Effectiveness of anti-inflation policy that ensures economic growth: Evidence from post-Soviet countries

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There 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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    • Table 1. Descriptive statistics
    • Table 2. Consumer price index forecasted value for 2023–2024
    • Table 3. Short-run dependency coefficients
    • Table 4. Long-run dependency coefficients
    • Table 5. Regression results for Azerbaijan
    • Table 6. Regression results for Belarus
    • Table 7. Regression results for Estonia
    • Table 8. Regression results for Georgia
    • Table 9. Regression results for Kazakhstan
    • Table 10. Regression results for Kyrgyzstan
    • Table 11. Regression results for Latvia
    • Table 12. Regression results for Lithuania
    • Table 13. Regression results for Moldova
    • Table 14. Regression results for Tajikistan
    • Table 15. Regression results for Ukraine
    • Table 16. Regression results for Uzbekistan
    • Conceptualization
      Atik Kerimov, Azer Babayev, Nigar Ashurbayli-Huseynova, Aybaniz Gubadova
    • Formal Analysis
      Atik Kerimov, Nigar Ashurbayli-Huseynova
    • Methodology
      Atik Kerimov, Azer Babayev
    • Supervision
      Atik Kerimov
    • Writing – review & editing
      Atik Kerimov
    • Funding acquisition
      Azer Babayev, Aybaniz Gubadova
    • Project administration
      Azer Babayev
    • Writing – original draft
      Azer Babayev, Nigar Ashurbayli-Huseynova
    • Data curation
      Nigar Ashurbayli-Huseynova, Aybaniz Gubadova
    • Investigation
      Nigar Ashurbayli-Huseynova, Aybaniz Gubadova
    • Software
      Nigar Ashurbayli-Huseynova
    • Validation
      Nigar Ashurbayli-Huseynova, Aybaniz Gubadova
    • Resources
      Aybaniz Gubadova
    • Visualization
      Aybaniz Gubadova