No abstract

No abstract

Abstract. Coronal mass ejections (CMEs) strong enough to create electromagnetic effects at latitudes below the auroral oval are frequent events that could soon have substantial impacts on electrical grids. Modern society's heavy reliance on these domestic and international networks increases our susceptibility to such a severe space-weather event. Using a new high-resolution model of the global economy, we simulate the economic impact of strong CMEs for three different planetary orientations. We account for the economic impacts within the countries directly affected, as well as the post-disaster economic shock in partner economies linked by international trade. For a 1989 Quebec-like event, the global economic impacts would range from USD 2.4 to 3.4 trillion over a year. Of this total economic shock, about 50 % would be felt in countries outside the zone of direct impact, leading to a loss in global Gross Domestic Product (GDP) of 3.9 to 5.6 %. The global economic damage is of the same order as wars, extreme financial crisis and estimated for future climate change.

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

In this paper, a new method is presented to derive an input-output table from a system of make and use tables. The method, which we call 'activity technology', is mathematically equivalent to the well-known commodity technology, but chooses another unit, i.e. the activity. We will argue that, in the activity technology model, negatives can only arise from causes such as heterogeneity and errors in the data. To apply the activity technology, very detailed make and use matrices are required, as well as additional data on the input structures of certain activities. We will describe a method that can incorporate this additional data within the activity technology framework. Statistics Netherlands has adopted the method