Determinants of Poverty and Their Variation Across the Poverty Spectrum: Evidence from Hong Kong, a High-Income Society with a High Poverty Level

Peng, Chenhong; Fang, Lue; Wang, Julia Shu‐Huah; Law, Yik Wa; Zhang, Yi; Yip, Paul

doi:10.1007/s11205-018-2038-5

Cited by 33 publications

(37 citation statements)

References 61 publications

(79 reference statements)

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“…Research on the determinants of poverty has developed under three different categories: macro or structural level, micro or individual level, and contextual level (Peng et al 2019). The structural level approach asserts that there are economic, social, and political factors that cause people to have limited opportunities and resources (Bradshaw 2007), while the micro-level approach holds that poverty can be explained by individual characteristics and behavior.…”

Section: Theoretical Perspectives On Povertymentioning

confidence: 99%

“…These studies have used the logistic regression method, which distinguishes only whether the household is poor or not but does not analyze the potentially different effects of each explanatory variable according to the income of the poor. To address this problem, recent studies (Habyarimana et al 2015;Heshmati et al 2019;Kedir and Sookram 2013;Peng et al 2019) have used quantile regressions to investigate whether the determinants of poverty vary along the income distribution of the poor. The purpose of including a quantile regression approach in the analysis of the determinants of poverty is to allow for the possibility of differential effects of these determinants across the different quantiles of the income distribution (Peng et al 2019).…”

Section: Introductionmentioning

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: Theoretical Perspectives On Povertymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Determinants of Poverty in Mexico: A Quantile Regression Analysis

et al. 2021

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“…Previous studies have investigated the determinants of poverty and energy poverty separately. Key factors found to have an impact on poverty include the education status of household members (Chen & Wang, 2015; Peng et al, 2019; Rahman, 2013) and health status (Peng et al, 2019; Weaver, 2012). These two combine to show the strength of the household's human capital.…”

Section: Literature Reviewmentioning

confidence: 99%

Are energy‐poor households also poor? Evidence from Ghana

Adusah‐Poku

Adjei‐Mantey

Kwakwa

2021

Poverty & Public Policy

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Poverty and energy poverty are parts of the Sustainable Development Goals (SDGs). The former has been extensively covered in the literature, whereas the latter has not been given the necessary attention until the last decade. In this paper, we use multidimensional measures of energy poverty and poverty to ascertain whether energy‐poor households are also poor, and vice versa. In addition, the study seeks to examine the factors responsible for poverty and energy poverty. This paper uses data sets constructed from the two most recent nationwide household surveys in Ghana (GLSS VI and GLSS VII samples). We find substantial differences in the incidence and index of multidimensional energy poverty and multidimensional poverty by subgroup demographic characteristics. Further, we find that households belong to different categories of poverty and energy poverty status. Our multinomial regression results reveal that household size, marital status, educational background, residential area, age, employment, and gender significantly predict the household's multidimensional poverty and energy poverty status. We recommend massive investment in renewable energy, to make cleaner energy readily available for Ghanaians. In addition, the Ghanaian government should pursue sustainable employment and job creation avenues, directed toward an improved standard of living for the population.

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“…The panel survey involved conducting face-6 to-face interviews with the household head to elicit a variety of information; Each interview lasted approximately minutes. Content of the survey and details of the sampling strategy has been reported elsewhere [40]. The first wave of the panel survey was conducted between September 2015 and April 2016, in which 2,002 households were recruited.…”

Section: Samplementioning

confidence: 99%

Valuing the impact of Self-rated Health and Social Support on life satisfaction among Hong Kong Chinese population

Chan

2021

Preprint

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Background Research has highlighted that satisfaction in health and social support are key areas of life affecting individual’s wellbeing. Many social and public health initiatives use these two intervention mechanisms to improve individual’s wellbeing. For the purpose of cost-benefit assessment, there has been growing interest in expressing these intervention effects in economic terms. However, only a handful of studies have ever estimated these effects in economic terms, and none of which examined in a Chinese context. The aim of this study is to extend this line of valuation work to estimate the implicit willingness-to-pays on the effects of improving individuals’ self-rated health status (SRH) and social support (SS) on their life satisfaction in the Chinese population. Methods Using individual’s life satisfaction data from a two-wave representative panel survey in Hong Kong (n = 1,109), this study first conducted a cross-lagged analysis with structural equation modelling technique to examine the causal effects of SRH and SS on life satisfaction, while simultaneously adjusting their reverse causal influences. The use of this cross-lagged approach was the effort to minimising the endogeneity problem. Then, substituting the respective estimates to the formulae of compensating surplus, the marginal rate of substitution of SRH and SS with respect to individual’s equivalised monthly household were estimated and were then expressed as the willingness-to-pays on the effect of improving individuals’ SRH and SS on their life satisfaction. Results The cross-lagged analysis ascertained the casual effects of SRH (β = 0.078, 95%CI: 0.020, 0.151) and SS on individuals’ satisfaction with life. The sample’s marginal rate of substitution of SRH and SS were found to be 1.28 (95%CI: 0.43, 2.15) and 1.36 (95%CI: 0.23, 2.49) respectively. Translating into the concept of compensating surplus, the implicit monetary values of improving the sample’s SRH from “poor health” to “excellent health” and their SS from “little support” to “a lot of support” are equivalent to an increase in their equivalised monthly household income by HK$56,000 and HK$39,400 respectively. Conclusions This study has implications for the cost-benefit assessment in wellbeing initiatives for the Chinese population.

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Determinants of Poverty and Their Variation Across the Poverty Spectrum: Evidence from Hong Kong, a High-Income Society with a High Poverty Level

Cited by 33 publications

References 61 publications

Determinants of Poverty in Mexico: A Quantile Regression Analysis

Determinants of Poverty in Mexico: A Quantile Regression Analysis

Are energy‐poor households also poor? Evidence from Ghana

Valuing the impact of Self-rated Health and Social Support on life satisfaction among Hong Kong Chinese population

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