• Title/Summary/Keyword: Vector Autoregressive

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The Impacts of Speculative Trading on Commodity Prices After the Global Financial Crisis (금융위기 이후 투기 거래가 원자재 가격에 미친 영향)

  • Kim, Hwa-Nyeon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.5
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    • pp.179-185
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    • 2016
  • This study verifies whether speculative trading in commodity markets acted as the primary cause of the increase in commodity prices after the global financial crisis using the Structural Vector Autoregressive (SVAR) model. The effects of speculative trading on commodity prices increased by a factor of 3 to 6 after the crisis compared to those before the crisis. Although the demand related variables, such as industrial production, affected commodity prices significantly before the crisis, their effects decreased after the crisis. Consequently, the rebound of commodity prices after the crisis was mainly caused by the increase in speculative money, fortified by the expansion of the global liquidity supply. The global liquidity may well increase in the future, because the U.S. Federal Reserve Board is likely to continue to increase its interest rate. This study claims that when global liquidity shrinks as a result of a change in the Fed's monetary policy stance, speculative trading will slow down, leading to a decline in commodity prices.

The Impact of the Regional Comprehensive Economic Partnership (RCEP) on Intra-Industry Trade: An Empirical Analysis Using a Panel Vector Autoregressive Model

  • Guofeng Zhao;Cheol-Ju Mun
    • Journal of Korea Trade
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    • v.27 no.3
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    • pp.103-118
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    • 2023
  • Purpose - This study aims to examine the dynamic relationship between the variables impacted by the Regional Comprehensive Economic Partnership (RCEP) and the level of intra-industry trade among member states, with the ultimate objective of deducing the short- and long-term effects of RCEP on trade. Design/methodology - This study focuses on tariffs, GDP growth rates, and the proportion of regional FDI to total FDI as research variables, and employs a panel vector autoregression model and GMM-style estimator to investigate the dynamic relationship between RCEP and intra-industry trade among member countries. Findings - The study finds that the level of intra-industry trade between member states is positively impacted by both tariffs and intra-regional FDI. The impulse response graph shows that tariffs and FDI within the region can promote intra-industry trade among member countries, with a quick response. However, the contribution rates of tariffs and intra-regional FDI are not particularly high at approximately 1.5% and 1.4%, respectively. In contrast, the contribution rate of GDP growth can reach around 8.5%. This implies that the influence of economic growth rate on intra-regional trade in industries is not only long-term but also more powerful than that of tariffs and intra-regional FDI. Originality/value - The originality of this study lies in providing a new approach to investigating the potential impact of RCEP while avoiding the limitations associated with the GTAP model. Additionally, this study addresses existing gaps within the research, further contributing to the research merit of the study.

The Effects of Foreign Direct Investment and Economic Absorptive Capabilities on the Economic Growth of the Lao People's Democratic Republic

  • NANTHARATH, Phouthakannha;KANG, Eungoo
    • The Journal of Asian Finance, Economics and Business
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    • v.6 no.3
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    • pp.151-162
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    • 2019
  • The paper examines the effects of Foreign Direct Investment (FDI) on the economic growth of Lao People's Democratic Republic (Lao PDR) between 1993 and 2015. The investigation is based on the influence of growth and economic absorptive capability determinants such as human capital, trade openness, and institutional quality. The methodological analysis uses a multivariate framework accounting capital stock, labor stock, FDI, human capital, trade openness, and institutional quality in regression of the Vector Autoregressive model. Augmented Dickey-Fuller unit root test, Johansen Cointegration test, and Granger Causality test were applied as parts of the econometric time-series analysis approach. The empirical results demonstrate the positive effects of FDI and trade openness, and the negative effects of human capital and institutional quality on the economic growth of the Lao PDR over the 1993 to 2015 period. The findings confirm that trade openness complemented by a sufficient level of infrastructure, education, quality institutions, and transparency significantly influence economic growth and attract more FDI. Research results lend credence to the need for the Lao PDR's government to focus on improving its economic absorptive capability and economic competitiveness regionally and globally by improving wealth and resource management strategies, as failure to take this course of action could lead to the Dutch Disease effects.

Analyzing Fluctuation of the Rent-Transaction price ratio under the Influence of the Housing Transaction, Jeonse Rental price (주택매매가격 및 전세가격 변화에 따른 전세/매매가격비율 변동 분석)

  • Park, Jae-Hyun;Lee, Sang-Hyo;Kim, Jae-Jun
    • Journal of The Korean Digital Architecture Interior Association
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    • v.10 no.2
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    • pp.13-20
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    • 2010
  • Uncertainty in housing price fluctuation has great impact on the overall economy due to importance of housing market as both place of residence and investment target. Therefore, estimating housing market condition is a highly important task in terms of setting national policy. Primary indicator of the housing market is a ratio between rent and transaction price of housing. The research explores dynamic relationships between Rent-Transaction price ratio, housing transaction price and jeonse rental price, using Vector Autoregressive Model, in order to demonstrate significance of shifting rent-transaction price that is subject to changes in housing transaction and housing rental market. The research applied housing transaction price index and housing rental price index as an indicator to measure transaction and rental price of housing. The price index and data for price ratio was derived from statistical data of the Kookmin Bank. The time-series data contains monthly data ranging between January 1999 and November 2009; the data was log transformed to convert to level variable. The analysis result suggests that the rising ratio between rent-transaction price of housing should be interpreted as a precursor for rise of housing transaction price, rather than judging as a mere indicator of a current trend.

Forecasting for a Credit Loan from Households in South Korea

  • Jeong, Dong-Bin
    • The Journal of Industrial Distribution & Business
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    • v.8 no.4
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    • pp.15-21
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    • 2017
  • Purpose - In this work, we examined the causal relationship between credit loans from households (CLH), loan collateralized with housing (LCH) and an interest of certificate of deposit (ICD) among others in South Korea. Furthermore, the optimal forecasts on the underlying model will be obtained and have the potential for applications in the economic field. Research design, data, and methodology - A total of 31 realizations sampled from the 4th quarter in 2008 to the 4th quarter in 2016 was chosen for this research. To achieve the purpose of this study, a regression model with correlated errors was exploited. Furthermore, goodness-of-fit measures was used as tools of optimal model-construction. Results - We found that by applying the regression model with errors component ARMA(1,5) to CLH, the steep and lasting rise can be expected over the next year, with moderate increase of LCH and ICD. Conclusions - Based on 2017-2018 forecasts for CLH, the precipitous and lasting increase can be expected over the next two years, with gradual rise of two major explanatory variables. By affording the assumption that the feedback among variables can exist, we can, in the future, consider more generalized models such as vector autoregressive model and structural equation model, to name a few.

Multivariate Causal Relationship between Stock Prices and Exchange Rates in the Middle East

  • Parsva, Parham;Lean, Hooi Hooi
    • The Journal of Asian Finance, Economics and Business
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    • v.4 no.1
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    • pp.25-38
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    • 2017
  • This study investigates the causal relationship between stock prices and exchange rates for six Middle Eastern countries, namely, Egypt, Iran, Jordan, Kuwait, Oman, and Saudi Arabia before and during (after) the 2007 global financial crisis for the period between January 2004 and September 2015. The sample is divided into two sub-periods, that is, the period from January 1, 2004 to September 30, 2007 and the period from October 1, 2007 to September 30, 2015, to represent the pre-crisis period and the post-crisis period, respectively. Using Vector Autoregressive (VAR) model in a multivariate framework (including two control variables, inflation rates and oil prices) the results suggest that in the case of Jordan, Kuwait and Saudi Arabia, there exists bidirectional causalities after the crisis period but not the before. The opposite status is available for the case of Iran. In the case of Oman, there is bidirectional causality between the variables of interest in both periods. The results also reveal that the relationship between stock prices and exchange rates has become stronger after the 2007 global financial crisis. Overall, the results of this study indicate that fluctuations in foreign exchange markets can significantly affect stock markets in the Middle East.

Relations Between Paprika Consumption and Unstructured Big Data, and Paprika Consumption Prediction

  • Cho, Yongbeen;Oh, Eunhwa;Cho, Wan-Sup;Nasridinov, Aziz;Yoo, Kwan-Hee;Rah, HyungChul
    • International Journal of Contents
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    • v.15 no.4
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    • pp.113-119
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    • 2019
  • It has been reported that large amounts of information on agri-foods were delivered to consumers through television and social networks, and the information may influence consumers' behavior. The purpose of this paper was first to analyze relations of social network service and broadcasting program on paprika consumption in the aspect of amounts to purchase and identify potential factors that can promote paprika consumption; second, to develop prediction models of paprika consumption by using structured and unstructured big data. By using data 2010-2017, cross-correlation and time-series prediction algorithms (autoregressive exogenous model and vector error correction model), statistically significant correlations between paprika consumption and television programs/shows and blogs mentioning paprika and diet were identified with lagged times. When paprika and diet related data were added for prediction, these data improved the model predictability. This is the first report to predict paprika consumption by using structured and unstructured data.

A Study on the Dynamic Relationship between Education Input and Economic Growth

  • He, Yugang
    • East Asian Journal of Business Economics (EAJBE)
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    • v.6 no.4
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    • pp.35-45
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    • 2018
  • Purpose - The operating mechanism between education input and economic growth is a mysterious proposition that has attracted a vast array of scholars' interests to study on it. Therefore, this paper sets China as an example to analyze the dynamic relationship between education input and economic growth. Research design and methodology - The annual time series from 1990 to 2017 will be employed to conduct an empirical analysis under the vector autoregressive model. The education input is treated as an factor that impacts the economic growth such as labor input and capital input. Meanwhile, the education input will be added to the Cobb-Douglas production function to form a new one so as to explore the dynamic relationship between education input and economic growth. Results - According to the results of empirical analysis, it can be found that the education input has an increasingly positive effect on economic growth. Simultaneously, the economic growth also has a positive effect on education input, but this kind of effect is not steady. Of course, the labor input and the capital input also can promote the economic growth to some degree. Conclusions - The education input is one of most important inputs for a country. Based on the empirical analysis, this paper suggests that the China's government should put more emphasis on the education input so to make its economy develop well.

The Effect of Exchange Rates and Interest Rates of Four Large Economies on the Health of Banks in ASEAN-3

  • PURWONO, Rudi;TAMTELAHITU, Jopie;MUBIN, M. Khoerul
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.10
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    • pp.591-599
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    • 2020
  • This study examines how the health of the banks in ASEAN-3 countries namely Indonesia, Malaysia and Thailand respond to the change in exchange rates and foreign interest rates in four large economies. The transmissions of the two external factors through domestic factors in each ASEAN-3 countries eventually affects Non-Performing Loan (NPL) of commercial banks. This study uses the monthly time series data and the renowned Structural Vector Autoregressive (VAR) model comprising five variables, namely exchange rate, foreign interest rate, domestic interest rate, money supply, and non-performing loan (NPL). The results indicate that there are different effects between ASEAN-3 countries, which can be classified as short-run effect and long-run effect. In the long run effect, external factors have a dominant role in determining NPL in ASEAN-3 countries. Yuan has the biggest effect on Malaysia's NPL, while Indonesia is more affected by European interest rates rather than the fluctuation of the US currency and China's interest rates. Among ASEAN-3 countries, Malaysia is the one that is the most vulnerable to external factors. While Thailand's NPL is affected dominantly by domestic factors. This study shows that the Fed Funds Rate (US official interest rate) is not always the dominant factor affecting the health of domestic banks in ASEAN-3.

For the Association between 3D VAR Model and 2D Features

  • Kiuchi, Yasuhiko;Tanaka, Masaru;Fujiki, Jun;Mishima, Taketoshi
    • Proceedings of the IEEK Conference
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    • 2002.07c
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    • pp.1404-1407
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    • 2002
  • Although we look at objects as 2D images through our eyes, we can reconstruct the shape and/or depth of objects. In order to realize this ability using computers, it is required that the method which can estimate the 3D features of object from 2D images. As feature which represents 3D shapes effectively, three dimensional vector autoregressive model is pro- posed. If this feature is associated other feature of 2D shape, then above aim might be achieved. On the other hand, as feature which represents 2D shapes, quasi moment features is proposed. As the first step of association of these features, we constructed real time simulator that computes both of two features concurrently from object data (3D curves) . This simulator can also rotate object and estimate the rotation The method using 3D VAR model estimates the rotation correctly, but the estimation by quasi moment features includes much errors. This reason would be that projected images are constructed by the points only, and doesn't have enough sizes to estimate the correct 3D rotation parameters.

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