• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.477-481
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• 2007

The purpose of this study is to provide the ideal forecasting model of cadastral survey work load through the Economeatric Analysis of Time Series, Granger Causality and VAR Model Analysis, it suggested the forecasting reference materials for the total amount of cadastral survey general work load. The main result is that the derive of the environment variables which affect cadastral survey general work load and the outcome of VAR(vector auto regression) analysis materials(impulse response function and forecast error variance decomposition analysis materials), which explain the change of general work load depending on altering the environment variables. And also, For confirming the stability of time series data, we took a unit root test, ADF(Augmented Dickey-Fuller) analysis and the time series model analysis derives the best cadastral forecasting model regarding on general cadastral survey work load. And also, it showed up the various standards that are applied the statistical method of econometric analysis so it enhanced the prior aggregate system of cadastral survey work load forecasting.

• New & Renewable Energy
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• v.16 no.3
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• pp.13-26
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• 2020

This study analyzed whether the diffusion of new and renewable energy contributed to mitigating emissions of various air pollutants, including particulate matter, using panel econometric models. The theoretical foundation of such econometric models is based on the Environmental Kuznets Curve (EKC) hypothesis, which assumes an inverted U-shaped relation between national income and environmental pollution, as originally proposed by Grossman and Krueger. We examined whether there are inverted U-, U-shaped, or N-shaped relations between national income and air pollution. We demonstrate that increases in new and renewable energy significantly mitigated emissions of CO, NO_X, and PM2.5. Additionally, we included NO_X, SO_X, PM10, and VOCs as secondary emission sources of PM2.5 and found that emission of PM10 resulted in the highest PM2.5 emissions, followed by NO_X and SO_X emissions. The impact of new and renewable energy on air pollution varied across regions. Increase of new and renewable energy in the Honam region significantly mitigated CO, NO_X, and TSP emissions, while that in the Youngnam and metropolitan areas did not significantly mitigate air pollution overall. There was a U-shaped relationship between air pollution and national income for CO, NO_X, PM2.5, and SO_X, while an inverted N-shape was observed for PM10.

• Journal of the Economic Geographical Society of Korea
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• v.12 no.4
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• pp.494-506
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• 2009

This paper tests whether or not manufacturing specialization, employment growth, establishment size, employment size, industrial mix in manufacturing, regional difference between the Capital region and the others and so on are empirically related to manufacturing employment volatility levels across 203 municipalities called shi-gun-gu during the period 1990~2006. Using the spatial econometric analysis of cross sectional data, the municipalities tending to be more volatile are more specialized; they have higher-than-average employment growth rates, smaller establishment and employment sizes, regardless of any industrial mix in manufacturing; and they tend to be located in the Capital region. Unlike existing foreign literature based upon the spatial econometric analysis of cross sectional data, this paper finds that volatility of growth in a municipality is negatively rather than positively influenced by volatility of growth in its neighboring municipalities.

• The Journal of Information Systems
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• v.30 no.2
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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.

• The Journal of Asian Finance, Economics and Business
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• v.1 no.2
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• pp.5-13
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• 2014

The purpose of this paper is to carry out an empirical analysis of the link that exists between microfinance and poverty alleviation. The analysis is driven by literature searches on empirical works done by different researchers in different contexts. Qualitative research methodology was adopted, following a desktop approach. An empirical literature review took a centre stage in this investigation. An analysis of empirical works shows that microfinance enhances poverty alleviation despite the challenges such as the Indian Andhra Pradesh crisis. The paper is limited to a review of empirical sources of literature. A field survey, supported by an econometric analysis would have helped to generate robust results. This paper attempts to bring together the empirical works that were done in different contexts to shed light on the important relationship between microfinance and poverty. Many research works on microfinance depend upon personal anecdotes, thus this present paper attempts to compile the scattered empirical findings on microfinance and poverty alleviation.

• Asian Journal of Innovation and Policy
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• v.4 no.2
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• pp.242-262
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• 2015

The relationship between geographical proximity and academics' formal and informal knowledge-transfer activities in the network is analyzed with a mixed research method. With social network analysis as a basis, we have explored the networks between academics and firms in the 16 regions of South Korea. The result shows Seoul and Gyunggi are identified as central nodes, meaning that the academics in other regions tend to collaborate with firms in these regions. An econometric analysis is performed to confirm the localization of knowledge-transfer activities. The intensity of formal channels measured by the number of academic papers is negatively, but significantly associated with the geographical proximity. However, we have not found any significant relationship between the formality of the channels and geographical proximity. Possibly, the regional innovation systems in South Korea are neither big enough nor strong enough to show a localization effect.

• Journal of Korean Institute of Industrial Engineers
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• v.4 no.2
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• pp.91-96
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• 1978

A modeling framework and its computational methodology for an industrial sector of the economy are investigated. The suggested industrial sector model is characterized by a programming (process analysis) representation of a production sector and an econometric estimation of the price sensitive (own and cross-prices) demands. By introducing the price sensitive demands into the process analysis representation of the production sector, it becomes possible to analyze and plan the pricing policy, the optimal production schedules and capacity expansion plans within a single framework. The computational scheme suggested in the report is based on the iterative approach each of which solves a separable convex programming problem.

• Communications for Statistical Applications and Methods
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• v.23 no.3
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• pp.231-239
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• 2016

A graphical diagnostic method based on multiple case deletions in a regression context is introduced by using the sampling distribution of the difference between two least squares estimators with and without multiple cases. Principal components analysis plays a key role in deriving this diagnostic method. Multiple case deletions of test statistic are also considered when a new observation is fitted to a given regression model. The result is useful for detecting influential observations in econometric data analysis, for example in checking whether the consumption pattern at a later time is the same as the one found before or not, as well as for investigating the influence of cases in the usual regression model. An illustrative example is given.

• Journal of Preventive Medicine and Public Health
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• v.28 no.2 s.50
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• pp.450-461
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• 1995

This paper tested by using Micro TSP, an empirical econometric analysis to approve officially a hypothesis of price elasticity of the demand for medical care services in Korean national medical insurance and the economic effect of health care delivery system with time-series datas of Medical Insurance Statistical Yearbook$(1981\sim1993)$. The results suggest that the Korean medical insurance system shows moral hazard due to the change of coinsurance and the economic effect according to intervention of the health care delivery system, but it is different by insurers regardless of the same structure of the medical insurance scheme.

• Journal of Korea Technology Innovation Society
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• v.4 no.2
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• pp.127-142
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• 2001

This paper presents an econometric model for measuring basic research capacity index(BRCI) of each OECD countries and analyses the gap in terms of time lag measured and forecasted in connection with factor analysis and BRCI progress function. Based on the analysis, gross domestic expenditure on R&D(GERD), total R&D personnel higher education expenditure on R&D(HERD) and number of science and technical papers based on SCI are more effective than other factors to BRCI. Also, BRCI progress function shows that 29 years is needed for Korea to catch up the level of German's BRCI of year 1998. But, it's impossible for Korea to catch up US and Japan. Therefore, with restricted scientific resources, Korea's own strategy for strengthening basic research capacity is going to be more important in 21st century.