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By Andrew Carr, Mark Abraham, and Nat Markey, DataHaven

Introduction

The recently passed One Big Beautiful Bill Act (H.R. 1) will have unequal effects on American families and will contribute to income and wealth inequality. A recent report from the nonpartisan Congressional Budget Office (CBO) shows that H.R. 1 will increase after-tax earnings for households at the top of the income distribution, while negatively impacting households in the bottom fifth of the distribution.

The CBO estimates weighed the positive effects of reduced taxes against the costs of reductions in Medicaid and SNAP in order to estimate average effects on each decile of the household income distribution.

For this report, DataHaven combined the CBO estimates with U.S. Census data to estimate the impact of H.R. 1 tax relief on the bottom quartile (less than or equal to the 25th percentile), middle 50 percent (between the 25th and 75th percentiles), and the top quartile (above the 75th percentile) of each Connecticut town’s household income distribution. The Methodology section below has detailed information on how we produced these estimates.

Results

Overall, we estimate that the bottom 25 percent of Connecticut households will collectively lose $148 million (an effect of negative $417 on average) due to H.R. 1. Meanwhile, households in the middle of the distribution will collectively receive $1.3 billion in tax relief ($1,815 on average), and households in the top 25 percent will receive $3.4 billion in tax relief ($9,535 on average).

Our estimates of the aggregate effects on households in each town, and the distributions of those households by income group within each town, are shown in the map above. Click on the map to explore data for each town. Estimates of the effects on individual households living in each town, county equivalent (COG area), and income group within each may be found in the Additional Interactive Maps and Data section below.

The figure above shows the effects of H.R. 1 by income group within select Connecticut towns. Most of the tax relief from H.R. 1 will accrue to the 25 percent of households with the highest incomes in each town. For example, high-income households in Greenwich will benefit from an additional $30K in tax relief per year on average, $22K more than the $8K that households in the middle of Greenwich’s income distribution will receive each year. The bottom 25 percent of Greenwich households will receive an average of $0 in tax relief.

In New Haven, Bridgeport, Waterbury, and Hartford, middle-income households will experience negligible benefit from H.R. 1, while low-income households will be negatively affected. For example, in New Haven, the top 25 percent of households by income will each receive $6,200 in tax relief on average, households in the middle will each receive $500 in tax relief on average. The bottom 25 percent of New Haven households by income will each see a $1,100 loss on average.

Our estimates showing unequal tax relief by community do not convey the full extent of hardship that H.R. 1 will impose on low-income households, as much of the negative effect of the bill will be experienced through loss of benefits like healthcare and food assistance. Additionally, the estimates in the CBO report do not consider how other current policies such as tariffs (projected to cause price increases equivalent to a $1,900 to $7,600 loss in average disposable income per household), or how the indirect impacts of the H.R. 1 legislation on society (such as through increased debt service, macroeconomic effects, and potentially catastrophic, community-wide losses of healthcare coverage), will ultimately impact families at different income levels and across different neighborhoods in Connecticut.

The above panel of maps shows how H.R. 1’s effects are distributed across income groups and towns. Each of these maps shows the average annual effect for the top 25 percent, middle 50 percent, and bottom 25 percent of households by household income.

The right map indicates that low-income households in most towns will be negatively affected by H.R. 1. The middle map shows that although H.R. 1 will affect middle-income households on average across all towns, these benefits will be less than $3K per year in most towns. Middle-income households in 70 percent of towns will receive less than $2K per year in tax relief, and in 16 towns they will receive less than $1K per year. The left map shows that the benefit of H.R. 1 will be heavily skewed toward the top 25 percent of each town’s income distribution. In 23 towns, high-income households will save more than $18K per year on average. In four towns – Greenwich, Darien, New Canaan, and Westport – high-income households will see tax relief of more than $30K per year on average. The top quartile of household incomes in these towns is comprised of households whose incomes are in the top two percent of the national household income distribution.

This next panel of maps shows the total effect of H.R. 1 by town. These maps take into account the household populations of each town. The left map shows that a disproportionate share of the additional money flowing to Connecticut households due to H.R. 1 will go to high-income households in the southwest part of the state, especially in Stamford ($195 million for high-income households), Greenwich ($173 million), Norwalk ($116 million), and Fairfield ($116 million). The right map shows that for most towns, the lowest-income 25 percent of households living in that town will experience a negative effect from the legislation.

Overall, the towns seeing the largest tax relief in the aggregate will be Greenwich ($262 million), Stamford ($239 million), Fairfield ($158 million), Norwalk ($143 million), Westport ($121 million), and West Hartford ($121 million), even though the bottom 25 percent of households across those 6 towns will collectively lose $12 million. Households in the state’s largest city, Bridgeport, will receive only $60 million in total, with $61 million in tax relief flowing to high-income households in that city, while the bottom 25 percent of households living in Bridgeport lose over $14 million.

Additional Interactive Maps and Data

Click here for a downloadable Excel spreadsheet with estimates for Connecticut towns, COG areas, and the state, and by income group within each area.

Discussion

The findings in this report indicate that H.R. 1 will considerably exacerbate the problem of rising income inequality in Connecticut, which has been increasing in the state since 1970. And even if H.R. 1 is eventually repealed, the impact on wealth inequality is likely to be permanent.

One way that wealth inequality appears at a community level is through unequal access to public infrastructure, such as quality parks and libraries. Wealthier towns and neighborhoods often have more money and political influence to dedicate towards maintaining high-quality public spaces. For example, in Greenwich, 93 percent of adults say their parks are in good condition and the town spent $182 per person on libraries in 2021, while in nearby Bridgeport, only 56 percent of adults report good-quality parks, and library spending was just $58 per person.

Resource gaps are closely tied to differences in health and longevity as well. According to the 2023 Fairfield County Community Wellbeing Index, adults under the age of 75 living in Bridgeport lost years of life at a rate more than three times higher than those in Greenwich, reflecting sharp differences in community investment. The disparity widened by H.R. 1’s impacts on tax policy could be further compounded as H.R. 1 also causes tens of thousands of area residents to lose access to healthcare and food assistance.

Increasing wealth inequality can also contribute to the state’s housing affordability and homelessness crisis, and reduce social mobility.

We encourage policymakers to use this report and data to understand and remedy the disparate impacts that H.R. 1 will have on their constituents.

Methodology

Estimating the effects of H.R. 1 on Connecticut towns consisted of two steps: estimating national income percentiles for each Connecticut household and mapping these percentiles to a distribution of H.R.1 effects. 

Estimating income percentiles for Connecticut households

Connecticut households were ranked according to where they fall on the national household income distribution. ACS PUMS data for 2019-2023 was used to create a table of household-size adjusted household incomes by percentile for the United States.

Next, the ACS summary table B19001 was used to estimate household incomes for each Connecticut town. This data provides counts of households by income bin (less than $10K, $10K-$20K, ect.). The binsmooth R package was used to estimate samples of exact incomes from these counts. 

These incomes were adjusted for household size. First, shares of household sizes (1, 2, and 3 or more) were calculated for each PUMA. Then, each town’s incomes were divided into groups by household size based on the household size distribution of the PUMA in which the town is located. The incomes were adjusted by household size by dividing by the square root of the household size. 

Finally, each household’s percentile was calculated from its size-adjusted income based on the percentiles of the national income distribution. 

Mapping from income percentile to H.R.1 effect

The CBO report provides ten estimates, the average H.R. 1 effect for each decile of the household income distribution. These CBO estimates are based on results from a microsimulation study from the Joint Committee on Taxation.

These estimates were used to plot coordinates of the cumulative share function of the H.R. 1 effect. This function is also known as the Lorenz curve.

These points were then interpolated to get the H.R. 1 effect cumulative share as a function of the household income percentile. The reason for using the cumulative share function is that CBO’s estimates can be converted into points on this function. For example, CBO estimates an average effect of -$1,214 for the bottom decile. This can be divided by the sum of the average effects of each decile to get -.056, the share of the bottom bin. The cumulative sum of the effects can be divided by the sum of all ten effects to plot points along the cumulative share function.

This plot shows the degree to which H.R. 1 disproportionately benefits the top decile, which is estimated by CBO to receive about 63 percent of the H.R. 1 benefit. This indicates that the distribution of H.R. 1 benefits, like the distribution of income, is right skewed. This poses a challenge for interpolation. The interpolated function must have two properties: first, the effect should increase from left to right along the range of percentiles. We can ensure this by fitting convex quadratic functions to each pair of points. Second, the slope of the function for the top bin should increase at an increasing rate to capture the right skew of the distribution. This is approximated by manually adding points, represented by the blue points below. The points are interpolated with a set of convex quadratic polynomial functions using the schumaker R package. The image below shows the interpolated function.

The black dashed line shows how the Schumaker method interpolates the top bin by default. This creates a discontinuity in the slope increase of the interpolated function. The blue points result in a function whose slope increases more smoothly. These additional points have no bearing on the total or average effect within the top decile. Rather, these points influence the distribution of effects within the decile (reducing the incomes closer to the 90th percentile and increasing the incomes closer to the 99th percentile).

H.R. 1 effects can be calculated from this function by multiplying the derivative at any point along the curve by the average effect, which can be calculated from the CBO estimates. The plot below shows the distribution of effects by percentile.

Finally, an H.R. 1 effect is assigned to each household based on its percentile.

The income groups for each town are based the town’s 25th and 75th household income percentiles. The percentile levels that determine the income groups vary considerably by town. For reference, in Connecticut as a whole, the bottom 25% of households by income earn less than $46,000, the middle 50% earn between $46,000 and $167,000, and the top 25% earn $167,000 or more.

The DataHaven website was redesigned by Studio Kudos in November 2025. Stay tuned to our social media pages for more information on how to navigate the new site!

Previous versions of the DataHaven website included:

By using a scientific, random-sample approach, the DataHaven Community Wellbeing Survey (DCWS) produces reliable local data for every Connecticut city and town, along with detailed insights about adults of different backgrounds and life experiences that no other public source provides. Drawing on interviews with more than 50,000 randomly selected adults across every ZIP code, the DCWS is believed to be the largest neighborhood-level quality-of-life survey in the United States.

The DCWS is informed by an Advisory Council of several hundred individuals representing organizations across the state, and has received financial support from over 100 public and private partners. Quantitative and qualitative data from the DCWS have been featured in hundreds of publications about all aspects of quality of life in Connecticut, including DataHaven’s Town Equity Reports and regional reports, as well as in many community health assessments and federal grant applications.

Quick Links

2025 DataHaven Community Wellbeing Survey (Wave 8)

Wave 8 of the DCWS completed in-depth interviews with 1,371 randomly-selected adults in every Connecticut town from August to October 2025. The first set of DCWS results were published on November 6, 2025, and may be found below.  Unlike our larger survey waves that produce granular town- and regional-level estimates, the 2025 DCWS was mostly designed to produce detailed statewide estimates as well as data for smaller population groups within the state.

2025 Survey Results

Additional results from the 2025 DCWS will be released later this fall and next year. An Excel version of the Connecticut Crosstabs is available on request. Please contact DataHaven for more information.

2024 DataHaven Community Wellbeing Survey (Wave 7)

Wave 7 of the DCWS completed in-depth interviews with 7,458 randomly-selected adults in every Connecticut town. The first set of DCWS results were released on November 25, 2024 and may be found below. DataHaven has distributed detailed results by neighborhood, town, and region to community partners throughout the state; please contact us with inquiries.

In 2024, DataHaven also worked with local partners to field a 2024 Community-Based Assets and Needs Survey (CBANS), which was designed to collect data with specific population groups. Results from the CBANS are not directly comparable to the population-based results from the DCWS, even though many of the questions are identical.

2024 Survey Results

2022 DataHaven Community Wellbeing Survey (Wave 6)

DataHaven fielded a sixth wave of the survey in summer 2022. The 2022 DCWS interviewed 1,196 randomly-selected residents throughout Connecticut, as it was mostly designed to produce state-level estimates, unlike our larger surveys that produce town- and regional-level estimates. Results are also included in the 2023 DataHaven Community Wellbeing Index reports.

2022 Survey Results

2021 DataHaven Community Wellbeing Survey (Wave 5)

From June to December 2021, DataHaven completed Wave 5 of the DataHaven Community Wellbeing Survey with support from dozens of hospitals, charitable organizations, and public agencies throughout Connecticut. The 2021 survey involved live interviews of 9,139 randomly-selected Connecticut residents in every town. Results are also included in the Town Equity Reports, Community Wellbeing Index reports and Community Health Needs Assessment reports published throughout the state in 2022 and 2023.

2021 Survey Results

2020 DataHaven Community Wellbeing Survey (Wave 4)

DataHaven fielded a special “COVID-19 rapid response” wave of the statewide DataHaven Community Wellbeing Survey (DCWS) by conducting live, in-depth interviews of 1,108 randomly-selected Connecticut adults from late July to mid-August 2020. Unlike larger-scale waves of the DCWS, this “rapid response” wave of the DCWS had a shorter questionnaire and was focused on estimating statewide trends by community type and demographic group, but not on measuring conditions within specific neighborhoods or small towns. Due to the smaller sample size of the 2020 DCWS wave as compared to the large-scale 2015 and 2018 DCWS waves, results should be compared to past years with caution.

2020 Survey Results

2018 DataHaven Community Wellbeing Survey (Wave 3)

In 2018, over 16,000 randomly-selected adults in every town in Connecticut participated in live, in-depth interviews. Support for the survey was provided by more than 80 public and private partners throughout the state.

2018 Survey Results

2015 DataHaven Community Wellbeing Survey (Wave 2)

In 2015, DataHaven expanded the Community Wellbeing Survey to encompass the entire State of Connecticut (as well as a small section of New York State), while retaining its mission to produce high-quality neighborhood-level and regional estimates for areas including Greater New Haven, Greater Bridgeport, Lower Fairfield County, Greater Hartford and New Britain, Southeastern Connecticut, the Naugatuck Valley, and other areas. The program completed in-depth interviews of nearly 17,000 randomly-selected residents in 2015.

2015 Survey Results

2012 DataHaven Community Wellbeing Survey (Wave 1)

The 2012 Community Wellbeing Survey asked 1,307 randomly selected adults living in New Haven and 12 surrounding towns what they thought about a variety of issues related to well-being, quality of life, and public health. Concurrently, an additional 1,300 residents in six New Haven neighborhoods were randomly selected and interviewed in person through a survey conducted by the Community Alliance for Research and Engagement.

2012 Survey Results

DataHaven Community Wellbeing Survey Research Advisory Committee and Advisory Council

The survey is developed with input from a Research Advisory Committee as well as an Advisory Council. The survey uses validated questions from national and international surveys to allow comparisons to benchmark data.

From 2018 through 2024, the Research Advisory Committee has included experts in survey research and epidemiology such as Sue Starkey, Northeast District Department of Health; Don Levy, Siena College Research Institute; Amanda Durante, Connecticut Department of Public Health; Brita Roy, Yale University; Byron Kennedy, New Haven Health Department; Mark Abraham, DataHaven; Jennifer Calder, Stamford Health Department; Lisa Morrissey, Danbury Health Department and Bridgeport Health Department; Russell Melmed, Ledge Light Health District and Chatham Health District; Amy Carroll-Scott, Drexel University; Tung Nguyen, City of Hartford; Brian Weeks, New Haven Health Department; Shayna Cunningham, University of Connecticut; Kathleen Duffany, Yale University; Emily Wang, Yale University; Victor G Villagra, University of Connecticut; Gregg Gonsalves, Yale University; Danya Keene, Yale University; Jane Ungemack, University of Connecticut.

Advisory Council members include representatives from approximately 300 different public agencies and private organizations throughout the state, representing a wide range of interests. Anyone may join the Advisory Council. Please sign up for our e-newsletter (at the bottom of this page) to receive invitations to the next round of Council meetings.

DataHaven Community Wellbeing Survey Funders

Please see our list of sponsors and partners. Please contact us to learn more.

This brief report, published by DataHaven and The Connecticut Immigrant Support Network, summarizes the impact of immigrants on Connecticut’s economy.

Immigrants play a critical role in supporting the Connecticut economy by filling crucial labor gaps, creating new businesses, contributing to state and local tax revenues, and supporting the state’s economy. For example, immigrants make up 15% of the state’s population but hold about 20% of all jobs. Immigrant workers are critical to sectors like construction, agriculture, health care, and early childhood education, and also account for 26% of the state’s entrepreneurs. It also notes that immigrant-led households in Connecticut wield approximately $22 billion in spending power, which supports businesses and jobs across the state.

PDF of report. See main report page for more information.