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Why Can’t I Afford a Home? By: Philippe Bonnan Emelia Bragadottir Troy Dewitt Anders Graham S. Matthew Scott Lingli Tang.

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Presentation on theme: "Why Can’t I Afford a Home? By: Philippe Bonnan Emelia Bragadottir Troy Dewitt Anders Graham S. Matthew Scott Lingli Tang."— Presentation transcript:

1 Why Can’t I Afford a Home? By: Philippe Bonnan Emelia Bragadottir Troy Dewitt Anders Graham S. Matthew Scott Lingli Tang

2 Organization Time Series Regression Time Series Regression United States: Ten year regression of explanatory variables against median price of a home United States: Ten year regression of explanatory variables against median price of a home

3 Organization Cross Section Regression Cross Section Regression 14 Different Areas for 2 separate years: 2000 and 2005 14 Different Areas for 2 separate years: 2000 and 2005

4 The Variables Median Price of a Home (dependent variable) Median Price of a Home (dependent variable) β 1 = Unemployment Rate β 1 = Unemployment Rate β 2 = Median Family Income β 2 = Median Family Income β 3 = Building Permits β 3 = Building Permits β 4 = Population β 4 = Population β 5 = Distance from the coast (Not applicable for Time-Series) β 5 = Distance from the coast (Not applicable for Time-Series) Β 6 = Mortgage Rates (Not applicable for Cross-Section) Β 6 = Mortgage Rates (Not applicable for Cross-Section)

5 Graphical Relationships The following graphs compare the median price of a home with each variable over a period of ten years The following graphs compare the median price of a home with each variable over a period of ten years Each variable uses 1996 as an index for comparison (For each variable, the value for 1996 is set to 1) Each variable uses 1996 as an index for comparison (For each variable, the value for 1996 is set to 1)

6 Unemployment Rate

7 Median Family Income

8 Building Permits

9 Population

10 Mortgage Rates

11 Our Hypothesis Ho: The explanatory variables in the regression don’t explain the median price of a home Ho: The explanatory variables in the regression don’t explain the median price of a home i.e. β 1 = β 2 = … =β n =0 Ha: At least one explanatory variable explains the median price of a home Ha: At least one explanatory variable explains the median price of a home i.e. β 1 ≠0 or β 2 ≠0 … or β n ≠0

12 Results for Time Series Analysis (U.S.)

13 Time Series Analysis – Correlation Matrix PRICEHOME MORTGAGE RATE INCOMEPERMITSPOPU LATION UNEMPLOYMENT RATE PRICE1-0.9085480.9237690.9784690.9525240.436929 HOMEMORTGAGERATE-0.908551-0.91219-0.93725-0.91575-0.573675 INCOME0.923769-0.91218810.9050820.9944860.413594 PERMITS0.978469-0.9372480.90508210.937110.385133 POPULATION0.952524-0.9157530.9944860.9371110.382568 UNEMPLOYMENTRATE0.436929-0.5736750.4135940.3851330.3825681

14 Time Series Regression Dependent Variable: PRICE Dependent Variable: PRICE Method: Least Squares Method: Least Squares Date: 12/06/06 Time: 09:38 Date: 12/06/06 Time: 09:38 Sample: 1 10 Sample: 1 10 Included observations: 10 Included observations: 10 VariableCoefficientStd. Errort-StatisticProb. VariableCoefficientStd. Errort-StatisticProb. HOMEMORTGAGERATE 632665. 1151196. 1.418234 0.2291 HOMEMORTGAGERATE 632665. 1151196. 1.418234 0.2291 INCOME-6.116375 6.401278-0.955493 0.3934 INCOME-6.116375 6.401278-0.955493 0.3934 PERMITS 0.092208 0.056354 1.636246 0.1771 PERMITS 0.092208 0.056354 1.636246 0.1771 POPULATION 0.006230 0.004887 1.274867 0.2714 POPULATION 0.006230 0.004887 1.274867 0.2714 UNEMPLOYMENTRATE 1033710. 358705.7 2.881777 0.0449 UNEMPLOYMENTRATE 1033710. 358705.7 2.881777 0.0449 C-1622644. 933044.8-1.739085 0.1570 C-1622644. 933044.8-1.739085 0.1570 R-squared 0.990920 Mean dependent var 153950.0 R-squared 0.990920 Mean dependent var 153950.0 Adjusted R-sq. 0.979571 S.D. dependent var 34063.41 Adjusted R-sq. 0.979571 S.D. dependent var 34063.41 S.E. of regression 4868.733 Akaike info criterion 20.10276 S.E. of regression 4868.733 Akaike info criterion 20.10276 Sum squared resid 94818259 Schwarz criterion 20.28432 Sum squared resid 94818259 Schwarz criterion 20.28432 Log likelihood-94.51382 F-statistic 87.30830 Log likelihood-94.51382 F-statistic 87.30830 Durbin-Watson sta 3.279181 Prob(F-statistic) 0.000357 Durbin-Watson sta 3.279181 Prob(F-statistic) 0.000357 Significant Test with 10 observations and Alpha = 0.05 Unemployment Rate is the only significant variable Therefore we reject the null hypothesis because unemployment is Therefore we reject the null hypothesis because unemployment isSignificant.

15 Explanation of results for time series analysis T-stats for coefficients of the explanatory variables are not significant (except unemployment) but coefficient of determination, R-squared, is high. T-stats for coefficients of the explanatory variables are not significant (except unemployment) but coefficient of determination, R-squared, is high. This means that the explanatory variables are highly correlated. This means that the explanatory variables are highly correlated. This is explained in the correlation matrix on a previous slide. This is explained in the correlation matrix on a previous slide. This is an example of multicollinearity. This is an example of multicollinearity. Therefore we decided to drop out one of the explanatory variables in order to erase the multicollinearity. Therefore we decided to drop out one of the explanatory variables in order to erase the multicollinearity.

16 Drop Mortgage Rate Dependent Variable: PRICE Dependent Variable: PRICE Method: Least Squares Method: Least Squares Date: 12/06/06 Time: 19:25 Date: 12/06/06 Time: 19:25 Sample: 1 10 Sample: 1 10 Included observations: 10 Included observations: 10 VariableCoefficientStd. Errort-StatisticProb. VariableCoefficientStd. Errort-StatisticProb. INCOME-12.22777 5.190382-2.355851 0.0651 INCOME-12.22777 5.190382-2.355851 0.0651 PERMITS 0.027076 0.035811 0.756096 0.4837 PERMITS 0.027076 0.035811 0.756096 0.4837 POPULATION 0.010664 0.004118 2.589475 0.0489 POPULATION 0.010664 0.004118 2.589475 0.0489 UNEMPLOYMENTRATE 824150.2 358395.3 2.299557 0.0698 UNEMPLOYMENTRATE 824150.2 358395.3 2.299557 0.0698 C -2334912. 862220.4-2.708022 0.0424 C -2334912. 862220.4-2.708022 0.0424 R-squared 0.986355 Mean dependent var 153950.0 R-squared 0.986355 Mean dependent var 153950.0 Adjusted R-squared0.975438 S.D. dependent var 34063.41 Adjusted R-squared0.975438 S.D. dependent var 34063.41 S.E. of regression 5338.490 Akaike info criterion 20.31013 S.E. of regression 5338.490 Akaike info criterion 20.31013 Sum squared resid 1.42E+08 Schwarz criterion 20.46142 Sum squared resid 1.42E+08 Schwarz criterion 20.46142 Log likelihood-96.55063 F-statistic 90.35561 Log likelihood-96.55063 F-statistic 90.35561 Durbin-Watson stat 2.343565 Prob(F-statistic) 0.000075 Durbin-Watson stat 2.343565 Prob(F-statistic) 0.000075 Significant Test with 10 observations and Alpha = 0.05 Significant Test with 10 observations and Alpha = 0.05 Population is the only significant variable Population is the only significant variable Unemployment now becomes insignificant Unemployment now becomes insignificant

17 Drop Permits Dependent Variable: PRICE Dependent Variable: PRICE Method: Least Squares Method: Least Squares Date: 12/06/06 Time: 19:27 Date: 12/06/06 Time: 19:27 Sample: 1 10 Sample: 1 10 Included observations: 10 Included observations: 10 VariableCoefficientStd. Errort-StatisticProb. VariableCoefficientStd. Errort-StatisticProb. HOMEMORTGAGERATE 97613.97 770997.7 0.126607 0.9042 HOMEMORTGAGERATE 97613.97 770997.7 0.126607 0.9042 INCOME-15.51536 3.264526-4.752713 0.0051 INCOME-15.51536 3.264526-4.752713 0.0051 POPULATION 0.013532 0.002301 5.880010 0.0020 POPULATION 0.013532 0.002301 5.880010 0.0020 UNEMPLOYMENTRATE 998640.4 413787.3 2.413415 0.0606 UNEMPLOYMENTRATE 998640.4 413787.3 2.413415 0.0606 C-2949376. 533483.0-5.528529 0.0027 C-2949376. 533483.0-5.528529 0.0027 R-squared 0.984843 Mean dependent var 153950.0 R-squared 0.984843 Mean dependent var 153950.0 Adjusted R-squared 0.972717 S.D. dependent var 34063.41 Adjusted R-squared 0.972717 S.D. dependent var 34063.41 S.E. of regression 5626.411 Akaike info criterion 20.41518 S.E. of regression 5626.411 Akaike info criterion 20.41518 Sum squared resid 1.58E+08 Schwarz criterion 20.56648 Sum squared resid 1.58E+08 Schwarz criterion 20.56648 Log likelihood-97.07592 F-statistic 81.21998 Log likelihood-97.07592 F-statistic 81.21998 Durbin-Watson sta 2.325004 Prob(F-statistic) 0.000098 Durbin-Watson sta 2.325004 Prob(F-statistic) 0.000098 Both Income and Population are now significant explanatory variables Both Income and Population are now significant explanatory variables

18 Drop Population Dependent Variable: PRICE Dependent Variable: PRICE Method: Least Squares Method: Least Squares Date: 12/06/06 Time: 19:28 Date: 12/06/06 Time: 19:28 Sample: 1 10 Sample: 1 10 Included observations: 10 Included observations: 10 Variable CoefficientStd. Errort-StatisticProb. Variable CoefficientStd. Errort-StatisticProb. HOMEMORTGAGERATE 2571603. 938466.0 2.740220 0.0408 HOMEMORTGAGERATE 2571603. 938466.0 2.740220 0.0408 INCOME 1.992947 0.761256 2.617971 0.0472 INCOME 1.992947 0.761256 2.617971 0.0472 PERMITS 0.157815 0.024359 6.478855 0.0013 PERMITS 0.157815 0.024359 6.478855 0.0013 UNEMPLOYMENTRATE 967915.6 376516.0 2.570715 0.0500 UNEMPLOYMENTRATE 967915.6 376516.0 2.570715 0.0500 C-442695.1 125212.2-3.535560 0.0166 C-442695.1 125212.2-3.535560 0.0166 R-squared 0.987231 Mean dependent var 153950.0 R-squared 0.987231 Mean dependent var 153950.0 Adjusted R-squared0.977016 S.D. dependent var 34063.41 Adjusted R-squared0.977016 S.D. dependent var 34063.41 S.E. of regression 5164.203 Akaike info criterion 20.24374 S.E. of regression 5164.203 Akaike info criterion 20.24374 Sum squared resid 1.33E+08 Schwarz criterion 20.39503 Sum squared resid 1.33E+08 Schwarz criterion 20.39503 Log likelihood-96.21871 F-statistic 96.64315 Log likelihood-96.21871 F-statistic 96.64315 Durbin-Watson stat3.147208 Prob(F-statistic) 0.000064 Durbin-Watson stat3.147208 Prob(F-statistic) 0.000064 When we drop Population, all our explanatory variables now become significant When we drop Population, all our explanatory variables now become significant

19 Drop Unemployment Rate Dependent Variable: PRICE Dependent Variable: PRICE Method: Least Squares Method: Least Squares Date: 12/06/06 Time: 19:29 Date: 12/06/06 Time: 19:29 Sample: 1 10 Sample: 1 10 Included observations: 10 Included observations: 10 VariableCoefficientStd. Errort-StatisticProb. VariableCoefficientStd. Errort-StatisticProb. HOMEMORTGAGERATE 266099.7 1645584. 0.161705 0.8779 HOMEMORTGAGERATE 266099.7 1645584. 0.161705 0.8779 INCOME-3.839510 9.965120-0.385295 0.7159 INCOME-3.839510 9.965120-0.385295 0.7159 PERMITS 0.082505 0.088246 0.934945 0.3927 PERMITS 0.082505 0.088246 0.934945 0.3927 POPULATION 0.004204 0.007586 0.554139 0.6034 POPULATION 0.004204 0.007586 0.554139 0.6034 C-1002577. 1424248.-0.703935 0.5129 C-1002577. 1424248.-0.703935 0.5129 R-squared 0.972069 Mean dependent var 153950.0 R-squared 0.972069 Mean dependent var 153950.0 Adjusted R-square 0.949725 S.D. dependent var 34063.41 Adjusted R-square 0.949725 S.D. dependent var 34063.41 S.E. of regression 7637.749 Akaike info criterion 21.02645 S.E. of regression 7637.749 Akaike info criterion 21.02645 Sum squared resid 2.92E+08 Schwarz criterion 21.17774 Sum squared resid 2.92E+08 Schwarz criterion 21.17774 Log likelihood-100.1322 F-statistic 43.50361 Log likelihood-100.1322 F-statistic 43.50361 Durbin-Watson stat1.359493 Prob(F-statistic) 0.000447 Durbin-Watson stat1.359493 Prob(F-statistic) 0.000447 We have no significant explanatory variables when we drop Unemployment Rate We have no significant explanatory variables when we drop Unemployment Rate

20 DROP INCOME Dependent Variable: PRICE Dependent Variable: PRICE Method: Least Squares Method: Least Squares Date: 12/06/06 Time: 09:42 Date: 12/06/06 Time: 09:42 Sample: 1 10 Sample: 1 10 Included observations: 10 Included observations: 10 VariableCoefficientStd. Errort-StatisticProb. VariableCoefficientStd. Errort-StatisticProb. HOMEMORTGAGERATE 2373126. 843852.1 2.812254 0.0374 HOMEMORTGAGERATE 2373126. 843852.1 2.812254 0.0374 PERMITS 0.140527 0.024652 5.700503 0.0023 PERMITS 0.140527 0.024652 5.700503 0.0023 POPULATION 0.001590 0.000543 2.927870 0.0327 POPULATION 0.001590 0.000543 2.927870 0.0327 UNEMPLOYMENTRATE 991406.2 352851.3 2.809700 0.0376 UNEMPLOYMENTRATE 991406.2 352851.3 2.809700 0.0376 C-749970.5 189154.5-3.964858 0.0107 C-749970.5 189154.5-3.964858 0.0107 R-squared 0.988848 Mean dependent var 153950.0 R-squared 0.988848 Mean dependent var 153950.0 Adjusted R-sq 0.979926 S.D. dependent var 34063.41 Adjusted R-sq 0.979926 S.D. dependent var 34063.41 S.E. of regression 4826.173 Akaike info criterion 20.10835 S.E. of regression 4826.173 Akaike info criterion 20.10835 Sum squared resid 1.16E+08 Schwarz criterion 20.25964 Sum squared resid 1.16E+08 Schwarz criterion 20.25964 Log likelihood-95.54174 F-statistic 110.8364 Log likelihood-95.54174 F-statistic 110.8364 Durbin-Watson sta 3.205994 Prob(F-statistic) 0.000046 Durbin-Watson sta 3.205994 Prob(F-statistic) 0.000046 All our explanatory variables are significant. All our explanatory variables are significant. This is the best result because the probability of the F-statistic is the lowest. This is the best result because the probability of the F-statistic is the lowest.

21 Observations of Time- Series Regression Analysis After the original regression, dropping the variables with the lowest t-statistic optimized the regression results. After the original regression, dropping the variables with the lowest t-statistic optimized the regression results. Ex: Population and Income  Dropping the variable with the highest t-stat made the regression analysis less optimal Ex: Unemployment Rate

22 Results for Cross Section Analysis

23 Organization Cross Section Regression Cross Section Regression 14 Different Areas for 2 separate years: 2000 and 2005 14 Different Areas for 2 separate years: 2000 and 2005

24 Relationship between Location, Income and House Price

25 The Variables Median Price of a Home (dependent variable) Median Price of a Home (dependent variable) β 1 = Unemployment Rate β 1 = Unemployment Rate β 2 = Median Family Income β 2 = Median Family Income β 3 = Building Permits β 3 = Building Permits β 4 = Population β 4 = Population β 5 = Distance from the coast β 5 = Distance from the coast

26 2000 and 2005 COAST OR NOT COAST OR NOT DUMMY VARIABLE DUMMY VARIABLE IF COAST 1 IF COAST 1 IF NOT 0 IF NOT 0

27 Relationship between Location and House Price

28 Explanation of Relationship Two different trends explained by dummy = 1 (coastal) and dummy = 0 (not coastal) Two different trends explained by dummy = 1 (coastal) and dummy = 0 (not coastal) Those cities close to the coast experience a higher median house price Those cities close to the coast experience a higher median house price Is this relationship significant? Is this relationship significant?

29 Results for Cross Section Analysis (14 Metropolitan Statistical Areas)

30 Cross Section Analysis Correlation Matrix - 2005 HOUSE PRICE DUMMY COAST INCOMEPERMITSPOPULAT ION UNEMPLOYMENT RATE HOUSEPRICE10.8763920.5370360.1526160.240021-0.005214 DUMMYCOAST0.87639210.4261850.3425070.3823090.063996 INCOME0.5370360.42618510.0323890.058681-0.637418 PERMITS0.1526160.3425070.03238910.883983-0.034606 POPULATION0.2400210.3823090.0586810.8839831-0.001086 UNEMPLOYMENTRATE-0.005210.063996-0.63742-0.03461-0.001091

31

32 Cross-Section Regression 2005 Dependent Variable: HOUSEPRICE Dependent Variable: HOUSEPRICE Method: Least Squares Method: Least Squares Date: 12/06/06 Time: 00:11 Date: 12/06/06 Time: 00:11 Sample: 1 14 Sample: 1 14 Included observations: 14 Included observations: 14 Variable CoefficientStd. Errort-StatisticProb. Variable CoefficientStd. Errort-StatisticProb. DUMMYCOAST323679.484887.583.8130360.0051 DUMMYCOAST323679.484887.583.8130360.0051 INCOME 3.7982663.4367861.1051800.3012 INCOME 3.7982663.4367861.1051800.3012 PERMITS-2.4599583.160409-0.7783670.4588 PERMITS-2.4599583.160409-0.7783670.4588 POPULATION0.0063280.0140420.4506170.6642 POPULATION0.0063280.0140420.4506170.6642 UNEMPLOYMENTRATE1141333.2298304.0.4965980.6328 UNEMPLOYMENTRATE1141333.2298304.0.4965980.6328 C -112592.2321611.0-0.3500880.7353 C -112592.2321611.0-0.3500880.7353 R-squared0.828896 Mean dependent var339964.3 R-squared0.828896 Mean dependent var339964.3 Adjusted R-squared0.721956 S.D. dependent var214654.6 Adjusted R-squared0.721956 S.D. dependent var214654.6 S.E. of regression113187.2 Akaike info criterion26.40900 S.E. of regression113187.2 Akaike info criterion26.40900 Sum squared resid1.02E+11 Schwarz criterion26.68288 Sum squared resid1.02E+11 Schwarz criterion26.68288 Log likelihood-178.8630 F-statistic 7.751030 Log likelihood-178.8630 F-statistic 7.751030 Durbin-Watson stat2.377582 Prob(F-statistic)0.006204 Durbin-Watson stat2.377582 Prob(F-statistic)0.006204 DummyCoast only variable that is significant

33 Drop all insignificant variables (2005) Dependent Variable: HOUSEPRICE Dependent Variable: HOUSEPRICE Method: Least Squares Method: Least Squares Date: 12/06/06 Time: 00:18 Date: 12/06/06 Time: 00:18 Sample: 1 14 Sample: 1 14 Included observations: 14 Included observations: 14 VariableCoefficientStd. Errort-StatisticProb. VariableCoefficientStd. Errort-StatisticProb. DUMMYCOAST362557.157513.806.3038290.0000 DUMMYCOAST362557.157513.806.3038290.0000 C 158685.740668.403.9019420.0021 C 158685.740668.403.9019420.0021 R-squared0.768063 Mean dependent var339964.3 R-squared0.768063 Mean dependent var339964.3 Adjusted R-squared0.748735 S.D. dependent var214654.6 Adjusted R-squared0.748735 S.D. dependent var214654.6 S.E. of regression107598.5 Akaike info criterion26.14176 S.E. of regression107598.5 Akaike info criterion26.14176 Sum squared resid1.39E+11 Schwarz criterion26.23306 Sum squared resid1.39E+11 Schwarz criterion26.23306 Log likelihood-180.9923 F-statistic39.73826 Log likelihood-180.9923 F-statistic39.73826 Durbin-Watson stat1.652406 Prob(F-statistic)0.000039 Durbin-Watson stat1.652406 Prob(F-statistic)0.000039

34 Cross Section Regression 2000 Dependent Variable: HOUSEPRICE Dependent Variable: HOUSEPRICE Method: Least Squares Method: Least Squares Date: 12/06/06 Time: 00:28 Date: 12/06/06 Time: 00:28 Sample: 1 14 Sample: 1 14 Included observations: 14 Included observations: 14 Variable CoefficientStd. Errort-StatisticProb. Variable CoefficientStd. Errort-StatisticProb. INCOME 2.9938432.8886531.0364150.3271 INCOME 2.9938432.8886531.0364150.3271 DUMMYCOAST134588.047862.772.8119570.0203 DUMMYCOAST134588.047862.772.8119570.0203 POPULATION-0.0029720.005146-0.5775890.5777 POPULATION-0.0029720.005146-0.5775890.5777 UNEMPLOYMENTRATE400794.12795135.0.1433900.8891 UNEMPLOYMENTRATE400794.12795135.0.1433900.8891 C -47469.59248491.1-0.1910310.8527 C -47469.59248491.1-0.1910310.8527 R-squared0.623754 Mean dependent var195085.7 R-squared0.623754 Mean dependent var195085.7 Adjusted R-squared0.456534 S.D. dependent var108047.6 Adjusted R-squared0.456534 S.D. dependent var108047.6 S.E. of regression79652.92 Akaike info criterion25.68120 S.E. of regression79652.92 Akaike info criterion25.68120 Sum squared resid5.71E+10 Schwarz criterion25.90943 Sum squared resid5.71E+10 Schwarz criterion25.90943 Log likelihood-174.7684 F-statistic 3.730130 Log likelihood-174.7684 F-statistic 3.730130 Durbin-Watson stat1.866677 Prob(F-statistic)0.046794 Durbin-Watson stat1.866677 Prob(F-statistic)0.046794 DummyCoast variable is very significant but not as significant as in 2005

35 Drop all insignificant variables (2000) Dependent Variable: HOUSEPRICE Dependent Variable: HOUSEPRICE Method: Least Squares Method: Least Squares Date: 12/06/06 Time: 00:29 Date: 12/06/06 Time: 00:29 Sample: 1 14 Sample: 1 14 Included observations: 14 Included observations: 14 VariableCoefficientStd. Errort-StatisticProb. VariableCoefficientStd. Errort-StatisticProb. DUMMYCOAST152342.940981.013.7174010.0029 DUMMYCOAST152342.940981.013.7174010.0029 C 118914.328977.954.1036130.0015 C 118914.328977.954.1036130.0015 R-squared0.535227 Mean dependent var195085.7 R-squared0.535227 Mean dependent var195085.7 Adjusted R-squared0.496496 S.D. dependent var108047.6 Adjusted R-squared0.496496 S.D. dependent var108047.6 S.E. of regression76668.45 Akaike info criterion25.46393 S.E. of regression76668.45 Akaike info criterion25.46393 Sum squared resid7.05E+10 Schwarz criterion25.55523 Sum squared resid7.05E+10 Schwarz criterion25.55523 Log likelihood-176.2475 F-statistic13.81907 Log likelihood-176.2475 F-statistic13.81907 Durbin-Watson stat1.843468 Prob(F-statistic)0.002941 Durbin-Watson stat1.843468 Prob(F-statistic)0.002941

36 Conclusion With time series we ran into multicollinearity issues, and as a result of this we were forced to drop one explanatory variable With time series we ran into multicollinearity issues, and as a result of this we were forced to drop one explanatory variable By dropping one explanatory variable we erased the multicollinearity issue and found that all of our variables can be significant (best results by dropping median family income) By dropping one explanatory variable we erased the multicollinearity issue and found that all of our variables can be significant (best results by dropping median family income) In the cross section analysis, none of these same variables were significant In the cross section analysis, none of these same variables were significant So we introduced one more variable (DummyCoast) and found it to be very significant So we introduced one more variable (DummyCoast) and found it to be very significant Conc - Due to the variability of the housing market, it is difficult to predict housing price over a period of time (difficult to determine the most significant explanatory variable when there is multicollinearity). Conc - Due to the variability of the housing market, it is difficult to predict housing price over a period of time (difficult to determine the most significant explanatory variable when there is multicollinearity). Since that is the case with all our explanatory variables, the best is the variable that does not change with time (i.e. location) Since that is the case with all our explanatory variables, the best is the variable that does not change with time (i.e. location)

37 References US Census Bureau US Census Bureau US Department of Housing and Urban Development US Department of Housing and Urban Development Real Estate Center at Texas A&M University Real Estate Center at Texas A&M University www.mapquest.com www.mapquest.com National Association of Realtors National Association of Realtors Keller – Statistics for Management and Economics Keller – Statistics for Management and Economics US Council of Economic Advisors US Council of Economic Advisors Bureau of Labor Statistics Bureau of Labor Statistics Maryland Association of Realtors Maryland Association of Realtors


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