RYAN DONNELLY
The remainder of the paper is arranged as follows: Part 2. documents the data on MORTG rates and HOUST; Part 3. presents the economic theory of the Keynesian Investment Function; Part 4. presents the forecast for MORTG for the year 20002002; Part 5. discuss the economic importance of the forecast; Part 6. addresses effects on economic policy.
Part 2.Data
The MORTG and HOUST data were taken from the Federal Reserve Bank of St. Louis Federal Reserve Economic Data (FRED).The data reported on a monthly basis measured in billions of chained 1992 dollars at seasonally adjusted annual rates.
Part 3.The Keynesian Function
to Forecast Interest Rates
HOUST cannot change the interest rate by itself, but it can help predict where the interest rate is going.Housing starts still represents a demand for loanable funds.Monthly data for lagged MORTG and HOUST are used to forecast the interest rate over the next three years.The prediction for interest rates will be determined by the Keynesian investment function, which is:
I=f(r)(1.
Inverted the investment function will become:
R=f(I)(2
This simple model will be used to forecast 30 year mortgage interest rates.The r_{t }is the interest rate once the forecast has been made.The function shows that either variable r_{t3 }or H_{t3 }can influence interest rates (rt). The Keynesian Investment Function becomes:
r_{t} = f (r_{t3}, H_{t3})(3.
Each explanatory variable can change the forecast of the interest rate independently.If, for example, MORTG started to increase, then it would send the forecast to increase or work viceversa.Now if HOUST started to decline then the interest rate would tend to be lower for it would cause the people to start building, if the HOUST started to increase, then interest rate would rise.
Part 4.Estimates of 30year
Mortgage Rate based on New Housing Starts
The investment function, equation 2, was estimated using monthly data from January 1990 to January 2001.When modified, the equation to handle the lagged MORTG and HOUST written as:
MORTG_{t} = f (MORTG_{t3}, HOUST_{t3})(4.
When the data was lagged, then the regression results are (with the tstatistics in parentheses):
MORTG_{t} = f (9.529313(0.05876)*MORTG
(0.00109)HOUST(5.
The regression for the project was only run once on the lagged portions ofthe project.The adjusted Rsquare for the threeyear lagged regression was 5 percent.Now this is the first indication that that there is not a good correlation between these MORTG and HOUST.Housing starts is not a good indicator for predicting interest rates.In TABLE 1, we will see the forecast for the interest rate.
DateMortgage Rate








































































Part 6.Forecast Implications
30year mortgage rates should stay around the same as they are now.A large change in interest rates is not in the picture to make any impact on the future of the economy.They should decrease by about .01 percent each year for the next three years.If this forecast holds true, then we can look at having the next couple of years to be prosperous for the housing industry.This is all because housing starts can be determined by the interest rate.
Federal Reserve Board of St. Louis, Federal Reserve Economic Data (FRED) http://www.stls.frb.org.fred/