Computational Economics: Help for the Underestimated Undergraduate

Our concern in this paper is that the capability of economics undergraduates is substantially underestimated in the design of the present college curriculum and that our students are insufficiently challenged and motivated. Students enter our classrooms with substantial previous knowledge about computers and computation and we are not taking full advantage of this opportunity. We suggest a set of examples from computational economics which are challenging enough to motivate students and simple enough that they can master them within a few hours. By encouraging the students to modify the models in directions of their own interest, avenues for creative endeavor are opened which deeply involve the students in their own education.     

Teaching Computational Economics to Graduate Students

The teaching of computational economics to graduate students has mostly been in a single course with a focus on algorithms and computer code. The shortcoming with this approach is that it neglects one of the most important aspects of computational economics—namely model development skills. These skills are the ability to conceptualize the science, engineering and economics of a problem and to convert that understanding first to a mathematical model and then to a computational representation in a software system. Thus we recommend that a two course sequence in computational economics be created for graduate students with the first course focusing on model development skills and the second course on algorithms and the speed and accuracy of computer codes. We believe that a model development course is most helpful to graduate students when it introduces the students to a wide variety of computational models created by past generations and ask them to first make small modification in order to better understand the models, the mathematics and the software. This in turn is followed by encouraging them to make more substantial modifications of the students’ own choosing so as to move the models in directions that permit the students to address current economic problems. We think that the key element of this process is it’s enhancement of the creative abilities of our students.      

Mathematica as an Environment for Doing Economics and Econometrics

Today's graduate students in economics must master early on a computational environment suitable for their research needs. A case is made here why Mathematica is an eminently reasonable choice for this purpose for many students. Salient features of Mathematica are examined in this context, and the breadth of economic research accomplished in Mathematica is illustrated.     

Green Tax Reforms and Computational Economics A Do-it-yourself Approach

The double or even triple dividend hypothesis of green tax reforms has beena major issue of dispute in both the scientific community and the politicalarena during the last decade. Theoretical analysis has provided a number ofimportant qualitative insights to the debate but lacks of actual policyrelevance due to very restrictive assumptions. Applied research that takes thestep from stylized analytical to complex numerical models usually comes as ablackbox to non-expert modelers. This paper aims at bridging the gap betweenstylized theoretical work and numerical analysis. We develop a flexible,interactive simulation model which is accessible underhttp://brw.zew.de. Users can specify their own green tax reforms andevaluate the induced economic and environmental effects. Based on illustrativesimulations, we demonstrate the usefulness of our do-it-yourself approach fora better understanding of the double (triple) dividend hypothesis.     

Programming Languages in Economics

Young economists sometimes ask which computer programming languages they should learn. This paper answers that question by suggesting that they begin with a high level language like GAUSS, GAMS, Mathematica, Maple or MATLAB depending on their field of specialization in economics. Then they should work down to one of the low level languages such as Fortran, Basic, C, C++ or Java depending on the planned areas of application. Finally, they should proceed to the languages which are used to develop graphical interfaces and internet applications, viz. Visual Basic, C, C++ or Java.     

Teaching Macroeconomics with GAMS

Our general goal in this paper is to show how to implement in GAMS standard deterministic nonlinear macro models, and stochastic linear macro models with rational expectations. We will also present basic concepts on solution methods and policy analysis for these kinds of models. As a practical illustration, we will use some well known teaching and experimental models in the macroeconomic literature.     

A Critical Guide to Empirical Validation of Agent-Based Models in Economics: Methodologies,Procedures, and Open Problems

This paper addresses the methodological problems of empirical validation in agent-based (AB) models in economics and how these are currently being tackled. We first identify a set of issues that are common to all modelers engaged in empirical validation. We then propose a novel taxonomy, which captures the relevant dimensions along which AB economics models differ. We argue that these dimensions affect the way in which empirical validation is carried out by AB modelers and we critically discuss the main alternative approaches to empirical validation being developed in AB economics. We conclude by focusing on a set of (as yet) unresolved issues for empirical validation that require future research.      

EXCEL在《计算方法》教学中的应用

该文通过龙贝格（Romberg）求积问题实例,介绍了本人在《计算方法》教学过程中,如何借助EXCEL,方便、直观、高效地解答习题,由此提高教学效果,增加学生学习兴趣。     

基于经济模型的计算网格资源分配

提出了一种基于市场的计算网格资源分配框架,在这个模型中,用效用函数刻画用户对网格服务的满意程度,将计算网格资源分配问题转化为在传统的考虑负载平衡的基础上,求最大化所有用户的效用和,并给出了分布式、可扩展的算法。     

EXCEL在《计算方法》教学中的应用

该文通过龙贝格(Romberg)求积问题实例,介绍了本人在《计算方法》教学过程中,如何借助EXCEL,方便、直观、高效地解答习题,由此提高教学效果,增加学生学习兴趣。     

财经院校程序设计类课程教学改革与实践

目前国内财经院校都会为学生开设至少一门程序设计类课程。基于财经类专业学生惯常的思维方式及学习方法,多数学生会在学习过程中感到非常困难。文中将详细分析财经院校中学生的特点,结合近几年来的教学实践经验,针对现有程序设计类课程教学模式下产生的问题,提出更有效的教学模式及教学对策。     

可计算函数的程序理解方法

为满足大规模软件开发的需要,自动化成为软件工程迫切的要求,并贯彻到软件设计、开发和维护的各个阶段.提出一种以可计算函数为基础的程序理解方法,最大程度地识别函数功能、验证组件安全属性,实现对二进制代码的理解,以精简的函数表达式和并发赋值形式展示函数理解结果,提高人工阅读程序的效率.实验表明生成并发赋值语句的数量、时间与软件代码大小成线性关系,并得出了经验公式.     

变电站增容改造方案

针对一区主变不能适应公司发展要求的问题,提出变电所增容改造方案.     

计算思维和程序设计能力的培养

随着信息化技术的发展加快,如何提高计算机人才的程序设计和开发能力显得尤为重要。本文从算法的一题多解入手,探讨对学生计算思维能力的培养。这一方法对培养学生学习兴趣和提高其程序设计及编程实践能力起到了极大的促进作用。采用这个方法进行教学,能达到理想的教学效果。     

Models and Methods of Finite-Dimensional Variational Inequalities

Algorithms for solving finite-dimensional inequalities are studied. The emphasis is on numerical methods based on the optimization approach. Examples of economic equilibrium models that assist in solving variational inequalities are presented.     

Computational experience with the constrained minimum variance input-output estimator

The numerical algorithm for the off-line design of the constrained minimum variance input-output estimator has been verified on a series of sample problems. While it has been found to work in the vast majority of practical cases, some computationally weak points have also been identified.     

Computational methods for option replication

A computational method is described for option replication. In particular, a procedure is provided for computing the projection basis that corresponds to a positive basis of ? ^m . Application of this procedure in order to compute maximal submarkets that replicate any option is demonstrated. Specifically, we provide a computational study for the replication of options in security markets with a finite number of states and a finite number of primitive assets with payoffs given by linearly independent vectors of ? ^m . The theoretical background of this work follows the results in Polyrakis and Xanthos [Maximal submarkets that replicate any option, Ann. Finance, DOI: 10.1007/s10436-009-0143-9]. Our goal is to make option replication computationally tractable and hence more viable as a financial tool.     

可重构的光总线并行计算模型及其算法

介绍几种典型可重构光总线并行计算模型及其高效的基本操作与并行算法,使人们更加了解光总线并行计算模型及优越性,为今后进一步研究光总线模型及其并行算法奠定基础。     

Towards an RCC-Based Accelerator for Computational Fluid Dynamics Applications

Computational Fluid Dynamics (CFD) applications are a critical tool in designing sophisticated mechanical systems such as jet engines and gas turbines. CFD applications use intensive floating-point calculations and are typically run on High-Performance Computing (HPC) systems. We analyze three of the most compute intensive functions (Euler, Viscous, and Smoothing algorithms) and develop a baseline system architecture for accelerating these functions in RCC hardware. We then present detailed design data for the most compute intensive (Euler) function. Based on this analysis, we show that an RCC-based CFD accelerator—compared to conventional processors—promises dramatic improvement in sustained compute speed at better price-performance ratios coupled with much lower overall power consumption.     

融入“计算思维”的计算机硬件类课程改革

针对大学计算机硬件类课程的教学实际,分析计算机硬件类课程和计算思维的内在关系。从整合教学内容、改革教学方法和考核评价模式三方面着手,阐述在计算机硬件类课程中贯穿计算思维能力的可行性,为深化课堂教学改革提供了新的思路。从近年学生的考核成绩看出,取得了良好的教学效果。