Predicting construction market growth for urban metropolis: An econometric analysis

Fan, Ryan Y.C.; Ng, S. Thomas; Wong, Johnny

doi:10.1016/j.habitatint.2010.08.002

Cited by 22 publications

(16 citation statements)

References 43 publications

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“…Both of these measurements indicate that forecasting accuracy of these ARDL models is very satisfactory and notably higher than several previous studies (e.g. Fan et al, 2010Fan et al, , 2011Jiang and Liu, 2011).…”

Section: Impact Of Property Pricementioning

confidence: 46%

“…In previous studies, GVC has been widely adopted as a proxy of construction output or demand (e.g. Chau, 1993;Tse and Ganesan, 1997;Yiu et al, 2004;Fan et al, 2010Fan et al, , 2011. In this study, we use two disaggregated sets of data of GVC, which are GVC of residential buildings (GVCH) and of retail buildings (GVCR).…”

Section: Gross Value Of Construction (Gvc)mentioning

confidence: 99%

“…In order to measure the forecast reliability, we employ two widely used measurements to evaluate the forecasting accuracy of ARDL models (e.g. Fan et al, 2010Fan et al, , 2011Jiang and Liu, 2011). The first one is the mean absolute percentage error (MAPE), which is acceptable if the magnitude of MAPE is smaller than 10%.…”

Section: Impact Of Property Pricementioning

confidence: 99%

“…For instance,Fan et al (2010) employ the Box-Jenkins approach to predict the construction demands of different property sectors in Hong Kong Jiang and Liu (2011). adopt the vector error correction (VEC) model to predict demand in the Australian construction market (seeFan et al, 2011 for another application of VEC model in Hong Kong construction demand prediction).…”

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confidence: 99%

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The impact of property price on construction output

Zheng

Chau

Hui

2012

Construction Management and Economics

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The interaction between the construction market and the overall economy has attracted much attention, but few studies have investigated the influence of the property market on the construction market in terms of property price. The disaggregated data of Hong Kong's housing and retail construction sectors are collected to investigate the impact of property price on construction output. The newly developed autoregressive distributed lag (ARDL) bounds testing approach and the error correction (EC)-based Granger causality test are employed. The bounds testing results suggest that there exist stable long-run relationships between construction output and property price for both housing and retail construction sectors. Specifically, a 1.00% increase in the housing price and retail price lead to a 0.55% and 0.42% increase in construction outputs for the two sectors respectively. In addition, the Granger causality tests confirm a distinct long-run causal flow from property price to construction output. Furthermore, the proposed ARDL approach provides an effective method for forecasting construction output.

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Section: Impact Of Property Pricementioning

confidence: 46%

Section: Gross Value Of Construction (Gvc)mentioning

confidence: 99%

Section: Impact Of Property Pricementioning

confidence: 99%

mentioning

confidence: 99%

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The impact of property price on construction output

Zheng

Chau

Hui

2012

Construction Management and Economics

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“…To meet the high quality standards set for the construction statistics, the statistics producers should not only produce statistics with a level of quality that meets user needs, but also be transparent about the methodological process by providing information on adopted methodologies and on any biases or other quality issues in the exiting statistics. Apart from these, construction economists readily single out the uniqueness of linkages between construction and the economy (Budiwibowo, Trigunarsyaj, Abidin, & Oeparto, 2009;Fan et al, 2010;Fan, Ng, & Wong, 2011;Giang & Pheng, 2011;Wong et al, 2010). The portrait of the role of construction in the economy is therefore a significant responsibility of construction statistics upon which they can be evaluated.…”

Section: Introductionmentioning

confidence: 99%