• Proceedings of the Korean Society for Information Management Conference
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• 1998.08a
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• pp.97-100
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• 1998

계량정보학 연구영역의 하나인 운영연구(Operation Research, OR)중, 미래예측이라는 목적을 가지고 있는 마코프모형(Markov chains)의 통계기법을 활용한 두가지 실험사례를 살펴보고, 최근의 연구경향을 분석함으로써, 도서관 시스템 운영과 설계에 마코프모형을 응용할 수 있는 네가지 방안을 제시하였다. 계량정보학의 한분야로 적용되고 있는 마코프모형에 관한 국내연구가 활발하지 못한 상태이므로, 국내 계량정보학에서의 마코프모형 연구의 필요성과 활성화를 제안하였다.

• Journal of Information Management
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• v.30 no.2
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• pp.31-52
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• 1999

This paper is done by studying two experimental cases which utilize the stochastic theory of Markov Chains, which is used for forecasting the future and by analyzing recent trend of studies. Since the study of Markov Chains is not applied to the Informetrics to a high degree in Korea. It is also proposed that there is a necessity for further study on Markov Chains and its activation.

• Economic Analysis
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• v.17 no.1
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• pp.103-130
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• 2011

This paper intends to provide applied economists which study the effects of research and development with valuable information on econometric model selection. It includes extensive discussion on econometric models which have been applied for the study on the relationship between research and development and productivity. In particular, it compares various stochastic production frontier models which have been developed recently. The discussion decomposes them into models with scaling property and the ones with nonscaling property as well as models with monotonic and nonmonotonic relationships between research and development and productivity. Finally, this paper applies the models to two different panel data sets (firm level data and country level data) and compare estimation results from competing econometric models.

• Economic and Environmental Geology
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• v.47 no.3
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• pp.237-246
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• 2014

In this study, it is estimated how many changes of macroeconomic variables are happened under the proposition of import substitution of mining products 1% using macroeconometric input-output model. For this, used macroeconometric input-output model is composed of 141 behavioral equations representing the macroeconomy structure. In general, macroeconometrics models are constructed mainly on the side of the expenditure then it is not easy to estimate the effects of the shocks occurred from industry level. To mitigate that, this study tries to construct a macroeconometric input-output model. Macroeconometrics model which is useful to estimate the effects of macroeconomic shocks, economic policy and more, in this study, is linked with input-output table through the NDI(national disposable income) derived from compensation of employee. And this paper presents the estimation results of import substitution effects of mining products on Korean economy. As a results, GDP is increased 0.00073%, gross labor employed 0.00029%, current balanace 0.00010% and unemployment rate is mitigated 0.00233%.

• Environmental and Resource Economics Review
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• v.17 no.2
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• pp.255-286
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• 2008

In this paper, it is tried to combine the decomposition method and econometric analysis for the extension of the decomposition method. Since two approaches approach the energy efficiency problem in the different perspectives, it is believed that it is hard to reconcile the results of two approaches. In the results of energy intensity effect analysis with the econometric method, it is found that the increase in the energy price results in the improvement of energy intensity effect. In enconometric analysis of energy efficiency, the coefficient of a time trend measured as a proxy of energy efficiency is significant and has a negative effect on the energy consumption. This finding implies the energy efficiency improves very slowly over time. In addition, the directions of energy efficiency improvement in the decomposition method are consistent with those in the econometric analysis in four industries. This finding indicates that two methods may be in complementary cooperation for the analysis of energy efficiency. Therefore, it is needed the efforts to seek the complementarity between two methods for the enhancement of academic and policy implications.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.1
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• pp.43-51
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• 2012

The OLS(ordinary least squares) method is widely used in hedonic housing models. One of the assumptions of the OLS is an independent and uniform distribution of the disturbance term. This assumption can be violated when the spatial autocorrelation exists, which in turn leads to undesirable estimate results. An alterative to this, spatial econometric models have been introduced in housing price studies. This paper describes the comparisons between OLS and spatial econometric models using housing transaction prices of Busan, Korea. Owing to the approaches reflecting spatial autocorrelation, the spatial econometric models showed some superiority to the traditional OLS in terms of log likelihood and sigma square(${\sigma}^2$). Among the spatial models, the SAR(Spatial Autoregressive Models) seemed more appropriate than the SAC(General Spatial Models) and the SEM(Spatial Errors Models) for Busan housing markets. We can make sure the spatial effects on housing prices, and the reconstruction plans have strong impacts on the transaction prices. Selecting a suitable spatial model will play an important role in the housing policy of the government.

• Environmental and Resource Economics Review
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• v.7 no.2
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• pp.137-169
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• 1998

본 연구는 탄소세 부과가 우리 나라의 에너지 및 국민 경제에 미치는 충격의 영향분석을 목적으로 하고 있다. 이를 위해 에너지-경제 연계 계량경제모형을 수립하였는데 본 모형은 기존의 거시경제모형을 수정한 후 에너지 모형과의 연계를 통해 에너지 부문의 충격이 경제부문에 미치는 효과를 정량적으로 파악이 가능하도록 하였다. 본 연구에서는 탄소배출량에 대한 규제가 탄소세 부과를 도입하도록 유도하고 에너지가격의 상승과 에너지수요를 감소시킴으로써 경제부문의 생산을 위축시키는 흐름도를 가정하고 있다. 분석의 과정에서 탄소세 부과가 에너지 및 국민경제 부문에 미치는 효과의 측정은 에너지가격 및 수요변화, 국내총생산액의 변화 등을 통하여 수행되었다. 분석 결과를 요약하면 탄소 배출량의 안정화를 도모하기 위해서는 탄소세가 상당히 높게 부과되어야 하며 전력가격 및 에너지가격의 상승에 미치는 효과와 국내총생산액 등 주요 경제 변수에 미치는 충격이 매우 심각한 것으로 나타났다. 본 연구에서 개발된 계량경제모형을 통하여 여러 가지 정책수단에 대한 시뮬레이션이 가능하게 됨으로써 정책의 효과분석 및 동 분야의 향후 연구에도 많은 도움이 될 것으로 판단된다.

• Proceedings of the Korean Information Science Society Conference
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• 2000.04b
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• pp.283-285
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• 2000

본 논문에서는 계량경제학적인 유가예측 모형과 전문가시스템을 결합한 중장기 유가예측 시스템을 설계 및 구현하였다. 즉, 계량 데이터를 기초로 유가예측 모형을 구성하고, 산유국 동향과 OPEC 정책 등과 같은 비계량적인 요인에 대한 실무자의 경험적인 지식은 지식베이스로 구축함으로써, 유가예측과 관련된 다양한 요인들을 폭넓게 고려할 수 있는 통합된 시스템을 개발하였다. 유가예측 모형으로는 수급과 대표 유종의 유가예측을 위한 동태적 선형연립 모형과 유종간 가격차를 예측하기 위한 Fully Modified 공적분 회귀분석 모형을 구성하였으며, 유가예측 모형에서 반영하기 어려운 산유국 동향, OPEC 정책, 선물시장 동향 등은 실무자의 경험적인 지식을 바탕으로 시스템 예측변수로 설정하여 유가예측에 반영되도록 지식베이스를 구축하였다. 또한, 본 시스템은 유가예측 이외에 석유 수급을 전망하고, 유가 및 수급과 관련된 관련 다양한 정보를 제공하고 관리하는 기능을 제공한다.

• The Journal of the Korea Contents Association
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• v.12 no.2
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• pp.461-471
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• 2012

The purpose of this paper is to visualize the housing market dynamics with ESDA (Exploratory Spatial Data Analysis) using MATLAB toolbox, in terms of the modeling housing market dynamics in the Busan Metropolitan City. The data are used the real housing price transaction records in Busan from the first quarter of 2006 to the second quarter of 2009. Hedonic house price model, which is not reflecting spatial autocorrelation, has been a powerful tool in understanding housing market dynamics in urban housing economics. This study considers spatial autocorrelation in order to improve the traditional hedonic model which is based on OLS(Ordinary Least Squares) method. The study is, also, investigated the comparison in terms of $R^2$, Sigma Square(${\sigma}^2$), Likelihood(LR) among spatial econometrics models such as SAR(Spatial Autoregressive Models), SEM(Spatial Errors Models), and SAC(General Spatial Models). The major finding of the study is that the SAR, SEM, SAC are far better than the traditional OLS model, considering the various indicators. In addition, the SEM and the SAC are superior to the SAR.

• Journal of Korean Society of Transportation
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• v.34 no.1
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• pp.95-106
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• 2016

Air transportation demand is consistently increasing in Korea due to economic growth and low cost carriers. For this reason, airport expansion plans are being discussed in Korea. Therefore, it is essential to forecast reliable air transportation demand with adequate methods. However, most of the air transportation demand models in Korea has been developed by simple regression analysis with several dummy variables. Simple regression analysis without considering stationarity of time-series data can bring spurious outputs when a direct causal relationship between explanatory variables and dependent variable does not exist. In this paper, econometric model were developed for air transportation demand based on stationarity in time-series data. Unit root test and co-integration test are used for testing hypothesis of stationarity.