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

这是一个基于成就的更新项目。 这个项目的目标是带来一些新的想法的经验模型的评估或经济理论，虽然两个既定的积木将被使用。 第一个来自面板分析，并讨论了“虚假的随机”发生在一个动态面板模型规格的可能性，使用的数据，从地区，在大小上有很大的不同，但规模效应没有正确建模。 规模本身可能是缓慢演变的，因此不能通过使用固定效应来捕获。 初步模拟表明，这可能是一个重要的问题。 由此而来的一个问题是如何评估面板模型，从而如何比较模型。 第二块是考虑预测的一般理论，一般成本t函数和预测分布函数的重点。 出现了针对预测误差的新测试，并且可以根据目标和知识更好地了解要使用的适当建模策略。 目前可用的大多数评价方法，如拟合优度、规范正确性和包容性的测量，都是统计测量。 有人认为，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，它可以更广泛地用于预测。 这一观点的含义将被探讨和分析

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