• Title/Summary/Keyword: spatial econometric model

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Analysis of Determinant Factors of Land Price in Rural Area Using a Hedonic Land Price Model and Spatial Econometric Models (헤도닉분석기법과 공간계량경제모형을 이용한 농촌지역 지가의 영향인자 분석)

  • Suh, Kyo
    • Journal of Korean Society of Rural Planning
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    • v.11 no.3 s.28
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    • pp.11-17
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    • 2005
  • Land prices reflect not only the uses of land, but the potential uses as well(Plantinga, 2002) so land values can be applied to very effective indices for deciding regional status and growing potential. The purpose of this study is to deduce determinant factors of regional land prices. Principal determinants of regional land prices are analyzed with a hedonic technique and spatial econometric models based on 2001 statistic data of Korea except large cities. The results provide the followings. 1. The spatial effect of rural regions are very little with adjacent regions. 2. The common index of land price is population density and other determinant factors are different depending on land uses.

Analysis of Functional Autocorrelation and Development of Functional Econometric Model through Urban Interactions - Focusing on Economic Growth of Small and Medium Sized Cities - (도시 상호작용에 따른 기능적 자기상관분석 및 기능계량경제모형 개발 - 중소도시의 경제성장을 중심으로 -)

  • Kim, Dohyeong;Woo, Myungje
    • Journal of Korea Planning Association
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    • v.54 no.3
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    • pp.63-74
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    • 2019
  • Korean government has implemented policies to strengthen the competitiveness of small and medium sized cities. However, since it is often difficult to enhance the competitiveness through individual projects, many local governments in metropolitan areas are working together to pursue local growth. On the other hand, small and medium sized cities that are not included in metropolitan areas due to their spatial limitations have difficulties in implementing effective growth policies. Given this background, the purpose of this study is to identify the functional correlation based on urban interactions and develop functional econometric model for the economic growth of small and medium sized cities. This study uses spatial econometrics models and functional weight matrix to identify the effects of functional networks on small and medium sized cities. The results show the effect of functional networks on the growth of small and medium sized cities and provide policy implications for regional spatial planning that addresses effective management of small and medium sized cities.

A Comparative Study on the Goodness of Fit in Spatial Econometric Models Using Housing Transaction Prices of Busan, Korea (부산시 실거래 주택매매 가격을 이용한 공간계량모형의 적합도 비교연구)

  • Chung, Kyoun-Sup;Kim, Sung-Woo;Lee, Yang-Won
    • 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.

Research on Spatial Dependence and Influencing Factors of Korean Intra-Industry Trade of Agricultural Products: From South Korea's Agricultural Trade Data

  • Lv, Hong-Qu;Huang, Chen-Yang
    • Journal of Korea Trade
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    • v.25 no.3
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    • pp.116-133
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    • 2021
  • Purpose - Intra-industry trade of agricultural products can eliminate the disadvantage of Korea's traditional agriculture and improve its lack of comparative advantage. The main purpose of this paper is to measure the level and index of intra-industry trade of Korean agricultural products and to explore the spatial dependence and spillover effect associated with this type of trade. The main factors influencing intra-agricultural trade are analyzed from two perspectives: the population and the classification of agricultural products. Design/methodology - First, the level of intra-industry trade of Korean agricultural products is measured. Second, to obtain a more accurate estimate of the influence of various factors, and based on two types of weight matrices, a spatial econometric model is constructed from two aspects: population and classification of agricultural products. The status and the factors influencing intra-industry trade are also studied. Findings - It is concluded that there is a positive spatial correlation between Korea's intra-industry trade in agricultural products and that of its trading partners. The spatial spillover effect of this type of trade is verified by using the spatial autoregressive model (SAR). Labor-intensive agricultural products are found to have a positive spillover effect on intra-industry trade, while land-intensive products do not have a significant effect. Originality/value - In this paper, the two types of agricultural products are meticulously distinguished, and the spatial effect of the intra-industry trade of agricultural products as well as the influence of various factors are analyzed. In addition, the accuracy of the estimation of the coefficients of the factors by using the spatial econometric model is higher than that of the ordinary panel data model.

A spatial heterogeneity mixed model with skew-elliptical distributions

  • Farzammehr, Mohadeseh Alsadat;McLachlan, Geoffrey J.
    • Communications for Statistical Applications and Methods
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    • v.29 no.3
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    • pp.373-391
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    • 2022
  • The distribution of observations in most econometric studies with spatial heterogeneity is skewed. Usually, a single transformation of the data is used to approximate normality and to model the transformed data with a normal assumption. This assumption is however not always appropriate due to the fact that panel data often exhibit non-normal characteristics. In this work, the normality assumption is relaxed in spatial mixed models, allowing for spatial heterogeneity. An inference procedure based on Bayesian mixed modeling is carried out with a multivariate skew-elliptical distribution, which includes the skew-t, skew-normal, student-t, and normal distributions as special cases. The methodology is illustrated through a simulation study and according to the empirical literature, we fit our models to non-life insurance consumption observed between 1998 and 2002 across a spatial panel of 103 Italian provinces in order to determine its determinants. Analyzing the posterior distribution of some parameters and comparing various model comparison criteria indicate the proposed model to be superior to conventional ones.

Onion yield estimation using spatial panel regression model (공간 패널 회귀모형을 이용한 양파 생산량 추정)

  • Choi, Sungchun;Baek, Jangsun
    • The Korean Journal of Applied Statistics
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    • v.29 no.5
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    • pp.873-885
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    • 2016
  • Onions are grown in a few specific regions of Korea that depend on the climate and the regional characteristic of the production area. Therefore, when onion yields are to be estimated, it is reasonable to use a statistical model in which both the climate and the region are considered simultaneously. In this paper, using a spatial panel regression model, we predicted onion yields with the different weather conditions of the regions. We used the spatial auto regressive (SAR) model that reflects the spatial lag, and panel data of several climate variables for 13 main onion production areas from 2006 to 2015. The spatial weight matrix was considered for the model by the threshold value method and the nearest neighbor method, respectively. Autocorrelation was detected to be significant for the best fitted model using the nearest neighbor method. The random effects model was chosen by the Hausman test, and the significant climate variables of the model were the cumulative duration time of sunshine (January), the average relative humidity (April), the average minimum temperature (June), and the cumulative precipitation (November).

Asymmetry of Price Competition between Hotel and Alternative Accommodation Submarkets (호텔과 대체숙박업소 간 비대칭적 가격 경쟁 : 공간계량경제모형의 응용)

  • Noh, Su-Hyang;Shim, Yeong-Seok;Lee, Hee-Chan;Lee, Seul-Ki
    • The Journal of Information Systems
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    • v.26 no.3
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    • pp.229-246
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    • 2017
  • Purpose The purpose of this study is to examine the potential asymmetry in price competition between the geographically defined submarkets of the lodging industry, namely the traditional and alternative accommodation facilities. Design/methodology/approach The study utilizes a spatial econometric model to empirically test for the hypothesized asymmetry in price competition. Property-level panel data on hotels and alternative accommodation facilities collected from a major online travel agency (OTA: Agoda.com) was used for this purpose. Findings Result of the analysis shows significant intra-segment spatial price competition among the properties, that is, within hotels and within alternative accommodation submarkets, respectively. However, the inter-segment competition was found to be asymmetric as hypothesized. Room rates of hotels are influenced by prices of geographically close alternative accommodations, but the reverse does not hold. Implications for practitioners and suggestions for future research are discussed along with the findings of the study.

Research on the Impact of Logistics Industry Efficiency and Agglomeration Effect on Import and Export Trade in Korea

  • Cheng, Wen-Si
    • Journal of Korea Trade
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    • v.25 no.5
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    • pp.93-109
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    • 2021
  • Purpose - The logistics industry is often featured by its location relevance and industrial concentration. Industrial concentration is conducive to the effective transmission of information by reducing transaction costs and improving transaction efficiency, thus promoting the development of trade. The main purpose of this paper is to measure the spatial total factor productivity and location quotient of the logistics industry in Korea, and to study the impact of the logistics industry efficiency and agglomeration effect on import and export trade in Korea. Design/methodology - First, used the spatial stochastic frontier method to measure the spatial total factor productivity of the logistics industry in Korea, this serves as the efficiency index of the logistics industry in various regions of Korea. Second, calculated the location quotient (LQ) of the logistics industry to measure the industry's concentration degree. Third, employed a spatial econometric model to analyze the impacts of factors such as the efficiency and concentration levels of the logistics industry on import and export trade in Korea. Findings - This study's main findings can be summarized as follows: this study found that the overall efficiency of the logistics industry in Korea needs to be improved, even though it showed an upward trend in all regions of the country; Moreover, the agglomeration level of Korea's logistics industry needs to be improved; Finally, the positive spatial correlation and industrial agglomeration effect of Korea's logistics industry had a positive impact on the country's import and export trade. Originality/value - This study is innovative in terms of research perspective and methods. Most of the previous studies have measured the development level of the logistics industry using the logistics performance index (LPI), Fewer studies have assessed through the spatial total factor productivity and location quotient of the logistics industry in Korea to measure the efficiency index of the logistics industry in various regions of Korea and concentration degree, as well as there was almost no study on the impact of logistics industry efficiency and agglomeration effect on import and export trade in Korea. This study addresses this limitation by analyzing the impacts of the efficiency and agglomeration effect of the logistics industry on import and export trade in Korea.

Determinants of Homicide Locations Using Spatial Regression Analysis (공간회귀분석을 활용한 살인사건 영향요인 분석)

  • Lee, Soochang
    • Journal of the Korea Convergence Society
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    • v.10 no.5
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    • pp.203-211
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    • 2019
  • This study is to examine the impact of spatial characteristics of cities on homicide based on spatial econometric model. It selects housing types, racial heterogeneity, residential instability, overcrowding, commercial area, rate of 15 to 29 ages, and rate of the elderly as variables for spatial characteristics of cities. This study employs spatial regression analysis applying the spatial error model to analyze the data from 229 locals collected from Korean Statistical Information Service and Statistical Year Book of local governments. As a result, it shows that homicide has close relationships with apartment and multi-housing as housing types, racial heterogeneity, residential instability, and overcrowding, but not with the commercial area, rate of 15 to 29 ages, and rate of the elderly. The study contributes to expanding understanding and explanation on the causes of homicide focusing on social-structure approach for criminology by analyzing a more advanced model in applying variables than one of existing literature. This study suggests follow-up research on homicide based on both social-behavior approach and social-structure approach in the near future for the development of criminological theory.