Bangkok warehouses: is the apparent +4.0% movement meaningful?

R

RightRoom

Real estate agent
Established
The main constraint is that my sample is small and the warehouses are not closely matched. It covers Bangkok listings from THB 20,300,000 to THB 30,460,000, with median marketing time near 74 days. The apparent movement is about +4.0%, but condition, neighbourhood boundaries and the mix of new listings could easily be driving that figure.

Service charges make the comparison harder. Should I adjust each property for the charge when its basis is clear, while excluding only those where the amount or coverage is unspecified? I also wonder whether a long marketing period reflects the charge itself or simply a less motivated seller.
 
I would adjust for them rather than exclude the listings, provided you can identify what the charge covers. Buyers compare total occupancy cost, not just the headline price. Whether they negotiate or walk will depend on alternatives and how unusual the charge looks beside comparable warehouses.
 
How is “service charge” being presented in your sample: fixed amount, rate, or an unspecified item to be confirmed? Also, are all the warehouses within the same estate or management arrangement? Without that, you may be combining genuinely different cost structures.
 
The +4.0% is the shakier conclusion. Asking prices can rise because cheaper stock sells, expires or is withdrawn, leaving more expensive listings behind. Recent completed sales would tell you much more than movement in the remaining advertisements.
 
Agreed with lcastillo. I would also track new-listing volume. A few higher-priced additions could create that +4.0% without any seller having increased expectations for an existing warehouse.
 
I wouldn’t discard the 74-day figure, though. Split it by condition and see whether the renovated or ready-to-use properties move differently from those needing work. The overall median may hide two recognisable groups.
 
Service charges may be negotiable in an economic sense even when the stated charge itself does not change. A buyer could instead seek a lower purchase price or another concession. Your notes should distinguish “charge reduced” from “price adjusted because of charge.”
 
There is also a boundary problem. “Bangkok” can group locations that buyers do not treat as substitutes. If the cheaper and more expensive ends of the sample sit in different neighbourhoods, neither the +4.0% nor the 74 days is a clean citywide signal.
 
That’s a good caveat. I’d narrow the comparison first by location, then by condition, and only then account for service charges. With a small sample, too many adjustments can create false precision, so retaining the raw figures beside the adjusted ones matters.
 
One missing item is price-cut timing. A warehouse listed for 74 days with a reduction on day 60 tells a different story from one priced consistently for the whole period. Record the original ask, current ask and days until the first cut where available.
 
Do you know which properties disappeared because they completed and which were merely withdrawn? Treating every disappearance as a sale would make both marketing time and demand appear stronger than the evidence supports.
 
A simple approach is three groups: still active, confirmed completed, and outcome unknown. Keep withdrawn stock in the unknown group unless you can verify what happened. Then calculate the 74-day measure only for the category it actually describes.
 
Buyer financing could also interact with condition. A lower headline price does not necessarily make a property easier to fund if substantial work is expected. That may explain longer exposure better than the service charge, but you would need transaction-level information rather than assumptions.
 
Seller motivation is worth recording separately. Repeated cuts, a relisting, or flexibility over other terms can indicate a different position from a seller holding firm. I would not convert those signals into hard numbers, but they help explain outliers.
 
Putting the suggestions together, the useful table would have location, condition, original and current asking price, first reduction date, service charge basis, listing status and any confirmed completion price. Until those fields are reasonably consistent, +4.0% should be described as sample movement, not market appreciation.
 
Late question: what exactly are the two periods behind +4.0%? If they contain different warehouses, this is a change in sample composition. If they follow the same listings, it may instead measure asking-price revisions. Those are separate findings.
 
And for repeat listings, be careful not to count a withdrawn warehouse returning under a new advertisement as fresh supply. Matching by location, price and property details may reveal duplicates, although uncertain matches should remain marked as such.
 
I partly disagree that service charges need to be converted into one adjusted purchase price. That requires assumptions about how long a buyer holds the property. Showing purchase price and recurring charge separately may be clearer and lets readers apply their own time horizon.
 
A practical comparison could therefore have two views: headline price per property, and a separate schedule of known ongoing charges. Add a note where the amount or inclusions are unclear rather than estimating them.
 
My reading after all the caveats: the sample can support a useful listing snapshot, but not yet a firm claim that Bangkok warehouse values moved +4.0%. The next effort should go into confirming completed sales and withdrawn outcomes, not refining the percentage further.
 
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