Table 1.
Fragment of static data of intellectual analysis of dynamic stability of national financial monitoring system subjects to money laundering.
Table 2.
Normalized values of regresants Financial Freedom and Currency in Circulation (% GDP).
Fig 1.
Dynamics of the average level of the integrated indicator in the characteristics of the country’s financial system propensity to ALM for the period from 2000 to 2020.
Table 3.
Dynamics of the integrated indicator of the characteristics of the country’s financial system propensity to ALM.
Fig 2.
Comparability of the integrated indicator of the characteristics of the country’s financial system propensity to ALM for the period from 2000 to 2020 in terms of countries.
Table 4.
Analysis of the dynamic stability of the national financial monitoring system subjects to money laundering based on a binary approach.
Table 5.
Vector autoregression estimates.
Fig 3.
Visualization of the reflection of the country’s financial system propensity to ALM under the influence of regressors GIt, IEFt, MSCPSt depending on the time lag.
Fig 4.
Distribution of the country’s financial system propensity balances to ALM, of regressors Index of economic freedom, Government Integrity, Monetary Sector credit to private sector (% GDP).
Table 6.
Vector autoregression estimates.
Table 7.
Statistically significant coefficients before the influential indicators of the country’s financial system propensity to ALM.