Riyadh studios at SAR 1.605m–2.408m: what is behind 68-day listings?

A

AishaSlate

Homeowner
Established
I’m sense-checking a Riyadh sample priced from SAR 1,605,000 to SAR 2,408,000. Most are studios, and the typical listing has remained visible for 68 days.

My working theory is that property tax helps explain the divide between quick sales and stale stock, but I may be giving it too much weight. Are completed sales supporting these asking prices? I’d also like to understand how much apparently old stock is actually withdrawn or relisted, and whether neighbourhood, condition, financing or seller motivation better explains the gap.
 
Listing age alone cannot establish a tax effect. First separate confirmed sales from withdrawals, expired adverts and relistings. Then compare similar studios by neighbourhood, condition and original asking price. If quick and slow listings still split after that, transaction costs may be worth examining; until then, seller expectations seem an equally plausible explanation.
 
How large is the sample, and what does “typical” mean here—median or average? The collection period matters too. A small group of repeatedly advertised units could push the figure toward 68 days. Studio size, furnished status and building condition would also help because total price is difficult to compare without them.
 
Neighbourhood boundaries are the biggest missing piece for me. A broad Riyadh label can conceal very different buildings and immediate surroundings. I would group listings as tightly as the data allows, then compare the SAR 1,605,000 end with the SAR 2,408,000 end. Otherwise a location or condition premium may be mistaken for market staleness.
 
I’m not convinced tax is the leading explanation. Financing friction can delay an otherwise realistic listing, while an unmotivated seller can leave an ambitious price online indefinitely. Track when the first reduction occurs and whether reductions lead to disappearance. That sequence would be more informative than the final number of visible days.
 
A simple weekly tracker could settle several points: listing identifier, neighbourhood, studio size, condition, first-seen date, original price, current price and status. Mark disappeared listings as “unknown,” not sold. Add a completed price only when there is a reliable basis for doing so. After a few rounds, genuine new volume and recycled stock should be easier to distinguish.
 
One caveat: even completed-sale information may not align neatly with the active listings because timing and unit condition can differ. I would avoid using one completed sale to validate an entire bracket. Several comparable outcomes within the same narrow area would be more persuasive.
 
Price per square metre would help, even for studios. Two units carrying similar total prices can be poor comparables if their floor areas, fit-out or building condition differ. I’d also distinguish a district name from the actual immediate location. Street-level differences are exactly what a citywide 68-day figure smooths away.
 
Agreed, although I would start smaller than a citywide tracker: choose two tightly defined areas and follow only genuinely comparable studios. Record new listings, cuts, withdrawals and relistings for each. That should reveal whether 68 days reflects the market or merely the way this particular sample was assembled.
 
Before testing the tax theory, define precisely which tax or transaction cost you mean and which party or property it affects. Current treatment can depend on the circumstances, so it is worth confirming the Saudi position rather than applying a broad “property tax” assumption. Then compare that cost with the price cuts and financing delays visible in the sample.
 
The practical order seems clear: clean out duplicate or relisted stock, narrow the neighbourhoods, add size and condition, and classify disappearances cautiously. Next, compare price-cut timing and any verifiable completed sales, while noting financing and seller motivation where known. If a sharp quick-versus-stale divide remains after those steps, the tax hypothesis will have something firmer to explain.
 
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