Purpose - This study examines the impact of oil price volatility on economic activities in Korea. The new millennium has seen a deregulation in the crude oil market, which invited immense capital inflow into Korea. It has also raised oil price levels and volatility. Drawing on the recent theoretical literature that emphasizes the role of volatility, this paper attends to the asymmetric changes in economic growth in response to the oil price movement. This study further examines several key macroeconomic variables, such as interest rate, production, and inflation. We come to the conclusion that oil price volatility can, in some part, explain the structural changes. Research design, data, and methodology - We use two methodological frameworks in this study. First, in regards to the oil price uncertainty, we use an Exponential-GARCH (Exponential Generalized Autoregressive Conditional Heteroskedasticity: EGARCH) model estimate to elucidate the asymmetric effect of oil price shock on the conditional oil price volatility. Second, along with the estimation of the conditional volatility by the EGARCH model, we use the estimates in a VECM (Vector Error Correction Model). The study thus examines the dynamic impacts of oil price volatility on industrial production, price levels, and monetary policy responses. We also approximate the monetary policy function by the yield of monetary stabilization bond. The data collected for the study ranges from 1990: M1 to 2013: M7. In the VECM analysis section, the time span is split into two sub-periods; one from 1990 to 1999, and another from 2000 to 2013, due to the U.S. CFTC (Commodity Futures Trading Commission) deregulation on the crude oil futures that became effective in 2000. This paper intends to probe the relationship between oil price uncertainty and macroeconomic variables since the structural change in the oil market became effective. Results and Conclusions - The dynamic impulse response functions obtained from the VECM show a prolonged dampening effect of oil price volatility shock on the industrial production across all sub-periods. We also find that inflation measured by CPI rises by one standard deviation shock in response to oil price uncertainty, and lasts for the ensuing period. In addition, the impulse response functions allude that South Korea practices an expansionary monetary policy in response to oil price shocks, which stems from oil price uncertainty. Moreover, a comparison of the results of the dynamic impulse response functions from the two sub-periods suggests that the dynamic relationships have strengthened since 2000. Specifically, the results are most drastic in terms of industrial production; the impact of oil price volatility shocks has more than doubled from the year 2000 onwards. These results again indicate that the relationships between crude oil price uncertainty and Korean macroeconomic activities have been strengthened since the year2000, which resulted in a structural change in the crude oil market due to the deregulation of the crude oil futures.
Noh, Hui Seong;Kang, Na Rae;Kim, Byung Sik;Kim, Hung Soo
Journal of Wetlands Research
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v.14
no.2
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pp.243-254
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2012
Recently, the use of radar rainfall data that can help tracking of the development and movement of rainfall's spatial distribution is drawing much attention in hydrology. The reliability of existing radar rainfall compared to gauge rainfall data on the ground has not yet been confirmed and so we have difficulties to apply the radar rainfall in hydrology. The radar rainfall for the applications in hydrology are adjusted merging method derived from gage. This study uses the Mean-Field Bias (MFB) and Statistical Objective Analysis (SOA) as correction methods to create adjusted grid-based radar rainfall data which can represent the temporal and spatial distribution of rainfall. This study used a storm event occurred in August 2010 for the adjustment of radar rainfall. In addition, the grid-based distributed rainfall-runoff model (Vflo), which enables more detailed examinations of spatial flux changes in the basin rather than the lumped hydrological models, has been applied to Gamcheon river basin which is a tributary of Nakdong River located in south-eastern part of the Korean peninsular and the basin area is $1005km^2$. The simulated runoff was compared with the observed runoff in an attempt to evaluate the usability of radar rainfall data and the reliability of the correction methods. The error range of peak discharge using each correction method was within 20 percent and the efficiency of the model was between 60 and 80 percent. In particular, the SOA method showed better results than MFB method. Therefore, the SOA method could be used for the adjustment of grid-based radar rainfall and the adjusted radar rainfall can be used as an input data of rainfall-runoff models.
The influences of the space allocation of design rainfall and partition of the subbasin on the characteristics of urban storm runoff was investigated for the 6 drainage basins by applying SWMM model. It show the deviation of -54.68∼18.77% in the peak discharge when we applied the composed JUFF quantiles to the two zones which are divided by upper and lower region of the basin. Then it is compared with the value for the case of using uniform rainfall distribution all over the drainage. Therefore, it would be helpful to decrease the flood risk when we adopt the space distribution of the design rainfall. The effects of the partitioning the drainage on the computing result shows various responses because of the surface characteristics of the each basin such as slope, imperviousness ratio, buy we can get closer result to the measured value as we make the subbasin detailed. If we use the concept of the skewness and area ratio when we determine the width of subbasin, we can improve the computed result even with fewer number of subbasins. We expect reasonable results which close into the measured results in the range of relative error, 25%, when we divide the basin into more than 3 subbasins and the total urban drainage area is less than 10$\textrm{km}^2$.
Kim, Yeonsu;Kim, Jeongyup;An, Hyunuk;Jung, Kwansue
Journal of Korea Water Resources Association
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v.48
no.10
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pp.807-816
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2015
In general, the water stage-discharge relationship curve is established based on the assumptions of linearity and homoscedasticity. However, the relationship between the water stage and discharge is affected from geomorphological factors, which violates the basic assumptions of the water stage-discharge relationship curve. In order to reduce the error due to the violations, the curve is divided into several sections based on the manager's judgement considering change of cross-sectional shape. In this research, the objective-splitting criteria of the curve is proposed based on the measured data without the subjective decision. First, it is assumed that the coefficient of variation follows the normal distribution. Then, if the newly calculated coefficient of variation is outside of the 95% confidential interval, the curve is divided. Namely, the groups is divided by the characteristics of the coefficient of variation and the reasonable criteria is provided for establishing a multi-segmented rating curve. To validate the proposed method, it was applied to the data generated by three artificial power functions. In addition, to confirm the applicability of the proposed method, it is applied to the water stage and discharge data of the Muju water stage gauging station and Sangegyo water stage gauging station. As a result, it is found that the automatically divided rating curve improves the accuracy and extrapolation accuracy of the rating curve. Finally, through the residual analysis using Shapiro-Wilk normality test, it is confirmed that the residual of water stage-discharge relationship curve tends to follow the normal distribution.
Journal of The Korean Society of Agricultural Engineers
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v.57
no.6
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pp.173-183
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2015
The aim of this study was to develop a soil moisture simulation model equipped with meteorological data enhanced by WRF (Weather Research and Forecast) model, and this soil moisture model was applied for quantifying soil moisture content and irrigation requirement. The WRF model can provide grid based meteorological data at various resolutions. For applicability assessment, comparative analyses were conducted using WRF data and weather data obtained from weather station located close to test bed. Water balance of each upland grid was assessed for soils represented with four layers. The soil moisture contents simulated using the soil moisture model were compared with observed data to evaluate the capacity of the model qualitatively and quantitatively with performance statistics such as correlation coefficient (R), coefficient of determination (R2) and root mean squared error (RMSE). As a result, R is 0.76, $R^2$ is 0.58 and RMSE 5.45 mm in soil layer 1 and R 0.61, $R^2$ 0.37 and RMSE 6.73 mm in soil layer 2 and R 0.52, $R^2$ 0.27 and RMSE 8.64 mm in soil layer 3 and R 0.68, $R^2$ 0.45 and RMSE 5.29 mm in soil layer 4. The estimated soil moisture contents and irrigation requirements of each soil layer showed spatiotemporally varied distributions depending on weather and soil texture data incorporated. The estimated soil moisture contents using weather station data showed uniform distribution about all grids. However the estimated soil moisture contents from WRF data showed spatially varied distribution. Also, the estimated irrigation requirements applied WRF data showed spatial variabilities reflecting regional differences of weather conditions.
Moon, Kyung Hwan;Son, In Chang;Seo, Hyeong Ho;Choi, Kyung San
Korean Journal of Agricultural and Forest Meteorology
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v.14
no.4
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pp.155-160
/
2012
This study was conducted to develop a practical method for estimating the extremes of minimum air temperature with given return-period based on the frequency distribution of daily minimum air temperature in January. Daily temperature data were collected from 61 meteorological observatories country-wide from 1961 to 2010. Most of daily minimum temperature in January could be represented by a normal-distribution, so it is possible to predict stochastically the lowest temperature by the mean and standard deviation. We developed a quadratic function to estimate standard deviation in terms of daily minimum temperature in January. Also, we introduced a coefficient which can be used to predict an extreme of minimum temperature with mean and standard deviation, and is dependent on return-periods. Using this method, we were able to reproduce the past 30-year extremes with an error of 1.1 on average and 5.3 in the worst case.
The source of a business competition is man and the core of a business success depends on people's ability, efforts and cooperation. Therefore, modern managers are making varied efforts to perform the ethical management for the organization immersion and job satisfaction of the employees. The managers of the financial agencies including the enterprises competing in the global market, face numerous ethical issues and problems. Considering the reality that financial institutions are actively asked to perform the responsibility and duties sincerely, the tasks how the head of financial agency will accept the social study of the level of ethics and change the level of recognition, and how he will settle it as the natural feature in the institution, become an important management target. In addition, it is necessary to figure out how the ethical management of the head of the financial agency will affect the organizational immersion of the employees. Based on the objective of this study, we attempted to confirm how the ethical management will of the head of the financial institution would affect the organizational immersion, the employees' mental result variables. Through this study, it became necessary for the directors of the financial institutions to search for the methods to improve the system of management and enhance the observance will of the business ethics so that they may not cause the disposition of the violation of the business ethics owing to the enforcement to achieve the target of the results of the business or the error recognition of the norm. Further, the heads of banks will have to set a management policy focused on the democratic management and the ethical justice based on the participating methods to induce the cooperative commitment of the stock company employees not to be shifted from the globalization and the competitive society.
Journal of the Korea institute for structural maintenance and inspection
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v.18
no.6
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pp.147-154
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2014
The cable damages of the bridge structures induce very important impact on the structural safety, which implies the close monitoring of the cable damage is required to secure sustained safety of the bridges. Most usual available maintenance techniques are based on the monitoring the change of the natural frequency of the structures by damages. However, existing method are based on vibration method to calculate lateral vibration and system identification can calculate the axial stiffness using sensitivity equation by trial error method. But the frequency study by the longitudinal movement need because of the sag effect in system identification. This study proposes a new method to investigate the damage magnitudes and status. The method improves the accuracies in the magnitudes and status of damages by adopting the natural frequency of longitudinal movement. The study results have been validated by comparing them with the approximate solution of FEM. Thus, the relationship of cable damage and frequency appear with relation that the severe damage has the little frequency. If we know the real frequency we can estimate the cable damage severity using this relationship. This method can be possible the efficient management of the cable damage.
Pattern recognition is the study of how machines can observe the environment, learn to distinguish patterns of interest from their background, and make sound and reasonable decisions about the categories of the patterns. Color image consists of various color patterns. And most pattern recognition methods use the information of color which has been trained and extract the feature of the color. This thesis extracts adaptively specific color feature from images with several limited colors. Because the number of the color patterns is limited, the distribution of the color in the image is similar. But, when there are some noises and distortions in the image, its distribution can be various. Therefore we cannot extract specific color regions in the standard image that is well expressed in special color patterns to extract, and special color regions of the image to test. We suggest new method to reduce the error of recognition by extracting the specific color feature adaptively for images with the low distortion, and six test images with some degree of noises and distortion. We consequently found that proposed method shouws more accurate results than those of statistical pattern recognition.
An approximation of speed of sound in the measurement plane is essential for the inverse estimation of temperature. To this end, an inverse problem relating the measured retarded time data in between set of sensors and actuators array located on the wall is formulated. The involved transfer matrix and its coefficient vectors approximate speed of sound of the measurement plane by using the radial basis function with finite number of interpolation points deployed inside the target field. Then, the temperature field can be reconstructed by using spatial interpolation technique, which can achieve high spatial resolution with proper number of interpolation points. A large number of retarded time data of acoustic paths in between sensors and arrays are needed to obtain accurate reconstruction result. However, the shortage of interpolation points due to practical limitations can cause the decrease of spatial resolution and deterioration of the reconstruction result. In this works, a regeneration for obtaining the additional retarded time data for an arbitrary acoustic path is suggested to overcome the shortage of interpolation points. By applying the regeneration technique, many interpolation points can be deployed inside the field by increasing the number of retarded time data. As a simulation example, two rectangular duct sections having arbitrary temperature distribution are reconstructed by two different data set: measured data only, combination of measured and regenerated data. The result shows a decrease in reconstruction error by 15 % by combining the original and regenerated retarded time data.
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