Laboratory Researchers Participate in ICEE Conference at PSU-Altoona

On August 1, 2026 , researchers from the Laboratory for Spatial Econometric Modeling of Socio-Economic Processes in Russia presented at the International Conference on Empirical Economics (ICEE) , organized by Pennsylvania State University at Altoona (USA).

Alina Urazbaeva (Research Assistant) delivered a talk titled "One Pandemic, Divergent Outcomes: Regional Entrepreneurship under Varied COVID-19 Measures" in the virtual session AM1J: Macroeconomics and Regional Economics. The study assessed the response of entrepreneurial activity in Russian regions to the severity of COVID-19 restrictions using dose–response functions. The findings indicate that any level of restrictions leads to a decline in the number of microenterprises. For small and medium enterprises, a decline is expected in the absence of restrictions; however, mild to medium measures can mitigate this effect, while strong restrictions exacerbate it.

Elena Semerikova (Senior Research Fellow) presented a talk titled "Robust Two–Stage M–Estimation of the Spatial Lag Model" in session AM2A: Mathematical and Quantitative Methods (co-authors: Vincenzo Nardelli and Giuseppe Arbia). The paper develops a robust two-stage M-estimator for the spatial autoregressive (SAR) model. Classical estimation methods for SAR models — maximum likelihood and instrumental variables — are sensitive to outliers and heavy-tailed error distributions. The proposed approach replaces ordinary least squares at each of the two stages of the instrumental variable procedure with M-estimation using bounded influence functions, thereby mitigating the impact of anomalous observations in both the projection of the endogenous spatial lag and the structural equation. Monte Carlo simulations demonstrate that the proposed estimator is resistant to data contamination and maintains high efficiency. An empirical illustration using Boston housing price data confirms the practical applicability of the method.