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    Effects of the Utilization of Non-Reciprocal Trade Preferences Offered by QUAD Countries on Economic Growth in Beneficiary Countries

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    The present article investigates empirically whether non-reciprocal trade preferences (NRTPs) offered by QUAD countries (Canada, the European Union, Japan, and the United States) to developing countries have helped to promote economic growth in the beneficiary countries. Two main blocks of NRTPs are considered here: Generalized System of Preferences (GSP) programs and other trade preferences programs. The analysis used a set of 90 beneficiary countries of NRTPs that are concurrently recipients of development aid over the period of 2002-2018. Using the two-step system generalized method of moments, the analysis indicated that while a higher degree of utilization of each of these two blocks of NRTPs has been associated with a high economic growth rate, development aid enhances this positive effect. This highlights the need for donors to support a development strategy based on the provision of both development aid and NRTPs if they are to help beneficiary countries to promote economic growth. Finally, when the positive economic growth effect of the utilization of NRTPs is higher, the result is a greater country’s share of exports (under preferential tariffs) to QUAD countries out of their total merchandise exports

    Feasibility trade-offs in decarbonising the power sector with high coal dependence: The case of Korea

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    Decarbonising the power sector requires feasible strategies for the rapid phase-out of fossil fuels and the expansion of low-carbon sources. This study assesses the feasibility of plausible decarbonisation scenarios for the power sector in the Republic of Korea through 2050 and 2060. Our power plant stock accounting model results show that achieving zero emissions from the power sector by the mid-century requires either an ambitious expansion of renewables backed by gas-fired generation equipped with carbon capture and storage or a significant increase of nuclear power. The first strategy implies replicating and maintaining for decades the maximum growth rates of solar power achieved in leading countries and becoming an early and ambitious adopter of the carbon capture and storage technology. The alternative expansion of nuclear power has historical precedents in Korea and other countries but may not be acceptable in the current political and regulatory environment. Hence, our analysis shows that the potential hurdles for decarbonisation in the power sector in Korea are formidable but manageable and should be overcome over the coming years, which gives hope to other similar countries.3

    Predictive Abilities of Inflation Expectations and Implications on Monetary Policy in Korea

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    This paper examines the predictive abilities of various inflation expectation indicators for inflation in Korea. We conducted real-time out-of-sample forecasting experiments utilizing three inflation expectation indicators – the general public’s expectation, professional forecasters’ expectation, and break-even inflation (BEI). The results can be summarized as follows: (i) BEI is at least as useful as the other expectation indicators in forecasting inflation; (ii) regression-based models using industrial production, oil price, and exchange rate do not help out-of-sample inflation forecasting in general; (iii) the policy interest rate, in contrast, can significantly reduce the forecasting errors; and (iv) a one percent-point increase in the policy interest rate is estimated to suppress inflation for the subsequent 12 months by around one percent-point. These results suggest that monetary policy is effective for controlling inflation and a simple model using the policy interest rate and an inflation expectation indicator may be preferred for inflation forecasting.1

    Investigating Effects of Customer Satisfaction, Awareness, Participation for e-CRM-Oriented Non-Profit Organization’s Public Sector Marketing : The Case of the Republic of Korea National Red Cross

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    본 연구는 비영리기관의 공공 기관 디지털 마케팅 활동 및 CRM에 관한 실증 연구로 대한적십자사의 디지털 마케팅 활동 사례를 양적 및 질적 분석을 통해 검토하고, 마케팅 활동의 중요 요소인 웹사이트의 정보의 질, 최신성, 유용성, 심미적 요인, 참여도 및 인지도가 고객만족도에 유의한 영향을 미치는지를 분석했다. 양적 분석은 대한적십자사의 만족도 설문조사 데이터를 활용해, 다중회귀분석을 적용하여 가설을 검증했고, 질적 분석은 전문가 개별 심층 인터뷰로 분석했다. 본 연구의 결과로 공공기관 마케팅 활동에서 정보의 질, 최신성, 유용성, 심미적 요인, 참여도 및 인지도가 고객 만족도에 유의한 영향을 미치는 것을 확인했고, 효과의 크기는 인지도, 유용성, 심미적 요인, 정보의 질, 정보의 최신성, 참여도 순으로 나타났다. 본 연구는 영리 기업에 활용되고 있는 마케팅 활동이 비영리 기관에도 적용되며e-CRM의 응용이 공공기관의 마케팅 활동의 중요한 부분이며 이에 따른 시사점을 제시한다.2

    Consumer Behavior towards E-Commerce in the Post-COVID-19 Pandemic: Implications for Relationship Marketing and Environment

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    Purpose: The purpose of this research paper is to explore what factors that affect customer purchase decisions in the online environment, particularly after the COVID-19 pandemic in the case of Vietnamese customers. Research Design, Data and Methodology: To clarify which factor has the most significant impacts on online purchasing decision-making process, this study proposed a research model including factors such as customer trust, proposensity to trust, system assurance, the quality of website design, attitude, and customer satisfaction. This study collected the data via online survey. Data analysis was conducted by AMOS 25.0 using the Structural Equation Modeling (SEM) method. Result: The results of this study shows that the purchase decisions were positively affected by customers’ attitude, satisfaction, trust, and the quality of websites design. Additionally, factors such as perceived size and reputation and system assurance, have impacts on buyers’ trust, while the propensity to trust has no significant impact. Conclusion: This study provides managerial implications. The results provide which factors should be improved to foster trust, attitude, customer satisfaction, and purchase decision in the online environment. The results also provide managerial implication on marketing strategies how to enhance better relationships with customers and to consider environmental issues in the era of post COVID-19.2

    성별에 따른 노동공급의 장기 추세, 1981~2021

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    Regulatory Sentiment and Economic Performance

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    Regulatory sentiment refers to the market’s subjective evaluation of regulatory reform and is one of the most widely adopted indicators to those charged with implementing and diagnosing regulatory policies. The use of regulatory sentiment in advanced analysis has become universal, albeit it is often limited due to difficulties in articulating consistent and objective quantitative indicators that can meticulously reflect market sentiment overall. Thus, despite ample effort by scholars to read the economic impact of regulatory sentiment in the real economy, causal links are difficult to spot. To fill this gap in the literature, this study analyzes a regulatory sentiment index and economic performance indicators through a text analysis approach and by inspecting diverse tones in media articles. Using different stages of tests, the paper identifies a causal relationship between regulatory sentiment and actual economic activities as measured by private consumption, facility investment, construction investment, gross domestic investment, and employment. Additionally, as a result of analyzing one-unit impulse of regulatory perception, the initial impact on economic growth and private investment was found to be negligible; this was followed by a positive (+) response, after which it converged to zero. Construction investment showed a positive (+) response initially, which then rapidly changed to a negative (-) response and then converged to zero. Gross domestic investment as the initial effect was negligible after showing a positive (+) reaction. Unfortunately, the facility investment outcome was found to be insignificant in the impulse response test. Nevertheless, it can be concluded that it is necessary and important to increase the sensitivity to regulations to promote the economic effectiveness of regulatory reforms. Thus, instead of dealing with policies with the vague goal of merely improving regulatory sentiment, using regulatory sentiment as an indicator of major policies could be an effective approach

    Equal Education, Unequal Outcomes?

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    Service Matters: Capital Misallocation and Sectoral Economic Growth

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    Growth of the Korean economy has been sluggish, and this situation is more pronounced in the service sector. We argue that capital misallocation, especially in the service sector, could contribute to this slowdown. Utilizing firm and sectoral level data, first we assess the rising dispersion of the marginal revenue product of capital (MRPK) driven by the service sector. This could represent a widening misallocation of capital. Furthermore, a panel regression shows that within-sector misallocations at the sectoral level are closely correlated with the lower growth rate of sectoral real value added. Again, this is mainly observed in the service sector, but not in the manufacturing sector. Misallocations of other resources, labor and the intermediate inputs do not stand out

    Improving Estimates of Mean Welfare and Uncertainty in Developing Countries

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    Reliable estimates of economic welfare for small areas are valuable inputs into the design and evaluation of development policies. This paper compares the accuracy of point estimates and confidence intervals for small area estimates of wealth and poverty derived from four different prediction methods: linear mixed models, Cubist regression, extreme gradient boosting, and boosted regression forests. The evaluation draws samples from unit-level household census data from four developing countries, combines them with publicly and globally available geospatial indicators to generate small area estimates, and evaluates these estimates against aggregates calculated using the full census. Predictions of wealth are evaluated in four countries and poverty in one. All three machine learning methods outperform the traditional linear mixed model, with extreme gradient boosting and boosted regression forests generally outperforming the other alternatives. The proposed residual bootstrap procedure reliably estimates confidence intervals for the machine learning estimators, with estimated coverage rates across simulations falling between 94 and 97 percent. These results demonstrate that predictions obtained using tree-based gradient boosting with a random effect block bootstrap generate more accurate point and uncertainty estimates than prevailing methods for generating small area welfare estimates


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