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.

Investigating relationships of construction prices in Australia using cointegration analysis

Research on construction prices is significant for contractors and traders. A comprehensive understanding of construction prices may influence crucial decisions in business operation and arbitrage activities. This study focuses on the cointegration relationships of regional construction prices in Australia by using a range of econometric techniques including the stationarity test, the Engle-Granger cointegration approach examines the long run equilibrium relationships within the regional markets, and the error correction models explore the short run disequilibrium relationships. Finds of this study reveal that the economic system in which the construction industry participants operate is characterized by a highly competitive, integrated marketplace, Especially in Melbourne and Sydney. But exclude Northern Territory and Queensland. Furthermore, the results of long term relationships estimation suggest that there are 15 pairs of regional construction prices have long term equilibrium relationships. Additionally, the causalities and diffusion among the construction price indices in six states and two territories of Australia are estimated in this study. These outcomes suggest that causal links between regions mainly exist among adjoining states.

lnvestigating spatial linkages of construction prices in Australia's regions

Linkages among different construction markets have attracted great of attention from the construction economist. With notable exceptions, most of this infestation has carried out by using input-output analysis. Interactions among regional construction markets have been discussed in few studies and none of them investigate spatial effects on the regional construction markets. This study employed spatial econometric techniques, spatial autocorrelation and convergence tests, to analysis interactions and linkages among construction price indices in Australian six states and two territories. The empirical results indicate the presence of significant positive spatial correlation between the construction prices in Australian eight construction markets and the degree of dependence decrease sufficiently quickly as the space between units increase. The results of convergence test further present evidence on "ripple effect" in the construction prices in Australian regional markets and the changes in regional construction price would positively influence neighboring states first, and then spread out into others, and then the regional prices converge and reach a long-run equilibrium in the following quarters. Urban development policymakers and construction developers could benefit from the analysis of spatial linkages in regional construction markets.

Sustainable construction : reliable forecasting for building construction prices

A reliable forecasting for future construction costs or prices would help to ensure the budget of a construction project can be well planned and limited resources can be allocated more appropriately in construction firms. Although many studies have been focused on the construction price modelling and forecasting, few researchers have considered the impacts of the global economic events and seasonality in price modelling and forecasting. In this study, an advanced multivariate modelling technique, namely the vector correction (VEC) model with dummy variables was employed and the impacts of the global economic event and seasonality were factored into the forecasting model for the building construction price in the Australian construction market. Research findings suggest that a long-run equilibrium relationship exists among the price, levels of supply and demand in the construction market. The reliability of forecasting models was examined by mean absolute percentage error (MAPE) and The Theil's inequality coefficient U tests. The results of MAPE and U tests suggest that the conventional VEC model and the VEC model with dummy variable are both acceptable for forecasting building construction prices, while the VEC model that considered external impacts achieves higher prediction accuracy than the conventional VEC model does.

Market effects on forecasting construction prices using vector error correction models

Construction price forecasting is an essential component to facilitate decision-making for construction contractors, investors and related financial institutions. Construction economists are increasingly interested in seeking a more analytical method to forecast construction prices. Although many studies have focused on construction price modelling and forecasting, few have considered the impacts of large-scale economic events and seasonality. In this study, an advanced multivariate modelling technique, namely the vector correction (VEC) model with dummy variables, was employed. The impacts of global economic events and seasonality are factored into the model to forecast the construction price in the Australian construction market. Research findings suggest that both long-run and dynamic short-term causal relationships exist among the price and levels of supply and demand in the construction market. These relationships drive the construction price and supply and demand, which interact with one another as a loop system. The reliability of forecasting models was examined by the mean absolute percentage error (MAPE) and the Theil's inequality coefficient U tests. The test results suggest that the conventional VEC model and the VEC model with dummy variable are both acceptable for forecasting the construction price, while the VEC model considering external impacts achieves higher prediction accuracy than the conventional VEC model. © 2014 © 2014 Taylor & Francis.

An economic analysis of construction industries producer prices in Australia

Research on construction prices is significant for contractors and traders. A comprehensive understanding of construction prices may influence crucial decisions in business operation and arbitrage activities. This study focuses on the cointegration relationships of regional construction prices in Australia by using a range of econometric techniques including the stationarity test, the Engle-Granger cointegration approach and error correction model. The cointegration relationships amongst the regional construction prices are detected in this study. The application of the Engle-Granger cointegration approach examines the long run equilibrium relationships within the regional markets, and the error correction models explore the short run disequilibrium relationships. Results of this study suggest that the economic system in which construction industry participants operate is characterised by a highly competitive integrated marketplace. Furthermore, the causalities and diffusion patterns among the construction price indices in six states and two territories of Australia are drawn by the cointegration analysis. These outcomes reveal a pattern of diffusion paths and network linkages among the six states and two territories, and then expose the regional price linkages.

Convergence among the sub-markets in Australian regional building and construction sector

Studies on market convergence are well considered in the literature. However, the majority of the previous research focused on housing markets and few studies have concentrated on construction markets. Owing to a simultaneously dramatic increase in the construction prices of the sub-markets in the building construction sector in Australia, this paper aims to identify the convergence among these markets, involving house construction market, other-residential building construction market, and non-residential building construction market. To achieve it the Granger causality test and generalized response function depending on the vector error correction model with the quarterly data of Australia’s eight states from 1998 to 2010 will be applied. Based upon the econometric tests, the price diffusion patterns among these construction markets have been identified. Research on the convergences of construction markets not only helps construction firms perform well in business operations and arbitrage activities, but also provides policy makers with useful information for enacting effective construction policies for national perspectives and approaches to infrastructure planning.

Spatial linkages among Australian construction markets

The linkages among different construction markets have recently attracted much attention from construction economists. The interactions among regional construction markets have been discussed in a few studies, most of which have been carried out by using input-output methods, and none of them investigated spatial effects on the regional construction markets. This study employed spatial econometric techniques, including spatial autocorrelation and convergence tests, to analyse interactions and linkages among construction price indices in Australian six states and two territories. The empirical results indicate the presence of significant positive spatial correlation among the construction prices in Australian eight construction markets and the degree of dependence decreasing sufficiently quickly as the space between regions increases. The results of convergence test further provide evidence of existence of a ripple effect in construction prices among the Australian regional markets and the changes in construction prices in a state would first positively influence neighbouring states, and then spread out into other non-neighbouring states or territories.

The effect of increased water prices on construction

The research aimed to investigate the effect an increase in water prices would have on construction. It was found that while there is a considerable amount of water embodied in construction the actual effect of a water tax on construction would be minimal unless implemented at the highest rate.

Railroad construction guide prices.

Oct. 1, 1945.

Multi-Outcome Construction Policies : Industry-Focused Research Summary

The Multi-outcomes Construction Policies research project, funded by the Cooperative Research Centre for Construction Innovation (Project 2006-036-A), sought to explore the costs and benefits of leveraging social outcomes on public construction contracts. The context of the research project was the trend towards the contracting out of public construction works and the attempts that have been made to use new contractual arrangements with construction companies to construction achieve a wide range of social outcomes. In federal and state jurisdictions it is now common for governments to impose a range of additional requirements on public works contractors that relate to broad social/community objectives. These requirements include commitments to train apprentices and trainees; to provide local and/or indigenous employment opportunities; to buy local materials; and to include art works. The cost and benefits of using public construction contracts to achieve social/community goals have, to our knowledge, not been thoroughly researched in an Australian context. This is likely to reflect in large part the relatively short history of contracting out public works. As Jensen and Stonecash (2004) explain, most previous empirical studies of contracting out have attempted to measure the cost savings achieved through privatization, as this was the focus of policy debate in the 1980s and 1990s. Relatively few studies have addressed the ability of contracting arrangements to ensure the delivery of desired ‘quality’ outcomes1, or the costs of achieving these outcomes via contracting arrangements. One of the potential costs of attempting to leverage social/community outcomes on public construction projects is a reduction in the amount of competition for these projects, with obvious consequences for average bid prices and choice. In jurisdictions, such as Western Australia and Queensland, where currently construction market conditions are already

The Profiling of Property, Plant & Equipment (PPE) Contributions in Australia and Malaysia Public Listed Construction Companies

The purpose of this paper is to study the profiling of property, plant and equipment (PPE) contributions in Australia and Malaysia construction companies. A company’s worth is usually based on the listed share price on the stock exchange. In arriving at the net profit, the contribution of PPE in the company’s assets is somehow being neglected. This paper will investigate the followings; firstly the level of PPE contribution in the construction firms by comparing the PPE contributions to the company’s asset as a whole which includes fixed (non-current) assets and current assets. This will determine the true strength of the companies, rather than relying on the share prices alone. Secondly, the paper will determine the trend of company’s asset ownership to show the company’s performance of the PPE ownership during the period of study. The data is based on the selected construction companies listed on the Australian Stock Exchange (ASX) and Malaysian Stock Exchange, known as Bursa Malaysia. The profiling will help to determine the strength of the construction firms based on the PPE holding, and the level of PPE ownerships in the two countries construction firms during the period of study.

Predicting freeway pavement construction cost using a back-propagation neural network : a case study in Henan, China

The objective of this research was to develop a model to estimate future freeway pavement construction costs in Henan Province, China. A comprehensive set of factors contributing to the cost of freeway pavement construction were included in the model formulation. These factors comprehensively reflect the characteristics of region and topography and altitude variation, the cost of labour, material, and equipment, and time-related variables such as index numbers of labour prices, material prices and equipment prices. An Artificial Neural Network model using the Back-Propagation learning algorithm was developed to estimate the cost of freeway pavement construction. A total of 88 valid freeway cases were obtained from freeway construction projects let by the Henan Transportation Department during the period 1994−2007. Data from a random selection of 81 freeway cases were used to train the Neural Network model and the remaining data were used to test the performance of the Neural Network model. The tested model was used to predict freeway pavement construction costs in 2010 based on predictions of input values. In addition, this paper provides a suggested correction for the prediction of the value for the future freeway pavement construction costs. Since the change in future freeway pavement construction cost is affected by many factors, the predictions obtained by the proposed method, and therefore the model, will need to be tested once actual data are obtained.