• The Korean Journal of Applied Statistics
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• v.16 no.2
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• pp.351-364
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• 2003

This paper derives Lagrange multiplier tests based on Double-Length Artificial Regression and Outer-Product Gradient for testing linear and log-linear panel regressions against Box-Cox alternatives. The proposed DLR based LM tests are easy to implement in an error component model. From the Monte Carlo study, the DLR based LM tests are recommended for testing functiona forms.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.697-710
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• 2021

Relative error prediction is preferred over ordinary prediction methods when relative/percentile errors are regarded as important, especially in econometrics, software engineering and government official statistics. The relative error prediction techniques have been developed in linear/nonlinear regression, nonparametric regression using kernel regression smoother, and stationary time series models. However, random effect models have not been used in relative error prediction. The purpose of this article is to extend relative error prediction to some of generalized linear mixed model (GLMM) with panel data, which is the random effect models based on gamma, lognormal, or inverse gaussian distribution. For better understanding, the real auto insurance data is used to predict the claim size, and the best predictor and the best relative error predictor are comparatively illustrated.

• International Commerce and Information Review
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• v.12 no.4
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• pp.151-170
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• 2010

The present study made an empirical analysis for investigating the competitiveness of technology trades in Korea. In particular, the study deduced the correlation between technology export and technology import using the variables of Gross Domestic Expenditure on R&D and Per capita industry value added Productivity and employed fixed effect model in panel linear regression model. It is found that the R&D expenditure of OECD countries made a significant effect on the technology import and the value-added labor productivity made a significant result on both technology export and import. Therefore, it showed that the technology trade in Korea made a sensitive response to labor productivity in OECD countries. By panel analysis, machine, construction, ICT, and service industry affect most on technology export in Korea for recent 5 years. For technology import, electric-electron, chemical, service, and construction industry have significant effects. This study contributed to understanding of industrial characteristics affecting technology trades in Korea and empirical analysis to show correlation between the factors affecting technology trade.

• Communications for Statistical Applications and Methods
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• v.26 no.3
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• pp.315-323
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• 2019

Panel data sets have recently been developed in various areas, and many recent studies have analyzed panel, or longitudinal data sets. Often a dichotomous dependent variable occur in survival analysis, biomedical and epidemiological studies that is analyzed by a generalized linear mixed effects model (GLMM). The most common estimation method for the binary panel data may be the maximum likelihood (ML). Many statistical packages provide ML estimates; however, the estimates are computed from numerically approximated likelihood function. For instance, R packages, pglm (Croissant, 2017) approximate the likelihood function by the Gauss-Hermite quadratures, while Rchoice (Sarrias, Journal of Statistical Software, 74, 1-31, 2016) use a Monte Carlo integration method for the approximation. As a result, it can be observed that different packages give different results because of different numerical computation methods. In this note, we discuss the pros and cons of numerical methods compared with the exact computation method.

• Journal of Distribution Science
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• v.12 no.11
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• pp.25-34
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• 2014

Purpose - Considering that the governments' official statistics on the optimum scale of the domestic service industry will be crucial in future, this study's results will be used as an important benchmark to develop and verify the parameters in the government's official statistics. Research design, data, and methodology - To identify the appropriate scale of Korea's service industry and its adequacy, I have determined them through estimation using a regression method involving panel data analysis on the panel data of 30 OECD countries. Results - The regression coefficient provided indications of being non-linear. This means that a U-shaped curve relationship exists-that is, the level of the economic growth leverage decreases along with the service industry's growth up to the level of 70.9% in terms of the Korean service industry's adequacy; it increases along with the service industry's growth at a level higher than 70.9%. Conclusions - While the current proportion of the size of the service industry among all industries in Korea stands at 50.7%, its proper proportion estimated by a regression analysis was 70.9%.

• Journal of the Korean Data and Information Science Society
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• v.28 no.3
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• pp.547-557
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• 2017

The health-related quality of life data are commonly skewed and bounded with spike at the perfect health status, and the variance tended to be heteroscedastic. In this study, we have developed a prediction model for EQ-5D using linear regression model, beta regression model, and extended beta regression model with mean and precision submodel, and also compared the predictive accuracy. The extended beta regression model allows to model skewness and differences in dispersion related to covariates. Although the extended beta regression model has higher prediction accuracy than the linear regression model, the overlapped confidence intervals suggested that the extended beta regression model was superior to the linear regression model. However, the expended beta regression model could explain the heteroscedasticity and predict within the bounded range. Therefore, the expended beta regression model are appropriate for fitting the health-related quality of life data such as EQ-5D.

• Asian-Australasian Journal of Animal Sciences
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• v.8 no.5
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• pp.505-513
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• 1995

The major factors affecting productivity on daily farms in Queensland, Australia, were determined using the stepwise linear regression approach. The data were obtained from a survey conducted on the total population of daily farms in Queensland in 1987. These data were divided into six major dailying regions. The technique was applied using 12 independent variables believed by a panel of experienced research and extension personnel to exert the most influence on milk production. The regression equations were all significant (p < 0.001) with the percentage coefficients of determination ranging from 62 to 76% for equations developed using' total farm milk: production as the dependent variable. Three of the variables affecting total farm milk: production were found to be common to all six regions. These were; the amount of supplementary energy fed, the area set aside to irrigate winter feed and the size of the area used for dailying. Higher production farms appeared to be more efficient in that they consistently produced milk production levels higher than those estimated from the regression equation for their region. Other methods of analysis including robust regression and non linear regression techniques were unsuccessful in overcoming this problem and allowing development of a model appropriate for farms at all levels of production.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.2
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• pp.363-370
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• 2022

The study aims to probe the impact of foreign ownership on Vietnamese listed firms' capital structure. This study employs panel data of 288 non-financial firms listed on the Ho Chi Minh City stock exchange (HOSE) and Ha Noi stock exchange (HNX) in 2015-2019. In this research, we applied a Bayesian linear regression method to provide probabilistic explanations of the model uncertainty and effect of foreign ownership on the capital structure of non-financial listed enterprises in Vietnam. The findings of experimental analysis by Bayesian linear regression method through Markov chain Monte Carlo (MCMC) technique combined with Gibbs sampler suggest that foreign ownership has substantial adverse effects on the firms' capital structure. Our findings also indicate that a firm's size, age, and growth opportunities all have a strong positive and significant effect on its debt ratio. We found that the firms' profitability, tangible assets, and liquidity negatively and strongly affect firms' capital structure. Meanwhile, there is a low negative impact of dividends and inflation on the debt ratio. This research has ramifications for business managers since it improves a company's financial resources by developing a strong capital structure and considering foreign investment as a source of funding.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.21 no.3
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• pp.169-176
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• 1988

In order to obtain the objective indices which can assess the quality and the shelf-life of dried squid, nonenzymatic browning, carbonyl value, trimethyl amine (TMA) and trimethyl amine oxide (TMAO) decrease and panel test were determined in dried squid at various water activity levels. When the data of nonenzymatic browning fit a zero order equation, $r^2$ value were more than 0.92 except aw 0.52 for 0.8241. Through variance analysis for the data of browning extent and TMAO decrease, the confidence limits of regression equation were $99\%$ and their limit values of shelf-life were shown 0.45390 O. D./g. solid and 190.322 g/g respectively. In case of TMAO, $r^2$ value was calculated more than 0.95. Linear regression equation for the correlation between browning data and average panel score was Y=0.6138-0.053X and its $r^2$ value was 0.9285. Also in TMAO decrease, the equation was InY=2.0314+0.08269x and $r^2$ value was 0.7854. The shelf-life, evaluated by nonenzymatic browning, TMAO decrease and panel test, was 110-170 days at aw 0.45-0.76 except aw 0.15.

• Child Studies in Asia-Pacific Contexts
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• v.5 no.1
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• pp.51-62
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• 2015

This study examined the role of ethnicity and extended family relationship in the longitudinal patterns of unmarried resident fathers' engagement with young children in the U.S. Using three waves of panel data from the Fragile Families and Child Wellbeing Study (FFCWS), data obtained from 292 respondents were analyzed by the Linear Mixed Effects Regression (LMER) method. Findings suggested that Black unmarried resident fathers exhibited more engagement with their infants at age one than their White counterparts did, but the initial difference reversed by age five as a result of decreasing engagement among Black fathers over time and comparatively increasing engagement among Whites. Results also suggested that Black unmarried resident fathers with a high relationship level with their extended family members exhibited less engagement with their infants than Black fathers with a low relationship level, but the initial difference reversed by age five as a result of decreasing engagement among Black fathers with a low relationship level over time and comparatively increasing engagement among Black fathers with a high relationship level.