Empirical studies examining the impact of various aspects of digitalization on the socio-economic development of regional economies are relatively scarce in the Russian academic literature. Despite the growing role of digital technologies in regional economic development, their effects on key indicators of regional economic activity remain insufficiently explored. The aim of this study is to analyze the effect of one of the fastest-growing indicators of digitalization — e-commerce intensity — on the unemployment rate as well as on SME performance across Russia’s regions. Two indicators were employed to capture e-commerce intensity: the share of online sales in total retail turnover and the volume of online sales per capita in a region. By using panel data for Russian regions from 2014 to 2023 and applying econometric modeling techniques, statistically significant relationships were identified between the development of e-commerce and selected indicators of regional economic activity. First, there is a negative correlation between the share of online sales in total retail trade and the unemployment rate, which may indicate the potential of e-commerce to create jobs and expand employment. Second, a positive correlation emerged between per capita online sales and SME performance per capita and is indicative of an association between digital sales channels and SME activity. These findings should facilitate the formulation of regional economic policy by emphasizing the importance of developing digital infrastructure and supporting e-commerce as a significant factor in economic activity.
The structural transformation of the Russian labor market accelerated by digitalization, gig economy development, and external challenges makes the population search for new, more flexible forms of employment. Self-employment has become a key driver of these changes, yet its impact on real labor behavior strategies remains insufficiently studied. This article analyzes the diversification of labor strategies among Russia's self-employed and defines the role of the self-employment regime in adaptation to the modern labor market. The study uses a mixed methodology combining macro-statistics (Federal Tax Service, Rosstat), digital footprint analysis (Google Trends), and indepth content analysis with parsing of the largest Telegram community of self-employed (over 45K messages, 966 active users), linking macro-trends with micro-level motives. The resulting analysis empirically proves that self-employment is not a single strategy but a polymotivational adaptive module forming a continuum of behavioral practices. Value-based and psychological motives dominate: 44% expressed dissatisfaction with hired labor and 35% seek autonomy, indicating a proactive shift in labor consciousness. Simultaneously, forced macroeconomic and socio-demographic factors confirm self-employment as a critical social buffer. Extensive empirical material substantiates a mass transition to the portfolio career model — dynamic management of multiple projects and income sources. Self-employment in Russia has become a systemic institutionalized phenomenon driving employment diversification, not a marginal or temporary segment. The results challenge the view that the professional income tax serves merely as a fiscal tool and indicates a need to understand it as a factor shaping new labor behavior models. This requires the state to ensure regulatory stability that will reduce vulnerability among the new selfemployed category of workers.
This article analyzes how alcohol market regulations targeting vodka consumption in ways that do not impact prices affect various income groups in Russia. Its theoretical and empirical starting point consists of Russian and international studies that establish the role of restrictions on the time and conditions of alcohol sales, although they often omit the factor of price. The article’s innovative aspect lies in its comprehensive assessment of several non-price measures (morning, evening, and night time restrictions along with mandatory “dry days”) in combination with price instruments in order to provide a differentiated analysis of these measures by income level. The empirical data runs from 2011 to 2022. The Heckman instrumental variable model and the difference-in-differences method with Callaway and Sant’Anna estimates are used to account for selection and heterogeneity of effects. The results indicate that excessively strict morning restrictions (no sales before 2:00 PM) reduce vodka consumption only in below-average income groups, whereas limiting the start of sales to a more reasonable time (10:00 AM or 11:00 AM) affects all groups. Tightening evening restrictions significantly reduces consumption among low-income groups, but has little impact on affluent consumers. However, increasing the number of “dry days” has an ambiguous impact, which may indicate that demand is deferred or that these measures are intended primarily to limit alcohol consumption during holidays. The already confirmed correlations between vodka consumption and age, education, religious belief, marital status, and type of residence also appeared in this study. The overall conclusion is that temporarily limiting availability of alcohol, combined with targeted pricing instruments has the greatest potential to reduce harm among the most vulnerable segments of the population, while price-based interventions are most effective among the most affluent groups.
The number or proportion of independent directors is a key characteristic of corporate boards that is regulated in most jurisdictions. As a concept, independent directors have no relationship with the company other than board membership. In practice, independence is operationalized through regulatory criteria that determine who qualifies as an independent director. But to what extent do companies comply with these criteria? This paper assesses the scale of independent director misclassification in Russian companies, compares the characteristics of quasi-independent and truly independent directors, and examines the factors determining election of quasi-independent directors. The authors employed descriptive, statistical and econometric methods on a 20% stratified sample of Russian publicly traded companies from 2009 to 2020 (596 company-years). Nearly half of the directors designated as independent fail to meet key independence criteria (mainly due to ties with shareholders) and are in fact quasi-independent. Truly independent and quasi-independent directors differ significantly in gender, age and citizenship. The share of truly independent directors has been gradually increasing over time. The likelihood with which quasi-independent directors are appointed to boards is linked to corporate governance factors (e.g., ownership structure) and prior company performance. In particular, firms with poor return on assets (ROA) in the year preceding board elections tend to select quasi-independent board members. These findings should be useful for regulators, exchanges, and investors seeking to improve corporate governance and reliability of disclosures.
This paper utilizes nonlinear dynamics and complexity theory to analyze dynamic resilience of the Republic of Tajikistan from 2010 to 2025. Identification of tipping points in this study was carried out with nonlinear dynamics, which can detect Critical Slowing Down (CSD) signals before they manifest overtly in macroeconomic indicators. The authors reconstructed the phase change of Takikstan's economy based on Takens' Theorem with inputs from cyclical components of GDP data and industrial production indices. Particular emphasis was placed on the analysis of CSD indicators, such as autocorrelation and time-series variance. The study mathematically verified a phase change of the macrosystem that occurred in 2019. Priorto 2018, the economyexhibited "fragile" equilibrium characterized by high autocorrelation coefficients (alpha= 0.89) accompanied by a loss of resilience. The commissioning of the first units of the Rogun Hydropower Plant was identified as a change in the control parameter (an order parameter according to Haken), which triggered bifurcation and the system's transition into a new "high-energy" source of attraction. The authors have provided econometric evidence that Tajikistan's current leadership in industrial growth rates within the CIS (reaching a record 22.1% in 2025) and stable economic growth of 8.4% are not short-term outliers, but rather direct consequences of the formation of a new stable industrial-type attractor. The predictive toolkit developed here can be utilized by government authorities for monitoring systemic risks and preemptively mitigating macroeconomic instability when implementing national development strategies and medium-term development programs for the Republic of Tajikistan.
