• The Korean Journal of Applied Statistics
• /
• v.35 no.5
• /
• pp.631-644
• /
• 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.

• Environmental and Resource Economics Review
• /
• v.12 no.4
• /
• pp.687-708
• /
• 2003

The purpose of this paper is to introduce time-series causality analysis by combining time-series technique with graph theory. Vector autoregressive (VAR) models can provide reasonable interpretation only when the contemporaneous variables stand in a well-defined causal order. We show that how graph theory can be applied to search for the causal structure In VAR analysis. Using Maryland crop cash prices and CBOT futures price data, we estimate a VAR model with directed acyclic graph analysis. This expands our understanding the degree of interconnectivity between the employed time-series variables.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2003.05a
• /
• pp.984-990
• /
• 2003

IMF 이후 연봉제의 도입과 정착과정에서 대부분 기업들이 연봉제의 연착륙과 함께 실질적인 성과창출에 많은 관심을 가지면서 효과적인 성과평가시스템의 구축에 주력하고 있지만 '전사 > 사업부 > 부서(팀) > 개인'으로 이어지는 일련의 목표연계과정과 부서(팀) 수준의 올바른 목표설정측면에서 그 방법론의 이해부족으로 혼란을 겪고 있는 실정이다. 본 연구는 효과적인 성과평가시스템이 작동되기 위한 전제조건인 부서(팀) 수준의 바람직한 목표설정방법 이 무엇인지에 초점을 두고 논의를 진행하였다. 특히 개별 부서(팀)이 궁극적으로 달성하려고 하는 본질적 성과목표인 'Value Added results'(VAR)의 개념에 초점을 맞췄다. 그리고 VAR 관점에 따라 본질적인 부서(팀) 목표를 도출하는 네 가지 방법인 고객다이어그램, 목표할당, 팀 피라미드, 프로세스맵에 대해 살펴본 후 마지막으로 실제 기업에서 이 네 가지 방법에 의해 도출된 VAR의 예를 인용하였다.

• Journal of the Korean Data and Information Science Society
• /
• v.25 no.4
• /
• pp.807-817
• /
• 2014

This paper considers multivariate time series modelling of PM10 data in Korea collected from 2008 to 2011. We consider both temporal and spatial dependencies of PM10 by applying the sparse vector autoregressive (sVAR) modelling proposed by Davis et al. (2013). It utilizes the partial spectral coherence to measure cross correlation between different regions, in turn provides the sparsity in the model while balancing the parsimony of model and the goodness of fit. It is also shown that sVAR performs better than usual vector autoregressive model (VAR) in forecasting.

• The Korean Journal of Applied Statistics
• /
• v.28 no.5
• /
• pp.871-883
• /
• 2015

Vector autoregressive (VAR) models in high dimension suffer from noisy estimates, unstable predictions and hard interpretation. Consequently, the sparse vector autoregressive (sVAR) model, which forces many small coefficients in VAR to exactly zero, has been suggested and proven effective for the modeling of high dimensional time series data. This paper studies coupling measures to select non-zero coefficients in sVAR. The basic idea based on the simulation study reveals that removing the effect of other variables greatly improves the performance of coupling measures. sVAR model coefficients are asymmetric; therefore, asymmetric coupling measures such as Granger causality improve computational costs. We propose two asymmetric coupling measures, filtered-cross-correlation and filtered-Granger-causality, based on the filtered residuals series. Our proposed coupling measures are proven adequate for heavy-tailed and high order sVAR models in the simulation study.

• Journal of Science and Technology Studies
• /
• v.16 no.1
• /
• pp.29-61
• /
• 2016

This paper explains the one of the most problematic factor in the society that leads to social inequality - increase in non-regular work. Theoretically, this expansion of non-regular work can be explained by technologies that are designed to save the labor force, especially since corporations in Korea have strategies to replace the regular workers with temporary workers, to save money. OECD also noted that Korea's income inequality is pretty high in ranking when compared with the rest of the OECD members, and says that globalization and technological innovation are the factors of this problem. To refine the argument, this study also looks at relationship between development made in sciences - which can be stated as a proxy variable to look at the advances made in technology - and expansion of temporary work force by using VAR methodology. Based on the results of this analysis in the future temporary/regular workers ratio started with decline, then turn to rise. These temporary/regular workers ratio sustained growth prediction shows that the expansion of the temporary expansion contributes to instability and social inequality in the labor market and technological change are interrelated.

• KDI Journal of Economic Policy
• /
• v.17 no.4
• /
• pp.143-217
• /
• 1995

거시모형(巨視模型)을 통하여 과거 우리나라의 고성장(高成長)을 이해하고 주요(主要) 정책변수(政策變數)와 외생변수(外生變數)가 경제에 미치는 영향을 파악하기 위해서는 중장기적으로 안정적이고 신뢰할 수 있는 거시모형(巨視模型)이 작성되어야 한다. 그러나 단순히 과거의 적합도(適合度)를 향상시키거나 단기(短期)시뮬레이션의 결과만을 토대로 작성된 거시모형은 중장기적인 안정성(安定性) 내지는 신뢰성(信賴性)을 확보하지 못할 수도 있다. 본고(本稿)에서는 거사모형의 작성에 있어서도 구조적(構造的) VAR모형(模型)에서처럼 모형의 중장기 특성을 파악하는 것이 중요함을 지적하였다. 구조적 VAR모형에서는 대부분의 이론이 수용할 수 있는 "수요충격(需要衝擊)은 장기에 실질성장에 영향을 미치지 않는다"는 최소한의 가정(假定)이 모형(模型)에 처음부터 직접적(直接的)으로 내재(內在)되도록 하고 있으나, 본고에서는 거시전망모형(巨視展望模型)의 작성을 위하여 중장기적(中長期的)인 시뮬레이션을 통하여 간접적(間接的)으로 위의 가정(假定)을 확인하는 방법을 택하였다. 이에 추가하여 중장기 전망을 시도했을 때 다른 나라의 경험과 크게 배치되는 결과가 나온 경우에는 모형을 수정하는 것이 필요함을 투자(投資) 및 소비식(消費式)의 예(例)를 들어서 논의하였다. 본고(本稿)의 공헌은, 중장기적으로 안정적이고 신뢰할 수 있는 거시전망모형(巨視展望模型)의 작성에 있어서 중장기시뮬레이션과 중장기전망의 결과가 모형작성자의 선험적(先驗的) 기대(期待)에 수렴될 때까지 모형의 수정을 해나가는 반복과정을 전망모형(展望模型) 작성에 있어 하나의 방법론(方法論)으로 제시한 데 있다.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.9
• /
• pp.243-251
• /
• 2022

In this paper, we propose a phenomenon that analyze the impact of market sentiment on China's real estate market through the perspective of behavioral economics. Previously, real estate market analyzation basically focus on some fundamental principles which include market price, monetary policies and income, etc. However, little research has explored market sentiment and its influence. By using principal components analysis (PCA), this study first creates buyer's sentiment and seller's sentiment to measure the heat of China's real estate market. Different from using traditional estimation method, the vector autoregressive model (VAR) is used to analyze how both sentiments affect real estate return. The overall results show that from unit root test and impulse response analyzation, the impact of seller's sentiment is positive to real estate market while buyer's sentiment is negative. At the same time, the higher seller's sentiment will have different influence on the housing market compared with the higher buyer's sentiment.

• Journal of Korea Port Economic Association
• /
• v.35 no.3
• /
• pp.61-72
• /
• 2019

In order to enhance the competitiveness of the container shipping industry and promote its development, based on the empirical analyses using multivariate time series models, this study aims to suggest a few strategies related to the dynamics of the container shipping market. It uses the vector autoregressive (VAR) and vector error correction (VEC) models as analytical methodologies. Additionally, it uses the annual trade volumes, fleets, and freight rates as the dataset. According to the empirical results, we can infer that the most exogenous variable, the trade volume, exerted the highest influence on the total dynamics of the container shipping market. Based on these empirical results, this study suggests some implications for ship investment, freight rate forecasting, and the strategies of shipping firms. Concerning ship investment, since the exogenous trade volume variable contributes most to the uncertainty of freight rates, corporate finance can be considered more appropriate for container ship investment than project finance. Concerning the freight rate forecasting, the VAR and VEC models use the past information and the cointegrating regression model assumes future information, and hence the former models are found better than the latter model. Finally, concerning the strategies of shipping firms, this study recommends the use of cycle-linked repayment scheme and services contract.

• Journal of Mushroom
• /
• v.21 no.4
• /
• pp.200-208
• /
• 2023

This study was conducted to investigate the reasons for the decreased importation of fresh Shiitake mushrooms into Korea after implementation of the Korea-China Free Trade Agreement (FTA). Monthly time-series data from January 2009 to December 2022 were analyzed using regression analysis and vector autoregression (VAR) models to determine the relationship between the amounts of fresh and spawn Shiitake mushrooms imported. The analysis revealed that a major reason for the decreased importation of fresh Shiitake mushrooms was an increase in mushroom spawn imports after Korea-China FTA implementation. The same results were obtained from the VAR model analysis. However, in terms of the dynamic changes in amount of fresh shiitake mushrooms imported, it was confirmed that the impact of the change in mushroom spawn imports could increase the amount of Shiitake mushrooms imported.