Econometrics

What is Econometrics?

Econometrics is an understanding of relations of economic data by using statistical model referencing and getting an observation or pattern from provided data for developing the approximation future trend. Econometrics is simply economic with the additive of Mathematics and Statistics and helps in forecasting and estimation by applying statistical methods.

Methods of Econometrics

The more common methods are:

Examples of Econometrics for Finance

Below are examples of econometrics for Finance

Econometrics Example #1

Michael has an income of $50000. The spending pattern of his income is 10000 – Fixed rent and other household expenses is 50% of his gross income earned during the period.

Multiple linear regression is one of the best tools to develop a relationship on the basis of past trends.

By using the equation one can get the amount Michael will spend on the basis of his earned income.

• Expense = B₀ (Fixed rent) + B₁ (other household exp.) + e (Error term)
• = 10000 + 50% (50000)
• = 35000

Error term shows that there can be little up or down deviation from the result arrived by applying the statistical tools.

Econometrics Example #2

Let’s find out the salary of the person on the basis of his working experience

Minimum wages: $10K

On the basis of regression on the person salary its find out that B₁ = 2000

So by applying the method, it can be understood as a person will get the minimum wages of 10000 + (2000*No. of years of experience)

These 10K and 2K are hypothesized values and are to be tested on statistical tools like t-test & F-test. If they are not significantly different from 0, then the hypothesized value has no relevance and test need to be done again to get a different value.

How does Econometrics Works in Finance?

Inputs	Output Data
Theories referred	Parameters used in data
Models selected	Confidence area drawn
Assumption taken	Test of hypothesis conduct
Methods applied	Graphics tools used

Advantages of Econometrics

Here are the advantages of Econometrics.

• By using the tools or applied econometrics one can be able to convert data into a specific model for the purpose of making the decision that supports empirical data.
• Help to getting the specified pattern or result from the scattered data.
• Benefitted to enable us to retrieve the relevant information from the basket of information.

Disadvantages of Econometrics

There are some disadvantages of Econometrics.

• Sometimes the relation build-up by the economic tools is spurious i.e. even no relation exists between two variables but the model is showing a pattern on the basis of past information. Ex. Correlation between rain and Dividend paid
• This shows that whenever the rain comes in a quarter then only the company declares the dividend in that period. Even the rain has no relation of dividend paid but as per the trend establish it can provide the false signals which can lead to the wrong decision.
• There is always a choice between simplicity and accuracy. Model specification is a very important task in applied economics. Choosing less variable can help in simplicity and provide faster result but it can be inaccurate due to insufficient information and if one goes for the high no. of variable then the model can be critical, uneconomical, or gigantic.
• There can be a problem of multicollinearity between the variables used in the data. It’s very important that the variable chosen should have been a low correlation between two explanatory variables. The model left this section on the model user.

Important Points

• The tools of econometrics are very judgmental. The final conclusion can vary from user to user.
• Result depending on the type and specification of the model. Results are model-oriented.
• Data Economical, Feasible, Time to get results to be considered while applying the model.
• It can be applied both on Cross-sectional or time-series data.
• There should be a perimeter or test required to conduct the resulting effectiveness like f-test in excel, T-test, Statistics table, ANOVA table analysis by using tool packs.

Conclusion

• Always remember to check that whether the result comes out are statistically significant for taking decisions
• It evolves out of the model or perimeter under consideration
• The result must be empirically as well as futuristic favorable.
• It is a reiterative exercise and different models can also be applied to the single problem to get better insights.
• Overfitting or underfitting of results can be diluted by an improved model specification.

Recommended Articles

This has been a guide to what is econometrics and its definition. Here we discuss top methods and examples of Econometrics for Finance along with advantages and disadvantages. You may learn more about our articles below on accounting –

• Linear Regression Examples in Excel
• Create Data Model in Excel
• Adjusted R Squared Calculation
• Regression vs ANOVA