Addressing Extreme Poverty in Bangladesh – The Case of Monga 2008 - 2009, Round 3
Bangladesh, 2009
Created on
Sep 29, 2011
Last modified
Mar 29, 2019
Page views
148546
Downloads
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- Data files
- access
- identity
- price_grocery
- respondent_info
- sec_1_a
- sec_1_b
- sec_2
- sec_3
- sec_4
- sec_5_1_4
- sec_5_5
- sec_6_1
- sec_6_2
- sec_6_3
- sec_6_4_5
- sec_6_6
- sec_7
- sec_8_1
- sec_8_2
- hh_id_001
- hh_sec1a_001
- hh_sec2_001
- hh_sec3_001
- hh_sec5a_001
- hh_sec5b_001
- hh_sec5c_001
- hh_sec6a_001
- hh_sec6b_001
- hh_sec6c_001
- hh_sec6d_001
- hh_sec6e_001
- hh_sec6f1_001
- hh_sec6f2_001
- hh_sec6f3_001
- hh_sec6f4_001
- hh_sec6f5_001
- hh_sec7_001
- hh_sec8a1
- hh_sec8a3
- hh_sec8a4
- hh_sec8a5
- hh_sec8a23
- hh_sec8b
- hh_sec9a_001
- hh_sec9b1_1_001
- hh_sec9b2_1_001
- hh_sec9d1_001
- hh_sec9d2_001
- hh_sec10a_001
- hh_sec10b_001
- hh_sec10c_001
- hh_sec11a_001
- hh_sec11b_001
- hh_sec11c_001
- hh_sec11d_001
- hh_sec11e_001
- hh_sec12ab_001
Where did you move to when left this household this most recent time? (If within (q14_2)
Data file: hh_sec9b1_1_001
Overview
Valid:
329
Invalid:
5956
Type:
Discrete
Decimal:
0
Start:
54
End:
55
Width:
2
Range:
1 - 64
Format:
Numeric
Questions and instructions
Categories
| Value | Category | Cases | |
|---|---|---|---|
| 1 | Bagerhat | 0 |
0%
|
| 2 | Bandarban | 0 |
0%
|
| 3 | Barguna | 0 |
0%
|
| 4 | Barisal | 0 |
0%
|
| 5 | Bhola | 0 |
0%
|
| 6 | Bogra | 46 |
14%
|
| 7 | Brahamanbaria | 1 |
0.3%
|
| 8 | Chandpur | 1 |
0.3%
|
| 9 | Chittagong | 4 |
1.2%
|
| 10 | Chuadanga | 0 |
0%
|
| 11 | Comilla | 21 |
6.4%
|
| 12 | Cox'S Bazar | 0 |
0%
|
| 13 | Dhaka | 91 |
27.7%
|
| 14 | Dinajpur | 12 |
3.6%
|
| 15 | Faridpur | 0 |
0%
|
| 16 | Feni | 3 |
0.9%
|
| 17 | Gaibandha | 4 |
1.2%
|
| 18 | Gazipur | 14 |
4.3%
|
| 19 | Gopalganj | 0 |
0%
|
| 20 | Habiganj | 0 |
0%
|
| 21 | Joypurhat | 21 |
6.4%
|
| 22 | Jamalpur | 6 |
1.8%
|
| 23 | Jessore | 0 |
0%
|
| 24 | Jhalokati | 0 |
0%
|
| 25 | Jhenaidah | 0 |
0%
|
| 26 | Khagrachhari | 1 |
0.3%
|
| 27 | Khulna | 0 |
0%
|
| 28 | Kishoreganj | 8 |
2.4%
|
| 29 | Kurigram | 1 |
0.3%
|
| 30 | Kushtia | 0 |
0%
|
| 31 | Lakshmipur | 0 |
0%
|
| 32 | Lalmonirhat | 2 |
0.6%
|
| 33 | Madaripur | 0 |
0%
|
| 34 | Magura | 0 |
0%
|
| 35 | Manikganj | 5 |
1.5%
|
| 36 | Meherpur | 0 |
0%
|
| 37 | Maulvibazar | 0 |
0%
|
| 38 | Munshiganj | 11 |
3.3%
|
| 39 | Mymensingh | 0 |
0%
|
| 40 | Naogaon | 1 |
0.3%
|
| 41 | Narail | 0 |
0%
|
| 42 | Narayanganj | 9 |
2.7%
|
| 43 | Narsingdi | 1 |
0.3%
|
| 44 | Natore | 0 |
0%
|
| 45 | Nawabganj | 0 |
0%
|
| 46 | Netrakona | 0 |
0%
|
| 47 | Nilphamari | 0 |
0%
|
| 48 | Noakhali | 3 |
0.9%
|
| 49 | Pabna | 3 |
0.9%
|
| 50 | Panchagarh | 0 |
0%
|
| 51 | Patuakhali | 0 |
0%
|
| 52 | Pirojpur | 0 |
0%
|
| 53 | Rajshahi | 1 |
0.3%
|
| 54 | Rajbari | 0 |
0%
|
| 55 | Rangamati | 1 |
0.3%
|
| 56 | Rangpur | 4 |
1.2%
|
| 57 | Shariatpur | 1 |
0.3%
|
| 58 | Satkhira | 0 |
0%
|
| 59 | Sirajganj | 4 |
1.2%
|
| 60 | Sherpur | 2 |
0.6%
|
| 61 | Sunamganj | 0 |
0%
|
| 62 | Sylhet | 6 |
1.8%
|
| 63 | Tangail | 39 |
11.9%
|
| 64 | Thakurgaon | 2 |
0.6%
|
| Sysmiss | 5956 |
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.