• East Asian Economic Review
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• v.22 no.2
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• pp.217-239
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• 2018

This paper tests empirically the causal relationship between bank loans and the monetary base before and after the adoption of inflation targeting in seven Asia-Pacific countries using Toda-Yamamoto Granger non causality test and the bootstrap test for causality. The most striking finding is that the bank loans Granger cause the monetary base during the inflation targeting period in all the countries, except Japan, which was under the influence of the quantitative easing, whereas the causality appeared diverse before the inflation targeting regime. This result implies the need for the policy makers to take the endogenous nature of the money supply into account in the modern economy.

• Journal of the Korean Data and Information Science Society
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• v.15 no.2
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• pp.485-493
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• 2004

This paper considers the test of money and income causality. Jeong (1991, 2003) developed a nonparametric causality test based on the kernel estimation method. We apply the nonparametric test to USA data of money and income. We also compare the test results with ones of the conventional parametric test.

• Journal of Technology Innovation
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• v.24 no.2
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• pp.91-113
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• 2016

The purpose of this study is to examine the causal relationship among R&D spending and variables of technology trade, and to explore promoting R&D activities and revitalizing technology trade. To analyze the causal relationship, we built a multivariate model that consists of government R&D spending, private R&D spending, technical importation and export of techniques, and employed the Granger-causality test based on an error correction model. The results show that there are five Granger-causality relationship among them in the short run, as well as there are eleven Granger-causality relationship among a total of twelve causal relationship, excluding only a unidirectional causality relationship from the government R&D spending to the export of techniques, in the long run. Besides, we attempted the impulse-response analysis on them to observe the reaction of any dynamic system in response to some external change. The significance of this paper is to make sure the causal relationship between R&D investments and the technology trade by analyzing empirically, and to suggest several implications for promoting the R&D activities and revitalizing the technology trade.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.607-617
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• 2020

This study investigates the causal relationship between public and private external debt and economic growth in developing countries. Our model includes 18 selected Asian developing and transition economies from 1995 thru 2019. We employ the dynamic heterogeneous panel data methods, pooled mean group (PMG), robust cross-sectional augmented autoregressive distributed lag (CS-ARDL), and pairwise panel causality test. The results of PMG and CS-ARDL show the existence of causality between external debt and economic growth both in the short-run and long-run. The pairwise Granger causality test found the bidirectional causal relationship runs from total external debt, public external debt, and private external debt to economic growth and economic growth to external debt. The results showed first the existence of causality in the short-run and long-run between external debt and economic growth and the second, bi-directional causality that runs from external debt to economic growth and economic growth to external debt. Both the dynamic models and robust estimator found the same inferences about the impact of main variables on economic growth in Asian developing and transition economies. The findings of this study suggest to assure debt management, investment in productive sectors, increase domestic savings, decrease external dependency, and focus on international trade.

• The Korean Journal of Applied Statistics
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• v.25 no.1
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• pp.89-99
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• 2012

This study investigates the Granger-causality between economic growth and demand for electricity in Korea, using two quarterly time-series data (real GDP and electricity consumption) for 1970:Q1 through 2009:Q4. We apply Hsiao's sequential procedure to identify a vector autoregressive model to a decision of the optimal lags in the vector error-correction model because the two time-series data contain unit roots respectively and they are cointegrated. According to the empirical results in this study, we find that Hsiao's approach to the Granger-causality indicates a bidirectional causal relation between economic growth and demand for electricity in Korea. Following the Granger and Engle's approach, we also find the statistical evidence on (1) short-run bidirectional causality between real GDP and electricity consumption, (2) bidirectional strong causality between them, and (3) long-run unidirectional causality running from demand for electricity to economic growth. Our results show an inconsistency with the existing studies on Korea's case; however, the results appear to provide more meaningful policy implications for the Korean economy and its strategy of sustainable growth.

• International Commerce and Information Review
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• v.8 no.2
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• pp.299-312
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• 2006

This study examines the relations among wage differentials, trade, and productivity in Korea, using the methodology of Granger causality and vector error correction modelling. Cointegration test results over the 1975-2004 period indicate that all the test variables are cointegrated. Therefore, wage differentials, trade, and productivity are all related in the long run. We found some evidence on long-run relationship, while there is no short-run relationship between three test variables. First, trade and wage differentials have positively and bi-directionally Granger causality in the long-run. Second, productivity Granger causes negatively wage differentials in the long-run. Finally, productivity Granger causes positively trade in the long-run. These results explain partially the current theoretical predictions for wage inequality as well as supports the productivity-led growth hypothesis in the Korean economy.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.837-848
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• 2021

Evaluating or predicting the effectiveness of economic policies is an important issue, but it is difficult to find an economic variable which causes a significant result because there are numerous variables that cannot be taken into account. A randomized controlled experiment is the best way to investigate causality, but it is not realistically possible to control through randomization and intervention in time series data such as macroeconomic data. Although some analysis methods have been proposed to find causality, the methods such as Granger causality method and Chow test are insufficient to explain causality. Recently, Pfister et al. (2019) proposed invariant causal prediction methods which can be applicable in time series data. In this paper, we introduce the method of Pfister et al. (2019) and use the method to find macroeconomic variables invariantly affecting the won-dollar exchange rate.

• Journal of Navigation and Port Research
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• v.42 no.5
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• pp.357-364
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• 2018

Colombo noticeably became the most economical gateway to the Indian subcontinent, in terms of cost as well as time. The Colombo Port Expansion Project (CPEP) started commencement with the purpose of accommodating mega ships, under the long-term strategies of making Colombo the hub of South Asia. In this context, the purpose of this study is to investigate the causal relationship between Indian ports' originated container traffic, and total transshipments of the port of Colombo, and also to identify the nature of the causality between the two variables, evaluating Granger causality test results. It finds unidirectional causality from total transshipments of Colombo to Indian ports' originated transshipments in the port of Colombo. It suggested that ongoing port expansion projects, opening up for new markets and attracting new shipping lines in the port of Colombo, have generated significant impact on Indian ports' container traffic, via the port of Colombo. Findings would be valuable for future forecasting of container traffic in Colombo port and the policy-making process in the port as well.

• 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.

• Journal of Climate Change Research
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• v.9 no.2
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• pp.171-179
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• 2018

The causal relationship between El Nino-Southern Oscillation (ENSO) and winter climate variability in Korea is tested by analyzing Korea Meteorological Administration Automatic Synoptic Observing System datasets for the past 59 years. Consistent with previous studies, positive phase of ENSO (El Nino) tends to cause warmer temperature and heavier precipitation in Korea in early winter with three-week lead time. This causality is quantified by performing Granger causality test. It turns out that ENSO explains an additional 9.25% of the variance of early-winter temperature anomalies in Korea, beyond that already provided by temperature itself. Likewise, 22.18% additional information is gained to explain early-winter precipitation variance by considering ENSO. This result, which differs from simple lead-lag correlation analysis, suggests that ENSO needs to be considered in predicting early-winter surface climate variability in Korea.