6 edition of **Computational techniques for econometrics and economic analysis** found in the catalog.

- 66 Want to read
- 33 Currently reading

Published
**1994**
by Kluwer Academic Publishers in Dordrecht [Netherlands], Boston [Mass.]
.

Written in English

- Econometric models -- Data processing,
- Economics, Mathematical -- Data processing

**Edition Notes**

Includes bibliographical references and index.

Statement | edited by D. A. Belsley. |

Series | Advances in computational economics ;, v. 3 |

Contributions | Belsley, David A. |

Classifications | |
---|---|

LC Classifications | HB141 .C625 1994 |

The Physical Object | |

Pagination | ix, 238 p. : |

Number of Pages | 238 |

ID Numbers | |

Open Library | OL1409327M |

ISBN 10 | 0792323564 |

LC Control Number | 93017956 |

Quantitative Methods in Economics CONTENT Beno Rastislav Trade-Off the Accuracy for Computational Time in Approximate Solving Technique for the P-Median Problem Economy: Econometric Analysis of Nominal Wages Quantitative Methods in Economics Školuda Václav. `Review from previous edition An excellent introduction to computational methods for the study of stochastic rational expectations models. Leading researchers in the field cover the main numerical techniques currently applied in the computation of business cycle and growth models.

Contemporary economists, when analyzing economic behavior of people, need to use the diversity of research methods. Mathematical economics is the application of mathematical methods to represent theories and analyze problems in convention, these applied methods are beyond simple geometry, such as differential and integral calculus, difference and differential equations, matrix algebra, mathematical programming, and other computational methods.

Economic Theory, Econometrics, and Mathematical Economics: New Quantitative Techniques for Economic Analysis provides a critical appraisal of the results, the limits, and the developments of well-established quantitative techniques. This book presents a detailed analysis of the quantitative techniques for economic analysis. Organized into four. Agent-based computational economics (ACE) is the area of computational economics that studies economic processes, including whole economies, as dynamic systems of interacting such, it falls in the paradigm of complex adaptive systems. In corresponding agent-based models, the "agents" are "computational objects modeled as interacting according to rules" over space and time, not real.

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It is unlikely that any frontier of economics/econometrics is being pushed faster, further than that of computational techniques.

The computer has become a tool for performing as well as an environment in which to perform economics and econometrics, taking over where theory bogs down, allowingBrand: Springer Nature. It is unlikely that any frontier of economics/econometrics is being pushed faster, further than that of computational techniques.

The computer has become a tool for performing as well as an environment in which to perform economics and econometrics, taking over where theory bogs down, allowing at least approximate answers to questions that defy closed mathematical or analytical solutions.

ISBN: OCLC Number: Description: ix, pages: illustrations ; 25 cm. Contents: Pt. The Computer and Econometric Methods --Computational Aspects of Nonparametric Simulation Estimation / Ravi Bansal, A.

Ronald Gallant, Robert Hussey and George Tauchen --On the Accuracy and Efficiency Of GMM Estimators: A Monte Carlo Study / A. Hughes. This book is an important contribution to the rapidly growing literature on computational economics and finance.

It provides an extremely well-integrated presentation of dynamic economic models and some of the most effective numerical methods for solving them.

It reinforces these ideas by providing illustrative solutions written in by: Computational Economics: A Concise Introduction is ideal for economics, mathematics, computer science, and engineering majors taking classes in computational or numerical economics.

The text is designed to help students move from the traditional and comparative static analysis of economic models, to a modern and dynamic computational study.

Computational economics uses computer-based economic modelling for the solution of analytically and statistically- formulated economic problems.

A research program, to that end, is agent-based computational economics (ACE), the computational study of economic processes, including whole economies, as dynamic systems of interacting agents. [8]. The book emphasizes the unique contributions of computational methods in economics, and focuses on problems for which well developed solutions are not already available from the literature in operations research, numerical methods, and computer science.

Numerical Methods in Finance and Economics: A MATLAB®-Based Introduction, Second Edition presents basic treatments and more specialized literature, and it also uses algebraic languages, such as AMPL©, to connect the pencil-and-paper statement of an optimization model with its solution by a software s: Book February statistical and econometric methods for conducting research to find answers to puzzling issues in modern economies.

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The book provides a range of interesting examples and is Reviews: 9. Summary To harness the full power of computer technology, economists need to use a broad range of mathematical techniques.

In this book, Kenneth Judd presents techniques from the numerical analysis and applied mathematics literatures and shows how to use them in economic analyses. The book is divided into five parts. Dougherty’s Introduction to Econometrics is a good book to learn the basics, and Mastering ‘Metrics by Agrist and Pischke will guide you through slightly more advanced methods (with accompanying examples).

This book presents a variety of computational methods used to solve dynamic problems in economics and finance. It emphasizes practical numerical methods rather than mathematical proofs and focuses on techniques that apply directly to economic analyses.

The examples are drawn from a wide range of subspecialties of economics and finance, with particular emphasis on problems in agricultural and.

Develops the techniques needed to carry out computational econometrics. Features network studies, non-parametric estimation, optimization techniques, Bayesian estimation and inference, testing methods, time-series analysis, linear and nonlinear methods, VAR analysis, bootstrapping developments, signal extraction, software history and evaluation.

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We welcome contributions and collaboration from the economics community and. Computational Economics, the official journal of the Society for Computational Economics, presents new research in a rapidly growing multidisciplinary field that uses advanced computing capabilities to understand and solve complex problems from all branches in topics of Computational Economics include computational methods in econometrics like filtering.

Mathematical models and computational methods are becoming increasingly important for quantitative analysis, risk management, strategies implementation, and other areas in the finance industry.

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Textbooks and journals: Packages AER, Ecdat, and wooldridge contain a comprehensive collections of data sets from various standard econometric textbooks (including Greene, Stock & Watson, Wooldridge, Baltagi, among others) as well as several data sets from the Journal of Applied Econometrics and the Journal of Business & Economic Statistics.

Simulation in Computational Finance and Economics: Tools and Emerging Applications presents a thorough collection of works, covering several rich and highly productive areas of research including Risk Management, Agent-Based Simulation, and Payment Methods and Systems, topics that have found new motivations after the strong recession.Econometrics and Statistics is the official journal of the networks Computational and Financial Econometrics and Computational and Methodological Statistics.

It publishes research papers in all aspects of econometrics and statistics and comprises of the two sections Part A: Econometrics and Part B: Statistics. Part A: Econometrics.

Emphasis is.The two main goals of this course are: 1) to provide numerical solution methods, optimization techniques, and simulation methods and implement them using R, Python, Mathematica and/or MATLAB; and 2) to apply these tools to the domain of experimental and computational economics.