• Environmental and Resource Economics Review
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• v.14 no.3
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• pp.569-593
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• 2005

This study tests for the law of one price and Grander Causality between the EU ETS and Nord Pool $CO_2$ allowance prices. The Johansen cointegration test shows that there exists a long run equilibrium between EU ETS and Nord Pool prices and support the law of one price. The Granger casuality test suggests that the EU ETS leads Nord Pool for all vintages traded. The test results imply that the EU ETS can be regarded as the representative carbon market in the EU where many exchanges just started competing for the newly rising market for carbon.

• Journal of Korea Port Economic Association
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• v.35 no.3
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• pp.61-72
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• 2019

In order to enhance the competitiveness of the container shipping industry and promote its development, based on the empirical analyses using multivariate time series models, this study aims to suggest a few strategies related to the dynamics of the container shipping market. It uses the vector autoregressive (VAR) and vector error correction (VEC) models as analytical methodologies. Additionally, it uses the annual trade volumes, fleets, and freight rates as the dataset. According to the empirical results, we can infer that the most exogenous variable, the trade volume, exerted the highest influence on the total dynamics of the container shipping market. Based on these empirical results, this study suggests some implications for ship investment, freight rate forecasting, and the strategies of shipping firms. Concerning ship investment, since the exogenous trade volume variable contributes most to the uncertainty of freight rates, corporate finance can be considered more appropriate for container ship investment than project finance. Concerning the freight rate forecasting, the VAR and VEC models use the past information and the cointegrating regression model assumes future information, and hence the former models are found better than the latter model. Finally, concerning the strategies of shipping firms, this study recommends the use of cycle-linked repayment scheme and services contract.

• Environmental and Resource Economics Review
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• v.14 no.3
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• pp.699-728
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• 2005

This article is basically an extension of Barten(1993), Brown et al. (1995), Holt and Bishop's(2002) price formation system. A new dynamic price formation system is attempted considering full rationality of the consumers' side. The underlying idea of the new dynamic price formation system is that consumers are rational and farsighted and thus consider past and future consumptions in addition to current consumption to accept the prices traders called. In an empirical application, the U.S. commercial fish demand data are particularly interesting to this analysis in which the species are over fished, including many of the most valuable species. Especially, the grouper-snapper complex are under management jurisdiction of the National Marine Fisheries Council. In the empirical section, it shows how to adapt the model to estimate the marginal values to consumers of commercial fisheries. Since it is conceived of regulations as inducing movements along the marginal value curves, it is of growing importance to regional and national policy makers who are confronted with competing claims on diminishing fish stocks by commercial fisheries interests. It performs well and shows the plausible signs and magnitudes of price flexibilities and interaction among species. It further contributes to the general methodology of applied economics.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.01a
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• pp.117-120
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• 2020

본 논문은 인공지능 메이커 교육과 관련한 요소를 논문 네트워크 키워드 분석과 다양한 빅데이터를 종합하여 핵심용어를 선정 후 인공지능 메이커 교육을 시스템 다이내믹스의 Vensim프로그램으로 인과지도(Casual Loop Diagramming)를 구조분석(모델의 구조)하여 예측 결과를 토대로 향후 미래 상황 추출 및 정책 결정 연구에 영향을 기여한다. 연구 결과 인공지능 교육 정책은 추후 인공지능 교육과 메이커 교육을 융합한 교육 관련 산업이 증대할 것으로 예측되며 교육 경쟁력 향상과 창의적 인재 양성, OTT를 이용한 인공지능 교육 콘텐츠 향상으로 학습에 활용성이 증대하게 된다. 또한 인공지능 교육 정책은 프로그래밍 교육으로 연결되어 성장기 학습자들의 사고력과 정서 발달에 도움 되며 다양한 교재 및 기기 등장으로 인한 학습에 다양성 역시 증가할 것으로 예측된다. 학교 차원에서는 교수·연구 지원 활동이 증가하여 수업 전문성을 가진 교사가 늘어나 학교 교육의 질은 확대되고 학부모는 인공지능 교육 정책에 긍정적으로 된다. 시스템 다이내믹스는 구조가 형태를 결정짓는다는 세계관에 기초하여 피드백 루프와 동태적 형태 유형을 파악하며 다양한 가능성이 존재하게 된다. 이는 추후 다양한 연구를 통해 인공지능 교육 정책 인과지도의 확대로 연결될 수 있음을 암시하며 본 논문을 통해 인공지능 교육 연구 확산에 시발점이 되었으면 한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.9
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• pp.387-396
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• 2020

The purpose of this study is to identify the variables of metropolitan and provincial offices of education that affect the academic achievement of unit schools, and to predict how academic achievements dynamically change with the support of offices of education. The results of academic achievement of 606 general high schools in 16 metropolitan and provincial offices of education(rates of attaining more than normal education in Korean, English, and mathematics subjects) were analyzed using a multi-level model and system dynamics. As a result of the analysis, it was confirmed that the provincial and provincial offices of education's efforts to increase the efficiency of local education finance, the efforts to reduce teacher administration, and the facilitation of faculty training were the variables of the provincial and provincial offices of education. In addition, through policy experiments, efforts to revitalize teacher training were the most influential factors in academic achievement of unit schools, followed by efforts to streamline local education finances and to reduce the administrative work of teachers. In order to improve the academic achievement of unit schools, the functions of the metropolitan and provincial offices of education should be strengthened based on the education accountability, and policies need to be established in the mid- to long-term perspective.

• The Korean Journal of Applied Statistics
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• v.16 no.1
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• pp.87-100
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• 2003

Most of statistical data are generated by a set of dynamic, stochastic, and simultaneous relations. An important question is how to specify statistical models so that they are consistent with the dynamic feature of those data. A general hypothesis is that the lagged effect of a change in an explanatory variable is not felt all at once at a single point in time, but The impact is distributed over a number of future points in time. In other words, current control variables are determined by a function that can be reduced to a distributed lag function of past observations. It is possible to explain the relationship between variables in different points of time and to estimate the long-run impacts of a change in a variable on another if time lag series of explanatory variables are incorporated in the model specification. In this study, distributed lag structure is applied to the domestic stock market model to capture the dynamic response of the market by exogenous shocks. The Domestic market is found more responsive to the changes in foreign market factors both in the short and the long run.

• International Area Studies Review
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• v.14 no.3
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• pp.35-60
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• 2010

In this paper, we develop a dynamic structural model based on a dynamic supergame and measure market power for the Dallas-Forth Worth fluid milk market in the U.S. In particular, we compare the conduct parameter estimates from a static model with that from the dynamic model and illustrate bias in the market-power measure in a static model. And we also analyze the cyclical behavior of firm conduct. We find that the conduct parameter in a static model underestimates true market power if firms' behaviors are posited by a dynamic oligopoly game. We also verify that firm conduct in the Dallas-Forth Worth fluid milk market is countercyclical against demand shocks and expected future cost shocks. Our results indicate that the firms' conduct in the Dallas-Forth Worth fluid milk market is consistent with what dynamic oligopoly models predict. This implies that the firms consider not only the contemporary reactions of the other firms' but also future market competition. Therefore, the measurement of market power requires the specification of fully dynamic pricing relationship.

• Journal of Industrial Convergence
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• v.16 no.2
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• pp.1-14
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• 2018

The interconnectedness of all things is continuously expanding. For example, bluetooth low energy (BLE) beacons are wireless radio transmitters that can send an identifier to nearby receivers and trigger a number of applications, from proximity marketing to indoor location-based service. iBeacon technology which is one of the newest technologies in the smart tourism field, is reckoned as being very useful for travelers in enhancing the experience with visiting places. However, there is consequently not much existing research yet about the connection between iBeacon technology and tourism destination. Considering that, this study analyzes the adoption of iBeacon in tourism destination, this study examine the interrelationships and feedback structures of key factors in iBeacon adoption. To serve the purpose, this study used system dynamics approach to develop a model of iBeacon adoption in tourism destination. The analysis results showed that the concept of 'Social Influences' is one of the significant predictors for individual's intention behavior to accept iBeacon, and word of mouth (WOM), subjective norm, privacy concern, and perceived usefulness are key factors influencing the iBeacon adoption.

• The Korean Journal of Financial Management
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• v.19 no.2
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• pp.211-231
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• 2002

본 연구의 목적은 VECM(Vector Error Correction Model)과 인공지능모형(Artificial Neural Networks)을 이용하여 우리나라 증권시장과 거시경제 변수들과의 장기적 관계에 대한 설명력을 비교해보고자 함에 있다. VECM이 APT(Arbitrage Pricing Theory)에 기초를 둔 선형동학모형이라고 한다면, 인공지능모형은 비모수적 비선형모형이라는 점에서, 두 방법론의 분석결과를 직접 비판하는 것은 의미있는 연구라고 할 수 있다. 인공지능모형을 주로 활용하는 선행연구들에 의하면, 증권시장은 시장의 특이패턴들로 인해 계량경제학적 접근인 선형 모형보다는 인공지능모형을 통해 증권시장의 움직임을 설명하고 예측하는 것이 더 바람직할 수도 있다는 것이다. 따라서, 본 연구에서는 VECM분석에서 자료의 안정성을 검증하고, 공적분 백터를 발견한 이후, 장기적 균형관계의 실증적 분석을 하였다. 그리고, 인공지능모형에서는 delta rule과 Sigmoid 함수를 이용한 GRNN(General Regression Neural Net)과 Back-Propagation등의 방법들을 활용하였다. 이러한 분석결과, Back-Propagation 모형이 다른 모든 모형들보다도 더 우수한 설명력을 보여주고 있었다. 이러한 결과들은 인공지능모형이 동태적인 선형 모형보다도 더 우수한 설명력을 제공할 수 있는 가능성을 보여주고 있었다.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1512-1516
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• 2007

자신의 현재와 과거의 시계열데이터만을 가지고 시계열 모형을 구축하는 단변량 ARIMA모형 분석법과는 달리, 관심의 대상이 되는 출력시계열과 이와 관련있는 입력시계열의 동태적 특성을 나타내는 전이함수모형(Transfer function model)을 사용하여 소양강댐, 충주댐, 화천댐에 대한 월별 수문자료를 이용하여 유입량을 예측해 보고자 한다. 본 연구의 주요 목적은 다변량 추계학적 시스템의 해석을 위한 모형의 추정과 등정을 위한 과정을 개발하는데 있다. 일반적 추계학적 시스템 모형이 표현되며 그것으로부터 수문학적 시스템의 모형을 매우 적절하게 유도하기 위한 다중 입력-단일 출력 TF, TFN모형을 유도하는데 있다. 이 모형은 수문학적 시스템을 위한 경우에 있어 상관된 입력을 설명할 수 있도록 개발된다. 일반적으로 모형을 만드는 전략이 유도되며 실제유역시스템에 적용하여 검토된다. 한강수계 주요 다목적댐인 소양강댐, 충주댐, 화천댐의 수문자료를 가지고 추계학적 모형(TF, TFN)에 의한 결과와 실제유입량을 비교하여 검토하고자 한다.