I

Ekonomi d.in Kcu.ingan Induncsi.i Volumo XLIII Nnmof 2. 1995

Beyond Total Factor Productivity: Issues in Indonesia's Technological Development

David Ray

Abstrak

Tulisan ini membahas cara-cara mengukur kemajuan teknologi dalam konteks Indonesia. Pendekatan pertama, yaitu pendekatan Neoklasik Growth Accounting (total factor productivity), merupakan cara yang sangat lemah. Ada dua masalah kunci dari pendekatan ini, yaitu: (1) asumsi hahwa teknologi dianggap sebagai input dalam proses produksi yang terpisah dari akumulasi modal fisik dan manusia dan (2) asumsi standar Contant Returns to Scale. Hasilan yang kurang realistis dapat ditemukan dengan tingkat pertumbuhan TFP Singapura dan Malaysia dibanding dengan Indonesia. Menggunukan pendekatan funksi biaya - seperti penyelidikan beberapa tema "New Grotvth" (endogenous growth) dalam pembangunan industri Korea oleh Sengupta (1993) - disimpulkan hahwa sektor industri Indonesia paling banyak didorong oleh penggunaan input fisik dan tenaga kerja yang kurang trampil. Tidak seperti negara-negara Asia lain, peran input teknologi atau pengetahuan dalam proses produksi di Indonesia tampaknya hanya sedikit. Kesimpulan ini didukung oleh 1) penggunaan indeks komposisi teknologi yang dihangun dengan menimhang (weighting) angka ekspor dengan nishah lithanglproduksi; dan 2) nishah ekspor-impor untuk baik golongan industri high-tech maupun medium-high tech yang menunjukkan Indonesia semakin tertinggal dalam perlomhaan regional untuk mengemgangkan industri ekspor yang herhasis teknologi tinggi.

135 Ray

All too often, economists concerned with the economy as a whole have heen willing to treat the economics of ideas as a footnote to the rest of economic analysis - important for understanding some of the details hut not something that changes how we think ahout hig policy questions. A neoclassical model with perfect competition and exogenous technological change continues to frame many if not most, policy discussions of growth and development. Ideas are routinely ignored....[However] in a world with physical limits, it is discoveries of hig ideas (for example, how to make high-temperature superconductors), together with the discovery of million of little ideas (better ways to sew a shirt), that make persistent economic growth possible. Ideas are the instructions that let us combine limited physical resources in 'arrangements that are ever more valuable. Kutipan (Paul Romer, 1992.)

I. INTRODUCTION

The use of technology or ideas (as it is referred to in the above quote) is clearly an important element of a developing country's efforts to industrialise. Cross-country experience in the post-war era shows that the rapid growth in the non-industrialised world have been those countries best equipped to import and effectively use modern forms of foreign technology; and in some cases to develop their own forms or technology compatible with local supply and demand conditions. Given the importance of technology to economic development it is clearly important for the economist to be able to quantitatively assess both the level and growth of technological capacity. There is, however, no clear cut method of quantitatively measuring technology. Technology is a multi• dimensional phenomenon whose compete characteristics can not be captured by the simple inclusion of a proxy variable in a growth equation or production function. Analytical tools available to today's economist provide only illustrative not precise or accurate assessments of a country's technological capacity. Section one of this paper discusses a number of these methods in regards to measuring Indonesian technology capacity. The first method considered is that of the standard Neoclassical growth accounting or Total Factor Productivity (TFP) approach. Due to the highly restrictive and unrealistic assumptions of the Neoclassical model, TFP ~a proxy for technological progress as measured by the residual from a constant returns production function— is found to have little or no economic meaning. The

136 Beyond Total Factor Productivity second method to be discussed uses an important theme from the "New Growth" literature, ie. the increasing returns to scale from the use of non- rival knowledge inputs in the production process; and the final method considered looks at the type of goods the country is exporting. The general result from these two latter approaches is that Indonesia, unlike her regional competitors, is failing to move into more knowledge based production.

II. THE NEOCLASSICAL APPROACH

The method of measuring technological progress most commonly used by economists over the past 3-4 decades is that of the Growth Accounting approach. Such an approach is closely associated with the one-sector neoclassical growth model developed by Solow (1956) and by Swan (1956). One of the attractive features of the growth accounting approach is that it permits the decomposition of economic growth into a number of key determinants. Solow (1957) and Denison (1985), for example, use a growth accounting framework that distinguishes the contributions of labour, capital and exogenous technological progress' to US economic growth. Their approach assumes a standard Cobb-Douglas production function of the form

y =A K^L" a-t-p = 1 ' (1) where A is an index of technology and the exponents on capital and labour sum to unity to ensure constant returns to scale. By differentiating with respect to time to find growth rates and then taking logs we get

y = a + ak + l[i ^ (2) where lower case represent logs. If we assume competitive markets with factors being paid their marginal products then the capital and labour shares correspond with the exponents a and p from (1) respectively, or the coefficients from (2). Most studies using this kind of analysis make the assumption that the exponent on capital is around 0.3 to 0.4 (which implies sharply diminishing returns to capital and therefore downplays the role of

one of the central features of the neoclassical growth model is the assumption that technological progress (the major determinant of growth) is determined by factors outside the model, ie. it is exogenous. This is the key point of departure from the many "New Growth" models which are built upon the premise that technological progress (and therefore growth) is endogenous, ie. determined by the profit seeking behaviour of agents operating within the system. Such behaviour includes investment in human and physical capital, R&D, innovation, etc.

137 Ray capital in the growth process) and 0.6 to 0.7 for the labour share. Fischer (1993) for example, uses 0.4 and 0.6 for the capital-labour share respectively. Using the above information we can write the growth equation and rearranging to get a (the rate of growth of exogenous technology) over to the left band side we get

y = a + (0.4).k + (0.6).l (3)

a = y - (0.4).k - (0.6).1 (4)

The term a is often referred to as the Solow residual, and in this style of growth accounting analyses is interpreted as a measure of total factor productivity (TFP)^, ie. that portion of income growth that cannot be explained by growth in the capital and labour stocks. Using the above methodology Solow (1957) concluded from US time series data over the period 1909 to 1949 that output per worker bad doubled with 87.5% of the increase attributable to TFP (a proxy for technological progress) and the remaining 12.5% due to the increased use of capital. Similar results were arrived at by Denison (1985) using the same neoclassical methodology. The growth accounting approach described above bas also been augmented to include human capital as represented by education enrolments (ed). Mankiw, Romer and Weil (1992) for example define their technology residual as follows where the three growth determinants share equal weights of 0.3333 such that the constant returns condition is maintained.

a = y - (0.333) k - (0.333) I - (0.333) ed

The methods described above appear to represent a simple and effective means of isolating the different determinants of growth (including technological progress). However, as can be seen from table 1, estimates of the growth of the technology residuals using the two approaches make little economic sense.

According to the growth equation as specified in (2), a 1% increase in output growth for exampie, couid be achieved by either a 1% increase in productivity growth, or a 1.4% growth in employment, or by a massive 3.3% increase in the capital stock. Sharply diminishing returns to capital clearly limits the model's ability to account for differences in growth rates across countries. Piosser (1992) notes that for capital accumulation to account for the fact that the US has 20 times the income per capita of Kenya, the capital stock per capita in the US would need to be ahout 8000 times the capital stock in Kenya. However according to Summers and Heston 5.5 data, US capital per worker is only about 26 times that of Kenya sometimes referred to as Multi-factor productivity.

138 Beyond Total Factor Productivity

Table 1 Technology Residuals - Average Growth Rates 1960-1988

Country Solow Residual Mankiw et.al Residual

Singapore -0.38% -0.10% Malaysia 0.12% -0.21% Japan 1.31% 1.64% Indonesia 1.13% 0.21% Thailand 0.62% 0.45% Korea 0.60% 0.41%

(Processed using the data set made available by the World Bank in relation to the series of articles on growth published in the Journal of Monetary Economics 1993 - December). Using the growth of the Solow residual as a proxy for technological progress Indonesia outperforms all the other listed Asian countries, but Japan. Singapore and Malaysia record the lowest rates of technological progress which is surprising given the rapid and successful development of many higher technology industries (particularly electronic) in these two countries over the past three decades. Also surprising is the high rate of TFP growth for Japan. Given Japan's role as a technological leader in the region, ber TFP growth should be less than the "follower" countries. The relocation of many Japanese industries in the 1970s and 1980s which facilitated a degree of technological convergence in the Asian region is clearly not reflected in the above figures. Incorporating the human capital proxy (column 3) reduces the aVerage growth rate of Indonesia's technology residual, however this rate remains higher than that of Singapore and Malaysia.'' Such an approach therefore does little to improve the descriptive ability of the growth accounting model. There are two major problems with the neoclassical growth accounting approach. The first is the idea that technical progress can be treated as a separate input to the production process completely independent of capital and labour stocks or any other variable in the system. Thus technical change is assumed to be off the disembodied exogenous type;^ exogenous in the

such results are similar to the World Bank (1993) which employed a similar approach.

a curious extension of the TFP-growth accoimting approach has heen to explore what determines TFP (or the Solow residual) by regressing it against a number of key endogenous variables (such as education levels, capital intensity, foreign investment, government policy type proxies and so on) - thus exploring what the endogenous determinants are of something assumed to be exogenous. This inconsistent approach

139 Ray sense that it simply descends upon an economy like "manna from heaven"*and is not the direct result of deliberate actions by profit seeking agents. One of the key problems with this approach is that it ignores the economic returns to innovative activity. As argued by Schumpeter (1942) and Schmookler (1966) firms innovate to compete for profits, however this is not reflected within the neoclassical growth model which simply assumes that technical progress is exogenous. On this matter Sbeeban (1993) writes Many successful international firms invest 10-15% of their sales revenue in R&cD; competition hetween firms, and indeed nations, is now more often determined on the hasis of technological excellence than of price competitiveness; the key strategic goals of many successful firms now relate to the development and strategic control of core technology rather than more traditional ohjectives.

Another important implication of the assumption regarding the disembodied exogenous nature of technical progress was that there could be no obvious link between investment (in both human and physical capital) and technical progress; and then through extension of the model, between investment and growth. Clearly technical progress A, in equation (1) is determined by the nature of the physical capital stock (K) and the labour force (L) - ie. technical progress is driven by the accumulation of both physical and human capital. As argued by De Long and Summers (1992,1993) and De Long (1991,1992) technology which is embodied within new capital equipment plays an important role in a country's technological development and therefore its growth rate. In regards to the labour force technology is more likely to be absorbed and/or developed by those countries with higher skill or education levels. The second major criticism of the neoclassical growth accounting approach relates to the standard assumption of constant returns to scale. Many technological inputs, such as a blueprint or some other piece of knowledge, are non rival' by nature and can therefore be used over and

has been employed by many including the World Bank (1993) in their comprehensive study of the high performing Asian economies and Sussongko Suhardjo (1992) in his study of the determinants of technical change in Indonesian engineering industries.

This popular phrase is used by many critics of the neoclassical growth model. Continuing this religious imagery Harcourt (1972) suggests that ".. this disembodied neutral technical progress may be liked to a mysterious manifestation of grace - when two or more, in this case capital and labour, are gathered together in this life, there immediately occurs a rise in total factor productivity."

see eg. Prahaiad and Hamei 1990

non-rival in the sense that an input can be used without preventing others from using it, or yourself from using it at some future point in time. Best exampie in this regard is the knowledge (such as a blueprint or design) of how to make something.

140 Beyond Total Factor Productivity over in the produaion process at little or no marginal cost. Thus if non-rival inputs (such as a design) are used in produrtion we would expea to find increasing, not decreasing returns to scale as output would be increasing at a faster rate than input costs. Thus the impaa of the very thing we are trying to measure might simply be overlooked because of the standard yet restrictive assumption of constant returns. Given such difficulties associated with TFP measurement it could be argued that alternative methods are required if we are to quantitatively assess the technological development of a country' Using the approach outlined above the measure of technology obtained is simply the residual from a constant returns production function (with assumed weights on both capital and labour) whereby that residual - which is assumed to be a proxy for technical progress - is totally independent of human and physical capital accumulation. Given that both human and physical capital play an integral role in a country's technological development the residual defined above should therefore not be defined as a proxy for technical progress.

III. ALTERNATIVE APPROACHES

New Growth Themes. A more realistic treatment of the tecbnology-growtb relationship can be found within the contemporary macroeconomics literature. Collectively known as the "New Growth" theorists, writers such as Romer (1986,1990) Lucas (1988) and Grossman and Helpman (1991, 1994) have suggested that technical progress is endogenous, that is, technological progress is the direa outcome of firm and market level phenomena. Central to much of their work is the idea that investment (in ideas and in both human and physical capital), technical progress and growth are inextricably linked. A crucial feature of many of the "New Growth" models is the notion of non-rival technology. That is, once a blueprint or design bas been created it can be used again at little or no marginal cost. For example the research costs for the design of a new product may be high - depending upon the complexity of the design and by what degree it differs from the existing product. However once the drawings are complete, the design (representing the ideas or knowledge embodied within the produa) can be reproduced at virtual zero or marginal cost on a photocopy machine. Thus as Romer (1990) argues the use of non-rival technology generates non-convexities (increasing returns) in the model. That is, if it is possible to double output

for a more complete critique of the neoclassical growth accounting -TFP approach see Sheehan (1994).

141 Ray by doubling all riyal inputs, tben if non-rival inputs are used - wbicb by definition do not require replicating - increasing returns will be inevitable. Consider tbat case of two input units - one rival (R) and one non-rival (N) - to produce two units of output (Y)

N,R Y,Y

To double output only rival inputs need to be doubled because tbe non-rival input (eg. tbe design) can be used again without replication.

N,R,R ^ y,Y, y, y

Thus three input units can produce four units of output - giving us increasing returns to scale. " This model bas important implications for developing countries in tbat tbey need to make themselves open to- and capable of - importing and adapting modern technologies from tbe industrial countries. Romer (1992) cites tbe case of Mauritius wbicb bas successfully exploited a development strategy tbat consisted almost entirely of trying to make use of ideas tbat already existed in industrial countries by encouraging foreigners to produce there. Another good example is found in tbe recent and successful development of tbe manufacturing industries in tbe Asian NlCs (South Korea, Hong Kong, Singapore and Taiwan). Over tbe past 30 years these countries, tbrougb various ways including reverse engineering, have been able to successfully use a backlog of unexploited foreign technology as a means to develop highly competitive manufacturing export sectors. Sengupta (1991,1993) in an investigation of tbe applicability of "New Growth" theory to South Korea's development experience, found strong evidence in favour of increasing returns in tbe manufacturing export sector tbat was due, in large part, to the use of non-rival knowledge or technology inputs. ' Evidence of increasing returns in tbe Korean manufacturing sector is found by tbe use of tbe following estimated cost function.

InC = 0.168 + 0.797* InY - 0.77 In z R^ = 0.92 where C is total costs, Y is output and z is value added growth wbicb be uses as a proxy for technological progress. Tbe asterisk denotes significant coefficients at tbe one percent level. A value of tbe coefficient on InY wbicb is less than one suggests increasing returns to scale, ie. costs increase at a lower rate than output. In this case total increasing returns are calculated to be 1.25 - tbe inverse of tbe output coefficient. Tbe negative value on Inz, be

142 Beyond Total Factor Productivity argues, is indicative of the cost reducing influence of technological 10 progress . Using the same data set from the Korean manufacturing sector Sengupta (1991) investigates the output elasticities for both rival and non- rival inputs. For this purpose be uses an extended Cobb-Douglas produaion funaion

InY = 4.92* - 0.47 In Rl + 0.16 lnR2 - 0.57 lnR3 + 1.51* InN Rf=0.99 where Rl, R2 and R3 represent capital, energy and materials respeaively - ie. rival goods - and N is a non-rival input measured by labour employed in tbe manufacturing export sector. He notes tbat tbe non-rival good (N) bas a much higher output elasticity than tbe rival goods and in itself exhibits strong increasing returns. This be argues is evidence of tbe key role technology and knowledge (as embodied within labour) have played in tbe seaor's successful development. A similar style of econometric analysis using Indonesian industrial data (1975-1992) produces dramatically different results. As can be seen from Table 2 tbe cost function approach shows tbat tbe nine industrial subseaors (2 digit data) display constant returns to scale or near to it. Slight increasing returns to scale is found in tbe basic metal industries (37) and fabricated metals produas and machinery industries (38). Furtbermore it is only in these two industries tbat technical progress as represented by z bas tbe correa sign (negative) and is significant. Using tbe extended Cobb-Douglas approach as discussed above tbe following equation is estimated InY = -6.57 + 0.41 In Rl - 0.092 In R2 + 0.302 R3 + 0.7 InN (-2.71) (1.59) (-1.12) (1.07) (2.69) n = 18 R^ = 0.992 DW = 1.72 t statistics in parenthesis Tbe key point to note bete is tbe relatively low coefficient on tbe non- rival input (N - as represented by tbe total labour employed in tbe manufacturing sector). Unlike Korea, labour, tbe proxy for non-rival inputs, displays diminishing returns. Although lacking sophistication tbe two approaches described above give general illustration of a manufaauring sector tbat is driven by tbe use of physical inputs and low skilled labour. The lack of technological or knowledge inputs prevents tbe attainment of

similar results were obtained by the author using Singapore industrial data. The estimated cost function In C = 2.699 + 0.813 In Y - 0.016 In z shows a) total increasing returns to be 1.23 and b) the cost reducing influence of technical progress.

143 Ray increasing returns and therefore higher sectoral growth. Export Data. Another useful way to judge the technological deyelopment of a particular country is to examine the type of goods it is exporting and importing. If only the high technology and medium-high technology industry groups"are considered then it is not surprising to find export-import ratios in many deyeloping countries that are less than one. Howeyer as the deyeloping country in question deyelops it owns technological capacity and progressiyely relies less on imported technology based goods, tbe export-import ratios for tbe aboye mentioned technology groups should be increasing oyer time. Tbe two graphs (Graphs 1 and 2) below proyide a comparison in this regard between Indonesia and a four Asian nation ayerage, wbicb includes Malaysia, Korea, Singapore and Taiwan.

Graph 1 & 2

Export-Import Ratios High Technology

1970 1974 1978 1982 1986 1990 1970 1974 1978 1982 1986 1990 Years Yaws Indonesia -^-MKSTavgJ Ulndonasia -^-MKSTavg.l

Oyer tbe past 2 decades tbe grovytb in tbe both tbe high and med-bigb technology export-import ratios for tbe four Asian nations bas been impressiye, particularly in tbe high tecb category. In both categories Indonesia bas shown a dramatic improyement in tbe last few years but from an extremely low base. Neyertbeless Indonesia remains firmly behind ber regional competitors in tbe command of high to medium-bigb technology production. Further eyidence of Indonesia's comparatiye technological backwardness can be found by using an index of technology composition of exports as deyeloped by researchers at tbe Centre for Strategic Fconomic

as defined by OECD (1994) - see table

144 Beyond Total Factor Productivity

Studies (CSES), Victoria Uniyersity in Melbourne, Australia. Their approach is to diyide a country's exports into 22 main industry groups according to their degree of knovyledge intensity as measured by tbe ayerage leyel of R&D expenditure per unit of production in those industry groups for tbe OECD countries taken as a vybole (see Table 2). Tbe highest R&D- production ratios are found in industries such as aerospace (20.2%), computers (12.4%) and electronics (10.8%) whilst tbe lowest are in tbe wood and furniture (0.1%), paper and printing (0.2%) and textiles and clothing (0.2%) industries. Export values are tben weighted using these R&D ratios, summed and rebased to produce an index of technology composition whereby an index value greater than one indicates tbat a country's exports are concentrated in industries with a high R&D intensity whilst a value less than one indicates a concentration in industries with low R&D intensities. Table 3 Index of Technology Composition - Manufacturing Exports

1970 1993 1993 (Excluding Computers and

Indonesia 0.19 0.34 0.24 Malaysia 0.24 1.72 0.47

Korea 037 1.07 0.53 Taiwan 0.57 1.19 0.5 Singapore 0.47 1.79 0.67

)apan 0.80 1-3 0.89 China 0.22 0.58 0.36 Philippines 0.1 0.95 0.33 Thailand 0.15 0.92 0.43

Source: CSES estimates using UN trade data. Using index values for both 1970 and 1993, Table 3 (columns 2 and 3) illustrates the development of technology composition for Asian exports over tbe past two and a half decades. Clearly evident in tbe above figures is tbe dramatic move into more knowledge/R&D based export production for all tbe above mentioned Asian economies, except Indonesia. Tbe most rapid improvers in this regard are Singapore and Malaysia, both of wbicb recording a technology composition index-value in 1993 in excess of 1.7. This compares extremely well with tbe same 1993 index values from a number of advanced western economies such as tbe EEC (0.96), USA (1.52), Canada (0.86), Australia (0.57) and New Zealand (0.21).

this method was developed for particular use in a yet to be published report to the Australian Science and Technology Council on the development of knowledge based industries in Australia and the Asian region

145 Ray

Unlike much of her immediate neighbours, Indonesia bas yet to make any significant moyes into more knowledge intensiye export production. Even tbe Philippines, tbe least successful developing economy in tbe Asian group, and China, Indonesia's most visible competitor in tbe production and export of low technology labour intensive manufacturing, have been able to outperform Indonesia in tbe drive toward higher technology exports. Indonesia's comparative technological backwardness is further illustrated in Crapb 3. wbicb compares Indonesia's technology index" with tbat of a five nation average which includes Singapore, Malaysia, Thailand, Philippines, Korea and Taiwan.

Graph 3

Index of Technology Composition Regional Comparison

" °1970 1973 1976 1979 1982 1985 1988 1991 Year

I — Indonesia — Asian Avg. [

Although starting from a lower base, Indonesia was able to keep pace with ber Asian neighbours throughout tbe 1970s and early 1980s. Howeyer beginning in 1982/83 Indonesia's driye toward higher technology exports loses momentum'^ such tbat by tbe early 1990s, Indonesia's index of technology composition is dramatically lower than tbat of tbe Asian ayerage and, furtbermore, yet to regain tbe high attained a decade before. Another interesting exercise carried out by researchers at CSES was to explore what industries baye driyen Asia's rapid moye into more knowledge based export production. For each of tbe countries listed in Table 1 tbe index of technology composition was again constructed but with each of tbe 22 industry groupings progressiyely excluded. For most of tbe industry groupings their exclusion bad little if no effect upon tbe country's export technology index. Two industries howeyer - tbe computers and electronics

the same graph was also constructed excluding oil and as exports (i.e. industry group 12). However there was no significant change to the development of Indonesia's index of export technology composition. This counters potential criticisms that the increasing trend of the index throughout the 1970s and early 1980s merely reflects the export growth associated with the oil boom.

146 Beyond loidi Factor Productivity industries - stand out as key contributors to tbe development of tbe export tecbnology index. As can be seen in tbe fourth column of table 3., excluding computers and electronics dramatically lowers tbe 1993 index values for all of tbe countries listed - except Indonesia. This suggests tbat tbe computer and electronics industries have played a leading role in tbe development of Asian industrial technological capacity. Graphs 4 to 7 further illustrate tbe importance of tbe two industries to Asian technological development.

Graphs 4, 5, 6 and 7

Indonesia Malavsia

1970 1973 1976 1979 1982 1985 1988 1991 1970 1973 1976 1979 1982 1965 1988 1991 — AI ritanuracturtng » All Manufacturing — Except computers dan aiactronlcs — Excluding Computers and electronics Singapore Taiwan 1.8 I 1 8 1.1 ' 1.2 e 1 0 8 ; o.e I 0.4 - 0.2 1970 1973 1976 1979 1982 1985 1968 1991 1970 1973 1978 1979 1982 1985 1988 1991 - All manuractunng | . Excluding compuf f and alectronica | — AH manuractunng — Excluding computers and electrc

Notice that tbe electronics and computer industries have bad little if no effect upon tbe growth of tbe Indonesian index of tecbnology composition, whilst in tbe other sample countries (Singapore, Malaysia and Taiwan) such industries represent tbe driving force behind tbe technological development of tbe export sector. Given Indonesia's low index value for all manufacturing in 1993, we could conclude tbat Indonesia bas failed to fully benefit from tbe development of local computer and electronic export industries. As discussed earlier in this article making precise measurements .of a country's rate of technological progress can be problematic. It would therefore be a mistake to consider tbe tecbnology index discussed above as an absolute indicator of a country's technological development. It must be remembered tbat tbe index bas been constructed using R&D-production

147 Ray ratios from the OECD countries from the late 1980s. However for any specific country, be it developed or developing, tbe R&D intensity of export production might be quite different to tbat of tbe OECD average reflecting tbe unique conditions of that country at tbat time. Thus we must view tbe index of tecbnology composition purely as a means to make useful cross-country comparisons of technological development. It by no means should be mistaken for measuring tbe actual R&D intensity of export production for a specific country. Nevertheless the index is able to illustrate tbe nature of technological development in an international context. In Indonesia's case, tbe index shows tbat tbe country is falling further and further behind other countries in tbe region in tbe race to develop medium- bigb tecb exports. Civen tbe likelihood of increased regional competition in tbe production and export of low tecb labour intensive manufactures from countries such as China, Vietnam, and India, tbe empirical work associated with tbe latter two approaches discussed above (i.e tbe "New Growth" approach exploring for non-convexities from tbe use of non-rival inputs and tbe export approach using both tbe tecbnology index and import-export ratios) provide strong analytical backing for assertions continually made by Indonesian politicians and economists tbat Indonesian industry must intensify its efforts to "move up tbe technological ladder" if it is to remain internationally competitive in tbe future. Tbe neoclassical TFP approach in tbe meantime, due to its rigid simplicity, provides misleading results and should therefore no longer be regarded as an effective means to measure technological progress.

148 Beyond Total Factor Productivity

BIBLIOGRAPHY

Denison, E.R 1985. Trends in American Economic Growth 1929-1982. Brookings Institution: Washington. Denison, E. F. 1993. The Growth Accounting Tradition and Proximate Sources of Growth, in Szirmai, A., B. Van Ark and D. Pilar (ed.) Explaining Economic Growth: Essays in Honour of Angus Maddison 37-64. Amsterdam: North Holland. Grossman, G., and E. Helpman. 1994. Endogenous Innovation in the Theory of Growth./owma/ of Economic Perspectives 8(1): 23-44. Grossman, G. M., and E. Helpman. 1991. Innovation and Growth in the Global Economy. Paperhack reprint. Cambridge and Londori: MTT Press, 1991, pages xiv, 359. Lucas, R. E. ,. J. 1988. On tbe Mechanics of Economic Development. Journal of Monetary Economics 22 (1): 3-42. Mankiw, N. G., D. Romer, and D. N. Weil. 1992. A Contribution to tbe Empirics of Economic Growth. Quarterly Journal of Economics 107 (2): 407-37. OECD. 1994. Science and Technology Policy: Review and Outlook 1994, OECD, Paris. Piosser, C. 1992. The Search For Growth. Paper prepared for tbe Federal Reserve Bank of Kansas City's conference on Long Term Growth and Long Term Policy, Jackson Hole, Wyoming, August. Prabalad, C.K and Hamel, G. 1990. Tbe Core Competence of tbe Corporation. Harvard Business Review. May-June. Romer, P. M. 1990. Are Nonconvexities Important for Understanding Growth.' American Economic Review 80 (2): 97-103. —. 1986. Increasing Returns and Long Run Growth. Journal of Political Economy 94 (5): 1002-1037. —. 1992. Two Strategies for Economic Development: Using Ideas and Producing Ideas. Paper presented at tbe World Bank Annual Conference on Development Economics. Schmookler, J. 1966. Invention and Economic Growth. Harvard University Press: Cambridge. Schumpeter, J. 1942. Capitalism, Socialism and Democracy. Harper: New York.

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Sengupta, J. K. 1993. Growth in NICs in Asia: Some Tests of New Growth Theory. Journal of Development Studies 29 (2): 342-357. —. 1991. Rapid Growth in NICs in Asia: Tests of New Growth Theory for Korea. Kyife/os 44 (4): 561-579. Sengupta, J. K., and J. R. Espana. 1994. Exports and Economic Growth in Asian NICs: An Economometric Analysis for Korea. Applied Economics 26: 41-51. Sheehan, P. J. 1993. Economic Theory and Economic Strategy: The New Growth Models. Paper delivered at the 21" Conference of Economists, University of Melbourne, July. ' —. 1994. Beyond tbe New Growth Models: Implications for Theory and Practice - Tbe Case of tbe 'East Asia Miracle'. Paper presented at tbe Conference of Economists, Gold Coast, Queenland. September. Solow, R.M. 1956. A contribution to tbe theory of economic growth. Quarterly Journal of Economics. —. 1957. Technical Change and tbe Aggregate Production Function. Review of Economic Studies 39 (August). Summers, R., and A. Heston. 1988. A New Set of International Comparisons of Real Product and Prices: Estimates for 130 Coimtries. Review of Income and Wealth 34: 1-25. Suhardjo, S. 1991. Tbe Impact of Foreign Investment on Technological Change in Indonesian Engineering Industries. Ekonomi dan Keuangan Indonesia. Swan, T. W. 1956. Economic Growth and Capital Accumulation. Economic Record 32 (November). World Bank. 1994. Tbe East Asian Miracle: Economic Growth and Public Policy. Oxford University Press. August.

150 I

Beyond Total Factor Productivity

Cost Function Regressions-Manufacturing Sector

1) LnC = C-t-LnY

2) LnC = C + LnY + LnYgr

Sector tcjuation LnY LnYgr r -squared

Ti lie 1 (77 ZQ 1 0.9899

U.UjD 1 OJ n n7Ai

1 7177 1 01QQ L. -U.UUU40 0.98876 - 1 .Z 1 X.X. 1 .UAyy

n nQQRiii u.UZ JD U.UUJU4 U.UJ JOH 1 "1 1 .UOJO n Q4AQR7 0.954277

U. 1 ODD t 1 n neiR7 U.UA I OZ X. 1 4QQ7 U.7n Q7QRAZ JODAD U.UU4r» 00477/ / 11 0.9529

n17Qftn7 n riAAAi Q U.UU0 007R/ OQJ U.UOOO 1 J 1 J'K'X J n Rl QQd, 1 OAQQ 0.9942 -U.O I J J**

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151 Ray

Techtrology Croup Industry Croup R&D ISIC Industries ratio Code (%) High

1 Aerospace 20.2 3845 Aircraft

2 Computers 12.4 3825 Off, computg, accountg mach 3 Electronics 10.8 3832 Radio, tele, comm eqp, appar 4 Pharmaceuticals 10.3 3522 Drugs + medicines

Medium-High

5 Instruments 4.8 385 Prof, scien, masmg. cnti equ

6 Motor vehicles' 3-5 3843 Motor vehicles

7 Chemicals 3.4 351 Man of indus chemicals 3521 Paints, varnish lacquers 3523 5oan cins nms nerf JKJOtVl, I.III3 IUI LI3, LJd 1, cosm 3529 r"hpmlcal nrodiicts V_lldlll1.al L/IUUUdS nec

8 elec. machinery 3.2 3831 Elec ind mach + apparatus 3833 Elec applncs + housewares 3839 Elec appar + supplies nec

Medium-Low

iviavi II1 Id y 2.1 3821 pnpjnps 4- tiirhinps Uli,,llluX X^ ,UlulllU„ 3822 Agric machinery and equip 3823 Metal + woodworking equip 3824 Spec ind mach + eqp ex 3823 3829 Mach, eqip ex elect nec

152 Beyond Total Factor Productivity

Technology Croup Industry Group R&D ISIC Industri^ ratio Code 1 • (%)

, 10 Other transport 1.9 3842 RaitrOfid equipment equipment

- 3844 Motor cycles + bicycles 3849 Transport equipment nec n Shipbuilding 1.4 3841 Shpbulding + repairing 12 Petroleum refining 1.1 3S3 Petroleum refineries

354 MIsc prods of petr. coal 13 Stone, clay and 1.1 36 Man non-metal min glass prods 14 1 TQ vOtHp-fiiIdr maniiiai i indiiiuuadict Ktripa^

15 Rubber and plastics 1 355 Rubber products

356 Plastic products nec •

•16 Non-ferrous metals 0.9 372 Non-ter metal basic low Ind 1

17 Iron and steel bas 0.7 371 Iron and steel bas inds inds 18 Fabricated metals 0.6 381 Fab met prds, ex pach, eqp 19 Food, drink and 0.3 31 Manut food, bevgs tobacco tobacco 20 Paper and printing 0.2 34 Man paper, prods, printing 21 Textiles and 0.2 32 Text, wearing appri. clothing leathr 22 Wood and tumlture 0.2 33 Man wood + wood products

153