big data

Can machine learning catch the COVID-19 recession?

Based on evidence gathered from a newly built large macroeconomic dataset (MD) for the UK, labelled UK-MD and comparable to similar datasets for the United States and Canada, it seems the most promising avenue for forecasting during the pandemic is to allow for general forms of nonlinearity by using machine learning (ML) methods. But not all nonlinear ML methods are alike. For instance, some do not allow to extrapolate (like regular trees and forests) and some do (when complemented with linear dynamic components).

Exploring the link between economic complexity and emergent economic activities

Recent studies have shown a strong link between the complexity of economies and their economic development. There remain gaps in our understanding of the mechanisms underpinning these links, in part because they are difficult to analyse with highly aggregated, official data sources that do not capture the emergence of new industrial activities, a potential benefit from complexity.

Mapping Information Economy Business with Big Data: Findings from the UK

Governments around the world want to develop their ICT and digital industries. Policymakers thus need a clear sense of the size and characteristics of digital businesses, but this is hard to do with conventional datasets and industry codes. This paper uses innovative ‘big data’ resources to perform an alternative analysis at company level, focusing on ICT-producing firms in the UK (which the UK government refers to as the ‘information economy’).

Exploring the digital economy with big data

NIESR's just published some new analysis of the UK’s digital economy, written by me and Anna Rosso with Growth Intelligence, and funded by Google. This is the first phase of a research programme with roots in the resurgence of industrial policy around the world ...