Leveraging improved seed technology, migration and climate information for building the adaptive capacity and resilience to climate risks in semi-arid regions - Gitonga, Zachary Maina (School of Economics, 2021)
Droughts induced by climate change will most likely push dryland ecosystems beyond their biophysical thresholds and lead to long-term decline in agricultural productivity. Subsistence farming in developing countries where agricultural productivity is low will become less viable for many families already ravaged by food insecurity and poverty. This dissertation examines three ways of reducing vulnerability to the adverse effects of climate variability and building resilience in the farming communities residing in semiarid lands. These include the use of adaptive seed technology, migration as a livelihood diversification and adaptive strategy, and the use of climate information in farm decision-making. The second chapter evaluates the impact of improved adaptive seed technology on market participation and food security, using data from a representative sample of 1344 households selected across six agroecological zones in Kenya. The study employed two estimation procedures for impact evaluation: a control function regression using OLS and IV regression estimated by Heckman bivariate sample selection model and 2SLS regression. The study used percentile shares approach to describe distributional inequalities in improved seed adoption across households. Kenya has a well-developed seed system, through which adaptive maize seed has been introduced for various agro-ecological zones. Despite its success with improved maize breeding programs, Kenya is still grappling with food insecurity. The marketed share of household's maize produce, among adopters, was on average 12 percentage points higher than for the control group. This increased with adoption intensity, albeit at a decreasing rate. The top 20% of households accounted for 63% of the quantity and 65% of the area planted with improved maize. The bottom 40% only accounted for 6% of the quantity purchased and 5% of the area planted with improved maize. Adopting households were less vulnerable to food insecurity and stored maize for longer than non-adopters. Larger families participated less in the market and were more food insecure. Wealth and education are other key determinants of food security and market participation. The results of the study indicate a need for a strategic policy on food security in Kenya that considers the concentrated nature of the maize farming sector, to address the problem of food insecurity. Such a policy could aim at food self-sufficiency for small farms and promote commercial production by large-scale producers for national strategic reserves. There is also a need for post-harvest policies that promote safe on-farm grain storage for small and medium scale producers. The third chapter focuses on migration, because of the growing interest among scholars in understanding the relationship between migration and adaptation to climate change. Past studies have looked at climate change as a trigger for migration, but the focus has now shifted to looking at migration as an enabler of climate-change adaptation and a livelihood diversification strategy. However, those most vulnerable to climate variability are the poor who are less able to afford mobility and entry costs. This study adds to the literature by evaluating, in chapter 3, the impact of migration on household consumption expenditure, relative food expenditure share, dietary diversity, spending on agricultural inputs and adaptive capacity. The study used survey data collected from a representative sample of 653 households across three arid regions of Northern Namibia. The study employed a novel identification strategy in migration studies by combining the standard exogenous instruments and Lewbel's constructed instruments using heteroscedastic errors. The study found two-thirds of the sampled households to be migrant-sending households. Poverty and the lack of economic opportunities in the rural villages were the main push factors driving migration to towns and cities. Although tertiary education and technical training of the migrants are key determinants of remittances received by migrant-sending households, over three quarters of the migrants were unskilled and very few having tertiary level training. Migrant-sending households had lower consumption spending and higher food budget share, suggesting relative deprivation. Although consumption spending increased with number of migrants, quality of human capital had greater impact on well-being. Migration had a positive impact on household's adaptive capacity but an inverse relationship between number of migrants and adaptation suggests failure of local adaptive strategies. The study finds households with migrants to have a significantly higher spending on agricultural inputs than those without migrants, with tractor-hire services for land preparation being a major component. The effect of family labour loss is somehow, through remittances, countervailed and compensated by mechanization. In conclusion, migration can potentially play a bigger role as an adaptive and risk-mitigation strategy in the face of climate variability, but poverty, lack of post-school skills training, and low transition to tertiary-level training are key barriers. Developing markets for credit, inputs and farm output, and preparing migrants for participation in labour markets and self-employment through training can further enhance the impact of migration and build resilience to climate shocks. Due to selfreinforcing poverty traps in poor households, the study recommends targeted public programs that support higher education and technical training. Lastly, chapter 4 examined the role of climate information and early warning in decision-making among farming communities in rural Namibia. Improved climate forecasting has been heralded as an important risk management and mitigation tool in climate-sensitive economic sectors such as agriculture. However, Africa has not reaped the benefits of improved climate forecasting and empirical studies about its impact are scanty. Chapter 4 first discusses access to and utilization of climate information in farm decisionmaking, and then evaluates its impact on dietary diversity, food spending and adaptive capacity of the households using propensity score matching, with a sensitivity analysis for hidden bias. Only half of the farmers had access to climate information and most of them relied primarily on traditional knowledge to make decisions on crop and livestock production. Many of the households without access to climate information also had little knowledge of alternative adaptive strategies. The likelihood of receiving climate information increased with the number of migrants per household, household size, social networks, trust and participation in community decision-making processes, but declined with age. Although male heads were more likely to receive climate information, females headed most of the households. The main sources of information for farmers were radios and peer learning. Respondents expressed a low level of trust in information from available channels and most of them rated the information received as insufficient for decision-making. Although 95% of households owned mobile phones, only 5% received information through them, indicating untapped opportunity of using an ICT platform to share information with farmers. Households with climate information had more diversified diets and significantly higher food spending. These households also engaged in more adaptive strategies, but the scale of adoption was small. Community empowerment through enhanced access to extension services, information on alternative adaptive choices, and the development of markets, rural communication and transport infrastructure are prerequisites to access to and effective utilization of improved climate forecast information for successful adaptation.