The International Institute of Forecasters sponsors workshops, each of which focuses on a specific forecasting theme. The purpose of these workshops is to hold smaller, informal meetings where experts in a particular field of forecasting can discuss forecasting problems, research, and solutions. There is generally a nominal registration fee associated with attendance. Following the usual refereeing process, papers from the workshops can be included in a special issue of the International Journal of Forecasting. If you are interested in hosting a workshop, contact Aris Syntetos, IIF Director, or click here for workshop guidelines.

Forecasting for Social Good Workshop | Oxford, England | July 10, 2022

While there is a growing recognition by agencies, organizations, and governments that data-driven decision-making tools, like forecasting models, can offer significant improvements to the societies they are working to improve, there is not a cohesive body of research that offers guidance on how to best implement, understand, use, and evaluate forecasting methods for societal impact in practice. The goal of this workshop is to improve the research and practice in issues related to forecasting for social good by: facilitating interactions between practitioners, researchers, and policy makers to develop a cohesive and sustainable network of international collaborations with a focus on issues related to forecasting for social good; promoting the development of new methodology and metrics to address the specific challenges related to forecasting for social good; providing professional development to policy makers; gaining a better understanding of the available data, challenges in data acquisition, and the uncertainty present in the data used to produce forecasts; and, addressing the ethical issues related to the use of forecasting methods for problems that impact society.

Buket Cilali, University of Oklahama
Ahmed Aziz​ Ezzat​, Rutgers, The State University of New Jersey
Michael Porter, University of Virginia
Bahman Rostami-Tabar Cardiff University

Feature-based Time Series Forecasting | Ordos City, China | schedule to be announced

Feature-based forecasting aims to use meta-learning to produce more accurate forecasts based on time series features. As early as the 1970s, Adam (1973) argued that the statistical characteristics of time series can be used to improve forecasting performances. Later literature supported this argument. Recently, related feature-based algorithms have been developed with great success, while some key issues remain to be tackled including automatic feature extraction and selection, feature-based density forecasting, forecasting related time series with features, time series generation based on features, and minimum forecast model pools for forecast model averaging. The proposed workshop aims to bring people together with diverse expertise and facilitate new research collaborations.

For more information: workshop webpage or Prof. Yanfei Kang

Democratising Forecasting

This is a series of ongoing workshops on forecasting using R in developing countries. The aim of the project is to ‘train the trainers’ in the form of university students, academics and professionals on the principles of forecasting using R software to support decision making. The ultimate goal of this project is to train 400 individuals, over 5 years in 20 developing countries in the world. The first series of workshops have already been offered in 2017-18. To date, the workshops have been offered in Tunisia, Iraq, Senegal, Nigeria, Uganda, Turkey, Georgia, and Indonesia

The workshops are given by Dr. Bahman Rostami-Tabar, Assistant Professor in Management Science at Cardiff Business School. To organise a workshop in your country, contact [email protected]

Past Workshops Revisiting and Improving Prediction Tools for Central Banks

2022 Virtual Revisiting and Improving Prediction Tools for Central Banks
2021 Paris, France New Directions for Inflation Forecasting
2021 Madrid, Spain Forecasting in a changing environment
2021 Nigeria Economic and Social Good Forecasting During Covid-19: Data Analytics & Forecasting Methods
2021 Virtual Forecasting for Social Good
2020 Virtual Economic Forecasting in Times of Covid-19
2019 Cambridge, England Predictive Analytics: Theory, Applications and Algorithms
2018 Cardiff, Wales Forecasting for Social Good
2017 Munich, Germany Predictive Analytics and Forecasting Research and Applications
2017 Cairns, Australia Predictive Energy Analytics in the Big Data World
2017 Washington DC, USA Forecasting Issues in Developing Economies
2017 New York, USA Forecasting with Massive Data in Real Time
2016 Lancaster, UK Supply Chain Forecasting for Operations
2016 Milan, Italy Forecasting New Products and Services
2015 Paris, France Advances in Time Series and Forecasting
2015 Santander, Spain Summer Forecasting Course
2015 Hong Kong Tourism Forecasting
2015 Paris, France ICT and Innovation Forecasting
2014 Bournemouth, UK Singular Spectrum Analysis
2014 London, United Kingdom Theory and Practice in ICT Forecasting
2014 Frankfurt, Germany Using big data for forecasting and statistics
2013 Melbourne, Australia Multivariate Time Series Modelling and Forecasting
2012 San Francisco, USA Predicting Rare Events: Evaluating Systemic and Idiosyncratic Risk
2011 Paris, France Forecasting the Business Cycle
2011 Verbier, Switzerland Flash Indicators
2009 Washington, DC Transportation Forecasters: Tools, Techniques and Information to Improve your Forecasts
2009 Lisbon, Portugal Predictability of Financial Markets
2007 Rio de Janiero, Brazil Risk, Volatility, and Forecasting in Energy and Financial Markets
2006 Leipzig, Germany Future of Forecasting
2005 Salamanca, Spain Stochastic Demographic Forecasting
2003 Madrid, Spain Nonlinearities, Business Cycles and Forecasting