BUSINESSES’ PERCEPTIONS OF CONFIDENTIALITY AND

THEIR ATTITUDES TOWARDS DATA SHARING

AMONG FEDERAL STATISTICAL AGENCIES

Diane K. Willimack1

U.S. Census Bureau, Washington, D.C.

Abstract

While research on the privacy and confidentiality attitudes of individuals and households is extensive, a similar body of knowledge

about business respondents does not exist. This paper presents some of the first empirical data available on confidentiality and data

sharing attitudes in the business sector, based on results of the survey of Businesses’ Perceptions of Confidentiality. Our findings

present some provocative evidence about business respondents’ attitudes towards data sharing and their relationship with variables

such as data sensitivity, confidentiality concerns, trust in government, and respondent burden. Although our results are not

representative of the U.S. business population, it is our goal to generate discussion and stimulate further research to more closely

examine tendencies identified here.

Key Words: Confidentiality, Data Sharing, Respondent Burden, Business Surveys, Attitudes and Opinions

Introduction

Pledging and protecting the confidentiality of data collected on surveys is of paramount importance to

federal statistical agencies. The belief is that such assurances are important, if not essential, to maintaining

high response rates and data quality on government surveys. Attitudes on privacy, confidentiality, trust in

government, and data sharing2 have been well researched among household respondents. However, a

similarly strong body of literature on business respondents does not exist.

The survey of Businesses’ Perceptions of Confidentiality was designed to provide some of the first

empirical evidence available describing the attitudes of business respondents on a variety of topics, including

the sensitivity of business data, respondents’ understanding of statistical agencies’ confidentiality pledges

and trust in the government’s ability to uphold them, their knowledge of legal penalties for breaching data

confidentiality, and their concerns about and support for data sharing for statistical purposes (Greenia et al.,

2001a). This paper will focus on survey results related to respondents’ attitudes on data sharing. Other

papers present detailed summaries and analyses of other items collected (Greenia, et al., 2001a, 2001b).

Review of the Literature on Confidentiality and Data Sharing

Attitudes of Household Members

Research on the privacy and confidentiality attitudes of individuals and households is extensive. A draft

annotated bibliography by Mayer (2000) lists 150 citations, most of which describe the attitudes of

household members, rather than businesses. Studies over the past twenty years suggest that not only does

the public doubt the U.S. Census Bureau’s confidentiality pledge, there is also a tendency to believe that the

Census Bureau shares data with other government agencies (National Research Council, 1979; DeMaio et

al., 1986; Gates, 1996; Kerwin and Edwards, 1996; and the Privacy Research Team, 1997). Household

1

This paper reports the results of research and analysis undertaken by Census Bureau staff and collaborators. It has undergone a

Census Bureau review more limited in scope than that given to official Census Bureau publications. This report is released to

inform interested parties of ongoing research and to encourage discussion of work in progress. The author acknowledges Nick

Greenia, Statistics of Income Division, Internal Revenue Service, and Dr. Julia Lane, of the Urban Institute, the American

University and the U.S. Census Bureau , for providing access to the data analyzed in this paper. She is grateful to Dr. Frederick

Knickerbocker, along with Dr. Lane, for facilitating this work and to Laura Zayatz, Tom Mesenbourg, Kristin Stettler, Elizabeth

Nichols and Nash Monsour for providing helpful review comments.

2 Here, data sharing means the flow of data from one agency to another, not necessarily the mutual exchange.
survey findings that may have pertinence for business respondents include the following:

• Focus group participants failed to distinguish among different government agencies, believing instead

that requested information is already available “from a government computer” (Response Analysis

Corporation, 1978).

• Focus group participants were willing to tolerate apparent duplication in requests for data across multiple

government agencies (i.e., respondent burden) in order to preserve privacy (Aguirre International, 1995).

• Respondents who believed that the Census Bureau already shared data were more likely to support

future data sharing (Singer and Presser, 1996).

• Multivariate regression results showed “The more trust and confidence people have in government, ...,

the more willing they are to have agencies share data.” (Singer et al., 1997).

• Respondents’ perceptions of the sensitivity of the requested information may affect the relationship

between confidentiality assurances and survey response (Singer et al. 1995).

• Findings are mixed on a link between survey participation and trust in confidentiality assurances

(National Research Council, 1979; Moore and McDonald, 1987; Kulka et al., 1991; Singer, 1994).

Attitudes of Business Respondents

In contrast, little published or unpublished research is available describing the attitudes of business

respondents regarding privacy, confidentiality, and data sharing. A 1992 Office of Management and Budget

(OMB) working group identified factors likely to affect businesses’ trust in government’s promises to

protect business data, including the sensitivity of various data items, the perceived benefits of the survey,

the costs to the business of survey response and procedures used to protect the data.

In research results that echo the household side, only 50% of business respondents believed that the Census

Bureau kept individual companies’ data confidential and that data sharing already went on. However, these

beliefs were unrelated to economic census response behavior (Zeisset et al., 1990).

Like household respondents, business respondents in 30 very large multiunit companies failed to distinguish

among the various statistical agencies, instead viewing them as “one government.” Unlike household

respondents, business reporters stressed respondent burden over confidentiality concerns, because a) they

basically trusted Census Bureau confidentiality pledges and b) requested data was often publicly available

in some form. These large companies generally supported data sharing among statistical agencies, but only

if reporting burden was actually reduced (Nichols and Willimack, 2001).

In results from the survey of Businesses’ Perceptions of Confidentiality, Greenia et al. (2001a) found that

the level and duration of sensitivity varied across different types of data items. Like household respondents,

business respondents seemed evenly split in their beliefs that federal statistical agencies keep their data

confidential. Greenia et al. (2001b) also found that a) the greater business respondents’ beliefs in government

competence, the less concerned they were about providing data to either statistical or regulatory agencies

and b) likewise, as trust increased, concerns about providing data decreased.

Methodology

The survey of Businesses’ Perceptions of Confidentialtiy was sponsored by the U.S. Census Bureau and

conducted by the Urban Institute, using Dillman’s Total Design Method (1978) for mail surveys. The first

mailing in late November, 2000, used first class postage and consisted of a paper self-administered

questionnaire booklet and a cover letter on Urban Institute letterhead, bearing the signature of the principal

investigator, along with a postage-paid return envelope. A follow-up thank-you/reminder postcard was sent

ten days later. A second mailing to nonrespondents, which included a replacement questionnaire, cover

letter and return envelope, followed after the Christmas holidays, 2000.

A detailed description of the survey, along with the entire questionnaire, can be found in Greenia et al.

(2001a). Topics covered by the survey included:
 

 

• sensitivity of different types and levels of business data and the duration of their sensitivity;

• concern about providing business data to various government and non-government entities;

• attitudes about government competence in collecting and protecting data;

• beliefs regarding the confidentiality pledges of federal statistical agencies;

• knowledge of legal penalties associated with unauthorized disclosure of business data by federal

statistical agencies or their employees;

• opinions about the enforcement of confidentiality laws relative to potential response behavior;

• support for data sharing among federal statistical agencies, and, if so, identification of agencies allowed

to share data, from among the Census Bureau, the Bureau of Labor Statistics (BLS), the Bureau of

Economic Analysis (BEA), the Statistics of Income Division of IRS (SOI/IRS), or others.

The survey questionnaire was mailed to a sample of 5,000 businesses obtained from Dunn and Bradstreet’s

commercial database, representing 11.3 million U.S. businesses. The sample was allocated equally across

four strata defined based on the number of employees: 1-49 employees, 50-249, 250-499 and 500 and above.

Since the survey was never expected or intended to be representative of the U.S. business population, we

do not utilize sample weights in our data analysis. Thus results of our analyses describe only survey

respondents, merely suggesting possible tendencies among members of the business population that require

further investigation.

Results and Interpretation

Response Rates and Respondent Characteristics

There were 509 useable responses to the survey of Businesses’ Perceptions of Confidentiality, resulting in

an overall response rate of 10.6%.3 We suspect the low response rate is the consequence of multiple

factors. First, survey participation was voluntary. The survey’s sponsorship by the Census Bureau was very

difficult to stress in the questionnaire, since the survey was not actually conducted by the Census Bureau,

but, rather, administered by the Urban Institute. In addition, the survey was conducted during the holiday

season, which is known to affect response rates in household surveys. Also, the target respondent was an

authority figure in the business, from whom studies have shown greater difficulty obtaining survey response

(Ramirez, 1996). Additionally, the low response rate may be indicative of a lack of salience of the survey

topic, particularly relative to traditional requests for business data.

Because of the low response rate there is great potential for nonresponse error in our results. Thus, it is

worthwhile to closely examine the characteristics of those who responded, and, to the extent possible,

compare characteristics of respondents versus nonrespondents.

Table 4.1 shows that response rates declined as business size increased. Businesses in the services sector

responded at a higher rate than in other industries, while those in manufacturing or retail showed the lowest

response rates. Thus, to the extent that attitudes about data sensitivity, confidentiality and data sharing are

related to size and industry characteristics, there is potential for bias in our results favoring small businesses

and businesses in the service sector. While Greenia et al. (2001a) found some variation in responses to

individual questions related to firm size, they found little or no significant relationship with either size or

industry for most of the survey responses. Moreover, since previous business perceptions data was based

solely on very large companies (Nichols & Willimack, 2001), the representation of small businesses in this

research was heartening.

Respondents were split evenly between single units and multiunits. One-third of respondents identified

themselves as the company’s chief executive officer, and another quarter were the owners of the business.

Respondents identifying themselves as chief executive or chief financial officers were more likely to be

3

Response rate = #Useable questionnaires received / (Sample size - Undeliverables); Undeliverables = 213.
associated with large businesses and with multiunits. Not surprisingly, nearly two-thirds of respondents who

identified themselves as business owners were associated with small businesses having fewer than 50

employees, and nearly all of these small businesses were single units. Since small businesses responded at

a higher rate, responses may disproportionately reflect attitudes related to personal characteristics of

business owners.

Table 4.1 Characteristics of respondents to the survey of Businesses’ Perceptions of Confidentiality

n

Percent of

Respondents N a Response rate a, b

Size (# employees)c

1 - 49

50 - 249

250 - 499

500 or more

c

Industry

Agriculture, Mining & Contract Construction

Manufacturing

Transportation, Communication & Public Utilities

Wholesale Trade

Retail Trade

Finance, Insurance & Real Estate

Services

d

Single Unit / Mutiunit

Single Unit

Multiunit

d Respondent Identity

Chief Financial Officer

Controller / Accounting Manager

 Chief Executive Officer

Owner

Other

Unknown

157

140

111

101

41

78

29

32

57

45

227

268

241

39

24

173

145

67

81

 30.84%

27.50

21.81

19.84

 8.06%

15.32

5.70

6.29

11.20

8.84

44.60

 52.65%

47.35

 7.66%

4.72

33.99

28.49

13.06

15.91

1152

1201

1208

1226

426

961

262

305

677

431

1725

–

–

–

–

–

–

–

–

 13.63%

11.66

 9.19

 8.26

 9.60%

 8.10

11.20

10.50

 8.40

10.40

13.20

–

–

–

–

–

–

–

–

Total 509 – 4787 10.64%

a

b

c

d

 Source: Greenia et al. (2001a). 

Response rate = #Useable questionnaires received / (Sample size - 

Based on frame data.

Based on survey responses.

Undeliverables).

Distributional Results

Three survey questions specifically requested business respondents’ attitudes about data sharing:

• Item 7c: Respondents’ degree of agreement/disagreement with the statement, “I believe that federal

statistical agencies do not share data provided by businesses with other government agencies.”

• Item 7e: Respondents’ degree of agreement/disagreement with the statement, “I believe that any federal

agency, such as the Internal Revenue Service, Small Business Administration and Federal Trade

Commission, can access data my company has provided to other federal agencies whenever it wants.”

• Item 10: Respondents’ selection from among the Census Bureau, BLS, BEA, SOI/IRS or other

federal agencies (respondent specified) in response to the question, “If data sharing were legal,

among which federal statistical agencies would your company be willing to allow its data to be

shared, for statistical purposes only?”
Greenia et al. (2001a) report that nearly 80% of respondents believed that federal statistical agencies do share

business data with other government agencies, according to their responses to Item 7c, and opinions did

not vary with the size of the business. Also, 70% of survey respondents reported believing that other

government agencies (such as IRS, SBA, and FTC) can access business data whenever they want,

according to their responses to Item 7e. Thus it is clear that most of this survey’s business respondents

believe data sharing already occurs and expressed some degree of distrust or cynicism about government

data sharing practices. These results are not unlike those for householders reported earlier.

Table 4.2, which summarizes Item 10,

shows that almost 60% of survey

respondents expressed willingness to

allow one or more of the listed

statistical agencies to share data. Nearly

50% of the respondents were willing to

allow data sharing at least among the

Census Bureau, BLS and BEA, and

almost half of these were willing to

include SOI/IRS as well.

 

 

Table 4.2 Summary of Item 10: If data sharing were legal, among which

federal statistical agencies would your company be willing to allow its data

to be shared, for statistical purposes only? 

Percent of

Agencies Respondents

Census Bureau & BLS & BEA & SOI/IRS 22.6%

Census Bureau & BLS & BEA 25.5

All other combinations of listed agencies a

11.4

Total supporting some data sharing 59.5%

n=509

a

This includes 18 cases marking only one statistical agency. Table 4.3 shows support for data

sharing by each listed agency with at least one of the

other agencies. At 58%, the strongest support was for

the Census Bureau, while only one in four respondents

were willing to allow SOI/IRS to share data. This

might be due to a lack of understanding that SOI is the

statistical, not the enforcement, arm of IRS. It might

also be possible that the term “data sharing” is

misleading: respondents might be comfortable with

IRS sending data to the Census Bureau, but not the

reverse. Clarifying this potential ambiguity may be important to agencies like the Census Bureau, which rely

on IRS administrative records for frame-building and coverage evaluation.

 

Table 4.3 Support for data sharing by each agency with

at least one of the other three

Agency Percent of Respondents

Census Bureau 58.0%

BLS 54.4

BEA 52.4

SOI/IRS 24.0

n=509

Although not statistically significant, bivariate analyses examining relationships between Item 10 responses

and other variables of interest suggested some interesting tendencies. First, our survey respondents viewed

data sharing among the Census Bureau, BLS, and BEA with some equanimity, but were less comfortable

with data sharing by IRS. This pattern was essentially the same across business size classes and industries.

However, larger businesses with 250 employees or more exhibited a slightly higher overall rate of support

for data sharing. This may suggest the business size threshold at which respondent burden outweighs

confidentiality concerns.

Data sharing attitudes appeared to reflect the role or duties of various positions within a business. Most

supportive of data sharing were CEOs who may evaluate data sharing from a cost-benefit perspective – the

benefits of respondent burden reduction attained through data sharing outweigh the risks of exposing

sensitive data due to breaches of confidentiality. Least supportive were CFOs, controllers or accounting

managers who may possess attitudes of protecting the data they are responsible for keeping.

Respondents with softer opinions (responses of somewhat agree/disagree to Items 7c and 7e) tended to

favor data sharing at a slightly higher rate than those who held their beliefs strongly. Regardless of the

strength of their opinions about the government’s current data sharing practices, all respondents were

considerably less inclined to allow SOI/IRS to share data – although this may reflect a lack of clarity about

the direction in which the data flow.

Those who strongly believed that IRS/SBA/FTC can indeed get business data whenever they want were less
 

 

 

inclined to allow the specific individual agencies to share data, showing reluctance to grant access to other

agencies. Oddly, those who tended to believe that IRS/SBA/FTC cannot get business data whenever they

want were more willing to grant SOI/IRS data sharing privileges. Perhaps these respondents recognized that

respondent burden could potentially be reduced if federal statistical agencies were permitted to obtain data

from SOI/IRS.

Multivariate regression analyses

Based on our interpretation of the literature and experience with business reporting patterns, we propose the

following conceptual model relating business respondents’ attitudes about data sharing with characteristics

of the business and their attitudes about government reporting:

Support for Data Sharing = f (respondent burden, data sensitivity, trust in (4.1)

government, belief in government competence).

We expect that support for data sharing would increase with respondent burden, trust in government and

belief in government competence. We also expect greater sensitivity of business data would result in less

support for data sharing. We further hypothesize that respondent burden increases with the size of the

company and that burden is greater for multiunit companies as opposed to those with only one unit (aka

single units). We also expect that respondent burden varies with the major industry within which the firm

operates. We hypothesize that trust is related to business respondents’ concerns about providing data to

federal statistical or regulatory agencies, their experience with government reporting and their positions within

the company.

In order to support regression analysis of attitudes about data sharing relative to these hypothesized

constructs, variables were defined using responses from the survey of Businesses’ Perceptions of

Confidentiality or data from the sample frame. Thus we identified the following empirical model:

yi = f (Log(employment), Multiunit, Sensitivity Score, Time Sensitivity, Trust in Federal

Statistical System, CEO/CFO, Owner, Concern/Federal Regulatory Agencies,

Concern/Federal Statistical Agencies, Belief/Govt. Competence),

(4.2)

where the yi are defined in Table 4.4a. The independent variables4

are defined in Table 4.4b, along with an

explanation of their interpretation and the expected direction of effects on data sharing attitudes.

Table 4.4a Dependent variables used in multivariate regression analysis.

Variable Name Definition

Support y1 = Q10a 1 if the respondent is willing to allow data sharing by the Census Bureau; 0 otherwise.

for data y2 = Q10b 1 if the respondent is willing to allow data sharing by BLS; 0 otherwise.

sharing y3 = Q10c 1 if the respondent is willing to allow data sharing by BEA; 0 otherwise.

y4 = Q10d 1 if the respondent is willing to allow data sharing by SOI/IRS; 0 otherwise.

y5 = Q10mult 1 if the respondent is willing to allow data sharing by at least one agency listed in Q10; 0 otherwise.

y6 = Q10 Number of agencies in Q10 among whom the respondent is willing to allow data sharing.

 

 

Table 4.4b Independent variables used in multivariate regression analyses.

Expected Variable Name Definition Interpretation / Hypothesis Sign

Burden

Size a

The larger the employment size of the firm, the

Log(employment) log(number of employees) + greater the respondent burden, the more likely to

favor data sharing.

Complexity 1 if multiunit in Q2; Multiunit firms have greater complexity than single Multiunit +

else 0 units and will more likely favor data sharing.

4We dropped industry dummy variables from our final model due to their lack of significance in both preliminary regression results

and bivariate analyses, and because they cost degrees of freedom relative to our small sample size.
Data sensitivity

Data items Sensitivity Score

Total number from list of 11

data items marked

Very/Extremely Sensitive

! 

The greater the number of very/extremely sensitive

items, the less likely the respondent (R) is to support

data sharing.

Duration Time Sensitivity Average duration, in years, data

are considered sensitive

! 

The greater the average, the longer the overall time

sensitivity of the various data items, the less likely R

is to support data sharing.

Trust in government

Trust in System

The average response from

among valid agree/disagree

responses to 5 items on

confidentiality

+

The greater the average score, the greater Rs’ trust

that stat agencies protect business data, the more

likely they are to favor data sharing.

Confidentiality

concerns

Concern / Fed.

Reg. Agencies

Concern abt providing data to

fed. reg. agencies; Range: 1

(Not at all) to 4 (Extremely)

! 

The lower Rs’ concern about providing data to fed.

regulatory agencies, the more likely they are to

favor data sharing.

Concern / Fed.

Stat. Agencies

Concern abt providing data to

fed. stat. agencies; Range: 1

(Not at all) to 4 (Extremely)

! 

The lower Rs’ concern about providing data to fed.

statistical agencies, the more likely they are to favor

data sharing.

Govt. reporting

experience Multiunit 1 if multiunit reported in Q2; else0

+

Multiunits are believed to have more experience

filing government forms. The greater the

experience, the greater the trust, the more likely to

favor data sharing.

Respondent

identity

CEO/CFO

Owner

Other

1 if CEO or CFO in Q12; else 0

1 if owner in Q12; else 0

Omitted category

?

This variable represents “preconceived” or personal

notions of trusting the government. 

Government competence

Respondent Belief / Govt. opinions about Competence govt. competence

Rs’ agreement with: “Fed. govt.

is better than private sector at

protecting business data from

<unauthorized> release.” Range:

1 (strongly agree) to 4 (strongly

disagree)

! 

The greater Rs’ belief in govt. competence, the

more likely they are to favor data sharing. (Note

the direction of the scale –lower numbers indicate

stronger agreement with the statement and greater

belief in govt. competence.)

a Data from the sample frame.

A separate linear probability model was estimated for each of the yi and results appear in Table 4.5. The

model explains a statistically significant 8-12 percent of the variation in business respondents’ attitudes about

allowing specific federal statistical agencies to share data. Respondent burden variables, such as the size

or complexity of the firm, or the identity of the respondent are not significantly related to attitudes about data

sharing. On the other hand, several attitudinal variables play a significant role.

Only for SOI/IRS does the number of business data items considered somewhat/extremely sensitive

(Sensitivity Score) have the hypothesized association with data sharing attitudes. Time Sensitivity is

nonsignificant also. However, the sensitivity variables become statistically significant in the absence of

variables describing respondents’ concerns about providing data to federal regulatory or statistical agencies

and their belief in government competence to protect data, suggesting respondents’ concerns – or lack

thereof – mediate the effect of data sensitivity on their willingness to allow data sharing. That is, if

respondents’ concerns about providing data to government agencies can be relieved, then the sensitivity of

the data is no longer an issue affecting respondents’ attitudes favoring data sharing.

The variable describing business respondents’ trust in federal statistical agencies (Trust in System) is

significant in all of the estimated equations, with the exception of the one for the Census Bureau. The

positive coefficient means that the greater the expressed trust in federal statistical agencies, the more likely

is the business respondent to be willing to allow those agencies to share data. Similar to the household side,

business respondents’ trust in federal statistical agencies’ confidentiality pledges appears to be a key variable

related to attitudes about data sharing. It seems that maintaining and improving this level of trust is critical

for respondents’ support of data sharing among federal agencies.
The variable describing business respondents’ concerns about providing data to federal statistical agencies

is statistically significant in all equations except the one for SOI/IRS. In contrast, the variable describing

business respondents’ concern about providing data to federal regulatory agencies fails to achieve

significance. This suggests that business respondents may indeed be able to distinguish between federal

regulatory agencies and their statistical counterparts, contrary to the aforementioned Nichols and Willimack

(2001) finding that businesses tend to consolidate federal agencies into “one government.” Yet businesses

they interviewed did distinguish the IRS from all other agencies, and wanted IRS excluded in any serious

implementation of data sharing. This may explain the lack of significance of both concern variables in the

SOI/IRS data sharing equation. It may simply be difficult for business respondents to consider even a

statistical division of IRS to be a statistical agency – particularly since there is a much greater public

awareness of the Census Bureau and BLS as statistical agencies as a result of census and survey data

collection efforts.

Table 4.5 Regression results for model (4.2).

Dependent variables

Number of Support for data sharing by -- agencies

Census One or more allowed to

Independent Variables Bureau BLS BEA SOI/IRS agencies share data

Log(employment) -0.002 0.005 -0.002 0.001 -0.004 0.002

Multiunit 0.027 0.005 0.045 -0.019 0.024 0.058

Sensitive Score 0.006 -0.000 -0.017 -0.022* 0.002 -0.034

Time Sensitivity -0.003 -0.003 -0.003 -0.001 -0.002 -0.009

Trust in system 0.057 0.113** 0.096** 0.150*** 0.094** 0.417***

Respondent is CEO or CFO -0.018 -0.025 -0.005 -0.001 -0.027 -0.048

Respondent is bus. owner -0.008 -0.025 -0.023 -0.018 -0.023 -0.073

Concern / fed. reg. agencies 0.002 0.002 -0.001 -0.001 0.002 0.002

Concern / fed. stat. agencies -0.122*** -0.126*** -0.092*** -0.020 -0.107*** -0.360***

Belief in govt. competence -0.018 0.015 -0.005 -0.043 -0.013 -0.051

Constant 0.852*** 0.597*** 0.670*** 0.196*** 0.776*** 2.315***

n 323 323 323 323 323 323

adjusted R2

0.08*** 0.10*** 0.08*** 0.09*** 0.08*** 0.12***

* significant at 10%; ** significant at 5%; *** significant at 1%

Furthermore, these results also suggest that being able to affect respondents’ level of concern about

providing data to statistical agencies is likely to affect their attitudes favoring data sharing. However, this

is not so for regulatory agencies. Greenia et al. (2001b) also suggest that lower levels of concern about

providing data to either regulatory or statistical agencies are associated with greater trust in confidentiality

pledges and stronger beliefs in government’s competence to collect, use and protect data. This implies that

by increasing business respondents’ trust in government and belief in its competence, their concern about

providing data to government statistical agencies will be reduced, which may subsequently improve their

willingness to allow agencies to share data. Thus, it is possible that greater public awareness that SOI/IRS

is a statistical agency, as well as understanding that data only flow from IRS to other authorized agencies,

such as the Census Bureau and BEA (rather than vice versa), might strengthen confidence in confidentiality

pledges, and hence the perceptions of data sharing.

Conclusions

Although admittedly not representative of the U.S. business population, our results provide some initial
empirical evidence about business respondents’ attitudes towards data sharing among federal statistical

agencies that is indeed provocative. Key findings include:

• The greater business respondents’ trust in federal statistical agencies to protect their data, the more likely

they are to favor data sharing.

• The favorability of attitudes towards data sharing may be improved by relieving business respondents’

concerns about providing data to federal statistical agencies.

• It appears the effect of data sensitivity on respondents’ willingness to allow data sharing can be mediated

by relieving their concerns about providing data and improving their beliefs in government competence.

Other interesting tendencies exhibited by these data are:

• Business respondents believe that federal statistical agencies already share data.

• They generally express reservations about including SOI/IRS in data sharing arrangements.

• Respondent burden appeared not to be associated with attitudes favoring data sharing, contrary to our

expectations. However, bivariate results suggest the possibility of identifying a threshold, related to firm

size, at which burden potentially outweighs confidentiality concerns.

• Likewise, although not statistically significant in the multivariate analyses, bivariate results suggest a

potential logical relationship between respondents’ roles in the business and their attitudes towards data

sharing.

It is notable that these results resemble those from household surveys on data sharing attitudes – that trust

in government is a key predictor of favorable attitudes towards data sharing, and that those who believe the

government already shares data tend to support data sharing. However, this is also somewhat disconcerting.

One would like to believe that business respondents’ attitudes would be driven more by the context of

business dealings with the government, which differ from households in their frequency and propriety, rather

than by personal feelings. That is, business respondents appear to be people first and business people

second.

This brings us to some concluding thoughts about the limitations of this study and suggestions for future

research. First, the measures we constructed for these analyses may be considered somewhat rudimentary,

subject to the limitations of the survey questions themselves. As the first survey of its kind among business

respondents, no doubt the questions will benefit from refinements based on limitations in interpretation noted

in this paper and in the Greenia et al. (2001a, 2001b) papers. Moreover, we may not be measuring the right

things. For example, we defined respondent burden in terms of business size and complexity, which turned

out to be nonsignificant in our multivariate analyses. Perhaps a more appropriate measure would be

respondents’ perceptions of burden, a more subjective phenomenon than the variables we used.

Lastly, of course, we cannot stress enough the great concern raised for potential nonresponse bias in the

results reported here, if the opinions of nonrespondents do indeed differ significantly from those of the

respondents. We reiterate that our goal in sharing these results, however suspect they may or may not be,

is to generate discussion and stimulate further research with sufficient sample sizes and authoritative survey

sponsors in order to achieve adequate response rates and representativeness of the target business

population. We welcome statistically defensible research to confirm or refute our initial efforts, and

encourage research linking attitudes to survey response behavior as well. Not only do the statistical agencies

have much to be gained from this research, but so do businesses, if demonstrated support for data sharing

leads to actions that reduce respondent burden.

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