Income inequality of households in Poland: A subgroup decomposition of generalized entropy measures

Muszyńska, Joanna; Wędrowska, Ewa

doi:10.15611/eada.2018.4.03

Cited by 9 publications

(17 citation statements)

References 21 publications

(30 reference statements)

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“…This was also true in our study, as malnutrition and food insecurity was also more prevalent among rural children belonging to the lowest socioeconomic class. Decomposed results of this study showed within group income variations to be a strong indicators of explaining socioeconomic inequalities, the latter findings also concur with results of the Poland study [31].…”

Section: Discussionsupporting

confidence: 89%

“…The study focused on two household characteristics in assessing income inequalities thus; location of the household and socioeconomic status. Economic inequalities among regions and socioeconomic classes within a country may can be attributed as the driving force of income inequalities as uneven progress in development across regions can result in the diversification of income and worsening income of inequalities [31].…”

Section: Decomposition By Residencementioning

confidence: 99%

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Prevalence and Socioeconomic inequalities trends in child health comparing within and between group inequalities: Food insecurity and malnutrition in Zimbabwe

Lukwa

Siya

Zablon

et al. 2020

Preprint

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BackgroundInequalities in child health remain a threat to this global efforts to achieve universal health coverage. We assessed socioeconomic inequalities in child health focusing on malnutrition and food insecurity in Zimbabwe.MethodsWe used Demographic Health Survey (DHS) data sets of 2010\11 and 2015. Food insecurity in children was determined based on the WHO dietary diversity score. Minimum dietary diversity was defined by a cut- off point of >4 therefore, in this study children with less than 3 of the 13 food groups were defined as food insecure. Malnutrition was assessed using weight for age Z-score, with children whose weight-for-age Z-score below minus two standard deviations (-2 SD) from the median considered malnourished. Concentration indices were computed to understand if malnutrition was dominant among the poor or rich. The study used the Theil index and decomposed the index by population subgroups (geographical clusters and socioeconomic status).ResultsOver the study period, malnutrition prevalence increased by 1.03 percentage points (p.p) [2010/11(3.73%); 2015(4.76%)], while food insecurity prevalence decreased by 4.35p.p [2010/11(78.29%);2015(73.94)]. Prevalence of malnutrition and food insecurity increased by; 9.6p.p and 2p.p among poor children & 10.23p.p and 0.5p.p among rural children. Children from wealthy households were more likely to be food secure and children from poor households were more likely to be nutritious. For nutrition status, socioeconomic inequality gaps appeared to be widening as the concentration indices between the two time periods increased, while for food security status socioeconomic inequality gaps appeared to be contracting as the concentration indices between the two time periods reduced. Food security status showed contracting socioeconomic inequality gaps in both geographical clusters (urban & rural), while for nutrition status there were widening socioeconomic inequality gaps among urban children and contracting socioeconomic inequality gaps among rural children.ConclusionWithin-group inequalities are driving most of the socioeconomic inequalities in nutritional status and food security status among children in Zimbabwe. There is need for policies that focus on addressing within-group inequalities and direct food security interventions for food insecure children through availing food aid parcels especially for children from poor households irrespective of where they reside.

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Section: Discussionsupporting

confidence: 89%

Section: Decomposition By Residencementioning

confidence: 99%

Prevalence and Socioeconomic inequalities trends in child health comparing within and between group inequalities: Food insecurity and malnutrition in Zimbabwe

Lukwa

Siya

Zablon

et al. 2020

Preprint

View full text Add to dashboard Cite

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“…Decomposed results of this study showed within group household wealth variations to be strong indicators explaining socioeconomic inequalities, the latter ndings also concur with results of other studies [15,54]. More recently, a study used Shapley decomposition to estimate the relative contributions of circumstances and analysed patterns of inequalities in health relative to nutrition outcomes among children under ve in Tunisia [19].…”

Section: Discussionsupporting

confidence: 88%

“…The study focused on two household characteristics in assessing health inequalities: location of the household and socioeconomic status/class. Socioeconomic inequalities among regions and socioeconomic classes within a country can be attributed as the driving force inducing uneven progress of economic development across regions [54].…”

Section: Decomposition Analysismentioning

confidence: 99%

Socioeconomic inequalities in food insecurity and malnutrition among under-five children: within and between-group inequalities in Zimbabwe

Lukwa

Siya

Zablon

et al. 2020

Preprint

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BackgroundFood insecurity and malnutrition in children are pervasive public health concerns in Zimbabwe. Previous studies only identified determinants of food insecurity and malnutrition with very little efforts done in assessing related inequalities and decomposing the inequalities across household characteristics in Zimbabwe. This study explored socioeconomic inequalities trend in child health using regression decomposition approach to compare within and between group inequalities.MethodsThe study used Demographic Health Survey (DHS) data sets of 2010\11 and 2015. Food insecurity in under-five children was determined based on the WHO dietary diversity score. Minimum dietary diversity was defined by a cut- off point of >4 therefore, children with less than 3 of the 13 food groups were defined as food insecure. Malnutrition was assessed using weight for age (both acute and chronic under-nutrition) Z-scores. Children whose weight-for-age Z-score below minus two standard deviations (-2 SD) from the median were considered malnourished. Concentration curves and indices were computed to understand if malnutrition was dominant among the poor or rich. The study used the Theil index and decomposed the index by population subgroups (place of residence and socioeconomic status).ResultsOver the study period, malnutrition prevalence increased by 1.03 percentage points, while food insecurity prevalence decreased by 4.35 percentage points. Prevalence of malnutrition and food insecurity increased among poor rural children. Theil indices for nutrition status showed socioeconomic inequality gaps to have widened, while food security status socioeconomic inequality gaps contracted for the period under review.ConclusionThe study concluded that unequal distribution of household wealth and residence status played critical roles in driving socioeconomic inequalities in child food insecurity and malnutrition. Therefore, child food insecurity and malnutrition are greatly influenced by where a child lives (rural/urban) and parental wealth.

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“…Today, entropy is part of the methodological output of world geography and application in many and varied research field studies (Batty, , , ; Wilson, ). In Poland, an upsurge of interest in the entropy method can be observed in spatial econometrics (Muszynska & Wędrowska, ). In Polish socioeconomic geography, the latest works on the use of entropy include a study of changes in the land‐use pattern in metropolitan areas (Werner et al., ) and an analysis of the convergence of regional development (Kudrycka, ).…”

Section: Uncertainty Measurement In Economic Disparitymentioning

confidence: 99%

Shannon Entropy for Quantifying Uncertainty and Risk in Economic Disparity

Mishra¹,

Ayyub

2019

Risk Analysis

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The rise in economic disparity presents significant risks to global social order and the resilience of local communities. However, existing measurement science for economic disparity (e.g., the Gini coefficient) does not explicitly consider a probability distribution with information, deficiencies, and uncertainties associated with the underlying income distribution. This article introduces the quantification of Shannon entropy for income inequality across scales, including national-, subnational-, and city-level data. The probabilistic principles of Shannon entropy provide a new interpretation for uncertainty and risk related to economic disparity. Entropy and information-based conflict rise as world incomes converge. High-entropy instances can resemble both happy and prosperous societies as well as a socialist-communist social structure. Low entropy signals high-risk tipping points for anomaly and conflict detection with higher confidence. Finally, spatial-temporal entropy maps for U.S. cities offer a city risk profiling framework. The results show polarization of household incomes within and across Baltimore, Washington, DC, and San Francisco. Entropy produces reliable results at significantly reduced computational costs than Gini coefficients.

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Income inequality of households in Poland: A subgroup decomposition of generalized entropy measures

Cited by 9 publications

References 21 publications

Prevalence and Socioeconomic inequalities trends in child health comparing within and between group inequalities: Food insecurity and malnutrition in Zimbabwe

Prevalence and Socioeconomic inequalities trends in child health comparing within and between group inequalities: Food insecurity and malnutrition in Zimbabwe

Socioeconomic inequalities in food insecurity and malnutrition among under-five children: within and between-group inequalities in Zimbabwe

Shannon Entropy for Quantifying Uncertainty and Risk in Economic Disparity

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