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Despite the susceptibility of cotton crops to pest attacks in the Malwa Region of Indian Punjab, no crop insurance policy has been implemented there– not even the Pradhan Mantri Fasal Bima Yojana (PMFBY), which is a central scheme. Therefore, this paper attempts to gauge the likely impact of the PMFBY on Punjab cotton farmers and assess the changes needed for greater uptake and effectiveness of PMFBY.

The authors have conducted a primary survey to conduct this study. Initially, the authors compared the costs of cotton production with the returns in two scenarios (with and without insurance). Additionally, the authors have applied a logistic regression framework to examine the determinants of the willingness of farmers to participate in the crop insurance market.

The study finds that net returns of cotton crops are conventionally small and insufficient to cope with damages from crop failure. Yet, PMFBY will require some modifications in the premium rate and the level of indemnity for its greater uptake among Punjab cotton farmers. Additionally, using the logistic regression framework, the authors find that an increase in awareness about crop insurance and farmers' perceptions about their crop failure in the near future reduces the willingness of the farmers to participate in the crop insurance markets.

The present study looks for the viability of PMFBY in Indian Punjab for the cotton crop, which can also be extended to other crops.

Punjab could also use crop insurance to encourage diversification in agriculture. There is a need for special packages for diversified crops under any crop insurance policy. Crops susceptible to volatility due to climate-related factors should be identified and provided with a special insurance package.

There exist very scant studies that have discussed the viability of a central crop insurance scheme in the agricultural-rich state of India, i.e. Punjab. Moreover, they do not also focus on crop losses accruing due to pest and insect attacks.

This study analyzes the role of cooperative behavior in facing the risk of encouraging innovative agricultural production projects by small-scale farmers in the context of farmers in developing countries.

A within-subjects field experiment was conducted with small-scale Colombian panela cane farmers. The authors used the collected data to run the regression analyses.

The results suggest that when small farmers can follow cooperative behavior by joining a group and pooling resources to face risk, they are more willing to invest in a novel and profitable alternative, albeit riskier. However, the possibility of cooperating with a group to invest in a novel production project depends on its expected risk level.

These results will help develop agricultural policies for sustainable development. Establishing informal networks for small-scale farmers to deal with unpredictable risks may aid in developing innovative systems.

Agriculture is highly vulnerable to climatic impacts, which, combined with the inherent risk of innovation, may reduce small farmers' willingness to adopt innovation. Cooperation appears to be a mechanism for pooling resources and facing risk.

Research has focused on experimentally testing the effect of cooperative behavior when facing risk. The authors contribute to the literature by demonstrating the impact of the ability of small-scale farmers in rural areas to collectively manage risk on investment in innovative projects.

Climate change increases systematic risk for firms, especially those in the agricultural industry. Therefore, the need to examine the consequences of climate-related risks on agribusiness companies' financial performance across the globe and emerging markets has risen. In this context, the paper aims to investigate the effects of climate change risks on the financial performance of agriculture listed firms in Vietnam.

The study sample includes 77 Vietnamese listed firms in the agricultural industry in the period of 2015–2019. The authors chose temperature, wind, rainfall and humidity proxies to measure climate change. The OLS regression, random regression and sub-sample analysis have been used to examine the impacts of climate risks on firms' financial performance.

Empirical results show that rain and temperature have positive impacts on financial performance of Vietnamese agriculture listed firms, while wind and humidity have insignificant impacts on financial performance.

The research helps researchers, businesses, practitioners and policymakers interested in the agricultural industry, especially those in developing and emerging countries, to develop a deep understanding of the impact of climate change risks on firm performance and therefrom prepare necessary measures to reduce the negative impacts.

This study adds to the literature stream on the impacts of climate change on financial performance. It is the first study to investigate this impact in Vietnam, a country which depends mainly on agriculture.

Using Nigeria, as a point of reference, this study aims to explore the applicability of climatic variables as analytically valid factors for conceptual cost estimation. This is in view of the vastness and topographical alignment of Nigeria's landmass, which makes it a country of extreme climatic variability from north to south. As construction costs in Nigeria, similarly, tend to show a north-south alignment, the study's objective is to establish cost-estimating relationships (CERs) between the variability of climatic elements and the variance in construction cost, to arouse interest in the concept.

Deploying correlation analysis and multiple regression analysis, significant associations/relationships between meteorological variables and building cost for selected locations, following a North-South transect of the major climatic zones, are sought, to explain climate-induced construction cost variance. Validation of the regression model was carried out using variance analysis and the Mean Absolute Percentage Error of a different dataset.

Climatic indices of atmospheric moisture exhibited strong direct and partial correlations with construction costs, while sunshine hours and temperature were inversely correlated. The study further establishes statistically significant CERs between climatic variables and building cost in Nigeria, which accounted for 47.9% of the variance in construction cost across the climatic zones.

The study outcome provides a statistically valid platform for the development of more elaborate analytical costing models, for prototype buildings to be cited in disparate climatic settings.

This study establishes the statistical validity of climatic variables in constituting CERs for predicting construction costs in disparate climatic settings.

In the UK, responses to intense weather events regarding national and regional level perils include the support of a General Insurance policy at the address level as part of private residential and other insurance policies covering the key risks of flooding, subsidence and windstorm. In respect of the subsidence peril, dry summers can lead to many thousands of properties on shrinkable clay soils suffering differential downward movement as water is abstracted from the soil by vegetation. These events are forecast to increase in frequency and severity due to climate change, with costs for a dry event year of more than £500m to UK insurers. Assessing the character of these event years can inform government, local government, insurers and their agents as to the typical characteristics of an event year and its impacts. The purpose of this paper is to provide a comprehensive overview of the 2018 UK subsidence event year as it relates to trees and low rise buildings.

The research material is taken from claims that originated within the period commencing in the Summer of 2018, which in the UK was dry and with high levels of claim notification, and is from the private database of Property Risk Inspection Limited, one of the largest UK specialist subsidence claims handling businesses.

The data clearly illustrates the wide range of vegetative species causing or contributing to claims in the UK, their age ranges, sizes and conditions, management options and the range of land uses and statutory controls that exist in relation to title and other boundaries.

There have been various small-scale studies looking at individual cases of subsidence and the impacts of vegetation, but there have been no detailed investigations of large-scale claims-driven events such as the 2018 surge. The importance of this population-level investigation will only increase given the modelling for increased hot and dry summers over the coming decades.

This paper examines the impact of extreme rainfall shocks on the performance in test scores of students living near at-risk urban areas in Brazil.

To identify the causal effect, we consider the exogenous variation of rainfall at the municipal level conditioned on the distance from the school to risk areas and the rainfall intensity in the school months.

The results suggest that extreme precipitation shocks, defined as a shock of at least three months of high-intensity rainfall, have an adverse impact on both math and language performance. Through a heterogeneous effects analysis, we find that the impact varies by student gender, with girls being more affected. In addition, among students who study near at-risk areas, those with better previous school performance and higher socioeconomic status are more negatively affected.

Our results suggest that extreme weather events can increase the differences in human capital accumulation between the population living near risk areas and those living more distant from these areas.

The agricultural sector is a critical component of global economic development, and its significance has grown significantly in recent years. The risks associated with agriculture and the behaviors of farmers in handling these risks are becoming increasingly important, given the sector’s increasing dependence worldwide. Various activities related to agriculture are vulnerable to multiple risks, which can have severe consequences for farmers’ livelihoods. The purpose of this systematic review is to present a comprehensive analysis of the sources of risk faced by farmers and their choices in adopting risk management strategies worldwide.

The Preferred Reporting Items for Systematic reviews and Meta-Analyses protocol was utilized to select relevant literature, and a total of 102 studies were analyzed. Through the use of Venn diagrams and graphical methods, the authors provide a transparent overview of the risks faced by farmers and the adoption of risk management strategies in developed and developing countries.

From the analysis, the authors found that, in terms of risk management strategies, diversification, reserve credit and accumulated assets are frequently used in developing countries, while developed countries tend to rely on future/forward contracts, crop insurance and hedging. Diversification is the most widely used risk management strategy across both developed and developing countries. Our study also highlights the different perceptions of weather-related risks among growers in developed and developing countries.

This systematic review provides valuable insights into the risks associated with agriculture and farmers' strategies in managing these risks, which could inform policy decisions and promote sustainable agricultural practices. For instance, understanding the individualistic nature of farmers' risk perception and the varying risk sources and management strategies depending on the locality and provide assistance to the farmers accordingly.

The paper explains how farmers behave during uncertainty in terms of risk perception and their decision to adopt risk management strategies in developed and developing countries.

This study examines the evidence of the impact of climate change on the financial performance of basic materials companies in Vietnam.

The research sample includes eighty-two basic materials companies listed on the Vietnamese stock market from 2003 to 2022. This study used one-way and two-way fixed-effects feasible generalized least squares (FGLS) estimation methods.

Climate change, measured through variables including changes in temperature, average rainfall, greenhouse gas emissions and rising sea levels, has a negative impact on the financial performance of companies in this industry. The study also found that, with rising temperatures, the financial performance of steel manufacturing companies decreased less than that of coal mining and forestry companies, but increasing greenhouse gases and rising sea levels reduced the financial performance of steel companies. We did not find evidence of any difference in the impact of climate change on the financial performance of basic materials companies before and after the UN Climate Change Conference (COP 21). This is a new finding, which is consistent with empirical studies in Vietnam and different from previous studies in that it provides new evidence on the impact of climate change on the financial performance of basic materials companies in the Vietnamese market and cross-checks the impact of climate change by sector and over time.

To the best of our knowledge, this is one of the first articles on climate change and the financial performance of basic materials companies.

This study aims to measure the status of rural household food security across regions using multidimensional indicators. It also aims to identify the determinants of rural household food security in Ethiopia.

The study adopted descriptive and explanatory designs. It used data from the fourth wave of the Ethiopian socioeconomic survey that has 3,115 respondents. The authors constructed household food security index using variables that capture availability, access, utilization and stability dimensions of food security. The authors categorized households into relative food security groups, namely, alarming and moderately food insecure, as well as moderately and highly food secure. Beta regression model, which is widely used to analyze response variables that assume values between 0 and 1, is used to estimate the determinants of food security.

The study finds that 77.7% of rural households are food insecure. Of this, 90% are moderately food insecure. Regional variations in magnitude of food security showed that Harari, Gambella and Benshanguel Gumuz regional states are relatively better-off than other regions in Ethiopia. The study identified sex, education level, marital status, location and wealth status of households as significant determinants of food security.

This study sheds light on regional variations in multidimensional food security in Ethiopia. It thus challenged previous estimates of food security using uni-dimensional indicator. It highlighted the need for region-specific analysis of determinants and a follow up of tailored regional interventions.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-02-2023-0139

Water pipes degrade over time for a variety of pipe-related, soil-related, operational, and environmental factors. Hence, municipalities are necessitated to implement effective maintenance and rehabilitation strategies for water pipes based on reliable deterioration models and cost-effective inspection programs. In the light of foregoing, the paramount objective of this research study is to develop condition assessment and deterioration prediction models for saltwater pipes in Hong Kong.

As a perquisite to the development of condition assessment models, spherical fuzzy analytic hierarchy process (SFAHP) is harnessed to analyze the relative importance weights of deterioration factors. Afterward, the relative importance weights of deterioration factors coupled with their effective values are leveraged using the measurement of alternatives and ranking according to the compromise solution (MARCOS) algorithm to analyze the performance condition of water pipes. A condition rating system is then designed counting on the generalized entropy-based probabilistic fuzzy C means (GEPFCM) algorithm. A set of fourth order multiple regression functions are constructed to capture the degradation trends in condition of pipelines overtime covering their disparate characteristics.

Analytical results demonstrated that the top five influential deterioration factors comprise age, material, traffic, soil corrosivity and material. In addition, it was derived that developed deterioration models accomplished correlation coefficient, mean absolute error and root mean squared error of 0.8, 1.33 and 1.39, respectively.

It can be argued that generated deterioration models can assist municipalities in formulating accurate and cost-effective maintenance, repair and rehabilitation programs.