Distorted measures of employment in charitable organizations: 

Causes, impact, and remedies 

Martin H. David 

Associate Scholar, Urban Institute, Washington DC 

Emeritus professor, University of Wisconsin – Madison 

email: david@ssc.wisc.edu telephone: 608.238.2181 

2603 Middleton Beach Rd., Middleton WI 53562 

22 August 2007 
Distortions in nonprofit employment 22 August 2007 1 

Martin David, Urban Institute 

Abstract 

Keywords: Charitable organizations, employment, administrative records 

Public sector failures lead to a large understatement of employment in charitable 

organizations. Multiple forces lead to this understatement. Partitioning private business into 

charities, other exempt organizations, and for profit business has a low priority in Federal 

Statistical Agencies. Regulatory failures in IRS oversight of exempt organizations compromise 

available statistics – the count of active organizations, data on employment, coverage of 

available employment reports, and consistency in its reporting. The incentive for IRS to regulate 

exempt entities is negative as the activity does not generate net revenue. Because exempt 

organizations constitute a small part of private businesses, publication of estimates for their 

establishments is limited by the imperative not to disclose proprietary information. Finally, 

regulation of burden in completing government forms leads to peculiar censoring of data within 

the population of exempt entities. 

This analysis demonstrates that existing published estimates of employment in charitable 

organizations is understated. We link IRS information returns to the BLS/QCEW. A substantial 

proportion of employers can not be matched. Employment on IRS returns contains substantial 

nonresponse. Imputation of QCEW employment to matched organizations and augmenting the 

available census of IRS returns with employment in exempt organizations that are not covered 

produces aggregates that are substantially larger than the published Economic Census for 2002. 

Understated employment can be overcome by a combination of more sophisticated 

imputation of information returns and matching of IRS information to records of payroll tax 

submissions, IRS/Form 941. 
 

 

 

 

 

Distortions in nonprofit employment 22 August 2007 2 

Martin David, Urban Institute 

1 Importance of nonprofit employment 

Charitable organizations constitute about 5% of the corporate business sector. They are 

private corporations and associations exempted from taxation by the Federal government under 

Internal Revenue Code (IRC) §501(c)(3). State and local codes often reduce sales tax liability 

and property taxes for charitable organizations (Brody 2002). Gifts to exempt charitable 

organizations substantially reduce tax burdens of individual donors.1 

Charitable organizations operate in a broad range of industries -- from the arts, advocacy, and 

social assistance to education, training, and hospital services to research and international 

services. Labor is the largest input to the sector. Wages paid are likely to be less than in forprofit companies.2 

Good measures of the number of employees in charitable organizations, classified by 

industry subsectors, are a first step to understanding the value of these organizations to the 

economy. This paper demonstrates that estimates of employment can be more timely and more 

comprehensive than understated estimates available in Census publications. 

2 Sources of employment measures 

2.1 Published estimates of exempt sector employment 

The Economic Census publishes employment information on private business entities that are 

exempted from corporation taxes every five years. Exempt includes charitable organizations as 

well as neighborhood associations, clubs, labor unions, credit unions, and cooperatives. Three 

NAICS sectors are classified by exempt status of the organization (Educational services, 61; 

Health Care and Social Assistance, 62; and Arts, Entertainment, and Recreation, 71). Sector 61 

excludes elementary and secondary schools and colleges and universities. One additional 

1

 Tax expenditures due to deductions for education, health, and social services ate estimated at more than $55 

billion in the 2008 Budget of the United States government (Table 19-3). 

2

 A plausible hypothesis is that workers in nonprofit organizations derive more satisfaction from their 

employment than workers in for-profit employment; they are willing to work at wages less than the wage paid 

in comparable for-profit positions [Helliwell and Huang 2005]. 
 

 

 

 

 

 

 

Distortions in nonprofit employment 22 August 2007 3 

Martin David, Urban Institute 

subsector, Religious, Grantmaking, Civic, Professional, and similar Organizations (813), is 

dominated by exempt organizations. Many are charitable organizations; some are not.3 

Employment reported for those (sub-) sectors totals 10.4 million (Table 1). That statistic is 

not only incomplete, it is timely only once in five years. Further it mixes employment of 

charitable organizations with employment of other exempt organizations. More extensive 

tabulation of charitable organizations is probably foreclosed by the disclosure review procedures 

used by the Economic Census.

4 

2.2 Unpublished microdata containing employment reports 

Regulations promulgated for IRC 501(c) organizations stipulate that most must file annual 

information returns.5 Organizations averaging revenue more than $25,000 must file; religious 

congregations are excused from filing information returns. However, religious organizations 

contracting to provide services funded by the Federal government also file information returns. 

Returns of organizations with more than $100,000 of revenue elicit employment in the week of 

March 12. Thus, employment of larger organizations can be estimated. (Charitable organizations 

can be distinguished from other exempted organizations.) 

The IRS count of employee is incomplete. What proportion of sector employment is 

included? How well is employment reported in different industries? Partial answers to these 

questions are provided in this report.6 

Microdata from these returns are accessible through the Urban Institute Dataweb. A census 

of all Form 990 and Form 990-EZ filed by charitable organizations is available for 1999-2003 

(GuideStar-NCCS National Nonprofit Research Database, ver. 1 [1999-2003], cited as 

NCCS:<year>). Form 990 elicits the number of employees; Form 990-EZ does not. 

3

 Most religious congregations included under this NAICS sector do not appear in any other official statistics 

of the US. 

4

 That is ironic, as exempt organizations are required to file information returns for public scrutiny. 

5

 The returns refer to fiscal years. Fiscal years ending after 1 December 2002 and before 1 December 2003 will 

be filed on the Form 990 for the year 2002. 

6

 Answers to this question may encourage the Statistics of Income Division of IRS to publish employment 

estimates in its annual statistical report on nonprofit organizations (Arnsberger 2006). 
 

3 Linking public IRS records to other employment data 

Distortions in nonprofit employment 22 August 2007 4 

Martin David, Urban Institute 

Matching any two datasets entails five steps: a) Finding a common identifier, b) determining 

the multiplicity of the matches, c) assessing the extent of matching errors, d) correcting the 

match to reduce bias from failed matches, and e) removing mismatches from the analysis files. 

We follow these steps in linking IRS information returns below. 

3.1 Gains from linking IRS nonprofit information returns to other sources 

Employment is reported on three administrative records: IRS Form 941, the BLS Quarterly 

Census of Employment and Wages (QCEW), and IRS W-2. The QCEW is derived from employer 

reports to state Unemployment Compensation (UC) agencies. Form 941 and QCEW both contain 

reports of employees on payroll in a particular month. The March reference month for those two 

series is identical to the reference month for employment elicited on Form 990. 

The identifier common to Form 941, QCEW, Forms 990/990-EZ, and the IRS Registry is the 

Federal Employer Identifying Number, or ein. Multiple establishments in the QCEW match some 

IRS ein’s. In most cases only one establishment matches. The IRS files contain one record for 

each ein. 

Errors in ein’s emanate from the employer who may enter an incorrect ein or omit an ein, and 

from the state and Federal administrative agencies that process the ein. An omitted ein leads to a 

match failure. An incorrect ein leads to a match failure or a mismatched pair of records. 

The candidates to link to nonprofit returns vary in coverage and reporting period: 

(a) Form 941, filed quarterly, includes most employees whose wages have been withheld for 

accruing income taxes or Social Security payroll taxes. Employers that owe less than $2500 

annually for withholding and payroll taxes do not file Form 941. (They file Form 944 at the end 

of the year.) Thus employers of few, or part-time, employees may not file Form 941. 

(b) QCEW covers many, but not all, Form 941 employees. (It also includes a few of the 

employers who file Form 944.) However, QCEW excludes nonprofit employers with less than 4 

employees in some states. QCEW excludes some employees – part-time workers, students, and 

interns – in some states. One or both exclusions apply in about 30 states. 

QCEW ‘breaks-out’ organization employment into employment at worksites dispersed over 

different counties. For larger organizations multiple worksites in different states can be 

identified. As services and products of exempt organizations are often tied to local sites, this 
 

 

 

 

Distortions in nonprofit employment 22 August 2007 5 

Martin David, Urban Institute 

geographic information is an extremely valuable addition to the Form 990/990-EZ report 

(Salamon-Sokolowski 2005]. 

(c) IRS W-2 reports total employment for a 12-month reference period. That is, every 

employee receiving wages in the prior calendar year will be counted. Multiple job-holders and 

employees switching jobs during the year will be counted twice. Multiple job-holders and some 

employees switching jobs during a month are counted twice on the QCEW and Form 941. While 

W-2 and Form 941 contain payroll information for different reporting periods, combining the 

four Forms 941 filed during a calendar year produces payroll comparable to Form W-2. Monthly 

employment for employers that do not file Form 941 might be estimable from the available 

annual information. 

In conclusion, a match of Forms 990/990-EZ to IRS Form 941 for March will yield a larger 

count of nonprofit employees than the QCEW. The QCEW match gives insight to the 

distribution of multi-establishment employment across worksites.7 

3.2 Losses from linking nonprofit information returns to other sources 

Any errors in ein’s being matched reduce the quality of matched data. Errors in identifying 

numbers arise from reporting errors by filers, from changes in the legal organization that entail a 

new identifier for continuing (perhaps expanded) activities, and from failures to maintain correct 

identifiers in the two record systems. 

 Errors in identifiers have two consequences: failed matches and mismatches. An incorrect 

identifier in the IRS file leads to a failed match when no corresponding identifier exists in the 

second data source, and vice versa. Mismatches result when the incorrect IRS identifier matches 

the identifier of a disparate organization in the second data source, and vice versa. The 

proportion of nonprofit organizations is small relative to the populations in the QCEW and Form 

941 universes, so mismatches are most likely to relate information about taxable organizations to 

the exempt organization. Failed matches reduce the coverage of statistics based on both records. 

Mismatches badly distort statistics. Both levels of the matched data and correlates of those data 

are distorted (Scheuren-Winkler 1997). For example, when employment is imputed to Form 990-

7

 As we describe later, non-filing employers can be identified from the IRS Registry of exempt organizations, 

an extract from the IRS Business Master File. 
 

 

 

 

 

 

Distortions in nonprofit employment 22 August 2007 6 

Martin David, Urban Institute 

EZ from Form 941, any difference in the mean employment of exempt organizations and the 

mean employment of mismatched employers will bias the imputed mean. 

4 Matching QCEW and IRS information on exempt organizations 

Our investigation matches IRS public information on nonprofits to the QCEW. Most 

estimates refer to matches and employment for March, 2003. 

4.1 Joining QCEW and IRS information 

Matching Forms 990/990-EZ, the Registry, and the QCEW yields eight outcomes. Outcomes 

that link QCEW to IRS information are indicated by m in the text table below. Unmatched 

records are indicated by “*”. Outcomes 1-5 are useful. Outcome 1 gives the most complete 

information since all three data files match. (Outcome 3 occurs primarily as organizations whose 

application for exempt status is pending, file Form 990/990-EZ.) Outcomes 2 and 4 do not 

match QCEW, but information on Forms 990/990-EZ is informative. 

 Outcomes 

Record system 1 2 3 4 5 6 7 8 

Forms 990/990-EZ m * m * 

Registry m * m * 

QCEW m m m * 

Outcomes 6-8 are uninformative. The function of the Registry is to identify active exempt 

organizations. Unfortunately, organizations that are inactive or defunct sometimes linger for a 

substantial time before they are identified and removed. Thus unmatched Registry records 

(outcome 6) overstate the number of active unmatched organizations. Unmatched QCEW records 

(outcome 7) include nonprofit entities, but they can not be identified reliably.8 Some nonprofits 

are not UC liable and do not file information returns (outcome 8). Neither IRS nor QCEW 

records afford insight into this group. 

8

 Employers are asked to identify tax-exempt status, but the information is not well-reported. 
 

 

Distortions in nonprofit employment 22 August 2007 7 

Martin David, Urban Institute 

Outcomes 1-4 include all exempt organizations filing Forms 990/990-EZ and processed into 

the NCCS:1999-2003.9 They constitute a census of operating charitable organizations, covering 

all states. Unmatched Forms 990/990-EZ (Outcome 2 and 4) provide information about 

organizations that do not fall in the QCEW universe. Understanding the unmatched cases is a 

lever that allows us to estimate employment outside the UC system and the proportion of 

organizations that operate without paid employees, i.e. nonemployers. 

Outcome 5 matches the Registry to three types of organizations: exempt organizations other 

than charities (exempted under subsections other than 501(c)(3)), private foundations, and 

operating charities failing to file timely returns. 

Each matched Form 990 reveals whether the organization failed to report employment on 

line 90(b), a false negative (FN). Each matched Form 990-EZ and Registry record reveals the 

number of employees covered by the UC system at each worksite. No matches provide any 

information on employees excluded from UC coverage. 

4.2 Assessing matching errors 

4.2.1 Failed and invalid matches 

Some failed matches can be detected by invalid ein’s. Those ein’s have less than the 

required nine characters or they have ciphers that indicate the ein is unknown. We scanned both 

the Registry and the QCEW for invalid ein’s. The Registry contained less than 500 or 3/10,000 

invalid ein’s. Though the Registry contains ein errors, we regard it as a “gold standard”. Less 

than 90 failed matches arise when it matches a population of less than 300,000 organizations. 

The QCEW contained an average of 1.7% invalid ein’s in the years 1999-2003. These invalid 

ein’s were not randomly distributed across the 35 million records that we scanned. The 

probability of invalid ein’s was higher in establishments with few employees than elsewhere. 

The probability varied substantially over the 49 jurisdictions (46 states, The District of 

9

 Operating charities and public foundations exempted under 501(c)(3) are included. Coverage is limited by 

cut-off of data processing before late returns are filed, long after they are due to the IRS. 

Information from Forms 990 for other organizations is available from NCCS Core File [year] and NCCS 

Private Foundation File [year] at http://nccsdataweb.urban.org. 
 

 

 

Distortions in nonprofit employment 22 August 2007 8 

Martin David, Urban Institute 

Columbia, Puerto Rico, and the Virgin Islands) in our universe. Three states had probabilities 

over 0.03; six had probabilities less than 0.005. 

We created weights for the QCEW that increase counts of establishments and the number of 

employees. Weighting offsets downward bias of unweighted counts (David 2007).10 Weights on 

the QCEW were transferred to all matching IRS records. They are applied to Form 990-EZ and 

Registry matches in the estimates below. 

Additional match failures occur because valid ein numbers are corrupted in the process of 

filing and transmitting the tax-related reports that are the basis for the QCEW. Digits can be 

transposed, duplicated, or erroneously entered. We do not know what order of magnitude to 

assign to this problem. 

4.2.2 Removing mismatches -- Forms 990/990-EZ 

Before appropriate estimates could be made, matches were scanned for evidence of 

mismatches. The legal name of the organization and its industry class were critical information 

for detecting mismatches. Forms 990/990-EZ and the QCEW use different industry 

classifications, the National Taxonomy of Exempt Entities (NTEE) and NAICS respectively. 

These classifications are relatively similar at the sector level (Appendix A). In examining 

matched records we discovered several pathologies. Some parent-teacher organizations were 

associated with large numbers of establishments in banks. Some private organizations awarding 

fellowships and scholarships were associated with employee counts for state university systems. 

And some private nonprofit entities were associated with school systems or governments. In 

many of these cases the name on the Form 990 was substantially different than the name on the 

QCEW. The pairing of large numbers of establishments to the nonprofit organization was also 

suggestive of mismatching. Hundreds of establishments exist for only a few of nonprofit 

charitable organizations. Because Forms 990/990-EZ contain more information than the 

Registry, the procedure for removing mismatches of Forms 990/990-EZ differs from the 

procedure applied where the Registry matches QCEW and no Form 990 exists. 

10 Salamon-Sokoloweski (2005) did not weight their estimates from matching the Registry to QCEW for the 

selective character of invalid ein’s. 
Distortions in nonprofit employment 22 August 2007 9 

Martin David, Urban Institute 

We test the relationship between payroll reported to the QCEW and nonprofit expenditures 

on Form 990/990-EZ. If first-quarter establishment payroll exceeds 20 percent of total 

expenditures for the organization, the establishment-organization link is suspect. All links 

between establishments and organization with any suspect links to the QCEW were severed. The 

logic for this procedure incorporates two assumptions: A) Most organizations with a QCEW 

record for the first quarter of the year were in operation for a whole fiscal year. B) Annual 

compensation for the nonprofit is at least 20 percent less than total expenditures for the fiscal 

year. Prorating annual compensation levels to the first quarter, we expect that one-quarter of 

eighty percent of annual expenditures is a reasonable upper bound for first quarter compensation. 

The test identified 2,564 organizations as suspect in 2003. The total of matched Forms 

990/990-EZ was 85,852 prior to testing for suspect matches. Failing the test caused 3.0 percent 

of tentatively matched organizations to be recoded as unmatched. The suspect matches were 

dominated by links between tiny organizations and entities classified as NAICS 522 (credit 

intermediation) or NAICS 5412 (Accounting, tax preparation, bookkeeping, and payroll 

services). Three-quarters of the establishments involved with suspect links were tied to entities 

in those NAICS classifications. 

Over the five years, 1999-2003, an average of more than 8%, or 11,000, establishments 

matched to Form 990/990-EZ are suspect. This average is low, as information on total expenses 

was missing in 4% of the 1999 Form 990’s and 7% of the 2003 Form 990’s. Mismatching 

associated with organizations filing Form 990-EZ is astronomically larger than for organizations 

filing Form 990. Figure 1 presents the rate of mismatched establishments separately for Form 

990 and Form 990-EZ. Over 50% of establishments linked to Form 990-EZ proved to be suspect 

in years 2000-2002 where expense data were almost universally available. 

Following the removal of suspect matches to the Registry (next section), we re-examined 

Forms 990/990-EZ matches to determine whether any NAICS 52 (Finance and Insurance) 

organizations passed the expense test. 15 organizations were identified in the sector and delinked 

from QCEW. The count of mismatched Forms 990/990-EZ increased from 2,564 to 2,579. 
 

 

 

 

Distortions in nonprofit employment 22 August 2007 10 

Martin David, Urban Institute 

4.2.3 Removing mismatches – Registry matches, no Forms 990/990-EZ 

QCEW matches to the Registry contain no information on organization expenses. 11 We 

investigated two classes of matches: Organizations that are charitable and exempted under 

section 501(c)(3) of the IRC, and organizations whose 501(c) subsection was unknown. The first 

class is more extensive than the operating charities for which we have Forms 990/990-EZ. 

Private foundations and trusts are included. The 3,500 organizations with subsection unknown 

are likely to include a majority with 501(c)(3) activity.12 

Registry-QWEW matches reveal industry and name of the organization on both records. 

NAICS signals many mismatches. Organizations matched to NAICS 52 (finance and insurance) 

appear to be suspect, as they included multiple establishment links of banks to parent-teacher 

organizations, paralleling the most egregious mismatches identified among the Forms 990/990-

EZ. We excluded all public sector, business associations, and labor unions (NAICS 92, 81391, 

81393) as they are not generally §501(c)(3). We excluded broader classes than with Forms 990 

because organizations with unknown subsection could be 501(c)(4) or (9), not relevant to our 

analysis of 501(c)(3). A total of 1210 organizations with matches to the Registry were declared 

suspect, representing 5.1% of the 23,878 tentatively matched organizations. 

Taken together the delinked organizations are 3.5% of tentative matches. Estimates of 

employment that include identified mismatches would be wildly overstated. 

Lastly, in cases where the subsection was unknown, we surmise that some organizations are 

not charitable organizations. Organizations linked to NAICS subsectors including the public 

sector, business associations, and labor unions are unlikely to be operating charitable 

organizations. Organizations in all of these sectors were deemed not 501(c)(3), and excluded 

from the 501(c)(3) universe. Table 2 describes the division of subsection “NA” between those 

tabulated with 501(c)(3) and those excluded. It also shows that less than 500 501(c)(3) were 

reallocated out of that class. The editing procedures described produced an enhanced match that 

we discuss below. 

11 Only matches to the Registry where no Form 990 information is in the Forms 990 database are considered 

here. Such matches include organizations exempted under many subsections other than 501(c)(3). 

12 501(c)(3) is the dominant exempt group sampled by the IRS. Arnsberger (2006). 
 

 

 

 

Distortions in nonprofit employment 22 August 2007 11 

Martin David, Urban Institute 

4.3 Structure of matched and unmatched data 

4.3.1 Available data 

Matched data bring together information defined by different measures and collected from 

different universes. Important conceptual differences are displayed below. 

Attribute Form 990 Form 990-EZ QCEW 

Employment Elicited from 

all 

Not collected Employment collected. Excludes: Parttime workers of nonprofits in all but 19 states, 

and students working for school, student 

nurses. Interns (some states) 

Compensation Detail on 

wages, benefits and 

payroll taxes 

All 

employment 

related payments 

Payroll 

Industry 

classification 

NTEE NTEE NAICS 

Universe Exempted 

entities 

Exempted 

entities 

Employers liable to pay UC benefits 

Minimum 

threshold for inclusion 

3-yr. avg. 

revenue >$100,000 

$25,000 < 

3-yr. avg. 

revenue 

<$100,000 

1+ employee working more than 20 

weeks in a calendar year, US standard 

Excluded states 

(this investigation) 

None None MA, MI, NY, WY 

Excluded entities Most religious Most 

religious 

Employers with 1-3 workers (29 states), 

some religious organizations, 

small agriculture employers, some local 

governments 

Periodicity Fiscal year Fiscal year Calendar quarters 

The measure of employment is critical to our investigation. Form 990 elicits March 12 

employment; Form 990-EZ does not. All workers on the payroll should be counted. QCEW does 
 

 

 

 

Distortions in nonprofit employment 22 August 2007 12 

Martin David, Urban Institute 

not count part-time employees in many states; students at work in their schools, student nurses in 

hospitals, and interns are excluded in some states. 

Industry is classified by the National Taxonomy of Exempt Entities (NTEE) on Forms 

990/990-EZ and the Registry. Industry is classified by the NAICS on the QCEW. 

Average revenue over the last three years determines which IRS form is used. A few 

organizations file returns because they are required to do so by Federal contracting rules, or 

because they have provisional permission to operate as a charitable organization or association. 

4.3.2 Censoring pertinent to the QCEW universe 

Exclusion of nonprofit employers with 1-3 workers in 29 states, and part-time employees of 

nonprofits in 33 states (largely, but not the same as the previous states) drastically reduces 

coverage of the QCEW for small organizations. 

Exclusion of states. Four states (MA, MI, NY, WY) did not release their information for this 

study. Those states provide the BLS with QCEW information for all periodic estimates in the 

BLS publication program. BLS could tabulate nonprofit UC employees directly for the entire US 

universe from its QCEW data. Geographic censoring of QCEW records affects our partition of 

organizations into matched and unmatched. Clearly, matches are precluded whenever an 

organization operates exclusively in the four states that declined to participate, indicating that 

substantial numbers of UC eligible nonprofit employees were not available to us.13 In addition, 

some matches are truncated. 

Exclusion of establishments. Organizations that operate in both included and excluded states 

will appear with fewer matching establishments than their full complement of worksites. For 

example, an organization operating in the New York metropolitan area will match to its NJ and 

CT establishments; it will not match to any NY establishments. Some insight to the extent of this 

problem comes from the proportion of matched organizations that have multiple establishments. 

13 Nonprofit employment in NY, MA, and MI are ranked as 1, 8, and 9 by Salamon and Sokolowski (2006) in 

2004. WY employment ranks 50 out of 51 jurisdictions. The authors estimated MA and WY employment. The 

number of nonprofit employees, in millions, in those states is: New York (1.329), Massachusetts (0.474), and 

Michigan (0.470), and Wyoming (0.037). 
 

 

 

 

 

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Martin David, Urban Institute 

Truncated multi-establishment organizations. Nearly 9/10 organizations matching the 

QCEW and filing Form 990 have only one establishment in one state.14 Four percent of Form 

990 filers operate in several states. These estimates of multi-establishment rates are lower 

bounds, as we can not count worksites in excluded states. Virtually no organization that files 

Form 990-EZ has more than one establishment. See Table 3. Registry matches include nearly 

half as many multi-establishment organizations as Form 990 filers.15 

This background about multi-establishment organizations colors the meaning of a partition of 

the data that we use repeatedly. 

5 Learning from the matched data 

5.1 Classifying matched organizations 

The universe is partitioned into three groups: included states, matched; included states, not 

matched; and excluded states. An organization with one worksite belongs in only one of these 

classes. An organization with worksites in both included and excluded states could be located in 

two of the three classes. We resolve the ambiguity by placing all matched cases together, in 

included states, matched, irrespective of the location at which the Forms 990/990-EZ were filed. 

As a consequence, organizations classified under excluded states are a subset of exempt 

organizations that operate in those states. A few more complex organizations that operate in 

excluded states will have establishments in included states, matched and will be tabulated under 

that heading. Logically, those organizations include some whose activity is concentrated in 

included states; others, whose activity is in concentrated in excluded states. 

Table 4 describes the link of IRS information to the QCEW in our enhanced match for 

organizations. Two features of the table are highlighted by boxes: 

• Column 1, matched to QCEW? Yes, includes all IRS records that match the QCEW; 

14 Almost without exception, if the organization operates one establishment, it files in the same state where it 

operates. Organizations may operate in states different than the state in which Form 990 is filed. This may or 

may not connote multiple worksites. For example the accounting firm for the organization may file the Form 

990 in DC, but the organization has a single worksite in MD. 

15 Two circumstances could lead to this finding. Registry matches include some large organizations that have 

not yet filed. Alternatively, some mismatched organizations have not been deleted. No evidence for either of 

these alternatives is available. 
 

 

 

Distortions in nonprofit employment 22 August 2007 14 

Martin David, Urban Institute 

• Rows A – C include all organizations for which we have Forms 990/990-EZ. 

The intersection of the two boxes gives the most information. Outside the intersection row D 

lacks Form 990 data and the column excluded states lacks QCEW data. The total number of IRC 

501(c)(3) organizations is 277,015 (Row E, last column). More than 90 percent are organizations 

filing Forms 990/990-EZ (254,347 Row C, last column). 

One-third of Forms 990/990-EZ match the QCEW. That percentage rises to 38% when we 

compare matches to the total number of organizations with a presence in included states. This 

larger percentage is closer to the yield of matches that could be obtained were all the states in the 

US included. 

Row A reveals that only 8% of organizations filing Form 990-EZ match the QCEW. That low 

rate is consistent with the small expenditures of EZ organizations and the exclusion of many 

nonprofit workers from UC benefits. 

Thirteen percent of organizations do not match QCEW and file Forms 990/990-EZ from 

excluded states. The column labeled excluded states excludes multi-state organizations operating 

establishments in included states. For example, an organization that has an establishment in CA 

and files Form 990 from its headquarters establishment in NY will be included in the column 

labeled Yes because the CA establishment matches the QCEW. 

Row D shows that Forms 990/990-EZ matches are augmented by matches from the Registry 

increasing matches by 27%. Row F contains an estimate of Form 990/990-EZ matches that could 

be obtained from excluded states.16 When estimates are added to actual matches, Form 990/990-

EZ matching in the QCEW universe rises to 43% (Row G). 

Arnsberger (2006) estimates 9,000 more §501(c)(3) organizations than we find among Form 

990/990-EZ’s. Our Registry match raises the universe in Table 4 to 14,000 organizations greater 

than estimated in Arnsberger (2006). Both differences are far beyond sampling errors. A cutoff 

date for processing Forms 990 into the NCCS database may be responsible for shortfall of 

§501(c)(3) filers. The excess produced by Registry matches has quite different sources. The 

Registry match may capture some large organizations that do not file Form 990 within two years 

16 Matching rates for each type of Form in the included states and the distribution of Form 990 and Form 990-

EZ in excluded states are used to estimate the division of organizations in excluded states between the matched 

and unmatched columns (Row F). 
 

 

 

 

Distortions in nonprofit employment 22 August 2007 15 

Martin David, Urban Institute 

of the end their fiscal year.17 Alternatively, some organizations are not required to file and 

participate in the UC system. Large religious organizations are an example. At the other extreme, 

many small organizations not required to file Forms 990 have no employees and would not have 

a UC record that matches the Registry. The number of organizations detected by Registry 

matches is a puzzle.18 

5.2 Employment 501(c)(3) organizations, 2003 

5.2.1 Aggregates for the US 

Rows A, B, and D of Table 4 include seven cells defined by the IRS data available (Form 

990, Form 990-EZ, Registry), match status (match [yes, no]) in included states, and the 

remainder, unmatched organizations filing from excluded states. We use the same logical 

structure to display employment aggregates in Table 5. The number of organizations (from Table 

4) is repeated in the leftmost column as a guide to the reader. The column headed establishments, 

raw shows the number of establishments operated by matched organizations. The column headed 

establishments, weighted indicates the extent to which invalid ein’s conceal presence of 

matching establishments. The remaining columns pertain to estimates of employment. 

The subtotal row sums Form 990/990-EZ filers with worksites in included states.19 The row 

Available states adds employment from matches to the Registry to the subtotal. The total row 

counts both matched and unmatched employment in all states. As no QCEW data are available 

for excluded states, totals can not be calculated for QCEW employment or establishments. 

The IRS column labeled employment, raw contains reports from Form 990. The top row 

indicates that IRS reports on Form 990 exceed raw QCEW employment by 50,000 (0.74%) for 

17 SOI sampling does not substitute prior year records for large organizations that are missing from the stratum that 

is sampled with certainty. 

18 An alternative hypothesis is that some of the organizations treated as 501(c)(3) here should be classified 

elsewhere. That possibility can only be resolved with detailed study of more recent data, where the 501(c) 

subsection is more completely classified. 

19 The subtotal for organizations appeared in Table 4, column subtotal, row C. 
 

 

 

 

Distortions in nonprofit employment 22 August 2007 16 

Martin David, Urban Institute 

matched records. 20 That difference has two principal sources: (1) workers not covered by UC do 

not appear in QCEW; and (2) workers reported on Form 990 include workers in excluded states. 

Multi-state organizations that operate in both excluded and included states will show more 

employees in the first row than their QCEW report which excludes some states. 

The column Imputed shows more employment than raw because we substituted QCEW raw 

employment for zeros on Form 990’s that failed to report employment. Attribution of QCEW 

employees increases aggregate employment by 633,000 on Form 990’s, an increase of 9.3%.21 

This imputation is too small because many part-time workers and student workers are not 

counted in QCEW. Also, employees of organizations that have establishments in excluded states 

are understated to the extent that the organization has employees in the excluded states. 

Additional employees should be imputed to unmatched Form 990 records (in 2nd row and 

990, exc.). Employment is presumably unreported and at a greater rate than matched Form 990 

filers. Smaller organizations are likely to have more difficulty in correctly completing Form 990 

than matched organizations. Ratio estimation of the imputation is inappropriate, as a proportion 

of unmatched organizations are nonemployers, while nearly all matched records currently 

employ workers. A statistical model that encompasses both the decision to employ workers and 

the number employed is needed to impute employees to the unmatched records. 

 The third row displays matched Form 990-EZ. No employment information can be garnered 

from those records. Weighting QCEW employment makes imputed numbers more representative 

of the universe, while unweighted employment would understate levels in the exempt sector 

(David 2007a). Weighted QCEW employment is transferred to the Imputed column, in the third 

row. 

Matching QCEW to the Registry identifies 22,668 organizations that did not file Form 

990/990-EZ (Row 6). The Registry organizations contribute a weighted count of 32,749 

worksites and weighted employment of 1,777,000. Weighted employment from the Registry is 

added to the count from Forms 990/990-EZ in the column labeled augmented. A considerable 

20 Weighted QCEW employment exceeds raw IRS employment. However, weights are not appropriate in this 

context. The cells compared pertain to records that match, precluding invalid ein’s. Employment for 

unmatched Form 990 in included states is represented in the second row. 

21 Raw employment is used in the imputation as invalid ein’s can not occur when matches are successful. 
 

 

 

 

Distortions in nonprofit employment 22 August 2007 17 

Martin David, Urban Institute 

part of the 1.8 million may be employed in large, late-filing organizations. That is suggested by 

the relatively large numbers of establishments associated with the Registry matches. The 

character of the remainder of the organizations that we identify by Registry matches is unknown. 

In the total row, covering all states, augmented employment is 11.7 million (50%) higher 

than the raw, 7.8 million, count of Form 990 IRS employment. The difference lies in two 

enhancements to the Form 990 data: (A) the 1.8 million employees represented by Registry 

rather than Form 990/990-EZ matches in included states; and (B) the 0.6 million imputed 

employees unreported to IRS on Form 990, again, in included states. 

Three other aspects of employment aggregates are noteworthy. First, Form 990 counts 1.0 

million workers in organizations that file from included states and do not appear in the QCEW. 22 

This count understates employment, as explained above. Second, UC coverage for Form 990-EZ 

filers is small. We estimate that a quarter of Form 990-EZ filers are employers and only 8% 

match QCEW. (Employment in small organizations must be elicited directly from a revised 

Form 990-EZ.) Third, extrapolation of imputed employment, or modeling of an employment 

imputation, would increase employment numbers in excluded states by roughly 8 percent (the 

ratio of imputed to raw in the subtotal row). It appears prudent to investigate differences among 

industry classes before attempting that imputation, as reporting of employees is not uniform 

across industries. 

5.3 Employment in major industries 

5.3.1 Industry classifications 

Forms 990/990-EZ are classified by the National Taxonomy of Exempt Entities (NTEE). This 

classification was adopted by the nonprofit sector in the 1980’s and is used in IRS/SOI statistics 

on the sector. Although more detail is available, we used a classification that collapsed the code 

to 15 classes and unclassified. Labels for the NTEE classes appear in the text table below. 

22 A match of QCEW to the Registry could impute employment to the IRS Business Master File, where 

employment does not appear. The resulting employment count could be weighted adding 200,000 (2.4%) to 

totals available from the QCEW. This experiment makes clear that QCEW without the Form 990 employment 

count lacks substantial coverage of 501(c)(3) employment shown in table 5. 
 

 

 

 

 

 

 

Distortions in nonprofit employment 22 August 2007 18 

Martin David, Urban Institute 

Abbreviation NTEE classes Label 

A A Arts, Culture & Humanities' 

B not B4 B except B4 Education, excludes post-secondary 

B4 B4 Higher education (post-secondary) 

C, D C, D Environment, Animal-related 

E, not E2 E,F,G,H except E2 Health, not hospitals 

E2 E2 Hospitals (and support organizations) 

I, M I,M Crime, public safety 

J, K, L J, K, L Employment, Food & Agriculture, Housing 

N, O N, O Recreation sports, Youth development 

P P Human services, multi-purpose, and other 

Q Q International, foreign affairs 

R – W R, S, T, U, V, W Advocacy, Philanthropy, Science, Society 

benefit 

X X Religion related 

Y Y Mutual/ membership benefit 

Z Z Unclassified 

The NTEE 15 provides detail that is similar to NAICS sectors. NAICS industry classes are 

available only for records matched to the QCEW. Those classes apply to establishments and can 

vary over the distinct worksites identified through the BLS disaggregation of multi-establishment 

organizations to counties. Multiple classifications occur in less than 10% of matched cases 

(derived from Table 3). 

Table 6 shows the distribution of organizations and matched establishments over NTEE 

classes. The difference in the distribution of matched establishments and the distribution of 

organizations reflects (a) variation in the match rate by NTEE and (b) differences in the 

proportion of organizations that have multiple establishments in different NTEE classes. For 

example, A, Arts organizations, tend to be small with too few employees to be matched. They 

also are unlikely to have multiple sites. The result is that matched establishments are 6% of all 

establishments, while arts organizations are 10% of the total. E2, Hospitals, reflect the opposite 
 

 

 

Distortions in nonprofit employment 22 August 2007 19 

Martin David, Urban Institute 

situation; match rates are high and many have multiple establishments. Hospitals are 4% of all 

matched establishments, and 1% of all organizations. 

5.3.2 Employment by NTEE 

Table 7 disaggregates employment into 15 NTEE classes. Weighted counts from the QCEW 

in column 3 are unbiased for each state and size of workforce.23 Columns 4-6 display NTEE 

aggregates of raw, imputed and augmented IRS employment (defined as in Table 5). Column 4 is 

limited to Form 990 information. The imputed and augmented columns enhance Form 990, Form 

990-EZ, and Registry matches with available QCEW data. Augmented employment is larger than 

the weighted QCEW for each of the 15 NTEE classes. More employees are identified by QCEW 

than by Form 990 in three industries (B not B4; X; and Y). 

The outcomes of imputation and augmentation vary widely over the 15 NTEE classes. Both 

Education, B not B4, and Mutual membership benefit, Y, acquire more than half of their 

employment from Registry matches. Mutual membership benefit, Y, also shows a large increase 

because employment is unreported on Form 990. At the other extreme, International, foreign 

affairs, Q, report employment well and are seldom identified by Registry matches. Together, 

imputation and augmentation increase reported employment for Q by 7.3%. 

Table 8 reveals the impact of imputation and augmentation through ratios of employment 

counts to various bases. Column 1, imputation rate, of Table 8 displays imputed employment as 

a proportion of employment reported by matched organizations filing Form 990. This ratio is 

smaller than the 20% of organizations that fail to report employment on matched Forms 990 

because the level of employment is lower in nonreporting organizations. The range of column 1 

is from 4% for E2, Hospitals and their related support organizations to 90% for Y, mutual/ 

membership benefit organizations. 

Column 2, Augmentation rate, displays the proportional increase of imputed employment 

that comes from Registry matches (over the included QCEW states). The concentration of 

unclassified industries in Registry matches assures that the augmentation rate is extreme for 

class Z. The reasons for remaining rates over 100% are unclear. Educational institutions other 

than higher education, class B not B4, may administer small trusts established to finance 

23 Weights do not control for industry, and introduce variance into these estimates (David 2007). 
Distortions in nonprofit employment 22 August 2007 20 

Martin David, Urban Institute 

scholarships. Employees in this case may be educators in the school, while the trusts are 

nonemployers. The trusts may be exempt from filing information returns. Further study of NTEE 

classes with high rates of augmentation is appropriate. 

Sorting the NTEE classes according to the proportionate change induced by imputation 

(column 1) gives the middle panel of Table 8. Sorting the NTEE classes according to the 

proportionate change induced by augmentation (column 2) gives the right panel of the table. The 

bold NTEE classes in the sorted panels are defined by the partition of all classes into thirds. E2 

and Q lie in the bottom third of both imputation and augmentation. B not B4; N, O; and Y lie in 

the top third of both imputation and augmentation. The association may be due to a concentration 

of small and relatively new organizations in the top third. 

We conclude: 

• Imputation of employment on Forms 990 is essential. Imputed employment counts 

exceed matched Form 990 in most industries by more than 10%. Higher education, hospitals, 

and international organizations are the exception. 

• A match of QCEW to the Registry is needed to augment IRS employment estimates 

for Education (not higher education) and for religious organizations. 

• Augmented employment is sufficiently larger than a match which relies only on 

QCEW in most NTEE classes that QCEW can not be the sole source for employment 

information on charitable organizations. 

6 Evaluation 

6.1 Nonemployers and matching: How much do we know? 

Accounting for nonemployers gives another perspective on coverage and employment 

reported in Tables 4 and 5. Both Form 990 and Form 990-EZ elicit reports of compensation. If 

that information correctly predicts absence of employees, it can be used in imputing employees. 

Comparison of Form 990 records matched to QCEW records revealed that 20% of organizations 

fail to report employment. 97% of the non-reporting organizations reveal compensation. The 

consistency of compensation reporting in the two record systems makes compensation a useful 

predictor of employment. However 1.1% of matched forms report neither compensation nor 
 

 

 

Distortions in nonprofit employment 22 August 2007 21 

Martin David, Urban Institute 

employees on Form 990. More than three-fifths of this group should report employment on Form 

990. Absence of compensation and employees on Form 990 do not always predict nonemployers. 

Unmatched Forms 990 in included states show 51% with no compensation; organizations in 

excluded states show 31% with no compensation. Using those estimates we calculate that almost 

50,000 of the 201,000 Form 990 filers are not employers; and 37,000 of the 53,000 Form 990-EZ 

filers are not employers. In all, 87,000 of the 254,000 Form 990/990-EZ filers can be tentatively 

identified as nonemployers. Those estimates are too high, as we can not quantify the proportion 

of filers who bury compensation expenses among other expenses.

24 

Our estimate of nonemployers can be applied to rows C and F in Table 4. 83,300 matches 

plus the 12,800 matches estimated for excluded states gives 96,100. Dividing those matches by 

the difference between all filers and nonemployers, 254,000 less 87,000, yields a match rate of 

57%. That compares to the 43% rate shown in row G. A clear reality is that some employers are 

exempt from UC and will never match. However, unknown errors also contribute to low match 

rates. The level of failed matches is certainly more than the 1.7% we have identified. An 

important contributor to those errors are birth, death, and merger of organizations. Each of those 

events can create discrepancies between ein’s used in filing Forms 900/990-EZ and QCEW. 

6.2 Adequacy of employment estimates for charitable organizations 

At this point we see a glass half-full, half-empty. The 2002 Economic Census counts 9.5 

million employees in exempt organizations in those industries in which charitable organizations 

are concentrated (Table 1). Some additional charities and religious organizations are counted in a 

sector that includes many exempt organizations that are not charities. The failure to divide 

exempt into two groups – (a) charities (501(c)(3)) and religious congregations and (b) other 

exempt entities –compromises the policy value of the estimates. Exclusion of K-12 and higher 

education compromises those estimates. 

The match of QCEW to IRS counts almost as many 501(c)(3) employees as the Economic 

Census, in a universe that excludes QCEW information for four states. The match shows 1.8 

million employees in education that are largely excluded from the Census universe. 

24 IRS/SOI has identified this pathology in completing Form 990 as an important source of error. 
Distortions in nonprofit employment 22 August 2007 22 

Martin David, Urban Institute 

IRS counts 1 million more employees in charitable organizations than QCEW. IRS counts 

0.7 million less than Census, when primary and secondary education are excluded. IRS fails to 

impute Form 990 and elicit employment for Form 990-EZ. Substituting QCEW employment for 

missing information fills most of the Census-IRS gap, via the 0.6 million employees we have 

imputed. More imputation is needed to estimate unreported employment for unmatched Form 

990 records. 

Our largest employment estimate for charitable organizations, the augmented composite of 

QCEW and Form 990, is 11.7 million, or 9.0 million, when education is excluded. That estimate 

is for 2003, while the comparable Census number reflects a smaller population of organizations 

with fewer employees in 2002. Including exempt organizations other than 501(c)(3) brings our 

augmented estimate to 13.3 million, substantially larger than the Census counts including all of 

NAICS 813. 

The current, quinquenial Census estimate does not adequately track increasing employment 

in a sector that is growing rapidly (David, Pollak, Arnsberger 2006). Total nonprofit 

employment is the same order of magnitude as the health sector of the economy (which includes 

a major group of exempt organizations). 

6.3 Timeliness and employment dynamics 

Openness and accountability motivate the mandate for exempt entities to file information 

returns open to the public. Donors, potential donors, and persons valuing an equitable and 

efficient tax structure need to know that every exemption is not a scam. 

The gestation period for both Census and IRS/SOI statistics on exempt organizations is more 

than two years, an interval that does not enable public review at a time when malfeasance can be 

nipped in the bud. Estimates of employment in exempt organizations could be produced by 

QCEW nine months after the quarter. The gestation period for estimates from Form 941 would 

be no longer. Tallies of those administrative records would also reveal the number of exempt 

organizations (or establishments), the exempt subsection (e.g., 501(c)(3)), and the NTEE 

classification of those organizations. 

We know that births and deaths of enterprises account for a large part of the flux in job 

creation and job destruction. (Haltiwanger, Davis, Schuh 1996; BED, BLS) The annual rate of 

births and deaths is staggering. A speculation is that both births and deaths of charitable 
 

 

Distortions in nonprofit employment 22 August 2007 23 

Martin David, Urban Institute 

organizations exceed levels in the private business sector. We can not know, until charitable 

organizations are partitioned from other private, nonfarm business employers. 

6.4 Summing up 

A great deal of value attaches to statistics on employment, and employment growth, in 

exempt organizations with classification by industry and geography. The potential to produce 

those statistics exists in current administrative record systems. The substantial tax subsidy to 

donors to charitable organizations, and a need to know more about how these organizations 

perform argues eloquently to publish employment estimates for charitable organizations, other 

exempt organizations, and the residual of private business. 

QCEW has been shown to enhance statistics derived from Forms 990/990-EZ and the 

Registry. The Form 941 appears to have a greater capacity to count employees, but that has not 

yet been proven. Coverage and presentation of charitable organizations in Economic Census 

needs to be improved to allow policy analysts to associate changes in employment with tax 

expenditures estimated for the sector. 

7 A work plan for the future 

7.1 Statistical Agencies 

7.1.1 First-best activity 

Both IRS/SOI and the Census have access to Form 941, with its employment and payroll 

information. Both agencies have unlimited access to information returns filed on behalf of 

exempt organizations and the Register.

25 The steps taken in this paper can be replicated on Form 

941. The tri-partite match – Forms 990/990-EZ, Registry, and Form 941 – can be executed in 

both agencies. Census may have an advantage in editing and linking records (Winkler 2004); 

IRS/SOI may have earlier and more comprehensive access to records. 

Both agencies currently receive updates from IRS Business Master Files monthly. Those 

files contain extracts from Form 941 and Form 990/990-EZ. The registry is also updated 

monthly. Both agencies could devise a quarterly estimate of exempt employment that is 

25 Publication of identifiable information at the organizations level is sanctioned. So no disclosure review is 

necessary at the organization (ein) level of detail. 
Distortions in nonprofit employment 22 August 2007 24 

Martin David, Urban Institute 

subsequently benchmarked to the more thoroughly edited annual samples of Form 990/Form

990-EZ produced by IRS/SOI. 

Indicators of exempt status and applicable IRC section can be taken from Form 990/990-EZ 

and the IRS Registry. They can be inserted into the Census Business Register. That would enable 

sampling using exempt status (not exempt, 501(c)(3), other exempt) and, more importantly, 

analyses of differences between exempt and other organizations. 

7.1.2 Second-best activities 

A. IRS/SOI can impute unreported employment on Form 990. This should yield far more 

employment than the 633,000 we substituted from the QCEW. We know from this investigation 

that even incomplete imputation can produce substantially larger employment for Form 990 than 

employment reported to the QCEW (Table 5). 

The BLS has its own business register that is derived from the QCEW. Under current law 

BLS can not access the Form 941, but it can receive the continuous stream of Forms 990/990-EZ 

as they become available in the IRS Business Master File, because all of that information is 

public. Thus it is feasible for BLS to continue the tri-partite match – Forms 990/990-EZ, 

Registry, and QCEW – pioneered in this research. The IRS Business Master File does not include 

employment so that employment estimates would only cover the QCEW universe. Such 

estimates could be produced within the current nine-month interval after the quarter that is the 

timetable for QCEW reports. The QCEW exempt employment series should be compared to SOI 

employment estimates that lag the reporting year by about 30 months. 

The gain from a continuing BLS activity would be to partition Business Employment 

Dynamics (BLS webpage) into estimates of private for-profit and a private nonprofit job creation 

and destruction. 

7.2 Operating Agencies 

7.2.1 IRS/TEGO 

IRS/TEGO administers approvals for tax exemption, updates the Registry and classifies 

exempt organizations by NTEE. IRS/TEGO has the power to reject Forms 990/990-EZ that are 

incomplete. It can identify organizations that fail to file timely information returns. It can reject 

all Form 990 returns where employment is not reported. IRS/TEGO should also reject Form 990 

where no compensation is paid and employees are present. 
 

 

 

 

 

Distortions in nonprofit employment 22 August 2007 25 

Martin David, Urban Institute 

IRS/TEGO is in the process of redesigning Form 990 to assure compliance of exempt 

organizations with terms of their approval. They can ask organizations to report employment on 

Form 941; that would assure that employment is public information for larger organizations.26 It 

can ask to have Forms redesigned so that answering the employment question is tied directly to 

reports of positive compensation. Then Form 990-EZ could have an employment question that is 

conditional on positive compensation. 

Electronic filing of Form 990 is required for large organizations and facilitated by free 

software for small organizations. With e-filing, Forms that fail to report employment, when 

requested, can be rejected by edits in the e-filing software. That eventuality will ultimately 

greatly reduce current unreported employment. 

7.2.2 OMB/OIRA 

OMB/OIRA administers the Paperwork Reduction Act. It contains the Office of the Chief 

Statistician whose role is to coordinate the US statistical agencies and provide guidance to good 

statistical practice. The Chief Statistician needs to be convinced that higher priority be given to 

employment statistics for charitable organizations. 

Acknowledgements 

I thank the Urban Institute and the Bureau of Labor Statistics for their far-sighted access to 

microdata pertaining to nonprofit organizations. The National Center for Charitable Statistics and 

its Dataweb (NCCS 2003) provided the Registry and Form 990/990-EZ from 1999-2003 for this 

research. Linda Lampkin and Tom Pollak offered critical suggestions on what was needed for 

policy-making on charitable organizations. Jen Auer ably assisted me in identifying mismatches 

and thinking about multi-establishment organizations. Kendal Golladay prepared extracts of the 

population files and detected invalid EIN’s. 

26 They can also ask for number of employees reported in connection with filing of W-2 at the end of the calendar 

year. That would establish number of employees in a reference year, a larger count than the number of employees in 

a reference pay period. Both measures are needed to estimate employment among small employers who currently 

file Form 990-EZ. 
 

 

 

 

 

 

 

Distortions in nonprofit employment 22 August 2007 26 

Martin David, Urban Institute 

Amy Knaup and Merissa Piazza reviewed work-in-progress and provided disclosure review 

for the tables presented. Rick Clayton and David Talan educated me about the QCEW program 

and reviewed this paper and David (2007). Access to BLS data through its secure research site is 

overseen by thoughtful peer review, chaired by James Spletzer, and is a major resource for 

scientific research on data collected by the BLS. 

The views expressed here do not reflect policies of the BLS. I am responsible for the design 

of this study and errors in its execution. I hope others can advance beyond these limited results. 

References 

Arnsberger, Paul. Fall, 2006. Charities and other tax-exempt organizations. SOI Bulletin. Washington DC: 

IRS/Statistics of Income. 26:2, 231-245. 

Brody, Evelyn (ed.). 2002. Property-tax Exemptions for Charities. Washington DC: Urban Institute Press. 

BLS webpage. Business Employment Dynamics: www.bls.gov/bdm/home.htm. 

David, Martin H. 2007. Employment in Nonprofit Entities: Coverage, Bias, and Measurement Errors in QCEW and 

public IRS Information, 1999-2003. 2006 ASA Proceedings. Alexandria VA: American Statistical Association. 

(CD- ROM publication). 

David, Martin H, Thomas Pollak and Paul Arnsberger. 2006 Compliance with information reporting: Exempt 

Organizations. IRS Research Bulletin: Recent Research on Tax Administration and Compliance (Publication 1500) 

231-245. 

Davis, Steven J., John C. Haltiwanger, and Scott Schuh. 1996. Job Creation and Destruction. Cambridge MA: MIT 

Press. 

Fellegi, I. P., and A. B. Sunter. 1969. A theory for record linkage. Journal of the American Statistical Association, 

64(328), 1183--1210. 

Foster, Lucia, Joel Elvery, C. J. Krizan, David Talan. 2007. Preliminary Micro Data Results from the Business List 

Comparison Project. Proceedings of the American Statistical Association, 2006 (forthcoming). 

Gronbjerg, Kirsten A. and Erich T. Eschmannn. May 2005. Indiana nonprofit employment. Ctr. on Philanthropy, 

School of Public and Environmental Affairs, Indiana University and the Johns Hopkins Nonprofit employment data 

project. 

Helliwell, John and H. Huang. 2005. How’s the job? Well-being and social capital in the workplace. NBER working 

paper 11759. Cambridge MA: NBER (on-line). 

Independent Sector. 2003. The Nonprofit Almanac: 2002. 

Michigan Nonprofit research program. 2005. Economic benefits of Michigan's nonprofit sector: 2004. 

NCCS:<year>. GuideStar-NCCS National Nonprofit Research Database [Years 1999-2003] Washington DC: Urban 

Institute. 

Okolie, Cordelia. 2004 July. Why size class methodology matters in analyses of net and gross job flows. Monthly 

Labor Review, 3–12. 

Salamon, Lester M. and S. Wojciech Sokolowski. 2005 Sept. Nonprofit organizations: new insights from QCEW 

data. Monthly Labor Review, 19–26. 

Salamon, Lester M. and S. Wojciech Sokolowski. 2006 Dec. Employment in America’s charities: a profile. 

Nonprofit Employment Bulletin 26. Baltimore MD: Johns Hopkins Center for Civil Society Studies, Table 3. 
 

 

 

 

 

 

 

 

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Scheuren, Fritz and William E. Winkler. Regression analysis of data files that are computer matched – Part II 

Survey Methodology, 1997. 

Spletzer, James and Joel Elvery. 21 October 2005. Presentation to CNSTAT workshop “Benefits of Interagency 

Business Data Sharing”. 

United States. 2008 Budget of the United States. Table 19-3. 

Vilhuber, Lars, Bryce E. Stephens, John M. Abowd, Fredrik Andersson, Kevin L. McKinney, Marc Roemer and 

Simon Woodcock (forthcoming, draft 2005 CRIW conference at NBER.org) The LEHD Infrastructure files and the 

creation of the Quarterly Workforce Indicators. 

Winkler, William E. 2004. Methods for evaluating and creating data quality. Information Systems, 29: 531-550. 

Appendix A. Comparison of NTEE and NAICS classifications 

The granularity of industry coding used in this analysis allows for 15 bins of the NTEE 

(excluding unclassified) and 15 bins for the NAICS. If the information in both coding systems 

were identical and no errors were made in coding, all NAICS sector codes should map into one 

NTEE bin, and conversely. Figure 2 shows the allocation of NAICS industries to NTEE classes 

for NTEE-NAICS combinations that include a total of 90% or more of NTEE employment.27 

Three NAICS sectors are “well-behaved” as the sector maps uniquely to one NTEE class. Seven 

additional sectors match to two NTEE classes. Four sectors (54, 61, 62, and 81) are substantially 

partitioned as NAICS is distributed to five or more NTEE bins. 

27 Limiting the combinations of NAICS to NTEE to classes that contain the preponderance of employment reduces 

combinations that result from a low level of classification error. The share of employment included was chosen to 

avoid problems with disclosure of employment information within each NTEE-NAICS combination. 
 

 

Tables and Figures for Distortions in nonprofit employment 22 May 2007 28 

Urban_institute_report2_22may2007rev21aug07.doc 

Table 1. Nonprofit employment reported in Economic Census 2002 

Naics 

classification 

Employment 

A C D 

Exempt All Ratio: A/C 

Establishments 

E G H 

Exempt All Ratio: E/G 

61 

62 

71 

813 

Total

 exc. 813 

 inc. 813 

120 431 0.28 

7,980 15,048 0.53 

1,363 1,847 0.74 

936 936 1.00 

9,463 17,326 

10,400 18,262 

12 50 0.24 

136 703 0.19 

49 109 0.45 

11 11 1.00 

197 862

208 874 

Source: A1 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Tables and Figures for Distortions in nonprofit employment 22 May 2007 29 

Urban_institute_report2_22may2007rev21aug07.doc 

Table 2. Reallocation of NA and mismatched 501(c) subsection 

matched organizations, 2003q1* 

Reallocated 501(c) Type of match Total 

subsection subsection Forms 990 Registry Count Percent 

501c3 plus NA 

501(c)(3) 

171 2,338 

83,117 20,330 

2,509 

103,447 

2.4 

97.6 

Total 83,288 22,668 105,956 100.0 

Type of reclassification 

None LbrBusGov 

Not 501c3 NA 

501(c)(3) 

Other 

5 527 

0 409 

64,872 0 

532 

409 

64,872 

0.8 

0.6 

98.6 

Total 64,877 936 65,813 100.0 

* Excludes all Naics 52 (Finance and Insurance). 

Source: Table 10. 02oct06. 

Wss_tables16oct06_d21may22mar07.xls 
 

 

Tables and Figures for Distortions in nonprofit employment 22 May 2007 30 

Urban_institute_report2_22may2007rev21aug07.doc 

Table 3. Proportion of matched organizations with multiple worksites, interstate 

operations 

By type of match, 501c3 plus organizations, 2003q1 

Organ- Rate: MultiMatch izations establishment Rate: multi-state 

Form 990 79045 9086 0.115 3161 0.040 

 Form 990-EZ 4243 d * d * 

Registry 22668 1197 0.053 482 0.021 

d, not disclosable 

* Less than 0.005 

Source: 12. 03oct06. 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Tables and Figures for Distortions in nonprofit employment 22 May 2007 31 

Urban_institute_report2_22may2007rev21aug07.doc 

Table 4. Strata defined by QCEW matches to Forms 990, 501(c)(3) organizations, 

2003q1* 

Included states Excluded Total 

Matched to 

QCEW? Subtotal states 

Yes No 

A Form 990-EZ 

 proportion of Forms 990 

4,243 

0.080 

42,166 

0.793 

46,409 6,733 

0.127 

53,142 

1.000 

B Form 990 

 proportion of Forms 990 

79,045 

0.393 

95,294 

0.474 

174,339 26,866 

0.134 

201,205 

1.000 

C Subtotal NCCS Census 

 proportion of Forms 990 

83,288 

0.327 

137,460 

0.540 

220,748 33,599 

0.132 

254,347 

1.000 

D Master QCEW matches 22,668 22,668 22,668 

augmentation rate 

0.10268723 

E TOTAL 105,956 137,460 243,416 33,599 277,015 

 proportion of total 0.382 0.496 0.121 1.000 

F 

G 

Estimated matches** 

UNIVERSE 

 proportion of universe 

12,797 

118,753 

0.429 

20,802 

158,262 

0.571 

277,015 

1.000 

0 

277,015 

1.000 

H 

I 

990dd/all_dd 

match rate 990 

0.790 

0.377 

0.800 

0.381 

*Includes 4,836 cases where 501(c) section is not known. 2338 are in the Master matches; the remainder 

are relatively equally distributed across the filing population. 

**Entry in 'Yes' column is the product of the estimated match rate in excluded states (row I) and the 

33,600 excluded filers (row E). 

No estimate of additional augmentation is included. 

Source: Table 1 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Tables and Figures for Distortions in nonprofit employment 22 May 2007 32 

Urban_institute_report2_22may2007rev21aug07.doc 

Table 5. Imputation and augmentation of Form 990 Employment, 

2003, Section 501(c)(3), in 1,000’s 

Source Match? Orgs. 

QCEW emp. 

Raw Wtd. Raw 

IRS employment 

Imputed Augmented 

990, inc. 

Yes 

No 

990-EZ, 

inc. 

Yes 

No 

79 

95 

4 

42 

6,780 6,930 

10 10 

6,831 

1,005 

NA 

7,463 7,463 

1,005 1,005 

10 10 

Subtotal 

Registry Yes 

220 

23 

6,790 6,940 

1,724 1,777 

7,836 

NA 

8,478 8,478 

NA 1,777 

Available states 243 8,514 8,717 10,255 

990, exc. 

990-EZ, 

exc. 

27 

7 

1,485 1,485 1,485 

NA 

Total 277 NA NA 9,321 9,963 11,740 

Excess of IRS employment over included QCEW 1.16 1.22 

Italics reflect model-based weighting of QCEW and substitution of QCEW for missing employment reports to IRS. 

Imputation would increase employment in unmatched and excluded states. 
 

 

 

 

 

 

Tables and Figures for Distortions in nonprofit employment 22 May 2007 33 

Urban_institute_report2_22may2007rev21aug07.doc 

Table 6. Organizations and matched establishments by NTEE

 2003 q1, 501c3 plus select NA subsection 

IRS Organizations QCEW establishments 

NTEE 15 Count 

A 28,582 

Percent 

10.3%

Count 

10,468

Percent 

6.0% 10,628

Wtd. 

B not B4 47,890 17.3% 20,487 11.8% 20,749 

B4 1,376 0.5% 2,029 1.2% 2,061 

C,D 10,273 3.7% 4,977 2.9% 5,047 

E not E2 33,480 12.1% 30,167 17.4% 30,496 

E2 3,378 1.2% 6,968 4.0% 7,067

I 4,811 1.7% 3,578 2.1% 3,619

J,K,L 21,069 7.6% 13,254 7.7% 13,405

M 4,003 1.4% 731 0.4% 741

N,O 25,772 9.3% 9,124 5.3% 9,249

P 38,627 13.9% 41,943 24.2% 42,374 

Q 4,982 1.8% 2,112 1.2% 2,149

R - W 32,980 11.9% 17,028 9.8% 17,256 

X 17,484 6.3% 7,681 4.4% 7,820

Y 659 0.2% 489 0.3% 495

Z 1,649

Total 277,015

0.6% 

100.0%

2,179 

173,215

1.3% 2,218

100.0% 175,373

Source: T5A_14sep06. 

Wss_tables16oct06_d21may22mar07.xls 
 

 

 

 

Tables and Figures for Distortions in nonprofit employment 22 May 2007 34 

Urban_institute_report2_22may2007rev21aug07.doc 

Table 7. Employment by NTEE major sectors, 2003 q1, 501c3 plus select NA subsection 

NTEE 15 

IRS organizations 

QCEW employment 

Raw Wtd. 

IRS employment 

Augmented** 

Raw Imputed* 

A 28,582 184,565 187,908 243,222 260,772 289,694 

B not B4 47,890 1,119,588 1,158,436 577,391 644,346 1,381,306 

B4 1,376 728,814 757,030 1,107,722 1,184,338 1,270,880

C,D 10,273 65,756 66,928 70,176 78,222 83,430 

E not E2 33,480 1,272,976 1,289,056 1,329,935 1,439,382 1,713,259 

E2 3,378 2,884,275 2,971,198 3,525,270 3,635,550 3,875,725 

I 4,811 47,447 47,882 55,246 62,594 65,325 

J,K,L 21,069 270,879 273,897 362,594 400,201 428,882 

M 4,003 7,181 7,226 6,940 8,167 9,199 

N,O 25,772 140,490 142,051 123,994 141,340 185,005 

P 38,627 1,258,663 1,271,529 1,544,368 1,693,076 1,761,028 

Q 4,982 20,429 20,687 39,046 40,835 41,882 

R – W 32,980 277,378 282,398 265,133 297,781 359,063 

X 17,484 125,731 128,391 64,997 69,936 160,529 

Y 659 13,057 13,207 3,424 5,411 14,855 

Z 1,649 96,660 99,043 1,175 1,261 99,769 

Total 277,015 8,513,889 8,716,863 9,320,633 9,963,211 11,739,831 

* Substitutes QCEW employment for matched Form 990, employment NA, and matched Form 990-EZ. 

** Adds Registry matches to imputed. 

Source: T5B_14sep06. 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

Tables and Figures for Distortions in nonprofit employment 22 May 2007 35 

Urban_institute_report2_22may2007rev21aug07.doc 

Table 8. Imputation and augmentation, 2003q1, 501(c)(3) 

Matched Form 990's 

Ordered by NTEE 15 

Impu- Augmentation tation 

NTEE 15 rate* rate** 

A 0.107 0.111 

B not B4 0.173 1.144 

B4 0.086 0.073 

C,D 0.132 0.067 

E not E2 0.117 0.190 

E2 0.043 0.066 

I 0.178 0.044 

J,K,L 0.139 0.072 

M 0.197 0.126 

N,O 0.177 0.309 

P 0.127 0.040 

Q 0.055 0.026 

R - W 0.154 0.206 

X 0.118 1.295 

Y 0.906 1.745 

Z 0.164 78.110 

All 0.093 0.210 

Ordered by 

Imputation 

NTEE 15 rate* 

E2 0.043 

Q 0.055 

B4 

0.086 

A 

0.107 

E not E2 0.117 

X 

0.118 

P 

0.127 

 C,D 0.132 

 J,K,L 0.139 

R - W 0.154 

Z 0.164 

B not B4 0.173 

N,O 0.177 

I 

0.178 

M 

0.197 

Y 0.906 

All 0.093 

Ordered by 

Augmentation 

NTEE 15 rate** 

Q 0.026 

P 

0.040 

I 

0.044 

E2 0.066 

C,D 0.067 

 J,K,L 0.072 

B4 

0.073 

A 

0.111 

M 

0.126 

E not E2 0.190 

R - W 0.206 

N,O 0.309 

B not B4 1.144 

X 

1.295 

Y 1.745 

Z 78.110 

All 0.210 

*Observed for Form 990 matched to QCEW. 

**Increase over imputed total, for all matches, included states. 

Bold emphasizes consistency of ranks for industries in the top of bottom third of NTEE classes. 

Italics emphasize that no industry class is assigned to Z. 

Source: F6_T6_Wss_tables16oct06.xls revised 
Tables and Figures for Distortions in nonprofit employment 22 May 2007 36 

Urban_institute_report2_22may2007rev21aug07.doc 

Fig. 1 Suspect establishment matches 

0 

0.1 

0.2 

0.3 

0.4 

0.5 

0.6 

0.7 

0.8 

99 00 01 02 03 

Year, Quarter 1 

includes false positive matches 

Suspect / tested

990 

990EZ 
Tables and Figures for Distortions in nonprofit employment 22 May 2007 37 

Urban_institute_report2_22may2007rev21aug07.doc 

Fig. 2 Major sectors in NTEE 15 

0 

2 

4 

6 

8 

10 

12 

14 

16 

31 42 44 51 52 53 54 55 56 61 62 71 72 81 92 

NAICS sector 

No. NTEE 15 classes 

Source: ddldb_nt2p_naics2dis28sep06.xls