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On Structural Breaks and Nonstationary Fractional Intergration in Time Series

机译：时间序列中的结构破坏和非平稳分数积分

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The growth of an economy is determined largely by the growth of its Gross Domestic Product (GDP) over time. However, GDP and some economic series are characterized by nonstationarity, structural breaks and outliers. Many attempts have been made to analyze these economic series assuming unit root process even in the presence of changes in the mean level without considering possible fractional integration. This paper aims at examining the structural breaks and nonstationarity in the GDP series of some selected African countries with a view to determining the influence of structural breaks on the level of stationarity of these series. These series are found to be nonstationary with some evidence of long memory. They were found to experience one or more breaks over the years and this may be due to instability in the government and economic policies in the selected African countries. The measure of relative efficiency shows that autoregressive fractional integrated moving average (ARFIMA) models is better than the corresponding autoregressive integrated moving average (ARIMA) models for the series considered in this study.
机译：经济的增长在很大程度上取决于其国内生产总值（GDP）随时间的增长。但是，GDP和某些经济系列的特点是不稳定，结构中断和离群值。已经进行了许多尝试来分析这些经济序列，即使在平均水平发生变化的情况下，也假设单位根过程，而没有考虑可能的分数积分。本文旨在研究某些选定非洲国家GDP序列中的结构性断裂和非平稳性，以确定结构性断裂对这些序列的平稳性水平的影响。这些系列被发现是不稳定的，有一些长记忆的证据。他们发现这些年来经历了一次或多次休息，这可能是由于所选非洲国家的政府和经济政策不稳定所致。相对效率的度量表明，对于本研究中考虑的序列，自回归分数积分移动平均值（ARFIMA）模型优于相应的自回归积分移动平均值（ARIMA）模型。

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