• East Asian Economic Review
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• v.23 no.2
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• pp.169-202
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• 2019

Productivity in agriculture or services has long been understood as playing an important role in the growth of manufacturing. In this paper we present a general equilibrium model in which manufacturing growth is stimulated by non-manufacturing sectors that provides goods used in both research and final consumption. The model permits the evaluation of two policy options for stimulating manufacturing growth: (1) a country imports more non-manufacturing goods from a foreign country with higher productivity and (2) a country increases productivity of domestic non-manufacturing. We find that both policies improve welfare of the economy, but depending on the policy the manufacturing sector responses differently. Specifically, employment and value-added in manufacturing increase with policy (1), but contract with policy (2). Therefore, specialization of the import non-manufactured goods helps explain why some Asian economies experience rapid growth in the manufacturing sector without progress in other sectors.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.1 no.1
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• pp.105-125
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• 2006

This paper relates recent empirical research on the growth. Smaller and younger firms have been growing more quickly than larger and older firms, thus, generating proportionately more new jobs. It is not difficult to understand why small and medium firms receive so much attention. Because SMEs provide about 80 percent of private sector employment so SMEs performance is an important economic and social factor. Despite this, they are subject to higher risk and mobility than those at the large firms. This paper is analyzes the relationship between firm growth measured as growth in employment, sales and production and firms age, size and R&D investment. The growth and its relationship with the determinants is linked to industrial policy in Korea. Empirical results are based on an unbalanced panel data covering period 1999-2002. Results show significant relationship between growth, size and age of firm.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.751-763
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• 2022

With the recent increase in spending growth in the IoT sector worldwide, the importance of lightweight block ciphers to encrypt them is also increasing. The lightweight block cipher PIPO algorithm proposed in ICISC 2020 is an SPN-structured cipher using an unbalanced bridge structure. The white box attack model refers to a state in which an attacker may know the intermediate value of the encryption operation. As a technique to cope with this, Chow et al. proposed a white box implementation technique and applied it to DES and AES in 2002. In this paper, we propose a white box PIPO applying a white box implementation to a lightweight block cipher PIPO algorithm. In the white box PIPO, the size of the table decreased by about 5.8 times and the calculation time decreased by about 17 times compared to the white box AES proposed by Chow and others. In addition, white box PIPO was used for mobile security products, and experimental results for each test case according to the scope of application are presented.

• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.35-47
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• 2004

Using data envelopment analysis, this paper annually estimates Malmquist total factor productivity indices and decomposes them into productive efficiency change, technical change, and scale change components for three publicly-owned rail transit properties: the Seoul Subway Corporation(SSC), the Seoul Metropolitan Electrified Railways Sector of Korea National Railroad (SMESRS) and the Busan Urban Transit Authority (BUTA). The paper then conceptualizes that the property produces a single output(car-kilometers) using four inputs(labor, electricity, car and maintenance, and track) and uses unbalanced panel data consisted of annual observations on SSC, SMESRS and BUTA. The results show that the average annual growth rate of productivity of the three properties is 6.6 percent, which is 0.5 percent less than the average annual increasing rate of their labor price. They also show that the greatest part of the growth in productivity is explained by technical change and to a lesser degree by scale change and changes in productive efficiency though each of the three components contributes more than 20 percent to the growth in productivity, These results suggest that the three properties should base the increasing rate of their wages on the growth rate of their productivity and utilize existing technologies more efficiently prior to introducing new ones to raise their productivity, and that all the three components should be considered to evaluate their productivity more correctly.

• Journal of Technology Innovation
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• v.17 no.1
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• pp.1-48
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• 2009

Recently we have found some symptoms that R&D fiscal incentives might not work well what it has intended through the analysis of current statistics of firm's R&D data. Firstly, we found that the growth rate of R&D investment in private sector during the recent decade has been slowdown. The average of growth rate (real value) of R&D investment is 7.1% from 1998 to 2005, while it was 13.9% from 1980 to 1997. Secondly, the relative share of R&D investment of SME has been decreased to 21%('05) from 29%('01), even though the tax credit for SME has been more beneficial than large size firm, Thirdly, The R&D expenditure of large size firms (besides 3 leading firms) has not been increased since late of 1990s. We need to find some evidence whether fiscal incentives are effective in increasing firm's R&D investment. To analyse econometric model we use firm level unbalanced panel data for 4 years (from 2002 to 2005) derived from MOST database compiled from the annual survey, "Report on the Survey of Research and Development in Science and Technology". Also we use fixed effect model (Hausman test results accept fixed effect model with 1% of significant level) and estimate the model for all firms, large firms and SME respectively. We have following results from the analysis of econometric model. For large firm: i ) R&D investment responds elastically (1.20) to sales volume. ii) government R&D subsidy induces R&D investment (0.03) not so effectively. iii) Tax price elasticity is almost unity (-0.99). iv) For large firm tax incentive is more effective than R&D subsidy For SME: i ) Sales volume increase R&D investment of SME (0.043) not so effectively. ii ) government R&D subsidy is crowding out R&D investment of SME not seriously (-0.0079) iii) Tax price elasticity is very inelastic (-0.054) To compare with other studies, Koga(2003) has a similar result of tax price elasticity for Japanese firm (-1.0036), Hall((l992) has a unit tax price elasticity, Bloom et al. (2002) has $-0.354{\sim}-0.124$ in the short run. From the results of our analysis we recommend that government R&D subsidy has to focus on such an areas like basic research and public sector (defense, energy, health etc.) not overlapped private R&D sector. For SME government has to focus on establishing R&D infrastructure. To promote tax incentive policy, we need to strengthen the tax incentive scheme for large size firm's R&D investment. We recommend tax credit for large size film be extended to total volume of R&D investment.