The Bala’s Table is an interesting take on interpreting the potential value of Leasehold properties in Singapore.
Looking at this chart, it is synonymous with the sentiments of most Singaporeans in regards to their thoughts on decaying leasehold value.
However, some improvements to the chart can be done as it is grossly misinterpreted by the general public. Saying that leasehold properties will depreciate upon reaching duration milestones oversimplifies leasehold prices.
Although this train of thought aids efficiency in our real estate markets, it casually disregards the true potential of leasehold properties.
This article will discuss the primary use of the Bala’s Table and in what way is the chart misinterpreted.
I’ll be basing most of my ideas on Determining the value of leasehold land: A closer look at “Bala’s Table” by Centre for Liveable Cities Singapore.
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What Is the Primary Use of The Bala’s Table?
The main use for the Bala’s Table is for the Singapore Land Authority (SLA) to determine the differential premium (DP) for lifting State title restrictions involving a change of use and/or increase in intensity in regards to leasehold properties. This provides greater transparency for developers and landowners.
The Bala’s Table is therefore calculated based on the potential rent from the state to its tenants. For example, if a 99-year leasehold land is charged to the tenants at $1 per square foot a year, this dollar value will be eroded over 99 years due to factors such as inflation. Therefore, a discount rate of 3.5% has been selected for an accurate prediction of leasehold prices back in 1948 till present.
This discount rate is very important because it is linked overall to the overall idea of how much leasehold properties should cost vs freehold properties.
However, should this rate be modified to present standards? Or left as it should be?
Is the Discount Rate Accurate as of Today?
The discount rate is rather close to Singapore’s Inflation Rate from 1962-2016 (2.68%), the Total Debt Servicing Ratio (TDSR) framework (3.5% Stress test), and the Government’s cost of capital (3.4%).
However, I believe that further research can be conducted based on this discount rate.
Singapore’s Inflation Rate
The yearly inflation rate of Singapore is roughly around ~0.50-1.0% as compared to the average across past decades of 2.68%.
These spikes are largely contributed by significant turnkey events such as the 1973-1974 energy crisis (Inflation Rate: ~21%), which had a global impact. A second oil price shock occurred from 1980-82 (Inflation Rate: ~6.88%), which was quickly suppressed by monetary policies. The last significant event will be the 2008 housing crisis (Inflation Rate: ~6.63%).
All these events have occurred a long time ago and do not have significant effects on our present economy, except for the 2008 housing crisis. Averaging these inflation numbers into consideration for our present-day analysis unnecessarily skews information and provides for an inaccurate picture.
However, I acknowledge that they do serve as a reminder on how to manage inflation rates. Removing these significant events will drastically drop the inflation average from the 1960s-present to be 1.8%!
TDSR Framework Stress Test and Government’s Cost of Capital
Due to the limited publicly available data on the above points, I’m unable to give my comment on the above points. However, one point to note that the TDSR framework for property loans have been implemented since 2013, and it is based on the proposed medium-term interest rate of 3.5%. There are no changes for the past 7 years, which I believe denotes a preference for stability rather than constant experimentation.
Depreciation after 40 Years
It's rather strange when I see that most Singaporeans will set particular duration milestones for maximum profit taking/minimal losses. I believe this to be true to a certain extent, as the duration term of ownership will usually signify the overall value of the purchase. (i.e., car ownership in Singapore comes to mind)
However, the Bala’s Table should not be referred to as an exact science as and when to sell a particular development.
The SLA Leasehold table below explains the depreciation rate for properties in Singapore. We will be using this table for the case studies below.
Case Studies Showing That The Bala’s Table Do Not Provide An Accurate Representation of Leasehold Prices
Orchard Court and Lloyd Court
I chose these two properties due to their proximity, but some slight differences such as accessibility to units with a lift and carpark space will be considered as negligible.
I’m unable to trace the actual start of the lease, but using the TOP year (1970) should be a good enough comparison. 51 years have passed and based on the Bala’s Table; leasehold values will be approximately 75.2%. As Lloyd Court have an average PSF of S$1,453.99 psf over the past 50 years, this means that Orchard Court should have an average PSF of S$1093.40 PSF right?
On the contrary! It shows that the average PSF is $814.41, almost $200 psf cheaper based on the Bala’s Table calculations. Does this mean that Orchard Court presents a good buying opportunity?
However, I realized that using the gross average of over 50 years of transactional data might give my readers a non-accurate impression of the market today, so let us focus on 2018. We will have to use the transacted prices from 2018, for a higher degree of accuracy. (i.e. $1,298 psf, Bala’s Table; 76.7%) By our estimation, this value should be $995.56 psf.
Still definitely a far cry!
Hock Mansions and Peace Mansion
Relying on the same way we calculated the previous case, Hock Mansion (TOP: 1975) is about 46 years old. We will be using an approximate 72.4% from freehold value. Will this mean that Peace Mansion will be worth $566.07 psf?
Again, the average psf of Peace Mansion is off by almost $160 psf. Let us compare with a more recent transaction from 2020. We will have to use the transacted prices from 2020, for a higher degree of accuracy. (i.e. $1,350 psf, Bala’s Table; 73.0%) By our estimation, this value should be $985.5 psf.
The difference in actual average psf of Peace Mansion is almost $362.5 psf!
Confused? You might be wondering how it might be possible for leasehold prices to be so wildly unpredictable.
Here are my reasons why leasehold prices don’t trail accurately with the Bala’s Table.
Why Leasehold Prices Don’t Follow The Bala’s Table Accurately
The Unreliable Interpretations on Decreasing Tenure
Freehold properties, other than their tenure, is pretty much near identical to its leasehold counterparts. This brings about the idea of sellers working to push prices naturally upwards for the highest prices, and buyers begrudgingly giving in so.
The opposite sadly happens for leasehold properties too. Most sellers/buyers will not rely on the Bala’s Table for an “accurate” representation of the discounted value, and will simply keep a mental impression of their decreasing lease. This downwards pressure will inevitably be reflected illogically in the transactions.
If the Bala’s Table was to be used as an accurate tool for dictating leasehold prices, aren’t we making a huge mistake by not referring to it for accurate measure and instead of making snap judgements based on feel?
Freehold vs Leasehold in The Area
For some buyers, they might not be as aware of the tenure of nearby properties. In that case, what will they refer to? Some areas in Singapore have a higher concentration of leasehold to freehold properties.
For example, District 07 comes into mind. Notice how skewed the graph is compared to its freehold counterparts. There are some limitations to this chart, however.
The freehold properties in D07 are relatively old (TOP: ~1980s) as compared to the recent new launches in Singapore.
Lack of transactions in Freehold properties might not act as an accurate measure of general sentiments.
Changes in construction regulations (i.e., land intensity, plot ratio, etc) cause such developments to be out of their time and pricing do not reflect modern standards.
Leasehold properties might be priced following other neighbouring core districts.
Some might argue that the huge price increase is due to the recent launch of new properties in D07. I do agree that new launches are a requirement to gentrify land for a more vibrant community.
That being said, the difference of almost ~$1500 psf between Freehold and leasehold properties is huge! Most construction projects will cost close to $450 psf/CFA (Cross Floor Area). This adds up to approximately $1500/psf for rebuild, new freehold projects. This is even before placing a healthy developer’s margin of 50% which is unheard of.
Only then, new freehold properties pricing will be on par with new leasehold properties!
I believe the Bala’s Table was not used in consideration for pricing, so why should individual consumers be too affected by it?
What About En-Bloc?
Land in Singapore is a scarce resource. No building will be left to disrepair. That being said, most properties in Singapore will eventually undergo an en-bloc sale. However, a successful en-bloc depends on other factors such as the asking price of the collective sale, land supply/demand and more.
The following are examples of potential en-bloc properties and their effect on the secondary real estate market.
The three developments are both leasehold and freehold properties and have bucked the trend of the Bala’s Table. If all properties have the potential for an en-bloc sale, shouldn’t this trend be more commonly seen?
For more information, you can read more on en-bloc properties here.
Conclusion
Not all old leasehold properties have low value as compared to their freehold counterparts. After I conducted some detective work, it shows that the prices of leasehold properties do not track accordingly to the Bala’s Table.
If the Bala’s Table were still to be used by both consumers and the authorities, I feel that the discount rate should be looked into further to provide a more accurate representation of our current economic climate.
Further suggestions go beyond my understanding of the subject matter and will require further rigorous study by real estate scholars.
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