Potential Economic Impacts of Agricultural Growth in Africa: Evidence from Guinea-Bissau

This research investigates the significant role of agriculture in economic development, particularly in Guinea-Bissau, a West African nation where agriculture constitutes a substantial portion of the economy. Early development economists like Kuznets, Lewis, and Johnston and Mellor highlighted the complementary relationship between agriculture and industry during economic transitions. While prior studies have demonstrated agriculture's contribution to economic growth, job creation, and poverty reduction, this paper aims to specifically quantify the potential impact of agricultural investment on Guinea-Bissau's economy and poverty levels. Guinea-Bissau's unique context, with approximately 60% of its population residing in rural areas and heavily reliant on agriculture for income (around 42% of output and 61% of the labor force), necessitates a thorough investigation of how agricultural improvements translate into broader economic and social benefits. The study's importance lies in understanding the potential for agricultural growth to alleviate poverty, enhance food security, and contribute to industrialization in a country where agricultural performance directly correlates with poverty incidence rates. Historical data reveals a clear link between agricultural productivity and poverty reduction, indicating that the agricultural sector is central to economic stability, growth, and the well-being of the population. The paper will focus on identifying the mechanisms through which agricultural performance impacts poverty alleviation.

The study builds upon existing literature examining agriculture's role in inclusive economic development. Ravallion and Chen (2007) analyzed the effect of sectoral growth on poverty rates in China, finding agriculture's impact on poverty reduction to be significantly larger than that of other sectors. However, their study focused on an economy where agriculture's share in GDP was declining, unlike Guinea-Bissau. Christiaensen et al. (2011) examined the impact of agricultural growth on poverty in several African countries, concluding that agricultural GDP growth is considerably more effective at reducing extreme poverty. However, their analysis lacked a dynamic computable general equilibrium (CGE) perspective, omitting crucial spillover and feedback effects over time. Several studies have used CGE models to evaluate the economy-wide outcomes of various reforms in Africa, including those by Cockburn et al. (2010), Maisonnave and Mamboundou (2022), and Savard and Adjovi (1998). Most relevant to this study are Chitiga et al. (2016), Vanduzai and Chitiga (2017), and Sangare and Maisonnave (2018), which applied recursive dynamic CGE models to assess the *ex ante* impacts of various economic policies. This study distinguishes itself by including multi-product industries, various types of rural and urban workers with cross-sector labor mobility, and a detailed analysis of the household-level effects of agricultural investment on job opportunities, income generation, and welfare implications. Furthermore, it addresses the critical role of agriculture in addressing housing shortages and food insecurity in Guinea-Bissau, a country highly dependent on agricultural taxes for government revenue.

This research employs a dynamic computable general equilibrium (CGE) model specifically designed for the Guinean-Bissau economy, building upon the PEP dynamic model described by Decaluwé et al. (2012). The model features an open economy with various industries producing multiple products. The key actors in the model include the government, the rest of the world (ROW), households, and firms. The model incorporates a nested optimization scheme to capture firm behavior, using a constant elasticity of substitution (CES) production function to model value-added, considering the substitution between capital and labor. Labor demand is disaggregated into skilled and unskilled workers across sectors, allowing for labor mobility. The model also includes demand-side components representing governments, households, and the ROW, using functional forms that reflect their behavioral characteristics. Household demand is modeled using a Stone-Geary function, considering heterogeneous rural and urban households with varying income levels. The model incorporates the supply of local goods to domestic and foreign markets, with perfect substitution for internationally traded goods, and captures the effects of both domestic and foreign prices. The price system includes factor prices, production prices, and final product prices, including a consumer price index (CPI). The model incorporates market clearing conditions, ensuring that supply equals demand across all markets. The dynamic aspect of the model incorporates public agricultural investment externalities, capturing their impact on productivity via a modified value-added equation. The dynamics of capital accumulation are also modeled, considering both public and private investment and their complementarity. The model uses a Social Accounting Matrix (SAM) for Guinea-Bissau, initially developed by Cabral (2015) and updated for 2014 by Cateia et al. (2023), incorporating both formal and informal activities. Households are disaggregated into groups based on wage levels, enabling analysis of poverty-level impacts. An econometric model, estimating an extended production function with capital, labor, and infrastructure as independent variables, is used to calibrate private investment sectoral allocation parameters. This model estimates the elasticity of private investment demand, which is then incorporated into the CGE model. The analysis includes direct, indirect, and price effects of investment on household welfare, considering changes in household income from different sources and changes in consumer prices. The simulation involves a baseline scenario (BAU) representing no interventions and a policy scenario involving a 4.3% increase in public agricultural investment financed through government revenues. The model's closure is dynamic, projecting investment levels from 2014 to 2030 while considering lags and adjustments. A sensitivity analysis was conducted by adjusting exogenous variables growth rates. The model was checked for consistency using staggered shocks of 5 and 10% of the numeraire.

The simulation results show that a 4% increase in agricultural investment leads to a substantial positive impact across various economic indicators. Aggregate real GDP increases by about 6%, with agricultural output rising by approximately 36% and non-agricultural sector production growing by about 19%. Exports increase by nearly 12%, driven by higher production and a falling real exchange rate. Employment increases significantly in both agricultural and non-agricultural sectors for both unskilled and skilled workers. Rural and urban household real incomes rise considerably (43% and 13% respectively), and aggregate household consumption increases in both rural and urban areas. Sectorally, agricultural investment's positive externalities stimulate growth across sectors, particularly in agriculture and food processing. The positive effects of externalities are magnified over time due to a cumulative effect. Significant increases in both export volume and the number of export goods are observed, potentially improving the country's trade balance and food security by reducing reliance on food imports. Analyzing household-level impacts reveals that rural households experience significantly higher real income growth (ranging from 8 to 15%) compared to urban households (3 to 4%). Poorer rural households benefit the most from increased labor income, while urban households with higher ex ante wages benefit more from capital income gains. Aggregate employment increases substantially (24%), with even higher gains in capital employment (37%). Direct effects, particularly improvements in agricultural employment income, dominate the income gains for the poorest rural households, while indirect effects via non-agricultural employment are crucial for urban poor households. Consumer price index (CPI) decreases contribute significantly to welfare gains for both rural and urban households, with the decline in food prices disproportionately benefiting the urban poor. Long-term simulation shows persistent positive effects on GDP growth, while the CPI decline diminishes over time due to capital depreciation. The study finds improved agricultural productivity leads to increased welfare, with household income and consumption increasing over the long term. The findings align with previous research showing positive impacts of agricultural investment on various economic and social outcomes.

The findings strongly support the hypothesis that increased agricultural investment in Guinea-Bissau can significantly improve economic outcomes and poverty reduction. The substantial growth in agricultural output, coupled with positive spillover effects into non-agricultural sectors, demonstrates the interconnectedness of the economy. The increased employment opportunities, particularly for unskilled workers in rural areas, directly address poverty alleviation. The model’s disaggregation of households into income groups allows for precise assessment of distributional impacts, revealing that the poorest households benefit most, particularly in rural areas due to direct income effects and in urban areas due to indirect income effects and falling food prices. The positive trade balance implications highlight the potential for improved food security and reduced dependence on food imports. The model's dynamic nature effectively captures the long-term impacts of agricultural investment, showing that its benefits persist even with capital depreciation. The results resonate with prior studies showing a positive correlation between agricultural growth and poverty reduction in various contexts. However, this study goes beyond simple correlations by providing quantitative estimates of the magnitudes of these effects within a specific economic model tailored to Guinea-Bissau.

This study makes a substantial contribution to the understanding of the economic impacts of agricultural investment in Guinea-Bissau and potentially other similar developing countries. The results demonstrate the significant potential for agricultural growth to drive overall economic growth, create jobs, alleviate poverty, and enhance food security. The dynamic CGE model provides a robust framework for assessing the complex interactions within the economy, highlighting the importance of targeted agricultural investments. Future research could explore the effects of other policies, such as climate change mitigation and adaptation strategies, on agricultural productivity and their combined impact on economic growth and poverty reduction. Further investigation into the potential complementarities between agricultural and industrial growth and its impact on labor reallocation could also enhance our understanding of Guinea-Bissau’s development path. Incorporating aspects like gender inequality and the impact of recent global shocks like COVID-19 would further strengthen the analysis and its policy relevance.

The study's limitations include its reliance on a specific CGE model and the inherent uncertainties associated with economic modeling. While the SAM incorporates informality, it might not fully capture all aspects of the complex informal economy. The model also doesn't explicitly account for recent shocks, like the COVID-19 pandemic, or thoroughly examine the implications for gender inequality. Future research could address these limitations by employing alternative modeling techniques, improving data quality, and incorporating more nuanced representations of the informal economy and social dynamics. The study is also limited by the quality and availability of certain data, which has affected the model's calibration.