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The purpose of this paper is to examine the effect of structural economic vulnerability of developing countries on their public indebtedness.

The authors perform the analysis by the use of fixed effects technique where the standard errors are corrected by the Driscoll-Kraay (1998) method. The panel covers 96 developing countries over the period 1980-2008.

The results suggest evidence of a “U-shaped” relationship between the structural vulnerability and the total public debt in developing countries. More particularly in low-income countries (LICs), the structural vulnerability appears to be a strong determinant of the build-up of the total public debt.

It would be interesting to extend the research to small Island developing states. Indeed, the authors do not include this group of countries because of lack of data, especially on the variable “quality of governance” for almost all countries of this group. Accordingly, the research should be extended to such countries as well as these data are available.

The implications of the study is that international institutions, including those of the Bretton Woods should take into account the structural vulnerability of developing countries when designing development policies, especially the ones related to debt sustainability in developing countries and particularly LICs.

The fact of the international institutions to take into account the structural vulnerability in the design of international development policy, especially those related to debt issues will have major implications on the macroeconomic policy design by these developing countries as well as on poverty reduction.

The added value of this paper is to use recent data on structural vulnerability to analyse the effect of the latter on public indebtdeness of developing countries.

This paper aims to illustrate how the climate change‐vulnerability‐risk model (CCVRM) can be used to analyze the changes in system vulnerabilities and risks, as a result of implementing a community‐based early warning system (EWS).

The CCVRM is used to examine the community‐based EWS being implemented in the municipalities of Infanta and General Nakar in Quezon Province, Philippines. The levels of vulnerabilities and risks of the two localities are assessed through qualitative analysis using the CCVRM as framework. The model is also used to analyze the effects of the EWS in addressing the localities' vulnerabilities and risks.

Technological and institutional vulnerabilities of the Infanta and General Nakar systems have lessened when the EWS project was implemented. Technological and institutional vulnerabilities have direct correlations with mortality risk; thus, when the levels of the former decrease, so does the latter. Although the reduced technological and institutional vulnerabilities have an effect on the other type of risks present in the municipalities, the effects were not as significant as that of with mortality risk.

Due to limited time and resources, only one adaptation program is analyzed, specifically, the community‐based EWS being implemented in the municipalities of Infanta and General Nakar, Philippines. An integrated analysis of different measures is not done. Although investigating a multi‐adaptation program is possible, this would require more time and resources to implement. Likewise, only a simple evaluation based on model definitions is conducted, instead of a more extensive risk and vulnerability assessment.

The CCVRM acts as an analytical guide in understanding the effects of climate change adaptive measures. Accordingly, this paper investigates the effects of an implemented adaptive measure. The study also shows how the CCVRM can be used to analyze planned measures and identify the types of risks and vulnerabilities that this type of adaptive measure can influence.

A core challenge of assessing regional agricultural drought vulnerability (RADV) is to reveal what vulnerability factors, under which kinds of synergistic combinations and at what strengths, will lead to higher vulnerability: namely, the influence patterns of RADV.

A two-phased grey rough combined model is proposed to identify influence patterns of RADV from a new perspective of learning and mining historical cases. The grey entropy weight clustering with double base points is proposed to assess degrees of RADV. The simplest decision rules that reflect the complex synergistic relationships between RADV and its influencing factors are extracted using the rough set approach.

The results exemplified by China's Henan Province in the years 2008–2016 show higher degrees of RADV in the north and west regions of the province, in comparison with the south and east. In the patterns with higher RADV, the higher proportion of agricultural population appears in all decision rules as a core feature. A smaller quantity of water resources per unit of cultivated land area and a lower adaptive capacity, involving levels of irrigation technology and economic development, present a significant synergistic influence relationship that distinguishes the features of higher vulnerability from those of the lower.

The proposed grey rough combined model not only evaluates temporal dynamics and spatial differences of RADV but also extracts the decision rules between RADV and its influencing factors. The identified influence patterns inspire managerial implications for preventing and reducing agricultural drought through its historical evolution and formation mechanism.

The notion of worker vulnerability is often seen as synonymous with disadvantage in discussions of nonstandard work. The purpose of this paper is to separate and examine these two notions by considering economic, social and psychological perspectives and exploring the reality as experienced by agency workers.

In total, 178 Australian clerical agency workers employed by eight agencies completed a mail questionnaire. Personalised responses were subjected to computer-assisted template analysis.

Sample characteristics revealed a gendered and heterogeneous workforce. Findings showed evidence of economic, psychological and social vulnerabilities although favourable features were also reported. This apparent contradiction suggests linkages between the features of nonstandard work, worker preferences, individual characteristics and the experience of worker vulnerability.

The notion of varying degrees of worker vulnerability offers a new lens to investigate agency work. The relatively small sample size, focus on clerical work and features of the Australian context may limit generalisability.

Findings demonstrate the nature and extent of agency worker vulnerability which allows us to offer policy interventions for governments, agencies and user organisations and insights for prospective agency workers.

The widespread use of agency workers provides an imperative for frameworks to assess the nuances of the agency work experience. This study presents the reality of agency work as experienced by the workers and reveals the good and bad aspects of agency work.

The purpose of this paper is to examine the impact of multilateral trade policy (MTP) liberalization on developing countries’ economic exposure to shocks.

The analysis is conducted on a panel data set comprising 120 countries over the period 1996–2013 and uses the within fixed effects estimator.

The empirical results suggest that over the entire sample as well as sub-samples of least developed countries (LDCs) and non-LDCs, multilateral trade liberalization have a negative and significant impact on economic exposure to shocks. Interestingly, LDCs appear to experience the highest magnitude of the reducing impact of multilateral trade liberalization on countries’ economic exposure to shocks.

These findings suggest that a greater cooperation among countries in the world, including among WTO members to further liberalize trade would surely contribute to reducing developing countries’ economic exposure to shocks.

The current study shows that the current backlash against trade and the consequent strong appeal for domestic trade protectionist measures would likely to undermine the likelihood of further multilateral trade liberalization. One implication of this could be a rise in countries’ economic exposure to shocks.

To the best of the author’s knowledge, this is first the study on this matter.

The purpose of this article is to understand how coronavirus impacts relate to existing vulnerabilities in different world regions.

The article utilizes quantitative analysis to examine regional variations in coronavirus risk assessment. It then qualitatively employs a policy coherence for development (PCD) approach to analyze how public policies contribute to or mitigate vulnerability, defined as the product of exposure to external shocks, institutional coping capabilities and risk associated with social divisions in societies.

The research presented below shows that significant regional variance exists in terms of coronavirus risk, based on statistical analysis of the INFORM COVID-19 Risk Report prepared by the European Commission. The PCD analysis highlights important relationships between public policy strategies and the construction of both underlying vulnerabilities and coronavirus impacts.

The PCD approach presented here focuses on the reconciliation of trade-offs. It shows how policy interactions affect vulnerabilities and suggests that coherent policy strategies aimed at reducing vulnerabilities are necessary in order to adequately respond to the coronavirus pandemic.

This analysis frames vulnerability as a socially constructed condition and through implementation of a PCD approach, it indicates how policy strategies contribute to or mitigate vulnerabilities. In doing so, it intends to contribute conceptually to the literature on vulnerability by showing how policy incoherences contribute to the construction of this condition. Empirically, the originality of this article is its statistical analysis of regional variance of coronavirus risk and the qualitative analysis of policy strategies in representative cases and how they have affected vulnerabilities and coronavirus impacts.

The purpose of the research is to develop a conceptual framework to anticipate the vulnerability of value of commercial properties towards changing risk of flooding. The existing patterns, themes, and issues associated with property value and their vulnerability towards flooding were identified and used to inform the development of the conceptual model.

Literature review is performed to identify the factors affecting vulnerability of commercial property values to the impact of flood risk in the UK. The review approach was based on related literature contributing to identified themes and sub-themes. The extant literature is summarized into two distinct themes of “vulnerability” and “value” contributing to changing risk of flooding. The synthesised literature is then utilized in developing the conceptual map which further paved the way towards designing the conceptual framework.

The generic conceptual framework presented explores the interaction between different internal and external influencing factors affecting the vulnerability of value of commercial property system. The framework highlighted the importance of space and time within the system. An extensive review of previous studies in both the residential and commercial sectors for different disaster studies reveals that the main research challenge in assessing the vulnerability of property values are the intensive data requirements. The need for data is considered to be the main restrictive factor resulting in lack of empirical studies in this field.

This study brings together two existing research domains of flood vulnerability and property value. Practitioners and researchers will find this study useful in developing an improved understanding of the vulnerability of commercial properties to flooding. The conceptual framework is an important outcome of the research which will encourage further research in this considerably neglected field.

The COVID-19 pandemic has exposed the financial-economic vulnerability of the public and threatened the household financial stability, especially of the low-income group population, in developing economies such as India. The assessment of household financial vulnerability has gained considerable attention these days, especially in poor and developing countries. This article seeks to assess the level of household financial vulnerability in India, based on a household survey conducted across India.

This paper has proposed a financial vulnerability index (FVI) based on three self-reported parameters: (1) making end meet, (2) perception of income shock and (3) perception of expenditure shock. Subsequently, the impact of various behavioural and socioeconomic factors on the proposed financial vulnerability index has been assessed using fractional probit regression.

The research findings indicate that higher financial knowledge, better money management skills and lower impulsivity in financial behaviour can reduce financial vulnerability. It is suggested that suitable financial literacy programmes be implemented for vulnerable sections of society to enhance their financial knowledge, improve money management skills and manage impulsivity, thereby helping them make informed financial decisions leading to their financial well-being.

To the best of the authors’ knowledge, none of the past studies have developed and assessed the financial vulnerability index in India. This study provides relevant recommendations for various financial sector regulators and government institutions in India.

The purpose of this study is to propose an unbiased generalized grey relational closeness evaluation model to improve the accuracy of regional agricultural drought vulnerability decision-making results, as well as to provide theoretical support for reducing agricultural drought risk and losses.

The index weight is calculated using a rough set and deviation minimization criterion, and the relational degree between the research object and the double reference sequence is thoroughly investigated using the generalized grey relational closeness degree. Because different index rankings can correspond to different closeness degrees, the Monte Carlo method was used to calculate an unbiased estimate of the generalized grey relational closeness degree, which was used as a decision basis.

Agricultural drought vulnerability in Henan Province in 2019 was clearly spatially differentiated. The vulnerability to agricultural drought in the southern and eastern regions was generally higher than that in other regions. The evaluation results of this model are highly stable and reliable compared to those of the traditional generalized grey relational evaluation model.

This study proposes an evaluation model based on an unbiased generalized grey relational closeness degree, which is important to supplement the grey relational analysis method system and plays a positive role in promoting the quantitative evaluation of regional agricultural drought vulnerability.

The Monte Carlo method is used to calculate the unbiased estimation of the generalized grey relational closeness degree, which solves the problem of the replacement dependence of the traditional generalized grey relational degree and the one-sidedness of the evaluation results, and provides a new research idea for the evaluation of regional agricultural drought vulnerability under cross-sectional informatics.

The objective of this study was to assess the relationship among intersectionality, vulnerability and resilience with evidence. The conceptual framework developed by the study believed that intersectionality and vulnerabilities intersect and reduce the level of disaster resilience.

A qualitative approach was followed with relevant support from both primary and secondary data to conduct the study. The study focused on flood as a specific natural hazard to assess the relationship among the indicators of the objective. Focus group discussions (FGDs) were performed in two different flood-prone areas of Bangladesh. FGDs included young men, young women, men and women with disabilities and older people. Also, secondary literature helped to support ground-level data.

In the face of a flood, results showed that people with intersectional characteristics become more vulnerable within the at-risk groups. There are differences in people's level of vulnerabilities among the people of vulnerable groups. The results support the discussion that intersectionality exaggerates vulnerabilities, thus reducing the level of disaster resilience. The study summarizes that intersectionality needs to be addressed while supporting groups at risk to achieve a resilient community.

The study is only based on qualitative and secondary data. For more generalized findings and implications, further research is needed. Also, this study will work as a guideline for future studies.

The study is one of the few works related to intersectionality. This study will open a new window to understand the importance of focusing on intersectional conditions while developing plans for disaster risk reduction (DRR).