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Trucking Industry Survey 2007

Uganda, 2007 - 2008
World Bank
Last modified February 14, 2018 Page views 289302 Metadata DDI/XML JSON
  • Study description
  • Data Description
  • Get Microdata
  • Identification
  • Coverage
  • Producers and sponsors
  • Sampling
  • Data Collection
  • Data Processing
  • Data access
  • Disclaimer and copyrights
  • Metadata production

Identification

IDNO
UGA_2007_TIS_v01_M
Title
Trucking Industry Survey 2007
Country
Name Country code
Uganda UGA
Abstract
Trucking Industry Survey as part of a major World Bank initiative called the Africa Infrastructure Country Diagnostic (AICD) study. The survey is carried out in several countries where the World Bank provides development loans. It is increasingly recognized that infrastructure services provide a critical platform for private sector activity and international trade. The trucking industry provides vital transportation services that facilitate both internal and external trade for the other productive sectors. The efficiency and quality of the services provided by the trucking industry is thus an important contributor to country competitiveness. In addition, as a major user of road infrastructure, trucking firms are uniquely placed to assess the functioning of road corridors. The objective of this study is to achieve a major improvement in the country level knowledge base of the infrastructure sectors in the region. The information obtained through the survey is precious as it will provide a baseline against which future improvements in infrastructure services can be measured, making it possible to monitor the results achieved from the current increase in financial flows. It should also provide a more solid empirical foundation for prioritizing investments and designing policy reforms in the infrastructure sectors in Africa.

Catalog of Trucking Surveys for nine sub-Saharan Africa countries is maintained by the Africa Transport unit (AFTTR).

The trucking surveys include nine sub-Saharan African countries. Each survey contains data for approximately 20 trucking companies and 60 truck owner-operators. Seven of the nine national surveys (i.e. Cameroon, Chad, Ghana, Burkina Faso, Kenya, Uganda and Zambia) were conducted for the "Transport Prices and Costs in Africa: A Review of the Main International Corridors" study by Supee Teravaninthorn and Gael Raballand (2008) mostly focusing on the trucking service on international corridors. The other two national trucking surveys (Malawi and Northern Mozambique) follow a slightly different approach with respect to sample selection mostly focusing on the link between the high agro-producing towns, the major cities and the exporting ports and using a revise survey instrument. All the surveys were performed by the Etude Economique Conseil (EEC) in 2007 and 2008 and financed by the World Bank.
Kind of Data
Sample survey data [ssd]

Coverage

Geographic Coverage
The Trucking Survey in Uganda targeted trucking companies and companies conducting their own transportation.
Unit of Analysis
- Truckers/ Truking Operators
- Trucking Companies

Producers and sponsors

Authoring entity/Primary investigators
Agency Name
World Bank

Sampling

Sampling Procedure
A trucking company is defined as a company that conducts trucking as its main operation and that has five or more full-time paid employees. A company conducting its own transportation is a company for whom trucking is not its main operation, that conducts the majority of its own transportation and that has five or more full-time paid employees. The companies surveyed serve at least one of the following routes:
o Kampala-Nairobi
o Kampala-Eldoret
o Kampala-Dar es salaam
o Kampala-Mombassa
o Kampala-Entebbe
o Kampala-Malaba
o Kampala-Mwanza
o Kampala-Kigali

The survey also sampled a selection of truckers (trucking operators with less than five full-time permanent paid employees) that serve the main roads listed above.

Companies with five or more full-time paid permanent employees: A list of Ugandan trucking operators was obtained from the Statistical Office. This list was completed and updated during the pilot survey. Following the results of the validation process, a sample frame consisting of a population of 47 establishments was drawn.

An attempt was made to contact each of these establishments. During the survey, it resulted that 4 establishments were closed, 14 establishments were out of scope or were unreachable despite repeated attempts by phone, 8 establishments refused to participate, and 21 establishments agreed to participate resulting in 21 completed trucking questionnaires, among which 4 trucking companies conducting their own transportation.

Truckers
In this survey, the trucker's stratum covers all establishments of the trucking industry with less than 5 employees. For many reasons, including the small size of establishments, their expected high rate of turnovers, the high level of ?informality? of establishments and consequently the difficulty to obtain trustworthy information from official sources, EEC Canada selected an aerial sampling approach to estimate the population of establishments and select the sample in this stratum according to the roads to be covered.

First, to randomly select individual truckers establishments for surveying, the following procedure was followed: i) select districts and specific zones of each district where there are lorry parks or where truckers usually off-loading; ii) count all truckers which generally stop in these specific lorry parks; iii) based on this count, create a virtual list and select establishments at random from that virtual list; and iv) based on the ratio between the number selected in each specific zone and the total population in that zone, create and apply a skip rule for selecting establishments in that zone.

The districts and the specific zones were selected at first according to our national sources. The EEC team then went in the field to verify these national sources and to count truckers. Once the count for each zone was completed, the numbers were sent back to EEC head office in Montreal.

At head office the following procedure was followed: the count by zone was converted into one list of sequential numbers for the whole survey region, and a computer program performed a random selection of the determined number of establishments from the list. Then, based on the number that the computer selected in each specific zone, a skip rule was defined to select truckers to survey in that zone. The skip rule for each zone was sent back to the EEC field team.

In Uganda, enumerators were sent to each zone with instructions as to how to apply the skip rule defined for that zone as well as how to select replacements in the event of a refusal or other cause of non-participation.

Data Collection

Dates of Data Collection (YYYY/MM/DD)
Start date End date
2007 2008
Mode of data collection
Face-to-face [f2f]
Data Collectors
Name Abbreviation
Étude Économique Conseil EEC

Data Processing

Cleaning Operations
Data entry and consistency check
1) When data entry was finished for the day, for each type of questionnaire for which additional cases were entered or existing cases were updated, that data file were exported to SPSS format using the provided export utility.
2) The resulting SPSS script was run to open the data in SPSS.
3) The consistency and completion tests script was run in order to generate data regarding the completion status of each case with respect to the consistency checks, and to generate a report detailing these results as well as the completion status of the whole sample with respect to sales.

Data access

Citation requirement
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download

Disclaimer and copyrights

Disclaimer
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.

Metadata production

Document ID
DDI_UGA_2007_TIS_v01_M
Producers
Name Abbreviation Affiliation Role
Development Economics Data Group DECDG World Bank Ducumentation of the DDI
Date of Production
2012-06-07
Document version
Version 01 (June 2012)
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