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    Home / Central Data Catalog / HFPS / KHM_2020_HFPS-LSMS_V04_M / variable [F91]
hfps

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
DOI
https://doi.org/10.48529/m4bs-r206
Producer(s)
World Bank Group
Collection(s)
High-Frequency Phone Surveys
Metadata
Documentation in PDF DDI/XML JSON
Study website
Created on
Mar 03, 2021
Last modified
Mar 05, 2021
Page views
256386
Downloads
4993
  • Study Description
  • Data Description
  • Documentation
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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: r7april2022_cses_section00.dta

Overview

Valid: 1698
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 51
3%
2 Battambang 98
5.8%
3 Kampong Cham 101
5.9%
4 Kampong Chhnang 61
3.6%
5 Kampong Speu 54
3.2%
6 Kampong Thom 74
4.4%
7 Kampot 88
5.2%
8 Kandal 72
4.2%
9 Koh Kong 43
2.5%
10 Kratie 70
4.1%
11 Mondul Kiri 37
2.2%
12 Phnom Penh 135
8%
13 Preah Vihear 61
3.6%
14 Prey Veng 85
5%
15 Pursat 59
3.5%
16 Ratanak Kiri 37
2.2%
17 Siemreap 84
4.9%
18 Preah Sihanouk 44
2.6%
19 Stung Treng 37
2.2%
20 Svay Rieng 90
5.3%
21 Takeo 64
3.8%
22 Otdar Meanchey 55
3.2%
23 Kep 24
1.4%
24 Pailin 62
3.7%
25 Tboung Khmum 112
6.6%
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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