Women Fertility Decision using the Count Model in Malaysia

Fertility depends on household decisions in Malaysia; and, in turn, these decisions are strongly influenced by economic and socio-economic factors. Currently, fertility levels around the world vary according to the intergenerational relationships, the socio-economics statuses, and the socio-demographic characteristics of a particular nation. In general, more industrialized and economically developed societies have lower fertility than less-developed societies do. Groups that are more educated and earn higher incomes have lower fertility than less-educated groups with lower incomes do. The purpose of this paper is to dicuss the development of the empirical model to identify the principal determinants of fertility in Malaysia. The results stemmed from the use of panel data that is obtained from the Minnesota Population Centre, the Integrated Public Use Microdata Series, and international data provided by the Department of Statistics, Malaysia. In the empirical analysis, count models are employed. The findings show that marital status, owning a house, and households having women of child-bearing age all affect fertility decisions. In addition, social characteristics, such as ethnicity, religion, socio-economic status, and education level, affect household’s fertility decision.

The Malaysian government has introduced policies designed to improve this demographic performance as it sees a direct link between population and human capital development.Recognising that the family is the primary determinant of a healthy, dynamic, productive and competitive nation, the Government through the Ministry of Women, Family and Community Development (MWFCD) took the initiative to formulate a National Family Policy (NFP).Indirectly, the NFP acts as a provider of human resource with moral integrity through the strengthening of the family institution.These policies are intended to act positively on the majority of the country's social parameters, with the aims to develop prosperous, healthy and resilient families to ensure social stability.Under Malaysia's Sixth Development Plan (1991Plan ( -1995)), a comprehensive family planning program was formulated to educate the public on the practice of fertility control and also to address the issue of Malaysia's declining fertility rate.Table 3 presents the fertility rate from the period 1991-2001.The data shows a consistent rate of fertility and start declining in 1997 to 2001.These periods also marked the start of Asian financial crisis.The purpose of this paper is to identify the determinants of women fertility decisions, in Malaysia, for the period 1990 to 2001.The research problem is to identify any regularity that underlies the fertility decision during the demographic transition process and which factors that contribute the most to the process.
The research questions of the study are specified as follows: (i) What are the determinants of women fertility decision in term of socio demographics and socio-economics background?
(ii) Which factors of intergenerational effect, relative income effect, opportunity cost contributes to the fertility decision making?An increase in women's economy activity, women's high educational attainment, late marriage, childcare and education expenses, changing valuation of children, household income and the instability of employment status and residence are important factors contributing to the declining fertility rate (Ermisch, 1988(Ermisch, , 1989;;Caldwell & McDonald, 2002).Many studies have indicated that as women become more socially active, they are less inclined to have a baby directly after marriage (Shapiro & Mott, 1994).However, other studies in European countries have indicated that countries with relatively high levels of women's social participation have correspondingly higher level of fertility (Del Boca, 2003).In the empirical estimation, household fertility decisions, intergenerational relationships, socio-economics factors and demographic behaviors all contribute to fertility decisions.The study's result has the potential to reveal pattern in household's preferences for deciding fertility.This may allow practitioners and policymakers to prioritize the benefits of child care allowances and preparations for the upcoming generations.The remainder of this paper is organized as follows: Section 2 presents the literature review.Section 3 provides the methodology and data.The results and discussion are presented in Section 4, and Section 5 concludes the paper.

Literature Review
A modern family prefers to have fewer children as there is a common belief that parents of small families are able to provide each child with a better life.Becker (1960) theory on this topic is the most widely discussed.
Their quantity-quality model describes the increasing marginal cost of quality (child outcome) with respect to quantity (number of children), which leads to a tradeoff between the quantity and the quality of children.Morgan (2003) states that most countries will reach low fertility levels over the next two decades, and although this is not yet at a crisis level, this problem has become obvious in developed nations.He found that this increasing low fertility has resulted in the present slow growth of the global population.However, the main concern is the speeds at which aging populations are increasing and country-level populations are decreasing.This analysis is further supported by Lee & Mason (2010) who describe the phenomena of low fertility in Europe and East Asia, which causes essential changes in the age structure and also declines in population growth.Herzer et al. (2010) use panel cointegration techniques to examine the long-run relationship between fertility, mortality, and income.They note that a decrease in mortality leads to a decrease in fertility and that higher incomes per capita also lead to declining fertility.They conclude that fertility is both endogenous and exogenous, such that the income-fertility interaction provides a virtual cycle of demo-economic development.As Angrist et al. (2010) explain, most scholarly empirical evidence finds that the quantity-quality trade-off comes from the negative association between family size and the schooling or academic achievement of the population.They findings on the child-quantity or child-quality trade-off analysis, using quasi-experimental variations that show twin births and preferences for a mixed sibling-sex composition including ethnic differences, prove there is no evidence of a quantity-quality trade-off.Hondroyiannis (2004) conducts an empirical study on Greece, by employing count models and using a normal distribution for the fertility decision model.Here, the empirical estimations for households are determined by using socio-economic factors for households, and controlling for specific female characteristics, such as education level, age, social status, and health status, and controlling for household-specific characteristics, such as the number of rooms in the house.The finding revealed that female characteristics such as education and number of hours working affect inversely the household decision making (increase in opportunity cost of children will decrease the number of children).Another finding directs the study to accept the women's desired number of children in Indonesia is not only affected by their lifestyle and economic preferences, but also influenced by several variables in socio-demographic, socio-economic and personal or family factors (Utomo & Firmanto, 2007).
Fertility studies often model the number of live births over a specified age interval of the mother, while analyzing variations in terms of, say, mother's level of schooling, age, and household income (Winkelmann, 1995).Since count data can still be treated using a panel regression, the occurrence of zeros and the discrete nonnegative nature of the dependent variable suggest that, perhaps, a Poisson regression model and maximum likelihood should be used (Cameron & Trivedi, 1998;Winkelmann, 2000).Poisson and negative binomial regression models are designed to analyze count data.However, these models differ in regard to their assumptions of the conditional mean and variance of the dependent variable.A Poisson model assumes that the conditional mean and the variance distribution are equal.

Data and Methodology.
This section explains the data and method for the study.The data is sourced from the Integrated Public Use Microdata Series (IPUMS), which is made possible by Malaysia National Statistical Offices.The data set consists of females of child-bearing age (age 18 to 49), for the years 1990 and 2001.The base-case count model used in this study includes the following variables in addition to the constant term: NCHILD = (urban, ownrshp, poploc, momloc, marst, relig, occisco, edugroup, ethnicgroup) The following is the description of data for the year of 1991.The unit of observation is the individual.The responses of each person to the different census questions are recorded in separate variables.The dependent variable, NCHILD, is the number of children in the household who are less than 16 years of age.The independent variables Poploc, Momloc are included so as to capture the role and importance of parents in providing for the family and also to gather information on the relationships of the family members to the household head.The group of independent variables Poploc, Momloc and Marst are used as proxies of the intergenerational relationships.The demographic variables in this data will be urban, ethnicity, and religion.The variables Ownership, Education and Occupation are the proxies of the socio-economic status (relative income) of the household, since this particular dataset does not include other variables related to the household's social status.
According to Olfa & Lahga (1990), to resolve the problem of relative income (Becker & Lewis, 1973;and Becker, 1981) The other option to evaluating this model is to analyze the effect of the independent variable on the dependent variable through the incidence rate ratio (IRR).The IRR represents the change in the dependent variable, in terms of a percentage increase or decrease, with the precise percentage determined by the amount the IRR either above or below 1.The IRR for ownership, marital status and child-bearing age suggests that the number of children will increase by (16x0.6)9.6%, 0.7%, 0.4%, respectively.

Conclusion
This study has developed an empirical model that explains the determinants of household fertility decisions in Malaysia.The empirical results show a negative relationship between the number of children and social status (ownership, education, and socio-economic status), implying that households prefer the quality of children to the quantity of children.On the socio-economic and socio-demographic factors, home ownership, age, and marital status positively affect the number of children.The empirical results presented in this study support the neo-classical theory of fertility and are consistent with fertility studies of many other countries.These findings have important empirical implications for Malaysia, where the declining fertility rate will have an impact on the country's future aspirations of attaining a strong reliable domestic economy and the reallocation of women's time towards work and having a child.

Table 5 .
Specification results for Poisson regression and negative binomial regression