Skip to main content

Macroeconomic Tail Risks: Malaysia

In a recent post on the World Economic Forum website (See here), Daron Acemoglu summarizes findings from his recent work on what really causes economic downturns. His focus is on the US economy and starts by showing that the distribution of post war growth in America has generally not followed the normal distribution. I was curious what this would look like for Malaysia (where I am currently working) so I ran the Normal Q-Q Plot in R and this is what I found.

Data from the World Bank's WDI database

Malaysian real per capita income growth between 1960 and 2013 has largely followed a normal distribution but there are significant tail risks. The plot above shows that large negative downturns are more common than the standard normal distribution would suggest. The downturns correspond,  in descending order of severity, to 1998 (Asian Financial Crisis), 1985 (Commodity Shock), 2009 (Great Recession), 1986 (Commodity Shock continued), 2001 (Dot Com Bust), and 1975 (1st oil shock).

Acemoglu et al (2015) conclude that "the frequency and depth of such downturns [in the US & advanced countries] may depend on the interaction between microeconomic firm-level shocks and the nature of input-output linkages across different firms. This is due to the fact that the propagation of shocks over input-output linkages can lead to the concentration of tail risks in the economy."

I will not venture to speculate too much as to the causes of the deep deviations from normality at the negative tail end observed in Malaysia. This may be covered in a more involved growth diagnosis for the country. Suffice it to say that the downturns largely emanate from the global economic environment and exacerbate domestic micro economic weaknesses. What is interesting about the above finding for Malaysia is that only large negative downturns appear to be common with no corresponding outliers on the positive side. Contrast that with the untruncated graph for post-war US in Acemoglu's post.

A bit more on the origins of Malaysia's downturns:

1974/5: US and global recession was triggered by a tripling of the price of oil following the Yom Kippur war, and by the oil embargo that followed.

1984/6: The high-interest rate policy in the US resulted in a collapse of world commodity trade: Malaysia’s export price index fell by 30% due to sharp declines in tin and palm oil prices.

1997/8: When the Thai baht came under speculative attack in mid May, the ringgit also experienced heavy selling pressure.

2001: The bursting of the dot com bubble led to low external demand for Malaysia’s electronics and other exports.

2008/9: Resulted in trade shock for Malaysia; sharp fall in share prices; and an exodus of short term capital flows. Manufacturing output contracted by about 15% in 2009.


Comments

Popular posts from this blog

Malaysia at a Cross Roads: Diagnosing the Constraints to High Income Status

Malaysia at a Crossroads: Diagnosing Constraints to High-Income Status In 2008, Malaysia was recognized by the Growth Commission – a distinguished panel comprising 2 Nobel Prize Winning Economists and other leading development practitioners – as one of thirteen countries that sustained high growth in the post-war period. The 30-year stretch that caught the attention of the Growth Commission was between 1967 and 1997 when Malaysia grew at an average of 7.3% per year. This long stretch of growth was interrupted by periods of external shocks including the Volcker shock of 1986, the Asian Financial crisis in 1997/8, later the so-called Dot Com Bubble of 2001, and more recently the Global Financial Crisis of 2008. Despite these shocks, Malaysia remained resilient - formally earning the title "Upper Middle Income Country" in 1992. (See summary figure that breaks down the country's per capita growth story). As...

Corporate Network Analysis

The complex interconnections that define modern society are most readily visible from our Facebook, Twitter, or Linkedin networks. What is perhaps less talked about is the extent to which corporations are linked. I just started building a network of cross shareholding among Malaysia's corporations using listed company data. The map below is a preliminary visualization of the country's corporate network as of 2015. I use social network analysis (SNA) tools to partition or color the network into key connected components or communities therein. I have deliberately excluded company names but I will tell you that the biggest nodes represent the most connected shareholders including governments, fund managers, and international asset managers.  Malaysia's Corporate Network in 2015 Created Using Gephi 0.9.1 As the Malaysia economy has grown so has the complexity of the corporate network from few shareholders to many interlinked players. Below is a visualization using sha...

Assessing labor market transitions in Ghana using panel data

Understanding labor market transitions is important for policymakers and researchers in developing countries. Changes in economic activity status (employed, unemployed, out of labor force) vary significantly from one country to another and also within countries from one socio-economic group to another. Below I summarize analysis from the latest Ghana Annual Household Income and Expenditure Survey ( AHIES ) published by the Ghana Statistical Service. The AHIES is a panel survey that has followed over 10,000 individuals since 2022Q1 to assess changes in their livelihoods. I am currently analyzing trends and show here what has happened to economic activity between Q2 and Q3.  Transitions in Ghana labor force status, 2022Q2 - 2022Q3 Source : Own analysis using AHIES from Ghana Statistical Service. Note : Left hand side is 2022Q2 and right side is 2022Q3 81 percent of working age individuals (15-64-years) who were  employed  in 2022Q2 were still employed in 2022Q3; 7 perc...