• Title/Summary/Keyword: 패널모형분석

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Dynamics of Consumer Preference in Binary Probit Model (이산프로빗모형에서 소비자선호의 동태성)

  • Joo, Young-Jin
    • The Journal of the Korea Contents Association
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    • v.10 no.5
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    • pp.210-219
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    • 2010
  • Consumers differ in both horizontally and vertically. Market segmentation aims to divide horizontally different (or heterogeneous) consumers into more similar (or homogeneous) small segments. A specific consumer, however, may differ in vertically. He (or she) may belong to a different market segment from another one where he (or she) belonged to before. In consumer panel data, the vertical difference can be observed by his (or her) choice among brand alternatives are changing over time. The consumer's vertical difference has been defined as 'dynamics'. In this research, we have developed a binary probit model with random-walk coefficients to capture the consumer's dynamics. With an application to a consumer panel data, we have examined how have the random-walk coefficients changed over time.

A Study on the Influence of the Urban Characteristics on the Incidence of Crime Using Panel Model (패널모형을 이용한 도시특성요소가 범죄 발생에 미치는 영향 분석)

  • Lee, Hyo Jin;Lee, Jae Song;Choi, Yeol
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.35 no.6
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    • pp.1439-1449
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    • 2015
  • This study, based on the sociological crime theory, is to examine the relation between urban characteristics and the incidence of crime, helping establish effective crime prevention measures. For doing so, the study employs crime data from the Supreme Prosecutors' Office and socio-demographic data including the regional Statistical Yearbooks -both from 2005 to 2012- to build the study's panel data, and analyzes the panel model on the 16 subordinate districts in the city of Busan. To reduce the incidence of crime and prevent crimes from occurring based on the analysis results, first, prevention measures specific to each region by its attributes are needed rather than general ones; second, new institutional frameworks or policies are required for utilizing accurate crime data; third, interdisciplinary research in which various fields including urban engineering are associated to that of social science is necessary to further the study.

A Longitudinal Study of the Ecological-Systemic Factors on School Absenteeism in South Korean Children - A Panel Fixed Effects Analysis - (아동의 학교결석일 변화에 영향을 미치는 생태체계요인에 관한 종단연구 - 패널고정효과모형을 활용하여 -)

  • Kim, Dong Ha;Um, Myung Yong
    • Korean Journal of Social Welfare
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    • v.68 no.3
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    • pp.105-125
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    • 2016
  • School absenteeism is considered one of the early predictors of school drop-out and serious delinquency or criminal behavior. The primary goal of the current study was to explore the protective and risk factors related to changing school absenteeism over time based on the ecological-systemic perspective. The data was derived from the Korean Children and Youth Panel Survey (KCYPS) using the 2011 and 2012 survey waves collected from 2,378 elementary school students. Using this data, Panel Fixed Effects Analysis was conducted. Major findings indicated that daily computer usage, parental abuse, school activity attendance, and school grades had an effect on students missing school days over time. Specifically, high levels of computer usage and parental abuse were related to increased school absenteeism, while high levels of school activity attendance and school grades were associated with decreased school absenteeism. These findings emphasized the importance of predictive intervention for children and suggested the need to construct a school absenteeism monitoring system in South Korea.

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The Factor Analysis of Land Surface Temperature(LST) Change using MODIS Imagery and Panel Data (MODIS 영상 자료와 패널 자료를 이용한 지표면온도변화 요인분석)

  • BAE, Da-Hye;KIM, Hong-Myung;HA, Sung-Ryong
    • Journal of the Korean Association of Geographic Information Studies
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    • v.21 no.1
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    • pp.46-56
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    • 2018
  • This paper aimed to identify main factors of community characters, which have an effect on the land surface temperature(LST) change and estimate the impacting coefficient(ratio) of factors in a significant level of statistics. Chungcheongbuk-do province was selected and then partitioned into city and county areas for the sake of convenience of modeling. LST time series data and the community character data were developed based on Terra Satellite MODIS data and collected from the National Statistical Office, respectively. By the cause and effect relationship between community characters and LST, regression coefficients were estimated using a penal model. In a panel modeling, LST and community characters were used as a dependent variable and explanatory variables, respectively. Panel modeling analysis was carried out using statistical package STATA14 and one-way fixed effect model was selected as the most suitable model to evaluate the regression coefficients in the study area. The impacting ratio of LST change by any explanatory variable derived from the regression coefficients of the panel model fixed. Impacting ratios for industrial areas, elevation ${\times}$ building, energy usage, average window speed, non-urban management area, agricultural, nature and environmental conservation, average precipitation were 3.746, 2.856, 2.742, 0.553, 0.102, 0.071 and 0.003, respectively.

KCYP data analysis using Bayesian multivariate linear model (베이지안 다변량 선형 모형을 이용한 청소년 패널 데이터 분석)

  • Insun, Lee;Keunbaik, Lee
    • The Korean Journal of Applied Statistics
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    • v.35 no.6
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    • pp.703-724
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    • 2022
  • Although longitudinal studies mainly produce multivariate longitudinal data, most of existing statistical models analyze univariate longitudinal data and there is a limitation to explain complex correlations properly. Therefore, this paper describes various methods of modeling the covariance matrix to explain the complex correlations. Among them, modified Cholesky decomposition, modified Cholesky block decomposition, and hypersphere decomposition are reviewed. In this paper, we review these methods and analyze Korean children and youth panel (KCYP) data are analyzed using the Bayesian method. The KCYP data are multivariate longitudinal data that have response variables: School adaptation, academic achievement, and dependence on mobile phones. Assuming that the correlation structure and the innovation standard deviation structure are different, several models are compared. For the most suitable model, all explanatory variables are significant for school adaptation, and academic achievement and only household income appears as insignificant variables when cell phone dependence is a response variable.

Consumer Durables and (S, s) Policy: Evidence from Panel Data (내구재 소비와 (S, s)모형: 가계패널자료 분석)

  • Hong, Kiseok;Sohn, Eunseung
    • KDI Journal of Economic Policy
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    • v.27 no.2
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    • pp.123-154
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    • 2005
  • Using Korean household data, this paper examines how consumption of durable goods is determined. Previous studies report that the standard Permanent Income Hypothesis (PIH), while being broadly consistent with non-durable goods consumption, provides little explanation for durable goods consumption. In this paper, we consider the (S, s) model as an alternative to the standard PIH. The (S, s) model predicts that, because of fixed adjustment costs, consumers make no adjustment to the durable goods stock until deviation from the optimal level becomes large. When the adjustments are made, the durable goods stock attains the optimal level. In order to test this prediction, we examine the intra-temporal relationship between non-durable goods and durable goods consumption and intertemporal changes in durable goods consumption, using data from the Korean Household Panel Study. The results show that, while the standard PIH is rejected by the data, the (S, s) model is not.

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An Analysis of the Determinants of Employment Productivity in Korean Transportation Industry Using Korea Labor and Income Panel Study (한국노동패널자료를 활용한 국내 운송업 고용생산성 결정요인 분석)

  • So, Ae-rim;Shin, Seung-sik
    • Journal of Korea Port Economic Association
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    • v.35 no.1
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    • pp.57-76
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    • 2019
  • This study deals with the determinants of employment productivity of transportation labor, who are the main agents of the transportation industry that has made significant contributions to our country's industrial development. The study selected the determinants of employment productivity using the Korea Labor and Income Panel Study data, and analyzed the effects of various factors using panel logistic regression, panel OLS model, and panel robust regression. The results were as follows. First, a more positive effect was shown when employees held a regular job, had a "high level of education", "joining the labor union" and "experiencing vocational training". Second, in the case of job security, having a "high level of education" and "joining the labor union" showed a more positive effect; further, job security was higher for employees who worked in a "big company" or were "married". Third, in the case of higher income productivity, higher values of "age", "academic ability" and "company size" had a more positive effect, whereas larger values of "education" and "health condition except job training" had a negative one. Fourth, in the case of job satisfaction, "female", "joining the labor union" and having a higher "income" or "job security" led to higher satisfaction and a better "health condition compared to an average person". Further, a higher "overall life satisfaction" and "economic level" led to lower job satisfaction. The analysis of the determinants of employment productivity of transportation business and seeking for improvement plan is expected to improve the employment productivity in the transportation business.

The Impact of Technological Competitiveness in the ICT Convergence Technology on Corporate Diversification (ICT 융합기술에서의 기술경쟁력이 기업 다각화에 미치는 영향)

  • Lee, Hyunmin;Kim, Sun Jae;Kim, Hong Young
    • Journal of Korea Technology Innovation Society
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    • v.21 no.1
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    • pp.385-419
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    • 2018
  • This study suggests an integrated model composed of factors of industrial environments and technology capacity for corporate diversification decision based on industrial organization theory and resource based perspectives. We examine the proposed model using patents and financial data of 272 applicants for 6 years (2010~2015) in the smart factory ICT convergence technology (application and platform field) sectors. The result of analyzing the fixed effect panel model shows that technological competitiveness has a positive effect on corporate diversification. Also, the additional result of analyzing the two-stage least square fixed effect model indicates that the convergence patent ratio increases technological competitiveness. Based on the results, we provide implications for corporate diversification strategies and government R & D policies for commercialization of corporate convergence technology resources and competencies.

Comparison of imputation methods for item nonresponses in a panel study (패널자료에서의 항목무응답 대체 방법 비교)

  • Lee, Hyejung;Song, Juwon
    • The Korean Journal of Applied Statistics
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    • v.30 no.3
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    • pp.377-390
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    • 2017
  • When conducting a survey, item nonresponse occurs if the respondent does not respond to some items. Since analysis based only on completely observed data may cause biased results, imputation is often conducted to analyze data in its complete form. The panel study is a survey method that examines changes of responses over time. In panel studies, there has been a preference for using information from response values of previous waves when the imputation of item nonresponses is performed; however, limited research has been conducted to support this preference. Therefore, this study compares the performance of imputation methods according to whether or not information from previous waves is utilized in the panel study. Among imputation methods that utilize information from previous responses, we consider ratio imputation, imputation based on the linear mixed model, and imputation based on the Bayesian linear mixed model approach. We compare the results from these methods against the results of methods that do not use information from previous responses, such as mean imputation and hot deck imputation. Simulation results show that imputation based on the Bayesian linear mixed model performs best and yields small biases and high coverage rates of the 95% confidence interval even at higher nonresponse rates.

Effectiveness of R&D Tax Credit for SMEs (중소기업 R&D 조세지원의 효과성 분석 및 개선방안)

  • Noh, Meansun;Cho, Hosoo;Baek, Chulwoo
    • Journal of Korea Technology Innovation Society
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    • v.21 no.2
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    • pp.663-683
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    • 2018
  • This study aims to analyze the effectiveness of R&D tax credit for SMEs. We surveyed to collect the information on firm's financial statements and R&D tax credit during 2014-2016, and implemented fixed effect model, random effect model and panel negative binomial model. The results show that the effect of R&D tax credit is 5.3 times larger in terms of R&D expenditure and 4.3 times bigger in terms of number of researchers than that of R&D subsidy. In addition, the effect of tax credit on non-metropolitan area companies is higher than that in the metropolitan area. Based on these results, we suggests three ways to improve the R&D tax incentive system for SMEs; To convert unused R&D tax credit of the start-ups to tax points, to exempt the minimum tax rate on R&D expenditure in equipment, and to unify the operation of various R&D tax credit institution.