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 Thomas J. Sargent, John Stachurski - QuantEcon
This website presents a series of lectures on quantitative economic modeling. From the table of contents: Data and Empirics; Tools and Techniques; Dynamic Programming; Multiple Agent Models; Time Series Models; Dynamic Programming Squared.
by Charles Frederick Roos - Principia Press
Contents: Static Versus Dynamic Economics; Demand for Consumer Goods; Automotive Demand for Gasoline; Demand for Agricultural Products; Demand for Capital Goods; Factors Influencing Residential Building; Growth and Decline of Industry; etc.
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 Melvyn Fuss, Daniel L. McFadden - North-Holland
Chapters: Cost, Revenue, and Profit Functions; Symmetric Duality and Polar Production Functions; Applications of Profit Functions; General Linear Profit Function; Duality, Intermediate Inputs and Value-Added; Hick's Aggregation Theorem; etc.