In the previous article, Assumptions of Classical Linear Regression Model (CLRM), we discussed the assumptions of CLRM. In this article, we discuss the variance and standard error of OLS estimators and the Gauss-Markov Theorem. It has been shown in the post Simple Linear Regression Model that the OLS estimates are
In the previous post, we discussed how to estimate a sample regression model, i.e., and . by applying the OLS method on sample data, both in simple and multiple linear regression models. You can read these posts here: A Numerical Example of Multiple Linear Regression by Hand and Simple Linear Regression
Introduction of Regression Through Origin Models So far we have studied models like Where intercept is present. An economic example of these models is the Keynes consumption function written as: Where is autonomous consumption i.e., level of consumption when income is zero. In some cases, we wish to impose the
What is Multiple Linear Regression? The linear regression model shows the linear dependence of one variable on one or more independent variables. A simple linear regression model consists of the linear dependence of one variable on only one independent variable. It is also called a bivariate or two-variable regression model. Such as
Goodness of Fit So far, we have no way of measuring how well the explanatory or independent variable, X, explains the dependent variable, Y. In other words, we must know how well the OLS regression line fits the data. Are the observations tightly clustered around the regression line, or are
Simple Linear Regression Model Simple Linear Regression Model is used to estimate the relationship between one dependent and one independent variable. It is also called bivariate or two variable regression model. For example, regression of consumption on disposable income, regression of sales revenue on advertisement expenses, regression of log of
In the previous post we explained the concept of regression analysis in detail along with its meaning, uses and objectives. Moreover, we also discussed how regression analysis differs from correlation analysis and causation. Further, we differentiate conditional and unconditional mean. To read previous article click Nature of Regression Analysis. In
In the previous lecture we discuss the types and nature of economic data used in any empirical economic analysis. To read click on Types of Economic Data. We also discuss the sources of obtaining economic data. In this post will discuss about the nature of regression analysis, its objectives, uses in
Types of Economic Data Data is central to any empirical analysis. An empirical analysis uses data to test a hypothesis or theory or to estimate a relationship. The first step in any empirical analysis is to formulate a research question. Model specification is the next step followed by obtaining data.
Introduction Welcome to the fascinating world of econometrics! Studying econometrics bridges the gap between being a student of economics and becoming a practicing economist. It equips you with essential tools for analyzing economic data, empirically testing economic theories, providing numerical estimates of economic relationships, and forecasting future events. In this
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