Projection of Indian Population by Using Leslie Matrix with Changing Age Specific Mortality Rate, Age Specific Fertility Rate and Age Specific Marital Fertility Rate

Pathak, Prasanta; Verma, Vivek

doi:10.1007/978-1-4614-6862-2_13

Cited by 1 publication

(1 citation statement)

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“…Hence, the total fertility rate is estimated by using this linear function. The procedure for estimation and prediction of TMFR using various alternative methods was already explored in studies by Garenne et al (2001), Yadava and Kumar (2002), Martin et al (2011), and Pathak and Verma (2013).…”

Section: Introductionmentioning

confidence: 99%

Bayesian estimation of fertility rates under imperfect age reporting

Verma¹,

Nath²,

Dwivedi³

2023

SiTns

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This article outlines the application of the Bayesian method of parameter estimation to situations where the probability of age misreporting is high, leading to transfers of an individual from one age group to another. An essential requirement for Bayesian estimation is prior distribution, derived for both perfect and imperfect age reporting. As an alternative to the Bayesian methodology, a classical estimator based on the maximum likelihood principle has also been discussed. Here, the age misreporting probability matrix has been constructed using a performance indicator, which incorporates the relative performance of estimators based on age when reported correctly instead of misreporting. The initial guess of performance indicators can either be empirically or theoretically derived. The method has been illustrated by using data on Empowered Action Group (EAG) states of India from National Family Health Survey-3 (2005–2006) to estimate the total marital fertility rates. The present study reveals through both a simulation and real-life set-up that the Bayesian estimation method has been more promising and reliable in estimating fertility rates, even in situations where age misreporting is higher than in case of classical maximum likelihood estimates.

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Section: Introductionmentioning

confidence: 99%