# Question: Consider the fitting of the following model Y 0

Consider the fitting of the following model:

Y = β0 + β1X1 + β2X2 + β3X3 + ε

where

Y = tax revenues as a percentage of gross national product in a country

X1 = exports as a percentage of gross national product in the country

X2 = income per capita in the country

X3 = dummy variable taking the value 1 if the country participates in some form of

economic integration, 0 otherwise

This provides a means of allowing for the effects on tax revenue of participation in some form of economic integration. Another possibility would be to estimate the regression

Y = β0 + β1X1 + β2X2 + ε

separately for countries that did and did not participate in some form of economic integration. Explain how these approaches to the problem differ.

Y = β0 + β1X1 + β2X2 + β3X3 + ε

where

Y = tax revenues as a percentage of gross national product in a country

X1 = exports as a percentage of gross national product in the country

X2 = income per capita in the country

X3 = dummy variable taking the value 1 if the country participates in some form of

economic integration, 0 otherwise

This provides a means of allowing for the effects on tax revenue of participation in some form of economic integration. Another possibility would be to estimate the regression

Y = β0 + β1X1 + β2X2 + ε

separately for countries that did and did not participate in some form of economic integration. Explain how these approaches to the problem differ.

**View Solution:**## Answer to relevant Questions

Discuss the following statement: In many practical regression problems, multicollinearity is so severe that it would be best to run separate simple linear regressions of the dependent variable on each independent variable. The following regression was fitted by least squares to 32 annual observations on time-series data: where yt = quantity of U.S. wheat exported x1t = price of U.S. wheat on world market x2t = quantity of U.S. wheat ...The data file German Income shows 22 annual observations from the Federal Republic of Germany on percentage change in wages and salaries (y), productivity growth (x1), and the rate of inflation (x2), as measured by the gross ...The administrator of a small city has asked you to identify variables that influence the mean market value of houses in small midwestern cities. You have obtained data from a number of small cities, which are stored in the ...You have been asked to develop a multiple regression model to predict per capita sales of cold cereal in cities with populations over 100,000. As a first step you hold a meeting with the key marketing managers that have ...Post your question