Varieties of Corruption: The Organization of Rent-Sharing in India
Jennifer Bussell
The University of California, Berkeley
Abstract: Studies of corruption shed little light on ways in which corrupt rents are distributed across
actors—insights that would prove enlightening for efforts to reduce corruption. I posit that the type
of state resource over which actors are attempting to gain control—e.g. permits and licenses versus
access to benefits from welfare schemes—shapes the character of control over resource allocation
and so is a key predictor of patterns in rent-sharing. I present a framework for categorizing corrupt
acts that emphasizes variation in the type of government resource and highlights disparities in the
character of illicit payments across multiple realms of government activity. I then draw on new and
original data from surveys of Indian politicians and bureaucrats and introduce a new measure of rent
dispersion, the effective distribution of rents (EDR), to show that there is considerable sharing of
rents across government and non-government actors and that the perceived distribution of rents is
strongly associated with the type of government resource. My evidence also shows that rent-sharing
occurs to similar degrees for different types of corruption, but that which actors benefit from
corruption depends sharply on the type of government resource.
This draft: April 10, 2014
Acknowledgments: This research was funded in part by a grant from the Policy Research Institute at
the University of Texas at Austin. I would like to thank Bhartendu Trivedi and the MORSEL team
for their assistance in data collection. Thanks also to James Alt, Thad Dunning, Nikhar Gaikwad,
Francesca Jensenius, Amy Lerman, Peter Lorentzen, Aila Matanock, Michaela Mattes, Daniel
Posner, Alison Post, Ken Scheve, Neelanjan Sircar, Devesh Tiwari, and to workshop participants at
the University of California, Berkeley’s Goldman School of Public Policy, the University of
California, Los Angeles, the University of Pennsylvania’s Center for the Advanced Study of India,
the Yale Program on Democracy, McGill University, the Edmond J. Safra Center for Ethics at
Harvard University, and the “Westminster Model of Democracy in Crisis?” conference at Harvard
University for comments on earlier drafts. An earlier version of this paper was presented at the 2013
Annual Meeting of the American Political Science Association.
1
Corruption is an important subject of concern for political economists and social scientists more
generally, with a large body of work covering the evolution of corruption, measurement of its
presence, evaluation of its causes, and exploration of opportunities for reform (inter alia, Bussell
2012; Ferraz and Finan 2010; Ko and Samajdar 2010; Fan et al. 2009; Fisman and Miguel 2008;
Reinikka and Svensson 2006; Rose-Ackerman 1975, 2002; Spector et al. 2005; Wade 1985; Scott
1972, 1969). Yet, this research agenda has focused only minimally on the organization of corrupt
activities. Who is engaging in corrupt acts? Is corruption a solitary activity, or are corrupt rents
shared across multiple actors? Are these dynamics the same for different forms of corrupt activity?
For example, is the same individual, or set of individuals, benefiting from bribes paid to speed up the
delivery of drivers’ licenses as from kickbacks to politicians to influence the licensing of access to
mineral-rich land rights? Does the nature of rent-sharing differ across these two forms of corruption?
These questions are significant both for their potential policy implications and theoretical
import. From a policy perspective, reducing or eliminating corruption demands an understanding of
who benefits from corrupt acts. If multiple actors profit from a single corrupt transaction, then the
incentives of this full set of actors, not just the individual who directly accepts the bribe, must be
considered to understand why such behaviors persist. Without this information, anti-corruption
reforms are likely to target only one piece in a complex corruption puzzle.
Theoretically, analysts have only occasionally addressed the organization of corruption and
the sharing of rents between actors. Variation in the degree to which individuals within a political
hierarchy monitor corruption at other (lower) levels and extract a portion of rents has been
considered as an important characteristic for explaining the role of corruption in certain contexts
(Darden 2008) and for differentiating between forms of corruption regimes (Shleifer and Vishny
1993). Yet, these authors either do not consider the potential causes of variation in rent-sharing or
2
they do not test their hypotheses empirically. As a result, we have few insights into either how rent-
sharing differs across contexts or what causes this variation.
In this paper, I develop an argument for explaining variation in the sharing of rents. I posit
that the type of state resource over which actors are attempting to gain control—e.g. permits and
licenses versus access to benefits from welfare schemes—shapes the character of control over
resource allocation and so is a key predictor of the way in which corrupt activities are organized, as
measured by patterns in the distribution of corrupt rents. This argument builds on a new framework
for categorizing corrupt acts, which emphasizes variation in the substance of government activities
over which bribers are attempting to have influence. The framework highlights general disparities in
the character of illicit payments across multiple realms of government activity: policy-making, e.g.
bribes for favorable legislation; licensing and contracting, such as bribes for allocation of natural
resources and government contracts; government employment, such as bribes for jobs or transfers;
and the delivery of public services, for example the payment of “speed money” by citizens to access
state benefits.
In order to test the argument that the sharing of rents is shaped by the type of government
resource for which bribes are paid, I ask: Are proceeds from a single bribe distributed across
multiple actors? If so, do different types of actors benefit differentially from corrupt acts? What
factors are associated with these variations in the distribution of rents? I use new, original data from
surveys of politicians and bureaucrats in India to answer these questions, drawing on a novel
scenario-based survey-experimental question that measures respondents’ perceptions of the manner
by which proceeds from a single bribe are shared across various actors. With this data, I test both the
overall sharing of rents, using a new measure of the effective distribution of rents (EDR), and the
relative sharing of rents across non-state actors and officials at multiple levels of government.
3
The findings suggest that bribes are shared across multiple individuals, helping to validate a
long-standing claim in the literature that a bribe paid to a single actor is likely to be subsequently
distributed in part to a set of other actors (Beteille 2009; Bussell 2012, Wade 1985). Initially
highlighted in the context of a single government department in India (Wade 1985), this is the first
comprehensive evidence of the manner by which corrupt rents are shared across actors and the
degree to which different sets of individuals benefit from diverse corrupt acts.
Perhaps even more importantly, I also find that the distribution of rents across actors is
strongly shaped by the type of government resource over which corruption occurs. While the overall
distribution of rents does not discernably differ across types of resources, the nature of sharing is
quite varied, with actors at different levels of government and different types of actors—middlemen,
bureaucrats, and politicians—perceived to receive differing shares of rents depending on the specific
character of the resource. Overall, while those actors with direct control over a government resource
are frequently perceived to benefit from corruption related to that resource, actors with indirect
influence over the same resource are also expected to be beneficiaries of the same corrupt act.
In the following sections, I present an argument to explain the presence of, and variation in,
rent-sharing, emphasizing the importance of differences in direct control and indirect influence over
state resources for predicting the organization of corrupt activities. I subsequently review the concept
of corruption and its various types before presenting a new framework for categorizing corrupt acts.
I then discuss the paper’s empirical strategy and tests of rent-sharing and the relationship between
the distribution of rents and the type of government resource, based on new data from three Indian
states, Bihar, Jharkhand, and Uttar Pradesh. I conclude with a discussion of the implications of my
findings for our understanding of corruption in India and elsewhere today.
4
The Organization of Corruption
The existing literature on the causes of corruption, and thus potential avenues for anti-corruption
reform, tends to highlight the role of specific actors engaged in corrupt activities. Strategies to
reduce bureaucrats’ incentives to engage in corruption by increasing their wages, while contested
with regard to their actual benefits (Svensson 2005), in general emphasize the motivations of
bureaucrats, but not their elected or appointed superiors. Analyses of efforts to reduce corruption by
politicians, such as the randomized audit program of the Brazilian government, documented by
Ferraz & Finan (2008), emphasize the role of exposure in increasing the chances that corrupt
politicians will be voted out of office, but do not consider other officials, such as bureaucrats, who
may remain in office.
This emphasis on the most visible actors engaged in corrupt activities results in a tendency to
elide the potential upsides of corrupt activities for other actors in the state, who may stand as indirect
beneficiaries of rent-seeking. Yet, there is reason to expect that these indirect benefits may play an
important role in the overall organization, and persistence, of corrupt activities. Darden (2008)
argues that corruption, in some contexts, benefits public officials at multiple levels of government.
He finds that “where graft is systematically tracked, monitored, and granted by state leaders as an
informal payment in exchange for compliance, it provides both an added incentive to obey leaders’
directives and the potent sanction of criminal prosecution in the event of disobedience” (Darden
2008: 35). Senior officials who allow corruption benefit from a share of the illicit rents due to “an
informal, implicit, and illegal contract between state leaders and subordinate officials, whereby the
receipts from bribery and embezzlement would be granted in exchange for effective implementation
of central directives and a share of the proceeds” (Darden 2008: 42).
5
Similarly, Shleifer and Vishny’s (1993) account of corruption emphasizes that in highly
centralized regimes where there is no competition between government agents in the provision of
state resources, there is likely to be coordination across and within the government hierarchy to
manage the collection of bribes and subsequent distribution to other state actors. As the authors note,
“In such places it is always clear who needs to be bribed and by how much. The bribe is then divided
between all the relevant government bureaucrats, who agree not to demand further bribes from the
buyer of the package of government goods, such as permits” (Shleifer and Vishny 1993: 605).
While both of these analyses describe specific institutional settings, it is fair to expect that we
might see sharing of rents, in some form or another, across multiple institutional contexts. If this is
the case, then attention solely to the recipient of a bribe and that individual’s incentive structure will
be insufficient for understanding the overall set of motivations encouraging the persistence of
corruption. In addition, any effort that attempts to evaluate corruption overall on the basis of costs or
benefits only to these direct recipients of bribes will fail to account for a potentially significant
portion of the corruption actually benefiting other actors within and outside the state.
Despite the potential theoretical and policy relevance of the manner by which rents are
shared across actors, minimal other work that attempts to evaluate the character of illicit rent-sharing.
Wade (1985) discusses the dynamics of corruption and rent-sharing in one government department
of one state in India, but we have little sense of whether these dynamics persist across other areas of
government activity and other regional contexts. I posit that efforts to understand potential strategies
for anti-corruption reform require both a more comprehensive descriptive understanding of the way
in which rents are shared across both state and non-state actors as well as a coherent theory for
explaining variation in the sharing of rents.
6
Rent-Sharing and the Character of Government Resources
I argue that in order to understand the organization of corruption, and specifically the ways in
which corrupt rents are shared between actors, it is necessary to take into account the power
structures underlying corrupt behavior. Corruption is enabled by formal control over the allocation
of state resources, including the discretion to allocate those resources in a particular manner. For
example, if there is a welfare program in place with specific requirements for inclusion in the
program, then the bureaucrat in charge of that program will have formal control over the allocation
of this resource. If there are more qualified applicants for the program than there are resources to
distribute, the bureaucrat may have discretion in choosing recipients, implying a potential
opportunity for corruption. Generally, those individuals with formal control over resource allocation
should have distinct advantages over other actors in the collection of corrupt rents, particularly
where demand exceeds supply and there is room for discretion in allocation.
Yet, formal control is not the only factor that can influence the extraction of corrupt rents.
Actors without formal control may instead wield forms of informal influence, over individuals or
information, which allows them to play a role in corrupt activities. For example, a politician who
does not have the authority to choose directly the recipient of a government contract may be able to
influence this choice indirectly through his formal authority over bureaucrats. Where politicians
have the ability to transfer or pro/demote officials, they can potentially use this influence to pressure
bureaucrats to allocate contracts in a corrupt fashion and then extract a portion of the rents from the
transaction.1 In this way, politicians’ direct control of one government resource, bureaucrats’ jobs,
1 This rent extraction may be general—demanded apart from any specific activities—or particular—
demanded in response to a specific act or acts of corruption in which the bureaucrat is engaged (or
could potentially be engaged).
7
provides them with indirect influence over different government resources, such as contracts, which
may enable them to influence and become indirect beneficiaries of others’ illicit acts.
Power over information entails a different type of indirect influence. Here, any individual,
not necessarily a public official, may possess valuable knowledge that would facilitate a corrupt
transaction. A local middleman might have a greater ability than front office bureaucrats to evaluate
the demand for specific services and the relative willingness of individuals to pay an extra “fee” to
acquire these services. Access to this information could make rent extraction more efficient for local
bureaucrats, such that they are willing to share these rents with middlemen who provide the
information to them. Peisakhin and Pinto note this role for middlemen in the processing of ration
card applications in India, in which “Payments of bribes [to middlemen] in bulk is standard practice
at PDS2 offices as it is the way business owners obtain official papers for their employees”
(Peisakhin and Pinto 2010: 268). Middlemen thus garner a portion of the bribes paid due to the
combination of their access to both public officials and valuable information from private contacts.3
For both direct control and indirect influence, the individuals holding these types of power
over state resources are likely to differ depending on the type of resource. I consider, in general, four
types of state resources, which should incorporate the majority of state resources with regard to
which corrupt activities occur: policies (formal legislation and departmental regulations), public
licenses and contracts, government jobs, and public goods and services.
2 Public Distribution System offices, where applications for ration cards are submitted, are an
important source of welfare benefits in India.
3 It is relevant to note that middlemen may also have indirect influence through their control over the
bribes themselves. As the direct recipient of the illicit payment, they may be able to negotiate with
the relevant bureaucrat a price for the applications that the middleman has collected. This implies
that the middleman could potentially extract a larger portion of the bribe itself than might otherwise
be the case.
8
For policies, legislators typically have the most direct control over the nature of legislation
and the content of departmental regulations. In addition, senior bureaucrats in relevant departments
can play a role in drafting legislation, and so have some formal control legislative content. Thus,
these actors are the most likely to benefit from any payments made by outside actors to encourage
favorable treatment within the legislation. In this context, the “middlemen” who may have indirect
influence over policies are most likely to be lobbyists who, through their connections to both firms
and politicians, may have information on who is willing to bribe and be bribed for favorable policies.
Once these policies are set, responsibility for their implementation typically shifts to bureaucrats. I
consider those actors with formal authority over the implementation of these policies in each of the
remaining categories of government resources.
Public licenses and contracts, such as those allocating mining rights for natural resources,
access to telecommunications spectrum, and contracts to build public structures and roads, are likely
to be shaped by legislation but allocated through implementation processes formally controlled by
bureaucrats. For example, bureaucrats typically oversee bidding processes for licenses, within the
rules set out by related legislation. Thus bureaucrats, at whatever level of government the license is
allocated, should have the most direct control over this resource. However, political superiors of
these bureaucrats are then the most likely to have indirect influence over the process, and in
particular, over the bureaucrats. These politicians can use the threat, or promise, of a transfer,
de/promotion, or other stick/carrot to claim a portion of any illicit rents from the allocation of
licenses.
Power over the allocation of public sector jobs depends on the character of administrative
rules. In many countries, merit-based procedures govern the processes for evaluating and hiring
bureaucrats. Where this is not the case, patronage-based selection is likely to be prevalent and those
9
with the power to select employees may be able to extract rents or favors from individuals in return
for employment. Examples of these dynamics run from the late 19th century in the United States, in
which political appointees where expected to contribute a portion of their salaries to the ruling party
(Schiesl 1991), through the Twentieth century in developing countries (Bussell 2012). Even where
merit-based procedures exist, opportunities for preferential treatment may arise when there are more
qualified candidates than there are open positions (Chandra 2004). Once individuals are employed,
political pressures may still exist (FMCSA 2000)4 and procedures for promotion and transfers can
create opportunities for rent-seeking in the context of weak or nonexistent formal merit-based
processes. This latter point may be particularly important for rent-sharing. Shleifer and Vishny posit
that one mechanism for the sharing of rents is the process for allocating government jobs: “[i]f jobs
are distributed among officials through an auction mechanism, whereby those who pay the most for
a job get it, then the prospective officials who do not collect bribes simply cannot afford jobs” (603-
604). Wade (1985) similarly emphasizes the relevance of bureaucratic transfers in an analysis of the
Indian bureaucracy. In this case, higher-level officials and politicians have power to transfer
bureaucrats laterally between posts with minimal oversight.5 This system of transfers “allows
pressures for ‘corrupt’ behavior to bear down strongly on the incumbents of certain posts – and itself
amplifies those pressures making it more likely that officials will behave in a corrupt manner than if
the transfer mechanism were different” (Wade 1985: 467-468).
4 In a recent scandal, state employees in Illinois engaged in party fundraising were linked to
corruption in the allocation of commercial driver’s licenses.
5 See also de Zwart 1994, Iyer and Mani 2012.
10
In the last case, the delivery of public goods and services to citizens is typically controlled
directly by bureaucrats at the lowest levels of government.6 These actors have the discretion to
determine who receives goods such as welfare benefits, driving licenses, and electricity service.
While formal rules typically exist regarding eligibility for particular goods, bureaucrats may, as in
the case of government jobs, have the power and discretion to choose beneficiaries when there are
more applicants than available goods. In addition, these actors could potentially provide services to
those individuals who do not meet eligibility requirements. In other cases, where a fee is required for
a service or in response to a particular action, such as a traffic fine for speeding, officials can use
their discretion to extract a smaller private fee rather than fining the individual officially. With
public goods and service provision, rents may be shared upward in the government hierarchy due to
the indirect influence of politicians over bureaucrats’ jobs, as described above.
Across all of these types of state resources, there may be a role for middlemen in providing
information and coordinating corruption. This seems most likely in those cases where there are a
large number of individuals or groups who have an interest in a particular resource, such as a welfare
benefit. In these cases, it can be quite difficult for local bureaucrats to assess the relative willingness
of so many individuals to pay a bribe. As a result, there may be significant value placed on people
who can collect this information and funnel individuals to bureaucrats on the basis of their bribe
potential. As the number of interested parties decreases, such as may be likely with building
contracts or coal mining licenses, the demand for middlemen may also decrease, as state officials
have more capacity to determine who would be willing to provide an additional “fee” for access. At
the same time, individuals with close knowledge of businesses and their interests, as well as
6 This includes those private actors who may be charged with provision of public goods and services
through public-private partnerships and privatization.
11
legislative politics—such as lobbyists—may play an important intermediating role between
companies that are willing to engage in corruption in order to influence the policy-making process
and receptive legislators.
The thrust of the discussion to this point is that across four very different types of state
resources—policies, contracts, jobs, and, public resources—we might expect rents to go not only to
officials with direct control over the resource, but also to those with indirect influence, e.g. influence
over the direct service provider. In addition, we should observe different actors engaging directly in
corruption depending on the state resource under consideration. Thus, we may observe a broad group
of actors benefiting from corrupt acts in general, but the make-up of this group is likely to vary in
tandem with variations in the nature of corruption.7 Empirically, I expect that:
1) Those actors with direct control over the distribution of that government resource should be
beneficiaries of corrupt rents,
2) However, those actors with indirect influence over the distribution of that resource should
also be beneficiaries, and
3) The set of actors receiving benefits will differ along with variations in the type of
government resource.
These expectations highlight the importance of directing attention to the broad set of actors
potentially benefiting from corruption. If those actors with indirect influence are able to extract a
portion of the rents from corrupt transactions, they are important, yet under analyzed, players in
corrupt acts. If corruption is organized through interlocking relationships between both the actors
who are the face of corruption, those with direct control over desired state resources, and less
prominent actors who play an indirect but important role in facilitating corruption, then we must
7 Degree of decentralization is also likely to affect the distribution of rents, given differing structures
of power across institutional contexts. Due to space constraints, I save the discussion of
decentralization and rent-sharing for an alternate forum.
12
consider the nature of rent-sharing between these actors in order to fully understand the incentive
structures underlying persistent corruption.
Given that the nature of direct control and indirect influence is likely to differ depending on
the type of resource under consideration, evaluation of these expectations requires that we also
consider the relationship between different types of government resources and different types of
corrupt acts. In order to do so, I briefly consider existing distinctions between types of corruption
before presenting a new framework for distinguishing between different forms of corruption, based
on the type of government resource for which a bribe is paid.
Frameworks for Conceptualizing Corruption
The existing literature offers only minimal insights into how we might distinguish between
various forms of corrupt activity, and thus the relationship between different types of government
resources and the character of rent-sharing. The most common definition of corruption as the abuse
of public office for private gain (inter alia, Olken 2007; Bardhan 2006; Jain 2001; Rose-Ackerman
1975), on which I generally rely in this discussion, offers a concise starting point for categorizing
various behaviors as corrupt or not, but it does little to help us explore variations in types of abuse. A
more comprehensive consideration of variation within the concept of corruption is required.
A number of analysts have responded to this conceptual gap with more specific typologies of
corrupt behavior. The most common distinction, highlighted by Rose-Ackerman (1999),
differentiates between petty and grand corruption. The former refers to bribes citizens pay to lower
level officials either to speed the delivery of services or to bribe officials to “bend the rules” (Rose-
Ackerman 2002; Cisar 2003), while the latter “involves large sums of money with multinational
13
corporations frequently making the payoffs” and politicians using their power to shape policies in
ways that benefit bribers (Rose-Ackerman 2002; 2008: 265; Jain 2001; see also Bussell 2012).
Yet, there are two key limitations to the existing use of typologies in the analysis of
corruption. First, the empirical literature in practice largely belies the question of variation in
corruption, typically analyzing only one example of corrupt behavior without categorizing it as a
particular form of corruption. As Kramon and Posner note, “some researchers measure [corruption]
in terms of local bribe taking by civil servants; others in terms of the valuation of publicly traded
companies with connections to top government officials; others in terms of tax evasion; and others in
terms of leakage in public expenditure” (Kramon and Posner 2013: 469).
This imprecise link between concept and measurement in the corruption literature is
highlighted more generally in a review of classic and more recent works shown in the online
Appendix. For each article or book, I note the definition of corruption used, if given, and the
measurement technique of the analysis, as well as the associated independent or dependent
variable(s). While there is often a reasonably logical match between the measure of corruption and
the independent or dependent variables under consideration, there is typically no further distinction
of the type of corruption that would allow us to compare results across individual analyses. These
differences in the measurement of corruption and the frequent gap between concept and
measurement may result in analyses with quite different findings regarding what factors encourage
corrupt behavior and how corruption affects political and social outcomes.
Second, the common dichotomy of petty and grand corruption is incomplete. For example, in
their analysis of municipal-level corruption in Brazil, Ferraz and Finan highlight that “most
corruption schemes used by local politicians to appropriate resources are based on a combination of
fraud in procurements, the use of fake receipts or ‘phantom’ firms, and over-invoicing the value of
14
products or services” (Ferraz and Finan 2008: 710). This corruption in contracting over government
resources is quite common in developing countries but does not necessarily fit the characteristics of
grand and petty corruption just discussed.
Thus, in order to evaluate the ways rents may be shared across actors, it is important to
distinguish between the diverse forms of corrupt acts in which politicians, bureaucrats, and
individual citizens are engaged and how they relate to different types of government resources. To
this end, I present here a framework for conceptualizing variation in forms of corruption on the basis
of the type of government resource over which an individual or group is attempting to gain influence
(Table 1). Attention to the type of resource tells us which government actors are most likely to have
formal authority or informal power over this resource and, thus, have the potential to feasibly extract
rents from any corrupt activities that may occur in the allocation of the resource.8
8 The specific actors with power over a given resource may change across institutional contexts.
15
Table 1 – Government Resources and Varieties of Corruption
Type of Government Examples of Holder(s) of Direct Holder(s) of Indirect
Influence
Resource Corruption Control
- Bureaucrats with control
- Government policies - Payments for - Presidents/Ministers/ over implementation
and regulations favorable Legislators - Politicians with power
over bureaucrats
legislation - Top department
- Middlemen
bureaucrats
- Middlemen
- Allocation of - Kickbacks on - Bureaucrats at level of
- Politicians with power
licenses/contracts licenses/contracts contract/project over bureaucrats
(natural resources, - Local politicians
- Middlemen
schools, roads, etc.)
- Government jobs - Bribes or favors - Politicians and
for jobs bureaucrats with hiring
and transferring authority
- Provision of - Bribes for - Local (“street-level”)
individual benefits “speedy” services bureaucrats
(e.g. IDs, welfare) or
sanctions (e.g.
traffic violations)
Empirical Strategy
In this section, I provide the background for using surveys of politicians and bureaucrats in India to
gain leverage on two key questions regarding rent-sharing and the organization of corruption:
1) Do actors with both direct control and indirect influence share bribes from corruption in
multiple types of government resources?
2) Does the identity of the recipients of rents correspond with the holders of direct control and
indirect influence identified in Table 1?
Corruption and Politics in India
India provides an important empirical testing ground for arguments about the organization of
corruption, not only because it is often a reference point for theoretical development but also due to
the persistence of multiple corruption types throughout the subcontinent. Even so, while many
16
studies highlight the pervasiveness of corruption in India (Bussell 2012; Transparency International
2008; Transparency International India and Centre for Media Studies 2005, 2008), little work has
analyzed the nature of variation in Indian corruption.9
Corruption in India reflects the range of corrupt activities considered above. A recent spate of
scandals has highlighted the prevalence of corrupt behavior by high-level politicians and bureaucrats
alike, involving scams related to building contracts and allocation of rights to natural resources
valued in the tens of billions of dollars.10 These scandals reflect corruption in the distribution of
many of the state resources discussed above, and in particular the allocation of licenses and
contracting for public projects. This corruption exists in parallel with frequent demands for bribes in
everyday dealings with the state—a majority of Indian citizens is estimated to have paid a bribe for
public services at some point in time (CMS & TII 2005).11
Yet, we have little understanding of how various actors benefit from these diverse activities
and, in particular, how rents may be shared across state and non-state actors. Limited analyses in the
water and education sectors (Wade 1985; Beteille 2009) provide the primary evidence of the extent
to which the recipient of a bribe has to distribute these rents to other actors and whether this differs
across types of corruption.
9 A recent exception is Charron (2010).
10 Investigations into construction of facilities for the 2010 Commonwealth Games in Delhi
“discovered widespread…falsification of records and unjustifiable inflation in contract costs”
(Sexton 2010); an apartment building in Maharashtra, intended to serve war veterans, was found
instead to be benefiting top government officials (NDTV 2010a; 2010b); and central government
officials were accused of costing the government nearly U.S. $40 billion (NDTV 2010c) and U.S.
$35 billion through questionable allocation of rights to telecommunications spectrum and coal
deposits, respectively. thro
11 An analysis of corruption in the delivery of services at the state level and across eleven
government departments found that more than 60% of Indians have paid a bribe to receive a
government service, amounting to more than Rs. 210 billion (approximately U.S. $4.7 billion) each
year (Transparency International India and Centre for Media Studies 2005: 3).
17
India also provides a viable empirical context for testing hypotheses regarding the
relationship between the power over state resources held by actors at various levels of government
and their access to corrupt rents. India’s federal structure includes five levels of elected officials:
national legislators, state legislators, district council members, block council members, and village
council members.12 In addition, there are multiple levels and categories of bureaucrats, including the
national and state administrative services, as well as lower levels of state employees. Policies are
typically made at the national and state levels, while decisions regarding the manner of policy
implementation may be made at the national, state, district, block, and/or local council level,
depending on the substance of the policy itself. This should allow us to evaluate how actors with
power over state resources at different levels of government organize to extract rents.
Sampling Strategy
The data source for this analysis is a set of original surveys of politicians and bureaucrats at multiple
levels of government in Bihar, Jharkhand, and Uttar Pradesh, three states in the Hindi-speaking belt
of North India.13 In every sampled constituency, surveys were conducted with all levels of elected
officials, from village councilors to members of parliament, and the three levels of bureaucrats active
in state governance.14 In the analysis and discussion below, I refer to three groups of politicians:
low-level, which includes members and presidents of village councils; mid-level, including members
and presidents of block and district councils; and high-level, including members of state legislatures
12 The most common administrative organization of Indian states is first into districts, then blocks,
and then village councils (gram panchayats). In some states, there may be an additional layer of
administration, but there will not be elected officials at this additional level.
13 Jharkhand was carved out of Bihar and made an independent state in 2000.
14 Members of central government administrative organizations, other than the Indian Administrative
Service (IAS), were not included in the sample. Members of the IAS with positions other than
District Collector, such as those within specific state departments, were also excluded.
18
(Members of the Legislative Assembly or MLAs) and members of national parliament (MPs). I also
refer to two groups of bureaucrats: low-level, who are secretaries of village councils, and mid-level,
which includes block development officers (BDOs) and district collectors (DCs).
In order to cover this range of respondents, the sampling procedure for the surveys
incorporated village, block, and district councils, as well as state and national legislative
constituencies.15 Mid- and high-level politician, as well as mid-level bureaucrat, respondents were
sampled randomly, through a multistage selection process. First, districts were randomly selected.
Then, blocks were randomly selected within the districts. The presidents of the block and district
councils, as well as one council member and the primary bureaucrat (BDO or DC) at each level were
included in the sample. For high-level respondents (MLAs and MPs), the blocks and districts in the
sample were mapped to state and national constituencies and all of the politicians whose
constituencies fall in the overlapping areas were included in the sample.
Once districts and blocks were chosen, the selection of village councils, and thus low-level
politicians and bureaucrats, was done on the basis of a regression discontinuity design, used for a
different study objective than that discussed here, which was determined by the reservation of
village council president seats for scheduled castes.16 Though the sampling of village councils is not
strictly random, it is largely consistent with a random sample. The set of selected councils is
statistically indistinguishable from the population on a host of characteristics, as measured in the
15 On average, the village council (gram panchayat), covers 5 villages in Bihar, 7 in Jharkhand and
2 in Uttar Pradesh; the block council (panchayat samiti), includes 16 village councils in Bihar, 20 in
Jharkhand, and 65 in Uttar Pradesh; and the district council (zilla parishad), incorporates 14 blocks
in Bihar, 9 in Jharkhand, and 12 in Uttar Pradesh. Bihar has 38,475 villages, 8,463 village councils,
534 blocks, and 38 districts; Jharkhand has 32,620 villages, 4423 village councils, 212 blocks, and
24 districts; and Uttar Pradesh has 97,607 villages, 52,905 village councils, 814 blocks, and 70
districts.
16 For additional details, see Dunning and Nilekani (2013).
19
Indian census (Dunning and Nilekani 2013). A summary of the sampled jurisdictions is shown in
Table 2 and summaries of the politician and bureaucrat samples are provided in Tables 3 and 4.
To my knowledge, this sampling procedure results in the most comprehensive set of
politician and bureaucrat surveys ever conducted in India or elsewhere. The response rate was also
quite good: For mid- and high-level officials, the overall non-response rate across states was 33.6%.
The lowest response rates were for block council members and MLAs in Uttar Pradesh.
Table 2 – Distribution of Sampling Units by State and Office
Administrative Region Bihar Jharkhand Uttar Total
Pradesh
Districts 15 9 54
Blocks 67 16 30 232
Village Councils 166 118 149 582
298
Table 3 – Overall Politician Sample
Politician Type of Politician Bihar Jharkhand Uttar Total
Pradesh
Group 16 6 15 37
53 18 80 151
High-level National Parliament 14 8 15 37
State Assembly 13
Mid-level District Council 58
61
Presidents 158
District Council 328 12 16 41
701
Members
Block Council Presidents 30 29 115
34 38 133
Block Council Members 120 280 558
Low-level Village Council
Presidents
Village Council Members 234 592 1154
462 1065 2226
Total Sample
Table 4 – Overall Bureaucrat Sample
Bureaucrat Type of Bureaucrat Bihar Jharkhand Uttar Total
Pradesh
Group 31 8 13 52
110 22 191
Mid-level District Collectors 59
142
Block Development
283
Officers
Low-level Village Council 99 256 497
Secretaries
Total Sample 129 328 740
20
Questionnaire Scenarios and Survey Experiment
I measure rent-sharing as the way in which a single bribe is distributed across a set of actors.
In other words, if a bureaucrat receives a bribe of $100 (or ~Rs. 5000), does the bureaucrat keep that
entire bribe, or does he share it with other actors? If the bribe is shared, what proportion is shared
with which other actors?
The questionnaires utilized scenarios to measure rent-sharing by evaluating respondents’
perceptions of how bribes related to state resources are shared across actors. A survey-experimental
design was used to ensure that exposure to one scenario did not affect respondents’ subsequent
perceptions of, and responses to, other scenarios.17 The full text of the scenarios is provided in
Appendix A.18
Two scenarios represent corruption in the provision of public goods and services. In the first,
a citizen who is attempting to collect his monthly ration of subsidized foodstuffs is approached by a
middleman19 who offers to help the individual, for a fee (Rs. 100 or ~ U.S. $2), based on contacts
that the middleman has in the department (Appendix A1). In a recent survey, 16% of people utilizing
the public distribution system20 (or 7% of the total population) reported having paid a bribe, with the
typical amount ranging from Rs. 50 to 500 (U.S. $1-10) (TII/CMS 2005).
17 For high- and mid-level politicians, as well as mid-level bureaucrats, each respondent was
presented with two of the four scenarios, which were altered in order across randomly assigned
versions of the questionnaire. Low-level politician and bureaucrat respondents were presented with
only one scenario due to the larger sample of these respondents, which afforded sufficient statistical
power from a fully between-subjects design, and a longer questionnaire.
18 For current purposes, I do not directly evaluate corruption related to the allocation of government
jobs.
19 In all scenarios, the Hindi term used for “middleman” is dalal.
20 India’s public distribution system is a food security programs that provides subsidized foodstuffs
and non-food items to the poor, via a network of public distribution or “ration” shops. In order to
access these goods, individuals must have a “ration card” that documents their eligibility.
21
In the second public services scenario, an individual attempts to make a change in his land
record (a basic property ownership document) at the Revenue Department, but there is a dispute with
his neighbor over the border of the plot. In order to resolve the issue, the Revenue official asks for an
additional “fee,” proposed in the questionnaire to be Rs. 1000 (U.S. $20) (Appendix A2). In the
same survey noted above, 48% of people who interacted with the government for land records paid a
bribe (approximately 7% of the total population), with the bribe paid at approximately Rs. 2,000
(U.S. $40) on average (TII/CMS 2005).
For corruption in public contracting, the third scenario presented a project to build a village
road in which the competitive bidding process to choose a contractor for the project was superseded
by the local administration so as to grant the contract to a company that has promised to provide
campaign contributions to politicians in the area (Rs. 100,000 or U.S. $20,000) (Appendix A3).
In the final scenario, designed to reflect corruption in policy making, the state government is
considering new legislation to change industrial development regulations. In order to influence the
policy content, a number of large companies are said to have secretly given politicians campaign
“contributions.” The proposed size of the bribe in this case is Rs. 1,000,000 (U.S. $200,000)
(Appendix A4).
The assigned scenario was read aloud and the respondent was asked how common is such a
scenario. They were then asked how they think the bribe, as specified in the scenario, would be
allocated across a set of individuals and groups, including local administrators and politicians, state
politicians, and political parties (i.e. the amount of the bribe that each type of actor would get).
These scenarios should be interpreted as representing a minimum measure of the rent-sharing
that is likely to be occurring in the described context. The descriptions are written in a manner that
focuses in each case on the specific bribe being paid. As a result, respondents are most likely to
22
interpret the question in a narrow fashion that refers only to distribution of the amount specified in
the description. This means that other forms of less direct rent-sharing may be unaccounted for in the
analysis. For example, if it is common for bureaucrats to collect many bribes over time and then, on
occasion, to provide a payment to one of their superiors, such as to secure a new position, this may
not be captured through this measurement strategy.
The scenarios also must be understood to measure the perceptions of respondents regarding
the distribution of rents related to each type of state resource. There are two goals of measuring
perceptions, rather than the actual incidence of corruption. First, measuring the occurrence of
corruption is a difficult task when considering rent-seeking related to any single type of government
resource, let alone multiple types. The likelihood of finding a single technique or strategy that would
allow for direct measurement across various forms of corruption is very small. Second, the strategy
that might provide the most comparable data across state resources is direct reports from those
involved in corrupt activities, but the risk of social desirability bias in responses to direct questions
about engagement in corrupt behavior seems very high (not to mention the fact that bribe-giving and
taking are formally illegal).
I anticipate that questions which do not directly implicate the respondent—those asking only
for their perceptions of corrupt activity—should help to alleviate both of these concerns related to
direct measures of corruption. Individuals at all levels of government can be asked in similar ways
about their perceptions, so as to increase comparability of responses across types of government
resources and across different types of respondents. Respondents should also be more willing to
report on the characteristics of corruption in theory, as this entails less of an implication that they
themselves benefit from these activities. I consider below the degree to which social desirability bias
appears to be present in responses.
23
However, there are also risks to using perceptions-based questions. First, measuring
perceptions is not measuring corruption. With this measure I am only viably able to report what
individuals say they understand about the organization of rent-sharing. This leads to the second point,
which is that individuals may differ substantially in their actual knowledge of rent-sharing. More
senior state officials who have risen through the government hierarchy may be more directly aware
of corruption in a range of government resources than those individuals who have only served in the
lower tiers of government. Alternatively, senior individuals may also be less aware of changes in
corrupt behavior at the lowest levels, such that junior politicians and bureaucrats are able to hide
some portion of the rents they receive, thereby distorting the perceptions of senior officials. Third,
actors at different levels of government may perceive the risks associated with discussing corruption,
even in the form of perceptions, differently. Thus, differing expectations related to the social
desirability of even knowing about corruption may affect the likelihood of respondents at different
levels of government to reply honestly about their perceptions of rent-sharing. Any of these issues
could potentially result in patterns of non-response that differ across groups of actors. I attempt to
adjudicate between these risks by considering here non-response related to types of respondents,
presenting below the responses of individuals at different levels of government separately and
considering in the discussion any implications differences across actors for my conclusions.
Patterns of question non-response across respondent groups may be relevant for interpreting
the findings presented below. As I show in greater detail in Appendix D, senior officials were more
likely to respond to this question in general. Across the individual scenarios, sub-groups were also
most likely to respond if the scenario they received described corruption in a government resource
for which they are likely to have direct control. However, in most cases, there were not large
differences in response rates across the four scenarios. In other words, individuals who were inclined
24
to respond did so largely regardless of the scenario they were assigned, with the exception being that
nearly all groups were least likely to respond to the Road scenario. This implies that high-level
officials may feel more comfortable responding to a question about corruption, but variation in
knowledge about different types of corruption only moderates the likelihood of response.
Hypotheses by Type of Government Resource
Based on the theoretical discussion above, I expect the following outcomes in each of the
four scenarios. First, in the ration scenario, this is a situation in which a middleman is intermediating,
based on some perceived private knowledge regarding access to food rations. As a result, this actor
should receive a significant portion of the rents. The ration shop owner is, in most cases, a private
individual who has contracted with the state and who should also receive some portion of the bribe
given his formal power over ration distribution. Finally, low-ranking bureaucrats or politicians with
direct control or indirect influence, respectively, over ration shop contracts might also to be able to
extract some portion of rents from this type of transaction.
Second, for land records, the individual with the most direct control is a local bureaucrat who
commands the official authority to alter land records, and so should be a relevant player in any legal
or illegal transaction. In addition, a middleman could share in rents by linking local bureaucrats to
individuals in need of assistance with their documents. The last group of actors that may benefit
from this type of transaction are those typically sub-national politicians with indirect influence over
property transactions through their power over transfers of local bureaucrats.
Third, with regard to road contracts, bureaucrats should have direct control over contract
allocation, most commonly those at the district level in India. There may be some opportunity for
middlemen here, however, given that there are likely to be a smaller number of actors interested in
25
contracts than in basic public services, the demand for middlemen may be lower than in the previous
two cases. Politicians, in contrast, particularly those at the state level who can transfer lower-level
bureaucrats, should have opportunities to share in rents from this type of transaction.
Fourth, corruption in the policy-making process is likely to provide benefits primarily to
legislators themselves, given their direct control over legislation. Senior bureaucrats, who often
participate in the drafting of policies, may also partake in rents from this form of corruption.
Middlemen with connections to large businesses and bureaucrats tasked with policy implementation
may also benefit, through their influence over the sources of bribes and the nature of policy
outcomes, respectively.
Measuring Rent Distribution
Building on these scenarios, I develop a new measure to evaluate the relative sharing of rents
perceived by respondents. Similar to measures of the effective number of parties, I measure the
Effective Distribution of Rents (EDR) based on the proportion of rents each respondent allocated to
each type of individual in a given scenario. The formula for the calculation is r = 1/Σpi2 where r
denotes the effective distribution of rents and pi is the proportion of rents received by each type of
actor, with the summation calculated over all possible recipients mentioned in each scenario.
Because this calculation does not take into account the level or type of actor receiving a portion of
rents, EDR summarizes the overall distribution of rents, regardless of which actors are sharing a
given bribe. A lower EDR score (close to one) indicates a more concentrated distribution of rents.
26
Findings
In this section, I discuss tests of the spread of rents across actors and the relationship between this
distribution and both the type of actor and the type of government resource for which corruption is
occurring. I first present the findings according to government resource and then consider overall
results for the effective distribution of rents. I describe findings from respondent sub-groups
separately, with responses from mid-level (district representatives and block representatives) and
high-level (MPs and MLAs) politicians shown first, followed by mid-level bureaucrats (DCs and
BDOs), then low-level politicians (village council representatives), and finally low-level bureaucrats
(village council secretaries). This allows for an evaluation of the difference in perceptions across
each of these groups, which would otherwise be lost in a pooled presentation.
Distribution of Rents
Figures 1-4 present results for initial tests of the expectations outlined above by
disaggregating mean responses to the “allocate the bribe” question by the type of government
resource in the scenario.21 For a given scenario, there are four graphs, one for each subset of
respondents. Within each graph, the bars represent the mean proportion of the bribe that respondents
allocated to each type of actor within the scenario.
The first observation is that, in general and as predicted, multiple individuals are expected to
receive some portion of the rents in each scenario. However, a second observation is that the
distribution of rents differs quite dramatically across the scenarios and these differences reflect quite
well the hypotheses above regarding the organization of rent-sharing related to different types of
21 The proportions for each scenario do not add up exactly to one (1) due to slight differences in the
number of response categories in the Bihar survey instrument versus the instrument used in
Jharkhand and Uttar Pradesh.
27
government resources. For the ration scenario, all respondent groups expect the middleman to
receive a large majority of available rents. While the questionnaire did not ask specifically about the
ration shop owner, we also see that all respondent groups expect low-level bureaucrats to be
secondary beneficiaries of this transaction, as predicted. All respondents other than mid-level
bureaucrats also perceive low-level politicians and both mid- and high-level bureaucrats, who may
have indirect influence over local bureaucrats, to be partial beneficiaries of this form of corruption.
The results for the second public services scenario, involving a change to a contested land
record, highlight a much stronger expectation by all respondent groups that low-level bureaucrats,
who hold direct control over this resource, will be primary beneficiaries. There is also a general
expectation that middlemen, who are thought to have indirect influence in this area, will benefit from
corrupt transactions. Indeed, even though this scenario described a Revenue official soliciting a
bribe—and did not mention a middleman—such intermediaries are expected by three of the four
categories of respondents to receive the majority of the illicit “fee.” No other actors are consistently
seen to benefit from this transaction.
For corruption in government contracting, as operationalized here in the road contract
scenario, I hypothesized that we should see a more significant allocation of rents to mid-level
bureaucrats, sharing of these rents with political superiors, and potentially a small allocation to
middlemen. Across all respondent groups except low-level bureaucrats, we do see the expectation
that mid-level bureaucrats will receive a greater proportion of rents than they do from any other
scenario. In addition, three of four respondent groups perceive mid- and high-level politicians to
garner a share of rents. While middlemen are again expected to receive significant rents, this is, in
most cases, a smaller proportion than for the previous two scenarios.
28
Finally, the policy-making scenario highlights some of the most dramatic difference from
other scenarios. Here, I hypothesized that high-level politicians should take the greatest share of
rents given their direct control over policy content, and this is what we observe for all but the low-
level bureaucrats group. Respondents at lower levels of government expect mid-level politicians to
benefit more from corruption in policy-making, however this may reflect their distance from the
actual policy-making process. I address the potential relationship between level of respondent and
likely direct knowledge of corrupt activities below. There is also a general perception (except among
low-level bureaucrats), that middlemen benefit relatively less from policy-making, while multiple
groups expected mid-level bureaucrats to benefit from this form of corruption, as predicted.22
22 A secondary finding is that respondents did not simply allocate a large proportion of the rents to
the first category of individual listed in the questionnaire.
29
Figure 1 – Ration Scenario – Mean proportion of funds allocated by each respondent group to
each type of actor
Mid-‐
&
High-‐Level
Politicians
Mid-‐Level
Bureaucrats
1
1
0.8
0.8
0.6
0.6
0.4
0.4
0.2
0.2
0
0
Low-‐Level
Politicians
Low-‐Level
Bureaucrats
1
1
0.8
0.8
0.6
0.6
0.4
0.4
0.2
0.2
0
0
Note: Findings are disaggregated by type of respondent, as distinguished in graph titles. The ration
scenario involves payment of a fee to acquire access to subsidized food stuffs.
30
Figure 2 – Land Record Scenario – Mean proportion of funds allocated by each respondent
group to each type of actor
Mid-‐
&
High-‐Level
Politicians
Mid-‐Level
Bureaucrats
1
1
0.8
0.8
0.6
0.6
0.4
0.4
0.2
0.2
0
0
Low-‐Level
Politicians
Low-‐Level
Bureaucrats
1
1
0.8
0.8
0.6
0.6
0.4
0.4
0.2
0.2
0
0
Note: Findings are disaggregated by type of respondent, as distinguished in graph titles. The land
record scenario involves payment of a fee to facilitate changes to a land ownership document.
31
Figure 3 – Road Contract Scenario – Mean proportion of funds allocated by each respondent
group to each type of actor
Mid-‐
&
High-‐Level
Politicians
Mid-‐Level
Bureaucrats
1
1
0.8
0.8
0.6
0.6
0.4
0.4
0.2
0.2
0
0
Low-‐Level
Politicians
Low-‐Level
Bureaucrats
1
1
0.8
0.8
0.6
0.6
0.4
0.4
0.2
0.2
0
0
Note: Findings are disaggregated by type of respondent, as distinguished in graph titles. The road
contract scenario involves making a “donation” to local politicians in order to win a contract to build
a road.
32
Figure 4 – Policy Scenario – Mean proportion of funds allocated by each respondent group to
each type of actor
Mid-‐
and
High-‐Level
Politicians
Mid-‐Level
Bureaucrats
1
1
0.8
0.8
0.6
0.6
0.4
0.4
0.2
0.2
0
0
Low-‐Level
Politicians
Low-‐Level
Bureaucrats
1
1
0.8
0.8
0.6
0.6
0.4
0.4
0.2
0.2
0
0
Note: Findings are disaggregated by type of respondent, as distinguished in graph titles. The policy
scenario involves making a “donation” to a politician to ensure favorable legislation.
Perceptions and Patterns of Response
Another way to account for differences in knowledge about corruption across respondent
groups is to consider only the findings for each group when they are reporting on the receipt of rents
by officials in their own category. This requires dropping results for perceptions of rents received by
33
middlemen, political parties, and high-level bureaucrats, as these groups were not directly included
in the subject pool, but it can give us a perspective on relative sharing of rents across the remaining
sub-groups. The results for this analysis are shown in Figure 5.
Figure 5 – Mean proportion of funds allocated by respondents in each sample sub-group to
their own sub-group, by scenario
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
Mid-‐level
High-‐level
Low-‐level
Mid-‐level
Politician
Politician
Bureaucrat
Bureaucrat
Low-‐level
Politician
Note: Dotted bars = Ration Card scenario, striped bars = Land Record scenario, black bars = Road
scenario, and dark gray bars = Policy scenario. Because results are pulled from multiple samples and
responses for some groups are excluded, the bars for each scenario will not add to one.
This graph provides perhaps the most compelling and consistent perspective on the allocation
of rents across scenarios. Overall, low-level actors perceive themselves to receive a larger proportion
of rents in the scenarios reflecting corruption in delivery of public goods and services, where they
are more likely to exercise direct control. Similarly, mid- and high-level actors perceive themselves
34
to receive the largest portion of rents from corruption in contracting and policy-making, respectively.
At the same time, most actors do perceive that their group receives rents from activities for which
they do not hold direct control, in particular high-level politicians who receive rents from corruption
in contracting and mid-level bureaucrats who receive rents from corruption in policy-making. These
latter findings, in line with my predictions, further emphasize the importance of indirect influence
over resource allocation and policy implementation.
These results can be tested further using more rigorous analyses of variation in responses
across the four scenarios. In Appendix C, I present the results of t-tests used to examine within-actor
differences in perceived share of rents (Tables C1-C4). Overall, the results validate the variations in
rent-sharing suggested by the mean responses shown in the previous graphs.
Effective Distribution of Rents
A second test of differences in the sharing of rents uses the effective distribution of rents
measure described previously. This measure evaluates overall rent distribution across different types
of government resource, rather than disaggregated by type of actor. In other words, instead of
emphasizing differences in the level and type of actor receiving rents, as highlighted in the previous
sub-section, this measures summarizes the overall spread of rents across all actors. The EDR
measures for each corruption scenario are provided in Table 5 for all respondent groups.
Table 5 – Summary Statistics for Effective Distribution of Rents, All Respondents*
Scenario Mid- & High- Mid-level Low-level Low-Level
level Politicians Bureaucrats Politicians Bureaucrats
Ration 1.32 (.78) 1.14 (.41) 1.64 (1.20) 1.18 (.44)
Land 1.50 (.84) 1.36 (1.39) 1.89 (1.38) 1.46 (.92)
Road 1.20 (.82) 1.02 (.10) 2.86 (1.86) 1.47 (1.16)
Policy 1.15 (.68) 1.39 (1.55) 2.12 (1.93) 1.26 (1.03)
*Mean is shown with standard deviation in parentheses.
35
There are a number of characteristics of the EDR scores worth noting. First, in nearly all
cases the EDR is greater than one, confirming the general finding that respondents perceive rents to
be shared by multiple actors. Second, the relative size of EDR scores differs across the groups of
respondents, which is evident when we focus on the scenarios with which each group is most likely
to be familiar (shaded cells in Table 5). Mid- and high-level politicians, as well as mid-level
bureaucrats, perceive relatively low EDRs in the policy and road contract scenarios, respectively. In
contrast, low-level bureaucrats and politicians perceive somewhat higher EDRs in the ration and
land record scenarios. This suggests differences in EDR across types of state resources.
To evaluate this latter observation, I use difference of means tests, reported in Table 6.
Comparisons of perceived differences in rent sharing between those state resources with which
respondent groups are most likely to have direct knowledge are shaded in the table. While there are
some statistically significant differences across scenarios, in no case are these differences apparent in
the comparisons with which they are most likely to be best acquainted. Mid- and high-level
politicians perceive no clear difference between the EDR associated with the policy and road
contract scenarios, nor do mid-level bureaucrats, who also see no difference between the road
contract and land record scenarios. Similarly, neither low-level politicians nor bureaucrats perceive
clear differences between the overall distribution of rents from the ration and land record scenarios.
Comparing across all types of state resources, however, requires analyses that move beyond
those resources with which respondents are likely to be most familiar. Considering mid- and high-
level politician respondents perceive corruption in public service delivery, the ration and land record
scenarios, to exhibit a greater distribution of rents than corruption in contracting or legislation. Low-
level politicians, on the other hand, generally perceive the opposite and there are no statistically
36
significant findings for either of the bureaucrat respondent groups.23 Thus, taking into account those
comparisons with which respondents are most likely to be familiar, as well as comparisons across all
of the scenarios, there is no evidence to support a hypothesis that the overall distribution of rents
differs across types of government resource.
Table 6 – t-tests comparing the Effective Distribution of Rents in the four scenarios – All
Respondents
Difference of Ration Ration- Ration- Land- Land- Road- N
Means -Land Road Policy Road Policy Policy
Respondent -.17* .18* .18** .30*** .32*** .05 358-411
Group (-2.17) (2.18)
(2.45) (3.54) (4.74) (.66)
Mid- and
High-level -.22 .11 -.25 .34 -.02 -.37 41-51
Politicians (-.69) (1.27) (-.69) (1.15) (-.06) (-1.11) 145-355
-.24 -1.21*** -.48* -.97*** -.23 .74* 36-94
Mid-level (-1.77) (-5.91 (-2.47) (-4.26) (-1.10) (2.31)
Bureaucrats -.28 -.29 -.07 -.01 .21 .22
(-1.93) (-1.46) (-.41) (-.03) (.82) (.59)
Low-level
Politicians
Low-level
Bureaucrats
Discussion and Conclusion
The presence of corruption, and even a range of its causes and consequences, is relatively well-
covered territory in analyses of political economy. Yet, the organization of corrupt practices and the
nature by which these behaviors differ in distinct realms is largely understudied, leaving substantial
questions regarding corruption and its persistence unanswered. In particular, our ability to discern
the range of individuals benefiting from a corrupt act, and thus the set of actors likely to resist anti-
corruption reforms, has been limited by attention only to the specific individuals benefiting directly
from corrupt actions.
23 It is worth noting that the respondent categories for which we observe statistically significant
results are those for which we have higher-powered tests due to the larger N.
37
The theoretical discussion and empirical analysis presented here provides evidence to suggest
that the type of government resource, by shaping those actors with direct control and informal
influence over access to corrupt rents, plays an important role in shaping a primary characteristic of
the way in which corruption is organized—the sharing of rents across actors. For examples of
corruption in public goods and service delivery, middlemen and low-level bureaucrats reap the
largest proportion of rents. For corruption in government contracts, on the other hand, mid-level
bureaucrats reap substantial rents, as well as middlemen and mid- and high-level politicians. With
regard to policy-making, high-level politicians are seen to be the predominant beneficiaries of
corruption, followed by mid-level bureaucrats.24 Overall, these results offer systematic empirical
support for the argument that actors with direct control over government resources are likely to be
substantial beneficiaries of corruption in the distribution of those resources, but that other actors with
indirect influence, either through their control over individuals or information, are also likely to be
recipients of a substantial proportion of these rents. Thus, differing power over state resources
structures the ability of actors to organize for rent-seeking and so shapes the distribution of illicit
rents from diverse corrupt activities.
These findings are also important from a policy perspective, because they suggest two
potential constraints on efforts to reduce corruption. First, and in general, where individuals
differentially benefit from corruption related to different types of government resources, they should
have clear incentives to pursue the types of corruption for which they will receive the greatest
benefits. Thus, differing groups within government may support or oppose a specific anti-corruption
measure.
24 While low-level politicians attributed more rents to mid-level politicians in this scenario, it seems
reasonable that they are less likely than their mid- and high-level peers to be aware of the allocation
of rents at high levels.
38
Second, and perhaps more importantly, understanding which actors would be the most or
least likely to support anti-corruption measures may not be as simple as determining who is directly
engaged in a particular type of corrupt act. Instead, many other actors may be indirect beneficiaries
of these transactions, and so would be likely to oppose such a policy agenda, but are difficult to
identify if analysts focus solely on the type of individual receiving a bribe.
Of particular interest here are the results for middlemen across the scenarios, which suggest
that non-state actors often play an important role in facilitating government corruption. These actors
are unlikely to respond to the same policy initiatives as public officials, so shedding light on their
part in corrupt transactions is fundamental for developing a comprehensive reform agenda. This also
suggests that further work is needed to understand whether the demand for middlemen is explained
by the reasons suggested above. For example, if a low information environment means that
middlemen share information with potential bribers on the appropriate size of bribes, then efforts to
make bribes transparent might make corruption easier in the short run, but also make reform more
feasible in the long run by eliminating a key actor in the bribing network who would otherwise resist
change. Thus, this analysis highlights the importance of identifying the motivations for, and role of,
both state and non-state actors in facilitating corruption.
Finally, these analyses also take advantage of a new framework for categorizing corrupt
activities, introduced here, which emphasizes the type of state resource over which actors are
attempting to gain access. Unlike in much previous work, this conceptual differentiation allows for
distinguishing between different forms of corrupt behavior and comparing characteristics of these
behaviors. Explicit attention to the variation in forms of corruption allows, here, greater insights into
the organization of corruption and distribution of rents and should similarly enable further research
into the characteristics of corruption more generally.
39
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44
Appendix A – Corruption Scenarios
A1: Scenario 1 – Rations
An individual goes to collect his monthly ration, but there is a long line. The person is approached
by a man who says that he knows people in the department and can help the individual for a fee.
If the individual pays 100 Rupees to gain access to their monthly ration, how much money, if any,
will each of the following individuals receive?
A2: Scenario 2 – Land records
A man goes to the Revenue Department to make a change to his land record, but there is a dispute
with his neighbor over the border of the plots. The Revenue official offers to help resolve the
situation for a fee.
If the individual pays 1,000 Rupees, how much of the fee, if any, will each of the following
individuals receive?
A3: Scenario 3 – Road contract
There is a project to build a road through a village in the state. Instead of a competitive bidding
process to choose a contractor for the project, the local administration grants the contract to a
company that has promised to provide campaign contributions to politicians in the area.
If the company contributes 1 lakh (Rs. 100,000), how much of that money, if any, will each of the
following individuals receive?
A4: Scenario 4 – Legislation
A new policy is being considered by the state government to change regulations regarding industrial
development policy in the state. A number of large companies have secretly given politicians
“contributions” in order to influence the policy in their direction.
If a company gives a 10 lakh (Rs. 1,000,000) contribution to an MLA, how much of that money, if
any, will go to the following individuals?
45
(Online) Appendix B - Studies Analyzing Corruption: Variables, Concepts, and Measures
Article/Book IVs and/or DVs Concept Measurement Strategy
Ades, Alberto and Rafael - IVs: “Natural” - Undefined
Di Tella. 1999. - Business Intelligence corruption
rents, e.g. from - The misuse of political and index, World Competitiveness Report
Alt, James E. and David natural resources, administrative power at the scores for “the extent to which
Dreyer Lassen. and “market” expense of citizens; the misuse of improper practices (such as bribing or
Forthcoming. rents, e.g. from public office for private gain corruption) prevail in the public
lack of sphere” (World Competitiveness
Bertrand, Marianne, competition - Undefined Report, as quoted in Ades and Di
Simeon Djankov, Rema - Operationalized as extra payments Tella, 986)
Hanna, and Sendhil - IV: Prosecutorial
Mullainathan. 2007. resources to agents or bureaucrats to receive - Corruption convictions in the United
a government service (driver’s States, as reported by the Public
- DV: Ability to license) Integrity Section of the US
obtain driver’s Department of Justice.
license - Undefined
- Information not provided on details - Difference between proportion of
Banerjee, Abhijit and - IV: Voter subjects in the “bonus for fast receipt
Rohini Pande. No date. ethnicization of corruption scale used and of driver’s license” treatment and
(greater voter content of vignettes those in the lesson and control
preference for the conditions who receive their license,
party representing - Payment/receipt of a bribe for a how quickly they receive it, whether
her ethnic group) “corrupt” service (e.g. reduction in they take the licensing exam, whether
tax, preferential treatment in court paid above official fees, whether tried
Barr, Abagail and Danila - IV: Country of hearing, speedier admission to a to bribe, whether used an agent, etc.
Serra. 2010. origin hospital)
Three measures:
Bhavnani, Rikhil. 2010. - IV: Holding - Misuse of public office for private - Survey of journalists and politicians
political office economic gain
about politicians and candidates
- Gains/benefits from public office - Index of the economic gain by the
politicians after entering politics,
averaging: “whether the politician
used political office for personal gain,
whether he or his family saw a
significant improvement in their
economic position, whether they
started or expanded a business, and
whether they started of expanded
contracting activity” (19).
- Whether the politician has a criminal
record
Individual corruption level
- Whether subjects are willing to pay a
bribe for a “corrupt” service and how
much
- Whether willing to accept a bribe and
how much
Home country corruption level
- Transparency International CPI
- Estimating changes in wealth among
elected politicians versus those not
elected who ran again in the next
election
Bose, Niloy, Salvatore - DV: Quality of “[W]hen bureaucrats leverage their - Transparency International Corruption
46
Capasso, and Antu Panini public positions to further their own Perceptions Index
Murshid. 2008. infrastructure interests” (1174).
- Corruption: the abuse of public - Grand corruption: Index based on
Bussell, Jennifer. 2012a. - DVs: Timing, office for private gain Government of India Report on the
comprehensivenes - Grand corruption: Corruption in Member of Parliament Local Area
s, and ownership procurement and government Development Scheme
and management contracting
model of - Petty corruption: Corruption in the - Petty corruption: Index based on
eGovernment delivery of public services Transparency International India and
policies Centre for Media Studies Indian
- Undefined Corruption Study (survey of Indian
Chong, Alberto, Ana L. - DV: Vote for citizens)
De La O, Dean Karlan, candidates, - Undefined
and Leonard Wantchekon. turnout - “[P]ercentage of resources mayors
2012. - “[A]ny irregularity associated with spent in a corrupt manner (i.e.
fraud in procurements, diversion of spending where some form of
De Figueiredo, Miguel F. - DV: Vote for public funds, or over-invoicing” irregularity was identified such as
P., F. Daniel Hidalgo, and candidates, (710). over-invoicing, fake receipts, diverting
Yuri Kasahara. 2012. turnout resources, fraud, etc.)” (3).
“The abuse of entrusted power for
Ferraz, Claudio and - DV: Election private gain.” - Convictions for impropriety while in
Frederico Finan. 2008. outcomes government office.
- Corruption: “An act that subverts
Fisman, Raymond and - IVs: Cultural the public good for private or - “Each audit report contains the total
Edward Miguel. 2007. norms, legal particularistic gain” (300). amount of federal funds transferred to
Gerring, John and Strom enforcement the current administration and the
C. Thacker. 2004. - Political corruption: “An act by a amount audited, as well as an itemized
- IVs: Territorial public official (or with the list describing each irregularity. Based
Glaeser, Edward L. and sovereignty acquiescence of a public official) on our readings of the reports, we
Raven E. Saks. 2006. (unitary or that violates legal or social norms codified the irregularities listed into
federal), for private or particularistic gain” those associated with corruption and
composition of the (Ibid.). those that simply represent poor
executive administration” (709-710).
(parliamentary or “Official corruption” – “conflicts of
presidential) interest, fraud, campaign-finance - Accumulation of unpaid parking
violations, and obstruction of violations by diplomats in Manhattan
- IVs: Education, justice” (1053).
income, income - Kaufman, Kraay, and Zoido-Lobaton
inequality, racial “Crimes by public officials for index; Transparency International
fractionalization personal gain (Rose-Ackerman, Corruption Perceptions Index
1975)” (1055).
- DV: Economic - The number of government officials
development convicted for corrupt practices through
the Federal justice department/the
number of Federal corruption
convictions per capita by state.
- “The usual problem with using
conviction rates to measure corruption
is that in corrupt places, the judicial
system is itself corrupt and fewer
people will be charged with corrupt
practices. This problem is mitigated
with focusing on Federal convictions,
47
Golden, Miriam A. and - N/A Though not stated explicitly, the because the Federal judicial system is
Lucio Picci. 2005. basic working definition of relatively isolated from local
corruption here is the misuse of corruption and should treat people
public finances. similarly across space” (1054).
“The difference between the amounts of
Mauro, Paulo. 1995. - DV: investment - Undefined physically existing public
infrastructure (roads, schools,
McMillan, John and Pablo - IVs: opposition - Undefined hospitals, etc.) and the amounts of
Zoido. 2004. parties, the - Operationalized as bribes paid by money cumulatively allocated by
judiciary, the government to create these public
Montinola, Gabriella R. news media the secret police chief to judges, works. Where the difference between
and Robert W. Jackman. politicians, and the news media the two is larger, more money is being
2002. - IVs: Political - Undefined lost to fraud, embezzlement, waste,
competition, and mismanagement; in other words,
Olken, Benjamin A. 2007. economic - Undefined corruption is greater” (37).
competition, - Operationalized as the misuse of - Business International Corruption
inequality, public measures, based on surveys of BI in-
sector wages public funds in building of roads country correspondents responding to
the statement: “the degree to which
- IVs: Government - Undefined business transactions involve
audits, grassroots - Operationalized as bribes paid by corruption or questionable payments”
participation in (684).
monitoring truckers to police, soldiers, and - Secret police chief Vladimiro
weigh station attendants Montesinos Torres’ records of bribes
Olken, Benjamin A. and - IVs: Market “Political and bureaucratic capture, paid
Patrick Barron. 2009. structure, price leakage of funds, and problems in
discrimination the deployment of human and in- - Business International corruption
kind resources, such as staff, scores, Transparency International
Reinikka, Ritva and Jakob N/A (review article) textbooks, and drugs” (360). Corruption Perceptions Index
Svensson. 2006.
- The difference between official project
- Misuse of public office/failure to cost (of building roads) and
perform required tasks while still independent engineers’ estimate of
taking salary costs.
- Observation of payments made by
truckers during trips to an from Ache,
Indonesia.
Public Expenditure Tracking Surveys –
“A public expenditure tracking survey
(PETS) tracks the flow of resources
through these strata [layers of
government bureaucracy], on a sample
survey basis, in order to determine
how much of the originally allocated
resources reach each level” (360).
Frontline Provider Surveys/Quantitative
service delivery survey
- Unannounced visits to
hospitals/schools to evaluate what
48
Reinikka, Ritva and Jakob - IVs: Local - Payment/receipt of bribes for fraction of professionals were at their
Svensson. 2004. community services posts
characteristics - Firm/corporation surveys
- Undefined (“corruption” not used
Shleifer, Andrei and - IV: Market explicitly in the discussion, though - The difference between money
Robert W. Vishny. 1993. structure of the it is referred to in footnotes and in allocated to schools by the Ugandan
supply of further work by this authors citing government and money actually
Treisman, Daniel. 2000. government goods this paper) received
Van Rijckeghem, - DV: Economic - Government corruption: “[T]he -
Caroline and Beatrice efficiency sale by government officials of - Unmeasured
Weder. 2001. government property for private
Wei, Shang-Jin. 2000. - IVs: Religion, gain” (599). - Transparency International Corruption
colonial history, Perceptions Index, Business
economic - The misuse of public office for International index of perceived
development, private gain corruption
import levels,
federalism, - Undefined - International Country Risk Group
democracy corruption scores
- Undefined
- IV: Bureaucratic - Operationalized, in the author’s - Business International index of
wages perceived corruption, International
interpretation of the surveys used, Country Risk Group corruption
- DV: Foreign as “the administration of rules/laws measure, and Transparency
direct investment pertinent to foreign International Corruption Perceptions
firms…weighted by efficiency Index
level as perceived by those who
were surveyed” (3).
49
(Online) Appendix C – Type of Actor and Within Question Non-Response
An additional potential concern related to the use of a perceptions-based question is that
different types of government actors and actors at different levels of government may be more or
less likely to respond to questions about rent-sharing, either due to their varying degrees of
knowledge about corruption or to differing comfort levels related to discussing corruption. I test the
validity of this concern by evaluating response rates of respondent sub-groups to the distribution of
rents question in general, shown in tables C1 and C2 for politicians and bureaucrats, respectively,
and to each version of the question, shown in tables C3-C6.25
In general, respondents at higher levels of government, particularly politicians, were more
likely to respond to this question. This may support the idea that higher-level actors feel that they
know more about the nature of corruption in general or perhaps also that they are less concerned
about discussing corruption than actors at lower levels. Alternatively, it could support an argument
that lower level actors keep more rents than they acknowledge to their superiors and so are
uncomfortable answering this question. With regard to differences across elected and non-elected
officials, bureaucrats at the district and block levels were slightly less likely to answer the question
than politicians at the same level, but village council-level bureaucrats were more likely to respond
than their political counterparts. Thus, there is no strong finding for differences across these different
types of officials.
25 Specifically, I evaluate whether the respondent provided a response to the question of how much
of a bribe a local council president would receive. This was the least likely sub-component of the
question to be skipped by any individual respondent.
50
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