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    Studying the Relationship between Stock Prices of Publicly Traded US Construction Companies and Gross Domestic Product: Preliminary Step toward Construction–Economy Nexus

    Source: Journal of Construction Engineering and Management:;2020:;Volume ( 146 ):;issue: 001
    Author:
    Islam H. El-adaway
    ,
    Gasser G. Ali
    ,
    Ibrahim S. Abotaleb
    ,
    Herbert M. Barber
    DOI: 10.1061/(ASCE)CO.1943-7862.0001742
    Publisher: ASCE
    Abstract: Many scholars from multiple professional and academic disciplines have investigated the various links between the construction industry and economic output. Nevertheless, there remains a noticeable dearth of studies that address the potential impact of the players within the construction industry on various economic indicators. The goal of this research is to study how the economic performance of the US—measured in GDP—is impacted by the performance of the construction industry and its key players and how the performance of the construction industry could help in forecasting future US GDP. This goal is achieved by studying the relationship between GDP, total construction spending (TTLCONS), the Standard and Poor’s 500 (S&P500) index (GSPC), and the stocks of major publicly traded construction companies. The authors applied an interdependent research methodology that included (1) data collection, (2) statistical testing on the data using correlation analysis and Granger causality testing, and (3) vector autoregression (VAR) for both fitting and prediction purposes. A positive correlation was found between GDP, the S&P500, TTLCONS, and the stocks of major publicly traded construction-related companies. Also, the Granger causality test showed that some major construction company stocks are useful in forecasting GDP. The developed VAR model was used to forecast GDP for 2 years with acceptable accuracy. In this connection, the model was validated by successfully forecasting in a retrospective manner the effect of the 2008 financial crisis. This shows that the stock prices of select publicly traded construction and equipment companies can be used to predict GDP. In fact, a similar model could have been used to predict the 2008 economic collapse and develop ex ante mitigation strategies. The findings of this study could open opportunities for abandoning the notion of studying the construction industry solely using the health of residential construction. As such, this research should help in moving toward the development of a construction–economy nexus.
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      Studying the Relationship between Stock Prices of Publicly Traded US Construction Companies and Gross Domestic Product: Preliminary Step toward Construction–Economy Nexus

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4268265
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    contributor authorIslam H. El-adaway
    contributor authorGasser G. Ali
    contributor authorIbrahim S. Abotaleb
    contributor authorHerbert M. Barber
    date accessioned2022-01-30T21:28:30Z
    date available2022-01-30T21:28:30Z
    date issued1/1/2020 12:00:00 AM
    identifier other%28ASCE%29CO.1943-7862.0001742.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4268265
    description abstractMany scholars from multiple professional and academic disciplines have investigated the various links between the construction industry and economic output. Nevertheless, there remains a noticeable dearth of studies that address the potential impact of the players within the construction industry on various economic indicators. The goal of this research is to study how the economic performance of the US—measured in GDP—is impacted by the performance of the construction industry and its key players and how the performance of the construction industry could help in forecasting future US GDP. This goal is achieved by studying the relationship between GDP, total construction spending (TTLCONS), the Standard and Poor’s 500 (S&P500) index (GSPC), and the stocks of major publicly traded construction companies. The authors applied an interdependent research methodology that included (1) data collection, (2) statistical testing on the data using correlation analysis and Granger causality testing, and (3) vector autoregression (VAR) for both fitting and prediction purposes. A positive correlation was found between GDP, the S&P500, TTLCONS, and the stocks of major publicly traded construction-related companies. Also, the Granger causality test showed that some major construction company stocks are useful in forecasting GDP. The developed VAR model was used to forecast GDP for 2 years with acceptable accuracy. In this connection, the model was validated by successfully forecasting in a retrospective manner the effect of the 2008 financial crisis. This shows that the stock prices of select publicly traded construction and equipment companies can be used to predict GDP. In fact, a similar model could have been used to predict the 2008 economic collapse and develop ex ante mitigation strategies. The findings of this study could open opportunities for abandoning the notion of studying the construction industry solely using the health of residential construction. As such, this research should help in moving toward the development of a construction–economy nexus.
    publisherASCE
    titleStudying the Relationship between Stock Prices of Publicly Traded US Construction Companies and Gross Domestic Product: Preliminary Step toward Construction–Economy Nexus
    typeJournal Paper
    journal volume146
    journal issue1
    journal titleJournal of Construction Engineering and Management
    identifier doi10.1061/(ASCE)CO.1943-7862.0001742
    page10
    treeJournal of Construction Engineering and Management:;2020:;Volume ( 146 ):;issue: 001
    contenttypeFulltext
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