• The Journal of Fisheries Business Administration
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• v.45 no.2
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• pp.29-38
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• 2014

This study is to analyse the timing of the structural change of price volatility and the asymmetry of price volatility during the period before and after the timing of the structural change of price volatility using Jeju Farming Olive Flounder's production area market price data from January 1, 2007 to June 30, 2013. The analysis methods of Quandt-Andrews break point test and Threshold GARCH model are employed. The empirical results of this study are summarized as follows: First, the result of Quandt-Andrews break point test shows that a single structural change in price volatility occurred on May 4, 2010 over the sample period. Second, during the period before structural change, daily price change rate has averagely positive value which means price increase, but during the period after structural change daily price change rate has averagely negative value which means price decrease. Also, daily volatility of price change rate during the period before structural change is higher than during the period after structural change. This indicates that price volatility decreases after structural change. Third, the estimation results of Threshold GARCH Model show that the volatility response against price increase is larger during the period after structural change than during the period before structural change. Also the result shows the volatility response against price decrease is larger during the period after structural change than during the period before structural change. And, irrespective of the timing of structural change, price increase has an larger effect on volatility than price decrease. This means volatility is asymmetric at price increase.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.188-195
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• 2022

Although issuing change orders is a common practice in the construction phase of any project, non-structural utility subcontractors are struggling and seek to find a way to reduce change orders. Therefore, this paper presents the analysis results on change orders to cultivate possible suggestions and solutions on how to reduce or minimize change orders in mechanical, electrical, and plumbing (MEP) works. Change orders in non-structural utility works are analyzed based on six categories such as rerouting and change of location, changes in weight, rejected design by Office of Statewide Health Planning and Development, District Structural Engineer, or the Structural Engineer of Record, unforeseen conditions, changed equipment, and owner-initiated change. The analysis findings showed that rerouting and changing location is the most significant cause, followed by unforeseen conditions. The results not only contribute to the existing body of knowledge on change order research area, but also help MEP contractors reduce the time and cost of change orders.

• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.1197-1211
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• 2011

The actual power performance of historical structural change tests are compared under various alternatives. The tests of interest are F, CUSUM, MOSUM, Moving Estimates and empirical distribution function tests with both recursive and ordinary least-squares residuals. Our comparison of the structural tests involves limiting distributions under the hypothesis, the ability to detect the alternative hypotheses under one or double structural change, and smooth change in parameters. Even though no version is uniformly superior to the other, the knowledge about the properties of those tests and connections between these tests can be used in practical structural change tests and in further research on other change tests.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.1
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• pp.13-24
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• 2022

The main goal of this study is to look at how South Korea can catch up to the rest of the world through policy-driven structural change and manufacturing revolutions. To achieve the objective, this study used annual data on real exports and real GDP from the World Development Indicator WDI of South Korea for the period 1960 to 2019. The study's goal is to use econometrics to detect this policy-driven structural change trend. Multiple nonlinear Granger causality test was used to accomplish this. The findings revealed structural breaks and nonlinearities in the dynamic link between South Korea's real GDP and real exports. Furthermore, results also show evidence of multiple structural breaks in South Korean data. South Korea's economic catch-up was the result of a constant reevaluation of industrial policies, readjustment, and structural change to constantly explore and utilize comparative advantage, realizing economies of scale at the global level, and reallocating and redistribution of resources towards productive sectors with high value-added output, according to econometric analysis. If South Korea would have not done this structural change this miracle to escape the middle-income trap would not have been possible. These findings support the descriptive evidence of structural change in favor of manufacturing revolutions and value addition industry development in South Korea.

• Journal of the Korean Data and Information Science Society
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• v.14 no.3
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• pp.641-651
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• 2003

This study suggests the hybrid models for interest rate forecasting using structural changes (or change points). The basic concept of this proposed model is to obtain significant intervals caused by change points, to identify them as the change-point groups, and to reflect them in interest rate forecasting. The model is composed of three phases. The first phase is to detect successive structural changes in the U. S. Treasury bill rate dataset. The second phase is to forecast the change-point groups with data mining classifiers. The final phase is to forecast interest rates with backpropagation neural networks (BPN). Based on this structure, we propose three hybrid models in terms of data mining classifier: (1) multivariate discriminant analysis (MDA)-supported model, (2) case-based reasoning (CBR)-supported model, and (3) BPN-supported model. Subsequently, we compare these models with a neural network model alone and, in addition, determine which of three classifiers (MDA, CBR and BPN) can perform better. For interest rate forecasting, this study then examines the prediction ability of hybrid models to reflect the structural change.

• Anayses & Alternatives
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• v.6 no.1
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• pp.195-222
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• 2022

From the economic development perspective, economic growth should accompany structural improvement in order to meet complex demands from a society. In the context of development economics, economic growth is critically dependent on successful structural advancement. The issue of structural change is also important for advanced economies as the landscape of modern industry is changing fast. Many advanced countries of slow growth are experiencing dawdling changes in industry structure. However, there is no definitive answer to the question of whether there is a causal relationship between structural change and growth. This study empirically assesses the relationship between structural change or 'speed' thereof and economic growth in developed countries of OECD. Rather than looking into the causes of structural changes, this study simply measures structural changes in OECD economies and examines if structural change is really contributing to growth. The reason why this study focuses on advanced countries of OECD is rather obvious; technological innovation and emergence of new industries pressure these countries to restructure their economies to address these new challenges though they are at stages well beyond conventional industrialization. And structural rigidity can always limit growth even in advanced countries. The main results of this study can be summarized as a positive relationship between 'change and growth'. 'Change' in this study refers to changes in the industrial structure based on value-added and was analyzed to have a close positive relationship with economic growth. This result is consistent with arguments of early development economists emphasizing structural upgrade as an indispensable process for growth and development. The result of this study potentially confirms that the main argument of development economics is valid also for advanced economies. One of our results suggests that business/professional services and social services should be main targets for restructuring for advanced economies. The rational may be that rapid convergence of manufacturing and services is a key for structural advancement in the era of new technologies. Obviously, as manufacturing technology and production are standardized, it is difficult to secure international competitiveness through traditional manufacturing alone and the role of R&D, design, logistics, and marketing is becoming more important.

• Ocean and Polar Research
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• v.37 no.4
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• pp.357-368
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• 2015

This study analyzed structural changes and asymmetry of price volatility during the period before and after a point of structural change in price volatility, using the Korean fresh common squid daily retail price data from January 1, 2004 to September 30, 2015. This study utilized the following analytical methods: the unit-root test was applied to ensure the stability of the data, the Quandt-Andrews breakpoint test was applied to find the point of structural change, and the Glosten-Jagannathan-Runkle GARCH and EGARCH models were applied to investigate the asymmetry of price volatility. The empirical results of this study are as follows. First, ADF, PP, KPSS and Zivot-Andrews tests showed that the daily retail price change rate of the Korean fresh common squid differentiated by logarithm was stable. Secondly, the ARIMA (2,1,2) model was selected by information criteria such as AIC, SC, and HQ. Thirdly, the Quandt-Andrews breakpoint test found that a single structural change in price volatility occurred on June 11, 2009. Fourthly, the Glosten-Jagannathan-Runkle GARCH and EGARCH models showed that estimates of coefficients within the models were statistically significant before and after structural change and also that asymmetry as a leverage effect existed before and after structural change.

• Structural Engineering and Mechanics
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• v.59 no.6
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• pp.1095-1120
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• 2016

This paper investigates the change of structural characteristics of steel cable-stayed bridges after cable failure. Cables, considered as the intermediate supports of cable-stayed bridges, can break or fail for several reasons, such as fire, direct vehicle clash accident, extreme weather conditions, and fatigue of cable or anchorage. Also, the replacement of cables can cause temporary disconnection. Because of the structural characteristics with various geometric nonlinearities of cable-stayed bridges, cable failure may cause significant change to the structural state and ultimate behavior. Until now, the characteristics of structural behavior after cable failure have rarely been studied. In this study, rational cable failure analysis is suggested to trace the new equilibrium with structural configuration after the cable failure. Also, the sequence of ultimate analysis for the structure that suffers cable failure is suggested, to study the change of ultimate behavior and load carrying capacity under specific live load conditions. Using these analysis methods, the statical behavior after individual cable failure is studied based on the change of structural configuration, and distribution of internal forces. Also, the change of the ultimate behavior and load carrying capacity under specific live load conditions is investigated, using the proposed analysis method. According to the study, significant change of the statical behavior and ultimate capacity occurs although just one cable fails.

• The Korean Journal of Applied Statistics
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• v.26 no.1
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• pp.1-14
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• 2013

ARIMA and ARIMA+IGARCH models are fitted and compared for daily Korean won/US dollar exchange rate data over 17 years. A linear structural change model and an autoregressive structural change model are fitted for multiple change-point estimation since there seems to be structural change with this data.

• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.889-898
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• 2017

In this research multiple change-points estimation for South Korean electricity generation data is considered. We analyze the South Korean electricity data via deterministically trending dynamic time series model with multiple structural changes in trends in a Bayesian approach. The number of change-points and the timing are unknown. The goal is to find the best model with the appropriate number of change-points and the length of the segments. A genetic algorithm is implemented to solve this optimization problem with a variable dimension of parameters. We estimate the structural change-points for South Korean electricity generation data and Nile River flow data additionally.