  Knowledge of the current state of economies, how they respond to COVID-19
mitigations and indicators, and what the future might hold for them is
important. We use recently-developed generalised network autoregressive (GNAR)
models, using trade-determined networks, to model and forecast the Purchasing
Managers' Indices for a number of countries. We use networks that link
countries where the links themselves, or their weights, are determined by the
degree of export trade between the countries. We extend these models to include
node-specific time series exogenous variables (GNARX models), using this to
incorporate COVID-19 mitigation stringency indices and COVID-19 death rates
into our analysis. The highly parsimonious GNAR models considerably outperform
vector autoregressive models in terms of mean-squared forecasting error and our
GNARX models themselves outperform GNAR ones. Further mixed frequency modelling
predicts the extent to which that the UK economy will be affected by harsher,
weaker or no interventions.
