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 Tjalling C. Koopmans - John Wiley & Sons
Quantitative economic study has a threefold basis: it is necessary to formulate economic hypotheses, to collect appropriate data, and to confront hypotheses with data. The latter task, statistical inference in economics, is discussed in this book.
by Daniel McFadden, Antti Talvitie, and Associates - University of California
From the table of contents: Theory and Estimation of Behavioral Travel Demand Models; Development, Testing, and Validaton of a Work-Trip Mode-Choice Model; Modeling Choices Other than Work-Trip; Issues in Demand Modeling and Forecasting.
by Roman Kozhan - BookBoon
This is a step-by-step guide to financial econometrics using EViews 6.0 statistical package. It contains brief overviews of econometric concepts, models and data analysis techniques followed by examples of how they can be implemented in EViews.
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.