• Statistical short-term forecasting of the Covid-19 pandemic has been published in the Journal of Clinical Immunology & Immunotherapy.

• Short-term forecasting of the coronavirus pandemic is now In Press at the International Journal of Forecasting.

• A short video on a green recovery from the coronavirus pandemic that links to our Economics Observatory article is available here.

• Modelling non-stationary 'Big Data' is available online at the International Journal of Forecasting.

• Can the UK achieve net-zero emissions in a post-Covid-19 economic recovery? has appeared on the Economics Observatory.

• I participated in the RES Webinar on ''Forecasting: What is a scenario, projection and a forecast - how good or useful are they particularly now?'', on 16th July 2020, available to view here.

• Can we get accurate short-term forecasts of coronavirus cases and deaths? has appeared on the Economics Observatory

• Jurgen Doornik has added forecasts of cumulative confirmed cases for lower tier local authorities of England (with more than 5 cases in the previous week).

• The São Paulo School of Economics (FGV EESP), in partnership with the School of Applied Mathematics (FGV EMAp) and the University of Oxford, host the webinar Forecasting Covid-19 from an econometric and epidemiologist perspectives, featuring Jurgen Doornik and David Hendry.

• Jurgen Doornik, David Hendry and I have been producing short term forecasts of Covid-19 confirmed cases and deaths, regularly updated, since 20 March 2020 for many countries and US States, published at www.doornik.com/COVID-19/. The working paper for the short term forecasts is available here. The paper for the medium term forecasts is still preliminary and is available here.

• Why short-term forecasts can be better than models for predicting how pandemics evolve with Jurgen A Doornik and David F. Hendry, The Conversation, 30 June 2020.

• Decarbonising the future UK economy with David F. Hendry, VoxEU, 4 June 2020.

• Short-term Forecasting of the Coronavirus Pandemic with Jurgen A Doornik and David F. Hendry, International Institute of Forecasters Blog, 30 April 2020.

• Short-term Forecasting of the Coronavirus Pandemic with Jurgen A Doornik and David F. Hendry, VoxEU, 24 April 2020.

• Even murky glasses are better than a blindfold with Jurgen A Doornik and David F. Hendry, lead letter to the Financial Times, 11 April 2020.

• The Paradox of Stagnant Real Wages yet Rising `Living Standards' in the UK with David F. Hendry and Andrew B. Martinez, VoxEU, 21 January 2020.




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Making accurate predictions about the economy has always been difficult, as F. A. Hayek noted when accepting his Nobel Prize in economics, but today forecasters have to contend with increasing complexity and unpredictable feedback loops. In this accessible and engaging guide, David Hendry, Michael Clements, and Jennifer Castle provide a concise and highly intuitive overview of the process and problems of forecasting. They explain forecasting concepts including how to evaluate forecasts, how to respond to forecast failures, and the challenges of forecasting accurately in a rapidly changing world. Topics covered include: What is a forecast? How are forecasts judged? And how can forecast failure be avoided? Concepts are illustrated using real-world examples including financial crises, the uncertainty of Brexit, and the Federal Reserve’s record on forecasting. This is an ideal introduction for university students studying forecasting, practitioners new to the field and for general readers interested in how economists forecast. The book is available from Yale University Press. See Climate Econometrics for a blog about the book and The Enlightened Economist for a review.




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The evolution of life on Earth - a tale of both slow and abrupt changes over time - emphasizes that change is pervasive and ever present. Change affects all disciplines using observational data, especially time series of observations. When the dates of events matter, so data are not ahistorical, they are called non-stationarity denoting that some key properties like their means and variances change over time. There are several sources of non-stationarity and they have different implications for modelling and forecasting. This open access book focuses on the concepts, tools and techniques needed to successfully model ever-changing time-series data. It emphasizes the need for general models to account for the complexities of the modern world and how these can be applied to a range of issues facing Earth, from modelling volcanic eruptions, carbon dioxide emissions and global temperatures, to modelling unemployment rates, wage inflation and population growth. The book is open access and is available from Palgrave Macmillan.




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A recent working paper with Takamitsu Kurita is available here. A dynamic econometric analysis of the dollar-pound exchange rate in an era of structural breaks and policy regime shifts We employ a newly-developed partial cointegration system allowing for level shifts to examine whether economic fundamentals form the long-run determinants of the dollar-pound exchange rate over a recent period chracterised by structural breaks and policy regime shifts. The paper uncovers a class of local data generation mechanisms underlying long-run and short-run dynamic features of the exchange rate using a set of economic variables that explicitly re ect quantitative monetary policy and the infl uence of a forward exchange market. The impact of the Brexit referendum is evaluated by examining forecasts when the dollar-pound exchange rate fell substantially around the vote. The accompanying online appendix is available here.




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