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Prediction of Egypt’s Construction Industry Resilience
The Covid-19 pandemic has affected industries globally: many have regressed due to stoppages, others have flourished, while some have remained dormant. The construction industry’s nature as “labor intensive” has forced some governments to allow its continuation through lockdowns and unstable times. Overall economic conditions can be explained through macroeconomic indicators as CPI, PPI, stock market indices, and unemployment rate. Construction industry’s output can be interpreted from indicators as the country’s GDP from construction. In Egypt, while Covid-19 impact has hit the economy, the overall GDP growth rate has dropped for the first time in nine years from 5% to –1.7%, while the GDP from construction has not been significantly affected presenting high resiliency. This research aims to propose a neural networks model to predict construction industry’s resilience, explained through GDP from construction, using lagged macroeconomic indicators as predictors. Granger causality test is utilized to identify which macroeconomic indicators can be the leading indicators of the GDP from construction up to three quarters ahead. Data in Egypt from June 2008 to December 2020 are used as the study domain. Results show that although long term correlation exists, construction industry in Egypt can be classified as a resilient one. Such an approach can be applied on global markets providing the ability to predict resilience of an industry during economic shocks and unstable times, which would better prepare governments, investors, and shareholders.
Prediction of Egypt’s Construction Industry Resilience
The Covid-19 pandemic has affected industries globally: many have regressed due to stoppages, others have flourished, while some have remained dormant. The construction industry’s nature as “labor intensive” has forced some governments to allow its continuation through lockdowns and unstable times. Overall economic conditions can be explained through macroeconomic indicators as CPI, PPI, stock market indices, and unemployment rate. Construction industry’s output can be interpreted from indicators as the country’s GDP from construction. In Egypt, while Covid-19 impact has hit the economy, the overall GDP growth rate has dropped for the first time in nine years from 5% to –1.7%, while the GDP from construction has not been significantly affected presenting high resiliency. This research aims to propose a neural networks model to predict construction industry’s resilience, explained through GDP from construction, using lagged macroeconomic indicators as predictors. Granger causality test is utilized to identify which macroeconomic indicators can be the leading indicators of the GDP from construction up to three quarters ahead. Data in Egypt from June 2008 to December 2020 are used as the study domain. Results show that although long term correlation exists, construction industry in Egypt can be classified as a resilient one. Such an approach can be applied on global markets providing the ability to predict resilience of an industry during economic shocks and unstable times, which would better prepare governments, investors, and shareholders.
Prediction of Egypt’s Construction Industry Resilience
Shiha, Ahmed (author) / Dorra, Elkhayam M. (author)
Construction Research Congress 2022 ; 2022 ; Arlington, Virginia
Construction Research Congress 2022 ; 361-369
2022-03-07
Conference paper
Electronic Resource
English
Prediction of Egypt’s Construction Industry Resilience
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