Determinants of Poverty: Is Age Non-Linearly Related with Poverty? Evidence from Sri Lanka

Deyshappriya, N.P. Ravindra; Minuwanthi, R.W.W.K.

doi:10.18488/journal.1.2020.104.181.192

Cited by 7 publications

(9 citation statements)

References 20 publications

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“…This may be due to historical, economic, political, and social factors that impact the income and asset-generating opportunities of these vulnerable groups. This effect has been widely documented in the literature (Canelas and Salazar 2014;De Silva 2008;Jayathilaka et al 2016;Ravindra Deyshappriya and Minuwanthi 2020).…”

Section: Ethnicitymentioning

confidence: 63%

“…In this way, it is to be expected that the relationship between poverty and age is not linear, but that poverty is higher at a very young age, decreases in middle age, and then increases in old age again (Garza-Rodríguez 2015). Among the authors who have found this U-pattern are Lekobane and Seleka (2017), D'Ambrosio et al (2011), Ravindra Deyshappriya and Minuwanthi (2020 and Rodrigues and Rueanthip (2019).…”

Section: Age Of Household Headmentioning

confidence: 93%

“…This phenomenon, known as the feminization of poverty (Pearce 1978), can be explained by discrimination against women in the labor market but also because women tend to have less education than men, which is why they receive less income in the labor market (Garza-Rodríguez 2015). Most studies have found evidence in favor of the feminization of poverty (Biyase and Zwane 2018;Chen and Wang 2015;Iqbal et al 2020;Ravindra Deyshappriya and Minuwanthi 2020;Teka et al 2019). Some studies, such as that of Jiménez Pozo et al (2006) for the case of Bolivia do not find evidence that female headship of the family increases poverty, as did (Székely 1998) for the case of Mexico.…”

Section: Empirical Evidencementioning

confidence: 99%

“…The absence of adequate social security systems and low savings in developing countries tends to increase the fertility rate, which causes large household sizes with more children, increasing the dependency burden and poverty (Garza-Rodríguez 2015). Many researchers (Artha and Dartanto 2018;Gounder 2013;Lekobane and Seleka 2017;Ogutu and Qaim 2019;Ravindra Deyshappriya and Minuwanthi 2020;Sekhampu 2013) have found a direct relationship between household size and poverty. For the case of Mexico specifically, Garza-Rodríguez (2015), Székely (1998), Serratos (2015), and Ramirez (2006) also found a strong association between poverty and household size.…”

Section: Household Sizementioning

confidence: 99%

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Determinants of Poverty in Mexico: A Quantile Regression Analysis

et al. 2021

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Most studies on the determinants of poverty do not consider that the relative importance of each of these determinants can vary depending on the degree of poverty suffered by each group of poor people. For Mexico’s case, the studies carried out so far do not contemplate this approach, even though there is wide variation in the degree of poverty among the different groups of the poor. Investigating these differences is important to design better policies for fighting poverty, which consider how each variable that explains poverty affects each group of people who suffer from poverty differently. This article examines the determinants of poverty for Mexican households. Using data from the Mexican National Household Income and Expenditure Survey (ENIGH) 2018, the study estimates a probit model and a quantile regression model to examine the extent to which the determinants of poverty vary across the poverty spectrum. The results from the probit model indicate that households with more than one member, having a female head, or speaker of an indigenous language are more likely to be poor. The results obtained in the quantile regressions indicate that there are significant differences with the results of the simple ordinary least squares model, especially for households in extreme poverty but also for the other income categories analyzed for several of the explanatory variables used in the models. Households in the categories extremely poor and deeply poor are most affected if they are in the southern region or if the household head speaks an indigenous language or is an elderly person. It is observed that achieving a higher educational level is an effective way to increase income across the poverty spectrum.

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Section: Ethnicitymentioning

confidence: 63%

Section: Age Of Household Headmentioning

confidence: 93%

Section: Empirical Evidencementioning

confidence: 99%

Section: Household Sizementioning

confidence: 99%

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Determinants of Poverty in Mexico: A Quantile Regression Analysis

et al. 2021

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“…Asset indices according to Filmer and Scott (2008) are of the basic form: The study used the Aggregate Asset Index which is created by using productive assets and consumer assets of a household. The independent variables of Table 1 and Table 2 were selected based on the availability of data in HIES (2016) and referring to previous studies (Ranthunga and Gibson, 2014;Dharmadasa and Polkotuwa, 2016;Deyshappriya and Minuwanthi, 2020).…”

Section: Welfare Measurementmentioning

confidence: 99%

Income diversification and household welfare in Sri Lanka

Senevirathna,

Dharmadasa

2021

J. Agric. Val. Add.

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Income diversification is globally considered as an effective way to reduce income risk and also to enhance household welfare especially in developing countries. However, much attention has not been paid to study the welfare implications of income diversification in Sri Lanka. By taking data of a nationally representative sample of 21,756 households of Household Income and Expenditure Survey 2016, this study attempted to examine the welfare implications of income diversification of households in Sri Lanka while identifying the determinants of income diversification. Data were analyzed using descriptive statistics, probit regression, and ordinary least square regression. Results suggest that income diversification significantly increased the welfare of Sri Lankan households. More than half of the households from the total population have diversified their income portfolio. Further, we explored that rural and estate households appeared to have a more diversified income portfolio relative to their urban counterparts, and households that depend on permanent employment income were less likely to diversify their income. Results depicted that the major determinants of household welfare and income diversification decision in Sri Lanka are human capital-related factors and regional differences. The study strongly recommends implementing programmes for entrepreneurial development, human capital development, and female empowerment which deserves special attention in the design of national poverty reduction strategies and enhancing the household welfare.

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The effect of local climatic conditions on household consumption: a case study of South Africa

Mudzingiri,

Mudiriza,

Jana

et al. 2024

Humanit Soc Sci Commun

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The article explores the causal effect of local climate conditions on household consumption in South Africa. The climatic conditions are represented by monthly average temperature and precipitation. The study utilises the nationally representative 2017 National Income Dynamics Study (NIDS), wave 5 data and 2017 Climate Research Unit (CRU) climate data. The parsimonious quantile regression shows that climatic conditions (precipitation, temperature, wet days, and cloud cover) impact household per capita consumption. The quadratic quantile regression model analysis shows that household per capita consumption is convex in precipitation. Below the turning point, increased precipitation is associated with decreased household per capita consumption. Above the turning point, increased precipitation is related to increased household per capita consumption. Regions that receive very low precipitation or experience extreme temperatures (very cold or very hot) require tailor-made interventions to alleviate consumption. When we control for household characteristics, the impact of climatic conditions on household per capita consumption is weak. Providing inclusive development policies and programmes can mitigate the impact of climatic conditions on household per capita consumption.

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Determinants of Poverty: Is Age Non-Linearly Related with Poverty? Evidence from Sri Lanka

Cited by 7 publications

References 20 publications

Determinants of Poverty in Mexico: A Quantile Regression Analysis

Determinants of Poverty in Mexico: A Quantile Regression Analysis

Income diversification and household welfare in Sri Lanka

The effect of local climatic conditions on household consumption: a case study of South Africa

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