• 보건행정학회지
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• 제13권3호
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• pp.91-103
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• 2003

The purpose of this study was to provide basic reference data for stabilization scheme of health expenditure through forecasting of health expenditure. The authors analyzed the health expenditure from 1985 to 2000 that had been calculated by Korean institute for health and social affair using transfer function model as ARIMA model with input series. They used GDP as the input series for more precise forecasting. The model of error term was identified ARIMA(2,2,0) and Portmanteau statics of residuals was not significant. Forecasting health expenditure as percent of GDP at 2010 was 6.8%, under assumption of 5% GDP increase rate. Moreover that was 7.4%, under assumption of 3% GDP increase rate and that was 6.4%, under assumption of 7% GDP increase rate.

• Architectural research
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• 제8권1호
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• pp.77-84
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• 2006

In spite of enormous increase in data generation, its practical usage in the construction sector has not been prevalent enough compared to those of other industries. The author would explore the obstacles against efficient data application in the arena of expenditure forecasting, and suggest a forecasting method by applying Case-based Reasoning (CBR). The newly suggested method in the research, enables project managers to forecast monthly expenditures with less time and effort by retrieving and referring only projects of a similar nature, while filtering out irrelevant cases included in database. Among 99 projects collected, the cost data from 88 projects were processed to establish a new forecasting model. The remaining 10 projects were utilized for the validation of the model. From the comprehensive study, the choice of the numbers of referring projects was investigated in detail. It is concluded that selecting similar projects at 12~19 % out of the whole database will produce a more precise forecasting. The new forecasting model, which suggests the predicted values based on previous projects, is more than just a forecasting methodology; it provides a bridge that enables current data collection techniques to be used within the context of the accumulated information. This will eventually help all the participants in the construction industry to build up the knowledge derived from invaluable experience.

• 한국건축시공학회지
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• 제12권3호
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• pp.257-265
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• 2012

공동주택 건설사업에서 건설사들은 다수의 프로젝트를 동시에 수행하고 있으며, 최적의 공정관리와 자원투입으로 프로젝트의 현금흐름을 정확히 예측하는 것은 합리적 자금운용과 경쟁력 향상을 위하여 필수적이다. 기존의 현금흐름 예측 방법은 수입과 지출요소의 차이가 크게 발생하여 정확성이 낮아졌다. 본 연구는 K 건설사의 공동주택 공사관리 실태를 조사하여 현금흐름 예측의 문제점을 파악하였다. 기존의 원가관리 시스템의 개선을 위해 업무프로세스와 공사관리 시스템의 통합이 필요하였다. 현금흐름 예측모델 구축을 위해 수입과 지출요소 및 지출방법 등을 종합 현금흐름 예측창에 표시하였다. 또한, K사의 실시간 손익실행금액과 매출기성을 산정할 수 있는 TO-BE 업무 모델을 구축하여, 수입과 지출의 부정확한 요소를 배제한 현금흐름 예측 모델을 제안하였다.

• 한국건설관리학회논문집
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• 제4권4호
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• pp.114-122
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• 2003

Dynamic and fragmented characteristics are two of the most significant factors that distinguish the construction industry from other industries. Previous forecasting techniques have failed to solve the problems derived from the above characteristics, and do not provide considerable support This paper deals with providing a more precise forecasting by applying Case-based Reasoning (CBR). The newly developed model in this study enables project managers to forecast monthly expenditures with less time and effort by retrieving and referring only projects of a similar nature, while filtering out irrelevant cases included in database. For the purpose of accurate forecasting, the choice of the numbers of referring projects was investigated. It is concluded that selecting similar projects at $5{\~}6{\%}$ out of the whole database will produce a more precise forecasting. The new forecasting model, which suggests the predicted values based on previous projects, is more than just a forecasting methodology; it provides a bridge that enables current data collection techniques to be used within the context of the accumulated information. This will eventually help all the participants in the construction industry to build up the knowledge derived from invaluable experience.

• 한국건설관리학회:학술대회논문집
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• 한국건설관리학회 2004년도 제5회 정기학술발표대회 논문집
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• pp.117-124
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• 2004

Dynamic and fragmented characteristics ale two of the most significant factors that distinguish the construction industry from other industries. Previous forecasting techniques have failed to solve the problems derived from the above characteristics and do not provide considerable support. This paper deals with providing a more precise forecasting by applying Case-based Reasoning (CBR). The newly developed model in this study enables project managers to forecast monthly expenditures with less time and effort by retrieving and referring only projects of a similar nature, while filtering out irrelevant cases included in database. For the purpose of accurate forecasting. the choice of the numbers of referring projects was investigated. it is concluded that selecting similar projects at $5\~6\;\%$ out of the whole database will produce a more precise forecasting. The new forecasting model. which suggests the predicted values based on previous projects, is more than just a forecasting methodology it provides a bridge that enables current data collection techniques to be used within the context of the accumulated information. This will eventually help all the participants in the construction industry to build up the know ledge derived from invaluable experience.

• 산업경영시스템학회지
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• 제20권44호
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• pp.257-261
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• 1997

Patents often serve as leading indicators of technological change. This patenting activity reflected R&D (Research & Development) of new technology. The purpose of this study is to set up a forecasting model that anticipate the number of domestic patent applications and the number of patents granted relating to R&D inputs (R&D expenditure, R&D manpower) at the level of three industrial sectors in Korea : electrical-electronic, machinery, chemical etc. In this study, forecasting models were used trend extrapolation and a set of regressions. Both Theil's inequality coefficient and MAE(Mean Absolute Error) were utilized to test the precision of predicted value. The patent data and the R&D data were based on Indicators of Industrial Technology data throught 1980 to 1996. The major results obtained in this study are as follows (1) The regression model is more useful for forecasting the trends of the number of patent applications and patents granted than the trend extrapolation method. (2) The variance of Theil's inequality is smaller in patent applications than in patent granted.

• 농업과학연구
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• 제47권4호
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• pp.769-782
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• 2020

Interest in fruit and vegetables has increased due to changes in consumer consumption patterns, socioeconomic status, and family structure. This study determined the factors influencing the demand for fruit and vegetables (strawberries, paprika, tomatoes and cherry tomatoes) using a panel of Rural Development Administration household-level purchases from 2010 to 2018 and compared the ability to the prediction performance. An artificial neural network model was constructed, linking household characteristics with final food expenditure. Comparing the analysis results of the artificial neural network with the results of the panel model showed that the artificial neural network accurately predicted the pattern of the consumer panel data rather than the fixed effect model. In addition, the prediction for strawberries was found to be heavily affected by the number of families, retail places and income, while the prediction for paprika was largely affected by income, age and retail conditions. In the case of the prediction for tomatoes, they were greatly affected by age, income and place of purchase, and the prediction for cherry tomatoes was found to be affected by age, number of families and retail conditions. Therefore, a more accurate analysis of the consumer consumption pattern was possible through the artificial neural network model, which could be used as basic data for decision making.

• KDI Journal of Economic Policy
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• 제28권2호
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• pp.1-49
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• 2006

가구원의 연령 및 성별, 가구원 수 등 인구학적 특성이 가계의 소비구조에 영향을 미친다는 점을 고려할 때, 급격한 인구구조 변화는 우리나라 전체의 가계소비지출 구성에 지대한 영향을 미칠 것으로 짐작된다. 인구학적 특성의 변화가 소비지출에 미치는 영향을 분석하기 위하여 본 논문에서는 가계소비지출 통계자료에 Quadratic Almost Ideal Demand System(QUAIDS) 모형을 적용하여 소비지출 항목별 구성비 함수를 추정하였으며, 경제 성장률, 인구, 가구구성 등 추정에 사용된 설명변수들의 전망치를 이용하여 2005~2020년 기간 중 우리나라 가계소비지출의 구성 변화를 전망하였다. 전망 결과에 따르면, 우리나라의 가계소비지출은 향후에도 상당한 변화를 보일 것이며, 이 가운데 많은 부분은 인구학적 특성 변화에 기인하는 것으로 분석되었다. 소비구조의 변화는 산업구조의 변화를 야기한다. 따라서 자원의 효율적 배분을 위해서는 생산요소의 유연한 산업 간 이동을 촉진하기 위한 정책적 노력이 필요하다. 한편, 본 논문의 전망 결과는 기업의 투자계획 수립에 있어 유용한 정보로 사용될 수 있다.

• 보건행정학회지
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• 제28권4호
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• pp.378-391
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• 2018

Background: People who were born in different years, that is, different birth cohorts, grow in varying socio-historical and dynamic contexts, which result in differences in social dispositions and physical abilities. Methods: This study used age-period-cohort analysis method to establish explanatory models on healthcare expenditure in Korea reflecting birth cohort factor using intrinsic estimator. Based on these models, we tried to investigate the effects of ageing population on future healthcare expenditure through simulation by scenarios. Results: Coefficient of cohort effect was not as high as that of age effect, but greater than that of period effect. The cohort effect can be interpreted to show 'healthy ageing' phenomenon. Healthy ageing effect shows annual average decrease of -1.74% to 1.57% in healthcare expenditure. Controlling age, period, and birth cohort effects, pure demographic effect of population ageing due to increase in life expectancy shows annual average increase of 1.61%-1.80% in healthcare expenditure. Conclusion: First, since the influence of population factor itself on healthcare expenditure increase is not as big as expected. Second, 'healthy ageing effect' suggests that there is a need of paradigm shift to prevention centered-healthcare services. Third, forecasting of health expenditure needs to reflect social change factors by considering birth cohort effect.

• 응용통계연구
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• 제31권2호
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• pp.303-313
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• 2018

본 논문에서는 약품비 지출에 대한 예측을 수행하기 위하여 시계열 모형을 도입한다. 2012년 약가 일괄인하를 반영하기 위하여 구간별 모형을 토대로, 자기회귀오차모형과 전이함수모형을 고려하였다. 자기회귀오차모형에서는 예측의 편리성을 위하여 결정적 추세만을 고려하였으며, 전이함수모형에서는 주요한 외생변수와의 교차상관성을 이용하여 약품비 지출의 인과 메커니즘을 설명하였다. 각 모형에서 약가 일괄인하 이후 수준 변화가 유의하게 나타났으며, 전이함수모형에서는 의약품 사용자 수 및 노인환자 비중 시계열 변수가 유의하게 나타났다. 자기회귀오차모형은 약가 일괄인하로 의한 약품비 수준이동에 좌우되어 비교적 낮은 예측값이 도출되었으며, 전이함수모형은 약품비 지출에 영향을 미치는 외부 설명변수의 증가 추세가 적절히 반영되어 더 높은 예측값을 보였다. 설명변수를 포함하지 않을 경우, 약품비 수준이동만을 고려한 ARIMA 모형은 약품비 지출 추세를 가장 높이 예측하였다.