# **2. Preliminary Estimates Based on Official Trade Data**

**Based on a number of sources (press, reports, and interviews with customs officials), it is possible to pinpoint several categories of goods (including petroleum products, cigarettes, food products, textiles, alcoholic beverages and electronic goods) that are most likely to be traded informally in significant quantities.** These products are known to benefit from major subsidies in Algeria or Libya (petroleum products and food products) or to be subject to substantial customs tariffs when imported into Libya (textiles, electronic goods). Annex 1 lists the categories of goods concerned according to their official category code under the Standard International Trade Classification (SITC), Revision 3.<sup>12</sup>

**The following analysis is based on the work of Fisman and Wei (2009), Jean and Mitaritonna (2010), Berger and Nitsch (2012), Kaminski and Mitra (2012), and Raballand et al. (2013) on evaluating the level of informal trade by using official trade data.**<sup>13</sup> These studies propose using the gap between the levels of trade in the same product reported by importing and exporting countries in order to make an initial evaluation of informal trade levels (this is known as an approach based on mirror statistics). In principle, there is a minimum gap between reported values on each side of a border because exports are calculated in terms of FOB (free on board), i.e., excluding transport and insurance costs, while imports are calculated in terms of CIF (cost, insurance, freight), i.e., including transport and insurance costs. This trade gap may grow as a result of classification errors or exchange rates.<sup>14</sup> Nonetheless, Bhagwati (1967) suggested that when the disparity was more than 30% of the value of the imported product, these traditional explanations are no longer sufficient because beyond that threshold, the most likely reason for this gap is an under- or over-evaluation of imports or exports.

The gap is calculated in the following manner for any given year and for any given pair of countries: where _K_ corresponds to any category of goods as defined at the group level by the STIC, Revision 3.

**The initial analysis of trade date between Tunisia and Libya currently available at the international level reveals that very little published data recorded by the Libyan authorities are available.**<sup>15</sup> Furthermore, trade flows are recorded for only a small number of products (45) compared to Tunisia (274 over the four years concerned). While the Tunisian authorities identified on average 80 different types of goods entering the market from Libya, the Libyan authorities recorded the exports of only a dozen different types of goods over the same period. While the average annual value of the trade flows recorded by the Tunisian authorities is US$508m, for the Libyan authorities, it is just US$204m. Most of the published data concern trade in hydrocarbons (petroleum and gas), which account for

> 12 This classification is preferred over the harmonized system as no data are available for Libya in the United Nations Commodity Trade Statistics Database (UN Comtrade).

> 13 This is a well-established approach that dates from the late 1960s following the work of Bhagwati (1967) and that is currently enjoying something of a revival as a result of new research into customs fraud.

> 14 For a wider discussion of the various explanations, see Raballand et al. (2013).

> 15  Data were provided for the period 2007 to 2010 only in COMTRADE.

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