Validating a dynamic input-output model for the propagation of supply and demand shocks during the COVID-19 pandemic in Belgium

25 May 2023  ·  Tijs W. Alleman, Koen Schoors, Jan M. Baetens ·

This work validates a dynamic production network model, used to quantify the impact of economic shocks caused by COVID-19 in the UK, using data for Belgium. Because the model was published early during the 2020 COVID-19 pandemic, it relied on several assumptions regarding the magnitude of the observed economic shocks, for which more accurate data have become available in the meantime. We refined the propagated shocks to align with observed data collected during the pandemic and calibrated some less well-informed parameters using 115 economic time series. The refined model effectively captures the evolution of GDP, revenue, and employment during the COVID-19 pandemic in Belgium at both individual economic activity and aggregate levels. However, the reduction in business-to-business demand is overestimated, revealing structural shortcomings in accounting for businesses' motivations to sustain trade despite the pandemic's induced shocks. We confirm that the relaxation of the stringent Leontief production function by a survey on the criticality of inputs significantly improved the model's accuracy. However, despite a large dataset, distinguishing between varying degrees of relaxation proved challenging. Overall, this work demonstrates the model's validity in assessing the impact of economic shocks caused by an epidemic in Belgium.

PDF Abstract
No code implementations yet. Submit your code now

Datasets


  Add Datasets introduced or used in this paper

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods