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 James P. LeSage - University of Toledo
This text provides an introduction to spatial econometrics as well as a set of MATLAB functions that implement a host of spatial econometric estimation methods. The intended audience is faculty and students involved in modeling spatial data sets.
by Second Bwanakare - De Gruyter Open
The book provides a new, non-extensive entropy econometrics approach to the economic modelling of ill-behaved inverse problems. Particular attention is paid to national account-based general equilibrium models known for their relative complexity.
by Bruce E. Hansen - University of Wisconsin
Econometrics is the study of estimation and inference for economic models using economic data. Econometric theory concerns the study of tools and methods for applied econometric applications. This is a first-year Ph.D. econometrics textbook.
by Kenneth Train - The MIT Press
This book is a comprehensive but concise text that covers the recently developed and widely applicable methods of qualitative choice analysis, illustrating the general theory through simulation models of automobile demand and use.