Deep Learning Models for Economic Research

Andrzej Dudek

$398.95 $319.42

Hardback

Not in-store but you can order this
How long will it take?

Availability Information

We source books from suppliers in Australia and overseas. For books we don't currently have in stock, the time it takes to get them from our suppliers can vary widely - from a few days to a few months - so we check each book with each supplier to determine the expected time it will take to be supplied to us.

We then advise you accordingly. If the time taken to get any book is too long for you, you can let us know and we will cancel or adjust your order, and refund as required.

To find out the anticipated arrival time for specific items prior to ordering, please contact us by phone or email:

Phone +61 2 9264 3111, or 1800 4 BOOKS (1800 4 26657) if outside Sydney:
option 1 Abbey's Bookshop (Crime, History, Science, Kids & more) • info@abbeys.com.au
option 2 Language Book Centre (ESL & Foreign Languages) • language@abbeys.com.au
option 3 Galaxy Bookshop (Sci-fi, Fantasy, Romance, Graphic Novels) • sf@galaxybooks.com.au

QTY:

English

Routledge
21 October 2025

Economic theory & philosophy; Econometrics; Economic forecasting; Artificial intelligence

Series: Routledge Studies in Economic Theory, Method and Philosophy

In today’s data-driven world, the ability to make sense of complex, high-dimensional datasets is crucial for economists and data scientists. Traditional quantitative methods, while powerful, often struggle to keep up with the complexities of modern economic challenges. This book bridges this gap, integrating cutting-edge machine learning techniques with established economic analysis to provide new, more accurate insights.

The book offers a comprehensive approach to understanding and applying neural networks and deep learning models in the context of conducting economic research. It starts by laying the groundwork with essential quantitative methods such as cluster analysis, regression, and factor analysis, then demonstrates how these can be enhanced with deep learning techniques like recurrent neural networks (RNNs), convolutional neural networks (CNNs), and transformers. By guiding readers through real-world examples, complete with Python code and access to datasets, it showcases the practical benefits of neural networks in solving complex economic problems, such as fraud detection, sentiment analysis, stock price forecasting, and inflation factor analysis. Importantly, the book also addresses critical concerns about the “black box” nature of deep learning, offering interpretability techniques like Local Interpretable Model-agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP) to demystify model predictions.

The book is essential reading for economists, data scientists, and professionals looking to deepen their understanding of AI’s role in economic modeling. It is also an accessible resource for non-experts interested in how machine learning is transforming economic analysis.

By: Andrzej Dudek
Imprint: Routledge
Country of Publication: United Kingdom
Dimensions: Height: 234mm, Width: 156mm,
Weight: 1.060kg
ISBN: 9781041062707
ISBN 10: 1041062702
Series: Routledge Studies in Economic Theory, Method and Philosophy
Pages: 464
Publication Date: 21 October 2025
Audience: College/higher education , Primary
Format: Hardback
Publisher's Status: Active

Andrzej Dudek is a Professor in the Department of Computer Science and Econometrics, Wrocław University of Economics and Business, Wrocław, Poland.