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The purpose of this study is to identify the most vulnerable households and districts in Northwest Ethiopia and help decision-makers in developing and prioritising effective adaptive strategies and actions.

A multi-scale analytical tool and hazard-generic socio-economic indicators were developed to identify and prioritise the most vulnerable households and districts in Northwest Ethiopia. Categorical principal component analysis with 36 indicators was used to develop weights for different indicators and construct a household intrinsic vulnerability index. Data were collected through key information interviews, focus group discussions and a household survey with 1,602 randomly selected households in three districts of Northwest Ethiopia.

Drawing on intrinsic vulnerability index computation, this study highlights that low levels of education, low access to climate information and credit services, long distance travelled to fetch water and frequent food shortages are the dominant factors contributing to high levels of intrinsic vulnerability at district level, while lack of livelihood support and income diversification are the key drivers of vulnerability at household level. The findings of this study further show that the majority of households (78.01%) falls within the very high to moderately high vulnerable category. Disaggregating the data according to agro-climatic zones highlights that the prevalence of high intrinsic vulnerability is most widespread in the lowland agro-climatic zone (82.64%), followed by the highland (81.97%) and midland zones (69.40%).

From a policy intervention vantage point, addressing the drivers of vulnerability provides a reliable approach to reduce the current vulnerability level and manage potential climate change-induced risks of a system. Specifically, reliable information on inherent vulnerability will assist policymakers in developing policies and prioritising actions aimed at reducing vulnerability and assisting in the rational distribution of resources among households at a local level.

This study contributes to the existing vulnerability literature by showing how hazard-generic socio-economic indicators in the vulnerability assessment adopted by the IPCC (2014) are important to identify drives of vulnerability which ultimately may feed into a more fundamental treatment of vulnerability.

Shadow banks or non-bank financial intermediaries (NBFIs) are facilitators of credit, especially in emerging market economies (EMEs). However, there are certain risks associated with them, such as their unchecked leverage and interconnectedness with the rest of the financial system. In light of this, the present study analyses the impact of the growth of shadow banks on the stability of the banking sector and the overall stability of the financial system. The authors further examine the effect of the growth of finance companies (a type of NBFIs) on financial stability.

The study employs data of 11 EMEs (monitored by the Financial Stability Board (FSB)) for the period 2002–2020 to examine the above relationships. Panel-corrected standard errors method and Driscoll–Kray standard error estimation are deployed to conduct the analysis.

The results signify that the growth of the shadow banking sector and the growth of lending to the shadow banking sector are negatively associated with the stability of the banking sector and increases the vulnerability of the financial system (overall instability). This implies that the higher the growth of the shadow banks, the higher the financial fragility. Finance companies are also found to negatively affect financial stability. These findings are validated by different estimation methods and point out the risks posed by the NBFI sector.

The extant study builds a composite index (Financial Vulnerability Index (FVI)) to measure financial stability; thus, the findings contribute to the evolving literature on shadow banks.

The purpose of this study is to develop a methodology which amalgamates quantitative and qualitative approaches to determine the best placement of mobile logistics hubs (MLH) to be established in different parts of Nepal as a part of real-life project, “Augmentation of National and Local-Level Emergency Logistics Preparedness in Nepal” (2017–2020), implemented by the World Food Programme in cooperation with the Government of Nepal.

The study develops a methodology using a combination of a modified version of the maximal covering location problem (MCLP) and focus group discussion. The MCLP model is used to determine the optimal number and spatial location of MLHs, and focus group discussion is used to identify the five first-priority strategic MLH locations using expert knowledge.

The authors identify the five first-priority locations for establishing MLHs using an amalgamation of quantitative approach (mathematical model) and qualitative approach (focus group discussion). By amalgamating mathematical model with expert knowledge, findings acceptable to a wide range of stakeholders are obtained. The focus group discussion helps to pinpoint the location of MLHs to city-level granularity which is otherwise impossible with data available on hand.

Although multiple experts’ judgements were obtained via focus group discussion, subjectivity and possible bias is inevitable. Overall, the quantitative results of the study are purely based on the data available during the study period; therefore, having updated data could possibly improve the quality of the results.

This study is the first of its kind that uses an amalgamation of mathematical model and expert knowledge to determine the strategic locations of MLHs and has been successful to an extent that the selected locations have been vetted by the government of Nepal for establishing MLHs and are undergoing implementation in real life. This study also considers multiple disaster scenarios and employs the concepts of human development, disaster risk and transportation accessibility to reflect Nepal's socioeconomic, geo-climatic and topographical features.

Climate data, including historical climate observations and climate model outputs, are often used in climate impact assessments, to explore potential climate futures. However, characteristics often associated with “islandness”, such as smallness, land boundedness and isolation, may mean that climate impact assessment methods applied at broader scales cannot simply be downscaled to island settings. This paper aims to discuss information needs and the limitations of climate models and datasets in the context of small islands and explores how such challenges might be addressed.

Reviewing existing literature, this paper explores challenges of islandness in top-down, model-led climate impact assessment and bottom-up, vulnerability-led approaches. It examines how alternative forms of knowledge production can play a role in validating models and in guiding adaptation actions at the local level and highlights decision-making techniques that can support adaptation even when data is uncertain.

Small island topography is often too detailed for global or even regional climate models to resolve, but equally, local meteorological station data may be absent or uncertain, particularly in island peripheries. However, rather than viewing the issue as decision-making with big data at the regional/global scale versus with little or no data at the small island scale, a more productive discourse can emerge by conceptualising strategies of decision-making with unconventional types of data.

This paper provides a critical overview and synthesis of issues relating to climate models, data sets and impact assessment methods as they pertain to islands, which can benefit decision makers and other end-users of climate data in island communities.

This study aims to analyze the imbalances in the public finance structure of Pakistan’s economy and highlight the need for comprehensive reforms. Specifically, it aims to contribute to the empirical literature by analyzing the relationship between fiscal vulnerability, financial stress and macroeconomic policies in Pakistan’s economy between 1971 and 2020.

The study develops an index of fiscal vulnerability, an index of financial stress and an index of macroeconomic policies. The fiscal vulnerability index is based on the patterns of fiscal indicators resulting from past trends of the selected variables in Pakistan’s economy. The financial stress in Pakistan is caused from the financial disorders that are acknowledged in the composite index, which is based on variables with the potential to indicate periods of stress stemming from the foreign exchange market, the securities market and the monetary policy components. The macroeconomic policies index is developed to analyze the mechanism through which fiscal vulnerability and financial stress have influenced macroeconomic policies in Pakistan. The causal association between fiscal vulnerability, financial stress and macroeconomic policies is analyzed using the auto-regressive distributive lags approach.

There exists a long-run relationship between the three indices, and a bi-directional causality between fiscal vulnerability and macroeconomic policies.

This study contributes to the development of a fiscal monitoring mechanism, which has the basic purpose of analyzing the refinancing risk of public liabilities. Moreover, it focuses on fiscal vulnerability from a macroeconomic perspective. The study tries to develop a framework to assess fiscal vulnerability in light of “The Risk Octagon” theory, which focuses on three risk components: fiscal variables, macroeconomic-disruption-associated shocks and non-fiscal country-specific variables. The initial contribution of this work to the literature is to develop a framework (a fiscal vulnerability index, financial stress index and macroeconomic policies index) for effective and result-oriented macro-fiscal surveillance. Moreover, empirical literature emphasized and advised developing countries to develop their own capacity mechanisms to assess their fiscal vulnerability in light of the IMF guidelines regarding vulnerability assessments. This study thus attempts to fulfill the said gap identified in literature.

The city of Can Tho, located on Vietnam’s Mekong Delta, has been identified as one of the nation’s most vulnerable sites for adverse climate change-induced impacts. Can Tho’s policymakers are faced with tackling these challenges but lack the necessary tools and funds to properly address the situation. The study aims to develop a set of indicators to assess the degree of climate change vulnerability so that policymakers can determine which of Can Tho’s districts are most in need of attention, and then propose the best options for climate change adaptation activities.

The indicators, including quantifications of exposure, sensitivity and adaptive capacity, were categorized in three tiers, from 1 to 3, to reflect their importance with regard to the situation. The higher tier indicators comprised a number of lower tier indicators, which were developed based on real-life, practical situations at the local level.

The results showed that the Thoi Lai District, with a vulnerability indicator estimated at 0.59, is more vulnerable to the impacts of climate change than other districts because of its lower adaptive capacity and higher sensitivity. In contrast, Ninh Kieu District’s climate change indicator of 0.24 demonstrates it has higher resilience to climate change impacts.

This study showed that the set of indicators developed provides a promising approach for supporting local policymakers in Can Tho to actively respond to climate change-related challenges, and that this approach has the potential to be upscaled for other cities in Vietnam.

This paper aims to understand the vulnerability of community livelihoods (human, social, financial, natural and physical assets) at a coastal environment in southern Mozambique, considering the level of exposure, sensitivity and adaptive capacity to climate change.

The study adopted the sustainable livelihoods approach. Data were collected through distribution of a structured questionnaire to 476 randomly selected households at the municipality of Inhambane. The questionnaire assessed all capital assets, covering 14 indicators and 43 sub-indicators of vulnerability, derived from published literature.

Results indicate that overall community vulnerability is largely derived from the vulnerability of physical, financial and social capitals, illustrated by declared food shortage, low nutrition levels, weak social networks, high level of biomass utilization and lack of financial resources due to unemployment. These aspects largely influence the noticed reduced adaptive capacity of surveyed households.

The study identified the need to improve the overall process of natural resources appropriation and utilization and the improvement of the governance capacity at the local targeting infrastructure, community structure and networks and capacity building that might enhance community livelihoods in changing scenarios.

The study is a contribution to the overall understanding of how livelihoods are exposed to climate change and variability in coastal settings.

This study aims to investigate the impact of economic vulnerability upon entrepreneurial competencies (i.e. commitment competency, conceptual competency, opportunity recognition competency, organizing competency, relationship competency and strategic competency) among respondents from varied development initiatives established by the eKasih program (National Poverty Data Bank) in Peninsular Malaysia.

Upon adopting the cross-sectional design, data were randomly gathered from selected 300 micro-entrepreneurs from the list of development organizations available in the eKasih (National Poverty Data Bank), located at four states in Peninsular Malaysia. The quantitative data were gathered by performing structured interview sessions from September until November 2017.

The outcomes of the study displayed that economic vulnerability has a significantly negative effect upon commitment, opportunity recognition, organizing and strategic competency. On the other hand, the results showcased that economi c vulnerability has a significantly positive effect on competency, but insignificantly positive impact upon conceptual competency.

These study outcomes appear to extend the scope of the resource-based view, apart from enriching the existing entrepreneurial competency literature, particularly within the Malaysian context. Hence, it is recommended that the government of Malaysia and development organizations should focus on maximizing the level of competency among micro-entrepreneurs as a viable approach to decrease the effect of economic vulnerability.

This paper studies social inequality in the vital field of employment in Spain during the crisis period 2009-2014.

Factor analysis is used to build a synthetic index of employment exclusion. The starting information matrix collects data from a wide set of employment variables for all 17 Spanish autonomous communities and the autonomous cities of Ceuta and Melilla. Based on this information, four factors are extracted which explain employment exclusion in different situations of vulnerability, such as unemployment, temporality, poverty or low pay.

In the territorial ranking, Madrid, Basque Country, Aragon and Catalonia show the lowest risk of employment exclusion, whereas Ceuta, Andalusia, Extremadura and Canary Islands show the highest ones.

The main value of this research is that it confirms the need for coordination of public policies in order to foster social and territorial cohesion in Spain.

The study examines the effect of macroeconomic risk, inflation uncertainty and instability associated with key macroeconomic indicators on the efficiency of financial institutions among economies in sub-Saharan Africa (SSA).

Data for the empirical inquiry were compiled from 35 SSA economies from 1996 to 2019. The empirical estimates were carried out using pooled ordinary least squares (POLS) with Driscoll and Kraay’s (1998) standard errors.

Reported empirical estimates show that macroeconomic risk and exchange rate volatility constrain the efficiency of financial institutions. Further results suggest that inflation uncertainty has a significant influence on the efficiency of financial institutions among economies in the subregion. Additionally, reviewed empirical estimates show that institutional quality positively moderates the nexus between inflation uncertainty and financial institution efficiency. At the same time, political instability is found to worsen the adverse effect of macroeconomic risk on the efficiency of financial institutions.

For policymakers and governments, improved institutional structures are recommended to ensure the operational efficiency of financial institutions, especially during an inflationary period. For decision-makers among financial institutions, the study recommends policies that have the potential to make their institutions less vulnerable to macroeconomic risk and exchange rate fluctuations.

The approach adopted in this study differs significantly from related studies in that the study examines and reviews interactions and relationships not readily found in the reviewed literature.