利用koyck类的ARMAX模型考察尼日利亚的偿债机制

IF 0.7 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE
U. Virtue, David E. Omoregie
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引用次数: 3

摘要

外债负担使经济容易受到外部冲击并排挤投资,从而影响一个经济体(或一个国家)的福祉。在处理像尼日利亚这样负债累累的穷国的债务管理问题时,合理的做法是将一部分出口收入用于偿还债务。在这方面,有必要确定偿债与出口收入之间的联系。因此,在koyck类自回归移动平均解释输入模型(KARMAX)的框架内,出口收入对偿债支付的当前和长期影响被建模为单投入-单产出的离散时间动力系统。利用世界银行数据库1970年至2018年的数据,基于最大似然(ML)方法确定了尼日利亚的KARMAX模型,并将所得结果与预测误差和工具变量方法进行了比较。从理论的角度来看,ML方法确定的KARMAX规范更加理想和鼓舞人心。通过这样做,本文有助于公共债务管理的计量经济学文献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Inspecting debt servicing mechanism in Nigeria using ARMAX model of the Koyck-kind
The burden of external debt affects the wellbeing of an economy (or a country) by making the economy vulnerable to external shocks and crowding out investment. When dealing with debt management in indebted poor countries like Nigeria, the rational approach is to allocate a portion of export earnings for debt service payments. Along this line, there is a need to identify the link between debt servicing and export earnings. Hence, the current and long-run effects of export earnings on debt service payments is modelled as a single-input-single-output discrete-time dynamical system within the framework of Autoregressive Moving Average Explanatory Input model of the Koyck-kind (KARMAX). The KARMAX model is identified for Nigeria, using data from the World Bank database from 1970 to 2018 based on the maximum likelihood (ML) method, and the obtained results are compared to the prediction error and the instrumental variable methods. From a theoretical perspective, the KARMAX specification identified by the ML method is more ideal and inspiring. By doing so, this article contributes to the literature on the econometrics of public debt management.
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来源期刊
Operations Research and Decisions
Operations Research and Decisions OPERATIONS RESEARCH & MANAGEMENT SCIENCE-
CiteScore
1.00
自引率
25.00%
发文量
16
审稿时长
15 weeks
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