Suchergebnisse

What we will call the age-based TMFR is computed conventionally by adding up age-specific marital fertility rates in the hope of estimating the number of children ever born to a woman who is married throughout her childbearing years. Demographers have long been strongly skeptical about this quantity because it normally indicates implausibly many children. Our analysis of data from the Romanian GGS confirms this finding, and we propose an alternative duration-based TMFR computed in the spirit of parity-progression ratios. At the same time, we extend the method to cover any type of living arrangement (cohabitation, marriage, non-partnered arrangement, and so on). Because each resulting total union-type fertility rate (TUFR) explicitly accounts for the living arrangement, it improves on the conventional total fertility rate (TFR), which does not. We embed the investigation in an event-history analysis with fixed and time-varying control covariates and find patterns of relative risks for such variables that reveal interesting features of childbearing behavior in the Romanian data, which we use to illustrate the method. In most cases, these patterns are quite robust against model re-specification, including the shift from the age-based to the duration-based approach. Since, the number of female respondents is "only" about 6,000 (minus records that cannot be used for the current purpose) in a normal single-round GGS, there is considerable inherent random variation in the data set, but we show that simple few-term moving average graduation suffices to overcome this problem.

The exceptionally high fertility among ultra-Orthodox Jews, and Arab minority, increasing portions of the population, is the main reason for Israel's flagging labor-force participation. In addition, high fertility diminishes Israel's skill attainment of the labor force. A rise in income inequality in all advanced economies, which in the last two decades has taken a sharp upward turn in Israel, has a potential for setting off social- divide and political polarization.

Paper presented at the 4th Strathmore International Mathematics Conference (SIMC 2017), 19 - 23 June 2017, Strathmore University, Nairobi, Kenya. ; Many studies have been done on fertility for many years. However, very little has been documented in the existing literature concerning modeling of fertility in the presence of interference, yet interference to fertility is a common phenomenon. In this study fertility data sets for Kenya were modeled both before and after interference. The parameters of the model were estimated by the maximum likelihood estimation method. Using Akaike's Information Criteria, (AIC), it was established that amongst the distributions fitted; Gamma, Weibull and Lognormal, Gamma gave the best fit for the Kenya fertility rate data and interference simply shifts the Gamma distribution parameters. The result of this study would help the Governments to understand fully the effect of interference on fertility rate and plan for it. Demographers would also benefit from this study since it can be used to project population growth after an interference. ; Masinde Muliro University of Science and Technology