{"type":"survey","doc_desc":{"title":"MLI_2017_IEFCP_v01_M_v01_A_OCS","idno":"DDI_MLI_2017_IEFCP_v01_M_v01_A_OCS","producers":[{"name":"Office of Chief Statistician","abbreviation":"OCS","affiliation":"Food and Agriculture Organization","role":"Metadata adapted for FAM"},{"name":"Thu-Hien Dao","abbreviation":"","affiliation":"Food and Agriculture Organization","role":"Metadata producer"},{"name":"Development Economics Data Group","abbreviation":"DECDG","affiliation":"The World Bank","role":"Metadata adapted for World Bank Microdata Library"}],"prod_date":"2023-01-31","version_statement":{"version":"Version 01 (January 2023): This metadata was downloaded from the FAO website (https:\/\/microdata.fao.org\/index.php\/catalog) and it is identical to FAO version (MLI_2017_IEFCP_v01_EN_M_v01_A_OCS). The following two metadata fields were edited - Document ID and Survey ID."}},"study_desc":{"title_statement":{"idno":"MLI_2017_IEFCP_v01_M_v01_A_OCS","title":"Impact Evaluation of the FAO\u2019s Cash(+) Project in Mali 2017","alt_title":"IEFCP 2017"},"authoring_entity":[{"name":"Silvio Daidone","affiliation":"Food and Agriculture Organization"},{"name":"Mari Kangasniemi","affiliation":"Food and Agriculture Organization"},{"name":"Thu-Hien Dao","affiliation":"Food and Agriculture Organization"}],"production_statement":{"producers":[{"name":"CEPAP de Nioro du Sahel","affiliation":"","role":"Data collection"}],"funding_agencies":[{"name":"Food and Agriculture Organization","abbreviation":"FAO","role":"Funding"}]},"distribution_statement":{"contact":[{"name":"Silvio Daidone","affiliation":"Food and Agriculture Organization","email":"Silvio.Daidone@fao.org","uri":""},{"name":"Thu-Hien Dao","affiliation":"Food and Agriculture Organization","email":"ThuHien.Dao@fao.org","uri":""},{"name":"Mari Kangasniemi","affiliation":"Food and Agriculture Organization","email":"Mari.Kangasniemi@fao.org","uri":""}]},"series_statement":{"series_name":"Other Household Survey [hh\/oth]"},"study_info":{"abstract":"The dataset contains 17 modules of a household survey conducted between October and November 2017 to assess the impacts of the Cash plus (+) project in the Nioro Circle in the region of Kayes in Mali. The data look specifically at several outcome and output indicators related to the following areas: food and non-food expenditures, food insecurity, livestock production, farm and non-farm activities, dietary intake, housing condition, durable assets, decision making, and behavioural characteristics such as risk preference, locus of control, hope and aspirations.","coll_dates":[{"start":"2017-10-27","end":"2017-11-04","cycle":""}],"nation":[{"name":"Mali","abbreviation":"MLI"}],"geog_coverage":"Regional coverage","analysis_unit":"Households","universe":"The survey covers the beneficiaries of the Cash+ project and the non-beneficiaries as part of a control group.","data_kind":"Sample survey data [ssd]","notes":"The scope of the household survey includes: \n- HOUSEHOLD ROSTER: socio-demographic characteristics (sex, age, marital status, ethnicity, orphanhood, illness education).\n- FOOD SECURITY: Food Insecurity Experience Scale module, following FAO guidelines; Household Food Insecurity Access Scale module, following FANTA guidelines.\n- WOMEN DIETARY DIVERSITY: minimum dietary diversity for women module, following FAO guidelines.\n- CHILDREN DIETARY DIVERSITY: young children feeding practices module, following WHO and UNICEF guidelines.\n- HYGIENE PRACTICES: handwashing, drinking water treatment following FAO guidelines for assessing nutrition-related knowledge, attitudes and practices.\n- LIVESTOCK PRODUCTION: type and number of livestock owned, purchased, sold, value of purchases and sales, sales of livestock by-products.\n- CROP PRODUCTION: crops planted, area planted, crops harvested, harvest used for own-consumption, crops sold, crops sharecropped-out).\n- AGRICULTURAL INPUTS: type of crops\/livestock input used\/owned\/rented\/borrowed\/used for free, and value of purchases and rentals.\n- NON-FARM ENTERPRISES: type of non-farm business, profit. \n- HOUSING AND WEALTH: housing conditions (floor, walls, roof, toilet, lighting), type of occupancy, access to electricity.\n- FOOD CONSUMPTION: type of food eaten in the last 7 days and value (48 items).\n- NON-FOOD CONSUMPTION: type of consumption in the last 7 days (frequent items) and in the last 3 months (non-frequent items).\n- DECISION-MAKING POWER: one woman and one man responding to decision-making power in the household.\n- ASPIRATIONS AND EXPECTATIONS: Cantrill's ladder of life in two and five years, expectations about income, locus of control, Powerful Others and Chance scale by Levenson \n- RISK ATTITUDE: general willingness to take risk, willingness to take risk in borrowing and investment on a 1-10 likert scale, choice of lotteries with a certain equivalent and a risky game. \n- PROJECT OPERATIONAL DETAILS: transfer collection, type of transfer, instructions about the use of transfer, use of transfer, preference about different transfers."},"method":{"data_collection":{"sampling_procedure":"The sample contains 1151 households, among which 336 received Cash only, 344 received Cash plus (+), and 471 non-beneficiary households forming the comparison group. The beneficiaries were vulnerable households considered as \"poor\" and \"very poor\" according to a community targeting based on the Household Economy Analysis framework. The households in the control group are in neighbouring villages which did not receive the intervention and were chosen according to the same criteria for selecting the project's beneficiaries. In total, the impact evaluation dataset covers 58 villages, in which 34 are beneficiary and 25 are comparison villages. \n\nUsing this dataset, the impact evaluation study adopts a post-intervention single-difference approach. It distinguishes three treatment arms: households receiving Cash only (T1), households receiving Cash plus + (T2), and non-beneficiary households constituting the comparison\/control group (C). This design allows calculating three types of impacts:\n\u2022 The impact of the cash provided by the project by comparing the outcome for group T1 with the outcome of group C.\n\u2022 The combined impact of the cash and the livelihood support given by the project, by comparing the outcome of group T2 with the outcome of group C.\n\u2022 The different impacts of the two types of intervention, by comparing the outcome of group T2 with the outcome of group T1. \n\nHaving a non-experimental design, the project did not apply a random process to select its beneficiaries. They were chosen following a specific set of poverty and vulnerability criteria. Therefore, it is important to make sure that the treatment groups and the control groups are comparable. The impact evaluation started with estimating the probabilities of treatment, then applied their inversed values to the regressions in order to predict treatment-specific outcomes.","coll_mode":["Computer Assisted Personal Interview [capi]"],"cleaning_operations":"Data was cleaned and edited by the data provider. The datasets were made anonymous, by removing sensitive fields, such as names and surnames, GPS coordinates, village names, to avoid identification of respondents.","method_notes":"Anonymization of the datasets was conducted by the Office of Chief Statistician, using various Statistical Disclosure Control (SDC) methods. \n\t\t\nAll direct identifiers have been removed from the dataset. Additionally, labels have been removed from the electoral district variable. Household member age in years and months have been recoded into 13 and 7 intervals, respectively. The relationship to the household head was recoded into eight categories, and marital status into three. Local suppressions were also applied to reduce disclosure risk, resulting in the suppression of 56 observations for age, 1 for marital status, 1 for ethnic group, and 1 for highest level of education achieved.  For the crop and livestock modules, the SDC processed resulted in the suppression of 4 observations, respectively. Finally, for the enterprise module, we suppressed 13 observations."}},"data_access":{"dataset_use":{"conf_dec":[{"txt":"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.","required":"yes","form_no":"","uri":""}],"cit_req":"Silvio Daidone, Food and Agriculture Organization of the United Nations, Thu-Hien Dao, Food and Agriculture Organization of the United Nations; Mari Kangasniemi, Food and Agriculture Organization of the United Nations. Evaluating the impacts of the FAO\u2019s programme Cash+ in Mali. Ref. MALI CASH+ 2017. Dataset downloaded from [URL] on [date].","conditions":"Micro datasets disseminated by FAO shall only be allowed for research and statistical purposes. Any user which requests access working for a commercial company will not be granted access to any micro dataset regardless of their specified purpose. Users requesting access to any datasets must agree to the following minimal conditions:\n- The micro dataset will only be used for statistical and\/or research purposes; \n- Any results derived from the micro dataset will be used solely for reporting aggregated information, and not for any specific individual entities or data subjects; \n- 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;\n- The micro dataset cannot be re-disseminated by users or shared with anyone other than the individuals that are granted access to the micro dataset by FAO.","disclaimer":"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 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