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    Home / Central Data Catalog / KHM_2020_HFPS-LSMS_V04_M / variable [F106]
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
52373
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

Why is [NAME] not currently attending school? (s14q6)

Data file: r7april2022_cses_section14_1.dta

Overview

Valid: 118
Invalid: 1830
Minimum: 1
Maximum: 96
Type: Discrete
Decimal: 0
Start: 18
End: 19
Width: 2
Range: 1 - 96
Format: Numeric

Questions and instructions

Categories
Value Category Cases
1 Schools closed due to coronavirus 3
2.5%
2 Schools closed for holidays 0
0%
3 Had enough/completed schooling 0
0%
4 Awaiting admission 0
0%
5 No school nearby/lack of teachers 0
0%
6 No time/no interest 11
9.3%
7 Lack of money 59
50%
8 Got married/ marital obligation 1
0.8%
9 Death of parents 0
0%
10 Too young to attend 0
0%
11 Too old to attend 0
0%
12 Domestic obligation 11
9.3%
13 Conflict (militancy/ insurgency) 0
0%
14 Got job / is working 17
14.4%
15 Worried about risk of contracting the virus 0
0%
96 Other (specify) 16
13.6%
Sysmiss 1830
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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