Introduction to Python for Econometrics, Statistics and Numerical Analysis
by Kevin Sheppard
Number of pages: 281
Python is a widely used general purpose programming language, which happens to be well suited to Econometrics and other more general purpose data analysis tasks. These notes provide an introduction to Python for a beginning programmer. They may also be useful for an experienced Python programmer interested in using NumPy, SciPy, and matplotlib for numerical and statistical analaysis.
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by Kenneth Train - Cambridge University Press
The book describes the new generation of discrete choice methods, focusing on the advances that are made possible by simulation. Researchers use these methods to examine the choices that consumers, households, firms, and other agents make.
by William H. Miernyk - Random House Inc
This volume is designed to give the reader an understanding of how the input-output system works; it is not a guide to the construction of an interindustry transactions table. Most of this book deals with a static, open input-output model.
by Harold T. Davis - The Principia Press
The object of this book is to set forth the present status of the problem of analyzing that very extensive set of data known as economic time series. This perplexing problem has engaged the attention of economists and statisticians for many years.
by Thomas J. Rothenberg - Yale University Press
This book presents an attempt at unifying certain aspects of econometric theory by embedding them in a more general statistical framework. The unifying feature is the use of a priori information and the basic tool is the Cramer-Rao inequality.