• Journal of Korea Trade
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• v.24 no.3
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• pp.1-19
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• 2020

Purpose - This study empirically analyzes the effects of provisional anti-dumping duties levied on imports by Korea following anti-dumping investigations. An anti-dumping duty is a legal tool that countries use to impose duties on imports to offset injurious dumping. This study verifies how effective the imposition of a provisional anti-dumping duty is and whether such duties have trade chilling effects on aggregate imports. Specifically, this study examines import trade diversion from named to unnamed countries caused by the imposition of provisional anti-dumping duties. Design/methodology - This empirical analysis employs an econometric model of provisional anti-dumping measures for cases in which Korea imposed final affirmative anti-dumping measures. We construct a monthly panel dataset for each stage of anti-dumping investigation undertaken by Korea for all manufacturing industries during 1995-2013. We illustrate a stage-by-stage analysis of anti-dumping investigations from initiation, preliminary decision, imposition of provisional duty, final affirmative decision, and imposition of final affirmative duty on a monthly basis at the six-digit harmonized system code-level. Findings - For cases in which provisional duties are imposed, the reduction in imports from named countries outweighs the increase in imports from unnamed countries. The substantial reduction in imports from named countries is large enough to offset the import diversion to unnamed countries, suggesting that import diversion in investigations is limited during the investigation period. Therefore, the use of provisional anti-dumping duties in Korea is effective, providing evidence of a chilling effect on aggregate imports. Originality/value - Few studies examine the size of the effects on import trade diversion of the imposition of provisional anti-dumping duties. We contribute to the literature by disentangling separate trade effects for each phase of the anti-dumping investigation process and imposition of provisional duty.

• Land and Housing Review
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• v.14 no.1
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• pp.67-82
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• 2023

Using the Artificial Neural Network model and Binary Logistic Regression model, this study investigates influence factors on the quality of life in terms of housing environment during the COVID-19 in Seoul. The results show that the lower the satisfaction level of housing policy, the lower the quality of life in the employment field and the lower the quality of residential field. On the other hand, permanent workers and self-employed respondents have experienced improvement in residential quality during the pandemic. A limitation of this study is associated with disentangling the causal relationship using the 'black box' characteristics of ANN method.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.214-214
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• 2022

Soluble starch synthases (SSs) elongate α-glucans from ADP-Glc to the glucan nonreducing ends and play a critical role in synthesizing resistant starch in the rice. A total of 10 SSs isoforms were reported in rice, including granules-bound starch synthase I (GBSSI), GBSSII, starch synthase I (SSI), SSIIa (SSII-3), SSIIb (SSII-2), SSIIc (SSII-1), SSIIIa (SSIII-2), SSIIIb (SSIII-1), SSIVa (SSIV-1), and SSIVb (SSIV-2). SSIII proteins are involved in forming the B chain and elongating cluster filling chains in amylopectin metabolism. The functions of SSIIIb (SSIII-1) are less clear as compared to SSs. Here, we sought to shed light on the genetic diversity profiling of the SSIII-1 gene in 374 rice accessions composed of 54 wild-type accessions and 320 bred cultivars (temperate japonica, indica, tropical japonica, aus, aromatic, and admixture). In total, 17 haplotypes were identified in the SSIII-1 coding region of 320 bred cultivars, while 44 haplotypes were detected from 54 wild-type accessions. The genetic diversity indices revealed the most negative Tajima's D value in the temperate-japonica, followed by the wild type, while Tajima's D values in other ecotypes were positive, indicating balancing selection. Nucleotide diversity in the SSIII-1 region was highest in the wild group (0.0047) while lowest in temperate-japonica. Lower nucleotide diversity in the temperate-japonica is evidenced by the negative Tajima's D and suggested purifying selection. The fixation index (F_ST) revealed a very high level of gene flow (low F_ST) between the tropical-japonica and admixture groups (F_ST=-0.21) followed by admixture and wild groups (-0.04), indica and admixture groups (0.02), while low gene flow with higher F_ST estimates between the temperate-japonica and aus groups (0.72), tropical-japonica and aromatic groups (0.71), and temperate-japonica and admixture groups (0.52). Taken together, our study offers insights into haplotype diversity and evolutionary fingerprints of SSIII-1. It provides genomic information to increase the resistant starch content of cooked rice.

• Journal of Technology Innovation
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• v.21 no.1
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• pp.85-108
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• 2013

This paper introduces a new qualitative measurement indicator, Relatively Rank-normalized Impact Factor ($R^2nIF$) that can overcome drawbacks of the existing research performance measures. With the help of this innovative indicator, this study analyzes and compares the quality of research papers across countries and National Science Indicators (NSI) standard academic fields. The development of an improved bibliometric indicator for evaluating the quality of research papers and disentangling the "international" dimension of research performance will be of interest to academics and practitioners alike.

• Journal of Korea Trade
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• v.27 no.3
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• pp.21-42
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• 2023

Purpose - This paper investigates the trade effect of the Korea-China Free Trade Agreement (KCFTA) which coincides with political conflicts between the two countries due to the deployment of the Terminal High Altitude Area Defense (THAAD) in Korea. The two events occurred in the same year and both are likely to affect trade between two countries but in opposite directions. Therefore, it is crucial to distinguish between the trade effects from the KCFTA event and those from the THAAD event to evaluate the true FTA effects. However, this would be difficult when using only annual data. Accordingly, ex post studies to examine the trade effects of KCFTA are lacking in trustworthiness while many ex ante studies that conjecture the positive trade effects neglect the THAAD deployment impact. This paper aims to fill that gap. Design/methodology - Given that the KCFTA and THAAD events occurred in the same year but in different months, we use the monthly data from 2000 to 2019 of Korea's exports to bracket this period. We employ the difference-in-difference (DID) method within a gravity equation specification that uses hi-dimensional fixed effects to address various endogeneity issues and seasonal effects. We identify the net impact of KCFTA ratification from these two near-simultaneous events to quantify the effects of trade liberalization between these two countries. Findings - After isolating the THAAD effects on trade, the analysis creates a positive and statistically significant coefficient estimate of the KCFTA impact. In contrast, failing to isolate the THAAD effect produced a negative and statistically significant coefficient estimate of the KCFTA impact. Our results indicate that KCFTA independently increased Korea's exports to China by 10.2%, but that this increase was fully mitigated by the THAAD event. Further, our results verify that unobserved heterogeneity and multilateral resistance are technically difficult to account for in those estimations as that rely solely upon annual data, as this type of data are inadequate to control for the potential for endogeneity. Originality/value - This paper is one of the first studies to carefully evaluate the net trade effects of the KCFTA on Korea's largest trading partner while isolating the impact of simultaneously occurred political events that may influence trade in opposing directions. Our findings indicate that the lack of prior evidence of positive trade effects of the KCFTA when using annual data may be attributed to a failure to identify the impact of each event separately. This analysis supports using the correct modeling specification to avoid misleading conclusions when evaluating any important international trade policy.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.761-774
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• 2022

Accurate hydrologic prediction is essential to analyze the effects of drought, flood, and climate change on flow rates, water quality, and ecosystems. Disentangling the uncertainty of the hydrological model is one of the important issues in hydrology and water resources research. Hydrologic data assimilation (DA), a technique that updates the status or parameters of a hydrological model to produce the most likely estimates of the initial conditions of the model, is one of the ways to minimize uncertainty in hydrological simulations and improve predictive accuracy. In this study, the two ensemble-based sequential DA techniques, ensemble Kalman filter, and particle filter are comparatively analyzed for the daily discharge simulation at the Yongdam catchment using airGRdatassim. The results showed that the values of Kling-Gupta efficiency (KGE) were improved from 0.799 in the open loop simulation to 0.826 in the ensemble Kalman filter and to 0.933 in the particle filter. In addition, we analyzed the effects of hyper-parameters related to the data assimilation methods such as precipitation and potential evaporation forcing error parameters and selection of perturbed and updated states. For the case of forcing error conditions, the particle filter was superior to the ensemble in terms of the KGE index. The size of the optimal forcing noise was relatively smaller in the particle filter compared to the ensemble Kalman filter. In addition, with more state variables included in the updating step, performance of data assimilation improved, implicating that adequate selection of updating states can be considered as a hyper-parameter. The simulation experiments in this study implied that DA hyper-parameters needed to be carefully optimized to exploit the potential of DA methods.