Time sensitive influences in the housing market
Marnix Hazelhoff
9 April 2025
Reading time 5 minutes
Friedrich, Marina, Yicong Lin, Pavitram Ramdaras, Sean Telg, and Bernhard van der Sluis. 2022. "Modelling Time-Varying Relations in Housing Prices: A Semiparametric Panel Approach."
A recent academic study sheds new light on the factors that determine housing prices – and more importantly, how these factors evolve over time. The researchers analyze data from more than sixty Dutch municipalities spanning a fifteen-year period (2006–2020). The key question: how do the relationships between housing prices and their underlying drivers change over time? Their insights prove crucial for anyone involved in the housing market: from policymakers and investors to agents and buyers.
What stands out?
Both property-specific characteristics (such as size, year built, and housing type) and broader economic factors (like interest rates, unemployment, and GDP growth) significantly impact housing prices — but their influence is not constant. Using a sophisticated statistical model, the authors show that the weight of these factors fluctuates over time.
Why does this matter
The realization that these relationships aren't stable is highly relevant for decision-makers across the housing sector:
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Buyers and sellers
The best time to buy or sell is not just about the house itself, but also the broader economic context. What works today may not work tomorrow. -
Agents and appraisers
A home's value can't be estimated using static models alone. Those who consider economic trends gain a more accurate view. -
Policymakers and economists
Policy on affordability or housing supply must be sensitive to both regional and time-dependent price dynamics. -
Investors and developers
Investment decisions require models that account for economic cycles. Many forecasting tools using fixed assumptions fall short.
Regional and Temporal Differences
In addition to time dynamics, the study also finds that the sensitivity of housing prices to external factors varies significantly by region. For example, an interest rate hike might affect Amsterdam very differently than Emmen. This reinforces the need for tailored local policies and more granular market analysis.
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Conclusion
The housing market isn’t a stable system, but a dynamic landscape that constantly shifts — with prices responding to a complex mix of time-varying and regional influences. Accounting for this variability allows market players to make better decisions, improve valuations, and create smarter policy.
For those who want to truly understand how housing prices behave, this study is not just academic — it's a practical wake-up call.
