Institutional Support for Innovations in Econometric and Statistical Computation

在过去的二十年里，我们看到了计算能力的爆炸式增长，统计学和计量经济学也相应地重新定位，倾向于大量使用计算来揭示更多关于数据的信息，并使得出的推论更加清晰。统计方面的例子是稳健估计方法的发展，数据检查的图形界面，以及自举和其他重采样技术，以提高有限样本推断。计量经济学的例子是半参数方法、非线性时间序列技术和推理模拟方法的发展。将这些方法纳入计量经济学课程和应用计量经济学软件的情况并不均衡，特别是主要在统计学中开发的方法。该基金支持统计计算和计量经济学应用的研究和教学会议，以解决这一问题。本项目下计划的活动促进在计量经济学中使用目前的统计方法和UNIX工作站软件，鼓励使用许多标准计量经济学程序所需的程序和模块来扩充统计软件系统（例如S语言）；使统计学家熟悉计量经济学应用中出现的一些方法和计算问题，并鼓励共同开发计算方法。计划召开三次研究会议，每年召开一次。这些会议讨论统计和计量经济学中计算机密集型方法的当前问题。将举行三次教学会议，每年一次。这些会议旨在为全国各地经济和统计部门提名的研究生团体提供统计计算方法和问题的深入介绍。这些活动的协调是为了实现以下目标：(1)提供一个统计计算环境，该环境集成了统计和计量经济学软件，并提供文档和教程，以鼓励计量经济学和统计学教师和研究生更有效地使用现有软件；(2)确定统计算法研究和开发的生产领域，并提出计量经济学软件的标准；(3)鼓励在“开放”软件中实施新算法；(4)为计量经济学研究界提供建立和运行用于研究和教学的统计计算环境的“如何”材料。以及计量软件标准。

The last two decades have seen an explosion in computational capacity, and a corresponding reorientation of statistics and econometrics toward making intensive use of computation to reveal more about data and sharpen the inferences drawn. Statistical examples are the development of robust estimation methods, graphical interfaces for data examination, and bootstrap and other resampling techniques to sharpen finite-sample inferences. Econometrics examples are the development of semiparametric methods, nonlinear time series techniques, and simulation methods for inference. Incorporation of these methods into econometrics courses and applied econometrics software has been uneven, particularly for methods developed primarily in statistics. This grant supports research and teaching conferences on statistical computation and econometric applications in order to address this problem. The activities planned under this project promote the use of current statistical methods and UNIX workstation software in econometrics, encourage the augmentation of statistical software systems (such as the S language) with the procedures and modules needed for many standard econometric procedures, familiarize statisticians with some of the methodological and computational problems encouraged in econometrics applications, and encourage joint developments of computational methods. Three research conferences are planned, one in each year of the proposal. The conferences deal with current issues in computer- intensive methods in statistics and econometrics. Three teaching conferences will be held, again one in each year. These conferences are designed to provide an intensive introduction in methods and issues in statistical computation to groups of graduate students nominated by Departments of Economics and Statistics around the country. These activities are coordinated to achieve the objectives of (1) providing a statistical computing environment that integrates statistical and econometric software, with documentation and tutorials that encourage more effective use of existing software by econometrics and statistics faculty and graduate students, (2) identifying productive areas for research and development on statistical algorithms, and suggesting standards for econometric software, (3) encouraging the implementation of new algorithms in "open look" software, and (4) providing "how to" materials to the econometric research community on setting up and operating a statistical computing environment for research and teaching, and on econometric software standards.