• Journal of the Economic Geographical Society of Korea
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• v.25 no.1
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• pp.183-201
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• 2022

Estimating the implicit value of housing assets is a very important task for participants in the housing market. Until now, such estimations were usually carried out using multiple regression analysis based on the inherent characteristics of the estate. However, in this paper, we examine the estimation capabilities of the Artificial Neural Network(ANN) and its 'Deep Learning' faculty. To make use of the strength of the neural network model, which allows the recognition of patterns in data by modeling non-linear and complex relationships between variables, this study utilizes geographic coordinates (i.e. longitudinal/latitudinal points) as the locational factor of housing prices. Specifically, we built a dataset including structural and spatiotemporal factors based on the hedonic price model and compared the estimation performance of the models with and without geographic coordinate variables. The results show that high estimation performance can be achieved in ANN by explaining the spatial effect on housing prices through the geographic location.

• The Korean Journal of Applied Statistics
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• v.29 no.6
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• pp.1129-1145
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• 2016

Functional neuro-connectivity is one of the main issues in brain science in the sense that it is closely related to neurodynamics in the brain. In the paper, we choose fMRI as a main form of response data to brain activity due to its high resolution. We review methods for analyzing functional neuro-connectivity assuming that measurements are made on physiological responses to neuron activation. This means that we deal with a state-space and measurement model, where the state-space model is assumed to represent neurodynamics. Analysis methods and their interpretation should vary subject to what was measured. We included analysis results of real fMRI data by applying a high-dimensional autoregressive model, which indicated that different neurodynamics were required for solving different types of geometric problems.

• Journal of the Economic Geographical Society of Korea
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• v.26 no.3
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• pp.310-323
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• 2023

Urbanization and income distribution issues are global interest, and the results of studies on the impact of urbanization on income inequality are different for each country and period. This study analyzes the impact of urbanization on income inequality using regional data from 2000-2021. In particular, serial correlation, spatial dependence, and common factor effects of the Gini coefficient are confirmed and analyzed through a dynamic spatial panel regression model. As a result, urbanization has a positive effect on reducing income inequality. Therefore, it is necessary to continuously promote regional urbanization to improve the income distribution problem. Areas with already high urbanization rates should reduce income inequality by narrowing the wage gap by expanding training opportunities for low-skilled workers, and need to come up with measures to prevent counter-urbanization.

• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.11-20
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• 2017

In this paper, we introduced linear spatial time series (space-time autoregressive and moving average model) and nonlinear spatial time series (space-time bilinear model). Also we estimated the parameters by Kalman Filter method and made comparative studies of power of forecast in the final model. We proposed several weight matrices such as equal proportion allocation, reciprocal proportion between distances, and proportion of population sizes. For applications, we collected Mumps data at Korea Center for Disease Control and Prevention from January 2001 until August 2008. We compared three approaches of weight matrices using the Mumps data. Finally, we also decided the most effective model based on sum of square forecast error.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.948-951
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• 2014

Road traffic noise is closely related with urban forms and urban components, such as population, building, traffic and land-use, etc. Hence, it is possible to minimize the noise exposure problem depending on how to plan new town or urban planning alteration. This paper provides ways to apply for urban planning in consideration of noise through exposed noise estimation for urban planning alteration. Spatial autoregressive model which explains about 81.4% of road traffic noise from the former paper is used. The simulation results by the spatial statistical model are compared with those by the engineering program-based modeling for 5 small-scaled scenarios of urban planning alteration. The error from the limitation of containing informations inside the grid cell and the difficulties of reflecting acoustic phenomena is existed. Nevertheless, in the stage of preliminary design, the use of the statistical models that have been estimated well is useful in time and economically.

• Korea Real Estate Review
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• v.28 no.4
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• pp.37-51
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• 2018

The purpose of this paper is to analyze the effects of location factors on sales by restaurant type in the six districts of Seoul (Jongno-gu, Jung-gu, Yeongdeungpo-gu, Gangnam-gu, Seocho-gu, and Songpa-gu). Ordinary least squares (OLS) regression model is selected for four restaurant types whose spatial autocorrelation is not identified, spatial lag model (SLM) is only selected for seafood restaurant, and spatial error model (SEM) is selected for nine other restaurant types. The floating population and the workers of surrounding businesses have generally positive effects on the sales of restaurants. The floating population elasticity of the sales of restaurants are found to be in the descending order of Oriental food, pub, Western food, and traditional food restaurant, and the elasticity of the workers of surrounding businesses are in the descending order of bakery, Oriental food, and Western food restaurant. The spatial multiplier effects are in the descending order of Oriental food, pub, and Western food restaurant. There is a statistically significant sales gap between roast meat, pub, and bakery in Gangnam-gu and those in five other districts. The results of this research can help in starting a restaurant in that they can provide information on the suitability of location by restaurant type.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1169-1182
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• 2016

Cancer is a typical cause of death in Korea that becomes a major issue in health care. According to Cause of Death Statistics (2014) by National Statistical Office, SMRs (standardized mortality rates) in Busan were counted as the highest among all cities. In this paper, we used data of Busan Regional Cancer Center to estimate the extent of the cancer incidence rate and cancer mortality rate. The data are considered in small areas of administrative units such as Gu/Dong from years 2003 to 2009. All cancer including four major cancers (stomach cancer, colorectal cancer, lung cancer, liver cancer) have been analyzed. We carried out model selection and parameter estimation using spatial multi-level model incorporating a spatial correlation. For the spatial effects, CAR (conditional autoregressive model) has been assumed.

• Journal of the Economic Geographical Society of Korea
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• v.17 no.2
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• pp.402-419
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• 2014

This study attempts to investigate the spatial characteristics of private tutoring markets for adults which have been expanded rapidly with labor market changes in Korea. In particular, For the purpose, we examine thoroughly various indies of labor markets and private tutoring markets for adults in Korea in first and then analyze the spatial characteristics. We classify private tutoring institutes for adults into two categories by job-statuses and education levels, and analyze the spatial distribution patterns of the attendants of the classes. In order to understand the spatial characteristic of their distributions, we distinguish whether there exist the spatial autocorrelation or not by applying Moran's I values for each categories in first. We also examine the spatial cluster patterns by Hot spots analysis utilizing $G^*$ statistics. Multiple linear regression models are developed for each category to explain the relationships between the spatial distributions of private tutoring institutes and geographical variables.

• Journal of the Korean Regional Science Association
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• v.33 no.3
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• pp.21-30
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• 2017

The purpose of this study is to analyze the effect of urban characteristics on regional population and to suggest policy implications based on the analysis results. For this purpose, this study used spatial econometrics analysis(SAR, SEM, SAC) using data on 122 eup-myon-dong areas in Incheon Metropolitan City. As a result of the analysis, First, in terms of spatial, population density showed positive (+) effect while employment density has negative (-) effect. Also, the increase in the number of tertiary industries and workers in the industry has a positive (+) effect. Second, in terms of housing, the apartment ratio showed positive (+) effect and the increase of low-rise deteriorated housing has negative (-) effect. Third, the increase in educational facilities and urban parks showed positive (+) effect on population. In conclusion several policy implications for urban management found through this analysis are discussed.

• Management & Information Systems Review
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• v.37 no.3
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• pp.27-47
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• 2018

In this study, we examine how land use zoning affects the land price controlling other variables such as road-facing condition of the land, land form, land age after its development and land size. We employ geographically weighted regression analysis which reflects spatial dependency as methodology with a data sample of land transaction price data of Jangyu, a new town, in Korea. The results of our empirical analysis show that the respective coefficients of traditional regression and geographically weighted regression are not significantly different. However, after calculating Moran's Index with residuals of both OLS and GWR models, we find that Moran's Index of GWR decreases around 26% compared to that of OLS model, thus improving the problem of spatial autoregression of residuals considerably. Unlike our expectation, though, in both traditional regression and geographically weighted regression where residential exclusive area is used as a reference variable, the dummy variable of the residential land for both housing and shops shows a negative sign. This may be because the residential land for both housing and shops is usually located in the level area while the residential exclusive area is located at the foot of a mountain or on a gentle hill where the residents can have good quality air and scenery. Although the utility of the residential land for both housing and shops is higher than its counterpart's since it has higher floor area ratio, amenity which can be explained as high quality of air and scenery in this study seems to have higher impact in purchase of land for housing. On the other hand, land for neighbourhood living facility seems to be valued higher than any other land zonings used in this research since it has much higher floor area ratio than the two land zonings above and can have a building with up to 5 stories constructed on it. With regard to road-facing condition, land buyers seem to prefer land which faces a medium-width road as expected. Land facing a wide-width road may have some disadvantage in that it can be exposed to noise and exhaust gas from cars and that entrance may not be easy due to the high speed traffic of the road. In contrast, land facing a narrow road can be free of noise or fume from cars and have privacy protected while it has some inconvenience in that entrance may be blocked by cars parked in both sides of the narrow road. Finally, land age variable shows a negative sign, which means that the price of land declines over time. This may be because decline of the land price of Jangyu was bigger than that of other regions in Gimhae where Jangyu, a new town, also belong, during the global financial crisis of 2008.