Brain Drain, Brain Gain or Somewhere in the Middle? “Rethinking” Talent Attraction and Retention from a Sticky State Perspective 2017 CDS/NACDEP Conference June 14, 2017 Matt Kures Community Development Specialist Center for Community and Economic Development University of Wisconsin-Extension A U.S. Department of Commerce Economic Development Administration University Center Some Observations on Data Driven Educational Programs for Policy Makers, Economic Developers and other Stakeholders • Many issues in our communities are driven by emotion rather than a rational understanding of conditions. Do not use data as a means of dismissing these emotions. • Data is useful in stimulating discussion, challenging perceptions and identifying strengths and weaknesses. Nonetheless, do not expect one data point or a single presentation to immediately change mindsets, create consensus or find an answer. • Be forthcoming with the strengths and weaknesses of data sets. • Speak their language – Relying on regression results, spatial statistics, academic jargon, etc. is a fast-track to losing the attention of your audience. However, this does not mean that your programming should ignore these types of tools or should not be rooted in peer-reviewed research. • Have a framework for telling a story with the data (i.e. a storyboard). 100,000 Projected Convergence of the Population Age 18 and Age 65 in the State of Wisconsin – 2010 to 2040 Age 18 90,000 Age 65 80,000 Number of Residents 70,000 60,000 50,000 40,000 30,000 20,000 10,000 2010 2015 2020 Data Source: Wisconsin Department of Administration and Author’s Calculations 2025 2030 2035 2040 Some Suggested Responses from Various Stakeholder Groups in Wisconsin • Emphasis on retention – We need to do a better job of keeping people in the state. • Financial incentives – Scholarships with post-graduation residency requirements; tax breaks or student loan repayment for college graduates who live in the state for a pre-determined amount of time; • Social capital development strategies – Internships, young professionals organizations; YP week, etc. • Broad calls for developing “high paying” jobs for college graduates; • Responses are largely in line with those summarized by Groen (2011) How Can we Better Understand College Graduate Migration and Develop Appropriate Policies? A Data-Driven Framework • Migration Dynamics - Often, there is a sole focus on net migration. Netmigration, out-migration, in-migration and gross migration rates need to be considered. • Timeframe – Migration patterns should consider historical perspectives in addition to a single period in time. • Structural Conditions – Industry composition, labor market thickness, natural amenities, etc. • Social and Cultural Factors – Diversity and personal/household characteristics of in-migrants, out-migrants and non-migrants. • Based on Masey (1990); Voss, Hammer & Meier (2001); Florida (2002); Deitz (2007); Verdugo and Young (2007); Gottlieb (2011); Fiore et al (2015), among others. WI Domestic Net Migration of College Graduates by Age (2011-2015) In-Migration to Wisconsin Out-Migration from Wisconsin Net Migration 18 to 24 6,756 8,221 -1,465 25 to 29 6,757 10,258 -3,501 30 to 34 4,655 5,345 -690 35 to 39 3,202 2,610 592 40 to 44 1,958 1,747 211 45 to 49 1,571 1,468 103 50 to 54 1,390 1,492 -102 55 to 59 1,172 1,373 -201 60 to 64 1,391 1,492 -101 65 to 69 674 1,213 -539 70 to 74 345 608 -263 75 and Over 693 792 -99 30,564 36,619 -6,055 Age Group Total Source: U.S. Census Bureau 2011-2015 American Community Survey PUMS and Author’s Calculations – Extracted from IPUMS Values are subject to margins of error. Domestic Net Migration Rate (2011-2015 5-Year Estimates) Per 1,000 Population Age 18 to 64 with a Bachelor's Degree or Higher Rhode Island, -19.3 -30 -20 Colorado, 15.7 Washington, 13.4 Nevada, 13.2 Oregon, 11.2 Texas, 10.3 Maine, 9.8 Arizona, 8.6 Florida, 7.8 North Carolina, 7.5 South Carolina, 6.4 Tennessee, 4.7 Montana, 4.5 Louisiana, 3.6 California, 3.2 Idaho, 3.1 Virginia, 2.9 New Hampshire, 2.8 Arkansas, 2.8 Delaware, 2.1 Maryland, 2.0 Minnesota, 2.0 Hawaii, 0.2 Kentucky, -1.5 Georgia, -1.8 Massachusetts, -2.2 North Dakota, -2.3 Kansas, -2.5 Wyoming, -2.6 Connecticut, -2.7 New Mexico, -3.6 Missouri, -3.9 Illinois, -4.6 Alabama, -4.7 District of Columbia, -5.1 Wisconsin, -5.4 Oklahoma, -5.5 Utah, -5.8 Pennsylvania, -6.4 New York, -6.8 Nebraska, -7.1 Vermont, -7.7 Ohio, -7.9 New Jersey, -9.0 Michigan, -9.5 South Dakota, -9.7 Indiana, -10.3 Mississippi, -10.3 West Virginia, -11.3 Iowa, -12.7 -10 0 Source: U.S. Census Bureau 2011-2015 American Community Survey PUMS and Author’s Calculations – Extracted from IPUMS 10 20 Values are subject to margins of error. 30 Domestic Out-Migration Rate (2011-2015 5-Year Estimates) Per 1,000 Population Age 18 to 64 with a Bachelor's Degree or Higher Alaska, 125.4 D.C. 122.2 Wyoming, 68.9 Rhode Island, 66.6 North Dakota, 58.3 Hawaii, 57.9 New Mexico, 56.9 Idaho, 54.2 Vermont, 53.6 South Dakota, 51.2 Nevada, 50.9 Delaware, 50.2 Virginia, 47.6 New Hampshire, 47.3 Utah, 47.3 Kansas, 47.1 Iowa, 46.4 Montana, 45.2 Arizona, 45.1 West Virginia, 44.5 South Carolina, 44.1 Mississippi, 43.2 Nebraska, 42.5 Maryland, 42.3 Colorado, 41.9 Oklahoma, 41.7 Missouri, 41.5 Indiana, 41.3 Oregon, 40.9 Connecticut, 39.7 North Carolina, 39.4 Alabama, 39.2 Georgia, 39.0 Tennessee, 38.8 Kentucky, 37.4 Massachusetts, 37.3 Pennsylvania, 36.1 New Jersey, 35.8 Wisconsin, 35.6 Maine, 35.2 Illinois, 35.0 Washington, 34.7 Ohio, 34.4 Arkansas, 33.8 Michigan, 33.7 New York, 33.5 Louisiana, 33.5 Florida, 32.6 Minnesota, 30.7 Texas, 24.8 California, 22.1 0 20 40 60 80 Source: U.S. Census Bureau 2011-2015 American Community Survey PUMS and Author’s Calculations – Extracted from IPUMS 100 120 Values are subject to margins of error. 140 Domestic In-Migration Rate (2011-2015 5-Year Estimates) Per 1,000 Population Age 18 to 64 with a Bachelor's Degree or Higher D.C., 117.1 Wyoming, 66.3 Alaska, 65.6 Nevada, 64.1 Hawaii, 58.0 Colorado, 57.6 Idaho, 57.3 North Dakota, 56.0 Arizona, 53.7 New Mexico, 53.4 Delaware, 52.3 Oregon, 52.1 Virginia, 50.5 South Carolina, 50.5 New Hampshire, 50.1 Montana, 49.7 Washington, 48.1 Rhode Island, 47.3 North Carolina, 46.9 Vermont, 45.9 Maine, 45.1 Kansas, 44.6 Maryland, 44.3 Tennessee, 43.5 South Dakota, 41.5 Utah, 41.5 Florida, 40.3 Missouri, 37.5 Georgia, 37.2 Louisiana, 37.1 Connecticut, 37.0 Arkansas, 36.6 Oklahoma, 36.2 Kentucky, 35.9 Nebraska, 35.4 Massachusetts, 35.2 Texas, 35.1 Alabama, 34.5 Iowa, 33.7 West Virginia, 33.1 Mississippi, 32.9 Minnesota, 32.6 Indiana, 31.0 Illinois, 30.5 Wisconsin, 30.2 Pennsylvania, 29.7 New Jersey, 26.8 New York, 26.7 Ohio, 26.6 California, 25.4 Michigan, 24.2 0 20 40 60 80 Source: U.S. Census Bureau 2011-2015 American Community Survey PUMS and Author’s Calculations – Extracted from IPUMS 100 120 Values are subject to margins of error. 140 Migration Dynamism – Correlation between In-Migration Rates and OutMigration Rates for the Population Age 18 to 64 with a Bachelor's Degree or Higher (2011-2015 5 Year Estimates) 80.0 Out-Migration Rate (Rate per 1,000) 70.0 60.0 50.0 40.0 30.0 20.0 10.0 0.0 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 In-Migration Rate (Rate per 1,000) Source: U.S. Census Bureau 2011-2015 American Community Survey PUMS and Author’s Calculations – Extracted from IPUMS Values are subject to margins of error. 80.0 Domestic Out-Migration Rate (2005-2009 5-Year Estimates) Per 1,000 Population Age 18 to 64 with a Bachelor's Degree or Higher Wyoming, 63.95 North Dakota, 57.22 Vermont, 54.72 Hawaii, 52.72 Rhode Island, 50.65 Idaho, 48.72 South Dakota, 48.13 Delaware, 47.32 Louisiana, 46.06 New Hampshire, 44.19 Nevada, 43.69 Kansas, 42.57 New Mexico, 42.55 Utah, 42.45 Mississippi, 42.12 West Virginia, 41.42 Virginia, 40.02 Maryland, 39.92 Maine, 39.74 Indiana, 39.25 Montana, 38.53 Arizona, 37.24 Colorado, 36.63 Nebraska, 35.89 Tennessee, 35.62 Massachusetts, 35.52 Missouri, 34.93 Oklahoma, 34.87 Iowa, 34.59 Kentucky, 34.45 Connecticut, 34.21 South Carolina, 34.08 North Carolina, 33.92 Alabama, 33.62 Georgia, 33.39 Michigan, 33.08 Arkansas, 32.69 Ohio, 32.28 Pennsylvania, 31.14 Oregon, 31.12 Florida, 31.12 Wisconsin, 30.98 New York, 29.72 Illinois, 29.64 Washington, 29.07 Minnesota, 28.24 New Jersey, 27.18 Texas, 21.84 California, 20.87 0 20 40 60 District of Columbia, 109.78 Alaska, 78.65 80 Source: U.S. Census Bureau 2005-2009 American Community Survey PUMS and Author’s Calculations – Extracted from IPUMS 100 Values are subject to margins of error. 120 Domestic In-Migration Rate (2005-2009 5-Year Estimates) Per 1,000 Population Age 18 to 64 with a Bachelor's Degree or Higher District of Columbia, 102.76 Nevada, 60.19 Wyoming, 58.20 Alaska, 57.96 Delaware, 53.16 Hawaii, 52.28 Arizona, 50.14 Idaho, 47.86 Virginia, 47.00 New Mexico, 46.71 South Carolina, 45.83 South Dakota, 44.86 Vermont, 44.73 Oregon, 43.79 North Carolina, 43.57 Maryland, 42.54 Colorado, 42.33 Montana, 41.53 Washington, 40.25 New Hampshire, 39.89 Tennessee, 39.02 Georgia, 38.60 Rhode Island, 38.46 Utah, 37.26 Florida, 36.61 Arkansas, 36.59 Kansas, 36.16 Maine, 36.15 Kentucky, 35.58 North Dakota, 34.38 Connecticut, 34.37 Alabama, 34.09 Iowa, 33.64 West Virginia, 32.73 Mississippi, 32.57 Missouri, 32.56 Oklahoma, 32.03 Massachusetts, 30.81 Indiana, 30.09 Texas, 29.61 Nebraska, 29.21 Louisiana, 28.62 Illinois, 27.53 Pennsylvania, 27.51 Wisconsin, 27.43 New Jersey, 27.25 Minnesota, 27.01 New York, 22.68 Ohio, 22.58 California, 21.06 Michigan, 19.46 0 20 40 60 Source: U.S. Census Bureau 2005-2009 American Community Survey PUMS and Author’s Calculations – Extracted from IPUMS 80 100 Values are subject to margins of error. 120 State Domestic Out-Migration Rates - 1990 to 2011 Number of Domestic Out-Migrants per 1,000 “Residents” 80.0 70.0 60.0 50.0 CO CO CO CO 40.0 CO CO CO CO CO 30.0 WA WA WA 20.0 MN WA IL MN WI MN WI MN WI WI IL IL IL IL WA WA WA IL MN WI WA MN WI IL MN WI MN WI WI CO WA WA IL MN WI IL MN WI WA IL IL MN CO Source: Internal Revenue Service Migration Data and Author’s Calculations 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 10.0 Domestic State In-Migration Rates - 1990 to 2011 80.0 Number of Domestic In-Migrants per 1,000 “Residents” 70.0 60.0 CO CO CO CO 50.0 CO CO WA CO WA 40.0 WA CO CO WA WA WA CO WA WA CO WA WA WA 30.0 MN WI IL 20.0 MN MN WI WI IL IL MN MN WI IL WI MN WI IL IL MN WI MN WI IL IL MN IL WI MN WI IL MN IL WI Source: Internal Revenue Service Migration Data and Author’s Calculations 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 10.0 State Domestic Gross Migration Rates (Churn) – 1990 to 2011 130.0 110.0 100.0 CO CO CO CO CO 90.0 CO 80.0 CO CO CO WA WA 70.0 WA WA WA CO CO WA WA IL MN WI IL MN WI WA 60.0 WA WA WA 50.0 40.0 IL MN IL MN WI WI IL MN WI IL MN IL MN WI WI IL MN IL MN WI IL MN WI WI IL MN WI Source: Internal Revenue Service Migration Data and Author’s Calculations 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 30.0 2012 Number of In and Out Migrants per 1,000 “Residents” 120.0 Negative Net Migration of College Graduates from Wisconsin is not a new Phenomenon (and Largely not Driven by Out-Migration). “ Several of the state’s citizens have pointed to these numbers or similar data as a sign that Wisconsin is experience a ‘brain drain’ – an alarming net loss of its educational capital (Drilias 1985). However, while the data clearly do signal a net loss of more highly educated persons, the use of emotive expressions such as ‘brain drain’ very likely is exaggerating the importance of what may also be viewed as a relatively small net migration difference.” “Furthermore… there is evidence in detailed migration rates that Wisconsin is among the top third of states in the ability to retain college graduates. The net loss results largely from Wisconsin’s inability to attract more college educated in-migrants to the state during the 1975-80 period .” Voss, P.R. (1988) State Policy Choices: The Wisconsin Experience. Sheldon H. Danziger and John F. Witte eds. University of Wisconsin Press, Madison, WI. Understanding Structural Conditions - National Share of Industry Sector Employees with a Bachelor’s Degree or Higher NAICS 54 Professional and technical services NAICS 61 Educational services NAICS 55 Management of companies & enterprises NAICS 52 Finance and insurance NAICS 51 Information NAICS 92 Public administration NAICS 62 Health care and social assistance NAICS 53 Real estate and rental and leasing NAICS 22 Utilities NAICS 71 Arts, entertainment, and recreation NAICS 42 Wholesale trade NAICS 31-33 Manufacturing NAICS 21 Mining, quarrying, and oil and gas extraction NAICS 81 Other services NAICS 44-45 Retail trade NAICS 56 Administrative and waste services NAICS 48-49 Transportation and Warehousing NAICS 11 Agriculture, forestry, fishing and hunting NAICS 23 Construction NAICS 72 Accommodation and food services 0.0% 63.2% 63.1% 55.6% 48.1% 45.0% 38.4% 35.5% 33.3% 28.3% 27.6% 27.5% 23.8% 21.1% 21.1% 17.2% 16.2% 15.4% 12.5% 10.9% 10.2% 20.0% 40.0% 60.0% Source: U.S. Census Bureau 2011-2015 American Community Survey PUMS and Author’s Calculations – Extracted from IPUMS Values are subject to margins of error. Understanding Structural Conditions - Wisconsin Employment and Average Wage Location Quotients by Industry Sectors with the Greatest Share of Employees with a College Degree NAICS and Industry Description 54 Professional and technical services 61 Educational services 55 Management of companies and enterprises 52 Finance and insurance 51 Information 92 Public administration 62 Health care and social assistance 53 Real estate and rental and leasing 22 Utilities 71 Arts, entertainment, and recreation 42 Wholesale trade 31-33 Manufacturing 21 Mining, quarrying, and oil and gas extraction 81 Other services, except public administration Source: U.S. Census Bureau 2011-2015 American Community Survey PUMS and Author’s Calculations – Extracted from IPUMS Values are subject to margins of error. % Bachelors or Employment Higher LQ 63.2% 63.1% 55.6% 48.1% 45.0% 38.4% 35.5% 33.3% 28.3% 27.6% 27.5% 23.8% 21.1% 21.1% 0.60 0.86 1.54 1.05 0.87 0.97 1.00 0.60 0.74 0.93 1.06 1.88 0.25 0.95 Average Wage LQ 0.90 1.13 0.97 0.84 0.83 0.87 1.11 0.85 1.12 0.89 1.00 0.99 0.70 0.91 Understanding Structural Conditions - Wisconsin Employment and Average Wage Location Quotients by Manufacturing Sub Sectors with the Greatest Share of Employees with a Bachelor’s Degree or Higher % Bachelors or Higher Employment LQ Average Wage LQ 334 Computer and electronic product manufacturing 48.3% 0.89 0.67 325 Chemical manufacturing 40.8% 1.07 1.02 324 Petroleum and coal products manufacturing 32.1% 0.20 0.16 339 Miscellaneous manufacturing 30.0% 1.17 1.09 312 Beverage and tobacco product manufacturing 28.7% 0.85 0.79 336 Transportation equipment manufacturing 27.4% 0.82 0.8 335 Electrical equipment and appliance mfg. 26.6% 3.12 3.74 333 Machinery manufacturing 23.4% 3.07 3.29 316 Leather and allied product manufacturing 20.2% 2.24 2.43 323 Printing and related support activities 19.2% 3.33 3.91 322 Paper manufacturing 17.5% 4.12 4.75 315 Apparel manufacturing 16.4% 0.34 0.3 327 Nonmetallic mineral product manufacturing 15.4% 1.18 1.27 331 Primary metal manufacturing 15.0% 2.15 2.16 NAICS and Industry Description Source: U.S. Census Bureau 2011-2015 American Community Survey PUMS and Author’s Calculations – Extracted from IPUMS Values are subject to margins of error. 836,000 College Grads (1.5% of U.S. Total) 1,004,000 College Grads (1.8% of U.S. Total) 1,974,000 College Grads (3.5% of U.S. Total) 2,117,000 College Grads (3.7% of U.S. Total) 783,000 College Grads (1.4% of U.S. Total) 1,479,000 College Grads (2.6% of U.S. Total) 3,112,000 College Grads (5.5% of U.S. Total) Understanding Structural Conditions – Distribution of College Graduates Age 18 to 64 by Rural-Urban Continuum Code (2011-2015 5-Year Average) 70.0% 65.1% United States Share of College Graduates 18 to 64 60.0% Wisconsin 50.0% 40.0% 37.8% 30.0% 23.2% 19.2% 20.0% 10.0% 21.5% 7.7% 7.2% 2.8% 0.0% RUCC 1 RUCC 2 RUCC 3 RUCC 4 6.6% 1.1% 2.3% 0.0% RUCC 5 RUCC 6 Source: U.S. Census Bureau 2011-2015 American Community Survey and Author’s Calculations. Values are subject to margins of error. 1.5% 1.5% RUCC 7 0.3% 1.1% 0.4% 0.6% RUCC 8 RUCC 9 Understanding Structural Conditions – Wisconsin Net Change in College Graduates Age 18 to 64 (2000 and 2011-2015 5-Year Estimates) 160,000 Net Change in College Graduates 140,000 Wisconsin's Four most Populous Counties 120,000 100,000 80,000 60,000 40,000 20,000 0 Source: U.S. Census Bureau 2011-2015 American Community Survey and Author’s Calculations. Values are subject to margins of error. Wisconsin's Other 68 Counties Combined USDA Natural Amenities Scale by County Natural Amenities Scale 1 (Lowest) of a county area that enhance the location as a place to live. The scale is constructed by combining six measures of climate, topography, and water area that re?ect environmental qualities most people prefer. These NW - 2016 University of Wisconsin-Extension measures are warm winter, winter sun, temperate summer, low summer 6 2 3 4 5 The natural amenities scale is a measure ofthe physical characteristics 6 7 (HigheSt) Center for Community and Economic Development humidity, topographic variation, and water area (Source USDA) IIH HUI Housing Units for Seasonal, Recreational or Occasional Use by County Percent of All Housing Units (2010 to 2014 Five-Year Estimates) Miles 0 200 400 . Seasonal or Recreational Housing Units: Miles Percent of all Housing Units (2010-2014) - 100 200 0 Data Source: US. Census Bureau 2010-2014 American Community Survey. Numbers are subject to a Less than 5'0 A) - 20'0 to 39'9 margin of error. Housing units for seasonal. recreational, or occasional use are vacant units used or intended for use only in certain seasons or for weekends or other occasional use throughout the year. 5.0% to 9.9% - 40.0% to 78.1% Seasonal units include those used for summer or winter sports or recreation, such as beach cottages and muf?ension hunting cabins. Seasonal units also may include quarters for such workers as herders and :ownership units, sometimes called shared-ownership or time-sharing condominiums. are included here. University of Wisconsin-Extension Do They Return? Domestic In-Migration by State 2010-2014 Share of In-Migrants who were also Born in the State Nevada 0.0% 5.0% 10.0% Michigan Ohio Illinois Louisiana New York Minnesota Utah California Iowa South Dakota West Virginia Pennsylvania Mississippi Wisconsin Maine Indiana New Jersey Nebraska Kentucky Massachusetts Missouri North Dakota Alabama Arkansas Texas Kansas Oklahoma Connecticut Tennessee Oregon Idaho Vermont Georgia Maryland Washington Montana New Mexico Delaware Rhode Island Virginia New Hampshire Colorado Wyoming North Carolina South Carolina Florida DC Arizona Hawaii Alaska 15.0% 20.0% 25.0% 30.0% Source: U.S. Census Bureau 2010-2014 American Community Survey PUMS and Author’s Calculations – Extracted from IPUMS 35.0% 40.0% 45.0% Share of College Graduates Born in Their Current State of Residence 2011 2015 Washington 37) New Hampshire Montana . 45) 28) North Dakota . Vermont ~52 41) (59.;r .10. 8) Minnesota . 39) 14) Idaho 36) Oregon - Massachusetts South Dakota . (48Neonork wyoming 1) Michigan (53.42.17) 40) . Rhode Island 2) (45. 24) Iowa Pe - Nebraska (61? 8?46 5) (61-5010, 6) - 0: evada . . 51) (56 2. 4'3. 1?0) Utah - New Jersey 62321? 3) 32) Illinois '"diana . Delaware California (45-79512Dora 0 (36-8/6, 33) 46) 9) Virginia Maryland Kansas Missouri 23) Kentucky (250%, 44) . . . 524District of Columbia i, 50) Arizona North Carolina 49) 34) Tennessee Oklahoma 27) 19) New Mexico Arkansas South Carolina 38) 20) 38.4%, 31) Mississippi Alabama Gaorgia 4) (54.7%.13) 35) Texas (435%. 25) LouiSlana {65. 5" x6. 1) Alaska 48) a0 Q: ??33 Hawaii . 29) - Share of College Graduates Born In their Current State of Residence (2011-2015) Miles _:lMi es 1st Quantile to 26.1%) - 4th Quantile (48.1% to 55.32nd Quantile (26.2% to 38.4%) - 5th Quantile (55.4% to 65.5%) Sources U.S. Census Bureau 2011-2015 American Community Survey 5-Year Estimates . NW Note: Some differences among states may not be statistically signi?cant 3rd (38.5% t0 48.0%) 7) Share, Rarik ExtenSIon 2017 UW-Extension Center for Community and Economic Development Sometimes we do not Reach a Definitive Conclusion, but Instead Provoke New Questions • Given historical migration patterns, what is Wisconsin’s true ability to increase inmigration rates? • Given Wisconsin’s out-migration rates, how much room is there to improve retention? • Given Wisconsin’s churn rates, do we need to emphasize other strategies that reduce dependence on labor availability? • Is the state the appropriate geographic level for policy development and implementation? • Does ethnocentrism or a potential preference for “in-group” members influence failed migrations to Wisconsin? • An altered narrative about amenities and quality of life? • Does migration churn influence our entrepreneurial propensity? Methods for Disseminating Information By the Numbers Presentations – Approximately 60 minute discussions prompted by a series of charts, tables and maps to help stakeholders on a topic of interest. Over 50 presentations have been given to state agencies, non-profit organizations, economic development entities, etc. Wisconsin Economy Series – Developed in partnership with UW-Madison’s Department of Agricultural and Applied Economics, and furthered by our EDA University Center designation, the series includes an in-depth analysis of a topic, followed by a policy brief and a series of factsheets. Committee Connect Partnership - Committee Connect is a program of UWMadison’s La Follette School of Public Affairs. It provides state legislators with a single point of access to UW–Madison researchers early in the policymaking process. Contact Information Matt Kures University of Wisconsin-Extension Center for Community & Economic Development www.uwex.edu/ces/cced @uwexcced 610 Langdon Street, Room 328, Madison, WI 53703 Phone 608-265-8258 matthew.kures@uwex.edu A U.S. Department of Commerce Economic Development Administration University Center