MLI_2014_RIMA_v01_EN_M_v01_A_OCS DDI_MLI_2014_RIMA_v01_EN_M_v01_A_OCS_FAO Ellestina Jumbe Office of Chief Statistician Nesstar Publisher MLI_2014_RIMA_v01_EN_M_v01_A_OCS Resilience Index Measurement and Analysis, Mali, 2014 RIMA, MLI, 2014 MLI_2014_RIMA_v01_EN_M_v01_A_OCS Food and Agriculture Organization Malian Association of Research Action for Development Nesstar Publisher FAO RIMA Team Other Household Survey [hh/oth] Agriculture Demographic characteristics Health Employment Income Shocks Food expenditure and consumption Food security Livestock Social services Community needs Prices Mali is a Sahelian country, landlocked and structurally vulnerable to food insecurity and malnutrition. The economy is heavily dependent on the primary sector: agriculture, livestock, fishing and forestry account for 68.0% of the active population1 . This sector is itself dependent on exogenous factors, mainly climatic, such as recurrent droughts. In 2018, the prevalence of food insecurity at the national level was 19.1%, of which 2.6% was severely food insecure. The most affected regions were Kidal, Gao, Timbuktu, Mopti and Kayes. The Global Food Crisis Network Partnership Programme baseline studies are designed to feed into the overall monitoring, evaluation, accountability and learning programme of each project. In this regard, the baseline study has short, medium and long-term objectives. Mali Regional Households Sample survey data [ssd] The EAC-I 2014 has been designed to have national coverage, including both urban and rural areas in all the regions of the country except Kidal. The domains were defined as the entire country, district of Bamako, other urban areas, and rural areas; and in the rural areas: agricultural zones, agro-pastoral zones and pastoral zones. Taking this into account, 51 explicit sample strata were selected. The target population was drawn from households in all regions of Mali except Kidal which was not accessible for security reasons. Kidal also has very low population density.The sample was chosen through a random two stage process: - In the first stage, 1070 enumeration areas (EAs) were selected with Probability Proportional to Size (PPS) using the 2009 Census of Population as the base for the sample, and the number of households as a measure of size. - In the second stage o 3 households were selected with equal probability in each of the rural EAs o 9 households were selected with equal probability in each of the urban EAs The total estimated size of the sample for the survey was 4,218. Computer Assisted Personal Interview [capi] Please refer to the Questionnaires for the value labels of the variables. In order to produce nationally representative statistics with the data weights or expansion factors need to be applied. These survey weights adjust for differences in the probability of selection within the sample. To accurately use the datasets, the data must be weighted to reflect the distribution of the full population in the country. A population weight was calculated for the households in the sample. It is found in the file named EACIPOIDS.dta. 1. Data Entry & Data cleaning Data entry was performed at the CPS/SDR using a CSPro application designed by an international consultant recruited by the LSMS team. The data entry program allows three types of data checks: (1) range checks; (2) intra-record check to verify inconsistencies pertinent to the particular module of the questionnaire; and (3) inter-record checks to determine inconsistencies pertinent between the different modules of the questionnaire. Data entry for the first visit was done from August 11th, 2014 to November 30th, 2014 and, from February 9th 2015 to March 27th, 2015 for the second visit. Data cleaning was done from May 2015 to July 2015. Data cleaning was done in a CSPro application. The data cleaning focused on more intra-record and inter-record checks. The users shall not take any action with the purpose of identifying any individual entity (i.e. person, household, enterprise, etc.) in the micro dataset(s). If such a disclosure is made inadvertently, no use will be made of the information, and it will be reported immediately to FAO FAO. Resilience Index Measurement and Analysis (RIMA), Mali, 2014 - 2015. Dataset downloaded from https://microdata.fao.org. The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses consumption.NSDstat 3804 24 Nesstar 200801 income.NSDstat 3804 268 Nesstar 200801 mli_14_pindex.NSDstat 45 11 Nesstar 200801 weight_conv_table.NSDstat 41066 9 Nesstar 200801 Grappe 3804 0 1 1070 567.13 329.455 Numero du menage 3804 0 1 9 5.629 2.545 1 156 2 153 3 962 4 155 5 157 6 954 7 153 8 161 9 953 food consumption annual - xof - imp 3804 0 0 3078400 399505.789 311768.811 3804 0 0 9850.88 1278.419 997.66 dummy for consuming auto-consumed food 3804 0 0 1 0.559 0.497 0 1679 1 2125 Coefficients d'extrapolation 3804 0 15.901 6453.211 470.628 459.891 region 3804 0 1 9 1 Kayes 548 2 Koulikoro 511 3 Sikasso 524 4 Ségou 595 5 Mopti 518 6 Tombouctou 261 7 Gao 123 9 Bamako 724 Cercle 3804 0 1 8 2.98 2.161 1 1633 2 391 3 349 4 333 5 428 6 333 7 292 8 45 Arrondissement 3804 0 1 96 54.225 35.8 1=rural/ 0=urban 3804 0 0 1 0.631 0.483 0 1405 1 2399 total expenditure annual - xof 3804 0 7500 13290600 1927209.095 2031559.49 total expenditure annual - usd 3804 0 12.56 22256.838 3227.362 3402.11 monetary value of consumed food 7 days XOF 3801 3 0 951425 26688.827 42241.351 monetary value of consumed food monthly XOF 3801 3 0 4134621.25 115982.015 183568.841 monetary value of consumed food monthly XOF percapita 3801 3 0 722841 15389.993 26129.796 monetary value of consumed food monthly USD percapita 3801 3 0 1210.491 25.773 43.758 monetary value of consumed food monthly USD percapita, imputed 3801 3 0 258.473 21.516 22.415 , imputed 3804 0 68700 12764000 2148581.237 1847284.302 , imputed 3804 0 128.928 26070.676 4227.154 3415.545 Household food consumption score 3804 0 0 119 64.988 24.134 (sum) calories_pc 3801 3 23.693 1060478.341 89440.408 86004.121 simpson diversity index 3801 3 0 1 0.479 0.194 Shannon Diversity Index 3801 3 0 2.038 0.937 0.392 HH dietary diversity score 3801 3 0 12 8.582 2.117 0 1 1 15 2 27 3 25 4 79 5 158 6 317 7 461 8 587 9 701 10 690 11 542 12 198 Sysmiss 3 Grappe 3804 0 1 1070 567.13 329.455 Numero du menage 3804 0 1 9 5.629 2.545 1 156 2 153 3 962 4 155 5 157 6 954 7 153 8 161 9 953 region 3768 36 1 9 1 Kayes 541 2 Koulikoro 506 3 Sikasso 517 4 Ségou 591 5 Mopti 512 6 Tombouctou 256 7 Gao 121 9 Bamako 724 Sysmiss 36 Cercle 3741 63 1 8 2.959 2.157 1 1626 2 383 3 338 4 324 5 425 6 318 7 282 8 45 Sysmiss 63 Arrondissement 3355 449 1 96 56.398 36.281 1=rural/ 0=urban 3804 0 0 1 0.631 0.483 0 1405 1 2399 Coefficients d'extrapolation 3804 0 15.901 6453.211 470.628 459.891 Income from safety nets programs 3804 0 0 65000 1395.306 6067.261 total value of other income imputed - xof 3804 0 -2871050 773958.313 -34297.643 192549.63 total value of other income imputed - usd 3804 0 -4807.946 1296.094 -57.436 322.449 total income from wage employment imputed - xof 3804 0 0 12240000 223812.477 777942.913 total income from wage employment imputed - usd 3804 0 0 20497.471 374.803 1302.767 Net income from livestock and by-products, imputed - xof 3804 0 -1150500 1470530 -6760.811 77918.509 Net income from livestock and by-products, imputed -usd 3804 0 -1926.662 2462.594 -11.322 130.485 Net income from non farm enterprises imputed, xof 3804 0 -29030000 22836000 60615.18 1572891.511 Net income from non farm enterprises imputed, usd 3804 0 -48614.508 38241.852 101.508 2634.011 Annual transfers received, xof 3804 0 0 6000000 73156.138 325316.398 Annual transfers give away, xof 3804 0 0 2400000 16393.336 85053.067 Annual net transfers imputed, xof 3804 0 -2400000 8950000 16868.835 275870.347 Annual net transfers imputed, usd 3804 0 -4019.112 14987.938 28.249 461.981 total value of other income imputed - xof 3804 0 0 300104992 179033.924 6880606.831 total value of other income less income from heritage, loterie, vente de bien im 3804 0 0 3000000 18475.768 138716.929 total value of other income imputed - usd 3804 0 0 502564.813 299.816 11522.471 total value of other income less income from heritage, loterie, vente de bien im 3804 0 0 5023.89 30.94 232.3 total income from fishing imputed - xof 3804 0 -1300000 26509600 45260.158 600951.59 total income from fishing imputed - usd 3804 0 -2177.019 44393.77 75.794 1006.372 food consumption annual - xof - imp 3804 0 26650 2600752384 1543694.571 42158026.772 3804 0 85.28 8322408 4939.823 134905.692 dummy for consuming auto-consumed food 3804 0 0 1 0.635 0.481 0 1388 1 2416 total expenditure annual - xof 3804 0 7500 13290600 1927209.095 2031559.49 total expenditure annual - usd 3804 0 12.56 22256.838 3227.362 3402.11 , imputed 3804 0 117150 14603500 2608163.992 2041937.791 , imputed 3804 0 265.587 31957.078 5715.53 4152.158 head of hh is bambara (majority ethnic groupe) 3804 0 0 1 0.354 0.478 0 2459 1 1345 female headed hh 3790 14 0 1 0.0583 0.234 0 3569 1 221 Sysmiss 14 age head of hh 3688 116 18 65 51.267 11.13 head of hh married 3804 0 0 1 0.898 0.302 0 387 1 3417 head of hh widowed 3804 0 0 1 0.0507 0.219 0 3611 1 193 share of male hh labor 3804 0 0 1 0.459 0.198 share of female hh labor 3804 0 0 1 0.537 0.198 hh labor age>14 but <60 3804 0 0 43 4.606 3.313 hh male labor age>14 but <60 3804 0 0 19 2.168 1.787 0 276 1 1480 2 848 3 552 4 296 5 161 6 83 7 39 8 27 9 19 10 11 11 3 12 4 13 2 16 2 19 1 hh female labor age>14 but <60 3804 0 0 24 2.438 1.896 number of people in the hh 3804 0 1 83 9.615 6.703 number of males in the hh 3804 0 0 41 4.745 3.608 number of females in the hh 3804 0 0 42 4.87 3.661 average years of education in hh 3802 2 0 16 2.353 3.053 years of education head of hh 3634 170 0 16 2.519 4.725 0 2677 1 9 2 16 3 28 4 55 5 81 6 130 7 34 8 49 9 105 10 30 11 46 12 65 13 139 14 11 15 43 16 116 Sysmiss 170 average years of education among hh members 15-60yrs 3780 24 0 16 2.711 3.72 number of child in hh 3804 0 0 40 4.486 3.807 number of elder in hh 3804 0 0 28 0.523 0.866 child dependency ratio: nber children/hhsize 3804 0 0 1 0.434 0.197 elder dependency ratio: nber elder/hhsize 3804 0 0 1 0.0559 0.0967 dependency ration: nber dependents/hhsize 3804 0 0 40 5.009 4.079 nber of dependents 3804 0 0 3320 73.449 145.996 ave years of education among hh members >15 yrs 3795 9 0 16 2.599 3.627 (mean) educhigh 3802 2 0 16 5.813 5.273 0 1240 1 68 2 101 3 133 4 169 5 177 6 243 7 185 8 193 9 314 10 100 11 141 12 198 13 210 14 50 15 90 16 190 Sysmiss 2 was the child (7-17ans) enrolled in 2013/2014? 2050 1754 0 1 0.898 0.303 0 209 1 1841 Sysmiss 1754 Was a health services or traditional healer consulted while sick? 2242 1562 0 1 0.787 0.409 0 477 1 1765 Sysmiss 1562 Household owns tractor 3804 0 0 1 0.00368 0.0606 0 3790 1 14 Household owns sprayer 3804 0 0 1 0.0444 0.206 0 3635 1 169 Household owns planter 3804 0 0 0 0 0 0 3804 Household owns plough 3804 0 0 1 0.375 0.484 0 2377 1 1427 Household owns hoe 3804 0 0 1 0.147 0.354 0 3246 1 558 Household owns harrow 3804 0 0 1 0.0576 0.233 0 3585 1 219 Household owns animals 3804 0 0 1 0.321 0.467 0 2582 1 1222 Household owns cart 3804 0 0 1 0.345 0.476 0 2490 1 1314 Household owns hive 3804 0 0 1 0.00841 0.0913 0 3772 1 32 Household owns huller 3804 0 0 1 0.00447 0.0667 0 3787 1 17 Household owns pump 3804 0 0 1 0.0284 0.166 0 3696 1 108 Household owns scales 3804 0 0 1 0.0092 0.0955 0 3769 1 35 Household owns bundling 3804 0 0 1 0.00131 0.0362 0 3799 1 5 Household owns cutter 3804 0 0 1 0.0549 0.228 0 3595 1 209 Household owns trough 3804 0 0 1 0.0649 0.246 0 3557 1 247 Household owns mower 3804 0 0 1 0.0515 0.221 0 3608 1 196 Household owns mill 3804 0 0 1 0.00499 0.0705 0 3785 1 19 Household owns spreader 3804 0 0 1 0.000263 0.0162 0 3803 1 1 Household owns milkingm 3804 0 0 1 0.00158 0.0397 0 3798 1 6 Household owns other 3804 0 0 1 0.0523 0.223 0 3605 1 199 Nber of ntractor 3804 0 0 4 0.00499 0.0958 0 3790 1 11 2 2 4 1 Nber of nsprayer 3804 0 0 6 0.0607 0.324 0 3635 1 125 2 33 3 7 4 2 5 1 6 1 Nber of nplanter 3804 0 0 13 0.236 0.74 0 3266 1 324 2 147 3 33 4 15 5 11 6 3 7 1 8 1 9 1 10 1 13 1 Nber of nplough 3804 0 0 8 0.57 0.886 0 2377 1 889 2 394 3 103 4 31 5 5 6 4 8 1 Nber of nhoe 3804 0 0 80 0.638 2.473 Nber of nharrow 3804 0 0 12 0.0973 0.544 0 3585 1 146 2 48 3 6 4 11 5 2 6 1 8 1 10 3 12 1 Nber of nanimals 3804 0 0 34 0.862 1.654 Nber of ncart 3804 0 0 10 0.408 0.642 0 2490 1 1124 2 159 3 21 4 8 5 1 10 1 Nber of nhive 3804 0 0 60 0.0636 1.252 Nber of nhuller 3804 0 0 2 0.00552 0.0871 0 3787 1 13 2 4 Nber of npump 3804 0 0 4 0.0355 0.232 0 3696 1 88 2 16 3 1 4 3 Nber of nscales 3804 0 0 4 0.0113 0.132 0 3769 1 30 2 3 3 1 4 1 Nber of nbundling 3804 0 0 1 0.00131 0.0362 0 3799 1 5 Nber of ncutter 3804 0 0 9 0.105 0.525 0 3595 1 97 2 76 3 16 4 9 5 6 6 2 7 2 9 1 Nber of ntrough 3804 0 0 20 0.17 0.902 0 3557 1 96 2 76 3 20 4 25 5 4 6 13 7 3 9 2 10 4 12 2 16 1 20 1 Nber of nmower 3804 0 0 20 0.158 0.869 0 3608 1 42 2 70 3 25 4 20 5 17 6 7 7 6 8 2 10 6 20 1 Nber of nmill 3804 0 0 18 0.0108 0.307 0 3785 1 14 2 3 3 1 18 1 Nber of nspreader 3804 0 0 1 0.000263 0.0162 0 3803 1 1 Nber of nmilkingm 3804 0 0 7 0.00342 0.122 0 3798 1 4 2 1 7 1 Nber of nother 3804 0 0 20 0.263 1.38 0 3605 1 15 2 32 3 26 4 40 5 20 6 23 7 11 8 5 9 4 10 11 12 3 14 2 15 3 16 1 18 1 20 2 total value of agricultural assets 3804 0 0 6100500 128323.667 274660.752 total value of agricultural assets - imputed 3804 0 0 3038000 112984.025 203797.461 total value of animals owned 3804 0 0 18575000 508506.923 1125448.264 total value of animals owned - imputed 3804 0 0 4682250 411041.31 738769.231 3804 0 0 1 0.543 0.498 0 1737 1 2067 Household owns bull 3804 0 0 1 0.333 0.471 0 2539 1 1265 Household owns cow 3804 0 0 1 0.188 0.391 0 3090 1 714 Household owns calf 3804 0 0 1 0.116 0.321 0 3361 1 443 Household owns sheep 3804 0 0 1 0.42 0.494 0 2208 1 1596 Household owns pig 3804 0 0 1 0.0113 0.106 0 3761 1 43 Household owns donkey 3804 0 0 1 0.341 0.474 0 2505 1 1299 Household owns camel 3804 0 0 1 0.0134 0.115 0 3753 1 51 Household owns poultry 3804 0 0 1 0.333 0.471 0 2536 1 1268 Household owns rabbit 3804 0 0 1 0.00289 0.0537 0 3793 1 11 Nber of npigs owned by HH, imputed 3804 0 0 50 0.0786 1.339 Nber of nbulls owned by HH, imputed 3804 0 0 34 1.215 2.462 Nber of ncows owned by HH, imputed 3804 0 0 80.5 1.346 4.589 Nber of ncalves owned by HH, imputed 3804 0 0 43.5 0.613 2.552 Nber of nsheeps owned by HH, imputed 3804 0 0 80 4.509 8.263 Nber of ndonkeys owned by HH, imputed 3804 0 0 22 0.633 1.13 Nber of npoultrys owned by HH, imputed 3804 0 0 262 5.857 12.269 Nber of ncamels owned by HH, imputed 3804 0 0 25 0.0418 0.637 Nber of nrabbits owned by HH, imputed 3804 0 0 30 0.0255 0.643 Tropical Livestock Units: bulls 3804 0 0 17 0.607 1.231 Tropical Livestock Units: sheep 3804 0 0 8 0.451 0.826 Tropical Livestock Units: pigs 3804 0 0 10 0.0157 0.268 0 3761 0.200000002980232 6 0.400000005960464 11 0.600000023841858 5 0.800000011920929 9 1.20000004768372 2 1.39999997615814 1 1.60000002384186 2 2 1 2.20000004768372 1 4 2 6 1 8.80000019073486 1 10 1 Tropical Livestock Units: poultry (chicken, turkeys) 3804 0 0 2.62 0.0586 0.123 Tropical Livestock Units: donkeys, mules, horses 3804 0 0 13.2 0.38 0.678 Tropical Livestock Units: cow 3804 0 0 40.25 0.673 2.295 Tropical Livestock Units: calf 3804 0 0 21.75 0.306 1.276 Tropical Livestock Units: rabbit 3804 0 0 0.3 0.000255 0.00643 0 3793 0.00999999977648258 1 0.0199999995529652 2 0.0399999991059303 1 0.0599999986588955 2 0.0799999982118607 1 0.0899999961256981 1 0.119999997317791 1 0.170000001788139 1 0.299999982118607 1 Tropical Livestock Units: camels 3804 0 0 25 0.0418 0.637 Tropical Livestock Units: cattle (cows, calves, bulls) 3804 0 0 65 1.587 4.189 Tropical Livestock Units: total 3804 0 0 65 2.534 5.084 Number of salon household owns 3804 0 0 18 0.356 1.114 0 3183 1 371 2 68 3 38 4 74 5 30 6 24 7 7 8 2 9 1 10 4 12 1 18 1 Number of ktable household owns 3804 0 0 25 0.28 1.187 Number of bed household owns 3804 0 0 46 1.971 2.857 Number of ofurniture household owns 3804 0 0 20 0.367 1.23 0 3228 1 268 2 124 3 69 4 52 5 17 6 22 7 4 8 5 9 1 10 10 16 1 17 2 20 1 Number of iron household owns 3804 0 0 10 0.18 0.545 0 3253 1 478 2 48 3 10 4 8 5 4 8 1 10 2 Number of stove household owns 3804 0 0 20 0.082 0.478 0 3573 1 185 2 35 3 8 4 1 9 1 20 1 Number of sewing household owns 3804 0 0 6 0.0389 0.297 0 3710 1 65 2 15 3 8 4 3 5 1 6 2 Number of moulinex household owns 3804 0 0 6 0.00841 0.139 0 3782 1 17 2 3 3 1 6 1 Number of foyer household owns 3804 0 0 10 0.283 0.872 0 3327 1 127 2 211 3 72 4 47 5 11 6 3 7 2 8 1 9 1 10 2 Number of fridge household owns 3804 0 0 5 0.101 0.391 0 3508 1 226 2 56 3 10 4 2 5 2 Number of fan household owns 3804 0 0 16 0.498 1.335 0 3027 1 330 2 178 3 111 4 73 5 33 6 19 7 8 8 8 9 6 10 5 11 1 12 1 13 1 14 1 15 1 16 1 Number of aircond household owns 3804 0 0 9 0.0268 0.262 0 3741 1 41 2 14 3 5 4 1 5 1 9 1 Number of waterheater household owns 3804 0 0 5 0.0116 0.137 0 3768 1 31 2 4 5 1 Number of radio household owns 3804 0 0 43 0.961 1.33 Number of tv household owns 3804 0 0 9 0.476 0.775 0 2398 1 1146 2 179 3 49 4 20 5 3 6 3 7 4 8 1 9 1 Number of dvd household owns 3804 0 0 8 0.222 0.536 0 3099 1 609 2 69 3 19 4 3 5 3 6 1 8 1 Number of decodeur household owns 3804 0 0 7 0.15 0.42 0 3295 1 462 2 38 3 6 4 1 5 1 7 1 Number of car household owns 3804 0 0 6 0.0676 0.331 0 3604 1 163 2 25 3 7 4 3 5 1 6 1 Number of bike household owns 3804 0 0 23 1.186 1.799 Number of photo household owns 3804 0 0 6 0.0276 0.245 0 3732 1 56 2 8 3 2 4 4 5 1 6 1 Number of video household owns 3804 0 0 8 0.00815 0.159 0 3784 1 16 2 2 3 1 8 1 Number of hifi household owns 3804 0 0 10 0.00999 0.193 0 3781 1 17 2 4 3 1 10 1 Number of tel household owns 3804 0 0 72 2.204 2.667 Number of computer household owns 3804 0 0 9 0.0678 0.39 0 3639 1 110 2 34 3 14 4 2 5 3 6 1 9 1 Number of generator household owns 3804 0 0 2 0.00894 0.0996 0 3772 1 30 2 2 Number of pirogue household owns 3804 0 0 9 0.0379 0.274 0 3697 1 84 2 16 3 5 4 1 9 1 Household owns salon 3804 0 0 1 0.163 0.37 0 3183 1 621 Household owns ktable 3804 0 0 1 0.0994 0.299 0 3426 1 378 Household owns bed 3804 0 0 1 0.647 0.478 0 1343 1 2461 Household owns ofurniture 3804 0 0 1 0.151 0.359 0 3228 1 576 Household owns iron 3804 0 0 1 0.145 0.352 0 3253 1 551 Household owns stove 3804 0 0 1 0.0607 0.239 0 3573 1 231 Household owns sewing 3804 0 0 1 0.0247 0.155 0 3710 1 94 Household owns moulinex 3804 0 0 1 0.00578 0.0758 0 3782 1 22 Household owns foyer 3804 0 0 1 0.125 0.331 0 3327 1 477 Household owns fridge 3804 0 0 1 0.0778 0.268 0 3508 1 296 Household owns fan 3804 0 0 1 0.204 0.403 0 3027 1 777 Household owns aircond 3804 0 0 1 0.0166 0.128 0 3741 1 63 Household owns waterheater 3804 0 0 1 0.00946 0.0968 0 3768 1 36 Household owns radio 3804 0 0 1 0.623 0.485 0 1436 1 2368 Household owns tv 3804 0 0 1 0.37 0.483 0 2398 1 1406 Household owns dvd 3804 0 0 1 0.185 0.389 0 3099 1 705 Household owns decodeur 3804 0 0 1 0.134 0.34 0 3295 1 509 Household owns car 3804 0 0 1 0.0526 0.223 0 3604 1 200 Household owns bike 3804 0 0 1 0.579 0.494 0 1601 1 2203 Household owns photo 3804 0 0 1 0.0189 0.136 0 3732 1 72 Household owns video 3804 0 0 1 0.00526 0.0723 0 3784 1 20 Household owns hifi 3804 0 0 1 0.00605 0.0775 0 3781 1 23 Household owns tel 3804 0 0 1 0.82 0.384 0 685 1 3119 Household owns computer 3804 0 0 1 0.0434 0.204 0 3639 1 165 Household owns generator 3804 0 0 1 0.00841 0.0913 0 3772 1 32 Household owns pirogue 3804 0 0 1 0.0281 0.165 0 3697 1 107 Rural: agricultural wealth index 3804 0 -1.626 24.622 0.0182 2.271 Non-agricultural wealth index, rural + urban 3804 0 -1.764 25.175 -0.0281 2.274 Urban: non-agricultural wealth index 1405 2399 -1.62 25.175 1.165 2.955 Rural: non-agricultural wealth index 2399 1405 -1.764 20.517 -0.727 1.329 land owned, hectacres 3804 0 0 527.338 8.092 28.216 Land owned that is fallow, hectares 3804 0 0 137.237 0.168 2.866 land owned on which there is a construction against erosion 3804 0 0 12 0.105 0.655 0 3640 1 79 2 31 3 19 4 13 5 8 6 4 7 3 8 3 9 2 10 1 12 1 hh is landless 3804 0 0 1 0.426 0.495 0 2184 1 1620 land ownership quintiles 3804 0 1 5 2.747 1.628 1 1620 3 688 4 713 5 783 HH is connected to drinking water system 3804 0 0 1 0.178 0.383 0 3127 1 677 Nber of rooms in the dwelling 3804 0 1 40 4.914 3.853 time to main drinking water point during dry season, min 2485 1319 0 90 8.128 10.202 HH is connected to electric system 3804 0 0 1 0.284 0.451 0 2723 1 1081 HH uses electricity as main source of lightening 3804 0 0 1 0.331 0.471 0 2543 1 1261 HH participe to a waste disposal system (depotoire public, ramassage 3804 0 0 1 0.393 0.488 0 2310 1 1494 HH uses improved sanitations (W.C avec chasse d'eau, latrines couvertes) 3804 0 0 1 0.598 0.49 0 1531 1 2273 Community has primary 3300 504 0 1 0.815 0.388 0 610 1 2690 Sysmiss 504 Community has secondary 3300 504 0 1 0.291 0.454 0 2339 1 961 Sysmiss 504 Community has literacy 3300 504 0 1 0.442 0.497 0 1842 1 1458 Sysmiss 504 Community has health 3300 504 0 1 0.608 0.488 0 1293 1 2007 Sysmiss 504 Community has drugstore 3300 504 0 1 0.445 0.497 0 1833 1 1467 Sysmiss 504 Community has post 3300 504 0 1 0.134 0.34 0 2859 1 441 Sysmiss 504 Community has market 3300 504 0 1 0.525 0.499 0 1568 1 1732 Sysmiss 504 Community has microf 3300 504 0 1 0.322 0.467 0 2237 1 1063 Sysmiss 504 Community has station 3300 504 0 1 0.176 0.381 0 2719 1 581 Sysmiss 504 Community has road 3300 504 0 1 0.805 0.396 0 644 1 2656 Sysmiss 504 Community has state 3300 504 0 1 0.41 0.492 0 1947 1 1353 Sysmiss 504 Community has agorg 3300 504 0 1 0.314 0.464 0 2263 1 1037 Sysmiss 504 distance in km to dist_primary 1460 2344 0 600 14.818 35.135 distance in km to dist_secondary 1876 1928 0 500 43.376 60.07 distance in km to dist_literacy 924 2880 0 150 19.252 25.789 distance in km to dist_health 2939 865 0 600 71.451 84.312 distance in km to dist_drugstore 1595 2209 0 325 21.344 31.838 distance in km to dist_post 2151 1653 0 500 30.128 44.874 distance in km to dist_market 2529 1275 0 250 27.747 33.807 distance in km to dist_microf 1746 2058 0 200 23.585 30.403 distance in km to dist_station 2040 1764 0 500 32.727 49.906 distance in km to dist_road 2006 1798 0 400 32.183 40.179 distance in km to dist_state 2336 1468 0 670 39.956 69.74 distance in km to dist_agorg 2194 1610 0 301 28.962 41.291 distance in km to dist_radio 2195 1609 0 500 27.995 53.125 HH has savings: 1=yes/0=no 3804 0 0 1 0.52 0.5 0 1825 1 1979 HH has access to credit: 1=yes/ 0=no 3013 791 0 1 0.238 0.426 0 2296 1 717 Sysmiss 791 Amount of last credit contacted imputed, xof 3804 0 0 4000000 42968.555 193326.948 Le menage s'est preoccuper d'avoir suffisament a  manger durant les 7 derniers jr 3804 0 0 1 0.251 0.433 0 2851 1 953 Le menage a ete face a  une situation oa il n'y avait pas suffisament a  manger po 3804 0 0 1 0.187 0.39 0 3094 1 710 Lack of diversification, hh eating mos of the time the same thing 3643 161 0 1 0.621 0.485 0 1379 1 2264 Sysmiss 161 hh was hungry (not enough food/no money) 3804 0 0 1 0.179 0.383 0 3124 1 680 HH received informal transfers 3804 0 0 1 0.284 0.451 0 2722 1 1082 HH received cereals 3804 0 0 1 0.143 0.35 0 3261 1 543 HH had a child who benefited from school feeding 3804 0 0 1 0.00999 0.0995 0 3766 1 38 HH participated to public works/food for work programs 3804 0 0 1 0.0071 0.084 0 3777 1 27 HH benefited from child programs: nutrition/healthcare for under 5/ bednets 3804 0 0 1 0.279 0.449 0 2741 1 1063 HH benefited from a cash transfer program 3804 0 0 1 0.0147 0.12 0 3748 1 56 HH benefited from a scholarship 3804 0 0 1 0.0226 0.149 0 3718 1 86 HH received pensions: retirement/disability/widow 3804 0 0 1 0.0421 0.201 0 3644 1 160 HH received subventions for ag inputs 1525 2279 0 1 0.0223 0.148 0 1491 1 34 Sysmiss 2279 HH received at least one type of formal transfers last 12 months 3804 0 0 1 0.415 0.493 0 2227 1 1577 Shock faced by hh last 3 years:drought 3804 0 0 1 0.42 0.494 0 2208 1 1596 Shock faced by hh last 3 years:flood 3804 0 0 1 0.0702 0.255 0 3537 1 267 Shock faced by hh last 3 years:crop_disease 3804 0 0 1 0.0773 0.267 0 3510 1 294 Shock faced by hh last 3 years:anim_disease 3804 0 0 1 0.0849 0.279 0 3481 1 323 Shock faced by hh last 3 years:low_price 3804 0 0 1 0.0505 0.219 0 3612 1 192 Shock faced by hh last 3 years:high_input_p 3804 0 0 1 0.158 0.365 0 3203 1 601 Shock faced by hh last 3 years:high_food_p 3804 0 0 1 0.277 0.448 0 2750 1 1054 Shock faced by hh last 3 years:notransfer 3804 0 0 1 0.0174 0.131 0 3738 1 66 Shock faced by hh last 3 years:loss_agrev 3804 0 0 1 0.0376 0.19 0 3661 1 143 Shock faced by hh last 3 years:bankrupt 3804 0 0 1 0.0281 0.165 0 3697 1 107 Shock faced by hh last 3 years:loss_salary 3804 0 0 1 0.0134 0.115 0 3753 1 51 Shock faced by hh last 3 years:loss_job 3804 0 0 1 0.0229 0.15 0 3717 1 87 Shock faced by hh last 3 years:illness 3804 0 0 1 0.127 0.333 0 3321 1 483 Shock faced by hh last 3 years:death 3804 0 0 1 0.057 0.232 0 3587 1 217 Shock faced by hh last 3 years:divorse 3804 0 0 1 0.0179 0.133 0 3736 1 68 Shock faced by hh last 3 years:theft 3804 0 0 1 0.0355 0.185 0 3669 1 135 Shock faced by hh last 3 years:violence 3804 0 0 1 0.0896 0.286 0 3463 1 341 Shock faced by hh last 3 years:locust 3804 0 0 1 0.0255 0.158 0 3707 1 97 pc expenditures, hhexp/hhsize 3804 0 12712.5 9113300 414173.492 537224.856 rural pcexp quintiles 2399 1405 1 5 2.899 1.376 1 489 2 532 3 515 4 458 5 405 Sysmiss 1405 rural pcexp deciles 2399 1405 1 10 5.31 2.78 1 223 2 266 3 263 4 269 5 246 6 269 7 230 8 228 9 210 10 195 Sysmiss 1405 rural & urban pcexp deciles 3804 0 1 10 5.555 2.865 1 345 2 388 3 392 4 375 5 383 6 365 7 396 8 388 9 367 10 405 urban pcexp quintiles 1405 2399 1 5 2.933 1.418 1 309 2 271 3 293 4 269 5 263 Sysmiss 2399 urban pcexp deciles 1405 2399 1 10 5.371 2.877 1 157 2 152 3 130 4 141 5 141 6 152 7 135 8 134 9 133 10 130 Sysmiss 2399 rural & urban pcexp quintiles 3804 0 1 5 3.025 1.411 1 733 2 767 3 748 4 784 5 772 region 38 7 1 9 1 Kayes 7 2 Koulikoro 7 3 Sikasso 7 4 Segou 0 5 Mopti 8 6 Tombouctou 5 7 Gao 3 9 Bamako 1 Sysmiss 7 cercle 45 0 1 8 3.778 2.088 1 8 2 7 3 7 4 6 5 6 6 5 7 5 8 1 region 45 0 Bamako 1 Gao 3 Kayes 7 Koulikoro 7 Mopti 8 Sikasso 7 Sigou 7 Tombouctou 5 prix_riz 45 0 241.667 500 349.312 45.323 inflation-riz 45 0 -26.471 50 -1.07 10.767 prix_mais 45 0 87.5 700 230.552 135.033 inflation-maiss 45 0 -10 2 -10.71429 1 -16.66667 2 -20 1 -25 1 -25.49019 1 -33.33333 3 -50 1 -67.03297000000001 1 -7.142857 1 -9.090909 1 -91.53543000000001 1 . 10 0 6 100 3 12.5 2 20 1 33.33333 1 436.1111 1 6.153851 1 7.352941 1 7.692307 1 76.66665999999999 1 8.333325 1 prix_mil 45 0 81.667 400 201.932 64.905 inflation-mil 45 0 -11.11111 2 -12.08791 1 -12.5 1 -13.93443 1 -14.28571 2 -16.66666 1 -16.66667 4 -2 1 -20 2 -20.2 1 -22.5 1 -26.66667 1 -27.08333 1 -28 1 -37.5 1 -38.09524 1 -38.46154 1 -39.43764 1 -43.39622 1 -5.263155 1 -50 1 -6.25 1 -6.666667 1 -91.11111 1 . 1 0 10 25 1 41.66667 1 50 1 7.5 1 prix_sorgho 45 0 90.625 400 201.214 72.465 inflation-sorgho 45 0 -10.71429 1 -11.76471 1 -12.5 2 -13.20755 1 -13.46153 1 -14.28571 1 -15.71428 1 -16.11185 1 -16.66667 1 -24.16667 1 -25 2 -25.92592 1 -33.33333 1 -41.66667 1 -46.66667 1 -55 1 -59.43878 1 -60 1 -64.24779 1 . 4 0 8 1.250004 1 10.34483 1 12.5 2 13.33333 1 14.28571 1 17.64706 1 20 1 20.68966 1 33.33333 1 87.49997999999999 1 90.47620000000001 1 Grappe 40983 83 1 1070 520 298.165 itemid 41066 0 501 623 547.067 36.181 unit 40983 83 1 99 7.165 10.804 price per unit 40478 588 0 999999 3323.962 13107.675 conversion in kg 40107 959 0 999 44.002 169.991 price per kg 38555 2511 0 18000000 11013.967 182726.767 label 41063 0 Abats et tripes 1 Ananas 1 Arachides decortiquees 1036 Arachides en coques 983 Arome (Maggi, Jumbo, etc) 1 Aubergine 1 Autres cereales 1 Autres farines de cereales 1 Autres fruits (pamplemousse, goyaves,etc) 1 Autres huiles 1 Autres legumes en feuilles 1 Autres legumes frais n. d. a 1 Autres legumes secs n . a. 1 Autres noix 1 Autres produits alimentaires 1 Autres produits laitiers 1 Autres tisanes et infusions 1 Autres tubercules n.d.a. 1 Autres viandes (porc, etc) 1 Autres epices et condiments (ail, gingembre,etc) 1 Banane douce 1 Beignets, galettes 1 Beurre 1 Beurre de karite 1287 Biscuits 1 Ble 340 Boisson gazeuse 1095 Boissons alcoolisees 1 Bonbons 1 Cacao/chocolat 1 Cafe en boisson chaude pris hors du domicile 1 Cafe en boite ou en sachet 1 Canne a  sucre 1 Carotte 1 Charcuterie 1 Cigarette 1 Citron 1 Concentre de tomate 1037 Concombre 1 Conserves d'autres produits de peche 1 Conserves de poisson 1 Conserves de viandes 1 Courge, courgette 1 Cube alimentaire (Maggi, Jumbo) 1585 Dattes 1 Eau minerale, autres boisson non alcoolisees 1 Farine de ble importe 1213 Farine de ble local 657 Farine de manioc (attieke, gari,etc.) 1 Farine de maiss 125 Farine de mil 77 Feuilles d'oseille 499 Feuilles de baobab 768 Feuilles de haricot 1 Fonio 872 Fromage 1 Gibiers 1 Gombo frais 639 Gombo sec 903 Haricot vert 1 Huile d'arachide 1 Huile de coton 913 Huile de palme 563 Huile de soja 1 Igname 625 Jujube 1 Jus de fruit 1 Jus en poudre 1 Lait caille 982 Lait en poudre 1 Lait frais 1104 Mangue 1 Manioc 1 Maiss 1453 Melon 1 Miel 1 Mil 1908 Niebe/ Haricots secs 1081 Noix de cola 1 Noix de karite 1 Oignon frais 995 Orange 1 Pain 1005 Pain de singe 1 Pastaque 1 Patate douce 1 Pate d'arachide 954 Pates alimentaires 1363 Patisseries (gateaux, croissants) 1 Petit dejeuner pris a  l'exterieur 1 Petit pois 1 Petit pois secs 1 Piment 815 Plantain 455 Pois sucres 1 Poisson frais 1 Poisson fume 1 Poisson seche 1 Poivron frais 1 Pomme de terre 1 Riz 2272 Salade (laitue, choux) 1 Sel 1472 Sorgho 1880 Sucre 1573 Tabac 1 Tamarin 1 Taro, macabo 1 The en paquet ou en sachet 1888 Tomate fraiche 761 Tomate sechee 284 Viande d'autres oiseaux 1 Viande de bÅ“uf 1323 Viande de chameau 1 Viande de chavre 1 Viande de mouton 1188 Viande de poulet 1010 Yaourt 1 Zaban 1 Å’ufs 1 kcal 41050 16 0 900 312.547 229.497 41066 0 2 3 1 master only (1) 0 2 using only (2) 83 3 matched (3) 40983 4 missing updated (4) 0 5 nonmissing conflict (5) 0