Forecasts play a central role in decision-making under uncertainty. After a brief review of the general issues, this article considers ways of using high-dimensional data in forecasting. We consider selecting variables from a known active set, known knowns, using Lasso and One Covariate at a time Multiple Testing, and approximating unobserved latent factors, known unknowns, by various means. This combines both sparse and dense approaches to forecasting. We demonstrate the various issues involved in variable selection in a high-dimensional setting with an application to forecasting UK inflation at different horizons over the period 2020q1–2023q1. This application shows both the power of parsimonious models and the importance of allowing for global variables.

Several decades ago, Sig Prais concluded that the root cause of the UK’s poor industrial performance was the poor quality of education and training. In this lecture, I will make a related argument, focussing on the lack of opportunity in the United Kingdom for workers who have not succeeded in the formal education system and the long-lasting impacts this has on their economic, health and social wellbeing. I will highlight the importance of providing opportunities for continued training over a worker’s lifetime for appropriate skills that are valued in the workplace in order to achieve inclusive growth.

This analysis aims at providing an interim assessment of the ECB’s current policy rate tightening cycle. Our analysis suggests that the ECB’s monetary policy measures are tightening financial conditions and reducing credit volumes in the euro area reducing credit volumes. In view of the lags from financing conditions to the real economy, the impact of the policy tightening cycle on inflation can currently be observed only to a limited extent. The scale of the policy tightening required to return inflation to the two percent target over the medium term will need to be regularly reviewed, in view of the uncertainty about the transmission mechanism and in line with the incoming evidence concerning underlying inflation dynamics.

The New Model Institute for Technology and Engineering (NMITE) reflects a systematic attempt to rethink what a higher education (HE) institution should look like, based on the best globally competitive models. NMITE has been designed as a model for a small, new, distinctive, open, academically rigorous, skills-based local university. Many cities or large towns across the UK have low economic growth and low value-added per capita, and little or no access to HE. Addressing this gap in attainment successfully would be both equitable and highly economically and culturally advantageous. It would be a major contribution to local people, local communities and to raising regional and national productivity.