Some mathematical models for human fertility behavior and their applications

Abstract

Fertility is a crucial factor in population change and the central importance of the newlinestudy for demographers. Fertility is a composite phenomenon which incorporates sociocultural, newlineeconomic and demographic as well as biological activities of the couples. The newlinestudy of fertility is categorized in the three sets (i) factors affecting the fertility and newlineimpact of these factors on fertility, (ii) measurement of tempo of fertility, and (iii) newlinereproductive pattern for study of fertility incorporating biological and demographical newlineconsideration. newlineThe first set is established by Davis and Blake (1956) through the intermediate newlinevariables categorized into three section a) intercourse variables, b) conception variables newlineand c) gestation variables. Since there is problem to measure all these variables suggested newlineby Davis and Blake (1956) and then Bongaart s (1978) suggested the concept of newlineproximate determinants which can be measured easily. After this Bongaart s and Potter newline(1983) suggested a relation to estimate the TFR. In this context, further there are several newlinestudies has been done to study the impact of many socio-cultural, demographical and newlineeconomical factors on fertility. newlineThe second set includes the establishment of formulae to measure the tempo of newlinefertility or we can say that they obtained or estimated some quantify values of measures newlineof fertility like estimation of crude birth rate (CBR), age specific fertility rate (ASFR), newlinetotal fertility rate (TFR), gross reproduction rate (GRR), net reproduction rate (NRR), etc. newlineThis includes the indirect techniques of demographic estimation. Using indirect method newlinethe TFR is generally estimated through the birth history data and own-children method. newlineCho et al. (1986) have suggested own child method which contains reverse survival newlinetechnique (15 years) for estimating ASFR from cross-sectional survey. newline