Measuring Vulnerability to Poverty with Latent Transition Analysis

Acconcia, Antonio; Carannante, Maria; Misuraca, Michelangelo; Scepi, Germana

doi:10.1007/s11205-020-02362-3

Cited by 7 publications

(4 citation statements)

References 95 publications

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“…The fields that have probably received the most attention are poverty (Acconcia et al, 2020 ; Azeem et al, 2016 ; Gallardo, 2020 ), climate change, and physical vulnerability to natural disaster (Halkos et al, 2020 ; Marulanda Fraume et al, 2020 ) and financial or economic vulnerability (Alessi et al, 2020 ). Vulnerability is defined in a various ways in the literature (for a review, see Acconcia et al, 2020 ; Gallardo, 2018 ; Mina & Imai, 2016 ), so a crucial step of this study is to define the conceptual framework of socio-economic vulnerability. This is also important because the conceptual framework will determine the empirical strategy of our study.…”

Section: Conceptual Frameworkmentioning

confidence: 99%

European Union Cohesion Policy: Socio-Economic Vulnerability of the Regions and the COVID-19 Shock

Sánchez¹,

Fernández

2022

Applied Research Quality Life

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The European Union Cohesion Policy for the period 2021–2027 focuses on five goals to make the European Union smarter, greener, more connected, more social and closer to citizens. However, a macroeconomic index is proposed as the predominant criterion for allocating the Structural Funds among regions. In this paper, we hypothesise that it is possible to take into account new, complementary criteria that better reflect citizens’ quality of life. To that end, we build a composite index of socio-economic vulnerability for the 233 regions. The results show that following our multidimensional approach for allocating the Structural Funds, there are remarkable differences in the maps of priority regions. In addition, the COVID-19 pandemic represents a threat to well-being. Are all regions equally exposed to COVID-19 in terms of their socio-economic vulnerability? To address this issue, we estimate multilevel models which indicate that country characteristics interact with regions’ characteristics to alter patterns of vulnerability. More specifically, increases in government expenditures in education and an improvement in political stability would reduce the regional vulnerability or foster the capacity for resilience, whereas increases in poverty would be associated with greater vulnerability. Likewise, more vulnerable regions would be the most exposed to the negative socio-economic effects of COVID-19. However, it is remarkable that several regions of Sweden and Finland would be among the group of regions whose socio-economic vulnerability would be the most negatively affected.

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Section: Conceptual Frameworkmentioning

confidence: 99%

European Union Cohesion Policy: Socio-Economic Vulnerability of the Regions and the COVID-19 Shock

Sánchez¹,

Fernández

2022

Applied Research Quality Life

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“…It is believed that such populations face a higher degree of multidimensional poverty and hence, warrant more attention. Vulnerability to poverty has been analyzed using latent transition analysis [23] and multilevel models [24], whereby individual and household vulnerabilities to poverty have been linked to socioeconomic characteristics [25,26]. Specifically, Gloede et al evaluated more than 4000 households in Thailand and Vietnam to measure the degree of risk for household poverty [27], while Gallardo et al adopted the multidimensional poverty vulnerability measurement approach based on mean risk behavior to analyze Chile's vulnerability to poverty using the multidimensional poverty vulnerability index (MPVI) [28].…”

Section: Introductionmentioning

confidence: 99%

Impact of the COVID-19 Pandemic on Farm Households’ Vulnerability to Multidimensional Poverty in Rural China

et al. 2021

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The COVID−19 pandemic has significantly impacted the economy and livelihoods of people worldwide. To analyze the impact of the pandemic on material conditions, income levels, health conditions, industrial development and employment opportunities of farmers in China’s rural areas, especially poor areas and explore whether farmers can achieve stable poverty eradication during the COVID−19 pandemic, we interviewed 2662 farm households in poverty−stricken areas of China and used the multidimensional poverty measurement model, three−step feasible generalized least squares and propensity score matching to analyze data. We achieved the following results. First, the overall level of multidimensional poverty vulnerability index (MPVI) of the surveyed households was low and the MPVI of each dimension varied significantly. The MPVI of households in the treated group was higher than that of the control group. Second, COVID−19 increased farm households’ vulnerability to multidimensional poverty in poverty−stricken regions; MPVI increased by 27.9%. Third, COVID−19′s impact on various dimensions differed: the greatest impact was on the vulnerability to health deprivation, followed by industrial development, employment and income deprivation. However, the pandemic slightly reduced the vulnerability to material deprivation. Finally, we proposed various measures in response to the impact of the pandemic to assist farm households in poverty−stricken areas.

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“…It is now widely accepted that a singular focus on income is not sufficient to indicate a household's deprivation in terms of several non-monetary aspects of wellbeing [28,29]. Based on existing research on vulnerability and multidimensional poverty [30][31][32][33], we define VMP as the probability that rural families will fall into or remain in multidimensional poverty in the future. The VMP of relocated households depends not only on the external risk shock, but also on the capacity to cope with risk in terms of the government, household, and community (Figure 1).…”

Section: Theoretical Analysismentioning

confidence: 99%

Risk of Returning to Multidimensional Poverty and Its Influencing Factors among Relocated Households for Poverty Alleviation in China

Liu,

Yuan,

Zhao

2024

Agriculture

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Poverty alleviation through relocation (PAR) is a milestone project in winning the battle against extreme poverty. Its aim is to relocate poor people from inhospitable areas and lift them out of poverty. Assessing the vulnerability to multidimensional poverty (VMP) of relocated households is of great significance for consolidating the achievements of targeted poverty alleviation and preventing a large-scale return to poverty. This study constructed a multidimensional poverty index (MPI) of relocated households and analyzed relocated households’ VMP and its influencing factors using panel data of 1009 households in 16 counties across eight provinces in China. The results reveal that the mean VMP of the relocated households gradually decreased from 2016 to 2020. Moreover, the VMP of the relocated households that have moved into centralized resettlement communities is relatively low compared to those that have moved into decentralized resettlement communities. In addition, the impact of household endowment on VMP is the highest, followed by supporting policies, such as PAR, industrial development, and employment policy. Therefore, the assistance mechanism must be improved to prevent a return to poverty, enhance the sustainable development capacity of relocated households, and optimize follow-up policies for PAR.

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Measuring Vulnerability to Poverty with Latent Transition Analysis

Cited by 7 publications

References 95 publications

European Union Cohesion Policy: Socio-Economic Vulnerability of the Regions and the COVID-19 Shock

European Union Cohesion Policy: Socio-Economic Vulnerability of the Regions and the COVID-19 Shock

Impact of the COVID-19 Pandemic on Farm Households’ Vulnerability to Multidimensional Poverty in Rural China

Risk of Returning to Multidimensional Poverty and Its Influencing Factors among Relocated Households for Poverty Alleviation in China

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