Analysis: Where Governments Are Losing the Most Revenues To Tax Abatements

by | April 26, 2018

New financial data provide the first look at how much revenue states and localities across the country are losing from tax breaks. Governments recently began disclosing the information on tax incentives as a result of an accounting rule implemented by the Governmental Accounting Standards Board.

Governing analyzed data compiled by corporate watchdog group Good Jobs First from governments' annual financial reports. Revenues lost to property tax abatements, economic development incentives and other programs were tallied for each jurisdiction. Total losses on a per capita basis were then compared to different socioeconomic measures for a sample of 446 cities and counties with complete data as of earlier this year.

Several of the top spenders in our sample were major cities with larger budgets, particularly New York and Chicago. Others, such as Los Angeles and Phoenix, reported minuscule totals by comparison. Mid-sized and smaller jurisdictions forgoing unusually high tax revenues typically heavily utilized tax-increment financing (TIFs) to fund major development projects. Mishawaka, Ind., reported the largest per capita abatement of any jurisdiction reviewed, with nearly $20 million going to TIF projects in fiscal 2016. 

Localities Reporting Largest Losses From Tax Abatements

The following cities and counties reported the largest total losses on a per capita basis of the 446 reviewed:

Jurisdiction Per Capita rate Total Annual Direct and Passive Revenue Losses
Mishawaka, Indiana $416 $20,072,792
St. John the Baptist Parish, Louisiana $407 $17,858,805
New York, New York $401 $3,389,468,000
Bloomington, Minnesota $333 $28,360,455
East Palo Alto, California $302 $8,855,528
Seneca County, New York $278 $9,726,072
Chicago, Illinois $220 $596,599,000
Greenville, South Carolina $211 $13,248,017
Kansas City, Missouri $190 $89,811,000
Kenosha, Wisconsin $181 $18,032,574
DeKalb, Illinois $177 $7,657,438
Glendale, California $171 $33,814,000
Cicero, Illinois $162 $13,621,598
Denver, Colorado $162 $107,244,000
Liberty, Missouri $158 $4,780,219
Niagara Falls, New York $156 $7,648,484
Pittsburg, California $155 $10,534,624
West Baton Rouge Parish, Louisiana $140 $3,501,030
District of Columbia $140 $92,037,000
Source: Governing calculations of data reported by Good Jobs First, U.S. Census Bureau 2012-16 American Community Survey

NOTE: View financial disclosures for all jurisdictions with available data on the Good Jobs First website.

The disclosure data, while from a limited sample of jurisdictions in the first batch to report their disclosures, further suggest that those most heavily reliant on tax incentives generally tend to be characterized by elevated levels of income inequality.

The median revenues lost to tax abatements for the top quarter of jurisdictions with the highest levels of inequality, as measured by the Census Bureau’s Gini index, was $9.29 per capita. That’s nearly double the rate for all other jurisdictions in the sample ($5.28).

Gini Index Quartile Group Gini Index Values Median Tax Abatements Per Capita
1st (Least Inequality) 0.346-0.423 $3.49
2nd 0.423-0.446 $6.90
3rd 0.446-0.472 $5.26
4th (Highest Inequality) 0.472-0.605 $9.29
Data reflect totals for 446 cities and counties for the most recent fiscal years with reported data.
Source: Governing calculations of data reported by Good Jobs First, U.S. Census Bureau 2012-16 American Community Survey

These initial findings do not imply causation or that tax breaks necessarily exacerbate disparities as a number of factors contribute to income inequality. It’s possible that areas with already high levels of inequality may opt to spend more on economic development incentives. Some central cities or distressed communities may feel the need to spend more to compete with jurisdictions offering more affordable land, better schools or other amenities.

Research, however, has also identified several reasons why spending large sums of money on tax incentives could worsen inequality. (See our related story for more on this.) Frequently, incentives are primarily utilized in cities’ central business districts rather than disadvantaged communities.

Differences in financial reporting account for some of localities’ varying totals as well. Good Jobs First identified incomplete disclosures for many jurisdictions that were excluded from our calculations. Localities’ disclosures also include passive losses stemming from programs initiated by other governments, typically states or surrounding counties. St. John the Baptist Parish, La., with a population of only 44,000, reported $17,858,805 in taxes were abated under the state Industrial Tax Exemption Program, for example. 

Note: A prior version of this story incorrectly stated tax abatement totals for Carbondale, Ill.


Good Jobs First provided Governing with financial data from its Subsidy Tracker 2 database earlier this year. The data reflect disclosures from localities’ Comprehensive Annual Financial Reports that were filed before March (not all governments filing before then are included in the database, however.) Smaller cities and counties with populations below 25,000 were excluded. Many Comprehensive Annual Financial Reports made no mention of the new GASB Statement No. 77 accounting rule, leaving it unclear whether or not they had any losses to report. We excluded these and a large number of other jurisdictions that Good Jobs First flagged as having incomplete disclosures (those citing the accounting rule and reporting zero losses were included, though.) Our final sample consisted of 446 cities and counties with populations exceeding 25,000.

Reported revenues lost from localities’ own tax abatement programs and those they lost due to other governments’ abatements were totaled for each jurisdiction’s most recent fiscal year. Total losses per capita were then calculated using population estimates from the Census Bureau’s 2016 five-year American Community Survey estimates. The median annual per capita rate for the sample was $5.85.

To measure income inequality, estimates of each jurisdiction’s Gini index were compiled from the same Census survey dataset. These indices ranged from 0.605 (highest inequality) to 0.346 (least inequality).

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