Computational Economics

Aims & Scope

Computational Economics, the official journal of the Society for Computational Economics, presents new research in a rapidly growing multidisciplinary field that uses advanced computing capabilities to understand and solve complex problems from all branches in economics.

The topics of Computational Economics include computational methods in econometrics like filtering, bayesian and non-parametric approaches, markov processes and monte carlo simulation; agent based methods, machine learning, evolutionary algorithms, (neural) network modeling; computational aspects of dynamic systems, optimization, optimal control, games, equilibrium modeling; hardware and software developments, modeling languages, interfaces, symbolic processing, distributed and parallel processing.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	2.2
2024	1.90

Journal Rank

Year	Value
2024	10856

Journal Citation Indicator

Year	Value
2024	1300

SJR (SCImago Journal Rank)

Year	Value
2024	0.535

Quartile

Year	Value
2024	Q2

h-index

Year	Value
2024	51

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science and Economics, Econometrics and Finance, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Solving Linear Rational Expectations Models

  Citation: 615

  Authors: Christopher A.

• Applied General Equilibrium Modeling with MPSGE as a GAMS Subsystem: An Overview of the Modeling Framework and Syntax

  Citation: 296

  Authors: Thomas F.

• Estimation of Agent-Based Models: The Case of an Asymmetric Herding Model

  Citation: 291

  Authors: Simone, Thomas, Friedrich

• Extracting Appropriate Nodal Marginal Prices for All Types of Committed Reserve

  Citation: 287

  Authors: Paria, Mohammad, Mohammad Reza Rezaie, Hamidreza, Noradin

• Explainable Machine Learning in Credit Risk Management

  Citation: 269

  Authors: Niklas, Paolo, Dimitri, Jochen

• Computing solutions for large general equilibrium models using GEMPACK

  Citation: 263

  Authors: W. Jill, K. R.

• Core–Periphery Structure in the Overnight Money Market: Evidence from the e-MID Trading Platform

  Citation: 227

  Authors: Daniel, Thomas

• An Application of Extreme Value Theory for Measuring Financial Risk

  Citation: 223

  Authors: Manfred, Evis

• A Critical Guide to Empirical Validation of Agent-Based Models in Economics: Methodologies, Procedures, and Open Problems

  Citation: 203

  Authors: Giorgio, Alessio, Paul

• Forecasting of Real GDP Growth Using Machine Learning Models: Gradient Boosting and Random Forest Approach

  Citation: 187

  Authors: Jaehyun

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