Lala Hamidova

In modern conditions, the one-sidedness in the economy of Azerbaijan makes it necessary to accelerate the diversification process of the country’s economy. From this point of view, the development of the non-oil sector in the country presents the main priority of the government’s economic policy in Azerbaijan. The purpose of the study is to investigate ways of ensuring the diversification of the national industries in Azerbaijan, which aims to move to a new economic growth model in modern conditions. The study analyzes the economy’s current state and export diversification level in Azerbaijan using the Herfindahl-Hirshman index. As a result of the analysis, the level of diversification in Azerbaijan’s economy and exports was found to be very low (in 2021, the Herfindahl-Hirshman index was 0.23 for the economy and 0.79 for exports). The findings indicate that cooperation between the state and business plays a significant role in increasing the diversification of the economy following the goals of sustainable development of Azerbaijan. On the other hand, it helps stimulate entrepreneurship development in the non-oil sector. One of the ways to solve existing problems in this area is to create Eximbanks to increase the country’s export capabilities of non-oil products. The study offers recommendations to speed up the process of diversification of the economy in Azerbaijan and increase its efficiency.

This study provides empirical evidence that CO₂ emissions from transport (total and by transport types) have an impact on countries’ logistics efficiency, both in general (Logistics Performance Index) and in terms of its individual indicators (volumes of freight transport (total and by transport types) and total investments in transport infrastructure). The aim is to empirically demonstrate the impact of CO₂ emissions from different modes of transport on the logistics efficiency of countries, specifically using data from 60 International Transport Forum (ITF) member countries. The Granger causality analysis, based on VAR modeling for six periods evaluated by the World Bank (2007, 2010, 2012, 2014, 2016, 2018), demonstrates that in 50% of the countries, changes in CO₂ emissions from transport are the cause of the shifts in the Logistics Performance Index (increasing emissions can impede logistics efficiency). The sample was reduced to these countries for the regression modeling. Regression modeling (with fixed and random effects, Hausman test, for 2002–2021 on panel data for countries in which direct causality was confirmed) showed that a one-unit increase in total CO₂ emissions from transport (in general and in air transport) is associated with 0.12 and 0.21 decrease in total investments in transport infrastructure. An increase in road CO₂ emissions is associated with a 0.49 decrease in road freight transport (ton-km per thousand units of GDP). An increase in CO₂ rail emissions is associated with a 0.15 increase in total investments in transport infrastructure and a 0.12 increase in total freight transport.

Telecommunication technologies have entered all spheres of society, creating wide chances for improvement. The splendid, safe, and effective digital revolution in best practices and the productive use of resources in this field are the driving force behind the improvement of innovation. The aim of the study is to identify the main problems of the arrangement and evolution of the digital economy in Azerbaijan, as well as to offer recommendations for the successful usage of digital technology opportunities. Using regression analysis, the impact of the digital economy on economic growth was determined. The analysis showed a direct relationship between the indicators (r = 0.857) and a high closeness of the relationship on the Cheddock scale. The outcomes showed that during the last eight years (2015–2023), there has not been a significant growth in the ICT Development Index in Azerbaijan. According to the ICT Development Index, Azerbaijan ranks 87th, the Development Index of e-government – 83rd, and the Network Readiness Index – 75th in the world. The results stressed the necessity of state support for the digital economy in Azerbaijan to solve problems in this area and the significance of applying the progressive foreign countries’ experience in the digitalization of the economy. The study examines the factors influencing the development of the digital economy in Azerbaijan and offers proposals and recommendations for the effective use of digital technologies that have practical and scientific significance.

Type of the article: Research Article

Abstract
This study examines the association between multidimensional digital transformation and national startup ecosystem performance across 23 European Union economies, comparing EU11 with 12 selected EU15 economies from 2017 to 2024. The balanced panel contains 184 country-year observations. Principal component analysis is used to construct three composite indicators: the Digital Services Index, Digital Connectivity Index, and Digital Human Capital Index. The indices demonstrate satisfactory factorial adequacy, internal consistency, and one-component structures supported by parallel analysis. Their associations with startup ecosystem performance are estimated using two-way fixed-effects models. Because the panel contains only 23 country clusters, the principal inference uses CR2 bias-reduced country-clustered standard errors with Satterthwaite-adjusted degrees of freedom. In the full-sample specification, DSI has a positive but only marginally significant association with startup ecosystem performance (β = 0.0834, p = 0.082), while DCI, DHCI, and e-government are statistically insignificant. R&D intensity has a negative contemporaneous coefficient that is also marginally significant (β = −0.0145, p = 0.053). Regional heterogeneity is jointly significant and is concentrated primarily in digital connectivity: DCI is negatively associated with startup ecosystem performance in the EU11 group, whereas its total slope is approximately zero in the selected EU15 group. DHCI has a positive total slope within the selected EU15 group, although the difference between the EU15 and EU11 slopes is not statistically significant. A one-year-lagged specification produces a positive but marginal DSI coefficient and does not identify statistically significant associations for the remaining predictors. These estimates should be interpreted as conditional associations rather than causal effects.