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.

Do spatial effects drive house prices away from the long-run equilibrium?

Long-run equilibrium of house prices has been investigated by researchers in multiple countries. The identification of this equilibrium not only provides references against contemporary house price levels, but also contributes to creation of stable-development policies and healthy investment strategies. However, there is little research investigating the factors that drive house prices away from the long-run equilibrium.
Based on a framework of the conventional stationarity test process, this research develops a panel regression model and a spatial regression model to investigate the roles of spatial heterogeneity and correlations on house prices preceding the long-run equilibrium, respectively. Housing data generated from the capital cities in Australia are used to illustrate the models. Spatial effects can have a strong influence in the long-run performance of house prices, while the short-run performance of house prices is not influenced by the spatial effects.

Generic drug prices and policy in Australia: room for improvement? A comparative analysis with England

To assess the degree to which reimbursement prices in Australia and England differ for a range of generic drugs, and to analyse the supply- and demand-side factors that may contribute to these differences.

A scalable and automatic mechanism for resource allocation in self-organizing cloud

Taking advantage of the huge potential of consumers’ untapped computing power, self-organizing cloud is a novel computing paradigm where the consumers are able to contribute/sell their computing resources. Meanwhile, host machines held by the consumers are connected by a peer-to-peer (P2P) overlay network on the Internet. In this new architecture, due to large and varying multitudes of resources and prices, it is inefficient and tedious for consumers to select the proper resource manually. Thus, there is a high demand for a scalable and automatic mechanism to accomplish resource allocation. In view of this challenge, this paper proposes two novel economic strategies based on mechanism design. Concretely, we apply the Modified Vickrey Auction (MVA) mechanism to the case where the resource is sufficient; and the Continuous Double Auction (CDA) mechanism is employed when the resource is insufficient. We also prove that aforementioned mechanisms have dominant strategy incentive compatibility. Finally, extensive experiment results are conducted to verify the performance of the proposed strategies in terms of procurement cost and execution efficiency.

Changes in use of types of tobacco products by pack sizes and price segments, prices paid and consumption following the introduction of plain packaging in Australia

Objectives: To describe changes among smokers in use of various types of tobacco products, reported prices paid and cigarette consumption following the standardisation of tobacco packaging in Australia.
Methods: National cross-sectional telephone surveys of adult smokers were conducted from April 2012 (6 months before transition to plain packaging (PP) to March 2014 (15 months afterwards). Multivariable logistics regression assessed changes in products, brands and pack types/sizes; multivariable linear regression examined changes in inflation-adjusted prices paid and reported cigarette consumption between the pre-PP and three subsequent periods – the transition phase, PP year 1 and PP post-tax (post a 12.5% tax increase in December 2013).
Results: The proposition of current smokers using roll-your-own (RYO) products fluctuated over the study period. Proportions using value brands of factory-made (FM) cigarettes increased from pre-PP (21.4%) to PP year 1 (25.5%; p=0.002) and PP post-tax (27.8%; p<0.001). Inflation-adjusted prices paid increased in the PP year 1 and PP post-tax phases; the largest increases were among premium FM brands, the smallest among value brands. Consumption did not change in PP year 1 among daily, regular or current smokers declined significantly in PP post-tax (mean=14.0, SE=0.33) compared to PP year 1 (mean=14.8, SE=0.17; p=0.037).
Conclusions: Introduction of PP was associated with an increase in use of value brands, likely due to increased numbers available and smaller increases in prices for value relative to premium brands. Reported consumption declined following the December 2013 tax increase.

Prediction interval estimation of electricity prices using PSO-tuned support vector machines

Uncertainty of the electricity prices makes the task of accurate forecasting quite difficult for the electricity market participants. Prediction intervals (PIs) are statistical tools which quantify the uncertainty related to forecasts by estimating the ranges of the future electricity prices. Traditional approaches based on neural networks (NNs) generate PIs at the cost of high computational burden and doubtful assumptions about data distributions. In this work, we propose a novel technique that is not plagued with the above limitations and it generates high-quality PIs in a short time. The proposed method directly generates the lower and upper bounds of the future electricity prices using support vector machines (SVM). Optimal model parameters are obtained by the minimization of a modified PI-based objective function using a particle swarm optimization (PSO) technique. The efficiency of the proposed method is illustrated using data from Ontario, Pennsylvania-New Jersey-Maryland (PJM) interconnection day-ahead and real-time markets.

Farmland prices, structural breaks and panel data

Previous time series evidence has indicated that farmland prices and cash rents are not cointegrated, a finding at odds with the present value model of farmland prices. We argue that this failure to find cointegration may be due to low power of tests and to the presence of structural change representing a shifting risk premium on farmland investments. To accommodate this possibility, we use panel unit root and cointegration methods that are more powerful than conventional time series methods and allow for breaks in the cointegration relationship. Our results, based on a large panel covering 31 US states between 1960 and 2000, suggest that the present value model of farmland prices cannot be rejected. © Oxford University Press and Foundation for the European Review of Agricultural Economics 2007; all rights reserved.

Call auction transparency and market liquidity: Evidence from China

This paper uses the natural experiment offered by the Shanghai Stock Exchange to investigate the impact of opening call auction transparency on market liquidity. We find that the dissemination of indicative trade information during the pre-open call auction session leads to an overall improvement in stock liquidity in the continuous trading session. Bid-ask spreads narrow in the first trading hour because adverse selection risk fell significantly and there is less price volatility in the continuous market. This effect is greater for actively traded securities than illiquid securities. Our findings are robust for different lengths of sample period, different lengths of trading hours after market open, and stocks that had (and had not) reformed the share split structure during our research period.

Perks and the informativeness of stock prices in the Chinese market

While the literature shows that perks can affect firm values positively or negatively, we argue that firms with higher perks are more likely to be associated with a lower quality of financial reporting, which, in turn, can affect the informativeness of stock prices. Based on hand-collected data on perks from Chinese listed firms, we find that firms with lower perks are associated with higher informativeness of stock prices (or lower R-square). Moreover, the positive association between perks and R-square is shown to be weaker for firms with higher financial reporting quality through audit and earnings quality measures.

Does board gender diversity improve the informativeness of stock prices?

We show that stock prices of firms with gender-diverse boards reflect more firm-specific information after controlling for corporate governance, earnings quality, institutional ownership and acquisition activity. Further, we show that the relationship is stronger for firms with weak corporate governance suggesting that gender-diverse boards could act as a substitute mechanism for corporate governance that would be otherwise weak. The results are robust to alternative specifications of informativeness and gender diversity and to sensitivity tests controlling for time-invariant firm characteristics and alternative measures of stock price informativeness. We also find that gender diversity improves stock price informativeness through the mechanism of increased public disclosure in large firms and by encouraging private information collection in small firms. © 2011 Elsevier B.V.

Counting the cost: the impact of cinema ticket prices in Australia

The authors discuss the change in cinema ticket price and its effect on audience perception on cinema attendance in Australia. Topics discussed include the comparison of ticket prices in Australia to countries such as the U.S., Japan, and New Zealand, the reason of high ticket prices in Australia such as high wages in theatre operation and piracy, and the drop of cinema admission as result of high ticket prices. They mention the social equity issues raised by the high cost of cinema tickets.