{"title":"The Regulatory Impact on Services Trade in Korea","authors":"Junghwan Cho, Seung-Hwan Yoon","doi":"10.20294/jgbt.2022.18.4.33","DOIUrl":null,"url":null,"abstract":"Purpose – This study aims to analyze the effect of Korea's Services Trade Restrictiveness Index (STRI) and STRI Heterogeneity Index (HG) on Korea’s services trade. \nDesign/Methodology/Approach – Using the Poisson Pseudo Maximum Likelihood (PPML) model, this study analyzes the impact of STRI and STRI HG provided by the OECD for 26 countries on Korea’s services trade (imports). The reason for using PPML is that first, a consistent estimator can be obtained regardless of the error term’s distribution. Second, if there is net-zero services trade in the data, sample selection bias can occur as the zero-trade data is excluded from the analysis when using ordinary least squares (OLS). \nFindings – After converting the STRI and the STRI HG into a single index through principal component analysis (PCA), results show that the STRI is not statistically significant, but the STRI HG shows a statistically significant negative (-) sign in all analysis models. This means that the greater the STRI HG with Korea's trading partners, the more negative the impact on services trade, which implies that even if the level of services restrictiveness is low, services trade volume will reduce as regulatory coherence with trading partners decreases. \nResearch Implications – Whereas previous studies primarily focused on major advanced countries such as OECD nations or specific service industries, this study analyzes the impact of the services trade restrictiveness on services trade for Korea and each services sector. In addition, existing studies perform cross-sectional analyses due to data availability, whereas this study reflects changes in services restrictiveness levels over time by constructing panel data for 2014–2019.","PeriodicalId":190222,"journal":{"name":"International Academy of Global Business and Trade","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Academy of Global Business and Trade","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20294/jgbt.2022.18.4.33","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose – This study aims to analyze the effect of Korea's Services Trade Restrictiveness Index (STRI) and STRI Heterogeneity Index (HG) on Korea’s services trade.
Design/Methodology/Approach – Using the Poisson Pseudo Maximum Likelihood (PPML) model, this study analyzes the impact of STRI and STRI HG provided by the OECD for 26 countries on Korea’s services trade (imports). The reason for using PPML is that first, a consistent estimator can be obtained regardless of the error term’s distribution. Second, if there is net-zero services trade in the data, sample selection bias can occur as the zero-trade data is excluded from the analysis when using ordinary least squares (OLS).
Findings – After converting the STRI and the STRI HG into a single index through principal component analysis (PCA), results show that the STRI is not statistically significant, but the STRI HG shows a statistically significant negative (-) sign in all analysis models. This means that the greater the STRI HG with Korea's trading partners, the more negative the impact on services trade, which implies that even if the level of services restrictiveness is low, services trade volume will reduce as regulatory coherence with trading partners decreases.
Research Implications – Whereas previous studies primarily focused on major advanced countries such as OECD nations or specific service industries, this study analyzes the impact of the services trade restrictiveness on services trade for Korea and each services sector. In addition, existing studies perform cross-sectional analyses due to data availability, whereas this study reflects changes in services restrictiveness levels over time by constructing panel data for 2014–2019.