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The paper aims to assess the impact of weather-induced shocks on household food consumption in the rural Vietnamese Mekong Delta (VMD) through the case of Long An province and evaluate the effectiveness of widely used coping strategies in mitigating weather-related shock impacts.

The system generalized method of moments (GMM) estimation method is applied to explore information on shock incidence, recovery, and time occurrences. The paper uses a sample of 272 repeated farming households from 5-wave survey data from 2008 to 2016, resulting in 1,360 observations.

The paper confirms the robust negative effect of a natural shock on food consumption. Additionally, using savings proves to be the most potent measure to smooth food consumption. Other favorable coping strategies are “getting assistance from relatives, friends” or “getting assistance from the Government, and non-government organizations (NGOs).” The mitigating effects are also traced in the current analysis.

Using caution when generalizing the results from Long An to the whole VMD is reasonable. The rather limited observations of coping strategies do not allow the authors to analyze any specific strategy.

The proposed approach employs the GMM technique and controls for endogenous coping strategies and thus provides accurate estimates of the effects of weather-related shocks and the mitigation effectiveness in the rural VMD.

Using cotton yield, and rainfall data from Tajikistan, the purpose of this paper is to investigate the magnitude of weather induced revenue losses in cotton production. Hereby the authors look at different risk aggregation levels across political regions (meso-level). The authors then design weather index insurance products able to compensate revenue losses identified and analyze their risk reduction potential.

The authors design different weather insurance products based on put-options on a cumulated precipitation index. The insurance products are modeled for different inter-regional and intra-regional risk aggregation and risk coverage scenarios. In this attempt the authors deal with the common problem of developing countries in which yield data is often only available on an aggregate level, and weather data is only accessible for a low number of weather stations.

The authors find that it is feasible to design index-based weather insurance products on the meso-level with a considerable risk reduction potential against weather-induced revenue losses in cotton production. Furthermore, the authors find that risk reduction potential increases on the national level the more subregions are considered for the insurance product design. Moreover, risk reduction potential increases if the index insurance product applied is designed to compensate extreme weather events.

The findings suggest that index-based weather insurance products bear a large risk mitigation potential on an aggregate level. Hence, meso-level insurance should be recognized by institutions with a regional exposure to cost-related weather risks as part of their risk-management strategy.

The authors are the first to investigate the potential of weather index insurance for different risk aggregation levels in developing countries.

Purpose – This chapter investigates vulnerability to poverty in the Republic of Haiti.

Methodology – We use a hierarchical modeling technique to allow the assessment and decomposition of vulnerability to poverty by exploiting the short-panel structure of nested data in a cross section.

Originality – Specifically, a three-level hierarchical model with a partially Bayesian restricted maximum likelihood is used in the estimation procedure. This is novel in this literature.

Findings – The decomposition method adopted in this chapter reveals that vulnerability in the Republic of Haiti is largely a rural phenomenon and is correlated negatively with schooling. The results also disclose the lack of equality in various aspects of circumstances or opportunities, including education, as the salient factor determining the status and level of vulnerability of households. Most importantly, among the different shocks affecting household's income, it is found that meso-level shocks are in general far more important than covariate shocks. This finding points to some interesting policy implications in terms of decentralizing policies and delegating more powers and providing better means to local governments to enhance household resilience to shocks and to alleviate their vulnerability to poverty.

Urban resilience is a fairly new but rapidly emerging area of interest. Academia as well as the professional and practitioner communities are increasingly engaged in understanding the characteristics of resilience in complex urban issues. The year 2007–2008 was a historical milestone in human history for two reasons. First, the percentage of urban population to total population in the world touched 50 percent; second, the works of climate scientists were recognized as being so significant that the Intergovernmental Panel on Climate Change (IPCC) received the Nobel Prize for Peace in 2007. Both events are closely associated with and provide special impetus to further research into and understanding of urban resilience, which this chapter discusses further in the following sections.

The purpose of this paper is to study how variations in weather affect demand and supply chain performance in sport goods. The study includes several brands differing in supply chain structure, product variety and seasonality.

Longitudinal data on supply chain transactions and customer weather conditions are analysed. The underlying hypothesis is that changes in weather affect demand, which in turn impacts supply chain performance.

In general, an increase in temperature in winter and spring decreases order volumes in resorts, while for larger customers in urban locations order volumes increase. Further, an increase in volumes of non-seasonal products reduces delays in deliveries, but for seasonal products the effect is opposite. In all, weather affects demand, lower volumes do not generally improve supply chain performance, but larger volumes can make it worse. The analysis shows that the dependence structure between demand and delay is time varying and is affected by weather conditions.

The study concerns one country and leisure goods, which can limit its generalizability.

Well-managed supply chains should prepare for demand fluctuations caused by weather changes. Weekly weather forecasts could be used when planning operations for product families to improve supply chain performance.

The study focuses on supply chain vulnerability in normal weather conditions while most of the existing research studies major events or catastrophes. The results open new opportunities for supply chain managers to reduce weather dependence and improve profitability.

This paper investigates whether weather affects stock market returns in Fiji's stock market.

The author employed an exponential general autoregressive conditional heteroskedastic (EGARCH) modeling framework to examine the effect of weather changes on stock market returns over the sample period 9/02/2000–31/12/2020.

The results show that weather (temperature, rain, humidity and sunshine duration) have robust but heterogenous effects on stock market returns in Fiji.

It is useful for scholars to modify asset pricing models to include weather-related variables (temperature, rain, humidity and sunshine duration) to better understand Fiji's stock market dynamics (even though they are often viewed as economically neutral variables).

Investors and traders should consider their mood while making stock market decisions to lessen mood-induced errors.

This is the first attempt to examine the effect of weather (temperature, rain, humidity and sunshine duration) on stock market returns in Fiji's stock market.

The purpose of this paper is to analyze smallholder farmers’ perceptions of climate change and its adverse effects, identify major adaptation strategies used by farmers and analyze the factors that influence the choice of adaptation strategy by smallholder farmers in eastern Ethiopia.

The study was based on a cross-sectional survey of 296 sample households selected from three districts in east Ethiopia. Data were collected with the aid of a semi-structured questionnaire and review of literature, documents and databases.

The study provides empirical evidence that majority of farmers in the study area are aware of climate change patterns and their adverse effect on income, food security, diversity, forest resources, food prices and crop and livestock diseases. In response to these adverse effects, major adaptation strategies used by farmers include cultivating different crops, planting different crop varieties, changing planting dates, use of soil and water conservation techniques, conservation agriculture practices and engaging in non-farm income activities. Choice of adaptation strategies are influenced by gender of household head, household size, farm size, distance from market and number of farm plots.

The study suggests that developing more effective climate change adaptation strategies need support from the government. Such an effort needs provision of the necessary resources such as credit, information and extension services on climate change adaptation strategies and technologies, and investing in climate smart and resilient projects.

The study adopts multivariate probit model that models farmers’ simultaneous adaptation choice behavior which has been rarely addressed by previous researches.

Cassava production surged noticeably in Southeastern Africa beginning in the 1990s. The purpose of this paper is to examine the commercial responses and food security consequences of cassava production growth in the region.

The paper incorporates a mix of quantitative analysis, based primarily on original analysis of national farm household survey data, together with key informant interviews with value chain participants in the three neighboring countries of Malawi, Mozambique and Zambia.

In the cassava production zones, cassava's high productivity translates into per kilogram carbohydrate costs 60 per cent to 70 per cent of the cost of cereals such as maize and wheat, thereby opening up a range of profitable opportunities for commercialization of cassava‐based foods, feeds and industrial products. Despite this potential, cassava commercialization in Southeastern Africa remains in its formative stages, with only 10 per cent to 30 per cent of production currently marketed. Unlike West Africa, where cassava commercialization has centered on marketing prepared cassava‐based convenience foods, the emerging cassava markets in Southeastern Africa have centered on fresh cassava, low value‐added cassava flour, and experiments in industrial processing of cassava‐based starches, biofuels and feeds. Strategic investment in a set of key public goods (breeding, training in food sciences and food safety, and research on in‐ground cassava storage) can help to shape this transition in ways that benefit both commercial interests and the food security of vulnerable households.

The paper compares cassava commercialization across differing agro‐climatic zones, policy environments and food staple zones.