Household energy demand and environmental management in Kenya Nyang, F.O.

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1 UvA-DARE (Digital Academic Repository) Household energy demand and environmental management in Kenya Nyang, F.O. Link to publication Citation for published version (APA): Nyang, F. O. (1999). Household energy demand and environmental management in Kenya Amsterdam: Thela Thesis General rights It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulations If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. UvA-DARE is a service provided by the library of the University of Amsterdam ( Download date: 09 Feb 2018

2 Chapter 11 Summary and conclusions This is a study of household energy use and its linkages to environmental management in Kenya. It is based on a field survey of rural and urban households in eight districts spanning a cross section of the entire width of the country from the shores of lake Victoria in the west to the shores of the Indian ocean in the east. The data set used in this thesis had to be generated specifically for the purpose since there was no existing data that could be utilised for the analysis. Thus the generation of this data is in itself an achievement in the fields of energy economics and environmental management. The objective of this study was two-fold: First, to analyse the responsiveness of household energy demand to prices and income, taking into account the influence of demographic and environmental variables. This analysis is undertaken in Chapters 4, 5, and 6. The second objective was to analyse the interaction between energy demand and environmental management practices of the household with specific reference to firewood. This part of the analysis is undertaken in Chapters 7, 8, and 9. The policy implications and recommendations emanating from the entire analysis are discussed in Chapter 10. This thesis is divided into four parts: The first part involves the surveys; that is a literature survey, a survey of the applicable economic theory and econometrics, and the field survey. The second part involves the analysis of household demand for energy and fuels and corresponds with the first objective as described in the previous paragraph. The third part involves the analysis of the interactions between energy demand and the households environmental management practices; and corresponds with the second objective of the study. The fourth part involves an analysis of Kenya's energy policy in the light of the findings of this study. From the literature survey in Chapter 1 it is clear that the estimation of household energy consumption in developing countries is hampered by data limitations, hence the need to generate purpose-specific data sets. For instance, with the data generated for this analysis it was possible to include non-commercial fuels which are normally excluded from analyses because of a lack of routinely collected data. It was also possible to include variables of specific interest to this analysis; for example: variables describing the rural and urban sectors, the use of improved

3 Chapter 11: Summary and conclusions 197 woodfuel stoves, the assignment of property rights, and environmental management activities. The literature review further revealed that firewood is under-priced, but the extent of this underpricing is not often estimated. In this thesis the shadow price of collected firewood is estimated. Finally, the issue of environmental degradation in developing countries is discussed with emphasis being given to degradation with respect to firewood resources. Various indicators of firewood scarcity are discussed in the review; and these are later utilised in the thesis to develop firewood scarcity profiles for the sampled districts. Chapter 2 reviews some issues from economic theory and econometrics which are of relevance to the empirical estimation of consumer demand. The specific issues reviewed include aggregation, two-stage budgeting, and qualitative response modelling. The discussion in the next section is a general summary of the findings from the field survey from Chapter 3, and from the analyses in part two (Chapters 4, 5, 6); part three (Chapters 7, 8, 9); and part four (Chapter 10) of the thesis A summary of the findings Households in Kenya can use five different fuels to meet their various energy needs. The five are electricity, liquified petroleum gas (lpg), kerosene, charcoal, and firewood. From the analysis in Chapter 3 it was found that kerosene had the highest penetration rate at 95%, next was firewood at 74%, charcoal at 57%, electricity at 19%, and lpg at 9%. It was found that agricultural residues were also used as fuel, especially in rural households. The use of electricity and lpg were found to be more prevalent in urban centres than in rural areas. Although kerosene had equally high penetration rates both in urban centres and rural areas; urban households consumed more than 150% of the rural households kerosene consumption rates. Firewood and charcoal are referred to as non-commercial fuels because they may be obtained through both market and non-market channels. Most charcoal is obtained through market channels, but only a small proportion of firewood goes through market channels. It was found that only 24% of rural households used purchased firewood for which they paid a mean price of KSh 0.97 per kilogram. Most households collected firewood for their own use and hence spent a considerable amount of time on the activity: an average of twenty hours of household time to gather one month's supply of firewood. Firewood collection was found to be mainly the preserve of female adults and children. The combinations in which a given household uses the different fuels is referred to as the fuel mix. Twenty one different fuel mixes were identified during the field survey. It was found

4 ] 9g 11.1 A summary of findings that only five of the mixes are used by approximately 90% of the households in Kenya. Most rural households use only two kerosene+firewood based fuel mixes; while most urban households use four different kerosene+charcoal based fuel mixes. Urban households supplement the basic mix with lpg, electricity, and firewood; while rural households supplement the basic mix with charcoal. Negligible proportions of the households use either a fuel mix including all the five fuels; or a mix with a single fuel. The stand alone fuels are firewood, kerosene, or electricity. Environmental management practices of relevance to energy use amongst rural households were found to be mainly confined to conservation activities, the use of agricultural residues for fuel, the planting of trees, and the use of purchased firewood. Conservation activities mainly involved the establishment of physical conservation structures, and the use of biological measures. It was found that the on-farm tree density tended to be higher, the smaller the farm size. A negligible proportion of rural households reported planting trees solely for firewood production. The multi-product nature of trees was further underscored by the fact that two thirds of the households reported that firewood production was only one of the reasons they planted trees. In Chapter 4 use is made of the fact that different fuels have different energy densities to compute the households aggregate energy consumption. Thus the gross aggregate energy consumed by the household is obtained by aggregating the energy contained in the quantity of fuel consumed. It was found that the monthly gross aggregate energy consumption for rural households (5409 MJ) was much larger than the monthly gross aggregate consumption for urban households (3015 MJ). However, when the thermal efficiency of conversion devices are taken into account, the resulting aggregate which is the effective aggregate energy consumption was found to be similar for rural (657 MJ) and urban (637 MJ) households respectively. Urban households were thus found to use energy more efficiently than rural households. One reason for this being that urban households consumed more of high quality fuels such as electricity, lpg, and kerosene; hence the quality effect of the respective fuels was generally smaller for urban households than for rural ones. Another reason for the greater efficiency of energy use among urban households was their greater use of efficient conversion devices. For example the penetration rate of the Kenya ceramic jiko is higher among urban households (54%) than rural ones (32%). When coupled with the fact that the usage of charcoal is higher among urban households, it goes to confirm the higher energy use efficiency observed amongst urban households. The household energy consumption structure refers to the shares of the various fuels either in total energy consumption or in total energy expenditure. The energy consumption structure was found to differ between rural and urban households; as well as between commercial and noncommercial fuels. The difference was found to be largest in rural households. The fuel with the largest difference in both urban and rural households was electricity; while the fuel with the least

5 Chapter 11: Summary and conclusions QQ was firewood. The responsiveness of effective energy demand to income was found to be similar between rural and urban households; with the effective energy demand being income inelastic in both sectors. Note that effective energy takes into account the efficiency of conversion devices and hence the technical quality, but not the economic quality. When the economic quality of energy is taken into account by considering household energy demand in value terms, the responsiveness was found to differ between rural and urban households. In value terms, energy was found to be an inferior commodity in rural households; while in urban households energy was found to be a normal income inelastic commodity. Effective energy was also found to be price inelastic in both rural and urban households. However, the price elasticity of effective energy in urban households turned out to be approximately twice that in rural households. While the analysis in Chapter 4 involved aggregate energy, the continuation in Chapter 5 considers the individual fuels. When the fuels are considered individually, kerosene and lpg turned out to be income inelastic; while electricity, charcoal, and purchased firewood were income elastic. The individual fuels all turned out to be price inelastic except for kerosene in the kerosene+charcoal+firewood fuel mix. Kerosene was price elastic in this fuel mix. It was also found that substitute relationships among the fuels were more common than complementary ones. The notable substitute relationships include: electricity-charcoal; electricity-lpg; kerosene-charcoal; kerosene-firewood; and charcoal-firewood. The complementary relationships include: electricitykerosene; lpg-kerosene; and lpg-charcoal. Demographic variables performed poorly in the energy demand models in Chapter 4. The only variable with a statistically significant effect on household energy demand is the household size. Its co-efficient was positive and had a magnitude less than unity which indicates the existence of economies of scale in energy consumption. Demographic variables performed a little better in models of fuel demand in Chapter 5; where the co-efficients for the presence of children and the occupation of the household head were statistically significant. Notable performances of demographic variables were also to be found in the fuel choice models in Chapter 6, and in Chapter 9. The variables with a good performance include: the age, the educational attainments of the household head, his or her occupation, and the household size. Education has a significant positive impact on the probability of households using electricity; and on the probability of households in high altitude zones using agricultural residues for fuel. It also has a significant positive impact on the probability of households using purchased firewood. Households are encouraged to use improved woodfuel stoves because the stoves are said to save the target fuel. In this thesis, the variable describing the use of improved stoves is a dummy variable indicating whether or not a household uses the stove. Thus from the analyses in Chapters 4, 5, and 8; it is only possible to conclude whether stove users have a different

6 A summary of findings energy demand from non-users depending on the significance of the co-efficient, its sign, and magnitude. The statistical significance of the co-efficient for improved woodfuel stoves varied between the different fuel mixes. However, in most of the cases where it was significant, the users of improved stoves actually had a higher energy and fuel demand than non-users. The only exceptions were in the case of the kerosene+firewoodfuel mix for households using collected firewood, and for kerosene+charcoal mix. In the first case, the users of the maendeleo jiko have a lower demand for firewood than non-users; in the second case the users of the Kenya ceramic jiko have a lower demand for charcoal than non-users. In all the other cases involving both the Kenya ceramic jiko and the maendeleo jiko, the results indicate that stove users actually had a higher woodfuel demand than non-users. The decision of a household to use electricity or to use purchased firewood can be regarded as the adoption of a "new" technology or a new product in the market. Such decisions are partly modelled in Chapter 6, and partly in Chapter 9 within a qualitative response framework. The variables motivating household fuel choices are classified under three broad categories namely: environmental, demographic, and economic factors. For the households decision to use electricity, which is modelled in Chapter 6, spatial variables are the most important particularly the rural or urban location and the region. Altitude is important in so far as it influences the economic activities in a given region. Next in importance are demographic variables especially education and age, both of which have a positive impact on the households probability of using electricity. Economic variables such as income are significant but have a low impact on the probability of the household using electricity. Regarding the households decision to use purchased firewood which is analysed in Chapter 9, scarcity variables had the greatest positive impact. These include the effort expended in obtaining a unit of firewood; and the distance travelled in search of firewood. Education was the demographic variable with the greatest positive impact on the households decision to use purchased firewood. Environmental management variables such as the practise of conservation and the use of agricultural residues as fuel were insignificant. The only spatial variable that was found to be significant was the mean altitude. The coefficient for the region turned out to be insignificant. The only economic variable that was found to be a significant determinant of the households decision to use purchased firewood was the per capita farm size, which is also an inverse measure of population pressure on the land. The influence of this variable was negative: the higher the population pressure the more likely is the household to use purchased firewood; as is likely to be the case in the productive high altitude areas of Kenya. The households decision to use agricultural residues as fuel is analysed in Chapter 9. The decision was found to be very strongly and positively influenced by the households use of purchased firewood. Economic variables, but not household income per se, therefore have a

7 Chapter 11: Summary and conclusions 201 strong impact on this decision. Next in importance were spatial variables particularly the district and the altitude. The importance of these lie in the link between the agricultural production system, the altitude, and the production of agricultural residues. Thus at higher altitudes households are more likely to use agricultural residues as fuel. Other variables with a positive impact on the households decision to use agricultural residues for fuel include, the localised population pressure, the occupation of the household head, and his or her educational attainment. Although the quantity of firewood consumed by the household has a rather small impact on the decision to use agricultural residues for fuel; it is noteworthy that the larger the consumption of firewood, the less likely the household to use agricultural residues. Hence the more scarce firewood is the more likely is the household to use agricultural residues. This is likely to be the case in high altitude regions of Kenya. The concept of firewood scarcity is analysed in Chapter 7 where scarcity profiles are constructed for the sampled districts on the basis of various measures of firewood scarcity namely: the distance travelled to the source of firewood (taking the mode of transporting the firewood into account), the effort expended in obtaining a unit quantity of firewood, and the use of agricultural residues as fuel. Other measures of scarcity include the price of firewood in the local market, if this is available, and a measure of local firewood stocks, say the on-farm tree density. Although, the various measures give different rankings the general finding is that firewood scarcity is highest in Uasin Gishu and Kilifi districts, and lowest in Kakamega and Kitui districts. A proposal is made in Chapter 7 for an indicator of firewood scarcity which combines the various measures used to construct the firewood scarcity profile in the chapter. For instance, using the proposed indicator known as the firewood scarcity indicator (FSI) it was found that firewood scarcity was higher among households without title to their land holdings. It has been indicated that nearly three quarters of the households in Kenya rely on collected firewood; the collection of which involves a considerable expenditure of family labour especially that of women and children. When firewood is obtained via non-market channels it forms part of the households income; hence labour costs are important in the determination of the shadow price of collected firewood. The analysis in Chapter 8 which is an application of the agricultural household model confirms that the shadow price of collected firewood is fundamentally dependent upon the rural wage rates. At low wages, households save money by collecting firewood; however, this saving diminishes as rural wages approach urban wage rates. At higher wage rates such as those prevailing in urban centres the shadow price of collected firewood greatly exceeds the observed mean price of firewood. The observed mean firewood price was found to be as low as one third of the shadow price. This gives an indication of the extent by which firewood is under-priced. Collected firewood turned out to be income (imputed) elastic and price (imputed) inelastic with income and elasticity figures similar to those for

8 2Q A summary of findings purchased firewood. Collected firewood was also found to have a substitute relationship with both kerosene and charcoal. The energy related environmental management variables analysed in Chapter 9 include: the decision of the household to use purchased firewood; the decision to use agricultural residues as fuel; the decision of households to engage in conservation practices; and the role of conservation in the households farm-forestry activities. The first two have been discussed above. However, it is noteworthy here that the use of agricultural residues as fuel proved insignificant in the households decision to use purchased firewood, and in the decision to undertake conservation. The households decision to undertake conservation was found to be strongly influenced by spatial variables including region and altitude. The influence of region varied from region to region; but altitude had a positive impact. Thus the higher the altitude, the more likely is the household to undertake conservation. However, altitude per se is insufficient; hence the need to include a variable describing the region. This takes into account factors that vary by region such as the topography of the land and the production system. Education also has a positive impact on the households decision to undertake conservation. Finally, the role of conservation in the households farm-forestry activities is found to be insignificant. However, the security of tenure to land and the altitude play an important role in the households farm-forestry activities. Kenya's energy policy and its impact on the households use of energy is discussed in Chapter 10; where it is noted that the policy involves both demand and supply management. Under demand management both price and non-price strategies are used; with price strategies being applied to commercial fuels and non-price strategies to non-commercial fuels. The pricing strategy with regard to commercial fuels is biased towards the collection of revenue for the government, hence the revenue objective clearly over-shadows other objectives. Non-pricing strategies with regard to non-commercial fuels have been successful with regard to the dissemination of improved woodfuel stoves especially in urban centres. Improved woodfuel stoves have a higher penetration rate in urban centres than in rural areas. Supply management strategies are intended to influence the availability of energy resources. They basically involve resource management strategies and apply to both commercial and non-commercial fuels. Notable achievements with regard to commercial fuels include: the extension of the oil pipeline from Nairobi to Eldoret and Kisumu respectively; the re-organisation of the Kenya Power and Lighting Company (KPLC); the licensing of electric power producers independent from the KPLC; and the commencement of construction works for another hydroelectricity plant. However, low cost options such as energy conservation have received little emphasis. Supply management in the case of non-commercial fuels essentially involves the management of woodfuel resources and hence takes some form of farm-forestry. The initiatives

9 Chapter 11: Summary and conclusions 203 of the LEAP programme have worked successfully in Kakamega district, and provides a clear pointer of the sustainable way to woodfuel resource management. However, energy policy with regard to the environment is un co-ordinated, with various aspects being dealt with by different agencies Conclusions The responsiveness of aggregate energy demand to income, prices and other variables masks the responsiveness of the demand for individual fuels. Since policy issues apply to specific fuels it is more appropriate for analysts to consider the responsiveness in the demand for individual fuels. The revenue that the government of Kenya receives from the taxation of commercial fuels appears secure. The commercial fuels over which the government still exercise control via fiscal and economic measures are price inelastic. However, for non-commercial fuels fiscal and economic options are still inapplicable. Their enforcement would be quite difficult. Supply management is still the most effective via regulatory instruments, some of which are explained below. If not well managed, woodfuel consumption does have a deleterious effect on the environment. The management function, along with the appropriate incentives for optimal management, should therefore be bestowed upon individual resource users. For instance, the issuance of title deeds to land owners should be coupled with incentives to ensure compliance with proper methods of land management. These incentives need not be tax-based; other alternatives include properly functioning markets for non-export agricultural produce especially from low altitude zones. Collected firewood was found to have economic response characteristics similar to purchased firewood. Furthermore, the shadow price was critically dependent upon rural wage rates. Thus, the process of firewood commercialisation will depend to some extent on the structure of production in the rural sector. If the wage gap between the rural and urban sectors diminishes, firewood commercialisation in rural areas will catch up with the pace in urban centres. As an incentive in the management of woodfuel resources the government should put appropriate mechanisms in place to help narrow the wage gap. A good point to start is with reforms in agricultural marketing especially for products from low altitude zones. Farm-forestry and conservation practices as environmental management variables have no significant impact on firewood production. However, in view of the fact that only a negligible proportion of households plant trees for firewood production; these two management variables

10 Conclusions can be promoted as a package with the added benefit of firewood production. Firewood as a priority product may not be a viable promotion issue, however, as a low priority product it fits into the standard education and extension packages promoted by various agricultural and environmental extension agencies. In time firewood will occupy the position of a priority product. Since agricultural residues make a significant contribution to the energy needs of rural households, and no significant link has been established between their use as fuels and deterioration in environmental quality, their use as fuels should be encouraged. Households are already using them, the government should show the way by providing a framework for the promotion of their use. Since economic variables such as household income, are insignificant in the process of firewood commercialisation; and instead it is socialisation variables that have the biggest impact, this process can be significantly moved forward by a broad based education of the rural population. Most significantly issues relating to energy, environment, and agriculture should be on the agenda of education and extension agencies. The penetration rate of improved woodfuel stoves, particularly the Kenya ceramic jiko, is testimony that it saves fuel and money for the users. They have voted for it with their KSh, hence the dissemination of the stove is bound to continue. However, the users also tend to be heavy consumers of energy, hence there is still room for the improvement on the energy conservation practices of the users of improved stoves. In particular, the maendeleo jiko should be specially disseminated amongst households using the kerosene+firewood fuel mix since they actually have a lower demand for firewood than non-users. Such households are mainly to be found in the rural areas. Since urban households are more responsive to the quality attributes of fuels, high quality fuels should be promoted in urban households. A good example is electricity which already has a higher penetration rate in urban households than in rural households. The effects of the recent tariff hikes may induce consumers to substitute away from electricity in the short run. In the long run some consumers may even stop using electricity altogether, and so change to non-electricity fuel mixes, most of which include woodfuels. Such a move may impose increased pressure on woodfuel resources, and the environment in general. A policy of transparency and gradual change in electricity tariffs would be more appropriate as it allows time for the government, the utility company, and the consumers to adjust to the already effected and impending changes.