Modelling individual fertility levels in Malawian women: a spatial semiparametric regression model

Kazembe, Lawrence

doi:10.1007/s10260-007-0076-2

Cited by 23 publications

(26 citation statements)

References 35 publications

(50 reference statements)

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“…The results obtained using the naive approach show that the education-fertility relationship follows a non-linear decreasing trend that is particularly strong for women with more than eight years of education. This pattern confirms the findings of Kalipeni (1997) and Kazembe (2009).…”

Section: Resultssupporting

confidence: 91%

“…Scholars have observed that births usually occur within marriage in developing countries (e.g., Martin, 1995;Manda and Meyer, 2005;Kazembe, 2009). In the present study, we have not considered the woman's age at marriage.…”

Section: Observed Confoundersmentioning

confidence: 99%

“…Note that empirical models that investigate the determinants of fertility in Malawi have usually included education as a categorical variable (Kalipeni, 1997;Kazembe, 2009). If we were to impose a priori assumptions by categorizing years of schooling, we might fail to capture some features in the fertility-education relationship.…”

Section: Applying 2sgam To the Fertility Datamentioning

confidence: 99%

“…To date, this issue has not been investigated for Malawi. Research shows an inverse relationship between education and number of children in Malawi (Kalipeni, 1997;Kazembe, 2009). It is not clear, however, whether this relationship is affected by endogeneity, which has to be accounted for to ensure that the effect of education is correctly quantified.…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, researchers usually account for the confounding effects of observed continuous covariates by including linear, polynomial, or categorical terms in the model (e.g., Bailey, 1989; Kalipeni, 1997;Kravdal, 2000;Kazembe, 2009). But the correct functional form is rarely known a priori, and incorrect specifications typically lead to residual confounding which, in turn, leads to inconsistent parameter estimates (e.g., Marra and Radice, 2011a and references therein).…”

Section: Introductionmentioning

confidence: 99%

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Modelling the impact of women’s education on fertility in Malawi

2014

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Many studies have suggested that there is an inverse relationship between education and number of children among women from sub-Saharan Africa countries, including Malawi.However, a crucial limitation of these analyses is that they do not control for the potential endogeneity of education. The aim of our study is to estimate the role of women's education on their number of children in Malawi, accounting for the possible presence of endogeneity and for non-linear effects of continuous observed confounding variables. Our analysis is based on micro data from the 2010 Malawi Demographic Health Survey, by using a flexible instrumental variable regression approach. The results suggest that the relationship of interest is affected by endogeneity and exhibits an inverted-U shape among women who are more than 30 years old and live in rural areas of Malawi, whereas it exhibits an inverse (non-linear) relationship for women living in urban areas.

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Section: Resultssupporting

confidence: 91%

Section: Observed Confoundersmentioning

confidence: 99%

Section: Applying 2sgam To the Fertility Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Modelling the impact of women’s education on fertility in Malawi

2014

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A Poisson Regression Model to Examine Spatial Patterns in Antenatal Care Utilisation in Nigeria

Gayawan

2013

Population Space and Place

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Despite the benefits of antenat]al care to the mother and the child, it is available less often in sub-Saharan Africa than in other regions. Coverage of at least four visits is lower, with a slower rate of increase, than in other regions of the world. Using data from 2008 Nigeria Demographic and Health Survey, we applied a Poisson regression model with geo-additive predictors to analyse individual-level and community-level determinants of antenatal care utilisation and quantify district specific spatial effect. The spatial structure was modelled using conditional autoregressive prior, whereas the metrical covariates were assumed to be nonlinear. Findings reveal substantial spatial variation with a distinct north-south divide in antenatal care utilisation in Nigeria. The effects of mother's age at birth, partner's age, and marital duration were non-linear, and utilisation was found to differ significantly between never-married and ever-married women respondents. Results further show that older women, particularly those above 35 years old, utilise antenatal care services during pregnancy more than the younger ones. Policymakers and public health providers need to put in more efforts to address these differentials as a minimum of four visits for antenatal care during pregnancy is required by all women in all parts of the country. Allocations for antenatal care services should also take into account the differentials so that those states lagging behind can be brought up, at least to scale with others.

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Advanced Techniques for Modelling Maternal and Child Health in Africa

Kandala

Ghilagaber

2014

The Springer Series on Demographic Methods and Population Analysis

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In recent decades, there has been a rapid development of demographic models and methods and an explosive growth in the range of applications of population analysis. This series seeks to provide a publication outlet both for high-quality textual and expository books on modern techniques of demographic analysis and for works that present exemplary applications of such techniques to various aspects of population analysis.Topics appropriate for the series include:• General demographic methods This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Exempted from this legal reservation are brief excerpts in connection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Duplication of this publication or parts thereof is permitted only under the provisions of the Copyright Law of the Publisher's location, in its current version, and permission for use must always be obtained from Springer. Permissions for use may be obtained through RightsLink at the Copyright Clearance Center. Violations are liable to prosecution under the respective Copyright Law. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein.Printed on acid-free paper SummaryThe estimation of levels, trends, and differentials in demographic and health outcomes in developing countries has, over the years, relied heavily on indirect methods that were devised to suit limited or deficient data. In recent decades, some worldwide surveys like the World Fertility Survey and its successor, the Demographic and Health Survey (DHS), have played an important role in filling the gap in the availability of survey data in developing countries. These surveys, conducted at enormous costs, are aimed at enabling investigators to make in-depth analyses that could guide policy intervention strategies. However, their utilization remains suboptimal, because optimal analyses of such data demand advanced statistical techniques.Since the use of DHS data in developing countries, many develop...

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Modelling individual fertility levels in Malawian women: a spatial semiparametric regression model

Abstract: Bayesian, Children ever born, Clustering, Fertility levels, Malawi, Poisson regression, Spatial modelling,

Cited by 23 publications

References 35 publications

Modelling the impact of women’s education on fertility in Malawi

Modelling the impact of women’s education on fertility in Malawi

A Poisson Regression Model to Examine Spatial Patterns in Antenatal Care Utilisation in Nigeria

Advanced Techniques for Modelling Maternal and Child Health in Africa

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