• Journal of Energy Engineering
• /
• v.22 no.4
• /
• pp.370-375
• /
• 2013

This paper attempts to estimate the city gas demand function in Korea over the period 1981-2012. As the city gas demand function provides us information on the pattern of consumer's city gas consumption, it can be usefully utilized in predicting the impact of policy variables such as city gas price and forecasting the demand for city gas. We apply lagged dependent variable model and ordinary least square method as a robust approach to estimating the parameters of the city gas demand function. The results show that short-run price and income elasticities of the city gas demand are estimated to be -0.522 and 0.874, respectively. They are statistically significant at the 1% level. The short-run price and income elasticities portray that demand for city gas is price- and income-inelastic. This implies that the city gas is indispensable goods to human-being's life, thus the city gas demand would not be promptly adjusted to responding to price and/or income change. However, long-run price and income elasticities reveal that the demand for city gas is price- and income-elastic in the long-run.

• Journal of Digital Convergence
• /
• v.16 no.5
• /
• pp.137-143
• /
• 2018

Korea's air passenger traffic has been growing steadily. In this paper, we propose a forecasting model of air passenger demand to ascertain the growth trend of air passenger transportation performance in Korea. We conducted a simulation based on System Dynamics with the demand as a dependent variable, and international oil prices, GDP and exchange rates as exogenous variables. The accuracy of the model was verified using MAPE and $R^2$, and the proposed prediction model was verified as an accurate prediction model. As a result of the demand forecast, it is predicted that the air passenger demand in Korea will continue to grow, and the share of low cost carriers will increase sharply. The addition of the Korean transportation performance of foreign carriers in Korea and the transportation performance of Korean passengers due to the alliance of airlines will provide a more accurate forecast of passenger demand.

• Journal of Korean Society of Forest Science
• /
• v.81 no.2
• /
• pp.124-138
• /
• 1992

This study was carried out to estimate long-term demand functions, and to project consumption of roundwood to the year 2030, using time series data for the period 1970-1990. Especially, the unique features of this study are in the estimation of demand functions for roundwood by species group and by end-use with help of dummy variables. It also, attempts to show how dummy variables can be utilized for improving the estimation result. The result of this study reveals that hardwood roundwood consumption is being substituted by softwood roundwood due to the rapid increase in the relative price of softwood, and this trend is expected to continue in the near future. The consumption of roundwood by mining industry is projected to fall as the coal :mining is expected to decline. The parametric estimates of timber demand function by species group and by end-use indicate that the demand for timber in Korea is more responsive to the performance of domestic economy as a whole, represented by GDP in this study, than to other variables such as own and substitute prices. The effects of population growth and substitute prices could not be determined.

• Communications for Statistical Applications and Methods
• /
• v.17 no.5
• /
• pp.697-712
• /
• 2010

This paper is concerned with the statistical analysis and development of stochastic models for the demand for life insurance policy loans. For these, firstly the characteristics of the regression trend, periodicity and dependence of the monthly demand for life insurance policy loans are investigated by a statistical analysis of the monthly demand data for the years 1999 through 2008. Secondly, the causal relationships between the demand for life insurance policy loans and the economic variables including unemployment rate and inflation rate for the period are investigated. The results show that inflation rate is main factor influencing policy loan demands. The overall evidence, however, failed to establish unidirectional causality relationships between the demand series and the other variables under study. Finally, based on these, univariate time series model and transfer function model where the demand series is related to one input series are derived, respectively, for the prediction of the demand for life insurance policy loans. A statistical procedure for using the model to predict the demand for life insurance policy loans is also proposed.

• The Korean Journal of Applied Statistics
• /
• v.21 no.1
• /
• pp.151-157
• /
• 2008

In generally, we use a method of the survey to forecast the economic demands and non-economic demands for a market trend. But we have a difficult problem to estimate the demand for the marketplace objectively because the survey with the non-response and the inadequate understanding on questionnaires did not provided the strong and uniform forecast. Here, we proposed a method compounded of survey and a statistical model to estimate the demand for the marketplace and discussed the mixture model applied to the service demand on an agency.

• Journal of the Korea Convergence Society
• /
• v.6 no.6
• /
• pp.221-229
• /
• 2015

This study aims to identify and analyze the main factors that determine the properties and buying behavior in the premium bottled select and analyze the degree of impact on the relevant variables are premium water demand. When applied to the truncated negative binomial model to derive the study results: The results of estimating the variables that affect the demand for premium mineral water are as follows. Premium bottled water demand of this group my purchases with a choice between buying behavior variables are significantly higher than the relative population. To also do a good ingredient water, it appeared to be on a statistically significant positive effect on the demand for the more groups you purchase a premium bottled water for the purpose of receiving special feeling, just buy purpose is called to drinking water does not significantly affect to be analyzed. Among demographic characteristics it showed that demand for premium bottled water purchases are significantly higher in women than in men, professional / clerical job, such as the military, college graduates were more consumer research as significant in comparison to the relative population. Taste and package design factors of premium bottled mineral water among the select attribute factors are having a significant positive impact on the purchasing demand, local conditions and cost factors have been estimated to be insignificant.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.14 no.7
• /
• pp.3223-3231
• /
• 2013

Fire service budget must be increased continually to supply sufficient fire service for safety life of people. A way to increases fire service budget is to plan and improve regional resources facilities tax system. The purpose of this articles is to analyzes the relationship between regional resources facilities tax and fire service budget, fire service investment budget, socioeconomic factor, fire service demand. To do this, this study sets up five hypotheses based on the theoretical backgrounds and the past research. The statistical methods used for the verification of hypotheses are multiple regression analysis and t test. The analysis showed that regional resources facilities tax was positive significant variable for fire service investment budget and fire service budget and socioeconomic factor was a positive significant variable for regional resources facilities tax. And the analysis showed that fire and rescue variable of fire demand factor were positive significant for regional resources facilities tax.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.12 no.4
• /
• pp.327-335
• /
• 2019

This study develops a prediction model for toilet and laundry water end-uses based on surveyed data which measured housing and household characteristics of 140 households over 5 years in Korea. Classical regression model assuming a normal distribution was not appropriate and estimated parameters were biased, because the distribution of measured water-uses was left-skewed. As an alternative to this problem, we considered the distribution of weibull and lognormal for each water-uses, and three regression models were compared using log-likelihood and scale parameter. As a result, weibull regression were chosen to be appropriate for both water-uses and also presented the factors that affect each water-use. This results expect that an insight is provided on water resources utilization and theoretical support role for effective water resource management.

• Journal of Korean Society of Transportation
• /
• v.27 no.6
• /
• pp.167-176
• /
• 2009

Several travel demand management schemes have been used for controlling overloaded traffics on urban area. To maximize efficiency of the travel management, traffic manager has to set target level that we try to arrive in advance, and then to find optimal variable to attain this goal. In this regard, this paper presents two travel demand management models, expressed by mathematical program, and also presents their solution algorithms. The first is to find optimal travel demand for origin-destination (OD) pair, based on average travel time between the OD pair, and the second is based on the ratio of volume over capacity on congested area. An example is given to test the models.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.39 no.1
• /
• pp.81-91
• /
• 2019

Although the number of users of urban railways is greatly influenced by the land use plan around the railway station, Korea has been studying this problem in a small scale, so that the entrance width is uniformly calculated irrespective of the land use plan, And there is little deviation. Therefore, this study aims to establish a demand estimation model for the entrance and exit of urban railway stations. For this purpose, the demand, land use area, and socioeconomic indicators for each of the 20 urban railway stations were surveyed at 200m and 500m Regression model. The model is based on the assumption that the dependent variable (response variable) of the model is set to 1 day, peak 1 hour, peak time 5 minutes, Education, and park) and socioeconomic indicators (population, employer, employee, and student) as independent variables (explanatory variables). As a result, it was analyzed that the fit of the model is more statistically significant when the use area of the land use by 500 meters of the center radius of the city rail is used as an independent variable and the demand for the daily use of the railway station is used as a dependent variable. The purpose of this study is to estimate the optimal size of urban railway entrance in order to improve the mobility of the user and the transportation weak in urban railway station.