What is 'Econometrics'
Econometrics is the application of statistical and mathematical theories in economics for the purpose of testing hypotheses and forecasting future trends. It takes economic models, tests them through statistical trials and then compare and contrast the results against reallife examples. Econometrics can therefore be subdivided into two major categories: theoretical and applied.
BREAKING DOWN 'Econometrics'
Econometrics uses a combination of economic theory, math and statistical inferences to quantify and analyze economic theories by leveraging tools such as frequency distributions, probability and probability distributions, statistical inference, simple and multiple regression analysis, simultaneous equations models and time series methods.
An example of a reallife application of econometrics would be to study the income effect. An economist may hypothesize that as a person increases his income, his spending will also increase. The hypothesis can be tested and proven using econometric tools like frequency distributions or multiple regression analysis.
Econometrics was pioneered by Lawrence Klein, Ragnar Frisch and Simon Kuznets. All three won the Nobel Prize in economics for their contributions.
The Methodology of Econometrics
Econometrics uses a fairly straightforward approach to economic analysis. The first step to econometric methodology is to look at a set of data and define a specific hypothesis that explains the nature and shape of the set. The explanatory variables being analyzed are specified during this step; the relationship between the dependent and independent variables are also specified. This stage of econometrics relies heavily on economic theory that will be tested for validity in the later stages.
The second step in the methodology is to choose the specific statistical tool or model that will test the hypothesis being posed. An effective model outlines a specific mathematical relationship between the explanatory variable and the dependent variable being tested. The most common relationship is linear, meaning that any change in the explanatory variable will have a positive correlated with the dependent variable. This is why the multiple linear regression model is the most used tool in econometrics, because it expresses relationships linearly.
The third step is the most passive in that all the data is imputed into a econometric software program. The program then uses the statistical model of choice to estimate the results, using the economic data provided.
The fourth and final step is the most important in proving the validity of a hypothesis. Economists will take the results from the program and conduct a small test. The test will help the economist understand whether or not the model resulted in good predictions or not. If the economist finds what he expected than he may safely assume that the hypothesis is true. If, however, the economist does not find what he expected, new hypotheses or inferences are needed.

Mathematical Economics
Mathematical economics is a form of economics that relies on ... 
Lawrence Klein
An American economist and winner of the 1980 Nobel Memorial Prize ... 
Hypothesis Testing
A process by which an analyst tests a statistical hypothesis. ... 
Regression
A statistical measure that attempts to determine the strength ... 
OneTailed Test
A onetailed test is a statistical test in which the critical ... 
Simon Kuznets
A RussianAmerican economist and statistician who won the 1971 ...

Financial Advisor
How Do Companies Forecast Oil Prices?
Read about the different forecasting methods that businesses use to predict future crude oil prices, and why it's so difficult to guess correctly. 
Investing
Hypothesis testing in finance: Concept and examples
When you're indecisive about an investment, the best way to keep a cool head might be test various hypotheses using the most relevant statistics. 
Trading
4 ways to forecast currency changes
Whether you are a business or a trader, forecasting currency exchanges helps guide your decisions to minimize risks and maximize returns. 
Investing
Efficient Market Hypothesis
An investment theory that states it is impossible to "beat the market". 
Investing
Seven Controversial Investing Theories
Find out information about seven controversial investing theories that attempt to explain and influence the market as well as the actions of investors. 
Investing
What's a Sensitivity Analysis?
Sensitivity analysis is used in financial modeling to determine how one variable (the target variable) may be affected by changes in another variable (the input variable). 
Investing
The Difference Between Finance And Economics
Learn the differences between these closely related disciplines and how they inform and influence each other. 
Insights
The History of Economic Thought
Economics is a vital part of every day life. Discover the major players who shaped its development. 
Investing
Does Weather Affect the Stock Market?
Find out if the weather can change the stock market, and why economists and meteorologists will probably always struggle to know the answer.

What is the difference between linear regression and multiple regression?
Learn the difference between linear regression and multiple regression and how multiple regression encompasses not only linear ... Read Answer >> 
How can I create a linear regression in Excel?
Learn the steps involved in creating a linear regression chart in Microsoft Excel. Read Answer >> 
How is correlation used differently in finance and economics?
Take a look at the similarities and differences between how statistical correlation is applied in economics as opposed to ... Read Answer >> 
What are the differences between weak, strong and semistrong versions of the Efficient ...
Discover how the efficient market theory is broken down into three versions, the hallmarks of each and the anomalies that ... Read Answer >> 
What is the difference between financial forecasting and financial modeling?
Understand the difference between financial forecasting and financial modeling, and learn why a company should conduct both ... Read Answer >> 
What is the most important type of data used in business analytics?
Consider what makes data useful in business analytics, and why companies should search for the types of data that provide ... Read Answer >>