• Title/Summary/Keyword: Vector Autoregression (VAR)

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The Economic Effects of Oil Tariff Reduction of Korea-GCC FTA based on VAR Model (VAR모형을 활용한 한-GCC FTA 체결 시 원유관세 인하의 경제적 효과 분석)

  • KIM, Da-Som;RA, Hee-Ryang
    • International Area Studies Review
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    • v.20 no.1
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    • pp.23-51
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    • 2016
  • This study analyzed the expected economic effects of the Korea-GCC FTA and sought strategies for industrial cooperation. To see the economic effects of Korea-GCC FTA, we analysed the effect of the oil tariff reduction of economy by Vector Autoregression(VAR) model. The estimation results shows that following the abolishment of the tariff on crude oil imports, GDP, GNI and consumption are expected to grow by 0.212%, 0.389% and 0.238%, respectively. Meanwhile, investment, export and import are estimated to drop by 0.462%, 0.413% and 0.342%, respectively. As for prices, producer prices are to rise by 6.356%p, whereas consumer prices fall by 2.996%p. In short, the Korea-GCC FTA and resultant abolishment of the tariff on crude oil imports followed by the decline in crude oil prices will result in declining prices whilst macroeconomic indices, such as GDP, GNI and consumption, will increase exerting positive effects on domestic economic growth. Also, it is necessary to proactively respond to GCC member states' industrial diversification policies for FTA-based industrial cooperation to diversify the sources of crude oil and natural gas imports for further resource risk management.

An Empirical Study on the Effects of Regulation in Online Gaming Industry via Vector Autoregression Model (벡터자기회귀(VAR) 모형을 활용한 온라인 게임 규제 영향에 대한 실증적 연구: 웹보드 게임을 중심으로)

  • Moonkyoung Jang;Seongmin Jeon;Byungjoon Yoo
    • Information Systems Review
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    • v.19 no.1
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    • pp.123-145
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    • 2017
  • This study empirically examines the effects of regulation on online gaming. Going beyond ad hoc heuristic approaches on individual behavior, we investigate the effects of regulation on dynamic changes of games or service providers. In particular, we propose three theoretical perspectives: social influence to investigate the regulation effect, the role of prior experience to determine the difference in the regulation effect size through users' prior experience, and network externalities to discover the difference in the regulation effect size according to the number of users on an online gaming platform. We use the vector autoregression methodology to model patterns of the co-movement of online games and to forecast game usage. We find that online gamers are heterogeneous. Therefore, policy makers should make suitable regulations for each heterogeneous group to effectively avoid generating gaming addicts without interrupting the economic growth of the online gaming industry.

Prediction Service of Wild Animal Intrusions to the Farm Field based on VAR Model (VAR 모델을 이용한 야생 동물의 농장 침입 예측 서비스)

  • Kadam, Ashwini L.;Hwang, Mintae
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.5
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    • pp.628-636
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    • 2021
  • This paper contains the implementation and performance evaluation results of a system that collects environmental data at the time when the wild animal intrusion occurred at farms and then predicts future wild animal intrusions through a machine learning-based Vector Autoregression(VAR) model. To collect the data for intrusion prediction, an IoT-based hardware prototype was developed, which was installed on a small farm located near the school and simulated over a long period to generate intrusion events. The intrusion prediction service based on the implemented VAR model provides the date and time when intrusion is likely to occur over the next 30 days. In addition, the proposed system includes the function of providing real-time notifications to the farmers mobile device when wild animals intrusion occurs in the farm, and performance evaluation was conducted to confirm that the average response time was 7.89 seconds.

The Impact of COVID-19 on Individual Industry Sectors: Evidence from Vietnam Stock Exchange

  • TU, Thi Hoang Lan;HOANG, Tri M.
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.7
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    • pp.91-101
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    • 2021
  • The paper examines the impact of the COVID-19 pandemic on the stock market prices. The vector autoregression model (VAR) has been used in this analysis to survey 341 stocks on the Ho Chi Minh City Stock Exchange (HOSE) for the period from January 23, 2020 to December 31, 2020. The empirical results obtained from the analysis of 11 economic sectors suggest that there is a statistically significant impact relationship between COVID-19 and the healthcare and utility industries. Additional findings show a statistically significant negative impact of COVID-19 on the utility share price at lag 1. Analysis of impulse response function (IRF) and forecast error variance decomposition (FEVD) show an inverse reaction of utility stock prices to the impact of COVID-19 and a gradual disappearing shock after two steps. Major findings show that there is a clear negative effect of the COVID-19 pandemic on share prices, and the daily increase in the number of confirmed cases, indicate that, in future disease outbreaks, early containment measures and positive responses are necessary conditions for governments and nations to protect stock markets from excessive depreciation. Utility stocks are among the most severely impacted shares on financial exchanges during a pandemic due to the high risk of immediate or irreversible closure of manufacturing lines and poor demand for basic amenities.

Estimation of Nonlinear Impulse Responses of Stock Indices by Asset Class

  • Chang, Young-Jae
    • The Korean Journal of Applied Statistics
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    • v.25 no.2
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    • pp.239-249
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    • 2012
  • We estimate nonlinear impulse responses of stock indices by asset class by the Local Projection method as suggested by Jorda (2005) to compute impulse responses. The method estimates impulse responses without the specification and estimation of the underlying multivariate dynamic system unlike the usual way of vector autoregression(VAR). It estimates Local Projections at each period of interest rather than extrapolating into increasingly distant horizons with the advantages of easy estimation and non-linear flexible specification. The Local Projection method adequately captures the nonlinearity and asymmetry of the impulse responses of the stock indices compared to those from VARs.

6-Parametric factor model with long short-term memory

  • Choi, Janghoon
    • Communications for Statistical Applications and Methods
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    • v.28 no.5
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    • pp.521-536
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    • 2021
  • As life expectancies increase continuously over the world, the accuracy of forecasting mortality is more and more important to maintain social systems in the aging era. Currently, the most popular model used is the Lee-Carter model but various studies have been conducted to improve this model with one of them being 6-parametric factor model (6-PFM) which is introduced in this paper. To this new model, long short-term memory (LSTM) and regularized LSTM are applied in addition to vector autoregression (VAR), which is a traditional time-series method. Forecasting accuracies of several models, including the LC model, 4-PFM, 5-PFM, and 3 6-PFM's, are compared by using the U.S. and Korea life-tables. The results show that 6-PFM forecasts better than the other models (LC model, 4-PFM, and 5-PFM). Among the three 6-PFMs studied, regularized LSTM performs better than the other two methods for most of the tests.

Robust estimation of sparse vector autoregressive models (희박 벡터 자기 회귀 모형의 로버스트 추정)

  • Kim, Dongyeong;Baek, Changryong
    • The Korean Journal of Applied Statistics
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    • v.35 no.5
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    • pp.631-644
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    • 2022
  • This paper considers robust estimation of the sparse vector autoregressive model (sVAR) useful in high-dimensional time series analysis. First, we generalize the result of Xu et al. (2008) that the adaptive lasso indeed has robustness in sVAR as well. However, adaptive lasso method in sVAR performs poorly as the number and sizes of outliers increases. Therefore, we propose new robust estimation methods for sVAR based on least absolute deviation (LAD) and Huber estimation. Our simulation results show that our proposed methods provide more accurate estimation in turn showed better forecasting performance when outliers exist. In addition, we applied our proposed methods to power usage data and confirmed that there are unignorable outliers and robust estimation taking such outliers into account improves forecasting.

A Study on Economic Linkages between Korea and Japan

  • Lee, Jae-Ki
    • Journal of Korea Port Economic Association
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    • v.20 no.1
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    • pp.43-55
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    • 2004
  • This paper investigates how Japanese economic shocks affect the Korean economy and analyzes the channels through which they are transmitted. Also, the relative importance of domestic and foreign shocks on the dynamics of certain key macro variables is investigated. The techniques of vector autoregression (VAR) are employed to investigate the international transmission of economic disturbances. The VAR methodology is a particularly useful means for characterizing the dynamic relationships among economic variables without imposing certain types of theoretical restrictions. The dynamic effects of Japanese economic shocks on the Korean economy are evaluated by estimating variance decompositions (VDCs) and impulse response functions (IRFs). This study supports the notion of economic dependence of a small open economy such as Korea to a large economy such as Japan.

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An Analysis of Macro Aspects Caused by Protectionism in Korea

  • Kim, Yuri;Kim, Kyunghun
    • Journal of Korea Trade
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    • v.25 no.1
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    • pp.1-17
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    • 2021
  • Purpose - The global trend of protectionism has expanded since the onset of US President Donald Trump's administration in 2017. This global phenomenon has led to a significant reduction in world trade volume and a negative impact on economic development in some countries where the external sector accounts for a large proportion of GDP. Although Korea is a country vulnerable to this deteriorating trade environment, few studies have examined the relationship between protectionism and its business cycles based on Korean data. Thus, this paper investigates the impact of protectionism on Korea's business cycle. Design/methodology - To identify future implications, we conduct a structural vector autoregression (VAR) analysis using monthly Korean data from 1994 to 2015. Macroeconomic variables in the model include the industrial production index, inflation rates, exports (or net exports), interest rates, and exchange rates. For the identification of the shock reflecting the expansion of protectionism, we use an antidumping investigation (ADI) data. Since ADIs are followed generally by the imposition of antidumping tariffs, they have no contemporaneous impact on tariffs and are also contemporaneously exogenous to other endogenous variables in the VAR model. We examine two kinds of ADI shocks i) shocks on Korean exports imposed by Korea's trading partners (ADI-imposed shocks) and ii) shocks on imports imposed by the Korean government (ADI-imposing shocks). Findings - We find that Korea's exports decline sharply due to ADI-imposed shocks; the lowest point at the third month after the initial shock; and do not recover until 24 months later. Simultaneously, the inflation rate decreases. Therefore, the ADI-imposed shock can be regarded as a negative shock on the demand curve where both production and price decrease. In contrast, the ADI-imposing shock generates a different response. The net exports decline, but the inflation rate increases. These can be seen as standard responses with respect to the negative shock on the supply curve. Originality/value - We shed light on the relationship between protectionism and Korea's economic fluctuations, which is rarely addressed in previous studies. We also consider the effects of both protective policy measures on imports to Korea imposed by the Korean government and on policy measures imposed by Korea's trading partner countries on its exports.

A Study on Macroeconomic Linkages between the USA and Japan (미일간 거시경제적 연계성에 대한 연구)

  • Lee, Jai Ki
    • International Area Studies Review
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    • v.15 no.3
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    • pp.175-188
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    • 2011
  • This study aims to examine how the U.S. economic shocks affect the Japanese economy. It is widely believed that the U.S. economy has a significant effect on the Japanese economy. Actually, the U.S. accounts for a considerable amount of Japan's exports and imports. To the economic policymakers, it is very important to know how economic disturbances generated by the U.S. are transmitted to the Japanese economy. A vector autoregression(VAR) model is employed to investigate the international transmission channel of economic disturbances. The interactions of the U.S.-Japansese economy are investigated by using variance decompositions(VDCs). The results of this study provided the evidence that the U.S. economic shocks were important for the Japanese economy during the sample period. This study supports the notion of economic dependence of smaller open economy such as Japan as compared with larger economy such as the U.S.