• Title/Summary/Keyword: Panel Regression Model

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Test in Unbalanced Panel Regression Model with Nuisance Parameter (장애모수가 존재하는 불균형 패널회귀모형에서의 검정법)

  • 이재원;정병철;송석헌
    • 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.

The Impacts of Seawater Surface Temperature Rising on Sea Mustard Yields of Goheung and Wando Coast in Korea (고흥·완도 해수표층온도 상승이 미역 단수에 미치는 영향)

  • Cho, Jae-Hwan;Suh, Jeong-Min;Lee, Nam-Su;Ha, Hyun-Jung
    • Journal of Environmental Science International
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    • v.27 no.3
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    • pp.147-154
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    • 2018
  • The purpose of this article is analyzing the impacts of seawater surface temperature rise on sea mustard yields of Goheung and Wando coast in Korea, with employing a panel data regression model. Our results show that there has been a negative impacts on sea mustard yields as seawater surface temperature continuously has been rising. Especially if the upward trend in seawater surface temperature since 2005 will be maintained in future, sea mustard yield is expected to decrease by 2.6% per year.

Analysis of Determinants of Civilian City Gas Demand Considering Spatial Correlation (공간적 상관성을 고려한 민수용 도시가스 수요결정 요인 분석)

  • Eunbi Park;DooHwan Won
    • Environmental and Resource Economics Review
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    • v.33 no.1
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    • pp.59-86
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    • 2024
  • Recently, research on city gas demand is increasing by reflecting the characteristics of each region. The similarity of the social structure of the adjacent region and the density of the supply infrastructure induce spatial correlation with the clustering that has a microscopic relationship between regions. Accordingly, as a result of analyzing the spatial correlation after dividing the demand for city gas for civilian use into a total of 54 regions based on the jurisdiction of 34 city gas companies, it was confirmed that there was a positive spatial correlation from a global and local perspective. In this study, the demand for city gas for civilian use for 54 regions from January 2014 to December 2022 was composed of panel data, and the spatial panel regression analysis and the general panel regression analysis were compared, and it was found that the spatial error model (SEM) was the most suitable model. This presents policy and practical implications by confirming that the demand for city gas for civilian use in one region has a significant relationship with the adjacent region.

Effects of Meteorological Elements in the Production of Food Crops: Focused on Regression Analysis using Panel Data (기상요소가 식량작물 생산량에 미치는 영향: 패널자료를 활용한 회귀분석)

  • Lee, Joong-Woo;Jang, Young Jae;Ko, Kwang-Kun;Park, Jong-Kil
    • Journal of Environmental Science International
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    • v.22 no.9
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    • pp.1171-1180
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    • 2013
  • Recent climate change has led to fluctuations in agricultural production, and as a result national food supply has become an important strategic factor in economic policy. As such, in this study, panel data was collected to analyze the effects of seven meteorological elements and using the Lagrange multipliers method, the fixed-effects model for the production of five types of food crop and the seven meteorological elements were analyzed. Results showed that the key factors effecting increases in production of rice grains were average temperature, average relative humidity and average ground surface temperature, while wheat and barley were found to have positive correlations with average temperature and average humidity. The implications of this study are as follow. First, it was confirmed that the meteorological elements have profound effects on the production of food crops. Second, when compared to existing studies, the study was not limited to one food crop but encompassed all five types, and went beyond other studies that were limited to temperature and rainfall to include various meterological elements.

Analysis of Factors for Private Universities Educational Restitution Rate using Data Mining : Focusing on the Panel Fixed Effect Model and Non-parametric Regression Estimation (데이터 마이닝을 활용한 사립대학 교육비 환원요인 분석 : 패널 고정효과모형과 비모수회귀추정을 중심으로)

  • Chae, Dong Woo;Lee, Mun-Bum;Jung, Kun-Oh
    • Journal of Information Technology Applications and Management
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    • v.27 no.6
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    • pp.153-170
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    • 2020
  • The Educational Restitution Rate is an important parameter that determines the quality of university education. This paper analyzed data from 148 private universities over the 10 years from 2009 to 2018 using data mining techniques in Korea. A significant causal relationship is detected in the fixed effect model as a result of the panel estimation. And the scale of faculty expansion and fund management, which are the university evaluation indicators, and the size of basic funds, respectively, have a positive effect on the ERR, which is within the confidence interval. In the analysis, the more private universities improve the tuition dependence rate, the more decisively positive affecting ERR. As a result of nonparametric regression estimation, when the faculty expansion ratio is reinforced, the effect of economies of scale is detected in some sections, the improvement of the tuition dependence rate, and the result value is generated through the improvement that results are derived at a certain point in time. We hope that the university based on this study can be a basic Indicators for the diagnosis of basic competencies and policy of student-centered education.

Effects of Human Capital and Innovation on Economic Growth in Selected ASEAN Countries: Evidence from Panel Regression Approach

  • CHE SULAIMAN, Nor Fatimah;SAPUTRA, Jumadil;MUHAMAD, Suriyani
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.7
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    • pp.43-54
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    • 2021
  • Human capital and innovation capacities are essential elements and one of the sustainable approaches to driving economic growth. However, there is debate among scholars concerning these two factors in fostering economic growth. This study investigates the relationships between human capital and innovation capacity and economic growth in selected ASEAN countries, namely, Malaysia, Thailand, and Indonesia. Economists widely discussed the interrelation of human capital and innovation. A large body of literature stated that human capital is an essential factor and engine of economic growth. Innovation has become key in transforming the economic development of developing countries. We analyze human capital (HC) and innovation capacity (INC) using static panel data analysis. The data analysis shows that the fixed-effect model is the best model in this study. Further, human capital (HC) has a significant positive relationship with economic growth. Meanwhile, innovation capacity has no significant relationship with economic growth. We also found that Malaysia's coefficient of human capital and innovation capacity is higher and more efficient than in Thailand and Indonesia. In conclusion, human capital and innovation capacity are crucial elements for measuring economic growth. Skilled human capital contributes significantly to the economic growth and economic development of a nation.

Traffic Accident Analysis of Link Sections Using Panel Data in the Case of Cheongju Arterial Roads (패널자료를 이용한 가로구간 교통사고분석 - 청주시 간선도로를 사례로 -)

  • Kim, Jun-Young;Na, Hee;Park, Byung-Ho
    • Journal of the Korean Society of Safety
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    • v.27 no.3
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    • pp.141-146
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    • 2012
  • This study deals with the accident model using panel data which are composed of time series data of 2005 through 2007 and cross sectional data of link sections in Cheongju. Panel data are repeatedly collected over time from the same sample. The purpose of the study is to develop the traffic accident model using the above panel data. In pursuing the above, this study gives particular attentions to deriving the optimal models among various models including TSCSREG (Time Series Cross Section Regression). The main results are as follows. First, 8 panel data models which explained the various effects of accidents were developed. Second, $R^2$ values of fixed effect models were analyzed to be higher than those of random effect models. Finally, such the variables as the sum of the number of crosswalk on intersections and sum of the number of intersections were analyzed to be positive to the accidents.

A Study on the Dissemination Structure of Unfilled Positions in Universities Across the Country using Big Data: Using Panel and Tobit Regression Model (빅 데이터를 활용한 대학의 지역·권역별 학과의 미충원 파급구조 연구: 패널회귀모형과 토빗회귀모형의 응용을 중심으로)

  • Dong Woo Chae;Kun Oh Jung
    • Journal of Information Technology Applications and Management
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    • v.30 no.1
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    • pp.33-52
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    • 2023
  • This study observes the difference in the actual regional ripple effect of the decrease in admission resources due to the decrease in school age population, which has been weak in empirical studies, and how much the decrease in competition rate by department nationwide provides a significant shock to the decrease in enrollment rate in the population unit. An empirical quantitative analysis was attempted. As a result of applying the panel-tobit regression model, a clear gap was confirmed in the decrease in the registration rate due to the decrease in the competition rate both nationally and in the provinces, and in particular, a highly significant relationship was derived with the decrease in the recruitment rate. In particular, the sensitivity of the risk of unrecruitment due to a decrease in competition rate was the highest in the Jeolla region (0.499), followed by the Gangwon region (0.475) and the Gyeongsang region (0.471), and the metropolitan region (0.158) was confirmed to be the most stable. This suggests that the gap in insufficient funding has gradually widened by region over the past 10 years, and that the shock wave becomes more pronounced in the provinces farther away from the metropolitan area. Based on this study, if we deviate from the standardized application of university development policies for the metropolitan area and regional universities, and present a customized higher education strategy for each region, it will be an opportunity to prevent local extinction due to a decrease in the school-age population and achieve coexistence with higher education institutions and regions at the same time.

Interrelationship Between Regional Population Migration, Crop Area, and Foreign Workers (지역 간 인구이동, 경지면적, 외국인 근로자의 관계 분석)

  • Seojin Cho;Heeyeun Yoon
    • Journal of the Korean Regional Science Association
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    • v.40 no.2
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    • pp.21-38
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    • 2024
  • Understanding the interrelationship between regional population dynamics and cultivated land is crucial for promoting regional economic vitality and enhancing food security. While prior research often addressed population migration and changes in crop area separately, this study employs a Panel Vector Auto Regression Model to examine the dynamic interaction between regional population shifts, changes in crop area, and the influx of foreign workers in agriculture. The results reveal a reciprocal relationship between population influx and crop area, indicating a negative impact on each other. Moreover, the analysis demonstrates that an expansion in crop area, particularly in field cultivation, significantly correlates with an increase in foreign workers. These findings underscore the mutual influence of labor shortages and diminished land availability in agriculture, with the influx of foreign workers potentially offering a positive impact on addressing structural challenges in rural areas.

Wage Determinants Analysis by Quantile Regression Tree

  • Chang, Young-Jae
    • Communications for Statistical Applications and Methods
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    • v.19 no.2
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    • pp.293-301
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    • 2012
  • Quantile regression proposed by Koenker and Bassett (1978) is a statistical technique that estimates conditional quantiles. The advantage of using quantile regression is the robustness in response to large outliers compared to ordinary least squares(OLS) regression. A regression tree approach has been applied to OLS problems to fit flexible models. Loh (2002) proposed the GUIDE algorithm that has a negligible selection bias and relatively low computational cost. Quantile regression can be regarded as an analogue of OLS, therefore it can also be applied to GUIDE regression tree method. Chaudhuri and Loh (2002) proposed a nonparametric quantile regression method that blends key features of piecewise polynomial quantile regression and tree-structured regression based on adaptive recursive partitioning. Lee and Lee (2006) investigated wage determinants in the Korean labor market using the Korean Labor and Income Panel Study(KLIPS). Following Lee and Lee, we fit three kinds of quantile regression tree models to KLIPS data with respect to the quantiles, 0.05, 0.2, 0.5, 0.8, and 0.95. Among the three models, multiple linear piecewise quantile regression model forms the shortest tree structure, while the piecewise constant quantile regression model has a deeper tree structure with more terminal nodes in general. Age, gender, marriage status, and education seem to be the determinants of the wage level throughout the quantiles; in addition, education experience appears as the important determinant of the wage level in the highly paid group.