Applied causal inference in regional economic-behavioral models of business decision making

Recently, behavioral operations research researchers have experienced increased interest in models based on causal inference, and the authors note a dearth of observational studies in national real estate markets. The present study fills this gap. His research hypotheses concern the benefits of incorporating behavioral factors into models of decision-making systems and optimizing the instrumental policies of companies. The work has both scientific and applied significance. The novelty of the work lies in the use of advanced machine learning methods to estimate the conditional causal effect.