Lower Pay and Greater Barriers to Success: An Examination of Gender Inequality in the Erie County, NY Labor Market

Executive Summary

This is an executive summary of findings of a study commissioned by the County of Erie (“County”) to gather and analyze qualitative and quantitative data on gender-based wage disparities in Erie County, New York.  The research project was undertaken in collaboration with the County’s Commission on the Status of Women which is seeking to determine the extent of a gender wage gap in order make recommendation on how such wage inequities can be addressed and eradicated.  Findings reveal persistent gender disparities in wages, career advancement, and political representation. Despite progress in women’s labor force participation, deep-rooted inequalities continue to limit women’s earning potential, workplace mobility, and influence in decision-making roles.

Methodology

This report examines gender inequality in the workforce of Erie County, NY, through a mixed-methods approach: Quantitative Analysis – Using data from the U.S. Census Bureau’s American Community Survey (ACS) Public Use Microdata Samples (PUMS) and the Current Population Survey (CPS) Earner Study, the study estimates generalized linear models (GLMs) of wages, controlling for key demographic and employment factors (e.g., age, education, race-ethnicity, occupation, industry, work hours). These models provide adjusted average wages to measure gender wage disparities across different groups. Qualitative Analysis – Five focus groups were conducted with 24 working women from key industries in Erie County, including healthcare, education, food service, and public administration. Discussions covered motivations for work, workplace discrimination, pay inequities, career advancement challenges, and work-life balance.

Key Findings

1. Persistent Pay Gaps Despite Workforce Contributions

• Women make up 49.3% of Erie County’s workforce, yet they are concentrated in lower-paid industries such as healthcare, education, and food services.
• Even after controlling for factors like education, experience, occupation, and industry, the adjusted average hourly wage for women is $2.74 less than men, leading to an annual economic loss of nearly $5,700 per full-time female worker.
• The wage gap widens with higher education—women with graduate or professional degrees earn $3.68 per hour less than equally qualified men, amounting to nearly $7,700 less per year.

2. The “Motherhood Penalty” and Unpaid Domestic Labor

• Mothers in dual-income households earn $3.18 per hour less than fathers, reinforcing national trends where caregiving responsibilities disproportionately affect women’s wages and career advancement.
• Focus group participants described shouldering both professional workloads and unpaid household responsibilities, often being the primary parent while also managing finances, child-rearing, and domestic tasks.
• Many women reported feeling pressure to sacrifice career growth for family obligations, limiting their opportunities for leadership roles and higher earnings.

3. Lack of Political and Economic Power

• Despite comprising 51.3% of Erie County’s population, women hold only 27.3% of County Legislature seats and represent just 30% of Buffalo’s most influential business and civic leaders.
• Women in focus groups described a “good ol’ boys club” culture, where men continue to dominate leadership roles in government, corporations, and key decision-making bodies.
• Political underrepresentation has tangible consequences—women’s interests, workplace policies, and economic challenges are often overlooked in policymaking and corporate governance.

4. Workplace Discrimination, Gender Bias, and Barriers to Advancement

• Focus groups revealed widespread gender discrimination, including lower pay, being overlooked for promotions, and assumptions that men are better suited for leadership roles.
• Many women lack salary transparency in their workplaces, preventing them from identifying and challenging pay disparities.
• In male-dominated environments, women described having to “prove” their competence repeatedly, often working harder than male colleagues for equal recognition.
• Many women, especially women of color, described that female supervisors were more difficult to work for than male supervisors, suggesting perhaps that women in positions of power felt compelled to overcompensate for being women in power.

Implications & Recommendations

• Enforce pay transparency laws to ensure women have access to salary information and can challenge unfair wage disparities.
• Implement stronger workplace regulations to hold employers accountable for gender-based pay inequities.
• Introduce affordable, high-quality childcare programs to alleviate the burden on working mothers.
• Advocate for paid family leave policies, allowing women and men to balance career growth with caregiving responsibilities.
• Create leadership development programs to support women’s advancement in corporate and government roles.
• Establish mentorship networks to connect women with influential leaders who can advocate for their career growth.
• Promote policies that encourage gender balance in political representation, such as recruitment initiatives and leadership training for women in Erie County.
• Unionized women in Erie County experience smaller wage gaps—supporting unionization efforts can help reduce gender-based pay disparities.

Conclusion

Women in Erie County continue to face systemic barriers to economic and political power, earning less than men despite equal qualifications and contributing significantly to the regional economy. Their underrepresentation in leadership and policymaking further limits their ability to advocate for structural reforms. Addressing these challenges requires bold policy interventions, corporate accountability, and cultural shifts to ensure that women receive equal pay, opportunities, and representation in decision-making positions.

By tackling wage disparities, expanding childcare support, promoting pay transparency, and increasing female leadership in politics and business, Erie County can take meaningful steps toward true gender equity in the workplace and beyond.

Introduction

By most measurable indicators, the status of women in the American economy has experienced marked, and seemingly rapid, improvement over the course of just a handful of generations. Roughly a century ago (i.e., before 1920), women did not have the right to vote in U.S. elections.[1] A half century ago, women could not apply for and receive a credit card without the formal and explicit consent of their husbands or a male relative.[2] And, prior to the passage of the Civil Rights Act in 1964, discrimination against women in the labor market was both effectively legal and commonly practiced in the open.[3]

Today, these and other formal institutions of gender discrimination often seem anachronistic, even though there are living individuals who experienced them (or whose parents experienced them) in real time – and even though, as this report will argue, the legacy of such institutions can still be seen and felt in the here and now. For instance, women not only have the right to vote in the U.S. today – they typically vote at higher rates than their male counterparts.[4] American women aged 15 years or older are among the most likely women in the world to possess a credit card (67.8%); and, as scholars such as Claudia Goldin have observed, there has been a “grand convergence” in labor force participation, and in the number of hours of work performed for paid employment, between men and women that started in the early 20^th Century and continues to the present.[5] What is more, roughly 85% of all contemporary American voters support Congress passing an Equal Rights constitutional amendment “that would guarantee equal rights for all citizens regardless of sex,”[6] suggesting that egalitarian gender relations are broadly valued by U.S. residents regardless of their personal gender identities.

At the same time, it should be obvious to most observers that such egalitarian gender relations – defined as the set of circumstances in which “men and women have equal power, equal autonomy, and equal opportunity”[7] in society – do not prevail in 21^st Century America. Women continue to shoulder disproportionate domestic burdens relative to men, and they face greater barriers to economic opportunities such as executive-level jobs, promotions, and decision-making power.[8] Women in the U.S. also experience a significant deficit in their collective political power. Despite making up over half of American residents (50.5% of the overall population[9]), women account for just:

• 28.2% of seats in the two houses of Congress;
• 31.0% of statewide executive seats;
• 33.4% of state legislators;
• 26.8% of mayors in U.S. cities with at least 30,000 residents; and
• 32.3% of all municipal officeholders in cities with at least 10,000 residents.[10]

At the federal level, this substantive underrepresentation of women in seats of power is arguably linked to recent backsliding in women’s rights in the United States. As just one example, the 2022 Supreme Court decision in Dobbs v. Jackson, which overturned a person’s constitutional right to an abortion, passed by a 6-3 majority. Crucially, five out of the six men who were on that Court (83.3%) voted to overturn the abortion protections previously established in Roe v. Wade, whereas two out of the three women on the Court at that time (66.6%) dissented with the [male] majority decision. The opinions of the majority of male Justices prevailed over the opinions of the majority of female Justices.

Insofar as experts argue that this sort of backsliding in gender relations might intensify under the Project 2025 policy agenda that is being pursued by allies of the current Presidential Administration,[11] it is worthwhile for officials at other levels of government (i.e., state and local governments) to document current conditions of gender inequality in their jurisdictions in order to establish something of a floor. More specifically, by building an understanding of current levels of gender inequality in a given location, state and local government officials can identify both (1) how far their jurisdictions remain from achieving more comprehensive visions of egalitarian gender relations, and (2) the extent of the advances that have been achieved in gender relations to date and must therefore be protected (e.g., with state and local policy) from backsliding. Toward that end, the remainder of this report uses Erie County, NY, as a case study with which to examine conditions in one specific domain of gender relations: work in the formal economy.

Study Area Context: Erie County, NY

Home to New York State’s (NYS’s) second largest city of Buffalo, Erie County (EC) is situated on New York’s western edge, adjacent to Lake Erie. After reaching a peak of just over 1.1 million residents in 1970, EC lost population for four consecutive decades, bottoming out at roughly 919,000 persons in 2010. Following that point, U.S. Census data recorded a net increase of almost 40,000 persons in the County between 2010 and 2020, with the population projected to continue rising for at least the next decade.^[12]

EC’s recent growth and population changes have been accompanied by rising concerns over economic (in)security. For instance, growth in dwelling costs throughout the County has substantially outpaced wage growth in recent years, leaving many residents – especially residents of households headed by women – in precarious housing situations.[13] According to the February 2024 version of the Cornell ILR Wage Atlas, just 52.8% of female wage earners in EC receive a “living wage” – i.e., a wage that allows them to meet the basic needs for their particular household composition – compared to 57.6% of men, and 60.1% of white men.[14] Furthermore, according to the WNY Women’s Foundation, the median full-time salary for women with some college training through an Associate’s Degree in EC is 14% less than the median salary for a man with just a high school diploma.[15]

These preliminary data points strongly suggest that gender relations in the formal EC economy remain inegalitarian and characterized by uneven outcomes. Although it is not the sole or even an unambiguous causal factor, it is important to note that, mirroring the national situation described above, women in EC tend to lack political power in proportion to their presence in the population. For example, despite making up 51.3% of the County population,[16] women in EC occupy only three (27.3%) of the seats in the current (2025) County Legislature.[17] Similarly, in Buffalo, EC’s principal city, a 2024 analysis performed by Our City Action Buffalo (OCAB) that identified the top 50 “highly-connected individuals” in Buffalo’s power structure revealed that only about 30% of such persons are women.[18] In short, women in EC appear to lack political and economic power at disproportionally high rates compared to men. Below, we draw on a mix of quantitative and qualitative data to reveal at least two important consequences of these inegalitarian gender relations: women in EC earn less than their male counterparts, even after accounting for age, educational, and other important differentials; and many EC women report that they face the dual challenges of unbalanced loads of domestic work at home coupled with barriers to economic advancement and mobility at work, even when they are as or more qualified than the men who tend to enjoy greater workplace freedoms and closer proximity to power and promotion.

A Note on Data and Methods

To build on the inchoate images from the prior section – images of an Erie County (EC) that is characterized by (1) unequal economic outcomes for men and women and (2) a collective power deficit for the County’s women – the remainder of this document develops and presents findings from a mixed methods study of the status of women in the EC labor force. First, drawing on two U.S. Census Bureau datasets – the current [2019-23 Five-Year] American Community Survey (ACS) Public Use Microdata Samples (PUMS) and the Current Population Survey (CPS) Earner Study – we estimate generalized linear models (GLMs) of wages on a robust set of control variables, including: occupation, age, race-ethnicity, educational attainment, household type, presence of children, work sector (e.g., public or private), disability status, citizenship, work hours (full- or part-time), and industry. The results of those models provide fully-adjusted average wages,[19] by gender, that can be used to compute gender wage gaps for a variety of scenarios (e.g., for a given level of education or household type). To add to the presentation of these wage gaps, Census ACS data on labor force participation are used to highlight the growing, though still incomplete, convergence in participation rates for men and women of Erie County, relative to the rest of New York State (NYS).

Second, our research team organized and facilitated five separate focus groups with 24 total participants who identified as women living and working in EC to ask questions related to motivations for work, experiences of gender inequity in the workplace, and challenges of balancing work and personal life. Taken together, the quantitative results from our wage models and the qualitative findings from these focus groups reveal an EC labor market that – despite the significant progress in advancing women’s right in the U.S. (refer to the Introduction) – continues to generate uneven outcomes for women, especially in the form of lower pay [for equivalent work], disproportionate domestic workloads, and greater barriers to economic mobility.

By the Numbers: Findings on Gender Pay Differentials in Erie County

American Community Survey Results

Using data from the current U.S. Census Bureau American Community Survey (ACS) Public Use Microdata Samples (PUMS), our research team developed and estimated a statistical model of hourly wages for all Erie County workers as a function of gender and a host of relevant control variables.[20] The results of the model allowed for the creation of fully-adjusted average wages, by gender, under a host of scenarios. For present purposes, our team generated these estimates for four broad categories of interest: education, household type, occupation type, and race-ethnicity.

Before summarizing these results, the interactive data tool below breaks down Erie County employment data from the ACS PUMS data by gender and industry. Overall, women constitute roughly half (49.3%) of all employed persons living in Erie County. However, as shown in in the visualization, women are disproportionately concentrated in just a handful of industries. Industries in the graph are arranged in descending order, so that the top employment industry in the County comes first. Observe that women make up the majority of persons employed in four out of Erie County’s top seven employment industries: Health Care and Social Assistance (largest industry; 75.4% women); Educational Services (second largest industry; 66.1% women); Finance and Insurance (sixth largest industry; 57.1% women); and Accommodation and Food Services (seventh largest industry; 52.4% women). Women are also the majority of persons employed in the “other services” sector (Other Services, except public administration) and make up a sizeable fraction of persons employed in Retail Trade (third largest industry; 46.9% women) and Professional, Scientific, and Technical Services (fifth largest industry; 48.0% women).

Insofar as women make up a supermajority of workers in the top two industries present within Erie County, it is reasonable to say that women are the driving force behind the County’s economy. Still, as already observed, mere presence in the County’s top industries has not translated into proportional representation in seats of political power,[21] nor has it coincided with proportional share of wages. Indeed, the tool below juxtaposes the industry-gender breakdown from above (left) with the gender-based share of wages in each industry (right). As shown in the graphs, in every industry in Erie County, women’s share of overall wages is below what should be expected based on their share of the given industry’s workforce. Some of the largest disparities occur in: Retail Trade, where women are 46.9% of workers but only receive 35.1% of wages; Other Services, where women are 51.9% of workers but receive only 38.0% of wages; Real Estate Rental and Leasing, where women are 39.8% of workers but receive only 27.7% of wages; and Finance and Insurance, where women are 57.1% of workers but receive only 46.5% of industry wages.

That being said, evidence of gender disproportionalities in industry-based wages is not, on its own, evidence of gender-based pay gaps. Although such findings are concerning, it is necessary to account for other potential sources of differential wage shares, such as differences in education, experience, age, occupation, and other relevant factors. Toward those ends, the following subsections present results from our statistical analyses, which revealed meaningful and statistically significant gender-based pay gaps even after controlling for important determinants of a worker’s wages. The results described in those sections can be found within the interactive data visualization tool, below. Using the dropdown menu at the top of the tool, users are able to explore fully-adjusted mean wages, and associated wage gaps, by gender, for various categories within four broad topical areas: education, household type (e.g., presence of children, occupation, and race-ethnicity.

Education

Conventional economic literature suggests that education is one of the most common paths to earning a higher wage. In short, completing formal educational programs and earning credentials therefrom (e.g., a high school diploma, a four-year degree, etc.) is linked to wage premiums, with the largest wage premiums tending to exist for graduate- and professional-level degrees.[22] Thus, one common position in the U.S. economy tends to be that, if a worker were to pursue and obtain additional education, then they would see their earnings [potential] rise, insofar as these premiums are [allegedly] coupled to the specific level of education involved and not necessarily to a worker’s gender or other ascriptive characteristics. As preliminary evidence from the WNY Women’s Foundation has already shown, though, this position tends to be somewhat of a myth in the American (and Erie County) economy. Rather than educational attainment producing the same economic advantages for all workers, there is an observable tendency for men to reap more wage benefits from higher education relative to women; and even for men with lower levels of education to out-earn some of their female counterparts with higher levels of educational attainment.[23]

The results of our statistical analyses support this contention and reveal statistically significant gender wage gaps in Erie County at all levels of education – after adjusting for a worker’s age, race-ethnicity, occupation, industry, sector, hours worked, and a handful of other controls. As observable in the above data tool, the adjusted average wage for men in Erie County across levels of education is $26.23 per hour, $2.74 per hour higher than the corresponding adjusted average for women ($23.50 per hour). For a full-time worker working 2,080 hours per year, this gap translates into an annual economic loss of roughly $5,700 for women relative to their male counterparts in similar jobs, industries, and demographic situations.

Gender Pay Gap:

On average, women earn $2.74 less per hour than men after controlling for relevant attributes. For workers with a graduate or professional degree, the gender pay gap jumps to $3.68 per hour, on average.

Crucially, the size of the gender gap in adjusted average wages is most extreme for higher levels of education. As illustrated more clearly in Figure 4, women with a four-year degree earn, on average, $3.01 less per hour than their male counterparts (nearly $6,300 per year for a full-time worker); and women with graduate or professional degrees earn $3.68 less per hour than men with similar backgrounds and situations (nearly $7,700 per year for a full-time worker).

Based on these results, simply creating additional pathways for women to enhance their educational credentials is not sufficient for closing gender wage gaps. Rather, proactive policies aimed at delivering authentic pay equity to women working in Erie County seem to be justified by the results of this subsection

Household Type

To the extent that mothers tend to earn less than fathers, even after adjusting for work hours and differences in education and experience,[24] analyzing the ways in which the overall pay gap detected above ($2.74 per hour) varies according to the presence or absence of children in a household allows for connections to broader findings on the motherhood wage penalty that has been observed in the overall American labor market.[25]

Using the interactive data tool to select “Household Type” reveals (1) adjusted average wages by gender for selected (mutually exclusive and exhaustive) household types in Erie County, and (2) the differences, or gaps, between wages for women and men within those household type categories.

The Motherhood Penalty:

Mothers who are part of a couple earn, on average, $3.18 less per hour than fathers living and working in similar situations.

Matching expectations, mothers in Erie County earn less than fathers, after controlling for a host of independent variables. Further, consistent with established findings, this ostensible motherhood penalty is greatest in magnitude for women who live in households with a parenting partner (e.g., a spouse or same-sex partner). Namely, mothers who are part of a couple earn, on average, $3.18 per hour less than similarly situated fathers (just over $6,600 per year for a full-time worker). Moreover, as discussed later in the findings from our focus groups, this hefty gap in wages [for similar work] are typically compounded and exacerbated by disproportionate shares of domestic work and child care in the household. These dual hardships – lower wages for similar work and more work in the home, thereby resulting in less leisure time relative to their male counterparts – suggest that Erie County has meaningful ground to cover in its efforts to advance a more egalitarian vision of gender relations in its local economy (NB: Erie County is far from alone in this campaign; indeed, the results for Erie County mirror results from economic investigations at much broader scales).[26]

Occupation Type

Next, to ensure that the gender pay gaps revealed in Erie County earnings data are not artifacts of wage differentials in, say, one or a small handful of occupations, our team used the results of our statistical model to generate adjusted mean wages, by gender, for workers in twelve major occupational groupings tracked by the Census Bureau. Three of those groupings – Construction and Extraction Occupations; Farming, Fishing, and Forestry Occupations; and Installation, Maintenance, and Repair Occupations – were associated with low observed frequencies, especially for women workers, and were thus excluded from the results. For the remaining nine occupational categories, adjusted mean wages and the gender gaps in those wages are presented in the interactive data tool above.

Observe that women who work as Healthcare Practitioners or in related Healthcare Technical Occupations earn, on average, $5.90 per hour less than men (almost $12,300 annually for a full-time worker) in those positions, after adjusting for age, education, and other relevant variables. The second largest pay gap can be observed for Management, Business, and Financial Occupations, for which an Erie County woman earns, on average, $4.59 less per hour (over $9,500 per year for a full-time worker) than an equivalent man in the same role. Whereas women are out-earned by similarly situated men, on average, across all occupational categories, traditional working-class roles in Service and Transportation and Material Moving are linked to meaningfully smaller pay gaps than positions that tend to have higher educational requirements, supporting earlier observations with respect to gender pay gaps by educational attainment.

Race-Ethnicity

To conclude this subsection, selecting “Race-Ethnicity” from the dropdown menu in the interactive data tool shows adjusted mean wages for women and men in Erie County, by race-ethnicity. Holding race-ethnicity constant, the largest gender gap in average adjusted wages occurs for persons who identify as white. Namely, whereas the adjusted mean wage for a white man is $26.57 per hour – the highest such value observed in Figure 9 – the corresponding wage for a similarly situated white woman is just $23.54 per hour, for a gap of $3.04 per hour (more than $6,300 annually for a full-time worker). In general, we estimate that a woman in Erie County earns roughly 88 cents for every dollar earned by a white man.

Interestingly, although a gender pay gap can be observed within nearly every racial-ethnic category covered in the interactive data visualization, women who identify with “Some Other” or “Two or More” racial identities (NB: these are the terms used by the U.S. Census Bureau), on average, earn slightly more ($0.24 per hour) than their male counterparts, after adjusting for relevant covariates. However, the 95% confidence intervals around adjusted male and female wages for members of this group overlap, suggesting that the wage premium for women in this group might not be much different from the wage difference that one might expect to find by chance alone.[27]

Current Population Survey Results

The U.S. Census Current Population Survey (CPS) Earner Study is the premier – and largely only – source of data on unionization for the United States. Relative to the ACS, the CPS tends to be timelier and more current (e.g., data already exist for the full year of 2024, unlike the ACS, which only goes through 2023); however, the CPS is distributed to a much smaller sample, which can lead to less stable results when subsetting by geography or other categories. Moreover, because of the smaller sample size, the finest resolution at which CPS estimates are published is the metropolitan region, meaning that one typically cannot use the dataset to study conditions in a single county. Nevertheless, for current purposes, it is possible to use the CPS to explore wages for Earner Study participants in the two-county Buffalo-Niagara metropolitan region, which consists of Erie and Niagara Counties.

The main interest in supplementing our ACS analyses with findings from the CPS Earner Study is to explore the possibility that unions raise wages for Erie County women, and to evaluate the potential of unions to close persistent gaps in average earnings. To perform this task, we built and estimated a generalized linear model (GLM) of average hourly earnings on a host of covariates, including the focal variable of gender, and the following controls: year of survey, age, race-ethnicity, educational attainment, household type, presence of children, occupation, sector (e.g., public/private), disability status, citizenship, hours worked, and industry. As above, the results of the model were used to generate fully-adjusted average wages for men and women in Buffalo-Niagara, by unionization status, over time.[28] The interactive data tool from above is reproduced below to show these adjusted mean wages.

The results contained in the data visualization reveal two important outcomes. First, as expected, unions raise wages – for men and for women. However, and second, the union premium does not necessarily close gender pay gaps. Indeed, throughout the 2010s, the gender gap in adjusted mean wages for union members tended to be somewhat larger than the corresponding gap for nonunion workers. Nevertheless, this situation appears to be inverting. Whereas it is difficult to see the findings for the period 2019-21 as anything other than anomalous given the influence of the COVID-19 pandemic during that interval, the most recent (2022-24) results show that the wage gap for women in union jobs is smaller than the corresponding gap for women in nonunion jobs, after controlling for relevant covariates. One implication of this result is that, as the Buffalo region continues to be a leader in union campaigns, especially in the service sector – recall that the nationwide Starbucks unionization effort has its origins in Buffalo[29] – optimistic observers might expect the wage gap between men and women to begin closing more forcefully than it has in years past.

As a final matter, observe that the data tool also graphs the “union premium” for women and men in Buffalo-Niagara over time. Once again, whereas the results for 2019-21 are seemingly aberrant due the impacts of COVID-19 shutdowns on the regional economy, there is a recent trend taking shape whereby the union premium for women might actually be outpacing the union premium for men. Once again, the implication is that, as (or if) unionization continues to advance in Buffalo-Niagara, gender wage gaps in Erie County may start to close at a faster pace. Beyond this recent trend, the bottom row of the series of graphs shows that, in the long-run, the union premium in Buffalo-Niagara has been roughly equal for men and women – once again pointing to unions as a potential source for advancing more egalitarian and equitable gender relations in the regional economy.

A Note on Convergence in Labor Force Participation

Prior to moving onto findings from our research team’s focus groups, the data tool provided below draws on long-form decennial census data from 1970, 1980, 1990, and 2000, as well as five-year ACS data for the years ending in 2010, 2020, and the current period (2023), to show patterns of labor force participation, by gender, in Erie County relative to the remainder of New York State (NYS), over time. Below these rates, the tool illustrates how the female-male participation gap has closed over the past 50-plus years. On this measure, Erie County and upstate tend to be ahead of the NYS curve. The labor force participation rate of women in Erie County is, according the most recent Census ACS, 59.4%, which is higher than the corresponding rates for “upstate” NYS and New York City (NYC). Only the Long Island area has a higher female labor force participation rate, at 60.5%. However, the gap between the male and female participation rates in Erie County is meaningfully lower than the gap observed in Long Island and is roughly equal to the rate measured for the remainder of upstate New York.

These findings support earlier claims that female labor force participation – especially in Erie County – experienced substantial growth over just a handful of generations, to the point where it is approaching the rate observed for men. Despite this positive development, however, the results unpacked earlier in this section show that wages have thus far failed to fully display the same degree of “convergence”. Put another way, while women are participating in the labor force at rates that are increasingly comparable to men, their earnings still show persistent levels of gender inequality in the Countywide labor market.

Through the Stories: Findings from Focus Groups with Women Working in Erie County

In order to enrich our quantitative analysis of the economic landscape and status of women wage earners in Erie County, and to identify some of the potential root causes of the persistent gender-based wage gaps revealed in our findings, the Cornell research team distributed a flyer to working women in Erie County and asked them to advertise the flyer to those working in similar fields as they, to produce a snowball effect. Outreach was targeted to industries in Erie County that are highly dependent on women’s labor (see above), including: Health Care and Social Assistance; Educational Services (both higher education and child care through 12^th grade); Food and Accommodation Services; and Public Administration.

Our flyer asked wage earning women in Erie County to confidentially book a slot in a focus group via a QR Code. The flyer indicated that themes of discussion in the focus groups would include: motivation for work, rates of pay and benefits, supervisory structure, the climate of your working environment, hierarchical structures, workplace discrimination and harassment (if any), opportunities for growth, and challenges to work/life balance.  Five separate focus groups were held between October and December 2024. The sessions included 24 total participants from the industries named above. The following subsections describe key themes and insights from the focus groups.

Reasons and Motivations for Working

Almost every participant stated that their primary reasons for working were financial in nature – that they needed income and/or benefits to care for themselves and their families.  Approximately half of the women we spoke with stated that they were the “primary breadwinner” in their households, either for themselves as a single person, or in their multi-earner families. Many women explicitly acknowledged that their situations counter conventional views of American households in which men tend to out-earn women.  At the same time, many of the women who indicated that they were their households’ primary earners mentioned that they felt some sense that their primary earner status was not widely recognized by other members of their professional and personal networks.  However, at least one participant noted that most members of her social networks are familiar with her household financial situation, which has resulted in some discomfort at work for her male spouse, whose coworkers occasionally joke about him earning less than his wife.

Beyond financial motivations, though, most participants stated that their jobs were an integral part of who they are. Nearly every participant stated that her work was personally fulfilling, and that she felt like she was giving back to the community and leaving a mark.  Respondents said that they felt a deep sense of responsibility to perform work that helps people and does something “good” for their communities.  Participants talked about how their work aligned with their academic training, and that they felt happy taking care of people, advocating for public health, educating children, preparing young people for careers, conducting research, assisting the poor, and working in government to provide public services to the citizens of Erie County. It was important to most women that their work gives them the ability to practice their values.  Others noted that they enjoyed their work as it gave them time away from home and identity of their own. One participant noted that her job sets a good example for her daughter, and it showed the value of getting an education to perform work that provided for the family and helped the sick.

Service workers were less likely to say that their identity was wrapped up in their work. Rather, the primary reasons they work are to have income (e.g., to be able to pay rent and bills), but also to have dynamic social interactions with different types of people on a regular basis. On the more material and practical motivation, there was general agreement that receiving tips was a big part of the choice to work in food and beverage service, insofar as worker can end a shift and walk away with money immediately in their pockets which was not taxable. With respect to the social motivations, every food and accommodation service worker we spoke with stated that they liked that their work was varied day to day and that they mostly enjoyed the work. However, the cheerful demeanor of the service workers was inconsistent with the actual content of how they explained their working conditions, and work life balance, as set out below.

The role of labor unions was an unexpected component of the focus groups.  Many of our participants discussed the role of the labor movement in their working lives.  They talked about the union as an important component of their work as it allowed them to have a voice at work and assist or “stick up” for their coworkers in obtaining better working conditions.  One participant stated that her work and union role set a good example for her daughter for social and upward mobility, that she could become a leader, improve her earnings and safety at work, and help other workers to do so also. Many felt that the union provided them with a better standard of living and a better workplace.

Experiencing Gender Inequality at Work

Every woman we spoke with reported experiencing some degree of gender inequality in the workplace. Below, we try to classify the major types of inequality that were raised.

Financial Inequality

Financially, many women expressed awareness that they were earning far less than men in similarly situated jobs. Some women noted that they earned approximately $10,000 less annually than men in the same position with similar experience. In one case, a woman in a senior-level development position in the educational services sector, and who has access to salary information at her place of employment, noted that she is currently earning $30,000 less than a man in the same position who has fewer years of experience and consistently requires training for skills that she (our focus group participant) has already mastered and been implementing at work throughout her longer tenure at the employer.  Most other women stated that men tended to be promoted ahead of them for supervisory positions, which, at least in food service, was linked to a 20% increase in salary.

Concerning employment terms, some women noted that they did not negotiate their pay at the start of their jobs, which caused them to start with a lower salary [than men] that then remains lower throughout their careers.  Other women said that they attempted to fight for higher salaries and/or job titles but were often denied.  One woman was bypassed for promotion by a man junior to her and was falsely told that she had to have higher qualifications in order to be promoted. It was only when she threatened to quit that she was promoted.

Another woman in the food service sector said that her company would rather hire men from the outside than internally hire qualified women for the job.  This resulted in qualified women, who were bypassed for promotion, training new male supervisors for jobs that paid those men about $10,000 more per year than what they (the women trainers) were earning. One participant described this dynamic as a “good ole boys club.”

Beyond these observable inequalities, many women said that they were not aware of pay differentials because their employers keep salary information confidential and employees to not voluntarily practice pay transparency. Finally, employees who were members of labor unions did not have this issue as their salaries are set by a negotiated contract that is open and available to the workforce.

Gendered Work

Many focus group participants openly acknowledged that they work in fields that are dominated by women: education, child care, health care, and food service.   Inside of those fields, participants said that women tend to perform the day-to-day work, while supervisory positions are disproportionately held by men (even in instances where nearly all of the rank-and-file workers are women).  In education, for example, women are teachers – men are administrators.  In health care, women are nurses, and men are doctors.  Where women are doctors, they are more likely to be lower paid public health doctors, whereas men are higher paid orthopedic doctors.  Women are food and beverage severs, and men are supervisors.  Indeed, a recurring theme in all five focus groups is that women often take and perform the duties that are “less valued”.  For example, for a focus group participant who works in higher education, her experienced is that committee work is almost exclusively performed by women, and after meetings it is women who do the cleaning up and kitchen work.   Similarly, in the service sector, women and men do certain chores; women clean the dishes and tidy up the workplace, while men handle the money.

“We are in jobs which are traditionally women’s work, not for profit world, cultural centers, child care, teaching, nursing, and historically underpaid and underappreciated, and it is disheartening to work to do better in the world and you find that there is a mindset that women’s work are less valuable and deserve less pay and/or recognition and I reject that.”

Another recurring theme, especially among women working in health, human, social, and public services, is that women often take positions that try to uplift those members of their communities who are in need; however, such jobs tend to be concentrated in cash-strapped nonprofit sectors that are often forced to pay low wages. The result is that women who are trying to use their professional lives to combat poverty or conditions of low wealth are themselves members of the working poor. As just one example, women working in child care facilities and selected nonprofit institutions indicated that they were unable to afford their student loan payments.

Many women also talked about having to take care of men at work and do more work than men, even if they were on her same level/position.  “It makes you feel not equal,” said one participant. For instance, in health care, some, though not all, of the focus group participants said that most of the doctors are men, and that the tone of the male doctors often makes them (women participants) feel disrespected.  A few respondents reported that doctors think that women health care workers are emotional, and that they need to “go toe to toe with the doctors” and show them the data to get their point across.  There was an indication from older nurses that women in health care are treated much better now than they used to be, citing time periods when physical sexual harassment was more common.

Inequality in the Workplace

Generally, focus group participants felt that their voices are valued less in their workplaces than a male voice. As a result, nearly all women feel that they have to work doubly hard, and be doubly qualified, in order to be heard and respected at work – regardless of the industry in which they work. Respondents said that “every day” they are ignored in meetings, especially if a man is facilitating the meeting. They further indicated that they are regularly underestimated, overlooked, ignored, talked over, and “mansplained”.  Women noted that they have to do “everything better”, be more qualified, speak physically louder, act more aggressively, and change their body language to be more aggressive – and that all of these actions are physically exhausting by the end of the workday.  Women report that they need to be experts in their work in order to be treated with more respect by men.

Women who manage men reported that they had a difficult time earning the respect of those men. This feeling seemed especially true in one woman’s construction industry workplace, where men were more dismissive a female boss and even clients would demand to speak with a male (often at a lower rank) because they did not want to deal with a woman.

Several women expressed that women who are considered more attractive by cultural norms, or are more “sexualized” such as by wearing attractive clothing, tend to receive greater rewards at work.  One respondent spoke of an attractive female coworker being asked at attend a work trip with the boss that other less attractive women were not asked to attend.  In the food service industry, conventionally attractive women are put in the public facing jobs, such as hostess or cashier, a strategy that one participant described as: “put the pretty girl up front.”  Respondents noted that such a strategy is not necessarily a good thing because these women often have to deal with more sexual harassment from male customers and coworkers in those public-facing roles.

Almost all of the women we talked to, in every field, noted that the farther up the hierarchy in their workplace’s supervisory structure, the more likely it was to find a man in charge, even where most of the workforce was female. In cases where the men occupying these key positions are from older generations than the women with whom they interact, interactions can be demeaning for women. For example, we heard that older men treat women worse than younger men because they “cannot get used to the idea that a woman is smart”.  Older men also expect younger women to get them coffee and listen to them (the men) talk like they are the expert, even in cases where the woman in the interaction has been working in the field for decades.  For all of these reasons, more than a few focus group participants stated that they sometimes ask, a male coworker put their (the women’s) ideas forward in the expectation that it will be better-received coming from a man.

Sexual Harassment

Somewhat surprisingly, focus group participants did not report many recent instances of quid pro quo sexual harassment.  Only one respondent reported ongoing sexual harassment. She was extremely upset by the ongoing situation and was unsure of how to respond because she feared retaliation for reporting.  Another respondent remembered back to her early years of working for a law firm where she was sexually harassed, and she became visibly upset as she remembered the abuse, noting that she had not thought of the event in years.  Similarly, nurses reported that sexual harassment by doctors was much more common several decades ago compared to the present.

In the food service industry, it seemed more common for there to be a sexually hostile work environment. Customers come from all walks of life, and some might say inappropriate things to staff. In such cases, female employees who have reported customer-based harassment to male supervisors did not feel that the supervisors were sufficiently supportive. In at least one case, food service employees asked “regular” customers to complain about an abusive male supervisor to corporate headquarters because staff complaints were not being acted upon. Participants reported that the strategy was successful, and the abusive supervisor was eventually terminated.

Discrimination by Female Supervisors

In all five focus groups, there was at least one woman who reported that older, especially white, women at their workplaces were more hostile toward them (focus group participants) than male supervisors or colleagues. This sentiment was especially true for women of color and younger women in our focus groups.

In fact, all of the women who identified as Black or African American in our focus groups commented that they felt they were treated better by white male supervisors than they were by female supervisors.  To one such participant: “As black women, we get this from older white women in professional spaces…. women expecting us to be grateful to be in a space where white women are and not respecting us.” At least one young white woman shared similar feelings about her older female colleagues.

While some white women felt uplifted by white women supervisors^[1], a sizeable number of respondents reluctantly reported that they did not enjoy working for female supervisors.  “Some women get to leadership roles and feel like that means they need to act in a patriarchal way….”  One person suggested that once women get to high level positions of supervision, they feel like they need to outperform their male counterparts, so they become abusive supervisors.  The participant indicated that some of the most emotionally manipulative and abusive supervisors she ever had were women, while found that dealing men was more straight forward.  To her: “Women can sometimes be misogynistic women leaders” and biased against other women, which was “disappointing”.  And some women were disappointed that women were harder on each other in an effort to move up.

Male Intimidation in Union Campaign

Several of the respondents had been involved in union campaigns at their workplaces.  In one case, it was estimated by a respondents that about 75% of managers at her workplace were male, despite women making up a supermajority of the workforce.  As her workplace was organizing, the company sent many male managers to surveil the workforce, which participants found to be intimidating.

Challenges of Balancing Work and Family Life

Participants initially seemed reluctant to talk about an imbalance in their lives.  It seemed that the women were reluctant to admit that they had trouble balancing work and home and family.  However, when given time to talk, there was eventually an outpouring of belief that there was an extreme imbalance in being able to work and have a home life.  The following direct quotations offer important examples:

“I have to work so much harder than my husband, and I have to be the primary parent, manage the kids, the household, and a lot of men do not think about it.”

“There is always extra toilet paper in case we run out.  The management at home is a lot of brain power”.

I don’t like the questions because to say I don’t have balance would mean that I was “wrong”.

“I get very little sleep, and I’m holding on like a thread, and working with vulnerable people, so I have to perform well at work and its very draining.”

One participant said that there is a term for work-life balance, “the invisible, spinning all the plates, managing the calendar while the counterpart at home or at work, live their own life and you have to do so much more.”

Participants said that employers have an “extreme lack of awareness, paying attention, to what huge amount of work is going on behind the scenes. If employers were aware, then employers would be helping workers who were dealing with these situations.”

Another participant expressed some resentment related to the “mismatch of perception” that [her] husband supports the family, “but I primarily support my family.”

Emphasizing the shared realization of imbalance, one woman initially explained that she and her husband share the work and family chores.  Then, upon reflection, she realized that she gave up a lucrative career in order to stay home with her children when they were born, and later trained herself to be a lower paid teacher so that she had time at home to raise children.  So, she said upon further reflection she realized she made substantial career concessions to have more balanced work life with home life.

Additional anecdotes worth highlighting include:

“In the dating world there is an expectation that a woman will center their lives around a man”

“Juggling is hard and it never gets to equilibrium depending upon sick kid, sick parent.”

“I show up at work with a full matchbook, but each step takes a match, and by the time you get to your own time, you have zero matches left, because someone has ripped those out of you.  No one is filling our cup back up.  I do my job, but also do…Children, grocery, cooking….  we do not get recognized for what takes away the matches.”

“Your wife is at home doing what we did to get in the same room as you.”

Finally, a number of young women said that they would not have children because they did not want to work so hard to have a work/life balance.

“The extra thing you have to do with kids, made me decide not to have children. I know that a lot of women have experienced this [imbalance] and I do not want to experience that.”

Special Considerations in the Food Service Industry

Not one focus participant from the food service industry claimed to enjoy work-life balance.  The main reason for this universal sentiment was that service work is not regularly scheduled, is physically hard, and is low paid.  Being essentially “on call” for work is extremely disruptive to work-life balance. Respondents said that “Call-ins are very disruptive to work-life balance. We are expected to come into work (looks good for promotion) when[ever] we are called to come in” when they were not previously scheduled to work.  It is a “poor reflection on my character not to come into work when I’m called to come in,” said one participant. Supervisors in the service sector are expected to cover for workers who do not report to work, which can frequently mean working double shifts and being available from open until close – making work-life balance impossible.  One respondent said “my family has to come and visit me at work in order to see me” because she works so much.

Service workers’ productivity is tracked during their shifts.  “The jobs are extremely labor intensive and physically mentally exhausting.”  If a worker does not meet benchmarks, then supervisors cajole them to work faster – with smiles on their faces the whole time – regardless of any unintended consequences that can come with more intense work.  As one participant put it: “When you get home you don’t feel like you can do anything else.”

In one workplace, if the metrics show that workers get a “good score”, then the employer rewards them with more workers on the floor.  If workers get bad customer reviews, they are punished by having fewer workers available on the floor. This backwards logic makes it more likely that lower-performing locations will be understaffed and unable to improve service quality over time.

Managers also track sales, and if the manager is not hitting the labor to sales ratio, then they are expected to reduce workers’ hours.

Because of these considerations, essentially every single service sector employee said that they would never be able to have a child, and not one of them was a parent already.  They all said that they could not have children and work in food service under current work conditions, largely because the hours are too variable and shifts often run over scheduled times (participants noted that workers are regularly encouraged to clock out and then finish their shifts, or else get punished).

One person reported that her restaurant manager had children, but she worked so much that she never saw her children.  Eventually that worker left her food service job to go manage a dental firm.

Conclusions and Implications

Through a combination of statistical analyses and focus group conversations, this report found that women working in Erie County, relative to men, simultaneously experience lower pay (after controlling for relevant factors) and greater barriers to success. Although this phenomenon is national, if not global, in scale and therefore not unique to Western New York (WNY),[32] by documenting conditions in the local economy, this report functions as a call to action for local and state representatives in Erie County. The industries that are driving our local economy are being powered disproportionately by women, and women working in Erie County are not receiving an equal share of their labor, nor are they being elevated equally into positions of political and economic influence.

That being said, what can local and state policymakers do to affect the outcomes observed throughout this report? Whereas much larger cultural and macroeconomic forces fuel the patterns of inequality observed hereinbefore, at least a few potential leverage points emerged from this study.

First, one recurring focus group theme is that women working in Erie County take on the lion’s share of their domestic and household burdens, even when they are their families’ primary earners. Quantitative evidence revealed this situation to be a double burden, insofar as not only are women – especially mothers – doing more work at home, but they are earning less than their male counterparts at work, even when they are working similar hours in similar occupations and roles. Whereas it is unlikely that any one policy measure could be capable of correcting this double burden, one action that seems likely to have a large impact is the social provision of child and related care services. The universal, or at least widespread, provision of affordable (or free), accessible, high quality care is an action that would have far-reaching impacts and would disproportionately benefit women, who perform the vast majority of their families’ care work.

Second, actions that promote a culture of pay transparency could help to expose situations of gender-based pay discrimination. Among focus group participants, women who had direct knowledge of being out-earned by male counterparts seemed to be the most motivated to close such pay gaps – with one even successfully using pay differentials as a justification for her threat to quit if she was not promoted. Whereas New York State recently passed a pay transparency law that requires job postings to publish salary ranges under certain circumstances,[33] such a law is not designed to promote or create opportunities for existing employees within organizations to see how their wages compare to wages earned by their peers. In this respect, advocates might look to unions as examples: union collective bargaining agreements (CBAs) generally result in the publication of transparent wage books that specify what persons working in certain positions are required to be paid.

Third, and relatedly, both quantitative and qualitative evidence revealed that unions increase pay for workers and, over the long-run, are capable of smoothing out gender-based pay inequality to advance more egalitarian gender relations at work. Labor and political education that inform workers of their organizing rights can therefore have both immediate and long-term impacts on improving the status of women in the Erie County workforce.

Finally, a number of women found our focus groups to be empowering.  Just one hour together showed them that they can greatly benefit from having a space where they and other women can come together to speak freely and share their experiences.  They felt that if they could talk to each other about issues such as gender inequities that they could lift each other up.  One woman called for a “human library where we could check out people instead of books.”  Building networked institutions of support and care seems like a necessary step toward more egalitarian gender relations in and beyond Erie County.

Notes

[1] In workplaces that were only female, with all female supervisory structure, strong women supported other women and advocated for them.  “We have the power because we run the place.”

[1] National Archives. (n.d.). “19th Amendment to the U.S. Constitution: Women’s Right to Vote (1920).” https://www.archives.gov/milestone-documents/19th-amendment

[2] Ulaby, Neda. (2024). “Smithsonian’s new series is tied to 50th anniversary of Equal Credit Opportunity Act.” NPR, 28 October 2024. https://www.npr.org/2024/10/28/nx-s1-5163432/smithsonians-new-series-is-tied-to-50th-anniversary-of-equal-credit-opportunity-act

[3] Rogers, Joel, & Wright, E. (2024). American society: How it really works, 3/e. W.W. Norton & Company.

[4] Igielnik, Ruth. (2020). “Men and women in the U.S. continue to differ in voter turnout rate, party identification.” Pew Research Center. https://www.pewresearch.org/short-reads/2020/08/18/men-and-women-in-the-u-s-continue-to-differ-in-voter-turnout-rate-party-identification/

[5] Goldin, C. (2014). A grand gender convergence: Its last chapter. American economic review, 104(4), 1091-1119.

[6] Jacobs, Sabrina. (2022). “Fifty Years Later, Voters Support Passing the Equal Rights Amendment.” Data for Progress. https://www.dataforprogress.org/blog/2022/6/2/fifty-years-later-voters-support-passing-the-equal-rights-amendment

[7] Rogers and Wright (2024, p. 384).

[8] Saini, A. (2023). The patriarchs: the origins of inequality. Beacon Press.

[9] U.S. Census Bureau. (n.d.). “QuickFacts: United States.” https://www.census.gov/quickfacts/fact/table/US/LFE046223

[10] Center for American Women and Politics. (n.d.). “Current Numbers.” https://cawp.rutgers.edu/facts/current-numbers

[11] Saez, Macarena. (2024). “Interview: Women’s Rights Under Trump: Expect Further Rollbacks in the US and Globally.” Human Rights Watch. https://www.hrw.org/news/2024/11/18/interview-womens-rights-under-trump

[12] Cornell Program on Applied Demographics. “New York Counties Data.” https://pad.human.cornell.edu/counties/index.cfm

[13] Weaver, R., & Knight, J. (2020). Advancing housing security: An analysis of renting, rent burden, and tenant exploitation in Erie County, NY. Rent Burden, and Tenant Exploitation in Erie County, Ny (December 28, 2020).

[14] Weaver, Russell. (2024) [2023]. Cornell ILR Wage Atlas. Cornell University ILR School. Available at: https://blogs.cornell.edu/livingwage.

[15] WNY Women’s Foundation. (2024). “Pay Gap.” Pathways to Progress. https://wnywomensfoundation.org/files/2023/03/gender_inequality.pdf

[16] U.S. Census Bureau. (n.d.). “QuickFacts: Erie County, New York.” https://www.census.gov/quickfacts/fact/table/eriecountynewyork/PST045224

[17] “Erie County Legislature.” https://www4.erie.gov/legislature/

[18] Our City Action Buffalo [OCAB]. (2024). Who Rules Buffalo? A Field Guide to the Local Power Structure. https://drive.google.com/file/d/1cr4mHGTZ4ePzuLyIaN4IS0WByJUqZyGg/view

[19] Here, “fully adjusted” means that reported average wages account for all of the attributes included in the models as control variables. Such figures differ from raw averages, which do not account for variation in attributes like a worker’s age, gender, occupation, or work hours.

[20] Average hourly wages were computed by, first, adjusting the ACS PUMS wage earnings variable for inflation using U.S. Census Bureau-provided adjustment factors. Second, all adjusted earnings were inflated to 2024$ using the Federal Reserve Bank of Minneapolis’s inflation calculator. Next, annual wage earnings were converted into hourly wages using the following formula:

Hourly Wage = (Annual Wage Earnings / Weeks Worked) / (Usual Hours Worked + (1.5*Overtime Hours Worked))

where Overtime Hours Worked equals 0 if the worker self-reported working 40 or fewer hours per week, and equals (Usual Hours Worked – 40) otherwise; and where, as documented in the attached code, Annual Wage Earnings is first be multiplied by a Census Bureau-provided adjustment factor to convert all wage earnings into 2024 dollars. In our generalized linear model (GLM) of wages, hourly wages were log-transformed to smooth out the distribution. Control variables in the model included: occupation, age, race-ethnicity, educational attainment, household type, presence of children work sector (e.g., public or private), disability status, citizenship, work hours (full- or part-time), and industry.

[21] OCAB (2024).

[22] Deere, D. R., & Vesovic, J. (2006). Educational wage premiums and the US income distribution: A survey. Handbook of the Economics of Education, 1, 255-306.

[23] E.g., WNY Women’s Foundation (2024).

[24] Goldin, C., Kerr, S. P., & Olivetti, C. (2024). The other side of the mountain: women’s employment and earnings over the family cycle. Oxford Open Economics, 3(Supplement_1), i323-i334.

[25] Id. See also: WNY Women’s Foundation (2024).

[26] Id.

[27] It should be noted that all other gaps in adjusted mean wages, by gender, covered in this section are statistically significant at a 95% level of confidence or higher.

[28] The CPS covers three categories of unionization: (1) union member, (2) not a union member, but covered by a union collective bargaining agreement [CBA], and (3) not in a union nor covered by a union CBA. For simplicity, these categories were collapsed into (a) has union coverage and (b) does not have union coverage. Further, to smooth out potential aberrations and evaluate more structural conditions, annual CPS data were grouped into three-year increments, beginning with the year 2010 and ending in 2024: 2010-12, 2013-15, 2016-18, 2019-21, and 2022-24.

[29] See: https://sbworkersunited.org/our-story/

[30] Weaver, R., Brady, A. M., & West, Z. (2023). Diminishing New York State’s Public Mental Healthcare Sector: The Impact of Austerity and Privatization on Wages and Employment. Cornell University ILR School.

[31] Weaver, R., Bagchi-Sen, S., Knight, J., & Frazier, A. E. (2016). Shrinking cities: Understanding urban decline in the United States. Routledge. (Ch. 5)

[32] E.g., Goldin (2014); Goldin et al. (2024); Saini (2023).

[33] See: https://dol.ny.gov/pay-transparency