• Title/Summary/Keyword: Causality

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A Study on the Efficiency of KTB Forward Markets (국채선도금리(Forward rate)의 효율성(Efficiency)에 관한 연구)

  • Moon, Gyu-Hyun;Hong, Chung-Hyo
    • The Korean Journal of Financial Management
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    • v.22 no.2
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    • pp.189-212
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    • 2005
  • This study examines the interactions between KTB spot and futures markets using the daily prices from March 4, 2002 to January 31, 2005. We use Granger causality test, impulse Response Analysis and Variance Decomposition through vector autoregressive analysis (VAR). However, considering the long-term relationships between the level variables of KTB spot and futures, we introduced Vector Error Correction Model. The main results are as follows. According to the results of Granger-causality test and impulse response analysis, we find that the yields of KTB forward have a great influence on the change of KTB spot but not vice versa. In terms of volatility analysis, there is no inter-dependence between KTB forward and spot markets. In the variance decomposition analysis we find that the short-term KTB forward has much more impact on the KTB spot market than the long-term KTB forward does. We think these results are meaningful for bond investors who are in charge of capital asset pricing valuation, risk management and international portfolio management.

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The Impact of Regional Economic Growth on Intraregional Disparities in Korea (지역경제 성장에 따른 지역 내부의 경제적 격차 추정에 관한 연구)

  • Lee, Ju-Han;Kim, Donghyun
    • Journal of the Korean Regional Science Association
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    • v.36 no.3
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    • pp.29-40
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    • 2020
  • The aims of this study to identify the relationship between regional economic growth and intraregional regional disparities. The 16 metropolitan area, the Capital region and the southeastern region of Korea were put in the spatial scope and the time range from 2005 to 2016. Regional gross domestic product data were used to show regional growth and intraregional disparity. Panel data for each spatial unit were established, panel unit root test and panel cointegration test were conducted to check the stability of the data. The DOLS method was used to identify relationship between regional economic growth and intraregional disparity, and the VECM model and Granger causality test was conducted to verify causality. The result of analysis of 16 metropolitan area units showed that the intraregional disparity increases as regional economic growth progresses. When the regional gross domestic product increased by 1%, the intraregional disparity increased by 1.258%, and there are short-term and long-term causality. Both the Capital region and the southeastern region had a mutual relationship between regional economic growth and intraregional disparity, but the disparity in the Capital region showed an increase and the southeastern region showed a decrease. The results of this study show that the regional disparity is increasing nationwide, but the Capital region and the southeastern region showed different stages of growth.

A Study on Regionalization in the World Crude Oil Markets Using Cointegration and Causality Analysis (공적분과 인과관계 분석을 통한 국제원유시장의 지역화 연구)

  • Kim, Jinsoo;Heo, Eunnyeong;Kim, Yeonbae
    • Environmental and Resource Economics Review
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    • v.16 no.2
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    • pp.213-237
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    • 2007
  • Discussions on regionalization of the world crude oil markets have provided important implications for the establishment of national energy policies. In particular, due to arbitrage trading, if these markets are regionalized, Korea who imports approximately 80% of the annual oil consumption from a single region may be faced with a crucial problem. Therefore, in this study, we analyzed regionalization of the world crude oil markets using causality analysis as well as cointegration method to consider temporal relationship and time lags. To analyze regionalization, we chose Dubai price for the Middle East market, Brent for the European, WTI for the U.S., and Tapis for the East Asian. For the case that long-run equilibrium existed between market prices, we used vector error correction model to analyze causal relationship, and for the case that equilibrium did not exist, we used Hsiao (1981)'s framework that can consider asymmetric time lags in the model for causality analysis. By the results of cointegration analysis, there did not exist long-run equilibrium among Dubai price and the other prices. However, we found the causal relationship among Dubai price and the other prices with one to four weeks time lags. Therefore, in effect, we could conclude that the world crude oil markets are unified supporting Adelman (1984)'s hypothesis.

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The Causality among Residents' Loyalty to an Environmental Festival and Its Influential Factors: With Special Reference to Hampyung Butterfly Festival (지역주민의 환경축제 충성도와 그 영향요인 간의 인과관계 - 함평나비축제를 중심으로 -)

  • Lee, Kyeong-Jin;Song, Myung-Gyu
    • Journal of Environmental Impact Assessment
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    • v.23 no.5
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    • pp.337-352
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    • 2014
  • The main purposes of this study are to find the causality among residents' loyalty to an environmental festival and its influential factors and, based upon the findings, to explore environmental festivals' developmental vision with special reference to Hampyung Butterfly Festival. Under these aims, this study applies structural equation modeling(SEM). The structural model for SEM analysis is composed of four independent variables which consist of residents' attachment(RA) to their region where its own environmental festival is provided, residents' participational intention(RP) to the festival, the economic effects(EE) of the festival, and the communication(CM) between the residents and the festival providers, one intermediate variable, residents' satisfaction(RS) from the festival, and one final dependent variable, residents' loyalty(RL) to the festival. The causality among these variables is hypothesized as follows; Among the independent variables, RP, EE, and CM have effects only on RS and RA has an effect on both RS and RL. And RS has an effect on RL. The facts found from the SEM are summed up as follows; First, (1) RP and CM turn out to have statistically significant effects on RS, (2) RA is confirmed to have a statistically very significant effect on both RS and RL, and (3) RS is also proved to show a statistically very significant effect on RL. Second, the total effects on RL of independent variables are stronger in the order of RA, CM, and RP. Third, EE seems to have no effect on RS, consequently no effect on RL, either. The reason why EE has no effect looks like to be due to environmental festivals' peculiar features. These findings offer the following suggestions for the future of environmental festivals in the part of festival providers. Firstly, to be successful in the festival, they have to provoke RL above all. Second, to do so, they need to encourage RA, CM, and RP in the mentioned order in the long run. Third, but for a short period, they had better concentrate upon promoting RS.

Prediction and Causality Examination of the Environment Service Industry and Distribution Service Industry (환경서비스업과 물류서비스업의 예측 및 인과성 검정)

  • Sun, Il-Suck;Lee, Choong-Hyo
    • Journal of Distribution Science
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    • v.12 no.6
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    • pp.49-57
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    • 2014
  • Purpose - The world now recognizes environmental disruption as a serious issue when regarding growth-oriented strategies; therefore, environmental preservation issues become pertinent. Consequently, green distribution is continuously emphasized. However, studying the prediction and association of distribution and the environment is insufficient. Most existing studies about green distribution are about its necessity, detailed operation methods, and political suggestions; it is necessary to study the distribution service industry and environmental service industry together, for green distribution. Research design, data, and methodology - ARIMA (auto-regressive moving average model) was used to predict the environmental service and distribution service industries, and the Granger Causality Test based on VAR (vector auto regressive) was used to analyze the causal relationship. This study used 48 quarters of time-series data, from the 4th quarter in 2001 to the 3rd quarter in 2013, about each business type's production index, and used an unchangeable index. The production index about the business type is classified into the current index and the unchangeable index. The unchangeable index divides the current index into deflators to remove fluctuation. Therefore, it is easy to analyze the actual production index. This study used the unchangeable index. Results - The production index of the distribution service industry and the production index of the environmental service industry consider the autocorrelation coefficient and partial autocorrelation coefficient; therefore, ARIMA(0,0,2)(0,1,1)4 and ARIMA(3,1,0)(0,1,1)4 were established as final prediction models, resulting in the gradual improvement in every production index of both types of business. Regarding the distribution service industry's production index, it is predicted that the 4th quarter in 2014 is 114.35, and the 4th quarter in 2015 is 123.48. Moreover, regarding the environmental service industry's production index, it is predicted that the 4th quarter in 2014 is 110.95, and the 4th quarter in 2015 is 111.67. In a causal relationship analysis, the environmental service industry impacts the distribution service industry, but the distribution service industry does not impact the environmental service industry. Conclusions - This study predicted the distribution service industry and environmental service industry with the ARIMA model, and examined the causal relationship between them through the Granger causality test based on the VAR Model. Prediction reveals the seasonality and gradual increase in the two industries. Moreover, the environmental service industry impacts the distribution service industry, but the distribution service industry does not impact the environmental service industry. This study contributed academically by offering base line data needed in the establishment of a future style of management and policy directions for the two industries through the prediction of the distribution service industry and the environmental service industry, and tested a causal relationship between them, which is insufficient in existing studies. The limitations of this study are that deeper considerations of advanced studies are deficient, and the effect of causality between the two types of industries on the actual industry was not established.

Time Series Analysis of the Relationship between Housing Consumer Sentiment and Regional Housing Prices in Seoul (서울시 주택소비심리와 권역별 주택가격의 시계열적 관계분석)

  • Yang, Hye-Seon;Seo, Won-Seok
    • Journal of Cadastre & Land InformatiX
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    • v.50 no.1
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    • pp.125-141
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    • 2020
  • This study investigated the time-series relationship between housing consumer sentiment and housing prices in the five major districts in Seoul and also analyzed the effect of the housing consumer sentiment on housing prices using Granger Causality and VEC (Vector Error Correction) models. To describe the key results, first of all, housing consumer sentiment and regional housing market prices were closely related to each other, and the consumer sentiment strongly affected the change of housing prices. Second, the housing consumer sentiment was confirmed to have a discriminatory effect on the housing prices among the districts in Seoul in the short term. Specifically, the housing price of the east southern district (ESD) was the main reason for the change in housing consumer sentiment in Seoul, and that the resulting impact was transferred to other districts. Third, it was analyzed that regions other than the ESD would increase the housing prices in the long term as the housing consumer sentiment turned positive, but that the ESD would see a steady tone. Fourth, in the case of relative influence by district, housing (apartment) price fluctuation in a district was generally found to be most affected by adjacent or competitive districts. Through these findings, this study confirmed that there is a clear causality between housing consumer sentiment and housing prices in each district of Seoul and that there is a discriminatory influence on housing consumer sentiment among the districts.

An Analysis on Causalities Among GDP, Electricity Consumption, CO2 Emission and FDI Inflow in Korea (한국의 경제성장, 전력소비, CO2 배출 및 외국인직접투자 유입 간 인과관계 분석)

  • Park, Chang-dae;Kim, Sung-won;Park, Jung-gu
    • Journal of Energy Engineering
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    • v.28 no.2
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    • pp.1-17
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    • 2019
  • This article analyzes causal relationships among gross domestic product(GDP), electricity consumption, carbon dioxide($CO_2$) emission and foreign direct investments(FDI) inflow of Korea over the period from 1976 to 2014, using unit root test, cointegration test, and vector error correction model(VECM). As the results, this article found (1) a long-run bi-directional causality between GDP and electricity consumption, which may imply a negative impact of electricity consumption-saving policy on economic growth, (2) uni-directional short- and long-run causalities running from $CO_2$ emission to GDP, and a uni-directional long-run causality running from $CO_2$ emission to electricity consumption, which can result in a negative impact of $CO_2$ emission reduction policy on economic growth and electricity consumption, (3) a uni-directional long-run causality running from FDI to GDP, and uni-directional short- and long-run causalities running from FDI to electricity consumption, which may result from relatively lower electricity prices than investing countries, (4) no causality between FDI and $CO_2$ emission, which is based on the characteristics of FDI composed of service industries. Considering the above causal relationships among the four variables, the policy implication needs to focus on the electricity demand management based on the relevant R&Ds, and on the gradual transition from fossil fuel- to renewable-energy. Adaptive policy to increase the FDI inflow is also needed.

An Empirical Study on the Causalities and Effects between International Trade and Economic Growth in China (중국의 국제무역과 경제성장간의 인과관계 및 파급효과)

  • Kim, Jong-Sup
    • International Area Studies Review
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    • v.13 no.1
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    • pp.55-79
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    • 2009
  • This papers studies the causalities and effects on the relationship between international trade and economic growth in China for the period of 1950-2007, using the unit root test, the Granger causality test, the cointegration test, VAR model, and VECM. The results of this study are as follows: Firstly, in the unit root test, I found that each time series was unstable one that has unit root. Secondly, in the Granger Causality test, this papers shows that variable dlexp and dlinp influence on dlgdp and dlgdd, while bilateral causality relation between dlexp and dlgdp, dlexp and dlgdd for the whole period, for the whole period, pre-reform period and post-reform period. Thirdly, there is no cointegraion relation between lgdp(or dlgdp, lgdd, dlgdd) and lexp, linp for lgdd-limp in the whole period, and pre-reform period, while no cointegration relation for the post-reform period. Finally, in the impulse-response test, it was proved that lgdp represents (-) correlation with lexp for the whole period. Thorough the variance decomposition test, it was proved that linp(or dlinp) is the most affected variable of the each data and relation between linp(or dlinp) and lexp(or dlexp) has become bigger recently.

An Analysis of Relationship between Social Sentiments and Cryptocurrency Price: An Econometric Analysis with Big Data (소셜 감성과 암호화폐 가격 간의 관계 분석: 빅데이터를 활용한 계량경제적 분석)

  • Sangyi Ryu;Jiyeon Hyun;Sang-Yong Tom Lee
    • Information Systems Review
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    • v.21 no.1
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    • pp.91-111
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    • 2019
  • Around the end of 2017, the investment fever for cryptocurrencies-especially Bitcoin-has started all over the world. Especially, South Korea has been at the center of this phenomenon. Sinceit was difficult to find the profitable investment opportunities, people have started to see the cryptocurrency markets as an alternative investment objects. However, the cryptocurrency fever inSouth Korea is mostly based on psychological phenomenon due to expectation of short-term profits and social atmosphere rather than intrinsic value of the assets. Therefore, this study aimed to analyze influence of people's social sentiment on price movement of cryptocurrency. The data was collected for 181 days from Nov 1st, 2017 to Apr 30th, 2018, especially focusing on Bitcoin-related post in Twitter along with price of Bitcoin in Bithumb/UPbit. After the collected data was refined into neutral, positive and negative words through sentiment analysis, the refined neutral, positive, and negative words were put into regression model in order to find out the impacts of social sentiments on Bitcoin price. After examining the relationship by the regression analyses and Granger Causality tests, we found that the positive sentiments had a positive relationship with Bitcoin price, while the negative words had a negative relation with it. Also, the causality test results show that there exist two-way causalities between social sentiment and Bitcoin price movement. Therefore, we were able to conclude that the Bitcoin investors'behaviors are affected by the changes of social sentiments.