• 산업경영시스템학회지
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• 제27권1호
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• pp.32-37
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• 2004

A new display device is required, which has concepts of flatness and slimness. FED can be one of the solutions. When we use flat panel, we can save the raw material and reduce the production time by eliminating the printing process, drying process, and washing process. In this case, good panel flatness and consistency with panel flatness and black matrix is the precondition. Therefor, we analyzed process capability of panel flatness and regression between panel flatness and BM position by experiments.

• Communications for Statistical Applications and Methods
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• 제21권5호
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• pp.395-409
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• 2014

Data limited, partial, or incomplete are known as an ill-posed problem. If the data with ill-posed problems are analyzed by traditional statistical methods, the results obviously are not reliable and lead to erroneous interpretations. To overcome these problems, we propose a dual generalized maximum entropy (dual GME) estimator for panel data regression models based on an unconstrained dual Lagrange multiplier method. Monte Carlo simulations for panel data regression models with exogeneity, endogeneity, or/and collinearity show that the dual GME estimator outperforms several other estimators such as using least squares and instruments even in small samples. We believe that our dual GME procedure developed for the panel data regression framework will be useful to analyze ill-posed and endogenous data sets.

• Asian Journal of Business Environment
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• 제12권2호
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• pp.1-12
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• 2022

Purpose: This study aims to analyze the inclusive growth in Central Sulawesi Province, an eastern province of Indonesia, up to the districts/cities level. The inclusive growth is analyzed by using Ramos, Ranieri, and Lammens' index that has three indicators which are employment, poverty, and income inequality. Research design, data, and methodology: This study uses panel data of 13 districts/cities in Central Sulawesi Province from 2015 to 2019. The statistical regression used is the panel regression method to analyze the determinants of inclusive growth there. Results: The study found that the average inclusive growth of districts/cities in Central Sulawesi is increasing from the low-level in 2015 to mid-level in 2019. The panel's data regression using fixed effect model FGLS-SUR found Investment (GFCF), Road Infrastructure, HDI, and Processing Industry have a significant positive effect. Regional minimum wage (RMW) has a significant negative effect. Government Expenditure on Education and Health Function has no significant positive effect on inclusive growth. Conclusions: throughout the study period, gini coefficient and poverty rate is slowly decreasing, while employment to population ratio remains volatile in districts/cities of Central Sulawesi.

• 한국항만경제학회지
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• 제35권1호
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• pp.57-76
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• 2019

본 연구는 우리나라 산업 발전에 크게 기여한 운송산업의 주체인 운송업 종사자의 고용생산성 결정요인에 대해 다룬다. 본 연구는 노동패널자료를 활용해 운송업의 고용생산성 결정요인을 선정하고 패널 로지스틱 회귀 모형(Panel Logistic Regression), Panel OLS 모형, Panel Robust regression 모형을 활용하여 요인 간 영향력을 분석하였다. 분석 결과는 다음과 같다. 첫째, 정규직 여부의 경우 '학력'이 높을수록, '노조가입' 할수록, '직업훈련 경험'이 있을수록 긍정적인 효과가 나타난 것으로 분석되었다. 둘째, 고용안정성은 '학력'이 높고 '노조가입' 할수록 긍정적인 영향이 미치는 것으로 조사되었으며, '회사규모'가 크고 '기혼'일 경우 고용안정성이 큰 것으로 분석되었다. 셋째, 소득생산성의 경우 '나이', '학력', '회사규모'의 값이 클수록 긍정적인 영향을 미치고 '직업훈련 이외의 교육', '건강상태'의 값이 클수록 부정적인 영향을 미치는 것으로 분석되었다. 넷째, 직무만족도의 경우는 '여성'일수록, '노조가입' 할수록, '소득'이 높을수록, '고용안정성'이 높을수록 높았고, '보통사람대비 건강상태'가 좋을수록, '전반적 생활만족도'와 '경제적 수준'이 높을수록 직무만족도는 낮은 것으로 분석되었다. 본 연구에서 도출한 운송산업 고용생산성 결정요인의 분석과 향상 방안 모색을 통해 운송업 고용 생산성 향상에 기여할 수 있을 것으로 생각된다.

• Communications for Statistical Applications and Methods
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• 제26권4호
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• pp.371-383
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• 2019

Panel data sets have been developed in various areas, and many recent studies have analyzed panel, or longitudinal data sets. Maximum likelihood (ML) may be the most common statistical method for analyzing panel data models; however, the inference based on the ML estimate will have an inflated Type I error because the ML method tends to give a downwardly biased estimate of variance components when the sample size is small. The under estimation could be severe when data is incomplete. This paper proposes the restricted maximum likelihood (REML) method for a random effects panel data model with a censored dependent variable. Note that the likelihood function of the model is complex in that it includes a multidimensional integral. Many authors proposed to use integral approximation methods for the computation of likelihood function; however, it is well known that integral approximation methods are inadequate for high dimensional integrals in practice. This paper introduces to use the moments of truncated multivariate normal random vector for the calculation of multidimensional integral. In addition, a proper asymptotic standard error of REML estimate is given.

• 응용통계연구
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• 제16권2호
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• pp.351-364
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• 2003

본 논문에서는 오차성분을 가지는 패널회귀모형에서 모형의 선형성을 검정 할 수 있는 검 정통계량을 제시하고, 유도한 검정통계량의 계산을 위하여 인공회귀방법을 이용하려한다. 모의실험 결과, Double-Length Artificial Resression(DLR)을 이용한 LM 검정통계량은 명목유의 수준을 잘 유지하고 있는 것으로 나타났으며 검정력에 있어서도 기존의 검정에 비하여 높게 나타났다.

• Communications for Statistical Applications and Methods
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• 제21권2호
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• pp.193-200
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• 2014

It was recognized by some researchers that the disturbance variance in a censored regression model is frequently underestimated by the maximum likelihood method. This underestimation has implications for the estimation of marginal effects and asymptotic standard errors. For instance, the actual coverage probability of the confidence interval based on a maximum likelihood estimate can be significantly smaller than the nominal confidence level; consequently, a Bayesian estimation is considered to overcome this difficulty. The behaviors of the maximum likelihood and Bayesian estimators of disturbance variance are examined in a fixed effects panel regression model with a limited dependent variable, which is known to have the incidental parameter problem. Behavior under random effect assumption is also investigated.

• Communications for Statistical Applications and Methods
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• 제17권3호
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• pp.349-356
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• 2010

The ordinary least squares based estimator of the disturbance variance in a regression model for spatial panel data is shown to be asymptotically unbiased and weakly consistent in the context of SAR(1), SMA(1) and SARMA(1,1)-disturbances when there is measurement error in the regressor matrix.

• Communications for Statistical Applications and Methods
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• 제6권3호
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• pp.667-676
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• 1999

We investigate the effects of omission of initial observations in each individuals in the panel data regression model when the disturbances follow a serially correlated one way error components. We show that the first transformed observation can have a relative large hat matrix diagonal component and a large influence on parameter estimates when the correlation coefficient is large in absolute value.

• Journal of the Korean Data and Information Science Society
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• 제25권6호
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• pp.1253-1262
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• 2014

회귀나무 (regression tree)는 독립변수로 이루어진 공간을 재귀적으로 분할하고 해당 영역에서 종속변수의 최선의 예측값을 찾고자 하는 비모수적 방법론이다. 회귀나무 모형이 제안된 이래 로지스틱 회귀나무모형이나 분위수 회귀나무모형과 같이 유연하고 다양한 모형적합을 위한 연구가 진행되어 왔다. 최근에 들어서는 Sela와 Simonoff (2012)의 RE-EM 알고리즘, Loh와 Zheng (2013)의 GUIDE 등 패널데이터와 관련하여 진일보한 나무모형 알고리즘도 제안되었다. 본 논문에서는 각 알고리즘을 소개하고 특징을 살펴보는 한편, 실험 데이터를 생성하여 평균제곱오차 (mean squared error)를 바탕으로 예측력을 비교하였다. 분석결과, RE-EM 알고리즘의 예측력이 상대적으로 우수하게 나타났다. 이 알고리즘을 통해 기업경기실사지수 업종별 패널자료를 분석한 결과 최근의 업황에 가장 큰 영향을 미치는 요소는 매출 실적으로 나타났으며 매출 상위 그룹의 경우 비제조업이 제조업에 비해 업황에 대한 판단이 긍정적인 것으로 나타났다.