• The Journal of the Korea Contents Association
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• v.18 no.4
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• pp.416-427
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• 2018

As the loan size of real estate PF is huge, its market ripple effect gets bigger when overdue occurs. Accordingly, the management of the delinquency rate and macroeconomic analysis are required. As the preceding research mainly proceeded with microeconomic analysis through the real estate PF data of individual banks to evaluate importance of list or analyzed core factors for delinquency, it lacked research on comprehensive real estate PF size. In order to overcome the limitations of such data, this research studied real estate PF delinquency rate of the entire market and effect relationship by the size. The research utilized the size of real estate PF loans, money supply, interest rate, consumer price index(CPI), and GDP data. Also, it applied the first model of VECM as linear relationship between at least two or more variables, following the result of co-integration test. As a result of Granger-causality test, the real estate PF loans delinquency rate is influenced by their loan size, and as a result of impulse response analysis, the interest rate is shown to be affecting delinquency rate the most. Interest rate could risesomeday and aggravate the delinquency rate of real estate PF. Also, risk exposure could be serious as the loan size increases.Therefore, the management of real estate PF delinquency rate requires continuous monitoring, tracking and observing issued loans from a macro point of view. The plans to prevent delinquency will be necessary.

• The Journal of Industrial Distribution & Business
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• v.9 no.5
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• pp.63-72
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• 2018

Purpose - This work analyzes, in detail, the specification of vector error correction model (VECM) and thus examines the relationships and impact among seven economic variables for USA - balance on current account (BCA), index of stock (STOCK), gross domestic product (GDP), housing price indices (HOUSING), a measure of the money supply that includes total currency as well as large time deposits, institutional money market funds, short-term repurchase agreements and other larger liquid assets (M3), real rate of interest (IR_REAL) and household credits (LOAN). In particular, we search for the main explanatory variables that have an effect on stock and real estate market, respectively and investigate the causal and dynamic associations between them. Research design, data, and methodology - We perform the time series vector error correction model to infer the dynamic relationships among seven variables above. This work employs the conventional augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root techniques to test for stationarity among seven variables under consideration, and Johansen cointegration test to specify the order or the number of cointegration relationship. Granger causality test is exploited to inspect for causal relationship and, at the same time, impulse response function and variance decomposition analysis are checked for both short-run and long-run association among the seven variables by EViews 9.0. The underlying model was analyzed by using 108 realizations from Q1 1990 to Q4 2016 for USA. Results - The results show that all the seven variables for USA have one unit root and they are cointegrated with at most five and three cointegrating equation for USA. The vector error correction model expresses a long-run relationship among variables. Both IR_REAL and M3 may influence real estate market, and GDP does stock market in USA. On the other hand, GDP, IR_REAL, M3, STOCK and LOAN may be considered as causal factors to affect real estate market. Conclusions - The findings indicate that both stock market and real estate market can be modelled as vector error correction specification for USA. In addition, we can detect causal relationships among variables and compare dynamic differences between countries in terms of stock market and real estate market.

• Journal of Science and Technology Studies
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• v.16 no.1
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• pp.29-61
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• 2016

This paper explains the one of the most problematic factor in the society that leads to social inequality - increase in non-regular work. Theoretically, this expansion of non-regular work can be explained by technologies that are designed to save the labor force, especially since corporations in Korea have strategies to replace the regular workers with temporary workers, to save money. OECD also noted that Korea's income inequality is pretty high in ranking when compared with the rest of the OECD members, and says that globalization and technological innovation are the factors of this problem. To refine the argument, this study also looks at relationship between development made in sciences - which can be stated as a proxy variable to look at the advances made in technology - and expansion of temporary work force by using VAR methodology. Based on the results of this analysis in the future temporary/regular workers ratio started with decline, then turn to rise. These temporary/regular workers ratio sustained growth prediction shows that the expansion of the temporary expansion contributes to instability and social inequality in the labor market and technological change are interrelated.

• Informatization Policy
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• v.26 no.4
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• pp.20-35
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• 2019

We empirically analyze the effects of psychological factors, such as the fear of parenting, on fertility rates. An index is calculated based on the share of negative news articles on child care in all social articles from 2000 to 2018. The analysis result shows that as the index increases, the fertility rate after three years falls. This result is repeated in the correlation analysis, simple regression, and VAR analysis. According to Granger causality analysis, it is found that the relation between the index and the fertility rate after three years is not just a simple correlation but a causal relationship. There are differences among age groups. The fertility rate of women in their 20s and 30s shows a significant response to the index, but that of the 40s does not. The index affects the birthrate of first child, but do not affect the birthrate of second or more children. These results are consistent with the intuition that younger women are more likely to be affected by the negative articles about parenting, but not to those who have already experienced childbirth. This study is meaningful in that a significant index for predicting social phenomena is extracted beyond the limited use of news big data such as a simple keyword mention volume monitoring. Also, this big data-based index is a 3-year leading indicator for fertility, which provides the advantage of providing information that helps early detection.

• The Journal of the Korea Contents Association
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• v.20 no.1
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• pp.304-316
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• 2020

Laos is rich in natural resources but lacks the capital to develop them. Partly alleviating the shortage is FDI from neighboring countries, especially Thailand. Not only does this contribute to directly increasing GDP by increasing effective demand, it also has an additional GDP increase effect by expanding Laos' production capacity. Laos' exports mostly consist of mineral resources and electricity. This, too, contributes to an increase in GDP by increasing the effective demand. Thailand accounts for more than 40 percent of Laos' exports. This paper tries to confirm the economic impact on Laos in Thailand through a econometric analysis of Laos' GDP, Laos' exports to Thailand and Thailand's FDI to Laos. It turns out that economic ties with Thailand, including exports to Thailand and Thailand's FDI, play a very important role in Laos' economic growth. Laos recently recorded relatively robust economic growth, but its driving force is weak. That's because Laos' growth engines are very limited and have no resilience to external shocks. Moreover, economic growth has not been linked to an increase in employment because the economy is not diversified and growth in the hydroelectric power sector does not lead to growth in other sectors. Given this, Laos needs to actively take advantage of its geographical proximity to Thailand. It is necessary to create a more active environment for the inflow of FDI in Thailand, to foster resource-based and labor-based manufacturing to take advantage of the Thai market.

• Korea Real Estate Review
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• v.24 no.1
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• pp.39-52
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• 2014

This study examines the degree of global co-movement & spillover effect among the housing price of ten major countries of OECD including Korea, based on the 3 hypothesis. The data used in this study is quarterly house price index of OECD countries from 1975 to 2012. VAR model is used to analyze the co-movement, and Granger causality methodology is used for the analysis of Spillover Effect. It is found that entire period of study is that the global house prices showed the co-movement, but the coefficient was weak. Since 2008 global financial crisis, the co-movement increased significantly and the adjusted R-square of this model increased 78% compared to the entire period (1975-2012). In general, all hypotheses in this study were significant, and the common shock hypothesis were most significant. In case of Korea, the degree of co-movement was weak compared to the other countries and spillover effect was independent since 2008.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.222-230
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• 2022

Recently, Korea's cultural content industry is developing, and behind the growing recognition around the world is the real-time sharing service of global network users due to the development of science and technology. In particular, in the case of YouTube, its propagation power is fast and powerful in that everyone, not limited users, can become potential video providers. As more than 80% of mobile phone users are using YouTube in Korea, YouTube's information means that psychological factors of users are reflected. For example, information such as the number of video views, likes, and comments of a channel with a specific personality shows a measure of the channel's personality interest. This is highly related to the fact that information such as the frequency of keyword search on portal sites is closely related to the stock market economically and psychologically. Therefore, in this study, YouTube information from a representative entertainment company is collected through a crawling algorithm and analyzed for the causal relationship with major variables related to stock prices. This study is considered meaningful in that it conducted research by combining cultural content, IT, and financial fields in accordance with the era of the fourth industry.

• Journal of Korea Port Economic Association
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• v.38 no.4
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• pp.107-118
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• 2022

In this study, daily data from January 2002 to June 2022 were used to investigate the relationship between risk-return relationship and market fear, uncertainty, stock market, and maritime freight index for the crude oil market. For this study, the time varying EGARCH-M model was applied to the risk-return relationship, and the wavelet consistency model was used to analyze the relationship between market fear, uncertainty, stock market, and maritime freight index. The analysis results of this study are as follows. First, according to the results of the time-varying risk-return relationship, the crude oil market was found to be related to high returns and high risks. Second, the results of correlation and Granger causality test, it was found that there was a weak correlation between the risk-return relationship and VIX, EPU, S&P500, and BDI. In addition, it was found that there was no two-way causal relationship in the risk-return relationship with EPU and S&P500, but VIX and BDI were found to affect the risk-return relationship. Third, looking at the results of wavelet coherence, it was found that the degree of the risk-return relationship and the relationship between VIX, EPU, S&P500, and BDI was time-varying. In particular, it was found that the relationship between each other was high before and after the crisis period (financial crisis, COVID-19). And it was found to be highly associated with organs. In addition, the risk-return relationship was found to have a positive relationship with VIX and EPU, and a negative relationship with S&P500 and BDI. Therefore, market participants should be well aware of economic environmental changes when making decisions.

• 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.