Forecasting and modeling of socio-economic systems. Statistical modeling and forecasting Sequence of constructing an economic and mathematical model

Optimization methods allow you to find the best options for economic solutions according to the selected optimality criterion. Based on them, it is possible to determine the optimal profit of the enterprise, the volume of output of various types of products, the number of employees, the volume of consumed resources and other indicators.

A model is a convenient, simplified representation of the essential characteristics of an object or situation.

Models must meet the following requirements:

1. The model must reflect the characteristic, essential features of the object.

2. This mapping must be expressed in a simplified form.

3. The model should allow you to change some of its parameters for the purpose of research.

4. The model should be more convenient for experiments and cheaper to manufacture than the object.

1. Sequence of constructing an economic-mathematical model

When building an economic model, a number of steps are usually followed:

1. The subject and goals of the study are formulated.

2. In the economic system under consideration, structural or functional elements are identified and their most important characteristics are determined.

3. A verbal description of the relationships between the elements of the model is given.

4. Symbolic notations are introduced for the considered characteristics of the modeling object and the relationships between them are formalized. Thus, a mathematical model is built.

5. Calculations are carried out using a mathematical model, and the resulting solution is analyzed.

1. Main types of models

Mathematical models used in economics can be divided into classes according to a number of characteristics related to the characteristics of the object being modeled, the purpose of the modeling and the tools used:

Depending on the type of object being modeled, models can be macro and microeconomic.

Macroeconomic models describe the economy as a single whole, connecting its aggregated indicators: GDP, investment, labor productivity, employment, interest rate and other indicators.

Microeconomic models describe the interaction of structural and functional components of the economy, or the behavior of one such component in a market environment. Due to the diversity of types of economic elements and forms of their interaction in the market, microeconomic modeling occupies the main part of economic and mathematical theory.

Depending on the purposes of modeling, theoretical and applied models can be developed.

Theoretical models make it possible to study the general properties of the economy and its characteristic elements. Applied models make it possible to evaluate the functioning parameters of a specific economic entity and formulate recommendations for making practical decisions.

In the modeling of a market economy, a special place is occupied by equilibrium models that describe the state of the economy when the resultant of all forces tending to bring it out of this state is equal to zero, for example, models of equilibrium of supply and demand.

Optimization models in a market economy are usually built at the micro level, such as profit maximization or cost minimization in corporate planning.

Depending on the tools used and the nature of the processes being studied, all types of modeling can be divided into deterministic and stochastic, discrete and continuous, static and dynamic, linear and nonlinear.

Deterministic modeling represents deterministic processes, i.e. processes in which the absence of any random influences is assumed.

Stochastic modeling depicts probabilistic processes and events. In this case, a number of realizations of a random process are analyzed, and the average characteristics of the process are estimated.

Discrete modeling is used to describe processes that are assumed to be discrete, i.e. discontinuous, consisting of separate parts.

Continuous modeling allows you to depict continuous processes in systems.

Based on time, models can be static and dynamic. Static models describe the state of an economic entity at a specific moment or period of time, while dynamic models include relationships among variables over time (for example, over a five-year period).

According to the degree of coarsening of the forms of structural relations of the object under study, models are divided into linear and nonlinear models. In linear models, all the desired variables are written to the first degree, and on graphs they can be represented as straight lines.

Depending on the form of representation of the object, mental and real modeling can be distinguished.

Mental modeling is often the only way to model objects that are practically impossible to realize in a given time interval, or exist outside the conditions possible for physical contemplation. Mental modeling can be implemented in the form of visual and mathematical ones.

With visual modeling, based on human ideas about real objects, various visual models are created that reflect the phenomena and processes occurring in the object.

The basis of hypothetical modeling by the researcher is a certain hypothesis about the patterns of the process in a real object, which reflects the researcher’s level of knowledge about the object and is based on cause-and-effect relationships between the input and output of the object being studied.

Analog modeling is based on the use of analogies at various levels. The highest level is complete analogy, which occurs only for fairly simple objects.

A mental model can be used in cases where the processes occurring in a real object cannot be physically modeled.

Symbolic modeling can be linguistic or symbolic. Language modeling is based on a certain thesaurus, i.e. a dictionary cleared of the ambiguity inherent in a regular dictionary (for example, the word "KEY").

Sign modeling allows you to use signs to display a set of concepts, creating chains of words and sentences and thus give a description of a real object.

Mathematical models are sets of mathematical dependencies that reflect the essential characteristics of the phenomenon being studied. In many cases, mathematical models most fully reflect the modeled object. At the same time, mathematical models are more dynamic; they are better used to find the optimal parameters of an object. To model economic phenomena, models other than economic-mathematical ones, as a rule, cannot be used. Economic and mathematical models, in turn, are of two types: analytical and simulation.

For analytical modeling, functioning processes are written in the form of certain functional relations (algebraic, finite-difference, etc.). In simulation modeling, elementary phenomena that make up the process are simulated while preserving their logical structure and sequence of events over time.

Real modeling is the most adequate, but its capabilities, taking into account the complexity of objects, are very limited.

Modeling is one of the methods, which is becoming increasingly widespread today.

Simulation ( lat. - measure, norm and French. - sample, prototype) is a method of studying objects of knowledge using their models.

Objects of knowledge are actually existing systems (organic and inorganic), objects, phenomena, social processes.

Object model- its analogue, which can be presented in the form of a structure, diagram, sign system, function, result. The analog serves to store and expand knowledge about the properties and structures of an object. From an epistemological point of view, it is a substitute for the original in knowledge and practice.

The results of the development and research of the model are transferred to the original. From a logical point of view, such a transfer is based on the relations of isomorphism (sameness) and homomorphism (similarity) that exist between the model and what is modeled with its help.

The need for modeling arises when studying the object itself is difficult or even impossible.

Modeling types:

• 1. Subject(the model reproduces certain geometric, physical, dynamic, functional characteristics of the original).
• 2. Analog(the original and the model are described by unified mathematical relations).
• 3. Iconic(the model is diagrams, drawings, formulas).
• 4. Logical-mathematical(construction of logical and mathematical models based on a mentally visual representation of signs and operations with them).

Modeling relies heavily on analogical reasoning from input data. In this case, the data can change, according to which the expressive capabilities of the model are expanded.

Changing data parameters of an object are variables that are classified into:

1) internal (object’s own parameters);

2) external (do not depend on and are not determined by the object)

• 3) managed (selected by the manager or researcher at his own discretion);
• 4) uncontrollable (do not depend on the subject’s input, their value can only be recorded);
• 5) random (distributed according to some probabilistic law, uncontrollable; do not have a probabilistic nature, uncertain).

Purpose of modeling- reproduce data assessing natural loads, the progress of the facility, and also explore its internal processes.

The main task of modeling-- reproduce a model that should be similar to the original, but should not be its complete analogue. This is the main condition of modeling. Otherwise, modeling becomes meaningless.

The main difference between the original and the model is the ability for flexible predictive modeling that does not affect the initial data of the model.

A social model can be a mathematical equation, a graphical display of various factors, tables of interdependent characteristics (events and phenomena). Unlike the physical model, the social model does not copy the objects or phenomena being studied, but transforms the value of some features of a social phenomenon or process, selected as independent, into the value of other features, selected as dependent.

The information value of a social model can be assessed by the degree of accuracy of displaying or predicting changes in the studied social processes or phenomena (dependent characteristics) with new values ​​of independent characteristics. That is, it is necessary to differentiate the concepts: developed scheme(in which something that can be independently represented depending on some conditions) and actual social reality with its objective independent conditions.

Simulation is applied;

• a) when studying global problems that cover all human life and narrow problems of the social sphere (for example, the state of the demographic situation in Russia);
• b) in conditions of market relations (for example, the state of education, healthcare, women and families in the conditions of social reforms, modeling of the spiritual and moral sphere of the individual, retraining systems in conditions of market relations of workers, etc.).

Modeling of social structures creates many models that take into account the influence of certain social factors on the social processes under study.

The basis and subject of modeling is a problem situation, which is caused by objective (contradiction between needs and methods of satisfying them, between the development process and the stabilization process) and subjective factors.

The most common modeling methods: development, analysis and research of a model, a problem situation, innovative models, heuristic models, special mathematical models. Recently, computer-generated models have become widespread.

Main modeling tools are:

• – verbal description is the simplest and most accessible way to specify models;
• – graphical representation in the form of curves, drawings - this method has limited independent value and can be an addition to others;
• – flowcharts, decision matrices - this method can be considered intermediate between verbal and mathematical descriptions;
• – mathematical description;
• – software description (for computers).

In everyday practice, the capabilities of the Excel computer program are often used, which has various functions for calculating trends in a variable in the foundation period for the continuation of the trend during the forecast period.

Types and functions of models

Mo division is a specific multifunctional study. Its main task is to reproduce, based on similarity with an existing object, another object (model) that replaces it. Model- this is an analogue of the original. It should be similar to the original, but not repeat it, since in this case the modeling itself loses its meaning. Arbitrary modeling is also unacceptable; in this case, it does not give a proper idea of ​​the original model, and also does not fulfill its function. Models differ in their degree of closeness to reality (degree isomorphism with reality).

All variety of models in accordance with the method of reproducing reality and the means used to construct the model can be divided into three classes:

• 1) material models, which, due to the specificity of social objects, must be implemented in the form of models based on the participation of people in them (as a rule, these are game models);
• 2) ideal models are currently used in sociology in almost all areas of scientific research. Ideal models are usually classified on the following basis:
  • – by scope of research distinguish between models of the social structure of society and socio-demographic processes, models of lifestyle and socio-political processes, etc.;
  • – according to the level of the simulated system- micro- and macromodels;
  • – by focusing on reproducing certain aspects of the original- substantial, structural, functional and mixed models;
  • – the method of displaying in model constructions the laws and patterns to which the object of study is subject, - deterministic and stochastic models;
  • – focus on studying the functioning or development of the system- models with constant and changing structure;
  • – place in the structure of scientific knowledge- measuring, descriptive, explanatory, predictive and criterial;
  • – level of formalization- conceptual and formal-logical (mathematical) models;
• 3) mixed models, combining elements of the first two (so-called man-machine models). The scope of application of the first and third class models is very limited in sociology.

Functions of models. Depending on the research objectives, models can be included in the cognitive process at both the empirical and theoretical levels of knowledge. Wherein at the empirical level

– measuring(measuring social characteristics) and descriptive (recording the results of empirical research and expressing them in scientific terms).

On theoretical level Model knowledge typically performs the following functions:

• – explanatory- revealing the essence of the objects under study,
• – criterial- checking the truth of some provisions of a theory or system of hypotheses,
• – predictive- assessment of the future state of the system under consideration.

Individual functions can be performed by models both at the empirical and theoretical levels of knowledge. As for specific models, they can be designed specifically to perform one of the named functions. In addition, models can be designed specifically to simultaneously implement several functions. For example, simulation models, as a rule, perform simultaneously descriptive and explanatory functions or descriptive and criterion functions.

What requirements must a social model meet?

First group of requirements . The model should

• – be simple, convenient;
• – provide new information about the object;
• – contribute to the improvement of the object itself.

For the second group of requirements can be attributed:

• – determining or improving the characteristics of an object;
• – rationalization of methods of its construction;
• – the ability to control or understand an object using its model.

Therefore, when developing models, it is legitimate to talk about their similarity to the original object. At the same time, on the one hand, strict focus is observed, linking the parameters with the expected results, on the other hand, the model must be quite “free”, capable of transformation depending on specific conditions and circumstances, be alternative, and have the largest number of options in stock.

Model evaluation

What requirements must a social model meet? Today in the scientific literature the following requirements are put forward for the model:

• – it should be simple and convenient;
• – allow you to study the object and obtain new information about it;
• – contribute to the improvement of the facility;
• – provide an opportunity to consider the control of an object on its model.

When developing a model, strict focus is observed, linking parameters with expected results; on the other hand, the model must be sufficiently “free”, capable of transformation depending on specific conditions and circumstances, be alternative, and have the largest number of options in reserve.

Model evaluation criteria

• 1) One of the evaluation criteria isprogressiveness of the model, meaning how leading it is in a number of parameters,
• 2) type of reflection(intuitive reflection, qualitative description, visual imitation, quantitative description, systemic reproduction);
• 3) prevalence(social sphere as a whole, industry, social group, etc.);
• 4) level of development(an idea was put forward, a diagram was built, an algorithm was developed, a formalized, materialized system, etc.);
• 5) level of creative solution using the model. The first level is definition (discrimination, recognition), classification of known facts, objects, events, ordering them and solving simple problems, improving the simplest model representations. The second level is the implementation of a scientific forecast of qualitatively new facts, events and their practical use.

Equally important is consideration of the structure of models. Into the model structure included three main components: a set of directions for the development of the object of knowledge; driving forces of development; factors of external influences.

When researching, it is important to record the degree of realized influence of all the main components at the previous stage of cognition of the object, which can be done through retrospective analysis. Such an approach largely predetermines the prediction of the development of the object under study, based on the experience of the past, on comparison with it, and is based on representative arrays of information.

The purpose of forecasting in social work - give variable forecast of changes in a social object (phenomenon, process, situation, group, personality), i.e. describe its state in the future, indicating quantitative and qualitative characteristics.

In accordance with the described characteristics, the forecasts will be called: qualitative forecasts, quantitative forecasts.

Forecasting in decision making

The uncertainty of the external environment puts the organization in such conditions that when making decisions, forecasting becomes necessary.

Definition 1

Forecasting– this is the development of forecasts (scientifically based judgments about the future states of the object under study, development alternatives, life spans, etc.).

Forecasting when making decisions means assessing the prospects for the development of the situation that may arise after the implementation of the decision. Forecasting is based on an analysis of the current situation in the organization and in the external environment. The purpose of forecasting is to identify trends that impact the organization and the market. Depending on the area of ​​consideration, forecasting is divided into the following types:

• economic(describe the general state of the economy for a certain period);
• technological(describe future technologies, innovations in terms of efficiency, labor intensity, cost-effectiveness, etc.);
• competitive(describe the strategy of competitors’ behavior in the market, their market share, sales level, new products, etc.);
• about the state of the commodity market(describe the market situation in terms of the influence of politics, economics, ecology, consumer income level, demographics, etc.);
• social(describes the attitude of consumers towards the organization, product).

Definition 2

Sources for making forecasts are information obtained from financial statements, statistical data, operational data, scientific and technical documentation, licenses, patents, external sources of information (mass media, Internet).

Main stages of forecasting are presented in the diagram.

Picture 1.

There are many types of forecasting; all existing methods are usually divided into three groups:

• quantitative;
• quality;
• informal.

Figure 2.

Quantitative methods include:

• mathematical methods (extrapolation, time series analysis, time series analysis),
• Causal modeling.

Qualitative methods are used when there is no complete information about the situation. The basis of this group of methods is expert assessments. These include:

• heuristic, expert methods;
• forecasting by analogy;
• logical forecasting;
• functional-logical forecasting.

Expert methods are applied in all categories of management. Experts are professionals in a particular field and evaluate a situation based on their experience and intuition.

Forecasting by analogy used very often. If there is an analogy between the current situation and the previous one, you can predict how the current situation will develop.

Informal methods forecasting is based on information that is collected in different ways: verbal, written, obtained as a result of espionage.

Modeling during decision making

Simulation of situations is a widely used method to help make management decisions. Modeling involves studying a problem by building a model, studying its properties and behavior. After a comprehensive analysis of the model, the information obtained is transferred to the real situation. A model is an abstract object that is brought into line with the situation being studied.

When making decisions, use the following types of modeling:

• conceptual (models are diagrams that reflect ideas about which variables in a situation are most significant for decision making and how they interact, what are the connections between them);
• mathematical (the situation is presented in the form of a formula, a set of mathematical symbols and expressions; such models are convenient for quantitative analysis, they show the influence of elements within the situation on the final decision);
• imitation (with the help of a computer, the algorithm of operation of complex systems or objects is reproduced in time, their behavior and constituent elements are imitated; at the same time, the structure of the object is preserved, the sequence of processes is also observed).

The construction of any model includes several stages:

1. Description of the object. This is a preliminary description that is as close as possible to real parameters. This stage is the basis for subsequent descriptions.
2. Formalization of the object. Based on the description, the most important characteristics of the object that affect its operation are identified. Then the controllable parameters and those that cannot be controlled are determined. A system of constraints is identified, a diagram or mathematical function is constructed. Thus, the verbal description is replaced by an abstract (formal) and ordered one. 3. Adequacy check. Calculations are carried out, and based on their results, a decision is made on whether to apply the model in practice or to adjust the model.
3. Adjustment. Information about the object is clarified and the parameters of the abstract model are adjusted. Then the adequacy assessment is carried out again.
4. Optimization. While maintaining the adequacy parameters, they try to simplify the model. In this way, you can get a simpler model, but working on the same principles. The form of the model changes, but not the content. Main indicators for optimization: resource costs, time for research, time to make a decision using the model.

A common technique for describing certain processes and phenomena is modeling. Modeling is considered a fairly effective means of predicting the possible occurrence of new or future technical means and solutions. For the first time, for forecasting purposes, the construction of operating models was undertaken in economics. The model is constructed by the subject of the study so that the operations reflect the characteristics of the object (interrelations, structural and functional parameters, etc.) that are essential for the purpose of the study. Therefore, the question of the quality of such a mapping - the adequacy of the model to the object - can only be legitimately decided in relation to a specific goal. Construction of a model based on a preliminary study of the object and identification of its essential characteristics, experimental and theoretical analysis of the model, comparison of results with object data, and adjustment of the model constitute the content of the modeling method.

The modeling method, the development of which in relation to forecasting scientific and technological progress encounters serious difficulties, requires special attention.

The difficulty of using the modeling method in predicting scientific and technological progress is caused by the complexity of the structure of technical development and therefore forces the use of not a single model, but a system of methods and models characterized by a certain hierarchy and sequence.

A system of models for forecasting scientific and technological progress should be understood as a set of methods and models that make it possible to give a consistent and consistent forecast of the scientific and technical development of the industry, based on the study of technical and economic trends and patterns emerging in the current and future periods, on specified targets, on existing resources, identified needs of the national economy and their dynamics.

Such a system assumes a certain order of use of models for the purpose of compiling a comprehensive forecast.

The use of mathematical apparatus to describe models (including algorithms and their actions) is associated with the advantages of a mathematical approach to multi-stage information processing processes, the use of identical means of forming problems, searching for methods for solving them, fixing these methods and converting them into programs designed for the use of computer technology .

The development of a system of forecasting models goes through three stages.

At the first stage of developing local forecasting methods, individual models and subsystems of forecasting models are developed. The developed models must be mutually linked and form a single system for forecasting purposes, ensuring the interaction of individual models in accordance with certain requirements. Such requirements will be recorded in the research program on the problem as a whole.

At the second stage of developing local methods for forecasting scientific and technological progress, a system of interacting forecasting models is created, model subsystems are specified and agreed upon, their interaction is checked, the sequence of use of individual models is determined, as well as assessment techniques and methods for verifying the resulting complex forecasts. At this stage, appropriate programs must also be compiled for solving problems on electronic computers.

The third stage of creating a system of forecasting models is mainly associated with the refinement and development of individual local systems and methods in the course of their practical use for the purposes of comprehensive forecasting of scientific and technological progress.

When drawing up detailed research programs for the first and second stages, it is necessary to take into account that the objectives of the methodology and the range of problems and indicators developed during forecasting significantly depend on the timing of the forecasts. With the increase in activity of the forecast period, indicators are enlarged, the amount of available and accessible information of all types decreases; This corresponds to the use of large-scale (aggregated) models and consideration of larger synthetic problems of national economic development. In this case, it is necessary to identify indicators that are connected by stable functional connections, both among themselves and with forecast indicators for a shorter period and which significantly influence the dynamics of indicators for the period as a whole and its individual parts (the principle of selecting essential and stable information).

The requirements for individual models and the system of forecasting models predetermine the methods by which these models can and should be developed, as well as the methods and means of performing calculations on them. These requirements boil down mainly to the following provisions:

• - the methodology must provide a clear description of the sequence of rules (algorithm), allowing one to make a separate forecast under fairly broad assumptions about the nature and values ​​of the information of a certain structure initial for a given forecast;
• - the methodology must use methods and technical means that allow calculations to be carried out in a timely manner and repeatedly, based, as a rule, on information that is heterogeneous and large in volume, changing according to forecast options;
• - such methods should take into account complex, multifactorial relationships of predicted processes and indicators. It is necessary to ensure the identification of the most important and stable patterns and trends in these conditions. Such identification is necessary both on the source material and in the process of analyzing the results obtained using this technique and their calculations using a set of related models;

There is a need for systematic coordination of individual forecasts, which should ensure consistency and mutual adjustment of the latter.

The use of mathematical methods is a necessary condition for the development and use of forecasting models, ensuring high requirements for the validity, effectiveness and timeliness of forecasts of scientific and technological progress.

Modeling is the construction of a model based on a preliminary study of an object and processes, highlighting its essential features and characteristics. Forecasting using models includes its development, experimental analysis, comparison of the results of preliminary forecast calculations with actual data on the state of a process or object, refinement and adjustment of the model.

2.2. Statistical forecasting methods

Some scientists estimate that there are more than 150 forecasting methods. There are much fewer basic methods; many of the “methods” rather refer to individual methods and procedures for forecasting, or are a set of individual techniques that differ from the basic methods in the number of private techniques and the sequence of their application.

The forecasting method is understood as a set of techniques and ways of thinking that allow, based on the analysis of retrospective data, exogenous (external) and endogenous (internal) connections of the forecast object, as well as their measurements within the framework of the phenomenon or process under consideration, to derive judgments of a certain reliability regarding the future development of the object. Based on the degree of formalization, economic forecasting methods can be divided into intuitive and formalized.

Intuitive methods are based on intuitive-logical thinking. They are used in cases where it is impossible to take into account the influence of many factors due to the significant complexity of the forecast object or the object is too simple and does not require labor-intensive calculations. It is advisable to use such methods in other cases in combination with formalized methods to increase the accuracy of forecasts.

Among intuitive methods, methods of expert assessments have become widespread. They are used both in our country and abroad to obtain forecast estimates of production development, scientific and technological progress, resource efficiency, etc.

Methods of historical analogies and model forecasting are also used. A kind of extrapolation takes place here. The forecasting technique consists of analyzing a highly developed system (country, region, industry) of the same approximate level, which is now available in a less developed similar system, and based on the history of the development of the process under study in the highly developed system, a forecast is constructed for the less developed system. Practice shows that such analogies can be used in determining the development paths of new industries and types of equipment (production of computers, televisions, etc.), the structure of production, consumption, etc. Naturally, the “sample” obtained in this way is only the starting point for forecasting. A final conclusion can be reached only by examining the internal conditions and patterns of development.

Formalized methods include extrapolation methods and modeling methods. They are based on mathematical theory.

Among extrapolation methods, the function selection method based on the least squares method (LSM) has become widespread. In modern conditions, increasing importance has been attached to modifications of the least squares method: the method of exponential smoothing with an adjustable trend and the method of adaptive smoothing.

Modeling methods involve the use of various kinds of economic and mathematical models in the process of forecasting and planning, which are a formalized description of the economic process (object) under study in the form of mathematical dependencies and relationships. The following models are distinguished: matrix, optimal planning, economic-statistical (trend, factor, econometric), simulation, decision-making. To implement economic and mathematical models, economic and mathematical methods are used.

In the practice of forecasting and planning, the method of economic (systemic) analysis, normative and balance methods are also widely used. To develop targeted complex programs, the program-target method (PTM) is used in combination with other methods. It should be noted that the presented list of methods and their groups is not exhaustive. Let's consider methods that have become widespread in world practice.

Expert assessment methods

The main idea of ​​forecasting based on expert assessments is to build a rational procedure for a person’s intuitive and logical thinking in combination with quantitative methods for assessing and processing the results obtained.

The essence of expert assessment methods is that the forecast is based on the opinion of a specialist or a team of specialists, based on professional, scientific and practical experience. There are individual and collective expert assessments.

Extrapolation methods

In methodological terms, the main tool of any forecast is the extrapolation scheme. The essence of extrapolation is to study the stable development trends of the forecast object that have developed in the past and present and transfer them to the future.

There are formal and predictive extrapolation. The formal one is based on the assumption that past and present trends in the development of the forecast object will be preserved in the future; in forecasting, actual development is linked to hypotheses about the dynamics of the process under study, taking into account changes in the influence of various factors in the future. It should be noted that extrapolation methods must be applied at the initial stage of forecasting to identify trends in changes in indicators.

Modeling methods and economic-mathematical methods

Modeling involves constructing a model based on a preliminary study of an object or process, identifying its essential characteristics or features. Forecasting economic and social processes using models includes the development of a model, its experimental analysis, comparison of the results of forecast calculations based on the model with actual data on the state of an object or process, adjustment and refinement of the model.

Depending on the level of management of economic and social processes, macroeconomic, intersectoral, interdistrict, sectoral, regional models and micro-level models (firm development models) are distinguished.

Based on aspects of economic development, forecasting models for the reproduction of fixed assets, labor resources, prices, etc. are distinguished. There are a number of other features for classifying models: time, factor, transport, production.

In modern conditions in the republic, the development of modeling and the practical application of models has been given particular importance in connection with the strengthening of the role of forecasting and the transition to indicative planning.

Economic analysis method

Economic analysis is an integral part and one of the main elements of the logic of forecasting and planning. It must be carried out at both macro and meso and micro levels.

When conducting economic analysis, a systematic approach should be used. The national economy (economy) as a whole and its structural parts are considered as a system: spheres, regions, industries, associations, enterprises. The analysis must be comprehensive, i.e. comprehensive.

The essence of the method of economic analysis is that an economic process or phenomenon is divided into its component parts and the relationship and influence of these parts on each other and on the course of development of the entire process is revealed. Analysis allows us to reveal the essence of such a process, determine the patterns of its changes in the forecast (planning) period, and comprehensively assess the possibilities and ways to achieve the goals.

The process of economic analysis is divided into a number of stages: formulation of the problem, determination of goals and evaluation criteria; preparing information for analysis; study and analytical processing of information; developing recommendations on possible options for solving the problem and achieving goals; registration of analysis results.

Balance sheet method

Using the balance method, the principle of balance and proportionality is implemented. It is used in the development of forecasts, plans and programs. Its essence lies in linking the country's needs for various types of products, material, labor and financial resources with production capabilities and sources of resources.

The balance method involves the development of balances, which are a system of indicators in which one part, characterizing resources by source of income, is equal to the other, showing the distribution (use) in all areas of their consumption.

During the transition period to market relations, the role of forecast balances developed at the macro level increases: the balance of payments, the balance of state income and expenditure, the balance of monetary income and expenditure of the population, the consolidated balance of labor resources, the balance of supply and demand. The results of balance sheet calculations serve as the basis for the formation of structural, social, fiscal and monetary policies, as well as employment and foreign economic activity policies. Balance sheets are also used to identify imbalances in the current period, reveal unused reserves and justify new proportions.

The system of balances used in forecasting and planning includes: material, labor and financial. Each of these groups includes a number of balances.

Normative method

The normative method is one of the main methods of forecasting and planning. In modern conditions, it has begun to be given special importance in connection with the use of a number of norms and regulations as regulators of the economy. The essence of the normative method lies in the feasibility study of forecasts, plans, programs using norms and standards. The latter are used to calculate resource requirements and indicators of their use. With the help of norms and standards, the most important proportions are substantiated, the development of material production and non-production spheres is substantiated, and the economy is regulated.

The norm characterizes a scientifically based measure of resource consumption per unit of production (work) in accepted units of measurement, for example, flour consumption per 1 ton of bakery products according to the approved recipe. The norm is the consumption of a particular product per capita according to a scientifically based diet. For example, the recommended rate of consumption of meat and meat products per year per person is 82 kg. In the non-production sphere, standards are applied that characterize the required size of total and living space per inhabitant, water consumption per person, etc.

Standards are usually developed in relative terms. They characterize the degree of resource use (for example, the percentage of yield of suitable casting from metal filling), resource consumption per 1 million rubles. products, loan fees (interest rates), etc.

Program-target method

Compared to other methods program-target method(PCM) is relatively new and insufficiently developed. It has become widespread only in recent years, although it has been known for a long time and was first used during the development of the GOELRO plan.

PCM is closely related to normative, balance sheet and economic-mathematical methods and involves the development of a plan starting with an assessment of final needs based on the goals of economic development with the further search and determination of effective ways and means to achieve them and resource provision. Using this method, the principle of priority planning is implemented.

The essence of the PCM lies in the selection of the main goals of social, economic and scientific-technical development, the development of interrelated measures to achieve them within the scheduled time frame with a balanced provision of resources, taking into account their effective use.

PCM is used in the development of targeted comprehensive programs, which are a document that reflects the goal and complex of research, production, organizational, economic, social and other tasks and activities, linked by resources, performers and implementation deadlines.