used to match the two datasets, this is referred to throughout the paper as the Firms’ Name Method (henceforth, FN). In addition, we take the names of the PEPs and then search to see whether they are shareholders or owners of firms, as listed in the _Orbis_ dataset for each country. Because of common names and other possible sources of error, each possible match was subsequently reviewed manually to ensure the integrity of the match.<sup>4</sup> A substantial number of matches were discarded as false positives and a revised set of matches adopted.<sup>5</sup> As names of people are used to match the two datasets, this is henceforth referred to as the PEPs’ Name Method (PN). Matches from both methods are then used to build the final dataset that contains the total known connections between PEPs and entities.

Table 1 provides some basic descriptive statistics including the number of PEPs identified under each method for each country. Using the FN Method gives a significant amount of variation in the number of companies associated with PEPs. For example, in Bulgaria, Hungary and Serbia only 46-88 firms are identified by this method, as against between 631800 in Russia and Romania respectively. The number increases significantly when including the PEP’s Name Method (PN). For the consolidated measure (FN+PN), the total number ranges between 384 in Serbia and 4,568 in Russia.<sup>6</sup> Using the assets of PEP-connected companies to get an approximation of the aggregate scale of connected companies, Table 1 shows that they account for around 0.8 percent of GDP in Bulgaria and Hungary, between 2.5-5 percent in the Slovak Republic, Serbia and Romania and _>_ 15 percent in Russia in 2013. The massive share for Spain relative to the other countries is due to the fact that in the latter SOEs play a more significant role. In Spain, by contrast, some massive private firms are connected, swelling the share.<sup>7</sup> Concerning the properties of connected firms depending on the method of identification, applying the size criteria (incorporating revenues, assets and employment) indicated in Appendix Table B1, it appears that the share of small firms among connected firms is far higher when applying the PN Method; 77 percent as against 40 percent for the FN Method. Correspondingly, the share of large and extra-large firms comprises 30 percent for FN identification but only 6 percent when using the PN approach (see Appendix Table B2). This disparity is true for all countries, bar Bulgaria. In addition, regarding the size distribution, – Spain looks different as between 27-52 percent of connected firms are large or very large a

> 4Researchers based in each country and with extensive local knowledge checked each match using a range of complementary sources and documentation. Only verified matches were maintained and false positives and ambiguous matches were discarded.

> 5We explored alternative approaches, such as stochastic matching through location used by Koren et al. (2015), but found that data gaps were too large.

> 6Note that for Russia, when using the FN Method a very large number of firms appeared, attributable to duplication of common firm names (e.g., Sputnik). To avoid this, we use only those firms with a unique name. For the PN Method, each entry was carefully cross-checked to ensure no duplication.

> 7For example, the total assets of just three connected companies amount to over 20% of GDP.

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