• 한국항만경제학회지
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• 제26권1호
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• pp.222-233
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• 2010

해상운임의 변동은 해운업계에만 영향을 미치는데 그치지 않고 전후방 연쇄효과를 통해 조선업계를 비롯하여 경제 전반에 영향을 미친다. 따라서 해상운임의 움직임을 정확히 예측하는 것은 해운업계 뿐만 아니라 우리나라 경제에도 중요한 의미를 갖게 된다. 그러나 해상운임은 주가나 환율과 같이 다양한 요인에 의해 결정될 뿐만 아니라 최근 들어 운임의 변동성이 크게 커지는 추세이어서 예측에 상당한 어려움이 있다. 본고는 2010년의 BDI를 예측하기 위하여 가장 단순한 모형인 단변량모형인 ARIMA 모형, 개입ARIMA모형, HP 모형을 이용한다. 개입ARIMA 모형은 글로벌 금융위기와 중국효과가 미친 효과를 분석하기 위한 것이다. ARIMA모형은 2010년 말에 4,230-4.690에 도달할 것으로, 개입ARIMA모형은 낙관적인 경우 4,460-4,900선에, 비관적일 경우 2,820-2,940선이 될 것으로 예상하여 모형별로 상당한 차이를 드러내고 있다. 그런데 HP 모형에 의한 예측치는 기준 역할을 하므로 HP모형에 의한 2010년 말 예측치 3,500 포인트를 감안하면 2010년 12월에 2,820-4,230의 범주에 도달할 것으로 예측된다. 2010년 12월 2,800 포인트는 해운업계에 어두운 그림자를 드리우는 예측치이다. 그러나 낙관적인 2010년 12월 4,000포인트는 2008년 BDI가 10,000 포인트를 넘어선 때를 기억하면 그리 높게 생각되지 않을 수 있으나 4,000 포인트 이상의 BDI는 해운관련업계에게 어느 정도의 안도감을 주고 재도약을 할 수 있는 기반을 제공할 수 있는 수준으로 판단된다.

• ETRI Journal
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• 제10권1호
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• pp.39-52
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• 1988

통신서비스의 확산을 예측하기 위한 확산모형을 제시하였다. Bass모형을 기본으로 하여 가격과 소득을 고려한 확장된 확산모형을 제시하였고, 이 모형을 이용하여 우리나라 전화의 확산에 대한 실증분석을 하였다.

• Journal of Korea Trade
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• 제25권3호
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• pp.116-133
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• 2021

Purpose - Intra-industry trade of agricultural products can eliminate the disadvantage of Korea's traditional agriculture and improve its lack of comparative advantage. The main purpose of this paper is to measure the level and index of intra-industry trade of Korean agricultural products and to explore the spatial dependence and spillover effect associated with this type of trade. The main factors influencing intra-agricultural trade are analyzed from two perspectives: the population and the classification of agricultural products. Design/methodology - First, the level of intra-industry trade of Korean agricultural products is measured. Second, to obtain a more accurate estimate of the influence of various factors, and based on two types of weight matrices, a spatial econometric model is constructed from two aspects: population and classification of agricultural products. The status and the factors influencing intra-industry trade are also studied. Findings - It is concluded that there is a positive spatial correlation between Korea's intra-industry trade in agricultural products and that of its trading partners. The spatial spillover effect of this type of trade is verified by using the spatial autoregressive model (SAR). Labor-intensive agricultural products are found to have a positive spillover effect on intra-industry trade, while land-intensive products do not have a significant effect. Originality/value - In this paper, the two types of agricultural products are meticulously distinguished, and the spatial effect of the intra-industry trade of agricultural products as well as the influence of various factors are analyzed. In addition, the accuracy of the estimation of the coefficients of the factors by using the spatial econometric model is higher than that of the ordinary panel data model.

• 한국인공지능학회지
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• 제7권2호
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• pp.9-12
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• 2019

With the Chinese government's attention to the artificial intelligence industry, the Chinese government has invested a lot in it recently. Of course, the importance of artificial intelligence industry for China's economic development is increasingly significant. The advent of artificial intelligence boom has also triggered a large number of scientists to analyze the impact of artificial intelligence on economic growth. Therefore, this paper use 31 China's cross-province panel data to study the effect of artificial intelligence on economic growth. Via empirical analyses under a series of econometric methods such as the province and year fixed effect model, the empirical result shows that artificial intelligence has a positive and significant effect on economic growth. Namely, the artificial intelligence is a new engine for economic growth. Meanwhile, the empirical results also indicate that the investment and consumption has a significant and positive effect on economic growth. Oppositely, the inflation and government purchase have a significant negative effect on economic growth. These findings in this paper also provide some important evidences for policy-makers to perform precise behaviors so as to promote the economic growth. Moreover, these finding enriches existing literature on artificial intelligence and economic growth.

• 유통과학연구
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• 제17권1호
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• pp.21-31
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• 2019

Purpose - As the market economy deepens, the issue of social equity caused by income distribution becomes more and more significant. Therefore, this paper attempts to exploit the determinants of income distribution in terms of macroeconomics. Research design, data, and methodology - The data set from 1990 to 2017 will be used to conduct an empirical analysis under a menu of econometric approaches such as vector autoregressive model and impulse response function. The income distribution and other macroeconomic variables such as foreign direct investment and employment will be used to conduct an empirical analysis to explore the determinants of income distribution in terms of macroeconomics. Results - The findings indicate that the income distribution is related with macroeconomics. More specifically, the export, import, GDP and foreign direct investment play a role in deteriorating the income distribution. Conversely, the industrialization, inflation and employment can improve the income distribution. Unfortunately, the inflation and employment do not get through under 5% significant test. Conclusions - Due to that a good income distribution can be beneficial for both a country and an individual, this paper provides a new scope for China's government to improve its income distribution in terms of macroeconomics.

• The Journal of Asian Finance, Economics and Business
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• 제8권3호
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• pp.731-740
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• 2021

This research aims to investigate the determinants of real effective exchange rate in emerging ASEAN countries, including Indonesia, Malaysia, Philippines, Thailand, and Vietnam. The research was conducted by using quarterly time series data set from 1980Q1 to 2020Q3. Cointegration and the error correction model (ECM) methods were applied to test the long run and short run relationship of the real effective exchange rate and its determinants. The results indicate that the ratio of foreign direct investment to GDP and the government spending have significantly positive impact on real effective exchange rate in the Emerging ASEAN countries. The trade opening had influencing real effective exchange rate in most the Emerging ASEAN countries, except Vietnam. In addition, the international reserve (INR) had significant long-run impacts variables on real effective exchange rate in Malaysia, Thailand and Vietnam. In the short run equilibrium, the error collection term suggest that Indonesia and Malaysia are the fastest speed adjustment to equilibrium. In addition, the term of trade influence the real effective exchange rate in Indonesia, Malaysia, and the Philippines but it is not in Thailand and Vietnam. However, FDI is a major factor of the real effective exchange rate in Vietnam, but not for other countries.

• 대한교통학회지
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• 제34권1호
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• pp.95-106
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• 2016

우리나라 항공 여객수요는 2014년 기준 국제선 5,700만명, 국내선 2,400만명에 도달하였으며, 지속적인 증가 추세를 보일 것으로 예상되고 있다. 이에 따른 국내 공항시설들의 확충 계획이 활발히 진행되고 있으며, 이를 위해 선행적으로 항공수요 예측을 위한 모형 개발이 필요하다. 우리나라에서는 국내총생산을 설명변수로 한 계량경제모형을 주로 항공수요 모형으로 이용하고 있으며, 시계열 자료의 안정성을 고려하지 않을 때 발생하는 허구적 회귀 현상에 대한 많은 논의가 이루어지지 않은 상태이다. 본 연구에서는 시계열 자료의 안정성을 고려한 항공수요 계량경제모형을 개발하였다. 시계열 자료의 특성을 검정하기 위한 단위근 검정과 변수들 간의 장기균형관계를 분석하기 위한 공적분 검정에 대한 이론적 고찰을 수행하였다. 마지막으로, 시계열 자료의 안정성을 고려한 항공수요 계량경제모형 개발 프로세스를 정립하였다. 정립된 프로세스의 적용 가능성을 검증하기 위해 제주공항 국내선 수요를 대상으로 항공수요 모형을 산정하였다. 수요 모형의 설명변수는 국내총생산과 항공요금지수를 이용하였으며, 기존 항공수요 계량경제모형에서 발생하는 문제점을 해소한 것으로 나타났다.

• International Journal of Human Ecology
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• 제4권2호
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• pp.77-87
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• 2003

This paper tried to construct statistical and econometric models on the basis of economic theory in order to discuss the issue of statistical efficiency and unbiasedness including the sample selection bias correcting problem. Comparative analytical tool were one stage Tobit of Maximum Likelihood estimation and Heckman's two-step Tobit of Ordinary Least Squares. The results showed that the adequacy of model for the analysis on demand and choice, we believe that there is no big difference in explanatory variables between the first selection model and the second linear probability model. Since the Lambda, the self- selectivity correction factor, in the Type II Tobit is not statistically significant, there is no self-selectivity in the Type II Tobit model, indicating that Type I Tobit model would give us better explanation in the demand for and choice which is less complicated statistical method rather than type II model.

• 한국콘텐츠학회논문지
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• 제18권11호
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• pp.430-446
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• 2018

본 논문에서는 전파자원 활용과 관련한 정책 및 투자 방안 수립에 대한 경제적 근거 및 기초자료로서의 파급 효과 분석 방법론에 관한 비교연구를 수행하였다. 정책 및 투자 방안 간 객관적 비교 및 선정을 위해 수치적 결과를 제공하는 방법론을 분석 대상으로 하였고 수학적인 모형에 기반을 둔 정량적 방법론인 계량경제모형, 산업연관분석, 연산일반균형, 시스템 다이내믹스 방법에 대해 분석 비용 등 다양한 관점에서 효용과 한계를 비교 분석하였다. 또한, 전파자원 활용의 효과 분석 측면에서 이들 방법론을 비교하고, 분석된 방법론의 장점들을 활용하고 한계를 상쇄시키기 위해 단일 방법론들을 결합한 혼합형 모형에 대한 최근 연구결과를 논의하였다. 연구결과는 전파정책 및 투자 방안 실행의 효율성 검증을 위한 다양한 분석방법 중 분석의 목적과 우선순위에 부합하는 방법을 선정하는 데 참고 지표로 활용할 수 있다.

• 한국정보시스템학회지:정보시스템연구
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• 제30권2호
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• pp.29-56
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• 2021

Purpose Cyber deviance of adolescents has become a serious social problem. With a widespread use of smartphones, incidents of cyber deviance have increased in Korea and both quantitative and qualitative damages such as suicide and depression are increasing. Research has been conducted to understand diverse factors that explain adolescents' delinquency in cyber space. However, most previous studies have focused on a single theory or perspective. Therefore, this study aims to comprehensively analyze motivations of juvenile cyber deviance and to develop a predictive model for delinquent adolescents by integrating four different theories on cyber deviance. Design/methodology/approach By using data from Korean Children & Youth Panel Survey 2010, this study extracts 27 potential factors for cyber deivance based on four background theories including general strain, social learning, social bonding, and routine activity theories. Then this study employs econometric analysis to empirically assess the impact of potential factors and utilizes a machine learning approach to predict the likelihood of cyber deviance by adolescents. Findings This study found that general strain factors as well as social learning factors have positive effects on cyber deviance. Routine activity-related factors such as real-life delinquent behaviors and online activities also positively influence the likelihood of cyber diviance. On the other hand, social bonding factors such as community commitment and attachment to community lessen the likelihood of cyber deviance while social factors related to school activities are found to have positive impacts on cyber deviance. This study also found a predictive model using a deep learning algorithm indicates the highest prediction performance. This study contributes to the prevention of cyber deviance of teenagers in practice by understanding motivations for adolescents' delinquency and predicting potential cyber deviants.