• Journal of Labour Economics
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• v.32 no.2
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• pp.95-124
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• 2009

In this article, I were trying to analyze the listed manufacturing companies' trend of productivity and the corporate education & training effect after the financial crisis. According to the analysis, the listed manufacturing companies have decreased their productivity since financial crisis, and from such declining trend. jobless growth and a growth without physical and human capital investment has been observed. Furthermore, there is no efficient labor force coordination within the manufacturing industry; In order to analyze the effect of education & training investment on productivity more deeply, I have practiced the dynamic panel data analysis from constructing the micro panel data which consists of company level information 1997~2008. According to the consequences, dynamic panel data analysis solved the problem of the overestimating education & training effect fairly well.

• 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.

• The Journal of Fisheries Business Administration
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• v.52 no.1
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• pp.47-63
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• 2021

The purpose of this study is to identify the leading price between Jeju and Wando's oliver flounder producer price and to analyze the dynamic effect of the regional producer price using the panel VAR model. In the process of analysis, it was confirmed that there are unit roots in the monthly data of Jeju and Wando's oliver flounder producer price. So, in order to avoid spurious regression, the rate change of producer price which carries out log difference was used in the analysis. As a result of the analysis, first, the panel Granger causality test showed that the influence of the change rate of producer price in oliver flounder in Jeju was slightly larger than that in Wando, but it was found that each region all leads the change rate of the producer price in oliver flounder. Second, the panel VAR estimation showed that the rate change of producer price in Jeju and Wando a month ago had a statistically significant effect on the change rate of producer price of each region. Third, the impulse response analysis indicated that other regions are affected a little more than the same region in case of the occurrence of the impact on the error terms of the change rate of produce price in Jeju and Wando oliver flounder. Fourth, the variance decomposition analysis showed that the change rate of producer price in the two regions was higher explained by Jeju compared to Wando. In conclusion, it is expected that the above results can not only be useful as basic data for the stabilization of oliver flounder producer price and the establishment of policies for easing volatility but can also help the oliver flounder industry operate its business.

• Survey Research
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• v.12 no.2
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• pp.89-112
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• 2011

This study shows the results of constructing panel data using Farm Household survey and presents some examples of empirical application. This study shows that ex post constructed panel data using repeated cross-sectional survey can be used in various dynamic analyses. This paper also shows that the well known difficult problem of longitudinal weights can be easily solved by using the existing cross-sectional weights in original cross-section data. Based on these results, we propose that the National Statistical Office not only try to construct panel data, but also construct panel data by using existing repeated cross-section data. The benefits of this approach seems to be very big in establishment survey.

• 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.

• The Journal of Industrial Distribution & Business
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• v.8 no.1
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• pp.5-13
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• 2017

Purpose - In this article, a dynamic model like a VAR is an appropriate choice for estimating the possible interrelationship between ownership structure and firm performance as a dynamic process. Research design, data, and methodology - Data of this work are collected from Chinese stock exchange including 350 Chinese-listed firms during the period of 1999-2012. We hypothesize that this interrelationship dynamically exists between ownership structure and firm performance. To examine the correlation, a panel Vector Auto-regression (PVAR) approach generated by GMM method is utilized to test the possible dynamic relation embedded in corporate governance. Another two dynamic analysis solutions such as orthogonalized impulse-response function and variance decomposition are also used simultaneously. Results - Findings of this study indicate the evidence that dynamically endogenous relationship exists between ownership structure and firm performance. Further, there is a dynamical correlation between investment and performance. Impulse response and variance decomposition illustrate that impact of a shock to variables themselves is the main source for their variability. Conclusions - The conclusion in this study is that there is a bidirectional and inter-temporal effect between proportion of ownership and corporate performance for a long run in accordance with impulse response function. Overall, our results suggest that corporate governance in China is more market oriented.

• International Area Studies Review
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• v.18 no.3
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• pp.175-201
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• 2014

This paper analyses the effect of R&D investment on local economies. R&D investment contributes to the regional local economy by increasing employment and production activity of the investees. The investees may end up with increased productivity, sales and employment. At the regional R&D level, the central government R&D fund and firm self R&D budget will be the source of R&D investment. Further positive effects are inter-related with local industries. This study carried out an empirical analysis on the effect of R&D investment on local economies using Korean panel data after comparing international literatures. The dynamic panel estimator is used to estimate an autoregressive model with lagged dependent variable. Using the Da Silva method, mixed variance-component moving-average error process is estimated and selected. R&D investment is very important factor to improve the productivity of a region and the size of the effect is dependent on the time periods within the Korean economic history.

• Journal of Technology Innovation
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• v.26 no.4
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• pp.173-198
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• 2018

In this paper, we analyze the determinants of the adoption of industrial robots using the data from 42 countries, and thereby examine the factors underlying the rapid expansion of industrial robots in Korea. To this end, the industrial robot data for the years 2001-2016 were drawn from the World Robotics dataset of the International Federation of Robotics (IFR). The explanatory variables included labor market environment variables and innovation capacity variables extracted from the dataset of the relevant international organizations. For data analysis, the Arellano-Bond dynamic panel analysis was performed to control for the endogeneity problem of some explanatory variables. The empirical results confirmed the exceptionally rapid expansion of industrial robots in Korea as compared to other countries, even when considering the national income level, employment cost, and innovation capacity. This phenomenon could be attributed to both the demand-side and supply-side factors. For one thing, changes in the labor market environment, such as an increase in employment costs, have led to an increase of the corporate demand for industrial robots. For another, the supply-side factors, such as an increase in the capital intensity and innovation capacity of companies, have also contributed to the widespread adoption of industrial robots.

• Journal of Families and Better Life
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• v.32 no.6
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• pp.89-107
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• 2014

This study analyzes how governmental financial support of child care affects the participation of married women in the labor market in Korea. This dynamic analysis used data gathered over four years via the fifth to the eighth Korea Welfare Panel Studies (KWPS). The major results are as follows. First, child care allowance has a negative effect on the participation of married women in the labour market. Providing cash for child care seems to decrease women's labour market participation by cementing the role of women as the primary child care providers in the household. Second, the support for families, used by child care facilities, is found to increase the probability of married women working either part-time or full-time, thereby decreasing the burden on household budgets caused by child care costs. In conclusion, governmental policy-based child care benefits, used by child care centers, should be continued so that married women may participate in the labour market while raising their children.

• Asia-Pacific Journal of Business
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• v.13 no.1
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• pp.277-288
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• 2022

Purpose - This study analyzed the determinants of local unemployment rate in Korea using panel data from 16 metropolitan cities and provinces from 2000 to 2018. Design/methodology/approach - We use a dynamic spatial panel model that considers characteristics of the regional unemployment rate such as the common factors effect, spatial dependence, and serial correlations. Findings - The local unemployment rate is affected by the past and present values of the national unemployment rate. And it is significantly affected by the past local unemployment rate and the past neighboring unemployment rate because spatial dependence and serial correlations are clearly present. In addition, when the industrial structure diversity and labor productivity were high, the regional unemployment rate decreased, and when the education level was high, the regional unemployment rate increased. Research implications or Originality - In order to reduce regional unemployment rate, it is necessary to plan and establish regional customized industrial structure policies under the stance of diversification rather than specializing the regional industrial structure and accompany improvement of the quality of education with the number of years of education. In addition, the redistribution of labor from low labor productivity sectors to high labor productivity sectors through technology development will help to reduce the local unemployment rate.