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.

This work aims to verify an authorial forecasting method from a system of interdependent equations, which is based on empirical equations of the structural form and is mainly intended for econometric micromodels. The prediction procedure will be analogous to the so-called chain prediction that is used for recursive models. The difference—compared with the prediction from a recursive model—entails the necessity of using one of the reduced-form empirical equations to begin the procedure of constructing a sequence of forecasts from successive structural-form empirical equations. The research results presented above indicate that the above-proposed iterative forecasting method from structural-form equations of a system of interdependent equations guarantees synchronization of forecasts as part of a closed cycle of relations. A different number of iterations is required to obtain convergent forecasts. It can be noticed that the further ahead the forecasted period is, the more iterations should be carried out to obtain convergent forecasts. Small business management with the use of forecasting can be done remotely. Rapid updates of statistical information will require cloud-based communication. Completion of data in a cloud will allow, on one hand, accurate assessment of expired forecasts and, on the other, to update the predictor equations. This can be carried out at any place with Internet access.

The rural e-payment market in China is becoming one of the important topics in the research field because of its contribution to the efficiency of fund flows in the economy. Further development of the rural e-payment market mainly depends on its partners’ acceptance. In March 2020, 776.08 million people were using mobile payments in China. After the COVID-19 pandemic in China, the Payment and Clearing Association of China launched an action to encourage citizens to use mobile payments. In this article evolutionary game theory is presented. The benefits of e-payments between financial institutions and users are studied. Based on the analysis of the partners’ selection of costs and profits as well as other factors, important conclusions were drawn. The growth of the rural economy is beneficial to the change of the partners’ behavior in the rural e-payment market. Dynamic evolution of the partners’ behavior makes the supply and demand for rural e-payment services consistent. In order to create more benefits, financial institutions will lead the move to merge the rural e-payment market with the China National Advanced Payment System. These research results are beneficial for its growth by developing strategies to encourage more partners to take part in the rural e-payment market in China.

This work will present an empirical econometric model describing an enterprise within the category of medium-sized companies (according to European Union classification). The company, code-named ENERGY, carries out a manufacturing, commercial, and service business activity. The statistical data used was in the form of quarterly time series, containing 24 statistical observations from the years 2008–2013. A hypothetical model of the enterprise is a system of interdependent equations. The econometric model is composed of seven stochastic equations. The empirical model is missing the equation describing investments in the enterprise. It results from the fact, that during the years 2008–2013 the company suffered meagre investments. Investment output equation, therefore, does not provide any relevant systemic information for the management, since most statistical information in the time series assumes zero values. An empirical model of the company ENERGY is a system of interdependent equations, with statistically significant feedback between labour efficiency (EFEMP) and the average pay per 1 employee (APAY). Additionally, there is recurrence of the relationships between the fixed assets (FIXAS), employment volume (EMP), and the size of the net sales income (SNET). The empirical equations of the model are characterized by a description accuracy of individual endogenous variables. The model also has good decision-making and forecasting qualities.

Dilemmas of Economic Measurements in Weak Scales: The attempts to measure economic phenomena and processes of qualitative nature have become commonplace among scholars engaged in empirical research. The use of measurement in the nominal and ordinal scales, however, requires a thorough knowledge of the meaning of numbers generated in the course of such operations. It is also necessary to have knowledge of acceptable statistical and econometric tools to be used in such research. Unfortunately, researchers often apply methods that are not acceptable for the numbers in the weak scales. As a result they "soup up" the outcome of their empirical research, instead of achieving a substantive truth. This article is devoted to the possibilities of statistical analysis of numbers resulting from the weak scale measurement.

Purpose: Electrical energy is in this day and age fundamental to the functioning of every household. The use of gas, heating oil or solid fuels for home heating also involves the supply of electricity. Today, electric power is the most environmentally friendly source of energy. Experience has shown that substitution of an oil heating system with a heat pump resulted in significant financial savings for the household. Design/methodology/approach: The purpose of this paper shall entail the construction of a multi-equation econometric model describing the mechanisms of electricity consumption in a specified household. The model takes the nature of a system of interdependent equations. Described shall be the monthly volume of electricity consumption, payment amount of for this energy (in PLN), and price per 1 MWh in a given month. Monthly time series from September 2015 to November 2022 have been used, which resulted in a time series with a count of 87 statistical observations. Findings: The econometric model of household electricity consumption presented in this paper confirms both the hypothesis about feedback between the variables USAGE and PRICE as well as the recursive effect of electricity consumption volume on its value in monetary units. In addition to the cognitive value of the econometric modeling results obtained, the empirical tool constructed makes enables forecast estimation of the energy consumption volume, its value and unit price in subsequent months, for at least 12 consecutive months. Practical implications: This type of research has great practical utility. They make it easier for rational interaction between electricity sellers and specific consumers. Social implications: Knowledge about the mechanisms of electricity consumption on the farm home may influence the rationalization of consumption and spending. This type of rationalization should have a positive impact on the environment natural, contributing to the reduction of greenhouse gas emissions. Originality/value: The novelty and originality of the work are the identification of the mechanism behavior of a single household consuming energy electric. Feedback between magnitudes revealed electricity consumption and its price on a specific farm home. The recipients of the work will be electricity sellers, consumers, and researchers of household market behavior. Keywords: econometric model, electricity consumption, interdependent equations. Category of the paper: Research paper. Case study.