Abu Dhabi inventory shifted in December 2025 — what are you seeing?

[inez.keel]

A 7.6% difference means little unless the asking and completed figures refer to the same Abu Dhabi properties. That is the main difficulty in my December 2025 notes. Well-presented mixed-use buildings seemed to secure buyers in about 75 days, while properties needing work remained on the market for longer, but most readily available information concerns advertised prices.

It is tempting to call that greater buyer selectivity, although a single month could just reflect seasonal timing or a small sample. Has anyone seen matched asking and sale figures, transaction volumes, or direct neighbourhood-level examples? Those would be more useful than citywide averages for deciding whether condition is genuinely affecting demand.

 

[clear_lane]

One month is too narrow to distinguish seasonality from a real change in buyer behaviour. The 7.6% also needs a clear basis: is it the difference between the original asking price and final sale price for matched properties, or an average asking figure compared with an average completed figure? Those can produce very different conclusions.

 

[otis.cedar]

How large is the sample behind the 75 days, and are all those mixed-use buildings genuinely comparable? A few unusually clean or well-priced listings could pull the result around. I’d also want transaction volume alongside time on market; quicker sales on very low volume would not necessarily indicate stronger demand.

 

[finn_budgets]

I’m not convinced selectivity is the only explanation. Condition may simply be standing in for seller realism: properties needing work can still move if the asking price reflects that work. It would help to separate physical condition from the number and timing of price reductions, otherwise “buyers prefer better presentation” risks becoming a circular conclusion.

 

[hugo_bell]

I’d rebuild this as matched groups by neighbourhood, property type, condition and listing month. For each completed deal, retain the first asking price, last asking price, completion price and days advertised. Keep withdrawn or relisted properties visible rather than treating them as sales.

Also record when the data was collected and whether earlier entries were later revised. Any policy timing can be annotated, but I would not assign an effect without several months on either side.

 

[inez.keel]

Fair points. December 2025 is the observation window, not a longer trend line, and my 75-day figure comes from the visible listing history rather than a complete set of completed transactions. The 7.6% is also pooled, which is probably the main weakness here.

I’m going to split original ask, latest ask and completed price, then group by neighbourhood and condition. That should show whether I’m seeing negotiation, repricing before sale, or simply unlike properties being averaged together.

 

[otis.cedar]

That revision should make the result much more useful. I’d publish the sample count beside every group, even if some groups then look too small to interpret. Compare December with adjacent months using the same method, and preserve each version of the table. If the apparent shift disappears after late completions or revisions arrive, that is evidence of reporting lag rather than changing buyer preferences.