Loss estimation and data storage methods utilised by stakeholders involved in residential reconstruction - A study of the Canterbury earthquake

Abstract

The importance of natural disaster economic loss estimations cannot be overstated. They help to assist policy maker in mitigation decisions, risk assessments and track the losses which occur due to such events. Despite this New Zealand has not employed a systematic method to estimate or record the losses which have occurred as a result of natural disasters therefore the records are poor.

The Canterbury Earthquake is one the most significant natural disasters in New Zealand’s history, with economic loss occurring at all levels of the economy. There are numerous complexities regarding how to measure this loss, and what should be included and excluded in these estimates. To further complicate this there are unique factors to this event such as the government’s intervention with red zone residents.

Loss estimates in the past have relied heavily on insurance information and this is one of the main sources of data for large scale events. This research aimed to investigate the estimation and data storage methods utilised by stakeholders involved in the residential reconstruction of Christchurch and compare the findings to the literature reviewed.

By conducting six semi-structured interviews with Insurance and Project Management Companies operating in Christchurch this exploratory research has allowed comparisons between the Insurance Companies, Project Management Companies and the literature with reference to estimation and data storage methods.

Although not all companies interviewed utilised an estimation method the research has found that there is a lack of consistency of process and method within the industry, which is in-line with the main findings from the literature. This was due to a number of factors most notably the lack of regulation within the industry and the competitive environment in which they operate. Due to the inconsistency there could be advantage in employing a systematic framework and centrally storing the information, however this too has its limitations and issues to overcome.