An Analysis of Unemployment in Jersey City

Jersey City is a diverse and vibrant city located in northern New Jersey, just across the Hudson River from Manhattan. With a bustling waterfront and lively downtown, it offers a thriving arts and culture scene, excellent dining options, and a growing business community. It's a popular destination for both locals and visitors alike, with easy access to transportation and stunning views of the New York City skyline.

Explore Jersey City and its demographics, economics and more using the interactive map below.

Unemployment Rate (in %) Which part of the city is experiencing high unemployment?

This layer highlights significant disparities in the unemployment rates within the same city. Specifically, the unemployment rate in the city's center is at recession-level (>10%), while the east and west waterfront areas exhibit remarkably low unemployment rates.

This contrast can be partially attributed to the development of the waterfront in the 1980s, particularly the construction of Newport and Exchange Place, which triggered a building boom. Waterfront facing New York City has been highly desirable as it is surrounded with local amenities and easy access to Manhattan. This development trend continued to the early 2020s, adding more skyscraper apartments, making Jersey City with the highest median rental costs in the country. As a result, high-income workers were attracted to the waterfront area, exacerbating the socioeconomic divide between the waterfront and the rest of the city.

Long Commute Time to Work (in Index, 100 = National Average) Who spends most time commuting to work?

This layer illustrates the likelihood of long commutes, which serves as a proxy for whether individuals work locally or not. Notably, areas with high unemployment rates also exhibit an above-average percentage of individuals who commute long hours, with a 40% higher likelihood of spending more than seven hours commuting to work. In contrast, areas with low unemployment rates, such as the waterfront, have an around or below-average likelihood of having long commutes.

This significant disparity in commute times can be interpreted as an indication of a lack of job opportunities within the same geographic area. Moreover, it correlates with the work-from-home ratio and transportation to work, as shown below. Overlaying unemployment rates, commute times, and the percentage of workers who drive alone to work reveals that individuals from areas with high unemployment rates often need to drive long distances to reach their workplace.

Work from Home (in %) Who is working from home?

This layer shows where the knowledge workers (who can work from home) are based.

Transportation to Work (Public Transportation, in %) Who is taking the bus or subway to work?

This layer shows whether their workplace is accessible without owning a car.

Transportation to Work (Driving Alone, in %) Who is driving their car to work?

This layer shows how many people get to their workplace by driving themselves.

Race and Origin (Predominant Category) ⭐ Where are black/white/Asian/Latinx people living?

Like New York City, Jersey City has been a popular destination for immigrants for centuries. Consequently, it has been named as one of the most ethnically diverse cities in the world. Over the last decade, the city's Asian American and Latino and Hispanic American populations have each increased by 15% and 12%, respectively.

This layer illustrates the correlation between the predominant race and the unemployment rate. It also highlights the segregation between the white and Asian populations and the black and Latinx population, as evident in the difference in unemployment rates between these groups. This divide is similarly reflected in the income and education spending layers shown below.

Median Home Value and Income Which part of the city has wealthy/impoverished population?

This layer depicts the correlation between the wealth gap and the unemployment rate. Specifically, it demonstrates how the wealth gap impacts the unemployment rate and vice versa.

The geography of home values in this area can be attributed to recent development efforts, as previously discussed in the unemployment rate section. The east side of the city has emerged as a hotspot for high-income workers employed in the financial district or in Manhattan.

Education Spending (in USD) Who spends the most on their children’s education?

This layer shows how generational wealth is passed down in the form of education spending, when viewed together with the Median Home Value and Income layer.

Education Level (Less than High School, in %) Who didn’t get the opportunity to finish high school?

This layer shows how individual’s current education level affects the unemployment rate.

Lack of Health Insurance & Asthma Prevalence (in %) Who is most vulnerable for sickness?

This layer shows how illness and vulnerability affect the unemployment rate.

Hot Spots of Asthma Which part of the city has higher/lower than average rates of asthma?

This layer shows that asthma is confined to certain parts of the city, highly correlated to the unemployment rate.

Socioeconomic Theme (Below Poverty Level, in %) How many people are living under the poverty line?

This layer shows the unemployment rate is significantly related to socioeconomic vulnerability.

Household Composition/Disability Theme How much of the household is part of the vulnerable group?

This layer shows old/young/disabled/single-parent households are related to socioeconomic vulnerability.

Housing/Transportation Theme How are the living conditions for each part of the city?

This layer shows poor housing and lack of transportation are correlated to the unemployment rate.

Jersey City gained a reputation as a working-class city with large manufacturing factories during the industrial era. However, the post-World War II era saw factories move to other parts of the country and overseas for cheaper labor, resulting in a significant decline in manufacturing jobs. This loss of employment had a substantial impact on Jersey City, particularly its blue-collar workforce, leading to a decrease in overall businesses and residents.

After the decline of manufacturing, the waterfront area fell into disrepair. However, by the early 1980s, it became an attractive investment opportunity due to its proximity to Manhattan and lower real estate costs. The city established an Economic Development Corporation to promote the city to investors and offer tax incentives for development, drawing large Wall Street firms.

This shift from manufacturing to a service-based economy led by financial services, insurance, and real estate industries increased income inequality and reinforced racial, ethnic, gender, and class divisions in the city. Although the financial services sector provided high-paying jobs, it did not directly benefit Jersey City residents who mainly worked in lower-paying service sectors overrepresented by women and minorities.

Furthermore, luxury housing development on the waterfront led to housing costs skyrocketing in working-class neighborhoods, displacing existing tenants from their apartments. Jersey City's preference for luxury housing over affordable housing led to a significant decline in affordable housing, forcing many residents to spend a higher proportion of their income on rent. The city's disregard for affordable and mixed-income housing has caused a permanent housing crisis that has had a detrimental effect on its residents.

Based on this historical and geographical analysis, we can clearly see the intricate connections between unemployment rates and other socioeconomic conditions and how these issues are often segregated into different areas of the same city. This segregation can be related to how different groups have settled in different parts of the city over time, as discussed above.

Most notably, the Long Commute Time to Work and Transportation to Work (Driving Alone) layer indirectly indicate the lack of job opportunities for residents within the city, which leads to high unemployment rates, poverty, poor living conditions, and other socioeconomic issues. These challenges can have significant impacts on public health and exacerbate identity-based disadvantages.

One potential solution to the issue of high unemployment is to redefine how we interpret unemployment data. The overall unemployment rate in New Jersey as of September 2022 is at an 11-year low of 2.8% ( FRED ). Does this mean that every part of New Jersey is enjoying the historically low unemployment rate? This analysis has shown that unemployment rates vary significantly even within the same city. Therefore, addressing the issue of unemployment at the county or city level is not sufficient enough. Instead, policymakers should focus on specific communities that are most affected by unemployment and aim to reduce unemployment inequality.

To achieve this, the local government can subsidize developments that will provide jobs for residents, such as offering tax breaks to new businesses that hire local workers or directly employing unemployed residents through a public employment program. Moreover, the government can also implement legally binding agreements that require businesses to train and hire local workers.

At the end of March, New Jersey Labor Department announced the expansion of the program, which offers $500 bonuses to new hires and covers half the costs of training to employers ( northjersey.com ). Financial subsidiary programs like this may help reduce the overall unemployment rate, but they do not address the lack of opportunities in specific communities.

To break the cycle of inequality caused by repeated unemployment, we need radical public policies that prioritize reducing unemployment inequality. By focusing on specific communities and providing targeted support, we can create more opportunities and ensure that everyone has access to meaningful employment.