• Journal of Distribution Science
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• v.14 no.3
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• pp.63-71
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• 2016

Purpose - A variety of indicators are used for the diagnosis of economic situation. However, most indicators explain the past economic situation because of the time difference between the measurement and announcement. This study aims to argue for the resurrection of an idea: electricity demand can be used as an indicator of economic activity. In addition, this study made an endeavor to develop a new Real Business Index(RBI) which could quickly represent the real economic condition based on the sales statistics of industrial and public electricity. Research design, data, and methodology - In this study monthly sales of industrial and public electricity from 2000 to 2015 was investigated to analyze the relationship between the economic condition and the amount of electricity consumption and to develop a new Real Business Index. To formulate the Index, this study followed next three steps. First, we decided the explanatory variables, period, and collected data. Second, after calculating the monthly changes for each variable, standardization and estimating the weighted value were conducted. Third, the computation of RBI finalized the development of empirical model. The principal component analysis was used to evaluate the weighted contribution ratio among 3 sectors and 17 data. Hodrick-Prescott filter analysis was used to verify the robustness of out model. Results - The empirical results are as follows. First, compatibility of the predictability between the new RBI and the existing monthly cycle of coincident composite index was extremely high. Second, two indexes had a high correlation of 0.7156. In addition, Hodrick-Prescott filter analysis demonstrated that two indexed also had accompany relationship. Third, when the changes of two indexes were compared, they were found that the times when the highest and the lowest point happened were similar, which suggested that it is possible to use the new RBI index as a complementing indicator in a sense that the RBI can explain the economic condition almost in real time. Conclusion - A new economic index which can explain the economic condition needs to be developed well and rapidly in a sense that it is useful to determine accurately the current economic condition to establish economic policy and corporate strategy. The salse of electricity has a close relationship with economic conditions because electricity is utilized as a main resource of industrial production. Furthermore, the result of the sales of electricity can be gathered almost in real time. This study applied the econometrics model to the statistics of the sales of industrial and public electricity. In conclusion, the new RBI index was highly related with the existing monthly economic indexes. In addition, the comparison between the RBI index and other indexes demonstrated that the direction of the economic change and the times when the highest and lowest points had happened were almost the same. Therefore, this RBI index can become the supplementary indicator of the official indicators published by Korean Bank or the statistics Korea.

• Journal of Korean Society of Transportation
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• v.17 no.1
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• pp.41-52
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• 1999

Recently, much literature has surveyed the economic effects of transportation investment, focusing on the relationship between transportation infrastructure investment and economic development. Although the conventional views assume that transportation investment stimulates economic growth, the results of recent studies are not conclusive and in some cases reject the conventional views. The contradictory results are linked with double counting Problem and Keynesian/Neo-classical economics theory. This article investigates the economic effects of road transportation with regard to freight transport using Stated Preference technique. This study examines, in particular, the value of time saving for freight which has been rarely studied in this area. In the first part, the value of time saving, excluding the value for driver and operating cost, is theoretically investigated through the model of continuous review system and periodic review system. At last, the empirical study using the Seated Preference technique shows the value of time saving for freight and the value of reliability, compared with other studies and the value of those in COBA. The result makes us conclude that road investment produces the secondary effects as well as the direct benefit such as time saving for passengers, operating cost saving. and accident cost reduction. The secondary effect includes the contribution to economic development.

• Journal of Technology Innovation
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• v.22 no.3
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• pp.101-133
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• 2014

Climate change and low-carbon consumer movement is demanding proper response around the world while rising oil price increases consumers' needs for green car. As a preliminary study to establish an industrial platform for green car and bring out corporate strategies, this article aims to propose an academic research framework by using various methodologies including conceptual/mathematical modeling, system dynamics, and ABM from different angles. First, an analysis framework for the industrial platform was introduced to analyze green car cases, required elements were proposed, and econometrics was applied to build a basic model related to green platform (two-sided market). Also, to analyze from a dynamic perspective, a system dynamics model was applied to green car environment to build a system dynamics analysis model that is applicable to particular green car industry analysis. Lastly, an agent based model was used to study the way to activate the hybrid car market in Korea from individual consumers' perspective. Based on the result, vehicle policies that are either being enforced or planned to be enforced in the Korean HEV market can be analyzed.

• 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.

• International Commerce and Information Review
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• v.14 no.4
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• pp.517-541
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• 2012

Since the Korea-Chile FTA in 2003, eight FTAs are now in force including Korea-EU and Korea-US FTA. The government anticipate that FTAs increase the GDP of Korea. Government-related research institutes officially reports the positive economic impact in Korea. However, the report does not show that how much Busan economy is affected by the FTAs. For this reason, we study the economic effects of FTAs in Busan. We compare the trade statistics before and after the time each FTA is in force. The resulting figures show that the exports and trades of Busan with the FTA nations increased significantly after the enforcement. For example, the exports to Chile increased by 273% when we compare the three-year average trade. We also construct an econometrics model to estimate the price elasticity. The estimated elasticity of exports for manufactured goods is 1.38 while that of imports is 0.83. Among the manufacturing industry, machinery has the highest price elasticity, 1.8. The average tariff for manufactured goods is 3.9% for FTA nations, while that is 5.8% for Busan. This higher price fall in Busan is offset by the lower price elasticity to make Busan's export increase be greater than Busan's import increase. Busan's export increases by 4.8% while import increases by 3.7%. So, it is expected to be added to the annual trade surplus of approximately $107million.

• Korean Journal of Construction Engineering and Management
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• v.19 no.3
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• pp.52-60
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• 2018

Korea's public construction projects are under construction through bidding, however, due to the nature of the bidding, collusion between participants can occur. The collusion of bids accordingly damages the client. So, it is necessary to calculate the appropriate fictitious competition price to compensate for this. In this regard, econometrics methods are generally used, but there are limitations and issues arising from the nature of construction, especially design-build bid. Therefore, this study proposes a method to estimate reasonable competitive bid-price in design-build bid. It derives the lowest bid-price from the design submitted by the proponent and estimates the competitive bid-price by examining the factors according to the penetration rate according to the technical level of the tester, the skill level of the competitor, and the type of tester. Based on the method proposed in this study, a reasonable price can be derived that reflects the characteristics of the design and construction bidding bidder selection method and also it can be used as a reference material in the actual bidding process as well as calculating the damage due to the answer.

• Journal of the Economic Geographical Society of Korea
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• v.23 no.2
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• pp.125-146
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• 2020

There is an increasing need to foster new industries at the local level. This study aims to analyze the spatial patterns of new industries in Korea from 2007-2017 and to figure out its determinants of agglomeration in 2017. Through this study, it is found that new industries are unevenly distributed around Seoul Metropolitan Area(SMA). The regional disparity between SMA and non-SMA is prominent. Furthermore, new industries represent a strong spatial positive autocorrelation, showing a strong concentration on a few regions in Korea. This study explores the determinants on agglomeration of new industries with spatial statistical model. From the results of spatial error model, it is indicated that the number of graduate students, the ratio of technology based start-ups, and the number of elementary, middle, and high schools have a significant effect on new industries. In addition, the specialization and the diversity of industrial structure on knowledge-based manufacturing industries and knowledge-based service industries have been statistically significant. This study provides implications that non-SMA needs policies with respect to attracting talented people, developing human resources, and improving regional environment in order to improve regional competitiveness in promoting new industries.

• Korea Science and Art Forum
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• v.37 no.2
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• pp.35-46
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• 2019

The purpose of this study was to develop a hybrid model forecasting the optimal number of employees for the hotel MICE and investigate indicators' reliability and validity empirically. The dominant approach of manpower planning has long been conducted based on heuristic experience in the field of Hotel and MICE. There is little research on the manpower planning and forecasting in the hotel and MICE studies. However, it is significantly important to ensure how many the optimal number of employees are calculated to meet the goals of the company as well as the expectation of their customers. A focus group interview was used to collect data through a series of surveys. A total of 289 samples were collected to test validity of finalized indicators for forecasting the optimal number of employees for the Hotel MICE. The study developed 15 quantitative indicators and 19 qualitative indicators to forecasting the optimal number of employees for the Hotel MICE, based on three types of groups such as 'service-oriented', 'stability-oriented', and 'profitability-oriented' hotel company The study revealed the econometrics formula for the practical application for this field.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.3
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• pp.129-141
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• 2019

In recent years, fast growing cities in Korea are showing signs of being vulnerable to more disasters as their population and facilities increase and intensify. In particular, fire is one of the most common disasters in Korea's cities, along with traffic accidents. Therefore, in this study, we analyze what type of factors affect the fire that threatens urban people. Fire data were acquired for 10 years, from 2007 to 2017, in Jinju, Korea. Spatial distribution pattern of fire occurrence in Jinju was assessed through the spatial autocorrelation analysis. First, spatial autocorrelation analysis was carried out to grasp the spatial distribution pattern of fire occurrence in Jinju city. In addition, correlation and multiple regression analysis were used to confirm spatial dependency and abnormality among factors. Based on this, OLS (Ordinary Least Square) regression analysis was performed using space weighting considering fire location and spatial location of each facility. As a result, First, LISA (Local Indicator of Spatial Association) analysis of the occurrence of fire in Jinju shows that the most central commercial area are fire department, industrial area, and residential area. Second, the OLS regression model was analyzed by applying spatial weighting, focusing on the most derived factors of multiple regression analysis, by integrating population and social variables and physical variables. As a result, the second kind of neighborhood living facility showed the highest correlation with the fire occurrence, followed by the following in the order of single house, sales facility, first type of neighborhood living facility, and number of households. The results of this study are expected to be useful for analyzing the fire occurrence factors of each facility in urban areas and establishing fire safety measures.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.2
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• pp.18-29
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• 2022

The purpose of this study is to examine the spatial characteristics and factors in the occurrence of COVID-19 from January 20 to August 30 of 2020. The exploratory spatial data analysis and spatial econometrics model are used. The spatial unit of analysis is 255 si-gun-gu in Korea. As a result of the analysis, COVID-19 infection did not appear to be a significant factors(host and environment) influencing the emergence of existing new infectious diseases, but there was a relationship between spatially adjacent areas and their occurrence. It also showed a close relationship with the outbreak pattern of group 4 infectious diseases, another type of new infectious disease in Korea. The result of this study shows that COVID-19 is not a new pattern of emerging infectious diseases. It means that the properties of the space where new infectious diseases appear must be continuously managed in order to effectively control new infectious diseases.