Consumption and Population Dynamics in Nigeria: Analysis and Micro simulations using Fertility Rate Variants

Abstract

This paper examines how changes in Fertility Rate Differentials affect household portfolio demand (expenditure on food, monetary transactions, goods and services and non-cash expenditure) in Nigeria. The paper disaggregated household portfolio into four categories and established a link between population dynamics (demographic variables) and household expenditure components using the Vector Error Correction Methodology. The estimated equations are used to project the pattern of the different components of household demand based on the optimum case population scenario. The results suggest that fertility dynamics in Nigeria can produce significant effects on the economy via the expenditure profiles of households.

Keywords

Portfolio choices population dynamics economic growth micro simulations

For most of this century, demographers have been intrigued by the consistencies of population issues in many different settings. These issues were considered so important that their occurrence spurred the development of the major body of conceptualization in demography. However, this notion gained momentum just after the publications by Davis (1945) and Notestein (1945), although the full essence of the contingency between modernization and declining mortality; fertility and the three-stage evolution had already been formulated by Thompson in 1929. Furthermore, the major elements of the subject matter had also been addressed previously by Landry (1909, 1934) and in the work of Carr-Saunders (1922, 1964/1936). Also, the classic representation of the demographic transition, sketched by Notestein, shows that mortality declined in the wake of the industrial revolution, which brought material changes in the sense of agricultural innovation, better communication, higher productivity, and improved health conditions. Nonetheless, fertility was much less responsive to such modernization, and its decline depended to a large extent on the collapse following mortality decline of normative systems that supported high fertility.

One of the most salient features of Nigeria’s economy is that since 1980, it has not shown real growth despite increasing population growth; however, the GDP per capita in 2006 was almost the same as it was in 1980 (Bloom et al., 2010). In 1980, Nigeria’s GDP per capita was slightly higher than that of Indonesia and Pakistan. Since then, Nigeria’s economy has stagnated, while Pakistan, and especially Indonesia, has grown considerably. Indonesia’s income per person is now roughly twice that of Nigeria. Meanwhile, East Asia in particular and the rest of the world have zoomed ahead. Part of the drag on Nigeria’s economy has been demographic. Since independence, Nigeria has struggled against very high fertility rates and high mortality, resulting in a high ratio of children in the population. Only since the 1980s have fertility rates begun to decline, albeit very slowly. Nigeria’s current fertility rate remains higher than in sub-Saharan Africa as a whole and is more than twice the world average fertility rate. The burden on society is reflected in the ratio of working-age to non-working-age population, which has declined since independence. But the demographic tide is turning, with falling crude birth and death rates beyond 2010, and fertility rates are also expected to continue falling. As a result, the share of working-age people in the population is expected to rise significantly from 2010 to 2050 (cited in Bloom et al., 2010), for the ratio of working-age to non-working age. Nonetheless, demographic change was not the only drag on Nigeria’s economy in the past. Other factors which have hindered Nigeria’s previous growth threaten its ability to realize its demographic dividend in the future. In particular, Nigeria’s institutions (example: rule of law, government capabilities in numerous realms, corporate ethics, civil liberties, interaction between private actions and public goals) are mediocre in African terms and poor when compared with countries from other regions (Bloom et al., 2010). Similarly, regional and ethnic inequalities, very low levels of investment in education and health, and a culture of youth violence pose significant challenges to Nigeria’s ability to benefit from its demographic transition (Alao, 2010).

The shape and structure of economic lifecycle, summarized by the amount consumed and by the amount produced through labor at each age, is important in understanding the interaction between age structure and the economic development of any country (Lee et al., 2008). There are extended periods at the beginning and end of life during which members of the population on average consume more than they produce through their labor. These periods of dependency bracket a period during which labor income substantially exceeds consumption. Nigeria, like most other countries in sub-Saharan Africa, is just beginning the transition to low fertility, but the economic support ratio for the country is not expected to peak for another 40 years or more. Although experiences of countries that already have a demographic dividend may be instructive for Nigeria, it is important to understand the general lessons that can be drawn from the experience of other countries. Nigeria’s economic life cycle is not conducive to a fast take-off. In particular, low labor income among young adults is a serious problem. If fertility decline is more rapid than anticipated and if labor conditions improve for young adults, then the economic support ratio will rise more rapidly and Nigeria will enjoy a larger demographic dividend over the next decade or two.

Population is both the producer and consumer of social and economic goods and services. Poor economic growth, which does not match the pace of increase in population numbers, puts more pressure on the limited capacity of governments to provide for basic socioeconomic needs. Recent studies on the nexus between population change and economic growth have two key features in common with another study that was published more than 50 years ago: Coale and Hoover’s book on Population Growth and Economic Development in Low-Income Countries published in 1958 (Coale and Hoover, 1958). These studies highlight and explain the fundamental insight that reducing the current rate of population growth does not lead always correspond to a reduction in the current rate of labor force growth. However, these studies also share some potentially significant limitations. Firstly, the imposition of a model in which causality runs only from population growth to income growth is at odds with established microeconomic theory and empirical evidence, which posits that income levels influence the growth and structure of population. For example, people with high incomes tend to place a high implicit value on their time. For example, given that child rearing is time intensive, it is not surprising that high-income earners also tend to have fewer children. This suggests that income growth tends to promote fertility decrease. Secondly, attention to population age structure is the key in both the study by Coale and Hoover and the recent literature. However, population growth and changes in age structure are only two of several plausible demographic influences on economic growth.

Furthermore, an important feature of the modern literature regarding the effects of demography on economic growth is the introduction of a broader definition of demography than simply the population growth rate (Barlow, 1994; Bloom and Freeman, 1988; Bloom and Sachs, 1998; Bloom and Williamson, 1997; Brander and Dowrick, 1994; Coale, 1986; Kelley and Schmidt, 1995). A finding from the recent economic development literature concerns the positive effect of good health status, as measured by life expectancy, on economic growth. Mason (1988) confirmed that this finding shows the greater incentives long-lived people have to save for old age. Furthermore, Meltzer (1995) shows that there are increased returns to investments in human capital associated with having longer horizons over which to recoup those returns, leading to higher productivity, and lower rates of absenteeism.

Conceptual Issues

Theoretical Framework

A striking feature of contemporary literature is the cosmetic attention given to the effects of population dynamics on economic growth. The basic framework acknowledges the possibility that rapid population growth might drag down economic growth. More often than not, demographic changes does not emerge as being significantly associated with the pace of economic growth, thereby supporting the conclusion of population neutralism (Bloom and Freeman, 1986) that has held sway for nearly two decades (Kelley and Schmidt, 1995). Recently, demographers have revisited the connection between population dynamics and development, and emphasized that demographic transition is the key factor underlying population growth in most countries (Bloom and Canning, 1999; Bloom and Freeman, 1988; Bloom and Sachs, 1998; Bloom and Williamson, 1997).

Nonetheless, demographic transition is a change from a situation of high fertility and high mortality to one of low fertility and low mortality. This indicates that high rates of population growth are temporary consequences of the decline in mortality before the decline in fertility. Less widely recognized, though perhaps more important, it also suggests sizable changes in the age distribution of the population. These changes occur for two major reasons. Firstly, the initial mortality decline is concentrated among infants, thereby concentrating its effects at the lower end of the age distribution. Secondly, the consequent fertility reduction has an effect on the age distribution that is, naturally, entirely concentrated at age zero. The combination of these two factors introduces a bulge into the population pyramid. Thus, over time, the bulge ages and moves from being concentrated among young people to being concentrated at the prime ages for working, saving, and reproduction, and eventually, to being concentrated at the years of old age. The young and the old tend to consume more output than they generate, unlike working-age individuals, whose contribution to output and to savings (Kelley and Schmidt, 1996; Lee et al., 1998; Mason, 1988; Webb and Zia, 1990) tends to be more than commensurate with their consumption. Consequently, the value of output per capita, which is the most widely used indicator of economic viability, tends to be boosted when the population of working-age persons is relatively large, and vice-versa when a relatively large part of the population consists of young and elderly people. In addition, a decline in the youth dependency ratio increases schooling per child to rise, adding to a possible future economic growth.

One of the significant issues of demographic aspects of economic development is that population changes, through its effects on population size, age structure and population distribution, affects the level of demand for consumption goods as well as its patterns. These changes of consumption pattern and level in turn affect overall and sectoral economic development. Knowledge of the determinants of household choices is important for many aspects associated with policy and economic analysis. Consumption by households is a determinant of sustainable development, and it has economic and social dimensions. It has important implications for the level and pattern of production, and for related demands for natural resources. Growth of private consumption has both positive and negative economic effects.

Malthus made his mark in the field of classical and Marxist economics in the 19th and beginning of the 20th century and in the economic analysis of population and development (United Nations, 1973). These macroeconomic approaches never became standard material in demographic theorizing, unlike the microeconomic orientations that firmly entered the field in the 1960s. Harvey Leibenstein (1957) may be called the progenitor of the view that the number of children is the result of individual decision-making within an economic context of income and prices. Among others, Willis (1973), Schultz (1981), and, most prominently, Gary Becker (Becker, 1981) developed the consumer choice theory into what became known as the new home economics of the Chicago school. The microeconomic approach not only involves the traditional variables of income and prices, but also the budget constraints in terms of allocation of time and opportunity costs. Given these variables, households are assumed to produce a bundle of consumer commodities in accordance with the maximization of household utility. The model links fertility decisions to other household decisions, including labor force participation and consumption. The notion of child quality became a key factor in Becker’s work to account for the inverse relation between income and number of children as experienced in the fertility transition. The quality of children also is assumed to be elastic with respect to income, whereas the quantity of children is not. This implies that the desired number of children may fall as income increases because the average cost per child may increase even faster.

The nexus of challenges to Nigeria’s sustainable development links population, household expenditure and economic growth together. The connection is indeed very complex. Nevertheless, proper understanding of how they interact is fundamental to the development of any sustainable economic policy in the country. Population is both the producer and consumer of social and economic goods and services. Poor economic growth, which does not match the pace of increase in population numbers, puts more pressure on the limited capacity of governments to provide for basic socioeconomic needs.

Fertility Projections in Nigeria: Historical Overview

The fertility inputs in the projection exercise are the Gross Reproduction Rate (GRR) that were obtained by applying a sex ratio at birth of 104 to the Total Fertility Rates (TFR) estimated from the 1991 Post Enumeration Survey (PES). Projected values of GRR were obtained based on the assumptions of the time it would take to reach a replacement level of 1 with the onset of fertility decline. The Economic Commission for Africa (ECA) has recommended similar assumptions for some Africa nations in population projection (ECA, 1986). The pattern of fertility decline is based on the stage of demographic transition and some results of family planning programs in Nigeria, from the results of the 1980 Nigeria demographic sample survey (NDSS), the 1981/82 Nigeria Fertility Survey (NFS) and the 1990 Nigeria Demographic and Health Survey (NDHS). At the state level, time-series data were not available for a similar evaluation. As indicted in the Analytical Report (Federal Office of Statistics of Nigeria, 1998), TFR values exceed the national average of 5.89 in 22 states and Abuja (Federal Capital Territory). The estimated GRR values indicate that a woman would replace herself with three female births in her lifetime in almost all the states. The past fertility rates, as stated above, suggest that Nigeria will not achieve a GRR of 1 in less than 50 years, and 1 after 70 years, i.e. at the rate of 6.7% decline every 5 years. With the high fertility in Nigeria, coupled with this background, it was assumed that fertility would decline at various rates until a replacement level of 1 is achieved in the future. The above assumption is applicable to all the states. However, they will achieve replacement level at different rates of decline during the projection period due to variations in the level of TFR and socioeconomic development. The age patterns of fertility and sex ratio at birth depicted by the 1991 Population Census and the PES were assumed to remain the same throughout the projection period. Due to the levels of TFR between 1980 and 1990, a medium variant (optimum case) of fertility decline was assumed for our analysis. However, the pessimistic and base cases were used in context for comparison effects.

Fertility variants

High variant: the high variant of a population growth pattern assumes that fertility will decline more slowly than the medium and low variant, and would reach a replacement level 10 years after the medium variant. Furthermore, the demand for, and supply of, the socioeconomic environment will continue to encourage mortality decline. International migration will be insignificant during the projection period. The total fertility rate is assumed to decrease gradually, to a value of 5.0 by 2005. The ultimate TFR will therefore be achieved after 35 years from 2025. This pattern implies a high and continuous population growth more than in the low and medium variants.

Medium variant: in the medium variant, the GRR is assumed to decline steadily at the rate of 6.5% to reach an ultimate level of 1 after 60 years. For this target to be achieved, it is assumed that the demand for and supply of family planning services with socioeconomic development be accelerated to encourage faster fertility decline. Contraceptive use in the 1990 survey was nearly negligible, but the medium projection shows it growing to about 28% over the 20 years from 1990 to 2010, at 1.1% a year; and continuing. Due to a young age structure and a high TFR the population in the decade before 2010 is projected to grow rapidly, by 23%-27% depending upon the projection chosen. (NDHS 1990). Fertility will decline more rapidly than the high variant, until it stabilizes at an ultimate level of 3.15 children per woman. It is assumed that the total fertility rate will decline slowly during the first 20 years, then faster until the replacement level is reached. It is expected that the TFR will be 5.47 between 2010 and 2015 and it will therefore continue to decline at faster rate from 2015–2020 until it reaches 3.15 in 2050. Despite the achievement of a replacement level of 1, the population will continue to increase due to the growth momentum in the age structure of the population.

Low variant: the rate of decline GRR under the low variant is assumed to be the fastest to achieve a replacement level of 1 after 50 years. The low variant assumes a faster decrease thereafter to reach a replacement level 10 years earlier. This accelerated rate of decline will occur with rapid socioeconomic progress and strong and effective family planning programs. As with the other variants, it is assumed that the fertility reduction factors will be favorable to a decline in TFR from 5.89 in 1990 to 3.20 in the 2015–2020 periods. At this accelerated rate of decline, a replacement level of 1, the population will continue to grow but at a slower rate.

Mortality Assumptions

The basic mortality inputs, both at the national and state levels, in the projections are the expectations of life at birth (e⁰) by sex. They correspond to the pattern of mortality implied by the North model life table (Coale and Demeny, 1966). Assumption on the future gains in life expectancy were made, taking into consideration the level of longevity already attained and the possible effects of any mortality and morbidity-reducing programs underway in Nigeria (Okoye, 1992). However, prevailing socioeconomic factors may not facilitate rapid and continuous mortality decline in Nigeria. As a result, it was assumed that the improvements (not the normal life table’s yearly increment) in expectation of life at birth by sex would vary under the three variants. Expectation of life (e⁰) at birth by sex is assumed to increase steadily. At the present estimates of e⁰ of 52.6 and 53.8 for male and female, respectively, it was assumed that the e⁰ will appreciate averagely at 1.6 and 1.8 quinquennials, respectively. These improvement rates were assumed based on the current e⁰ levels and pace of socioeconomic development in Nigeria.

The component of consumption expenditure will continue to rise in the future especially as the population is projected to increase. The next expenditure component in order of importance, but with growing tendency to decrease, is expenditure on goods and services. It accounts for about 28% of total household expenditure as at 1989. By 1996 its share of the total has decreased to about 16%. It started rising again in 1999, after reaching an all-time low in 1998. Hence, after another record low in 2003 it is expected to rise again into the future, especially as the population expands. Expenditure on monetary transactions and non-cash expenditure as percentage of total are exhibiting a decreasing share, with only monetary transaction expenditure showing signs of recovery beginning from 2001. The present study sheds more light on the time part of these variables over time.

Data and Methods

VECM Analytical Framework

The specification shown below was used to estimate equations for four components of disposable income expenditure categories: food, (CEXFOOD) monetary transaction (CEXMONTRAN), non-cash expenditure (CEXNCE) and other goods and services (CEXOGAS). The specification shown below is used to estimate equations for four expenditure categories: goods and services (CEXOGAS), expenditure on monetary transactions (CEXMON), expenditure on food (CEXFOOD) and non-cash expenditure (CEXNCE). The equations serve as a basis for projecting household expenditure. Projected expenditures sum up the disposable income, which is used in estimating the private consumption function. The general specification of the expenditure equation is:

Expenditure (YD) = f (Pop, Pcy, Int, Roete)

(1)

The general specifications of the disposable income expenditure equations for households are:

CEXFOOD = f (P o p, I n t, R o e t e, P c y)

(2)

CEXMONTRAN = f (P o p, I n t, R o e t e, P c y)

(3)

CEXNCE = f (P o p, I n t, R o e t e, P c y)

(4)

CEXOGAS = f (P o p, I n t, R o e t e, P c y)

(5)

Where

Exp = expenditure categories (CEXFOOD, CEXMONTRAN, CEXNCE and CEXOGAS)

Pop = population variables (AVPOP5 and below, AVPOP5-14, AVPOP15-24,

AVPOP25-34, AVPOP35-44, AVPOP45-54, AVPOP55-64, AVPOP65 – 74 and AVPOP75 and above)

Int = interest rate

Roete = ratio of other exp categories to total exp

Pcy = per-capita income

The equations are estimated in log-linear form. The E-Views Software has an in-built Lag Selection Criterion. This tries to see the impact of past historical information on current situation. We chose to lag for only a period because of robustness of results and to avoid Type Errors. Lagging is done because most policy frameworks require a bit of time for the effects to be seen. Thus within a year, we argue that the effects of population dynamics would have been seen on expenditure patterns.

The sampling period used for the equations is 1980–2010 and a lagged dependent variable was introduced on the right-hand side in each of the five equations to test for serial dependence. The signs of the right-hand side variables varied. The interest rate have a negative sign for CEXFOOD, CEXNCE, CEXOGAS and positive sign for CEXMONTRAN; the ratio of other expenditure categories to total expenditure had a negative sign, while population variables had a positive sign for all expenditure categories of the disposable income, and per-capita income had a positive sign against all endogenous variables. The per-capita variable in the model increases expenditure from the demand side, thus measuring how elastic income of households are, just as an increase in any of the specified age bracket raises aggregate demand schedule of households and vice-versa.

Testing for Stationarity

Testing for stationarity involved the use of several tests; namely the Dickey–Fuller (DF) tests; Augmented Dickey–Fuller tests (ADF); Phillips–Perron tests (PP) and Akaike Information Criterion (AIC).

DF, ADF and PP procedures involve testing whether variables/series in a model are stationary or testing the order of integration through unit root tests. The DF test is a test against the null hypothesis that there is a unit root series integrated of orders one (i.e. I (1)). The ADF test is the same as the DF, except that here augmentations in terms of lags of Xt are incorporated. All the tests were run at a 1% and 5% level of significance. An attempt was made to strengthen the test by systematically eliminating insignificant lags to finally establish the optimal lag length. To avoid over-differencing the variables therefore, we ignore the suggestion by the ADF test that some of the variables are integrated of orders higher than one. This assumption is consistent with econometric theory, which postulates that most macroeconomic variables would exhibit unit roots, becoming stationary after first differencing. Otherwise macroeconomic variables would likely be stationary. The test for unit root using the ADF indicated that real gross domestic product, private investment, public investment and real exchange rate are non-stationary, with one as the order of integration.

Results

Domestic credit to the private sector and real interest rate were shown to be stationary series. All tests were significant at both 5% and 1%. The lag length criteria (AIC) did not improve with further increases in the lag length.

Using our data set we estimated micro equations on the four expenditure categories to project the household aggregate consumption and hence the disposable income up to 2017, as well as their growth rates over the same period on the base line, optimum, and pessimistic population projections.

Equation Results: Expenditure on Goods and Services

In general, estimation of this equation using a lagged dependent variable¹ improves the result, looking at the information criteria and R² statistics. The results suggest that this expenditure category increases as people become older. This is so because old people tend to consume more than the young.

Results in Table 2 present a robust outlook using the information criteria and R² statistics. The results suggest that expenditure on this category decreases as population dynamics spreads. The age bracket of 18–24 and 25–34 show a strong influence on this expenditure pattern of the household. This becomes obvious given the excessive demand of the people within this age bracket. It is within this age bracket that most people begin to increase their demand for goods and services as they settle down into married life, and experience has shown that demand for goods and services by people within this age bracket is more than eight times the demand by the older segment of the population (i.e. people above the age of 65). The estimated equation seems to support the above view.

In general, estimation of this equation using a lagged dependent variable worsens the result. The results suggest that expenditure on this line item is correlated to the working-age bracket. This is due to the belief that these individuals are in a position to use non-cash methods such as credit cards, value cards, cheques, etc., to make most of their purchases and payments. Results indicate that households have less of their income to spend on this category.

Further simulations show that the percentage change between the base line and optimum and between the base line and the pessimistic projections for expenditure on food, and goods and services is increasing over time, while that for monetary transactions and non-cash expenditure is negative but decreasing in absolute value, which implies increase as well. However, the percentage change between base line and pessimistic projection is wider than the percentage change between base line and optimum projection, thus suggesting that population dynamics have significant effects on the growth rate of consumption expenditure.

These findings reinforce the previous results in the aggregate case. The percentage increases are offset by the percentage decreases so that in the long run, consumption expenditure follows a constant growth path, despite the increases projected for the total population. This prediction is consistent with the Solow² growth model which concludes that changes in consumption, savings and investment as well as population increases cannot account for sustained increases in either the standard of living or in economic growth. Such sustained growth can only be achieved through increases in technological progress. From the foregoing, it is obvious that fertility differentials in Nigeria may pose adverse effects on the socioeconomic wellbeing of the country.

In addition, the graphs show how the aggregate household consumption changes over time. The base line projection (Figure 1) shows that aggregate real consumption between 2005 and 2008 would be on the decrease and thereafter begins to grow, reaching all-time high of 2.9% by the year 2010. The projection further shows that aggregate consumption would plummet to about 2% by the year 2011 and stabilizes there for the rest of the period until 2017. This is because the fall in the growth rate of non-cash expenditure and monetary transactions would be counter-balanced by the increase in growth of the expenditure food and expenditure on goods and services, so that the aggregate consumption remains stable at about 2% despite the threat of total population increase.

Figure 1.

Percentage change in disposable income (base case projections).

The results from optimum projection (Figure 2) suggest a two-period variation in aggregate consumption over the projection period as the population expands. First, the projections show increasing consumption between 2006 and 2010 of about 3%, and thereafter it decreases to about 2% and remains constant until 2017 despite the threat of population growth over the projection period.

Figure 2.

Percentage change in disposable income (optimum projections).

The pessimistic projection (Figure 3) shows a somewhat different picture for aggregate consumption expenditure. The graph shows that as population expands, the growth rate of aggregate expenditure converges to about 2.9%. One common characteristic observed from the results is stability in the growth of aggregate consumption expenditure. This is suggestive that the current reform policies in Nigeria as well as the realization of the millennium development goals would lead to economic stability but may prevent rapid growth rate of the economy. Also, population dynamics are likely to lead to a rise in the aggregate consumption expenditure of the household, looking at the figures for the pessimistic projections. This would have profound implications for the growth of the Nigerian economy, realizing that consumption expenditure alone accounts for about one-third of total aggregate expenditure of the economy. High consumer spending, especially on goods and services, is needed to encourage investment and thus propel growth in any economy.

Figure 3.

Percentage change in disposable income (pessimistic projections).

Generally, our results reveal an interesting path for household consumption expenditure as the population expands over time. We found that expenditure on food will continue to dominate the other components of household consumption expenditure in the long run, followed by expenditure on goods and services (Figure 4). As higher population is projected into the future, it is expected that households will spend more on food, as well as on goods and services, than on other categories of expenditure (i.e. non-cash and monetary transactions expenditure). This could be attributed to the fact that population expansion is consistent with increases in the demand for food as well as the demand for goods and services, especially in a typical developing country.

Figure 4.

A comparison of base case, optimum and pessimistic projections in disposable income in Nigeria.

General Discussion

The estimated elasticities shown in Table 1 indicate that other factors remaining constant, one percentage increase in the ratio of other expenditure categories results in about a three percentage real decline in the spending on goods and services. This could be attributed to the fact that as other expenditure categories, such as payment of house rents, school fees, etc., become due for payment, an extra burden is added to households. Thus, the demand for goods and services would decline or at least be postponed. A 1% increase in real interest rate decreases household expenditure on goods and services by about 2% (probably due to wealth effects).

Table 1.

Population dynamics and expenditure on goods and services.

Variables	LnCEXOGAS	LnCEXOGAS	LnCEXOGAS
Constant term	2.56(1.341)	−5.3(4.031)	7.02(2.143)
LnCEXOGAS (-1)			0.326 (1.531)
LnAVPOP5	−0.876 (−2.169)		−0.183 (−1.786)
LnAVP6-11		0.321 (−3.021)	−0.573 (2.113)
LnAVP18-24	1.783 (2.391)		3.06 (−3.184)
LnAVP25-34			2.523 (1.340)
LnAVP35-44			1.784 (−2.727)
LnAVP45-54	1.987 (2.241)		1.534 (−3.43)
LnAVP55-64		0.308 (7.753)
LnAVP65-74			−0.354 (3.213)
LnAbove75	0.112	−0.345 (5.907)
LnInt	−1.456 (6.32)		−2.213 (0.231)
LnRoete			−3.098 (−2.564)
LnPcy			1.987 (−2.341)
R 2	0.789	0.565	0.875

The results from Table 2 further suggest that people above the age of 45 do form a significant part of household total demand for goods and services. Hence, the ageing component of the population is still important in determining the aggregate expenditure of the household on goods and services, despite the higher expenditure by the younger generation or age groups. Members of the household below the age of 5 do not seem to have any positive influence on the household demand for goods and services. As the per-capita income increases, the household expenditure on goods and services increases. More specifically, one can say that household expenditure on goods and services is income elastic. The estimated elasticities also indicate that other factors remaining constant; a 1% increase in the interest rate results in over a 3% real growth in the spending on monetary transactions (this could still be attributed to wealth effect); a 1% increase in household per-capita income increases expenditure on monetary transactions by almost 3%; while a 1% rise in the ratio of other expenditures to the total expenditure causes the household expenditure on monetary transactions to fall by almost 2%. The results also indicate that as population of people within the age bracket of 18–75 begin to increase their expenditure on monetary transactions, households have less to invest (Table 2). Thus a negative relationship between population dynamics and monetary transactions becomes clearer, especially at the middle age brackets when people involve themselves more and more in financial transactions. Moreover, people who are in the middle age brackets find it relatively easier to borrow money to spend than the younger segment of the population. The life cycle hypothesis predicts that at middle ages people would involve themselves in a lot of monetary transactions as they pay off accumulated debts at the start of life and begin to acquire financial assets such as shares, bonds, as well as other real estates in order to provide for the age of retirement. Also, people within this age group spend money on the payment of school fees for their children and other forms of child-related expenditure. All these factors help to explain increases in monetary transactions in Nigeria as the population spreads. We also found from the estimated equation that past expenditure of the household on monetary transactions does have a significant positive elasticity on current expenditure. This is in agreement with the relative income hypothesis that predicts that immediate past expenditure has some significant positive effect on the current spending of the household.

Table 2.

Population dynamics and expenditure on monetary transactions.

Variables	LnCEXMON	LnCEXMON	LnCEXMON
Constant term	−4.8 (5.97)	2.65 (−6.462)	3.12 (2.198)
LnCEXMON (-1)	0.696 (−2.098)		0.391 (6.310)
LnAVPOP5	1.473 (3.121)	1.836 (2.407)	2.563 (0.231)
LnAVP6-11	1.789 (−3.432)		0.361 (2.09)
LnAVP18-24		−1.869 (−5.241)	−1.805 (3.139)
LnAVP25-34		−1.672	−2.634 (0.563)
LnAVP35-44			−3.654 (−1.784)
LnAVP45-54			1.972 (−1.919)
LnAVP55-64	1.337 (1.239)
LnAVP65-74			−2.348 (5.218)
LnAbove75
LnInt		1.973 (0.671)	3.389 (0.764)
LnRoete			−1.953 (−2.31)
LnPcy			2.786 (−1.221)
R²	0.542	0.613	0.861

The results from Table 3 suggest that all the exogenous variables have a positive relationship with the endogenous variable except the interest rate. It would therefore be safe to infer that as the interest rate increases, forward-looking households would reduce the current spending on food in order to invest their money so as to earn a high-interest income that would guarantee them higher future consumption (Table 3). The results indicate in general terms that households would be more inclined to spend on food subsequently unless there is a shift in policy. Results show that those between the ages of 18–64 drive this expenditure pattern, as their corresponding elasticity coefficients are greater than unity. This pattern of household expenditure on food explains the high incidence of poverty and high level of underdevelopment in Nigeria. Development theorists such as Ragnar (1961) predict that high consumption expenditure on food in most least developed countries (LDCs) is an indication of underdevelopment. This result, however, confirms the high level of underdevelopment and poor standard of living of the Nigerian populace. We also found that immediate past food expenditure does have a positive, though not a significant, influence in the current expenditure. Furthermore, the estimated elasticities in Table 4 suggest that non-cash expenditure decreases with age brackets 5–24 because this household category does not have many non-cash transactions to make, as they are dependents and can spend only when they are given cash. The positive elasticity on interest rate with respect to this expenditure category suggests that a high interest rate could mop up cash balances in the economy, as households would undertake more saving and use advance payments receipt and other means to pay for their purchases³.

Table 3.

Population dynamics and expenditure on food.

Variables	LnCEXFOOD	LnCEXFOOD	LnCEXFOOD
Constant term	−0.452 (3.11)	1.231 (0.716)	1.338 (0.227)
LnCEXFOOD (-1)	1.705 (9.932)	1.842 (−1.49)	2.653 (0.573)
LnAVPOP5	1.032 (7.231)		0.867 (2.509)
LnAVP6-11		1.467 (2.117)
LnAVP18-24			1.987 (3.103)
LnAVP25-34	0.459 (4,481)	1.936 (−6.341)	2.532 (0.541)
LnAVP35-44		1.876 (1.872)	2.337
LnAVP45-54	1.876 (−3.315)		1.357 (0.657)
LnAVP55-64			1.875 (1.219)
LnAVP65-74
LnAbove75	−1.814 (4.512)	1.980 (−0.432)
LnInt
LnRoete			−2.883 (4.381)
LnPcy	1.983 (0.897)	1.992 (0.841)	2.234 (0.284)
R ²	0.501	0.764	0.982

Table 4.

Population dynamics and expenditure non-cash expenditure.

Variables	LnCEXNCE	LnCEXNCE	LnCEXNCE
Constant term	1.032 (−4.351)	0.756 (4.423)	0.865 (1.784)
LnCEXNCE (-1)	0.234 (0.761)	0.345 (1.307)	0.452 (2.324)
LnAVPOP5	1.481 (2.112)
LnAVP6-11	−1.739 (−3.334)	−1.801 (0.413)	−2.231(0.467)
LnAVP18-24			−3.014 (−2.098)
LnAVP25-34		1.983 (−1.285)	2.876 (1.345)
LnAVP35-44			1.975 (0.327)
LnAVP45-54		0.832 (2.642)
LnAVP55-64	1.349 (4.876)		−3.815(−2.326)
LnAVP65-74			−2.362 (3.312)
LnAbove75	0.874 (2.221)		−1.672 (−4.610)
LnInt	0.830 (3.431)	−1.451 (−3.032)	−2.970 (1.098)
LnRoete			−.4.853 (−0.116)
LnPcy			2.993 (2.174)
R²	0.729	0.664	0.935

Available statistics suggest that Nigeria has started a demographic transition. A major issue, however, is whether the decline in fertility is real or due to problems with the data. While some evidence suggests that there has been an underestimation of births, data on other proximate determinants of fertility appear to be inconclusive. There is a need to strengthen initiatives made in health care to ensure that preventive and curative health services reach many women and children. This will contribute to the achievement of a sustained demographic transition. Economic difficulties in maintaining large families as a result of the economic crisis are forcing people to change traditional beliefs in large family sizes and the traditional system of the African extended family that had hitherto led to high fertility rates. At the same time, the desire for child bearing is still strong in Nigeria, particularly in the rural areas. This has given rise to the strong view that the levels of fertility and contraception use are not likely to change until there is a drop in desired family size and until the idea of reproductive choice is widely accepted.

Nonetheless, fertility impact has been felt within child and maternal health, human capital investment, natural environment and economic growth of the country. Recent studies suggest that a high fertility rate places children at high risk, with the impact of high fertility considered a critical human capital investment within formal schooling. However, parents need to decide to have fewer children in order to invest more per child, with school investment salient. Policies on fertility reduction have been an effort that needs to encourage couples to reduce the prevalence of large siblings-sets that are obstacles to the schooling of their members (Casterline, 2010).

The impact of fertility differentials is greatly felt on the available services, increased expenditure on goods, rapid population growth, and increased imported food and consumer goods, with the emergence of street children within the economy. As a result, poverty and unemployment rate have increased, with rural urban migration on the rise. The changing trends in expenditures on food within this society are obvious, with the implication of most national income spent on food, monetary transactions between the have and have not, and with an increased demand for imported food products which has caused harm to the domestic market. However, the high fertility rate has been attributed to the early marriages that are still a common practice in most parts of the country, with three-quarters mothers getting married before the age of 18 years. Moreover, contraceptive use is very low, with a high demand for children due to tradition, religion and high infant mortality in most parts of the country (Ogujiuba and Ade, 2005).

A recent study indicates Nigeria’s engagement in demographic transition, but with some doubts on the accuracy of the information released, as most of the results underestimated records on births. However, Nigeria needs to strengthen its initiatives within the health care milieu in order to ensure that preventive and curative health services are made available to most women and even children, as this will help achieve a sustainable demographic transition (Schultz, 2007). The challenges of maintaining large families as a result of the high fertility rate are now pushing people to change their traditional beliefs in large family sizes and the traditional system of the African extended family. Thus, having many children is no longer a source of pride within most African societies, as they are aware that a large family size entails greater expenditure. Despite this, the desire for child bearing in Nigeria is still very strong, especially within the rural areas, and this has led to a strong view that the fertility level and the rate of contraceptive use will not change unless there is a drop in the desire for family size (Ogujiuba and Ade, 2005).

It is therefore recommended that the government integrates population variables in socioeconomic development, and policy makers, planners and grass root community agents should appreciate the need for balanced development within the economy. However, programs that are geared towards development should be introduced at the grass root level, with collaboration between governments, NGOs, the private sector, community leaders and religious organizations on issues related to development and population dynamics initiated. Moreover, strategies that are aimed at reducing poverty, especially involving income generation and employment creation, should be integrated into policies and programs within the various sectors. It is therefore necessary that structures coordinating population and development are in line with finance, and staff training and facilities are strengthened in order to enable population and development to be properly coordinated and executed effectively.

It is important to understand that as family sizes increases, households tend to incur more debts with more interest in order to sustain the family. It can therefore be ascertained that, as the interest rate increases, households that are aimed at moving ahead in terms of growth would reduce their current spending on food in order to invest their money so as to earn a high-interest income that would guarantee them higher future consumption. Thus, such households would be looking forward to spending more on food at a subsequent time unless there is a shift in policy. This pattern of household expenditure on food explains the high incidence of poverty and high level of underdevelopment in Nigeria.

Conclusion

In Nigeria, the nature of development planning and policy analysis has changed remarkably since the early 1980s. A lot has to be done to fully realize the goal of full integration of population data in socioeconomic planning and reducing the impact of fertility differentials on household portfolio demand.

This process involves more than the adequacy of data, and includes putting in place the required institutional arrangements to ascertain the interrelationship between population and capacity of the planning system. The National Planning Commission has a major role to play here, while other data-producing agencies should co-operate with it to ensure that data is produced in good time. Furthermore, people should be educated on how to manage the implications of expenditures wisely, and limit monetary transactions on goods and services, because of the long-term implications. Much has to be done to reduce the impact of fertility differentials on household portfolio demand. This process, however, involves more than just reducing fertility levels within the economy, but also training experts to educate people on how to manage their expenditures wisely, and limit monetary transactions on goods and services, especially in situations where population dynamics are strong.

Footnotes

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Notes

Author Biographies

Ogujiuba Kanayo is a member of several research and management development networks. He has published several articles in reputed journals. His consulting and research interests are in Economic Demography, Public Policy and Economic Theory. He has worked on several projects and has been a consultant/senior policy adviser on World Bank, USAID, DFID, ECA, UNDP, EU, WAMI projects and to government agencies in Nigeria in the last 15 years. He holds a PhD in Development Economics, which was funded through a research grant from the African Economic Research Consortium (AERC). At present he is a Research Associate at the Statistics and Population Studies Department, University of Western Cape.

Ogujiuba Chinelo has a background in economics and is currently a Post-Graduate Student at the Statistics and Population Studies Department, University of Western Cape. Her research interests are in the areas of Migration, Reproductive Health and Development.

Appunni Sathiya Susuman completed his PhD in Demography at the University of Kerala, India, in 2000. His research efforts are concentrated in the field of population components such as fertility, mortality, and migration. Keeping abreast of his research aspirations in the field of technical demography, he focuses mainly on the Demography of Health, with attention to a life course analysis of health risks, interventions and outcomes. He worked on several research projects in India, Ethiopia and South Africa. He has published several articles in reputed journals. He is a member of the Population Association of America, the Union for African Population Studies, the International Union for Scientific Study of Population, the Asian Population Association and Statistics South Africa and Population Association of South Africa. At present he is working as Professor (Associate) in the Faculty of Natural Sciences, University of the Western Cape, Cape Town, South Africa.

References

Alao

(2010) The politics and socio-economic dynamics of demography in Nigeria: The past and present in the future. Background Paper for Nigeria: The Next Generation Project; Next Generation

Barlow

(1994) Population growth and economic growth: Some more correlations. Population and Development Review 20: 153–165.

Becker

(1981) A treatise on the family. Cambridge (MA): Harvard University Press, 288 p. (2nd ed., 1991, 424 p.).

Bloom

Canning

(1999) From demographic lift to economic liftoff: The case of Egypt. Paper presented at the Conference on Growth Beyond Stabilization: Prospects for Egypt. 3–4 February 1999. Cairo, Egypt.

Bloom

Freeman

(1986) The effects of rapid population growth on labor supply and employment in developing countries. Population and Development Review 12: 381–414.

Bloom

Freeman

(1988) Economic development and the timing of economic growth. Journal of Policy Modeling 10: 57–81.

Bloom

Sachs

(1998) Geography, demography, and economic growth in Africa. Brookings Papers on Economic Activity 2: 207–273.

Bloom

Williamson

(1997) Demographic transitions and economic miracles in emerging Asia. World Bank Economic Review 12: 419–456.

Bloom

Finlay

Humair

. (2010) Prospects for Economic Growth in Nigeria: A Demographic Perspective. Paper presented at the IUSSP Seminar on Demographics and Macroeconomic Performance held at Novotel, Gare de Lyon, Paris, France, 4–5 June 2010. Available at: http://www.ntaccounts.org/doc/repository/BFHMOS2010.pdf.

10.

Brander

Dowrick

(1994) The role of fertility and population in economic growth: Empirical results from aggregate cross-national data. Journal of Population Economics 7: 1–25.

11.

Casterline

(2010) Determinants and Consequences of High Fertility: A Synopsis of the Evidence – portfolio review. Washington, DC: World Bank. Available at: http://documents.worldbank.org/curated/en/2010/06/14500903/determinants-consequences-high-fertility-synopsis-evidence-portfolio-review.

12.

Carr-Saunders

(1922) The Population Problem: A Study in Human Evolution. Oxford: Clarendon Press.

13.

Carr-Saunders

(1964) World Population: Past Growth and Present Trends. London: Frank Cass & Co.

14.

Coale

(1986) Population trends and economic development. In: Menken

(ed) World Population and U.S. Policy: The Choices Ahead. New York: Norton. Chap. 3, pp. 110–126.

15.

Coale

Demeny

(1966) Regional Model Life Tables and Stable Population. Princeton (New Jersey): Princeton University Press.

16.

Coale

Hoover

(1958) Population Growth and Economic Development in Low-Income Countries. Princeton (New Jersey): Princeton University Press.

17.

Davis

(1945) The world demographic transition. Annals of the American Academy of Political and Social Science 273: 1–11.

18.

ECA (1986) Economic Commission for Africa, Annual Report. ECA.

19.

Federal Office of Statistics of Nigeria (1998) Nigeria Demographic and Health Survey. Columbia, MD: lRD/Macro International Inc.

20.

Kelley

Schmidt

(1995) Aggregate population and economic growth correlations: The role of the components of demographic change. Demography 32: 543–555.

21.

Kelley

Schmidt

(1996) Savings, dependency, and development. Journal of Population Economics 9: 365–386.

22.

Landry

(1909) Les trois théories principales de la population. Scientia 6(11– 3): 3–29.

23.

Landry

(1934) La Révolution Démographique. Paris: Recueil Sirey.

24.

Lee

Mason

Miller

(1998) Saving, Wealth and Population. Paper prepared for The Symposium on Population Change and Economic Development co-sponsored by the Rockefeller and Packard Foundations and The United Nations Fund for Population Activities (UNFPA) held at Bellagio Center, Lake Como, Italy, 2–6 November 1998.

25.

Lee

S-H

Mason

(2008) Charting the economic life cycle. In: Prskawetz

Bloom

Lutz

(eds) Population Aging, Human Capital Accumulation, and Productivity Growth, a supplement to Population and Development Review Vol. (33); pp. 208–237 New York: Population Council.

26.

Leibenstein

(1957) Economic Backwardness and Economic Growth. NY: John Wiley & Sons

27.

Mason

(1988) Saving, economic growth, and demographic change. Population and Development Review 14: 113–144.

28.

Meltzer

(1995) Mortality Decline, the Demographic Transition, and Economic Growth. Unpublished paper. Cambridge (MA): Brigham and Women’s Hospital and National Bureau of Economic Research.

29.

Nigeria Demographic and Health Survey (1990) Preliminary Report (Federal Office of Statistics and Demographic and Health Surveys, Institute for Resource Development/Macro Systems, March 1991)

30.

Notestein

(1945) Population: the long view. In: Schultz

(ed) Food for the World, Chicago: Chicago University Press, pp.36–57.

31.

Ragnar

(1961) Equilibrium and Growth in the World Economy. Gottfried Haberler and Robert M. Stern (eds). Harvard Economic Studies CXVIII. Cambridge, MA: Harvard University Press.

32.

Ogujiuba

Ade

(2005) Challenges of Population Dynamics in Nigeria: Implications for Household’s Portfolio Choices. Nigerian Statistical Association Conference proceedings, 12–17 September, Enugu, Nigeria.

33.

Okoye

(1992) Population Projections; Techniques of Demographic Data Analysis with special reference to Sub-Saharan Africa. Monograph Series No. 6. Legion: Regional Institute for Population Studies, University of Ghana, pp.350–404.

34.

Schultz

(2007) Fertility in Developing Countries. Center Discussion Paper.Economic Growth Center, No. 953; Available at: http://hdl.handle.net/10419/26992.

35.

Schultz

(1981) Economics of population. Reading (MA), Addison-Wesley, 240 p.

36.

United Nations (1973) The determinants and consequences of population trends. New summary of findings on interaction of demographic, economic and social factors, vol. 1. New York: United Nations.

37.

Webb

Zia

(1990) Lower Birth Rates = Higher Savings in LDCs. Finance and Development 27: 12–14.

38.

Willis

(1973) A new approach to the economic theory of fertility behaviour. Journal of Political Economy 81(2 Pt. 2): 14–64.