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Using Python For Introductory Econometrics
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Book Synopsis Using Python for Introductory Econometrics by : Florian Heiss
Download or read book Using Python for Introductory Econometrics written by Florian Heiss and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Introductory Econometrics for Finance by : Chris Brooks
Download or read book Introductory Econometrics for Finance written by Chris Brooks and published by Cambridge University Press. This book was released on 2008-05-22 with total page 752 pages. Available in PDF, EPUB and Kindle. Book excerpt: This best-selling textbook addresses the need for an introduction to econometrics specifically written for finance students. Key features: • Thoroughly revised and updated, including two new chapters on panel data and limited dependent variable models • Problem-solving approach assumes no prior knowledge of econometrics emphasising intuition rather than formulae, giving students the skills and confidence to estimate and interpret models • Detailed examples and case studies from finance show students how techniques are applied in real research • Sample instructions and output from the popular computer package EViews enable students to implement models themselves and understand how to interpret results • Gives advice on planning and executing a project in empirical finance, preparing students for using econometrics in practice • Covers important modern topics such as time-series forecasting, volatility modelling, switching models and simulation methods • Thoroughly class-tested in leading finance schools. Bundle with EViews student version 6 available. Please contact us for more details.
Book Synopsis Using R for Introductory Econometrics by : Florian Heiss
Download or read book Using R for Introductory Econometrics written by Florian Heiss and published by . This book was released on 2020-05-24 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces the popular, powerful and free programming language and software package R Focus implementation of standard tools and methods used in econometrics Compatible with "Introductory Econometrics" by Jeffrey M. Wooldridge in terms of topics, organization, terminology and notation Companion website with full text, all code for download and other goodies: http: //urfie.net Also check out Using Python for Introductory Econometrics http: //upfie.net/ Praise "A very nice resource for those wanting to use R in their introductory econometrics courses." (Jeffrey M. Wooldridge) Using R for Introductory Econometrics is a fabulous modern resource. I know I'm going to be using it with my students, and I recommend it to anyone who wants to learn about econometrics and R at the same time." (David E. Giles in his blog "Econometrics Beat") Topics: A gentle introduction to R Simple and multiple regression in matrix form and using black box routines Inference in small samples and asymptotics Monte Carlo simulations Heteroscedasticity Time series regression Pooled cross-sections and panel data Instrumental variables and two-stage least squares Simultaneous equation models Limited dependent variables: binary, count data, censoring, truncation, and sample selection Formatted reports and research papers combining R with R Markdown or LaTeX
Book Synopsis Introductory Econometrics: A Modern Approach by : Jeffrey M. Wooldridge
Download or read book Introductory Econometrics: A Modern Approach written by Jeffrey M. Wooldridge and published by Cengage Learning. This book was released on 2019-01-04 with total page 816 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gain an understanding of how econometrics can answer today's questions in business, policy evaluation and forecasting with Wooldridge's INTRODUCTORY ECONOMETRICS: A MODERN APPROACH, 7E. This edition's practical, yet professional, approach demonstrates how econometrics has moved beyond a set of abstract tools to become genuinely useful for answering questions across a variety of disciplines. Information is organized around the type of data being analyzed, using a systematic approach that only introduces assumptions as they are needed. This makes the material easier to understand and, ultimately, leads to better econometric practices. Packed with relevant applications, this edition incorporates more than 100 intriguing data sets in different formats. Updates introduce the latest developments in the field, including recent advances in the so-called “causal effects” or “treatment effects” literature, for an understanding of the impact and importance of econometrics today. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
Book Synopsis An Introduction to Modern Econometrics Using Stata by : Christopher F. Baum
Download or read book An Introduction to Modern Econometrics Using Stata written by Christopher F. Baum and published by Stata Press. This book was released on 2006-08-17 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Integrating a contemporary approach to econometrics with the powerful computational tools offered by Stata, this introduction illustrates how to apply econometric theories used in modern empirical research using Stata. The author emphasizes the role of method-of-moments estimators, hypothesis testing, and specification analysis and provides practical examples that show how to apply the theories to real data sets. The book first builds familiarity with the basic skills needed to work with econometric data in Stata before delving into the core topics, which range from the multiple linear regression model to instrumental-variables estimation.
Book Synopsis Applied Econometrics with R by : Christian Kleiber
Download or read book Applied Econometrics with R written by Christian Kleiber and published by Springer Science & Business Media. This book was released on 2008-12-10 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: R is a language and environment for data analysis and graphics. It may be considered an implementation of S, an award-winning language initially - veloped at Bell Laboratories since the late 1970s. The R project was initiated by Robert Gentleman and Ross Ihaka at the University of Auckland, New Zealand, in the early 1990s, and has been developed by an international team since mid-1997. Historically, econometricians have favored other computing environments, some of which have fallen by the wayside, and also a variety of packages with canned routines. We believe that R has great potential in econometrics, both for research and for teaching. There are at least three reasons for this: (1) R is mostly platform independent and runs on Microsoft Windows, the Mac family of operating systems, and various ?avors of Unix/Linux, and also on some more exotic platforms. (2) R is free software that can be downloaded and installed at no cost from a family of mirror sites around the globe, the Comprehensive R Archive Network (CRAN); hence students can easily install it on their own machines. (3) R is open-source software, so that the full source code is available and can be inspected to understand what it really does, learn from it, and modify and extend it. We also like to think that platform independence and the open-source philosophy make R an ideal environment for reproducible econometric research.
Download or read book Econometrics written by Fumio Hayashi and published by Princeton University Press. This book was released on 2011-12-12 with total page 708 pages. Available in PDF, EPUB and Kindle. Book excerpt: The most authoritative and comprehensive synthesis of modern econometrics available Econometrics provides first-year graduate students with a thoroughly modern introduction to the subject, covering all the standard material necessary for understanding the principal techniques of econometrics, from ordinary least squares through cointegration. The book is distinctive in developing both time-series and cross-section analysis fully, giving readers a unified framework for understanding and integrating results. Econometrics covers all the important topics in a succinct manner. All the estimation techniques that could possibly be taught in a first-year graduate course, except maximum likelihood, are treated as special cases of GMM (generalized methods of moments). Maximum likelihood estimators for a variety of models, such as probit and tobit, are collected in a separate chapter. This arrangement enables students to learn various estimation techniques in an efficient way. Virtually all the chapters include empirical applications drawn from labor economics, industrial organization, domestic and international finance, and macroeconomics. These empirical exercises provide students with hands-on experience applying the techniques covered. The exposition is rigorous yet accessible, requiring a working knowledge of very basic linear algebra and probability theory. All the results are stated as propositions so that students can see the points of the discussion and also the conditions under which those results hold. Most propositions are proved in the text. For students who intend to write a thesis on applied topics, the empirical applications in Econometrics are an excellent way to learn how to conduct empirical research. For theoretically inclined students, the no-compromise treatment of basic techniques is an ideal preparation for more advanced theory courses.
Book Synopsis Introduction to Econometrics by : James H. Stock
Download or read book Introduction to Econometrics written by James H. Stock and published by . This book was released on 2018-09-28 with total page 755 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ensure students grasp the relevance of econometrics with Introduction to Econometrics -- the text that connects modern theory and practice with motivating, engaging applications. The 4th Edition maintains a focus on currency, while building on the philosophy that applications should drive the theory, not the other way around. The text incorporates real-world questions and data, and methods that are immediately relevant to the applications. With very large data sets increasingly being used in economics and related fields, a new chapter dedicated to Big Data helps students learn about this growing and exciting area. This coverage and approach make the subject come alive for students and helps them to become sophisticated consumers of econometrics.-Publisher's description.
Book Synopsis Introduction to Numerical Programming by : Titus A. Beu
Download or read book Introduction to Numerical Programming written by Titus A. Beu and published by CRC Press. This book was released on 2014-09-03 with total page 676 pages. Available in PDF, EPUB and Kindle. Book excerpt: Makes Numerical Programming More Accessible to a Wider Audience Bearing in mind the evolution of modern programming, most specifically emergent programming languages that reflect modern practice, Numerical Programming: A Practical Guide for Scientists and Engineers Using Python and C/C++ utilizes the author’s many years of practical research and teaching experience to offer a systematic approach to relevant programming concepts. Adopting a practical, broad appeal, this user-friendly book offers guidance to anyone interested in using numerical programming to solve science and engineering problems. Emphasizing methods generally used in physics and engineering—from elementary methods to complex algorithms—it gradually incorporates algorithmic elements with increasing complexity. Develop a Combination of Theoretical Knowledge, Efficient Analysis Skills, and Code Design Know-How The book encourages algorithmic thinking, which is essential to numerical analysis. Establishing the fundamental numerical methods, application numerical behavior and graphical output needed to foster algorithmic reasoning, coding dexterity, and a scientific programming style, it enables readers to successfully navigate relevant algorithms, understand coding design, and develop efficient programming skills. The book incorporates real code, and includes examples and problem sets to assist in hands-on learning. Begins with an overview on approximate numbers and programming in Python and C/C++, followed by discussion of basic sorting and indexing methods, as well as portable graphic functionality Contains methods for function evaluation, solving algebraic and transcendental equations, systems of linear algebraic equations, ordinary differential equations, and eigenvalue problems Addresses approximation of tabulated functions, regression, integration of one- and multi-dimensional functions by classical and Gaussian quadratures, Monte Carlo integration techniques, generation of random variables, discretization methods for ordinary and partial differential equations, and stability analysis This text introduces platform-independent numerical programming using Python and C/C++, and appeals to advanced undergraduate and graduate students in natural sciences and engineering, researchers involved in scientific computing, and engineers carrying out applicative calculations.
Book Synopsis The Effect by : Nick Huntington-Klein
Download or read book The Effect written by Nick Huntington-Klein and published by CRC Press. This book was released on 2021-12-20 with total page 646 pages. Available in PDF, EPUB and Kindle. Book excerpt: Extensive code examples in R, Stata, and Python Chapters on overlooked topics in econometrics classes: heterogeneous treatment effects, simulation and power analysis, new cutting-edge methods, and uncomfortable ignored assumptions An easy-to-read conversational tone Up-to-date coverage of methods with fast-moving literatures like difference-in-differences
Book Synopsis Python for Data Analysis by : Wes McKinney
Download or read book Python for Data Analysis written by Wes McKinney and published by "O'Reilly Media, Inc.". This book was released on 2017-09-25 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the IPython shell and Jupyter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples
Book Synopsis A Guide to Econometrics by : Peter Kennedy
Download or read book A Guide to Econometrics written by Peter Kennedy and published by John Wiley & Sons. This book was released on 2008-02-19 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dieses etwas andere Lehrbuch bietet keine vorgefertigten Rezepte und Problemlösungen, sondern eine kritische Diskussion ökonometrischer Modelle und Methoden: voller überraschender Fragen, skeptisch, humorvoll und anwendungsorientiert. Sein Erfolg gibt ihm Recht.
Book Synopsis Learning Microeconometrics with R by : Christopher P. Adams
Download or read book Learning Microeconometrics with R written by Christopher P. Adams and published by CRC Press. This book was released on 2020-12-29 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focuses on the assumptions underlying the algorithms rather than their statistical properties Presents cutting-edge analysis of factor models and finite mixture models. Uses a hands-on approach to examine the assumptions made by the models and when the models fail to estimate accurately Utilizes interesting real-world data sets that can be used to analyze important microeconomic problems Introduces R programming concepts throughout the book. Includes appendices that discuss many of the concepts introduced in the book, as well as measures of uncertainty in microeconometrics.
Book Synopsis Python for Marketing Research and Analytics by : Jason S. Schwarz
Download or read book Python for Marketing Research and Analytics written by Jason S. Schwarz and published by Springer Nature. This book was released on 2020-11-03 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to quantitative marketing with Python. The book presents a hands-on approach to using Python for real marketing questions, organized by key topic areas. Following the Python scientific computing movement toward reproducible research, the book presents all analyses in Colab notebooks, which integrate code, figures, tables, and annotation in a single file. The code notebooks for each chapter may be copied, adapted, and reused in one's own analyses. The book also introduces the usage of machine learning predictive models using the Python sklearn package in the context of marketing research. This book is designed for three groups of readers: experienced marketing researchers who wish to learn to program in Python, coming from tools and languages such as R, SAS, or SPSS; analysts or students who already program in Python and wish to learn about marketing applications; and undergraduate or graduate marketing students with little or no programming background. It presumes only an introductory level of familiarity with formal statistics and contains a minimum of mathematics.
Book Synopsis Practical Econometrics by : Michael Hilmer
Download or read book Practical Econometrics written by Michael Hilmer and published by McGraw-Hill Education. This book was released on 2013-10-08 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical Econometrics bridges the gap between theoretical and practical knowledge of introductory econometrics. The intuition underlying each individual econometric tool is explained, both verbally and visually whenever possible, before introducing the technical details required to actually implement the tool. Particular attention is paid to developing correct interpretation skills and the how-to's associated with effectively communicating the quality of one's work. The goal is to provide readers with not only the desire but also the practical know-how to correctly utilize the econometric tools introduced and thereby increase the true power of the introductory econometrics course. Both Microsoft Excel and Stata software packages provide data examples throughout the text.
Book Synopsis Learning Python Data Visualization by : Chad Adams
Download or read book Learning Python Data Visualization written by Chad Adams and published by . This book was released on 2014-08-22 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you are a Python novice or an experienced developer and want to explore data visualization libraries, then this is the book for you. No prior charting or graphics experience is needed.
Book Synopsis Econometric Methods with Applications in Business and Economics by : Christiaan Heij
Download or read book Econometric Methods with Applications in Business and Economics written by Christiaan Heij and published by OUP Oxford. This book was released on 2004-03-25 with total page 816 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nowadays applied work in business and economics requires a solid understanding of econometric methods to support decision-making. Combining a solid exposition of econometric methods with an application-oriented approach, this rigorous textbook provides students with a working understanding and hands-on experience of current econometrics. Taking a 'learning by doing' approach, it covers basic econometric methods (statistics, simple and multiple regression, nonlinear regression, maximum likelihood, and generalized method of moments), and addresses the creative process of model building with due attention to diagnostic testing and model improvement. Its last part is devoted to two major application areas: the econometrics of choice data (logit and probit, multinomial and ordered choice, truncated and censored data, and duration data) and the econometrics of time series data (univariate time series, trends, volatility, vector autoregressions, and a brief discussion of SUR models, panel data, and simultaneous equations). · Real-world text examples and practical exercise questions stimulate active learning and show how econometrics can solve practical questions in modern business and economic management. · Focuses on the core of econometrics, regression, and covers two major advanced topics, choice data with applications in marketing and micro-economics, and time series data with applications in finance and macro-economics. · Learning-support features include concise, manageable sections of text, frequent cross-references to related and background material, summaries, computational schemes, keyword lists, suggested further reading, exercise sets, and online data sets and solutions. · Derivations and theory exercises are clearly marked for students in advanced courses. This textbook is perfect for advanced undergraduate students, new graduate students, and applied researchers in econometrics, business, and economics, and for researchers in other fields that draw on modern applied econometrics.