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American Politics Research
DOI: 10.1177/1532673X073016542007; 35; 790American Politics Research
Jason A. MacDonald and William W. Franko, JRCongress Tie Policy Authority to Performance?
Bureaucratic Capacity and Bureaucratic Discretion: Does
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790
American Politics Research
Volume 35 Number 6
November 2007 790-807
2007 Sage Publications
10.1177/1532673X07301654
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Authors Note: The authors would like to thank Steve Balla and anonymous reviewers for
American Politics Research for comments that improved this manuscript. This research was
supported in part by the University Research Council of Kent State University.
Bureaucratic Capacity andBureaucratic Discretion
Does Congress Tie Policy Authority
to Performance?
Jason A. MacDonaldWilliam W. Franko Jr.
Kent State University
This article assesses whether the managerial capacity of agencies influences
the volume of policy authority that lawmakers delegate. Examining a sample
of agencies whose managerial capacities were assessed along the same criteria,
and allowing for the comparison of performance across agencies, we observe
that poorly performing agencies are more likely to lose policy authority. Our
findings suggest that lawmakers promote effective policymaking by giving
agencies the incentive to perform well and that models of discretion that do notaccount for performance underestimate the effect of another factorpolicy
conflict between the legislative and executive brancheson how much discretion
agencies receive.
Keywords: bureaucracy; Congress; public policy; bureaucratic discretion;
agency capacity; delegation; policy authority
Modern democracies confront complex problems, often employingpolicies that combine scientific knowledge across disciplines fromthe natural sciences and engineering to economics and policy analysis.Given this complexity, it is unlikely that modern lawmakerswith their
backgrounds in law, business, and public servicewill ever be the most
well-equipped individuals in government to design policy mechanisms to
pursue favorable outcomes for these problems. Yet electoral status confers
on lawmakers both the legitimacy to make policy decisions and the incen-
tive to balance competing societal values and interests successfully. In part,
lawmakers manage this responsibilitycapacity mismatch by delegating
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MacDonald, Franko / Bureaucratic Capacity and Bureaucratic Discretion 791
authority to make policy decisions to the bureaucracy, as has been documented
in diverse research traditions from the political economy of institutional
design (e.g., McCubbins, Noll, & Weingast, 1987; Moe, 1989) to Americanpolitical development (e.g., Carpenter, 2001; James, 2000).
A major area of research on delegation involves assessing why lawmak-
ers vary the level of discretion provided to agencies, where discretion is
defined as bureaucratic freedom to make policy decisions free from con-
straints, such as rulemaking-requirements, and other tools used by law-
makers to influence the substance of bureaucratic decisions (Epstein &
OHalloran, 1999, chapter 5). A central finding of this research is that as
policy disagreement between lawmakers and agencies increases lawmakersreduce the volume of discretion that agencies receive (Epstein & OHalloran,
1999; Huber & Shipan, 2002; Huber, Shipan, & Pfahler, 2001; Lewis,
2003; Potoski, 1999; Wood & Bohte, 2004). The theoretical basis for this
finding is that policy disagreement prevents lawmakers from trusting agen-
cies to render policy decisions consistent with lawmakers priorities. In the
language of the transaction cost approach taken by these studies, such dis-
agreement increases the costs of delegation to lawmakers to the point at
which it becomes less costly for them to make policy themselves by writingdetailed laws (see especially Epstein & OHalloran, 1999 and Huber &
Shipan, 2002).
These studies constitute significant theoretical and empirical progress in
understanding why agencies receive discretion to make policy. However,
this literature does not address the question of whether lawmakers vary dis-
cretion based on the capacity of agencies to make policies that are effective
in meeting policy goals. This issue is central to understanding whether law-
makers decisions in delegating policy authority contribute to the capacity
of democratic governments to solve problems. Some agencies perform the
tasks delegated to them effectively, solving problems that the architects of
legislation place in their hands, whereas other agencies flounder (Ingraham,
Joyce, & Donahue, 2003). To be sure, theories of delegation stress that law-
makers provide greater discretion to agencies as policy complexity increases
(Bawn, 1995; Epstein & OHalloran, 1999; Huber & Shipan, 2002). For
any number of equally complex policy areas, though, the capacity of
agencies to make effective policy can vary. Do agencies with greater/
lesser capacities receive higher/lower levels of discretion? If the answeris in the affirmative, then there is reason to believe that democratic govern-
ments can create effective solutions to important problems; however, if
lawmakers do not tie bureaucratic authority, at least in part, to bureaucratic
capacity, students of government should be more sanguine about the ability
of democracies to solve many problems.
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792 American Politics Research
Agency Capacity and Bureaucratic Discretion
Research on discretion, bureaucratic autonomy, and agency terminationprovides a basis for the hypothesis that agency capacity affects the latitude
agencies receive to make policy decisions, though no empirical research
employs a systematic indicator of capacity that varies across agencies to
assess the relationship. With respect to discretion, formal models predict
that lawmakers provide greater discretion to agencies as policy complexity
increaseseven when lawmakers expect that agencies will make policy
decisions that stray from lawmakers priorities (Bawn, 1995; Epstein &
OHalloran, 1999; Huber & Shipan, 2002). The basis for this result is thatlawmakers need for policy solutions trumps the loss of utility they experi-
ence from bureaucratic shirking. The implication of this research for the
relationship between capacity and discretion is clear. If lawmakers did not
care about effective policy solutions, there would be no reason to delegate
when agencies are likely to make decisions that stray from lawmakers
priorities. Of course, if agencies reputations for effective policymaking are
poor, then lawmakers have reason to doubt that agencies will produce effec-
tive solutions, undercutting the rationale for ceding discretion. This literature,therefore, suggests that agency capacity to perform the tasks delegated
effectively is positively related to discretion.
Research on bureaucratic autonomy suggests the same relationship,
though the causal mechanism differs. Examining the histories of three agen-
cies during the late 19th and early 20th centuries, Carpenter (2001) argues
that elected institutions cede policy authority after agencies evidence the
capacity to solve policy problems. Briefly, this capacity was created by
middle-level managers, whose career longevities and institutional positions
fostered policy learning and the ability to build support for policies they
favored among diverse sets of interest groups. After securing interest group
support for the policies they wanted to pursuein part because of sound
reputations for the capacity to solve problems effectivelythese managers
were able to place electoral pressure on members of Congress to give man-
agers authority to create policies that they favored. Bureaucratic autonomy,
then, was largely the result of sound policy performance engineered by man-
agerial leadership.
Research on agency termination also provides a basis for the hypothesisthat discretion is because of the capacity to make policies effectively.
Carpenter (2000) and Carpenter and Lewis (2004) argue that failure by an
agency, accompanied by media coverage of the negative consequences of
its bungling of the tasks to which it was assigned, imposes political fallout
on the legislators that delegated authority. Such costs might include the loss
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of electoral support from key constituencies, the provision of an election
issue to an opponent who could trace the lawmaker to the failure (Arnold,
1990) by credibly arguing that the lawmaker presided over the fiasco, andhaving to allocate scarce time on the legislative calendar in the future to
revisit the policy. These costs increase the likelihood that legislators will
exercise the ultimate act of political control (Carpenter & Lewis, 2004,
p. 202), eliminating the agencyan act that, to understate the point,
reduces discretion.
In summary, various research traditions on the authority that agencies
receive either suggest, or explicitly state, that discretion increases with
agency capacity. The basis for this relationship is that lawmakers observethe capacity of agencies to perform the policymaking tasks delegated to
them through a variety of means, including media reports (Carpenter &
Lewis, 2004) and information from interest groups and constituents dissat-
isfied with agencies (McCubbins & Schwartz, 1984) and react by manipu-
lating discretion in the future. Yet empirical support for this hypothesis is
wanting. Neither research on discretion nor agency termination incorpo-
rates variables into empirical models of these phenomena to assess the
influence of capacity on bureaucratic policy authority. Although Carpenter(2001) shows that the authority of the three agencies was due in large part
to their reputation for effective policymaking, this finding has not been
extended to contemporary politics.
Data and Methods
One reason why the relationship between capacity and discretion is
not well understood empirically is because of the difficulty of calibrating
capacity/performance in a valid manner and comparing it systematically
across agencies. We take advantage of the availability of such a measure
for a sample of 27 federal agencies. This sample was created by a joint
effort of the Federal Performance Project (FPP), teamed by scholars in the
Department of Public Administration at The George Washington University
(GW) and correspondents for Government Executive, a biweekly periodical
that provides specialized coverage of federal agencies. The project evaluated
how well all agencies managed the tasks to which they were assigned, gradingagencies in 1999, 2000, and 2001. To be clear, the FPP did not assess how
well agencies achieved the policy goals assigned to them by laws enacted
in the past. Rather, the project assessed how well agency managers managed
for results based on the criteria employed by the researchers.1 Managing
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for Results refers to administrating agencies, so that they can realize the out-
comes they are charged with achieving by law. The researchers employed
surveys of agency managers and employees, external reports on agencyeffectiveness, and interviews with experts on the agencies inside and outside
government to gauge performance.2 Researchers at George Washington
University and correspondents for Government Executive then evaluated
this information across agencies and assigned grades based on the performance
of agencies in relation to one another. Hence, according to the collective
judgment of the researchers, agencies receiving As performed better than
agencies receiving Bs on these criteria and so on. As such, the grades
constitute assessments of the managerial capacity of agencies. A presence/lack of capacity indicates the success/failure of managers to facilitate the
realization of policy results desired by political principals.
Although the sample of agencies is small, it represents the best data on
agency capacity that are comparable across multiple agencies.3 Hence, in
evaluating the connection between capacity and discretion, it makes sense
to use this data as a starting point. Twenty-seven agencies were selected by
FPP researchers because of their close interaction with the public. Therefore,
the agencies do not represent a random sample of all federal agencies andour findings cannot be so generalized. Appendix A itemizes these agencies.
The unit of analysis is the agency, that is, each agency has one observation
and includes information on the grade received in the year that it was
graded, as well as the other independent variables and the dependent
variable described below.
In evaluating the agencies management of their tasks, the FPP employed
a grade range from F to A. However, no agency received F to D
grades, limiting the range of the variables created to measure performance.
Below, we assess the relationship between how much Congress limits the
agencies discretion in the year after the grades were assigned and these
grades. We do so by measuring capacity in three ways. First, we employ the
plus/minus grades on a 1-13 scale with a grade of F coded as 1 and an
A coded as 13 (in practice, the scale ranged between 4 and 13). Second,
we employ a collapsed, traditional grade version of this variable ranging
from F (1) to A (5) to guard against the possibility that there is little dif-
ference between, for example, a B and B (in practice, this scale
ranged between 2 and 5). Finally, to account for the possibility that perfor-mance affects discretion in a nonlinear manner, we create dummy variables
for whether the agencies received grades of D, C, or B (1 if the agen-
cies received these grades; 0 otherwise), with A as the reference category
(because no agency received an F, no dummy variable for this grade was
794 American Politics Research
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created). The basis for this variable is that Congress may not view the dif-
ference between an A and B performance as it does a C and D per-
formance. For example, Congress may take no action to limit the discretionof an agency when it receives a B instead of an A; although the
agencys performance is not excellent, its mere good performance probably
will not cause a political fallout. However, once an agencys performance
becomes lackluster, for example, if the agencys performance is worthy of
a D, political principals may limit discretion. Calibrating performance in
this way allows us to observe such nonlinear effects. To be clear, we offer
no theory that specifies precisely how poorly an agency must perform to
lose discretion; rather, we note that it makes sense theoretically thatCongress will limit discretion after performance has become sufficiently
poor. How low capacity must be to reach this tipping point will remain
an empirical question.4
To measure discretion, we create a variable that is the count of the
number of limitation riders (LRs) attached to agencies appropriations in
the year after their managerial capacities were assessed by the FPP. LRs
forbid agencies from spending money for specific purposes. Importantly,
agencies possess the authority to use funds for these purposes from pastlaws. However, when an LR is included in an appropriations bill that
becomes law, agencies are prohibited from exercising that authority during
the next fiscal year, limiting their discretion. For example, the fiscal year
2001 Labor, Health and Human Services, and Education appropriations bill
mandated that none of the funds . . . may be used by the Occupational
Safety and Health Administration to promulgate, issue, implement, admin-
ister, or enforce any proposed, temporary, or final standard on ergonomic
protection. Congress includes hundreds of such LRs in appropriations bills
annually (MacDonald, 2007), giving it an annual opportunity to reign in
agency authority. As such, LRs constitute a tool that Congress employs to
constrain agency authority regularly, making these tools of political control
a valid indicator of the limitation of discretion.5
To measure how much Congress impinged on discretion, we counted the
number of LRs in Congresss annual appropriation acts that applied to each
of the 27 agencies in the year after their performances were evaluated by the
FPP.6 We examined LRs in the subsequent year because that was Congresss
first opportunity to limit discretion after performance was assessed duringthe period for which grades were assigned.7 Therefore, for agencies whose
performances were assessed in 1999/2000/2001, we counted LRs imposed
on these agencies in the appropriations bills passed in 2000/2001/2002.
If discretion is reduced because of low capacity, the relationship between this
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dependent variable and the independent variables measuring capacity using
the plus/minus and traditional grade scales should be negative and sig-
nificant, whereas its relationship with the dummy variables indicating thepresence of low capacity (e.g., the dummy variable for agencies who received
the grade of D) should be positive and significant.
Because research demonstrates that Congress limits discretion when
faced with a president of the opposite party (Epstein & OHalloran, 1999),
a finding that holds for state governments (Huber & Shipan, 2002; Huber
et al., 2001), we control for partisan conflict between the legislative and
executive branches. To do so, we employ a dummy variable assuming the
value of 1 when there is pure divided government, meaning that the pres-idency was controlled by one party and both chambers of Congress were
controlled by its rival. Therefore, observations for agencies graded in 1999,
for which we counted LRs applied in 2000 (under Democratic control of the
presidency and Republican control of the House and Senate), were coded 1.
Observations for agencies graded in 2000 and 2001, for which we counted
LRs applied in 2001 and 2002, respectively (under Republican control of the
presidency and House and Democratic control of the Senate), were coded as
0. Although the Democratic Senate had the opportunity to influence the sub-stance of appropriations bills during these years, its capacity to do so was
limited to a greater degree than was the case for the Republicans who con-
trolled both chambers in 2000. We expect this variable to be positively and
significantly related to the number of LRs imposed on agencies.
We also account for congressional and presidential policy disagreement
with agencies missions. Carpenter and Lewis (2004) show that agencies are
more likely to be eliminated when the same party controls the U.S. House and
the presidency but held minority status in the House and did not control the
presidency when the agency was created. Agencies in this situation are in a
precarious position because the current majority party is likely to object to the
policy priorities embodied in the agencies missions. This conditiona uni-
fied governments hostility toward agenciesmissionsmakes it more likely
for such agencies to lose discretion. Therefore, following Carpenter and
Lewis (2004), we create a variable assuming the value of 1 when this hos-
tility condition holds, 0 otherwise, and expect this variable to be positively
and significantly associated with the imposition of LRs.
Additionally, because research shows that the public salience of policiesincreases the likelihood that members of Congress make, rather than dele-
gate, policy (Epstein & OHalloran, 1999, chap. 8; Gormley, 1986, 1989) and
that Congress tries to influence bureaucratic policy decisions to a greater
extent in salient policy areas (Ringquist, Worsham, & Eisner, 2003), we control
796 American Politics Research
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for the salience of the policy area over which agencies have jurisdiction. This
variable is a count of the number of stories appearing in theNew York Times
in which the agency was mentioned during the year before the agency wasgraded.8 In general, the Timess coverage is followed by other media outlets
(Page, 1996). As such, this count approximates the degree to which the agen-
cies missions are made salient to the public. We expect that it will be posi-
tively and significantly related to the imposition of LRs.9
Finally, we control for the size of the appropriation bill in which the agen-
cies were funded, because bigger bills may contain a higher volume of LRs.
Appendix B provides summary statistics for all variables employed in the
analysis.10
Because the dependent variable is a count, we employ the Poissonmaximum likelihood estimator to assess the effects of the independent vari-
ables on the volume of LRs using the traditional grade-scale specification
and the dummy variable grade specification. In using the plus/minus grade
scale specification, likelihood ratio tests indicated that the variance of the
dependent variable exceeded its mean; therefore, we employed the negative
binomial maximum likelihood estimator for this model.
Findings
Models 1, 2, and 3 of Table 1 present estimates for the influence of the
independent variables on the volume of LRs, employing the traditional
grade scale variable (Model 1), the plus/minus grade scale variable
(Model 2), and dummy variables for agency grades (Model 3). The hypoth-
esis that Congress limits discretion as capacity declines is supported in all
three models. Measuring capacity using the traditional and plus/minus
grades assigned to the agencies yields a negative and significant association
between the number of LRs imposed on agencies and the coefficient for
agency grades. Additionally, in Model 3, the coefficients of the dummy vari-
ables indicating that the agency received Cs and Ds are positively and
significantly associated with the number of LRs with which agencies were
burdened. This specification supports the interpretation that once agency per-
formance drops below some adequate level at which Congress is willing to
leave agencies alone, Congress will reduce discretion. Empirically, Model 3
identifies this threshold level as the performance that merits a C based onthe FPPs criteria.
Table 2 provides information on the magnitude of the influence of per-
formance, as measured by the traditional grade scale, on LRs use, as
estimated by Model 1. Setting the values of the independent variables to
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798 American Politics Research
the modal or mean values, the model predicts that about 20 LRs will beimposed on agencies receiving a B.11 However, when agencies receive an
A, this prediction drops to approximately 17 LRs. Conversely, when
agencies managerial capacities are graded at the C and D levels, the
model predicts that agencies will be saddled with about 25 and 30 LRs,
Table 1
Poisson Regression Models of the Imposition of Limitation
Riders on the FPP Sample of Agencies in the Year AfterAgency Performance Was Graded
Independent Variables Model 1 Model 2 Model 3
Traditional grade scale .191***
(.056)
Plus/minus grade scale .060***
(.024)
B .127
(.145)C .277*
(.141)
D .784***
(.230)
Divided government .188 .107 .193
(.144) (.132) (.121)
Unified and hostile government .298* .321* .358**
(.141) (.179) (.152)
No. ofNew York Times stories .0010* .0010 .0010*
(.0005) (.0007) (.0005)No. of pages in bill .005* .006* .004*
(.002) (.003) (.002)
Constant 3.254 3.120 2.636
(.270) (.320) (.188)
Log likelihood 86.181 85.57 85.02
Chi-square 31.30*** 14.49*** 33.63***
N 27 27 27
Note: Coefficients are unstandardized. Standard errors are in parentheses. The estimates for
Models 1 and 3 are Poisson maximum likelihood estimates, because likelihood ratio tests didnot reject the null hypothesis that the mean and variance of LRs were equal. The estimates for
Model 2 are negative binomial maximum likelihood estimates, because the null hypothesis
that the mean and variance of LRs were equal could be rejected (p < .05) and the alpha statis-
tic was positive. Models 1 and 3 were also analyzed using the negative binomial estimator; the
only change in the significance of the coefficients was that, for both models, the no. ofNew
York Times stories variable was significant at the .1, rather than at the .05, level.p < .10. *p < .05. **p < .01. ***p < .001 (one-tailed tests).
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MacDonald, Franko / Bureaucratic Capacity and Bureaucratic Discretion 799
respectively. Hence, a decline in performance from the maximum to mini-
mum grades assigned by the FPP leads to almost a 2 standard deviation
increase in the number of LRs that Congress is expected to impose on agen-
cies. Simulationsnot presentedbased on the coefficients from Model 2
present a similar story. Simulations using the coefficients from Model 3
paint a more nuanced picture of the relationship between managerial per-
formance and discretion. Setting the independent variables to their mean
and modal values with the dummy variable for a B grade equal to 1,
Model 3 predicts that Congress will impose about 21 LRs on agencies, a
prediction that decreases to 18 if agencies receive As, and increases to 24
if agencies receive Cs. However, Model 3 predicts that Congress will
attach about 41 LRs to appropriations language funding agenciesprograms
during the next fiscal year if a D is assigned to their managerial perfor-mance. This finding suggests that there is a nonlinear relationship between
performance and discretion. It is also consistent with a bounded ratio-
nality explanation of political institutions (Jones & Baumgartner, 2005).
Specifically, the finding suggests that Congress underreacts to information
Table 2
The Predicted Number of Limitation Riders by Agency
Characteristics (Model 1 Estimates)
Predicted Values for Model 1:
Agency Characteristics Traditional Grade Scale
Performance
A 16.62
B (baseline) 20.30
C 24.65
D 29.98
Policy disagreement with agenciesAgency has support in at least one branch (baseline) 20.30
Unified and hostile government 27.93
No. ofNew York Times stories
Mean (baseline) 20.30
+ 1 Standard deviation 21.61
Note: Predicted values were calculated using Clarify (Tomz et al., 2003). The predicted values
are compared with a hypothetical, or baseline model, where the variables are set to the
modal or mean categories. The baseline was calculated using an agency operating under
divided government that received a B, was created during a period when the presidency andthe House were not controlled by a unified and hostile party, and was covered by theNew York
Times at the mean level for all agencies (58.63 stories). The bill in which the baseline agency
was funded spanned 65.85 pages.
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stressing that the performance of agencies is merely average (C grades),
limiting discretion slightly. However, when Congress learns that agency
performance is poor (D grades), it decreases discretion greatly.The hypothesis that divided government reduces discretion receives
some support for the models presented in Table 1. The coefficient for the
divided government variable is positively and significantly related to the
number of LRs imposed on agencies in Models 1 and 3, albeit at the .1
level. Turning to the hypothesis that a unified and hostile government leads
to less discretion, the coefficient for a hostile and unified government is
positive and significant in all three models, providing support for the
hypothesis. Table 2 provides information on the magnitude of this relation-ship, showing that Model 1 predicts about eight additional LRs (approxi-
mately 1 standard deviation of the dependent variable) for an agency
supervised by a U.S. House and a president controlled by the opposite party
that created the agency.
Additionally, the number of stories in theNew York Times mentioning
agencies is positively and significantly related to the number of LRs
imposed on agencies in all three models presented in Table 1. Table 2 shows
that Model 1 predicts two additional LRs for agencies mentioned by theTimes at a standard deviation above the mean of that variable. This finding
supports the hypothesis derived from the work of Gormley (1986, 1989) by
Ringquist et al. (2003) that Congress will try to influence the bureaucracys
policy decisions to a greater degree in policy areas that the public views as
salient. Ringquist et al. (2003) find that Congress both introduces and
passes a greater number of new bills to reverse agency decisions when
agencies preside over policy areas of salience to the public. The positive
and significant coefficients for this variable, though not the main focus of
the research presented in this article, reinforce this finding.
One objection to the analysis presented above involves the ability to
draw conclusions based on this small sample of agencies. What if the few
agencies receiving very low grades happened to be burdened with relatively
high numbers of LRs for idiosyncratic reasons, and these reasons led to the
significant relationships between performance and discretion observed in
the models? If this is the case, a sample with more agencies, or an analysis
including the entire population of federal agencies, would make it less
likely that we would make a Type I error and reject the null hypothesis thatperformance does not influence discretion when it is in fact true. To
respond to this very real concern, we reestimated Models 1 and 2 without
the one observation for which an agency received a D. In Model 1, the
coefficient for the Traditional Grade Scale variable remained positive and
800 American Politics Research
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significant (p < .05). This finding held for Model 2, though the significance
slipped to the .1 level.12 In other words, it is not simply one observation dri-
ving the finding that Congress imposes a greater number of LRs on agenciesas the managerial performance of agencies decreases.13
Conclusions
The Federal Emergency Management Agencys (FEMA) bungling of the
federal response to the devastation wrought by Hurricane Katrina and the
scurrying by members of Congress and President Bush to avoid the politi-cal fallout (e.g., VandeHei, 2005; Weisman & Goldstein, 2005) demonstrate
that poor performance on the part of agencies managers can create substantial
trouble for elected officials.14 Additionally, formal theories of delegation
stress that legislatures are willing to trade control over policy for the technical
expertise agencies offer (Bawn, 1995; Epstein & OHalloran, 1999). It should
be no surprise, then, that when agencies perform poorly elected officials
respond by stripping agency authority.
Yet to our knowledge, no prior research has examined the relationshipbetween agency capacity and discretion across a large sample of agencies.
To be sure, research on agency termination emphasizes agency failure as a
factor that increases the risk of termination (Carpenter, 2000; Carpenter &
Lewis, 2004); however, this research does not show a relationship between
these phenomena because of the lack of a measure of performance across
the sample of agencies it examines. Using a unique data set, we observe that
lower levels of performance are indeed associated with the loss of discre-
tion, controlling for the political environment, the salience of the agency,
and the size of appropriations legislation through which lawmakers scale
back discretion.
These findings suggest the need to account for performance for a more
complete understanding of why lawmakers grant discretion. Importantly,
this emphasis on performance implies that lawmakers give agencies the
incentive to make effective policies. If agencies want freedom to design the
programs under their direction, as research on bureaucratic policymaking
emphasizes (Carpenter, 2001), then convincing lawmakers of their effec-
tiveness is one way to obtain this freedom. Although prior studies of discre-tion improved the understanding of interbranch policymaking substantially,
they provided no evidence as to whether lawmakers rewarded effective
agencies by increasing their authority to make policy decisions (or punished
ineffective agencies by reducing such authority). Our analysis, however,
MacDonald, Franko / Bureaucratic Capacity and Bureaucratic Discretion 801
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implies that lawmakers promote effective policymaking, a hopeful finding
in an era in which many problems are complex and require bureaucratic
expertise. As such, it is consistent with recent research stressing thatCongress sometimes fosters effective policymaking by employing policy
research (Esterling, 2004).
An additional implication of this study is that models of discretion that do
not control for performance risk underestimating the influence of legislative
executive policy conflict on discretion. Consider one hypothetical case dur-
ing unified government when legislativeexecutive conflict is low, and, all
else equal, lawmakers are prone to grant discretion (Epstein & OHalloran,
1999; Huber & Shipan, 2002). Nevertheless, the agency that would imple-ment a law under consideration has a poor record of performance, leading
lawmakers to scale back the agencys discretion. In contrast, a second case
occurs during divided government when lawmakers, all else equal, lean
toward slashing discretion. In this case, however, the agency that would
receive authority has a record of good performance, enticing lawmakers to
take advantage of its technical capacity (Bawn, 1995) by providing more
discretion than they would have if the agency had a mediocre reputation.
Ignoring considerations about performance, theory would predict a rela-tively high level of discretion for the former observation and a relatively low
level of discretion for the latter. However, considerations about performance
attenuate this relationship. Any model using these observations to probe the
relationship between legislativeexecutive conflict and discretion that did
not control for performance, then, would underestimate the magnitude of the
relationship between interbranch policy conflict and discretion. Therefore,
the findings of this research suggest that prior studies of discretion that do
not control for performance observe a weaker connection than exists.
Of course, our findings are based on a relatively small number of agen-
cies whose inclusion in the sample was based on their close interaction with
the public. Do lawmakers limit discretion based on performance generally?
Or is this relationship conditional on the nature of agencies interaction
with the public? Future research on the link between capacity and discre-
tion should focus on developing measures of performance across more, and
different types of, agencies to answer these questions. This is especially the
case given there is good reason to believe that many of the factors influ-
encing the volume of discretion agencies receive are conditional. Forexample, Volden (2002) theorizes that interbranch policy disagreement
influences how much discretion agencies receive conditional on the existence
of an executive veto. Similarly, Huber and Shipan (2002) theorize that the
professional capacity of legislatures to craft effective policies conditions
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MacDonald, Franko / Bureaucratic Capacity and Bureaucratic Discretion 803
whether interbranch disagreement affects how much discretion agencies
receive, and they provide empirical support for this perspective.
Additionally, although our findings support the hypothesis that (a lackof) capacity (reduces) increases the policymaking authority that agencies
receive, there are several causal mechanisms that can account for this rela-
tionship. A goal of future research should be to explore the underlying
cause. Do lawmakers cede (reduce) authority based on assessments of how
likely the agencys actions are to lead to negative political fallout? Are law-
makers concerned intrinsically about the quality of policies created by
agencies when providing authority?
Appendix A
Federal Agencies Graded by the Federal Performance Project
Agency Year of Grade Grade
Coast Guard 2000 A
National Weather Service 2001 A
Social Security Administration 1999 A
Postal service 2001 A
Administration for Children and Families 2001 B
Army Corps of Engineers 2000 B
Federal Emergency Management Agency 1999 B
Food and Drug Administration 1999 B
Food and Nutrition Service 1999 B
Food Safety and Inspection Service 1999 B
NASA 2001 B
Veterans Health Administration 1999 B
Environmental Protection Agency 1999 BFederal Housing Administration 1999 B
Occupational Safety and Health Administration 1999 B
Patent and Trademark Office 1999 B
Veterans Benefits Administration 2000 B
Bureau of Consular Affairs 2001 C
Customs service 1999 C
Federal Aviation Administration 1999 C
Forest service 2001 C
Health Care Financing Administration 1999 C
Internal Revenue Service 1999 CNational Park Service 2000 C
Office of Student Financial Assistance 2000 C
Immigration and Naturalization Service 1999 C
Bureau of Indian Affairs 2001 D
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Appendix B
Descriptive Statistics
Variable Minimum Maximum Mean Standard Deviation
Limitation riders 6 36 21.63 7.62
Grade dummies
B 0 1 0.48 0.51
C 0 1 0.33 0.48
D 0 1 0.04 0.19
Traditional grade scale 2 5 3.74 0.76
Plus/minus grade scale 4 13 8.96 2.24
Divided government 0 1 0.56 0.51Unified and hostile government 0 1 0.11 0.32
No. ofNew York Times stories 0 304 58.63 75.65
No. of pages in bill 28 98 65.85 21.33
Notes
1. Briefly, the criteria included how well managers defined and measured success, man-
aged agency resources, took measures to ensure that managers were held accountable for deci-
sions and performance, communicated effectively and honestly with stakeholders and politicalprincipals, ensured that employees possessed information necessary to perform tasks to
achieve results, staffed individuals with appropriate skills for the tasks they performed, pos-
sessed the physical infrastructure necessary to achieve the results, and provided sound fiscal
management.
2. The FPP interviews included groups such as congressional oversight and appropria-
tions committees, the GAO, the OMB, think tanks, the press, client and advocacy groups, aca-
demic institutions, and government commissions (Laurent, 1999). More detailed information
about the FPP can be found on the projects Web site: http://www.gwu.edu/~fpp/. Also see
Ingraham et al. (2003).
3. Another source on agency performance is the Performance Assessment Rating Tool
(PART) through which the Office of Management and Budget (OMB) evaluates the performance
of federal programs. Using PART data would increase the size of the sample of agencies.
However, given that the OMB works directly for the president within the executive office of
the president (EOP), and given that presidents politicize the work of the EOP (Lewis, 2005;
Moe, 1985), we believe that PART ratings are likely to be endogenous to the political priori-
ties of the president, making them an invalid measurement of agency performance.
4. The grades assigned to agencies by the FPP can be found in Laurent (1999, 2000, 2001).
5. Measuring the volume of authority stripped from agencies in this way has an advan-
tage. It is possible that agencies that possess high levels of discretion develop greater capaci-
ties than agencies that possess low levels of discretion. If this were the case, employing a
dependent variable that measures the volume of discretion that agencies possess would pre-
clude unbiased estimates of the influence of capacity on discretion because higher levels of
discretion also cause high levels of capacity. However, our indicator measures the volume of
authority taken away from an agency in year t+ 1. Authority taken away in the future cannot
804 American Politics Research
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affect agency capacity in the present. Additionally, existing research on the link between
agency capacity and authority emphasizes that capacity leads to authority (Carpenter, 2001)
rather than the other way around, suggesting that, at any rate, managerial capacity is notendogenous to the volume of discretion agencies possess.
6. All the agencies graded by the FPP receive funding from these bills. We examined the
versions of bills that became public lawrather than House/Senate committee passed or
House/Senate passed versions.
7. To count LRs, we first identified the bill in which the agency was funded. Next, we
counted the number of instances stating no funds or none of the funds could be spent for
specific purposes that applied to the agency. LRs applied to the agency if they were located in
the specific section funding the agency, or a general provisions section, or title that applied to
the agency. Using counts of the number of LRs in the year during which, and the year before,
performance was graded did not change the findings reported below.8. This count was obtained through a Lexis/Nexis search of agency names, as they
appear in Appendix A, in the titles and lead paragraphs ofNew York Times stories in the year
before the agencys managerial performance was graded.
9. Ringquist et al. (2003) also examine the relationship between complexity and con-
gressional efforts to direct the bureaucracy, finding no direct relationship between complexity
and such efforts even though complexity does condition the relationship between salience and
such efforts. We opt not to control for complexity in our analysis because of the following:
The primary focus of our analysis does not involve the relationship between policy type
and discretion.
These authors found no direct relationship between complexity and such efforts.There is no readily available measure of complexity across agencies.
The degrees of freedom in our analysis is small to begin with.
10. Huber and Shipan (2002) identify factors, such as legislative capacity that vary across
legislatures influencing the level of discretion agencies receive. In the analysis below, we
focus on cases in which a single legislature delegates authority. Therefore, these factors are
constant and cannot explain variance in our dependent variable.
11. The note in Table 2 provides information on these baseline values. Predictions were
calculated using Clarify 2.1 (Tomz, Wittenberg, & King, 2003).
12. These results are available from the authors on request.
13. The results of this estimation are available from the authors on request.14. The title of VandeHeis article in The Washington Post illustrates the alacrity with
which members of Congress and the President sought to avoid the political costs of Federal
Emergency Management Agencys (FEMA) failure: Officials Deal with Political Fallout by
Pointing Fingers.
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Jason A. MacDonald is an assistant professor in the Department of Political Science at Kent
State University.
William W. Franko Jr. is a PhD candidate in the Department of Political Science at Kent
State University.
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