Hands-on Intermediate Econometrics Using R: Templates For Learning Quantitative Methods And R Software

This book provides practical understanding of Econometrics with hands-on examples and software snippets. It covers topics such as iteratively reweighted least squares, pillar charts, stochastic frontier analysis, model selection, and more. The second edition includes new topics like NKPC, ANN, vector AR and VARMA models, and more.

Format: Hardback
Length: 644 pages
Publication date: 05 May 2022
Publisher: World Scientific Publishing Co Pte Ltd

This comprehensive textbook is designed to provide students with a solid foundation in both applied statistics (econometrics) and free, open-source software R. It offers a hands-on approach to learning, allowing students to gain practical knowledge by copying and pasting numerous hands-on templates provided within the book. The textbook is an essential resource for anyone seeking to develop a comprehensive understanding of a wide range of econometric topics.

One of the key strengths of this textbook is its emphasis on providing software snippets to learn a diverse array of new statistical tools with hands-on examples. The explicit knowledge of inputs and outputs for each new method enables students to identify which algorithms are worth studying and applying. The book offers comprehensive theoretical and algorithmic details about a vast range of statistical techniques, making it an invaluable resource for both novice and advanced students.

In addition to its comprehensive coverage of statistical techniques, the second edition of this textbook includes several topics that are often overlooked in other textbooks. These topics include iteratively reweighted least squares, pillar charts for representing 3D data, stochastic frontier analysis (SFA), model selection with Mallows' Cp criterion, Hodrick-Prescott (HP) filter, automatic ARIMA models, nonlinear Granger-causality using kernel regressions and bootstrap confidence intervals, new Keynesian Phillips curve (NKPC), market-neutral pairs trading using two cointegrated stocks, artificial neural network (ANN) for product-specific forecasting, vector AR and VARMA models, new tools for diagnosing the endogeneity problem, the elegant set-up of k-class estimators and identification, probit-logit models and Heckman selection bias correction, receiver operating characteristic (ROC) curves and areas under them, confusion matrix, quantile regression, elastic net estimator, generalized correlations, maximum entropy bootstrap for time series, convergence concepts quantified, and generalize.

By incorporating these additional topics, the textbook provides a more comprehensive and up-to-date understanding of econometric analysis. Whether you are a student, researcher, or professional seeking to expand your knowledge in this field, this textbook is an excellent choice. Its clear explanations, practical examples, and extensive software snippets make it an invaluable resource for anyone wishing to learn both applied statistics (econometrics) and free, open-source software R.

ISBN-13: 9789811256172
Edition number: Second Edition