Introduction
The exploitation of novel data streams (for example from card payments) will allow rapid and real-time model estimates to be made available to stakeholders. As the quantity of
Explaining the science
This project will exploit the recent advances in the signature methodology using controlled differential equation models, which give a generic approach to efficient use of
Project aims
Challenge 1 focuses on specific economic applications. The challenge is to produce high-frequency near to real-time estimates of consumer spending and consumer income at
A related challenge is the production of high-frequency measures of inflation, in particular the CPI. Real-time spending data and large-scale data on the prices of goods are
Challenge 2 seeks to understand how disparate, irregularly sampled time series can be understood and exploited in an official statistics context. The project aims to build robust
Applications
By creating a signature model for Nowcasting, the project aims to provide new economic indicators to assist policy makers with:
- High-frequency near to real-time consumer income forecasts at very detailed geographic level.
- Improved high-frequency measures of CPI
- Analysis of impacts on spending of exogenous factors like COVID-19 lockdown policies, opening or closure of shops, new roads or rail links, or changes in tax structure