Household Income and Expenditure Survey 2013-2014

The sampling frame used was the 2012 Palau census, which provided population figures for everyone living in both private households and group quarters (e.g. worker barracks, school dormitories, prison). The sampling selection was done separately in private dwellings and group quarters.

It is an accepted practice for the Household Income and Expenditure Survey (HIES) to cover all living quarters regarded as private dwellings, and the Palau 2013/14 HIES will follow this recommendation.

For group quarters it is also recommended to exclude the prison, as it is not considered appropriate to include such institutions in a survey such as HIES.

A decision as to whether the remaining group quarters should be included is based on the following criteria:

1. Ease in accessing and covering them in a survey such as HIES
2. Relevance to the subject matter of the survey
3. Whether their impact on the subject matter is mostly covered already

Under these criteria, the following recommendations are made:
-School/college dormitories: Will exclude from HIES as these individuals will be covered in the households from which they came (if selected)
-Work dormitories: Aim to include in the HIES as they are an important aspect of the subject matter focused on in this survey, and not addressed elsewhere
-Live aboard: Will exclude due to the movement of such vehicles, and the minimal impact they may have on such a survey
-Convents/religious quarters: Will exclude based on their expected minimum impact on the survey subject matter

NB: Given students in dorms are expected to have a high portion of their income and expenses covered in their original household of origin, and there were no religious group quarters identified during the census, only persons in the prison and living aboard are expected to be excluded from the survey. These people account for 81 out of 2,322 group quarters residents (only 3.6%).

Although the response rates were down in the 2006 HIES, with a smaller more experienced team working over 12 months, it is expected there will be improvements in this area. However, the expected sample loss of 10 per cent was probably too ambitious, and given the actual rate ended up at 287/1,063 = 27 per cent, it is more realistic to assume a sample loss of around 15 per cent with improvements for the 2013/14 HIES.
Based on the RSEs presented in 2.3.2, it also appears that the 20 per cent desirable sample produced sound results for the survey, and with higher response rates anticipated, these results from a sample error perspective should improve. It is therefore proposed for the 2013/14 Palau HIES that a sample size of 20 per cent be adopted, which also allows for sample loss of 15 per cent.

In the 2006 Palau HIES, effort was made to design a sample which could produce results for the six domains (stratum). Whilst reasonable results were generated for each of these domains, it was felt that post survey, there was no great use of these results at that level.
For the 2013 HIES it is proposed to focus on generating reliable results at the national level, with focus also being place on producing results for the urban/rural split. In the case of Palau, the urban population is considered to consist of the states of Koror and Airai.

The last phase to finalizing the sample numbers was to adjust the desirable sample numbers, so that they could be easily applied by the HIES team in a practical manner over the course of the 12 month fieldwork.
This was achieved by modifying the sample counts (not too much) to enable sample sizes each round would be of a similar size, and workloads for each enumerator were the same size each round.
The desirable workload for an enumerator covering the PD population was 10 households, whereas this figure was increased to 14 persons for GQs as it was envisaged the amount of time required to cover a person in a GQ would be significantly less.
With this in mind, we wanted to ideally have the PD sample to be divisible by 160 so this would enable an even number of households each round, whilst maintaining a workload of 10 households for interviewers covering these areas.
For the GQ sample, given the desirable number of GQs was already 225, and 16x14=224, then a simple reduction of 1 in the GQ sample would result in a nice even workload of 14 persons per round for 1 interviewer. This logic was also applied to the split between urban and rural resulting in 14 workloads in urban and 2 workloads in rural.