• Journal of Korea Port Economic Association
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• v.31 no.2
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• pp.55-67
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• 2015

This study analyzes the relationship between shipping profit and market return in the tramp trade from January 2000 to October 2014. First, we carry out the causality test and find a causal relationship between the studied variables. Second, the estimates from the Johansen cointegration test show that shipping profit is cointegrated with market return, which implies that a long-run relationship exists among the variables. The empirical results thus imply that shipping firms need diverse risk management strategies.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.12
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• pp.271-282
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• 2021

In recent years, a significant number of empirical studies have examined the relationship between export and economic growth in India. However, this study analyses the relationship between exports and economic growth through the time series model. The main aim of this study is to investigate the causal relationship between exports and economic growth in India. The VAR model was used for the period 1961 to 2015 after verifying the stationarity of the variables through using Augmented Dickey-Fuller and Phillip-Perron tests. The Indian export sector has been found to have a significant and positive impact on economic growth and other long-term economic activities. The study also employed the Granger causality test to check the direction of causality and found that RXGS, RGDP, RPFC, and RGFC had a unidirectional relationship and RXGS and RMGS had a bidirectional relationship in long run. Also, the findings of this study suggest that a steady-state between exports and economic growth can be achieved in India over a long period. The overall outcome of this study provides a testimony of the fact that the export sector plays a vital role in economic growth in India and also leads to the long-term growth of other economic activities.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.9
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• pp.165-176
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• 2021

The paper has used the Solow-Swan growth model to analyze the long-term impact of credit market development and stock market development on economic growth in Asia from 2000 to 2019. The empirical model is performed with panel cointegration analysis by Common Correlated Effects (CCE) method with cross-sectional dependencies. The results find that there exists a cointegration relationship among stock market, credit market development, and economic growth. These results also show that financial structure improves the exact impact of financial development on economic growth, namely the opposite effect of stock market development and credit market development. Moreover, the Granger causality test reveals a bi-directional relationship between credit market development and economic growth, while only unidirectional causality from stock market development to economic growth for the whole group panel. And it is different for a specific country, according to Kónya's test. The view of the new structuralism does not apply in the Asian financial system when we estimate the Nonlinear Autoregressive Distributed Lag model (NARDL) to analyze the asymmetric relationship between financial structure and economic growth. On the whole, policymakers can draw on the findings to provide policy implications to improve their country's financial system as well as pursue the goal of sustainable economic growth.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.325-334
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• 2021

This study aims to investigate whether economic growth is elevated by banking industry development in Jordan. The study adopts time-series econometric methodologies, which comprise the bounds testing approach within the autoregressive distributed lag (ARDL) and the conditional causality analysis. Consistent with the assumptions of the adopted methodology, the study utilized annual time-series data for a relatively long period of thirty-nine years, between 1980 and 2018. The empirical results show that Jordan's economic growth is strongly responsive in respect to any changes in banking industry development. Also, the results reveal the harmful impact of rising lending interest rate; as this rate increases, economic growth will decrease. The findings are in line with the conceptual arguments of the supply-leading hypothesis, which confirmed that banking development is considered as one of the main pillars that have stimulating effects on economic growth. The evidence of the current study may provide important implications for policymakers and bankers. Those professionals should work to maintain a stable regulatory system that enhances the banking system function in activating economic growth. Also, a considerable focus should be placed on designing a steady interest rate policy to avoid the inherently undesirable impacts of high-interest rates on the Jordanian economy.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.1-9
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• 2021

UAE has rapidly developed into one of the leading global financial hubs, with significant transformations in its stock exchanges. In its attempt at economic diversification in the last two decades, the country has also taken a lead in the GCC region in introducing extensive reforms to attract FDI to the Emirates. However, oil price volatilities have posed a significant challenge to all oil-exporting countries. The main aim of this study is to explore the impact of economic diversification and oil price on the UAE stock market. The study applies Granger Causality and Vector Autoregressive Model on monthly Abu Dhabi stock exchange index, Dubai Fateh crude oil spot price, and FDI inflows during 2001-19. The short-term interbank rate has been included as a monetary policy variable. The results show a substantial difference between the two phases of reforms. Oil price and Abu Dhabi stock index show bidirectional relationship during 2001-09 but no causality was found during 2010-19. Furthermore, the second phase was characterized by unidirectional causation from FDI to ADX index. This study highlights FDI inflows as a key driver of stock market performance during the last decade and emphasizes the success of the intense reforms in the UAE initiated for the diversification of its economy.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.191-199
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• 2021

The study examines the causal relationship between financial development and economic growth through trade openness for the leading ASEAN countries (Indonesia, the Philippines, Malaysia, Singapore, Thailand, and Vietnam). The study employs a panel data for the period of 25 years spanning from 1995 to 2015 for the six countries, yielding a balanced panel of 150 observations. Fixed effect model (FEM) and random effect model (REM) are used for the panel data, following the Hausman test performed for model selection. The trivariate Granger causality test is also used to check for possible relationship between the variables. The results show that REM is chosen based on the Hausman test result, suggesting that the trade openness has a positive association with growth whereas the financial development is positively, but insignificantly associated with growth. The reason for this is that the financial development and economic growth may be related to each other. The results are, then, further explored and confirmed by the causality test. That is, the financial development and the economic growth, through the trade openness, are found to have bidirectional positive relationships. This implies that there would be shortcomings when ignoring the presence of trade openness, which positively impacts the relationship between finance and growth.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.1
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• pp.13-24
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• 2022

The main goal of this study is to look at how South Korea can catch up to the rest of the world through policy-driven structural change and manufacturing revolutions. To achieve the objective, this study used annual data on real exports and real GDP from the World Development Indicator WDI of South Korea for the period 1960 to 2019. The study's goal is to use econometrics to detect this policy-driven structural change trend. Multiple nonlinear Granger causality test was used to accomplish this. The findings revealed structural breaks and nonlinearities in the dynamic link between South Korea's real GDP and real exports. Furthermore, results also show evidence of multiple structural breaks in South Korean data. South Korea's economic catch-up was the result of a constant reevaluation of industrial policies, readjustment, and structural change to constantly explore and utilize comparative advantage, realizing economies of scale at the global level, and reallocating and redistribution of resources towards productive sectors with high value-added output, according to econometric analysis. If South Korea would have not done this structural change this miracle to escape the middle-income trap would not have been possible. These findings support the descriptive evidence of structural change in favor of manufacturing revolutions and value addition industry development in South Korea.

• Journal of Distribution Science
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• v.11 no.10
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• pp.63-72
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• 2013

Purpose - This study analyzes the relationship and dynamic interactions between stock price index, interest rate, price index, and housing price indices using Korean monthly data from 2000 to 2013, based on a VAR model. This study also examines Granger causal relationships among these variables in order to determine whether the time series of one is useful in forecasting another, or to infer certain types of causal dependency between stochastic variables. Research design, data, and methodology - We used Korean monthly data for all variables from 2000: M1 to 2013: M3. First, we checked the correlations among different variables. Second, we conducted the Augmented Dickey-Fuller (ADF) test and the co-integration test using the VAR model. Third, we employed Granger Causality tests to quantify the causal effect from time series observations. Fourth, we used the impulse response function and variance decomposition based on the VAR model to examine the dynamic relationships among the variables. Results - First, stock price Granger affects interest rate and all housing price indices. Price index Granger, in turn, affects the stock price and six metropolitan housing price indices. However, none of the Granger variables affect the price index. Therefore, it is the stock markets (and not the housing market) that affects the housing prices. Second, the impulse response tests show that maximum influence on stock price is its own, and though it is influenced a little by interest rate, price index affects it negatively. One standard deviation (S.D.) shock to stock price increases the housing price by 0.08 units after two months, whereas an impulse shock to the interest rate negatively impacts the housing price. Third, the variance decomposition results report that the shock to the stock price accounts for 96% of the variation in the stock price, and the shock to the price index accounts for 2.8% after two periods. In contrast, the shock to the interest rate accounts for 80% of the variation in the interest rate after ten periods; the shock to the stock price accounts for 19% of the variation; however, shock to the price index does not affect the interest rate. The housing price index in 10 periods is explained up to 96.7% by itself, 2.62% by stock price, 0.68% by price index, and 0.04% by interest rate. Therefore, the housing market is explained most by its own variation, whereas the interest rate has little impact on housing price. Conclusions - The results of the study elucidate the relationship and dynamic interactions among stock price index, interest rate, price index, and housing price indices using VAR model. This study could help form the basis for more appropriate economic policies in the future. As the housing market is very important in Korean economy, any changes in house price affect the other markets, thereby resulting in a shock to the entire economy. Therefore, the analysis on the dynamic relationships between the housing market and economic variables will help with the decision making regarding the housing market policy.

• Land and Housing Review
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• v.13 no.4
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• pp.45-53
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• 2022

This paper investigates empirically the lead-lag relation between the 'apartment price index' and 'Internet search volume'. This study uses Naver Trend Index as a proxy for Internet search volume. An increase in Internet search volume on the apartment price index indicates an increase in people's attention to an apartment. Different from previous studies exploring the relation between 'the released price index of the apartment' and 'Naver Trend Index', this study investigates the relation of the Naver Trend Index with 'the fundamental price component of an apartment' and 'the transitory price component of an apartment', respectively. The results of the Granger causality test reveal that there are bidirectional Granger causalities between the 'released price' and Naver Trend Index. In addition, the 'fundamental price component of an apartment' and Naver Trend Index have a feedback relation, while 'the transitory price component of an apartment' Granger causes the Naver Trend Index uni-directionally. The impulse response function analysis indicates that the shock of apartment prices increases Naver Trend Index in the first month. Overall, The close relationship between apartment prices and Naver Trend Index suggests that increases in the movement of apartment prices are positively associated with public attention on the apartment market.

• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.33-53
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• 2021

In the crossroads of social change caused by the spread of the Fourth Industrial Revolution and the prolonged COVID-19, the Korean government announced the Digital New Deal policy on July 14, 2020. The Digital New Deal policy's primary goal is to create new businesses by accelerating digital transformation in the public sector and industries around data, networks, and artificial intelligence technologies. However, in a rapidly changing social environment, information asymmetry of the future benefits of technology can cause differences in the public's ability to analyze the direction and effectiveness of policies, resulting in uncertainty about the practical effects of policies. On the other hand, the media leads the formation of discourse through communicators' role to disseminate government policies to the public and provides knowledge about specific issues through the news. In other words, as the media coverage of a particular policy increases, the issue concentration increases, which also affects public decision-making. Therefore, the purpose of this study is to verify the dynamic relationship between the media coverage and the stock market on the Korean government's digital New Deal policy using Granger causality, impulse response functions, and variance decomposition analysis. To this end, the daily stock turnover ratio, daily price-earnings ratio, and EWMA volatility of digital technology-based companies related to the digital new deal policy among KOSDAQ listed companies were set as variables. As a result, keyword search volume, daily stock turnover ratio, EWMA volatility have a bi-directional Granger causal relationship with media coverage. And an increase in media coverage has a high impact on keyword search volume on digital new deal policies. Also, the impulse response analysis on media coverage showed a sharp drop in EWMA volatility. The influence gradually increased over time and played a role in mitigating stock market volatility. Based on this study's findings, the amount of media coverage of digital new deals policy has a significant dynamic relationship with the stock market.