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A comparative record of technological capability in ASEAN countries
Pergamon PII: S0166-4972(97)00117-X
Technovation, 18(4) (1998) 263–274 1998 Elsevier Science Ltd. All rights reserved Printed in Great Britain 0166-4972/98 $19.00 + 0.00
A comparative record of technological capability in ASEAN countries Alan Jones Industry Canada, Ottawa, Ontario, Canada K1A 0H5 Ashish Lall Nanyang Technological University, Nanyang Business School, Room S3-B1A-04, Singapore, Singapore 639798
Abstract The rapid economic growth in newly industrializing countries (NICs) over the past decade has been impressive. However, the ability of these countries to sustain high growth in the future has come under question repeatedly. A number of measures are used in this paper to assess the state of technology in the ASEAN and to draw comparisons with a select group of developed countries. Productivity trends in ASEAN and other countries are examined first due to the intimate relationship between technology and productivity. While popular measures of technological capability, such as the number of R&D personnel and expenditures, are used, the focus is on trade in manufactured goods classified by R&D intensity. In the case of the ASEAN, the evidence suggests that they are net importers of technology and have yet to develop strong domestic R&D capabilities. ASEAN countries have considerable ground to cover before they can rival the technological capabilities of developed countries. Policy prescriptions for enhancing the technological capabilities of ASEAN countries are presented at the conclusion. 1998 Elsevier Science Ltd. All rights reserved
1. INTRODUCTION The rapid economic growth that has been witnessed in newly industrializing countries (NICs) over the past decade has been impressive. However, the ability of these countries to sustain high growth in the future has come under question repeatedly. In the neo-classical framework, economic growth is accomplished through some combination of the accumulation of the factors of production and total factor productivity
(TFP) growth. Yet in this framework, growth that relies only on the accumulation of factors of production cannot be sustained due to diminishing returns. Long run economic growth requires TFP growth. Technological change, defined as ‘a new way of doing things’, is the primary enabling factor of productivity growth. This definition obviates the need to make distinctions between concepts such as process
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innovation and product innovation. The former relates to the use of new production processes with the products remaining unchanged, while the latter refers to the introduction of new products. This simple definition accommodates the ‘Schumpeterian trilogy’ of invention, innovation and diffusion.1 While invention involves pushing out the existing technological boundaries, innovation and diffusion refer to the application and adoption of existing technology. All activities in the trilogy can be thought of as representing an improvement in technology. The definition also encompasses advancements in both science and technology. From the view point of economics, an important difference between the two is that the benefits from the former are available to all, whereas in the latter case some or all information may be proprietary. Arrow’s (Arrow, 1994) interpretation, that technology is information or knowledge, also fits this definition. Clearly, doing things in a new way requires information. Since technology is typically embodied in both final and intermediate goods, improvements in technology benefit both consumers and producers. Consumers benefit directly from technological change that increases product variety or introduces new products. Consumer welfare can also be enhanced by technologies that either reduce costs or result in time savings. For example, consumer welfare may be increased as a result of new technologies that improve the energy efficiency of consumer durables (e.g. major appliances, automobiles and homes) and reduce energy bills. Time savings may result from the introduction of intelligent transportation systems which reduce commuting times and therefore increase the leisure time of consumers. From the producer’s perspective, a new way of doing things may involve, for example, process changes on the factory floor or computer software upgrades that reduce production costs or improve service quality. In short, firms expect efficiency or productivity gains from improved technology. At the national level, improvements in the productivity of the factors of production resulting from technical advance are a source of higher economic growth and standards of living. The process of technological change and diffusion across countries is both complex and multi-faceted. There are complex feedback mechanisms from diffusion back to invention and innovation, since in many cases, technology improves on an existing pro1 See Stoneman (1995) pp. 3–8 and Nelson and Rosenberg (1993) for details.
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duct. There is also a selection process at work. At each stage of the Schumpeterian trilogy the selection of a given technology may be based on both conscious decision regarding practical matters such as profitability as well as exogenous or chance events. Nor does the ‘best’ technology always ‘win’. Supporters of the concept of the evolution of technological dominance advocate that once a particular technology gets ahead, increasing returns set in that, in some instances, allow it to capitalize on the lead leaving behind a superior technology. Technology, like information, cannot be concealed forever. International diffusion, from leaders to followers, takes place through a variety of mechanisms, including foreign direct investment, joint ventures, licenses, sub-contracting, reverse engineering and overseas education and training. Important in this regard is that technology, or what Arrow calls knowledge, is both an input and an output in the production process. Thus, the development and transfer of new technology requires both producers and users to be ‘skilled’ or educated. Another point of note is that independent R&D and reverse engineering are the most effective means of learning about competitors’ innovations.2 In addition, though imitation costs, on average, account for 70% of the costs of innovation, only a small part of imitation costs are for the purchase of protected intellectual property.3 Finally, barriers to imitation arise from the high costs of accumulating tacit knowledge, rather than from the withholding of information. In ASEAN4 countries, factor accumulation has played an important role in the process of technological change through typically very high savings rates. Hence, growth in these countries has been driven primarily by capital accumulation. Of late, however, governments of some ASEAN countries are making a concerted effort to attract foreign firms to establish R&D facilities in ASEAN and to promote the R&D activities of domestic firms. In view of this policy shift, this paper seeks to assess the current technological capability of ASEAN countries. The following section presents the manner in which we will measure and assess the state of technology in
2 Compared to licensing for example. See Table 2.2 in Patel and Pavitt (1995). 3 At p. 8, Patel and Pavitt (1995) cite the work of Mansfield. 4 The Association of South East Asian Nations (ASEAN) comprises Indonesia, Malaysia, Singapore, Thailand, the Phillippines, Brunei Darussalam Negara and Vietnam. In addition, as of July 1997 ASEAN will also include Laos, Cambodia and Myanmar.
A comparative record of technological capability in ASEAN countries
the ASEAN countries.5 In addition to conventional measures, such as R&D expenditures and persons engaged in R&D, a variety of trade related measures are used, since international trade continues to play a vital role in the economic growth of these countries. We present the empirical evidence of technological change in ASEAN countries based on these measures in the subsequent section and we draw comparisons with a select group of developed countries. Due to the intimate relationship between technology and productivity, productivity trends in ASEAN and other countries are examined first. While popular measures of technological capability, such as the number of R&D personnel and expenditures are used, our focus is on trade in manufactured goods classified by R&D intensity. The analysis is conducted both at the aggregate level and at the commodity level. Cross country comparisons are made within ASEAN countries and between ASEAN and developed countries, such as Japan, Switzerland and the United States, to determine the degree of ‘catch-up’ that has occurred. A concluding section summarizes a number of issues in the debate that surrounds the assessment of the technological capability of countries and provides policy prescriptions for improving productivity and the technological capabilities of ASEAN countries.
2. MEASUREMENT TFP growth, which is intimately related to the process of technological change, measures the productivity of all factors of production. TFP growth also drives long run economic growth. Under the assumptions of constant returns to scale, competitive markets and long run equilibrium, TFP growth is identical to the rate of technical change or the rate of upward shift in the production function over time. Measuring technological change is much more difficult than defining it and the literature is replete with proxy measures. While the boundary between the producers of technology and the user of technology is not always well defined, such a distinction can be useful to aid in the measurement. Producers contribute to the expansion of the technological frontier, while users facilitate catch-up. Common measures of technology usually focus on the activities of the former group. For example, comparisons across industries are often made using indicators such as the number of R&D personnel and/or the expenditures on R&D. The weaknesses of these measures are reflected in the fact that R&D personnel is a stock measure and more representative of the potential capabilities of an industry 5 Due to data limitations, we only cover the ASEAN-5, or Indonesia, Malaysia, Singapore, Thailand and the Phillippines.
or country, rather than its actual contribution to improvement in technology. The latter, expenditures on R&D, is a measure of ‘spend’ and as, an input into the process of technological change, is therefore not indicative of the ‘output’ of R&D effort. Another shortcoming of using R&D personnel and/or R&D expenditure is that it does not account for changes in ‘software’, such as engineering and organizational changes, which may assist in enhancing innovation and productivity.6 The productivity of technology may be measured using the number of patents granted per R&D employee or per dollar of R&D expenditure. The use of patent data, however, can be misleading to the extent that the importance of patenting differs across sectors and the criteria for granting patents differ across countries. Since technology is embodied in both consumer goods and capital goods, trade in commodities classified by R&D intensity is a useful indicator of the state of technology in a country. Imports are important because they are indicative of the ability of a country to use technology-intensive products. In all probability, a country that imports technology-intensive intermediate goods has a workforce that is both skilled and educated enough to use them. Similarly, a country that exports technology-intensive products (both consumer and capital goods) must have the ability to produce or assemble such goods for the international market which is usually more demanding than the domestic market. While exports or export shares of high and medium technology products can be used as indicators of technological performance, the index of revealed comparative advantage (RCA) is a more informative measure. The index is the ratio of the share of exports of a particular commodity in total exports of that country to a similar construct for a reference group of countries, or:
冘 冘 冘冘 Xij/
RCAij =
Xij
i
Xij/
j
i
(1) Xij
j
where Xij is the value of exports of commodity i by country j. This measure provides information on the structure of exports of a country, permitting a ranking of countries based on their comparative advantage. A number greater than unity indicates superior performance relative to the group.
6
We thank an anonymous referee for this observation.
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A second measure of technological performance, revealed comparative trade advantage is presented in equation (2): RCTAij =
Xij ⫺ Mij Xij + Mij
(2)
where Xij is the value of exports of commodity i by country j and Mij is the value of imports of commodity i by country j for the years 1980 and 1990.7 Furthermore, it is useful to appraise changes in the technological capabilities of countries. This is done by constructing an index that indicates a movement up the technology ladder or one that measures unidirectional structural change. The technology ladder index (TLI) is given as: TLIjtt⬘ =
SHjt ⫺ SHjt⬘
冘
SHjt ⫺
j
冘
∀t ⬎ t⬘
TFP growth has been much higher in Japan and the Republic of Korea than in ASEAN countries.8 Table 2 compares the level of productivity of a number of developed countries. In this case the U.S. was the most productive in 1988, not Japan. The manufacturing sector in Japan, however, displays the highest rate of growth of TFP and at the economy-wide level, Japan had the second highest growth rate. Continuation of these trends suggests that higher TFP growth rates in Japan will allow it to catch up to the U.S. While Tables 1 and 2 do not report estimates of the level of TFP for ASEAN countries, it is probable that these levels are lower than in Japan. Table 1 does show that the rate of growth of TFP has been higher in Japan than in the ASEAN countries and further suggests that there is no convergence of productivity levels between Japan and the ASEAN countries.9
(3)
SHjt⬘
j
where SHjt is the share of high R&D intensity exports of country j at time t. The TLI is the change in the share of high R&D intensity exports of a country over any given time period, relative to that of a reference group of countries. Two additional direct measures of catch-up in export shares of high-tech manufactures are also calculated. The first is the distance of any particular country from the leader, or, for any given year, the difference between high-tech export share of the leader and that of the country in question. The second is the change in the distance measure described above, between any two time periods.
3. EMPIRICAL EVIDENCE Average annual rates of growth of TFP for select ASEAN and other countries over the period 1960– 1990 are presented in Table 1. It can be seen that
Kim and Lau (1994) also reach the conclusion that technical advance has been significant for G-5 countries, but not for the East Asian NICs. Using both growth accounting and econometric methods they show that the contribution of TFP to economic growth is higher for G-5 countries than for NICs. The authors conclude that “the hypothesis of zero technical progress can be rejected for G-5 countries but not for the East Asian NICs”.10 They also compare productive efficiency over time and across countries by providing each country with the measured U.S. endowment of labour and capital and trace the evolution of the resulting output over time. They found that the output efficiencies of Japan, France, West Germany and the U.K. clustered around 50–70%, while the four NICs had output efficiencies of only 20% of that of the U.S. By 1990, the G-5 were catching up to the U.S., but the NICs fell to 14% of the output of the U.S. They conclude that “the empirical evidence does not appear to support the hypothesis of convergence in technology, i.e. given the same inputs, different countries will over time produce increasingly similar levels of real output.”
TABLE 1. Average annual percentage rate of growth of total factor productivity, 1960–1990 Country Indonesia Malaysia Singapore Thailand Republic of Korea Japan
High estimate 1.25 1.08 1.19 2.50 3.10 3.48
Low estimate ⫺ 0.80 ⫺ 1.34 ⫺ 3.01 0.55 0.24 1.43
Source: World Bank (1993) Table A1.2.
7 Other than being a nominal magnitude that is affected by movements in both prices and exchange rates, this measure does not provide any indication of the magnitude of trade and is scale invariant.
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8 These are the results from a sensitivity exercise. Briefly, the low estimates are the result of a higher weight being accorded to capital inputs. Since capital accumulation is higher in ASEAN, giving a greater weight to capital increases the contribution of capital to economic growth and therefore reduces the importance of TFP as an explanatory variable. The greatest negative impact occurs for Singapore, since it has one of the highest rates of capital accumulation in the world. 9 See Young (1992) for a comparison of TFP growth in Singapore and Hong Kong. His results indicate that the contribution of TFP growth to growth in output is minimal for Singapore, whereas this is not the case for Hong Kong. 10 See Kim and Lau (1994), Tables 3.1 and 7.2; in addition Footnote 19 on page 249 indicates that for the G-5 countries, the hypothesis of zero technical change is rejected at “almost any reasonable level of significance”. Thus the rejection is decisive.
A comparative record of technological capability in ASEAN countries
TABLE 2. G-7 countries—total factor productivity, 1979–1988 Country
Economy-wide TFP level in 1988
United States Japan Germany France Canada United Kingdom
Manufacturing sector
Average annual % growth rate of TFP 1979–1988
100 87 78 87 83 74
0.41 1.25 0.57 1.07 ⫺ 0.03 1.38
TFP level in 1988
Average annual % growth rate of TFP 1979–1988
100 *91 62 65 *66 56
1.92 3.71 0.10 0.57 0.25 2.49
Note: *1987 value; Source: Wolff (1994) Table 8.3.
TABLE 3. Scientists and engineers engaged in R&D per 1000 of labour force Country
Year
Number
Japan Switzerland United States Republic of Korea Brunei Darussalam* Indonesia Malaysia Philippines Singapore Thailand Viet Nam
1992 1989 1988 1992 1984 1988 1988 1984 1987 1991 1985
11.2 5.1 7.9 4.5 116 0.5 0.8 0.2 2.7 0.3 0.7
Note: *Actual number of scientists and engineers is reported for Brunei; Source: UNESCO (1994) Table 5.3 and World Bank (1995).
Table 5 shows that Singapore continued to lag behind other NICs such as the Republic of Korea, and developed countries such as Japan and the U.S. Japan spends approximately twice that of Singapore on R&D, it has twice the number of R&D personnel and the share of R&D expenditures in GDP is twice that of Singapore. Tables 6–16 provide values for the trade measures outlined in the previous section and derived using data on trade in manufactured goods (the goods are grouped according to high, medium and low R&D intensity11).
Singapore has from 3 to 10 times more scientists and engineers engaged in R&D per 1000 workers than other ASEAN countries (Table 3). Intellectual property rights statistics reported in Table 4 supplement this picture. In the area of trademarks and patents, the number granted in Singapore are comparable to those in some developed countries and substantially higher than those in other ASEAN countries. However,
Each country’s revealed comparative trade advantage (RCTA) for the years 1980 and 1990 is presented in Table 6. It is apparent that on average, ASEAN countries as well as the Republic of Korea were net importers of high-tech and medium-tech goods and net exporters of low-tech goods, while the opposite was true for developed countries such as Japan, Switzerland and the U.S. However, all Asian countries (with the exception of Indonesia) registered an increase in the ratio of net exports to total trade in
TABLE 4. Intellectual property statistics, 1993
TABLE 5. Research and development indicators—comparative
Country
Trademark registrations effected
Patents granted
Country (year)
GERD per RSE (thousands of USD)
RSE per 10 000 of labour force
GERD as a percentage of GDP
93.2 70.25
40.54 47.31
1.12 2.17
194.63 249.3 162.61
80.72 74.74 69.89
2.72 2.51 2.72
Per 10 000 of labour force Brunei Darussalam Malaysia Singapore Thailand Viet Nam Republic of Korea Germany Japan Switzerland United States
922 3.9 55.1 2.4 2.4 13.2 5.1 37.7 55.3 6.5
0 1.7 10.5 0.1 0.0 5.8 8.2 21.0 64.5 7.9
Singapore (1993) Republic of Korea (1992) Japan (1992) Switzerland (1992) United States (1991)
Source: National Science and Technology Board (1993).
11
Notes: *Actual number of trademarks and patents is reported for Brunei; all countries—labour force data are provisional. Source: Yu (1993) and World Bank (1995).
All data tables are based on Yearbook of Industrial Statistics, UNIDO (1992). UNIDO classifies goods into three categories, but does not define R&D intensity. The latter usually refers to expenditure on R&D within any particular sector.
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TABLE 6. Revealed comparative trade advantage (ratio of net exports to total trade) Country
Year
R&D intensity of manufactures High
Indonesia Indonesia Malaysia Malaysia Philippines Philippines Singapore Singapore Thailand Thailand Republic of Korea Republic of Korea Japan Japan Switzerland Switzerland United States United States
1980 1990 1980 1988 1980 1988 1980 1990 1980 1990 1980 1990 1980 1990 1980 1991 1980 1990
⫺ ⫺ ⫺ ⫺ ⫺ ⫺ ⫺ ⫺ ⫺ ⫺ ⫺ ⫺
0.85 0.84 0.24 0.09 0.74 0.36 0.08 0.01 0.64 0.38 0.33 0.14 0.39 0.44 0.29 0.22 0.32 0.11
Medium ⫺ ⫺ ⫺ ⫺ ⫺ ⫺ ⫺ ⫺ ⫺ ⫺ ⫺ ⫺
0.77 0.74 0.39 0.29 0.70 0.37 0.20 0.12 0.43 0.51 0.06 0.03 0.73 0.62 ⫺ 0.05 0.00 0.03 ⫺ 0.22
Low ⫺ 0.27 0.27 ⫺ 0.03 0.16 0.15 0.02 0.12 0.08 ⫺ 0.05 0.11 0.39 0.32 0.19 ⫺ 0.22 ⫺ 0.38 ⫺ 0.30 ⫺ 0.21 ⫺ 0.34
Source: UNIDO (1992); calculated using nominal US dollar value of exports and imports.
high-tech goods (the opposite is true for Switzerland and the U.S.). Therefore, while ASEAN countries continued to be net importers of high-tech goods, net imports declined (and net exports increased) over the decade in all countries except Indonesia. Within the group of five ASEAN countries, Singapore had a revealed comparative advantage (RCA) in exports of high-tech manufactures in both 1980 and 1990 (Table 7). Malaysia led the group in mediumtech products in 1980, but by 1990 Singapore had also assumed a number one position in this group as well. With its declining RCA in low-tech exports and increase in both medium-tech and high-tech products, Singapore moved up the technology ladder over the decade. In 1980, the Philippines led the group at TABLE 7. Index of revealed comparative advantage, ASEAN-5 Country
Year
R&D intensity of manufactures High
Indonesia Indonesia Malaysia Malaysia Philippines Philippines Singapore Singapore Thailand Thailand
1980 1990 1980 1988 1980 1988 1980 1990 1980 1990
0.24 0.10 1.28 1.13 0.28 0.60 1.29 1.34 0.54 0.63
Medium 0.83 0.54 1.17 0.92 0.51 1.03 1.03 1.14 1.15 0.97
Low 1.29 1.77 0.86 0.95 1.38 1.25 0.90 0.72 1.09 1.25
Source: UNIDO (1992), calculated using on nominal USD value of exports.
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exporting low-tech manufactures, followed by Indonesia. The two countries exchanged positions in 1990. Table 8 shows that, compared to the Republic of Korea and developed countries (Japan, Switzerland and the U.S.), ASEAN countries are below average. In 1980, Switzerland was the best at exporting hightech manufactures, followed by the U.S. By 1990, the U.S. assumed the number one position in this commodity group, followed closely by Singapore. Japan was the best at exporting medium-tech products in both 1980 and 1990. It is noteworthy that over the period 1980–1990, all Asian countries with the exception of Indonesia registered an increase in the RCA index for high-tech manufactures. The reverse is true for the leaders, Switzerland and the U.S. This result suggests that export shares of high-tech manufactures may be converging. Though the index of RCA is scale invariant, an examination of the nominal values of high-tech exports (Table 9) leads to conclusions similar to those that were derived from the previous two tables. In 1990, the share of high-tech exports in total manufacturing industry exports was highest for the U.S., that of medium-tech exports was the highest for Japan, and Indonesia had the highest low-tech export share of all countries. In addition, the U.S. had the highest nominal value of high-tech exports and Indonesia, the lowest. More interesting is the fact that even though the nominal value of high-tech exports of the U.S. was about 6.5 times that of Singapore, the share of high-tech exports in total manufacturing industry exports of Singapore (42.4%) was just half a percentTABLE 8. Index of revealed comparative advantage, ASEAN-5 and selected countries Country
Year
R&D intensity of manufactures High
Indonesia Indonesia Malaysia Malaysia Philippines Philippines Singapore Singapore Thailand Thailand Republic of Korea Republic of Korea Japan Japan Switzerland Switzerland United States United States
1980 1990 1980 1988 1980 1988 1980 1990 1980 1990 1980 1990 1980 1990 1980 1991 1980 1990
0.16 0.09 0.88 0.98 0.19 0.52 0.88 1.16 0.37 0.55 0.43 0.63 0.72 0.91 1.48 1.14 1.25 1.17
Medium 0.41 0.28 0.58 0.48 0.25 0.54 0.51 0.60 0.57 0.51 0.46 0.65 1.24 1.36 0.93 0.98 0.97 0.90
Low 2.48 3.41 1.65 1.82 2.67 2.40 1.74 1.38 2.11 2.40 2.19 2.07 0.92 0.58 0.68 0.82 0.82 0.91
Source: Calculated using nominal USD value of exports from UNIDO (1992).
A comparative record of technological capability in ASEAN countries
TABLE 9. 1990 percentage shares of manufacturing industry exports Country
Indonesia Malaysia* Philippines* Singapore Thailand ASEAN-5 Republic of Korea Japan Switzerland* United States
R&D intensity of manufactures
High
Medium
Low
3.3 35.7 19.0 42.4 20.0 31.5 23.1 33.1 41.7 42.9
10.9 18.5 20.6 22.9 19.5 20.1 24.9 52.3 37.7 34.3
85.8 45.8 60.4 34.7 60.5 48.4 52.0 14.7 20.7 22.8
Value of high-tech exports USD mill.
394 4827 708 21 099 3605 30 632 14 496 92 937 23 743 134 388
Note: *Malaysia and Philippines–1988 data. Switzerland–1991 data. Source: UNIDO (1992); calculated using nominal USD value of exports.
age point lower than the same measure for the U.S. (42.9%). The more striking result is that high-tech exports account for a higher proportion of total manufacturing industry exports of Malaysia (35.7%) than of Japan (33.1%). Table 9 also shows that among the group of ASEAN-5, Singapore has the highest value of high-tech manufactures exports and the highest export share. In 1990, Singapore accounted for approximately two-thirds of ASEAN-5 high-tech exports. Indonesia had the highest share of low-tech exports and the lowest nominal value of high-tech exports. The index of movement into high-tech exports (TLI) is calculated according to equation (3) and presented in Table 10. Once again Singapore led the group of ASEAN-5 followed by the Philippines.12
TABLE 11. Distance from export share of the leader in high R&D intensity exports, ASEAN-5 Country Indonesia Malaysia Philippines Singapore Thailand
1980 0.1933 0.0005 0.1852 0.0000 0.1383
1990
Change
0.39 *0.07 *0.23 0.00 0.22
0.20 0.07 0.05 0.00 0.09
Note: *1988 data. Source: UNIDO (1992), calculated using nominal USD value of exports.
The two countries maintained their rank as the group is expanded to include the Republic of Korea, Switzerland, Japan and the U.S. Therefore, as in the case of Table 7, the results suggest a movement up the quality ladder in manufacturing over the period 1980– 1990, with the convergence in high-tech export shares being the greatest for Singapore, while Indonesia fell behind. Tables 11 and 12 provide a more direct measure of catch-up in export shares of high-tech manufactures. They present both the distance of any particular country from the leader (the difference between high-tech export share of the leader and that of the country in question) and the change in the distance over the period 1980–1990. Table 11 shows that within the ASEAN-5, Singapore was the leader in both 1980 and 199013 and has increased its lead over its ASEAN neighbours. Thus with the ASEAN-5 there is no convergence. This conclusion changes as the group is expanded once again (Table 12). All Asian countries, with the exception of Indonesia, are catching-up to the leading developed countries. Singapore again has been most effective at closing the gap as its high-tech
TABLE 10. Index of movement into high R&D intensity exports Country Indonesia Malaysia* Philippines* Singapore Thailand ASEAN-5 Republic of Korea Japan Switzerland* United States
ASEAN-5
All countries
⫺ 0.09 0.92 1.05 1.42 0.77 – – – – –
⫺ 0.12 1.26 1.44 1.96 1.06 1.38 1.20 1.42 0.16 0.96
Notes: *Malaysia and Philippines–1988 data. Switzerland–1991 data. The index is the change in the share of high R&D intensity exports of a country over the years 1980–1990 relative to the reference group of countries, ASEAN-5 or all countries in the table. Source: UNIDO (1992), calculated using nominal USD value of exports.
TABLE 12. Distance from export share of the leader in high R&D intensity exports, all countries Country Indonesia Malaysia Philippines Singapore Thailand ASEAN-5 Republic of Korea Japan Switzerland United States
1980
1990
0.36 0.16 0.35 0.16 0.30 0.22 0.28 0.21 0.00 0.06
0.40 *0.07 *0.24 0.00 0.23 0.11 0.20 0.10 **0.01 0.00
Change 0.04 0.09 0.11 0.16 0.07 0.10 0.09 0.11 0.01 ⫺ 0.06 ⫺ ⫺ ⴚ ⫺ ⫺ ⫺ ⫺
Notes: *1988 data, **1991 data. Source: UNIDO (1992), calculated using nominal USD value of exports.
12
This is interesting because not too long ago, the Philippines was known as ‘sick man of ASEAN’ due to its low economic growth compared to other ASEAN members.
13
Therefore the distance from the leader is zero for Singapore in both 1980 and 1990.
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TABLE 13. Index of revealed comparative advantage for high R&D intensity manufactures, 1990 Country
Indonesia Malaysia* Philippines* Singapore Thailand Republic of Korea Japan Switzerland United States SITC 51 52 53 54 57 59 72 73 86
Standard International Trade Classification (SITC) code 51
52
53
54
57
59
72
73
86
0.2 0.2 0.7 0.6 0.1 0.4 0.7 1.7 1.3
na 0.0 3.3 4.7 na 0.9 0.1 0.0 1.6
0.4 0.1 0.0 0.5 0.2 0.3 0.6 3.6 0.6
0.1 0.1 0.1 0.3 0.1 0.1 0.2 4.8 0.9
0.0 0.0 1.7 0.4 0.0 0.2 0.0 0.3 1.7
0.2 0.6 0.4 0.8 0.5 0.1 0.5 1.5 1.3
0.1 3.0 1.5 2.1 1.1 1.9 1.8 0.9 1.2
0.1 0.1 0.0 0.2 0.1 0.6 1.6 0.1 1.2
0.1 0.3 0.1 0.7 0.4 0.4 1.8 3.3 1.2
Product group Chemical elements and compounds Mineral tar etc. Dyes, tanning, colouring products Medicinal, pharmaceutical products Explosives, pyrotechnic products Chemical materials n.e.s. Electrical machinery Transport equipment Instruments, watches, clocks
Notes: *1988 data. Scores are based on a reference group of 43 countries according to the above groups. Source: UNIDO (1992).
export share moved to only half a point behind that of the U.S. in 1990.14 Tables 13–16 present trends in high-tech exports at a more detailed level. Table 13 presents indices of RCA for nine commodity groups at the 2-digit SITC level for 1990. All nine commodity groups are classified as high R&D intensive products.15 The reference group against which comparisons are made consists of 43 countries. Developed countries led the group of nine countries in seven out of nine high-tech products. Switzerland took the lead in chemical compounds, dyes and colouring products, pharmaceuticals and instruments. The U.S. had the highest RCA in chemical materials and explosives (the Philippines shared the lead in the latter). Japan led the group in transportation equipment and Singapore led in mineral tar and electrical machinery. Tables 14 and 15 identify the commodity for which each of the nine countries had the highest RCA for the years 1980 and 1990, respectively. In other words, they show the export strength of each country or the commodity with the highest index of RCA irrespective of its R&D intensity. In Table 14, Singapore and Switzerland are shown to have the highest revealed comparative advantage for high-tech goods, mineral 14
Due to rounding, Table 11 indicates that both the U.S. and Singapore have the same high-tech export share. However, as is evident from Table 8, Singapore is marginally behind the U.S. 15 Transport equipment is a mix of medium-tech (automobiles) and high-tech (aircraft engines).
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tar and pharmaceuticals, respectively. The U.S. had an advantage in the medium-tech good fertilizer, while the export strength of all other countries, including Japan, lay in low-tech goods. In 1990, Japan moved to high-tech products such as instruments and electrical machinery and Singapore moved to petroleum products, a low-tech product. The export strengths of other countries were more or less unchanged in 1990. Table 16 presents indices of revealed comparative advantage for seven high tech commodity groups in the ASEAN-5 countries. In 1990, Singapore emerged as the leader in five of the seven, while the Philippines led in chemicals and Malaysia led in electrical products. Singapore’s technological superiority in ASEAN is confirmed at the disaggregated level.
4. CONCLUSIONS AND POLICY IMPLICATIONS The literature on technology gaps suggests that technological differences across countries are reflected in gaps in productivity levels. Consequently, national technological activities are expected to be correlated with productivity. Fagerberg (1994) found, in a large sample of developed and newly industrializing countries that, “the tendency toward convergence across countries in productivity levels was parallelled by a similar tendency for levels of R&D and patenting activity”.16 The evidence that we have provided 16
See Fagerberg (1994), p. 1161.
A comparative record of technological capability in ASEAN countries
TABLE 14. Product with highest index of revealed comparative advantage, 1980 SITC 2 4 4 52 0 83 67 54 56
Product group
Country
RCA index
Simply processed materials Animal, vegetable oils, fats Animal, vegetable oils, fats Mineral tar etc. Food products Travel goods etc. Iron and steel Medicinal, pharmaceutical products Fertilizers, manufactured
Indonesia Malaysia Philippines Singapore Thailand Republic of Korea Japan Switzerland
R&D intensity
11.7 20.5 21 24.7 5.3 9.6 2.2 4.8
United States
Low Low Low High Low Low Low High
2
Medium
Notes: Based on a reference group of 43 countries. Source: UNIDO (1992). TABLE 15. Product with highest index of revealed comparative advantage, 1990 SITC 63 4 4 332 83 83 72 86 54 56
Product group
Country
RCA index
R&D intensity
Wood, cork manufactures n.e.s. Animal, vegetable oils, fats Animal, vegetable oils, fats Petroleum products Travel goods etc. Travel goods etc. Electrical machinery Instruments, watches, clocks Medicinal, pharmaceutical products Fertilizers, manufactured
Indonesia Malaysia* Philippines* Singapore Thailand Republic of Korea Japan Japan Switzerland
35.8 24.1 19.2 7.6 5.8 8.5 1.8 1.8 4.8
Low Low Low Low Low Low High High High
United States
2
Medium
Notes: *1988 data; based on a reference group of 43 countries. Source: UNIDO (1992). TABLE 16. Index of revealed comparative advantage in high R&D intensity manufactures, ASEAN-5, 1990 Country
Standard International Trade Classification (SITC) code 51
Indonesia Malaysia* Philippines* Singapore Thailand SITC 51 53 54 59 72 73 86
0.4 0.4 1.4 1.1 0.2
53
54
59
2.5 0.8 0.0 3.3 1.7
0.7 1.4 0.7 2.7 0.7
0.5 1.4 1.0 1.9 1.2
72 0.1 2.3 1.2 1.6 0.8
73 1.0 1.3 0.5 2.9 1.2
86 0.6 1.7 0.3 3.8 2.1
Product group Chemical elements & compounds Dyes, tanning, colouring products Medicinal, pharmaceutical products Chemical materials n.e.s. Electrical machinery Transport equipment Instruments, watches, clocks
Notes: *1988 data; some product groups are excluded due to incomplete data. Source: UNIDO (1992), calculated using nominal USD value of exports.
appears, at first glance, to concur. For example, Tables 1 and 2 showed that the U.S. had the highest level of TFP, while TFP growth is highest in Japan. The trade-related measures that we presented also support the lead position of the U.S. ASEAN countries, on the other hand, have a poor record in this regard, though, as is evident from Table 1, this conclusion depends on the nature of the weights used in aggregation.
Hobday (1994) also raises a number of relevant issues in attempting to explain Singapore’s poor TFP growth performance given that country’s technological edge over other ASEAN countries. He states17:
17
Hobday (1994), p. 835.
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In contrast with its strong supply of technicians and production engineers Singapore lags behind other countries in the supply of research engineers and scientists. In 1990 Singapore had around 28 research engineers and scientists per 10 000 workers (a total of 4300), compared with 87 for Japan, 77 for the US, 44 for Switzerland, 43 for Taiwan and 33 for the Republic of Korea. Similarly, government spending on R&D as a percentage of GDP lags behind many developed countries as well as Taiwan and the Republic of Korea. Hobday argues that although R&D is increasingly becoming a target of Singapore’s technology policy, it has not been the basis for success so far. Instead, Singapore’s success is based on low-cost, high-quality production engineering. As of 1992, “product output in Singapore was advanced and mainstream, but not at the leading edge of experimental technology”.18 Mainstream product design and R&D was carried out by MNCs at their headquarters, rather than in Singapore. This theme is echoed by Kim and Lau (1994) who provide some additional insights into the issue of R&D. They suggest that imported capital goods may be fully priced, thus reflecting amortized R&D and other development costs. The scope for indigenous improvement may be limited because the installed capital goods are likely to be of an ‘off-the-shelf’ variety. They also allude to ‘software’ components such as managerial methods and the institutional environment lagging behind ‘hardware’ in the NICs. Their research also suggests that the importance of indigenous R&D increases as a country moves closer to the technological frontier and that a certain level of R&D is a necessary condition for successful imitation. Thus copying is not enough and to do so also requires indigenous innovation. In the case of the ASEAN, the evidence suggests that they are net importers of technology and have yet to develop strong domestic formatting R&D capabilities. However this should not be surprising, since the assimilation of technology, learning by doing and imitation occurs in stages. In the manufacturing sector, for example, the first stage may require assembly skills and basic production capabilities, whereas the final stage entails competitive R&D capabilities in advanced product/process innovation. The apparent correlation between productivity growth and technological capability (Young, 1992;
Kim and Lau, 1994) must be softened due to a closer look at the trade-related measures. Though a discussion of the sources of economic growth is not central to our paper, a few comments are in order.19 Young (1992) used an old technique to evaluate a new theory—endogenous growth. His work did not support endogenous growth models that are linear in accumulable factors of production, since such models should find higher TFP growth for Singapore than for Hong Kong. Kim and Lau (1994), using more sophisticated econometric techniques, found that TFP growth was low, not only in Singapore, but also in other Asian NICs. Krugman (1994) based his arguments on both these works. More recently, Nelson and Pack (1995) criticized these methods and pointed out that they suffer from identification problems and do not take into account the fact that the weights used in a growth accounting exercise are endogenous. To borrow the terminology of Nelson and Pack (1995), one cannot use an ‘accumulation’ type model to provide ‘assimilation’ type prescriptions. To be fair, since Young (1992) and Kim and Lau (1994) confined themselves to the neo-classical straightjacket, their conclusions are only logical. If there is no TFP growth, diminishing returns must set in. Yet, such analyses are less than informative from either a policy viewpoint or in advancing our understanding of the causal mechanisms behind East Asian growth. Constructing an index of TFP or estimating production functions merely provide a scalar measure of efficiency. They generally assume that technical progress is disembodied and do not take into account the vintage of different type of capital goods. They therefore ignore the complex feedback mechanisms of technology alluded to earlier in this paper and their prescriptive power is poor, since TFP growth is essentially a residual.20 These empirical models and methods cannot lead one to conclude that a particular country should increase investment in R&D, since they do not take into account R&D, and yet these are precisely the type of prescriptions that Kim and Lau provide. We suggest that there are a number of important reasons why we may never know what TFP growth in Singapore really is. First, as is evident from Table 1, the results are very sensitive to the weights used in aggregation. Second, there has been no survey of wealth conducted in Singapore and so all studies rely
19
In the context of Singapore, these papers are discussed in Lall et al. (1996). Interestingly enough, this has not stopped the Singapore government from ‘targeting’ TFP growth. The government has announced a ‘targeted TFP growth’ of 2.5% per annum.
20 18
See Hobday (1994), p. 843 for a more detailed treatment of the stages of product marketing and technology.
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on either an accounting benchmark capital stock, or one that is ‘maximum likelihood’ as in the case of Kim and Lau. Finally, as Young (1992) pointed out, 47% of the components of the index of industrial production consist of nominal magnitudes. Thus the output measure for the manufacturing sector is a mixture of real and nominal magnitudes and, given that this sector accounts for about a quarter of GDP, it is not clear whether one can even calculate correctly the growth of real output in Singapore. A more plausible story is that of Nelson and Pack (1995) who argue that a country cannot increase capital per worker without learning about new techniques and how to use them, otherwise the marginal return on the new capital will be zero.21 Thus, under the ‘assimilation’ theory, high investment is induced by learning. Clearly, to proponents of this viewpoint, Singapore’s high investment rates are indicative of the amount of learning that has taken place. On the other hand, using the same information in a growth accounting exercise would lead to a small residual because the growth in capital explains a very large amount of the growth in output. The results of our trade-related measures indicate that all ASEAN countries (with the possible exception of Indonesia) have been doing a lot of learning, particularly Singapore.
capabilities of ASEAN countries are clear. First, ASEAN countries should continue their efforts to attract foreign direct investment and qualified personnel. This can be achieved either by economy-wide measures, such as providing tax incentives for the conduct of R&D, or through sector or technology specific incentives, or both. Second, intellectual property laws should be strengthened to further attract foreign providers of technology and to protect domestic inventors and innovators. The recent multilateral agreements on TRIPS (trade related aspects of intellectual property rights) may in fact hasten this process. Third, there is considerable evidence to show that the producer of new technology is unable to appropriate all the gains. The public good nature of knowledge results in intra- and inter-industry R&D spillovers. This implies that the social rate of return to R&D investment exceeds the private rate of return. Thus governments should fund R&D activity and not leave it entirely to the private sector. Finally, ASEAN countries should continue to upgrade the skill sets of their workforce. An educated workforce is a necessary prerequisite for the production and absorption of new technology.
Acknowledgements In general, our work leads us to caution those who would describe a country’s competitive advantage based on any one indicator. The various measures of technological capability that we have presented for the ASEAN nations lead us to the following broad conclusions. First, regardless of the measure of technology employed, ASEAN countries have considerable ground to cover before they can rival the technological capabilities of developed countries. They are net importers of high-tech manufactures and net exporters of low-tech manufactures. Second, within ASEAN, Singapore is clearly the technological leader. Convergence in export shares of high-tech manufactures is occurring across countries and Singapore has made the greatest gains in the catch-up game over the 1980–1990 period. Furthermore, export shares of high-tech manufactures are not converging within ASEAN and Singapore has increased its lead over the other countries. Fourth, compared to developed countries, the level and rate of growth of TFP is low in ASEAN countries. Finally, the U.S. is the most productive country in the world, at both the economy-wide level and at the manufacturing level. Therefore, based on the evidence provided, the policy prescriptions for enhancing the technological
21
See Nelson and Pack (1995), p. 8.
An earlier version of this paper was presented at the 21st ASEAN-Japan Businessmen’s Meeting, 8–10 November 1995, Kobe, Japan, by A. Lall. The authors wish to thank an anonymous referee for his/her perceptive comments.
REFERENCES Arrow, K. J. (1994) The production and distribution of knowledge. In The Economics of Growth and Technical Change: Technologies, Nations, Agents, eds G. Silverberg and L. Soete, Chapter 2. Edward Elgar, Brookfield, VT. Fagerberg, J. (1994) Technology and international differences in growth rates. Journal of Economic Literature 32, 1147–1175. Hobday, M. (1995) Innovation in East Asia: The Challenge to Japan. Edward Elgar, Brookfield, VT. Hobday, M. (1994) Technological learning in Singapore: a test case of leapfrogging. The Journal of Development Studies 30, 831–858. Kim, J. -I. and Lau, L. J. (1994) The sources of economic growth of the East Asian newly industrialized countries. Journal of the Japanese and International Economies 8, 235–271. Krugman, P. (1994) The myth of Asia’s miracle. Foreign Affairs 73, 62–78. Lall, A., Tan, R. and Chew, S.B. (1996) Total factor
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productivity growth experience of Singapore. In Economic Policy Management in Singapore, ed. C. Y. Lim, Chapter 1. Addison-Wesley. National Science and Technology Board (1993) National Survey of R&D in Singapore. NSTB, Singapore. Nelson, R. R. and Pack, H. (1995) The Asian Growth Miracle and Modern Growth Theory, mimeo. Nelson, R. R. and Rosenberg, N. (1993) Technical innovation and national systems. In National Innovation Systems: A Comparative Analysis, ed. R. R. Nelson, Chapter 1. Oxford University Press, New York. Patel, P. and Pavitt, K. (1995) Patterns of technological activity: their measurement and interpretation. In Handbook of the Economics of Innovation and Technological Change, ed. P. Stoneman, Chapter 2. Blackwell, Cambridge, MA. Stoneman, P. (ed.) (1995) Handbook of the Economics of Innovation and Technological Change. Blackwell Publishers, Cambridge, MA. UNESCO (1994) Statistical Yearbook. UNESCO, Paris. UNIDO (1992) Yearbook of Industrial Statistics. UNIDO, Vienna. Wolff, E. N. (1994) Productivity growth and capital intensity on the sector and industry level: specialisation among OECD countries, 1970–88. In The Economics of Growth and Technical Change:
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Technologies, Nations, Agents, eds G. Silverberg and L. Soete, Chapter 8. Edward Elgar, Brookfield, VT. World Bank (1995) World Tables. Johns Hopkins University Press, Baltimore, MD. World Bank (1993) The East Asian Miracle: Economic Growth and Public Policy. Oxford University Press, New York. Young, A. (1992) A tale of two cities: factor accumulation and technical change in Hong Kong and Singapore. In NBER Macroeconomics Annual 1992, eds O. J. Blanchard and S. Fischer. MIT Press, Cambridge, MA. Yu, G. (1993) Issues in protection of intellectual property rights in ASEAN countries from an International perspective. Paper published at the ASEAN Roundtable, August 1995, Singapore. Ashish Lall holds a Ph.D. in economics from Carleton University in Ottawa, Canada and has been a lecturer in economics at Nanyang Technological University in Singapore since 1993. Prior to that he worked in Canada for Canada Post, The Royal Commission on National Passenger Transportation and for a major consulting firm. He has published various articles on deregulation, competition policy, multilateral trade policy and productivity and technological change and has spoken at numerous academic and business events in South-East Asia and Japan. Alan Jones holds a masters degree in economics from Carleton University in Ottawa, Canada. He has been a member of Industry Canada and the federal government of Canada for the past thirteen years. He is currently involved in research that pertains to the service economy of Canada. He has a previous publication in the Service Industries Journal.
Technovation, 18(4) (1998) 263–274 1998 Elsevier Science Ltd. All rights reserved Printed in Great Britain 0166-4972/98 $19.00 + 0.00
A comparative record of technological capability in ASEAN countries Alan Jones Industry Canada, Ottawa, Ontario, Canada K1A 0H5 Ashish Lall Nanyang Technological University, Nanyang Business School, Room S3-B1A-04, Singapore, Singapore 639798
Abstract The rapid economic growth in newly industrializing countries (NICs) over the past decade has been impressive. However, the ability of these countries to sustain high growth in the future has come under question repeatedly. A number of measures are used in this paper to assess the state of technology in the ASEAN and to draw comparisons with a select group of developed countries. Productivity trends in ASEAN and other countries are examined first due to the intimate relationship between technology and productivity. While popular measures of technological capability, such as the number of R&D personnel and expenditures, are used, the focus is on trade in manufactured goods classified by R&D intensity. In the case of the ASEAN, the evidence suggests that they are net importers of technology and have yet to develop strong domestic R&D capabilities. ASEAN countries have considerable ground to cover before they can rival the technological capabilities of developed countries. Policy prescriptions for enhancing the technological capabilities of ASEAN countries are presented at the conclusion. 1998 Elsevier Science Ltd. All rights reserved
1. INTRODUCTION The rapid economic growth that has been witnessed in newly industrializing countries (NICs) over the past decade has been impressive. However, the ability of these countries to sustain high growth in the future has come under question repeatedly. In the neo-classical framework, economic growth is accomplished through some combination of the accumulation of the factors of production and total factor productivity
(TFP) growth. Yet in this framework, growth that relies only on the accumulation of factors of production cannot be sustained due to diminishing returns. Long run economic growth requires TFP growth. Technological change, defined as ‘a new way of doing things’, is the primary enabling factor of productivity growth. This definition obviates the need to make distinctions between concepts such as process
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innovation and product innovation. The former relates to the use of new production processes with the products remaining unchanged, while the latter refers to the introduction of new products. This simple definition accommodates the ‘Schumpeterian trilogy’ of invention, innovation and diffusion.1 While invention involves pushing out the existing technological boundaries, innovation and diffusion refer to the application and adoption of existing technology. All activities in the trilogy can be thought of as representing an improvement in technology. The definition also encompasses advancements in both science and technology. From the view point of economics, an important difference between the two is that the benefits from the former are available to all, whereas in the latter case some or all information may be proprietary. Arrow’s (Arrow, 1994) interpretation, that technology is information or knowledge, also fits this definition. Clearly, doing things in a new way requires information. Since technology is typically embodied in both final and intermediate goods, improvements in technology benefit both consumers and producers. Consumers benefit directly from technological change that increases product variety or introduces new products. Consumer welfare can also be enhanced by technologies that either reduce costs or result in time savings. For example, consumer welfare may be increased as a result of new technologies that improve the energy efficiency of consumer durables (e.g. major appliances, automobiles and homes) and reduce energy bills. Time savings may result from the introduction of intelligent transportation systems which reduce commuting times and therefore increase the leisure time of consumers. From the producer’s perspective, a new way of doing things may involve, for example, process changes on the factory floor or computer software upgrades that reduce production costs or improve service quality. In short, firms expect efficiency or productivity gains from improved technology. At the national level, improvements in the productivity of the factors of production resulting from technical advance are a source of higher economic growth and standards of living. The process of technological change and diffusion across countries is both complex and multi-faceted. There are complex feedback mechanisms from diffusion back to invention and innovation, since in many cases, technology improves on an existing pro1 See Stoneman (1995) pp. 3–8 and Nelson and Rosenberg (1993) for details.
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duct. There is also a selection process at work. At each stage of the Schumpeterian trilogy the selection of a given technology may be based on both conscious decision regarding practical matters such as profitability as well as exogenous or chance events. Nor does the ‘best’ technology always ‘win’. Supporters of the concept of the evolution of technological dominance advocate that once a particular technology gets ahead, increasing returns set in that, in some instances, allow it to capitalize on the lead leaving behind a superior technology. Technology, like information, cannot be concealed forever. International diffusion, from leaders to followers, takes place through a variety of mechanisms, including foreign direct investment, joint ventures, licenses, sub-contracting, reverse engineering and overseas education and training. Important in this regard is that technology, or what Arrow calls knowledge, is both an input and an output in the production process. Thus, the development and transfer of new technology requires both producers and users to be ‘skilled’ or educated. Another point of note is that independent R&D and reverse engineering are the most effective means of learning about competitors’ innovations.2 In addition, though imitation costs, on average, account for 70% of the costs of innovation, only a small part of imitation costs are for the purchase of protected intellectual property.3 Finally, barriers to imitation arise from the high costs of accumulating tacit knowledge, rather than from the withholding of information. In ASEAN4 countries, factor accumulation has played an important role in the process of technological change through typically very high savings rates. Hence, growth in these countries has been driven primarily by capital accumulation. Of late, however, governments of some ASEAN countries are making a concerted effort to attract foreign firms to establish R&D facilities in ASEAN and to promote the R&D activities of domestic firms. In view of this policy shift, this paper seeks to assess the current technological capability of ASEAN countries. The following section presents the manner in which we will measure and assess the state of technology in
2 Compared to licensing for example. See Table 2.2 in Patel and Pavitt (1995). 3 At p. 8, Patel and Pavitt (1995) cite the work of Mansfield. 4 The Association of South East Asian Nations (ASEAN) comprises Indonesia, Malaysia, Singapore, Thailand, the Phillippines, Brunei Darussalam Negara and Vietnam. In addition, as of July 1997 ASEAN will also include Laos, Cambodia and Myanmar.
A comparative record of technological capability in ASEAN countries
the ASEAN countries.5 In addition to conventional measures, such as R&D expenditures and persons engaged in R&D, a variety of trade related measures are used, since international trade continues to play a vital role in the economic growth of these countries. We present the empirical evidence of technological change in ASEAN countries based on these measures in the subsequent section and we draw comparisons with a select group of developed countries. Due to the intimate relationship between technology and productivity, productivity trends in ASEAN and other countries are examined first. While popular measures of technological capability, such as the number of R&D personnel and expenditures are used, our focus is on trade in manufactured goods classified by R&D intensity. The analysis is conducted both at the aggregate level and at the commodity level. Cross country comparisons are made within ASEAN countries and between ASEAN and developed countries, such as Japan, Switzerland and the United States, to determine the degree of ‘catch-up’ that has occurred. A concluding section summarizes a number of issues in the debate that surrounds the assessment of the technological capability of countries and provides policy prescriptions for improving productivity and the technological capabilities of ASEAN countries.
2. MEASUREMENT TFP growth, which is intimately related to the process of technological change, measures the productivity of all factors of production. TFP growth also drives long run economic growth. Under the assumptions of constant returns to scale, competitive markets and long run equilibrium, TFP growth is identical to the rate of technical change or the rate of upward shift in the production function over time. Measuring technological change is much more difficult than defining it and the literature is replete with proxy measures. While the boundary between the producers of technology and the user of technology is not always well defined, such a distinction can be useful to aid in the measurement. Producers contribute to the expansion of the technological frontier, while users facilitate catch-up. Common measures of technology usually focus on the activities of the former group. For example, comparisons across industries are often made using indicators such as the number of R&D personnel and/or the expenditures on R&D. The weaknesses of these measures are reflected in the fact that R&D personnel is a stock measure and more representative of the potential capabilities of an industry 5 Due to data limitations, we only cover the ASEAN-5, or Indonesia, Malaysia, Singapore, Thailand and the Phillippines.
or country, rather than its actual contribution to improvement in technology. The latter, expenditures on R&D, is a measure of ‘spend’ and as, an input into the process of technological change, is therefore not indicative of the ‘output’ of R&D effort. Another shortcoming of using R&D personnel and/or R&D expenditure is that it does not account for changes in ‘software’, such as engineering and organizational changes, which may assist in enhancing innovation and productivity.6 The productivity of technology may be measured using the number of patents granted per R&D employee or per dollar of R&D expenditure. The use of patent data, however, can be misleading to the extent that the importance of patenting differs across sectors and the criteria for granting patents differ across countries. Since technology is embodied in both consumer goods and capital goods, trade in commodities classified by R&D intensity is a useful indicator of the state of technology in a country. Imports are important because they are indicative of the ability of a country to use technology-intensive products. In all probability, a country that imports technology-intensive intermediate goods has a workforce that is both skilled and educated enough to use them. Similarly, a country that exports technology-intensive products (both consumer and capital goods) must have the ability to produce or assemble such goods for the international market which is usually more demanding than the domestic market. While exports or export shares of high and medium technology products can be used as indicators of technological performance, the index of revealed comparative advantage (RCA) is a more informative measure. The index is the ratio of the share of exports of a particular commodity in total exports of that country to a similar construct for a reference group of countries, or:
冘 冘 冘冘 Xij/
RCAij =
Xij
i
Xij/
j
i
(1) Xij
j
where Xij is the value of exports of commodity i by country j. This measure provides information on the structure of exports of a country, permitting a ranking of countries based on their comparative advantage. A number greater than unity indicates superior performance relative to the group.
6
We thank an anonymous referee for this observation.
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A second measure of technological performance, revealed comparative trade advantage is presented in equation (2): RCTAij =
Xij ⫺ Mij Xij + Mij
(2)
where Xij is the value of exports of commodity i by country j and Mij is the value of imports of commodity i by country j for the years 1980 and 1990.7 Furthermore, it is useful to appraise changes in the technological capabilities of countries. This is done by constructing an index that indicates a movement up the technology ladder or one that measures unidirectional structural change. The technology ladder index (TLI) is given as: TLIjtt⬘ =
SHjt ⫺ SHjt⬘
冘
SHjt ⫺
j
冘
∀t ⬎ t⬘
TFP growth has been much higher in Japan and the Republic of Korea than in ASEAN countries.8 Table 2 compares the level of productivity of a number of developed countries. In this case the U.S. was the most productive in 1988, not Japan. The manufacturing sector in Japan, however, displays the highest rate of growth of TFP and at the economy-wide level, Japan had the second highest growth rate. Continuation of these trends suggests that higher TFP growth rates in Japan will allow it to catch up to the U.S. While Tables 1 and 2 do not report estimates of the level of TFP for ASEAN countries, it is probable that these levels are lower than in Japan. Table 1 does show that the rate of growth of TFP has been higher in Japan than in the ASEAN countries and further suggests that there is no convergence of productivity levels between Japan and the ASEAN countries.9
(3)
SHjt⬘
j
where SHjt is the share of high R&D intensity exports of country j at time t. The TLI is the change in the share of high R&D intensity exports of a country over any given time period, relative to that of a reference group of countries. Two additional direct measures of catch-up in export shares of high-tech manufactures are also calculated. The first is the distance of any particular country from the leader, or, for any given year, the difference between high-tech export share of the leader and that of the country in question. The second is the change in the distance measure described above, between any two time periods.
3. EMPIRICAL EVIDENCE Average annual rates of growth of TFP for select ASEAN and other countries over the period 1960– 1990 are presented in Table 1. It can be seen that
Kim and Lau (1994) also reach the conclusion that technical advance has been significant for G-5 countries, but not for the East Asian NICs. Using both growth accounting and econometric methods they show that the contribution of TFP to economic growth is higher for G-5 countries than for NICs. The authors conclude that “the hypothesis of zero technical progress can be rejected for G-5 countries but not for the East Asian NICs”.10 They also compare productive efficiency over time and across countries by providing each country with the measured U.S. endowment of labour and capital and trace the evolution of the resulting output over time. They found that the output efficiencies of Japan, France, West Germany and the U.K. clustered around 50–70%, while the four NICs had output efficiencies of only 20% of that of the U.S. By 1990, the G-5 were catching up to the U.S., but the NICs fell to 14% of the output of the U.S. They conclude that “the empirical evidence does not appear to support the hypothesis of convergence in technology, i.e. given the same inputs, different countries will over time produce increasingly similar levels of real output.”
TABLE 1. Average annual percentage rate of growth of total factor productivity, 1960–1990 Country Indonesia Malaysia Singapore Thailand Republic of Korea Japan
High estimate 1.25 1.08 1.19 2.50 3.10 3.48
Low estimate ⫺ 0.80 ⫺ 1.34 ⫺ 3.01 0.55 0.24 1.43
Source: World Bank (1993) Table A1.2.
7 Other than being a nominal magnitude that is affected by movements in both prices and exchange rates, this measure does not provide any indication of the magnitude of trade and is scale invariant.
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8 These are the results from a sensitivity exercise. Briefly, the low estimates are the result of a higher weight being accorded to capital inputs. Since capital accumulation is higher in ASEAN, giving a greater weight to capital increases the contribution of capital to economic growth and therefore reduces the importance of TFP as an explanatory variable. The greatest negative impact occurs for Singapore, since it has one of the highest rates of capital accumulation in the world. 9 See Young (1992) for a comparison of TFP growth in Singapore and Hong Kong. His results indicate that the contribution of TFP growth to growth in output is minimal for Singapore, whereas this is not the case for Hong Kong. 10 See Kim and Lau (1994), Tables 3.1 and 7.2; in addition Footnote 19 on page 249 indicates that for the G-5 countries, the hypothesis of zero technical change is rejected at “almost any reasonable level of significance”. Thus the rejection is decisive.
A comparative record of technological capability in ASEAN countries
TABLE 2. G-7 countries—total factor productivity, 1979–1988 Country
Economy-wide TFP level in 1988
United States Japan Germany France Canada United Kingdom
Manufacturing sector
Average annual % growth rate of TFP 1979–1988
100 87 78 87 83 74
0.41 1.25 0.57 1.07 ⫺ 0.03 1.38
TFP level in 1988
Average annual % growth rate of TFP 1979–1988
100 *91 62 65 *66 56
1.92 3.71 0.10 0.57 0.25 2.49
Note: *1987 value; Source: Wolff (1994) Table 8.3.
TABLE 3. Scientists and engineers engaged in R&D per 1000 of labour force Country
Year
Number
Japan Switzerland United States Republic of Korea Brunei Darussalam* Indonesia Malaysia Philippines Singapore Thailand Viet Nam
1992 1989 1988 1992 1984 1988 1988 1984 1987 1991 1985
11.2 5.1 7.9 4.5 116 0.5 0.8 0.2 2.7 0.3 0.7
Note: *Actual number of scientists and engineers is reported for Brunei; Source: UNESCO (1994) Table 5.3 and World Bank (1995).
Table 5 shows that Singapore continued to lag behind other NICs such as the Republic of Korea, and developed countries such as Japan and the U.S. Japan spends approximately twice that of Singapore on R&D, it has twice the number of R&D personnel and the share of R&D expenditures in GDP is twice that of Singapore. Tables 6–16 provide values for the trade measures outlined in the previous section and derived using data on trade in manufactured goods (the goods are grouped according to high, medium and low R&D intensity11).
Singapore has from 3 to 10 times more scientists and engineers engaged in R&D per 1000 workers than other ASEAN countries (Table 3). Intellectual property rights statistics reported in Table 4 supplement this picture. In the area of trademarks and patents, the number granted in Singapore are comparable to those in some developed countries and substantially higher than those in other ASEAN countries. However,
Each country’s revealed comparative trade advantage (RCTA) for the years 1980 and 1990 is presented in Table 6. It is apparent that on average, ASEAN countries as well as the Republic of Korea were net importers of high-tech and medium-tech goods and net exporters of low-tech goods, while the opposite was true for developed countries such as Japan, Switzerland and the U.S. However, all Asian countries (with the exception of Indonesia) registered an increase in the ratio of net exports to total trade in
TABLE 4. Intellectual property statistics, 1993
TABLE 5. Research and development indicators—comparative
Country
Trademark registrations effected
Patents granted
Country (year)
GERD per RSE (thousands of USD)
RSE per 10 000 of labour force
GERD as a percentage of GDP
93.2 70.25
40.54 47.31
1.12 2.17
194.63 249.3 162.61
80.72 74.74 69.89
2.72 2.51 2.72
Per 10 000 of labour force Brunei Darussalam Malaysia Singapore Thailand Viet Nam Republic of Korea Germany Japan Switzerland United States
922 3.9 55.1 2.4 2.4 13.2 5.1 37.7 55.3 6.5
0 1.7 10.5 0.1 0.0 5.8 8.2 21.0 64.5 7.9
Singapore (1993) Republic of Korea (1992) Japan (1992) Switzerland (1992) United States (1991)
Source: National Science and Technology Board (1993).
11
Notes: *Actual number of trademarks and patents is reported for Brunei; all countries—labour force data are provisional. Source: Yu (1993) and World Bank (1995).
All data tables are based on Yearbook of Industrial Statistics, UNIDO (1992). UNIDO classifies goods into three categories, but does not define R&D intensity. The latter usually refers to expenditure on R&D within any particular sector.
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TABLE 6. Revealed comparative trade advantage (ratio of net exports to total trade) Country
Year
R&D intensity of manufactures High
Indonesia Indonesia Malaysia Malaysia Philippines Philippines Singapore Singapore Thailand Thailand Republic of Korea Republic of Korea Japan Japan Switzerland Switzerland United States United States
1980 1990 1980 1988 1980 1988 1980 1990 1980 1990 1980 1990 1980 1990 1980 1991 1980 1990
⫺ ⫺ ⫺ ⫺ ⫺ ⫺ ⫺ ⫺ ⫺ ⫺ ⫺ ⫺
0.85 0.84 0.24 0.09 0.74 0.36 0.08 0.01 0.64 0.38 0.33 0.14 0.39 0.44 0.29 0.22 0.32 0.11
Medium ⫺ ⫺ ⫺ ⫺ ⫺ ⫺ ⫺ ⫺ ⫺ ⫺ ⫺ ⫺
0.77 0.74 0.39 0.29 0.70 0.37 0.20 0.12 0.43 0.51 0.06 0.03 0.73 0.62 ⫺ 0.05 0.00 0.03 ⫺ 0.22
Low ⫺ 0.27 0.27 ⫺ 0.03 0.16 0.15 0.02 0.12 0.08 ⫺ 0.05 0.11 0.39 0.32 0.19 ⫺ 0.22 ⫺ 0.38 ⫺ 0.30 ⫺ 0.21 ⫺ 0.34
Source: UNIDO (1992); calculated using nominal US dollar value of exports and imports.
high-tech goods (the opposite is true for Switzerland and the U.S.). Therefore, while ASEAN countries continued to be net importers of high-tech goods, net imports declined (and net exports increased) over the decade in all countries except Indonesia. Within the group of five ASEAN countries, Singapore had a revealed comparative advantage (RCA) in exports of high-tech manufactures in both 1980 and 1990 (Table 7). Malaysia led the group in mediumtech products in 1980, but by 1990 Singapore had also assumed a number one position in this group as well. With its declining RCA in low-tech exports and increase in both medium-tech and high-tech products, Singapore moved up the technology ladder over the decade. In 1980, the Philippines led the group at TABLE 7. Index of revealed comparative advantage, ASEAN-5 Country
Year
R&D intensity of manufactures High
Indonesia Indonesia Malaysia Malaysia Philippines Philippines Singapore Singapore Thailand Thailand
1980 1990 1980 1988 1980 1988 1980 1990 1980 1990
0.24 0.10 1.28 1.13 0.28 0.60 1.29 1.34 0.54 0.63
Medium 0.83 0.54 1.17 0.92 0.51 1.03 1.03 1.14 1.15 0.97
Low 1.29 1.77 0.86 0.95 1.38 1.25 0.90 0.72 1.09 1.25
Source: UNIDO (1992), calculated using on nominal USD value of exports.
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exporting low-tech manufactures, followed by Indonesia. The two countries exchanged positions in 1990. Table 8 shows that, compared to the Republic of Korea and developed countries (Japan, Switzerland and the U.S.), ASEAN countries are below average. In 1980, Switzerland was the best at exporting hightech manufactures, followed by the U.S. By 1990, the U.S. assumed the number one position in this commodity group, followed closely by Singapore. Japan was the best at exporting medium-tech products in both 1980 and 1990. It is noteworthy that over the period 1980–1990, all Asian countries with the exception of Indonesia registered an increase in the RCA index for high-tech manufactures. The reverse is true for the leaders, Switzerland and the U.S. This result suggests that export shares of high-tech manufactures may be converging. Though the index of RCA is scale invariant, an examination of the nominal values of high-tech exports (Table 9) leads to conclusions similar to those that were derived from the previous two tables. In 1990, the share of high-tech exports in total manufacturing industry exports was highest for the U.S., that of medium-tech exports was the highest for Japan, and Indonesia had the highest low-tech export share of all countries. In addition, the U.S. had the highest nominal value of high-tech exports and Indonesia, the lowest. More interesting is the fact that even though the nominal value of high-tech exports of the U.S. was about 6.5 times that of Singapore, the share of high-tech exports in total manufacturing industry exports of Singapore (42.4%) was just half a percentTABLE 8. Index of revealed comparative advantage, ASEAN-5 and selected countries Country
Year
R&D intensity of manufactures High
Indonesia Indonesia Malaysia Malaysia Philippines Philippines Singapore Singapore Thailand Thailand Republic of Korea Republic of Korea Japan Japan Switzerland Switzerland United States United States
1980 1990 1980 1988 1980 1988 1980 1990 1980 1990 1980 1990 1980 1990 1980 1991 1980 1990
0.16 0.09 0.88 0.98 0.19 0.52 0.88 1.16 0.37 0.55 0.43 0.63 0.72 0.91 1.48 1.14 1.25 1.17
Medium 0.41 0.28 0.58 0.48 0.25 0.54 0.51 0.60 0.57 0.51 0.46 0.65 1.24 1.36 0.93 0.98 0.97 0.90
Low 2.48 3.41 1.65 1.82 2.67 2.40 1.74 1.38 2.11 2.40 2.19 2.07 0.92 0.58 0.68 0.82 0.82 0.91
Source: Calculated using nominal USD value of exports from UNIDO (1992).
A comparative record of technological capability in ASEAN countries
TABLE 9. 1990 percentage shares of manufacturing industry exports Country
Indonesia Malaysia* Philippines* Singapore Thailand ASEAN-5 Republic of Korea Japan Switzerland* United States
R&D intensity of manufactures
High
Medium
Low
3.3 35.7 19.0 42.4 20.0 31.5 23.1 33.1 41.7 42.9
10.9 18.5 20.6 22.9 19.5 20.1 24.9 52.3 37.7 34.3
85.8 45.8 60.4 34.7 60.5 48.4 52.0 14.7 20.7 22.8
Value of high-tech exports USD mill.
394 4827 708 21 099 3605 30 632 14 496 92 937 23 743 134 388
Note: *Malaysia and Philippines–1988 data. Switzerland–1991 data. Source: UNIDO (1992); calculated using nominal USD value of exports.
age point lower than the same measure for the U.S. (42.9%). The more striking result is that high-tech exports account for a higher proportion of total manufacturing industry exports of Malaysia (35.7%) than of Japan (33.1%). Table 9 also shows that among the group of ASEAN-5, Singapore has the highest value of high-tech manufactures exports and the highest export share. In 1990, Singapore accounted for approximately two-thirds of ASEAN-5 high-tech exports. Indonesia had the highest share of low-tech exports and the lowest nominal value of high-tech exports. The index of movement into high-tech exports (TLI) is calculated according to equation (3) and presented in Table 10. Once again Singapore led the group of ASEAN-5 followed by the Philippines.12
TABLE 11. Distance from export share of the leader in high R&D intensity exports, ASEAN-5 Country Indonesia Malaysia Philippines Singapore Thailand
1980 0.1933 0.0005 0.1852 0.0000 0.1383
1990
Change
0.39 *0.07 *0.23 0.00 0.22
0.20 0.07 0.05 0.00 0.09
Note: *1988 data. Source: UNIDO (1992), calculated using nominal USD value of exports.
The two countries maintained their rank as the group is expanded to include the Republic of Korea, Switzerland, Japan and the U.S. Therefore, as in the case of Table 7, the results suggest a movement up the quality ladder in manufacturing over the period 1980– 1990, with the convergence in high-tech export shares being the greatest for Singapore, while Indonesia fell behind. Tables 11 and 12 provide a more direct measure of catch-up in export shares of high-tech manufactures. They present both the distance of any particular country from the leader (the difference between high-tech export share of the leader and that of the country in question) and the change in the distance over the period 1980–1990. Table 11 shows that within the ASEAN-5, Singapore was the leader in both 1980 and 199013 and has increased its lead over its ASEAN neighbours. Thus with the ASEAN-5 there is no convergence. This conclusion changes as the group is expanded once again (Table 12). All Asian countries, with the exception of Indonesia, are catching-up to the leading developed countries. Singapore again has been most effective at closing the gap as its high-tech
TABLE 10. Index of movement into high R&D intensity exports Country Indonesia Malaysia* Philippines* Singapore Thailand ASEAN-5 Republic of Korea Japan Switzerland* United States
ASEAN-5
All countries
⫺ 0.09 0.92 1.05 1.42 0.77 – – – – –
⫺ 0.12 1.26 1.44 1.96 1.06 1.38 1.20 1.42 0.16 0.96
Notes: *Malaysia and Philippines–1988 data. Switzerland–1991 data. The index is the change in the share of high R&D intensity exports of a country over the years 1980–1990 relative to the reference group of countries, ASEAN-5 or all countries in the table. Source: UNIDO (1992), calculated using nominal USD value of exports.
TABLE 12. Distance from export share of the leader in high R&D intensity exports, all countries Country Indonesia Malaysia Philippines Singapore Thailand ASEAN-5 Republic of Korea Japan Switzerland United States
1980
1990
0.36 0.16 0.35 0.16 0.30 0.22 0.28 0.21 0.00 0.06
0.40 *0.07 *0.24 0.00 0.23 0.11 0.20 0.10 **0.01 0.00
Change 0.04 0.09 0.11 0.16 0.07 0.10 0.09 0.11 0.01 ⫺ 0.06 ⫺ ⫺ ⴚ ⫺ ⫺ ⫺ ⫺
Notes: *1988 data, **1991 data. Source: UNIDO (1992), calculated using nominal USD value of exports.
12
This is interesting because not too long ago, the Philippines was known as ‘sick man of ASEAN’ due to its low economic growth compared to other ASEAN members.
13
Therefore the distance from the leader is zero for Singapore in both 1980 and 1990.
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TABLE 13. Index of revealed comparative advantage for high R&D intensity manufactures, 1990 Country
Indonesia Malaysia* Philippines* Singapore Thailand Republic of Korea Japan Switzerland United States SITC 51 52 53 54 57 59 72 73 86
Standard International Trade Classification (SITC) code 51
52
53
54
57
59
72
73
86
0.2 0.2 0.7 0.6 0.1 0.4 0.7 1.7 1.3
na 0.0 3.3 4.7 na 0.9 0.1 0.0 1.6
0.4 0.1 0.0 0.5 0.2 0.3 0.6 3.6 0.6
0.1 0.1 0.1 0.3 0.1 0.1 0.2 4.8 0.9
0.0 0.0 1.7 0.4 0.0 0.2 0.0 0.3 1.7
0.2 0.6 0.4 0.8 0.5 0.1 0.5 1.5 1.3
0.1 3.0 1.5 2.1 1.1 1.9 1.8 0.9 1.2
0.1 0.1 0.0 0.2 0.1 0.6 1.6 0.1 1.2
0.1 0.3 0.1 0.7 0.4 0.4 1.8 3.3 1.2
Product group Chemical elements and compounds Mineral tar etc. Dyes, tanning, colouring products Medicinal, pharmaceutical products Explosives, pyrotechnic products Chemical materials n.e.s. Electrical machinery Transport equipment Instruments, watches, clocks
Notes: *1988 data. Scores are based on a reference group of 43 countries according to the above groups. Source: UNIDO (1992).
export share moved to only half a point behind that of the U.S. in 1990.14 Tables 13–16 present trends in high-tech exports at a more detailed level. Table 13 presents indices of RCA for nine commodity groups at the 2-digit SITC level for 1990. All nine commodity groups are classified as high R&D intensive products.15 The reference group against which comparisons are made consists of 43 countries. Developed countries led the group of nine countries in seven out of nine high-tech products. Switzerland took the lead in chemical compounds, dyes and colouring products, pharmaceuticals and instruments. The U.S. had the highest RCA in chemical materials and explosives (the Philippines shared the lead in the latter). Japan led the group in transportation equipment and Singapore led in mineral tar and electrical machinery. Tables 14 and 15 identify the commodity for which each of the nine countries had the highest RCA for the years 1980 and 1990, respectively. In other words, they show the export strength of each country or the commodity with the highest index of RCA irrespective of its R&D intensity. In Table 14, Singapore and Switzerland are shown to have the highest revealed comparative advantage for high-tech goods, mineral 14
Due to rounding, Table 11 indicates that both the U.S. and Singapore have the same high-tech export share. However, as is evident from Table 8, Singapore is marginally behind the U.S. 15 Transport equipment is a mix of medium-tech (automobiles) and high-tech (aircraft engines).
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tar and pharmaceuticals, respectively. The U.S. had an advantage in the medium-tech good fertilizer, while the export strength of all other countries, including Japan, lay in low-tech goods. In 1990, Japan moved to high-tech products such as instruments and electrical machinery and Singapore moved to petroleum products, a low-tech product. The export strengths of other countries were more or less unchanged in 1990. Table 16 presents indices of revealed comparative advantage for seven high tech commodity groups in the ASEAN-5 countries. In 1990, Singapore emerged as the leader in five of the seven, while the Philippines led in chemicals and Malaysia led in electrical products. Singapore’s technological superiority in ASEAN is confirmed at the disaggregated level.
4. CONCLUSIONS AND POLICY IMPLICATIONS The literature on technology gaps suggests that technological differences across countries are reflected in gaps in productivity levels. Consequently, national technological activities are expected to be correlated with productivity. Fagerberg (1994) found, in a large sample of developed and newly industrializing countries that, “the tendency toward convergence across countries in productivity levels was parallelled by a similar tendency for levels of R&D and patenting activity”.16 The evidence that we have provided 16
See Fagerberg (1994), p. 1161.
A comparative record of technological capability in ASEAN countries
TABLE 14. Product with highest index of revealed comparative advantage, 1980 SITC 2 4 4 52 0 83 67 54 56
Product group
Country
RCA index
Simply processed materials Animal, vegetable oils, fats Animal, vegetable oils, fats Mineral tar etc. Food products Travel goods etc. Iron and steel Medicinal, pharmaceutical products Fertilizers, manufactured
Indonesia Malaysia Philippines Singapore Thailand Republic of Korea Japan Switzerland
R&D intensity
11.7 20.5 21 24.7 5.3 9.6 2.2 4.8
United States
Low Low Low High Low Low Low High
2
Medium
Notes: Based on a reference group of 43 countries. Source: UNIDO (1992). TABLE 15. Product with highest index of revealed comparative advantage, 1990 SITC 63 4 4 332 83 83 72 86 54 56
Product group
Country
RCA index
R&D intensity
Wood, cork manufactures n.e.s. Animal, vegetable oils, fats Animal, vegetable oils, fats Petroleum products Travel goods etc. Travel goods etc. Electrical machinery Instruments, watches, clocks Medicinal, pharmaceutical products Fertilizers, manufactured
Indonesia Malaysia* Philippines* Singapore Thailand Republic of Korea Japan Japan Switzerland
35.8 24.1 19.2 7.6 5.8 8.5 1.8 1.8 4.8
Low Low Low Low Low Low High High High
United States
2
Medium
Notes: *1988 data; based on a reference group of 43 countries. Source: UNIDO (1992). TABLE 16. Index of revealed comparative advantage in high R&D intensity manufactures, ASEAN-5, 1990 Country
Standard International Trade Classification (SITC) code 51
Indonesia Malaysia* Philippines* Singapore Thailand SITC 51 53 54 59 72 73 86
0.4 0.4 1.4 1.1 0.2
53
54
59
2.5 0.8 0.0 3.3 1.7
0.7 1.4 0.7 2.7 0.7
0.5 1.4 1.0 1.9 1.2
72 0.1 2.3 1.2 1.6 0.8
73 1.0 1.3 0.5 2.9 1.2
86 0.6 1.7 0.3 3.8 2.1
Product group Chemical elements & compounds Dyes, tanning, colouring products Medicinal, pharmaceutical products Chemical materials n.e.s. Electrical machinery Transport equipment Instruments, watches, clocks
Notes: *1988 data; some product groups are excluded due to incomplete data. Source: UNIDO (1992), calculated using nominal USD value of exports.
appears, at first glance, to concur. For example, Tables 1 and 2 showed that the U.S. had the highest level of TFP, while TFP growth is highest in Japan. The trade-related measures that we presented also support the lead position of the U.S. ASEAN countries, on the other hand, have a poor record in this regard, though, as is evident from Table 1, this conclusion depends on the nature of the weights used in aggregation.
Hobday (1994) also raises a number of relevant issues in attempting to explain Singapore’s poor TFP growth performance given that country’s technological edge over other ASEAN countries. He states17:
17
Hobday (1994), p. 835.
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In contrast with its strong supply of technicians and production engineers Singapore lags behind other countries in the supply of research engineers and scientists. In 1990 Singapore had around 28 research engineers and scientists per 10 000 workers (a total of 4300), compared with 87 for Japan, 77 for the US, 44 for Switzerland, 43 for Taiwan and 33 for the Republic of Korea. Similarly, government spending on R&D as a percentage of GDP lags behind many developed countries as well as Taiwan and the Republic of Korea. Hobday argues that although R&D is increasingly becoming a target of Singapore’s technology policy, it has not been the basis for success so far. Instead, Singapore’s success is based on low-cost, high-quality production engineering. As of 1992, “product output in Singapore was advanced and mainstream, but not at the leading edge of experimental technology”.18 Mainstream product design and R&D was carried out by MNCs at their headquarters, rather than in Singapore. This theme is echoed by Kim and Lau (1994) who provide some additional insights into the issue of R&D. They suggest that imported capital goods may be fully priced, thus reflecting amortized R&D and other development costs. The scope for indigenous improvement may be limited because the installed capital goods are likely to be of an ‘off-the-shelf’ variety. They also allude to ‘software’ components such as managerial methods and the institutional environment lagging behind ‘hardware’ in the NICs. Their research also suggests that the importance of indigenous R&D increases as a country moves closer to the technological frontier and that a certain level of R&D is a necessary condition for successful imitation. Thus copying is not enough and to do so also requires indigenous innovation. In the case of the ASEAN, the evidence suggests that they are net importers of technology and have yet to develop strong domestic formatting R&D capabilities. However this should not be surprising, since the assimilation of technology, learning by doing and imitation occurs in stages. In the manufacturing sector, for example, the first stage may require assembly skills and basic production capabilities, whereas the final stage entails competitive R&D capabilities in advanced product/process innovation. The apparent correlation between productivity growth and technological capability (Young, 1992;
Kim and Lau, 1994) must be softened due to a closer look at the trade-related measures. Though a discussion of the sources of economic growth is not central to our paper, a few comments are in order.19 Young (1992) used an old technique to evaluate a new theory—endogenous growth. His work did not support endogenous growth models that are linear in accumulable factors of production, since such models should find higher TFP growth for Singapore than for Hong Kong. Kim and Lau (1994), using more sophisticated econometric techniques, found that TFP growth was low, not only in Singapore, but also in other Asian NICs. Krugman (1994) based his arguments on both these works. More recently, Nelson and Pack (1995) criticized these methods and pointed out that they suffer from identification problems and do not take into account the fact that the weights used in a growth accounting exercise are endogenous. To borrow the terminology of Nelson and Pack (1995), one cannot use an ‘accumulation’ type model to provide ‘assimilation’ type prescriptions. To be fair, since Young (1992) and Kim and Lau (1994) confined themselves to the neo-classical straightjacket, their conclusions are only logical. If there is no TFP growth, diminishing returns must set in. Yet, such analyses are less than informative from either a policy viewpoint or in advancing our understanding of the causal mechanisms behind East Asian growth. Constructing an index of TFP or estimating production functions merely provide a scalar measure of efficiency. They generally assume that technical progress is disembodied and do not take into account the vintage of different type of capital goods. They therefore ignore the complex feedback mechanisms of technology alluded to earlier in this paper and their prescriptive power is poor, since TFP growth is essentially a residual.20 These empirical models and methods cannot lead one to conclude that a particular country should increase investment in R&D, since they do not take into account R&D, and yet these are precisely the type of prescriptions that Kim and Lau provide. We suggest that there are a number of important reasons why we may never know what TFP growth in Singapore really is. First, as is evident from Table 1, the results are very sensitive to the weights used in aggregation. Second, there has been no survey of wealth conducted in Singapore and so all studies rely
19
In the context of Singapore, these papers are discussed in Lall et al. (1996). Interestingly enough, this has not stopped the Singapore government from ‘targeting’ TFP growth. The government has announced a ‘targeted TFP growth’ of 2.5% per annum.
20 18
See Hobday (1994), p. 843 for a more detailed treatment of the stages of product marketing and technology.
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A comparative record of technological capability in ASEAN countries
on either an accounting benchmark capital stock, or one that is ‘maximum likelihood’ as in the case of Kim and Lau. Finally, as Young (1992) pointed out, 47% of the components of the index of industrial production consist of nominal magnitudes. Thus the output measure for the manufacturing sector is a mixture of real and nominal magnitudes and, given that this sector accounts for about a quarter of GDP, it is not clear whether one can even calculate correctly the growth of real output in Singapore. A more plausible story is that of Nelson and Pack (1995) who argue that a country cannot increase capital per worker without learning about new techniques and how to use them, otherwise the marginal return on the new capital will be zero.21 Thus, under the ‘assimilation’ theory, high investment is induced by learning. Clearly, to proponents of this viewpoint, Singapore’s high investment rates are indicative of the amount of learning that has taken place. On the other hand, using the same information in a growth accounting exercise would lead to a small residual because the growth in capital explains a very large amount of the growth in output. The results of our trade-related measures indicate that all ASEAN countries (with the possible exception of Indonesia) have been doing a lot of learning, particularly Singapore.
capabilities of ASEAN countries are clear. First, ASEAN countries should continue their efforts to attract foreign direct investment and qualified personnel. This can be achieved either by economy-wide measures, such as providing tax incentives for the conduct of R&D, or through sector or technology specific incentives, or both. Second, intellectual property laws should be strengthened to further attract foreign providers of technology and to protect domestic inventors and innovators. The recent multilateral agreements on TRIPS (trade related aspects of intellectual property rights) may in fact hasten this process. Third, there is considerable evidence to show that the producer of new technology is unable to appropriate all the gains. The public good nature of knowledge results in intra- and inter-industry R&D spillovers. This implies that the social rate of return to R&D investment exceeds the private rate of return. Thus governments should fund R&D activity and not leave it entirely to the private sector. Finally, ASEAN countries should continue to upgrade the skill sets of their workforce. An educated workforce is a necessary prerequisite for the production and absorption of new technology.
Acknowledgements In general, our work leads us to caution those who would describe a country’s competitive advantage based on any one indicator. The various measures of technological capability that we have presented for the ASEAN nations lead us to the following broad conclusions. First, regardless of the measure of technology employed, ASEAN countries have considerable ground to cover before they can rival the technological capabilities of developed countries. They are net importers of high-tech manufactures and net exporters of low-tech manufactures. Second, within ASEAN, Singapore is clearly the technological leader. Convergence in export shares of high-tech manufactures is occurring across countries and Singapore has made the greatest gains in the catch-up game over the 1980–1990 period. Furthermore, export shares of high-tech manufactures are not converging within ASEAN and Singapore has increased its lead over the other countries. Fourth, compared to developed countries, the level and rate of growth of TFP is low in ASEAN countries. Finally, the U.S. is the most productive country in the world, at both the economy-wide level and at the manufacturing level. Therefore, based on the evidence provided, the policy prescriptions for enhancing the technological
21
See Nelson and Pack (1995), p. 8.
An earlier version of this paper was presented at the 21st ASEAN-Japan Businessmen’s Meeting, 8–10 November 1995, Kobe, Japan, by A. Lall. The authors wish to thank an anonymous referee for his/her perceptive comments.
REFERENCES Arrow, K. J. (1994) The production and distribution of knowledge. In The Economics of Growth and Technical Change: Technologies, Nations, Agents, eds G. Silverberg and L. Soete, Chapter 2. Edward Elgar, Brookfield, VT. Fagerberg, J. (1994) Technology and international differences in growth rates. Journal of Economic Literature 32, 1147–1175. Hobday, M. (1995) Innovation in East Asia: The Challenge to Japan. Edward Elgar, Brookfield, VT. Hobday, M. (1994) Technological learning in Singapore: a test case of leapfrogging. The Journal of Development Studies 30, 831–858. Kim, J. -I. and Lau, L. J. (1994) The sources of economic growth of the East Asian newly industrialized countries. Journal of the Japanese and International Economies 8, 235–271. Krugman, P. (1994) The myth of Asia’s miracle. Foreign Affairs 73, 62–78. Lall, A., Tan, R. and Chew, S.B. (1996) Total factor
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productivity growth experience of Singapore. In Economic Policy Management in Singapore, ed. C. Y. Lim, Chapter 1. Addison-Wesley. National Science and Technology Board (1993) National Survey of R&D in Singapore. NSTB, Singapore. Nelson, R. R. and Pack, H. (1995) The Asian Growth Miracle and Modern Growth Theory, mimeo. Nelson, R. R. and Rosenberg, N. (1993) Technical innovation and national systems. In National Innovation Systems: A Comparative Analysis, ed. R. R. Nelson, Chapter 1. Oxford University Press, New York. Patel, P. and Pavitt, K. (1995) Patterns of technological activity: their measurement and interpretation. In Handbook of the Economics of Innovation and Technological Change, ed. P. Stoneman, Chapter 2. Blackwell, Cambridge, MA. Stoneman, P. (ed.) (1995) Handbook of the Economics of Innovation and Technological Change. Blackwell Publishers, Cambridge, MA. UNESCO (1994) Statistical Yearbook. UNESCO, Paris. UNIDO (1992) Yearbook of Industrial Statistics. UNIDO, Vienna. Wolff, E. N. (1994) Productivity growth and capital intensity on the sector and industry level: specialisation among OECD countries, 1970–88. In The Economics of Growth and Technical Change:
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Technologies, Nations, Agents, eds G. Silverberg and L. Soete, Chapter 8. Edward Elgar, Brookfield, VT. World Bank (1995) World Tables. Johns Hopkins University Press, Baltimore, MD. World Bank (1993) The East Asian Miracle: Economic Growth and Public Policy. Oxford University Press, New York. Young, A. (1992) A tale of two cities: factor accumulation and technical change in Hong Kong and Singapore. In NBER Macroeconomics Annual 1992, eds O. J. Blanchard and S. Fischer. MIT Press, Cambridge, MA. Yu, G. (1993) Issues in protection of intellectual property rights in ASEAN countries from an International perspective. Paper published at the ASEAN Roundtable, August 1995, Singapore. Ashish Lall holds a Ph.D. in economics from Carleton University in Ottawa, Canada and has been a lecturer in economics at Nanyang Technological University in Singapore since 1993. Prior to that he worked in Canada for Canada Post, The Royal Commission on National Passenger Transportation and for a major consulting firm. He has published various articles on deregulation, competition policy, multilateral trade policy and productivity and technological change and has spoken at numerous academic and business events in South-East Asia and Japan. Alan Jones holds a masters degree in economics from Carleton University in Ottawa, Canada. He has been a member of Industry Canada and the federal government of Canada for the past thirteen years. He is currently involved in research that pertains to the service economy of Canada. He has a previous publication in the Service Industries Journal.