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 Michael Creel - Universitat Autonoma de Barcelona
Textbook for graduate econometrics, it teaches ordinary least squares, maximum likelihood estimation, restrictions and hypothesis test, stochastic regressors, exogeneity and simultaneity, numeric optimization methods, method of moments, etc.
by Miroslav Verbič - InTech
This book provides recent insight on some key issues in econometric theory and applications. It focuses on three recent advances in econometric theory: non-parametric estimation, instrument generating functions, and seasonal volatility models.
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 Daniel McFadden - University of California, Berkeley
The contents: Economic Analysis and Econometrics; Analysis and Linear Algebra in a Nutshell; Probability Theory in a Nutshell; Limit Theorems in Statistics; Experiments, Sampling, and Statistical Decisions; Estimation; Hypothesis Testing.