CHALLENGES IN PRODUCING DISAGGREGATED DATA

Sample size For surveys a small sample size is used which makes disaggregation a challenge. Cost Accurate Survey data disaggregation by geographic location is obtained at higher cost for the survey. Timely release of data e.g Botswana Multi Topic Household Survey (BMTHS) 2015 and part of it (employment section) released in 2017. The result therefore did not depict the current employment situation.

Challenges in producing Disaggregated Data Race/ ethnicity We do not disaggregate by race but there is no law forbidding us to do so, it is just a long standing accepted practice of not collecting data on ethnicity. Central database The lack of a centralised database makes it difficult to access data from other sources. There is waste of time running around collecting the data.

Challenges in producing Disaggregated Data Income Income data is collected through surveys and respondents are usually reluctant to disclose income which leads a need to cross-reference questions in the questionnaire to arrive at more accurate income bracket for the respondent. Use of unskilled manpower Use of unskilled personnel during surveys deputizes the quality of the data.

Challenges in producing Disaggregated Data Un-harmonized districts Different data sources use different Districts. For instance; there are 28 census districts, 26 administrative districts and other departments use their own number of districts which makes harmonizing data almost impossible.

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