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首页> 外文期刊>Economic inquiry >CHARACTERIZING ECONOMIC GROWTH PATHS BASED ON NEW STRUCTURAL CHANGE TESTS
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CHARACTERIZING ECONOMIC GROWTH PATHS BASED ON NEW STRUCTURAL CHANGE TESTS

机译:基于新的结构变化测试表征经济增长路径

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摘要

One of the prevalent topics in the economic growth literature is the debate between neoclassical, semi-endogenous, and endogenous growth theories regarding the model that best describes the data. An important part of this discussion can be summarized in three mutually exclusive hypotheses: the "constant trend," the "level shift," and the "slope shift" hypotheses. In this article we propose the characterization of a country's economic growth path according to these break hypotheses. We address the problem in two steps. First, the number and timing of trend breaks is determined using new structural change tests that are robust to the presence, or not, of unit roots, surpassing technical and methodological concerns of previous empirical studies. Second, conditional on the estimated number of breaks and break dates, a statistical framework is introduced to test for general linear restrictions on the coefficients of the suggested linear disjoint broken trend model. We further show how the aforementioned hypotheses, regarding the economic growth path, can be analyzed by a test of linear restrictions on the parameters of the breaking trend model. We apply the methodology to historical per capita gross domestic product for an extensive list of countries. The results support the three alternative hypotheses for different sets of countries. (JEL C22, F43, O40)
机译:经济增长文献中最普遍的话题之一是新古典主义,半内生性和内生性增长理论之间关于最能描述数据的模型的争论。该讨论的重要部分可以归纳为三个相互排斥的假设:“恒定趋势”,“水平移动”和“坡度移动”假设。在本文中,我们根据这些突破性假设提出了一个国家经济增长路径的特征。我们分两步解决这个问题。首先,使用新的结构变化测试来确定趋势突破的次数和时机,这些测试对单元根的存在与否具有鲁棒性,超过了先前经验研究的技术和方法论关注。其次,以估计的中断次数和中断日期为条件,引入统计框架来测试对建议的线性不相交的中断趋势模型的系数的一般线性限制。我们进一步展示了如何通过对突破趋势模型的参数进行线性限制的检验来分析关于经济增长路径的上述假设。我们将该方法应用于许多国家的历史人均国内生产总值。结果支持针对不同国家集的三个替代假设。 (JEL C22,F43,O40)

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  • 来源
    《Economic inquiry》 |2014年第2期|845-861|共17页
  • 作者单位

    Insper, Rua Quata, 04546-042 Sao Paulo, Brazil;

    Nova School of Business and Economics-INOVA, Universidade Nova de Lisboa, 1099-032 Lisbon, Portugal;

    Banco de Portugal, Nova School of Business and Economics and CEFAGE, 1099-032 Lisbon, Portugal;

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