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 ... 
Ragnar Frisch
A Norwegian economist and joint winner in 1969 of the very first ... 
Jan Tinbergen
A Dutch economist who won the Nobel Memorial Prize in Economics ... 
Multiple Linear Regression  MLR
Multiple linear regression (MLR) is a statistical technique that ... 
Regression
A statistical measure that attempts to determine the strength ...

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. 
Trading
The Linear Regression of Time and Price
This investment strategy can help investors be successful by identifying price trends while eliminating human bias. 
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
Stock and Flow Variables Explained: A Closer Look at Apple
The difference between stock and flow variables is an essential concept in finance and economics. We illustrate with financial statements from Apple Inc. 
Investing
Efficient Market Hypothesis: Is The Stock Market Efficient?
Deciding whether it's possible to attain aboveaverage returns requires an understanding of EMH. 
Investing
Arbitrage Pricing Theory: It's Not Just Fancy Math
What are the main ideas behind arbitrage pricing theory? Find out how this model estimates the expected returns of a welldiversified portfolio.

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 variables are most important when making a prediction through sensitivity analysis?
Explore sensitivity analysis and how this method considers different variables to determine a course of action based on statistical ... 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 >> 
Has the Efficient Market Hypothesis been proven correct or incorrect?
Explore the efficient market hypothesis and understand the extent to which this theory and its conclusions are correct or ... Read Answer >> 
Are perfect competition models in economics useful?
Take a look at some of the arguments made by the proponents and critics of the theory of perfect competition in contemporary ... Read Answer >> 
How can you calculate correlation using Excel?
Find out how to calculate the Pearson correlation coefficient between two data arrays in Microsoft Excel through the CORREL ... Read Answer >>