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Economic modelling of free trade areas and zones

It is notoriously difficult to economically model the benefits of FTAs and Special Economic Zones with respect to their impact on the domestic regulatory position.

The Department for International Trade has been rightly criticised, including by me and colleagues at Cebr, Doug McWilliams and Cristian Niculescu-Marcu (see for its economic modelling of some of the key trade agreements it is negotiating, especially the US-UK, UK-Australia (formally launched yesterday), UK-New Zealand and UK-Japan FTAs. We argued in that article that current models were far too static in nature, and did not properly weight non-geographic distance factors such as common law and common language. We also argued that the models did not take into account the potential gains from a reduction of market distortions inside the border, which could be significantly higher than a reduction of mere border barriers (see in particular the Cebr report on market distortions behind the border here and the IEA Plan A Plus here).  Current modelling does not take into account the impact of pooled markets where, for example the UK is able to secure a financial services agreement with the US leading to a transatlantic financial services area or a similar common defence area. This is ironic, because treasury models appear to value pooled markets tremendously highly in the EU context, but ignore them completely in any other context.

First, we must acknowledge that these are complex systems, akin to biological systems that are notoriously difficult to model. That is why the International Trade Commission (when the US was still a member) looking at the then Transpacific Partnership concluded that while tariff reductions could be relatively easily understood, the benefits of a reduction of behind the border barriers was much more difficult to model.

Secondly, we must also acknowledge that Treasury departments constantly underestimate the benefits of trade agreements.  The NZ Treasury underestimated the impact of the China-New Zealand FTA by 500%, and the agreement reached the gains projected for 11 years in a mere 11 months.

Thirdly, this is more art and less hard science.  Any practitioner of the physical sciences knows that economic modelling is by comparison educated and guided speculation.  It can certainly be useful speculation, but I would not bet my life on it, however good the modelling is. It is therefore important to use multiple models to try and capture specific benefits.

Fourth, no group of trade negotiators in the world goes around with a laptop modelling potential agreements in order to decide where to negotiate. Trade negotiations support foreign policy objectives, they support geo-political realities, and often they benefit form opportunities that present themselves with narrow windows in which to act (such as the US-UK FTA for example).

Fifth, it is almost impossible to say anything useful about the economic impact of a trade agreement before it has actually been agreed and we know what it actually does. A US-UK FTA that dealt only with industrial goods tariffs would have limited benefit, but a much deeper comprehensive agreement that tackled the anti-competitive restrictions in both markets would have a much bigger impact and we cannot know which one we are modelling until we see the words on a page.

Economic Modelling in Special Economic Zones

It is even more difficult to model well Advanced Special Economic Zones which make meaningful changes to the domestic regulatory position.  The Special Economic Zone in Duqm, Oman for example changes the Omanisation requirements from 35% to 10%, and eliminates a law giving significant protection to local distributors of foreign multinationals that has damaged competition and trade.  Other Special Zones, such as Panama Pacifico have made significant changes to immigration law. The recently instituted Honduras Prospera operates under a completely different set of rules under the Honduras ZEDE legislation (Zones of Economic Development).  A recent Ernst and Young report placed the Honduras ZEDE Prospera 9th in the World Bank Doing Business Index if it were a country, whereas Honduras itself languishes 133rdplace.  The table below illustrates the improvements made with respect to setting up a business:

The table below shows the difference in approach on permitting, which is a significant delay for business.

In Prospera, firms can essentially choose common law, or the law of other OECD members, or they can make suggestions for regulatory changes.

We have used the Productivity Simulator based on the Singham-Rangan-Bradley model (see here and here) of market distortions to model the economic impact of the zones.  As these zones work to optimise their internal regulatory environments as the ones cited to above do, we can model the impact on productivity (as measured by GDP per capita), and hence their contribution in economic terms to the countries in which they are located.  Zones that optimise around the three dimensions of openness to international trade, markets where competition policy is the organising economic principle, and property rights protection will do better economically.

There are a number of tools that can be used to measure the potential economic development in these zones. The potential for these to be global economic engines is clear and we need to make sure we have good ways to measure this.

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