The Economic Shock Explorer allows the user to explore the economic resilience of 65 Austrian economic sectors. Resilience has several definitions, here it refers to the ability to quickly recover from shocks. The underlying model follows the method presented in Klimek 2019 with several adaptions similar to Santos 2009.

To simulate the recovery from a given demand-shock we use the sectoral interdependencies represented in a dynamic Input-Output model. The Input-Output model takes also the indirect effects of an economic shock into account and, hence, allows us to quantify its total effect on the economy. In principle an Input-Output economy tries to satisfy the public demand D by producing outputs Y. In order to produce these outputs intermediate inputs, specified by the matrix of technical coefficients A, are necessary. Deviations from the equilibrium are tried to compensate. The data used in this model are the Input-Output tables provided by Statistik Austria for the year 2016.

Use the Economic Shock Explorer as follows:
  • First compose the economic shock to apply. To do this change the preloaded settings by clicking on the green pencil or delete them using the red button.
  • There are several types of global and sector specific shocks available:
    • “Business slowdown” and “Kurzarbeit” represent the global shocks that are described in the scenario below.
    • The option “box” and “% box” offer the user the opportunity to specify a step-demand shock in terms of absolute (Mio. €) or relative (% of the sector output) terms, for certain time period.
    • The option “gaussian” allows to specify a shock shaped like a Gaussian with with the ability to control the shock size, time and duration (variance).
  • After defining the shock, the “Total Shock” panel displays the total shock applied to the economy, or, in other words, the sum of all sector shocks.
  • The panel below, called “Response”, displays the weekly reduction in output for each sector. Hover over the curve to see the sector name and the accumulated reduction in output over the first year. In the lower left corner, the output reduction of the Austrian economy over the first year is displayed.

The preloaded example shows the following realistic scenario. However, we invite the user to change assumptions and customize the economic prediction.

  • Reduction in business activity is observed by the sector-wise drop in employment since March 15
  • Reduction in business activity observed by the sector-wise rise in partial layoffs (Kurzarbeit) since March 15 (currently: estimate)
  • Tourism and events sector experience a reduction for almost 100%
  • Retail and air travel are reduced by 70% during the time of the restrictions.
  • Reduction in global trade of 2.5%.
  • Restrictions are expected to continue until end of May. This is a major source of uncertainity.
Klimek, P., Poledna, S., & Thurner, S. (2019). Quantifying economic resilience from input–output susceptibility to improve predictions of economic growth and recovery. Nature communications, 10(1), 1-9.
Santos, J. R., Orsi, M. J., & Bond, E. J. (2009). Pandemic recovery analysis using the dynamic inoperability input‐output model. Risk Analysis: An International Journal, 29(12), 1743-1758.

This project has been sponsored by the Oesterreichische Nationalbank (OeNB),
and has been partially funded by the Vienna Science and Technology Fund (WWTF) through project COV20-001.

Global shock [x: weeks, y: million €]
Sector specific shocks (the graphs show sector specific shocks only, without global shocks) [x: weeks, y: million €]
Add sector specific shock
Total Shock (global shock + sector specific shocks)
Sector to display
Overall output reduction
reduction over first year, compared to baseline scenario

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