+ PHOE004BP1FHSA and the Effective Federal Funds Rate By: Anissa Khan.

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Presentation transcript:

+ PHOE004BP1FHSA and the Effective Federal Funds Rate By: Anissa Khan

+ What is PHOE004BP1FHSA anyway??? Title : New private housing units authorized by building permits: 1 unit structures for Phoenix-Mesa-Glendale, AZ (Metropolitan Statistical Area) Frequency : monthly, 1988 to 2016 Seasonally adjusted: Yes Stationary: No Importance: Economic well-being Population PHU= Private housing units authorized

+ What is the Effective Federal Funds Rate? Definition : the interest rate banks use to charge each other for overnight loans so that they can meet their reserve requirements. Frequency: monthly, 1988 to 2016 Seasonally Adjusted: No Stationary: No Importance : Economic well-being FFR = Federal Funds Rate

+ Dealing with Non-Stationarity: 1.Private Housing Unit Authorizations How do I know? Local Trends ACF ADF Test ADF P-values: 1 lag: lags: lags:

+ Dealing with Non-Stationarity: 1.Effective Federal Funds Rate How do I know? Local Trends ACF ADF Test ADF P-values: 1 lag: lags: lags: 0.99

+ Dealing with Non-Stationarity: How do I fix it? Difference Stationary  take the difference (Difference(log(series))*100 = Monthly growth rate

+ Summary Statistics VariableMinimum1 st QuartileMedianMean3 rd QuartileMaximum PHU %- 7.8 %-0.38 %0.06 %7.9 %45.6 % FFR %- 2.9 % 0.00 % % 2.4 %69.3 % FFR = Effective Federal Funds Monthly Growth Rate PHU = Private Housing Unit Authorizations Monthly Growth Rate On average: fairly constant Widely spread

+ Histogram of FFR Monthly Growth Rate Kurtosis: Skewness: Centered at 0

+ Scatterplot of X and Y Question: Is this relationship statistically significant?

+ Bivariate Regression Model 1: CoefficientEstimateT-valueP-value Positive relationship BUT: statistically insignificant THEREFORE: no relationship

+ Residual Plot: Average predicted PHU: Residual = y - y predicted

+ Outliers Why are they a problem? Outliers can cause regression results to be incorrect. How to identify outliers: Calculate studentized residuals Those larger than 1.96 are outliers Does this series have outliers? YES: there are 20

+ What happens when outliers are removed? Positive Relationship Statistically significant The outliers had been affecting results Model 2: Equation is the same, data is different CoefficientEstimateT-valueP-value

+ Level-Level vs. Log-Level vs. Log-Log What is the difference? The interpretation Equation : Level-Level Model: PHU=difference(PHU) FFR=difference(FFR) Log-Level Model: PHU = 100*difference(log(PHU)) FFR = difference(FFR) Log-Log Model: Same as Model 1 PHU=100*difference(log(PHU)) FFR=100*difference(log(FFR))

+ Level-Level CoefficientEstimateT-valueP-value CoefficientEstimateT-valueP-value CoefficientEstimateT-valueP-value Log-Level Log-Log Note: Outliers have been excluded Which is best?

+ Quadratic Regression CoefficientEstimateT-valueP-value e Model 3: Note: Outliers have been excluded

+

+ Groupwise Regressions CoefficientEstimateT-valueP-value CoefficientEstimateT-valueP-value Models 4 and 5: Before January 2000 After January 2000 Note: Outliers have been excluded

+ FFR Group Summary Statistics On average, the FFR growth rate is larger post 2000 FFRMinimum1 st QuartileMedianMean3 rd QuartileMaximum pre %- 1.71% % % 1.96 %11.91 % post % %0.00 % % 3.65 %35.67 %

+ Concluding Remarks Most appropriate model Linear log-log: interpretation, significance However 1. Results differ when sample differs Larger sample 2. Questionable robustness OVB? Most likely no causal relationship

+ Questions?