• The Journal of Asian Finance, Economics and Business
• /
• 제7권11호
• /
• pp.23-31
• /
• 2020

This paper investigates the impact of monetary policy independence shock on bond yield by allowing for heterogeneous coefficients in the model based on panel data for 19 developing countries using quarterly data from 1991 to 2016. First, we estimate the model using conventional panel VAR estimation with the assumption of homogeneous coefficients across countries. Second, by performing Chow and Roy-Zellner tests to check the homogeneity assumption, we find that the assumption does not hold in the model. Third, we apply a mean-group estimation for panel VAR as a solution for heterogeneity panel model. The results reveal that central bank independence is effective in reducing bond yield with the maximum at period 6 after the shock. Shock one standard deviation bond yield has a negative effect on consumption and investment. We determine that central bank independence has a contradictory effect on real activity; a negative effect on consumption but a positive influence on investment for the first two years after the shock. Additionally, we split our sample into three groups to make the subgroups pool. Our empirical result shows that monetary policy independence shock reduces bond yield. Meanwhile, the response of economic activity to bond yield varies for all three groups.

• 산업경영시스템학회지
• /
• 제32권3호
• /
• pp.99-109
• /
• 2009

Negative binomial yield model for semiconductor manufacturing consists of two parameters which are the average number of defects per die and the clustering parameter. Estimating the clustering parameter is quite complex because the parameter has not clear closed form. In this paper, a Bayesian approach using Markov Chain Monte Carlo is proposed to estimate the clustering parameter. To find an appropriate estimation method for the clustering parameter, two typical estimators, the method of moments estimator and the maximum likelihood estimator, and the proposed Bayesian estimator are compared with respect to the mean absolute deviation between the real yield and the estimated yield. Experimental results show that both the proposed Bayesian estimator and the maximum likelihood estimator have excellent performance and the choice of method depends on the purpose of use.

• 한국기후변화학회지
• /
• 제6권1호
• /
• pp.21-31
• /
• 2015

Various crop models have been extensively used for estimation of the crop yields. Compared to the other models, the EPIC model uses a unified approach to simulate more than 100 types of crops. It has been successfully applied in simulating crop yields for various combinations of weather conditions, soil properties, crops, and management schemes in many countries. The objective of this study was to estimate the rice and maize yield in South Korea using the EPIC model. The input datasets for the 30 types in the 11 categories were created for the EPIC model. The EPIC model simulated rice and maize yields. The performance of the EPIC model was evaluated with the goodness-of-fit measures including Root Mean Square Error (RMSE), Relative Error (RE), Nash-Sutcliffe Efficiency Coefficient (NSEC), Mean Absolute Error (MAE), and Pearson Correelation Coefficient (r). The rice yield showed to more high accuracy than maize yield on four type of method without NSEC. Theses results showed that the EPIC model better simulated rice yields than maize yields. The results suggest that the EPIC crop model can be useful to estimate crop yield in South Korea.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
• /
• pp.917-919
• /
• 2003

This paper demonstrates that RADARSAT ScanSAR data can be an important data source of radar remote sensing for monitoring crop systems and estimation of rice yield for large areas in tropic and sub-tropical regions. Experiments were carried out to show the effectiveness of RADARSAT ScanSAR data for rice yield estimation in whole province of Guangdong, South China. A methodology was developed to deal with a series of issues in extracting rice information from the ScanSAR data, such as topographic influences, levels of agro-management, irregular distribution of paddy fields and different rice cropping systems. A model was provided for rice yield estimation based on the relationship between the backscatter coefficient of multi-temporal SAR data and the biomass of rice.

• 한국농공학회논문집
• /
• 제46권5호
• /
• pp.89-98
• /
• 2004

The amount of rice yield reduction due to inundation should be estimated to analyse economic efficiency of the farmland drainage improvement projects because those projects are generally promoted to mitigate flood inundation damage to rice in Korea. Estimation of rice yield reduction will also provide information on the flood risk performance to farmers. This study presented the relationships between inundated durations and rice yield reduction rates for different rice growth stages from the observed data collected from 1966 to 2000 in Korea, and developed the rice yield reduction estimation model (RYREM). RYREM was applied to the test watershed for estimating the rice yield reduction rates and the amount of expected average annual rice yield reduction by the rainfalls with 48 hours duration, 10, 20, 50, 100, 200 years return periods.

• 한국지하수토양환경학회지:지하수토양환경
• /
• 제25권3호
• /
• pp.52-64
• /
• 2020

The universal soil loss equation (USLE), a model for estimating the potential soil loss, has been used not only in research areas but also in establishing national policies in South Korea. Despite its wide applicability, USLE cannot adequately address the effect of seasonal variances. To overcome this limit, the ArcGIS-based Sediment Assessment Tool for Effective Erosion (ArcSATEEC) has been developed as an alternative model. Although the field-scale (< 100 ㎡) application of this model produced reliable estimation results, it is still challenging to validate accuracy of the model estimation because it only estimates potential soil losses, not the actual sediment yield. Therefore, in this study, a method for estimating actual soil loss based on the ArcSATEEC model was suggested. The model was applied to eight watersheds in South Korea to estimate sediment yields. Correction factor was introduced for each watershed, and the estimated sediment yield was compared with that of the estimated yield by LOAD ESTimator (LOADEST). Sediment yield estimation for all watersheds exhibited reliable results, and the validity of the proposed correction factor was confirmed, suggesting the correction factor needs to be considered in estimating actual soil loss.

• 한국태양에너지학회 논문집
• /
• 제30권6호
• /
• pp.95-101
• /
• 2010

This paper presents performance estimation approach of grid-connected photovoltaic(PV) system to predict energy yield from irradiance to PV system using normalized yield model for changing meteorological conditions. The accuracy and validity of proposed performance estimation method is identified by compared measured with estimated yield using monitored data. These results will indicate that it is useful to estimate various loss factors causing the system performance obstruction and enhance the lifetime yield of PV system.

• 한국측량학회지
• /
• 제34권5호
• /
• pp.525-534
• /
• 2016

쌀은 오랜 기간 동안 남한 지역의 주식임과 동시에 농부들의 주 수입원이며, 농업 분야 관련 정책 수립을 위한 수학적인 쌀 생산량 추정 모델의 구축이 필요하다. 본 연구의 목적은 (1) 쌀 생산량 추정을 위한 회선신경망 모델의 구축과, (2) 최고의 성능을 보이는 회선신경망의 파라미터를 결정하는 것과, (3) 인공신경망 모델과의 비교를 통해 회선신경망의 성능을 평가하는 것이다. 각 모델의 입력데이터로는 2000~2013년도의 4~9월까지에 해당하는 기상자료와 MODIS 위성자료를 사용하였으며, 정확도 평가를 위해 교차 검증을 실시하였다. 회선신경망과 인공신경망은 쌀 생산 표본점을 대상으로 각각 36.10kg/10a, 48.61kg/10a와 시군구 지역을 대상으로 각각 31.30kg/10a, 39.31kg/10a의 RMSE를 보였다. 회선신경망 모델은 인공신경망 모델보다 우수한 성능을 보였으며, 본 연구를 통해 쌀 생산량 추정 분야에 대한 회선신경망 모델의 적용 가능성을 확인할 수 있었다.

• 대한원격탐사학회지
• /
• 제37권2호
• /
• pp.199-209
• /
• 2021

장기적인 시계열 수량 평균이 기술적인 발전 요인에 의해 증가하는 추세를 제거하여, 기존 MODIS NDVI 및 기상자료를 이용한 우리나라 벼 수량 추정 모형을 개선하고자 하였다. 이를 위해 2002년부터 2019년 까지의 NDVI (MYD13Q1)와 기상자료를 사용하여 다중 선형 회귀 분석을 수행하였다. 벼 수량 추세를 분석하고 이를 제거하여 모형을 보완하였다. 개선된 모형을 이용하여 추정한 벼 수량과 수량 통계 값 간의 상관 분석을 통해 추세 제거에 따른 정확도를 평가하였다. 그 결과, 추세가 제거된 벼 수량 추정 모형에 의해 예측된 수량이 통계 수량의 연간 변동 특성을 잘 반영하고 있는 것으로 나타났다. 추세 제거 전의 모형과 비교하여 통계 수량과의 상관계수와 결정계수도 높게 나타났다. 따라서 추세 제거 방법이 벼 수량 추정 모형을 효과적으로 보정하는 방법임을 확인하였다.

• 전자공학회논문지A
• /
• 제30A권2호
• /
• pp.46-52
• /
• 1993

The estimation of yield for semiconductor devices requires not only establishment of critical area but also a new parameter of process defect density that contains inspection mean defect density related cleanness of manufacure process line, minimum feature size and the total number of mask process. We estimate the repaired yield of memory devide, leads the semiconductor technique, repaired by redundancy scheme in relation with defect density distribution function, and we confirm the repaired yield for different devices as this model. This shows the possibility of the yield estimation as statistical analysis for the condition of device related cleanness of manufacture process line, design and manufacture process.