Publications | Matthew D. Baird

2024

Do sectoral training programs reduce arrests?: Evidence from a low-income targeted training program RCT

Shamena Anwar, Matthew Baird, John Engberg, and 1 more author

Journal of Human Resources, 2024

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This study presents the first causal evidence of the impact on arrest rates of a sectoral training program that was implemented using a randomized control trial. The results indicate that, among those with a prior criminal record, individuals in the treatment group were two-fifths as likely to be arrested post-randomization as those assigned to the control group. Among the overall population, arrest probabilities decreased by one-half. We explore potential mechanisms for this effect and find suggestive evidence in favor of the training program’s impact on earnings, as well as peer effects from other trainees.
Beyond test scores: the impact of test persistence value-added on student achievement

Matthew Baird, John Pane, and James Soland

Education Economics, Dec 2024

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This study presents the first causal evidence of the impact on arrest rates of a sectoral training program that was implemented using a randomized control trial. The results indicate that, among those with a prior criminal record, individuals in the treatment group were two-fifths as likely to be arrested post-randomization as those assigned to the control group. Among the overall population, arrest probabilities decreased by one-half. We explore potential mechanisms for this effect and find suggestive evidence in favor of the training program’s impact on earnings, as well as peer effects from other trainees.
Skill signals in a digital job search market and duration in employment gaps

Matthew Baird, Paul Ko, and Nikhil Gahlawat

Journal of Labor Research, Dec 2024

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With the rise of the digital job search market, new opportunities for signaling skills and competencies to employers have emerged. In this paper, we examine listed skills on individuals’ LinkedIn profiles in the United States between 2015 and 2021, both those members add themselves and skills for which they are endorsed from others in their network. We use an inverse probability weighted proportional hazards model with time varying covariates to estimate the relationship between listed skills on shortening employment gaps (time between jobs). We find that, for self-added and peer-endorsed skills respectively, an additional ten skills on the profile decreases median employment gap duration by about 0.7 and 0.4 months, from a median baseline of around 6 months gap. Individuals with no education listed on their profile have the largest benefit from listed skills in terms of reducing employment gaps. Disruptive tech and soft skills also are related to higher returns. Additionally, skills added during the employment break have a substantially stronger relationship than pre-existing added skills. More experienced workers have larger returns than less experienced workers, consistent with the hypothesis that these skills are otherwise difficult to signal to potential employers. These findings are consistent with online job markets’ use of technology offering more efficient ways to signal skills, shortening time to reemployment.
Do publicly funded neighborhood investments impact individual-level health-related outcomes? A longitudinal study of two neighborhoods in Pittsburgh, PA from 2011 to 2018

Rebecca B. Smith, Matthew D. Baird, Gerald P. Hunter, and 4 more authors

Housing Policy Debate, Jul 2024

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Research examining the relationship between a neighborhood’s built environment and resident health has largely either used a static, cross-sectional research design or focused on the neighborhood in its entirety, making it difficult to understand the relationship between specific dynamic neighborhood characteristics and individual well-being. We use longitudinal data from the Pittsburgh Research on Neighborhood Change and Health (PHRESH) studies to assess the relationship between publicly funded neighborhood investments between 2011 and 2018 and five health-related outcomes: food insecurity, stress, perceived neighborhood safety, neighborhood satisfaction, and dietary quality. We additionally determine whether the distance between an individual’s place of residence and the investment affects the magnitude of associations. Using individual and year fixed effects models, we find that when measured at the neighborhood level, an increase by one standard deviation (SD) in investments (about $130 million) is associated with decreased food insecurity (−0.294 SD), increased safety (0.231 SD), and increased neighborhood satisfaction (0.201 SD) among adults who remain in the study for at least two waves of data collection. We also analyze specific investment types and find that commercial investments are largely driving the changes in food insecurity, safety, and neighborhood satisfaction, while business and residential investments are correlated with the decrease in stress.
Food insecurity among aging SNAP participants and eligible nonparticipants in two predominantly low-income Black neighborhoods: Implications for SNAP enrollment and outreach for older adults

Sameer M. Siddiqi, Jonathan Cantor, Madhumita Ghosh Dastidar, and 5 more authors

Journal of the Academy of Nutrition and Dietetics, Jul 2024

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Background The Supplemental Nutrition Assistance Program (SNAP) plays a critical role in alleviating poverty and food insecurity. Despite these benefits, many older Americans who are eligible for SNAP do not participate in the program. Few studies have explored household factors and food insecurity outcomes associated with nonparticipation among older Black Americans. Objectives The study aim was to explore changes in food insecurity and related financial hardship outcomes between 2020 and 2021 among SNAP participants, eligible nonparticipants, and ineligible nonparticipants; compare reasons for not participating in SNAP; and to compare household factors associated with SNAP nonparticipation. Methods Longitudinal design examining data from 2020 and 2021 to assess changes in food insecurity over the course of the coronavirus disease 2019 pandemic. Participants/setting Participants were 528 adults (aged 30 to 97 years) in households randomly selected from a listing of all residential addresses in two predominantly Black neighborhoods with lower incomes in Pittsburgh, PA, and surveyed between March to May 2020 and May to December 2021. Main outcome measures Food security was measured using the validated 6-item US Department of Agriculture Adult Food Security Survey Module. Statistical analyses performed Findings are based on a descriptive analysis of food security and related indicators. Statistical testing was performed to assess differences between SNAP participation status and individual characteristics, food security, and financial hardship using Wald F test for continuous measures and Pearson χ2 test for categorical measures. A multivariable linear model was used to assess the association of SNAP participation and eligibility status with change in food insecurity. Results In cross-sectional analyses of 2021 data, no differences were observed between SNAP participants and eligible nonparticipants for food insecurity, food bank use, mean weekly food spending per person, and difficulty paying for basics. However, with respect to changes in food insecurity over the course of the pandemic, SNAP participants experienced a greater improvement in mean food security scores between 2020 and 2021 (–0.52 reduction in mean food insecurity score or a 16% improvement in food security; P ≤ 0.05) relative to SNAP-eligible nonparticipants. Perceived ineligibility (71.3%) and perceived lack of need (23%) were the most common reasons for not participating in SNAP. Conclusions More than one-third of SNAP participants and eligible nonparticipants experienced food insecurity and financial hardship. However, there were differences in the changes in food insecurity between these groups.
Disability status and work: Employment trends in the US, 2024

Matthew Baird, and Danielle Kavanagh-Smith

LinkedIn Economic Graph Research Note, Oct 2024

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We examine work disparities for individuals with disabilities in the United States, leveraging self-reported data from LinkedIn members. Overall, while differences between workers with and without disabilities persist across such outcomes as employment, seniority, and retention, the gaps are shrinking with younger generations.
The relationship between gender differences in relocation and promotion

Caroline Liongosari, Matthew Baird, and Allison Lewis

LinkedIn Economic Graph White Paper, Aug 2024

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We analyze survey and LinkedIn profile data to understand how men and women differ in their likelihood to relocate and motives for doing so. We find that not only men are more likely to relocate, but they are also more likely to relocate to locations where they do not already have many connections. In contrast, women are more likely to live close to their hometowns and are more likely to relocate for their partner’s career and not for their own. These differences are also reflected in the gender difference in promotion rates. We find that even though relocation to places where members have few connections only account for 5% of promotions, they account for 40% of the gender gap.
Measuring gender gaps in economic network strength in the US

Matthew Baird, Danielle Kavanagh-Smith, and Osonde Osoba

LinkedIn Economic Graph White Paper, Jul 2024

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We build a new framework of network strength that combines four elements into a cohesive model of how a network could help career advancement: (a) value of the information your connections have for you, (b) bandwidth of information sharing between connections, (c) redundancy of information in your network based on shared connections, and (d) overall size of your network. We estimate the model for gender in the United States (US). We find an 8 percentile point gap in network strength and across several of the above-listed features, of which approximately 2/3rds is explainable by gaps in occupations, firms, platform activity, and other features. Network strength is predictive of the amount of recruiter contact as well as the likelihood the member increased seniority over one year.
Generative AI’s influence on employment patterns

Mar Carpanelli, Matthew Baird, and Cristian Jara-Figueroa

LinkedIn Economic Graph White Paper, Jun 2024

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In this study, we investigate the differential impacts of Generative Artificial Intelligence (GAI) on workers in the US using LinkedIn data, both overall and by their educational attainment levels. We find a gradual shift away from GAI-disrupted occupations over the past six years towards potentially augmented or insulated roles, particularly pronounced among higher-educated workers. Through an analysis of occupational transitions, we make predictions under various scenarios of GAI impact, examining the proportions of workers within different GAI occupation classifications, transitions from employment to non-employment, and shifts in occupational categories. While workers with higher educational attainment tend to exhibit higher rates of occupational mobility, the differential effects of GAI on employment and occupational changes underscore the importance of considering educational disparities in the context of technological advancements.
Generative AI’s impact on the workforce: A technical framework

Mar Carpanelli, Cristian Jara-Figueroa, Karin Kimbrough, and 1 more author

LinkedIn Economic Graph Technical Note, Apr 2024

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This technical note presents a comprehensive approach to understanding the impact of Generative AI (GAI) technologies on the workforce based on skills. We outline a technical framework and methodology aligned with the latest literature, composed of three stages: GAI-assisted skill classification; embedding-driven skill classification expansion; and skill-based occupation classification.
Gender differences in skills: Global differences in shares of types of skills

Matthew Baird, and Silvia Lara

LinkedIn Economic Graph Research Note, Mar 2024

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New data from LinkedIn shows that women possess a higher proportion of soft skills compared to men across all examined countries, with the global gap widening over the past eight years. Men have higher shares of tech skills, although the gender gaps diminish when considering skills inferred from job descriptions or when examining differences within occupation and industry.
Generative AI and gender: Global measures of workers in GAI classifications

Matthew Baird, Mar Carpanelli, and Silvia Lara

LinkedIn Economic Graph Research Note, Mar 2024

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We examine gender disparities in the potential impact of generative AI across countries. While impact varies, in nearly all countries, women are more likely to work in disrupted occupations than men, while men are more likely than women to be employed in augmented or insulated roles. The extent of these disparities fluctuates considerably among countries.
US race/ethnicity work trends: Leadership and remote work

Matthew Baird, and Danielle Kavanagh-Smith

LinkedIn Economic Graph Research Note, Feb 2024

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We examine differences in labor outcomes, including leadership and remote and hybrid work, in the US by race/ethnicity. Our analysis focuses on individuals who were LinkedIn members who self-identify as either Asian, Black, Latino, or White.
Insights into U.S. migrations: Migration’s impact on network formation

Caroline Liongosari, Brian Xu, and Matthew Baird

LinkedIn Economic Graph Research Note, Jan 2024

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When moving to a new city, people naturally make new connections through a variety of ways. We analyze how this phenomenon manifests through the creation of professional connections on LinkedIn by examining how LinkedIn members make connections in the first year after a move.

2023

Optimal allocation of seats in the presence of peer effects: Evidence from a job training program

Matthew D. Baird, John Engberg, and Isaac M. Opper

Journal of Labor Economics, Apr 2023

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We model optimal treatment assignment in programs with a limited number of seats and study how the presence of peer effects impacts the optimal allocation rule. We then use data from a randomized control trial to show evidence that there are large peer effects in the context of job training for disadvantaged adults in the United States. Finally, we combine the model and the empirics to show that the program would have had a much greater impact if the assignment choices had accounted for the peer effects.
A longitudinal study of predictors of serious psychological distress during COVID-19 pandemic

Joshua Breslau, Elizabeth A. Roth, Matthew D. Baird, and 2 more authors

Psychological Medicine, Apr 2023

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Background The prevalence of serious psychological distress (SPD) was elevated during the COVID-19 pandemic in the USA, but the relationships of SPD during the pandemic with pre-pandemic SPD, pre-pandemic socioeconomic status, and pandemic-related social stressors remain unexamined. Methods A probability-based sample (N = 1751) of the US population age 20 and over was followed prospectively from February 2019 (T1), with subsequent interviews in May 2020 (T2) and August 2020 (T3). Multinomial logistic regression was used to assess prospective relationships between T1 SPD with experiences of disruption of employment, health care, and childcare at T2. Binary logistic regression was then used to assess relationships of T1 SPD, and socioeconomic status and T2 pandemic-related stressors with T3 SPD. Results At T1, SPD was associated with age, race/ethnicity, and household income. SPD at T1 predicted disruption of employment (OR 4.5, 95% CI 1.4–3.8) and health care (OR 3.2, 95% CI 1.4–7.1) at T2. SPD at T1 (OR 10.2, 95% CI 4.5–23.3), low household income at T1 (OR 2.6, 95% CI 1.1–6.4), disruption of employment at T2 (OR 3.2, 95% CI 1.4–7.6), and disruption of healthcare at T2 (OR 3.3, 95% CI 1.5–7.2) were all significantly associated with elevated risk for SPD at T3. Conclusions Elevated risk for SPD during the COVID-19 pandemic is related to multiple psychological and social pathways that are likely to interact over the life course. Policies and interventions that target individuals with pre-existing mental health conditions as well as those experiencing persistent unemployment should be high priorities in the mental health response to the pandemic.
Retention of racial-ethnic minorities in the regular army

Maria C. Lytell, Michael L. Hansen, Avery Calkins, and 4 more authors

RAND Report, Nov 2023

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The authors examined retention of racial-ethnic minorities in the Regular Army’s enlisted and officer ranks and how racial-ethnic composition changes as soldiers progress in their careers. The authors also explored reasons that individuals stay in the Army or leave at given points, how unit leader decisionmaking affects such decisions, and what influences promotion decisions.
Pathways into STEM jobs

Nikhil Gahlawat, Matthew Baird, Silvia Lara, and 2 more authors

LinkedIn Economic Graph White Paper, Nov 2023

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Jobs in science, technology, engineering, and mathematics (STEM) have higher incomes and lower unemployment rates on average compared to other jobs. While workers typically prepare for STEM employment through a STEM degree program, many in the STEM workforce do not have a STEM degree. Given this accessibility to STEM jobs and their benefits, we examine pathways into STEM jobs, including for high school graduates and non-STEM college degree holders compared to STEM degree holders. We look at levels of STEM job experience and interest in STEM jobs by workers of different educational backgrounds. We examine the rate of transition into STEM jobs, and how workers persist once in STEM. While pathways into STEM exist, we see differences the types of STEM jobs obtained by workers of different educational backgrounds.
Economic network strength: Race, gender, and community gaps in the US

Matthew Baird, Danielle Kavanagh-Smith, Osonde Osoba, and 1 more author

LinkedIn Economic Graph Research Note, Sep 2023

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We explore economic networks—crucial for career advancement—and data from LinkedIn to analyze disparities across race, gender, and community income groups. We find men, individuals in higher income communities, and Asian and White members tend to have stronger networks than their counterparts, highlighting the need for targeted interventions in fostering inclusive networking environments.
Network formation homophily: Race, gender, and community income in the US

Matthew Baird, Danielle Kavanagh-Smith, Osonde Osoba, and 1 more author

LinkedIn Economic Graph Research Note, Sep 2023

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We present new findings on invitation and acceptance rates in network formation, examining sender and receiver demographics to uncover patterns of homophily and privilege. Key takeaways highlight significant tendencies for members to connect with individuals of their own gender, race/ethnicity, and ZIP Code median income quartile, with marginalized groups exhibiting the strongest homophily, emphasizing the need for inclusive networking strategies.
Disability status and work: Employment and leadership trends in the US

Matthew Baird, and Kory Kantenga

LinkedIn Economic Graph Research Note, Sep 2023

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We examine employment disparities for individuals with disabilities in the United States, leveraging self-reported data from LinkedIn members. Key findings reveal distinct trends, including higher representation in specific sectors, lower representation in senior positions, and higher interest in remote job postings.
International gender representation in STEM employment and skills

Matthew Baird, Silvia Lara, Rosie Hood, and 2 more authors

LinkedIn Economic Graph White Paper, Sep 2023

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Jobs in Science, Technology, Engineering, and Mathematics (STEM) are important for a dynamic economy and offer potential for career progress with higher income and lower unemployment. Consistently, across countries we analyzed, women are consistently underrepresented in STEM, and have the lowest representation in leadership positions within STEM occupations. We investigate possible contributing factors, such as the differences in showcasing STEM-related LinkedIn skills and the stark drop off in women representation between STEM graduation and STEM employment. While these trends are relatively consistent across countries, there is nonetheless wide variation in the magnitude of the disparities.
Disparities in U.S. economic network formation: Gender, race, and community income

Matthew Baird, Danielle Kavanagh-Smith, Osonde Osoba, and 1 more author

LinkedIn Economic Graph White Paper, Jun 2023

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Economic networks provide key opportunities for career progression. We evaluate U.S. LinkedIn network data to examine disparities in network size and growth by gender, race, and local median income. We find large disparities in total network size, but smaller and at times reversed gaps for network growth rates, many of which are narrowing over time. We also demonstrate several important gaps in the inputs to network growth, with members living in lower income communities, Black and Latino members, and women tending to receive fewer invitation requests to connect and many of these same groups having a somewhat lower percentage of invitations they send out being accepted.
Progress and barriers in global gender leadership

Silvia Lara, Matthew Baird, and Rosie Hood

LinkedIn Economic Graph White Paper, Apr 2023

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Despite efforts to promote gender equality, women remain underrepresented in leadership positions globally, in every country and every sector. Using LinkedIn data to estimate the barriers women face in the workplace, our research found that women represent only 32.1% of senior leadership globally despite accounting for 41.8% of the overall workforce. This represents an increase of only one percentage point over the last seven years. However, there have been larger increases in the share of new leadership hires who are women, and in representation in emerging fields such as AI. Our analysis of eight major economies highlights the need to promote gender diversity through inclusive hiring practices including skills-based hiring, flexible work arrangements, and opportunities for women to advance to leadership positions.
Measuring gender gaps in the U.S. STEM workforce

Matthew Baird, Paul Ko, Nikhil Gahlawat, and 2 more authors

LinkedIn Economic Graph White Paper, Mar 2023

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Women continue to be underrepresented in Science, Technology, Engineering, and Mathematics (STEM) education and careers. In this paper, we analyze millions of LinkedIn profiles in the United States to examine the transition from obtaining a STEM degree to securing STEM employment. A significant gender gap exists in both the rate of holding STEM skills and in STEM employment. Our paper also reveals that the greatest expansion in the gender gap occurs between obtaining a STEM degree and working in STEM one year after graduation. We found that during this timeframe, the gender gap in STEM widens by ten percentage points. Nevertheless, we also observe an improvement in the gender representation of new STEM employees across graduation cohorts.
LinkedIn STEM classification methodology

Matthew Baird, Nikhil Gahlawat, Paul Ko, and 1 more author

LinkedIn Economic Graph Technical Note, Feb 2023

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This report outlines the methodology used to create international taxonomies that classify each representative occupational group as STEM or non-STEM. We take a skills-based approach, as STEM is primarily a conceptualization about skills.

2022

Veteran educators or for‐profiteers? Tuition responses to changes in the Post‐9/11 GI Bill

Matthew Baird, Michael S. Kofoed, Trey Miller, and 1 more author

Journal of Policy Analysis and Management, Sep 2022

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In 2010, Congress reauthorized the Post‐9/11 GI Bill by changing reimbursement rates from by‐state maximums to a nationwide limit. This policy created exogenous variation in financial aid for veterans at private universities. We detect changes in tuition only for for‐profit colleges, where we estimate a 1 percent pass‐through rate. This response is mainly from states with decreased benefits; colleges with more veterans, and colleges whose pre‐change tuition was above the state maximum but below the new nationwide level had a pass‐through rate of 8 percent. We also find a negative association between changes in benefits and overall student enrollment for for‐profit colleges.
Beyond traditional academic degrees: The labor market returns to occupational credentials in the United States

Matthew D. Baird, Robert Bozick, and Melanie A. Zaber

IZA Journal of Labor Economics, Aug 2022

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Occupational credentials provide an additional—and, at times, alternative—path other than traditional academic degrees for individuals to increase productivity and demonstrate their abilities and qualifications to employers. In the United States, these credentials typically take the form of licenses and certifications. Although a critical part of the workforce landscape, the literature on the returns to credentials is inadequate, with prior research typically relying on Ordinary Least Squares (OLS) regressions which do not sufficiently control for selection. Using questions that identify credential receipt from the 2015 and 2016 United States’ Current Population Surveys, we construct an instrumental variable of local peer influence using the within-labor market credential rate of individuals sharing the same sociodemographic characteristics, while controlling for the same group’s average wages and a suite of demographic and geographic controls. We use this instrument in a marginal treatment effects estimator, which allows for estimation of the average treatment effect and determines the direction of selection, and we estimate the effects of credentials on labor market outcomes. We find large, meaningful returns in the form of increased probability of individual employment, an effect which is concentrated primarily among women. The effect of having a credential on log wages is higher for those in the sub-baccalaureate labor market, suggesting the potential role of occupational credentials as an alternative path to marketable human capital and a signal of skills in the absence of a bachelor’s degree.
Use of and willingness to use video telehealth through the COVID-19 pandemic

Shira H. Fischer, Zachary Predmore, Elizabeth Roth, and 3 more authors

Health Affairs, Nov 2022

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We examined use of and willingness to use video telehealth during the COVID-19 pandemic in a longitudinally followed cohort. Between February 2019 and March 2021, use and willingness to use increased among nearly all subgroups, with large increases among Black adults and adults with lower educational attainment. In March 2021 Black adults, adults ages 20–39, and high-income adults reported the greatest willingness to use video telehealth.
RCT evidence on differential impact of US job training programmes by pre-training employment status

Matthew D. Baird, John Engberg, and Italo A. Gutierrez

Labour Economics, Apr 2022

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While the recent evidence around the effectiveness of job training programmes has been generally positive, there has been little evidence regarding the differential impact in the U.S. by pre-training employment status. The city of New Orleans implemented a job training programme funded by the U.S. Department of labour Workforce Innovation Fund. They screened potential trainees for suitability and likelihood of completing and benefiting from training. They selected and developed curriculum with input from local firms. The city implemented the training as a randomized controlled trial. In this paper, we evaluate the impact of the training on employment, earnings, and industry of employment, both overall and separately by baseline employment status. We find overall positive effects for earnings, driven by those who did not have a job at the time of training enrolment. We also find positive employment effects for short-term unemployed workers. Individuals in the treatment group were more likely to work in the target industries, suggesting that the gains were happening through the gains in industry-specific human capital.
Job loss and psychological distress during the COVID‐19 pandemic: Longitudinal analysis from residents in nine predominantly African American low‐income neighborhoods

Matthew D. Baird, Jonathan Cantor, Wendy M. Troxel, and 1 more author

Health Economics, Sep 2022

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While psychological distress is a common sequelae of job loss, how that relationship continued during the COVID‐19 pandemic is unclear, for example, given higher health risk to working due to disease exposure. This paper examines changes in psychological distress depending on job loss among a cohort of randomly selected residents living in nine predominantly African American low‐income neighborhoods in Pittsburgh PA across four waves between 2013 and 2020. Between 2013 and 2016, we found an increase in psychological distress after job loss in line with the literature. In contrast, between 2018 and 2020 we found change in psychological distress did not differ by employment loss. However, residents who had financial concerns and lost their jobs had the largest increases in psychological distress, while residents who did not have serious financial concerns—potentially due to public assistance—but experienced job loss had no increase in distress, a better outcome even than those that retained their jobs. Using partial identification, we find job loss during the pandemic decreased psychological distress for those without serious financial concerns. This has important policy implications for how high‐risk persons within low‐income communities are identified and supported, as well as what type of public assistance may help.
Examining the impact of employment status on sleep quality during the COVID-19 pandemic in two low-income neighborhoods in Pittsburgh, PA

Matthew D Baird, Tamara Dubowitz, Jonathan Cantor, and 1 more author

Sleep, Mar 2022

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Study Objectives African Americans have faced disproportionate socioeconomic and health consequences associated with the COVID-19 pandemic. The current study examines employment and its association with sleep quality during the initial months of the pandemic in a low-income, predominantly African American adult sample. Methods In the early months of COVID-19 (March to May 2020), we administered a survey to an ongoing, longitudinal cohort of older adults to assess the impact of COVID-related changes in employment on self-reported sleep quality (N = 460; 93.9% African American). Participants had prior sleep quality assessed in 2018 and a subset also had sleep quality assessed in 2013 and 2016. Primary analyses focused on the prevalence of poor sleep quality and changes in sleep quality between 2018 and 2020, according to employment status. Financial strain and prior income were assessed as moderators of the association between employment status and sleep quality. We plotted trend lines showing sleep quality from 2013 to 2020 in a subset (n = 339) with all four waves of sleep data available. Results All participants experienced increases in poor sleep quality between 2018 and 2020, with no statistical differences between the employment groups. However, we found some evidence of moderation by financial strain and income. The trend analysis demonstrated increases in poor sleep quality primarily between 2018 and 2020. Conclusion Sleep quality worsened during the pandemic among low-income African American adults. Policies to support the financially vulnerable and marginalized populations could benefit sleep quality.
What is associated with changes in food security among low-income residents of a former food desert?

Jonathan Cantor, Bonnie Ghosh-Dastidar, Gerald Hunter, and 4 more authors

Nutrients, Dec 2022

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Lack of geographic access to foods has been postulated as a cause for food insecurity, which has been linked to poor nutrition, obesity, and chronic disease. Building on an established cohort of randomly selected households from a low-income, predominantly Black neighborhood, we examined household food security, distance to where study participants reported doing their major food shopping, and prices at stores where they shopped. Data from the Pittsburgh Hill/Homewood Research on Eating, Shopping, and Health study for years 2011, 2014 and 2018 was limited to residents of the neighborhood that began as a food desert (i.e., low access to healthy foods), but acquired a full-service supermarket in 2013. We calculated descriptive statistics and compared study participants in the former food desert neighborhood whose food security improved to those whose food security did not improve across survey waves. We estimated cross sectional linear regressions using all waves of data to assess food security level among study participants. Distance to major food shopping store was positively associated with food security (p \textless 0.05) while food-store prices were not significantly associated with food security. Findings suggest that for predominantly low-income residents, food secure individuals traveled further for their major food shopping.
Societal impact of research funding for women’s health in rheumatoid arthritis

Matthew D. Baird, Melanie A. Zaber, Annie Chen, and 7 more authors

RAND Report, Jan 2022

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Without information on the potential return on investment for women’s health research, stakeholders lack a basis for altering research investments to improve knowledge of women’s health. In this report, the authors examine the societal cost impact of increasing research funding in rheumatoid arthritis and find that investing in women’s health research yields benefits beyond investing in general research.

2021

Who gets counted as STEM? A new approach for measuring the STEM workforce and its implications for identifying gender disparities in the labor market

Drew Anderson, Matthew Baird, and Robert Bozick

International Journal of Gender, Science and Technology, Dec 2021

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Defining who works in STEM has relied on top-down categorizations of occupations. This study takes a bottom-up approach and surveys a national sample of workers to classify their jobs. We identify a sizeable group of workers who are in the “periphery STEM workforce,” who report working in STEM jobs, but whose occupations are outside of STEM classifications. Using this approach, the gender gap in STEM workforce participation decreases substantially because women are more likely to work in the periphery. However, women in the periphery are compensated less than men, a fact invisible using the current classifications.
Playing catch up: A term-level investigation of the racial gap in STEM retention

Veronica Sovero, Moshe Buchinsky, and Matthew D. Baird

Economics of Education Review, Aug 2021

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This paper examines differences in STEM retention between minority and non-minority students enrolled at the University of California, Los Angeles (UCLA) from 1980 through 2006. Using detailed administrative records of undergraduate students, we document that minority students and non-minority students take divergent pathways through the STEM major. Specifically, minority students take fewer lower division STEM courses in their early career, which delays their enrollment in upper division STEM courses and leads to lower graduation probability in STEM within four years and higher dropout rates. We investigate the potential reasons (and/or predictors) for this apparent discrepancy. To do so, we first identify a student’s major-specific Individual Performance Potential (IPP) from lower division course regressions. We find that once we control for the heterogeneity in the IPP’s and a rich set of term level controls, the differences in intermediate outcomes (declared major, STEM course load) between minority and non-minority students largely disappear, but that some of the gap in outcomes persist, with the exception being in graduation from STEM within five years, for which minority students are more likely after controlling for these factors. Our findings suggest that minority STEM majors would benefit from additional support such as early career course advising.
Trade-offs in selecting the number of years for estimation of teacher effectiveness

Matthew Baird, and John Engberg

Education Economics, Jul 2021

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The number of years to estimate value-added measures (VAM) has received insufficient attention. Researchers often use as many years as available, to increase precision and decrease transitory sorting bias. However, this decision has little theoretical or empirical backing. We develop a theoretical framework and evaluate data from thousands of teachers in three large school districts across several years. For evaluations of past effectiveness for policy purposes, one should almost always use one-year of VAM, while for personnel purposes, use one year of VAM or take a weighted average. Predicting future effectiveness depends on mean reversion or persistence in VAM.
Mixed effects of neighborhood revitalization on residents’ cardiometabolic health

Wendy M. Troxel, Andy Bogart, Stephanie Brooks Holliday, and 4 more authors

American Journal of Preventive Medicine, Nov 2021

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Introduction Despite the growing recognition of the importance of neighborhood conditions for cardiometabolic health, causal relationships have been difficult to establish owing to a reliance on cross-sectional designs and selection bias. This is the first natural experiment to examine the impact of neighborhood revitalization on cardiometabolic outcomes in residents from 2 predominantly African American neighborhoods, one of which has experienced significant revitalization (intervention), whereas the other has not (comparison). Methods The sample included 532 adults (95% African American, 80% female, mean age=58.9 years) from 2 sociodemographically similar, low-income neighborhoods in Pittsburgh, PA, with preintervention and postintervention measures (2016 and 2018) of BMI, diastolic and systolic blood pressure, HbA1c, and high-density lipoprotein cholesterol and covariates. Data were collected in 2016 and 2018 and analyzed in 2020. Results Difference-in-difference analyses showed significant improvement in high-density lipoprotein cholesterol in intervention residents relative to that in the comparison neighborhood (β=3.88, 95% CI=0.47, 7.29). There was also a significant difference-in-difference estimate in diastolic blood pressure (β=3.00, 95% CI=0.57, 5.43), with residents of the intervention neighborhood showing a greater increase in diastolic blood pressure than those in the comparison neighborhood. No statistically significant differences were found for other outcomes. Conclusions Investing in disadvantaged neighborhoods has been suggested as a strategy to reduce health disparities. Using a natural experiment, findings suggest that improving neighborhood conditions may have a mixed impact on certain aspects of cardiometabolic health. Findings underscore the importance of examining the upstream causes of health disparities using rigorous designs and longer follow-up periods that provide more powerful tests of causality.
SNAP participants and high levels of food insecurity in the early stages of the COVID-19 pandemic

Sameer M. Siddiqi, Jonathan Cantor, Madhumita Ghosh Dastidar, and 4 more authors

Public Health Reports, Jul 2021

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Objectives The coronavirus disease 2019 (COVID-19) pandemic has disproportionately strained households experiencing poverty, particularly Black and Latino households. Food insecurity, which entails having limited or uncertain access to a sufficient quantity of nutritious food, is a key pandemic-related consequence. We examined how people enrolled in the Supplemental Nutrition Assistance Program (SNAP) have been affected by the pandemic, particularly Black participants and participants residing in food deserts. Methods Using survey data from a longitudinal cohort study of predominantly Black low-income adults aged ≥18 residing in urban food deserts in Pittsburgh, Pennsylvania, we examined changes in food insecurity and SNAP participation before COVID-19 (2018) and early in the COVID-19 pandemic (March–May 2020). We modeled changes in food insecurity from 2018 to 2020 via covariate-adjusted logistic regression. Results Food insecurity increased significantly among participants enrolled in SNAP and surveyed in both 2018 and 2020 (from 25.9% in 2018 to 46.9% in 2020; P \textless .001). Compared with cohort participants not enrolled in SNAP at both points, cohort participants enrolled in SNAP in 2018 and 2020 had the highest rates of using a food bank in 2020 (44.4%) and being newly food insecure in 2020 (28.9%) (ie, they were food insecure in 2020 but not in 2018). Conclusions Food insecurity during the COVID-19 pandemic increased among low-income Black households enrolled in SNAP and residing in a food desert. Public health recovery efforts might focus on modifying SNAP to improve the food security of people experiencing poverty.
Iprovements in neighborhood socioeconomic conditmions may improve resident diet

Andrea S. Richardson, Rebecca L. Collins, Bonnie Ghosh-Dastidar, and 7 more authors

American Journal of Epidemiology, May 2021

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Neighborhood socioeconomic conditions (NSECs) are associated with resident diet, but most research has been cross-sectional. We capitalized on a natural experiment in Pittsburgh, Pennsylvania, in which 1 neighborhood experienced substantial investments and a sociodemographically similar neighborhood that did not, to examine pathways from neighborhood investments to changed NSECs and changed dietary behavior. We examined differences between renters and homeowners. Data were from a random sample of households (n = 831) in each of these low-income Pittsburgh neighborhoods that were surveyed in 2011 and 2014. Structural equation modeling tested direct and indirect pathways from neighborhood to resident dietary quality, adjusting for individual-level sociodemographics, with multigroup testing by homeowners versus renters. Neighborhood investments were directly associated with improved dietary quality for renters (β = 0.27, 95% confidence interval (CI): 0.05, 0.50) and homeowners (β = 0.51, 95% CI: 0.10, 0.92). Among renters, investments also were associated with dietary quality through a positive association with commercial prices (β = 0.34, 95% CI: 0.15, 0.54) and a negative association with residential prices (β = −0.30, 95% CI: −0.59, −0.004). Among homeowners, we did not observe any indirect pathways from investments to dietary quality through tested mediators. Investing in neighborhoods may support resident diet through improvements in neighborhood commercial environments for renters, but mechanisms appear to differ for homeowners.
Food insecurity in a low-income, predominantly African American cohort following the COVID-19 pandemic

Tamara Dubowitz, Madhumita Ghosh Dastidar, Wendy M. Troxel, and 9 more authors

American Journal of Public Health, Mar 2021

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Objectives. To examine the impact of COVID-19 shutdowns on food insecurity among a predominantly African American cohort residing in low-income racially isolated neighborhoods. Methods. Residents of 2 low-income African American food desert neighborhoods in Pittsburgh, Pennsylvania, were surveyed from March 23 to May 22, 2020, drawing on a longitudinal cohort (n = 605) previously followed from 2011 to 2018. We examined longitudinal trends in food insecurity from 2011 to 2020 and compared them with national trends. We also assessed use of food assistance in our sample in 2018 versus 2020. Results. From 2018 to 2020, food insecurity increased from 20.7% to 36.9% (t = 7.63; P \textless .001) after steady declines since 2011. As a result of COVID-19, the United States has experienced a 60% increase in food insecurity, whereas this sample showed a nearly 80% increase, widening a preexisting disparity. Participation in the Supplemental Nutrition Assistance Program (52.2%) and food bank use (35.9%) did not change significantly during the early weeks of the pandemic. Conclusions. Longitudinal data highlight profound inequities that have been exacerbated by COVID-19. Existing policies appear inadequate to address the widening gap.
A longitudinal study of psychological distress in the United States before and during the COVID-19 pandemic

Joshua Breslau, Melissa L. Finucane, Alicia R. Locker, and 3 more authors

Preventive Medicine, Feb 2021

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The COVID-19 pandemic has caused financial stress and disrupted daily life more quickly than any prior economic downturn and on a scale beyond any prior natural disaster. This study aimed to assess the impact of the pandemic on psychological distress and identify vulnerable groups using longitudinal data to account for pre-pandemic mental health status. Clinically significant psychological distress was assessed with the Kessler-6 in a national probability sample of adults in the United States at two time points, February 2019 (T1) and May 2020 (T2). To identify increases in distress, psychological distress during the worst month of the past year at T1 was compared with psychological distress over the past 30-days at T2. Survey adjusted logistic regression was used to estimate associations of demographic characteristics at T1 (gender, age, race, and income) and census region at T2 with within-person increases in psychological distress. The past-month prevalence of serious psychological distress at T2 was as high as the past-year prevalence at T1 (10.9% vs. 10.2%). Psychological distress was strongly associated across assessments (X2(4) = 174.6, p \textless .0001). Increase in psychological distress above T1 was associated with gender, age, household income, and census region. Equal numbers of people experienced serious psychological distress in 30-days during the pandemic as did over an entire year prior to the pandemic. Mental health services and research efforts should be targeted to those with a history of mental health conditions and groups identified as at high risk for increases in distress above pre-pandemic levels.
The surgical and anesthesia workforce and provision of surgical services in rural communities: A mixed‐methods examination

Catherine Cohen, Matthew Baird, Nirabh Koirola, and 2 more authors

The Journal of Rural Health, Jan 2021

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Purpose Rural‐urban disparities in the surgical and anesthesia workforce exist. This mixed‐methods study describes the distribution of the surgical and anesthesia workforce and qualitatively explores how such workforce and other factors influence rural hospitals’ provision of surgical services. Methods We calculated provider counts by county from the Area Health Resource File. Using American Hospital Association survey data, we sampled rural hospitals, stratified by critical access status and state policies. We conducted qualitative semistructured interviews with administrators at 16 hospitals and performed directed content analysis of factors influencing surgical services provision at rural hospitals. Findings Within rural counties, 55.1% of counties had no surgeon, 81.2% had no anesthesiologist, and 58.1% had no Certified Registered Nurse Anesthetist (CRNA). Administrators reported that rural hospitals struggled to provide many surgical services given lack of subspecialty surgeons and adequate postsurgical care. Rural hospitals likely struggle to generate volumes necessary to support safe and profitable subspecialty surgery programs. Anesthesia services were not reported as a current limitation given that CRNAs in particular had strong, diverse skills sets and many hospitals allowed high CRNA autonomy. However, meeting anesthesia needs for emergency surgeries and 24‐hour obstetrics posed significant challenges. Conclusions While rural hospitals reported meeting community needs for elective and noncomplex surgeries, rural hospitals continued to face significant challenges providing subspecialty surgeries, emergency surgeries, and 24‐hour obstetrical services.
Research funding for women’s health: A modeling study of societal impact: Findings for coronary artery disease

Matthew D. Baird, Melanie A. Zaber, Andrew W. Dick, and 7 more authors

RAND Report, Oct 2021

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Using microsimulation analyses, the authors examined the societal cost impact of increasing research funding in Coronary Artery Disease.
Research funding for women’s health: Modeling societal impact

Matthew D. Baird, Melanie A. Zaber, Annie Chen, and 7 more authors

RAND Report, Oct 2021

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Using microsimulation analyses, researchers examined the impact of increasing funding for women’s health research, with a focus on the following three disease areas: brain health, immune and autoimmune disease, and cardiovascular disease. They found that large societal gains may be possible by increasing investment in women’s health research.
Societal impact of research funding for women’s health in Alzheimer’s disease and Alzheimer’s disease–related dementias

Matthew D. Baird, Melanie A. Zaber, Andrew W. Dick, and 7 more authors

RAND Report, Apr 2021

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Without information on the potential return on investment for women’s health research, stakeholders lack a basis for altering research investments to improve knowledge of women’s health. In this report, the authors examine the societal cost impact of increasing research funding in Alzheimer’s disease and Alzheimer’s disease–related dementias and find that investing in women’s health research yields benefits beyond investing in general research.

2020

Do investments in low-income neighborhoods produce objective change in health-related neighborhood conditions?

Stephanie Brooks Holliday, Wendy Troxel, Ann Haas, and 6 more authors

Health & place, Jul 2020

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This study examined the effect of neighborhood investments on neighborhood walkability, presence of incivilities, and crime in two low-income, primarily African American neighborhoods in Pittsburgh, USA. During the study period, one of the neighborhoods (the intervention neighborhood) received substantially more publicly-funded investments than a demographically matched comparison neighborhood. Comparisons between the neighborhoods showed a significant difference-in-difference for all three outcomes. The intervention neighborhood experienced significantly more change related to improved walkability and decreased incivilities. However, the control neighborhood experienced better crime-related outcomes. Analyses that focused on resident proximity to investments found similar results. This highlights the nuances of neighborhood investment, which is important to consider when thinking about public policy.
Does large-scale neighborhood reinvestment work? Effects of public–private real estate investment on local sales prices, rental prices, and crime rates

Matthew D. Baird, Heather Schwartz, Gerald P. Hunter, and 4 more authors

Housing Policy Debate, Mar 2020

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During the 1990s, the U.S. Department of Housing and Urban Development awarded over \6 billion in competitive grants (HOPE VI) to spur neighborhood redevelopment. We add to HOPE VI research by examining the impacts of a large set of public–private real estate investments, including HOPE VI, made over a 16-year period in a distressed neighborhood of Pittsburgh, Pennsylvania (Hill District). We estimate the effects of \468 million additional public–private investments that Hill District received compared with a demographically similar neighborhood on sales prices, rental prices, and crime. We find large, statistically significant impacts of these investments on residential sales prices, commercial sales prices, and on rental prices, and a marginally significant yet meaningful decline in nonviolent arrests. For each \10 million of public–private investment, we find a 0.95%, 2.7%, and 0.55% increase in residential sales prices, commercial sales prices, and rental prices, respectively. Given the accumulated difference over 16 years of \468 million in these investments across the two neighborhoods, the percentage increases amount to large changes in prices over that time. Cities should anticipate the potential impacts of major neighborhood investment on low-income households, especially unsubsidized renters who most directly experience the brunt of rising rents.
Effects of opting‐out from federal nurse anesthetists’ supervision requirements on anesthesiologist work patterns

Matthew Baird, John M. O’Donnell, and Grant R. Martsolf

Health Services Research, Feb 2020

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Objective To estimate the impact of opting‐out from Medicare supervision requirements for certified registered nurse anesthetists (CRNAs) on anesthesiologists’ work patterns. Data Sources/Study Setting Secondary data from two national surveys of anesthesiologists and the Area Health Resource File. Study Design We use a matching difference‐in‐difference regression which contrasts the change in work patterns for anesthesiologists in California, which dropped supervision requirements, to the change for similar anesthesiologists. Key outcome variables include the number of weekly hours worked, the type of work done, and type of care delivery teams. Data Collection/Extraction Methods Self‐reported national survey data drawn from members of the American Society of Anesthesiologists. Principal Findings Anesthesiologists in California saw no change in time spent working or time spent supervising CRNAs. There was a decrease in direct care clinical work hours along with a shift in working more in intraoperative care, a decrease in postoperative care, and an increase in the percentage of cases supervising residents. Conclusions Anesthesiologists had small but real responses to California’s decisions to opt‐out of the physician supervision requirement for CRNAs, doing more work in intraoperative care and less outside of the operating room. Total hours worked saw no change.
Variation in improvement among schools in the intensive partnerships for effective teaching

Alice Huguet, Deborah J. Holtzman, Abby Robyn, and 8 more authors

RAND Report, Sep 2020

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The Bill & Melinda Gates Foundation, along with researchers from RAND and the American Institutes for Research, speculated that there were lessons to be learned from variation among schools within the Intensive Partnerships for Effective Teaching initiative sites because some schools had improved more than others. They conducted a qualitative study and a survey study to investigate factors that might be associated with positive student outcomes.
Education, employment, and wages in the Appalachia region: Final report (2020)

Matthew D. Baird, Gerald P. Hunter, Nathaniel Edenfield, and 2 more authors

RAND Report, Apr 2020

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The authors examine indicators of education and labor markets in the Appalachia Partnership Initiative (API) region, with a focus on science, technology, engineering, and mathematics, and on the extraction industry. The authors look at how the indicators have changed over time, tighten some of their analysis specifically to the API region, and introduce new measures, such as participation in career and technical education.

2019

Translating standardized effects of education programs into more interpretable metrics

Matthew D. Baird, and John F. Pane

Educational Researcher, May 2019

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Evaluators report effects of education initiatives as standardized effect sizes, a scale that has merits but obscures interpretation of the effects’ practical importance. Consequently, educators and policymakers seek more readily interpretable translations of evaluation results. One popular metric is the number of years of learning necessary to induce the effect. We compare years of learning to three other translation options: benchmarking against other effect sizes, converting to percentile growth, and estimating the probability of scoring above a proficiency threshold. After enumerating the desirable properties of translations, we examine each option’s strengths and weaknesses. We conclude that years of learning performs worst, and percentile gains performs best, making it our recommended choice for more interpretable translations of standardized effects.
Relationship between state policy and anesthesia provider supply in rural communities

Grant R. Martsolf, Matthew Baird, Catherine C. Cohen, and 1 more author

Medical Care, May 2019

Publisher: LWW

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Background: There is a significant geographic variation in anesthesia provider supply. Lower supply in rural communities raises concerns about access to procedures that require anesthesia in rural areas. State policies related to certified registered nurse anesthetist (CRNA) practice may help to alleviate rural supply concerns. Objectives: To estimate the association between state CRNA policy and anesthesia provider supply especially in rural communities. Research Design: Repeated cross-sectional design using ordinary least squares and 2-stage least squares regressions. Subjects: All counties in the United States from 2010 to 2015. Measures: Dependent variables include anesthesia provider counts per 100,000 people, calculated separately for anesthesiologists, CRNAs, and their sum. Key variables of interest include state-level CRNA policy based on scope of practice (SOP) regulations and Medicare opt-out status. Results: Opt-out status and less restrictive SOP regulations were consistently correlated with a greater supply of CRNAs, especially in rural counties. Furthermore, we found that anesthesiologists and CRNAs tend to be complements to each other, but less restrictive SOP and opt-out status tend to weaken the importance of this relationship. Conclusions: State regulations may lead to increased supply of CRNAs in rural communities. However, the design of our study makes causality difficult to assert. So, it is also possible that states set CRNA policy as a response to counts of anesthesia providers in rural areas. Furthermore, given supply of anesthesiologists and CRNAs are complementary to one another, improving access to anesthesia services may require addressing issues pertaining to the supply of all anesthesia provider types.
Effectiveness of screened, demand-driven job training programs for disadvantaged workers: An evaluation of the New Orleans Career Pathway training

Matthew D. Baird, John Engberg, Gabriella C. Gonzalez, and 3 more authors

RAND Report, Oct 2019

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Lower-skilled workers face a shrinking pool of employment opportunities. To combat this, the city of New Orleans developed a job training program that helped these individuals train for and find skilled jobs in particular industries. The authors of this report examine that program’s implementation and effectiveness and perform a cost-benefit analysis. Findings include improved wage growth and a positive return on investment.
Raising the bar for graduation pathways to college and work: Early signals on how Louisiana’s education policy strategies are affecting college and career readiness

Shelly Culbertson, Matthew D. Baird, Sophie Meyers, and 1 more author

RAND Report, Jun 2019

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Since 2012, Louisiana has been developing policies to improve student outcomes in the areas of early childhood education, K–12 academics, teacher preparation, and graduation pathways. This report, part of a four-part series on the implementation and outcomes of these reforms, focuses on Louisiana’s implementation of high school graduation pathways and associated efforts to improve college readiness, career readiness, and access to financial aid.
Raising the bar for K–12 academics: Early signals on how Louisiana’s education policy strategies are working for schools, teachers, and students

Julia H. Kaufman, Elizabeth D. Steiner, and Matthew D. Baird

RAND Report, Jun 2019

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Since 2012, Louisiana has been developing policies to improve student outcomes in the areas of early childhood education, K–12 academics, teacher preparation, and graduation pathways. This report, part of a four-part series on the implementation and outcomes of these reforms, focuses on Louisiana’s strategies to support and improve K–12 academics.
Principal Pipelines: A feasible, affordable, and effective way for districts to improve schools

Susan M. Gates, Matthew D. Baird, Benjamin K. Master, and 1 more author

RAND Report, Apr 2019

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Through its Principal Pipeline Initiative (PPI), The Wallace Foundation provided funding and technical assistance to support six large school districts in their efforts to put in place systematic processes for the strategic management of school leaders. This report describes the implementation of the PPI and its effects on student achievement, other school outcomes, and principal retention.
Preparing school leaders for success: Evaluation of New Leaders’ Aspiring Principals program, 2012–2017

Susan M. Gates, Matthew D. Baird, Christopher Joseph Doss, and 6 more authors

RAND Report, Feb 2019

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To assess the relationship between New Leaders’ Aspiring Principals program and school and student outcomes, this report compares New Leaders principals with other new principals in the same district, analyzing student achievement, program-graduate placement and retention, and satisfaction with the Aspiring Principals program.

2018

Estimating associations between medical home adoption, utilization, and quality: a comparison of evaluation approaches

Grant R. Martsolf, Ryan Kandrack, Matthew Baird, and 1 more author

Medical Care, Jan 2018

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Improving teaching effectiveness: Final report: The Intensive Partnerships for Effective Teaching through 2015–2016

Brian M. Stecher, Deborah J. Holtzman, Michael S. Garet, and 12 more authors

RAND Report, Jun 2018

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The Intensive Partnerships for Effective Teaching initiative was a multiyear effort to dramatically improve student outcomes by increasing students’ access to effective teaching. Researchers from the RAND Corporation and the American Institutes for Research conducted a six-year evaluation of the initiative, documenting the policies and practices each site enacted and their effects on student outcomes. This is the final evaluation report.

2017

Labor supply estimation biases from disregarding nonwage benefits

Matthew D. Baird

Economic Inquiry, Apr 2017

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Labor supply models and research underpinned by labor supply decisions often assume that workers’ choices are functions of wage and wage offers. However, the literature shows evidence that such decisions at least partly depend on nonwage benefits encompassed in jobs and occupations. In this paper, I develop and estimate a stochastic dynamic model of occupation and job choice, where nonwage benefits are directly incorporated into the decision alongside wages (a full model). Nested within the full model is a wage model, which represents the common practice in the literature of basing selection solely on wages and disregarding nonwage benefits. I separately estimate the full model and the nested wage model to compare the implications (biases) of omitting nonwage benefits. I compare the two models’ estimates of elasticities and an inequality reduction intervention policy. I find that disregarding nonwage benefits generally causes biases. There are cases when the two models predict very similar outcomes and have close estimates, such as in occupation‐specific elasticities and job transition elasticities. But these special cases are products of canceling biases. In most cases, ignoring nonwage benefits will bias estimates by overestimating the importance of wage in the selection process and by disregarding changes in relative prices between wage and nonwage benefits.
Postsecondary education and STEM employment in the United States: An analysis of national trends with a focus on the natural gas and oil industry

Matthew D. Baird, Robert Bozick, and Mark A. Harris

RAND Report, Dec 2017

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This report aims to contribute new knowledge to understanding the role that postsecondary education plays in meeting the increasing demands of the science, technology, engineering, and mathematics (STEM) workforce. The study indicates that the receipt of a bachelor’s degree in a STEM field and the attainment of a certification or license (in any field) are important educational milestones that support success in the STEM labor market.
The RAND American Life Panel: Technical description

Michael S. Pollard, and Matthew D. Baird

RAND Report, Jul 2017

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The RAND American Life Panel is an Internet panel that has been recruited primarily using probability sample methods and consists of approximately 6,000 active respondents ages 18 and older. This document provides a detailed description of the RAND American Life Panel methodology related to sample recruitment, sample retention, and weighting and should be of use for users of the panel and as general reference material.
Informing progress: Insights on personalized learning implementation and effects

John F. Pane, Elizabeth D. Steiner, Matthew D. Baird, and 2 more authors

RAND Report, Jul 2017

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This report describes the concept and implementation of personalized learning (instruction that is focused on meeting students’ individual learning needs while incorporating their interests and preferences), along with some of the challenges and facilitators, and considers achievement findings in a small sample of schools.
The effects of travel and tourism on California’s economy: A labor market–focused analysis

Matthew D. Baird, Edward G. Keating, Olena Bogdan, and 1 more author

RAND Report, Jun 2017

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In California, travel/tourism employs a diverse workforce and contributes meaningfully to the state’s economy. This report evaluates the role of travel/tourism in the state’s economy. It uses data on the state’s tourism and labor force to provide insight about tourism workers in California and how their careers evolve and should be of interest to policymakers and researchers interested in economic development issues and career pathways.
Are current military education benefits efficient and effective for the services?

Jennie W. Wenger, Trey Miller, Matthew D. Baird, and 6 more authors

RAND Report, Jun 2017

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A primary purpose of military education benefits is to assist service members’ transitions back to civilian life, but the benefits likely have implications for recruiting and retention as well. This research takes a mixed-methods approach to examine the effects of education benefit programs on recruiting and retention–related outcomes, and to assess how the two largest education benefits may work together.

2016

Gains from joint cross validation bandwidth selection for derivatives of conditional multidimensional densities

Matthew Baird

Journal of Statistical Computation and Simulation, Mar 2016

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This paper studies bandwidth selection for kernel estimation of derivatives of multidimensional conditional densities, a non-parametric realm unexplored in the literature. This paper extends Baird [Cross validation bandwidth selection for derivatives of multidimensional densities. RAND Working Paper series, WR-1060; 2014] in its examination of conditional multivariate densities, derives and presents criteria for arbitrary kernel order and density dimension, shows consistency of the estimators, and investigates a minimization criterion which jointly estimates numerator and denominator bandwidths. I conduct a Monte Carlo simulation study for various orders of kernels in the Gaussian family and compare the new cross validation criterion with those implied by Baird [Cross validation bandwidth selection for derivatives of multidimensional densities. RAND Working Paper series, WR-1060; 2014]. The paper finds that higher order kernels become increasingly important as the dimension of the distribution increases. I find that the cross validation criterion developed in this paper that jointly estimates the derivative of the joint density (numerator) and the marginal density (denominator) does orders of magnitude better than criteria that estimate the bandwidths separately. I further find that using the infinite order Dirichlet kernel tends to have the best results.
Access to dental providers in Pennsylvania: Exploration of the county-level distribution of dental providers and populations in 2013

Matthew D. Baird, Michelle K. Baird, and Joseph Vesely

RAND Report, Jan 2016

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This report examines an important factor in the ability to access dental care: the distribution and availability of dental health providers. The authors assess these characteristics of providers across the counties of Pennsylvania, primarily using data from the 2013 Survey of Dentists and Dental Hygienists administered by the Pennsylvania Department of Health.
Improving teaching effectiveness: Access to effective teaching: The Intensive Partnerships for Effective Teaching through 2013–2014

Matthew D. Baird, John Engberg, Gerald P. Hunter, and 1 more author

RAND Report, Jun 2016

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This report attends to the distribution of effective teachers within and across schools in the Intensive Partnership sites. The authors examine trends in the distribution of effective teachers between low-income minority (LIM) students and other students and what mechanisms might explain changes in LIM students’ access to effective teaching.
Wages, employment, and STEM education in Ohio, Pennsylvania, and West Virginia: Report No. 1 (2016)

Gabriella C. Gonzalez, Kyle Siler-Evans, Gerald P. Hunter, and 1 more author

RAND Report, Mar 2016

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This first of five annual reports focuses on employment and wages in energy and advanced manufacturing–related industries and on science, technology, engineering, and mathematics (STEM) education indicators in the Appalachia Partnership Initiative (API) region. These reports will inform the regional stakeholder community about localities with greater demand for STEM careers and guide API investments and collaborative work.

2015

Regional and gender differences and trends in the anesthesiologist workforce

Matthew Baird, Lindsay Daugherty, Krishna B Kumar, and 1 more author

Anesthesiology, Nov 2015

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Background Concerns have long existed about potential shortages in the anesthesiologist workforce. In addition, many changes have occurred in the economy, demographics, and the healthcare sector in the last few years, which may impact the workforce. The authors documented workforce trends by region of the United States and gender, trends that may have implications for the supply and demand of anesthesiologists. Methods The authors conducted a national survey of American Society of Anesthesiologists members (accounting for \textgreater80% of all practicing anesthesiologists in the United States) in 2007 and repeated it in 2013. The authors used logistic regression analysis and Seemingly Unrelated Regression to test across several indicators under an overarching hypothesis. Results Anesthesiologists in Western states had markedly different patterns of practice relative to anesthesiologists in other regions in 2007 and 2013, including differences in employer type, the composition of anesthesia teams, and the time spent on monitored anesthesia care. The number and proportion of female anesthesiologists in the workforce increased between 2007 and 2013, and females differed from males in employment arrangements, compensation, and work hours. Conclusions Regional differences remained stable during this time period although the reasons for these differences are speculative. Similarly, how and whether the gender difference in work hours and shift to younger anesthesiologists during this period will impact workforce needs is uncertain.
Continued progress: Promising evidence on personalized learning

John F. Pane, Elizabeth D. Steiner, Matthew D. Baird, and 1 more author

RAND Report, Nov 2015

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This report examines achievement in 62 schools pursuing a variety of personalized learning practices, and implementation details in 32 of the schools. It uses data from site visits, interviews, and surveys to create a broad picture of efforts to implement personalized learning and the perceptions of teachers and students. Achievement data for personalized learning students are compared to a matched group of students attending other schools.

2014

The anesthesiologist workforce in 2013: A final briefing to the American Society of Anesthesiologists

Matthew D. Baird, Lindsay Daugherty, Krishna B. Kumar, and 1 more author

RAND Report, May 2014

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Important changes are taking place in the health care sector that have implications for future supply and demand of anesthesiologists. To determine the implications for the anesthesiologist workforce, RAND Corporation researchers conducted a national survey of American Society of Anesthesiologists members in 2013. This report documents findings by region, gender, and other provider and facility characteristics.
Preparing principals to raise student achievement: Implementation and effects of the New Leaders program in ten districts

Susan M. Gates, Laura S. Hamilton, Paco Martorell, and 9 more authors

RAND Report, May 2014

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New Leaders is a nonprofit organization that partners with school districts to prepare and support principals. This report describes how the New Leaders program was implemented in partner districts, and it provides evidence of the effect that New Leaders has on student achievement.