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Retailers have long been aware that weather affects the sales of a myriad of products, but until now, most were not in a position to manage the risks weather presents. Rising weather variability combined with advances in weather-index financial instruments have prompted new interest in investigating the relationship between sales and weather. The purpose of this paper is to explore the impact of changes in weather on UK retail sales, to estimate the contribution of weather to sales, and evaluate the maximum potential loss caused by adverse weather, for each season and retail sector.

The authors present a methodology to identify and quantify the extent to which a company is exposed to weather risks, in order to incorporate them into its risk management policy and take actions to mitigate these risks. For each season and each retail category, the authors provide a measure of the impact of weather on sales that can be used as a benchmark to analyse sales performance.

The authors propose a new risk assessment indicator to evaluate the potential losses caused by adverse weather (WeatherRisk). The authors show that intra-annual changes in weather significantly affect retail sales. The exposure of retail categories to weather are not the same depending on the season, and the response of individual retail categories to the same change in weather varies considerably. Although temperature is a predominant explanatory variable, the authors show that weather-sensitivity analysis should include precipitation, humidity rate and wind.

One limitation of this study is that the authors individually compute WeatherRisk for each significant weather variable. Further research could explore new approaches to evaluate Total WeatherRisk, which take into account potential multicollinearity issues between weather variables.

The methodology allows retailers to measure the effects of weather on sales performance, evaluate the risks at stake, and protect sales and margins from weather risks, with newly available index-based financial instruments. Managers may now actively use weather as a differential advantage, and at the same time focus their efforts on improving resiliency to increasing climate variability.

In this paper, the authors produce a detailed analysis of the exposure of each retail sectors to unseasonal weather. This is the first time all retail sectors are analysed and ranked per season at a national level. The authors provide managers with actionable information to improve their understanding of how weather impact sales over each season, and to allow them to structure weather-index-based instruments with financial partners.

The purpose of this paper is to investigate the role that weather shocks can play in the livestock mortality microinsurance take-up when the insured risk has a prevalent covariant component.

The sample consists of 360 rural Ethiopian households. Data were collected in a panel-structure at the end of three agricultural seasons (2011-2013). In the questionnaire, a specific section on insurance was meant to collect information on the farmer’s willingness-to-pay (WTP) for a set of insurance products, including livestock mortality insurance. Two OLS regression models and a quantile regression model were employed to estimate the impact of weather anomalies on the WTP for the insurance product.

The authors find that weather anomalies contribute to changes in the WTP to a large extent. Negative (positive) changes in precipitation (temperature) anomalies can lead to more than a 30 percent reduction in the WTP. This general finding is complemented with the analysis of the conditional distribution of the WTP, which shows that other elements can prevail for low values of the conditional distribution. In this case, the WTP seems to be represented more by the interviewee’s age and basic knowledge of insurance, and village fixed-effects. Basic knowledge of insurance, in particular, can increase WTP by about 60 percent.

This paper has straightforward implications from a policy perspective. It suggests that farmers would prefer an insurance premium that follows the changes in the systemic component. On the contrary, insurance as well as reinsurance companies are usually reluctant to frequently revise their premiums. Financial education programs, farmer-driven design, trust building, and bundling insurance with other financial and non-financial products can increase the value proposition perceived by the farmers. From a marketing perspective, the overall findings suggest that continuous fine-tuning of the contract, transparency, and targeted information campaigns can contribute to increase and stabilize potential customers’ WTP.

To the best of the authors’ knowledge, this is the first paper that considers the impact of weather shocks on the WTP for a livestock mortality insurance product. Livestock is one of the most strategic assets of poor rural households in Africa. This study contributes to the theoretical and empirical literature on the determinants of weather insurance take-up in developing countries and, in particular, the role of spatiotemporal adverse selection and basis risk (e.g. Jensen et al., 2016).

Research draws the distinction between noise traders and informed traders. Research also documents market biases in equity returns due to cloud cover, a non‐informational (noise) event, showing that returns decrease on cloudy days. The purpose of this paper is to investigate the trading behaviour of short‐sellers, who are considered informed traders, conditioning on the level of cloudiness, and find an increase in short selling with the level of cloudiness. Additionally, the paper finds decreases in short selling the three days prior to a cloudy day (or series of cloudy days).

The authors replicate the weather anomaly in stock returns reported in the literature for the sample period, and then study the trading behaviour of short sellers conditioned on cloud cover. Additionally the authors treat cloud cover as an event and study short selling volume in the pre‐event window.

The paper finds an increase in short selling with the level of cloudiness. Additionally, the paper finds decreases in short selling, relative to the event day(s), in the three days prior to a cloudy day (or series of cloudy days).

The authors believe that they are the first to document that weather impacts short seller's trading behaviour. The authors argue that the results point towards a behavioural bias.

The purpose of this paper is to investigate the weather and calendar effects on the usage pattern of a tourism web site.

This paper analyses data from a yearlong web log involving 21,655,089 visitors to a popular tourism web site. The weather factors include rain, snow, cloud cover, and the calendar factors include seasons and holidays in order to test the proposed model.

Using data from the Korea Tourism Organisation and the Korean Meteorological Administration, the results show that when it was rainy, cloudy, summer or a workday, the number of visitors to the tourism information web site was higher.

The results provide managers involved in the tourism industry with useful insights for effective use of web sites by running them more efficiently and setting up appropriate marketing strategies in terms of the weather and calendar variables.

Extensive literature studies the causes of crime and crime reporting behaviour. In contrast, there is hardly any scholarship on delays in reporting a crime and what drives them. Understanding delays in reporting crimes is important for various reasons, for example, because they could decrease the likelihood of an arrest or lead to an issue with the statute of limitations. This paper is the first to analyse the delay in reporting crimes and environmental drivers of these delays.

The authors construct a novel data set combining all crimes reported in New York City from 2006 to 2020 (N = 2,442,288) with station-level data on weather variables (temperature, rainfall, relative humidity, visibility and wind speed) and four types of air pollutants (carbon monoxide, ozone, sulphur dioxide, nitrogen dioxide). Matching these three data sets using the geolocation occurs at an hourly frequency. Importantly, the crime data provided by the NYPD allows us to control for several other factors that could potentially affect crime reporting behaviour.

The authors show that 30 percent of reported crimes in New York City were reported with a delay. The average reporting delay was 10.79 days. Carbon monoxide influences for delays in reporting violent crimes and rainfall affects delays in reporting property crimes. Relative humidity, as a driver of wet bulb temperature, affects delays in reporting violent crimes as well.

The authors present novel facts about delays in reporting crimes and how these are related to weather and air pollution. The authors’ findings have implications for government regulation of air pollution as well as for real-time crime forecasting. They should also aid victim support groups in providing services.

This paper is the first to analyse the impact of environmental factors on the delay in reporting crimes.

In the wake of climate change and its associated impact on firms' performance, this paper attempts to provide a piece of empirical evidence in support of the effect of weather conditions on the stock market performance.

Monthly time-series dataset and the fully modified ordinary least square (FMOLS) semi-parametric econometric technique are used to establish the effect of weather variables on stock market return.

This study finds that temperature and wind speed have a negative and statistically significant relationship with stock market performance. Likewise, humidity exhibits a negative relationship with stock market performance, albeit insignificant. The relevant stock market and macroeconomic control variables are statistically significant in addition to exhibiting their expected signs. The findings lend support to advocates of behavioural factors inclusion in asset pricing and decision-making.

For policy purposes, the authors recommend that traders, investors and stock exchange managers must take into consideration different weather conditions as they influence investors' behaviour, investment decisions, and consequently, the stock market performance.

To the best of the authors’ knowledge, this study provides the first empirical evidence of the nexus between disaggregated weather measures and stock market performance in Ghana. This study uses monthly data (which are very rare in the literature, especially for developing country studies) to provide empirical evidence that weather influences stock market performance.

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

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.

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

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).

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

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.

This paper uses a historical case study, the controversy over the possibility of climatic extremes caused by hydrogen bomb tests on Pacific Ocean atolls during the 1950s, to show how, in a context of few scientific data and high uncertainty, political affiliations and public concerns shaped two types of argumentation, the “energy” and the “precautionary” arguments.

Systematic analysis of publications 1954–1956: scientific and semiscientific articles, publications of C.-N. Martin and contemporary newspaper articles, especially from the Asia–Pacific region.

First, epistemological and scientific reasoning about the likelihood of extreme natural events aligned to political convictions and pressure. Second, a geographical and social distribution of arguments: the relativizing “energy argument” prevailed in English-language scientific journals, while the “precautionary argument” dominated in popular journals and newspapers published worldwide. Third, while the “energy argument” attained general scientific consensus within two years, it lost out in the long run. The proponents of the “precautionary argument” raised relevant research questions that, though first rejected in the 1950s, later exposed the fallacies of the “energy argument” (shown for the case of the climatologist William W. Kellogg).

In contrast to the existing secondary literature, this paper presents a balanced view of the weaknesses and strengths of two lines of arguments in the 1950s. Further, this historical study sheds light on how once-discarded scientific theories may ultimately be reconsidered in a completely different political and scientific context, thus justifying the original precautionary argument.