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pISSN : 1738-7132

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2021, Vol.30, No.1

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    Analysis of the employment impact of the minimum wage increase in 2018 and its implications

    Jin Sung Yoo | 2021, 30(1) | pp.9~28 | number of Cited : 0
    Abstract PDF
    In this study, I analyzed the effect of the rapid increase in the minimum wage in 2018 on employment using the recent Korean Welfare Panel Study. As a result, it was found that the sharp increase in the minimum wage in 2018 reduced the employment rate of those subject to the minimum wage by about 4.1 to 4.6 percentage points. It is also analyzed that about 27.4~30.5% of the unemployed ratio in the group subject to the minimum wage is due to the rapid increase in the minimum wage in 2018. As it has been shown that a sharp increase in the minimum wage has a negative effect on employment, it is necessary to refrain from rapid increase in the minimum wage in the future. If a minimum wage increase is inevitable, it is necessary to avoid a big increase and find ways to reduce the negative impact on the employment, for example, by gradually increasing the minimum wage, or applying differentiated level by industry to the minimum wage, and so on.
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    An Analysis on the Environmental Cost from the Deregulation of the Regulation on Supervision of Electronic Financial Transactions

    Seungyoon Lee | Lim, Byung-in | 2021, 30(1) | pp.29~53 | number of Cited : 0
    Abstract PDF
    Korea government relaxed the regulation of Electronic Finance Supervision(hereafter, EFS) in January, 2019 before global IT companies have established a Data Center for private financial information. The deregulation made the Microsoft and the Google build in 2019 and provide the Cloud Service in 2020, and also many global IT companies, like Apple, Oracle, Facebook, declared that the Data Center would construct in Korea. We estimate the environmental cost from a Data Center under an assumption that the electric power facility capacity of a Data Center is 40, then it cost about 6.4 billion Korean Won, and converted it to the present value, 87 billion Korean Won, by using both the life cycle period(20 year) of a Data Center and the social discount rate(4.5%). It implies that Data Center has a negative influence on the environment. Nevertheless, the EFS deregulation does not provide any kinds of restrictions or conditions on the environment now. In fact, overseas global IT companies are well aware of the environmental problems induced by their Data Centers and steadily make efforts to use the renewable energy more, but they don’t still take the same action in Korea. In this context, we derive a following policy implication: any kinds of supplementary and environmental condition for overseas global IT companies to deploy and build the Data Center in Korea should be added, i.e., the production of the electricity with a renewable energy by themselves, etc.
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    A study on the identification of policy demand for project-type regulatory sandbox through the analysis of perception differences in stakeholders

    HaeOk CHOI | Kwang-ho Lee | 2021, 30(1) | pp.55~78 | number of Cited : 0
    Abstract PDF
    Since the existing regulatory improvement mainly aims to amend laws or to reorganize governance, it often fails to reflect the perceptions of the stakeholder’s, involved in the regulatory improvement process. Therefore, this study is meaningful in that it provided policy implications by identifying the stakeholder’s participating in the regulatory sandbox in order to overcome the limitations of existing studies. First, in the project-type regulatory sandbox, the issues related to evaluation and certification will be the most important factor for law revisions. Second, it is necessary to clearly set the differences between the place-based empirical issues in the project-type and regional-limited regulatory sandbox. Third, in the case of new technology, it is difficult to purchase insurance due to the limitations of insurance. So it need to use deduction system for implementation. Fourth, in the safety verification-related examination procedure, the examination procedure should be simplified. This study suggests that there is a need for a support system that identifies the perception differences of stakeholder’s participating in the regulatory sandbox.
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    From Comprehensively Negative to Flexible Regulation: A Search for an Innovation-friendly Principle of Regulatory Reform

    Seung-Hun Hong | 2021, 30(1) | pp.79~118 | number of Cited : 0
    Abstract PDF
    The Moon Jae-in government has put forward regulatory reform of newly emerging technologies based on the comprehensively negative principle. This regulatory principle was achieved through the methods of flexible regulatory rulemaking and regulatory sandbox. However, unlike regulatory sandbox, which has been actively developing, the reform regarding flexible regulatory rulemaking displayed slow progress. The purpose of this article is to present flexible regulation as a new principle for regulatory reform of newly emerging technologies by defining its concept and rationale theoretically. Two tasks are tackled. First, the article analyzes regulatory reform cases in the fields of smart mobility, bio-health and fintech and points out limits of flexible regulatory rulemaking as a tool for making regulation flexible. Second, it defines flexible regulation as diversifying the choices of regulatees that achieve the regulatory objectives across regulatory governance, which comprises rule structure, enforcement structure and regulatory feedback. Here, the flexibility of regulatory rulemaking becomes a way of achieving flexible regulation, and the principle of comprehensively negative becomes one way to achieve flexible rule structure. Drawing on regulatory theories that have been presented as alternatives to command-and-control regulation, this article builds systematic ways to increase the choices of regulatees, establishes the system of classifying flexible regulation and presents policy implications and suggestions for future research.
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    Exploring the Possibility of Ai-Aid-Ria: Focusing on Occupational Safety And Health Regulations

    SUIMYANG | Su-Ah Lee | Shinhoi, Heo and 1other persons | 2021, 30(1) | pp.119~162 | number of Cited : 0
    Abstract PDF
    In this study, problems occurring in the regulatory impact analysis process were theoretically confirmed. It was suggested that the use of AI can overcome these problems. Furthermore, it exemplified that AI can overcome problems in the implementation process through the case of occupational safety and health regulation regulatory impact analysis. First, the general difficulties of regulatory impact analysis were analyzed with three theories of Rational decision-making theory(analysis), Principal-agent theory(control), and Governance theory(participation). It presented how the difficulties of each regulatory impact analysis could be overcome if AI was introduced. Afterwards, based on the case of Occupational Safety and Health Regulatory RIA, the essential difficulties in the process of conducting the regulatory impact analysis were divided into four areas: identification of regulatory impact groups, deriving scenarios, and evaluation and deduction of costs and benefits of regulatory impacts. AI techniques and tasks that can be specifically used in each of the four fields are exemplified. As a result, in the analytical aspect, AI possesses the strengths of data collection and organization, powerful computation, and optimization computation, so it is possible to ① time and budget saving, ② analysis technique improvement and objectification of subjective value, ③ mass data handling, ④ securing timeliness, and ⑤ Conduct comparative analysis of alternatives. In terms of control, continuous monitoring made it possible to ① identify the owner's preferences, ② prevent capture and become independent from political logic, and ③ enhance expertise and acquire information. Lastly, in the participatory aspect, it was possible to collect and reflect real-time public opinion through the expansion and management of its own data. Therefore, by introducing AI into specific administrative areas (regulatory impact analysis), evidence-based administration centered on objective data is possible. In addition, through participation and two-way communication, AI can assist in the overall institutional decision-making process.