The Population Policies and Fertility Decline in Ghana 

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Theoretical Framework of Ghanaian Fertility Transition

Developing countries have experienced significant decline in fertility in recent decades (Bongaarts, 2008) and this decline has been faster in sub-Saharan Africa (Parr, 2002). A variety of factors and theories ranging from economic, social to cultural have been proposed to explain this transition, related to patterns of family formation, family size and fertility control behaviors. In Ghana’s case, we focus on how norms and attitudes influence fertility behavior using the theory of planned behavior and the Innovation-Diffusion theory.

Theory of Planned Behavior

Norms and beliefs play a critical role in shaping individuals’ fertility behavior. These norms are prescriptive or proscriptive in the sense of “should” or “should not”, which are supported by consensus (Settersten Jr & Mayer, 1997) and are backed by sanctions ranging from punishment to stigmatization (Durkheim, König, & König, 1984). The theory of planned behavior (Ajzen, 1991) underscores how subjective norms impact fertility behavior. According to the theory, the intention of a particular act is the immediate determinate and single best predictor of certain behavior. See figure2 below Ghana is one of the countries in sub-Saharan Africa that has several ethnic groups and beliefs based on tribal associations and common socio-cultural identity. These beliefs vary across the various tribes and ethnic groups. Therefore the decisions of an individual, especially reproductive rights or decision are influenced by the ethnic and family setting, which influences the timing of birth and the number of children an individual can have. The Akans for instance are predominately pro-natalist but have relatively long birth intervals, whereas the other ethnic groups such as Ga-Adangme have shorter birth intervals (Oheneba-Sakyi & Heaton, 1993). Religion is also another important predictor of fertility in sub-Saharan Africa (Adongo, Phillips, & Binka, 1998; Gyimah, Adjei, & Takyi, 2012).
For instance, the traditionalist believes that children are lineage, therefore if there are no children, lineage will break so a woman should give birth to many children. However a study conducted by Adongo et al. (1998) in the northern region of Ghana, where these practices are common, shows that preference for a small family size is now evident even in these rural communities.
A number of studies on fertility have pointed to education especially female education as an important factor in reducing family size in developing countries (see Bbaale & Mpuga, 2011; Kravdal, 2002; Vavrus & Larsen, 2003). The question is how does female education reduce family size?
A high level of women’s autonomy or power through education in decision making is one mechanism of having fewer children. In a much cited paper, Dyson and Moore (1983:45) define Autonomy as ‘‘the capacity to manipulate one’s personal environment and the ability- technical, social and psychological to obtain information and to use it as the basis for making decisions about one’s private concerns and those of one’s intimates’’. Women’s education and labor participation are the two main proxy variables used as women’s autonomy. Many studies (e.g., Basu, 1996; Jejeebhoy, 1995; Sathar, 1996) used female education as a proxy to measure women’s autonomy and reproductive behavior. Although it is widely held that women’s autonomy leads to fertility decline, results from these studies are more complex. Sathar’s (1996) findings indicate that education gives women more autonomy and a greater role in fertility decision making to have fewer children, whereas Basu’s (1996) study concluded that women’s education and autonomy is not sufficient for fertility decline. She argued that although women’s education is essential in the fertility decision making process, contraceptive use and other family planning measures should not be ignored.
Even though women’s autonomy plays a role in the reproductive decision making, the role of the man and his fertility desire cannot be overlooked. In a male-dominated society like Ghana where males dominate over fertility decision, work by DeRose and Ezeh (2005) on men’s influence on fertility decline in Ghana revealed that although a man’s influence on fertility decision outweighs a woman’s, her education plays a role in the reproductive decision making process. Thus, a high level of education empowers women in decision making to question traditional roles (McDonald, 2006) and reject traditional beliefs and values supporting a large family size (Weinberger, 1987), hence fertility decline.

Innovation-Diffusion Theory

The diffusion of innovation theory is one of the oldest theories in the social sciences developed by E.M Rogers in 1962 (Rogers, 2010). This theory provides an alternative explanation to the main stream socio-economic demographic theories to explain fertility decline (Casterline, 2001). Over the last two decades, a number of studies using this theory assert that fertility decline is not only an adaptive response to socio economic changes but also is due to the spread of key attitudes and behaviors as well as social interactions (Casterline, 2001; Montgomery, Casterline, & Heiland, 1998; Palloni, 2001). This theory has not only been applied to fertility transition, but also to mortality change (Montgomery, 2000).
The innovation diffusion theory consists of two components that are linked but distinguishable-“innovation” and “diffusion”. The former being the increased prevalence of attitudes and behavior that were hitherto absent in society and the latter involving the spread of attitudes and behavior due to increased prevalence (Casterline, 2001). The spread of ideas, behavior and technique from one social group or individual to another (Retherford & Palmore, 1983) is often through channels such as language, ethnicity and religion. According to the theory, during the diffusion process, individuals can be categorized into five stages: innovators, early adopters, early majority, late majority and laggards. The early adopters and innovators of contraceptive use are individuals who are well educated (Casterline, 2001; Weinberger, 1987), live in urban areas (Casterline, 2001) and then later spread their ideas and behavior to other parts or segments of society. For instance, if a woman of reproductive age begins using modern contraceptives, other women in the community might also start using them through either formal or informal social learning. This form of social influence leads to attitudinal change in reproductive behavior in the population, which may lead to fertility decline.
Research has consistently shown that female education is an important element of contraceptive behavior because it supports the ability to use modern contraceptive and even switch from one method to another in developing countries (see Bbaale & Mpuga, 2011; Benefo, 2006; Cleland, 2002; Curtis & Blanc, 1997; Parr, 2002). There are several reasons why contraceptive use increases as female education increases. To summarize briefly, these studies indicate that educated women have adequate information about modern family planning methods and use them effectively as compared to women with no or less education. Also, less educated women are less capable of understanding television and radio messages on family planning methods as compared to highly educated women due to differences in literacy rates (Parr, 2002).
Education also increases spousal communication (Weinberger, 1987), which can lead to fertility decline (Oyediran & Isiugo-Abanihe, 2002). Avogo and Agadjanian (2008) study on the impact of traditional religion on fertility in the northern region of Ghana revealed that the social networks of partners and communication on reproductive matters significantly increases the likelihood of contraceptive use among women. The availability of family planning methods and the use of modern types of contraceptives by women may contribute to the reduction in the demand for children as well as influence the spacing and timing of births contributing to fertility decline.
The recent rapid fertility decline in Ghana may be the result of the increased prevalence of attitudes and behaviors that were previously rare in the society. The use of modern contraceptives and other family planning methods which were hitherto not practiced in Ghana have now become diffuse throughout the country. Even modern birth control measures that were previously unknown or unacceptable by some segment or ethnic groups due to religious and ethnic beliefs are now practiced (Adongo et al., 1998). This is due to the intensive campaign of family planning methods and education expansion across the country by the government. As indicated earlier, there has been a rise in knowledge and use of modern contraceptives over time after the policy implementation; because educated women are more likely to be aware of these family planning methods and even use them effectively as compared to women without any education.
Recent studies conducted by Parr (2002) on contraceptive use and fertility decline in Ghana indicate that knowledge about family planning methods increases the likelihood of usage. The finding of the study further shows that contraceptive use is higher among highly educated women as compared to low educated women. With respect to trends, the late 1990s and early 2000s witnessed higher usage of modern contraception among women with secondary education as compared to the periods before the policy implementation. The difference in percentage between women with no education and those with secondary education is non negligible. This is evident in the Ghana Demographic Health survey (GDHS) report. The report revealed that, women with secondary and higher education who were current users of modern contraception was about 6.7% in 1988, 13.8% in 1993, then increased to 20.3% in 1998 and 28.1% in 2003 as compared to 3.2% in 1988, 3.6% in 1993, 8.9% in 1998 and 11% in 2003 for women with no education (GSS & Macro, 1989, 1994, 1999, 2004). The effect of increase contraceptive use especially among highly educated women might lead to postponing childbearing to later years; which can lower the chances of giving birth to many children.

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Data and Methods

The data for the study was obtained from the Ghana Demographic & Health survey (GDHS) conducted in 2003. The survey was undertaken by the Ghana Statistical Service (GSS) in collaboration with the Noguchi Memorial Institute for Medical Research (NMIMR) and Ghana Health Service (GHS) and was conducted between July and October in 2003. The GDHS in 2003 was a national representative survey of women and men in their reproductive age, 15 to 49 years from 6,251 households. A total of 5,691 women and 5,015 men were interviewed yielding a response rate of 96% and 94% respectively. Only women were included in the analyses because the population policy was mainly targeted at women. The survey obtained detailed information on fertility, marriage, sexual activity, fertility preferences and awareness of and the use of family planning methods.

Method of Analysis

The analytical design of this study is to estimate the propensity of having had a first, second, third, fourth and fifth birth. Examining the risk of birth using retrospective information brings to bear some problems where some of the events of interest may not have occurred yet to some portion of the sample (Allison, 2010). This brings about the problem of right censoring caused by incomplete experience of the event studied. In this regard, “censored cases need special attention and treatment when estimating the exposure time; for this reason, normal regression procedures are unsuitable. To overcome this problem, survival models are more appropriate for such analyses, since they make the assumption that censored individuals will eventually experience the event at some time” (Gyimah, 2003, p. 8) or not.
The study is done using piece-wise exponential hazard model based on exponential distribution to estimate the relative risk of births controlling for the relevant covariates that affect the risk of birth. The choice of exponential hazard regression model over other models, especially the non-parametric model, is that the exponential model completely specifies the hazard function h(t) and the survival function s(t) and is more consistent with theoretical s(t) (Hamilton, 2012).
The exponential distribution has a constant hazard ( ) = . Thus, the survival function is ( ) = exp{− } and the density is ( ) = exp{− }. (1)
In this study, we used ´ command to fit a piece-wise exponential proportional hazard model, thus the explanatory variables were introduced into the hazard model using the proportional hazard model specification below; = 1 1+ 2 2 +⋯+ (2)
Where is the hazard corresponding to the individual i in interval j, is the baseline hazard for interval j, and 1 1+ 2 2+⋯+ is the relative risk for an individual with covariate , compared to the baseline, at any given time.

Variables

The dependent or outcome variable in our study is the risk of bearing a(nother) child (or survival time of women until the time they bear a(nother) child), up to the fifth birth. To observe childless women at risk of having a first child, the trajectory is followed since they turn 15 until the first birth, or turn 50, or were interviewed (by October 2003), whichever comes first. In the case of higher order births, duration since first birth, duration since second birth, duration since third birth and duration since fourth birth are measured for second, third, fourth and fifth birth analyses, respectively, or were censored at age 50 or the interview, whichever comes first.
Calendar period is the most essential time-variant covariate used in this study, because the main goal of the study is to evaluate the population policy of Ghana. Since women who turned 49 years in 2003 were born in 1954 and turned 15 years in 1969, we used 1969 as the base year. Calendar years is aggregated into seven year groups (1969-73, 1974-78, 1979-83, 1984-88, 1989-93, 1994-98, 1999-03) for first birth, second birth and third birth and six year groups (1969-78, 1979-83, 1984-88, 1989-93, 1994-98, 1999-03) for fourth and fifth birth, where special attention will be given to childbearing trends after the 1994 population policy. We categorized calendar year systematically so that the year the policy was implemented will be at the beginning of the period instead of putting it in the middle or at the end. This will enable us to see easily the effect or non-effect of the policy.
Education is an important variable that helps to explain women’s reproductive behavior and the impact of the policy. Because one of the main objectives of the policies is to increase the proportion of females with secondary and higher education, women’s education is one of the main independent variable used for the study. According to Gyimah (2003), because the educational attainment of women in Ghana does not change once childbearing starts, it is always assumed that the educational level at the time of the survey is similar to the educational level at the birth of the first child. Nevertheless, we reconstruct the educational histories of women at first birth to avoid anticipatory analysis (see Hoem & Kreyenfeld, 2006). The reconstruction of the educational histories follows the (6-3-3-4) education system in Ghana, which starts at the age of 6 years. The system represents 6 years of primary school, 3 years of junior high school, 3 years of senior high school and 4 years of university or 3 years for other tertiary institutions like the polytechnic or teachers training college. We combined the variable “highest educational level” and “highest year of education” to reconstruct a time varying education variable and categorized it into three groups: no education, primary and secondary / higher.

Table of contents :

1.0 Introduction 
2.0 The Population Policies and Fertility Decline in Ghana
3.0 Theoretical Framework of Ghanaian Fertility Transition
4.0 Data and Methods
5.0 Findings and Discussion
6.0 Summary and Conclusions
Acknowledgement
References
Appendix

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