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A Class of Decomposable Poverty Measures
... This paper utilizes the FGT index to measure poverty. The FGT index meets both axiomatic and decomposability requirements, which many other measures do not (Foster et al., 1984). For instance, neither the basic poverty index nor the Sen poverty index (Sen, 1976) satisfies the axiomatization requirement. ...
... This paper employs the grouped data recovery method to estimate initial income observations, thereby obtaining national-level income grouped data. Additionally, to measure the FGT index (Foster et al., 1984), the Beta model is used to fit the Lorenz curve (Datt, 1998). ...
... This study employs the FGT index, as defined by Foster et al. (1984), to measure poverty. The discrete form of the FGT index is given as: ...
In this study, we propose a new method for poverty decomposition that offers advantages such as time-reversion consistency. Our decomposition is based on the Shapley decomposition method from cooperative game theory. It separates changes in mean income into changes in total income and in total population. These two factors, combined with changes in inequality and the poverty line, generate four effects: growth, distribution, population, and poverty line effects. Our decomposition includes twenty-four possible ways, and we take the mean of these to compute the four effects. However, considering the practical significance of the poverty line effect, we compute this effect using the final period as the reference period. By excluding the eighteen decomposition ways that do not meet the conditions, we average the remaining six ways to obtain the constrained four-dimensional poverty decomposition method. Applying this method to China for the period 2001–2022 demonstrates its feasibility under different poverty lines. We believe that the poverty decomposition method presented in this study has broad applicability and can help identify the sources of changes in poverty, thereby providing policymakers with valuable information to implement more effective antipoverty policies.
... Para conocer el impacto de programas como Oportunidades en el nivel de pobreza, primero hay que medirla, para ello se emplea el método de líneas de pobreza (LP) y los índices FGT (Sen, 1976;Foster et al., 1984) y, luego se recurre a la Técnica de Microsimulación Estática (TMSE) para conocer el cambio microeconómico en el ingreso de cada individuo y hogar (Bourguignon y Spadaro, 2006), luego estimar las diferencias de ingreso atribuidas al programa y los cambios en el índice FGT y finalmente precisar la diferencia entre los índices antes de Oportunidades y después de la aplicación del programa. ...
... En términos generales, cuanto mayor es el índice FGT los ingresos de los hogares pobres estarán más alejados de las líneas de pobreza. Foster et al. (1984) utilizan el parámetro a=2 para medir la "severidad" de la pobreza en atención a los axiomas de pobreza de Sen (1976) 7 , de suerte que el índice FGT(2) refleja una mayor sensibilidad al déficit de ingreso de los hogares más pobres; es decir, éste índice va más allá del elaborado por el propio Sen, toda vez que permite conocer si las transferencias de ingreso del programa están contribuyendo a reducir la pobreza de los más pobres de los pobres, grupo al cual deberían estar dirigidos todos los esfuerzos en el combate a la pobreza. ...
... La familia de los índices FGT calcula el porcentaje de hogares en pobreza cuando el ponderador á=0; la intensidad de la pobreza "I", que mide la distancia entre el ingreso promedio de los hogares pobres y las líneas de pobreza si á=1; y, permite incorporar el déficit de ingreso de los hogares más pobres cuando el ponderador á=2; véaseFoster et al., 1984. ...
La pobreza se define en base al enfoque monetario, se estima con el método de líneas de pobreza y la técnica de microsimulación estática (Bourguignon et. al., 2006) ayuda a captar el impacto de Oportunidades, la información proviene de las ENIGH’s 2002 y 2006. Se encontró un impacto muy limitado en la reducción de la pobreza en México y la región Tradicional debido a la insuficiencia de recursos y errores en la focalización, los estados de Zacatecas, Michoacán, Guanajuato y Durango tenían mayores niveles de pobreza que México y la región. En el país el impacto fue ligeramente mayor en el sector rural, mientras que en la región Tradicional Oportunidades resultó más efectivo en la reducción de los tres tipos de pobreza en el sector urbano y en el sector rural el mayor impacto se observó en pobreza de patrimonio, luego en pobreza alimentaria y en menos medida en pobreza de capacidades.
... Monetary measures are also flexible. For example, consumption expenditures data can be used to estimate the Foster-Greer-Thorbecke (FGT) class of distribution-sensitive poverty measures, including the "poverty gap" and "poverty gap squared" (26). The FGT measures take into account how far below the poverty line people's incomes or consumption expenditures fall, and satisfy a range of desirable axiomatic properties (26,27). ...
... For example, consumption expenditures data can be used to estimate the Foster-Greer-Thorbecke (FGT) class of distribution-sensitive poverty measures, including the "poverty gap" and "poverty gap squared" (26). The FGT measures take into account how far below the poverty line people's incomes or consumption expenditures fall, and satisfy a range of desirable axiomatic properties (26,27). The advantages of consumption-based poverty measures are balanced by the expense (and therefore scarcity) of high quality training data and the stochastic nature of consumption. ...
... Next, we construct the FGT poverty measures {P s }, = 0, 1, 2, for the survey cluster s of interest (26). Specifically, we calculate the estimated share of individuals ## with consumption expenditures that fall below a national or international poverty line, or poverty headcount {P 0 s }; the average shortfall, or poverty gap {P 1 s }; and the average squared poverty gap {P 2 s }: ...
For many countries in the Global South traditional poverty estimates are available only infrequently and at coarse spatial resolutions, if at all. This limits decision-makers’ and analysts’ ability to target humanitarian and development interventions and makes it difficult to study relationships between poverty and other natural and human phenomena at finer spatial scales. Advances in Earth observation and machine learning-based methods have proven capable of generating more granular estimates of relative asset wealth indices. They have been less successful in predicting the consumption-based poverty measures most commonly used by decision-makers, those tied to national and international poverty lines. For a study area including four countries in southern and eastern Africa, we pilot a two-step approach that combines Earth observation, accessible machine learning methods, and asset-based structural poverty measurement to address this gap. This structural poverty approach to machine learning-based poverty estimation preserves the interpretability and policy-relevance of consumption-based poverty measures, while allowing us to explain 72 to 78% of cluster-level variation in a pooled model and 40 to 54% even when predicting out-of-country.
... Poverty is commonly assessed using three measures: (i) prevalence, (ii) normalized gap, and (iii) severity. [15][16][17][18][19] Prevalence of poverty refers to the number of people in a given population living below a specified poverty line. [15][16][17][18][19] It therefore represents the number of people who need financial assistance to eradicate poverty. ...
... [15][16][17][18][19] Prevalence of poverty refers to the number of people in a given population living below a specified poverty line. [15][16][17][18][19] It therefore represents the number of people who need financial assistance to eradicate poverty. [15][16][17][18][19] The normalized gap of poverty indicates the average gap between the income of individuals in a given population and the poverty line. ...
... [15][16][17][18][19] It therefore represents the number of people who need financial assistance to eradicate poverty. [15][16][17][18][19] The normalized gap of poverty indicates the average gap between the income of individuals in a given population and the poverty line. [15][16][17][18][19] It is used to estimate the average amount to be disbursed per poor person (and therefore the total amount required, also known as the total economic effort) to eradicate poverty in the said population. ...
... Poverty is commonly assessed using three measures: (i) prevalence, (ii) normalized gap, and (iii) severity. [15][16][17][18][19] Prevalence of poverty refers to the number of people in a given population living below a specified poverty line. [15][16][17][18][19] It therefore represents the number of people who need financial assistance to eradicate poverty. ...
... [15][16][17][18][19] Prevalence of poverty refers to the number of people in a given population living below a specified poverty line. [15][16][17][18][19] It therefore represents the number of people who need financial assistance to eradicate poverty. [15][16][17][18][19] The normalized gap of poverty indicates the average gap between the income of individuals in a given population and the poverty line. ...
... [15][16][17][18][19] It therefore represents the number of people who need financial assistance to eradicate poverty. [15][16][17][18][19] The normalized gap of poverty indicates the average gap between the income of individuals in a given population and the poverty line. [15][16][17][18][19] It is used to estimate the average amount to be disbursed per poor person (and therefore the total amount required, also known as the total economic effort) to eradicate poverty in the said population. ...
... To assess farmers' vulnerability to the risks posed by climate change based on their financial status, this study adapted the Foster, Greer, and Thorbecke (FGT) index equation used to measure poverty. While various poverty indices have been developed (Sen, 1976;Chakravarty, 1983;Foster et al., 1984;Pyatt, 1987), the FGT index has broader applications (Walelign, 2013) and can be calculated as follows: ...
... When α = 1, the index represents the poverty gap (or depth), which is the aggregated shortfall of income for all the poor individuals from the poverty line and represents the percentage of their mean shortfall from the poverty line. When α = 2, the index represents the squared poverty gap, which measures the severity of poverty in the community (Foster et al., 1984). The poverty line (Z) equation as used by Omonona et al. (2008) is calculated as follows ...
... A farmer is counted to be vulnerable when his financing gap (y) is M.P. Ojo et al. Environmental and Sustainability Indicators 24 (2024) 100476 greater than the vulnerability line (z), such that I is equal to 1. Adapting equation (14) as used by Foster et al. (1984) to capture poverty incidence based on the poverty line, also based on the vulnerability line in the study area, we take farmers who are below the vulnerability line as having a financial status that enables moderate to high adaptive capacity, while those above the line have low or significantly reduced adaptive capacity which makes them vulnerable. Although VG 0 gives the number of vulnerable farmers, it does not give the degree to which their financing gap exceeds the vulnerability line. ...
With climate change continuously threatening global food production, smallholder farmers are increasingly
struggling to adapt to changing climatic conditions, decreasing productivity, and limited access to finance. To
examine these challenges, this study used cross-sectional data collected through a multi-stage approach across
three plantain-producing states in southwest Nigeria, with 100 farmers randomly selected in 5 local government
areas per state to give a total of 300 farmers. A two-step Stochastic Frontier model is used to examine the
relationship between climate adaptation strategies and plantain productivity while the Harold-Dorma growth
equation and Multivariate Probit regression are used to assess the financing gap and its effect on adaptive ca-
pacity. Finally, the Foster Geer-Thorbecke (FGT) equation is used to measure the vulnerability of farmers to
climate change. Findings show that as the financing gap of the farmers decreases, their ability to adopt climate
adaptation strategies to enhance their productivity increases. However, 80% of the farmers are financially
vulnerable to climate change, with 37% facing severe financial constraints. The vulnerability depth for the
farmers is 56%, indicating that with 190.26), many farmers’ adaptive
capacity could be enhanced to reduce their vulnerability below the vulnerability line. This study’s approach
provides a comprehensive approach for assessing smallholder farmers’ ability to adopt adaptation strategies that
increase productivity and enhance resilience. While other policy measures to enhance smallholder farmers’
ability to address the challenges of climate change are important, it is crucial to prioritise actions that improve
the financial status of smallholders.
... Food Security Index (FSI) was used to measure how food secures of catfish farmers in the study area. There have been several dimensions as to the measures of food security some of which are Foster, Greer and Thorbeck (Foster, Greer and Thorbecke 1984) food insecurity measures widely discovered and used widely in several empirical studies (Omonona and Agoi 2007;Bamou and Mkouonga 2008). Poverty index (Foster, Greer and Thorbecke 1984), the index of food security was expressed thus: ...
... There have been several dimensions as to the measures of food security some of which are Foster, Greer and Thorbeck (Foster, Greer and Thorbecke 1984) food insecurity measures widely discovered and used widely in several empirical studies (Omonona and Agoi 2007;Bamou and Mkouonga 2008). Poverty index (Foster, Greer and Thorbecke 1984), the index of food security was expressed thus: ...
Change in climate is already a reality as all countries are taking action to reduce their gas emissions from greenhouse and get ready for its effects. The study examined socioeconomic dimension of food insecurity among catfish farmers in Ondo State, Nigeria. Other objectives were to examine the effects of climate change on catfish production and to evaluate the adaptation strategies employed by the catfish farmers and to determine the factors contributing to food security in the study area. Two stage sampling techniques were employed in selecting 231 catfish farmers for the study. Results revealed that the average age for catfish farmers was 42 years with a standard deviation of 10.69. In addition, male dominated the enterprise with an average of 0.76 and a standard deviation of 0.43 and that majority of the respondents were married with mean of 2.00 and a standard deviation of 0.622. Average number of years spent in school was 13 years. The mean farming experience of the catfish farmers was 11 years with a standard deviation of 7.74. The result of food security status revealed that food secure households were estimated to be 42.86% while 57.14% of the respondents were food insecure. Results further revealed the household size, (p < 0.10), education (p < 0.001) experience, (p<0.05) climate variable (p<0.05) showed a relationship to the food insecurity status of catfish farmers. The study recommends that catfish farmers should be more educated about climate change. Keyword: Climate Change, Socioeconomic, Catfish farmers, Food insecurity, Odd ratios
... Per capita income and the extreme poverty level were calculated following the methodology proposed by [29], who determined the proportion of the population in extreme poverty using the Foster-Greer-Thorbecke (FGT) poverty index [44]. The formula used is Po = Np/N, where Po represents the proportion of the sample classified as extremely poor, Np is the number of households in extreme poverty, and N is the total number of households in each producer association. ...
... Two indicators were used to assess household economic welfare: per capita income (PCI) and the poverty index (FGT) [44,55]. Our results show that the average annual PCI was highest among cacao-producing households in the Tsatsayaku association (USD 714.15), largely due to larger landholdings and engagement in additional activities such as livestock farming. ...
This study integrates the Sustainable Livelihoods Framework (SLF) and the Sustainability Assessment of Food and Agriculture Systems (SAFA) to evaluate the sustainability and livelihood dynamics of the Amazonian Chakra system, recently designated as a Globally Important Agricultural Heritage System (GIAHS) by the FAO. Using data from 330 producers across three associations (Kallari, Wiñak, and Tsatsayaku) in the Ecuadorian Amazon, the study employed discriminant analysis to assess governance, environmental integrity, economic resilience, social well-being, and livelihood capitals. Results revealed significant disparities across associations in key sustainability dimensions. Kallari and Wiñak demonstrated stronger governance, environmental integrity and economic resilience, linked to mature organizational structures and effective governance mechanisms. In contrast, Tsatsayaku excelled in demographic diversity and larger landholdings but lagged in governance and environmental practices. Extreme poverty affected 82% of households, with Tsatsayaku having the lowest rate (69%) compared to Wiñak (89%) and Kallari (87%). Chakra income contributed significantly to livelihoods, accounting for 44% of total income in Kallari, 37% in Wiñak, but only 16% in Tsatsayaku, whose producers relied more on off-farm activities and livestock. The integration of SLF and SAFA methodologies offered a nuanced understanding of sustainability, highlighting the importance of governance, financial strategies, and environmental conservation in promoting resilience. Policies should prioritize participatory governance, market transparency, and credit access to address disparities and strengthen sustainability. These findings underscore the critical role of the Amazonian Chakra as a sustainable agroforestry system, providing economic and cultural benefits, while emphasizing the need for tailored interventions to enhance the sustainability of Amazonian producer associations.
... Food Security Index (FSI) was used to measure how food secures of catfish farmers in the study area. There have been several dimensions as to the measures of food security some of which are Foster, Greer and Thorbeck (Foster, Greer and Thorbecke 1984) food insecurity measures widely discovered and used widely in several empirical studies (Omonona and Agoi 2007;Bamou and Mkouonga 2008). Poverty index (Foster, Greer and Thorbecke 1984), the index of food security was expressed thus: ...
... There have been several dimensions as to the measures of food security some of which are Foster, Greer and Thorbeck (Foster, Greer and Thorbecke 1984) food insecurity measures widely discovered and used widely in several empirical studies (Omonona and Agoi 2007;Bamou and Mkouonga 2008). Poverty index (Foster, Greer and Thorbecke 1984), the index of food security was expressed thus: ...
Change in climate is already a reality as all countries are taking action to reduce their gas emissions from greenhouse and get ready for its effects. The study examined socioeconomic dimension of food insecurity among catfish farmers in Ondo State, Nigeria. Other objectives were to examine the effects of climate change on catfish production and to evaluate the adaptation strategies employed by the catfish farmers and to determine the factors contributing to food security in the study area. Two stage sampling techniques were employed in selecting 231 catfish farmers for the study. Results revealed that the average age for catfish farmers was 42 years with a standard deviation of 10.69. In addition, male dominated the enterprise with an average of 0.76 and a standard deviation of 0.43 and that majority of the respondents were married with mean of 2.00 and a standard deviation of 0.622. Average number of years spent in school was 13 years. The mean farming experience of the catfish farmers was 11 years with a standard deviation of 7.74. The result of food security status revealed that food secure households were estimated to be 42.86% while 57.14% of the respondents were food insecure. Results further revealed the household size, (p < 0.10), education (p < 0.001) experience, (p<0.05) climate variable (p<0.05) showed a relationship to the food insecurity status of catfish farmers. The study recommends that catfish farmers should be more educated about climate change.
... Per capita income and the extreme poverty level were calculated following the methodology proposed by [30], who determined the proportion of the population in extreme poverty using the Foster-Greer-Thorbecke (FGT) poverty index [45]. The formula used is Po = Np/N, where Po represents the proportion of the sample classified as extremely poor, Np is the number of households in extreme poverty, and N is the total number of households in each producer association. ...
... Two indicators were used to assess household well-being: per capita income (PCI) and the poverty index (FGT) [45]. Our results show that the average annual PCI was highest among cacaoproducing households in the Tsatsayaku association (USD 714.15), largely due to larger landholdings and engagement in additional activities such as livestock farming. ...
This study combines two methodologies—key indicators from the Sustainable Livelihoods Framework (SLF) and the Sustainability Assessment of Food and Agriculture Systems (SAFA) approach—to evaluate sustainability among 330 producers from three associations working within the recently recognized Amazonian Chakra system, designated as a Globally Important Agricultural Heritage System (GIAHS). The SAFA framework's four dimensions—Good Governance, Environmental Integrity, Economic Resilience, and Social Well-being—were used to assess sustainability, while the SLF considered key capitals such as financial, natural, and human capitals as critical for understanding livelihood outcomes. The discriminant analysis revealed significant differences across the associations, with Kallari and Wiñak performing better in financial management, environmental practices, and governance compared to Tsatsayaku, which exhibited weaker outcomes in these domains. Key indicators such as chakra income, price determination, and civic responsibility were the most effective in distinguishing the groups. The income analysis further highlights that Tsatsayaku reported the highest total income but relies heavily on non-Chakra sources, while Kallari and Wiñak showed stronger reliance on Chakra income, which aligns with their more sustainable agricultural practices. Per-capita income was higher for Tsatsayaku, but extreme poverty levels remained similar across all associations, underscoring the need for targeted financial interventions. Policy recommendations include promoting access to financial resources and strengthening participatory governance models to enhance sustainability outcomes across associations. For future research, combining the SAFA and SLF provides a comprehensive and robust methodology for assessing sustainability in agricultural systems, enabling a deeper understanding of the interactions between social, economic, and environmental factors in diverse contexts.
... Depth of poverty refers to how far below the poverty line the average poor households' income (expenditure) falls. Severity of poverty explains sensitivity to changes in the distribution of income among the poor (Foster andGreer, 1984, andHaughton andKandker, 2009). 7 489 households receive both internal and international remittances. ...
... Depth of poverty refers to how far below the poverty line the average poor households' income (expenditure) falls. Severity of poverty explains sensitivity to changes in the distribution of income among the poor (Foster andGreer, 1984, andHaughton andKandker, 2009). 7 489 households receive both internal and international remittances. ...
Large numbers of people are migrating from the countryside to cities and abroad for work in Nepal. Migrants' remittances play an important role in improving household welfare. Using the latest household survey data from 2010, this study observes the probability of receiving remittances at the household level. Since remittances are a potential substitute for domestic income, the impact of remittances on poverty and inequality is examined using counterfactual scenarios. Results show that the probability of receiving remittances is higher in richer households than poorer households. Remittances contribute twenty percentages of total poverty headcount ratio reduction in Nepal. The role of international remittance is greater than that of internal remittance in decreasing the poverty headcount, the poverty gap and the squared poverty gap. However, remittances widen inequality in Nepal.
... It is defined as the proportion of the population living below a considered poverty line. It belongs to the class of poverty indicators defined by Foster et al. (1984). However, it does not satisfy the transfer and monotonicity axioms outlined by Sen (1976) or Zheng (1993). ...
Regional differences in price levels are substantial in many countries, but little is known about how they affect the measurement of income inequality and poverty. To bridge this gap, we construct a new regional price level database which combines indices published by official authorities, previous literature, and our original estimates. The database covers 23 countries including the world’s seven biggest economies. The combination of these indices with household-level data from the Luxembourg Income Study allows us to assess changes in indicators of income inequality and relative poverty caused by the adjustment of income for within-country price level differences. Our findings point to the necessity of considering the properties of specific indicators while assessing the potential effects of regional price levels.
... We use the Alkire-Foster (2011) (A-F) counting approach to calculate the multidimensional poverty index. The A-F method is the extension of Foster et al. (1984) poverty measure in the multidimensional space. This approach applies dual cut-off to identify multidimensional poor households. ...
This study bridges a critical gap by examining the impact of access to microcredit loan on the poverty and vulnerability level of households in multidimensional framework. Using longitudinal data from 2016 to 2019, we find a significant reduction in multidimensional poverty as well as the probability of future poverty of the households. After correcting for the sample selection bias, the impact of microcredit on both poverty and vulnerability is amplified. Further, we find that microcredit loan for productive purposes prevents the household from falling into multidimensional poverty in the future whereas the loan for nonproductive purposes reduces both current and future poverty. The households who first time take loans experience a significant reduction in current as well as future deprivations compared to nonborrowers.
... as expenditure. In this paper, we focus on estimating a class of poverty measures known as the Foster-Greer-Thorbecke (FGT) poverty measures, introduced by Foster, Greer and Thorbecke (1984). Consider a finite population of size N partitioned into m small areas of size N 1 , · · · , N m . ...
This paper extends the Nested Error Regression Model with High-Dimensional Parameters (NERHDP) to address challenges in small area poverty estimation. Building on the NERHDP framework, we develop a robust and flexible approach to derive empirical best predictors (EBPs) of small area poverty indicators, while accommodating heterogeneity in regression coefficients and sampling variances across areas. To overcome computational limitations in the existing algorithm, we introduce an efficient method that significantly reduces computation time, enhancing scalability for large datasets. Additionally, we propose a novel method for generating area-specific poverty estimates for out-of-sample areas, improving the reliability of synthetic estimates. To quantify uncertainty, we introduce a parametric bootstrap method tailored to the extended model. Through design-based simulation studies, we demonstrate that the proposed method has better performance in terms of relative bias and relative root mean squared prediction error compared to existing approaches. Furthermore, the proposed method is applied to household survey data from the 2002 Albania Living Standards Measurement Survey to estimate poverty indicators for 374 municipalities using auxiliary information from the 2001 census.
... Aggregating monetary poverty After identifying the poor from the non-poor, the next step was to assess the poverty status of households using appropriate poverty indices. The analysis of poverty was based on the statistical model developed by Foster et al. (1984), known as the FGT model of poverty decomposition. It combines information on the extent of poverty (as measured by the headcount ratio), the intensity of poverty (as measured by the total poverty gap) and inequality among the poor (as measured by the severity of poverty) as adopted for consumption poverty analysis (Anyanwu, 2014). ...
Poverty and environmental degradation are two of the most pervasive global issues today and among the pressing problems catching the attention of governments, development practitioners and researchers for decades. This research was conducted on the magnitude of and the interaction between poverty and environmental degradation in Girar Jarso district of North-central Ethiopia. To this effect, 377 sample households were randomly taken for the survey. Both primary and secondary data sources have been used. The quantitative data collected in the field survey was edited, coded, and entered into the statistical package for social sciences version 26 for analysis. Inferential statistical techniques such as chi-square test and regression model as well as descriptive statistical techniques like independent samples t-test were used to analyze the data. In addition, such poverty assessment indices as the Foster-Greer and Thorbecke as well as the multidimensional poverty index were employed to analyze the consumption and multi-dimensional poverty, respectively. The finding of the study shows that about 28.3% of households in the study area were consumption poor and the poverty gap was about 8.1% while poverty severity was about 2.6%. Furthermore, the multidimensional poverty in the study area was 55.6%. From this, multidimensional headcount ratio was 92.2% while multidimensional intensity was 59.8%. The above figures show the magnitude of poverty in terms of both monetary and multidimensional aspects, which force the poor to consume and exploit environmental resources. The mean consumption of these environmental resources was higher for poor households as compared to non-poor households. The study identified that there is a nexus between poverty and environmental degradation in the study area.
... These indexes are the headcount index, the poverty gap index, and the squared poverty gap index. Three indexes can be calculated using a general formula [24] as follows. ...
This study focuses on evaluating the impact of access to formal credit on the living standards of rural households in the North Central region of Vietnam. The propensity score matching (PSM) method was used on the Vietnam Household Living Standards Survey (VHLSS) 2020 database to examine this impact. The research results indicate that participation in formal credit has the potential to improve the living standards of households in the rural area of the North Central region. The improvement is approximately 2 percent of per capita income. In addition, this study also shows that formal credit can have a positive impact on poverty reduction. Specifically, participation in formal credit reduces poverty rates in rural areas of North Central Vietnam, although the reduction in these poverty rates is still modest.
... Poverty indices mentioned in this paper are (i) headcount ratio; (ii) aggregate income gap ratio; (iii) poverty gap ratio (which is nothing but the headcount ratio multiplied by the aggregate income gap ratio) and (iv) Foster-Greer-Thorbecke (FGT) (Foster et al., 1984). In analyzing the trend in poverty, it is also important to understand the nature of such changes, which may be associated with the incidence, intensity or severity. ...
In this paper we examined a large number of sector and household-specific variables, to understand their roles in the prolonged poverty in Manipur. We investigated the reasons by decomposing the household-specific variables based on Foster Greer Thorbecke (FGT) measure. The important factors responsible for this outcome were found to be unfavorable distribution of landholding, household size, low educational attainment and high dependency ratio. The analysis also highlighted that during this period, poverty ratio, as officially measured, has declined slightly but the intensity and severity as a measure of poverty have increased. The decline in poverty ratio during the study period is mainly reflected through the fall in head-count ratio and not attributed to reduction in depth of poverty in the state.
... This research estimates multidimensional poverty using a method developed by (Alkire & Foster, 2011) inspired by Sen's capabilities approach. To consistently assess both continuous and ordinal data, the AF method employs a complete set of poverty measures derived from the FGT class's hardship indicators (Foster et al., 1984) and the counting approach (Atkinson et al., 2002). Money poverty is just one part of the multidimensional idea of poverty, which may be explored in great depth using this approach because of its simplicity and adaptability (Table 1). ...
The pursuit of a comprehensive understanding of poverty has driven the formulation of innovative methodologies, with the multidimensional poverty index (MPI) standing as a prominent metric. But under empirical literature, role of geography concerning poverty remains under-documented; little emphasis has been placed to evaluating the pockets of poverty from geographic lens. This study employs the Alkire and Foster methodology to estimate MPI across diverse districts in Pakistan, utilizing data from the 2019-20 Pakistan Social and Living Standards Measurement (PSLM) survey. To identify spatial clusters Hot Spot Analysis is used along with bivariate mapping analysis, revealing spatial patterns of poverty and nuanced variations in MPI. Findings expose a disconcerting reality: 18% of Pakistan’s population grapples with multidimensional poverty, notably concentrated in Baluchistan and rural areas. Logistic regression analysis and Marginal Effects emphasizes the interplay of household demographics, with impoverished households showing larger dependency ratios and higher child proportions, while non-impoverished counterparts have a higher prevalence of working-age, employed, and educated individuals. The study underscores the critical need to tailor poverty alleviation strategies to diverse socio-economic and geographic contexts for effective policymaking and interventions.
... However, in modern era, the poverty estimation has expanded to encompass a multidimensional perspective (Alkire & Foster, 2011), which measures both the count of deprived individuals and the severity of poverty across various socioeconomic and demographic factors. Other methodologies from income or consumption point such as Foster-Greer-Thorbecke (1984) approach and the Cost of Basic Needs (CBN) approach. These approaches offer valuable insights into poverty measurement allows for measuring absolute poverty rates, particularly counting the proportion of poor household given consumption aggregates and poverty lines derived from household expenditure on essential goods and services in CBN and measuring severity and vulnerability of the household towards poverty in FGT (Jamal 2019). ...
The paper estimated the absolute poverty rate in case of the state of Azad Jammu & Kashmir (AJ&K) Pakistan. The absolute poverty was measured adopting Cost of Basic Needs (CBN) approach. The study utilized Household Integrated Economics Survey of Pakistan 2018-19 data to measure absolute poverty in AJ&K. The study found that AJ&K had a low rate 12.65 percent absolute poverty at provincial level. The regional analysis of the state revealed that rural poverty is higher in AJ&K compared to urban counterpart. Moreover, gender comparisons revealed that the male head had a higher rate of poverty compared to the female counterpart. The study also measured the income distribution inequality curve - Lorenz curve and the Gini coefficient. Similar to absolute poverty at provincial level, AJ&K had a lower level of income distribution inequality suggested that income is more equitably distributed over the population in the state compared to rest of the region of the country. The analysis of poverty bands indicated that 0.06 percent households were extremely poor, 2.75 percent were ultra-poor, 9.84 percent were poor and 18.63 percent were vulnerable to poverty, suggested that there is chance of 18 percent of the population to slip into poverty. Based on these finding, we propose that there should be targeted social programs specifically for rural AJ&K and income support through generating employment opportunities. The study contributes to a deeper understanding of the poverty in AJ&K and informed evidence based strategies for poverty reduction and promoting sustainable development.
Keywords: : Cost of Basic Needs, Poverty, Azad Kashmir
... The study suggests that overseas remittances boost household income, with more significant gains for migrant households. Table 3 illustrates the impact of remittances on various poverty indices using the Foster-Greer-Thorbecke (FGT) index (Foster et al., 1984) 8 . We compute FGT poverty indices by comparing household monthly per capita income under counterfactual and observed scenarios with the national poverty lines provided by the BBS. 9 The results show that the presence of remittances significantly reduces poverty incidence, depth, and severity, especially for migrant households. ...
This paper analyzes the effect of foreign remittances on household well-being at both national and regional levels in Bangladesh, utilizing extensive data from the latest Household Income and Expenditure Survey (HIES) conducted in 2016. The study, employing the Heckman two-step selection control method, finds that remittances significantly increase household income and reduce poverty incidence, depth, and severity. The study also reveals that migrant families experience substantial income and poverty reduction gains. The 2SLS-IV estimation, using the logarithm of historical migration stock as an instrument, further confirms these findings, providing additional support for the positive impact of remittances on household well-being. The findings are also consistent with the previous round of HIES 2010 data. However, the regional analysis identifies heterogeneous effects of remittances on household well-being among Bangladesh's eastern and western administrative divisions. The study demonstrates that families with higher migration density in the East benefit substantially more than those with lower migration density in the West. These findings underscore the significance of regional disparities in terms of the effects of remittances on household well-being in Bangladesh.
... The benefits of keeping a particular species of livestock can be perceived differently by livestock keepers depending on their attitude towards risk. In this context, it was reported by [9] that one of the government's policies was to encourage the private sector economy to concentrate on the production of poultry, swine, small ruminants, and micro livestock. The role of small ruminant production cannot be overemphasized in the economy of Nigeria, since majority of Nigeria diets contain meat produced from small ruminants. ...
The study was carried out to assess the food security status of small ruminants (sheep & goat) producing households in Ogun State. A total of 120 small ruminant producing households were selected through a multistage sampling procedure from Ilaro Agricultural Development Zone (ADP) in Ogun State. Data were analyzed using descriptive statistics, Ordinary Least Square (OLS) and Logit regression model. Result showed small ruminant production is male dominated, with an average age of 47 years and average household size of 5 persons. 29.2% of the household head had no formal education. 47.5%, 13.3% and 39.2% of the farmers reared goats only, sheep only and both sheep and goats, respectively. OLS result indicated that small ruminant production were influenced by gender (p<0.01), age (p<0.01), credit access (p<0.1), off-farm income (p<0.05), management system ((p<0.05), and prevalence of diseases outbreak (p<0.01). Analysis of food security status revealed that food security incidence, gap and severity were 0.62, 0.278 and 0.07 respectively. Logit regression result showed that the relevant and significant factors that determined household's food security status were gender, household size, credit access, off-farm activities and herd size. It is concluded from the study that, majority of the farmers were living below the food security line and that small ruminant production contributes positively to household food security status. The study recommended policy intervention that provides credit support, disease prevention and control mechanism for small ruminant farmers.
... This study employed the Foster-Greer-Thorbecke (FGT) indices to determine the incidence of poverty. The standard mathematical expression for FGT poverty measurement (Foster et al., 1984(Foster et al., , 2010 is shown in Equation (1). ...
This study examines the impact of rural transformation on income and poverty in Bangladesh using district‐level panel data from five rounds of the Household Income and Expenditure Survey conducted in 1995, 2000, 2005, 2010, and 2016. Two key indicators are assessed: the share of high‐value agriculture and non‐farm employment. Fixed effects and moments‐quantile regression models are employed to analyze the relationships between rural transformation, income, and poverty, accounting for education, healthcare, electricity access, and land ownership. The results show that both high‐value agriculture and non‐farm employment significantly boost rural income and reduce poverty. Geographic disparities are evident, with high‐value agriculture being most effective in agriculturally favorable regions, while non‐farm employment has a stronger impact in areas with fewer agricultural opportunities. These findings are critical in shaping policies aligned with Sustainable Development Goal 1, which seeks to eradicate poverty. The findings indicate the need for policies to prioritize high‐value agriculture and non‐farm employment to promote income growth and reduce poverty. Expanding agricultural extension services and vocational training is vital for this transformation, alongside targeted investments in infrastructure, education, healthcare, and energy access to enhance rural development and poverty alleviation across Bangladesh.
... For instance, comparing inequality at the market and disposable incomes shows how much redistribution is achieved by direct transfers (Enami et al., 2019;Higgins & Lustig, 2016). Similarly, the impact of BIS on poverty is assessed by tracing the changes in the popular Foster-Greer-Thorbecke (FGT) class of poverty measures across the different income concepts (Foster et al., 1984). For poverty, we use three indicators: headcount index (a measure of the proportion of the population that is poor), the poverty gap ratio (a measure of the depth of poverty-the aggregate poverty deficit of the poor relative to the poverty line) and poverty severity (a measure of the (squared) proportional shortfall from the poverty line). ...
The study investigates the potential welfare effect of basic income support (BIS) in reducing poverty and inequality in South Africa. Using the 2017 labour force survey and a benefit incidence analysis, we consider three BIS scenarios: (i) universal income support for those aged between 18 and 59; (ii) only those who are unemployed receive the benefit; and (iii) only unemployed individuals in extremely poor households defined by the food poverty line receive the benefit. Results show that BIS can reduce poverty and inequality. However, the specific effects of the BIS will depend on the targeting scenario considered. The universal BIS is more costly and has higher leakage, with more benefits going to the non‐poor. However, this universal support has the biggest overall impact on poverty and inequality reduction because more South Africans receive income support under this scenario. Meanwhile, targeting only the unemployed and the impoverished makes the BIS more pro‐poor and progressive, as well as mitigating the leakage of the benefit to the non‐poor. This would, however, require that an appropriate targeting mechanism be in place.
... To achieve the objective stated at the top of this study, we employ the Foster Geer Torbeck index, a poverty incidence baseline constructed by Ref. [94] The general formula is given by equation (10): ...
Deterrent taxes are a crucial policy tool for reducing the consumption of harmful products like tobacco and alcohol. However, assessing dissuasive taxes impact different income groups is important to ensure that their burden is not disproportionately borne by low-income households. This study examines the effectiveness of deterrent taxes as an economic policy tool for reducing tobacco and alcohol consumption in Cameroon. We analyse the impact on household welfare and distributional effects using microsimulation analysis. The data come from the Cameroon Household Living Conditions Survey and the 2022 tax records. Our methodology is based on a dynamic computable general equilibrium (CGE) model enriched with an addiction model. The results indicate that deterrent taxes can significantly reduce the consumption of these harmful products but also have regressive effects on low-income households. In response, we recommend the adoption of a progressive tax structure and the establishment of targeted support programmes to mitigate the negative impact on vulnerable populations.
... These variations reflect differences in average incomes across the three cities. The method described by [57] was used to determine the incidence, gap, and severity of poverty across the study area. ...
Many models depicting the spatial dimensions of poverty are based on cities in developed countries, raising questions about their appropriateness for urban spaces in developing countries. This study evaluates the spatial suitability of these models in understanding poverty distribution and informing alleviation efforts related to Sustainable Development Goal (SDG). One in cities of developing nations. A grid sampling technique in ArcGIS 10.8 was used to select 1098 households across 56 wards in three mid-sized Nigerian cities. Household data were collected through structured questionnaires using GeoODK, and Maxar high-resolution imagery was used to assess urban building density. The Foster-Greer-Thorbecke (FGT) poverty indices and Pearson correlation were applied for analysis. Results showed that over 29 wards had a poverty incidence and gap index greater than 0.20, while poverty severity remained below 0.20 in most wards. High building density was more prevalent in the city’s interior. Significant correlations were found between the income poverty gap (p = 0.005, r = 0.367), poverty severity (p = 0.009, r = 0.346), and building density. The study concludes that these models are suitable for informing poverty alleviation policies in mid-sized cities of developing countries, especially Nigeria.
... Though the frequently used measure of the extent of poverty has been the head count index, the FGT measures are considered to be the standard as they combine the head count index with the poverty gap index and the squared poverty gap index (Yesuf, 2007;MoFED, 2008). Foster, Greer and Thorbecke (1984) lumped these measures into one formula that incorporates the three consistent and additively decomposable (by income class or region) poverty indices. ...
Ethiopia has implemented various fiscal policy reforms in the past decade. Most of these reforms centre on indirect taxes and pro-poor expenditure patterns. This study investigates the economy-wide impacts of these fiscal policy changes on poverty. To this effect, the study used a static computable general equilibrium (CGE) model linked to a micro simulation (MS) model. The CGE model used the 2005/06 social accounting matrix (SAM) and the MS model used the 2004/05 Household Income, Consumption and Expenditure (HICE) survey to investigate household poverty by way of the consumption expenditure changes from the CGE model. The fiscal policies simulated are domestic indirect taxes, government consumption expenditures, and government transfers to households. The findings of the study suggest that the increase in revenue from indirect taxes has worsened the poverty state of households. The results from the CGE model have all shown decline in real GDP, sectorial output, employment and welfare. In contrast, the study found improvements in the poverty state of households as a result of the introduction of various short-run expenditure measures. However, examination of the net effect revealed worsening poverty at the national level in general and for rural households in particular. On the other hand, poverty tended to decline among urban households. The major conclusion is that the tax policy has dominant adverse effect on poverty in the short-run. Thus, policy makers need to take into account these adverse effects and come up with pro-poor spending policies that would protect households from the negative strains while the financing policies go along.
... The dependent variable in Equation 2, which is poverty, will be estimated via measurement poverty headcount. We measured poverty rate based on a methodology of Foster, Gareer and Thorbecke (FGT) (Foster et al., 1984). The most widely used measure is the headcount index, which simply measures the proportion of the population that is counted as poor, often denoted by and described by the following formula: ...
The main goal of this paper is to assess the effect of remittances on economic growth and poverty reduction in case of the Tajik economy. In this paper we use a panel data set on economic growth and poverty estimates (poverty headcount). We found that, on an average, a 1%-point increase in remittances would provoke a 0.21% to 1.8% increase in the average per capita GDP of a Tajik economy. Moreover, our result suggests that there is a long relationship between remittances and poverty reduction in case of Tajik economy. Remittances are found to have a significant impact on the poverty headcount. We found that, on average, an increase in remittances by 1% leads to a reduction in poverty level from 0.7% to 2.82%.
... A multidimensional poverty index (mpi) can be computed using various approaches, such as via theoretical frameworks or modifications (Alkire & Foster, 2011;Foster et al., 1984;Sen, 2006;Onsay, 2022;Sobreviñas, 2017). This index encompasses three key dimensions at the household level: health, education, and standard of living. ...
Indigenous peoples are among the most vulnerable, ignored, and marginalized groups in society. Poverty is the oldest social problem and difficult to counter. The Indigenous people with which the authors live and work, the Agta Tabangnon, suffer from poverty and multidimensional socioeconomic deprivations. Indigenous peoples’ studies are qualitative, while poverty studies are typically generic, exposed to large sampling errors, and intended for nationwide decisions. Therefore, measuring poverty for specific tribes through complete enumeration with multifaceted disaggregation is critical for economic development. There is no comprehensive census specifically designed for Indigenous peoples to encompass the multidimensional aspects of their way of life. Nonetheless, the authors are resourceful in generating useful datasets from their partners. The locale is situated in the poorest district of the poorest province in the poorest region of Luzon, Philippines. The datasets contain multidimensional poverty indicators that are readily usable, along with complementary analytics to visualize the data. They may serve to measure poverty in Indigenous communities across different regions and countries. By utilizing this data, further empirical analysis, regressions, machine learning, and econometric modeling can be conducted. It can be freely utilized to target policies that address the multifaceted poverty and promote economic development within tribal communities.
... Where the vulnerability of a household during the current period Vt is dependent on the probability that future household consumption C(t+1) was less than poverty line (Z). Empirically, building upon the works of Chaudhuri et al. (2002), VEP was obtained by the following procedure: First, the FGT measure of headcount poverty (Foster, et al., 1984) was estimated from household data. Second, household's expected consumption and its variance of the error term was estimated using the 3 stage Feasible Generalized Least Square (FGLS) estimation procedure. ...
The study assessed persistence and vulnerability to poverty among rural households in Nigeria. The Nigeria - Living Standards Survey (NLSS) of year 2018 – 2019 dataset was used. Employing 3-stage Feasible Generalized Linear Regression (FGLS) to estimate vulnerability to poverty; the average age of the respondents stood at 48 years with average household size of 6 and dependant of 4 on average. The result further showed that higher proportion of the rural households were vulnerable to poverty. Less than half (44%) of the households were highly vulnerable to poverty and 34.5% were moderately vulnerable to poverty. The expected poverty was higher (71.4%) than the observed poverty (67.1%), indicating that higher poverty is imminent in future. Furthermore, the study shows that the coefficient of primary education (p = 0.075), access to credit (p = 0.000), electricity (p = 0.033), farm asset (p = 0.000), and remittance (p = 0.043) indicated a negative sign and significantly influence vulnerability to poverty. In conclusion, poverty will persist and increase with rise in age, dependency ratio, covariate and idiosyncratic shocks, lack of formal education, distance to health facility and type of toilet used by the respondents. The study therefore recommends prompt implementation of measures that will reduces shocks specific to regions in the country.
... Le taux de pauvreté, l'indice de l'intensité de la pauvreté et les indices de la pauvreté de FGT sont les plus utilisés dans la littérature comme des indicateurs communs de mesure de la pauvreté (Duclos et Araar, 2006 ;Foster et al. 1984). Ces indicateurs sont utilisés dans cet article pour analyser la pauvreté en ressources productives des entreprises agricoles du Bénin. ...
La disponibilité en ressources productives constitue le socle pour toute entreprise. Cette étude a pour objectif d’analyser la disponibilité en ressources productives des entreprises agricoles au Bénin. Elle porte sur un échantillon de 458 entreprises, agricoles sélectionnées de façon aléatoire à partir d’une liste d’entreprises agricoles. Les disponibilités en ressources et leur concentration, le taux de pauvreté, l’indice de l’intensité de pauvreté, les indices de FGT de la pauvreté, la courbe de Lorenz et le coefficient de Gini ont été utilisés pour appréhender la pauvreté en ressources des entreprises agricoles béninoises. Les résultats montrent une forte disparité de la disponibilité en ressources productives de ces entreprises. Les indices d’inégalité de Gini sont estimés respectivement à 0,68 ; 0,69 ; 0,71 et 0,57 pour les superficies disponibles et exploitées, et pour les mains-d’œuvre permanente et occasionnelle et les courbes de Lorenz construites. Pour réduire les inégalités en ressources productives, les entrepreneurs agricoles non pauvres devront transférer près de 53 % de leur propriété foncière aux entrepreneurs pauvres. L’Etat devra élaborer une politique efficace d’accès au foncier en faveur des entreprises agricoles béninoises.
... The Foster, Greer and Thorbecke (FGT) Index was developed in 1984 to find out the incidence, depth and severity of poverty and it is known as a generalized measure of poverty (Foster et al., 1984). We apply the FGT Index in our analysis. ...
An attempt has been made here to examine the probable indicators associated with the child underweight belonging to the age group 0–5 years across different socio-ethnic groups in West Bengal, India using National Family Health Survey NFHS-V (2019–2021) data. Multilevel logistic regression models are employed to examine the direct and joint effects of child background such as gender, birth weight etc., maternal characteristics such as mothers’ education, BMI, Anemia status etc., and socioeconomic characteristics like wealth class, caste etc. on the underweight children. We find that indicators from different axes such as gender, birth weight, place of delivery, mother’s education, mother’s BMI level, household wealth quintiles and social class significantly impact the probability of being underweight among children. The findings of the interactive variables suggest that female children belonging to the poorest of the poor families and disadvantaged groups residing in rural areas exhibit a higher probability of being underweight. The interactive and joint effects results suggest implementing disaggregated public health policies. We recommend integrating the existing health policies to the poverty eradication programme to obtain a socially desirable result of nutritional equity among the children.
... Esta investigación se fundamentó en el planteamiento teórico que establece un encadenamiento causal entre las seis carencias sociales, el desarrollo económico, los ingresos f iscales, el gasto social y la desigualdad económica, que sumados al crecimiento del PIB per cápita, a un correcto gasto social y la reducción sostenida de desigualdades económicas, deberían reducirse de manera sustancial las carencias sociales, como han encontrado otros estudios para el caso de la pobreza (Ferreira et al., 2010;Foster y Thorbecke, 1984), pues la literatura revela una alta correlación entre el incremento del ingreso -medido por el PIB-, los mecanismos de transmisión de los benef icios del crecimiento económico y el gasto gubernamental como mecanismos efectivos para reducir los niveles de pobreza (Barro, 1991;Baulch y McCulloch, 2000;Montalvo y Ravallion, 2010;Warr, 2002). ...
De acuerdo con la teoría de crecimiento endógeno, se esperaría la presencia de spillovers, derivados de invertir en infraestructura social, que muestren el mejoramiento de las carencias sociales y disminución de la pobreza, pues la oferta de servicios públicos crea efectos spillovers entre municipalidades vecinas, de ahí la relevancia de comprender hasta qué punto las unidades geográficamente cercanas (estados) se influyen para abatir las carencias sociales. Por lo anterior, esta investigación centró su atención en el FAIS en su vertiente estatal, y tuvo como objetivo: identificar si a través de las obras y acciones de infraestructura social realizadas con el Fondo de Infraestructura Social para las Entidades (FISE) se genera un efecto de desbordamiento (spillover) que abata las carencias sociales.
... It is used to analyze the incidence, depth, and severity of consumption poverty. As one of the measures proposed by Foster et al. (1984), it can generally be expressed as ...
... Even before Foster et al. (1984) proposed a class of decomposable poverty measures, now known simply as the FGT poverty measures, certain desirable attributes for poverty measures had been discussed in the literature. Sen (1976) highlights some of the shortcomings of the headcount ratio, such as its violation of the monotonicity and transfer axioms. ...
Research on Quality of Life (QOL) encompasses a variety of dimensions, with some studies examining the factors that influence QOL and others focusing on methods to enhance it. One of the challenges in this field is understanding how to improve QOL across different economic contexts. Within this spectrum, capability stands out as a key determinant of QOL. The substantial correlation between capability and QOL has been established by numerous previous studies. This research primarily explores aspects related to capability. The goals of this study were manifold. First, we aimed to investigate the link between poverty and various capability variables. Second, we intended to assess the relationship between capability and QOL. The third objective was to introduce grit as a mediator in the capability-QOL relationship. Lastly, we explored the comparison between two classes within the overall model. The Structural Equation Modeling (SEM) analysis indicated that capability variables do have an impact on QOL in the baseline model. However, when comparing models, the one representing individuals under the poverty line showed no significant relationship between capability and QOL. The introduction of a mediation variable led to the identification of a fully mediated model in the context of poverty within this study. The distinctive contribution of this research is highlighted by the mediation findings between the two models, underscoring the nuanced interplay between capability, grit, and QOL in the backdrop of economic challenges.
Durante los últimos años, Bolivia ha tenido avances notables en términos de reducción de pobreza; sin embargo, muchos hogares aún viven con bajos ingresos o enfrentan privaciones en otros aspectos. Por tal motivo, el objetivo de esta investigación consiste en estimar la evolución de la pobreza, tanto en términos multidimensionales como monetarios, y los efectos del crecimiento y la distribución del ingreso en Bolivia desde 2015 hasta 2022. Para el cálculo de la pobreza multidimensional, se emplea la metodología de Alkire y Foster (2011). Para estimar la pobreza monetaria se utiliza el método de línea de pobreza. Los efectos de crecimiento y distribución se evalúan con la metodología de Datt y Ravallion (1992). Los resultados muestran que, aunque la pobreza multidimensional se redujo entre 2015 y 2022, cerca de un 45% de los hogares del país sufren de privaciones simultáneas relacionadas con aspectos diferentes al monetario. En cuanto a la pobreza monetaria, entre 2015 y 2019 esta se redujo de un 38,6% a un 37,2%; en 2020 esta aumentó a un 39%, y en 2022 disminuyó a un 38,1%. El resultado más importante del efecto crecimiento y distribución del ingreso señala que la pobreza en Bolivia es más sensible al crecimiento económico.
Poverty is the most devastating global problems catching the attentions of development scholars. The issue of poverty was enshrined in the first goal of the Millennium Development Goals and the Sustainable Development Goals. This study was conducted on the determinants of consumption poverty in Fitche Town, Ethiopia, using cross-sectional survey. To this effect, two kebeles were randomly selected out of the seven kebeles of the town. Likewise, 372 sampled households were selected out of the 5300 total households of the selected kebeles through a stratified simple random sampling technique. Using the statistical model developed by Foster, Greer and Thorbecke, results of the study reveals that 22.4 percent of sample households fall below the poverty line. Likewise, poverty gap and severity were 4.5 and 1.6 percent, respectively. Result of the regression model reveals that sex of household, family size, educational status, dependency ratio, shelter ownership, persons per room and household shocks were the determinants of poverty in the study area. The study result is relevant to inform policy interventions. As poverty in the study town is worse than the national urban centers, the government of Ethiopia, hand-in-hand with the local government, should address the socioeconomic and demographic challenges that intensify poverty.
Objective
The aim of this study is to analyze complementary feeding practices, to assess the extent to which minimum dietary diversity (MDD) recommendations are being met in the population studied and to study factors that influence the achievement of MDD.
Design
We pooled individual level data form the Demographic and Health Surveys (DHS) and Multi Indicator Cluster Surveys (MICS). We apply methods from poverty measurement to identify individual gaps towards achieving minimum dietary diversity (MDD). We further identify food groups that separate children who achieve MDD from those who do not.
Setting
West and Central Africa.
Participants
62,257 children aged 6 and 23 months.
Results
82.0 percent of children do not achieve and on average are lacking 2.5 out of five required food groups. For 19.0 percent of children the gap to MDD is one food group and for 23.7 percent of children the gap is two food groups. Consumption of eggs, other fruits and vegetables as well as legumes and nuts, is particularly low among children who are not achieving MDD. More than 90 percent of children who do not achieve MDD do not consume these food groups compared to around half of children who achieve MDD.
Conclusions
Overall MDD is low, but there is large potential for improving MDD achievement if food consumption can be increased by one or two food groups. Available, affordable and culturally accepted food groups are identified that could be prioritized in interventions to close this gap.
This study examines the impact of the Human Development Index (HDI), labor force participation, and infrastructure expenditure on poverty levels in Aceh Province, with zakat, infaq, and Sadaqah serving as moderating variables. Utilizing secondary data, the research employs panel regression methods and Moderated Regression Analysis (MRA) to analyze data collected from 23 districts and cities in Aceh Province over the 2008–2022 period. The findings reveal that the HDI and labor force participation rate do not significantly influence poverty in Aceh. However, infrastructure expenditure demonstrates a negative and statistically significant effect, indicating its potential to reduce poverty in the region. Furthermore, zakat, infaq, and sadaqah can moderate the effects of HDI and infrastructure expenditure on poverty but fail to moderate the relationship between labor force participation and poverty. Based on these results, it is recommended that the Aceh Provincial Government adopt more targeted and comprehensive strategies to alleviate poverty. Efforts should focus on enhancing the HDI and labor force participation rates, alongside optimizing the collection and allocation of zakat, infaq, and Sadaqah, and increasing infrastructure investment. Such measures can potentially address the persistent issue of poverty in Aceh Province more effectively
Poverty is the oldest social problem that ever existed and is difficult to reverse. It is multidimensional and unmeasurable. Thus, measuring by decomposing rural multidimensional poverty is critical. Most poverty studies are usually generic, exposed to large sampling errors, and intended for macroeconomic decisions. Thus, measuring poverty for a specific locality with various configurations (15) is critical for economic development. The paper combines predictive analytics and advanced econometrics to decompose poverty at the micro-level by utilizing the Community-Based Monitoring system at complete enumeration (L = 34, S = 4). Logistic Regression (78) Models with 19 Independent Variables and 12 Intervening Variables were fitted. Headcount Analysis (0.2138–0.9845), Poverty Gap (0.2228–0.0502), Severity statistics (0.0723–0.0168) and Watts Index (0.2724–0.0618) are scrutinized. Poverty levels vary by location; a significant fraction of the population (P0i = 68.50%, P0f = 55.80%) and households (P0i = 63.70%, P0f = 50.70%) live below the poverty line and food threshold. It has been revealed that poverty is extreme in Isarog (i = 0.7793), moderate in Poblacion (p = 0.4019), intense in Ranggas (r = 0.6542), and severe in Salog (s = 0.6353). Multidimensional variables (13VAR) significantly predict poverty outcomes (p-value = 0.0000, PseudoR2 = 0.75). Moreover, intervening variables have been impacting poverty across all locals. All models tested are significant across all sectors and correctly predicted by the model classifications (Estat = 73.29–74.12%). Poverty is multifaceted; thus, it requires different interventions. Finally, policy proposals (54) were outlined to alleviate poverty and promote local economic development.
The objective of this paper is to establish a general asymptotic representation ( GAR ) for a wide range of statistics, employing two fundamental processes: the functional empirical process ( fep ) and the residual functional empirical process introduced by Lo and Sall (2010a, 2010b), denoted as ( lrfep ). The functional empirical process ( fep ) is defined as follows: where X, , , is a sample from a random d-vectors X of size (n+1) with and h is a measurable function defined on such that is finite. It is a powerful tool for deriving asymptotic laws. An earlier and simpler version of this paper focused on the application of the ( fep ) to statistics that can be turned into an asymptotic algebraic expression of empirical functions of the form: However, not all statistics, in particular welfare indexes, conform to this form. In many scenarios, functions of the order statistics are involved, resulting in L-statistics. In such cases, the ( fep ) can still be utilized, but in combination with the related residual functional empirical process introduced by Lo and Sall (2010a, 2010b). This combination leads to general asymptotic representations (GAR) for a wide range of statistical indexes where is the indicator function of the interval of , and is a measurable function of . Such representations, when associated with copulas, provide a robust framework for comparing indices over the time or across different areas. The comprehensive theory is presented alongside explicit examples, facilitating the utilization by researchers.
Gender disparities persist within the aquaculture value chain, affecting women‘s
empowerment and overall food security. Multistage sampling techniques were used in
selecting 231 catfish farmers for the study. Data were collected with the aid of structured
questionnaire and were subjected to descriptive statistics such as frequency, percentage and
mean as well as inferential statistics such as Food Security Index and Logistic regression.
Results revealed that average age for catfish farmers were 42, 43 and 40 years for the pooled,
male and female respectively (p<0.10). The distribution of catfish farmers according to years
of fishing experience showed that the mean farming experience of the fish farming were 11,
12 and 9 years for the pooled, male and female respectively (p<0.05). The results showed that
while food insecurity affects households led by men and women equally, it affects the latter
group more severely. Household size (p<0.10), education (p<0.001), fishing experience
(p<0.05), climate effects (p<0.05), were found to be significant factors influencing food
security status for families headed by men and women, respectively. The study concluded
that food insecurity affects female households‘ more than male households. The study
recommends that introduction of programmes educating the catfish farmers about climate
change, boosting increase catfish production through adaptive capacity should be encouraged
while government and fishing stakeholders should implement gender-responsive food
policies, programmes, and institutional frameworks.
This study examines the relationship between Gross Domestic Product (GDP) per capita and the Global Hunger Index (GHI) over the past two decades. By analyzing data from various countries across different income levels, the research explores how economic growth intersects with hunger dynamics. The study utilizes reputable sources, including reports from the Food and Agriculture Organization (FAO), the International Food Policy Research Institute (IFPRI), and the World Bank. The findings highlight that while GDP per capita is an important factor in reducing hunger, other elements such as income inequality, education, health expenditure, agricultural productivity, and governance significantly influence hunger outcomes. The research underscores the necessity for holistic approaches that integrate economic growth with social equity and effective policy interventions to eradicate hunger globally.
The present study seeks to examine the livelihood pattern, incidence of poverty and multiple deprivation among the tribal communities or Scheduled Tribes (STs) of Odisha by using secondary data collected from the various rounds of the National Sample Survey (NSS), Census of India reports, District Level Household and Facility Survey (DLFS) reports, etc. It evaluates the contributions of the different sources of livelihood on level of living, quality of life and economic well-being of the tribals. Methodologically, the study employs the Foster, Greer and Thorbecke (FGT) class of poverty measures to examine the incidence and magnitude of poverty among the tribals. It finds a strong relationship between livelihood pattern and poverty among them. Though there has been a decline in the incidence of poverty (head count ratio) among the tribals over a period of time, the rate of decline has been slower among the tribal communities than the other social classes. The tribals are confronted with low levels of income and higher levels of poverty due to their subsistence level of livelihood. Most of them are engaged in low-paid works, and suffer from chronic poverty and multiple deprivation. Finally, the study concludes with suggestions on how potential policy options can improve the livelihood condition of the tribals and redress the problem of heavy incidence of poverty among them.
Poverty is a major challenge faced by many households in Nigeria, which is a result of inadequate income to cater for household needs. As a source of additional income, remittance helps fulfil the purpose of catering to needs. It serves as a source that enhances livelihood diversification to generate more income. The study's general objective was to determine the effect of remittance on livelihood diversification and poverty. The study was carried out in the six geopolitical zones in Nigeria. Secondary data collected from General Household Survey data, 2015 were used. The data collected were analysed using the Simpson index, Logit regression model, Foster-Greer-Thorbecke (FGT), and Tobit regression model. Remittance, Gender, Age, Marital Status, Household size, Farm size, and Distance to market significantly influenced livelihood diversification. Poverty was influenced by Gender, Marital Status (married), Years of formal education, household size, Farm size, occupation, and access to credit. Remittance was not found to significantly influence poverty because only a few had access to it. Remittance access should be improved as increased access and a greater proportion of remittance in the study area would significantly increase livelihood diversification and indirectly reduce poverty.
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