A Numerical Approach for Quantifying Bi-directional Interactions between Macro Economic Indicators and Construction Industry

This article discusses a numerical approach for quantifying bidirectional interactions between economic indicators and the Turkish construction industry. The construction industry is a significant sector that has a substantial impact on economies, especially in terms of jobs and Gross domestic product (GDP). The article explores the relationship between the construction industry and macroeconomics, and uses macroeconomic models to analyze this relationship. The study focuses on Turkish construction industry and Turkish macro-economic datasets provided by Turkish Statistical Institute (TURKSTAT). The prediction model is constructed using Gradient Boosting algorithm, and sensitivity analysis based on improved Analytic Hierarchy Process (AHP) applied to capture model priority vector. The results show that some indicators can predict changes in construction prices, while others do not have predictive power. The article concludes by discussing the implications of these findings.