Global Trade in Fakes

Chapter 2. Updating the picture

Data

Following the approach taken in the (OCDE, 2008[9])) report and the (OECD/EUIPO, 2016[1]) and (OECD/EUIPO, 2019[3]) reports, the analysis in this report is based on international trade statistics and customs seizures of infringing products.

Trade data

The trade statistics are based on the United Nations (UN) Comtrade database (based on the value of merchandise assigned by customs officials, i.e. the landed customs value). With 171 reporting economies and 247 partner economies, the database covers the majority of world trade and is considered the most comprehensive trade database available. Products are registered based on the six-digit Harmonised System (HS) (an international commodity classification system, developed and maintained by the World Customs Organization [WCO]), meaning that the level of detail is high. Data used in this study are based on landed customs value. In most instances, this is the same as the transaction value appearing on accompanying invoices. Landed customs value includes the insurance and freight charges incurred when transporting goods from the economy of origin to the economy of importation.

Seizure data

Data on customs seizures originate from national customs administrations. This report relies on customs seizure data from the WCO, the European Commission’s Directorate-General for Taxation and Customs Union (DG TAXUD) and from the United States Department of Homeland Security (DHS). The latter submitted seizure data from US Customs and Border Protection (CBP), the American customs agency, and from the US Immigration and Customs Enforcement (ICE).

In each year analysed (2017, 2018 and 2019), the total number of customs seizures of counterfeit and pirated goods worldwide consistently exceeded 130 000. Overall, the unified database on customs seizures of IP-infringing goods includes almost 465 000 observations, as compared to the 428 000 recorded from 2011-13 (OECD/EUIPO, 2016[1]).

A detailed analysis of these data revealed a set of limitations. Some of them are to do with discrepancies between the datasets, others product classification levels or outliers in terms of seized goods or provenance economies. All limitations were thoroughly discussed in the (OECD/EUIPO, 2016[1]) and (OECD/EUIPO, 2019[3]) reports, and a methodological way forward was proposed for each limitation. This report also relies on the same methodology presented and discussed in the 2016 study, and it employs the same solutions to the seizure-data limitations.

Methodological and statistical aspects: The GTRIC methodology

The GTRIC (General Trade-Related Index of Counterfeiting) methodology employed in this report draws on the one used in the (OECD/EUIPO, 2016[1]) study. This methodology in turn was based on the one used in the (OCDE, 2008[9]). A brief overview of these key components is presented below, and more details can be found in the (OECD/EUIPO, 2016[1]) report. Detailed, technical and methodological notes can be found in Annex A at the end of this report

Industry analysis (GTRIC-p)

The GTRIC-p (General Trade-Related Index of Counterfeiting for products) index represents the relative likelihood for products in one category to be counterfeit in comparison with another. It is done based on a customs data system that includes the 96 two-digit product modules included in the HS. In particular, if any of the reporting customs authorities registered a fake good in a given HS category, the whole category is treated as sensitive. Of course, within any category there may be considerable variation among products. The GTRIC-p index must therefore be seen as averages for the hundreds of goods covered by each HS chapter.

The GTRIC-p is compiled in two steps. In the first step, the seizure intensities in each product category are weighted by the respective share in total imports of these products of each reporting economy. This reflects the sensitivity of product infringements occurring in a particular product category relative to the intensity of imports of the products for each reporting economy. In the second step, these indices are transformed statistically to account for a number of known biases related to seizure techniques and propensities for which products in international trade are counterfeited and/or pirated.

Provenance economies (GTRIC-e)

The GTRIC-e (General Trade-Related Index of Counterfeiting for economies) index represents the relative likelihood for a given provenance economy to export fakes in comparison with other economies.

A provenance economy refers to where the production of infringing goods takes place, as well as economies that function as ports of transit through which infringing goods pass prior to reaching the economy of destination.

As with the GTRIC-p, the propensity for a given provenance economy is obtained by relating the weighted average of its seizure percentages to the respective share of total imports. The GTRIC-e is then determined along the same lines as the GTRIC-p and indicates the relative propensity of importing infringing goods from different provenance economies.

The trade in counterfeits as a whole

The GTRIC assigns the relative likelihood of there being counterfeit products in each product category and from each provenance economy.

The GTRIC index itself can be represented as a matrix table in which provenance economies are listed across the rows and in which the two-digit HS modules are listed in columns. Each element of the matrix, i.e. the value of GTRIC, denotes the relative propensity of a given provenance economy to export infringing products covered by a given HS module. These propensities can only be interpreted relative to each other; the GTRIC itself does not provide any information about the absolute magnitude of counterfeiting and piracy in world trade. Instead, the index should be considered as a tool to aid better appraisal of the problem of counterfeit and pirated trade. To go one step further and calculate the absolute value of counterfeit and pirated products in international trade, it is important to identify at least one probability of there being counterfeit and pirated products in a given product category from at least one provenance economy. This is established through structured interviews with industry experts and enforcement officials.

References

[9] OCDE (2008), The Economic Impact of Counterfeiting and Piracy, Éditions OCDE, Paris, https://doi.org/10.1787/9789264045521-en.

[8] OCDE/EUIPO (2021), Misuse of Containerized Maritime Shipping in the Global Trade of Counterfeits, Éditions OCDE, Paris,, https://doi.org/10.1787/e39d8939-en.

[12] OECD (2021), COVID-19 vaccine and the Threat of Illicit Trade, Chair’s Summary Note, https://www.oecd.org/gov/illicit-trade/summary-note-covid-19-vaccine-and-the-threat-of-illicit-trade.pdf.

[10] OECD (2020), Illicit Trade in a Time of Crisis. Chair’s Summary Note, https://www.oecd.org/gov/illicit-trade/oecd-webinar-illicit-trade-time-crisis-23-april.pdf.

[14] OECD (2020), Trade in Fake Medicines at the Time of the Covid-19 Pandemics. Chair’s Summary Note, https://www.oecd.org/gov/illicit-trade/oecd-fake-medicines-webinar-june-10-summary-note.pdf.

[13] OECD (2018), Governance Frameworks to Counter Illicit Trade, OECD Publishing, Paris,, https://doi.org/10.1787/9789264291652-en.

[7] OECD/EUIPO (2020), Trade in Counterfeit Pharmaceutical Products, Illicit Trade, OECD Publishing, Paris, https://dx.doi.org/10.1787/a7c7e054-en.

[3] OECD/EUIPO (2019), Trends in Trade in Counterfeit and Pirated Goods, OECD Publishing, Paris,, https://doi.org/10.1787/g2g9f533-en.

[6] OECD/EUIPO (2018), Misuse of Small Parcels for Trade in Counterfeit Goods: Facts and Trends, OECD Publishing, Paris, https://doi.org/10.1787/9789264307858-en.

[4] OECD/EUIPO (2018), Trade in Counterfeit Goods and Free Trade Zones: Evidence from Recent Trends, OECD Publishing, Paris/EUIPO, Alicante, https://doi.org/10.1787/9789264289550-en.

[5] OECD/EUIPO (2018), Why Do Countries Export Fakes?: The Role of Governance Frameworks, Enforcement and Socio-economic Factors, OECD Publishing, Paris/EUIPO, Alicante, https://doi.org/10.1787/9789264302464-en.

[2] OECD/EUIPO (2017), Mapping the Real Routes of Trade in Fake Goods, Illicit Trade, OECD Publishing, Paris, https://doi.org/10.1787/9789264278349-en.

[1] OECD/EUIPO (2016), Trade in Counterfeit and Pirated Goods: Mapping the Economic Impact, Illicit Trade, OECD Publishing, Paris, https://doi.org/10.1787/9789264252653-en.

[11] UNICRI (2020), “Cyber-crime during the COVID-19 Pandemic”, http://www.unicri.it/news/cyber-crime-during-covid-19-pandemic.