Determinants and Spatial Distribution of Multidimensional Poverty in Cameroon

Ningaye, Paul; Njong, Aloysius Mom

doi:10.11114/ijsss.v3i1.619

Cited by 9 publications

(9 citation statements)

References 19 publications

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“…Therefore relying on a single income is not sufficient, and a more reason why women should get involved in jobs. This result tie with those of Hosny (2007); Bagozzi and Vanloo (1991); Ningaye and Njong (2015).…”

Section: Logit Regression Results Of the Determinant Of Female Laboursupporting

confidence: 90%

Determinants of Female Labour Force Participation in Cameroon

Njang

Sundjo

2018

International Journal of Applied Economics, Finance and Account

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Recently, women have become relatively more engaged in the labour market and this increasing trend toward women's participation in jobs in the third world countries has drawn both social and academic attention. It is on the bases of this context, that this paper purports to empirically investigate the determinants of female labour force participation in Cameroon. Specifically, the study attempts to scrutinise the effect of: (a) spouse working status, (b) mothers/household characteristics, and (c) the type of religion practiced, on female labour force participation. To ascertain these objectives, data is sourced from the 2011 Cameroon Demographic Health Survey data collected by the National Institute of Statistics (NIS) and used is made of both descriptive and inferential statistics. The logit regression model is employed to test the objectives. The empirical findings, among others suggested that, a woman with a non-working husband, an increase in age, presence of woman in the household increases the likelihood of women participating in the labour market. Contrarily, the presence of young children aged 0-5 years in the household and being a Muslim reduces the likelihood of women participating in the labour market. Policy wise, it is important for policy makers to understand women's decision to supply labour in the labour market as well as the factors that enable them to either participate or not in the job market. To assess the effect of the employability of the spouse on female labour force participation in Cameroon and across residence.  To investigate the effects of mother/household characteristics on female labour force participation in Cameroon and across residence.  To scrutinise the differential effects of religion on female labour force participation across residence. These objectives are guided by the following testable hypotheses, stated in alternative form: The partner"s employability is expected to relate negatively with FLFP  Mother"s household characteristics have a positive effect on FLFP  We expect Muslims to participate less in the labour market than Christians. The remaining sections of this paper is structured as follows: section II focus on the literature reviews, section III presents the methodology and the data description is done in section IV while section V present the findings and section VI concludes the paper.

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Section: Logit Regression Results Of the Determinant Of Female Laboursupporting

confidence: 90%

Determinants of Female Labour Force Participation in Cameroon

Njang

Sundjo

2018

International Journal of Applied Economics, Finance and Account

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“…Quantiles were generated using the multiple correspondence analysis (MCA) [ 6 , 11 ]. Other studies that have used MCA to generate socio-economic index measures included the works of:- Asselin and Anh [ 13 ] in Vietnam; Ki et.al in Senegal [ 14 ]; Ndjanyou [ 15 ] and Njong [ 16 ] both for the Cameroon case. Booysen et.…”

Section: Methodsmentioning

confidence: 99%

Socio-economic inequality and HIV in South Africa

Wabiri

Taffa²

2013

BMC Public Health

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BackgroundThe linkage between the socio-economic inequality and HIV outcomes was analysed using data from a population-based household survey that employed multistage-stratified sampling. The goal is to help refocus attention on how HIV is linked to inequalities.MethodsA socio-economic index (SEI) score, derived using Multiple Correspondence Analysis of measures of ownership of durable assets, was used to generate three SEI groups: Low (poorest), Middle, and Upper (no so poor). Distribution of HIV outcomes (i.e. HIV prevalence, access to HIV/AIDS information, level of stigma towards HIV/AIDS, perceived HIV risk and sexual behaviour) across the SEI groups, and other background characteristics was assessed using weighted data. Univariate and multivariate logistic regression was used to assess the covariates of the HIV outcomes across the socio-economic groups. The study sample include 14,384 adults 15 years and older.ResultsMore women (57.5%) than men (42.3%) were found in the poor SEI [P<0.001]. HIV prevalence was highest among the poor (20.8%) followed by those in the middle (15.9%) and those in the upper SEI (4.6%) [P<0.001]. It was also highest among women compared to men (19.7% versus 11.4% respectively) and among black Africans (20.2%) compared to other races [P<0.001]. Individuals in the upper SEI reported higher frequency of HIV testing (59.3%) compared to the low SEI (47.7%) [P< 0.001]. Only 20.5% of those in poor SEI had “good access to HIV/AIDS information” compared to 79.5% in the upper SEI (P<0.001). A higher percentage of the poor had a stigmatizing attitude towards HIV/AIDS (45.6%) compared to those in the upper SEI (34.8%) [P< 0.001]. There was a high personal HIV risk perception among the poor (40.0%) and it declined significantly to 10.9% in the upper SEI.ConclusionsOur findings underline the disproportionate burden of HIV disease and HIV fear among the poor and vulnerable in South Africa. The poor are further disadvantaged by lack of access to HIV information and HIV/AIDS services such as testing for HIV infection. There is a compelling urgency for the national HIV/AIDS response to maximizing program focus for the poor particularly women.

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“…Apesar de essas evidências apresentarem grande relevância para a área, não há na literatura estudos que buscam analisar a pobreza multidimensional no âmbito convergência em clubes, uma vez que há uma grande diversidade no desenvolvimento socioeconômico das regiões brasileiras, informando melhor a dinâmica da evolução espacial da pobreza. Além disso, é relevante mencionar a importância da análise espacial para a pobreza multidimensional, seja para o Brasil Raiher, 2017) ou para outros países (Ningaye;Njonh, 2015;Ramírez et al, 2016), devido à sua dependência e heterogeneidade espacial.…”

Section: Palavras-chaveunclassified

“…Surgiram na literatura diversos estudos nacionais (Albuquerque; Cunha, 2012;Giovanetti;Raiher, 2015;Silva et al, 2017;Struminskiy;Raiher, 2017;Santos et al, 2017;Raiher et al, 2018) e internacionais (Bourguignon;Chakravarty, 2003;Silber, 2005;Alkire;Foster, 2011;D'Ambrosio et al, 2011;Akerele et al, 2012;Cepal, 2013;Machado et al, 2014;Ningaye;Njong, 2015;David et al, 2018;Amaghouss;Ibourk, 2020), que mensuraram a pobreza em uma perspectiva multidimensional.…”

Section: Aspectos Teóricos E Empíricos Da Pobreza Multidimensionalunclassified

Pobreza multidimensional no Brasil, 1991, 2000 e 2010: uma abordagem espacial para os municípios brasileiros

Brambilla

Cunha

2021

Nova econ.

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O presente estudo analisa a distribuição espacial da pobreza multidimensional nos municípios brasileiros considerando as Áreas Minimamente Comparáveis (AMC) e sua convergência nos anos de 1991, 2000 e 2010. Para isso, foi construído um Índice de Pobreza Multidimensional (IPM), realizada a análise exploratória de dados espaciais (AEDE) e, para verificar a convergência da pobreza multidimensional, utilizou-se a abordagem de econometria espacial. Os resultados indicaram que condições de habitação e demografia foram as dimensões que mais contribuíram para a pobreza multidimensional, e as dimensões de saúde e saneamento e renda são as que mais contribuíram para a redução da pobreza multidimensional. O estudo também apontou que o Brasil apresentou convergência absoluta e clubes de convergência da pobreza multidimensional, especialmente de 2000 para 2010. Além disso, as dimensões trabalho e condições de habitação foram as que mais contribuíram para a convergência da pobreza multidimensional.

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Determinants and Spatial Distribution of Multidimensional Poverty in Cameroon

Cited by 9 publications

References 19 publications

Determinants of Female Labour Force Participation in Cameroon

Determinants of Female Labour Force Participation in Cameroon

Socio-economic inequality and HIV in South Africa

Pobreza multidimensional no Brasil, 1991, 2000 e 2010: uma abordagem espacial para os municípios brasileiros

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