Finishing baseline & preparing mobile follow-ups

Having completed our 550 face-to-face baseline interviews and preparing the mobile follow-up phase, it seems about time for some first data-poking. At this point, things still are rather preliminary, mainly because we so far have entered the baseline data only for two out of the three districts of Dar es Salaam. Also, if you had a look at my earlier posts you will know that our sampling procedure (non-proportional stratified) requires weighting. But with coordinating fieldwork, solving lots of small practical issues and all that, we just haven’t had the time yet to put together the weights. So here you go. So much for the smallprint.

With heavy traffic being a major problem in the city, part of our questionnaire dealt with public transportation and the time people need to get to work.

At this point, we are looking at 265 adult respondents from two districts: Temeke & Ilala. Generally, respondents were very willing to answer our questions, and their attitude was almost always perceived as cooperative by the interviewers. As I mentioned in an earlier post, this was also very much due to the help of the balozi who introduced the interviewer to the head of the household and expressed his/her support for the survey, thus reducing fears and suspicion amongst respondents.

The mean age is 35, and women are overrepresented with 59%. In 42.3% of the cases had we selected the head of the household, in 31.8% his/her spouse followed by another 13.1% adult children of household heads.

Garbage dump in western outskirts of Dar es Salaam.

The face-to-face baseline survey focusses on the provision of a number of public services such as water, sewage, garbage disposal, schools and health facilities (click here for the translated questionnaire). Even though this blog is about the mobile phone follow-up part, I will first throw some of these numbers (and some graphs) at you – to get a general idea of the lives of the people that make up our sample.

Looking at education levels, 11.7% of our respondents never went to school and 23.4% had attained any form of education beyond primary school (which goes up to about 14 years). 29.3% reported to be unemployed at the time of the interview.

Lack of cash income / food during previous month (n=265, percentages on y-axis)

For the majority of respondents the main source of water is either a covered bore hole / well (32.8%) or a neighbour’s tap (32.5%). 6.4% have running water in their own building. When it comes to garbage disposal, about half of the respondents report that their garbage (sometimes) gets picked up, 30% bury it and 10% burn it themselves. As a toilet, 63.4% use a pit latrine which is mostly shared with other households and 23.0% have a flush toilet. 48.3% of the households own a television set, 74% have chairs and 83.4% have a table. 9.1% have a car, 8.7% have a computer and 2.6% a washing machine.

The first rains come to Pugu, Dar es Salaam

A clear majority of respondents (72.1%) own a mobile phone themselves, and another 18.1% have access to the phone of another household member or friend. Of those with a mobile phone, about 60% had credit at the time of the interview. This leaves us with 9.8% without phone ownership or access – constituting the most obvious and serious source of selection bias for the mobile follow-up. Particularly, since we can already see that this group is indeed somewhat different from the rest: less educated, more often female and slightly older. Most of these differences are not (yet) significant, but this is one of the things we will continue to monitor very carefully when the rest of the data comes in – to estimate the size of the problem (bias) but also think about possible solutions (e.g. handing out phones).

Frequency of media usage (n=265, percentages on y-axis)

One thing that is giving us a bit of a headache at the moment is that only very few respondents actually have the skills and technology to use WAP to answer our mobile surveys. To be sure, this is not problematic in itself. After all, we are not favouring one technology over another just because it looks fancier on paper. In an ideal situation, respondents are approached through a channel which they are familiar and comfortable with, to decrease data entry errors and drop-out rates. However, as part of our interest (and my interest in particular) is in the methodological aspects of it all, we would like to have a decently sized group of WAP respondents so we can compare their response behaviour – or lack thereof – with those using other technologies. But again, as we are still awaiting about half of the data, much of which coming from better-off areas, there is no reason to be overly pessimistic about this.

Right now we are ironing out the last issues regarding our different mobile data gathering channels – WAP, IVR, USSD, Call Center – solving technical problems and rounding off negotiations with mobile providers.

If all this runs smoothly, we will start our first round of mobile data gathering at the end of this week – so things are bound to get pretty exciting here once again.

This entry was posted in call center, IVR, nonresponse, poverty, sampling, USSD, WAP. Bookmark the permalink.

One Response to Finishing baseline & preparing mobile follow-ups

  1. Hello,

    interesting to see another “Engelhardt” working in research for development🙂.
    Do you have any updates on the panel stage or is this too early now?
    I would be most interested to see what kind of panel mortalities you ended up with in the different settings. Have you planned to replenish the panel every once in a while or has this project a fixed duration only for test reasons? Did you also run variations on the panel frequency to see which time interval produces an optimum?

    And: do you release the dataset? I have not seen such a thorough methodological test of different variants for years and would love to run some analyses to contribute to the discussion (maybe here on the blog?)🙂.

    Best from Timor-Leste

    Kay

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