1. Were more regional center-cities better able to manage fiscal stress through the Great Recession? Evidence from 2007-2011. Joseph D. Manzella, II April 17, 2013

2. Outline Introduction to Regionalism Rationale Review of Literature –Regionalism –Fiscal Stress Data and Model Development Identification and testing of Hypothesis Conclusions, comments and feedback.

3. Introduction to Regionalism Metropolitan Governance –Tiebout –Ostrom Metropolitan Government –Rusk –Unigov, City-County Consolidation, flexible borders, et cetera

4. Introduction to Regionalism Interlocal agreements Revenue Sharing –In Michigan, 425 Agreements Shared Services –Police and Fire –Water and Sewer –Rec Centers Reached through agreement of equal parties

5. Introduction to Regionalism New York (1895) Jacksonville City-County (1968) Indianapolis City-County (1972) Louisville City-County (2003)

6. Rationale for Study Trending topic in local government A new talking point in the regionalism discussion

7. Review of Literature Regionalism and Cities: –Ed Glaeser –Richard Florida –David Rusk –Robert Putnam –Jane Jacobs –Elinor Ostrom

8. Review of Literature Fiscal Stress: –Kloha, Weissert and Kleine –Trussel & Patrick –CBO –ACIR

9. StudyIndicatorMeasures Comparable measures used in this study ACIR (1985)Continuous operationsRevenues – Expenditures over time Change in Revenue, 2007-2011 Change in Expenses, 2007-2011 Congressional Budget Office (1978) Continuous operationsRevenues – Expenditures over timeYearly Surplus (Deficit) Congressional Budget Office (1978) Debt burdenTotal Debt / Total revenuesNet General Bonded Debt per Capita Trussell & Patrick (2009)Use of Intergovernmental RevenueIGR as portion of total revenueOmitted. Not comparable. Trussell & Patrick (2009)Revenue GrowthCurrent Revenue – Previous RevenueChange in Revenue Trussell & Patrick (2009)Administrative Expenditures(Total – Non-Admin Expend.) / Total Employees per capita, Debt per capita, change in employees per capita Trussell & Patrick (2009)Debt LevelDebt to RevenueDebt per capita Kloha, Weissert, & Kleine (2005) Population Growth Year to year percentage change in Population Change in Population – 2007 to 2011 Kloha, Weissert, & Kleine (2005) Revenue GrowthReal Taxable Value GrowthChange in Revenue Kloha, Weissert, & Kleine (2005) Revenue Growth Large Taxable Value Decrease (over 2 years) Change in Revenue Kloha, Weissert, & Kleine (2005) Current ExpensesExpenditures / Taxable ValueYearly Surplus (Deficit) / Revenue Kloha, Weissert, & Kleine (2005) General Fund Operating Deficit(Revenue – Expenditure) / Total RevenueYearly Surplus (Deficit) / Revenue Kloha, Weissert, & Kleine (2005) General fund balance to revenuesGeneral fund balance / Total RevenueFund Balance Per Capita Kloha, Weissert, & Kleine (2005) Fund deficits in current or previous year (Revenue – Expenditure) / Total Revenue for t 0 and t -1 Captured in time series, general fund only Kloha, Weissert, & Kleine (2005) Long Term Debt to Taxable ValueLT debt / taxable valueNet General Bonded Debt per Capita

10. Notes on Data Sources Comprehensive Annual Financial Reports Census Data Interviews FOIA Requests

11. Methodology Approach 1: Determine the effect of regionalism on measures of fiscal stress –Service cuts, –Debt, and –Deficits. Approach 2: Determine the effect of regionalism on composite scores of fiscal stress.

12. Hypotheses for Approach 1 H 1 : Higher levels of regionalism positively affect employment changes. H 2 : More regional cities had smaller debt per capita H 3 : More regional cities had smaller revenue deficits.

13. Hypothesis 1 H 1 : Higher levels of regionalism positively affect employment changes. %Change_FTE i(2007-2011) =  1 +  2 City_MSA_Ratio i(2011) +  3 %Change_in_Pop i(07-11) +  4 %Change_in_Rev (07-11)I +  5 City_Unem i(2011) +  6 Region_Unem i(2011) +  i

14. Center-City Metro Area PopulationCity Pop. Total Govs in RegionGov’ts per CapitaRank City's Share of Pop. (City-MSA)Rank Akron, OH 703,200199,110380.00005403873728.31%29 Ann Arbor, MI 344,791112,852100.00002900314532.73%23 Appleton, WI 225,66672,623410.0001816844732.18%24 Bloomington, IN 192,71480,405150.00007783552641.72%12 Canton, OH 404,42273,007290.00007170733018.05%39 Cedar Rapids, IA 257,940120,758430.00016670541046.82%7 Champaign, IL 231,89181,055470.0002026814434.95%18 Chicago, IL 9,461,1052,695,5983920.00004143284328.49%28 Cincinnati, OH 2,130,151296,9432070.00009717621813.94%42 Cleveland, OH 2,077,240396,8151140.00005488053519.10%38 Columbus, OH 1,836,536787,0331050.00005717293242.85%11 Davenport, IA 379,69099,685630.00016592481126.25%30 Dayton, OH 841,502141,729650.00007724282716.84%40 Des Moines, IA 569,633203,433670.00011761961335.71%17 Detroit, MI 4,296,250713,3871270.00002956074416.60%41 Duluth, MN 279,77186,265900.0003216917230.83%26 Elkhart, IN 197,55950,949110.00005567963425.79%32 Evansville, IN 358,676117,429400.00011152131532.74%22 Flint, MI 425,790102,434190.00004462294124.06%35 Fort Wayne, IN 416,257253,691220.00005285203860.95%3 Grand Rapids, MI 744,160192,435420.00005643953325.86%31 Green Bay, WI306,241104,057650.0002122511333.98%20

15. Center-City Metro Area PopulationCity Pop. Total Govs in Region Gov’ts per CapitaRank City's Share of Pop. (City-MSA)Rank Holland, MI 263,80133,051110.00004169814212.53%43 Indianapolis, IN 1,778,568807,584840.00004722904045.41%8 Kalamazoo, MI 326,58974,262270.00008267272522.74%36 Kansas City, MO 2,035,334459,7871870.00009187681922.59%37 Lafayette, IN 201,78967,140200.00009911341733.27%21 Lansing, MI 464,036119,128350.00007542522825.67%34 Lincoln, NE 302,157254,001250.00008273842484.06%1 Madison, WI 568,593228,2001010.0001776315840.13%14 Milwaukee, WI 1,555,908594,833770.00004948883938.23%15 Minneapolis, MN 3,279,833382,5782460.00007500382911.66%44 Peoria, IL 379,186115,007640.0001687826930.33%27 Racine, WI 195,40878,860220.00011258501440.36%13 Rochester, MN 186,011106,7691030.0005537307157.40%4 Rockford, IL 349,431152,871190.00005437413643.75%10 Saginaw, MI 200,16851,508180.00008992452025.73%33 South Bend, IN 319,224101,168190.00005951933131.69%25 Springfield, IL 210,170116,250320.00015225771255.31%5 Springfield, MO 436,712157,360390.00008930372136.03%16 St. Cloud, MN 189,09365,862360.0001903825534.83%19 St. Louis, MO 2,815,000319,2943070.00010905861611.34%45 Toledo, OH 651,429287,208540.00008289472344.09%9 Topeka, KS 233,870127,473440.0001881387654.51%6 Wichita, KS625,526382,368550.00008792602261.13%2

16. Regression Results Change in Total FTEs (2007-2011) Coeff.Std. Err.P-Value City-to-MSA Ratio0.04954740.274280.858 City-to-MSA Ratio (Squared)-0.10212740.25228770.688 Change in Pop (07 to 11)0.85941430.37657510.029 Change in Rev (07 to 11)0.00954260.01417610.506 City Unemployment-0.00616540.00705360.389 MSA Unemployment0.00685830.01093460.535 constant-0.05381460.06777320.433 Observations39 Adjusted R 2 0.484 [1] [1] All reported standard errors are robust standard errors unless otherwise noted.

17. Combined Effect of Population and Regionalism Coeff.Std. Err.P-Value City-to-MSA(squared)-0.078190.1225360.528 City-to-MSA*Population Change2.115431.0309110.048 Change in Rev (07 to 11)0.0203330.0159380.211 City Unemployment-0.009160.0060230.138 MSA Unemployment0.0093460.0090430.309 constant-0.047530.0502820.351 Observations39 Adjusted R 2 0.396

18. Effect of Governments per Capita on Cuts to Service Coeff.Std. Err.P-Value %Change in Population0.85364410.31732890.011 Governments per 10k-Pop0.04585150.02205520.046 Governments per 10k-Pop Squared-0.00642860.00356650.081 %Change in Revenue (07-11)0.00559680.01273280.663 Center-City Population6.29E-094.92E-090.211 City Unemployment-0.00388520.00668370.565 MSA Unemployment0.00771980.01020830.455 constant-0.12443340.06202520.054 Observations39 R20.5334

19. Hypothesis 2 H 2 : More regional cities had smaller debt per capita –Net Bonded Debt divided by Population Estimates

20. Debt per Capita Over Time

21. YearDebt per Capita Mean 2007 $ 1,093.63 Median 2007 $ 803.87 Std Dev 2007 $ 1,189.73 Mean 2008 $ 1,142.62 Median 2008 $ 858.45 Std Dev 2008 $ 1,231.66 Mean 2009 $ 1,174.72 Median 2009 $ 891.32 Std Dev 2009 $ 1,245.07 Mean 2010 $ 1,242.29 Median 2010 $ 1,072.17 Std Dev 2010 $ 1,306.00 Mean 2011 $ 1,226.52 Median 2011 $ 1,019.38 Std Dev 2011 $ 1,328.25 Mean 2007-2011 $ 1,175.76

22. Hypothesis 2: Debt per Capita Debt grow for most cities through the crisis. Debt is not necessarily an indicator of stress, but too much debt is. Econometric model: Debt Per Capita (2007-2011) =  1 +  2(2007-2011) City-MSA +  3(2007-2011) City-MSA 2 +  4(2007-2011) City_Unem +  i +  i

23. Regression Results Effect of Population Ratio on Debt Per Capita Coeff.Std. Err.P-Value Ratio of City to MSA-7645.1093259.6540.02 Ratio of City to MSA Squared5886.1633358.9840.082 Metro Population (2010) -0.0041070.00915630.654 Yearly Revenue 0.0000003670.0000002710.177 Yearly Average Unemployment (City)15.253925.0447550.003 Constant 7173.17210048.570.476 Observations 195 Groups 39 R 2 : Within 0.1223 Between 0.1224 Overall0.1207

24. Interpretation Downward effect of regionalism is strongest when the center city has 65.94% of the region’s population. Center-CityMetro Area PopulationCity Pop. City's Share of Pop. (City-MSA)Rank Lincoln, NE302,157254,00184.06%1 Wichita, KS625,526382,36861.13%2 Fort Wayne, IN416,257253,69160.95%3 Rochester, MN186,011106,76957.40%4 Springfield, IL210,170116,25055.31%5 Topeka, KS233,870127,47354.51%6 Cedar Rapids, IA257,940120,75846.82%7 Indianapolis, IN1,778,568807,58445.41%8 Toledo, OH651,429287,20844.09%9 Rockford, IL349,431152,87143.75%10

25. Hypothesis 3 H 3 : More regional cities had smaller revenue deficits. Every city had a revenue shortfall Shortfalls are mitigated by new taxes, asset sales, service cuts and new debt.

26. Average Deficit as Percent of Revenue

27. Regression Results Time series regression accounting for fixed effects Yearly Deficits as Percent of Revenue Coeff.Std. Err.P-Value City-MSA Ratio-1.3803270.73101930.061 Metropolitan Population -2.32E-064.93E-060.639 Yearly Revenue3.17E-101.46E-100.032 City Unemployment -0.00351520.00263730.185 Constant 2.8066995.429810.606 Number of Obs 194 Number of Groups 39 R 2 Within 0.0574 R 2 Between 0 R 2 Overall0

28. Approach 2: Composite Scores Switching gears to fiscal health Measuring relative health compared to other cities in the dataset Comparing these results to regionalism measures using regression.

29. Fiscal Health Variables % Change in Employees % Change in Revenue Deficit to Revenue Ratio Fund Balance per capita Debt per Capita

30. City2008200920102011Overall ScoreRank Appleton 7.90860945.86544673.64319444.543636621.960887131 Indianapolis 4.44469326.25958313.6603054-0.146174914.218406792 Peoria 2.70362011.89708882.4537523.930591810.985052733 South Bend 2.3705925-0.29828665.7598792.06291839.8951031844 Springfield, MO 1.98563262.62509592.73851642.11929469.4685394795 Cedar Rapids 0.33403256.0560661.4387461.47414819.3029925746 Champaign 2.92065631.75288011.28923550.37205746.3348293377 Springfield, IL 2.58529321.71831821.22632360.49517856.025113428 Rockford 0.56944281.2011703-3.99135778.0181695.7974243789 Fort Wayne 4.514262-0.3102135-0.58803491.40283315.01884669610 Madison 2.31661530.53580421.2657063-0.30120653.81691921911 Kalamazoo -2.11140543.09598781.21976611.41149753.61584602412 St. Louis 0.66069051.73569250.39069680.40921763.19629740813 Grand Rapids 1.43534760.2714540.98629950.28604852.97914954114 Rochester 0.86807240.22055660.94887020.70285032.7403494815 Lincoln 0.15745581.02208161.4730453-0.14396062.50862211416 Saginaw -0.56306880.86114221.3489577-0.6378321.00919906917 Canton -0.4051581-0.15875061.25986310.19239770.88835214618 St. Cloud 0.4123255-1.3364351.11839180.66506110.85934337419 Wichita 0.00338770.2003735-0.15217370.03097740.08256486120 Lansing 0.11322860.99088690.0911794-1.2289282-0.03363319721 Green Bay -1.612930.54920210.6656654-0.0088615-0.40692390922

31. City2008200920102011Overall ScoreRank Cincinnati 0.4601762-0.2417379-0.05651-1.1288621-0.96693374323 Minneapolis -0.70626730.5691505-1.418360.5681622-0.98731454424 Dayton -1.0205293-1.0783599-1.66805152.6985549-1.06838584625 Toledo -2.9704286-0.524937-0.07246681.2793703-2.28846211626 Ann Arbor 1.41688440.3641005-2.4407551-2.4421774-3.10194768927 Duluth -1.5389397-2.87006170.5422531-0.8020958-4.66884417428 Holland -1.0043805-1.877013-1.0591484-1.1849643-5.12550618929 Davenport -1.0037397-0.1737316-2.8670617-1.44389-5.48842293930 Des Moines -1.611399-0.6649604-2.0242857-1.937282-6.23792715831 Columbus -3.3707171-3.42090220.8300537-1.3767919-7.33835751432 Milwaukee -2.8181861-1.3025006-1.4592386-1.8037971-7.38372237233 Kansas City -0.0262318-2.2867193-3.4356919-1.7852474-7.53389039834 Chicago -2.0348663-4.2287628-1.3992727-1.1454811-8.8083829335 Flint -0.8799748-4.0145231-3.1970611-2.991268-11.0828270236 Detroit -3.4106822-2.8262291-2.6404354-2.5271394-11.4044860537 Akron -3.8126071-4.5720571-0.8398441-4.085057-13.3095652738 Cleveland-7.2795069-5.6059001-5.0409512-5.5419477-23.468305939

32. Regression Results SCORE =  1 +  2 City-MSA +  3 City Unemployment +  4 MSAUnemployment +  5 Population + e i Effect of City-MSA Proportion on Fiscal Health Scores Coeff.Std. Err.P-Value City-MSA15.663296.0131430.014 City Unemployment-1.1972040.49892220.022 MSA Unemployment2.2080541.0972410.052 Population-0.00000550.000001950.008 Constant-1.00E+017.23E+000.176 Observations39 R2R2 0.2384

33. Conclusions Services Debt Deficits Overall Health

34. Possible Implications Regionalism Extraordinary measures –EMs –Municipal Bankruptcy New Remedies from old ideas

35. Opportunities for Further Research General Framework Decrease granularity by coding for services and powers Expand to all cities and towns in Metropolitan Regions

36. Discussion and Feedback