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Forecast Uncertainty (forecast + uncertainty)

Distribution by Scientific Domains

Mathematics and Statistics	42%
Business, Economics, Finance and Accounting	28%

Selected Abstracts

Forecast uncertainty: sources, measurement and evaluation

JOURNAL OF APPLIED ECONOMETRICS, Issue 4 2010
Matteo Ciccarelli
First page of article [source]

A Bayesian hierarchical approach to ensemble weather forecasting

JOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES C (APPLIED STATISTICS), Issue 3 2010
A. F. Di Narzo
Summary., In meteorology, the traditional approach to forecasting employs deterministic models mimicking atmospheric dynamics. Forecast uncertainty due to partial knowledge of the initial conditions is tackled by ensemble predictions systems. Probabilistic forecasting is a relatively new approach which may properly account for all sources of uncertainty. We propose a hierarchical Bayesian model which develops this idea and makes it possible to deal with ensemble predictions systems with non-identifiable members by using a suitable definition of the second level of the model. An application to Italian small-scale temperature data is shown. [source]

Reanalysis and reforecast of three major European storms of the twentieth century using the ECMWF forecasting system.

METEOROLOGICAL APPLICATIONS, Issue 2 2005
Part II: Ensemble forecasts
In Part II of this study the ECMWF Ensemble Prediction System (EPS) is used to study the probabilistic predictability of three major European storms of the twentieth century. The storms considered are the Dutch storm of 1 February 1953, the Hamburg storm of 17 February 1962, and the British/French storm of October 1987 (Great October storm). Common to all these storms is their severity that caused large loss of life and widespread damage. In Part I of this study it has been found that deterministic predictability of the Dutch and Hamburg storms amount to 48 and 84 hours, respectively. Here, it is shown that the ensemble forecasts supplement the deterministic forecasts. The large number of members in the 48 and 84 hour ensemble forecasts of the Dutch and Hamburg storms, respectively, suggest that at this forecast range and for these storms the sensitivity of the forecasts to analysis and model uncertainties is rather small. From these results, therefore, it is argued that reliable warnings (i.e. low probability for the occurrence of a forecast failure) for the Dutch and Hamburg storms could have been issued 48 and 84 hours, respectively, in advance, had the current ECMWF EPS been available. For the Great October storm it has been found in Part I of this study that short-range and medium-range forecasts of the intensity and track of the storm were very skilful with a high-resolution model of the ECWMF model. The actual timing of the storm, however, was difficult to predict. Here, it is shown that the EPS is capable of predicting large forecast uncertainties associated with the timing of the Great October storm up to 4 days in advance. It is argued that reliable warnings could have been issued at least 96 hours in advance had the ECMWF EPS been available. From the results presented in this study it is concluded that an Ensemble Prediction System is an important component of every early warning system for it allows an a priori quantification of the probability of the occurrence of severe wind storms. Copyright © 2005 Royal Meteorological Society [source]

RATIONAL PARTISAN THEORY, UNCERTAINTY, AND SPATIAL VOTING: EVIDENCE FOR THE BANK OF ENGLAND'S MPC

ECONOMICS & POLITICS, Issue 2 2010
ARNAB BHATTACHARJEE
The transparency and openness of the monetary policy-making process at the Bank of England has provided very detailed information on both the decisions of individual members of the Monetary Policy Committee (MPC) and the information on which they are based. In this paper, we consider this decision-making process in the context of a model in which inflation forecast targeting is used, but there is heterogeneity among the members of the committee. We find that rational partisan theory can explain spatial voting behavior under forecast uncertainty about the output gap. Internally generated forecasts of output and market-generated expectations of medium-term inflation provide the best description of discrete changes in interest rates, in combination with uncertainty in the macroeconomic environment. There is also a role for developments in asset, housing and labor markets. Further, spatial voting patterns clearly differentiate between internally and externally apzpointed members of the MPC. The results have important implications for committee design and the conduct of monetary policy. [source]

Risk-sensitive sizing of responsive facilities

NAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 3 2008
Sergio Chayet
Abstract We develop a risk-sensitive strategic facility sizing model that makes use of readily obtainable data and addresses both capacity and responsiveness considerations. We focus on facilities whose original size cannot be adjusted over time and limits the total production equipment they can hold, which is added sequentially during a finite planning horizon. The model is parsimonious by design for compatibility with the nature of available data during early planning stages. We model demand via a univariate random variable with arbitrary forecast profiles for equipment expansion, and assume the supporting equipment additions are continuous and decided ex-post. Under constant absolute risk aversion, operating profits are the closed-form solution to a nontrivial linear program, thus characterizing the sizing decision via a single first-order condition. This solution has several desired features, including the optimal facility size being eventually decreasing in forecast uncertainty and decreasing in risk aversion, as well as being generally robust to demand forecast uncertainty and cost errors. We provide structural results and show that ignoring risk considerations can lead to poor facility sizing decisions that deteriorate with increased forecast uncertainty. Existing models ignore risk considerations and assume the facility size can be adjusted over time, effectively shortening the planning horizon. Our main contribution is in addressing the problem that arises when that assumption is relaxed and, as a result, risk sensitivity and the challenges introduced by longer planning horizons and higher uncertainty must be considered. Finally, we derive accurate spreadsheet-implementable approximations to the optimal solution, which make this model a practical capacity planning tool.© 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008 [source]

The effects of wording on the understanding and use of uncertainty information in a threshold forecasting decision

APPLIED COGNITIVE PSYCHOLOGY, Issue 1 2009
Susan L. Joslyn
Many believe that information about small chances of severe weather would be useful to the general public for precautionary action. What is the best way to explain this kind of information to a non-expert audience? The studies reported here investigated effects of framing (negative vs. positive), format (frequency vs. probability), likelihood (low vs. high) and compatibility (task-match) on interpretation of verbal expressions of forecast uncertainty and on subsequent forecasting decisions. The crucial factor was the match between the verbal expression and the overall task goal. Errors increased when there was a mismatch between the expression (e.g. winds less than 20,knots) and the task (e.g. post an advisory when winds will exceed 20,knots). However, framing and format had little impact. We conclude that consideration of user expectations arising from the overall task goal is crucial in explaining uncertainty information to a naïve audience. Global expectations overpower other potential effects. Copyright © 2008 John Wiley & Sons, Ltd. [source]