Statistika: Statistics and Economy Journal - No. 2/2026

Statistika, 106(2): 136–151
https://doi.org/10.54694/stat.2025.29

Abstract

Motivated by rising demand for timely economic insights, we explore the predictive power of the Industrial Confidence Indicator (ICI) for forecasting the Industrial Production Index (IPI) across EU Member States. Our purpose is to assess whether business sentiment data can serve as a real-time leading indicator for industrial production and explore possible structural patterns across EU countries and over time. The study analyses monthly IPI and ICI data for 27 EU Member States from 2008 to 2024 (while also considering only the prepandemic part of the time series) using correlation analysis, ARIMA/ARIMAX forecasting methods (with expanding and rolling window techniques) and clustering. Our analysis results in rather weak linear correlation between ICI and IPI, very limited forecasting dominance of ARIMAX models over ARIMA models (especially during volatile periods), and identification of contextually fairly meaningful clusters. Using all three methods the pre-pandemic data turn out to better reflect expected relationships compared to the whole time series.

Keywords
Business tendencies, time-series, timeliness, real-time, estimates, nowcasting, clustering

Statistika, 106(2): 152–163
https://doi.org/10.54694/stat.2025.47

Abstract
Time-series clustering is a convenient tool for analysing hidden structures in data. However, as is the case with clustering, it is possible to encounter a number of complications, especially with regards to the sensitivity to the initial algorithm conditions and the subjective choice of the number of groups. The aim of this article is to conduct an experiment using real life data of housing prices in the EU to suppress subjectivity, whether in terms of finding subgroups in the data or the validation of the result for partitional clustering. The proposed procedure is based on a modified bootstrapping principle, where the principle of stability via repetition is applied to the algorithm and its results. As such, this method is applied both to the group selection by monitoring the Calinski-Harabasz index and the final assignment of the resulting classification of clustered objects. The result of this process is a structure that has a better informative value about the relationships in the data.

Keywords
Partitional clustering DTW distance, k-means algorithm, time-series

Statistika, 106(2): 164–179
https://doi.org/10.54694/stat.2025.28

Abstract
The past three decades of survey research have revealed a shift from traditional probability-based surveys to various types of web surveys. In official statistics, the probability-based web panels (PWPs), for which respondents are recruited once and then incentivized for repeated participation in web surveys, play a particularly important role in this process. This article provides insights into the use of PWPs for official statistics. First, a survey of European Union national statistics offices revealed that one-quarter had already implemented or were planning to implement PWPs; the main barriers to their implementation were lack of knowledge and expertise. In addition, we evaluated the quality of the estimates in the Slovenian PWP (1KA Panel) that replicated questions from 12 traditional probability-based surveys. The findings showed that 205 of 651 PWP estimates (31%) exhibited relative bias exceeding 10%. Biases varied substantially across survey topics, indicating the selective suitability of PWPs for official statistics.

Keywords
Probability-based web panels, survey estimates, relative bias, nonresponse error, measurement error, coverage error, processing error

Statistika, 106(2): 180–195
https://doi.org/10.54694/stat.2025.34

Abstract
This paper investigates how domestic market competition influences beer export performance in the European Union between 2014 and 2023. Employing a gravity model framework and Poisson Pseudo-Maximum Likelihood estimation, it incorporates standard trade variables alongside two measures of domestic competition: the Herfindahl-Hirschman Index and the ratio of microbreweries to total breweries. The empirical results, based on 1 277 observations, indicate that lower market concentration and a higher share of microbreweries are significantly associated with greater export volumes. Conceptually, the paper extends heterogeneous-firm trade to a mature, differentiated consumer industry and identifies both an efficiency/selection channel and a non-price differentiation channel. Empirically, it offers new sector-level, multi-country evidence that links domestic market dynamism and firm diversity to external competitiveness, and informs policies on competition and SME support.

Keywords
Competition, export performance, international trade, beer industry, microbrewery

Statistika, 106(2): 196–213
https://doi.org/10.54694/stat.2025.51

Abstract
This study evaluates regional eco-efficiency and market competitiveness in the dairy sector of the Visegrad Four (V4) regions – Czechia, Slovakia, Hungary, and Poland – for 2015 and 2022. Eco-efficiency was assessed using input-oriented Data Envelopment Analysis (DEA) with an undesirable output, assuming constant returns to scale, while competitiveness was measured with a composite Dairy Competitiveness Index based on economic and sectoral indicators. Results indicate that high environmental performance does not consistently align with market competitiveness, with only the Polish region PL92: Mazowiecki regionalny excelling in both dimensions. The research hypothesis – The eco-efficiency of a region ensures a higher level of outputs for given inputs, thereby increasing its competitiveness – was rejected. Four regional groups were identified – Leaders, Market-driven, Eco-driven, and Laggards – highlighting persistent structural differences across the V4. The findings provide evidence for designing region-specific policies that support sustainable, competitive, and resilient dairy systems.

Keywords
dairy eco-efficiency, competitiveness, V4 regions, interrelationship

Statistika, 106(2): 214–227
https://doi.org/10.54694/stat.2025.37

Abstract
The Statistical Office of the Republic of Slovenia (SURS) developed a predictive model to estimate the intended slaughter or breeding of young bovine animals using administrative data from the Central Register of Bovine Animals (CRB). A binomial regression model with a logit link was employed to forecast slaughter rates, replacing the traditional, resource-intensive survey-based approach. Internal bootstrap validation and external calibration confirmed the model’s robustness, ensuring that predictions align with real-world occurrences and are suitable for future forecasting. The model demonstrated a significant improvement in predictive accuracy, with a difference of around 2% between the model's estimates and the survey results, equating to approximately 3 000 animals per year. The model is now closely aligned with observed values, demonstrating that administrative data can effectively replace costly telephone surveys. This shift promises both cost savings and enhanced accuracy in official agricultural statistics, with potential for broader application in other agricultural sectors or regions.

Keywords
Central Register of Bovine Animals, logistic regression, prediction, calibration, validation

Statistika, 106(2): 228–240
https://doi.org/10.54694/stat.2025.44

Abstract
We examine how pay and staffing conditions relate to the attractiveness of public-university faculties in Czechia. Using harmonised faculty-level administrative data for 2017–2024, we fit a covariance-based
structural equation model (CB-SEM) with four latent constructs: structural conditions, research drive (including a time trend), wages and student interest. Student interest is positively associated with structural conditions and with research drive. The relationship between wages and student interest is not statistically significant once the other constructs are included. Research drive is also related to wages and structural conditions. Taken together, the results suggest that teaching capacity and research visibility are the main factors associated with faculties’ attractiveness, while wage policy appears, if at all, related through those channels rather than directly. These insights can inform discussions of public funding formulas and institutional staffing strategies by emphasising teaching capacity and research visibility rather than undifferentiated wage increases.

Keywords
CB-SEM, higher education institutions, institutional attractiveness, administrative data, academic staff workload, faculty-level funding

Statistika, 106(2): 241–251
https://doi.org/10.54694/stat.2025.35

Abstract
Macroeconomic theory and macroeconomic aggregates are a sine qua non for the economic policy decisionmaking. It is of vital importance not only that macroeconomics aggregates are measured as correctly as possible but also that their content constitutes an appropriate input into the macroeconomic models, in line with the expectations and intentions of modellers. In this paper, we focus on the current methodological treatment of respective statistical indicators serving as an illustration of conditions under which external balance in the IS-LM-BP model is achieved and where pressures on foreign exchange rate ensue. We will investigate the consequences of the current content of external statistics indicators for their interpretation in the stories economists tell about the international equilibrium and its adjustments, whether in class or in policy-making.

Keywords
International equilibrium, BP curve, exchange rate