Vacant Land and the Cook County Land Bank

Abstract

A single vacant lot in Englewood is one row in a spreadsheet the City of Chicago keeps. The spreadsheet is the City-Owned Land Inventory, and on the day we pulled it there were 20,732 rows in it. This paper reads that inventory as a public ledger and asks a narrow question. How much of the city's land does the city still hold, and where does the held land sit. The work is a synthesis of published scholarship and our own descriptive count of one real public dataset. We ran no experiment, fit no model, and interviewed no one, and we make no causal claim. The published record establishes that Chicago's vacant land concentrates in historically redlined Black neighborhoods on the South and West Sides, that land banks and dollar-lot transfers are the policy tools built to return that land to use, and that putting lots back in residents' hands yields measurable gains in upkeep and modest reductions in crime. Our count of the city's ledger lines up with that geography. The five community areas with the most city-owned parcels each hold more than a thousand, and Englewood, New City, North Lawndale, West Englewood, and East Garfield Park together account for 34.2 percent of the inventory. The ledger is held-heavy. The city still owns 58.5 percent of the parcels outright and has sold 29.7 percent. Joining the geocoded parcels to the digitized 1938 Home Owners' Loan Corporation map, 61.9 percent of the parcels inside the mapped area fall in zones the federal corporation graded D, the lowest grade, and the ratio of parcels in declining-or-hazardous zones to parcels in best-or-desirable zones is 53 to one. We scope strictly to city land, not the separately governed Cook County Land Bank Authority, and we report the inventory's missing fields in the body rather than hiding them in a note.^[1]

A lot on the West Side, and the ledger it belongs to

There is a vacant lot in Englewood that belongs to the City of Chicago. It does not announce itself. It is grass gone to seed, or a concrete slab where a two-flat once stood, or a fenced rectangle the block has learned to walk past on the way to the bus. What makes the lot legible is not the lot. It is the row the lot occupies in a table the city maintains and posts online. The row carries a PIN, the parcel identification number the Cook County Assessor assigns to every taxable piece of ground in the county. It carries a street address. It carries a property status, one of a short list of values the city uses to record whether a parcel is owned, sold, leased, or no longer city land. It carries a managing organization, the department or program responsible for the parcel. It carries a ward and a community area, the two ways Chicago divides itself, one for politics and one for planning. It carries a latitude and a longitude. And it carries dates, the day the city took the parcel and, if the parcel has left city hands, the day it went.

That row is the unit of this paper. Multiply it by 20,732 and the result is the City-Owned Land Inventory, a machine-readable ledger the City of Chicago Department of Planning and Development maintains and publishes through the Chicago Data Portal on the Socrata platform under the dataset identifier aksk-kvfp.^[1] We pulled the full table on 2026-05-29. Its records were last updated between late December 2025 and early January 2026, so the ledger is recent. Like the books of any working bureaucracy, it is also blank in places, a fact that turns out to govern most of what the numbers can and cannot say, and one we keep returning to for that reason.

A ledger is a dull object. Read closely, it is also a record of decisions. Every parcel the city owns is a parcel the city has not returned to a private use, whether that use would have been a side yard for the house next door, a community garden, a developer's site, or simply a neighbor who wanted the empty lot beside her. Every parcel marked sold is a closed transaction. Every parcel marked leased is land doing something without changing hands. The status field is, in effect, a photograph of a backlog. This paper asks what the backlog looks like when you read the ledger as held against disposed, and where the held land lies.

The question is bureaucratic, and the point of the paper is to make the bureaucracy legible. The city hides none of this. It posts the entire table for anyone with a browser. But twenty thousand rows resist reading at human scale, and the columns that matter most for a civic question are scattered across the file and buried under hundreds of thousands of cells. Our contribution is small and specific. We took the published table, counted it carefully, and joined the parcels that carry coordinates to a digitized 1938 map of Chicago's Home Owners' Loan Corporation grades, the map that came to be known as the redlining map. Then we report what the counting shows. We built nothing predictive. We forecast nothing. We do not claim the 1938 map caused the 2025 ledger. We describe where two geographies overlap and leave the causation to the scholars who have studied it, several of whom carry most of the explanatory weight in the pages below.

One result is worth stating up front, not as a conclusion but as the thread the second half of the paper follows. Of the parcels in the inventory that carry usable coordinates, 92.8 percent sit inside a zone the 1938 redlining map graded.^[1] Hold that figure for now. It has to be earned, which means explaining what the overlay measures, what it does not, how much of the inventory has no coordinates at all, and how much of the modern city the eighty-eight-year-old map even covers. That accounting comes later. The reason to raise the number here is only to mark the through line. The ledger and the old map fall on the same ground.

A note on terms, since the parcel is the atom of everything that follows. In Cook County, a parcel is the legal unit of real property, identified by its PIN and recorded in the Assessor's rolls. A vacant lot is usually one parcel. A larger holding can be several. The City-Owned Land Inventory is a list of parcels in which the city records an interest, and the property status field tells you the kind of interest. When we count parcels by community area, we count these legal units. We do not count acres, and we do not count buildings, and we say which we mean wherever the difference could matter. The inventory does carry lot size in square feet and a recorded land value, but both fields are sparse enough that we treat them as a limit on the analysis rather than a result of it, a point taken up plainly near the end.

The geography that falls out of the counting will not surprise anyone who has read the literature on Chicago's vacant land, and it will not surprise anyone who lives on the South or West Side. The lots cluster where disinvestment clustered. Englewood and West Englewood. North Lawndale and East Garfield Park. New City, Grand Boulevard, Austin. These are the community areas that show up in the city's ledger carrying more than a thousand parcels apiece. They are also the areas that show up across decades of scholarship as the places where vacancy gets studied in the first place. In that sense the ledger is a second draft of a history other people have already written. Our job is to read the draft with care and report what is in it.

The shape of the paper is plain. We set the terms of the work first, because the title names the Cook County Land Bank Authority and the dataset does not, and that gap has to be visible before any number is reported. We then walk the published record on Chicago's vacant land, from the practitioner theory of land banking to the Chicago-specific scholarship that has measured both the disinvestment geography and the outcomes of returning land to use. Only then do we count. We report where the land sits, how much of it is held against disposed, who manages it, how the redlining overlay falls out, and where land actually moves through the disposition pipeline. We close on what the ledger leaves blank and the claims it therefore cannot carry. Every empirical figure is either ours, computed from the published table and tagged to our primary analysis record, or it belongs to a named source.^[1]

What this paper is, and what it is not

The epistemic contract deserves to be stated flatly, because the rest of the paper rests on it. This is a research synthesis plus an original descriptive analysis of one real public dataset. That is all of it. We ran no experiment. We did not build a predictive model, fit a regression, or estimate a treatment effect. We pulled a published table through a public API the City of Chicago maintains for that purpose, so there was nothing to scrape. We interviewed no residents, no aldermanic staff, and no planners, and we ran no survey. Every figure we report from our own work is a count, a share, a median, or a ratio computed over the rows of a single inventory, and every one of them is tagged to our primary analysis record.^[1] Where we report a finding we did not produce, it is attributed to the source that produced it.

The first line to draw is the scope line, and it concerns the title. This paper belongs to a collection about vacant land and the Cook County Land Bank Authority, and the CCLBA is a real and consequential institution. The dataset we analyze is not the CCLBA's inventory. It is the City of Chicago's own City-Owned Land Inventory, a body of municipal land governed by the city's Department of Planning and Development.^[1] The Cook County Land Bank Authority is a separately governed entity, created by the county in 2013, with its own board, its own acquisition pipeline, and its own holdings.^[9] None of those holdings is in the table we read. The CCLBA does publish a public property viewer, but it offers only limited per-record export rather than a bulk machine-readable download, which is to say it is not a dependable anchor for a counting exercise like this one. So we take the honest route. We count the city's land, we name it as the city's land at every point where it could be mistaken for something else, and we cover the CCLBA through the literature and the qualitative record alone.^[9] We do not count the CCLBA here. No number in this analysis should be read as describing it.

Why does the city's inventory belong in a paper that names the county land bank at all? Because the two bodies of land share a geography and a toolbox. The disinvestment that left the city holding thousands of vacant parcels on the South and West Sides is the disinvestment that produced the tax-delinquent and abandoned parcels the CCLBA was built to absorb.^[9] The policy instruments overlap too. Land banking, dollar-lot transfers to neighbors, the cycle of acquisition and rehabilitation and disposition. The city pulls these levers, the county pulls these levers, and the scholarship that evaluates them does not always draw a sharp line between city-owned and land-bank-owned parcels, because the underlying problem runs continuously across both.^[2][4][5] Reading the city's ledger is one way into the question the CCLBA exists to answer, namely what happens to land the market left behind, even though the ledger is not the land bank's.

We make two more promises about handling the data, and we keep them. The first concerns missingness. We report it in line, at the moment a field is used, rather than tucking it into a note. When a field is blank for a large share of parcels, we say so where we use it, and we compute shares over the populated rows instead of pretending the blanks are zeros. The gaps are not trivial. Geography is missing for roughly one parcel in eight. The managing organization is blank for more than half the table. The sales pipeline field is blank for more than half as well. Land value and usable lot size are recorded for a minority of parcels. We do not hide any of this. It is part of the result.

The second promise is about language. We read every number as a description of a pattern, never as proof of a cause. When we write that city-owned vacant land concentrates in a set of community areas, we mean the parcels are counted there. We do not mean that any particular force put them there. When we write that 61.9 percent of geocoded parcels inside the 1938 map fall in formerly redlined zones, we mean the points land inside those polygons across an eighty-eight-year gap, and we mean nothing past that.^[1] The scholarship has done the harder work of establishing why the geography looks as it does, and we defer to it on cause. Our value is a current, reproducible accounting, not an explanation. Holding that line is the only way a descriptive read of a public ledger earns its place, and it is the standard the paper holds to from here on.^[1]

How we read the inventory

The procedure is worth spelling out, because the whole value of a descriptive paper rests on the reader being able to repeat it. We pulled the City-Owned Land Inventory through the Chicago Data Portal's Socrata API, the public interface the city maintains for the dataset aksk-kvfp, on 2026-05-29.^[1] The pull returned the full table, 20,732 rows across 27 columns, with the records' last-update timestamps running from 22 December 2025 to 5 January 2026.^[1] We did not sample, filter, or subset the table before counting. Every figure in the paper is computed over the full pull or over a stated populated subset of it, and the file we worked from is posted alongside the paper so a reader can pull a fresh copy and compare.^[1]

The counts are arithmetic, not statistics. To report the property-status distribution we tallied the values in the property status field and divided by the row total. To rank community areas and wards we grouped on the community area and ward fields and counted rows, dropping the parcels where those fields are blank and saying so. To report the disposition rate of a community area we counted the parcels in that area that carry either a Sold status or a recorded disposition date and divided by the parcels the area holds. There is no weighting, no imputation of missing values, and no model anywhere in the pipeline. Where a field is blank, the blank is excluded from the denominator and the exclusion is named at the point of use, which is why the same parcel total, 20,732, recurs throughout while the denominators under it shift from section to section.

The one step that goes beyond counting is the spatial join, and even that is mechanical. The repository holds a digitized version of the 1938 HOLC map of Chicago as a set of graded polygons. For each parcel that carries a latitude and a longitude, we tested which polygon, if any, contains that point, a standard point-in-polygon operation, and recorded the grade of the containing polygon. A parcel with no coordinates cannot be placed and is excluded. A parcel whose coordinates fall outside every 1938 polygon is recorded as outside the mapped footprint rather than forced into a grade. On the small number of parcels whose point fell on or across the boundary of two polygons, the worse of the two grades was assigned, which for a redlining-persistence read is the conservative direction, since it can only raise the share attributed to the C and D zones and never lower it.^[1] About twenty HOLC polygons in the digitized layer carried no clean A, B, C, or D grade and were left out of the join. None of this is inference. A point is inside a polygon or it is not.

A word on the coordinates themselves, since the join depends on them. The latitude and longitude in the inventory are the city's own, carried in the published table rather than geocoded by us, which means the join inherits whatever accuracy the city's coordinates have and adds none of its own. We treat a parcel as locatable when both coordinate fields are present and excluded it otherwise. That choice is what produces the 18,083-parcel geocoded subset and the 2,649-parcel gap, and it is the same gap that drops those parcels from the community-area and ward rankings, since in this table the rows missing coordinates are largely the rows missing community area and ward as well. The upshot for a reader who wants to check us is that nothing in the procedure requires trust. The table is public, the HOLC layer is in the repository, the point-in-polygon test is a standard operation in any geographic toolkit, and the counts are sums and divisions over named columns. A fresh pull of the same dataset, run through the same steps, should reproduce the figures up to whatever the inventory has changed since our pull date, which is the only moving part we cannot freeze.

What the literature already settled about vacant land in Chicago

It helps to know what is already known before counting anything, because the published record on Chicago's vacant land is deep and our descriptive read mostly confirms it. The literature answers the questions the data cannot. Why the city holds so much vacant land. Why the land is where it is. What happens when the land goes back into use. We move from the practitioner theory of land banking out toward the Chicago-specific evidence, because the theory names the object the ledger is a snapshot of and the local evidence draws the map our count falls on.

The instrument comes first. Alan Mallach's account of abandoned property is the practitioner foundation for why land banks exist.^[2] His argument is institutional, not ideological. Tax-delinquent, abandoned, and vacant parcels pile up faster than ordinary market and legal machinery can clear them. Back taxes mount. Titles cloud. Owners vanish or walk away, sometimes dying without a will, sometimes simply deciding that the building is worth less than the taxes and the repairs it would take to keep it. What remains is a stock of property no private buyer will touch and that local government ends up holding almost by default, not because anyone chose to hold it but because no other actor would take it. A land bank is the device built to break that logjam. It takes title to property the market has abandoned, clears the tangle of liens and clouded titles that keeps the property frozen, and moves it back toward a productive use, so that the parcel becomes a community asset instead of a standing liability.^[2] Mallach's framing matters here because it names what the City-Owned Land Inventory captures. A ledger of thousands of held parcels is exactly the backlog land banking was invented to work down, whether the holder is a municipality or a county authority.

The framing also explains why a held parcel is not the same as a neglected one. Mallach's central observation is that abandoned and tax-delinquent property is sticky in a specific legal sense.^[2] A clouded title, an unpaid tax lien, an unknown or unreachable heir, each of these can freeze a parcel in place for years, because no buyer will close on land whose ownership cannot be cleanly conveyed and no lender will finance a purchase that might later be contested. The market does not reject such parcels because they are worthless. It rejects them because the transaction costs of untangling them exceed what the cleared land is worth, particularly in a neighborhood where comparable land already sells low.^[2] Government inherits the parcel as the actor of last resort, and the inventory of held land is the visible accumulation of that process, parcel by parcel, over years. Read against Mallach, the City-Owned Land Inventory is less a portfolio the city assembled on purpose than a backlog the city absorbed because the alternative was leaving the land in legal limbo.

Chicago's institutional answer to that backlog is the Cook County Land Bank Authority, and the Metropolitan Planning Council's case study is the direct source on it.^[9] The county created the CCLBA in 2013 as a separate governmental authority charged with acquiring, holding, and disposing of vacant, tax-delinquent, and abandoned parcels across Cook County, a portfolio that runs into the tens of thousands of parcels.^[9] Its mandate is the acquisition-rehabilitation-disposition cycle Mallach describes in the abstract, applied to the particular geography of Cook County disinvestment.^[9] The case study is the institutional record of how the county chose to organize the work. It is also the reason this paper can discuss the CCLBA even though the authority's own inventory sits outside our data. We use it for the institutional facts and keep the scope line firmly around it, since the land we count is the city's, not the authority's.

The targeting of that work has a documented history of its own. A collaboration led by the University of Chicago's Data Science for Social Good program, working with the CCLBA and DePaul's Institute for Housing Studies, built an open-source analytics tool to help the land bank decide which vacant and abandoned parcels to pursue.^[10] The effort drew on Cook County Assessor and Recorder records, parcel-level geographic data, Chicago open data, and American Community Survey figures, the same families of public data that make our own counting possible.^[10] Two things are worth carrying away from that project. The public data needed to study Chicago's vacant land is real and usable, which is the premise of this paper. And data-driven targeting of vacancy is an established practice rather than a novelty, which means a descriptive accounting of the city's ledger sits inside a tradition rather than off to the side of one.^[10]

Knowing how a land bank works does not explain why the vacancy sits where it does, and for that the disinvestment scholarship does the heavier lifting. Rea Zaimi's study of Chicago's South Side reframes what the word disinvestment even means.^[3] Working from roughly ten thousand postwar property records in Englewood, the precise neighborhood that tops our own community-area ranking, Zaimi argues that the familiar story of vacancy as a simple withdrawal of capital is incomplete.^[3] In her account the emptying of South Side blocks was not produced by capital quietly leaving. It was produced by predatory, race-linked property relations, the contract sales and speculation and extractive arrangements that targeted Black residents and pulled value out of their neighborhoods before the lots ever went vacant.^[3] The distinction is not academic hairsplitting. A neighborhood that capital merely abandoned and a neighborhood that capital actively mined arrive at vacancy by different routes, and the second route leaves a different residue. Zaimi's reframing changes how we are entitled to read our own count. When the city's ledger shows nearly two thousand vacant parcels in Englewood, the literature tells us those lots are the sediment of a specific history of extraction, not the neutral byproduct of impersonal market forces. We do not re-derive that history. We count its residue and point to Zaimi for what laid it down.^[3]

The link between that history and today's vacancy has also been measured at scale, and the Cook County Treasurer's office did the measuring.^[7] Drawing on the county's Scavenger Sale records, the Treasurer's 2022 study found that parcels inside 1940-era redlined zones are 2.75 times more likely to be distressed today than parcels outside them.^[7] In raw counts, more than 14,000 of the 27,358 vacant or abandoned properties in the Scavenger Sale sat inside 1940 redlined areas.^[7] The Scavenger Sale is itself a piece of the machinery Mallach describes. It is the county's periodic auction of parcels whose owners have fallen so many years behind on property taxes that the ordinary annual tax sale has failed to move them, the last legal stop before a parcel's tax debt is cleared and its title is supposed to change hands.^[7] A parcel that lands in the Scavenger Sale is, almost by definition, a parcel the market has given up on, which is what makes the Treasurer's finding so pointed. More than half of the sale's vacant and abandoned stock sits inside the old redline, eight decades after the lines were drawn.^[7] That is a county-level corroboration of the persistence we observe at the city level, produced independently, from a different dataset, by an office with no stake in our particular count. We treat it as a parallel finding, not a substitute for ours. The Treasurer counted distressed and Scavenger Sale parcels across the whole county. We count city-owned parcels against a 1938 map. The two reads reinforce each other precisely because they are separate. The redlining-to-vacancy link is not our discovery. It is established, and we cite it as established.^[7]

That link has been carried one step further, into health. Chen and colleagues, in a 2026 path analysis of Chicago, find that vacant land and active construction sites concentrate in historically redlined neighborhoods and that this concentration helps account for worse neighborhood mental-health outcomes.^[6] The pathway they trace runs from the historical grade, to the present-day pattern of land use, to the well-being of the people who live among it.^[6] We invoke the study for one narrow purpose. It is independent evidence, from a peer-reviewed analysis using a method we did not use, that vacant land sits disproportionately inside formerly redlined Chicago neighborhoods.^[6] When our own overlay turns up the same co-location, Chen and colleagues are one reason we can say the pattern is not an artifact of our particular file. We borrow none of their causal machinery. We note only that their geography and ours agree.

If the disinvestment scholarship explains why the land sits empty, the disposition scholarship explains what happens when it is returned, and here the evidence is both more encouraging and more directly tied to a program that appears by name in our data. Stern and Lester evaluated Chicago's Large Lots program, the initiative that sells city-owned vacant lots to nearby owners for one dollar apiece.^[4] The program's design is the part that makes the evaluation matter. A Large Lot sale is not an open-market transaction. It is a transfer aimed at the people already on the block, who can buy the empty parcel beside or near their home, take title, and fold it into the property they already maintain. Stern and Lester's finding is that those dollar sales are associated with a block-level crime reduction of about 3.5 percent, and that the reduction rises to roughly 6.8 percent when the lot goes to a resident of the same neighborhood rather than to a buyer from elsewhere.^[4] The doubling is the signal worth holding onto. It says the benefit is not in the sale as a paperwork event but in who ends up tending the ground, since a neighbor who lives beside a lot has a reason to keep it up that a distant buyer does not.^[4] The program they studied shows up in our ledger as the DPD Large Lots managing organization, which makes their result the single most relevant piece of outcome evidence we cite. It tells us what disposition of the held parcels can do, and it puts the to-whom question on the same footing as the whether question for any reading of the backlog.^[4]

Rigolon and colleagues looked at the same program through a different lens and reached a complementary result.^[5] Examining lots transferred into private, owner-occupant ownership, they found that the transfer improves the upkeep of the lots and strengthens residents' sense of control over their own blocks.^[5] The two findings sit naturally together. A lot that a neighbor mows, fences, gardens, or otherwise tends stops reading as abandoned ground, and a block whose residents feel some ownership over the empty parcels on it is a block that behaves differently from one where the vacant land belongs to a distant office. Stern and Lester measured crime. Rigolon and colleagues measured care and agency. Both point the same direction, and the second helps explain the first, since the upkeep and the sense of control are plausibly the channel through which a transferred lot ends up a little safer.^[4][5] Together the two studies make the policy stakes of a held-against-disposed count concrete. A parcel that stays on the city's books is a parcel not yet producing the upkeep, the resident control, and the modest safety gains the literature ties to putting it in a neighbor's hands.^[4][5] We do not claim our data demonstrates any of those gains. We cite the studies that did and let them frame why the size of the held inventory is worth counting in the first place.

The descriptive geography our analysis produces has its own grounding in local research, and the Institute for Housing Studies at DePaul University is the anchor.^[8] The Institute maintains quarterly Cook County vacancy data and has documented that long-term residential vacancy concentrates in a familiar set of South and West Side community areas, naming Englewood, West Englewood, Roseland, and West Pullman among them.^[8] Those are the same community areas that rise to the top of our city-owned parcel count, which is the point of citing the Institute at all. The agreement is worth dwelling on, because the two datasets measure different things. The Institute tracks residential vacancy, empty homes and lots regardless of who owns them, drawn from sources like postal-service delivery records and assessor data.^[8] We track parcels the city itself owns, a narrower category that excludes the privately held vacant building down the block. Two measures built from different sources, capturing overlapping but not identical populations of land, landing on the same four or five neighborhoods. When independent instruments converge like that, the reading they share is harder to write off as a quirk of one dataset's definitions. When we report the concentration in the next section, then, we are not unveiling a new map of Chicago disinvestment. We are showing that the city's own land ledger falls on the map the Institute for Housing Studies and the broader literature have already drawn.^[8] That an external vacancy dataset and the city's internal inventory point at the same ground is part of what gives a descriptive read its footing.

Set the published work in a row and it settles the questions our data cannot touch. Land banks exist because abandoned property accumulates past the reach of ordinary markets and law.^[2] Chicago organized its response through the county land bank in 2013 and has used public data to target acquisitions.^[9][10] The vacancy concentrates in historically redlined Black neighborhoods on the South and West Sides, a pattern the disinvestment literature traces to predatory property relations and the county and the health literature quantify across redlining grades.^[3][6][7] And returning that land to residents yields measurable improvements in upkeep, in resident agency, and in block safety.^[4][5] Our work starts where that record stops, with a current and reproducible count of how much of the city's own land is held, where it sits, and how it lines up with the 1938 map. The count is next.^[1]

Where the land sits

Sort the ledger by place and the first thing it shows is concentration, and the concentration is steep. Five community areas each hold more than a thousand city-owned parcels.^[1] Englewood leads with 1,981, which is 9.6 percent of the entire inventory in one neighborhood. New City follows with 1,375. North Lawndale with 1,365. West Englewood with 1,361. East Garfield Park with 1,007.^[1] Those five areas hold 7,089 parcels between them, 34.2 percent of the full 20,732-parcel inventory.^[1] A third of the city's held land sits in five of its seventy-seven community areas. That is the headline of the geography. It is not subtle, and it is not new to anyone who has read the disinvestment literature, but the ledger states it in the city's own bookkeeping.

The ranking does not drop off a cliff after the top five. It steps down through the same parts of the city. Near West Side holds 836 parcels, Grand Boulevard 827, each about 4.0 percent of the inventory.^[1] Austin follows with 700, then West Pullman with 626 and South Chicago with 623, each near 3.0 percent.^[1] Humboldt Park holds 579, Roseland 565, and those two round out the top twelve.^[1] Read the list down and the map draws itself. Englewood, West Englewood, New City, Grand Boulevard, South Chicago, Roseland, and West Pullman trace the South Side. North Lawndale, East Garfield Park, Austin, and Humboldt Park trace the West Side. The Near West Side is the lone entry that sits closer to the center, the exception that makes the rest of the pattern legible rather than breaking it. This is the disinvestment geography the literature describes, the terrain Zaimi works from in Englewood and the terrain the Institute for Housing Studies tracks across the South and West Sides.^[3][8] We are not redrawing that map. We are reporting that the city's land inventory falls on it.

The ward view tells the same story in the city's political vocabulary, and it sharpens the picture rather than softening it. Ward 16 holds 2,461 parcels, 11.9 percent of the inventory, more than any other ward.^[1] Ward 20 follows with 2,191, 10.6 percent.^[1] Both cover stretches of the South Side that overlap the leading community areas, and between them the two wards account for more than a fifth of all the city's held land. The next tier is West Side. Ward 24 holds 1,556 parcels and Ward 28 holds 1,526, 7.5 and 7.4 percent of the inventory, both covering ground that takes in North Lawndale and East Garfield Park.^[1] Ward 27 follows with 1,231, then Ward 3 with 959, Ward 10 with 912, Ward 21 with 793, Ward 6 with 789, and Ward 9 with 779.^[1] Slice Chicago by community area or slice it by ward, the held land piles up in the same place. Two ways of dividing the city, one answer about where the vacant municipal land is.

The two geographies do not align perfectly, and the reason is structural. Wards are redrawn every ten years to equalize population, and they cut across community-area lines, so a single ward can span several community areas and a single community area can fall into more than one ward. We report both because each is a way the city actually governs its land. The community area is the planner's unit, one of seventy-seven fixed statistical districts that researchers at the University of Chicago laid out in the 1920s and that the city has used for planning ever since, which is part of why the disinvestment literature reports its findings in the same units. The ward is the unit through which the politics of disposition runs, since an alderman's office sits close to decisions about which city lot is offered and to whom. The two units agreeing is more informative than either alone. When the community-area ranking and the ward ranking point at the same neighborhoods from different directions, the concentration is harder to wave off as an artifact of where someone drew a line.

The neighborhoods at the top of the ranking did not arrive at heavy vacancy by the same path, even though they share a grade on the old map. The West Side areas, North Lawndale and East Garfield Park and the West Garfield Park beside them, lost large blocks of housing in the unrest that followed the assassination of Martin Luther King Jr. in April 1968, and many of the parcels burned or condemned then never returned to use, leaving gaps that widened as population fell through the following decades. The South Side areas tell a slower story. Englewood, New City, and West Englewood thinned out over a longer arc of departure and decline, the emptying that Zaimi reframes as the residue of predatory, race-linked property dealing rather than a simple withdrawal of capital.^[3] The result by the 2020s is similar, blocks pocked with empty lots the city has come to hold, but the routes there differ, and the ledger, counting only the present state of each parcel, cannot distinguish a lot that came open in 1968 from one that came open in 2008. That history is the literature's to tell. The ledger supplies the endpoint, not the path.

A concentration finding is only as trustworthy as the field it rests on is complete, so the missingness belongs here, in the body, not in a note. The community area name is populated for 18,080 of the 20,732 parcels, 87.2 percent of the inventory.^[1] The ward field is populated for 18,083, also 87.2 percent.^[1] That leaves 2,649 parcels with no ward attached, just under 12.8 percent of the inventory, and those rows drop out of every ranking above.^[1] The exclusion is honest. It is not free. If the blank rows were spread unevenly across the city, the rankings could move, and the data alone cannot rule that out. What the data can settle is the direction of the risk. The shares are computed over the populated rows and reported as such. A missing geography for one parcel in eight is material enough to state out loud. And the exclusion runs one way only, because a blank row contributes nothing to any community area's total and so cannot inflate the top five. If those 2,649 rows were geocoded tomorrow and landed disproportionately in Englewood or Ward 16, the concentration would read sharper than it does now, not softer. The land the ledger does place puts a third of itself in five neighborhoods, and those neighborhoods are the ones the literature already marked.^[1][3][8]

What the geography does not tell us, by itself, is what the land is doing. A parcel in Englewood and a parcel in East Garfield Park each count as one row in the concentration ranking whether the city is holding the parcel indefinitely, leasing it out, or has already sold it to a neighbor. Concentration counts where the land is. It does not measure whether the land moves. To read the ledger as a ledger and not just a map, the next question is the structural one the inventory was built to answer. How much of this land does the city still hold, and how much has it actually let go.

Held, not moved

The concentration tells you where the land is. The status field tells you what the city is doing with it, and the short answer is mostly nothing. This is the structural core of the paper, the held-against-disposed accounting, and the plain counts come before any reading drawn from them.

The property status field sorts the inventory into four named values and a small remainder. Owned by City covers 12,134 parcels, 58.5 percent of the inventory.^[1] Sold covers 6,160, 29.7 percent.^[1] Leased covers 1,501 parcels, 7.2 percent. Not City Owned covers 904, 4.4 percent.^[1] A residual 33 parcels, 0.2 percent, carry no status at all.^[1] The plain reading is the one the counts force. A clear majority of the inventory, nearly three parcels in five, is still held by the city rather than returned to use. Roughly three in ten have been sold. The remainder is leased, no longer city-owned, or unlabeled. Whatever else the ledger says, it says first that the city holds more land than it has moved, and that the held share runs to roughly double the sold share. This is a stock-heavy ledger. It is a backlog more than it is a pipeline.

The disposition counts confirm the held majority from the other direction. A parcel can carry a recorded disposition date without its status reading Sold, so an honest count has to capture both. Count every parcel that has either reached Sold status or carries a recorded disposition date, and only 31.4 percent of the inventory, 6,506 parcels, has ever been disposed.^[1] Narrow the test to a recorded disposition date alone and the figure falls to 20.5 percent, 4,259 parcels.^[1] The gap between those two numbers is itself worth a sentence, since some parcels are marked sold without a clean date in the disposition field, but both readings land in the same neighborhood. Somewhere between a fifth and a third of the city's land inventory has moved. The remaining two-thirds to four-fifths sits. For a stock of land the literature says could be returned to residents with measurable benefit, the share actually returned is the minority of the table.^[4][5]

What that 31.4 percent represents is a cumulative figure, not an annual one, and the distinction sharpens what the held majority means. The disposed parcels are every parcel the city has ever moved, summed across all the years those parcels have sat in the inventory. The held parcels are what is left over after all of that activity. So the picture is not that the city disposed of a third of its land last year and is working briskly through the rest. It is that across the whole history captured in this snapshot, the disposal programs have cleared roughly a third of what the city holds, and two parcels in three remain. A backlog that survives the cumulative effort to date is a backlog of a particular kind, the residue that the existing tools, at their existing pace, have not reached. The literature gives that residue a value, since each held parcel is a lot that the Large Lots evidence says could be doing something on its block.^[4][5] The ledger gives it a size. Neither tells us how fast the gap is closing, a limit the paper returns to when it reaches what a single snapshot cannot show.

Who holds the held land is a question the inventory answers only partway, and the partial answer has to be reported as partial. The managing organization field is populated for 9,278 of the 20,732 parcels, 44.8 percent, which means it is blank for 55.2 percent of the inventory.^[1] More than half the table does not record which department or program is responsible for the parcel. We therefore compute the organization shares over the 9,278 populated rows and never over the full inventory, and we label them that way every time. Among the parcels where the field is populated, DPD Large Lots manages 1,713, 18.5 percent of the populated rows and the largest single share.^[1] The Department of Fleet and Facility Management, recorded in the data as 2FM, manages 1,565, 16.9 percent.^[1] DPD Planning holds 1,180. The Park District holds 1,134. The Department of Housing, recorded as DOH, holds 1,036.^[1] Those five span between 11.2 and 18.5 percent of the populated rows each. Smaller holdings follow, with DPD Open Space at 801, DPD Real Estate at 586, Skyway Concessions at 328, an Obsolete PIN category at 228, and a Community Block by Block round at 217.^[1] This is the bureaucratic anatomy of the held land, and it is an anatomy of fewer than half the parcels. The 55.2 percent blank is the dominant fact about the field. No single organization dominates the populated rows either. The held inventory is scattered across planning, housing, parks, fleet management, and disposition programs, in many hands and under many mandates, and more than half of it sits in hands the dataset declines to name.

The largest managing organization is also the one the literature has examined most directly, which is worth a pause. DPD Large Lots is the program behind the dollar-lot sales Stern and Lester and Rigolon and colleagues evaluated.^[4][5] It manages more populated parcels than any other organization in the field, 1,713 of them, and it is the channel through which city-owned vacant lots actually reach neighbors.^[1][4] The connection runs one direction, and we keep it there. The presence of a large DPD Large Lots holding does not demonstrate the crime or upkeep benefits those studies found. It identifies the channel through which such benefits, where they occur, would be realized.^[4][5] What the held-against-disposed accounting establishes is the size of the pool that channel draws from. With 58.5 percent of the inventory still held and only a minority ever disposed, the backlog feeding the disposition programs is large. That is a description of a stock, not a verdict on the programs that draw it down.^[1]

What managing organization cannot tell us is whether any given held parcel is stuck, banked on purpose, or simply waiting on a buyer who has not appeared. A status of Owned by City is a snapshot, not an intention, and the dataset records no reason for the holding. To tell whether held land is land nobody wants or land inching through a queue, the inventory offers a sales status field that tracks where a parcel sits in the disposition process, and we come to it after the overlay. The overlay goes first, because the question of where the held land sits has a second answer the concentration ranking only gestured at, and that answer is eighty-eight years old.

The 1938 map under the 2025 ledger

This is the headline descriptive result, and it earns the most careful framing in the paper, because it is the one most easily misread. The claim is narrow. Take each city-owned parcel that carries coordinates, ask which 1938 redlining zone its location falls inside, and the parcels land overwhelmingly in the zones the Home Owners' Loan Corporation graded declining or hazardous. That is a statement about where points fall on an old map. It is not a statement about cause, and the section returns to that line more than once before it ends.

Some history makes the join readable. The Home Owners' Loan Corporation was a New Deal agency, created in 1933 to refinance home mortgages during the foreclosure wave of the Great Depression. In the late 1930s it produced color-coded Residential Security Maps for cities across the country, Chicago among them, where a survey graded neighborhoods from A to D. Grade A, drawn in green, marked the areas a lender was told to treat as the best risk. Grade B, in blue, was desirable. Grade C, in yellow, was declining. Grade D, in red, was hazardous, and the red was applied heavily to Black neighborhoods almost regardless of the condition of the housing in them. The area description sheets that accompanied the Chicago map recorded race and ethnicity as grading factors in plain language, and the presence of Black residents alone could pull a neighborhood's grade down a step or two. The grade then traveled into lending. A red or yellow grade told appraisers and lenders the area was a poor bet, which made mortgages there scarcer, costlier, and shorter in term, so the capital that builds and maintains housing thinned out across exactly the blocks the survey had marked.

The Chicago the survey graded was in the middle of the Great Migration, the decades-long movement of Black Americans out of the rural South into northern industrial cities, and the South Side Black Belt had swelled with new arrivals hemmed into a narrow corridor by restrictive covenants, private agreements among white owners not to sell or rent to Black buyers. The Supreme Court would not strike the judicial enforcement of those covenants until Shelley v. Kraemer in 1948, a decade after the map. So the red on the 1938 sheet did not fall on random ground. It tracked the color line the city had already drawn by covenant and by violence, and it gave that line the imprimatur of federal mortgage policy. That layered history is what makes a 2026 overlay legible. The map our analysis joins against is a snapshot of where capital was told not to go, and the grades are the categories the join reports.

The method is a spatial join and nothing more elaborate. The repository holds a digitized version of the 1938 HOLC map of Chicago, the graded zones the federal corporation drew when it color-coded the city for mortgage risk. We loaded those polygons by grade, 49 zones graded A, 161 graded B, 338 graded C, and 158 graded D, 706 polygons in all.^[1] For each parcel in the inventory that carries a latitude and longitude, we asked which polygon, if any, contains the point, and we recorded the grade. There is no model here. There is no estimation, and no inference about why the point sits where it sits. A point either falls inside a 1938 polygon or it does not, and if it does, the polygon carries a grade.

Coverage governs what the join can say, so the coverage numbers come before the result. Of the 20,732 parcels, 18,083 carry usable coordinates, 87.2 percent of the inventory.^[1] The 2,649 parcels without coordinates drop out of the overlay entirely, the same roughly 12.8 percent that lack geography in the rankings.^[1] Among the 18,083 geocoded parcels, 16,783, which is 92.8 percent, fall inside a 1938 graded zone.^[1] The remaining 1,300 geocoded parcels, 7.2 percent, fall outside the 1938 map footprint, because the HOLC map covers most but not all of the modern city, and a parcel in an ungraded area simply has no grade to record.^[1] We report the grade distribution two ways for exactly that reason, once as a share of all geocoded parcels and once as a share of those inside the mapped footprint, so the parcels outside the old map are never quietly folded into another category.

The distribution is lopsided. As a share of geocoded parcels, Grade D, the hazardous and redlined category, accounts for 57.5 percent, and as a share of those inside the map it rises to 61.9 percent.^[1] Grade C, the declining category, accounts for 33.7 percent of geocoded parcels and 36.3 percent of those inside the map.^[1] The two top grades barely register. Grade B, the desirable category, is 1.6 percent of geocoded parcels and 1.8 percent of those inside the map.^[1] Grade A, the best category, is 0.1 percent on either basis, fourteen parcels in absolute terms.^[1] Put the categories in raw counts and the contrast is hard to look away from. The C and D zones together hold 16,474 city-owned parcels.^[1] The A and B zones together hold 309.^[1] That is a ratio of 53 to one, declining-or-hazardous against best-or-desirable.^[1] Inside the mapped footprint, the C-and-D zones hold 98.2 percent of the parcels and the A-and-B zones hold 1.8 percent.^[1] The city's held land sits, almost in its entirety, on ground the 1938 map marked down.

The figure invites a causal reading it cannot bear, so the restraint has to be stated as plainly as the number. This is descriptive co-location across an eighty-eight-year gap. The map was drawn in 1938. The inventory was pulled in 2026. All we have shown is that the parcels in the recent ledger fall inside the old polygons. We have not shown that the 1938 grading caused the present-day vacancy, and our data holds nothing that could establish such a chain. A spatial join measures position, not mechanism. The most it can report is that the geography of city-owned vacant land today and the geography of redlining grades from 1938 sit on the same ground. The pattern is persistence. The same parts of Chicago that were redlined are the parts where the city now holds vacant land. Persistence of a pattern is not proof that one pattern produced the other. The causal questions belong to the scholarship, not to this join, and the scholarship has taken them up. Zaimi traces the South Side route from predatory property relations to vacancy.^[3] The Treasurer's office quantifies the odds that a 1940-redlined parcel is distressed today.^[7] Chen and colleagues run the path from grade to land use to health.^[6] Our join does none of that work. It locates points.

The overlay is scoped to city land alone, and that scope line holds here as everywhere. The 16,783 parcels inside the graded zones are city-owned parcels, drawn from the City-Owned Land Inventory, and they are not the Cook County Land Bank Authority's holdings.^[1] The overlay measures nothing about the CCLBA. A reader who wants to know how the land bank's own parcels fall on the 1938 map will not find the answer here, because the land bank's parcels are not in our data.

Where the descriptive read does connect to the broader record is as one more piece of evidence pointing the same way, and we keep our numbers separate from the published ones even while noting the agreement. The Cook County Treasurer's office found that 1940-redlined parcels are 2.75 times more likely to be distressed today and that more than 14,000 of 27,358 Scavenger Sale vacant or abandoned properties sit inside 1940 redlined zones.^[7] Chen and colleagues found that vacant land concentrates in historically redlined Chicago neighborhoods and helps account for worse mental-health outcomes.^[6] Those are independent findings, from different datasets and different methods, describing the same redlining-to-vacancy persistence that our overlay describes for city-owned land.^[6][7] We do not pool their numbers with ours. The Treasurer counted distressed and Scavenger Sale parcels. Chen and colleagues ran a path analysis. We joined city parcels to a 1938 map. The value of citing them beside our result is that three separate reads of Chicago's land, none of them ours alone, land on the same geography. That convergence is what makes the co-location worth reporting, and it is also exactly where the descriptive reading stops.^[1][6][7]

Where land moves and where it sits

The inventory can be read as a stock, which is what the status and overlay sections did, or it can be read as a flow, which is what the sales status field allows. Sales status records where a parcel sits in the disposition process. Like managing organization, it is sparse. It is populated for 9,293 of the 20,732 parcels, 44.8 percent. The remaining 11,439 rows, 55.2 percent, are blank, and a blank here is best read as a parcel that is not in an active sales pipeline at all.^[1] The funnel below is computed over the populated rows only. It describes the parcels the city is actively processing, not the inventory as a whole.

The shape of the funnel is lopsided. Interest, the earliest stage, accounts for 5,845 parcels, well over half of every parcel in the pipeline.^[1] Application Closed follows at 1,648. Offered, the stage at which the city has actually put a parcel forward, accounts for just 881. Application(s) Received accounts for 698.^[1] The smaller tails run through Not offered at 109, Apply at 58, a separate Application Received bucket at 30, and a See note category at 17.^[1] Demand sits far upstream of disposition. Early-stage interest outnumbers active offers by roughly six and a half to one, which says the bottleneck in returning land to use is not a shortage of interest. It is the distance between expressed interest and an actual offer on the table.

A funnel is normally read top to bottom, with each stage feeding the next, and the natural worry is that the early stages should always be the largest because they have not yet been winnowed. That worry is real, and it is why we do not read the 881 offered parcels as a failure rate. What the lopsidedness does show is where the inventory's activity is pooled. Five thousand-plus parcels carry a recorded interest, a level of expressed demand that sits oddly against a held inventory the city has mostly not moved. The land is not sitting because no one has asked after it. On more than five thousand parcels someone has. The parcels that have reached an actual offer, the stage where the city commits a specific lot to a specific disposition, number fewer than nine hundred. Read beside the Large Lots evidence, the gap is the part worth flagging. Stern and Lester and Rigolon and colleagues measured what happens once a lot reaches a resident's hands.^[4][5] The funnel measures how few lots have reached the point where that transfer is even on the table. A backlog this size, with demand banked this far upstream, is a backlog whose drawdown is constrained somewhere between interest and offer, and the dataset records the constraint without naming its cause.^[1]

Disposition also varies sharply by place, and the variation does not track concentration. Among community areas holding 200 or more parcels, the slowest movers form a recognizable South Side cluster. Washington Park has disposed of just 94 of its 556 parcels, a 16.9 percent disposition rate.^[1] West Pullman sits at 19.6 percent, 123 of 626. Fuller Park at 20.1 percent, 60 of 299. Roseland at 23.5 percent, 133 of 565.^[1] West Englewood, one of the five largest holders in the city, has moved only 24.7 percent of its 1,361 parcels, and Morgan Park sits at 26.3 percent, 67 of 255.^[1] These are the places where the land sits.

The fast movers are a different set. East Garfield Park, the fifth-largest holder, has disposed of 478 of its 1,007 parcels, a 47.5 percent rate, nearly half.^[1] Austin sits at 45.7 percent, 320 of 700. North Lawndale at 40.2 percent, 549 of 1,365. Humboldt Park at 39.7 percent, 230 of 579.^[1] Near West Side at 37.0 percent and New City at 36.4 percent follow close behind.^[1] These are the places where the land moves.

The instructive part is that high-inventory community areas turn up at both ends of the list. North Lawndale and East Garfield Park each hold more than a thousand parcels and each dispose of land at or above 40 percent. West Englewood holds 1,361 and disposes at 24.7 percent. West Pullman holds 626 and disposes at 19.6 percent. Concentration and disposition speed are not the same axis. A community area can hold a great deal of city land and still move it, or hold a great deal and let it sit, and the inventory records both patterns side by side without telling us why one place clears its backlog faster than another. The dataset carries the rates, not the reasons. So the reading stays at the level the data supports. The pace of disposition differs across the same neighborhoods where the land concentrates, and the difference is large, running from under a fifth in Washington Park to nearly half in East Garfield Park. Why two West Side neighborhoods that border each other move land at such different rates is a question the ledger raises and does not answer, and we leave it raised.

What the ledger does not say

A ledger is defined as much by its blank cells as by its filled ones, and an honest accounting reads the gaps as plainly as the totals. The most important limit governs the whole paper. This analysis covers the City of Chicago's own land inventory, the 20,732 parcels the city records as owned, sold, leased, or formerly held. It does not cover the Cook County Land Bank Authority. The CCLBA is a separately governed entity created in 2013 with its own acquisition-rehabilitation-disposition mandate over tens of thousands of parcels, and its inventory is not in this dataset, was not pulled, and is not measured by any number in this paper.^[9] The CCLBA enters this work through the literature and the qualitative record alone, never through our counts. Every figure above is city land.

Two of the inventory's substantive fields are sparse enough that they belong in the limits section rather than the findings, because the sparseness is itself the finding. Land value is recorded for only 5,103 of the 20,732 parcels, and 5,101 of those are usable values above zero, 24.6 percent of the inventory.^[1] Among those usable values the median recorded land value is $12,445 and the mean is $54,699.^[1] The gap between the median and the mean says the recorded values are pulled upward by a small number of high figures, which is its own caution against reading the field as a clean valuation. Lot size is worse. The square-footage field is populated for 94.0 percent of rows, but only 3,765 of those values exceed zero, 18.2 percent of the inventory, with a median usable lot of 3,153 square feet.^[1] Roughly three parcels in four carry no usable land value, and more than four in five carry no usable lot size. Any statement about value or size describes the minority of parcels where the city happened to record it.

Where land value is recorded, broken out by community area for areas with at least thirty usable values, the lowest recorded medians fall on the South and West Sides, which is consistent with the rest of the geography and still must be read narrowly. Riverdale shows the lowest recorded median, $7,922 across 43 usable parcels.^[1] West Pullman follows at $8,123 across 205 parcels, Chatham at $9,175 across 51, and West Englewood at $9,308 across 536.^[1] Morgan Park, New City, Greater Grand Crossing, and Roseland round out the low end, all under $10,000.^[1] These are recorded-where-present figures, not assessments of every parcel in those areas, and the small per-area counts mean each describes a sample the city chose to value rather than the full local inventory. Read as a complete valuation, the numbers would be wrong. Read as the values the ledger actually carries, they line up with the disinvestment geography the rest of the paper traces.

The reason these fields stay in the limits section rather than the findings is that we cannot tell why a given parcel carries a value and another does not, and that unknown is what blocks any stronger claim. If the city records a land value mainly at the moment a parcel enters a sale or a lease, then the valued parcels are the ones in motion, and the quarter of the inventory with a recorded value would be a biased window onto the three quarters without one. If instead the values were entered in some past assessment sweep that simply never finished, the gap would be closer to random. The dataset does not say which story is true, and the two imply different things about what the recorded medians represent. We therefore decline to generalize from them at all. The most we draw is the weak, internally consistent observation that the values the ledger does carry are lowest in the same South and West Side areas where the parcels concentrate, which fits the geography without resting any weight on it. A field populated for a minority of rows, by an unknown selection rule, is a field that can illustrate but cannot establish, and we hold it to the lower standard throughout.

The structural limits are several, and stating them flatly is the point of the section. The inventory is a point-in-time snapshot, pulled on 2026-05-29 from records last updated between December 2025 and January 2026, and it shifts as the city acquires and sells parcels, so every count is current to the pull date and no later.^[1] Roughly 12.8 percent of rows carry no community area, no ward, and no coordinates, and those parcels fall out of every ranking and the overlay alike. Managing organization and sales status are each blank for 55.2 percent of the inventory, so the organizational anatomy and the disposition funnel describe fewer than half the parcels. Inside the overlay, 1,300 geocoded parcels fall outside the 1938 footprint, and about twenty HOLC polygons were left out because they carried no clean A, B, C, or D grade.^[1] On the rare parcel that overlapped two grades, the worse grade was assigned, the conservative choice for a redlining-persistence read and one that could only push the C-and-D share up, never down.^[1] None of these choices is buried in the numbers. Each is stated so the counts can be reproduced and checked against a fresh pull.

The snapshot nature deserves its own line, because it bounds what every count in the paper can claim. A single pull is a photograph, not a film. We can say that 58.5 percent of the parcels were held on the pull date. We cannot say whether that share is rising or falling, because we have one observation in time and no second pull to compare it against. A reader who wanted to know whether the city is working the backlog down, holding it steady, or letting it grow would need the same table pulled at two or more dates and differenced, which is a study we did not run and do not report. The disposition rates carry the same caution. A community area that has disposed of 47.5 percent of its parcels has done so cumulatively, over whatever years its parcels have been in the inventory, and the rate says nothing about the pace in any single year. None of this weakens the cross-sectional findings, which are exactly what a snapshot is good for, namely where the land is and what state it is in on one day. It only marks the boundary. Anything about change over time is outside a single pull, and we do not reach for it.

What follows from all of this is a short list of claims the data cannot support, and the discipline of the paper is to refuse them. The inventory does not establish cause. It does not show that redlining produced the current geography, only that the two patterns co-locate across eighty-eight years. It says nothing about the Cook County Land Bank Authority's holdings or behavior, because the CCLBA is not in the file. It carries no revenue, no sale prices, no post-disposition outcomes, no record of what gets built on a disposed lot, and nothing else the dataset does not contain. Where the published literature reports such outcomes, those are the literature's findings, attributed as such, not ours. The ledger says what it says. It records where the city's land is, what status the land carries, who manages the assigned slice of it, and where the located parcels sit relative to a 1938 map. Everything past that is outside the data, and the honest move is to leave it outside.

The backlog, read plainly

Return to the single vacant parcel in Englewood, the one row this paper opened on, with its PIN, its address, its status, its managing organization, its ward, its community area, and its pair of coordinates. It is one of 20,732. Read across the whole inventory, three findings carry the weight, and each is a description of a pattern rather than a claim about a cause.

The city's land holdings concentrate on the West and South Sides, with a third of the located inventory, 34.2 percent, sitting in five community areas.^[1] The inventory is mostly held rather than disposed, with 58.5 percent of parcels still owned by the city against fewer than three in ten sold.^[1] And the located parcels sit, overwhelmingly, where the 1938 redlining map drew its worst grades, with 61.9 percent of the parcels inside the mapped footprint falling in D-graded zones.^[1] Concentration. Holding. Co-location. None of the three asserts that any one thing caused another. They report where the land is, what state it is in, and what historical boundary it happens to sit inside.

Set beside the published record, the descriptive read knows its place. The literature already explains why this geography exists and what can be done with the land in it. Mallach establishes why land banks exist as instruments for turning abandoned and tax-delinquent property into community assets.^[2] Zaimi reframes South Side vacancy as the residue of predatory, race-linked property relations rather than a simple withdrawal of capital.^[3] The Cook County Treasurer's office and Chen and colleagues quantify the redlining-to-vacancy persistence from the county rolls and from the health literature.^[6][7] Stern and Lester and Rigolon and colleagues show that returning vacant lots to nearby residents through the Large Lots program improves upkeep and modestly cuts crime.^[4][5] Our contribution sits underneath all of that, smaller and more recent, a current and reproducible accounting of the city's own ledger as it stood on the pull date. The files behind every count are posted on the site, so a reader can re-run the numbers and check them against a fresh pull of the same public table.^[1] The aim was never to settle anything the scholarship has not already settled. The aim was to read the public ledger as a ledger and report what it holds.

A held parcel is a decision deferred. The city has not chosen to keep the parcel forever, and it has not chosen to let the parcel go, and the snapshot catches the parcel in that suspended state. Multiply the suspension across the inventory and those deferred decisions are the backlog. The backlog is large, it is old, and it concentrates in the same places a surveyor's red ink marked down in 1938. The maps were officially retired and the grades changed names. The land the city is still holding traces the old boundaries anyway, almost line for line. The ledger does not editorialize. It keeps the rows, and the rows point one way.

^[1]: Author analysis of City-Owned Land Inventory (City of Chicago). City of Chicago Department of Planning and Development, via the Chicago Data Portal (Socrata). Reproducible files at rooted-forward.org/research/data/cook-county-vacant-land-land-bank.

^[2]: Mallach, Alan. Bringing Buildings Back: From Abandoned Properties to Community Assets. 2nd ed. New Brunswick, NJ: Rutgers University Press / National Housing Institute, 2010. ISBN 9780813549866.

^[3]: Zaimi, Rea. "Rethinking 'disinvestment': Historical geographies of predatory property relations on Chicago's South Side." Environment and Planning D: Society and Space 40, no. 2 (2022): 245-263. DOI 10.1177/02637758211013041.

^[4]: Stern, Marc, and T. William Lester. "Does Local Ownership of Vacant Land Reduce Crime? An Assessment of Chicago's Large Lots Program." Journal of the American Planning Association 87, no. 1 (2021): 73-86. DOI 10.1080/01944363.2020.1792334.

^[5]: Rigolon, Alessandro, et al. "Transferring Vacant Lots to Private Ownership Improves Care and Empowers Residents." Journal of the American Planning Association 87, no. 4 (2021): 570-584. DOI 10.1080/01944363.2021.1891126.

^[6]: Chen, Liang, Maria M. Conroy, Bruce C. Mitchell, and Helen C. S. Meier. "Historical redlining, locally unwanted land uses, and neighborhood mental health: Investigating the mediating effect in Chicago, Illinois." Urban Studies (2026). DOI 10.1177/00420980261440823.

^[7]: Cook County Treasurer's Office (Maria Pappas). Maps of Inequality: From Redlining to Urban Decay and the Black Exodus. Chicago, 2022.

^[8]: Institute for Housing Studies at DePaul University. "Understanding Vacancy: Patterns of Long-Term Vacancy in Cook County" (and related vacancy-data releases).

^[9]: Metropolitan Planning Council. "Cook County Land Bank Authority" (case study).

^[10]: Data Science for Social Good (University of Chicago) with the Cook County Land Bank Authority and DePaul Institute for Housing Studies. "land-bank" analytics tool (open-source repository), 2013.