Improving Agricultural Statistics in the COMCEC Region

the internet. Vehicle requirements are also very important for implementation of the field

surveys.

iv. Methodology Used in Agricultural Statistics

Sampling Frames:

Surveys conducted by UBOS are generally based on probability sampling.

UBOS uses PHC 2002 Agricultural Module as a sample frame for agricultural surveys. For the

first time in the history of conducting agricultural census/sample surveys in Uganda, a more

appropriate sampling frame for surveys was used. In previous censuses and surveys,

Household (Population)-based sampling frames were used in sampling. In this Livestock

Census, a cattle-based sampling frame-Agricultural Households, which reported rearing of

cattle, constructed from the PHC 2002 Agricultural Module was used. It is well-known that

frames which are human population-based are not the best for Livestock Censuses/Surveys,

because areas with a higher population density-people per square kilometre are likely to have

less livestock than those with a lower population density.

Data Collection:

Field organization is understood as the set-up of regional and local data

collection offices for surveys and censuses. This includes the staff composition and their

responsibilities, and the communication network between these groups as well as with the

headquarters or central coordinating office.

Since the inception of the National Household Survey (NHS) Programme in 1989; the

Demographic and Health Survey (DHS) in 1995 and 2000; and the Census of Business

Establishments (COBE), moving teams of supervisors and enumerators have carried out the

fieldwork. Many of them serve in a number of survey rounds, which means they are semi-

permanent.

There is, however, a belief that the moving teams are much more expensive than

if they were permanently field-based staff, or what is normally referred to as a Permanent

Field Organization (PFO).

The results of different surveys are stored in Microsoft Excel files. Applications are being

developed to organize them in a SQL server database. Currently, there is no comprehensive

database of the various primary agricultural surveys. The information and communication

technology are starting to be used increasingly in the collection, processing and dissemination

of data.

Commodity Classification:

Uganda uses up-to-date classification systems as shown in Table

56 below:

Table 56 Classification Systems Used in Uganda

Classification

Version

ISIC (International Standard Industrial Classification)

Version 3

SITC (Standard International Trade Classification)

Version 2 (National Version)

HS (Harmonized System Classification)

SH2002/2007 (National Version)

SNA (System of National Accounting)

SNA93

Source: SSAQ Results.

SSAQ Results.

UBOS, 2014d.

UBOS, 2014c.