1. In collaboration with

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

3. 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

4. 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

5. 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

6. UNIVERSITY OF WISCONSIN
Data
Applicant data gathered from WECAN during hiring period for the 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

7. 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

8. 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

9. 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

10. 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

11. 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

12. 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

13. 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

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

15. 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

16. 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