R&D expenditure and nominal GDP growth in Uzbekistan: Exploratory evidence from first difference and distributed lag models

Innovations play an inevitable role in achieving macroeconomic growth of countries, and innovative activity is perceived as a source of sustainable development. This paper’s main objective is to explore the impact of innovation determinants on the macroeconomic development of the EU (28) member countries and identify key problem areas distorting sustainable development and growth of these countries. The research analysis is performed using panel data regression models estimated from 2010 to 2018. Innovation potential was quantified using selected indicators, such as patent granted, high-tech exports, gross domestic expenditures on R&D, government expenditure on education, direct investment, gross fixed capital, and tertiary educational attainment. Such indicators as real GDP per capita and GNI per capita were applied to measure economic growth. The results provide evidence of a statistically significant relationship between innovation and economic growth (p < 0.01). Therefore, both research hypotheses were accepted. Based on innovation potential assessment, the statistically significant impact of five indicators were confirmed (high-tech exports, gross domestic expenditure on R&D, government expenditure on education, direct investment, and tertiary educational attainment). In this backdrop, the most significant effect was revealed for variable gross domestic expenditure on R&D (0.5343). The findings lead to the conclusion that the EU’s and national innovation policies and initiatives should aim to create framework conditions that favor the innovation environment and increase R&D expenditure to endorse real economic growth.

Acknowledgment
This article has been prepared within the research project VEGA No. 1/0279/19 “Model approaches to increase performance and competitiveness in the European area in the context of sustainable development”.

Corporate performance is one of the core pillars of accelerating the economic growth of any economy. There are some direct and indirect components of corporate performance. This study is conducted to measure the impact of indirect factors, such as corporate voluntary disclosures, on corporate performance. A sample of 872 annual reports is investigated. A content analysis has been conducted to measure voluntary disclosure. The study employs the short panel data, fixed model regression, and Panel Corrected Standard Error (PCSE). The analysis indicates that corporate voluntary disclosure has influenced the return on assets with a regression coefficient of 0.0724 at p ≤ 0.01. Corporate voluntary disclosure in the transitional economy significantly influences corporate performance. However, the volume of corporate voluntary reporting in energy-related disclosure and climate-related disclosure is minimal, as the mean is only 2.21% and 2.31%. This implies that the government of the transitional economy may focus on persuading corporations to disclose additional information besides mandatory disclosure. In addition, indirect determinant of corporate performance, like corporate voluntary disclosure, brings sustainability to corporate performance, which further assists the transitional economy in shifting its economic status from one dimension to another.

Acknowledgment
The authors are very thankful to the Institute of Advanced Research, United International University, Bangladesh, for providing partial funds to complete this empirical study.
This project is partially funded by the Institute for Advanced Research Publication Grant of United International University, Ref. No.: IAR-2024-Pub-069.

Type of the article: Research Article

Abstract
This study investigates the nonlinear dynamics of the relationship between foreign trade and carbon dioxide (CO₂) emissions in Uzbekistan over the period 1997–2024. The analysis employs annual time-series data from the World Bank’s World Development Indicators (WDI) database, including three key variables: CO₂ emissions per capita (tonnes), exports of goods and services (current USD), and imports of goods and services (current USD). Using the Markov switching regression (MSR) model, the study identifies two distinct economic states: an export-oriented regime (Regime 1) characterized by high industrial production and export activity, and an import-driven regime (Regime 2) characterized by domestic consumption patterns and elevated import flows.
The empirical results demonstrate that the export–emissions relationship is regime-dependent: exports have a statistically significant positive effect on CO₂ emissions only during export-oriented periods (β = 1.54 × 10–10, p < 0.01), while this relationship becomes insignificant during import-driven periods (β = 5.20 × 10–11, p = 0.378). In contrast, imports consistently reduce CO₂ emissions across both regimes (Regime 1: β = −1.05×10–10; Regime 2: β = −1.07 × 10–10, both p < 0.01), indicating a stable import-substitution effect that displaces domestic production-related emissions. The transition probability analysis reveals high persistence in both regimes (P₁₁ = 79.69%, P₂₂ = 81.22%), with structural shifts occurring approximately every five years (expected durations: 4.92 years for Regime 1 and 5.32 years for Regime 2). These findings confirm that the trade–emissions relationship in Uzbekistan is nonlinear and regime-dependent, necessitating the development of regime-sensitive environmental and trade policies.