Factors affecting children ever born for 15-49 year old women in Bangladesh: Application of finite mixture regression model

Md. Karimuzzaman, Md. Moyazzem Hossain, Azizur Rahman

Research output: Book chapter/Published conference paperConference paper

Abstract

The number of ever born children is one of the main components of population
dynamics that determine the size, structure, as well as the composition of a countries’ population. Children ever born refer to the number of children born alive to the person up to a specified reference date and served as a response variable here. A secondary dataset is used in this paper that is obtained from a countrywide representative survey entitled Bangladesh Demographic and Health Survey (BDHS) 2014. This study aims to identify the socioeconomic and demographic factors influencing children ever born to the women of 15-49 years old in Bangladesh. The first attempt of this paper is to identify the best-fitted model among generalized Poisson, Negative Binomial, truncated, COM and finite mixture regression model form. The results suggest that among the model considered in this study Finite Mixture Negative Binomial Regression with three components gives the best-fitted model to estimate the number of ever born
children in Bangladesh. It reveals that respondents age, residential status, family size and intention of using contraception have shown positive impact and respondents education, drinking water, toilet facility, religious status, household head age, wealth index, age at first birth, and husband education shows a negative impact on ever born children.
Original languageEnglish
Title of host publicationApplied Statistics and Policy Analysis Conference, 2019
Subtitle of host publicationEffective policy through the use of big data, accurate estimates and modern computing tools and statistical modelling
PublisherSpringer
Number of pages16
Publication statusAccepted/In press - 2020
EventThe 2nd Applied Statistics and Policy Analysis Conference: ASPAC2019 - Charles Sturt University, Wagga Wagga, Australia
Duration: 05 Sep 201906 Sep 2019
http://csusap.csu.edu.au/~azrahman/ASPAC2019/
http://csusap.csu.edu.au/~azrahman/ASPAC2019/Program%20draft.pdf?attredirects=0&d=1 (program)
http://csusap.csu.edu.au/~azrahman/ASPAC2019/ASPAC2019_Refereed_Book%20of%20Abstracts.pdf?attredirects=0&d=1 (book of abstracts)

Conference

ConferenceThe 2nd Applied Statistics and Policy Analysis Conference
Abbreviated titleEffective policy through the use of big data, accurate estimates and modern computing tools and statistical modelling
CountryAustralia
CityWagga Wagga
Period05/09/1906/09/19
OtherProceedings due for publication May 2020 https://www.springer.com/gp/book/9789811517341
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Karimuzzaman, M., Hossain, M. M., & Rahman, A. (Accepted/In press). Factors affecting children ever born for 15-49 year old women in Bangladesh: Application of finite mixture regression model. In Applied Statistics and Policy Analysis Conference, 2019: Effective policy through the use of big data, accurate estimates and modern computing tools and statistical modelling Springer.