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refugee_pads:000098
23
2
Ethiopia Socioeconomic Survey
1,109
1,138
named
named
survey
⟦Ethiopia Socioeconomic Survey⟧ — Water Quality Testing (ESS-WQT) 2016
true
null
refugee_pads:000098
27
1
meteorological- and hydrological-related information
995
1,047
descriptive
descriptive
other
the use of ⟦meteorological- and hydrological-related information⟧ can deliver enormous socioeconomic benefits to society
true
null
refugee_pads:000098
30
1
social assessment prepared for the WASHP
881
921
descriptive
descriptive
other
a ⟦social assessment prepared for the WASHP⟧ has been updated
false
null
refugee_pads:000098
31
0
social M&E surveys
1,192
1,210
descriptive
descriptive
survey
conducting ⟦social M&E surveys⟧ with beneficiaries before the midterm review and post-implementation
true
null
refugee_pads:000098
31
0
gender-disaggregated data
1,339
1,364
descriptive
vague
other
The surveys will use ⟦gender-disaggregated data⟧ to measure and verify citizens’ perceptions
true
null
refugee_pads:000098
36
1
data from the water
697
716
vague
vague
other
using ⟦data from the water⟧ resources management information system
true
null
refugee_pads:000098
40
1
HH surveys
286
296
descriptive
descriptive
survey
Regular WASH MIS<br>reports, ⟦HH surveys⟧, and Project progress<br>reports
true
null
refugee_pads:000098
41
0
HH surveys
484
494
descriptive
descriptive
survey
Regular WASH MIS<br>reports, ⟦HH surveys⟧, and Project progress<br>reports
true
null
refugee_pads:000098
42
1
HH surveys
88
98
descriptive
descriptive
survey
reports, ⟦HH surveys⟧, and Project progress<br>reports
true
null
refugee_pads:000098
45
0
water resource data
1,253
1,272
descriptive
descriptive
other
It measures the use of the ⟦water resource data⟧ (meteorology, hydrology<br>and groundwater) to inform<br>design and management
true
null
refugee_pads:000098
45
1
water resource data
40
59
descriptive
descriptive
other
It measures the use of the ⟦water resource data⟧ (meteorology, hydrology<br>and groundwater) to inform<br>design and management
true
null
refugee_pads:000098
49
0
social assessment
1,142
1,159
descriptive
descriptive
other
WASHP and findings from the ⟦social assessment⟧
false
null
refugee_pads:000098
54
0
Beneficiary survey
712
730
descriptive
descriptive
survey
⟦Beneficiary survey⟧ at<br>mid-term and Project<br>completion
true
null
refugee_pads:000098
58
2
financial data
425
439
vague
vague
other
They will collect and aggregate all ⟦financial data⟧ and information from implementing entities
true
null
refugee_pads:000098
59
2
budget tracking records
1,175
1,198
descriptive
descriptive
administrative
maintain up-to-date ⟦budget tracking records⟧ to ensure budget availability before processing payments
true
null
refugee_pads:000098
63
0
quarterly unaudited IFRs
1,549
1,573
descriptive
descriptive
report
using ⟦quarterly unaudited IFRs⟧ will continue to be followed for this new program
true
null
refugee_pads:000098
63
1
IFRs
107
111
descriptive
named
report
cash forecasts included in the ⟦IFRs⟧[1]
true
null
refugee_pads:000098
67
2
budget tracking record
371
393
descriptive
descriptive
administrative
Maintaining ⟦budget tracking record⟧[2] on the accounting system in use
true
null
refugee_pads:000098
73
0
assessed records
1,670
1,686
descriptive
descriptive
administrative
The ⟦assessed records⟧[3] show that the construction bureau takes between 18 to 46 days
true
null
refugee_pads:000098
76
0
RWRDBs
964
970
named
named
other
WDC, WRDF, ⟦RWRDBs⟧[4]
false
null
refugee_pads:000098
80
2
Gender profiles for the MoWIE
162
191
descriptive
named
report
⟦Gender profiles for the MoWIE⟧[5] show that the majority of the positions in the ministry are occupied by men
true
null
refugee_pads:000098
81
1
social M&E surveys
800
818
descriptive
descriptive
survey
conducting ⟦social M&E surveys⟧[6] with beneficiaries
true
null
refugee_pads:000098
81
1
genderdisaggregated data
1,038
1,062
descriptive
vague
other
The surveys will use ⟦genderdisaggregated data⟧[7] to measure and verify citizens’ perceptions
true
null
refugee_pads:000098
82
0
regional baseline reports
535
560
descriptive
descriptive
report
using data collected from ⟦regional baseline reports⟧[8]
true
null
refugee_pads:000098
82
0
Health Management Information System
562
598
named
named
system
data collected from regional baseline reports, ⟦Health Management Information System⟧[9] and
true
null
refugee_pads:000098
82
0
Education Management Information System
603
642
descriptive
named
system
⟦Education Management Information System⟧[10] reports
true
null
refugee_pads:000098
82
0
National WASH Inventory
1,568
1,591
named
named
database
findings will be further refined during the planned ⟦National WASH Inventory⟧[11]
true
null
refugee_pads:000098
82
1
National WASH Inventory
401
424
named
named
database
regular updating of the ⟦National WASH Inventory⟧[12] as well as use of the data for decision making
true
null
refugee_pads:000098
83
1
MIS
625
628
named
named
system
Information from the ⟦MIS⟧[13] will be the basis for selecting best-performing woredas
true
null
refugee_pads:000098
83
1
MIS
770
773
named
named
system
regular updating of information into the ⟦MIS⟧[14]
true
null
refugee_pads:000098
86
1
WASH baseline data
1,357
1,375
descriptive
descriptive
other
Level of WASH access and coverage based on the ⟦WASH baseline data⟧[15] compiled from regions
true
null
refugee_pads:000098
86
1
health MIS
1,901
1,911
descriptive
named
system
data collected from the ⟦health MIS⟧[16] at the woreda level
true
null
refugee_pads:000098
86
2
health MIS
133
143
descriptive
named
system
data collected from the ⟦health MIS⟧[17] at the woreda level
true
null
refugee_pads:000098
86
2
woreda-level health MIS
244
267
descriptive
descriptive
system
data from the ⟦woreda-level health MIS⟧[18]
true
null
refugee_pads:000098
87
1
water resources information
930
957
vague
descriptive
other
build on available ⟦water resources information⟧[19] to identify a mix of appropriate technology
true
null
refugee_pads:000098
88
1
baseline data
1,787
1,800
vague
vague
other
The ⟦baseline data⟧[20] collected for the preparation of this Project indicate a negative correlation
true
null
refugee_pads:000098
88
2
baseline data
64
77
vague
vague
other
The ⟦baseline data⟧[21] collected for the preparation of this Project indicate a negative correlation
true
null
refugee_pads:000098
90
2
2016 Ethiopia Socio Economic Survey
957
992
named
named
survey
According to the findings of the ⟦2016 Ethiopia Socio Economic Survey⟧[22], 70 percent of the samples
true
null
refugee_pads:000098
93
2
hydromet data
356
369
descriptive
descriptive
other
support the enhancement of ⟦hydromet data⟧[23] collection, analysis
true
null
refugee_pads:000098
94
0
abbreviated WASH baseline data
1,822
1,852
descriptive
descriptive
other
⟦abbreviated WASH baseline data⟧[24], July 2018
true
null
refugee_pads:000098
94
1
abbreviated WASH baseline data
11
41
descriptive
descriptive
other
and (iii) ⟦abbreviated WASH baseline data⟧[25], July 2018
true
null
refugee_pads:000098
95
2
National WASH Inventory
370
393
named
named
database
financing the second ⟦National WASH Inventory⟧[26], development of the MIS
true
null
refugee_pads:000098
97
1
local data
1,048
1,058
vague
vague
other
in the absence of reliable and actual ⟦local data⟧[27], estimates from global and regional studies are used
true
null
refugee_pads:000098
97
2
Ethiopia WASH Poverty Diagnostic
528
560
named
named
report
the bottom 40th percentile of the wealth distribution having approximately 50 percent of the cumulative share of the susceptibility and risk (⟦Ethiopia WASH Poverty Diagnostic⟧[28])
true
null
refugee_pads:000098
98
0
contract registers
422
440
descriptive
descriptive
administrative
contracts obtained from the ⟦contract registers⟧[29] of the regions
true
null
refugee_pads:000098
99
1
Ethiopia Time Use Survey
1,168
1,192
named
named
survey
about 56 percent of rural households had to travel less than an hour, but a large share (37 percent) had to travel between 1.0 and 2.5 hours, and about 15 percent had to travel even longer to fetch water (⟦Ethiopia Time Use Survey⟧[1], CSA, December 2014)
true
null
refugee_pads:000098
99
1
Data on water and sanitation
1,518
1,546
descriptive
descriptive
other
⟦Data on water and sanitation⟧[2] are from J. Wolf et al.
true
null
refugee_pads:000099
10
1
inequality-adjusted 2013 Human Development Index
1,269
1,317
named
named
indicator
As revealed by the World Bank’s ⟦inequality-adjusted 2013 Human Development Index⟧[3] (HDI)
true
null
refugee_pads:000099
10
1
World Bank EdStats
1,521
1,539
named
named
database
⟦World Bank EdStats⟧[4] accessed 10.7.14
true
null
refugee_pads:000099
11
1
Trends in International Mathematics and Science Study
1,264
1,317
named
named
survey
The level of public school students was 10 percent lower than that of private schools in the 2011 ⟦Trends in International Mathematics and Science Study⟧[5] (TIMSS) results
true
null
refugee_pads:000099
11
1
2004 household survey
1,356
1,377
descriptive
descriptive
survey
Indeed, based on the ⟦2004 household survey⟧[6], poverty and education are highly correlated in Lebanon.
true
null
refugee_pads:000099
11
1
2013 Human Capital Index
1,631
1,655
named
named
indicator
World Economic Forum’s ⟦2013 Human Capital Index⟧[7]
true
null
refugee_pads:000099
11
1
World Bank Ed Stats
1,795
1,814
named
named
database
8 ⟦World Bank Ed Stats⟧[8]
true
null
refugee_pads:000099
35
0
D-RASATI survey
846
861
named
named
survey
Statistics provided by the ⟦D-RASATI survey⟧[9] (2011)
true
null
refugee_pads:000099
35
1
database
594
602
descriptive
vague
database
Project preparation included the preparation of a ⟦database⟧[10] which accounts for many of the school facilities characteristics
true
null
refugee_pads:000099
5
0
Institutional Data
471
489
descriptive
vague
other
**⟦Institutional Data⟧[11]**
false
null
refugee_pads:000099
9
0
available but incomplete data
1,615
1,644
vague
vague
other
Based on ⟦available but incomplete data⟧[12], significant progress was made in reducing poverty
true
null
refugee_pads:000099
9
1
available but incomplete data
34
63
vague
vague
other
Based on ⟦available but incomplete data⟧[13], significant progress was made in reducing poverty
true
null
refugee_pads:000100
14
1
demand forecasts
750
766
descriptive
descriptive
estimates
The ⟦demand forecasts⟧[14] of these companies were evaluated
true
null
refugee_pads:000100
16
1
international tendering information
448
483
descriptive
descriptive
other
The cost estimates reflect end-1997 prices and are based on the latest ⟦international tendering information⟧[15] available for similar works
true
null
refugee_pads:000100
37
3
EPRS
475
479
named
named
other
Sources: EPBiH, EPM and ⟦EPRS⟧[16]
true
null
refugee_pads:000100
41
1
Actual cost data
291
307
descriptive
descriptive
other
⟦Actual cost data⟧[17] for the first half of 1997 were extrapolated.
true
null
refugee_pads:000100
41
2
economic data
798
811
vague
descriptive
other
All data shown in Table A4.5 are ⟦economic data⟧[18].
true
null
refugee_pads:000100
43
1
data presented in Bechtel Consulting
1,534
1,570
descriptive
named
other
The estimates for the comparison are based partly on ⟦data presented in Bechtel Consulting⟧[19], "Coal and Thermal Power Cost Study for Bosnia and Herzegovina"
true
null
refugee_pads:000100
43
2
1998 contracts for gas imports into BiH
547
586
descriptive
descriptive
other
a gas import price of US$134 per thousand cubic meters was selected based on ⟦1998 contracts for gas imports into BiH⟧[20]
true
null
refugee_pads:000100
47
0
ELEKTROPRIVREDA BiH Balance Sheets
85
119
named
named
other
**BOSNIA AND HERZEGOVINA SECOND ELECTRIC POWER RECONSTRUCTION PROJECT ⟦ELEKTROPRIVREDA BiH Balance Sheets⟧[21]**
true
null
refugee_pads:000100
53
0
ELEKTROPRIVREDA REPUBLIKA SRPSKA Balance Sheets
86
133
named
named
other
**BOSNIA AND HERZEGOVINA SECOND ELECTRIC POWER RECONSTRUCTION PROJECT ⟦ELEKTROPRIVREDA REPUBLIKA SRPSKA Balance Sheets⟧[22]**
true
null
refugee_pads:000100
55
1
Project Financing Data
1,774
1,796
named
descriptive
other
The estimated annual disbursement schedule by IDA fiscal year is shown in the ⟦Project Financing Data⟧[23] on page 1.
true
null
refugee_pads:000100
56
0
record of withdrawals on the IDA credit
1,008
1,047
descriptive
descriptive
administrative
These accounts would include: (i) a ⟦record of withdrawals on the IDA credit⟧[24] with copies of all disbursement requests and underlying documentation
true
null
refugee_pads:000100
56
0
record of transactions on the special Accounts
1,130
1,176
descriptive
descriptive
administrative
and (ii) a ⟦record of transactions on the special Accounts⟧[25] and the copies of the bank statements on this account.
true
null
refugee_pads:000100
67
5
1996 data
238
247
vague
vague
estimates
Note: ⟦1996 data⟧[26] are preliminary estimates.
true
null
refugee_pads:000100
68
1
Export price index
467
485
descriptive
descriptive
indicator
⟦Export price index⟧[27]**(1987=100)**
true
null
refugee_pads:000100
68
1
Import price index
603
621
descriptive
descriptive
indicator
⟦Import price index⟧[28] (1987=100)
true
null
refugee_pads:000100
68
2
Import price index
43
61
descriptive
descriptive
indicator
⟦Import price index⟧[29] (1987=100)
true
null
refugee_pads:000101
102
1
project data
361
373
vague
vague
other
building a stronger evidence base on ⟦project data⟧[30]
true
null
refugee_pads:000101
103
0
routine data from NUSAF3
1,700
1,724
named
named
other
⟦routine data from NUSAF3⟧ should be fed to the District Planning unit
true
null
refugee_pads:000101
104
0
NUSAF2 database
267
282
named
named
database
communicate with key systems such as the Integrated Financial Management System/IFMS and the ⟦NUSAF2 database⟧ at the Northern Uganda Data Center (NUDC)
true
null
refugee_pads:000101
104
0
data from the MIS
662
679
descriptive
named
system
data from routine project monitoring drawing upon information in periodic reports from the districts as well as ⟦data from the MIS⟧
true
null
refugee_pads:000101
112
0
data collected by the project team
1,781
1,815
descriptive
descriptive
other
The analysis was prepared using the ⟦data collected by the project team⟧
true
null
refugee_pads:000101
112
0
data collected under NUSAF 1 and 2
1,841
1,875
descriptive
descriptive
other
including other earlier ⟦data collected under NUSAF 1 and 2⟧
true
null
refugee_pads:000101
112
1
data collected under NUSAF 1 and 2
31
65
descriptive
descriptive
other
team, including other earlier ⟦data collected under NUSAF 1 and 2⟧
true
null
refugee_pads:000101
113
1
data on food and cash crop production
478
515
descriptive
descriptive
other
The analysis of the economic rate of return uses the ⟦data on food and cash crop production⟧, value-addition/agribusiness and non-agricultural/vocational enterprises
true
null
refugee_pads:000101
113
1
enterprise data
1,075
1,090
descriptive
descriptive
other
All the ⟦enterprise data⟧ used for estimating the rates of return are from the following regions of Northern Uganda
true
null
refugee_pads:000101
114
1
Uganda National Panel Survey
722
750
named
named
survey
The welfare analysis uses the ⟦Uganda National Panel Survey⟧ (UNPS)
true
null
refugee_pads:000101
115
1
Uganda Monthly Market Monitor
1,125
1,154
named
named
report
World Food Program, 2015. ⟦Uganda Monthly Market Monitor⟧, January 2015 Issue 1
true
null
refugee_pads:000101
116
0
objective data
1,988
2,002
vague
vague
other
The rate of return analysis is limited to LIS component for which ⟦objective data⟧ is available
true
null
refugee_pads:000101
116
1
objective data
221
235
vague
vague
other
The rate of return analysis is limited to LIS component for which ⟦objective data⟧ is available
true
null
refugee_pads:000101
117
0
Enterprise data
1,445
1,460
descriptive
descriptive
other
⟦Enterprise data⟧ upon which indicative activity budgets have been estimated are presented in Annex 2 of this report
true
null
refugee_pads:000101
119
0
Enterprise budget data
21
43
descriptive
descriptive
other
## **Attachment 6.2: ⟦Enterprise budget data⟧**
true
null
refugee_pads:000101
119
1
NUSAF 2 field data
430
448
named
named
other
Source: Based on ⟦NUSAF 2 field data⟧
true
null
refugee_pads:000101
123
1
NUSAF2
996
1,002
named
named
other
in ⟦NUSAF2⟧, deaths of some animals have been reported
false
null
refugee_pads:000101
123
1
NUSAF2
1,100
1,106
named
named
other
reported in ⟦NUSAF2⟧, especially with communities close to towns
false
null
refugee_pads:000101
124
0
NUSAF2
1,223
1,229
named
named
other
some deaths of bulls in ⟦NUSAF2⟧ have been
false
null
refugee_pads:000101
125
1
NUSAF2
320
326
named
named
other
estimated at 21.6 percent by 2013 in ⟦NUSAF2⟧ mainly due New Castle disease
false
null
refugee_pads:000101
125
2
NUSAF2
349
355
named
named
other
This has been experienced in ⟦NUSAF2⟧
false
null
refugee_pads:000101
12
1
Uganda National Household Survey
417
449
named
named
survey
_Sources_ : a/ ⟦Uganda National Household Survey⟧[21] 2012/13
true
null
refugee_pads:000101
12
1
Uganda Demographic Health Survey 2011
462
499
named
named
survey
b. ⟦Uganda Demographic Health Survey 2011⟧[22]
true
null
refugee_pads:000101
12
1
Uganda National Household Survey
504
536
named
named
survey
c. ⟦Uganda National Household Survey⟧[23] 2012/13
true
null
refugee_pads:000101
12
1
Uganda Demographic Health Survey 2011
549
586
named
named
survey
d. ⟦Uganda Demographic Health Survey 2011⟧[24]
true
null
refugee_pads:000101
14
0
monitoring data on the project
776
806
descriptive
descriptive
administrative
recent ⟦monitoring data on the project⟧ show that the income of the households that participated in these schemes increased
true
null