Factor Analysis of Attitudes to Corruption in India Bangladesh: Methods of workshops and use of World Values Survey In this research, funded by ESRC DFID Poverty Alleviation grant on Gender Norms: Comparative research on India & Bangladesh, I look at attitudes about bribes and corrupt practices. I used the World Values Survey question wording. Here the respondent has to answer whether they think it is never, sometimes, or always justifiable to take a bribe. The questionnaire is available on my facebook Group site, Integrated Mixed Methods Network. The slides show a link to my twitter account. @Sandhyamma You can also look at my writing on attitudes to gender roles (online links). The issue is really about methods. Should workshops spread the discussion about attitudes among lay audiences? or is factor analysis a method only for specialists, for statisticians, for the ivory tower? I think the former. I hope you like the slide show!

1. Attitudes About Corruption In
India and Bangladesh: A Method
Combining Measurement With
Impact
(DHAKA DECEMBER 2014)
Conference on Political Economy,
Accountability and Governance
Wendy Olsen University of Manchester

2. Overview of Talk
 1. Approaches to measuring
attitudes
 Norms, roles, attitudes, beliefs,
desires
 2. Transparency International’s
approach
 3. Attitudes : a measurement error
approach
 Introduction
 The SEM approach (World Values
Survey)
 Findings for Bangladesh Vs. India
 4.
 Linear regression results.
 5. Conclusions 2 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.human
ities.manchester.ac.uk/P
rofile.aspx?Id=Wendy.Ol
sen%2&curTab=4
Quick access on
twitter.com as:
@Sandhyamma

3. General
approaches to
measuring
attitudes
Three Broad Schools of
Thought
 Norms, roles, attitudes, beliefs, desires
 King et al. argue that we need to use
anchoring vignettes
 This presumes a latent ‘thing’ which is the
core attitude in question.
 WE CALL THIS A SOCIAL NORM
KING errs toward individualist wording
Empirical reality, for instance, is one of the phrases they
use
 the core attitude in question.
3 Gender Norms and Labour Supply in
Comparative Context

4. A stylized fact about India: Regional variations occur in the
women’s labour-force participation rate.
INDIA EPW 2012
Figure 1: State
Variations in
FLFP

5. Questions about corruption in India and in Bangladesh: Is
there a latent factor of corruption which we could study
coherently?
Key Findings:
Both countries
are high on
corruption, low
on transparency.
Relative to Italy
and UK,
however,
Bangladesh
has very strong
honesty norms
Thanks to
Priyanka Vyas,
who made this
map.
Significant
differences
between states in
the attitude about
the justifiability of
corruption

6. Variations in Patriarchy, and would they
matter for attitudes to corrupt practices?
 India WVS Sample 76% Hindu
 Andre Beteille, in Uberoi, Ed., Family, Kinship and
Marriage in India,
Gender Norms and Labour Supply in
Comparative Context
6
“The family plays a crucial part in the socialization of its
children, ... Indians of all classes have a markedly
conservative attitude toward both marriage and
parenthood”... pg 438.
 Perhaps this is too universalistic.
 Bangladesh WVS Sample 91% Muslim
 Case study of a rural informal worker from Comilla
 General points made by Farah Deeba Chowdhury,
Women’s Political Participation in Bangladesh: An
Empirical Study, 2013 (The University Press, Dhaka)

7. Three Broad
Schools of
Thought
 Norms, roles, and attitudes
 1) idealised psychometric approaches,
e.g. Schwartz, see the World Values
Survey
 2) realist approach, capabilities school
and Bourdieuvian ‘domains’ with habitus
and doxa in each domain, creating
tensions.
 Therefore we can test for class-based or
ethnic-based differences of the
measurement model parameters (group
test)
 These would suggest that there are
differences in the shape of the distribution of
the attitudes surrounding the general social
norm, by class.
 3) GAD integrates feminism with the
Bourdieuvian class-contrast approach.
 GENDER AND DEVELOPMENT:
 All WOMEN are not alike.
 All PEOPLE do not agree.
7 Gender Norms and Labour Supply in
Comparative Context
1) Inadequate
2) 2+3 agreeable

8. Empirical Literature Review
Della Porta and Vannucci Empirical Papers - WVS
 Theory of corruption
Gender Norms and Labour Supply in
Comparative Context
8
Moral costs higher/lower
Resistance to corruption is
a mutable moral wall
Institutionalised loyalty
norms support corrupt
behaviour and can create a
feedback loop
Transparency International:
Accountability and
transparency are the
opposite of corruption
(they form barriers to it)
 Wang-Sheng Lee (IZA
2013)
 20 Eurozone countries
 Microdata 43,300 cases
 Important to seek
adventures mediates the
gendered ‘can justify bribe’
outcome
 Parboteea et al (IJCCM
2005)
 WVS data shows GB,
France, Italy, Hungary, and
Germany all higher ‘can
justify bribe’ than India **
(no data Bangladesh)

9. Comparing Bangladesh / India
 Attitudes about corruption were analysed repeatedly
in the World Values Survey,
 Attitudes to corruption will differ depending on both
one’s hopes and ethics, and one’s constraining or
enabling economic factors.
 We can combine answers to questions about:
Gender Norms and Labour Supply in
Comparative Context
9
 ‘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’

10. Muthen & Muthen’s MPLUS software
The factor
can be an
independent
variable, or a
dependent
variable.
 Useful, but so is STATA now. I used MPLUS.
 The results are similar to a classical scale (adding up
10’s).
 SPSS can also do a simple factor analysis.
Gender Norms and Labour Supply in
Comparative Context
10

11. THE SUM OF FOUR
SCALES
1 Can Justify Bribe,
Etc.
2002, 2006 WVS
Kernel density estimate
Gender Norms and Labour Supply in
Comparative Context
 World Values Survey
11
0
.02 .04 .06 .08
Density
0 10 20 30 40
cheatjust
kernel = epanechnikov, bandwidth = 2.1529
.2 .4 .6
0
Kernel density estimate
5 10 15 20 25 30
cheatjust
kernel = epanechnikov, bandwidth = 0.4767
Figure 3: Justifiability of
Figure 2: Justifiability of Cheating in India
Cheating in Bangladesh

12. These are strongly
correlated
Scale of 1-10 for each
variable
You can create a
classical scale
 Four Variables Used in a Factor
Analysis for Bangladesh World Values
Survey 2002
 And India WVS 2006
 …to estimate the social norm that
corruption can be justified, measured
by these 4 indicators:
 You can justify taking a bribe
 You can justify cheating on tax
 You can justify cheating on benefits
from government
 You can justify cheating on a
transport cost
 Does not vary much by class or
education.
Gender Norms and Labour Supply in
Comparative Context
12
 The difference by Country is much larger,
with Country giving an R-squared of 23%
for the Factor as Dependent Variable

13. Strong Cross
Correlations
Cheatbenju
st
cheatbusju
st
0.6794
cheattaxju
st
0.6423
0.7344
bribejust
0.5751
0.6756
0.7623
The mean of a latent factor for attitude to corruption was .42 in
India, {.39, .45 is the confidence interval at 95%}, but in
Bangladesh, the mean was -0.13 with a narrow confidence
interval, {-0.14 to-0.12}.
The weighted cases are brought down to 1500 per country, giving
these proportions:
Students 12%
Rural 22%
Female 44%
Educ years estimated 7.8 years
The subjective social class averages 2.65, on a scale 1-5, with
5=Upper Class. Thus the average is between working and middle
class. This had no correlation with attitude to bribery.
Gender Norms and Labour Supply in
Comparative Context
 Findings
76% Hindu in India
7% Hindu in B’desh
915Muslim in Bangladesh
13

14. BANGLADESH 2001 INDIA 2006
Gender Norms and Labour Supply in
Comparative Context
14
Banglades
h
Mean
Justifiabili
ty of
Cheating
Standard
Error of
Estimate
Lower
Confidenc
e Interval
Limit
Upper
Confidenc
e Interval
Limit N
Faridpur -0.20 0.00 . . 56
Kishorega
n -0.20 0.00 . . etc.
Coxes
Bazaar -0.20 0.00 . .
BrahmanB
aria -0.20 0.00 . .
Habiganj -0.20 0.00 . .
Chudanga -0.20 0.00 . .
Nator -0.20 0.00 . .
Mymensin
gh -0.19 0.01 -0.20 -0.17
Sylhet -0.18 0.01 -0.21 -0.16
Sirajganj -0.17 0.02 -0.20 -0.14
Jhenaidah -0.16 0.02 -0.20 -0.11
Chittagon
g -0.14 0.02 -0.18 -0.10
Rangpur -0.13 0.03 -0.18 -0.08
Comilla -0.12 0.03 -0.17 -0.07
Feni -0.11 0.04 -0.19 -0.04
Dhaka -0.08 0.02 -0.12 -0.04
Barisal -0.07 0.03 -0.12 -0.01
Rajshahi -0.05 0.05 -0.14 0.04
Tangail -0.04 0.04 -0.11 0.04
Sherpur -0.02 0.05 -0.13 0.09
Gaibandh
a 0.08 0.05 -0.02 0.18
India
Mean
Justifiabilit
y of
Cheating
Standard
Error of
Estimate
Lower
Confidenc
e Interval
Limit
Upper
Confidenc
e Interval
Limit
Coefficient
of
Variation N
Gujarat -0.14 0.01 -0.17 -0.11 -11%
Assam -0.03 0.05 -0.12 0.06 -167%
Orissa 0.00 0.05 -0.10 0.09 -1550%
AP 0.02 0.03 -0.04 0.09 140%
Kerala 0.05 0.05 -0.06 0.15 111%
Rajasthan 0.18 0.04 0.10 0.26 22%
Karnataka 0.26 0.05 0.17 0.36 18%
Delhi 0.27 0.08 0.11 0.43 31%
Punjab 0.36 0.09 0.19 0.53 24%
Haryana 0.42 0.08 0.26 0.59 20%
West
Bengal 0.47 0.04 0.39 0.54 8%
Chhatisgar
h 0.50 0.12 0.26 0.73 24%
UP 0.51 0.03 0.45 0.57 6%
MP 0.61 0.05 0.52 0.70 8%
Maharasht
ra 0.65 0.06 0.53 0.77 9%
Bihar 0.66 0.06 0.54 0.78 9%
Jharkhand 0.84 0.09 0.65 1.02 11%
TamilNadu 0.89 0.04 0.82 0.96 4%

15. In gender norms,
education is
strongly
associated with
more egalitarian
norms.
In attitudes to the
justifiability of
bribery and
cheating, however,
education and
class were not key
explanatory
factors.
 SEM approach
 A. Created a factor for traditional vs.
egalitarian (modern) norms existing at
social level about women’s appropriate
roles.
 DHS variables
 Bangladesh 2007 and 2011
 India NFHS 2005/6
 There were strong state-wise differences.
The lower-income states have more
traditional norms, excepting those with the
high Women’s Labour Force Participation.
15 Gender Norms and Labour Supply in
Comparative Context

16. Figure 4: Summary of Justifiability of Bribery & Cheating
Gender Norms and Labour Supply in
Comparative Context
16
HIGHER GNI
PER CAPITA
LOWER GNI
PER CAPITA
MORE
JUSTIFABLE
TN UP
MP
JH
BIHAR
LESS
JUSTIFIABLE
AP
Delhi
Kerala

17. Hypotheses of This Paper

Locality differences in corruption index average values reflect a mixture of factors.
Seeking harmonised and refined measurement is not the only aim.
It is also important to respond to differences in the causes of change in norms.
We will in future measure changes in the real constraining or enabling factors, and
change in the norms over time.
ACCEPTING THAT BRIBERY CAN BE JUSTIFIED:
At the moment our summary is: females less than males
No class difference overall; no education difference overall;
Bangladesh residents less accepting (totally against it);
Indian 7% say it definitely can be justified, and 5% don’t know.
The more modernised states 17 have LESS ACCEPTANCE OF JUSTIFIABILITY.

18. How the Scale
Works
India
Higher values = those
who say it can be justified
to pay a bribe or
otherwise cheat the
government
Figure 5: Latent Factor Using Four Indicators for the
Justifiability of Bribery & Cheating
Kernel density estimate
Gender Norms and Labour Supply in
Comparative Context
18
1
1.5
.5
0
-.5 0 .5 1 1.5 2
f1
kernel = epanechnikov, bandwidth = 0.1283

19. How the Scale
Works
India
Higher values = those
who say it can be justified
to pay a bribe or
otherwise cheat the
government
Bangladesh
Great homogeneity
Kernel density estimate
Kernel density estimate
Gender Norms and Labour Supply in
Comparative Context
19
1
1.5
.5
0
Density
-.5 0 .5 1 1.5 2
f1
kernel = epanechnikov, bandwidth = 0.1283
0 2 4 6
Density
-.5 0 .5 1 1.5
f1
kernel = epanechnikov, bandwidth = 0.0480
% of
the
Res
pon
dent
s
Is
On
The
Verti
cal
Scal
e
Figures 6 & 7: Justifiability of Bribery & Cheating in India & Bangladesh, 2002,
2006

20. Bangladesh
Gender Norms and Labour Supply in
Comparative Context
Banglade
sh
20
Mean
Justifiabi
lity of
Cheating
Standard
Error of
Estimate
Lower
Confiden
ce
Interval
Limit
Upper
Confiden
ce
Interval
Limit N
Faridpur -0.20 0.00 . . 56
Kishoregan -0.20 0.00 . . etc.
Coxes Bazaar -0.20 0.00 . .
BrahmanBaria -0.20 0.00 . .
Habiganj -0.20 0.00 . .
Chudanga -0.20 0.00 . .
Nator -0.20 0.00 . .
Mymensingh -0.19 0.01 -0.20 -0.17
Sylhet -0.18 0.01 -0.21 -0.16
Sirajganj -0.17 0.02 -0.20 -0.14
Jhenaidah -0.16 0.02 -0.20 -0.11
Chittagong -0.14 0.02 -0.18 -0.10
Rangpur -0.13 0.03 -0.18 -0.08
Comilla -0.12 0.03 -0.17 -0.07
Feni -0.11 0.04 -0.19 -0.04
Dhaka -0.08 0.02 -0.12 -0.04
Barisal -0.07 0.03 -0.12 -0.01
Rajshahi -0.05 0.05 -0.14 0.04
Tangail -0.04 0.04 -0.11 0.04
Sherpur -0.02 0.05 -0.13 0.09
Gaibandha 0.08 0.05 -0.02 0.18

21. India
Gender Norms and Labour Supply in
Comparative Context
21

India
Mean
Justifiabi
lity of
Cheating
Standard
Error of
Estimate
Lower
Confiden
ce
Interval
Limit
Upper
Confiden
ce
Interval
Limit
Coefficie
nt of
Variation N
Gujarat -0.14 0.01 -0.17 -0.11 -11%
Assam -0.03 0.05 -0.12 0.06 -167%
Orissa 0.00 0.05 -0.10 0.09 -1550%
AP 0.02 0.03 -0.04 0.09 140%
Kerala 0.05 0.05 -0.06 0.15 111%
Rajasthan 0.18 0.04 0.10 0.26 22%
Karnataka 0.26 0.05 0.17 0.36 18%
Delhi 0.27 0.08 0.11 0.43 31%
Punjab 0.36 0.09 0.19 0.53 24%
Haryana 0.42 0.08 0.26 0.59 20%
West Bengal 0.47 0.04 0.39 0.54 8%
Chhatisgarh 0.50 0.12 0.26 0.73 24%
UP 0.51 0.03 0.45 0.57 6%
MP 0.61 0.05 0.52 0.70 8%
Maharashtra 0.65 0.06 0.53 0.77 9%
Bihar 0.66 0.06 0.54 0.78 9%
Jharkhand 0.84 0.09 0.65 1.02 11%
TamilNadu 0.89 0.04 0.82 0.96 4%

22. Labour Supply: Differences in the Degree
or Even Absence of Shrinkage of Female LFP
Total Female Rural LFPR 15 to 64 by LFP6 Declining
State* 19831993-94 2004-05 2011-12
Andhra Pradesh 76.0 79.7 72.5 65.6
Arunachal Pradesh 100.0 74.0 71.3 64.2
Goa 67.3 56.7 35.5 42.6
Gujrat 75.0 75.1 76.5 62.6
Haryana 88.2 87.3 75.5 63.1
Himachal Pradesh 84.7 88.7 84.0 78.6
Jammu & Kashmir 82.9 89.6 59.0 55.2
Karnataka 68.4 73.6 77.4 55.0
Kerala 55.6 47.9 50.6 45.7
Maharastra 78.3 79.3 73.0 60.3
Manipur 64.0 60.8 61.9 54.7
Meghalaya 74.1 79.8 78.3 70.3
Mizoram 85.3 67.7 73.9 75.3
Nagaland NA 73.1 79.4 68.6
Punjab 86.9 80.3 74.4 60.4
Tamil Nadu 76.6 77.3 77.1 59.8
Pondicheri 68.6 70.1 60.6 36.5
Total (both those going UP and DOWN) 68.8 71.2 70.7 64.8
Total Female Rural LFPR 15 to 64 by
LFP6 States Showing a Rise
State* 19831993-94 2004-05 2011-12
Assam 52.0 55.9 59.9 66.6
Bihar 61.2 59.7 62.7 63.4
Madhya Pradesh 76.2 80.3 79.0 77.9
Orissa 58.2 63.1 67.6 60.2
Rajasthan 77.0 86.8 84.5 75.5
Sikkim 61.7 52.8 61.7 73.8
Tripura 17.1 24.2 23.0 54.3
Uttar Pradesh 61.6 64.6 66.1 65.2
West Bengal 60.6 70.1 71.6 71.9
Pondicheri 68.6 70.1 60.6 36.5
Total 68.8 71.2 70.7 64.8

23. Regression, T-Tests, Kolmogorov-Smirnov
Tests Show…
 Linear regression Number of obs = 3501
 F( 4, 3496) = 315.96
 Prob > F = 0.0000
 R-squared = 0.230
Gender Norms and Labour Supply in
Comparative Context
23

 Dep Var: Latent Justifiability of Taking Bribe or Cheating
 f1 | Coef. Std. Err. t P>|t| [95% Conf. Interval]
 rural | -.1107588 .0243446 -4.55 0.000 -.1584899 -.0630276
 female | -.0546155 .0172899 -3.16 0.002 -.0885149 -.0207161
 hindu | -.0991072 .0269871 -3.67 0.000 -.1520193 -.0461951
 country | .6442233 .0251678 25.60 0.000 .5948782 .6935683
 _cons | -.0873473 .0103564 -8.43 0.000 -.1076526 -.067042
 ------------------------------------------------------------------------------

24. 3 GROUPS
‘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’
 Briefly classify your own attitudes to
corruption by answering the four
questions on a scale of 1 to 10.
 1= CAN NEVER JUSTIFY IT..
 10 = CAN ALWAYS JUSTIFY IT.
 Add up your score to make a
Gender Norms and Labour Supply in
Comparative Context
 Workshop Activity
24
CLASSICAL SCALE
 Factor analysis with MPLUS is similar

25. Gender Relevance
Women in Bangladesh
and in India are expected
(more than men) to
conform, be submissive,
… to be silent
… to be appreciative of
what causes others to do
things which offend the
woman’s own honour
… to not defend her
honour, yet work toward it
 PURPOSES OF THE WORKSHOPS
 DIVERSITY-REALISATION
 GROWTH OF TOLERANCE
 AWARENESS OF THE NEED TO
DISCUSS THIS CRUCIAL ISSUE
IMPROVED AWARENESS OF WHAT
THE ISSUES ARE
 The constraining factors
 The things that enable anti-corruption
 Whether corruption or bribery can be
Gender Norms and Labour Supply in
Comparative Context
 SENSITISATION
25
good
 How we deal with disagreements
 Dealing with the issue constructively
 Alternatives to violence over this issue

26. RESOLUTIONS
We aim to develop our
ideas scientifically
We aim also to
disseminate good ideas
as we go along in the
research
This is known as ‘impact’
(Not the same as
Participatory research.)
 Any factor analysis can be followed up
by workshops that involve
stakeholders such as policymakers
and representatives of business in a
dialogue. KETSO, post-it notes, or
simple tape-recorded focus groups
can be used to gather up differences
of opinion.
 A PREVIOUS TRIAL WAS FELT A
SUCCESS
 Profound differences of opinion? No–
each norm has a surrounding aura of
disagreement about competing
ROLES
Gender Norms and Labour Supply in
Comparative Context
26

27. Substantive Conclusions
 The pattern of disapproval of cheating the public sector,
or paying bribes, was strong universal disapproval in
Bangladesh, but variations of a significant kind across
states of India, using World Values Survey.
Gender Norms and Labour Supply in
Comparative Context
27
 Possible desirability bias in Bangladesh survey situation.
 Transparency International ranks Bangladesh as highly corrupt in
practice.
 The pattern of labour force participation is that it is
RISING in India in the same states that have weaker
disapproval of cheating the public sector, or paying
bribes.
 E.g. BIHAR, UTTAR PRADESH, and JHARKHAND
 Most modernised, higher-average-income states have
less willingness to approve cheating the public sector, but
also have had shrinkage of women’s labour force
participation.

28. References
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.
Gender Norms and Labour Supply in
Comparative Context
28
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.

29. Acknowledgements
 Thank you to Mr. Nathan Khadaroo, Research Assistant,
Manchester 2014; 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.
 Reader in Socio-Economics
 University of Manchester
 Manchester M13 9PL
 EMAIL wendy.olsen@manchester.ac.uk
Gender Norms and Labour Supply in
Comparative Context
 Wendy Olsen
 Social Statistics
 UK
 0044 161 275 3043
29