Labor force, total in Ethiopia was reported at 54470278 in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ethiopia - Labor force, total - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Ethiopia ET: Unemployment: Modeled ILO Estimate: % of Total Labour Force data was reported at 5.204 % in 2017. This records an increase from the previous number of 5.093 % for 2016. Ethiopia ET: Unemployment: Modeled ILO Estimate: % of Total Labour Force data is updated yearly, averaging 5.232 % from Dec 1991 (Median) to 2017, with 27 observations. The data reached an all-time high of 8.710 % in 1999 and a record low of 3.081 % in 1991. Ethiopia ET: Unemployment: Modeled ILO Estimate: % of Total Labour Force data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ethiopia – Table ET.World Bank.WDI: Employment and Unemployment. Unemployment refers to the share of the labor force that is without work but available for and seeking employment.; ; International Labour Organization, ILOSTAT database. Data retrieved in September 2018.; Weighted average; Data up to 2016 are estimates while data from 2017 are projections. National estimates are also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.

Ethiopia ET: Labour Force Participation Rate: National Estimate: Ratio of Female to Male data was reported at 84.059 % in 2013. This records an increase from the previous number of 83.187 % for 2005. Ethiopia ET: Labour Force Participation Rate: National Estimate: Ratio of Female to Male data is updated yearly, averaging 68.969 % from Dec 1981 (Median) to 2013, with 7 observations. The data reached an all-time high of 84.059 % in 2013 and a record low of 38.811 % in 1981. Ethiopia ET: Labour Force Participation Rate: National Estimate: Ratio of Female to Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ethiopia – Table ET.World Bank.WDI: Labour Force. Labor force participation rate is the proportion of the population ages 15 and older that is economically active: all people who supply labor for the production of goods and services during a specified period. Ratio of female to male labor force participation rate is calculated by dividing female labor force participation rate by male labor force participation rate and multiplying by 100.; ; Derived using data from International Labour Organization, ILOSTAT database. Data retrieved in September 2018.; Weighted average; The series for ILO estimates is also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.

Abstract

Statistical information on all aspects of the population is vital for the design, implementation and evaluation of economic and social development plan and policy issues. Labour force surveys are one of the important sources of data for assessing the role of the population of a country in the economic and social development process. These surveys provide data on the main characteristics of the work force engaged or available to be engaged in productive activities during a given period and also its distribution in the various sectors of the economy. They are also useful to indicate the extent of available and unutilized human resource that must be absorbed by the national economy to ensure full employment and economic well being of the population. Furthermore, the information obtained from such surveys is useful for the purpose of macro-economic monitoring and human resource development planning. The other broad objective of statistics on the labour force is for the measurement of the relationship between employment, income and other social and economic characteristics of the economically active population for the purpose of formulating and monitoring employment policies and programs, income-generating and maintenance schemes, vocational training and other similar programs. Seasonal and other variations in the size and characteristics of the labour force can also be monitored using up-to-date information from labour force surveys.

In order to further fill the gap in data requirement for the socio-economic development planning, monitoring and evaluation, the Central Statistical Authority (CSA) has conducted Rural Labour Force Survey (RLFS) as a part of the National Integrated Household Survey Program (NIHSP) at the end of 1980. To maintain the continuity and to update the Rural Labour Force Survey of 1981/82 results, another Rural Labour Force Survey was conducted in 1987/88. Also the CSA has conducted the 1976 Addis Ababa Manpower and Housing Sample Survey and the 1978 Manpower and Housing survey in Seventeen Major Towns. Moreover, some data on the labour force were also collected as a part of other surveys such as the 1990 Family and Fertility Survey, 1996 Urban Informal Sector Sample Survey and in the country wide deccennial Population and Housing Censuses of Ethiopia conducted in 1984 and 1994.

The labour force surveys that were conducted earlier were limited in areal coverage and content of the questionnaires. In this respect, both the 1981/82 and 1987/88 surveys covered only the rural part of the country. Till the current survey was conducted, there hasn't been a comprehensive national labour force survey representing both the urban and the rural areas of the country. Moreover, the information that should have been provided through labour force surveys could be said relatively out-dated, as the sector is dynamic and sensitive to economic and social changes. To fill this data gap, a series of current and comprehensive labour force surveys need to be undertaken.

Recognizing this fact, the Central Statistical Authority (CSA) has conducted a national labour force survey in March 1999. The survey is the first of its kind in that it covers the rural and the urban areas and it contains detailed information on the subject. The results of this survey have been already released to users in a publication entitled "Statistical Report on the 1999 National Labour Force Survey (NLFS)" and this presented the data in a former of detailed statistical tables including the concepts and definitions on the major technical terms used in the survey. The CSA hopes that users have benefited a lot from this publication. To increase the utility of the result of the survey, the CSA taught that it necessary to make further analysis on the data. The analytical presentation of this report will be based on the tables that have been presented in the statistical report (Report on Statistical Tables of the 1999 Labour Force Survey, CSA, 1999) and some additional tables produced and included in this report. This chapter presents an overview to the survey background. The 1999 National Labour Force survey was designed to provide statistical data on the size and characteristics of the employed, unemployed, underemployed and the non-active population of the country. In general, the data obtained from the survey is useful for policy makers, planners, researchers and other institutions and individuals engaged in the design and implementation of human resource development projects and programs.

The specific objectives of the 1999 National Labour Force Survey are to :- - collect statistical data on the potential manpower who are available to take part in various socio-economic activities - determine the size and distribution of the labour force; and the status and rates of economic activity and also to study the socio-economic and demographic characteristics of these groups - identify those who contributed to economic development and those who are partially employed, without work and economically inactive - to estimate and assess the levels and characteristics of the unemployed population - generate data on the status and type of professional and vocational training - assess the size and characteristics of children aged between 5 - 14 years that were engaged in economic activities - assess the situation of women's employment or the participation of women in the labour force

Geographic coverage

The survey covered both urban and rural parts of the country, except six zones in Somali Region and two zones in Affar Region

Analysis unit

• Household
• Household member
• Household members aged 10 years and over

Universe

The survey covered all households in selected sample areas except residents of collective quarters, homeless persons and foreigners.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 1999 National Labor Force Survey covered both urban and rural parts of the country, except six zones in Somali Region and two zones in Affar Region. In addition the residents of collective quarters, homeless persons and foreigners were not covered in the survey. For the purpose of the survey, the survey population in the country was divided into urban and rural categories.

Category I: Urban parts of 26 zones, that is 4 zones in Tigray, 10 zones in Amhara, and 12 zones in Oromiya regions; and 9 zones and 5 special weredas in SNNP Region; and urban parts of Affar, Somali, Benishangul-Gumuz, Gambela and Harari regions and Addis Ababa and Dire Dawa Administration were grouped in this category. Each of the above mentioned urban parts of the zones, except the 5 special weredas in SNNP Region were the survey domains (reporting levels). All in all 47 basic urban domains (Reporting levels) including total urban (regional and country level) were defined for the survey.

Category II: Rural parts of 26 Zones that is 4 zones in Tigray, 10 zones in Amhara, 12 zones in Oromiya regions and 9 zones and 5 special weredas in SNNP regions; and rural parts of Affar, Somali, Benishangul-Gumuz, Gambela and Harari regions, Addis Ababa and Dire Dawa Administration were grouped in this category. Each of the above mentioned rural parts of zones and special weredas, except Addis Ababa rural, were the survey domains (reporting levels). All in all 51 basic rural domains (reporting levels) including total rural (regional and country level) were defined for the survey. In addition to the above urban and rural domains, survey results can be reported at regional and country levels by aggregating the survey results for the corresponding urban and rural areas. Definition of the survey domains was based on both technical and resource considerations. More specifically, sample sizes for the domains were determined to enable provision of major indicators with reasonable precision subject to the resources that were available for the survey.

Selection Scheme and Sample Size: In both categories stratified two-stage sample design was used to select the sample in which the Primary Sampling Units (PSUs) were enumeration areas (EAs). Sample EAs from each domain were selected using systematic probability proportional to size; size being number of households obtained from the 1994 Population and Housing Census. From category I, a total of 913 EAs and from category II, a total of 1428 EAs were selected. Within each sample EA, fresh list of households was prepared at the beginning of the survey's fieldwork for urban sites and at the beginning of the 1991 E.C. Agricultural Sample Survey's fieldwork for rural sites. The survey questionnaire was administered to 35 systematically selected households within each of the sampled EAs.

Note: Distributions of sample units by domain (reporting levels) and category are presented in Table 2.1 and Table 2.2 of the 1999 National Labour Force Survey report which is provided in this documentation.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey has used a structured questionnaire to solicit the required data. Before taking its final shape, the draft questionnaire was tested by undertaking a Pilot Study. Based on the result of the pilot study the content, layout and presentation of the questionnaire was amended. The content of the questionnaire has been further revised on the basis of the discussion made on the user - producer forum organized by the CSA. The questionnaire used in the field was prepared in Amharic language and most questions have pre-coded answers and column numbers were assigned for each question.

The questionnaire is organized into six sections: Section-1 Area identification of the selected household: this section has

Ethiopia ET: Labour Force data was reported at 51,450,036.000 Person in 2017. This records an increase from the previous number of 49,661,396.000 Person for 2016. Ethiopia ET: Labour Force data is updated yearly, averaging 33,025,014.000 Person from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 51,450,036.000 Person in 2017 and a record low of 20,132,057.000 Person in 1990. Ethiopia ET: Labour Force data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ethiopia – Table ET.World Bank.WDI: Labour Force. Labor force comprises people ages 15 and older who supply labor for the production of goods and services during a specified period. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.; ; Derived using data from International Labour Organization, ILOSTAT database and World Bank population estimates. Labor data retrieved in September 2018.; Sum; Data up to 2016 are estimates while data from 2017 are projections.

In 2022, there were nearly 56 million people employed in Ethiopia. The majority of the employed individuals in the country were men, accounting for nearly 53.7 percent. In the period examined, the number of female and male employees in the country followed the same trend, while the gender gap in employment was largest in 2020.

Unemployment, total (% of total labor force) (modeled ILO estimate) in Ethiopia was reported at 3.398 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ethiopia - Unemployment, total - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

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. Like the National Labour Force Survey of 1999, it covered both the urban and rural areas of all regions.

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

The 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.

Analysis unit

Household Individual

Universe

The survey covered all households in selected sample areas except residents of collective quarters, homeless persons and foreigners.

Kind of data

Sample survey data [ssd]

Sampling procedure

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.

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 seven 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.

SAMPLE SIZE AND SELECTION SCHEME: Category I: - Totally 830 EAs and 24,900 households were selected from this category. Sample EAs of each reporting level were selected using Probability Proportional to Size (PPS) systematic sampling technique; size being number of household obtained from the 2001/2 Ethiopian Agricultural Sample Enumeration. From the fresh list of households prepared at the beginning of the survey 30 households per EA were systematically selected and surveyed.

Category II: - In this category 720 EAs and 21,600 households were selected. Sample EAs from each reporting level in this category were also selected using probability proportional to size systematic sampling; size being number of households obtained from the 2004 EUEEC. From the fresh list of households prepared at the beginning of the survey 30 households per EA were systematically selected and covered by the study.

Category III:-127 urban centers, 275 EAs and 8,250 households were selected in this category. Urban centers from each domain and EAs from each urban center were selected using probability proportional to size systematic selection method; size being number of households obtained from the 2004 EUEEC. From the fresh listing of each EA 30 households were systematically selected and the study carried out on the 30 households ultimately selected.

Note: Distribution of number of samples planned and covered from each domain are given in the Summary Table 2.1, Table 2.2 and Table 2.3 of the 2005 National Labour Force Survey report which is provided as external resource.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey has used a structured questionnaire to produce the required data. Before taking its final shape, the draft questionnaire was tested by undertaking a pre-test. The pre-test was conducted in Addis Ababa, Sendoffs, Teji and their vicinity. Based on the findings of the pre-test, the content, layout and presentation of the questionnaire was amended comments and inputs on the draft contents of the survey questionnaire obtained from user-producer forum were also incorporated in the final questionnaire.

The contents of the questionnaire and methods used in this survey were further improved based on comment of international consultant. The consultancy was obtained as part of a joint World Bank/IMF project to improve statistics of countries in Anglo-phone Africa participating in the General Data Dissemination System (GDDS).

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 gained from non-agricultural sector. The questionnaire used in the field for data collection was prepared in Amharic language. Most questions have pre-coded answers. A copy of the questionnaire translated to English is provided as external resource.

Cleaning operations

Data Editing, Coding and Verification: The filled-in questionnaires that were retrieved from the field were first subjected to manual editing and coding. During the fieldwork the enumerator, the field supervisors, Statisticians and the heads of branch statistical offices have done some editing. However, the major editing operation was carried out at the head office. All the edited questionnaires were again fully verified and checked for consistency before they were submitted to the data entry.

Response rate

Ultimately 100.00 % EAs and 99.84% household were covered

Ethiopia ET: Unemployment: National Estimate: Female: % of Female Labour Force data was reported at 2.943 % in 2013. This records a decrease from the previous number of 3.251 % for 2005. Ethiopia ET: Unemployment: National Estimate: Female: % of Female Labour Force data is updated yearly, averaging 3.251 % from Dec 1984 (Median) to 2013, with 5 observations. The data reached an all-time high of 5.062 % in 1999 and a record low of 1.400 % in 1984. Ethiopia ET: Unemployment: National Estimate: Female: % of Female Labour Force data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ethiopia – Table ET.World Bank.WDI: Employment and Unemployment. Unemployment refers to the share of the labor force that is without work but available for and seeking employment. Definitions of labor force and unemployment differ by country.; ; International Labour Organization, ILOSTAT database. Data retrieved in September 2018.; Weighted average; The series for ILO estimates is also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.

In 2022, there were close to 56 million people estimated as employed in Ethiopia. The number increased compared to the previous year, when around 53.8 million people were registered. Overall, employment in the country incremented in the period examined, dropping only in 2020.

Ethiopia ET: Unemployment: National Estimate: % of Total Labour Force data was reported at 17.060 % in 2016. This records an increase from the previous number of 16.990 % for 2015. Ethiopia ET: Unemployment: National Estimate: % of Total Labour Force data is updated yearly, averaging 17.040 % from Dec 1984 (Median) to 2016, with 14 observations. The data reached an all-time high of 23.130 % in 2004 and a record low of 1.200 % in 1984. Ethiopia ET: Unemployment: National Estimate: % of Total Labour Force data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ethiopia – Table ET.World Bank: Employment and Unemployment. Unemployment refers to the share of the labor force that is without work but available for and seeking employment. Definitions of labor force and unemployment differ by country.; ; International Labour Organization, ILOSTAT database. Data retrieved in November 2017.; Weighted Average; The series for ILO estimates is also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.

The labor participation rate among the total population aged between 15 and 64 in Ethiopia saw no significant changes in 2024 in comparison to the previous year 2023 and remained at around 69.08 percent. Yet 2024 saw the lowest labor participation rate in Ethiopia with 69.08 percent. The labor force participation rate refers to the share of the population aged 15 years and over who are economically active. Unemployed people actively searching for work are included, whereas the long-term unemployed (economically inactive) are not. It is calculated by dividing the total number of workers aged 15 and over by the total population aged 15 and over.Find more key insights for the labor participation rate among the total population aged between 15 and 64 in countries like Uganda and Eritrea.

There were nearly 2.23 million unemployed people in Ethiopia as of 2024. The number increased compared to the previous year, when nearly 2.16 million people where unemployed but in the labor force in the country. Overall, unemployment in Ethiopia followed a rising trend from 2012 onwards, with a significant increase in 2020.

SL.TLF.TOTL.FE.IN. Female labor force comprises women ages 15 and older who supply labor for the production of goods and services during a specified period. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave. The Gender Statistics database is a comprehensive source for the latest sex-disaggregated data and gender statistics covering demography, education, health, access to economic opportunities, public life and decision-making, and agency.

Abstract

Statistical information on all aspects of the population is vital for the design, implementation, monitoring and evaluation of economic and social development plan and policy issues. Labor force survey is one of the most important sources of data for assessing the role of the population of the country in the economic and social development process. It is useful to indicate the extent of available and unutilized human resources that must be absorbed by the national economy to ensure full employment and economic wellbeing of the population. Statistics on the labor force further present the economic activity status and its relationship to other social and economic characteristics of the population. Seasonal and other variations as well as changes over time in the size, distribution, and characteristics of employed and unemployed population can be monitored using up-to-date information from labor force surveys. It serves as an input for assessing the achievements of the Millennium Development Goals (MDGs). Furthermore, labor force data is also useful as a springboard for monitoring and evaluation of the five years growth and transformation plan of the country.

Geographic coverage

The 2012 Urban Employment and Unemployment Survey (UEUS) covered all urban parts of the country except three zones of Afar, Six zones of Somali, where the residents are pastoralists.

Analysis unit

• Households
• Individuals

Universe

This survey follows household approach and covers households residing in conventional households and thus, population residing in the collective quarters such as universities/colleges, hotel/hostel, monasteries, and homeless population etc., were not covered by this survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

The list of households obtained from the 2007 population and housing census was used to select EAs. A fresh list of households from each EA was prepared at the beginning of the survey period. The list was then used as a frame to select 30 households from sample EAs.

The country was divided into two broad categories - major urban centers and other urban center categories.

Category I: In this category all regional capitals and five other major urban centers that have a high population size as compared to others were included. Each urban center in this category was considered as a reporting level. This category has a total of 16 reporting levels. To select the sample, a stratified two-stage cluster sample design was implemented. The primary sampling units were EAs of each reporting level.

Category II: Urban centers other than those under category I were grouped into this category. 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.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire was organized into seven sections. Section 1 - Area identification of the selected household Section 2 - Particulars of household members Section 3 - Economic activity status during the last seven days Section 4 - Unemployment rate and characteristics of unemployed persons Section 5 - Economic activity status the population during the last six months Section 6 - Employment in the informal sector of Employment Section 7 - Economic activity of children aged 5-17 years

A structured questionnaire was used to solicit the required data in the survey. The draft questionnaire was tested by undertaking a pretest in selected kebeles (lower administrative unit) in Addis Ababa. Based on the pretest, the content, logical flow, layout and presentation of the questionnaire was amended. The questionnaire used in the field for data collection was prepared in Amharic language. Most questions have pre coded answers and column numbers were assigned for each question.

Cleaning operations

The filled-in questionnaires that were retrieved from the field were first subjected to manual editing and coding. During the fieldwork the field supervisors 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 the edited questionnaires were again fully verified and checked for consistency before they were submitted to the data entry by the subject matter experts.

Using the computer edit specifications 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 frequency and tabulation results. This was done by senior programmers using CSPro software in collaboration with the senior subject experts from Manpower Statistics Team of the CSA.

Response rate

Response rate was 99.68%.

Abstract

Statistical information on all aspects of the population is vital for the design, implementation, monitoring and evaluation of economic and social development plan and policy issues. Labour force survey is one of the most important sources of data for assessing the role of the population of the country in the economic and social development process. It is useful to indicate the extent of available and unutilized human resources that must be absorbed by the national economy to ensure full employment and economic well being of the population. Statistics on the labour force further present the measurement of economic activity status and its relationship to other social and economic characteristics of the population. Seasonal and other variations as well as changes over time in the size and characteristics of employed and unemployed populations that can be monitored using up-to-date information from labour force surveys. It serves as an input for assessing the meeting of the Millennium Development Goals (MDGs). Furthermore, labour force datais also used as a springboard for monitoring and evaluation of the five years growth and transformation plan of a country.

Despite the significance of the labopur force data, the availability of reliable and timely labour force data were inadequate. The lack of reliable and timely data on different aspects of the population hinders the monitoring and evaluation of changes of developmental activities.

In order to fill the gap in data requirement for the purpose of socio-economic development planning, monitoring and evaluation, the Central Statistical Agency (CSA) has been providing labour force and related data at different levels with various contents and details. 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 (RLFS). Also, the 1984, 1994 and 2007 Population and Housing Censuses and the 1999 and 2005 National Labour Force Surveys provided a comprehensive national labour force data representing both urban and rural areas.

The survey results mainly provide data on the main characteristics of employed and unemployed population, that is, the work force engaged or available to be engaged in the production of economic goods and services and its distribution in the various sectors of the economy during a given reference period.

In addition, data on economic activities of children were also collected to measure child labour in urban areas. For this purpose, the former minimum age limit 10 years was lower down to 5 years since May 2009. Therefore, the data in this survey were collected from those persons aged five years and over. However, for the purpose of measuring the economic activity status based on Ethiopian situation, the lower age limit was fixed in to ten years. This is because children in rural and urban areas used to work at their early age such as collection of fire wood, looking after cattle, shoeshine, street vendor, petty trading…etc. Thus, the May 2011 Urban Employment and Unemployment Survey statistical report is mainly aimed at provide information on the economic characteristics of the population aged ten years and over.

Furthermore, the 2011 UEUS provide data on employment on the informal sector, their spatial distribution and problem in the sector.

Geographic coverage

The 2011 Urban Employment and Unemployment Survey (UEUS) covered all urban parts of the country except three zones of Afar, Six zones of Somali, where the residents are pastoralists.

Analysis unit

• Household
• Individual aged 10 years and above

Universe

The survey follows household approach and covers households residing in conventional households and thus, population residing in the collective quarters such as universities/colleges, hotel/hostel, monasteries and homeless population etc., are not covered by this survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING FRAME The list of households obtained from the 2007 population and housing census is used to select EAs. A fresh list of households from each EA was prepared at the beginning of the survey period. The list was then used as a frame in order to select 30 households from sample EAs.

SAMPLE DESIGN For the purpose of the survey the country was divided into two broad categories. That is major urban center and other urban center categories. Category I:- Major urban centers:- In this category all regional capitals and five other major urban centers that have a high population size as compared to others were included. Each urban center in this category was considered as a reporting level. The category has a total of 16 reporting levels. In this category, in order to select the sample, a stratified two-stage cluster sample design was implemented. The primary sampling units were EAs of each reporting level. From each sample EA 30 households were then selected as a Second Stage Unit (SSU).

Category II:- Other urban centers: Urban centers in the country other than those under category I were grouped into this category. A domain of other urban centers is formed for each region. Consequently 8 reporting levels were formed in this category. Harari, Addis Ababa and Dire Dawa do not have urban centers other than that grouped in category I. Hence, no domain was formed for these regions under this category.

A stratified three stage cluster sample design was also adopted to select samples from this category. The primary sampling units were urban centers and the second stage sampling units were EAs. From each EA 30 households were selected at the third stage and the survey questionnaires administered for all of them.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire is organized into six sections; Section - 1: Area identification of the selected household: this section deals with area identification of respondents such as region, zone, wereda, etc. Section - 2: Particulars of household members: it consists of the general socio-demographic characteristics of the population such as age, sex, educational status, types of training and marital status. Section - 3: Economic activity during the last seven days: this section deal with whether persons were engaged in productive activities or not during the last seven days prior to date of interview, the status and characteristics of employed persons such as occupation, industry, employment status, hours of work, employment sector /formal and informal employment/ and earnings from paid employment. Section - 4: Unemployment rate and characteristics of unemployed persons: this section focuses on the size, distribution and characteristics of the unemployed population and unemployment rate only for those aged 10 years and over. Section - 5: Economic activity during the last six months: this section contains information on the economic activity status of the population in the long reference period or during the last six months.
Section - 6: Economic activity of children aged 5-17 years: this section consists of information on the participation of children aged 5-17 years in the economic activities, whether attending education, reason for not attending education…etc.

Cleaning operations

The filled-in questionnaires that were retrieved from the field were first subjected to manual editing and coding. During the fieldwork the field supervisors 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 the edited questionnaires were again fully verified and checked for consistency before they were submitted to the data entry by the subject matter experts.

Using the computer edit specifications 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 frequency and tabulation results. This was done by senior programmers using CSPro software in collaboration with the senior subject experts from Manpower Statistics Team of the CSA.

Response rate

It was initially planned to cover 660 EAs and 19,800 households in the survey, but ultimately 100% of EAs and 99.68% of households were successfully covered.

Ethiopia ET: Unemployment: National Estimate: Male: % of Male Labour Force data was reported at 9.400 % in 2016. This records a decrease from the previous number of 10.500 % for 2015. Ethiopia ET: Unemployment: National Estimate: Male: % of Male Labour Force data is updated yearly, averaging 10.830 % from Dec 1984 (Median) to 2016, with 14 observations. The data reached an all-time high of 15.810 % in 2004 and a record low of 1.000 % in 1984. Ethiopia ET: Unemployment: National Estimate: Male: % of Male Labour Force data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ethiopia – Table ET.World Bank: Employment and Unemployment. Unemployment refers to the share of the labor force that is without work but available for and seeking employment. Definitions of labor force and unemployment differ by country.; ; International Labour Organization, ILOSTAT database. Data retrieved in November 2017.; Weighted Average; The series for ILO estimates is also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.

Ethiopia ET: Unemployment: Modeled ILO Estimate: Male: % of Male Labour Force data was reported at 3.102 % in 2017. This records an increase from the previous number of 3.050 % for 2016. Ethiopia ET: Unemployment: Modeled ILO Estimate: Male: % of Male Labour Force data is updated yearly, averaging 2.994 % from Dec 1991 (Median) to 2017, with 27 observations. The data reached an all-time high of 4.921 % in 1999 and a record low of 1.761 % in 1993. Ethiopia ET: Unemployment: Modeled ILO Estimate: Male: % of Male Labour Force data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ethiopia – Table ET.World Bank.WDI: Employment and Unemployment. Unemployment refers to the share of the labor force that is without work but available for and seeking employment.; ; International Labour Organization, ILOSTAT database. Data retrieved in September 2018.; Weighted average; Data up to 2016 are estimates while data from 2017 are projections. National estimates are also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.

Agglomeration effects on the workers’ and firms’ productivity in developed countries are widely confirmed by previous studies, while empirical evidence for developing countries is still limited. This paper sheds light on another urban productivity factor that is particularly important for developing countries: self-employment and wage jobs. The transition from the economy dominated by the former to the one by the latter is a key to economic development. This study examines how urban agglomerations are linked to the mix of self-employment and wage jobs by focusing on one of the least urbanized low-income countries: Ethiopia. Applying an instrumental variable approach to worker-level cross-sectional data, the analysis finds a negative link between town population size and the share of self-employment workers: a log increase in town population size lowers the probability of engaging in self-employment by 7.9 percentage points. Particularly female, young, and less-educated workers are more likely to work with wage jobs in larger towns. The findings suggest a crucial link between urban agglomerations and employment modes in the developing world.

Ethiopia ET: Unemployment: National Estimate: Youth Male: % of Male Labour Force Aged 15-24 data was reported at 17.140 % in 2016. This records a decrease from the previous number of 21.320 % for 2015. Ethiopia ET: Unemployment: National Estimate: Youth Male: % of Male Labour Force Aged 15-24 data is updated yearly, averaging 21.150 % from Dec 2004 (Median) to 2016, with 11 observations. The data reached an all-time high of 28.240 % in 2004 and a record low of 4.090 % in 2005. Ethiopia ET: Unemployment: National Estimate: Youth Male: % of Male Labour Force Aged 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ethiopia – Table ET.World Bank: Employment and Unemployment. Youth unemployment refers to the share of the labor force ages 15-24 without work but available for and seeking employment. Definitions of labor force and unemployment differ by country.; ; International Labour Organization, ILOSTAT database. Data retrieved in November 2017.; Weighted Average; The series for ILO estimates is also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.