• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.61-68
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• 2021

The exchange rate is considered a tool improving the volume of exports and reducing imports. This paper aims to determine the impact of the exchange rate on exports and imports between Vietnam and the United States in the context of the trade war. The research uses Autoregressive Distributed Lag (ARDL) and Nonlinear Autoregressive Distributed Lag (NARDL) Model in the time-series data from 2010:1 to 2020:9. The ARDL's results support that real exchange rate impact on export and import volumes, but less than the trade war. The trade war helps trade balance increase 0.35%, while the exchange rate increases trade balance 0.191% when the Vietnamese currency devalues 1% in the long run. In the short term, the real exchange rate makes the trade balance decrease. Therefore, the J curve exists between Vietnam and the U.S. The NARDL expresses that the exchange rate is asymmetric both in the short term and the long term. The findings of this study point to two important elements. Firstly, the exchange rate plays a minor role in exports and imports. Secondly, trade war plays a vital role in increasing exports and imports volume between two countries, and the J curve exists between the two countries.

• Journal of Distribution Science
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• v.20 no.8
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• pp.1-8
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• 2022

Purpose: Research on attracting foreign direct investment (FDI) plays an important role in helping provinces attract more FDI projects. However, with local competition, FDI enterprises also have to consider their investment. This study evaluates the provincial competitiveness to attract FDI in Thai Nguyen province, a province of Vietnam. In which provincial distribution of competitiveness is measured through nine indicators. Research design, data, and methodology: The study collects data (FDI and the provincial competitiveness index) from 2006 to 2020. The study uses Autoregressive Distributed Lag (ARDL) to text the impact of distribution of competitivenes on foreign direct investment. With time-series, the ARDL is suitable for data analysis. Results: The regression results indicate that the competition index of market entry and informal costs negatively impact attracting FDI into the province; The human resource training quality index has a positive effect on FDI. The results show that FDI enterprises pay much attention to business establishment procedures, hidden costs, and quality of human resources in the province. Conclusions: At the same time, in terms of practice, the results of this study, the authors also offer solutions to help improve the ability to attract FDI into Thai Nguyen province. The significant provincial competitiveness indicators should be taken into account for improvement first.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.2
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• pp.57-72
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• 2020

The price of iron ore has continued to fluctuate with high demand and supply from many countries and companies. In this business environment, forecasting the price of iron ore has become important. This study developed the machine learning model forecasting the price of iron ore a one month after the trading events. The forecasting model used distributed lag model and deep learning models such as MLP (Multi-layer perceptron), RNN (Recurrent neural network) and LSTM (Long short-term memory). According to the results of comparing individual models through metrics, LSTM showed the lowest predictive error. Also, as a result of comparing the models using the ensemble technique, the distributed lag and LSTM ensemble model showed the lowest prediction.

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.663-670
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• 2016

This paper analyzes the asymmetric pass-through effects of crude oil price changes on export prices in Korea's manufacturing sector using a nonlinear autoregressive distributed lag (NARDL) model. These pass-through effects are important for Korean companies that are highly dependent on exports. Because the effects differ by industry, eight sectors of the manufacturing industry were examined. The model is effective for separately testing the long-term and short-term differences between the export-price pass-through effects when crude oil prices increase and decrease. The estimation results show that there is positive pass-through to export prices as crude oil prices change, and there are asymmetric effects in some manufacturing sectors. Short-term asymmetries were detected in the export prices of five sectors that include general machinery and transport equipment, and significant long-term asymmetries were found for petroleum and coal products and for textile and leather products. The long-term export price of oil and coal products rose by 0.992% with a 1% increase in the oil price and fell by 0.977% with 1% decrease. Therefore, corporate strategies and government export policies should be established in accordance with these asymmetric pass-through effects.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.3
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• pp.160-174
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• 2014

The purpose of this paper is to develop a meso-scale grid-based continuous hydrological model and apply to assess the future watershed hydrology by climate change. The model divides the watershed into rectangular cells, and the cell profile is divided into three layered flow components: a surface layer, a subsurface unsaturated layer, and a saturated layer. Soil water balance is calculated for each grid cell of the watershed, and updated daily time step. Evapotranspiration(ET) is calculated by Penman-Monteith method and the surface and subsurface flow adopts lag coefficients for multiple days contribution and recession curve slope for stream discharge. The model was calibrated and verified using 9 years(2001-2009) dam inflow data of two watersheds(Chungju Dam and Soyanggang Dam) with 1km spatial resolution. The average Nash-Sutcliffe model efficiency was 0.57 and 0.71, and the average determination coefficient was 0.65 and 0.72 respectively. For the whole Han river basin, the model was applied to assess the future climate change impact on the river bsain. Five IPCC SRES A1B scenarios of CSIRO MK3, GFDL CM2_1, CONS ECHO-G, MRI CGCM2_3_2, UKMO HADGEMI) showed the results of 7.0%~27.1 increase of runoff and the increase of evapotranspiration with both integrated and distributed model outputs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.676-686
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• 2016

This study analyzed the long term relationship between the K-REITs' lending rate and interest rate variables based on ARDL (autoregressive distributed lag) and also examined the short term relationship based on the ARDL-ECM model. In the results of the empirical test, there is a co-integration relationship among the K-REITs' lending rate, 3 year government bond (rate), 3 year government bond (rate), corporation bond (rate) (AA-, 3year) and general fund loan rate. This means that the K-REITs' lending rate is related to the long term interest rate. The corporate general fund loan rate has a significant correlation with the K-REITs' lending rate in the long term relation and short term adjustment process. The establishment of a management plan by the REITs considering the trends in the corporate general fund loan rate in the decision making process for finance sector borrowings can be practically helpful for the K-REITs.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.373-381
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• 2022

The Fukushima nuclear power plant water spill caused by the Great East Japan Earthquake in March 2011 raised fears about radiation exposure through consumption of radioactively contaminated seafood. The Korean government banned importing agricultural and fishery products from eight prefectures near Fukushima, but the related news were continuously reported partly due to the WTO dispute with Japan, which seems to have aggravated consumers' anxiety about seafood. In this study, data on daily purchases of products for three years (2018-2020) were collected and the effect of Japanese radiation-related news on domestic consumers' purchases of seafood was estimated using a polynomial lag distributed model. As a result of the analysis, it was found that radiation-related news had a statistically significant negative effect on the purchase of seafood on the 5th and 6th days after exposure to consumers through the media. It captures the carryover effect in which consumers' perceptions are reflected in the purchase of seafood after exposure to related news.

• Communications for Statistical Applications and Methods
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• v.29 no.1
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• pp.41-51
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• 2022

We forecast the US oil consumption level taking advantage of google trends. The google trends are the search volumes of the specific search terms that people search on google. We focus on whether proper selection of google trend terms leads to an improvement in forecast performance for oil consumption. As the forecast models, we consider the least absolute shrinkage and selection operator (LASSO) regression and the structured regularization method for large vector autoregressive (VAR-L) model of Nicholson et al. (2017), which select automatically the google trend terms and the lags of the predictors. An out-of-sample forecast comparison reveals that reducing the high dimensional google trend data set to a low-dimensional data set by the LASSO and the VAR-L models produces better forecast performance for oil consumption compared to the frequently-used forecast models such as the autoregressive model, the autoregressive distributed lag model and the vector error correction model.

• Structural Engineering and Mechanics
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• v.34 no.3
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• pp.285-300
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• 2010

The two-dimensional deformation of a homogeneous, isotropic thermoelastic half-space with voids with variable modulus of elasticity and thermal conductivity subjected to thermomechanical boundary conditions has been investigated. The formulation is applied to the coupled theory(CT) as well as generalized theories: Lord and Shulman theory with one relaxation time(LS), Green and Lindsay theory with two relaxation times(GL) Chandrasekharaiah and Tzou theory with dual phase lag(C-T) of thermoelasticity. The Laplace and Fourier transforms techniques are used to solve the problem. As an application, concentrated/uniformly distributed mechanical or thermal sources have been considered to illustrate the utility of the approach. The integral transforms have been inverted by using a numerical inversion technique to obtain the components of displacement, stress, changes in volume fraction field and temperature distribution in the physical domain. The effect of dependence of modulus of elasticity on the components of stress, changes in volume fraction field and temperature distribution are illustrated graphically for a specific model. Different special cases are also deduced.