Labor Markets | César Garro-Marín

Rooted Decisions: How Birthplace Shapes Women's Work

Thu, 04 Jun 2026 00:00:00 +0000

When we ask why women work more in some places than others, the instinct is to look at present-day conditions: available jobs, wages, childcare access, cultural attitudes today. These matter. But a growing body of research suggests that where a person grew up—and what they observed around them as a child—can be just as consequential as where they live now. Research on second-generation immigrants, for instance, finds that women’s work choices in their new country are shaped by the cultural norms of the country their parents left behind (Fernandez and Fogli, 2009).

This paper puts that idea to a precise test within a single country, using Indonesian data. Indonesia is a useful setting: it is a large, diverse country with 22 percentage points of spread between high- and low-employment districts, and a history of internal migration that makes it possible to separate childhood environment from adult environment.

The identification challenge

Studying the effect of childhood exposure is harder than it sounds. A woman living in a high-employment city today might work more simply because more jobs are available where she is—not because of where she grew up. To isolate the childhood effect, the paper compares women who moved away from their birthplace at different ages but ended up living in the same location as adults (Chetty and Hendren, 2018).

Women who left as teenagers had more childhood exposure to their origin’s labor market environment; women who left early in childhood had less. By comparing these groups—all observed in the same current location—the study separates where you grew up from where you are now.

The critical window: ages 6 to 14

Not all childhood years matter equally. The effects of early exposure to high-female-employment places are strongest when that exposure happens between ages 6 and 14—roughly primary school through early secondary. This is the period when children are most actively learning social roles and forming expectations about what the adults around them do. Evidence from psychology and economics identifies this as a key window for preference formation: adolescents are mature enough to form their own opinions but still receptive to external influences (Dhar et al., 2022; Olivetti et al., 2020).

Exposure concentrated before age 6, or primarily during adulthood, shows weaker effects. The formative years of late childhood and early adolescence appear to be when gender norms around work take deepest root.

How large is the effect?

Comparing a woman who grew up in a district at the 75th percentile of female employment to one from a district at the 25th percentile—a gap of 22 percentage points in local female employment rates—the paper finds that the first woman is about 5 percentage points more likely to work as an adult. This is a meaningful difference: the average female employment rate in Indonesia is around 42%, so the effect represents a roughly 12% increase.

Crucially, this effect holds even after women move to a different location. It reflects something internalized, not just a response to local conditions. Taken together, the patterns suggest that roughly 23% of the spatial inequality in women’s employment across Indonesia is transmitted from one generation to the next through childhood exposure to local gender norms.

A substantial share of today’s gender gaps in employment are, in part, yesterday’s gender gaps carried forward.

The evidence points to internalized gender norms—not skills or formal education—as the main channel (Jayachandran, 2021). The effects are not explained by differences in schooling or marriage patterns: high-FLFP areas actually have worse schooling completion rates, and women with more birthplace exposure do not choose husbands with different characteristics. The pattern is consistent with women who grew up seeing other women work updating their expectations about what women do—and those updated expectations staying with them.

What this means

Gender policies today create multiplier effects tomorrow. Raising women’s employment in a place does not just help current workers—it changes the environment in which the next generation of girls grows up. Some of that effect will carry forward even if those girls later move elsewhere.
The 6–14 window is a high-leverage target. Interventions that shape gender norms—role models in schools, community programs, representations of working women—may be most effective when aimed at this age group, when norms appear most malleable.
Spatial gender gaps are partly self-reinforcing. Low-employment areas raise daughters who are less likely to work, which perpetuates the gap across generations even as individuals migrate. Closing the gap requires changing the social environment where girls grow up, not just expanding economic opportunities.
Skills programs alone may miss the mechanism. If the channel is norms rather than human capital, policies focused only on job training or education are targeting the wrong lever. Complementary investments in changing social expectations may be necessary.

References

Chetty, R and N Hendren. 2018. “The impacts of neighborhoods on intergenerational mobility I: Childhood exposure effects.” Quarterly Journal of Economics, 133(3): 1107–1162.
Dhar, D, T Jain, and S Jayachandran. 2022. “Reshaping Adolescents’ Gender Attitudes: Evidence from a School-Based Experiment in India.” American Economic Review, 112(3): 899–927.
Fernandez, R and A Fogli. 2009. “Culture: An empirical investigation of beliefs, work, and fertility.” American Economic Journal: Macroeconomics, 1(1): 146–177.
Jayachandran, S. 2021. “Social Norms as a Barrier to Women’s Employment in Developing Countries.” NBER Technical Report 3.
Olivetti, C, E Patacchini, and Y Zenou. 2020. “Mothers, Peers, and Gender-Role Identity.” Journal of the European Economic Association, 18(1): 266–301.

Status: Working paper

Learn more: Full Paper

Work Hours and Amenity Trade-offs

Wed, 03 Jun 2026 00:00:00 +0000

When you accept a job, you’re not just agreeing to a salary. You’re agreeing to a schedule, a commute, a set of expectations about your time, and a package of benefits. Some jobs pay well but demand long hours. Others offer lower hours but provide fewer perks. This trade-off seems familiar.

But what exactly are workers trading against what?

The standard story

The classic economic answer is clean: workers who value flexible hours are willing to accept lower pay to get them. Firms respond by offering lower wages in exchange for better working conditions. Workers sort into jobs that match their preferences, and the wage gap between demanding and flexible jobs reveals how much people value those perks.

This is the theory of compensating differentials (Rosen, 1986)—and it has shaped how economists and policymakers think about salaries and job characteristics for decades. For example, if workers accept lower wages in exchange for lower hours, salary differences across jobs partly reflect workers preferences.

But jobs don’t offer only one perk, they often package several of them together. Moreover, some perks are not offered when others are. For example, jobs with flexible hours often do not offer health insurance, or the ability to work from home.

When firms package multiple perks together, workers often trade lower hours for other benefits—not just for wages—and this reshapes how we should understand salary differences in the labour market.

The bundling problem

Think of a job as a package deal. A job with flexible hours might also come with the option to work from home but a smaller health insurance contribution. A high-paying job might come with long hours but generous paid leave. Workers don’t pick individual features, they choose from a menu of bundles.

In our paper, we develop a model that accounts for how firms combine amenities (perks) and how workers decide whether a bundle suits their preferences. The key insight is that whether you end up with the amenity mix you want depends not just on what you value, but on what bundles firms offer and how those bundles are put together.

Flexible hours don’t just cost you wages

Using data tracking 6,755 Americans from their teens through adulthood (Bureau of Labor Statistics, 2024), we find that:

American workers who value lower hours often must give up other amenities.
Shorter work hours are frequently bundled with fewer other benefits, such as less paid leave or health insurance.
The simple trade-off between wages and work hours that standard theory predicts is far less common than the trade-off between one amenity and another

Workers are not just choosing between money and work hours. They’re navigating a menu of bundles where getting one benefit often means giving up another.

Who ends up where, and the gender gap

These patterns matter especially for understanding why men and women end up in different jobs with different pay.

Women are more likely than men to value flexible hours, particularly those with caregiving responsibilities:

Women are more likely to end up in jobs with flexible hours—but these jobs also tend to bundle in fewer other benefits
As a result, women face a compounded disadvantage: lower wages and a thinner non-wage benefits package
Thus gender gap in total compensation—wages plus the full value of benefits—is wider than the gender wage gap alone suggests.

What this means

Wage statistics understate inequality. If men receive better non-wage benefits on top of higher wages, standard pay comparisons miss a significant share of the gap. Policies and audits that focus only on wages may give a misleadingly narrow picture.
Flexible work alone is not enough. The remaining gender gap in labour market outcomes is closely tied to how flexibility in hours is packaged alongside other benefits (Goldin, 2014). Expanding part-time or reduced-hour arrangements only helps if those arrangements don’t strip away other perks in the process.

References

Bureau of Labor Statistics, U.S. Department of Labor (2024), “National Longitudinal Survey of Youth 1997 cohort, 1997–2021 (rounds 1–20)”, produced and distributed by the Center for Human Resource Research (CHRR), The Ohio State University.
Goldin, C (2014), “A grand gender convergence: Its last chapter”, American Economic Review 104(4): 1091–1119.
Rosen, S (1986), “The theory of equalizing differences”, Handbook of Labor Economics 1: 641–692.

Co-authored with: Neil Thakral (Brown University) and Linh Tô (Boston University)

Published in: AEA Papers & Proceedings, Vol. 115, May 2025

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Do Elite Universities Overpay Their Faculty?

Fri, 20 Feb 2026 00:00:00 +0000

In most industries, some firms pay more than others—even for seemingly similar workers. Economists have shown that otherwise similar employees who move to higher-paying firms typically receive wage increases, while those moving to lower-paying firms experience comparable losses (Bagger and Lentz, 2019; Moscarini and Postel-Vinay, 2018; Haltiwanger et al., 2018, Abowd et al., 1999). These persistent differences across employers are often interpreted as firm wage effects or rents. These are firm-specific wage premiums captured by workers.

Universities appear to fit this pattern. There is a clear prestige hierarchy, and faculty at elite institutions earn higher salaries on average. But in our paper, we show that elite universities do not systematically pay more for the same faculty. Instead, they pay more because they hire more productive academics. In fact, we find very little evidence of any significant university pay premia in the US academic market.

Higher academic salaries reflect better faculty quality

As in other sectors, academic salaries are strongly correlated with institutional prestige. Faculty at top-ranked universities earn more on average, and these institutions have greater resources and visibility.

Higher salaries at these universities can result from firm-level pay premiums — paying higher salaries to all their faculty — or from hiring higher-quality faculty. To understand whether universities themselves pay more, we need to compare what the same faculty member would earn across institutions. We distinguish between these two stories using survey data from the Survey of Doctorate Recipients, which allows us to observe STEM faculty job and salary histories.

By following the same person across jobs, we can separate what the employer pays from what the employee is worth. If elite institutions pay genuine premiums, we would expect salaries to rise whenever someone moves to a more prestigious university—and fall whenever they move down.

We find that university-specific pay premiums explain very little of salary variation. Most of it comes down to individual faculty characteristics. In other words, elite universities do not pay a meaningful premium for identical academics. Even when comparing the most and least prestigious institutions, the implied salary differences—holding faculty quality constant—are modest, around 15%. Thus, the observed salary differences reflect who institutions hire.

Worker mobility in academia looks very different from other labor markets

Academic careers also exhibit mobility patterns that differ from the broader labor market. In most labor markets, workers tend to move up the job ladder, and moving down typically comes with a pay cut (Card et al., 2018). In academia, neither holds: moves up and down the prestige hierarchy are equally common, and salaries tend to increase after a move regardless of direction. Faculty moving to less prestigious institutions often receive substantial pay increases.

Why is academia different?

We argue that two key features distinguish academia from most labor markets:

High information about productivity Academic output (publications, citations, grants) is highly visible, allowing institutions to assess researchers’ quality early in their careers.
Scarce and irregular job openings
Departments hire infrequently and often in narrow fields, meaning that good matches are not always available when candidates enter the market.

These features lead to a labor market shaped by mismatch and gradual improvement. Initial placements are often imperfect—the right candidate and the right department don’t always meet at the same time. When academics do move, whether up or down the prestige ladder, the match typically improves, translating into higher productivity and higher salaries.

This can explain both the symmetric mobility pattern and the limited role of institutional rents. If a better fit drives moves in either direction, both directions should be associated with pay increases—which is exactly what we find. And if salaries reflect worker quality rather than employer generosity, there is little room for rents to accumulate.

Implications

Our findings suggest that academia operates under a different logic than most labor markets. Employer-specific pay premiums play a limited role; talent sorts strongly across institutions, and mobility is driven by match quality rather than climbing a prestige ladder.

More broadly, the results highlight how information and the timing of job opportunities shape labor market outcomes.

Elite universities do not necessarily pay more. They employ faculty who would earn more almost anywhere.

References

Abowd, J M, F Kramarz and D N Margolis (1999), “High wage workers and high wage firms”, Econometrica 67(2): 251–333.
Bagger, J and R Lentz (2019), “An empirical model of wage dispersion with sorting”, The Review of Economic Studies 86(1): 153–190.
Card, D, A R Cardoso, J Heining and P Kline (2018), “Firms and labor market inequality: Evidence and some theory”, Journal of Labor Economics 36(S1): S13–S70.
Haltiwanger, J C, H R Hyatt, L B Kahn and E McEntarfer (2018), “Cyclical job ladders by firm size and firm wage”, American Economic Journal: Macroeconomics 10(2): 52–85.
Moscarini, G and F Postel-Vinay (2018), “The cyclical job ladder”, Annual Review of Economics 10(1): 165–188.

Co-authored with: Shulamit Kahn (Boston University) and Kevin Lang (Boston University)

Forthcoming at: Review of Economics and Statistics

Learn more: Full Paper