Lyudmila Ryabushka

This study came to inspect a new approach to the government debt security assessment based on the systematization of indicators in terms of four directions: solvency, liquidity, domestic indebtedness, and external indebtedness. The proposed methodology considers the weaknesses, which negatively affect the level of government debt security.
It was established that in 2014−2016 the level of security at emerging markets was the worst. The main reason was insufficient solvency. Also, the obtained results showed that the general assessment of domestic indebtedness in recent years had a more dangerous level than the external one. In addition, it was revealed that similar problems with the level of debt burden are also presented in the EU countries since the value of the analyzed indicator – general government debt to GDP – exceeds 60%.
It is recommended to consider the experience of debt management reform of new members of the EU and, at the same time, post-socialist countries by other emerging economies.

As cities increasingly adopt smart technologies and seek to foster innovation-driven economies, it is vital to understand how smart city development relates to the strength of local startup ecosystems. This study investigates whether a statistically significant relationship exists between a city’s performance in the smart city ranking and the strength of its startup ecosystem. The study employed available data from the Global Startup Ecosystem Report (by Startup Genome) and the Smart City Index (SCI by the IMD World Competitiveness Center). A balanced panel regression analysis was conducted on a dataset comprising 77 cities across the years 2020, 2021, and 2023 (2022 is excluded as the SCI was not published). The findings reveal that the Random Effects model yielded statistically significant results, indicating a weak (R² = 25.63%) but significant inverse relationship between SCI and startup ecosystem development, which means cities that rank higher on smart city metrics tend to show lower levels of startup ecosystem performance. This counterintuitive result challenges the assumption that technologically advanced cities automatically provide fertile ground for entrepreneurial activity. One possible explanation is that smart cities, dominated by large tech players and rigid governance structures, may present entry barriers for emerging startups. High operational costs, regulatory constraints, and a focus on large-scale infrastructure projects may disincentivize startups from localizing their innovations within these environments. Although the R² suggests that other variables beyond the smart city ranking influence startup development. This study highlights the need for urban policies that actively integrate startup-supportive mechanisms into smart city strategies.