Questions that Count: A Livestock Module for Multi-topic Household Surveys

Abstract

The adequate inclusion of the major dimensions and determinants of livelihoods in multi-topic household surveys is essential for deriving appropriate measures of wellbeing and for effective investment design, implementation and evaluation. A review of existing Living Standards Measurement Study (LSMS) questionnaires reveals that livestock is largely neglected: they contain a limited set of questions on livestock, which focus ownership, and only infrequently inquire about animal health / diseases and on production of animal foods. This challenges the design and implementation of effective investments in the sector, despite about 60 percent of rural households in developing countries being fully or partly dependent on livestock for their livelihoods. This paper presents a short, a standard and an expanded version of a livestock module for multi-topic household surveys, jointly elaborated by the FAO, the ILRI (International Livestock Research Institute) and the World Bank. The standard version of the module consists of a set of questions that help quantify both livestock herd and the various contributions of farm animals to household livelihoods, including cash income, food, manure, draft power and hauling services, savings and insurance, and social capital. The expanded version contains additional questions on livestock characteristics (e.g. breeding, branding, etc.), husbandry practices (e.g. feeding, watering, etc.) and outputs (e.g. milk, dung, etc.) which, depending on the country, may or may not be included in the survey questionnaire. The short version consists of a minimum set of livestock-related questions, which is recommended be included in all LSMS survey questionnaires. Survey designers can adapt any of the three versions of the module to design a questionnaire that best suits their needs. The paper also illustrates examples from Niger, Tanzania and Uganda, where the livestock modules have been used to enhance the content of LSMS-type survey questionnaires, and discusses issues and options to further improve the livestock module for LSMS surveys.