tables which are typically derived from the underlying SUTs with additional assumptions. Moreover, SUTs can be easily combined with trade statistics that are product-based and employment statistics that are industry-based. It also allows one to take into account the multi-product nature of many firms and their so-called secondary production. In a supply table the output of firms are classified on a product basis such that it might be recorded in different product classes. However, there is no information on the possible differences in the production processes of the various products within a firm, or across firms in the same industry. A column for a particular industry in the Use table only provides the average production structure across all firms and all products in that industry. It has been found that these structures might be rather different for exporters and non-exporters (e.g. Koopman, Wang and Wei, 2012; Ottaviano et al., 2009) National supply and use tables have been collected from national statistical institutes and harmonized in terms of concepts and classifications. National tables are only available for particular benchmark years which are infrequent, unevenly spread over time and asynchronous across countries. Moreover, they are not designed for comparisons over time which becomes clear when comparing data from the SUTs with the national accounts statistics. While the latter are frequently revised and designed for inter-temporal comparisons, the former are not. To deal with both these issues simultaneously, a procedure was applied that imputes SUT coefficients subject to hard data constraints from the National Accounts Statistics (NAS). The unknown product shares of intermediate inputs, imports, exports and final expenditure are imputed using a constrained least square method akin to the well-known biproportional (RAS) updating method. The solution matches exactly the most recent NAS data on final expenditure categories (household and government consumption and investment), total exports and imports, and gross output and value added by detailed industry.

In a second stage the imports of products are broken down by country-industry origin and allocated to a use category. This type of information is not available in published input-output tables. Typically, researchers rely on the so-called import proportionality assumption, applying a product’s economy-wide import share for all use categories (as e.g. Johnson and Noguera, 2012). Various studies have found that this assumption can be rather misleading as import shares vary significantly across use category (Feenstra and Jensen, 2012, Winkler and Milberg, 2012). To improve upon this, bilateral trade statistics have been used in WIOD to derive import shares for three end-use categories. Bilateral import flows of all countries covered in WIOD from all partners in the world at the 6-digit product level of the Harmonized System (HS) were taken from the UN COMTRADE database. We used the detailed description for about 5,000 products in COMTRADE to refine the well-known BEC (“broad end-use categories”) codes which allocates to intermediate use, final consumption use, or investment use. Within each end-use category, the allocation was based on the proportionality assumption (as dictated by a lack of additional information). For intermediate use by industries, for example, we had to apply ratios between imported use and total use that were equal across industries, but differed from the corresponding ratio for consumption purposes. A similar procedure was used to split the imports table according to country of origin. Unlike under the standard proportionality assumption, country import shares differ across end-use categories (but not within these categories). To resolve the well-known 15