• 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.

• 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 the Economic Geographical Society of Korea
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• v.10 no.4
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• pp.394-413
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• 2007

This paper attempts to analyze spatial determinants of innovative activities at the municipal level in Korea, capitalizing upon spatial econometric techniques. Several spatially weighted matrices will be employed, implying diverse spatial conceptions and interactions. A contribution can be have been made to enhancing an understanding of the spatial interaction and structure of knowledge spillovers in Korea.

• Journal of the Korean association of regional geographers
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• v.7 no.3
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• pp.107-120
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• 2001

This study is concerned with providing a reliable procedure of calibrating a set of places specific distance parameters and with applying it to U.S. inter-State migration flows between 1985 and 1900. It attempts to conform to recent advances in quantitative geography that are characterized by an integration of ESDA(exploratory spatial data analysis) and local statistics. ESDA aims to detect the spatial clustering and heterogeneity by visualizing and exploring spatial patterns. A local statistic is defined as a statistically processed value given to each location as opposed to a global statistic that only captures an average trend across a whole study region. Whereas a global distance parameter estimates an averaged level of the friction of distance, place-specific distance parameters calibrate spatially varying effects of distance. It is presented that a poisson regression with an adequately specified design matrix yields a set of either origin-or destination-specific distance parameters. A case study demonstrates that the proposed model is a reliable device of measuring a spatial dimension of migration, and that place-specific distance parameters are spatially heterogeneous as well as spatially clustered.

• Environmental and Resource Economics Review
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• v.7 no.1
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• pp.61-84
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• 1997

본 연구는 기존의 특성가격기법(特性價格技法)(hedonic price technique)에 공간(空間)개념을 도입한 계량경제모형을 이용하여 분석하였다. 이 공간시차모형은 기존의 모형과 달리 특성변수의 변화에 따른 직(直) 간접효과(間接效果)를 동시에 포착할 수 있는 장점을 가지고 있다. 또한 공간시차모형의 회귀진단 및 가설검정 결과는 공간시차모형이 적합한 것으로 나타났다. 이 경우 공간시차를 고려하지 않은 OLS 회귀분석 결과의 계수들은 편기추정(biased)된 동시에 효율적(efficiency)이지 못하다는 것이다. 회귀분석 결과는 주택에 자본화된 대기오염에 대한 잠재가격(潛在價格)(marginal implicit price)은 주택평균가격의 약 1.5% 정도인 것으로 추정된다.

• Environmental and Resource Economics Review
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• v.28 no.3
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• pp.327-354
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• 2019

In this paper, we conducted panel data analysis considering spatial correlation between regions, which were not considered in previous papers in analyzing the causes of fine dust concentration in Korea. Many existing researchers implicitly assume the independence of the effects of incomes and other explanatory variables of adjoining countries(or regions). Using panel data on fine dust concentration, this paper has established that existing EKC can be established even when considering the spatial correlation of the region, and when these effects are not taken into account, it can be underestimated or overestimated on the effects and causes of fine dust concentration.

• 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.

• Spatial Information Research
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• v.20 no.1
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• pp.81-90
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• 2012

When analyzing geographical phenomena, two properties need to be considered. One is the spatial dependence structure and the other is a variation or an uncertainty inhibited in a geographic space. Two problems are encountered due to the properties. Firstly, spatial dependence structure, which is conceptualized as spatial autocorrelation, generates heterogeneous geographic landscape in a spatial process. Secondly, generic statistics, although suitable for dealing with stochastic uncertainty, tacitly ignores location information im plicit in spatial data. GIS is a versatile tool for manipulating locational information, while spatial statistics are suitable for investigating spatial uncertainty. Therefore, integrating spatial statistics to GIS is considered as a plausible strategy for appropriately understanding geographic phenomena of interest. Geographic hot-spot analysis is a key tool for identifying abnormal locations in many domains (e.g., criminology, epidemiology, etc.) and is one of the most prominent applications by utilizing the integration strategy. The article aims at reviewing spatial statistical perspective for analyzing spatial processes in the framework of GIS by carrying out empirical analysis. Illustrated is the analysis procedure of using spatial scan statistic for detecting clusters in the framework of GIS. The empirical analysis targets for identifying spatial clusters of breast cancer incidents in Erie and Niagara counties, New York.

• Proceedings of the Korean Institute of Landscape Architecture Conference
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• 2023.10a
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• pp.90-91
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• 2023

• Journal of the Economic Geographical Society of Korea
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• v.25 no.4
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• pp.617-628
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• 2022

In this study, the land market in Eastern District of Gyeongseong is examined using land price data in the 1920's. For the study, land information in 1927 is constructed as a DB, and a map in 1929 is constructed as a GIS file to realize digitalization of historical data. As a result of the study, it is confirmed that spatial autocorrelation exists, and through spatial econometrics analysis, some factors affecting the modern land market are also valid at that time. The results show that land use and road accessibility have a positive effect on the land market, while the proximity of anchor facilities and educational facilities have a negative effect. This study is meaningful in that it has moved on to a research topic that has been insufficient until now by examining whether the factors operating in the land market in the 21st century are also valid in the land market in the 1920's.