Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
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 References Abe, Shigeyuki ( 1987) A CGE Analysis of Income Distribution: The Case of the Malaysian Economy. Asian Economic Journal, September, pp.19-40. Agosin, M. R. and Mayer, R. (2000) Foreign investment in developing countries. Does it crowd-in domestic investment? UNCTAD Discussion Paper, no.146, pp. 1-23. Ang, J. (2008) What are the mechanisms linking financial development and economic growth in Malaysia ? Economic Modelling, vol.25, issue 1, pp.38-53. Appleyard, R. (2000) International Economics, fourth edition. Boston, U.S: McGrawHill Press. Bautista, R. M. (1988) Macroeconomic Models For East Asian Developing Countries. Asian Pacific Economic Literature, vol.2, no.2, pp.1-25 Cheong, K.C. (1976) A macroeconomic model for West Malaysia, 1949-1969 The Developing Economies, 14, pp. 46-71. Chong, C. K., Yusop, Z. and Soo, S. C. (2005) Foreign direct investment and economic growth in Malaysia: The role of domestic financial sector. The Singapore Economic Review, vol.50, no. 2, pp. 245-268. Gujarati,D. (1992) Essentials of Econometrics, United States: McGraw-Hill, Inc.. Hideki, I. et al (1990) Models of the Malaysia economy: A survey. Kuala Lumpur: Malaysian Institute of Economic Research (MIER). International Monetary Fund (various issues) International Financial Statistics (quarterly), Washington, D.C. __________2008.World Economic Outlook Update, Washington, D.C. [Online] [Accessed on 16th January 2009] Available from: http://www.imf.org/external/pubs/ft/weo/2008/update/01/pdf/0108.pdf Jomo K.S., Khong, H. L. and Ahmad, S. K.,ed. (1987) Crisis and response in the Malaysian economy. Kuala Lumpur: Malaysian Economic Association. Jomo, K. S. ed. (2001) Malaysian Eclipse: Economic Crisis and Recovery. London and New York: Zed Books Ltd. Malaysia. Bank Negara (various issues) Monthly Statistical Bulletin, Kuala Lumpur. _________ Malaysia Industrial Development Authority (MIDA) various issues. Report on the Performance of the Manufacturing Sector. ________ Ministry of Finance (various issues) Economic Report. 28 Pindyck, R. S. and Rubinfeld, D. L. (1991) Econometric models and economic forecasts, third edition, Singapore: McGraw-Hill Press. Porter, M. E. (1990) The competitive advantage of nations. New York: The Free Press. Semudram, M. (1982) A macro model of the Malaysian economy: 1959-77. Developing Economies, 20, pp.154-172. Whitley, J. (1994) A course in macroeconomic modeling and forecasting. Whitehouse Station: Harvester Wheatsheaf. Wong, K.Y. and Tang, T.C. (2007) Foreign direct investment and electronics exports: Exploratory evidence from Malaysia’s top 5 electronics exports. Economic Bulletin, vol.6, no.14, pp.1-7. World Bank (1993) The East Asian Miracle: Economic growth and public policy. New York: Oxford University Press. World Trade Organization (WTO) (various issue) International Trade Statistics Report, Geneva: WTO _________ (various issue) Trade Policy Review: Malaysia, Geneva: WTO. _________ (various issue) World Trade Report, Geneva: WTO. 29