A Toolkit for Endogenous Regime-Switching model Estimation

该提案旨在开发一个工具包，以便有效估计和使用广泛的最新技术水平的时间序列模型进行政策分析和预测。模型允许变量之间的关系，并随着时间的推移，在一个国家依赖的方式演变是必不可少的分析时间序列，偶尔约束。它们的复杂性和计算强度为大多数潜在用户，包括学者和政策制定者，创造了一个巨大的进入障碍。主要的问题是，这些模型（的未知参数）的估计目前依赖于大量的蒙特卡罗模拟，难以有效地并行化，导致非常长的计算时间。因此，毫不奇怪，大多数研究人员和政策分析师仍然依赖于科学上不合理的解决方案，导致潜在的偏见预测和误导性的政策处方。我们建议通过提供一种新的方法来准确和有效地估计这些模型，并通过开发一个工具包，在用户友好的环境中实现新的方法来解决这个问题。这种方法在统计和计算上都比现有的替代方案更有效：它可以很容易地并行化，并提供准确的估计数量级更短的计算时间。该提案还旨在利用云计算的可用性和可访问性，其规模在这一领域以前从未有过。为了启动这一想法的商业化，我们将建立一个先进的原型，并与早期采用者合作，测试原型，为更广泛的市场做好准备。我们还将开展一系列与商业相关的活动，以确定商业化的最佳途径。该项目的成果将是先进的原型，分析我们的技术的竞争方面，并就其路线走向市场的战略。

This proposal aims at developing a Toolkit for efficient estimation and use of a broad class ofstate-of-the-art time-series models for policy analysis and forecasting. Models that allowrelationships between variables and over time to evolve in a state-dependent fashion areessential for analysing time series that are subject to occasionally binding constraints. Theircomplexity and computational intensity create a significant barrier to entry for most potentialusers, including academics and policy makers. The main problem is that the estimation of (theunknown parameters of) these models currently relies on vast amounts of Monte Carlosimulations that are difficult to parallelize efficiently, resulting in exceedingly long computationaltimes. It is, therefore, unsurprising that most researchers and policy analysts still rely onscientifically unjustified solutions, leading to potentially biased forecasts and misleading policyprescriptions. We propose to address this problem by providing a novel method for theaccurate and efficient estimation of those models and by developing a Toolkit that implementsthe new method in a user-friendly environment. This method is both statistically andcomputationally more efficient than existing alternatives: it can be readily parallelized andprovides accurate estimates with orders of magnitude shorter computational times. Theproposal also aims to leverage the availability and accessibility of cloud computing at a scalethat has not been done before in this area. To initiate the commercialisation of the idea, we willbuild an advanced prototype and work with early adopters to test the prototype and prepare itfor the broader market. We will also perform a range of business-related activities to identifythe best route for commercialization. The project outcomes will be the advanced prototype, ananalysis of the competitive aspects of our technology, and a strategy regarding its route tomarket.