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High Demand Labor Sectors and College Enrollment: A Preliminary Analysis of the Work Ready Kentucky Scholarship (WRKS)

Jillian Frost University of Kentucky

Martin School of Public Policy and Administration Fall 2020

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Executive Summary

States have taken a variety of approaches to improving educational investment in the

labor market and increasing educational attainment statewide. One such approach is the idea

of target sectors – identifying high demand and high growth industries to direct business and

educational investment across the state. Since 2011, the Commonwealth of Kentucky has

utilized target sectors to identify high demand high wage occupations in order to drive labor

force participation, employment, and educational alignment. To combat projected employee

shortages in the identified target sectors and low educational attainment across the state,

Kentucky launched the Work Ready Kentucky Scholarship (WRKS) program in 2016 to financially

incentivize educational investment in programs that created a clear pathway to employment in

a target industry sector. While existing literature has found some benefit to incentivizing

enrollment and aligning curriculum with occupational outcomes, there is little research that

identifies a causal relationship between offering a scholarship program and increases in the

identified sector’s enrollment.

In this paper, I examine the impact of the Work Ready Kentucky Scholarship (WRKS) on

enrollments in target sector programs at the 16 colleges in the Kentucky Community and

Technical College System (KCTCS). Using panel data from academic years 2014 to 2018, I

estimate a fixed effects regression model. Overall, results suggest that the implementation of

WRKS has had a minimally positive effect on increasing the number of students enrolled in

target industry sector programs. However, given research limitations due to data availability,

the findings of this paper should not be taken as conclusive but rather supplementing the

narrative and motivation for providing such a scholarship. The results demonstrate that further

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research is needed to isolate the impact of the Work Ready Kentucky Scholarship program on

target sector enrollment as it continues into its fourth year. If these results confirm that the

Work Ready Kentucky Scholarship has in fact, had a minimal effect on increasing total sector

enrollments, policy changes may need to be considered around scholarship redesign and/or

marketing.

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Introduction

In 2016, the Commonwealth of Kentucky launched the Work Ready Kentucky

Scholarship program to encourage students to enroll in industry-specific degree programs in

order to improve educational attainment across the state and increase investment in target

sector workforce areas. The Work Ready Kentucky Scholarship (WRKS) provides scholarships to

students who enroll in diploma, certificate, and associate degree programs in high demand

target industry sectors. In this paper, I evaluate the early impact of WRKS on student

enrollment in target sectors at the Kentucky Community and Technical College System (KCTCS)

in its first two years of operation.

Educational Attainment and Work Readiness of Kentucky Counties

Kentucky consistently ranks at the bottom of the United States for educational

attainment. The American Community Survey five-year estimates rank Kentucky as having the

fourth lowest attainment of bachelor’s degrees, and 45th for high school graduation rates. Just

23.2 percent of Kentucky’s adult population (aged 25 years and older) has a bachelor’s degree

or higher, compared to a 30.6 percent nationwide average (American Community Survey,

2018). High school graduation rates (and therefore the population eligible to pursue a college

degree) are similarly low. Kentucky reports that 85.2 percent of the state’s population has a

high school diploma or equivalent, while the nationwide average stands at 88.9 percent.

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Figure 1: Educational Attainment in Kentucky, United States

Source: American Community Survey, 2018

The annual High School Feedback Report published by KYStats tracks educational and

occupational outcomes for students in the years following their high school graduation and

demonstrates similarly low educational attainment rates. Just 22 percent of 2012 high school

graduates had obtained a bachelor’s degree and just nine percent had obtained a certificate or

associate’s degree by 2019 (Council on Postsecondary Education, 2019). Sixty-nine percent of

2012 graduates were working in 2019, with a mean average wage of $27,374. These data

indicate the need for a scholarship such as WRKS to increase educational attainment and

employment in higher wage fields.

The Work Ready Scholarship is also intended to increase the supply of workers trained

in high demand industry sectors. The Work Ready Community report estimates a total demand

of over 70,500 workers for target sectors; however, between 2013 and 2017, just 28 percent of

all graduates in Kentucky were employed in a target employment sector (KY Stats, 2019). In

order to meet this expected demand, Kentucky needs to increase the number of trained

workers in the identified target sectors.

23.20%

85.20%

30.60%

88.90%

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

Bachelor's Degree High School Graduate

Kentucky United States

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Target Sectors and the Evolution of the Work Ready Kentucky Scholarship

In 2011, the Commonwealth of Kentucky implemented sector strategies, “regional,

industry-focused approaches to building skilled workforces” in order to address workforce

needs and economic development (Sector Strategies, 2020). Target sectors are workforce

industries that are expected to have strong future demand, high projected growth, and high

wages and are based on expected talent needs. Kentucky identified its first set of target sectors

for workforce and career pathway development, based on talent needs and future growth. In

2016, the Commonwealth released the Work Ready Kentucky Strategic Plan, which updated the

target sectors to address emerging skills gaps, tying industry-recognized credentials and

potential career pathways to high wage, high demand occupations (Table 1) (WIOA State Plan,

2018). The state aimed to align demand high demand industry sectors with postsecondary

educational opportunities to create clear career pathways for Kentuckians.

The sector strategies initiative compiled both the original and current sectors from a

review of economic and workforce data, an assessment of industry credentials and the supply

of jobs in demand, and collaboration with local workforce investment boards, KCTCS, and the

Workforce Development Cabinet (Kentucky Workforce Investment Board, 2013). By identifying

these target sectors, the state hoped to promote investment and interest in these fields to

promote additional growth.

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Table 1: Original and Current Target Sectors for Kentucky

Original Target Sectors (2011) Current Target Sectors (Updated 2016)

• Automobile and Aircraft Manufacturing

• Transportation, Distribution and Logistics

• Business Services and Research and Development

• Health Care/Social Assistance

• Energy Creation/Transition

• Advanced Manufacturing

• Business Services and Information Technology

• Construction

• Healthcare

• Transportation, Distribution, and Logistics

Source: WIOA State Plan, 2018

To further the Work Ready Strategic Plan and support career pathways to these target

industries, Governor Bevin announced the Work Ready Kentucky Scholarship (WRKS) program

in December of 2016. Bevin’s executive order aimed to both increase educational attainment

and the number of skilled workers in the top five high-demand workforce sectors by offering

scholarships to those students who enroll in industry-recognized degree and certificate

programs (Watkins, 2016).

The Work Ready Kentucky Scholarship Program (WRKS) is a last-dollar scholarship

program aimed at providing Kentuckians who do not hold an associate’s degree the means to

afford and complete a college certificate, diploma, or associate’s degree (Work Ready

Scholarship Program, 2020). WKRS is available to college-age and adult students, as well as

through dual credit for certain high school students. Eligible students must enroll in an

approved program of study leading to an industry-recognized Certificate, Diploma, or Associate

of Applied Science (AAS) degree in one of the five identified high demand target workforce

sectors. Eligible programs are selected by each college and approved by the Kentucky Higher

Education Assistance Authority (KHEAA), which then publishes a list of accepted programs.

KHEAA is also responsible for the disbursement of student aid. Students may enroll as full-time

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or part-time students, though enrolling part-time may exhaust eligibility for the program prior

to finishing a certificate or degree, depending on the number of required credits. High school

students may enroll in a maximum of two Work-Ready courses per year following exhaustion of

Dual Credit Scholarship funding options (Work Ready Kentucky Dual Credit Scholarship, 2020).

Student eligibility expires when the first of the following conditions are met:

• Receipt of scholarship funding for four academic terms;

• Receipt of the scholarship for 60 credit hours of enrollment; or

• Receipt of associate’s degree.

Table 2: Work Ready Kentucky Scholarship (WRKS) Overview

Adult Students (18+) High School Students

Eligibility • Kentucky Resident and U.S. Citizen

• High school diploma or GED (or working towards GED)

• Have not previously earned an associate’s degree or higher

• Be enrolled or accepted in an approved postsecondary program

• Kentucky resident enrolled in Kentucky high school

• Not be eligible for, or have exhausted eligibility for the Dual Credit Scholarship

• Enroll in career and technical education coursework in an approved industry-specific pathway

Award Details

• Covers remaining tuition and fees after other state and federal grant aid

Limited to the first of:

• Four academic terms;

• 60 credit hours; or

• Completion of an associate’s degree

• Equal to the dual credit enrollment rate

Limited to:

• two approved technical and career dual credit courses per year

Source: Work Ready Kentucky Scholarship Program, 2020; Work Ready Kentucky Dual Credit Scholarship, 2020

Early Results from the Work Ready Kentucky Scholarship

In its first two years of operation, the Work Ready Kentucky scholarship was awarded to

2,926 non-high school students enrolled at one of the 16 colleges in the KCTCS system, with an

average award amount of $2,856 per student (Office of Research and Policy Analysis, 2019).

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Note that KHEAA disbursed WRKS for the 2019-2020 academic year, but this data is not yet

available. At the time, KCTCS colleges offered 2,181 approved diploma, certificate, and

associate’s degree programs in the five target sectors (Figure 2). Note that there may be

additional programs offered in target sectors but may not be on the approved list of eligible

programs. Most scholarships were awarded in advanced manufacturing (27.5 percent),

business and information technology (28.4 percent), and healthcare (26.7 percent). Relatively

few scholarships were awarded in the construction and transportation sectors in comparison

(10.7 percent and 6.7 percent, respectively) (Office of Research and Policy Analysis, 2019). This

may be due to a lack of interest in the construction and transportation fields, given that pre-

scholarship enrollments in these fields were much less than other fields, and fewer programs

were offered at the colleges in years prior to WRKS.

Figure 2: Work Ready Awards by Sector (2017-2018) and Work Ready Eligible Programs (2014-2018)

Source: Office of Research and Policy Analysis, 2019

In its second year (2018-2019), WRKS funding was expanded by $2.5 million to account

for the expansion of eligibility to dual credit high school students (Chilton, 2018). Additionally,

the number of programs offered by KCTCS colleges in eligible fields expanded by 151 programs

Distribution of WRKS Awards Across Sectors

Business Health

Advanced Manufacturing Construction

Transportation

2,1152,090

2,139

2,181

2,332

1,950

2,000

2,050

2,100

2,150

2,200

2,250

2,300

2,350

2,400

2014 2015 2016 2017 2018

WRKS Eligible Programs

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providing students with a wider variety of work-ready programs to choose from (Course

Catalog, 2020). With expanded funding, additional programs, and higher familiarity and

recognition, WRKS awards to KCTCS students increased by over 1,000 awards between 2017

and 2018. These trends have likely continued for the 2019-2020 school year with constant

funding levels, increased awareness of the scholarship, and an increase of 115 eligible programs

across the 16 KCTCS colleges.

However, it is difficult to evaluate if WRKS has had an impact on enrollments in target

sector fields given downward trends in total enrollment overall. Community colleges have been

facing declining enrollments since peak enrollment during the Recession. Between 2007 and

2017, Kentucky community college enrollment fell by 26 percent (AACC, 2019). These trends

are true for enrollment in target sector fields as well – enrollments in target sector fields fell by

21.8 percent in comparison since 2014 (Figure 3). Furthermore, since the implementation of

WRKS in 2017, target sector enrollments have continued to fall, from 22,614 in 2016 to 22,359

in 2018. Non-target sector field enrollment follows a similar trend, though at a faster rate,

falling from 33,102 in 2016 to 29,524 in 2018 (Interactive Data Center, 2020).

Figure 3: Work Ready and Non-Sector Enrollments, 2014-2018

Source: Interactive Data Center, 2020

29,325 22,359

32,64929,524

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

2014 2015 2016 2017 2018

Work Ready Sector Enrollments Non-Sector Enrollments

WRKS

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Enrollment trends within individual sectors vary – while enrollments in advanced

manufacturing, construction, and transportation have increased from pre-WRKS levels,

enrollments in business and health fields have continued to decline (Figure 4).

Figure 4: Target Sector Enrollments at KCTCS Colleges, 2014-2019

Source: Interactive Data Center, 2020

Previous Literature

Aligning Education and Workforce Needs

Literature on the topic of workforce alignment and higher education curricula confirms

the important relationship between the labor market development and institutions of higher

education. As the role of higher education increasingly becomes focused on employment

outcomes, institutions face heightened pressures and incentives to create occupation-driven

strategies to align curriculum and programs with workforce demand. A number of studies have

identified frameworks and models for institutions to follow when re-aligning curriculum and

degree programs with labor market information to best serve their students.

A study published by Cleary and Van Noy outlined several frameworks to effectively

approach alignment across postsecondary education using dual outcomes of job vacancies and

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

2014 2015 2016 2017 2018

Advanced Manufacturing Business and IT Construction

Healthcare Transportation and Logistics

WRKS

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employer-identified skills gaps (2014). Evaluating various metrics to quantify labor market

demand and postsecondary alignment, their models encourage states and universities to use

comparisons of graduate production and job openings, earnings and employment, and real

time jobs data and turnover. The Aspen Institute took a similar approach and heavily

emphasized the data and resources available to institutions in order to improve student success

across community colleges (2016). New data sources, including unemployment insurance

matching (UI), aggregate job postings for state and regional markets, and public labor market

information can help community colleges make informed decisions about how best to prepare

students for the current and future state of regional labor markets. Community colleges should

leverage this data to advise their students, determine the viability of new programs, improve

existing program alignment to labor demand, and close ineffective programs with limited

workforce opportunity.

Incentive Effects of Financial Aid

Prior research on the relation of financial aid and college decision-making confirms that

monetary aid contributes to a variety of college-going decisions and behaviors, including

enrollment, retention, and graduation. Price manipulation through tuition decreases and

financial aid (grants, loans, and work study) is seen as one of the main policy instruments to

expand access and enrollment in higher education. Leslie and Brinkman reviewed expansive

literature on the relationship between price and enrollment to evaluate the relationship

between these mechanisms and enrollment outcomes. They concluded that financial aid has a

significant impact towards lessening the burden of attending college (Leslie and Brinkman,

1987). Heller’s update to Leslie & Brinkman’s review concludes that aid sensitivity is dependent

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on the type of aid awarded, though decreases in financial aid leads to declining enrollments

across all types of aid (1997). Students are most sensitive to changes in grant aid, potentially

due to the visibility of the price and being focused on net cost as opposed to the sticker price of

enrolling.

Dynarski and Scott-Clayton reviewed literature on efficacy of financial aid policy while

also highlighting potential barriers to conducting causal research in the field (2013). Their

review of existing literature found evidence that lower costs can improve access and

completion rates, with knowledge of grant assistance or a price discount increasing enrollment

rates. Dynarski’s study of the Social Security Benefit found that after the grant program

abruptly ended, college attendance of the eligible awardee group fell sharply and the combined

results of several quasi-experimental studies about state merit aid programs suggest that an

additional $1,000 in grant aid may increase college enrollment by 4 percentage points (Dynarski

and Scott-Clayton, 2013).

It is important to note that the financial aid program itself may create a barrier to entry

for some students. Dynarski and Scott-Clayton also address the idea that the complexity of

applying for an aid program may undermine the effectiveness of the award (Dynarski & Scott-

Clayton, 2013). Given that the applications for FAFSA and other aid programs are lengthy and

burdensome, many students and parents may not choose to apply for a program. Eric Bettinger

confirms this concern in an experimental study, where groups of parents and students received

differential amounts of information about and assistance with completing the FAFSA. The

treatment group which received the most information about and assistance with completing

the FAFSA had a higher college enrollment rate for both high school seniors (24 percent) and

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for those with no prior college experience (16 percent) when compared with the groups that

received no information or minimal information (Bettinger, 2012).

The authors also draw an important distinction about the difficulty of disentangling the

effect of financial aid from unobservable student characteristics and interactions with other aid

programs that may also impact college enrollment rates (Dynarski & Scott-Clayton, 2013).

Researchers have often addressed such concerns using discrete policy changes in financial aid

policy to compare pre-and post-policy outcomes, or by using eligibility cut-offs to compare

differences in student outcomes for those students who receive differential aid amounts (Page

and Scott-Clayton, 2015). Using these methods, multiple studies find that enrollment increases

when the net price of attending college is exogenously lowered. Furthermore, interactions

between aid programs (i.e. federal aid and loans versus state-based aid and loans) based on

eligibility or applications may prevent researchers from isolating the causal effect of a singular

aid program (Page and Scott-Clayton, 2015).

In Tennessee, lawmakers sought to take advantage of the relationship between price

and enrollment to encourage college enrollment and educational attainment by offering last

dollar scholarship funding for all high school students and adults who did not already hold an

associate’s or bachelor’s degree. Eligible students can use scholarship aid received towards any

degree program at an approved community or technical college. Given its early successes, the

program is often cited as evidence of the benefit of such financial aid programs on enrollment.

The Tennessee Promise program for graduated high school students has grown in each cohort –

from 57,660 applicants in cohort 1 to 62,570 in cohort 4. Additionally, enrollment (of those who

were deemed eligible and completed award requirements) has grown from 16,206 to 17,782 in

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2018. In its first year, the Tennessee Reconnect program for working adults planned for 8,000-

10,000 applications, and instead received 31,000 (Tennessee Promise Annual Report, 2018).

While these numbers are certainly impressive, there is no causal link established between the

awarded scholarship and increased enrollment.

As of 2019, at least 26 states across the United States have adopted some sort of

financial aid program specifically directed at increasing enrollment in high demand workforce

sectors (Anderson et. al, 2020). These states all offer a financial aid incentive to students

seeking a postsecondary credential in fields that have been designated as high demand within

the state. However, despite the recent launch of these industry-focused financial aid programs

(a majority have been launched in the past three to four years), there is little research to

confirm that offering a scholarship for target programs will increase enrollment and that any

subsequent enrollment gains are not due to prior trends or other factors. In this study, I will

conduct a preliminary analysis of the impact of WRKS on increasing community college student

enrollment in workforce sectors in Kentucky.

Data and Methodology

Data

To analyze preliminary impacts of the Work Ready Kentucky Scholarship on increasing

target sector enrollment at the Kentucky Community and Technical College System (KCTCS), this

study utilizes publicly available enrollment and demographic data from KCTCS and the Council

on Postsecondary Education from academic years 2014 to 2018 for each of the 16 community

and technical colleges in Kentucky. While the Work Ready Kentucky Scholarship was disbursed

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in the 2019-2020 school year, data are not yet available through KHEAA or KCTCS, and

therefore the analysis is limited to the first two years of WRKS operation.

The outcome variable of interest, target sector enrollment, is measured as a share of

the total KCTCS enrollment (target sector enrollment/total enrollment) to better evaluate the

overall impact of WRKS. Using the percentage of enrollment helps approximate if WRKS is

generating new enrollments in target sector programs or cannibalizing existing enrollments

from non-sector fields. This variable was created by aggregating enrollments in associate’s

degree, certificate, and diploma programs as reported by CPE for the programs that correspond

to KHEAA’s list of Work Ready Kentucky eligible programs. For both academic years 2017 and

2018, the target sector share of enrollment includes all for-credit certificates, degrees, and

diplomas offered in eligible WRKS fields at KCTCS. In 2017, associate’s degrees were excluded

from WRKS eligibility, however, these are included in all years of data to account for any

spillover effects of emphasizing high wage high demand jobs, as well as the fact that certificate

programs may comprise the majority of the associate’s degree in the same field.

The main explanatory variable of interest is the number of Work Ready Kentucky

Scholarships awarded by college for 2017 and 2018. These data exclude the Work Ready

Kentucky Scholarship for high school students due to a lack of sufficient data on high school

student demographics, awards by college, and the distribution of awards across sectors. Data

also include covariates that may influence target sector enrollment including the average WRKS

amount awarded, the number of WRKS eligible programs offered1, demographic count

variables for race, gender, adult (over 25 years of age), and low income status, in addition to

1 Variable generated using KHEAA’s published list of eligible Work Ready Kentucky programs.

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control variables for area development district unemployment rate and full-time equivalent

enrollment. Figures A1 to A3 in the Appendix display summary statistics for each of these

variables.

Methodology

The primary objective of this study is to investigate the relationship between the share

of target sector enrollment and the number of Work Ready Kentucky Scholarships awarded

over time to address the question: has WRKS increased the number of students enrolled in

target sector fields? These results may be used to inform future development of the WRKS

program or may suggest that investment might better serve Kentuckians through other means.

This analysis uses an OLS regression model on panel data from 2014 to 2019 for the 16 KCTCS

community colleges with institution and year fixed effects estimation. Institution fixed effects

are included to account for time invariant characteristics of each KCTCS college over time. Each

college operates in a unique region with a distinct set of student populations which should be

accounted for in this analysis.

I use three models as described below to examine the impact of WRKS:

Model 1: Targetshare1= β0 + β1WRKSi+ui where Targetshare represents the share of

total enrollments comprised by target sector enrollment and WRKS represents the number of

Work Ready Kentucky Scholarships awarded.

Model 2: Targetshareit = β0 + β1WRKSit + αi + δt + uit where fixed effects for institution

(αi) and year δt (base year 2014) are included in the basic OLS regression.

Model 3: Targetshareit = β0 + β1WRKSit+ β2fteit + β3lowincit + β4programsit + β5avgdollarit

+ β6femaleit + β7maleit + β8blackit + β9hispit + β10whiteit + β11adultit + β12unempit + αi + δt + uit

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where fte is full time equivalent enrollment, lowinc counts the number of low income students,

programs is the number of WRKS eligible programs offered, avgdollar is the average WRKS

award amount, female and male are counts for each gender, black, white, and hisp are counts

for each race, adult is the number of adults aged 25 and over, and unemp is the employment

rate for the area development district.

Correlation

Preliminary analysis of the relationship between target sector enrollment and the

number of Work Ready Scholarships awarded indicate a very slight positive relationship. As the

number of scholarships awarded increases, there is a small upward trend in the share of

enrollment comprised of target sector fields (Figure 5). However, the strength of this

relationship may not be very strong, particularly given limited years of data.

Figure 5: Target Sector Enrollment and number of Work Ready Kentucky Scholarships Awarded

I also ran secondary analyses using the same model and control variables to evaluate

the relationship between the number of WRKS awarded in each target sector and enrollments

in that target sector. Furthermore, given the large drop in healthcare enrollments between

0

0.2

0.4

0.6

0.8

0 50 100 150 200 250 300 350

Targ

et S

ecto

r Sh

are

of

Enro

llmen

t

WRKS Awarded

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2014 and 2015 (over 4,000), new variables were generated to evaluate the impact of WRKS

excluding healthcare sector enrollments and WRKS awarded in healthcare fields. The resultant

scatterplots for both individual sectors and the new sector that excludes healthcare suggest a

stronger correlation between the number of WRKS awarded and the total number of

enrollments, indicating that the decline in healthcare enrollments may outweigh a stronger

positive effect of WRKS on total sector enrollments in the original analysis (Figure 6).

Figure 6: Individual Target Sector and New Sector Compared to WRKS Awarded in Target Sector Field

0

100

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300

400

500

600

700

0 50 100 150 200Ad

van

ced

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ufa

ctu

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WRKS Awarded in Advanced Manufacturing

Advanced Manufacturing

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1000

1200

1400

1600

0 50 100 150 200

Bu

sin

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WRKS Awarded in Business

Business

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Co

nst

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WRKS Awarded in Construction

Construction

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WRKS Awarded in Healthcare

Healthcare

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Results

Results from Model 1 do not suggest a strong relationship between the number of

WRKS awarded and the share of enrollment composed of target sector fields. While the

resultant coefficient is minimally positive, the relationship is not statistically significant

However, Model 1 does not account for time invariant characteristics across KCTCS colleges or

cross-year variation. Adding in institution and year fixed effects in Model 2 results in a slightly

larger coefficient of relation, though not significant. While minimal, this shift suggests that state

and year fixed effects do account for some variation in target sector enrollment. Model 2 does

not account for variation attributable to covariates and therefore may suffer from omitted

variable bias. Consequently, estimates for both Model 1 and Model 2 involve bias that weakens

the results.

To control for potential bias as discussed above, Model 3 includes both time and year

fixed effects and covariates. Controlling for age, race, gender, income level, area

unemployment, full-time equivalent enrollment, and the number of WRKS eligible programs

slightly increases the magnitude of the coefficient and the results become statistically

0

50

100

150

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Tran

spo

rtat

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rollm

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WRKS Awarded in Transportation

Transportation

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New

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New Sector WRKS Awarded

New Sector (Excluding Healthcare)

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significant at p<0.1. These results suggest that increasing the number of WRKS awarded by one

scholarship increases the total share of enrollment comprised by target sector enrollment by an

almost imperceptible .025 percent.

Table 3: Regression Results, Three Models

Explanatory Variable

Coefficient Estimates

(1) Basic OLS

(2) With fixed effects

(3) With fixed effects and

controls

WRKS Awarded 0.0000816 (9.83e-05)

0.000138 (0.000126)

0.000250* (0.000129)

Observations 80 80 80

R2 0.0036 0.863 0.917 Robust standard errors in parentheses Significant covariates include: full-time equivalent enrollment (p<.01), male (p<0.05), and adult (p<.05). Coefficients for significant covariates are all smaller than .05%. See Table A.4 for full covariate detail. *** p<0.01, ** p<0.05, * p<0.1

Secondary analysis for the new sector (excluding healthcare) and evaluating the impact

of WRKS on individual target sectors yields interesting results. The basic OLS regression yields

positive and statistically significant results for the new sector, construction, and transportation.

Using this simple analysis would suggest that, excluding healthcare, awarding one additional

Work Ready Scholarship increases enrollment in the new sector fields by over two students,

awarding WRKS in construction increases construction enrollments by 1.4 students, by 1.6

students in the transportation field. However, with the exception of transportation, these

results do not hold up in the fixed effects estimation, or the fixed effects and covariates

estimations.

Controlling for covariates and institution and year fixed effects, the number of WRKS

awarded in a particular field has a positive and statistically significant relationship with the

number of enrollments in that field for advanced manufacturing, healthcare, and

transportation. These results mirror the upward trends identified in Figure 6: Individual Target

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Sector and New Sector Compared to WRKS Awarded in Target Sector FieldFigure 6, with the

exception of healthcare. For every WRKS awarded to a student enrolled in an advanced

manufacturing field, the total number of students enrolled in advanced manufacturing

increases by 0.6 (p<.01). The relationship between WRKS and enrollment is even more

pronounced in the transportation field, with enrollment in the transportation sector increasing

by 1.09 for every WRKS awarded (p<.05). Interestingly, the results show the largest impact

occurring in the healthcare sector – for every WRKS awarded in health, the number of students

enrolled in healthcare fields increases by 1.3 (p<.01) – which contradicts the almost flat trends

suggested in Figure 6.

When fixed effects for school are excluded, however, results for the relationship

between healthcare WRKS awarded and healthcare enrollments aligns with the expected trend,

and yield a negative, non-statistically significant coefficient. This may suggest that variation in

the healthcare sector may be largely due to differences in school characteristics.

Table 4: New Sector and Individual Sector Enrollment Regression Results

Explanatory Variable

Coefficient Estimates

(1) Basic OLS

(2) With fixed effects

(3) With fixed effects and

controls

New Sector Enrollments

2.340** (1.067)

-.00439 (0.366)

0.364 (0.340)

Advanced Manufacturing

2.085 (0.512)

0.564** (0.215)

.608*** (0.203)

Business 0.936

(0.921) -0.503 (0.314)

-0.173 (0.206)

Construction 1.466** (0.462)

0.263 (0.294)

0.351 (0.297)

Healthcare -0.216 (1.075)

-0.0290 (0.774)

1.312*** (0.421)

Transportation 1.671*** (0.491)

0.790 (0.644)

1.09** (0.524)

Note that regressions for individual sectors and the new sector excluding healthcare were run on total sector enrollment

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Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1

Discussion

The preliminary data from the Work Ready Kentucky Scholarship in years 1 and 2 is

largely inconclusive regarding the effect of WRKS on enrollment in target sector fields. Overall,

regardless of potential threats to validity, it appears that WRKS did not affect any systematic

change in target sector enrollment in its first two years of operation. The strongest potential

impact is seen in advanced manufacturing fields and transportation sectors. However,

preexisting enrollment declines across the KCTCS colleges may bias the results. While awarding

WRKS may not reverse declining enrollment trends in target sectors, it may be contributing to a

slower decline that may, in time, reverse. Furthermore, while WRKS may not have a strong

impact on enrollment itself, awarding WRKS may have positive impacts in other areas that are

not measured in this paper, such as retention and graduation rates for students already

enrolled in target sector programs.

In order to identify a true causal relationship between the Work Ready Kentucky

Scholarship and enrollments in target sector fields at the KCTCS colleges, additional research is

needed. The results presented are challenged by a number of factors including but not limited

to: identification of WRKS programs, missing data for scholarships awarded in 2019, low

numbers of WRKS, aggregate data, and a lack of a counterfactual to measure the impact of

WRKS implementation versus expected enrollment values.

Future research should consider issues of data collection and availability. Currently, the

process for identifying programs eligible for the Work Ready Kentucky Scholarship is left to

each college. The outcome variable was created based on the current list of eligible programs,

Frost 24

which may not be an exhaustive list of all programs offered in the target sectors at an

institution. Institutions may offer additional programs in target sectors that have not been

submitted to KHEAA for WRKS eligibility. If there are programs missing from the eligible list, this

may bias the results downwards, if indeed enrollment is increasing in target sector programs

not included on the WRKS list. Furthermore, the limited sample size and low numbers of WRKS

awarded decrease the power of this study. Early results from Work Ready may suggest a

minimally positive relationship with target sector enrollments, but year 3 (and beyond) results

may indicate a stronger trend, or even a reversal. Without additional data and a true

counterfactual, the research cannot conclude that these target sector enrollments would not

have happened but for implementation of WRKS.

This study does not comprehensively evaluate the source of student enrollment. While

the outcome variable (target sector share of total enrollment) attempts to address this by

measuring growth in the percentage of students enrolled in target sector fields, this not fully

answer the question if WRKS is attracting new, never-enrolled students to WRKS programs,

drawing them away from future enrollment in a non-sector field, attracting students already

enrolled in a target sector program, or cannibalizing students who are currently enrolled in non-

sector fields. If students were already enrolled in a target sector program, and subsequently

applied for WRKS in their second term, this would not be considered new enrollment, and there

could introduce reverse causality where enrollment in a target sector program is driving

applications and WRKS awards.

Additionally, WRKS programs are not typically considered transferable programs – it

may be that WRKS encourages students to enroll in target sector programs but reduces the

Frost 25

number of students enrolled in and transferring to four-year institutions. Individual level data

about enrollment and the time of WRKS application and award coupled with a difference in

differences model that uses community college enrollments in another state as a

counterfactual would help provide additional details necessary to further isolate the causal

relationship between Work Ready Kentucky Scholarship awards and enrollment in a target

sector field.

Policy Implications

If indeed the impact of the Work Ready Kentucky Scholarship is minimal on increasing

student enrollment in target sectors, policy changes should be considered. However, given that

WRKS is still in its first years of operation, decisions should not be made too hastily, and be

considered in the broader context of the scholarship’s mission and the higher education

environment in Kentucky. Policy considerations focus on three key areas: marketing and

awareness, scholarship processes, and redesign and expansion.

Given that WRKS is still in the first few years of operation and is targeted towards a

narrow audience, it may be a lack of awareness and the relative “newness” of the program that

contributes to both low scholarship participation and low subsequent enrollments. In contrast

to the Tennessee Promise program, which was branded nationally and throughout the state as

a “free college” program, Work-Ready was marketed for in-demand sector employment

(Blackford, 2017). Previous marketing focused more on the outcome, as opposed to providing

free education. In November 2020, however, Work Ready Kentucky launched a redesigned

website and marketing campaign, “Never Underestimate You!”, in hopes of raising awareness

of and interest in the program, especially during the pandemic (Vogt, 2020). Now, the campaign

Frost 26

prominently features “Tuition Paid” language and has partnered with a popular Kentucky name,

B. Stille of Nappy Roots, to draw attention to the scholarship program (Work Ready Kentucky,

2020). In the coming years, we may see a renewed interest in the WRKS program and an

increase in target sector enrollments, due to additional press, the new marketing campaign,

and interest driven by the COVID-19 pandemic.

The state should also evaluate potential barriers to entry and enrollment for prospective

Work Ready Kentucky Scholarship awardees. Currently, students must first apply to an eligible

college, be an enrolled or accepted to enroll in an approved program, complete the FAFSA, and

then apply to the Work Ready Kentucky Scholarship (Work Ready Kentucky, 2020). Even

minimal barriers such as an additional application may dissuade some students from enrolling

or participating in a financial aid program. Students may not be aware of the additional

application required or that the FAFSA is required in order to complete the application and

award. Furthermore, the last-dollar approach of WRKs may introduce additional confusion into

the financial aid process. Students may expect to receive a certain amount, and then Last dollar

scholarship amounts are more difficult to predict, given the number of factors that are

considered in identifying the scholarship amount to fill the gap after considering other forms of

aid and ability to pay.

Finally, if WRKS continues to have a minimal impact on target sector enrollment, the

state may want to consider redesigning and/or expanding the program. Looking to Tennessee

may provide a model for the state, whose early results with their Promise programs for high

school students and for adults show promising tends towards increasing enrollments and

attainment. Such a program could be limited to a target population, a type of institution (i.e.

Frost 27

two-year institutions), or degree levels (similar to WRKS). A true Promise program (and

marketed as such) may attract more awareness than the industry specific WRKS and have a

greater impact on a broader population, increasing enrollment in target sector fields and in

other fields. However, an expansion of this nature would involve significant monetary and

political investment which would need to be fully considered prior to implementation.

Frost 28

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Appendix Table A.1: Summary Statistics (1)

Year WRKS Sector Enrollments

Non-WRKS Sector Enrollments

Work Ready Scholarships

Awarded

Target Sector Programs Offered

Average Work Ready Dollar

Amount

Mean SD Mean SD Mean SD Mean SD 0 0

2014 1832.8125 1263.946 2040.563 1324.141 0 0 132.1875 34.0200 0 0

2015 1498.8125 997.830 2082.438 1437.167 0 0 130.625 33.4781 0 0

2016 1413.375 819.083 2068.875 1421.789 0 0 133.6875 34.6655 0 0

2017 1399.375 831.979 1949.563 1418.958 58.9375 54.774 136.3125 33.6704 2340.375 480.345

2018 1397.4375 812.434 1845.25 1414.368 124.0625 103.675 145.75 33.5688 2384.625 350.118

2019 1431.5625 819.134 1761.313 1427.728 124.0625 103.675 152.9375 33.6322 2384.625 350.118

Table A.2: Summary Statistics (2)

Year Female Male Black Hispanic White

Mean Std. Dev Mean SD Mean SD Mean SD Mean SD

2014 3034.563 1848.711 2340.5 1283.248 511.188 818.241 160.875 190.520 2366.438 1289.854

2015 2812.188 1624.738 2184.812 1214.073 425.5 654.553 164.375 201.706 2034.313 1111.645

2016 4134.188 5580.893 2173.000 1224.380 360.563 585.093 182.313 214.555 1912.563 1038.905

2017 2571.375 1381.917 2099.813 1159.846 384.875 596.831 202.5 257.307 1796.813 1005.343

2018 2714.125 1512.168 2188.563 2188.563 374 602.238 213.688 260.620 1748.813 970.547

2019 2761.16 1632.919 2106.375 1228.369 401.563 668.653 240.75 308.307 1716.563 990.767

Table A.3: Summary Statistics (3)

Year Adult Low Income Full Time Equivalent Student

Area Development District Unemployment

Rate

Mean SD Mean SD Mean Std. Dev Mean SD

2014 2366.438 1289.854 2624.066 1481.691 2977.063 2036.604 .0738 .0180

2015 2034.313 1111.645 2228.563 1256.289 2904.944 1752.867 .0596 .0156

2016 1912.563 1038.905 2080.438 1062.612 2843.538 1658.171 .0643 .0240

2017 1796.813 1005.343 1992.063 1102.644 2782.713 1657.201 .0587 .0161

2018 1748.813 970.547 1900.75 1067.500 2775.531 1651.880 .0506 .0113

2019 1716.563 990.767 1900.75 1067.500 2772.443 1727.490 .0499 .0111

Table A.4: Main Regression Results with Covariates, Model 3

Variables Share of Sector Enrollment

WRKS Awarded 0.000250*** (0.000129)

Full Time Equivalent Enrollment -5.16e05*** (1.38e-05)

Low Income -2.62e-05 (6.12e-05)

Number of WRKS Eligible Programs 0.00113 (0.00178)

Average WRKS Amount Awarded -1.49e-06 (1.85e-05)

Frost 33

Female -1.03e-06 (8.93e07)

Male -9.25e-05** (4.23e-05)

Black 4.88e-05 (4.43e-05)

Hispanic -0.000191 (0.000130)

White 4.37e-05 (3.20e-05)

Adult (25 and over) 9.39e-05** (4.37e-05)

Unemployment Rate (Area Development District) -0.00668 (0.00537)

Big Sandy CTC 0.00455 (0.128)

Bluegrass CTC 0.0677 (0.179)

Elizabethtown CTC -0.0138 (0.103)

Gateway CTC 0.00191 (0.0485)

Hazard CTC -0.0685 (0.0600)

Henderson CC 0.0706 (0.115)

Hopkinsville CC -0.0997* (0.571)

Jefferson CTC 0.0839 (0.249)

Madisonville CC 0.190*** (0.464)

Maysville CTC -0.0637 (0.0453)

Owensboro CTC -0.0786 (0.0870)

Somerset CC -0.138 (0.110)

Southcentral KY CTC 0.0347 (0.0481)

Southeast KY CTC -0.228** (0.110)

West Kentucky CTC 0.106 (0.0969)

2015 -0.0372 (0.0234)

2016 -0.0299 (0.0282)

2017 -0.0369 (0.0647)

2018 -0.0454

Frost 34

(0.0779)

Constant 0.414* (0.208)

R2 0.917 Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

Table A.5: Individual Sector Regression Results with Covariates, Model 3

Variables New Sector

Advanced Manufacturing

Business Construction Healthcare Transportation

WRKS Awarded 0.364 0.608*** -0.173 0.351 1.312*** 1.090** (0.340) (0.203) (0.206) (0.297) (0.421) (0.524)

Full Time Equivalent Enrollment

-0.000500 -0.00882 0.00487 0.00265 -0.0966** 0.000744 (0.0188) (0.00852) (0.00960) (0.00777) (0.0455) (0.00358)

Low income 0.211*** 0.00665 0.145*** 0.0308 0.278* 0.0310** (0.0735) (0.0233) (0.0494) (0.0225) (0.160) (0.0122)

Number of WRKS Eligible Programs

-2.120 -1.965** -1.553 0.294 1.069 1.354** (2.500) (0.757) (1.429) (0.701) (3.827) (0.517)

Average WRKS Amount Awarded

-0.00166 -0.00499 -0.00285 -0.00388 0.00958 0.00617 (0.0166) (0.0102) (0.0126) (0.00588) (0.0370) (0.00594)

Female -0.00104 -0.000640 0.00162* -0.00171*** -0.00544 -0.000430 (0.00152) (0.000803) (0.000842) (0.000518) (0.00409) (0.000304)

Male 0.00602 -0.00492 -0.0147 -0.00117 -0.254** 0.0312* (0.0703) (0.0299) (0.0450) (0.0246) (0.117) (0.0183)

Black 0.0716 0.0192 0.0374 0.0104 0.446 0.00612 (0.0824) (0.0227) (0.0563) (0.0267) (0.328) (0.0177)

Hispanic -0.0989 0.0742 -0.170 0.0373 -1.032** -0.0557 (0.261) (0.0921) (0.223) (0.0603) (0.505) (0.0654)

White 0.00580 0.0275 0.00746 -0.00105 0.202** -0.0337** (0.0528) (0.0187) (0.0405) (0.0168) (0.0798) (0.0130)

Adult (25 and over)

0.0547 0.0254 0.0346 -0.00393 0.229** 0.00675

(0.0582) (0.0296) (0.0391) (0.0179) (0.114) (0.0177)

Unemployment Rate (Area Development District)

-1.854 -1.516 -4.690 3.472** -25.76 -0.0743 (4.478) (3.089) (3.474) (1.687) (15.83) (1.623)

Big Sandy CTC 104.2 -31.38 78.78 104.9* -19.09 -59.09 (199.7) (57.17) (116.7) (56.42) (325.1) (42.45)

Bluegrass CTC 691.6** 158.0* 491.9** 70.76 -167.7 -47.38 (293.2) (92.68) (203.2) (81.38) (657.8) (68.01)

Elizabethtown CTC

551.2*** 115.9* 254.3** 86.96** -439.7 70.84* (153.4) (58.42) (100.3) (41.00) (287.2) (41.28)

Gateway CTC 155.8** -86.58*** 193.5*** 3.672 -75.85 40.50** (70.90) (28.13) (43.44) (22.36) (147.3) (19.80)

Hazard CTC -168.3** -184.4*** -42.35 36.66* -19.07 21.43 (69.84) (29.01) (41.47) (18.29) (112.9) (17.39)

Henderson CC -229.0 -248.0*** -13.70 -7.137 215.1 60.67* (174.4) (45.99) (107.1) (49.62) (311.9) (31.83)

Hopkinsville CC -218.0** -176.9*** 47.50 -53.97** 113.4 -34.60

Frost 35

(92.31) (39.69) (74.91) (22.73) (282.6) (25.85)

Jefferson CTC 408.8 96.60 393.3 -124.5 -288.9 6.612 (400.2) (141.8) (277.9) (113.4) (1,093) (110.5)

Madisonville CC

-233.1*** -197.2*** -15.48 -26.32 608.0*** 15.75 (68.57) (27.00) (43.29) (19.57) (135.2) (16.39)

Maysville CTC -3.950 -56.60** 27.97 14.59 -187.0* 9.973 (62.29) (21.14) (38.63) (17.67) (110.4) (13.58)

Owensboro CTC

82.38 -71.51* 125.8* 46.75 -111.1 -20.59 (110.2) (36.81) (65.17) (30.38) (179.8) (24.42)

Somerset CC -74.38 -54.59 9.867 -40.32 -762.5* 1.925 (214.2) (56.74) (150.0) (59.01) (392.9) (39.09)

Southcentral KY CTC

208.8*** -7.058 139.5*** 33.04 -32.47 51.62*** (68.41) (33.79) (44.33) (24.10) (148.1) (15.57)

Southeast KY CTC

-225.3 -105.2** -53.07 -2.461 -199.6 -74.74** (149.4) (47.90) (86.81) (42.21) (244.6) (31.38)

West Kentucky CTC

52.71 -121.8** 86.45 18.24 409.0 64.17** (137.8) (52.06) (92.18) (37.58) (283.3) (31.83)

2015 24.11 14.21 12.68 -3.237 -37.01 1.902 (29.27) (10.92) (18.46) (8.319) (50.00) (8.076)

2016 63.13** 42.17*** 23.17 -0.931 17.02 1.810 (26.60) (11.75) (15.23) (7.398) (56.60) (7.885)

2017 80.30* 41.29 51.69 9.106 -9.264 -16.21 (46.84) (25.19) (34.07) (15.50) (107.5) (18.24)

2018 110.7* 57.69** 67.57 16.47 -10.12 -31.55 (62.61) (27.79) (41.33) (19.21) (120.8) (19.20)

Constant 376.0 366.7*** 159.9 -49.20 -258.2 -132.2* (348.2) (92.04) (213.5) (96.59) (615.8) (66.54)

Observations 80 80 80 80 80 80

R-squared 0.994 0.991 0.992 0.965 0.973 0.958 Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1