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The object of the Investment Profiles is to expose the bidden assumptions which lie behind valuations of investment properties, and in doing so to provide a more objective platform for debate and argument about any particular valuation. The traditional approach to valuation is to apply an ‘all risks’ yield to the flow of income from any property, reflecting the advantages and disadvantages of that investment. However, there is no sound objective basis on which to justify the ‘all risks’ yield used. In reality, the valuer arrives at the yield by making a number of subconscious mental adjustments to the yield based on the particular features or disadvantages of the property under consideration. Investment Profiles arrive at the same ‘all risks’ yield by an explicit approach, the valuer making a series of adjustments to the yield. These adjustments can then be debated and argued. The need to resort to unscientific cliches like ‘prime’, ‘semi‐prime’ and ‘secondary’ can be much reduced or avoided. The paper considers a number of example valuations, and demonstrates that the technique is easy to understand and simple to use.

The purpose of this paper is to extend the studies of commercial property yields by providing a cross-field approach through the implementation of methods used in physics.

Based on the equations used to describe real gases in physics, the commercial property yields are expressed through a model, as a product of two terms. The first term estimates the influence of the income change and investment on yields. The second estimates the yield variation as a function of property size. Additionally, the model combines the macroeconomic and microeconomic components influencing yield adjustment. Calculation of each component involves procedures developed in physics, with the investment volume being linked to the amount of gas and the microeconomic yield being linked to the gas compressibility.

The model was applied to the Auckland office and industrial markets, both to the historic and current cycle. At the macro-level, it was found that the use of accumulation of investment over a relevant cycle, results in a high data to model correlation. When modelling the yields at the micro-level, a relationship between the outlying properties and the yield softening was observed.

The paper provides an enhanced modelling power through association of the cyclic and investment activity with the yield change. Moreover, the model may be used to decouple the local and the international investment components and the extent of their influence on the local property market. Furthermore, it may be used to estimate the influence of the property size on the yield.

This research provides a new cross-field application of modelling techniques and enhances the understanding of factors influencing yield adjustments.

The purpose of this paper is to develop methods for inferring if crop insurance premiums imply yield distributions that are valid according to standard laws of probability and broadly consistent with observed empirical evidence. The authors also survey current premium-implied distributions both before and after conditioning on the producer’s choice of coverage level.

Under an assumption of actuarial fairness, the authors derive expressions for upper and lower bounds for premium-implied yield cumulative distribution functions (CDFs) at loss thresholds for each coverage level. When observed premiums imply a CDF that exceeds one or is not non-decreasing, the authors conclude that premiums cannot be actuarially fair. The authors additionally specify very weak conditions for premium-implied yield CDFs to be consistent with two possible reasonable parametric distributions.

The authors evaluate premiums for the year 2018 for 19,104 county-crop-type-practice combinations, both before and after conditioning on producer’s choice of coverage level. The authors find problems in roughly one-third of cases. Problems are exhibited for all crops evaluated, and are strongly associated with areas with lower expected yields and higher yield variability. At least 40m acres are currently insured under premium schedules that cannot possibly be consistent with valid probability distributions.

The authors make two primary contributions. First, the premium-implied yield CDF bounds the authors derive requires fewer assumptions than previous similar work, while simultaneously placing more stringent conditions on premiums to be consistent with actuarial fairness. Second, the authors show that current US crop insurance premiums cannot possibly be actuarially fair for many cases, reflecting tens of millions of insured acres, which implies sub-optimal producer risk mitigation and inequitable expenditures for producers and taxpayers.

The aim of this paper is to examine the degree to which it is possible or practicable to make the analysis and valuation of property investments an explicit exercise. This is in direct contrast to the closed implicit nature of the practice which currently prevails, and which is epitomised by the use of the ‘all‐risks yield’ as a single gauge of the complex relationships of advantages and disadvantages within a particular investment. To what extent can the ‘all‐risks yield’ be purified, and to what extent will comparison with non‐property investments be facilitated as a result?

Responds to “A note on ‘The initial yield revealed: explicit valuations and the future of property investment’” published in an earlier issue of the Journal of Property Valuation & Investment. Addresses issues raised and develops and extends the organizations of the original paper, in particular: definitions of certain concepts; the determination of value; the need for explicit valuations; price formation in the property market; and the influence of valuation on price. Reiterates the purposes of the original worked example of valuations; produces a corrected version; and in an appendix presents extended solutions and a fuller discussion of the central issues.

This paper aims to conduct bibliometric analysis on the studies dealing with capital structure’s speed of adjustment (SoA) and identify the prominent themes while suggesting future research directions in the area. The existing reviews broadly focus on the capital structure, which provides the scope for conducting a review on this sub-aspect of capital structure.

This study uses a three-stage process to conduct this review: identification of academic journals, selection and analysis of target papers. This study uses a combination of bibliometric tools and a system thinking approach to assess the current status of publications and emerging themes within the literature.

This study has found a progressive evolution of SoA in capital structure research from 1984 to 2021. Studies largely focus on implementing the dynamic models to analyse the impact of adjustment costs, dynamic economic conditions, corporate governance practices and other variables on the firms’ adjustment speed and financial decisions. The network analysis of citations, keywords and clusters gives further knowledge on the intellectual structure of the data.

This study is highly dependent on the papers available within the SCOPUS database. Studies not included herein are not part of this analysis, which may or may not bear an effect on the study’s findings.

To the best of the authors’ knowledge, the application of systems engineering concept of “system thinking approach” to identify literature gap and suggest directions for forthcoming research is the first of its kind, thus adding a novel and multidisciplinary aspect to this study.

The UK government, in late 2019, announced new proposed targets for the energy efficiency legislation in the UK, MEES – Minimum Energy Efficiency Standards. The current suggestion is that all let properties, commercial or residential, need to be B rated by 2030. If this is implemented, it will have a significant impact upon the UK market property investment market.

This practice briefing is an overview of the 2018 legislation and comments on how market awareness has changed since its introduction and the potential impact upon prices of affected properties moving forward

This paper discusses how capital and rental values are beginning to be discounted in the market to allow for current and future liabilities under the MEES legislation. This has a significant impact on strategies for property investment.

This paper analyses the likelihood of (negative) capital and rental value changes under the proposed stricter energy efficiency guidelines.

This provides guidance on how valuations can be undertaken to reflect any impact of the likely changes to UK energy efficiency legislation.

It can be argued that the property valuation profession has historically relied upon uniformity as the basis of all capital and rental valuations. Within each property sector, differences in location and design were secondary to the underlying fundamental that the lease contracts for the properties were the same. During the 1980s most leases, in all sectors, were of 25‐year duration with the tenant being responsible for all outgoings. In the early 1990s the lease length reduced but most other terms remained constant. Rental valuation could therefore be made by direct comparison on a pro‐rata basis. Similarly, capital valuation would be made either by direct capital comparison, or by reference to a comparable rent and yield to determine the capital value by the investment method. Comparison was still the principal tool of analysis and this relied upon uniformity of leases within the market. In the late 1990s, the business environment experienced substantial structural change and tenants began to demand bespoke leases to suit their particular requirements. This has led to a plethora of different lease contracts, as tenants require shorter leases, the ability to expand and contract, break clauses and upwards/downwards rent reviews. The market is now as diverse as it was uniform in the 1980s. However, as pricing models relied upon comparison, valuers were reluctant to accept tenants’ new demands for flexibility as it was difficult to price these new contracts. This paper reviews the change in market conditions and equates the new requirements of the tenants with an increase in the uncertainty in the market. It argues that this uncertainty can be built into pricing models using probability‐based models and provides a scenario analysis to price a flexible lease contract.