This paper aims to examine the effect of FDI on the unemployment rate in Azerbaijan from 1993 to 2022. The Augmented Dickey–Fuller (ADF) unit root test, Phillips-Perron (PP) unit root test, ARDL co-integration test, and Granger Causality test have been employed for the statistical analysis. The results of the ARDL approach indicated a significant relationship between FDI and the unemployment rate. The outcomes of the long-run analysis noted a negative and significant relationship between FDI and unemployment. In contrast, the short-run test showed a negative but insignificant relationship between FDI and unemployment. Moreover, the findings of the Granger causality test showed no causal link running from FDI to unemployment, meaning the null hypothesis that FDI does not Granger cause unemployment should be accepted. This suggests that FDI leads to employment in Azerbaijan. Conversely, a causal relationship running from unemployment to FDI was confirmed, indicating that the null hypothesis that unemployment does not Granger cause FDI should be rejected, and the alternative hypothesis that unemployment does Granger cause FDI must be accepted. This implies that the unemployment rate influences FDI inflow into the country. Hence, it has been demonstrated that FDI inflows decreased Azerbaijan's unemployment rate during the examined period.

The purpose of this paper is to systematize and justify the factors for the effective implementation of digitalization to ensure the innovative development of agriculture in Azerbaijan. Based on the survey completed by 1,513 senior managers of agricultural enterprises in Azerbaijan, the key factors and barriers to digitalization of agriculture were substantiated: the cost of introducing and using digital technologies, unregulated legislative processes of digitalization of the industry, and the level of cybersecurity. The levels of development of digitalization of the country's agricultural sector have been determined and empirically substantiated the qualitative nature of the influence of digitalization factors on the innovative development of agricultural enterprises using the regression modeling method. The results obtained can help develop a state strategy for enhancing the digitalization of the country's agricultural sector to ensure its innovative development, food security, and diversifying the economy.