Niger is a landlocked country where rainfall is characterised by high inter-annual and spacetime variability. It faces many natural and human constraints that explain the erratic evolution of its agricultural production. In addition, since signing the African Union Maputo Declaration of 2003 of keeping expenditure on agriculture to at least 10% of the national budget, Niger has surpassed this share, however, the problem of food security still lingers. Hence our research topic: Households’ Resilience to Food Insecurity and Adaptation Strategies to Climate Change in Niger.
Therefore, this study focuses on two major themes: resilience to food insecurity and adaptation strategies to climate change. To address these themes, the following approaches are used: principal component analysis, structural equation modelling, ordered probit model and multivariate probit model. Principal component analysis (PCA) is run on five household level variables (income, food expenditure, duration of grain held in stock, livestock units owned by the household calculated as Tropical Livestock Units and number of farms exploited) to create the resilience index. Data from the 2010 National Survey on Households’ Vulnerability to Food Insecurity done by the Niger National Institute of Statistics on 9354 rural households is used. The results show that households from Diffa, Dosso, and Tillabery regions are the most resilient to food insecurity, compared to those from Maradi, Tahoua, Zinder, and Niamey. The index shows also that female-headed households are less resilient to food insecurity than maleheaded ones.
To analyse factors affecting households’ resilience to food insecurity, structural equation modelling is used and the results show that Asset and Social Safety Nets indicators have a positive and significant impact on households’ resilience to food insecurity, while the climate change indicator approximated by long-term average rainfall has a negative and significant effect.
To identify factors affecting rural households’ food security status, an ordered probit model is used and the dependent variable is a proxy indicator of food security, namely the Food Consumption Score. The results show that the likelihood of change in the food security status of a household is determined by the sex of the head of the household, livestock ownership, long-term climate (rainfall and temperature), duration of grain held in stock, household income and migration of household member.
This study also identifies factors affecting farm households’ adaptation strategies to climate change using the 2011 Niger National Survey on Living Conditions and Agriculture executed by the National Institute of Statistics. The results of the multivariate probit technique show that there is a strong complementarity between practices, and the cross-technology correlation may have important policy implications in that a policy change that can affect one agricultural practice can have spillover effects on other practices. The results also show that higher long-term mean rainfall and higher maximum temperatures increase adoption.
Moreover, the study shows the importance of climate variables, biophysical, institutional, infrastructural and socio-demographic characteristics in the choice of adaptation strategies. The importance of system-level variables on adoption suggests the need for strengthening local institutions to sustain agricultural practices. Notably, these results indicate that to strengthen households’ resilience to food insecurity, there is a need to help them to gather more resources in order to acquire more assets. They also need assistance through social safety nets, especially for women. In addition, it is suggested that the Government should establish efficient early warning signals that could alert households so as to prepare for the uneven events.