Abifarin Modupe O., Isah Audu, Yakubu Yisa, Adeyemi Rasheed A.
{"title":"存在爆发力时的稳定纠错机制","authors":"Abifarin Modupe O., Isah Audu, Yakubu Yisa, Adeyemi Rasheed A.","doi":"10.9734/ajpas/2024/v26i1584","DOIUrl":null,"url":null,"abstract":"In the presence of explosiveness of the adjustment term in the error correction model, the adjustment of the dependent variable Y was too large and overshoots the equilibrium, creating a divergent pattern. The error correction model fails to capture the deviation from equilibrium appropriately, thereby resulting in overshooting of the model. In this paper, a new model to stabilize the explosiveness in an Error Correction model called the stabilizing Error Correction Mechanism was proposed. Mathematical methodology for obtaining the estimate of the model using the Ordinal Least Square method was derived. Error Correction model was used to model the relationship among the variables and the result was compared with the Stabilizing Error Correction Mechanism using root mean square error. A Monte-Carlo simulation was performed, and the stimulation results showed that the error correction model exhibited some explosiveness, and the damping coefficient of the stabilizing model exerted a stabilizing effect on the error correction mechanism, thereby reducing the overshooting in the error correction model. The proposed model contributed to a smoother and more stable response to deviations from the long-run equilibrium. The root mean square error of the stabilizing Error Correction model was observed to be 1.30663, 1.04533, 12.55786, 10.49876, 10.0034, and 19.41545 as compared to the adjustment model in the Error Correction model (60.6888, 35.5929, 315238, 24.31958, 10.1485 and 19.7687) when the persistence is high and . Therefore, the Stabilizing Error Correction model performs better than the Error Correction model.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":"21 4","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Stabilizing Error Correction Mechanism in the Presence of Explosiveness\",\"authors\":\"Abifarin Modupe O., Isah Audu, Yakubu Yisa, Adeyemi Rasheed A.\",\"doi\":\"10.9734/ajpas/2024/v26i1584\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the presence of explosiveness of the adjustment term in the error correction model, the adjustment of the dependent variable Y was too large and overshoots the equilibrium, creating a divergent pattern. The error correction model fails to capture the deviation from equilibrium appropriately, thereby resulting in overshooting of the model. In this paper, a new model to stabilize the explosiveness in an Error Correction model called the stabilizing Error Correction Mechanism was proposed. Mathematical methodology for obtaining the estimate of the model using the Ordinal Least Square method was derived. Error Correction model was used to model the relationship among the variables and the result was compared with the Stabilizing Error Correction Mechanism using root mean square error. A Monte-Carlo simulation was performed, and the stimulation results showed that the error correction model exhibited some explosiveness, and the damping coefficient of the stabilizing model exerted a stabilizing effect on the error correction mechanism, thereby reducing the overshooting in the error correction model. The proposed model contributed to a smoother and more stable response to deviations from the long-run equilibrium. The root mean square error of the stabilizing Error Correction model was observed to be 1.30663, 1.04533, 12.55786, 10.49876, 10.0034, and 19.41545 as compared to the adjustment model in the Error Correction model (60.6888, 35.5929, 315238, 24.31958, 10.1485 and 19.7687) when the persistence is high and . Therefore, the Stabilizing Error Correction model performs better than the Error Correction model.\",\"PeriodicalId\":8532,\"journal\":{\"name\":\"Asian Journal of Probability and Statistics\",\"volume\":\"21 4\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Asian Journal of Probability and Statistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.9734/ajpas/2024/v26i1584\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Asian Journal of Probability and Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.9734/ajpas/2024/v26i1584","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
在误差修正模型中调整项存在爆炸性的情况下,因变量 Y 的调整幅度过大,超调了均衡状态,形成了背离模式。误差修正模型未能适当捕捉到均衡的偏离,从而导致模型的超调。本文提出了一种在误差修正模型中稳定爆炸性的新模型,称为稳定误差修正机制。并推导出了使用正序最小平方法获得模型估计值的数学方法。使用误差修正模型来模拟变量之间的关系,并使用均方根误差将结果与稳定误差修正机制进行比较。蒙特卡洛模拟结果表明,误差修正模型具有一定的爆炸性,而稳定模型的阻尼系数对误差修正机制起到了稳定作用,从而减少了误差修正模型中的过冲现象。所提出的模型有助于对偏离长期均衡做出更平滑、更稳定的反应。与误差修正模型中的调整模型(60.6888、35.5929、315238、24.31958、10.1485 和 19.7687)相比,稳定误差修正模型的均方根误差在持续性较高时分别为 1.30663、1.04533、12.55786、10.49876、10.0034 和 19.41545。因此,稳定误差修正模型优于误差修正模型。
Stabilizing Error Correction Mechanism in the Presence of Explosiveness
In the presence of explosiveness of the adjustment term in the error correction model, the adjustment of the dependent variable Y was too large and overshoots the equilibrium, creating a divergent pattern. The error correction model fails to capture the deviation from equilibrium appropriately, thereby resulting in overshooting of the model. In this paper, a new model to stabilize the explosiveness in an Error Correction model called the stabilizing Error Correction Mechanism was proposed. Mathematical methodology for obtaining the estimate of the model using the Ordinal Least Square method was derived. Error Correction model was used to model the relationship among the variables and the result was compared with the Stabilizing Error Correction Mechanism using root mean square error. A Monte-Carlo simulation was performed, and the stimulation results showed that the error correction model exhibited some explosiveness, and the damping coefficient of the stabilizing model exerted a stabilizing effect on the error correction mechanism, thereby reducing the overshooting in the error correction model. The proposed model contributed to a smoother and more stable response to deviations from the long-run equilibrium. The root mean square error of the stabilizing Error Correction model was observed to be 1.30663, 1.04533, 12.55786, 10.49876, 10.0034, and 19.41545 as compared to the adjustment model in the Error Correction model (60.6888, 35.5929, 315238, 24.31958, 10.1485 and 19.7687) when the persistence is high and . Therefore, the Stabilizing Error Correction model performs better than the Error Correction model.