household survey programme in uganda: past experiences and future plans by james muwonge uganda...

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HOUSEHOLD SURVEY PROGRAMME IN UGANDA: PAST EXPERIENCES AND FUTURE PLANS By James Muwonge Uganda Bureau of Statistics OCTOBER , 2009

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HOUSEHOLD SURVEY PROGRAMME IN UGANDA:

PAST EXPERIENCES AND FUTURE PLANS

By

James Muwonge

Uganda Bureau of StatisticsOCTOBER , 2009

OUTLINE Background

Household surveys conducted since 1988

Sample Design and Survey organisation

The future plan- The long term household survey programme

Background Increased demand for data at both local and international

level (for PEAP, MDGs, PMA monitoring, NDP,etc) Less attention was put on micro level data in the past and

emphasis was mainly on financial and economic statistics collected mainly through administrative sources.

The Demand for data has however evolved over time and now demands for information that is necessary to determine the effects of government policies on peoples welfare

Background Cont’d

It is important to provide household level data to further strengthen the systems of data production to sustain the flow of information

Household surveys also become more relevant when information generated addresses the requirements of national development frameworks

Household Surveys Conducted by UBOS

The household survey programme dates back to 1988 -the rich database with annual information (with breaks in 1991 and 1998).

The surveys have had varying objectives and scope in order to mainly address the data gaps

Both consumption expenditure surveys and Demographic surveys have contributed to the body of knowledge in Uganda

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2000

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12000

14000

16000

18000

1989/90 1992/93 1993/94 1994/95 1995 1995/96 1997 1999/2000 2000/2001 2002/2003 2004 2005/2006 2006

HBS IHS FMS SMS UDHS II TMS FMS UNHS I UDHS III UNHS II NSDS UNHS III UDHS IV

Household Surveys conducted since 1988 and their respective sample Size

Series1

Household Surveys Conducted by UBOS Cont’d

Clearly, UBOS has evolved into an organisation capable of conducting nation-wide household surveysIt has also succeeded in conducting them on a regular basis – rarely found in other countriesThese household surveys can be categorised into two : Consumption surveys and Demographic and Health surveys

Consumption / Expenditure surveys conducted since 1988

Survey Round Dates Households covered

1. Household budget survey (HBS- for CPI weights) Apr. 1989 – Mar. 1990 4,595

2. Integrated household survey (IHS- Baseline multi-subject) Mar 1992 – Mar. 1993 9,925

3. Monitoring survey 1 (MS I-) Aug. 1993 – Feb 1994 4,925

4. Monitoring survey 2 (MS-2 diagnostic Agric module) Jul. 1994 – Jan 1995 4,925

5. Monitoring survey 3 (MS-3 Agric Module) Sep. 1995 – Jun. 1996 5,515

6. Monitoring survey 4 (MS-4 Pilot labour force module) Mar. 1997 – Nov. 1997 6,654

7. Uganda National Household survey 1 (UNHS-1) Aug. 1999 – Jul. 2000 10,696

8. Uganda National Household survey 2 (UNHS-2) May 2002 – Apr. 2003 9,711

9. Uganda National Household survey 3 (UNHS III)

10. Uganda National Household Survey (UNHS IV)

May 2005 – Apr. 2006

May 2009 -ongoing

7,500

7500

Demographic and other household surveys conducted since 1988

Survey Round Dates Households covered

1. Uganda Demographic and Health Survey 1988 7000

2Uganda Demographic and Health Survey 1995 9,000

3. Uganda Demographic and Health Surveys 2000-2001 9000

4. National Service Delivery Survey 2004 18000

5. National Service delivery survey 2008 10200

Sample design

Two Stage sample design for all the surveys with the exception in a few cases

First stage Unit (FSUs) -Enumeration Areas selected with PPS

Households are selected using SRS/systematic as Ultimate sampling units (second stage)

Sampling Frame The Population and Housing censuses of 1991 and 2002

provided the frame for household surveys In some of the surveys, each district was treated as a

stratum. In others, the stratification is based on the stratification variable of interest (rural-urban, region etc)

Depending on the objective of the survey, further sub stratification is sometimes introduced at listing stage to ensure adequate representation (agriculture, informal sector and employment)

Survey Organisation

Involves planning (stakeholder consultations), questionnaire development, Pretest/pilot the survey instruments, training (both field and data entry staff), quality checks both in the field and during data entry, data analysis and dissemination

Survey organisation Cont’d

Data collection uses a mobile team approach to manage fieldwork

The team composition consists of a supervisor, 3-4 interviewers and a driver

Fieldwork spread over a 12 months period to account for seasonality

Data processing

All data is processed centrally at UBOS The IT Directorate is responsible for processing,

and management of the data Data usually captured by a team of Data Entry

Operators (DEO) for a period of up to one year The DEO are recruited on temporary terms

Dissemination Channels

Information disseminated through workshops, UBOS Website, Press releases/briefs, on CD ROMs

The UBOS resource centre

The proposed 10 year survey programme

Will ensure continued production of information. The periodicity of the survey programme based on

pace of the decision making process (PEAP revision, NDP, etc)

The dynamism of the indicators also dictates the frequency of household surveys

The ten year plan Cont’d

The long term census and survey programme details out all planned field undertakings

The demand for data dis- aggregated to lower levels continues to pose a real challenges to the data production process and alternative sources of data provide some solutions (Community Information System,).

Ten year plan Cont’d

Censuses are also included in the plan to because of their importance (directly or indirectly- )

Panel surveys have been initiated to provide annual outcome indicators

Current and future plan

Data entry moved to the field Computerised data collection to be adopted soon Paper questionnaires to be limited to a few

surveys

Conclusion

Continued production of household level information is vital for monitoring development programmes.

Best practices in data management should also be used to ensure safety of data