• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.969-977
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• 2016

Climate change affects the growth of crops which were planted especially in fields, and it becomes more important to use climate data to predict the yields of the major vagetables. The variation of the crop products caused by climate change is one of the significant factors for the discrepancy of the demand and supply, and leads to the price instability. In this paper, using a panel regression model, we predicted the garlic yields with the weather conditions of different regions. More specifically we used the panel data of the several climate variables for 15 main garlic production areas from 2006 to 2015. Seven variables (average temperature, average maximum temperature, average minimum temperature, average surface temperature, cumulative precipitation, average relative humidity, cumulative duration time of sunshine) for each month were considered, and most significant 7 variables were selected from the total 84 variables by the stepwise regression. The random effects model was chosen by the Hausman test. The average maximum temperature (January), the cumulative precipitation (March, October), the cumulative duration time of sunshine (April, October) were chosen among the variables as the significant climate variables of the model

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1253-1262
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• 2014

Regression tree is a tree-structured solution in which a simple regression model is fitted to the data in each node made by recursive partitioning of predictor space. There have been many efforts to apply tree algorithms to various regression problems like logistic regression and quantile regression. Recently, algorithms have been expanded to the panel data analysis such as RE-EM algorithm by Sela and Simonoff (2012), and extension of GUIDE by Loh and Zheng (2013). The algorithms are briefly introduced and prediction accuracy of three methods are compared in this paper. In general, RE-EM shows good prediction accuracy with least MSE's in the simulation study. A RE-EM tree fitted to business survey index (BSI) panel data shows that sales BSI is the main factor which affects business entrepreneurs' economic sentiment. The economic sentiment BSI of non-manufacturing industries is higher than that of manufacturing ones among the relatively high sales group.

• Informatization Policy
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• v.18 no.4
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• pp.42-58
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• 2011

This paper starts from one question: what are the key factors of the web accessibility policy, which is significant for realizing equity in the web and enhancing human dignity in the information society. To find significant factors for complying with web accessibility, this paper analyzes panel data of 16 Korean local governments (for five years: 2004-2009) according to the research design which is based on the demand and supply balance model and consists of four variables : 'legal and institutional environment (including legal infrastructure)', 'financial foundation (fiscal self-reliance ratio)', 'policy inputs (amount of imformatization budget, employee of information experts)'and 'policy demand (internet usage rate, the number of disabled people and elderly people)'. From the results of this study, this paper can explain the mechanism and impact factors on the web accessibility policy of Korean local governments. Some factors are critical to improve web accessibility: (1) the importance of policy demand, (2) the importance of policy inputs, (3) the importance of legal and institutional environment. Finally, this paper concludes with some suggestions to enhance the web accessibility capacity for Korean local governments: (1) improve awareness on web accessibility, (2) develop a standard and invest R&D on web accessibility, (3) foster experts in web accessibility.

• Korea journal of population studies
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• v.29 no.3
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• pp.159-188
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• 2006

This study attempts to create a longitudinal dataset by linking tdata on the identical individuals across the monthly sample household management lists of the Economically Active Population Survey(EAPS) and the Household Income and Expenditure Survey(HIES). Using the data constructed through such process, the study also tryies to analyze the duration of longitudinal responses and the characteristics of nonrespondents. Between 1998 and 2002, longitudinal response rates had declined to 46% of total EAPS and 34% of total HIES. The fact that nonresponse was not a random phenomenon leads to concerns about the representativeness of the remaining sample. Using Cox's proportional hazard model the study revealed that the duration of longitudinal responses is affected by the ownership of house and the age of the respondent.

• Proceedings of the Korean Association for Survey Research Conference
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• 2002.06a
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• pp.157-162
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• 2002

패널 무응답자(panel nonrespondent)란 처음 조사에서는 응답을 하였으나 나중 조사에서는 응답을 하지 않은 사람을 의미한다. 패널조사에서는 앞 단계에서의 응답으로부터 뒷 단계의 무응답에 대한 정보를 얻을 수 있다. 무응답에 대한 수정 방법은 어떤 보조 변수들을 선택하고, 그 변수들이 수정하는 데 어떻게 사용하는 가를 결정하는 것이다. 우리는 가중 수정을 패널 무응답자에 대해서만 생각한다. 이러한 가중은 패널 무응답자에 대하여 보상하기 위하여 패널 무응답의 가중값을 수정한다. 종속 변수로서 패널응답 상태(status)는 로지스틱 회귀분석으로 패널 무응답에 대한 모형을 선택하는 방법이다. 로지스틱 회귀분석에서 패널무응답과 상관이 있는 변수들은 패널무응답 편향을 감소시키기 위하여 가중 수정에서 사용하기 위한 변수들이다.

• 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.

• The Korean Journal of Applied Statistics
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• v.17 no.3
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• pp.547-556
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• 2004

This paper consider the testing problem of variance component for the unbalanced two-way error component model with nuisance parameter. We derive the one-sided LM test statistic for testing zero individual(time) effects assuming that the other time-specific(individual) effects are present. Using the Monte Carlo experiments, the computational more demanding LR test slightly underestimates the nominal size and has the low powers relative to LM test statistic.

• Journal of Korean Society of Transportation
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• v.30 no.1
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• pp.103-112
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• 2012

This research introduces a trip generation model reflecting time-series effects derived from a panel analysis with the data collected from the national household trip surveys conducted in 1996, 2002 and 2006. The existing methods are unable to reflect time-series effects from the change of socioeconomic conditions because the parameters applied to the model were basically from the base year of study - the parameter values were unchanged. This study proposes a new trip generation model developed through a panel analysis performed with the data collected from the last three national household trip surveys. From the results, it was found that the number of school trips increases and that the number of shopping trips decreases as time passes. The results showed that there are time-series effects affecting in trip generation.

• Environmental and Resource Economics Review
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• v.16 no.4
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• pp.803-832
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• 2007

Electricity and heat load profiles by use types on an hourly basis at the least are essential for assessing economic viability of new cogeneration and CES projects and for optimally operating existing cogeneration and CES facilities. We adopt a multilevel model to specify heat load profiles so as to utilize in a flexible manner the panel nature of our data on weather and heating/cooling use. Converting the multilevel model to the linear mixed-effects model, we estimate the model by panel FGLS. The estimated load profile model for each distinct use type accounts for the effects of temperature, humidity, each hour over the year, each day of the week, each type of legal holidays, and heating/cooling area on energy use. To save space, we feature in detail the heating profile of the household.

• Journal of Convergence for Information Technology
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• v.10 no.9
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• pp.229-236
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• 2020

The purpose of this study was to investigate the current status of unmet medical need using data from the Korea Health Panel study from 2009 to 2013 (excluding 2010), and to analyze the trends of unmet medical need and related factors. The subjects of this study were 11,598 in 2009, 11,035 in 2011, 10,584 in 2012, 10,099 in 2013, and 7,144 people in panel data, and conducted frequency analysis, chi-square test and generalized estimating equation. As a result of the analysis by year, it was found that women, under middle school graduation, medical aid, the lowest household income and low subjective health status experienced more unmet medical need. As a result of analysis using generalized estimating equation, women, under 40 years of age, under elementary school graduation, lowest quartile household income, subjective health status of less than 20 points, and activity restrictions are more likely to experience unmet medical need. Based on these results, we intend to provide basic data for establishing policies on the use of medical services.