Michelle Budig

Professor

Department of Sociology, University of Massachusetts Amherst

NLS user since 1996

Citations
  • Budig, Michelle J. and Paula England. 2001. "The Wage Penalty for Motherhood." American Sociological Review 66:204-225.
  • Budig, Michelle J. 2002. "Male Advantage and the Gender Composition of Jobs: Who Rides the Glass Escalator?" Social Problems 49(2):258-277.
  • Budig, Michelle J. 2006. "Gender, Self-Employment, and Earnings: The Interlocking Structures of Family and Professional Status." Gender & Society 20(6):725-753.
  • Budig, Michelle J. 2006. "Intersections on the Road to Self-Employment: Gender, Family, and Occupational Class." Social Forces 84(4):2223-2239.
  • Hodges, Melissa and Michelle J. Budig. 2010. "Who Gets the Daddy Bonus? Markers of Hegemonic Masculinity and the Impact of First-time Fatherhood on Men's Earnings." Gender & Society 24(6):717-745.
  • Budig, Michelle J. and Melissa Hodges. 2010. "Differences in Disadvantage: How the Wage Penalty for Motherhood Varies Across Women's Earnings Distribution." American Sociological Review 75(5)705-728.
What I learned from NLS data

The excellent longitudinal labor market, workplace characteristics, fertility, and marriage data provided by the NLSY allowed me to explore the relationship between fertility, employment and earnings for women and men; the impact of care work employment on wages; the wage advantages experienced by male occupational tokens; and the interrelationships between self-employment, gender, family structure and and class. Perhaps most importantly, the NLSY data have allowed me to examine the effects of parenthood on earnings of men and women. This research revealed the wage penalty for motherhood, or how much women's earnings decline for each additional child she has. Moreover, it allowed me to discover that this penalty accrues less to women who command higher wages. Using the NLSY, I also examined the fatherhood wage bonus, and how it accrues more to men privileged by race, educational attainment, and upper level job placement. Understanding dimensions of gender inequality, particularly in the ways that American women and men combine paid and unpaid work and its impact on family economies, have been deeply informed by NLS data.

Why I chose NLS data

The NLS provides the highest quality longitudinal data on the educational, labor market, family formation, and workplace characteristics available in the U.S. The high retention rates over time, combined with the oversampling of minority racial and ethnic groups, makes the NLSY data an amazing resource for understanding how processes of racial/ethnic, gender, and class inequality unfold across the lifecourse.