Journal of Statistical and Econometric Methods

Aims and Scope

The Journal of Statistical and Econometric Methods offers peer-reviewed original papers, reviews and survey articles focusing on statistical and econometric methods and dealing with the applications of existing or new techniques to a wide variety of problems in business, finance, economics and related subjects.

Coverage includes the most current progress on topics such us:Techniques for evaluating analytically intractable problems such as high-dimensional multivariate integrals, Search and Optimization Methods, Computer Intensive Statistical Methods, Simulation and Monte Carlo, Asymptotic statistics, Bayesian Statistics, Biostatistics,

Business statistics, Computational statistics, Econometric Techniques, Regression Analysis, Statistical Analysis with complex data, Time series analysis, Singular Spectrum Analysis, Mathematical Statistics, Markov Processes, Stochastic Differential Equations, and Financial Market Microstructure.

Impact Factor: 0.11 (RePEc)

Special Issue 2024: Cost of Living Crisis-Global Impact and Challenges

Journal of Statistical and Econometric Methods invites submissions from researchers on the broader topic of the impacts and challenges from the cost of living crisis. A series of dedicated Special Issues will be published within 2024.

The themes of the Special Issues are (but not limited to) the following:

• Statistical analysis of econometric parameters for affected economies
• Mathematical and stochastic analysis of finance and investment problems
• Mathematical and stochastic projections for affected economies
• Statistical analysis of financing for governmental bodies
• Applied econometric methods for affected businesses
• Mitigation tools and techniques for financial programming 
• Advanced mathematical models for projecting market recovery
• Mathematical trends of inflation, taxation and commodity prices
• Inflation and trend of econometric parameters
• Mathematical models for recovery funding for financing resilient infrastructure
• Mathematical models for Insurance and reinsurance for infrastructure recovery
• Mathematical models for recovery from major events and insurance policies