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Forecasting Construction Cost Index based on visibility graph: A network approach

Author

Listed:
  • Zhang, Rong
  • Ashuri, Baabak
  • Shyr, Yu
  • Deng, Yong

Abstract

Engineering News-Record (ENR), a professional magazine in the field of global construction engineering, publishes Construction Cost Index (CCI) every month. Cost estimators and contractors assess projects, arrange budgets and prepare bids by forecasting CCI. However, fluctuations and uncertainties of CCI cause irrational estimations now and then. This paper aims at achieving more accurate predictions of CCI based on a network approach in which time series is firstly converted into a visibility graph and future values are forecasted relied on link prediction. According to the experimental results, the proposed method shows satisfactory performance since the error measures are acceptable. Compared with other methods, the proposed method is easier to implement and is able to forecast CCI with less errors. It is convinced that the proposed method is efficient to provide considerably accurate CCI predictions, which will make contributions to the construction engineering by assisting individuals and organizations in reducing costs and making project schedules.

Suggested Citation

  • Zhang, Rong & Ashuri, Baabak & Shyr, Yu & Deng, Yong, 2018. "Forecasting Construction Cost Index based on visibility graph: A network approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 493(C), pages 239-252.
    • Handle: RePEc:eee:phsmap:v:493:y:2018:i:c:p:239-252
    DOI: 10.1016/j.physa.2017.10.052
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    References listed on IDEAS

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    1. Kilian, Lutz & Taylor, Mark P., 2003. "Why is it so difficult to beat the random walk forecast of exchange rates?," Journal of International Economics, Elsevier, vol. 60(1), pages 85-107, May.
    2. Chen, Shiyu & Hu, Yong & Mahadevan, Sankaran & Deng, Yong, 2014. "A visibility graph averaging aggregation operator," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 403(C), pages 1-12.
    3. Armstrong, J. Scott & Overton, Terry S., 1977. "Estimating Nonresponse Bias in Mail Surveys," MPRA Paper 81694, University Library of Munich, Germany.
    4. Lü, Linyuan & Zhou, Tao, 2011. "Link prediction in complex networks: A survey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(6), pages 1150-1170.
    5. Zhang, G. Peter & Qi, Min, 2005. "Neural network forecasting for seasonal and trend time series," European Journal of Operational Research, Elsevier, vol. 160(2), pages 501-514, January.
    6. Liu, Chuang & Zhou, Wei-Xing & Yuan, Wei-Kang, 2010. "Statistical properties of visibility graph of energy dissipation rates in three-dimensional fully developed turbulence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(13), pages 2675-2681.
    7. Yang, Yue & Wang, Jianbo & Yang, Huijie & Mang, Jingshi, 2009. "Visibility graph approach to exchange rate series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(20), pages 4431-4437.
    8. Baabak Ashuri & Seyed Mohsen Shahandashti & Jian Lu, 2012. "Empirical tests for identifying leading indicators of ENR Construction Cost Index," Construction Management and Economics, Taylor & Francis Journals, vol. 30(11), pages 917-927, November.
    9. Dimitris Kirikos, 2000. "Forecasting exchange rates out of sample: random walk vs Markov switching regimes," Applied Economics Letters, Taylor & Francis Journals, vol. 7(2), pages 133-136.
    10. James Wong & Albert Chan & Y. H. Chiang, 2005. "Time series forecasts of the construction labour market in Hong Kong: the Box-Jenkins approach," Construction Management and Economics, Taylor & Francis Journals, vol. 23(9), pages 979-991.
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    Cited by:

    1. Dong-Rui Chen & Chuang Liu & Yi-Cheng Zhang & Zi-Ke Zhang, 2019. "Predicting Financial Extremes Based on Weighted Visual Graph of Major Stock Indices," Complexity, Hindawi, vol. 2019, pages 1-17, October.
    2. Fengchang Jiang & John Awaitey & Haiyan Xie, 2022. "Analysis of Construction Cost and Investment Planning Using Time Series Data," Sustainability, MDPI, vol. 14(3), pages 1-16, February.

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