• 제목/요약/키워드: Var Model

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How to improve oil consumption forecast using google trends from online big data?: the structured regularization methods for large vector autoregressive model

  • Choi, Ji-Eun;Shin, Dong Wan
    • Communications for Statistical Applications and Methods
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    • 제29권1호
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    • pp.41-51
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    • 2022
  • We forecast the US oil consumption level taking advantage of google trends. The google trends are the search volumes of the specific search terms that people search on google. We focus on whether proper selection of google trend terms leads to an improvement in forecast performance for oil consumption. As the forecast models, we consider the least absolute shrinkage and selection operator (LASSO) regression and the structured regularization method for large vector autoregressive (VAR-L) model of Nicholson et al. (2017), which select automatically the google trend terms and the lags of the predictors. An out-of-sample forecast comparison reveals that reducing the high dimensional google trend data set to a low-dimensional data set by the LASSO and the VAR-L models produces better forecast performance for oil consumption compared to the frequently-used forecast models such as the autoregressive model, the autoregressive distributed lag model and the vector error correction model.

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

  • 김다솜;나희양
    • 국제지역연구
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    • 제20권1호
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    • pp.23-51
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    • 2016
  • 한-GCC FTA 체결은 안정적인 에너지 자원의 확보에서 뿐만 아니라 향후 대규모 소비시장으로서 GCC의 성장 잠재성과 한국과의 보완적인 산업 구조를 고려해 볼 때 그 중요성이 크다. 최근 한-GCC FTA의 필요성이 제기되고 있는 시점에서 한-GCC FTA의 경제적 기대 효과에 대하여 분석하고 FTA의 조속한 체결의 필요성을 제시하고자 하였다. 한-GCC FTA의 경제적 효과를 알아보기 위하여, 본 연구에서는 원유관세 인하를 통한 경제적 효과를 분석하기 위하여 벡터자기회귀모형(VAR: Vector Autoregression Model)을 이용하였다. 추정 결과, GDP는 총 0.212%, GNI는 0.389%, 소비는 0.238% 증가한다. 반면 투자, 수출, 수입은 각각 0.462%, 0.413%, 0.342% 감소하는 것으로 나타났다. 물가수준의 경우 생산자물가상승률은 6.356%p, 소비자물가상승률은 2.996%p 감소하는 것으로 나타났다. 즉, GCC와의 FTA를 통한 원유수입관세의 철폐 및 이로 인한 원유수입가격의 하락은 물가의 하락을 가져오는 동시에 GDP, GNI, 소비 등의 거시경제지표의 증가를 통해 우리나라 경제성장에 긍정적인 영향을 미침을 알 수 있다.

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

  • 김동영;백창룡
    • 응용통계연구
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    • 제35권5호
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    • pp.631-644
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    • 2022
  • 본 논문은 고차원 시계열 자료에 이상점이 존재하는 경우 희박벡터자기회귀모형(sparse VAR; sVAR)의 모수를 강건하게 추정하는 방법에 대해서 연구하였다. 먼저 Xu 등 (2008)이 독립인 자료에서 밝혔듯이 adaptive lasso 방법이 sVAR 모형에서도 어느 정도의 강건함을 가짐을 모의 실험을 통해 알 수 있었다. 하지만, 이상점의 개수가 증가하거나 이상점의 영향력이 커지는 경우 효율성이 현저히 저하되는 현상도 관찰할 수 있었다. 따라서 이를 개선하기 위해서 최소절대편차(least absolute deviation; LAD)와 Huber 함수를 기반으로 벌점화 시키는 adaptive lasso를 이용하여 sVAR 모형을 추정하는 방법을 본 논문에서는 제안하고 그 성능을 검토하였다. 모의 실험을 통해 제안한 로버스트 추정 방법이 이상점이 존재하는 경우에 모수 추정을 더 정확하게 하고 예측 성능도 뛰어남을 확인했다. 또한 해당 방법론들을 전력사용량 데이터에 적용한 결과 이상점으로 의심되는 시점들이 존재하였고, 이를 고려하여 강건하게 추정하는 제안한 방법론이 더 좋은 예측 성능을 보임을 확인할 수 있었다.

수입 수산물과 국내산 수산물의 가격간 유통단계별 인과성 분석 : 명태, 갈치, 조기 냉동품을 대상으로 (A Causality Analysis of the Prices between Imported Fisheries and Domestic Fisheries in Distribution Channel)

  • 차영기;김기수
    • 수산경영론집
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    • 제40권2호
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    • pp.105-126
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    • 2009
  • This study applies the cointegration theory to analyse the causality of the prices between imported fisheries and domestic fisheries in distribution channel. We've focused on the prices of import, wholesale and retail about the frozen Alaska pollack, hairtail and croaker which take up high portion and are popular among most of the consumers. In process of analysis, the unit root test was adopted to find the stability of time series data prior to the cointegration test. If the time series data was found as stable one in unit root test, we should analyse the VAR model. If unstable, the cointegratioin test was adopeted to find the long-run equilibrium relationship between the data. When the long-run equilibrium relationship was found among the price of the import, wholesale and retail price, the VECM model was adoped. If not, the differenced VAR model was adopted. The main findings of this study could be summarized as follows ; First, according to the result of the analysis on VAR model, time series data of frozen Alaska pollack was found as stable and has causality relationship and close effect was existing among the import, wholesale and retail price. Second, the data of frozen hairtail was found as an unstable one in unit root test and the result of cointegration test showed the long-run equilibrium relationship at lag 1. From the results of VECM model, we could find that the coefficient of error correction is effective, and the sign is negative(-). It means that the existence of adjustment tendency to long-run equilibrium after a short-run deviation. But the short-run causality of the prices were not found except the price of wholesale. Third, according to the results of differenced VAR model, data from frozen croaker did not have the stability and long-run equilibrium. Moreover, it was found that the import price has a weak causality on the retail price. Because of having difficulties in collecting data, the result of this paper could not explain the relationship among the prices of import, wholesale and retail perfectly. However, it more or less contributed to a long-lasted debate on the direction of causality of price-setting in academic research and provided a useful guide for the policy makers in charge of the price-setting of fisheries products as well.

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Active Contours Level Set Based Still Human Body Segmentation from Depth Images For Video-based Activity Recognition

  • Siddiqi, Muhammad Hameed;Khan, Adil Mehmood;Lee, Seok-Won
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제7권11호
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    • pp.2839-2852
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    • 2013
  • Context-awareness is an essential part of ubiquitous computing, and over the past decade video based activity recognition (VAR) has emerged as an important component to identify user's context for automatic service delivery in context-aware applications. The accuracy of VAR significantly depends on the performance of the employed human body segmentation algorithm. Previous human body segmentation algorithms often engage modeling of the human body that normally requires bulky amount of training data and cannot competently handle changes over time. Recently, active contours have emerged as a successful segmentation technique in still images. In this paper, an active contour model with the integration of Chan Vese (CV) energy and Bhattacharya distance functions are adapted for automatic human body segmentation using depth cameras for VAR. The proposed technique not only outperforms existing segmentation methods in normal scenarios but it is also more robust to noise. Moreover, it is unsupervised, i.e., no prior human body model is needed. The performance of the proposed segmentation technique is compared against conventional CV Active Contour (AC) model using a depth-camera and obtained much better performance over it.

Estimation Model and Vertical Distribution of Leaf Biomass in Pinus sylvestris var. mongolica Plantations

  • Liu, Zhaogang;Jin, Guangze;Kim, Ji Hong
    • 한국산림과학회지
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    • 제98권5호
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    • pp.576-583
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    • 2009
  • Based on the stem analysis and biomass measurement of 36 trees and 1,576 branches in Pinus sylvestris var. mongolica (Mongolian pine) plantations of Northeast China, this study was conducted to develop estimation model equation for leaf biomass of a single tree and branch, to examine the vertical distribution of leaf biomass in the crown, and to evaluate the proportional ratios of biomass by tree parts, stem, branch, and leaf. The results indicated that DBH and crown length were quite appropriate to estimate leaf biomass. The biomass of single branch was highly correlated with branch collar diameter and relative height of branch in the crown, but not much with stand density, site quality, and tree height. Weibull distribution function would have been appropriate to express vertical distribution of leaf biomass. The shape parameters from 29 sample trees out of 36 were less than 3.6, indicating that vertical distribution of leaf biomass in the crown was displayed by bell-shaped curve, a little inclined toward positive side. Apparent correlationship was obtained between leaf biomass and branch biomass having resulted in linear function equation. The stem biomass occupied around 80% and branch and leaf made up about 20% of total biomass in a single tree. As the level of tree class was increased from class I to class V, the proportion of the stem biomass to total biomass was gradually increased, but that of branch and leaf became decreased.

A VAR Model of Stimulating Economic Growth in the Guangdong Province, P.R. China

  • Ortiz, Jaime;Xia, Jingwen;Wang, Haibo
    • The Journal of Asian Finance, Economics and Business
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    • 제2권2호
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    • pp.5-12
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    • 2015
  • The authors calculate the long-term predictability of GDP, domestic demand, investment, and net exports for Guangdong province, P.R. China from 2000 to 2013. A vector autoregressive (VAR) model with quarterly data for this period is first co-integrated then the Granger causality test is applied to empirically assess the relationships among gross domestic product (GDP), consumption, investment, and net exports. There is a strong causality effect between investment and net exports in Guangdong province. However, the variance decomposition results indicate that exports respond to foreign shocks rather than domestic ones, making their impact on the Guangdong economy to predict. Results show the stimulating effect of domestic demand on GDP is larger than the stimulating effect of net exports and much larger than even the stimulating effect of investment. The analysis suggests that there are dynamic influences with various levels of persistence between GDP, consumption, investment, and net exports. Macroeconomic policy adjustments are urgently required to expand domestic demand and thereby stimulate economic growth in Guangdong province.

발틱운임지수(BDI)와 해상 물동량의 인과성 검정 (Analysis of causality of Baltic Drybulk index (BDI) and maritime trade volume)

  • 배성훈;박근식
    • 무역학회지
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    • 제44권2호
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    • pp.127-141
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    • 2019
  • In this study, the relationship between Baltic Dry Index(BDI) and maritime trade volume in the dry cargo market was verified using the vector autoregressive (VAR) model. Data was analyzed from 1992 to 2018 for iron ore, steam coal, coking coal, grain, and minor bulks of maritime trade volume and BDI. Granger causality analysis showed that the BDI affects the trade volume of coking coal and minor bulks but the trade volume of iron ore, steam coal and grain do not correlate with the BDI freight index. Impulse response analysis showed that the shock of BDI had the greatest impact on coking coal at the two years lag and the impact was negligible at the ten years lag. In addition, the shock of BDI on minor cargoes was strongest at the three years lag, and were negligible at the ten years lag. This study examined the relationship between maritime trade volume and BDI in the dry bulk shipping market in which uncertainty is high. As a result of this study, there is an economic aspect of sustainability that has helped the risk management of shipping companies. In addition, it is significant from an academic point of view that the long-term relationship between the two time series was analyzed through the causality test between variables. However, it is necessary to develop a forecasting model that will help decision makers in maritime markets using more sophisticated methods such as the Bayesian VAR model.

Stock Prices and Exchange Rate Nexus in Pakistan: An Empirical Investigation Using MGARCH-DCC Model

  • RASHID, Tabassam;BASHIR, Malik Fahim
    • The Journal of Asian Finance, Economics and Business
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    • 제9권5호
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    • pp.1-9
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    • 2022
  • The study examines stock prices (LOGKSE) and exchange rate (LOGPK)-Pakistani Rupee vis-à-vis US Dollar- interactions in Pakistan. This study employs a multivariate VAR-GARCH model using monthly data from January 2012 to October 2020. The results of the Johansen cointegration test show that there is no relationship between Foreign Exchange Market and Stock Market in the long run. In the short-run, stock exchange returns are affected slightly negatively by the changes in the foreign exchange market, but the foreign exchange market does not seem to be affected by the ups and downs of the stock exchange. The VAR model and Granger Causality show that both markets are strongly influenced by their own lagged values rather than by the lagged values of one another and show weak or no correlation between the two markets. Volatility persistence is observed in both the stock and foreign exchange markets, implying that shocks and past period volatility are major drivers of future volatility in both markets. Thus greater uncertainties today will induce panic and consequently generate higher volatility in the future period. This phenomenon has been observed many times on Pakistan Stock Exchange especially. The results have important implications for local international investors in portfolio diversification decisions and risk hedging strategies.

The Nexus Between Monetary Policy and Economic Growth: Evidence from Vietnam

  • NGUYEN, Hoang Chung
    • The Journal of Asian Finance, Economics and Business
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    • 제9권1호
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    • pp.153-166
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    • 2022
  • The study estimates the Structured VAR and the Dynamic Stochastic General Equilibrium Model for the Vietnamese economy based on the new Keynesian model for small and open economies, with the output gap, inflation, policy interest rate, the Vietnamese exchange rate, and the inflation and interest rate in the United States. The paper aims to clarify the impulse response of the macro variables through their shocks. It offers to model the SVAR and DSGE processes, as well as describe why and how interest rate policy is important in the impulse response of macro variables like the output gap and inflation process. The study supports the central role of monetary policy by giving empirical evidence for the new Keynesian theory, according to which an interest rate shock causes the output gap to widen and inflation to decrease. Finally, the application of the DSGE model is becoming more and more popular in the State Bank of Viet Nam to improve its policy planning, analyzing, and forecasting policy towards sustainable and stable growth.