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This paper evaluates the impact of socio and demographic factors on the multidimensional poverty of smallholder arable crop farming households in Nigeria.

Data were drawn from the second wave of the LSMS-Integrated Surveys on Agriculture General Household Survey Panel 2012/2013. The methods adopted in analysing the data were descriptive statistics, Alkire and Foster Method (AFM) and logit regression model.

The result shows that 84.34% of the households were headed by a male while 80.26% of the respondents were married with a mean household size of seven persons. The multidimensional poverty of arable crop farm households in Nigeria is 0.60, while the adjusted headcount ratio (MPI) is 0.27, with an average intensity of 0.45. We found that deprivation in the dimension of living standard accounted for 45.5% of the overall multidimensional poverty index (MPI). The result of the logistic regression indicates that household location, gender, household size and non-farm income are negatively correlated to poverty. The factors that increase poverty among households are the age of the household head and access to extension services.

The study presents an alternative means of assessing poverty among smallholder arable crop farming households in Nigeria. This study recommends that policymakers should focus more on improving the living standard of arable crop farming households to reduce poverty in rural areas. Similarly, concerted efforts should be made towards providing adequate health care and improved sanitation, supply of electricity and educational training that goes beyond primary education for farming household members.

The purpose of this paper is to examine the factors influencing the use of family planning and its link with multidimensional poverty in rural Nigeria.

The Alkire and Foster measure of poverty as well as the Logistic and Probit models were used to identify the factors influencing the use of family planning and its effect on the multidimensional poverty status of rural households in Nigeria.

The results indicate that 31.1 percent of rural households were poor with deprivations in health and education contributing the most to multidimensional poverty. The low use of contraception was closely linked to low level of literacy, lack of awareness of the different methods and high levels of poverty. The use of contraception reduced the level of poverty in the household.

The intensity of poverty should be considered in the design of policies and programs. The wide and proper use of family planning is a sine qua non for any significant reduction in poverty. Potent and assertive family planning programs by government could be achieved through public-private sector partnership and assistance of international development partners.

This paper attempts to bridge the knowledge gap in the empirical literature on the link between multidimensional poverty and family planning. In particular`, its application to the rural context, often characterized by high rate of poverty and unmet needs for family planning employing nationally representative data is of immense value for social policy.

There has been a rapid expansion in the literature on the measurement of multidimensional poverty in recent years. This paper focuses on the longitudinal aspects of multidimensional poverty and its link to dynamic income poverty measurement. Using panel household survey data in Vietnam from 2007, 2008, and 2010, the paper analyses the prevalence and dynamics of both multidimensional and monetary poverty from the same dataset. The results show that the monetary poor (or non-poor) are not always multidimensionally poor (or non-poor) – indeed the overlap between the two measures is much less than 50 percent. Additionally, monetary poverty shows faster progress as well as a higher level of fluctuation than multidimensional poverty. We suggest that rapid economic growth as experienced by Vietnam has had a larger and more immediate impact on monetary than on multidimensional poverty.

This article aims to analyse the spatial and temporal evolution of multidimensional poverty in Brazil's North Region and its relationship with territorial, economic and population dynamics.

A multidimensional poverty index (MPI) was calculated using the Alkire-Foster method and a spatial econometric model was estimated. The data come from population censuses conducted by the Brazilian Institute of Geography and Statistics (IBGE) for the years 1991, 2000 and 2010.

The results show a decrease in multidimensional poverty over the period analysed. However, they show this reduction occurred in a heterogeneous way in time and space, with emphasis on microregions in which, despite a reduction in the rate, the percentage of the population considered multidimensionally poor remained high during the 30 years of the study.

The quality of available data.

It is possible to point out that public policies focused on improving infrastructure in medium-sized locations tend to have two positive effects: first, making production and consumption more accessible and sustainable for local communities, given that currently the cost of transport and logistics are factors that hinder socioeconomic development; second, to reduce the pressure of demand that this population of small and medium-sized locations exerts on public services currently offered only in larger locations. Although the logic of concentrating most public services in the largest cities makes sense in terms of economic efficiency, the particularities of the northern region and the recognition of its environmental importance point to the need for incentives for more spatially distributed economic activity.

From the paper results, it is possible to think about more local public policies which are able to improve people's lifes without to damage the environment.

This is the first study on multidimensional poverty that covers the entire North region of Brazil (Amazon region) and that contemplates both the temporal and spatial dynamics of poverty.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2021-0699.

Poverty is one of the most significant economic and social problems that European countries have to face. In recent years, it has become widely accepted that poverty is a multidimensional concept and now many studies use indicators of deprivation to examine the phenomenon. The focus on financial resources alone does not capture people’s quality of life as being poor means a lack of access to resources enabling a minimum standard of living and participation in the society within which one belongs. The paper aims to discuss this issue.

Using a longitudinal component (2006-2010) of EU Statistics on Income and Living Conditions data on 26 European countries, the author apply a second-order confirmatory factor analysis to estimate deprivation. To describe the patterns of change over time and to evaluate the role of household characteristics in deprivation level, the author employ a set of multilevel growth curve models.

Three findings clearly stand out from my analysis. First, there is great variability in deprivation between European countries. Second, European countries show various patterns of change in deprivation over time. Third, households with different characteristics have quite different deprivation levels; moreover, the impact of household characteristics on deprivation can vary over time and between countries.

This paper sheds light on the importance of analysing deprivation from a longitudinal perspective and that financial resources alone does not capture people’s quality of life.

This study aims to investigate whether the participation in land rental markets helps to mitigate impacts by climate change on multidimensional poverty in Thailand and Vietnam.

The authors use precipitation data from the National Aeronautics and Space Administration (NASA) and self-reported shocks from the Thailand Vietnam Socio-Economic Panel (TVSEP) project to estimate climate change. Data from the TVSEP are also used to calculate a multidimensional poverty index (MPI). Fixed-effect logit panel regressions with interaction terms are implemented to analyze the above mentioned.

The results show that land rental markets are used as mitigation strategies to climate change in Thailand and Vietnam. The participation in land rental markets also reduces multidimensional poverty. However, as a mitigation strategy, land rental markets are only successful in certain circumstances.

The results show that there is potential in using land rental markets as mitigation strategies to climate change. Further research is needed to better understand which adaptation strategies, besides land rental market participation, and which combinations of different adaptation strategies are successful to mitigate negative effects induced by climate change.

The results show that there is potential in using land rental markets as mitigation strategies to climate change. Therefore, education in the participation in land rental markets and how to use them as a mitigation strategy can be a way to increase households' resilience to negative effects induced by climate change. Households make better decisions regarding their land when they are better informed on the functionality of land rental markets. Additionally, being better informed increases self-confidence to participate in land-rental markets.

Land rental markets as a mitigation strategy to climate change rarely have been studied, and if so, mainly the effect of leasing land has been studied. Additionally, the authors implement new measures of poverty – a multidimensional view on poverty which provides new insights into who are the poor and how they can be lift out of poverty.

A number of multidimensional poverty measures that respect the ordinal nature of dimensions have recently been proposed within the counting approach framework. Besides ensuring a reduction in poverty, however, it is important to monitor distributional changes to ensure that poverty reduction has been inclusive in reaching the poorest. Distributional issues are typically captured by adjusting a poverty measure to be sensitive to inequality among the poor. This approach, however, has certain practical and conceptual limitations. It conflicts, for example, with some policy-relevant measurement features, such as the ability to decompose a measure into dimensions post-identification and does not create an appropriate framework for assessing disparity in poverty across population subgroups. In this chapter, we propose and justify the use of a separate decomposable inequality measure – a positive multiple of “variance” – to capture the distribution of deprivations among the poor and to assess disparity in poverty across population subgroups. We demonstrate the applicability of our approach through two contrasting inter-temporal illustrations using Demographic Health Survey data sets for Haiti and India.

This paper aims to examine the mismatch between multidimensional deprivation and monetary poverty in identifying the poor in Egypt and investigates their determinants empirically.

The paper uses the Alkire-Foster multidimensional poverty measurement method using data from Egypt’s 2017/2018 Household Income, Expenditure and Consumption Survey (HIECS 2017/2018). Using a logistic regression model, the paper assesses the empirical relationship between multidimensional and monetary poverty and their determinants at the aggregate level and by dimension.

The paper demonstrates a significant mismatch between multidimensional and monetary poverty measures, underscoring their complementary nature. Statistics indicate that both measures overlap in classifying 35.81% of Egyptians, whereas monetary poverty ignores 63.12% of multidimensionally poor in at least one dimension. Regression estimates show a significant moderate negative association between expenditure per capita and multidimensional poverty and its dimensions. Moreover, they show that household head’s gender, age, education attainment, marital status, job proficiency, household size and location affect poverty mismatch and match in Egypt.

This paper offers Egyptian policymakers the multidimensional poverty index that enables more efficient designing and targeting of poverty alleviation programs and assessing current poverty alleviation programs to modify them if needed.

To the best of the authors’ knowledge, this study is the first to examine the mismatch between both poverty measures in Egypt, using the recent full data set of HIECS 2017/2018. This paper confirms that depending only on monetary measures can send inaccurate insights for crafting effective social policies. Also, it offers policymakers a comprehensive insight into the country’s poverty landscape, which enable more efficient design, targeting of poverty alleviation programs and monitoring their effectiveness.

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.

The multidimensional nature of well-being is now widely recognized. However, multidimensional poverty measurement is still an expanding field of research and a consensus about the “best” composite indicator has not yet emerged. In this chapter, we provide an empirical analysis using three existing methodologies: Bourguignon and Chakravarty (2003), Alkire and Foster (2007), and Lemmi (2005); Chiappero Martinetti (2000). We present an empirical study of the convergence and divergence of poverty profiles for children in Uruguay considering the following dimensions: nutritional status, child educational achievement, housing condition, and household income. Our data gather information of 1,185 children attending public schools in Montevideo and the surrounding metropolitan area, and were specially gathered to carry out a multidimensional analysis of poverty.

Our results indicate that the three families of indexes yield very different cardinalizations of poverty. At the same time, the correlation coefficients among the three groups of measures for the generalized headcount ratio also highlight important differences in the children labeled as “more deprived.” For the generalized severity and intensity indexes the correlation coefficients increase significantly suggesting a high level of concordance among the three measures, particularly among the Bourguignon and Chakravarty methodology and the Alkire and Foster one.