Although multiregional input-output (MRIO) databases use data from national statistical offices, the reconciliation of various data sources results in significantly altered country data. This makes it problematic to use MRIO-based footprints for national policy-making. This paper develops a potential solution using the Netherlands as case study. The method ensures that the footprint is derived from an MRIO dataset (in our case the World Input-Output Database (WIOD)) that is made consistent with Dutch National accounts data. Furthermore, usage of microdata allows us to separate re-exports at the company level. The adjustment results in a foreign footprint in 2009 that is 22% lower than the original WIOD estimates and a significantly altered country allocation. We demonstrate that already in the data preparation phase due to the treatment of re-exports and margins, large differences arise with Dutch national statistics, which may help explain the variation in footprint estimates across MRIO databases.

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There is great uncertainty about the ratings. To show the magnitude of uncertainty, league tables should include the best-case scenario and the worst-case scenario ratings of each clinic.

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A defining characteristic of our modern economy is the fragmentation of production across national borders (Amador & Cabral, 2017;Baldwin, 2016). This fragmentation involves the cross-border flow of physical inputs and a range of professional business functions, such as design, engineering, sourcing, marketing and after-sales services of consumer products (Feenstra, 1998;Timmer et al., 2019). As production has been unbundled, firms have specialised in activities. 1 The best-known example is the iPhone. On the back of the iPhone, it reads designed by Apple in California, but assembled by Foxconn in Guangdong. Does specialisation in activities, such as in the design or assembly, relate to levels of economic development? Or, to narrow it down since value added per worker is closely associated with wages and living standards: Does functional specialisation relate to productivity?This paper proposes a straightforward yet novel approach to measure the specialisation of firms and provides an empirical test of the relation between firm productivity and functional specialisation.We measure the functional specialisation of firms using unique data from two survey rounds in 2012 and 2017, in which Dutch firms report on the composition of their employees by function. The surveys we use were administered by Statistics Netherlands and sent to private firms with at least 50 employees. Managers who complete such surveys indicate the allocation of their employees across business functions is a natural way for them to categorise their workers (Sturgeon & Gereffi, 2009).