group 3 members:dan sun hongliang wu hui lai hui wang ling-ching hsu seok-rahn lee
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Analysis of House Price in California. Group 3 Members:Dan Sun Hongliang Wu Hui Lai Hui Wang Ling-Ching Hsu Seok-Rahn Lee Shin-Hao Lee Yuanbo Mao. Econ 240 A. Agenda Historical House Prices in California The Purpose of Our Project Statistical Analysis Conclusion. - PowerPoint PPT PresentationTRANSCRIPT
Group 3Members: Dan Sun
Hongliang WuHui LaiHui WangLing-Ching HsuSeok-Rahn LeeShin-Hao LeeYuanbo Mao
Analysis ofHouse Price in
California
Econ 240 A
Agenda
Historical House Prices in California
The Purpose of Our Project
Statistical Analysis
Conclusion
Historical House Prices in California 1976 - 2008
0
100000
200000
300000
400000
500000
600000
1980 1985 1990 1995 2000 2005
MEDIANHOMEPRICE
The Purpose of This Project
To Test the Possible Factors that May Influence the House Prices
• Personal Income per Capita• Mortgage Rate• Unemployment Rate• Population Growth
To Investigate How Each of These Factors Affects the House Prices
To Build Models to Forecast Future House Prices in California
House Price vs. Income per Capita
Statistical Analysis
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15000 20000 25000 30000 35000 40000
INCOMEPERCAPITA
ME
DIA
NH
OM
EP
RIC
E
House Price vs. Unemployment Rate
Statistical Analysis
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4 5 6 7 8 9 10 11
UNEMPLOYMENT
ME
DIA
NH
OM
EP
RIC
E
Statistical AnalysisHouse Price vs. Mortgage Rate
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200000
300000
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600000
4 6 8 10 12 14 16 18
MORTGAGE
ME
DIA
NH
OM
EP
RIC
E
Statistical AnalysisHouse Price vs. Population Growth
Rate
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600000
0 1 2 3 4 5 6 7
CHANGEOFPOPULATION
ME
DIA
NH
OM
EP
RIC
E
Statistical AnalysisHouse Price vs. Income per Capita,
Unemployment Rate and Mortgage Rate
Statistical AnalysisRegression Diagnostics - Normality
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2
4
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12
-100000 -50000 0 50000 100000
Series: ResidualsSample 1976 2008Observations 33
Mean 6.17e-12Median 8791.570Maximum 96547.63Minimum -84804.66Std. Dev. 45012.33Skewness 0.023099Kurtosis 2.605266
Jarque-Bera 0.217180Probability 0.897098
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-50000
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0 100000 300000 500000
PREDICTED
RESID
Statistical AnalysisRegression Diagnostics –
Homoscedasticity
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-50000
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100000
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600000
1980 1985 1990 1995 2000 2005
Residual Actual Fitted
Statistical AnalysisRegression Diagnostics -
Independence
Statistical Analysis
4
5
6
7
8
9
10
11
UNEMPLOYMENT
16000
20000
24000
28000
32000
36000
40000
INCOMEPERCAPITA
Regression Diagnostics - Outliers
Statistical AnalysisHouse Price vs. Income per Capita,
Unemployment Rate and Mortgage Rate w/ Dummy Variables
Statistical AnalysisRegression Diagnostics - Normality
0
2
4
6
8
10
12
-100000 -50000 0 50000 100000
Series: ResidualsSample 1976 2008Observations 33
Mean -5.12e-11Median 6280.711Maximum 93582.02Minimum -80773.18Std. Dev. 42062.68Skewness -0.024300Kurtosis 2.596128
Jarque-Bera 0.227528Probability 0.892469
Statistical AnalysisRegression Diagnostics -
Homoscedasticity
-100000
-50000
0
50000
100000
0 100000 300000 500000
PREDICTED
RESID
Statistical AnalysisRegression Diagnostics -
Independence
-100000
-50000
0
50000
100000
1980 1985 1990 1995 2000 2005
MEDIANHOMEPRICE Residuals
Conclusion Income per Capita, Unemployment Rate and Mortgage
Rate Are Significant, whereas Population Grow Rate is not
T here Is a Linear Correlated Relationship between House Price and Income per Capita, Unemployment rate and Mortgage Rate
Build Model to Forecast Future House Prices in California
Questions?