• Title/Summary/Keyword: Exogenous Variable

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Forecasting Foreign Visitors using SARIMAX Models with the Exogenous Variable of Demand Decrease (수요감소 요인 외생변수를 갖는 SARIMAX 모형을 이용한 관광수요 예측)

  • Lee, Geun-Cheol;Choi, Seong-Hoon
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.43 no.4
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    • pp.59-66
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    • 2020
  • In this study, we consider the problem of forecasting the number of inbound foreigners visiting Korea. Forecasting tourism demand is an essential decision to plan related facilities and staffs, thus many studies have been carried out, mainly focusing on the number of inbound or outbound tourists. In order to forecast tourism demand, we use a seasonal ARIMA (SARIMA) model, as well as a SARIMAX model which additionally comprises an exogenous variable affecting the dependent variable, i.e., tourism demand. For constructing the forecasting model, we use a search procedure that can be used to determine the values of the orders of the SARIMA and SARIMAX. For the exogenous variable, we introduce factors that could cause the tourism demand reduction, such as the 9/11 attack, the SARS and MERS epidemic, and the deployment of THAAD. In this study, we propose a procedure, called Measuring Impact on Demand (MID), where the impact of each factor on tourism demand is measured and the value of the exogenous variable corresponding to the factor is determined based on the measurement. To show the performance of the proposed forecasting method, an empirical analysis was conducted where the monthly number of foreign visitors in 2019 were forecasted. It was shown that the proposed method can find more accurate forecasts than other benchmarks in terms of the mean absolute percentage error (MAPE).

A Stagewise Approach to Structural Equation Modeling (구조식 모형에 대한 단계적 접근)

  • Lee, Bora;Park, Changsoon
    • The Korean Journal of Applied Statistics
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    • v.28 no.1
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    • pp.61-74
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    • 2015
  • Structural equation modeling (SEM) is a widely used in social sciences such as education, business administration, and psychology. In SEM, the latent variable score is the estimate of the latent variable which cannot be observed directly. This study uses stagewise structural equation modeling(stagewise SEM; SSEM) by partitioning the whole model into several stages. The traditional estimation method minimizes the discrepancy function using the variance-covariance of all observed variables. This method can lead to inappropriate situations where exogenous latent variables may be affected by endogenous latent variables. The SSEM approach can avoid such situations and reduce the complexity of the whole SEM in estimating parameters.

Speed and position control of the AC motor using variable structure controller with disturbance observer (외란 관측자와 가변구조제어기를 이용한 AC 서보모터의 속도 및 위치 제어)

  • 은용순;김광수;조동일
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.652-655
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    • 1996
  • This paper develops an AC motor controller for applications. The AC motor controller is designed based on the variable structure control method and a variable structure disturbance observer is added to reduce the effects of exogenous disturbances. The designed controller is installed on the z-axis of a CNC machining center and milling experiments were performed. The results show improved performance on both position and speed tracking, when compared to the factory-designed servo controller.

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Some limiting properties for GARCH(p, q)-X processes

  • Lee, Oesook
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.3
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    • pp.697-707
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    • 2017
  • In this paper, we propose a modified GARCH(p, q)-X model which is obtained by adding the exogenous variables to the modified GARCH(p, q) process. Some limiting properties are shown under various stationary and nonstationary exogenous processes which are generated by another process independent of the noise process. The proposed model extends the GARCH(1, 1)-X model studied by Han (2015) to various GARCH(p, q)-type models such as GJR GARCH, asymptotic power GARCH and VGARCH combined with exogenous process. In comparison with GARCH(1, 1)-X, we expect that many stylized facts including long memory property of the financial time series can be explained effectively by modified GARCH(p, q) model combined with proper additional covariate.

A Study on Environmental and Economic Cost Analysis of Coal Thermal Power Plant Comparing to LNG Combined Power Plant (석탄화력발전대비 LNG복합화력발전 환경성 및 경제성 비용분석에 관한 연구)

  • Kim, Jong-Won
    • Asia-Pacific Journal of Business
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    • v.9 no.4
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    • pp.67-84
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    • 2018
  • This study is about comparing coal thermal plant to LNG combined power plant in respect of environmental and economic cost analysis. In addition sensitive analysis of power cost and discount rate is conducted to compare the result of change in endogenous and exogenous variable. For environmental assessment, when they generate 10,669GWh yearly, coal thermal power plant emits sulfur oxides 959ton, nitrogen oxide 690ton, particulate matter 168ton and LNG combined power plant emits only nitrogen oxide 886ton respectively every year. Regarding economic cost analysis on both power plants during persisting period 30 years, coal thermal power plant is more cost effective 4,751 billion won than LNG combined taking in account the initial, operational, energy and environmental cost at 10,669GWh yearly in spite of only LNG combined power plant's energy cost higher than coal thermal. In case of sensitive analysis of power cost and discount rate, as 1% rise or drop in power cost, the total cost of coal thermal power plant increases or decreases 81 billion won and LNG combined 157 billion won up or down respectively. When discount rate 1% higher, the cost of coal thermal and LNG combined power plant decrease 498 billion won and 539 billion won for each. When discount rate 1% lower, the cost of both power plant increase 539 billion won and 837 billion won. With comparing each result of change in power cost and discount rate, as discount rate is weigher than power cost, which means most influential variable of power plan is discount rate one of exogenous variables not endogenous.

Robustness of discrete-time variable structure control to parametric uncertainties (매개변수의 불확실성에 대한 이산시간 가변구조 제어기법의 견실성)

  • 은용순;조동일
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.293-296
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    • 1997
  • Robust stability conditions for discrete-time variable structure control is proposed. Conventionally the discrete-time variable structure control method with a variable structure uncertainty compensator approach requires a bounded changing rate of the uncertainties to ensure robust stability. However, when uncertainties vary as a function of state variables, which occur with parametric uncertainties, it is not reasonable to assume a bounded variation on the uncertainties. In this paper, uncertainties are assumed to consist of exogenous disturbances and parametric uncertainties. An uncertainty compensator is used to deal with the former, and a robust stability condition is derived using Small Gain Theorem for the latter.

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A Study on Causal Factors of Organizational Commitment of Public Servants in Urban Health Centers: Testing a Hypothetical Canusal Model (도시보건소 공무원의 조직몰입도 인과요인에 관한 연구 - 한 가설적 인과모형분석을 통해 -)

  • 이상준;김창엽;김용익;신영수
    • Health Policy and Management
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    • v.8 no.1
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    • pp.52-96
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    • 1998
  • To find causal factors and improvement plans of organizational commitment of public servants in urban health centers, a hypothetical causal model, which included 2 endogenous variables(organizational commitment & organizational satisfaction) and 15 exogenous variables, was constructed. Exogenous variables consisted of individual factors (sex, age, education, job-grade, and annual salary), psychological variables(pride for organization, extrinsic motivation, intrinsic motivation and support of supervisor) ad structural variables(formalization, centralization, communication, job-conflict, job-decision, and workload). In the hypothetical causal model, organizational commitment was supposed to be effect variable, and organizational satisfaction was presumed to be intervening variable to mediate between organizational commitment and exogenous variables. For data collection, cross-sectional self-administered questionnaire survey was conducted to 1,295 public servants from 32 urban health centers nationwide. The survey responses were from 934, 72.1% of subjects. But 756 responses(58.4%) were analyzed because of excluding ones with missing values. The hypothetical causal model was fitted by covariance structural analysis with maximum likelihood method. Main results were as follows: (1) The fitted causal model accounted for 33 and 55 percent of total variance of organizational commitment and organizational satisfaction of public servants, respectively. (2) In order of effect size, pride for organization, supervisor support, communication, extrinsic motivation and centralization had an indirect effect effect on organizational commitment through organizational satisfaction. However, the effect of centralization was negative. (3) Pride for organiztion, intrinsic motivation, organizational satisfaction, job-conflict, supervisor support, communication, age, centralization, annual salar and extrinsic motivation had indirect or direct effects on organizational commitment in order of effect size. Among them, effects of job-conflict and centraldization were negative. In conclusion, these results suggested that organizational commitment of public servants in urban health centers could be enhanced by pride for organization, intrinsic and extrinsic motivations, prevention of job-conflict and excess centralization, supervisor support and active communication. Especially, pride for organization and intrinsic motivation were expected to play the most important role.

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A study on prediction for attendances of Korean probaseball games using covariates (공변량을 이용한 한국프로야구 관중 수 예측에 대한 고찰)

  • Han, Ga-Hee;Chung, Jigyu;Yoo, Jae Keun
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.6
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    • pp.1481-1489
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    • 2014
  • For predicting yearly total attendances in Korean probaseball games, ARIMA models have been widely adopted so far. In this paper, we discuss two other ways of ARIMAX and growth curves with an exogenous variable to predict the attendances. By using the exogenous variable, it turns out that the prediction has been improved compared to ARIMA. It is concluded that various statistical methods must be considered for better prediction, and its results can be applied to predict the attendances of other pro sports.

Comparison of forecasting performance of time series models for the wholesale price of dried red peppers: focused on ARX and EGARCH

  • Lee, Hyungyoug;Hong, Seungjee;Yeo, Minsu
    • Korean Journal of Agricultural Science
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    • v.45 no.4
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    • pp.859-870
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    • 2018
  • Dried red peppers are a staple agricultural product used in Korean cuisine and as such, are an important aspect of agricultural producers' income. Correctly forecasting both their supply and demand situations and price is very important in terms of the producers' income and consumer price stability. The primary objective of this study was to compare the performance of time series forecasting models for dried red peppers in Korea. In this study, three models (an autoregressive model with exogenous variables [ARX], AR-exponential generalized autoregressive conditional heteroscedasticity [EGARCH], and ARX-EGARCH) are presented for forecasting the wholesale price of dried red peppers. As a result of the analysis, it was shown that the ARX model and ARX-EGARCH model, each of which adopt both the rolling window and the adding approach and use the agricultural cooperatives price as the exogenous variable, showed a better forecasting performance compared to the autoregressive model (AR)-EGARCH model. Based on the estimation methods and results, there was no significant difference in the accuracy of the estimation between the rolling window and adding approach. In the case of dried red peppers, there is limitation in building the price forecasting models with a market-structured approach. In this regard, estimating a forecasting model using only price data and identifying the forecast performance can be expected to complement the current pricing forecast model which relies on market shipments.

Can Religion Save Our Health?: Quasi-Experimental Evidence from the U.S.

  • PARK, YOON SOO
    • KDI Journal of Economic Policy
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    • v.40 no.1
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    • pp.31-43
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    • 2018
  • There is a large amount of empirical literature reporting that people who regularly attend religious services tend to have better health outcomes. However, it remains an unanswered question as to whether the observed correlation reflects any causality. Exploiting exogenous changes in church attendance driven by law changes in 21 states of the U.S., I find tentative but suggestive evidence that the observed strong correlation between religious participation and health is likely to be driven by endogenous selection.