ICAME 2022 E-Proceeding

Proceedings [e ISBN 978-629-97614-0-2]
International Conference on Accounting, Management and Economics (ICAME2022)

14-15 December 2022│Faculty of Management and Economics,
Universiti Pendidikan Sultan Idris

that their capital structure included debt and equity. As a result, the bank will face increased
risk as well as increased liabilities. Islamic banks are not permitted to pay or receive interest
under Islamic law. Deposit or investment accounts in Islamic banks are not subject to
liability or equity, making them risk-free (Al-Deehani et al., 2015).

2. LITERATURE REVIEW

2.1 The Effect of Bank Specifics, Market Condition, Macroeconomic
Indicators on Islamic and Conventional Banks Stability

According to (Čihák & Hesse, 2010) and (A. Rashid, A. Jabeen, & Khaleequzaman., 2017)
financial stability can be effectd by internal and external indicators. Internal indicators that
are bank specific related to the scope of bank capital adequacy, size, efficiency,
profitability, liquidity, credit risk, and income diversity. External indicators are market
condition and the macroeconomic indicators that are measured by Gross Domestic Product
Growth Rate and Inflation. Capital Adequacy Ratio as measured by Capital to Risk
Weighted Assets Ratio interpreted that the higher the level of Capital Adequacy Ratio, the
higher financial stability, this means that the Capital Adequacy Ratio has positive effect on
financial stability. Capital Adequacy Ratio is used to examine the stability of the financial
systems around the world (Tabash & Dhankar, 2014).

Bank stability can be controlled by the size effect. Cihak and Hesse (2010),
Chakroun and Gallali (2013), and Muhammad and Humayon (2016) using the Size is
measured by Natural Logarithmic (Ln) Total Assets in examining financial stability. Some
of the results of previous studies have different results. Some claimed that the positive
effect on bank size stability. Large size can reduce the costs of economies of scale so that
financial stability is increased. The other finding stating that small banks are more likely to
achieve good performance, whereas large banks are less likely to achieve good
performance.

Efficiency Ratio is measured by Cost to Income Ratio interpreted that the lower the
Cost Income Ratio increasingly efficiency. Cihak and Hesse (2010), Chakroun and Gallali
(2013), and Muhammad and Humayon (2016) using the Cost to Income Ratio in controlling
financial stability. According to Delis M, Iosifidi M, & Tsionas (2016) under the impulse
of the prospect and the behavioral theories, banks with relatively low efficiency levels are
likely to take very high risk. Cost to Income Ratio interpreted that the lower the cost to
income ratio this mean the higher efficiency, the higher the bank's financial stability. The
efficiency ratio positively effect on financial stability.

Profitability Ratio is measured by Return On Asset interpreted that the higher
profitability the higher financial stability, this means that the profitability ratio has positive
effect on financial stability. Cihak and Hesse (2010), Gamaginta and Rofikoh (2011) used

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Proceedings [e ISBN 978-629-97614-0-2]
International Conference on Accounting, Management and Economics (ICAME2022)

14-15 December 2022│Faculty of Management and Economics,
Universiti Pendidikan Sultan Idris

Profitability Ratio was measured by Return On Asset to controlling financial stability.
Liquidity Ratio is measured by Total Deposits to Total Financing, which is expressed by
the Islamic Bank Financing to Deposit Ratio (FDR). Chakroun and Gallali (2013), Mosab
and Tabash (2014) use this ratio to control financial stability. The higher the risk, the lower
the liquidity held by banks. Liquidity Ratio negatively effect financial stability, interpreted
that the higher the liquidity ratio, the lower the bank's financial stability.

Islamic Bank needs to control the liquidity ratio in accordance with Bank
Indonesia’s rule. Efforts for Islamic banking in the liquidity squeeze one of them is to
increase savings. Liquidity Ratio is expected not to trigger a banking instability. Do not let
Islamic bank financing taps open as wide as possible while insufficient liquidity. Credit
Risk Ratio as measured by Non Performing Financing to Total Financing ratio is
interpreted that the Credit Risk The higher the ratio, the greater the amount of debt that is
guaranteed by the bank, it means the risk of failure should be imposed and credit risk
increase. Shahid and Abbas (2012), Chakroun and Gallali (2013), and Mufda J.A, Shamsul
R. M. S, Mohd Tahir I (2014) use this ratio to measure the stability of the bank. Credit Risk
Ratio negatively affect to financial stability, interpreted that the higher the Credit Risk
Ratio, the lower the bank's financial stability.

According to Cihak and Hesse (2010) the income diversity follows Leaven and
Levine define as the income diversity capture the degree to which banks diversity from
traditional lending activities. For Islamic banks, the net interest income is generally defined
as the sum of the positive and negative income flows associated with the Profit and Loss
Sharing (PLS) arrangements. To further capture differences of Islamic banks in their
business orientation, we interact the income diversity variable with the Islamic bank
dummy. Controlling for these variables are important because there are differences in these
variables between Islamic and conventional banks.

Cihak and Hesse (2010), Chakroun and Gallali (2013), and Muhammad and
Humayon (2016) measured market concentration in-Hirscman Herfindahl Index (HHI) to
measure financial stability. This ratio is used to detect the effect of market share financing
offered by Islamic banks to the stability of the bank. The higher the market concentration,
the market is getting stronger financial stability. Market concentration have positive effect
on financial stability.

Cihak and Hesse (2010), Chakroun and Gallali (2013), and Muhammad and
Humayon (2016), Rashid et al (2017) used Gross Domestic Product (GDP) Growth Rate
to measured financial stability. Macroeconomic indicators are measured by Gross
Domestic Product (GDP) Growth Rate has positive influence to financial stability, where
the higher GDP Growth Rate, the higher financial stability. Cihak and Hesse (2010),
Chakroun and Gallali (2013), and Muhammad and Humayon (2016), Rashid et al (2017)
use Inflation in measuring financial stability. Macroeconomic indicator as measured by
inflation have negative influence on financial stability, where the higher the inflation the
lower financial stability and vice versa.

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Proceedings [e ISBN 978-629-97614-0-2]
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Universiti Pendidikan Sultan Idris

3. RESEARCH METHODOLOGY

Multiple regression analysis is used to investigate the impact of bank-specific
characteristics, market concentration, and macroeconomic variables. In the meanwhile,
parametric (t test) and nonparametric (Mann-Whitney and Kolmogorov Smirnov) tests are
employed to compare the mean bank specific indicators and Z score for Islamic and
conventional banks in Indonesia. The factors of Islamic and conventional bank stability
were investigated using pooled OLS regression analysis.

Before performing regression analysis, first we need to perform a classical
assumption test on the data to ensure that the best linear assumptions of unbiased data are
fulfilled. Before the estimated equation models can be used for hypotheses tests, the data
stationary normality, multicollinearity, autocorrelation, heteroskedasticity are some of the
issues that need to be identified and addressed in the panel estimation techniques.

The sample size was 50 banks, with 9 Islamic banks and 41 mainstream banks
included. The data was collected from the Bank's Annual Report for the years 2008 to 2017.
The data utilized in this study was collected from the financial statements of Indonesian
Islamic and conventional banks from their annual reports from 2008 to 2017. Financial
statements for conventional full-fledged banks were acquired from the data directory
Indonesia Stock Exchange (IDX), whereas data for Islamic full-fledged banks were
obtained from the websites of each bank, Financial Authority Service, and the central bank.

Bank stability is measured by bank specific indicator, market concentration, and
macroeconomic indicator, in accordance with the indicators used by Cihak and Hesse
(2010), Muhammad and Abbas (2012), Chakroun and Gallali (2013), Hateem, et al (2013),
Dawood, et al (2016), Muhammad and Humayon (2016), Santoso, et al (2016), Odeduntan
(2016), Rashid, et al (2017). At this research Bank performance is measured by bank
specific using CAMEL ratio these are Capital Adequacy Ratio (CAR), Asset Quality Ratio
is measured by Firm Size (Ln Total Assets Ratio), Efficiency Ratio is measured by Cost to
Income Ratio (CIR), Earning quality or Profitability Ratios measured by Return On Assets
(ROA), and Liquidity Ratio is measured by Financing to Deposit Ratio (FDR) and other
ratio is Risk and solvency ratio is measured by Loan to Assets, Income Diversity is
measured by Leaven and Levine. In addition market concentration is measured by
Herfindahl-Hirscman Index (HHI) and macroeconomic indicator such as Gross Domestic
Product (GDP) growth rate and inflation.

Following Cihak & Hesse (2010) this study use Z score to measure bank stability.
This indicator has an advantage to measure the probability of bank’s insolvency as follow:

Z = (k+µ)/σ ……………………………………………………………...............(1)

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Proceedings [e ISBN 978-629-97614-0-2]
International Conference on Accounting, Management and Economics (ICAME2022)

14-15 December 2022│Faculty of Management and Economics,
Universiti Pendidikan Sultan Idris

Where k is an equity capital and reserves as percentage of asset, µ is an average return as
percentage of assets, while σ is a standard deviation of return on assets as a proxy for return
volatility.

Multiple Regression analysis is used to examine the effect of bank specific
indicators, market concentration, and macroeconomic indicators (Zarrouk, et al, 2015;
Rashid, et al, 2017) as follow:

Zit = α + β1T + β2CARit + β3LN(TA)it + β4CIRit + β5ROAit + β6FDRit + β7NPFit+
β8INCDIVit + β9Hit + β10GDPt + β11INFt + β12P + ԑit …………………………(2)

The bank's cross section dimension is denoted by i, while the time series dimension
is denoted by t. IB is a dummy variable that represents bank type, with a value of 1 for an
Islamic bank and a value of 0 for conventional banks, and Period is a dummy variable that
represents crisis period, with a value of 1 for during the crisis (2008-2010) and a value of
0 for after the crisis (2011-2017). According to Grotenhuis and Thijs (2015), value 1
denotes "this unit belongs to category x" or "included," whereas value 0 denotes "this unit
does not belong to category x" or "excluded." k – 1 dummy variable can be used, where k
is the total number of categories in the ordinal/nominal variable. The category left out of
the calculation is referred to as the ‘reference category.' All the dummy variables'
parameters represent the difference/deviation from this reference category. Following
Brown (1968), Yip and Tsang (2007) dummy variables were used to discover any
systematic differences that are traceable. The dummy variables in this study are as follows:
bank type (Islamic and conventional), and crisis period (during crisis and post crisis).
According to Gujarati (2015), the dummy variable coefficient is frequently referred to as
the differential intercept coefficient since it explains how much the intercept value that
receives a value of 1 (included dummy) differs from the intercept excluding dummy
coefficient (value 0). The meaning of the positive sign on the differential intercept
coefficients is "greater," whereas the interpretation of the negative sign is "lower."

The dependent variable is the Z score, while examine of bank specific, market
concentration, and macroeconomic variables. Bank specific indicators devided of Capital
to Risk Weighted Assets to examine the effect of Capital Adequacy Ratio, LN(TA) to
examine the effect of firm size. The Cost to Income Ratio (CIR) to examine the efficiency
of bank’s management, the Return On Assets to examine the effect of profitability. The
Problem Financing Rate to Total Financing Ratio to examine the effect of credit risk. Cihak
and Hesse (2010); Muhammad and Humayon (2016) state that to examine the differences
of the structure of the bank’s income is use income diversity that follows Leaven & Levine.

Market concentration is by the Herfindahl Hirshman Index, defined as the sum of
squared market shares (in terms of total assets) of all banks (Cihak and Hesse, 2010). While
macroeconomic indicators are examined by GDP Growth and inflation. The period dummy
variables for during Global Financial Crisis (GFC) peiod 2008-2010 and post GFC period
2011-2017.

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Proceedings [e ISBN 978-629-97614-0-2]
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Universiti Pendidikan Sultan Idris

4. FINDINGS
4.1 Regression Analysis

To examine the determinants of banks stability, both Islamic and conventional banks using
equation (2). The results are shown in table 1. Specification of model at equation (2) is
similar to several previous research, such as Cihak and Hesse (2010), Shahid and Abbas
(2012), and Rashid, et al (2017). The different from previous study is on bank specific
variable added Capital Adequacy Ratio (CAR).

Table 1 Coefficientsa All Banks

Unstandardized Standardized

Coefficients Coefficients

Model B Std. Error Beta t Sig.

1 (Constant) -7.843 3.698 -2.121 .034
5.225 .000
CAR 1.519 .291 .220 5.070 .000
-1.964 .050
Size .515 .102 .283 -2.724 .007
2.573 .010
ROA -42.421 21.596 -.147 -2.039 .042
.481 .631
CIR -3.555 1.305 -.211 -5.174 .000
1.712 .088
LDR 4.382 1.703 .119 -.956 .340

NPL -42.443 20.821 -.092

IncDiv .520 1.081 .023

Market -28.883 5.582 -.262

GDP 110.315 64.444 .093

Inflation -18.353 19.196 -.052

a. Dependent Variable: Z_Score

Based on findings in table 1 coefficient of regression analysis for all banks shows
that the determinants of the factors that effect bank stability are Capital Adequacy Ratio
(CAR), Size, Return On Assets (ROA), Net Performing Loan (NPL), and Market indicates
significant at the 5% level. Subsequently the determinant of the factors that effect bank
stability indicates significant at 10% level are Cost to Income Ratio (CIR), Loan to Deposit
Ratio (LDR), and Gross Domestic Product (GDP) Growth Rate While Income
Diversification and Inflation indicates no significant effect to Bank Stability.

The first indication of bank specificity was the Capital Adequacy Ratio, which was a
predictor of stability for both Islamic and conventional banks (CAR). The CAR coefficient
signals were positive and significant at 1%, implying that increasing the CAR tended to
enhance the level of stability. Following that, the Size coefficient indications suggested a
negative and significant relationship at the 1 per cent level.

139

Proceedings [e ISBN 978-629-97614-0-2]
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Universiti Pendidikan Sultan Idris

The sign of the coefficient of profitability ratio, which was proxied by ROA was
negative but insignificant. This demonstrates that the observation findings failed to refute
the Hypothesis, which states that profitability ratio has no positive significant impact on
the stability of Islamic and conventional banks. The coefficient sign of the efficiency ratio,
which was proxied by the Cost to Income Ratio (CIR), was negative and statistically
significant at 10%. The coefficient sign of the liquidity ratio, which was proxied by the
Loan to Deposit Ratio (LDR), was positive and significant at 5 per cent level.

Furthermore, the sign of the coefficient of credit risk ratio, which was proxied by
Non-Performing Loan (NPL), was negative but statistically insignificant. This
demonstrates that the observation findings failed to refute the Hypothesis, which states that
credit risk ratio has no negative substantial effect on the stability of Islamic and
conventional banks. The last bank-specific indicator was Income Diversification (ID), with
a positive but negligible coefficient sign. This demonstrates that the observation findings
failed to refute the hypothesis that income diversification has no substantial effect on the
stability of Islamic and conventional banks.

Following that, the coefficient of market concentration indicates a negative and
significant relationship at 10% and 5% levels. This demonstrates that the observation data
failed to refute Hypothesis, which states that market concentration has no positive
substantial impact on the stability of Islamic and conventional banks. The fourth category
was macroeconomic indicators; the first indicator was GDP, and the coefficient sign at
Model (3) was positive but insignificant, whereas the coefficient at Model (4) was positive
but insignificant. This demonstrates that the observation findings failed to disprove the
hypothesis that GDP has no major effect on the stability of Islamic and conventional banks.
The last indicator was inflation, the coefficient sign indicated a negative but insignificant
relationship.

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Universiti Pendidikan Sultan Idris

Table 2 Coefficients Conventional Banks

Unstandardized Standardized

Coefficients Coefficients

Model B Std. Error Beta t Sig.

1 (Constant) 15.210 1.341 11.339 .000
17.886 .000
CAR 1.057 .059 .583 -9.967 .000
-1.414 .158
Size -.668 .067 -.483 -4.790 .000
6.442 .000
ROA -7.523 5.323 -.092 -4.313 .000
.685
CIR -1.447 .302 -.317 .405 .000
4.513 .359
LDR 3.171 .492 .235 -.917 .057
-1.909
NPL -18.715 4.340 -.148

IncDiv .117 .288 .015

Market 12.780 2.832 .207

GDP -12.832 13.986 -.038

Inflation -7.838 4.106 -.077

a. Dependent Variable: Z_Score

Based on findings in table 2 coefficient of regression analysis for conventional banks
shows that the determinants of the factors that effect bank stability are Capital Adequacy Ratio
(CAR), Size, Cost to Income Ratio (CIR), Loan to Deposit Ratio (LDR), Net Performing Loan
(NPL), and Market indicates significant at the 5% level. Subsequently the determinant of the
factors that effect bank stability indicates significant at 10% level inflation. While Return On
Assets (ROA), Income Diversification, and GDP Growth Rate indicates no significant effect
to Conventional Bank Stability.

Table 3 Coefficients Islamic Banks

Unstandardized Standardized

Coefficients Coefficients

Model B Std. Error Beta t Sig.

1 (Constant) 537.459 73.292 7.333 .000
.468 .641
CAR 2.424 5.175 .043 -7.191 .000
1.482 .142
Size -17.370 2.416 -1.214 .694 .490
-.940 .350
ROA 110.527 74.574 .163 .190 .850
-.965 .338
CIR 4.715 6.798 .079 4.362 .000
-1.263 .210
LDR -4.005 4.259 -.077 -.458 .648

NPL 25.378 133.381 .018

IncDiv -3.052 3.164 -.081

Market 85.642 19.632 .674

GDP -353.267 279.665 -.137

Inflation -35.293 77.044 -.046

a. Dependent Variable: Z_Score

Based on findings in table 3 coefficient of regression analysis for Islamic banks shows
that the determinants of the factors that effect Islamic banks stability are just Size and Market
indicates significant at the 5% level. While Capital Adequacy Ratio (CAR), Return On Assets
(ROA), Cost to Deposit Ratio (CIR), Loan/Financing to Deposit Ratio (LDR), Net Performing

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Loan/Financing (NPL), Income DiUvneivrserisfiitci Paetniodind,ikGanDSuPltaGnrIodrwisth Rate, and Inflation indicates no
significant effect to Islamic Banks Stability.

5. CONCLUSION

The main result of this study are factors that have a significant effect on Islamic banks
stability are only size and market, while the factors that effect conventional banks stability are
Capital Adequacy Ratio, Size, Cost to Income Ratio, Loan to Deposit Ratio, Net Performing
Loan, Market, and Inflation. This study's contributions are extremely beneficial not only to
bank executives, but also to bank customers and investors. The findings contribute to a better
understanding of how bank-specific variables and macroeconomic indicators relate to banking
system financial stability. The findings also help to clarify the roles of Islamic and conventional
banks in financial stability. Furthermore, the findings indicate that encouraging healthy
competition in the banking sector may increase banks' contributions to financial stability. The
findings are relevant for macroeconomic indicators in the sense that implementing
sustainability should be implemented to increase GDP's positive influence on financial stability
while decreasing inflation's negative influence on financial system stability.

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CM019

THE EMPIRICAL ANALYSIS OF GOVERNMENT EXPENDITURE IN
EDUCATION AND HEALTH CRISIS DUMMY ON ECONOMIC
GROWTH IN MALAYSIA

Kavithanjali a/p Sandrasegaran

Phd Student, Faculty of Management and Economics, Universiti Pendidikan Sultan Idris(UPSI)
Email: [email protected]

Norimah Rambeli

Associate Professor, Faculty of Management and Economics, Universiti Pendidikan Sultan Idris(UPSI)
Email: [email protected]

Norasibah Abdul Jalil

Associate Professor, Faculty of Management and Economics, Universiti Pendidikan Sultan Idris(UPSI)
Email: [email protected]

Asmawi Hashim

Senior Lecturer, Faculty of Management and Economics, Universiti Pendidikan Sultan Idris(UPSI)
Email: [email protected]

Emilda Hashim

Lecturer, Faculty of Management and Economics, Universiti Pendidikan Sultan Idris(UPSI)
Email: [email protected]

ABSTRACT

The focal point of this study is to investigate the relationship between the Government spending on
Education (EDU), Unemployment Rate (UNEM), Consumer Price Index (CPI), and Health Crisis(D3)
in Malaysia. This study utilizing the Ordinary Least Square (OLS) in developing the multiple linear
regression for the model with and without health crisis dummy (D3). This study adopts the monthly
data spinning from 2010 until 2020. According to the results, the education expenditure (EDU) effect
the GDP negatively and significant for both model with and without the crisis dummy variable (D3).
The result further suggest that, the crisis dummy variable is negatively affect the GDP in the long
term. Moreover, the CPI is positively significant influence the GDP in the long term. Yet, the
unemployment is not significant influence the GDP. In conclusion, the main finding in this study is
contradict and persistence with some of previous studies. As implication, further study by using the
dynamic approach is recommended to improve the existing models, for instance the VECM and
ARDL in order to estimate the short- and long –run relationship between the variables.

KEYWORDS
Economic growth, Government Expenditure, Ordinary Least Square,

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1. INTRODUCTION

The increasing competition in the economy creates an issue efficiency become very important. So
that every country, including agencies world related in the field of development, felt the need to get rid
of all kinds of distorting activities economy headed for efficiency, and corruption became the main
target. Gross Domestic Product, is one of the prominent indicators of the national economics. It has
been a trademark that these indicators annually aggregate the production on the total goods and total
services in a country. On this study GDP were used as a measuring means for the growth of economic.
GDP were used to ration the market rate of final goods and services that are produced by resources
that exist in a state over a period, frequently one year. GDP can also be used in the economic study
over the time as well as associate it with the economics at a certain period. There might evoke of the
questions is one country that has a higher GDP compare to others tend to stand as a better one? If it is
rejected, then why a country tends to put GDP as the main target of a state’s policy? Was not the
living standard of a country’s people as well as their welfare should be the main goal of a state?

However, to answer these question that keep on rising would not be an easy and in any way been
answered directly. The economic impact should not only be seen in the form of numbers and statistics,
because behind these figures and statistics, there are real people whose lives are squeezed as a result of
the loss of livelihood resources. The Bureau of Economic Analysis (BEA) has concepted of the GDP
clear definition where it serves as the equal of the sum of the individual consumption expenses, gross
investment private local, net exportations of good and services as well as government consumptions
expenses and gross asset. Moreover, in the recent years, Malaysian Education systems has been
debated on the scrutiny as per the debates the unemployment rate has been rising in action these days.
It also reflects that in a country where the population is still growing, the workforce is more numerous,
the young people are more, so it is a natural progression for the GDP to grow. The conceptual
framework of the study is illustrated in Figure 1. The objectives and research questions of the study
are as follows;

Research Objectives

i) Develop a multiple regression model for Malaysia's Gross Domestic Product (GDP).
ii) Determine the most relevant elements affecting Malaysia's Gross Domestic Product (GDP).
iii) Determine the elements that have the least impact on Malaysia's Gross Domestic Product

(GDP).

Research Questions

i) Is there multiple regression model for Gross Domestic Product (GDP) in Malaysia can be
developed?

ii) What are the most important factors in affecting Gross Domestic Product (GDP) in Malaysia?
iii) What are the least important factors in affecting Gross Domestic Product (GDP) in Malaysia?

The conceptual framework in Figure 1 shows the direction of relationship. In this study the dependent
variables are the economic growth. While the independent variables are unemployment rate, education
spending and consumer price index.

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Figure 1: The Conceptual Framework

Independent variable Dependent variable

Unemployment Rate Gross Domestic
- Labour market Product (GDP)
-economic growth
Education spending proxy

- Government spending in the
education

- contribution of education to
economic growth

Consumer price index
- cost of living
- inflation

2. LITERATURE REVIEW

The economic literature has long considered investing in education to be a critical component in
fostering economic growth. Education is a significant kind of investment in human capital since it
develops, enriches, and improves human capital. Human capital in the form of education has economic
worth. Education helps people acquire information through education, which may lead to greater pay
and faster economic growth. Investing in educated and competent personnel will result in more
productive utilization of labour and capital resources. A country's output and per capita income
improve with the implementation of education programmers and investments in human capital, such as
health and vocational training. As a result, when nations invest more in education, their economies
will rise rapidly.

Connolly and Li (2016) state that there are three types of government spending: public
consumption spending, public investment spending, and public expenditure. Additionally, studies
conducted by the Organization for Economic Cooperation and Development (OECD) have
demonstrated that an increase in public spending on secondary education has a favorable impact on
GDP and economic growth.

Malaysia has given the growth of its higher education system a lot of attention. The period of
higher education liberalization to enable broader access began with the passage of the Private Higher
Education Act in 1996. The number of degree holders has significantly increased in less than ten
years, but this has put a lot of pressure on the labour market and may eventually cause a problem with
graduate unemployment. Given the relationship between education, technology, and unemployment,
obtaining such high levels of education and Malaysia's economy's level of openness may put pressure
on the labour market and, as a result, over time increase the rate of unemployment.

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The Consumer Price Index (CPI) and the cost of living in a given nation are strongly correlated.
The actual cost of living index was established from the home level and then expanded into a bigger
societal level platform. It was thought that the CPI provided an assessment of the cost of a basket of
goods and services that simultaneously reflected the GDP's worth and the cost of living.

This component undoubtedly has a close relationship with GDP as it controls inflation. It all began
with a change in the CPI, continued to have an impact on the GDP deflator, and eventually inflation
occurred. The central bank will be in charge of monetary policy in order to sustain and stable the GDP.

3. MODEL SPECIFICATION AND METHODOLOGY

This study adopted the model specification proposed by Rambeli, Dayang, Podivinsky. Amiruddin &
Ismail (2021). The study used the monthly data from 2010 until 2020.

Model Specifications

This study employed the Cobb Douglast production function, basically a nonlinear productivity model,
as pioneered by Cobb & Douglas (1928). In the early development phase of the function, Cobb &
Douglas believed that a country’s productivity can be enhanced by using two main sources, namely
capital and labour force. The productivity model maintained that aggregate productivity is influenced
by these two variables. Therefore, the following basic model of Cob-Douglas model will be used;

GDPt = αCAPβ1 EMPβt υt (1)

Nevertheless, many past studies have also maintained that productivity is not only effected by capital
and labour but additionally by other macroeconomic factors (Abugamea and Gaber, 2017 and Rambeli
eta al., 2016b). As referenced to Rambeli et al. (2021) the augmented model specificantion proposed in
this study is as follows;

GDP = β UNEM β1 EDU β2 CPI β3 υt (2)
t0

Since equation (2) is a non linear model, parameter values for βi ( i = 0,1,2,3) cannot be directly

estimated. Therefore, it is suggested that the production function be amended into log-linear model as
follows:

log GDPt = β0 + β1 log UNEM t + β2 log EDU t + β3 log CPI t +ν t (3)

In equation (3), GDP represents economic growth data series and represented by Gross Domestic
Product (GDP). The UNEM is unemployment and EDU represents government expenditure in
education. CPI denotes as consumer price index. All data series are in monthly frequency as denoted

by t, and all values are in natural logarithm. The notation ν t is error term, β0 is constant and βi is

coefficient or magnitude where i = 1,2,3.

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Moreover, in this study also consider the impact of health crisis that occur at the end of 2019
(approximately December, 2019). Therefore, equation (3) expended further by taking in to account the
impact of Health Crisis Dummy;

log GDPt = β0 + β1 log UNEM t + β2 log EDU t + β3 log CPI t + β4 log D3 +ν t (4)

Equations (3) and (4) will be estimate using the ordinary least square (OLS) method through the
development of multiple regression models. The testing procedure will adopt the estimating proposed
by Rambeli et al. (2021). The study will employ the t-test and F-test for hypothesis testing. For
diagnostic test, this study utilized the heteroscedasticity, multicolinearity and autocorrelation tests.

4. EMPIRICAL RESULTS

In this study, there will be a discussion of the procedure or approaches used by the researchers to
form a prediction model for the study conducted. The approach used is the Least Square (OLS-
Ordinary Least Square) to explore on the determining factors of Gross Domestic Product (GDP) in
Malaysia. The OLS theory examines on the multi-collinearity, heteroscedasticity and auto-correlation
which been test to know whether the model is suitable or not. This study also used the SPSS
application to test each of the established variables.

Researchers investigate the relationship between unemployment rate and government spending on
education upon the Gross Domestic Product of Malaysia (GDP) where this research only focusses on
only a state. Time series data that has been reached and collected the data is from 1990-2019 which is
29 years. There are three variables which is Unemployment Rate (UNEM), Government Spending on
Education (EDU), Consumer Price Index (CPI) and Gross Domestic Product (GDP) where the data is
been collected is from website of World Bank, World Economic and Department of Statistic Malaysia.

This study consists of the total of Unemployment Rate ( ), the total of Consumer Price Index
( ), Government spending on Education ( ), Financial Crisis (D1it), World Crisis (D2it) and
Health Crisis(D3it) as its independent variables. This research focuses on the dependent variable.
Gross Domestic Product in Malaysia ( ). Every variable is tested to identify whether it has its
significances toward the GDP of Malaysia.

The study will describe the full research findings obtained from every test run on the independent
variables toward the dependent variable in this chapter. This study consists of the total of
Unemployment Rate ( ), the total of Consumer Price Index ( ), Government spending on
Education ( ), Financial Crisis (D1it), World Crisis (D2it) and Health Crisis(D3it) as its
independent variables. This research focuses on the dependent variable. Gross Domestic Product in
Malaysia ( ). Every variable is tested to identify whether it has its significances toward the GDP
of Malaysia.

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Without Health Crisis Dummy Model

From 1990 to 2018, the model is estimated as follows: (5)
GDPt = 1.022 + 0.152 UNEMt – 0.713 EDUt + 3.502 CPIt
SE = (0.953) (0.367) (0.343) (0.338)
t* = (1.073) (0.413) (-2.078)** (10.368)***
F*= 37.443; R2 = 0.806; Ṝ2 = 0.785 ; DW value = 0.555

With Health Crisis Dummy Model

GDPt = 0.991+ 0.160UNEMt –0.712EDUt + 3.511CPIt -0.011D3t (6)
SE = (1.174) (0.416) (0.351) (0.394) (0.233)
t* = (0.844) (0.386)* (-2.029)** (8.900)*** ( 0.963)*
F*=27.045; R2 = 0.898; Ṝ2 = 0.806 ; DW value = 0.559

Tables 1 and 2 simplify the t-test for equations (5) and (7). In general, the independent variable of
, and CPIit is significant in explaining the dependent variable of at 95% and 99%
significant level. The other independent variable which is, are not significant in explaining
the dependent variable. According to equation (5), the education expenditure effect the GDP
negatively, except unemployment and consumer price index. This result quite surprisingly because its
contradict with most of previous finding, for instance Abdul Jabbar & Selvaratnam (2017) and
Rambeli et al. (2016), among others studies. Particularly, there is inverse relationship between
education expenditure and economic growth. In other words, the increase in will reduces the
GDP of Malaysia by 0.713 percent at 95% significant level (Reject Ho). Explicitly, in equation (5), if
education rises by 100%, then the economic growth will decrease by 71.3%. The same result is also
found in equation (6). Meanwhile, if CPI increasing, it will increases the GDP of Malaysia by 3.502
percent at 99% significant level (Reject Ho). But, if the UNEM increase, it will lead the GDP to raise,
but not significant (Accept Ho).

Referring to equation (6), the UNEM is insignificant in affecting the GDP. But, the CPI, EDU and D3
(Heath Crisis Dummy) are significant in affecting the GDP at least 90% significant level. According to
equation (6), the education expenditure effect the GDP negatively as well as health crisis dummy
(D3), excluding unemployment and consumer price index which affecting the GDP positively. This
result quite surprisingly because its contradict with most of previous finding, for instance Abdul
Jabbar & Selvaratnam (2017) and Rambeli et al. (2016), among others studies. Particularly, there is
inverse relationship between education expenditure and economic growth. In other words, the increase
in will reduces the GDP of Malaysia by 0.712 percent at 95% significant level (Reject Ho).
Explicitly, in equation (6), if education rises by 100%, then the economic growth will decrease by
71.2%. The same result is also found in equation (5). Meanwhile, if CPI increasing by 1 percent, it
will lead the GDP to rises by 3.511 percent at 99% significant level (Reject Ho). Also, if the UNEM
increase, it will lead the GDP to raise, but not significant (Accept Ho).

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GDPt = 1.022 + 0.152 UNEMt – 0.713 EDUt + 3.502 CPIt (5)

Table 1: The results of t-test for equation (5) Result
Accept H0
Variables Hypothesis Statistical Critical Reject H0
Test (t*) Value (tꞵ) Reject H0
UNEMt H0 : 1 = 0
H1 : 1 ≠ 0 0.413 2.052 (6)
H0 : 2 = 0
H1 : 2 ≠ 0 -2.078 2.052 Result
H0 : 3 = 0 Accept H0
H1 : 3 ≠ 0 10.368 2.052 Reject H0
Reject H0
GDPt = 0.991+ 0.160UNEMt –0.712EDUt + 3.511CPIt -0.011D3t Reject H0

Table 2: The results of t-test for equation (6)

Variables Hypothesis Statistical Critical
Test (t*) Value (tꞵ)
UNEMt H0 : 1 = 0
H1 : 1 ≠ 0 0.386 2.056
H0 : 2 = 0
3 H1 : 2 ≠ 0 -2.029 2.056
H0 : 3 = 0
H1 : 3 ≠ 0 8.900 2.056
H0 : 6= 0
H1 : 6≠ 0 0.963 2.056

Based on Table 3 above, for equation (5), the results suggest that the critical value of = 2.98 is
greater than the value of statistical F value at 37.443 at the 95% significant level. Therefore the result
will reject 0. In other words, all independent variables are adequate in explaining the dependent
variable at a 95% significant level. For equation (6), the value of = 2.51 at the 95% is larger than
the value of ∗ = 22.758. Since ∗ > , 1, 2 , therefore the result will reject 0. In other words,
all independent variables are adequate in explaining the dependent variable at a 95% significant level.

Finally, both estimated equations are passed the diagnostics test namely autocorrelation,

heteroscedasticity and multicollinearity tests.

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Table 3: The results of F-test for equations (5) and (6)

Equation Hypotheses StatisticalTest Critical Result
Equation (5) (F*) Value (F)

Equation (6) H0 : 1 = 2 = 37.443 >
3 = 0 2.98 2.98
F∗ =
H1 : 1 ≠ 0 Reject H0

H0 : 1 = 2 = 22.758>2.51
3 = 4= 5 = 37.443 2.51 Reject H0
= 6 = 0
H1 : 1 ≠ 0

∗ =



= 22.758

5. CONCLUSION

This paper is to determine the relation between education, unemployment rate, customer price
index and economic growth in Malaysia from 1990 to 2020. There are many researchers has studied
on this matter however there are broader more aspects that can be evaluated and experimented on this
issue. In this research, it suggests that there are various more exploratory needed on other variables
that influence on the development of economy. Such that when the significant variable can be
identified, the government will tend to have a setting that can control on the country’s fiscal level and
degeneration. The researcher also recommends the government to make some adjustment on the
weightage of CPI as by increase the education group weight. This is as the measure of the living cost
has been hard as there are many other indicators as well influencing the behavior of consumer
spending. The government should also keep track on the unemployment rate as it also gave a
significant result on the GDP. As it also become the mean on affecting the economic growth. Thus,
more solution for this problem need to be examined and researched in future. As implication, further
study by using the dynamic approach is recommended to improve the existing models, for instance the
vecm and ardl in order to estimate the short- and long –run relationship between the variables.

6. REFERENCES

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expenditures in Malaysia. Journal of International Business, Economics and Entrepreneurship
(JIBE), 2(1), 1-10.

Abugamea, G. (2017). The Impact Of Education On Economic Growth In Palestine: 1990-
2014. Munich Personal Repec Archive.

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Azam, M., Khan, A. Q., & Bakhtyar, B. (2017). Surveying sources of economic growth: Empirical
evidence from Malaysia. Problems and perspectives in management, 15 (4), 114-123.

Aziz, R. N. A. R., & Azmi, A. (2017). Factors affecting gross domestic product (GDP) growth in
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Azmin, N. A. M., Affandi, S., Shukur, N. A., & Aumran, N. A. (2017, December). The Determinants
of Unemployment in Malaysia. International Business Management Conference (IBMC 2017)
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Cobb, C.W. and Douglas, P.H. (1928) A Theory of Production. American Economic Review, 18, 139-
165. https://www.aeaweb.org/aer/top20/18.1.139-165.pdf

Connolly, M., & Li, C. (2016). Government spending and economic growth in the OECD countries.
Journal of Economic Policy Reform, 19(4), 386- 395.

Habibi, N. (2009). The impact of the global economic crisis on Arab countries: a year-end assessment.
Middle East Brief, 40(10), 1-9

Hashim, A., Rambeli, N., & Jalil, N.A., & Hashim, E. (2019). Analyzing the Direct and Indirect
Impact of Budget Deficit and other Factors on GDP in Malaysia. International Journal of
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Hashimd, E. (2019). The Dynamic Relationship between Unemployment, Inflation, Interest Rate and
Economic Growth. International Journal of Innovation, Creativity and Change, 8(7), 89-94.

Hussin, M.Y.M., Muhammad, F., Hussin, M.F.A., & Razak, A. A. (2017). Education Expenditure and
Economic Growth: A Causal Analysis for Malaysia. Journal of Economics and Sustainable
Development, 3(7), 71-81.

Irpan, H. M., Saad, R. M., Nor, A. H. S. M., Noor, A. H. M., & Ibrahim, N. (2016). Impact of foreign
direct investment on the unemployment rate in Malaysia. In Journal of Physics: Conference
Series, 710(1), 1-10.

Kabuga, N.A., & Hussaini, M. (2015). Government Spending on Education and Economic Growth in
Nigeria: An Empirical Investigation. Kano Journal of Educational Studies (KAJEST), 4(3),
225-236.

König, M., & Winkler, A. (2021). COVID-19: Lockdowns, fatality rates and GDP growth.
Intereconomics, 56(1), 32-39.

Kouki, M., Belhadj, R., & Chikhaoui, M. (2017). Impact of financial crisis on GDP growth: The
case of developed and emerging countries. International Journal of Economics and
Financial Issues, 7(6), 212.

Noor, Z. M., Nor, N. M., & Abdul-Ghani, J (2017). The Relationship between Output and
Unemployment in Malaysia: Does Okun’s Law exist?. International Journal of Economics
and Management, 1(3), 337-344.

Okafor, M. I. & Ichoku, H. M. (2015). Benefit Incidence Analysis of Government Spending on
Education in Anambra State, Nigeria. Journal of Economics and Sustainable Development,
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Rambeli, N., Marikan, D. A. & Hashim, E.(2016a). The Effect of Foreign Direct Investment,
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Academic Research in Business and Social Sciences 2016, Vol. 6(11) 361-376. DOI:
10.6007/IJARBSS/v6-i11/2405 URL: http://dx.doi.org/10.6007/IJARBSS/v6-i11/2405

Rambeli, N., Hashim, E., Leh, F. C., Hashim, A., & Jalil, N. A. (2020). The Role Of
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Rambeli, N., Podivinsky, J. M., & Jalil, N. A. (2019). The Re-Examination Of The Dynamic
Relationship Between Money, Output And Economic Growth In Malaysia.
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Rambeli, N., & Podivinsky, J. M. (2013). A Study Of Exogeneity Tests On Export-Led
Growth Hypothesis The Empirical Evidences On Post-Crisis Exchange Rate Regime
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Volatility & Exports Nexus – “A Case For ASEAN”. Management Research
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CM020

THE RESEARCH UNIVERSITIES EXPERIENCES ON
COMMERCIALISATION SUPPORT SYSTEM (CSS)

Amin Irfan Mohamad Suwarno1
Universiti Pendidikan Sultan Idris

Siti Asma’ Mohd Rosdi2,
Universiti Pendidikan Sultan Idris

Abstract

This article explores the experiences of Research Universities (RU) on Commercialisation Support Systems (CSS) with a specific focus
in the Malaysian context. A qualitative research was carried out, in which six RU were interviewed. A structured interview was
conducted. To analyse and interpret the data was using an approach adopted in qualitative thematic strategy. The findings were
transcribed using Atlas.ti software to analyse related themes through a thematic analysis approach to link theories. Results: The findings
provide useful insights into the significant roles of support system on the commercialisation strategy and impacts on the ecosystem of
innovation and commercialisation to strengthen the role of university-industry-community relation to drive the economy towards a high-
income nation. This study will contribute theory through commercialisation literature by adding new knowledge concerning the link
between universities and support system in commercialisation. Therefore, the practical contributions are significant for universities;
industries; research institutes; government and societies to develop and plan strategically for effective, strategic and sustainable support
system in innovation and commercialisation ecosystem.
Keywords : Commercialisation Support System, Research University, Malaysia

12

1. Introduction

* Acknowledgements: This study was supported by Ministry of Higher Education (MOHE), the title of this research is “The Development of
Dynamic Support Services of Universities Research Output and Commercialisation”, research code: 2019-0168-106-62
(RACER/1/2019/SS01/UPSI//2). We thank to Research Management and Innovation Centre (RMIC), Universiti Pendidikan Sultan Idris
(UPSI), and all contributors of the research team who have contributed to this research. We additionally thank the guidance committee,
informants, and different stakeholders who participated with inside the study.

1 First Author or Corresponding Author. Amin Irfan Bin Mohamad Suwarno
2 Second Author. Senior Lecturer, Faculty of Management and Economics, Universiti Pendidikan Sultan Idris, Malaysia. Email:

[email protected] ORCID: https://orcid.org/0000-0001-8291-4997

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Malaysia is a developing country that strives to be developed. It recognises that one of the keys in achieving this ambitious
goal is to focus on the development of its higher education (HE) system. The Malaysian government has structured all public
universities into three categories, namely, Research University (RU); Focused University (FU); and Comprehensive
University (CU). The research universities (RU) are University of Malaya (UM), Universiti Kebangsaan Malaysia (UKM),
Universiti Sains Malaysia (USM), Universiti Putra Malaysia (UPM) and Universiti Teknologi Malaysia (UTM). These
research universities (RU) are required to focus primarily on research and innovation activities, driven by highly competent
academics and competitive student admissions. Research universities (RU) are expected to explore their intellectual capacity
and become models of Malaysian universities in conducting research activities aimed at knowledge advancement. Apart from
this research universities (RU) are entrusted to generate their own income and establish holding companies responsible for
conducting business ventures through the commercialization of their research products (Da Wan et al., 2020). Thus, the higher
education institutions (HEIs) have been geared towards reduction of reliance on the government, and universities are required
to generate own income through commercialisation and other income generating activities (Da Wan et al., 2018). Definitely,
universities play a pivotal position within the innovation atmosphere, given their position within the introduction and diffusion
of recent knowledge, simultaneously changing the role of university traditions, from teaching and learning to innovation and
commercialisation (Da Wan et al., 2020).

To enhance diffusion, the institutional framework must promote knowledge sharing among innovation players, namely
knowledge creators and users. As a result, the phrases Triple Helix, Quadruple Helix, and Quintuple Helix have gained
acceptance in academic circles. Etzkowitz and Leydesdorff (2000), find knowledge and use in context of university-industry-
government relation are on the focus on The Triple Helix meanwhile the Quadruple Helix extends of it by adding the helix of
media-based and culture-based public (Carrayanis & Cambell, 2009). Consequently, the emergent Quadruple Helix Model of
Stakeholder Relationships reflects a shift from the normative Triple Helix (government, university and industry) to include
end users as a core stakeholder in regional innovation ecosystems (Carayannis & Campbell, 2009; Leydesdorff, 2012;
Carayannis & Rakhmatullin, 2014; Lara et al., 2021).

This paper seeks to explore the experiences of Research Universities (RU) on commercialisation with a specific focus in
the Malaysian context. This paper consists of six sections. First, this paper generally introduces the research universities
and its role in higher education system. Second, discuss on the current issues on commercialisation. Third, the methodology
to explore the experiences of RU on commercialisation, guided by the question: “What experiences do RU perceived in
commercialisation?”. This is followed by section four which discusses the finding. The conclusion briefly deliberates in
section five, limitation and future research deliberates the final section.

2. Literature Review

2.1. Current Issues on Commercialisation

The ecosystem of innovation and commercialisation still needs to improve due to the dynamic challenges especially in
the era of COVID-19 pandemic. Innovation and commercialisation are indeed a challenging process for HEIs. HEIs face
competition and challenges in order to gain competitive advantage in both national and international settings. For example,
changing government policy, ongoing student growth, stakeholder demand for quality, change in leadership, renewed
institutional strategy; and financial sustainability are some of the internal factors contributing to the challenges within
universities (De Wan et al., 2018). According Miller et al. (2018), challenges of academic entrepreneurship include three
levels of challenges. The first level is individual challenges such as lack of resources for combining different roles and absence
of entrepreneurial role model, the second level of challenges is institutional level challenges such as lack of legitimacy and
incentives, lack of institutional support, and uncertainty university roles for society and the third level of challenges is regional
level challenges such as policy related issues, geographical proximity and clusters presence.

Unfortunately, in 2020, the prolonged lockdown imposed by political authorities to halt the development of the COVID-
19 had negative effects felt all around the world. As to overcome, the pandemic outbreak is likely to require global effort,
sharing resources, knowledge and global cooperation to deal with other global challenges; practicing more openness in science
and technology for example, user innovation find attractive business uses is to experiment in a wide variety of strategic ways
(Ramdan et al., 2021; Siegel & Guerrero, 2021).

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However, in the real world of today, the process of establishing, growing, and maintaining structured techno-companies
can be difficult and complex. Competencies such as R&D contracts, suppliers, customers, and competitors can be required to
translate scientific output into marketable goods or services in order to gain a competitive advantage (Mascarenhas et al.,
2018; Cenamor, 2021). In this sense, techno-companies have to gain profit by creating new values and accomplish competitive
advantage through innovation and commercialisation capabilities while providing new product and service development
through R&D, investment and quality improvement (Kim et al., 2020). The linkages and network between these players are
weak and fragmented (Khin et al., 2017). Siegel and Guerrero (2021), have identified three new areas of micro and macro
research on how COVID-19 affects the commercialization of science.

The first thing to pay special attention to is the performance, quantity and quality of research bases and performance,
social networks, and strategic management of innovation, commercialization of research as well as the relationship between
universities and industry. The second point of concern is innovation and the entrepreneurial ecosystem which have important
public policy implications as there is substantial public investment in property -based institutions and high -tech economic
development initiatives. The third thing to pay attention to is the scientific workforce, such as role conflict, identity, work-
life balance, ‘winning’, organizational justice and leadership. This is important to understand micro and macro, especially
those involved in commercialization efforts to assist and determine how to better manage the scientific workforce and the
process of commercialization of research in challenging conditions. Thus, the innovation and commercialisation support
system still need to be enhanced due to the dynamic issues and challenges (Khin et al., 2017).

Malaysia continues to rely heavily on technology transfer from abroad to boost its competitive advantage in export
markets. In addition, technopreneurs face operational and strategic challenges such as achieving monetary sustainability;
finding and retentive management groups with the proper mentality and skill sets; and strive to achieve the right “deal flow”
(Khin et al., 2017). Prior literature indicates that industry players require support in term of technology, market, finance,
training and skill development programs (Heydebreck & Klofsten, 2000). Therefore, the accessibility of the support system
is crucial as it facilitates and accelerates its operation and commercialisation process to transform Malaysian innovation
landscape not only the needs of society today, but critically, of tomorrow.

2.2. Commercialisation Support Systems (CSS)

A commercialisation atmosphere is a mixture of diverse social, political, economic and cultural, technology, marketplace
and community factors inside a place that guide the development and growth of innovative start-ups, assist and evokes nascent
technopreneurs to require on the beginning and funding risky ventures (Mason & Brown, 2014). The essential concept of
commercialisation environment is to create and surroundings conducive to assisting innovation, forming new success
ventures, and producing the corresponding sustainable employment growth inside a selected geographic region (Brekke, 2015;
Jacson et al., 2018). Ecosystems constitute extra of a conceptual umbrella encompassing a whole lot of exclusive views at the
geography of entrepreneurship instead of a coherent principle approximately the emergence of a sustainable group of
technology entrepreneurs (Spigel, 2017).

The commercialisation support systems can be best understood from the perspectives of technology support; market-
support; finance-support; know-how support and leadership-support as stated below.

Technology-Support: Technology-support provided by government-funded incubators, new technology developed in
educational institutions, imported technology know-how, locally available talent pool. The use of technology in the right way
would provide a firm with various alternatives, possibilities, and opportunities in a mission to form alliances, making deals
and discerning motives (Hsieh, 2010). It is important for a firm to create the right framework, have the flexibility and
willingness to think creatively to gain advantage as the first movers (Bridge, 2012; McRae, 2010). Innovation is necessary as
new ideas, novelty, experiments and inventive processes lead to new products, services or technological processes, in addition
to the search for creative, unusual or new problem solutions (Certo et al., 2009; Madhousi et al. 2011). According to Mazidah
(2014), many SMEs neglect the significant role of innovation and technology to their business performance. Abdullah et al.
(2009), claimed that only a small portion of SMEs took the challenge to embed technology in their business operation even
though the Malaysian government has implemented many initiatives to promote the use of technology. Realizing the
importance of technology has a strong relationship with innovation, it is very important to have an understanding of
technology support.

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Market-Support: Market-support refers to the support system that provide entrepreneurs with the support of finding a
place in the market, as well as ways to market entrepreneurs' products. In addition, it consists of certain business associations,
alumni associations and online social sites consisting of Facebook, LinkedIn, friends, community-markers and distributors
(Sujianto, 2021). Also, in Malaysia a lot of agencies that provide the support for entrepreneurs such as SMECorp Malaysia,
Majlis Amanah Rakyat (MaRa), Center for Entrepreneur Development and Research (CEDAR), Institut Keusahawanan
Negara (INSKEN), and Perbadanan Usahawan nasional Berhad (PUNB) (11th Malaysia Plan 2015). According to Kee et al.
(2010), building and developing the right networks is the most critical key success factor.

Financial-Support: Financial support include assistance with European Community programs, intermediation with
financiers and direct assistance in financing new innovative projects (Heydebreck et al., 2000). Financial assets should
construct and strengthen the technology base, acquire formal IPRs in a way that limits the risk of expropriation, find and
access suitable partners. An observation by Svensson (2007), indicates that patents in the first phases are characterized by
high costs and a lack of income thus requiring considerable amounts of funding. Financial assistance comes from local family,
banks, Venture Capitalists, friends, relatives, in-laws, educational institutions, angel buyers, and small buyers from the capital
market, foreign monetary institutions, government agencies and supplier credit rating.

Know-How Support: Know-how is anticipated to consult the understanding and attempt out something new on the way
to attain the goal; consolidation of lessons discovered via practice (Elzinga, 2021). Know-how support system is regarding
the expertise includes access to education and knowledge, talent pool, empowerment of human capital, community
participation, mentoring, coaching and moral support. Reward and collaboration are the two factors to foster knowledge
creation process and by knowledge creation process, it will enhance the R&D project (Xue et al., 2018; Yee et al., 2020).
Also, knowledge collaboration allows the two companies to use their individual strengths to overcome the weakness of each
company (Yee et al., 2020).

Leadership-Support: Leadership support is understood to mean the actions and decisions of the actors who have been
assigned key roles in a higher education system. Within individual HEIs, those actors consist of especially the individuals of
governing boards, the members of vice-chancellors, executive group, and the members of academic senates (Wan et al., 2020).
These actors are involved with what is described by Gallagher (2001, p. 49) as leadership, that is in “seeing opportunities and
setting strategic directions, and investing in and drawing on people’s capabilities to develop organizational purposes and
values.” Leadership-support includes governance, policy coordination, regulatory, transparency, public services delivery,
procurement, and political environment.

3. Research Methods

The objective of this research is to explore the experience of RU on commercialisation phase. In this case, the case study
technique appears to be suitable considering the fact that this paper is an exploratory study of those ambitions to increase a
higher knowledge of the support system in commercialisation. We chose this population, research university outputs. One of
the reasons is that RUs spend lots of grant money on research projects but only few percentages of outputs are commercialized
(MOSTI, 2018). So, this study will uncover the support system that will help them generate economic return for the invested
effort in research projects. Therefore, this research targeted one RU in Malaysia due to the recognition of excellent status in
innovation and commercialisation. Structured interviews were administered during work hours.

We took a qualitative approach with structured interviews. The structured interviews were conducted in January 2020. We
operationalized our enquiry by asking broad questions about the commercialisation’s support system in Malaysia. The consent
of the interviewees was obtained for the recording of the interview. All questions were open ended. The interview lasted an
hour on average. Use an open interview schedule such as the following questions: “What experiences do you perceive of the
support system in commercialisation?”

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Upon completion of data collection through interview sessions, the findings were transcribed using Atlas.ti software to
analyse related themes through a thematic analysis approach to link theories (Ramdan et al., 2020). Thematic analysis refers to
a procedure that allows for easy information retrieval and organizes important and relevant themes or sub -themes, which can
then be applied (Javadi & Zarea, 2016; Guest et al., 2020). Specifically, this software can help easily read, organize and encode
data as it has comprehensive online support guidelines to assist users (Friese, 2019; Othman, 2019). Thus, the support of themes
was divided into codes corresponding to the findings of the study which could be categorized separately.

Each recorded interview transcribed verbatim in English. At the beginning of the interview process, we coded data related
to different themes, then used different methods to identify key themes (Glaser & Strauss, 1967). Through non-stop methods,
we discover the sub-theme under each main theme, such as trends or descriptors, and the nature of the theme underlying the
study. By non-stop methods, we discover the sub-themes under each main theme as properties or descriptors making explicit
the underlying theme properties. The data are provided thematically and the connection among findings and literature is
included into thematic discussions (Glaser & Strauss, 1967).

3.1. Data Analysis

To analyse and use the data, we used qualitative thematic strategies (Boyatzis, 1998). Data are presented thematically and
the relationship between findings and literature is integrated into thematic discussions (Glaser & Strauss, 1967).

4. Results and Discussion

The results of the interviews are presented below:

“In terms of technology, we have an organization called ITMA, Innovation and Technology Manager Association.
Currently its president is UPM. I am from AJK only. It has a lot of potential in it. We also have Malaysian Bioeconomy
Development Corporation Sdn Bhd. We also have CREST Sdn Bhd, a government-owned company; commercials do not just
talk about technology because innovation can be product, technology and know-how. Therefore, the importance of technology
in commercialization is depending again by project. There are technological projects, some more than expertise” (RU1).

“Technology is an enabler now in people’s everyday tasks; computers and smart devices are becoming an indispensable
part of life. Technology nowadays is building fast, even 5G technology will widely use in the future. The evaluation
demonstrates that the commercial potential of information technologies and biotechnologies are most influenced by elements
such as technology features and value for the consumer by using technology for commercialisation, it will increase the rate
of successful” (RU2).

“Most of start-up businesses in Malaysia need to access this kind of support and by the help from consultant/expert or RU
will increase chances to get the support. The agencies that provide these supports such as Malaysian Industrial Development
Finance Berhad (MIDF), Majlis Amanah Rakyat (MARA), Technology Park Malaysia (TPM), SME Corporation, Malaysian
Technology Development Corporation (MTDC), Ministry of Science, Technology and Innovation (MOSTI), Federal
Agriculture Marketing Authority (FAMA) and SIRIM Berhad” (RU3).

“This university is actually in my opinion; it has a very clear platform. Now any university must have at least one
innovation centre in cooperation with the research management centre. Why a research management centre? Because in the
Research Management Centre (RMC) we usually call CCI do not be surprised if you use that term. When a research
management centre he manages and when he manages the funds, he has to make sure there is output. In addition, that output,
all kinds of output and one of them is intellectual property. Okay. because the output can be human capital, student, it can
also be output, okay, expertise, and well that means that people are not experts, so are experts. But along with the big
innovation centre is IP. Therefore, our academicians are also technopreneurs because some of them not only do research, they
have IP and commercialise their R&D output. As you asked about -support, yes we need it to support our research output in
the marketplace, ways to distribute our products” (RU3).

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“How to commercialese this thing, meaning how product to be recognised and want to be commercialise. Of course, we
need that technology support in term of distribution maybe via online social sites like Facebook, LinkedIn, and others
platform…business network, financial incentives, R&D grants and promoting technology distribution. A lot of research, lot
of IP but the commercialise very low including industry demand low, why?. The government needs to look at policies especially
supply chain and distribution system. Universities need to understand the needs of the industry and understand the needs of
the local community. Industry, don't think he needs R&D because that's what determines his profitability at the end….
Researcher does market research. What makes it an innovation centre?” (RU4).

“The centre of innovation is the safest way to avoid unwanted legal issues with a special purpose vehicle. Not only for the
promotion but also for the endorsement of the job and not only for the academic staff it should be available to the executives.
Social science is okay. That is all I can suggest ... So, yes I believe it helps to clear the guidelines. In all areas of innovation–
incubation-university. The driving line must be clear. The second is to ensure that the researcher understands the need to
protect intellectual property, when protected, there should be a feeling of market driven rather than market push because we
think that is what universities should be more like” (RU5).

“In any case, SMEs are the only university that generates market reports for researchers. Other universities do not, so
industry and government need to join forces to create an IP Repository marketplace. This means that there is one ministry
that holds a single database where all the IP Universities are located. Ready with description is not just a list. So when the
industry has access to it, they can shop. To this day it is no longer in Malaysia ... So in order to promote this innovation what
I suggest is that at the start of 2017 all public universities have sent representatives to discuss with MyIPO about building an
IPR market place. It's where it helps promote intellectual property from universities to industry”. So, we are playing that role
especially the technology and innovation. We have the labs, we have the experts here. So, which can grow and contribute into
higher level but need to strategies on how the best that we can contribute to the other channel in other words to through the
commercialization” (RU5).

“This leadership must be on the research track, the entrepreneurial track, and the legal track. It means they understand
the results of research, entrepreneurship, legal and financial. To support innovation, leadership research in innovation on
publishing, consulting, intellectual property (IP) innovation, legislation and regulation and policy. Financial is about
financial governance. Financial governance means that there is a budget, some in terms of accountability. Integrity is in the
legal aspect. These leadership characters are essential in guiding an innovation; there is competency and knowledge about
research. That's why I believe that any university's innovation centre must be guided by academics. So, in this case managerial
and technical competencies that we see must be related to these 4 things. Research, innovation, legal and financial” (RU2)
“Recently we will find recruit new marketing officer for help or to promote.so far we don’t have it, we lacking at marketing…
So, Marketing Officer really not just our problem but others also don’t have the position for marketing officer for universities,
no warren that warren don’t have, need to use N or Q, so that also the things we still confuse. Can’t use Q, because Q is
researcher. So, now we proposing warren for real…” (RU6).

Therefore, technology support system is essential for innovation and commercialisation in today’s know-how intensive
and innovation-led economy. Not surprisingly, technology, innovations and commercialisation have created successful techno-
companies that have transformed industries landscape and society as a whole through new economic growth that increase jobs
creation and wealth. The development of R&D in Malaysia is evolving from time to time through innovation and
improvement of various aspects as well as developing human capital skills among academics in addition to the competencies
and outcomes of science, technology and innovation (Fini et al., 2020). Recognizing the importance of productivity to model
improvement, research assets and expenditure, of course, Malaysia recognizes the need to adopt an innovation -driven
improvement model to weather the dynamic global crisis and achieve its aspiration to transform into a high -income nation.
To prepare for the Smart Industry 4.0, the support system for innovation and commercialization in Malaysia needs to be
strengthened. Given that commercialisation includes transferring information from research laboratories to market areas to
innovative products and services, there is a need to focus efforts on improving the governance effectiveness of public research
systems with a view to positive impact and impact in markets and society (Liboreiro et al., 2022).

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Therefore, innovation and commercialisation entail collaborating between academia and industry to successfully move
new scientific discoveries, information, and technologies from the research lab to the market (Clayton et al., 2018). These two
inter-related ideas of innovation and commercialisation have set the tone and direction for the nation to enhance the quality
of life by emphasizing technology commercialization activities, connecting entrepreneurs, innovators, investors, social media,
society, government, university and industry in strategic collaborations (Spigel, 2017; Zahra et al., 2018). The connection and
strategic collaboration between these entities is a vital driver of innovation, and productivity (De Wit-de Vries et al., 2019;
Fini et al., 2020).

5. Conclusions

In the era of globalisation, the fact that needs to be recognised is that universities in Malaysia need to have their own
mould to become a learning institution that is relevant to the National Education Philosophy as its starting point and guiding
principle. While there have been drastic changes to the key role of universities, the Malaysian HEIs system must clearly have
the right structure, efficient governance and no exception in relevant leadership if they are to be relevant and actively
participate in reshaping life through education. The governance system of HEIs plays an important role in the education of
world citizens who receive and contribute to the creation and dissemination of relevant knowledge for the community, society
at large. This and many more are the way forward for the future. This study will contribute to commercialisation literature by
adding new knowledge concerning the link between innovation, commercialisation and support systems. Practically, the
findings of this study will be valuable to HEIs because the success of technopreneurs will, in turn, encourage and promote
innovation by means of Research, Development & Commercialization (R&D&C) among Malaysian HEIs. Global Innovation
Index (2009-2010) reported that Malaysia is ranked 28th, way below other Asian countries such as Singapore, China, Korea,
and Taiwan. These situations have prompted the Malaysian government to shift policies to promote new forms of research
communication and collaboration between universities and industries (Lu & Etzkowitz, 2008). Thus, this study impacts on
the ecosystem of innovation and commercialisation in providing the importance of support system to strengthen the role of
university-industry-community relation to drive the economy towards a high-income nation to meet the needs of today and
more critically, that of tomorrow.

6. Limitations and Future Research

These findings are subject to the usual limitations arising from the field survey method. The interview used in this study
has not been triangulated with data from other sources. From the perspectives of Research University (RU), the findings give
rise to several questions for practice. Within a bundle of Commercialisation Support System (CSS), which particular CSS are
more critical to achieving sustained commercialisation? Can a separate bundle of CSS be managed to improve innovation
outcomes? Thus, further research could address such questions, and provide greater insights into the issue of managing CSS
in the university especially in terms of innovation, technology transfer and commercialisation. Moreover, future research
could also seek to refine the instrument constructed in this study and further test its validity.

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CM021

THE INFLUENCE OF SHARI'AH SUPERVISORY BOARD (SSB)
REPUTATION AND SSB MEETING TOWARD SHARI’AH
COMPLIANCE DISCLOSURE

Iwan Fakhruddin

Faculty of Economic and Business, Universitas Muhammaadiyah Purwokerto, Indonesia
E-mail: [email protected]

Mohd Abdullah Jusoh

Universiti Pertahanan Nasional Malaysia

Norlia Mat Norwani

Faculty of Management and Economics, Universiti Pendidikan Sultan Idris, Malaysia

ABSTRACT

The intention of this paper is to analyze the role of the interfaces of the Shari'ah Supervisory Board (SSB) on
Shari'ah Disclosures. The population in this study are financial institutions that administer transactions in Indonesian Islamic
banking based on the principles of Shari'ah. An Islamic financial institution registered with the Central Bank of Indonesia is a
sample of this project. Data collected from the Central Bank of Indonesia website and from websites that are part of the
sample of the organization. The final sample of 65 Islamic banks' annual reports in 2016-2020. Utilizing multiple regression
analysis showed the impact of regression analysis SSB Reputation and SSB Meeting on Shari’ah Disclosures. The result
showed that SSB reputation positively influences Shari’ah Disclosures. However, SSB meetings showed a negative effect on
Shari’ah Disclosures. The finding provides useful insight in formulating Shari’ah compliance disclosure particularly among
Islamic Financial Institution in Indonesia

Keywords: Shari'ah, Supervisory Board, Disclosures, Islamic Bank

1. INTRODUCTION

Islamic Financial Institutions are financial institutions that are in activity its operations use Islamic principles and
rules in accordance with the Qur'an and the Sunnah of the Prophet Muhammad Shalallahu 'Alaihi Wassalam
(Fakhruddin et al., 2021). They have principles and practices that are different from conventional banks
(Fakhruddin & Jusoh 2018). The application of the principles and rules of Shari'ah is part of the prohibition of
usury (interest) (Rahman & Bukair, 2013; Muhamed, Fahmi & Ahmad, 2015; Fakhruddin, Jusoh & Mat Norwani,
2020).

In Indonesia, regulations regarding the importance of compliance with Shari’ah principles in Shari’ah banking have
been regulated in OJK 2015 Article 2. This regulation explains that the activities of Shari’ah banks in issuing
products and carrying out activities must apply Shari’ah principles, prudential principles, and customer protection
principles (OJK, 2015). The practice of Shari’ah compliance in Indonesia is still a legitimate problem because
many Islamic banks in Indonesia are still under the authority of conventional banks so the system used still uses a
dual banking system. In the dual banking system, conventional banks and Islamic banks are both recognized. Based
on Law no. 21 the year 2008 SSB has a role in the supervisory process of compliance-related Shari’ah principles
in Shari’ah banking. SSB also has the role of giving advice and advice to the board of directors and overseeing the

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bank's activities following the principles of Shari’ah. At the national level, there is a National Shari’ah Council
(Dewan Syariah Nasional/ DSN) established by the Indonesian Ulama Council (Majelis Ulama Indonesia/ MUI)
which is in charge and has the authority to establish a fatwa on products and services in the business of a bank
conducting business based on Shari’ah principles

Implementation of good corporate governance will affect the success and improvement of firm value (Mollah &
Zaman, 2015), and (Hashim, Mahadi, & Amran, 2015). Disclosure of Shari’ah compliance is part of the governance
of Islamic financial institutions. Islamic finance standards regulatory bodies such as AAOIFI managed to set
standards for corporate governance and Shari’ah governance in IFIs over the past decade (Fakhruddin et al., 2021).
Fakhruddin, Setyadi, and Pramono (2018) in their research report show that users of Shari’ah accounting reports
still believe in Shari’ah accounting information

2. LITERATURE REVIEW

The existence of an active role of the SSB (SSB) is a must and exists. SSB is one of the things that distinguishes
conventional banks from Islamic banks or other Islamic financial institutions. Islamic financial institutions in
Indonesia is still relatively low in disclosure of Shari’ah compliance compared to other countries. The role and
responsibility of Islamic financial institutions are to provide certainty for all activities carried out by financial
institutions in Shari’ah according to Shari’ah principles. This study’s purpose is to analyze the influence of SSB
Reputation and SSB Meetings on Shari’ah disclosure. Information about Shari’ah disclosure and SSB is very
important to give confidence to the public about SSB. SSB will guarantee the application of Shari’ah principles in
Shari’ah financial institutions. The reputation of SSB is a significant factor in the disclosure practice. The literature
on compliance with AAOIFI explores the compliance level (Ullah, 2013; Vinnicombe, 2010; Ahmed & Khatun,
2013); El-halaby & Hussainey, 2016). Resource dependence theory is related to the role of the company board as
a resource for the company (Johnson et al., 1996). Directors, including SSB are company assets that help maintain
the continuity of the company's business (Hillman et al., 2009). Directors have the responsibility of being involved
in supervisory duties and providing advice in decision-making (Hillman & Dalziel, 2003). Resource dependency
theory focuses on the role of the board of directors in providing access to resources.

3. RESEARCH METHODOLOGY

The population in this study are financial institutions that operate according to Shari’ah principles in Indonesian
Islamic banking. The sample of this study is an Islamic Financial Institution registered at the central bank of
Indonesia. Data was obtained through the website of the central bank of Indonesia (www.bi.co.id) and websites
that are part of the company example. The sampling technique used is saturated sampling. The samples are 13
Islamic financial institutions in Indonesia. A final sample including 65 annual reports of Islamic banks in 2016-
2020. The 2010-2018 fiscal year was chosen for this research because most banks have uploaded their annual report
on their website. Data is also quite new to ensure access through the company's internet. The data obtained gives a
rational picture of the practice of disclosure of Shari’ah compliance.

In this study using the dependent variable is Shari’ah Disclosure. This is done because information about Shari’ah
is very important to give confidence to the public about shari’ah in Islamic Financial Institutions. SSB is a party
that will guarantee the application of Shari’ah principles in Shari’ah financial institutions. This study uses
independent variables regarding the existence of SSB using SSB meetings and SSB reputation proxies. SSB
Meetings are held by the SSB to coordinate and discuss matters related to Shari’ah banking activities so that they
remain in accordance with Shari’ah principles (Bank Indonesia Regulation, 2009). The variable number of
supervisory board meetings refers to the research of Shabhrina et al. (2022). Rahman and Bukair (2013) explain

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that Islamic banks have SSB with good reputations can effectively monitor and control the Islamic bank activities
related to Shari’ah rules and principles disclosures

This study uses multiple regression analysis to investigate the influence between the SSB Meetings and SSB
Reputation on the Shari’ah Disclosures level. Shari’ah Disclosures level with AAOIFI Governance Standards No
1 and No 5 related to Shari’ah Disclosures. The equation of this regression is as follows:

SHARI’AH_DISC = α + β1SSB_REPit + β2SSB_MEETINGit + eit

Where:

α = The Constant

SHARI’AH_DISC = Shari’ah Disclosure Level with AAOIFI Governance Standards No 1 and No 5

SSB_REP = SSB as measured by the Number of SSB with Reputation

SSB_MEETING = SSB as measured by Meetings Number of years of SSB

e = Error of Regression

4. FINDINGS

Table 1 Coefficientsa

Unstandardized Standardized
Coefficients
Coefficients
Beta
Model B Std. Error t Sig.
0.276 8.010 0.000
1 (Constant) 13.889 1.734 2.320 0.024
-0.204
SSB_REPUTATIO 1.902 0.820

N

SSB_MEETING -0.123 0.072 -1.713 0.092

a. Dependent Variable: DISC_SHARI’AH_COMPL

The reputation of the SSB variable has a significant positive effect on the disclosure of Shari’ah compliance at the
0.024 level. The behavior of Islamic financial institutions that appoint SSBs based on popularity makes SSB carry
out maximum supervision. In Indonesia, information like this is vital in helping the National Supervisory Board
(DSN) recruit graduates to comprehend Islamic economics and finance. The optimization of the role of SSB in
supervision will be realized and will improve with comprehensive information. SSB is better to have the experience,
integrity, and credibility of financial professionals such as bankers, lawyers, and accountants who are related to the
rules of professional bodies that enforce certain professional ethics (Onagun, 2013). This study's findings support
El-Halaby and Hussainey (2016), who found that SSB reputation positively influences the level of Shari’ah
compliance disclosure. They found evidence that companies with more reputable SSB members will disclose more
Shari’ah compliance information in their annual reports and on their websites. Almutairian and Quttainah (2017)
state that SSB who have expertise in Shari’ah law and Shari’ah finance will have the ability to make better policies
and decisions to improve the bank's financial performance. The research results by Nomran et al. (2018) found that
members' reputation positively affects the performance of Islamic financial institutions. Scholars with financial
understanding and expertise are more influential in their performance as SSB members in Islamic financial
organizations than those who do not (Rahman and Bukair, 2013). Furthermore, most of IB's SSB members are

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Islamic scholars, with only a handful having accountancy, financial, macroeconomic, or financial skills. The results
of this study support the Resource Dependence Theory. Resource Dependence Theory is related to the role of the
company board as a resource for the company (Johnson et al., 1996). Directors, including SSB, are company assets
that help maintain the continuity of the company's business (Hillman et al., 2009). Directors have the responsibility
of being involved in supervisory duties and providing advice in decision-making (Hillman & Dalziel, 2003).
Resource Dependency Theory focuses on the role of the Board of Directors in providing access to resources.
according to company needs (Awotundun et al., 2011).
The meetings of the SSB variable have a significant negative effect on the disclosure of Shari’ah compliance at the
0.092 level. SSB members who actively conduct meetings, even though there are only a few bank SSB members,
must be able to make a good contribution to Islamic banks. More meetings held will open up opportunities for SSB
members to discuss information outside of their main duties, namely discussing disclosure of Shari’ah compliance
on the annual report. However, the research results describe a different situation. The more SSB members hold
meetings, the less disclosure of information related to Shari’ah compliance. SSB members have not been able to
provide oversight and advice to management regarding the disclosure implementation of Shari’ah principles when
holding internal discussion meetings. Consistent with the results of research on the characteristics of SSB,
Fakhruddin & Jusoh (2018) state that the number of SSB meetings has a negative effect although not significant to
Shari’ah compliance disclosure as measured by information disclosure related. SSB. SSB with more limited
Knowledge about Islamic accounting and finance has a negative impact on the value of Islamic banks (Bakar, 2016)
The results of this study are not in line with stewardship theory which assumes a relationship exists between
institutional success and owner satisfaction. Steward, in this case, SSB has not protected and maximized
organizational wealth with company performance related to disclosure of Shari’ah compliance

5. CONCLUSION

Based on stewardship theory, Stewards, in this case, SSB will protect and maximize organizational wealth with
company performance related to Shari’ah compliance disclosure. The company will have a high level of business
continuity if the company can be accepted by the Public. This study has aimed to gauge the influence of the SSB
Reputation and SSB Meetings on Shari’ah Disclosures. This paper finds that SSB Reputation and SSB Meetings
have a significant positive effect on the disclosure of Shari’ah. These results indicate that bank reporting that
formally implements an AAOIFI standard significantly improves the disclosure level for Shari’ah disclosure. The
finding provides useful insight into formulating shari’ah compliance disclosure, particularly among Islamic
Financial Institutions in Indonesia.

REFERENCES

Ahmed, N. & Khatun, M. (2013). “The compliance with Shari’ah governance system of AAOIFI: A study on
Islamic banks Bangladesh”. Journal of Islamic Economics, Banking, and Finance, 9 (3), 178-191

Almutairi, A. R., & Quttainah, M. A. (2017). Corporate Governance: Evidence from Islamic Banks.
Social Responsibility Journal, 13(3), 601–624

Awotundun, D. A., Kehinde, J. S., & Somoye, R. O. C. (2011). Corporate governance and Stakeholders interest: a
case of Nigerian banks. International Journal of Business and Management, 6(10), 102–112

Bakar, A.D. (2016). Shari’ah minds in Islamic finance: An inside story of a Shari’ah scholar. Kuala
Lumpur, Malaysia: Amanie Media, xi + 322

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Universiti Pendidikan Sultan Idris

El-Halaby, Sherif. & Hussainey, Khaled, (2016), “Determinants of compliance with AAOIFI standards by Islamic
banks”, International Journal of Islamic and Middle Eastern Finance and Management, Vol. 9 Iss 1 pp. –

Fakhruddin, I., Jusoh, M. A., & Mat Norwani, N. (2020). The Shari’ah Compliance with AAOIFI
Governance Standards Related SSB Information: A Study on Indonesia Islamic Banks. Journal of Islamic,
Social, Economics and Development (JISED), 5(33), 175 – 181

Fakhruddin, I. Setyadi, E.J, & Pramono, H. (2018). Implementation Of Shari’ah Accounting Standard: Reviewed
From The Perception Of The Accountants Candidate. Advanced Science Letters, 1, 3398–3402.

Fakhruddin, I., & Jusoh, Mohd. Abdullah. (2018). Influence Of SSB Characteristics On The Shari’ah Compliance.
Advances In Social Science, Education, And Humanities, 231, 355-357

Hashim, F., Mahadi, N.D. & Amran, A. (2015). Corporate Governance and Sustainability
Practices In Islamic Financial Institutions: The Role Of Country Of Origin. Procidia Production Economics
and Finance, 31, 36-43

Hillman, A. J., & Dalziel, T. (2003). Boards of directors and firm performance: Integrating agency and resource
dependence perspectives. Academy of Management Review, 28(3),383-396

Hillman, A. J., et al. (2009). Resource Dependence Theory: A Review. Journal of Management,p. 1404-1427

Johnson, J.L., Daily, C.M. & Ellstrand,A.E. (1996). Boards Of Directors: Areview Of Research Agenda”. Journal
Of Management, 22 (3), 409-438

Muhammed, Farizal Nor. Fahmi, Fadzlina Mohd., & Ahmad, Asyaari Elmiza. (2015). Procedia
Economics and Finance. 31, 418 – 424

Nomran, M. N., Haron, R., & Hassan, R. (2018). SSB Characteristics Effects On Islamic Banks’ Performance:
Evidence from Malaysia. International Journal of Bank Marketing, 36(2).

Onagun, A.I & Mikail A. (2013). “Shari’ah Governance System: A Need For Professional Approach”.
Proceeding of Shari’ah Economics conference, February 29, 2013, Hanover, Germany, 71-80

Rahman, Azhar Abdul & Abdullah Awadh Bukair. (2013). The Influence Of The Shari’ah
Supervision Board On Corporate Social Responsibility Disclosure By Islamic Banks Of Gulf
C0-Operation Council Countries. Asian Journal Of Business And Accounting 6(2)

Shabrina, A.N., Pratama, B.C., Fakhruddin, I. & Wibowo, H. (2022)., Pengaruh Intellectual Capital, Islamic Social
Reporting, Kepemilikan Publik, Ukuran Dewan Pengawas Syariah Dan Jumlah Rapat Dewan Pengawas
Syariah Terhadap Social Performance., Ratio: Reviu Akuntansi Kontemporer Indonesia Juli 2021, Volume
2, No 2. (In Indonesia)

Ullah, M. (2013). Accounting and Reporting Practices of Islamic Banks in Bangladesh. PhD. University of
Chittagong, Bangladesh

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Vinnicombe, T. (2010). AAOIFI reporting standards: measuring compliance. Advances in Accounting.
Incorporating Advances in International Accounting, 26(1), 55-65

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CM022

UJIAN KOINTEGRASI JOHANSEN JUSELIUS ANTARA FAKTOR
MAKROEKONOMI TERPILIH DAN HARGA EMAS

Debbie Liza Anak Pencil
Pelajar Sarjana, Fakulti Pengurusan dan Ekonomi, Universiti Pendidikan Sultan

Idris(UPSI)
Email: [email protected]

Norimah Rambeli
Prof. Madya, Fakulti Pengurusan dan Ekonomi, Universiti Pendidikan Sultan Idris(UPSI)

Email: [email protected]

Norhanishah Mohamad Yunus
Pensyarah Kanan, Pusat Pengajian Pendidikan Jarak Jauh, Universiti Sains Malaysia

(USM)
Email: [email protected]

Noor Zahirah Mohd Sidek
Prof. Madya, Fakulti Pengurusan Perniagaan, UiTM

Email: [email protected]

ABSTRAK
Objektif utama kajian yang ini adalah untuk mengkaji hubungan jangka panjang antara pembolehubah
makroekonomi terpilih termasuklah harga minyak mentah, eksport, kadar pertukaran asing, keluaran dalam
negara kasar dan harga emas di Malaysia. Dengan menggunakan data siri masa berfrekuansi bulanan, kajian
yang menggunakan data aggregate ini akan menggunakan pendekatan dinamik. Secara terperinci, kajian ini
juga akan menggunapakai ujian kointegrasi Johansen Juselius bagi menganalisis hubungan jangka panjang
antara pembolehubah dalam pemerhatian, di samping Vector Autoregression (VAR) dan ujian punca unit
Augmented Dickey Fuller (ADF). Hasil dari dapatan kajian menunjukkan bahawa kesemua pembeolehubah
siri masa yang digunakan di dalam kajian ini adalah bersifat I(1). Dengan erti kata lain ianya pegun pada aras
perbezaan pertama. Selain itu, berdasarkan kepada nilai Akaike (AIC) pada ujian Vector Autoregression
(VAR) menunjukkan bahawa lat yang optimum adalah pada lat 8. Berdasarkan kepada ujian kointegarsi pula
membuktikan bahawa wujud sekurang-kurangnya satu vektor kointegrasi antara pembolehubah
makroekonomi terpiliah dan harga emas. Ini menunjukkan wujud keseimbangan jangka panjang antara
pemboleh ubah-pemboleh ubah tersebut. Kewujudan kointegrasi ini bermaksud hubungan yang wujud antara
perbelanjaan, makroekonomi terpilih dan harga emas adalah tidak ‘spurious’ atau tidak palsu dan
keseimbangan wujud dalam jangka panjang.

KATA KUNCI
Harga emas, faktor makroekonomi terpilih, ujian kointegrasi Johansen Juselius

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1. PENGENALAN

Emas merupakan salah satu sumber pendapatan negara yang boleh mempengaruhi
pertumbuhan ekonomi negara secara langsung atau tidak langsung dalam tempoh jangka
panjang dan pendek (Levin & Wright, 2006; and Ibrahim, Kamaruddin & Hassan, 2014,
among others studies). Harga emas juga merupakan salah satu petunjuk penting yang
digunakan untuk membantu mengekalkan kestabilan ekonomi sesebuah negara. Dari sudut
mikroekonomi, menurut Wang (2013), emas adalah salah satu alat lindung nilai. Kecairan
nilai emas di masa depan adalah lebih cekap daripada menyimpan stok atau wang kertas.
Dari sudut makroekonomi, pasaran emas menjadi fokus utama para pelabur ketika krisis
ekonomi berlaku. Kestabilan ekonomi dalam jangka panjang mahupun dalam jangka
pendek penting bagi sesebuah negara kerana ianya dapat menarik minat pelabur asing
untuk melabur ke dalam negara tersebut. Justeru, suatu kajian perlu di jalankan bagi
meneliti pengaruh jangka panjang pembolehubah makroekonomi terpilih dan harga emas
dalam jangka panjang. Tidak dinafikan harga emas boleh diklasifikasikan sebagai data siri
masa berfrekuansi tinggi. Maka peningkatan dan penurunan pasaran emas di Malaysia
mungkin dipengaruhi oleh beberapa faktor makroekonomi tertentu. Justeru, dalam kajian
yang dijalankan ini, pengkaji memilih faktor makroekonomi seperti harga minyak mentah,
kadar pertukaran wang, eksport dan keluaran dalam negara kasar benar bagi mengkaji
hubungan faktor makroekonomi terhadap harga emas di Malaysia. Kajian yang di jalankan
ini adalah berdasarkan kepada kajian yang di jalankan oleh Ibrahim, Kamaruddin, &
Hassan (2014). Objektif utama kajian adalah untuk menganalisis hubungan jangka panjang
antara empat faktor makroeonomi terpilih, iaitu harga minyak mentah, kadar pertukaran
wang, eksport dan keluaran dalam negara kasar benar dengan harga emas di Malaysia.
Justeru hipotesis kajian adalah seperti berikut;

H0: Tidak terdapat hubungan jangka panjang antara faktor makroekonomi terpilih dan
harga emas.

H1: Terdapat hubungan jangka panjang antara faktor makroekonomi terpilih dan harga
emas.

Bagi mencapai matlamat utama kajian, pendekatan ujian siri masa yang di gunakan oleh
Rambeli, Podivinsky& Jalil (2019) akan di gunakan.

2. KAJIAN LEPAS

Pada bahagian ini akan di bincangkan berkaitan dengan kajian-kajian harga emas yang
dilaksanakan oleh pengkaji terdahulu.

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Menurut Warda (2014), Ibrahim (2014), Sindhu (2013), Amalendu (2013), Wang (2013),
Simakova (2011), Le, Chang, (2011), Lin, Yang, Chen (2010), Zhang, Wei (2009) dan
Kaspar (2008) menjelaskan bahawa wujudnya hubungan jangka panjang yang positif
antara harga emas dan harga minyak mentah. Menurut Le & Chang (2011), kajian tentang
harga emas dan harga minyak mentah menunjukkan wujudnya hubungan positif antara
emas dan harga minyak mentah. Keadaan ini membuktikan bahawa harga minyak mentah
merupakan salah satu faktor makroekonomi penting untuk meramal peningkatan dan
penurunan harga emas pada massa hadapan.

Ling (2011) menjalankan kajian tentang harga emas dan kadar pertukaran nilai mata wang
negara Asia (Ringgit Malaysia, Singapore Dolar, dan Thai Bath) terhadap US dolar.
Kaedah yang digunakan dalam kajian yang dijalankan adalah Ujian Kepegunan, Ujian
Johansen Juselius, Ujian Kausaiti Granger dan Model Vektor Pembetulan Ralat (VECM).
Hasil kajian mendapati bahawa terdapat hubungan jangka panjang dan hubungan positif
antara harga emas dan nilai mata wang Ringgit Malaysia, manakala wujudnya hubungan
negatif antara harga emas dengan Singapore Dolar dan Thai Bath. Wujudnya korelasi
negatif antara kadar pertukwaran wang terhadap emas, manakala korelasi positif antara
harga minyak mentah dan harga emas di Malaysia (Ibrahim, Kamaruddin and Hassan,
2014). Satu kajian yang dijalankan oleh Fei & Adibe (2010) di Malaysia menunjukkan
terdapat hubungan negatif antara harga emas dan kadar pertukaran wang kerana nilai emas
tetap kekal stabil walaupun kadar pertukaran wang mengalami susut nilai. Menurut Pushpa
& Muruganandam (2014), penurunan dalam kadar keluaran dalam negara kasar benar
(GDP) menyebabkan meningkatnya harga emas sehinggakan para pelabur lebih berminat
dalam pasaran emas.

3. SPESIFIKASI MODEL

Model spesifikasi dalam kajian ini menggunakan pendekatan yang dipelopori oleh
Ibrahim,Kamaruddin, & Hassan (2014).

ln HEit = α0+ 1 ln HMMit+ 2 ln KPWit+ α3 ln Xit+ ln KDNKBit + εit

di mana, HEit = harga emas untuk ‘i’ dan masa ‘t’
HMMit
= harga minyak mentah untuk ‘i’ dan masa ‘t’

KPWit = kadar pertukaran wang untuk ‘i’ dan masa ‘t’

Xit = eksport untuk ‘i’ dan masa ‘t’
KDNKBit = keluaran dalam negara kasar benar untuk ‘i’ dan masa ‘t’

αiitt = istilah ralat untuk 'i' dan masa 't'
= pekali bagi pemboleh ubah penentu.

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Di dalam kajian ini, pendekatan kajian yang digunakan adalah dipelopori oleh Rambeli,
Podivinsky& Jalil (2019). Dimana, mengikut pendekatan ini, analisis yang terlibat adalah
ujian punca unit Augmented Dickey Fuller (ADF), analisis vektor autoregresi (VAR) dan
ujian kointegrasi Johansen Juselius akan di gunakan.

4. HASIL KAJIAN

Pada bahagian ini akan di bincangkan keputusan analisis termasuklah adalah ujian punca unit

Augmented Dickey Fuller (ADF), analisis vektor autoregresi (VAR) dan ujian kointegrasi Johansen Juselius.

Ujian Punca Unit ADF

Jadual 1:
Hasil kajian Ujian Kepegunan Hubungan antara Faktor Makroekonomi Terpilih dan

Harga Emas di Malaysia

MALAYSIA

Pada aras Pada perbezaan pertama

Data siri masa Trend dan Trend dan
pintasan pintasan
Pintasan Pintasan

Harga emas -1.362224 -0.950354 -11.70500 -11.77810
(Lag 9) (Lag 9) (Lag 9) (Lag 9)

Harga minyak -2.334740 -2.279530 -11.70708 -11.71021
mentah (Lag 9) (Lag 9) (Lag 9) (Lag 9)

Kadar pertukaran -1.368281 -1.386806 -9.952811 -10.00420
asing (Lag 9) (Lag 9) (Lag 9) (Lag 9)

Eksport -2.754500 -2.747363 -6.272497 -6.262700
(Lag 13) (Lag 13) (Lag 9) (Lag 9)

Keluran dalam -3.358056 -3.444153 -6.920365 -6.912679
negara kasar benar (Lag 3) (Lag 13) (Lag 9) (Lag 9)

Nota: Angka-angka dalam kurungan adalah susunan lag yang dipilih berdasarkan AIC.

Jadual 1 menunjukkan hasil ujian punca unit ADF, kedua-duanya pada tahap dan pada
perbezaan pertama. Ujian punca unit ini mengambil kira model gerakan rawak (random
walk) dengan pintasan dan trend dan pintasan. Jadual 1 juga menunjukkan nilai statistik
dari ujian-t untuk semua siri data yang digunakan. Hasil kajian menjukkan bahawa, semua
data siri masa yang digunakan adalah tidak pegun. Dengan erti kata lain, ini menunjukkan
bahawa siri ini tidak pegun pada aras. Justerus, kesemua data siri masa yang digunakan

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adalah bukan data I(0). Oleh itu, ujian diteruskan pada perbezaan pertama. Apabila ujian
ADF dijalankan untuk setiap pembolehubah pada perbezaan pertama, hipotesis nol tidak
pegun mudah ditolak pada tahap 99% seperti yang ditunjukkan dalam Jadual 1.

Vektor Autoregrasi (Vector Autoregression-VAR)

Jadual 2:
Hasil Kajian Ujian Vektor Autoregresi (VAR) Hubungan antara Faktor

Makroekonomi Terpilih dan Harga Emas di Malaysia.

VAR AIC
MALAYSIA

2 -0.788446

3 -0.727383

4 -0.767748

5 -0.911905

6 -0.840127

7 -1.010976

8 -1.020940

9 -0.937620

10 -0.951998

11 -0.831830

12 -0.911645

Nota: Angka dalam kurungan adalah urutan
ketinggian yang dipilih berdasarkan AIC.

Berdasarkan Jadual 2, keputusan setiap lag bermula Lag 2 hingga Lag 12 dibentangkan
dengan menggunakan nilai Akaike Information Criteria (AIC). Nilai AIC yang optimum
untuk Malaysia adalah pada lag 8 dengan nilai AIC -1.020940.

Analisis Kointegrasi Johansen Juselius

Jadual 3:
Hasil Kajian Ujian Johansen Juselius Hubungan antara Faktor Makroekonomi

Terpilih dan Harga Emas di Malaysia.

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Siri data dari MALAYSIA
2000M01
sehingga Sistem Ko-integrasi
2018M12 F( harga minyak mentah, kadar pertukaran wang, eksport, keluaran dalam negara kasar

Hipotesis benar )

H0 H1 λ Trace 5% nilai 1% nilai λ Max 5% nilai 1% nilai
kriktikal kritikal kritikal kritikal

r=0 r=0 89.77226** 68.52 76.07 39.02202** 33.46 38.77

r≤1 r>1 50.75024* 47.21 54.46 33.24552* 27.07 32.24

r≤2 r>2 17.50472 29.68 35.65 13.02636 20.97 25.52

Perhatikan bahawa, notasi 'r' menandakan bilangan vektor ko-integrasi. Nilai bertanda (*) menunjukkan ketara secara
statistik pada 95% dan (**) pada tahap 99%. Nilai kritikal untuk ujian Johansen Juselius diperoleh dari (Osterwald-
Lenum, 1992)

Keputusan ujian kointegrasi ditunjukkan pada Jadual 3. Ujian kointegrasi yang digunakan
mengambil kira andaian bahawa persamaan kointegasi hanya mengandungi pintasan
sahaja. Oleh yang demikian, statistik ujian yang digunakan diperoleh daripada Osterwald-
Lenum (1992). Nilai lat optimum untuk ujian kointegrasi ini ditentukan dengan
menggunakan kriteria Akaike (AIC) seperti yang telah digunakan dalam ujian unit root.
Kedua-dua nilai statistik ujian dan adalah signifikan pada aras keertian 5% dan hipotesis
nol yang mengatakan tiada kointegrasi berjaya ditolak. Keputusan ini juga membuktikan
wujud sekurangkurangnya satu vektor kointegrasi antara pembolehubah makroekonomi
terpilih dan harga emas di Malaysia. Ini menunjukkan wujud keseimbangan jangka
panjang antara pemboleh ubah-pemboleh ubah tersebut. Kewujudan kointegrasi ini
bermaksud hubungan yang wujud antara pembolehubah makroekonomi terpilih dan harga
emas adalah tidak ‘spurious’ dan keseimbangan wujud dalam jangka panjang.

5.0 IMPLIKASI DAN CADANGAN

Peningkatan dan penurunan data pemboleh ubah yang dikaji memberi impak kepada
kestabilan harga emas. Justeru wujud hubungan jangka panjang antara pembolehubah
makroekonomi terpilih dan harga emas di Malaysia. Kajian yang dijalankan ini boleh
membolehkan pihak kerajaan lebih peka dengan keadaan ekonomi dan faktor-faktor
penting yang boleh memberi kesan kepada pendapatan dan pertumbuhan ekonomi negara.
Pihak kerajaan sepatutnya memainkan peranan dengan mencari langkah-langkah baru yang
berkesan untuk mengekalkan kestabilan harga emas bagi meningkatkan pertumbuhan
ekonomi sesebuah negara tersebut. Malah, pihak kerajaan perlu mengawal kenaikan dan
penurunan pembolehubah makroekonomi tersebut yang boleh mempengaruhi harga emas
dengan menggubal dasar atau polisi baru yang lain berkaitan dengan faktor makroekonomi

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agar harga emas kekal stabil. Cadangan bagi pengkaji ingin menjalankan kajian yang lebih
mendalam tentang hubungan pembolehubah makroekonomi dengan harga emas di masa
hadapan, adalah disarankan untuk menggunakan data siri masa yang panjang bagi
mengenal pasti hubungan jangka panjang dan jangka pendek.

RUJUKAN
Allese, K. (2008). Understanding the development and influences of the price of

gold. Bachelor of Arts in the School of Business International University Audentes,
Estonia, US.

Bhunia, A. (2013). Cointegration and causal relationship among crude price, domestic gold
price and financial variables: an evidence of BSE and NSE. Journal of contemporary
issues in business research, 2(1), 1-10.

Fei, F., & Adibe, K. (2010). Theories of gold price movements: Common wisdom or
myths?. Undergraduate Economic Review, 6(1), 5.

Ibrahim, S. N., Kamaruddin, N. I., & Hassan, R. (2014). The Determinants of Gold Prices
in Malaysia. Journal of Advanced Management Science Vol. 2, No.1, 38-41.

Le, T. H., & Chang, Y. (2011). Dynamic relationships between the price of oil, gold and
financial variables in Japan: a bounds testing approach.

Levin, E. J., Montagnoli, A., & Wright, R. E. (2006). Short-run and long-run determinants
of the price of gold.

Lin, C. C., Fang, C. R., & Cheng, H. P. (2010). Relationships between oil price shocks and
stock market: an empirical analysis from Greater China. China Economic Journal, 3(3),
241-254.

Ling, A. C. (2011). The Relationship between Gold Price and Exchange Rate Of Asean
Currencies (Ringgit Malaysia, Singapore Dollar, Thai Baht) Against U.S Dollar. Faculty of
Economics and Business Universiti Malaysia Sarawak.

Nadeem, W., Zakaria, M., & Kayani, F. (2014). Impact of macroeconomic factors upon
gold prices in Pakistan. Pakistan Journal of Social Sciences (PJSS) Vol, 34, 383-395.

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Pushpa, B., & Muruganandam, S. (2014). Estimation of Relation between Financial
Variables and Gold Price Using Fuzzy Multiple Linear Regression. Journal of Business
and Management, 17-23.

Rambeli, N., Podivinsky, J. M., & Jalil, N. A. (2019). The Re-Examination Of The
Dynamic Relationship Between Money, Output And Economic Growth In
Malaysia. International Journal Of Innovation, Creativity And Change, 5(2), 1812-
1834.

Rambeli, N., & Podivinsky, J. M. (2013). A Study Of Exogeneity Tests On Export-Led
Growth Hypothesis The Empirical Evidences On Post-Crisis Exchange Rate
Regime In Malaysia. International Business Education Journal. UPSI.

Šimáková, J. (2011). Analysis of the relationship between oil and gold prices. Journal of
finance, 51(1), 651-662.

Sindhu, D. (2013). A study on impact of select factors on the price of Gold. Journal of
Business and Management, 8(4), 84-93.

Wang, Y. (2013). An empirical study in the relationship between crude oil and gold futures.
Wang, Y. S., & Chueh, Y. L. (2013). Dynamic transmission effects between the interest

rate, the US dollar, and gold and crude oil prices. Economic Modelling, 30, 792-798.
Zhang, Y. J., & Wei, Y. M. (2010). The crude oil market and the gold market: Evidence for

cointegration, causality and price discovery. Resources Policy, 35(3), 168-177.

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CM023

THE EFFECT OF SELECTED MACROECONOMIC VARIABLES TOWARD ECONOMIC
GROWTH: AN APPLICATION OF ORDINARY LEAST SQUARE METHOD

Ainur Attira Azmi
Master Student, Faculty of Management and Economics, Universiti Pendidikan Sultan Idris (UPSI)

Email: [email protected]

Norimah Rambeli
Associate Professor, Faculty of Management and Economics, Universiti Pendidikan Sultan Idris

(UPSI)
Email: [email protected]

Dayang Affizah Awang Marikan
Associate Professor, Faculty of Management and Business, University Malaysia Sarawak (UNIMAS)

Email: [email protected]

Emilda Hashim
Lecturer, Faculty of Management and Economics, Universiti Pendidikan Sultan Idris (UPSI)

Email: [email protected]

Nooraisah Katmon
Lecturer, Faculty of Management and Economics, Universiti Pendidikan Sultan Idris (UPSI)

Email: [email protected]

ABSTRACT

The Gross Domestic Product growth has always been regarded as current issue that attract attention by
many researchers to measure the growth. Thus, the focal point of this study to investigate the
determinants of economic growth in Malaysia by using yearly data. Employing the annually time
series data for the period proposed on the selected indicators such the foreign direct investment,
export, rate of employment growth, real effective exchange rate, the methodology Ordinarily Least
Square adopted in this paper. This paper further utilizing the diagnostic tests namely autocorrelation,
multicollinearity and heteroscedasticity. The finding of this paper suggests that each variables effects
the Gross Domestic Product positively. In other words, if foreign direct investment increases it will led
the Gross Domestic Product to increase in the long term for the case of Malaysia. As implication, the
foreign direct investment is important explanatory variables in determinate the Gross Domestic
Product in the long run for the case of Malaysia, among others focus variables.

KEYWORDS
Gross Domestic Product, foreign direct investment, export, rate of employment growth, real effective
exchange rate.

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1. INTRODUCTION

The paradigm shift in the economy from static to dynamic has sparked considerable attention from
economists since the 90s until now. The idea is that economy is not static, thus the economic structure
can change (Galbraith, 1994). A change in the economy can affect the development of a country. For
this reason, economic growth and the factors leading to growth has been a constant area of study.

Economic growth of any country reflects its capacity to increase production of goods and
services. The simplest definition of economic growth can be stated as the increase in the Gross
Domestic Product (GDP) of that country. Thus, the Gross domestic product is a preferable indicator to
measure the growth of the country. According to previous literature, the economic growth is
influenced by many factors. Among other variables, the foreign direct investment, export, rate of
employment growth, real imports and real effective exchange rate.

For the case of Malaysia, (Chowdhury & Mavrotas, 2006) examined the causal relationship
between FDI and economic growth for three developing countries, namely Chile, Malaysia and
Thailand and found that in Malaysia, there is strong evidence of a bidirectional causality between the
two variables (Duasa, 2007) examined the causality between FDI and output growth in Malaysia, but
the study found no strong evidence of causal relationship between FDI and economic growth.
However, (Omer & Yao, 2011) have empirically analyzed Malaysia annual data (1970 to 2008.) and
again proved the bi-directional causality and long-run relationships between inward FDI and economic
growth.Past studies (Baro, 1996a; Alfaro, Chanda, Kalemli-Ozcan and Sayek, 2004; Cortes-Jimenez
and Pulina, 2006) use a lot of analysis based on cross-country data or include import as well as export
variables (Jung and Marshall, 1985; Chow, 1987; Thirlwall, 1994; Ahmad and Harnhirun, 1996;
Balaguer and Jorda, 2001; Awokuse, 2002; Sharma and Panagiotidis, 2005; Cortes-Jimenez and
Pulina, 2006) in explaining the relationship between economic growth and determinant factors. Some
of the cited factors are: consumption expenditure, government expenditure, investment and import-
export. Most literature however focus more on export factor as a determinant to output growth
(Chow,1987; Thirlwall, 1994; Ahmad and Harnhirun, 1996; Balaguer and Jorda, 2001).

The main objective of this study is to examine the long run relationship of selected
macroeconomic variables namely, foreign direct investment, export, rate of employment growth, real
import and real effective exchange rate) towards economic growth in Malaysia. In addition, this study
will also look into the conceivable effects of combined determinant factors towards economic growth.

Research Objectives
i) Developed the multiple regression model for GDP in Malaysia.
ii) Identify the most important factors in influencing GDP in Malaysia.
iii) Identify the least important factors in influencing GDP in Malaysia.
iv) Analyse trend of each time series data.

Research Questions
i) Is there multiple regression model for Gross Domestic Product (GDP) in Malaysia can be
developed?
ii) What are the most important factors in affecting Gross Domestic Product (GDP) in Malaysia?
iii) What are the least important factors in affecting Gross Domestic Product (GDP) in Malaysia?
v) What are the trend of each time series data.

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2. LITERITURE REVIEW

Despite the multitude of studies about the relationship between FDI, exports, rate of employment
growth, real import and real effective exchange rate, there are no common consensuses regarding this
issue between different studies, so working on this issue is still required. The absence of common
consensus can be due to the different time periods, countries and econometric method employed in
these studies.

Nath (2009) employed a fixed effect panel data approach to examine the effects of trade and
FDI on the growth of per capita real GDP in 13 transition economies of Central and Eastern Europe
and the Baltic region from 1991 to 2005. He found a significant positive effect of trade on growth, but
FDI has had no significant impact on growth in these transition economies. However, when
controlling the effects of domestic investment and trade on FDI, Nath expressed that it appears to be a
significant determinant of growth for the period after 1995.

Sayef & Mohamed (2016) examined the relationship between exports, imports and economic
growth in Turkey. As a result, the found the strong evidence of bidirectional causality from exports to
economic growth. Next, Evelina N.& Cyril A. analyzed the investigates the export-economic growth
relationship for Namibia. The study models the relationship through the augmented neoclassical
production function framework. The Johansen co-integration test, the vector-error correction model
(VECM) and the Granger causality tests were employed to test for the nature of the relationship The
Granger causality test indicates a unidirectional causation from export to economic growth. This
allows us to confirm the validity of the export-led growth hypothesis in the case of Namibia. The
findings also suggest that economic growth is dependent on export performance in a way.

More recent studies have been looking specifically into variables that are important in
affecting employment growth. Several authors have estimated employment elasticities (a measure of
the relationship between employment and economic growth) for a variety of nations. Norazlina et al.,
(2010) examines the meaningful relationship between employment and macroeconomic variables such
as domestic capital, gross domestic product and government expenditure in three major ASEAN
economies, namely Malaysia, Singapore and Philippines. They found that employment performance is
powerfully influenced by macroeconomic policies

Enrico & Marcello (2010) The purpose of this paper is to identify the main “models of
growth” characterizing the EU countries in the last two decades, with particular reference to the
employment-productivity relationship, and to reveal the key determinants of productivity. They found
that high employment growth is likely to lead to slower productivity growth.

Exchange rate is thought to influence economic growth through the effect of exchange rate
volatility on the profitability of international trade and investment. Among the few researchers, such as
according to Aghion et al., (2009), exchange rate (volatility) does significantly affect the economic
growth when taking into account the level of financial development. This finding is robust when
taking into consideration of various measurements of financial development and also its interactions.
Additionally, the volatility of exchange rate by itself did not play its significant role on the isolation.

Awokuse, T. O. (2008) in an article Trade openness and economic growth: is growth export-led or
import-led? This article re-examines the relationship between trade and economic growth in
Argentina, Colombia, and Peru with emphasis on both the role of exports and imports. Granger
causality tests and impulse response functions were used to examine whether growth in trade stimulate
economic growth (or vice versa). The results suggest that the singular focus of past studies on exports
as the engine of growth may be misleading. Although there is some empirical evidence supporting
export-led growth, the empirical support for import-led growth hypothesis is relatively stronger. In
some cases, there is also evidence for reverse causality from gross domestic product growth to exports
and imports.

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3. MODEL SPECIFICATION AND METHODOLOGY

This study adopted the model specification proposed by Rambeli, Marikan & Hashim (2016a). This
study used the annually data in Malaysia.

Model Specifications

The first function of the factors that affect GDP in Malaysia can be developed as follows:

GDPt = f (FDIt , Xt , PERt , REERt , RIt ) (1)

In equation (3), GDP represents economic growth data series and represented by Gross Domestic
Product (GDP). The FDI is foreign direct investment, X is exports, PER is rate of employment growth,
REER is real effective exchange rate and RI represents interest rate in the year.

GDPt = β0 FDIβ1 X β 2 PERβ 3REERβ 4 RI β 5ε µt (2)

Since equation (2) is a non-linear model, parameter values for (ί = 1,2,3,4) cannot be directly
estimated. Therefore, it is suggested that the production function be amended into log-linear model as
follows:

log GDPt = β0 + β1FDIt + β2 Xt + β3PERt + β4 REERt + β5 RIt + ε t (3)

Where, the gross domestic product denotes as GDP and FDI represented the foreign direct investment
variables. The notation of X and PER represented real exports and employment rate. Reer devoted real
effective exchange rate index, while RI is real import. In equation (3), all data series are in annually
frequency as denoted by t. All time series data are transforming into are in logarithm form. The
equation is estimated using the ordinary least square (OLS) method through the development of
multiple linear regression models. The testing procedure adopted the testing procedure proposed by
Rambeli et al. (2021). For hypothesis testing, this study employed the t-test and F-test. At the
diagnostic stages, this study utilized the heteroscedasticity, multicollinearity and autocorrelation tests.

4. EMPIRICAL RESULTS

In this chapter, the study will be discussing the entire research finding obtain from every test that had
been carried put on the independent variables toward the dependent variable. This study consists of
foreign direct investment (FDI), total of export (X), total of rate of employment growth (PER), total of
real effective exchange rate (REER) and real import (RI) as its independent variables. As for the
dependent variable, this study is focusing on a gross domestic product (GDPt). Each variable is being
tested to identify whether it has its significances toward the GDP in Malaysia.

GDPt =-78.141+ 0.634 FDIt + 6.698Xt +1.301PERt +0.135REERt +17.652RIt+ εt

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Where, the gross domestic product denotes as GDP and FDI represented the foreign direct investment
variables. The notation of X and PER, represented real exports and employment rate. Reer devoted
real effective exchange rate index, while RI is real import. All data are in time series and its denoted
by ‘t’ in the equation.

t-test

T-Test Hypotheses Statistical Critical Result
Variables Test Value Reject H0
H0 : β1 = 0 2.099 2.086 Accept H0
FDIt H1 : β1 ≠ 0 2.086 Accept H0
Xt H0 : β1 = 0 1.327 2.086 Reject H0
H1 : β1 ≠ 0 0.897 Reject H0
PERt H0 : β1 = 0 2.086
REERt H1 : β1 ≠ 0 2.411
H0 : β1 = 0 2.086
RIt H1 : β1 ≠ 0 5.277
H0 : β1 = 0
H1 : β1 ≠ 0

According to Table 4.3.2.1.1 above, the results of T-test shows either to accept 0 or reject 0.

Table 1: The results of t-test hypothesis testing

The Table 1 simplify the t-test hypothesis testing. The first results of significance tests were performed

on , the total of foreign direct investment shows that the value of 2.099 which is larger than

2.086, then the result will reject. This means that FDIt is important in explaining the dependent

variable, the gross domestic product (GDPt) in Malaysia at 95 percent significance level. The second

results of significance tests were performed on , the total of export (Xt) shows that the value of

which is smaller than , then the result will accept . This means that Xt is not

important in explaining the dependent variable, the gross domestic product (GDPt) in Malaysia at 95

percent significance level.Next, results of significance tests were performed on , the value of rate of

employment growth (PERt) shows that the value of which is smaller than , then the

result will again accept t . This means that PERt is not important in explaining the dependent

variable, the , the gross domestic product (GDPt) in Malaysia at 95 percent significance level.Then,

results of significance tests were performed on , the total of real effective exchange rate (REERt)

shows that the value of 2.411 which is larger than 2.086, then the result will reject . This

means REERt is important in explaining the dependent variable, the gross domestic product (GDPt) in

Malaysia at 95 percent significance level.Last but not least, the results of significance tests were

performed on , the total of real import (RIt) shows that the value of 5.227 which is larger than

2.086, then the result will reject . This means that RIt is important in explaining the dependent

variable, the gross domestic product (GDPt) in Malaysia at 95 percent significance level.

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Wald test

Based on the table above, it was found that F = 2.71 at the 95% confidence level while F* = 3.914.

Since , therefore the result will reject . Mediator all good independent variables in

explaining the dependent variable at a 95% confidence level.

Table 2: The results of F-test (Wald test) hypothesis testing

Hypotheses Statistical Critical Result
H0 : β1 = β2 = 0 Value Reject H0
H1 : β1 ≠ 0 Test
2.71


∗ =


= 3.914

Diagnostic tests

Autocorrelation analysis using Durbin Watson (DW) test

In examining the problem auto-correlation in the model, then the test will be carried out on the model.
Among the tests that will be done is Durbin Watson.

L DW N K DL DU 4-DL 4-DU :

1% 2.103 26 5 0.782 1.635 3.218 2.365 X
5% 2.103 26 5 0.979 1.873 3.021 2.127 X

At the significance level of and , the results of the Durbin Watson (DW)

statistical test obtained from SPSS version 23 is 2.103. Based on the above test results, the

significance auto-correlation problem doesn’t exist to be test at the level of significance for both

and .

Multicollinearity Analysis using comparison approach

Multi-collinearity tests conducted to determine whether there is a problem multi-collinearity serious or
not serious between the dependent variable.

Table 3: The Multicollinearity analysis

Relation R2 Pearson Result
Correlation
FDIt & Xt 0.813 Imperfect MC
FDIt & PERt 0.813 0.995 Imperfect MC
FDIt & REERt 0.813 0.858 Imperfect MC
FDIt & RIt 0.813 0.238 Imperfect MC
X t & PER t 0.813 0.224 Imperfect MC
X t & REER t 0.813 0.881 Imperfect MC
0.813 -0.636 Imperfect MC
X t & RI t 0.813 -0.411 Imperfect MC
PER t &REER t 0.813 -0.735 Imperfect MC
PER t & RI t 0.813 -0.528
Imperfect MC
REER t & RI t 0.462

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Based on the Table 3, above, . It was found that the relationship between the independent

variables, total of foreign direct investment with total of export (FDIt & Xt ), total of foreign direct

investment with total of rate of employment growth (FDIt & PERt), total of foreign direct investment

with total of real effective exchange rate (FDIt & REERt), total of foreign direct investment with total

of real import (FDIt & RIt), total of export with total of rate of employment growth ( Xt & PERt),

total of export with total of real effective exchange rate (Xt & REERt ), total of export with total of

real import (Xt & RIt), total of rate of employment growth with real effective exchange rate (PERt &

REERt), total of rate of employment growth with real import (PERt & RIt) and total of real effective

exchange rate with real import (REERt & RIt ) are having imperfect multi-collinearity problems. This

is because is larger than all those eleven relation, which are ,

,, ,

,, , ,and

In that case, every variables are applicable in the model.

Heteroscedasticity analysis using Park test

According to Table 4, Based on the first result obtained from new model Park Test (t-Test), total

foreign direct investment (FDIt) is which is smaller than the value of . When

, then the result suggested to accept . In other words, there is no

heteroscedasticity problem in the modelling. The same conclusion is the same across others variables.

t-test hypothesis for Park test

Table 4: The t-test hypothesis for Park test

Variables Hypotheses Statistical Critical Result
FDIt Test Value Accept H0
Xt H0 : β1 = 0 2.086 Accept H0
PERt H1 : β1 ≠ 0 -0.175 Accept H0
REERt H0 : β1 = 0 0.499 2.086 Accept H0
RIt H1 : β1 ≠ 0 1.003 2.086 Accept H0
H0 : β1 = 0
H1 : β1 ≠ 0 0.769 2.086
H0 : β1 = 0
H1 : β1 ≠ 0 0.459 2.086
H0 : β1 = 0
H1 : β1 ≠ 0

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5. CONCL USION

This study has focused on examining the contribution of economic-to-economic growth (GDP) in
Malaysia 1991 to 2016. There are five variable which have been selected for this study, namely
foreign direct investment, export, rate of employment growth, real effective exchange rate and real
import. There as on for selecting the independent variables in the study is due to their influenced
toward GDP from 1991 to 2016.In Malaysia an adaptation strategy, National Policy in climate change
was formulated to provide a framework which could be used as a guide for all government agencies,
industry, community as well as other stakeholders in order to face challenges in climate change
scenario. The policy was to ensure climate-resilient development to accomplish national aspiration for
sustainability.

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Rambeli, N. & Podivinsky, J. M. (2013) A study of exogeneity tests on export-led growth
hypothesis the empirical evidences on post-crisis exchange rate regime in Malaysia.

Rambeli, N., & Podivinsky, J. M. (2013). A Study Of Exogeneity Tests On Export-Led Growth
Hypothesis The Empirical Evidences On Post-Crisis Exchange Rate Regime In Malaysia.
International Business Education Journal. UPSI.

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