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About Using Julia for Introductory Econometrics
Introduces the popular powerful and free programming language and software package Julia Julia an ideal candidate for starting to learn econometrics and data analysis As we will show in this book learning Julia and the basics of econometrics are two goals that can be achieved very well together And Julia is completely free and available for all relevant operating systems When using it in econometrics courses students can easily download a copy to their own computers and use it at home or their favorite cafes to replicate examples and work on take home assignments This hands on experience is essential for the understanding of the econometric models and methods It also prepares students to conduct their own empirical analyses for their theses research projects and professional work This book does not attempt to provide a self contained discussion of econometric models and methods Instead it builds on the excellent and popular textbook Introductory Econometrics by Wooldridge It is compatible in terms of topics organization terminology and notation and is designed for a seamless transition from theory to practice The first chapter provides a gentle introduction to Julia covers some of the topics of basic statistics and probability presented in the appendix of Wooldridge and introduces Monte Carlo simulation as an additional tool The other chapters have the same names and cover the same material as the respective chapters in Wooldridge Assuming the reader has worked through the material discussed there this book explains and demonstrates how to implement everything in Julia and replicates many textbook examples We also open some black boxes of the built in functions for estimation and inference by directly applying the formulas known from the textbook to reproduce the results Some supplementary analyses provide additional intuition and insights Focus implementation of standard tools and methods used in econometricsCompatible with Introductory Econometrics by Jeffrey M Wooldridge in terms of topics organization terminology and notationCompanion website with full text all code for download and other goodiesTopicsA gentle introduction to JuliaSimple and multiple regression in matrix form and using black box routinesInference in small samples and asymptoticsMonte Carlo simulationsHeteroscedasticityTime series regressionPooled cross sections and panel dataInstrumental variables and two stage least squaresSimultaneous equation modelsLimited dependent variables binary count data censoring truncation and sample selectionFormatted reports using Jupyter Notebooks
Detailed Information
| Author: | Florian Heiss |
|---|---|
| Publication Year: | 2023 |
| ISBN: | 9798392400041 |
| Pages: | 402 |
| Language: | English |
| File Size: | 12 |
| Format: | |
| Price: | FREE |
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