• Communications for Statistical Applications and Methods
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• v.16 no.1
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• pp.31-40
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• 2009

Spatial time series data can be viewed either as a set of time series collected simultaneously at a number of spatial locations. In this paper, We estimate the parameters of spatial time autoregressive moving average (SIARMA) process by method of Gibbs sampling. Finally, We apply this method to a set of U.S. Mumps data over a 12 states region.

• Communications for Statistical Applications and Methods
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• v.16 no.4
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• pp.659-667
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• 2009

Recently Song and Cheon (2006) and Cheon and Lim (2009) developed the generalized maximum entropy(GME) estimator to solve ill-posed problems for the regression coefficients in the simple panel model. The models discussed consider the individual and a spatial autoregressive disturbance effects. However, in many application in economics the data may contain nested groupings. This paper considers a two-way error component model with nested groupings for the ill-posed data and proposes the GME estimator of the unknown parameters. The performance of this estimator is compared with the existing methods on the simulated dataset. The results indicate that the GME method performs the best in estimating the unknown parameters in terms of its quality when the data are ill-posed.

• 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.

• International Commerce and Information Review
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• v.16 no.4
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• pp.385-408
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• 2014

The purpose of this paper is to find the determinants of Korean FDI(1996~2012) in China using the spatial autoregressive model and four regions of China is analyzed respectively. Most previous studies ignored spatial interdependence to analyze the determinants of Korean outward FDI in China. Empirical results of total Chinese area shows per RGDP and spatial effects are positive and significant variables. Results of region A reveal that per RGDP is positive and spatial effects are negative and significant. Results of region B shows that both per GDP and spatial effects are positive. All variables of region C are insignificant but those of region D are significant and positive. This means that Korean companies to invest in region D should consider spatial characteristics of surrounding areas of D.

• Journal of Korean Society of Transportation
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• v.15 no.1
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• pp.5-15
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• 1997

공간통계분석은 공간적으로 연계된 변수들간의 관계를 분석하는 통계분야이다. 일 반적으로 공간적으로 연계된 변수들간의 관계는 각 변수간의 공간적 분포정도에 따라서 영 향을 받는다. 전통적인 통계 분석의 방법은 동질의 자료발생과정에 의하여 확률적으로 축출 된 표본자료를 가정하고 있으나, 공간적인 자료는 이와 같은 동질의 자료발생과정의 가정을 부정한다. 교통류 및 교통사고 등과 같은 교통분야의 자료는 대부분 공간적인 상관관계에 의하여 축출된 이질적인 표본자료이며 따라서 공간상관관계를 동질적으로 가정한 전통적인 통계적 분석 방법은 오류를 범할 수 있다. 본 논문은 공간적인 관계를 고려한 공간자기상관 분석기법을 이용하여 고속도로상의 교통사고에 관하여 분석하였다. 분석의 결과에 의하면 4 개 고속도로 중 경인고속도로를 제외한 3개의 고속도로상의 교통사고건수는 통계적으로 현 저한 양의 공간적 상관관계가 있음을 알 수 있었다. 이에 따라 공간적 상관관계를 고려한 교통사고분석을 위하여 종속변수로 단위구간별 교통사고건수를 그리고 설명변수로서는 단위 구간별 교통량, I.C. 유무 및 화물차량비율을 이용하여 공간 자기회귀분석을 시도하였다. 분 석의 분석에서는 구간별 교통량과 화물차량의 비율이 호남/남해 고속도로의 경우에는 구간 별 교통량과 I.C. 유무가 통계적으로 유의한 것으로 분석되었다.

• Asia-Pacific Journal of Business
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• v.15 no.1
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• pp.335-352
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• 2024

Purpose - Low fertility rate is a serious problem, and this study analyzes factors affecting total fertility rate using panel data from 16 metropolitan cities and provinces in Korea from 2000 to 2022. Design/methodology/approach - Estimating the SAR model considering the weak cross-sectional dependence that exists in variables related to the regional total fertility rate, and using the DKSE estimation method considering the strong cross-sectional dependence. Findings - Estimation results considering weak and strong cross-sectional dependence were similar, confirming the robustness of the results. Female labor force participation rate has a positive effect on total fertility rate, and employment rate has no effect. However, the interaction term is a negative (-) sign. Crude marriage rate has a positive effect on total fertility rate, and apartment price has a slightly positive effect. Environmental factor has no effect, and policy factor has a negative effect. Research implications or Originality - In order for an increase in the female labor force participation rate to lead to an increase in the total fertility rate, qualitative improvements in female employment must be made. Financial investment policies for childbirth must increase their effectiveness. The problem of low fertility rate requires not only population policy but also social, economic, cultural, environmental, and policy conditions to be considered.

• Journal of the Korean Regional Science Association
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• v.40 no.2
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• pp.91-106
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• 2024

Around the world, many countries experiencing the issue of shrinking cities are continually expanding high-speed rail networks to enhance regional accessibility and address imbalances. This study analyzed the effects of high-speed train operations on the age-specific population migration in South Korean municipalities from 2012 to 2019, taking into account the risk levels of shrinking cities. For this purpose, an analysis was conducted using age-specific net in-migration population as the dependent variable, employing the spatial panel autoregressive model. The research results indicated that the influence of high-speed rail on regional population inflow varies depending on the risk level of shrinking city. In other words, high-speed railway operations had positive effects on population inflow in the capital areas and some major cities, while explained population outflow in the other regions. High-speed railways particularly exerted a significant impact on the inflow of the young and middle-aged population, representing the working age, but this effect was also limited to regions with a low risk of shrinkage. The findings of this study emphasize the importance of considering planned population and industrial attraction when installing high-speed rail with the goal of achieving regional balanced development and mitigating shrinkage. The results of this study also suggest the need for subsequent research to explore factors that positively influence population structure and inflow based on the level of shrinkage risk in each region, as well as the introduction of new policies tailored to the specific situations of each local government.

• The Korean Journal of Applied Statistics
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• v.21 no.5
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• pp.855-866
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• 2008

Recently many small area estimation methods using the lattice data analysis have been studied and known that they have good performances. In the case of using the lattice data which is mainly used for small area estimation, the choice of better neighborhood information system is very important for the efficiency of the data analysis. Recently Lee and Shin (2008) compared and analyzed some neighborhood information systems based on GIS methods. In this paper, we evaluate the effect of various neighborhood information systems which were suggested by Lee and Shin (2008). For comparison of the estimators, MSE, Coverage, Calibration, Regression methods are used. The number of unemployment in Economic Active Population Survey(2001) is used for the comparison.

• The Korean Journal of Applied Statistics
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• v.21 no.4
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• pp.705-716
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• 2008

The objectives of this study are the detection and forecast of climate change signal in the annual mean of surface temperature data, which are generated by MRI/JMA CGCM over the Korean Peninsula. MRI/JMA CGCM outputs consist of control run data(experiment with no change of $CO_2$ concentration) and scenario run data($CO_2$ 1%/year increase experiment to quadrupling) during 142 years for surface temperature and precipitation. And ECMWF reanalysis data during 43 years are used as observations. All data have the same spatial structure which consists of 42 grid points. Two statistical models, the Bayesian fingerprint method and the regression model with autoregressive error(AUTOREG model), are separately applied to detect the climate change signal. The forecasts up to 2100 are generated by the estimated AUTOREG model only for detected grid points.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.4
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• pp.138-150
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• 2012

The purpose of this study was to examine the regional disparity of ambulatory health care utilization considering spatio-temporal variation in South Korea during 1996-2008(precisely, in 1996, 1999, 2002, 2005, and 2008) using bayesian hierarchial spatio-temporal model. The spatial pattern uses an intrinsic gaussian conditional autoregressive (CAR) error component. Ornstein-Uhlenbeck method was applied to detect the temporal patterns. The results showed that substantial temporal-geographical variation depending on diseases exists in Korea. On the Contrary to the pattern of total outpatient utilizations, for example, the areas that chronic diseases distributed relatively high were most in rural where the proportion of elderly population was higher than in the urban. Chungcheongnam-do, Junlabuk-do, and Kyeongsangbuk-do had higher risks in hypertension, whereas arthritis was higher risk in the Kyeonggi-do, Chungcheongbuk-do, Junlanam-do, and Junlabuk-do. The results of this study suggested that the effective health intervention programmes needed to alleviate the regional variation of health care utilization. These outcomes also provided the foundation for further investigation of risk factors and interventions in these high-risk areas.