• Journal of the Korean Statistical Society
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• v.29 no.1
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• pp.9-16
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• 2000

This article addresses the problem of maximum likelihood estimation in ARCH regression with lagged dependent variables. Some topics in asymptotics of the model such as uniform expansion of likelihood function and construction of a class of MLE are discussed, and the regularity property of MLE is obtained. The error process here is possibly non-Gaussian.

• Journal of Korean Society of Forest Science
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• v.98 no.2
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• pp.148-155
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• 2009

The objective of this study is to know market structures of softwood logs being imported to South Korea from log producing countries. Import demand of softwood logs imported to South Korea from America, New Zealand and Chile is fixed as a function of log prices, the lagged dependent variable and output. On the basis of the adaptive expectations model, linear regression models that the explanatory variables included and the lagged dependent variable were estimated by Seemingly Unrelated Regression Equations (SURE). The short-run and long-run own price elasticity of America's softwood log import demand is -1.738 and -4.250 respectively. Then long-run elasticity is much higher than short-run elasticity. Short-run and long-run crosselasticity of New Zealand's softwood log import demand with respect to American's softwood log import price are inelastic at 0.505 and 0.883 respectively. Short-run and long-run cross-elasticity of Chile's softwood log import demands with respect to American's softwood log import prices were highly elastic at 2.442 and 4.462 respectively. Long-run elasticity was almost twice as high as short-run elasticity.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.8 no.11
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• pp.27-34
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• 1985

Recently the distributed lag models for time series data have been used in several quantitative analyses. But the analyses of time series which have the serial correlations in error terms and the lagged values of dependent variables violate the hypothesis of OLS method. This paper suggests that the approach technique of distributed lay model with serial correlation should be applied by the Bayesian inference to estimate the parameters. For the application of distributed lag model by Bayesian analysis, the data for monthly consumption expenditure per household by items of commodities from 1972 to 1981 are used in order to estimate the lagged coefficient of processed food and the regression coefficient of the food and beverage.

• Safety and Health at Work
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• v.11 no.3
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• pp.314-321
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• 2020

Background: Occupational accidents occur for a variety of reasons, such as unsafe behaviors of workers and insufficient safety equipment at the workplace, but there are also various economic and social factors that can impact working conditions and working environment. This study analyzed the relationship between changes in economic factors and the occurrence of occupational accidents in Korea. Methods: Multilinear regression analysis was used as the analysis model. The general to specific method was also used, which consecutively removes statistically insignificant variables from a general model that includes dependent variables and lagged variables of dependent variables. Results: The frequency of occupational accidents was found to have a statistically significant relationship to economic indicators. The monthly number of cases of occupational injury and disease and fatal occupational injuries were found to be closely related to manufacturing capacity utilization, differences in the production index in the services sector, and commencements of building construction. The increase in equipment investment indicators was found to reduce fatal occupational injuries. Conclusion: The results of this study may be used to develop occupational accident trends or leading indicators, which in turn can be used by organizations that manage and monitor occupational accidents toward taking administrative action designed to reduce occupational accidents. The results also imply that short-term and mid- to long-term economic and social changes that can impact workers, workplaces and working conditions, and workplace organizations must be taken into account if more effective government policies are to be established and implemented toward further prevention of occupational accidents.

• Journal of Preventive Medicine and Public Health
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• v.52 no.1
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• pp.51-59
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• 2019

Objectives: The purpose of this study was to estimate the mediating effect of subjective unmet healthcare needs on poor health. The mediating effect of unmet needs on health outcomes was estimated. Methods: Cross-sectional research method was used to analyze Korea Health Panel data from 2011 to 2015, investigating the mediating effect for each annual dataset and lagged dependent variables. Results: The magnitude of the effect of low income on poor health and the mediating effect of unmet needs were estimated using age, sex, education level, employment status, healthcare insurance status, disability, and chronic disease as control variables and self-rated health as the dependent variable. The mediating effect of unmet needs due to financial reasons was between 14.7% to 32.9% of the total marginal effect, and 7.2% to 18.7% in lagged model. Conclusions: The fixed-effect logit model demonstrated that the existence of unmet needs raised the likelihood of poor self-rated health. However, only a small proportion of the effects of low income on health was mediated by unmet needs, and the results varied annually. Further studies are necessary to search for ways to explain the varying results in the Korea Health Panel data, as well as to consider a time series analysis of the mediating effect. The results of this study present the clear implication that even though it is crucial to address the unmet needs, but it is not enough to tackle the income related health inequalities.

• Journal of Energy Engineering
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• v.25 no.2
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• pp.37-44
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• 2016

The demand for electricity has a considerable impact on various energy sectors since electricity is generated from various energy sources. This paper attempts to estimate the electricity demand function and obtain some quantitative information on price and income elasticities of the demand. To this end, we apply a lagged dependent variable model to derive long-run as well as short-run elasticities using the time-series data over the period 1991-2014. Our dependent variable is annual electricity demand. The independent variables include constant term, real price of electricity, and real gross domestic product. The results show that the short-run price and income elasticities of the electricity demand are estimated to be -0.142 and 0.866, respectively. They are statistically significant at the 5% level. That is, the electricity demand is in-elastic with respect to price and income changes in the short-run. The long-run price and income elasticities of the electricity demand are calculated to be -0.210 and 1.287, respectively, which are also statistically meaningful at the 5% level. The electricity demand is still in-elastic with regard to price change in the long-run. However, the electricity demand is elastic regarding income change in the long-run. Therefore, this indicates that the effect of demand-side management policy through price-control is restrictive in both the short- and long-run. The growth in electricity demand following income growth is expected to be more remarkable in the long-run than in the short-run.

• The KIPS Transactions:PartB
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• v.14B no.7
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• pp.531-540
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• 2007

In this research, we proposed a two-phase hybrid stock price forecasting model with cointegration tests and artificial neural networks. Using not only the related stocks to the target stock but also the past information as input features in neural networks, the new model showed an improved performance in forecasting than that of the usual neural networks. Firstly in order to extract stocks which have long run relationships with the target stock, we made use of Johansen's cointegration test. In stock market, some stocks are apt to vary similarly and these phenomenon can be very informative to forecast the target stock. Johansen's cointegration test provides whether variables are related and whether the relationship is statistically significant. Secondly, we learned the model which includes lagged variables of the target and related stocks in addition to other characteristics of them. Although former research usually did not incorporate those variables, it is well known that most economic time series data are depend on its past value. Also, it is common in econometric literatures to consider lagged values as dependent variables. We implemented a price direction forecasting system for KOSPI index to examine the performance of the proposed model. As the result, our model had 11.29% higher forecasting accuracy on average than the model learned without cointegration test and also showed 10.59% higher on average than the model which randomly selected stocks to make the size of the feature set same as that of the proposed model.

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

• 한국노년학
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• v.39 no.2
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• pp.347-362
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• 2019

This study aimed to investigate the association between social support and the change of depressive symptoms and its difference by gender among Korean Baby Boomer. We used the Korean Longitudinal Study of Aging (KLoSA) 5th (in 2014) and 6th waves (in 2016). Samples were Korean Baby Boomer (born 1955 to 1963) who have spouse and children(N = 1,210). Dependent variable was depressive symptoms and independent variables were four social support variables (spousal relationship satisfaction, parent-child relationship satisfaction, frequency of social contact, and number of participation groups). Interaction variables between social support and gender were also included in the model. Hierarchical regression analysis with the lagged dependent variable was performed. Results showed that the higher the satisfaction of spousal relationship and the satisfaction of parent-child relationship, the less the depressive symptoms increased. All interaction variables were not significant. These findings mean that the support from the spouse and the child is helpful in lowering depressive symptoms, and the associations between social support and depressive symptoms are not different by gender among Baby Boomer. It implies that interventions for enhancing family relationships, especially spousal relationship and parent-child relationship, may be useful to reduce depressive symptoms among Korean Baby Boomer.

• Journal of Korea Water Resources Association
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• v.33 no.1
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• pp.51-59
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• 2000

A dynamic model, which combined time series model with distributed-lag model, is applied to understand the relationship between rainfall and groundwater level. In the model, rainfall with distribution lags and past groundwater level as a dependent variables were used to estimate present groundwater level. The distribution of the lagged rainfall effects for groundwater levels was modeled by Almon polynomials. The model was applied to Banglim and Tanbu groundwater stations in Pyungchang river and Bocheong stream watershed which are representative basins for International Hydrological Program (IHP). The dynamic model represents observed groundwater levels very well and can be used to predict the levels. The model parameters reflect hydraulic characteristics of aquifer. In addition, from the parameters it appears that the increase in groundwater level due to rainfall takes place significantly within first two days of the rainfall event. The rainfall of the order of 18mm/day and 30mm/day at Banglim and Tanbu, respectively, had no significant effect on the groundwater levels.