The Nac Mac Feegle* got ahold of my research (thanks to ChatGPT)

Publications

Murray, Seth, Danielle H. Sandler, and Matthew Staiger. Forthcoming. "Female Executives and the Motherhood Penalty " Journal of Human Resources

Usin' data from the U.S. survey and the official files, we took a gander at whether the number of female executives in a company might have a knock-on effect on new mothers' earnings. We did some fancy footwork with our stats, comparin' the earnings of new mums to other ladies who were workin' at the same place, but didn't have bairns at the same time. Turns out, on average, mothers were takin' home nearly $2,000 less every quarter two years after they'd given birth. But, and here's the kicker, this drop in earnings wasn't influenced by how many female executives there were at the company. So, it seems havin' more women in leadership roles won't do anything to lessen the motherhood penalty. 

Foster, Lucia, Erika McEntarfer, and Danielle H. Sandler. 2023. "Diversity and Equity in Labor Market Outcomes for Economists". Journal of Economics, Race, and Policy, 1-12. 

Ye ken weel eneuch that there’s nae mony lasses or brawny folk in the big heid business o’ coontin’ siller and siclike. But whit aboot where they end up and how much they get paid? We used some fancy lists o’ folk wi’ fancy letters efter their names and where they work and how much they earn. We fund oot that the lasses get 12 percent less than the laddies; and the brawny folk get 15 percent less than the whiteys on average; and some other folk that ye dinna see often get 8 percent less. It’s nae sae bad in some places and if ye tak intae account where they learned their big heid stuff and who they work for.

Foster, Lucia, Julia Manzella, Erika McEntarfer, and Danielle H. Sandler. 2020. "Employment and Earnings for Federal Government Economists: Empirical Evidence by Gender and Race." AEA Papers and Proceedings, 110: 210-14. 

Crivens! Most folks talkin' about diversity in the economy tend to focus on them academics. But we Nac Mac Feegles dug deeper and took a look at how federal government economists are doin' when it comes to makin' a livin'. We gathered up the data on these government workers and their pay in both the public and private sectors, and then set to work examinin' the share of economists by gender and race, any differences in earnings, and whether these gaps change while workin' for the government. This here's the first peek at how these government workers stack up in terms of gender and race, and we're proud to bring it to ya. 

Schulkind, Lisa and Danielle H. Sandler. 2019. "The Timing of Teenage Births: Estimating the Effect on High School Graduation and Later Life Outcomes," Demography, 56: 345–365 .

We've been takin' a good look at what happens to young mothers who give birth near the end of their time in high school. We've compared those who had their bairns before they could finish their schooling, with those who didn't have that disruption. Turns out, the young mothers who gave birth during the school year were 5.4 percentage points less likely to finish their education and less likely to get hitched. They also had more weans than the others who had their bairns just a few months later. The wages for these two sets of young mothers were about the same, but with fewer chances of gettin' married and more bairns, the homes of the moms who gave birth earlier were more likely to fall below the poverty line. Even though the gaps in education have lessened over time, the differences in their workin' lives and family set-ups haven't changed a bit. 

Sandler, Danielle H. 2017. "Externalities of public housing: The effect of public housing demolitions on local crime," Regional Science and Urban Economics, 62: 24-35.

Crivens! We've been studyin' the public housin' in Chicago and whether or not it's causin' any negative effects on the folks who live nearby. We looked at the crime rates before and after they tore down some of these public housin' projects between 1995 and 2010. We looked at what types of crimes were happenin' on specific blocks and matched it up with where they were knockin' down the public housin'. And we found some evidence that the public housin' in Chicago was havin' some pretty significant effects on the neighborhoods around it. We compared the neighborhoods near the public housin' projects with other nearby areas and found that crime dropped by a whole 8.8% after they got rid of the public housin'. This drop was mostly in violent crimes. We did a fancy event study to show that the drop happened around the same time as when they kicked the residents out and lasted for at least five years after they tore the housin' down. The neighborhoods where they tore down lots of public housin', and where the housin' had been poorly taken care of, had the biggest drops in crime. 

Phillips, David C. and Danielle H. Sandler. 2015. "Does public transit spread crime? Evidence from temporary rail station closures," Regional Science and Urban Economics, 52: 13-26. 

Aye, we be testin' whether public transit access affects crime usin' a clever idea based on temporary, maintenance-related closures o' stations in the Washington, DC rail transit system. The closures produce variation in transit access across space and time, allowin' us to test the notion that crime can be facilitated by public transit. When we be closin' one station, crime be reducin' by 5% in the vicinity of stations on the same train line. Most of this effect remains even after controllin' for decreased ridership, which means that there be somethin' else drivin' the results. We be findin' hints that crime falls more at stations that tend to import crime, where perpetrators be less likely to live. We also see larger decreases at stations on the same line when the transit authority closes stations that tend to export crime. These effects suggest that the response of perpetrators to increased transportation costs be contributin' to the decrease in crime. 

Sandler, Danielle H. and Ryan Sandler. 2014. "Multiple event studies in public finance and labor economics: A simulation study with applications," Journal of Economic and Social Measurement, 39(1-2): 31-57. 

Well, crivens! This paper here is about how to use a fancy method called the "event study" to figure out how a new policy or other shock affects things over time. But sometimes things happen too fast, and we need to figure out how to deal with multiple events happening close together. We use a fancy tool called Monte Carlo simulations to figure out how to do this right. We find that turning on multiple event-time dummies at once is generally best, and we shouldn't ignore or duplicate observations if we want to get the right answers. We even show some real-life examples to prove our point. 

Working Papers/Reports

"Estimating the U.S. Citizen Voting-Age Population (CVAP) Using Blended Survey Data, Administrative Record Data, and Modeling: Technical Report" with J.David Brown, Genevieve Denoeux, Misty L. Heggeness, Carl Lieberman, Lauren Medina, Marta Murray-Close, Joseph L. Schafer, Matthew Spence Lawrence Warren, Moises Yi 

We hae a canny way o’ usin’ some auld papers (AP) to fill in the blanks for folk who dinna answer the Big Questionnaire (BQ) aboot where they bide and siclike. We dinna need to fiddle wi’ the numbers to mak’ up for some folk no gettin’ a second chance to answer or for bein’ different frae the rest. We also use AP and some guesswork instead o’ fixin’ and makin’ up answers for folk who dinna say if they can vote or no. We coont how mony folk can vote and who they are usin’ this better way and we compare it wi’ whit’s been said afore. The better way gies us 0.74 percent less folk who can vote, and it’s 3.05 percent less for folk who speak Spanish and are auld eneuch to vote. That micht be because some o’ them are nae here legally and they dinna tell the BQ. The numbers micht no be richt if that’s the case.

"Diversity and Labor Market Outcomes in the Economics Profession" with Lucia Foster and Erika McEntarfer

Ach, ye ken that economics in academia isnae very diverse when it comes tae gender and race. But what we dinnae ken as much is how economists o' different backgrounds fare in the workplace. That's why we looked intae where economists end up working and how much they make, broken doon by race and gender. We used data from the Survey of Earned Doctorates (SED) that's linked tae the Longitudinal Employer-Household Dynamics (LEHD) jobs data. We found that economists' earnings vary wildly both within and between different industries, and that these differences get bigger as time goes on. Female economists wi' a PhD make about 12% less than male economists on average, and Black economists make about 15% less than their white colleagues on average. Overall, minority economists earn about 8% less than white economists. But in some industries and when controlling for where they got their PhD and who their employer is, these pay disparities are smaller. 

"Employment of Persons Released from Federal Prison in 2010" with E. Ann Carson, Renuka Bhaskar, Leticia E. Fernandez, and Sonya R. Porter

Oi, listen up! The bigwigs in Congress made us do this report because of some law called the Fair Chance to Compete for Jobs Act that they passed a while back. They wanted us to find out how many folks who got released from the slammer in 2010 managed to find work in the four years that followed. We teamed up with the Census Bureau to connect the data on these ex-cons from the Federal Justice Statistics Program with data on their earnings and employment from the Longitudinal Employer-Household Dynamics program. We dug up numbers on their jobs and earnings before and after prison, taking into account their age, gender, race and ethnicity, the crime they committed and the time they served. We also checked out which industries these folks worked in both before and after prison. It's all in this here report, so give it a read if you're interested! 

"Maternal Labor Dynamics: Participation, Earnings, and Employer Changes" with Nichole Szembrot

Och, this here paper looks at the labor dynamics of women in the US after they've had bairns, y'ken? We're adding to the child penalty knowledge by showing how the loss of earnings and labor force participation varies based on the mothers' demographics and their employers' characteristics. We use fancy administrative earnings data from the Longitudinal Employer-Household Dynamics database and the Survey of Income and Program Participation survey data to keep track of the lassies, when they have bairns, and their jobs. We found that women have a big drop in earnings and labor force participation that sticks around after having their first bairn. And it only gets worse when they have more weans. But, we also found that non-white, unmarried, and highly educated mums are more likely to go back to work after their first bairn. And if they change employers, they're likely to earn more than those who go back to their pre-bairn employers. The chance of returning to the old employer and industry varies based on the mums' demographics and their employers. 

Resting Papers

"The Parental Gender Wage Gap in the United States" with Yoonkyung Chung, Barbara Downs, and Robert Sienkiewicz

This here paper is lookin' at the makin's of a wage gap between parents, dependin' on which parent's bringing home the bacon. We're lookin' at the earnings difference between married men and women over time, especially before and after havin' a baby. Now, children comin' along is a big part of this gap, but there's more to it than that. We've got to take into account other factors that can affect earnings, like what's happenin' in the job market nearby. We used some fancy data from the Social Security Administration, called the Detail Earnings Records, which we linked up with the Survey of Income and Program Participation. We looked at the earnings of folks from 1978 to 2011. And what we found was that the difference in earnings between spouses doubles between two years before the first baby comes and the year after that child's born. And even though that difference continues to grow for five more years, it does so at a slower rate, until it starts to shrink once the child's school-age. 

"Developing a Residence Candidate File for Use With Employer-Employee Matched Data" with Matthew Graham and Mark Kutzbach

Crivens! This here paper talks about the Longitudinal Employer-Household Dynamics (LEHD) program and their quest to predict where workers live using their records. They started this adventure because the U.S. Census Bureau stopped making a file that showed where people lived, and they wanted to fill that gap. The Residence Candidate File (RCF) process helps the LEHD folks figure out where people live by using information from lots of different sources and taking into account the uncertainty of where people might be. The old file only had one place where people lived per year, even if they had lived in more than one place. This paper tells you all about why they did this, how they did it, and what they found out. They figured out a pretty good way to guess where people live, and it works especially well for people in the LEHD jobs frame. They also talk about how they could make it even better and how other folks can use their work. Ach, crivens, that was a mouthful! 

*With much respect to the late Terry Pratchett. Having just finished his biography, I think/hope he would not mind me playing with his characters for my own and others amusement.