Does Income Affect Climbing the Energy Ladder? A New Utility-Based Approach for Measuring Energy Poverty.

Date01 July 2023
AuthorNguyen, Luan Thanh
  1. INTRODUCTION

    A broad consensus suggests that energy poverty is the lack of modern energy services because households do not have access to or cannot afford them. However, no single measure of energy poverty provides a reference point. Instead, past energy poverty measures mainly deal with one or several facets of energy-poor. They have provided a comparison across countries or regions and intertemporal differences that may help progress towards minimizing energy poverty. However, some concerns have arisen beyond the scopes of these studies. For example, the widespread use of a diversified residential energy mix consists of carbon-intensive fuels, even in wealthy households in the emerging economies. The underlying reason for having such an energy mix is living habits linked to the abundant availability of polluted energy at lower prices. Thus, practitioners and policymakers may fail to scrutinize the issue, subsidy programs may be wrongly targeted, and policies to relieve energy poverty may be ineffective.

    In this paper, we develop a new method to evaluate energy poverty. This method is based on the disutility that occurs if households use polluted energy, e.g. solid biomass, or have to give up other demands to afford clean energy, e.g. electricity. For instance, a well-off family that can afford cleaner energy keeps consuming solid biomass as a long-term habit. The family absorbs much indoor pollution and derives disutility due to pollution. Another case is that a low-middle-income household pays a significant proportion of their disposable income for clean energy, so they must scarify other demands. We propose an extension of Lewbel and Pendakur's (2009) Exact Affine Stone Index (EASI) demand system to quantify implied disutility associated with consumer choices when using a different mix of energies, some with emissions. In an application, we adopt three waves of the Vietnam Household Living Standards Survey (VHLS) data (2012, 2014 and 2016) with more than 24,000 observations.

    The empirical results demonstrate that the new method is more comprehensive than the previous approaches to identifying energy poverty households in many unsolved circumstances. Our findings suggest that energy poverty can be escalated at different income levels, including middle-income or above levels. Furthermore, we also find that consuming conventional fuels, usually considered dirty energy, does not always mean the household is in energy poverty. Thus, energy policy also needs to be updated to adapt to these new conditions.

    In the literature, common energy poverty measures are mainly based on two pillars, accessibility to modern energy like electricity and affordability measured in terms of energy expenditure. Accessibility measures implicitly assume that households gradually move away from traditional energy inputs like solid biomass as countries progress in the development path, a concept proposed by the International Energy Agency (IEA, 2002). Accordingly, a household is in energy poverty if it lacks access to modern energy services or depends on traditional biomass for activities, such as cooking meals.

    Some examples of studies that have used IEA measures are Sesan (2012), Bhide and Monroy (2011), Mirza and Szirmai (2010), Birol (2007), and Sagar (2005). These researchers identified the reliance on traditional biomass in cooking as a measure of energy poverty. Meanwhile, studies by Singh and Inglesi-Lotz (2021), Legros et al. (2009) and Foster et al. (2000) provided examples that consider the accessibility to electricity as a proxy for energy poverty. Other studies (Pereira et al., 2011; Action, 2010; Pachauri et al., 2004; Foster et al., 2000; Goldemberg et al., 1988) defined energy poverty by estimating the minimum level of energy needed to maintain a certain living standard.

    Within the accessibility perspective, energy poverty could also be evaluated by composite measures, which are combinations of several weighted indicators. Two well-known composite measures are the Energy Development Index (EDI) developed by IEA (2010) and the affordable and clean energy goal (Sustainable Development Goal 7 [SDG7]) developed by the United Nations Desa (2016). Both the EDI and the SDG7 rely on electricity accessibility and macro indicators, such as the average usage level of modern fuels in the residential sector or renewable share in total final energy consumption. Thus, these methods are more suitable for a cross-country comparison than a household-level analysis.

    Providing a composite measure for a specific country, Nussbaumer et al. (2012) proposed the Multidimensional Energy Poverty Index (????), which focuses on a household's privation to modern energy services. This method considers a set of micro-level indicators that includes: (a) the use of non-modern fuels, (b) cooking produces indoor pollution, (c) having access to electricity, and (d) having either a fridge or a radio/television or a landline/mobile phone. A recent study by Delugas and Brau (2021) applied the ???? method to identify a significant link between subjective well-being and energy poverty intensity. In applications of the ????, Munyanyi and Churchill (2022) found that foreign aid helped reduce energy poverty by 3.3% in Senegal. In addition, Abbas et al. (2020) suggested that better socioeconomic status mitigates the energy poverty in South Asia. Meanwhile, studies by Dong et al. (2022), Dong et al. (2021) and Zhao et al. (2021) all employed an energy poverty composite index with four components: energy service availability, energy consumption cleanliness, energy management completeness, and energy affordability and efficiency.

    The second pillar, affordability, was initially introduced to measure fuel poverty by Lewis (1982) and considered the inability to afford warmth for the house. Later on, Boardman (1991) defined fuel poverty as if a household has energy costs higher than 10% of their income to maintain adequate indoor temperature. A study by Phimister et al. (2015) adapted the 10% indicator with the consideration of disposable income, which excludes housing costs instead of total household income. Other studies by Barnes et al. (2011) and Pachauri et al. (2004) adopted a 10% indicator to analyze energy poverty, instead of fuel poverty, for India and Bangladesh. The 10% measurement was officially applied by the U.K. Government in their formal legislation before Hills (2011) proposed a new definition of fuel poverty as low-income high cost (LIHC). According to the LIHC, a household is in fuel poverty if its income is lower than 60% of the national median income level while its energy expenditure is above the median level. More recently, studies by Dogan et al. (2022), Nguyen et al. (2019) and Mayer et al. (2014) adopted LIHC to determine households in energy poverty. Besides, among several studies that applied both the 10% indicator and LIHC, Charlier and Kahouli (2019) and Welsch and Biermann (2017) found that more energy poverty leads to higher energy price elasticity.

    The terms energy poverty and fuel poverty have been used interchangeably in the literature. The studies of Charlier and Kahouli (2019), Romero et al. (2018), Welsch and Biermann (2017), Herrero (2017), Schuessler (2014), and Foster et al. (2000) are some examples among many. It may imply that the boundary between energy poverty and fuel poverty is getting blurred, such as the issue of households in many developing countries is no more about inaccessibility but how to afford the energy bill. Furthermore, while affordability has become a more common concern than accessibility, the expenditure-based approaches could not become dominant in measuring energy poverty because they ignore the mitigating expenditure behavior (Phimister et al., 2015). Some recent studies, including Perez et al. (2021), Charlier and Legendre (2019), Welsch and Biermann (2017), and (Phimister et al., 2015), paid more attention to household behavior by involving subjective measures together with the affordability. However, subjective measures could also not be consistent solutions because they rely on the household's perspective, in which families living in poor condition houses are more likely to address themselves as energy poor.

    To this end, extant energy poverty measures are gradually becoming irrelevant for rapidly developing countries, such as China or Vietnam. On the one hand, the accessibility approach has limited relevance in those countries as the accessibility to modern energies is no longer an obstacle and solid biomass is still a significant part of the energy used for cooking. This situation violates the implicit assumption of the accessibility measure, that people substitute low quality, high pollutant energy sources with modern energy as they escape income poverty. Instead, it could be associated with the energy consumption behaviors and living habits linked to the abundant availability of such fuels at lower prices. Thus, neither traditional methods entirely capture the energy poverty in these countries nor comprehensively accommodate the choice to use solid biomass associated with the customer behavior perspective.

    On the other hand, the affordability methods have also been questioned in the context of rapidly developing countries for various limitations. For example, Li et al. (2014) recommended that these measures could only be used under specific conditions. Those conditions include households located in cold climate regions, households lacking access to modern energy (for cooking), and households having difficulty achieving satisfactory indoor temperatures with reasonable energy costs. Furthermore, the 10% indicator is debated in the literature by Schuessler (2014) and Heindl (2014) as inappropriate for countries other than the United Kingdom because of cross country parity and cost of living differences. The LIHC definition is also disputed by Moore (2012) and Boardman (2012) because...

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