Nigar Ashurbayli-Huseynova
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Effectiveness of anti-inflation policy that ensures economic growth: Evidence from post-Soviet countries
Atik Kerimov , Azer Babayev , Nigar Ashurbayli-Huseynova , Aybaniz Gubadova doi: http://dx.doi.org/10.21511/ppm.21(2).2023.50Problems and Perspectives in Management Volume 21, 2023 Issue #2 pp. 542-555
Views: 419 Downloads: 142 TO CITE АНОТАЦІЯThere are active debates on the scale of inflation-economic growth causality in the short- and long-term perspectives and factors affecting the correlation and effectiveness of anti-inflationary measures depending on initial economic conditions. These scientific debates result in controversial results. This study aims to explore short- and long-run relationships in the inflation-economic growth chain of 12 post-Soviet countries (Azerbaijan, Estonia, Latvia, Lithuania, Kazakhstan, Kyrgyzstan, Tajikistan, Uzbekistan, Belarus, Moldova, Ukraine, and Georgia) to determine the most effective system of anti-inflationary policy. The paper employed statistical analysis and trend line extrapolation (analysis of inflationary trends in 2000–2021 and forecast for 2022–2024), pooled mean group of the autoregressive distributed lag model in the Stata 14.2/SE software (identification of the short and long-run coefficients characterizing relationships between inflation and economic growth), and ordinary least squares regression (country-specific modeling results). Statistical analysis showed that Latvia, Lithuania, and Estonia have the most effective anti-inflationary policy; Azerbaijan, Kazakhstan, Kyrgyzstan, and Moldova demonstrate moderate effectiveness, and the other countries have low effectiveness. It is also established that in the long run, a 1% increase in inflation results in a 0.195% decrease in GDP growth with a 99% confidence probability, while in the short run, this causal relationship is insignificant. Country-specific modeling results revealed that within 12 post-Soviet countries, economic growth in Kazakhstan, Lithuania, and Ukraine in a short-term perspective depends on inflation dynamics. According to the modeling results, Lithuania has the most effective anti-inflationary policy to ensure sustainable economic growth.
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Interconnection between bank capitalization and macroeconomic stability in the countries of South-West Asia
Nigar Ashurbayli-Huseynova , Yevgeniya Garmidarova doi: http://dx.doi.org/10.21511/bbs.18(4).2023.22Banks and Bank Systems Volume 18, 2023 Issue #4 pp. 268-280
Views: 260 Downloads: 44 TO CITE АНОТАЦІЯThe paper aims to define the specifics of the mutual interconnection between bank capitalization and indicators of macroeconomic stability. This is achieved by the following methods: grouping, analysis and synthesis, analysis of descriptive statistics, and canonical correlation analysis. The study was carried out based on eight bank capitalization indicators and five macroeconomic stability indicators in seventeen South-West Asian countries from 2010 to 2020. The information base of the research is the dataset from the World Bank. The selected list of indicators is determined by the availability of statistical information for the countries participating in the study. It was found that there is a close canonical correlation between the level of bank capitalization and the macroeconomic stability of the countries under investigation – 0.97 (2010) and 0.99 (2020). The variation of the investigated indicators of macroeconomic stability (68.95% (2010) and 70.64% (2020)) is determined by the change in bank capitalization indicators. On the other hand, the difference in macroeconomic stability indicators of countries by 48.66% (2010) and 42.79% (2020) is due to changes in bank capitalization indicators. Four indicators exert the most significant favorable influence on the level of bank capitalization: Bank return on assets – 0.303 (2010) and 13.033 (2020), Bank return on equity – 0.446 (2010) and 13.387 (2020), Bank regulatory capital to risk-weighted assets – 0.812 (2010), and Bank deposits to GDP – 1.580 (2020). The macroeconomic stability of countries is determined by two indicators: GNI – 3.311 (2010) and 3.461 (2020); GDP – 4.748 (2010) and 4.672 (2020).
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