Sarkodie Samuel Asumadu, Owusu Phebe Asantewaa
Nord University Business School (HHN), Post Box 1490, 8049 Bodø, Norway.
MethodsX. 2020 Nov 27;7:101160. doi: 10.1016/j.mex.2020.101160. eCollection 2020.
The application of dynamic Autoregressive Distributed Lag (dynardl) simulations and Kernel-based Regularized Least Squares (krls) to time series data is gradually gaining recognition in energy, environmental and health economics. The Kernel-based Regularized Least Squares technique is a simplified machine learning-based algorithm with strength in its interpretation and accounting for heterogeneity, additivity and nonlinear effects. The novel dynamic ARDL Simulations algorithm is useful for testing cointegration, long and short-run equilibrium relationships in both levels and differences. Advantageously, the novel dynamic ARDL Simulations has visualization interface to examine the possible counterfactual change in the desired variable based on the notion of . Thus, the novel dynamic ARDL Simulations and Kernel-based Regularized Least Squares techniques are useful and improved time series techniques for policy formulation.•We customize ARDL and dynamic simulated ARDL by adding plot estimates with confidence intervals.•A step-by-step procedure of applying ARDL, dynamic ARDL Simulations and Kernel-based Regularized Least Squares is provided.•All techniques are applied to examine the economic effect of denuclearization in Switzerland by 2034.
动态自回归分布滞后（dynardl）模拟和基于核的正则化最小二乘法（krls）在时间序列数据中的应用在能源、环境和健康经济学领域正逐渐得到认可。基于核的正则化最小二乘技术是一种简化的基于机器学习的算法，在解释以及考虑异质性、可加性和非线性效应方面具有优势。新颖的动态自回归分布滞后模拟算法可用于检验协整、水平和差分形式下的长期和短期均衡关系。有利的是，新颖的动态自回归分布滞后模拟具有可视化界面，可基于……概念来检验所需变量可能的反事实变化。因此，新颖的动态自回归分布滞后模拟和基于核的正则化最小二乘技术是用于政策制定的有用且经过改进的时间序列技术。
•我们通过添加带置信区间的绘图估计来定制自回归分布滞后模型和动态模拟自回归分布滞后模型。
•提供了应用自回归分布滞后模型、动态自回归分布滞后模拟和基于核的正则化最小二乘法的分步程序。
•所有技术都用于检验到2034年瑞士无核化的经济影响。
