• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.281-286
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• 2023

This study analyzed the causal relationship between housing sales prices and jeonse prices in Seoul, specifically in the Gangnam and Gangbuk neighborhoods. The time-invariant Granger causality test showed bidirectional causality between the sales price and the jeonse price in Seoul and Gangbuk, but no bidirectional causality was found in Gangnam. However, the time-varying Granger causality test showed a Granger causal relationship between the housing jeonse price and the sales price for the entire period after 1993 in all three areas. Notably, the causal effect of jeonse prices on sales prices has been continuous in Gangnam since 2010. These analysis results suggest that an increase in liquidity supply to the jeonse market could increase volatility throughout the housing market, given the strong influence between the sales and jeonse markets in both directions.

• International Area Studies Review
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• v.15 no.1
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• pp.107-133
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• 2011

This paper aims to analyze the causal relationships between agricultural exports and economic growth in the U.S. economy by 50 states. Using the annual data from 1973 to 2007, the theoretical methodologies based on the export-led growth (ELG) model under the static model, the impulse response function (IRF) and forecast error variation decomposition (FEVD) under the vector autoregressive (VAR) model, and the Granger causality test. The results show the causal relationship between agricultural exports and economic growth at the states' level. Especially, the ELG hypothesis is strongly supported in the case of 16 states (HI, ID, KS, MD, MI, MN, NJ, NC, ND, OK, OR, RI, SD, TX, WA, and WI) and is also weakly supported in the case of 31 states. Therefore, the agricultural exports are important factor of developing in the U.S. economy, and furthermore some states (located in coastal area and breadbasket) indicate the strong evidence for agricultural exports-led growth.

• International Area Studies Review
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• v.12 no.3
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• pp.449-465
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• 2008

This paper aims to analyze the causal relationship between exports and regional economic growth based on the provincial data over the period from 1952 to 2004. To reflect the regional and chronical characteristics, this paper divides China into three regions; Eastern, Central and Western regions, and also the whole period into two sub-periods; before and after 1979 when the Open-door policy(ODP) was initiated and applies Granger causality analysis. The Granger causality tests showed that exports Granger cause economic growth in the Eastern region, but not in the Central and Western regions, as a whole. When the period is divided, in the Eastern region, causal relation between the two variables was not found before the Open-door policy. For the second period, however it turns out that exports cause the region's economic growth. This result is consent with the fact that the region has been a main beneficiary of the policy. For the Central region, the tests showed no causality in the pre-ODP period, but significant bidirectional causality in the post-ODP period. Meanwhile, in the Western region, exports turned out causing economic growth significantly before the ODP, while economic growth appeared to causing trade after the ODP.

• Journal of Convergence for Information Technology
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• v.11 no.9
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• pp.84-93
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• 2021

The purpose of this study is to analyze whether the spread of COVID-19 infectious diseases acts as a fear to investors and affects the direction and volatility of stock returns. The investor fear index was proposed using the domestic confirmed patient information of COVID-19, and the influence on stock prices was empirically analyzed. The direction and volatility models of stock prices used the Granger causality and GARCH models, respectively. The results of empirical analysis using the KOSPI index from February 20, 2020 to June 30, 2021 are as follows: First, the COVID-19 fear index showed causality to future stock prices. Second, the COVID-19 fear index has a negative effect on the volatility of KOSPI index returns. In future studies, it is necessary to document the cause by using individual business performance and stock price instead of the stock index.

• Journal of Convergence for Information Technology
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• v.12 no.3
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• pp.116-125
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• 2022

The purpose of this study is to analyze whether investor anxiety caused by COVID-19 affects cryptocurrency prices in the COVID-19 pandemic, and to experiment with cryptocurrency price prediction based on a deep learning model. Investor anxiety is calculated by combining Naver's Corona search index and Corona confirmed information, analyzing Granger causality with cryptocurrency prices, and predicting cryptocurrency prices using deep learning models. The experimental results are as follows. First, CCI indicators showed significant Granger causality in the returns of Bitcoin, Ethereum, and Lightcoin. Second, LSTM with CCI as an input variable showed high predictive performance. Third, Bitcoin's price prediction performance was the highest in comparison between cryptocurrencies. This study is of academic significance in that it is the first attempt to analyze the relationship between Naver's Corona search information and cryptocurrency prices in the Corona phase. In future studies, extended studies into various deep learning models are needed to increase price prediction accuracy.

• The Journal of the Korea Contents Association
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• v.22 no.8
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• pp.329-338
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• 2022

As the non-face-to-face economic situation developed due to the COVID-19 pandemic, untact stock groups appeared in the stock market. This study proposed the Korea COVID-19 fear index following the spread of infectious diseases in the COVID-19 pandemic situation and analyzed the influence on the untact stock and contact stock returns. The results of the empirical analysis are as follows. First, as a result of the Granger causality analysis using the Korea COVID-19 fear index, significant causality was found in the return of contact stocks such as Korean Air, Hana Tour, CJ CGV, and Paradise. Second, as a result of stock price prediction based on the LSTM model, Kakao, Korean Air, and Naver's prediction performance was high. Third, the investment performances of the Alexander filter entry rule using the predicted stock price were high in Naver futures and Kakao futures. This study can find a difference from previous studies in that it analyzed the influence of the spread of the COVID-19 pandemic on untact and contact stocks in the COVID-19 situation where the non-face-to-face economy is in full swing.

• The Korean Journal of Financial Management
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• v.20 no.1
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• pp.125-162
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• 2003

This paper investigates the short- and long- run relationship among Korean, U.S. and Japanese construction indices. We conducted the Johansen's cointegration tests on the hypotheses that the construction indices of three countries we related in the long-run as well as in the short-run. The test results show that there exists no long-run relationship among three countrie's construction indices. In addition, the cointegrating relation did not exist for three countrie's stock market indices and five major Korean construction firms. It fumed out that the U.S. indices Granger-causes Japanese and Korean indices. This finding implies that there may exist international diversification benefit through forming a portfolio from these indices.

• Journal of Korea Port Economic Association
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• v.38 no.3
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• pp.87-104
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• 2022

Considering the complex structure and high volatility in the shipping market, it is important to investigate the connectedness amongst influencing factors. This study explores the dynamic relationship between supply-demand factors and shipping freight indices. We choose Capesize and Panamax in the bulk carrier market and use quarterly data of GDP, world fleet, BCI, and BPI from 1999 to 2021. Applying the wavelet analysis and wavelet Granger causality test, the simultaneous examination of co-movement and causality between two factors and the shipping market in both the time and frequency domains is achieved. We find that co-movement and causality vary across time and frequencies, thereby existing dynamic relationships between variables. Second, compared to multiple coherencies using demand and supply factors together, partial coherencies indicate noticeable causalities. It implies that analyzing demand and supply factors separately is essential. Finally, shipping freight indices show a high correlation with the demand factor in a good market and with the supply factor in a bad market. Generally, GDP positively leads shipping freights in the recovery phase while the world fleet negatively leads shipping freights in the downturn. The research is meaningful in that the rarely-applied wavelet analysis is adopted in the shipping market and that it gives a reasonable ground to explain the role of supply and/or demand factors in different phases of the market cycle.

• Journal of Korean Society of Transportation
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• v.22 no.3 s.74
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• pp.69-84
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• 2004

1990년대 중반이후 정보통신의 발달에 의한 인터넷의 활용이 전세계적으로 급속히 팽창하면서 사이버마켓이라는 새로운 시장형태하에서 전자상거래가 급속히 성장하고 있다. 인터넷 전자상거래의 성장은 기존의 유통구조를 오프라인으로부터 온라인으로 전환시키고 물류체계까지 변화시키고 있다. 전자상거래의 경우 인터넷과 같은 정보시스템의 발달에 의해 독자적으로 성장할 수 있는 것은 아니며, 실제거래를 위한 물류와 연계해서만이 가능하다. 따라서 전자상거래의 급속한 성장과 더불어 문전배송서비스(door-to-door delivery service)가 가능한 택배서비스가 급속히 증가하고 있다. 이러한 관점에서 도시내에서의 전자상거래에 의한 택배서비스시장 환경변화를 고려하여 전자상거래를 촉진시키는 어떤 요인이 택배서비스에 영향을 미치고 성장에 중요한 역할을 하는지를 파악해 보는 것도 흥미있는 일이라 하겠다. 본 연구는 시계열데이터를 이용하여 전자상거래에 의한 택배서비스시장의 상관관계를 검토하고 전자에 의한 후자의 성장요인을 분석해 보는데 그 목적이 있다. 본 연구에서는 택배서비스시장의 성장요인을 시장내부의 내적요인과 외부의 외적요인으로 구분하고, 외적요인을 다시 교통요인과 사회경제적 요인으로 구분하여 전자상거래를 사회경제적 요인으로 간주하였다. 그리고 이 사회경제적 요인으로서의 전자상거래에 의한 택배서비스시장의 인과관계성을 그랜저-심즈(Granger-Sims) 인과관계검정을 이용하여 분석하였다. 분석결과, 한국의 전자상거래는 EDI(전자문서교환)도입업체수, 인터넷 쇼핑몰수, 인터넷 이용자수, 전자상거래를 위한 법제도 체계 등의 증가에 의해 촉진되었으며, 이에 따라 택배서비스시장도 성장한 것으로 나타났다. 특히 정부주도에 의한 정보화추진이 전자상거래를 촉진시켜 택배서비스시장에 영향을 미친 것으로 분석되었다.

• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1573-1583
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• 2016

It is necessary to check mutual correlations between related variables because housing prices are influenced by a lot of variables of the economy both internally and externally. In this paper, employing the Granger causality test, we have validated interrelated relationship between the variables. In addition, there is cointegration associations in the results of the cointegration test between the variables. Therefore, an analysis using a vector error correction model including an error correction term has been attempted. As a result of the empirical comparative analysis of the forecasting performance with ARIMA and VAR models, it is confirmed that the forecasting performance by vector error correction model is superior to those of the former two models.