Download Macroeconomic Model for Malaysia`s

Macroeconomic Model for Malaysia’s Manufactured Exports:
A Simulation Analysis
Ghin Yin, Leow
School of Social Sciences
Universiti Sains Malaysia
11800 Penang, MALAYSIA
Telephone Number :604-6533140
Faks Number: 604-6589666
Email:[email protected]
JEL Categories: C51, F17, F42
Keywords: Macroeconomic model, Malaysia, Manufactured exports
This paper proposes a macroeconomic model for Malaysia. The model consists of the
private, government, trade and the monetary sector. It is a developed KeynesianNeoclassical synthesis macro model to study Malaysia’s macroeconomic behavior,
particularly the manufactured exports market share in the East Asian region. The
two-stage least square (2SLS) method is used for estimation. A complete listing of
the model equations and its performance are presented. Three simulations are
conducted, testing the model’s response to an earlier Ringgit exchange rate peg,
simulated foreign direct investment and simulated credit facilities for domestic
investment. Among the important findings are 1) Malaysia’s exchange rate peg has
overstayed. An exchange rate control should not be used for long-term. It is more of
a stabilization policy, especially for Malaysia’s trade-oriented developing economy.
2) Foreign direct investment (FDI) plays a key role in driving Malaysia’s
manufacturing sector, resulting in a much amplified economy expansion 3) Credit
financing for domestic investment helps to improve Malaysia’s manufactured market
share in the East Asian region, but not as great as FDI in economic development.
1
1. Introduction
This paper presents a macro econometric model for Malaysia, focusing more
on the trade sector. The foundation of macro econometric modeling is its underlying
economic theory. Macro econometric models are used in academic teaching as well
as research. In the former, the models can be used to illustrate theoretical
relationships in macroeconomics. In the latter, models can be used to create ‘what if’
scenarios and particularly useful to assess the effects of economic policies. Some
researchers also used macro econometric models to do forecasting.
In Malaysia, macro model analysis started in the late 1960s. Among the early
studies is by the Malaysian Institute of Economic Research (MIER). This institution
has published a book, entitled the Models of the Malaysian Economy (Imaoka, et al.,
1990) explaining macroeconomic models done by individual researchers as well as
the Malaysian government institution. Among the individual studies are by Cheong
(1976), Semudram (1982) and Abe (1987). These early work of econometric
modeling aimed to evaluate the impact of government polices on the whole
economy. Each of the studies has its own model structure which differs widely in
size and coverage. Thus, the models constructed are mainly comprehensive macro
econometric models and rather complicated. The relative complexities of the model
specification and disaggregation are important as they can determine the strong and
weak points of the model concerned.
In this paper, we are using a medium-sized annual econometric model. We
will be focusing on the trade sector. Specifically, this study aims to examine how the
Malaysian government can help to maintain the country’s manufactured exports
2
market share in the East Asian region1. We will be focusing on the manufactured
exports as there has been significant progress in Malaysia’s manufactured export
industries particularly the electrical and electronics (E&E). Three policy simulations
will be carried out on the model in order to gain some insight into the effect of any
exogenous factors or/and government policies on the manufactured exports. This is
pertinent as Malaysia is surrounded by competitive manufactured exporters in
particular Taiwan, South Korea and the emerging People’s Republic of China
(hereafter China). Furthermore, the technology structure of Malaysia’s manufactured
exports are still relatively lower compared to the ‘Four Asian Tigers’ namely Hong
Kong, Singapore, South Korea and Taiwan.
The remaining of this paper has been organized as follows. Section 2 gives a
brief overview of the EA economy. This is then followed by a brief overview of
Malaysia’s economy with focus on the manufactured-export industries since the
1970s. Section 3 describes specification of the model, methodology and the data.
This is then followed by discussion of the empirical results. Finally, Section 5
provides the possible policy implications of the analysis and the conclusion.
2. The Economies of East Asia
For over the past four decades, export has played an important role in the EA
economies. Even though each of the EA economies is different in terms of the size of
its population, land area, and availability of resources, they have focused on exportoriented industrialization to pursue their economic development and growth. The EA
1
In this study, East Asian (EA) countries include Hong Kong, Taiwan, South Korea, Singapore,
Thailand, Malaysia, the Philippines, Indonesia and China.
3
economies (Indonesia in a lesser extent) have experienced great evolution in their
manufactured exports profile particularly the electrical and electronics (E&E)
exports.
In the Asian region, the shift in the manufactured goods production and
exports began with labor-intensive products, and then moved towards more capitalintensive and technological-based exports, particularly the E&E. This process is led
by the ‘Four Asian Tigers’ namely Hong Kong, Singapore, South Korea and Taiwan;
and then followed by the emerging economies such as Malaysia, Thailand, the
Philippines, Indonesia and China. It is believed that combination of export-oriented
policies, inflow of foreign investments as well as supportive macroeconomic policies
has brought much prosperity and changes to these EA economies
2.1 Malaysia
From an agro-based economy in the 1960s, Malaysia today has also become a
manufactured exports-driven economy. The growing importance of the manufactured
exports is distinctly reflected in the structure of the economy. In 1980, the
agricultural sector contributed a 21% share to the Gross Domestic Product (GDP),
while the manufacturing sector’s share was 17.2%. But in 2008, the latter’s sectoral
share was 29.85% and the former was only a marginal 7.49% (Economic Report
1980/81 and 2008/09). Other than changes in the structure of the economy, there are
also changes in the composition of Malaysia’s manufactured exports as shown in
Table 1 below.
4
Table 1
Malaysia: Composition of Manufactured Exports, 1970-2008(%)
1970
1975
1980
1985
1990
2004
Food, beverages and tobacco
18.0
13.0
8.0
6.0
4.0
2.4
Textiles, clothing and
5.0
12.0
13.0
10.0
9.0
2.6
footwear
Wood products
15.0
11.0
7.0
3.0
3.0
2.7
Rubber products
3.0
2.0
1.0
1.0
3.0
1.6
Chemicals and petroleum
32.0
10.0
6.0
13.0
7.0
10.6
product
Non-metallic mineral
3.0
1.0
1.0
1.0
2.0
0.8
products
Iron, steel and metal
4.0
2.0
4.0
3.0
3.0
4.9
manufacture
Electrical and electronic
2.0
15.0
48.0
52.0
57.0
65.8
machinery and appliances
Other machinery and
11.0
13.0
4.0
5.0
4.0
1.3
transport equipment
Other manufactures
7.0
23.0
8.0
7.0
8.0
2.2
Total manufactured exports
615
1786
6319 12471 46833 390938
(RM million)
2008
3.9
2.2
2.0
2.5
14.7
1.08
5.9
56.4
1.9
2.6
491930
Source: Malaysia, Bank Negara Monthly Statistical Bulletin, various issues.
It is obvious that the E&E category dominates an increasing part of the
Malaysian manufactured exports. Malaysia’s semiconductor industry has established
in the early 1970s. Since then, the E&E industry rapidly has developed to be a major
industrial sub-sector. As shown the Table 1, the share of the E&E has started to
dominate Malaysia’s manufactured exports in the 1980s. Continued investments by
domestic and foreign companies have transformed the country’s E&E industry from
labor-intensive to capital-intensive based activities. Only towards the l990s, more
technology activities are introduced by the foreign companies. The rising share of
chemical and petroleum product exports in 2008 is contributed by the higher world
fuel prices.
Today, the total value of Malaysia’s exports and imports is twice as large as
her national income. According to the WTO 2008 Report, Malaysia was the world’s
21st largest exporting country and the 28th leading importer. All these statistics
reflect the rapid expansion of Malaysia’s trade.
5
Nonetheless, there is a reminder that some of Malaysia’s neighbors continue
to be remained ahead of us while others are catching up. The ‘Four Asian Tigers’ are
always ahead of Malaysia while China today is definitely ahead of the others.
Moreover, global uncertainties are rising. After the 1997 Asian financial crisis, Asian
countries are hit again by a series of global economic risks such as the 2001 global
economic slowdown, the Iraq conflict and the outbreak of the severe acute
respiratory syndrome (SARS) epidemic. At present, the world is in a recession
inflicted by a financial crisis which originated from the US subprime crisis in August
2007. Despite various policies, global financial stability could not be restored and the
G3 economies of the US, Japan and the Europe economies plunged into recession.
Trade-dependent economies in particular East Asia were badly affected as external
demand fell2. The current global trade market is getting difficult and uncertain. Only
those relatively competitive trading nations can survive. Can Malaysia’s
manufactured exports survive? Thus, this present study aims to address the question
of how the Malaysian government can help to maintain the country’s manufactured
exports in an econometric model. Section 3 explains the model, methodology and
sources of data.
3. Specification of Model
Basically, the model consists of four sectors; i.e. the private sector,
government sector, external trade and monetary sectors. Within each sector, there
are behavioral equations and identities. The structure of the model has been laid out
in Table 2 below.
2
The overall growth in East Asian economies declined by nearly 4% (from 10.4% to 6.6%), between
the year 2007 and 2008. It is expected to worsen in 2009 (IMF Economic Outlook 2009).
6
i) Private Sector
In this private sector, there are two behavioral equations:
real private
consumption and real private investment equations. In both these equations, we will
be able to gain some insight on any possible effects of interest rate policy on the
private sector. In Malaysia, the Bank Negara is entrusted to control interest rates
under the monetary policy. Over decades, the nation’s interest rate is basically set for
price stability in the economy. In our private investment equation, the independent
variables included are interest rate, foreign direct investment (FDI), domestic credit
from the government and a dummy variable for capital controls imposed by the
Malaysian government in 1994, 1998 and 1999. The last two variables are to explore
the possible effects of government policies in influencing private investment in the
economy.
ii) Government Sector
The aim of this model is not to provide a model of the government’s
behavior. The purpose of these tax equations is to link some relationships in the
model. We have direct taxes, export duties, import duties and other tax categories
equations. The government expenditure is specified as an exogenous variable and the
tax revenues are assumed to grow in line with the national income.
iii) The trade sector
This sector plays a key role in the model. It consists of export supply
equation, import demand equation, an equation for manufactured export
competitiveness as well as several identities. Total exports are disaggregated to
7
manufactured exports and other miscellaneous manufactured exports.3 In both these
export functions, factors included are the conventional factors of income and price.
In the manufactured exports equation, we have slotted in FDI and import factors on
the right hand side as both are features of Malaysia’s manufactured exports. On the
imports side, we have import equations for the machinery and transport equipment
(SITC 7), manufactured goods and miscellaneous intermediate manufactured articles
(SITC 6, 8) the remaining ones (excluding SITC 6, 7 and 8) mainly consist of
consumer goods. These import demand equations are also traditional import demand
functions where income and price are the explanatory variables.
Unfortunately, there is no traditional equation for competitiveness. No doubt
there is a rich literature review on the issue of competitiveness. But, there is no one
concise academic definition for the term competitiveness. This is due to lack of
international competitiveness theories, factors affecting competitiveness are
controversial
and
researchers
may
concentrate
on
different
‘levels’
of
competitiveness. In this present study, we will follow Tham and Loke (2001) in
constructing the manufactured exports competitiveness equation4. It is basically an
eclectic approach. The development in Malaysia’s economy will be a factor to follow
closely. Relevant empirical studies and the international trade theories will also serve
3
The manufactured exports include manufactured goods (STIC 6), machinery and transport
equipment (SITC 7) and miscellaneous manufactured articles (SITC 8). The miscellaneous ones are
the remaining items of aggregate exports such as consumer goods, mineral items and chemicals.
4
According to Tham and Loke (2001), the term competitiveness needs to be quantifiable in order to
be analyzed in research. Tham and Loke added that there are four approaches to measure
competitiveness. They are the ‘engineering’ approach, the environmental approach, the ‘capital
development’ approach and the ‘eclectic/academic’ approach. The last approach is more suitable for
studies analyzing competitiveness at the industry level, as an eclectic approach takes into account
various aspects of competitiveness.
8
as a guide in explaining the manufactured exports competitiveness equation
iv) The financial sector
This sector comprises the money market, government bond (securities)
market and the foreign exchange market. This sector may seem unrelated to the
trade, but most of the trade equations in this model consist of monetary components.
There are several identities and the equations included are the money demand and
price equation.
Table 2: Equations of the model
1) Private Sector
a)Private consumption
RCONS t   0  1RGDP t   2 DPL t   3 RINTt  1t
b)Private investment
RINVt   0  1 D(RGDP ) t   2 RINTt   3 FDI t 1   4 D(CREDITPRI ) t
 5 CAPt   2 t
2) Government Sector
c) Direct Tax
DTX t   0  1GDPt   3t
d) Indirect Tax
Export Taxes
EXDU t   0  1EX t   2 RPX t  3 EXDU t 1   4 t
e) Import Duties
IMDU t   0   1IM t   2 RPM t   3 IMDU t 1   5 t
f) Other taxes and non-tax revenue
OTHTAX t   0  1GDPt   2 OTHTAX t 1   6 t
3) Trade Sector
g) Manufactured exports supply
RMANUFX t   0  1RGDP t   2 RPX t   3 FDI t 1   4 RMANUFM t   7 t
h) Other non-manufactured exports supply
ROTHX t   0  1 RGDPt   2 RPX t  3 FDI t  1   4 ROTHX t 1   8 t
) Demand of imported investment goods
RINVM t   0  1 D(RINV) t   2 RPM t   3 REER t   4 RINVM t 1   9 t
j) Demand of imported investment goods
RMANUFM t   0   1 RGDP t   2 RPM t   3 REER
9
t 
 4 RMANUFM
t 1
 10t
k) Demand of other imported items
ROTHM   0  1 RGDP t   2 RPM t   3 REER t  11t
l) Manufactured export competitiveness
COMPET t  0  1OPEN t   2 INFt  3 REER t
 4 USGDP t  5 CHIGDPt  12t

4) Financial Sector
m) Money demand equation
M 3 t   0  1RGDP t   2 INT t   3 D(DPL) t  13t
n) Domestic price level
DPL t   0   1 MSS t   2 IMDUt   3DPL t 1  14 t
Identities and Definitions:1) GDPt  CONS t  INVt  G t  EX t  IM t
2) Yd t  GDP t  DTX t
3) EX t  (RMANUFX  PX / 100 )
t

CSTOCK
 (ROTHX  PX / 100 ) t 
4 IM t   (RMANUFM  PM / 100 ) t  (RINVM  PM / 100 ) t

(ROTHM  PM / 100 )t

5) RGDP t  GDP t / DPL t
6) CONSt  RCONSt * DPL t
7) INVt  RINVt * DPL t
8) REER t  NEER t * WCPI t / DPL t
9) RPM t  PM t / DPL t
10) MSS t  NFA t

CREDITPRI t  CREDITPUB t  NEXOP t
11) NFAt  EX t  IM t  NT  BALONGTC t  BASHORTC t  EO t
12) BOPt  EX t  IM t

KA t
13) OPEN t  ( EX t  IM t ) / GDP t
List Of Endogenous Variables
1. COMPET: Malaysia’s manufactured export market share to the average EA share
2. GDP: Nominal Gross Domestic Product (RM million, in current prices)
3. Yd: Disposable income (RM million, in current prices)
4. EX: Aggregate exports (RM million, in current prices)
5. IM : Aggregate imports (RM million, in current prices)
6. DTX: Direct tax revenue from households and corporations (RM million,
in current prices)
7. EXDU: Indirect tax revenue from exports (RM million, in current prices)
8. IMDU: Indirect tax revenue from imports (RM million, in current prices)
9. OTHTAX: Other taxes and non-taxes revenue (RM million, in current prices)
10. RCONS: Real private consumption (RM million, in constant prices, (2000=100)), that is
private consumption deflated by the domestic price index
11. RINV: Real private investment (RM million, in constant prices, (2000=100)), that is
private investment deflated by the domestic price index
12. RMANUFX: Real manufactured exports (SITC 6,7,8) (RM million, in constant prices,
10
(2000=100)), that is manufactured exports deflated by the export price index
13. ROTHX: Real non-manufactured exports (other than SITC 6,7,8) (RM million, in
constant prices, (2000=100)), that is non-manufactured exports deflated by the export
price index
14. RMANUFM : Real import demand for
manufactured goods miscellaneous
manufactured articles (SITC 6,8 ) (RM million, in constant prices, (2000=100)) that is
import of the manufactured goods deflated by the import price index
15. RINVM : Real import demand for investment goods such as machinery and transport
equipment (SITC 7) (RM million, in constant prices, (2000=100) that is import of the
investment goods deflated by the import price index
16. ROTHM : Real import demand for other items excluding SITC (6,7,8) such as consumer
goods, mineral fuel and chemicals (RM million, in constant prices, (2000=100)) that is
import of the other items deflated by the import price index
17. DPL: Domestic price level based on consumer price index (2000=100)
18. REER: Real effective exchange rate, that is, price adjusted by the nominal
effective exchange rate (RM/US$)
19. RPM : Relative import price index, PM/DPL
20. MSS : Money Supply (RM million, in current prices)
21. M3: Money demand (RM million, in current prices)
22. NFA: Net Foreign Asset (RM million, in current prices)
23. RGDP: Real Gross Domestic Product, GDP/DPL
24. CONS: Private Consumption, RCONS * DPL
25. INV: Private Investment, RINV*DPL
26. OPEN: Ratio of sum of EX and IM to GDP
27. BOP: Balance of Payment (RM million, in current prices)
List Of Exogenous Variables
1.G: Central government consumption and investment expenditures (RM million in current
prices)
2.NEER: Nominal effective exchange rate, that is, trade weighted effective
exchange rate based on Malaysian top ten trading partners.
3.WCPI: World consumer price index (2000=100)
4.PM: Import price Index (2000=100)
5.PX: Export price Index (2000=100)
6.RPX: Relative export price, PX/WCPI
7. INT: Market interest rate (%)
8.FDI: Inflow of foreign direct investment to the manufacturing sector (RM
million in current prices)
9.CREDITPRI: Domestic credit to the private sector (RM million in current prices)
10.CREDITPUB: Domestic credit to the public sector (RM million in current prices)
11.NEXOP: Net external operations (RM million in current prices)
12.KA: Capital account (RM million in current prices)
13.NT: Net transfer (RM million in current prices)
14.CHIGDP: China GDP (Yuan billion in current prices )
15.USGDP: The GDP of the U.S. (US$ million in current prices)
16.INF: The difference between Malaysia’s inflation rates with the
average inflation rates of the EA economies
17. CAP: Capital controls imposed by the government, dummy variable =1
for the period 1994, 1998 and 1999, 0 otherwise.
11
18. BALONGTC: Net Long-term Capital Inflows (RM million, in current prices)
19. BASHORTC: Net Short-term Capital Inflows (RM million, in current prices
20. EO: Errors and Omissions (RM million, in current prices)
21. CSTOCK: Change in stocks (RM million in current prices) to make the
national income identity holds in data
Other than behavioral equations, we also need identities to complete the
model. Identities are definitional equations. There will be 13 identities to complete
the model. Several important identities are the standard national income, balance of
payments, money supply, net foreign assets, exchange rate, ratio of prices, aggregate
exports and aggregate imports.
In any macro economy model, the Keynesian national income identity plays
the key role, whereby national output is the sum of private consumption, investment,
government expenditure and net exports. Money supply is identified as the sum of
net foreign asset (NFA), domestic credit to the private sector (CREDITPRI),
domestic credit to the public sector (CREDITPUB) and net external operations
(NEXOP). Both CREDITPRI and CREDITPUB are set as exogenous variables and
they help to link the monetary sector and real sector. The net foreign asset (NFA) is
defined as a simple identity, the sum of the balance of payments (BOP) and net
foreign reserves. The BOP consists of current account and capital account where the
former indicates trade performance while the latter account consists of net short-term
capital, net medium-term capital and any long-term capital flows.
The
abovementioned identities are in fact determined by the nation’s trade performance,
underlining the importance of the trade sector of this model. The exchange rate
(REER) has been adjusted by domestic price effect; the same for relative import
prices (RPM).
12
3.1Methodology
In order to examine the factors influencing Malaysia’s manufactured exports
competitiveness, the model will be estimated using the simultaneous equations
system. This framework is chosen as competitiveness for an economy’s exports
depends on several economic variables which are inter-related. It is going to be a
system of equations where the endogenous variable in one equation affects the other
variables in another equation. Thus, this helps to capture the direct and indirect
effects of trade competitiveness changes on the key macroeconomic variables and
vice versa.
Feedback between endogenous variables is a common feature in simultaneous
equations system. There are also exogenous variables, which are determined outside
the system. As for equations, a simultaneous equations system must consist of at
least two behavioral equations and one equilibrium condition. Behavioral equations
are equations determined by the behavior of economic agents such as the
consumption equation. In a simultaneous equations model, the ordinary least-squares
(OLS) estimation cannot be used as the error terms are going to be correlated with
the endogenous variables. The use of the OLS may produce inconsistent and biased
estimators. The most common estimator applied in a simultaneous equations model
is the 2SLS method. For more information on the 2SLS method, refer to Pindyck and
Rubinfeld, 1991.
Just like in a single-equation regression model, the overall statistical fit
of a simultaneous-equations model also needs to be evaluated. One of the ways to
13
evaluate the overall statistical fit of a simultaneous equations model is to evaluate the
statistical fit of the individual variables in a simulation context. Therefore, we will
carry out a historical simulation from 1980 till 2006 to test how well the endogenous
variables of this model track their historical data. Common measures used are the
root-mean-square simulation error (RMSE) and the mean squared error (MSE).
Both of these statistical measures serve to evaluate the goodness of fit of the model,
just like the coefficient of determination R2 in the single equation model.
3.2 Data Sources
The data required to establish the model is the annual time-series of Malaysia
from 1980 to 2006. The sources of data include the Bank Negara Malaysia, Monthly
Statistical Bulletin, Annual Economic Report, Annual Statistics of Manufacturing
Industries and the IMF’s International Financial Statistics.
4. Policy Simulations
Generally, policies to be simulated on a model can be classified into three
groups: supply side policies, demand side policies, and trade policies. In this paper,
three policy simulations will be carried out on the model in order to gain some
insight into the possible effect of any exogenous factors or/and government policies
on the manufactured exports5.
5
Prior to the simulation exercise, several assumptions need to be made. We assume that Malaysia will
be relatively stable and there are no exogenous shocks such as a global downturn, electronics cycle,
SARS and so forth which are capable of slowing down our manufactured exports.
14
The three cases of policy simulations are carried out between 1998 till 2006.
This period is chosen as the Malaysian authority responded rather differently to the
1997 financial crisis. At that point, the government needed to address the current
account deficit, inflationary pressures and large outflows of short-term capital as a
result of a sliding Ringgit. Just between July and December 1997, the Ringgit has
depreciated by more than 35 per cent and fell to a record-low of 4.88 against the US
dollar by 7 January 1998. The exports sector was also not doing well due to negative
sentiments from the EA region. To confront the crisis, the Malaysian authority
diverged from the ’conventional’ measures, i.e. pegged the Ringgit to the US dollar
at 3.8 to regain some monetary power and used selective capital controls to contain
economy stability, despite skepticism among economists as well as policymakers.
Table 3 below presents the policy changes and explanations for the three simulations.
15
Table 3 : Changes of Policies in Simulations
Policy Changes
Changes of Policy and Explanation
Case 1: Exchange Rate
Abandon the dollar peg in 2000 since many argued that
the peg has ‘overstayed’. The exchange rate is allowed
to appreciate by 0.4%, 0.8% and continuously until
2.4% in 2006. We chose the year 2000 as Malaysia has
nearly recovered from the financial crisis by then.
Case 2: Case 1 and FDI
A rise of 10% in FDI flows in 2001, and followed by
the actual rate changes till the end of the simulation
years. The Malaysian selective capital controls are
maintained. These control measures were aimed to
contain disruptive short-term speculative capital flows,
and did not affect trade and FDI flows into the
economy.
Case 3: Case 2 and credit
financing to domestic
Case III and a rise in financing for the manufacturing
investors of 6.4% (the average rise in the last decade)
starting 2001.
Note: After the earlier depeg in Case 1, we have increased the market interest rate to 3.286 in 2001 (a
rise of 24 %), and then 4% continuously till the end of the simulation years. This is because in the
actual scenario whereby de-pegging is done in 2005, the market interest rate has risen by 23.9% in
2006. Theoretically, a higher interest rate is needed to support a stronger exchange rate. Furthermore, a
stronger interest rate prevents expectations of currency depreciation and capital outflows. However,
the higher interest rate did not affect Case 2 much as interest rate is not a significant factor in the
investment equation.
4.1 Discussion of Results
4.1.1 Model Evaluation Results
Before discussing the policy simulation results, Section 4.1.1 will present the
evaluation results of the model; i.e. the RMSE and MSE values. The Table 4 below
reports the RMSE and MSE values for key endogenous variables in this
simultaneous-equations model. On the whole, the model can be considered to have
performed satisfactorily in the dynamic simulation as about three-quarters of the
RMSE and MSE values are less than 20%. Therefore, the tracking ability of the
16
model is satisfactory and the consequent simulation results are of acceptable
standard.
Table 4: Statistical Fit of Simulated Values For Key Endogenous Variables
Variables
RMSE (%)
MSE (%)
COMPET
13.74
-1.58
RGDP
10.77
5.0
MSE
DPL
1.35
-0.07
RCONS
13.74
5.66
RINV
43.50
8.25
RMANUFX
27.91
6.19
ROTHX
15.00
3.07
RINVM
19.11
3.64
RMANUFM
45.55
20.06
ROTHM
11.09
2.40
MSS
2.53
-0.26
M3
26.87
14.57
DTX
17.22
7.88
EXDU
43.37
15.53
IMDU
12.33
1.57
EX
11.31
3.44
IM
10.19
3.76
YD
11.48
4.89
REER
1.36
0.08
4.1.2 Policy Simulation Results
We will now turn to the policy simulations using the model. The results for
the three scenarios are shown as percentage deviations from a base run in a dynamic
17
simulation. In order to examine the effect of the simulated variable (such as the
exchange rate) on the economy, it is necessary to increase (decrease) the
control/original value of the exogenous variable concerned, ceteris paribus. Having
altered only that exogenous variable, under ceteris paribus conditions, the model will
be run again over the simulation years in order to obtain a new set of simulated
values. The percentage change of the simulated values from the effect of the
exogenous variable concerned from the baseline values will indicate the impact of
the variable on the economy. Table 5 below shows the percentage changes from the
baseline values for the actual scenario while Tables 5.1, 5.2 and 5.3 present the
simulation results for Case 1, 2 and 3 respectively.
Table 5: Percentage change from baseline values in the actual scenario
(% deviations from the baseline)
Endogenous
Variables
COMPET
DPL
RGDP
RINV
RMANUFX
ROTHX
RMANUFM
RINVM
ROTHM
REER
2001
2002
2003
2004
2005
2006
0.20
0.02
0.01
0.65
0.07
0.07
0.15
0.14
0.14
-0.02
0.10
0.02
-0.07
0.13
0.00
0.16
0.03
0.08
-0.09
-0.02
0.00
0.01
-0.02
-0.13
0.02
0.30
0.00
-0.01
-0.10
-0.01
-0.09
-0.01
0.05
0.06
-0.02
0.20
-0.06
0.04
0.09
0.01
0.00
0.00
0.11
-0.68
0.01
0.09
-0.07
0.04
0.13
0.00
-0.10
-0.01
0.07
-0.12
-0.05
0.00
-0.08
0.01
0.10
0.01
Case 1
The objective of the Case 1 simulation is to assess the impacts of an earlier
de-peg on Malaysia’s main economic variables. The result shows that Malaysia’s
18
Table 5.1: Percentage change from baseline solution for Case 1 Simulation
(% deviations from the baseline)
Endogenous
Variables
COMPET
DPL
RGDP
RINV
RMANUFX
ROTHX
RMANUFM
RINVM
ROTHM
REER
2001
2002
2003
2004
2005
2006
-2.86
0.0
-1.00
6.43
-2.54
-0.16
-5.60
1.84
3.08
-5.52
-3.55
0.06
-1.64
4.61
-4.51
-0.46
-9.30
2.88
2.00
-5.78
-2.28
0.18
-1.70
0.12
-4.88
-0.68
-9.10
2.29
-0.35
-2.13
-1.69
0.33
-1.49
-1.23
-4.61
-0.78
-8.30
1.50
-1.36
-0.15
-2.58
0.42
-1.97
1.97
-5.29
-0.91
-9.10
1.69
-0.86
-1.86
-3.85
0.51
-2.70
5.63
-6.73
-1.15
-12.0
2.31
-0.70
-3.94
relative manufactured exports competitiveness worsened for the first two years.6
Year 2001 was a global economic slowdown. Being a trade-dependent nation, the
Malaysian economy has not been spared from the slowdown (refer Table 3.1).
Between 2003 and 2004, Malaysia’s relative competitiveness improved (as shown by
the smaller negative percentage changes). But, it worsened again later on. Even
though Malaysia is relatively uncompetitive throughout the simulation period,
overall the situation is not so bad compared to the actual scenario. In the actual
scenario (refer Table 5), Malaysia has lost her competitive position to the reference
economies starting from 2003 until 2006, when in fact Malaysia de-pegged her
exchange rate only in July 2005. This suggests that an exchange rate peg need not
necessarily ‘protect’ a country’s exports market share. The strength of a country’s
export standing in a region depends on a combination of internal as well as external
factors.
Improvement in competitiveness means the growth in Malaysia’s manufactured exports market share
compared to the reference economy as a whole is higher and vice versa.
6
19
The other domestic variables responded in different ways. Firstly, the earlier
de-peg has a contractionary effect on the GDP. On average, the GDP has suffered a
drop of nearly 2% (-1.75%). The lower GDP was mainly caused by the contraction in
exports. Manufactured exports suffered a significant reduction and worsened towards
the end (around 7% after 6 years). The negative impact of an earlier de-peg on the
non-manufactured exports is less. This suggests that Malaysia’s manufactured
exports are likely to have over-depended on the 7-year exchange rate peg and faced
difficulties to adjust to a floating exchange rate
We can actually observe a rather similar trend of change for manufactured
imports. In fact, the drop in manufactured imports is double that of manufactured
exports, a reduction of 12% by the year 2006. The sharp decline in manufactured
imports reflects the high usage of imports by both foreign and local manufacturing
firms7. No noticeable drop in investment imports is observed. This is because
imported investment items such as heavy machineries do not follow the on-going
production closely. These items are ordered only when there are plans to expand the
coming production.
The stronger Ringgit also did not help to curb inflation as
shown by the slightly higher price simulated values. This finding in fact matches
Malaysia’s economy whereby the exchange rate policy has been seldom used as a
tool to fight inflation.
7
In Malaysia, industries in the manufacturing sector are largely dominated by foreign firms. Many of
the industries are import-dependent, particularly electrical machineries. These electronic industries
are the key driver of the economy, but import a considerable amount of intermediate and investment
goods every year. Foreign firms have accounted over three-quarter of Malaysia’s manufactured
exports since the nineties.
20
Case 2
The objective of the Case 2 simulation is to examine the impact of FDI flows
on the economy. In the Case 1 simulation earlier, we have taken off the Ringgit peg
earlier. This allows the currency to move in tandem with the market forces and
remain at a fairly fair value. This would have boosted Malaysia’s position as a FDI
destination. In addition, the Malaysian currency has been considered by many to be
undervalued during the 7 year period peg; and led to the lethargic FDI inflows then.
The simulation results in Table 5.2 below suggest that the simulated FDI
inflows did not favor Malaysia’s manufactured exports competitiveness. Compared
to the preceding scenario, the negative percentage changes are marginally bigger.
This may suggest that the FDI inflow in Malaysia is mainly the export-oriented type
whereby they are believed to have limited contribution to technology transfer and
exports’ upgrading. Most of the TNCs are slow in transferring the expertise needed
to achieve maturity in production technology. Moreover, majority of Malaysia’s own
domestic investment are concentrated in the petroleum and petrochemical industries.
Not many have ventured into the E&E industries8. Therefore, it is of no surprise that
Malaysia’s technological maturity is still relatively low compared to her neighboring
countries.
Nonetheless, one good point of this type of FDI is it contributes to
employment, trade and economic growth. This explains our higher simulated values
for the GDP starting the year 2002. This is contributed by higher key components of
8
According to the Malaysia Industrial Development Authority (MIDA) 2008 report, in 2007 RM 13.7
billions amount of foreign investment was in the E&E products. This is then followed by RM 5.3
billions in the petroleum and petrochemical products. As for the domestic investment, they were
mainly in the petroleum and petrochemical products (RM 8.5 billions) and basic metal products (RM
7.2 billions). Only about 1.4 billion amount of domestic investment was in the E&E products.
21
the economy’s aggregate demand, particularly investment and manufactured exports.
This in fact matches Malaysia’s economy during the export-oriented industrialization
(EOI) phase in the 1980s. During the EOI phase, the Malaysia government has been
relying mainly on FDI in the manufacturing sector to create more employment and
thus stimulate the economy growth
Table 5.2: Percentage change from baseline solution for Case 2 Simulation
(% deviations from the baseline)
Endogenous Var.
COMPET
DPL
RGDP
RINV
RMANUFX
ROTHX
RMANUFM
RINVM
ROTHM
REER
2001
-3.14
0.14
-1.11
1.74
-3.35
2.15
-7.55
2.05
3.19
-5.66
2002
-4.49
0.22
0.95
9.24
-1.91
-1.06
-9.40
3.41
4.86
-5.93
2003
-3.30
0.25
0.32
11.75
-2.89
-2.27
-8.22
3.09
1.76
-2.20
2004
-2.34
0.31
0.64
9.79
-1.52
-3.48
-6.47
2.02
1.10
-0.12
2005
-2.75
0.29
-0.96
13.20
-3.07
-3.53
-6.98
2.06
0.19
-1.74
2006
-3.77
0.33
-1.24
16.02
-3.38
-4.31
-9.26
2.28
0.92
-3.77
A strong complementary relation between FDI and domestic private
investment is observed, especially towards the end of the simulation period. This
illustrates that FDI in Malaysia crowds-in domestic investment. Agosin and Mayer
(2000) also found that FDI crowds-in domestic investment in Asia, but crowds-out
domestic investment in Latin America. Given a complementary relationship between
FDI and domestic investment, we found higher simulated values for Malaysia’s
manufactured exports. Again, we found that the manufactured imports grew in line
with manufacturing production. The most significant rise is found in imported
consumer goods, primarily due to the income effect of a stronger GDP. Interestingly,
the higher imports did not lead to inflationary pressures (compared to Case 1). This
could be ascribed, partly by the FDI in Malaysia. FDI helps to absorb unemployed
resources in the economy and thus improves the country’s output and productivity.
22
An important point to be noted from this simulation is that FDI per se is
inadequate for Malaysia to capture a larger market share of manufactured exports in
the East Asian region. This is because FDI is almost a norm for most EA developing
countries. Furthermore, Malaysia is likely to have lost to her neighbors such as China
in attracting FDI inflows. However, higher FDI inflows help Malaysia’s developing
economy to develop and grow.
Case 3
This Case 3 simulation aims to evaluate the impact of the government’s credit
facilities (CREDITPRI) on the economy. Table 5.3 below shows Malaysia’s
competitiveness only started to improve in the last two simulation years as compared
to previous Case 2. The most obvious positive impact is a substantial positive effect
on the investment.
The simulation led to a surge in private investment starting from the first
year. Private investment has risen on average, by around 26% during the simulation
period. Added by the multiplier and accelerator effects, the result is an amplified
economic expansion whereby the GDP rose by nearly 2% in the first year. After the
rise in the GDP reached a peak of 2.5% in 2004, the rise diminished in the latter part.
This shape of impacts on GDP over time reflects that the credit facilities stimulus has
been partially offset by higher import demand and prices. Imported consumer goods
rose the fastest, followed by imports of investment goods and manufactured goods.
The higher import is mainly induced by stronger income effect. Fortunately the
Ringgit did not appreciate much, probably because of the earlier de-peg. This does
23
not impact the manufactured exports negatively. Though the performance of the
manufactured exports improved, but imports rose much faster. The higher demand
for imported consumer goods is mainly induced by the strong income effect, whereas
the higher non-consumer imports especially imported investment items indicates the
dependency of the local private investors on imports in the manufacturing production
line.
Table 5.3: Percentage change from baseline solution for Case 3 Simulation
(% deviations from the baseline)
Endogenous Var.
COMPET
DPL
RGDP
RINV
RMANUFX
ROTHX
RMANUFM
RINVM
ROTHM
REER
2001
-4.09
0.25
1.72
29.56
-2.24
2.61
-6.17
3.04
6.33
-5.76
2002
-4.75
0.45
3.13
29.11
-0.58
-0.24
-7.44
4.03
7.40
-6.15
2003
-3.29
0.62
1.96
24.20
-1.50
-1.33
-6.12
3.45
3.86
-2.55
2004
-2.36
0.80
2.46
25.81
0.24
-2.43
-3.88
2.62
3.96
-0.61
2005
-1.95
0.84
-1.64
12.69
-2.39
-2.88
-5.33
1.73
0.20
-2.27
2006
-3.59
0.96
-0.74
32.69
-2.42
-3.73
-7.62
2.95
2.55
-4.37
This Case IV has underscored the importance of the government’s financial
support for domestic investors and consequently the development of Malaysia’s
economy. Furthermore, there are many channels through which a financial sector can
affect the pattern of economic growth. Under the endogenous growth theory, there
are studies analyzing the role of domestic financial system for Malaysia’s economic
development9. For Malaysia, we have found a complementary relationship between
FDI and private investment. Therefore, provision of efficient credit services enable
quicker and more efficient flow of technical expertise, higher productivity and many
9
For recent studies, see Chong et al. (2005) and Ang (2008). In general, their results show that
financial evolution leads to output expansion. This is because financial development promotes
domestic savings and thus attracts foreign capital. With stronger financial support, technological
expertise from the foreign investors is also easier to be transferred to the local firms.
24
more efficiency gains within the domestic economy. For Malaysia, financial support
from the government needs to reach a certain threshold in order for the economy,
particularly the domestic investors to absorb even more positive spillovers of FDI.
We attempted an additional scenario to compare the relative importance of
FDI and financial assistance to the investors. In this simulation, we did not simulate
FDI in 2001. Only the exchange rate, interest rate and credit facilities to the private
investors are simulated. The effects for key variables are summarized in Table 5.3b
below.
Table 5.3b: Percentage change from baseline solution for Case 3b Simulation
(Without FDI simulation)
(% deviations from the baseline)
Endogenous Var.
COMPET
DPL
RGDP
RINV
RMANUFX
ROTHX
RMANUFM
RINVM
ROTHM
REER
2001
-3.76
0.10
1.70
36.39
-1.48
0.27
-4.34
2.92
6.09
-5.62
2002
-3.76
0.30
0.34
26.52
-3.30
0.30
-7.53
3.55
4.34
-6.00
2003
-2.21
0.56
-0.34
14.31
-3.67
0.17
-7.25
2.70
1.47
-2.50
2004
-1.64
0.84
-0.04
16.82
-3.14
0.12
-6.11
2.16
1.11
-0.65
2005
-1.68
0.99
-3.09
3.57
-5.04
-0.44
-8.0
1.41
-1.35
-2.42
2006
-3.69
1.18
-2.57
23.33
-6.24
-0.78
-11.04
2.95
0.50
-4.58
Interestingly, we found that the credit facilities simulation led to a slight
improvement in Malaysia’s competitiveness, even though Malaysia is still losing out
to the reference economies. This is shown by smaller negative percentage changes
since 2002. The credit facilities’ simulation triggered a sizeable increase in domestic
investment, but not much impact on the growth of the economy. On the other hand, it
is the presence of FDI that could drive the economy more (Refer Table 5.2).
Performance of the manufactured exports also worsened whereby the negative
percentage change in Table 5.3b) above is much larger than those in Case 2.
25
Consequently, the GDP growth is less dynamic. The comparison of results in Table
5.2 and Table 5.3b has highlighted again that foreign investors play an important role
in Malaysia’s economic development, in particular in the manufacturing sector10.
5. Conclusion
This paper has presented a medium-scale macro econometric model for
Malaysia’s economy. The main purpose is to perform dynamic simulation on the
model from 1980 till 2004; and thereby determine the effect of the Ringgit/US dollar
peg, higher foreign investment flows and government support to the domestic
investors on the key macroeconomic variables in particular manufactured exports
competitiveness. Malaysia’s manufactured exports competitiveness is indeed still
behind her East Asia neighbors. An exchange rate peg should not be used for longterm. Once the economy regains its growth momentum, the exchange rate should be
allowed to move in tandem with economic forces. It is better to keep pace with
global developments. The longer an exchange peg stays; it is only going to a tougher
transition period for the economy.
Malaysia’s manufactured exports are still highly dependent on imports and
FDI in the production line. Till today, foreign investors still play important role in
Malaysia’s manufactured export-dependent economy. Malaysia’s industrial base
needs to rely on FDI to further develop, especially for the capital-intensive and
10
In the Case 2 earlier, the presence of FDI has led to higher simulation values for the real GDP
variable starting from the second year. Positive spillovers from FDI usually involve some lagged
effects. The GDP is certainly more stable as shown by the stronger positive percentage changes and
smaller negative ones (refer Table 5.2 on p.16 and Table 5.3b above). The stronger GDP is mainly due
to the manufactured exports
26
valued-added segments in the manufacturing production line. In view of the
importance of FDI inflows for Malaysia, a rich assortment of incentives need to be
maintained in order attract continued FDI inflows.
Concurrently, domestic investors should not be neglected. Financial support
from the government plays a key role in generating domestic investment. Many of
the Malaysian investors lack the knowledge and skills to venture into capitalintensive and high technology projects. Financial constraint is another difficulty. It is
also important for the policy makers
to
give more attention to the
efficiency/productivity of domestic investment than just to the magnitude of
investment. Those inefficient domestic industries need to be cut off and more to be
focused in the E&E industries; so that the domestic investors can absorb even more
positive externalities from the FDI flows. Gradually, Malaysia needs to produce her
own intermediate and investment parts to cut down the high import costs. This may
not be possible within a short period, but over the long-term with steady FDI flows
and government support, it would be realized. Only with a stronger economic and
technological base, Malaysia can further develop her economy which is important to
enhance her manufactured exports competitiveness.
27
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