Regressions are used to compare variables to determine how strong the nature of the correlation and causation between variables. Variables in regression analysis are separated into explanatory variables and endogenous variables. Explanatory variables are usually seen as policy instruments, which are variables that economists and policy makers can control or change¹. An example of a policy instrument is the supply of money, which is controlled by the Federal Reserve. The Federal Reserve must collect data on a periodic basis and the statistics will tell the Federal Reserve if there is a problem in the economy, such as inflation¹.

Regression analysis is present in almost all fields of economics. An example would be a family’s consumption expenditure being represented by the dependent variable and the family’s income, number of family members, and other factors being represented by the independent variable. A basic regression technique is the ordinary least squared regression.

References:

1. Naghshpour, Shahdad. *Statistics for Economics*. New York, NY: Business Expert, LLC, 2012.