Objectivity and knowability of socio-economic processes serve as the theoretical foundation of forecasting. Based on the qualitative and quantitative analysis of real socio-economic processes, the identification of objective conditions, factors and trends in their development, forecasting is based on both general scientific and specific approaches and fundamental principles. Among the general approaches are the following.
The historical approach is to consider each phenomenon and process in the interrelation of its historical forms. In the process of forecasting, it should be assumed that the current state of the object under study is a natural result of its previous development, and the future is the natural result of its development in the past and present.
An integrated approach involves the consideration of the object of research in its connection and dependence with other processes and phenomena. For example, when studying an economic object, we consider it in relation to demographic, scientific, technical, social, environmental and other processes. In an integrated approach, genetic (research) and normative (target) approaches are distinguished.
With a genetic (research) approach, based on the current state of affairs and identified development trends, possible results are predicted; the consequences of a particular development option become clear. The genetic approach allows you to reflect stable trends inherent in the object of forecasting and giving its development an inertial character. Any foreseeable phenomenon or process has its origins in the present and in the past, its origin, its genesis. And the future, no matter how different it may be from the past and the present, is always connected with them, it is formed from already known elements, although in different ratios, in a system of new connections.
The normative (targeted) approach has a different nature: it reflects the possibility of managing predicted processes based on the goals of socio-economic development. The goal of development is presented normatively, i.e. in the form of a certain normative state, and the ways of achieving it are investigated.
At first glance, the target and genetic approaches seem mutually exclusive due to their opposite direction. But it’s not. They complement each other: when exploring the future, we always assume a goal, and when we set a certain goal, we provide in general terms the ways of its implementation, based on the trends that have developed in the past and present. And this makes it impossible to use in practice only a genetic or purely normative approach. For if the goal put forward is in no way connected with the emerging trends, then the ways to achieve it cannot be justified, and in this case the forecast loses all scientific grounds. And vice versa – if foresight reflects only the established trends, then the opportunity to assess the prospects for their development disappears and the possibility of managing them is unreasonably ignored. But the relationship between the genetic and normative approaches may change in favor of one and the other. It depends on the period and specifics of the forecasting object. In forecasting with a long period of anticipation, the scope of the normative approach expands, as the link between the development perspective and current trends weakens. With small periods of anticipation, genetic approaches are more often used.
The specifics of the forecasting object depend on the possibility of its regulation. If the predicted processes are poorly controlled (for example, demographic), then the use of the genetic approach expands. With a high degree of controllability of the object (for example, dynamics, structure of production), the normative approach is more widely used. The use of a genetic or normative approach predetermines the choice of forecasting method (see Chapter 5), and their combination allows a comprehensive study of the problem and the development of an integrated approach.
The fundamental principle of forecasting is the principle of consistency. It involves the study of quantitative and qualitative patterns in economic systems, the construction of such a logical chain of research, on which the process of developing and justifying any decision is based on the definition of the overall goal of the system and subordinates the activity of all subsystems to the achievement of this goal. At the same time, this system is considered as part of a larger system, and at the same time itself consists of subsystems. For example, the national economy, on the one hand, is considered as a single object of research, and on the other hand, as a set of relatively independent objects.
The system approach involves the creation of a system of indicators, methods, models that would correspond to the content of each individual relatively independent object and at the same time would allow to build a holistic picture of the possible development of the national economy. With such requirements, methodological difficulties arise: the construction of a holistic picture that requires unified models and an information data bank comes into conflict with forecast blocks – separate economic objects that have their own specifics and require maximum approximation to their internal features. This makes it difficult to obtain a single and internally agreed forecast, impoverishes its economic content. To eliminate contradictions, the “block” principle of building a comprehensive forecast is used.
The principle of adequacy assumes that the methods and models for the development of forecasts are designed, first of all, to identify and quantitatively measure stable trends and interrelations in the development of the national economy and create a theoretical analogue of real economic processes with their complete and accurate imitation. Adequacy means the maximum approximation of the theoretical model to stable development trends, taking into account the probabilistic, stochastic nature of real processes and assessing the probability of realization of the identified trends. When using the principle of adequacy, forecasting methods and models should be tested for the ability to imitate already established processes and phenomena, i.e. they should be not only an instrument of foresight, but also an instrument of cognition.
When moving from imitation of processes and trends to anticipation of their development, it is necessary to determine possible ways of their development, i.e. construction of alternative options for the development of the predicted object. The principle of alternative forecasting is associated with the possibility of developing the national economy and its individual links along different trajectories, with different interrelations and structural relations, i.e. it proceeds from the assumption of the possibility of qualitatively different options for the development of the forecasted object.
The main thing when using this principle is to separate development options that are feasible from those that are not feasible under the prevailing and foreseeable conditions. Here it is necessary to gradate alternatives according to the probability of their practical implementation. At the same time, each alternative may be accompanied by a set of problems, which will require the study and definition of additional conditions, the fulfillment of which will assess the feasibility of implementing this alternative. The formation of alternatives is also influenced by the specific goals of the development of the predicted object. In this case, the principle of purposefulness begins to work.
The principle of purposefulness gives an active character to forecasting: the forecast is not reduced to foresight, but includes the goals to be achieved in the economy through active state actions. This principle is linked to and derives from the normative approach.
These forecasting principles are the main (although not exhaustive) and underlie specific forecasting methods and models. They are interrelated, their selective use is impossible. In the development of science-based forecasts, these principles should be considered as a whole.