134 interesting to see whether similar findings to those reported below hold for lower-level officials. The Riots Data We use two separate sources of riots data, which we will call Riots-A and Riots-B. Riots-A: Our main source of riots data is the annual Government of India publication Crime in India, which provides yearly data on the number of riots per 100,000 population for each Indian state. This data covers the same years as Potter‟s transfer frequency data.The all-India average number of riots per 100,000 people increased somewhat, from 10.4 in 1976 to 13.3 in 1985, with a peak of 16.3 in 1981. The total number of riots recorded varied from a low of 63,675 in 1976 (which was unusually low) to a high of 110,361 in 1981. Given the large numbers of riots reported, this data probably does not primarily measure large-scale Hindu- Muslim or inter-caste riots. 19 Instead, most of these “riots” 17 Though reports of corruption within the IAS are not hard to find, the the-ory does not depend on officials literally demanding bribes. Officials may face a choice between acting impartially or attempting to gain protection from transfers by aligning themselves with some locally powerful faction. One possible (loose) in-terpretation of the model is that one faction‟s willingness to collude with an official in this way can depend on how vulnerable faction members are to retaliation in other games. 18 A “riot” is defined as five or more people who use violence or the threat of violence against others, and therefore includes intergroup conflict as well as political violence. 19 On average, only(!) a few hundred large Hindu-Muslim riots occur each year Page 33 are probably fairly minor incidents involving small groups. This makes the data quite suitable as a general measure of social and political conflict. This data has been used by Kohli (1990), among others, as a measure of political conflict and instability. Riots-B: Krishna (1985) reports the proportion of districts in each state affected by Hindu-Muslim riots between 1961 and 1970. While this data does not cover the same time period as Potter‟s transfer data, it is useful because it will not be distorted by the presence of “hotspots” in several states (it measures the proportion of districts in which some violence occurred, but not the intensity or frequency of the violence). Control Variables A number of other factors may affect corruption and/or transfer fre-quency. The variable most robustly associated with corruption in cross-country regressions is per-capita income. A second promising control variable is newspaper readership, which may affect officials‟ bargaining power (literate and informed citizens are more aware of their rights), as well as the nature of democratic politics. Besley et al. (2002) show that governments are more responsive where newspaper circulation is higher. Thirdly, inequality among the clients of a bureaucracy may affect administrative behavior. For example, local governments may be more prone to “capture” by affluent groups if affluent voters are better informed than poor voters (Bardhan and Mookherjee 1998) ; this asym-metry may be more pronounced if inequality is severe. Sample The 19 IAS cadres included in the Riots-A sample are Assam-Meghalaya, Andhra Pradesh, Bihar, Gujarat, Haryana, Himachal Pradesh, Jammu (eg., Brass 1994:240). 20 The primary source cited is Government of India, Ministry of Home Affairs. 21 Regressions using literacy instead of newspaper circulation produced similar results. Page 34 and Kashmir, Karnataka, Kerala, Madhya Pradesh, Maharashtra, Manipur-Tripura, Nagaland, Orissa, Punjab, Rajasthan, Tamil Nadu, Uttar Pradesh, and West Bengal. Union territories are omitted. This sample corresponds exactly to those states with populations over 750,000 in 1981. For regressions involving the Riots-B variable, Manipur-Tripura, Nagaland, and Himachal Pradesh are omitted due to a lack of data. The resulting sample of 16 contains exactly those states with popula-tions over 5 million in 1981. Results We have considered a number of possible hypotheses concerning the relationships between social integration, political instability, and trans-fer frequency. To summarize the predictions: several different
135 theories might explain why social integration would reduce corruption. Of these, most would seem likely to predict a negative correlation between social integration and transfer frequency (eg., Hypotheses 1, 2 and 3). It is harder to tell stories which, like Hypothesis 4, predict a positive rela-tionship. Thus, examining the relationship between social integration and transfer frequency enables us to see how social integration affects the level of corruption. Table I investigates the cross-sectional relationship between social integration (proxied by a low level of riots) and transfer frequency. Overall, it appears that, using either measure of riotousness, in states with a low level of riots, transfer frequency is higher. The explanation 33 Page 35 Table I Determinants of A vera ge Transfer Frequency (λ)Crosssection (OLS, const ants not shown) (1) (2) (3) (4) (5) (6) (7) (8) (9) l n ( R iots-A ) -0.061 -0.034 -0.062 -0.035 -0.036 (2.22) (2.01) (2.16) (2.14) (1.83) R iots-B -0.280 -0.200 -0.226 (4.27) (2.34) (2.52) l n ( I ncome ) -0.157 -0.152 -0.118 (1.16) (1.16)
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justified by recourse to some princ
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er;ubah, [bukan/tidak] hakim, maupu
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suatu courtroom [yang] menentukan d
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pelatihan dewan pejabat pemberlaku
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and compromised in a corrupt and in
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corruptor (as we have defined corru
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to, a large corporation who steal f
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including the moral characters of t
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disibukkan dengan suatu tindakan ko
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penawaran dengan demikian digangsir
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corruption — although it might se
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yang ia percaya untuk;menjadi [hak/
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case they would occasionally make e
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Indicates the frequency of attempts
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Population Public officials . Not e
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4. Corruption expectations Populati
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. that it is a successful practice
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as corruption within international
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wrath is seen as directed at our ow
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Publisher: Prentice Hall Copyright:
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studies, for example, Watergate. In
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Corruption is widely recognised to
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Developing Cultural Criminology: Th
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Paradigms of Power & Persuasion, 1-
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phenomenon, is it not plausible tha
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Definition of Institutional Corrupt
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The third and final thesis to be di
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A final point about social groups.
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espect of the moral weight to be at
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institutional actor in this setting
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elationship can be overcome or even
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Related research VI Page 1 The Role
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esources are embezzled from the sec
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sentiments and when the rule of sys
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trade liberalization; (6) liberaliz
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president the power to enact decree
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that create deprivation face little
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The debate about the composition of