Commercial property loan valuations in the UK : implications of current trends in practice and liability

This paper is the second of two papers which aim to examine the major legal liability implications of changes to the commercial property loan valuation process caused by the recession in the UK property market and to make recommendations to valuers and their professional institutions to improve the quality of the process and the result. The objectives of this paper are to address a number of the practical implications of changes to the loan valuation process within the context of legal liability. The results of an interview survey of lenders and valuers are reported and analysed. The survey examined the loan valuation process including the selection and instruction of valuers, bases of valuation and valuation reporting. In the selection and instruction process, the findings of the survey reveal two potential problems within the valuer/lender relationship. First, valuers still occasionally accept instructions from borrowers and this could lead to a conflict of interest as lenders may rely on the survey. Second, the occasional lack of formal instructions prior to the delivery of reports casts doubt on the valuer’s ability to correctly identify the needs of clients. Regarding the basis of valuation, it was found that valuers are providing valuations on bases which they do not think are appropriate. Valuers may be legally liable if they do not inform clients of their reservations and this situation must be urgently addressed. The survey also confirms previous research that valuation reports are considered to be light on contextual information concerning markets. The paper concludes by making a number of specific recommendations concerning possible improvements to the commercial property loan valuation process.

Liability of country foreignness and liability of regional foreignness: their effects on geographic diversification and firm performance

The costs of inter- and intra-regional diversification have been widely discussed in the existing international business literature, but the findings are mixed. Explanations for the mixed findings have important managerial implications, because business managers have to estimate accurately the costs of doing business within and across regions before they make their internationalization decisions. To explain the existing mixed findings, this study differentiates between liabilities of foreignness at the country and regional levels, and explores the joint effects of liability of country foreignness (LCF) and liability of regional foreignness (LRF) on the performance of internationalizing firms. Using data from 167 Canadian firms, we find that LCF may not necessarily be negatively correlated with intra-regional diversification, but LRF is positively correlated with inter-regional diversification. LCF moderates the relationship between LRF and inter-regional diversification, and also mediates the relationship between intra-regional diversification and firm performance. LRF mediates the relationship between inter-regional diversification and firm performance. Missing one or more of these variables may result in different cost estimates. Identification of the relationships between these variables helps to improve the accuracy of estimating the costs of doing business aboard.

The impact of uncertain precipitation data on insurance loss estimates using a flood catastrophe model

Catastrophe risk models used by the insurance industry are likely subject to significant uncertainty, but due to their proprietary nature and strict licensing conditions they are not available for experimentation. In addition, even if such experiments were conducted, these would not be repeatable by other researchers because commercial confidentiality issues prevent the details of proprietary catastrophe model structures from being described in public domain documents. However, such experimentation is urgently required to improve decision making in both insurance and reinsurance markets. In this paper we therefore construct our own catastrophe risk model for flooding in Dublin, Ireland, in order to assess the impact of typical precipitation data uncertainty on loss predictions. As we consider only a city region rather than a whole territory and have access to detailed data and computing resources typically unavailable to industry modellers, our model is significantly more detailed than most commercial products. The model consists of four components, a stochastic rainfall module, a hydrological and hydraulic flood hazard module, a vulnerability module, and a financial loss module. Using these we undertake a series of simulations to test the impact of driving the stochastic event generator with four different rainfall data sets: ground gauge data, gauge-corrected rainfall radar, meteorological reanalysis data (European Centre for Medium-Range Weather Forecasts Reanalysis-Interim; ERA-Interim) and a satellite rainfall product (The Climate Prediction Center morphing method; CMORPH). Catastrophe models are unusual because they use the upper three components of the modelling chain to generate a large synthetic database of unobserved and severe loss-driving events for which estimated losses are calculated. We find the loss estimates to be more sensitive to uncertainties propagated from the driving precipitation data sets than to other uncertainties in the hazard and vulnerability modules, suggesting that the range of uncertainty within catastrophe model structures may be greater than commonly believed.

Political culture and corporate homicide liability in the UK and Europe

This chapter outlines recent developments in the emergence within Europe of systems of criminal law designed to hold corporate bodies liable where they cause the deaths of workers or members of the public. These changes point to the emergence of a new, more punitive, legal culture in relation to corporate crime. At the same time, however, there is evidence to suggest that this punitive culture is not uniform; different national jurisdictions reflect it to differing degrees. The chapter explores the degree to which the UK’s willingness to criminalise work-related deaths is mirrored elsewhere in Europe, and identifies some factors that might account for variations in this regard. In particular, attention is paid to the influence that social and political culture have on practices in this area. It is written as part of a research handbook on corporate crime in Europe, so has an eye on a more generalist audience in some regards.

Asset liability modelling and pension schemes: the application of robust optimization to USS

This paper uses a novel numerical optimization technique - robust optimization - that is well suited to solving the asset-liability management (ALM) problem for pension schemes. It requires the estimation of fewer stochastic parameters, reduces estimation risk and adopts a prudent approach to asset allocation. This study is the first to apply it to a real-world pension scheme, and the first ALM model of a pension scheme to maximise the Sharpe ratio. We disaggregate pension liabilities into three components - active members, deferred members and pensioners, and transform the optimal asset allocation into the scheme’s projected contribution rate. The robust optimization model is extended to include liabilities and used to derive optimal investment policies for the Universities Superannuation Scheme (USS), benchmarked against the Sharpe and Tint, Bayes-Stein, and Black-Litterman models as well as the actual USS investment decisions. Over a 144 month out-of-sample period robust optimization is superior to the four benchmarks across 20 performance criteria, and has a remarkably stable asset allocation – essentially fix-mix. These conclusions are supported by six robustness checks.

Search engine liability for autocomplete suggestions: personality, privacy and the power of the algorithm

This article is concerned with the liability of search engines for algorithmically produced search suggestions, such as through Google’s ‘autocomplete’ function. Liability in this context may arise when automatically generated associations have an offensive or defamatory meaning, or may even induce infringement of intellectual property rights. The increasing number of cases that have been brought before courts all over the world puts forward questions on the conflict of fundamental freedoms of speech and access to information on the one hand, and personality rights of individuals— under a broader right of informational self-determination—on the other. In the light of the recent judgment of the Court of Justice of the European Union (EU) in Google Spain v AEPD, this article concludes that many requests for removal of suggestions including private individuals’ information will be successful on the basis of EU data protection law, even absent prejudice to the person concerned.

Exploiting satellite-based rainfall for weather index insurance: the challenges of spatial and temporal aggregation

Lack of access to insurance exacerbates the impact of climate variability on smallholder famers in Africa. Unlike traditional insurance, which compensates proven agricultural losses, weather index insurance (WII) pays out in the event that a weather index is breached. In principle, WII could be provided to farmers throughout Africa. There are two data-related hurdles to this. First, most farmers do not live close enough to a rain gauge with sufficiently long record of observations. Second, mismatches between weather indices and yield may expose farmers to uncompensated losses, and insurers to unfair payouts – a phenomenon known as basis risk. In essence, basis risk results from complexities in the progression from meteorological drought (rainfall deficit) to agricultural drought (low soil moisture). In this study, we use a land-surface model to describe the transition from meteorological to agricultural drought. We demonstrate that spatial and temporal aggregation of rainfall results in a clearer link with soil moisture, and hence a reduction in basis risk. We then use an advanced statistical method to show how optimal aggregation of satellite-based rainfall estimates can reduce basis risk, enabling remotely sensed data to be utilized robustly for WII.

The use of remotely sensed rainfall for managing drought risk: a case study of weather index insurance in Zambia

Remotely sensed rainfall is increasingly being used to manage climate-related risk in gauge sparse regions. Applications based on such data must make maximal use of the skill of the methodology in order to avoid doing harm by providing misleading information. This is especially challenging in regions, such as Africa, which lack gauge data for validation. In this study, we show how calibrated ensembles of equally likely rainfall can be used to infer uncertainty in remotely sensed rainfall estimates, and subsequently in assessment of drought. We illustrate the methodology through a case study of weather index insurance (WII) in Zambia. Unlike traditional insurance, which compensates proven agricultural losses, WII pays out in the event that a weather index is breached. As remotely sensed rainfall is used to extend WII schemes to large numbers of farmers, it is crucial to ensure that the indices being insured are skillful representations of local environmental conditions. In our study we drive a land surface model with rainfall ensembles, in order to demonstrate how aggregation of rainfall estimates in space and time results in a clearer link with soil moisture, and hence a truer representation of agricultural drought. Although our study focuses on agricultural insurance, the methodological principles for application design are widely applicable in Africa and elsewhere.

Non-monotone insurance contracts and their empirical consequences

The goal of this paper is to show the possibility of a non-monotone relation between coverage ans risk which has been considered in the literature of insurance models since the work of Rothschild and Stiglitz (1976). We present an insurance model where the insured agents have heterogeneity in risk aversion and in lenience (a prevention cost parameter). Risk aversion is described by a continuous parameter which is correlated with lenience and for the sake of simplicity, we assume perfect correlation. In the case of positive correlation, the more risk averse agent has higher cosr of prevention leading to a higher demand for coverage. Equivalently, the single crossing property (SCP) is valid and iplies a positive correlation between overage and risk in equilibrium. On the other hand, if the correlation between risk aversion and lenience is negative, not only may the SCP be broken, but also the monotonocity of contracts, i.e., the prediction that high (low) risk averse types choose full (partial) insurance. In both cases riskiness is monotonic in risk aversion, but in the last case there are some coverage levels associated with two different risks (low and high), which implies that the ex-ante (with respect to the risk aversion distribution) correlation between coverage and riskiness may have every sign (even though the ex-post correlation is always positive). Moreover, using another instrument (a proxy for riskiness), we give a testable implication to desentangle single crossing ans non single croosing under an ex-post zero correlation result: the monotonicity of coverage as a function os riskiness. Since by controlling for risk aversion (no asymmetric information), coverage is monotone function of riskiness, this also fives a test for asymmetric information. Finally, we relate this theoretical results to empirical tests in the recent literature, specially the Dionne, Gouruéroux and Vanasse (2001) work. In particular, they found an empirical evidence that seems to be compatible with asymmetric information and non single crossing in our framework. More generally, we build a hidden information model showing how omitted variables (asymmetric information) can bias the sign of the correlation of equilibrium variables conditioning on all observable variables. We show that this may be the case when the omitted variables have a non-monotonic relation with the observable ones. Moreover, because this non-dimensional does not capture this deature. Hence, our main results is to point out the importance of the SPC in testing predictions of the hidden information models.

The insurance function of contracts

One of the central problems in contract law is to define the frontier between legal and illegal breaches of promises. The distinction between good and bad faith is perhaps the conceptual tool most commonly used to tell one from the other. Lawyers spend a lot of energy trying to frame better definitions of the concepts of good and bad faith based on principles of ethics or justice, but often pay much less attention to theories dealing with the incentives that can engender good faith behavior in contractual relationships. By describing the economics of what Stiglitz defined as “explicit” and “implicit” insurance, I highlight the “insurance function” hidden in any promise with basically no mathematical notation. My aim is to render the subject intelligible and useful to lawyers with little familiarity with economics.

On insurance markets with endogenous information acquisition: A robust mechanism design approach

Neste trabalho propomos a aplicação das noções de equilíbrio da recente literatura de desenho de mecanismo robusto com aquisição de informação endógena a um problema de divisão de risco entre dois agentes. Através deste exemplo somos capazes de motivar o uso desta noção de equilíbrio, assim como discutir os efeitos da introdu ção de uma restrição de participação que seja dependente da informação. A simplicidade do modelo nos permite caracterizar a possibilidade de implementar a alocação Pareto efiente em termos do custo de aquisição da informação. Além disso, mostramos que a precisão da informação pode ter um efeito negativo sobre a implementação da alocação efi ciente. Ao final, sao dados dois exemplos específicos de situações nas quais este modelo se aplica.