Question

Answer the following:

1. What is Econometrics?

2. What is the Structure of Economic Data

3. What are the steps in Econometric Modelling

4. What are the steps in Empirical Economic Analysis

5. Definition of the Simple Regression Model

6. What is the Interpretation of Regression Output

7. Define OLS

Answer 1

1.The word econometrics mean economic measurement which quantifies and verifies the expectations from the theories of economy. Econometrics is defined as the statistical application of economic data to find the empirical content to economic relations. It utilizes mathematics, theory or other statical expectations in order to measure economic phenomena. It gives the tools which helps us to collect useful information on the relevant economic policy issues from th provided data.

2. Economic structure explains the changing balance output , incomes , considered employments and trade from various economic sectors. Cross sectional data and time series data are the two structures of data in economics. The set od data includes sample observations of considered unit or individual agents of economics in a stretch  or point of time is called cross sectional data set. On other hand , set of data having one or more variables taken in intervals of time or in consecutive periods is defined as time series data set.

3. For successful economic modeling firstly review the appropriate literature effectively. Analyze both empirical and theoretical relevance. then it is necessary to conceptionalise th relationship which taken for modeling. Should have knowledge on the research gaps and problems.The identify different methods for the study of the topic.

4. The steps in empirical economic analysis are :

* appropriate choosing of a hypothesis or any observed phenomenon

* Analyze and implement the objectives or aim of the analysis

* Develop a economic model for the analysis

*Econometric model development

* Find the values of coefficients

* Proper validation and data analysis

5. Simple regression model is explained as the statisttical method which allows to analyze the relationships within two successive variables. The one of the variable is represented as X is taken as he predictor , independent or explanatory variable in the model.

6. Regression output comprises of four kinds of information.  

* R^2 value

*adjusted R^2 value

* F value

* Coefficients of constants and independent variables

Regression model is the main character of egression analysis. In the model P values used to find the relationships which is identified in the population.The regression output finds the values of these regression variables. The values of coefficient in regression is the measure of correlation within the dependent and independent variable which shows whether the correlation is positive or negative.

7. Ordinary least squares is the kind of linear least squares it is used to determine the variables in linear regression model of statistics. This method connects the data points and decreases the total sum of squared difference within the noted values and appropriate fitted values.