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Assessing Forecast Uncertainty : An Information Bayesian Approach
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Year: 2017 Publisher: Washington, D.C. : The World Bank,

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Abstract

Regardless of the field, forecasts are widely used and yet assessments of the embedded uncertainty-the magnitude of the downside and upside risks of the prediction itself-are often missing. Particularly in policy-making and investment, accounting for these risks around baseline predictions is of outstanding importance for making better and more informed decisions. This paper introduces a procedure to assess risks associated with a random phenomenon. The methodology assigns probability distributions to baseline-projections of an economic or social random variable-for example gross domestic product growth, inflation, population growth, poverty headcount, and so forth-combining ex-post and ex-ante market information. The generated asymmetric density forecasts use information derived from surveys on expectations and implied statistics of predictive models. The methodology also decomposes the variance and skewness of the predictive distribution accounting for the shares of selected risk factors. The procedure relies on a Bayesian information-theoretical approach, which allows the inclusion of judgment and forecaster expertise. For reliability purposes and transparency, the paper also evaluates the constructed density forecasts assigning a score. The continuous ranked probability score is used to assess the prediction accuracy of elicited density forecasts. The selected score incentivizes the forecaster to provide its true and best predictive distribution. An empirical application to forecast world gross domestic product growth is used to test the Bayesian entropy methodology. Predictive variance and skewness of world gross domestic product growth are associated with ex-ante information of four risk factors: term spreads, absolute deviations of headline inflation targets, energy prices, and the Standard and Poor's 500 index prices. The Bayesian entropy technique is benchmarked with naive-generated density forecasts that utilize information from historical forecast errors. The results show that the Bayesian density forecasts outperform the naive-generated benchmark predictions, illustrating the value added of the introduced methodology.


Book
Challenges and Opportunities for the Renewable Energy Economy
Author:
Year: 2020 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

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Renewable energy deployment as an alternative to traditional energy sources is the cornerstone of the emission-reduction energy policies that aim to facilitate the transition to a low-carbon economy. This transition poses risks and opportunities for companies with business models that rely directly or indirectly on renewables, which will be reflected in the revaluation of assets and in the reallocation of private and public financial investments from carbon-intensive to low-carbon energies. In a series of selected articles, this book addresses current challenges and opportunities for renewable energies from technological, economic and financial perspectives.

Keywords

Research & information: general --- day-ahead market --- balancing market --- gate closure --- forecast uncertainty --- wind power forecast --- agent-based simulation --- the MATREM system --- drying --- solar energy --- sustainable processing --- energy efficiency --- global heat production --- energy market --- energy conversion --- electricity --- carbon trading --- palm oil producer --- renewable energy --- economy --- sustainable development --- clean development mechanism --- Sustainable Development Goals (SDGs) --- Malaysia --- energy planning --- Modern Portfolio Theory (MPT) --- Capital Asset Pricing Model (CAPM) --- low-carbon economy --- renewable energy deployment --- environmental efficiency --- pumped hydro storage --- wind farm --- simulated annealing --- genetic algorithm --- pattern search --- Matlab optimization toolbox --- economic and environment feasibility --- renewables --- low carbon --- interdependence --- copulas --- conditional quantiles --- liquefied natural gas --- cold energy --- regasification --- chilled water --- techno economic --- coevolution --- the fuel ethanol industry --- history-friendly model --- entry regulation --- ethanol mandate --- production subsidy --- R&amp --- D subsidy --- day-ahead market --- balancing market --- gate closure --- forecast uncertainty --- wind power forecast --- agent-based simulation --- the MATREM system --- drying --- solar energy --- sustainable processing --- energy efficiency --- global heat production --- energy market --- energy conversion --- electricity --- carbon trading --- palm oil producer --- renewable energy --- economy --- sustainable development --- clean development mechanism --- Sustainable Development Goals (SDGs) --- Malaysia --- energy planning --- Modern Portfolio Theory (MPT) --- Capital Asset Pricing Model (CAPM) --- low-carbon economy --- renewable energy deployment --- environmental efficiency --- pumped hydro storage --- wind farm --- simulated annealing --- genetic algorithm --- pattern search --- Matlab optimization toolbox --- economic and environment feasibility --- renewables --- low carbon --- interdependence --- copulas --- conditional quantiles --- liquefied natural gas --- cold energy --- regasification --- chilled water --- techno economic --- coevolution --- the fuel ethanol industry --- history-friendly model --- entry regulation --- ethanol mandate --- production subsidy --- R&amp --- D subsidy


Book
Challenges and Opportunities for the Renewable Energy Economy
Author:
Year: 2020 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

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Export citation

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Bookmark

Abstract

Renewable energy deployment as an alternative to traditional energy sources is the cornerstone of the emission-reduction energy policies that aim to facilitate the transition to a low-carbon economy. This transition poses risks and opportunities for companies with business models that rely directly or indirectly on renewables, which will be reflected in the revaluation of assets and in the reallocation of private and public financial investments from carbon-intensive to low-carbon energies. In a series of selected articles, this book addresses current challenges and opportunities for renewable energies from technological, economic and financial perspectives.


Book
Challenges and Opportunities for the Renewable Energy Economy
Author:
Year: 2020 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

Loading...
Export citation

Choose an application

Bookmark

Abstract

Renewable energy deployment as an alternative to traditional energy sources is the cornerstone of the emission-reduction energy policies that aim to facilitate the transition to a low-carbon economy. This transition poses risks and opportunities for companies with business models that rely directly or indirectly on renewables, which will be reflected in the revaluation of assets and in the reallocation of private and public financial investments from carbon-intensive to low-carbon energies. In a series of selected articles, this book addresses current challenges and opportunities for renewable energies from technological, economic and financial perspectives.

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