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

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.


INTRODUCTION
The impact of inflation on economic dynamics has been the focus of scientists' attention for the past several decades. During this period, new theoretical models were developed to explain the relationships in the "inflation-economic growth" chain and the nature of these relationships was empirically substantiated. It is traditionally considered that there is an inverse relationship between economic growth and inflation because excessive inflation leads to a rapid deterioration of economic dynamics and "absorbs" GDP growth. Even intense economic growth can act as a trigger for unwinding an inflationary spiral due to the inability of supply to meet rapidly growing consumer demands, rising wages, and consumer expectations for price increases.
At the same time, it is possible to have both low inflation and positive economic growth. In some cases, moderate inflation can even act as a driver of economic growth. The stimulating effect of inflation can be achieved only in conditions of sustainable economic growth and a permanent increase in production capacity, which is synchronized with the growth of aggregate demand. Despite an established theoretical paradigm for identifying relationships in the "inflation-economic growth" chain, many empirical studies testify to rather ambiguous and atypical causal patterns between these variables. This proves that critical determinants of the vector of causality between the components of the described chain are historical prerequisites, institutional capacity, and geographical conditioning.
Thus, evaluating the effectiveness of the state's anti-inflationary policy in the context of ensuring economic growth looks like a rather complex task. It should be empirically determined in the short and long run with consideration of the concomitant influence of other externalities as well as within a limited geographical sample, characterized by the convergence of historical prerequisites and institutional development. Considering all the parameters mentioned above, studying the effectiveness of the antiinflationary policy will not only empirically reveal the relationships between the variables of the model but also substantiate the country-specific pattern, which will allow choosing anti-inflationary measures on a more scientifically-ground basis.

LITERATURE REVIEW
The effectiveness of the anti-inflation policy and the prerequisites for choosing tools to overcome the destructive impact of inflation depends on several vital prerequisites. In particular, Bardy and Rubens (2022) note that policy goals can be achieved if each has its own instrument and the overall goal of the policy is agreed upon in both the short and long term. This approach determines the need to differentiate between anti-inflationary measures of operational intervention and strategic management. That is why it is crucial to consider this causality separately in the short and long run when conducting empirical research on determining the relationship in the inflation-economic growth chain. Solow (1956), Sala-i-Martin (1994), and Barro (1995) laid the foundations of the relationship between economic growth and the intensity of inflationary processes based on a time-differentiated approach. All studies found a negative impact of inflation on economic dynamics in the long run if the rate of economic growth lags behind the rate of capital accumulation and the growth of production productivity. The investigations were conducted on panel data for different groups of countries, making a generalized result possible. Specifically, Barro (1995) sampled 120 units and found the negative impact of inflation on the economic growth rate.
Nevertheless, empirical results eventually demonstrate controversial evidence regarding temporal patterns of inflation influence on macroeconomic indicators. Using the autoregressive distributed lag model, the absence of a statistically significant effect of inflation on investment activity was confirmed in the long run. However, there is an inverse relationship between inflation and the outcome variable in the short run (Olonila et al., 2023). In contrast, Bouyacoub (2022) investigated the relationship between inflation and economic growth in 20 countries in the Middle East and North Africa (MENA) for 2000-2020. The same econometric instrument did not reveal a statistically significant relationship between the variables in the short run but confirmed this relationship in the long run. In turn, the case of Sri Lanka confirmed the negative impact of the inflation increase both in short-and long-run perspectives: a 1% increase in inflation stagnated economic growth by 3,427.94 mln USD in the short run and 107,263.8 mln USD in the long run (Atigala et al., 2022). These controversial modeling results might be explained not only by temporal patterns but also by geographical patterns and specific features of macroeconomic situation. Khan and Senhadji (2001) researched the inflation-economic growth causality chain in 140 countries during 1960-1998. They revealed different thresholds of acceptable inflation levels, which do not enormously damage the economic growth rate. Specifically, up to 3% inflation is not a severe obstacle to economic well-being in developed countries and 11-12% in developing countries, while the average indicator for the whole country sample is up to 9%. Kremer et al. (2013) revealed different inflation thresholds for industrialized and non-industrialized countries. It is empirically confirmed that inflation of up to 2.5% and 17.3% does not harm economic growth.
The consequences of inflation are more dramatic for economic growth if the initial level of inflation is high (Barro, 1995). Thus, regarding inflation-economic growth causality, not just temporal patterns but also historical inflationary trends do matter. It is also substantiated that economics, including monetary policy, largely depends on the historical prerequisites of developing socio-economic systems, the state of development of markets, and the institutional environment (Gentle, 2022(Gentle, , 2023. In addition, slight and moderate inflation does not harm economic growth, while there is still a threshold after which economic growth becomes damaged (Bruno & Easterly, 1995). These empirical findings provide an assumption about the non-linear character of inflation-economic growth causality for some countries.
Sala-i-Martin (1994) considered a shortcoming in the predictive quality of cross-country research on inflation-economic growth coherence because of the high level of convergence between macroeconomic trends in countries with common socioeconomic history. This drawback might be eliminated in case of the realization of separate models for the specific country and country sample and its comparison.
The country-specific approach in inflation-economic growth causality is also strongly supported by Mallik and Chowdhury (2001). They examined relationships between economic growth and inflation in four South Asian countries (Bangladesh, India, Pakistan, and Sri Lanka). The study revealed that in contrast to international monetary organizations' recommendations, reducing inflation to a low or zero level in these countries might harm the economic growth rate. Basically, economic growth and inflation are positively correlated in this country-specific case, and inflation is more affected by the volatility of the economic growth rate than vice versa. Therefore, the recommendation for this group of countries is to support moderate inflation instead of its complete elimination.
Besides historical and geographic conditionality, these factors can affect the effectiveness of the anti-inflation policy scientists: • initial economic conditions -price stability and economic sustainability depend on the country's involvement in foreign trade; they are determined by capital market development and structural changes ( It is also possible that the approach to inflation management changed after some crisis. Therefore, the attention of academicians increases to the inflation-economic growth causality after some crisis. Specifically, Sinaga (2022) examines the impact of inflationary processes on the dynamics of economic growth in the context of the unfolding of the COVID-19 pandemic in Indonesia. The study established that a 1% increase in the level of consumer prices during this period led to an intensification of economic growth rates by 0.187%. Thus, there is a direct relationship between the dependent and explanatory variables.
Moreover, Jałtuszyk (2023) developed a comparison of inflationary trends after the 2007-2008 global financial crisis and 2020-2021 COVID-19 pandemic. The global financial crisis significantly lower contributed to the price instability than the global pandemic. The reason for such a situation might lie in the field of supply chain break that stimulated enormous consumer price increases. Izvorski et al. (2023) pointed out the consequences of war in Ukraine on the inflationary trends in Europe and Central Asia. They declared that the region's inflation level reached its 20-years-old level. According to the evaluation of the World Bank experts, economic growth in developing countries of Europe and Central Asia in 2023 continued to decrease because of economic, political, social, and monetary instability in the region. It was also noticed that "median annual inflation in the emerging markets and developing economies of Europe and Central Asia in September 2022 was 15.9 %." It is a dramatic level of inflation that has not been recorded since 1999.
Therefore, based on the literature review, the inflation and economic growth causal relationship has been in the focus of scientific attention for a long time, but the research results are often controversial. These relationships also depend on numerous country-specific institutional, social, and industrial factors. However, it is advisable to carry out a more detailed and in-depth empirical analysis of the specified issue to determine a more specific set of relevant drivers and inhibitors for ensuring the effectiveness of anti-inflationary policy in post-Soviet countries.
Thus, the main task of this study is to explore shortand long-run relationships in the inflation-economic growth chain in post-Soviet countries to determine the most effective system of anti-inflationary policy.

METHODOLOGY
This study follows several stages to achieve set research tasks. Stage 1 is the analysis of general trends in the dynamics of inflationary processes in the studied countries for 2000-2022, formalization of the functional form of the dependence of the change in the indicator (consumer price index) over time (trend line function), and forecast-ing the level of inflation in the studied post-Soviet countries for 2023-2024.
Stage 2 is the determination of the relationship between the dynamics of inflationary processes (consumer price index, explanatory variable) and parameters of economic growth (GDP growth, dependent variable) using autoregression modeling tools, in particular, the pooled mean group (PMG) method in the Stata 14.2/SE software product. Pooled mean group estimator allows clarifying long-run coefficients for the whole country sample. Therefore, all beta coefficients are equal across all panels. Nevertheless, PMG estimators allow obtaining short-run coefficients for the whole panel and for each country separately. The appropriateness of choosing GDP growth as a key indicator of economic dynamics is confirmed by numerous studies ( Tahat Stage 3 is a determination of individual coefficients characterizing the relationship between the dynamics of inflationary processes and parameters of economic growth using least squares regression modeling in the Stata 14.2/SE software product. Each of these models is also supplemented with the control variables mentioned in the previous step. Summary descriptive statistics for all variables used in the study are presented in Table 1.
According to the results of the preliminary analysis of the model variables, the sample is strongly balanced, and there are no missed observations. This allows for asserting the satisfactory quality of the data set for modeling.

RESULTS
In order to realize the main research goal, it is necessary to carry out the sequential implementation of several stages. The first stage involves the analysis of general trends in the dynamics of inflationary processes in the studied countries for 2000-2022, as well as forecasting the levels of the consumer price index for 2023-2024. To implement this stage, the dynamics of the inflation level for 2000-2022 for every 12 post-Soviet countries were formalized using a trend line. For each of the 12 cases available in the MS Excel package, trend lines were constructed -exponential, linear, logarithmic, polynomial, and power. In the next step, the most effective functional form of the trend line was chosen. The choice was made based on the coefficient of determination (R²) value. The coefficient of determination demonstrates the predictive quality of the trend line equations; that is, it reflects the probability of variation of the resulting variable as a result of variation of the factor variable. The coefficient of determination varies in the range [0; 1]; a higher coefficient value confirms the better quality of the model. Table 2 shows the forecasting results.
According to the analysis of inflation for 2000-2022 in 12 studied post-Soviet countries Latvia, Lithuania, and Estonia implement the most effective anti-inflation management. The average annual growth rate of consumer prices in these countries for 2000-2022 did not exceed 3.5%. The countries with an average effectiveness of anti-inflation policy include Azerbaijan, Kazakhstan, Kyrgyzstan, and Moldova. The average annual inflation rate in these countries is not higher than 8.6%. In the rest of the countries, anti-inflationary management is characterized by low efficiency.
According to Table 2, the trend lines of the inflationary processes of Belarus, Kyrgyzstan, Moldova, and Uzbekistan are characterized by the highest quality of predictiveness. The high value of the coefficient of determination proves that in the mentioned countries, the dynamics of inflationary processes are determined by the internal patterns of changes in the consumer price index. At the same time, for the rest of the countries for which the value of the coefficient of determination is less than 0.5, inflationary processes are determined not only by trend patterns but also by the influence of external factors. Therefore, it is advisable to use more complex modeling tools to forecast their volatility.
At the same time, in 2022, compared to 2021, the situation in the field of price stability worsened in almost all countries. A decrease in the rate of inflation was observed only in Estonia. In addition, in the studied countries, an increase in the level of inflation is also predicted in 2023-2024. Thus, the lowest inflation in 2024, according to forecast data, will be in Estonia -6.64%, and the highest in  Ukraine -29.12%. Such dynamics of inflationary processes are connected with the socio-economic instability in the region.
In order to determine the relationship between the dynamics of inflationary processes and economic growth, regression modeling is performed on panel data using the pooled mean group (PMG) method in the Stata 14.2/SE software product. The modeling results allow for determining the relationships between variables for the entire sample of countries in both the short (Table 3) and the long run (Table 4). Note: *** -significance at a 1% level; ** -significance at a 5% level.
The analysis of relationships between variables in the short-term perspective proved the absence of a statistically significant effect of changes in the inflation rate on GDP growth rates for the entire panel of 12 post-Soviet countries for 2000-2022.
Nevertheless, statistically significant relationships were established between the dependent variable and some independent control variables, namely: • a 1% increase in total government final consumption expenditure leads to a 1.61% reduction in economic growth with a 99% confidence probability; such a result indicates the elasticity of economic growth to changes in current government expenditures and, therefore, an excessive increase of this item of expenditures in post-Soviet countries is ineffective; • a 1% increase in gross fixed capital formation leads to a 0.41% increase in GDP with a 95% confidence probability. Note: *** -significance at a 1% level; * -significance at a 10% level.
However, the relationships between the variables of the model are somewhat transformed in the long run, namely: • an increase in the level of consumer prices by 1% leads to a reduction in GDP by 0.2% in the long run in the studied post-Soviet countries with a 99% confidence probability, i.e., inflation reduces the level of economic dynamics, but this effect is not large-scale; • long-term drivers of economic growth in the studied countries are also the growth of the gross fixed capital formation and trade openness: a 1% increase in independent variables leads to an increase in GDP by 0.35% and 0.03%, respectively. Therefore, in 12 post-Soviet countries, inflation is an inhibitor of the economic dynamics of the average power of influence. At the same time, it is advisable to conduct regression modeling for each country of the sample separately to identify more country-specific tendencies. The simulation results are presented in Tables 5-16.
The simulation results for Azerbaijan (Table 5) show the absence of a statistically significant effect of inflation on economic growth. At the same time, a statistically significant influence of the control variables on the dynamics of GDP growth was found: a 1% share of agricultural land leads to a reduction of GDP by 34.93% with a confidence probability of 99%; an increase in trade turnover by 1% determines the growth of GDP by 0.51% with a 95% confidence probability.
Similarly to the previous country, no statistically significant relationship between inflation rates and economic growth has been established for Belarus (Table 6). At the same time, a statistically significant effect of almost all control variables was found: a 1% increase in government expenditures, gross fixed capital formation, and trade turnover led to an increase in GDP by 1.83%, 0.69%, and 0.15%, respectively.
Modeling results for Estonia (Table 7) and Georgia (Table 8) showed no statistically significant relationships between all model variables. Table 9 shows that the variation of the independent variables explains 81.72% of the variation of the dependent variable. In addition, it was established that a 1% increase in the level of the consumer Note: *** -significance at a 1% level; ** -significance at a 5% level. Note: *** -significance at a 1% level; ** -significance at a 5% level; * -significance at a 10% level. price index in Kazakhstan causes a decrease in GDP by 0.33% with a 95% confidence probability. In contrast to Azerbaijan, an increase in the area of agricultural land by 1% leads to an increase in GDP by 3.17%. For Kazakhstan, the driver of economic growth is also the increase in turnover (a 1% increase in the independent variable causes a 0.28% increase in the dependent variable).
The simulation results for Kyrgyzstan (Table 10) also did not reveal a statistically significant impact of rising inflation on economic growth. At the same time, excessive growth of public spending is a significant inhibitor of economic dynamics in the country: a 1% increase in gross government final expenditure leads to a 2.05% reduction in GDP with a 95% confidence probability. Note: *** -significance at a 1% level; ** -significance at a 5% level. Note: ** -significance at a 5% level. Note: *** -significance at a 1% level; ** -significance at a 5% level.
According to Table 11, there is no statistically significant impact of the inflation level on economic growth for Latvia. At the same time, the expansion of the area of agricultural land acts as an inhibitor of economic growth in the country (a 1% increase in the independent indicator leads to a reduction in economic growth by 2.01%). Instead, a 1% increase in the gross accumulation of fixed capital and trade turnover increases GDP growth rates by 1.36% and 0.32%, respectively.
Analysis of the results of regression modeling for Lithuania (Table 12) confirms the negative impact of the increase in the level of consumer prices, which is statistically significant at a 10% confidence interval -an increase in the independent variable by 1% leads to a decrease in GDP by 0.99%. Thus, Lithuania has a unit elasticity between inflation and economic growth. Among the control varia-bles, the positive impact of the growth of the gross accumulation of fixed capital on economic growth was confirmed (a 1% increase in the independent variable leads to a 1.35% increase in the dependent variable with a 95% confidence probability).
The results of the regression modeling for Moldova (Table 13) did not prove the existence of a statistically significant relationship between the variables. It is also worth noting that the quality of this model is the worst among 12 countries since the variation of the selected variables explains only 19.4% of the variation in GDP growth.
For Tajikistan (Table 14), a statistically significant impact of changes in inflation rates on the dynamics of GDP changes has yet to be empirically confirmed. However, among the control variables, a statistically significant inhibitor of economic Note: ** -significance at a 5% level; * -significance at a 10% level.  growth is the growth of gross government spending on consumption, which causes a decrease in GDP by 0.52%.
The simulation results for Ukraine (Table 15) prove the existence of an inverse relationship between inflation rates and GDP growth rates; namely: a 1% increase in consumer prices leads to a loss of economic growth rates by 0.28% with a 95% confidence probability. In addition, for Ukraine, the relevance of the contribution of the increase in trade turnover to economic growth was established: a 1% increase in the independent variable leads to an improvement in the dependent variable by 0.28% with a 90% confidence probability.
For Uzbekistan (Table 16), a statistically significant relationship between inflationary processes and economic growth has not been empirically confirmed; however, a 1% increase in trade turnover leads to an increase in the economic growth rate by 0.32%.

DISCUSSION
The These research results correlate with Khan and Senhadji (2001) in differentiating the destructive impact of inflation on economic growth with consideration of the level of economic development: economic growth in developed countries is more resistant to inflationary damages. Barro (1995) also went to a familiar conclusion that a higher initial level of inflation contributes to a more harmful influence on economic growth. Thus, Latvia, Lithuania, and Estonia have the most effective anti-inflationary policies within the whole country sample. This also supports the assumption that initial levels of economic development (developed countries with stable economic dynamics) and inflationary trends (low or moderate inflation levels in the long run) are significant determinants of anti-inflationary effectiveness.
The results of modeling the relationship between the inflation rate and economic growth for a panel Note: ** -significance at a 5% level; * -significance at a 10% level.  2023), on the contrary, empirically confirmed a statistically significant negative im-pact of inflation on the performance indicator in the short term, while in the long term, this relationship turned out to be statistically insignificant. Therefore, in terms of clarification of the long-run inflation-economic growth causality, geographical and historical determinants lose their relevance because most of the analyzed empirical research confirmed the negative impact of inflation on economic growth rate in a long-term perspective despite the differentiation of the research data sample.
Regression modeling for each of the 12 post-Soviet countries separately proved that the economic growth of such countries as Kazakhstan (coefficient value -0.33%), Lithuania (-0.99%), and Ukraine (-0.28%) depends inversely on the dynamics of inflationary processes. The positive impact of foreign trade on economic dynamics has been empirically confirmed in Azerbaijan, Belarus, Kazakhstan, Latvia, Ukraine, and Uzbekistan; gross fixed capital formation -Belarus, Latvia, and Lithuania; public expenditure on final consumption -Belarus; shares of agricultural land -Kazakhstan. At the same time, the increase in the share of agricultural land is an inhibitor of economic growth in Latvia and Azerbaijan, and the growth of public expenditures on final consumption is in Kyrgyzstan and Tajikistan.
Taking into account the sensitivity of the rates of economic growth to an increase in the level of inflation even in the short term, as well as taking into account the value of the actual and forecasted values of inflation, the anti-inflationary management system in Lithuania is the most effective among the 12 studied countries (despite the unit elasticity between the indicators, the country is characterized by a low level of inflation). In contrast, Kazakhstan and Ukraine are characterized by low efficiency (the economic growth sensitivity to price fluctuations determines the criticality of this state of affairs).

CONCLUSION
The aim of the study is to explore short-and long-run relationships in the inflation-economic growth chain in post-Soviet countries and determine the most effective system of anti-inflationary policy. The empirical results proved a moderate-scale inverse relationship between inflation and economic growth in the long run while rejected the assumption of the same causality in the short run for the 12 post-Soviet countries.
Country-specific modeling results revealed that economic growth in Kazakhstan, Lithuania, and Ukraine is, even in the short run, quite sensitive to inflation growth. These results show that long-term inflation targeting is a unique goal to contribute to economic growth sustainability. It depends on geographical, social, economic, political, institutional, industrial, and other determinants but only to some extent. Specifically, all these factors identify the scale of these causalities (high, moderate, or low) but not their reliability. Nevertheless, the operational choice of anti-inflationary measures and instruments strongly relies on country-specific and historical proxies because, in the short run for the whole panel, there is no statistical significance of the inflation-economic growth causality.
At the same time, country-by-country modeling results allow for revealing these cases. Short-and long-run economic growth sensitivity to inflation fluctuations stipulates governors build even more severe anti-inflation policies. Moreover, a combination of short-run economic growth to inflation sensitivity and low historical, actual, and forecasted inflation levels (case of Lithuania) indicates the effectiveness of anti-inflationary policy in the country. The Lithuanian model might be considered a benchmark for the whole country sample and can be used to improve anti-inflationary policy in other 11 post-Soviet countries.