1. Determents of Housing Prices

2. What & WHY Our goal was to discover the determents of rising home prices and to identify any anomies in historic housing prices. To figure out if current housing market is over priced – if there is a real estate bubble.

3. Hypothesis Population and wealth increases drive up home prices

4. HOW 1)We collected average home prices in the US: on a monthly basis (1975-2002). 2) Then we gathered data we thought would be good determents of home prices 3) Set up a model and ran a regression 4) Modified our model 5) Interpreted the results

5. Exploratory Data Analysis Variables: Mortgage rates, unemployment rates,CPI, PPI, S&P Index (alterative INV), and income per capita. Sources: Economagic and the St. Louis Fed.

6. STAT Analysis

7. mean home prices vs income per capita

9. Dependent Variable: AVGHOMESALES Method: Least Squares Date: 11/20/02 Time: 18:16 Sample: 1975:01 2002:07 Included observations: 331 VariableCoefficientStd. Errort-StatisticProb. INCPERCAP7.0690480.021993321.42480.0000 R-squared0.976423 Mean dependent var126863.7 Adjusted R-squared0.976423 S.D. dependent var50204.56 S.E. of regression7708.746 Akaike info criterion20.74112 Sum squared resid1.96E+10 Schwarz criterion20.75260 Log likelihood-3431.655 Durbin-Watson stat0.383130

10. all variables

11. Dependent Variable: AVGHOMESALES Method: Least Squares Date: 11/20/02 Time: 18:03 Sample: 1975:01 2002:07 Included observations: 331 VariableCoefficientStd. Errort-StatisticProb. CPI-2620.066479.5200-5.4639350.0000 PPI1900.434253.71327.4904810.0000 UNEMP_RATE-1308.266486.8899-2.6869850.0076 INCPERCAP8.7754420.9470949.2656540.0000 MRTG_RATE-657.8159311.1963-2.1138290.0353 MONTHS385.3148172.78062.2300810.0264 C30352.7812264.192.4749110.0138 R-squared0.984578 Mean dependent var126863.7 Adjusted R-squared0.984292 S.D. dependent var50204.56 S.E. of regression6292.141 Akaike info criterion20.35291 Sum squared resid1.28E+10 Schwarz criterion20.43332 Log likelihood-3361.407 F-statistic3447.484 Durbin-Watson stat0.615215 Prob(F-statistic)0.000000

12. time vs home price

13. Dependent Variable: AVGHOMESALES Method: Least Squares Date: 11/20/02 Time: 18:39 Sample: 1975:01 2002:07 Included observations: 331 VariableCoefficientStd. Errort-StatisticProb. MONTHS517.87494.625557111.95950.0000 C40896.51885.960246.160660.0000 R-squared0.974425 Mean dependent var126863.7 Adjusted R-squared0.974347 S.D. dependent var50204.56 S.E. of regression8041.062 Akaike info criterion20.82853 Sum squared resid2.13E+10 Schwarz criterion20.85151 Log likelihood-3445.122 F-statistic12534.92 Durbin-Watson stat0.341824 Prob(F-statistic)0.000000

15. Further Analysis Changes in income per capita have no effect on changes in mean home prices This is also true for changes in mortgage, unemployment rates, S&P and CPI.

20. Conclusions 1) real estate prices move in long-term cycles 2) time is most significant variable; it that helps explain price increases:

22. Center for Economic and Policy Research -in the last 7 years, home sale prices have increased nearly 30 percent more than the overall rate of inflation -there is no obvious explanation for a sudden increase in relative demand for housing which could explain the price rise - the only plausible explanation for sudden surge in home prices is the existance of a housing bubble -major factor driving housing sales is the expectation that housing prices will be higher in the future - the collapse of the bubble will lead to a loss of between $1.3 trillion and $2.6 trillion of housing wealth

23. Questions ?