Chapter 15 briefly describes some additional extensions to input–output analysis for which space does not permit a detailed treatment in this text, including measuring total factor productivity, modeling economic impacts of disasters, the inoperatbility input–output model, accounting for alternative technologies, and linkages to econometric or computable general equilibrium models.

Chapter 3 introduces a range of multidisciplinary data sources available to study disasters and history and outlines some of the methodologies through which we can interpret and analyze these sources. The underpinning argument is that we can use history as a laboratory to better understand disasters – testing hypotheses rather than merely describing conspicuous phenomena, albeit with a recognition of what this also demands of us as historians. In particular, we discuss the production of suitable measures and methods to understand hazards and their effects, whilst also keeping in mind the limitations of the historical record and the need for a critical approach to sources. We consider, therefore, state-of-the-art challenges in historical disaster research such as how we can compensate for lacunae in the historical record by incorporating rapidly increasing volumes of data from the natural sciences, and the opportunities and pitfalls of historical ‘big data’. The chapter concludes by arguing for the importance of systematic comparative methodologies in moving beyond the descriptive and towards the analytical, which requires that we pay particular attention to scale and context.