ImoEconometrics · Economic analysis · 30 October 2026
Start with the decision
A large dataset creates value only when it helps answer a specific question: what to develop, what rent is sustainable, which price to test or how to phase marketing. Analysis should begin with the objective, geography and market segment.
Different indicators measure different things
An asking price expresses a seller’s intention; a transaction records a completed deal. A bank valuation arises from a valuation process associated with lending. Rents on new leases do not necessarily describe the entire rental stock. Confusing these populations can produce misleading comparisons even when calculations are correct.
Quality before quantity
Data preparation should identify duplicates, observation dates, floor areas, unit types, condition and location. Sources may use different definitions of floor area. New and existing properties, total prices and prices per square metre, and nominal changes and sample-composition effects should also be distinguished.
From comparables to model assumptions
Comparables should be selected for their relevance to the asset and target user. An area’s median provides context rather than an individual valuation. Translating evidence into a financial model requires specific assumptions about discounts, incentives, vacancy, absorption, operating costs and receipt schedules.
Traceability and updating
Useful analysis allows each conclusion to be traced to its source, date and processing method. It should explain sample limitations and distinguish observations from estimates. Subsequent monitoring compares actual outcomes with initial assumptions, helping update decisions and understand differences.
Practical application
Data creates value by connecting market diagnosis with feasibility. A robust conclusion combines statistics, relevant comparables and asset knowledge, tests assumption sensitivity and explains what is known, what is estimated and what remains to be validated.