• Korea Trade Review
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• v.41 no.4
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• pp.91-110
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• 2016

AEO certification has a positive effect on firm's performance. Therefore, this study analyzed the effect of AEO certification on firm's performance using panel data analysis for firm to have international competitiveness. It uses the Hausman-Taylor test for effective solutions of endogenous matter. In terms of the result of analysis, AEO certification has a positive effect on domestic and foreign sales, especially direct benefit and business process improvement of AEO certification have a positive effect on domestic and foreign sales through the improvement of international logistics flow. In conclusion, this study proposes the policy of AEO certification by analyzing the effect of AEO certification on firm's performance by using the panel data analysis.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2017.05a
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• pp.619-619
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• 2017

현대사회의 제품생산과 기업활동에서 소프트웨어의 중요성과 그 가치가 날로 높아져 가는 가운데 소프트웨어 기술혁신은 과거 소프트웨어 산업 영역에 국한되었던 비교적 작은 구조에서 이제는 다양한 산업 영역에서 다발적으로 일어나는 보다 넓은 구조로 변모하고 있다. 이 연구에서는 한국 출원인이 포함된 약 270만 건의 특허 메타데이터와 기업정보 데이터를 활용한 패널데이터를 구축하여 한국 산업계 전반에 걸쳐 일어나고 있는 소프트웨어 기술혁신의 구조 변동 현상을 밝혀내고, 이를 토대로 정부의 소프트웨어 산업 정책에 관한 함의를 도출하고자 한다. 이 연구는 다음의 네 부분으로 구성이 된다. 첫째, 최근 여러 분야에서 일어나고 있는 소프트웨어와 타 산업 간의 융합 현상과 이에 대한 이론적 논의를 전개한다. 둘째, 연구에 활용 할 데이터와 실증분석 방법론에 관하여 논의한다. 셋째, 패널분석을 기초로 한 실증분석을 수행하고, 그 결과를 제시한다. 넷째, 한국정부의 소프트웨어 산업 정책을 살펴보고, 이를 바탕으로 실증분석 결과가 지니는 함의에 관하여 논의한다.

• Korean Journal of Legislative Studies
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• v.23 no.2
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• pp.147-177
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• 2017

Although a number of empirical studies found that political ideology plays a significant role in Korean elections, they entirely rely on cross-sectional data analysis. In contrast to previous research, this study investigates the effects of ideology in the 2012 Korean presidential election through standard panel data analysis. Specifically, using "EAI Panel Study, 2012", the effects of ideology on both candidate evaluation and vote choice were examined via fixed effects, random effects, and pooled regression analysis. And the results from applying the two most popular models of ideological voting, the proximity model and the directional change model were also compared. The results show that candidate evaluations and vote choice during the election (April, 2012- December, 2012) were significantly influenced by the ideological difference between voters and candidates, independent from partisanship and other standard socio-demographic factors. And this ideological voting during the election seems better captured by the directional change model than by the proximity model.

• 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.

• 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.

• Environmental and Resource Economics Review
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• v.25 no.1
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• pp.89-112
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• 2016

In this paper, as a determining factor of the Environment Kuznets Curve hypothesis, we analyzed the impact of technological innovation. In this paper, in order to empirically validate the role of technological innovation to an inverted U-shaped Environments Kuznets Curve hypothesis, we utilize the 2SLS considering relationship between R&D and the GDP per capita. Also, using the Panel VAR (Panel Vector Auto Regression) model to analyze with what time lag R&D per capita has impact on the emissions of greenhouse gases per capita. Empirical results show that R&D per capita(proxy of innovation) is a important factor to explain Environmental Kuznets Curve hypothesis, and that the external shock such as R&D per capita reduces greenhouse gas emissions per capita with about 3 time lag.

• The Journal of the Convergence on Culture Technology
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• v.5 no.2
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• pp.77-82
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• 2019

The purpose of this study is to analyze the relationship between the controlling shareholding ratio and the business diversification of savings banks The difference in this study is the analysis of the relationship between the controlling shareholding ratio of the savings bank and the business diversification using panel data. In this study, the semi-annual financial statements for the period 2014-2018 were used on the basis of a sample of 79 saving banks. The research model is analyzed using random effects generalized linear square (GLS) model considering the autocorrelation problem. As a result of the empirical analysis, it is estimated that the relationship between the controlling shareholding ratio of the savings bank and the business diversification is significant (+). This is the result of supporting the hedging hypothesis.

• Journal of Korea Technology Innovation Society
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• v.13 no.3
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• pp.513-537
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• 2010

According to the "FDI-as-market-discipline" hypothesis, inward FDI acts as a mechanism of change in market structure affecting innovative activities of domestic firms. We used panel KIS data for testing this hypothesis. Binary probit estimation shows that, in contrast to the German case of Bertschek (1995), FDI is insignificant in Korean case for explaining product innovation. 1his result maybe comes from the fact that the industries in Korea are more monopolistic or oligopolistic than those of Germany. Using panel data, we tried random parameter estimation using matrix weighted average of GLS and OLS. The result shows different estimates from cross-section outcome and panel estimation with parameter homogeneity, so we can infer large parameter heterogeneity across firms. But, interpretation for FDI variable is similar across panel and cross-section estimation.

• Journal of Labour Economics
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• v.41 no.3
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• pp.161-186
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• 2018

Albeit numerous endeavors in matching names and surveying inventors, inventor-level studies of patent data have been scarce because unique inventors can not be identified across patents. Using the Korean patent data with inventor IDs, birth year, and gender available, we construct unique inventor-level panel data. As the first undertaking with our data, we investigate the age profile of patent productivity among inventors. We find an inverted U-shaped profile with the peak at age 31. We also find an increasing productivity for younger cohorts of inventors. These findings are robust after we control for the calendar year effects and the quality of patents.

• The Journal of Bigdata
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• v.5 no.2
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• pp.135-143
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• 2020

This paper proposes a pre-processing method and a dimensional reduction method in the analysis of shopping carts where there are many correlations between variables when dividing the types of consumers in the agri-food consumer panel data. Cluster analysis is a widely used method for dividing observational objects into several clusters in multivariate data. However, cluster analysis through dimensional reduction may be more effective when several variables are related. In this paper, the food consumption data surveyed of 1,987 households was clustered using the K-means method, and 17 variables were re-selected to divide it into the clusters. Principal component analysis and factor analysis were compared as the solution for multicollinearity problems and as the way to reduce dimensions for clustering. In this study, both principal component analysis and factor analysis reduced the dataset into two dimensions. Although the principal component analysis divided the dataset into three clusters, it did not seem that the difference among the characteristics of the cluster appeared well. However, the characteristics of the clusters in the consumption pattern were well distinguished under the factor analysis method.