Tax optimization in an agent-based model of real-time spectrum secondary market

The wireless communication industry is an essential sector boosting economic progress worldwide. The structure of the legacy wireless communication market, characterised by static licensing schemes, is moving towards real-time secondary spectrum markets. While the technological body of spectrum trading has been discussed in detail, from an economic perspectives there are still a lot of gaps in understanding how these transactions affect the economy of future communication standards. A challenging aspect of the real-time spectrum market deployment is the implementation of the appropriate tax system that impacts the market structure. With regards to this, we aim to build an agent-based model of the real-time secondary spectrum market in which various taxes including value-added tax, corporate tax, consumption tax and fixed tax, are employed. The relations between selected tax type rates and the hypothetical revenue of the national regulator is established using Laffer curves. The results of the analysis confirm the existence of a tax distortion, i.e. a system deviation from the efficient system functioning affected by the tax introduction. To measure the complexity of the tax strategies and the emergent tax distortion, an original approach based on Euclidean metrics defined over a vector space of the system performance indicators was proposed. This approach was later applied in parallel with the traditional Harberger’s triangle methodology. We found that the constrained optimisation with the tax distortion restrictions provide satisfactory results regarding the stability of the tax distortion measure. Therefore, we propose the application of the most effective corporate tax optimisation complemented by selected additional tax types.