Oxford Economics has elevated its real estate analytics by integrating 40 years of MSCI historical data into its Real Estate Economics Service and Global Economic Model. This development offers clients an enriched platform to analyse trends, compare past cycles, and stress-test scenarios, redefining strategic planning for an evolving real estate market. The enhancement enables sophisticated forecasting, ensuring businesses can align decisions with historical context while planning for future market dynamics.
According to George Armitage, Managing Director of Global Real Estate at Oxford Economics, “Anticipating the future requires learning from the past.” This philosophy underpins the integration, which bridges historical real estate performance with forward-looking forecasts. By combining data with Oxford Economics’ proprietary climate scenarios and economic models, clients can conduct detailed stress tests and make informed decisions. The enhancement empowers users to explore datasets, uncover trends, and improve strategic real estate investments through data-driven insights.
The addition comes at a critical time as real estate markets worldwide navigate economic uncertainties and sustainability challenges. Historic data offers invaluable lessons, helping businesses adapt to fluctuating market cycles. The seamless access to both MSCI’s robust data and Oxford Economics’ modelling ensures users can confidently plan in increasingly unpredictable conditions. By facilitating informed decision-making, this integration reinforces Oxford Economics’ commitment to helping industries make resilient and responsible choices.
From a sustainability perspective, the integration allows organisations to evaluate real estate through climate scenarios. By aligning business strategies with environmental trends, the platform supports responsible urban development and reduces ecological footprints. The tool becomes a vital resource for industries striving to build a future aligned with green goals, bridging the gap between economic growth and environmental responsibility.
