General objectives The research evaluates the impact of education on energy poverty in Vietnam, thereby proposing recommendations in line with the actual situation in Vietnam.. Besides,
The urgency of the research
‘‘Life is but a continuous process of energy conversion and transformation.’’
Energy plays a crucial role in the socio-economic development of humanity, serving as a foundation for economic growth, scientific advancement, industrialization, and modernization It is essential for enhancing human longevity and quality of life, with the effective utilization of diverse energy sources significantly contributing to civilization's progress As the global population exceeds 8 billion and living standards rise, the demand for energy continues to escalate According to the International Energy Outlook 2021, global energy consumption is projected to increase by nearly 50% by 2050, driven largely by population growth and economic expansion, particularly in Asian countries However, as society evolves, the depletion of traditional energy sources poses a challenge that parallels the rapid growth of the world economy.
Vietnam is experiencing a significant increase in energy demand due to its ongoing industrialization and modernization efforts, while energy supplies are becoming increasingly strained Despite having a diverse range of energy sources, including coal, oil, gas, hydropower, and renewable options like solar, biomass, and geothermal, the country still has low energy production and consumption per capita Over the past 35 years, Vietnam's economy has grown rapidly, with an annual GDP growth rate of approximately 6-7%, except for the two years of 2020.
The COVID-19 pandemic has highlighted the critical role of the energy sector, as noted by Nhan Dan Newspaper Energy poverty and long-term supply shortages are increasingly prevalent in developing nations, exacerbated by energy security challenges in Europe, according to Saul Kavonic, an energy analyst at Credit Suisse Bank This issue poses significant obstacles to global economic growth and affects the quality of life, particularly in Vietnam To tackle energy poverty effectively, it is essential to identify the factors contributing to this issue and implement appropriate strategies.
Energy poverty is influenced by various external factors that complicate its resolution Research by Apergis et al (2022), Banerjee et al (2021), and Nguyen et al has identified key elements contributing to the growth of this issue.
Education plays a crucial role in enhancing GDP per capita and reducing carbon dioxide emissions by creating a more efficient workforce As the level of education among workers increases, their ability to perform jobs that require critical thinking and reading improves, making education one of the most effective strategies for alleviating poverty and inequality In Vietnam, the government prioritizes education as a key national policy, investing resources to eliminate hunger, reduce poverty, and promote socio-economic development UNESCO research indicates that if all adolescents completed secondary education, the global poverty rate could be significantly reduced By equipping individuals with essential skills, education not only boosts employment opportunities and income but also mitigates socio-economic risks.
The "Tracking SDG7" report highlights that in 2021, 675 million people globally lacked access to electricity, a significant reduction from 2020, yet nearly 2.3 billion still rely on unclean fuels for cooking and heating, predominantly in sub-Saharan Africa, which also faces high school dropout rates Research shows that individuals with higher education levels are more likely to use clean energy sources, making investment in education crucial for economic development Additionally, studies indicate that academic performance in subjects like math and Chinese can reflect the impact of energy poverty on children's well-being Despite the importance of education in addressing energy poverty, the specific effects of education on energy poverty in Vietnam remain underexplored Therefore, the study titled "The impact of education on energy poverty: Empirical evidence from Vietnam" aims to examine how years of schooling influence energy poverty in the country.
Research objectives
The research evaluates the impact of education on energy poverty in Vietnam, thereby proposing recommendations in line with the actual situation in Vietnam
- Expose the basic theoretical issues of energy poverty and education, and emphasize the impact of education on energy poverty
- Identify and evaluate the energy poverty trend based on household energy costs in Vietnam
- Develop several economic models to analyze and evaluate the impact of education on energy poverty
- Combination of the theory and practical data obtained, the research presents some recommendations and policies to overcome energy poverty in Vietnam and towards sustainable energy development
- Question 1: How are energy poverty and education happening in Vietnam?
- Question 2: How does education affect energy poverty in Vietnam?
- Question 3: Does Vietnam have solutions for energy poverty reduction and sustainable energy development?
Research methodology
Researchers employ quantitative analysis methods to effectively utilize the VHLSS data set, enabling access to a vast array of samples from all regions in Vietnam This approach enhances the accuracy and objectivity of the study Additionally, the collection of panel data facilitates comparisons of energy poverty trends in Vietnam over time and allows for the evaluation of findings from related research both nationally and globally.
The authors collected household data from the VHLSS dataset to analyze the impact of education on energy poverty in Vietnam They compiled fuel spending statistics across three categories—primitive, transition, and advanced—for households engaged in agricultural, forestry, and fishery activities This analysis evaluates trends in energy transition and poverty by year, region, living area, overall poverty, and ethnicity Additionally, indices representing energy poverty, education, and other control variables were calculated Energy poverty measurement models were developed based on educational factors, allowing for the analysis of correlations between variables The findings were compared with existing research, leading to policy recommendations and suggestions for future studies.
Subjects and scope of research
Subject : The research focuses on research on energy poverty and the impact of education on energy poverty
Spatial scope : The research focuses on the evaluation of the real state of the impact of education on energy poverty in Vietnam
New contribution
Limited studies have explored energy poverty in Vietnam, particularly the connection between education and energy poverty The measurement methods, such as the Energy Ladder, energy stacking models, and the Multidimensional Energy Poverty Index (MEPI), are relatively new and underutilized in Vietnamese research The control variables utilized in OLS and logistic regression models, including ethnicity, gender, household head age, household poverty status, and household size, are common yet carry significant practical implications Moreover, previous research has lacked in-depth analysis of findings, which is crucial for developing effective policy recommendations Our article aims to address these research gaps by providing comprehensive insights into energy poverty in Vietnam.
- Provide a theoretical basis for energy poverty, energy transaction, education, and other dependent variables and the situation of these factors in Vietnam
- Provide a theoretical basis for the impact of independent variables (education, household head ethnicity, income, living area, ) on dependent variables (energy poverty)
- Test these relationships based on the Vietnam Household Living Standard Survey (VHLSS), one OLS regression model, and three logistic regressions
- Provide appropriate policy implications from the results of the research paper and serve as a premise for the following research papers
This study aims to enhance understanding of energy poverty and education in Vietnam, exploring their interconnections and current status It offers valuable theoretical insights and meaningful policy recommendations By engaging with this research, readers will gain a deeper comprehension of energy poverty and recognize the critical role of energy and education, ultimately fostering more informed and positive behaviors, such as adopting modern energy solutions.
‘‘green’’ energy sources or accessing more research articles and courses related to energy.
Research structure
The research is arranged in six chapters, with the following particular content: Chapter 1: Overview of the Impact of Education on Energy Poverty
Chapter 3: The Current Situation of Education and Energy Poverty
Chapter 6: Conclusion and Policy Implications
OVERVIEW OF THE IMPACT OF EDUCATION ON ENERGY
Overview of energy poverty
Energy poverty has become a widespread problem, wreaking devastation on many households throughout the world because of the worldwide economic downturn
(Apergis et al., 2022) Energy poverty can be described in a variety of ways Defined by
Energy poverty refers to the inadequate access to essential energy resources required for basic needs, as defined by Greer and Thorbecke (1986) Bouzarovski et al (2012) expand on this concept, characterizing energy poverty as a condition where households are unable to obtain the socially and physically necessary levels of home energy services This highlights the critical issue of energy access and its impact on households.
In their 2016 study, Okushima categorized approaches to energy poverty into two main groups: "availability" and "affordability." The "availability" aspect highlights the lack of access to modern energy sources, such as electricity, often seen in developing countries Conversely, "affordability" addresses the challenges that prevent individuals from meeting their essential energy needs.
Energy poverty, as defined by Reddy et al (2000), is the absence of sufficient options for accessing energy services that are adequate, affordable, reliable, high-quality, safe, and environmentally sustainable, which are essential for fostering economic development and improving people's lives.
Energy poverty is defined as the inability to access, select, and utilize energy to meet essential human needs and support development Our team offers a more comprehensive understanding of this concept, building on previous definitions.
1.1.2 General problems of energy poverty
Energy poverty primarily stems from the gap between average household income and energy prices, compounded by inefficient energy consumption in buildings, including poor insulation and outdated heating systems Research by Healy and Clinch (2004) and Liddell et al (2012) in the UK and Ireland highlights that low household income, coupled with energy-inefficient homes, has led to unprecedented levels of energy poverty, even in relatively mild climates.
Energy poverty is influenced by various factors, particularly the sociopolitical system, which affects energy markets, institutional frameworks, and infrastructure Herrero and Bouzarovski (2014) highlight that Eastern European nations have become increasingly energy-poor due to insufficient investment in energy efficiency and social welfare since the fall of communism Additionally, the sociopolitical environment shapes market, economic, and social policies, where a highly liberalized and competitive energy market can significantly impact energy pricing and the effectiveness of interventions aimed at enhancing energy affordability.
Income significantly impacts energy poverty, affecting both the amount households spend on energy and their willingness to invest in it for their living and development needs Additionally, income levels influence the size of homes, the quality of infrastructure, and the efficiency of heating and cooling systems.
Climate significantly impacts energy poverty by influencing energy needs for heating and cooling It also affects the investment in building structures and the types of heating and cooling systems used, highlighting the relationship between climate and energy requirements.
Education plays a crucial role in alleviating energy poverty by significantly influencing the economic and social status of family members Individuals with higher qualifications tend to enjoy more stable and higher incomes, which decreases their chances of facing energy access issues or payment difficulties Additionally, education enhances knowledge, raises awareness, and develops effective budgeting skills, all contributing to an improved quality of life.
1.1.3 Indicators for measuring energy poverty
In general, there are several approaches to quantifying energy poverty depending on the various hypotheses that prior research has used to learn about this issue
The expenditure-based method is a widely used approach to assess energy deprivation by comparing household energy expenses to specific thresholds, as highlighted by Khandker et al (2012) In contrast, the consensus method relies on individuals' self-assessments of their living conditions and ability to meet basic needs The direct measuring approach evaluates whether the energy services in a home meet established standards but is less common in poorer nations due to the need for detailed information on energy services and environmental conditions Bouzarovski et al (2012) identify two key factors contributing to energy poverty: "availability," which addresses the lack of access to modern energy forms like electricity, and "affordability," which encompasses the challenges that hinder individuals from fulfilling their basic energy requirements.
In 1987, Hosier and Dowd introduced the Energy Ladder and energy stacking models, illustrating how low-income households initially rely on traditional, less clean energy sources like firewood and cattle manure, represented as the lower rungs of the energy ladder As these households experience an increase in income, they transition to cleaner, more modern energy sources such as coal, kerosene, liquefied petroleum gas (LPG), and eventually electricity and biofuels, which correspond to the higher rungs of the ladder Consequently, households utilizing these modern fuels, positioned higher on the energy ladder, exhibit reduced levels of energy poverty.
Figure 1: Energy ladder and energy stacking models
Research on energy poverty frequently utilizes specific indicators for measurement, as highlighted in studies by Hosier and Dowd (1987) and Han et al (2018) These established methodologies serve as a foundation for various investigations into the topic of energy poverty.
Table 1: Popular energy poverty measurement indicators Research title Authors, year Index Indicator calculation
The Energy Development Index (EDI)
Gather information and compute the following factors:
(ii) The proportion of commercial energy to overall final energy consumption; and (iii) The amount of commercial energy consumed per person
Compute an equally weighted average of the aforementioned three elements
Energy ladder model Energy stacking model
Energy poverty in Ghana: Any progress so far?
The Multidimensional Energy Poverty Index (MEPI)
Determined by multiplying the headcount ratio - the proportion of people who are categorized as being energy poor - by the average severity of energy poverty
The Energy Poverty Index (EPI)
Integrates various physical shortage aspects, which are cross-referenced with monetary shortage measures
The Compound Energy Poverty Index (CEPI)
The factors used by Herrero and Bouzarovski (2014) to generate the CEPI are supplemented with two additional self-assessed variables that are directly related to energy poverty
Source: Compiled by the authors
The Multidimensional Energy Poverty Index (MEPI) is a widely recognized measure of energy poverty, evaluating it through five key factors These factors assess households' access to and utilization of modern fuels, along with the ownership of essential electrical appliances that fulfill daily needs.
Table 2: MEPI’s deprivation dimensions, indicators, and cut-offs
Dimension Indicator (weight) Variables Deprivation cut- offs (energy poor if
Any fuel use besides electricity, LPG, kerosene, natural gas, or biogas
Food cooked on stove or open fire (no hood/ chimney), indoor, if using any fuel beside electricity, LPG, natural gas, or biogas
Services provided by means of household appliances
A household's electricity usage for cooking and lighting is a strong indicator that it is less likely to experience energy poverty Additionally, the ownership of appliances for entertainment, education, and communication further reflects this positive trend.
Our research aims to effectively apply existing theories to the unique context of Vietnam By utilizing data from the Vietnam Household Living Standards Survey (VHLSS) and the General Statistics Office (GSO) of Vietnam, we measure energy poverty in the country through two distinct methods.
Overview of education
Education is essential for the growth and development of humanity The term "education" originates from the Latin word "Educationem," meaning "a rearing" or "training," and has roots in Middle French As emphasized by Adesemowo, education plays a crucial role in shaping individuals and society as a whole.
Education is a lifelong process that fosters a positive mindset, distinct from merely attending school According to Osborne (2022), school serves as a venue for accessing educational resources, while education encompasses the active engagement with these tools to gain a deeper understanding of society Adesemowo and Sotonade (2022) echo this sentiment, emphasizing that education involves the comprehensive process of human learning, knowledge transfer, skill development, and that schooling is just one method of facilitating this broader educational experience.
Education is an ongoing process of acquiring intellectual qualities, abilities, and attitudes that shape individuals' perspectives and actions in life (Bamisaiye, as cited in Adesemowo & Sotonade, 2022) According to the Dictionary of Education (C.V Good, 1973), it encompasses all processes through which individuals develop skills and dispositions that reflect the values of their community Education is fundamentally an interpersonal process where people are influenced by a structured environment, particularly in schools, aimed at fostering social competence and personal development.
Consequently, our team has developed a broader and clearer definition of
Education encompasses the teaching and learning processes, involving the sharing of information and experiences among individuals Its meaning can vary based on context, user, and location Generally, education utilizes language and symbolic systems to enhance human reasoning and judgment, while also playing a crucial role in preserving and advancing humanity's existence and evolution.
Education is the cornerstone of society, driving social prosperity, political stability, and economic growth It significantly influences individuals' economic and social standing, as higher education enhances their ability to improve their quality of life According to the University of the People, societies with higher educational attainment are more equitable, healthier, and economically stable, with lower crime rates Furthermore, education empowers individuals to combat discrimination and violence, equipping them with the knowledge and skills to understand their rights and responsibilities within their families and communities (Prasad & Gupta, 2020).
Education is essential for personal development, significantly impacting individuals' social and spiritual well-being (Dash, 2015) It empowers people to realize their true potential, expand their interests, and fosters the confidence to express and defend their opinions Ultimately, education plays a crucial role in earning respect and recognition within society.
Poverty is fundamentally linked to limited access to education, making education a vital tool for breaking the cycle of poverty (Hickman, 2015) Those with education gain improved employment opportunities, allowing them to contribute positively to society and the economy (Prasad & Gupta, 2020) When individuals are recognized for their contributions, they can better support themselves and their families Conversely, a lack of education stifles creativity and innovation, hindering societal progress As educational levels rise, so does societal advancement and civilization Areas with inadequate education cannot achieve the same prosperity as those with high educational standards (Jhaeyzson, n.d.).
Research on the relationship between education and energy poverty has highlighted various measurement approaches Apergis et al (2022) assess education through total household education expenditure, while Acharya and Sadath (2019) focus on the ratio of individuals completing 12th grade relative to the overall Indian population Other studies suggest evaluating household education based on the educational attainment of the household head Tewathia (2014) employs three indicators: high school completion, university degree attainment, and postgraduate education of the household head Sharma et al (2019) add two variables: the number of years the household head attended school and their awareness of energy-saving practices Additionally, Koomson and Danquah (2021) emphasize the educational status of the household head as a key variable.
In Vietnam, educational variables are used to assess the educational status of household heads, as introduced by Son and Yoon (2020) and Nguyen et al (2019) These variables include the completion of basic education, general education, and university attendance by the household head Additionally, Feeny et al (2021) provide an alternative measure by evaluating the total years of schooling among household members.
Utilizing insights from prior research and data from the Vietnam Household Living Standard Survey (VHLSS), we selected two key variables to assess household educational levels: the highest grade completed and the highest degree attained by the head of the household.
Factors affecting energy poverty
The study's models incorporate not only independent educational variables but also various control variables to enhance the accuracy and objectivity of the findings These control variables are categorized into two groups: one focuses on the characteristics of the household head, while the other pertains to the household's status.
Research by Burney and Khan (1992), Hua and Erreygers (2019), and Rahman (2013) highlights that the characteristics of the household head significantly impact savings habits, overall poverty levels, and educational outcomes within the household This underscores the crucial role of the household head in shaping various aspects of family dynamics Previous studies have examined factors associated with the head of household, yielding insightful results, as illustrated in the table below.
Table 3: The correlation between the characteristics of the household head and energy poverty in previous researches
Assessing the determinants and drivers of multidimensional energy poverty in
The MEPI multidimensional energy poverty index is positively impacted by household heads who are male and over 60
Energy poverty in rural Bangladesh
Gender of household head; Age of household head
Female household heads and younger household heads tend to consume less energy in general
Energy transition, poverty and inequality in
Ethnicity of household head; Age of household head
Minority and younger householders have lower electricity expenditures as a percentage of total energy expenditures
Temperature shocks and energy poverty:
Gender of household head; Age of household head
Male household heads and older household heads tend to have a negative impact on the MEPI
Source: Compiled by the authors
Research utilizing the VHLSS dataset identifies three key variables that characterize household heads: the gender, ethnicity, and age of the head of the household.
Factors related to family status have also been shown by many studies to have impacts on household energy poverty, typically through some of the following researches:
Table 4: The correlation between the household status and energy poverty in previous researches
Assessing the determinants and drivers of multidimensional energy poverty in
Households in the Rural region and in the Upper East (Ghana) tend to have higher MEPI calculation results
Energy poverty in rural Bangladesh
Proportion of village land irrigated; Male/
In villages with electricity and limited irrigated land, female household members tend to earn lower salaries, while male members experience higher earnings This disparity in income contributes to increased electricity costs for households.
Energy transition, poverty and inequality in
Households with a greater value of durable assets, fewer members, and those that are self-employed, do not engage in deforestation, and reside in urban areas typically exhibit a higher ratio of electricity expenditure relative to their total energy spending.
Temperature shocks and energy poverty: Findings from Vietnam
Household size and average rainfall in the district have a negative impact on the MEPI
Source: Compiled by the authors
Based on prior research and the VHLSS data set, four key variables were identified concerning household status: household income, poverty status, agricultural self-production and business activities, and the living area along with household size.
OVERVIEW OF RESEARCHES
Overview of researches on energy poverty
In today's society, energy is crucial for economic growth, scientific progress, and modernization, as it enhances longevity and improves the quality of life However, energy poverty remains a significant issue, characterized by insufficient fuel for essential daily activities like heating and cooking, or by prohibitively high fuel prices that many cannot afford.
Energy poverty, as defined by Barnes et al (2011), refers to the ratio of energy demand to family income, highlighting that families with higher incomes can still experience energy poverty due to a lack of modern energy services This complex issue has persisted globally, with Sovacool et al (2012) and organizations like the International Energy Agency (2010) confirming its prevalence In 2009, approximately 1.4 billion people lacked access to electricity, while over 1 billion relied on unstable electricity grids Additionally, 2.7 billion individuals depended on traditional fuels such as wood, coal, and dung for their energy needs, with Asia accounting for 55% of those without electricity and 72.3% of those using traditional fuels.
The Multidimensional Energy Poverty Index (MEPI) is a widely utilized tool for measuring energy poverty, as highlighted in studies by Nussbaumer et al (2012), Crentsil et al (2019), and Koomson and Danquah (2021) According to Jr et al (2019), MEPI defines energy poverty as the lack of access to energy, offering a comprehensive overview of household energy shortages within a single metric However, it does not account for energy used for productive purposes or outside the home Koomson and Danquah (2021) identified five key aspects of MEPI: cooking, lighting, household appliances, entertainment/education, and communication.
Energy poverty is particularly acute in developing countries, where it is closely associated with economic poverty (Nguyen et al., 2019) However, a decrease in overall spending poverty does not necessarily lead to improvements in energy poverty levels.
Energy poverty, while not always linked to income poverty, can be observed in certain contexts, such as Vietnam, which is experiencing rapid economic growth and increasing foreign direct investment (Barnes et al., 2011; Le & Tran, 2018) This economic expansion has led to a widening gap in living standards between urban and rural areas (Nguyen et al., 2019) Key indicators for assessing energy poverty include the percentage of the population with access to electricity, differentiated by urban and rural areas, as well as average energy consumption metrics, including electricity, coal, and biomass per capita (Apergis et al., 2022; Nguyen et al., 2019).
Overview of researches on education
Research consistently shows a strong link between economic development and education, with studies indicating that nations with a higher percentage of educated workers experience greater economic efficiency This improvement is largely due to the enhanced skills of educated individuals, particularly in reading and critical thinking, which enable them to perform tasks more effectively.
Investment in education is a crucial driver of economic growth, as it enhances human capital (Apergis et al., 2022) Researchers Psacharopoulos, Patrinos, and Gillette emphasize that education is foundational for sustainable progress, effectively addressing poverty and inequality (Apergis et al., 2022) Koomson and Danquah (2021) highlight that education benefits low-income households by promoting economic growth, increasing income, and improving efficiency Overall, education significantly contributes to human development and yields long-term positive effects on the economy.
Research indicates that individuals with higher education levels tend to experience greater happiness, improved health, and longer lifespans compared to those with lower education This trend is further supported by the notion that a healthier society creates a conducive environment for acquiring advanced educational qualifications and professional training (Zajacova & Lawrence as cited in Banerjee et al., 2021).
Until now, the Party and the State of Vietnam have continuously regarded
Vietnam prioritizes education as a key national policy, allocating significant funds to enhance educational advancement aimed at eradicating hunger and poverty while fostering socio-economic development Since the start of its reforms in 1986, Vietnamese education has consistently evolved, with national strategies focusing on human resource growth and learning This has led to improvements in both the quality and accessibility of education, particularly for children in challenging socioeconomic conditions and ethnic minority areas Currently, Vietnam's education system is progressively aligning with global development trends.
Overview of researches on the impact of education on energy poverty
The interplay between education and economic growth significantly influences households' access to essential resources, such as energy supplies, highlighting that energy poverty is closely linked to socioeconomic status (Apergis et al., 2022; Acharya & Sadath, 2019) A nation’s electrification rate serves as a strong indicator of its economic development, with uneducated populations facing heightened energy poverty (Acharya & Sadath, 2019; Donev et al as cited in Apergis et al., 2022) Consequently, achieving robust economic growth is often obstructed by inefficient energy consumption, shortages of clean fuel, and restricted energy access (Banerjee et al., 2021).
Education can play a crucial role in indirectly alleviating energy poverty A study by Amin et al (2020) in South Asia highlighted that while energy poverty negatively impacts economic growth, education contributes positively to it.
Research by Banerjee et al (2021) suggests a correlation between lower energy poverty rates and higher educational achievement Evidence shows that children with access to electricity, particularly girls, dedicate more time to studying compared to those without it (Khandker et al., 2012) Similarly, Acharya and Sadath (2019) emphasized the crucial role of education in combating energy poverty, based on data from India.
Research indicates that the education level of a household head significantly influences household awareness regarding electricity use Tewathia (2014) highlighted this connection, while Sharma et al (2019) emphasized that higher education correlates with increased awareness among household members Both studies, along with findings from Acharya and Sadath (2019), demonstrate that greater education levels are associated with reduced household electricity consumption, particularly among low- and very low-income Indian households This increased education fosters a better understanding of efficient energy use, ultimately aiding families in saving on electricity costs Consequently, investing in education is linked to effective energy-saving measures and alleviating energy scarcity.
Agreeing with that perspective, Acharya and Sadath (2019) and Crentsil et al
Raising education levels may reduce energy poverty, but the impact is not always significant Higher education in a household does not guarantee lower energy consumption, as even well-educated families, especially in upper and middle-income brackets, can be negligent about energy conservation Their greater financial resources may lead to a reduced concern for energy costs (Sharma et al., 2019).
The integration of innovative energy sources through education significantly boosts knowledge and decision-making abilities, leading to improved living standards and household welfare (Crentsil et al., 2019) Individuals equipped with this knowledge recognize the benefits of transitioning to modern commercial energy sources, such as electricity, natural gas, and renewable energy, which play a crucial role in alleviating energy poverty, as opposed to relying on traditional fuels like kerosene, animal manure, and biomass (Apergis et al., 2022).
Research indicates that the educational attainment of the household head serves as a key indicator of energy-related decision-making and its impact on energy poverty Higher education levels enhance understanding and capacity for utilizing modern energy sources, improving household quality of life through better cooking and lighting options As the educational achievement of the household head increases, the likelihood of experiencing multidimensional energy poverty decreases Short-term education can drive behavioral changes that facilitate the transition to clean energy use and energy efficiency, particularly by raising awareness of the health, environmental, and economic costs associated with reliance on biomass Additionally, when householders are informed about the opportunity costs linked to solid fuel use, they are more inclined to opt for modern or transitional fuel sources Ultimately, higher educational levels among household heads correlate with improved awareness, increased income, and the ability to effectively choose and utilize modern energy sources.
Research indicates that households led by individuals with higher education levels tend to have lower Multidimensional Energy Poverty Index (MEPI) scores A lower MEPI reflects greater access to modern energy sources for lighting and cooking, as well as a higher likelihood of owning essential household appliances (Rahut et al., 2019; Crentsil et al., 2019; Acharya, 2018).
Previous studies have explored the relationship between education and energy poverty by proposing various measurement methods For instance, Barnes et al (2011) and Banerjee et al (2021) assessed educational variables using the highest educational attainment of household members, the primary/secondary school ratio, and average years of schooling Additionally, Khandker et al (2012) expanded this approach by incorporating household spending on education, child enrollment and attendance rates, and per capita household income alongside traditional educational metrics.
Research gaps
Research indicates that while energy poverty is a well-established concept frequently discussed in academic literature, particularly in developing nations, its relationship with education remains a significant area of study.
Energy poverty is a relatively recent issue in scientific research in Vietnam, with previous studies lacking consensus on the independent factors influencing it Differences in research samples and methods may contribute to these inconsistencies Moreover, the critical relationship between energy poverty and education, essential for a country's sustainable development, has not been thoroughly explored Additionally, the Multidimensional Energy Poverty Index (MEPI), a widely recognized indicator in global energy poverty research, has been insufficiently addressed in the context of Vietnam.
The authors utilized the Energy Ladder and Energy Stacking models, originally proposed by Hosier and Dowd in 1987, to assess the current energy poverty situation in Vietnam They calculated the household spending ratios for self-production and business activities in agriculture, forestry, and fishery across three fuel categories: primitive, transitional, and modern Additionally, the authors developed models to analyze factors influencing energy poverty, with a particular emphasis on educational aspects, using the multidimensional energy poverty index (MEPI) as a framework The study concludes by discussing the relationships between independent variables, control variables, and dependent variables in the context of Vietnam's current circumstances and the research timeframe.
THE CURRENT SITUATION OF EDUCATION AND ENERGY
The current situation of energy poverty
3.1.1 The current situation of energy poverty in the world
According to the Laborer newspaper (2022), the conflict between Russia and
In 2022, the global energy crisis, particularly affecting European countries, was exacerbated by Western sanctions against Russia following the Ukraine conflict This situation arose amid a recovering global economy struggling with inadequate energy supply to meet rising demand post-COVID-19 As a leading energy producer, Russia responded to severe sanctions from the U.S and its allies by halting gas supplies and demanding a new payment system from European buyers Consequently, energy prices have experienced significant fluctuations due to the constrained supply.
According to the Ministry of Industry and Trade’s Institute for Industry and Trade
In 2023, Strategy and Policy Research reported that natural gas prices have surged to their highest levels in years, while oil prices approached 140 USD per barrel, nearing an all-time high This surge has contributed to a post-pandemic inflationary spiral and a cost-of-living crisis in various countries As major economies strive to find alternative energy sources to replace Russian supplies, there has been a significant increase in the deployment of solar and wind power, alongside a rise in coal imports, which has delayed progress on climate change goals.
In 2022, the global energy crisis led to significant supply shortages and a sharp increase in oil, gas, and electricity prices across many regions In response, European governments have invested over 681 billion Euros since September 2021 to mitigate the impacts of this crisis, alongside an additional 103 billion Euros from the United States.
Norway's energy market is facing turmoil as sanctions and Russian responses heighten concerns about energy supply, leading to a chaotic reallocation of gas exports This situation is driving energy prices to rise, with implications for the broader market.
The ongoing conflict between Russia and Ukraine, coupled with escalating tensions in the Middle East, is driving oil prices higher and raising concerns about a potential global crisis Iran, a major oil producer, is currently engaged in direct conflict with Israel As reported by Tuoi Tre newspaper (2024), these political tensions resulted in a 1% increase in oil prices during the last trading session on April 12, 2024, due to fears of possible supply disruptions.
While Europe faces energy shortages, the Asia-Pacific region enjoys a stable electricity supply largely due to its reliance on coal However, the shift of natural gas (LNG) resources to Europe has led to limited access and increased prices for many Asian power plants, creating challenges in energy availability.
3.1.2 The current situation of energy poverty in Vietnam
Vietnam's energy challenges are expected to lead to a rise in imported energy prices, aligning with global market trends Currently, the country relies heavily on energy imports, including significant volumes of oil, coal, and soon, liquefied natural gas.
Gasoline prices in Vietnam have undergone multiple adjustments from 2022 to the present, significantly impacting transportation and increasing manufacturing costs for essential consumer goods This rise in fuel prices directly affects production and business operations, as petroleum serves as a critical input for various industries Consequently, food prices have surged by 5-10% due to higher import and shipping expenses, further complicating daily life for consumers.
By the end of 2022, Vietnam is facing fuel scarcity alongside rising prices, as reported by Lao Dong newspaper Many gas stations in the southern regions are struggling to meet daily fuel demands, and this issue has now spread to several districts in Hanoi City, where supply is expected to remain inconsistent As a result, people are experiencing long wait times to purchase gasoline for their daily needs, although some may not have to endure lengthy lines.
Vietnam is currently grappling with electricity shortages exacerbated by the global energy crisis, a persistent issue for its energy sector (Vietnam Energy Magazine, 2023) The country faces low power supply due to severe water shortages in hydroelectric reservoirs and reduced capacity at coal-fired power plants affected by prolonged hot weather In response to insufficient power generation, the government has proposed various strategies, including resource mobilization, promoting energy conservation, and reducing electricity consumption While Vietnam has potential renewable energy sources like wind and solar, these have yet to be effectively integrated into the national power infrastructure (People’s Army Newspaper, 2023).
The current situation of education
3.2.1 The current situation of education in the world
The United Nations' Sustainable Development Goals 4 (SDG4) emphasize the importance of providing equitable, high-quality education and fostering lifelong learning opportunities for all, a priority established in 2015 Ritchie et al (2023) assert that governments are responsible for ensuring access to education, recognizing it as a fundamental right for every individual However, significant disparities persist, with adult illiteracy rates in Sub-Saharan Africa reaching one-third of the population, particularly affecting marginalized groups such as individuals with disabilities, the poor, rural communities, and refugees, compared to just 2% in Europe and Central Asia, according to UNICEF's 2014 report.
According to UNICEF (2021), prior to the COVID-19 pandemic, 258 million children and adolescents were completely deprived of education, primarily due to poverty In less developed nations, young women from impoverished rural areas face significant barriers, with few finishing high school, despite the UN's goal of achieving universal secondary education by 2030 Sub-Saharan Africa was the hardest hit, with over 32 million primary school-aged children lacking access to education, while Central and East Asia and the Pacific saw more than 27 million children out of school Additionally, literacy poverty, defined as the inability to read and understand simple text, affected about 90% of youth in low-income countries, compared to just 9% in industrialized nations.
‘‘COVID-19 has fuelled a global ‘learning poverty’ crisis’’, stated Azevedo
The COVID-19 pandemic disrupted the educational system, forcing 1.6 billion children and teenagers to miss school, according to the World Bank's lead economist (2020) UNICEF (2022) revealed that 70% of children aged 10 and older in low- and middle-income countries were unable to read and comprehend a simple paragraph due to school closures, a significant increase from 53% before the pandemic Mr Azevedo noted that if the 15-year trend from 2005 continued, it would take 50 years to halve the rate of learning poverty, but the pandemic is expected to exacerbate the situation and widen the gap in access to education.
3.2.2 The current situation of education in Vietnam
Eradicating illiteracy and achieving universal education are essential for unlocking knowledge, sustainable development, and prosperity Our Party and State prioritize these goals to enhance citizens' knowledge and facilitate successful industrialization and modernization The 2013 Constitution underscores this commitment, stating that "Citizens have the right and obligation to study" (Article 39) and that "Developing education is a top national policy" (Article 61).
By the end of 2000, literacy rates among individuals aged 15 to 35 in our nation reached 94%, as reported by the Ministry of Education and Training Significant progress has been made since then, with current literacy rates soaring to 98.55% for the same age group as of October 2023.
Despite meeting literacy standards for levels 1 and 2 among individuals aged 15 and over, efforts to mobilize students and combat illiteracy in ethnic minority communities remain insufficient Even with support for school supplies, literature, and infrastructure, the participation rate in literacy initiatives continues to be low.
Figure 2: Percentage of literate population at 15 years old and above in the whole country from 2010-2022
Vietnam had an extremely high primary school completion rate (up to 98%), with rates in all regions ranging from 95% or more, according to the ‘‘Vietnam Education
According to UNICEF's 2022 Summary Report, Vietnam is making progress towards achieving universal primary education However, the completion rates for higher education levels reveal concerns, with middle school completion at 87% and high school significantly lower at 59% Although urban and rural areas share similar general characteristics, their socioeconomic conditions vary greatly Notably, the disparity in school completion rates between the wealthiest and poorest children increases as the level of education rises within the system.
92% of students in the wealthiest group finished high school, just 31% of youngsters in the poorest group reached this milestone
Girls consistently outperformed boys in educational completion across all school levels The Red River Delta region achieved an impressive 99% secondary school completion rate, while the Central Highlands lagged behind at 68% In stark contrast, the Northern Midlands and Mountains region reported a significantly lower high school completion rate of just 41% Additionally, the Kinh ethnic group led with a 64% high school graduation rate, compared to only 15% for the Khmer ethnic group.
At all three levels, children who drop out of school are primarily found in rural areas Tran and Yang (2022) asserted that there was still inequality within and across
In Vietnam, significant disparities in educational achievement exist among various geographic regions and ethnic groups, particularly affecting ethnic minorities Households from the Kinh ethnic group, the country's majority, invest seven times more in private tuition for their children compared to those from ethnic minority areas These funding inequalities in education contribute to differing levels of educational attainment, ultimately impacting job prospects and potentially worsening overall inequality.
Notwithstanding these successes, the nation continues to face certain difficulties
Lower secondary education continues to struggle with challenges related to access and quality, especially in remote areas where educational resources are limited Female students and those from ethnic minorities encounter additional barriers that hinder their ability to access and complete their education Therefore, it is essential for the State to implement strategies and regulations that guarantee equitable access to education for all students, regardless of their background or abilities.
QUANTITATIVE RESEARCH METHODOLOGY
Research process
The authors’ research process is carried out as follows:
The authors conducted a comprehensive review of global studies, including those from Vietnam, to explore shared issues and objectives This research informed their understanding of relevant concepts, theories, and current conditions Based on their findings, they opted for quantitative research methods and developed suitable models to assess the impact of education on energy poverty.
- Second, the authors research and select variables representing energy poverty, independent variables representing education, and other control variables that impact energy poverty
After identifying suitable variables, the authors gather and process data for each one, analyzing the effects of independent variables, such as education and other control factors, on the dependent variable of energy poverty using the chosen models.
- Fourth, clarify the current status of the impact of education and other independent variables on energy poverty in Vietnam, thereby providing appropriate policy recommendations and future research directions.
Model for measuring the impact of education on energy poverty
The researchers propose four models to test the impact of education and other control variables on energy poverty, including one OLS regression model and three logistic regression models:
Model 1: OLS regression model measures electricity consumption of a household in Vietnam in 2010, 2012, 2014, 2016, 2018
ECi: Electricity consumption of the household i
EDU1i: The highest grade completed by the head of the household i
EDU2i: The highest degree the head of the household i
HHHEthnici: Ethnicity of the head of household i
HHHAgei: Age of the head of household i
HHHGi: Gender of the head of household i
HHIncomei: Total income of the household i
Poori: Poverty status of the households i
SPBi: Status of self-production and business in agricultural, forestry, and fishery activities of the households i
Areai: Living area of the household i
HSi: Size of the household i
Lightingi: Lighting energy of the household i
Servicei: Household appliance (fridge) ownership status of the household i
EEi: Entertainment/Education appliance (TV/radio) ownership status of the household i
Model 2: Logistic regression model measures the probability of a household to use electricity as lighting energy in Vietnam in the years 2010, 2012, 2014, 2016, 2018
P1 (Lighting=1): The probability of variable Lighting is equal to 1, means the household uses electricity as lighting energy
1−𝑝1) : Logarithm of the ratio Lighting equal to 1 divided by Lighting equal to 0
EDU1i: The highest grade completed by the HHHi
EDU2i: The highest degree the HHHi
HHHEthnici: Ethnicity of the HHHi
HHHGi: Gender of the HHHi
HHIncomei: Total income of the HHi
Poori: Poverty status of the HHi
SPBi: Status of self-production and business in agricultural, forestry, and fishery activities of the HHi
Areai: Living area of the HHi
HSi: Size of the HHi
Model 3: Logistic regression model measures the probability to own a household appliance (fridge) in Vietnam in 2010, 2012, 2014, 2016, 2018
P2 (Service=1): The probability of variable Service is equal to 1, means the household owns the household appliance (fridge)
1−𝑝2) : Logarithm of the ratio Service equal to 1 divided by Service equal to 0
EDU1i: The highest grade completed by the HHHi
EDU2i: The highest degree the HHHi
HHHEthnici: Ethnicity of the HHHi
HHHAgei: Age of the HHHi
HHHGi: Gender of the HHHi
HHIncomei: Total income of the HHi
Poori: Poverty status of the HHi
SPBi: Status of self-production and business in agricultural, forestry, and fishery activities of the HHi
Areai: Living area of the HHi
HSi: Size of the HHi
Model 4: Logistic regression model measures the probability of a household to own entertainment/education appliances (TV/radio) in Vietnam in 2010, 2012, 2014, 2016,
P3 (EE=1): The probability of variable EE is equal to 1, means the household owns entertainment/education appliance (TV/radio)
1−𝑝3) : Logarithm of the ratio Lighting equal to 1 divided by Lighting equal to 0
EDU1i: The highest grade completed by the HHHi
EDU2i: The highest degree the HHHi
HHHEthnici: Ethnicity of the HHHi
HHHAgei: Age of the HHHi
HHHGi: Gender of the HHHi
HHIncomei: Total income of the HHi
Poori: Poverty status of the HHi
SPBi: Status of self-production and business in agricultural, forestry, and fishery activities of the HHi
Areai: Living area of the the HHi
HSi: Size of the HHi
Research data
This study primarily utilizes the Vietnam Household Living Standard Survey (VHLSS) dataset, which is a national statistical resource compiled by the General Statistics Office of Vietnam in partnership with the World Bank and the United Nations Development Program This comprehensive survey is conducted biennially in even-numbered years, providing valuable insights into the living standards of households across Vietnam.
In 2002, a study was conducted to gather data on various aspects of Vietnamese households, including education, economy, society, spending, income, and energy use The research utilized exchange rate data from the International Monetary Fund (IMF) to convert Vietnamese Dong (VND) into US dollars, enhancing accessibility for readers The authors aim for the article to help a broader audience better understand the current situation in Vietnam.
The study used an observation sample of households that participated in the survey in the years 2010, 2012, 2014, 2016, and 2018 Over time, the quantity of observations has been quite consistent (about 9,000 each)
Due to the extensive number of observation samples and variables collected over several years, missing data is an inherent challenge in the study The authors addressed this by thoroughly cleaning the data, identifying and correcting any issues, and performing calculations using Excel and Stata software Ultimately, they utilized Stata to obtain the research results.
RESULTS AND DISCUSSION
Background information
Table 5: Background information on Vietnam’s regions
Source: Authors’ computation the data of the General Statistics Office
In 2018, Vietnam's regions exhibited significant variations in area, population, and density, as detailed in Table 5 from the General Statistics Office of Vietnam The country spans over 331 million square kilometers and is divided into six regions: Red River, Northern, Central Coast, Central Highlands, Southeast, and Mekong River Delta The Central Coast and Northern regions are the largest, covering approximately 95 million square kilometers, while the Red River and Southeast regions are the smallest at 21 and 23 million square kilometers, respectively Notably, despite their smaller size, the Red River and Southeast regions boast the highest population densities, with 1,048 and 744 people per square kilometer, respectively In contrast, the Mekong River Delta, Central Coast, and Northern regions show lower population densities, with the Central Highlands recording the lowest density figures Additionally, the poverty rate in Vietnam as of 2016 is also highlighted in the statistics.
The Red River and Southeast regions of Vietnam exhibit the highest urban population densities, with 34.9% and 62.9% of their populations living in cities, respectively In contrast, two-thirds of the population resides in rural areas, particularly in the Northern region, where over 80% live outside urban centers The Mekong River Delta, Central Highlands, and Central Coast regions show urbanization rates between 24% and 28% Vietnam is home to 54 ethnic groups, with the Kinh group comprising 85% of the population As of 2016, 9.2% of households were classified as poor, with the Northern region having the highest poverty rate at 13.8%, while the Southeast region boasts the lowest at just 0.6%.
Data description
Table 6: Descriptive statistics of the variables
Variable Obs Mean Std dev Min Max
Source: Authors’ computation using Stata
Table 6 shows data on variables from 46,995 observed home samples in Vietnam during five even years beginning with 2010 Here is s a summary of the model’s dependent and independent variables
As stated above, our research would employ four dependent variables to reflect energy poverty: spending on electricity, lighting energy, entertainment & education, and service
Electricity expenditure (EC) represents the total cost of electricity paid by households during the survey year, measured in US Dollars The average electricity expenditure was approximately 103.6 USD, with a standard deviation of 84.58 USD Households reported a minimum electricity expenditure of 10.62 USD and a maximum of 318.56 USD per year.
The Lighting energy variable indicates the availability of electricity for lighting in households, with a value of 1 signifying the use of electricity and 0 indicating reliance on alternative energy sources like generators, gas, or oil lamps With a mean value of 0.987, it is evident that the vast majority of homes depend on electricity for illumination, while the standard deviation of 0.11 reflects minimal variation in this usage among residences.
Service (Service) : This is a variable representing an element of the MEPI energy poverty index, representing the household appliance ownership status of the household
A value of 1 represents households that have a refrigerator and 0 represents households that do not have this appliance The mean and standard deviation of this variable are 0.58 and 0.49, respectively
The Entertainment & Education (EE) variable indicates a household's access to entertainment and educational technology, specifically through ownership of devices like televisions or radios A value of 1 signifies that a household owns these devices, while a value of 0 indicates otherwise With a mean value of approximately 0.92, most households own such technology, and the standard deviation stands at about 0.28, reflecting a relatively consistent trend in device ownership.
Independent variables related to Education
The study aims to determine the influence of education on household energy poverty We offer two variables denoting education, which are connected to the household head’s educational degree
The highest grade of education attained by household heads in Vietnam, referred to as EDU1, is measured within the country's 12-grade system, with values ranging from 0 to 12 A value of zero is assigned to those who have not completed grade one, while the mean value for household heads is 7.3, accompanied by a standard deviation of 3.7, as illustrated in Table 6.
The variable EDU2 represents the highest level of education or occupational qualification attained by the household head Responses are scored based on educational attainment, with those who do not meet the criteria assigned a value of 0 Elementary, middle, and high school graduates receive scores of 1, 2, and 3, respectively, while individuals with primary vocational degrees, vocational secondary, vocational high schools, and vocational colleges are assigned values from 4 to 7 College, university, master’s, and doctoral degree holders score 7 to 10, while those with other qualifications receive a value of 11 The mean and standard deviation for EDU2 are 2.19 and 2.11, respectively.
Other indepentdent variables (control variables)
To enhance the model's comprehensiveness, objectivity, and accuracy, the authors incorporated eight additional control variables, comprising three related to the characteristics of the household head and five reflecting the household's status.
The ethnic background of the household head (HHHEthnic) is a control variable that distinguishes between heads of households from ethnic minorities, represented by a value of 1, and those from the predominant ethnic group, the Kinh, indicated by a value of 0 The mean value for this variable is 0.18, suggesting a lower representation of ethnic minorities, with a standard deviation of 0.38.
The variable HHHAge indicates the age of the household head, with VHLSS data showing that from 2010 to 2018, the youngest head of household was just 11 years old, while the oldest was significantly older.
105 years old The mean value of this variable is 50.59, and a standard deviation of 14.11
The gender of the household head (HHHG) is a key control variable, where a value of 1 indicates a female-headed household and 0 indicates a male-headed household The average value of this variable is 0.25, reflecting a standard deviation of 0.43.
The study analyzed total household income (HHIncome) over a year, revealing a range from a minimum of $404.02 to a maximum of $25,372.08 The average annual income among the sampled households was $5,095.08, with a standard deviation of $4,476.94, indicating significant variability in income levels.
In the survey, households are classified as poor based on a control variable, where a value of 1 indicates a poor household and a value of 0 represents all other households The mean value of this variable is 0.11, with a standard deviation of 0.32, highlighting the distribution of poverty among the surveyed households.
Households involved in self-production and business activities in agriculture, forestry, and fishing are categorized under the variable SPB In a recent survey, families engaged in these sectors indicated their participation by answering '1,' while other households provided different responses.
0 This variable has a mean value of 0.83 and a standard deviation of 0.37, indicating that families participating in the survey engage in self-production and business activities related to agriculture, forestry, and fishing
Living area of household (Area): This control variable is used to assess whether a household is in a rural or urban location The value 0 indicates urban households, and
The variable representing rural households has a mean value closer to 1 than to 0, indicating that most observed samples are predominantly from rural areas, with a standard deviation of 0.46.
The study includes household size (HHS) as a final control variable, revealing that survey participants live in households ranging from 1 to 15 individuals The average household size is 3.83, with a standard deviation of 1.58.
Data characteristics testing results
Table 7: Variable correlation in the model
Source: Authors’ computation using Stata
The correlation coefficient, as utilized in Galton's 1880 model, reveals that all values in Table 7 are below 0.8, indicating a lack of significant cross-correlation among the variables that could influence the estimation results.
Table 8: Results of testing the phenomenon of multicollinearity
Source: Authors’ computation using Stata
Multicollinearity occurs in statistical analysis when independent variables in a linear model exhibit a strong linear relationship, impacting the accuracy of estimated results (Kim, 2019) As indicated in Table 8, multicollinearity is absent, as the VIF coefficients for the variables and the average coefficient are both below 10.
Table 9: Results of testing the phenomenon of heteroskedasticity
Breusch–Pagan/Cook–Weisberg test for heteroskedasticity
Variable: Fitted values of EC
Source: Authors’ computation using Stata
To determine if our data were normally distributed, we performed the Breusch- Pagan/Cook-Weisberg test (Jeroh, 2016) More specifically, Table 9 shows that the model has heteroskedasticity due to P-value = 0.000 < α = 0.05.
Results and discussion
5.4.1 Measuring energy poverty in Vietnam
Tables 10, 11, and 12 present the energy expenditures of households engaged in self-production activities within agriculture, forestry, and fishery These tables analyze the three energy groups featured in the energy ladder and energy stacking models.
Table 10: Energy transition in Vietnam from 2010-2018
Share of advanced fuels in energy expenditure for production (%) 14 21 22 20 18 4
Share of transition fuels in energy expenditure for production (%) 78 72 72 73 77 -1
Share of primitive fuels in energy expenditure for production (%) 8 7 5 6 5 -3
Source: Authors’ computation using VHLSS
Table 10 shows the shifting trend in the percentage of spending on types of energy used in agricultural, forestry, and fishery activities of households in Vietnam in
Between 2010 and 2018, the percentage of households utilizing advanced energy for production activities saw significant changes In 2012, this percentage rose sharply from 14% in 2010 to 21% Although it continued to increase slightly to 22% in 2014, a downward trend followed By 2018, the proportion of spending on electricity and LPG in relation to total energy production expenses had increased by 4% compared to 2010.
Household spending on transition fuels and primitive fuels has declined, reflecting a shift towards advanced energy sources From 2010 to 2018, expenditure on transition fuels such as coal, briquette, gasoline, and kerosene decreased by 1%, while spending on primitive energies, particularly firewood, fell by 3%.
Table 11 presents the distribution of expenditures on fuel sources across three categories: advanced, transition, and primitive fuels, in relation to the overall fuel spending in six regions of Vietnam, namely the Red River, Northern, Central Coast, Central Highlands, Southeast, and Mekong River Delta.
Data from Table 11 reveals a notable decline in spending on transition fuels across most regions in Vietnam, with the exception of the Central Highlands In the Red River and Central Coast regions, manufacturing households reduced their fuel expenditures by over 20% from 2010 to 2018 Other areas, including the Northern, Southeast, and Mekong River Delta regions, also experienced decreased spending, albeit at lower rates of 11%, 7%, and 3%, respectively In contrast, the Central Highlands saw a significant increase of 24% in household spending on fuel transactions during the same period, diverging from the overall national trend.
With data representing spending on fuels in the advanced energy group, it can be seen that compared to 2010, households in general spent more on this fuel group in
Table 11: Energy transition in Vietnam from 2010 - 2018 by region 2010 2018 De lt a 2018 -2010 Re d Rive r Nor th -e rn Ce n tr al Coas t Ce n tr al Hi gh lan d s S ou th - eas t
M ek on g Rive r De lt a Re d Rive r Nor th -e rn Ce n tr al Coas t Ce n tr al Hi gh lan d s S ou th - eas t
The Mekong River Delta demonstrates varying trends in energy expenditure across different regions In 2018, all regions experienced an increase of over 10% in spending on advanced fuels, with the Central Coast region seeing a notable 20% rise Conversely, the Central Highlands region was the only area to report a decline, with a decrease of 14% This data highlights the diverse energy consumption patterns and the reliance on advanced fuels in the Mekong River Delta compared to other fuel types.
The spending on fuel by the primitive group shows uneven fluctuations across different regions In the Red River, Central Coast, and Southeast regions, fuel expenditure has increased by 7%, 2%, and 2%, respectively Conversely, the Northern, Central Highlands, and Mekong River Delta regions have experienced more significant decreases in fuel spending, with reductions of 2%, 10%, and 7%, respectively.
Table 12: Disaggregated energy transition in Vietnam from 2010 to 2018
Urban vs Rural Urban Rural Urban Rural Urban Rural
Share of advanced fuels in energy expenditure for production (%)
Share of transition fuels in energy expenditure for production (%)
Share of primitive fuels in energy expenditure for production (%)
Ethnic majority vs minority Majority Minority Majority Minority Majority Minority
Share of advanced fuels in energy expenditure for production (%)
Share of transition fuels in energy expenditure for production (%)
Share of primitive fuels in energy expenditure for production (%)
Consumption non-poor vs poor
Share of advanced fuels in energy expenditure for production (%)
Share of transition fuels in energy expenditure for production (%)
Share of primitive fuels in energy expenditure for production (%)
Source: Authors’ computation using VHLSS
Table 12 illustrates the spending ratios of households involved in agricultural, forestry, and fishery production for three fuel categories—advanced, transition, and primitive—classified by living area (urban and rural), ethnicity of the household head (majority and minority), and poverty status (poor and non-poor) for the years 2010 and 2018 The data reveals a notable shift from traditional energy consumption to modern energy sources, with urban households increasing their spending on advanced fuels by 7% and rural households by 14% Conversely, expenditures on transition fuels decreased significantly, dropping by 13% for urban and 14% for rural households.
In 2018, the expenditure ratio of households led by ethnic minorities and the majority was 10% and 2%, respectively, showing a downward trend from 2010 Table
In 2018, families led by the Kinh majority reduced their spending on transition energy by 2%, while ethnic minority households increased their expenditure on advanced fuels by 5% compared to 2010, reflecting a notable shift in energy spending habits.
In line with national trends, non-poor households engaged in agriculture, forestry, and fisheries reduced their spending on traditional and primitive fuels by 1% and 3%, respectively, while increasing their investment in modern fuel sources Conversely, while poor households did not significantly transition to advanced energy options, they also decreased their expenditure on primitive fuels by 3% and allocated more towards transitional fuels.
In 2018, agricultural, forestry, and fisheries families increased their spending on advanced fuels compared to traditional fuels, marking a significant shift since 2010 This transition from traditional to modern fuels is promising for reducing energy poverty, as noted by Khandker et al (2012) Additionally, Nguyen et al (2021) corroborated these findings, highlighting a decline in the use of environmentally harmful transitional fuels like coal and biomass in favor of cleaner energy sources, such as electricity, between 2004 and 2016.
Table 13: Factors affecting Energy Poverty (Model results after fixing heteroskedasticity errors)
VARIABLES EC Lighting Service EE
Source: Author’s computation using Stata Energy poverty measured by Electricity consumption
According to Table 13, there is a positive correlation between education measurement variables and annual electricity spending Notably, at a 1% significance level, each additional class taken results in a slight increase in electricity consumption, while achieving one higher degree level contributes to an increase of approximately 2.39 units in electricity use.
Household head characteristics such as ethnicity, age, and gender significantly impact electricity consumption, with a notable correlation at the 1% level Specifically, being part of a minority group leads to a considerable decrease in electricity usage Conversely, there is a positive relationship between electricity consumption and the gender and age of the household head; as the head is female and older, electricity consumption tends to increase.
Household status factors are also proven to have statistical value at the 1% level of significance Regarding the variables measuring income poverty (HHIncome and
Research indicates that households classified as poor significantly reduce their electricity consumption, while a $1 increase in income leads to a marked rise in electricity expenditures Additionally, the presence of an extra household member correlates with increased electricity usage; however, self-employed households in rural areas experience a decrease in consumption by $7.31 and $24.44, respectively Furthermore, variables related to household electrical appliances, especially refrigerators, demonstrate a strong positive correlation with annual electricity costs.
Energy poverty measured by Lighting – Service – Entertainment & Education
Table 13 reveals that educational variables significantly influence energy poverty, particularly in the use of electricity for lighting, housing services like refrigerators, and entertainment devices such as TVs and radios Specifically, for each additional class completed by the householder, the likelihood of owning and using these electrical appliances increases While a high school, university, or vocational degree held by the household head positively correlates with refrigerator ownership, it shows minimal negative effects on the usage rates of electric lighting and TVs/radios.