Stochastic Forecast of Construction Cost Index Using a Cointegrated Vector Autoregression Model

Xu, Jiang-wei; Moon, Soo Young

doi:10.1061/(asce)me.1943-5479.0000112

Cited by 71 publications

(35 citation statements)

References 24 publications

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“…Table 4.2 shows the indices that are related to construction project (e.g. Xu and Moon 2013;Hassanein and Khalil 2008), housing price (e.g. , consumer (Koster et al 2014) and environment (e.g.…”

Section: Indices Construction Methodsmentioning

confidence: 99%

Relevant Data in the Rising Tide of Big Data: A Text-Mining Analysis in Construction Safety Index

2014

Risk Engineering

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The previous generation of academia faced the problem of insufficient data, academic journal articles and books. Thanks to the rapid development of World Wide Web since 90s, academic papers published in one place can be viewed in another side of the globe, insufficient literature and data problems have been relieved. Modern academic researchers, however, face another major problem of big data. There are too many irrelevant articles. Much of the time has been spent to search for the relevant articles from the irrelevant ones. One of the major aims of this chapter is to review the problem of big data based on the example of construction safety index. Construction safety is an important issue Worldwide. The development of construction safety index is of particular importance as it provides an objective measurement on the level of safety on sites. This chapter reviews (1) how intelligence is the academic search engine in screening the relevant articles out the irrelevant materials, (2) compare and contrast the methods which are used to construct the construction safety indices with the other indices constructed worldwide.

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Section: Indices Construction Methodsmentioning

confidence: 99%

Relevant Data in the Rising Tide of Big Data: A Text-Mining Analysis in Construction Safety Index

2014

Risk Engineering

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“…β'X t -p , which is a linear combination of r, denotes disequilibrium error in the t-p point and influences {X t } in the next time point, t, by coefficient α. Therefore, the (n × r) coefficient matrix, α, is called the error modification coefficient [33]. In this study, the cointegration test was performed, and the VEC model was applied because the result confirmed the existence of cointegration.…”

Section: Methodsmentioning

confidence: 99%

“…If there is a long-term linear relation among them, i.e., cointegration, the VEC model can be used instead to perform the analysis [35]. The VEC model is a limited form of the VAR model when cointegration is available; therefore, this is a dynamic model in which the cointegration relation among time series is considered along with other short-term dynamic relationships [33].…”

Section: Methodsmentioning

confidence: 99%

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The Impact of Multinational Business Diversification on the Financial Sustainability of Construction Firms in Korea

2016

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This study investigated empirically whether multinational business diversification by Korean construction firms contributes to their financial sustainability using the vector error correction model. In this study, the current ratio and the debt ratio were used as proxy variables for financial sustainability. International construction orders and domestic construction orders were used as proxy variables for multinational business diversification for the analysis. Of the models used for analysis in this study, Model A used the current ratio and international and domestic construction orders, and Model B used the debt ratio and international and domestic construction orders. The time-series data utilized consisted of the quarterly data from Q1 of 2001 to Q4 of 2015. The results of the analysis imply that an increase in international construction orders undermines the financial viability of construction firms because of a decrease in the current ratio and an increase in the debt ratio. The results also show that the scrutinized analysis of profitability was insufficient because overseas project orders were not pursued based on a long-term business strategy but on short-term turnover. Therefore, Korean construction firms should recognize the overseas construction market as an independent market, not an alternative to the domestic market, and establish a long-term business strategy to enter overseas markets effectively to secure financial sustainability.

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“…Xu et al [14] pointed out that the building cost index had been widely used to measure the cost level of the construction industry. However, to improve the accuracy of measurement, the interaction between the cost indices and other variables (such as consumer price index) should be considered.…”

Section: Introductionmentioning

confidence: 99%

Cost Forecasting of Substation Projects Based on Cuckoo Search Algorithm and Support Vector Machines

Niu

Zhao

et al. 2018

Sustainability

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Accurate prediction of substation project cost is helpful to improve the investment management and sustainability. It is also directly related to the economy of substation project. Ensemble Empirical Mode Decomposition (EEMD) can decompose variables with non-stationary sequence signals into significant regularity and periodicity, which is helpful in improving the accuracy of prediction model. Adding the Gauss perturbation to the traditional Cuckoo Search (CS) algorithm can improve the searching vigor and precision of CS algorithm. Thus, the parameters and kernel functions of Support Vector Machines (SVM) model are optimized. By comparing the prediction results with other models, this model has higher prediction accuracy.

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Stochastic Forecast of Construction Cost Index Using a Cointegrated Vector Autoregression Model

Cited by 71 publications

References 24 publications

Relevant Data in the Rising Tide of Big Data: A Text-Mining Analysis in Construction Safety Index

Relevant Data in the Rising Tide of Big Data: A Text-Mining Analysis in Construction Safety Index

The Impact of Multinational Business Diversification on the Financial Sustainability of Construction Firms in Korea

Cost Forecasting of Substation Projects Based on Cuckoo Search Algorithm and Support Vector Machines

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