Real options and game theoretical approaches to real estate development projects: multiple equilibria and the implications of different tie-breaking rules

This paper contributes to a fast growing literature which introduces game theory in the analysis of real option investments in a competitive setting. Specifically, in this paper we focus on the issue of multiple equilibria and on the implications that different equilibrium selections may have for the pricing of real options and for subsequent strategic decisions. We present some theoretical results of the necessary conditions to have multiple equilibria and we show under which conditions different tie-breaking rules result in different economic decisions. We then present a numerical exercise using the in formation set obtained on a real estate development in South London. We find that risk aversion reduces option value and this reduction decreases marginally as negative externalities decrease.

Spatial concentration in institutional industrial real estate investment in the England and Wales

In two recent papers Byrne and Lee (2006, 2007) examined the geographical concentration of institutional office and retail investment in England and Wales at two points in time; 1998 and 2003. The findings indicate that commercial office portfolios are concentrated in a very few urban areas, whereas retail holdings correlate more closely with the urban hierarchy of England and Wales and consequently are essentially ubiquitous. Research into the industrial sector is very much less developed, and this paper therefore makes a significant contribution to understanding the structure of industrial property investment in the UK. It shows that industrial investment concentration is between that of retail and office and is focussed on LAs with high levels of manual workers in areas with smaller industrial units. It also shows that during the period studied the structure of the sector changed, with greater emphasis on the distributional element, for which location is a principal consideration.

Timing and the holding periods of institutional real estate

The literature on investors’ holding periods for equities and bonds suggest that high transaction costs are associated with longer holding periods. Return volatility, by contrast, is associated with short-term trading and hence shorter holding periods. High transaction costs and the perceived illiquidity of the real estate market leads to an expectation of longer holding periods. Further, work on depreciation and obsolescence might suggest that there is an optimal holding period. However, there is little empirical work in the area. In this paper, data from the Investment Property Databank are used to investigate sales rate and holding period for UK institutional real estate between 1981 and 1994. Sales rates are investigated using the Cox proportional hazards framework. The results show longer holding periods than those claimed by investors. There are marked differences by type of property and sales rates vary over time. Contemporaneous returns are positively associated with an increase in the rate of sale. The results shed light on investor behaviour.

New rôles and development rules for housing associations: rhe rise of design and build?

This paper summarises an initial report carried out by the Housing Business Research Group, of the University of Reading into Design and Build procurement and a number of research projects undertaken by the national federation of Housing Associations (NFHA), into their members' development programmes. The paper collates existing statistics from these sources and examines the way in which Design and Build procurement can be adapted for the provision of social housing. The paper comments on these changes and questions how risk averting the adopted strategies are in relation to long term housing business management issues arising from the quality of the product produced by the new system.

The effects of institutional distance and headquarters’ financial performance on the generation of environmental standards in multinational companies

This article combines institutional and resources’ arguments to show that the institutional distance between the home and the host country, and the headquarters’ financial performance have a relevant impact on the environmental standardization decision in multinational companies. Using a sample of 135 multinational companies in three different industries with headquarters and subsidiaries based in the USA, Canada, Mexico, France, and Spain, we find that a high environmental institutional distance between headquarters’ and subsidiaries’ countries deters the standardization of environmental practices. On the other hand, high-profit headquarters are willing to standardize their environmental practices, rather than taking advantage of countries with lax environmental protection to undertake more pollution-intensive activities. Finally, we show that headquarters’ financial performance also imposes a moderating effect on the relationship between environmental institutional distance between countries and environmental standardization within the multinational company.

Institutional capacity and implementation issues in farmers' rights

Armed with the ‘equity’ and ‘conservation’ arguments that have a deep resonance with farming communities, developing countries are crafting a range of measures designed to protect farmers’ access to innovations, reward their contributions to the conservation and enhancement of plant genetic resources and provide incentives for sustained on-farm conservation. These measures range from the commericialization of farmers’ varieties to the conferment of a set of legally enforceable rights on farming communities – the exercise of which is expected to provide economic rewards to those responsible for on-farm conservation and innovation. The rights-based approach has been the cornerstone of legislative provision for implementing farmers’ rights in most developing countries. In drawing up these measures, developing countries do not appear to have systematically examined or provided for the substantial institutional capacity required for the effective implementation of farmers’ rights provisions. The lack of institutional capacity threatens to undermine any prospect of serious implementation of these provisions. More importantly, the expectation that significant incentives for on-farm conservation and innovation will flow from these ‘rights’ may be based on a flawed understanding of the economics of intellectual property rights. While farmers’ rights may provide only limited rewards for conservation, they may still have the effect of diluting the incentives for innovative institutional breeding programs – with the private sector increasingly relying on non-IPR instruments to profit from innovation. The focus on a rights-based approach may also draw attention away from alternative stewardship-based approaches to the realization of farmers’ rights objectives.

Employee turnover, HRM and institutional contexts

Literature on comparative capitalism remains divided between approaches founded on stylized case study evidence and descriptions of broad trends, and those that focus on macro data. In contrast, this study explores the relevance of Amable’s approach to understanding differences in employment relations practice, based on firm-level micro data. The article examines employee–employer interdependence (including turnover rates) in different categories of economy as classified by Amable. The findings confirm that exit – whether forced or voluntary – remains more common in market-based economies than in their continental counterparts and that institutionalized employee voice is an important variable in reducing turnover. However, there is as much diversity within the different country categories as between them, and across continental Europe. In Denmark’s case, high turnover is combined with high unionization, showing the effects of a ‘flexicurity’ strategy. While employee voice may be stronger in Scandinavia, interdependence is weaker than in continental Europe.

Parallel induction of modular classification rules

The Distributed Rule Induction (DRI) project at the University of Portsmouth is concerned with distributed data mining algorithms for automatically generating rules of all kinds. In this paper we present a system architecture and its implementation for inducing modular classification rules in parallel in a local area network using a distributed blackboard system. We present initial results of a prototype implementation based on the Prism algorithm.

J-PMCRI: a methodology for inducing pre-pruned modular classification rules

Inducing rules from very large datasets is one of the most challenging areas in data mining. Several approaches exist to scaling up classification rule induction to large datasets, namely data reduction and the parallelisation of classification rule induction algorithms. In the area of parallelisation of classification rule induction algorithms most of the work has been concentrated on the Top Down Induction of Decision Trees (TDIDT), also known as the ‘divide and conquer’ approach. However powerful alternative algorithms exist that induce modular rules. Most of these alternative algorithms follow the ‘separate and conquer’ approach of inducing rules, but very little work has been done to make the ‘separate and conquer’ approach scale better on large training data. This paper examines the potential of the recently developed blackboard based J-PMCRI methodology for parallelising modular classification rule induction algorithms that follow the ‘separate and conquer’ approach. A concrete implementation of the methodology is evaluated empirically on very large datasets.

Induction of modular classification rules: using Jmax-pruning

The Prism family of algorithms induces modular classification rules which, in contrast to decision tree induction algorithms, do not necessarily fit together into a decision tree structure. Classifiers induced by Prism algorithms achieve a comparable accuracy compared with decision trees and in some cases even outperform decision trees. Both kinds of algorithms tend to overfit on large and noisy datasets and this has led to the development of pruning methods. Pruning methods use various metrics to truncate decision trees or to eliminate whole rules or single rule terms from a Prism rule set. For decision trees many pre-pruning and postpruning methods exist, however for Prism algorithms only one pre-pruning method has been developed, J-pruning. Recent work with Prism algorithms examined J-pruning in the context of very large datasets and found that the current method does not use its full potential. This paper revisits the J-pruning method for the Prism family of algorithms and develops a new pruning method Jmax-pruning, discusses it in theoretical terms and evaluates it empirically.

Jmax-pruning: a facility for the information theoretic pruning of modular classification rules

The Prism family of algorithms induces modular classification rules in contrast to the Top Down Induction of Decision Trees (TDIDT) approach which induces classification rules in the intermediate form of a tree structure. Both approaches achieve a comparable classification accuracy. However in some cases Prism outperforms TDIDT. For both approaches pre-pruning facilities have been developed in order to prevent the induced classifiers from overfitting on noisy datasets, by cutting rule terms or whole rules or by truncating decision trees according to certain metrics. There have been many pre-pruning mechanisms developed for the TDIDT approach, but for the Prism family the only existing pre-pruning facility is J-pruning. J-pruning not only works on Prism algorithms but also on TDIDT. Although it has been shown that J-pruning produces good results, this work points out that J-pruning does not use its full potential. The original J-pruning facility is examined and the use of a new pre-pruning facility, called Jmax-pruning, is proposed and evaluated empirically. A possible pre-pruning facility for TDIDT based on Jmax-pruning is also discussed.

Computationally efficient induction of classification rules with the PMCRI and J-PMCRI frameworks

In order to gain knowledge from large databases, scalable data mining technologies are needed. Data are captured on a large scale and thus databases are increasing at a fast pace. This leads to the utilisation of parallel computing technologies in order to cope with large amounts of data. In the area of classification rule induction, parallelisation of classification rules has focused on the divide and conquer approach, also known as the Top Down Induction of Decision Trees (TDIDT). An alternative approach to classification rule induction is separate and conquer which has only recently been in the focus of parallelisation. This work introduces and evaluates empirically a framework for the parallel induction of classification rules, generated by members of the Prism family of algorithms. All members of the Prism family of algorithms follow the separate and conquer approach.