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The supposition that the availability and cost of insurance will have an effect on house prices is often accepted as fact. However the mechanism for this supposed impact has not been clearly articulated and the hypothesis is far from proven in the UK market. Measurement of the effect of insurance is complicated by the fact that the parties are acting in the presence of incomplete information and that insurance costs can act as a proxy for other value drivers such as flood risk. Models useful in other countries cannot be applied sensibly to the UK market because of the unique properties of the UK insurance regime. Novel hypotheses are suggested for the three principal ways in which the availability and cost of insurance might influence the prospective property transfer. A method for testing one of these hypotheses is proposed using a quasi‐experimental approach with the aim of determining whether a relationship between insurance cost and house price does indeed exist.

The purpose of this research is to show how the measurement of the effect of flooding on house value can be invaluable information for professional valuers and homeowners alike. In the UK, even for an event as devastating as the autumn 2000 flood, the number of properties affected in any one town is small and so robust estimation is problematic and methodology applied elsewhere needs modification. A new framework for analysing the effect of flooding on house value in the UK is presented.

Data issues play a crucial role in determining the methodology employed in any analysis. A repeat sales methodology is proposed which allows for the tracking of effects through time. The analysis can be extended to multiple sites via a block design thereby increasing the sample size.

Empirical analysis of one case study site demonstrates the inherent small sample problem and yet reveals patterns that fall in line with expected outcomes in many respects.

The case study results are illustrative only. A programme of further analysis is planned which includes comparison of the new framework with more traditional approaches.

A novel methodology is developed tracking the temporal variability in flood effect. The minimisation of data requirements inherent in the model allows for transfer to multiple sites and easy updating of the analysis.

Microenterprises in emerging economies are known to operate in turbulent and resource-scarce environments. We test our hypothesis that a more comprehensive “Integrated Capital-Based Model” (ICBM) is needed when explaining the performance of microenterprises in such an environment. The model combines traditionally researched financial, human and social capital with more recently emphasized psychological and cognitive capital, providing greater explanatory power than models using only the traditional types of capital.

We use a pooled linear regression to analyze an existing survey of more than 900 independent business owners who were interviewed seven times between 2008 and 2012 in the Accra and Tema marketplaces in Ghana. We measure the performance of microenterprises using three dependent variables (revenue, profits, and productivity). We contrast the explanatory power of ICBM models against the more traditional models.

The ICBM has significantly higher levels of explanatory power over the traditional models in examining the performance of these microenterprises. These results highlight the importance of psychological and cognitive capital in emerging economies.

We advocate for a more comprehensive view of capital as shown in our ICBM. However, the data were gathered only in an urban setting, which limits the generalizability to rural parts of emerging economies.

These findings suggest the utility of government and appropriate agencies finding ways to enhance the level of psychological and cognitive capital of microenterprise owners.

This paper's originality stems from hypothesizing and empirically confirming the higher predictive efficacy of ICBM against more traditionally researched capital sources.