Key - Exam 2 2009

Key - Exam 2 2009 - Key - Exam 2A Please use the data set...

Info iconThis preview shows pages 1–3. Sign up to view the full content.

View Full Document Right Arrow Icon
Key - Exam 2A Please use the data set Exam2 – Demand for Money.xls for all analyses. Variables in the Excel spreadsheet are for the years 1960-1983 and are defined as follows: ± GNP – the U.S. Gross National Product in billions of dollars. ± M1 – U.S. demand for money in billions of dollars. ± TBillR – Treasury Bill Rate in percent. 1. Before you do anything, save the Excel spreadsheet in the Dropbox as “ yourlastname Exam2.xls .” Then click the “Save” icon often as you work. We have had crashes in the lab, and we are under time constraints. 2. These data will be used to estimate a demand function for money for the U.S. The demand for money should be affected by both the cost of holding money (a price of money – T-Bill Rates) and a measure of income for the economy (GNP): 01 2 tt t t M 1T B i l l R G N P u β ββ =+ + + (5) a. Every regression model has certain parts. For the model above, explain/name each of the elements (i.e., what are: M1, the β s, TBillR , and u ?) M1 is the dependent variable . TBillR and GNP are the independent variables – they cause the dependent variable to change. The β s are the population parameters – the constants that define how the independent variables affect the dependent variable. u is the disturbance, the random component of the model . (4) b. Before completing any analyses, what expectations do you have for β 1 . How is this used in a hypothesis test. This is a demand function – the demand for money – and TBill Rate is used to measure the price of holding money, so we expect the effect β 1 to be negative . This expectation, β 1 < 0 , is used for the alternative hypothesis. (6) 3. In Excel , create a correlation matrix/table for the three variables, Money Demand, T-Bill Rates and GNP. Briefly interpret each correlation coefficient . There are very strong positive correlations among all variables . We can see that GNP and M1 are nearly perfectly positively correlated. M1and TBillR also has a very strong positive correlation of 0.856 as do the variables TBillR and GNP (correlation of 0.874). These strong positive correlations among the independent variables suggest that omitting one of them, if they were important, would result in specification bias (more later).
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
(6) 4. Use Excel functions
Background image of page 2
Image of page 3
This is the end of the preview. Sign up to access the rest of the document.

Page1 / 5

Key - Exam 2 2009 - Key - Exam 2A Please use the data set...

This preview shows document pages 1 - 3. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online