The Flux of Attitudes About Corruption in S. Asia: Interpreting Social Change and Prosocial Attitude Gaps By Wendy Olsen Manchester University, Social Mobility & Labour Markets Research Group. Abstract The main aim of this paper is to set out an argument about corruption and gender. Sociological in nature, my argument does not rest upon functionalist falsehoods, but instead it takes seriously the dynamics of structure, institutions and agency. I apply social theory to the problem of how to solve the corruption problem in S. Asia and particularly in North India and Bangladesh over time. Corruption and hierarchy run parallel with patriarchy in South Asian countries, yet variations of the hierarchical texture, the informal institutions, and the official regulation system are important during the process of social change. Data from both Transparency International and the World Bank on Nepal, India, Bangladesh, Pakistan, Myanmar (was Burma), and Sri Lanka show high levels of corruption and low levels of public accountability. I explore how interlinkages of patriarchal attitudes correspond to, and support, corrupt behaviours, but also how the converse attitudes which are known as “prosocial attitudes” can help to eradicate corrupt behaviours. Cross-sectional differences within India are also examined, given strong secondary data as evidence, to help develop the argument with empirical detail. Measures are available of some psycho-social drivers of corruption and anti-corruption – compliancy on the one hand, and honesty, risk-taking and self-confidence on the other. Gendered patterns in these drivers arise early in childhood but training and workshops could offset corruption by developing a wider appreciation of the prosocial habitus. This paper thus offers a theory-based investigation of the drivers of improvement in the corrupt practices which are evident in the public sector of most S. Asian societies. [Note for the conference: A brief workshop asks participants in the seminar to fill in a short questionnaire and then comment on their norms. A model of this questionnaire is appended and this can be used in your own work, without citation or hesitation.] Key Data Source: WORLD VALUES SURVEY 1981-2008 OFFICIAL AGGREGATE v.20090901, 2009. World Values Survey Association (www.worldvaluessurvey.org). Aggregate File Producer: ASEP/JDS, Madrid.

1. Prosocial Attitudes and
Corruption in S. Asia, Especially
In India and Bangladesh
FEB. 2015
Workshop on Trust and Prosocial
Attitudes in EU and Beyond
Wendy Olsen
Social Mobility and Labour Markets Research Group
University of Manchester

2. Overview ofTalk
 1. Corruption Heavily Dominant in Six S.
Asian Countries
 2.Transparency International’s approach
ignores patriarchy
 Looking for prosocial behav  solutions
 3. Contrasts Within India Show Prosocial
Attitudes Common Among Well Educated
People
 4. Against Simplistic Solutions
 Morphogenesis; retroduction.
 5. Conclusions
2 Project: Gender Norms and Labour Supply
in Comparative Context
The author, Wendy Olsen,
works in social statistics at
the University of
Manchester.
Her writings can be found
online at:
http://staffprofiles.humaniti
es.manchester.ac.uk/Profile
.aspx?Id=Wendy.Olsen
%2&curTab=4
Quick access on
twitter.com as:
@Sandhyamma

3. Gender Norms and Labour Supply in
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3
Regulatory Quality
Lower in S.Asia
http://info.worldbank.org/go
vernance/wgi/index.aspx#ho
me

4. Gender Norms and Labour Supply in
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4
Source authors:
The Worldwide Governance Indicators (WGI) project reports
aggregate and individual governance indicators for 215 economies
over the period 1996–2013, for six dimensions of governance:
Voice and Accountability
Political Stability and Absence ofViolence
Government Effectiveness
Regulatory Quality
Rule of Law
Control of Corruption
These aggregate indicators combine the views of a large number of
enterprise, citizen and expert survey respondents in industrial and
developing countries. They are based on 32 individual data sources
produced by a variety of survey institutes, think tanks, non-
governmental organizations, international organizations, and private
sector firms.
TheWGI are produced by:
Daniel Kaufmann, Natural Resource Governance Institute (NRGI)
and Brookings Institution
Aart Kraay,World Bank Development Research Group
Massimo Mastruzzi,World Bank Institute

5. URL address
<iframe frameborder="0" height="620"
width="940"
src="http://media.transparency.org/maps/cpi2014-
940.html"></iframe>
Gender Norms and Labour Supply in
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5

6. Glimpse of the Literature Review
Della Porta and Vannucci
Gender Norms and Labour Supply in
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6
 Theory of corruption
Moral costs higher/lower
 Resistance to corruption
is a mutable moral
wall.
 Institutionalised
loyalty norms support
corrupt behaviour. These
norms can create a
feedback loop which is
morphostasis.
 The theory offered by
Della Porta and Vannucci
is a sociological theory
 Morphogenesis
 Agency is prominent in
social change.

7. Patriarchal norms
and family loyalty
co-reinforce each
other.
Inequality enhances their
prevalence.
Loyalty serves to help
ensure survival.
Questioning the behaviour
of elders is punished and
thus discouraged.
Compliance is valued in
Asia.
Gender Norms and Labour Supply in
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7
 2.Transparency International’s
approach ignores patriarchy
 Patriarchal structures are reinforced
through the rings of corrupt payments,
as elite money is dominated by elder
males and, in general, elders
 Bangladesh, Nepal, India, Sri Lanka, and
Pakistan

8.  To capture cultural norms, King et al. argue
that we need to use anchoring vignettes
 TheWorldValues Survey has mini-vignettes
 This presumes a latent ‘thing’ which is the
core attitude in question.
 WE CALLTHIS A SOCIAL NORM
 We measure the core attitude in question.
 One Example:The Justifiability of bribery
 (WORLDVALUES SURVEY; EuroSocSurvey)
 No one values corruption; no one in Bangladesh or India
admits to valueing corruption.
8 Gender Norms and Labour Supply in
Comparative Context

9. 2nd
Glimpse of the Literature Review
Empirical Papers - WVS
Gender Norms and Labour Supply in
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9
 Theory of corruption
Moral costs higher/lower
to the cheater
Resistance to corruption is
a mutable moral wall
 Wang-Sheng Lee (IZA
2013)
 20 Eurozone countries
 Microdata 43,300 cases
 “Important to seek
adventures” is an attitude
that mediates the gendered
outcome that one
“can justify bribes & cheating”

10. 3. Contrasts Within India Show Prosocial
Attitudes Common Among Well Educated
People – Comparing Bangladesh / India
Gender Norms and Labour Supply in
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 Attitudes about corruption were analysed in the World
Values Survey. The mean is the norm.
 Corruption is anathema to the culture.
 We combine answers to questions about:
 ‘whether it can be justified to claim government benefits to which
you are not entitled’
 ‘whether it can be justified to avoid a fare on public transport’,
 'whether it can be justified to cheat on taxes if you have a chance’
 ‘whether it can be justified to accept a bribe’

11. Gender Norms and Labour Supply in
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Mean
Justifiability of
Cheating
Standard
Error of
Estimate
Lower
Confidence
Interval Limit
Upper
Confidence
Interval Limit
Chhatisgarh 0.50 0.12 0.26 0.73
Uttar Pradesh 0.51 0.03 0.45 0.57
Madhya Prad. 0.61 0.05 0.52 0.70
Bihar 0.66 0.06 0.54 0.78
Jharkhand 0.84 0.09 0.65 1.02
Bangladesh -0.13 -.14 -.12
. Attitudes about bribery and
cheating in Bangladesh and in 5
states of India (WVS data)

12. World Values Survey: Education & Anti-
Corruption Are Not Linearly Related in India
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13. A stylized fact about India: Regional variations in campaigning against
corruption. Court cases very different; eg. very few in Uttar Pradesh.
CONTROL CORRUPTION
Figure 1: Some Indian states with
high corruption
UPU -0.03 4.91
UPR -0.13 4.91
DelU 0.04 4.96
DelR 4.96
TNU 0.08 5.09
TNR 5.09
HaryU 0.10 5.16
HaryR -0.21 5.2
JhaU 5.2
JhaR 0.16 5.42
RajR 0.05 5.43
RajU 0.30 5.43
KarnU 0.12 5.76
KarnR 0.16 5.76
MPU -0.03 5.84
MPR -0.19 5.84
BihU 0.13 6.95
BihR 0.12 6.95

14. Sources
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 Control: World Values Survey India, 2006
 See http://www.worldvaluessurvey.org/WVSOnline.jsp
 Corruption within India:
www.transparencyinternationalindia.org
 Note: TII Board has no women on it
 This could become illegal; a 2013 law makes all listed
companies have at least one female on their board.

15. The states with high corruption also have
high ‘control’
Gender Norms and Labour Supply in
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 Control
 A factor representing a social norm.
 The norm is that people think they have and
should have control over outcomes in their
lives. It is also called efficacy. The person who
feels efficacious does not believe in luck or fate
as much as others. These ‘feelings’ are not
personal, nor merely psychological. The range
of ‘feelings’ and attitudes is culturally shaped
through socialisation, habitus, doxa and norms.

16. The factor for control in WVS
Gender Norms and Labour Supply in
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 They agree that hard work brings success in the long run.
 They often or sometimes (vs rarely or never) think about
the meaning and purpose of life.
 They disagree that “everything is determined by fate”,
instead saying that “people shape their fate themselves”.
 3 indicators; confirmatory factor analysis.
 We also measured women’s autonomy over household
decision making using the National Family & Health Survey

17. Urban and Rural India : Variations in the
Mean of Several Factors… Not in Corruption
Gender Norms and Labour Supply in
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17
X048 rural
numinstat
e fsp justbrib fegal fcontrol fcomply risktake edyears wealth aufactor ti2005
356010. "IN: Kerala" 0 59 0.38 0.05 -0.08 0.01 -0.05 3.43 11.49 0.764 0.021 2.4
356006. "IN: Gujarat" 1 26 -0.91 -0.12 -0.73 -0.14 -0.22 4.00 4.04 -0.202 -0.010 4.17
356006. "IN: Gujarat" 0 76 -0.84 -0.14 -0.58 0.10 0.22 4.74 7.66 0.785 0.053 4.17
356001. "IN: Andhra Pradesh" 1 70 -0.59 -0.04 -0.06 -0.22 -0.19 4.33 4.56 -0.432 0.057 4.21
356001. "IN: Andhra Pradesh" 0 73 0.17 0.08 -0.02 -0.18 -0.33 2.72 5.49 0.611 -0.073 4.21
356012. "IN: Maharashtra" 1 71 -0.27 0.27 0.01 -0.11 -0.17 4.77 3.39 -0.464 0.015 4.33
356012. "IN: Maharashtra" 0 130 0.10 0.85 -0.10 -0.02 -0.15 4.75 7.77 0.786 -0.013 4.33
356004. "IN: Chhatisgarh" 0 33 -0.73 0.55 -0.01 -0.18 -0.22 2.80 5.42 0.328 -0.120 4.45
356004. "IN: Chhatisgarh" 1 11 -1.027 -0.107 4.45
356014. "IN: Punjab" 0 28 -0.22 0.41 0.15 -0.04 -0.04 3.43 8.50 1.089 -0.034 4.59
356014. "IN: Punjab" 1 25 -0.04 0.31 0.04 -0.01 0.03 3.18 9.36 0.366 -0.099 4.59
356018. "IN: West Bengal " 1 38 0.38 0.49 0.06 -0.24 -0.31 2.55 9.32 -0.833 -0.043 4.61
356018. "IN: West Bengal " 0 117 0.44 0.46 -0.04 -0.22 -0.38 3.04 11.46 0.591 -0.103 4.61
356013. "IN: Orrisa" 0 22 -0.17 0.19 0.23 0.00 -0.10 4.18 8.55 0.305 -0.113 4.75
356013. "IN: Orrisa" 1 53 0.15 -0.08 -0.08 -0.06 0.13 3.96 6.64 -0.840 -0.052 4.75
356017. "IN: Uttar Pradesh " 0 202 -0.30 0.56 -0.05 -0.03 -0.15 3.98 6.18 0.691 -0.051 4.91
356017. "IN: Uttar Pradesh " 1 99 -0.17 0.41 -0.04 -0.13 -0.19 3.57 5.31 -0.718 -0.093 4.91
356005. "IN: Delhi" 0 37 -0.13 0.25 0.20 0.04 0.15 3.74 10.84 1.018 -0.003 4.96
356005. "IN: Delhi" 1 1 0.652 -0.012 4.96
356016. "IN: Tamil Nadu " 0 160 0.23 0.89 0.29 0.08 0.17 4.86 10.76 0.430 0.128 5.09
356016. "IN: Tamil Nadu " 1 5 -0.470 0.109 5.09
356007. "IN: Haryana" 0 44 0.31 0.42 0.17 0.10 0.34 3.09 10.66 0.929 0.024 5.16
356008. "IN: Jharkhand" 1 38 -0.74 0.90 -0.27 -0.21 -0.20 3.60 1.37 -1.120 0.034 5.2
356008. "IN: Jharkhand" 0 14 0.506 -0.093 5.2
356002. "IN: Assam" 0 52 1.11 -0.03 -0.11 0.16 0.10 3.98 14.56 0.383 -0.099 5.42
356015. "IN: Rajasthan" 1 47 0.29 0.25 -0.11 0.05 0.34 3.42 2.28 -0.672 -0.080 5.43
356015. "IN: Rajasthan" 0 65 0.30 0.14 0.19 0.30 0.40 4.49 4.02 0.877 -0.043 5.43
356009. "IN: Krnataka" 0 70 0.13 0.29 0.32 0.12 0.03 3.95 5.53 0.483 -0.053 5.76
356009. "IN: Krnataka" 1 33 0.34 0.21 0.21 0.16 0.18 3.93 8.61 -0.554 -0.088 5.76
356011. "IN: Madhya Pradesh" 0 38 -0.02 0.37 0.19 -0.03 -0.19 3.97 7.89 0.747 -0.009 5.84
356011. "IN: Madhya Pradesh" 1 66 0.24 0.75 -0.39 -0.19 -0.41 3.91 3.15 -0.939 -0.031 5.84
356003. "IN: Bihar " 0 140 0.09 0.81 0.15 0.13 0.17 4.55 7.20 0.294 -0.104 6.95
356003. "IN: Bihar " 1 57 0.21 0.28 0.26 0.12 0.20 4.86 3.95 -0.750 0.026 6.95

18. India : Variations in the Mean of Several
Factors… Higher Corruption…
Gender Norms and Labour Supply in
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18
Fsp Justbrib fegal fcontrol fcomply risktake ti2005
356005. "IN: Delhi" 4.96
356016. "IN: Tamil Nadu " 0.23 0.89 0.29 0.08 0.17 4.86 5.09
356016. "IN: Tamil Nadu " 5.09
356007. "IN: Haryana" 0.31 0.42 0.17 0.10 0.34 3.09 5.16
356008. "IN: Jharkhand" -0.74 0.90 -0.27 -0.21 -0.20 3.60 5.2
356008. "IN: Jharkhand" 5.2
356002. "IN: Assam" 1.11 -0.03 -0.11 0.16 0.10 3.98 5.42
356015. "IN: Rajasthan" 0.29 0.25 -0.11 0.05 0.34 3.42 5.43
356015. "IN: Rajasthan" 0.30 0.14 0.19 0.30 0.40 4.49 5.43
356009. "IN: Krnataka" 0.13 0.29 0.32 0.12 0.03 3.95 5.76
356009. "IN: Krnataka" 0.34 0.21 0.21 0.16 0.18 3.93 5.76
356011. "IN: Madhya Pradesh" -0.02 0.37 0.19 -0.03 -0.19 3.97 5.84
356011. "IN: Madhya Pradesh" 0.24 0.75 -0.39 -0.19 -0.41 3.91 5.84
356003. "IN: Bihar " 0.09 0.81 0.15 0.13 0.17 4.55 6.95
356003. "IN: Bihar " 0.21 0.28 0.26 0.12 0.20 4.86 6.95

19. Control is correlated with compliance
Gender Norms and Labour Supply in
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 Those who are compliant (behave, follow tradition, and
being helpful to the people nearby) are also relatively
tending to feel that they can control outcomes. On the
other hand there is a contrasting group somewhere who
are not compliant. These also feel that fate rules and
they can’t control outcomes.
 WORLD VALUES SURVEY 1981-2008 OFFICIAL AGGREGATE
v.20090901, 2009. World Values Survey Association
(www.worldvaluessurvey.org). Aggregate File Producer: ASEP/JDS,
Madrid.

20. 3. Against Simplistic Solutions
Morphogenesis; retroduction.
Both countries
are high on
corruption, low
on transparency.
Relative to Italy
and UK,
however,
Bangladesh &
India have very
strong honesty
Thanks to
Priyanka Vyas,
who made our
maps.
Within India, high
levels of everyday
corruption affect
those living ‘Below
the Poverty Line’,
TI study, 2005 and
2008

21. A humanist
agenda:
 Key research question:
 Could strong people act as agents to
promote the reduction of corruption by
challenging those who practice
informal corruption? They would have
to refuse to collude with informal
norms,
 Which through being informal,
 Are enforced with violence and strong
bullying.
 There is a class challenge here, too.
 Agency: we need prosocial traits
to challenge a social system that
is doing harm.
21 Gender Norms and Labour Supply in
Comparative Context
One has to encourage the
prosocial attitudes as
substantive values.
Challenging corruption is a
strategic capability.
It is necessary as an
enabling factor for other
functionings.

22. Substantive Conclusions
Gender Norms and Labour Supply in
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22
 The pattern of disapproval of cheating the public sector, or
paying bribes, was strong universal disapproval in
Bangladesh, and nearly so in India.
 Transparency International ranks both as highly corrupt in practice.
 India had high rates of disapproval of cheating – higher than
in EU.
 Those who live in Kerala have high education, high GSP per
capita, and low corruption. Nearly everywhere else in India,
high corruption affects poor people badly.
 Control and compliance are co-correlated, and they do not,
in themselves, presently create a basis for anticorruption.
 Belief in fate is however declining and agency is possible.

23. References
Gender Norms and Labour Supply in
Comparative Context
23
Borsboom, Denny, Gideon J. Mellenbergh, and Jaap van Heerden (2003), The Theoretical Status
of Latent Variables, Psychological Review, 110:2, 203–219, DOI 10.1037/0033-295X.
Della Porta, Donnatella, and Alberto Vannucci (2004*) The Hidden Order of Corruption: An
Institutional Approach, London: Ashgate.
Della Porta, D., and A. Vannucci(2005), “Corruption as a Normative System”, CIES – ISCTE
conference paper, May. URL http://home.iscte-iul.pt/~ansmd/CC-DellaPorta.pdf, Accessed
Dec. 2014.
Farah Deeba Chowdhury (2013) Women’s Political Participation in Bangladesh: An Empirical Study,
UPL Monograph Series, Dhaka: The University Press Ltd.
Kabeer, Naila, Lopita Huq, and Simeen Mahmud (2013) Diverging Stories Of “Missing Women”
In South Asia : Is Son Preference Weakening In Bangladesh? Feminist Economics,
http://dx.doi.org/10.1080/13545701.2013.857423, 1-26.
Khattak, Saba Gul, Kiran Habib, and Foqia Sadiq Khan (2008) Women and Human Security in South
Asia: The Cases of Bangladesh and Pakistan, Dhaka: The University Press Ltd.
King, G., And J. Wand (2007), “Comparing Incomparable Survey Responses: Evaluating and
Selecting Anchoring Vignettes”, Political Analysis, 15:46-66.
Lee, Wang-Sheng, and Cahit Guven (2013), Engaging in Corruption: The Influence of Cultural Values
and Contagion Effects at the Micro Level, IZA Working Paper No. 7685.
Parboteea et al (2005), “Does National Culture Affect Willingness to Justify Ethically Suspect
Behaviours?” , IntlJournCrossCulturalManagement, 5:2, 123-138.
Uberoi, P., ed., (1998*) Family, Kinship and Marriage in India, Oxford in India Reading,s. Delhi:
OUP.

24. Acknowledgements
Gender Norms and Labour Supply in
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24
 Thank you to Mr. Nathan Khadaroo, Research Assistant; Nik
Loynes, Research Associate; Prof. Simeen Mahmud, BRAC Institute
for Government and Development, Dhaka; and Prof. Amaresh
Dubey, JNU, Centre for the Study of Regional Development, Delhi
and Indian Institute for Dalit Studies. This research was funded by
the ESRC DFID Poverty Alleviation funds as a research grant 2014-
2017.
 Wendy Olsen
 Reader in Socio-Economics
 Social Statistics
 University of Manchester
 Manchester M13 9PL
 UK
 0044 161 275 3043
 EMAIL wendy.olsen@manchester.ac.uk