Development Centre RESEARCH MEMORANDUM

Transcription

1 University of Groningen Groningen Growth and Development Centre Manufacturing Performance in Indonesia, South Korea and Taiwan before and after the Crisis. An international Perspective, Research Memorandum GD-63 Edwin Stuivenwold and Marcel Timmer RESEARCH MEMORANDUM

2 Manufacturing Performance in Indonesia, South Korea and Taiwan before and after the Crisis. An international Perspective, Research Memorandum GD-63 Edwin Stuivenwold and Marcel P. Timmer Groningen Growth and Development Centre July 2003

3 Manufacturing Performance in Indonesia, South Korea and Taiwan before and after the Crisis. An international perspective, Edwin Stuivenwold Marcel P. Timmer Groningen Growth and Development Centre University of Groningen/The Conference Board* July 2003 Abstract This paper analyses developments of comparative output and productivity levels in 17 manufacturing industries in Taiwan, South Korea and Indonesia compared to the United States for the period In order to express value added in a common currency, unit value ratios are developed for the benchmark year The study provides an update and extension of the benchmark studies for 1987 of Taiwan (Timmer, 1998), South Korea (Pilat, 1994) and Indonesia (Szirmai, 1994). In addition, comparisons of unit labour cost are made. It is shown that the Asian financial crisis has led to a quick restructuring process in South Korea which maintained its catch-up trend with the US during the 1990s. The level of value added per hour worked in 2000 is 35% of the US. On the other hand, performance in Taiwanese manufacturing dwindled in the 1990s and it has almost lost it productivity lead over South Korea. In 2000, labour productivity was 40% of the US level. Catching up in Indonesia started to take off at the end of the 1980s but this process has been dramatically reversed in the aftermath of the 1997 financial crisis. It has barely recovered to pre-1997 levels and growth relies heavily on export industries with little productivity growth. In 2000, value added per hour worked in the medium and large scale industry is still below 10 % of the US level. * Thanks are due to Eddy Szirmai and Michiel van Dijk for help with the Indonesian data and to The Conference Board for hosting Edwin Stuivenwold while working on this project.

4 List of Tables and Figures Tables: Table 1 Unit Value Ratios and Relative Price Levels, Indonesia, 1997 Table 2 Unit Value Ratios and Relative Price Levels, South Korea, 1997 Table 3 Unit Value Ratios and Relative Price Levels, Taiwan, 1997 Table 4 Reliability indicators for Indonesian Unit Value Ratios, 1997 Table 5 Reliability indicators for South Korea Unit Value Ratios, 1997 Table 6 Reliability indicators for Taiwanese Unit Value Ratios, 1997 Table 7 Korea Basic Census data, 1997 Table 8 Korea Basic National Accounts data, 1997 Table 9 Korea National Accounts & Census Comparison, 1997 Table 10 Taiwan Basic Census data, 1996 updated to 1997 Table 11 Taiwan Basic National Accounts data, 1997 Table 12 Taiwan National Accounts & Census Comparison, 1997 Table 13 Indonesia Basic data, medium and large scale, 1997 Table14 Comparison of Large & Medium companies with Small and household establishments, 1997 Table 15 Indonesia Basic data, all establishments, 1997 Table 16 Basic US Census data, 1997 Table 17 Basic US Census data, establishments with 20 employees and more, 1997 Table 18 US National Accounts data, 1997 Table 19 US National Accounts & Census Comparison, 1997 Table 20 Value added and employment, Korea, Taiwan and Indonesia as % of USA, Census based, 1997 Table 21 Labour productivity Korea, Taiwan and Indonesia as % of USA, Census based, 1997 Table 22 Value added and Total workers Korea, Taiwan and Indonesia as % of USA, National Accounts based, 1997 Table 23 Labour Productivity Korea, Taiwan and Indonesia as % of USA, National Accounts based, 1997 Table 24 Comparison of estimates of relative labour productivity levels in 1997, Taiwan Table 25 Comparison of estimates of relative labour productivity levels in 1997, Indonesia Table 26 Comparison of estimates of relative labour productivity levels in 1997, South Korea Table 27 Relative Labour productivity in Taiwan, Table 28 Relative Labour productivity in South Korea, Table 29 Relative Labour productivity in Indonesia (medium and large scale manufacturing), Table 30 Annual wages per employee, 1997 Table 31 Labour productivity in national currencies and in US Dollars, 1997 Table 32 Unit Labour Costs relative to the US, 1997 Table 33 Unit Labour Costs in South Korea relative to the US, Table 34 Unit Labour Costs in Taiwan relative to the US, Table 35 Unit Labour Costs in Indonesia relative to the US,

5 Table 36 US Value added in constant 1995 prices, Table 37 US Number of workers, Table 38 US Hours Worked per employee, Table 39 US Total labour compensation per employee, Table 40 Indonesian Gross Value added in constant 1983 prices, Table 41 Indonesian total persons engaged, Table 42 Indonesia Hours worked per employee, Table 43 Indonesia Wages per employee, Table 44 South Korea Gross Value added in constant 1995 market prices, Table 45 South Korea Number of persons engaged, Table 46 South Korea Hours worked per employee, Table 47 South Korea Labour compensation per employee, Table 48 Taiwan Gross Value added in constant 1996 market prices, Table 49 Taiwan Total persons engaged, Table 50 Taiwan Hours worked per employee, Table 51 Taiwan Wages per employee, Appendix I: Exchange rates Appendix II: Deflators Appendix Table II.1 Indonesia Gross output deflators, 1983=100 Appendix Table II.2 Korea Gross value added deflators, 1995=100 Appendix Table II.3 Taiwan Gross value added deflators, 1996=100 Appendix Table II.4 US Gross Value added deflators, 1995=100 Appendix III: Aggregation example Appendix Table III.1 Example of Aggregation Step 1: Rubber and Plastic Products, Indonesia/USA Appendix Table III.2 Example of Aggregation Step 2: Rubber and Plastic Products, Indonesia/USA Appendix IV Comparison of old and new benchmarks at branch level Appendix Table IV.1 Comparison of estimates of relative labour productivity levels in 1986, Taiwan Appendix Table IV.2 Comparison of estimates of relative labour productivity levels in 1987, Indonesia Appendix Table IV.3 Comparison of estimates of relative labour productivity levels in 1987, Korea Appendix Table IV.4 Indonesia Extrapolation of 1997 UVRs to 1987 Appendix Table IV.5 Taiwan Extrapolation of 1997 UVRs to 1986 Appendix Table IV.6 Korea Extrapolation of 1997 UVRs to 1987 Figures: Figure 1 Total manufacturing employment and GDP growth Figure 2 Industry shares in GDP, 1985, 1997 and 2000 Figure 3 Relative productivity trends, Figure 4 Unit labour costs, Figure 5 Relative labour costs, productivity and unit labour costs, Indonesia Figure 6 Relative labour costs, productivity and unit labour costs, Korea Figure 7 Relative labour costs, productivity and unit labour costs, Taiwan 3

6 1. Introduction Manufacturing is an important engine of economic growth, especially for less advanced countries. During the first phase of industrialisation, the contribution of manufacturing to aggregate growth is mainly through its expansion: labour is shifted from low-productive traditional activities towards more productive manufacturing activities (Lewis, 1954). Asian countries like China, India and Indonesia still can benefit from this basic process of structural change. In the second stage of development, the share of manufacturing in total employment and production declines, and market services grow in importance. Also in this phase the contribution of manufacturing to aggregate growth remains important because productivity growth in manufacturing is often higher than in the service sector (van Ark and Timmer 2003). The importance of manufacturing for economic growth was reinforced by the ICT-revolution of the 1980s and 1990s. Rapid advances in the technology of ICT goods production led to high productivity growth in the electronics manufacturing industry. South Korea and especially Taiwan benefited from the opportunities provided by booming global demand for electronics. However, the financial crisis in 1997 has had strong effects on the growth paths of East and South-East Asia. Figure 1 shows for Asian countries (South Korea, Taiwan and Indonesia) trends in manufacturing GDP and employment for the period Since the end of the 1980s, Taiwan and South Korea are clearly in a process of de-industrialisation as employment growth in manufacturing stagnates and it even turned negative during the 1990s. In Indonesia, the process of industrialisation was in full swing until the Asian financial crisis hit the country. In 1998, GDP in manufacturing declined by more than 10%. Growth resumed slowly in the years thereafter, and in 2001 real manufacturing GDP was back to the level of The effects of the crisis were different for Taiwan and South Korea. Output in the Korean manufacturing sector declined for the first time in decades, but a swift process of restructuring, including the shedding of more than 10 per cent of the manufacturing labour force led to a quick recovery. Taiwanese growth was barely affected by the financial crisis, but it was hit in 2001 mainly because global demand for electronics stalled. In Figure 2 structural changes within manufacturing can be traced by comparing the (current) GDP structure of 1985, 1997 and In Indonesia the share of traditional manufacturing industries declined slowly but steadily during the period , but this process stalled after the crisis. Due to the severe weakening of the Indonesian rupiah, exports of light manufactures like textiles, furniture and clothing were stimulated. Also the transport sector became an important (export oriented) manufacturing industry. The decline of traditional manufacturing had already progressed far in East Asia. The major development in the industrial structure of Taiwan is the rapid increase in importance of electrical machinery production, including electronics. The heavy concentration of manufacturing production in this sector increased after the crisis, as it made up almost 30% of manufacturing GDP in In South Korea, dependence on electrical machinery is also high (23% of GDP in 2000), but its industrial structure is more diversified than in Taiwan. Manufacturing of 4

7 Figure 1a Total manufacturing GDP growth (1985 = 100) Tai GDP Kor GDP Indo GDP Figure 1b Total manufacturing Employment growth (1985 = 100) Tai Emp Kor Emp Indo Emp Sources: see Appendix Tables. 5

8 transport equipment has become the second most important single industry in Korea, accounting for 17% of manufacturing GDP in To assess the future growth potential of the manufacturing industries in these countries, it is important to have an indication of the relative levels of labour productivity and unit labour costs in these countries from an international perspective. This has been the focus of studies within the ICOP project (International Comparisons of Output and Productivity) at the University of Groningen. Previous work in this tradition, which focused on the period has shown that potential for further growth in these countries was still high at the beginning of the 1990s (see, for example, Pilat 1994, Szirmai 1994 and Timmer 2000). Labour productivity levels were well below the levels attained in the US in all manufacturing branches. Indonesia has had a long experience of rapid output growth with little or no catch-up in labour productivity levels with the US, as gaps relative to the US were still huge in the early 1990s (Szirmai 1994). Gaps in Taiwan and South Korea have quickly narrowed in most manufacturing industries, but were still sizeable before the Asian crisis, especially in the important electrical machinery branch. Comparisons of capital intensities showed that in most industries gaps in capital stocks per worker with the US were much smaller than gaps in labour productivity. This suggested that further improvements in productivity had to be brought about by improving the efficient use of labour and capital input rather than continuing on an extensive growth path (Timmer 2002, van Ark and Timmer 2002a). Figure 2 Industry shares in current GDP, 1985, 1997 and % 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Indo 85 Indo 97 Indo 00 Tai 85 Tai 97 Tai 00 Kor 85 Kor 97 Kor 00 Traditional Resource Heavy Transport Electrical Note: traditional includes food, textiles, wearing apparel, leather and furniture and other. Resource intensive includes wood, paper, non-metallic minerals, petroleum refining and rubber and plastics. Heavy includes chemical, basic metal, fabricated metal and non-electrical machinery. Source: appendix tables. 6

9 This paper provides new evidence on the catch-up potential and the competitive position of South Korea, Taiwan and Indonesia before and after the Asian crisis. It analyses the productivity performance in the manufacturing sector compared to the United States for the period Labour productivity is measured in terms of value added per hour worked and value added per person employed for 17 manufacturing industries. In addition, it provides a comparison of unit labour costs. The main data sources used are the Censuses of Manufacturing and the National Accounts. In order to express value added in a common currency, unit value ratios (UVRs) are used instead of exchange rates or expenditure PPPs. These industry specific conversion factors are based on relative output prices of representative baskets of goods using methods developed within the ICOP project. Our study provides an update and extension of the previous benchmark studies of Taiwan/US (Timmer 1998), South Korea/US (Pilat 1994) and Indonesia/US (Szirmai 1994) for the year It provides new benchmark results for 1997 and extrapolations for the period The paper is organised as follows. In Section 2 unit value ratios for 1997 and relative price levels of the Asian countries vis-à-vis the USA are presented for 17 manufacturing branches. Data sources and details of the product matching procedure are described. The UVRs are used to convert national measures of output and labour productivity into a common currency to facilitate international comparisons of relative productivity levels. In previous ICOP-rounds these comparisons were based on output and employment figures from manufacturing censuses and surveys. However, with the improvements in national accounts conventions and their greater implementation in these countries, comparisons based on national accounts data presently provide a more comprehensive and internationally standardised picture of relative labour productivity levels. This switch from census to national accounts comparisons is discussed in more detail in Section 3. We argue that the use of national account sources for value added and employment is to be preferred for industry-level productivity studies, complemented by census data in case more industry detail is needed. In Section 4, international comparisons of output and labour productivity levels are made for the benchmark year Differences when using national accounts or census material are discussed. It is shown that the use of the new benchmark has only minor implications for the relative performance of Indonesia and South Korea, but major ones for Taiwan. In contrast to the previous studies, it is shown that Taiwan has a higher relative labour productivity level than South Korea. Furthermore, the new 1997 benchmark comparisons for relative value added, employment and labour productivity for Korea, Indonesia, Taiwan are extrapolated to the period and compared with developments in Japan. In Section 5 comparisons of relative unit labour costs are made, defined as relative wage costs (based on exchange rates) divided by relative labour productivity (based on manufacturing UVRs). This indicates the competitive position of each country vis-à-vis the US and each other. The unit labour costs benchmark for 1997 is also extrapolated for the period It is shown that due to a rapid increase in wages, Taiwan and especially Korea quickly lost their initial advantages in labour costs. Although the devaluations in 1998 provided a temporary relief, these findings indicate that export competitiveness in East Asia must increasingly come from non-cost factors, such as higher quality and shifts towards more technologically advanced products. Section 6 concludes. 7

10 2. Unit Value Ratios and Matching Details for 1997 For comparing output and labour productivity levels of the Asian countries with the United States, the methodology of the ICOP project is used. A detailed description of this methodology based on Timmer et al. (2001) can be found in Annex 1. The first step in the bilateral comparisons is the matching of Asian products with US products based on the product descriptions which are given in the various Censuses. Matches can only be made if product data the quantity and the value of shipments are given for both the US and the Asian country. Unit values (UVs) are calculated by dividing the value of the shipments by the quantity of the shipments. Unit value ratios (UVRs) are then calculated by dividing the Asian UV by the US UV. The product UVRs are aggregated in three steps, see Annex 1 for details. Appendix Table III provides an example of the aggregation procedures used in the comparison of output in the rubber and plastics industry in Indonesia and the US. 2.1 Basic Product Data Unit values are derived from data in the manufacturing censuses and surveys in the various countries. US product data was acquired from the Bureau of the Census, 1997 Manufacturing Census and from the Current Industrial Report 1997 (CIR). The product data for Korea were taken from National Statistical Office, 1997 Report on Mining and Manufacturing Survey. 1 For Indonesia use is made of the 1997 Industri Statistik, Volume III published by the Biro Pusat Statistik (BPS, the Indonesian Statistical Office). Taiwanese product data was derived from Directorate General of Budget, Accounting and Statistics (DGBAS), The 1996 Report on industry, commerce and service census. Because comparisons are made for the year 1997, Taiwanese unit values were updated using wholesale price indices from the DGBAS October 2001 issue of the Monthly Bulletin of Statistics. Unit values are at factor cost in the Korean and US census and hence to maintain comparability, the unit values for Indonesia and Taiwan had to be adjusted from market price to a factor cost basis. The difference between market costs and factor costs are the indirect taxes, which are given at industry level in the Taiwanese census. The tax rate for each industry has been calculated by dividing the indirect taxes through the output of that industry. This tax rate was then used to convert the value of shipments from market to factor costs. A similar procedure has been followed for Indonesia. 2.2 Main results of the matching procedure The main results for the UVRs and the comparative price level are given in Tables 1 to 3. Columns 1 to 3 show the UVRs at US quantities (Laspeyres), Asian quantities (Paasche), and the geometric average (Fisher). Column 4 presents the relative price level, i.e. the ratio of the Fisher UVR to the 1 In the Korean census a number of product unit values appeared to be highly improbable and supplementary information from the National Statistical Office 1998 Report on Mining and Manufacturing Census and Korea Statistical Yearbook 1999 was used. The 1997 value of petroleum production is calculated with the quantities from the Statistical Yearbook (page 304) and the unit value of the 1998 Census. Because of the use of the 1998 UV a correction for inflation has to be made. The inflation was calculated with the help of the producer price index for petroleum products (page 491, Statistical Yearbook 1999). Unit values for products in the Office, accounting and computing machinery were clearly wrong. To arrive at acceptable UVs for this important industry the 1998 UVs were used in combination with the 1997 quantity data. Again a correction was made with the producer price index for Office machinery products. The matching of Copper-wire bars (Korea product number ) also caused a problem. The UV of the Korean product was clearly much too low and an adjustment has been made. Replacing the 1997 UV with the 1998 UV and using this UV in combination with the 1997 quantity data from the 1999 Statistical Yearbook (page 257) resulted in a plausible UVR. Again a correction for inflation was made. 8

11 nominal exchange rate. This ratio indicates whether Asian products are relatively cheaper or more expensive than those produced in the USA (ratio below or above 100 respectively). On average, Korea and Taiwan had a small comparative advantage in manufacturing production as output prices were somewhat below the exchange rate (94 and 87 percent of the US price level in 1997 respectively). Indonesian manufacturing products were less expensive by quite a margin (64% of the US price level). However, the latter finding must be qualified. The exchange rates used are yearly averages. The Indonesian rupiah experienced a steep decline at the end of 1997 when the Asian financial crisis hit the country. The exchange rate increased from 2140 (Rupiah/US$) in June to 4650 (Rupiah/US$) in December. Consequently relative price levels expressed relative to the yearly average exchange rate are rather low. A better comparison is made with the exchange rate for the period Jan- June. This is shown in column (5). Prices were still well below this exchange rate as well (77% of the US price level). The Asian countries each had price advantages in different branches. In Indonesia, the highest relative prices were observed in Office, Accounting & Computing Machinery and Wood products, the lowest in Paper products, Printing & Publishing, Leather products and Footwear, Wearing Apparel and Textile mill products. In Taiwan, the highest relative prices were in Food and Kindred products, Electrical machinery and in Transport Equipment. Low relative prices were found in Office, Accounting and Computing Machinery and in Machinery & Equipment. High Korean prices were found in Food and Kindred products and Wearing Apparel. In Furniture and Fixtures, Office, Accounting and Computing Machinery and Non-Metallic Mineral products low relative prices were observed. In Tables 4 to 6, indicators for the reliability of the UVRs are given. For Korea 216 matches were made, covering 26% of Korean output and 20% of US output. Most matches were made in the Food and Kindred products branch and the Basic metals branch. In addition, quite a few matches were made in the Chemicals & Allied products branch. In the Indonesia-US comparison, 228 matches were made, covering 50% of Indonesian output and 18% of US output. Again many matches were made in the Food and Kindred products and the Basic Metals branch. Other branches with many matches were the Chemicals & Allied products branch, the Wearing Apparel branch and the Textile Mill Products branch. In the Taiwan-US comparison it was possible to make 102 matches, covering 22% of Taiwanese output and 13% of US output. Most matches were made in the Food and Kindred products branch and in the Basic Metals branch. In contrast to the other comparisons, in some Taiwanese branches only 2 or only 1 match could be made. As a consequence no coefficients of variation could be calculated for eight branches. One of the main reasons of the low number of matches in the Taiwan/US matching was the scarcity of product detail in the Taiwanese census. Compared to the Korean and Indonesian Census, the Taiwan Census lists relatively few items with data on both quantities and values. The UVRs for total manufacturing of all three bilateral comparisons turn out to be fairly reliable, as the coefficients of variations are well below 0.1 (see last line of columns 4 and 5). The coefficient of variation of the Korea/USA and the Indonesia/USA comparison are a bit higher than those of the Taiwan/USA comparison indicating the latter are more consistent. Some individual branch results of the Indonesia/USA comparison have to be used with caution, as the coefficients of 9

12 variation for branches like Food and Kindred Products, Machinery & Equipment, Office, Accounting & Computing Machinery and the Electrical Machinery branch exceed 0.1. The same holds for some Korean branches like the Non-metallic Minerals and the Fabricated Metals branches. The Taiwanese results are the most reliable as there is only one branch (the Textile mill products branch) with a coefficient of variation that only slightly exceeds 0.1. However it should be kept in mind that in eight branches less than 3 matches could be made, making it impossible to calculate a meaningful variance. Coverage ratios are another indicator of the reliability of the results (see columns 1 and 2 of tables 4 to 6). Coverage ratios are the share in total sales covered by products included in the matches. The coverage ratios of Indonesia and the US in the Indonesia/USA matching is in both cases the highest, the coverage ratios of the Taiwan/US matching for Taiwan and the US are the lowest. The outcome that high coverage ratios could be obtained for Indonesia is consistent with previous research by Szirmai (1994). Indonesia s transition to an industrialised economy started later than that of Taiwan and Korea. Because of this later start the composition of Indonesian production consists of less complicated products compared to Taiwan and Korea. It is easier to match simple, homogeneous products like milk and T-shirts than products like refrigerators and computers because of the quality differences that exist between the US and other countries. From the column with the coverage ratios it can be seen that branches like Food and Kindred Products and Basic Metals, which produce simple products usually have higher percentages of matched output than more complex product producing branches like the Office, Accounting and Computing Machinery, the Electrical Machinery and the Fabricated Metals branches. 3. Discussion of Basic Sources Unit value ratios are used to convert output in national currencies into a common denominator in order to derive relative output measures. In combination with measures of labour input (either number of persons engaged or total hours worked) relative labour productivity levels for a particular benchmark year are derived. In principle two data sources can be used for national output and employment figures: manufacturing censuses and surveys which were also used for deriving the UVRs, and national accounts (complemented with labour force surveys in case employment figures are not integrated within the national accounts). In previous rounds of the ICOP project use was made of the census data on output and inputs as default. However, it becomes clear that trends and levels of the two alternative sources are increasingly inconsistent, not only for the countries under consideration, but also for others such as Japan (see Inklaar, Wu and van Ark 2003). Therefore the choice for a particular data source to derive comparable output and labour productivity levels needs to be reconsidered. This is discussed in section 3.1. In section 3.2 an elaborate description of the data sources used in this study is given. 3.1 Census versus National Accounts In previous rounds of the ICOP project (comparisons based on 1975, 1987 and 1992 benchmarks, see van Ark and Timmer 2001) use was made of census data on output and inputs as default. Using census data for productivity benchmark comparisons has a number of advantages. Firstly, it provides a coherent source for both input and output as both are derived from the same set of surveyed firms. Hence consistency in the coverage of both is ensured, which is crucial for deriving meaningful labour 10

13 productivity levels. This can be an important advantage of census data compared to national accounts data, especially in cases were employment figures are not integrated with output figures in the national accounts. 2 A second advantage is that census data normally provide more industry detail which allows for more disaggregated analysis. Furthermore, adjustments for differences in classification of manufacturing activities between countries can be easily made. Finally, differences in the measurement of employment across countries, which is not internationally standardised as is the GDP measure in the national accounts, can be reconciled. This includes possible corrections for the inclusion of non-employed workers (own account and family workers) and inclusion of employment at auxiliary and head offices. The use of census data, however, has two major disadvantages. First, the concept of value added in the census differs across countries and is not always similar to the concept used in the national accounts. The manufacturing censuses of South Korea and the USA, but not of Indonesia and Taiwan, use the so-called census concept of value added which includes purchased non-industrial services such as business services (rental of machinery, communication, legal and cleaning services etc.). This is because data is collected on an establishment basis and service inputs paid for by headquarters of enterprises are not allocated to individual establishments. In the system of national accounts, purchased services are part of the intermediate inputs. Therefore, the national-accounts concept is more net than the census concept (van Ark 1993). The census concept is therefore a somewhat anachronistic concept, and can largely impact the results in particular when there is great deal of outsourcing to service industries. As most binary comparisons within ICOP are made with the US, one is forced to use the census-concept of value added, even when the other country provides census data on a national accounts concept. This is a clear disadvantage of choosing the census as the basic source for comparison. A second disadvantage of using census data is that the coverage of firms in the census is often incomplete. The census normally covers less activities than the national accounts. This is caused by both intended and unintended undercoverage. To keep survey costs down, the censuses in many countries deliberately exclude some small-scale activities, mostly by having a cut-off point in terms of the number of employees in an establishment. In Taiwan and the USA, the manufacturing census covers all establishments, having one employee or more. 3 The annual manufacturing survey in South Korea covers establishments with at least five employees. Small scale firms are only covered in quinnenial census years (1978, 1983 etc.). In Indonesia only the medium and large scale sector is covered in the industrial census. Establishments with less than twenty employees are excluded. Also, the important oil and gas refining industry is excluded from the survey. In addition, parts of manufacturing are sometimes not covered for reasons of confidentiality, e.g. in the case of defence industry or government monopolies. Unintended undercoverage is due to informal activities which should have been covered but are not. In some cases an estimate for these activities is included in the national accounts. Employment figures should be adjusted in a similar manner. 2 For example, in the case of Mexico and Brazil, Mulder, Montout and Lopez (2002) found that output figures from the national accounts were highly inconsistent with employment figures from the labour force survey. 3 This does not mean that all manufacturing firms are actually surveyed. Estimates for small establishments are based on samples rather than full enumeration. 11

14 Census data and national accounts data can be reconciled making the appropriate adjustments using additional census information (see e.g. Mulder, Montant and Lopez 2002) or other sources such as input-output tables (see e.g. Szirmai and Pilat, 1990a,b). Szirmai and Pilat (1990a,b) provide productivity comparisons of South Korea and Japan with the USA for 1975 using both census data and national accounts data. They conclude that the general patterns of international productivity differentials are quite consistent between the different sources. However in the 1990s, this no longer holds true, as will be shown below. The choice for a particular data source ultimately depends on the availability and quality of the basic data sources. In some cases there is no alternative to the use of census data. In many lessdeveloped countries, there is no detailed labour force survey which provides figures on employment by manufacturing branch. Detailed labour force surveys are missing in the case for Indonesia, but also for other Asian countries like India and China (see Timmer 2000, Szirmai, Bai and Ruoen 2002). In case there are surveys, the consistency between the employment figures from the labour force survey and the output figures from the national accounts can sometimes be doubted, as shown in the case of Mexico and Brazil by Mulder et al. (2002). Fortunately, for the case of South Korea and Taiwan, there is detailed labour force survey material which can be reasonably combined with output figures from the national accounts. The US is the only country which provides employment data which is fully integrated with the national accounts. The large differences which can arise between benchmarks based on the two different sources are illustrated in Tables 9, 12 and 19. In these tables differences between census and national accounts figures for respectively Korea, Taiwan and the USA are given. The differences between output figures from the census and National Accounts data for Taiwan are relatively small, in particular at the level of total manufacturing, suggesting that output figures from the census are an important input in the construction of the national accounts (Table 12). The biggest differences in output measures can be found in the food, petroleum and transport equipment branches, which might be due to the exclusion of certain public firms in the census. On the other hand, output in the wearing apparel, metal, machinery and electrical machinery industries is higher according to the census (up to 20%). But employment in these branches is also higher according to the census compared with the labour force survey. Hence labour productivity levels calculated on basis of census data, or on the basis of NA data combined with the labour force survey, would yield results which are not widely divergent. At the aggregate manufacturing level, the choice for national accounts data would result in a labour productivity level which is about 8 % higher than the level on the basis of census data. This is in big contrast to the case of Korea (Table 9). According to the manufacturing survey employment is much lower in all branches (70% on average). This can be partly explained by the fact that the 1997 survey only surveys establishments with more than five employees (5+ firms). However, this explains less than half of the difference. From the 1993 census it can be derived that small scale employment is about 13% of total employment in 5+ firms. Value added on the other hand is much higher in the survey than in the NA, for total manufacturing more than 60 per cent. This can partly be explained by the census concept of value added which is used in the 1997 survey. But again, this 12

15 explanation goes only some way. This discrepancy has been noted before (Timmer 2001, Pilat 1994 p. 167 Young 1995, footnote 45, Dollar and Sokoloff 1990) and the problem is getting worse over time. The main reason appears to be the increasing amount of outsourcing of service activities by manufacturing firms. Whereas in the 1980s most service activities were still performed in-house, in the 1990s a process of specialisation has taken place and the amount of outsourced services increased dramatically. This rising share of services in intermediate inputs makes comparisons based on census value added less informative as census value added is increasing without a corresponding increase of factor input. Therefore the use of national accounts data is to be preferred in the case of Korea, both for the benchmark comparisons and extrapolation of the benchmark over time. For the US, differences in value added figures between the census and the national accounts are mainly due to the different value added concepts (Table 9). Employment figures are generally consistent between the two sources. However, in some branches, industry classifications seem to differ between the two sources, especially in metal products and machinery. The use of the NA as the basic source is to be preferred, especially since employment statistics have been fully integrated. In the case of Indonesia, however, we prefer the census-based estimates because of lack of detail in national accounts and the inclusion of small-scale handicraft industries which are difficult to compare directly with U.S. manufacturing. In section 4 we will show the international labour productivity comparisons for the benchmark year 1997 based on census and national accounts basis, and indicate the differences when appropriate. Based on the discussion above, the national accounts figures are where possible to be preferred and will be used in the remainder of this paper when the benchmark is extrapolated through time. 3.2 Data sources In this section we discuss the basic sources which have been used for the benchmarks comparisons, based both on manufacturing survey and national accounts data, and for the extrapolations in section 5, which are based on national accounts data only. The following definitions are used throughout the paper. GVA is gross value added at factor cost. A distinction is made between GVA (census) and GVA (NA). The first is the census concept of value added, the latter indicates the national accounts concept of value added. Employment refers to number of employees, or number of workers, as indicated. Number of workers includes all employees, own-account workers and family workers, and also employment at head offices and auxiliaries. United States Census For each comparison based on census material data on output, value added and employment were taken from the General Summary of 1997 US Census (June 2001 issue). The US Census does not include the publishing and logging industries under Manufacturing. These industries have been added to be internationally comparable. Employment figures of the US Census do not contain administrative offices and auxiliary staff. This can be corrected by calculating the ratio of auxiliary to normal (i.e. 13

16 the employees mentioned in the Census) personnel. This is done with the help of the 1996 Annual Survey of Manufacturers. 4 National Accounts Time series on value added and employment are obtained from the OECD, STAN database which in turn is based on data from the Bureau of Economic Analysis (BEA). Taiwan Census Data on value added, output, employment and indirect taxes for the Census comparison were taken from the DGBAS, 1996 Report on industry, commerce and service census. Value added was put on a census-concept of value added to make it comparable with the US using the DGBAS, 1996 Inputoutput table. The ratio of non-industrial services to total intermediate inputs varies from 4.6% to 32.5% for individual branches and was 19.6% for total manufacturing. Value added and employment for 1996 was updated to 1997 using growth rates in current value added and employment from DGBAS, National Income in Taiwan Area of the Republic of China, 1999 and DGBAS, Yearbook of Earnings and Productivity Statistics 1999, respectively. National Accounts Current and constant value added are from DGBAS, National Income in Taiwan Area of the Republic of China, various issues and internal data provided by DGBAS, Third Bureau. Constant price series are double deflated using a fixed base year (Laspeyres). The National Accounts does not include Publishing under manufacturing and a correction has been made using the ratio of Paper and printing to Publishing from the Taiwan 1996 Census. Number of employees was derived from DGBAS, Yearbook and Monthly bulletin of Earnings and Productivity Statistics, various issues and adjusted to number of workers using shares of own account and family workers in total number of workers from DGBAS, Censuses of Manufacturing, various issues. Hours worked are derived from DGBAS, Yearbook and Monthly bulletin of Earnings and Productivity Statistics, various issues, and refer to hours worked by employees. It is assumed that non-employed workers work similar hours. South Korea Census The output, value added and employment data for the Census comparison were taken from the National Statistical Office, 1997 Report on Mining and Manufacturing Survey. National Accounts The value added, employment and labour compensation for the 1997 National Accounts comparison benchmark comparison as well as the time series were supplied by the OECD STAN (March 2001) which is based on national accounts data from the Bank of Korea and several secondary sources (like the Economically Active Population Survey and monthly business surveys). By combining these sources OECD STAN provides more detail than the National Accounts. But even the OECD STAN database does not always have enough detail. The National Accounts data on value added and 4 Since the 1997 census head and auxiliaries are included as a separate industry, and no breakdown by industry 14

17 employment for textiles, wearing apparel and leather industries (ISIC Rev ) are not separated. A breakdown was made based on census and survey data. 5 Similarly data for the chemical branch has been split. Korean hours worked were taken from the Ministry of Labour, Monthly Labour Survey, various issues and refer to hours worked by employees. They include regular hours worked and overtime hours worked. Indonesia Census For Indonesia the data on value added, output and employment were obtained from the 1997 Industri Statistik, Volume III published by the Biro Pusat Statistik (BPS, the Indonesian Statistical Office). Value added was put on a census concept of value added using the 1995 Input-Output table to calculate the ratio of non-industrial services to total intermediate inputs used by manufacturing industries. This ratio varies from 5.8% to 30.5% for individual branches and is 18.1 % for total manufacturing. The Indonesian Census only reports on establishments having twenty or more employees. The US data was adjusted to a similar basis. Alternatively, figures on small scale establishments in Indonesia can be added. When small establishment and household figures would be taken into account the labour productivity for the whole manufacturing sector would decline. The number of persons engaged in the small establishments is on average 1.5 times as large as persons engaged in medium and large establishments. But the contribution to value added from small establishments and households is rather small, on average only 9 percent compared to the medium and large establishments. For industries 31 (Food and kindred products), 33 (Wood products), 36 (Non-metallic products) and 39 (Other manufacturing) the impact of the small establishments would be the largest (Tables 14 and 15). The Biro Pusat Statistik provides consistent time series for value added and labour input in the medium and large scale manufacturing sector based on the annual Industri Statistik. The series are revised annually on the basis of a backcasting project that makes imputations for the past production of newly discovered firms (Jammal 1993). In 1993, when this project was first implemented, the estimate for average annual labour productivity growth during the period was revised downwards from 6 per cent, as published originally, to 3 per cent. This indicates the importance of the revisions in the national accounts. The sizeable oil refining and liquid natural gas production sector is excluded in these series. In 1993 this sector produced 21 per cent of total manufacturing value added in the medium and large scale sector, whereas it employed less than 1 per cent of the manufacturing labour force. Backcast data on gross value added and employment for the period from 1985 to 1998 are taken from Takii and Ramstetter (2000). These series are gross value added in current prices and were deflated with wholesale output price indices from Szirmai (1994) updated with BPS, Indikator of origin is given anymore. Hence we use data for Since 1993, the Korean data is classified according to the new Korean standard industrial classification (KSIC 1991) which is convertible to the ISIC rev 3, but not to the old KSIC. It proved impossible to construct consistent time series for these industries for the period before and after To solve this problem, Census and manufacturing survey data for the period was used for a breakdown extrapolation of these figures. Summing these figures and calculating the shares of each branch in the total gives shares which can be applied to the aggregate data supplied by the OECD STAN database. 15

18 Ekonomi, various issues. Hours worked for total manufacturing is based on the average hours worked per week in urban manufacturing from BPS, Keadaan angkatan kerja di Indonesia, various issues, multiplied by 52 weeks. This is under the assumption that the medium and large scale manufacturing establishments will reside mainly in the urban areas. 6 The figure for total manufacturing is used for all manufacturing industries. 6 Szirmai (1994, Appendix A2) assumed alternatively that hours worked per week refers to weeks actually worked and multiplies by 46 to adjust for holidays, strikes etc. 16

19 4. Benchmark productivity levels in Indonesia, Korea and Taiwan for 1997 Using the unit value ratios for 1997 shown in section 2, relative output and labour productivity comparisons of the three Asian countries and the US can be made. As discussed above, for South Korea and Taiwan we prefer to make comparisons based on national accounts data rather than census data. 7 The results are discussed in section 4.1. In section 4.2, the comparisons on the basis of national accounts are compared with those based on output and employment data from the manufacturing census or survey for In section 4.3 the results of the new benchmark are compared with results from the earlier benchmark studies. In Section 4.4, the new benchmark is extrapolated Benchmark based on national accounts Table 22 provides comparisons of value added and employment by manufacturing branch based on national accounts material for All figures in this table are expressed as a percentage of the US level. Compared to the US, output and employment levels in textile, leather, petroleum, non-metallic minerals and basic metal branches are relatively high in both South Korea and Taiwan. In addition in South Korea the transport equipment branch is relatively large, whereas in Taiwan the office, accounting and computing machinery is much larger than the average manufacturing branch. Indonesian industrial structure is (relatively) dominated by the food, textile, wearing apparel and leather branches. Table 23 shows the relative labour productivity levels (measures are provided on a per worker and per hour worked basis) on national accounts basis. In terms of relative labour productivity performance Taiwan clearly outperforms South Korea. Relative labour productivity is 44 % in Taiwan (on a per hour basis) and 32 % in South Korea. Looking at branch level performance, it follows that productivity performance in Taiwan is stronger than in Korea in most industries, especially for food and textiles, rubber and plastics and the office, accounting and computing machinery. Korea slightly outperforms Taiwan in metal branches and electrical machinery n.e.c. But even in Taiwan relative productivity levels are well below the US level, except in petroleum refining. Branch performance in Taiwan varies from a low 30% of the US level in electrical machinery up to 69% in textiles. Korean performance varies from 15% in wearing apparel up to 63% in basic metals. Indonesian relative performance is well below the other countries. Relative levels vary from 2 per cent in furniture and fixtures, up to 26% in transport equipment manufacturing. This is an indication of the dual structure of the Indonesian economy which is still present. A relatively modern sector such as transport equipment which is dominated by large scale foreign investors exists side by side with a small-scale handicraft sector such as furniture. For comparisons with other more advanced countries, comparisons based on the (modern) large and medium scale establishments seem to be the most appropriate. For this we can only rely on census-based comparisons. Indonesian relative performance in medium and large scale manufacturing is at 11% of the US level in 1997, varying 7 Note that national accounts in the case of South Korea and Taiwan indicates the use of a mix of output figures from the national accounts and employment figures from labour force surveys, which are not officially integrated in the national accounts. Only in the case of the US, output and employment are integrated in national accounts data. Indonesia does not have detailed national accounts figures, and in this case, national accounts indicates comparisons for the total manufacturing sector, including small scale establishments. 17