• Korea Trade Review
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• v.48 no.3
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• pp.69-88
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• 2023

This study analyzes the dynamic characteristics of cargo volume (demand), ship fleet (supply), and freight rate (price) of container, dry bulk, and tanker shipping markets by using the VAR and VECM models. This analysis is expected to enhance the statistical understanding of market dynamics, which is perceived by the actual experiences of market participants. The common statistical patterns, which are all shown in the three shipping markets, are as follows: 1) The Granger-causality test reveals that the past increase of fleet variable induces the present decrease of freight rate variable. 2) The impulse-response analysis shows that cargo shock increases the freight rate but fleet shock decreases the freight rate. 3) Among the three cargo, fleet, and freight rate shocks, the freight rate shock is overwhelmingly largest. 4) The comparison of adjR² reveals that the fleet variable is most explained by the endogenous variables, i.e., cargo, fleet, and freight rate in each of shipping markets. 5) The estimation of co-integrating vectors shows that the increase of cargo increases the freight rate but the increase of fleet decreases the freight rate. 6) The estimation of adjustment speed demonstrates that the past-period positive deviation from the long-run equilibrium freight rate induces the decrease of present freight rate.

• Journal of Mushroom
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• v.21 no.4
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• pp.200-208
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• 2023

This study was conducted to investigate the reasons for the decreased importation of fresh Shiitake mushrooms into Korea after implementation of the Korea-China Free Trade Agreement (FTA). Monthly time-series data from January 2009 to December 2022 were analyzed using regression analysis and vector autoregression (VAR) models to determine the relationship between the amounts of fresh and spawn Shiitake mushrooms imported. The analysis revealed that a major reason for the decreased importation of fresh Shiitake mushrooms was an increase in mushroom spawn imports after Korea-China FTA implementation. The same results were obtained from the VAR model analysis. However, in terms of the dynamic changes in amount of fresh shiitake mushrooms imported, it was confirmed that the impact of the change in mushroom spawn imports could increase the amount of Shiitake mushrooms imported.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.33-42
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• 2021

This study aims to investigate the relationship between foreign direct investment (FDI) and economic growth at the provincial level by using time-series data in Binh Dinh from 1997 to 2019. We applied the quantitative approaches Vector Autoregression (VAR) and Autoregressive Distributed Lags (ARDL) in the model, which includes economic growth, real foreign direct investment capital, ratio of trained workers, and infrastructure. The results show that all these variables are stationary at the first difference. In ARDL analysis, we found that the economic growth positively affects FDI attraction. However, there is no evidence of the effect of FDI on economic growth in the condition of low capital implemented. Moreover, findings also show that the impact of FDI on economic growth is influenced by two factors: infrastructure and human capital. The lack of human capital, which is trained personnel and infrastructure, is the main barrier hindering and inhibiting FDI's contribution to local economic growth. In order to improve the efficiency of FDI on economic growth in the future, it is suggested that the Binh Dinh government should have proper policies in terms of the infrastructure, the human capital investment. They would allow Binh Dinh to enhance the capital absorptive capacity and capital efficiency.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.119-126
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• 2021

This study is to examine the foreign direct investment (FDI) response to real effective exchange rate volatility in Vietnam by using the vector autoregression model. The research data are quarterly frequency data in the period from 2004:Q1 to 2019:Q2. The data on real effective exchange rate were collected from the statistics of Bruegel (Europe) and FDI data were collected from the International Financial Statistics. The quantitative study was conducted with two steps: (1) measuring exchange rate volatility by the GARCH(1,1) method; and (2) examining the impact of exchange rate volatility on FDI in the context of the global financial crisis. The estimation results show that FDI responded significantly to real exchange rate volatility with the lag of 3 periods at the 5% significance level. The FDI response increased after the exchange rate volatility with the lag of 3 periods, and the impact extended to the lag of 6 periods, and then gradually stabilized. The research findings indicate that FDI in Vietnam responds positively and significantly to exchange rate volatility with the lag of 3 periods. Simultaneously, the negative impact of the global financial crisis in 2008 with the lag of 2 periods leads to a slight decrease in FDI inflows into Vietnam.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.61-67
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• 2021

The covid-19 pandemic scenario caused the most extensive economic shocks the world has experienced in decades. Maintaining financial performance and economic stability is essential during the pandemic period. In these conditions, where movement is severely restricted, media consumption is considered to be increasing. The social media platform is one of the media online used by the public as a source of information and also expressing their sentiment, including individual investors in the capital market as social media users. Twitter is one of the social media microblogging platforms used by individual investors to share their opinion and get information. This study aims to determine whether microblogging sentiment investors can predict the capital market during pandemics. To analyze microblogging sentiment investors, we classified sentiment using the phyton text mining algorithm and Naïve Bayesian text classification into level positive, negative, and neutral from November 2019 to November 2020. This study was on 68 listed companies on the Indonesia stock exchange. A Vector Autoregression and Impulse Response is applied to capture short and long-term impacts along with a causal relationship. We found that microblogging sentiment investor has a significant impact on stock returns and volatility and vice-versa. Also, the response due to shocks is convergent, and microblogging investors in Indonesia are categorized as a "news-watcher" investor.

• Asia-Pacific Journal of Business
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• v.13 no.3
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• pp.463-473
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• 2022

Purpose - The purpose of this study is to examine the effect of the North Korea's net export to China and Liaoning on the North Korean economic growth. Design/methodology/approach - This study collects the data on the net export of North Korea to China and Liaoing from General Administration of Customs, People's Republic of China. Vector Autoregression(VAR) is also employed for the analysis. Findings - First, North Korea's net export to all of China and Liaoning gives the positive effect on North Korean economic growth. Second, the nuclear test of North Korea gives the negative effect on the North Korean economic growth. Third, the net export to China and Liaoning granger causes the North Korean economic growth. Lastly, the nuclear test of North Korea also granger causes the North Korean economic growth. Research implications or Originality - The estimation results show the net export of North Korea to China as well as Liaoning is important to the economic growth. Therefore, we need to examine North Korea's trades with specific region as well as all of China in order to enhance the North Korean economic growth.

• The Journal of the Korea Contents Association
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• v.15 no.10
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• pp.457-467
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• 2015

Despite the recent phenomena of Chonsei price increase, low interest rate and low growth, the indexes of financial and insurance industry production showed the results contrary to the common belief that the financial industry is sensitive to such financial crises. This is because the index of financial industry has continuously maintained a certain level of increase as opposed to the index of all industry production. Thus, this study aimed to analyze the dynamic correlation between the index of financial industry production and Chonsei price increase. A vector autoregression (VAR) model, which doesn't have a cointegrating relationship, was used to define the Chonsei price index and the indexes of all industry production and financial and insurance industry, which are macro economic variables, and describe the data. The results of the analysis on the time series data of 183 months from January 2000 to May 2015 showed that Chonsei price increase was not directly derived from the index of financial industry, but the finance industrial index affected Chonsei price increase.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2953-2966
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• 2018

Housing prices are closely related to various variables that indicate macroeconomic conditions. In this paper, empirical analysis based on data is performed referring to previous studies. Focusing on the policy interest rate among the factors affecting the housing price, the non-linear impulse responses of other variables to the interest rate shock are analyzed. Using the random forest algorithm, the variable importance scores of the macroeconomic variables presented in the previous studies are calculated. After selecting the variables through this process, the impulse responses are calculated using a model that can capture non-linearity. According to the model, the responses of housing prices to the policy rate is only significant when the rate is raised. Especially, the impulse response is amplified when the shock increases due to the non-linear characteristics that can not be captured by the traditional VAR methodology. The analysis results suggest that the interest rate as a policy instrument should be approached from a more cautious perspective.

• Journal of Korea Trade
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• v.25 no.1
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• pp.34-46
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• 2021

Purpose - This paper aims to analyze the impact of the terms of trade, export price, and import price on the Korean economy (that is, real GDP, CPI, money market rate, and real effective exchange rate), and vice versa in the simple vector autoregression. Design/methodology - We impose two assumptions, i.e., diagonality and bloc exogeneity, to correctly identify the impact of a factor to the others in the structural equation. With two contemporaneous assumptions in the structural VAR, this paper investigates the impacts of the terms of trade on the Korean economy and vice versa. Findings - Impulse responses to the shocks in the terms of trade and Korean economy show that 1) an impact of the terms of trade on the economy is different in export prices and in import prices. A higher export price is beneficial to the economy while a higher import price hurts the economy, and 2) an increase in real effective exchange rate and in interest rate constrains domestic production and lowers consumer prices. Originality/value - Unlike the conventional perception that a depreciation of a currency would promote exports and domestic production at the price of inflation, our result shows the opposite, and 3) real GDP and consumer prices are positively correlated. That is, an increase in real GDP does not only cause inflation, but an increase in consumer prices also promote domestic production. Yet, the only difference is that export prices and import prices end up higher with an increase in real GDP, but lower with inflation.

• Management & Information Systems Review
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• v.31 no.4
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• pp.287-307
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• 2012

We empirically examine the price discovery dynamics among the VKOSPI, the KOSPI200 spot, and the KOSPI200 futures markets. The analysis employs the vector-autoregression, Granger causality, impulse response function, and variance decomposition using both daily data from 2009. 04. 13 to 2011. 12. 30 and 1 minute data from the bull market, bear market, and the flat period. The main results are as follows; First, the lead lag relationships between KOSPI200 spot(futures) yield VKOSPI returns could not be found from the daily data analysis. But KOSPI200 spot(futures) have a predictive power for VKOSPI from 1 minute data. Especially KOSPI200 spot(futures) and VKOSPI show the bi-directional effects to each other during the return rising period Second, We chose the VAR(1) the model in daily data but adopt the VAR(3) model in the one minute data to determine the lead lag time. We know that there is predictability during the very short period Third, Spot returns and futures returns makes no difference in daily data results. According to the one minite data results, VKOSPI returns have a predictive power for KOSPI200 spot return, but have no predictive power for KOSPI200 futures return.