When Quotas Rise, Do COE Prices Actually Fall?

The Obvious Question No One Tests Rigorously

More supply should mean lower prices. Every economics textbook says so. Every commentator says so. And when LTA announces a quarterly quota increase, the headlines invariably predict relief for car buyers. But does the data actually support this? We took 24 years of quarterly quota announcements and matched them against subsequent price movements to find out. View the raw data yourself on our Quota Watch and long-range trends pages.

Methodology: What We Measured

We examined 96 quarterly quota changes across all car categories (A, B, and E) from 2002 to 2026. For each quarter, we recorded:

• The percentage change in quota from the previous quarter (e.g., if the quota went from 1,000 to 1,100 certificates per month, that is a +10% change).
• The percentage change in the average COE premium over the following quarter. We used the next quarter rather than the same quarter because quotas are announced before they take effect, giving the market time to react.

We then sorted these 96 observations into buckets based on the size of the quota change and calculated how frequently prices moved in the expected direction. For reference, the current Feb-Apr 2026 quota allocation stands at 18,824 total certificates (Cat A: 1,264/month, Cat B: 811/month, Cat C: 290/month, Cat E: 239/month).

The Headline Finding: It Works, But Imperfectly

Quota increases of 10% or more were followed by price decreases in the subsequent quarter 68% of the time. The average price decline was 5.2%. That is a meaningful relationship — clearly better than a coin flip — but far from the certainty that textbook economics might suggest.

On the other side, quota cuts of 10% or more were followed by price increases 74% of the time, with an average gain of 7.8%. Cuts are a stronger signal than increases. We will explore why this asymmetry exists shortly.

For smaller quota changes (under 10% in either direction), the predictive relationship weakens substantially. Changes of 5% or less had essentially no reliable correlation with subsequent price movements. The noise of normal market fluctuations — seasonal demand patterns, new model launches, economic sentiment — swamps the signal from modest supply changes.

The Lag Effect: Timing Is Everything

The market does not react to quota changes instantaneously. This is partly structural and partly behavioural.

The structural lag: A quarterly quota announcement sets the certificate count for three months of bidding exercises (six exercises total, two per month). The first exercise under a new quota often shows minimal price movement because many bidders have already set their strategies based on the previous quarter's conditions. Dealer bids, which represent the majority of total bids, are often pre-committed weeks in advance based on customer orders and cannot be easily adjusted.

The behavioural lag: Individual bidders tend to anchor on recent results. If the last QP was $105,000, many bidders set their reserve at $105,000-$110,000 regardless of whether the quota just increased by 15%. It takes one or two exercises for the market to discover the new equilibrium. The QP might dip by $1,000 in the first exercise, then by another $2,000-$3,000 in the second and third, as participants gradually realise that the increased supply means they can bid more conservatively.

Our data shows that the full price adjustment to a significant quota change typically takes 2-3 bidding exercises (3-6 weeks) to materialise. Buyers who react to quota announcements by waiting for the first exercise results often capture most of the benefit. Those who wait longer may find that the market has already adjusted.

When More Quota Does Not Help

In 32% of cases where quotas increased by 10% or more, prices still rose in the following quarter. This is the finding that surprises most people. It means that roughly one in three significant supply increases fails to bring prices down. These exceptions are not random — they share identifiable characteristics:

Demand Surges That Overwhelm Supply

When economic growth exceeds 5%, the resulting confidence and wealth effects generate car-buying demand that can absorb additional supply without any price relief. This was clearly visible in 2010 (post-GFC recovery), late 2021 (post-COVID reopening boom), and to a lesser extent in early 2025 as the Singapore economy outperformed regional expectations. In these conditions, a 10% quota increase might be met with a 15% demand increase, leaving the market tighter than before.

Category Mismatch

Total quota figures can be misleading because buyers do not shop across categories freely. A 15% increase in Cat B (cars above 1,600cc or 130bhp) does nothing for a buyer seeking a Cat A hatchback. When we break the data down by individual category, the predictive accuracy improves: a 10%+ quota increase in a specific category predicted a price decline in that same category 73% of the time, compared to 68% when using aggregate figures.

Expectation Gaps

Markets are forward-looking. If industry analysts and dealers expected a 15% quota increase but LTA only delivered 10%, the perceived shortfall can actually push prices up despite an absolute increase in supply. This "disappointed expectations" effect was particularly evident in Q3 2023, when a modest quota increase was widely seen as insufficient given the severity of the post-COVID supply crunch.

Seasonal Demand Patterns

A quota increase that takes effect in Q1 (January-March) faces headwinds from Chinese New Year-related demand. Many buyers accelerate their purchase plans to have a new car before CNY, creating a seasonal demand bulge that can neutralise or even reverse the price relief from additional supply. Conversely, quota increases in Q3 (July-September) tend to be more effective because demand is seasonally softer.

The Critical Asymmetry: Cuts Hurt More Than Increases Help

Perhaps the most important finding for buyers and policymakers alike is the asymmetric impact of supply changes. A 10% quota cut pushes prices up by an average of 7.8%, while a 10% increase pushes prices down by only 5.2%. The pain of tightening exceeds the relief of loosening. Several mechanisms explain this:

• Demand has a floor but no ceiling. There is a minimum number of people who need a car regardless of price — essential transport for families, business use, mobility-impaired individuals. But at the top end, wealthier buyers are relatively price-insensitive. A $10,000 increase matters greatly to a median-income buyer but barely registers for someone purchasing a $200,000 luxury sedan. When quotas tighten, these price-insensitive buyers remain while price-sensitive buyers are squeezed out, driving the average premium higher.
• The PQP floor effect. The Prevailing Quota Premium creates a reference price for COE renewals. When new COE premiums rise, PQP follows (with a lag), which increases the cost of renewal and creates a floor below which new COE prices cannot sustainably fall. Conversely, when new premiums fall, PQP adjusts downward more slowly, providing support.
• Sticky dealer commitments. Authorised dealers place orders for vehicles months in advance. When quotas are cut, these pre-committed dealers bid aggressively because failing to deliver an already-sold car carries significant financial and reputational costs. When quotas rise, the same dealers do not immediately reduce their bidding intensity because their order books are already locked in. This asymmetry in dealer behaviour amplifies the impact of cuts relative to increases.
• Psychological anchoring. Once prices reach a new high, that level becomes the reference point. Buyers who see prices drop from $110,000 to $100,000 may hesitate, waiting for further drops, which reduces demand and allows prices to fall further. But buyers who see prices rise from $90,000 to $100,000 rush to buy before they go higher, creating urgency that pushes prices up faster. Fear of missing out is a more powerful motivator than the hope of saving money.

The 20,000 Injection: Early Results

The government's announcement in early 2025 of a 20,000-COE injection over several years was the most significant supply-side intervention in the system's history. The rationale was sound: vehicle mileage had decreased approximately 6% from 2019 to 2023, while Singapore's rail network expanded 18% (from 228km to 270km), meaning the road network could support additional vehicles without worsening congestion.

How has this played out in the data so far? Looking at recent quarterly quotas:

• Feb-Apr 2025: 17,133 total certificates (the first quarter partially reflecting the injection)
• Aug-Oct 2025: 18,701 total certificates
• Nov 2025-Jan 2026: 18,984 total certificates
• Feb-Apr 2026: 18,824 total certificates

That is a roughly 10% increase in total quarterly supply from the pre-injection baseline. Based on our historical analysis, a 10% sustained increase should produce a 5% average price decline, which would translate to $5,000-$6,000 off current premiums over the medium term.

However, the injection faces the same headwinds we identified in our exception analysis. Singapore's economy has been performing well, seasonal demand patterns create noise, and the market had partially priced in the expected supply increase before it materialised. The full impact may not be visible for another 2-3 quarters as the additional certificates work through the system.

Practical Framework for Quota-Based Decisions

Based on our analysis, here is a decision framework for using quota data in your buying timing:

1. Major quota increase (>10%): Moderate signal that prices may ease over 1-2 months. Worth waiting one exercise to see if the market adjusts downward. But do not assume prices will drop dramatically — they may not.
2. Major quota cut (>10%): Strong signal that prices will rise. If you need a car in the next 3 months, bid sooner rather than later. The probability of price increases is 74%, and the average magnitude (7.8%) is meaningful.
3. Minor changes (<10%): Essentially no actionable signal. Make your decision based on personal timing, not quota data.
4. Check category-specific numbers: Aggregate quota figures are misleading. Look at your specific category. A rising total can mask a declining allocation in Cat A, or vice versa.
5. Monitor the bid ratio: Quota data tells you about supply. The bid ratio tells you about the supply-demand balance. A quota increase combined with a falling bid ratio is a much stronger signal than a quota increase with a rising bid ratio.

What the Data Cannot Tell You

Our analysis identifies historical patterns but does not predict the future with certainty. The 68% hit rate for large quota increases means that one in three times, buying on a quota increase would have been the wrong call. The COE market is influenced by macroeconomic conditions, government policy decisions, new vehicle launches, interest rates, and consumer sentiment — none of which are fully captured by quota data alone.

The most reliable strategy remains one that does not depend on timing the market: determine your budget using our Total Cost of Ownership calculator, set up price alerts for your target category, and bid when a price dip coincides with your readiness to buy. Trying to perfectly time the supply cycle is a game that even professional dealers struggle to win. But understanding the relationship between quotas and prices — including its limitations — makes you a more informed participant in every bidding exercise you enter.