• Journal of Families and Better Life
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• v.19 no.6
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• pp.145-155
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• 2001

The purposes of this study were first to construct statistical and econometric models based on Amemiya\`s Type I Tobit mainly addressing the issue of statistical efficiency; second to explore income, price, and curvilinear age effects on the explained variable in order to illustrates its statistical marginal effects related to econometric issues; finally to provide invaluable insight for graphical simulations as a new interpretation approach using Tobit analysis. Results indicated that interpretation for the mean marginal effects of three possible cases of dependent variable was more likely to be evident to understand Tobit results compared to conventional analysis only using latent variable, beta. Results also revealed that prediction value of dependent variable can be possibly and easily projected by the independent variable changed whereas only beta value can not illustrate its projection as independent variables'changes.

• East Asian Economic Review
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• v.20 no.4
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• pp.493-517
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• 2016

This paper examines the persistent properties of 12 sectoral relative prices between Korea and Japan obtained following the Classification of Individual Consumption according to Purpose (COICOP) over the period of 1985-2016. Applying a new econometric method developed by Pesaran which controls for the cross-section dependence in a panel, we are not able to reject the hypothesis that the sectoral real exchange rates contain a common stochastic trend. On the other hand, the well-known panel unit root tests such as the IPS and LLC tests widely used by previous studies strongly reject the unit root hypothesis. Since the error term of the regression for our panel exhibits significant cross-section dependence, these opposite results justify that the use of the new econometric method is appropriate.

• The Journal of Information Systems
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• v.32 no.3
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• pp.19-39
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• 2023

Purpose This study aims to identify user experience factors that can enhance both metaverse utilization and satisfaction based on the honeycomb model. For this we presented two research questions: first, what are the experience factors of metaverse users? Second, do metaverse user experience factors impact satisfaction? Design/methodology/approach To address these questions, a mixed-methodology approach is employed, including text mining techniques to analyze online reviews and quantitative econometric analysis to reveal the relationship between user experience factors and satisfaction. A total of 69,880 reviews and ratings data were collected. Findings The analysis revealed eight metaverse user experience factors: entertainment, operability, virtual reality, immersion, economic activity, visual performance, avatar, and sociality, all of which were found to have a positive impact on user satisfaction.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.255-256
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• 2001

• Journal of Korean Society of Transportation
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• v.33 no.1
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• pp.61-69
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• 2015

This study compares the forecasting accuracy of five econometric models on domestic total freight volume in South Korea. Applied five models are as follows: Ordinary Least Square model, Partial Adjustment model, Reduced Autoregressive Distributed Lag model, Vector Autoregressive model, Time Varying Parameter model. Estimating models and forecasting are carried out based on annual data of domestic freight volume and an index of industrial production during 1970~2011. 1-year, 3-year, and 5-year ahead forecasting performance of five models was compared using the recursive forecasting method. Additionally, two forecasting periods were set to compare forecasting accuracy according to the size of future volatility. As a result, the Time Varying Parameter model showed the best accuracy for forecasting periods having fluctuations, whereas the Vector Autoregressive model showed better performance for forecasting periods with gradual changes.

• Environmental and Resource Economics Review
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• v.17 no.2
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• pp.255-286
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• 2008

In this paper, it is tried to combine the decomposition method and econometric analysis for the extension of the decomposition method. Since two approaches approach the energy efficiency problem in the different perspectives, it is believed that it is hard to reconcile the results of two approaches. In the results of energy intensity effect analysis with the econometric method, it is found that the increase in the energy price results in the improvement of energy intensity effect. In enconometric analysis of energy efficiency, the coefficient of a time trend measured as a proxy of energy efficiency is significant and has a negative effect on the energy consumption. This finding implies the energy efficiency improves very slowly over time. In addition, the directions of energy efficiency improvement in the decomposition method are consistent with those in the econometric analysis in four industries. This finding indicates that two methods may be in complementary cooperation for the analysis of energy efficiency. Therefore, it is needed the efforts to seek the complementarity between two methods for the enhancement of academic and policy implications.

• Journal of Korea Port Economic Association
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• v.26 no.4
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• pp.207-218
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• 2010

The purpose of the study is to predict the shipping business during the period of 2011 using the ARIMA-type models. This include the ARIMA and Intervention-ARIMA models. The multivariate cause-effect econometric model is not employed for not assuring a higher degree of forecasting accuracy than the univariate variable model. Such a cause-effect econometric model also fails in adjusting itself for the post-sample. This article introduces the four ARIMA models and six Intervention-ARIMA models. The monthly data cover the period January 2000 through October 2010. The out-of-sample forecasting performance is compared between the ARIMA-type models and the random walk model. Forecasting performance is measured by three summary statistics: root mean squared percent error, mean absolute percent error and mean percent error. The root mean squared percent errors of all the ARIMA-type models are somewhat higher than normally expected. Furthermore, the random walk model outperforms all the ARIMA-type models. This reveals that the BDI is just a random walk phenomenon and it's meaningless to predict the BDI using various econometric techniques. The ARIMA-type models show that the shipping market is expected to be bearish in 2011. These pessimistic ex-ante forecasts are supported by the Hodrick-Prescott filtering technique.

• Health Policy and Management
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• v.28 no.4
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• pp.339-351
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• 2018

Background: The purpose of this study is to estimate empirically whether there is a difference in medical use among income groups, and if so, how much. This study applies econometric model to the most recent year of Korean Medical Panel, 2015. The model consists of outpatient service and inpatient service models. Methods: The probit model is applied to the model which indicate whether or not the medical care has been used. Two step estimation method using maximum likelihood estimation is applied to the models of outpatient visits, hospital days, and outpatient and inpatient out-of-pocket cost models, with disconnected selection problems. Results: The results show that there was the inequality favorable to the low income group in medical care use. However, after controlling basic medical needs, there were no inequities among income groups in the outpatient visit model and the model of probability of inpatient service use. However, there were inequities favorable to the upper income groups in the models of probability of outpatient service use and outpatient out-of-pocket cost and the models of the number of length of stay and inpatient out-of-pocket cost. In particular, it shows clearly how the difference in outpatient service and inpatient service utilizations by income groups when basic medical needs are controlled. Conclusion: This means that the income contributes significantly to the degree of inequality in outpatient and inpatient care services. Therefore, the existence of medical care use difference under the same medical needs among income groups is a problem in terms of equity of medical care use, so great efforts should be made to establish policies to improve equity among income groups.

• Journal of Korean Society of Forest Science
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• v.100 no.1
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• pp.79-87
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• 2011

This study was conducted to identify the relationship between urban heat island effect and forest, analyzing electricity consumption model and temperature change model. Electricity consumption model was adopted to clarify a role of forests in alleviating the heat island effect at the national scale, while temperature change model was adopted to clarify a role of forests in mitigating urban heat island effect on metropolis with using econometric analysis. The analysis results from both models clearly show a negative correlation between the urban forests within living areas and heat island effect. In particular, when urban forests within living area per person increases by $1m^2$, the average municipal electricity consumption decreases by 0.02MWh and the summer daytime temperature for metropolitan cities decreases by $1.15^{\circ}C$.

• Journal of Korean Society of Forest Science
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• v.98 no.3
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• pp.284-289
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• 2009

This study estimated the fiberboard demand using VAR and econometric model, and compared the prediction accuracy of the two models. And the variance decomposition and impulse response were analyzed using VAR model, and predicted the fiberboard demand. The VAR model was specified with lagged dependent variable, lagged own price, lagged construction product, dummy. The econometric model was specified with own price, substitute price, construction product, dummy. The dummy variable reflected the abrupt decrease in fiberboard demand in the late 1990's. The results showed that the fiberboard demand prediction can be performed more accurately by VAR model than by econometric model. In the VAR model of fiberboard demand, after twelve months, the construction product change accounts for about fifty percent of variation in the demand, and the own price change accounts for about thirty percent of variation in the demand. On the other hand, the impact of a shock to the construction product is significant for about twelve months on the demand of fiberboard, and the impact of a shock to the own price is significant for about six months on the demand of fiberboard.