• Journal of Korean Society of Rural Planning
• /
• v.26 no.3
• /
• pp.103-113
• /
• 2020

Land price can be affected by convenience or psychological repulsion like PIMFY (Please In My Front Yard) or NIMBY (Not In My Back Yard) for various facilities. The purpose of this study is to evaluate whether non-preferred facilities are related to NIMBY impact that negatively affect land prices using the spatial econometrics models which are spatial autoregressive models (SAR), spatial errors models (SEM), and general spatial model (SAC). The land price in urban area increases by 0.07-0.2% when the distance from aversion facilities increases by 1%. However, the land price in rural areas decreases when the distance from aversion or pollution facilities increase. Therefore, these facilities in rural areas located in the areas with higher land price because funeral homes located in center of rural administrative areas and charnel house or crematorium located in the fringe of urban areas. That is, this study explain the difference between land price and non-preferred facilities in urban and rural areas and why there are more N IMBY symptoms in urban areas.

• Journal of Korean Society of Rural Planning
• /
• v.22 no.4
• /
• pp.25-36
• /
• 2016

The purpose of this study is to construct a quantitative evaluation method that can analyze the policy effectiveness with the construction of a implicit composite index incorporating spatial econometrics models. In order to propose a methodological framework for the program evaluation, this study conducts an empirical analysis with the application of the Comprehensive Rural Village Development Project (CRVDP) which explicitly claims to achieve comprehensive goal of community development. The present study pays particular attention to quantifying the composite evaluation index and drawing net effect through the application of a series of spatial econometrics models. The spatial unit of the analysis is drawn at Eup-Myeon level in rural areas in Korea, and the time horizon is in between 2005 and 2010. We utilize the Korean Agricultural Census data in 2005 and 2010. Three steps of methodological processes are needed to satisfy the objective of the present study. First, we apply factor analysis to construct the composite index that represents comprehensive settlement environment in rural area. The index should be matched with the main objective of the CRVDP. Second, we apply the derived index to a series of spatial econometrics model as dependent variable. Lastly, utilizing the estimated coefficients of the econometrics models, we apply decomposition technique to estimate CRVDP's net effect from both cross-sectional and longitudinal perspectives. We find that the results of the decomposition analysis by the execution of the CRVDP are positively associated with the explicit object of the project.

• Asian Journal of Innovation and Policy
• /
• v.11 no.3
• /
• pp.320-341
• /
• 2022

Empirical applications to explain criminogenic events are abundant. While much of the research in criminal studies concentrates on understanding the motivations of offenders and preventing victimization from a micro perspective, there have been recent theoretical advancements that give priority to the role of spatial factors in directly impacting crime rates. The primary purpose of this study is to investigate the empirical inference between violent crime incidence and spatial characteristics of local areas focusing particularly on spatial accessibility conditions in the areas. Applying discrete spatial econometrics models, this study reveals a significant relationship between spatial accessibility and the formation of violent crime hot spots in South Korea. Along with other variables, it is revealed that road accessibility has a clear association with violent crime hot spots. Based on the findings, this study suggests some policy implications such as effective surveillance systems, land use restrictions, and advanced street lighting.

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

• Asian Journal of Innovation and Policy
• /
• v.10 no.2
• /
• pp.249-273
• /
• 2021

While many criminal studies have focused on the motivation of offenders and avoidance of victimization in the micro perspective, there have been a number of theoretical developments emphasizing space as a direct factor that influences the incidence of crime. The main purpose of this study is to analyze the effects of regional characteristics and violent crime incidence in Korea. Applying diverse spatial econometrics models that have less been utilized in the crime literature, this study finds an important association between spatial accessibility and crime incidence. The results suggest that the type of predominant business and the level of road accessibility affect the vulnerability of areas with respect to the incidence of violent crime. This study concludes with some important implications for urban planners and policymakers with respect to crime control and prevention.

• Journal of Korean Society of Rural Planning
• /
• v.14 no.4
• /
• pp.97-108
• /
• 2008

The present study construct a new technique that can evaluate diverse rural policies, which have been applied to the rural development programs at the village level. The method incorporates spatial econometrics models with a decomposition method that has little been utilized before. We applies the technique to evaluate the rural development programs that have been carried out by the Korea Forest Service and. Korea Rural Development Agency. The technique proved to be quite useful in that the technique efficiently separate the direct effect caused by the government policy from the effect explained by the endowment effect such as regional or area characteristics, and residual effect that cannot be identified by the models. The present study concludes with suggesting more quantitative methods need to be developed to evaluate diverse government policy programs, which enables us to discern correct policy effects.

• Communications for Statistical Applications and Methods
• /
• v.28 no.4
• /
• pp.315-327
• /
• 2021

The Spatial Autoregressive (SAR) models have drawn considerable attention in recent econometrics literature because of their capability to model the spatial spill overs in a feasible way. While considering the Bayesian analysis of these models, one may face the problem of lack of robustness with respect to underlying prior assumptions. The generalized Bayes estimators provide a viable alternative to incorporate prior belief and are more robust with respect to underlying prior assumptions. The present paper considers the SAR model with a set of linear restrictions binding the regression coefficients and derives restricted generalized Bayes estimator for the coefficients vector. The minimaxity of the restricted generalized Bayes estimator has been established. Using a simulation study, it has been demonstrated that the estimator dominates the restricted least squares as well as restricted Stein rule estimators.

• Journal of the Korean Regional Science Association
• /
• v.38 no.4
• /
• pp.75-91
• /
• 2022

With the recent increase in interest in climate change issues, the use of bicycles is complementing public transportation and attracting attention as one of the eco-friendly means of transportation. Daejeon Metropolitan City has been operating Tashu, a public bicycle, since 2008. This study empirically analyzed the spatial characteristics that affect the use of public bicycles by grasping the current status and characteristics of public bicycles and applying spatial econometrics analysis, an analysis model that considers the spatial dependence of spatial data. In addition, a comparative analysis was performed by deriving the results of analyzing six models in terms of rental, return, peak time, non-peak time, weekday, and weekend based on the spatial error model identified as the optimal spatial econometrics model. The analysis model results showed that significant spatial characteristics differed according to the type of public bicycle use. In general, the use of public bicycles was high in areas with a high proportion of young people, a high number of public transportation users, good access to universities and rivers, and relatively low land use mix, and high proportion of apartments. These results indicated that public bicycles are used for commuting purposes on weekdays and leisure purposes on weekends, and if the convenience of using bicycles is improved, the use of public bicycles can be further increased.

• East Asian Economic Review
• /
• v.25 no.1
• /
• pp.3-31
• /
• 2021

This paper estimates the effects of transport (road and rail) & energy and ICT infrastructure (telephone, mobile, and broadband) on GDP growths in neighboring countries as well as own countries. We confirm positive direct contributions of infrastructure, access to Internet, and human capital on economic growth. The spatial panel regression models indicate that there exist positive externalities of the broadband infrastructure and human capital, and these results are robust regardless of the choice of spatial weight matrices. Our findings on spillover effects of infrastructure suggest the key role of neighboring countries' infrastructure on own country's economic growth.

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