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Poverty dynamics and the ability of the Italian welfare system to reduce poverty are investigated by using the 1991‐1995 panel of the Bank of Italy’s Survey of Household Income and Wealth. Households most exposed to poverty live in the South, have a larger size, a young or female head, with a low educational level or a discontinuous work profile. The dynamic and static effectiveness (in terms of poverty reduction) of social transfers is analysed, as well as the factors affecting exclusion from the safety net. A closer look is taken at the effects of a minimum income guarantee in the experimental phase in Italy.

Currently, Malaysia uses the Poverty Line Income (PLI) to measure poverty. This is because income measurement is the easiest way to collect data, but in its simplicity, it fails to capture the broader meaning and implications of poverty. Asset index is one of the non-monetary poverty measurements which have been established by researchers but not used in measuring poverty in Malaysia. A household might be poor in income, but assets may prevent them from being trapped in poverty.

This study will reassess the poverty of 302 households in the Northern States of Malaysia using the asset index and also the current state of poverty incidence with change under asset index.

The results show that households in the Northern States of Malaysia are interpreted as being ‘poorer’ when poverty is measured using assets as opposed to income alone. Besides that, poverty incidence of Malay households, households living in urban area and households with middle-aged heads have high poverty incidence, while households with a head of households that is single and highly educated have low poverty incidence. The logistic regression analysis shows that the determinants of poverty incidence based on the asset index are Indian, Penang and Perak State, the age of the head of household, distance to the education centre from home.

This study shows the asset index measurement which have not been done in Malaysia. This will contribute to the improvement of poverty measurement of the country.

The purpose of this paper is to examine the determinants of poverty and the persistence of poverty in Benin using a longitudinal data for the years 2006-2011. The paper also seeks to understand the dynamic of poverty and what factors explain households’ mobility across poverty status over time.

To answer the research questions, the paper develops and estimates logit and probit models of poverty. In addition to households’ characteristics as explanatory variables, the models control for the previous years’ poverty status to test for the hypothesis of persistence in poverty. Next, the paper extends the analysis to compute poverty transition matrix and estimates a multinomial models of the determinants of these transitions.

The paper finds that households’ demographic and socio-economic characteristics are strongly correlated with their poverty status. It also finds a strong evidence of persistence of poverty: being poor in a year increases the likelihood of remaining poor in the following years. The analysis of the dynamic of poverty reveals that there is a large and rapid change in poverty with households moving in and out of poverty. Across all models, it appears that human capital accumulation through education and labor skills are the strongest forces lifting households out of poverty and persistence of poverty.

Taken together, the results suggest that public policies should not only seek to lift households out of poverty, but also seek to reduce re-entries into poverty by investing in education and improving employment skills.

A key contribution of the study is the characterization of the profile of poor and persistently poor households in Benin, and the analysis of the factors explaining the dynamic of poverty. It updates and complements previous studies on poverty in Benin using the most recent nationally representative longitudinal data. The findings stress the crucial importance of human capital as a key force to lift households out of poverty.

The purpose of this paper is to reveal the internal mechanism of the deviation of targeted poverty alleviation under the condition of asymmetric information.

Introducing a traditional signaling game theory model with dynamic asymmetric information, this study uses a dataset covering 813 poor households from Southern Xinjiang, China, to theoretically and empirically study the effect of aspiration of the poor households on poverty alleviation.

First, there exists asymmetric information between the poor households and village leaders. Second, the “short, arbitrary and fast” poverty alleviation approach may quickly pull people out of poverty, but it may also nurture a dependency culture where poor households lose their aspiration and ability to escape poverty through their own efforts. Third, due to long lasting universal state support, poor households in the national designated poor counties are less able and ambitious to escape poverty by themselves than their counterparts living in the national nondesignated areas.

The research results show that pro-poor development policies should be upheld to improve the residual utility that can benefit all households as a result of the poverty alleviation campaign. Relevant policy recommendations are made for China's continuous effort to fight relative poverty beyond 2020.

The purpose of this paper is to find the determinants of participation and targeting efficiency of the following safety net programs in West Bengal: Mahatma Gandhi National Rural Employment Guarantee Act (MNREGA), self-targeted program; National Rural Livelihood Mission (NRLM), subsidy based livelihood program; Indira Awaas Yojona (IAY), targeted cash transfer program and Public Distribution System (PDS), targeted in kind transfer program.

The study is based on a household survey comprising 900 households across three Districts: Murshidabad, Nadia and Burdwan.

Benefits from MNREGA and PDS are not substantial, whereas financial benefits are substantial from NRLM and IAY. This paper shows that poor people have higher likelihood of participation in MNREGA and PDS. But, non poor get disproportionate benefits from IAY and NRLM both have been designed for the poor. Therefore, targeting cannot remove elite capture altogether. Socially down trodden section have higher participation in MNREGA and PDS, whereas people who are at upper tier of social hierarchy enjoy the benefits of IAY and NRLM. However, it cannot be said that these programs miss their target completely.

The study suffers from the usual limitations of sampling.

Programs targeted for the poor are being appropriated by the non poor. If there is better targeting money will be channelized to the desired beneficiaries and welfare will be enhanced.

The study has unearthed the underlying reasons behind why some safety net programs have better targeting and some safety net programs have poor targeting.

This paper aims to explore the poverty and vulnerability of poor urban communities living in Dhaka City's slums.

Poverty line definition often conceptualises poverty in terms of income, consumption and household resources which has been used for this study. Data have been collected from 500 respondents living in slums in three neighbourhoods of Dhaka City by using a structured questionnaire. In addition, qualitative data have been used to supplement the survey data. Both descriptive and inferential statistics are used for analysing data.

The paper argues that slum communities experience poverty and vulnerability in terms of income, consumption and asset which is most strongly influenced by location, pattern of habitat, gender, recent migration and household organisation.

The paper offers insights into poverty and vulnerability in urban Bangladesh.

The purpose of this paper is to examine the impact of individual components of financial literacy in promoting financial inclusion of poor households in rural Uganda.

The study was cross-sectional combined with correlation and regression analyses. Data were collected from 400 poor households drawn from four regions in rural Uganda. Hierarchical regression analysis was used to test for the contribution of individual components of financial literacy on financial inclusion of poor households in rural Uganda. In addition, confirmatory factor analysis was used to establish existence of convergent validity between the items used to measure the different constructs under study. Furthermore, analysis of variance was also adopted to test for variation in perceptions of poor households on being financially included.

The results generated from the study revealed that only attitude as a component of financial literacy significantly and positively predicts financial inclusion of poor households in rural Uganda. Contrary to previous thinking and empirical studies, behavior, knowledge, and skills are not significant predictors of financial inclusion of poor households in rural Uganda. Overall, the combined effect of the different components of financial literacy explains about 11.2 percent of the variance in financial inclusion of poor households in rural Uganda.

The study was not without limitations. The study adopted only cross-sectional study design, thus, leaving out longitudinal study. Therefore, future studies employing longitudinal research design worth undertaking. Furthermore, the sample although large enough focused only on poor households located in rural Uganda, therefore, ignoring peri-urban and urban areas in Uganda. Besides, the study used only quantitative data, thus, qualitative study using key informant interviews may be considered for further research.

The paper indicates that policy makers, advocates of financial inclusion and researchers, should reconsider investigating individual contribution of the different components of financial literacy in promoting financial inclusion of poor households in rural Uganda. For researchers, it is important to re-analyze the individual components of financial literacy of behavior, knowledge, skills, and attitude in influencing financial inclusion of poor households in rural Uganda.

This paper combines both functional components (behavior and attitude) and non-functional measures (knowledge and skills) of financial literacy to explain financial inclusion of poor households in rural Uganda. Most financial literacy studies have mainly adopted only non-functional measures of knowledge and skills. Besides, these studies ignore the individual contribution of functional components and non-functional measures of financial literacy in explaining financial inclusion of poor households. Thus, this study is the first to examine the impact of individual components of financial literacy in explaining financial inclusion of poor households in rural Uganda.

This paper aims to evaluate the social safety nets in Tunisia using targeting performance indicators which consider the divergence observed between the beneficiary selection process at the regional level and the official identification of poor.

In the first part of this research, the author intend to quantify the degree of association between social programs coverage and poverty incidence, with special emphasis on the contribution of the center's targeting of regions and on the efforts of the regions themselves to reach their poor households. Next, the author measure four targeting errors: inclusion and exclusion errors, by eligibility and by poverty. These targeting errors help policymakers to understand how well a program is performing in terms of its specific eligibility criteria and knowing whether a social transfer is reaching poor people at the regional level.

The author’s empirical findings show there is a positive targeting differential which rejects the nullity of independence between poverty incidence and coverage of the program in Tunisia. The author then found that the overall targeting differential is accounted for by the intra-region component. After estimating the eligibility thresholds at the regional level, the author found that the targeting performance differs from one region to another, while some recorded gains that others did not.

To the best of our knowledge, no research has addressed the distinction between eligibility and poverty in the measurement of targeting errors. Thus, this paper contains research to fill this gap. It differs from previous studies in two important ways. First, the targeting errors will be estimated on the basis of the official eligibility criteria used at the regional level. Second, we estimate the eligibility thresholds by considering the programs coverage rate variations between regions based on quotas allocated to each governorate by the Ministry of Social Affairs (MSA).

This paper investigates the effect of reducing inequality in household education, health and access to credit on pro-poor growth in Cameroon using the 2001 and 2007 Cameroon household consumption surveys. Results indicate that education and access to credit registered relative pro-poor growth driven by a fall in inequality. However, health failed to record pro-poor growth due to an increase in health-inequality at the bottom of the welfare distribution. In addition, equalizing education, health and access to credit among households, would increase average growth in household spending and pro-poor growth.

Most poverty research has explored monetary poverty. This chapter presents and analyzes the global multidimensional poverty index (MPI) estimations for China. Using China Family Panel Studies (CFPS), we find China’s global MPI was 0.035 in 2010 and decreased significantly to 0.017 in 2014. The dimensional composition of MPI suggests that nutrition, education, safe drinking water, and cooking fuel contribute most to overall non-monetary poverty in China. Such analysis is also applied to subgroups, including geographic areas (rural/urban, east/central/west, provinces), as well as social characteristics such as gender of the household heads, age, education level, marital status, household size, migration status, ethnicity, and religion. We find the level and composition of poverty differs significantly across certain subgroups. We also find high levels of mismatch between monetary and multidimensional poverty at the household level, which highlights the importance of using both complementary measures to track progress in eradicating poverty.