Identifying determinants of demand for construction using an econometric approach

Economic variation and its effects on construction demand have received a great deal of attention in construction economics studies. An understanding of future trends in demand for construction could influence investment strategies for a variety of parties, including construction developers, suppliers, property investors and financial institutions. This paper derives the determinants of demand for construction in Australia using an econometric approach to identify and evaluate economic indicators that affect construction demand. The forecasting contribution of different determinants of economic indicators and their categories to the demand for construction are further estimated. The results of this empirical study suggest that changes in consumer’s expectation, income and production, and demography and labour force are closely correlated with the movement of construction demand; and 14 economic indicators are identified as the determinants for construction demand. It was found that the changes in construction price, national income, size of population, unemployment rate, value or export, household expenditure and interest rates play key roles in explaining future variations in the demand for construction in Australia. Some “popular” macroeconomic indicators, such as GDP, established house price and bank loans produced inconclusive results.

Construction labor productivity convergence: a conditional frontier approach

Purpose-Understanding and simulating construction activities is a vital issue from a macro-perspective, since construction is an important contributor in economic development. Although the construction labor productivity frontier has attracted much research effort, the temporal and regional characteristics have not yet been explored. The purpose of this paper is to investigate the long-run equilibrium and dynamics within construction development under a conditional frontier context. Design/methodology/approach-Analogous to the simplified production function, this research adopts the conditional frontier theory to investigate the convergence of construction labor productivity across regions and over time. Error correction models are implemented to identify the long-run equilibrium and dynamics of construction labor productivity against three types of convergence hypotheses, while a panel regression method is used to capture the regional heterogeneity. The developed models are applied to investigate and simulate the construction labor productivity in the Australian states and territories. Findings-The results suggest that construction labor productivity in Australia should converge to stable frontiers in a long-run perspective. The dynamics of the productivity are mainly caused by the technology utilization efficiency levels of the local construction industry, while the influences of changes in technology level and capital depending appear limited. Five regional clusters of the Australian construction labor productivity are suggested by the simulation results, including New South Wales; Australian Capital Territory; Northern Territory, Queensland, and Western Australia; South Australia; and Tasmania and Victoria. Originality/value-Three types of frontier of construction labor productivity is proposed. An econometric approach is developed to identify the convergence frontier of construction labor productivity across regions over time. The specified model can provides accurate predictions of the construction labor productivity.

Determination of long-run and short-run dynamics in EC-VARMA models via canonical correlations

This article studies a simple, coherent approach for identifying and estimating error-correcting vector autoregressive moving average (EC-VARMA) models. Canonical correlation analysis is implemented for both determining the cointegrating rank, using a strongly consistent method, and identifying the short-run VARMA dynamics, using the scalar component methodology. Finite-sample performance is evaluated via Monte Carlo simulations and the approach is applied to modelling and forecasting US interest rates. The results reveal that EC-VARMA models generate significantly more accurate out-of-sample forecasts than vector error correction models (VECMs), especially for short horizons.

Detection and classification of anomaly intrusion using hierarchy clustering and SVM

Anomaly detection as a kind of intrusion detection is good at detecting the unknown attacks or new attacks, and it has attracted much attention during recent years. In this paper, a new hierarchy anomaly intrusion detection model that combines the fuzzy c-means (FCM) based on genetic algorithm and SVM is proposed. During the process of detecting intrusion, the membership function and the fuzzy interval are applied to it, and the process is extended to soft classification from the previous hard classification. Then a fuzzy error correction sub interval is introduced, so when the detection result of a data instance belongs to this range, the data will be re-detected in order to improve the effectiveness of intrusion detection. Experimental results show that the proposed model can effectively detect the vast majority of network attack types, which provides a feasible solution for solving the problems of false alarm rate and detection rate in anomaly intrusion detection model.

Decomposition of temporal changes in construction labour productivity

Construction productivity is recognized as an indicator reflecting the performance efficiency and competitiveness of the industry. A large amount of research has been carried out focusing on the decomposition of the influential factors and the temporal trends of construction productivity changes, respectively. However, the decomposition of the temporal changes in construction labour productivity has not yet been explored. Analogous to the framework of the productivity frontier, this research argues for a four-component decomposition of the temporal changes in construction labour productivity, including technology, technology-utilization efficiency, the capital-labour ratio and production capacity. An error correction model is subsequently estimated using the panel data regression method to investigate the effects of these components on the temporal changes in construction productivity across a sample of the Australian construction industry. The empirical results con?rm that the effects of the four components on the temporal changes in construction productivity changes vary over the observed time periods. From the aggregate level, the technology-utilization efficiency and capital-labour ratio across the regions are found to be barriers to growth in Australian construction productivity. Nevertheless, the effects of technology-utilization efficiency and production capacity varied significantly over the three sub-periods, when innovative national economic systems were introduced.

Prevalence of visual impairment and uncorrected refractive error - report from a Canadian urban population-based study

The prevalence of visual impairment due to uncorrected refractive error has not been previously studied in Canada. A population-based study was conducted in Brantford, Ontario. The target population included all people 40 years of age and older. Study participants were selected using a randomized sampling strategy based on postal codes. Presenting distance and near visual acuities were measured with habitual spectacle correction, if any, in place. Best corrected visual acuities were determined for all participants who had a presenting distance visual acuity of less than 20/25. Population weighted prevalence of distance visual impairment (visual acuity <20/40 in the better eye) was 2.7% (n = 768, 95% confidence interval (CI) 1.8–4.0%) with 71.8% correctable by refraction. Population weighted prevalence of near visual impairment (visual acuity <20/40 with both eyes) was 2.2% (95% CI 1.4–3.6) with 69.1% correctable by refraction. Multivariable adjusted analysis showed that the odds of having distance visual impairment was independently associated with increased age (odds ratio, OR, 3.56, 95% CI 1.22–10.35; ≥65 years compared to those 39–64 years), and time since last eye examination (OR 4.93, 95% CI 1.19–20.32; ≥5 years compared to ≤2 years). The same factors appear to be associated with increased prevalence of near visual impairment but were not statistically significant. The majority of visual impairment found in Brantford was due to uncorrected refractive error. Factors that increased the prevalence of visual impairment were the same for distance and near visual acuity measurements.