Oxford Economics proudly launches its upgraded Real Estate Economics Service, now spanning 100 cities around the world. This upgrade aims to offer a clearer and steadier grasp of the factors shaping real estate results globally. By blending AI-driven data on property supply with model-driven views of demand forces, it stands as the top independent forecasting tool for real estate right now.
A model-driven take on demand
At the heart of this service lies Oxford Economics’ prediction method and setup, centered on our Global Economic Model. This setup keeps every real estate forecast aligned and rooted in basic economic truths.
“Real estate markets today hold more twists than before. Tariffs, rates that stay high, global conflicts, and weather threats all affect property trends,” noted Innes McFee, who leads Macro, Industry, and City Services at Oxford Economics. “Our prediction tools and skilled staff link the big economy, money markets, city growth, and local property outcomes. They hand over useful facts that users can act on.”
A fresh way to track real estate supply
The Real Estate Economics Service brings in new data on building stocks, created through map-based info, AI, and machine learning.
“We change how we watch real estate supply data,” McFee added. “Old ways depend on on-site checks, which often feel personal and uneven across places. Our method pushes ahead. We grab map data for building shapes, then use AI and machine learning to sort building kinds. This helps us gauge stock with better precision and fairness. It yields a steadier, wider view of real estate supply.”
Raising the bar for worldwide real estate predictions
“The property field has pushed for quicker, better data for years,” said George Armitage, top leader for Real Estate globally at Oxford Economics. “A key hurdle in guessing real estate trends has been too much trust in slow, slanted, and costly gathering techniques. Local groups add good details, but their styles differ a lot. This leads to broken-up pictures that are hard to match across areas. At Oxford Economics, we stick to one steady method for all spots, backed by strong data tools. This lets clients get solid, equal matches across nations, cities, and fields—key for those active in many regions.”