Econometrics - Recent Advances and Applications

Edited by Brian William Sloboda

Abstract: Econometrics uses statistical methods and real-world data to predict and establish specific trends. This analytical method sustains limitless potential, but the necessary research for professionals to understand and implement this is often lacking. Econometrics - Recent Advances and Applications explores the theoretical and practical aspects of detailed econometric theories and applications within economics, policymaking, and finance. This book covers various topics such as dynamic stochastic general equilibrium (DSGE) models, machine learning, spatial econometrics, and time series analysis. This book is a useful resource for economists, policymakers, financial analysts, researchers, academicians, and graduate students seeking research on the various applications of econometrics.

JEL-codes: C01 (search for similar items in EconPapers)
Date: 2023
ISBN: 978-1-80356-524-8
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Chapters in this book:

A Primer on Machine Learning Methods for Credit Rating Modeling: Yixiao Jiang
Evaluating DSGE Models: From Calibration to Cointegration: Bjørnar Karlsen Kivedal
Forecasting Weekly Shipments of Hass Avocados from Mexico to the United States Using Econometric and Vector Autoregression Models: Oral Capps
Incorporating Model Uncertainty in Market Response Models with Multiple Endogenous Variables by Bayesian Model Averaging: Jonathan Lee and Alex Lenkoski
Spatiotemporal Difference-in-Differences: A Dynamic Mechanism of Socio-Economic Evaluation: Lijia Mo
The Impact of Inflation Expectations and Public Debt on Taxation in South Africa: Thobeka Ncanywa and Noko Setati

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Persistent link: https://EconPapers.repec.org/RePEc:ito:pbooks:8194

DOI: 10.5772/intechopen.100862

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