A Comparison of Singapore (SG) and USA Personal Savings Rate (PSR)

-

 

Statistics from: Singapore Department of Statistics and US Federal Reserve Bank of St. Louis.

The Personal Savings Rate (PSR) of an economy is one of the components in the assessment of a country’s economic health; and resilience to economic and financial market shocks. 

PSR= Savings/Disposable Income x 100. Disposable Income= Income-Taxes. 

Notes

  •  Personal Savings Rate % (PSR) is computed at National Accounts (GDP) level therefore some items may not be what you usually think of as personal savings.
  •  Here, Savings include CPF contributions, as well as the Personal Disposable Income and Private Consumption of Goods and Services of Permanent Residents and Migrant Labor.
  •  Income includes the rental income of private property by the rich, as well as amounts from CDC Vouchers, and other government transfers.
  •  With $36 trillion in debt, a weakening USD and increasing budget deficit due to tax cuts, and a low PSR, the US economy has the potential to implode.
  •   The rates are adjusted for seasonal components such holidays, seasons, production cycles, employment cycles etc.

Observations

1.       SG Personal Savings Rate (PSR) is consistently above US PSR.

2.       In this 45 years series from 1980 to 2024, US Mean PSR=6.9 SG Mean PSR= 21.8

3.       The US PSR peak in 2020 was due to Covid-19 when consumers had nothing to spend on. 

4.       The SG PSR from 1980 to 2004 was unstable during the economy’s transition to a high value-add economy.

5.       In 1985 there was a recession and from 2007 to 2008 was the Asian Financial Crisis,

6.       From 2005 SG PSR developed a strong upward trend due to higher and higher CPF contribution rates as well as the influx of rich migrants and expatriate labor.

7.       The recent two decades from 2005 to 2024 saw higher productivity growth in high value industries such as financial services, precision and process engineering, logistics, pharmaceuticals and electronics. This resulted in higher PSR resulted for the SG economy as a whole.



Comments

Post a Comment

Popular posts from this blog

A Comparison of Four Noise Reduction Algorithms as Applied to the BSE Sensex index.

-
Image
Chart 1: Noise Reduction Algorithms Compared. Data as of 12 June 2025 As compared with established and mature stock exchanges such as the New York, Japanese and European stock exchanges, frontier and emerging stock exchanges have a higher level of ‘noise’. In financial markets, "noise" refers to the erratic and often unpredictable fluctuations in price and volume that can make it difficult to discern genuine market trends. This noise can stem from various sources, including news reports, market sentiment, and even algorithmic trading. It essentially obscures the underlying fundamental value of an asset, making it difficult for investors to make sound decision. In this post, I am applying four types of de-noising algorithms on the Bombay Stock Exchange Sensex Index (“BSE” or “Sensex”). My hypothesis is that the Sensex  has  a high level of noise. This is because a large proportion of the investors on the approximately 5000 stocks listed on the BSE are retail investors stee...
Read more

USD and Gold provide a more accurate insight into the true state of the US economy than the SP500

-
Image
  Why? (1   - 60-70% of trades in the US equities market are done by automated AI-driven algorithms, including high frequency micro-second trading. These algorithms make their decisions not on economic or corporate fundamentals but on momentum, arbitrage opportunity, pattern recognition etc. (2  -  Previously the USD was a safe-haven currency that investors flock to in periods of economic, political or military instability. But with the chaos that is now going on in the USA, the USD seems to be losing its safe-haven status. As for Gold, it is still a safe haven asset, and recently we have seen the Central Banks of China, Russia, Japan and even some of the EU countires load up on Gold while paring down the amount of US Treasuries they hold. (3- The USD is the lynchpin that holds the US stock market and the Treasuries market together and a falling USD will make any rise in stock or bond prices unsustainable. Would you invest in US stocks if your profit is ...
Read more

Markov Regime Switching Model for Risk‑On/Risk‑Off Dashboards of Stock Indices

-
Image
Knowing the market’s current risk state is foundational for portfolio decisions. Basic Markov chain models are a good starting point, but they fall short on three realities of financial data. Using as case study China's CSI300 Index, here’s how our model resolves each one and delivers a robust, reproducible Risk‑On/Risk‑Off signal. 1) Beyond “memoryless”: markets have persistence and aging Problem: Standard Markov chains assume memorylessness—the next state depends only on the current state, not on how long we’ve been there. Markets don’t behave that way; regimes “age” and persistence changes with time. Our solution: We use a hidden semi‑Markov model (HSMM) with explicit duration modeling. Each regime has a duration distribution (e.g., Negative Binomial), and transitions are allowed to depend on time spent in the state. This breaks the memoryless assumption, curbs flicker, and captures realistic regime persistence. 2) Heavy‑tailed, skewed returns are the norm—not Gaussian Problem: ...
Read more