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Quarterly Data Analysis for PNB Reporting Platform 26th June - 26th September 2017

This report presents data for the 5 sectors of the PNB Campaign (Education, Electricity, Health

Care, Sierra Leone Police, and Water) from the Pay No Bribe Reporting Platform for the period,

26th June – 26th September 2017. The data represent reports received from the public under the

three reporting mechanisms: The 515 hotline; Mobile Apps; and Website. The data present

reporting from the 5 implementing districts of Bo, Bombali, Kenema, Western Area Urban and

Western Area Rural.

Data is presented under the following headings:

1. Overall number of reports received ................................................................................... 2

2. Distribution of report – a new way to perceive trends ....................................................... 4

3. Distribution of reports received under each sector ............................................................ 8

Education ........................................................................................................................... 8

Electricity Sector .............................................................................................................. 10

Sierra Leone Police .......................................................................................................... 13

Health Care Sector ........................................................................................................... 16

Water Sector..................................................................................................................... 20

4. Distribution of Method of Payment and Value of Payment per Sector ........................... 22

5. Demographics of reporting .............................................................................................. 24

6. Actions points for the PNB Programme .......................................................................... 26

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1. Overall number of reports received

During the third quarter of 2017, the PNB Campaign received 5,768 reports. This represents a

significant decrease of 49.5% in comparison to the 11,424 reports received in the previous

quarter. The reporting levels to the PNB Campaign has been volatile throughout the

campaign as illustrated in Figure 1. The steep decline in the 3rd quarter of 2017 shows clearly

on the chart, with a decline from a total of 4329 reports in June 2017 to just 660 incoming

reports in September 2017. Despite the volatility there has been a slight upward trend in

reporting since inception on the 26th of September 2017.

Figure 1: Distribution of reports in the first 12 months.

The figure above shows 3 major declines in reporting levels in January, May and

August/September 2017. Common for the 3 periods were a decline in outreach activities,

particularly the animation activities, carried out by the partnering CSOs.

In January 2017, there was a delay in CSO Animators resuming work after the

holiday season and the PNB Campaign received very few reports in particularly the

first 2 weeks of January.

In May 2017 Coffey, the implementing partner of the PNB Campaign, had

administrative challenges with regards to the agreement with the CSOs, which lead to

a reduced animation and outreach by the CSOs.

In August/September the PNB developed a new strategy for PNB outreach and

sensitization which led to reduced activity levels during the period, as well as the wet

season which reduced intensity of the CSO Animators outgoing activities.

There is reason to believe in a strong correlation between CSO Animators activity and the

level of reporting. All CSO animators carry a phone with the PNB Mobile Apps installed.

The CSOs indicate that they primarily used the PNB Mobile Apps to facilitate reports,

whenever someone wished to submit a report but did not have the means to do so. Since,

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using the App requires a smart phone and data, it is not considered to be the most accessible

means of reporting for the general public. Therefore, we assumed that the majority of PNB

Mobile App reports are generated as a result of the CSO animator’s outreach. Figure 2 shows

the source of the reports received by the PNB Campaign.

Figure 2: Distribution of reports by Source in first 12 months by month

There is a clear correlation between the number of reports received in Figure 1 and the PNB

Mobile App reporting in Figure 2. Hence, if the majority of reports on the PNB Mobile App

are derived from CSO Animator activities, it is reasonable to assume that the volatility of the

PNB reporting level is a consequence of the activity level of the CSO Animators.

Strategic Re-orientation of Outreach Activities

The PNB Campaign identified reliance on CSO Animators facilitating reports to be an issue

for the sustainability of the programme. A new outreach strategy aimed at increasing the

number of self-reporting of the citizens were devised in August/September. It is expected that

reporting will increase significantly as the new strategy is implemented and outreach activity

levels pick up after the rainy season.

As indicated, the volume of reports shown by the PNB Data does not necessarily represent

changes in the level of bribery or honest officials, but the intensity of outreach activity.

Consequently, the raw numbers of reports are do not necessarily reflect trends in level of

bribery. The next section will explore another way to perceive trends: the changes of

distribution between indicators.

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2. Distribution of report – a new way to perceive trends

Despite the drop in the overall number of reports between the 2nd and 3rd quarters of 2017,

they remain more or less equally distributed between “I Paid a Bribe”, “I Did not Pay a

Bribe” and “I Met an Honest Official”.

Figure 3: Distribution of reports in 2nd quarter 2017 Figure 4: Distribution of reports in 3rd quarter 2017

Seen across all 12 months of the programme on figure 5, it is clear that the distribution of

reports among “I Paid a Bribe”, “I Did not Pay a Bribe” and “I met an Honest Official” is

relatively stable, with an average of 76% “I Paid a Bribe”, 17% “I Did not Pay a Bribe” and

8% “I met an Honest Official”

Figure 5: Distribution of reports by What Happened in first 12 months

Hence, despite the volatility of reporting level (as shown in figure 1), the distribution of

reporting between the indicators are more or less constant (figure 5).

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With regards to the distribution of reports between Sectors, a similar picture emerges when

comparing the 2nd and 3rd quarter of 2017, with an almost identical distribution despite a large

variance in the number of reports received.

Figure 6: Distribution between Sectors in Q2 2017 Figure 7: Distribution between Sectors in Q3 2017

Over 12 month period, few variances can be detected but overall the report distribution

remains relatively stable month after month (see figure 8).

Figure 8: Distribution of reports between Sectors in first 12 months

The distribution of reports in the targeted Districts, however, changed significantly from the

2nd quarter to the 3rd quarter of 2017, as shown in figure 9 and 10. In Kenema District, for

instance, reports dropped from 30% of all reports in Q2 to 15% in Q3.

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Figure 9: Distribution between Districts in Q2 2017 Figure 10: Distribution between Districts in Q3 2017

Figure 11 below, which displays the distribution of reports by months between Districts,

shows a high variance in distribution patterns.

Figure 11: Distribution of reports between Districts in first 12 months

In the previous section, it was argued that the volume of reports depended on the level of

outreach. Since the outreach by the CSO Animators is a local variable, this can explain the

shifts in reporting levels, where for instance Kenema received a significant proportion of

reports from December 2016 to March 2017, but hardly received any in August/September

2017.

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Whilst the volume of reporting fluctuates due to the level of outreach activities, the

distribution of reports between “I paid a Bribe”, “I did not Pay a Bribe”, “I met an Honest

Official” between the Sectors are more or less constant.

This “standard distribution” can therefore serve as a baseline for the data, and help determine

whether a sector nationally or in a specific location is performing better or worse over time.

However, “standard distribution” cannot be used to compare the overall performance of

locations, since the volume of reporting in the location are determined by the level of

outreach.

Figure 12: Baseline distribution of reports between sectors in first 12 months

Note that local variances are not caused by the level of outreach, but also of differences in

sectors and services delivered in particular areas

Table 1: District baseline distribution of reports between sectors in first 12 months

Education Electricity Health Care Police Water Other

Bo District 21% 5% 29% 41% 1% 3%

Bombali District 31% 5% 30% 29% 0% 5%

Kenema District 20% 2% 29% 40% 1% 7%

Western Area Rural 20% 2% 28% 49% 1% 0%

Western Area Urban 10% 7% 21% 53% 4% 4%

Grand Total 20% 4% 27% 42% 2% 5%

Table 1 shows that there are recognizable differences in the distribution of reports in the

Districts. For Education, Bombali District received 31% while Western Area Urban received

only 10%. For Electricity and Water, the highest frequency was in Western Area Urban (7%

and 4%), which is surprising since these are services mainly provided in urban areas. Health

Care was relatively equally distributed, whereas for the Police sector Bombali stands out with

only 29% of the reporting.

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Table 2: Sector baseline distribution of reports between districts in first 12 months

Education Electricity Health Care Police Water Other Total

Bo District 9% 11% 9% 9% 4% 5% 9%

Bombali District 35% 24% 25% 16% 3% 24% 23%

Kenema District 34% 17% 35% 31% 17% 47% 33%

Western Area Rural 8% 4% 9% 10% 5% 1% 8%

Western Area Urban 13% 44% 22% 35% 71% 24% 28%

The following sections explore the data of the 3rd quarter of 2017 at both district and service

levels.

3. Distribution of reports received under each sector

In this section the distribution of “I Paid a Bribe”, “I did not pay a Bribe” and “I Met an

Honest Official” will be presented for each of the 5 sectors of the Pay No Bribe Campaign.

Education

Education received a total of 1230 reports in the 3rd quarter of 2017, out of which 1045 were

“I Paid a Bribe”, 76 “I did Not Pay a Bribe” and 109 “I met an Honest Official”. While the

volume of report on Education decreased significantly from the 2nd quarter, Education still

received 21% of all reports (figure 7), which is very close to the baseline of 20% (figure 12).

Figure 13: Education reports and Districts in Q3 of 2017

Bombali District received 42% of the reports on Education in the 3rd quarter, which is higher

than the cross sector average of 29% for reporting on Bombali District (figure 1). Similarly,

Kenema District had a higher ratio of Education reports (16%) compared to the cross sector

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average (15%). On the other end of the scale, Western Area Urban only received 11% of the

Education reports compared to 36% of all reports. Hence, reporting on the Education Sector

was relatively higher in Bombali and Kenema compared to the other districts, while it was

significantly lower for Western Area Urban.

Figure 14: Disaggregation of Reports in Services for Education (Q3 2017)

In the 3rd quarter “Grades and Exams” where the most frequently reported services in

Education.

From the inception of the PNB Campaign in the end of September 2019, Education has been

the most volatile sector in terms of seasonal changes on the most and least reported services,

as show in figure 15 below. Figure 15: Distribution of Services reported under Education

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Figure 15 shows that in April to July there was a high frequency of reporting on “Grades and

Exams”. In July and August, “Report Card” were frequently reported, while in August and

more so in September, “Admissions” were the most reported service.

This reporting pattern reflects, with a slight delay, the school calendar year. Hence, the PNB

reports about services provided by the Education sector reflect the school calendar.

Since the provision of services within the Education sector is seasonal, it is not suitable to

benchmark one month to the next. However, information of the seasonal occurrence of

bribery for certain services can be used to do time specific sensitization and interventions.

Figure 16: I Paid a Bribe for Services each District (Q3)

“I Paid a Bribe” reporting on “Grades and Exams”, which were the most reported, had high

frequency in all Districts apart from Western Area Urban. Reporting on “Report Cards”

followed a similar pattern as “Grades and Exams”, since they are related services as the

Exams leads to the issuing of Report Cards.

Notably, reporting on “Others” almost solely derived from Bombali and Kenema Districts.

Based on the feedback provided by the Call Centre operators, who receive reports directly

from the public, we know that a large proportion of reports on “Others” in the Education

Sector relates to the School Feeding Programme.

The high level of reporting from Bombali District, and particularly Bombali Shebora, is a

concern, since it is significantly higher than the cross sector average. Furthermore, the

reporting on “Others” could indicate challenges for the School Feeding Programme in

Bombali and Kenema District.

Electricity Sector

Electricity only receives on an average 4% of the reports, which is exactly the same ratio as

in the 3rd quarter (figure 7 and 12). The relative low level of reporting is likely due to two

factors: distribution of service and level of interaction with service providers. Electricity

services are not accessible in most parts of the country, which reduces the number of

potential users significantly. Secondly, after initial installation the interaction between user

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and service provider is very limited, which reduces the instances where corrupt practices can

occur.

The low levels of reporting reduces the data set, the representational value of the data and

increases the volatility.

Figure 17: Electricity reports and Districts in Q3 of 2017

Western Area Urban accounted for 56% of all reports on the Electricity Sector, which is

higher than the averages frequency of 44% of all reports concerning Electricity coming from

Western Area Urban (table 2).

Figure 18: Electricity and Services in Q3 of 2017

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During the 3rd quarter “New Connections” was most frequently reported with 39% of all

reports, followed by “Meter Replacement” (25%) and “Reconnection” (22%).

Figure 18: Distribution of reporting on Services for Electricity in 12 month

In the last year of the programme there has been minor fluctuations as seen in Figure 18.

However, on average, distribution is relatively close to the Q3 data with 40% for “New

Connections”, 22 for “Meter Replacement” and 25% for “Reconnection. The reason for the

fluctuation is most likely the volatility caused by a relatively small dataset.

It is noticeable, that while “Reduced Bill” initially was scoped as an important issue for

bribery in the Electricity sector, there has only been few reports on it. This can be attributed

to the implementation of pre-paid meters by EDSA, which reduces the opportunities for

corrupt practices in the providing electricity. The services with the highest level of reporting

are, on the contrary, those with a high degree of human interaction (New Connection, Meter

Replacement, and Reconnection).

In February to April, Meter Replacement had an increase in reporting ratio. In this period

EDSA was challenged by supplying new meters, which generated delays for the costumers.

The discontent and/or attempt to circumvent the delayed process could be the cause of the

upsurge in Meter Replacement reporting during that period.

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Figure 20: I Paid a Bribe reports for Electricity in Q3 of 2017

Reports on the Electricity sector are generally focused on few locations. In the 3rd quarter of

2017, all 18 reports on “Reduced Bill” came from Makari Gbanti in Bombali. 32 of 50

reports on “New Connection” in Western Area Urban came from Portee and 13 of 30 reports

on Meter Replacement in Western Area Urban came from Juba. These “hotspots” can either

be caused by the teams working in the area, the activity of the CSO animators or

misrepresentation caused by a too small dataset.

Sierra Leone Police

The Police received a total of 2345 reports in the 3rd quarter of 2017, which is 40% of all

reports captured by PNB in the period and slightly below the yearly average of 42% (figure 7

and 12). Of the reports 1719 related to “I Paid a Bribe, 504 to “I Did Not Pay a Bribe” and

122 on “I Met an Honest Official”.

Figure 21: Distribution of Police reports in Districts in Q3 2017

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The district distribution of reports differed significantly from the yearly average in table 2.

Western Area Urban had, mainly due to a large number of “I did not pay a Bribe” reports,

higher frequency than the yearly average (47% Q3, 35% year), just as Western Area Rural

(20% Q3, 10% year) and Bombali (19% Q3, 16% year). On the opposite spectrum, Kenema

reduced its frequency from 31% yearly average to 11% in Q3. Bo only received 3% of all

Police reports in the 3rd Quarter.

This variance from the general trend can either be seen as a result of the SLPs actions in

Kenema in response to the PNB Data, or as caused by the decline in reporting from Kenema

in the 3rd quarter of 2017 (figure 9 and 10). Since Kenema during the first 12 months of the

programme had a relatively high average on Police reporting (table 2), the decline is most

significant in this sector.

Figure 22: Police reports by Sectors in Q3 2017

“Traffic” remained the most commonly reported service followed by “Bail”.

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Figure 23: Distribution of reporting on Services for Police in 12 month

Since inception this pattern has been consistent with “Traffic” accounting for 69% and “Bail”

for 17% of all Police Reports.

Figure 24: I Paid a Bribe reports for Police in Q3 of 2017

While “Bail” only constitutes at an average 17% of all reports relating to the Police, 35% of

all reports in Western Area Urban in the 3rd quarter of 2017 related to “Bail”. This significant

variation from the average mainly derived from two location in the East-End of Freetown:

Kissy (74) and Up-Gun (69).

Furthermore, it is noticeable that "Traffic” only constitutes 50% of the Kenema reports,

which is below the average of 69%. Particularly considering that Kenema earlier in the

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programme had a high frequency for “Traffic”, it could suggest that the interventions of SLP

targeting traffic related bribery in Kenema has had a positive effect.

Health Care Sector

27% of the reports made by the public in the 3rd quarter of 2017 related to the Health Care

sector, which is exactly the same ratio as for the first 12 months of the PNB Programme.

Figure 25: Disaggregation of Health Care Sector reports in Districts in Q3 2017

The most noticeable on the district disaggregation of Health Care reports is the high number

of “I did Not Pay a Bribe” reports from Western Area Urban, combined with the relatively

low number of “I Paid a Bribe” reports from the same location and from Bo District.

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Figure 26: Disaggregation of Health Care Sector reports in Services in Q3 2017

“Pregnancy and Child Birth” accounted for 33% and “Under 5 Child Health” for 27% of the

reports to the Health Care Sector in Q3. A significant proportion of these were “I did not pay

a Bribe” particularly from Western Area Urban.

Figure 27: “Pregnancy and Child Birth” and “Under 5 Child Health” in Western Area Urban Q3

The “I did not Pay a Bribe” reports constituted 92% of all reports relating to “Pregnancy and

Child Birth” and “Under 5 Child Health” in Western Area Urban. In Western Area Urban

73% of these reports came from Ola During Children’s Hospital and 26% from PCM

Hospital.

4028

50 66 38 250

500

1000

1500

2000

2500

3000

3500

4000

4500

Cash Other Products, Animals orFood

Service and Favours Sexual Favours

Total

Total

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Since the start of the PNB programme, the Health Care Sector has received 39% of all reports

in respect of “I did not pay a Bribe” or “I met an Honest Official”, because it is a sector

where users are more inclined to show appreciation.

However, the concentration of reports at few services and locations is an issue which the

programme should look into. This could likely be as a result of a high degree of appreciation

by the public, sensitization at the specific location carried out by the staff, false reporting or

an error in the data capturing multiplying the number of reports.

Figure 27: Distribution of Health Care Sector reports between Services in 12 months

The Health Care Sector has experienced a relatively stable distribution of reports, with at an

average 32% for “Under 5-child health” and 32% for “Pregnancy and Child Birth”, which is

relatively close to the 3rd quarter distribution.

The high level of reports concerning these services can be attributed to the widespread public

awareness about these service under the free health care. This has made easier for the public

to recognize if illegitimate charges are added (I Paid a Bribe) The high levels of report in this

sector can also be attributed to the level of appreciation when service is delivered (I met an

Honest Official).

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Table 3: I Paid a Bribe reports for the Health Care Sector in Q3 of 2017

Cer

tifi

cate

(h

ealt

h, b

irth

, dea

th)

Dru

gs a

nd

Tre

atm

en

t

Emer

gen

cy C

are

Med

ical

Tes

ts

Pre

gnan

cy a

nd

Ch

ild B

irth

Re

gist

rati

on

an

d C

on

sult

atio

n

Un

der

5 C

hild

Hea

lth

Vac

cin

atio

ns

Oth

er

Gra

nd

To

tal

Bo District 3 9 8 13 2 16 1 52

Bo Government Hospital 3 5 8

Government Clinic or PHU 9 3 13 2 16 43

Private or NGO Hospital 1 1

Bombali District 15 35 3 16 102 33 81 2 14 301

Government Clinic or PHU 15 34 1 12 73 28 67 1 13 244

Makeni Government Hospital 1 2 4 29 5 9 1 1 52

Private or NGO Hospital 5 5

Kenema District 8 3 7 8 84 21 82 3 10 226

Government Clinic or PHU 7 3 5 74 1 73 2 10 175

Kenema Government Hospital 1 2 8 10 20 9 1 51

Western Area Rural 39 10 12 41 40 16 56 14 228

Government Clinic or PHU 39 10 12 40 40 15 56 14 226

Private or NGO Hospital 1 1 2

Western Area Urban 5 36 9 30 11 2 93

Connaught Hospital 1 1

Kingtom Police Hospital (MI Room) 1 1

Lumley Government Hospital 3 3 3 9

Macauley Satellite Hospital 1 1

Ola During Children's Hospital 1 16 8 8 1 34

PCM Hospital 7 3 2 12

Prison Hospital 1 1

Private or NGO Hospital 7 1 3 11

Rokupa Government Hospital 1 2 1 4

Wilberforce Military Hospital 1 1

Government Clinic or PHU 1 2 3 10 1 1 18

Grand Total 62 56 31 109 248 102 246 22 24 900

While the “I did not pay a bribe” reports concentrated on few locations in Western Area

Urban, the “I Paid a Bribe” reports focused on the “Government Clinics and PHUs” in the

Districts. The relatively few reports on “I Paid a Bribe” from Western Area Urban mainly

came from Ola During Children’s Hospital.

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The overall distribution can represent the way in which service is delivered in the capital vis-

à-vis the Districts, where the former has many large hospitals and the service in the latter is

delivered at a multitude of smaller Clinics and PHUs.

The higher frequency of “I Paid a Reports” in the districts, could suggest that the challenges

with delivering Health Care services without invoking additional charges are higher in the

district than in the capital. The CSO animators reports that there are challenges with both

supplies and payment of staff in the districts, which could be the cause of such issues.

Water Sector

The Water Sector has an even lower level of reporting than the Electricity Sector with an

average of only 2% of the total number of reports (figure 12) and 3% in the 3rd quarter of

2017. Being a utility sector with a limited penetration, just like the Electricity Sector, similar

factors of limited distribution and infrequent interaction with service providers apply. The

extremely low level of reporting make the date even more vulnerable to representational

reporting and subject to a high level of volatility.

Figure 28: Disaggregation of Water Sector reports in Districts in Q3 2017

93% of all reports relating to the Water Sector derived from Western Area Urban in the 3rd

quarter of 2017. That is a significantly higher than the average of 71%. On the same token,

the ratio of reporting from the other districts declined correspondingly.

Figure 29: Disaggregation of Water Sector reports between Services in Q3 2017

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“New Connection” was the most frequently reported service (43%), as it also was the case for

the Electricity Sector. The second highest was “Illegal Connection” with 33%, which may

suggest challenges for the Water companies in limiting/controlling these. The dismantling of

Illegal Connection is also a human intervention and not an automatic, which makes it more

vulnerable for bribery.

Figure 30: Distribution of Water Sector reports between Services in 12 months

On an average since inception, Illegal Connection has constituted 17% of the Water Sector

reports and it is therefore significantly higher with 33% in the 3rd quarter of 2017. Otherwise,

figure 27 show the high degree of volatility of the data relating to the Water Sector, which is

a consequence of the low level of reporting.

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Figure 31: Disaggregation I Paid a Bribe reports in Districts and Services in Q3 2017

15 of the 36 I Paid a Bribe reports on “Illegal Connection” in Western Area Urban came from

Juba and 32 of 45 reports on “New Connection” from Portee. However, the GUMA Valley

Water Company has reported that they have not carried out any New Connections in that

area. Therefore, the reports could relate to other private service providers, as suggested by the

CSO animator in the area. This implies that an indication of the service provider could be a

useful addition to the PNB reporting platform.

4. Distribution of Method of Payment and Value of Payment per Sector

Paying a bribe cannot be reduced to the transfer of cash. Bribes can also be in Services and

Favour, Products or Sexual Favours. Knowledge on the nature of bribes for specific

sectors/services can be valuable in designing targeted sensitization and responses to these

sectors/services.

Figure 32: Distribution of Method of Payment in Q3 2017 Figure 33: Average Distribution of Method of Payment

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In the 3rd quarter, Cash had a high prevalence as the most reported method of payment; 96%

of all “I Paid a Bribe” reports. Products, Food and Animals constituted 1,6% and the rest less

than a percentage (figure 32), which is very close to the average distribution of the first 12

months of the programme (figure 33).

The extraordinarily high prevalence of cash as the reported method of payment, can have 2

main causes:

1. The cash is the simplest, easiest and most anonymous way to transfer value, and

therefore a preferred method of payments of bribes,

2. That there is an underreporting of bribes paid using other methods of payment, since

the payee may not recognize services or a favour as bribes, but considers it similar to

a legitimate social gesture.

If the former is the case, capturing method of payment is less relevant, since proportion of

bribes paid using other methods of payment are not statically significant. It is a latter, the

public should be further sensitized on what can constitute a bribe, so the public knows that

providing unwarranted services and favours also can constitute bribery.

Table 4: Method of Payment in Piloted Sectors

Cash Products,

Animals or Food Service and

Favours Sexual

Favours Other Grand Total

Education 963 32 12 22 16 1045

Electricity 205 3 208

Health Care 837 32 22 1 8 900

Police 1709 1 3 1 5 1719

Water 103 7 110

Other 211 1 1 1 11 225

Grand Total 4028 66 38 25 50 4207

Education and Health Care had the highest frequency of non-cash reported bribes, with

Bombali District accounting for 68% of all non-cash reports in Q3 and Western Area Urban

only 4%. Education had the vast majority of reports on Sexual Favours (88%) and 18 of the

22 reports came from a single chiefdom in Bombali District.

Table 5: Value of Payment in Q3

Edu

cati

on

Elec

tric

ity

Hea

lth

Car

e

Po

lice

Wat

er

Oth

er

Tota

l

0-5000 SLL 282 2 134 237 4 2 661

6000-10.000 SLL 286 10 236 318 9 3 862

11.000-50.000 SLL 295 50 414 818 21 57 1655

51.000-100.000 SLL 109 66 86 307 31 55 654

101.000-250.000 SLL 36 72 21 24 37 45 235

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251.000-500.000 SLL 13 8 6 11 8 48 94

Above 500.000 SLL 1 1 3 5 10

Other/Beyond Value 1 1 9 11

Sexual Favours 22 1 1 1 25

Total number of reports

1045 208 900 1719 110 225 4207

Total Mean Value in SLL of reported bribes

31.919.

500

22.233.0

00

27.781.

500

61.106.

500

12.560.5

00

34.341.5

00

189.942.50

0

Average Median Value per Bribery in SLL

31.232

106.889

30.937

35.568

114.186

159.728

45.539

The Police accounted for the highest total value of reported bribes paid in the 3rd quarter of

2017with a total of 61.106.500 LE. The Police also had the highest number of received reports.

“Other Sectors” followed with a total value of 34.341.500 LE, despite having received

relatively few reports. The average value for the reported bribes under “Other Sectors” was

much higher than the remaining sectors, so even with few report the total value exceeded that

of the remaining sectors.

In general, the average value of reported bribes is lowest in the most frequently reported sectors

(Police, Education and Health Care), while being highest in the less frequently reported sectors

(Electricity, Water, Other). As described previously, Water and Electricity are sectors where

there is less direct interaction between the public and the service provider. However, when the

interaction is required, for instance to carry out installations, the value of a potential bribe is

high. The opposite applies to the Police, Education and Health Care, where the service delivery

always involved human interaction. This makes it more vulnerable to bribery, but the value of

a potential bribe is relatively low.

5. Demographics of reporting

Figure 34: Distribution of Gender in Q3 2017 Figure 35: Average Distribution of Gender 12 months

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There is almost an equal gender distribution in the overall PNB reporting. While the overall

gender distribution is equal there are variances between the various sectors.

Figure 35: Gender distribution per sector in Q3 2017

Most sectors had a relatively equal gender distribution apart from Health Care, which is

primarily women reporting, and Police, where men accounted for the majority of reporting.

Figure 36: Age distribution in Q3 2017 Figure 37: Average age distribution 12 months

The age distribution of the 3rd quarter of 2017 was similar to the yearly average with a minor

increase in Above 50 Years reporting ratio and a minor decline in 30-49 years reporting.

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Figure 38: Age distribution per sector in Q3 2017

The youth (15-29 years) accounted for the majority of reporting to the Education sector. In the

Health sector, it was primarily young and adult women, whereas for the police, it is young and

adult men. The above 50 years old had the highest reporting ratio on Electricity, Water and

Others.

The above demographics of reporting reflects the user demographics in the various sectors;

Young people attends educational institutions, pregnant women and mothers take children for

Health Care, the commercial drivers are primarily men, the people able to have water and

electricity installed are of a certain age, before they afford accessing these services. That is the

reason why the 15-29 years have the majority of reporting for Education, Women for Health

Care, Men for Police and few young people reports on Electricity and Water.

6. Actions points for the PNB Programme

High dependence on CSO animators to encourage the public to report is a cause for concern

as this has the potential to increase the volatility of reporting thereby making trend analysis

less feasible and reduces the sustainability of the programme.

As a result, in order to encourage the public to make their reports directly into the PNB

Platform, the PNB Programme should focus more on the outreach activities that promote self-

reporting. This can be accomplished by focusing the communication on the positive

achievement of the PNB Programme. That is, the actions taken by the MDAs to reduce

bribery and improve service delivery, as well as further sensitizing the public on how to self-

report without a CSO animator being present.

The above requires that the PNB produces actionable data and provides support to the MDAs

in identifying areas of concern and possible actions to address these. Hence, the data

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capturing should be reviewed taking into consideration of the needs of MDAs and by also

intensifying engagements with the MDAs.