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An overview of regression analysis
Econometrics – literally ,,economic measurement” is the quantitative measurement and analysis of actual economic and business phenomena.
Econometrics has three major uses: 1) Describing economic reality 2) Testing hypothesis about economic theory 3) Forecasting future economic activity
The simplest use of econometrics is description.
For most goods, the relationship between consumption and disposable income is expected to be positive, because an increase in disposable income will associated with increase in the consumption of the goods.
Consumer demand for a particular commodity often can be thought of as relationship between the quantity demanded (Q) and the commodity’s price (P), the price of a substitute good (Ps), and disposable income (Yd).
The second and perhaps most common use of econometrics is hypothesis testing – the evaluation of alternative theories with quantitative evidence.
Normal good – one for which the quantity demanded increases when disposable income increases.
The third and most difficult use of econometrics is to forecast or predict what is likely to happen next quarter, next year, or further into the future, based on what has happened in the past.
Nonexperimental quantitative research: 1) Specifying the models or relationships to be studied 2) Collecting the data needed to quantify the models 3) Quantifying the models with the data
Regression analysis – is a statistical technique that attempts to “explain” movements in one variable, the dependent variable, as a function of movements in a set of other variables, called the independent (or explanatory) variables, though the quantification of a single equation.
The simplest single – equation linear regression model is: Y = β0 + β1X βs – coefficient that determine the coordinates of the straight line at any point
β0 – is the constant or intercept term, it indicates the