1. Understanding Growth in Phoenix Can the FFR Help Explain Economic Activity in the MSA? Charlotte D. Smith MIAMI UNIVERSITY

2. Variable of Interest: Economic Growth Index of Phoenix, AZ PHXAGRIDX : Economic Conditions Index for Phoenix-Mesa-Scottsdale, AZ (MSA) Source: Federal Reserve Bank of St. Louis Note: first-differenced series for stationarity

3. QUESTION: Is the FFR a stationary series? Source: FRED

4. Stationarity of the FFR Dickey-fuller unit root tests imply non-stationarity Null Hypothesis: series follows a Random Walk P-value greater 0.05 for 1, 2, and 4 lags p-value > 0.05

5. Stationarity of the FFR: Debate in the literature Bec and Bassil (2009) Stationary with 2 breaks Figueiredo and Shikida (2010) Linear models inappropriate Heavy tails Existence of outliers

6. Stationarity of the FFR: First-difference to stationarize Notable improvement in ACF

7. Descriptive Statistics Source: FRED Fat tails in FFR distribution

8. Source: FRED Fat tail Left-hand side Negatively skewed Distribution of FFR

9. Source: FRED Positively correlated Significant? “Eyeball” outliers Relationship between FFR and Phoenix Growth Rate

10. Regression Results FFR positively, significantly correlated with Phoenix growth rate Adjusted R-squared quite low (0.05) Simple Regression Analysis

11. Source: FRED Concerns: 1) Nonlinearity 2) Heteroskedasticity Concentration at (0,0) Recall mean and median values of FFR ~0.0 Patterns?

12. Identifying Outliers 19 outliers Studentized residuals that are > 1.96 Source: FRED

13. Influence of the Outliers Explanatory power increases Regression Results: Full Sample Regression Results: Excluding Outliers

14. Considering Functional Forms: Log-level and Log-log Explanatory power null Regression Results: Log-level Regression Results: Log-log

15. Considering Nonlinearity: Including Quadratic Term Regression Results: PHX Growth = FFR + FFR 2

16. Using ANOVA to Determine Better Model Null Hypothesis FFR has a constant marginal effect on Phoenix growth rate Include FFR 2 Reject H 0

17. Revisiting Residual Plot: Evidence of Nonlinearity? Source: FRED

18. Before January 2000 120 observations After January 2000 188 observations

19. Groupwise Regressions Explanatory power greater for later observations Regression Results: Before January 2000 Regression Results: After January 2000

20. Conclusion of Findings Both series appear to follow Random Walk processes First-difference to stationarize Positive relationship between growth and FFR Relationship strengthens using more recent data (2000-2015) Better to use nonlinear model (quadratic)

21. References Claudio D Shikida and Erik A Figueiredo, (2010). "Is the Federal Funds rate stationary? New evidence from P-ADF" Revista de Economia e Administração Vol. 9 Iss. 1 Frédérique Bec andCharbel Bassil, (2009). “Federal Funds Rate Stationarity: New Evidence'', Economics Bulletin, Vol. 29 no.2 pp. 867-872 Board of Governors of the Federal Reserve System (US), Effective Federal Funds Rate [FEDFUNDS], retrieved from FRED, Federal Reserve Bank of St. Louis https://research.stlouisfed.org/fred2/seri es/FEDFUNDS, May 24, 2016. Charlotte D. Smith ECO 690 May 24, 2016