• Title/Summary/Keyword: 성장모형

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내생적(內生的) 성장모형(成長模型): 이론적(理論的) 구조(構造)와 함의(含意)

  • Yu, Yun-Ha
    • KDI Journal of Economic Policy
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    • v.15 no.4
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    • pp.69-112
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    • 1993
  • 최근 한국(韓國)을 비롯한 동(東)아시아지역(地域) 몇 나라들의 성공적인 성장업적(成長業績)에 자극되어 이들 국가들의 성공사례를 모형내(模型內)에서 이론적으로 설명해 보려는 노력이 활발히 진행되고 있다. 이 글에서는 최근의 이러한 노력의 일환으로 개발되고 있는 '내생적(內生的) 성장이론(成長理論)'을 개관하고 그 함의(含意)와 한계점(限界點)을 정리해 보았다. 먼저 내생적(內生的) 성장모형(成長模型)의 비판대상이 되고 있는 신고전파(新古典派) 성장모형(成長模型)의 한계점(限界點)을 요약하고 대체모형(代替模型)으로 제시되고 있는 몇 가지의 대표적인 신성장모형(新成長模型)을 그 특성별로 구분하여 정리하였다. 성장(成長)의 기본적 동인(動因)이라고 할 수 있는 기술진보(技術進步)나 인적자본(人的資本)의 축적(蓄積)을 내생화시키고 이를 통해 국가간(國家間) 성장률(成長率) 격차(隔差)를 모형내(模型內)에서 설명하려고 시도하는 등 여러 가지 새로운 이론적(理論的) 혁신(革新)이 이루어지고 있으나, 아직 비현실적인 수학적(數學的) 가정에 의존하고 있고 모형(模型)의 경직성으로 인하여 성장과정(成長過程)의 설명에 필수적인 주요 이슈들이 간과되어 있다는 점 등을 지적하였다.

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수정(修正)된 Jones모형(模型)을 이용(利用)한 한국(韓國)의 성장요인(成長要因) 분해(分解)

  • Lee, Chang-Su
    • KDI Journal of Economic Policy
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    • v.21 no.2
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    • pp.105-145
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    • 1999
  • Romer류의 내생적 성장모형과 신고전학파의 성장모형을 통합한 Jones(1997, 1998a)에 의하면 장기균형성장요인의 기여도가 예상보다 작고 여러 단기요인의 성장기여도가 큰 것으로 나타났다. 본고에서는 기술이용능력과 모방노력의 개념을 도입하여 Jones모형을 수정하고 이를 이용하여 한국의 성장요인을 분해한다. 이에 따르면 대GDP 투자비중, 연구인력비율 및 취업자 교육연수의 증가 등 이행경로상의 단기요인이 지난 30년간의 노동생산성 증가의 78%를 설명하고 있으며 균형성장경로 요인의 기여도는 22%에 지나지 않는다. 자본축적의 뒤를 이어 R&D 투자 등 새 단기요인의 역할이 증대되면서 우리나라의 경제성장률이 크게 하락하지 않을 것으로 예상된다.

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A Study on the Application of Latent Growth Model for Measuring the Outcomes of Library (도서관 성과 측정을 위한 잠재성장모형 적용에 관한 연구)

  • Park, Sung-jae;Han, Sang-woo;Cho, Sae-hong
    • Journal of the Korean Society for Library and Information Science
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    • v.52 no.4
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    • pp.179-194
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    • 2018
  • The purpose of this study is to discuss the application of the Latent Growth Model to measure the outcomes of public library. For outcome measurements, library circulation data were collected to identify longitudinal changes of library users' reading habit. The latent growth model was applied to statistically test the changes over time. The circulation data of 95,962 users registered in some public libraries in Seoul, ranged between 2010 and 2015, were analyzed using unconditional model, conditional model, and growth mixture model which all are called the latent growth model. The results show that the intercept of the model is 4.19 and the slop is 0.24 in the linear growth model. The gender difference in two latent variables including intercept and slop was a shade difference. The result from the growth mixture model analysis, additionally indicates that the number of books checked out by children under age 10 is rapidly increased. The application of the latent growth model in library fields is expected to widely spread out for the longitudinal data analysis.

Population Forecasting System Based on Growth Curve Models (성장곡선모형에 의한 인구예측 시스템)

  • 최종후;최봉호;양우성;김유진
    • Korea journal of population studies
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    • v.23 no.1
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    • pp.197-215
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    • 2000
  • 이 논문에서는 선형·비선형 성장곡선모형의 종류와 특성을 살펴보고, 이들을 비교·검토하고, 모형선호기준 통계량에 입각하여 추정결과를 비교한다. 또한 최종사용자 환경을 위한 SAS/AF로 구현한 성장곡선모형에 의한 인구예측시스템을 소개한다.

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Optimal Growth Model of the Cochlodinium Polykrikoides (Cochlodinium Polykrikoides 최적 성장모형)

  • Cho, Hong-Yeon;Cho, Beom Jun
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.26 no.4
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    • pp.217-224
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    • 2014
  • Cochlodinium polykrikoides is a typical harmful algal species which generates the red-tide in the coastal zone, southern Korea. Accurate algal growth model can be established and then the prediction of the red-tide occurrence using this model is possible if the information on the optimal growth model parameters are available because it is directly related between the red-tide occurrence and the rapid algal bloom. However, the limitation factors on the algal growth, such as light intensity, water temperature, salinity, and nutrient concentrations, are so diverse and also the limitation function types are diverse. Thus, the study on the algal growth model development using the available laboratory data set on the growth rate change due to the limitation factors are relatively very poor in the perspective of the model. In this study, the growth model on the C. polykrikoides are developed and suggested as the optimal model which can be used as the element model in the red-tide or ecological models. The optimal parameter estimation and an error analysis are carried out using the available previous research results and data sets. This model can be used for the difference analysis between the lab. condition and in-situ state because it is an optimal model for the lab. condition. The parameter values and ranges also can be used for the model calibration and validation using the in-situ monitoring environmental and algal bloom data sets.

Analysis of latent growth model using repeated measures ANOVA in the data from KYPS (청소년패널자료 분석에서의 반복측정분산분석을 활용한 잠재성장모형)

  • Lee, Hwa-Jung;Kang, Suk-Bok
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.6
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    • pp.1409-1419
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    • 2013
  • We analyzed the data from KYPS using the latent growth model which has been widely studied as an analysis method of longitudinal data. In this study, we applied repeated measures ANOVA to unconditional model in order for faster decision of the unconditional model of the latent growth model. Also, we compared the six-type models, the quadratic model and the model of which repeated measures ANOVA is applied.

A Study on the Demand Forecasting using Diffusion Models and Growth Curve Models (확산모형과 성장곡선모형을 이용한 중장기 수요예측에 관한 연구)

  • 강현철;최종후
    • The Korean Journal of Applied Statistics
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    • v.14 no.2
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    • pp.233-243
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    • 2001
  • 중장기 수요예측을 위해 자주 사용되는 방법으로 확산모형과 성장곡선모형을 들 수 있다. 본 논문에서는 이들 방법론의 성격 및 실제 적용에 있어 모수추정에 따른 문제점들을 살펴보고, 모수추정을 효율적으로 수행하기 위한 전략을 제시한다. 또한 실제 자료에 각 방법론들을 적용하여 예측결과를 비교한다.

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Genetic Aspects of the Growth Curve Parameters in Hanwoo Cows (한우 암소의 성장곡선 모수에 대한 유전적 경향)

  • Lee, Chang-U;Choe, Jae-Gwan;Jeon, Gi-Jun;Kim, Hyeong-Cheol
    • Journal of Animal Science and Technology
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    • v.48 no.1
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    • pp.29-38
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    • 2006
  • The objective of this study was to estimate genetic variances of growth curve parameters in Hanwoo cows. The data used in this study were records from 1,083 Hanwoo cows raised at Hanwoo Experiment Station, National Livestock Research Institute(NLRI). First evaluation model(Model I) fit year-season of birth and age of dam as fixed effects and second model(Model II) added age at the final weight as a linear covariate to Model I. Heritability estimates of A, b and k from Gompertz model were 0.22, 0.11 and 0.07 using modelⅠ and 0.28, 0.11 and 0.12 using modelⅡ. Those from Von Bertalanffy model were 0.22, 0.11 and 0.07 using modelⅠ, 0.28, 0.11 and 0.12 using modelⅡ. Heritability estimates of A, b and k from Logistic model were 0.14, 0.07 and 0.05 using modelⅠ, 0.18, 0.07 and 0.12 using modelⅡ. Heritability estimates of A from Gompertz model were higher than those from Von Bertalanffy model or Logistic model in both model Ⅰand model Ⅱ. Heritability estimates of b from Logistic model were higher than those from Gompertz model or Von Bertalanffy model in both modelⅠand model Ⅱ. Heritability estimates of birth weight, weaning weight, 3 month weight, 6 month weight, 9 month weight, 12 month weight, 18 month weight, 24 month weight, 36 month weight were after linear age adjustment 0.27, 0.11, 0.19, 0.14, 0.16, 0.23, 0.52 and 0.32, respectively. Heritability estimates of birth weight, weaning weight, 3 month weight, 6 month weight, 9 month weight and 24 month weight fit by Gompertz model were larger than those estimated from linearly adjusted data. Heritability estimates of 12 month weight, 18 month weight and 36 month weight fit by Von Bertalanffy model were larger than those estimated from linearly adjusted data. In the multitrait analyses for parameters from Gompertz model, genetic and phenotypic correlations between A and k parameters were -0.47 and -0.67 using modelⅠand -0.56 and -0.63 using model Ⅱ. Those between the A and b parameters were 0.69 and 0.34 using modelⅠand 0.72 and 0.37 using model Ⅱ. Those between the b and k parameters were -0.26 and 0.01 using modelⅠand -0.30 and 0.01 using model Ⅱ. In the multitrait analyses for parameters from Von Bertalanffy model, genetic and phenotypic correlations between A and k parameters were -0.49 and -0.67 suing model Ⅰ and -0.57 and -0.70 using modelⅡ. Those between the A and b parameters were 0.61 and 0.33 using modelⅠ and 0.60 and 0.30 using model Ⅱ. Those between the b and k parameters were -0.20 and 0.02 using modelⅠ and 0.16 and 0.00 using modelⅡ. In the multitrait analyses for parameters from Logistic model, genetic and phenotypic correlations between A and k parameters were -0.43 and -0.67 using model Ⅰ and -0.50 and -0.63 using modelⅡ. Those between the A and b parameters were 0.47 and 0.22 using modelⅠ and 0.38 and 0.24 using modelⅡ. Those between the b and k parameters were -0.09 and 0.02 using model Ⅰ and -0.02 and 0.13 using model Ⅱ.

A Model for Promoting Strategies of Emerging ICT (ICT 신기술 산업의 발굴 육성을 위한 전략 모형)

  • Park, S.J.
    • Electronics and Telecommunications Trends
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    • v.27 no.4
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    • pp.29-39
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    • 2012
  • 이 논문에서는 ICT(Information and Communications Technologies) 신기술 산업 발굴 추진 시 적용할 수 있는 신기술 발굴 육성 모형과 성장산업으로서 지속적인 유지를 위해 필요한 활동의 프레임워크를 제안하였다. 미래 신성장 기술에 대하여 대상 기술의 발굴, 기획 시부터 산업화에 이르기까지 전체 프로세스에 대하여 전략적 추진이 가능하도록 하는 구성 항목과 프레임워크를 제시하였다. 이를 위해 신기술 산업에 대한 기본적 개념과 기술혁신적 특성, 기술 성장 모형, 신기술 산업 성장 모형으로서 기능에 대하여 설명하였다. 또한 신기술이 성장산업으로 육성될 수 있도록 추진 시 필요한 활동과 구성 요소들의 프레임워크와 육성정책 추진 시 필요한 각각의 주요 관점과 고려사항들을 제시하였다.

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A Methodology for Improving fitness of the Latent Growth Modeling using Association Rule Mining (연관규칙을 이용한 잠재성장모형의 개선방법론)

  • Cho, Yeong Bin;Jun, Jae-Hoon;Choi, Byungwoo
    • Journal of the Korea Convergence Society
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    • v.10 no.2
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    • pp.217-225
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    • 2019
  • The Latent Growth Modeling(LGM) is known as the typical analysis method of longitudinal data and it could be classified into unconditional model and conditional model. It is common to assume that the growth trajectory of unconditional model of LGM is linear. In the case of quasi-linear, the methodology for improving the model fitness using Sequential Pattern of Association Rule Mining is suggested. To do this, we divide longitudinal data into quintiles and extract periodic changes of the longitudinal data in each quintiles and make sequential pattern based on this periodic changes. To evaluate the effectiveness, the LGM module in SPSS AMOS was used and the dataset of the Youth Panel from 2001 to 2006 of Korea Employment Information Service. Our methodology was able to increase the fitness of the model compared to the simple linear growth trajectory.