Inequality in New York City Neighborhoods, 1990-2015

This blog post consists of a collection of maps and graphs examining the changes in economic inequality throughout neighborhoods in New York City. The maps were inspired by Daniel Kay Hertz’s fantastic series of maps visualizing inequality in Chicago. See also my previous maps examining the change in income inequality in San Francisco. To create these maps and graphs, I used census block group data from the National Historical Geographic Information System. 

Rising economic inequality has been well documented both in New York City and throughout the nation. This post takes a look at one specific consequence of that rise in inequality: the decline of middle-class neighborhoods in New York City. The map below visualizes this decline from 1990 to 2015. Middle-income areas are colored in light-grey, upper-income areas in shades of green, and lower-income areas in shades of red. Because this map is so large it can be hard to see changes in individual neighborhoods, so throughout the rest of this post are maps for each of the five boroughs of New York City.


In 1990, 40% of New Yorkers lived in middle-income areas, but by 2015 that number had dropped to 35%. This decline has not been uniform across NYC, but has instead varied widely between the five boroughs. Manhattan and The Bronx have seen many of their middle-class neighborhoods decimated, with less than 20% of their population residing in these areas by 2015. Queens and Brooklyn saw smaller, but still significant, declines in middle-class areas. Staten Island was the one borough to defy this trend, with a larger share of residents living in middle-class areas in 2015 than in 1990.

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The share of New Yorkers living in upper-income neighborhoods increased during this period, going from 14% of the City’s population in 1990 to 18% in 2015. The number of people living in lower-income neighborhoods stayed relatively stable, at 46% in 1990 and 47% in 2015. However, once again these changes varied sharply between boroughs, with Manhattan and Brooklyn seeing large increases in the share of individuals living in upper-income neighborhoods, while Queens, The Bronx, and Staten Island have instead seen growth in lower-income neighborhoods. 

This post will examine trends in neighborhood income inequality for each of the five boroughs, going in order of their population size. Brooklyn will start, followed by Queens, Manhattan, The Bronx, and finally Staten Island. A few conclusions and final thoughts follow. The methodology, which describes how lower-income, middle-income, and upper-income areas were defined and measured, is located at the bottom of this post.


Of the five boroughs, Brooklyn’s neighborhoods are most representative of the city as a whole, at least in terms of income. There are still some notable differences however. 56% of the population lives in lower-income neighborhoods, which is 9 percentage points higher than the city as a whole. In contrast, only 11% of Brooklynites live in upper-income neighborhoods, compared to 18% for the entire city.  The share of the population living in middle-income neighborhoods is very similar at 33% for Brooklyn vs. 35% for the City. Brooklyn has slightly poorer neighborhoods than the rest of the city, but this gap has declined over the past 25 years.

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Since 1990 the share of Brooklyn residents living in upper-income neighborhoods has more than doubled, from 5% of the population in 1990 to 11% in 2015. This gain has come at the expense of both lower-income and middle-income neighborhoods. Interestingly, the growth of upper-income neighborhoods in Brooklyn has come entirely in the last 15 years. Between 1990 and 2000, the share of people living in upper-income neighborhoods was stable, as seen in the graph above. But after 2000 the population of upper-income neighborhoods rose sharply.


This rapid rise in the number of upper-income neighborhoods is tied to the gentrification of north-west Brooklyn. Neighborhoods such as Gowanus, Red Hook, Boerum Hill, and northern Williamsburg have undergone massive transformations in a relatively short period of time, going from lower-income or middle-income neighborhoods to some of the highest-income areas in the city. This transformation can be observed in the map above, as the red and grey areas between Park Slope and Manhattan disappear into a sea of green. 


Queens is the most middle-class borough in New York City. Well over a million Queens residents live in middle-income areas, 54% of the borough’s total population. Still, a significant chunk of Queens’ population, 33%, live in lower-income areas. However, unlike other borough’s in the city, the majority of low-income areas in Queens have median incomes just on the edge of middle-class status. These neighborhoods could be thought of as “lower middle-class” or “working-class”. Likewise, the majority of upper-income areas in Queens are not super-rich, but instead have median incomes only slightly above middle-class status. Thus, very few neighborhoods in Queens are intensely rich or extremely poor, which suggests that income inequality in Queens is significantly lower than in the rest of the city.

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Despite Queens’ relatively low levels of inequality, since 1990 it has still seen a decline of 7 percentage points in the proportion of it’s population living in middle-class neighborhoods. The percentage of the population living in upper-income areas has also declined by 3 percentage points. In their place, many more residents are living in lower-income areas, although as noted earlier these areas are usually not intensely impoverished. It may be that Queens has become a refuge for those priced out of other parts of New York City, which could explain this rise in the proportion of the population living in lower-income neighborhoods.


Neighborhoods in Queens have seen relatively subtle changes in income status over the past 25 years. One of the few changes visible in the map above is that lower-income areas around Flushing and Jamaica have grown in size. A more general change can also be seen throughout Queens, as large areas that had been almost entirely middle-income, such as Middle Village, Woodhaven, and Ozone Park, have seen bits and pieces of territory shift out of the middle-income category. These neighborhoods, after being almost entirely middle-income in 1990, became patchworks of low-income, middle-income, and high-income areas by 2015. Still, it is difficult to see many dramatic changes in these neighborhoods, especially compared to some of the neighborhood transformations in Brooklyn or Manhattan. 


Manhattan’s neighborhoods look drastically different from the rest of the city. The borough is starkly divided between lower-income and upper-income neighborhoods, with very few middle-income neighborhoods in between. The share of residents living in upper-income neighborhoods is particularly large, at 47%. Of all New Yorkers who live in upper-income neighborhoods, more than half live in Manhattan, despite the borough having less than 20% of the total population of New York. This concentration of upper-income neighborhoods becomes even more stark when looking at extremely high-income neighborhoods, defined as those neighborhoods with a household median income over 200% of the metropolitan area median income (this translates to neighborhoods with a median income of over $137,500 dollars in 2015). Over 80% of the New Yorkers living in these extremely high-income areas reside in Manhattan. 

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By 1990 Manhattan already had a much smaller number of middle-class neighborhoods compared to the other boroughs, but even these few middle-class neighborhoods have shrunk rapidly. 29% of residents lived in middle-income areas in 1990, but by 2015 the number had dropped to 18%. Likewise, the share of the population living in low-income areas dropped from 47% to 35%. The share of the population living in upper-income areas has skyrocketed, and is well on it’s way to becoming a majority within the next few years.


Those middle-income areas that remain are mostly positioned as thin buffers between intensely high-income and intensely low-income areas, such as a few blocks located between Midtown and the Lower East Side, or middle-class pockets wedged between the Upper East/Upper West sides and Harlem. Middle-income neighborhoods that existed in 1990, including portions of the Upper West Side and Midtown, have rapidly transitioned into high-income areas. Lower-income areas around Washington Heights, Harlem, and the Lower East Side have all shrunk dramatically over the past 25 years. This dramatic transformation of Manhattan shows no signs of slowing down.

The Bronx

As of 2015, The Bronx has by far the largest number of people living in low-income areas compared to the rest of the city, at 77%. Additionally, 46% of the Bronx population lives in “extremely low-income” neighborhoods, defined as those where the median household makes less than 45% of the metropolitan area median income. In 2015, this meant that the median household income in “extremely low-income” areas was less than $31,000 a year. There are still some middle-income areas in the Bronx, but they only contain 18% of the population. A handful of upper-income areas contain another 5% of the population.


Since 1990, the number of individuals living in low-income areas increased by 8 percentage points, while the number living in middle-income areas dropped by 8 percentage points, and the number in upper-income areas remained stable. Nearly all of the jump in the number of people living in low-income areas occurred between 1990 and 2000. Since 2000 the low-income portion of the population has stayed flat, while the % of the population living in middle-income areas has slowly dropped and the % living in upper-income areas has slowly risen. This suggests that the already-small number of middle-class neighborhoods in the Bronx are in danger of shrinking even further.


The Bronx is starkly divided geographically, with the south-western portion of the borough composed almost entirely of low-income areas, while the eastern portion of the borough has more middle-income and high-income areas. There is also a pocket of high-income areas in the neighborhood of Riverdale in the north-west corner of the borough. Between 1990 and 2015, the main geographic change visible was the transition of some portions of the eastern section of the borough from middle-income to low-income. The neighborhood of Allendale is a good example of this, as in 1990 only the western edge of the neighborhood was low-income, wheareas by 2015 most of the neighborhood had transitioned. The western half of the borough remained more stable, with south-west neighborhoods like Belmont, Highbridge, and Mott Haven remaining solidly low-income, while Riverdale remained mostly high-income.

Staten Island

Staten Island’s neighborhoods have a very different income distribution from the rest of the city. Only 14% of Staten Island residents live in low-income neighborhoods, far lower than any other borough. 51% of the population lives in middle-income neighborhoods, second only to Queens, and 35% of the population lives in upper-income neighborhoods, second only to Manhattan. The island has a relatively low level of inequality compared to the rest of the city, and is generally on the wealthier side. 

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Not only is the current composition of Staten Island radically different from the rest of the city, but it has also been subject to very different trends. The broadest trend across the rest of the city has been a decline in the number of people living in middle-income areas, and an increase in the number living in high-income areas. In Staten Island, this trend has been reversed: The number living in middle-income areas grew by 12%, while the number living in high-income areas declined by 14%. It seems that incomes did not grow as quickly in Staten Island as in the rest of the city, meaning that many high-income areas slid back into middle-income status. 



No Staten Island neighborhoods saw the dramatic swings in income that areas in Manhattan and Brooklyn saw. Even the more subtle changes seen in The Bronx and Queens are hard to pick out in Staten Island. One visible trend is that Southern Staten Island had been mostly green in 1990, but by 2015 the area had transitioned to a mix of upper-income and middle-income areas. Areas scattered across the island went from being light green, representing the lowest category of upper-income, to being grey for middle-income areas.


New York City as a whole has seen a rise in upper-income neighborhoods, and a decline in middle-income neighborhoods, but this trend has varied greatly between boroughs. Some parts of the city, including portions of Brooklyn and Manhattan, have seen rapid increases in the number of upper-income neighborhoods due to gentrification and the pricing out of lower-income residents. Other boroughs, including Queens and the Bronx, have been more stable and seen less dramatic changes in their income composition, although their middle-class neighborhoods have also declined in numbers. Staten Island in many ways is the outlier, as it’s middle-class residents have grown while the number living in high-income neighborhoods.

Making predictions is always dangerous, but it certainly seems as if Manhattan will continue on it’s path towards becoming homogenously upper-income. Brooklyn has farther to go, but is being effected by many of the same forces as Manhattan. As more census data is released, it will be critical to see whether areas in Queens, the Bronx, and Staten Island begin to be affected by these same forces, or if these boroughs will remain bastions of middle-income and low-income neighborhoods. The effects of these changes in the city will continue to ripple out into the rest of the Tri-State Area, as more residents are priced out and move to other nearby cities and suburbs.


The incomes of areas/neighborhoods were measured using census block group data, with the household median income of each block-group compared to the household median income of the New York City metropolitan area. Block-groups where the median income was less than 75% of the metropolitan area median income were defined as lower-income, 75-125% was defined as middle-income, and areas with 125% or more of the metropolitan area median income were defined as upper-income. 

It is important to note that these figures represent the number of people living in each type of neighborhood, rather than the number of households that are themselves lower-income, middle-income, or upper-income. For example, 35% of New Yorkers live in middle-income areas as of 2015, which is different than saying that 35% of New Yorkers are middle-income themselves. These two concepts are strongly related, but not equivalent to each other. You could, theoretically, have an upper-income neighborhood with a large minority of lower-income residents. This neighborhood would be classified as upper-income under my system, even though a large portion of it’s residents live in poverty. Or you could have a neighborhood with roughly even proportions of lower-income, middle-income, and upper-income residents, which would make the neighborhood a middle-income neighborhood even though most of it’s population was not middle-income. However, research has shown that neighborhoods are becoming increasingly homogenous, meaning that upper-income neighborhoods have fewer and fewer poor residents, and lower-income neighborhoods have fewer and fewer rich residents (


Best-Selling Album by Year, 1992-2016

Top-Selling Albums

This chart shows the best-selling album by year from 1992 to 2016. Only albums sold within each year are counted.  Since it’s the best-selling album within a year, it often helps for an album to be released earlier in the year, since it then gets the more months of sales. Some albums which were the best-selling in a certain year were actually released the previous year, such as Jagged Little Pill by Alanis Morissette, which was released in 1995 but was the best-selling album of 1996. Another example is 21 by Adele, which was released in 2011 but was the best-selling album in both 2011 and 2012.



Projected Healthcare Coverage Loss under the Senate Republican Healthcare Bill, by US State

Healthcare Losses

This map shows the projected net drop in the number of people with healthcare coverage by 2026 as a percentage of each state’s projected 2026 population. The non-partisan Congressional Budget Office estimated that the Better Care Reconciliation Act (BCRA), the Senate Republican’s version of the healthcare bill, would increase the number of people without insurance by 22 million people in 2026, relative to current law.  The Center for American Progress, a progressive think-tank, then created their own estimates of how this 22 million drop in coverage would be distributed across the US.

I took these state by state projected coverage losses and divided them by the population of each state in 2026 to get the net % of the state’s population that would lose coverage. I was unable to find a projection for the 2026 population, but the Cooper Center had population projections for each state for both 2020 and 2030, so I used those to create an estimate for the 2026 population. This projection will obviously not be exact, but it should only affect the estimates on the margins.

North Carolina would see the largest share of their population lose coverage under the BCRA, with 1,348,300 people losing coverage, equaling 12.1% of the state’s 2026 population. The majority of southern states would be hit hard with coverage losses, as would north-western states like Nebraska, Wyoming, Idaho, Montana, and Alaska. The Southwest, Midwest, and New England would see smaller losses as a share of their population, although Vermont and Maine would lose a lot of coverage. North Dakota would see the smallest reduction, a loss in coverage for 25,100 people, 2.8% of the state’s 2026 population.

State Net Coverage Loss by 2026 2026 Population % of Population losing Coverage
Alabama 480,500 5,022,882 9.57%
Alaska 64,500 799,748 8.07%
Arizona 461,000 7,825,693 5.89%
Arkansas 172,400 3,108,621 5.55%
California 2,483,000 43,340,158 5.73%
Colorado 240,100 6,462,721 3.72%
Connecticut 206,800 3,623,350 5.71%
Delaware 59,500 1,052,949 5.65%
District of Columbia 41,200 847,324 4.86%
Florida 2,086,500 23,692,297 8.81%
Georgia 963,200 11,392,280 8.45%
Hawaii 58,200 1,590,275 3.66%
Idaho 144,700 1,850,456 7.82%
Illinois 654,800 12,912,550 5.07%
Indiana 270,400 6,903,913 3.92%
Iowa 127,900 3,287,772 3.89%
Kansas 198,200 3,033,930 6.53%
Kentucky 231,400 4,603,890 5.03%
Louisiana 343,000 4,963,945 6.91%
Maine 117,900 1,330,507 8.86%
Maryland 227,400 6,513,263 3.49%
Massaschusetts 285,300 7,328,967 3.89%
Michigan 489,400 9,996,796 4.90%
Minnesota 217,600 5,889,676 3.69%
Mississippi 278,000 3,042,504 9.14%
Missouri 479,000 6,279,214 7.63%
Montana 81,100 1,128,361 7.19%
Nebraska 173,100 2,047,640 8.45%
Nevada 122,500 3,327,906 3.68%
New Hampshire 45,500 1,359,273 3.35%
New Jersey 418,300 9,303,740 4.50%
New Mexico 133,400 2,138,070 6.24%
New York 1,139,000 20,670,766 5.51%
North Carolina 1,348,300 11,173,353 12.07%
North Dakota 25,100 899,823 2.79%
Ohio 469,600 11,765,616 3.99%
Oklahoma 395,100 4,261,102 9.27%
Oregon 283,300 4,468,784 6.34%
Pennsylvania 731,000 13,002,441 5.62%
Rhode Island 45,800 1,063,341 4.31%
South Carolina 458,000 5,505,311 8.32%
South Dakota 63,700 957,376 6.65%
Tennessee 634,600 7,153,339 8.87%
Texas 2,430,600 33,007,950 7.36%
Utah 186,000 3,541,234 5.25%
Vermont 51,200 626,280 8.18%
Virginia 521,800 9,225,884 5.66%
Washington 298,700 8,186,933 3.65%
West Virginia 118,100 1,825,027 6.47%
Wisconsin 394,100 5,944,911 6.63%
Wyoming 49,000 635,003 7.72%

NBA Win-Share Charts,


I last looked at each NBA team’s win-share charts in Mid-December, see this link to look at those older versions of the charts.

These charts look at each team’s distribution of “win shares” across players. Win Shares are a measure of a players total contribution to a teams success, as explained here:

A few notes:

-If you don’t see a player listed in the win-share pie chart, it’s because they either have 0 win shares or negative win shares.

-The change in win-shares is stated as being from December 15th to February 15th. That is slightly incorrect, as the change is actually measured from December 8th to February 16th.

-Obviously a lot of the changes in win-shares for players come from players being injured or traded. However, there are still some large changes in the win-share % of certain players who did not suffer any major injuries. See Anthony Davis as an example in New Orleans, who’s percentage of the team’s win-shares has dropped sharply as other contributors have picked up some of the slack for him.

-The change in a players win-share percentage is sometimes greater than their total win-share percentage. This is for one of two possible reasons:

1. In Mid-December those players had a negative win-share total.

2. It is an artifact of the fact that I could not include players with negative win-shares in the pie charts. I made the mistake of including those players when calculating the change in each players win-share %, which meant that players who were on a team with lots of negative win-share players saw their percentages inflated, since the total number of win-shares on the team was lower. I probably shouldn’t have calculated them this way for consistency’s sake, but by the time I realized it was too late and I was too lazy to go back and change everything.



NBA Championship Run Win-Share Charts, 1990-2016

These charts look at each NBA champion’s distribution of “win shares” across players during their playoff runs. Win Shares are a measure of a players total contribution to a teams success, as explained here:

Some players on a championship team are not listed, either because they had negative win shares, a net of zero win shares, or did not play in the playoffs.

Some random observations on a few team’s championship team’s win-share distributions:

2014: The Spurs player with the most win-shares during their 2014 run was Tim Duncan, at 17% of their win-share total. This is by far the lowest percentage for any championship team’s top player. The 2014 Spurs really live up to their reputation as a team that shared the ball and had everyone contribute, as 6 different players had over 10% of the team’s playoff win shares apiece.

2013: This is the most recent year where the top player on a championship team had over 30% of the team’s playoff win shares (Lebron obviously). Interesting to note that the “Big Three” according to win-shares for this playoff run was not Lebron, Bosh, and Wade, but actually Lebron, Bosh, and Andersen. Wade had a bit of a down playoffs, and the Birdman was able to sneak into the top three in win shares.

2012: Like in 2013, one of the “Big Three” didn’t make the Heat’s top three in win-shares. In this case, the Big Three was Lebron, Wade, and Mario Chalmers, with Bosh falling to fourth in win-shares during this playoff run.

2004 Pistons: This is one of the most unique win-share distributions of any championship team. Chauncey Billups led the team with 20.4% of their playoff win shares (only Duncan on the 2014 Spurs had a lower % of win shares as the top player on a championship team), but Ben Wallace also had 20% and Richard Hamilton 19.4%. That means there was only a 1% difference between the top player and the third player in win-shares, by far the lowest of any team. This is one of the few championship teams without a clear-cut top player, or even top two players.

2003 Spurs: This was a very un-Spursy Spurs team, with Duncan carrying a massive load with little help at 34.9% of all the team’s playoff win-shares.

2000 Lakers: Shaquille O’Neal had the highest win-share % on any championship run, at 35.3%. During this playoff run Kobe wasn’t quite on his level yet, at only 15.8% of the team’s playoff win-share total.


NBA Win-Share Charts, as of 12/8/2016

These charts look at each team’s distribution of “win shares” across players. Win Shares are a measure of a players total contribution to a teams success, as explained here:

Some of the teams with interesting win share distributions:

New Orleans Pelicans: Anthony Davis has 42% of all New Orleans’ win shares, the highest % for any player. The next highest player on the Pelicans is Tim Frazier, all the way down at 9%.

Detroit Pistons: Andre Drummond has the most win shares on the Pistons, but this is only 18% of the teams total, which is tied for the lowest % for the top player on a team. The Pistons have a very egalitarian distribution of win shares, with 5 players having above 10% of the total win shares.

Denver Nuggets: The Denver Nuggets has two players tied for the most win shares on the team, both also at 18%: Danilo Gallinari and Kenneth Faried. The player with the third-most win shares, at 17% of the total, is Wilson Chandler, while Nikola Jokic has 16%. Thus the gap between the player with the fourth-most win shares, Jokic, and the player with the most, Gallinari, is only 2 percentage points, by far the lowest in the league.


Third-Place Candidate, by county, 2016 Presidential Election


The map above uses preliminary results from the 2016 US presidential election to show the third-place finisher in the presidential election in each county. In almost every county the top two candidates were Donald Trump and Hillary Clinton (with the exception of several extremely conservative and heavily mormon counties in Utah and Idaho where Hillary fell to third behind Independent Evan McMullin).

The Libertarian ticket of former New Mexico Governor Gary Johnson and former Massachusetts Governor William Weld received 3.3% of the nationwide popular vote, over 4 million votes total, which was by far the strongest performance of a third-party this year. It was also the best result for a third-party since Ross Perot’s Reform Party run in 1996. This success is evident on the map, as the Johnson ticket reached third-place in the vast majority of counties in the US.

Jill Stein of the Green Party came in fourth in the national popular vote with 1.3 million votes (1%). She was only able to reach third-place in a handful of counties. Among these were several major cities, including Portland, San Francisco, Oakland, and New York City (she had more votes than Johnson in every borough except Staten Island). She was also the strongest third-party candidate on most of the islands of Hawaii (and the San Juan islands of Washington state), part of the northern coast of California (Humboldt and Mendocino counties), and two Native American reservations in North Dakota and one reservation in Wisconsin, along with a couple of other counties.

Evan McMullin is an interesting case. He ran as an independent conservative, hoping to gain the votes of Republicans who were unhappy with Donald Trump. However, he entered the race late and was unable to get on the ballot in most states. Additionally, Republican voters ended up coming home to the party, voting in strong numbers for Trump. McMullin, who is LDS, ended up as the “mormon candidate”. Trumps was unpopular among the conservative Mormon population, which allowed McMullin to pull 21% of the vote in Utah and 7% in Idaho. Nationally, he came in fifth, receiving only 0.4% of the vote, but he came closest of any third-party candidate to capturing a state. McMullin actually placed second in several counties in Utah and Idaho, beating Hillary Clinton in those areas, though he placed third overall in both states. Donald Trump did not fall to third in any counties, though he came closest in the District of Columbia, where he received 4% of the vote and write-in’s received 2.5%.

This year also saw an uptick in the number of “write-in” votes. For example, write-ins dominated the third-party vote in Vermont, and these votes were almost certainly  for the state’s own Senator Bernie Sanders. Almost 8% of Vermont voters wrote-in a presidential candidate on their ballot. Write-ins also placed third in one county in western Wyoming, and in the District of Columbia.

Nevada is the only state with a “None of these Candidates” option on the ballot, and it got 2.6% of the vote in that state and won third-place in two rural Nevada counties.

Finally, the Prohibition Party’s candidate, James Hedges, received 5,565 votes nationwide (apparently the best showing for the Prohibition Party since 1988), which comes to 0.00004% of the national vote. Nonetheless, despite this tiny showing, James Hedges somehow came in third in Arkansas County, Arkansas, with 133 votes, beating Gary Johnson’s total by 7 votes.

Several other third-parties ran candidates, such as the Constitution Party (0.14% of the vote) and the Party of Socialism and Liberation (0.04% of the vote), but none of these parties finished third in any counties.