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Testing Goodwin with a stochastic differential approach-The United States (1948-2019)

机译：用随机差动方法 - 美国（1948-2019）测试Goodwin（1948-2019）

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摘要

This paper follows Harvie and Grasselli and Maheshwari's research program in testing both Goodwin's predator-prey model and the extension proposed by van der Ploeg. The aim of this paper is to provide a guideline for the bloc estimation and the backtesting strategy that can be applied to such a class of continuous-time non-linear macroeconomic models. The goal of this paper is to propose and test stochastic differential equations for Goodwin's model and one of its extensions by an estimation technique based on simulated maximum likelihood developed by Durham and Gallant. The data considered here are that of wage share and employment rate in the United States from 1948:Q1 to 2019:Q4. Results show that two structural breaks-at the beginning of the 80s' and late 90s'-are likely to have occurred and the Goodwin-type model endowed with Leontief production technology explains more accurately the data than the van der Ploeg's CES production function. These results are partly confirmed by a backtesting strategy, which highlights the predicting property of the van der Ploeg-like model on a purely statistical VAR model. Both the estimation and backtesting strategies can be used to assess the empirical improvement on any extensions of the models investigated in this paper.
机译：本文遵循Harvie和Grasselli和Maheshwari在测试Goodwin的捕食者 - 猎物模型和Van der Ploeg提出的延伸方面的研究计划。本文的目的是提供集团估计的指导和可应用于这种连续时间非线性宏观经济模型的反向策略。本文的目的是提出和通过基于Durham和Gallant开发的模拟最大可能性，通过估计技术提出和测试Goodwin模型的随机微分方程和其延伸。这里考虑的数据来自美国1948年的工资份额和就业率：Q1至2019：Q4。结果表明，在80年代初期和90年代初的两个结构突破，并且赋予了利用生产技术的商业型模型更准确地解释了比范德普尔格的CES生产功能更准确地解释了数据。这些结果部分通过反向策略部分证实，其突出了普通统计VAR模型上VAN DEL PLOEG型模型的预测性质。估计和反垄断策略都可用于评估本文调查的模型的任何扩展的实证改进。

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