Appendix. List of Sample Firms
B. Legal-procedure group (16 firms)
Firm
Month and year of filing for Protection under the Corporate Reorganization
Law
MSHARE
LEC, Inc. May 1992 21.9%
Daiichibo Co., Ltd. October 1992 5.2%
Nikkatsu Corporation July 1993 0.4%
KYC Machine Industry Co., Ltd. December 1993 4.3%
Oriental Photo Corporation May 1995 0.4 %
Kyotaru Co., Ltd. January 1997 34.3%
Tokai-Kogyo, Ltd. July 1997 0.3%
Tada Corporation July 1997 10.6%
Daito Kogyo Co., Ltd. August 1997 21.3%
Yaohan Japan, Ltd. September 1997 11.7%
Toshoku Ltd. December 1997 0.1%
Daido Concrete Co., Ltd. March 1998 0.3%
Mitsui Warf Co., Ltd. June 1998 45.5%
Asakawagumi Co., Ltd. July 1998 14.6%
Longchamp Co., Ltd. August 1998 8.7%
JDC Corporation December 1998 0.5%
Notes:
1. When there were several newspaper reports on the reorganization of a firm in the private-procedure group, the first date of reporting is used.
2. MSHARE is calculated as the sum of shares held by the executives themselves, and those held by their family members, relatives, and family-owned corporations, as a percentage of the total outstanding shares.
Productivity Gap between Major Firms and Small and Me-dium Enterprises in the Manufacturing Industries of Japan, Korea and Malaysia
Noriyoshi Oguchi
1. Introduction
Small and medium enterprises (SMEs) account for a significant portion of many national econo-mies in terms of employment and production, but a closer examination reveals that the nature and roles of SMEs differ from country to country. Gen-erally speaking, such firms are often associated with low productivity and survive by making up for the low productivity with low wages. In fact, in the three countries covered by this paper, the capital equipment ratio and labor productivity per worker are lower at SMEs than at large firms. However, the contention on the basis of this alone that the productivity of SMEs is low does not tell the whole story.
Labor productivity represents only one aspect of production technology, and a more comprehensive indicator of productivity is total factor productivity (TFP). This paper uses TFP as measure of the productivity of large firms and SMEs. By compar-ing the TFP of large firms and SMEs in Japan, Korea and Malaysia, we make a comparison be-tween the relationships of large firms and SMEs in the three countries and their relative positions in the respective economies on the basis of differences in the TFP gaps.
The definition of SMEs differs from country to
country. While SMEs are defined by both the number of employees and capital in all the three countries under review, this paper classifies com-panies by size based on the number of workers employed.
2. Data
2.1 Malaysia
The Department of Statistics (DOS) of the Ma-laysian government conducts a survey of the man-ufacturing industry every year. It covers enough firms to account for over 80 percent of the output in each 3-digit level sub-sector of manufacturing. In this paper we use the cross section data of indi-vidual firms for each year from 1992 to 1999 except for 1998. The definition of SME is based on the number of employees. The large firms are those with employees of more than 150 and SMEs are those with less than 150 employees.
2.2 Korea
We used the data on individual firms for the years from 1985 to 2003 provided by a private cre-dit rating firm, Korea Information Service, for Ko-rea. In total we had about 48,000 samples although the sample number varies from year to year. The definition of SME is based on the number of
em-ployees. The large firms are those with employees of more than 299 and SMEs are those with less than 300 employees.
2.3 Japan
The analysis of Japan is based on data of Finan-cial Statement Statistics of Corporations by In-dustry, provided by the Ministry of Finance. Using data from 1980 to 2006, the company size is classi-fied by capital, with firms with capital of less than
¥100 million defined as SMEs and those with cap-ital of ¥100 million or more defined as large com-panies. This paper’s analysis used the industry average data in subsector data rather than indi-vidual firm data. For comparison with Malaysia and Korea, it would be more convenient to use Japanese data with company size classified by the size of the workforce as with the case of the other two countries, but in this paper we chose to use the company size classification by capital as provided in Financial Statement Statistics of Corporations by Industry. Even in that case, it would be more appropriate to distinguish between SMEs and large companies using a capital size of ¥300 million, but again the dividing line of ¥100 million was chosen in this paper.
3. SMEs in the Three Countries a. Malaysia
Table 3.1 shows shares of large firms and SMEs in terms of output employment and fixed assets in manufacturing industries by subsector.
As shown by the table, SMEs account for some 36% of employment and some 23% of output in Malaysia’s manufacturing industries. These shares differ distinctly from those of SMEs in Korea and Japan, where SMEs account for far larger propor-tions in terms of manufacturing employment. The large difference partly reflects that in Malaysia,
SMEs are defined as firms with the workforce of Less than 150, a far smaller figure than the criteria adopted in Korea and Japan.
b. Korea
In Korea in recent years, SMEs account for over 75% of employment in manufacturing industries.
In terms of output, SMEs account for around 50%, a share that has been stable since 2000.
c. Japan
In Japan, SMEs account for about 75% of em-ployment and around 45% of production in manu-facturing. These shares are nearly the same as those of Korean SMEs, but the share in output is a bit lower.
Table 3.1 Shares of Large Firms and SMEs in Malaysia
Industry
Output Employment Fixed Assets
Share (%) Share (%) Share (%)
Large Firms SMEs Large Firms SMEs Large Firms SMEs
Manufacturing industries 76.87 23.13 64.15 35.85 81.05 18.95
Textiles 77.18 22.82 63.43 36.57 85.77 14.23
Apparel 57.19 42.81 51.54 48.46 54.06 45.94
Industrial chemicals 77.03 22.97 60.91 39.09 84.43 15.57
Other chemicals 52.90 47.10 42.22 57.78 46.18 53.82
Petroleum refining 99.21 0.79 97.37 2.63 99.78 0.22
Other petroleum, coal products 35.00 65.00 32.96 67.04 21.22 78.78
Scientific, measuring and control
instruments and equipment 90.97 9.03 80.63 19.37 82.49 17.51
Transport equipment 86.60 13.40 69.31 30.69 78.07 21.93
Plastic products 54.20 45.80 49.37 50.63 55.19 44.81
Ceramics 50.28 49.72 37.68 62.32 45.25 54.75
Glassware 90.54 9.46 85.57 14.43 93.43 6.57
Nonmetallic mineral products 69.17 30.83 48.92 51.08 77.15 22.85
Iron and steel 80.62 19.38 62.17 37.83 91.83 8.17
Nonferrous metals 69.49 30.51 71.84 28.16 79.98 20.02
Fabricated metals 54.29 45.71 42.13 57.87 60.11 39.89
Machinery 84.56 15.44 66.46 33.54 77.88 22.12
Wood products 49.57 50.43 41.62 58.38 73.45 26.55
Furniture and household
equipment 41.48 58.52 31.31 68.69 42.85 57.15
Paper products 60.52 39.48 52.30 47.70 94.84 5.16
Rubber products 65.12 34.88 58.74 41.26 76.48 23.52
Food 46.62 53.38 42.75 57.25 49.47 50.53
Other food products 21.34 78.66 22.78 77.22 32.79 67.21
Beverages 78.47 21.53 61.22 38.78 87.32 12.68
Tobacco 96.27 3.73 53.52 46.48 95.08 4.92
Printing and publishing 63.98 36.02 54.03 45.97 55.71 44.29
Source: Survey of Manufacturing Industries of the Department of Statistics
The statistics are taken from the Survey of Manufacturing Industries of the Department of Statistics. These are slightly different from the SNA based statistics.
Table 3.2 Shares of Large Firms and SMEs in Korea
Employment 1,000 Output $billion
Total SMEs Share (%) Total SMEs Share (%)
1990 3019 1864 62 177 76 43
2000 2652 1962 74 565 268 47
2001 2627 1990 76 575 282 49
2002 2675 2057 77 628 319 51
2003 2719 2090 77 672 340 51
2004 2780 2105 76 789 383 49
Source: Small and Medium Business Administration website http://www.smba.go.kr/main/index.jsp
Table 3.3 Shares of Large Manufacturing Companies and SMEs in Japan (by workforce)
Size SMEs
Large firms Small enterprises
Year
Workforce
(person) Share (%) Workforce
(person) Share (%) Workforce
(person) Share (%) 1999
2001 2004
8,425,330 8,137,677 7,455,508
74.7 74.3 75.0
3,083,844 2,964,485 2,629,993
27.3 27.1 26.5
2,855,662 2,819,073 2,484,941
25.3 25.7 25.0 Note: Firms with a workforce of 300 or less are defined as SMEs, and those with a workforce of 20 or less as small
businesses.
Source: White Paper on Small and Medium Enterprises in Japan
Table 3.4 Shares of Large Manufacturing Companies and SMEs in Japan (by value added) (%)
Workforce size 1999 2001 2003 2005
4～9 6.0 5.2 4.8 4.6
10～19 6.4 6.9 6.4 5.7
20～99 23.9 24.1 23.1 22.4
100～299 20.9 21.6 22.5 22.6
300～999 21.9 22.1 22.0 22.8
1,000 or more 20.9 20.2 21.1 21.9
Source: White Paper on Small and Medium Enterprises in Japan
4. Productivity
Labor productivity is the most widely used indi-cator of productivity. In this section, we compare labor productivity in Malaysia, Korea and Japan on the basis of company size. The table below shows the ratio of labor productivity of SMEs to that of large firms. It shows that the labor productivity of SMEs is quite low compared with that of large companies.
4.1 Labor productivity a. Malaysia
In Malaysia, in manufacturing industries on av-erage, the labor productivity of SMEs is only 54% of that of large companies. By subsector, while SMEs have higher labor productivity than large firms in
nonferrous metals and other food products, large firms have much higher labor productivity in all other subsectors. In petroleum refining, as large firms employ large-scale equipment, SMEs have a far smaller capital equipment ratio and lower labor productivity. In other petroleum and coal products, SMEs outrank large companies in all areas in-cluding output, employment and fixed capital making the subsector very special.
b. Korea
In Korea, the capital equipment ratio for SMEs is smaller than that of large companies in all in-dustry subsectors. The ratio is particularly low for SMEs in industrial chemicals, a subsector where large companies are operating with large-scale
Table 4.1.1. Comparison of Labor Productivity in Malaysia
SME/Large Firm Ratio SME/Large Firm Ratio
Labor productivity
Capita-labor ratio
Labor productivity
Capita-labor ratio
Manufacturing industries 0.54 0.42 Iron and steel 0.40 0.15
Textiles 0.51 0.29 Nonferrous metals 1.12 0.64
Apparel 0.80 0.90 Fabricated metals 0.61 0.48
Industrial chemicals 0.46 0.29 Machinery 0.36 0.56
Other chemicals 0.65 0.85 Wood products 0.73 0.26
Petroleum refining 0.29 0.08 Furniture and household
equipment 0.64 0.61
Other petroleum, coal products 0.91 1.83 Paper products 0.72 0.06
Scientific, measuring and control
instruments and equipment 0.41 0.88 Rubber products 0.76 0.44
Transport equipment 0.35 0.63 Food products 0.86 0.76
Plastic products 0.82 0.79 Other food products 1.09 0.60
Ceramics 0.60 0.73 Beverages 0.43 0.23
Glassware 0.62 0.42 Tobacco 0.04 ―p0.06
Nonmetallic mineral products 0.43 0.28 Printing and publishing 0.66 0.93
Source: Estimated by the author on the basis of the Survey of Manufacturing Industries of the Department of Statistics
equipment. No other subsectors show noticeably unexpected ratios.
SMEs have higher labor productivity than large companies in the four subsectors of leather prod-ucts and footwear, wood prodprod-ucts, paper, printing and publishing, and other manufacturing. Among these subsectors, labor productivity of SMEs in paper, printing and publishing has increased ra-pidly since 2000, largely because the spread of en-hanced means of ITC technology made it easier for SMEs to receive orders from overseas.
c. Japan
In Japan, it is noticeable that both the capital equipment ratio and labor productivity are uniformly lower for SMEs than for large companies. The highest labor productivity is 0.65 for wood and wood products, while the highest ratio for SMEs in the capital equip-ment ratio is 0.54 for the apparel subsector. These re-sults support the general description of SMEs as being labor-intensive. In line with this, SMEs have low labor productivity, and the gap between large companies and SMEs continues to widen.
Table 4.1.2. Comparison of Labor Productivity in Korea (2000-03 Average)
Industry
SMEｓ Major Firms SME/Large Firm Ratio
Labor productivity
Capital equipment
ratio
Labor productivity
Capital equipment
ratio
Labor
productivity Capital- labor ratio
Food, beverages, tobacco 308.51 97.28 338.1 133.2 0.91 0.73
Textiles, apparel 207.54 82.17 225.8 143.4 0.92 0.57
Leather products, footwear 275.92 39.27 242.0 56.1 1.14 0.70
Wood products 384.99 47.35 246.5 79.9 1.56 0.59
Paper, printing, publishing 322.13 143.41 272.5 253.4 1.18 0.57
Petroleum refining, petroleum and
coal products 192.85 91.52 316.9 204.8 0.61 0.45
Industrial chemicals 531.80 93.18 3017.9 1052.7 0.18 0.09
Other chemicals 311.34 124.64 516.9 285.0 0.60 0.44
Rubber and plastic products 220.17 81.38 251.9 146.2 0.87 0.56
Glassware, ceramics 295.94 129.58 399.5 331.1 0.74 0.39
Other nonmetallic mineral products 452.11 129.98 571.9 403.0 0.79 0.32
Iron and steel 220.57 78.16 271.5 107.9 0.81 0.72
Nonferrous metals 207.81 67.98 323.0 97.0 0.64 0.70
Fabricated metals 392.87 38.78 686.8 70.0 0.57 0.55
Machinery 231.01 59.25 375.1 152.7 0.62 0.39
Electric and electronic products 247.84 47.16 548.4 175.6 0.45 0.27
Medical and optical equipment 233.68 55.84 335.5 100.0 0.70 0.56
Transport equipment 280.30 101.66 384.7 120.1 0.73 0.85
Furniture and household
equipment 212.48 81.52 326.0 175.6 0.65 0.46
Other manufacturing 250.58 73.44 215.7 86.1 1.16 0.85
Unit: Million won/person
Table 4.1.3. Labor Productivity of large Firms and SMEs in Japan
Large Firms Labor Productivity ¥million/person
1981-85 1986-90 1991-95 1996-2000 2001-05
Manufacturing industries 6.89 7.87 8.35 9.33 10.33
Food 6.35 7.16 7.91 7.86 7.87
Textiles 4.35 5.50 5.85 6.53 7.10
Apparel and other textile products 4.50 5.29 5.64 5.72 5.58
Wood and wood products 4.60 6.60 7.15 6.05 6.44
Paper and pulp, paper products 7.66 8.81 8.51 9.31 9.38
Printing and related products 7.72 9.30 9.36 10.22 9.79
Chemicals 8.45 10.45 10.91 13.03 15.00
Petroleum and coal products 16.86 14.43 18.25 14.31 23.33
Ceramics, soil and stone 6.83 8.17 7.97 8.14 9.44
Iron and steel 8.06 10.19 10.24 10.47 14.09
Nonferrous metals 7.10 8.47 8.35 9.01 9.80
Metal products 5.94 7.52 7.92 7.45 7.87
General machinery and equipment 6.53 7.47 7.90 8.85 9.65
Electric machinery and equipment 6.69 7.15 7.68 9.17 9.44
Automobiles and accessories 6.56 7.30 7.44 9.24 11.64
Other transport machinery and equipment 7.07 7.51 11.43 10.75 10.53
Precision equipment and instruments 6.43 7.02 7.51 9.57 11.48
Other manufacturing 5.66 7.40 8.35 8.85 9.70
SMEs Labor Productivity ¥million/person
1981-85 1986-90 1991-95 1996-2000 2001-05
Manufacturing industries 3.91 4.72 5.10 4.93 4.78
Foodstuffs 3.31 3.73 4.13 3.92 3.70
Textiles 3.32 4.31 4.86 4.04 4.01
Apparel and other textile products 2.87 3.90 3.42 3.25 3.08
Wood and wood products 3.62 4.48 5.12 4.39 4.17
Paper and pulp, paper products 4.14 4.95 5.46 5.22 4.95
Printing and related products 5.07 5.73 6.02 5.49 5.45
Chemicals 5.21 6.18 6.61 6.15 6.21
Petroleum and coal products 5.09 6.95 7.20 6.98 6.33
Ceramics, soil and stone 4.00 5.20 5.52 5.39 5.11
Iron and steel 4.81 6.52 6.41 5.44 6.02
Nonferrous metals 4.91 5.64 6.02 5.57 5.41
Metal products 4.41 5.08 5.67 5.46 5.13
General machinery and equipment 4.53 5.69 6.03 5.77 5.86
Electric machinery and equipment 3.33 4.05 4.51 4.78 4.18
Automobiles and accessories 4.08 4.88 5.35 5.23 5.42
Other transport machinery and equipment 3.72 4.80 6.80 5.60 5.58
Precision equipment and instruments 4.12 4.59 4.98 5.31 5.18
Other manufacturing 3.79 4.67 5.18 5.21 4.79
Table 4.1.4. Capital-labor Ratio of large Firms and SMEs in Japan
Major Firms Capital-labor ratio ¥million/person
1981-85 1986-90 1991-95 1996-2000 2001-05
Manufacturing industries 6.96 8.40 11.00 12.01 12.31
Food 5.91 7.64 10.28 10.74 10.40
Textiles 4.20 7.03 10.40 12.42 13.51
Apparel and other textile products 1.86 2.37 3.80 4.01 3.33
Wood and wood products 3.98 5.05 6.90 8.01 8.78
Paper and pulp, paper products 14.18 20.11 25.60 27.93 26.94
Printing and related products 4.44 6.65 9.24 10.32 10.29
Chemicals 9.22 11.56 15.22 16.05 16.39
Petroleum and coal products 31.37 36.27 55.05 69.18 66.93
Ceramics, soil and stone 9.15 10.91 13.93 15.62 15.83
Iron and steel 18.76 20.72 28.14 34.55 33.43
Nonferrous metals 10.19 10.95 17.76 25.05 34.73
Metal products 5.00 6.26 8.64 9.02 8.97
General machinery and equipment 4.15 5.20 7.16 7.36 7.61
Electric machinery and equipment 4.07 5.60 7.12 8.36 9.14
Automobiles and accessories 6.21 7.54 10.10 10.11 10.45
Other transport machinery and equipment 4.60 6.10 9.10 11.11 10.89
Precision equipment and instruments 4.35 5.50 6.57 7.07 8.39
Other manufacturing 4.24 5.68 8.05 8.97 9.41
SMEs Capital equipment ratio ¥million/person
1986-90 1991-95 1996-2000 2001-05 0
Manufacturing industries 2.30 2.97 3.93 3.76 3.80
Food 2.53 2.90 3.87 3.97 3.88
Textiles 2.28 2.96 4.15 3.92 4.46
Apparel and other textile products 0.90 1.57 1.60 2.02 1.79
Wood and wood products 2.41 3.13 4.03 4.22 3.84
Paper and pulp, paper products 3.21 4.77 5.58 5.00 4.73
Printing and related products 2.38 3.23 4.31 3.61 3.85
Chemicals 3.10 4.10 6.05 5.35 6.18
Petroleum and coal products 3.88 5.57 7.46 6.43 5.73
Ceramics, soil and stone 2.92 4.23 5.72 5.65 5.46
Iron and steel 4.41 4.77 7.05 5.68 6.09
Nonferrous metals 3.16 4.17 5.66 4.33 4.02
Metal products 2.81 3.30 4.61 4.32 4.09
General machinery and equipment 2.39 2.88 4.04 3.94 3.58
Electric machinery and equipment 1.39 1.99 2.39 2.41 2.36
Automobiles and accessories 2.60 3.47 4.47 3.99 4.92
Other transport machinery and equipment 2.72 3.89 5.23 4.94 4.83
Precision equipment and instruments 1.68 2.39 2.97 2.91 3.15
Other manufacturing 2.08 2.98 4.05 3.68 3.38
Table 4.1.5. Comparison of Labor Productivity in Japan (SME/Large Firm Ratio) (2001-2005 Average)
Industry Labor
productivity
Capital equipment
ratio
Industry Labor
productivity
Capital equipment
ratio
Manufacturing industries 0.46 0.31
Food 0.47 0.37 Nonferrous metals 0.55 0.12
Textiles 0.56 0.33 Fabricated metals 0.65 0.46
Apparel 0.55 0.54 General machinery and
equipment 0.61 0.47
Wood and wood products 0.65 0.44 Electric and electronic products 0.44 0.26 Paper, pulp, paper products 0.53 0.18 Information and communication
equipment n.a. n.a.
Printing and publishing 0.56 0.37 Transport machinery and
equipment (aggregate) n.a. n.a.
Industrial chemicals 0.41 0.38 Automobiles and accessories 0.47 0.47
Petroleum and coal products 0.27 0.09 Other transport machinery and
equipment 0.53 0.44
Ceramics, soil and stone 0.54 0.35 Precision equipment and
instruments 0.45 0.38
Iron and steel 0.43 0.18 Other manufacturing 0.49 0.36
Source: Estimated by the author on the basis of Financial Statement Statistics of Corporations by Industry
4.2 Total Factor Productivity 4.2.1 Model
For Malaysia and Korea, we used cross section data for each sub-sector as we had data on indi-vidual firms. We use the stochastic frontier model to estimate the production function and efficiency.
Since our data is not a panel data, we estimate the production function for every year with cross sec-tion data and estimate the total factor productivity growth using the estimated parameters.
We specify the production function as follows.
) ( ) ( log )
(
log
Yi t
j Xij t
ei t (1)where
and
j is the elasticity of output with respect to i-th factor, and Yi(t) is the output of i-th firm. Xij(t) is the j-th input of i-th firm and ei(t) is the error term. Suffix i indicates firm and j indi-cates the factor and t stands for year. Thus we es-timated the Cobb-Douglas production function.With respect to the error term e, we follow Coelli, Rao and Battese (1998) and specify as follows.
it it
i V U
e
) , (
~
it U2it N m
U
) , 0 (
~
V2it N
V
where V is a random error with normal distribu-tion and U is a non-negative random variable to give the efficiency.
The technical efficiency of i-th firm is given by
)]
( )
[exp(
it it itit E U V U
TE
(2)We used the “Frontier 41” developed by Coelli, et.
al. to estimate the above model.
For Japan, we used aggregated data. So we es-timated the Cobb-Douglas production function for each sub-sector for SMEs and large firms using
time series data of 1980 to 2006.
Using the estimation results, we did the follow-ing analyses.
1) Estimation of the rate of technical change We use the following equation to estimate the growth rate of the total factor productivity of SMEs and large firms in each sub-sector and of all firms of manufacturing.
Rate of TFP Growth = (lnYt – lnYt-1) – 1/2(Skt + Skt-1)(lnKt – lnK t-1) –1/2(Slt + Slt-1)(lnLt– lnL t-1) (3)
Skt and Slt are the relative income shares of capital and labor in period t and we used the esti-mated values of equation (1).
For the estimation of the rate of TFP growth, we need the estimates of Skt and Slt. We use the es-timated values of
j’s in equation (1).2) Comparison of Total Factor Productivity
We apply the same equation to estimate the rel-ative productivity of SMEs against that of large firms in each sector as well as the total manufac-turing. In case of comparison of the total factor productivity, equation (3) becomes as follows.
TFP Ratio = (lnYlt – lnYst) – 1/2(Sklt + Skst)(lnKlt – lnKst) –1/2(Sllt + Sslt)(lnLlt– lnLst) (4)
where Ylt and Yst are the outputs of large firms and SMEs in year t, respectively. Similarly, Sklt and Skst are the shares of capital of large firms and SMEs, respectively.
4.2.2. Estimation Results
(1) Estimation of the rate of technological progress
As noted in the preceding section, the rate of change in total factor productivity (TFP) was es-timated as the rate of technological progress from year t to year t+1. The estimation for individual years can show large short-term fluctuations and
does not necessarily represent technological progress partly due to the impact of business cycles, etc. Hence, the average for several years was ex-amined, as discussed below.
a. Malaysia
Table 4.2.1 shows the average annual rate of technological progress from 1992 to 1999 for Ma-laysia. While the three-digit classification of man-ufacturing industries produces a total of 28 indus-try sectors, the table shows only 20 industries as
there are some sectors for large firms that could not be analyzed due to an insufficient number of samples, as a finer industry classification reduces the number of companies and/or simply data is not made public. All industries were covered for SMEs.
As indicated in the table, technological progress was seen in nearly all manufacturing industries over the estimation period. Exceptional negative figures are shown for large companies in the three industries of printing and publishing, industrial chemicals and transport equipment. Of the three,
Table 4.2.1. Rate of Technological Progress and Productivity Gap in Malaysian Manufacturing Industries
1 2 3 4 5
Rate of Technological Progress (％) (TFPG)
Industry Industry Large Firms SMEs Productivity
Gap (%)
311 Food 5.55 6.49 -5.69
321 Textiles 4.63 6.17 -0.12
322 Apparel 7.37 8.51 -0.84
331 Wood and wood products 9.45 6.61 0.87
332 Furniture and household equipment 10.88 6.67 10.48
341 Paper and paper products 6.49 6.24 0.97
342 Printing and publishing -0.72 4.30 -12.00
351 Industrial chemicals -0.79 5.74 1.60
352 Other chemicals 5.00 10.94 -20.18
355 Rubber products 10.97 14.07 5.47
356 Plastic products 4.15 4.90 -12.66
369 Nonmetallic mineral products 1.65 9.99 14.29
371 Iron and steel 4.59 5.60 -9.54
372 Nonferrous metals 10.13 3.85 4.36
381 Fabricated metals 6.21 4.54 -8.67
382 Machinery 7.17 11.16 -6.49
383 Electric and electronic products 10.63 10.28 3.20
384 Transport equipment -2.90 5.96 1.00
385 Scientific, measuring and control equipment 10.90 5.96 15.48
390 Other manufacturing 0.35 14.04 15.78
Source: Estimated by the author
industrial chemicals and transport equipment are priority industries and are heavily protected by the government.
For SMEs, the rate of technological progress was positive for all industry subsectors. The lowest rate was 3.85% for nonferrous metals, the bulk of industries registered rates of over 5%, and the rates were in excess of 10% for five subsectors:
other chemicals, rubber products, machinery, electric and electronic products, and other manu-facturing. The estimation results for SMEs show technological progress across all industrial sub-sectors.
With regard to major firms, as noted above, there were major gaps between subsectors, with some having negative figures. This stems partly from the fact that because of the relatively small number of companies covered, the performance of a single company could have a large impact on the subsec-tor as a whole.
Under Malaysia’s economic development policy, industries are classified into four groups: interna-tional industries, policy-guided industries, re-sources-related industries and other industries.
However, no distinct relationship can be seen be-tween the group classification and the analysis
results shown in Table 4.2.1. In other words, even policy-guided industries failed to display notewor-thy technological progress. While many interna-tional industries showed higher rates of technolo-gical progress, the rate was negative for large companies in industrial chemicals.
b. Korea
The estimated rate of change of total factor productivity by subsector for Korea’s manufactur-ing industries is shown in Table 4.2.2., which in-dicates that Korea also had the large increase in productivity for manufacturing industries as a whole over the course of the estimation period.
Negative growth was registered only by large companies in iron and steel, and petroleum refin-ing and petroleum and coal products. Negative growth in these two subsectors was the direct re-sult of the Asian financial crisis of 1997-1998. The sharp fall in capacity utilization in 1998 led to a steep drop in the rate of technological progress in the year into negative territory, making the aver-age for the estimation period negative. Similar de-velopments were observed in some subsectors, but were not sufficiently large to make the average rate for the entire period negative.
Table 4.2.2. Rate of Change in TFP in Korea’s Manufacturing Industries by Subsector (Average for 1995-2003) (%)
Industry Large
Firms SMEs Industry Large
Firms SMEs
Food, beverages, tobacco 3.61 4.17 Nonmetallic mineral products 5.62 3.46
Textiles, apparel 4.74 6.54 Iron and steel -4.68 4.42
Leather products, footwear 5.59 4.45 Nonferrous metals 6.65 5.51
Wood products 2.90 6.26 Fabricated metals 10.34 6.37
Petroleum refining, petroleum and coal products -3.73 18.92 Machinery 5.27 6.24
Industrial chemicals 3.44 9.66 Electric and electronic products 16.74 12.22
Other chemicals 7.32 6.48 Medical and optical equipment 9.64 11.32
Rubber and plastic products 2.16 5.93 Transport equipment 7.39 2.64
Glassware, ceramics 8.85 7.43 Furniture and household equipment 6.39 6.18
Other manufacturing 3.88 3.12
Source: Estimated by the author