Cooking energies can be classified according to nature of energy development as either; traditional which consists of dung from animals and fuel-wood or intermediate where we have; wood pellets, charcoal, briquettes, lignite, coal and kerosene and modern consisting of; solar, LPG, biogas, natural gas, electricity, gel-fuel, plant oils, and dimethyl ether. Cooking energy can also be classified depending on the nature of production as either primary or secondary. Primary sources are provided by the environment like fuel-wood, solar, dung, natural gas, and coal while secondary sources of energy come from the processing of primary sources of energy hence we have; petroleum products like kerosene and LPG from crude oil, ethanol from sugarcane, charcoal and wood pellets from fuel-wood, biogas from animal and agricultural wastes, electricity from the combustion of fossil fuels and from renewable sources like solar, hydro and wind.
Cooking energy types can also be classified as renewables as in the case of; biomass, solar and biogas, or non-renewables as coal, kerosene, LPG, natural gas.
A wide range of factors influence each household’s choice of energy types of which some of them are:
Most studies already conducted show that when per capita income increases many households switch to cleaner fuels for cooking(energy ladder hypothesis). This is in accordance with studies by Bansal et al. (2013) in rural India, Chaudhuri, and Pfaff (2003) in Pakistan, Heltberg (2005) in Guatemala and Nlom, and Karimov (2014) in northern Cameroon. This, therefore, shows that income plays a role in the determination of a household energy type.
Moreover, during Ouedraogo’s (2006) analysis concerning urban households cooking fuel choice in Ouagadougou, Burkina Faso, he found that when household income increases there is a decrease in wood-fuel utilization. Similarly, findings from Arthur et al. (2010) indicate transition from biomass dependency to electricity in Mozambique depends on household wealth.
In contrast, there are other researches which show that the energy ladder hypothesis does not hold an example of such is researched by; Sehjapal et.al(2014) conducted in rural India found that income levels in a household have an insignificant effect on the choice of energy used in a household. Studies in developing countries by; Arnold et al. (2006) and Cooke et al. (2008) found that elasticity in income on wood-fuel was not significant. Moreover, studies by Hiemstra-van der Horst and Hovorka (2008) in Botswana, Brouwer, and Falco (2004) in Mozambique and Bhagavan and Giriappa (1995) in India found that wood is used by all households while there are evidence of the utilization of electricity and LPG for cooking by low-income households according to studies conducted by; Davis (1998) in South Africa, Campbell et al. (2003) in Zimbabwe and Brouwer and Falco (2004) in Mozambique.
Pundo and Fraser (2006) in their research in Kenyan rural areas found that the level of education of women could influence the type of energy used in a household hence the transition from non-clean energy sources. Similarly, findings reported by Heltberg (2004) in eight developing countries and by Suliman (2010) in Sudan. Moreover, Pandey and Chaubal (2011) found that a number of educated females between the ages of 10 and 50 years of an average household’s level of education had a positive and significant impact on the choice of using clean cooking fuels in rural India. In urban setup , studies by Mekonnen and Kohlin (2008) and Gebreegziabher et al. (2012) in Ethiopia and by Farsi et al. (2007) in India came up with similar findings that households with more educated members are more likely to choose cleaner fuels. Based on the 2008 Nigerian Demographic and Health Survey data, Oyekale (2012) found that access to electricity and modern cooking energy sources significantly increased among urban dwellers and educated household heads but declined with a resident in rural northern Nigeria. This, therefore, shows that level of education among family members has a positive effect on the type of choice of energy since there are no contradicting findings.
Jain (2010) in his research found that high costs of modern energies were a reason as why most residents in India depended on traditional fuel sources. Schlag and Zuzarte (2008) on the other hand found similar results regarding fuel choices in SSA. Apart from this, the substitution of sources of energy was analyzed, where the reference was made on the data from household surveys in ten developing countries of SSA, South Asia (SA) and Latin America and the Caribbean (LAC) regions, by Kojima et al. (2011) from where he found that increase in the level of education and price of alternative cooking fuels, in general, increased use of LPG whereas a study by Zhang and Kotani (2012) in rural Beijing found that fuel prices did not exhibit substitution effects between cooking fuels (coal and LPG), but an increase in these prices led to reduced use of these cooking fuels.
In addition, socio-economic factors influence the choice of energy used together. For instance, Narasimha Rao and Reddy (2007) in their research found that household expenditure, size, and education all act together in determining fuel choices in rural and urban areas in India while Andadari et al. (2014) found the same in Indonesia. Using regression analysis, Peng et al. (2010) found that incomes, fuel prices, demographic characteristics, and topography had a significant effect on household fuel choices in rural China.
Nnaji et al. (2012) in his study in rural Nigeria found that fuel-wood is the fuel of choice for households with relatively large sizes. Walekhwa et al. (2009) on the other hand found that the probability of a household adopting biogas technology in Central and Eastern Uganda increased with decreasing age of head of household, increased with a number of cattle owned, increased household size, the male head of household and increased cost of traditional fuels. In contrast, the study also finds that likelihood of adoption of biogas decreases with increasing remoteness of the household location and increased household land area.
These include; household preferences, food tastes, cooking practices, and cultural beliefs. Masera et al. (2000) found that people in rural Mexico used fuel-wood even when most of them could afford to use cleaner and modern fuels because cooking on LPG is more time consuming and negatively affects the taste of food. Indian households also prefer to use wood cook-stoves for baking traditional bread (IEA, 2006). Using 2000 Guatemalan LSMS survey data, Heltberg (2005) argued that traditional cooking practices and food tastes might make people prefer fuel-wood, even where fuel-wood is as expensive as cleaner alternatives. Taylor et al. (2011) in his study found that migrant households in Guatemala often used the traditional ways of preparing foods despite LPG being available and affordable. In Ougadougou, Burkina Faso, Ouedraogo (2006) finds that the frequency of cooking a staple traditional meal made of millet, sorghum, or maize increases the likelihood of using fuel-wood.
Link et al. (2012) found that increased household’s access to organizations and services, e.g., employment, banking, schooling, health care, and transportation, in the local community increased the use of alternative fuels in Nepal. Bandyopadhyay and Shyamsundar (2004) found strong linkages between fuel-wood consumption and community forest participation in India and household participation has a significant positive impact on fuel-wood consumption. Examining fuel-wood use in five rural villages in the Bushbuckridge region of South Africa, Madubansi and Shackleton (2007) found that improvement in access to electricity had little impact on fuel-wood consumption. Wang et al. (2012) found that off-farm employment and agricultural specialization are the primary driving force of household fuel-wood substitution in rural Southeast China. In Pakistan, Bacon et al. (2010) found that a greater proportion of rural households used LPG than their urban counterparts at all income levels because of the availability of natural gas in urban areas.
In a study by Narasimha Rao and Reddy (2007) shows that households headed by women generally opt for modern fuels than those headed by men. Women generally play a major role in household cooking decision-making activities. Based on the household survey of access and transitions to cleaner cooking fuels in Sri Lanka, Wickramasinghe (2011) found that women are more likely to switch to cleaner fuels if they are employed in activities outside of the home.
Many types of research have been carried out concerning patterns and determinants of energy consumption were depending on the scope of the study, different statistical models have been used. Below are some of the models used in various researches.
Lee(2013) and Svoboda(2013) when assessing determinants of household electricity consumption using variables like temperature, electric water heater, electric clothes drier, dishwasher, number in house, family income, age of respondent, nature of employment, expenditure per capita, private water connection, price of kerosene, age of household head, and gas price employed ordinary least square regression where he found significance in the price of electricity, change of temperature, to electricity consumption, unlike the other variables.
Koshal et al(1999) used the OLS model to determine kerosene use in Indonesia where he obtained significant negative value for price changes and positive value of income elasticity of kerosene . In the research, while applying cross elasticity with respect to the price of electricity it was found to be positive implying kerosene and electricity could act as substitutes for each other.
Moreover, Isiolo (2010) used the same OLS to examine determinants of fuel-wood expenditure in Kenya where age of household head and level of education of household head were found to positively have an influence on fuel-wood expenditure . From above it can be noted that the OLS model had limited scope and could only be used to investigate one dependent parameter at any given point and the prediction of determinants of household energy choice decision can be difficult.
The most frequent categories for the dependent variables when using this model were ; biomass fuel, kerosene, electricity, and liquefied petroleum gas whereas independent variables like household income, age of household head, level of education of household head, household size, dwelling ownership, occupation of household head, number of rooms, number of years when the household was built, size of resident, the ratio of female in the household, were found to have a positive influence on use of firewood instead of kerosene or electricity or gas according to research by (Nnaji et al,2012, Song et al 2012) while some studies showed that these variables had a negative effect on the use of firewood hence lead to the conclusion that electricity or gas should be used. These variations was due to the fact that these studies were carried out at different times with the use of different data . From this we can learn that variations in the type of energy used do exist due to difference in regions of study and various factors considered in the study.
Nlom and Karimov (2014), Eakins(2013), and Mensah and Adu (2013)applied ordered logit/probit models to examine factors that influence household energy choice to more cleaner source, variables employed such as income, firewood price, education level of household head, the share of dwelling with other people, urban household, access to liquefied petroleum gas, was found to have a positive relationship with probability of adopting more cleaner energy while other variables like; electricity price , price of kerosene, age of household health, household size, gender(male) of the household head, and access to firewood had negative influence on probability of using cleaner and more efficient energy.The major limitation about these studies is that they are based on the assumption that the various household energy choices categories are ordered in ranking manner, wherein real life ,the various categories are not an ordered basic choice.
To summarise it all various researches have been undertaken in both the developed and developing countries on household energy consumption however limitations do exist from such researches ranging from the scope of the study , the models used, and the variables employed in the various studies . A study on household energy consumption by (Svoboda, Br 2013;Pourazarm and Cooray,2013;Auffhammer and Aroonruengsawat,2012)focused on household electricity consumption, therefore neglecting other aspects like; consumption of wood, kerosene,use of liquefied petroleum gas,as sources household energy consumed.Naibbi and Healey 2013, Onoja and Emodi, 2013) had their focus on wood fuel analysis neglecting other aspects like electricity ,kerosene e.t.c
Moreover from the review it can be noted that not all factors have positive impact in determining the pattern and choice of source of energy to use given that the setting of the research areas are different.The difference in the study areas could lead to conclusion that there are inconsistencies in literature on household energy behaviours .From this we would wish to eliminate this thought or notion in our study by laying our emphasis on the university setting which in our case is TaitaTaveta University and given that the logit model (logistic regression model) captures most of the factors considered during our study we would employ it during analysis for we will be able to predict or estimate the choice of cooking energy by students living outside the university hostels.
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