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Rational small business management necessitates the development of a system for recording important internal information. Companies are obliged to collect statistical data that mainly serves fiscal needs. Exemplary use of such significant data entails financial liquidity (LIQt) and debt recovery efficiency (EVINDt) measures. This work presents constructions of such measures and the manner of their application when they accrue in the form of time series. Both these measures should remain in feedback. Feedback complicates the forecasting of each of the variables that make up this relationship. In the existing forecasting practice, forecasts of such variables have been estimated using empirical equations of a reduced-form model. Such forecasts—in the case of an econometric micromodel—exhibit synchronization properties. This paper presents an empirical system of interdependent equations describing the relationship between financial liquidity and debt collection efficiency. An econometric model was used to build forecasts for both of these characteristics in a small business. An iterative method of forecasting from structural-form equations was used, which guarantees synchronization of forecasts under feedback conditions. The current use of the reduced form of the model to build such forecasts results in divergent forecasts that are not useful in small business management. They can also lead to wrong decisions. In the case under consideration, the forecast value synchronization (convergence) was obtained after five to nine iterations. The more distant the forecasted period is, the greater the number of iterations required to synchronize the forecasts.

Financial Liquidity and Debt Recovery Efficiency Forecasting in a Small Industrial Enterprise