Understanding the factors that influence household use of clean energy in the Similipal Tiger Reserve, India

June 9, 2018 | Author: Madhusmita Dash | Category: Documents


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Natural Resources Forum 42 (2018) 3–18

DOI: 10.1111/1477-8947.12140

Understanding the factors that influence household use of clean energy in the Similipal Tiger Reserve, India Madhusmita Dash, Bhagirath Behera and Dil Bahadur Rahut Abstract Biotic pressure in and around protected areas (PA) is the primary cause of biodiversity loss in many developing countries across the globe. The pressure comes partly from biomass energy dependency in the form of heavy extraction of fuelwood from the forests. Although biomass fuels provide easily accessible and affordable sources of domestic energy to the rural masses, their combustion results in environmental and health-related hazards. The objectives of this paper are to assess the patterns of household energy use in a subsistence forest economy and analyze the factors that influence their energy use choice for cooking and lighting. The paper uses primary data collected randomly from 244 households located in and around the Similipal Tiger Reserve (STR), situated in the eastern Indian state of Odisha. Age of the household head, number of days in wage employment, number of adult males and females in a household, education of the household head and landholding size are found to be the major variables that determine household fuelwood collection sources inside the reserve. Considering household structure as an income indicator, the analysis clearly shows that non-poor households prefer to use clean energy (i.e. solar) for lighting, while poor households tend to use solid fuel. Energy policies for development should be based on the realistic proposition that fuelwood will remain the major source of energy for cooking for substantial proportions of the world’s population. Promotion of public education, social forestry schemes and fuel-efficient improved chulhas should be encouraged in order to reduce household dependence on fuelwood. Moreover, devolving sufficient property rights over forest resources to local communities may help secure their broad-based and active participation in the decision-making process, which may result in a positive change in the attitude of the local people towards biodiversity conservation. Keywords: Biomass; clean energy; gender; education; cooking; lighting.

1. Introduction Conservation of biodiversity in the form of protected areas (PA) is an important policy agenda for natural resource management, particularly in developing countries. Biotic pressure in and around PAs is one of the major factors affecting biodiversity conservation. It has been argued that in a subsistence economy, people depend more on the natural environment due to economic compulsion arising out of poverty (Ekholm et al., 2010). The pressure comes mostly from energy dependency in the form of biomass use Madhusmita Dash is at Sri Sri University, Department of Management Studies, Cuttack, Odisha, India. E-mail: [email protected] Bhagirath Behera is at the Indian Institute of Technology Kharagpur, Department of Humanities and Social Sciences, Kharagpur, West Bengal, India. E-mail: [email protected] Dil Bahadur Rahut, Socioeconomics Program, International Maize and Wheat Improvement Center (CIMMYT), El Batan, Texcoco, Mexico CP 56130. E-mail: [email protected] © 2018 The Authors. Natural Resources Forum © 2018 United Nations

(Heltberg et al., 2000). Although biomass fuels provide easily accessible and affordable sources of domestic energy to rural households, their unsustainable use poses numerous environmental and health-related hazards (Heltberg, 2001; Ekholm et al., 2010; WHO, 2014). Literature explains the two-way relationship between fuelwood collection and deforestation (Heltberg et al., 2000; Heltberg, 2001). Demand for fuelwood from village commons and forests is the prime cause of forest degradation, and fuelwood scarcity is the result of the perpetuation of forest degradation (Heltberg et al., 2000; Rahut et al., 2016). There are several other adverse impacts of forest degradation, such as damage to biodiversity, degradation of watershed management functions, discharge of carbon dioxide, soil erosion, etc. Although not long-term solutions, alternative sources of domestic energy such as animal excrement, crop residues, fuelwood from farms, biogas, kerosene oil and the use of improved stoves, etc. do not cause forest degradation, and in turn reduce

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pressure on the forest area. However, alternate energy sources that are clean and user-friendly involve both financial and opportunity costs.1 In addition to environmental consequences, indoor air pollution from combustion of solid biomass fuels (such as fuelwood, crop residue, cow dung, etc.) for cooking and heating has emerged as an important risk factor in the pathogenesis, morbidity and mortality from chronic respiratory diseases such as chronic bronchitis (CB), chronic obstructive pulmonary disease (COPD), asthma, tuberculosis, cataracts, etc. (Heltberg, 2005; WHO, 2014). Apart from the environmental and health hazards, several social and economic problems are associated with the use of biofuels, particularly in inefficient ways.2 The dire effects of overuse of biomass are often serious for the most vulnerable people in a community, i.e. women, children, and low-income groups (Heltberg et al., 2000; Heltberg, 2001). The scarcity of fuelwood has increased the time burden, especially for women who are traditionally responsible for collecting fuelwood for domestic purposes.3 With the increase in scarcity of fuelwood, women and girls have to walk many miles daily to collect only a head load of fuelwood. This has often resulted in the increase in school dropout rate among the girls (Heltberg, 2005). Even the time burden associated with the collection of fuelwood tends to increase for women when men migrate to urban areas in search for employment (Ishaya et al., 2009). Numerous studies argue that institutions (both formal and informal) at the local level play a vital role in forest resource conservation (Agrawal and Chhatre, 2006; Behera, 2009; Dash and Behera, 2015). The objective is to promote local communities’ active involvement in the management of natural resources since they have some comparative advantage over the state, specifically with respect to monitoring, enforcement, and adaptation to local conditions (Dash and Behera, 2015). While studies have highlighted that the recent destruction of natural resources and the resultant biodiversity loss can be strongly attributed to a lack of a well-defined and secure system of property rights4 (Heltberg, 2001), literature on common property resource management emphasizes the ability of user communities to effectively manage collectively-owned 1 In many South Asian and African countries, animal dung is used not only as fuel, but also as a primary source of manure, and the use of it as fuel can have an adverse impact on soil fertility (Amacher et al., 1999; Heltberg et al., 2000). 2 Inefficient use of biomass implies practices of biomass use and not the biomass itself. It means using cooking devices with high biomass consumption, low per-unit energy production, and increased emissions of smoke and particulate matter (Karekezi et al., 2005). 3 A study conducted by the United Nations reveals that almost 80% of total rural women aged 10–60 years are affected by fuelwood scarcity in India (UN, 2015). 4 Property rights are defined as the legal expression of the guarantee of access to a benefit stream in the context of a given legal, political and social order (Gerber, 2009).

natural resources through informal institutional arrangements (Dash and Behera, 2015). It is found that the share of population that relies on the traditional use of biomass is highest in sub-Saharan Africa and India (World Energy Outlook, 2008). As per the 2011 census, almost 85% of rural households in India are dependent on traditional biomass fuels for their cooking energy requirements. Further, the National Sample Survey Organization (NSSO), in its 55th, 61st and 66th Round Reports, further supports the fact that there has been an increase in biomass fuel use in terms of absolute consumption over the past decade among rural households in India. The recent unveiling of the Sustainable Development Goals (SDGs) has emphasized on the diminution in household biomass fuel use and ensures universal access to affordable, reliable and modern energy services by 2030 (UN, 2016). Recently, non-conventional renewable energies are proven to be more efficient in bridging the rural-urban energy gap while making the development process more inclusive and sustainable (Kirubi et al., 2009). It is increasingly recognized that the use of renewable energies that condense the dependency on conventional grid electricity is crucial for the conservation of natural resources and protection of the environment.5 Among the copious sources of renewable energy, such as biomass, solar, hydro and wind, solar energy is considered to be superior due to its free and continuous flow (Palit, 2013). The literature is replete with cases where solar electrification has uplifted the socioeconomic conditions of the rural poor and contributed to greenhouse gas mitigation from the use of kerosene (Mahapatra and Dasappa, 2012; Palit, 2013). It is reported that solar electricity lighting in remote rural schools allows children to extend their study hours in the evening and helps to retain teachers in school for longer time (UNDP, 2004). Moreover, the increasing incidence of humanwildlife conflicts in the inhabited areas of tiger buffer zones and corridor areas can be brought under control with solar electrification in the concerned villages (Dash and Behera, 2012). However, there exist a number of constraints that limit the spread of solar electrification into the non-electrified forest areas of developing countries (Mishra and Behera, 2016). Some of these constraints are lack of markets for solar energy, inadequate access to institutional credit or subsidies for poor households, lack of awareness and confidence on the part of the marginalized consumers and unavailability of efficient service providers. Nevertheless, it has also been observed that in many areas where alternative energy sources are apparently available, many households still continue to use solid fuels, mostly fuelwood, for cooking (Heltberg, 2005). 5

Globally, strategies on climate protection call for greater use of renewable energies such as solar power to conserve critical natural resources, reduce greenhouse gas emissions and contribute to sustainable development (Palit, 2013). © 2018 The Authors. Natural Resources Forum © 2018 United Nations

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Figure 1. The energy transition process. Source: Hedges and Enters (2000).

The issues discussed above raise a few important questions. First, which energy sources do people use at the household level, and why do they choose those sources? Second, does unsustainable extraction of fuelwood result in forest degradation? Third, are the communities fully aware of the fuelwood scarcity issue? And last, why the households in many forest-dependent economies are not willing to switch from traditional energy sources to clean energy? Or more precisely, which factors predict household energy choice behaviour in a forest-dependent economy? The analysis will be useful in crafting and executing suitable conservation policies by understanding households’ needs, livelihood strategies and dependency on forest resources. This paper begins with a theoretical framework on the expected determinants of household energy preference, followed by a brief description of the study area and the database used. This is followed by an analysis of the empirical data by inferring the results from a multinomial logit choice model. Finally, the paper draws conclusions and policy implications.

2. Theoretical framework The fact that a household chooses one or more energy source depends on the interaction of a number of factors that influence household energy demand (Leach, 1992). Such factors, as recorded in much of the literature, consist of disposable household income, age, gender composition, gender of the household head, education, occupation, marital status, household size, number of children, location, availability of fuel alternatives and accessibility, wage level in the labour market, house type and access to energy carriers (Rahut et al., 2014; Behera et al., 2015). In most of the earlier research, household income and consumption are used as the common determinants, followed by the ground-breaking study by Leach (1992) that introduces the concept of the “energy ladder hypotheses” © 2018 The Authors. Natural Resources Forum © 2018 United Nations

(Figure 1). It demonstrates the relationship between income and types of energy used by the households. It postulates that in response to an increase in income and changes in other socio-economic characteristics, families will move from traditional biomass and other solid fuels to transitional, more modern and efficient cooking fuels such as kerosene, LPG, natural gas, solar or electricity (Leach, 1992). However, the energy model has been criticized because of its major focus on the income factor in explaining household fuel choices. The critics argue that in addition to income, the opportunity costs of fuelwood collection also need to be considered in shaping the demand for all fuels (Heltberg, 2005; World Bank, 2003). Other than income, wealth, the demographic composition, economic status, caste, gender, and age of the household head, education level and religious affiliations of its members are likely to affect the household’s principal activity related to energy (Hedge and Enters, 2000). Caste plays an important role in India in shaping each person’s type of employment (ibid). However, recently the household energy choice is explained as a portfolio choice rather than as a ladder process, which is called “energy stacking” (Figure 1). The model states that households do not simply shift to a new modern and efficient fuel as income rises, but are likely to continue using more than one fuel (Masera et al., 2000; Sclag and Zuzarte, 2008). The energy transition is a bidirectional process, as users can go up or down the ladder and continue using traditional fuels (Masera et al., 2000). Education presents better employment opportunities for people, consequently shifting them away from farming and other subsistence livelihood activities (Hedges and Enters, 2000). The higher social status of the educated person may restrict their direct involvement in energy-dependent activities, such as fuelwood gathering, since they can afford a modern lifestyle. Therefore, it is hypothesized that in this context, dependence on low-quality energy is inversely associated with the level of the education of the household

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members. Households with an educated head and/or spouse tend to choose cleaner energy because of the convenience of use, health benefits and the opportunity cost of their labour (Behera et al., 2015). Household energy consumption generally shifts from traditional biomass fuel to clean fuel with an increase in household wealth (Toman and Jemelkova, 2003), which is often measured by farm size or livestock ownership in a rural economy (Khandker et al., 2012). Therefore, an increase in farm size and income from agricultural production results in a reduction in the gathering of fuelwood from the forest and a household switch to higher-quality energy sources. In rural Africa, livestock acquisition remains a key form of wealth accumulation (Fisher, 2004). Culturally, in most parts of the world, women are responsible for cooking and hence, responsible for the collection of fuelwood (Behera et al., 2015). Therefore, it is assumed that they have a strong interest in cleaner and more convenient energy sources (Behera et al., 2015). In the rural households of India, female members are more engaged in collecting fuelwood from the forests than are the male members, who are more associated with agriculture, wage earning, and in other non-farm employment activities (Dash and Behera, 2013). The presence of a high number of women in the household increases available labour for gathering fuelwood and cooking, which reduces the probability of the household in engaging in less timeconsuming sources of energy (Dash and Behera, 2013). However, having children under six-years old reduces a household’s use of fuelwood, perhaps because there is less time available for wood collection because more time is needed for childcare (Rahut et al., 2014). Moreover, the role of female members of the household ranges from gathering fuel at low-income levels to making decisions about the choice of fuel at higher-income levels (Fisher, 2004). With the use of cleaner sources of energy, female members of the households have superior health and more leisure and family time; hence, when a female member of the household is the principal decision-maker, great importance will be placed on goods that offer higher convenience to the female members of the household (Rahut et al., 2014). Family size has a positive influence on the collection of fuelwood, both because of an increased demand for energy and an augmented labour supply for fuelwood gathering and other activities in rural areas (Dash and Behera, 2013; Behera et al., 2015). The number of members in the household positively affects the use of fuelwood and selfcollected fuels because the collection does not include any financial cost. However, their collection and usage are guided by the relative opportunity costs that depend on the productivity of labour in fuelwood gathering in relation to the time spent in alternative employment (Khandker et al., 2012). Therefore, if a household member has a potentially better employment option, the cost of collecting fuelwood would mean forgoing the income from other employment.

Whether or not the age of the household head has a positive or negative influence on the decision to adopt clean energy cannot be determined a priori (Bekele and Drake, 2003). While it is argued that old age can be equated with a higher economic status and therefore a greater ability to afford clean energy, it is also assumed that the older generation is less likely to accept innovation (Walekhwa et al., 2009). They are more risk-averse and not ready to experiment with new ideas (Adesina and Baidu-Forson, 1995). Microeconomic theory suggests a range of factors that influences household energy use and choice. Household income is one of the important parameters that influences the choice of energy use. However, the relationship between household income and energy choice remains ambiguous in nature. While studies reveal that with the increase in household income an energy transition process happens whereby households move from low-quality traditional fuels to more convenient and cleaner modern fuels (Bruce et al., 2000), several studies find that some higherincome households do not make the energy transition and try to consume clean fuels along with traditional fuels (Masera et al., 2000; Nansaior, 2011). Therefore, it is important to consider other factors like household landholding possessions, asset holdings, education and other socio-economic factors. Therefore, in such circumstances, other variables like household land/livestock/asset possession, household construction type (kuchcha/pucca) and whether a household is below poverty line (BPL) or nonBPL are considered to be better indicators than income when examining one household’s economic condition (Sehjpal et al., 2014). However, all of the factors that may hold true in the regions where studies are carried out are location-specific. Based on the above conceptual framework, the empirical evidence and the availability of data, the above-mentioned factors were analyzed in a forest economy to assess their effect on the choice of fuel for cooking and lighting.

3. Methodology 3.1. Study area description The Similipal Tiger Reserve (STR) is situated in Mayurbhanj district of Odisha between 85 580 to 86 420 E longitude and 21 100 to 22 120 N latitude in the province of Chota Nagpur plateau Deccan Peninsula (Figure 2). Once the hunting place of the king of Mayurbhanj, Similipal was first ruled by two royal families, the “Mayuras” and the “Bhanjas”, until 1361. In 1400 the area was named “Mayurbhanj” for the first two royal families. The STR was formally designated as a “Tiger Reserve” in 1956, and was included under the national flagship conservation programme “Project Tiger” in 1973 in order to save the Indian tiger from extinction. The Indian Wildlife (Protection) Act, 1972 was implemented in the state in August 1974, and a © 2018 The Authors. Natural Resources Forum © 2018 United Nations

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Figure 2. Map of Similipal Tiger Reserve. Source: Official Website of Wildlife Protection Society of India. Retrieved from http://www.wpsi-india.org/tiger/simlipal.php on 22 October 2015.

separate wildlife wing within the state forest department was created in June 1976. The state government declared Similipal as a wildlife sanctuary in 1979, with a designated area of 2,750 sq. km. The sanctuary has a “core area” (1,194.75 sq. km), which has been accorded national park status by the state government, without a final notification by the central government due to the non-eviction of all villages from the designated park zone. The “buffer zone” (1,555.25 sq. km) surrounds the core zone, and human activities and resource uses are managed in a way that reduces pressure on the core zone. The STR, along with a “transitional area” of 2,250 sq. km, was declared a Biosphere Reserve in 1994, and incorporated in the UNESCO world network of biosphere reserves in 2009. Since the reserve has been declared as a biosphere reserve, a wildlife sanctuary and a designated national park, having two central flagship conservation programmes (i.e. “Project Tiger” and “Project Elephant’) the STR is a rare protected area. The entire forest of Similipal falls under one of the Schedule V category (tribal sub-plan area) of the state, as © 2018 The Authors. Natural Resources Forum © 2018 United Nations

the majority of forest dwellers are tribal. Similipal forest is the homeland of many tribal communities, such as the Kolha, Bhumija, Bhuyan, and Munda tribes, and some of the more primitive tribes of Odisha, such as the Birhors, Hill Khadias and Ujias. Similipal is a grand repository of indigenous knowledge pertinent to the conservation of biodiversity, ethno-botanical study and traditional ecological knowledge. Three villages6 inside the core zone and 61 villages inside the buffer zone, forming a total population of 12,500, directly depend on the STR for their daily livelihoods (STR, 2013). The intimate association and dependence of the tribal communities on the natural resources have enriched them with invaluable knowledge on bioresource utilization (Mallik, 2000). However, over the years the population of the tribal villages located inside the STR has registered phenomenal growth, which has put further biotic pressure on the tiger 6 Earlier there were four villages inside the core zone of the STR, namely – Kabatghai, Jamunagarh, Jenabil and Bakua. However, Jenabil village was relocated from the STR boundary in 2010.

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habitat (Dash and Behera, 2013).7 The high dependency of local people on the STR’s resources and their increasing activities pose a number of challenges to biodiversity conservation inside the reserve. Many local livelihood activities, such as excessive harvesting of green felled fuelwood, timber felling and smuggling, over-grazing of livestock population and Akhand Shikar (ritualistic tribal hunting for herbivores) and manmade wildfires for raising fresh grass for cattle are found to be highly unsustainable inside the STR (Dash et al., 2016). Studies highlight that notching, cutting and lopping of branches and sometimes the extraction of whole plants cause a significant decrease in the basal area, species richness, diversity and stem density (Sahoo and Dvidar, 2013; Sahoo et al., 2013). Therefore, excessive fuelwood harvesting for household use (mostly for cooking), in combination with illegal logging, results in the degradation of the forest in the STR. 3.2. Sampling procedure and data collection The study is based on primary data and information collected by the first author through a household survey. The data for the study was elicited using a structured questionnaire from a random sample of 244 households8 from 11 different villages residing in both the core and buffer areas of the STR from November 2012 to April 2013 on various indicators ranging from fuelwood collection time, source, availability of other cooking and lighting fuels, respondents’ level of education, socio-economic status, and other variables relating to household characteristics and energy consumption patterns. The village identification was based on permission received from the Office of the Field Director, STR, Odisha. The STR authority granted permission to conduct the field survey in 11 villages (two from the core and nine from the buffer zones) from the entire core and buffer villages due to the sensitive nature of the study area during the time of the field survey.9 A census survey was conducted in two core area villages since the number of households that reside in these villages is relatively small (30 and 31, respectively) compared to the buffer villages. However, the remaining households were selected using a proportionate random sampling method, i.e. 30% of the total households from each buffer village. The collected data were cross-checked by questioning other 8 A group of persons living together and taking food from a common kitchen constitutes a household (NSSO). 9 The three and a half decades of conservation efforts in the STR under Project Tiger suffered a major setback due to a series of attacks carried out by suspected left-wing extremists between 28 March 2009 and 15 April 2009 (Dash and Behera, 2012). These attacks resulted in extensive damage to important reserve-management infrastructure, including range and beat offices, anti-poaching camps, and communication networks, and badly affected the morale of reserve staff. The savage Maoist attack had not only threatened biodiversity conservation, but also reduced tourist inflow into the reserve for a long time (Dash and Behera, 2012, 2013). Although the Maoist activities are not reported at present, there is an undercurrent of left-wing activities in the fringe areas of the reserve.

respondents during conversations throughout the study period. In order to gather qualitative information, focus group discussions with different groups, including women, forest ground staff, tribes and key informant discussions with village elders and tribal leaders, were conducted on household fuelwood collection and energy consumption behaviours. Discussions with the local forest department (FD) officials, both at the local and divisional level, were held on the issues related to various aspects of the functioning of the institutions. 3.3. Socio-economic and demographic profile of sample households Socio-economic and demographic characteristics of the sampled households are presented in Table 1. Close to a quarter of the sample households are found to live in the core region of the tiger reserve. While Hindus constitute 80.82% of the sampled households, Christians account for the remaining 19.18%. A majority of the households are from the Majhi community (50.61%) followed by Kolha Hindu (30.20%), and Kolha Christians (19.8%). While a majority of the households are headed by males (94.29%), a large section of them (95.9%) are in the working age group of 21–59 years. This is important since these people bear the chief responsibility of providing sustainable livelihoods for their families. While about 79% of the respondents have no formal education, only around 17% have acquired education up to secondary level or less. Similarly, about 82% of the household heads are illiterate, whereas only 16% have education up to secondary level or less. Possibly because of the low levels of education, a significant share of the sample households are BPL card holders. Although a large section of the households (66.9%) have agricultural land up to three acres in size, household annual income is found to be less than INR26,000 for nearly 73% of the sample households. Notably, annual household income is seen to be more than INR55,000 for only a small share of the households (9.43%). The housing structure of the sample households is not encouraging. A significant share of the households (nearly 63%) still lives in dilapidated dwellings, whereas a little more than a quarter of the households live in pucca (concrete) houses. 3.4. Access to various energy sources The major energy resources in the STR are fuelwood, followed by cow dung, kerosene and solar. While comparing various available energy sources, fuelwood ranked first, followed by animal dung, kerosene and solar (only used for lighting). Three major factors are found to be responsible for fuelwood being favored as a major energy source in the area: (1) the easy availability of fuelwood; (2) it is an almost-free commodity; and (3) the lack of better © 2018 The Authors. Natural Resources Forum © 2018 United Nations

Madhusmita Dash, Bhagirath Behera, and Dil Bahadur Rahut / Natural Resources Forum 42 (2018) 3–18 Table 1. Particulars of the sample households

Frequency

Percentage Share

Distribution of households by area Core 61 24.90 Buffer 183 75.10 Total 244 100.00 Distribution of households by religion category Hindu 197 80.82 Christian 47 19.18 Total 244 100.00 Distribution of households by caste composition Kolha Hindu 73 30.20 Majhi 124 50.61 Kolha Christian 47 19.18 Total 244 100.00 Distribution of respondents by gender group Male 204 83.67 Female 40 16.33 Total 244 100.00 Distribution of household heads by gender group Male 230 94.29 Female 14 5.71 Total 244 100.00 Distribution of respondents by age group 15–40 years 119 48.60 40–60 years 116 47.30 60 years and above 09 3.70 Total 244 100.00 Distribution of household heads by age group 40 years and less 98 40.40 40–60 years 136 55.50 60 years and above 10 4.10 Total 244 100.00 No. of adult males (average per 04 – household) No. of adult females (average per 03 – household) No. of children (under 6 years) 02 – Distribution of respondents by literacy rate Illiterate 194 79.18 Literate 50 20.82 Total 244 100.00 Distribution of household heads by literacy rate Illiterate 200 81.63 Literate 44 18.37 Total 244 100.00 BPL card holder Yes 184 75.51 No 60 24.49 Total 244 100.00 Distribution of households by range of agricultural land holding (acres) 3 acres and less 163 66.90 3–6 acres 71 29.00 6 acres and above 10 4.10 Total 244 100.00 Sample households by state of housing Kuchcha (Mud wall) 53 21.72 Kuchcha (Wooden wall) 100 40.98 Kuchcha-Pucca (Mixture of mud 26 10.66 and cement) Pucca (Cement wall) 65 26.64 Total 244 100.00

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alternative energy options. However, because of the restriction imposed by the FD and the remoteness of markets, whatever fuelwood STR households collect, they consume. There is no scope for the sale of fuelwood in the area. While collecting fuelwood, women travel together in groups because they are afraid of the animals found in the wild and, by going together, they are able to strengthen the social bonds with each other. Unmarried girls from the age of 10 also assist their mothers on the fuelwood collection trips in the study site. The scarcity of fuelwood in the study area was evident from the increase in the distance travelled by the fuelwood collectors. It was learned from the key informant discussion that the time taken to walk has increased from 15–20 minutes to 1.5–2 hours in the study area. The non-availability of fuelwood within the villages is an indicator of over-exploitation of forests, given the fact that this was not the situation in the past and people had enough forests within the villages themselves to fulfill their energy requirements. Therefore, it is important to know from which sources households collect fuelwood and which factors determine a households’ fuelwood collection sources. The first author was involved in some fuelwood collection walks with the collectors, and observed that the walk to collect fuelwood was spent gossiping non-stop about the village and their household affairs. However, returning home the walk was done in silence because they were tired from the work of collecting fuelwood and carrying it on their heads. As fuelwood became scarcer, it was reported that girls older than 10 stayed home to take care of the infants. But in some cases, women were seen to carry their infants strapped on their backs when they went to collect fuelwood, integrating child-care with their labour. Moreover, the situation becomes more grievous during the rainy season since fuelwood collection cannot be done regularly. Women were reported to collect wood every two or three days. In such circumstances, households were forced to make unhealthy choices to control wasted fuelwood use, such as eating half-cooked meals, cooking only once a day, cooking low nutritional-value food items that require less cooking time, etc. – all of which affect the health of household members. A solar electrification programme was implemented in the buffer villages of the STR under the flagship project of Lighting a Billion Lives by The Energy Resources Institute (TERI) in 2010, with the major objective of reducing incidents of human-wildlife conflict, since the bright light of solar lanterns would work as a deterrent to wild animals (Dash and Behera, 2012). The provision of light during evening hours would also allow villagers to use that time for productive work, which in turn would help reduce their dependence on the forest. Accordingly, each village is given at least 50 solar lamps, providing each individual household with one lamp. Each of these lamps has the facility of a night LED lamp, dimmer, mobile charger and battery status indicator. These lamps are charged in the

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community-based solar charging stations, which are manned by Prakash Dut (messenger of light), who is in fact a member of that particular village community. She/he is responsible for the distribution and upkeep of the lanterns being given to the villagers, as well as maintaining the charging station. Prakash Dut serves as an extremely important link between local communities and the forest. She/he often acts as an effective informer against poachers or other wildlife crimes that occur in the area. Further, such charging stations are proving to be the ideal platform for the village community to gather and discuss the local issues. The solar electrification in the STR is a supply-driven program and not a demand-driven program by the FD and TERI, having the dual objective to conserve biodiversity and improve local livelihoods. While access to solar electrification is uniform for all households in the STR, its adoption depends on a household’s desire for solar panels. This requires the interested households to approach the Field Director of Similipal with a written application through the Prakash Dut of the respective village. During the field survey, it was observed that despite access, many households are still not solar electrified, which induced the authors to carry out an analysis to examine a household’s differential preference of energy usage in the STR. 3.5. Household energy use pattern in Similipal While three different fuel mixes are found for cooking, four different fuel mixes are identified for lighting in the STR (Table 2). The major dependency of rural households on fuelwood is supported by high percentage (67%) of this energy consumption for cooking, followed by “cow dung cake and fuelwood” (20%) and “fuelwood and kerosene” (13%). An important cultural factor for using biomass mostly for cooking purposes is found to be the taste and texture of the food associated with biomass cooking. For lighting, kerosene is found to be the major source of fuel used by the STR households (49%), followed by “kerosene and solar” (32%), only solar (11%) and only fuelwood (8%). The differential energy preference, both for cooking and lighting, has incited us to identify and analyze the factors determining a households” energy choice. Table 2. Percentage distributions of households by fuel mix (dependent variables used in the multinomial logit regression)

Sources of energy for cooking Only fuelwood Cow dung and fuelwood Fuelwood and kerosene Sources of energy for lighting Only solar Only kerosene Kerosene and solar Fuelwood

67% 20% 13% 11% 49% 32% 8%

3.6. Econometric model explanation To identify the factors that determine the sources of fuelwood collection, a multivariate probit model has been used. A multinomial logit model (MNL) is used to examine factors that affect household energy choices for cooking and lighting. Faced with the availability of fuelwood from the reserve options, households opt to adopt a mix of strategies rather than relying on the single source of fuelwood (to exploit complementarities among alternatives). Thus, in addition to fuelwood collection from the “nearby forest and own farmland”, a household may choose to collect fuelwood from the deep reserve forest. While fuelwood collection sources may be used simultaneously, they can also be used as substitutes. It is thus essential to employ a model that evaluates the effect of the exogenous factors on the choice/ use of fuelwood sources concurrently, while permitting for the error terms of each of these strategies to be freely correlated (Golob and Regan, 2002). Therefore, this study employs a multivariate probit model to investigate the interdependent energy choice decisions. The multivariate probit model is a generalization of the probit model used to appraise several interrelated binary outcomes together. The multivariate probit model is appropriate for jointly predicting these two choices on an individual-specific basis. Following several other studies of household decisions on fuel choice (Jumbe and Angelsen, 2011; Rahut et al., 2014), the MNL was applied to ascertain the determinants of fuelwood, kerosene, cow dung cake, and solar, for two different energy uses: lighting and cooking. The fuel choices were analyzed by taking all of them into account simultaneously. In the MNL, all the logit models are estimated concurrently; that enforces the logical relationships between the parameters and uses the data more efficiently (Long, 1997). The comparative odds of one alternative being chosen over a second should be autonomous of the presence or absence of an unchosen third alternative (Luce, 2012). An individual i has a set of alternatives from which he chooses the particular fuel j, which maximizes the benefit he derives from its utility. The fuel use varies among families, and depends on the degree of accessibility, price, the shadow price of labour and other socio-economic characteristics. According to random utility theory (RUT), the utility of choice is comprised of a deterministic and an error element e, which is independent of the deterministic part and follows a predetermined distribution. Selections of the fuel sources made between alternatives will be a function of the probability that the utility associated with a particular alternative j is greater than that related to other alternatives. It has been shown (McFadden, 1976) that if the M error terms εij(j = 1, . … M) are independently and identically distributed with Weibull distribution F(εij) = exp[exp (−εij)], then the probability that (household) i chooses © 2018 The Authors. Natural Resources Forum © 2018 United Nations

Madhusmita Dash, Bhagirath Behera, and Dil Bahadur Rahut / Natural Resources Forum 42 (2018) 3–18

alternative m can be stated as a function in function of household characteristics Z as: expðZim Þ PrðYi = mÞ = PM  : j = 1 exp Zij

PrðYi = 1Þ = PrðYi = mÞ =

1+

1

 , j = 2 exp Zij

PM

expðZim Þ  m = 2, …m: P 1+ M j = 2 exp Zij

Table 3. Results of the multivariate probit model estimation on the determinants of household source of fuelwood collection

ð1Þ

The MNL is now defined by Equation (1) but with the caveat that: P Zij = Rr= 1 βjr Xir because the probabilities Pr(Yi = j) add P to 1 over all the choices (that is, m j = 1 Pr ðYi = jÞ = 1, only M-1 of the probabilities) can be determined independently. Consequently the multinomial logit of Equation (1) is indeterminate, as it is a system of M equations in only M-1 autonomous unknowns. A suitable normalization that solves the problem is to set β1r = 0,r = 1 , . … R. under this normalization Zi1 = 0 and so from Equation (1): ð2Þ ð3Þ

As a result of the normalization, the probabilities are uniquely determined so that Equation (3) represents a system of M-1 equations in the M-1 unknown probabilities, Pr (Yi = 1), having been defined by Equation (1) through the normalization adopted.

Age of household head Age square of head No. of days in wage employment No. of adult males No. of adult females No. of children ( chi2 Log likelihood

Deep reserve forest

Nearby forest and own farmland

0.153 (0.126) −0.001 (0.001) 0.011 (0.029) −0.599** (0.284) 0.627** (0.287) 0.214 (0.1920) −2.623*** (0.681) −0.142 (0.131) −6.063 (644.126) −0.188 (0.323) −11.684 (532.514) −7.731*** (2.7378) −6.692** (2.782) −4.742* (2.615) 0.778* (0.416) 0.652*** (0.239) 244 76.340 0.001 −83.97

0.111 (0.122) 0.001** (0.001) −0.083 (0.034) 0.607** (0.316) 0.393** (0.388) −0.155 (0.2097) 2.397** (0.969) 0.091** (0.148) −0.161 (0.471) −7.440 (332.331) 2.134 (481.832) 5.556 (332.333) 7.388 (641.966) 7.814 (332.335)

Notes: Standard errors are given in parentheses. ***, ** and * indicate significance at the 1%, 5%, and 10% levels. Likelihood ratio test of rho21 = 0: chi2 (1) = 5.15951, Prob > chi2 = 0.0231. aDummy variables. b Excluded category: illiterate head. cExcluded category: male headed. d Excluded category: Kolha Hindu. eExcluded category: Kuchcha wall.

and nearby forests, perhaps because of the high opportunity cost associated with fuelwood collection from the deep reserve forest. However, the number of adult females is found to be positive and significant for fuelwood collection from the reserve forest. This justifies the argument that female members in developing countries are engaged in fuelwood collection and, hence, more members can be employed in the collection from the reserve forests. A literate household head is positively associated with “nearby forest and own farmland” and negatively and significantly associated with “deep reserve forest”, denoting that educated household heads prefer to collect fuelwood from nearby areas and their own fields rather than collect it from

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reserve forests, perhaps due to the high opportunity costs involved in traveling long distances to collect fuelwood. The impact of land-holding size is found to be significantly associated with the increase in fuelwood collection from “nearby forest and own farmland” and the decline in fuelwood collection from the reserve forest. Compared with the kuchcha households, households that have wooden, kuchha-pucca and pucca households have a significant negative impact on fuelwood collection from the deep reserve forest. This indicates that, with the improvement in household conditions, households refrain from fuelwood collection from the STR, and instead prefer to collect it from their own farmland and nearby forests. 4.2. Factors that affect choice of energy for lighting This section examines the elements that affect household’s energy choice for lighting, which are hypothesized to be

determined by the household’s socio-economic status and access to clean energy (see Table 4, Specification 1). The dependent variable is the choice of energy for lighting in the STR, which can be broadly categorized as fuelwood, kerosene, kerosene and solar, and only solar. However, the independent variables are household socio-economic and demographic characteristics. As the outcome variables are disconnected, we employ the MNL, and only solar is used as the base category. The results show that the age of the household head is positively and significantly associated with “only kerosene” as compared to “only solar’. However, age square of the household head is found to be negatively associated with “only kerosene”, which implies that with the increase in age of the household head, the household preference for solar or clean energy increases. The result coincides with the studies conducted by Walekhwa et al. (2009) in Uganda, and Tadesse (2002) in Ethiopia, which indicated

Table 4. Multinomial logit model for choice of energy for lighting (base category: only solar)

Specification 1 Kerosene Age of household head Age square of head No. of days in wage employment No. of adult males No. of adult females No. of children ( chi2 Log pseudolikelihood

244 149 0.001 −168

Specification 2 (Robustness check)

Kerosene and solar

Fuelwood

−0.928* (0.499) 0.006 (0.004) 0.550** (0.265) −11.660** (5.850) 5.780* (3.065) −1.789** (0.921) −9.767** (3.985) 3.468** (1.505) −4.015** (1.760) −6.593** (3.113) 1.131 (1.600) −8.423** (4.134) 4.960 (3.631) 1.461 (2.575)

0.142 (0.102) −0.002 (0.001) −0.184** (0.045) −0.513 (0.538) −0.184 (0.488) −0.178 (0.276) −1.882** (0.826) −0.236 (0.223) −2.444*** (0.934) 0.012 (0.630) 0.736 (0.804) 1.380 (2.830) 1.033 (3.086) 2.522 (2.854)

Kerosene 0.142** (0.058) −0.002** (0.001) −0.134*** (0.038) −0.671 (0.346) −0.595* (0.350) −0.490** (0.211) 1.035* (0.604) −0.169 (0.154) −1.072** (0.555) 0.585 (0.447) −0.054 (0.625)

1.088* (0.670) 244 10,111 0.001 −117.200

Kerosene and solar

Fuelwood

−0.217 (0.189) −0.002 (0.002) −0.049 (0.090) −0.578 (2.081) 2.079 (1.895) −2.752*** (1.063) −5.179*** (1.653) 1.223* (0.703) −7.827*** (2.505) 1.823 (2.087) 7.689** (3.749)

0.205 (0.159) −0.002 (0.002) −0.120** (0.049) −0.859 (2.406) −0.263 (0.710) −1.278** (0.569) −3.793*** (1.210) −0.592 (0.401) −3.554*** (1.299) 2.501** (1.018) 2.521* (1.479)

−21.440 (2.599)

22.360*** (1.726)

Notes: Standard errors are given in parentheses. ***, ** and * indicate significance at the 1%, 5%, and 10% levels. aDummy variables. bExcluded category: illiterate head. cExcluded category: male headed. dExcluded category: Kolha Hindu. eExcluded category: Kuchcha wall. © 2018 The Authors. Natural Resources Forum © 2018 United Nations

Madhusmita Dash, Bhagirath Behera, and Dil Bahadur Rahut / Natural Resources Forum 42 (2018) 3–18

that households tend to choose clean and safe energy sources as the head gets older, perhaps because the older generation has enough experience to assess the characteristics or benefits of modern technology in a better way than the younger generation. Moreover, the older generation can often be equated with a higher economic status and therefore a greater ability to afford clean energy (Adesina and Baidu-Forson, 1995), and a greater inability to walk long distances to collect wood. However, the positive effect of age of the household head on energy choice needs further research. A household that has a higher number of days in wage employment increases the likelihood of choosing “solar”, a clean energy, over “fuelwood and kerosene” for lighting, which implies that when alternative sources of energy are available, households prefer clean energy to other primitive or transitional fuels. Gender plays a major role in the selection of energy for lighting the house. The households headed by a female are more likely to choose “solar” over all other energy sources for lighting. This implies that female-headed households are likely to prefer a clean energy source, such as solar cooking, because female members, who are primarily responsible for cooking and other domestic energy uses, are acutely aware of the health hazards of using traditional fuels and, hence, prefer to switch to clean energy sources. This finding has interesting policy implications in the sense that solar energy dissemination may directly contribute towards alleviating women’s energy and labour burdens, and indirectly contribute towards the restoration of denuded areas. It is often argued that because gender roles have been largely ignored in energy, the global potential for renewable energy has been negatively affected (Behera, 2015). The presence of more adult females (between the ages of 10 and 60) and children (under 6 years) in a household increases the preference for clean energy, perhaps because having young children reduces the available labour, and the time available for fuelwood collection is reduced by the time needed for childcare. Moreover, the number of adult males (between the ages of 10 and 60) in a household increases the likelihood of choosing “solar” over “fuelwood” (though not significantly), and “kerosene and solar” as an energy source for lighting. Perhaps the potential for good employment opportunities takes precedence over the time needed to collect solid fuels. Education plays a significant role in the choice of energy for lighting. If the household head is literate, the preference for clean fuel increases compared to the preferences of an illiterate household head. This implies that households that have a literate head are more likely to choose solar, which confirms our hypothesis that the preference for cleaner fuel increases with the level of education. The wealth of a particular household, measured by the ownership of land, is an important determinant in the choice of energy for lighting. The result reveals that households that own larger areas of agricultural land are more © 2018 The Authors. Natural Resources Forum © 2018 United Nations

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likely to use clean energies, i.e. “only solar” and “kerosene and solar”, as an increase in farm size and revenue from agricultural yield can result in a decline in collection of fuelwood from the forest, and consequently a switch to higher-quality energy sources. A number of studies have recognized that household socio-economic variables, including caste/ethnicity and religion, significantly affect a household’s resource collection as well as preference behaviour (Bandyopadhyay et al., 2006, Kempen et al., 2009). Given different tribal groups’/religion’s major occupations, levels of education and food preferences/tastes, their preferences for a particular source of energy also vary (Kempen et al., 2009). The results reveal that, compared to the Kolha Hindu, Majhi households are more likely to prefer “solar” as the energy source for lighting. This may be attributed to the fact that the Majhi tribal groups are more educated than the other tribal households in Odisha (Lal, 2005; Behera, 2015). Household structure has been taken as a proxy for a household’s condition or a substitute for income variable (i.e. poor, medium or rich). Households having wooden, kuchha-pucca and pucca walls are more likely to prefer a clean fuel compared to the kuchcha households. Therefore, with the improvement in household structure, the preference for clean energy increases. This finding confirms the energy ladder hypothesis that an increase in income leads households to switch from dirty fuel to clean fuel.

4.3. Factors that affect choice of energy for cooking The results of the multivariate model estimation on the factors that influence a household’s choice of energy sources for cooking are presented in Table 5. Three types of energy consumption sets are identified for cooking purposes: only fuelwood, cow dung cake and fuelwood and fuelwood and kerosene. In the absence of solar as a cooking energy source (used only for lighting), household use of both “fuelwood and kerosene” is taken as the reference or base variable. It is considered to be a relatively better energy source because a transition fuel (i.e. kerosene) is used along with a primitive fuel (i.e. fuelwood) (see Figure 1). While the age of the household head is found to be positively and significantly related to fuelwood use, the age square of the head is found to be negative and significant. This implies that, with an increase in age, the likelihood of choosing “fuelwood and kerosene” for cooking increases compared to “only fuelwood”, perhaps because older people realize the situation of fuelwood scarcity in the STR and want to use kerosene along with fuelwood. The number of adult males and females in a family increases the household’s preference for dirty fuel (though not significantly) for cooking energy. However, the number of children in a household greatly reduces a household’s preference for dirty energy – and necessitates inclusion of kerosene along with fuelwood. Perhaps the presence of a large number

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Madhusmita Dash, Bhagirath Behera, and Dil Bahadur Rahut / Natural Resources Forum 42 (2018) 3–18 Table 5. Multinomial logit model for choice of cooking energy (base category: fuelwood and kerosene)

Specification 1 Only fuelwood Age of household head Age square of head No. of days in wage employment No. of adult males No. of adult females No. of children ( chi2 Log pseudo likelihood

Specification 3 (Robustness check)

Cow dung and fuelwood

0.179** (0.131) −0.003** (0.001) −0.036 (0.048) 0.013 (0.872) 0.563 (0.826) −1.317*** (0.380) 3.880*** (1.107) 0.337 (0.344) 14.065*** (0.943) −0.754 (1.410) −2.664 (1.817) 1.3492 (1.922) 2.381 (2.635) 0.872 (1.990) 244 9234 0.001 −116

0.071 (0.160) −0.003 (0.002) −0.025 (0.055) 0.065 (0.902) 0.504 (0.852) −1.581*** (0.424) 4.453*** (1.218) 0.373 (0.368) 14.759*** (1.070) −1.939 (1.443) −3.859 (1.854) 1.8868 (2.545) 2.851 (3.138) 3.233 (2.570)

Only fuelwood 0.232*** (0.087) −0.004*** (0.001) −0.021 (0.057) 0.174 (0.867) 1.146 (0.838) −1.331*** (0.384) 3.698*** (1.2071) 0.287 (0.412) 12.985*** (1.190) −1.383 (1.554) −2.989 (1.863)

0.993 (1.109) 244 3115 0.001 −121

Cow dung and fuelwood 0.194** (0.094) −0.003*** (0.001) −0.016 (0.062) 0.205 (0.890) 1.103 (0.871) −1.643*** (0.437) 3.953*** (1.289) 0.437 (0.425) 13.101*** (1.327) −1.863 (1.592) −4.301 (1.925)

1.693 (1.172)

Notes: Standard errors are given in parentheses. ***, ** and * indicate significance at the 1%, 5%, and 10% levels.aDummy variables. bExcluded category: illiterate head. cExcluded category: male headed. dExcluded category: Kolha Hindu. eExcluded category: Kuchcha wall.

of children (under 6 years) reduces the time available for fuelwood collection as childcare requires more time. The gender of the household head is an important determinant in the choice of fuel for cooking. Female-headed households are found to prefer both “only fuelwood” and “cow dung cake and fuelwood” over “fuelwood and kerosene”, perhaps because in the absence of clean energy for cooking, female-headed households still prefer to stick to fuelwood for cooking. The level of education of a head of the household is an extremely important factor influencing a household’s decision to choose a set of energy sources. The result reveals that even households that have a literate household head are more likely to prefer solid fuels, perhaps because no better alternative for cooking fuel is available inside the STR and, again, the collection of fuelwood does not include any cost. Compared to the Kolha Hindu, both Majhi and Kolha Christian are more likely to prefer “fuelwood and kerosene” as their cooking energy compared to

only fuelwood, and dung cake and fuelwood. However, the effect is found to be insignificant. Households that have wooden, kuchha-pucca and pucca walls are more likely to prefer “fuelwood” and “dung cake and fuelwood” compared to “fuelwood and kerosene”, though the effect is not significant. This is evident because solid fuel, especially fuelwood, is readily available inside Similipal, and its collection does not include any cost. Besides, in the absence of clean cooking energies, households are compelled to stick to solid energy use. 4.4. Robustness check We classified the households into poor and non-poor households based on the BPL criteria, and re-estimated the determinants of energy choices for lighting and cooking. The dependent variables and independent variables used in this analysis are the same, except that the household type is replaced with a binary variable equal to 1 for poor © 2018 The Authors. Natural Resources Forum © 2018 United Nations

Madhusmita Dash, Bhagirath Behera, and Dil Bahadur Rahut / Natural Resources Forum 42 (2018) 3–18

families holding BPL cards and 0 for non-poor households not holding BPL cards. The finding illustrates that lowincome/BPL families are more likely to use dirty fuels like kerosene oil and fuelwood instead of solar for lighting, compared to non-BPL households (Table 4, Specification 2). However, its effect is insignificant in the case of cooking energy use (Table 5, Specification 3). The econometric result coincides with our descriptive analysis (Table 6). The energy ladder is visible in households’ choices of lighting energy. There is a shift towards cleaner fuels like only solar and “kerosene and solar” for non-BPL households, whereas the usage of dirty fuels as a source for lighting dominates BPL households.

5. Conclusion and policy implications In this paper, the patterns of household energy choice and the sources of fuelwood collection are analyzed using primary data collected from 244 households across 11 villages of the STR. The analysis shows that the households depend heavily on forests for their fuelwood requirements, especially for cooking since the tribal households are resourceconstrained, and other better alternatives to fuelwood are unavailable. The households collect fuelwood from two sources: “deep reserve forests” and “nearby forest and own farm land”. The results of the multivariate probit model estimation on the household choice of fuelwood collection sources show that the age of the household head, number of days in wage employment, number of adult males and females in a household, education of the household head, household type and land-holding size are found to be the major variables that determine a household’s fuelwood collection inside the STR. Households with large landholdings are more likely to collect fuelwood from their own private sources and nearby forest areas, and are less likely to collect from the reserve forest. Similarly, households headed by a literate head are more likely collect fuelwood from their own private land and nearby forest areas compared to the reserve forest. Table 6. Percentage distribution of households by fuel-mix across BPL and non-BPL

Sources of energy for cooking Only fuelwood Fuelwood and kerosene Cow dung and fuelwood Sources of energy for lighting Only solar Only kerosene Kerosene and solar Fuelwood

Non-BPL 57% 20% 23%

BPL 70% 10% 20%

Non-BPL 32% 23% 42% 3%

BPL 4% 58% 28% 10%

© 2018 The Authors. Natural Resources Forum © 2018 United Nations

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The result of MNL for choice of fuels for lighting reveals that the age of the household head increases the preference for clean energy. Households with a higher number of days in wage employment increase the likelihood of choosing solar over fuelwood and kerosene. Female-headed households are more likely to choose solar over all other energy sources for lighting. The presence of more adult females and children under age six in a household increases the preference for clean energy. Households that own larger areas of agricultural land are more likely to use clean energies. Moreover, with the improvement in household structures, a household’s preference for clean energy, i.e. solar, increases. The findings endorse and support the energy ladder hypothesis. Education of the household head emerges as a prominent determinant of energy choice model for lighting. The households that have a literate head are more likely to opt for solar energy, which confirms the hypothesis that the preference for cleaner fuel increases with the level of education. With the increase in age of the household head, the likelihood of choosing “fuelwood and kerosene” increases compared to “only fuelwood” for cooking. The more children in a household significantly reduces a household’s preference for solid energy and requires the inclusion of kerosene along with fuelwood, perhaps because having more children reduces the available labour for fuelwood collection and requires more time for child care. Female-headed households are found to prefer “both fuelwood and dung cake” and “fuelwood” (solid fuels) over “fuelwood and kerosene”. Interestingly, households that have a literate household head are more likely to prefer solid fuels, probably because they are freely available, cheaper than other fuels if purchased and other sources of clean energy are completely absent for cooking. Despite the introduction of solar energy for lighting to the study area, its scope for cooking has not been explored by either the government or non-government organizations (NGOs), i.e. there has been no introduction of solar cookers in the STR. In such a situation, the households continue to use fuelwood, animal dung and kerosene. This implies that deforestation and land degradation will continue and remain as unresolved challenges in the study areas. The robustness assessment of the models exhibited consistent outcomes for relevant variables. Although the findings of the study should be considered within the cultural and geographical context of the STR, they have some significant policy implications that can be applied to other forest areas as well. The findings of the present study have the following key policy implications for achieving long-term socio-economic and ecological sustainability. • Energy policies for development should be based on the realistic proposition that fuelwood will remain the major source of energy for cooking for substantial portions of the world’s population (Heltberg et al., 2000; Berhe et al., 2017). Therefore, efforts to promote safe and

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efficient household energy are needed, but such efforts should not always exclusively focus on fuel switching. An appropriate balance needs to be developed between policies aiming at inter-fuel substitution and policies seeking to ameliorate the negative consequences of the use of fuelwood (Berhe et al., 2017). Interventions must be taken to make solid fuels less risky for health. Although analysis of such interventions is outside the scope of this paper, further research should be done in this direction. Although the effects of fuelwood scarcity on environment and the inhalation of biomass smoke during cooking have been highlighted in much of the literature (Heltberg, 2005; Rahut et al., 2014; Behera et al., 2015), they are scarcely considered by policymakers while designing appropriate policies. Therefore, while planning policies, women’s needs and preferences need to be studied and considered with a participatory approach. Training should be given to them regarding the efficient use of fuelwood through a variety of modern techniques and other cheap alternatives. Such measures should promote the use of energy carriers other than biomass, as well as the use of biomass in modern ways. Measures should be taken by stakeholders in the energy sector to develop and promote renewable and clean technologies to lessen the burden of economic activities on the ecosystem, reduce pollution and meet demand in rural areas (Heltberg, 2005). Technological initiatives including the fuel-efficient improved chulhas, solar energy and bio-gas should be encouraged in the area. The Government of India launched the Integrated Rural Energy Programmes (IREP) in 1987. These programmes should more greatly emphasize fuelwood-forest hotspot areas like PAs (Jaiswal and Bhattacharya, 2013). Distribution of better quality improved chulhas under the Reducing Emissions from Deforestation and Forest Degradation Plus (REDD+) project from the Ministry of Environment and Forests (MoEF) should be extended to the PAs (Jaiswal and Bhattacharya, 2013). Promotion of public education could be an effective instrument in reducing dependence on fuelwood and in facilitating the use of clean fuels. In addition, governments and NGOs need to spread more awareness among the households regarding increasing fuelwood scarcity and its resultant effects on local communities in the future. Since fuelwood is the fuel of choice by a majority of the rural populace for cooking, the government should undertake activities like social forestry, which includes trees of fodder and fruits to deal with the problem of fuelwood scarcity and to increase forest cover (Heltberg et al., 2001; Heltberg, 2005). The fruit trees like jackfruit, mango and guava in hilly areas and other fruit trees on the plains can deal with the twin problem of fuelwood scarcity and forest degradation.

• Participation of the local communities in PA management should be promoted by developing a participatory management plan for the tiger reserve. Therefore, attention must be focused on strengthening local-level community and/or village institutions that can prevent the excess use of resources from the reserve by framing rules and regulations (Adhikari, 2005; Behera, 2009; Dash and Behera, 2015). An extensive study has been conducted by the first and second author of the paper on the type, functioning and effectiveness of local institutions in the STR and their impacts on forest conservation outcomes (Dash and Behera, 2015). The study finds that villagers’ own institutions in terms of their beliefs, customs and rituals are more likely to reduce biomass dependency on the commons. However, the Joint Forest Management (JFM) programme, an important instructional arrangement that facilitates collective action, is very neglected in the STR. That failure can be attributed to improper revenue sharing among the FD and local communities and the dismal representation of female JFM members.10 Rejuvenation of such formal and informal institutions in and around the STR will go a long way in promoting forest conservation. • Lastly, devolving sufficient property rights over forest resources to local communities may help secure their broad-based and active participation in the decisionmaking process, which may result in a positive change in the attitude of the local people towards conservation of biodiversity (Heltberg, 2001; Dash and Behera; 2015). In this context, better implementation of the recently-implemented Scheduled Tribes and Other Traditional Forest Dwellers Act/Forest Rights Act, 200611 (FRA, 2006), under which local people are entitled to have rights over forest land and resources, may act as a panacea to accomplish the twin objectives: biodiversity conservation and improvement in tribal livelihoods.

10

The JFM Resolution, 2011 strongly indicates that at least 50% of the Executive Committee of VSS/EDC shall be women members. Either the chairperson or the vice chairperson shall be a woman, which promotes the leadership role of women in forest areas. 11 The FRA (2006) aims to address the historical injustice done to the communities whose forest rights have so far not been legally recorded, and thereby were denied their traditional rights to forest lands and resources. The Act recognizes and grants forest-related rights to scheduled tribes and other communities that traditionally have been living in or depending on forest land for their legitimate livelihood needs. Members of scheduled tribes (in states where they are scheduled) can claim rights under this Act if they have been residing in or dependent on forests prior to 13 December 2005. However, other traditional forest dwellers can only claim rights if they have been in occupation for at least three generations, i.e. 75 years prior to 13 December 2005. © 2018 The Authors. Natural Resources Forum © 2018 United Nations

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References Adesina, A.A., Baidu-Forson, J., 1995. Farmers’ perceptions and adoption of new agricultural technology: Evidence from analysis in Burkina Faso and Guinea, West Africa. Agricultural Economics, 13: 1–9. Adhikari, B., 2005. Poverty, property rights and collective action: Understanding the distributive aspects of common property resource management. Environment and Development Economics, 10: 7–31. Agrawal, A., Chhatre, A., 2006. Explaining success on the commons: Community forest governance in the Indian Himalaya. World Development, 34: 149–166. Amacher, G.S. Hyde, W.F., Keshav, K.R. 1999. Nepali fuelwood production and consumption: Regional and household distinctions, substitution and successful intervention. The Journal of Development Studies, 35(4): 138–163. Bandyopadhyay, S., Shyamsundar, P., Baccini, A., 2006. Forest, biomass use and poverty in Malawi. Background paper for the Malawi Poverty Assessment. World Bank Policy Research Working Paper, 4068. Behera, B., 2009. Explaining the performance of state: Community joint forest management in India. Ecological Economics, 69: 177–185. Behera, B., Rahut, D.B., Jeetendra, A., Ali, A., 2015. Household collection and use of biomass energy sources in South Asia. Energy, 85 (2015): 468–480. Bekele, W., Drake, L., 2003. Soil and water conservation decision behaviour of subsistence farmers in the eastern highlands of Ethiopia: A case study of the Hunde Lafto area. Ecological Economics, 6(3): 437–451. Berhe, M., Hoag, D., Tesfay, G., 2017. Factors influencing the adoption of biogas digesters in rural Ethiopia. Energy Sustainability and Society, 7(10): 1–11. Bruce, N., Perez-Padilla, R., Albalak, R., 2000. Indoor air pollution in developing countries: A major environmental and public health challenge. Bulletin World Health. Organization, 78(9): 1080–1093. Dash, M., Behera, B., 2012. Management of similipal biosphere reserve forest: Issues and challenges. Advances in Forestry Letter, 1: 7–15. Dash, M., Behera, B., 2013. Biodiversity conservation and local livelihoods: A study on Similipal Biosphere Reserve Forest, India. Journal of Rural Development, 32(4): 409–426. Dash, M., Behera, B., 2015. Local institutions, collective action and forest conservation: The case of similipal Tiger Reserve in India. Journal of Forest Economics, 21: 167–184. Dash, M., Behera, B., Rahut, D.B., 2016. Determinants of household collection of non-timber forest products (NTFPs) and alternative livelihood activities in Similipal Tiger Reserve, India. Forest Policy and Economics, 73: 215–228. Ekholm, T., Krey, V., Pauchari, S., Riahi, K., 2010. Determinants of household energy consumption in India. Energy Policy, 38(10): 5696–5707. Fisher, M., 2004. Household welfare and forest dependence in Southern Malawi. Environment and Development Economics, 9(2): 135–154. FRA, 2006. Forest Rights Act, 2006: Act, Rules and Guidelines. Ministry of Tribal Affairs, Government of India: United Nations Development Programme. Gerber, J., 2009. Institutional Resource Regimes: Towards sustainability through the combination of property-rights theory and policy analysis. Ecological Economics, 68(3): 798–809. Golob, T.F., Regan, A.C., 2002. Trucking industry adoption of information technology: A multivariate discrete choice model. Transportation Research Part C: Emerging Technologies, 10(3): 205–228. Hedge, R., Enters, T., 2000. Forest products and household economy: A case study from Mudumalai Wildlife Sanctuary, Southern India. Environmental Conservation, 27(3): 250–259. Heltberg, R., 2001. Determinants and impact of local institutions for common resource management. Environment and Development Economics, 6(2): 183–208. Heltberg, R., 2005. Factors determining household fuel choice in Guatemala. Environment and Development Economics, 10(3): 337–361. © 2018 The Authors. Natural Resources Forum © 2018 United Nations

17

Heltberg, R., Arndt, T.C., Sekha, R.N.U., 2000. Fuelwood consumption and forest degradation: A household model for domestic energy consumption in rural India. Land Economics, 76(2): 213–232. Ishaya, S., Ifatimehin, O.O., Abaje, I.B., 2009. Mapping flood vulnerable areas in a developing Urban Centre of Nigeria. Journal of Sustainable Development in Africa, 11(4): 180–194. Jaiswal, A., Bhattacharya, P., 2013. Fuelwood dependence around protected areas: A case of Suhelwa Wildlife Sanctuary, Uttar Pradesh. Journal of Human Ecology, 42(2): 177–186. Jumbe, C.B., Angelsen, A., 2011. Modeling choice of fuelwood source among rural households in Malawi: A multinomial probit analysis. Energy Economics, 33(5): 732–738. Karekezi, S., Khennas, S., Natu, S., Rakos, C. 2005. Status of biomass energy in developing countries and prospects for international collabouration. 5th Global Forum on Sustainable Energy in Vienna, Austria, 11–13, May. Kempen, L.V., Muradian, R., Sandóval, C., Castañeda, J.P., 2009. Too poor to be green consumers? A field experiment on revealed preferences for firewood in rural Guatemala. Ecological Economics, 68(7): 2160–2167. Khandker, S.R., Barnes, D.F., Samad, H.A., 2012. Are the energy poor also income poor? Evidence from India. Energy Policy, 47: 1): 1–1):12. Kirubi, C., Jacobson, A., Kammen, D.M., Mills, A., 2009. CommunityBased Electric Micro-Grids Can Contribute to Rural Development: Evidence from Kenya. World Development, 73: 1208–1221. Lal, M., 2005. Education – the inclusive growth strategy for the economically and socially disadvantage society. Developing Country Studies, 2: 1–10. Leach, G., 1992. The energy transition. Energy Policy, 20(2): 116–123. Long, J.S., 1997. Regression Models for Categorical and Limited Dependent Variables. Sage, Bloomington, USA. Luce, R.D., 2012. Individual Choice Behavior: A Theoretical Analysis. Dover Publications; New York, USA. Mahapatra, S., Dasappa, S., 2012. Rural electrification: Optimising the choice between decentralised renewable energy sources and grid extension. Energy for Sustainable Development, 16: 146–154. Mallik, R.M., 2000. Impact of NTFP-policies on sustainable livelihood of forest-dependent communities in Orissa: An empirical exercise. Nabakrushna Choudhury Centre for Development Studies, Bhubaneswar: Mimeo. Masera, O.R., Saatkamp, B.D., Kammen, D.M., 2000. From linear fuel switching to multiple cooking strategies: A critique and alternative to the energy ladder model. World Development, 28(12): 2083–2103. McFadden, D., 1976. Quantal choice analaysis: A survey. Annals of Economic and Social Measurement, 5(4): 363–390. Mishra, P., Behera, B., 2016. Socio-economic and environmental implications of solar electrification: Experience of rural Odisha. Renewable and Sustainable Energy Review, 56: 953–964. Nansaior, A., Patanothai, A., Rambo, A.T., Simaraks, S., 2011. Climbing the energy ladder or diversifying energy sources? The continuing importance of household use of biomass energy in urbanizing communities in Northeast Thailand. Biomass Bio Energy, 35(10): 4180–4188. Palit, D., 2013. Solar energy programs for rural electrification: Experiences and lessons from South Asia. Energy for Sustainable Development, 17: 270–279. Rahut, D.B., Das, S., Groote, H.D., Behera, B., 2014. Determinants of household energy use in Bhutan. Energy, 69 (2014): 661–672. Rahut, D.B., Behera, B., Ali, A., 2016. Household energy choice and consumption intensity: Empirical evidence from Bhutan. Renewable and Sustainable Energy Reviews, 53: 993–1009. Registrar General & Census Commissioner of India, 2011. Census of India. Registrar General & Census Commissioner of India, New Delhi. Sahoo, S., Davidar, P., 2013. Effect of harvesting pressure on plant diversity and vegetation structure of Sal forests of Similipal Tiger Reserve, Odisha. Tropical Ecology, 54(1): 97–107.

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Madhusmita Dash, Bhagirath Behera, and Dil Bahadur Rahut / Natural Resources Forum 42 (2018) 3–18

Sahoo, S., Puyravaud, J.P., Davidar, P., 2013. Local knowledge suggests significant wildlife decline and forest loss in insurgent affected Similipal Tiger Reserve, India. Tropical Conservation Science, 6(2): 230–240. Schlag, N., Zuzarte, F., 2008. Market Barriers to Clean Cooking Fuels in Sub-Saharan Africa: A Review of Literature. Stockholm Environment Institute. Sehjpal, R., Aditya, R., Anmol, S., Atul, K., 2014. Going beyond incomes: Dimensions of cooking energy transitions in rural India. Energy, 68: 470–477. STR (2013). Annual report of similipal Tiger reserve 2012-13. Office of the Field Director cum CCF, Baripada, Odisha. Tadesse, T., 2002. Empowering Women in Ethiopia. Choices, 2002: 12–13. Toman, M.A., Jemelkova, B., 2003. Energy and economic development: An assessment of the state of knowledge. Energy Journal, 24(4): 93–112.

UN, 2015. The Millennium Development Goals Report 2015. Time for Global Action. For People and Planet. UN, 2016. International Energy Agency: OECD. UN, 2016. The Sustainable Development Goals Report. United Nations, New York. Walekhwa, P.N., Mugisha, J., Lars, D., 2009. Biogas energy from familysized digesters in Uganda: Critical factors and policy implications. Energy Policy, 37: 2754–2762. WHO, 2014. Reducing Risks, Promoting Healthy Life. World Health Organization, Geneva. World Bank, 2003. The Environmental Sector in Viet Nam. World Bank, Washington, DC. World Energy Outlook, 2008. International Energy Agency: OECD.

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