We consider a class of infinite‐horizon dynamic Markov economic models in which the parameters of utility function, production function, and transition equations change over time. In such models, the optimal value and decision functions are time‐inhomogeneous: they depend not only on state but also on time. We propose a quantitative framework, called extended function path (EFP), for calibrating, solving, simulating, and estimating such nonstationary Markov models. The EFP framework relies on the turnpike theorem which implies that the finite‐horizon solutions asymptotically converge to the infinite‐horizon solutions if the time horizon is sufficiently large. The EFP applications include unbalanced stochastic growth models, the entry into and exit from a monetary union, information news, anticipated policy regime switches, deterministic seasonals, among others. Examples of MATLAB code are provided.

中文翻译：

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分析一类非平稳马尔可夫模型的易处理框架

我们考虑一类无限水平动态马尔可夫经济模型，其中效用函数，生产函数和转移方程的参数随时间变化。在这样的模型中，最优值和决策函数在时间上是不均匀的：它们不仅取决于状态，还取决于时间。我们提出了一个定量框架，称为扩展功能路径（EFP），用于校准，求解，仿真和估计此类非平稳Markov模型。EFP框架依赖收费公路定理，这意味着如果时间范围足够长，则有限水平解渐近收敛于无限水平解。EFP应用程序包括不平衡的随机增长模型，进入和退出货币联盟，信息新闻，预期的政策体制转换，确定性的季节等等。提供了MATLAB代码示例。