Explain how the factors outlined above could contribute to a rise in Singapore’s unemployment rate.
In its Recent Economic Developments Statement released in December 2019, the Monetary Authority of Singapore indicated that unemployment was expected to increase. This was largely attributed to weak external demand and the rapid advancement and adoption of artificial intelligence (AI) technologies within Singapore.
Adapted from: Recent Economic Developments in Singapore, MAS, 6 Dec 2019
a. Explain how the factors outlined above could contribute to a rise in Singapore’s unemployment rate. [10]
Introduction
Unemployment refers to a situation where individuals who are actively seeking employment are unable to find work. In the case of Singapore, the Monetary Authority of Singapore (MAS) highlighted two major contributing factors to the rise in unemployment in 2019: weak external demand and the rapid adoption of artificial intelligence (AI) technologies. These two factors can be linked respectively to cyclical unemployment and structural unemployment, both of which can push up the overall unemployment rate in the economy.
Weaknesses in External Demand Leading to Cyclical Unemployment
One of the primary contributors to higher unemployment in late 2019 was the deterioration of global trade conditions, most notably due to the US-China trade war. As the world’s two largest economies imposed multiple rounds of tariffs on each other’s goods, business and consumer confidence in both countries fell. This led to reduced spending and a fall in incomes.
Singapore, being a small and open economy that is highly dependent on trade, was inevitably affected. Both the United States and China are among Singapore’s largest trading partners. As their economies slowed, demand for Singapore’s exports declined, leading to a fall in net exports (X-M), which is a key component of aggregate demand (AD).
Additionally, poor global sentiments likely caused foreign direct investment (FDI) into Singapore to fall, further contributing to a decrease in investment (I). With a simultaneous fall in both (X-M) and I, aggregate demand would shift leftward from AD₀ to AD₁, resulting in a fall in real national income from Y₀ to Y₁, as illustrated on the AD-AS diagram.
As national output contracts, firms cut back on production and reduce hiring to contain costs. This leads to a rise in cyclical unemployment, which is unemployment caused by a lack of demand for goods and services in the economy. Workers who would otherwise be employed in export-driven sectors or in industries supported by foreign investment may find themselves retrenched or unable to secure new employment, thus contributing to an overall increase in the unemployment rate.
Technological Displacement and Structural Unemployment
The second factor contributing to higher unemployment in Singapore is the rapid development and deployment of artificial intelligence (AI) technologies across industries. While such technological advancements bring long-term productivity gains, they often come with short- to medium-term labour market disruptions, especially if the workforce is not adequately prepared for the transition.
AI technologies have increasingly replaced labour in routine and repetitive job functions. For example, the development of autonomous vehicles poses a direct threat to the job security of bus drivers, truck drivers, and delivery personnel. Similarly, the use of AI chatbots and robotic process automation has begun replacing roles in customer service and administrative work.
While technological progress also creates new job opportunities—such as software engineers, data analysts, and robotics technicians—these new roles typically require different and higher-order skill sets. Workers displaced by automation may not possess the necessary qualifications or training to fill the newly created jobs. This leads to structural unemployment, which arises from a mismatch between the skills of job seekers and the requirements of available jobs.
In Singapore’s case, the accelerated pace of digital transformation, if not accompanied by effective retraining and reskilling programmes, risks leaving behind a segment of the workforce—particularly older workers or those in lower-skilled jobs. As a result, even as AI creates opportunities, the transition period can result in rising unemployment levels as displaced workers struggle to re-enter the labour market.
Conclusion
In summary, the rise in Singapore’s unemployment rate in 2019 can be traced to two distinct yet significant factors. Weak external demand—exacerbated by the US-China trade war—reduced export and investment activity, causing a fall in aggregate demand and a rise in cyclical unemployment. At the same time, the rapid adoption of AI technologies led to structural unemployment, as workers displaced by automation found it difficult to secure employment in newly emerging industries.
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