Construction Prices : the Market Effect

Teachers of construction economics and estimating have for a long time recognised that there is more to construction pricing than detailed calculation of costs (to the contractor). We always get to the point where we have to say "of course, experience or familiarity of the market is very important and this needs judgement, intuition, etc". Quite how important is the matter in construction pricing is not known and we tend to trivialise its effect. If judgement of the market has a minimal effect, little harm would be done, but if it is really important then some quite serious consequences arise which go well beyond the teaching environment. Major areas of concern for the quantity surveyor are in cost modelling and cost planning - neither of which pay any significant attention to the market effect. There are currently two schools of thought about the market effect issue. The first school is prepared to ignore possible effects until more is known. This may be called the pragmatic school. The second school exists solely to criticise the first school. We will call this the antagonistic school. Neither the pragmatic nor the antagonistic schools seem to be particularly keen to resolve the issue one way or the other. The founder and leader of the antagonistic school is Brian Fine whose paper in 1974 is still the basic text on the subject, and in which he coined the term 'socially acceptable' price to describe what we now recognise as the market effect. Mr Fine's argument was then, and is since, that the uncertainty surrounding the contractors' costing and cost estimating process is such that the uncertainty surrounding the contractors' cost that it logically leads to a market-orientated pricing approach. Very little factual evidence, however, seems to be available to support these arguments in any conclusive manner. A further, and more important point for the pragmatic school, is that, even if the market effect is as important as Mr Fine believes, there are no indications of how it can be measured, evaluated or predicted. Since 1974 evidence has been accumulating which tends to reinforce the antagonists' view. A review of the literature covering both contractors' and designers' estimates found many references to the use of value judgements in construction pricing (Ashworth & Skitmore, 1985), which supports the antagonistic view in implying the existence of uncertainty overload. The most convincing evidence emerged quite by accident in some research we recently completed with practicing quantity surveyors in estimating accuracy (Skitmore, 1985). In addition to demonstrating that individual quantity surveyors and certain types of buildings had significant effect on estimating accuracy, one surprise result was that only a very small amount of information was used by the most expert surveyors for relatively very accurate estimates. Only the type and size of building, it seemed, was really relevant in determining accuracy. More detailed information about the buildings' specification, and even a sight to the drawings, did not significantly improve their accuracy level. This seemed to offer clear evidence that the constructional aspects of the project were largely irrelevant and that the expert surveyors were somehow tuning in to the market price of the building. The obvious next step is to feed our expert surveyors with more relevant 'market' information in order to assess its effect. The problem with this is that our experts do not seem able to verbalise their requirements in this respect - a common occurrence in research of this nature. The lack of research into the nature of market effects on prices also means the literature provides little of benefit. Hence the need for this study. It was felt that a clearer picture of the nature of construction markets would be obtained in an environment where free enterprise was a truly ideological force. For this reason, the United States of America was chosen for the next stage of our investigations. Several people were interviewed in an informal and unstructured manner to elicit their views on the action of market forces on construction prices. Although a small number of people were involved, they were thought to be reasonably representative of knowledge in construction pricing. They were also very well able to articulate their views. Our initial reaction to the interviews was that our USA subjects held very close views to those held in the UK. However, detailed analysis revealed the existence of remarkably clear and consistent insights that would not have been obtained in the UK. Further evidence was also obtained from literature relating to the subject and some of the interviewees very kindly expanded on their views in later postal correspondence. We have now analysed all the evidence received and, although a great deal is of an anecdotal nature, we feel that our findings enable at least the basic nature of the subject to be understood and that the factors and their interrelationships can now be examined more formally in relation to construction price levels. I must express my gratitude to the Royal Institution of Chartered Surveyors' Educational Trust and the University of Salford's Department of Civil Engineering for collectively funding this study. My sincere thanks also go to our American participants who freely gave their time and valuable knowledge to us in our enquiries. Finally, I must record my thanks to Tim and Anne for their remarkable ability to produce an intelligible typescript from my unintelligible writing.

Semi-parametric forecasting of spikes in electricity prices

The occurrence of extreme movements in the spot price of electricity represents a significant source of risk to retailers. A range of approaches have been considered with respect to modelling electricity prices; these models, however, have relied on time-series approaches, which typically use restrictive decay schemes placing greater weight on more recent observations. This study develops an alternative, semi-parametric method for forecasting, which uses state-dependent weights derived from a kernel function. The forecasts that are obtained using this method are accurate and therefore potentially useful to electricity retailers in terms of risk management.

Does the price of oil interact with clean energy prices in the stock market?

In this paper, we analyze the relationships among oil prices, clean energy stock prices, and technology stock prices, endogenously controlling for structural changes in the market. To this end, we apply Markov-switching vector autoregressive models to the economic system consisting of oil prices, clean energy and technology stock prices, and interest rates. The results indicate that there was a structural change in late 2007, a period in which there was a significant increase in the price of oil. In contrast to the previous studies, we find a positive relationship between oil prices and clean energy prices after structural breaks. There also appears to be a similarity in terms of the market response to both clean energy stock prices and technology stock prices. © 2013 Elsevier B.V.

CSI Lincoln : an investigation into a declining housing market

The residential property market in New Zealand has been experiencing a boom and bubble period from 2001 through to mid 2007. Following a number of increases in the Official Cash Rate by the Reserve Bank and a decline in net migration numbers the housing market was perceived to be over inflated and due for a major correction. Numerous media, Government Departments, property experts and economists have been predicting significant reductions in the median price of residential property throughout New Zealand. This paper will analyse house prices in specific socio-economic locations within Christchurch over the past 12 months to determine how significant the current housing decline is. This study will review the change in residential property prices, variations in property listings since April 2008, sale volumes and days on the market across a range of housing sectors to determine the extent and range of any residential property downturn in the NZ recession.

Stochastic modelling of financial time series with memory and multifractal scaling

Financial processes may possess long memory and their probability densities may display heavy tails. Many models have been developed to deal with this tail behaviour, which reflects the jumps in the sample paths. On the other hand, the presence of long memory, which contradicts the efficient market hypothesis, is still an issue for further debates. These difficulties present challenges with the problems of memory detection and modelling the co-presence of long memory and heavy tails. This PhD project aims to respond to these challenges. The first part aims to detect memory in a large number of financial time series on stock prices and exchange rates using their scaling properties. Since financial time series often exhibit stochastic trends, a common form of nonstationarity, strong trends in the data can lead to false detection of memory. We will take advantage of a technique known as multifractal detrended fluctuation analysis (MF-DFA) that can systematically eliminate trends of different orders. This method is based on the identification of scaling of the q-th-order moments and is a generalisation of the standard detrended fluctuation analysis (DFA) which uses only the second moment; that is, q = 2. We also consider the rescaled range R/S analysis and the periodogram method to detect memory in financial time series and compare their results with the MF-DFA. An interesting finding is that short memory is detected for stock prices of the American Stock Exchange (AMEX) and long memory is found present in the time series of two exchange rates, namely the French franc and the Deutsche mark. Electricity price series of the five states of Australia are also found to possess long memory. For these electricity price series, heavy tails are also pronounced in their probability densities. The second part of the thesis develops models to represent short-memory and longmemory financial processes as detected in Part I. These models take the form of continuous-time AR(∞) -type equations whose kernel is the Laplace transform of a finite Borel measure. By imposing appropriate conditions on this measure, short memory or long memory in the dynamics of the solution will result. A specific form of the models, which has a good MA(∞) -type representation, is presented for the short memory case. Parameter estimation of this type of models is performed via least squares, and the models are applied to the stock prices in the AMEX, which have been established in Part I to possess short memory. By selecting the kernel in the continuous-time AR(∞) -type equations to have the form of Riemann-Liouville fractional derivative, we obtain a fractional stochastic differential equation driven by Brownian motion. This type of equations is used to represent financial processes with long memory, whose dynamics is described by the fractional derivative in the equation. These models are estimated via quasi-likelihood, namely via a continuoustime version of the Gauss-Whittle method. The models are applied to the exchange rates and the electricity prices of Part I with the aim of confirming their possible long-range dependence established by MF-DFA. The third part of the thesis provides an application of the results established in Parts I and II to characterise and classify financial markets. We will pay attention to the New York Stock Exchange (NYSE), the American Stock Exchange (AMEX), the NASDAQ Stock Exchange (NASDAQ) and the Toronto Stock Exchange (TSX). The parameters from MF-DFA and those of the short-memory AR(∞) -type models will be employed in this classification. We propose the Fisher discriminant algorithm to find a classifier in the two and three-dimensional spaces of data sets and then provide cross-validation to verify discriminant accuracies. This classification is useful for understanding and predicting the behaviour of different processes within the same market. The fourth part of the thesis investigates the heavy-tailed behaviour of financial processes which may also possess long memory. We consider fractional stochastic differential equations driven by stable noise to model financial processes such as electricity prices. The long memory of electricity prices is represented by a fractional derivative, while the stable noise input models their non-Gaussianity via the tails of their probability density. A method using the empirical densities and MF-DFA will be provided to estimate all the parameters of the model and simulate sample paths of the equation. The method is then applied to analyse daily spot prices for five states of Australia. Comparison with the results obtained from the R/S analysis, periodogram method and MF-DFA are provided. The results from fractional SDEs agree with those from MF-DFA, which are based on multifractal scaling, while those from the periodograms, which are based on the second order, seem to underestimate the long memory dynamics of the process. This highlights the need and usefulness of fractal methods in modelling non-Gaussian financial processes with long memory.

An analysis of the Brisbane residential property market and the global financial crisis

The period from 2007 to 2009 covered the residential property boom from early 2000, to the property recession following the Global Financial Crisis. Since late 2008, a number of residential property markets have suffered significant falls in house prices, buth this has not been consistent across all market sectors. This paper will analyze the housing market in Brisbane Australia to determine the impact, similarities and differences that the4 GFC had on range of residential sectors across a divesified property market. Data analysis will provide an overview of residential property prices, sales and listing volumes over the study period and will provide a comparison of median house price performance across the geographic and socio-economic areas of Brisbane.

A dynamic approach to forecast rental growth

Numerous econometric models have been proposed for forecasting property market performance, but limited success has been achieved in finding a reliable and consistent model to predict property market movements over a five to ten year timeframe. This research focuses on office rental growth forecasts and overviews many of the office rent models that have evolved over the past 20 years. A model by DiPasquale and Wheaton is selected for testing in the Brisbane, Australia office market. The adaptation of this study did not provide explanatory variables that could assist in developing a reliable, predictive model of office rental growth. In light of this result, the paper suggests a system dynamics framework that includes an econometric model based on historical data as well as user input guidance for the primary variables. The rent forecast outputs would be assessed having regard to market expectations and probability profiling undertaken for use in simulation exercises. The paper concludes with ideas for ongoing research.

Tracking the Brisbane residential property market : Post GFC

Prior to the GFC, Brisbane and Perth were experiencing the highest increases in median residential house prices, compared to the other major Australian cities, due to strong demand for both owner occupied and investment residential property. In both these cities, a major driver of this demand and subsequent increases in residential property prices was the strong resources sector. With the onset of the GFC in 2008, the resources and construction sectors in Queensland contracted significantly and this had both direct and indirect impacts on the Brisbane residential property market. However, this impact was not consistent across Brisbane residential property sectors. The affect on houses and units differed, as did the impact based on geographic location and suburb value. This paper tracks Brisbane residential property sales listings, sales and returns over the period February 2009 to July 2010 and provides an analysis of the residential market for 24 Brisbane suburbs. These suburbs cover main residential areas of Brisbane and are based on an equal number of low, medium and high socioeconomic areas of Brisbane. This assessment of socio-economic status for the suburbs is based on both median household income and median house price. The analysis will cover both free standing residential property and residential units/townhouses/villas. The results will show how each of these residential property sub markets have performed following the GFC.

An analysis of NSW rural property market : 1990-2010

Rural property in Australia has seen significant market resurgence over the past 3 years, with improved seasonal conditions in a number of states, improved commodity prices and a greater interest and purchase of rural land by major international corporations and investment institutions. Much of this change in perspective in relation to rural property as an asset class can be linked to the food shortage of 2007 and the subsequent interest by many countries in respect to food security. This paper will address the total and capital return performance of a major agricultural area and compare these returns on the basis of both location of land and land use. The comparison will be used to determine if location or actual land use has a greater influence on rural property capital and income returns. This performance analysis is based on over 40,000 rural sales transactions. These transactions cover all market based rural property transactions in New South Wales, Australia for the period January 1990 to December 2010. Correlation analysis and investment performance analysis has also been carried out to determine the possible relationships between location and land use and subsequent changes in rural land capital values.

Beyond demand management : the value of sharing electricity information

Technologies such as smart meters and electricity feedback are becoming an increasingly compelling focus for HCI researchers in light of rising power prices and peak demand. We argue, however, that a pre-occupation with the goal of demand management has limited the scope of design for these technologies. In this paper we present our work-in-progress investigating the potential value of socially sharing electricity information as a means of broadening the scope of design for these devices. This paper outlines some preliminary findings gathered from a design workshop and a series of qualitative interviews with householders in Brisbane, Australia, regarding their attitudes towards electricity feedback and sharing consumption information. Preliminary findings suggest that; (1) the social sharing of electricity feedback information has the potential to be of value in better informing consumption decisions, however; (2) the potential for sharing may be constrained by attitudes towards privacy, trust and the possibility of misinformation being shared. We conclude by outlining ideas for our future research on this topic and invite comments on these ideas.

Occupant comfort, the housing industry and electricity infrastructure : understanding the synergies

Despite increasingly stringent energy performance regulations for new homes, southeast Queensland has a high and growing penetration of, and reliance on, air conditioners to provide thermal comfort to housing inhabitants. This reliance impacts on electricity infrastructure investment which is the key driving force behind rising electricity prices. This paper reports initial findings of a research project that seeks to better understand three key issues: (i) how families manage their thermal comfort in summer and how well their homes limit overheating; (ii) the extent to which the homes have been constructed according to the building approval documentation; and (iii) the impact that these issues have on urban design, especially in relation to electricity infrastructure in urban developments.

International stock market linkages : are overnight returns on the U.S. Market informative?

Based on the theory of international stock market co-movements, this study shows that a profitable trading strategy can be developed. The U.S. market return is considered as overnight information by ordinary investors in the Asian and the European stock markets, and opening prices in local markets reflect the U.S. overnight return. However, smart traders would either judge the impact of overnight information more correctly, or predict unreleased information. Thus, the difference between expected opening prices based on the U.S. return and actual opening prices is counted as smart traders’ prediction power, which is either a buy or a sell signal. Using index futures price data from 12 countries from 2000 to 2011, cumulative returns on the trading strategy are calculated with taking into account transaction costs. The empirical results show that the proposed trading strategy generates higher riskadjusted returns than that of the benchmarks in 12 sample countries. The trading performances for the Asian markets surpass those for the European markets because the U.S. return is the only overnight information for the Asian markets whereas the Asian markets returns are additional information to the European investors.

The Chinese state enterprise sector: Labour market reform and the impact on male–female wage structure

The paper examines the wage structure in the Chinese state enterprise sector between 1981 and 1987. This period is of particular interest given the introduction of major labour market reforms in China during the early 1980s. In essence the reforms represented a movement away from administratively determined prices towards a market–oriented system combined with a relatively flexible system of labour allocation. The Juhn, Murphy and Pierce (1991) decomposition is employed to shed light on the role of changing labour market institutions over the period.