The highly prized ability to make financial plans with some certainty about the future comes from the core fields of economics. In recent years the availability of more data, analytical tools of greater precision, and ex post studies of business decisions have increased demand for information about economic forecasting. Volumes 2A and 2B, which follows Nobel laureate Clive Granger's Volume 1 (2006), concentrate on two major subjects. Volume 2A covers innovations in methodologies, specifically macroforecasting and forecasting financial variables. Volume 2B investigates commercial applications, with sections on forecasters' objectives and methodologies. Experts provide surveys of a large range of literature scattered across applied and theoretical statistics journals as well as econometrics and empirical economics journals. The Handbook of Economic Forecasting Volumes 2A and 2B provide a unique compilation of chapters giving a coherent overview of forecasting theory and applications in one place and with up-to-date accounts of all major conceptual issues. - Focuses on innovation in economic forecasting via industry applications - Presents coherent summaries of subjects in economic forecasting that stretch from methodologies to applications - Makes details about economic forecasting accessible to scholars in fields outside economics

Role and application of forecasting in organizations; Introduction to management forecasting; Sales forecasting requirements; Forecasting requirements for operations planning and control; Capacity planning forecasting requirements; Financial forecasting; Forecasting and strategic planning; Forecasting in the electric utility industry; State and local government revenue forecasting; Population forecasting; Forecasting: the issues; Approaches to forecasting; Smoothing methods for short-term planning and control; A practical overview of arima models for time series forecasting; Decomposition methods for medium term planning annnd budgeting; Econometric methods for managerial applications; Judgemtal and bayesian forecasting; An integrated approach to medium andlong term forecasting: the marketing mix system; Forecasting challenges; Forecasting and the environment: the challenges of rapid change; Price forecasting using experience curves and the product life-cycle concept; Life cycle forecasting; Forecasting recessions; Forecasting macroeconomic variables: an eclectic approach; ; Managing the forecasting functions; Forecasting and planning: an evaluation; Integrating forecasting and decision making; The forecasting audit; The future of forecasting.

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.

Greater data availability has been coupled with developments in statistical theory and economic theory to allow more elaborate and complicated models to be entertained. These include factor models, DSGE models, restricted vector autoregressions, and non-linear models.

This handbook summarises knowledge from experts and empirical studies. It provides guidelines that can be applied in fields such as economics, sociology, and psychology. Includes a comprehensive forecasting dictionary.

Research on forecasting methods has made important progress over recent years and these developments are brought together in the Handbook of Economic Forecasting. The handbook covers developments in how forecasts are constructed based on multivariate time-series models, dynamic factor models, nonlinear models and combination methods. The handbook also includes chapters on forecast evaluation, including evaluation of point forecasts and probability forecasts and contains chapters on survey forecasts and volatility forecasts. Areas of applications of forecasts covered in the handbook include economics, finance and marketing.*Addresses economic forecasting methodology, forecasting models, forecasting with different data structures, and the applications of forecasting methods *Insights within this volume can be applied to economics, finance and marketing disciplines

A comprehensive and integrated approach to economic forecasting problems Economic forecasting involves choosing simple yet robust models to best approximate highly complex and evolving data-generating processes. This poses unique challenges for researchers in a host of practical forecasting situations, from forecasting budget deficits and assessing financial risk to predicting inflation and stock market returns. Economic Forecasting presents a comprehensive, unified approach to assessing the costs and benefits of different methods currently available to forecasters. This text approaches forecasting problems from the perspective of decision theory and estimation, and demonstrates the profound implications of this approach for how we understand variable selection, estimation, and combination methods for forecasting models, and how we evaluate the resulting forecasts. Both Bayesian and non-Bayesian methods are covered in depth, as are a range of cutting-edge techniques for producing point, interval, and density forecasts. The book features detailed presentations and empirical examples of a range of forecasting methods and shows how to generate forecasts in the presence of large-dimensional sets of predictor variables. The authors pay special attention to how estimation error, model uncertainty, and model instability affect forecasting performance. Presents a comprehensive and integrated approach to assessing the strengths and weaknesses of different forecasting methods Approaches forecasting from a decision theoretic and estimation perspective Covers Bayesian modeling, including methods for generating density forecasts Discusses model selection methods as well as forecast combinations Covers a large range of nonlinear prediction models, including regime switching models, threshold autoregressions, and models with time-varying volatility Features numerous empirical examples Examines the latest advances in forecast evaluation Essential for practitioners and students alike

Ready-to-use forecasting and modeling tools to read the future under any given set of assumptions. Manipulate variables such as revenues, expenses, cash flow and earnings while improving the quality of decision-making and reduces risk of error.

Sharp, in-depth and highly visual, this is the fully revised textbook and teaching aid for students, tutors and in-house learning and development teams keen to know more about the world of trends, forecasting, innovation thinking and strategic foresight. Designed and written as a practical ‘how to’ guide for design, marketing, brand and innovation studies students, updated chapters include the latest research and industry case studies on superforecasting, three horizon scanning, scenario planning, foresight framework building and the creation and running of your own trend and innovation sprints. Students also have a chance to mix and merge the worlds of forecasting with future studies as we look at how techniques and processes such as the Delphi Method, cross-impact analysis, futures wheels and backcasting are being used by next generation forecasters to expand the ways they map, assess and define the needs and behaviours of tomorrow’s consumers.