Prioritising interventions for sustainable structural transformation in Africa: a structural equation modelling approach

ABSTRACT

Development paradigms offer competing theories on the drivers of structural transformation. Most of the analysis has so far focused on the economic factors with little emphasis placed on either the social or environmental dimensions of sustainable development. Furthermore, there has been little theoretical or empirical analysis of how the three dimensions (e.g. economic, social, and environmental) interact to impact on structural transformation. This leaves an important gap in the literature since the three sectors are interlinked, not mutually exclusive, and hence cannot be analysed in isolation from one another. Using a panel data set for a group of 29 African countries spanning the period 1995–2011, this study employs a structural equation modelling approach to estimate the direct and indirect impacts of social, economic and environmental indicators on a composite index of structural transformation. We find that strategies that prioritise investments in social inclusion programmes have the greatest catalytic effect in advancing structural transformation in Africa.

KEYWORDS:

• Structural transformation
• sustainable development
• structural equation modeling
• Africa
• development planning

Disclaimer

The views expressed in this paper are those of the authors and do not necessarily reflect the views of the United Nations.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Bartholomew Armah joined ECA following his tenure as a Professor at the University of Wisconsin-Milwaukee (USA). In his capacity as Chief of the Renewal of Planning, he coordinated consultations on the Post-2015 Development Agenda culminating in the adoption of the Common African Position by the AU Heads of State and Government summit in January 2014. He subsequently served as ECA’s technical advisor to the Permanent Representatives of African countries to the UN (i.e., African Group) in their post-2015 inter-governmental negotiations. He has a wide range of publications in his area of research, which include inclusive growth, poverty reduction and inequality. (Chief Renewal of Planning Section/Macroeconomic Policy Division/United Nations Economic Commission for Africa/PO Box 3005, Addis Ababa, Ethiopia)

Seung-Jin Baek is a South Korean Political Economist at ESCWA, working on knowledge production for the provision of evidence-based advisory services to countries on development plans, strategies, and frameworks. Additionally, he explored extensively designing of macroeconomic policy for sustainable development, working through other UN Economic and Social Commissions, including ECA and ECLAC. His research focus lies at the nexus of multidimensional inequality and sustainable structural transformation and is broadly applicable, most notably to the fields of development policy and political economy. (Economic Development and Integration Division/United Nations Economic and Social Commission for Western Asia/UN House P.O. Box: 11-8575, Riad El Solh 1107-2812, Beirut, Lebanon)

Notes

1 They are: Algeria, Angola, Botswana, Burkina Faso, Cameroon, Cote d'Ivoire, Egypt, Gabon, the Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Madagascar, Malawi, Mali, Morocco, Mozambique, Namibia, Niger, Nigeria, Senegal, Sierra Leone, South Africa, United Republic of Tanzania, Togo, Tunisia, Uganda and Zambia.

2 Economic growth has four selected areas of importance: output (proxied by annual growth rates of per capita GDP from the WDI), investment (proxied by total investment as percent of GDP from the WEO), green economy (proxied by renewable energy consumption as share of total energy consumption from the WDI) and energy use (proxied by energy intensity level of primary energy from the WDI).

3 Per capita GDP is admittedly controversial indicator of well-being. Despite its merit as a widely used measure of economic performance across countries it can be a misleading metric since it tells us little about the utility of the goods and services produced by a country. For instance, going to war increases GDP and destroying infrastructure and re-building it also increases GDP. Alternative measure of well-being includes the Genuine Progress Indicator and ‘Beyond GDP’ under the System of Environmental-Economic Accounts. For the purpose of this study it would be hard to see clearly the trade-offs or synergies effects between social inclusion and economic growth (using the Genuine Progress Indicator), and between environmental conservation and economic growth (using ‘Beyond GDP’ indicator) since these two indicators tend to be multidimensional in nature. Most importantly, lack of data availability in these relatively new measures remain a challenge in Africa. In fact, per capita GDP indicator is ultimately excluded from the analysis since it not statistically significance in the measurement model.

4 Social inclusion has four selected areas of importance: poverty (proxied by unemployment rate from the WDI), sanitation (proxied the share of population with access to sanitation facilities from the WDI), life quality (proxied by the number of years of life expectancy from the WDI) and maternal health (proxied by adolescent fertility rate at births per 1000 women ages 15–19 from the WDI).

5 The Physical Quality of Life Index is an equally weighted measure on well-being. It is based on: the basic literacy rate; infant mortality; and life expectancy. The Human Development Index (HDI) is a composite index of life expectancy, education and income per capita. A variant of the HDI is the Inequality-adjusted Human Development Index, regularly published by the United Nations Development Programme. These are the two most popular measures of social development, particularly emphasising human physical performance as a core element (Ray, 2008; Chang and Baek, 2011).

6 Environmental conservation has four selected areas of importance: climate change (proxied by emissions of carbon dioxide at metric tons per capita from the WDI); agricultural land (proxied by arable land at hectares per person; WDI); forest cover (proxied by forest area (square km); WDI); and water (proxied by the share of population with access to improved water sources; WDI).

7 Structural transformation has five selected areas of importance: agriculture (proxied by cereal yield (kg per hectare) from the WDI and by per capita gross agricultural production index from the FAO); manufacturing (proxied by manufacturing value added as a percent of GDP from the WDI); ICT (proxied by services value added as a percent of GDP and by internet users per 100 people from the WDI); health (proxied by infant mortality rate per 1,000 live births from the WDI); and financial market (proxied by domestic credit provided by financial sector as a percent of GDP from the WDI).

8 Thirteen of the 19 indicators are used to construct the social, economic and environmental drivers of structural transformation and they are transformed into the natural logarithm for modelling that show a positive skew to normalise their distributions.

9 Lower ratio of energy intensity indicates that less energy is used to produce one unit of output.

10 This is calculated by multiplying the two indirect effects (i.e. 1.073 by −1.630).

11 This is calculated by multiplying the two indirect effects (i.e. 0.933 by 0.869).

12 This is calculated by multiplying the two indirect effects (i.e. 1.060 by 2.629).

13 This is calculated by multiplying the two indirect effects (i.e. 0.958 by −2.472).

14 This is calculated by multiplying the two indirect effects (i.e. 1.039 by 1.645).

15 This is calculated by multiplying the two indirect effects (i.e. 1.056 by −1.184).