• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.731-733
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• 1996

In this paper, a new time-domain reduction method for unbalanced 3 phase power systems will be represented. The impulse response of the system is used to identify a discrete-time equivalent filter model. The model is formulated directly in the phase domain. Each phase has a self-mode equivalent model and two mutual-mode equivalent models. The equivalent model is determined by the transfer function identification technique based on the Prony analysis. The model is implemented in EMTDC and tested with an unbalanced 3 phase network. The result of test showed that the equivalent model is accurate.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.11a
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• pp.568-574
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• 2000

This paper presents the vibration characteristics of a continuous circular cylindrical shell multi-simply supported at arbitrary axial positions for searching design parameters. In this modal test the impulse test method is applied to the excitation of experimental model. Natural frequencies are obtained from the peak points of frequency response function(FRF) through frequency analyzer and vibration behaviors are investigated. FE analysis is performed with ANSYS 5.5 to improve the reliability of experimental results. Their results are compared with experimental results. The effect of dynamic characteristics is analyzed for the number of support point on the shell.

• Wind and Structures
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• v.28 no.3
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• pp.171-180
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• 2019

This paper presents a restart iterative approach for time-domain flutter analysis of long-span bridges using the commercial FE package ANSYS. This approach utilizes the recursive formats of impulse-response-function expressions for bridge's aeroelastic forces. Nonlinear dynamic equilibrium equations are iteratively solved by using the restart technique in ANSYS, which enable the equilibrium state of system to get back to last moment absolutely during iterations. The condition for the onset of flutter instability becomes that, at a certain wind velocity, the amplitude of vibration is invariant with time. A long-span suspension bridge was taken as a numerical example to verify the applicability and accuracy of the proposed method by comparing calculated results with wind tunnel tests. The proposed method enables the bridge designers and engineering practitioners to carry out time-domain flutter analysis of bridges in commercial FE package ANSYS.

• Korea Trade Review
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• v.46 no.5
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• pp.83-98
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• 2021

This study aims to examine the effects of international trade in intermediate input on the implications of international business cycle properties in Korea. To do this, I have extended standard one goods New Keynesian international business cycle model to incorporate the role of intermediate inputs. After constructing the DSGE model, I have analysed the impulse response function and varian decomposition results. The results show that the model could introduce a new channel, that is, "cost channel" like Eyquem and Kamber (2014). In other words, the model has changed the dynamics of aggregate inflation by the cost channel. When the trade in intermediate goods increase, which is measured by openness of foreign input, the volatility of output, consumption and inflation increase two or three times. However, the model itself fails to explain the full account of cycle behavior of historical data, but the results imply that the trade in intermediate input assumption can help to improve the forecasting ability of international business cycle models.

• Asian Journal of Business Environment
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• v.14 no.2
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• pp.19-30
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• 2024

Purpose: This research article investigates the intricate relationship between economic growth and employment in the Korean agri-food industry. Research design, data and methodology: Drawing on Okun's law, which proposes a negative correlation between economic growth and unemployment, the study explores the applicability of this law to different sectors. By focusing on the agri-food industry, the study examines the impact of economic growth on both full-time and temporary employment. Results: The findings highlight the industry's role as a buffer, absorbing workers from other sectors, particularly manufacturing. Moreover, the study reveals that temporary employment is more sensitive to economic growth fluctuations compared to full-time employment. Conclusions: The research emphasizes the importance of implementing employment programs that support transitioning workers in the agri-food industry, facilitating knowledge and skill transfer to ensure sustained employment. Furthermore, it recommends government and company support for temporary employment during buffering periods to ensure safe job transitions. This study provides valuable evidence to understand the nuanced relationship between economic growth and employment in the Korean agri-food industry.

• Journal of Information Processing Systems
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• v.20 no.1
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• pp.76-84
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• 2024

This study constructed a VAR model with cotton futures and spot price data from April 30, 2009 to November 16, 2022, for empirical analysis utilizing the Granger causality test to analyze the dynamic relationship between cotton futures and spot market prices in China. The impulse response function and variance decomposition analysis showed that the cotton spot prices at flowering have a causal relationship with each other; in terms of mutual influence and impact, futures prices are higher than spot prices. Finally, it proposed countermeasures and suggestions from the perspective of establishing a standardized cotton spot market, improving the laws and regulations of the cotton futures market and trading system, and optimizing the structure of investment subjects.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.3
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• pp.103-113
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• 2019

The effectiveness of monetary policy critically depends upon how well the transmission mechanism functions, so that the desired impact on output and inflation is achieved. The purpose of this paper is to study the transmission mechanism of monetary policy by analyzing the impact on inflation and output during multiple indicator regime (1998-99 to 2014) in an emerging economy-India. The Inflation Targeting Regime is also briefly outlined alongwith the impact on output and inflation. Using quarterly data for the period 1997 to 2017, the paper uses weighted average call money market rate as a proxy for the policy rate and evaluates the strength of the interest rate channel. We use a conventional Structural vector auto regression (SVAR) methodology to evaluate the efficacy and show the impluse response functions. Our results find that changes in the policy rate impact output growth steeply with a lag of about two quarters and the impact on inflation is maximized after three quarters. The study concludes that the monetary policy in India has a significant impact on output and inflation in the short-to-medium-run. After the policy shock, the fall in the output growth rate is of greater magnitude than the fall in inflation.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.2
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• pp.269-275
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• 2019

This study intended to examine the relationship between inflation and unemployment rate in Indonesia during 1987 to 2018 period. The study applied a quantitative method using Vector Error Correction Model (VECM) in order to comprehensively understand the causality between inflation and unemployment rates. The data were collected from various main sources including the World Bank, Central Bank of Indonesia, and Central Bureau of Statistics (BPS). The findings showed that inflation has a one-way relationship toward unemployment in Indonesia and it occurs at the third lag. Impulse Response Function (IRF), shows that the inflation rate are fluctuating in response to the shock of unemployment. The unemployment rate responses to shocks from inflation initially increased until it is eventually diminished. It shows that the shocks caused by the impact of inflation were only in the short term. Further, inflation in the three previous lags will have consequences for the unemployment rate in the year. Lastly, both in the long run and short run, unemployment did not affect inflation rates. These findings suggest that high inflation in Indonesia is determined the rising price of basic commodities and fuel. In addition, most companies in Indonesia applying capital intensive so that employment growth in Indonesia is small.

• Journal of Distribution Science
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• v.11 no.10
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• pp.63-72
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• 2013

Purpose - This study analyzes the relationship and dynamic interactions between stock price index, interest rate, price index, and housing price indices using Korean monthly data from 2000 to 2013, based on a VAR model. This study also examines Granger causal relationships among these variables in order to determine whether the time series of one is useful in forecasting another, or to infer certain types of causal dependency between stochastic variables. Research design, data, and methodology - We used Korean monthly data for all variables from 2000: M1 to 2013: M3. First, we checked the correlations among different variables. Second, we conducted the Augmented Dickey-Fuller (ADF) test and the co-integration test using the VAR model. Third, we employed Granger Causality tests to quantify the causal effect from time series observations. Fourth, we used the impulse response function and variance decomposition based on the VAR model to examine the dynamic relationships among the variables. Results - First, stock price Granger affects interest rate and all housing price indices. Price index Granger, in turn, affects the stock price and six metropolitan housing price indices. However, none of the Granger variables affect the price index. Therefore, it is the stock markets (and not the housing market) that affects the housing prices. Second, the impulse response tests show that maximum influence on stock price is its own, and though it is influenced a little by interest rate, price index affects it negatively. One standard deviation (S.D.) shock to stock price increases the housing price by 0.08 units after two months, whereas an impulse shock to the interest rate negatively impacts the housing price. Third, the variance decomposition results report that the shock to the stock price accounts for 96% of the variation in the stock price, and the shock to the price index accounts for 2.8% after two periods. In contrast, the shock to the interest rate accounts for 80% of the variation in the interest rate after ten periods; the shock to the stock price accounts for 19% of the variation; however, shock to the price index does not affect the interest rate. The housing price index in 10 periods is explained up to 96.7% by itself, 2.62% by stock price, 0.68% by price index, and 0.04% by interest rate. Therefore, the housing market is explained most by its own variation, whereas the interest rate has little impact on housing price. Conclusions - The results of the study elucidate the relationship and dynamic interactions among stock price index, interest rate, price index, and housing price indices using VAR model. This study could help form the basis for more appropriate economic policies in the future. As the housing market is very important in Korean economy, any changes in house price affect the other markets, thereby resulting in a shock to the entire economy. Therefore, the analysis on the dynamic relationships between the housing market and economic variables will help with the decision making regarding the housing market policy.

• ETRI Journal
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• v.34 no.4
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• pp.511-517
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• 2012

The best linear unbiased estimator (BLUE) is most suitable for practical application and can be determined with knowledge of only the first and second moments of the probability density function. Although the BLUE is an existing algorithm, it is still largely unexplored and has not yet been applied to channel estimation in amplify and forward (AF)-based wireless relay networks (WRNs). In this paper, a BLUE-based algorithm is proposed to estimate the overall channel impulse response between the source and destination of AF strategy-based WRNs. Theoretical mean square error (MSE) performance for the BLUE is derived to show the accuracy of the proposed channel estimation algorithm. In addition, the Cram$\acute{e}$r-Rao lower bound (CRLB) is derived to validate the MSE performance. The proposed BLUE channel estimation algorithm approaches the CRLB as the length of the training sequence and number of relays increases. Further, the BLUE performs better than the linear minimum MSE estimator due to the minimum variance characteristic exhibited by the BLUE, which happens to be a function of signal-to-noise ratio.