This paper explores a bootstrap modelling approach to estimating the value of mobile, spectrum and data demand. A mobile data forecast is not required, since data growth is modelled endogenously. The approach also dispenses with the notion of a “spectrum crunch” since data demand responds to available capacity. The results differ from those of an orthodox approach which treats data demand as exogenous and fixed (equivalent to assuming a data price elasticity of demand of zero). Spectrum value is less sensitive to supply side capacity assumptions; whilst economic surplus and spectrum value increase rather than decrease with reduced site costs - due to the stimulus to data traffic. The approach enables policy options, via their impact on supply (costs) and demand (willingness to pay) and the competitive equilibrium to be estimated. A range of policy issues are explored including auction reserve prices and spectrum fees, a hypothetical mobile data tax, mobile cost reduction, mobile mergers and fixed-mobile substitution.