Business and Management
Submitted By zandy
Project of Econometrics
In this paper our motivation to discuss effects of models by estimating its parameters in matrix and scalar notations, its variances checked via different formal and informal methods, checked the depends of error terms and analyze that auto-correlation whether it is positive, zero or negative, we also check the data is normality distributed or not, and check the structural stability.
We consider the civilian unemployment rate and manufacturing hourly compensation in US dollars for simple regression.
We consider the data in multiple regressions on Wildcat activity. Wildcats are wells drilled to find and produce oil and gas in an improved area or to find a new reservoir in a field previously found to be productive of oil or gas or to extend the limit of a known oil or gas reservoir.
For hetroscedasticity tests we consider for simple regression wholesale and consumer price index data and for multiple regressions we take same data which we above used for multiple regression.
We consider Fertility and other data for 64 countries for the F-test, Durbin-Watson test and CHOW test where child mortality depends upon the female literacy rate, per capita GNP and total fertility rate.
I took the data from the Guajarati book. Table 5.10 on page no. 158 represents the data which we used for simple regression for hetroscedasticity tests. Table 7.7on page no. 237 represents the data which I used for multiple regressions. Table 6.4 on page no. 185 represents the data which I used for the F-test, Durbin-Watson test and Chow test.
REGRESSION AND METHODOLOGY
Consider model for multiple regression i.e.
Where Y= thousands of wildcats X2= per barrel price
X3= domestic output.
Here thousands of wildcats are a dependent variable and per barrel price and domestic output are independent variables. In…...