Macroeconomic Instability Index and Malaysia Economic Performance

The economic performance of Malaysia was affected by a series of financial crises that had induced macroeconomic instability in the country, which in turn had immensely dampened the nation’s economic growth rate. No doubt Malaysia needs an indicator to monitor the nation’s economic performance from time to time. This study attempts to construct such indicator known as Macroeconomic Instability Index (MII). The constructed MII shows two significant spikes at 1998 and 2008, which correspond to the Asian Financial Crisis and US Subprime Mortgage respectively, that had resulted in negative growth rate for GDP of Malaysia in 1999 and 2010. Results obtained from further analysis by the ARDL technique show that MII has negative and significance effects on economic performance. Moreover, MII has predictive power against economic performance as early as two periods in advance. The constructed MII could serve as end-product for policy purposes or intermediate-product for other economic and finance studies.


Introduction
The economic performance of Malaysia was affected by a series of financial crises that had induced macroeconomic instability in the country, which in turn had immensely dampened the nation's economic growth rate.For instance, the negative effect of 1997 Asian Financial Crisis and the 2007 US Subprime Mortgage Crisis (which turned into a fully-blown Global Financial Crisis in September 2008) caused Malaysian economy to perform poorly.These crises reduced Malaysia's exports as well as national aggregate demand.Many businesses failed and the non-performing loan of commercial banks escalated to 22.4% in November 1998 from 6.5% in 1997, just for an instance.In 1998, the output of the real economy declined plunging the country into its first recession for many years.During that year, the ringgit plunged below 4.7 and the KLSE fell below 270 points.Foreign direct investment inflow to Malaysia in 1998 also reduced by 59% compared to 1997.As a result, the country's gross domestic product plunged 6.2% in 1998.On the other hand, after the Global Financial Crisis, the contraction in manufacturing was steepest in export-oriented sectors that are facing the full brunt of the collapse in demand in developed markets.Overall, exports fell by -7.5% in the fourth quarter of 2008 and -20% in the first quarter of 2009.Electronics exports, which was badly affected, declined by -44.0% in the first quarter and -34.6% in the second quarter of 2009.Moreover, the construction sector contracted 23.5%, manufacturing shrunk 9% and the agriculture sector 5.9%.The unemployment rate rose from 3.2% in 2007 to 3.7 % in 2008 (Zainal Abidin and Rasiah, 2009).Stock market in Malaysia also fell from a closing index of 1445.03 in 2007 to 876.75 in 2008, amounting to fall of 39.3%.Hence, it is obvious that Malaysia needs an indicator to monitor the nation's economic performance from time to time.In this conjunction, Macroeconomic Instability Index (MII) is an important indicator of a country's economic condition.This study aims to construct MII for Malaysia and analyses its impact on economic performance.
Macroeconomic instability was ambiguously defined back in those days, however, World Bank (1993) emphasized that budget deficit, foreign debt and the instability of exchange rates as influential factors in macroeconomics instability.In addition to this, World Bank (1993) made it clear that the foundation of macroeconomic stability in one's country is to have a constant growth rate, moderate or low inflation rate, and taking control of external debt and currency management.Since then, studies between macroeconomic instability and growth nexus became widely explored by economists and policymakers to formulate a perfect measurement for macroeconomic instability index (MII).

Literatu
Many econ literatures growth.In inflation r aforementi (1992)   Table 2 shows that GDPPC, SSE and TLF are not stationary in their levels, as the null hypothesis of stationary series could not be rejected at 5% significance level.However, their achieved stationarity after taking the first difference.Thus, it can be concluded that theses variables are integrated of order 1.On the other hand, FDI and MII are determined to be stationary in their levels.So, they are considered as integrated of order zero.With these findings, since the variables are integrated with mixed orders of zero and one, ARDL technique rather than OLS technique is more appropriate to be adopted for the estimation of Equation ( 2).Thus, the ARDL technique which is available at EViews 9 is performed and the results obtained are reported in Table 3.As seen in Table 3, the optimal lags for GDPPC, SSE, TLF, FDI and MII are 4,4,4,4 and 2 respectively.These lags are selected based on Akaike information criterion.The selected model has passed through a battery of diagnostic tests on the model's residuals.Specifically, the residuals are normally distributed by the Jarque-Bera test, since the probability of the test statistic is 0.00, which is less than conventional significance level, for instance 0.10.Besides, the Breusch-Godfrey LM Serial Correlation Test result indicates no serial correlation in residuals.Meanwhile, the Breusch-Pagan-Godfrey heteroscedasticity Test result shows no heteroscedasticity in the residuals.The F-statistics reveals the overall significance of the included independent variables and the R2 value indicates that these variables can explained 99% of the variations in the dependent variables, i.e., GDPPC.Thus, this model has fitted the data excellence well and it is thus suitable for interpretation.
The results as shown in the middle panel of Table 3 indicate that GDPPC is significantly affected by the present and past values of itself and all the control variables.Moreover, the variable of interest in this study, i.e., MII has negative effects on GDPPC and the effects are significance at 10% level.In this respect, GDPPC is also significantly affected by the present (MII t ) and the two past values (MII t-1 , MII t-2 ).This means MII has predictive power against GDPPC as early as two periods ahead.In addition, as the current value of GDPPC is significantly affected by the two lagged values of MII, this is essentially meaning that GDPPC is Granger caused by MII.

Conclusion
The economic performance of Malaysia was affected by a series of financial crises that had induced macroeconomic instability in the country, which in turn immensely dampened the nation's economic growth rate.For instance, the negative effect of 1997 Financial Crisis and the 2008 US Subprime Mortgage Crisis caused Malaysian economy to perform poorly.Typically, Malaysia gross domestic product experienced an economy contraction of 7.4% in 1998.Malaysian production growth was exposed to high inflation, excessive budget deficit and negative trade balance when the economy slumped into recession in 1997.Hence, it is obvious that Malaysia needs an indicator to monitor the nation's economic performance from time to time.In this conjunction, Macroeconomic Instability Index (MII) is an important indicator of a country's economic condition.
This study is taken up to construct the MII for the case of Malaysia.The variables adopted to construct this index include unemployment, inflation rate, budget deficit as percentage of per GDP, trade deficit and exchange rate depreciation rate.The constructed MII shows two spikes at 1998 (MII=0.66)and 2008 (MII=0.59),which correspond to the Asian Financial Crisis and US Subprime Mortgage Crisis respectively, that had resulted in negative growth rate for GDP of Malaysia in 1999 and 2010.Results obtained from further analysis by the ARDL technique show that MII has negative and significance effects on economic performance.Moreover, it is found that MII has predictive power against economic performance as early as two periods ahead.
The constructed MII could serve as end-product for policy purposes or intermediate-product for other economic and finance studies.The potential users of this new index include governments, exporters, foreign direct investors, international firms, corporations, bankers, fund managers, stock market and foreign exchange markets participants.

Table 2 .
Integration Order as Identified by DFGLS Stationarity Test Notes.a The test is estimated with Intercept and Trend.b The test is estimated with Intercept.** and *** indicate rejection of the null hypothesis at 5 and 1% significance levels respectively.