• 제목/요약/키워드: Bayesian VAR

검색결과 19건 처리시간 0.019초

Bayesian VAR를 이용한 해운경기, 환율 그리고 산업생산 간의 동태적 상관분석 (Bayesian VAR Analysis of Dynamic Relationships among Shipping Industry, Foreign Exchange Rate and Industrial Production)

  • 김현석;장명희
    • 한국항만경제학회지
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    • 제30권2호
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    • pp.77-92
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    • 2014
  • 본 연구는 2000~2013년까지의 월별 시계열 자료를 이용하여 실물 금융변수와 해운경기간의 동태적 상관관계를 분석한다. 특히, 2008년 글로벌위기 이후 운임지수의 지속적인 하락국면에서 실물 금융변수가 얼마만큼의 영향을 미쳤는가를 중심으로 분석하였다. 모형의 적합성과 예측력 비교를 위해 기존의 일반적인 VAR 모형과 베이지안 VAR를 비교하였으며, VAR 모형 설정에 있어 외생성을 보다 객관적으로 도출하기 위해 DAG(Directed Acyclic Graph)를 활용하여 충격반응분석을 실시하고 각각의 모형에 대한 예측력을 비교하였다. 분석결과 BDI에 대한 금융 실물 부문의 영향에 대하여 베이지안 VAR 모형의 충격반응분석 결과는 일반적인 VAR 모형보다 명확하게 드러났으며, 두 모형 간의 예측력을 검정한 결과 베이지안 VAR 모형의 예측력이 매우 우월한 것으로 나타났다.

A Comparison Analysis of Monetary Policy Effect Under an Open Economy Model

  • Lee, Keun Yeong
    • East Asian Economic Review
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    • 제22권2호
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    • pp.141-176
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    • 2018
  • The paper analyzes and compares the effects of domestic monetary policy using DSGE, DSGE-VAR, and VAR based on a two-country open economy model of Korea and the U.S. According to impulse response analysis, a domestic interest rate hike raises won value in the case of DSGE and DSGE-VAR models, while in the case of the unrestricted VAR model, it lowers won value. In the marginal data density standard, DSGE-VAR (${\mu}=1$) is superior to DSGE or Bayesian VAR over the sample period. Conversely, in the in-sample RMSE criterion, especially for the won/dollar exchange rate, VARs are superior to DSGE or DSGE-VAR. It is necessary to study further if these differences are caused by model misspecification or omitted variable bias.

ISSR 표지자를 이용한 느릅나무 자연집단의 유전변이 분석 (Population Genetic Variation of Ulmus davidiana var. japonica in South Korea Based on ISSR Markers)

  • 안지영;홍경낙;이제완;양병훈
    • 한국산림과학회지
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    • 제102권4호
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    • pp.560-565
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    • 2013
  • 국내의 느릅나무(Ulmus davidiana var. japonica) 집단에 대한 유전구조와 유전다양성을 분석하였다. 느릅나무 7개 자연집단, 171개체에 대하여 7개 ISSR 표지자를 이용하여 총45개의 다형적 증폭산물을 확인하였다. 유효대립인자와 다형적 유전자좌 비율의 평균값은 1.5개와 89%이었다. Shannon의 다양성 지수(I)가 0.435, 빈도주의 방법에 의한 이형접합도 기대치($H_e$)는 0.289, 베이즈 추정에 의한 이형접합도 기대치(hs)가 0.323으로 나타났다. AMOVA 분석에서 느릅나무 집단의 유전변이 중 4.2%가 집단간 차이(${\Phi}_{ST}=0.042$)에 기인하였으며, 95.8%를 집단내 개체들이 보유하고 있었다. 베이즈 추정에 의한 집단간 유전분화율(${\theta}^{II}$)은 0.043으로 나타났다. 국내 느릅나무 집단의 유전다양성은 다른 느릅나무속 수종과 유사한 수준에 해당하였으나, 집단간 유전분화 정도는 매우 낮았다. 베이즈 근사추정에서 집단별 고정지수(평균 $PS-F_{IS}=0.822$)나 집단 특이적 유전분화율(평균 $PS-F_{ST}=0.101$)에서 유의할 만한 차이를 보이는 집단은 없었다. 군집분석과 주성분분석에서 7개의 집단들을 3개 군집으로 나눌 수 있었으나, 두 방법의 군집 양상은 일치하지 않았다. 또한 베이즈 군집분석에서 집단간 유연관계와 지리적 분포의 상관성을 확인할 수 없었다.

벡터자기회귀(VAR) 모형을 이용한 지하수위와 하천수위의 추계학적 모의기법 개발 (A development of stochastic simulation model based on vector autoregressive model (VAR) for groundwater and river water stages)

  • 권윤정;원창희;최병한;권현한
    • 한국수자원학회논문집
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    • 제55권12호
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    • pp.1137-1147
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    • 2022
  • 하천수위와 지하수위는 수문학적 순환과정에서 나타나는 수문학적 요소로 상호 연관성이 높으며 이러한 수문학적 요소에 대해 확률적 시뮬레이션을 독립적으로 수행하는 경우 상호 관련 정보손실과 같은 문제가 발생할 수 있다. 하천수위와 지하수위는 수문학적·농업적 가뭄을 평가하는 중요한 지표로 활용되지만 하천수위의 경우 건기 중에는 정확한 관측을 얻기가 매우 어려우며, 지하수위의 경우 데이터 기간이 상대적으로 짧아 이를 활용한 가뭄지수 사용이 제한적이다. 이와 관련하여 손실 없이 자료를 최대한 이용하기 위해 본 연구는 각 변수의 시간 의존성을 고려하는 동시에 상호 연관된 변수의 시간 의존성을 고려하는 벡터자기회 모형VAR)을 구성했다. 하천수위와 지하수위 사이의 자기 상관 및 상관관계를 확인하고, 정보 손실을 최소화하는 하천수위 및 지하수위를 예측할 수 있는지 여부를 결정하기 위해 벡터 자기 회귀 모델의 최적 순서 결정과 매개변수를 결정하였다. 또한, 두 변수 간의 상관관계를 반영하지 않는 자기회귀모형(AR)을 구축하고 모의에 대한 DIC와 상관계수를 VAR 모형과 비교하여 VAR 모형 더 적합함을 보이고 하천수위와 지하수위의 간의 상호관계성을 효과적으로 반영함을 확인하였다.

International Transmission of Macroeconomic Uncertainty in China: A Time-varying Bayesian Global SVAR Approach

  • Wongi Kim
    • East Asian Economic Review
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    • 제28권1호
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    • pp.95-140
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    • 2024
  • This study empirically investigates the international transmission of China's uncertainty shocks. It estimates a time-varying parameter Bayesian global structural vector autoregressive model (TVP-BGVAR) using time series data for 33 countries to evaluate heterogeneous international linkage across countries and time. Uncertainty shocks are identified via sign restrictions. The empirical results reveal that an increase in uncertainty in China negatively affects the global economy, but those effects significantly vary over time. The effects of China's uncertainty shocks on the global economy have been significantly altered by China's WTO accession, the global financial crisis, and the recent US-China trade conflict. Furthermore, the effects of China's uncertainty shocks, typically on inflation, differ significantly across countries. Moreover, Trade openness appears crucial in explaining heterogeneous GDP responses across countries, whereas the international dimension of monetary policy appears to be important in explaining heterogeneous inflation responses across countries.

The Effectiveness of Foreign Exchange Intervention: Empirical Evidence from Vietnam

  • DING, Xingong;WANG, Mengzhen
    • The Journal of Asian Finance, Economics and Business
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    • 제9권2호
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    • pp.37-47
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    • 2022
  • This study uses monthly data from January 2009 to December 2020 to examine the effectiveness of foreign currency intervention and its influence on monetary policy in Vietnam using a Hierarchical Bayesian VAR model. The findings suggest that foreign exchange intervention has little influence on the exchange rate level or exports, but it can significantly minimize exchange rate volatility. As a result, we can demonstrate that the claim that Vietnam is a currency manipulator is false. As well, the forecast error variance decomposition results reveal that interest rate differentials mainly determine the exchange rate level instead of foreign exchange intervention. Moreover, the findings suggest that foreign exchange intervention is not effectively sterilized in Vietnam. Inflation is caused by an increase in international reserves, which leads to an expansion of the money supply and a decrease in interest rates. Although the impact of foreign exchange intervention grows in tandem with the growth of international reserves, if the sterilizing capacity does not improve, rising foreign exchange intervention will instead result in inflation. Finally, we use a rolling window approach to examine the time-varying effect of foreign exchange intervention.

Asset Price, the Exchange Rate, and Trade Balances in China: A Sign Restriction VAR Approach

  • Kim, Wongi
    • East Asian Economic Review
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    • 제22권3호
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    • pp.371-400
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    • 2018
  • Although asset price is an important factor in determining changes in external balances, no studies have investigated it from the Chinese perspective. In this study, I empirically examine the underlying driving forces of China's trade balances, particularly the role of asset price and the real exchange rate. To this end, I estimate a sign-restricted structural vector autoregressive model with quarterly time series data for China, using the Bayesian method. The results show that changes in asset price affect China's trade balances through private consumption and investment. Also, an appreciation of the real exchange rate tends to deteriorate trade balances in China. Furthermore, forecast error variance decomposition results indicate that changes in asset price (stock price and housing price) explain about 20% variability of trade balances, while changes in the real exchange rate can explain about 10%.

Forecasting Government Bond Yields in Thailand: A Bayesian VAR Approach

  • BUABAN, Wantana;SETHAPRAMOTE, Yuthana
    • The Journal of Asian Finance, Economics and Business
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    • 제9권3호
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    • pp.181-193
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    • 2022
  • This paper seeks to investigate major macroeconomic factors and bond yield interactions in Thai bond markets, with the goal of forecasting future bond yields. This study examines the best predictive yields for future bond yields at different maturities of 1-, 3-, 5-, 7-, and 10-years using time series data of economic indicators covering the period from 1998 to 2020. The empirical findings support the hypothesis that macroeconomic factors influence bond yield fluctuations. In terms of forecasting future bond yields, static predictions reveal that in most cases, the BVAR model offers the best predictivity of bond rates at various maturities. Furthermore, the BVAR model has the best performance in dynamic rolling-window, forecasting bond yields with various maturities for 2-, 4-, and 8-quarters. The findings of this study imply that the BVAR model forecasts future yields more accurately and consistently than other competitive models. Our research could help policymakers and investors predict bond yield changes, which could be important in macroeconomic policy development.

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.

A Study of a Combining Model to Estimate Quarterly GDP

  • Kang, Chang-Ku
    • 응용통계연구
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    • 제25권4호
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    • pp.553-561
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    • 2012
  • Various statistical models to Estimate GDP (measured as a nation's economic situation) have been developed. In this paper an autoregressive distributed lag model, factor model, and a Bayesian VAR model estimate quarterly GDP as a single model; the combined estimates were evaluated to compare a single model. Subsequently, we suggest that some combined models are better than a single model to estimate quarterly GDP.