Conceptual framework
The study used the Production Function (PF) analytical framework to estimate the loss in GDP attributable to deaths related to disasters in the Region. A PF describes the transformation of the factors of production (inputs) into outputs with its existing technology. The general mathematical form of the production function is: Y = f(L, K, R, S, v, ã), where: Y = output, L = labour (skilled, semi-skilled and unskilled), K = capital (buildings, equipment and inventories), R = raw materials, S = land input (which encompasses all natural resources), v = returns to scale, and ã = efficiency parameter, measuring the entrepreneurial-organizational aspects of production [
9]. Thus, a PF shows the maximum amounts of the various combinations of outputs that a country can produce with its existing resources and techniques [
10].
The gross domestic product (GDP) is one of the main national output measures. GDP is the sum of the total value of consumption expenditure, total value of investment expenditure, government purchases of goods and services and net exports (i.e. exports minus imports) of goods and services. It can also be viewed as the total value of consumption expenditure, gross private savings (including business and personal savings); net tax revenues (tax revenue minus domestic transfer payments, net interest paid and net subsidies); and total private transfer payments to foreigners [
11].
Intuitively, disaster-related deaths can impact on the production of GDP in a number of ways. First, they reduce the quantity of the labour force and hence the number of people involved in output production. Second, disasters maim and kill the unskilled, semi-skilled and highly skilled labour force and entrepreneurs, who are in acute short supply in the African Region. The attrition of the latter three categories of human resources may impact negatively on GDP.
Third, the typically high funeral-related costs might force affected households to liquidate/sell off some of the output-producing assets (e.g. land, farm machinery and equipment) to pay for funerals. In third world economies, characterized by the high levels of underemployment/unemployment of the labour force and the low levels of capital investment, depletion of these assets could spontaneously lead to a reduction in output.
Fourth, given the high levels of poverty across the African Region, the bereaved children may be forced to drop out of school due to lack of school fees, or to work in order to compensate for the lost household income. This would have adverse repercussions on human capital creation (i.e. the quality and quantity of future labour force) and hence on the sustainability of GDP and its growth.
Fifth, premature death of people in active labour force may lead to a reduction in the total household consumption expenditure, government tax revenues, private business and personal savings, and hence the resources available for investment purposes.
Sixth, when disasters strike, households, governments and non-governmental organizations are forced to divert resources from productive sectors into reconstruction/rehabilitation programmes. And often, such programmes do not make net contributions to GDP.
Formally, the effect of disaster-related mortality on GDP can be expressed as follows:
GDP = f(D, L, K, HK, EA, OE, DS) (i)
where: GDP = real per capita gross domestic product, i.e. real value of annual volume of goods and services divided by population; D = land; L = labour input (persons aged 15 years and above); K = physical capital stock; HK = human capital, i.e. the skills and knowledge embodied in a person; EA = entrepreneurial ability (the ability to plan, organize and produce new commodities); OE = openness of the economy; and DS = number of people killed by disasters.
Equation (i) shows the effect of DS on GDP, holding the effects of D, L, K, HK and EA constant. If deaths caused by disasters are a burden on the economies of African countries, the coefficient for DS variable would be expected to assume a negative sign. The effects of the explanatory variables on the dependent variable (GDP) are unlikely to be linear; thus, in this study we shall estimate Cobb-Douglas production function of the following form:
GDP = aDß1Lß2Kß3LEß4ENß5Xß6Mß7DSß8e (ii)
where: LE is life expectancy; EN is school enrolment; X is exports and M is imports.
Taking the logarithms of both sides of equation (ii), we obtain the following log-log (or double-log, log-linear or constant elasticity model):
log GDP = log a + ß1 log D + ß2 log L + ß3 log K + ß4 log LE + ß5 log EN + ß6 log X + ß7 log M + ß8 log DS + e (iii)
where: log is the natural log (i.e. log to the base e, where e equals 2.718); a is the intercept term (i.e. the output if all the explanatory variables included in the model were equal to zero); ß's are the coefficients of elasticity, which can take any value between 0 (perfectly inelastic) to 8 (perfectly/infinitely elastic); and e is a random (stochastic) error term capturing all factors that affect gross domestic product but are not taken into account explicitly in the model [
12]. Why, readers might ask, did the authors choose to include the above-mentioned variables in the model?
'Land' includes all natural resources like soil, mineral deposits, rivers, lakes, sea, fish, forests, oil (petroleum), natural gas, wild animals, etc. Civilizations have drawn great strength from productive land resources [
13]. It is common knowledge that agriculture is the backbone of the majority of the economies in Africa. Most of the African people earn their livelihood from land, either directly (through farming) or indirectly (in agro-processing industries). More than three decades ago, Professor Gunnar Myrdal [
14], a Nobel laureate in economics, made the following remarkable statement: "It is in the agricultural sector that the battle for long-term economic development will be won or lost." That statement is very pertinent to Africa even today. We would expect a positive relationship between the arable land per capita and GDP per capita, since agriculture makes substantive contribution to the latter.
'Capital' means the stock of physical reproducible factors of production, i.e. tangible investment goods, e.g. plant and equipment, machinery, buildings, etc. [
15]. Development economists have argued that capital formation (i.e. investment in capital goods that leads to increase in capital stock, national output and income) is the key to economic growth and development. The process of capital formation entails: (i) an increase in the volume of real savings; (ii) the existence of credit and financial institutions to mobilize savings and channel them to productive use; and (iii) the use of these savings for investment in capital goods [
10].
There are a number of ways of bringing about capital accumulation/formation: (i) forced savings through taxation (to siphon them off into the coffers of the State), deficit financing and borrowing from the public; (ii) government could use the profits earned by public corporations for capital formation; (iii) government could restrict importation of luxury consumer commodities through import duties or tariffs; (iv) removal of underemployed agricultural workers whose marginal productivity is negligible or zero from the land and employing them on various capital projects such as irrigation, roads, railways, hospitals, house buildings, etc.; (v) start of joint ventures whereby foreign investors bring technical know-how along with capital, and train local labour and entrepreneurs; and (vi) negotiate for favourable terms of trade, save part of the export earnings and invest them in the acquisition of capital stocks. Since capital is acquired primarily to boost production, one would expect a direct (positive) relationship between capital investment and GDP per capita.
'Labour force' refers to all economically active persons, including the armed forces and the unemployed but excluding housewives, students and economically inactive groups [
15]. Given the high levels of unemployment and under-employment in African economies, it is difficult to predict whether an increase in the labour force, with the stock of capital held constant, would translate into an increase in the total output (GDP).
'Human capital' are the productive investments embodied in human beings. These include skills, abilities, ideals, values and health resulting from expenditures on education, on-the-job training programmes and health care (including curative, rehabilitative, preventive and promotive care). It is the human resource of a nation (i.e. the quantity and quality of its labour force) and not its physical capital or natural resources that ultimately determines the character and pace of its economic and social development [
15]. Unlike capital and natural resources, which are passive factors of production, human beings are the active agents who accumulate capital, exploit natural resources, build social, cultural, economic and political institutions and carry forward national development [
16]. To be consistent with the past production function studies on the economic burden of health problems [
17], we have used two proxies of the human capital in this study.
(i) Combined primary, secondary and tertiary school enrolment ratio (EN) as a proxy for education-related human capital, the rationale being that there is evidence in the economics of education literature that schooling raises earnings and productivity mainly by providing knowledge, skills and a way of analysing problems [
18]. Some studies have shown that education promotes health, reduces the likelihood of smoking [
19], increases the likelihood of toilet ownership [
20], improves the probability of the use of contraceptives [
21], raises the propensity to vote (i.e. participate in the democratic process) and stimulates the appreciation of classical music, literature and even sports [
22], all these being non-monetary benefits. Other studies have also found that health education knowledge about modes of transmission of HIV/AIDS, its prevalence and preventive measures empowered women to exercise their right to uncoerced choice to have safe sexual relationships [
23]. Given the direct relationship between education and earnings, it is expected that the education variable (EN) will have a positive impact on GDP.
(ii) We have used life expectancy at birth (LE) to capture health-related human capital. Of course, we are aware that health consists of both health-related quality of life as well as quantity of life. Since in this study we are concerned with only the mortality aspect of disasters, it made sense to include only life expectancy. According to the World Bank [
24], there is strong evidence which shows that poor health (from high morbidity and mortality) imposes immense economic costs on individuals, households and society at large. Becker [
18] argued that a decline in the death rate at working ages may improve earning prospects by extending the period during which earnings are received. Ram [
25] found a positive relationship between life expectancy and real GDP per capita. Keeping in view the foregoing arguments, one would expect life expectancy to have a positive partial effect on GDP per capita.
All economies in the countries in the African Region are open economies, which means that they do not exist in isolation but trade goods and services [
26]. However, the degree of 'openness' among countries varies considerably. In this study we have used exports and imports as a proportion of GDP as a measure of the degree of openness.
Export (X) is the value of all goods and non-factor services
sold to the rest of the world; they include merchandise, freight, insurance, travel and other non-factor services [
15]. Since exports represent an injection of expenditure by foreigners into the domestic expenditure/income flow, it is expected to be directly related to GDP per capita.
'Import' (M) is the value of all goods and non-factor services 'purchased' from the rest of the world; they include consumer goods (e.g. pharmaceuticals, non-pharmaceutical supplies) and capital goods (e.g. machinery, equipment, medical technologies, vehicles, computers). Thus, M captures all expenditure on imports by all economic agents – households, business enterprises, the government sector, parastatal institutions, non-governmental organizations, etc. Imports (M) mean a leakage from the national income/expenditure flow to the rest of the world [
27], implying that it would be expected to be inversely related to GDP per capita.
The purpose of the current study was to estimate the loss in GDP attributable to natural and technological 'disaster-related deaths' (DS). Thus, it is obvious that the variable had to be included in the analysis. If DS imposes economic burden on African economies, its coefficient would be expected to assume a negative sign.