Evaluation and Adjustment of Age Sex Data of the Population and Housing Census of Ghana 2000 and 2010

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dc.contributor.advisor Gaisie, S. K.
dc.contributor.author Tekpli, G. D.
dc.contributor.other University of Ghana, College of Humanities, Regional Institute for Population Studies
dc.date.accessioned 2016-01-21T15:50:43Z
dc.date.accessioned 2017-10-14T03:10:56Z
dc.date.available 2016-01-21T15:50:43Z
dc.date.available 2017-10-14T03:10:56Z
dc.date.issued 2013-07
dc.identifier.uri http://197.255.68.203/handle/123456789/7468
dc.description Thesis (M.A) - University of Ghana, 2013.
dc.description.abstract The simplest and most basic census item age, mostly present difficulties with regard to its accuracy in statistically underdeveloped countries where civil registration coverage is limited in terms of its accessibility. The study aimed at evaluating and adjusting age data of the population and housing census of Ghana. Several evaluation tools were used to examine the errors. These include visual inspection of the data and at the same time graphing the single age data which revealed heaping at certain digits especially 0 and 5. Comparison was also made using computed sex ratio for Ghana and some selected African countries. Though there was a decline in the sex ratio from 97.3 in the year 2000 to 95.2 in 2010, Ghana’s sex ratio fell within the standard for an African country. The trend of decline experienced in the sex ratio at the national level, however affected most of the administrative regions of Ghana especially Ashanti, Greater Accra and Western regions. This phenomenon was attributed to the plausibility of more female migration to these regions. Analysis based on age ratio showed that the ages of females in the 20 to 29 age groups had been exaggerated plausibly because of “assuming a typical marriage age”. Likewise, ages of both males and females 50 years and above were misreported either by overstatement or understatement resulting in erratic fluctuations (signifying errors) when the ratios are plotted on a line graph. A relationship between literacy and digit preference was also established where it became evident that non-literate heads of household misreported more than their literate counterparts. Detection of error in the data resulted in the need to adjust the age-sex data. The Strong Smoothing technique proved to be closer to the observed population data. At the end, some recommendations were made to improve the collection of age sex data in future censuses and survey. Notable among them are for the Ghana Statistical Service to sensitize enumerators on potential age heaping issues. Also, the GSS should explore ways of introducing self administered questionnaire to household that have the head or other responsible member literate. en_US
dc.format.extent xii, 80p. : ill.
dc.language.iso en en_US
dc.publisher University of Ghana en_US
dc.title Evaluation and Adjustment of Age Sex Data of the Population and Housing Census of Ghana 2000 and 2010 en_US
dc.type Thesis en_US
dc.rights.holder University of Ghana


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