• Journal of Korea Trade
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• v.25 no.1
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• pp.1-17
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• 2021

Purpose - The global trend of protectionism has expanded since the onset of US President Donald Trump's administration in 2017. This global phenomenon has led to a significant reduction in world trade volume and a negative impact on economic development in some countries where the external sector accounts for a large proportion of GDP. Although Korea is a country vulnerable to this deteriorating trade environment, few studies have examined the relationship between protectionism and its business cycles based on Korean data. Thus, this paper investigates the impact of protectionism on Korea's business cycle. Design/methodology - To identify future implications, we conduct a structural vector autoregression (VAR) analysis using monthly Korean data from 1994 to 2015. Macroeconomic variables in the model include the industrial production index, inflation rates, exports (or net exports), interest rates, and exchange rates. For the identification of the shock reflecting the expansion of protectionism, we use an antidumping investigation (ADI) data. Since ADIs are followed generally by the imposition of antidumping tariffs, they have no contemporaneous impact on tariffs and are also contemporaneously exogenous to other endogenous variables in the VAR model. We examine two kinds of ADI shocks i) shocks on Korean exports imposed by Korea's trading partners (ADI-imposed shocks) and ii) shocks on imports imposed by the Korean government (ADI-imposing shocks). Findings - We find that Korea's exports decline sharply due to ADI-imposed shocks; the lowest point at the third month after the initial shock; and do not recover until 24 months later. Simultaneously, the inflation rate decreases. Therefore, the ADI-imposed shock can be regarded as a negative shock on the demand curve where both production and price decrease. In contrast, the ADI-imposing shock generates a different response. The net exports decline, but the inflation rate increases. These can be seen as standard responses with respect to the negative shock on the supply curve. Originality/value - We shed light on the relationship between protectionism and Korea's economic fluctuations, which is rarely addressed in previous studies. We also consider the effects of both protective policy measures on imports to Korea imposed by the Korean government and on policy measures imposed by Korea's trading partner countries on its exports.

• Environmental and Resource Economics Review
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• v.13 no.2
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• pp.175-194
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• 2004

Volumes of research have been implemented to estimate and predict the oil price. These models, however, fail in accurately predicting oil price as a model composed of only a few observable variables is limiting. Unobservable variables and news that have been overlooked in past research, yet have a high likelihood of affecting the oil price. Hence, this paper analyses the news impact on the price. The standard GARCH model fails in capturing some important features of the data. The estimated news impact curve for the GARCH model, which imposes symmetry on the conditional variances, suggests that the conditional variance is underestimated for negative shocks and overestimated for positive shocks. Hence, this paper introduces the asymmetric or leverage volatility models, in which good news and bad news have different impact on volatility. They include the EGARCH, AGARCH, and GJR models. The empirical results showed that negative shocks introduced more volatility than positive shocks. Overall, the AGARCH and GJR were the best at capturing this asymmetric effect. Furthermore, the GJR model successfully revealed the shape of the news impact curve and was a useful approach to modeling conditional heteroscedasticity.

• Communications for Statistical Applications and Methods
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• v.16 no.1
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• pp.21-29
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• 2009

Engle and Russell (1998) proposed the ACD(Autoregressive Conditional Duration) model to explain the relationship between the prices and the duration times of the stocks. In this paper, we first introduce the various types of the ACD models such as the linear ACD, log ACD and Box-Cox ACD models and we evaluate the performance of the models for analysing the transaction data of the stocks in Korea.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.2
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• pp.269-275
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• 2019

This study intended to examine the relationship between inflation and unemployment rate in Indonesia during 1987 to 2018 period. The study applied a quantitative method using Vector Error Correction Model (VECM) in order to comprehensively understand the causality between inflation and unemployment rates. The data were collected from various main sources including the World Bank, Central Bank of Indonesia, and Central Bureau of Statistics (BPS). The findings showed that inflation has a one-way relationship toward unemployment in Indonesia and it occurs at the third lag. Impulse Response Function (IRF), shows that the inflation rate are fluctuating in response to the shock of unemployment. The unemployment rate responses to shocks from inflation initially increased until it is eventually diminished. It shows that the shocks caused by the impact of inflation were only in the short term. Further, inflation in the three previous lags will have consequences for the unemployment rate in the year. Lastly, both in the long run and short run, unemployment did not affect inflation rates. These findings suggest that high inflation in Indonesia is determined the rising price of basic commodities and fuel. In addition, most companies in Indonesia applying capital intensive so that employment growth in Indonesia is small.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.19 no.1
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• pp.51-56
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• 2013

From the time the product is manufactured until it is carried and ultimately used, the product is subjected to some form of handling and transportations. During this process, the product can be subjected to many potential hazards. One of them is the damage caused by shocks. In order to design a product-package system to protect the product, the peak acceleration or G force to the product that causes damage needs to be determined. When a corrugated fiberboard box loaded with products is dropped onto the ground, part of the energy acquired due to the action of the gravitational acceleration during the free fall is dissipated in the product and the package in various ways. The shock absorbing characteristics of the packaging cushion materials are presented as a family of cushion curves in which curves showing peak accelerations during impacts for a range of static loads are shown for several drop heights. The new method for determining the shock absorbing characteristics of cushioning materials for protective packaging has been described and demonstrated. It has been shown that cushion curves can be produced by combining the static compression and impact characteristics of the material. The dynamic factor was determined by the iterative least mean squares (ILMS) optimization technique in which the discrepancies between peak acceleration data predicted from the theoretical model and obtained from the impact tests are minimized. The approach enabled an efficient determination of cushion curves from a small number of experimental impact data.

• Journal of Korea Port Economic Association
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• v.31 no.1
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• pp.1-14
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• 2015

The standard GARCH model imposing symmetry on the conditional variance, tends to fail in capturing some important features of the data. This paper, hence, introduces the models capturing asymmetric effect. They are the EGARCH model and the GJR model. We provide the systematic comparison of volatility models focusing on the asymmetric effect of news on volatility. Specifically, three diagnostic tests are provided: the sign bias test, the negative size bias test, and the positive size bias test. This paper shows that there is significant evidence of GARCH-type process in the data, as shown by the test for the Ljung-Box Q statistic on the squared residual data. The estimated unconditional density function for squared residual is clearly skewed to the left and markedly leptokurtic when compared with the standard normal distribution. The observation of volatility clustering is also clearly reinforced by the plot of the squared value of residuals of export volume and values. The unconditional variance of both export volumes and export value indicates that large shocks of either sign tend to be followed by large shocks, and small shocks of either sign tend to follow small shocks. The estimated export volume news impact curve for the GARCH also suggests that $h_t$ is overestimated for large negative and positive shocks. The conditional variance equation of the GARCH model for export volumes contains two parameters ${\alpha}$ and ${\beta}$ that are insignificant, indicating that the GARCH model is a poor characterization of the conditional variance of export volumes. The conditional variance equation of the EGARCH model for export value, however, shows a positive sign of parameter ${\delta}$, which is contrary to our expectation, while the GJR model exhibits that parameters ${\alpha}$ and ${\beta}$ are insignificant, and ${\delta}$ is marginally significant. That indicates that the asymmetric volatility models are poor characterization of the conditional variance of export value. It is concluded that the asymmetric EGARCH and GJR model are appropriate in explaining the volatility of export volume, while the symmetric standard GARCH model is good for capturing the volatility.

• Journal of Korea Port Economic Association
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• v.30 no.3
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• pp.1-14
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• 2014

This paper aims at measuring how new information is incorporated into volatility estimates. Various GARCH models are compared and estimated with daily BDI(Baltic Dry Index) data. While most researchers agree that volatility is predictable, they differ on how this volatility predictability should be modelled. This study, hence, introduces the asymmetric or leverage volatility models, in which good news and bad news have different predictability for future. We provide the systematic comparison of volatility models focusing on the asymmetric effect of news on volatility. Specifically, three diagnostic tests are provided: the sign bias test, the negative size bias test, and the positive size bias test. From the Ljung-Box test statistic for twelfth-order serial correlation for the level we do not find any significant serial correlation in the unpredictable BDI. The coefficients of skewness and kurtosis both indicate that the unpredictable BDI has a distribution which is skewed to the left and significantly flat tailed. Furthermore, the Ljung-Box test statistic for twelfth-order serial correlations in the squares strongly suggests the presence of time-varying volatility. The sign bias test, the negative size bias test, and the positive size bias test strongly indicate that large positive(negative) BDI shocks cause more volatility than small ones. This paper, also, shows that three leverage models have problems in capturing the correct impact of news on volatility and that negative shocks do not cause higher volatility than positive shocks. Specifically, the GARCH model successfully reveals the shape of the news impact curve and is a useful approach to modeling conditional heteroscedasticity of daily BDI.

• Korean Circulation Journal
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• v.53 no.5
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• pp.331-343
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• 2023

Background and Objectives: The prognostic implication of right atrial (RA) and left atrial (LA) size for an immediate success of direct current cardioversion (DCCV) in atrial fibrillation (AF) remains unclear. This study aimed to compare RA and LA size for the prediction of DCCV success. Methods: Between 2012 and 2018, 734 consecutive outpatients were screened for our prospective registry. Each eligible patient received a medical history, blood analysis, and transthoracic echocardiography with a focus on indexed RA (iRA) area and LA volume (iLAV) prior to DCCV with up to three biphasic shocks (200-300-360 J) or additional administration of amiodarone or flecainide to restore sinus rhythm. Results: We enrolled 589 patients, and DCCV was in 89% (n=523) successful. Mean age was 68 ± 10 years, and 40% (n=234) had New York heart association class >II. A prevalence of the male sex (64%, n=376) and of persistent AF (86%, n=505) was observed. Although DCCV success was associated with female sex (odds ratio [OR], 1.88; 95% confidence interval [CI], 1.06-3.65), with absence of coronary heart disease and normal left ventricular function (OR, 2.24; 95% CI, 1.26-4.25), with short AF duration (OR, 1.93; 95% CI, 1.05-4.04) in univariable regression, only iRA area remained a stable and independent predictor of DCCV success (OR, 0.27; 95% CI, 0.12-0.69; area under the curve 0.71), but not iLAV size (OR, 1.16; 95% CI, 1.05-1.56) in multivariable analysis. Conclusions: iRA area is superior to iLAV for the prediction of immediate DCCV success in AF.