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E. Examples of the merging of data from enterprise surveys with customs data

 7.17.        Uganda: Informal Cross Border Trade Survey. The Uganda Bureau of Statistics conducts an Informal Cross Border Trade Survey on a monthly basis (see chap IV, box IV.1 for details). The data are collected by trained enumerators under the supervision of the informal cross border trade technical team at various border crossings around the country. The following data elements are captured: customs station, item/commodity name, quantity, price, unit of measure, country of origin/destination, mode of transport, date and day of the week. After processing the data, the information is assigned to international and national codes for commodity, country, mode of transport and border post among others. The Trade Survey data structure is aligned to the customs structure before merging is carried out.

7.18.        Challenges in commodity classification. InUganda, a number of challenges are encountered when transforming (coding) the cross-border data for incorporation into the HS. Most of the commodity names cannot be easily traced in the HS system, thus making the classification of commodities difficult. Moreover, various units of measure are assigned to the same commodity, which requires harmonization before integration with data from other sources.

7.19.        Turkey: Survey for the shuttle trade. The Statistics Institute of Turkey conducts a quarterly survey for the shuttle trade at specific border crossings. As shown in figure IV.1, the following data elements are captured: country of residency, country of citizenship, nights of stay inTurkey, type of goods and value of those goods, type of payment, cost of packaging, loading and shipping, countries of exports, and cost of private spending inTurkey. These data items are combined with the customs records (see chap. IV, Box IV.2 for details)

7.20.        Further examples. Chapters III and IV contain additional examples of the use of non-customs data sources.