About the project
Economic models used for forecasting and to aid policy decisions have been estimated by the use of data from before the Covid-19 pandemic and the ensuing lockdowns, drop in economic activity and surge in unemployment. An important question for model developers and users is therefore how the empirical relationships that represented normal behavior of firms and households before Covid-19 have been affected by the pandemic and by the policy responses.
The aim of the project is to close this knowledge gap. Another goal is to contribute to the development of methods that may mitigate the consequences of such effects for model based forecasting and for policy analysis during future pandemics and other disruptions to the economy. This will include development of methods for early detection of breaks in relationships, which may cut down the time-delay before the implications for policy can be analyzed. This may be of importance for economic performance during a future crisis.
The project includes an extended investigation of earlier crises, namely the financial crisis of 2008/09 and the crisis brought about by fall in oil prices in 2015/16. These crises have originated in different parts of the economy and the policy response have been different.
Improved knowledge of the robustness of model relationships with respect to different crises can increase the usefulness of models during future crises. The policy responses during a pandemic are motivated by health issues, but will have consequences for the economy in whole. In this project, the joint forecasting of public health and economics system will be explored which is major R&D challenge in this field.
The Covid-19 crisis has affected all national economies. The project will therefore include comparative analyses of the crisis. The goal is to investigate empirically whether institutional differences and different policy responses have affected the economic performance during and after the crisis.
Work packages
Work Package 1. Model invariance and robustness with respect to Covid-19 and the earlier crises of the 2000s in the Norwegian economy.
Work Package 2. Improving on raw model-based forecasts and the role of robust forecasting methods.
Work Package 3. Joint forecasting of health and the economy
Work Package 4. Comparative analysis of Covid-19 and policy measures using dynamic panel data models of OECD countries
Work Package 5. Comparative analysis of policy response and structural breaks during Covid-19 using country specific econometric models
Objectives
The primary aim is to close the knowledge gap about how the relationships of macroeconometric models that represent normal behaviour of firms and households have been affected by the pandemic and by the policy responses. Equally important is to contribute to the development of methods that may mitigate the consequences of such effects for model based forecasting and for policy analysis during future pandemics and other sudden disruptions to the economy.
A secondary aim of the project is to renew and increase the intellectual capacity in Norway in the field of empirical macroeconometric modelling. To contribute to the development of knowledge and skills of both model producers and of model users, in ways that may maintain and increase model relevance, and further the use of empirical macroeconometric models to aid policy judgement and decisions. Furthermore to improve the transparency of communication between policy makers and the general public in the field of macroeconomics.
