• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.243-251
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• 2022

In this paper, we propose a phenomenon that analyze the impact of market sentiment on China's real estate market through the perspective of behavioral economics. Previously, real estate market analyzation basically focus on some fundamental principles which include market price, monetary policies and income, etc. However, little research has explored market sentiment and its influence. By using principal components analysis (PCA), this study first creates buyer's sentiment and seller's sentiment to measure the heat of China's real estate market. Different from using traditional estimation method, the vector autoregressive model (VAR) is used to analyze how both sentiments affect real estate return. The overall results show that from unit root test and impulse response analyzation, the impact of seller's sentiment is positive to real estate market while buyer's sentiment is negative. At the same time, the higher seller's sentiment will have different influence on the housing market compared with the higher buyer's sentiment.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.3
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• pp.409-416
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• 2022

This paper relates to the blind noise separation method of time-delayed convolutive mixed signals. Since the mixed model of acoustic signals in a closed space is multi-channel, a convolutive blind signal separation method is applied and time-delayed data samples of the two microphone input signals is used. For signal separation, the mixing coefficient is calculated using an inverse model rather than directly calculating the separation coefficient, and the coefficient update is performed by repeated calculations based on secondary statistical properties to estimate the speech signal. Many simulations were performed to verify the performance of the proposed blind signal separation. As a result of the simulation, noise separation using this method operates safely regardless of convolutive mixing, and PESQ is improved by 0.3 points compared to the general adaptive FIR filter structure.

• Korea Trade Review
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• v.42 no.6
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• pp.131-154
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• 2017

In international trade, transportation generally has the largest and direct impact on freight costs. However, it is also sensitive to external factors such as global economic conditions, global trade volume and exchange rate. Therefore, it is necessary to examine the relationship and influence of international trade in terms of external factors that affect the change of imports and exports by marine and air transportation through empirical analysis. In particular, the analysis of the impact of these external factors on marine and air transportation is an important topic when recent exchange rate changes are significant, and it is also necessary to analyze what transportation means are more sensitive to exchange rate changes. In this study, we use the Vector Error Correction Model to analyze the dynamic effects of changes in exchange rate and domestic and international economic conditions on marine and air transportation from January 2000 to March 2017. Respectively. Alos, Impulse response function and variance decomposition were examined.

• Asia-Pacific Journal of Business
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• v.14 no.4
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• pp.305-318
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• 2023

Purpose - This study analyzed the decoupling phenomenon between energy consumption and economic growth in Korea from 1990 to 2021. The main purpose of this study is to suggest policy implications for achieving a low-carbon society and decoupling that Korea must move forward in the face of the climate change crisis. Design/methodology/approach - This study investigated the relationship between energy consumption and economic growth by energy source and sector using the energy-EKC (EEKC) hypothesis which included the energy consumption on the traditional Environmental Kuznets Curve (EKC), and the impulse response function (IRF) model based on Bayesian vector auto-regression (BVAR). Findings - During the analysis period, the trend of decoupling of energy consumption and economic growth in Korea is confirmed starting from 1996. However, the decoupling tendency appeared differently depending on the differences in energy consumption by sources and fields. The results of the IRF model using data on energy consumption by source showed that the impact of GDP and renewable energy consumption resulted in an increase in energy consumption of bio and waste, but a decrease in energy consumption by sources, and the impact of trade dependence was found to increase the consumption of petroleum products. Research implications or Originality - According to the main results, efficient distribution by existing energy source is required through expansion of development of not only renewable energy but also alternative energy. Additionally, in order to increase the effectiveness of existing energy policies to achieve carbon neutrality, more detailed strategies by source and sector of energy consumption are needed.

• Journal of Korean Society of Forest Science
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• v.98 no.3
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• pp.284-289
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• 2009

This study estimated the fiberboard demand using VAR and econometric model, and compared the prediction accuracy of the two models. And the variance decomposition and impulse response were analyzed using VAR model, and predicted the fiberboard demand. The VAR model was specified with lagged dependent variable, lagged own price, lagged construction product, dummy. The econometric model was specified with own price, substitute price, construction product, dummy. The dummy variable reflected the abrupt decrease in fiberboard demand in the late 1990's. The results showed that the fiberboard demand prediction can be performed more accurately by VAR model than by econometric model. In the VAR model of fiberboard demand, after twelve months, the construction product change accounts for about fifty percent of variation in the demand, and the own price change accounts for about thirty percent of variation in the demand. On the other hand, the impact of a shock to the construction product is significant for about twelve months on the demand of fiberboard, and the impact of a shock to the own price is significant for about six months on the demand of fiberboard.

• Journal of Navigation and Port Research
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• v.44 no.1
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• pp.44-52
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• 2020

More accurate forecasting of port cargo in the global long-term recession is critical for the implementation of port policy. In this study, the Busan Port container volume (export cargo and transshipment cargo) was estimated using the Vector Autoregressive (VAR) model and the vector error correction (VEC) model considering the causal relationship between the economic scale (GDP) of Korea, China, and the U.S. as well as ARIMA, a single volume model. The measurement data was the monthly volume of container shipments at the Busan port J anuary 2014-August 2019. According to the analysis, the time series of import and export volume was estimated by VAR because it was relatively stable, and transshipment cargo was non-stationary, but it has cointegration relationship (long-term equilibrium) with economic scale, interest rate, and economic fluctuation, so estimated by the VEC model. The estimation results show that ARIMA is superior in the stationary time-series data (local cargo) and transshipment cargo with a trend are more predictable in estimating by the multivariate model, the VEC model. Import-export cargo, in particular, is closely related to the size of our country's economy, and transshipment cargo is closely related to the size of the Chinese and American economies. It also suggests a strategy to increase transshipment cargo as the size of China's economy appears to be closer than that of the U.S.

• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.2
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• pp.69-78
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• 1999

In this paper, a neural network approach to forecast Korean regional precipitation is presented. We first analyze the characteristics of the conventional models for time series prediction, and then propose a new model and its learning method for the precipitation forecast. The proposed model is a layered network in which the outputs of a layer are buffered within a given period time and then fed fully connected to the upper layer. This study adopted the dual connections between two layers for the model. The network behavior and learning algorithm for the model are also described. The dual connection structure plays the role of the bias of the ordinary Multi-Layer Perceptron(MLP), and reflects the relationships among the features effectively. From these advantageous features, the model provides the learning efficiency in comparison with the FIR network, which is the most popular model for time series prediction. We have applied the model to the monthly and seasonal forecast of precipitation. The precipitation data and SST(Sea Surface Temperature) data for several decades are used as the learning pattern for the neural network predictor. The experimental results have shown the validity of the proposed model.

• Journal of KIISE:Computer Systems and Theory
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• v.28 no.9
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• pp.415-423
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• 2001

Recently, there are many attempts to reproduce real world fine art pieces in digital forms. The digital representations are convenient to store and/or transmit. In contrast, mobiles, or moving sculptures, such as those designed by Alexander Calder cannot to reproduced realistically by usual reproduction techniques. Since mobiles are originally designed to generate motions in response to external forces applied to it, people could not fully enjoy them through photographs or static images. We present a virtual mobile system where use can easily control the mobile and can feel the impressions that the artist originally intended to provide. A real-world mobile is reconstructed in a three-dimensional physically-based model. and then virtual wind is generated to give motions to it. The motions of the mobile are generated by constraint dynamics and impulse dynamics techniques, which are modified to fully utilize the characteristics of the mobile, and finally give interactive displays on the PC platforms. The techniques presented can easily be extended to simulate other interactive dynamics systems.

• Journal of Environmental Policy
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• v.10 no.4
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• pp.3-37
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• 2011

This paper investigates the existence of the environmental Kuznets curve (EKC) for carbon dioxide $CO_2$ emissions and its causal relationships with economic growth and openness by using time series data (1971-2006) from China (an emerging market), Korea (a newly industrialized country), and Japan (a developed country). The sample countries span a whole range of development stages from industrialized to newly industrialized and emerging market economies. The environmental consequences according to openness and economic growth do not show uniform results across the countries. Depending on the national characteristics, the estimated EKC show different temporal patterns. China shows an N-shaped curve while Japan has a U-shaped curve. Such dissimilarities are also found in the relationship between $CO_2$ emissions and openness. In the case of Korea, and Japan it represents an inverted U-shaped curve while China shows a U-shaped curve. We also analyze the dynamic relationships between the variables by adopting a vector auto regression or vector error correction model. These models through the impulse response functions allow for analysis of the causal variable's influence on the dynamic response of emission variables, and it adopts a variance decomposition to explain the magnitude of the forecast error variance determined by the shocks to each of the causal variables over time. Results show evidence of large heterogeneity among the countries and variables impacts.

• Journal of the Economic Geographical Society of Korea
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• v.22 no.4
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• pp.555-575
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• 2019

Though housing market varies spatially, housing policy is limited in reflecting detailed regional differentiation. This study looked at the differences in Seoul Gu Districts' response to housing policy for the efficient implementation of housing policies in the future. Housing policy index was established by each Gu-districts' according to investigated housing policies from 2003 to 2018, weighted in two categories(financial/urban planning) and the status of designated areas. The VECM model was established to analyze the impact of the housing policy on the housing market. According to the analysis, although housing policies were established in response to market prices change, the impact of policies on prices was lower than the impact of vice versa. The housing policy's impact to the housing market is limited in some areas in northeastern Seoul. These results show that there are differences in the responses to housing policy in Seoul districts', and therefore detailed consideration of the differences in the regional aspects of housing policy is needed.