Abstract
This paper aims to present a new approach to measure downsize reputational risk, based on an event study methodology. To this aim, the share market value is used as a proxy of the company’s ability to create economic value, and the market reaction to different types of event is analyzed. Empirical data are derived from a large multinational company, operating in the Oil & Gas industry, with a dataset of 67 events, concerning environmental, social and economic performances. In detail, we propose a new model and we show how it overcomes the limitations of previous approaches by providing for each event a confidence interval for the estimated downsize impact and taking into account both the presence of price sensitive events and the share volatility. In this way, the proposed model provides the company’s managers with a clear insight about the impact and statistical significance of each event.
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Arena, M., Azzone, G., Conte, A., Secchi, P., Vantini, S. (2015). Measuring Downsize Reputational Risk in the Oil & Gas Industry. In: Paganoni, A., Secchi, P. (eds) Advances in Complex Data Modeling and Computational Methods in Statistics. Contributions to Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-11149-0_3
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DOI: https://doi.org/10.1007/978-3-319-11149-0_3
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