The Determinants of Poverty in Mexico

Garza-Rodríguez, Jorge

doi:10.2139/ssrn.2774570

Cited by 14 publications

(15 citation statements)

References 16 publications

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“…However, from the gendered results, increases in female household head's age significantly reduce rural poverty, though this relationship is non-linear, with further increases in age leading to less than proportionate decreases in rural poverty. This result is consistent with those of Gang et al (2004), Datt and Jolliffe (1999), and Rodriguez (2002). From the results in Table 15, an increase of one year in the age of the female household head decreases the odds of being poor by 6.57 percent.…”

Section: Poverty and Agesupporting

confidence: 91%

“…The results in this study, for all rural Nigeria, show that indeed female-headed households are more likely to be poor than male-headed households. This is contrary to the findings of Cortes (1997), Szekely (1998) and Rodriguez (2002) but similar to those of Ghazouani and Goaied (2001) and Simler et al (2004). From the results in Table 15, being in a male-headed household decreases the odds of being poor by 40.31 percent while the odds are increased by 67.53 percent for female-headed households.…”

Section: Poverty and Gendercontrasting

confidence: 70%

“…To gauge the determinants of gendered poverty in rural Nigeria, a separate estimation was made by gender of household head. The dependent variable is defined as 1 if average per capita household expenditure is below the poverty line and 0 if it is above the poverty line (see also Mason, 1996;Anyanwu, 1997Anyanwu, , 1998Rodriguez, 2002;Ghazouani and Goaied, 2001;and Gang et al, 2004).…”

Section: Empirical Specificationmentioning

confidence: 99%

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Rural Poverty in Nigeria: Profile, Determinants and Exit Paths

Anyanwu¹

2005

African Development Review

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This paper studied the profile of rural poverty in Nigeria, what accounts for it, and what specific measures can be taken to reduce it, using the 1996 National Consumer Survey data set. The results show that by 1996, the proportion of the rural population living under the poverty line stood at 71.7 percent, up from 46 percent in 1992. The depth of poverty in rural Nigeria was 33 compared with 18.9 percent severity during the same year. A logistic regression model was estimated based on the data, with the probability of a household being poor as the dependent variable and a set of personal, demographic, economic and locational variables as explanatory variables. From the multivariate analysis the variables that are positively and significantly correlated with the probability of being poor in rural Nigeria are: household size, primary education level and below, rural occupations in the clerical, production and 'other' activities. The variables that are negatively and significantly correlated with the probability of being poor are: quadratic of household size, and residence in the central, south-east and south-south zones of rural Nigeria. Besides, strong evidence was found in this study to support the hypothesis of the feminization of rural poverty. This led to further estimation of the determinants of gendered poverty in rural Nigeria. The estimations show that male-headed households mirror the overall rural poverty results, while for female-headed households, the size of the household, education level of primary school and below, and residence in the central zone of Nigeria (unlike their male counterparts) are positively and significantly correlated with the probability of poverty. In addition, for female-headed households, the higher the age of the household head the lesser the probability of being poor, though less proportionately. Based on these results, a number of policy interventions necessary to reduce poverty in rural Nigeria are suggested. 435Re´sume´: Cette e´tude analyse le profil de pauvrete´rurale au Nigeria, ses causes et les mesures particulie`res qui peuvent eˆtre prises pour la re´duire; tout ceci sur la base des informations du sondage « Consommateur National » de 1996. Les re´sultats montrent qu'en 1996, le pourcentage de la population vivant en dessous du seuil de pauvrete´repre´sentait 71,7%, soit une hausse par rapport au chiffre de 46% de 1992. L'acuite´de la pauvrete´au Nigeria e´tait 33% dont 18,9% e´taient estime´s « se´ve`re » durant la meˆme anne´e. Un mode`le de re´gression logistique fut e´tabli par rapport aux donne´es, avec comme variable de´pendante la probabilite´qu'un me´nage soit pauvre, ainsi qu'un lot de variables explicatives compose´es de variables prive´es, de´mographiques, e´conomiques et d'emplacement. A partir d'une analyse multi-variable, les variables positivement et significativement corre´le´es avec la probabilited 'eˆtre pauvre dans une zone rurale du Nigeria, sont: la taille du me´nage, le niveau d'e´ducation primaire ou e´le´mentaire, les taˆches rurales dans le ...

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Section: Poverty and Agesupporting

confidence: 91%

Section: Poverty and Gendercontrasting

confidence: 70%

Section: Empirical Specificationmentioning

confidence: 99%

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Rural Poverty in Nigeria: Profile, Determinants and Exit Paths

Anyanwu¹

2005

African Development Review

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“…Second, education increases the stock of human capital, which in turn increases labour productivity and wages and reduces poverty (Aakvik, Salvanes and Vaage, 2005;Ranis, 2004;Tilak, 2002aTilak, , 2002bMingat and Tan, 1996;Weale, 1992;Sen, 1995Sen, , 1985Schultz, 1961). Since labour is by far the most important asset of the poor, provision of education to the poor will tend to reduce poverty through increased labour productivity (Rodriguez, 2002;Guneratne, 1985). Loweducation is one of the most serious causes of poverty.…”

Section: Introductionmentioning

confidence: 99%

Human capital formation within families: a study in the North Central Province of Sri Lanka

Chandrakumara

2013

Sri Lanka J. Soc. Sci.

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Abstract:The aim of this paper is to uncover the role of family in human capital formation through education, so as to draw important policy implications for poverty reduction. The study used both descriptive statistics and Binary Logistic Analysis to examine the infl uence of different family factors on the education level of children. The study is based on primary data collected from three villages of the North Central Province of Sri Lanka. The study found that four family factors-namely, family assets, presence of senior siblings, presence of junior siblings and father's age, had been signifi cant in determining the children's education level thereby forming a family role model. The two factors, family assets and presence of senior siblings, had a positive relationship with children's education level, while the other two had an inverse relationship. Further, it was found that gender, living area of the family were not signifi cant factors to be included in the model. Finally, the model developed by the study is useful in the public policy decisions on human capital formation through education, which uses the family as the bottom level basis for reducing poverty.

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“…According to the World Bank: 'In 2002, half the population in Mexico was living in poverty and one fifth was living in extreme poverty.' 3 Literature on Mexico has so far mainly focused on the distribution of income, largely ignoring the poverty analysis 4 ; poverty among the self-employed has been, up till now, an unexplored area.…”

Section: Introductionmentioning

confidence: 99%

Trade Liberalization and the Self-Employed in Mexico

Popli¹

2010

World Development

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In this paper I examine the trend in income inequality and poverty among the selfemployed workers in Mexico over the last two decades (1984)(1985)(1986)(1987)(1988)(1989)(1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002). This is the period over which Mexico opened its economy to the global market through trade and investment liberalization. For the first decade following the liberalization, inequality and poverty among the self-employed increased; as the economy stabilized and the country saw economic growth inequality started to go down, but poverty kept increasing. To understand the changes in inequality and poverty I decompose the inequality and poverty indices into within and between group components. Rising returns to skilled labour, regional differences in impact of liberalization and sectoral shifts in employment are important factors in explaining the trends in both inequality and poverty.

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The Determinants of Poverty in Mexico

Abstract: This study examines the determinants or correlates of poverty in México.

Cited by 14 publications

References 16 publications

Rural Poverty in Nigeria: Profile, Determinants and Exit Paths

Rural Poverty in Nigeria: Profile, Determinants and Exit Paths

Human capital formation within families: a study in the North Central Province of Sri Lanka

Trade Liberalization and the Self-Employed in Mexico

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