Horizon Blog: Demystifying the Data – The Story Behind the International Agri-Food Trade Network Model

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With the government setting an ambitious vision to position the UK as a champion of free trade after leaving the EU, the AHDB rightly felt that further work was needed to educate the industry on the effects. likely of our new trade relationship on our agricultural sectors – the first being his recently published analysis of the UK-Australia deal. Over the past several months at Harper Adams, we have used our new business model and worked with the AHDB to quantify these potential impacts.
Modeling can be a very useful tool in trying to understand how policy changes, such as entering into new trade deals, can affect farmers and producers and the prices they will be paid for their products in the future. But when we looked at the existing models, we found that they did not take into account the complexities of global agri-food trade and came to the conclusion that we need to look at it from a different perspective.
Indeed, international trade in agricultural and food products is characterized by a number of factors.
A good example is the influence of intermediaries, such as food processors, on other participants in the supply chain: in a buyer’s market, these intermediaries have power over the prices they pay to farmers. Competition with intermediary firms from other countries is also a source of influence, resulting in strong integration of supply chains between countries. This means that anything that affects a country’s market, like signing a trade deal, has a ripple effect on the other countries it trades with.
So, for example, if country A increases exports of a product to country B, this increases the level of competition in country B, negatively affecting the profits of competing intermediaries in that country. As a result, these companies adjust to compensate for their losses. They reduce the quantity of products sold in their own country and divert trade to third countries. Likewise, the costs of intermediaries in country A may increase, reducing their own profits, as they have to pay farmers more to source products for export.
Another important factor in international agri-food trade is the existence of political biases between countries. Often governments develop policies to help certain groups, perhaps under the influence of powerful pressure groups, creating distortions in trade flows.
A third factor is âintra-industry tradeâ. This is where countries export and import the same product. Here, âproduct differentiationâ comes into play if consumers do not view domestic and imported products alike in terms of attributes such as quality.
Existing business modeling approaches normally do not take into account the factors described above, as they tend to assume that markets operate under idealized conditions. While this gives them the advantage of being relatively simple to use and can certainly be useful, it does not reflect what happens in the real world. So we had to find a different way of doing things.
Using our new International Agri-Food Trade Network (IAFTN) model, which is an alternative and innovative modeling approach designed to take into account all of the important market characteristics described above, we have worked closely with AHDB market analysts to provide a more realistic assessment of the likely effects of trade agreements. Anyone interested in delving deeper into the methodology behind the work can read the full technical report.
Like all predictive models, the IAFTN model has limitations because it predicts trends based on historical data. As such, we depend on the availability and quality of this data. Additionally, economic modelers do not have access to a crystal ball, so we cannot anticipate unexpected shocks to the economy (such as a collapse of trade between countries due to political disagreements). It may have its caveats, but the IAFTN model has provided deeper and more realistic information on the impacts of trade agreements on our food and agriculture sectors than was previously possible and its capacity will continue to be developed.
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