Socioeconomic and locational disparities in primary education completion in Burkina Faso

Primary education is foundational for national development and individual advancement, particularly in sub-Saharan Africa, where human capital remains underutilized. Despite global commitments toward universal primary education, countries like Burkina Faso face severe challenges. With one of the world’s lowest literacy rates, Burkina Faso grapples with low enrollment, poor retention and substantial gender and spatial school disparities.

These challenges are compounded by geopolitical instability, economic hardship and armed conflict, especially in the northern and eastern regions. Widespread school closures and population displacements have disrupted access to education, disproportionately affecting rural communities and exacerbating existing inequalities.

The country’s education system is further constrained by underdeveloped infrastructure and sociocultural barriers such as early marriage and child labor. Although the government – often supported by international partners – has introduced targeted programs to improve access, these efforts have struggled to overcome the combined effects of poverty, insecurity and social exclusion. Despite significant global attention, empirical research on educational disparities in Burkina Faso remains limited, especially regarding regional variations in primary school completion. Most studies depend on national averages, which mask vital differences across geographic, gender and income-based lines.

This study addresses that gap by analyzing primary education completion by region. Specifically, it aims to assess regional disparities in primary education completion rates across Burkina Faso, examine rural-urban differences, analyze how geographic location influences educational attainment and investigate the role of socioeconomic factors in shaping completion outcomes. The study seeks to inform more context-sensitive policies and planning by identifying and quantifying these disparities. The findings will be valuable for national and international stakeholders working to improve educational equity in Burkina Faso and will offer broader insights for similarly affected countries in the West African region.

Beyond the national context, the study contributes to the broader West African discourse on educational equity. Many countries in the region share structural and contextual challenges similar to those observed in Burkina Faso. As such, the study offers a valuable reference for policymakers and development actors seeking to advance universal primary education through more localized, evidence-based approaches that respond to geographic and sociocultural inequality dimensions.

Socioeconomic disparities are widely recognized as key determinants of educational outcomes globally. Numerous studies affirm that socioeconomic status (SES) profoundly affects academic achievement, with students from lower-income families facing limited access to resources, higher absenteeism and reduced educational attainment (García and Weiss, 2020; Reardon, 2011). In sub-Saharan Africa, these effects are particularly pronounced. Research by Banda et al. (2023) and Wodon et al. (2021) highlights how financial constraints in low-income households contribute to early dropout rates in contexts where public education systems are chronically underfunded.

The rural-urban divide compounds these disparities. Students in urban areas benefit from better infrastructure, access to trained teachers and learning materials, while rural learners often lack basic educational facilities (Barro and Lee, 2015; Banda and Liu, 2025; World Bank Group, 2021). Case studies in Rwanda (Ruberandinda and Mugiraneza, 2024), India (Rathee, 2024) and Nepal (Joshi et al., 2024) similarly underscore the impact of poor transportation, teacher shortages and infrastructural neglect in rural areas.

Beyond material constraints, SES also shapes student self-perceptions. Tan et al. (2023) and Banda and Liu (2025) demonstrate that students from lower SES backgrounds report lower self-efficacy, negatively influencing motivation and academic performance. This adds a psychological dimension to material inequalities, highlighting the need for multifaceted interventions.

Human Capital Theory (Becker, 1993; Schultz, 1961) offers a compelling lens to interpret these patterns, viewing education as an investment in economic productivity. The theory suggests that students from disadvantaged backgrounds are less likely to complete school due to an inability to invest in education, thereby perpetuating poverty. The observed gender differences – where boys show slightly lower completion rates – may also reflect social norms and labor expectations that divert boys from school, impacting their long-term human capital development (Psacharopoulos and Patrinos, 2018). Similarly, the disparities between rural and urban areas align with Human Capital Theory’s emphasis on the role of the environment in shaping educational investment and returns.

Gupta (2024), drawing from Bourdieu’s theory of cultural capital and social reproduction theory, emphasizes that higher SES confers educational advantages through institutional familiarity and access to cultural knowledge. These mechanisms reinforce intergenerational inequality and deepen the divide between socioeconomic groups.

International comparisons further contextualize Burkina Faso’s challenges. Despite the Sarva Shiksha Abhiyan program in India, rural regions still face severe infrastructural and teacher shortages (De et al., 2011). Brazil’s Bolsa Família has shown the promise of conditional cash transfers in improving school attendance (Soares et al., 2010), while Kenya’s Free Primary Education FPE) policy illustrates the risks of rapid expansion without quality safeguards (Chimombo, 2005; Oketch and Rolleston, 2007). In the USA, persistent rural-urban educational gaps mirror issues seen in Burkina Faso (Showalter et al., 2015), whereas Finland’s model demonstrates how equal investment across regions can minimize disparities (Sahlberg, 2015).

Despite this rich literature, a notable gap remains in studies that address Burkina Faso’s unique sociopolitical context. Much of the existing research relies on generalized global or regional data sets – such as those from the World Bank, OECD and UNICEF – which, though valuable, often lack interpretative depth without localized analysis. These data sets fail to fully capture the intersection of insecurity, economic instability and political upheaval affecting education in Burkina Faso. Consequently, the interaction between gender, location and SES within the country’s evolving crisis remains underexplored.

This study addresses that gap by analyzing regional and locational disparities in primary education completion in Burkina Faso, interpreting complex socioeconomic and political realities through a locally informed lens. It aims to generate context-sensitive evidence to guide education policy and resource allocation in one of the region’s most fragile states.

This study adopts a quantitative, non-experimental design to explore regional disparities in primary education completion in Burkina Faso. Relying on secondary data drawn from nationally representative surveys, the analysis is structured to identify statistical associations between primary school completion and a range of individual-, household- and contextual-level variables. The central aim is to uncover spatial patterns of educational attainment and assess how structural and demographic factors contribute to observed inequalities across the country.

The data used in this study were obtained from publicly available repositories compiled by international agencies. These repositories aggregate household-level survey data from multiple years, enabling cross-sectional and temporal analyses. Following data cleaning, the analytical sample was restricted to observations with complete records on the primary outcome variable – primary education completion – and key covariates such as gender, location and socioeconomic indicators. Observations with missing data on critical variables were excluded through listwise deletion to maintain the integrity of multivariate analyses. Details about data preprocessing are in the supplementary file 1, while the data set used in this analysis was derived from an extensive public database shared by Datocms at: www.datocms-assets.com/41369/1699460825-wide_2023_sept.csv

A three-tiered statistical approach was adopted. First, descriptive statistics were used to summarize key variables and illustrate disparities in primary school completion rates by region, gender and urban-rural location. This also involved creating regional maps and temporal line graphs to capture spatial and temporal trends visually.

Second, binary logistic regression was applied to estimate the likelihood of primary school completion as a function of individual and household characteristics. This technique is suitable for modeling dichotomous outcomes and enables the estimation of marginal effects while adjusting for confounding covariates.

A Hierarchical Linear Model (HLM) was used to examine the multilevel structure of educational disparities. The data set exhibits a nested structure, with individual observations (students or household-level entries) grouped within administrative regions. Such clustering introduces the potential for intra-class correlation, violating the independence assumption of ordinary least squares regression. HLM is well-suited for this context as it accounts for individual-level (Level 1) and region-level (Level 2) variance. The model enables the decomposition of the total variance in primary education completion rates into within-region and between-region components, thereby identifying the extent to which contextual factors contribute to disparities in outcomes. This approach allows for a more accurate estimation of fixed effects while simultaneously modeling unobserved heterogeneity across regions. Including a random intercept for region captures systematic differences in completion rates attributable to regional contexts, such as infrastructure, policy implementation or social environment. This model captures intra-regional outcome variation while controlling for inter-regional differences in unobserved characteristics.

These statistical techniques are methodologically appropriate given the research objectives and structure of the data. However, it is acknowledged that, due to the observational nature of the data set and the absence of strong exogenous instruments, causal inferences cannot be firmly established. Consequently, all associations are interpreted descriptively, not causally. The findings are presented as statistical relationships, with consideration given to the potential for omitted variable bias and unmeasured confounding.

Table 1 presents the variables and analytical models used for the statistical analyses.

Given the nested structure of the data – individuals within regions – we used a two-level HLM to estimate the effect of urban residence on education completion, controlling for fixed effects of gender and income and random intercepts at the regional level:

where P_ij is the probability of completion for individual i in region j, and u_j ∼ N(0, σ_u²) captures unobserved regional heterogeneity.

We used logistic regression to estimate associations between primary completion and individual-level characteristics:

Given the absence of an exogenous instrument or natural experiment, these estimates are interpreted as associational rather than causal. Potential omitted variables – such as parental education or school quality – may confound the relationships observed.

To examine rural-urban differences while controlling for confounding variables, we applied nearest-neighbor propensity score matching (PSM) using gender and income as covariates. The average treatment effect on the treated compares matched urban and rural students with similar characteristics. Although this reduces observable bias, unobserved confounders may remain, limiting causal inference.

The analysis of primary education completion rates in Burkina Faso was conducted using a series of statistical techniques, each carefully chosen to address specific research objectives and ensure the robustness of the findings. The methodologies employed were meticulously selected to examine the regional disparities in education outcomes, assess the influence of socioeconomic factors and understand the impact of rural-urban locations on primary education completion rates.

All statistical analyses in this study were conducted using the R, selected for its robust capabilities in handling complex multilevel models, PSM and various other statistical tests essential for this study.

Furthermore, this study uses external qualitative and contextual sources to enhance the interpretation of statistical results and address the limitations inherent in observational quantitative research. These sources include reports from development agencies, policy documents and peer-reviewed studies that offer relevant narratives and institutional background on regional education systems, public investment patterns and sociopolitical dynamics in Burkina Faso. These insights were selectively integrated to provide explanatory depth and policy relevance. This mixed-inference strategy is commonly used in applied policy research, particularly in low-resource contexts, to bridge the gap between statistical trends and the lived realities they represent.

Since this study used secondary data, ethical clearance was addressed by ensuring adherence to the ethical guidelines associated with using pre-existing data sets. The data, which was anonymized and aggregated, posed a minimal risk of identifying individual subjects. The research was conducted following the terms and conditions set by the original data collectors, and proper citation of the data source was maintained. Given these considerations, the study did not require additional ethical clearance from an institutional review board.

Table 2 presents descriptive statistics on primary education completion rates, disaggregated by gender and residential location. The data reveal pronounced disparities both by gender and by urban-rural setting.

Among female students, urban students report a markedly higher mean completion rate (⁠$x¯$ = 0.488, SD = 0.084) than those in rural areas (⁠$x¯$ = 0.182, SD = 0.140). The larger standard deviation in the rural subgroup suggests greater variability in completion outcomes across rural localities. Completion rates among rural females range from as low as 3.2% to 50.7%, while the urban female range is narrower (35.4% to 56.6%).

Male students’ average completion rate in urban settings is also higher (⁠$x¯$ = 0.617, SD = 0.132) than in rural settings (⁠$x¯$ = 0.252, SD = 0.156). Again, rural male outcomes show broader dispersion (10.4% to 69.3%), indicating uneven access or attainment within that category. Urban males exhibit the highest observed completion rate in the data set (78.1%).

These descriptive patterns point to consistent urban advantages and highlight gender and locational inequalities in primary education outcomes.

Statistical data demonstrates considerable differences in educational achievements between rural and urban areas, as urban populations typically achieve better completion results for both male and female students. Figure 1 is the map of Burkina Faso illustrating the spatial differences in the completion rates between the rural and the urban, denoted by color intensities. This choropleth map visualizes the geographic variation in average primary education completion rates across administrative regions. Darker shades represent higher regional completion rates, while lighter shades indicate lower attainment.

A descriptive temporal trend analysis was conducted to examine the evolution of disparities in primary education completion across Burkina Faso. The aim was to assess how average completion rates have varied across administrative regions, thereby identifying improvement patterns or persistent inequality.

The data set was filtered to retain observations with non-missing values for year, region and completion rate. A total of 27 region-year combinations were retained for analysis. Mean completion rates were computed by region and survey year. This analysis was descriptive and did not involve hypothesis testing. No inferential statistics were computed, and all estimates reflect sample means stratified by region and time. Refer to Figure 2 for this illustration.

Figure 2 Temporal trends in average primary education completion rates across regions in Burkina Faso. It displays region-level changes in mean completion rates over time based on available survey years. While some regions exhibit modest improvements, others – particularly in the northern and eastern parts of the country – consistently lag, reflecting persistent spatial disparities in educational attainment. This line graph illustrates changes in mean primary education completion rates across Burkina Faso’s administrative regions over selected survey years. Regional disparities are evident, with some regions (e.g. Centre and Ouagadougou) consistently exhibiting higher completion rates, while others (e.g. Sahel and Est) show persistently lower completion levels despite gradual improvements.

The results revealed notable variations in trajectories across regions. For instance, regions such as Cascades and Centre Est showed moderate improvement over time, whereas others, including Sahel and Centre Nord, exhibited persistently lower completion rates with minimal temporal gains. These findings highlight spatial inequalities in educational attainment and underscore the importance of region-sensitive policy interventions.

Table 3 presents the logistic regression model results estimating the likelihood of completing primary education, with urban residence as the key independent variable. The binary outcome variable indicates whether a student has completed primary education.

The model yielded a statistically significant intercept (β = 0.812, SE = 0.055, z = 14.665, p < 0.001), representing the baseline log-odds of completion for rural male students from low-income households. The coefficient for urban residence was also statistically significant (β = 0.102, SE = 0.002, z = 51.850, p < 0.001, 95% CI [0.098, 0.105]). When exponentiated, this corresponds to an odds ratio (OR) of 1.107 (95% CI [1.103, 1.111]), indicating that students in urban areas had approximately 10.7% higher odds of completing primary education than their rural counterparts, controlling for other variables in the model. Although the magnitude of the coefficient appears small in raw log odds, the tight confidence interval reflects the precision and robustness of the estimated effect.

Fixed Effects of Socioeconomic and Location Variables on Primary Education Completion Rates.

Table 4 presents the fixed-effects estimates from the multilevel logistic regression model predicting the likelihood of primary education completion. The binary outcome variable indicates whether an individual has completed primary education. The model includes an intercept and one key explanatory variable: residential location.

The intercept is estimated at 0.812 with a standard error of 0.055, yielding a z-value of 14.665 and a p-value < 0.001. This coefficient represents the log odds of completing primary education for individuals in the reference category – i.e. those residing in rural areas – assuming all other variables are constant. While the intercept itself is not the primary focus of the analysis, it serves as the baseline from which the effect of urban residence is measured.

The coefficient for urban location is 0.102 (SE = 0.002), with a z-value of 51.850 and a p-value < 0.001. This indicates a statistically significant positive association between urban residence and primary education completion. Specifically, the log odds of completion are higher for individuals living in urban areas than those in rural settings. The 95% confidence interval for this effect, ranging from 0.098–0.105, is both narrow and well above zero, confirming the robustness and precision of the association.

While the coefficient magnitude (0.102) is modest on the log-odds scale, its statistical significance and narrow confidence interval indicate a consistent relationship between urban location and higher educational attainment. This finding complements the earlier descriptive statistics, which showed consistently higher average completion rates in urban areas for both male and female students. Overall, the fixed-effects results underscore the role of geographic residence as a salient correlate of educational attainment in Burkina Faso, warranting further investigation into the structural and contextual factors that differentiate urban and rural education outcomes.

In addition to examining individual-level predictors of primary education completion, the model incorporated a random intercept at the regional level to assess whether unobserved contextual differences across administrative regions contribute to outcome variability. This approach allows the analysis to distinguish between within-region effects – attributable to individual or household characteristics – and between-region differences that may reflect broader structural or institutional factors.

Table 5 reports the variance component from the random intercepts model, where observations are nested within administrative regions. The variance attributable to differences across regions is estimated at 0.021, corresponding to a standard deviation of 0.074.

This result indicates non-negligible variation in primary education completion rates across regions, even after controlling for individual-level fixed effects. Although the magnitude is modest, regional-level variance justifies using a multilevel modeling approach to account for the hierarchical structure of the data appropriately. The findings suggest that region-specific contextual factors are associated with differences in educational outcomes beyond what is explained by individual or household characteristics.

This association reinforces descriptive patterns observed earlier in the analysis and highlights the importance of considering geographic context when examining disparities in primary education attainment.

Although a multilevel model was initially considered to account for clustering observations within regions, the estimated variance component (0.021) indicated minimal between-region variability. As such, a single-level logistic regression model was adopted for the primary analysis, with region-level influences accounted for through fixed effects or relevant covariates. This approach improves model parsimony while capturing the most substantial sources of variation in primary education completion.

Table 6 presents the results of the PSM analysis, which was conducted to estimate the association between residential location (urban vs rural) and primary education completion while adjusting for differences in socioeconomic backgrounds. Matching was performed using relevant covariates to ensure comparability between the rural and urban subpopulations.

The mean completion rate among students in urban areas was 0.8715, compared to 0.8731 among their matched rural counterparts. This results in a mean difference of −0.0016, indicating that after adjusting for observable covariates, rural students in the matched sample exhibit a slightly higher average completion rate than urban students. However, the difference is minimal and statistically negligible, especially when considered alongside the standard deviation of the difference (0.1060), which reflects some dispersion across matched pairs.

The analysis was based on 8,512 matched pairs, providing a substantial sample size for assessing the balance between the treatment and control units. The near-zero difference in completion rates post-matching suggests that, once socioeconomic and demographic factors are accounted for, residential location alone may not strongly correlate with completion outcomes in this matched subsample.

These results complement earlier regression findings by illustrating that differences in underlying household and individual characteristics may primarily explain the apparent urban advantage in completion rates observed in raw data. These findings reveal important statistical associations that may inform policy decisions to address the individual-based factors contributing to educational disparities.

The findings of this study offer a comprehensive understanding of the educational disparities in Burkina Faso, emphasizing the significant roles of SES and rural-urban location in determining primary education completion rates. These results align with global patterns observed in various contexts and highlight unique challenges within Burkina Faso that require targeted interventions. A comparative and contrastive analysis with case studies from other countries further enriches our understanding and emphasizes the need for context-specific solutions.

This study presents robust empirical evidence regarding the factors associated with primary education completion in Burkina Faso, integrating individual-level predictors with structural and contextual considerations. The logistic regression analysis indicates that urban residence is a statistically significant predictor of completion. Students living in urban areas have approximately 1.107 times higher odds of completing primary education compared to their rural counterparts (OR = 1.107, 95% CI [1.103, 1.111], p < 0.001) while controlling for gender and household income. The intercept term (β = 0.812, SE = 0.055, z = 14.665, p < 0.001) reflects the baseline log-odds of completion for rural male students from low-income households. Although the magnitude of the coefficient for urban residence may seem modest in raw log-odds terms, its narrow confidence interval and high statistical significance emphasize a robust and persistent spatial disparity in educational attainment.

These findings align with the human capital theory (Becker, 1964), which conceptualizes education as a strategic investment in personal and societal advancement. The urban advantage observed is not merely a geographic artifact but reflects underlying structural inequalities in infrastructure, service delivery and governance. Urban areas are more likely to benefit from proximity to schools, trained teachers, educational materials and administrative support (World Bank Group, 2021; UNDP, 2023), while rural settings suffer from thin resource distribution and weaker institutional presence. These disparities are further entrenched in areas affected by insecurity, particularly the northern and eastern regions, where armed conflict has resulted in widespread school closures and displacement of learners and educators (UNICEF, 2022).

This urban-rural divide echoes patterns observed in other developing countries. In Kenya, urban learners have historically outperformed their rural counterparts due to access to better school facilities, well-trained teachers and parental support, as demonstrated by Oketch and Rolleston (2007). Similarly, in Brazil, socioeconomic segregation in urban centers led to marked disparities in learning outcomes and completion rates, disproportionately affecting children from the poorest urban favelas. These comparative insights reinforce the understanding that spatial disparities often serve as a proxy for compounded economic and institutional disadvantage.

The descriptive statistics further highlight the stratification of outcomes. Rural females recorded the lowest mean completion rates (⁠$x¯$ = 0.182) compared to urban males (⁠$x¯$ = 0.617), revealing stark disparities shaped by intersecting gender and spatial disadvantages. This pattern reflects Bourdieu’s social reproduction theory (as cited in Gupta, 2024), whereby existing social hierarchies and inherited disadvantages constrain access to education. These gaps persist despite national policies aimed at gender parity, suggesting that policy design has yet to penetrate deeply embedded sociocultural norms and economic pressures that discourage school retention for girls, particularly in rural and conflict-prone areas.

Though the multilevel model revealed a modest regional variance component (σ² = 0.021), the finding remains analytically significant. It implies that while most variations in primary education completion occur at the individual level, regional contexts still exert a non-negligible influence. This affirms the rationale for incorporating HLM, consistent with DiPrete and Forristal (1994) and Goldstein (2003), who argue for multilevel analysis when micro and macro factors shape educational outcomes. Reports from conflict-affected provinces (e.g. Centre-Nord, Sahel) indicate chronic teacher shortages, compromised infrastructure and constrained access due to security checkpoints and displacement (UNICEF, 2022). Comparable dynamics have been observed in regions of Northern Nigeria where security-related school closures have similarly disrupted educational access, compounding pre-existing regional inequalities.

PSM results lend further insight into the mechanisms underlying urban-rural disparities. After matching students on gender and household income, the rural-urban completion gap becomes negligible (mean difference = –0.0016). This suggests that spatial disparities are primarily mediated by underlying socioeconomic inequalities rather than location per se. Such findings are congruent with prior research from similar contexts, such as in India, where De et al. (2011) showed that controlling for household wealth and proximity to schools significantly attenuates observed geographic gaps in education completion. In South Africa, VA der Berg (2008) similarly found that when controlling for socioeconomic factors, much of the schooling disadvantage attributed to race or region dissipated, suggesting that structural inequality, not identity or place, drives disparities.

Interestingly, gender was not statistically significant in the logistic model when controlling for other factors, but this should not be misinterpreted as evidence of gender equality. Instead, it reflects a statistical adjustment for variables that are themselves deeply gendered in real-world contexts. Qualitative insights from field reports reveal that girls, especially in rural and conflict-affected areas, face considerable obstacles, including early marriage, domestic responsibilities and exposure to violence or harassment en route to school (WG_HHS_2, 2021; UNICEF, 2022). These burdens are often invisible in quantitative models yet profoundly shape educational trajectories. Comparable evidence from Niger and Mali also points to entrenched gender norms and household labor expectations as key barriers to girls’ schooling (UNESCO, 2020), reinforcing the need to interpret statistical insignificance through a lens of lived experience.

Temporal trends illustrated in Figure 2 demonstrate regional improvements in completion rates across certain provinces, likely reflecting the effects of targeted policy reforms and donor interventions. However, the gains remain uneven and fragile, particularly in areas experiencing persistent insecurity or governance instability. This emphasizes the importance of policy continuity and localized implementation, which aligns with Sahlberg’s (2015) assertion that sustainable education reform necessitates political commitment and contextual sensitivity.

These findings confirm that completing primary education in Burkina Faso is a multidimensional issue shaped by intersecting individual, household and regional factors. Integrating empirical analysis with contextual and theoretical insights highlights the inadequacy of one-size-fits-all interventions. Instead, the study advocates for a differentiated policy approach that combines household-level support (e.g. cash transfers, conditional subsidies), community-level engagement and macro-level investments in infrastructure and teacher deployment. Only through such multi-layered responses can Burkina Faso progress toward equitable and resilient education outcomes.

The findings of this study have significant implications for educational policy and practice in Burkina Faso. Addressing the socioeconomic and locational disparities in primary education completion rates requires a multifaceted approach that draws on lessons from successful and challenging case studies worldwide.

First, implementing conditional cash transfer programs similar to Brazil’s Bolsa Família could provide financial incentives for families to keep their children in school. Conditional cash transfers would likely be most effective if explicitly directed at rural, low-income households with the most pronounced economic barriers to education. The findings highlight that economic hardship is a significant deterrent to school completion, and therefore, such transfers could mitigate the opportunity cost of schooling, particularly for families in rural regions. This targeted intervention could help reduce school dropout rates by providing economic incentives that directly address the financial pressures on families.

However, as shown by the challenges faced in Kenya’s FPE policy (Chimombo, 2005; Oketch and Rolleston, 2007), expanding access without improving quality and infrastructure could exacerbate existing problems. Therefore, any such program in Burkina Faso must be accompanied by investments in educational quality, particularly in under-resourced rural areas.

Finally, closing the rural-urban educational gap in Burkina Faso will require substantial investments in rural infrastructure, teacher training and resource allocation. Drawing on Finland’s model of equitable education (Sahlberg, 2015) and adapting it to Burkina Faso’s context could help achieve more balanced educational outcomes across the country. Infrastructure improvements should focus not only on building schools but also on creating inclusive educational environments. The study reveals that regional access to education is restricted by physical and socioeconomic factors, particularly in rural areas where transportation and access to schools are major obstacles. Infrastructure improvements, therefore, should be coupled with community-based strategies to engage local populations in education-related initiatives and address cultural barriers that affect educational participation, especially for girls. However, this will require financial resources, strong political commitment and community engagement.

In conclusion, this study underscores the urgent need for targeted policy interventions that address the specific barriers faced by low-income and rural populations in Burkina Faso. By learning from the successes and challenges of other countries, Burkina Faso can develop and implement strategies that promote more equitable educational outcomes for all students, regardless of their SES or geographic location.

The findings of this study provide a comprehensive understanding of the factors influencing primary education completion in Burkina Faso, which are deeply rooted in the theoretical framework of human capital theory and corroborated by extensive literature. The significant impact of SES, gender and locational factors on educational outcomes underscores the critical need for targeted interventions that promote equitable access to education. Addressing these disparities is essential not only for the individual economic potential of students but also for the broader socioeconomic development of Burkina Faso. As the literature suggests, improving educational outcomes through strategic investment in human capital is a crucial pathway to breaking the cycle of poverty and fostering sustainable development in the region.

The findings of this study underscore significant regional disparities in primary education completion rates in Burkina Faso, primarily influenced by the urban-rural divide. The analysis reveals that urban areas generally have higher completion rates than rural regions. This suggests that a substantial portion of the disparities in education outcomes can be attributed to geographical location, with urban students benefiting from better access to educational resources, infrastructure and qualified teachers. These findings highlight the need for targeted educational interventions in rural areas to improve access to and quality education. Such interventions should include strategies for better resource allocation, enhanced teacher training and infrastructure development tailored to the unique challenges faced by rural communities.

By comparing Burkina Faso’s educational challenges with those in India, Brazil, the USA, Finland and Kenya, we gain a broader perspective on how different countries address rural-urban educational disparities. These comparisons underscore the need for comprehensive strategies beyond mere access to education, focusing on improving the quality of education and addressing the socioeconomic barriers that disproportionately affect rural students. Lessons from these case studies suggest that Burkina Faso could benefit from targeted interventions that combine increased investment in rural educational infrastructure with economic support mechanisms, aiming for a more equitable distribution of educational opportunities across the country.

This study offers valuable insights for policymakers and educational planners by providing a clear understanding of how regional and locational disparities impact primary education completion in Burkina Faso. Addressing these disparities is essential for promoting equitable educational outcomes and supporting the broader goal of national development.

While this study offers important insights, it is not without limitations. The reliance on secondary data constrains the ability to capture real-time changes and nuances in educational conditions, particularly in a rapidly evolving socio-political environment like Burkina Faso. Additionally, the study’s focus on primary education completion rates may overlook other critical aspects of educational quality and student learning outcomes, which are equally important in assessing the overall effectiveness of the educational system.

Future research could explore the impact of ongoing security challenges on education in Burkina Faso, mainly how conflict and displacement affect student retention and learning outcomes in rural and urban areas. This research could involve qualitative methods to provide a more nuanced understanding of the barriers to education in conflict-affected regions, thereby informing more effective and context-specific interventions.

The study did not receive any funding. The author has no conflict of interest in this study. The study acknowledges the source of the data for making it available online.

The supplementary material for this article can be found online.