• Korean Journal of Social Welfare
• /
• v.62 no.2
• /
• pp.161-185
• /
• 2010

The purpose of this study is to verify the causal relationship between depression and aggressiveness among adolescents. The 4-year longitudinal data collected from 2,670 4th grade elementary school students by the Korean Youth Panel study was used in this study. From the analysis result using the Autoregressive Cross-Lagged Model, the depression and aggressiveness in adolescents were continued from elementary school 4th grade to middle school 7th grade in significant stability. In addition, the previous aggressiveness turned out to have significant positive effect on the later period depression. Similarly, the previous depression had significant effect on the later aggressiveness, but the direction was negative. This means that the adolescents's depression increases as their aggressiveness increases, but as the depression increases, the later aggressiveness of the adolescents decreases. There were no differences between girls and boys within the relationship of these two variables. Finally, the implication derived from the results, the limitation of this study, and suggestion for following studies were presented.

• Journal of The Korean Astronomical Society
• /
• v.40 no.4
• /
• pp.99-106
• /
• 2007

Statistical analyses were performed to investigate the relative success and accuracy of daily maximum X-ray flux (MXF) predictions, using both multilinear regression and autoregressive time-series prediction methods. As input data for this work, we used 14 solar activity parameters recorded over the prior 2 year period (1989-1990) during the solar maximum of cycle 22. We applied the multilinear regression method to the following three groups: all 14 variables (G1), the 2 so-called 'cause' variables (sunspot complexity and sunspot group area) showing the highest correlations with MXF (G2), and the 2 'effect' variables (previous day MXF and the number of flares stronger than C4 class) showing the highest correlations with MXF (G3). For the advanced three days forecast, we applied the autoregressive timeseries method to the MXF data (GT). We compared the statistical results of these groups for 1991 data, using several statistical measures obtained from a $2{\times}2$ contingency table for forecasted versus observed events. As a result, we found that the statistical results of G1 and G3 are nearly the same each other and the 'effect' variables (G3) are more reliable predictors than the 'cause' variables. It is also found that while the statistical results of GT are a little worse than those of G1 for relatively weak flares, they are comparable to each other for strong flares. In general, all statistical measures show good predictions from all groups, provided that the flares are weaker than about M5 class; stronger flares rapidly become difficult to predict well, which is probably due to statistical inaccuracies arising from their rarity. Our statistical results of all flares except for the X-class flares were confirmed by Yates' $X^2$ statistical significance tests, at the 99% confidence level. Based on our model testing, we recommend a practical strategy for solar X-ray flare predictions.

• Journal of the Korean Statistical Society
• /
• v.35 no.1
• /
• pp.37-47
• /
• 2006

Recently, as a result of the growing interest in modeling stationary processes with discrete marginal distributions, several models for integer valued time series have been proposed in the literature. One of these models is the integer-valued autoregressive (INAR) models. However, when modeling with integer-valued autoregressive processes, the distributional properties of forecasts have been not yet discovered due to the difficulty in handling the Steutal Van Ham thinning operator 'o' (Steutal and van Ham, 1979). In this study, we derive the mean squared error of h-step-ahead prediction from a Poisson INAR(1) process, reflecting the effect of the variability of parameter estimates in the prediction mean squared error.

• Korean Journal of Child Studies
• /
• v.35 no.5
• /
• pp.135-154
• /
• 2014

This study examined the causal relationships between parenting stress and self-efficacy of Korean mothers with an infant according to employment status using the second through fourth wave data of the Panel Study of Korean Children (PSKC). Autoregressive cross-lagged modeling was performed to test the longitudinal reciprocal relationships between the two constructs. Our results indicated that both maternal parenting stress and self-efficacy were consistent over time. The results also indicated that there was a significant cross-lagged effect of maternal parenting stress on their self-efficacy, rather than vice versa. No differences between working and non-working mothers were found in the relationship between the two constructs.

• Communications for Statistical Applications and Methods
• /
• v.21 no.2
• /
• pp.169-181
• /
• 2014

Marginalized random effects models (MREM) are commonly used to analyze longitudinal categorical data when the population-averaged effects is of interest. In these models, random effects are used to explain both subject and time variations. The estimation of the random effects covariance matrix is not simple in MREM because of the high dimension and the positive definiteness. A relatively simple structure for the correlation is assumed such as a homogeneous AR(1) structure; however, it is too strong of an assumption. In consequence, the estimates of the fixed effects can be biased. To avoid this problem, we introduce one approach to explain a heterogenous random effects covariance matrix using a modified Cholesky decomposition. The approach results in parameters that can be easily modeled without concern that the resulting estimator will not be positive definite. The interpretation of the parameters is sensible. We analyze metabolic syndrome data from a Korean Genomic Epidemiology Study using this method.

• Journal of Korea Society of Industrial Information Systems
• /
• v.19 no.3
• /
• pp.115-125
• /
• 2014

This paper has two purposes. The first is to suggest the new and simple method to derive a regional input-output model from the national input-output table published by the Bank of Korea. The interregional input-output table has not been devised in spite of its potential use while the national table has been made every five years with the revised version during each five years. Second, this paper aims to derive Kangwon interregional input-output model from the national model using the regional supply proportion of industry and to analyze the effect of medical tourism industry on the regional economy of Kangwon Province. The paper measures, in particular, the effect of medical tourism industry on the financial self-sufficiency of Kangwon Province using the estimated output elasticity of tax revenue with the autoregressive distributed lag scheme ADL(1,1) in which the dependent variable and the single explanatory variable are each lagged once.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.7
• /
• pp.1-9
• /
• 2021

This paper investigates the impact of the domestic and global outbreak of the coronavirus (COVID-19) pandemic on the trading size of the Malaysian stock (MS) market. The theoretical model posits that stock markets are affected by their response to disasters and events that arise in the international or local environments, as well as to several financial factors such as stock volatility and spread bid-ask prices. Using daily time-series data from 27 January to 12 May 2020, this paper utilizes the traditional Augmented Dickey and Fuller (ADF) technique and Zivot and Andrews with structural break' procedures for a stationarity test analysis, while the autoregressive distributed lag (ARDL) method is applied according to the trading size of the MS market model. The analysis considered almost all 789 listed companies investing in the main stock market of Malaysia. The results confirmed our hypotheses that both the daily growth in the active domestic and global cases of coronavirus (COVID-19) has significant negative effects on the daily trading size of the stock market in Malaysia. Although the COVID-19 has a negative effect on the Malaysian stock market, the findings of this study suggest that the COVID-19 pandemic may have an asymmetric effect on the market.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.2
• /
• pp.809-820
• /
• 2021

The study aimed to investigate the impact of sectoral bank credit facilities provided by commercial banks on the non-oil economic growth in Saudi Arabia. Bank credit facilities are given for nine economic sectors: agriculture, manufacturing, mining, electricity and water, health services, construction, wholesale and retail trade, transportation and communications, services, and finance sector. The study employs annual data from 1970 to 2019. The study employs the Autoregressive Distributed Lag (ARDL) approach to identify the long-run and short-run dynamics relationships among the variables. The main results reveal that the overall impact of total bank credit has a significant and positive effect on non-oil economic growth in KSA. The results revealed that the effect of bank credit on the non-oil GDP growth in the short and long run was uneven. The study finds that all sectors have a positive and significant impact in the long run, except for the agricultural and mining sectors. Likewise, all sectors have a positive and significant impact in the short run, except for construction, finance, services, and transportation & communications. As a result, bank credit facilities in different sectors have played an important role in enhancing the non-oil economic growth in the KSA.

• Korean Journal of Social Welfare Studies
• /
• v.43 no.1
• /
• pp.5-29
• /
• 2012

The present study was to explore what makes adolescents think of themselves as troublemakers even without conduct problems. It was expected that the failure to attain socio-developmental milestones(e.g., healthy relationships with others, academic achievement) would lead to form trait aspect of deviant self-concept. A latent state-trait autoregressive modeling was used to analyze five annual waves of data from 3,449 adolescents taken from the Korean Youth Panel Study. We decomposed trait and state aspect of deviant self-concept and identified significant predictors of trait-like deviant self-concept, while additionally testing for gender differences. Our results showed that conduct problems had greater effect on deviant self-concept among girls compared with boys. Conduct problem was most predictive of deviant self-concept, and yet both poor peer-relations and school failures predisposed adolescents to have deviant self-concept. Low academic achievement conferred risk for trait aspects of deviant self-concept with no gender difference, whereas poor peer relation was more predictive among girls. It highlights the cultural value system underlying self-concept and how and why adolescents think of themselves as troublemakers.

• Journal of the Korean Statistical Society
• /
• v.34 no.4
• /
• pp.345-366
• /
• 2005

This paper considers the cointegrating vector estimator in the error correction model with stationary covariates, which combines the stationary vector autoregressive model and the nonstationary error correction model. The cointegrating vector estimator is shown to follow the locally asymptotically mixed normal distribution. The variance of the estimator depends on the co­variate effect of stationary regressors, and the asymptotic efficiency improves as the magnitude of the covariate effect increases. An economic application of the money demand equation is provided.