• Survey Research
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• v.2 no.2
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• pp.131-152
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• 2001

In this Era of Information and Localization. Gross Regional Domestic Product(GRDP) is recognized as indispensable information to establish regional economic policy. Especially, to raise Chungbuk province's economical independence and to establish effectual regional economic development plans, Chungbuk province needs quarterly estimated GRDP for developing regional economic forecasting system. In this study. utilizing small area estimation is proposed to estimate the quarterly Chungbuk-GRDP. To estimate quarterly GRDP. this study assumes that the comovement between the annual Chungbuk-GRDP provided by the Bureau of Statistics and nation's GDP provided by the Bank of Korea exists. Moreover, from the nation's quarterly GDP in each section of economical activity, this study has presumed the quarterly comovement. applied ft to subdivide Chungbuk annual GRDP quarterly, and estimated quarterly Chungbuk-GRDP.

• Proceedings of the Korean Association for Survey Research Conference
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• 2001.11a
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• pp.47-64
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• 2001

In this Era of Information and Localization, GRDP is recognized as indispensable information to establish regional economic policy. Especially, to raise Chungbuk province's economical independence and to establish effectual regional economic development plans, Chungbuk province needs quarterly estimated GRDP for developing regional economic forecasting system. In this study, utilizing small area estimation is proposed to estimate the quarterly Chungbuk-GRDP. To estimate quarterly GRDP, this study assumes that the comovement between the annual Chungbuk-GRDP provided by the Bureau of Statistics and nation's GDP provided by the Bank of Korea exists. Moreover, from the nation's quarterly GDP in each section of economical activity, this study has presumed the quarterly comovement, applied it to subdivide Chungbuk annual GRDP quarterly, and estimated quarterly Chungbuk-GRDP.

• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.1129-1138
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• 2011

Small area estimation has received significant intention in recent years due to a growing demand for reliable local area statistics. Traditional area-specific direct estimates based solely on sample survey data in the areas of interest do not provide adequate small area precision; however, design-based indirect local area estimators borrow strength from sample observations of related areas to increase the effective sample size. Design-based indirect estimation methods such as synthetic and composite estimators are considered to adjust local area unemployment rate estimates in the Korean Economically Active Population Survey. This study suggests an efficient alternative to minimize the cost to construct the unemployment rate of a local area through simulation under the condition that we can maintain a certain level of CV for the estimates. We obtained the results that the composite estimators using a sample size greater than 10 are more stable and significant at the level of CV 25% in our design scheme.

• The Korean Journal of Applied Statistics
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• v.16 no.1
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• pp.1-14
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• 2003

In this study, we suggest the method of small area estimation based on the Economically Active Population Survey (EAPS) data in producing unemployment statistics for the local self-government areas (LSGAs) within large areas. The small area estimators considered are design-based indirect estimators such as the synthetic and composite estimators. The jackknife mean square error was used as a measure of accuracy of such small area estimators. The total unemployed and jackknife mean square errors of the 10 LSGAs within the large area of ChoongBuk region are derived from the estimation procedure suggested in this study, using EAPS data of December 2000. The reliability of small area estimators was assessed using the relative bias values and relative root mean square errors of these estimators. We find that under the current Korean EAPS system, the composite estimator turns out to be much more stable than other estimators.

• Journal of Korean Society of Transportation
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• v.16 no.1
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• pp.79-98
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• 1998

교통계획의 수립은 사람과 화물의 이동상태에 대한 파악으로부터 시작되며 화물이동상태를 파악 하기 위한 가장 기본적인 데이터는 지역별 발생집중 화물량일 것이다. 이러한 지역별 발생집중 화물량의 추계방법중 추계의 간편성과 경제상황변화의 반영이 용이하다는 점에서, 최근 학자들의 상당한 주목 을 받으며 연구되고 있는 것이 산업연관분석을 응용한 물류해석방법이다. 그러나 이방법은 대상지역의 산업연관표를 기본 data로 하기 때문에 해당지역의 산업연관표의 존재 여부에 따라서 그 적용범위가 제한된다. 이러한 문제점을 해결하기 위해서 연구되고 있는 방법이 Nonsurvey법이다. Nonsurvey법은 대 지역의 산업연관표로부터 그 지역에 포함된 소지역의 산업연관표를 여러 가지 보조적인 데이터를 이용해 서 간접적으로 추계하는 방법이다. 본연구에서는 이러한 Nonsurvey법의 하나로서 대지역의 산업연관표 와 지역분해된 각 소지역의 산업부문별 생산량만을 이용해서 각 소지역의 발생집중화물량을 추계하는 방법을 제안했다. 그리고 일본의 긴키(Kinki)지역과 이에 속하는 4부현을 대상으로 본연구의 방법으로 추계된 이출입양과 실제의 산업연관표상의 이출입량을 비교.분석함으로써 본 연구의 방법에 대한 검증을 실시했다. 본 연구에서 제아한 지역별 발생집중 화물량 추계방법의 특징은 다음과 같다. 첫째, 대지역내 각 소지역간의 이출입량이 분기계수라고 하는 산업관계표의 산업관계표의 행방향의 합에 대한 비율을 사용함으로서 간단히 추계가능 하다. 둘째, 추계된 소지역의 산업관계표는 대지역에 대한 시스템전체의 정합성이 유지된다. 셋째 분해되는 소지역의 수에 관계없이 각소지역의 이출입양에 대한 추계가 가능하다.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.63-68
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• 2003

도시가구의 지출 중 집세가 차지하는 비율이 높으며 그 변동에 따라 도시가구의 생활에 미치는 영향도 커서 중요한 통계자료로 인식되고 있다. 집세 계약기간이 통상 2년 단위이기 때문에 집세변동의 발생빈도가 적어서 이러한 소표본 군의 통계단위로 일반적인 집세지수를 작성하는데는 많은 어려움이 따른다. 그렇다고 해서 소표본 군의 표본을 확대하는 것도 어렵기 때문에 이러한 산술적인 표본확대가 어려운 소표본 군의 문제점을 해결하기 위해 소지역 추정법을 도입하였다. 이러한 소표본 통계단위에서의 집세 변동률 추정방법을 경기도 지역의 6개 도시에서의 집세변동을 추정하는데 적용하였으며 검토해 보았다.

• Proceedings of the Korean Statistical Society Conference
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• 2002.05a
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• pp.7-12
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• 2002

경제활동인구조사에서 시군구의 실업자를 추정하는데 소지역 추정법을 이용하는 방안에 대한 연구는 관심의 대상이 되고 있다. 본 연구에서는 합성 추정법과 복합 추정법을 이용한 시군구 실업통계 작성법을 소개하였고 추정량이 편향이므로 잭나이프 방법을 이용한 추정량의 정도를 계산하는 절차를 설명하였으며, 광주광역시의 구별 실업통계작성을 사례로 제시하였다.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.97-115
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• 2023

In recent years, the structure of the population has been changing rapidly, with a declining birthrate and aging population, and the inequality of population distribution is expanding. At this point, changes in population estimation methods are required, and more accurate estimates are needed at the subregional level. This study aims to estimate the population in 2040 at the 500m grid level by applying an explainable machine learning to Busan in order to respond to this need for a change in population estimation method. Comparing the results of population estimation by applying the explainable machine learning and the cohort component method, we found that the machine learning produces lower errors and is more applicable to estimating areas with large population changes. This is because machine learning can account for a combination of variables that are likely to affect demographic change. Overestimated population values in a declining population period are likely to cause problems in urban planning, such as inefficiency of investment and overinvestment in certain sectors, resulting in a decrease in quality in other sectors. Underestimated population values can also accelerate the shrinkage of cities and reduce the quality of life, so there is a need to develop appropriate population estimation methods and alternatives.

• Survey Research
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• v.1 no.1
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• pp.1-19
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• 2000

The present status of utilizing statistics and problems in the era of information and localization are summarized and the developing process in a computerized survey is investigated. Also, characteristics and development plans of the internet surveys to come, which can substitute for telephone surveys, are discussed. We introduced small area estimation for producing the local statistics and suggested the standardization of statistics of improve statistics use and avoid misunderstanding in various areas of studies.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1133-1146
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• 2016

Counts or averages over arbitrary regions are often analyzed using conditionally autoregressive (CAR) models. The spatial neighborhoods within CAR model are generally formed using only the inter-distance or boundaries between the sub-regions. Kyung and Ghosh (2009) proposed a new class of models to accommodate spatial variations that may depend on directions, using different weights given to neighbors in different directions. The proposed model, directional conditionally autoregressive (DCAR) model, generalized the usual CAR model by accounting for spatial anisotropy. Bayesian inference method is discussed based on efficient Markov chain Monte Carlo (MCMC) sampling of the posterior distributions of the parameters. The method is illustrated using a data set of median property prices across Greater Glasgow, Scotland, in 2008.