Cost-Benefit Analysis for a Quinquennial Census: The 2016 Population Census of South Africa

Abstract

The question of whether to carry out a quinquennial Census is faced by national statistical offices in increasingly many countries, including Canada, Nigeria, Ireland, Australia, and South Africa. We describe uses and limitations of cost-benefit analysis in this decision problem in the case of the 2016 Census of South Africa. The government of South Africa needed to decide whether to conduct a 2016 Census or to rely on increasingly inaccurate postcensal estimates accounting for births, deaths, and migration since the previous (2011) Census. The cost-benefit analysis compared predicted costs of the 2016 Census to the benefits of improved allocation of intergovernmental revenue, which was considered by the government to be a critical use of the 2016 Census, although not the only important benefit. Without the 2016 Census, allocations would be based on population estimates. Accuracy of the postcensal estimates was estimated from the performance of past estimates, and the hypothetical expected reduction in errors in allocation due to the 2016 Census was estimated. A loss function was introduced to quantify the improvement in allocation. With this evidence, the government was able to decide not to conduct the 2016 Census, but instead to improve data and capacity for producing post-censal estimates.

Assessing the Feasibility and the Potential of Implementing Solar Water Heaters in Dimbaza, a Township in Eastern Cape, South Africa

“…The study methodology involved the analyses of the secondary data collected from the literature of published articles [23]. It also included the historical data on the electrical energy consumption in a home in Dimbaza, the relative humidity, the ambient temperature, and the solar radiation of Dimbaza, which were obtained from the South African Weather Service database [24]. The methodology included the analyses of both the quantitative and qualitative data on the sources of energy consumed in the 73 sample houses via questionnaires (see Appendix A) and walk-through energy audits.…”

“…Approximately, over 1000 adults have never received any form of formal schooling [23]. According to a study conducted by Gantsho [24], most of the households are on a monthly income ranging from ZAR 1 to ZAR 400, resulting in an annual income of ZAR 12 to ZAR 4800 [23]. Several authors [21] further highlighted that only 14% of the inhabitants are employed, while 8% of the population are discouraged jobseekers.…”

“…There are 300 houses in Ward 36. So, out of the 73 houses of the sample size that were surveyed, 50 were considered in the analysis and 1 household that met the criteria (low-income household with a 200 L electric water heater) was identified as a representative of the monthly energy consumption [24]. Hence, the residence was used in the determination of the projected simple payback period of a SWH.…”

The Effect of Differentially Private Noise Injection on Sampling Efficiency and Funding Allocations: Evidence From the 1940 Census

“…We do this separately for both enumeration districts and counties. This analysis relates to the prior literature on the effects of error in population estimates on funding allocations, but is more specific in that it considers the effects of DP and uses 1940 data as a test case (National Research Council, 2003;Spencer, 1980;Spencer et al, 2017;Zaslavsky & Schirm, 2002).…”

South Africa ID Case Study

“…In doing so they can reap substantial savings in costs without sacrificing coverage of census topics or quality. For South Africa's planned census for 2016 a costbenefit analysis was done to advise government whether the benefits would outweigh the costs (Spencer et al 2017). With this evidence in hand, the government was able to decide not to conduct the 2016 census, but instead to improve data and capacity for producing post-censual estimates.…”