• Title/Summary/Keyword: Panel Data

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Analysis on the Relationship between R&D Inputs and Performance by using Panel Data : Focus on Defense Industry (패널 데이터를 이용한 방위산업의 R&D 투입과 성과 관계 분석)

  • Lee, Kang-Taek;Kim, Geun-Hyung;Lee, Seung-Hyun;Lee, Ik-Do
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.12
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    • pp.491-497
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    • 2018
  • This study analyzes the relationship between R&D input and performance using panel data from the defense industry. A research model is established based on the R&D logic model, and the study sample consists of a strongly balanced panel data (n=351) empirically analyzed using panel linear regression. Results identified that defense improvement expenditure has a positive influence on the R&D input, and R&D input positively affected patents using a 5-year time lag. In addition, R&D input positively impacts economic performance, including sales and profit. Hence, the major finding includes R&D inputs have statistically significant effects on economic outcome and the R&D logic model featuring a time-lag.

BIM-Based Generation of Free-form Building Panelization Model (BIM 기반 비정형 건축물 패널화 모델 생성 방법에 관한 연구)

  • Kim, Yang-Gil;Lee, Yun-Gu;Ham, Nam-Hyuk;Kim, Jae-Jun
    • Journal of KIBIM
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    • v.12 no.4
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    • pp.19-31
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    • 2022
  • With the development of 3D-based CAD (Computer Aided Design), attempts at freeform building design have expanded to small and medium-sized buildings in Korea. However, a standardized system for continuous utilization of shape data and BIM conversion process implemented with 3D-based NURBS is still immature. Without accurate review and management throughout the Freeform building project, interference between members occurs and the cost of the project increases. This is very detrimental to the project. To solve this problem, we proposed a continuous utilization process of 3D shape information based on BIM parameters. Our process includes algorithms such as Auto Split, Panel Optimization, Excel extraction based on shape information, BIM modeling through Adaptive Component, and BIM model utilization method using ID Code. The optimal cutting reference point was calculated and the optimal material specification was derived using the Panel Optimization algorithm. With the Adaptive Component design methodology, a BIM model conforming to the standard cross-section details and specifications was uniformly established. The automatic BIM conversion algorithm of shape data through Excel extraction created a BIM model without omission of data based on the optimized panel cutting reference point and cutting line. Finally, we analyzed how to use the BIM model built for automatic conversion. As a result of the analysis, in addition to the BIM utilization plan in the general construction stage such as visualization, interference review, quantity calculation, and construction simulation, an individual management plan for the unit panel was derived through ID data input. This study suggested an improvement process by linking the existing research on atypical panel optimization and the study of parameter-based BIM information management method. And it showed that it can solve the problems of existing Freeform building project.

Panel data analysis with regression trees (회귀나무 모형을 이용한 패널데이터 분석)

  • Chang, Youngjae
    • 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.

Does Population Aging Contribute to Increased Fiscal Spending?

  • LEE, Mihye
    • Asian Journal of Business Environment
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    • v.9 no.4
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    • pp.23-28
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    • 2019
  • Purpose - With rapid population aging in Korea, changes in the population structure will result in a rise in the fiscal burden. This paper investigates the effects of population aging on fiscal spending based on Korea's province data and country panel data from the OECD. Research design, data, and methodology - We use province-level fiscal data from Local Finance Integrated Open System and the Korean Statistical Information Service and also collect country panel data from the OECD. To investigate the relationship between population aging and fiscal expenditures, our analysis uses the fixed effects model. Results - The empirical analysis based on Korean local finance and country panel data show that population aging has a positive impact on social welfare expenditures and it also has a positive impact on spending related to children and the elderly, implying that population aging may lead to an increase in fiscal spending via an increase in social welfare expenditures and spending related to children and the elderly. Conclusion - These empirical results suggest that countries like Korea that expect to experience rapid population aging need to pay more attention to prepare for the expected increase in age-related spending in the near future.

Analysis of Indonesian Tuna Fish Export to Twelve Main Destination Countries: A Panel Gravity Model

  • PUTRA, I Wayan Edy Darma;NASRUDIN, NASRUDIN
    • Asian Journal of Business Environment
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    • v.13 no.1
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    • pp.31-41
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    • 2023
  • Purpose: This study purposes to analyze the determinants of the volume of Indonesian tuna exports. Research design, data and methodology: The framework was developed from the gravity model for trade, which was expanded with additional variables of competitiveness, exchange rate, and industrial share of the destination country. The data sources used in this study are UN Comtrade and the World Bank. The data used is yearly data from 12 countries in 2001-2019. The scope of the study is limited to exports to the twelve main export destinations. Panel data regression analysis is used to determine the factors that affect the volume of Indonesian tuna exports. Results: The results show that according to the theory, Indonesia's GDP has a positive effect and economic distance has a negative effect on the volume of the exports. Meanwhile, the GDPs of the destination countries are not proven to have a positive effect. However, the higher the industrial share in the country, the higher the export volume tends to be. Conclusions: The conclusion obtained from this study is that Indonesia's GDP, economic distance, real exchange rate, industrial GDP share of the destination country, and the RCA index affect the volume of Indonesian tuna exports.

The Study on the Optimal Angle of the Solar Panel using by Solar Radiation Model (태양복사모델을 이용한 태양전지판의 최적 경사각에 대한 연구)

  • Jee, Joon-Bum;Choi, Young-Jean;Lee, Kyu-Tae
    • Journal of the Korean Solar Energy Society
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    • v.32 no.2
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    • pp.64-73
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    • 2012
  • The angle of solar panels is calculated using solar radiation model for the efficient solar power generation. In ideal state, the time of maximum solar radiation is represented from 12:08 to 12:40 during a year at Gangneung and it save rage time is12:23. The maximum solar radiation is 1012$W/m^2$ and 708$W/m^2$ inc lear sky and cloudy sky, respectively. Solar radiation is more sensitive to North-South (N-S) slope angle than East-West (E-W) azimuth angle. Daily solar radiation on optimum angle of solar panel is higher than that on horizontal surface except for 90 days during summer. In order to apply to the real atmosphere, the TMY (typical meteorological Year) data which obtained from the 22 solar sites operated by KMA(Korea Meteorological Administration) during 11 years(2000 to 2010) is used as the input data of solar radiation model. The distribution of calculated solar radiation is similar to the observation, except in Andong, where it is overestimated, and in Mokpo and Heuksando, where it is underestimated. Statistical analysis is performed on calculated and observed monthly solar radiation on horizontal surface, and the calculation is overestimated from the observation. Correlationis 0.95 and RMSE (Root Mean Square Error) is10.81 MJ. The result shows that optimum N-S slope angles of solar panel are about $2^{\circ}$ lower than station latitude, but E-W slope angles are lower than ${\pm}1^{\circ}$. There are three types of solar panels: horizontal, fixed with optimum slope angle, and panels with tracker system. The energy efficiencies are on average 20% higher on fixed solar panel and 60% higher on tracker solar panel than compared to the horizontal solar panel, respectively.

Comparison between homogeneity test statistics for panel AR(1) model (패널 1차 자기회귀과정들의 동질성 검정 통계량 비교)

  • Lee, Sung Duck;Kim, Sun Woo;Jo, Na Rae
    • The Korean Journal of Applied Statistics
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    • v.29 no.1
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    • pp.123-132
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    • 2016
  • We can achieve the principle of parsimony and efficiency if homogeneity for panel time series model is satisfied. We suggest a Rao test statistic and a Wald test statistic for the test of homogeneity for panel AR(1) and derived the limit distribution. We performed a simulation to examine statistics with the same chisquare distribution when number of the individual is small and in common with large. We also simulated to compare the empirical power of the statistics in a small panel. In application, we fit panel AR(1) model using regional monthly economical active population data and test homogeneity for panel AR(1). It is satisfied homogeneity, so it could be fitted AR(1) using the sample mean at the time point. We also compare the power of prediction between each individual and pooled model.

Dynamic Structural Equation Models of Activity Participation and Travel Behavior using Puget Sound Transportation Panel (Puget Sound Transportation Panel을 이용한 활동참여와 통행행동의 Dynamic SEM)

  • 최연숙;정진혁
    • Journal of Korean Society of Transportation
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    • v.20 no.6
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    • pp.129-140
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    • 2002
  • This paper develops a dynamic structural equation model, which captures relationships among socio-demographics, activity participation(i.e., time use) and travel behavior in consideration with time variation effects. The data used in developing the model are two waves(the year 1991 and 1992) from Puget Sound Transportation Panel (PSTP). which is surveyed in Puget Sound Region in United States. The PSTP is widely used in transportation behavior analysis and includes various information of traveler's socio-economic, travel patterns, and activity participation. In the model, we use 10 endogenous variables including activity participations and travel behaviors and 10 exogenous variables composed of time variant and invariant traveler's socio-demographic variables. The empirical model shows that strong relationships exist not only between socio-demographics and travel behavior, but between waves. We also confirm needs of panel data set to identify and understand time variation effects and travel behaviors.

Dynamic Model Considering the Biases in SP Panel data (SP 패널데이터의 Bias를 고려한 동적모델)

  • 남궁문;성수련;최기주;이백진
    • Journal of Korean Society of Transportation
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    • v.18 no.6
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    • pp.63-75
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    • 2000
  • Stated Preference (SP) data has been regarded as more useful than Revealed Preference (RP) data, because researchers can investigate the respondents\` Preference and attitude for a traffic condition or a new traffic system by using the SP data. However, the SP data has two bias: the first one is the bias inherent in SP data and the latter one is the attrition bias in SP panel data. If the biases do not corrected, the choice model using SP data may predict a erroneous future demand. In this Paper, six route choice models are constructed to deal with the SP biases, and. these six models are classified into cross-sectional models (model I∼IH) and dynamic models (model IV∼VI) From the six models. some remarkable results are obtained. The cross-sectional model that incorporate RP choice results of responders with SP cross-sectional model can correct the biases inherent in SP data, and also the dynamic models can consider the temporal variations of the effectiveness of state dependence in SP responses by assuming a simple exponential function of the state dependence. WESML method that use the estimated attrition probability is also adopted to correct the attrition bias in SP Panel data. The results can be contributed to the dynamic modeling of SP Panel data and also useful to predict more exact demand.

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A Query Model for Consecutive Analyses of Dynamic Multivariate Graphs (동적 다변량 그래프의 연속적 분석을 위한 질의 모델 설계 및 구현)

  • Bae, Yechan;Ham, Doyoung;Kim, Taeyang;Jeong, Hayjin;Kim, Dongyoon
    • The Journal of Korean Association of Computer Education
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    • v.17 no.6
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    • pp.103-113
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    • 2014
  • This study designed and implemented a query model for consecutive analyses of dynamic multivariate graph data. First, the query model consists of two procedures; setting the discriminant function, and determining an alteration method. Second, the query model was implemented as a query system that consists of a query panel, a graph visualization panel, and a property panel. A Node-Link Diagram and the Force-Directed Graph Drawing algorithm were used for the visualization of the graph. The results of the queries are visually presented through the graph visualization panel. Finally, this study used the data of worldwide import & export data of small arms to verify our model. The significance of this research is in the fact that, through the model which is able to conduct consecutive analyses on dynamic graph data, it helps overcome the limitations of previous models which can only perform discrete analysis on dynamic data. This research is expected to contribute to future studies such as online decision making and complex network analysis, that use dynamic graph models.

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