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This is a science that studies quantitative and qualitative economic relationships using statistical and other mathematical methods and models.


The term "econometrics" consists of two parts: "econo" - from "economics" and "metrics" - from "metrical". Econometrics is part of an extensive family of disciplines devoted to the measurement and application of statistical methods in various fields of science and practice. This family includes, in particular, biometrics, technometry, scientometrics, psychometry, chemometry, qualimetry. Sociometry stands apart - this term has been assigned to statistical methods for analyzing relationships in small groups, that is, to a small part of such a discipline as statistical analysis in sociology and psychology.

Theoretical econometrics is concerned with the evaluation of properties and tests, while applied econometrics is concerned with the application of econometric methods to the evaluation of economic theories. Econometrics provides tools for economic measurements, as well as a methodology for assessing the parameters of micro- and macroeconomics. In addition, econometrics is actively used to predict economic processes both on the scale of the economy as a whole and at the level of private enterprises. At the same time, macroeconometrics is part of economic theory, combined with - and microeconomics.

Econometric methods of analysis

Regression analysis is a statistical method for studying the relationship between the dependent variable Y and one or more independent variables X1,X2,...,Xp. At the same time, the terminology of dependent and independent variables reflects only the mathematical dependence of variables, and not causal relationships. For an adequate description of complex internally heterogeneous economic processes, as a rule, systems of econometric equations are used. In simpler cases, simple isolated equations can also be used.

Time series analysis is a set of mathematical and statistical methods of analysis designed to identify the structure of time series and to predict them. Revealing the structure of the time series is necessary in order to build a mathematical model of the phenomenon that is the source of the analyzed time series. The forecast of future values ​​of the time series is used in decision making. Forecasting is also interesting in that it rationalizes the existence of time series analysis apart from economic theory.

As a rule, forecasting is based on some given parametric model. In this case, standard methods of parametric estimation (LSM, MMP, method of moments) are used. On the other hand, non-parametric estimation methods for fuzzy models have been sufficiently developed.

Panel analyzes are spatial microeconomic samples traced over time, that is, they consist of observations of the same economic units that are carried out in successive periods of time. Panel data has three dimensions: signs - objects - time. Their use provides a number of significant advantages in assessing the parameters of regression dependencies, since they allow both the analysis of time series and the analysis of spatial samples. With the help of such data, they study poverty, unemployment, crime, and also evaluate the effectiveness of government programs in the field of social policy.


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