• Korea Trade Review
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• v.47 no.2
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• pp.175-193
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• 2022

This study analyzes the effects of road transportation networks on the local economy in korea. The analysis methods are SNA and spatial panel regression model. The subjects of this study are inland areas of Korea, and the research period is from 2010 to 2019. The network analysis showed that the connection centrality of Gyeongg-do was high internally and externally. Gyeonggi-do has played a central role in the domestic road freight transportation industry. The results of spatial panel regression analysis showed that there was economic competition between regions. Domestic road transportation industry has been competitive among regions and has economic ripple effect. And Internal cargo has been shown to boost the economy of the region. But internal cargo has been shown to lower the economy of surrounding regions, but external cargo has been shown to increase the economy. In order to revitalize the local economy, it is necessary to increase road cargo.

• Survey Research
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• v.11 no.1
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• pp.1-18
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• 2010

We compare various imputation methods for compensating wave nonresponse that are commonly adopted in many panel surveys. Unlike the cross-sectional survey, the panel survey is involved a time-effect in nonresponse in a sense that nonresponse may happen for some but not all waves. Thus, responses in neighboring waves can be used as powerful predictors for imputing wave nonresponse such as in longitudinal regression imputation, carry-over imputation, nearest neighborhood regression imputation and row-column imputation method. For comparison, we carry out a simulation study on a few income data from the Korean Welfare Panel Study based on two performance criteria: predictive accuracy and estimation accuracy. Our simulation shows that the ratio and row-column imputation methods are much more effective in terms of both criteria. Regression, longitudinal regression and carry-over imputation methods performed better in predictive accuracy, but less in estimation accuracy. On the other hand, nearest neighborhood, nearest neighbor regression and hot-deck imputation show higher performance in estimation accuracy but lower predictive accuracy. Finally, the mean imputation shows much lower performance in both criteria.

• 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.

• The Korean Journal of Applied Statistics
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• v.14 no.1
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• pp.121-135
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• 2001

This paper derives the BLUP in a panel data regression model with two way error components and investigates the performance of various predictors. Through simulation study and real data anaysis some of basic finding is following: the computationally simple FGLS(AM, SA) predictors perform reasonably well when compared with the computationally involved MLE and RMLE predictors.

• Korea Trade Review
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• v.47 no.6
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• pp.173-187
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• 2022

Since the economic reform 1991, Indian has been implementing policies to promote trade and foreign direct investment (FDI). In particular, since the inauguration of the Modi government in 2014, India has created an economic environment in which more FDI can be launched and more jobs created in manufacturing sector. This study aims to analyze between FDI outflows and export from Korea to India. Using the quarter data from 2000 to 2021, this study examines panel regression. From the panel regression result, Korea's FDI outflows to India has a significantly positive impact on the Korea's export into India. Therefore, the relationship between FDI outflows and export from Korea to India is complementary. It is due that Korea's companies invest into India directly for the purpose of construction of production factors, and export capital goods and intermediate goods for producing in the factors. Therefore, for promoting FDI and export between Korea and India, Korean government should do continuous economic cooperation and discussion for the cooperation with Indian government.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.461-479
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• 2006

This paper derives joint and conditional Lagrange multiplier tests based on Double-Length Artificial Regression(DLR) for testing functional form and/or the presence of individual(time) effect in a panel regression model. Small sample properties of these tests are assessed by Monte Carlo study, and comparisons are made with LM tests based on Outer Product Gradient(OPG). The results show that the proposed DLR based LM tests have the most appropriate finite sample performance.

• Journal of the Korean Statistical Society
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• v.28 no.4
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• pp.489-501
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• 1999

In this paper, we consider the panel data regression model in which the disturbances have nested error component. We derive a Lagrange Multiplier(LM) test which is jointly testing for the presence of random individual effects and nested effects under the normality assumption of the disturbances. This test extends the earlier work of Breusch and Pagan(1980) and Baltagi and Li(1991). Further, it is shown that this LM test has the same asymptotic distribution without normality assumption of the disturbances.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2016.10a
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• pp.70-76
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• 2016

• 유체기계공업학회:학술대회논문집
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• 2006.08a
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• pp.487-488
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• 2006

In these days, demand of a LCD monitor is remarkably increasing with development of the LCD technology. However, there are thermal problems for improvement of efficiency for the LCD monitor. Thus, this research analyzed thermal problems such as convection and conduction heat transfer characteristics in the LCD monitor using an infrared (IR) camera. Also, the results of the outer side of the front LCD panel using the IR camera have been compared with the results of the inner side of the front panel using T-type thermocouples. The equations have been derived for the temperature distribution of the inner side of the front LCD panel by a multiple regression method including variables for ambient temperature, humidity and temperature differences between the front and back panels of the LCD monitor.

• The Journal of Industrial Distribution & Business
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• v.9 no.8
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• pp.17-26
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• 2018

Purpose - Indonesian economy often receives negative impact from external factors, particularly through trade linkage. To mitigate that impact, the export market and product diversification should be established. Latin America is one of the potential regions to augment the Indonesian export market. Research design, data, and methodology - This study attempts to classify the potential market and product for Indonesian export, particularly in Latin America, by using panel regression, trade complementarity, and export similarity index over the period 2000-2015. Regression was also used to examine whether the presence of the Indonesian Trade Promotion Center (ITPC) can support diversification. Results - Based on regression results, those indexes established Chile, Uruguay, Suriname, and Ecuador as the priority countries with the products: animal and vegetable oils, fats and waxes; chemicals and related products; miscellaneous manufactured articles; commodities and transactions. Conclusions - The results of the regression concludes that the trade complementarity index gave a significant positive effect to boost Indonesian export, whereas, the export similarity index gave a significant negative effect. The regression also conclude that ITPC gave a significant positive impact on Indonesian export. For instance, the government should prioritize those countries and products and also develop ITPC there to optimize Indonesian export.