care” (Gill et al.,
2010). As a result of these heavy burdens, women and girls have little to no time to further their own desires and interests. Time is a valuable resource that women need for economic advancement. The use of technologies that improve timesavings is therefore important because it allows women to have additional time to devote to other activities—activities that can contribute to economic empowerment.
In my second empirical model, I proposed that the health benefits of ICS use could be translated into economic benefits—specifically, women’s productivity. My prediction for this model, based on studies of the health benefits of ICS technologies, was that because ICS users generally have lower exposure to harmful IAP and are less likely to have debilitating respiratory
53 infections, they are less likely to miss work due to illness. My regression results showed that ICS use does not have a statistically significant effect on the likelihood of women losing productivity by being unable to work. Missing observations in my data set and omitting relevant variables, because they were unreliable, from my model may have contributed to the lack of statistical significance for my key variable of interest. Data on women who use ICS technologies is also scarce and could be another attributing factor to the lack of statistical significance. Many fuel- efficient technology programs are still in their infancy, and much of the data that has been collected is specific to the health or environmental benefits of ICS use, not economic or social benefits. Additionally, most available data is not disaggregated by gender, meaning we are still relatively uninformed about how energy development programs affect women specifically. To assess the connection between ICS use and women’s economic empowerment, I employed the use of a general dataset with some information on households that used improved chulhas. The
IHDS surveyors did not specifically collect data on ICS, target users of fuel-efficient technologies, or observe ICS users before and after the implementation of the development program. Despite this outcome, I still believe there is a link between health benefits of ICS technologies and women’s participation in non-household activities. Women who are unable to participate in everyday activities due to illness are unable to earn an income and cannot gain independence or advance economically. The inability to earn furthers the gender gap in the developing world and perpetuates the cycle of poverty. This issue underscores the importance of collecting more expansive information on the impact of sustainable development programs.
In my final regression, I explored the influence of ICS technology on changing business practices by measuring the relationship between ICS use and the likelihood of women operating or participating in secondary businesses. Participating in economic endeavors gives women the
54 opportunity to gain new skills, earn an income, and influence work place policies. These outcomes contribute to changing business practices and economic empowerment. Regression results for this model revealed that ICS use has a statistically significant and, as predicted, a positive effect on the likelihood of women’s participation in a side business. In my model, using improved chulhas increases the likelihood of women participating in a side business by three percentage points. A woman’s decision to participate in or start a small business usually requires the consideration of many obstacles including asking for permission from family members, securing investment seed money, and rearranging the management of household responsibilities.
These and many other factors that complicate the process of starting a side business are difficult to quantify and are therefore not captured in my model, which could explain why my results did not show a stronger relationship. Despite the omission of these factors and my use of a broad and generalized dataset, my model did show that the use of ICS technologies increases the likelihood of women participating in a side business. In addition, the timesavings shown in my first set of regressions reduced some of the burden of household responsibilities for women, which may relieve some of the pressures women face when deciding whether or not to participate in a side business.
The purpose of this study is to contribute to the growing body of work on the benefits of
ICS development programs and the movement to engender sustainable energy development programs. According to a report released by the WHO in March 2014, about 4.3 million people a year die prematurely from household air pollution-related illnesses (World Health Organization,
2014). The heavy soot produced by burning wood, crop residue, and dung used for heating and cooking in many middle- and low-income countries is the main cause for many of these illnesses.
To combat this problem, development organizations and government agencies should increase
55 their efforts to promote policies that encourage the use of clean cooking and heating technologies and reduce dependence on biomass. One such policy should be the expansion of development projects that produce and promote fuel-efficient cooking technologies. As demonstrated in this thesis and in many other studies on ICS use, improved cooking technologies can yield time- and cost-savings benefits that are especially significant for women, who often bear the burden of the majority of household responsibilities. If clean cooking policies are to be successful, they must target women specifically. Because of their position as the managers of their households, women are the main users of these technologies and can play an integral part in increasing awareness and demand for clean cooking technologies (Global Alliance for Clean Cookstoves, n.d., b.).
To enhance the adoption of clean cooking technologies, development agencies should increase efforts to educate women about the benefits of ICS use. Because women are the primary users of these technologies, ICS development strategies must incorporate women’s needs and preferences into their design and education efforts. This includes designing cookstoves that are easy to use and minimizing the differences in food taste between traditional and improved stoves. In addition, in order to encourage women to abandon the use of traditional cooking methods that have been passed down through generations and adopt improved cooking technologies, agencies must provide women with sufficient information on the benefits of improved cooking technologies. This information should include details about the potential health and economic benefits of ICS use for women and their families. Furthermore, ICS promotion agents must be readily available to educate women about the proper use of clean cookstoves and to assist with follow up questions, as many improved cookstoves require regular maintenance and upkeep. For the successful adoption of clean cookstove programs, ICS development groups must raise more awareness among women users about their programs and
56 the potential health, social, and economic gains that can contribute to the improvement in gender equality and the eventual reduction or eradication of poverty.
In order to better target women, development agencies need more accurate and representative data on women’s needs and preferences. Unfortunately, very little quantitative information is currently available on how women use improved cooking technologies in the developing world, and there is even less information on the social and economic impact of ICS use on the lives of female users of these technologies. Data on successful and unsuccessful technology interventions is necessary for sustainable development and the eradication of poverty.
Without these data, we are unable to differentiate successes from failures and cannot systematically formulate effective policy.
One of the reasons we lack sufficient data on technology and women’s economic empowerment is the gender-neutral approach to sustainable energy programs. Because of this gender-neutral outlook, many development agencies have failed to incorporate different user styles and preferences into the design and implementation of their programs. What many development organizations are learning is that women will not use clean cooking technologies that do not suit the needs and preferences. Failure to incorporate gender preferences in energy development is an obstacle in the eradication global poverty. For successful global development and the eradication of poverty, women’s needs should be incorporated into the design and implementation phases of development projects.
To accurately assess women’s preferences, ICS development organizations should conduct follow-up studies evaluating the impact of interventions on a regular basis and the data collected from these studies should be stored in a centralized database that is accessible to all development organizations. Having access to a central data source where information on
57
“technology impacts[,] fuel use, emissions, durability[,] and safety [is readily available] will allow consumers to make more informed choices, spur manufacturers to build higher quality stoves, and increase the level of overall investment in the [fuel-efficient cooking technology] sector” (Global Alliance for Clean Cookstoves, n.d.,a.). Furthermore, following these steps will allow scientists, engineers, and global development professionals to learn from each other’s successes and mistakes.
The failure to incorporate gender in energy development programs also contributes to the lack of information on potential economic benefits and/or improved living standards that may result from these programs. This is why “[m]any existing technologies had the potential to benefit women but, for a host of reasons, were never embraced or adopted” (Gill et al., 2010). If policies that promote clean cooking methods and the use of less polluting fuels are not implemented, billions of people will continue to rely on these harmful fuels and millions will continue to die from respiratory diseases. According to my analysis, these policies can only be implemented successfully if they focus on women’s needs.
The analysis in this paper attempts to establish the influence of the use of fuel-efficient cooking technologies on women’s economic empowerment. Results from my regression analyses reveal that ICS use can reduce the amount of time women and girls spend foraging for biomass and increase the likelihood of women participating in activities outside of the domestic domain.
While these findings are based on a broad dataset that is not focused on Indian ICS users, I still found statistically significant relationships between my variables of interest. My analysis shows promise that in addition to health and environmental benefits, fuel-efficient cooking technologies can also have social and economic impacts that are especially beneficial to women. More targeted field-testing and program evaluation studies are needed to further explore this
58 relationship. It was not my intention in this study to prove that improved cooking technologies are the only contributing factor to women’s economic empowerment. Instead I hoped to show that energy development programs can yield social and economic benefits that have the potential to improve the lives of women. To unlock this potential and create successful development policies and programs, ultimately we need more data. My study shows that we are on the right track, and with reliable data and robust analysis we can formulate policies and programs that actually solve the problems we hope to fix. Ultimately, these solutions will lead to better the lives of millions (if not billions) of women and girls around the globe.
59
References
Akbar, Sameer, Douglas F. Barnes, Andrew Eil, and Anastasia Gnezditskaia. (2011). Household Cookstoves, Environment, Health, and Climate Change: A New Look at an Old Problem. The World Bank, Environment Department. Retrieved from http://climatechange.worldbank.org/sites/default/files/documents/Household%20Cookstoves-web.pdf.
Ayoub, Josef and Eric Brunet. (1996). Performance of Large Portable Metal Woodstoves from Community Kitchens. Renewable Energy 7(1), 71-80. Retrieved from http://www.sciencedirect.com/science/article/pii/0960148195001077#.
Barnes, Douglas, F., Priti Kumar, and Keith Openshaw. (2012). Cleaner Hearths, Better homes, New Stoves for India and the Developing World. Oxford University Press. Retrieved from http://www.esmap.org/sites/esmap.org/files/Cleaner%20Hearths,%20Better%20Homes_Book_Small.pdf.
Cecelski, Elizabeth. (2000a). Enabling Equitable Access to Rural Electrification: Current Thinking and Major Activities in Energy, Poverty and Gender [Briefing Paper for the World Bank]. Retrieved from http://www.sarpn.org/genderenergy/resources/cecelski/energypovertygender.php.
Cecelski, Elizabeth. (2000b). The Role of Women in Sustainable Energy Development [Subcontractor report for the National Renewable Energy Laboratory]. Retrieved from http://www.nrel.gov/docs/fy00osti/26889.pdf
Clark, Maggie, L., Stephen J. Reynolds, James B. Burch, Stuart Conway, Anette M. Bachand, and Jennifer L. Peel. (2010). Indoor air pollution, cookstove quality, and housing characteristics in two Honduran communities. Environmental Research 110(1), 12-18. doi: 10.1016/j.envres.2009.10.008.
Dasgupta, Susmita, Mainul Huq, M. Khaliquzzaman, Kiran Pandey, David Wheeler. (2004). Indoor Air Quality for Poor Families [Working Paper No. 3393 for the World Bank]. Retrieved from http://elibrary.worldbank.org/doi/pdf/10.1596/1813-9450-3393.
Desai, Sonalde, Amaresh Dubey, B.L. Joshi, Mitali Sen, Shariff, Abusaleh, and Reeve Vanneman. (2005). India Human Development Survey (IHDS) [Data file]. Retrieved from doi:10.3886/ICPSR22626.v8.
Desai, Sonalde, Amaresh Dubey, B.L. Joshi, Mitali Sen, Shariff, Abusaleh, and Reeve Vanneman. (2008). India Human Development Survey (IHDS) Documentation, Release 01, 2008 [Documentation report]. Retrieved from http://ihds.umd.edu/IHDS_files/ihdsdoc01.pdf.
Duflo, Esther, Michael Greenstone, and Rema Hanna. (2008). Indoor Air Pollution, Health and Economic Well- Being. Surveys and Perspectives Integrating Environment and Society (S.A.P.I.E.N.S) 1(1). Retrieved from http://economics.mit.edu/files/2375.
ENERGIA International Network on Gender and Sustainable Energy. (n.d.). Why Gender and Energy? Retrieved from http://www.energia.org/who-we-are/why-gender-energy/.
Ezzati, Majid, Alan D. Lopez, Anthony Rodgers, and Christopher J.L. Murray. (2004). Comparative Quantification of Health Risks Global and Regional Burden of Disease Attributable to Selected Major Risk Factors [Report for the World Health Organization (WHO)]. Retrieved from http://www.who.int/healthinfo/global_burden_disease/cra/en/.
Galitsky, Christina, Ashok Gadgil, Mark Jacobs, and Yoo-Mi Lee. (2006). Fuel Efficient Stoves for Darfur campus of Internally Displaced Person Report of Field trip to North and South Darfur [Report for the Ernest Orlando Lawrence Berkeley National Laboratory, University of California, Berkeley]. Retrieved from http://eetd.lbl.gov/node/49399.
60
Garcia-Frapolli, Eduardo, Astrid Schillmann, Victor M. Berrueta, Horacio Riojas-Rodriguez, Rufus D. Edwards, Michael Johnson, Alejandro Guevara-Sangines, Cynthia Armendariz, and Omar Masera. (2010). Beyond fuelwood savings: Valuing the economic benefits of introducing improved biomass cookstoves in the Purepecha region of Mexico. Ecological Economics 69(12), 2598-2605. doi: 10.1016/j.ecolecon.2010.08.004.
Gifford, Mary Louise (2010). A Global Review of Cookstove Programs. Retrieved from University of California, Berkeley, College of Engineering, Electrical Engineering and Computer Science (EECS) http://www.eecs.berkeley.edu/~sburden/misc/mlgifford_ms_thesis.pdf.
Gill, Kirrin, Kim Brooks, Janna McDougall, Payal Patel, and Aslihan Kes. (2010). Bridging the Gender Divide: How Technology Can Advance Women Economically [Report for the International Center for Research on Women (ICRW)]. Retrieved from http://www.icrw.org/publications/bridging-gender-divide.
Global Alliance for Clean Cookstoves. (n.d.,a.). Priorities Driving Global Change: Promote International Standards. Retrieved from http://www.cleancookstoves.org/our-work/the-issues/women-and-livelihood.html.
Global Alliance for Clean Cookstoves. (n.d.,b.). The Issues: Women & Livelihoods. Retrieved from http://www.cleancookstoves.org/our-work/the-issues/women-and-livelihood.html.
Golla, Anne Marie, Anju Malhotra, Priya Nanda, and Rekha Mehra. (2011). Understanding and Measuring Women’s Economic Empowerment: Definition, Framework and Indicators [Report for ICRW]. Retrieved from http://www.icrw.org/files/publications/Understanding-measuring-womens-economic- empowerment.pdf.
Hanbar, R.D. and Priyadarshini Karve. (2002). National Programme on Improved Chulha (NPIC) of the Government of India: an overview. Energy for Sustainable Development 6(2), 49-55 doi: 10.1016/S0973-0826(08)60313-0.
Holmes, Michelle, Setsu (2010). Potential Effects of Improved Cookstove Use and Barriers to Acceptance: A Case Study Measkron, Tanzania. Retrieved from Evergreen State College Olympia http://archives.evergreen.edu/masterstheses/Accession86-10MES/Holmes_MSMESThesis2010.pdf.
International Energy Agency (IEA). (2008). World Energy Outlook 2008. Retrieved from http://www.worldenergyoutlook.org/media/weowebsite/2008-1994/WEO2008.pdf.
International Institute for Population Sciences (IIPS) and Macro International. (2007). National Family Health Survey (NFHS-3), 2005-06: India Vol.1. Retrieved from http://www.measuredhs.com/pubs/pdf/FRIND3/FRIND3-Vol1AndVol2.pdf.
Johnson, Michael, A., Veronica Pilco, Rafael Torres, Sandeep Joshi, Rajeev M. Shreshta, Mahesh Yagnaraman,… David Pennise. (2013). Impacts on household fuel consumption from biomass stove programs in India, Nepal, and Peru. Energy for Sustainable Development 17(5), 403-411. doi: 10.1016/j.esd.2013.04.004.
Kumar, Major, Sachin Kumar, and S.K. Tyagi. (2013). Design, development and technological advancement in the biomass cookstoves: A review. Renewable and Sustainable Energy Reviews 26, 265-285. doi: 10.1016/j.rser.2013.05.010.
Lambe, Fiona and Aaron Atteridge. (2012). Putting the Cook Before the Stove: a User-Centered Approach to Understanding Household Energy Decision-Making A Case Study of Haryana State, Northern India [Working Paper No. 2012-03 for the Stockholm Environment Institute]. Retrieved from http://www.sei- international.org/mediamanager/documents/Publications/Atmospheric/sei-wp-2012-03-cookstoves.pdf.
61
Legros, Gwénaëlle, Ines Havet, Nigel Bruce, and Sophie Bonjour. (2009). The Energy Access Situation in Developing Countries: A Review Focusing on the Least Developed Countries and Sub-Saharan Africa [Report for the United Nations Development Programme (UNDP)]. Retrieved from www.undp.org/energyandenvironment.
MacCarty, Nordica, Dean Still, Damon Ogle, and Thomas Drouin. (2008). Assessing Cook Stove Performance: Field and Lab Studies of Three Rocket Stoves Comparing the Open Fire and Traditional Stoves in Tamil Nadu, India on Measures of Time to Cook, Fuel Use, Total Emissions, and Indoor Air Pollution [Report for the Aprovecho Institute]. Retrieved from http://www.aprovecho.org/lab/rad/rl/perf-stud/category/20.
Malinksi, Britta. (2008). Impact Assessment of Chitetezo Mbaula Improved Household Firewood Stove in Rural Malawi [Report for the Deutsche Gesellschaft für Technische Zusammenarbeit (GTZ) GmbH Programme for Basic Energy and Conservation (ProBEC)]. Retrieved from http://www.probec.net/fileuploads/fl09222008074344_Impact_Assessment_of_Chitetezo_Mbaula_Improv ed_Household_Firewood_Stove_in_Rural_Malawi.pdf.
Manibog, Fernando, R. (1984). Improved Cooking Stoves in Developing Countries: Problems and Opportunities. Annual Review of Energy 9, 199-227. doi: 10.1146/annurev.eg.09.110184.001215.
Manuel, John. (2003). The Quest for Fire: Hazards of a Daily Struggle. Environmental Health Perspectives 111(1) , 28-33. Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1241326/pdf/ehp0111-a00028.pdf.
Modi, Vijay, Susan McDade, Dominique Lallement, Jamal Saghir. (2005). Energy Services for the Millennium Development Goals: Achieving the Millennium Development Goals [Report for the World Bank and the United Nations Development Programme]. Retrieved from http://www.unmillenniumproject.org/documents/MP_Energy_Low_Res.pdf
Parikh Jyoti, K. (1995). Gender issues in energy policy. Energy Policy 23(9), 745-754. doi: 10.1016/0301-4215(95)00056-O.
Patrick, Erin. (2007). Sexual violence and firewood collection in Darfur. Forced Migration Review 27, 40-42. doi: 10.1001/jama.2012.9733.
Pitt, Mark, M., Mark R. Rosenzwieg, and Md. Nazmul Hassan. (2005). Sharing the Burden of Disease: Gender, the Household Division of Labor and the Health Effects of Indoor Air Pollution [Working paper no. 093 for the Bureau for Research and Economic Analysis of Development, Duke University]. Retrieved from http://ipl.econ.duke.edu/bread/papers/working/093.pdf.
Sinha, Bhaskar. (2002). The Indian stove programme: an insider’s view – the role of society, politics, economics and education. Boiling Point 48, 23-26. Retrieved from http://practicalaction.org/docs/energy/docs48/bp48_pp23-26.pdf.
Smith, Kirk, R., R. Uma, V.V.N. Kishore, Junfeng Zhang, V. Joshi, and M.A.K. Khalil. (2000). Greenhouse Implications of Household Stoves: An Analysis for India. Annual Review of Energy and the Environment 25, 741-763. doi: 0.1146/annurev.energy.25.1.741.
Smith, Kirk. National Burden of Disease in India from Indoor Air Pollution. (2000). Proceedings of the National Academy of Sciences (PNAS) 97(24), 13286 –13293. Retrieved from http://www.pnas.org/content/97/24/13286.full.pdf
Stata. (n.d.). Margins – Marginal means, predictive margins, and marginal effects. Retrieved from http://www.stata.com/manuals13/rmargins.pdf.
62
The Economist. (n.d.). Economics A-Z: Terms beginning with S. Retrieved from http://www.economist.com/economics-a-to-z/s#node-21529673.
UNICEF, United Nations Children’s Fund. (2014). All Children in School by 2015: Global Initiative on Out-of- School Children South Asia Regional Study Covering Bangladesh, India, Pakistan, and Sri Lanka. UNICEF, United Nations Children’s Fund. Retrieved from http://www.uis.unesco.org/Education/Documents/OOSCI%20Reports/oosc-south-asia-regional-report.pdf.
Venkataraman, C., A.D. Sagar, G. Habib, N. Lam, and K.R. Smith. (2010). The Indian National Initiative for Advanced Biomass Cookstoves: The benefits of clean combustion. Energy for Sustainable Development 14(2), 63-72. doi: 10.1016/j.esd.2010.04.005.
Wickramasinghe, Anoja.(2003). Gender and health issues in the biomass energy cycle: impediments to sustainable development. Energy for Sustainable Development 7(3), 51–61. doi: 10.1016/S0973-0826(08)60365-8.
World Bank. (2011). Household Cookstoves, Environment, Healthy, and Climate Change - A New Look at an Old Problem. Retrieved from http://climatechange.worldbank.org/sites/default/files/documents/Household%20Cookstoves-web.pdf.
World Health Organization (WHO). (2005). World Health Report: 2005: Make Every Mother and Child Count. Retrieved from http://www.who.int/whr/2005/whr2005_en.pdf.
World Health Organization (WHO). (2014). Household air pollution and health [Media Fact Sheet]. Retrieved from http://www.who.int/mediacentre/factsheets/fs292/en/.
Zhang, Yabei. (2009). Household Energy use, Indoor Air Pollution, and Health Impacts in India: A Welfare Analysis. Retrieved from ProQuest Dissertations and Theses http://udini.proquest.com/view/household- energy-use-indoor-air-pqid:1974971421/.
63