Corruption in the corridors of power?

2009 CPS Key Findings

CPS Project is funded by a grant from The Foundation for Civil Society (FCS)

AWARENESS AND STATE OF CORRUPTION IN TANZANIA

INTRODUCTION

Corruption Perception Survey (CPS) is the mechanism used to gauge public perception in relation to functions and operations of integrity systems. The CPS process employs scientific methodologies to capture views of the people, analyse and compile the same to internally determine effective functioning of integrity system, and externally demonstrating public consent of good governance and anti-corruption policy and regulations in practices. CPS uses survey participatory tools, which are developed and designed collaboratively; involving especially civil society organisations and governance stakeholders at both national level and local level. The tools used to collect views of the people are designed specifically to augment data collection and analysis with a focus on social service delivery in effect placing Local Government Authorities (LGAs) to a unit of analysis. CPS national stakeholders are vital for analysing the methodological aspects, data and findings, while the LGAs-based stakeholders play the role of hosting and undertaking survey fieldwork activities.

The information generated and presented as CPS findings report is significant and vital, applicable by Government, business community, political parties, civil society organisations (CSOs), media and development partners.

In the vein of gauging governance performance, the Concern for Development Initiatives in Africa (ForDIA) has since 2007/8 pioneered Corruption Perception Survey in Tanzania. CPS study conducted between March and July 2009, hence this findings released in December 2009, reflect corruption perception of the public in forty LGAs in the regions of Mwanza, Tabora, Singida, Iringa, Arusha, Dodoma, Coast, Kigoma, Shinyanga and Ruvuma. The findings reveal interesting results on the extent to which the country is forging ahead in the terrain of good governance. The findings are vital for reinforcing civic awareness, knowledge and skills for engaging with the Government and promote good governance at local level. Moreover, CPS findings are so useful that they provide corruption quantitative evidence that bankroll public users of social service deliverables to hold LGAs to account. Tanzania 2009 CPS findings are based on strong evidence drawn from 40 wards and 80 streets/villages involving 945 household respondents composed of 547 male and 398

Gauging Governance Performances in Tanzania with Corruption Perception Survey

Pg. 1.

female. Furthermore, CPS findings reflect the views of 320 opinion leaders composed of 210 male and 110 female. Finally, the views of discussion groups composed of 420 members across the folks of men, women, employees, secondary schools students and primary school, in rural and urban areas reinforce the findings.

CPS findings provide quantified evidence about governance performance by assessing the level of public awareness on corruption; driving forces to corruption behaviour; information on corruption actors in LGA; attitude towards demand and supply of corruption rent; forms of and experience in corruption transactions; magnitude and trend of corruption rent; assessment of applicable anti-corruption policy and law; and determination of LGAs with lowest or highest corruption perception ranking.

It is important to know the extent to which the public is aware about corruption before rightly gauging the perception. Responses from key informants, households and focus groups helped to assess the level of public awareness on corruption in Tanzania. When asked the question, 'do you know what corruption is all about', the implication of responses is such that 91.4 percent of the household respondents said they did, while only 8.6 percent said they did not. As for key informants, 96.9 percent of opinion leaders said they were aware about corruption, while only 1.9 percent of them said they were not. The assessment of the focus groups on the level of awareness about corruption indicates over 95 percent of focus groups' members indicated satisfactory level of awareness about corruption.

OBJECTIVES OF THE CORRUPTION PERCEPTION SURVEYS The survey is broadly dedicated to promote increased dialogue between the political bureaucracies and leadership, on one hand and civil society and private sector stakeholders on the other hand, in order to attain the following objectives: i. To measure the magnitude and comprehensive picture of corruption across villages, wards, constituency and districts in the country, in effect augmenting efforts initiated to promote good governance and fight corruption at all levels. ii. To create civic awareness, knowledge and skills (competence) amongst

the electorate at the grassroots level of society by encouraging the citizenry to hold the government at their level accountable, through existing governance structures, but maintaining political stability,

Pg. 2.

tolerance, peace and security. iii. To encourage citizens' participation in the development policy-making

process by creating and maintaining trust, promotion of demand for accountability and strengthening stakeholders' commitment towards improved information flow and transparency that will eventually act as a 'deterrent' to corruption.

iv. To share information and engage the community in open dialogues with LGAs so that the views of the citizens get reflected and influence development policy decisions, making LGAs responsive and accountable to public/users of social service delivery.

v. To promote transparency and encourage openness in the LGAs, build ownership of development policy decisions and social development programmes/projects.

vi. To nurture and empower, through capacity-building and collaboration, the LGAs-based CSOs whose capacity-building support is crucial for supporting the respective NSAs-led dialogues given the findings of the CPS on governance and corruption status of LGAs.

vii. To promote the LGAs-based networks for good governance and anti -corruption involving activists and stakeholders supporting CPS project annual functions in the LGAs.

2009 CPS FINDINGS: GRAPHICAL PRESENTATIONS

1. The Sample

Graph 1/1: Age distribution of the sample

Pg. 3.

Age Distribution of the sample

0

10

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18< 18-25 26-35 36-45 46-55 >55

Age Groups

Perc

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tag

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tin

g

Key Informants

Households

Graph ½: Literacy level of sample respondents

Pg. 4.

L

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Percentage Ranking

Ke

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Pg. 5.

Graph 1/3: Household occupation structure

Graph 1/4: Key informants work station distribution

Household Occupation Structure

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Work Stations of Key Informants

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Pg. 6.

Graph 1/5: Occupation structure of key informants

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52

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Militias

Faithleaders

Health

Officers

Teachers OfficerSecretary

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Percentage Ranking

2. Level of Awareness of Corruption

3. Driving Forces for Corruption Behaviour and Acts

Graph 2: General level of public awareness of corruption

Table 3/1: Driving forces for corruption across LGAs

Public Awareness about Corruption

0

20

40

60

80

100

120

Household Key Informant

Sample Major Category

Perc

en

tag

era

nkin

g

Yes

No

Driving forces by percentage rating Respondent category Greed &

selfishness Immorality Need

for Service fast Track

Weak civic competence

Poverty Abuse of power

Response to Foreign Policy

Meagre salary

Households 39.3 0.9 4.6 10.9 17.1 0.6 0.2 26.5

Key informants

42.1 2.4 4.1 4.5 17.1 1 0 28.8

Pg. 7.

Graph 3/1: Perceived driving forces for corruption across LGAs

Table 3/2: The regional dimension of corruption driving forces in LGAs

Perception on Driving Forces to

Corruption

05

1015202530354045

Gre

ed

&

selfis

hn

ess

Imm

ora

lity

Pre

ssu

reto

ge

tserv

ice

We

ak

civ

iccom

pete

nce

Pove

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Abuse

of

po

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r

Re

sponse

to

Fo

reig

n

Po

licy

Me

agre

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ry

Corruption Driving Force

Perc

en

tag

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ati

ng

Households

Key informants

Significant forces by percentage rating Category by region

Greed & selfishness

Immorality Need for Service Fast Track

Weak civic competence

Poverty Abuse of power

Response to Foreign Policy

Meagre salary

Total

Arusha 19.8 1.2 3.5 9.3 20.9 0 0 45.3 100

Mwanza 47.2 0 2.8 9.7 19.4 0 0 20.8 99.9

Iringa 32.1 0.9 8 20.5 23.2 0.9 0 14.3 99.9

Singida 57.9 0 5.3 10.5 15.8 0 0 10.5 100

Ruvuma 51.7 3.4 0 10.5 10.3 3.4 0 20.7 100

Dodoma 5.5 0 14.5 10.9 23.6 0 0 45.5 100

Kigoma 57.8 3.1 0 7.8 3.1 1.6 1.6 25 100

Coast 56.7 0 0 3.3 13.3 0 0 26.7 100

Tabora 66 0 4 20 0 0 10 100

Household

Shinyanga 40.7 0 0 3.7 0 0 0 55.6 100

Arusha 23.5 8.8 0 11.7 23.5 0 0 32.4 99.9

Mwanza 57.4 4.3 8.5 4.3 8.5 0 0 17 100

Iringa 17.6 7.9 3.9 3.9 27.5 0 0 39.2 100

Singida 56.2 6.2 0 6.2 6.2 0 0 25 99.8

Ruvuma 41.7 0 8.3 0 8.3 0 0 41.7 100

Dodoma 25 0 3.6 3.6 32.1 0 0 35.7 100

Kigoma 51.7 0 3.4 10.3 24.1 0 0 10.3 99.8

Coast 44.4 0 7.4 0 11.1 0 0 37 99.9

Tabora 51.5 0 3 0 9.1 0 0 36.4 100

Key Informant

Shinyanga 93.3 0 0 0 0 0 0 6.7 100

Pg. 8.

Graph 3/2: Driving forces for corruption: contending positions of 'ordinary persons' and 'leaders’

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Mwanza

Iringa

Singida

Ruvuma

Dodoma

Kigoma

Coast

Tabora

Shinyanga

Arusha

Mwanza

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Singida

Ruvuma

Dodoma

Kigoma

Coast

Tabora

Shinyanga

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Corruption Diving Forces Ranking

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Pg. 9.

4. Rationale for and Analysis of Corruption Actors

Table 4/1: Overview of corruption actors' perception ranking

Source: 2009 CPS Data sheets

Pg. 10.

percentage ranking Respondent category

Actor

Department employees

Office bearers-LGAs level

Office bearers-ward/village level

Political parties leaders

Total

Education 72.3 12.2 12.8 2.7 100

Health 76.3 8.9 12.3 2.5 100

Land & housing 67.5 10.3 17.8 4.4 100 Licensing & revenue 76.3 7.5 12.5 3.7 100 Judiciary 79 13.8 4.5 2.7 100

WDCs 41.1 11.9 37.5 9.5 100

Police 78.1 6.2 12.7 3 100

DED office 48.2 18.9 21 11.9 100

Natural resources 68.4 9.6 17.5 4.5 100

Water & sewerage 74.4 4.3 17 4.3 100 Power utility/TANESCO

78.9 6.1 8.1 6.9 100

HIV/AIDS 75.6 4.4 10.9 9.1 100

Cooperatives 59.6 8.2 21.3 10.9 100

Household

Road Works 62.8 10.9 17.5 8.8 100

Education 65.9 16.3 13 4.8 100

Health 73 14.8 10 2.2 100

Land & housing 62.1 17.7 13.2 7 100

Licensing & revenue 75 12.3 7.2 5.5 100

Judiciary 72.5 12.5 11.7 3.3 100

WDCs 41.3 16.1 38.3 4.3 100

Police 73.5 14.3 11.1 1.1 100

DED office 55.7 20.9 15.1 8.3 100

Natural resources 66.8 17.3 11 4.9 100

Water & sewerage 75.4 9.5 9.5 5.6 100

Power utility/TANESCO

85.8 5.8 4.2 4.2 100

HIV/AIDS 67.8 14.5 6.3 11.4 100

Cooperatives 60.5 14.7 15.3 9.5 100

Key informant

Road Works 69.5 13 9.9 7.6 100

Education 69.1 14.25 12.9 3.75 100

Health 74.65 11.85 11.15 2.35 100

Lands & Housing 64.8 14 15.5 5.7 100

Licensing & Rev. 75.65 9.9 9.85 4.6 100

Judiciary 75.75 13.15 8.1 3 100

WDCs 41.2 14 37.9 6.9 100

Police 75.8 10.25 11.9 2.05 100

DED Office 51.95 19.9 18.05 10.1 100

Natural Resources 67.6 13.45 14.25 4.7 100

Water & Sewerage 74.9 6.9 13.25 4.95 100

Power Utility/TANESCO

82.35 5.95 6.15 5.55 100

HIV/AIDS 71.7 9.45 8.6 10.25 100

Cooperatives 60.05 11.45 18.3 10.2 100

All respondents

Road Works 66.15 11.95 13.7 8.2 100

Graph 4/1: Households' corruption perception ranking

Graph 4/2: Key Informants' corruption perception ranking

Household Corruption Perception Ranking

0

10

20

30

40

50

60

70

80

90

Educa

tion

Health

Land

&ho

using

Lice

nsing&

reve

nue

Judicia

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WDCs

Police

DEDoffic

e

Natur

alre

sour

ces

Wat

er&

sewer

age

Power

utilit

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HIV/A

IDS

Coope

rativ

es

Wor

ks

Actors

Perc

ep

tio

nR

an

kin

g(%

)

Department employees

Office bearers-LGAs level

Office bearers-ward/village level

Political parties leaders

Key Informant Corruption Perception Ranking

0

10

20

30

40

50

60

70

80

90

100

Educa

tion

Health

Land

&ho

using

Lice

nsing

&re

venu

e

Judiciar

y

WDC

s

Police

DED

offic

e

Nat

ural

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urce

s

Wat

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age

Power

utilit

y/TA

NES

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HIV/A

IDS

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tives

Wor

ks

Actors

Per

cep

tio

nR

an

kin

g(%

)

Department employees

Office bearers-LGAs level

Office bearers-ward/village level

Polit ical p arties leaders

Pg. 11.

Graph 4/3: Overall corruption perception ranking

Table 4/2: entry-exist analysis of corruption actors

Overall Corruption Perception Ranking

0

10

20

30

40

50

60

70

80

90

Edu

catio

n

Heal

th

Lands

&Hous

ing

Lice

nsing

&R

ev.

Judi

ciary

WD

Cs

Pol

ice

DED

Offi

ce

Natu

ral R

esour

ces

Wate

r &Sew

erage

Pow

erU

tility

/TANESC

O

HIV

/AID

S

Coop

erativ

es

Wor

ks

Actors

Perc

ep

tio

nR

an

kin

g(%

)

Department employees

Office bearers-LGAs level

Office bearers-ward/village level

Political parties leaders

Actor position

2009 score

Actor position

2008 score

Power Utility/TANESCO

82.35 Power Utility/TANESCO

83.15

Police 75.8 Police 82

Judiciary 75.75 Licensing & Rev. 78.5

Licensing & Rev. 75.65 Health 76.85

Water & Sewerage 74.9 Water & Sewerage 76.3

Health 74.65 Natural Resources 73.45

HIV/AIDS 71.7 Judiciary 73.3

Education 69.1 Education 71.8

Natural Resources 67.6 Lands & Housing 70.4

Road & Works 66.15 HIV/AIDS 66.3

Lands & Housing 64.8 Cooperatives 64.8

Cooperatives 60.05 DED Office 58.5

DED Office 51.95 WDCs 42.65

WDCs 41.2 Road & Works

nil

Pg. 12.

Graph 4/4: Corruption Actors' Entry-Exit Analysis

Table 5/1: Salient features of corruption perception distribution across LGAs

5. Analysis of Magnitude of Corruption as Basis for Perception

Corruption Actors' Entry-Exit Analysis

0

10

20

30

40

50

60

70

80

90

Power Utili

ty/T

ANESCO

Police

Judici

ary

Lice

nsing

&R

ev.

Wate

r &Sew

erage

Heal

th

HIV/A

IDS

Educatio

n

Natu

ral Reso

urces

Road&

Work

s

Lands&

Hous

ing

Coopera

tives

DED

Offi

ce

WDC

s

Actors

Per

ce

nta

ge

Ra

nk

ing

Sc

ore

2009 score

2008 score

Percentage score Actor

Low Average High

Education 41 20 31.5

WDCs 33.4 26 26.1

DED Office

31.3 23.7 30.9

Natural resources

27.6 23.4 37.9

Water & Sewerage

40.7 16.9 17

HIV/AIDS 30.6 9.5 22.8

Pg.13

Table 5/2: entry-exit analysis of shared magnitude of corruption in LGAs

Graph 5/1: Entry-exit analysis of shared magnitude of corruption in LGAs

Actor Position 2009 score Actor Position

2008 score

Police 77.7 Police 82.8

Judiciary 68.45 Judiciary 80.4

Health 57.4 Health 62.7

Lands & Housing 46.35 Lands & Housing 52

Licensing & Rev. 45.45 Licensing & Rev. 50.8

Natural Resources 37.6 Power Utility/TANESCO

47.9

Power Utility/TANESCO

35.6 DED Office 36.1

Education 34.65 Natural Resources 35.2

WDCs 31.6 WDCs 30.5

DED Office 31.15 Road construction 29

Road construction 27.95 Education 24.7

HIV/AIDS 17.95 HIV/AIDS 24.4

Cooperatives 16.75 Cooperatives 21.7

Water & Sewerage 16.35 Water & Sewerage 21.6

Entry-Exit Analysis of Shared Magnitude of Corruption in LGAs

0

10

20

30

40

50

60

70

80

90

Police

Judici

ary

Health

Lands

&Housin

g

Lice

nsin

g&

Rev

.

Natura

l Res

ourc

es

Power Utili

ty/T

ANESCO

Educatio

n

WD

Cs

DED

Offi

ce

Road&

work

s

HIV

/AID

S

Coopera

tives

Wate

r &Sew

erage

Actors

Per

ce

nta

ge

Ra

nk

ing

Sc

ore

2009 score

2008 s core

Pg. 14.

Table 5/3: Perception on the extent corruption is shared amongst LGAs departments

Qualitative ranking Respondent category

Actors

Low Average High Indifferent Total

Education 33.4 20 37.8 8.8 100

Health 17.5 17.7 59.1 5.7 100

Lands & Housing 20.3 19.6 44.7 15.4 100

Household

Licensing & Rev. 17.7 15.8 44.9 21.6 100

Judiciary 11.3 12.8 69.4 6.5 100

WDCs 27.9 20 37.1 15 100

Police 7.2 6.4 81.9 4.5 100

DED Office 29.8 20.7 31.4 18.1 100

Natural Resources 28.4 12.8 37.3 21.5 100

Water & Sewerage 33 11.5 15.7 39.8 100

TANESCO 17.9 12.2 34.4 35.5 100

HIV/AIDS 26.1 9.1 13.1 51.7 100

Cooperatives 28.9 7.8 16.9 46.4 100

Road & works 17.8 13.7 25.9 42.6 100

Education 41 20 31.5 7.5 100

Health 19.2 21.2 55.7 3.9 100

Lands & Housing 18.3 24.7 48 9 100

Licensing & Rev. 17 23.4 46 13.6 100

Key Informant

Judiciary 13.7 14 67.5 4.8 100

WDCs 33.4 26 26.1 14.5 100

Police 7.1 12.8 73.5 6.6 100

DED Office 31.3 23.7 30.9 14.1 100

Natural Resources 27.6 23.4 37.9 11.1 100

Water & Sewerage 40.7 16.9 17 25.4 100

Power Utility/TANESCO

18.5 17.2 36.8 27.5 100

HIV/AIDS 30.6 9.5 22.8 37.1 100

Cooperatives 36.1 14.8 16.6 32.5 100

Road & works 30 16 30 24 100

Education 37.2 20 34.65 8.15 100

Health 18.35 19.45 57.4 4.8 100

Lands & Housing 19.3 22.15 46.35 12.2 100

Licensing & Rev. 17.35 19.6 45.45 17.6 100

Judiciary 12.5 13.4 68.45 5.65 100

WDCs 30.65 23 31.6 14.75 100

Police 7.15 9.6 77.7 5.55 100

DED Office 30.55 22.2 31.15 16.1 100

Natural Resources 28 18.1 37.6 16.3 100

Water & Sewerage 36.85 14.2 16.35 32.6 100

Power Utility/TANESCO

18.2 14.7 35.6 31.5 100

HIV/AIDS 28.35 9.3 17.95 44.4 100

Cooperatives 32.5 11.3 16.75 39.45 100

Key Informant & Household combined

Road & works 23.9 14.85 27.95 33.3 100

Pg.15.

Graph 5/2: Household qualitative ranking on share of corruption in LGAs

Graph 5/3: Key informant qualitative ranking on share of corruption in LGAs

Household Corruption Perception on Actors Across LGAs

0

10

20

30

40

50

60

70

80

90

Educatio

n

Health

Lands

&Housin

g

Licensin

g&

Rev.

Judici

ary

WD

Cs

Police

DED

Offi

ce

Natura

l Reso

urces

Wate

r &Sewera

ge

Power Utili

ty/T

ANESCO

HIV

/AID

S

Coopera

tives

Road

&work

s

Actors (LGAs Agencies)

Qu

ali

tati

ve

Ra

nk

ing

Low

Average

High

Indifferent

Key Informant Corruption Perception on Actors Across LGAs

0

10

20

30

40

50

60

70

80

Educatio

n

Health

Lands

&Housin

g

Licensin

g&

Rev.

Judici

ary

WD

Cs

Police

DED

Offi

ce

Natura

l Reso

urces

Wate

r &Sewera

ge

Power Utili

ty/T

ANESCO

HIV

/AID

S

Coopera

tives

Road

&work

s

Actors (LGAs Agencies)

Qu

ali

tati

ve

Ra

nk

ing

Low

Average

High

Indifferent

Pg. 16.

Graph 5/4: Overall qualitative ranking on share of corruption in LGAs

Graph 6/1: Confession to have or not paid corruption to access services in LGAs

6. Forms of and Experiences in Corruption

Overall Corruption Perception on Actors Across LGAs

0

10

20

30

40

50

60

70

80

90

Educatio

n

Health

Lands

&Housin

g

Licensin

g&

Rev.

Judici

ary

WD

Cs

Police

DED

Offi

ce

Natura

l Reso

urces

Wate

r &Sewera

ge

Power Utili

ty/T

ANESCO

HIV

/AID

S

Coopera

tives

Roadco

nstru

ctio

n

Actors (LGAs Agencies)

Qu

ali

tati

ve

Ra

nk

ing

Low

Average

High

Indifferent

0

10

20

30

40

50

60

70

80

Percentage Ranking

Never Yes, once Sometimes Always

Confession Variations

Confession to Involvement in the Corruption Transactions: Households

Pg.17.

Implication: 29.43 percent of ordinary Tanzanians confess to have, at le ast once, paid a bribe as means to access services in the LGAs. This finding is a far better relief than similar revelation in the 2008 CPS report in which the assessment similarly indicates 43 percent of ordinary Tanzanians being forced to bribe duty bearers in LGAs to access social services.

Table 6/1: cross tabulation of experience in paying corruption in the LGAs

Region Frequency (percentage) LGA Never Yes, once Sometimes Always Total

Tabora Urban 71.4 14.3 14.3 0 100 Sikonge 82.6 17.4 0 0 100 Urambo 95.8 0 0 4.2 100

Tabora

Uyui 100 0 0 0 100 Kongwa 43.5 30.4 0 26.1 100 Dodoma Urban 54.1 0 29.2 16.7 100 Chamwino 100 0 0 0 100

Dodoma

Mpwapwa 54.2 20.8 20.8 4.2 100 Kigoma rural 91.6 0 4.2 4.2 100 Kigoma urban 79.1 4.2 12.5 4.2 100 Kibondo 83.3 8.3 8.4 0 100

Kigoma

Kasulu 70.8 12.5 8.3 8.4 100 Songea urban 77.3 13.6 4.5 4.6 100 Ruvuma

Songea rural 79.2 16.6 4.2 0 100 Shinyanga rural 72 8 12 8 100 Shinyanga

Maswa 100 0 0 0 100 Arumeru 31.8 9.1 59.1 0 100 Monduli 70.8 8.3 16.7 4.2 100 Karatu 73.9 17.4 0 8.7 100 Loliondo 52.2 4.3 34.8 8.7 100

Arusha

Arusha urban 45.8 8.4 12.5 33.3 100 Ludewa 25 20.8 45.9 8.3 100 Njombe 57.7 26.9 15.4 0 100 Kilolo 58.3 12.5 29.2 0 100 Iringa Municipal 66.7 20.8 8.3 4.2 100 Makete 83.3 8.3 4.2 4.2 100

Iringa

Iringa rural 76 4 12 8 100 Mufindi 87.5 12.5 0 0 100

Kisarawe 87.5 8.3 4.2 0 100 Rufiji 83.3 8.3 0 8.4 100 Mkuranga 58.3 20.8 20.9 0 100

Coast

Bagamoyo 76.9 23.1 0 0 100 Magu 91.7 4.1 0 4.2 100 Nyamagana 37.5 33.3 12.5 16.7 100 Ukerewe 58.3 8.3 16.7 16.7 100

Mwanza

Missungwi 41.7 29.2 24.9 4.2 100 Geita 58.3 20.8 12.6 8.3 100 Kwimba 91.3 0 8.7 0 100

Singida rural 79.2 12.5 8.3 0 100 Singida Manyoni 75 4.2 20.8 0 100

Pg. 18.

Graph 6/2: Final recipients of actually paid corruption by households

Graph 6/3: 2008-2009 comparison of actual recipients of corruption across LGAs

0

5

10

15

20

25

30

35

40

45

50

Percentage Ranking

Police Health Education Judic iary Others

LGAs Agencies (Actors)

LGAs Agencies: Recepients of Actually Transacted Corruption

Actual Reci pient of Corruption Transactions: 2008-2009 Comparizon

0

10

20

30

40

50

60

Police Health Education Judiciary Others

Dominant Recipients in LGAs

Per

ce

nta

ge

Ra

nk

ing

2009

2008

Pg.19.

Graph 6/4: Comparison of social services Exchanged by actually Transacted Corruption across LGAs during years 2008 and 2009

Pie chart 6: Share of corruption proceeds across LGAs rank and file

Comparizon of Services Exchanged by actually Transacted Corruption: 2008 vs. 2009

0

10

20

30

40

50

60

Health services Court acquittance Building Plot Educationservices

Police Bail Permits others

Exchanged Social Services

Per

ce

nta

ge

Ra

nk

ing

2009

2008

Share of Corruption Proceedsmacross LGAs

Rank and File

rank & file

Midle staff

Senior officers

Pg. 20.

Table 6/2: Preference and choice of corruption transaction form

Graph 6/5: Preference and choice of corruption transaction form

Pg. 21.

Preference ranking in percentage Corruption form

Very rare Rare Frequent total

Money 1.6 4.85 93.55 100

Valuables/properties 27.2 55.55 17.25 100

Services 37.25 42.65 20.1 100

Sex 22.55 37.15 40.3 100

Favoritism 27.4 37.2 35.4 100

Abuse of office 23.4 43 33.6 100

Corruption Form Preference

0

10

20

30

40

50

60

70

80

90

100

Money

Valuab

les/p

rope

rties

Servic

es Sex

Favorit

ism

Abuseof of

ficce

Forms of Corruption

Pe

rce

nta

ge

Ran

kin

g

Very rare

Rare

Frequent

7. Attitude Towards Demand For And/or Supply Of Corruption

Graph 7/1: Attitudes towards demand and supply of corruption in LGAs: 2008/2009 comparison.

Pie chart 7/1: Extent of public confidence to report corruption grievances

Pg. 22.

Attitudes towards Demand/Supply of Corruption in LGAs: 2008/2009 Comparison

0

10

20

30

40

50

60

Voluntarily giving Forced by bureaucratic design Enticed by LGAs service facility

emplyees

Hinted by friends to do so

Environmental conditions

Pe

rce

nta

ge

Ran

kin

g

2009

2008

Interpreting the above findings, 97.4 percent of service users paying corruption to access services in the LGAs do so fo rcefully; only a few corruption amateur s, accounting to 2.6 percent, do so voluntarily.

Public Confidence to Expose Corruption

92.5

5.6 1.9

No, not yet receivedcomplaints

Yes, seldom receivecomplaints

Yes, regularlyreceive complaints

Graph 7/2: Public confidence to expose corruption: 2009 and 2008 findings comparison

Pie chart 7/2: Types and level of exposed/reported corruption issues to duty bearers

Public Confidence to Expose Corruption: 2008/2009 Findings Comparison

0

10

20

30

40

50

60

70

80

90

100

No, not yet received complaints Yes, seldom receive complaints Yes, regularly receive complaints

Public Confidence Indicators

Per

ce

nta

ge

Ra

nk

ing

2009

2008

Corruption Issues Reported to Duty Bearers

5%

10%

15%

20%

5%

5%

5%

5%

15%

10%

5%

Embezzlement of funds

Plot a llocation

denying m edical services

arbitrary a nd i llegal de mand f or prepayments

demanding s ex f rom gi rl s tudents

selling of a rki

bribing of magisrate

forgery of c ertificate

School posting

Bail

conflict

Pg. 23.

8. Selective Assessment of Current Anti-corruption Policy and Legal Measures in Practice in The LGAs

Graph 8/1: Availability and applicability of anti-corruption regulatory framework and institutional mechanism

Graph 8/2: General public awareness about CSOs fighting corruption: 2008/2009 comparison

Awareness on Availability and Application of Legal and Policy Instruments in LGAs

24

52.3

23.7

32.4

67.6

0

20

40

60

80

100

120

140

Yes No I don't know

Households and Key Informants Confirmations to availability of Legal or Similar Instruments in

Localities

Per

ce

nta

ge

Ra

nk

ing

Key Informant

Household

Awareness about CSOs Fighting Corruption: 2008-2009 Comparison

0

10

20

30

40

50

60

70

80

90

TAMW A HakiElimu ForDIA TNIB SKUVI MESO TGNP FBOs

Mentioned CSOs

Per

ce

nta

ge

Ra

nk

ing

2008 Hosehold

2008 Key Inform at

2009 Household

2009 Key Inform ant

Pg. 24.

Graph 8/3: Public Assessment of Government anti-corruption performance in LGAs

Graph 8/4: Public Assessment of Government anti-corruption performance in LGAs: 2008 and 2009 comparison

Public Assessment of Government Anti-Corruption Performance in LGAs

22.4

8

0

94.7

0

37

22.8

15

11.8

11

2.40

10

20

30

40

50

60

70

Establishment of

PCCB

Govt. Directive Public Opinion

Polling

Investigation &

Prosecution

Community

Education throughMedia

Money & Informer

Performance Indicators

Per

ce

nta

ge

Ra

nk

ing

Key Informant

Household

Public Assessment of Government Anti-Corruption Performance across LGAs: 2008-2009

Comparison

0

10

20

30

40

50

60

Establishment ofPCCB

Govt. Directive Public OpinionPolling

Investigation &Prosecution

CommunityEducation through

Media

Money & Informer

Performance Indicators

Per

ce

nta

ge

Ra

nk

ing

2008 Household

2008 Ke y I nformant

2009 H oousehold

2009 Ke y I nformant

Pg. 25.

9. Determining Lowest Vs. Highest Corruption Perception LGAs

Determination of LGAs perceived to be either lowest or highest corrupt is a combination of data analysis through four iterations destined to identify one LGA perceived positively with “lowest” or “conversely”, with highest corruption perception. Every LGA appears once in each column with a complementary data element in the corresponding column. The expectation is that respondents' answers to the 'control question' in each LGA constitute 100 percent valuation. This means, therefore, if %, of respondents feel corruption is low, then (100-)% of respondents in the same LGAs must feel and indicate that the state of corruption is high. The findings are conclusively indicated in table 8/5 below.

Pg. 26.

Table 9/5: Final determination of LGAs with lowest/highest corruption perception

Pg. 27.

LGA Low % rate LGA High % rate Mufindi 97.9 Ludewa 93.75 Kigoma rural 91.65 Maswa 86.6 Songea rural 89.15 Kongwa 83.35 Chamwino 85.4 Nyamagana 79.15 Singida Rural 84.8 Arusha urban 77.35 Kigoma urban 83.3 Geita 72.9 Uyui 80 Longido 72.65 Iringa Rural 75.65 Kasulu 71.3 Sikonge 75 Kisarawe 70.4 Songea urban 72.5 Tabora Urban 70.15 Karatu 67.2 Ukerewe 67.85 Rufuji 66.65 Iringa Municipal 66.65 Monduli 61.4 Arumeru 65.9 Dodoma Urban 60.4 Mpwapwa 60.4 Njombe 59.25 Manyoni 57.7 Makete 56.25 Urambo 56.25 Bagamoyo 55.3 Shinyanga Rural 54.5 Kilolo 54.15 Mkuranga 52.1 Magu 54.15 Missungwi 50 Kwimba 50.55 Kibondo 50 Missungwi 50 Kwimba 49.45 Kibondo 50 Kilolo 45.85 Mkuranga 47.9 Magu 45.85 Shinyanga Rural 45.5 Bagamoyo 44.7 Urambo 43.75 Makete 43.75 Manyoni 42.3 Njombe 40.75 Mpwapwa 39.6 Dodoma Urban 39.6 Arumeru 34.1 Monduli 38.6 Iringa Municipal 33.35 Rufuji 33.35 Ukerewe 32.15 Karatu 32.8 Tabora Urban 29.85 Songea urban 27.5 Kisarawe 29.6 Sikonge 25 Kasulu 28.7 Iringa Rural 24.35 Longido 27.35 Uyui 20 Geita 27.1 Kigoma urban 16.7 Arusha urban 22.65 Singida Rural 15.2 Nyamagana 20.85 Chamwino 14.6 Kongwa 16.65 Songea rural 10.85 Maswa 13.4 Kigoma rural 8.35 Ludewa 6.25 Mufindi 2.1

Given the findings as indicated in table 3.11/5 above, Mufindi is the LGA ranked with lowest corruption perception by 97.9 percent, whil e converse ly, Ludewa is the LGA ranked with highest corruption perception by 93.75 percent.

STATISTICAL ANALYSIS

RESULTS (for household and key informant)

Low LGA (Symmetrical but Leptokurtic)

Pg. 28.

Statistics

LGA( low) LGA (High)

N Valid 40 40

Missing 0 0

Mean 52.0425 47.9575

Median 51.6500 48.3500

Mode

Std. Deviation

24.13854 24.13854 Variance

582.669 582.669 Skew ness

.221 -.221 Std. Error of Skew ness

.374 .374 Kurtosis

-.627 -.627 Std. Error of Kurtosis 0.733

.733

Pg. 29.

High LGA (Symmetrical but Leptokurtic)

Statistical explanation of the output aboveFrom the above table and graphs the measures of central tendency (mean and median) show almost the same result due to the character of the data; we cannot assess the mode for both low and high LGA because it does not exists.

1. MeanThe mean for low corruption perception LGAs is 52.0425 percent and that for high corruption perception LGA is 47.9575 percent. Using the mean therefore, the result shows that on average, for all regions and LGAs the mean is low in the household (although the difference between low and high is just 2 percent which is slightly small)

2. MedianThe median for low corruption perception LGA is 51.65 percent and that for high corruption perception LGA is 48.35 percent. Using median as measure of central tendency therefore, indicates the result showing that for all regions and LGAs the median is low in the household (although the difference

Pg. 30.

between low and high is just 2 percent which is slightly small)

ConclusionsTherefore the two measures of central tendency that is mean and median show the same results that corruption perception in LGAs is slightly low for household on average and therefore due to the nature of the data that they do not have extreme value we can use either of the two to determine the level of corruption perception (index) across LGAs in Tanzania.

3. Standard Deviation and VarianceThe standard deviation of the low corruption perception LGAs is 24.13854 with the variance of 582.669, while for high corruption perception LGAs is 24.13854 with the variance of 582.669, this means that the percent of variation for high or low LGAs from one districts to another is a bit large.

4. Skew nessThe coefficient of skew ness for low corruption perception LGAs was 0.221, and its standard error of 0.374. If we take the Standard Error (S.E) multiply by two we get 0.748. And the coefficient of skew ness must lie between -2 S.E and 2S.E, from (-0.748 and 0.748), then since 0.221 is between these two value or 0.221 is not far from zero then we can say that the data is symmetrically distributed. Also for high corruption perception LGAs the data was also symmetrically distributed since -0.221 is near to zero and it lies between (-0.748 and 0.748)

But the coefficient of kurtosis is -0.627 and -0.627 for low and high corruption perception LGAs respectively, these shows that data form a leptokurtic distribution because numerical value of kurtosis is negative and is far from zero.

Conclusion Therefore by using skew ness and kurtosis it shows that although the data is symmetrically distributed they are not following a normal distribution due to the fact that they have high negative value of kurtosis that form (leptokurtic) and we can say the data are not normally distributed (there are no uniform distribution from the small percent up to the high percent)

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