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Rural Teacher Labor Markets in Wisconsin Ellie Bruecker Yue Yu Peter Goff 11/7/2018 UNIVERSITY OF WISCONSIN

Why examine rural teacher labor markets? 59.4% of WI districts classified as ‘Rural’ Most research on teacher labor markets has focused on urban districts Proposal to change teacher certification requirements in last state budget justified due to benefit for rural school districts Proposal scaled back to allow for licensure of technical education teachers and teachers licensed in other states 11/7/2018 UNIVERSITY OF WISCONSIN

UNIVERSITY OF WISCONSIN Research Questions How does the teacher labor supply vary across geographic contexts? What are the characteristics of individuals who are active in the rural teacher labor market? Moved this up the audience will know ASAP what we’re doing. You usually want to hit your RQ within the first few slides. Mention that the first question is focused on the vacancy as the unit of analysis and the second question is focused on the individuals as the unit of analysis. 11/7/2018 UNIVERSITY OF WISCONSIN

Recruiting, Hiring, and Retaining Teachers in Rural School Districts Teacher labor markets tend to be geographically small (Boyd et al., 2005) Does this have a negative impact on certain types of districts? Rural districts employ higher proportions of first-year teachers than non-rural districts (Miller, 2012) Teachers in rural districts are more likely to transfer to non-rural schools than teachers working in other geographic categories (Cowen et al. 2012) We may want to mention (slide 5) that we don’t actually know the implications of reducing certification requirements. It’s kind of bizarre, but we really don’t know if this will attract more viable candidates (viable being the key word here - who cares if we triple the applicant pool, but all those new folks couldn’t possibly be hired).  11/7/2018 UNIVERSITY OF WISCONSIN

UNIVERSITY OF WISCONSIN Data Applicant data gathered from WECAN during hiring period for the 2014-2015 school year Applicant Characteristics Teaching experience Selectivity of undergraduate institution Highest level of education Certification Vacancy Characteristics Student demographics Subject to be taught School funding Membership affluence Applicants: 16,000 Applications: 195,000 Districts: 327 Vacancies: 6,000 76% of all WI districts 88% of all WI teaching positions Say this: Majority of previous research uses data related to teachers that are hired Our data is unique in that it examines prospective teachers and the districts in which they are applying for jobs 11/7/2018 UNIVERSITY OF WISCONSIN

UNIVERSITY OF WISCONSIN Measures Vacancy-level: Locale (CCD) City, Suburb, Town, Rural Supply High: Elementary, Early Childhood, PE, & Social Studies Medium: Math, ELA, Science, Music/Theatre/Art, & Special Education Low: ELL, FCS, Agriculture Education, & Technology Education Applicant-level: (What are we calling this? Use the term here) Exclusively Rural Exclusively Non-rural Geographically Flexible Might want to mention that the examples of the supply categories are not exhaustive. Take a look at the proportion of applications that the geo-flexible folks sent to rural vacancies. You don’t need to put it in the presentation, but you can mention it here. City, Large = Inside urbanized area and inside a principal city, population of 250,000+ City, Midsize = Inside urbanized area and inside a principal city, population of >= 100,000 and < 250,000 City, Small = Inside urbanized area and inside a principal city, population of > 100,000 Suburb, Large = Outside principal city and inside urbanized area, population of 250,000+ Suburb, Midsize = Outside a principal city and inside urbanized area, population of >= 100,000 and < 250,000 Suburb, Small = Outside a principal city and inside urbanized area, population of > 100,000 Town, Fringe = Inside an urban cluster <= 10 miles from urbanized area Town, Distant = Inside an urban cluster > 10 miles and <=35 miles from urbanized area Town, Remote = Inside an urban cluster > 35 miles from urbanized area Rural, Fringe = Rural territory <= 5 miles from urbanized area and <= 2.5 miles from urban cluster Rural, Distant = Rural territory > 5 miles and < 25 miles from urbanized area and > 2.5 miles and <= 10 miles from urban cluster Rural, Remote = Rural territory > 25 miles from urbanized area and > 10 miles from urban cluster 11/7/2018 UNIVERSITY OF WISCONSIN

UNIVERSITY OF WISCONSIN Method Descriptive Vacancy Applicant Probit regression (# apps) = 𝛽0+ 𝛽1(income)+ 𝛽2(town)+ 𝛽3(suburb)+𝛽3(city)+ 𝛽4(town)*(income)+ 𝛽5(suburb)*(income)+ 𝛽6(city)*(income)+ e 11/7/2018 UNIVERSITY OF WISCONSIN

Average Applicants per Vacancy by School District Locale City 32.15 Large 29.45 Midsize 34.23 Small 32.35 Suburb 45.14 50.65 49.24 22.39 Town 26.29 Fringe 31.31 Distant 23.50 Remote 23.17 Rural 27.56 31.71 29.65 20.00 Is this applications or applicants? I think it’s applications I would do something (color, circles, etc.) here to emphasize: Similarities between remote towns, small suburbs, and remote rural districts Similarities between fringe rural, fringe town, and large cities. 11/7/2018 UNIVERSITY OF WISCONSIN

UNIVERSITY OF WISCONSIN One of the supply level/locale interactions here. Which one? - Income (but let’s discuss) Present coefficients or graphs? I’ll need help explaining the poisson regression. OK. 11/7/2018 UNIVERSITY OF WISCONSIN

UNIVERSITY OF WISCONSIN Mobility (should this go with the vacancy-level questions or applicant-level questions?) - Are teachers currently working in rural districts more likely than teachers currently working in non- rural districts to try to exit their current locale? 11/7/2018 UNIVERSITY OF WISCONSIN

Applicants’ Geographic Preferences Proportion of Statewide Applicants Average Number of Applications per Applicant Exclusively Rural 4.72% 1.40 Exclusively Non-rural 55.57% 4.66 Geographically Flexible 39.71% 24.22 We need to know how these numbers change when we take out teachers with no experience. 11/7/2018 UNIVERSITY OF WISCONSIN

Applicants’ Geographic Preferences and Experience Average Years of Experience Exclusively Rural 8.09 Exclusively Non-rural 7.68 Geographically Flexible 4.73 11/7/2018 UNIVERSITY OF WISCONSIN

Applicants’ Geographic Preferences and Education 11/7/2018 UNIVERSITY OF WISCONSIN

UNIVERSITY OF WISCONSIN Should I include our findings of no significant difference among geographic preferences for certification and selectivity of undergrad institution? Nah – we’re already full here. 11/7/2018 UNIVERSITY OF WISCONSIN

UNIVERSITY OF WISCONSIN Summary Rural schools have fewer applicants than suburban districts, but so do towns and cities. XX vacancies are in rural locales, however 56% of applicants are exclusively non-rural. Exclusively rural applicants are veteran educators, but make up only 5% of the labor supply. Was Walker’s policy supported by the data? We’ll be able to check, using this next round of WECAN data, to see if rural areas actually attracted more applicants and if those applicants were more likely to be uncertified. 11/7/2018 UNIVERSITY OF WISCONSIN