# An Introduction To Econometrics

Introduction

Econometrics deals with applying the theories of mathematics, statistical methods and computer science to economic data. It can be defined as the subdivision of economics that aims to provide empirical or practical content to economic relations. In econometrics, a quantitative analysis of actual economic phenomena is carried out based on the parallel development of theory and observation, connected by suitable methods of inference. Econometrics is often described as the intersection of economics, mathematics, and statistics. It includes empirical content to economic theory thereby enabling the theories to be tested and supporting tasks such as forecasting and policy evaluation.

Econometric Methods

Normal statistical models can be used in econometrics in order to study economic questions; however the problem lies in the fact that these contain a lot of observational data. It is precisely because of this reason that the field of econometrics has devised a number of methods for recognition and estimation of simultaneous-equation models. These methods are similar to methods that are utilized in other areas of science, for example, the field of system identification in systems analysis and control theory. This type of methods can help researchers to estimate models and look into their practical consequences, without directly manipulating the system. Below mentioned are some of the important econometric methods.

Experimental Economics – Of late, the use of experiments to estimate some of the conflicting conclusions of observational studies has become increasingly popular. In this context, controlled and randomized experiments offer statistical inferences that may produce better empirical performance than just using observational studies.

Data – The analysis done using econometrics can be applied different types of data sets. These include time-series data, cross-sectional data, panel data and multi-dimensional panel data. Observations done over a period of time are known as time-series data, while cross-sectional data may refer to observations made at a single juncture. Panel data takes into account both time-series as well as cross-sectional data. Multi-dimensional panel data also includes both observations over time and at a single juncture but also takes into account a third dimension.

Instrumental Variables – The instrument variables method may be used in econometric analysis in cases where the ordinary least squares method is unable to recover the desired hypothetical relation or may generate approximations with poor statistical properties due to the violation of the assumptions for valid use of the method.

Computational Methods – Computational concerns are used for the evaluation of econometric analysis. These include being mathematical well-posed, numerical accuracy of software and usability of econometric software.

Structural Econometrics – This method enables researchers to analyze data based on economic models. It encourages researchers to use more complex models with strategic interactions and multiple equilibriums.

Conclusion

Econometric analysis is of great importance as it takes into account the practical implications of economic theories.