• Title/Summary/Keyword: Stationarity

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Long-run Relationship between R&D Expenditures and Economic Growth (공적분 관계를 고려한 연구개발과 경제성장의 상호관계 연구)

  • Han, Woongyong;Jeon, Yongil
    • International Area Studies Review
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    • v.20 no.1
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    • pp.147-165
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    • 2016
  • We empirically examine the validity of second generation endogenous growth theory suing 21 OECD countries' panel data(1981~2011). Due to non-stationarity in all variables, we test the cointegrated relationships strongly supporting the semi-endogenous growth model. In the estimation of total factor productivity growth function, the growth of domestic and foreign R&D investment levels statistically significantly affect total factor productivity growth. R&D intensity, however, has significant impacts on the total factor productivity growth only in a few models, and international technology gap also has positive impacts on GDP growth. Thus the semi-endogenous growth model is relatively supported while fully endogenous growth model is weakly and occasionally supported in OECD countries. The policy implication of supporting the semi-endogenous growth model is that the sustaining growth requires increasing R&D expenditures.

Exports of SMEs against Risk? Theory and Evidence from Foreign Exchange Risk Insurance Schemes in Korea

  • Lee, Seo-Young
    • Journal of Korea Trade
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    • v.23 no.5
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    • pp.87-101
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    • 2019
  • Purpose - This paper examines the effectiveness of the foreign exchange risk insurance system in the promotion of SME exports in Korea. The purpose of this study is to analyze the short-term and long-term responses of SME exports to foreign exchange risk insurance support policies. Based on these empirical studies, we would like to present some operational improvements to the operation of the foreign exchange risk insurance system. Design/methodology - In order to analyze the effect of exchange risk insurance on the exports of SMEs, a VAR model consisting of foreign exchange risk insurance underwriting values, export relative price, and domestic demand pressure, including export volume, was established. The study began with tests of the stationarity of time series data. The unit root tests showed that all concerned variables were non-stationary. Accordingly, the results of the cointegration test showed that the tested variables are not cointegrated. Finally, an impulse response function and variance decomposition analysis were conducted to analyze the impulse of foreign exchange risk insurance on exports of SMEs. Findings - As a result of estimating the VAR (1) model, foreign exchange risk insurance was found to be significant at a 1% significance level for SME' export promotion. In the impulse response analysis, SMEs' export response to the impulse of foreign exchange risk insurance showed that exports gradually increased until the third quarter, and then slowed down. However, the impulse did not disappear, and appeared continuously. Originality/value - This study analyzed the effect of foreign exchange insurance on exports of SMEs by applying the VAR model. In particular, this study is the first to analyze the short-term and long-term effects of foreign exchange risk insurance on exports of SMEs. The empirical evidence in the current study have a policy implication for the policy authority to support and promote the foreign exchange risk insurance in the effect of exchange rate volatility on Korea' export SMEs.

Quantile Co-integration Application for Maritime Business Fluctuation (분위수 공적분 모형과 해운 경기변동 분석)

  • Kim, Hyun-Sok
    • Journal of Korea Port Economic Association
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    • v.38 no.2
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    • pp.153-164
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    • 2022
  • In this study, we estimate the quantile-regression framework of the shipping industry for the Capesize used ship, which is a typical raw material transportation from January 2000 to December 2021. This research aims two main contributions. First, we analyze the relationship between the Capesize used ship, which is a typical type in the raw material transportation market, and the freight market, for which mixed empirical analysis results are presented. Second, we present an empirical analysis model that considers the structural transformation proposed in the Hyunsok Kim and Myung-hee Chang(2020a) study in quantile-regression. In structural change investigations, the empirical results confirm that the quantile model is able to overcome the problems caused by non-stationarity in time series analysis. Then, the long-run relationship of the co-integration framework divided into long and short-run effects of exogenous variables, and this is extended to a prediction model subdivided by quantile. The results are the basis for extending the analysis based on the shipping theory to artificial intelligence and machine learning approaches.

ON THE COARSE-GRAINNING OF HYDROLOGIC PROCESSES WITH INCREASING SCALES

  • M. Levent Kavvas
    • Proceedings of the Korea Water Resources Association Conference
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    • 1998.05b
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    • pp.3-3
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    • 1998
  • In this pressentation it is argued that the heterogeneity of a hydrologic attribute which may seem to be nonstationary at one scale, may become stationary at a larger scale. The fundamental reason for transformation from nonstationarity to stationarity whith the increase in scale is the phenomenon of coarse-graining of the hydrologic processes with increasing scale. Due to the phenomenon of aliasing, a particular scale hydrologic process heterogeneity which is observed as a nonstationary process at that scale, may be observed as a stationary process at a higher(larger) scale whose size is bigger than the stationary extent of the lower scale heterogeneity. As one goes through a hierarchical sequence of larger and larger scales for observations, one would eliminate nonstationarities which emerge at some lower scales at the expense of losing information on the high frequency fluctuations of the lower scale heterogeneities which will no longer be observed at the larger sampling scales. We call this phenimenon as the "coarse-graining in hydrologic observations". In this presentation, it is also argued that by the coarse-graining of hydrologic processes due to the averaging and aliasing operations at increasing scales, the conservation laws corresponging to these scales may still be quite parsimonious, and need not be more complicated as the scales get larger. It is shown that shen a higher(larger) scale process is formed by averaging a lower(smaller) scale process in time or space, the high frequency components of the lower scale process will be eliminated by the averaging operation. Thereby, the resuliiting average hydrologic dynamics, free from the effects of the high frequency components of the lower scale process, can still be quite simple in form. This is demonstrated by means of some recent upscaling work on the solute teansport conservation equation for hetergeneous aquifers. By means of this solute transport example, it is also shown that for the ensemble average form of a hydrologic conservation equation to be equivalent to its volume-average form at any scale, the parameter functions of that conservation equation at the immediately lower scale must be ergodic.

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The timing of unprecedented hydrological drought under climate change

  • Yusuke Satoh;Hyungjun Kim
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.48-48
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    • 2023
  • The intensified droughts under climate change are expected to threaten stable water resource availability. Droughts exceeding the magnitude of historical variability could occur increasingly frequently under future climate conditions. It is crucial to understand how drought will evolve over time because the assumption of hydrological stationarity of the past decades would be inappropriate for future water resources management. However, the timing of the emergence of unprecedented drought conditions under climate change has rarely been examined. Here, using multimodel hydrological simulations, we investigate the changes in the frequency of hydrological drought (defined as abnormally low river discharge) under high and low greenhouse gas concentration scenarios and with existing water resources management and estimate the timing of the first emergence of unprecedented regional drought conditions that persist for over several consecutive years. This new metric enables a new quantification of the urgency of adaptation and mitigation with regard to drought under climate change. The times are detected for several sub-continental-scale regions, and three regions, namely, southwestern South America, Mediterranean Europe, and northern Africa, exhibit particularly robust and earlier critical times under the high-emission scenario. These three regions are expected to confront unprecedented conditions within the next 30 years with a high likelihood, regardless of the emission scenarios. In addition, the results obtained herein demonstrate the benefits of the lower-emission pathway in reducing the likelihood of emergence. The Paris Agreement goals are shown to be effective in reducing the likelihood to the unlikely level in most regions. Nevertheless, appropriate and prior adaptation measures are considered indispensable to when facing unprecedented drought conditions. The results of this study underscore the importance of improving drought preparedness within the considered time horizons.

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An improved time-domain approach for the spectra-compatible seismic motion generation considering intrinsic non-stationary features

  • Feng Cheng;Jianbo Li;Zhixin Ding;Gao Lin
    • Nuclear Engineering and Technology
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    • v.55 no.3
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    • pp.968-980
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    • 2023
  • The dynamic structural responses are sensitive to the time-frequency content of seismic waves, and seismic input motions in time-history analysis are usually required to be compatible with design response spectra according to nuclear codes. In order to generate spectra-compatible input motions while maintaining the intrinsic non-stationarity of seismic waves, an improved time-domain approach is proposed in this paper. To maintain the nonstationary characteristics of the given seismic waves, a new time-frequency envelope function is constructed using the Hilbert amplitude spectrum. Based on the intrinsic mode functions (IMFs) obtained from given seismic waves through variational mode decomposition, a new corrective time history is constructed to locally modify the given seismic waves. The proposed corrective time history and time-frequency envelope function are unique for each earthquake records as they are extracted from the given seismic waves. In addition, a dimension reduction iterative technique is presented herein to simultaneously superimpose corrective time histories of all the damping ratios at a specific frequency in the time domain according to optimal weights, which are found by the genetic algorithm (GA). Examples are presented to show the capability of the proposed approach in generating spectra-compatible time histories, especially in maintaining the nonstationary characteristics of seismic records. And numerical results reveal that the modified time histories generated by the proposed method can obtain similar dynamic behaviors of AP1000 nuclear power plant with the natural seismic records. Thus, the proposed method can be efficiently used in the design practices.

Development of Urban Flood Warning System Using Regression Analysis (회귀분석에 의한 도시홍수 예보시스템의 개발)

  • Lee, BeumHee
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.4B
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    • pp.347-359
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    • 2010
  • A simple web-based flood forecasting system using data from stage and rainfall monitoring stations was developed to solve the difficulty that real-time forecasting model could not get the reliabilities because of assumption of future rainfall duration and intensity. The regression model in this research could forecast future water level of maximum 2 hours after using data from stage and rainfall monitoring stations in Daejeon area. Real time stage and rainfall data were transformed from web-sites of Geum River Flood Control Office & Han River Flood Control Office based MS-Excel 2007. It showed stable forecasts by its maximum standard deviation of 5 cm, means of 1~4 cm and most of improved coefficient of determinations were over 0.95. It showed also more researches about the stationarity of watershed and time-series approach are necessary.

Real-time prediction on the slurry concentration of cutter suction dredgers using an ensemble learning algorithm

  • Han, Shuai;Li, Mingchao;Li, Heng;Tian, Huijing;Qin, Liang;Li, Jinfeng
    • International conference on construction engineering and project management
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    • 2020.12a
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    • pp.463-481
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    • 2020
  • Cutter suction dredgers (CSDs) are widely used in various dredging constructions such as channel excavation, wharf construction, and reef construction. During a CSD construction, the main operation is to control the swing speed of cutter to keep the slurry concentration in a proper range. However, the slurry concentration cannot be monitored in real-time, i.e., there is a "time-lag effect" in the log of slurry concentration, making it difficult for operators to make the optimal decision on controlling. Concerning this issue, a solution scheme that using real-time monitored indicators to predict current slurry concentration is proposed in this research. The characteristics of the CSD monitoring data are first studied, and a set of preprocessing methods are presented. Then we put forward the concept of "index class" to select the important indices. Finally, an ensemble learning algorithm is set up to fit the relationship between the slurry concentration and the indices of the index classes. In the experiment, log data over seven days of a practical dredging construction is collected. For comparison, the Deep Neural Network (DNN), Long Short Time Memory (LSTM), Support Vector Machine (SVM), Random Forest (RF), Gradient Boosting Decision Tree (GBDT), and the Bayesian Ridge algorithm are tried. The results show that our method has the best performance with an R2 of 0.886 and a mean square error (MSE) of 5.538. This research provides an effective way for real-time predicting the slurry concentration of CSDs and can help to improve the stationarity and production efficiency of dredging construction.

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Effectiveness of export credit insurance in export performance of SMEs (수출신용보험이 중소기업의 수출 실적에 미치는 영향에 관한 연구)

  • Xiaoyi Chen;Xinchen Wang;Po-Lin Lai;Thi Kim Cuc Nguyen
    • Korea Trade Review
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    • v.46 no.6
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    • pp.73-92
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    • 2021
  • Small and medium-sized enterprises (SMEs) account for a large proportion of the total number of enterprises in many countries. The development of SMEs has contributed to job creation and economic benefits. Every government has formulated active diversification strategies to promote the export market of SMEs, but the performance of export capabilities remains insufficient. The primary purpose of this study is to examine the effectiveness of export credit insurance in promoting SME export performance in Canada. Using data from 2008-2017, the augmented Dickey-Fuller (ADF) model to test the stationarity of the concerned variables and the error correction model (ECM) and autoregressive distributed lag (ARDL) cointegration test to empirically investigate the cointegration relationship between the research targets. The results represent the positive and critical impact of export relative price and domestic demand pressure on Canada's export performance, and the negative impact of the export volume index at a significant level. Regrettably, the impact of export credit insurance on the export performance of Canadian SMEs is considered exaggerated overall. In view of this result, it is necessary for the Canadian government to enact policies based on the current market status. And enhance confidence among SMEs to begin exports and diversify their markets rather than focusing only on the domestic or US market, especially given the impact of COVID-19. From the case of Canada, Korean government can attempt to learn from them to conduct more efficient strategies for SMEs.

Analyzing on the cause of downstream submergence damages in rural areas with dam discharge using dam management data

  • Sung-Wook Yun;Chan Yu
    • Korean Journal of Agricultural Science
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    • v.50 no.3
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    • pp.331-347
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    • 2023
  • The downstream submergence damages caused during the flood season in 2020, around the Yongdam-dam and five other sites, were analyzed using related dam management data. Hourly- and daily-data were collected from public national websites and to conduct various analyses, such as autocorrelation, partial-correlation, stationary test, trend test, Granger causality, Rescaled analysis, and principal statistical analysis, to find the cause of the catastrophic damages in 2020. The damage surrounding the Yongdam-dam in 2020 was confirmed to be caused by mis-management of the flood season water level. A similar pattern was found downstream of the Namgang- and Hapcheon-dams, however the damage caused via discharges from these dams in same year is uncertain. Conversely, a different pattern from that of the Yongdam-dam was seen in the areas downstream of Sumjingang- and Daecheongdams, in which the management of the flood season water level appeared appropriate and hence, the damages is assumed to have occurred via the increase in the absolute discharge amount from the dams and flood control capacity leakage of the downstream river. Because of the non-stationarity of the management data, we adapted the wavelet transform analysis to observe the behaviors of the dam management data in detail. Based on the results, an increasing trend in the discharge amount was observed from the dams after the year 2000, which may serve as a warning about similar trends in the future. Therefore, additional and continuous research on downstream safety against dam discharges is necessary.