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    Home / Central Data Catalog / KHM_2020_HFPS-LSMS_V04_M / variable [F73]
central

COVID-19 High Frequency Phone Survey of Households 2020-2022, CSES

Cambodia, 2020 - 2022
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Reference ID
KHM_2020_HFPS-LSMS_v04_M
Producer(s)
World Bank Group
Metadata
DDI/XML JSON
Created on
Mar 22, 2021
Last modified
Dec 22, 2022
Page views
52576
Downloads
530
  • Study Description
  • Data Dictionary
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  • Data files
  • r1may2020_lsms_section00.dta
  • r1may2020_lsms_section01.dta
  • r1may2020_lsms_section02.dta
  • r1may2020_lsms_section03_1.dta
  • r1may2020_lsms_section03_2.dta
  • r1may2020_lsms_section04.dta
  • r1may2020_lsms_section05.dta
  • r1may2020_lsms_section06.dta
  • r1may2020_lsms_section07.dta
  • r1may2020_lsms_section10.dta
  • r1may2020_lsms_section11_1.dta
  • r1may2020_lsms_section11_2.dta
  • r1may2020_lsms_section12.dta
  • r2august2020_lsms_section00.dta
  • r2august2020_lsms_section01.dta
  • r2august2020_lsms_section02.dta
  • r2august2020_lsms_section02c.dta
  • r2august2020_lsms_section02d.dta
  • r2august2020_lsms_section02e.dta
  • r2august2020_lsms_section05.dta
  • r2august2020_lsms_section06.dta
  • r2august2020_lsms_section07.dta
  • r2august2020_lsms_section08.dta
  • r2august2020_lsms_section11_1.dta
  • r2august2020_lsms_section11_2.dta
  • r2august2020_lsms_section11_3.dta
  • r2august2020_lsms_section11a.dta
  • r2august2020_lsms_section12.dta
  • r3october2020_lsms_section00.dta
  • r3october2020_lsms_section01.dta
  • r3october2020_lsms_section02.dta
  • r3october2020_lsms_section02c.dta
  • r3october2020_lsms_section03.dta
  • r3october2020_lsms_section05.dta
  • r3october2020_lsms_section06.dta
  • r3october2020_lsms_section07.dta
  • r3october2020_lsms_section08.dta
  • r3october2020_lsms_section11_1.dta
  • r3october2020_lsms_section11_2.dta
  • r3october2020_lsms_section11_3.dta
  • r3october2020_lsms_section11a.dta
  • r3october2020_lsms_section12.dta
  • r3october2020_lsms_section13.dta
  • r4december2020_lsms_section00.dta
  • r4december2020_lsms_section01.dta
  • r4december2020_lsms_section02.dta
  • r4december2020_lsms_section02c.dta
  • r4december2020_lsms_section05.dta
  • r4december2020_lsms_section06.dta
  • r4december2020_lsms_section07.dta
  • r4december2020_lsms_section08.dta
  • r4december2020_lsms_section10.dta
  • r4december2020_lsms_section11_1.dta
  • r4december2020_lsms_section11_2.dta
  • r4december2020_lsms_section11_3.dta
  • r4december2020_lsms_section11a.dta
  • r4december2020_lsms_section12.dta
  • r4december2020_lsms_section13.dta
  • r5march2021_lsms_section00.dta
  • r5march2021_lsms_section01.dta
  • r5march2021_lsms_section02.dta
  • r5march2021_lsms_section02c.dta
  • r5march2021_lsms_section05.dta
  • r5march2021_lsms_section06.dta
  • r5march2021_lsms_section07.dta
  • r5march2021_lsms_section07_1.dta
  • r5march2021_lsms_section08.dta
  • r5march2021_lsms_section11_1.dta
  • r5march2021_lsms_section11_2.dta
  • r5march2021_lsms_section11_3.dta
  • r5march2021_lsms_section11a.dta
  • r5march2021_lsms_section12.dta
  • r6february2022_cses_section00.dta
  • r6february2022_cses_section01.dta
  • r6february2022_cses_section02.dta
  • r6february2022_cses_section02c.dta
  • r6february2022_cses_section02d.dta
  • r6february2022_cses_section05.dta
  • r6february2022_cses_section06.dta
  • r6february2022_cses_section07.dta
  • r6february2022_cses_section08.dta
  • r6february2022_cses_section10.dta
  • r6february2022_cses_section11_1.dta
  • r6february2022_cses_section11_2.dta
  • r6february2022_cses_section11_3.dta
  • r6february2022_cses_section11a.dta
  • r6february2022_cses_section12.dta
  • r6february2022_cses_section14.dta
  • r6february2022_cses_section15_1.dta
  • r6february2022_cses_section15_2.dta
  • r7april2022_cses_section00.dta
  • r7april2022_cses_section01.dta
  • r7april2022_cses_section02.dta
  • r7april2022_cses_section02c.dta
  • r7april2022_cses_section02d.dta
  • r7april2022_cses_section05.dta
  • r7april2022_cses_section06.dta
  • r7april2022_cses_section07.dta
  • r7april2022_cses_section08.dta
  • r7april2022_cses_section10.dta
  • r7april2022_cses_section11_1.dta
  • r7april2022_cses_section11_2.dta
  • r7april2022_cses_section11_3.dta
  • r7april2022_cses_section11a.dta
  • r7april2022_cses_section12.dta
  • r7april2022_cses_section14_1.dta
  • r7april2022_cses_section14_2.dta
  • r7april2022_cses_section15_1.dta
  • r7april2022_cses_section15_2.dta

Province (province)

Data file: r6february2022_cses_section00.dta

Overview

Valid: 1706
Invalid: -
Minimum: 1
Maximum: 25
Type: Discrete
Decimal: 0
Start: 38
End: 39
Width: 2
Range: 1 - 25
Format: Numeric

Questions and instructions

Categories
Value Category Cases
1 Banteay Meanchey 70
4.1%
2 Battambang 97
5.7%
3 Kampong Cham 79
4.6%
4 Kampong Chhnang 68
4%
5 Kampong Speu 60
3.5%
6 Kampong Thom 73
4.3%
7 Kampot 90
5.3%
8 Kandal 85
5%
9 Koh Kong 43
2.5%
10 Kratie 56
3.3%
11 Mondul Kiri 39
2.3%
12 Phnom Penh 228
13.4%
13 Preah Vihear 51
3%
14 Prey Veng 64
3.8%
15 Pursat 64
3.8%
16 Ratanak Kiri 34
2%
17 Siemreap 96
5.6%
18 Preah Sihanouk 41
2.4%
19 Stung Treng 29
1.7%
20 Svay Rieng 75
4.4%
21 Takeo 61
3.6%
22 Otdar Meanchey 44
2.6%
23 Kep 20
1.2%
24 Pailin 52
3%
25 Tboung Khmum 87
5.1%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
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