What Is Econometrics?

What Is Econometrics?
Econometrics is the use of statistical and mathematical models to develop theories or test existing hypotheses in economics and to forecast future trends from historical data. It subjects real-world data to statistical trials and then compares the results against the theory being tested.
Depending on whether you are interested in testing an existing theory or in using existing data to develop a new hypothesis, econometrics can be subdivided into two major categories: theoretical and applied. Those who routinely engage in this practice are commonly known as econometricians.
KEY TAKEAWAYS

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  Econometrics is the use of statistical methods to develop theories or test existing hypotheses in economics or finance.
  
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  Econometrics relies on techniques such as regression models and null hypothesis testing.
  
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  Econometrics can also be used to try to forecast future economic or financial trends.
  
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  As with other statistical tools, econometricians should be careful not to infer a causal relationship from statistical correlation.
  
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  Some economists have criticized the field of econometrics for prioritizing statistical models over economic reasoning.
  

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Understanding Econometrics
Econometrics analyzes data using statistical methods in order to test or develop economic theory. These methods rely on statistical inferences to quantify and analyze economic theories by leveraging tools such as frequency distributions, probability, and probability distributions, statistical inference, correlation analysis, simple and multiple regression analysis, simultaneous equations models, and time series methods.
Econometrics was pioneered by Lawrence Klein, Ragnar Frisch, and Simon Kuznets. All three won the Nobel Prize in economics for their contributions.123 Today, it is used regularly among academics as well as practitioners such as Wall Street traders and analysts.
An example of the application of econometrics is to study the income effect using observable data. An economist may hypothesize that as a person increases their income, their spending will also increase.
If the data show that such an association is present, a regression analysis can then be conducted to understand the strength of the relationship between income and consumption and whether or not that relationship is statistically significant—that is, it appears to be unlikely that it is due to chance alone.