Chart and table of population level and growth rate for the Addis Ababa, Ethiopia metro area from 1950 to 2025.

This statistic shows the total population of Ethiopia from 2013 to 2023 by gender. In 2023, Ethiopia's female population amounted to approximately 64.21 million, while the male population amounted to approximately 64.49 million inhabitants.

This statistic shows the biggest cities in Ethiopia in 2022. In 2022, approximately 3.86 million people lived in Adis Abeba, making it the biggest city in Ethiopia.

Abstract

The Central Statistical Agency (CSA) has been providing labour force and related data at different levels and with varying details in their content. These include the 1976 Addis Ababa Manpower and Housing Sample Survey, the 1978 Survey on Population and Housing Characteristics of Seventeen Major Towns, the 1980/81 and 1987/88 Rural Labour Force Surveys, the 1984 and 1994 Population and Housing Census, and 2003 and 2004 Urban Bi-annual Employment Unemployment Survey. The 1996 and 2002 Surveys of Informal Sector and most of the household surveys undertaken by the Agency also provide limited information on the area. Still pieces of information in relation to that of employment can also be derived from small, large and medium scale establishment surveys. Till the 1999 Labour Force Survey (LFS) there hasn't been a comprehensive national labour force survey representing both urban and rural areas. This 2005 LFS is the second in the series.

The 2005 National Labor Force Survey was designed to provide statistical data on the size and characteristics of the economically active and the non-active population of the country, both in urban and rural areas. The data will be useful for policy makers, planners, researchers, and other institutionsand individuals engaged in the design, implementation and monitoring of human resource development plans, programs and projects. The specific objectives of this survey are to: - generate data on the size of work force that is available to participate in production process; - determine the status and rate of economic participation of different sub-groups of the population; - identify those who are actually contributing to the economic development (i.e., employed) and those out of the sphere; - determine the size and rate of unemployed population; - provide data on the structure of the working population; - obtain information about earnings from paid employment; - identify the distribution of employed population working in the formal/informal enterprises; and - provide time series data and trace changes over time.

Geographic coverage

Like the National Labour Force Survey of 1999, it covered both the urban and rural areas of all regions. Exceptions are Gambella Region, where only the urban parts of the region are covered, Affar Region with only zone one and zone three were covered and Somali Region where only Shinile, Jijiga and Liben zones were covered.

Analysis unit

• HouseHold (HH)
• Household Member

Universe

The survey is mainly aimed at providing information on the economic characteristics of the population aged 10 years and over,

Kind of data

Données échantillonées [ssd]

Sampling procedure

2.1 COVERAGE The 2005 (1997 E.C) Labour Force Sample Survey covered all rural and urban parts of the country except all zones of Gambella Region excluding Gambella town, and the non-sedentary population of three zones of Afar & six zones of Somali regions. In the rural parts of the country it was planned to cover 830 Enumeration Areas (EAs) and 24,900 households. All planned EAs were actually covered by the survey; however, due to various reasons it was not possible to conduct the survey in 39 sample households. Ultimately 100.00 % EAs and 99.84% household were covered by the survey. Regarding urban parts of the country it was initially planned to cover 995 EAs and 29,850 households. Eventually 100% of the EAs and 99.24% of the households were successfully covered by the survey.

2.2 SAMPLING FRAME The list of households obtained from the 2001/2 Ethiopian Agricultural Sample Enumeration (EASE) is used to select EAs from the rural part of the country. For urban sample EAs on the other hand the list consisting of households by EA, which was obtained from the 2004 Ethiopian Urban Economic Establishment Census, (EUEEC) was used as a frame. A fresh list of households from each urban and rural EA was prepared at the beginning of the survey period. The list was then used as a frame for selecting sample households of each EAs.

2.3 SAMPLE DESIGN For the purpose of the survey the country was divided into three broad categories. That is; rural, major urban center and other urban center categories.

Category I: Rural: - This category consists of the rural areas of 8 regions and two city administrations found in the country. Regarding the survey domains, each region or city administration was considered to be a domain (Reporting Level) for which major findings of the survey are reported. This category totally comprises 10 reporting levels. A stratified two-stage cluster sample design was used to select samples in which the primary sampling units (PSUs) were EAs. Households per sample EA were selected as a second Stage Sampling Unit (SSU) and the survey questionnaire finally administered to all members of sample households

Category II:- Major urban centers:- In this category all regional capitals and 15 other major urban centers that had a population size of 40,000 or more in 2004 were included. Each urban center in this category was considered as a reporting level. The category has totally 26 reporting levels. In this category too, in order to select the samples, a stratified two-stage cluster sample design was implemented. The primary sampling units were EAs. Households from each sample EA were then selected as a Second Stage Unit.

Category III: - Other urban centers: Urban centers in the country other than those under category II were grouped into this category. Excluding Gambella a domain of other urban centers is formed for each region. Consequently 7 reporting levels were formed in this category. Harari, Addis Ababa and Dire Dawa do not have urban centers other than that grouped in category II. Hence, no domain was formed for these regions under this category. Unlike the above two categories a stratified three stage cluster sample design was adopted to select samples from this category. The primary sampling units were urban centers and the second stage sampling units were EAs. Households from each EA were finely selected at the third stage and the survey questionnaires administered for all of them.

To have more informations on th sampling view the report (Page 8)

Mode of data collection

Interview face à face [f2f]

Research instrument

The questionnaire was organized in to five sections; Section - 1 Area identification of the selected household: this section dealt with area identification of respondents such as region, zone, wereda, etc.,

Section -2 Socio- demographic characteristics of households: it consisted of the general sociodemographic characteristics of the population such as age, sex, education, status and type of disability, status and types of training, marital status and fertility questions.

Section - 3 Productive activities during the last seven days: this section dealt with a range of questions which helps to see the status and characteristics of employed persons in a current status approach such as hours of work in productive activities, occupation, industry, employment status, and earnings from employment. Also questions included are hours spent on fetching water, collection of firewood, and domestic chores and place of work.

Section - 4 Unemployment and characteristics of unemployed persons: this section focused on the size and characteristics of the unemployed population.

Section - 5 Economic activities during the last twelve months: this section covered the usual economic activity status (refereeing to the long reference period), number of weeks of employment /unemployment/inactive, reasons for inactivity, employment status, whether working in the agricultural sector or not and the proportion of income gainedfrom non-agricultural sector.

The questionnaire used in the field for data collection was prepared in Amharic language. Most questions have pre-coded answers.

Cleaning operations

During the fieldwork, the field supervisors, statisticians and the heads of branch statistical offices have checked the filled-in questionnaires and carried out some editing. However, the major editing and coding operation was carried out at the head office. All urban questionnaires were subjected to complete manual editing, while most of rural questionnaires were partially edited. All the edited questionnaires were again fully verified and checked for consistency before they were submitted to the data entry. This system of data processing was followed on the assumption that, there is less complication of activities in rural areas than urban centers.

After the data was entered, it was again verified using the computer edit specification prepared earlier for this purpose, the entered data were checked for consistencies and then computer editing or data cleaning was made by referring back to the filled-in questionnaire. This is an important part of data processing operation in attaining the required level of data quality. Consistency checks and re-checks were also made based on tabulation results. Computer programs used in data entry, machine editing and tabulation were prepared using the Integrated Microcomputer Processing System (IMPS).

The metropolitan area of Lagos in Nigeria counted over 14 million middle-class people as of 2018. This was the highest number in Africa. Addis Ababa in Ethiopia followed with 2.7 million individuals belonging to the middle class. The middle-class population included people who had a disposable income of over 75 percent of their salary, were employed, had a business activity, or were in education, and had at least a secondary school degree.

Accessibility to regional cities dataset is modeled as raster-based travel time/cost analysis, computed for the largest cities surrounding the country. The following cities are included: City - Population Addis Ababa, Ethiopia - 5 153 002 Asmara, Eritrea - 1 258 001 Sohag, Egypt - 979 800 Wau, South Sudan - 328 651 Abeche, Chad - 83 155 This 500m resolution raster dataset is part of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) aimed at the identification of value chain infrastructure sites (or optimal location).

Abstract

Introduction Dabat Health and Demographic Surveillance System (HDSS), also called the Dabat Research Center (DRC), was established at Dabat District in 1996 after conducting initial census. Later re-census was done in 2008. The surveillance is run by the College of Medicine and Health Sciences which is one of the colleges/faculties of the University of Gondar. Dabat district is one of the 21 districts in North Gondar Administrative Zone of Amhara Region in Ethiopia. According to the report published by the Central Statistical Agency in 2007, the district has an estimated total population of 145,458 living in 27 rural and 3 urban Kebeles (sub-districts). The altitude of the district ranges from about 1000 meters to over 2500 meters above sea level. The district population largely depends on subsistence agriculture economy. There are two health centers, three health stations, and twenty-nine health posts providing health services for the community. An all-weather road runs from Gondar town through Dabat to some towns of Tigray. Dabat town, the capital of Dabat District, is located approximately 821 km northwest of Addis Ababa and 75 kms north of Gondar town. The surveillance is funded by Centers for Disease Control and Prevention (CDC) through Ethiopian Public Health Association.

Objectives Dabat HDSS/ Dabat Research Centre was established to generate longitudinal data on health and population at district level and provide a study base and sampling frame for community-based research.

Methods Dabat district was initially selected purposively as a surveillance site for its unique three climatic conditions, namely Dega (high land and cold), Woina dega (mid land and temperate) and Kolla (low land and hot). The choice was made with the assumption that there would be differences in morbidity and mortality in the different climatic areas. Accordingly, seven kebeles from Dega, one kebele from Woina dega, and two kebeles from Kolla were selected randomly after stratification of the kebeles by climatic zone.

After the re-census, update has been done regularly every 6 months. During each round, data has been collected using a semi-structured questionnaire which included information related to birth and other pregnancy outcomes, death, migration, and marital status change. Interviews are administered to the heads of the household but in the absence of the head, the next elder family member is interviewed. This is only done after repeated trial of getting the head. While the regular update round is every six months, deaths that occur in the surveillance site are reported immediately to the data collectors by the local guides. After the mourning period, usually 45 days, the trained data collectors administer Verbal Autopsy (VA) questionnaire to the close relative of the deceased to get information on the possible cause(s) of death. Three VA questionnaires are prepared for the age groups 0-28 days, 29 days to 15 years, and greater than 15 years. To assign cause(s) of death, the VA data collected by data collectors is given to physicians who have got training on VA. These physicians independently assign causes of death using the standard International Classification of Diseases (ICD-10).

Geographic coverage

Dabat Health and Demographic Surveillance System (HDSS) included seven rural kebeles (sub districts) and three urban kebeles in Dabat district which is located 75 km North of Gondar town in Ethiopia. There are highlands, midlands and few low land households in the HDSS site.

Analysis unit

Individual

Universe

All individuals residing in Dabat HDSS site.

Kind of data

Event history data

Frequency of data collection

Two rounds per year

Mode of data collection

Face-to-face [f2f]

Research instrument

All questionnaires are prepared in Amharic language. The surveillance questionnaires are related to birth and other pregnancy outcomes, death, and migration.

Cleaning operations

The filled questionnaire is checked by filled supervisors, document clerk, data entry clerks for missings and other violations. In addition, DRC Software, a software developed from Microsoft Access and Visual Basic, checks violations against set of rules for data quality during data entry.

Response rate

100% response rate

Sampling error estimates

Not applicable

Data appraisal

CentreId MetricTable QMetric  Illegal   Lega  Total  Metric RunDate 
ET051 MicroDataCleaned Starts  0  59082  0  0.0 2014-06-27 19:33 
ET051 MicroDataCleaned Transitions 0  129938 129938 0.0 2014-06-27 19:33 
ET051 MicroDataCleaned Ends 0  59082  0  0.0 2014-06-27 19:33

Clinical and pathological characteristics of the study population (subgroup of AACCR*) compared to the AACCR cohort.

Patients characteristics and treatment received in the study cohort.

These raster files show the land cover classification around Harare in 2006 and 2010. The classification results were based on Spot 5 imagery. Land cover classes in the attribute table are as follows: Class 1 Regular Residential (small planned buildings) Class 2- Regular Residential (small unplanned buildings) Class 3 Commercial/Industrial (large buildings) Class 4 Natural (Vegetation/Soil/non built-up This dataset is part of a paper which illustrates how the capabilities of GIS and satellite imagery can be harnessed to explore and better understand the urban form of several large African cities (Addis Ababa, Nairobi, Kigali, Dar es Salaam, and Dakar). To allow for comparability across very diverse cities, this work looks at the above mentioned cities through the lens of several spatial indicators and relies heavily on data derived from satellite imagery. First, it focuses on understanding the distribution of population across the city, and more specifically how the variations in population density could be linked to transportation. Second, it takes a closer look at the land cover in each city using a semi-automated texture based land cover classification that identifies neighborhoods that appear more regular or irregularly planned. Lastly, for the higher resolution images, this work studies the changes in the land cover classes as one moves from the city core to the periphery. This work also explored the classification of slightly coarser resolution imagery which allowed analysis of a broader number of cities, sixteen, provided the lower cost. When using this dataset keep in mind: Accuracy is higher in closer to the City center, and the distinction between class 1 and class 2 has not been validated, so use with caution. To learn more about the methodology please refer to https://ssrn.com/abstract=2883394

Abstract

The Household Consumption and Expenditure (HCE) survey is administered by the Central Statistical Agency every five years, most recently in 2010/11. The core objective of the HCE survey is to provide data that enable to understand the income dimension of poverty and the major objectives are to: • Assess the level, extent and distribution of income dimension of poverty. • Provide data on the levels, distribution and pattern of household expenditure that will be used for analysis of changes in the households' living standard level over time in various socio-economic groups and geographical areas. • Provide basic data that enables to design, monitor and evaluate the impact of socio- economic policies and programs on households/individuals living standard. • Furnish series of data for assessing poverty situations, in general, and food security, in particular. • Provide data for compiling household accounts in the system of national accounts, especially in the estimation of private consumption expenditure. • Obtain weights and other useful information for the construction and /or rebasing of consumer price indices at various levels and geographical areas.

Geographic coverage

The 2010/11 HCE survey covered all rural and urban areas of the country except the non-sedentary populations in Afar (three zones) and Somali (six zones).

Analysis unit

• Household
• Individual
• Consumption expenditure items

Universe

The survey covered households in the selected samples except residents of collective quarters, homeless persons and foreigners.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame The 2007 Population and Housing Census served as the sampling frame from which the rural and urban EAs were selected. A fresh list of households for each selected EA was collected at the beginning of the survey period. Households were then selected for inclusion in the survey by choosing a random number as the starting point in the list and selecting every nth household (n being the necessary number to achieve the desired number of households in each EA).

Sample Design & Selection In order to produce a representative sample, the country was stratified into the following four categories: rural, major urban centers, medium towns, and small towns.

a. Category I - Rural This category consists of the rural areas of 68 zones and special weredas, which are considered zones, in 9 regions of the country. This category also includes the rural areas of the Dire Dawa City Administration. A stratified two-stage cluster sample design was used, with the primary sampling unit being the EAs. Sample EAs were selected using Probability Proportional to Size, with size being the number of households identified in the 2007 Population and Housing Census. Twelve households were randomly selected from each sample rural EA for survey administration. The total sample for this category is 864 EAs and 10,368 households.

b. Category II - Major Urban Centers This category includes all regional capitals as well as five additional major urban centers with large populations, for a total of 15 major urban centers. These 15 urban centers were broken down into the 14 regional capitals and the 10 sub-cities of Addis Ababa City Administration resulting in a total of 24 represented urban domains. A stratified two-stage sample design was also used for this category as in the rural sample with EAs as the primary sampling unit. For this category, however, 16 households were randomly selected in each EA. In total, 576 EAs and 9,216 households were selected for this category.

c. Categories III & IV - Other Urban Centers These two categories capture other urban areas not included in Category II. A domain of other urban centers was formed from 8 regions (all except Harari, Addis Ababa, and Dire Dawa where all urban centers are included in Category II). Unlike the other categories, a three-stage sample design was used. However, sampling was still conducted using probability proportionate to size. The urban centers were the primary sampling units and the EAs were secondary sampling units. Sixteen households were randomly selected from each of the selected EAs. A total sample of 112 urban centers, 528 EAs, and 8,448 households were selected for these two categories.

Mode of data collection

Face-to-face [f2f]

Research instrument

A hard copy (Paper print) booklet type questioner has been used for data collection. The design of the questionnaire has structured/organized into five main parts (forms).

The main components of the survey questionnaire are: Form 0: is used together basic household information that could help to assess the general livelihood nature of a household and its members, such as: source of household income, status and scope of agriculture engagement (diversity and specialization), safety net/asset accumulation participation, participation in micro and small scale business enterprise, accessibility and/or credit facility status from micro-finance institution, …etc.,

Form 1: has been used to collect data on demographic characteristics and economic activity of household members, such as: age, sex, marital status, education, income contribution status, economic activity and other related variables.

Form 2 (2A & 2B): is used to collect actual consumption (quantity consumed) and equivalent expenditure of food, beverages and tobacco items, that would have been actually consumed by the household (members of the household) within the reference period of the survey. Note that the first three consecutive day's consumption being collected in Form 2A and 2B is used to collect the second phase (consecutive 4 days) of the survey week.

Form 3 (3A, 3B & 3C): Household consumption and expenditure data on non-durable goods and frequent services has been collected using three segments of form 3. Of which 3A and 3B are designed to handle three and four day's data, respectively; while 3C has been used to capture a full month reference data.

Form 4 (4A-4E): Household expenditure data of durable goods and Less-Frequent services was administered in form 4. In order to facilitate a systematic way of data collection approach, these goods and services are grouped into classes and data were collected using five chapters of the main module in such a way that expenditure data on: • Clothing and footwear was collected in 4A; • Dwelling rent, water, fuel and energy, furniture's & furnishing, household equipment and operation were collected by use of form 4B; • Health, transport and communication goods and services has been collected in form 4C; • Education, recreation, entertainment, cultural and sport goods and services were collected by the use of 4D; and • Personal goods and services, financial services, and others including operational cost of production with respect to unincorporated household economic enterprises;

Dairy book: Consumption expenditure of food and beverages data are collected, at first on daily basis, by listing every consumed item by the household (every household member) in each day in a dairy book, to facilitate exhaustiveness of consumption. And, then a summary of attributes are transferred to the main questionnaire.

Measuring tools: Kitchen balance (digital type in urban and analog type in rural areas) and measuring type are used for consumption/quantity data collection.

Cleaning operations

Data Processing All data processing was undertaken at the head office. Completed questionnaires were returned to the CSA data processing department from the field periodically. Data processing activities included cleaning, coding, and verifying data as well as checking for consistency. These activities were carried out on a quarterly basis after entering three months of data. Further processing, including the estimation of sampling weights, was carried out at the close of data entry.

Data Entry and Coding Manual editing and coding of data began as early as August 2010, when the first round of completed questionnaires was received at the head office. A team of 21 editors, 5 verifiers, and 4 supervisors carried out these activities. Subject matter experts provided a 5-day intensive training for this team to equip them with the necessary skills. Additionally, a team of 12 encoders was trained to enter the data. A double-entry system was used, wherein two separate encoders manually entered each survey. Any discrepancies between the two entries were flagged automatically and the physical survey was reviewed to correct the errors. Data entry was completed in October 2011.

Data Validation and Cleaning Data validation and cleaning was carried out by subject matter experts and data programmers. Systematic validity checks were completed at the commodity, household and visit levels. Activities related to consistency, validity, and completeness included the following: a. Imputation of missing observations on consumption goods (in quantity or value) using the market price survey that was collected at the time of the HCE. b. Validity and consistency of quantity and value of consumption items was checked by comparing the figures across both household visits (using the household-provided prices and/or the market price survey). c. Estimation of the value of consumption of own production using the household-provided quantities and market survey prices. d. Comparison of household expenditure on durable goods using different recall periods (i.e., 3 and 12 months). After analyzing the annualized values using each reference period, it was decided to use whichever period resulted in the largest expenditure, which was often the

Abstract

Ethiopia is believed to have the largest livestock population in Africa. This livestock sector has been contributing considerable portion to the economy of the country, and still promising to rally round the economic development of the country. It is eminent that livestock products and by-products in the form of meat, milk, honey, eggs, cheese, and butter supply the needed animal protein that contribute to the improvement of the nutritional status of the people. Livestock also plays an important role in providing export commodities, such as live animals, hides, and skins to earn foreign exchanges to the country. On the other hand, draught animals provide power for the cultivation of the smallholdings and for crop threshing virtually all over the country and are also essential modes of transport to take holders and their families long-distances, to convey their agricultural products to the market places and bring back their domestic necessities. Livestock as well confer a certain degree of security in times of crop failure, as they are a “near-cash” capital stock. Furthermore, livestock provides farmyard manure that is commonly applied to improve soil fertility and also used as a source of energy.

Due to the very important role that the livestock sector plays in the economy of the country, formulation of development plan regarding the sector is indispensable. It is therefore imperative that livestock development plans should be formulated on the basis of reliable statistical data, and hence, timely and accurate livestock data are required for the formulation, implementation, monitoring, and evaluation of development plan and program in the sector. These livestock data can be generated usually using surveys and censuses. In this regard, subsequent surveys and a solitary agricultural census have been carried out by the Central Statistical Authority (CSA) to make available data on livestock though they were not comprehensive. The 2004/05 Annual Agricultural Sample Survey was also conducted to produce these same data so as to keep hold of continuity and update users in general.

The general objective of the livestock survey is to produce data that could be used for development planning and policy formulation regarding the sector, and the specific objectives are to purvey quantitative information on the size and characteristics of livestock in rural sedentary areas at zonal level. In order to meet these objectives, data on: livestock number by type, age, sex, purpose and breed; livestock products particularly milk, egg, and honey; livestock diseases and vaccination; and animal feed were collected from sampled agricultural households in rural sedentary areas.

Geographic coverage

The Livestock Sample Survey covered entire rural parts of the country except three zones of Afar regional state, six zones of Somali and all zones of Gambella regional state.

Analysis unit

Agricultural Household/Holder/Livestock

Universe

Households, who were engaged in growing crops and/or breeding and raising livestocks in private or in partnership with others in the selected sample.

Kind of data

Sample survey data [ssd]

Sampling procedure

A stratified two -stage cluster sample design was used to select the sample. Enumeration areas (EAs) were taken to be the primary sampling units (PSU's) and the secondary sampling units (SSU's) were agricultural households. Sample enumeration areas from each stratum were sub-samples of the 2001-2002 (1994 E.C) Ethiopian Agricultural Sample Enumeration. They were selected using probability proportional to size systematic sampling; size being number of agricultural households obtained from the 1994 Population & Housing Census and adjusted for the sub-sampling effect. Within each sample EA a fresh list of households was prepared and 25 agricultural households from each sample EA were systematically selected at the second stage. The survey questionnaire was finally administered for those 25 agricultural households selected at the second stage.

The sample size for the 2004/05 Agricultural Sample Survey was determined by taking into account both the required level of precision for the most important estimates within each domain and the amount of resources allocated to the survey. In order to reduce non-sampling errors, manageability of the survey in terms of quality and operational control was also considered in addition. Except Harari, Addis Ababa and Dire Dawa, where each region as a whole was taken to be the domain of estimation; each zone of a region / special wereda was adopted as a stratum for which major findings of the survey are reported.

Distribution of number of planned and actually covered sampling unit (EAs and households) of the 2004-2005 (1997 E.C) is given in APPENDIX II of 2004-2005 Livestock and Livestock Characteristic Survey report which is provided as external resource. Remark: As of the 2002 Ethiopian Agricultural Sample Enumeration, Addis Ababa City Administration had a total of 35 enumeration areas (EA). However, during the 2004 Urban Economic Establishments Census it was found that some of the rural enumeration areas were to be part of the urban areas of the city. Consequently, only 24 enumeration areas (EAs) were left as the rural EA's of the City Administration. Therefore, the 2004-2005(1997 E.C) Livestock Sample Survey covered all the 24 EA's with certainty. Hence, there could be great variation among estimates of the 2004-2005(1997 E.C) Livestock Sample Survey and that of the previous years.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2004-2005 Livestock Sample Survey used structured questionnaire to collect data on livestock and livestock characteristics. The questionnaire is organized in to two parts. Part 1: Identification particulars: This part contains area identification of the selected household. It dealt with area identification of respondents such as Region, Zone, wereda, Farmer's association, Enumeration area household number, holder number, and type of holding.

Part II: Livestock population and products: This part of the questionnaire dealt with number of cattle, sheep, goats, horses, mules, asses and camels by age and purpose; production of poultry and beehives; milk, egg and honey production; livestock diseases, treatment and vaccination; and livestock feeds used.

The questionnaire used in the field for data collection purpose was prepared in Amharic language. A copy of the questionnaire translated to English is provided in this documentation.

Cleaning operations

Editing, Coding, and Verification The editing and coding instruction manuals were prepared, and intensive training was given to the editor-coders. Those trained editors-coders were accompli the editing and coding tasks. In due course, professional staff members were assigned to facilitate the editing and coding activities and the edited and coded questionnaires were verified by statistical technicians as well as by professionals.

Data Entry, Cleaning, and Processing The data was entered by data encoders in personal computers using IMPS (Integrated Microcomputer Processing System) software. Then the data were checked and cleaned by regular staff members. Finally, the data processing activity was also done by personal computers (PCs) to produce results that were indicated in the tabulation plan.

Response rate

Initially, a total of 2016 Enumeration Areas (EAs) were selected to be covered by the survey, however, due to various reasons three EAs were not covered and the survey was effectively carried out in 2,013 (99.85%) EAs. As regards, the ultimate sampling unit, it was planned to conduct the survey on 50,400 agricultural households and 50,114 (99.43 %) households were actually covered by the Livestock Sample Survey.

Sampling error estimates

Estimation procedure for totals and ratios and their sampling errors are given in Appendix II of 2004-2005 Livestock and Livestock Characteristic Survey report. Estimates of standard errors and Coefficient of Variations for selected estimates are also presented in the Annex Tables 1-10.