In the field of insights and scientific speculations, econometrics is connected for the reason to test theory and estimate the future patterns. The usage of econometrics is to plot financial matters models and looks at them through factual preliminaries, and when the results show up, it is thoroughly analyzed to genuine precedents so as to give observational substance to monetary relations.
The term “Econometrics” refers to the application of statistical methods to economic data in order to give empirical content to economic relationships. More precisely, it is "the quantitative analysis of actual economic phenomena based on the concurrent development of theory and observation, related by appropriate methods of inference".
Economists around the globe, develop economic models to explain consistently recurring relationships. Their models link one or more economic variables to other economic variables. Econometrics is all about turning theoretical economic models into useful tools for economic policymaking.
Econometrics was spearheaded by Lawrence Klein, Ragnar Frisch, and Simon Kuznets. Each of the three won the Nobel Prize in financial matters in 1971 for their commitments. Econometrics is used to develop economic theories by analyzing data using statistical methods. These methods further rely on statistical inferences to quantify and analyze economic theories by leveraging tools ranging from frequency distributions to simple and multiple regression analysis.
Econometrics can be categorized as follows:
This type of econometrics relies on consumer behavior and predictive models of how one thing will respond to specific changes in some other thing.
In the case of theoretical econometrics, various statistical methods are used to figure out whether using an economic model is beneficial or futile. The methods involved include regression analyses, probability, and frequency distributions.
Applied Econometrics finds various applications when it comes to businesses. Those, who neglect the importance of Econometrics, are losing out on a number of opportunities to beat their competitors and stay ahead of them. Today, businesses find it difficult to reap benefits from respective lucrative markets due to increased competition, deflating profit margins, looming economic crisis, and other such elements. In order to be a part of the competition, they need to employ certain strategies which further require them to conduct thorough researches and collect heaps of useful data. That's where applied econometrics steps in and help businesses make inferences, and monitor and measure the impact of their decisions.
The methodology of econometrics refers to the study of the range of different approaches to undertaking the econometric analysis. It involves the following stages:
1. Statement of theory or hypothesis:
The first stage involves suggesting a theory or hypothesis explain the data being analyzed. This is followed by the specification of explanatory variables and the magnitude of the relationship between each explanatory variable and the dependent variable.
2. Specification of the mathematical model of the theory:
Once a theory or hypothesis is stated, it's time to specify a statistical model that captures the essence of the theory that the economist wishes to test. The chosen model proposes a specific mathematical relationship between the dependent variable and the explanatory variables.
3. Specification of the Statistical or Econometric model:
The third step is all about employing the most suitable statistical procedure and an econometric software package to estimate the unknown parameters (coefficients) of the model using economic data.
4. Obtaining Data:
Now that the econometricians are armed with all the tools they would need, the next step is to set out on a search-spree for the required data.
5. Estimation of the parameters of the Econometric Model
Having accumulated required data, the econometricians are now required to make the most out of the specified statistical and econometric models to estimate the parameters of the model using economic data.
6. Hypothesis testing:
Hypothesis testing refers to a formal statistical procedure in which an econometrician makes a specific statement about the true value of an economic parameter. This is followed by a statistical test that determines whether or not the estimated parameter is consistent with that hypothesis. In case the parameter lacks consistency with the proposed hypothesis, the econometrician is supposed to reject the hypothesis and start over.
7. Forecasting or Prediction:
In the event that step 6 turns out to be successful, the hypothesis and the empirical model can be used to construct a way to forecast the dependent variable.
8. Using the model for control or policy purpose:
Using the empirical model to forecast the dependent variable can further help policymakers make decisions about changes in fiscal policy to keep the economy on an even keel.
Regression analysis is employed for prediction and forecasting, where its use has substantial overlap with the field of machine learning. This technique can further used to figure out which among the independent variables are related to the dependent variable and to dig deeper into the forms of these relationships. Over the years, a lot of methods have been developed for carrying out regression analysis. Here's a list of top techniques:
These are the most familiar regression techniques/models. However, several regression models have been developed lately. Methods such as linear regression and ordinary least squares (OLS) regression are parametric. That's because here, the regression function is defined in terms of a finite number of unknown parameters that are estimated from the data. On the other hand, nonparametric regression involves procedures that permit the relapse capacity to lie in a predefined set of capacities, which might be unbounded dimensional.
These days, econometrics is conducted using statistical analysis software packages designed for these purposes, such as STATA, SPSS, or R.
Econometrics faces criticism for a number of reasons. It is often criticized for being dependent on the interpretation of raw data without making use of any logical economic theory. It is urgent that the discoveries uncovered in the information can be enough clarified by a hypothesis, regardless of whether that implies building up your very own hypothesis of the hidden procedures.
Furthermore, econometrics is worried about the connection which has got nothing to do with causation. As it were, econometrics neglects to demonstrate causation, and on the grounds that two informational collections demonstrate an affiliation, it might be deceptive. For instance, suffocating passings in pools increment with GDP. Does a developing economy cause individuals to suffocate? Obviously not, however maybe more individuals purchase pools when the economy is blasting.
That's what econometrics is all about. Students pursuing a higher degree in Economics need to be well-versed with these concepts so as to secure a bright career in the same. However, it is not always possible for them to get hold of all the twisted concepts in econometrics. That's when they feel a need to refer to certain textbooks written by expert econometricians or online resources. Here are the most referred books on econometrics that may help understand respective concepts in a better manner:
Econometrics by Fumio Hayashi (published by Princeton University Press, 2011)
Advanced Econometrics By Takeshi Amemiya (published by Harvard University Press, 1985)
These books and online resources need hours of research to polish unclear concepts. It's quite a time-consuming process which can prove to be harmful when students are already stressed about their exams and half-done assignments. That's when highly reliable assignment writing services like myassignmenthelp.com step in and make students' life easier.
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