9 Chapter DATA COLLECTION TOOLS TOOL NO 4: CHALLENGES IN COLLECTING QUANTITATIVE ETHNIC DATA This tool was developed by UNDP’s Regional Centre for Europe and CIS. It draws from the experiences of data collection on minority groups, including innovative surveys conducted in support of the UNDP Regional Human Development Report on the Roma, ‘Avoiding the Dependency Trap’ (2003) and ‘At Risk: Roma and the Displaced in Southeast Europe’ (2006). Using this tool: This tool provides a detailed introduction to the approaches and challenges of collecting disaggregated data by ethnicity, religion and/ or language. It provides UNDP COs with some guiding principles to observe when commissioning new data collection on minorities. Data on household incomes and expenditures and in Labour Force surveys disaggregated by ethnicity or religion is scarce. For many reasons, statistical institutes do not tend to monitor household budgets along these lines. In the case of the Roma, for example, this reflects both political sensitivity regarding Roma and the rest of society and resistance from Romani organizations. The latter have (not wholly unreasonable) concerns that ethnically disaggregated data could be used for discriminatory purposes and thereby increase tensions and intolerance between the minority and majority. Current data collection instruments fail to capture accurate information about minorities because of the following reasons:    In some countries, legal constraints prevent collection of ethnic data in censuses or other surveys. Government and minorities fear the consequences of data collection Household surveys and censuses often significantly underestimate the size of ethnic minorities. In a national census, members of minorities may opt not to identify themselves as such, often out of fear of discriminatory practices. With fluid definitions of identity, the very populations in question are unclear and any estimates can be susceptible to speculation. National representative survey samples are usually based on census data with all the consequences from under-representation of minority groups. As a consequence, minorities who did not selfidentify in the census are therefore likely to be under-sampled. Here both researchers and policy-makers face a peculiar vicious circle: data is necessary but not available. When available, it is not reliable (different estimations of minorities can be equally acceptable and justified using different sets of arguments). As a result, the opportunity for data misinterpretation is disturbingly broad. Depending on whether higher or lower estimates “work” better in the particular political context, different actors can argue for or against Chapter 9: Data Collection Tools 129