• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1295-1309
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• 2016

This paper is to reproduce the result of Kim et al. (2014) by deriving a benchmark dose lower bound (BMDL) of lead based on the 2005 cohort data set of Children's Health and Environmental Research (CHEER) data set. The ADHD rating scales in the 2005 cohort were not consistent along the three follow-ups since two different ADHD rating scales were used in the cohort. We first unified the ADHD rating scales in the 2005 cohort by deriving a conversion formula using a penalized linear spline. We then constructed two linear mixed models for the 2005 cohort which reflected the longitudinal characteristics of the data set. The first model introduced the random intercept and the random slope terms and the second model assumed the first order autoregressive structure of the error term. Using these two models, we derived the BMDLs of lead and reconfirmed the "regression to the mean" nature of the ADHD score discovered by Kim et al. (2014). We also noticed that there was a definite difference between the sampling distributions of the two cohorts. As a result, taking this difference into account, we were able to obtain the consistent result with Kim et al. (2014).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.572-578
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• 2020

The stock market is affected by unexpected factors, such as politics, society, and natural disasters, as well as by corporate performance and economic conditions. In recent days, artificial intelligence has become popular, and many researchers have tried to conduct experiments with that. Our study proposes an experiment using not only stock-related data but also other various economic data. We acquired a year's worth of data on stock prices, the percentage of foreigners, interest rates, and exchange rates, and combined them in various ways. Thus, our input data became diversified, and we put the combined input data into a nonlinear autoregressive network with exogenous inputs (NARX) model. With the input data in the NARX model, we analyze and compare them to the original data. As a result, the model exhibits a root mean square error (RMSE) of 0.08 as being the most accurate when we set 10 neurons and two delays with a combination of stock prices and exchange rates from the U.S., China, Europe, and Japan. This study is meaningful in that the exchange rate has the greatest influence on stock prices, lowering the error from RMSE 0.589 when only closing data are used.

• Journal of Distribution Science
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• v.11 no.10
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• pp.73-79
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• 2013

Purpose - This study examines the impact of oil price volatility on economic activities in Korea. The new millennium has seen a deregulation in the crude oil market, which invited immense capital inflow into Korea. It has also raised oil price levels and volatility. Drawing on the recent theoretical literature that emphasizes the role of volatility, this paper attends to the asymmetric changes in economic growth in response to the oil price movement. This study further examines several key macroeconomic variables, such as interest rate, production, and inflation. We come to the conclusion that oil price volatility can, in some part, explain the structural changes. Research design, data, and methodology - We use two methodological frameworks in this study. First, in regards to the oil price uncertainty, we use an Exponential-GARCH (Exponential Generalized Autoregressive Conditional Heteroskedasticity: EGARCH) model estimate to elucidate the asymmetric effect of oil price shock on the conditional oil price volatility. Second, along with the estimation of the conditional volatility by the EGARCH model, we use the estimates in a VECM (Vector Error Correction Model). The study thus examines the dynamic impacts of oil price volatility on industrial production, price levels, and monetary policy responses. We also approximate the monetary policy function by the yield of monetary stabilization bond. The data collected for the study ranges from 1990: M1 to 2013: M7. In the VECM analysis section, the time span is split into two sub-periods; one from 1990 to 1999, and another from 2000 to 2013, due to the U.S. CFTC (Commodity Futures Trading Commission) deregulation on the crude oil futures that became effective in 2000. This paper intends to probe the relationship between oil price uncertainty and macroeconomic variables since the structural change in the oil market became effective. Results and Conclusions - The dynamic impulse response functions obtained from the VECM show a prolonged dampening effect of oil price volatility shock on the industrial production across all sub-periods. We also find that inflation measured by CPI rises by one standard deviation shock in response to oil price uncertainty, and lasts for the ensuing period. In addition, the impulse response functions allude that South Korea practices an expansionary monetary policy in response to oil price shocks, which stems from oil price uncertainty. Moreover, a comparison of the results of the dynamic impulse response functions from the two sub-periods suggests that the dynamic relationships have strengthened since 2000. Specifically, the results are most drastic in terms of industrial production; the impact of oil price volatility shocks has more than doubled from the year 2000 onwards. These results again indicate that the relationships between crude oil price uncertainty and Korean macroeconomic activities have been strengthened since the year2000, which resulted in a structural change in the crude oil market due to the deregulation of the crude oil futures.

• The Korean Journal of Applied Statistics
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• v.25 no.1
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• pp.89-99
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• 2012

This study investigates the Granger-causality between economic growth and demand for electricity in Korea, using two quarterly time-series data (real GDP and electricity consumption) for 1970:Q1 through 2009:Q4. We apply Hsiao's sequential procedure to identify a vector autoregressive model to a decision of the optimal lags in the vector error-correction model because the two time-series data contain unit roots respectively and they are cointegrated. According to the empirical results in this study, we find that Hsiao's approach to the Granger-causality indicates a bidirectional causal relation between economic growth and demand for electricity in Korea. Following the Granger and Engle's approach, we also find the statistical evidence on (1) short-run bidirectional causality between real GDP and electricity consumption, (2) bidirectional strong causality between them, and (3) long-run unidirectional causality running from demand for electricity to economic growth. Our results show an inconsistency with the existing studies on Korea's case; however, the results appear to provide more meaningful policy implications for the Korean economy and its strategy of sustainable growth.

• Management & Information Systems Review
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• v.36 no.2
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• pp.81-92
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• 2017

This study was to investigate the elasticity in tourism demand of Chinese tourists visiting Malaysia through ARDL models by using Chinese tourists arrivals, GDP, CPI, transportation costs and others. When China was implementing an open-door policy with foreign countries in the early 15th century, the movement of Chinese was very limited, and then communication between China and other countries was very weak. However, the Chinese government persistently and entirely implemented an open-door policy by participating in the World Trade Organization(WTO) in 2001. The Chinese government has opened the economy through foreign direct investment by providing various incentives for foreign investment. As a result, inbound and outbound Chinese movements increased in the early 21st century. China was one of the top five most visited tourist destinations in the world by 2016, and also Chinese tourists traveling abroad increased, so they made Malaysia a popular tourists destination because of increase sharply to around 1.41 million. This study examined the significance of major economic factors affecting the increase in Chinese tourists arriving in Malaysia. Other factors that induced their arrival included income, tourism prices, transportation costs and promotional activities. Short-run shocks from the Asian economic crisis and the outbreak of SARS were included to understand how tourism demand in Malaysia was affected. Finally this study found that the combination of the ARDL and the Error Correction Model were useful to statistically estimate the elasticities of tourism demand.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.1
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• pp.22-28
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• 2021

Multivariate processes, such as chemical and mechanical process, power plants are operated in a state where several facilities are complexly connected, the fault of a particular system can also have fatal consequences for the entire process. In addition, since process data is measured in an unstable environment, outlier is likely to be include in the data. Therefore, monitoring technology is essential, which can remove outlier from measured data and detect failures in advance. In this paper, data obtained from dynamic and multivariate process models was used to detect fault in various type of processes. The dynamic process is a simulation of a process with autoregressive property, and the multivariate process is a model that describes a situation when a specific sensor fault. Mahalanobis distance was used to remove outlier contained in the data generated by dynamic process model and multivariate process model, and fault detection was performed using ICA. For comparison, we compared performance with and a conventional single ICA method. The proposed fault detection method improves performance by 0.84%p for bias data and 6.82%p for drift data in the dynamic process. In the case of the multivariate process, the performance was improves by 3.78%p, therefore, the proposed method showed better fault detection performance.

• Management & Information Systems Review
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• v.39 no.2
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• pp.17-37
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• 2020

The purpose of this study is to investigate the global spillover effects through the existence of linear and nonlinear causal relationships between the US, European and BRIC financial markets after the period from the introduction of the Euro, the financial crisis and the subsequent EU debt crisis in 2007~2010. Although the global spillover effects of the financial crisis are well described, the nature of the volatility effects and the spread mechanisms between the US, Europe and BRIC stock markets have not been systematically examined. A stepwise filtering methodology was introduced to investigate the dynamic linear and nonlinear causality, which included a vector autoregressive regression model and a multivariate GARCH model. The sample in this paper includes the post-Euro period, and also includes the financial crisis and the Eurozone financial and sovereign crisis. The empirical results can have many implications for the efficiency of the BRIC stock market. These results not only affect the predictability of this market, but can also be useful in future research to quantify the process of financial integration in the market. The interdependence between the United States, Europe and the BRIC can reveal significant implications for financial market regulation, hedging and trading strategies. And the findings show that the BRIC has been integrated internationally since the sub-prime and financial crisis erupted in the United States, and the spillover effects have become more specific and remarkable. Furthermore, there is no consistent evidence supporting the decoupling phenomenon. Some nonlinear causality persists even after filtering during the investigation period. Although the tail distribution dependence and higher moments may be significant factors for the remaining interdependencies, this can be largely explained by the simple volatility spillover effects in nonlinear causality.

• Journal of Korean Society of Forest Science
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• v.90 no.2
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• pp.217-226
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• 2001

This study estimated the impacts of the building permit area change on the forest products import quantities in Korea. The first objective of this dissertation is to analyze whether there is any causal relationship between change in the building permit area and changes in the import quantities of forest products in Korea. Assuming that there is any causal relationship, the second objective is to evaluate the dynamics of the impacts of the building permit area change on the forest products import quantities in Korea. The relationship between the building permit area and the import quantity was represented by bivariate vector autoregressive or vector error correction model. Whether there is any causal relationship between change in the building permit area and changes in the import quantities of forest products was analyzed by the causality test of Granger. And the dynamics of the impacts of the building permit area change on the forest products import quantities were evaluated by variance decomposition analysis and impulse response analysis. The import quantity of forest products can be explained by the lagged building permit area variables and the lagged import quantity variables in Korea. Change in the building permit area causes change in the high-density fiberboard import quantity in Korea. In the bivariate model of the high-density fiberboard import quantity, after six months, the building permit area change accounts for about ten percent of variation in the import quantity, and its own change accounts for about ninety percent of variation in the import quantity. On the other hand, the impact of a shock to the building permit area is significant for about six months on the import quantity of high-density fiberboard in Korea. That is, if the building permit area change indeed had an impact on the import quantity of high-density fiberboard in Korea, it was only of a short-term nature.

• Journal of the korean academy of Pediatric Dentistry
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• v.49 no.3
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• pp.274-284
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• 2022

The purpose of this study was to analyze the trend of the number of births in Gwangju and the number of outpatients in Pediatric Dentistry at Chonnam National University Dental Hospital over the past 10 years (2010 - 2019) and predict the next year using time series analysis. The number of births showed an unstable downward trend with monthly variations, with the highest in January and the lowest in December. The average number of births in 2020 was predicted to be 682 (595 to 782, 95% CI), and the actual number of births was an average of 610. The number of outpatients was relatively stable, showing a month-to-month variation, with highest in August and the lowest in June. The average number of patients in 2020 was predicted to be 603 (505 to 701, 95% CI), and the average number of actual visits was 587. Despite the decrease in the number of births, the number of outpatients was expected to increase somewhat. Due to the special situation of COVID-19, the actual number of births and patients was to be slightly lower than the predicted values, but it was that they were within the predicted confidence interval. Time series analysis can be used as a basic tool to prepare for the low fertility era in the field of pediatric dentistry.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.255-266
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• 2021

Investment demand for factory facilities has increased due to the balloon effect caused by housing price regulation. This study investigated the impact of the real estate market and macroeconomic factors on the bid price ratio of apartment auctions and factory auctions, focusing on the metropolitan area. To this end, we reviewed theories and previous studies on real estate auctions, and examined how macroeconomic variables affect bid price ratio of apartments and factories using the panel vector autoregressive model. It was found that the increase in the apartment bid price ratio increases as the participation in apartment auctions increases. However, as the factory bid price ratio increases, the factory bid price ratio does not increase, it was confirmed that the positive (+) relationship between the successful bid price ratio and the bid price ratioe does not exist, unlike previous studies. Based on the analysis results, it is suggested that the real estate market and macroeconomic factors should be considered for the stable operation of the related relevant auction system. This study has limitations in that it is limited to the metropolitan area. In the future, research that expands the scope of research to the whole country and provinces should be conducted.