Research into Spurious Stochastics in Panels, Generalized Forecast Theory and Evaluation of Models

这是一个基于成就的续订项目。这个项目的目标是在评估经验模型或经济理论方面带来一些新的想法；尽管将使用两个已建立的基础。第一种方法来自面板分析，讨论了在动态面板模型规范中出现“伪随机性”的可能性，使用的数据来自大小差异很大但尺寸效应没有正确建模的区域。大小本身可能是缓慢演变的，因此不能通过使用固定效果来捕捉。初步模拟表明，这可能是一个重要的问题。随之而来的是如何评估面板模型，从而如何比较模型。第二块是考虑一般的预测理论，具有一般的成本t函数，并强调预测分布函数。出现了对预测误差的新测试，并根据自己的目标和知识更好地认识到要使用的适当建模策略。目前可用的大多数评价方法，如适合性、规格的正确性和包容性的衡量，都是统计衡量。有人会争辩说，更好的方法是考虑新模型或理论对经济的价值，或者至少考虑它对决策者的帮助。这是金融领域已经采用的方法，可以在预测中得到更广泛的应用。本文将探讨和分析这一观点的含义。

This is an accomplishment based renewal project. The goal of this project is to bring some fresh thoughts on the evaluation of empirical models or to economic theories; although two established building blocks will be used. The first comes from panel analysis and discusses the possibility of `spurious stochastics` occurring in a dynamic panel model specification, using data from regions that differ greatly in size, but where the size effect is not properly modeled. Size itself may be slowly evolving and so not be captured by the use of fixed effects. Initial simulations suggest that this is potentially an important problem. One that follows from it is how to evaluate panel models, and thus how to compare models. The second block is consideration of a general theory of forecasting, with general cost t functions and an emphasis on predictive distribution functions. New tests for forecast errors arise and a better appreciation of the appropriate modeling strategy to use depending on ones objective and knowledge. The majority of the currently available methods of evaluation, such as measures of goodness of fit, correctness of specification and encompassing, are statistical measures. It will be argued that a better approach considers the value to the economy of a new model or theory, or at least the aid it gives to decision makers. This is the approach is already taken in finance and it could be more widely used in forecasting. The implications of this viewpoint will be explored and analyzed