• Title/Summary/Keyword: Empirical model decomposition

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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.

Relationships between Inbound Tourism, Financial Development, and Economic Growth: An Empirical Study of Fujian Province, China

  • An Lin, LIU;Yong Cen, LIU
    • The Journal of Asian Finance, Economics and Business
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    • v.10 no.2
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    • pp.213-222
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    • 2023
  • This paper mainly studies the relationship between financial development, inbound tourism development, and economic growth rate in Fujian Province, China. This study uses the data of real GDP, foreign exchange income from international tourism, and financial interrelations ratio from 1994 to 2019. In the analysis process, the Johansen cointegration test is first used to analyze whether the three have a long-term equilibrium relationship. Then the vector error correction model is established to test the restrictive relationship among the three. Next, the Granger causality test assesses whether the three have a causal relationship. Finally, the contribution rate of the three is analyzed by variance decomposition. The above methods show the following conclusions: first, the three have a long-term equilibrium relationship. Secondly, in the short term, local economic growth is constrained by inbound tourism and financial development. Thirdly, there is a causal relationship between economic growth and inbound tourism in Fujian, while there is a unidirectional causal relationship between financial development and economic growth, financial development, and inbound tourism. Fourthly, the contribution rate of inbound tourism to economic growth fluctuations in Fujian is higher than that of financial development.

The Connectedness between Categorical Policy Uncertainty Indexes and Volatility Index in Korea, Japan and the US (한국, 일본, 미국의 정책별 불확실성 지수와 변동성지수 간의 연계성)

  • Hangyong Lee; Sea-Gan Oh
    • Asia-Pacific Journal of Business
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    • v.14 no.4
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    • pp.319-330
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    • 2023
  • Purpose - The purpose of this paper is to examine the connectedness between categorical economic policy uncertainty (monetary, fiscal, trade and foreign exchange policy uncertainty) indexes and option-implied volatility index in Korea, Japan and the US. Design/methodology/approach - This paper employs the Diebold-Ylmaz (2012) model based on a VAR and generalized forecast error variance decomposition. This paper also conducts regression analyses to investigate whether the volatility indexes are explained by categorical policy uncertainty indexes. Findings - First, we find the total connectedness is stronger in Korea and Japan relative to the US. Second, monetary, fiscal, and foreign exchange policy uncertainty indexes are connected to each other but trade policy uncertainty index is not. Third, the volatility index in Japan and the US is mainly associated with monetary policy uncertainty while the volatility index in Korea is explained by fiscal policy uncertainty index. Research implications or Originality - To our knowledge, this is the first study to investigate the connectedness among categorical policy uncertainty indexes and the volatility index in Korea, Japan, and the US. The empirical results on the connectedness suggest that transparent policy and communication with the market in one type of policy would reduce the uncertainty in other policies.

A Meta Analysis of Using Structural Equation Model on the Korean MIS Research (국내 MIS 연구에서 구조방정식모형 활용에 관한 메타분석)

  • Kim, Jong-Ki;Jeon, Jin-Hwan
    • Asia pacific journal of information systems
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    • v.19 no.4
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    • pp.47-75
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    • 2009
  • Recently, researches on Management Information Systems (MIS) have laid out theoretical foundation and academic paradigms by introducing diverse theories, themes, and methodologies. Especially, academic paradigms of MIS encourage a user-friendly approach by developing the technologies from the users' perspectives, which reflects the existence of strong causal relationships between information systems and user's behavior. As in other areas in social science the use of structural equation modeling (SEM) has rapidly increased in recent years especially in the MIS area. The SEM technique is important because it provides powerful ways to address key IS research problems. It also has a unique ability to simultaneously examine a series of casual relationships while analyzing multiple independent and dependent variables all at the same time. In spite of providing many benefits to the MIS researchers, there are some potential pitfalls with the analytical technique. The research objective of this study is to provide some guidelines for an appropriate use of SEM based on the assessment of current practice of using SEM in the MIS research. This study focuses on several statistical issues related to the use of SEM in the MIS research. Selected articles are assessed in three parts through the meta analysis. The first part is related to the initial specification of theoretical model of interest. The second is about data screening prior to model estimation and testing. And the last part concerns estimation and testing of theoretical models based on empirical data. This study reviewed the use of SEM in 164 empirical research articles published in four major MIS journals in Korea (APJIS, ISR, JIS and JITAM) from 1991 to 2007. APJIS, ISR, JIS and JITAM accounted for 73, 17, 58, and 16 of the total number of applications, respectively. The number of published applications has been increased over time. LISREL was the most frequently used SEM software among MIS researchers (97 studies (59.15%)), followed by AMOS (45 studies (27.44%)). In the first part, regarding issues related to the initial specification of theoretical model of interest, all of the studies have used cross-sectional data. The studies that use cross-sectional data may be able to better explain their structural model as a set of relationships. Most of SEM studies, meanwhile, have employed. confirmatory-type analysis (146 articles (89%)). For the model specification issue about model formulation, 159 (96.9%) of the studies were the full structural equation model. For only 5 researches, SEM was used for the measurement model with a set of observed variables. The average sample size for all models was 365.41, with some models retaining a sample as small as 50 and as large as 500. The second part of the issue is related to data screening prior to model estimation and testing. Data screening is important for researchers particularly in defining how they deal with missing values. Overall, discussion of data screening was reported in 118 (71.95%) of the studies while there was no study discussing evidence of multivariate normality for the models. On the third part, issues related to the estimation and testing of theoretical models on empirical data, assessing model fit is one of most important issues because it provides adequate statistical power for research models. There were multiple fit indices used in the SEM applications. The test was reported in the most of studies (146 (89%)), whereas normed-test was reported less frequently (65 studies (39.64%)). It is important that normed- of 3 or lower is required for adequate model fit. The most popular model fit indices were GFI (109 (66.46%)), AGFI (84 (51.22%)), NFI (44 (47.56%)), RMR (42 (25.61%)), CFI (59 (35.98%)), RMSEA (62 (37.80)), and NNFI (48 (29.27%)). Regarding the test of construct validity, convergent validity has been examined in 109 studies (66.46%) and discriminant validity in 98 (59.76%). 81 studies (49.39%) have reported the average variance extracted (AVE). However, there was little discussion of direct (47 (28.66%)), indirect, and total effect in the SEM models. Based on these findings, we suggest general guidelines for the use of SEM and propose some recommendations on concerning issues of latent variables models, raw data, sample size, data screening, reporting parameter estimated, model fit statistics, multivariate normality, confirmatory factor analysis, reliabilities and the decomposition of effects.

Operational performance evaluation of bridges using autoencoder neural network and clustering

  • Huachen Jiang;Liyu Xie;Da Fang;Chunfeng Wan;Shuai Gao;Kang Yang;Youliang Ding;Songtao Xue
    • Smart Structures and Systems
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    • v.33 no.3
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    • pp.189-199
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    • 2024
  • To properly extract the strain components under varying operational conditions is very important in bridge health monitoring. The abnormal sensor readings can be correctly identified and the expected operational performance of the bridge can be better understood if each strain components can be accurately quantified. In this study, strain components under varying load conditions, i.e., temperature variation and live-load variation are evaluated based on field strain measurements collected from a real concrete box-girder bridge. Temperature-induced strain is mainly regarded as the trend variation along with the ambient temperature, thus a smoothing technique based on the wavelet packet decomposition method is proposed to estimate the temperature-induced strain. However, how to effectively extract the vehicle-induced strain is always troublesome because conventional threshold setting-based methods cease to function: if the threshold is set too large, the minor response will be ignored, and if too small, noise will be introduced. Therefore, an autoencoder framework is proposed to evaluate the vehicle-induced strain. After the elimination of temperature and vehicle-induced strain, the left of which, defined as the model error, is used to assess the operational performance of the bridge. As empirical techniques fail to detect the degraded state of the structure, a clustering technique based on Gaussian Mixture Model is employed to identify the damage occurrence and the validity is verified in a simulation study.

Kinetic Studies on the Thermal Degradation of Pantothenic Acid (Pantothenic Acid의 열분해(熱分解)에 관한 속도론적(速度論的) 연구(硏究))

  • Pyun, Yu-Ryang;Park, Hyun-Jeong;Cho, Hyung-Yong;Lee, Young-Yup
    • Korean Journal of Food Science and Technology
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    • v.13 no.3
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    • pp.188-193
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    • 1981
  • Thermal degradation of pantothenic acid in potassium biphthalate buffer and in food samples such as rice, mushroom and beef was studied as functions of temperature and pH. Thermal degradation of pantothenic acid in buffer and food systems followed first order reaction at temperature between $60{\sim}104^{\circ}C$. Activation energy calculated from the Arrhenius equation ranged from 15,700 cal/mole 17,300 cal/mole for both systems. D values at $120^{\circ}C$ were approximately 18 hours for food samples and 15.4 hours at pH 5.65 for buffer sample. Z values of food samples were about $37^{\circ}C$, which were similar to those of buffer sample. The decomposition rate constant of pantothenic acid in buffer sample decreased when the pH increased from 4.0 to 6.46, but activation energy increased. In the range of $pH\;6.46{\sim}8.0$, decomposition rate constant increased but activation energy decreased as pH increased. The kinetic model of pantothenic acid decomposition in buffer system was proposed on the basis of empirical relationship.

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A Study on the Ozone Consumption Rate for Drinking Water Treatment Process with Ozone Application (오존의 정수처리 적용을 위한 오존소비인자에 관한 연구)

  • Kang, Tae-Hee;Oh, Byung-Soo;Kwon, Soon-Buhm;Sohn, Byeong-Yong;Kang, Joon-Wun
    • Journal of Korean Society of Environmental Engineers
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    • v.27 no.6
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    • pp.663-669
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    • 2005
  • The aim of this study was to investigate the ozone decay pattern for the effective application of ozone in drinking water treatment. In order to measure the ozone decomposition in water, ozone measuring instrument was developed with flow injection analysis (FIA) method. From the result of continuous residual ozone concentration in water, it was confirmed that the ozone decay pattern was divided with instantaneous ozone demand(I.D) and pseudo first-order rate($k_c$) phases, which were influenced by the variation of ozone dose. The empirical model obtained from I.D and $k_c$ values enabled us to predict the residual ozone concentration according to the reaction time, showing the high correlation between model and experimental values. The concentration of OH radical and $R__{ct}$ could be indirectly measured by OH radical probe compound. In both I.D and $k_c$ phases, the production pattern of OH radical could be observed, which was also affected by the variation of ozone dose. Finally, it was confirmed that the ozone consumption rate was varied according to the each drinking water treatment process and seasoning. Therefore, the optimum position and dosage of ozone have to be selected by considering various factors.

An Empirical Study on the Causalities and Effects between International Trade and Economic Growth in China (중국의 국제무역과 경제성장간의 인과관계 및 파급효과)

  • Kim, Jong-Sup
    • International Area Studies Review
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    • v.13 no.1
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    • pp.55-79
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    • 2009
  • This papers studies the causalities and effects on the relationship between international trade and economic growth in China for the period of 1950-2007, using the unit root test, the Granger causality test, the cointegration test, VAR model, and VECM. The results of this study are as follows: Firstly, in the unit root test, I found that each time series was unstable one that has unit root. Secondly, in the Granger Causality test, this papers shows that variable dlexp and dlinp influence on dlgdp and dlgdd, while bilateral causality relation between dlexp and dlgdp, dlexp and dlgdd for the whole period, for the whole period, pre-reform period and post-reform period. Thirdly, there is no cointegraion relation between lgdp(or dlgdp, lgdd, dlgdd) and lexp, linp for lgdd-limp in the whole period, and pre-reform period, while no cointegration relation for the post-reform period. Finally, in the impulse-response test, it was proved that lgdp represents (-) correlation with lexp for the whole period. Thorough the variance decomposition test, it was proved that linp(or dlinp) is the most affected variable of the each data and relation between linp(or dlinp) and lexp(or dlexp) has become bigger recently.

An Empirical Study on Mutual Influence between Economic Index and Distribution Industry in Korean (한국 유통산업이 한국 경제에 미치는 상호영향력에 관한 실증적 연구)

  • YIM, Byung-Jin
    • The Journal of Industrial Distribution & Business
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    • v.10 no.9
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    • pp.53-60
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    • 2019
  • Purpose - The objective of this paper is to discover if there exists a relationship between the economic index and distribution industry index in Korean. Because of the distribution industry boom in the recent years, a lot of interest in the relationship between the economic index and distribution industry index in Korean and the economy has been generated. This article examine on the mutual influence between economic index and distribution industry index in Korean. Research design, data, and methodology - For this purpose, we use the vector-auto regression model, impulse response function and variance decomposition of the economic index and distribution industry index, Granger causality test using weekly data on the economic index and distribution industry price index in korea. The sample period is covering from January 2, 2010 to August 31, 2019. The VAR model can also be linked to cointegration analysis. Cointegration Analysis makes possible to find a mechanism causing x and y to move around a long-run equilibrium (Engle and Granger, 1987). This equilibrium means that external shocks may separate the series temporarily at any particular time, but there will be an overall tendency towards some type of long-run equilibrium. If variables are found to have this tendency they are said to be cointegrated and a long-run relationship between these series is established. These econometric tools have been applied widely into economics and business areas to analyze intertemporal linkages between different time series. Results - This research showed following main results. First, from the basic statistic analysis of the economic index and distribution industry index in Korean, the economic index and the distribution industry index in korea have unit roots. Second, there is at least one cointegration between the economic index and distribution industry index in Korean. Finally, the correlation between of the economic index and the distribution industry index in korea is (+) 0.528876. Conclusions - We find that the distribution industry price index Granger cause the economic index in korea. As a consequence, the distribution industry index affect the economic index in Korean. The distribution industry index to the economic index is stronger than that from the economic index to the distribution industry index.

Dynamically Induced Anomalies of the Japan/East Sea Surface Temperature

  • Trusenkova, Olga;Lobanov, Vyacheslav;Kaplunenko, Dmitry
    • Ocean and Polar Research
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    • v.31 no.1
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    • pp.11-29
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    • 2009
  • Variability of sea surface temperature (SST) in the Japan/East Sea (JES) was studied using complex empirical orthogonal function (CEOF) analysis. Two daily data sets were analyzed: (1) New Generation 0.05o-gridded SST from Tohoku University, Japan (July 2002-July 2006), and (2) 0.25o-gridded SST from the Japan Meteorological Agency (October 1993-November 2006). Linkages with wind stress curl were revealed using 6-h 1o-gridded surface zonal and meridional winds from ancillary data of the Sea- WiFS Project, a special National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) product (1998-2005). SST anomalies (SSTA) were obtained by removing the seasonal signal, estimated as the leading mode of the CEOF decomposition of the original SST. Leading CEOF modes of residual SSTA obtained from both data sets were consistent with each other and were characterized by annual, semiannual, and quasi-biennial time scales estimated with 95% statistical significance. The Semiannual Mode lagged 2 months behind the increased occurrence of the anticyclonic (AC) wind stress curl over the JES. Links to dynamic processes were investigated by numerical simulations using an oceanic model. The suggested dynamic forcings of SSTA are the inflow of subtropical water into the JES through the Korea Strait, divergence in the surface layer induced by Ekman suction, meridional shifts of the Subarctic Front in the western JES, AC eddy formation, and wind-driven strengthening/weakening of large-scale currents. Events of west-east SSTA movement were identified in July-September. The SSTA moved from the northeastern JES towards the continental coast along the path of the westward branch of the Tsushima Current at a speed consistent with the advective scale.