Conference Agenda

Agricultural transformation in sub-Saharan Africa is often pursued via on-farm innovations such as climate-smart agriculture (CSA), yet many households also diversify into off-farm self-employment. Evidence on the relative welfare gains from these pathways at the farm level is scarce. We use farm-level data from southeastern Madagascar and inverse-propensity weighting (IPTW) to estimate the mean difference of CSA adoption and off-farm self-employment on total household income and months of adequate household food provisioning (MAHFP). On average, CSA adoption is associated with higher income than traditional farming methods or off-farm self-employment. However, the CSA-associated income gains decline with farm size and become statistically insignificant at 1.37 hectares; beyond this threshold, marginal returns to CSA are negative relative to traditional farming practices. Off-farm self-employment shows a positive average effect but is not statistically significant at the current scale of investment. While CSA adoption alone does not translate into better food security outcomes, its combination with off-farm self-employment does. These results imply that CSA delivers income gains primarily for small farms, while larger farms face diminishing returns, and that off-farm activities may require greater scale or complementary investments to translate into household income growth. Agricultural adaptation policy leans towards the prioritisation of very small farms, placing larger ones in a structural “missing middle”. Policies should facilitate transitions to higher-return off-farm opportunities and integrate farm-size considerations into agricultural adaptation and rural transformation strategies.

The restoration of ecosystem services is essential for addressing growing food insecurity in the Sahel. Innovative nature-based solutions (NbS) are urgently needed, as climate change, agricultural expansion, and regional instability are putting pressure on rangelands that sustain over 50 million livestock herders. Our study focuses on the Hadejia Valley in Northern Nigeria, where the invasive plant species Typha spp. has become a serious environmental and socio-economic threat, degrading wetlands and irrigation systems vital for local livelihoods. We evaluate the adoption of a novel NbS that converts Typha into silage—livestock feed—offering a dual benefit: controlling the spread of the invasive species while enhancing climate resilience and food security. Using survey data from 260 herders in the Hadejia Valley, we apply Heckman’s two-stage model to examine both the decision to adopt this solution and the willingness to pay (WTP) for silage derived from Typha. Our results show that although women are less likely to adopt the practice, they exhibit a higher WTP for the silage. Membership in herder organizations and shared infrastructure significantly increase WTP. Transhumant herders are more inclined to adopt the technology, reflecting its relevance to mobile pastoral systems. Furthermore, participation in workshops and demonstration sessions positively influences adoption decisions. These findings offer critical insights for designing and scaling locally adapted NbS in the region. By linking ecosystem restoration with livelihood resilience, the study highlights a promising pathway for sustainable development in drought-prone pastoral areas.

Climate change is making it increasingly difficult for farmers, particularly those in lower-income countries reliant on rainfed agriculture, to avoid crop losses, with implications for food security and livelihoods more broadly. In this paper we provide robust evidence from Ethiopia, Tanzania, Uganda, and Bangladesh, that farmers with access to more accurate weather forecasts are less likely to report crop losses. Our analysis further highlights one plausible mechanism by which farmers are able to act on weather forecasts, by changing their labour hiring decisions during the harvest season in response to forecasts of extreme weather. Our findings suggest that investment in improved weather forecasting can improve agricultural productivity, which has the potential to reduce food insecurity.

Smallholder farmers increasingly adopt Climate-Smart Agriculture (CSA) practices to mitigate climate risks and improve livelihoods. However, the comparative effectiveness of adopting these practices in isolation versus integrated "packages" remains a subject of empirical debate. This study utilizes primary survey data from 120 households to evaluate the determinants and food security impacts of various CSA adoption packages. Principal Component Analysis (PCA) is used to cluster CSA practices into four bundle: Crop Management (C1), Farm Risk Management (C2), Soil Conservation (C3), and General Field Management (C4). We employ a robust multi-model econometric approach, comprising Propensity Score Matching (PSM), Endogenous Switching Regression (ESR), and Inverse Probability Weighted Regression Adjustment (IPWRA), to account for both observable and unobservable selection bias. The descriptive analysis reveals a mean Household Food Consumption Score (HFCS) of 83.22, with 95% of households classified as food secure. Principal Component Analysis (PCA) identifies improved varieties, organic manure, and diversification as high-adoption pillars. Multinomial Logit results indicate that adoption decisions are significantly driven by household size, education, access to off-farm income, and extension services. Impact estimations reveal a clear "synergy effect": the Full package (C1C2C3C4) is the only strategy that yields robustly positive and significant gains in food security across all models, with a PSM-estimated increase in HFCS of approximately 28.8% (t=2.77). Conversely, partial packages, particularly those lacking risk-reduction components (e.g., C1C3C4) showed consistent negative impacts on food security, suggesting that incomplete adoption may expose farmers to higher vulnerability. Consequently, policy interventions should pivot from promoting isolated technologies toward integrated, comprehensive CSA packages supported by strengthened institutional credit and extension frameworks.

This study examines different approaches to measuring ambiguity aversion among maize farmers in northern Ghana in relation to the adoption of climate-smart agriculture (CSA). Using incentivized field experiments based on Baillon et al. (2018) and surveys, we elicit farmers’ preferences regarding yield outcomes from two drought-tolerant maize varieties: Sanzal-sima and Bihilifa. The experimental data from the farmers show moderate ambiguity aversion under the Baillon et al. framework, while the traditional Ellsberg measure indicates ambiguity-neutral or ambiguity-seeking behaviour. The findings show significant variability in ambiguity aversion: Muslim farmers as well as larger farm households tend to show lower ambiguity aversion, while married, older farmers and farmers that own their own land tend to be more averse. The Baillon et al. method captures these behavioural differences more precisely and in a contextually relevant way, displaying greater dispersion and contextual sensitivity. Findings highlight the value of framing experiments around natural agricultural uncertainties and suggest refinements such as probability training and sequencing experiments before surveys to enhance CSA adoption, climate resilience, research and policy.

Farmers throughout the US confront and manage numerous sources of risk. For irrigators in the arid West, this includes water shortages amid increasing demand to manage droughts. Along with physical scarcity, groundwater irrigators face additional regulations aiming to limit their collective withdrawals. Here we conduct a contingent choice experiment with groundwater irrigators in two such regions – San Luis Valley, Colorado and Northwest Kansas – to better understand how irrigators view tradeoffs in water risk and profits. Furthermore, we randomize the stated source of the risk to be either from drier weather cycles or from more stringent water conservation policies. We find that irrigators are risk averse on average, willing to forego 1.25% in profit per acre to reduce their risk of crop failure by one percentage point. More notably, they exhibit a bias in that they are far more sensitive, three times as much, to risk induced by policy than by weather. Additionally, irrigators tend to favor investing in irrigation technology to improve efficiency over switching to a less-water intensive crop indicating the presence of important non-pecuniary costs to adaptations.

I provide the first comprehensive analysis of green employment across 18 developing

countries, using harmonized labor force survey data covering approximately 23 mil-

lion workers from 2010 to 2023. Green task intensity averages just 0.45 percent of

employment, with high concentration in utilities and public administration and dispro-

portionate representation in urban, formal sector jobs. Linking individual labor market

outcomes to ERA5-Land climate data, I find that heat exposure significantly reduces

earnings: each additional day above 90°F lowers log wages by 1.4 percent. However,

green workers are buffered from these effects—the green-heat interaction is positive

and highly significant (+0.5% per hot day, p < 0.001). This climate-resilience property

of green employment suggests that green transition policies may have co-benefits for

climate adaptation in developing economies facing rising temperatures.