Income and food Engel curves in Rwanda: a household microdata analysis

Nsabimana, Aimable; Swain, Ranjula Bali; Surry, Yves; Ngabitsinze, Jean Chrysostome

doi:10.1186/s40100-020-00154-4

Cited by 19 publications

(31 citation statements)

References 31 publications

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“…According to other studies, poor households only eat food that is richer in carbs and starches and less on healthy diets (Nsabimana et al, 2020), consistent with the findings in this study. This leads to a low investment of poor households in other significant facets of life, like education and health and therefore leads to further disparity in these indicators and results in the poor quality of life among these households.…”

Section: Discussionsupporting

confidence: 92%

Income Distribution and Its Effect on Food Expenditure, Non-Food Expenses and Savings in Households of a Developing Economy

Aryal

Aryal²

2023

JEFAS

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The study examined the income distribution and effects of income on food expenditure, non-food expenditure and savings of households. The survey data was used, and Gini-coefficient was derived from observing the income distribution across households of different income classes. Engel coefficient was used to estimate the income elasticity of the expenditure on food items. This study found significant disparities in the income of rich and poor households with a high Gini Index. Also, it found significant variations in food consumption patterns across different income classes. The proportion of food basket share of a household declined with an increase in income. Similarly, the proportion of the budget share of food items shifted to other non-food items with increased income. According to the findings, lower income households had a higher elasticity of food expenditure than higher income households, complying with Engel’s law. The results of this study are noteworthy because they would provide crucial policy recommendations and a foundation for future research.

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Section: Discussionsupporting

confidence: 92%

Income Distribution and Its Effect on Food Expenditure, Non-Food Expenses and Savings in Households of a Developing Economy

Aryal

Aryal²

2023

JEFAS

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“…The model includes demographic variables to control for variations in preferences between households that are likely due to differences in their demographic characteristics. Some researchers also include household demographic variables in their demand models, such as those conducted by Ngui et al (2011), Gostkowski (2018, Nsabimana et al (2020), Korir et al (2020), andVargas-Lopez et al (2022). Research that examines food demand in Indonesia also incorporates demographic variables (Jensen & Manrique, 1998;Faharuddin et al, 2017;Suriani et al, 2018).…”

Section: Variablesmentioning

confidence: 99%

“…Hamlets, villages, towns, and other small settlements are in or surrounded by rural areas. Nsabimana et al (2020) estimate that about 40-48% of the population in Asia and Africa live in rural areas. In Ethiopia, a less-developed country where agricultural jobs are much more common, 87% of the people live in rural areas.…”

Section: Introductionmentioning

confidence: 99%

Rural Household Food Consumption in Bengkulu, Indonesia: Estimating a Demand System Based on SUSENAS Microdata

N.¹,

Matsuda²

2022

JAS

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The paper aims to estimate the food demand of rural households in Bengkulu Province, Indonesia, using the Quadratic Almost Ideal Demand System (QUAIDS) and microdata from the SUSENAS. We aggregate food into five groups: staple food, animal food, vegetables & fruits, prepared food, and other food. The results show that demand for animal food is the most sensitive to food expenditure, whereas the demand for staple food is the most expenditure-inelastic. Staple food, animal food, vegetables & fruits, and other food are substitutes for each other. On the other hand, prepared food and staple food complement each other. Other food is the easiest to be substituted, and staple food is the most difficult to be substituted. The demographic variables, as well as prices and expenditures, impact household demand. For example, as family size increases, the demand for staple food increases, while the demand for animal food, vegetables & fruits decreases. The number of children under five years old has a positive impact on animal food demand but a negative impact on staple food and other food demand. Staple farmer households have a higher need for staple food than non-agricultural households. Due to being unmarried, divorced or bereaved, single households have a lower demand for staple food but a higher demand for prepared food. We mainly imply that the food price stabilization policy should emphasize animal food, especially beef and poultry, without increasing prices.

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“…Research on household consumption patterns in Nepal differentiated the consumption behaviors of lowincome households and high-income households (Khanal, Banskota, & Giri, 2018). Research into consumption patterns that specifically analyzes the behavior of poor households has been carried out in Rwanda using micro data (Nsabimana, Bali, Surry, & Ngabitsinze, 2020). However, this study does not make comparisons between households in other groups and does not use policy variables as indicators of poverty.…”

Section: Asian Economic and Financial Reviewmentioning

confidence: 99%

“…As an illustration, the pattern of household consumption can be described using a scheme such as the following: Figure 1 shows the framework of this research, which was modified from empirical research in Rwanda (Nsabimana et al, 2020). Household consumption demand is a reflection of household decisions on expenditure allocation.…”

Section: Literature Reviewmentioning

confidence: 99%

Poverty Conditions and Patterns of Consumption: An Engel Function Analysis in East Java and Bali, Indonesia

Rasyid

Kristina

Sutikno

et al. 2020

Asian Economic and Financial Review

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This paper aims to analyze consumption patterns of various household goods. The data used in this study was sourced from results of household surveys in the East Java and Bali Provinces in Indonesia. The analytical model used to evaluate household consumption patterns was the Engel function. Engel's function model maps the level of consumption to household income. In this study, the explanatory variables used include household expenditure levels, household characteristics and household poverty conditions. The results showed that the consumption of staple foodstuffs was relatively inelastic in terms of an increasing household expenditure. Moreover, the consumption of processed food is relatively more elastic in terms of expenditure. The study also found that poor households have a different consumption pattern in comparison to nonpoor households. Poor households allocate less income to basic necessities that are important for health, such as vegetables, meat and fish. The implication is that government assistance for poor households must be accompanied by education on healthy consumption patterns. Contribution/ Originality: This study is one of the few studies examining household consumption patterns and their relationship with household welfare and poverty indicators in developing countries. This research is a preliminary study that uses poverty rates of poor households based on indicators of government assistance in the form of financial aid.

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Income and food Engel curves in Rwanda: a household microdata analysis

Cited by 19 publications

References 31 publications

Income Distribution and Its Effect on Food Expenditure, Non-Food Expenses and Savings in Households of a Developing Economy

Income Distribution and Its Effect on Food Expenditure, Non-Food Expenses and Savings in Households of a Developing Economy

Rural Household Food Consumption in Bengkulu, Indonesia: Estimating a Demand System Based on SUSENAS Microdata

Poverty Conditions and Patterns of Consumption: An Engel Function Analysis in East Java and Bali, Indonesia

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