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Article
Publication date: 20 December 2022

Xuan Liu, G. Cornelis van Kooten, Eric Martin Gerbrandt and Jun Duan

The authors investigate whether an index-based weather insurance (WII) product can complement or replace existing traditional crop yield insurance for mitigating farmers'…

Abstract

Purpose

The authors investigate whether an index-based weather insurance (WII) product can complement or replace existing traditional crop yield insurance for mitigating farmers' financial risks, with an application to blueberry growers in British Columbia (BC).

Design/methodology/approach

A hybrid model combining expected utility (EU) and prospect values is developed to analyse farmers' demand for WII.

Findings

While weather data are used to investigate supply elements, a hybrid model combining EU theory and prospect theory (PT) is developed to analyse farmers' demand for WII. On the supply side, a quality index is constructed and the relationship between the quality index and key weather parameters is quantified using a partial least squares structural model. The authors then model weather parameters via time-series analysis and statistical distributions to provide reasonable estimates for calculating actuarially sound insurance premiums for a rainfall indexed, insurance product. This model indicates that decreases in the proportion of a blueberry grower's total revenue and revenue volatility will decrease the possibility that they participate in WII. At the same time, an increase in the value loss aversion coefficient and WII's basis risk further leads to less demand for WII. In short, a grower may decide not to participate in WII at an actuarially fair premium due to the combined effects of the above factors. Overall, while the supply analysis enables us to demonstrate that WII can potentially help in mitigating farmers' financial risks, it turns out that, on the demand side, blueberry growers are unwilling to pay for such a product without large government subsidies.

Originality/value

The authors argue that the demand for insurance may be affected by the level and the volatility of a berry grower's total revenue. Hence, the authors propose a hybrid expression that assumes a farmer seeks to maximize the total utility function to capture the rational and intuitive parts of a farmer's decision-making process. The EU represents rationality and the prospect value represents the intuitive component. Meanwhile, the authors investigate the possibility of using key weather parameters to construct a berry quality index – one that could be applied to other agricultural areas for studying the relationship between weather conditions and product quality.

Details

Agricultural Finance Review, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0002-1466

Keywords

Open Access
Article
Publication date: 31 May 2009

Kwang-Il Bae and Jin Hee Choung

The weather largely affects economic activity, and thus, companies vulnerable to weather risk need to plan ahead to cope with unexpected weather changes, just as they do…

32

Abstract

The weather largely affects economic activity, and thus, companies vulnerable to weather risk need to plan ahead to cope with unexpected weather changes, just as they do for changes in interest rates, oil prices, or foreign exchange rates to stabilize their earning stream. Weather derivatives can be a useful tool for weather risk management.

This paper focuses on pricing one of the most popular weather derivatives -HDD/CDD options- and estimating the market price of weather risk (MPR). Historical data are used to construct the stochastic process of temperature, while the current market prices of Chicago and New York HDD futures options are used to extract the implied MPR. The Monte-Carlo Simulation Method is proposed to estimate the price of weather derivatives numerically. In addition, the approximate closed form formula for the options is provided modifying the Alaton, Djehiche, and Stillberg (2002) model. Finally, option price sensitivity to changes in MPR is analyzed to show the important role of the MPR in the weather option pricing model.

Details

Journal of Derivatives and Quantitative Studies, vol. 17 no. 2
Type: Research Article
ISSN: 2713-6647

Keywords

Article
Publication date: 1 February 1999

Martin Lohmann and Eike Kaim

Five factors are a prerequisite for tourism: Ability to travel and motivation to travel on the demand side, and attractiveness, amenities and accessibility on the side of…

1096

Abstract

Five factors are a prerequisite for tourism: Ability to travel and motivation to travel on the demand side, and attractiveness, amenities and accessibility on the side of the destination. Concerning the attractiveness of a destination, the factor weather is of particular importance. Until now, there is a lack of empirical data, showing if and how weather affects holiday destination preferences.

Details

The Tourist Review, vol. 54 no. 2
Type: Research Article
ISSN: 0251-3102

Keywords

Article
Publication date: 20 March 2007

Karyl B. Leggio

The purpose of this study is to demonstrate the use of weather derivatives to hedge firm exposure to previously unmanageable risk events caused by natural phenomenon such…

2295

Abstract

Purpose

The purpose of this study is to demonstrate the use of weather derivatives to hedge firm exposure to previously unmanageable risk events caused by natural phenomenon such as excessive rainfall.Design/methodology/approach – The paper adopts a case study approach to meet the objectives above, focusing on golf courses in the Midwest USA, which provide perfect examples of businesses with seasonal cash flows.Findings – It is shown that a firm can reduce its revenue volatility by up to 80 per cent. Weather derivatives are important additions to firm portfolios of risk management tools. Purchasing weather derivatives will improve the owner's ability to forecast revenues and assure expenditure coverage, both important goals for a small business owner.Practical implications – Many firms find the uneven revenue streams associated with their industry to be difficult to manage. One of the primary risks faced by firms is exposure to weather phenomena. With the introduction of weather derivatives, firms can now hedge their exposure to climatologic events. The application for weather derivatives is quite limitless. Weather derivatives are a relatively new product, and most firms are either unaware of their existence or believe them to be complicated. It is an industry that may experience explosive growth in the coming years.Originality/value – This paper demonstrates the use of derivatives to hedge exposure to climatic events.

Details

Managerial Finance, vol. 33 no. 4
Type: Research Article
ISSN: 0307-4358

Keywords

Article
Publication date: 16 September 2022

Anas Al-Refaie, Ali Alashwal, Zulkiflee Abdul-Samad, Hafez Salleh and Ahmed Elshafie

Weather is one of the main factors affecting labour productivity. Existing weather-productivity models focussed on hot and cold climates paying less attention to the…

Abstract

Purpose

Weather is one of the main factors affecting labour productivity. Existing weather-productivity models focussed on hot and cold climates paying less attention to the tropics. Many tropical countries are expected to be the most areas affected by accelerated climate change and global warming, which may have a severe impact on labour health and productivity. The purpose of this paper is to assess whether the existing models can be used to predict labour productivity based on weather conditions in the tropics.

Design/methodology/approach

Five models are identified from the literature for evaluation. Using real labour productivity data of a high-rise building project in Malaysia, the actual productivity rate was compared with predicted productivity rates generated using the five models. The predicted productivity rates were generated using weather variables collected from an adjusting weather station to the project.

Findings

Compared with other models evaluated in this paper, the United States Army Corps of Engineers (USACE) was found to be the best model to predict productivity based on the case study data. However, the result shows only a 57% accuracy level of the USACE model indicating the need to develop a new model for the tropics for more accurate prediction.

Originality/value

The result of this study is perhaps the first to apply meteorological variables to predict productivity rates and validate them using actual productivity data in the tropics. This study is the first step to developing a more accurate productivity model, which will be useful for project planning and more accurate productivity rate estimation.

Details

Built Environment Project and Asset Management, vol. 13 no. 2
Type: Research Article
ISSN: 2044-124X

Keywords

Article
Publication date: 16 August 2022

Pankaj Singh

The purpose of the present paper is to review studies on weather index-insurance as a tool to manage the climate change impact risk on farmers and to explore the study…

Abstract

Purpose

The purpose of the present paper is to review studies on weather index-insurance as a tool to manage the climate change impact risk on farmers and to explore the study gaps in the currently existing literature by using a systematic literature review.

Design/methodology/approach

This study analyzed and reviewed the 374 articles on weather index insurance (WII) based on a systematic literature search on Web of Science and Scopus databases by using the systematic literature review method.

Findings

WII studies shifted their focus on growing and emerging areas of climate change impact risk. The finding shows that the impact of climate change risk significantly influenced the viability of WII in terms of pricing and design of WII. Therefore, the cost of WII premium increases due to the uncertainty of climate change impact that enhances the probability of losses related to insured weather risks. However, WII has emerged as a risk management tool of climate insurance for vulnerable agrarian communities. The efficacy of WII has been significantly influenced by repetitive environmental disasters and climate change phenomena.

Research limitations/implications

This study will be valuable for scholars to recognize the missing and emerging themes in WII.

Practical implications

This study will help the policy planners to understand the influence of climate change impact on WII viability.

Originality/value

This study is the original work of the author. An attempt has been made in the present study to systematically examine the viability of WII for insuring the climate change risk.

Details

Journal of Science and Technology Policy Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2053-4620

Keywords

Article
Publication date: 11 August 2021

Wienand Kölle, Matthias Buchholz and Oliver Musshoff

Satellite-based weather index insurance has recently been considered in order to reduce the high basis risk of station-based weather index insurance. However, the use of…

Abstract

Purpose

Satellite-based weather index insurance has recently been considered in order to reduce the high basis risk of station-based weather index insurance. However, the use of satellite data with a relatively low spatial resolution has not yet made it possible to determine the satellite indices free of disturbing landscape elements such as mountains, forests and lakes.

Design/methodology/approach

In this context, the Normalized Difference Vegetation Index (NDVI) was used based on both Moderate Resolution Imaging Spectroradiometer (MODIS) (250 × 250 m) and high-resolution Landsat 5/8 (30 × 30 m) images to investigate the effect of a higher spatial resolution of satellite-based weather index contracts for hedging winter wheat yields. For three farms in north-east Germany, insurance contracts both at field and farm level were designed.

Findings

The results indicate that with an increasing spatial resolution of satellite data, the basis risk of satellite-based weather index insurance contracts can be reduced. However, the results also show that the design of NDVI-based insurance contracts at farm level also reduces the basis risk compared to field level. The study shows that higher-resolution satellite data are advantageous, whereas satellite indices at field level do not reduce the basis risk.

Originality/value

To the best of the author’s knowledge, the effect of increasing spatial resolution of satellite images for satellite-based weather index insurance is investigated for the first time at the field level compared to the farm level.

Details

Agricultural Finance Review, vol. 82 no. 4
Type: Research Article
ISSN: 0002-1466

Keywords

Article
Publication date: 26 July 2021

Álvaro Rodríguez-Sanz, Javier Cano and Beatriz Rubio Fernández

Weather events have a significant impact on airport arrival performance and may cause delays in operations and/or constraints in airport capacity. In Europe, almost half…

Abstract

Purpose

Weather events have a significant impact on airport arrival performance and may cause delays in operations and/or constraints in airport capacity. In Europe, almost half of all regulated airport traffic delay is due to adverse weather conditions. Moreover, the closer airports operate to their maximum capacity, the more severe is the impact of a capacity loss due to external events such as weather. Various weather uncertainties occurring during airport operations can significantly delay some arrival processes and cause network-wide effects on the overall air traffic management (ATM) system. Quantifying the impact of weather is, therefore, a key feature to improve the decision-making process that enhances airport performance. It would allow airport operators to identify the relevant weather information needed, and help them decide on the appropriate actions to mitigate the consequences of adverse weather events. Therefore, this research aims to understand and quantify the impact of weather conditions on airport arrival processes, so it can be properly predicted and managed.

Design/methodology/approach

This study presents a methodology to evaluate the impact of adverse weather events on airport arrival performance (delay and throughput) and to define operational thresholds for significant weather conditions. This study uses a Bayesian Network approach to relate weather data from meteorological reports and airport arrival performance data with scheduled and actual movements, as well as arrival delays. This allows us to understand the relationships between weather phenomena and their impacts on arrival delay and throughput. The proposed model also provides us with the values of the explanatory variables (weather events) that lead to certain operational thresholds in the target variables (arrival delay and throughput). This study then presents a quantification of the airport performance with regard to an aggregated weather-performance metric. Specific weather phenomena are categorized through a synthetic index, which aims to quantify weather conditions at a given airport, based on aviation routine meteorological reports. This helps us to manage uncertainty at airport arrival operations by relating index levels with airport performance results.

Findings

The results are computed from a data set of over 750,000 flights on a major European hub and from local weather data during the period 2015–2018. This study combines delay and capacity metrics at different airport operational stages for the arrival process (final approach, taxi-in and in-block). Therefore, the spatial boundary of this study is not only the airport but also its surrounding airspace, to take both the arrival sequencing and metering area and potential holding patterns into consideration.

Originality/value

This study introduces a new approach for modeling causal relationships between airport arrival performance indicators and meteorological events, which can be used to quantify the impact of weather in airport arrival conditions, predict the evolution of airport operational scenarios and support airport decision-making processes.

Details

Aircraft Engineering and Aerospace Technology, vol. 94 no. 1
Type: Research Article
ISSN: 1748-8842

Keywords

Content available
Article
Publication date: 28 June 2021

Chaur-Luh Tsai, Dong-Taur Su and Chun-Pong Wong

The objective of this research is to examine the performance of weather routing service in the North Pacific Ocean based on a global container shipping company.

Abstract

Purpose

The objective of this research is to examine the performance of weather routing service in the North Pacific Ocean based on a global container shipping company.

Design/methodology/approach

The data comprise two passages: one that departs from the port of Taipei to the port of Los Angeles (TPE-LAX) and another that departs from the port of Tacoma to the port of Kaohsiung (TCM-KSG). A weather routing service was utilized to compare the differences of the distance, sailing time and fuel consumed among different voyages.

Findings

Results indicated that the average speed of vessel in winter is faster than in summer. The vessels consumed much more fuel in the winter than they did in the summer. In terms of the distance of the passage, the results show that the ships' sailing distance across the North Pacific Ocean in the summer was shorter than it was in the winter.

Research limitations/implications

Due to the difficultly of practical data collection, relatively few sailing records were employed in this study. It is suggested that additional sailing records should be collected, which adopt weather routing recommendations, to more comprehensively analyze sailing performance in future research.

Practical implications

The study's findings offer valuable guidance to different stakeholders in the maritime industry (e.g. seafarers, marine hull and machinery companies, Protection and Indemnity Club (P&I), ocean container carriers and freight forwarders) to clarify their responsibilities in order to achieve desired sailing outcomes.

Originality/value

To the best of the authors' knowledge, the current study is the first research to utilize practical sailing data to provide objective evidence of sailing performance based on a weather routing service, which can assist various stakeholders to make optimal decisions.

Details

Maritime Business Review, vol. 6 no. 3
Type: Research Article
ISSN: 2397-3757

Keywords

Article
Publication date: 12 October 2021

Janesh Sami

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

Abstract

Purpose

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

Design/methodology/approach

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.

Findings

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

Research limitations/implications

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).

Practical implications

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

Originality/value

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.

Details

Review of Behavioral Finance, vol. 15 no. 1
Type: Research Article
ISSN: 1940-5979

Keywords

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