Making Location Quotients More Relevant as a Policy Aid in Regional Spatial Analysis

Abstract

Location Quotients (LQs) remain an important tool for geographical analysis, particularly in terms of assessing industrial specialisation and clustering. LQs as decision aids are typically understood through the use of arbitrarily set cut-off values. However, LQs are rarely accompanied by an associated level of variance that can be connected with the estimated data used to calculate them. This paper reveals the importance of understanding this variance and shows how confidence intervals can be estimated for employment-based LQs. A systematic process is introduced, through which the arbitrariness of cut-off-value choice can be mitigated and borderline industry cases in terms of their LQ values and the considered cut-off value, identified. A case from a UK region is used to illustrate the issues covered in the paper.