Christophe Muller
email: christophe.muller@univ-amu.fr.

Huijie Yan

Household Fuel Use in Developing Countries: Review of Theory and Evidence

Keywords: Household decisions, Fuel transition, Energy consumption JEL Classification: Q41, Q42, R22

Because of recent concerns about the negative externalities of traditional fuel use on the environment and health, the issue of the household fuel transition in developing countries, from dirty fuels towards clean fuels, has received growing research attention. This paper provides an up-to-date survey of the economic literature on household fuel use in these countries. First, we present the conceptual and theoretical frameworks. Then, we discuss the empirical results that show how a wide range of factors drive the household fuel transition. Finally, we suggest priorities for policy initiatives and highlight areas of future research.

Introduction

Currently, around 2.7 billion people still primarily rely on traditional biomass for cooking and heating in developing countries [START_REF] Yao | Analysis of rural residential energy consumption and corresponding carbon emissions in China[END_REF]. This is a cause for severe environmental and health problems. For example, the incomplete burning of these fuels is responsible for indoor air pollution, mostly associated with carbon monoxide, particulate matter, sulphur dioxide and nitrogen dioxide. These pollutants play a major role in generating respiratory diseases and cardiovascular mortality. The consumption of these fuels also spurs climate change by releasing carbon dioxide into the atmosphere. In turn, climate change damages agricultural production and subsequently threatens the nutritional health of human beings.

Because of these concerns, the issue of household fuel transition in developing countries, from dirty and traditional fuels to clean and modern fuels, has received growing research attention. Over the past three decades, a number of studies have investigated the factors driving the transition. Even though, some studies are merely based on simple descriptive statistics, one can see an emergence of the use of econometric methods to quantify the patterns and factors of household fuel use.

Despite intensive research, the knowledge about the determinants of household fuel use remains limited. For example, the actual impact of fuel prices on fuel substitution is still debated in the literature. Often, different conclusions have been reached concerning the effects of social-economic factors that drive fuel substitution. These divergences among authors translate into uncertainties when designing adequate energy policies.

In this context, we review a wide body of literature on the subject. The purposes of this survey are, thus, to identify knowledge gaps regarding the complex factors that drive the fuel transition, and, second, to facilitate policy design for promoting the use of cleaner fuels. Our survey complements and extends the contributions of [START_REF] Barnes | Rural energy in developing countries: A Challenge for Economic Development[END_REF], [START_REF] Kowsari | Three dimensional energy profile: A conceptual framework for assessing household energy use[END_REF], Lewis and Pattanayak (2012), [START_REF] Van Der Kroon | The energy ladder: Theoretical myth or empirical truth? Results from a meta-analysis[END_REF] and Malla and Timilsina (2014) in several respects. First, it presents a more comprehensive and updated review of the existing empirical findings on household fuel transition in developing countries, detailing for the first time the related econometric issues and theoretical issues. Second, it reviews the current state of knowledge and issues related to the theory of household fuel use, a relatively little treated question The remainder of the paper is organized as follows. Section 2 provides a review of the theoretical research. Section 3 discusses the empirical determinants of household fuel use. Section 4 examines the policy implications derived from the research. Finally, Section 5 offers concluding remarks and suggestions for future research.

Theoretical literature

This section discusses the conceptual and theoretical frameworks that guide the analyses of household fuel use in developing countries.

The "Energy ladder" theory

The 'energy ladder' has been a commonly used concept in explaining household fuel use in developing countries. The energy ladder depicts a process by which households, as their income rises, move away from traditional fuels (e.g., biomass), first to adopt intermediate fuels (kerosene, coal), and then to use modern fuels (gas, electricity). 1 In that sense, the energy ladder concept serves as a stylized extension of the typical income effect of consumer economic theory that explains how consumers substitute necessary goods and luxury goods for inferior goods, as their income rises. A subjacent assumption is that households are faced with an array of fuel choices that can be arranged according to increasing technological sophistication, and that this is reflected in household preferences. 2 As a consequence, as their income increases, households shift to more sophisticated energy carriers and simultaneously give up less 1 Heltberg (2005), [START_REF] Chambwera | Fuel switching in Harare: An almost ideal demand system approach[END_REF], [START_REF] Lay | Renewables in the energy transition: Evidence on solar home systems and lighting fuel choice in Kenya[END_REF]. 2 Hosier and Dowd (1987) [START_REF] Chambwera | Fuel switching in Harare: An almost ideal demand system approach[END_REF], Link et al. (2012). sophisticated alternatives. 3 In this theory, the characteristics of the final technologies are implicitly associated with some features of consumer preferences that divide the fuels into necessary goods and luxury goods. Although such hypothesis has still to be fully validated empirically, one achievement of this theory is its ability to fit well common observations of the strong income dependency of household fuel use.

The 'Fuel stacking' theory

However, Masera et al. (2000) criticized the energy ladder theory on the grounds that it cannot adequately describe the dynamics of households' fuel use. Instead, they note that fuel stacking is common in both urban and rural areas of developing countries. Fuel stacking corresponds to multiple fuel use patterns-where households choose a combination of fuels from both lower and upper levels of the ladder. Indeed, modern fuels may serve only as partial, rather than perfect substitutes for traditional fuels (van der [START_REF] Van Der Kroon | The energy ladder: Theoretical myth or empirical truth? Results from a meta-analysis[END_REF][START_REF] Van Der Kroon | The impact of the household decision environment on fuel choice behavior[END_REF]. Multiple fuel use arises from several reasons, such as, occasional shortages of modern fuels [START_REF] Hosier | Urban household energy use in Tanzania: prices, substitutes and poverty[END_REF][START_REF] Kowsari | Three dimensional energy profile: A conceptual framework for assessing household energy use[END_REF], high cost of appliances associated with using exclusively modern fuels [START_REF] Davis | Rural Household Energy Consumption: The Effects of Access to Electricity--Evidence from South Africa[END_REF], fluctuations of commercial fuel prices [START_REF] Leach | The energy transition[END_REF]) and preferences inducing households not to fully adopt modern fuels (Masera et al. 2000). The complexity of the fuel switching process thus suggests that there is a multiplicity of factors, besides income, that may affect fuel use. This led some authors to delve into more sophisticated modeling approaches. [START_REF] Edwards | Startup Costs and the Decision to Switch from Firewood to Gas Fuel[END_REF] and [START_REF] Gupta | Preferences for Domestic Fuel: Analysis with Socio-Economic Factors and Rankings in Kolkata, India[END_REF] set up household consumer models to describe the simultaneous consumption of non-commercial and commercial fuels in urban areas. They model households' fuel consumption by following standard consumers' utility maximization principles subject to a budget constraint, which bring about the driving role of prices. Even, in such narrow setting, the set of considered consumption goods vary with the studied contexts and the authors.

Urban household models

For example, [START_REF] Edwards | Startup Costs and the Decision to Switch from Firewood to Gas Fuel[END_REF] suppose that households maximize utility through the consumption of fuels, market good and stove (see Table 1). Instead [START_REF] Gupta | Preferences for Domestic Fuel: Analysis with Socio-Economic Factors and Rankings in Kolkata, India[END_REF] assume utility defined over consumption of fuels, food, health and other goods. These different specifications correspond to implicit assumptions of separability in preferences so as to allow for two-stage budgeting focusing on some goods of interest only. In all cases, fuel consumption is seen as fully determined by income, market prices and household preferences. However, this approach makes it hard to understand how non-market fuels, such as firewood and straw, may be included in household decisions, and what is the interaction with agricultural activities involving these products.

Agricultural household models

As a response to these limitations, a few authors proposed a more complex theoretical framework, particularly well fitted to rural households. It is well recognized that rural households in developing countries often face absent or incomplete markets, not only for fuels (e.g., firewood, electricity), but also for agricultural products, labor and credit.

In the absence of market failure, a rural household may be seen as behaving firstly as a profit maximizing producer, and then as a utility maximizing consumer given the profit realized in the first stage. Instead, under market failure, the allocation decisions for production and consumption are made jointly in a non-separable fashion.

Different types of market failures may lead to non-separabilities that matter for the analysis of fuel use. For example, [START_REF] Heltberg | Fuelwood Consumption and Forest Degradation: A Household Model for Domestic Energy Substitution in Rural India[END_REF] consider the market failures for crop residues, animal dung and labor. They study the substitution of private non-marketed fuels (animal dung and crop residues) for firewood, in response to increasing firewood scarcity. In that case, the diverse rural household's decisions relating to energy supply, energy demand, farm and off-farm labor supply are made simultaneously. In this framework, rural households are modeled as maximizing utility, subject to: leisure and budget constraints, an agricultural production function, a residue and dung production function, and finally a fuelwood collection function. Even under separability, the household total income is endogenous since it depends on production decisions that generate farm profits. A further complication brought by the non-separability is that the production constraints, or other non-budget constraints, have to be explicitly considered in the determination of consumption decisions, instead of merely summarizing their effects through an extended income variable in the budget.

In a non-separable model, the fuel use decision may thus be seen as guided by the household-specific shadow price of fuel, which depends on household and community characteristics associated with both preferences and all constraints. [START_REF] Chen | Energy Consumption in Rural China: A household Model for Three Villages in Jiangxi Province[END_REF] extend the approach of [START_REF] Heltberg | Fuelwood Consumption and Forest Degradation: A Household Model for Domestic Energy Substitution in Rural India[END_REF] by introducing the missing market for firewood, and emphasize the substitution between firewood and coal. Manning and Taylor (2014) consider rural labor market failure and substitution between firewood and gas. Finally, Muller and Yan (2014) propose a fully-fledged non-separable decision model that simultaneously links fuel use decisions with agricultural production, domestic technology, fuel collection technology and rationing of fuels.

Assessment

The conceptual and theoretical frameworks discussed above rely on the microeconomic theory of the consumer and they serve as the prominent explanations of the household fuel transition in developing countries. These approaches have progressively addressed how fuel decisions occur as part of the multiple activities in which households of developing countries engage. However, the challenge is still significant to obtain both sophisticated and tractable explanations of fuel uses in less developed countries. Detailed descriptions of market failures, domestic technologies, interactions between agricultural outputs and fuel types, and fuel rationing should play a larger role in realistic model specification. We now turn to empirical determinants of household fuel use that reflect the above theoretical reflections.

Empirical literature

Consistently with our theoretical discussion, the determinants of fuel use that are considered in the empirical literature can be categorized into: incomes, prices, household preferences, production characteristics and energy supply factors. Table 2 lists the effects estimated in the empirical literature, along with the data sources and the estimation methods. Early research into the determinants of the quantity of fuels consumed often applies OLS regression technique, sometimes with selectivity correction.. 4 To allow for zero quantity of fuels consumed, some studies use Tobit models. 5 Other authors investigate fuel choices from cross-section data with multinomial, probit or logit models. Finally, Muller and Yan (2014) estimate panel data random effect logit and multinomial models to investigate fuel choices in China. There is therefore a tendency towards increasingly flexible specifications, allowing for the discreteness in fuel type choices.

Note that the literature makes typically the implicit assumption that the estimated correlation effects well reflect causal effects of interest, sometimes with instrumentation of some total expenditure variables. It shares this feature with most consumption studies. Furthermore, we discuss all empirical results under the hypothesis that most specification errors in the models can be neglected, a strong while inevitable assumption in the state of this literature.

Income

The effects of income on fuel use have been investigated in almost all empirical econometric studies. Most authors specify income as a measure of household earnings. 6 Several authors also use household expenditure as a proxy for income. 7 That is because expenditure data are often more reliable and more reflective of long-term income.

Household wealth is sometimes used as an alternative measure approximated from information on household durable assets [START_REF] Chen | Energy Consumption in Rural China: A household Model for Three Villages in Jiangxi Province[END_REF][START_REF] Démurger | Poverty and Firewood Consumption: A Case Study of Rural Households in Northern China[END_REF].

Numerous studies point to income as the major driver behind the uptake of modern fuels. 8 Hosier and Dowd (1987) find that Zimbabwean urban households tend to move away from wood, towards kerosene and electricity, as their income rises. Ouedraogo (2006) observes in Burkina Faso that a higher income induces urban households to choose natural gas over kerosene. [START_REF] Baiyegunhi | Rural household fuel energy transition: Evidence from Giwa LGA Kaduna State, Nigeria[END_REF] show in rural Nigeria that the transition from fuelwood to kerosene, natural gas and electricity occurs along to rising income. A similar trend is observed when household expenditure is used as a proxy for income. [START_REF] Gupta | Preferences for Domestic Fuel: Analysis with Socio-Economic Factors and Rankings in Kolkata, India[END_REF] find in urban India some evidence for an energy transition from fuelwood and kerosene to LPG (Light Petroleum Gas), which is largely driven by expenditure levels. [START_REF] Lay | Renewables in the energy transition: Evidence on solar home systems and lighting fuel choice in Kenya[END_REF] show in Kenya that rising expenditure induces households to choose electricity and solar energy over wood and kerosene. In addition, [START_REF] Démurger | Poverty and Firewood Consumption: A Case Study of Rural Households in Northern China[END_REF] provide evidence indicating that Chinese rural households respond to rising wealth by substituting coal for firewood. All these studies seem to corroborate the energy ladder concept, which emphases income in explaining the transition from 'inferior' traditional fuels to 'normal' modern fuels.

However, such a simple pattern of income dependence is increasingly questioned by emerging empirical evidence showing that the effect of income on fuelwood demand in 6 For example, [START_REF] Hosier | Household fuel choice in Zimbabwe: an empirical test of the energy ladder hypothesis[END_REF], [START_REF] Abebaw | Household Determinants of Fuelwood Choice in Urban Ethiopia: A Case Study of Jimma Town[END_REF], [START_REF] Arthur | On the adoption of electricity as a domestic source by Mozambican households[END_REF], [START_REF] Zhang | The determinants of household energy demand in rural Beijing: Can environmentally friendly technologies be effective?[END_REF], [START_REF] Baiyegunhi | Rural household fuel energy transition: Evidence from Giwa LGA Kaduna State, Nigeria[END_REF] and Nlom and Karimov (2014). 7 An et al. (2002), [START_REF] Edwards | Startup Costs and the Decision to Switch from Firewood to Gas Fuel[END_REF], [START_REF] Rao | Variations in energy use by Indian households: An analysis of micro level data[END_REF], [START_REF] Akpalu | Demand for cooking fuels in a developing country: To what extent do taste and preferences matter?[END_REF] and [START_REF] Lee | Household energy mix in Uganda[END_REF]. 8 e.g., [START_REF] Brew-Hammond | Energy access in Africa: Challenges ahead[END_REF], [START_REF] Peng | Household Level Fuel Switching in Rural Hubei[END_REF] and [START_REF] Kowsari | Three dimensional energy profile: A conceptual framework for assessing household energy use[END_REF].

rural and urban households may sometimes be insignificant regardless of how income is measured. 9 Mekonnen (1999), [START_REF] Israel | Fuel Choice in Developing Countries: Evidence from Bolivia[END_REF], [START_REF] Lee | Household energy mix in Uganda[END_REF] and [START_REF] Guta | Effect of fuelwood scarcity and socio-economic factors on household bio-based energy use and energy substitution in rural Ethiopia[END_REF] report that in some contexts fuelwood is not an inferior good as often thought. [START_REF] Edwards | Startup Costs and the Decision to Switch from Firewood to Gas Fuel[END_REF] show that wood is a normal good for low income households, but an inferior good for high income households in Guatemala (i.e., an inverse U relationship between income and wood consumption). [START_REF] Heltberg | Fuel Switching: Evidence from Eight Developing Countries[END_REF][START_REF] Heltberg | Factors Determining Household Fuel Choice in Guatemala[END_REF] observe in different countries that, with increasing income, households tend to add modern fuels into their mix as partial rather than perfect substitutes for traditional ones. All these studies bring evidence against the energy ladder concept.

Table 3 reports the estimated income elasticities of fuel consumption, and of fuel choices for different fuel types, in the empirical literature. 10 The results show a wide range of estimates. For example, the income elasticity estimates for firewood consumption range from -1.7 to 1.85. Besides, the income elasticities of the choice probability for firewood fall into the -0.23 to 0.04 range. In turn, the income elasticity of charcoal consumption can drop as low as -0.28 [START_REF] Hughes-Cromwick | Nairobi households and their energy use: An economic analysis of consumption patterns[END_REF] or rise as high as 2.95 [START_REF] Pitt | Equity, Externalities and Energy Subsidies: The Case of Kerosene in Indonesia[END_REF]. In contrast, the estimates of the income elasticity of kerosene consumption are almost always positive and relatively inelastic, from 0.07 [START_REF] Lee | Household energy mix in Uganda[END_REF] to 0.59 [START_REF] Pitt | Equity, Externalities and Energy Subsidies: The Case of Kerosene in Indonesia[END_REF]. This implies that kerosene can be safely assumed to be a normal good for most households. In contrast, the estimates of gas and electricity income elasticities vary a lot across studies. The estimates reported by Macauley et al. (1989), [START_REF] Akpalu | Demand for cooking fuels in a developing country: To what extent do taste and preferences matter?[END_REF] and [START_REF] Lee | Household energy mix in Uganda[END_REF] suggest that LPG and electricity are necessary goods, while the results found by [START_REF] Hughes-Cromwick | Nairobi households and their energy use: An economic analysis of consumption patterns[END_REF] and [START_REF] Gupta | Preferences for Domestic Fuel: Analysis with Socio-Economic Factors and Rankings in Kolkata, India[END_REF] instead indicate that they are rather luxury goods in their studied context. Muller and Yan (2014) find an income elasticity of -0.15 for the choice probability of coal in rural China. In addition, the choice probabilities for gas and electricity appear to be 9 [START_REF] Kaul | Rural household energy use in China[END_REF], [START_REF] Chen | Energy Consumption in Rural China: A household Model for Three Villages in Jiangxi Province[END_REF], [START_REF] Akpalu | Demand for cooking fuels in a developing country: To what extent do taste and preferences matter?[END_REF], [START_REF] Zhang | The determinants of household energy demand in rural Beijing: Can environmentally friendly technologies be effective?[END_REF] and Manning and Taylor (2014). 10 As they are usually not provided by the authors, we computed, when possible, the elasticities from the published estimated coefficients and descriptive statistics, sometimes using lognormal approximations. However, the calculated elasticities in [START_REF] Farsi | Fuel Choices in Urban Indian Households[END_REF] turn out not to be reasonable and we drop them. In Gupta and Kohlin (2006) and in [START_REF] Lay | Renewables in the energy transition: Evidence on solar home systems and lighting fuel choice in Kenya[END_REF] only mean or median incomes are provided without dispersion information, and the calculus is not possible in that case. Finally, the elasticities in Muller and Yan (2014) are calculated from the multinomial logit estimates. rather inelastic. On the whole, it seems fair to say that while some fuels are more likely to be necessities in most cases (firewood, biomass) and others normal goods (kerosene), ultimately their classification into inferior goods, necessities and luxuries depends on the studied context and must therefore be carefully established empirically.

Prices

The role of fuel prices in household fuel use is emphasized in an extensive literature.

Table 2 shows the diversity of the price information used. However, most studies consider market prices among these for firewood, coal, charcoal, kerosene, LPG and electricity11 . Instead, Mekonnen (1999) and [START_REF] Démurger | Poverty and Firewood Consumption: A Case Study of Rural Households in Northern China[END_REF] use collection time as a proxy for the shadow price of firewood.

There is much evidence showing significant negative own-price effects both for the quantity of fuel consumed and the probability of choosing this fuel. For instance, [START_REF] Farsi | Fuel Choices in Urban Indian Households[END_REF] in India and [START_REF] Zhang | The determinants of household energy demand in rural Beijing: Can environmentally friendly technologies be effective?[END_REF] in Biejing, China find that an increase in LPG price significantly reduces the probability of choosing LPG and the LPG consumption, respectively. Many authors12 come up with a negative relationship between firewood consumption and firewood price. However, the magnitude of the effects varies across products, years and countries. For kerosene, [START_REF] Gupta | Preferences for Domestic Fuel: Analysis with Socio-Economic Factors and Rankings in Kolkata, India[END_REF] and [START_REF] Akpalu | Demand for cooking fuels in a developing country: To what extent do taste and preferences matter?[END_REF] observe that the demand is elastic (elasticity greater than unity in absolute value) with respect to own price in India and Ghana (see Table 4), while [START_REF] Pitt | Equity, Externalities and Energy Subsidies: The Case of Kerosene in Indonesia[END_REF] finds in Indonesia an own-price elasticity closer to unity in absolute value and [START_REF] Lee | Household energy mix in Uganda[END_REF] an elasticity of -0.32 in Uganda. [START_REF] Farsi | Fuel Choices in Urban Indian Households[END_REF] and [START_REF] Lay | Renewables in the energy transition: Evidence on solar home systems and lighting fuel choice in Kenya[END_REF] observe that the price of kerosene is associated with the expected negative effect on kerosene choice in India and Kenya. Moreover, there is also evidence of cases for which the own price has no significant impact on fuel use. Thus, [START_REF] Gupta | Preferences for Domestic Fuel: Analysis with Socio-Economic Factors and Rankings in Kolkata, India[END_REF] find in India an insignificant (negative) own-price elasticity for coal. Although own-price elasticities for coal separate into the ones for charcoal (mostly for the poorest countries) and proper coal, they are still generally significantly negative, ranging from -0.96 [START_REF] Guta | Effect of fuelwood scarcity and socio-economic factors on household bio-based energy use and energy substitution in rural Ethiopia[END_REF], for coal consumption) to -0.29 (Muller and Yan, 2004, for coal choice). Surprisingly, few estimates are available for electricity, for which we could only calculate the elasticities for three studies. Though, on the whole, negative own-price effects are rather well established empirically.

The cross-price effect estimates found in the literature are more controversial. Some scholars suggest that cross-price effects can be an important driver of fuel substitution. [START_REF] Peng | Household Level Fuel Switching in Rural Hubei[END_REF] show that high coal prices increase the probability of choosing biomass in China, suggesting that coal and biomass may be substitutes. [START_REF] Heltberg | Factors Determining Household Fuel Choice in Guatemala[END_REF] reports a significant substitution effect between light petroleum gas and wood in Guatemala. [START_REF] Pitt | Equity, Externalities and Energy Subsidies: The Case of Kerosene in Indonesia[END_REF] finds a significant substitution effect between kerosene and firewood in Indonesia. However, these findings are challenged by the evidence provided by other authors. [START_REF] Kaul | Rural household energy use in China[END_REF] and [START_REF] Zhang | The determinants of household energy demand in rural Beijing: Can environmentally friendly technologies be effective?[END_REF] find that an insignificant estimated coefficient of coal price for explaining fuelwood consumption in China. [START_REF] Gupta | Preferences for Domestic Fuel: Analysis with Socio-Economic Factors and Rankings in Kolkata, India[END_REF] conclude that coal and fuelwood have negative cross-price elasticities in India. [START_REF] Akpalu | Demand for cooking fuels in a developing country: To what extent do taste and preferences matter?[END_REF] also claim to observe complementarities between LPG and firewood in Ghana. [START_REF] Lay | Renewables in the energy transition: Evidence on solar home systems and lighting fuel choice in Kenya[END_REF] report a statistically significant negative effect of kerosene price on choosing wood in Kenya.

As a matter of fact, most statements of complementarities and substitutabilities of fuels by diverse authors are strictly speaking inaccurate since they are deduced from estimated direct price effects instead of compensated effects. In theory, such complementary/substitution relationships should be derived from a Slutsky equation, for example using a simple consumer model. In that case, cross-price effects can be decomposed into substitution and income effects. But it may occur that the income effect offsets the substitution effect, which would invalidate some of the stated interpretations in the literature. For example, the cross-price elasticity of -0.699 reported by [START_REF] Akpalu | Demand for cooking fuels in a developing country: To what extent do taste and preferences matter?[END_REF] would suggest at first sight that LPG and firewood are complements. However, since LPG has a relatively high income elasticity of 0.701 in this study, a decrease in real income due to an increase in firewood price may result in a decreased demand for LPG, even though the two considered fuels were (Slutsky-)substitutes.

Therefore, face to this impressive amount of analyses on the substitutability/complementarity of consumed fuels, it is useful to recall a few fundamentals of economic theory in order to relativise their interpretations. First, in a basic consumer model setting, one should estimate and control for the income effects before to deduce any substitutability/complementarity relationship. However, there is still more trouble ahead. Indeed, the relatively simple analysis of price effects in the consumer model does not extend so easily to more complex household models. Often, the prices of other consumed and produced goods may also affect fuel use. Finally, when consumption and production are not separable, which is the case for rural households under missing markets, the observed prices do not fully summarize the shadow prices that determine household decisions. In that case, e.g., in Muller and Yan (2014), it is still possible to exhibit how variations in food prices may affect fuel choices. Muller and Yan (2014) find that an increase in the price of purchased food make Chinese rural households to choose cheaper dirty fuels, while an increase in the price of self-produced food stimulates the switch to clean fuels. These considerations imply that price effect estimates in simple econometric specifications may be, at best, considered only as approximate estimates rather than definite ones, especially for rural areas. Therefore, caution must be applied when interpreting the estimated direct and especially cross price effects in the literature.

Household preferences

Previous research tends to focus on household characteristics that reflect blatant disparities in households' energy preferences. A wide range of factors describing age, gender, education, occupation, religion, lifestyle, household size, device characteristics and environment awareness have received attention.

1) Age

The empirical findings on the role of age in explaining household fuel use remain contradictory. Some studies find that age is positively associated with preference for traditional fuels. [START_REF] Baiyegunhi | Rural household fuel energy transition: Evidence from Giwa LGA Kaduna State, Nigeria[END_REF] observe that an increase in the age of household head induces Nigerian rural households to shift away from natural gas towards fuelwood. [START_REF] Edwards | Startup Costs and the Decision to Switch from Firewood to Gas Fuel[END_REF] show a positive and significant association of household head's age with wood consumption in Guatemalan households. [START_REF] Démurger | Poverty and Firewood Consumption: A Case Study of Rural Households in Northern China[END_REF] find that household average age has a positive and significant impact on firewood consumption in rural households of northern China. [START_REF] Gebreegziabher | Urban energy transition and technology adoption: The case of Tigrai, northern Ethiopia[END_REF] report that older household heads are more likely to consume charcoal, while less likely to consume kerosene and electricity in Ethiopia. [START_REF] Rahut | Determinants of household energy use in Bhutan[END_REF] show that households with older heads prefer fuelwood to electricity in Bhutan. Such preferences for traditional fuels support the notion that older people tend to perpetuate traditional habits, related to fuels, more than young people.

However, other authors find that age is instead positively associated with preference for modern fuels. [START_REF] Farsi | Fuel Choices in Urban Indian Households[END_REF] and [START_REF] Gupta | Preferences for Domestic Fuel: Analysis with Socio-Economic Factors and Rankings in Kolkata, India[END_REF] provide evidence showing that older household heads are more likely to prefer LNG (Light Natural Gas) to wood in Indian households. [START_REF] Rao | Variations in energy use by Indian households: An analysis of micro level data[END_REF] use instead the average age of household members and find similar results. [START_REF] Guta | Application of an almost ideal demand system (AIDS) to Ethiopian rural residential energy use: Panel data evidence[END_REF] finds that older household heads are more likely to prefer modern fuels to traditional fuels in Ethiopian rural households. Özcan et al. (2013) observe that older household heads are more likely to shift away from wood towards natural gas, liquid fuel and electricity in Turkey. These results may suggest a life cycle effect where young people facing liquidity constraints would resort to cheaper fuels, while old people would be able to afford cleaner fuels more easily. In addition, [START_REF] An | Modeling the choice to switch from fuelwood to electricity Implications for giant panda habitat conservation[END_REF], [START_REF] Israel | Fuel Choice in Developing Countries: Evidence from Bolivia[END_REF] and [START_REF] Abebaw | Household Determinants of Fuelwood Choice in Urban Ethiopia: A Case Study of Jimma Town[END_REF] claim that age is not affecting fuel use.

2) Gender

Gender is another debated factor. There is evidence indicating that female-headed households prefer modern fuels to traditional fuels [START_REF] Farsi | Fuel Choices in Urban Indian Households[END_REF][START_REF] Rao | Variations in energy use by Indian households: An analysis of micro level data[END_REF][START_REF] Rahut | Determinants of household energy use in Bhutan[END_REF]). This may be attributed to the fact that women are often responsible for household cooking and thus they are directly affected by the air pollution emitted from the burning of the dirty fuels. However, this evidence is challenged by [START_REF] An | Modeling the choice to switch from fuelwood to electricity Implications for giant panda habitat conservation[END_REF], Ouedraogo (2006) and [START_REF] Abebaw | Household Determinants of Fuelwood Choice in Urban Ethiopia: A Case Study of Jimma Town[END_REF] who observe that the coefficient of gender of the household's head is insignificant in some contexts. Link et al. (2012) show that a high proportion of female members induce households to use fuelwood in Nepal. This is attributed to the fact that women are the main gatherers of fuelwood. In contrast, [START_REF] Heltberg | Factors Determining Household Fuel Choice in Guatemala[END_REF] observes that a large proportion of female does not affect the use of fuelwood in Guatemala. Moreover, [START_REF] Israel | Fuel Choice in Developing Countries: Evidence from Bolivia[END_REF] finds an association of a high female share of the family earned income with a low probability of using firewood in urban Bolivia. Women who work for monetary compensation may have higher opportunity costs of time and thus prefer time-saving fuel. Nonetheless, [START_REF] Gupta | Preferences for Domestic Fuel: Analysis with Socio-Economic Factors and Rankings in Kolkata, India[END_REF] find that the number of women not working does not affect fuel use in India. The general impression produced by all these results is that the role of gender in explaining fuel use stems from a combination of preferences characteristics, time opportunity cost considerations and within-household bargaining position of women.

3) Education

The importance of education in the decision making process of fuel use is emphasized in various studies. For example, education level is found to have a negative relationship with firewood consumption by [START_REF] Abebaw | Household Determinants of Fuelwood Choice in Urban Ethiopia: A Case Study of Jimma Town[END_REF] and [START_REF] Démurger | Poverty and Firewood Consumption: A Case Study of Rural Households in Northern China[END_REF]. The opportunity costs of fuel collection time, seen as increasing in education, may explain the observed results. Likewise, more education generally implies higher income. It may thus be that the estimated education effect is just an ill observed income effect, which is consistent with typical rankings of fuels according to necessities and luxuries. [START_REF] Gupta | Preferences for Domestic Fuel: Analysis with Socio-Economic Factors and Rankings in Kolkata, India[END_REF] and [START_REF] Baiyegunhi | Rural household fuel energy transition: Evidence from Giwa LGA Kaduna State, Nigeria[END_REF] observe in India and Nigeria that a higher education level induces households to move away from firewood dependence towards the use of kerosene and LPG. [START_REF] Gebreegziabher | Urban energy transition and technology adoption: The case of Tigrai, northern Ethiopia[END_REF] find in Ethiopia that, the higher the education level, the less likely the households will choose wood, while the more likely the households will choose electricity. [START_REF] Lay | Renewables in the energy transition: Evidence on solar home systems and lighting fuel choice in Kenya[END_REF] show in Kenya that a higher education level is associated with a higher probability of using electricity and solar energy, and with a lower probability of using wood and kerosene. Beyond its effect on tastes and time opportunity costs, education as a powerful determinant of fuel switching could also be explained by better education translating into higher awareness of the negative health impacts of dirty fuels, and enhanced knowledge about efficiency and convenience of modern fuels [START_REF] Farsi | Fuel Choices in Urban Indian Households[END_REF]). Identifying how these distinct channels of education influence combine or separate is one of the challenges of future research.

4) Household size

Household size also plays an important role in energy choices. [START_REF] Israel | Fuel Choice in Developing Countries: Evidence from Bolivia[END_REF], [START_REF] Abebaw | Household Determinants of Fuelwood Choice in Urban Ethiopia: A Case Study of Jimma Town[END_REF] and [START_REF] Zhang | The determinants of household energy demand in rural Beijing: Can environmentally friendly technologies be effective?[END_REF] all find evidence of negative association of household size with per capita energy consumption. These results may reveal the presence of economies of scale in energy use. Alternatively, they may merely stand in for a subjacent income effect if equivalent incomes are measured by dividing income by a scale increasing in household size, as usual. Note that the effect of household size on fuel switching still remains ambiguous empirically. The results in the studies of [START_REF] Reddy | A multilogit model for fuel shifts in the domestic sector[END_REF]), Ouedraogo (2006), [START_REF] Rao | Variations in energy use by Indian households: An analysis of micro level data[END_REF], [START_REF] Pandey | Comprehending household cooking energy choice in rural India[END_REF] and Özcan et al. (2013) indicate that larger households prefer dirty fuels over clean fuels.

One possible reason is that household size is often larger in poorer households that cannot afford modern fuels. Instead, [START_REF] Hosier | Household fuel choice in Zimbabwe: an empirical test of the energy ladder hypothesis[END_REF], [START_REF] Gupta | Preferences for Domestic Fuel: Analysis with Socio-Economic Factors and Rankings in Kolkata, India[END_REF] and [START_REF] Baiyegunhi | Rural household fuel energy transition: Evidence from Giwa LGA Kaduna State, Nigeria[END_REF] find the opposite trend: households with larger members are more likely to choose clean fuels. Besides, [START_REF] Chen | Energy Consumption in Rural China: A household Model for Three Villages in Jiangxi Province[END_REF] and [START_REF] Guta | Application of an almost ideal demand system (AIDS) to Ethiopian rural residential energy use: Panel data evidence[END_REF] show insignificant impact of household size on household fuel transition.

Another contrasting finding is that of [START_REF] Heltberg | Fuel Switching: Evidence from Eight Developing Countries[END_REF], who reports that larger households are more likely to consume both dirty and clean fuels (i.e., they are more involved in fuel stacking). Clearly, the nature and the shape of the effects of household composition on fuel use still need more investigations to identify what the mechanisms at work are.

5) Lifestyle

Lifestyle factors such as cooking habits, food tastes and cultural beliefs are found to be closely linked to the observed fuel use behavior. [START_REF] Baiyegunhi | Rural household fuel energy transition: Evidence from Giwa LGA Kaduna State, Nigeria[END_REF] find in Nigeria that longer cooking time hampers the transition from fuelwood to natural gas and electricity. [START_REF] Pundo | Multinomial logit analysis of household cooking fuel choice in rural Kenya: The case of Kisumu district[END_REF] obtain a similar result with Kenyan households preferring firewood over charcoal and kerosene when food requires lengthy cooking. A possible reason may be that fuelwood alternatives have higher relative costs per unit of time [START_REF] Baiyegunhi | Rural household fuel energy transition: Evidence from Giwa LGA Kaduna State, Nigeria[END_REF]. It may also be that lengthy cooking is found inconvenient by some household members, and using some fuel type may help reduce cooking time. The taste of the cooked meals may also be a reason for fuel choice. For example, Ouedraogo ( 2006) finds that a more common occurrence of cooking tô increases the likelihood of using firewood in Ouagadougou.13

Domestic constraints

Practical domestic constraints play a role for how cooking tasks can be performed.

They can be gathered into too categories respectively linked to dwelling and device characteristics.

1) Dwelling characteristics

A few dwelling characteristics are sometimes listed among the determinants of fuel choices. Diverse measures of dwelling characteristics have been used: dwelling ownership, material used for floor, roof and wall, modern or traditional dwelling unit, number of room, drinking water source and whether house is electrified or not. The dwelling characteristics are often considered as proxies of a household's wealth and living conditions. They can also be seen as constraints to choices. For example, inflammable house material may deter the use of firewood; or installing some cooking device may favour some fuels. Using electricity is facilitated by the existence of electric connections already in place, and this may be more likely in modern-type housing. [START_REF] Arthur | On the adoption of electricity as a domestic source by Mozambican households[END_REF], [START_REF] Lay | Renewables in the energy transition: Evidence on solar home systems and lighting fuel choice in Kenya[END_REF] and [START_REF] Baiyegunhi | Rural household fuel energy transition: Evidence from Giwa LGA Kaduna State, Nigeria[END_REF] find that house owners are more likely to shift towards cleaner fuels as compared to tenants, which is contrary to the results reported by Ouedraogo (2006) and [START_REF] Pundo | Multinomial logit analysis of household cooking fuel choice in rural Kenya: The case of Kisumu district[END_REF]. [START_REF] Baiyegunhi | Rural household fuel energy transition: Evidence from Giwa LGA Kaduna State, Nigeria[END_REF] observe in Nigeria that households living in traditional houses are less likely to choose natural gas and electricity over fuelwood. [START_REF] Heltberg | Factors Determining Household Fuel Choice in Guatemala[END_REF] shows in Guatemala the association of number of rooms with a switch away from wood towards LPG exclusively. [START_REF] Arthur | On the adoption of electricity as a domestic source by Mozambican households[END_REF] find in Mozambique that house size measured by the number of rooms is associated with adoption of electricity. Similarly, they found that the access to piped water induces an increase in the likelihood of using electricity. [START_REF] Heltberg | Fuel Switching: Evidence from Eight Developing Countries[END_REF] also exhibits a link between access to tap water and LPG usage in eight different countries. Moreover, [START_REF] Heltberg | Fuel Switching: Evidence from Eight Developing Countries[END_REF] and Ouedraogo (2006) point to the higher propensity of electrified households to move towards modern fuels. All these results, consistent with the energy ladder model, suggest that subjacent income effects may be present, if one chooses to interpret the coefficient of these dwelling characteristics as related to some ill observed income effect. However, other explanations are also possible as for example the proximity of wood material that could be used simultaneously to construct dwellings and as fuel, or other unobserved domestic constraints.

2) Device characteristics

Other determining factors may include cooking and heating device and appliance characteristics, since they imply different domestic technologies of fuel use. Obviously, not all sources of energy are compatible with using traditional furnaces, for example. In that sense, the choice of fuel may be simultaneous with device acquisition or may be constrained by the devices already available at home. However, the empirical evidence in this regard is scant. [START_REF] Chen | Energy Consumption in Rural China: A household Model for Three Villages in Jiangxi Province[END_REF] find in Chinese villages that the possession of improved stoves does not affect fuelwood consumption but results in lower coal consumption. [START_REF] Hughes-Cromwick | Nairobi households and their energy use: An economic analysis of consumption patterns[END_REF] and Manning and Taylor (2014) suggest that ownership of modern cooking and heating appliances is a necessary condition for adopting higher-grade energy sources. Similarly, [START_REF] Edwards | Startup Costs and the Decision to Switch from Firewood to Gas Fuel[END_REF] claim that in Guatemala the high upfront cost of appliances is a significant impediment to the adoption of LPG as an alternative to wood .

These results point to joint choices of energy sources and of appliances, while they need confirmation.

Production characteristics

Several authors provide evidence that the pattern of fuel use of rural households may depend on agricultural production characteristics. This is consistent with non-separable agricultural household models in which consumption and production decisions are made jointly. In this sense, the fuel consumption decisions may be seen as guided by the household-specific shadow prices of fuel, which potentially depend on all household and community characteristics associated with consumption and production. To reflect agricultural production characteristics, the authors have relied on the following variables: farmland size, livestock number, household size and ratios of labor force by activities, which are directly included in fuel use regressions.

The evidence on the effects of household production assets, as measured by farmland size or livestock, on fuel use is ambiguous. However, it is often in favour of a direct link between fuel choice and the biomass byproducts of the farm activities. [START_REF] Chen | Energy Consumption in Rural China: A household Model for Three Villages in Jiangxi Province[END_REF] find that, in a remote Chinese village, farmland size does not affect firewood consumption. On the contrary, still for China, [START_REF] Démurger | Poverty and Firewood Consumption: A Case Study of Rural Households in Northern China[END_REF] report that farmland size is associated with a significant increase in firewood consumption in Labagoumen township. Likewise, [START_REF] Kaul | Rural household energy use in China[END_REF] and [START_REF] Pandey | Comprehending household cooking energy choice in rural India[END_REF] find a close link between farmland size and the use of biomass in China and India. [START_REF] Démurger | Poverty and Firewood Consumption: A Case Study of Rural Households in Northern China[END_REF] also observe that households with more livestock have lower firewood consumption, which is contrary to the findings of [START_REF] Kaul | Rural household energy use in China[END_REF][START_REF] Kaul | Rural household energy use in China[END_REF]Mekonnen (1999) in the distinct Ethiopian context, who finds the opposite effect. [START_REF] Guta | Application of an almost ideal demand system (AIDS) to Ethiopian rural residential energy use: Panel data evidence[END_REF] finds, in Ethiopia, that households with a larger livestock prefer traditional fuels and mix of fuels over modern fuels only. These contradictory results found in different contexts may reflect different local habits in fuel collection. In any case, it is interesting to note that the correlation of household assets with fuel choice cannot be readily interpreted as a mere income effect since it does not systematically follow the 'ladder' of energy sources.

The empirical findings for the effect of household time endowment, measured by household size, or proportion of active members, are mixed. As mentioned before, the positive association of household size with biomass consumption is often observed. 14Beyond the already mentioned interpretation of income effects, another, not exclusive interpretation is that of larger households having more available labor both for firewood collection and agricultural production. This labour endowment translates into lower opportunity costs of collecting firewood and preparing crop residues for combustion. [START_REF] Chen | Energy Consumption in Rural China: A household Model for Three Villages in Jiangxi Province[END_REF] find in China a positive association between proportion of active members and fuelwood consumption, albeit Zhang and Koji (2012) find an opposite trend. Still for rural China, Muller and Yan (2014) find an association of agricultural specialization with higher probability of using biomass as fuel. In all cases, at least in rural areas, production characteristics, including agricultural specialization or labor force endowment, appear to be connected to fuel choices, although this is rarely taken into account in the modeling approaches in the literature.

Access

Obviously, availability and accessibility of fuels should contribute to explaining household fuel use. In the literature, the availability of traditional fuels has been measured by: distance to fuelwood [START_REF] Kaul | Rural household energy use in China[END_REF][START_REF] An | Modeling the choice to switch from fuelwood to electricity Implications for giant panda habitat conservation[END_REF][START_REF] Heltberg | Factors Determining Household Fuel Choice in Guatemala[END_REF], households' perceptions of availability of fuelwood [START_REF] Hosier | Household fuel choice in Zimbabwe: an empirical test of the energy ladder hypothesis[END_REF] and geographic location [START_REF] Peng | Household Level Fuel Switching in Rural Hubei[END_REF]). On the other hand, the accessibility of modern fuels has been measured by: households' perceptions of availability of LPG [START_REF] Gupta | Preferences for Domestic Fuel: Analysis with Socio-Economic Factors and Rankings in Kolkata, India[END_REF], community access to electricity [START_REF] Heltberg | Fuel Switching: Evidence from Eight Developing Countries[END_REF][START_REF] Lay | Renewables in the energy transition: Evidence on solar home systems and lighting fuel choice in Kenya[END_REF], prevalence of solar home systems [START_REF] Lay | Renewables in the energy transition: Evidence on solar home systems and lighting fuel choice in Kenya[END_REF]) and renewable energy technologies [START_REF] Zhang | The determinants of household energy demand in rural Beijing: Can environmentally friendly technologies be effective?[END_REF].

It is also recognized that the scarcity of traditional fuels may affect fuel use. Several authors find that households living far from fuelwood sources tend to shift towards fuelwood alternatives. 15 This can be explained by higher opportunity costs of collection time. [START_REF] Hosier | Household fuel choice in Zimbabwe: an empirical test of the energy ladder hypothesis[END_REF] find that households who do not perceive any difficulty in collecting wood tend to use more wood in Zimbabwe. Some scholars go as far as to attribute the fuel transition to improved access to modern energy, mostly electricity. [START_REF] Heltberg | Fuel Switching: Evidence from Eight Developing Countries[END_REF] reports a strong link between electrification at community level, on the one hand, and incidence of LPG use in India and Brazil, on the other. [START_REF] Lay | Renewables in the energy transition: Evidence on solar home systems and lighting fuel choice in Kenya[END_REF] observe that improved access to electric power induces Kenyan households to move away from wood and kerosene towards electricity. [START_REF] An | Modeling the choice to switch from fuelwood to electricity Implications for giant panda habitat conservation[END_REF] argue that low voltage levels and high outage frequencies hinder the adoption of electricity by Chinese. [START_REF] Zhang | The determinants of household energy demand in rural Beijing: Can environmentally friendly technologies be effective?[END_REF] and [START_REF] Lay | Renewables in the energy transition: Evidence on solar home systems and lighting fuel choice in Kenya[END_REF] provide evidence that access to renewable energy technology fosters a greater acceptance of modern fuels by households. In the next section, we discuss a few policy implications of all these empirical findings.

Policy Implications for the Fuel Transition

In this section, we examine a few policy implications about how to foster the fuel transition. First, some economic changes may not stem from policies, while they could still enhance incomes, and thereby spur the transition to modern fuels because of income effects, as long as dirty fuels are inferior goods and clean fuels are necessary or luxury goods. This is the case of the improvement of living standards that arises naturally from the growth of the economy. However, the question of why the use of firewood is persistent as income rises remains not well answered. This may be first related to the uncertain characterization of firewood as either a normal or an inferior good. It may also be that other factors, such as preferences for food cooked firewood, limited access to modern fuels, or opportunity costs from time-consuming activities, dominate income effects.

Second, price policies can be implemented in the form of price taxes to deter the consumption of dirty fuels, and/or price subsidies to foster the use of clean fuels. In some countries, a certain degree of local decentralization of price policies is possible (e.g., in China, Su, 2011). Nonetheless, the commonly observed negative effect of own-price suggests that central governments ought to tax carbon-intensive fuels on the one hand, and subsidize modern clean fuel types on the other hand. However, the lack of agreement on the levels of elasticities across countries implies that actual price responses should be carefully investigated in each context before designing tax policies. Some words of caution are of order here. Although price subsidies for modern fuels have been historically used for promoting fuel transition, they are often undesirable, beyond the well known issue of the price distortions caused by price subsidies. One reason is that subsidies may be financially unsustainable for the State. Another reason is that subsidy programs are often ill targeted. Indeed, they typically benefit high-income households disproportionately more than the poor. Finally, the poor face barriers of high connection costs for electricity. Then, they may little benefit from subsidies, and therefore little change their fuel use pattern. Under these circumstances, policy makers need to look beyond pricing measures for broader policy options.

Third, more policy emphasis should be laid on the factors fostering household preferences that favor modern clean fuels. In particular, specific education curricula should be promoted so as to better inform households of the benefits of adopting clean fuels. Practical training on how to use the fuels and the corresponding devices would be useful and easy to implement. For example, one could disseminate the lessons from the numerous development projects promoting the use of improved furnaces in less developed countries. In addition, policy initiatives should encourage the transformation of the traditional lifestyle, since sustained use of modern fuels requires compatibility with local lifestyles. For example, diet changes may make firewood cooking less attractive.

Fourth, the costs of the practical use of different fuels could be converted into policy instruments. For example, the government may increase the opportunity cost of time for gathering biomass. Policy could also directly address stove acquisition and start-up cost problems, because of the connected choices of fuel types and of appliances. The initial investment cost of modern fuel devices has been mentioned in the empirical literature as a barrier to upward fuel switching. Providing subsidies or credit for purchasing these devices seems to be a promising policy direction.

Fifth, the findings exhibiting the dependence of rural household fuel use on agricultural production characteristics suggest that policies should account for the non-separability of consumption and production decisions in the contexts of imperfect rural markets. Therefore, effective policies for promoting the fuel transition in rural areas could depend on socioeconomic or technological characteristics pertaining to consumption and production activities, and shaping household's responses to market failures. For example, in China, financial incentives are proposed by the government to pork producers to incentivized them to raise their output level. Such policy measures are likely to generate a higher use of biomass by-products as fuels by these households or their neighbours. Some coordination of agricultural and energy policies would be desirable in that case.

Finally, policies should lay more emphasis on supply-driven factors. On the one hand, and given the evidence showing a strong link between the household fuel transition and access to modern energy, either governments or markets should ensure a sufficient and reliable supply of modern fuels. On the other hand, policy makers could devote more efforts to restrict the availability of traditional fuels. Given the strong effect of wood scarcity on this fuel use, forbidding wood collection, or at least raising the opportunity costs of wood collection by barriers may yield results. To reduce biomass use as fuel, the government may support the commercialization of biomass by subsidizing investment in biomass-based clean energy (e.g., biomass-based power generation) or other industrial uses. Surely, more policy recommendations could be suggested from what has been learned in the literature. However, many interesting findings still remain rather isolated and would require confirmation.

Conclusion

Our survey has detailed the theoretical and empirical underpinnings of household fuel use in developing countries. Household fuel use was initially explained by the "energy ladder" concept that much boils down to traditional income effects in the economic consumer model. Subsequently, more sophisticated urban and agricultural household models were proposed to explain fuel use patterns. Our review of the empirical literature reveals a few noticeable findings. Firstly, beyond income, an intricate web of closely interrelated social-economic factors drive the household fuel transition, and the extent of influence from these factors varies widely within or across countries.

Secondly, the pace of the upward transition brought about by shifting energy prices also varies widely across countries. Thirdly, the sustained use of modern clean fuels requires the compatibility of stove technologies with local lifestyles. Fourthly, in contexts of imperfect markets, the fuel transition in rural households depends upon the interaction of non-separable consumption and production household decisions. Finally, easy access to modern energy sources is a necessary condition for the transition.

Although there has been considerable progress in both the theoretical and empirical research on household fuel use in the past three decades, there remain areas where more research is needed. First, future studies should provide additional evidence on the determinants of fuel stacking. The hypothesis of fuel stacking behavior, especially in rural households, has been gaining increasing support in the literature. Nonetheless, econometric estimations of fuel stacking models are almost completely lacking. As a consequence, the causes of fuel stacking are still not well understood.

Second, future studies should further examine the impacts of awareness of the health hazards of indoor air pollution resulting from dirty fuel use. There is a growing recognition that such awareness may motivate households to shift toward clean fuels.

However, to date only [START_REF] Gupta | Preferences for Domestic Fuel: Analysis with Socio-Economic Factors and Rankings in Kolkata, India[END_REF] have provided empirical evidence on these effects.

Third, additional evidence on evaluating the effectiveness of renewable energy technologies is needed for designing future policies aimed at promoting the deployment of these technologies. The diversification brought by renewable energies technologies is expected to improve the energy consumption structure in developing countries.

However, understanding of the role that renewable energy technologies play in the household fuel transition is still lacking.

Fourth, future research should further explore the impacts of off-farm employment on the rural households' fuel transition. Off-farm employment participation, especially through migration, is one of the quintessential features of economic development in developing countries. Off-farm employment complicatedly affects household fuel transition through providing new income sources, increasing fuel consumption, diminishing household available labor and also changing household habits [START_REF] Shi | The Role of Off-Farm Employment in the Rural Energy Consumption Transition -A Village-Level Analysis in Jiangxi Province, China[END_REF]). However, current research has not adequately addressed these issues.

Finally, future research should not neglect the impacts of food prices, especially on rural households. As a matter of fact, rising food prices could either foster or impede the fuel transition, both through consumer-side and producer-side effects. On the consumer side, an increase in the price of purchased food may induce rural households to choose cheap dirty fuels so as to be able to meet their necessary food needs. On the producer side, an increase in the price of self-produced food may shift the budget constraint by an extra income. This additional income effect may stimulate the fuel transition to clean fuels if fuel is a normal good. Moreover, non-separable effects of food prices may occur.

For example, a hike in pork price in China may stimulate both pig production and the production biomass by-products that are used as convenient energy sources by producer households. What is also missing is a theoretical standard comparative statics framework that would clarify the meaning of the estimated price effects, and help eliciting substitutability and complementarity with fuels. In these conditions, it is still early days for a deep understanding of food price effects on household fuel use.

Lewis, Jessica J., and Subhrendu K. Pattanayak. 2012. "Who Adopts Improved Fuels and Cookstoves? A Systematic Review." Environmental Health Perspectives 120 (5): 637-45. Link, Cynthia F., William G. Axinn, and Dirgha J. Ghimire. 2012. "Household energy consumption: Community context and the fuelwood transition." Social Science p e is the consumption vector of private non-marketed fuels (e.g., crop residues, animal dung), m l and w l are the leisure times, respectively for adult men, women and children, w f l is female and child labor time spent collecting firewood, m a l and w a l are male farm labor time, and female/child labor time, respectively, inp measures the use of residues and dung as farm inputs, p q is the vector of the private non-marketed fuel productions, m out l is male labor time in off-farm work.

) ; ( v f f z l q ) ; ( h a a z l q E wl q p e p c p out a a c c M M     T l l l l out a f    
g f F m   ) , ( f f f k l q ) ( a a l q q p a T D S p c p a a s M M     ) ; ) 1 ((  T l l l l c a f     

Muller and Yan

(2014) f ), ; , ( (  p h C C C U ), , , ( (
dc ds dw d F F F F F ) ( dw dw L q c ds M Q q     ), , ( ( c c c AG A L Q Q ) )); ( , (  l h p l L M M Q ce ce cl cl dc dc p p h h p F p F p F p C p C     0 ) ( Y wL p M p A p Q off mp p ac c h AG      T l L L L L off l c dw      ) ; ), ); , ( Z l V F F F ce cl c a) m c
e) F c is the vector of home-produced food, g e measures the use of gas, c l is the household labor time spent in cooking,  is the proportion of households living at home and represents the proportion of the labor endowment in the household, is time endowment in household,

T

) 1 (   describes migrations to the US, a is the migration cost, D denotes the remittances.

f) h C and p C describe the vectors of the household produced and consumed food, on the one hand, and of the market-purchased food, on the other.  stands for predetermined variables related to the domestic technology and constraints yielding the final food consumption. Z is a vector of household characteristics pertaining to preferences, notably with respect to fuel use.

Table 1 Theoretical models of fuel use

 1

	Author	Utility function					Firewood	Agricultural	Income constraint	Time constraint
																	collection/private	production
																	fuel production	function
																	function
	Chen et al. (2006) a	U	( c	H	( e	f	,	e c	,	S	),	c M	,	l	;	z	)

  describes the consumption vector of market goods, h c is the consumption vector of household goods, f e and e are the amounts of firewood and energy used, Sindicates whether the household owns a stove or not, z represents the vector of household characteristics, m p , ) c is food consumption, G groceries, i F is the vector of fuels as input in the domestic food consumption technology (cooking), H is an health indicator, I is health-related investment and consumption, i K denotes the polluting characteristics of fuel, X describes other goods and services. coal and agricultural goods, w is the exogenous wage rate, out l is labor time spent off-farm, E is the exogenous household income, T is the total

		f p , e e p and s p are the prices of market good,
		firewood, energy and stove, respectively, y is income.
	c)	H c is the vector of consumption goods that require energy inputs, c e is coal consumption, M c denotes the vector of other consumption goods, l is leisure, f q is
		collected firewood, f l is the labor time spent in collecting firewood, v z is a vector of exogenous variables reflecting forest access, a q is the vector of agricultural
		outputs, a l is household labor time spent in agriculture, h z is a vector of household endowments pertaining to farming, M p , c p and a p are the respective prices of
		other goods, available household time.
	d)

b

  are the purchased and homemade cattle feeding quantities. l L denotes the labor time allocated in cattle feeding activities.  is a vector of household endowments pertaining to land and livestock.  and  denote the corresponding proportions. ds q is the straw output produced by the household.

					d F and c F are, respectively, indices for dirty and clean fuel consumptions . d F consists of used quantities of firewood
	) F , straw ( dw	( ds F	)	and coal	) F , while ( dc	c F is made of quantities of liquefied natural gas	( cl F	)	and electricity	) F . Vector V denotes predetermined ( ce
	variables associated with the cooking technology and access constraints.	dw q is the quantity of collected firewood, dw L is the household labor time spent collecting
	firewood. c Q and l Q are crop and livestock production levels, respectively. c L is the household labor time spent in crop production. c A represents the other fixed
	agricultural inputs.
	h p and p p respectively refer to the prices of household produced and market purchased food;	dc p , cl p and ce p are the prices of coal, liquefied natural gas and
	electricity, respectively;	ac p represents the prices of the other fixed inputs in crop production; mp p is the price of purchased feeding; off L	denotes the household
	labor time allocated in off-farm; w is the wage rate and 0 Y denotes the other exogenous incomes.

p M and h M

Table 2 Empirical literature on fuel use in developing countries

 2

	Author	Fuel type	Data source	Econometric	Income	Fuel price	Household	Community
				method			characteristics	characteristics
	Abebaw (2007)	Fuel consumption	Jimma town of	Tobit model	Per capita		Household head's age	Perceived
		(firewood,	Ethiopia, household		monthly		Household size	fuelwood supply
		charcoal)	survey, urban, 2000		household		Household head's	in future
					income		gender	Distance from
					Square of per		Household head's	nearest fuelwood
					capita monthly		education	entry rout to the
					household		Cattle ownership	town
					income		Refrigerator ownership
							Home ownership
	Ahmad and Puppim de	Fuel choice	Indian Human	Multinomial	Household	Firewood price	Household size
	Oliveira (2015)	(traditional, mixed	Development	logit model	income	LPG price	Highest education
		and modern fuels)	Survey, urban, 2004			Kerosene price	Number of meals per
							day
							Piped water supply
							Electricity supply
	Akpalu et al. (2011)	Fuel consumption	Ghana Living	Regression	Household	Kerosene price		Geographic
		(firewood,	Standards Survey,	analysis	expenditure	Firewood price		location
		charcoal,	1998			Charcoal price
		kerosene, LPG)

[START_REF] Kowsari | Three dimensional energy profile: A conceptual framework for assessing household energy use[END_REF],[START_REF] Rahut | Determinants of household energy use in Bhutan[END_REF].

e.g.,[START_REF] Chen | Energy Consumption in Rural China: A household Model for Three Villages in Jiangxi Province[END_REF],[START_REF] Gupta | Preferences for Domestic Fuel: Analysis with Socio-Economic Factors and Rankings in Kolkata, India[END_REF],[START_REF] Lee | Household energy mix in Uganda[END_REF].

[START_REF] Edwards | Startup Costs and the Decision to Switch from Firewood to Gas Fuel[END_REF],[START_REF] Chen | Energy Consumption in Rural China: A household Model for Three Villages in Jiangxi Province[END_REF],[START_REF] Abebaw | Household Determinants of Fuelwood Choice in Urban Ethiopia: A Case Study of Jimma Town[END_REF],[START_REF] Zhang | The determinants of household energy demand in rural Beijing: Can environmentally friendly technologies be effective?[END_REF],[START_REF] Lee | Household energy mix in Uganda[END_REF].

e.g.,[START_REF] An | Modeling the choice to switch from fuelwood to electricity Implications for giant panda habitat conservation[END_REF],[START_REF] Gupta | Preferences for Domestic Fuel: Analysis with Socio-Economic Factors and Rankings in Kolkata, India[END_REF],[START_REF] Akpalu | Demand for cooking fuels in a developing country: To what extent do taste and preferences matter?[END_REF],[START_REF] Zhang | The determinants of household energy demand in rural Beijing: Can environmentally friendly technologies be effective?[END_REF].

[START_REF] Pitt | Equity, Externalities and Energy Subsidies: The Case of Kerosene in Indonesia[END_REF],Mekonnen (1999),[START_REF] Gupta | Preferences for Domestic Fuel: Analysis with Socio-Economic Factors and Rankings in Kolkata, India[END_REF],[START_REF] Akpalu | Demand for cooking fuels in a developing country: To what extent do taste and preferences matter?[END_REF],[START_REF] Démurger | Poverty and Firewood Consumption: A Case Study of Rural Households in Northern China[END_REF],[START_REF] Lee | Household energy mix in Uganda[END_REF] andNlom and Karimov (2014).

Tô is a staple food made of millet, sorghum or maize flower, a traditional meal in Burkina Faso, which tastes better when cooked with firewood.

[START_REF] Démurger | Poverty and Firewood Consumption: A Case Study of Rural Households in Northern China[END_REF],[START_REF] Pandey | Comprehending household cooking energy choice in rural India[END_REF] and[START_REF] Rahut | Determinants of household energy use in Bhutan[END_REF], while not in[START_REF] Chen | Energy Consumption in Rural China: A household Model for Three Villages in Jiangxi Province[END_REF].

[START_REF] Kaul | Rural household energy use in China[END_REF],[START_REF] An | Modeling the choice to switch from fuelwood to electricity Implications for giant panda habitat conservation[END_REF] and[START_REF] Chen | Energy Consumption in Rural China: A household Model for Three Villages in Jiangxi Province[END_REF].

Acknowledgments

The corresponding author acknowledges financial support from the A*MIDEX project (n° ANR-11-IDEX-0001-02) funded by the « Investissements d'Avenir » French Government program, managed by the French National Research Agency (ANR).

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 Survey, 1989Survey, , 1991Survey, , 1993Survey, , 1997Survey, , 2000Survey, , 2004Survey, , 2006-3.09 -0.34 to -0.35 [START_REF] Kaul | Rural household energy use in China[END_REF] -0.79 [START_REF] Lee | Household energy mix in Uganda[END_REF] -0.32 -0.32 [START_REF] Pitt | Equity, Externalities and Energy Subsidies: The Case of Kerosene in Indonesia[END_REF] -1.1 to -1.14 -0.64 to -0.72 -0.93 to -1.1