The 1995/1996 Household Income, Expenditure - (PDF, 101 mb ...

1.13
HIECS as well as international technical experience. The Census Bureau and
the survey manager settled on an initial procurement list in May 1995, hoping
that the material could be received in-country for testing with all the pre-test
components and requirements. Due to circumstances beyond the control of
CAP MAS, the procurement material did not arrive until October. The delay in
procuring and shipping the computer hardware for the project caused grave
concerns that the survey would not stick to the schedule. CAPMAS-owned
hardware was memory deficient, so even the data dictionary could not be
revised. Training data entry operators for the pre-test stretched computing
resources to the limit, and the team had to abandon programming CENTS tables
to present pre-test results. Ultimately the delay in receiving hardware and
software for the project was one reason for not employing bar-code reading
technology for data processing.
Difficulties in securing and retaining manpower for the project
continually dogged efforts to stay on schedule, especially in the beginning.
Renewal of the main programmers' part time work contract authorization from
the CAPMAS data processing sector was only assured after considerable
bureaucratic delay. Adequate staff were not allocated to the coding, editing,
and totalling task, nor was a team leader appointed for data validation until
production launch. Despite these setbacks, the final data set and analysis
were completed on schedule. Moreover, the 1995/1996 HIECS data, which was
declared final and validated on November 23, 1996, proved to be of exceptional
quality.
1.D. Evaluation as an On-going Practice
The continual evaluation of tasks is essential to the application of largescale
surveys. This is so because the final result should be data of high
quality, and many activities associated with survey work have the potential to
affect data quality. Indeed quality control is so ingrained in the use of best
practices for survey operations that evaluation should be understood as an
integrated component, not separated from its context. There are certain
identifiable practices and stages which, when singled out for refinement, tend
to complement and enhance data quality.
Proper (meaning comprehensive) evaluation requires full information,
which in turn assumes a great deal of communication among and between
actors. In general the conditions for such an information-rich control of data
quality are poor within CAPMAS headquarters, and the links between
headquarters and governorate offices are tenuous. There are many reasons
for this, but few readily identifiable solutions. Decisions are overly
centralized. The incentive structure does not reward flexibility and initiative.
The last chapter returns to the matter of institutional rigidity in the
context of data dissemination, but a short statement about headquarters'
experience with formal evaluation should be mentioned here to illustrate the
difficulties HIECS survey management faced in controlling error. The former
resident advisor from the US Bureau of the Census assisted CAPMAS in
developing a program of statistical quality control and provided formal and
informal training in quality control to CAP MAS staff as part of the 1986
population census. The Quality Control Unit (QCU) was established in CAPMAS,
at one time with 30 staff members. In May of 1995, the QCD even released a
report evaluating the 1990/91 HIECS, "with coverage errors, nonresponse
errors, statistical content errors, and interviewer and respondent errors,"