三种非线性计量经济学方法在秘鲁识别商业周期的应用

G. Rodríguez
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引用次数: 3

摘要

我使用三个非线性计量经济模型来识别和分析秘鲁经济在1980:1-2008:4期间的商业周期。这些模型分别是Terasvirta(1994)提出的平滑过渡自回归(STAR)模型、Hamilton(1989)提出的马尔可夫切换模型的扩展版和Friedman(1964,1993)的拔拔模型。结果表明强烈拒绝线性的零假设。大多数模型将集中在1988-1989年和1990-1991年的季度确定为衰退时期。秘鲁经济中发生的其他重要事件(1983年的自然灾害,1990年代亚洲和俄罗斯危机的影响,1980年代的恐怖主义活动)除了作为非典型观察外,没有选择。大多数模型还将1995:1-2008:4时期确定为中高增长率的非常长且稳定的时期。从秘鲁经济史的角度和统计学角度来看,MSIAH(3)模型是首选模型。
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Application of Three Non-Linear Econometric Approaches to Identify Business Cycles in Peru
I use three non-linear econometric models to identify and analyze business cycles in the Peruvian economy for the period 1980:1-2008:4. The models are the Smooth Transition Autoregressive (STAR) model suggested by Terasvirta (1994), the extended version of the MarkovSwitching model proposed by Hamilton (1989), and the plucking model of Friedman (1964, 1993). The results indicate strong rejection of the null hypothesis of linearity. The majority of models identify quarters concentrated around 1988-1989 and 1990-1991 as recession times. Other important events which happened in the Peruvian economy (natural disaster in 1983, effects of the Asian and Russian crises in 1990s, terrorist activities in 1980s) are not selected except as atypical observations. Most of models also identify the period 1995:1-2008:4 as a very long and stable period of moderate-high growth rates. From the perspective of the Peruvian economic history and from a statistical point of view, the MSIAH(3) model is the preferred model.
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