Empirical tests for identifying leading indicators of ENR Construction Cost Index

被引：56

作者：

Ashuri, Baabak ^{[1
]}

Shahandashti, Seyed Mohsen ^{[1
]}

Lu, Jian ^{[1
]}

机构：

[1] Georgia Inst Technol, Sch Bldg Construct, ESBE Lab, 280 Ferst Dr,First Floor, Atlanta, GA 30332 USA

来源：

CONSTRUCTION MANAGEMENT AND ECONOMICS | 2012年 / 30卷 / 11期

关键词：

Cointegration; cost estimation; ENR Construction Cost Index; Granger causality; leading indicator;

D O I：

10.1080/01446193.2012.728709

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

Engineering News-Record (ENR) publishes its Construction Cost Index (CCI) monthly. CCI is the weighted average price of construction activities in 20 United States (US) cities. CCI has widely been used for cost estimation, bid preparation and investment planning. Cost estimators and investment planners are not only interested in the current CCI, but also are interested in forecasting changes in CCI trends. However, CCI is subject to significant variations that are difficult to predict. An important step towards forecasting CCI trends is to identify its leading indicators. The research objective is to identify the leading indicators of CCI using empirical tests. The results of Granger causality tests show that consumer price index, crude oil price, producer price index, GDP, employment levels in construction, number of building permits, number of housing starts and money supply are the leading indicators of CCI. The results of Johansen's cointegration tests show that money supply and crude oil price are the leading indicators with long-term relationships with CCI. These findings contribute to the body of knowledge in CCI forecasting. CCI can be predicted more accurately using its leading indicators. Cost estimators and capital project planners can benefit from better forecasting through reduction in uncertainty about future construction costs.

引用

页码：917 / 927

页数：11

共 29 条

[1] NEW LOOK AT STATISTICAL-MODEL IDENTIFICATION [J].