• Journal of Korea Technology Innovation Society
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• v.15 no.3
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• pp.649-674
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• 2012

The purpose of this study is to investigate the effects of public R&D subsidies on private R&D. We have analyzed rationales for the public R&D subsidy from different perspectives. On the basis of literature review, a two step research model is constructed: participation phase (when firms benefit from public subsidies) and decision phase (when firms make decision on additional R&D investments). Using propensity score matching(PSM) method, we compare the potential outcome of the treated group to a matched controlled group of non-subsidized firms. The data used in this paper was collected from various sources. The Korean Innovation Survey 2008(manufacturing sector) is a main source of data. Financial data such as revenue, asset and capital stock, and number of employees were supplemented from the Nice Information Service KIS Value database. The R&D survey, conducted by MEST(Ministry of Education, Science and Technology) each year, was also used for the R&D expenditures of the manufacturing firms. This study comes up with the following empirical results. First, a firm's innovation capability, financial constraints, and sector appear to influence the selection of firms who were benefited from government's financial supports for R&D. Second, empirical results show that public R&D funding complements private investment on average and appear to have perpetual effects on the following year. Finally, sectoral difference in the effect of public subsidies on firms' R&D investment was confirmed. In addition, SMEs show more positive effects than large firms.

• KDI Journal of Economic Policy
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• v.12 no.4
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• pp.3-20
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• 1990

The multisector model is designed to analyze and forecast structural change in industrial output, employment, capital and relative price as well as macroeconomic change in aggregate income, interest rate, etc. This model has 25 industrial sectors, containing about 1,300 equations. Therefore, this model is characterized by detailed structural disaggregation at the sectoral level. Individual industries are based on many of the economic relationships in the model. This is what distinguishes a multisector model from a macroeconomic model. Each industry is a behavioral agent in the model for industrial investment, employment, prices, wages, and intermediate demand. The strength of the model lies in the simulating the interactions between different industries. The result of its simulation will be introduced in the next paper. In this paper, we only introduce the structure of the multisector model and the coefficients of the equations. The multisector model is a dynamic model-that is, it solves year by year into the future using its own solutions for earlier years. The development of a dynamic, year-by-year solution allows us to combine the change in structure with a consideration of the dynamic adjustment required. These dynamics have obvious advantages in the use of the multisector model for industrial planning. The multisector model is a medium-term and long-term model. Whereas a short-term model can taken the labor supply and capital stock as given, a long-term model must acknowledge that these are determined endogenously. Changes in the medium-term can be analyzed in the context of long-term structural changes. The structure of this model can be summarized as follow. The difference in domestic and world prices affects industrial structure and the pattern of international trade; domestic output and factor price affect factor demand; factor demand and factor price affect industrial income; industrial income and relative price affect industrial consumption. Technical progress, as measured in terms of total factor productivity and relative price affect input-output coefficients; input-output coefficients and relative price determine the industrial input cost; input cost and import price determine domestic price. The differences in productivity and wage growth among different industries affect the relative price.

• Journal of Technology Innovation
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• v.21 no.2
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• pp.169-197
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• 2013

Despite many theoretical and empirical studies, general causality between IPRs system, firm technological innovation and financial performance is not clear. This study notices that the core factor to create financial performance is different by each industry. The study analyzed the effect of IPRs system on innovation and economic growth targeting 3 industries; pharmaceutical industry to which the basic track of creating performance is applied (strengthening IPRs${\rightarrow}$increasing R&D input/output${\rightarrow}$increasing sales); semiconductor industry where the relationship between stronger IPRs and R&D input/output is weak; and shipbuilding industry which has weak correlation between R&D and sales. It used panel data for 15 years since TRIPs when the patent institution in Korea reached up to the level of advanced countries, and applied the dynamic regression model which estimates the fixed effect model with difference-GMM. As a result, stronger IPRs increased R&D input/output, and financial performance in pharmaceutical industry, but has no influence on semiconductor and shipbuilding industries. That is, it is necessary to customize the construction of system and policy for strengthening IPRs by each industry, and unitary strengthening or weakening may have no significant impact on financial performance improvement in specific sectors.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.441-453
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• 2021

Recently, the untact healthcare industry due to COVID-19 has been attracting attention, and the telemedicine industry based on medical information has become a field of the healthcare industry receiving attention. However, in Korea, due to obstacles in the legal system, telemedicine is still illegal between doctors and patients. In the case of neighboring China, the reality is the opposite of the recent rapid growth of the telemedicine industry under the leadership of the government. This study looks at this from the perspective of the industrial innovation system on the grounds that telemedicine is an industry and innovative technology needs to be changed to clarify the difference between domestic and Chinese telemedicine industries. As a result of analyzing China's telemedicine industry on the seven sub-divisions of demand conditions, innovators, networks et al., Such as seizing appropriate opportunities for demand driving effects and appropriate communication between economic actors were identified as major success factors. This researcher proposes the following suggestions. first, it conforms to the current digital New Deal policy flow, and conducts a demand survey on the change in demand for medical services in the 4th Industrial Revolution and the Untact Era. For the introduction, a plan to conduct a demand survey for the public and second, second, a plan to grow and intensively foster digital high-tech medical care as a new industry was suggested.

• Journal of Korea Trade
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• v.27 no.5
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• pp.113-136
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• 2023

Purpose - Global production chains and their impacts on economic growth have drawn extensive attention from researchers. Close relationships among global production chains, export and economic growth have been illuminated, as evidenced by the fast and stable economic growth of East Asian economies. These economies perform various roles within global production chains using offshoring, in which the impact of import on domestic gross output is as strong as that of export. The impact of import on economic growth would depend on whether imported inputs substitute or complement domestic inputs production, which is likely to vary according to individual countries' functions within global production chains. The economic growth of concerned countries would also be diverse. However, little attention has been paid to the impact brought by imports compared to its significance. Design/methodology - The principal methodology used in this paper is structural decomposition analysis (SDA), widely chosen to elucidate the impact of various factors on domestic gross output using input-output tables. This paper extracts trade data of six Asian economies from the World Input-Output Database (WIOD) 2016 release that covers 43 countries for the period 2000-2014. The extracted data is then categorised into 37 sectors. First, this paper calculates the Feenstra-Hanson Offshoring Index (OSI) of each country. It then applies SDA to measure the changes in each economy's gross output, export, import input coefficients, and domestic input coefficients. Finally, after taking the first difference from pooled time-series data, it estimates the correlations between imported input coefficients and OSI using the ordinary least square (OLS) method. Findings - The main findings of this paper can be summarised as follows. Firstly, all six countries have increasingly engaged in global production chains, as evidenced by the growing size of OSI. Secondly, there are negative correlations in five countries except Japan, with sectoral differences. Thirdly, changes in import input coefficients are not negative in all six countries, indicating that offshoring does not necessarily substitute for domestic inputs production but does complement it and, therefore, fosters their economic growth. This is observed in China, Indonesia, Korea and Taiwan. Offshoring has led to an increase in the use of imported inputs, which has, in turn, stimulated domestic inputs production in these countries. Originality/value - While existing studies focus on the role of export in evaluating the impact of participating global production chains, this paper explicitly examines the unexplored impact of import on domestic gross output by considering both the substitution and the complementary effect, using the WIOD. The findings of this paper suggest that Asian economies have achieved fast and stable economic growth not only through successful export management but also through effective import management within global production chains. This paper recommends that the Korean government and enterprises carefully choose offshoring strategies to minimise disruption to domestic production chains or foster them.