the impact of government sectoral expenditure on malaysia’s economic growth presenter : aimi ajlaa...
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THE IMPACT OF GOVERNMENT SECTORAL
EXPENDITURE ON MALAYSIA’S ECONOMIC
GROWTH
Presenter : AIMI AJLAA BINTI SALIMI
CONTENTS
INTRODUCTION
Malaysia’s Overview: After independence in 1957, economic growth of
Malaysia was increased due to the increased on government expenditure on health, education, communication and other public sectors.
During the financial crisis in 1997 until 1999, the current account is deficit over 6% of gross domestic product (GDP). In 2008, the crisis again occurred which impact to the Malaysian economy performed decrease on GDP growth rate of 4.6%.
In 2009 until 2012, economy of Malaysia has been recovered and expected to record positive growth rate.
INTRODUCTION
Background of the study:
The Malaysia’s economy have impact on two types of government expenditure which includes government development expenditure and government operating expenditure.
From these two types of government expenditure has performed the total government expenditure.
The government expenditure includes security, social services, economic services and general administration. These study focuses on economic services : health and education expenditure that will impact to economic growth
INTR
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UC
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INTR
OD
UC
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LITERATURE REVIEW
LITERATURE REVIEW
METHODOLOGY
METHODOLOGY Steps on gathering the results:
1) Stationarity Test (Unit Root Test) by using Augmented Dickey-Fuller (ADF) test and Philips Perron (PP) test
2) Autoregressive Distributed Lags (ARDL) test:
a) F-statistic testb) Long Run Cointegration
c) Short Run Cointegration
3) Diagnostic Test:
a) Jarque-Bera Normality test
b) Lagrange Multiplier (LM) serial correlation test
c) Autoregressive Conditional Heteroscedasticity (ARCH) test
d) Ramsey RESET functional form tests (Error test)
e) CUSUM and CUSUM-squared test
RESULT AND DISCUSSION
To test the unit root most
widely used test is
Augmented Dickey-Fuller
(ADF) test and Philips-Perron
(PP)
S T A T I O N A R I T Y
ADF test and PP test
Notes: Significant Level: *** 1% ; **5% ; *10%
RESULT AND DISCUSSION
ARDL cointegration test:
To perform ARDL cointegration test, the model should be transformed into unrestricted error correction model (UECM)
Autoregressive Distributed Lags (ARDL) test
APPR
OA
CH
ARDL
Cointegration test
RESULT AND DISCUSSION
Critical Values for ARDL Cointegration Test, Narayan (2005)
Significant Level
Lower Bound Upper Bound
1% 4.428 6.2505% 3.202 4.54410% 2.660 3.838
Critical Values ( k = 4 , n = 40)
10% Significant level
APPR
OA
CH
ARDL
H0 : 1 = 2 = 3 = 4 = 5 = 0 (no cointegration)
H1 : 1 ≠ 2 ≠ 3 ≠ 4 ≠ 5 ≠ 0 (cointegration)
Reject the H0
RESULT AND DISCUSSION
APPR
OA
CH
ARDL
Variable Coefficient t-Value
Constant -0.7044 *** -3.0275
Capital Formation 0.1548 *** 4.1971
Labor Force 1.4854 *** 4.0054
Health Expenditure
0.2767 ** 2.3345
Education Expenditure
-0.2327 * -1.8119
Long Run Cointegration
Notes: Significant Level: *** 1% ; **5% ; *10%
RESULT AND DISCUSSION
APPR
OA
CH
ARDL
Variable Coefficient t-Value
Constant -4.2368 *** -3.9542
Capital Formation 0.2610 *** 6.3979
Labor Force 0.8934 *** 5.049
Health Expenditure
0.1664 * 1.9313
Education Expenditure
-0.1400 * -1.9271
Short Run Cointegration
(ECTt-1) -0.60146 Adjustment at 60% over the period of
time
Notes: Significant Level: *** 1% ; **5% ; *10%
RESULT AND DISCUSSION
DIAGNOSTIC TESTS
RESULT AND DISCUSSION
Plot of Cumulative Sum of RecursiveResiduals
The straight lines represent critical bounds at 5% significance level
-5-10-15-20
05
101520
1973 1978 1983 1988 1993 1998 2003 2008 2012
Plot of Cumulative Sum of RecursiveResiduals
The straight lines represent critical bounds at 5% significance level
-5-10-15-20
05
101520
1973 1978 1983 1988 1993 1998 2003 2008 2012
Plot of Cumulative Sum of Squaresof Recursive Residuals
The straight lines represent critical bounds at 5% significance level
-0.5
0.0
0.5
1.0
1.5
1973 1978 1983 1988 1993 1998 2003 2008 2012
Plot of Cumulative Sum of Squaresof Recursive Residuals
The straight lines represent critical bounds at 5% significance level
-0.5
0.0
0.5
1.0
1.5
1973 1978 1983 1988 1993 1998 2003 2008 2012
*CUSUM and CUSUM-squared in order to test for constancy of long-run parameters Brown et al. (1975)
*Result:Both stay within the critical bounds as the estimated parameters are stable over the analysis period
CO
NC
LU
SIO
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Presenter : AIMI AJLAA BINTI SALIMI
Q&A
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