Research

Abstract:

Generative AI has diffused into white-collar work faster than any prior technology, yet firm-level productivity gains remain elusive. We test whether institutional ambiguity, AI deployed faster than rules for its use, is a binding constraint. In a preregistered 2 x 2 experiment with 3,026 U.S. and 572 German workers, a one-sentence AI-use policy raised self-reported task AI use by 39 percentage points, cut completion time by 0.4 standard deviation, and raised clarity by 0.4 standard deviation, in both countries. Gains concentrate on clarity, depth, and speed. Workers in low-collaboration jobs capture nearly all the quality dividend. The policy leaves demographic adoption gaps unchanged, but workers with favorable views of AI become much more likely to use it, with the U.S. gap between favorable and unfavorable workers quadrupling from 7 to 30 percentage points.

Giuntella, Osea et al. 2026. "Making Workers AI Ready: Behavioral Interventions and AI Adoption Among Workers." AEA RCT Registry. April 27. https://doi.org/10.1257/rct.18144-1.0 

Paper available upon request.

Abstract

Using a randomized control trail, we evaluate the impacts of a Housing Stabilization Initiative on very low-income and severely housing cost burdened renters in a large Ohio city. The collaborative initiative combined flexible financial assistance with case management and due to limited funds and excess demand following the conclusion of ERA, during the 6-month program pilot, randomization was used to assign more than 1200 participants to the intensive program or a minimal intervention strategy: housing problem solving. By comparing the outcomes of those who receive the intensive intervention to those who receive Housing Problem Solving, we estimate the causal impact of the program on emergency shelter entry and eviction filings. We find that the participants of the intensive intervention experience a 2.8*** percentage point reduction (p-value 0.002) in the likelihood of shelter entry on average. The effects are larger for those at imminent risk of homelessness- that subpopulation experiences a 4pp*** reduction (p-value 0.002). Additionally, participants in the full-service intervention experience a statistically significant 6-7 percentage point*** reduction in the likelihood of receiving a filing. Among those receiving financial assistance, we also observe repeated measures of participant well-being on 13 dimensions and show aggregate improvements 1-3 months into program participation. Using administrative case management and financial assistance processing records, we explore mechanisms including timeliness of financial assistance payment and clients’ selection/prioritization of self-determined goals.

Frye, Brandon and Ashley Orr. 2025. "Housing Stabilization Initiative – Program Evaluation." AEA RCT Registry. November 21. https://doi.org/10.1257/rct.17204-1.0 

Abstract

Educators who experiment with new and emerging teaching interventions and methods face an important tradeoff between costs (upfront and ongoing implementation time costs) and sometimes uncertain returns (student learning and retention gains) to the intervention. Using an online survey and a pre-registered choice experiment, we measure the preferences of over 50 economics educators, including those engaged with the Economics Education Network for Experiments (EENE). The discrete choice experiment asks instructors to select their preferred class to teach between two classes with randomly assigned attributes. We examine how instructors' hypothetical choices vary with class size, intervention time cost, student performance, and retention. We then investigate how, if at all, preferences change with a hypothetical additional monetary payment that rewards the initial use and application of a new teaching strategy. We also report descriptive results regarding instructors' ranking of the hypothesized impact and time cost of educational interventions and self-reported willingness to experiment with academic/growth mindset-embedded teaching strategies. Preliminary findings indicate that instructors predict the largest effects on student learning from teaching strategies that they rank as the most time intensive to implement. Thus, monetary incentives for instructors may enable future experimentation with these teaching strategies, suggesting direction for future research in economics education.

Marshall, Emily and Ashley Orr. 2025. "Preferences over Growth Mindset Embedded Teaching Strategies: A Discrete Choice Experiment." AEA RCT Registry. November 17. https://doi.org/10.1257/rct.17196-1.0 

Paper available upon request.

Abstract

Working professionals re-engage with local universities through many professional development programs. In this paper we measure learning gains made by public service professionals in single day courses. We leveraged a pre-post survey instrument that was collaboratively developed with the five instructors of the 12 courses we study. These participant survey assessments measure learning: the change in pre- and post-course objective performance on skill assessments and subjective self-efficacy aligned to measurable course learning objectives. Should other instructors or programs be interested in this approach, we describe the implementation. Combining the standardized data across the courses, serving over 300 public servants, we find large statistically significant learning gains. Objective skill improves 27 percentage points (pp), a .7 s.d. improvement and subjective self-efficacy/confidence measures improve 31pp, a 1.7 s.d. improvement. Taken together, our work implies that single day professional development courses are an impactful mechanism for continued public and nonprofit sector workforce development.  

Joint work with Greg Moody and Sandra Miller. [Recently Submitted].

Paper available upon request.

Abstract

Survey evidence is widely used in economics and economics education. In this practical guide, focused on surveys relevant to economics education and college students, we provide a review of lessons learned from previous studies, other disciplines, and our own use of surveys in research and teaching. The piece is organized chronologically following a survey researcher's research design, survey design, iteration, and analysis of data.

Joint work with Brandon Sheridan.

Paper available upon request.

Abstract:

Job posting websites have expanded awareness of employment opportunities beyond a worker's location of origin, yet there is persistent heterogeneity in unemployment rates and labor earnings across labor markets in the US. Do employers disregard far applicants? How difficult is job search at a distance in the USA? Using a resume audit methodology, this pre-registered experiment compares the callback rates and likelihood of receiving an interview invitation for fictitious job candidates who apply to local jobs, jobs that are non-local but commutable, and jobs that would require migration. Sending nearly 10,000 resumes to low and middle income jobs, from candidates originating in 36 randomly selected US cities, and applying across the entire USA- I find that candidates that would have to move to accept the job are contacted 3.5 percentage points (or 23%) less and invited to interview 4.2 pp (or 47%) less relative to close candidates. Middle distance/longer commute candidates have a marginally longer duration to contact and are invited to interview 1.5 pp (or 17%) less. While previous research notes that workers may prefer to apply to local jobs (Marinescu and Rathelot 2018), this research suggests that employers also prefer local applicants. This may be a significant structural barrier for workers and households who find job search at a distance necessary.

Check this link for the latest version of the paper.

Funding/Awards:

National Science Foundation Doctoral Dissertation Research Improvement Grant in Economics and Public Policy:  "Employer Preference for Applicants based on Geographic Location: A Resume Audit." Grant Number: 2018750  Brian Kovak (PI) and Ashley E. Orr (CO-I).

Institute for Research on Poverty Dissertation Award for my Dissertation Proposal: “Frictions to Labor Mobility and the Geographic Inequality of Labor Market Opportunities.” Fall 2023

Pre-registered with AEA RCT Registry:

• Kovak, Brian, Ashley Orr and Lowell Taylor. 2023. "Employer Preferences for Local vs. Non-Local Workers: A Resume Audit." AEA RCT Registry. February 13. https://doi.org/10.1257/rct.9904-1.0 

Presented at the annual meeting of the Labor Employment Relations Association (LERA) conference in NYC, June 2024.

Abstract

Rapid technological advances in robotics and artificial intelligence influence the challenges and composition of tasks completed by workers, in both existing and emerging occupations, necessitating nearly continuous learning and experimentation among managers, workers, and new/returning labor market entrants. In this project, funded by a subgrant of the Federal Build Back Better Regional Challenge award focused on workforce development training programs in Southwestern PA, we embed growth mindset training in existing workforce development programs. The growth mindset training is interdisciplinary (using neuroscience, education, and cognitive psychology research), and is collaboratively designed with the community stakeholders, using a community based/community engaged research approach. We implement the training with organizations that support key populations including youth, justice-involved job seekers, skilled apprentices and trainees, and educators at all levels (K-12, regional universities, and community colleges). This paper discusses the training components, which affirm to both job trainers and trainees that our skills are malleable and improve with effort, support, and strategies. In this phase of the project, we train job trainers/instructors/mentors of training programs and use a pre-post assessment to determine the effectiveness of the training session. Early results imply that a short 75 minute session can influence trainers’ mindset beliefs (by .88 s.d.) and self-efficacy by 14 percentage points (or .84 s.d.). This paper provides resources for others to implement growth mindsets in their contexts and discusses directions for future work.

 Keywords: Growth Mindset, Management, Job Training, Train-the-Trainer

JEL Codes: M53- Personnel Economics: Training,  I24-Education and Inequality

Press coverage: NextPittsburgh, Block Center Blog, and CMU News

Full paper and slides available upon request.

Presented at the Urban Economics Association, Southern Economics Association, and Western Economics Association International annual meetings in 2021/2022.

Submitted to Advances in Industrial Labor Relations and presented at the annual meeting of the Labor Employment Relations Association (LERA) conference in Detroit. June 2, 2023. Paper Link.

Abstract

This paper examines workers’ stated workplace retention plans by leveraging a survey of nearly 5,000 randomly selected adults from Northeast Ohio during the pandemic recovery period in 2022. We investigate what workplace experiences and benefits increase or decrease the likelihood of planned retention at a workers’ current job and planned job search. We find that retention plans are increasing in workers’ satisfaction, pay satisfaction, and desire for training, and for workers who are in the middle or at the end of their career relative to early career. We also investigate the relative importance of remote work on retention plans. We show that retention plans decrease as the demands for the job interfere with workers’ family lives, and as workers reported increased stress at work during the pandemic. We find workers with reported perceived financial security, and second/alternative income sources are also less likely to plan to be retained by their current employer and more likely to search for work. We conduct subgroup analyses and discuss how different amenities are important to different worker subsets. We conclude by offering recommendations for how employers may increase retention and policymakers may support job seekers and hiring firms.

 Keywords: Labor Economics, Retention, Employment Benefits, Worker Preferences, Job Search

JEL Codes: J2- Demand and Supply of Labor, J32: Nonwage Labor Costs and Benefits