Economic Implications of Data Regulation

Annex C. Additional data flow regulation simulations

C.1. Introducing the data flow shocks one by one

The channels of transmission across the different shocks can be gleaned by introducing the shocks one by one, cumulatively, starting from the change in trade costs, followed by the change in willingness to pay (Figure A C.1).

Under the first scenario of no regulation and given that the shocks are added cumulatively in the figure, the adverse effect of a reduction in trust generating reduced willingness to pay more than compensates for the beneficial fall in trade costs. Although getting rid of data flow policies would reduce costs and thus raise exports (by 1.86%) and GDP (by 1.28%), global exports and GDP are projected to fall when regulations are abolished and the trust effect is taken into account (by respectively 2.12% and 0.91%), because regulations come with enhanced trust among consumers and thus increased sales. As explained above, the size of the trust effect is based on information in the business questionnaire on the size of the cost effect of data flow policies relative to the size of the sales effect.

In the other counterfactual scenarios, the willingness to pay shock reinforces the trade cost shocks for regions which currently have ad hoc authorisation data flow policies (the fourth approach in Figure 3.6), because both trade costs will fall and willingness to pay rise when moving away from ad hoc authorisation towards a safeguards approach. Instead, for regions starting from no regulation changes in trade costs and willingness to pay work in opposite directions. For example, moving to a safeguards approach will raise trade costs which limits trade, whereas it will also raise willingness to pay which will increase trade.

Figure A C.1. Contribution of the different data flow regulation shocks (added cumulatively)

 

Note: The figure displays the projected percentage change of real exports and real GDP at the global level under four scenarios: (1) no regulation; (2) moving to the middle; (3) geoeconomic fragmentation; (4) data flows doomsday with the four shocks associated with each of these scenarios introduced cumulatively. The four shocks added cumulatively are changes in iceberg trade costs, fixed trade costs, and willingness to pay (related to data flow policies) and changes in the costs of inputs of data management services associated with data localisation policies.

Source: Simulations with the WTO Global Trade Model (version with Melitz market structure as described in Bekkers and Francois (2018[34]).

C.2. Impact on trade patterns from changes in data flow regulation

The projected change in exports between regions with different data flow regimes are shown in the upper panel of Figure A C.2. Under the first no regulation scenario the projected increase in trade is very modest for regions with ad hoc authorisation policies, because most of these regions cannot reduce trade costs, because of prohibitive data localisation policies which prevent such regions from transferring data even if data flow policies were abolished.

By contrast, the regions with open or pre-authorised safeguards tend to see their exports fall to all regions except those with ad hoc authorisation. The falling exports to regions without regulation can be explained by import demand shifting towards regions with ad hoc authorisation who see their exports increase because of reductions in trade costs. The rising exports from regions without regulations to regions with ad hoc authorisation are driven by rising demand in the latter regions for imports because of increased output and thus increased demand for intermediate inputs. For regions, the same mechanism is at play and on top of that there is a reduction in trust for these regions which dominates falling trade costs.

For the second scenario (moving to the middle) both regions without regulations and regions with safeguards see very small changes in their exports to other regions with the same regime. The reason for regions without safeguards is that the impact of increased competition of exports from regions with ad hoc authorisation is about as large as increased export opportunities because of increased willingness to pay. For regions with safeguards there are no changes in trade costs and trust and thus no large changes in exports. However, both regions see their exports increase to regions with ad hoc authorisation, because of increased demand from these regions which see their exports and income rise.

For the third scenario (geoeconomic fragmentation) the projected changes in exports between regions with different types of data flow regimes for most pairs of regions are negative as expected although the effects are small. For the fourth scenario (data flows doomsday) the projected changes in exports are negative for all pairs except for two (from 0 to 3, from 1 to 3 and from 3 to 3). The reason for these increases is that trade is shifting to pairs for which trade costs are not increasing as much.

Figure A C.2. The projected change in real exports between regions with different data flow regimes (upper panel) and regions with different geopolitical alignment under the four scenarios

Notes: The figure displays the projected change in real exports (in per cent) between regions with different data flow regimes (upper panel) and with different geopolitical alignment (lower panel) under four scenarios: (1) no regulation; (2) moving to the middle; (3) geoeconomic fragmentation; (4) data flows doomsday. The four data flow regimes are (0) No regulation; (1) open safeguards; (2) pre-approved safeguards; (3) Ad hoc regulation. The three geopolitical blocs are: (1) Western Bloc; (2) Eastern Bloc; (3) Non-aligned.

Source: Simulations with the WTO Global Trade Model (version with Melitz market structure as described in (Bekkers and Francois, 2018[34]).

For the lower panel of Figure A C.2 displaying the change in exports between regions by geopolitical affiliation Scenarios 3 and 4 are most interesting, because the first three scenarios are not directly related to geopolitical affiliation. Under Scenario 3, Figure A C.2shows that trade within geopolitical blocs is projected to rise substantially (EAS,EAS and WES,WES) and fall between blocs as expected. Trade between the non-aligned region and other regions is projected to rise, because of trade shifting away from trade between the Eastern and Western Blocs.

For the fourth scenario (data flows doomsday) trade is projected to fall for almost all combinations as expected because trade costs rise between all regions, except for trade from the Non-Aligned Bloc to the Eastern Bloc. The reason for this increase is that trade is shifting to pairs for which trade costs are not increasing as much and this is only the case for exports from NAL to EAS.