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Advances in Social Sciences Research Journal – Vol. 11, No. 2.2
Publication Date: February 25, 2024
DOI:10.14738/assrj.112.2.16429.
Che-Yahya, N., Rosdi, N. E. A. S., Zaghlol, A. K., & Alyasa-Gan, S. S. (2024). Explaining Youth Unemployment in Malaysia: The Auto- Regressive Distributive Lag (ARDL) Approach. Advances in Social Sciences Research Journal, 11(2.2). 521-536.
Services for Science and Education – United Kingdom
Explaining Youth Unemployment in Malaysia: The Auto- Regressive Distributive Lag (ARDL) Approach
Norliza Che-Yahya
Corresponding author: norliza9911@uitm.edu.my
Faculty of Business and Management, Universiti
Teknologi MARA, Puncak Alam, Malaysia Selangor, Malaysia
Nur Ernisha Anis Suraya Mohd Rosdi
Faculty of Business and Management, Universiti
Teknologi MARA, Puncak Alam, Malaysia Selangor, Malaysia
Azlul Khalilah Zaghlol
Faculty of Business and Management, Universiti
Teknologi MARA, Puncak Alam, Malaysia Selangor, Malaysia
Siti Sarah Alyasa-Gan
Faculty of Business Management and Professional Studies,
Management and Science University, Selangor, Malaysia
ABSTRACT
This study examines the influence of macroeconomic factors, namely Gross
Domestic Product (GDP), Inflation, Population and Foreign Direct Investment (FDI)
on Youth Unemployment in Malaysia from 1991 to 2021 using time series analysis.
The data was obtained from World Bank Data and analyzed using EViews software.
The time series data was conducted using the Augmented Dickey-Fuller (ADF) test.
The Auto-Regressive Distributive Lag (ARDL) approach to cointegration was then
employed to determine the short- and long-term analysis of the series. The ARDL
bound test analysis indicates that there is a cointegration relationship between
macroeconomic factors and youth unemployment. The results suggest that
economic growth, inflation, and population have a negative and significant impact
on youth unemployment, while foreign direct investment has a positive but
insignificant effect on youth unemployment in the long term. Upon analyzing the
short-term outcome, it was observed that all factors exhibited a negative
correlation and exerted a substantial impact on youth unemployment’s rate.
Keywords: Youth Unemployment, Malaysia, Auto-Regressive Distributive Lag (ARDL)
Approach
INTRODUCTION
Unemployment, defined by the International Labor Organization (ILO), is the state of being of
working age and not employed while actively seeking employment. Many countries, especially
developing ones with large population including Malaysia, report high unemployment rate.
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Increased unemployment shows that labor resources are not being utilized in any positive way
(Mohd Azhar and Ibrahim, 2021). The unemployment is continuously discussed in previous
academic works, and policymakers used unemployment rates to understand a country’s well- being from the economic development to public satisfaction. If the unemployment issue is not
resolved, socio-economic and society threats are likely to develop (Ramli et al., 2018; Tan et al.,
2021). That is, the unemployment will result in high poverty rate, increase in crime rates
including robberies and theft.
In accordance with the rules that govern each country, the concept of youth varies from one to
the next. Indicated as a proportion of the youth labor force in a country, youth unemployment
refers to the population's aged between 15 to 24 claimed to be available for work but not having
a job (Institute of Labor Market Information and Analysis, 2023). Specifically, individuals within
the mentioned age range who have actively sought employment in the recent three to four
weeks were referred to be unemployed youth (Michael and Geetha, 2020). For a country to
foster economic development, youth is unquestionably one of its most valuable and significant
resources. In addition to being valuable and resourceful, youth are also enthusiastic,
courageous, and capable of coming up with novel ideas that, if well-organized and included in
a country’s economic operations, will help improve socioeconomic development.
The primary causes of youth unemployment are acknowledged to be lack of demand brought
on by a slow trend of economic growth, repeated economic recessions, minimum wage, an
unqualified young labor force, and a high rate of young population growth (Bayrak and Tatli,
2016; Balemba, 2022). Rising unemployment results in income losses for people and decreased
tax revenue for the state (Balemba, 2022). According to Balemba (2022), young people are also
supported by their families and/or married ladies whose husbands have jobs. Due to their lack
of responsibility, youth who are unemployed put off becoming adults, which negatively affects
national production, their income and ability to keep up with changes in their field. This is
because the educated workforce is excluded from the production process, which makes it
difficult for them to keep up with developments in their field. In addition, the lack of
employment opportunities, which can create psychological and family problems, is a source of
radical behavior exhibitions of people (Sever and Igdeli, 2018).
Malaysia has the highest rate of youth unemployment in 2018, at 10.9 percent (Michael and
Geetha, 2020). Although it is lower than the 12.2 percent regional average for Southeast Asia,
Malaysia was the ASEAN's third-highest percentage of youth unemployment, behind only
Philippines and Indonesia. Additionally, Malaysia's 3.1 percent unemployment rate in 2013
placed it as the 20th nation in the world (Mohd Azhar and Ibrahim, 2021). The unemployment
rate dropped to 2.85 percent in 2014, which was its lowest level. In addition, the Ministry of
Education reported that 57,000 of the 173,000 graduates from the 2018 academic year were
still without a job six months after their graduation. This circumstance arose primarily because
the graduate of young unemployment has a gap between their graduate qualifications and the
country's workforce qualifications.
The reported statistics could be caused by the Industrial Revolution (IR) 4.0 phase, in which
machines carry out tasks. Subsequently, less unskilled labor is needed, and a great demand is
made for skilled workers who can contribute value by running the equipment. Nonetheless, a
slowed economic growth will be experienced if the proper steps are not done to address the
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Che-Yahya, N., Rosdi, N. E. A. S., Zaghlol, A. K., & Alyasa-Gan, S. S. (2024). Explaining Youth Unemployment in Malaysia: The Auto-Regressive
Distributive Lag (ARDL) Approach. Advances in Social Sciences Research Journal, 11(2.2). 521-536.
URL: http://dx.doi.org/10.14738/assrj.112.2.16429
high rate of youth unemployment as future economic growth still needs to come from increases
in youth productivity. Additionally, the modernization of technology emphasizes the necessity
of educating the nation's children in order to meet future labor demands.
Young workers and recent graduates are now facing even more challenging circumstances as a
result of the Covid-19 recession of 2020 and the ongoing hardships of 2021. Prior to 2020,
Malaysia's youth experienced unemployment at a rate that was lower than the 13 percent
global average but higher than that of the adult working population (aged 25- 64), by a factor
of six that was high (compared to the global average of three) (Aun and Zhang, 2021). Over the
past ten years, young unemployment has increased relative to the national average, and
graduate unemployment has remained a major national concern. In 2020, youth
unemployment rose to 12.5 percent from 10.5 percent in 2019 and 10.7-10.9percent between
2015 to 2018 (Aun and Zhang, 2021).
Acknowledging the threats that youth unemployment poses to their income and well-being in
the long term, economic growth and a country's workforce's ability to accumulate human
capital, this study is developed to examine the influence of macroeconomic factors including
economic growth, foreign direct investment, inflation, population on youth unemployment in
Malaysia from 1991 to 2021. An autoregressive-distributed lag (ARDL) bounds testing
approach is used to understand influence of the macroeconomic factors on youth
unemployment. The remainder of this paper is organized as follows. Section 2 presents the
background of youth unemployment in Malaysia and factors associated to it. This is followed
by section research methodology. The last two sections report and discuss the findings and
finally the conclusion and implications on the results of this study.
LITERATURE REVIEW
Youth Unemployment in Malaysia
Unemployment is a significant issue in many countries, including Malaysia. Malaysia exhibits
higher levels of unemployment compared to the general population, especially among youth,
suggesting that this country is significantly vulnerable to the issue of youth unemployment
(Michael and Geetha, 2020). Malaysia, similar to other countries globally, encounters challenges
in educating and employing its youth population, which comprised 2.6 million individuals in
2020, accounting for 16.7 percent of the labour force (Aun and Zhang, 2021). According to the
Ministry of Finance, youth unemployment is primarily attributed to a dearth of work
experience, skills, education levels, and skill compatibility necessary for engaging in the labour
market. From the perspective of employers, communication is the most essential skill in the
hiring process apart from professional experience, interpersonal skills, passion, and
commitment. While the causes of youth unemployment are not novel and conclusive, they must
now be given significant attention.
The global economy's growth can be significantly hindered by the high rates of youth
unemployment, prompting governments worldwide to acknowledge this issue. Calvin and
Mohamad (2020) present substantial circumstantial evidence that engaging in employment
during one's youth, particularly for prolonged durations, has a detrimental impact on future
earnings and employment opportunities. This subsequently diminishes overall labour
productivity and hampers the accumulation of human capital in the labour force for several
decades. Youth are a nation's most precious asset as they possess the capability to rapidly
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acquire fresh knowledge and skills despite limited experience, enabling them to promptly adapt
to the established practices of their employer. Young individuals are expected to be industrious
members of society who advance the interests of their nation. Thus, youth unemployment
would lead to a squandering of resources (Thirunaukarasu, 2004).
In light of this context, it is unsurprising that governments worldwide prioritize coordinated
policies to tackle the issue of youth unemployment. Prior to formulating effective strategies and
initiatives to address youth unemployment, it is imperative for the authorities to gain a
comprehensive understanding of the underlying reasons why young individuals are unable to
secure employment. Global research and evidence, relevant to Malaysia, suggest that the
primary causes are structural shifts in the job market that disproportionately impact young
individuals, sometimes worsened by economic recessions or downturns. However, a more
covert motive is simply employers engaging in discriminatory practices. It is comprehensible
that companies prefer older employees due to their greater experience, perceived reliability,
ability to inspire trust in customers or clients, and lower rates of absenteeism. Consequently,
during periods of business difficulties or economic downturns, employers often employ the
"last in, first out" principle to reduce the workforce, disproportionately impacting the younger
segment of employees.
Macroeconomic Factors on Youth Unemployment
GDP is one macroeconomic factor reported to has a significant influence on youth
unemployment. Michael and Geetha (2020) reported that GDP and youth unemployment have
a negative relationship and Okun's law applies to this conclusion. Additionally, the co- integration test of the study revealed a long-term link between GDP and youth unemployment,
demonstrating the interdependence of the two variables. In a prior study, Riaz & Zafar (2018)
also revealed that there is a negative relationship between GDP and unemployment. In the case
of Pakistan, Asan and Zaheer (2021) reported that GDP positively related to unemployment and
Okun’s law does not hold any place. Patel and Choga (2018) and Abugamea (2018) also found
similar results when that an increased GDP contributes to a decline in youth unemployment.
Another study in Malaysia using data from 1991 to 2019, Tan et al. (2021) supports that GDP
and youth unemployment is significantly related and have an inverse relationship. Meanwhile,
Hasan and Sasana (2020) looked into the factors that affect the youth unemployment rate in
ASEAN nations. The results shown that GDP significantly influence youth unemployment rate
in an inverse direction. Similar result is produced by Bayrak and Tatli (2016). Another study in
Arab countries by Ali and Almula-Dhanoon (2021) during the period from 1990 to 2019
revealed that the economic growth has an insignificantly influence on youth unemployment
rate. This is evidence that GDP in Arab countries is not favorable to the poor.
Economic theory holds that rising inflation reduces unemployment and vice versa. A greater
inflation rate suggests a decline in purchasing power and may signify less economic stability,
which will hamper economic activity and a rise in unemployment (Ali and Almula-Dhanoon,
2021). Based on Michael and Geetha (2020), a short-run curve shows that there is a trade-off
between inflation and unemployment. They investigated inflation as a macroeconomic factor
that affects youth unemployment in Malaysia. The study revealed that Phillips Curve is valid
that inflation and youth unemployment show that it has a negative relationship. The co- integration test also showed a long-run relationship between inflation and youth
unemployment. Similar results are reported in Hasan and Sasana (2020), Hasan and Zaheer,
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Che-Yahya, N., Rosdi, N. E. A. S., Zaghlol, A. K., & Alyasa-Gan, S. S. (2024). Explaining Youth Unemployment in Malaysia: The Auto-Regressive
Distributive Lag (ARDL) Approach. Advances in Social Sciences Research Journal, 11(2.2). 521-536.
URL: http://dx.doi.org/10.14738/assrj.112.2.16429
(2021) and Balemba (2022) that inflation and youth unemployment have a negative and
significant relationship, in which confirms the validity of the Philips curve. The Philips curve
propositioned those workers are no longer in a position to effectively demand a pay raise after
a certain duration of their unemployment; productivity increases are then distributed in the
company's favor. In contrast, Tan et al. (2021) using data from 1991 to 2019, revealed that
inflation had an insignificant relationship with youth unemployment in Malaysia.
The population size in a given period is defined as the average yearly percentage change in the
growth of the population, which included all residents regardless of citizenship or legal status.
When there are constraints on increasing productive capacity, population growth results in
more people joining the labor force, which increases unemployment (Ali and Almula-Dhanoon,
2021). Sam et. al (2020) analyzed the contribution of the population to youth unemployment
in Kenya using the cointegration of time series data. The study revealed that an increase in
population leads to a decrease in youth unemployment. Similar results are reported in Bruno
et al., (2014) as well as Hasan and Sasana (2020) examining the ASEAN nations. In contrast, Ali
and Almula-Dhanoon (2021) revealed that population impacted the youth unemployment rate
negatively and significantly. One of the possible reasons is that the population policies applied
by the Arab countries have contributed to reducing population growth. Balemba (2022) offer
support to the finding in Ali and Almula-Dhanoon (2021). The negative relationship can be
accounted for by the demographic slowdown the nation has seen recently. So, if there had been
a geometric development, the population might not have increased. Meanwhile, using data from
1982 to 2013, Mohd Azhar and Ibrahim (2021) showed that the population appears to have
insignificant influence on youth unemployment.
FDI refers to the investment made by an entity (individual, business, or government) from one
country into business interests located in another country. Patel and Choga (2018), Hasan and
Sasana (2020), Tan et al. (2021) showed that FDI contributes to a decline in youth
unemployment. A study by Ma'in et al. (2021) using Malaysian data also shown that FDI has a
negative and significant relationship with unemployment. This is because FDI provides new job
opportunities that contribute to increasing the employment rate. Sam et, al. (2020) also
revealed a similar result which FDI leads to an increase in youth unemployment in Kenya. In
contrast, Balemba (2022) examining Democratic Republic of the Congo between 2001 and 2020
FDI positively predicts the rate of youth unemployment. Investment in this nation is subject to
many taxes that the business environment is much more beneficial. Investors are compelled to
allocate their investments solely to the mining and telecommunications sectors, disregarding
other industries that have a significant workforce and contribute to reducing unemployment.
DATA AND METHODOLOGY
Data Description
This study examines the influence of gross domestic product (GDP) growth, foreign direct
investment (FDI, inflation and population on youth unemployment in Malaysia. This study
applied secondary time series annual data over the period 1991 to 2021 for all of its variables,
which are sourced from the World Bank. Upon obtaining the complete dataset, this study
analyzes the data using EViews statistical software. This study adopts the autoregressive- distributed lag model (ARDL) to answer its research objectives. The detailed definition and
interpretation of data for each variable are described in the table below.
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Figure 2: Plot of Cumulative Sum of Square of Recursive Residuals
The results of the stability test are shown in Figure 1 and Figure 2. Both the cumulative sum
(CUSUM) and the cumulative sum of squares (CUSUMSQ) show the absence of any instability of
the coefficients because the plots of these statistics remain within the critical bounds of the 5
percent significance level. The null hypothesis cannot be rejected if the plot of these statistics
remains within the critical bound on the 5 percent significance level.
Based on Figures 1 and 2, the plots of both the CUSUM and the CUSUMQ are within the
boundaries, at a 5 percent level of significance and hence providing evidence that these
statistics confirm the stability of the model. The model does not suffer from any structural
instability over the period of the study.
CONCLUSION AND RECOMMENDATION
This study examines the influence of macroeconomic determinants on youth unemployment
rate in Malaysia using the ARDL model. Employing annual time series data from 1991 to 2021,
this study found that economic growth, inflation, and population affect youth unemployment
negatively while foreign direct investment affects youth unemployment positively. The findings
on the relationship economic growth and inflation in the long run are consistent with economic
theory, Okun’s Law and Phillip curve. In the short run, all independent variables, economic
growth, inflation, population, and foreign direct investment are found to be significantly
decreasing the rate of youth unemployment in the current period. The coefficient of foreign
direct investment, in the long run, is found to be insignificantly affecting youth unemployment
in a positive way, however, the sign of the current coefficient value of the foreign direct
investment in the short term is found to be negative and significantly affects the youth
unemployment. Another finding of the study is that a positive change in youth unemployment
could be balanced in the long run, because it estimates that -0.798 implies a 1.3-year change in
the deviations toward long-run equilibrium. Meanwhile, the diagnostic checks show that the
residual in this study has normality, no serial correlation, and no heteroscedasticity and
functional form that ensures a dynamically stable model.
Since youth unemployment has a significant impact on a nation's economic growth, the
government must adopt a long-term strategy to boost labor force participation and increase