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Article

Impact of Access to Electricity and Socio-Economic Environment on Poverty Reduction: An Empirical Study on Myanmar

by
Qian Xiong
1,
Wenxin Shen
2,
Chunna Liu
3,
Xuteng Zhang
1,
Wenzhe Tang
1,*,
Colin F. Duffield
4,
Felix Kin Peng Hui
4 and
Lihai Zhang
4
1
State Key Laboratory of Hydroscience and Engineering, Institute of Project Management and Construction Technology, Tsinghua University, Beijing 100084, China
2
Department of Construction Management, School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China
3
China Institute of Water Resources and Hydropower Research, Beijing 100048, China
4
Department of Infrastructure Engineering, The University of Melbourne, Melbourne 3010, Australia
*
Author to whom correspondence should be addressed.
Energies 2024, 17(21), 5451; https://doi.org/10.3390/en17215451
Submission received: 25 September 2024 / Revised: 13 October 2024 / Accepted: 28 October 2024 / Published: 31 October 2024
(This article belongs to the Section B: Energy and Environment)
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Versions Notes

Abstract

:
Previous studies have identified the importance of access to electricity and the socio-economic environment for poverty reduction, but the comprehensive interplay and synergistic relationships between them remain unclear. Using data collected from Myanmar, this study establishes and tests conceptual models to explore the paths from access to electricity and socio-economic environment to capability and income poverty reduction. The results of structural equation modeling show that capability poverty reduction acts as a complete mediator between access to electricity and income poverty reduction, and plays a partial mediating role between socio-economic environment and income poverty reduction. Analysis of fuzzy-set qualitative comparative analysis demonstrates that lack of electricity is a key barrier impeding poverty alleviation efforts. Moreover, five effective configurations of poverty reduction factors are identified for Myanmar by considering the heterogeneity of different regions. This indicates that individual factors could not ensure a highly effective poverty reduction and different factors need to be appropriately configured for achieving the synergistic effects. These findings contribute to practical insights into poverty reduction policy making and sustainable development for developing countries.

1. Introduction

Persistent poverty remains a pervasive global challenge, significantly obstructing the attainment of Sustainable Development Goals [1]. Despite concerted efforts to alleviate poverty, 9% of the global population still subsists on less than $2.15 per day [2,3]. Myanmar, the largest country in mainland Southeast Asia, confronts severe poverty challenges, with a poverty rate of 24.8% in 2017 [4]. The causes of poverty in Myanmar are multifaceted. One notable issue is the limited access to electricity. Myanmar’s electrification rates stand at only 55% in rural areas and 92% in urban areas [2], which impedes both local development and poverty reduction efforts [5]. Political instability and the agriculture-dependent economy have also slowed Myanmar’s economic progress, making it more vulnerable to global market fluctuation [6]. The country’s vast geography, compounded by military coups and ongoing conflicts, further complicates the equitable provision of infrastructure and services, as well as economic opportunities. These challenges underscore the urgent need for identifying and implementing effective poverty reduction strategies in Myanmar.
Academia has identified several key factors for poverty reduction. Firstly, the socio-economic environment plays a pivotal role in alleviating poverty, encompassing education, health services, technological advancement, and industrialization [1,7,8]. An enhanced socio-economic environment not only equips individuals with essential professional skills but also fosters job creation [9,10]. Secondly, with the development of modern society, access to electricity has become fundamental to poverty alleviation, aligning with the seventh Sustainable Development Goal. Ensuring electricity access could significantly enhance people’s well-being by improving their educational and health conditions [11,12]. It also prolongs working hours and enables the use of sophisticated equipment, boosting people’s productivity and supporting sustained poverty reduction [13,14]. Previous research has often focused on how these factors influence singular poverty indicators, such as income levels or household expenditure. Yet, poverty alleviation encompasses not only overcoming income poverty but also enhancing people’s capabilities for meaningful participation in productive activities [15,16]. Drawing upon this view, this research advances the existing body of knowledge by examining how access to electricity and the socio-economic environment influence capability and income poverty reduction from a holistic perspective.
Beyond identifying key factors of poverty reduction, it is also crucial to strategically integrate these elements to develop effective poverty alleviation strategies. Despite numerous policies aimed at improving people’s living standards, their effectiveness in Myanmar remains limited, which is partly due to the uneven development across different sectors of society and the economy [17]. The regional diversity inherent to Myanmar’s extensive geography further necessitates tailored poverty alleviation approaches [18]. However, the empirical exploration of how various poverty reduction factors interact and achieve synergistic effects is scant. To fill this gap, this study has collected data across different townships to assess the effectiveness of various factor combinations for poverty reduction, thereby contributing to the nuanced understanding and strategic formulation of poverty alleviation policies for Myanmar.
This study employs the combined methods of structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA), which has been demonstrated as suitable for understanding causality in social problems and policy formulation [19,20,21]. Initially, this research develops a conceptual model delineating the pathways through which electricity access and the socio-economic environment contribute to capability and income poverty reduction. The data collection employs a triangulated methodology, encompassing surveys, interviews, and observations across Myanmar’s diverse regions. SEM is used to empirically validate this model. Subsequently, this research assesses the synergistic effects of electricity access and socio-economic conditions by leveraging township-level data from Myanmar. FsQCA is applied to identify optimal combinations of factors for region-specific poverty alleviation strategies.
This research enriches both theoretical frameworks and practical research on poverty alleviation. Firstly, it expands the literature by mapping capability and income poverty reduction onto electricity access and the socio-economic environment. Secondly, the study reveals the pivotal role of electricity access in mitigating both income and capability poverty. Thirdly, the results demonstrate the significance of integrating electricity access and socio-economic factors for effective poverty reduction. This research identifies five tailored combinations of these elements for Myanmar, each adapted to specific regional characteristics. These findings also contribute to formulating effective policies for poverty alleviation in developing countries.

2. Literature Review

2.1. Multidimensional Nature of Poverty Reduction

The concept of poverty has evolved over time. In the late 1960s, it initially centered on economic metrics, such as income level and employment [22]. Since the 1970s, it has encompassed broader human welfare aspects, including health, education, food, housing, and clothing [23], and has subsequently extended to individuals’ capabilities and freedom in productive activities [24,25]. This nuanced understanding has led to the classification of poverty into two types: income poverty, which relates to the lack of sufficient resources for necessities like food, housing, and heating [26,27], and capability poverty, which reflects a lack of freedom to engage in productive activities [15,16]. Empowering the impoverished has emerged as a crucial strategy in this context, helping individuals to take control of their lives, invest in their futures, and permanently escape the grip of poverty.
Eradicating poverty stands as the cornerstone of the Sustainable Development Goals [1], requiring both social and economic development [28,29]. Extensive studies underscore the significance of socio-economic factors in poverty alleviation [9,10]. For instance, improved education correlates closely with enhanced economic and social outcomes [30]. Numerous studies observe that higher educational attainment would contribute to increased earnings, as education could increase individuals’ supportive knowledge and skills for higher wages [31]. Qualified health conditions are also important for poverty reduction [32]. For the poor, health is a critical economic asset that can reduce income loss and healthcare costs due to health problems [33]. Enhancing health conditions can ensure the quality and quantity of labor, thereby contributing to economic growth and poverty alleviation [34]. Furthermore, technological development could boost productivity and increase demand for labor outside of traditional agriculture, collectively supporting poverty reduction efforts [35].
Previous studies have also highlighted the critical role of electricity access in improving human well-being, notably education and health outcomes [12,36,37,38,39]. For example, Oum [12] demonstrates that energy poverty in Lao PDR negatively impacts household education levels and health statuses. Batool et al. [36] identify energy poverty as a significant driver of income poverty, health poverty, educational poverty, and environmental poverty. Ahmad et al. [37] assert that electricity access promotes people’s education and health attainment in rural India. In addition, improving electricity access can facilitate the use of advanced equipment, thereby increasing access to productive activities and enhancing working efficiency to reduce poverty [13,14]. Some studies have further underscored that eliminating energy poverty not only enhances social capital among the poor but also contributes to broader societal prosperity [40,41,42].
Despite the multidimensional nature of poverty reduction, previous studies often focus on the impact of these factors on a single poverty indicator, without distinguishing between their roles in reducing capability poverty and income poverty. To fill this gap, this research establishes conceptual models to elucidate the interconnections between electricity access and socio-economic factors, as well as their differential impacts on capability poverty reduction and income poverty reduction.

2.2. Poverty Reduction in Myanmar

Myanmar, the most extensive nation in mainland Southeast Asia, is confronting significant poverty challenges. Although concerted efforts have led to a reduction in the poverty rate from 42.2% in 2010 to 24.8% in 2017, Myanmar still exhibits a high poverty rate within the Southeast Asian region [4]. The country’s vast geographical expanse, compounded by the ramifications of military coups and ongoing conflicts, significantly hampers its poverty alleviation efforts. This context accentuates the critical need for identifying pivotal factors that can drive poverty reduction in Myanmar and for the development of effective poverty alleviation policies.
The existing literature has explored the multidimensional nature of poverty in Myanmar, assessing factors such as education, health, standard of living, and access to basic services [43,44]. Findings indicate that approximately 60% of Myanmar’s population is grappling with multidimensional poverty issues. Considering critical factors for poverty reduction in Myanmar, academia has evaluated aspects including health conditions [45], education [46], food security [47], technology development [48], society stability [6,49], and energy access [5,50]. For example, Teerawichitchainan and Knodel [45] demonstrate the interrelationships between poverty, economic inequality, and health among the elderly in Myanmar. Boughton et al. [6] show that COVID-19 and military coups significantly have impacted human welfare and poverty in Myanmar. Shyu [5] examines Myanmar’s electrification progress and analyzes the relationship between electricity access and poverty reduction. However, these studies often rely on macroeconomic data without fully considering the interactions between multiple factors and different types of poverty. This research gap stems from incomplete national statistical data and challenges in conducting fieldwork in Myanmar, which hinders direct engagement with the residents [6].
Public policy plays an indispensable role in poverty reduction, which could foster supportive conditions for the poor by providing adequate access to physical and human assets [38,51]. Corresponding to the poverty reduction factors, both social policies (e.g., investment in education, health care, and housing conditions) and energy policies (e.g., tax reduction and energy efficiency improvements) have been implemented in Myanmar. For example, initiatives like Housing Development Projects and Thirty-year Long-term Education Development Plan have been carried out to improve the residents’ living conditions [52,53,54]. In the 21st century, the Myanmar government has implemented community energy projects to reduce reliance on wood fuel and advocate for electricity generation and distribution, aiming to enhance residents’ productivity and reduce poverty [55]. Nevertheless, these policies have yielded limited success. On one hand, the lack of development across different sectors of society and the economy has restricted the benefits from these policies [17]. For example, low education levels limit residents’ awareness of energy efficiency and reduce their demand for electricity-powered products, thereby hindering electrification progress and impeding poverty reduction efforts. On the other hand, poverty in Myanmar has regional characteristics due to the country’s vast size, necessitating tailored poverty reduction policies [18]. These findings underscore the necessity of integrating social and energy policies by considering the characteristics of different regions in Myanmar to enhance the efficacy of poverty reduction.
To address this issue, this research conducted a field trip, including a questionnaire survey, interviews, and direct observations, to collect data from different regions in Myanmar. Utilizing this dataset, this study aims to address two primary questions: (1) What is the holistic relationship between electricity access, the socio-economic environment, capability poverty reduction, and income poverty reduction? and (2) How can diverse factors be effectively configured to formulate highly effective poverty alleviation policies in Myanmar?

3. Hypotheses and Conceptual Models

3.1. The Role of Capability Poverty Reduction in Income Poverty Reduction

People with higher capabilities can attain higher education levels and obtain more professional skills, positioning individuals for well-compensated employment opportunities, and thereby boosting their income [56]. Enhanced capability correlates with improved health, mitigating disease risk and enhancing work efficiency and potential earnings [57]. Additionally, adequate access to productive resources represents another crucial component of capability poverty reduction. This includes efficient use of the internet and social networks for job searching, which facilitates engagement in income-generating activities [13]. Therefore, the hypothesis was proposed as follows:
Hypothesis 1.
Capability poverty reduction has a positive influence on income poverty reduction.

3.2. The Role of Access to Electricity in Poverty Reduction

Considering capability poverty, enhancing electricity access could provide diverse educational resources and extend study hours, thereby improving residents’ job market competitiveness [11]. Electricity also facilitates the widespread use of advanced technologies like the internet, broadening access to employment opportunities [13]. It also reduces reliance on wood and fossil fuels, decreasing respiratory diseases and improving health conditions [58]. Furthermore, electricity boosts health facilities’ efficiency, aiding in diagnosis and treatment [59]. Regarding income poverty, improved electricity access boosts productivity and efficiency, leading to higher incomes [11]. Moreover, electricity extends lighting hours, allowing for more time for income-generating activities, such as handicrafts and home-based businesses [60]. Therefore, the following hypotheses were developed:
Hypothesis 2.
Increasing access to electricity has a positive influence on capability poverty reduction.
Hypothesis 3.
Increasing access to electricity has a positive influence on income poverty reduction.

3.3. The Role of Socio-Economic Environment in Poverty Reduction

The socio-economic environment is crucial for poverty reduction at a macro level [7]. Considering the capability poverty reduction, an enhanced socio-economic environment can bolster infrastructure investment and professional development. This can further enrich educational and health systems and, in turn, boost labor productivity [61]. As a key factor of socio-economic development, technological development helps people access employment information via the internet and increase income through sophisticated tools [62]. For alleviating income poverty, a better socio-economic environment could allocate more resources for financial support to the underprivileged [63], create additional job opportunities, and boost employment rates to increase people’s income [64]. As a result, the following hypotheses were developed:
Hypothesis 4.
Socio-economic environment has a positive influence on capability poverty reduction.
Hypothesis 5.
Socio-economic environment has a positive influence on income poverty reduction.

3.4. Conceptual Models for Poverty Reduction

Considering all the hypotheses proposed above, the conceptual model for the roles of access to electricity and socio-economic environment in capability poverty reduction and income poverty reduction is shown in Figure 1. The first part of this research aims to evaluate this model and explore the mechanism of poverty reduction.
Previous studies have highlighted that enhancements in electricity access and the socio-economic environment are critical to alleviating poverty. However, the interaction between these two contributors and their potential synergistic effects on poverty reduction remains unclear. To provide practical insights for policymaking, this research further develops a framework focusing on the interplay between key factors for effective poverty reduction, as shown in Figure 2.
The socio-economic environment encompasses a wide range of elements that impact human well-being, including education, healthcare, and technology [11,12]. Considering that improvements in educational and health outcomes generally require investments in both infrastructure and human capital development [29], this study specifically deconstructs the socio-economic environment into five targeted factors, as shown in Figure 2, i.e., health human resources, health infrastructure, education human resources, education infrastructure, and technology development. Along with the factor of access to electricity, these six factors for poverty reduction are depicted around the periphery of Figure 2. The outer black circle indicates the potential interconnections between these factors, while the inner arrows signify their positive influence on poverty reduction.
Building on this theoretical model, the second part of this study aims to reveal the synergistic effects of electricity access, healthcare and educational infrastructure, the workforce in the health and education sectors, and technology advancement on poverty reduction in Myanmar.

4. Datasets and Methods

4.1. Individual-Level Data from Fieldtrip in Myanmar

4.1.1. Measures

  • Access to electricity
Previous studies emphasize the significance of ensuring reliable, affordable, and stable electricity access to foster economic growth and sustainable development [65,66,67]. Reliable access implies that households are connected to a consistent power supply [65]. Affordability pertains to residents’ satisfaction with electricity prices [66], while stability concerns the quality of the power supply, such as the frequency of electricity blackouts [67]. Accordingly, accessibility, affordability, and stability were used to assess electricity access.
2.
Socio-economic environment
Improving the socio-economic environment involves enhancing the local macroeconomy, which facilitates economic growth and the provision of social services [9]. Furthermore, socio-economic stability is crucial for mitigating the vulnerability of impoverished populations to economic fluctuations, thereby fostering a pro-poor environment [68]. Consequently, economic growth conditions and socio-economic stability were used to evaluate the socio-economic environment.
3.
Capability poverty reduction
Introduced by UNDP in 1997, the capability poverty measure (CPM) focuses on health and nutrition, healthy reproduction, and female illiteracy. Subsequently, education and health emerged as pivotal factors in mitigating capability poverty [25]. As comprehension of poverty advanced, addressing social exclusion gained importance, emphasizing improved market access and participation in pro-poor policy formulation [28]. Thus, health status, education level, and access to productive activities were used to evaluate the capability poverty reduction.
4.
Income poverty reduction
Eliminating income poverty ensures individuals can afford essentials like food, housing, and heating [26]. Adequate food is vital for survival and health [69], and better housing offers protection against environmental hazards such as floods and cyclones [70]. In addition, effective heating systems could help households have a balanced diet and live in a safe environment [71]. Therefore, diet affordability, housing affordability, and heating affordability were used to evaluate income poverty reduction.

4.1.2. Questionnaire

The questionnaire was divided into two sections for gathering quantitative data. The first section included the demographic information of the respondents, and the second section contained questions related to electricity access, the socio-economic environment, and poverty status, aligning with the study’s conceptual framework. Questions in the second section were applied to a Five-point Likert Scale ranging from ‘strongly disagree’ (1) to ‘strongly agree’ (5). The English version of the questionnaire was first reviewed for validity by a panel of experts and then translated into Burmese by scholars from Myanmar universities. Through iterative refinement and pilot testing, the questionnaire’s linguistic precision and reliability were verified.

4.1.3. Triangulated Approach in Fieldtrip

The triangulated approach in this study included a questionnaire survey, interviews, and direct observations to collect data in Myanmar for analysis of structural equation modeling. This approach aims to leverage both quantitative and qualitative data to substantiate and deepen the understanding of the research propositions within a real-world context.
The data were obtained from two weeks of fieldwork along the Ayeyarwady Basin in Myanmar in December 2019. A collaborative team of experts and researchers from universities in China and Myanmar was recruited to conduct this fieldtrip. The Ayeyarwady Basin, occupying 62% of Myanmar, is a critical commercial zone supporting trade, transport, and energy generation for residents which plays a pivotal role in poverty alleviation for Myanmar [72]. The questionnaire survey engaged respondents from four key hydro-ecological zones in the Ayeyarwady Basin, including the Upper Ayeyarwady (e.g., Myitkyina), the Middle Ayeyarwady (e.g., Sagaing), the Lower Ayeyarwady (e.g., Magway) and the Ayeyarwady Delta (e.g., Yangon). To reduce the dropout rate and improve accuracy, this research implemented the following measures: (1) the aim of the survey was declared to be non-profit, (2) all questionnaires were completed with respondents accompanied by researchers for elaborating on the questions, and (3) all respondents were informed that they were completing the questionnaires with anonymity.
A total of 128 questionnaires were sent out and all these questionnaires were collected. Excluding six invalid questionnaires with incomplete information, one hundred and twenty-two questionnaires were used for analysis, which met the requirements of the PLS-SEM method for the sample size [73]. The respondents were sourced from diverse demographic and professional backgrounds. Of the respondents, 58% were female, and 42% were male. Regarding employment status, 58% identified as self-employed, 31% as regularly employed, 13% as students, and 2% as either unemployed or retired. The participants’ ages ranged from 18 to 70, with an average age of 42 years. The age distribution included 19% aged 18–25, 15% aged 26–35, 21% aged 36–45, 26% aged 46–55, and 18% over 55.
After the questionnaires were completed, semi-structured interviews with respondents were conducted on topics covered by the questionnaires to learn how access to electricity and the socio-economic environment impact respondents’ daily lives. Direct observations were conducted during the fieldwork to enhance the researchers’ understanding of the poverty status in the visited regions.

4.2. Township-Level Data from Government Statistics

Township-level data from all 330 townships in Myanmar were gathered from the Myanmar Information Management Unit (MIMU) to assess the effectiveness of various factor combinations by using fuzzy-set qualitative comparative analysis (fsQCA). Given that random sampling has been recommended in fsQCA to minimize the emergence of contradictory configurations [74], this study randomly selected 110 cases. The outcome variable ‘poverty reduction’ was represented by the township wealth ranking index, which has been stated to be capable of reflecting poverty status [10,75].
The poverty reduction factors (causal conditions) consist of the factors of access to electricity and the socio-economic environment. For access to electricity, this research used the percentage of households using electricity for lighting to represent the status of local access to electricity. For the socio-economic environment, both investments in infrastructure and human resources were considered [7], including the school–pupil ratio, teacher–pupil ratio, sub-health center–population ratio, nurse–population ratio, and percentage of households with the internet, to measure the local status of education infrastructure, education human resources, health infrastructure, health human resources, and technology development, respectively. Table 1 lists the measures, data sources, and relevant references of the outcomes and causal conditions.

4.3. Data Analysis Techniques

The data analysis employed two methodologies: structural equation modeling (SEM) to examine the poverty reduction mechanisms (see Figure 1) and fuzzy-set qualitative comparative analysis (fsQCA) to explore the interplay between factors contributing to poverty alleviation (see Figure 2). This dual-analysis approach, widely used in research, is suitable for analyzing and understanding causality in social problems and policy formulation [19,20,21]. Additionally, we used ChatGPT (Chat Generative Pre-Trained Transformer) 4.0, developed by OpenAI in San Francisco, CA, USA, for grammar checks to ensure clarity in the elaboration and discussion.
Structural equation modeling serves as a tool for measuring and testing substantive and complex interrelationships [83]. Partial least squares structural equation modeling enables the simultaneous estimation of multiple causal relationships between one or more independent and dependent variables, which is more suitable for a small sample size [84]. Considering the sample size of this study, the 122 responses exceed both the requirements of (1) ten times the largest number of formative indicators used to measure one construct, and (2) ten times the largest number of structural paths directed at a particular latent construct [73]. Analyses of this study were conducted by the software SmartPLS 3.0, developed by SmartPLS GmbH in Bönningstedt, Germany.
FsQCA, developed by Charles Ragin [85], applies Boolean algebra logic to identify the relationships between the outcomes and all configurations of the independent variables (causal conditions) [85]. Unlike traditional quantitative methods that focus on correlations, fsQCA is particularly suited to cases where the relationships between variables are complex or asymmetric [86]. This method identifies multiple combinations of conditions that can produce the same outcome, providing a nuanced understanding of causality that goes beyond simple correlation. Furthermore, fsQCA offers more accurate depictions of real-world processes, enabling it to provide practical insights and recommendations for policymaking. In this study, fsQCA 3.0 was used for corresponding analyses, an open-access tool developed by the Department of Sociology at the University of California in Irvine, CA, USA.

5. Empirical Results and Discussion

5.1. Results of Structural Equation Modeling

5.1.1. Measurement Model Evaluation

Confirmatory factor analysis (CFA) was conducted to evaluate the measurement model. The Cronbach’s Alpha (CA) value and Composite Reliability (CR) were used to examine internal consistency, both recommended to exceed 0.7 [87]. Table 2 shows that the Cronbach’s Alpha values for all constructs range from 0.765 to 0.881, and the composite reliability values range from 0.865 to 0.931, indicating the model’s satisfactory internal consistency. Convergent validity was examined through factor loadings and the Average Variance Extracted (AVE). All loadings exceed 0.7 and the AVE values are above 0.5, demonstrating adequate convergent validity (see Table 2).
Discriminant validity was evaluated by comparing whether the square roots of AVE values of constructs were higher than the correlations between each two constructs [88]. Table 3 shows that all AVE values meet the requirement, indicating all constructs in the model possess discriminant validity. Additionally, all heterotrait–monotrait ratio (HTMT) values fall below 0.90, reinforcing discriminant validity. Variance Inflation Factors (VIFs) range from 1.215 to 3.144, far below the threshold of 5.0, indicating that multicollinearity did not affect the analysis.

5.1.2. Structural Model and Hypothesis Testing

The standardized root means square residual (SRMR) was calculated to assess the model fit, which is 0.075 in this study. The SRMR value meets Henseler’s criterion of being below 0.08 and indicates a satisfactory structural model fit [89]. R2 is often used to evaluate the explanatory capability, which describes the degree of variance explained by each endogenous construct [90,91]. The R2 value of capability poverty reduction is 0.255, and the R2 value of income poverty reduction is 0.573, demonstrating a satisfactory predictive accuracy for income poverty reduction. Q2 based on the blindfolding procedure was then calculated to examine the predictive accuracy, which is recommended to be positive. The Q2 values of capability poverty reduction and income poverty reduction are 0.190 and 0.454, respectively, showing a reasonable predictive capability.
Regression coefficients ( β ) were used to present direct and indirect relationships between constructs [73]. Bootstrapping assessed significance through t-values, revealing broad support for our hypotheses, except for H3 (see Table 4). Considering mediating effects, capability poverty reduction acts as a complete mediator between access to electricity and income poverty reduction (βAE→CPR→IPR = 0.173, p = 0.006), and serves as a partial mediator between the socio-economic environment and income poverty reduction (βSE→CPR→IPR = 0.303, p < 0.001).

5.1.3. Paths from Access to Electricity and the Socio-Economic Environment to Poverty Reduction

The relationships between access to electricity, the socio-economic environment, capability poverty reduction, and income poverty reduction, along with the results of the structural equation modeling, are summarized in Figure 3.
First, access to electricity can significantly promote capability poverty reduction, thereby facilitating income poverty reduction. The complete mediation effect of capability poverty reduction between electricity access and income poverty reduction (βAE→CPR→IPR = 0.173, p = 0.006, see Table 4) indicates that the impact of electricity access on income poverty reduction in Myanmar is primarily through enhancing people’s capability. Field interviews in Myanmar confirm that access to electricity enhances educational outcomes by offering a broader range of learning resources and a better learning environment. The respondents also indicate that access to electricity facilitates the use of mobile phones, televisions, and radios, helping them obtain employment information. Both aspects contribute to higher employment rates and income levels among the residents.
Second, the socio-economic environment plays an important role in poverty reduction in two ways: (1) directly promoting income poverty reduction (βSE→IPR = 0.145, p = 0.014, see Table 4), and (2) promoting capability poverty reduction, thereby assisting income poverty reduction (βSE→CPR→IPR = 0.303, p < 0.001, see Table 4). The development of the socio-economic environment is instrumental in fostering macroeconomic growth [9,10], allowing governments to allocate more resources towards poverty reduction efforts and enhancing living conditions for the impoverished. For instance, the Department of Human Settlement and Housing Development (DHSHD) in Myanmar has initiated numerous housing development projects targeting impoverished households [52]. Improvement of the socio-economic environment also increases investment in education and health for capability enhancement. Interviewees on the fieldtrip confirmed that good schools and medical conditions helped their children obtain higher education levels, which has made it easier for them to find well-paid jobs, particularly in major urban centers like Yangon.

5.2. Results of Fuzzy-Set Qualitative Comparative Analysis

5.2.1. Calibration and Truth Table

This study calibrated condition and outcome variables into fuzzy sets with values ranging from 0 to 1, for which 0 means no set membership and 1 means full set membership [92]. As all variables were continuous, this research adopted a direct calibration method [93]. Moreover, 95%, 50%, and 5% quantile values were used as the thresholds for full membership, the crossover point, and full non-membership, respectively [94]. The cut-offs for each condition and outcome are shown in Table 5.
The truth table is the main tool for finding out which configurations cause the outcome. Based on Ragin [93], Proportional Reduction in Inconsistency (PRI) levels should not be below 0.75, and at least 75% of the cases should be included in the truth table. Given the sample size, this study set the PRI consistency threshold at 0.76, requiring at least one case for each configuration. The positive outcome (PR) signifies poverty reduction presence, while the negative (pr) denotes absence. In fsQCA, necessity analysis investigates the conditions required for the outcome, while sufficiency analysis identifies the conditions consistently leading to the outcome. This research conducted separate necessity analyses for positive (PR) and negative (pr) outcomes. Additionally, one sufficiency analysis for the positive outcome (PR) was conducted to explore effective configurations for poverty reduction in Myanmar.

5.2.2. Analysis of Necessity

All conditions were tested for the presence and absence of the outcomes. Table 6 shows the necessity for individual conditions.
According to Schneider and Wagemann [95], a condition is necessary if the consistency value exceeds 0.9 and the coverage value exceeds 0.5. Table 6 reveals that the consistency values for all conditions regarding poverty reduction presence fall below 0.9, suggesting that individual factors related to electricity access or the socio-economic environment alone cannot ensure highly effective poverty reduction in Myanmar. However, lacking access to electricity exhibits a consistency value of 0.903 and a coverage value of 0.803, surpassing the necessary thresholds. This underscores that lacking electricity access is a key reason leading to ineffective poverty reduction in Myanmar.

5.2.3. Effective Configurations for Poverty Reduction

FsQCA 3.0 provides complex, intermediate, and parsimonious solutions. As existing research has not reached a consensus on the relationships between the conditions and outcomes, this study chose “present or absent” when calculating the intermediate solution and reported the intermediate solution with a parsimonious solution [95]. Configurations for the presence of poverty reduction are shown in Table 7. Black circles (●) mean the presence of conditions, while crossed-out circles (⊗) mean the absence of them [93]. Core elements of a configuration are denoted by larger circles, while peripheral elements are denoted by smaller circles. Blank spaces denote conditions as either present or absent [96].
The consistency values demonstrate whether a configuration is consistent with the empirical cases, and the coverage values represent how many cases a configuration can cover [85]. Table 7 presents five configurations for the presence of poverty reduction, all exhibiting consistency values exceeding the recommended 0.8 threshold. Solution consistency and coverage value are 0.946 and 0.653, respectively, indicating satisfactory reliability.
Table 7 shows that access to electricity plays a core role in all configurations for the presence of poverty reduction, confirming its substantial impact on poverty alleviation, as evident in the structural equation modeling results (see Table 4). However, individual access to electricity alone does not guarantee highly effective poverty reduction. It is essential to configure access to electricity with socio-economic factors, emphasizing their synergistic relationship in effectively reducing poverty in Myanmar.
Within the socio-economic environment, the human health resources emerge as pivotal for poverty alleviation, evident in configurations PR2 to PR5 (see Table 7). In Myanmar, only approximately 40% of households have access to healthcare services [97]. In rural areas, the health service is mainly provided by basic health staff such as midwives, lady health visitors, and health assistants, who cannot reach out in a timely manner to remote and poor communities [77]. Thus, enhancing health human resources is imperative to ensure broader access to essential healthcare services in Myanmar. Technology development also plays a crucial role in poverty reduction, evident in configurations PR1 to PR3. In Myanmar, 41.2% of individuals aged 15 and above in urban areas have convenient access to the internet, whereas rural areas lag at 16.1% [98]. Enhancing technology access, especially in rural regions, is vital for leveraging advanced technologies in poverty alleviation efforts. However, the presence of education infrastructure and human resources is not central to poverty reduction. This is attributable to over 90% of the population having a high school education or below [73]. Such educational levels often lead to inadequate professional skills and knowledge. Interviewees corroborate that despite widespread primary education access, suitable employment remains elusive due to the lack of professional skills and adverse economic conditions.
Five configurations (see Table 7) can be generalized into three patterns for effective poverty reduction in Myanmar. The first pattern, represented by configuration PR1, underscores the critical roles of electricity access and technology development. With the highest raw coverage of 0.565, this combination proves effective across most townships. The second pattern consists of configurations PR2 and PR3, which have the presence of the core conditions of access to electricity, technology development, and health human resources. This suggests that a robust health workforce is also vital for poverty alleviation in many areas. The third pattern, encompassing configurations PR4 and PR5, highlights the critical roles of electricity access and health human resources, albeit with the lowest raw coverage among the patterns. This suggests that interventions targeting these areas should be highly focused, particularly in townships with deficient basic infrastructure and inadequate health services.

6. Contributions

6.1. Theoretical Contributions

Previous studies have identified the importance of access to electricity and the socio-economic environment for poverty reduction [12,37,99], but the comprehensive interplay and synergistic relationships between them remain unclear. First of all, this study establishes conceptual models to reveal the paths from access to electricity and the socio-economic environment to capability and income poverty reduction, facilitating a holistic understanding of poverty reduction (see Table 4).
Second, this study highlights that electricity access primarily reduces income poverty by mitigating capability poverty (see Table 4). This underscores electricity’s pivotal role in human development and its capacity to empower individuals to escape poverty. Additionally, the lack of electricity is identified as a key barrier to effective poverty alleviation. Its centrality in all effective configurations for poverty eradication reaffirms its social importance in Myanmar [14,100].
Third, this research shows that the socio-economic environment reduces poverty in two ways (see Table 4). It directly impacts capability and income poverty reduction, highlighting the importance of enhancing socio-economic conditions for poverty alleviation [101]. It also indirectly aids in income poverty alleviation by boosting capability poverty reduction. This demonstrates that a favorable socio-economic environment can empower individuals with skills, health, and access to job markets, which can subsequently facilitate higher-paying employment.
Fourth, this study reveals five effective configurations for effective poverty reduction in Myanmar (see Table 7). These findings demonstrate the complementary relationships between access to electricity and the socio-economic environment for effective poverty reduction. Understanding these patterns further provides a sound basis for formulating suitable poverty reduction interventions by considering regional characteristics [102].

6.2. Practical Implications

The above findings have significant practical implications in dealing with issues of poverty and suggesting poverty reduction policies in Myanmar as well as developing countries.
Access to electricity is a core condition for poverty reduction, since only 55% of rural households are connected to electricity in Myanmar. Therefore, the development of an electricity grid covering both urban and rural areas, coupled with the promotion of renewable energy, such as hydropower, wind power, and solar power, is paramount. In addition to the government’s and energy companies’ investment, the funds for energy development could also be loaned from multilateral institutions such as the World Bank and Asian Development Bank.
Considering the role of the socio-economic environment in poverty reduction, fostering economic growth on a macro scale is crucial in Myanmar. Considering that agriculture accounts for 38% and industry for 20.3% of Myanmar’s GDP [103], it is imperative to promote technological advancement and enhance high-productivity labor within the industrial sector. As 87.0% of the poor population lives in rural areas, prioritizing rural development is also essential for efficient poverty reduction strategies [98].
Capability poverty reduction plays a critical role in poverty reduction in Myanmar. Therefore, cultivating professional skills needs to be emphasized to increase people’s capability. Given that more than 90% of the population’s highest educational attainment is high school or below [73], the development of infrastructures and human resources should pay more attention to university, college, diploma, post-graduate, and vocational education in Myanmar.
The provision of workers for health services also needs emphasis, considering the core role of health human resources. In Myanmar, the ratio of nurses and midwives, as well as dental surgeons per 100,000 residents stands at 100 and 7, respectively, below the Southeast Asia averages of 153 and 10 [104]. This shortage impedes timely access to healthcare in remote and impoverished communities. To address this disparity, it is essential to ensure equitable distribution and access to education and training for healthcare professionals across both urban and rural areas.
The complimentary relationships between access to electricity and the socio-economic environment in Myanmar should be considered to ensure anti-poverty policy effectiveness in Myanmar. Different configurations of policy interventions to improve poverty reduction should be chosen by considering the heterogeneity of different regions, including local communities’ resource endowment, technology development level, human resources, educational and health conditions, and economic status.
These findings also provide valuable insights for poverty reduction in other developing countries. Notably, energy poverty has been identified as a significant contributor to poverty in developing countries, such as Pakistan and Cambodia [36,38]. These nations face several challenges, including limited access to modern energy services, inadequate grid infrastructure, and underdeveloped energy markets. Furthermore, many individuals are unable to afford modern energy, which exacerbates the issue. Addressing these challenges requires more than just investment in the energy sector. It also necessitates stimulating the broader macroeconomy. A better socio-economic environment can not only create employment opportunities but also increase public investment in infrastructure and human resources, supporting sustainable social development. Among these factors, empowering individuals to build self-reliance is crucial for achieving long-term poverty alleviation. Rather than relying solely on direct financial aid, empowering people with the skills and resources to become more competitive in the labor market is a more sustainable solution.
Another persistent challenge for the authorities in poverty alleviation is the constraint of limited financial resources. The fsQCA results from this study demonstrate that effective configurations for poverty reduction vary by region, with access to electricity emerging as a key component across all combinations. Recognizing these regional differences, this research proposes an analytical methodology for future studies to explore the unique contexts of other developing countries more deeply. Overall, while each factor for poverty reduction has merit, it is more practical to identify the effective combinations of these factors, considering their synergistic effects within specific regional contexts. By understanding and leveraging these interdependencies, the authorities can optimize resource allocation and maximize the impact of poverty reduction initiatives.

7. Conclusions

This study establishes and tests conceptual models to demonstrate how access to electricity and the socio-economic environment interact with each other and promote capability and income poverty reduction in Myanmar. The results of the structural equation modeling show that the benefit of access to electricity to reducing income poverty in Myanmar is mainly through helping the poor increase their capability of getting rid of poverty. The socio-economic environment not only directly alleviates capability and income poverty, but also mitigates income poverty by enhancing the poor’s capabilities. The results of the fsQCA further demonstrate five effective configurations of factors of access to electricity and the socio-economic environment for poverty reduction in Myanmar. This first indicates that individual factors could not make a highly effective poverty reduction and different factors need to be appropriately configured for achieving synergistic effects to reduce poverty. In addition, the absence of access to electricity serves as a necessary condition for ineffective poverty reduction, and the presence of it plays a core role in all configurations for effective poverty reduction. This finding shows that energy-dependent nations like Myanmar should prioritize expanding electricity access to combat poverty effectively.
The above findings offer substantial theoretical and practical contributions: First, this study builds conceptual models that reveal the fundamental paths from access to electricity and the socio-economic environment to capability poverty reduction and income poverty reduction, facilitating a holistic understanding of poverty reduction. Second, it uncovers diverse effective poverty reduction configurations in Myanmar, demonstrating the complementary relationship between electricity access and socio-economic factors. Third, these findings have significant practical implications for offering policymaking recommendations for efficient poverty alleviation in Myanmar as well as other developing countries.

8. Limitations and Future Research

This study recognizes the limitation of not covering all Myanmar regions in the sample size. Yet, the sample’s occupational, gender, age, and income distributions align with local official statistics, enhancing data representativeness. Future research could broaden this exploration to include both developing and developed countries, offering insights into diverse poverty reduction mechanisms. Longitudinal studies are also recommended to further track the dynamic evolution of individuals’ poverty status over time.

Author Contributions

Conceptualization, Q.X., X.Z. and W.T.; methodology, Q.X. and W.T. validation, Q.X.; formal analysis, Q.X.; investigation, Q.X., W.S., C.L., X.Z. and W.T.; data curation, X.Z., W.S., C.L. and W.T.; writing—original draft preparation, Q.X. and W.T.; writing—review and editing Q.X., C.F.D., F.K.P.H., L.Z., W.S. and W.T.; project administration, W.T. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China [grant numbers 72171128, 72201027, and 51579135] and the Fund Program of the State Key Laboratory of Hydroscience and Engineering [grant numbers 2022-KY-04].

Data Availability Statement

The data presented in this study are all available on request from the corresponding author due to legal reasons.

Acknowledgments

The authors thank the collaborators from universities in Myanmar for the arrangements during the fieldwork and all respondents for their help during the survey. In addition, we utilized ChatGPT 4.0 solely for grammar checks to ensure clarity and accuracy in the content.

Conflicts of Interest

The authors declare no conflicts of interest.

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Energies 17 05451 g001
Figure 1. Conceptual model of effects of access to electricity and socio-economic environment on capability poverty reduction and income poverty reduction.
Figure 1. Conceptual model of effects of access to electricity and socio-economic environment on capability poverty reduction and income poverty reduction.
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Figure 2. Conceptual model of interactions between factors of access to electricity and socio-economic environment.
Figure 2. Conceptual model of interactions between factors of access to electricity and socio-economic environment.
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Figure 3. Results of the structural model of effects of access to electricity and socio-economic environment on capability poverty reduction and income poverty reduction.
Figure 3. Results of the structural model of effects of access to electricity and socio-economic environment on capability poverty reduction and income poverty reduction.
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Table 1. Description of the outcomes, causal conditions, and data sources for fuzzy-set qualitative comparative analysis.
Table 1. Description of the outcomes, causal conditions, and data sources for fuzzy-set qualitative comparative analysis.
ConstructMeasuresData SourcesReferences
Poverty ReductionWealth ranking indexMIMU-HARP Vulnerability Study[75]
Access to electricityPercentage of households using electricity for lightingMyanmar Population and Housing Census[37,76]
Health InfrastructureSub-health center–population ratioTownship Health Profile[43]
Health Human ResourcesNurse–population ratioTownship Health Profile[77]
Education InfrastructureSchool–pupil ratio Education Statistical Yearbook[43,78]
Education Human ResourcesTeacher–pupil ratio Education Statistical Yearbook[79,80]
Technology DevelopmentPercentage of households with internetMyanmar Population and Housing Census[81,82]
Table 2. Measurement model evaluation.
Table 2. Measurement model evaluation.
ConstructsItemsLoadingsVIFCACRAVE
Access to electricity (AE) 0.7650.8650.681
Electricity accessibility0.842 2.908
Electricity affordability0.8813.144
Electricity stability0.748 1.215
Socio-economic Environment (SE) 0.8510.9310.870
Economic growth conditions0.931 2.212
Socio-economic stability0.935 2.212
Capability Poverty Reduction (CPR) 0.8320.8990.749
Health status0.894 2.133
Education level0.853 1.793
Access to productive activities0.848 1.930
Income Poverty Reduction (IPR) 0.8810.9260.806
Diet affordability0.927 2.999
Heating affordability0.916 2.697
Housing affordability0.848 2.087
Abbreviations: VIF, Variance Inflation Factor; CA, Cronbach’s Alpha; CR, Composite Reliability; AVE, Average Variance Extracted.
Table 3. Fornell–Larcker criterion for the measurement model.
Table 3. Fornell–Larcker criterion for the measurement model.
ConstructsAVEAECPRIPRMPR
Access to electricity (AE)0.6810.825
Capability Poverty Reduction (CPR)0.7490.251 (0.305)0.865
Income Poverty Reduction (IPR)0.8060.204 (0.240)0.753 (0.864)0.898
Socio-economic Environment (SE)0.8700.032 (0.074)0.460 (0.541)0.458 (0.528)0.933
Abbreviations: AE, access to electricity; CPR, Capability Poverty Reduction; IPR, Income Poverty Reduction; SE, Socio-economic Environment; and HTMT values are in parentheses.
Table 4. Results of direct effects and significant indirect effects among constructs.
Table 4. Results of direct effects and significant indirect effects among constructs.
Path RelationPath
Coefficient		Standard
Deviation		t-Valuep-ValueResult
CPR→ IPR0.683 ***0.0749.225<0.001Supported
AE → CPR0.252 ***0.0763.0920.002Supported
AE → IPR0.030 ns0.0730.4030.687Rejected
SE → CPR0.444 ***0.0765.992<0.001Supported
SE → IPR0.145 **0.0592.4610.014Supported
AE → CPR→ IPR0.173 ***0.0592.7240.006Supported
SE → CPR→ IPR0.303 ***0.0615.028<0.001Supported
Notes: ***, **, and ns indicate 1%, 5%, and non-significant, respectively.
Table 5. Calibration and codification for outcomes (poverty reduction) and each condition (poverty reduction factors).
Table 5. Calibration and codification for outcomes (poverty reduction) and each condition (poverty reduction factors).
ConstructsCodificationFull
Membership		Crossover
Point		Full Non-
Membership
Poverty ReductionPR2.957−1.241−4.027
Access to electricityAE0.6350.1880.050
Health InfrastructureHI0.6260.1600.064
Health Human ResourcesHHRs0.8160.1660.029
Education InfrastructureEI0.0210.0080.004
Education Human ResourcesEHRs0.0700.0380.024
Technology DevelopmentTD0.1160.0250.003
Table 6. Test of necessity for individual conditions.
Table 6. Test of necessity for individual conditions.
ConditionPR (Presence of
Poverty Reduction)		pr (Absence of
Poverty Reduction)
ConsistencyCoverageConsistencyCoverage
AE (Access to Electricity)0.789 0.895 0.463 0.501
ae0.5600.522 0.903 0.803
HI (Health Infrastructure)0.580 0.660 0.732 0.795
hi0.820 0.762 0.687 0.609
HHRs (Health Human Resources)0.640 0.762 0.581 0.660
hhr0.714 0.641 0.790 0.677
EI (Education Infrastructure)0.586 0.637 0.744 0.772
ei0.790 0.764 0.650 0.600
EHRs (Education Human Resources)0.633 0.695 0.665 0.696
ehr0.723 0.694 0.708 0.648
TD (Technology Development)0.776 0.876 0.535 0.576
td0.625 0.585 0.885 0.790
Note: Upper-case words denote the presence of the condition or outcome; lower-case words denote the absence of the condition or outcome.
Table 7. Combinations for the presence of poverty reduction.
Table 7. Combinations for the presence of poverty reduction.
ConditionCombinations
PR1PR2PR3PR4PR5
Access to Electricity (AE)Energies 17 05451 i001Energies 17 05451 i001Energies 17 05451 i001Energies 17 05451 i001Energies 17 05451 i001
Health Infrastructure (HI)Energies 17 05451 i003 Energies 17 05451 i003Energies 17 05451 i003
Health Human Resources (HHRs) Energies 17 05451 i001Energies 17 05451 i001Energies 17 05451 i001Energies 17 05451 i001
Education Infrastructure (EI)Energies 17 05451 i003Energies 17 05451 i004 Energies 17 05451 i002
Education Human Resources (EHRs) Energies 17 05451 i002Energies 17 05451 i004
Technology Development (TD)Energies 17 05451 i001Energies 17 05451 i001Energies 17 05451 i001Energies 17 05451 i004Energies 17 05451 i004
Consistency0.9600.9660.9800.9640.976
Raw coverage0.5650.4090.3430.2830.292
Unique coverage0.1800.0150.0140.0030.010
Solution consistency0.946
Solution coverage0.653
Notes: Black circles (●), presence of conditions; crossed-out circles (⊗), absence of conditions; core elements are denoted by larger circles; peripheral elements are denoted by smaller circles.
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Xiong, Q.; Shen, W.; Liu, C.; Zhang, X.; Tang, W.; Duffield, C.F.; Hui, F.K.P.; Zhang, L. Impact of Access to Electricity and Socio-Economic Environment on Poverty Reduction: An Empirical Study on Myanmar. Energies 2024, 17, 5451. https://doi.org/10.3390/en17215451

AMA Style

Xiong Q, Shen W, Liu C, Zhang X, Tang W, Duffield CF, Hui FKP, Zhang L. Impact of Access to Electricity and Socio-Economic Environment on Poverty Reduction: An Empirical Study on Myanmar. Energies. 2024; 17(21):5451. https://doi.org/10.3390/en17215451

Chicago/Turabian Style

Xiong, Qian, Wenxin Shen, Chunna Liu, Xuteng Zhang, Wenzhe Tang, Colin F. Duffield, Felix Kin Peng Hui, and Lihai Zhang. 2024. "Impact of Access to Electricity and Socio-Economic Environment on Poverty Reduction: An Empirical Study on Myanmar" Energies 17, no. 21: 5451. https://doi.org/10.3390/en17215451

APA Style

Xiong, Q., Shen, W., Liu, C., Zhang, X., Tang, W., Duffield, C. F., Hui, F. K. P., & Zhang, L. (2024). Impact of Access to Electricity and Socio-Economic Environment on Poverty Reduction: An Empirical Study on Myanmar. Energies, 17(21), 5451. https://doi.org/10.3390/en17215451

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