Download or read book A Comparative Study of the Forecasting Performance of Three International Organizations written by Pingfan Hong and published by . This book was released on 2014 with total page 1 pages. Available in PDF, EPUB and Kindle. Book excerpt: This article evaluates and compares the forecasting performance of three international organizations: the United Nations, the International Monetary Fund and the World Bank. The annual forecasts made by the United Nations in the period of 1981-2011 are found to be fairly robust, in terms of bias and efficiency. In comparison, the forecasting performance of the United Nations is found to be marginally better than the other two organizations during the period of 2000-2012. However, the forecasts of all these organizations missed the Great Recession of 2009 by a large margin.
Download or read book A Comparative Study of Forecasting Performance written by A. Banerji and published by . This book was released on 2000 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Comparative Analysis of Forecasting Performance written by Abdullahi Farah Ahmed and published by . This book was released on 2001 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Comparative Study of the Forecasting Performance of Fixed Parameter and Varying Parameter Inflation Models written by Haiyan Song and published by . This book was released on 1991 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Comparative Analysis of Two Cost Performance Forecasting Models The Automated Financial Analysis Program Electronic Systems Division November 1976 Versus a Cost Performance Forecasting Concept and Model Aeronautical Systems Division November 1974 written by and published by . This book was released on 1980 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt: The authors investigated the comparative accuracy of linear and non- linear cost forecasting models in estimating a contractor's cost at completion. Using cost performance reports for 20 completed aircraft programs, the authors generated estimates covering the span of the programs. The mean absolute percentage errors for each method and program were analyzed using ANOVA. Where indicated by ANOVA, Fisher's least significant difference test statistic was used to test the differences and established set groupings. The authors conclude, based on the sample that the linear cost forecasting model is as accurate as the non-linear cost forecasting model. (Author).
Download or read book A Comparative Study of Univariate Time series Methods for Sales Forecasting written by Vishvesh Shah and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Sales time-series forecasters, data scientists and managers often use timeseries forecasting methods to predict sales. Nonetheless, it is still a question which time-series method a forecaster is best off using, if they only have time to generate one forecast. This study investigates and evaluates different sales time-series forecasting methods: multiplicative Holt-Winters (HW), additive HW, Seasonal Auto Regressive Integrated Moving Average (SARIMA) (A variant of Auto Regressive Integrated Moving Average (ARIMA)), Long Short-Term Memory Recurrent Neural Networks (LSTM) and the Prophet method by Facebook on thirty-two univariate sales time-series. The data used to forecast sales is taken from time-series Data Library (TSDL). With respect to the Root Mean Square Error (RMSE) evaluation metric, we find that forecasting sales with the SARIMA method offers the best performance, on average, relative to the other compared methods. To support the findings, both mathematical and economic reasoning on the drivers of the observed performance for each method are provided. However, a decision maker or an organization need to evaluate the trade-off between forecasting accuracy and the shortcomings associated with each method.
Download or read book Econometric Model Performance written by Lawrence R. Klein and published by University of Pennsylvania Press. This book was released on 2016-11-11 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: Models of the American economy exist in government, research institutes, universities, and private corporations. Given the proliferation, it is wise to take stock because these models come from diverse sources and describe different conditions from alternative points of view. They could be saying different things about the economy. The high-level comparative studies in this volume, gathered from several issues of the International Economic Review, with a substantive introduction and the addition of more comparative material, evaluate the performance of eleven models of the American economy: the Wharton Mark Ill Model; Brookings Model; Hickman-Coen Annual Model; Liu-Hwa Monthly Model; Data Resources, Inc. (DRI) Model; Federal Reserve Bank of St. Louis Model; Michigan Quarterly Econometric (MOEM) Model; Wharton Annual and Industry Model; Anticipation Version of the Wharton Mark Ill Model/Fair Model; U.S. Department of Commerce (BEA) Model. Each of the proprietors or builders of these models describes his own system in his own words. These studies come closer than ever before to standardizing model operations for testing purposes. Some of the models are monthly, while others are annual. but the quarterly unit of time is the most frequent. Some are demand oriented, others are supply oriented, and focus on the input-output sectors of the economy. Some use only observed. objective data; others use subjective. anticipatory data. Both large and small models are included. In spite of the diversity, the contributors have cooperated to trace the differences between their models to root causes and to report jointly the results of their research. There are also some general papers that look at model performance from outside the CEME group.
Download or read book A comparative study on the performance of two forecasting techniques based either on distributed lag models or on pay off distributions written by Hans-Joachim Lenz and published by . This book was released on 1979 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Comparative Analysis of Two Cost Performance Forecasting Models written by Edward L. Preston (CAPT, USAF.) and published by . This book was released on 1980 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Comparison of Forecast Performance Between Federal Reserve Staff Forecasts Simple Reduced form Models and a DSGE Model written by Rochelle Mary Edge and published by . This book was released on 2009 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Recurrent Neural Networks for Short Term Load Forecasting written by Filippo Maria Bianchi and published by Springer. This book was released on 2017-11-09 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt: The key component in forecasting demand and consumption of resources in a supply network is an accurate prediction of real-valued time series. Indeed, both service interruptions and resource waste can be reduced with the implementation of an effective forecasting system. Significant research has thus been devoted to the design and development of methodologies for short term load forecasting over the past decades. A class of mathematical models, called Recurrent Neural Networks, are nowadays gaining renewed interest among researchers and they are replacing many practical implementations of the forecasting systems, previously based on static methods. Despite the undeniable expressive power of these architectures, their recurrent nature complicates their understanding and poses challenges in the training procedures. Recently, new important families of recurrent architectures have emerged and their applicability in the context of load forecasting has not been investigated completely yet. This work performs a comparative study on the problem of Short-Term Load Forecast, by using different classes of state-of-the-art Recurrent Neural Networks. The authors test the reviewed models first on controlled synthetic tasks and then on different real datasets, covering important practical cases of study. The text also provides a general overview of the most important architectures and defines guidelines for configuring the recurrent networks to predict real-valued time series.
Download or read book Introduction to Time Series Analysis and Forecasting written by Douglas C. Montgomery and published by John Wiley & Sons. This book was released on 2015-04-21 with total page 670 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition "...[t]he book is great for readers who need to apply the methods and models presented but have little background in mathematics and statistics." -MAA Reviews Thoroughly updated throughout, Introduction to Time Series Analysis and Forecasting, Second Edition presents the underlying theories of time series analysis that are needed to analyze time-oriented data and construct real-world short- to medium-term statistical forecasts. Authored by highly-experienced academics and professionals in engineering statistics, the Second Edition features discussions on both popular and modern time series methodologies as well as an introduction to Bayesian methods in forecasting. Introduction to Time Series Analysis and Forecasting, Second Edition also includes: Over 300 exercises from diverse disciplines including health care, environmental studies, engineering, and finance More than 50 programming algorithms using JMP®, SAS®, and R that illustrate the theory and practicality of forecasting techniques in the context of time-oriented data New material on frequency domain and spatial temporal data analysis Expanded coverage of the variogram and spectrum with applications as well as transfer and intervention model functions A supplementary website featuring PowerPoint® slides, data sets, and select solutions to the problems Introduction to Time Series Analysis and Forecasting, Second Edition is an ideal textbook upper-undergraduate and graduate-levels courses in forecasting and time series. The book is also an excellent reference for practitioners and researchers who need to model and analyze time series data to generate forecasts.
Download or read book Examining the Forecasting Performance of a Modified Affine Model with Macroeconomic and Latent Factors written by Anastasios Evgenidis and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Various studies model the dynamics of the yield curve assuming that some of the yields are measured without error but this methodology lacks economic interpretation. We overcome this problem by estimating a modified affine model with macroeconomic and latent factors which introduces measurement noise on both yields and macroeconomic determinants. Our results suggest that under the proposed model there is a significant reduction in the persistence of the latent factors and an increase in the effect of macroeconomic shocks to the entire yield curve. We provide a comparative analysis of these models, and we conduct out of sample comparative forecasts to investigate if our specification has a superior performance. We find important differences concerning the magnitude of the dynamics that move the yield curve. Our model provides better forecasts for the entire yield curve while it also beats random walk in many cases. This is an important finding since according to the relative literature it is very difficult for any affine model to outperform random walk.
Download or read book Benchmarking written by Chaman L. Jain and published by Institute of Business Forec. This book was released on 2006 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Comparison of the Forecast Performance of Markov Switching and Threshold Autoregressive Models of Us Gnp written by Michael P. Clements and published by . This book was released on 1999 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: While there has been a great deal of interest in the modelling of non-linearities in economic time series, there is no clear consensus regarding the forecasting abilities of non-linear time-series models. We evaluate the performance of two leading non-linear models in forecasting post-war US GNP, the self-exciting threshold autoregressive model and the Markov-switching autoregressive model. Two methods of analysis are employed: an empirical forecast accuracy comparison of the two models, and a Monte Carlo study. The latter allows us to control for factors that may otherwise undermine the performance of the non-linear models.
Download or read book Forecasting principles and practice written by Rob J Hyndman and published by OTexts. This book was released on 2018-05-08 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
Download or read book Sales Forecasting A Practical Proven Guide to Strategic Sales Forecasting written by Gerard Assey and published by Gerard Assey. This book was released on 2024-01-08 with total page 103 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Sales Forecasting: A Practical & Proven Guide to Strategic Sales Forecasting" navigates the intricate landscape of sales forecasting, providing a holistic understanding of its intricacies, contemporary significance, and practical applications. From the responsibilities of Sales Managers to the benefits of accurate predictions for strategic planning, resource allocation, and risk mitigation, this guide equips readers with the tools to excel in the dynamic world of business strategy. Real-life case studies, interactive exercises, and workshops bring theoretical concepts to life, fostering active engagement. With a focus on diverse methods, techniques, and addressing common challenges, the book serves as a comprehensive toolkit for refining forecasting strategies. The conclusion encourages continuous learning and adaptation, ensuring readers are poised to navigate the ever-evolving realm of sales forecasting with confidence and mastery.
