• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.1
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• pp.165-174
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• 2019

As a nonstationarity is observed in hydrological data, various studies on nonstationary frequency analysis for hydraulic structure design have been actively conducted. Although the inherent diversity in the atmosphere-ocean system is known to be related to the nonstationary phenomena, a nonstationary frequency analysis is generally performed based on the linear trend. In this study, a nonstationary frequency analysis was performed using climate indices as covariates to consider the climate variability and the long-term trend of the extreme rainfall. For 11 weather stations where the trend was detected, the long-term trend within the annual maximum rainfall data was extracted using the ensemble empirical mode decomposition. Then the correlation between the extracted data and various climate indices was analyzed. As a result, autumn-averaged AMM, autumn-averaged AMO, and summer-averaged NINO4 in the previous year significantly influenced the long-term trend of the annual maximum rainfall data at almost all stations. The selected seasonal climate indices were applied to the generalized extreme value (GEV) model and the best model was selected using the AIC. Using the model diagnosis for the selected model and the nonstationary GEV model with the linear trend, we identified that the selected model could compensate the underestimation of the rainfall quantiles.

• International Area Studies Review
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• v.21 no.4
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• pp.159-172
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• 2017

In a typical trend-cycle decomposition of GDP, the trend component is usually assumed to follow a random walk process. This paper considers an ARIMA trend and assesses the validity of the ARIMA trend model. I construct univariate and bivariate unobserved-components(UC) models, allowing the ARIMA trend. Estimation results using U.S. data are favorable to the ARIMA trend models. I, also, compare the forecasting performance of the UC models. Dynamic pseudo-out-of-sample forecasting exercises are implemented with recursive estimations. I find that the bivariate model outperforms the univariate model, the smoothed estimates of trend and cycle components deliver smaller forecasting errors compared to the filtered estimates, and, most importantly, allowing for the ARIMA trend can lead to statistically significant gains in forecast accuracy, providing support for the ARIMA trend model. It is worthy of notice that trend shocks play the main source of the output fluctuation if the ARIMA trend is allowed in the UC model.

• Environmental and Resource Economics Review
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• v.19 no.2
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• pp.215-242
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• 2010

This study constructs a bayesian neoclassical DSGE model that applies oil usage. The model includes technology shocks, oil price shocks, and shocks to energy policies as exogenous driving forces. First, this study aims to analyze the roles of these exogenous shocks in the Korean business cycle. Second, this study examines the effects of long-term changes in the energy consumption structure, including the reduction in oil use as a share of energy consumption and improvement in oil efficiency. In the case of oil price shocks, results show that these shocks exert recessionary pressure on the economy in line with those obtained in the previous literature. On the other hand, shocks to energy policies, which reduce oil consumption per capital, result in opposite consequences to oil price shocks, decreasing oil consumption. Also, counterfactual exercises show that long-term changes in the energy consumption structure would mitigate the contractionary effects of oil price shocks.

• 한국데이터정보과학회:학술대회논문집
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• 2003.10a
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• pp.107-113
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• 2003

최근 활발히 행하여지고 있는 금융 CRM(customer relationship management)의 주요 목적은 고객의 이해도 증진을 통하여 은행의 수익성을 높이는데 있으며 또한 그 과정에서 높은 수익과 낮은 수익을 주는 고객을 여러 가지 유형으로 나누어 관리에 효율성을 도모한다. 일반적으로 고객 세분화의 중요변수로 고객수익성을 고려하고 이러한 고객 세분화 결과에 의해 마케팅 시사점을 도출하게 된다. 본 연구에서는 고객 세분화 그룹에 따른 수익성 변동과정을 모형화하여 보다 효율적인 고객관계 관리를 가능하게 하는데 있다. 수익성 변동의 모형화 과정은 수익금액에 따라 고객을 몇 개의 범주로 분류하여 여러 기간에 걸쳐 나타내는 고객별 범주의 변화 추이를 전이행렬(transition matrix)로 나타내고 마코프 모형을 이용한 전이 확률의 추정을 통하여 다음 시점에서의 각 범주별 고객의 수를 예측 가능함을 보인다.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.183-183
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• 2018

최근 국지성 호우와 홍수, 그리고 극심한 가뭄과 같은 기후변화로 인한 극치수문현상이 빈번하게 관측되고 있다. 이는 과거와는 다른 양상의 강우사상으로 광화문(2010), 강남역(2010), 청계천(2010), 청주(2017), 부산(2017) 등 주요 도심지역에 내수침수로 인한 막대한 인명, 재산 피해를 발생시켰으며, 피해의 빈도와 강도가 증가되고 있는 추세이다. 특히 기후변화에 따른 강우강도의 증가는 설계홍수량의 변화를 초래하며, 그로 인해 홍수 위험도 증가와 치수안전도 감소 등 수공구조물의 설계기준에 불확실성을 증가시키는 원인이 되고 있다. 최근 국내에서도 기후변화에 따른 수공시설물 설계빈도 상향에 대한 필요성이 대두되고 있으나 기후변화의 불확실성 및 기후시나리오의 한계로 인해 정량적 분석결과가 제시되지 않아 정책 수립에 반영하기 현실적으로 어려운 상황이다. 본 연구에서는 기후변화에 따른 홍수특성에 대한 도시유역의 영향을 평가하기 위하여 서울 효자배수분구를 대상유역으로 선정하고, 과거관측자료 기준 S0 대비 상세화 기법(Downscaling) 및 편의보정(Bias Correlation)으로 생성된 RCP 4.5 기후시나리오 HadGEM3-RA(RCM)모델을 통해 생산된 S1, S2, S3 기간의 확률강우량의 변화를 평가하였다. 이때 확률분포형은 Gumbel, 매개변수 추정은 최우도법(ML)을 사용하였고, 도시유출모형을 이용하여 최대첨두홍수량 및 침수면적 산정하고 기후변화 기간별 변동성을 분석하였다. 평가 결과 대부분의 도시배수시설물의 설계빈도인 10년빈도를 3사분위값을 기준으로 할 때 50년과 70년 이상의 미래를 가정할 경우 각각 약 10%, 20%의 확률 홍수량이 증가가 예상되었다. 이러한 결과 현재 구축되어 있는 배수시스템의 설계빈도를 크게 상회하는 값으로 도시배수시스템에 많은 어려움을 줄 것으로 예상되며, 정량적 평가 결과가 기후변화 적응 대책 신규 시설물 설계시 참고할 수 있는 기초자료로 활용될 것으로 판단된다.

• Environmental and Resource Economics Review
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• v.27 no.3
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• pp.495-520
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• 2018

Because of structural changes in the international oil market and the economy, it is widely recognized that the impact of oil shocks on the economy has weaken since the mid-1980s. This study tries to examine the validity of the recent perception about the relationship between oils shocks and the economy, estimating the time-varying effects of oil shocks on the Korean economy. The results show that the dynamic effects of oil shocks normalized to a one standard deviation has been relatively constant, in contrast to the recent perception and a number of existing studies. In addition, because the shape of impulse response functions at each point in time spanning from 1984:II to 2017:IV has not been changed significantly, it seems that the propagation mechanism of oil shocks also has not been substantially altered. These findings indicate that even though structural changes of the economy, such as the reduction in the share of oil consumption and the spread of high-efficiency energy technologies, have been rapidly progressed, it is not still enough to offset the negative effects of oil shocks. Rather, it seems that the recent perception about the shrinking effects of oil shocks is mainly due to the assumptions that do not reflect changes in the size of oil shocks. In particular, this problem appears more pronounced in the case of the typical a one standard deviation increase oil shock under homoskedasticity assumption, which is widely adopted in the most VAR analyses. Therefore, in estimating the effects of oil shocks on the economy, it is important to specify the correct model and normalization method, to reflect changes in the size of oil shocks.

• Journal of Korean Society of Transportation
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• v.23 no.3 s.81
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• pp.95-108
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• 2005

The purpose of this study is to develop the ITS evaluation model using the Probabilistic Risk Analysis (PRA) methodology and to demonstrate the goodness-of-fit of the large ITS projects through the comparative analysis between DEA and PRA model. The results of this study are summarized below. First, the evaluation mode] using PRA with Monte-Carlo Simulation(MCS) and Latin-Hypercube Sampling(LHS) is developed and applied to one of ITS projects initiated by local government. The risk factors are categorized with cost, benefit and social-economic factors. Then, PDF(Probability Density Function) parameters of these factors are estimated. The log-normal distribution, beta distribution and triangular distribution are well fitted with the market and delivered price. The triangular and uniform distributions are valid in benefit data from the simulation analysis based on the several deployment scenarios. Second, the decision making rules for the risk analysis of projects for cost and economic feasibility study are suggested. The developed PRA model is applied for the Daejeon metropolitan ITS model deployment project to validate the model. The results of cost analysis shows that Deterministic Project Cost(DPC), Deterministic Total Project Cost(DTPC) is the biased percentile values of CDF produced by PRA model and this project need Contingency Budget(CB) because these values are turned out to be less than Target Value(TV;85% value), Also, this project has high risk of DTPC and DPC because the coefficient of variation(C.V) of DTPC and DPC are 4 and 15 which are less than that of DTPC(19-28) and DPC(22-107) in construction and transportation projects. The results of economic analysis shows that total system and subsystem of this project is in type II, which means the project is economically feasible with high risk. Third, the goodness-of-fit of PRA model is verified by comparing the differences of the results between PRA and DEA model. The difference of evaluation indices is up to 68% in maximum. Because of this, the deployment priority of ITS subsystems are changed in each mode1. In results. ITS evaluation model using PRA considering the project risk with the probability distribution is superior to DEA. It makes proper decision making and the risk factors estimated by PRA model can be controlled by risk management program suggested in this paper. Further research not only to build the database of deployment data but also to develop the methodologies estimating the ITS effects with PRA model is needed to broaden the usage of PRA model for the evaluation of ITS projects.

• KDI Journal of Economic Policy
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• v.36 no.3
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• pp.1-23
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• 2014

This paper has studied the monetary policy in Korea with a time varying VAR model using four key macroeconomic variables. First, inclusion of the exchange rate was a crucial factor in evaluating Korean monetary policy since the monetary policy demonstrated sensitivity to exchange rate movements during the crisis periods of both the Asian financial crisis of 1997 and the global financial crisis of 2008. Second, a specification of the stochastic volatilities in TVP-VAR model is important in explaining excessive movements of all variables in the sample. The overall moderation of variables in 2000s was more or less due to a reduction of the stochastic volatilities but also somewhat due to the macroeconomic fundamental structures captured by impulse response functons. Third, the degree of the monetary policy effectiveness of inflation was mitigated in recent periods but with increased persistence. Lastly, the monetary policy stance towards inflation stabilization has advanced ever since the inflation targeting scheme was adopted. However, there still seems to be a room for improvement in this aspect since the degree of the monetary policy stance towards inflation stabilization was relatively weaker than to output stabilization.

• Economic Analysis
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• v.25 no.3
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• pp.70-99
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• 2019

Using a stochastic volatility-in-mean VAR model consisting of the KOSPI index, the foreign exchange rate, the government bond rate, and the credit spread, this study investigates the effects of financial market uncertainty on financial markets. We find that higher uncertainty has recessionary effects on financial markets. The effects are especially stronger in equity markets and in won-dollar exchange markets. We also find that the effects of uncertainty become stronger during times of financial market stress compared to normal times. Finally, the results imply that financial market uncertainty may potentially affect the real sector, too.

• Water for future
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• v.28 no.2
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• pp.103-114
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• 1995

A stochastic model "STO-RIV" for the prediction of water quality variation in a river system has been developed. Extended Streeter-Phelps equation and Monte Carlo simulation are used in the model. The model is applied to the reach of Waegwan to Mulkeum in the Nakdong River to compute the probability distribution of BOD and DO concentration at Mulkeum site. As the strategies to attain the goal of the water quality, some alternatives considering the treatment effect of the Keumho river are discussed using the stochastic model. Application of stochastic analysis to water quality management is strongly recommended in this country.s country.