Services sector growth in Singapore.

Anwar, Sajid ; Sam, Choon Yin

Abstract

While a number of studies have examined the performance of the Singaporean manufacturing sector, none of the available studies has explicitly considered the Singaporean services sector. This paper empirically examines the main determinants of the Singaporean services sector value-added. It uses panel data which covers four major services industries from 1984 to 2004. Empirical analysis suggests that services sector employment, human capital, and the growth rate of GDP have a significant positive effect on the services sector value-added and unobserved fixed effects are present across the selected industries. The paper also considers panel cointegration. It is shown that manufacturing sector value-added, employment, and human capital are cointegrated. The estimated vector error correction model suggests that adjustment to the long-run equilibrium is fairly slow.

Key Words: Singapore, Services sector growth, Human capital

Introduction

Since separating from Malaysia in 1965, Singapore has experienced accelerated economic growth. In the early years, economic growth relied heavily on manufacturing sector growth. Because of its location, heavy investment in infrastructure, tax incentives, and strict government control that led to political stability, Singapore became an attractive destination for foreign investment. The Economic Development Board (EDB), established in 1961, focused on the promotion of foreign investments while it passed on roles like industrial financing and industrial estates development to other agencies. While the services sector continued to grow in absolute terms, the manufacturing sector grew at a more rapid pace. More attention was devoted to the export oriented manufacturing sector during the early years because of the need to create additional employment opportunities.

The services industries, like the banking services, created value added but contributed little to jobs growth (Lee, 1990). But this does not mean that the services sector was left entirely on its own. State-led plans and directions were visible even in the 1960s through to the early 1980s in the expansion of the financial (Khalid and Tyabi, 2002; Ariff and Khalid, 2005) as well as the tourism sectors (Wong, 1997; Khan, 1998). The visible government role in economic development allowed researchers to label Singapore as a state-led economy (Tan, 2005) and a developmental-state (Low, 2004). In fact, the role of government in the economic development of Singapore has been widely acknowledged and discussed (for example, see Huff, 1995; 1999; and Amsden, 2001).

Table 1 shows that the share of the services and manufacturing sectors as a percentage of GDP. The share of the services sector has been well above 60 per cent in recent years. The services sector has played an important role in cushioning the negative external impacts on Singapore like the oil price shock in the 1970s (Wong, 1982) and more recently, the global economic downturn in the aftermath of the 11 September 2001 attacks in the United States. In 2001, for example, the manufacturing industry experienced a negative growth of 11.6 per cent, due mainly to the economic downturn in the USA. The services sector, on the other hand, registered a positive growth of 2.4 per cent in the same period. The overall risk of external shocks, a particular concern to small open economies like Singapore, has to be contained and diversified. Broadly speaking, the strategy adopted by Singapore involves treating the manufacturing and services sectors as twin engines of economic growth (MTI, 1986, p 142).

Given the openness of the Singapore economy, the external shocks such as the Asian financial crisis of 1997-98 and the outbreak of Severe Acute Respiratory Syndrome (SARS) in 2003 had a significant effect on the services sector. During the Asian crisis for instance, the number of tourist arrivals fell 13.3 per cent in 1998 as compared to 1997 while the occupancy rate in gazetted hotels fell to 71.3 per cent in 1998 as compared to 82.3 and 79.4 per cent in 1996 and 1997 respectively. The services sector as a whole contracted marginally by 0.6 per cent, cushioned mainly by the positive growth registered in the transport and communications (6.4 per cent) and business services sectors (2.3 per cent).

There has been a significant increase in R&D in Singapore since the early 1990s. Spending on R&D increased from S$3 billion in 2000 to S$4.1 billion in 2004 (Department of Statistics, 2007). Increased spending on R&D has contributed to increase in human capital in Singapore which has implications for the services sector. Despite the importance of the services sector in the Singaporean economy, most existing studies have focused exclusively on the manufacturing sector. This paper attempts to fill this gap. It utilises panel data to empirically examine the determinants of Singapore' s services sector output. The use of panel data allows one to control for some omitted variables without actually observing them. (2) The paper considers four major manufacturing industries over the period 1984-2004. Empirical analysis shows that services sector employment, human capital and the growth rates of real GDP have significant positive impact on the real value-added of the services industries. In addition, significant fixed effects are present across the selected industries. By making use of Johansen-Fisher panel cointegration technique, it is shown that the services sector employment, human capital and the services industry value-added are cointegrated.

The rest of this paper is organised as follows. The next section contains a discussion of the role of the services sector and empirical investigation of the sources of output growth for the period 1984-2004. The last section contains concluding remarks.

Singaporean Services Sector

Within the services sector, new types of services began to replace the entrepot trade as reflected in the decline in the commerce sector share of the services value-added from 35.3 per cent in 1960 to 27.1 per cent in 1980 and 24.2 per cent in 2000. The transport and communications industry and financial and business services industry grew most rapidly. The transport and communications industry accounted for 12.5 per cent of services output in 1960, 17.2 per cent and 20.4 per cent in 1980 and 2000, respectively. Increased activities of the Port of Singapore Authority (PSA), Singapore Airlines Ltd (SIA), Neptune Orient Lines (NOL) and later Singapore Telecommunications (SingTel) helped to stimulate growth in the services sector. Financial and business services grew from 22.3 per cent of the services output in 1960 to 37.3 per cent in 1980, and 38.9 per cent in 2000. The establishment of the Asian Dollar Market in 1968, abolishment of the cartel system of interest rate setting in 1975 and lifting of exchange rate controls in 1978, and subsequently the growth of Singapore as an international financial centre were some of the factors that contributed to services sector growth (Lee, 1990; Khalid and Tyabi, 2002; Ariff and Khalid, 2005). Development of the financial sector fits Singapore's comparative advantage given its political stability, confidence in the Monetary Authority of Singapore, and the relatively skilled and technology-savvy working population. The financial and transport and communications sectors serve as a useful complement to Singapore's plan to expand the manufacturing and services hub (see Dee and Sidorenko, 2006).

In 1957, the financial and business services sector accounted for merely 6.6 per cent of total employment in the services sector. In 1980, the figure rose to 12.1 per cent and further increased to 17.5 per cent in 1990. This reflects Singapore's strategic policy to become an international financial and technical service centre. The financial and business services sector accounts for more than one-fifth of the total employment in the services sector. The commerce (wholesale, retail trade, hotels and restaurants) sector, which is relatively more labour intensive, accounts for almost one-third of the total employment.

It can be argued that the extent of the services sector growth in a country is closely linked with its overall economic performance. This follows from the fact that increased economic prosperity contributes to increased demand for services. (3) In the case of Singapore, at least prior to the 1985-86 recession, the services sector was 'merely the unforeseen effect of growth in other areas' (Lee, 1990, p 287). Being an open economy, the services sector might have been neglected by the government since it mostly involves non-traded goods at least prior to the establishment of the General Agreement on Trade in Services (GATS) in December 1993 under the Uruguay Round. The other reason could be that the basic philosophy of the Singapore government is based on pragmatism, such that the government will intervene only as and when necessary to correct market failures (Schein, 1996). This may explain why the services sector did not receive much attention from the government before 1985. (4)

The lack of political support for the services sector (as noted by Lee, 1990) could be attributed to the lack of generous incentives given to the firms operating in the services sector as compared to the manufacturing sector. The Services Subcommittee Report, released in 1984 by the Singapore Department of Statistics pointed out: "... services are taken for granted ... little effort has gone into promoting them.... Business services and warehousing and distribution have suffered most. Not only have most fiscal incentives been denied to them but certain government regulations are actually biased against them, for example, higher land rentals for warehousing than for manufacturing" (quoted in Lee, 1990). The Economic Committee Report convened in April 1985--to examine the longer term problems and prospects of the Singapore economy in the midst of the 1985-86 recession--rectified this and suggested the promotion of the services sector as actively as the manufacturing sector (MTI, 1986). Labelling the manufacturing and services sector as the twin engines of growth, fiscal incentives were provided for the services along with other measures like deregulation, privatisation, and admission of foreign professionals into Singapore. Foreign investments were attracted primarily in services and manufacturing, not only because of these measures but also to take advantage of the relatively inexpensive skilled labour (particularly after the reduction in the Central Provident Fund rates as part of the government measures to revive the economy) and political stability in Singapore. The Singaporean economy quickly recovered from the recession of 1985-86. The services sector grew by an average of 9.6 per cent in 1986-96 until the onset of the Asian financial crisis. (5)

The growth of the services sector since 1986 can be attributed to the Services Promotion Division (SPD) that was set up by the EDB in May 1986. The primary aim of SPD was to promote 18 tradable service industries. Firms investing in Singapore were encouraged 'to do more than just production' but 'manufacturing-related services' such as purchasing and testing but subsequently expanded into stand-alone service activities like distribution and logistics management. (6) However, the first year of the SPD passed without visible results. The turning point came when Sony decided to establish its operational headquarters in Singapore, which was soon followed by Sharp, Sanyo, Fujitsu and others. (7) Interestingly, the OHQ awards were so successful that firms (mainly from Japan) thought that Singapore was favouring services over manufacturing. This could be linked to the Baumol disease. Baumol (1967) postulates that traditional services like hairdressing and restaurants do not improve their technology as fast as manufacturing does. Hence, a shift from manufacturing activities to services may yield possibly a one-time benefit of raising the profit margin but not year after year improvements, an outcome that Singapore would want to avoid. (8)

When the services sector suffered from the economic downturn during the Asian financial crisis, albeit marginally, the government released the Committee on Singapore's Competitiveness (CSC) report, noting that 'the strategy of manufacturing and services as twin engines, aimed at diversifying our sectoral and market dependency, reducing vulnerability, and promoting a broad base for the economy, is a proven one' (MTI, 1998, p 50). The CSC was not originally established to address the economic slowdown caused by the crisis. It was aimed at long-term development of the Singaporean economy but had its terms of reference extended to consider short-term measures. Convinced that manufacturing and services are 'mutually supporting', the CSC's 'vision for the services sector is to build Singapore into the 'premier services hub in Asia with a global connection' (ibid, p 53). The CSC identified 12 services comprising education, health care, information technology, engineering, transport and logistics, exhibition management, marketing, international trading, financial, tourism, leisure and entertainment, lifestyle retail management, and communications and media. High value-added and exportable services were promoted as a reaction to Singapore's physical smallness and small domestic market. However, the services sector in Singapore still trails behind the developed countries in productivity and capability (MTI, 2002, p 154). It is interesting to note that as compared to countries such as Taiwan, South Korea, Finland, Sweden, France, and the USA, Singapore has not done enough to boost its innovative capabilities measured in terms of R&D expenditures expressed as a percentage of GDP.

The rest of this section attempts to empirically examine the main determinants of Singapore's services sector output. The services sector relies heavily on the availability of labour. A number of studies including Lucas (1988) and Romer (1990) have highlighted the importance of human capital in the process of economic growth. Human capital is an important determinant of the services sector output. GDP growth also contributes to higher demand for services and hence it has implications for the services sector output. This paper focuses on the performance of four major services industries for the period 1984-2004. These industries account for more than 90 per cent of the services sector output. The industries considered in this paper are (a) Transport, Storage & Communications; (b) Financial & Insurance Related Services; (c) Real Estate & Business Services; and (d) Community, Social & Personal Services.

Equation (1) is used to empirically examine the impact of employment and human capital on Singapore's services industries. (9)

Log [(VA).sub.it] = [lambda] + [beta]Log [(L).sub.it] + [phi] Log[(HC).sub.t]t + [gamma][[??].sub.t] + [alpha][Z.sub.t] + [[zeta].sub.it], (1)

Where t = 1984, 1985 ... 2004; i = 1,2,3,4 ; [(VA).sub.it], is the real value-added in industry i and period t; ([L.sub.it]) is labour employed in industry i and period t; H[C.sub.t] is human capital in period t; l? is the growth rate of the real GDP in period t, [Z.sub.it] represents the unobserved factors that effect the output of industry i; and [[zeta].sub.it], is the random variable.

All slope coefficients are expected to be positive. The unobserved factors that affect the services output include management techniques that vary across industries. In other words, the population regression equation attempts to capture industry specific fixed effects that do not vary over time. The random variable represents idiosyncratic errors (see Wooldridge, 2002; Stock and Watson, 2007). The above specification takes into account the fact that human capital in a country results in spillover effects for all industries.

It is well-known that in general, capital is an important determinant of value-added. However, Singapore almost exclusively relies on foreign capital which is concentrated mainly in its manufacturing sector. Given that the growth rate of GDP is affected by both domestic and foreign capital, the inclusion of the growth rate of GDP as an independent variable indirectly captures the effect of variations in the supply of capital on services sector value-added.

It has been suggested that the number of scientists and researchers is a better indicator of human capital in a country. However, in the case of Singapore, such information is available only from 1989 onwards and hence real government spending on education is used as an indicator of human capital in Singapore. All data are annual, collected from various issues of the Year Book of Statistics published by Singapore Department of Statistics (Department of Statistics, 2007). Empirical analysis is conducted by making use of the econometric software EViews version 6.

Panel Generalised Least Squares with cross-section weights was used to estimate equation (1). The results are summarised in Table 2. This method iterates coefficients after one-step weighting matrix. Convergence was achieved after 22 coefficient iterations. Degrees of freedom corrected cross-section standard errors and covariances were calculated by making use of Halbert White' s approach. A good discussion of these and related techniques can be found in Wooldridge (2002), Hsiao (2003), and Cameron and Trivedi (2005).

Values in parenthesis underneath the estimated coefficients in Table 1 are the corresponding p-values. The above equation shows that an increase in employment and human capital contributes to increase in the real value added of the services sector. The impact of both independent variables on the dependent variable is highly significant. The sum of the estimated slope coefficients is less than one which suggests that the services industry is largely characterised by decreasing returns to scale. The explanatory power of the model is also high. The estimated p-value corresponding to the cross-section F-statistic which is based on the Likelihood Ratio test shows that unobserved fixed effects across industries are highly significant. (10) Based on the estimated equation it can be claimed that both employment and human capital have made a significant contribution to the services sector growth in Singapore. Based on the estimated [[bar.R].sup.2] , it appears that the model that includes the growth rate of GDP as an independent variable provides a marginally better fit. A similar conclusion can also be drawn if one uses information criterions such as AIC and SC.

While the sample size is not very large, it is possible to test for panel-cointegration. Testing for cointegration makes sense only if the variables in question are non-stationary. Results of a unit root test based on the approach of Levin, Lin and Chu are summarised in Table 3. The Levin, Lin and Chu test assumes a common unit root process.

Table 3 shows that the hypothesis of a common unit root cannot be rejected for the services sector because the estimated p-value is quite large. The estimated p-values for the real value-added and human capital are not so large. However, estimated p-values corresponding to the first differences of all variables are zero in four digits. Hence, one can claim with very high level of confidence that the first differences of all variables are non-stationary. Since all variables are assumed to be integrated of order 1, it is possible to test for cointegration. Cointegration is a test of a long-run relationship among all variables. The results of a panel contegration test based on Johansen-Fisher approach are summarised in Table 4. Trace and maximum Eigen-value based tests indicate the presence of a cointegration relationship. The growth rate of GDP is essentially a shift variable and hence was not included in cointegration analysis. In any case, the growth rate of GDP series is integrated of order zero with probability value that is very close to unity.

In Table 4, values in parenthesis underneath the estimated coefficients are MacKinnon-Haug-Michelis p-values. This result is based on two lags. Once the existence of cointegration has been established, it makes sense to estimate the corresponding Vector Error Correction Model (VECM). VECM model corresponding to equation (1) is as follows:

[DELTA]Log[(VA).sub.t] = [[phi].sub.0] + [[phi].sub.1][(EC).sub.t-1] + [summation over i=1][[phi].sub.21][DELTA]Log([L.sub.t-i]) + [summation over i=1][[phi].sub.22][DELTA]Log[(HC).sub.t-i] + [[upsilon].sub.t] (2)

Where [(EC).sub.t-1] is the lagged value of the corresponding error correction term; [phi]'s are the population regression coefficients and [v.sub.t] is a random variable.

It is well-known that the estimated coefficient of the error correction term is expected to be negative but less than unity. EViews version 6 was used to estimate the above log-linear model. A summary of the estimated Vector Error Correction Models is shown in Table 4.

Values in parenthesis underneath the estimated coefficients are t-values. Table 5 shows that increase in employment has a significant positive effect on value-added in the services sector. In addition, an increase in human capital also increases the real value-added. The estimated error correction terms indicate that the real value-added adjusts to its long-run value at a fairly slow rate (approximately 3.15 to 5.56 per cent per year). The results presented in Table 5 support the view that there is a long-run relationship among the services sector employment, real value-added and human capital. (11)

It is perhaps worth mentioning that Young (1992, 1994, 1995) has highlighted the lack of technological progress-based growth in Singapore. Because of increased competition from China and India, Singapore needs to further develop and increase its human capital. Increased availability of human capital through increased spending on advanced education and training will also help Singapore to continue to attract foreign investment which is vital for its manufacturing sector. While increased spending on R&D in recent years has generated some rewards (Toh and Ng, 2002), more needs to be done to increase the contribution of technological progress in overall economic growth. (12)

Conclusion

This paper examines the performance of Singapore's services sector. As compared to the manufacturing sector, the services sector can be viewed as relatively labour intensive where the associated employment effect is quite small. The manufacturing and the services sectors are regarded as twin engines of the Singaporean economic growth. However, the existing literature has largely ignored the services sector. By making use of panel data for the period 1984-2004, this paper considers the main determinants of the real value-added of the services sector. Panel data approach allows one to consider the effect of the unobserved factors. The services industries considered are (a) Transport, Storage and Communications; (b) Financial and Insurance Related Services; (c) Real Estate and Business Services; and (d) Community, Social and Personal Services. It is shown that the services sector employment, human capital and GDP growth have a significant positive effect on the real value-added of the services industries. In addition, significant fixed effects are present across the selected industries. The estimated equation suggests the presence of decreasing returns to scale in the services sector. The paper also considers panel-cointegration. Empirical estimation based on Johansen and Fisher approach shows that the real value-added in the services sector, employment and human capital are cointegrated. The estimated vector error correction models reveal that adjustment to the long-run equilibrium is fairly slow.

References

Amsden AH, 2001. The Rise of the Rest: Challenges to the West from Late-industrializing Economies. New York: Oxford University Press.

Ariff M and AM Khalid, 2005. Liberalization and Growth in Asia: 21st Century Challenges, Edward Elgar: Cheltenham.

Baumol W, 1967. "Macroeconomics of Unbalanced Growth: The Anatomy of Urban Crisis", American Economic Review, Vol 57 No 3, pp 415-426.

Cameron AC and PK Trivedi, 2005. Microeconometrics: Methods and Applications, New York: Cambridge University Press.

Chan CB, 2002. Heart Work, Singapore Economic Development Board and EDB Society, Singapore.

Dee P and A Sidorenko, 2006. "The Rise of Services Trade: Regional Initiatives and Challenges for the WTO", in H Soesastro and C Findlay (eds) Reshaping the Asia Pacific Economic Order, Routledge: Oxford.

Department of Statistics, 2007. Yearbook of Statistics 2006, Singapore: Department of Statistics.

--, 2007. http://www.singstat.gov.sg/, accessed on 10 Feb 2007.

Gujarati D 2006. Essentials of Econometrics, 3e, New York: McGraw-Hill/Irwin.

Huff WG, 1995. "The Developmental State, Government, and Singapore's Economic Development since 1960", World Development, Vol 23 No 8, pp 1421-1438.

Huff WG, 1999. "Turning the Corner in Singapore's Developmental State?", Asian Survey, Vol XXXIX No 2, March/April, pp 214-242.

Hsiao C, 2003. Analysis of Panel Data. New York: Cambridge University Press.

Khalid AM and A Tyabi, 2002. "Financial Sector Developments: Strategies and Challenges", in Koh, AT, Lira, KL, Hui, WT, B Rao and Chng, MK (eds) Singapore Economy in the 21st Century: Issues and Strategies, McGraw-Hill: Singapore.

Khan H, 1998. "The Tourism Explosion: Policy Decisions Facing Singapore", in D Tyler, Y Guerrier and M Robertson (eds) Managing Tourism in Cities, John Wiley: New York.

Koh WTH, 2006. "Singapore's Economic Growth Experience" in Winston TH Koh and RS Mariano (eds) The Economic Prospects of Singapore, Pearson: Singapore.

Koh TH and PH Wong, 2005. "Competing at the Frontier: The Changing Role of Technology Policy in Singapore's Economic Strategy". Managing Emerging Technologies in Asia, Vol 72 No 3, March, pp 255-285.

Lee SA, 1990. "Expansion of the Services Sector", in KS Sandhu and P Wheatley (eds) Management of Success: The Moulding of Modern Singapore, Institute of Southeast Asian Studies, Singapore.

Leung HM, 2006. "Industrial Policy and Economic Development: Comparing Singapore with Hong Kong, Korea and Taiwan", in Winston TH Koh and RS Mariano (eds) The Economic Prospects of Singapore, Pearson: Singapore.

Low L, 2004. "Singapore's Developmental State between a Rock and a Hard Place", in Low, L (ed) Development States: Relevancy, Redundancy or Reconfiguration?, Nova Science Publishers: New York.

Lucas R, 1988. "On the Mechanics of Economic Development", Journal of Monetary Economics, Vol 22, July, pp 3-42.

Ministry of Trade and Industry (MTI), 1986. The Singapore Economy: New Directions, MTI, Singapore.

--, 1998. Committee of Singapore's Competitiveness, MTI, Singapore.

--, 2002. The Pursuit of Competitive Advantage: Value Manufacturing in Singapore, MTI, Singapore.

Romer P, 1990. "Endogenous Technological Change", Journal of Political Economy, Vol 98, pp 71-102.

Schein EH, 1996. Strategic Pragmatism: The Culture of Singapore's Economic Development Board, MIT Press: Cambridge.

Stock J and MW Watson, 2007. Introduction to Econometrics, 2e, Addison Wesley: Boston.

Tan L, 2005. The Paradox of Catching-Up: Rethinking State-Led Economic Development, Palgrave MacMillan: New York.

Writz J, 1999. Growth of the Services Sector in Asia, Research Paper Series, Faculty of Business and Administration, NUS, RPS99-089 (November).

Young A, 1992. "A Tale of Two Cities: Factor Accumulation and Technical Change in Hong Kong and Singapore", NBER Macroeconomics Annual 7, pp 13-54.

--, 1994. "Lessons from the East Asian NICs: A Contrarian View", European Economic Review Vol 38, pp 964-973.

--, 1995. "The Tyranny of Numbers: Confronting the Statistical Realities of the East Asian Growth Experience", Quarterly Journal of Economics, Vol 110, pp 641-680.

Verbeek M, 2004. A Guide to Modern Econometrics, 2e, John Wiley: Cornwall.

Wong KP, 1982. Essays on the Singapore Economy, Federal Publications and Nanyang Siang Pau, Singapore.

--, 1997. "Singapore: Tourism Development of an Island City-State", in DG Lockhart and D Drakakis Smith (eds) Island Tourism: Trends and Prospects, New York.

Wooldridge JM, 2002. Econometric Analysis of Cross-Section and Panel Data, MIT Press: Boston.

Sajid Anwar*

University of South Australia

Choon Yin Sam

TMC International Holdings Ltd, Singapore

* The author is indebted to John Rice and Sam Wells for valuable comments.

End Notes

(1) The economy relied primarily on multinational corporations (MNCs) and state-owned enterprises to spearhead economic development (Low, 2004).

(2) See Gujarati (2006), Stock and Watson (2007) and Verbeek (2004).

(3) Writz (1999) argues that growth of the services sector in Asia has been attributed to (1) restructuring of the economies towards higher levels of specialisation fuelled by outsourcing of non-core activities, (2) reduction in the transaction costs due to advancement of information technology and (3) opening up of many restricted sectors in many Asian countries.

(4) Conversely, when slower and negative growths of tourist arrivals were observed in 1982 and 1983, respectively, the government reacted. The Singapore Tourist Promotion Board (STPB) was reorganised and expanded in 1984 and two years later, the STPB released the Tourism Product Development Plan to increase the number of tourist arrivals, length of stay and tourist expenditure (Wong, 1997 and Khan, 1998).

(5) For a recent discussion of the Singaporean economic polices see Koh (2006) and Leung (2006).

(6) Chan, Wing Leong, Services and Total Business in Chan (2002, p 215).

(7) Tan, Chek Ming, Services: A Road Less Travelled, in Chan (2002, p 260)

(8) In a recent government report, the Economic Review Committee Report confirms the relevance of the manufacturing sector in Singapore, saying that 'manufacturing has long been one of the prime engines of progress in Singapore, and it is essential that it remains vibrant, sustainable and substantial component of the Republic's economy for years to come' (MTI, 2002, p 7).

(9) The production function behind equation (1) is [VA.sub.it] = [e.sup.[lambda]+[gamma][??]t + [alpha]Zi + [zeta]it] [L.sup.[beta].sub.it] [HC.sup.[phi].sub.t].

(10) A linear functional form of equation (1) was also estimated but the results were very poor.

(11) AIC values suggest that model with 1-3 lags is the best whereas SC values support model 1 with 1 lag. In overall terms, all three VECMs provide the same information.

(12) Koh and Wong (2005) have examined the role of science and technology in Singapore's transition to an innovation-based growth strategy.

Table 1: Share of the Services Sector as a Percentage of GDP

Year Services Manufacturing Others

1960 79.0 11.9 9.1
1965 64.6 15.3 20.1
1970 66.9 20.5 12.6
1975 70.6 21.4 8.0
1980 72.0 23.8 4.2
1985 69.6 23.6 6.8
1990 66.3 27.1 6.6
1995 67.6 25.7 6.8
2000 62.0 25.1 13.0
2001 64.7 22.6 12.7
2002 64.6 23.6 11.8
2003 64.6 23.9 11.5
2004 64.0 25.2 10.8
2005 63.4 26.4 10.2
2006 63.2 27.6 9.2

Source: Department of Statistics (2007)

Table 2: Estimated Panel Regression Equation (1984-2004)

 Estimated Equation after Correcting for AR(1) Errors

Dependent Constant Log (L) Log (HC) [??]
Variable

Log (VA) 0.91872 0.7701 0.0339 0.0021
 (0.0000) (0.0013) (0.0452)

 Estimated Equation without Y

Log (VA) 0.4809 0.8046 0.0308
 (0.0000) (0.0200)

Dependent [bar.R].sup.2] F- Cross-section
Variable statistic F-statistic

Log (VA) 0.9910 2175.37 3.1986
 (0.0000) (0.0284)

Log (VA) 0.9906 2789.97 3.9001
 (0.0000) (0.0224)

Table 3: Panel Unit Root Test

 Levin, Lin & Chu t-value Estimated p-values

Log(VA) -2.27345 0.0115
Log(L) -1.18133 0.1187
Log(HC) -2.45674 0.0070

[DELTA]Log(VA) -4.77743 0.0000
[DELTA]Log(L) -4.77743 0.0000
[DELTA]Log(HC) -11.5512 0.0000

Table 4: Johansen-Fisher Panel Cointegration Test

Hypothesised Fisher's Fisher's Trace
Number of Maximum Statistic
Cointegrating Eigenvalue
Equations Statistic

 1 Lag

 25.48 35.40
None * (0.0013) (0.0000)

 18.06 18.72
At most 1 (0.0208) (0.0164)

 9.17 9.17
At most 2 (0.3281) (0.3281)

 1-2 Lags

 47.67 52.32
None * (0.0000) (0.0000)

 14.47 15.38
At most 1 (0.0702) (0.0522)

 8.292 8.292
At most 2 (0.4054) (0.4054)

 1-3 Lags

 65.87 74.22
None * (0.0013) (0.0000)

 19.50 21.53
At most 1 (0.0124) (0.0059)

 11.09 11.09
At most 2 (0.1969) (0.1969)

* Denotes rejection of the hypothesis at the 0.05 level.

Table 5: Estimated Vector Error Correction Models

Dependent
Variable: Log Log Estimated Error
[(VA).sub.t] Log ([L.sub.t]) [(HC).sub.t] Correction Term

 1 Lag (AIC = -4.60, SC = -4.14)

 0.6874 0.2058 -0.0556
 (3.3153) (1.1651) (6.4771)

 1-2 Lags (AIC = -4.61, SC = -3.85)

 0.6045 0.3478 -0.0438
 (2.3584) (1.5862) (6.0139)

 1-3 Lags (AIC = -4.72, SC = -3.64)

 0.6244 0.3808 -0.0315
 (1.9784) (1.39208) (3.9944)