3. Trends of Poverty, Economic Structure, Human Capital, Infrastructure and Environmental Degradation

Spatial analysis of poverty: Combining geospatial data and survey data to Public Disclosure Authorized study regional inequality in Ghana Tomomi Tanaka (World Bank) Jia Jun Lee (World Bank) Abstract This study combines district level poverty rates, population census data, income data, and Public Disclosure Authorized geospatial data to investigate how human capital, structural change, infrastructure, and environmental degradation impacted poverty and employment in Ghana. We find that poverty reduction was primarily achieved through increased share of working age population, employment rates and income in the service sector, shift of labor from agriculture to the service sector, expansion of access to electricity, and increased rainfall. Further, the paper investigates the factors that have affected changes in agricultural income and shift of labor from agriculture to industry and services. Soil erosion had a large impact on the changes in agricultural income. Improved access to electricity, road, and market was crucial for creating jobs in non-agricultural sectors. In areas where droughts are severe, more people became engaged in agriculture and less in industry and services. It may be because severe droughts prevent people from investing in non-agricultural sectors. The results of this study suggest that for Ghana to reduce poverty and Public Disclosure Authorized create jobs in non-agricultural sectors in lagging areas, it needs to invest in infrastructure, and take actions to mitigate damages from soil degradation and droughts. Public Disclosure Authorized 1 1. Introduction Ghana has achieved significant poverty reduction since the 1990s and accomplished the first Millennium Development Goal (MDG) of reducing the poverty rate by more than half. Between 1991 and 2012, the national poverty rate declined from 52.7 percent to 24.2 percent. The national poverty rate further declined to 23.4 percent by 2016. Starting from higher than the mean for low- and middle-income countries (LMICs), Ghana’s international poverty headcount today is lower than the current LMIC average. Even though the poverty rate fell at the national level, spatial inequality intensified with some regions lagging. Regional poverty rates had fallen dramatically in the Ashanti, Eastern, Greater Accra, Brong Ahafo, Central, and Western regions (Figure 1), while poverty rates remain above 50 percent in the Northern, Upper West, and Upper East regions. In addition, the pace of poverty reduction has slowed down in the Volta region. Poverty rates vary not only across regions but also across districts within regions. As Figure 2 shows, poverty rates were generally high in most districts in the three northern regions (Northern, Upper West, and Upper East regions) in 2000. However, the spatial distribution of poverty has changed dramatically between 2000 and 2010. The eastern part of the three Northern regions achieved significant poverty reduction, while several districts in the western side of the country witnessed rising poverty. Clusters of districts with high poverty rates also developed in the inland parts of the country and in the Volta region. A key question of this study is how some districts were able to reduce poverty, while others were not. We investigate how human capital development, structural change, infrastructure, and environmental degradation affected poverty, income and employment in Ghana. Human capital development is critical for poverty reduction as educated and healthy labor force is central to wealth creation and productivity growth (Schultz 1961). A higher share of working age population in the economy helps the country achieve economic development and poverty reduction, since there are more people available for productive activities. Investment on education is a plausible way to escape poverty, as education is often a prime means of social mobility. Reduction of fertility helps families to invest more on each of their children. For these reasons we select a share of working age population, educational attainments among working age population, and fertility as key variables for the anlysis. Even when there is a higher share of working age population, economic development is difficult if there are not enough jobs in productive sectors. McMillan and Harttgen (2014) and Diao, Harttgen, and McMillan (2017) show much of Africa’s recent growth and poverty reduction has been associated with structural change; a substantive decline in the share of the labor force engaged in agriculture. In Ghana, the share of employment in agriculture fell from 50 percent to 42 percent between 2000 and 2010, while the share of employment in services rose from 34 to 2 42 percent during that period. Meanwhile, the employment share in industry slightly declined. Ghana’s pattern of structural change is consistent with the general observation in Sub-Saharan Africa, i.e. premature deindustrialization (Rodrik 2016). In Africa, workers mainly relocated from agriculture to trade services, instead of manufacturing (De Vries, Timmer, and De Vries 2015). De Vries, Timmer, and De Vries (2015) and Duarte and Restuccia (2010) point out that even though productivity levels in trade services are often higher than productivity in agriculture in Africa, its productivity growth is sluggish and stagnant. Geiger, Trenczek, and Wacker (2018) confirm that Ghana is following the same trend; productivity in services is stagnant and has been declining in Ghana since 2005. The question arises whether structural change, a shift of labor from agriculture to services, contributed to poverty reduction in Ghana. Gollin, Parente, and Rogerson (2002) and Christiaensen, Demery, and Kuhl (2011) demonstrate how agriculture can be effective in reducing poverty, especially among the poorest. Breisinger et al. (2008) shows the poverty rate among cocoa farmers declined from 60 percent to 24 percent in Ghana between 1991 and 2005. Beginning in the late 1990s, cocoa production rapidly grew due to favorable prices, and Ghana has become the world’s second-largest cocoa producer. As a result, the poverty rate among cocoa farmers significantly declined. This paper validate that increases in agricultural income contributed to increased consumption not only in cocoa production areas, but also in the whole country. People in poor areas are often disadvantaged by lack of access to infrastructure such as roads and electricity. Access to infrastructure is necessary for developing household enterprises, raising productivity and increasing incomes. In South Africa, household electrification encouraged the establishments of microenterprises and raised employment (Dinkelman 2011). Improved roads stimulate industrial development (Fernald 1999), and benefits the poor (Jacoby 2000). Growth of road and electricity-generating capacity accounted for approximately half the growth of the productivity residual of India’s manufacturing sector (Hulten, Bennathan, and Srinivasan 2006). In Ghana, there is a substantial difference in access to electricity, market and roads between poor and rich areas. It is conceivable that lack of access to infrastructure inhibits the development of non-agricultural sectors, and misallocate labor across sectors (Gollin, Lagakos, and Waugh 2013). The spatial inequality may not only reflect disparities in infrastructure but also ecological differences. Even though agriculture remains the dominant sector in the three Northern regions, the climate is not suitable for cocoa and other cash crops. Farmers in these regions are mainly engaged in rain-fed, traditional subsistence agriculture, as they have limited access to irrigation. In addition, the northern regions are frequently affected by floods and droughts, accompanied by high temperatures and intense heat (Figure 4). The northern floods of 2007, for example, affected 317,000 people, destroyed 1,000 km of roads, 210 schools, and 45 health clinics, and damaged or contaminated 630 water facilities. Furthermore, it was followed immediately by drought. Crop losses are higher in districts with no irrigation, and when floods and droughts occur one after another (Yiran and Stringer 2016). Poverty in the northern regions may have been also influenced by land degradation, as land degradation is concentrated in the poor northern regions (Figure 4). land degradation leads to lower agricultural production, which in turn leads to food insecurity, poverty and vulnerability (Lal 2004, West et al. 2014). 3 This study combines district level poverty rates, population census data, income data, and geospatial data to investigate how human capital, structural transformation, access to infrastructure, and environmental factors affected poverty, income and employment. We find poverty reduction was achieved through increased employment rates, especially women, increased income in the service sector, shifts of labor from agriculture to services, expansion of access to electricity, and increased rainfall. In addition, education, access to electricity, shift of labor from agriculture to services are important determining factors of the level of poverty. The paper further investigates what determines agricultural income and structural change. Better access to electricity is the most critical factor facilitating the shift of labor from agriculture to industry and services. Soil erosion had a large impact on the changes in agricultural income. Severe drought inhibits people from moving from agriculture to non-agricultural sectors. It may be because a large economic loss from

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