Testing Of The “export-led Growth” Hypothesis: Case Study Of Sabah

Testing of the “Export-led growth” Hypothesis: Case Study of Sabah Ting Siew King1, Dr. Fumitaka Furuoka2, Lim Fui Yee Beatrice2 and Chong Hui Ing3

Abstract

Malaysia has adopted the so-called “Export-led growth” strategy since its independent from Britain in 1957. This paper chooses Sabah as the case study to test the hypothesis and examine the relationship between Sabah’s exports and economic growth. The case of Sabah is interesting because the State has promoted exports as the “engine” for its economic growth. On the other hand, exports have been playing a crucial role in the Sabah’s economy, there is still lack of systematic empirical analysis of the impact of exports on the state’s economic performance. There are two main empirical findings from this study. Firstly, the Johansen cointegration tests indicate that there is no existence of equilibrium relationship between exports and economic growth in Sabah state. Secondly, the “Granger” causality tests indicate that there is also no causality between exports and economic growth in Sabah. Therefore, the results of the empirical analysis do not support the “export-led growth” hypothesis. Some recommendations for policy makers could be drawn from this empirical research. Despite of exports’ important role in the Sabah’s economy, exports don’t seem to “Granger” cause economic growth. In other word, some other economic activities, such as consumption, investment, or government expenditure, could be alternative sources of its economic growth. The future research may incorporate these variables into the econometric model in order to identify a real “engine” of the Sabah economy. Keywords

Sabah, Exports, Economic Growth

1

Lecturer, Universiti Teknologi Mara, Faculty of Business Management, Sabah Branch. Lecturer, Human Resource Economics Program, School of Business and Economics, Universiti Malaysia Sabah 3 Master Research Student, School of Business and Economics, Universiti Malaysia Sabah 2

1

1. Introduction The Malaysian government has adopted the so-called “export-led” economic development strategy since its independent from Britain in 1957. The effectiveness of this strategy seems to depend on whether the country could find its own niche in the global marketplace. In other word, whether the country could tap into the demands of the world economy. Some developing countries could overcome their dismal economic situation by promoting exports. In these efforts, exports have been viewed as “engine” of economic growth. In recent decades, the validity of export-led growth hypothesis has been supported by impressive success stories from Asian countries. For example, Japan’s remarkable performance in the global export market in the 1960s was repeated in the 1970s by Asian Newly Industrialising Economies (NIEs) and in the 1980s. More recently, China’s economic success highlighted the importance of exports to stimulate its economic growth. Until the end of the 1970s, China’s doors were closed for foreigners, and the country was in grips of economic stagnation and pervading poverty. After the introduction of the “open-door policy” in the end of the 1970s, China has been experiencing a very rapid economic growth. There are some successful stories among the ASEAN countries. However, each country has its own different niche for international market. For example, Singapore could be placed at one end of the most successful case as its exports consist mostly of high-tech and capital-intensive manufactured goods. By contrast, Indonesia could be placed at another end since its exports are mainly primary commodities, such as petroleum, plywood, and rubber. Malaysia and Thailand could be considered as the ‘in-between’ they export both primary commodities and manufactured goods. Thailand’s exports include automobiles, electronic parts and rice while the main bulk of Malaysia’s exports are electronic components, petroleum, Liquefied Natural Gas (LNG) and palm oil. Sabah's external trade sector remained strong registering increasing trade surpluses since 2001. The State's trade surplus has risen from RM1.14 billion in 2001 to RM5.68 billion in 2003(External Trade Statistics Sabah, 2006). Such encouraging growth was mainly attributed by commodities exported by the State such as crude palm oil, rubber, sawn timber, plywood, wooden mouldings, crude petroleum, palm kernel oil, methanol, hot briquetted iron (HBI) and uncoated printing and writing paper. The State has intensively promoted the three priority productive sectors, namely agriculture, tourism and manufacturing sectors to sustain the economy growth. Figure 1 shows the relationship between the natural log of external export of Sabah and the natural log of Gross Domestic Product (GDP) in Sabah for the year of 1970-2005. There is a positive and upward relationship between external export and GDP over the years. However, external exports seemed more vulnerable to the world fluctuations compared to GDP and experienced major decline in 1975, 1981, 1983, 1986 and 2001.

2

Realising the importance of the relationship between external export and economy growth, this study aims to examine whether the hypothesis is applicable to Sabah by using econometric analyses.

Figure 1: External Export and GDP in Sabah, 1970-2005

11

10

9

8

7

6 1970

1975

1980

1985

1990

LEXPORT

1995

2000

2005

LGDP

The main objective of this research is to examine the “export-led growth” hypothesis for Sabah’s economy. The paper consists of five sections. Following this Introduction, Section 2 offers literature review on the relationship exports and economic growth. Section 3 discusses the research methodology adopted in this study, and Section 4 reports findings of the research. Section 5 concludes. 2. Literature Review For more than two centuries, the role of exports in the economic growth has been a topic of intense debate. Classical economists Adam Smith and David Ricardo emphasised the importance of international trade for a country’s economic growth. They argued that a country could benefit considerably if it specialised in a certain commodity or product and then exported it to the foreign countries that lacked this commodity (Smith, 1976; Ricardo, 1817). There are several criticisms on the simple version of classical international trade theory. Firstly, the theory does not incorporate a perspective on the consequences of the deteriorating terms of trade, which became a central trade issue between the developed and developing nations. Cypher and Dietz (1998, p.305) argued, “Especially for poor,

3

less-developed nations, we show that the generalised argument in favour of free trade policy derived from (classical) trade theory cannot be sustained once one takes the longterm historical trend of the terms of trade into consideration”. They developed a dynamic model to analyse the relationship between economic growth and terms of trades. Cyhper and Dietz concluded that the innovation in term of agricultural technology tends to lead the deterioration of terms of trade in developing countries. Furthermore, it could be considered as a difficult task to spot in advance a country’s comparative advantage. As a consequence, it became a difficult enterprise for developing countries to hammer out their own market niche in the global demand. According to Hausmann and Rodrick (2002), for developing nations, the economic development could become a process of “trial and error” process or “self discovery” by finding out their own strengths in the global competition. They concluded that in case of El Salvador the lack of “self-discovery” became a constraint for economic development. There have been numerous empirical researches to examine the relationship between exports and economic growth. Some studies lend empirical support to the “export-led growth” hypothesis (Michaely, 1977; Balassa, 1978; Feder, 1983; Ram, 1985). However, Love and Chandra (2005) argued that these studies are criticised because they employed cross-section data which are, methodologically, unable to establish causal relationship between the variables. On the other hand, other researchers make use of time-series methods and examined the Granger causal relationship between exports and economic growth. However, those empirical studies provided weak empirical evidence to support the “export-led growth” hypothesis. (Jung et al. 1985; Dodaro, 1993). Some researches used co-integration method and error correction model to analyze the “export-led growth” hypothesis. For example, Bahmani-Oskooee and Alse (1993) used quarterly data for nine countries, including four ASEAN nations, for the 1973-1988 period and established that there had been a long-run relationship between exports and economic growth. Ahmad and Harnhirun (1996) tested the hypothesis for five ASEAN countries (i.e., Malaysia, Indonesia, Singapore, Thailand, and the Philippines) for the 1966-1986 period; they found that there was no co-integrating relationship between exports and economic growth. Ahmad and Harnhirun’s empirical findings indicated that economic growth was causing the expansion of exports, and not vice versa. 3. Research Methodology Econometric models will be built to analyze the impact of international trade on Sabah’s economic growth. This study uses time-series data sets for the period 1970-2005.4 The model assumes that Sabah’s economic performance is determined by the amount of external export.

4

The main source of data is various issues of the Yearbook of Statistics, Sabah, and External Trade Statistics published by the Department of Statistics, Sabah.

4

To incorporate this determinant into an econometric model, the function of Sabah’s Gross Domestic Product (GDP) could be expressed as:

GDPt = f (EXt)

(1)

where GDPt is Sabah’s Gross Domestic Product in year t; EXt, is the amount of Sabah’s external export in year t. Several econometric tests are run to analyze the regression model. Firstly, the unit root test is used to examine whether the time series data is stationary.5 Standard stationarity test, i.e. the augmented Dickey-Fuller (ADF) unit root test (Dickey and Fuller, 1979, 1981), is used. The ADF test is based on the following regression,

∆yt = µ + βtt-1 +δyt-1+ εt

(2)

where t is linear time trend, β and δ are coefficients, and εt is an error term. Secondly, co-integration test is done to examine the long-run movement of the variables.6 The co-integration test is employed to analyse whether pairs of variables are co-integrated or move jointly. 7 An important prerequisite for the existence of a cointegrating relationship between variables is that the variables have same order of integration. This means that if a variable is an integrated of order d, the other variables should also be an integrated of order d.8 A standard test – Johansen co-integration test - is used to check the long-run movement of variables (Johansen, 1988, 1991). The lag length n in the error correction model was chosen by using the Akaike information criterion (AIC).9 The test is based on maximum likelihood estimation of the K-dimensional Vector Autoregression (VAR) of order p,

∆Zt= µ + Г1 ∆Zt-1+ Г2 ∆Zt-2+…Гk+1 ∆Zt-p+1+πZt-k + εt where Zt is a k × 1 vector of stochastic variables, µ is a k × 1 vector of constants, εt is a k × 1 vector of error terms, π and Г1…. Гk+1 are k × k matrices of parameters. According to Engle and Granger (1987), if variables are co-integrated, the relationship between them can be expressed in the Error Correction Model (ECM). An error 5

The time series data is stationary if its mean, variance and covariance remain constant over time (Thomas, 1997, p.374). 6 In economics, the difference between short run and long run is not distinguished by a specific period of time. Normally, in short run period it is not possible to change all inputs to production, and only some inputs to production could be changed. Long run refers to a period of time when all inputs to production could be changed (Taylor, 2001). 7 According to the definition, the pairs of variables could be described as co-integrated if they have a longrun equilibrium relationship which means that these variables move jointly (Gujarati, 2003, p.822). 8 In general, if a time series data has to be differenced d times to make it stationary, that time series data is said to be integrated of order d (Gujarati, 2003, p.805). 9 Appropriate lag length should ensure that the error term from the regression equation is white noise. Sewa (1979) argues that employing the AIC method results in an over-fitted model. However, the bias is negligible when the selected lag length is less than (N/10) where N is equal to the number of observations.

5

correction model will be estimated to analyze the short-run relationship between these two variables. Hence, the following error correction model is estimated: n

∆GDPt = b1+

n

∑ b2i ∆EXt − i + i =0

∑b

4i

∆GDPt − i + b5ut-1 + εt

(5)

i =1

The lag length n that minimizes the AIC is used for the analysis. To decide on the final form of the ECM, this study initially started with one-year lagged differences of each variable and then deleted the insignificant lagged variables.10 Finally, this study uses Granger-causality test to analyse the causality between exports and economic growth. Gujarati (1995) distinguishes three types of causality: (1) unidirectional causality from independent variable to dependent variable, but not vice versa, (2) unidirectional causality from dependent variable to independent variable, but not vice versa, and (3) bilateral causality, which is causality from independent variable to dependent variable and vice versa. The lag length n that minimizes the AIC is used for the analysis. 4. Empirical Results The ADF unit root test is run to test stationarity of time series data sets. The results from the ADF test are reported in Table 1. Table 1: ADF Unit Root Test

GDP EX

Constant without trend 2.985 (0) 1.713(0)

Level Constant with trend 1.953(5) -1.839(1)

First Difference Constant without Constant with trend trend -4.191 (0)** -4.944(0)** -3.794 (2)** -4.627(2)**

Notes: Figures in parentheses indicate number of lag structures ** indicates significance at 1% level, * indicates significance at 5% level Despite minor differences in the findings as reported in the tables, the obtained results indicate that two variables – GDP and EX -- are integrated of order one, I(1). Further, the Johansen co-integration test is done to test the long-run movement of the variables. In the present study, two variables – GDP and EX – could be examined for cointegration because all these variables have the same order of integration. Results of the co-integration test are presented in Table 2.

10

A variable should not be deleted if the deletion would cause autocorrelation in the error term of the regression model. Also, the F-test is used to determine whether unrestricted or restricted model is a better choice.

6

Table 2: Johansen Co-Integration Test Eigenvalue

Likelihood Ratio

5 percent critical value

10 percent critical value

0.254 0.081

12.900 2.902

15.41 3.76

20.04 6.65

Number of co-integrating equations None At most 1

Notes: The result corresponds to VAR’s with one lag, as this is the number that minimizes AIC The findings indicate that there exists no co-integrating relationship between two variables (GDP and EX). In other words, the variables are not stationary in levels, in the long run, they do not closely move with each other. As the Johansen test indicates, there is no cointegrating relationship between exports and economic growth in Sabah. This paper could not employ the error correction methods in order to analyze the short-run relationship between Sabah’s economic performance and international trade. Finally, the Granger-causality method is employed to examine casual relationships between government expenditure and the amount of gross domestic product in Sabah. The result of the F test and t-tests are reported in Table 3.

Table 3: Granger-Causality Test Variable F-statistics Export→GDP 0.039

P-value 0.849

Notes: The result corresponds to Granger-causality test with one lag, as this is the number that minimizes AIC According to the results of the F-test, there exists no bilateral Granger causality between exports and GDP in Sabah. This means that an increase in the Sabah’s export could not cause an increase in gross domestic product. These results apparently confirm the nonexistence of long-run relationships between GDP and Exports in the state As a conclusion, empirical findings of the present research imply that there is no equilibrium or co-integrating relationship between Sabah’s GDP and exports. Also, no causal relationship between two variables has been detected. This means that exports have no significant impact on economic growth in the state. 5. Conclusion This paper empirically analyzed the relationship between Sabah’s economic performance and exports. The empirical findings offer some interesting insights. First of all, as the Johansen co-integration test indicates, there exists no co-integrating relationship

7

between Sabah’s economic growth and exports. It means that Sabah’s GDP and its international trade have no equilibrium relationship in the long run. Secondly, Granger causality test confirm the non-existence of the long-run relationship between Sabah’s GDP and its export (EX), no causality between two variables has been detected between these variables. This indicates the lack of statistically significant causal relationship between Sabah’s economic growth and exports. To conclude, the importance of international trade for ensuring a dynamic economic growth of Sabah has been not confirmed in this paper. A policy recommendation could be drew from this research is that Sabah, like El Salvador, seems to struggle for “selfdiscovery” in order to find out market niche in the international economy. The government to provide further financial intensives to support export-related industries in the states. Finally, there is an ample room left for further studies on this important topic. For example, incorporating other variables and investigating their impact on the economic performance of Sabah in the future studies could help to identify additional determinants of Sabah’s economic performance. These future researches could offer a detailed picture of the state’s multifaceted economic activities.

8

References Cypher, James M. and James L. Dietz (1998). “Static and Dynamic Comparative Advantage: A Multi-Period Analysis with Declining Term of Trade?”, Journal of Economic Issues, Vol.32, No.2, (June), pp.305-314. Department of Statistics. Yearbook of Statistics, Sabah. Kota Kinabalu: Department of Statistics, Sabah Branch, various issues. Department of Statistics. External Trade Statistics, Kota Kinabalu: Department of Statistics, Sabah Branch, various issues. Dickey, D. and W. Fuller (1979). “Distribution of the Estimators for Autoregressive Time Series with a Unit Root”, Journal of the American Statistical Association, Vol. 74, No.366, pp. 427-431. Dickey, D. and W. Fuller (1981). “Likelihood Ratio Tests for Autoregressive Time Series with a Unit Root”, Econometrica, Vol.49, No. 4, pp.057-1072. Engle R. and C. Granger (1987). “Co-integration and Error Correction: Representation, Estimation and Testing”, Econometrica, Vol.55, No. 2, pp.251-276. Gujarati, Damodar N. (2003). Basic Econometrics, 4th edition. Singapore: McGraw-Hill. Hausmann, Ricardo and Dani Rodrick (2002). “Economic Development as SelfDiscovery”, NBER Working Paper 8952, Cambridge, MA, National Bureau of Economic Research. Johansen, S. (1988). “ Statistical Analysis of Cointegration Vector”, Journal of Economic Dynamics and Control, 12(2/3), pp.231-254. Johansen, S. (1991). “Estimation and Hypothesis Testing of Cointegrated Vectors in Gaussian VAR Models”, Econometrica, 59(6), pp.1551-1580. Okposin, S.B., A.H.A. Hamid and H.B. Ong (1999). The Changing Phases of Malaysian Economy. London: ASEAN Academic Press. Phillips P. and P. Perron (1988). “Testing for a Unit Root in Time Series Regression”, Biometrica, Vol. 75, No. 3, pp.335-346.

9

Prebisch, Raul (1950). The Economic Development of Latin America and Its Principal Problems”, New York: United Nations. Ricardo, David (1817). The Principles of Political Economy and Taxation, reprint, London: J.M. Dent and Sons, 1948. Sachs, Jeffrey and Andrew Warner (1995). “Economic Reform and the Process of Global Integration”, Brookings Papers on Economic Activities, No.1. Sewa, T. (1978). “Information Criteria for Discriminating Among Alternative Regression Models”, Econometrica, Vol.46, No. 6, pp.1273-1291. Singer, Hans W. (1950). “The Distribution of Gains Between Borrowing and Investing Countries”, American Economic Review, Vol.50, (May), pp.473-485. Smith, Adam (1776). An Inquiry into the Nature and Causes of the Wealth of Nations, reprint, London: J.M. Dent and Sons, 1977. Taylor, John B. (2001). Economics, 3rd edition. Boston: Houghton Mifflin, Thomas, Leighton R. (1997). Modern Econometrics. Essex: Addison Wesley Longman. Todaro, Michael P. (2000). Economic Development, Essex: Pearson Education Limited. Untied Nations Development Program (1995). Human Development Report, New York, United Nations. World Bank (1987). World Development Report 1987, Washington, D.C., World Bank.

10