Introduction to Econometrics. Bacisc of Regression Analysis

Content

1. Introduction to Econometrics…………………………………………………        3

1.  Main Concepts of Econometrics……………………………………        3
2.  Econometrics Elements…………………………………………….. 5
3.  Econometrics Methodology…………………………………………        6

1. Theoretical Basics to Regression Analysis……………………………………        13

1.  Key Ideas and Terminology…………………………………………        13
2.  Linear Regression Model…………………………………………….        16
3.  Regression Model Selection Process        ………………………………..18

Conclusions        ………………………………………………………………………...20

Bibliography……………………………………………………………………….        22

Appendixes        ………………………………………………………………………..        24

1. Introduction to Econometrics

1. Main Concepts of Econometrics

The term "econometrics" was first used by the Polish accountant Pawel Ciompa in 1910. He decided that he could get a new insight into the results of operations, if the mathematical techniques (algebra and geometry) are applied to accounting data. Despite the fact that this concept has not received further development, the term "econometrics" was remembered and found the application for designation of a new branch of economic knowledge, formed in 1930 [1; 4].
The word "econometrics" consists of a combination of two words: "the economy" and "metrics". This term already emphasizes the content of econometrics as a science, namely quantification of links and relations, disclosed and justified by economic theory. Let’s have a closer look at some other definitions of the term “econometrics”^[1].

• “Econometrics is an amalgam of economic theory, mathematical economics, economic statistics, and mathematical statistics” (Gujarati, 2009).
• “Econometrics is application of the mathematical statistics to economic data in order to lend empirical support to the economic mathematical models and obtain numerical results” (Tintner, 1968).
• “Econometrics is the quantitative analysis of actual economic phenomena based on concurrent development of theory and observation, related by appropriate methods of inference” (P.A.Samuelson, T.C.Koopmans and J.R.N.Stone, 1954).
• “It consists of the application of mathematical statistics to economic data to lend empirical support to the models constructed by mathematical economics and to obtain numerical results” (Gerhard, 1968).
• “Econometrics may be defined as the social science in which the tools of economic theory, mathematics, and statistical inference are applied to the analysis of economic phenomena” (Goldberger, 1964).
• “Econometrics is concerned with the empirical determination of economic laws” (Theil, 1971).

In 1933, a scientist R. Frisch gave his definition of econometrics: "Econometrics is not the same as economic statistics. It is not identical to economic theory, although much of this theory is quantitative. Econometrics is not synonymous with the application of mathematics to economics. Each of the three starting points - statistics, economic theory and mathematics - is necessary but not sufficient for the understanding of quantitative relations in modern economic life. Econometrics is the unity of all three components. " [2; 8]

Summing up the above said, econometrics is the science that deals with a quantitative expression of the relationship of economic phenomena and processes.
It is impossible, however, to argue that the controversy around the definition of econometrics is over. For example, E. Malenvo interpreted econometrics as “any application of mathematics and statistical methods to the study of economic phenomena”. Lange thought that “... econometrics implies some of the quantitative laws observed in the economic life, using statistical methods for this purpose”. This statistical approach to econometric measurement has become dominant [7].

Econometrics may be defined as an independent discipline because the subject deserves to be studied in its own right for the following reasons:

• Economic theory makes statements or hypotheses that are mostly qualitative in nature (the law of demand), whereas econometrics gives empirical content to most economic theory. The law does not provide any numerical measure of the relationship. This is the job of the econometrician.
• The main concern of mathematical economics is to express economic theory in mathematical form without regard to measurability or empirical verification of the theory. Econometrics is mainly interested in the empirical verification of economic theory.
• Economic statistics is mainly concerned with collecting, processing, and presenting economic data in the form of charts and tables. It does not go any further. The one who does that is the econometrician.
• Mathematical statistics provides many of tools for economic studies, but econometrics supplies the later with many special methods of quantitative analysis based on economic data [3; 6; 13].

Econometrics mainly consists of:

• estimating relationships from sample data;
• testing hypotheses about how variables are related:
• the existence of relationships between variables;
• the direction of the relationships between the dependent variable and its hypothesized observable determinants;
• the magnitude of the relationships between a dependent variable and the independent variables thought to determine it [15; 16].

Being a discipline related to the economy and the statistical analysis (See Figure 1.1 in Appendix A), econometrics includes the following scientific and applied activities, grouped according to the degree of specificity of methods [17]:

• Development and analysis of statistical techniques, taking into account the specifics of economic data;
• Development and analysis of econometric models based on the specific needs of economic science;
• The use of econometric methods for statistical analysis of economic data.
  

Development and analysis of statistical techniques, taking into account the specifics of economic data, has a much wider range of applications, rather than the analysis of econometric models based on the specific needs of economic science, but the value of a particular economic situation increases in the latter method.