Determinants of inequalities in welfare among households in Ethiopia: A comparative study of urban and rural Ethiopia

Sherka, Tsegamariam Dula; Yasin, Jemil; Meseret, Haymanot; Seyoum, Abrham Article Determinants of inequalities in welfare among households in Ethiopia: A comparative study of urban and rural Ethiopia Cogent Economics & Finance Provided in Cooperation with: Taylor & Francis Group Suggested Citation: Sherka, Tsegamariam Dula; Yasin, Jemil; Meseret, Haymanot; Seyoum, Abrham (2023) : Determinants of inequalities in welfare among households in Ethiopia: A comparative study of urban and rural Ethiopia, Cogent Economics & Finance, ISSN 2332-2039, Taylor & Francis, Abingdon, Vol. 11, Iss. 2, pp. 1-17, https://doi.org/10.1080/23322039.2023.2290371 This Version is available at: https://hdl.handle.net/10419/304289 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Cogent Economics & Finance ISSN: (Print) (Online) Journal homepage: www.tandfonline.com/journals/oaef20 Determinants of inequalities in welfare among households in Ethiopia: A comparative study of urban and rural Ethiopia Tsegamariam Dula, Jemil Yasin, Haymanot Meseret & Abrham Seyoum To cite this article: Tsegamariam Dula, Jemil Yasin, Haymanot Meseret & Abrham Seyoum (2023) Determinants of inequalities in welfare among households in Ethiopia: A comparative study of urban and rural Ethiopia, Cogent Economics & Finance, 11:2, 2290371, DOI: 10.1080/23322039.2023.2290371 To link to this article: https://doi.org/10.1080/23322039.2023.2290371 © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. Published online: 06 Dec 2023. Submit your article to this journal Article views: 1001 View related articles View Crossmark data Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=oaef20 DEVELOPMENT ECONOMICS | RESEARCH ARTICLE Determinants of inequalities in welfare among households in Ethiopia: A comparative study of urban and rural Ethiopia Tsegamariam Dula 1 *, Jemil Yasin 1 , Haymanot Meseret 2 and Abrham Seyoum 2 Abstract: This study aims to investigate welfare inequality between households in rural and urban Ethiopia using secondary data obtained from the Living Standards Measurement Surveys (LSMS) available on the World Bank website. The data was analyzed using the Atkinson Index to identify welfare inequality among households and quantile regression to identify determinants of welfare inequality in rural and urban Ethiopia. The results show that the Atkinson index for the rural group is 0.123006, while it is 0.110899 for the urban group, indicating a higher level of welfare inequality in rural areas. Furthermore, the quantile regression analysis reveals that among the factors measured, the number of assets, access to health services, and saving are important determinants of welfare inequality in rural households. On the other hand, the number of livestock and household size are found to be significant factors contributing to welfare inequality in urban areas. This study provides valuable insights into the specific drivers of welfare inequality in both Tsegamariam Dula ABOUT THE AUTHORS Tsegamariam Dula is an accomplished academic and researcher, currently serving as a lecturer and researcher at Wolkite University in Ethiopia. He is A development Studies Specialist. He is also a PhD Candidate in development studies at Addis Abeba University. His research interests are wideranging, but he has a particular focus on issues related to development studies, livelihood security, Inequality, food security, agricultural economics, natural resource management, agricultural extension, and climate-smart agriculture. Jemil Yasin is a Development Studies Specialist and PhD Candidate at Addis Abeba University. His research interests are food security, Poverty reduction, and agricultural extension. Haymanot Meseret is a Ph.D. candidate at the Center for Rural Development Studies, Addis Ababa University. Abraham Seyoum (Ph.D.) is an Associate Professor at the Center for Rural Development Studies, Addis Ababa University. PUBLIC INTEREST STATEMENT This study explores the differences in welfare between urban and rural households in Ethiopia. It reveals a higher level of welfare inequality among rural families, indicating they have fewer resources and services compared to their urban counterparts. The study identifies factors contributing to such disparities, like assets and access to health services in rural areas, and livestock and household size in urban regions. The findings can help officials understand what drives these inequalities, and formulate strategies to bridge this gap. The aim is to boost economic development and social equality across the nation. This research adds to our understanding of the persistent economic imbalances between rural and urban areas not only in Ethiopia but potentially in other developing countries as well. Dula et al., Cogent Economics & Finance (2023), 11: 2290371 https://doi.org/10.1080/23322039.2023.2290371 Page 1 of 17 Received: 10 July 2023 Accepted: 28 November 2023 *Corresponding author: Tsegamariam Dula, Center for Rural Development, Addis Abeba University, Addis Abeba, Ethiopia E-mail: [email protected] Reviewing editor: Walid Mensi, Sultan Qaboos University College of Economics and Political Science, Oman Additional information is available at the end of the article © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. rural and urban settings and can inform policymakers on how to address these inequalities to promote social and economic development in Ethiopia. Subjects: Development Studies; Development Policy; Rural Development; Urban Development; Economics and Development; Sustainable Development; Economics Keywords: Atkinson Index; Ethiopia; inequality; Lorentz curve; quantile regression; social and economic development; rural and urban; welfare 1. Introduction Both academic and policy circles have recently shown an increasing interest in the subject of inequality. The concept of inequality is complex as it encompasses various dimensions, including income, wealth, welfare, access to resources and opportunities, and distribution of public goods and services. Knowing the factors that contribute to inequalities in well-being among households is a crucial prerequisite for formulating and executing effective strategies aimed at mitigating the gap between the wealthy and the poor (World Bank, 2016). Worldwide, inequality has been accordingly acknowledged as a major obstacle to accomplishing the United Nations’ Sustainable Development Goals (SDGs), particularly Goal 10, which mandates the reduction of inequalities within and among nations. Therefore, there is a growing focus on understanding the underlying factors contributing to disparities in welfare among households on a national and global scale (United Nations, 2015). Ethiopia has undergone rapid economic growth and a transition from an agrarian-based economy to a more diversified, urban-centric growth model. Despite the impressive economic growth over the past two decades, a significant gap exists between urban and rural households in terms of welfare outcomes. Generally, urban areas have superior access to basic services, education, healthcare, and employment opportunities. This information is according to the World Bank’s report in 2015. National policy frameworks in Ethiopia have attempted to address inequality through a range of poverty alleviation and social protection programs. The Ethiopian government implemented the Growth and Transformation Plan (GTP) between 2010 and 2015, which aimed to achieve broad-based economic growth and reduce poverty by focusing on human development, infrastructure development, and good governance (Muleta & Belete, 2017). Despite these efforts, regional disparities persist, and understanding the factors that drive these disparities has become vital for planning effective policy interventions. A substantial body of literature exists on the determinants of inequalities in welfare among households, which has identified factors such as income, education, access to basic services, employment opportunities, social safety nets, and demographic factors as significant determinants of welfare disparities between households (Alemu et al., 2018; Korzeniewicz & Moran, 2018). Moreover, the significant influence of geography as a determinant of welfare has been duly acknowledged, with a discernible spatial dimension to inequality, primarily resulting from disparities in access to natural resources, infrastructure, and public services between the urban and rural areas (Dorosh & Schmidt, 2010). This research endeavors to make a valuable contribution to the existing literature by analyzing the determinants of inequalities in welfare among households in Ethiopia, with a specific focus on comparing the urban and rural areas. The comparative analysis seeks to discern the pivotal factors driving welfare disparities between urban and rural households and to provide insights into potential policy interventions that could potentially bridge the gap. Through its emphasis on the Ethiopian context, the study is further enhancing the global understanding of the factors underlying inequality, thereby enriching debates on the global and national development agenda and policy frameworks pertinent to the issue of welfare inequality. The severity and scope of inequality are evident in various critical indicators such as income, health, education, and access to basic services. As per the World Bank (2017), approximately 22% of Ethiopians still live below the poverty line. The Gini coefficient scaled from 0.30 in 1995 to 0.40 in Dula et al., Cogent Economics & Finance (2023), 11: 2290371 https://doi.org/10.1080/23322039.2023.2290371 Page 2 of 17 2011, reflecting the development in inequality within the nation. The Gini coefficient measures income inequality on a scale of 0 (perfect equality) to 1 (highest inequality) (The World Bank, 2017). The Urban-Rural Divide in Ethiopia’s Human Development Index (HDI) was also reported by the United Nations Development Programme (UNDP) in 2015 to be 0.585 and 0.293, respectively (UNDP, 2015). These disparities extend beyond income and wealth and are also evident in access to healthcare and education, thereby perpetuating the cycle of poverty and inequality. Previous research has predominantly focused on individual determinants of welfare in Ethiopia, and limited comparative perspectives have been adopted. For example, Woldehanna et al. (2005) analyzed the role of education and public investment in determining welfare; Dercon and Krishnan (2000) examined the impact of droughts and macroeconomic shocks on rural livelihoods, while Ravallion and Wodon (2000) studied the influence of food prices on poverty dynamics. Although these studies provide critical insights, they do not integrate all the essential determinants of welfare inequalities between urban and rural households, leaving a significant research gap. Therefore, the objective of this research was to carry out a comprehensive comparative analysis of the factors causing welfare inequalities among urban and rural households in Ethiopia. The study is intended to aid understanding of the extent and nature of the contributing factors of welfare inequality among households in rural and urban Ethiopia. The study’s contribution lies in adding value to the existing literature on the subject and offering substantial support to policymakers, development practitioners, and local communities in Ethiopia, by providing them with educated direction on improving equity and inclusivity in their development processes. 2. Literature review 2.1. Concept and theory Welfare inequality refers to inequality among households relate to the uneven allocation of resources, opportunities, and socio-economic prosperity within families and individuals across the nation. This subject place emphasis on the diversities of living circumstances, resource and service accessibility, and overall quality of life among diverse households, primarily based on the differences between urban and rural areas. The fundamental theory driving this inquiry is that various determinants impact the inequalities in welfare among households. Some of the crucial factors encompass geographical location (urban vs. rural), poverty, resource and service accessibility, educational attainment, and employment prospects. Examining these determinants will be advantageous in understanding the underlying reasons for the observed inequalities. Several studies have highlighted that poverty, educational attainment, and resource access are the principal factors affecting households’ welfare (Mossie & Demissie, 2020). By examining these determinants, policymakers can devise strategies and interventions aimed at reducing inequalities, improving households’ welfare, and fostering more inclusive and equitable development. Various theories and viewpoints may aid in comprehending the origins and outcomes of these disparities, encompassing factors like the allocation of wealth and more holistic dimensions of prosperity, such as competencies and availability of fundamental amenities. For instance, The Capability Approach, an intellectual framework pioneered by Amartya Sen, centers on the notion of robust freedoms and capabilities that a household possesses to experience an optimal standard of living. The analysis of inequality in welfare is predicated on an evaluation of varying capabilities that different households hold, encompassing their entitlements to education, healthcare, political engagement, and others. 2.2. Empirical review 2.2.1. Determinates of inequality in welfare The investigation of disparities in welfare among households in Ethiopia is a crucial initial step in comprehending the socio-economic differences and developing effective policies for poverty Dula et al., Cogent Economics & Finance (2023), 11: 2290371 https://doi.org/10.1080/23322039.2023.2290371 Page 3 of 17 alleviation. Numerous empirical studies have been conducted regarding this matter, specifically concentrating on the determinants of inequalities between urban and rural areas. These determinants comprise income, consumption, education, gender, accessibility of services and other factors that impact the well-being of households. Income is one of the principal determinants of welfare inequalities. In Ethiopia, the income inequality between urban and rural regions is considerable (World Bank, 2015). As per the Central Statistical Agency of Ethiopia (2016), the average annual per capita income in the country was $797 for urban households and merely $291 for rural households. This substantial disparity can be attributed to the differences in access to and quality of education and employment opportunities between the two regions. Access to education is another significant determinant of welfare inequalities in Ethiopia. Studies have revealed that individuals with higher levels of education are more likely to have higher incomes and better access to resources (Beyene & Mekonnen, 2014). Educational attainment is also essential in providing individuals with relevant skills and knowledge that are necessary for sustaining livelihoods and enhancing the well-being of households (Girma & Genebo, 2014). However, access to education in rural areas of Ethiopia is limited compared to urban areas. A study by Assefa and Letamo (2019) discovered that urban households had better access to primary, secondary, and tertiary education than their rural counterparts. Gender is another factor that contributes to welfare inequalities in Ethiopia. Research has shown that women experience more considerable income inequality than men due to limited opportunities for education and employment (World Bank, 2015). In addition, the accessibility of services, such as healthcare, water, sanitation, and electricity, plays a crucial role in determining welfare inequalities. According to research, urban households tend to have better access to these services than their rural counterparts (Alemu, 2011). For instance, the Ethiopian Demographic and Health Survey (EDHS) of 2016 found that just 57% of rural households have access to improved sources of drinking water, compared to 83% of urban households (Central Statistical Agency CSA & ICF, 2016). Last but not least, it’s serious to remember that Ethiopia’s agricultural sector is essential for household welfare, especially in rural areas where the majority of the population works in agriculture (United Nations Development Programme UNDP, 2014). Several factors, such as access to land, technology, credit, and extension services, can impact the welfare of agricultural households. Studies have shown that addressing these factors can significantly improve the welfare of agricultural households (Dercon & Krishnan, 2000). In conclusion, the literature has highlighted several determinants of welfare inequalities among households in Ethiopia, with urban and rural households experiencing varying levels of income, education, gender disparities, access to services, and agricultural opportunities. The creation of policies and interventions targeted at reducing inequality and enhancing the well-being of households in both urban and rural contexts depend on an understanding of these determinants. 2.2.2. Welfare inequality between urban and rural area In developing countries, the link between urban and rural sectors is characterized by economic dualism which manifests itself through the coexistence of a modern urban sector and a traditional rural sector. This dualism has facilitated the isolated resolution of problems that affect each area. The main premise is that the lack of urban-rural optimal links is bad for the enlarged growth of the economy, for it divides societies and leads to inefficiencies, a situation that is an original cause of inequality that in itself inhibits growth (African Development Bank AfDB, 2012). In recent years, regional inequality has become both for researchers and decision-makers, an important policy problem to reduce global inequality in several developing countries, owing to its social and economic implications. Several studies are focused on living standards across regions such as the factors which contribute to the urban-rural income gap. In Sub-Saharan Africa, a region that is considered among the most unequal in the world, the analysis of regional inequality has received Dula et al., Cogent Economics & Finance (2023), 11: 2290371 https://doi.org/10.1080/23322039.2023.2290371 Page 4 of 17 little attention in the previous literature. Given these factors, the study of the differences in urban and rural incomes is crucial to understanding regional development models (Ali et al., 2013). Ethiopia is a contradiction; in comparison to other nations, it is a very impoverished country with an incredibly fast rate of economic growth and low inequality across the board. Ethiopia’s economic growth and inequality reduction rates, however, differ along socioeconomic, rural/urban, educational, and racial/ethnic lines. Different urban elites with advanced educations have benefited from economic expansion (Kuznar, 2019). Due to an aggressive economic development policy implemented after 2000 and founded on the idea that advances in the agricultural sectors would lead to subsequent development in industry, Ethiopia boasts some of the lowest inequality and most rapid economic growth (more than 10%) in the world (World Bank, 2014). However, economic growth has not impacted all ethnic groups and socioeconomic levels equally. Within the rural agrarian sector, inequality is similar in other developing countries (Gebeyehu et al., 2018). Several measures have been proposed in the literature to characterize inequality in the distribution of income or expenditure (Anyanwu, 2005). One of the inequality measures of interest is the one proposed by Fields (Chamarbagwala, 2010) which makes it possible to evaluate the importance of the specific attributes of the household in the explanation of the level of inequality, where the amount explained by each factor is independent of the inequality measure used. This method consists in carrying out a set of regressions. The alternative approach is the quantile regression method in which, instead of estimating the mean of a conditional dependent variable using the values of independent variables, we estimate the median, that is, we minimize the sum of absolute residuals instead of the sum of squared residuals as in ordinary least squares regressions. It is possible to estimate different percentiles of dependent variables, and thus to obtain the estimates of different parts of the income or expenditure distribution (Chameni Nembua & Miamo Wendji, 2012). A study was conducted by Teshome et al. (2021), to identify the factors that contribute to income inequality among urban households in Nekemte Town, Ethiopia, by breaking it down into several demographic groupings. As a result, 275 families were selected using a stratified sampling technique, with kebeles (the smallest administrative unit) serving as strata. As a stand-in for income inequality, household expenditure per adult equivalent was employed. Using the Distributive Analysis Stata Package (DASP), the inequality situation and decomposition analysis by population subgroups were carried out to determine the relative contributions of the components of inequality within and between subgroups. Quintile Regression (QR) and Ordinary Least Square (OLS) Models were also used in the econometric analysis. In addition, for this study, we used the Atkinson index, because it takes into account the welfare of all citizens and recognizes that achieving an equitable distribution of resources entails prioritizing the well-being of the most disadvantaged over the average per capita income (Afonso & Do Rosário Cabrita, 2015). 2.3. Conceptual framework The conceptual Framework of this study indicate that through an analysis of the association among diverse socio-economic and demographic factors and the status of household expendituresis a key indicator of a household’s economic situation and is directly linked to welfare inequality, we can gain a more comprehensive grasp of the status of inequality in terms of welfare among household in the rural and urban areas in Ethiopia. By pinpointing the primary drivers of this inequality, policymakers and stakeholders can formulate precise interventions and strategies to tackle these disparities and strive towards establishing a more just living environment for all citizens of Ethiopia (Figure 1). 3. Research methodology 3.1. Description of the study area Ethiopia is a country located in the Horn of Africa. It is bordered by Eritrea to the north, Sudan to the west, South Sudan to the southwest, Kenya to the south, Somalia to the east, and Djibouti to Dula et al., Cogent Economics & Finance (2023), 11: 2290371 https://doi.org/10.1080/23322039.2023.2290371 Page 5 of 17 the northeast. Ethiopia has a population of over 115 million people, making it the second-most populous country in Africa. It is a diverse nation with more than 80 ethnic groups, each with its own unique language and culture. Amharic is the official language, but there are also many regional languages spoken throughout the country. In terms of socioeconomic conditions, Ethiopia has a predominantly rural population. Agriculture is the backbone of the economy, with the majority of Ethiopians engaged in subsistence farming. However, there has been significant urbanization in recent years, with the growth of cities like Addis Ababa, the capital, and other regional centers. Urban areas offer more diverse economic opportunities, including manufacturing, services, and trade. Despite progress, Ethiopia still faces challenges in terms of poverty and inequality. The government has been implementing various development initiatives to address these issues, including efforts to improve infrastructure, education, healthcare, and access to clean water. 3.2. Types of data The data type is quantitative and The Living Standards Measurement Study (LSMS). The LSMS is an extensive household survey research enterprise that is executed by the World Bank. This initiative aims to provide top-tier data on the socioeconomic conditions prevalent in developing countries. The LSMS data about Ethiopia from 6770 households have been obtained from the Ethiopia Socioeconomic Survey (ESS), which is a collaborative venture between the Central Statistics Agency (CSA) of Ethiopia and the World Bank. The ESS is an all-encompassing survey that collects detailed information on various facets of household welfare, such as consumption, income, education, health, labor, and assets. The present study endeavors to draw a comparison between the determinants of welfare inequalities in urban and rural Ethiopia, to gain a better understanding of their similarities and differences. 3.3. Method of data analysis A decomposition analysis was undertaken by dividing the origins of the inequality in welfare between urban and rural areas. This shall involve the computation of the Atkinson index of inequality for the urban and rural areas, with consumption expenditure per adult equivalent as the measurement of welfare. Furthermore, inequality in welfare determinants was investigated through a series of regression models (Quantile Regression), wherein welfare levels were regressed against a series of explanatory variables. 3.4. Atkinson Index The Atkinson index, introduced by esteemed British economist Anthony Barnes Atkinson in 1970, is a widely recognized measure of welfare inequality that serves as an alternative to the conventional Gini coefficient. The index takes into account the welfare of all citizens and recognizes that achieving an equitable distribution of resources entails prioritizing the well-being of the most Household Expenditure status Welfare inequality status among household in rural and urban area Socio-economic Variables •Number of assets •Number of Livestock •Mobile phone access •To be employed •Saving Demographic Variables •Sex •Age •Education level •Household Size Figure 1. Conceptual framework. Source: Own Computing, 2023. Dula et al., Cogent Economics & Finance (2023), 11: 2290371 https://doi.org/10.1080/23322039.2023.2290371 Page 6 of 17 disadvantaged over the average per capita income (Afonso & Do Rosário Cabrita, 2015). In essence, the index gives greater importance to the lower-income segments of society in its computation of the degree of inequality. The Atkinson Index is a measure based on the concept of “equally distributed equivalent income,” which refers to the income per person that would generate the same level of overall societal welfare as the current distribution if it were distributed equally among all individuals. This concept was introduced by Atkinson in 1970. The index is represented by A(ε), where ε is a parameter that represents the degree to which individuals are concerned about inequality. Higher values of ε indicate a greater concern for inequality, while lower values signify less concern for disparities in welfare distribution. The Atkinson Index can be calculated using the following mathematical formula: Here, A (ε) refers to the Atkinson Index, ε refers to the inequality aversion parameter, y_i refers to the welfare of individual i, and N refers to the total number of individuals in the population. The Atkinson Index has a range of 0 to 1, with 0 representing total equality (everyone has the same degree of welfare) and 1 representing utter inequality (only one individual has all the welfare). An increase in the Atkinson Index signifies a rise in inequality, while a decrease in the index indicates reduced inequality. One important feature of the Atkinson Index is its sensitivity to the chosen value of ε, which allows policymakers and economists to customize the analysis based on their specific concerns regarding income or welfare inequality. This flexibility makes the Atkinson Index a valuable tool for evaluating disparities in economic welfare across populations, thereby contributing to informed decisions on issues related to social equity and income redistribution. 3.4.1. Quantile regression model The OLS regression method assumes that the effects of repressors do not vary along the conditional distribution of the dependent variable. For example, the effect of schooling on household welfare is assumed to be the same at the bottom as well as at the top of the welfare distribution. However, if these effects vary along the household welfare distribution, quantile regressions, which provide models for different percentiles of the welfare distribution, constitute a parsimonious way to describe the whole distribution. In the ordinary least square (OLS) method in linear regression analysis to estimate the conditional mean of the consumption expenditure given a collection of explanatory variables. The average change in consumer expenditure resulting from a change in the relevant explanatory variable is represented by the estimated coefficients in the regression (Table 1). While the Koenker and Bassett (1978) quantile regression model is used to evaluate poverty determinants at various places along the expenditure distribution. It benefits from permitting parameter variation between consumption expenditure distribution quantiles. The quantile estimator is more effective than linear regression when errors are not normally distributed, making it a robust method since the estimated coefficients of the quantile regression are less susceptible to outliers of the dependent variable than OLS (Buchinsky, 1998; Cameron & Trivedi, 2005). To produce more accurate and reliable estimates, the standard errors were computed using bootstrapped methodologies (Koenker & Hallock, 2001). Additionally, it enables researchers to predefine any distribution positions by their particular study questions (Hao & Naiman, 2007). The quantile regression is as follows: Dula et al., Cogent Economics & Finance (2023), 11: 2290371 https://doi.org/10.1080/23322039.2023.2290371 Page 7 of 17 Table 5. Empirical result for determinates of welfare inequality among households in rural and urban RURAL URBAN OLS 25 th quantiles 50 th quantiles 75 quantiles OLS 25 th quantiles 50 th quantile 75 quantiles Age Square 1.365 (11.018) 5.273 (2.767) 5.238 (10.335) −1.209 (16.524) 1.123 (4.883) −0.463 (3.714) −5.111 (5.834) 10.50373 (12.768) Sex −108079 (79733.63) 0 0 0 20064.13 (17860.04) 0 0 0 Household size −6518.01 (5829.65) −1497.51 (2012.233) 2786.094 (6845.37) 3339.066 (7961.523) 3433.209 (2217.985) 1768.888 (1362.825) 3258.708 (2007.275) 11244.55** (4850.884) Education level 1087.60 (670.637) 221.148 (232.7081) 177.6208 (791.644) 186.163 (920.724) −168.452 (165.398) −226.948** (99.992) −222.499 (147.275) 105.9487 (355.913) Number of livestock −43782.8 (15435.16) −7278.55 (5454.817) −11884.8 (18556.62) −13768 (21582.31) 4591.672 (5486.229) 9834.755*** (3503.061) 8567.562 (5159.58) −2715.9 (12468.91) Own mobile phone −43918.1 (36764.64) 4592.965 (12606.92) −8096.15 (42887.18) −13577.1 (49880.03) −2352.01 (9251.727) −1828.05 (5830.262) 1836.956 (8587.264) 14331.66 (20752.43) Access to health insurance 10338.33 (12100.03) 38221.16*** (12773.19) 36205.24 (43452.81) 41797.55 (50537.89) 2155.348 (4200.897) 1518.823 (8089.293) −6640.82 (11927.8) −46307.5 (28825.33) Employment 0 0 0 0 0 0 0 0 Number of Assets 0 14766*** (4597.784) 21056.8*** (7555.824) 47744*** (15256.78) 0 2294 (14924.43) 17849.72 (18323.5) −26631.2 (290784.9) Saving 317577.7 (30478.66) 18849.69* (10771.47) 18580.87 (36643.23) 3127.464 (42617.99) 2406.371 (9681.786) 9551.557 (6302.655) 16020.06* (9283.04) 986.0932 (22433.88) _cons 387863.8 (138100.5) 22497.63 (28132.27) 41603.18 (95702.54) 83805.29 (111307.1) −307.254 (39911.1) −3667.03 (37579.3) −50832.6 (55349.72) −56106.5 (133761) Pseudo R 2 0.287 0.277 0.331 0.237 0.182 0.133 0.113 0.151 *** Significance at one % significance level, ** significance at 5% significance level, * significance at 10% significance level. Source: Own Computing result from LSMS, 2023. Dula et al., Cogent Economics & Finance (2023), 11: 2290371 https://doi.org/10.1080/23322039.2023.2290371 Page 14 of 17 household size, education level, number of livestock possessed, possession of mobile phones, accessibility to health amenities, employment status, savings, and involvement in trading activities (Table 5). It was established that household size exhibited a substantial positive influence on welfare inequality, with a coefficient of 11,244.55. This denotes that when the household size is augmented by one unit, the overall consumption of the household escalates by 11,244.55 units annually, as does welfare inequality at this quantile. This correlation between household size and welfare inequality has been noted in alternative research. 4.3.2. Determinates of inequality in welfare among rural households The outcomes illustrated in Table 5 reveal that a quantile regression analysis at the 0.25 percentile level, was conducted to identify the determinants of inequality in welfare among rural areas. The coefficients presented to signify the partial effects that the independent variables exert on the total consumption at the 0.25 percentile. In simpler terms, they uncover the relationship between the 25th percentile of total consumption and the impact of a one-unit increase in each independent variable, while keeping other factors constant. The evidence suggests that the availability of health services has a positive and statistically significant influence on total consumption. This implies that the accessibility of health services is a crucial driver of welfare in rural areas, which aligns with the conclusions of Case and Deaton’s (2005) study highlighting the affirmative relationship between health service availability and welfare in rural India. Furthermore, the possession of assets has a positive and statistically significant impact on total consumption, indicating that households with more assets have higher levels of welfare. This observation corresponds with the findings of Sahn and Stifel (2003), who explored the connection between asset ownership and welfare in rural Mozambique. Saving also has a positive and marginally significant effect on total consumption, implying that households with higher savings could have higher welfare levels, although this effect is not statistically significant at the 95% confidence level. This result supports Ethiopian policies that aim to increase access to health services for rural populations, promote asset accumulation, and encourage saving. In terms of assets, Ethiopia has been implementing various agricultural and rural development programs, such as the Sustainable Land Management Program, the Productive Safety Net Program, and the Rural Financial Intermediation Program. These policies aim to increase the agricultural productivity and income of rural households, which could enable them to accumulate productive assets and increase their consumption and welfare. For savings, Ethiopia has been promoting micro-saving schemes and rural saving and credit cooperatives to enhance the financial inclusion and saving capacity of rural households. Table 5 presented a 0.5 quantile regression analysis for the determinants of inequality in welfare in a rural household. From the findings, it is evident that the number of assets owned by a household has a large and significant positive impact on welfare inequality, as evidenced by the coefficient of 21,056.8 and p-value of 0.006 (p < 0.05). This suggests that a unit increase in the number of assets held by a household leads to a substantial rise in welfare inequality. This is consistent with previous literature highlighting the role of assets in determining household welfare and inequalities (e.g., Günther & Klasen, 2009). The findings from Table 5 present a 0.75 quantile regression analysis that centers on elucidating the interconnection between multiple factors and their determinants on the issue of inequality in welfare in rural localities. The outcomes reveal that the variable of Asset Quantity holds a statistically significant positive influence on overall consumption in rural regions, with a coefficient of 47,744 and a p-value of 0.002. This suggests that households with a greater number of assets tend to demonstrate a higher level of welfare, as evidenced by their higher total consumption. However, the OLS result indicates that any of the explanatory variables have no statistically significant effect on inequality in welfare among households in rural and urban. 5. Conclusion and policy implication The study has examined the welfare inequality among rural and urban households in Ethiopia, using the Atkinson index and quantile regression methods. The study has found that there is a significant Dula et al., Cogent Economics & Finance (2023), 11: 2290371 https://doi.org/10.1080/23322039.2023.2290371 Page 15 of 17 difference in welfare inequality between rural and urban areas, with rural areas having a higher degree of inequality. The study has also identified the main factors that determine welfare inequality in different consumption percentiles for both rural and urban households. The study has implications for policy and practice to reduce welfare inequality and improve the well-being of the population. The study suggests that education level and livestock production are important determinants of welfare inequality among urban households in the lower consumption percentiles, while household size is the only significant factor in the higher consumption percentiles. Therefore, policies aimed at reducing welfare inequality in urban areas should focus on enhancing educational opportunities and promoting livestock activities, especially for the poor and vulnerable groups. Moreover, policies should also consider the effects of household size on welfare inequality and explore ways to support larger households. The study also indicates that asset accumulation, saving and health access are key determinants of welfare inequality among rural households in both lower and higher consumption percentiles. Hence, policies aimed at reducing welfare inequality in rural areas should emphasize the promotion of asset ownership, saving behavior and health service provision, which can improve the living standards and resilience of rural households. Furthermore, policies should also investigate the other factors that may influence welfare inequality in rural areas, such as mobile phone ownership, trade and education. 5.1. Limitation of the study The study on the Determinants of Inequalities in Welfare among Households in Ethiopia, focusing on the urban and rural divide, possesses several limitations that warrant consideration. Firstly, the research may face challenges in generalizing its findings to the entire Ethiopian population, as the scope is confined to urban and rural areas, potentially overlooking nuances in peri-urban or other specific contexts. Additionally, the accuracy and reliability of the results may be influenced by the quality of data, potentially affected by recall biases or data collection limitations. Moreover, the study might not adequately address cultural and contextual variations within urban and rural settings, limiting the depth of its analysis. Finally, external factors such as political and economic changes that occurred after the study period could impact the relevance and applicability of the findings to the current socioeconomic landscape in Ethiopia. Funding The authors have not received funding for this research. Author details Tsegamariam Dula 1 E-mail: [email protected] ORCID ID: http://orcid.org/0000-0002-6906-2870 Jemil Yasin 1 Haymanot Meseret 2 Abrham Seyoum 2 1 Center for Rural Development, Addis Abeba University, Addis Abeba, Ethiopia. 2 Departement of Agricultural economics, wolkite University, Wolkite, Ethiopia. Disclosure statement No potential conflict of interest was reported by the author(s). Abbreviation LSMS: Living Standards Measurement Surveys; SDGs: Sustainable Development Goals; GTP: Growth and Transformation Plan; HDI: Human Development Index Author contribution All Authors have written and analyzed all parts of the paper together Availability of data and materials The data can be obtained from the corresponding author upon request Citation information Cite this article as: Determinants of inequalities in welfare among households in Ethiopia: A comparative study of urban and rural Ethiopia, Tsegamariam Dula, Jemil Yasin, Haymanot Meseret & Abrham Seyoum, Cogent Economics & Finance (2023), 11: 2290371. References Afonso, H., & Do Rosário Cabrita, M. (2015). Developing a lean supply chain performance framework in an SME: A perspective based on the balanced scorecard. Procedia Engineering, 131, 270–279. https://doi.org/ 10.1016/j.proeng.2015.12.389 African Development Bank (AfDB). 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