Building capacity to help Africa trade better

Capacity building at tralac – Geek Week, 9-13 September 2013


Capacity building at tralac – Geek Week, 9-13 September 2013

Capacity building at tralac – Geek Week, 9-13 September 2013

As an essential part of tralac’s capacity building mandate in Southern Africa, we conducted the annual trade data accessing, collation and interpretation training exercise (colloquially known as ‘Geek Week’) at Stellenbosch from Monday 9th to Friday 13th of September 2013. Participants came from the Western Cape Department of Agriculture at Elsenburg, Department of Agriculture, Fisheries and Forestry at Pretoria, National Agricultural Marketing Council, and South African Revenue Services (SARS). The workshop was conducted by Ron Sandrey and Willemien Viljoen from tralac and Cecilia Punt from the Department of Agricultural Economics at Stellenbosch University, with assistance from William Mwanza from tralac and Elisha Tshuma, a tralac intern.

The group was split into five work groups, each with the objective of producing a tralac Working Paper or Trade Brief. The projects were designed to begin with data gathering and progress through to data collation and analysis and then to policy advice where possible. The emphasis was on getting participants to learn about where to find data but just as importantly how to use it. The five projects were:

  1. A spreadsheet simulation of the tariff revenue implication for Tanzania of regional free trade agreements (FTAs): This was done at the very detailed level of imports using the 2011 Comtrade import data. The objective was to produce a model that can be adapted for use by any of the Tripartite FTA countries for their trade negotiations. It shows the changes to trade flows at a detailed level and the associated tariff revenue implications. The distinction is made between trade creation that is genuine new trade and trade diversion that is merely reflecting existing trade to preferential sources under the changing tariff regimes. The model is very hands-on, and unlike most ‘black box’ models, easy to use. The operator can easily change any of the variables and quickly assess the difference to the overall result that this change makes.

  2. “Lies, damned lies and trade statistics”: An ongoing problem with trade data, certainly not specific to Africa, is that associated with timeliness and the non-reporting and inaccurate compilation of data in the region. This results in so-called mirror data whereby the use of partner data is used as a proxy for the non-reporting trading partner. This overall problem is accentuated when neither party has a reliable and accurate publication of their data. The objective for this project was to examine alternative trade data sources and assess the differences between these alternative sources. We used Tanzanian data as the reporting example. The study built in part upon the data used in the Tanzanian simulation exercise in Project 1 above using Comtrade data and compared that with, firstly, the Global Trade Atlas (GTA) data that tralac (and others) have, and secondly, various other sources of trade data. This is expected to highlight the problems associated with trade data, problems accentuated in Africa but by no means unique to the continent. We were unable to offer many reasons for the differences but consider it important to highlight these differences.

  3. An analysis of exports between South Africa and China: This project examined the trade data between South Africa and China at both the aggregate and detailed levels. The GTA data was used for each country to examine the reconciliation and the problems associated with differing reporting techniques before going on to examine the respective trade performances of South Africa and China in each other’s markets. There are wide and disturbingly large differences in the reported trade data. Building on this (admittedly inconsistent) trade data, an examination was undertaken to assess how well the partners were doing in the respective bilateral markets. This analysis was definitely hampered by the quality of the trade data. Download the paper here.

  4. ‘Terms of trade in agricultural trade’: This project again used the GTA South African data to assess the changes in prices for both agricultural exports and imports over the last few years to asses, in reality, if South Africa imports and exports the “right” products over this period. A ‘big picture’ view of global prices for the main commodities trade was presented to set the scene, and this was followed by compiling spreadsheets for the trade values and their associated average unit prices over the last six years. The big picture showed that the historical situation, whereby agricultural exports from South Africa were more than agricultural imports, is being challenged, and furthermore the trade reporting is biased in favour of exports as, unlike the international norm, South Africa does not include costs of freight and insurance in its import values. This effectively changes the overall trade balance in agriculture away from a surplus to a deficit. The six year period was chosen as it encompassed both the major impacts of the 2008 global commodity boom and subsequent decline from those highs. The data also shows that the commodity prices have largely recovered from the disruption of that price spike and its aftermath. The analysis showed that over the period South African export prices have increased more than the comparable import prices Index. These South African exports prices have also been above the Index calculated for agricultural exports from Brazil. Download the paper here.

  5. EU and South African trade data for Africa: This again used the GTA data from the EU and South Africa respectively to duplicate the spreadsheets that tralac has on the website for China and India showing the bilateral trading relationships for each and every African country. These sets of EU and South African files will be placed on the tralac website to augment those from China and India that are currently available. The data is at the somewhat aggregated HS 4 level and shows up to the top 20 HS 4 trade lines with their most recent and historical trade values.

It was especially pleasing to have the week supported by a study group who for the most part had strong Excel capabilities and were interested in furthering those skills. We thank them for their attendance at tralac.

Geek Week 9 - 13 September 2013 Attendance Register
Instructors: Ron Sandrey (This email address is being protected from spambots. You need JavaScript enabled to view it.) and Willemien Viljoen (This email address is being protected from spambots. You need JavaScript enabled to view it.)
Plus Cecilia Punt, Department of Agricultural Economics, University of Stellenbosch
Name Surname Organisation
Tania Gill Department of Agriculture
Andrew Partridge Department of Agriculture
Mildred Pheema Department of Agriculture
Constence Tshimangadzo Department of Agriculture, Fisheries and Forestry
Stephanie Van der Walt NAMC
Yolanda Potelwa NAMC
Eric Makamole Mpitsa SARS
Rudi Beets SARS
Jacques Vermaak SARS
Marius De Beer SARS
William Mwanza tralac researcher
Elisha Tshuma tralac intern


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Tel +27 21 880 2010