FACTORS AFFECTING HOUSING PRICES IN SYRACUSE Sample collected from Zillow in January, 2015 Urban Policy Class Exercise - Lecy.

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Presentation transcript:

FACTORS AFFECTING HOUSING PRICES IN SYRACUSE Sample collected from Zillow in January, 2015 Urban Policy Class Exercise - Lecy

Factors we included in the model: Size (sqft, lot size) Age Garage Bedrooms and bathrooms Proximity to parks Proximity to restaurants / coffee shops Proximity to highways Quality of the school district Crime in the neighborhood

Houses from the Sample

Syracuse Min. $12,000 1st Qu. $56,000 Median $72,250 Mean $90,430 3rd Qu. $105,600 Max. $368,000

$29k difference

$31k difference

Crime

Data Sources:

Interpretation is important and the direction of causality is key. Black individuals have historically been forced into poor neighborhoods through policies related to financing.

Call: lm(formula = price ~ sqft + lot.size + bath + as.factor(garage) + year + school + as.factor(highway)) Residuals: Min 1Q Median 3Q Max Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) *** sqft ** lot.size * bath as.factor(garage)Yes year *** school * as.factor(highway)Yes Signif. codes: 0 ‘***’ ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: on 138 degrees of freedom (2 observations deleted due to missingness) Multiple R-squared: , Adjusted R-squared: F-statistic: on 7 and 138 DF, p-value: 2.794e-12

Call: lm(formula = price ~ sqft + lot.size + bath + as.factor(garage) + year + school + as.factor(highway) + crime.count + prop.black) Residuals: Min 1Q Median 3Q Max Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) *** sqft ** lot.size * bath as.factor(garage)Yes year *** school as.factor(highway)Yes crime.count prop.black * --- Signif. codes: 0 ‘***’ ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: on 136 degrees of freedom (2 observations deleted due to missingness) Multiple R-squared: , Adjusted R-squared: F-statistic: on 9 and 136 DF, p-value: 8.631e-11