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This paper illustrates that natural disasters can significantly threaten financial institutions serving the poor. The authors test the case of a microfinance institution (MFI) in Northern Peru, where severe El Niño events create catastrophic flooding.

Portfolio‐level, monthly data from January 1994 to October 2008 were examined using an intervention analysis. The paper tested whether the 1997‐1998 El Niño increased problem loans and estimated the magnitude of the effect.

The results indicate El Niño significantly increased problem loans, specifically the level of restructured loans. While restructured loans averaged 0.5 percent of the total loan portfolio before the El Niño, the estimated cumulative effect of El Niño indicates that an additional 3.6 percent of the portfolio value was restructured due to this event.

Future research could build on these results by modeling insurance‐type mechanisms for the MFI. Additional research that replicates these analyses in another context would be highly valuable for comparison across natural disasters and financial institutions.

The findings demonstrate that the correlated risk exposure of many small borrowers can significantly affect the lender and the importance of considering bank management in assessing disaster risk of a financial institution.

Lender strategies to minimize losses may require long‐term restructuring that perpetuates the effects of the disaster in the community.

This paper may be of particular value to researchers and practitioners hoping to improve the effectiveness and efficiency of MFIs concentrated in regions exposed to natural disaster risk.

The purpose of this paper is to demonstrate how the contingency approach to disaster preparedness inhibits proactive management of slow-onset disasters, such as El Niño, with the purpose of advancing disaster risk theory.

This study draws on fieldwork data from Nariño, Colombia, combined with secondary data and a review of the literature on El Niño and disaster preparedness.

Disaster managers in Nariño do have contingency plans for El Niño events at their disposal. Yet, these plans do not come into play before impacts reach a certain severity. This “contingency approach” to disaster preparedness appears to stem from the assumption that disaster must come before response, effectively inhibiting proactive responses to El Niño impacts.

Attributing observed cases of droughts and oral accounts of impacts to the El Niño phenomenon is methodologically challenging. To overcome this, the aim of this study is not the documentation of subjective attributions. Instead, the focus is on bringing to the fore key dilemmas that preparedness professionals may face when they prepare for disasters with a slow onset.

Developing prevention and preparedness conceptualisations that focus on preemptive measures should ensure a more proactive response to slow-onset disasters.

Whether slow-onset disasters lend themselves to the same types of risk reduction strategies applied to rapid-onset disasters is a theoretical and practical issue that has not been explored sufficiently in the disaster risk literature.

Is a holistic approach to the disaster problem required? Seeks to answer this question by examining the 1997‐1998 El Niño disasters in Peru. Explores the key factors that contributed to the disaster and highlights the subsequent effects and response operations. Discusses the need for a theory of disaster management that takes into account all types of hazards, numerous variables from the physical and social environments, as well as each phase of emergency management.

In the equatorial Pacific, rainfall is affected by global climate phenomena, such as El Niño Southern Oscillation (ENSO). However, current publicly available methodologies for valuing weather derivatives do not account for the influence of ENSO. The purpose of this paper is to develop a complete framework suitable for valuing rainfall derivatives in the equatorial Pacific.

In this paper, we implement a Markov chain for the occurrence of rain and a gamma model for the conditional quantities using vector generalized linear models (VGLM). The ENSO forecast probabilities reported by the International Research Institute for Climate and Society (IRI) are included as independent variables using different alternatives. We then employ the Esscher transform to price rainfall derivatives.

The methodology is applied and calibrated using the historical rainfall data collected at the El Dorado airport weather station in Bogotá. All the estimated coefficients turn out to be significant. The results prove more accurate than those of Markovian gamma models based on purely statistical descriptions of the daily rainfall probabilities.

This procedure introduces the novelty of incorporating variables related to the climatic phenomena, which are the forecast probabilities regularly published for the occurrence of El Niño and La Niña.

This study aims to systematically reveal the complex interaction between uncertainty and the international commodity market (CRB).

A composite uncertainty index and five categorical uncertainty indices, together with wavelet analysis and detrended cross-correlation analysis, were used. First, in the time-frequency domain, the coherency and lead-lag relationship between uncertainty and the commodity markets were investigated. Furthermore, the transmission direction of the cross-correlation over different lag periods and asymmetry in this cross-correlation under different trends were identified.

First, there is significant coherency between uncertainties and CRB mainly in the short and medium terms, with natural disaster and public health uncertainties tending to lead CRB. Second, uncertainty impacts CRB more markedly over shorter lag periods, whereas the impact of CRB on uncertainty gradually increases with longer lag periods. Third, the cross-correlation is asymmetric and multifractal under different trends. Finally, from the perspective of lag periods and trends, the interaction of uncertainty with the Chinese commodity market is significantly different from its interaction with CRB.

First, this study comprehensively constructs a composite uncertainty index based on five types of uncertainty. Second, this study provides a scientific perspective on examining the core and diverse interactions between uncertainty and CRB, as achieved by investigating the interactions of CRB with five categorical and composite uncertainties. Third, this study provides a new research framework to enable multiscale analysis of the complex interaction between uncertainty and the commodity markets.

The purpose of this paper is to define and discuss the concept of zero-order responders (ZOR). It explores the potential lessons and the additive value that assimilation of responses of disaster-affected people into disaster risk reduction (DRR) and disaster risk management (DRM) programs can provide.

In order to support this concept, the authors review two recent extreme hydrometeorological events, illustrating how local populations cope with disasters during the period before external support arrives. Additionally, the authors address their under-leveraged role in the management of recovery. The empirical evidence was collected by direct observations during the 2017 El Niño Costero-related floods in Peru, and by the review of press following 2017 hurricanes Irma and Maria destruction in Puerto Rico.

During disasters, there is a window of time before official and/or external support arrives. During this period, citizens must act unsupported by first responders – devising self-coping strategies in order to survive. In the days, weeks and months following a disaster, local populations are still facing recovery with creativity.

Citing references arguing for or against the value of documenting survivor methods to serve as a testimony for the improvement of DRR programming.

DRR and DRM must integrate local populations and knowledge into DRR planning to improve partnerships between communities and organizations.

The actions and experiences of citizens pro-acting to pave fruitful futures is a valuable commentary on improvements for DRR and management.

This paper proposes a citizen-centered contribution to future disaster risk reducing actions. This approach emphasizes the reinterpretation of local responses to disasters. DRRs and DRMs growth as fields would value from heralding ZOR coping and improvisation skills, illustrated under stressful disaster-related conditions, as an additive resource to programming development.