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 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.
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Optimal Regulation addresses the central issue of regulatory economics -- how to regulate firms in a way that induces them to produce and price 'optimally'. It synthesis an extensive theoretical literature on what constitutes optimality.
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CGE framework encompasses both the I-O and SAM frameworks by making demand and supply of commodities and factors dependent on prices. A CGE model simulates the working of a market economy in which prices and quantities adjust to clear all markets.