Aims and scope

The subject area of the published articles covers theoretical and practical aspects of the methods of econometrics, statistics, and mathematics. Their applications concern wider economic issues, including macro- and microeconomic analyses, statistical and econometric analysis, data analysis and modelling, as well as capital investment and insurance problems. Social and demographic analyses deal with the issues of education, employment and unemployment, poverty, sustainable development, and social exclusion. The papers appearing in the journal are an inspiration to undertake new research challenges. Our aim is to publish valuable and highly rated articles. We particularly encourage the publication of papers that present groundbreaking topics and solutions. Authors have the possibility to attach supplementary data and result files that could not be included in the article itself.

International reach and promotion of Polish research

The journal publishes exclusively in English to maximise the international impact of the research it disseminates. At the same time, a substantial share of the published work originates from Polish academic institutions and addresses economic, social, and methodological questions of direct relevance to Poland and international economy. In this way, the journal serves as a bridge between Polish scientific thought and the global research community, contributing to the international visibility and recognition of Polish scholarship in econometrics, statistics, and applied data analysis.

Subject areas

  • Mathematical or Statistical Models in Economic, Social and Business Sciences
  • Econometric Models
  • Single and Multiple or Simultaneous Equation Models
  • Bayesian Econometrics
  • Financial Econometrics
  • Microeconometrics
  • Time Series Analysis
  • Panel Data Methods
  • Discrete Regression and Choice Modelling
  • Treatment Modelling
  • Models for Count Data
  • Duration Models and Limited Dependent Variables
  • Quantile Regression
  • Multidimensional Statistical Analysis
  • Classification and Taxonomic Methods
  • Big Data (Data Storage and Management, Data Search and Mining, Machine Learning)
  • Data Collecting, Survey Methods, Sampling
  • Methods of Visualisation
  • Statistical Decision Theory
  • Optimisation Techniques
  • Operations Research
  • Application of Econometric Techniques in Various Subject Areas