I am an Economist at the Federal Trade Commission (FTC). My research is centered on how women make decisions about work and family and how policy impacts these decisions. My work lies at the intersection of labor economics, health economics, family demography, and policy.
I received my PhD in Policy Analysis and Management with a minor in Demography from Cornell University in 2020. I received an Honors Bachelor of Arts in Economics and Philosophy, Politics, and the Public from Xavier University in Cincinnati, OH in 2014.
PhD in Policy Analysis and Management, 2020
MS in Policy Analysis and Management, 2018
Honors BA in Economics and Philosophy, Politics, and the Public, 2014
Using the universe of U.S. births and a difference-in-differences strategy, we find that access to leave increases fertility by 2.8 percent, driven by higher order births to mothers in their 30s as well as Hispanic mothers and those with a high school degree.
We develop a working definition and provide data on the demographic and labor market composition of these workers. We find that the broader group of essential workers comprises a large share of the labor force and tends to mirror its demographic and labor market characteristics. In contrast, the narrower category of frontline workers is, on average, less educated, has lower wages, and has a higher representation of men, disadvantaged minorities, especially Hispanics, and immigrants.
Using data from the 2003–2017 waves of the American Time Use Survey (ATUS), we find that first-generation immigrants, both women and men, from source countries with more gender equality (as measured by the World Economic Forum’s Global Gender Gap Index) allocate tasks more equally, while those from less gender equal source countries allocate tasks more traditionally.
PDFs available upon request
Improved labor market opportunities for women increase returns to human capital investments and the opportunity cost of marriage and childbearing. This paper uses 1940-1980 U.S. Census data to examine whether equal pay laws designed to reduce sex discrimination influenced women’s educational, marital, and fertility decisions. We exploit variation in state-level equal pay laws in place prior to the federal Equal Pay and Civil Rights Acts to compare outcomes among young women who came of age in states with sex discrimination laws in place to those of similar women in states without such laws. Our findings indicate that women who grew up in states with equal pay laws are more likely to attend and complete college than their counterparts in other states. They are also less likely to marry and have children, and more likely to delay marriage and childbearing if they do become wives and mothers. To our knowledge, this is the first paper to examine the impact of antidiscrimination laws on women’s educational, marital, and fertility choices, and we find that antidiscrimination laws have impacts for women that extend beyond the labor market.
Currently, 37 states in the US have parental involvement in abortion laws. Previous research on risky sexual behavior has lumped the two types of parental involvement laws (notification and consent) into one treatment variable with mixed findings. This study separates them to estimate the effect of each law on risky sexual behavior among teens using data from the 2001-2015 Youth Risky Behavior Surveillance Survey. Counter to the theory that the more burdensome law would have a larger impact on minors’ behavior, notification laws have a larger impact on sexual activity, an effect that increases over time, though there is no evidence of a significant impact on contraception use. Consent laws have impacts opposite of the hypothesized direction on both recent sexual activity and contraception use. Given that each law is enacted individually, knowing the impact of each policy may shape future legislation.
Encouraging women to pursue degrees and employment in STEM (science, technology, engineering, and mathematics) fields is a key component of government and industry efforts to reduce gender inequality. Yet women’s representation in computer science occupations has declined since the 1980s. Research has found that family factors – marriage and parenthood – are important drivers of gender imbalance in STEM careers (Cech and Blair-Loy 2019). We use data from the 2009-2018 American Community Survey to examine factors contributing to gender differences in earnings among those working full-time in computer science. The results show a persistent gender wage gap in computer science, even after controlling for human capital and family attributes. Our findings challenge explanations that family factors account for gender disparities in earnings in computer science. The wage gap emerges well before the prime family formation years. We find no evidence of a marriage penalty for women working in computer science, though men earn a considerable marriage premium. The motherhood penalty is limited to women with infants; mothers of older children earn a wage premium, though it is significantly smaller than the fatherhood bonus. Differential returns to attributes – often attributed to discrimination – account for three-quarters of the gender wage gap.
A virtual Economics pro-seminar for grad students and early career Economics and Econ-adjacant researchers. Join the email list: https://bit.ly/econ_prosem-email-signup
RSVP link: https://bit.ly/econ_prosem-09-06-22
RSVP link: https://bit.ly/econ_prosem-09-20-22
RSVP link: https://bit.ly/econ_prosem-10-04-22
RSVP link: https://bit.ly/econ_prosem-10-18-22
RSVP link: https://bit.ly/econ_prosem-11-01-22
RSVP link: https://bit.ly/econ_prosem-11-15-22
JMCs, sign up here by 11/1: https://bit.ly/mock_interview-JMCsignup
Volunteer to conduct by 11/15: https://bit.ly/mock-interview-volunteer
Average instructor rating: 3.8/5
TA In-person: Fall 2016
TA In-person: Spring 2016, 2019*
TA Start in person, moved online: Spring 2020*
TA including prepping and teaching Stata lab: Fall 2019*
*Full evaluations available upon request
“Pamela was concise in her explanations of class material and her vast knowledge on the subject matter allowed her to make helpful real-world comparisons. By connecting the abstract concepts from class to more tangible examples, she made the material easier to understand.” - PAM 2030, Spring 2019 Student
“Ms. Meyerhofer was very knowledgable about the subject and it was evident that she was interested in being a professor, her availability was super helpful and great.” - PAM 2030, Spring 2020 Student
“Pamela is very energetic and cares a lot about being a TA. You can tell she is excited to teach us and is passionate about statistics. I had Pamela last semester as well and she was equally as passionate about that class as well. She wants us to succeed in the course.” - PAM 2101 Student