By Goh Lim Thye
THE Movement Control Order (MCO), instituted in response to the Covid-19 pandemic and implemented since March 18, has changed the ecosystem of domestic economic activities. People are now required to socially distance themselves and remain at home, while shops have been asked to shut and production plants have stopped running.
The level of economic distress due to the pandemic is serious, with even the significant short-term disruptions resulting in the World Bank slashing Malaysia’s 2020 GDP growth projection from a positive 4.5% to a negative 0.1%. And, this may be reduced further.
Negative growth signifies a contraction in business sales or earnings, hence indicating that the return on assets, the earnings per share and the dividend per share of commercial organisations are all expected to fall. This situation raises a question. What is the possible impact of the pandemic on Malaysia’s income distribution?
Malaysia’s level of income inequality, as measured by the Gini index (an index between 0 and 100 where 0 represents perfect equality and 100 total inequality), was reported at 40.6 in 2016.
In January 2020, before the outbreak of the pandemic, Malaysia’s labour force participation rate (percentage of working-age population working or seeking work) stood at 68.9%, or approximately 15.8 million people. Assuming that the Covid-19 pandemic will affect the entire labour force, in one way or another, there are several possible outcomes.
First, the income of a large number of members of the elite group (entrepreneurs, company owners, directors of boards) – the Top 20 (T20) — who share in company profits, will be worse off due to reductions in expected income.
Second, the income of the middle-income group (M40) is expected to be sustained, assuming that their companies are still in operation and that no pay reductions are enforced.
Third, the income of the lower-income group (B40) who receive minimum or fixed wages will be sustained. However, for the contract labour force, a termination of contracts is expected.
As a result, if the income of the T20 group is reduced more significantly than that of the M40 and B20 groups, a correction in the level of the income distribution is expected, with the Gini index expected to improve.
However, this prediction is over-optimistic, as well as being too mired in theory. In reality, when a company suffers losses, we would expect to see pay cuts and even layoffs among employees.
A recent report by Bank Negara Malaysia highlighted that amid the Covid-19 pandemic, it expects “the labour market to be considerably weaker and the unemployment rate to increase to about 4% in 2020”.
Hence, with the GDP predicted to suffer negative growth and unemployment to increase, the chain-effects could be more severe than initially expected, with all household groups being affected. This may harm the existing demography of income distribution disparities, rather than improve it.
Although the government has introduced various packages to stimulate the economy and to support vulnerable groups in society, the challenges ahead remain significant.
The Covid-19 pandemic has exposed weaknesses in the global economy, where most countries are susceptible to uncertain shocks. Thus, policymakers should look into ways to improve the existing system, to minimise the impact of uncertain shocks.
From the perspective of manufacturing plants, it is now time to fully embark on human capital investment and the ideas brought forward by the Industrial Revolution 4.0, such as Artificial Intelligence and the Internet of Things, to enhance the competency level of their labour forces and the production processes.
The Covid-19 pandemic is unlikely to reshape the income distribution of Malaysia but it has manifested a severe social and economic crisis which offers important lessons that need to be learnt.
Policymakers should explore and learn from Germany, as reported by the Centre for European Economic Research (ZEW), where robots are creating more jobs, instead of taking them away.
ZEW explained the aggregate employment effects of robotic and technological changes through five important mechanisms: the direct labour-creating effect, direct labour-saving effect, productivity-induced labour-enhancing effect, income-induced labour-enhancing effect and the wage-induced labour-enhancing effect.
Besides, policymakers should also look into establishing an educational and life-long learning system that concentrates further training in digital skills and competencies that remain difficult for machines to acquire, such as problem-solving capabilities, creativity and communicating abilities. — April 9, 2020
Dr Goh Lim Thye is senior lecturer at the Economics Department of University of Malaya
