Introduction to Econometrics
Introduction
The study of econometrics refers to the determination of economic relationships. Intending to give numerical values to the features of economic links, it is a combination of economics, mathematical economics, and statistics.
An economic model is an ensemble of assumptions that represents an event, or more in general, the behavior of an economy. A model provides a simplified picture of an actual approach. It needs to be relevant in a way that it should contain the most important aspects of the event that is being studied. Using a fundamental framework to break down something complicated is referred to as modeling. An aim like that may at times end in an unrealistic model with inaccurate presumptions. In reality, the model usually contains all the variables that the researcher believes are necessary to comprehend what is happening. The other elements are put into a collection termed "disturbances" wherein the disturbances are made up of random variables.
Objectives of Econometrics
Econometric model development and specification - The models of economics are constructed in a way that can be verified through experimentation. It can be utilized for developing a wide range of mathematical models. Such models vary due to a ranged selection of functional forms, specification of the randomized structure of the parameters, etc.
Model estimation and testing - Models undergo calculation based on the information that was observed set and the suitability testing. This is the component of the modeling's statistical conclusion. Several estimating approaches are used to understand the numerical values of the undefined variables of the models. A suitable and adequate model is chosen from among several statistical model formulations.
Model Utilisation - Forecasting and designing policies, which are both the core elements of any policy decision, are carried out using models that are created. Policymakers can assess the fit of the model they have constructed and make the necessary modifications to the relevant economic variables with the support of these projections.
Econometric Methods
Regression Method - Regression analysis is a widely commonly used methodology to forecast the demand for a given product. This method combines statistical estimation techniques with economic concepts. To define the demand determinants and the nature of the link between a product's determinants and demand, the theory of economics is used.
Simultaneous Equations Method - Several simultaneous equations need to be computed to forecast demand according to the simultaneous equation model. These equations include mathematical identities, market-clearing formulas, and behavioral equations.
Limitations of Econometrics
Ceteris Paribus Assumption - The ceteris paribus presumption, stating that all other factors remain constant, often serves as the basis of econometric models. It can be challenging to separate the impact that comes from one variable while keeping the others constant in practice, which might distort the results and produce erroneous data.
Endogeneity - When an explanatory variable in the regression model correlates with an error term, endogeneity develops. Parameter estimations may become skewed and inconsistent as a result. To resolve endogeneity concerns, instrumental factors or more advanced techniques would be required.
The Concept of Multicollinearity - When several independent variables in a regression model have a strong correlation, this is referred to as multicollinearity. This may result in inaccurate estimates and inflated standard errors, which also makes it difficult to identify the distinctive effects of every variable.
Sample Selection Bias - Sample selection bias may arise if the sample selected for the study doesn't seem representative of the population of interest. This could result in findings that are tricky to extrapolate for a larger group.
Autocorrelation - When error terms in a time series model indicate temporal correlation, it can be referred to as autocorrelation. In addition to breaking the presumption of independence, this could end up in incorrect interpretations concerning the statistical value of the correlations and inefficient estimates.
Conclusion
Despite these drawbacks, econometrics is still a helpful and widely used method in the field of economics. conducting sensitivity studies, applying suitable approaches to address specific questions, and remaining open about the assumptions made, researchers can enhance the consistency of their findings. The accessibility of more extensive and high-quality data in addition to the continuing growth of advanced econometric techniques supports the constant improvement of economic analysis.
In conclusion, econometrics provides an organized framework for assessing theories, establishing correlations, and generating forecasts in the area of economics. Econometrics can make an important contribution to our understanding of economic events and aid in making informed choices in several sectors when used properly with an understanding of its constraints.
References
https://businessjargons.com/econometric-methods.html
https://www.investopedia.com/terms/e/econometrics.asp#toc-methods-of-econometrics
https://appliedeconomics.bc.edu/what-is-econometrics/
http://home.iitk.ac.in/~shalab/econometrics/Chapter1-Econometrics-IntroductionToEconometrics.pdf
https://www.econometrics-with-r.org/
Written by Arushi Gupta | Proofread by Amina Meiirkhan
