ANALYTICAL REPORT ON THE 2010 URBAN EMPLOYMENT UNEMPLOYMENT SURVEY

Transcription

1 THE FEDERAL DEMOCRATIC REPUBLIC OF ETHIOPIA CENTRAL STATISTICAL AGENCY ANALYTICAL REPORT ON THE 2010 URBAN EMPLOYMENT UNEMPLOYMENT SURVEY Addis Ababa December 2010 STATISTICAL BULLETIN

2 TABLE OF CONTENT Table of Content List of Summary Tables List of Figures i iii iv Capter I Background to te Survey Introduction Objectives of te Survey Concepts and Definitions of Key Variables Organization of te Report Abbreviation Capter II Survey Metodology Coverage Sample Frame Sample Design Sample Size and Selection Sceme Capter III Size and Socio-demograpic Caracteristics of Urban Population Introduction Distribution of urban population by Region, Sex and Sex Ratio Age-Sex Structure and Sex Ratio of Urban Population Age Dependency Ratio of Urban Population Average Houseold Size and Number of Persons Per Houseold Head Sip Rate of Urban Population Educational Attainment of Urban Population Training Status of Urban Population Marital Status of Urban Population Capter IV Economic Activity Status Introduction Data Collection Approaces of te Economically Active and Non- Active Population Current Activity Status Approac Usual Activity Status Approac

3 4.3 Economically Active and Activity Rate Major Findings of Economic Activity Rates Based on te Current and Usual Activity Status Approac Reasons for Not Being Economically Active Economic Dependency Ratio Based On te Current Activity Status approac Capter V Caracteristics of te Currently Urban Employed Population Introduction Employment to Population Ratio Occupation and Industry Status in Employment Number of Hours Worked Earnings from Paid Employment Sectors of Economic Activities Capter V I Size, Rate and Caracteristics of te currently Urban Unemployed Population Introduction Measurement of Unemployment Size and Rate of Unemployment Urban Yout Unemployment Rate and Sex Unemployment Rate, Literacy status and Educational level Urban Unemployment Rate of Regions Problems of Establising Own Business Unemployment and Marital Status of Urban Population Previous Work Experience Duration of unemployment Annex I Survey Questionnaire Annex II Estimation Procedures of Total, Ratio and Sampling Errors Annex III Estimates and CV's for Selected Tables ii

4 Summary Table 3.1 Summary Table 3.2 Summary Table 3.3 Summary Table 3.4 Summary Table 3.5 LIST OF SUMMARY TABLES Page Distribution of Urban Population by region, Sex and Sex Ratio: Distribution of Urban Population by Age Group, Sex and Sex Ratio, Country Total: Distribution of Urban Population by Region, Sex and Age Dependency Ratio: Distribution of Average Houseold Size by Region and Sex of Head of Houseold: Percentage Distribution of Population of Urban Areas by Region and Number of Houseolds: Summary Table 3.6 Distribution o f Headsip Rate by Region and Sex: Summary Table 3.7 Distribution of Urban Population Aged Ten Years and Over by Sex and Educational Attainment, Country Total: Summary Table 3.8 Proportion of Urban Population Aged Ten Years and Over by Region, Sex and Literacy Status: Summary Table 3.9 Distribution of Urban Population Aged Ten Years and Over by Region, Sex and Training Status: Summary Table 3.10 Percentage Distribution of Population of Urban Areas Aged Ten Years and Over by Sex, Marital Status and Region: Summary Table 4.1 Distribution of Urban Population of Aged Ten Year and Over by Age Group, Sex and Activity Rate Current and Usual Status Approac),During te Five Survey periods, Country Total Summary Table 4.2 Activity Rate of Population Aged Ten Years and Over by Region and Sex (Current and Usual Status Approac), During te Five Survey Periods Summary Table 4.3 Percentage Distribution of Economically Non- active Population of urban Areas by Region and Reason for not Being Active, During te last seven days (Current Status Approac)- country total Summary Table 4.4 Distribution of Population of Urban Areas Aged Ten years and over by Region, Sex and Economic Dependency Ratio During te Five Survey Periods iii

5 Summary Table 5.1 Employment to Population Ratio of Urban Areas by Region and Sex, During te Five Surveys Periods Summary Table 5.2 Percentage Distribution of Employed Population of Urban Areas Aged Ten Years and Over by Sex and Status in Employment, During te Five Survey periods, Country Total Summary Table 5.3 Percentage Distribution Employed Population of Urban Areas Aged Ten Years and Over by Region and Number of Hours Worked Per Week: Summary Table 5.4 Distribution of Employed Population of Urban Areas Aged Ten Years and over by Region and Mean Number of Hours Worked Per Week, During te Five Survey periods-- 54 Summary Table 5.5 Distribution of Paid Employees of Urban Population Aged Ten Years and Over by Major Industrial Divisions, Sex, Percent and Mean Amount of Payment/Earnings Summary Table 5.6 Per Mont, Country Total: Proportion of Urban Employed Population Aged Ten Years and over Wo were Working in te Informal Sector by Region and Sex During te Five Survey Period Summary Table 6.1 Distribution of Unemployment Rate of Population of Urban Areas Aged Ten Years and Over by Sex, Age Group, During te Four Survey Period, Country Total Summary Table 6.2 Distribution of Unemployment Rate of Urban Population Aged Ten Years and Over by Region and Sex, Literacy Status and educational Level During te Five Survey Periods Summary Table 6.3 Distribution of Unemployment Rate for Urban Population Aged Ten Years and Over by Region and Sex, During te Six Survey Periods Summary Table 6.4 Distribution of Unemployed Population of Aged Ten Years and over Wo wants to Establis Own Business by Sex and Type of Problems Faced, During te Five Survey Periods Country-Total-72 Summary Table 6.5 Percentage Distribution of Urban Unemployed Population Aged Ten years and over by Sex, Region and Marital Status: Summary Table 6.6 Percentage Distribution of Urban Unemployed Population Aged Ten Years and Over by Sex, Previous Work Experience, During te Four Survey Periods, Country Total Summary Table 6.7 Percentage Distribution of Unemployed Population of Urban Areas Aged Ten Years and Over by Sex and Duration of Unemployment, During te Five Survey Period Country- Total iv

6 LIST OF FIGURES Figure 3.1 Urban Population Pyramid, Country Total: Figure 3.2 Proportion of Literacy status of Urban population by Sex, Country- Total: Figure 3.3 Distribution of Training Status of Urban Population by Sex, Country Total: Figure 4.1 Age Specific Activity Rate of Population of Urban Areas (Current Status Approac) During te tree survey periods, Country Total: Figure 5.1 Distribution of Urban Population by Employment to Population Ratio and Sexes, During te tree Survey Periods, Country total: Figure 5.2 Distribution of Currently Employed Population of Urban Areas by Major Occupation, Country Total: Figure 5.3 Percentage Distribution of Currently Urban Employed Population by Major Industrial Divisions, Country Total: Figure 5.4 Trends of Mean Number of ours Worked for Urban Employed Population by Sex, During te Five Survey Periods, Country Total Figure 5.5 Proportion of Urban Employed Population Working in te Informal Sector, During te Four Survey Periods Figure 6.1 Trends of Urban Unemployment Rate, During te Tree Survey Periods, Country Total Figure 6.2 Urban Yout Unemployment Aged 15-29, During te Tree Survey Periods, Country Total: Figure 6.3 Unemployment Rate by Literacy Status, During te Four Survey Periods, Country Total: Figure 6.4 Distribution of Urban Unemployment Rate by Educational Level, Country Total: Figure 6.5 Urban Unemployment Rate by Region and Sex Country Total: Figure 6.6 Percentage Distribution of Urban Unemployed Population by Pervious Work Experience, During Te five survey periods, Country Total: v

7 BACKGROUND TO THE SURVEY 1.1 Introduction Statistical information on all aspects of te population is vital for te design, implementation, monitoring and evaluation of economic and social development plan and policy issues. Labour force survey is one of te most important sources of data for assessing te role of te population of te country in te economic and social development process. It is useful to indicate te extent of available and unutilized uman resources tat must be absorbed by te national economy to ensure full employment and economic well being of te population. Statistics on te labour force furter deals wit te measurement of economic activity status and its relationsip between oter social and economic caracteristics of te population. Seasonal and oter variations as well as canges over time in te size and caracteristics of te employment and unemployment can be monitored using up-to-date information from labour force surveys. It is also an input for assessing te meeting of te Millennium Development Goals (MDGs). Furtermore, data on economic activity and oter labour force data would be used as a springboard for monitoring and evaluation of te five years growt and transformation plan tat launced at different levels of te country. In order to fill te gap in data requirement for te purpose of socio-economic development planning, monitoring and evaluation, te Central Statistical Agency (CSA) as been providing labour force and related data at different levels wit various contents and details. Tese include te 1976 Addis Ababa Manpower and Housing Sample Survey, te 1978 Survey on Population and Housing Caracteristics of Seventeen Major Towns, te 1980/81 and 1987/88 Rural Labour Force Surveys (RLFS). Also, te 1984, 1994 and 2007 Population and Housing Censuses and te 1999 and 2005 National Labour Force Surveys provided a compreensive national labour force data representing bot urban and rural areas. Considering te dynamic and sensitive nature of te sector and also in response to te demands of different data users, te CSA ad launced Continuous Urban Employment Unemployment Survey program since Te Agency conducted four surveys in four rounds, tat is, October 2003, April 2004, April 2006 and May Te results of tese surveys were publised in statistical and analytical Bulletin

8 number 301,319,373,469 and 477. Te current Urban Employment Unemployment Survey, wic was conducted from May 20 - June 5, 2010 is te fift series. Unlike te previous surveys, te May 2009 and te current survey of May 2010 information was collected from selected major towns wit population size 100,000 and above including regional capitals and te results was released independently. Tese survey results mainly provide data on te main caracteristics of employed and unemployed, tat is, te work force engaged or available to be engaged in te production of economic goods and services and its distribution in te various sectors of te economy during a given reference period. To capture cild labour data, te former minimum age limit 10 years was lowered down to 5 years during te survey periods May 2009 and May Terefore, te data in tese surveys was collected from tose persons aged five years and over. However, for te purpose of measuring te economic activity status based on Etiopian situation te lower age limit was fixed at ten years. Tis is because cildren in rural and urban areas used to work at teir early age suc as collection of fire wood, looking after cattle, soe siner, street vendor, petty trader etc. Terefore, te May 2010 Urban Employment and Unemployment Survey statistical report is mainly aimed at providing information on te economic caracteristics of te population aged ten years and over. Etiopia being among te African countries wit relatively fast growing population coupled wit developing economies, te proper management and efficient utilization of its work force is essential. In tis respect, te capacity of te economy in absorbing te potential labour force needs to be monitored regularly, and appropriate employment policy sould consequently be adopted. Tus, te level of employment and unemployment of te country is widely used as overall indicators in evaluating te current performance of te economy. Te analysis of te employment status is terefore essential bot in tackling present difficulties and foreseeing future canges. For tis purpose, in tis analytical report, te following key indicators suc as activity rate, employment to population ratio, unemployment rate, te percentage sare of informal sector..,etc., are included. Furtermore, to sow te trends of labour force situations, te comparison of May 2010 survey results was made to tat of te previous survey results.

9 1.2. Objectives of te Survey Te 2010 Urban Employment and Unemployment Survey program was designed to provide statistical data on te caracteristics and size of te economic activity status i.e. employed, unemployed population of te country at urban levels on annual basis. Te data obtained from tis survey will be useful for policy makers, planners, researcers, entrepreneurs, and oter data users. Te specific objectives of te 2010 Urban Employment and Unemployment Survey are: collect statistical data on te potential manpower and tose wo are available to take part in various socio-economic activities; update te data and determine te size and distribution of te labour force participation and te status of economic activity for different sub-groups of te population at different levels of te country; and also to study te socioeconomic and demograpic caracteristics of tese groups; identify te size, distribution and caracteristics of employed population i.e. working in te formal or informal employment sector of te economy and earnings from paid employees and its distribution by occupation and Industry...etc; provide data on te size, caracteristics and distribution of unemployed population and rate of unemployment; provide data tat can be used to assess te situation of women s employment or te participation of women in te labour force; Provide te generated time series data to trace canges over time;

10 1.3. Concepts and Definitions of Key Variables Some of te major operational definitions of basic concepts are given below. Moreover, oter concepts and definitions related to te economic activity status are provided under respective capters. Urban Center: it is defined as a locality wit 2000 or more inabitants. In tis survey, owever, for practical purposes an urban center includes te following regardless of te number of inabitants. a) All administrative capitals i) Regional capitals ii) Zonal capitals not included in (i) iii) Wereda capitals not included in (i) and (ii) iv) Localities wit Urban Dweller's Association (UDAs) not included in (I-iii). b) Municipal town not included in item (a) above. c) All localities wic are not included eiter in item (a) or (b) above, aving a population of 1000 or more persons, and wose inabitants are primarily engaged in non-agricultural activities. Note tat localities wit population less tan 1000 persons sould be considered as rural. Major Urban Centers: For te purpose of tis study, major urban center include tose selected urban centers wit population 100,000 and above. It also includes region capitals irrespective of teir population size. Urban Kebele: is te lowest administrative unit in an urban center wit its own jurisdiction. It is an association of urban dwellers (commonly known as kebele) formed by te inabitants. Enumeration Area (EA): is a unit of land delineated for te purpose of enumerating population and ousing units witout omission and duplication. An EA in rural areas usually consists of ouseolds. On te oter and, an EA in urban areas constitutes ousing units. Houseold: Consists of a person or group of persons, irrespective of weter related or not, wo normally live togeter in te same ouseold and ousing units and ave common cooking and eating arrangements. Housing Unit : is defined as a separate and independent place of abode eiter intended for abitation or not intended for abitation but was occupied as a living quarter by a ouseold during te survey period. Altoug intended for abitation by one ouseold, a ousing unit may, at te time of te survey be occupied by one or more ouseolds or may be used partly for living and partly for establisment.

11 Head of Houseold: is a person wo provides economic supports or manages te ouseolds. Te ead of te ouseold is selected by ouseold members for some reasons of is age or respect regardless of teir sex. Usual Member of a Houseold: a person is considered as usual members of a ouseold if e or se is:- a) Person wo continuously live/reside at least for six monts and ave a common cooking and eating arrangements wit te ouseold; or b) Person wo is temporarily absent from te ouseold at te time of te survey but is absence as not elapsed te six monts criterion. c) House maids, guards, baby sitters, etc wit no oter dwelling and wo were staying wit te ouseold at te time of te survey. d) Persons wo plan to live more tan six monts due to searcing for job and transfer from job etc Organization of te Report Tis analytical report on te findings of Urban Employment and Unemployment Survey mainly provides information on te economic caracteristics of population aged ten years and over. Te analytical report contains six capters. Te first capter covers background to te survey, objectives and concept and definition of key variables and organization of te report. Please note tat detailed information on te contents and organization of te survey questionnaire, training of field staff, organization of field work and data processing procedure are provided in te Statistical Report of te 2010 Urban Employment and Unemployment Survey. Capter II deals wit te survey metodology, were scope and coverage, sample size and response rate were briefly discussed. Capter III deals in brief wit te size and socio-demograpic caracteristics suc as te distribution of urban population by age, sex, age dependency ratio, average ouse old size, eadsip rate, literacy status, educational attainment, training and marital status. Capter IV presents data on te economic activity status of te population aged ten years and over using te usual and current status approac. Capter V deals wit te size, distribution and caracteristics of te employed population wile Capter VI focuses on te size, caracteristics and distribution of te unemployed population and unemployment rate aged ten years and over. Annex I provides survey questionnaire, wile estimation procedures of total, ratio and sampling errors; and estimates of coefficient of variation (CV's) are presented in Annex II and Annex III, respectively.

12 1.5 ABBEREVATIONS CSA- Central Statistical Agency EA - Enumeration Area HH- Houseolds ICSE- International classification of Status in Employment ILO- International Labour Organization CSPro- Census and Survey Processing system ISCO- International Standard Classification of Occupation ISIC- International Standard Industrial Classification of all economic activities ICLS- International Conference on Labour Statistics KILM- Key Indicators of Labour Market MDGs- Millennium Development Goals NIHSP- National Integrated Houseold Survey Program NLFS - National Labour Force Survey NS- Not Stated NOIC- National Occupation and Industrial Classification PASDEP- Plan for Accelerated and Sustained Development to End Poverty PSU- Primary Sampling Unit RLFS- Rural Labour Force Survey SNA- System of National Account SNNPR- soutern Nations, Nationalities and Peoples Region TVET- Tecnical Vocational Educational Training UEUS- Urban Employment and Unemployment Survey UBEUS- Urban Bi-annual Employment and Unemployment Survey

13 2.1 COVERAGE CHAPTER II SURVEY METHODOLOGY Te 2010 Urban Employment and Unemployment Survey (UEUS) covered all urban parts of te country except tree zones of Afar, six zones of Somali, were te residents are pastoralists. Tis survey follows ouseold approac and covers ouseolds residing in conventional ouseolds, tus population residing in te collective quarters suc as universities/colleges, otel/ostel, monasteries and omeless population. etc are not covered by tis survey. It was initially planned to cover 660 EAs and 19,800 ouseolds in te survey, but ultimately 100% of EAs and 99.7% of ouseolds were successfully covered. 2.2 SAMPLING FRAME Te list of ouseolds obtained from te 2007 population and ousing census is used to select EAs. A fres list of ouseolds from eac EA was prepared at te beginning of te survey period. Te list was ten used as a frame in order to select ouseolds from sample EAs. 2.3 SAMPLE DESIGN For te purpose of te survey, te country was divided into two broad categories. Tat is major urban center and oter urban center categories. Category I:- Major urban centers:- In tis category all regional capitals and four oter major urban centers tat ave a ig population size as compared to oters were included. Eac urban center in tis category was considered as a reporting level. Te category as a total of 15 reporting levels. In tis category, in order to select te sample, a stratified two-stage cluster sample design was implemented. Te primary sampling units were EAs of eac reporting level. From eac sample EA 30 ouseolds were ten selected as a Second Stage Unit (SSU). Category II: - Oter urban centers: Urban centers in te country oter tan tose under category I were grouped into tis category. A domain of oter urban centers is formed for eac region. Consequently 8 reporting levels were formed in tis category. Harari, Addis Ababa and Dire Dawa do not ave urban centers oter tan tat grouped in category I. Hence, no domain was formed for tese regions under tis category.

14 A stratified tree stage cluster sample design was adopted to select samples from tis category. Te primary sampling units were urban centers and te second stage sampling units were EAs. From eac EA 30 ouseolds were finally selected at te tird stage and te survey questionnaires administered for all of tem. 2.4 SAMPLE SIZE AND SELECTION SCHEME Category I: - In tis category 394 EAs and 11,820 ouseolds were selected. Sample EAs from eac reporting level in tis category were selected using probability proportional to size systematic sampling; size being number of ouseolds obtained from te 2007 population and ousing census. From te fres list of ouseolds prepared at te beginning of te survey, 30 ouseolds per EA were systematically selected and covered by te study. Category II:-81 urban centers, 266 EAs and 7,980 ouseolds were selected in tis category. Urban centers from eac domain and EAs from eac urban center were selected using probability proportional to size systematic metod; size being number of ouseolds obtained from te 2007 Population and ousing census. From te listing of eac EA ten 30 ouseolds were systematically selected and te study performed on tem. Te distribution of planned and covered EAs and ouseolds and te Estimation procedures are given in te appendix.

15 Appendix I: Number of planned and actually covered sampling units (EAs and ouseolds) of te 2010 (2002 E.C.) Urban Employment and Unemployment Survey (UEUS). Region Stratum Enumeration Areas Houseolds Major urban/ Planned Covered Planned Covered Oter urban Tigray Mekele Tigray oter urban Affar Asayita Affar oter urban Amara Bair dar Gonder Dessie Amara oter urban Oromiya Debrezeit Nazret Jimma Sasmene Oromiya oter urban Somalie Jijiga Somalie oter urban Benisangul Asosa Gumuz Benisangul gumuz oter urban S.N.N.P. Awassa S.N.N.P oter urban Gambela Gambella Gambella oter urban Hareri Hareri Addis ababa Addis ababa Diredawa Diredawa Total

16 CHAPTER III SIZE AND SOCIO - DEMOGRAPHIC CHARACTERISTICS OF 3.1 Introduction URBAN POPULATION Tis capter presents some igligts on te basic socio-demograpic caracteristics of urban population. Te topics covered in tis capter include estimates of urban population size, distribution of urban population by age and sex, sex ratio, age dependency ratio, average ouseold size, eadsip rate, literacy status, educational level and training status. Te figures in tis section refer to te dejure population residing in te conventional ouseolds. Te dejure population comprises all persons wo belong to a given area at a given time by virtue of usual residence. Tus, excluded are visitors, persons residing in collective quarters (otel/ostel, boarding scools, prisons...etc.) as well as omeless persons Distribution of Urban Population by Region, Sex and Sex Ratio Te survey result estimated tat te total urban population of te country as of May 2010 was 12,572,775 of wic 5,993,743 (47.7 percent) are males and 6,579,033 (52.3 percent) are females. Oromia Region wit urban population of 3,602,544 (28.7 percent) followed by Addis Ababa City Administration 2,903,886 (23.1 percent) and Amara Region 2,333,277 (18.6 percent) took te igest sare out of te total urban population of te country, wile te smallest proportions of urban population are observed for Gambella Region (87,172), Harari Region (98,731) and Benisangul- Gumuz Region (113,279), accounted for 0.7 percent, 0.8 percent and 0.9 percent of te total urban population, in tat order (See Summary Table 3.1).

17 Summary Table 3.1 Distribution of Urban Population by Region, Sex and Sex Ratio: 2010 Region Bot Sexes Male Female No. % No. % No. % Sex Ratio Country Total 12,572, ,993, ,579, Tigray 892, , , Affar 178, , , Amara 2,333, ,102, ,230, Oromia 3,602, ,730, ,872, Somali 601, , , Bensangul- Gumuz 113, , , S.N.N.P. 1,539, , , Gambella 87, , , Harari 98, , , Addis Ababa City Administration 2,903, ,351, ,552, Dire Dawa Administration 222, , , Sex ratio is defined as te number of males per 100 females. Te sex composition as an effect on economic activities troug canging te relative size of te working population. Assuming no selective migration, sex ratio in te general population is expected to be 100. Te data in Summary Table 3.1 indicates te overall urban sex ratio to be 91.1, sowing sligt excess of females tan males. Observation of sex ratio by regions reveals females predominantly exceeding males in almost all regions except in Somali Region (103.9) Age-Sex Structure and Sex Ratio of Urban Population Te distribution of urban population of Etiopia by five year age group, sex and sex ratio of urban population is sown in Summary Table 3.2 and grapically in Figures 3.1. Te age structure of te country s population is typical of te pattern observed for te developing countries, tat is, te age pyramid as a broad base at te lower age groups and te proportion in te young age groups was muc iger tan tat of adult and old age groups. Te data in Summary Table 3.2 sow tat 32.6 percent of te population was constituted by cildren below age 15 years. Te proportion aged 15 -

18 29 years was 36.3 percent, caracterizing a young age structure of te urban population. Tose aged years constituted (27.3 percent) and tat of te old age (65 years and over) was only 3.7 percent of te total population. Te percentage of males and females in te age group years is found to be iger as compared to oter age groups. Tis migt be partly due to age sifting and partly due to migration of students from rural to urban areas in searc of education and/or job. Summary Table 3.2 Distribution of Urban Population by Age Group, Sex and Sex Ratio, Country Total: 2010 Age Group Bot Sexes Male Female No. % No. % No. % Sex Ratio All Ages 12,572, ,993, ,579, ,295, , , ,316, , , ,487, , , ,678, , , ,501, , , ,393, , , , , , , , , , , , , , , , , , , , , , , , , , , Evidence suggested tat sex ratio at birt is around 105. However, since mortality rates are greater among males tan females, at iger ages tis ratio tends to reduce as age advances. Te sex ratios at early age below 5 years and te age groups sows excess of males tan females, wile te reverse is true for te rest of oter age groups.

19 Figure 3.1 Urban Population Pyramid - Country Total: Age Dependency Ratio of Urban Population One important implication of te age structure can be explained by te concept of age dependency. Age dependency structure as an effect on te socio-economic development of a country. Hig age dependency ratio indicates te eavy burden on te working age population, as tey ave to support non-working population. All persons in te working age group do not actually participate in economic activities and also all persons outside tese ages are not dependents. In spite of tese, te ratio of persons in te dependent age groups to tose of te working age group provides a useful approximation to economic dependency burden. Te young, old and over all age dependency ratio by region and sex is given in Summary Table 3.3. Young dependency ratio is defined as te ratio of population in te age group 0-14 to tose in te age group multiplied by 100. Similarly, old dependency ratio is defined as te ratio of persons aged 65 and above to tose in te age group multiplied by 100. Te sum of young and old dependency ratios will give te overall dependency ratio.

20 Summary Table 3.3 Distribution of Urban Population by Region, Sex and Age Dependency Ratio: 2010 Regions and Sex All Ages Age Dependency Ratio Young Old Overall Country Total Total 4,099,001 8,004, ,858 12,572, Male 2,025,649 3,744, ,277 5,993, Female 2,073,351 4,260, ,581 6,579, Tigray Total 304, ,570 44, , Male 153, ,723 20, , Female 150, ,847 24, , Affar Total 62, ,048 4, , Male 33,361 50,911 2,603 86, Female 29,303 60,137 2,104 91, Amara Total 755,261 1,473, ,188 2,333, Male 377, ,501 47,319 1,102, Female 377, ,327 56,869 1,230, Oromia Total 1,262,314 2,220, ,425 3,602, Male 619,436 1,054,797 56,140 1,730, Female 642,878 1,166,007 63,286 1,872, Somali Total 278, ,830 12, , Male 145, ,151 5, , Female 133, ,679 7, , Benisangul-Gumuz Total 40,550 69,127 3, , Male 18,786 33,761 2,004 54, Female 21,764 35,366 1,599 58, SNNPR Total 565, ,453 34,590 1,539, Male 284, ,202 16, , Female 281, ,251 17, , Gambella Total 37,510 48, , Male 19,212 21, , Female 18,297 27, , Harari Total 28,136 65,481 5,114 98, Male 14,021 31,276 1,538 46, Female 14,116 34,205 3,576 51, Addis Ababa City Administration Total 692,794 2,081, ,988 2,903, Male 322, ,640 66,802 1,351, Female 370,043 1,119,464 63,185 1,552, Dire Dawa Administration Total 70, ,778 9, , Male 37,158 67,322 4, , Female 33,761 74,456 5, ,

21 At country urban level, te young and old age dependency ratio, defined in te preceding page are estimated to be about 51.2 and 5.9 persons per 100, respectively. Tis means, tere are about 51 young and 6 old persons wo are supported by every 100 working age population. Te igest dependency ratios, tat is, te overall dependency ratios of 94.1 and young dependency ratio of 89.9 found in Somali Region. Tis means for every 100 persons in te productive age groups about 94 overall and 90 young persons are to be supported. Tis followed by Gamebella Region by 78.3 percent per 100 persons. Except in Benisangul-Gumuz and Harari regions, in te rest of oter regions te age dependency ratio for male is iger tan tat of females. Te old dependency ratio is, owever, significantly iger in Tigary and Harari regions constituting 8.2 persons and 7.8 persons, respectively. Te results sould be cautiously interpreted as tese measures are crude because tey do not consider actual engagement in productive activities but calculated based on age category Average Houseold Size and Number of Persons per Houseold Houseold caracteristics affect te social and economic well being of te members of te ouseold. Large ouseold size is associated wit crowding, wic can lead to unfavorable ealt and economic conditions. In view of tis data, ouseold size and distribution of persons per ouseolds can sometimes be used as a proxy of crowdness of population and is used to reflect tat it as great implication to ealt and ousing problems. Average ouseold size defined as te ratio of population living in te ouseolds to tat of te total number of ouseolds. Summary Table 3.4 sows te distribution of average ouseold size by region and sex of ouseold. Te average number of ouseolds is estimated to be about 4 persons in te urban parts of te country. An average ouseold size is significantly iger in male eaded ouseolds tan in female eaded ouseolds, i.e. 4.1 persons against 3.4 persons, respectively. Among regions, te average ouseold size for Somali Region found to be te igest (4.6 persons per ouseold) as compared to oter regions, wile te smallest ouseold size is reported for Affar and Harari Regions (3.4 persons per ouseold in bot cases). Average ouseold size of 4 persons and more is also reported for Addis Ababa City Administration,Somali, SNNP and Gamebella regions. Unanimously, in all regions except Gambella region average ouseold size of male eaded ouseolds is iger tan tat of female eaded ouseolds.

22 Summary Table 3.4 Distribution of Average Houseold Size by Region and Sex of Head of Houseold: 2010 Male Headed Female Headed Total Region Population Size Houseold size Average HH Size Population Size Houseold size Average HH Size Population Size Houseold size Average HH Size Country Total 8,616,751 2,098, ,956,024 1,163, ,572,775 3,261, Tigray 558, , , , , , Affar 134,651 36, ,769 16, ,420 52, Amara 1,573, , , , ,333, , Oromia 2,577, , ,025, , ,602, , Somali 412,540 85, ,756 45, , , Benisangul Gumuz 89,009 23, ,270 9, ,279 32, SNNP 1,164, , , , ,539, , Gambella 47,475 12, ,697 9, ,172 21, Harari 62,676 18, ,055 11, ,731 29, Addis Ababa City Administration 1,852, , ,051, , ,903, , Dire Dawa Administration 145,490 36, ,547 21, ,036 57,

23 Te number of ouseolds classified in to 1 up to 10 ouseolds wic presented in Table 3.5. As observed from te above table, te igest sare nearly alf of te ouseolds occupy 3 persons and less per ouseold. Harari, Affar, Bensangul Gumuz, Amara and Dire Dewa regions reported more tan alf of te total ouseolds occupied less tan 4 persons per ouseold. Summary Table 3.5 Percentage Distribution of Population of Urban Areas by Region and Number of Houseolds: 2010 Region Houseolds Houseold Size No. % Country Total 3,261, Tigray 255, Affar 52, Amara 656, Oromia 940, Somali 131, Benisangul- Gumuz 32, SNNP 384, Gambella 21, Harari 29, Addis Ababa City Admini. 699, Dire Dawa Admini. 57,

24 3.6 Headsip Rate of Urban Population Te eadsip rate denotes te ratio of te number of eads of ouseolds in te specific categories to tat of te total population of te corresponding category. In tis survey, a ead of ouseold is defined as any members of ouseold wo is recognized as a ead by members of a ouseold. Te concept of eadsip rate is an important measure of ouseold formation and ence it is a pivot around wic modern metod of projecting ouseolds and families turns. Headsip rate can be calculated for specific age, sex and marital status, region or oter demograpic variables. In tis sub-section, an attempt is made to examine te pattern of eadsip rate by region and sex. In general, male eadsip rate is iger tan tat of female eadsip rate in all urban areas of te regions reflecting te fact tat males in most societies assume te role of cief bread winner in te ouseolds as well as tey are assumed to be te ones wo mainly bear responsibilities for family affairs, apart from domestic cores. As sown in Summary Table 3.6 te overall eadsip rate for urban areas of te country is about 26 percent of wic female eadsip rate is about 18 percent and male eadsip rate is 35 percent, wic fits to te general expectation. Te igest eadsip rate is reported in Harari and Affar regions in wic nearly one tird of te population are playing te role of eads. Te lowest eadsip rate observed in Somali Region is (21.8 percent).

25 Summary Table 3.6 Distribution o f Headsip Rate by Region and Sex: 2010 Region Population Male Female Total Heads Headsip Rate Population Heads Headsip Rate Population Heads Headsip Rate Country Total 5,993,743 2,098, ,579,033 1,163, ,572,775 3,261, Tigray 408, , , , , , Affar 86,875 36, ,544 16, ,420 52, Amara 1,102, , ,230, , ,333, , Oromia 1,730, , ,872, , ,602, , Somali 306,438 85, ,859 45, , , Benisangul - Gumuz 54,550 23, ,729 9, ,279 32, SNNP 756, , , , ,539, , Gambella 41,111 12, ,061 9, ,172 21, Harari 46,835 18, ,896 11, ,731 29, Addis Ababa City Administration 1,351, , ,552, , ,903, , Dire Dawa Administration 108,515 36, ,521 21, ,036 57,

26 3.7 Educational Attainment of Urban Population In te survey, information on literacy status and educational attainment were collected from every member of persons aged five years and over of te sampled ouseolds. A literate person was defined as one wo as te ability of bot reading and writing in at least one language, and educational attainment refers to igest grade completed for tose wo declare to be literate. In tis survey ig scool/ secondary education not completed comprise tose wo ave completed grade 9-11 in te old Curriculum and tose wo ave completed grade 9 in te new devised curriculum. Respondents wo ave completed grade 10 in te new system and tose wo completed grade 12 in te old program are separately sown as "Hig scool/secondary education completed". Tose respondents wo completed te Diploma or Degree program are categorized as Diploma and above. Te data in Summary Table 3.7 presents te distribution of urban population by sex and education attainment. Te categories of levels of education include Non formal, Grades 1-8, Hig scool/secondary education not completed, Hig Scool/Secondary education completed, TVET 10+1,10+2, Preparatory grade 11 and grade 12, Certificate, Diploma /10+3/ and Above. Tis classification is made in consultation wit te Ministry of Education and takes care of te new revised educational structure in te country. Summary Table 3.7 Distribution of Urban Population Aged Ten Years and Over by Sex and Educational Attainment- Country Total: 2010 Educational Attainment Sex Bot Sexes Male Female No. % No. % No. % All Literate 7,911, ,135, ,775, Non-Formal 158, , , Grade 1-8 4,264, ,080, ,184, Hig Scool/Secondary Education Not Completed 884, , , Hig Scool/Secondary Education Completed 1,311, , , TVET 10+1 & , , , Preparatory 11 and , , , Certificate 73, , , Diploma & Above 962, , , Not Stated 4, , ,

27 Te overall educational composition of te total urban literate population sows tat substantially iger proportion (53.9 percent) attaining primary education (Grade 1-8). On te oter and, tose wo are at te level of 'ig scool/secondary education completed' constituted 16.6 percent of te total literate population. Literate female population tends to concentrate at te lowest levels of education tan teir male counterparts. For instance te proportion of tose wo completed grade 1-8 is 57.9 percent for females and 50.3% for males, were as females wit diploma and above constitutes 9.5 percent against 14.6 percent for te males. Te literacy status of te surveyed urban population aged 10 years and over by region and sex. Accordingly, 79.4 percent were found to be literate and 20.6 percent were illiterate. Consistent wit previous survey results, te proportion of literates among te males (88.3 percent) is iger tan tat of te females (71.6 percent). Te lowest proportion of illiterate as been observed for males (11.7 percent) against (28.4 percent) for females (See Figure 3.2). Te proportion of literate population in urban areas of te country was found to be 77.9 percent in October 2003 survey, 78.8 percent in may 2009 survey and 79.4 percent in May 2010, sowing very small improvement over te last six years (See also Analytical Report of October 2003 and May 2009)

28 According to te results of te data, Addis Ababa City Administration, Harari, SNNP and Oromia regions stood on te top in terms of proportion of literate population, wit more tan 80 percent. Tese are closely followed by Tigray Region (78.6 percent). A significant proportion of illiterate persons were found in Somali and Affar regions 40.9 percent and 30.7 percent, respectively. Summary Table 3.8 Proportion of Urban Population Aged Ten Years and Over by Region, Sex and Literacy Status: 2010 Region Literacy Status All Persons Literate Illiterate Bot Sexes Male Female Bot Sexes Male Female Bot Sexes Male Female Country Total 9,961,607 4,686,119 5,275, Tigray 693, , , Affar 136,347 64,650 71, Amara 1,857, ,785 1,002, Oromia 2,794,009 1,337,459 1,456, Somali 406, , , Bensangul- Gumuz 88,173 43,157 45, SNNP 1,191, , , Gambella 60,817 27,537 33, Harari 80,946 37,614 43, Addis Ababa City Admini. 2,476,443 1,145,218 1,331, Dire Dawa Admini. 175,076 83,986 91, Training Status of Urban Population Training increases te cance of getting employment and develops productivity of workers. In tis survey, every member of te ouseold aged 10 years and over was asked to state weter e/se ad any kind of training, i.e., professional, vocational or tecnical, regardless of te duration of training. Tose persons wo took any sort of training and ad received a certificate or diploma are considered as trained but tose wo do not ave any certified training are described as not trained.

29 Summary Table 3.9 Distribution of Urban Population Aged Ten Years and Over by Region, Sex and Training Status: 2010 Region Training Status All Persons Not Trained Trained Bot Sexes Male Female Bot Sexes Male Female Bot Sexes Male Female CountryTotal 9,961,607 4,686,119 5,275, Tigray 693, , , Affar 136,347 64,650 71, Amara 1,857, ,785 1,002, Oromia 2,794,009 1,337,459 1,456, Somali 406, , , Bensangul- Gumuz 88,173 43,157 45, SNNP 1,191, , , Gambella 60,817 27,537 33, Harari 80,946 37,614 43, Addis Ababa City Admini. 2,476,443 1,145,218 1,331, Dire Dawa Admnistration 175,076 83,986 91, Note: Not Stated cases are not included in te above figures. Summary Table 3.9 presents te training status of urban population aged ten years and over by region and sex. Out of te total urban population aged 10 years and over, about 18.3 percent were described as trained, wile predominately iger proportions, i.e., 81.7 percent as not trained. Furter classification of te trained population by sex reveals tat te proportion of trained males (24.5 percent) are almost double tan tat of te trained females (12.8 percent). Te proportion of trained population by sex in all regions sows te same pattern of males exceeding females. Among regions, te proportion of trained persons is igest for Addis Ababa City Administration (26.6 percent) followed by Harari Region (20.9 percent). On te oter and, te lowest proportion of trained persons are reported in Somali and Affar regions (8.0 percent and 11.7 percent), respectively (See also Figure 3.3).

30 Te proportion of trained persons in urban areas of te country was found to be 12.3 percent in October 2003 survey, 16.7 percent in May 2009 survey and 18.3 percent in May 2010 survey, sowing sligt improvement over te last seven years. 3.9 Marital Status of Urban Population Te survey as collected data on te marital status of urban population aged 10 years and over. Marital status was classified into six major groups, i.e., never married or single, married, divorced, separated, widowed and live togeter. Married person is a person wo is living togeter as a couple bonded by any kind of marital engagement, i.e., weter legal, religious or traditional at te time of te survey. Divorced person is a person wo ad been married but wose marital engagement was dissolved before te date of interview, wile separated persons are considered as tose temporarily separated but did not dissolve teir engagement. A person wo as not remarried after te deat of a spouse is considered as widowed. Te marital status of living togeter refers to a person wo do not ave any legal, religious or traditional marital engagement but live togeter irrespective of weter tey ave cildren or not.

31 Summary Table 3.10 Percentage Distribution of Population of Urban Areas Aged Ten Years and Over by Sex, Marital Status and Region: 2010 Sex and Region All Persons No. % Never Married Marital Status Married Divorced Separated Widowed Live Togeter Not Stated Country Total Bot sexes 9,961, Male 4,686, Female 5,275, Regions Tigray 693, Affar 136, Amara 1,857, Oromiya 2,794, Somali 406, Benisangul-Gumuz 88, SNNP 1,191, Gambella 60, Harari 80, Addis Ababa City Administration 2,476, Dire Dawa Administration 175,

32 Summary Table 3.10 above presents te percentage distribution of te marital status of respondents aged 10 years and over by sex and region. Te result indicates tat 50.9 percent of te population aged 10 years and over residing in urban areas are never married. About 37.1 percent are married, wile about 11.6 percent of te population as once been in marriage but dissolved permanently or temporarily troug a divorce, separation or deat of spouse. Te data among sexes revealed tat 56.6 percent of males and 45.8 percent of females are never married, 38.8 percent of te males and 35.5 percent of te females are married, wile about 4.3 percent of te males and 18.2 percent of te females are divorced, separated or widowed. Furtermore, it is observed tat te proportion of single is igest (56.8 percent) in Addis Ababa City Administration followed by SNNP and Somali regions (53.3 percent and 50.4 percent), respectively. Te proportion of divorce was found to be igest in Tigray Region (7.2 percent) followed by Amara Region (7.1 percent), wereas, regarding separated persons te igest proportion is reported in Harari region (9.3 percent) followed by Dire Dawa administration and Affar regions (7.5 percent and 7.1 percent), respectively.

33 Notice: Note tat tis analytical report presents te key findings and summary tables from different survey results tat ave been conducted by CSA since Comparison of te latest May 2010 survey results wit tat of te previous survey results as been made in te subsequent capters. Te detailed information on 2010 survey results are also provided in te statistical report entitled "te 2010 Urban, Employment Unemployment Survey", Statistical Bulletin Number 499, wic was publised in November 2010.

34 CHAPTER IV ECONOMIC ACTIVITY STATUS 4.1 Introduction Tis capter presents te economic activity of urban population. In tis survey, information was collected on economic activities or participation of all persons aged five years and over. However, for te purpose of measuring te economic activity status of te population, te analysis in tis analytical report is based on te population aged ten years and over wic is divided into broad categories of economically active and non active population. Te 2010 Urban Employment and Unemployment Survey administered detailed labour force questions to measure te economic activity status in urban areas of te country. Tis analytical report focuses on te comparison of economic activity rate of te population over time based on different survey results tat as been conducted by CSA wic includes: a) Economic activity rates of te population and reasons for not being economically active during te last seven days for tose wo were not active; b) Economic activity rates of te population during te last twelve monts; c) Te distribution of population aged ten years and over by economic dependency ratios. Te 2010 Urban Employment and Unemployment Survey followed te ILO international standard definitions of economic and non-economic activities. Te concept of economic activity as adopted by te 13 t International Conference on Labour Statistics (ICLS,1982) is defined in terms of te production of goods and/or services tat falls witin te United Nations System of National Accounts (SNA) production boundary (ILO, 1990). Accordingly, in tis report economic activity or productive activity is defined as work, wic involves te production of goods and /or services for sale or excange. In addition, production of goods and services for own consumption or own uses are also considered as economic activities. Tese include production of primary products (agriculture, unting, fising, forestry and logging, mining and quarrying), for own consumption; processing of primary products by te producers temselves;

35 production of oter commodities were part of it is sold on te market; and own account construction and fixed asset formation (expected life use of one year or more). Suc economic activities could be performed for an individual, family or private enterprise, government establisment or social organization. Te remuneration may be on daily, weekly, montly, yearly or contract basis. Te practical activities of apprentices are also considered as economic activities. On te oter and, unpaid ouseold cores suc as preparing food, cleaning te ouse, taking care of cildren are not considered to be economic activities. Similarly, unpaid community and volunteer services are classified as non-economic activities. 4.2 Data Collection Approaces of te Economically Active and Non- active Population In te 2010 Urban Employment and Unemployment Survey, te two approaces were used in te collection of data on economic activity status, tat is, current and usual activity status approaces. Te main difference of tese two approaces is te lengt of te reference period. Te current activity status approac measures te economic activity based on a sort reference period of seven days before te date of interview. Wereas te usual activity status approac, measures te economic activity based on te long reference period of six monts prior to te date of interview. In te rural areas to capture te seasonal variations i.e. te slack and peak periods in te agricultural activities, a longer reference period (i.e. usual status approac) is found to be more appropriate to determine te overall economic activity status of te rural population. In urban areas, te activities are relatively less affected by seasonal variations and ence sorter reference period or te current status approac was found to be more convenient. Terefore, except in tis capter, te consecutive V and VI capters present only te results of te current status approac to measure te economic activity status Current Activity Status Approac In te current activity status approac a series of inquiries related to engagement in economic activity, seeking and availability to work, reason for not being seeking or available to work, etc., were administered to determine te economic activity status of te population during te reference week or te last seven days. Based on tese

36 questions, tose population aged ten years and over are used to divide into te tree mutually exclusive categories: employed, unemployed, and not in te labour force. Te employed and te unemployed population togeter make up te labour force or te currently economically active population. Te tird category represented te population, not currently active, tat is, tose wo neiter engaged nor available to furnis teir labour were considered as economically non active population. Te employed population based on te current activity status approac consists: i) Tose wo were engaged in productive activity at least for four ours during te seven days prior to te date of interview; ii) Persons wo ad regular jobs or business or oldings to return to but wo were temporarily absent from work (i.e. tose wo were not at work or worked less tan four ours) for various reasons suc as illness or injury, oliday or vacation, strike or lockout, and seasonality of work, annual leave, temporarily closure of establisment were also considered as employed. For te detailed information please refer te 2010 UEUS, Statistical Bulletin Number 499, publised in Novemeber, Te currently unemployed population, wic will be defined in detail in Capter VI, consists of persons witout work but looking for work or available and ready to work if any job is found during te reference period of te coming one mont. Te reference period of te coming one mont refers to te survey week plus te consecutive tree weeks. Note tat a person wo is looking for work but engaged in productive activity during te reference period is recorded as employed but not as unemployed Usual Activity Status Approac Te usual activity status approac refers to all persons aged ten years and over weter tey were engaged in productive activities during most of te previous six monts. Tose wo were engaged in productive activities during te reference period were classified as usually employed. In te cases of persons engaged in agriculture, it was decided to classify tem in te usually employed category if tey ave worked during most of te main agricultural seasons of te reference period. Persons wo responded tat tey were not engaged in productive work were furter asked te reasons wy tey were not so engaged during most of te six monts prior to te

37 survey date. Tose wo were not working during most of te reference period and looking for work or available and ready to work considered as usually unemployed. Te usually employed and te usually unemployed persons togeter make up te usually economically active population. On te oter and, tose wo were not engaged in productive activity during most of te last six monts for te following reasons suc as engaged in omemaking activities, attending education, illness, old age/pensioned etc. are classified as population not usually economically active or non-active Economically Active and Activity Rate Tis section presents te size of te economically active and activity rate for te latest survey of May For te purpose of comparison, te activity rate of te pervious Urban Employment and Unemployment survey (i.e., October 2003, April 2004, April 2006 and May 2009) results are also presented in following sub section. Te economic activity rates are relatively a good indicator about te economic condition of an area at a given period of time. Te economic activity rate or labour force participation rate is computed as te percentage of te economically active population over te total of te economically active plus te non-active population Major Findings of Economic Activity Rate Based on te Current and Usual Activity Status Approac According to May 2010 Survey results, te total labour force /economically active population/ of urban areas of te country as measured using te current activity status approac is estimated to be 5,914,979. Tis gives an activity rate of about 59.4 percent, wic is greater tan te activity rate observed for te surveys conducted in October 2003, April 2004 and April 2006 and a little less tan May At country urban level, in all surveys, te activity rates of males are greater tan females. Regarding te relationsip between age and activity rate sows a curve linear association for all te tree survey periods. Te figure exibits, low and increasing labour force participation of persons at a younger ages and ig and relatively stable for middle age (between age group years) and ten after a steady decline at older age groups. Te lowest activity rates were observed in te age group bellow years and above 65 years (See Figure 4.1).

38 Summary Table 4.1 Distribution of Urban Population Aged Ten Years and Over by Age Group Sex and, Activity Rate (Current and Usual Status Age Group and Sex Oct Approac), During te Five Survey Periods, Country Total Economic Activity Rate Current Activity Status Approac Usual Activity Status Approac April 2004 April 2006 May 2010 Oct. April April May May 2009 Rate Economically Active May 2009 Rate Economically Active All Ages Total ,914, ,594,151 Male ,079, ,001,973 Female ,835, ,592, Total , ,895 Male , ,450 Female , , Total , ,959 Male , ,476 Female , , Total ,065, ,758 Male , ,589 Female , , Total ,195, ,125,171 Male , ,002 Female , , Total , ,167 Male , ,760 Female , , Total , ,735 Male , ,396 Female , , Total , ,142 Male , ,661 Female , , Total , ,212 Male , ,866 Female , , Total , ,165 Male , ,970 Female , ,195

39 Summary Table 4.1 ( Cont d) Age Group and Sex October 2003 Economic Activity Rate Current Activity Status Approac Usual Activity Status Approac April 2004 April 2006 May 2009 Rate May 2010 May 2010 Economically October April April May Rate Active Economi cally Active Total , ,953 Male , ,671 Female , , Total , ,156 Male , ,509 Female , , Total , ,838 Male , ,623 Female , ,215

40 As can be seen from Summary Table 4.2, relatively iger activity rates based on te current activity status approac were observed in Addis Ababa City administration followed closely by Harari and Benisangul- Gumuz regions reported more tan 60 percent eac. Te activity rate in SNNP and Oromia regions took te intermediate position and reported 59.5 percent and 58.9 percent, respectively. Te lowest participation rate were observed in Somali Region (45.0 percent) followed by Affar Region (52.0 percent), respectively. Te size of te economically active population during te last six monts prior to te survey date using usual activity status approac along wit te corresponding activity rates by age group for te 2010 survey periods are also presented in Summary Table 4.1. Te survey results sow tat tere were 5,594,151 of a total labour force or economically active population at country urban level. Te corresponding economic activity rate is 56.2 percent. Looking at te activity rates of regions during te last six monts, te igest was reported for Addis Ababa City administration about (60.8 percent), followed by Harari Region (59.0 percent), wile Somali Region as sown te lowest participation rate as compared to te oter regions (41.3 percent). Wit regard to te difference by sex, in all surveys, male dominate over teir female counterparts in terms of activity rate (See also Summary Table 4.2).

41 Summary Table 4.2 Region and Survey Period Activity Rate of Population Aged Ten Years and Over by Region and Sex (Current and Usual status Approac), During te Five Survey Periods Economic Activity Rate Current Activity Status Approac Usual Activity Status Approac Total Male Female Total Male Female Country Total October April April May May Tigray October April April May May Affar October April April May May Amara October April April May May Oromia October April April May May Somali October April April May May Benisangul-Gumuz October April April May May

42 Summary Table 4.2 Cont d Region and Economic Activity Rate Survey Periods Current Activity Status Approac Usual Activity Status Approac Total Male Female Total Male Female S.N.N.P. October April April May May Gambella October April April May May Harari Region October April April May May Addis Ababa City Administration October April April May May Dire Dawa Administration October April April May May Reasons for Not Being Economically Active In tis survey, persons are broadly categorized as active and non-active population as defined in section and of tis capter, te former comprises employed and unemployed persons, wile te latter consists of tose neiter employed nor unemployed or not in te labour force. Persons wo were economically non-active or inactive (i.e., tose wo were not engaged and/or not available to be engaged in productive activities) were asked to state te main reasons for not participating in economic or productive activities. Te size of te current non-active population aged 10 years and over as presented in Summary table 4.3 were 4,046,628 persons, wo were economically non-active during te seven days prior to te survey week. Te igest

43 sare reported for females tan males to be engaged in non-productive activities (i.e percent of females against 40 percent of males). Te majority (68.1 percent) of te economically non-active persons stated scool attendance as a reason for inactivity during te last seven days prior to te survey date. i.e., being a student as a reason for teir inactivity. Homemaking was found to be te second main reason (9.1 percent) for inactivity in urban areas of te country followed by Old age/pension (8.8 percent) and illness or injury (6.3 percent). Being student is more common reason among males (82.2 percent) tan te females (58.7 percent). As expected; omemaking was more common reason for inactivity among females tan males. Similar to te urban areas of te country figure, in all regions, more tan alf of te non-active was found to be students followed by omemakers. Te proportions of omemakers is relatively iger among inactive persons of Affar and Somali regions.

44 Summary Table 4.3 Percentage Distribution of Economically Non-Active Population of Urban Areas by Region and Reason for not Being Active, during te Last Seven Days (Current Status Approac - Country Total): 2010 Reason for Not Being Active Total Non - active Home Injury/ Too Pregnancy Students Illness Makers Disabled Young Remittance Pensioned/ Not Oters Old age Stated Sex and Region No. % Country Total Bot Sexes 4,046, Male 1,606, Female 2,440, Regions Tigray 301, Afar 65, Amara 781, Oromia 1,147, Somali 223, Benisangul- Gumuz 33, S.N.N.P. 482, Gambella 27, Harari 30, Addis Ababa City Administration 878, Dire Dawa Administration 73,

45 4.5. Economic Dependency Ratio Based On te Current Activity Status Approac All persons were not participating in economic activities. Tus, some of te population were not ready or available to work due to various reasons and tey depend for teir living on tose wo ave already engaged or available to be engaged in productive activity. Te ratio of persons in te dependent category to tose of economically active groups provides a useful approximation to economic dependency burden. Te economic dependency ratio is defined as population not in te labour force (i.e., economically non active population aged ten years and over plus tose cildren below ten years of age) to tat of population in te labour force (Sryock, 1976). Summary Table 4.4 presents economic dependency ratio by region and sex during te five survey periods. Te 2010 Urban Employment and Unemployment Survey results sow tat te economic dependency ratio for bot sexes at country level is 113. Tis means for eac 100 economically active persons tere are about 113 dependants to be supported in terms of food, cloting, ealt, education and te like. Except te 2009 survey results, tis measure as sown a decline as compared to tat of te previous similar surveys (121 in October 2003, 132 in April 2004 and 117 in April 2006). In all survey period, females were found to be more dependents as compared to male counterparts. Tis summary Table furter sows a marked difference between regions wit regard to economic dependency ratio. Te igest economic dependency burden in te year 2010 was found in Somali Region (229 dependent persons) followed by Gambella Region about (165 dependent persons and Affar Region (151 dependents). Te lowest dependency ratio as been observed in Addis Ababa City Administration, wic is about 82 dependents followed by Harari Region 97 dependents per 100 economically active persons. Somali and Tigray regions ad te igest economic dependency ratio during te October 2003, April 2004 and April 2006 Urban Employment and Unemployment Survey periods.

46 Summary Table 4.4 Distribution of Urban Population Aged Ten Years and Over by Region, Sex and Economic Dependency Ratio, During te Five Survey Periods Region Country Total Tigray Affar Amara Oromia Somali Bensangul- Gumuz S.N.N.P. Gambella Harari Addis Ababa City Admini. Dire Dawa Admini. October 2003 April 2004 Bot Sexes Male Female April 2006 May 2009 May 2010 October 2003 April 2004 April 2006 May 2009 May 2010 October April 2004 April 2006 May 2009 May 2010

47 CHAPTER V CHARACTERISTICS OF THE CURRENTLY URBAN EMPLOYED POPULATION 5.1 Introduction Te previous capter as defined te economically active population to be te sum of te employed and te unemployed population. Tis capter presents major findings on te size, distribution and caracteristics of te currently employed population based on te definition given in capter IV. Accordingly, te employed population in te current status approac consists of tose wo were engaged in productive activity at least for four ours or more during te seven days prior to te date of te interview. Persons wo ad regular jobs or business or oldings to return to but were absent from work (i.e., not at work or worked less tan four ours) for various reasons were also considered as employed persons. In tis capter, some of te caracteristics of te currently employed population will be presented. Te survey as collected data regarding te size and caracteristics of te currently employed population. For te purpose of tis analytical report, te following major information on employment were selected and presented in te subsequent sections, suc as: Employment to population ratio; Main type of occupation; Main product or service of te establisment or industry; Employment status for main activity; Number of ours worked per week; Earnings from paid employment and Formal and informal sector of economy activity..

48 5.2 Employment to Population Ratio According to te 18 Key Indicators of Labour Market (KILM) used by te ILO, Employment to Population Ratio is calculated as a percentage of total employed persons to tat of te working age population aged ten years and over. Hig employment to population ratio means a large proportion of population is employed, wile low ratio means tat a large sare of te population is not involved directly in productive activities, because tey were eiter unemployed or out of te labour force. According to te data in Summary Table 5.1, te employment to population ratio for urban parts of te country in te year 2010 survey is reported to be 48.2 percent. Tis means, nearly alf of te total population of urban areas of te country aged 10 years and over was working or engaged in productive activities during te reference period. Te employment to population ratio for male is about 58.5 percent, wic is significantly iger tan te ratio for te females 39.0 percent. In 2010 survey periods, employment to population ratio for bot sexes compared to tat of te previous survey was increased by 0.7 percentage point. Te increment for female was 1.7 percentage point as compared to tat of te employment to population ratio of te 2009 survey results wile tat of te males decreased by 5 percentage points. Engagement in productive activity as sown an increasing trend i.e. from 43 percent in 2004 to 48 percent in te year Apparently, in May 2010 Urban Employment Unemployment Survey, te igest employment to population ratio was reported for Benisangul-Gumuz, Harari and SNNP regions, in wic more tan alf of teir population engaged in productive activities, in tat order. Te lowest employment to population ratio is recorded for Somali Region about (39.0 percent).

49 Summary Table 5.1 Employment to Population Ratio of Urban Areas by Region and Sex, During te Five Survey Periods Region Oct April 2004 Employment to Population Ratio Bot Sexes Male Female April May May 2010 Oct. April April May May 2010 Oct. April April May May Rate Employed Rate Employed Rate Employed Population population Population Country Total ,798, ,739, ,058,697 Tigray , , ,033 Affar , , ,331 Amara , , ,998 Oromia ,383, , ,433 Somali , , ,690 Bensangul- Gumuz , , ,945 S.N.N.P , , ,331 Gambella , , ,852 Harari , , ,917 Addis Ababa City Admni ,168, , ,599 Dire Dawa Admin , , ,570

50 5.3 Occupation and Industry In tis survey, te currently employed persons were asked about te type of main activity (occupation) and major product or service of te establisment (industry) in wic tey were engaged during te survey reference period. Te questions used to identify te type of occupation and industry, were left open ended so tat tey will be filled in wit te fullest description and its code in te field. For tose employed persons engaged in multiple activities, te activity tat took te largest sare of te respondents time was taken as te main type of activity. Responses of te type of occupation and industry of employed persons were coded in te field and furter verified at te ead office during data editing and coding stage, using te National Occupation and Industry Classification (NOIC) codebook. Te NOIC codes were adopted from te International Standard Classification of Occupation (ISCO-88) and International Standard Industrial Classification (ISIC, 1990), taking into account te prevailing national socio-economic conditions. Te NOIC uses a 3-digit coding system corresponding to 3 level classifications in successively finer detail. In te case of occupation, tese levels referred as Major group, Sub-major group and Minor group. Similarly, in te case of industry, te levels are ordered as Major division, Sub-major division and Minor division. In te NOIC, te occupational classification was categorized into 9 major groups, 28 sub-major groups and 113 minor groups. Wereas, te industrial classification contains 13, 60, and 159 major, sub-major and minor divisions, respectively. Figure 5.1 below presents te distribution of te currently employed population of urban areas aged 10 years and over by major occupational groups at country level.

51 As observed from Figure 5.2 more tan tree- fift of urban employed population of te country is engaged mainly in tree equally major occupations, namely: service, sop and market sales workers about (23.3 percent), elementary occupation (22.6 percent), and craft and related trades (18.8 percent). Professionals togeter wit tecnician and associate professionals make up 13.2 percent of te employed population. Wile te proportion of tose wo were working in legislation, senior officials and managers is reported te lowest sare only 3.1 percent of te total urban employed population of te country. Figure 5.3 sows te distribution of te urban employed population of te country aged 10 years and over by major industrial divisions. As expected, most urban employed population are absorbed by wolesale and retail trade about 20.0 percent and oter service sectors covers 48.5 percent, wic includes otel and restaurant, public administration; education; oter community, social and cultural and personal service in

52 private ouseolds and Healt and social work; extra-territorial organizations; financial intermediation, electricity, gas and water supply and real estate. Altogeter te service sectors constituted about 68 percent. Manufacturing, mining quarrying and construction took te second position by about 21 percent. Te lowest sare only 11.0 percent contributed by agriculture and related activities in urban areas. As regards by sex females were more dominant tan males in private ouseolds, ealt and social work, otel and restaurant industrial division Status in Employment Status in Employment of a person indicates te level of involvement and degree of decision-making in respective activity. Status in Employment is classified into employee government, employee government parastatal, employee private organization, employee NGO s, domestic employees, oter employees, self-employed, unpaid family worker, employer, apprentice, members of cooperatives and oters.

53 Te percentage distribution of urban employed population of te country by status in employment and sex is presented in Summary Table 5.2. At country urban level, te majority of employed population are self-employed (37.6 percent) followed by tose employed by government 22.0 percent and private organization 19.3 percent. Te paid employees altogeter constitutes about 50.0 percent of te total working population. Paid employees consist of employees of government, government parastatal, private organization, NGO s and Domestic employees. Te data in Summary Table 5.2 also sows tat males are dominant in paid employment except in domestic employees. Te proportion of females wo were unpaid family workers were almost two fold as compared to tat of te males. Te proportion of paid employees found in May 2010 was almost equal as compared to te previous survey results of April However, te proportions of self employed ave sown sligt decline.

54 Summary Table 5.2 Percentage Distribution of Employed Population of Urban Areas Aged ten Years And Over by Sex and Status in Employment, During te Five Survey Periods-Country Total Status in Employment Sex and Survey Periods Bot Sexes Total Employed Population No. % Gov't Employees Gov't Prastitatal Paid employees Private Organization Employees NGO's Employees Domestic Employees Self Employed Unpaid Family Workers Employer Members of Cooperatives Apprentice and Oters Oct ,858, April ,854, April ,836, May ,547, May ,798, Male Oct ,628, April ,625, April ,099, May ,646, May ,739, Female Oct ,229, April ,228, April ,737, May ,900, May ,058, Not Stated

55 5.5 Number of Hours Worked Due to te absence of standard working ours and irregular nature of working days in te informal sectors or in te self employment, data collection and getting accurate data on ours of work was found to be difficult. In addition, te reliability of te data collection is likely to be affected due to memory lapse and lack of knowledge or information about te concepts of time on te part of te respondents. Tus, considering te inerent data collection problem on ours of work, wic is a common problem mainly in developing countries, te figures presented in tese tables sould be regarded as indicative rater tan te true levels of intensity of work. Despite tese, te 2010 Urban Employment and Unemployment Survey included questions on te number of ours worked for two purposes. First, te response on te number of ours worked during te seven days prior to te date of te interview is used to classify weter te respondents is employed or not based on te given minimum criteria i.e. te number of ours worked. As described in Capter IV, persons wo worked at least four ours or more, and tose wo were not working or worked less tan 4 ours but ad a job to return to were considered as employed. Te rest of persons were ten subjected to oter filtering questions on unemployment and inactivity. Te second objective of including questions on number of ours worked was to gater data on te intensity of work among te employed population. According to te resolution concerning statistics on ours actually worked tat adopted by te tent ICLS in 1962 (ILO, 1976), in tis survey included: a) Hours actually worked during normal periods of work and time spent for waiting for te market; b) Time worked in addition to normal periods of work, and generally paid at iger rates tan normal rates (overtime); c) Time spent at place of work on activities suc as te preparation of te work place; repairing, maintenance, preparing and cleaning of tools and oters; d) Time spent at te place of work waiting or standing by for suc reasons as lack of supply of work, break down of macinery, or accidents, or time spent at te place of work during wic no work is done but for wic payment is made under a guaranteed employment contract and; e) Time corresponding to sort rest periods at te work place including tea and coffee breaks.

56 According to tis resolution in recording te number of ours worked, care was taken to exclude ours paid for but not worked, suc as paid annual leave, paid public olidays or paid sick leave. Also excluded are meal breaks, time spent on travel from ome to work and vice versa /for tose wo ave specified place of work/, and ours spent on ouseold activities tat were not considered as productive. For employed persons wo were not at work during te seven days prior to te date of interview, te number of ours of work is recorded as zero. On te oter and, any time tat employed persons ave spent in productive activity in places oter tan work site is considered as working our. Summary Table 5.3 Percentage Distribution of Employed Population of Urban Areas Aged Ten Years and Over by Region and Number of Hours Worked Per Week: 2010 Region Total Employed Population Number of Hours Worked Per Week Not Stated All Regions Tgray Affar Amara Oromia Somali Benisangul- Gumuz S.N.N.P Gambella Harari Addis Ababa City Admini. Dire Dawa Admin No. 4,798, ,572 6, ,409 1,074,913 1,861, , ,101 1,719 % No. 320,729 14, ,497 73,530 96,399 52,487 60,779 - % No. 61,447 2, ,685 15,589 24,613 8,749 6,608 - % No. 907,587 42,600 1, , , , ,409 60,678 - % No. 1,383,062 43,623 1, , , , , , % No. 158,279 3,547-11,248 39,979 62,475 24,193 16,837 - % No. 48,740 1, ,676 17,671 15,671 4,113 2,468 - % No. 607,908 21,509 1,374 84, , ,410 70,563 56, % No. 28, ,379 10,821 7,262 2,793 2,543 - % No. 42,491 1,531-3,615 6,323 21,067 5,285 4,670 - % No. 1,168,220 53, , , , , ,453 1,159 % No. 71,251 2, ,017 11,362 28,000 12,732 10,030 - %

57 Te percentage distribution of urban employed population by number of ours worked and region during te seven days prior to te date of interview is presented in Summary Table 5.3. At country urban level, it is found tat te igest proportion (38.8 percent) of te employed population was working for ours, followed by tose wo worked ours (22.4 percent). Persons, wo ave job attacment but did not work at all for te last seven days (zero working ours) make up 3.9 percent of te employed population. Te majority of urban employed population in most of te regions reported to ave worked between ours except tose in Benisangul-Gumuz and Gambella regions. As can be seen from Summary Table 5.4, at country urban level, te mean number of ours worked in te current survey was reported to be (45 ours). Regarding te number of ours worked by region was reported to be te igest in Tigray Region and Dire Dawa Administration wit a mean number of 51 ours and 50 ours work closely followed by Addis Ababa City administration (49 ours). Wereas te mean number of ours worked in Benisangul-Gumuz Region was found to be te lowest (39 ours) per week. In all regions, te mean number of ours worked for male is iger tan tat of female counterparts. As observed from figure 5.4 sows sligt fluctuation as compared to tat of te previous surveys i.e. te mean number ours worked reported 43 ours in October 2003 and April 2004 and declined to 41 ours in April 2006 and tereafter increase to 45 ours of work in te year 2010.

58 Summary Table 5.4 Distribution of Employed Population of Urban Areas Aged Ten Years and over by Region and Mean Number of Hours Worked Per Week During te Five Survey Periods Mean Number of Hours Worked Per Week Region Bot Sexes Male Female October 2003 April 2004 April 2006 May 2009 May 2010 October 2003 April 2004 April 2006 May 2009 May 2010 October 2003 April 2004 April 2006 May 2009 May 2010 Country Total Tigray Affar Amara Oromia Somali Bensangul-Gumuz S.N.N.P Gambella Harari Addis Ababa Dire Dawa Note: Te survey was not conducted in urban areas of Gambella Region te year 2004

59

60 5.6 Earnings from Paid Employment Paid employment jobs are tose jobs were te employees old explicit (written or oral agreement) or implicit employment contracts, wic give tem a basic remuneration. Some or all of te tools, capitals, equipment, information systems and/or premises used by te employees may be owned by oters, and te employees may work under direct supervision or according to strict guidelines set by te owner(s) or persons in te owners employment. Persons in paid employment jobs are typically remunerated by wages and salaries, but may be paid by commission from sales, by piece rates, bonuses or in kind payments suc as food, ousing or cloting. In tis survey, earnings for employees refer to gross remuneration and include bonus, overtime, allowances and oter benefits tat are obtained only from te main job. Summary Table 5.5 sows te distribution of percent and mean amount of payment/earnings for paid employees by major industrial divisions and sex at country urban level. Te mean amount of earning for te total paid employees of te country is estimated to be 861 Birr per mont. Comparison of mean amount of earning among different sectors (industries) as sown tat te igest amount of average payments per mont is paid to tose wo were working in NGOs and extra territorial organization (1,447 Birr) closely followed by financial intermediation (1,441 Birr). Employees of private ouseolds wit employed persons earn 174 Birr and Employees of otel and restaurant 379 birr earn wic was te least payment per mont. Generally, except in Transport storage and Communication, in most of te industrial divisions, male paid workers earn more tan teir female counterparts.

61

62 Summary Table 5.5 Distribution of Paid Employees of Urban Population Aged Ten Years and Over by Major Industrial Divisions, Sex, Percent and Mean Amount of Payment/Earnings Per Mont Country Total: 2010 Total Paid Employees Percent of Amount of Payment/Earnings Per Mont Major Industrial Divisions and Sex No. % < Not Stated Mean Amount of Earnings Per Mont (In Birr) Total Employed Population Total 2,438, Male 1,432, ,049 Female 1,005, Agriculture, Hunting Forestry & Fising Total 84, Male 57, Female 26, Mining & Quarrying Total 9, Male 8, Female 1, Manufacturing Total 278, Male 176, Female 102, Electricity, Gas and Water Supply Total 36, ,141 Male 26, ,152 Female 10, ,112 Construction Total 203, Male 162, ,059 Female 41, Wolesale and Retail Trade Total 148, Male 92, Female 55,

63 Summary Table 5.5 Cont'd Major Industrial Divisions and Sex Total Paid Employees Percent of Amount of Payment/Earnings Per Mont No. % < Not Stated Mean Amount of Earnings Per Mont (In Birr) Hotels and Restaurants Total 141, Male 51, Female 90, Transport, Storage and Communications Total 160, ,074 Male 143, ,049 Female 16, ,295 Financial Intermediation Total 86, ,441 Male 52, ,603 Female 34, ,193 Real Estate, Renting and Business Activities Total 62, ,168 Male 39, ,319 Female 23, Public Administration and Defence Total 343, ,091 Male 236, ,199 Female 106, Education Total 320, ,117 Male 188, ,257 Female 131, Healt and Social Work Total 139, ,165 Male 64, ,515 Female 75,

64 Summary Table 5.5 Cont'd Major Industrial Divisions and Sex Total Paid Employees Percent of Amount of Payment/Earnings Per Mont No. % < Not Stated Mean Amount of Earnings Per Mont (In Birr) Oter Community, Social and Personal Total 142, Male 86, Female 56, Private Houseolds wit Employed Persons Total 244, Male 23, Female 221, Extra-Territorial Organizations and NGOs Total 30, ,447 Male 21, ,542 Female 9, ,230 Not Stated Total 2, Male Female 1,

65 5.7 Sectors of Economic Activities For statistical purposes, te informal sector is considered as a group of production units, wic according to te definitions and classification provided in te United Nation System of National Accounts (SNA Rev.4), form part of te ouseold sector as ouseold enterprises or, equivalently, unincorporated enterprises owned by ouseolds. Te informal sector is defined irrespective of te kind of work place were te productive activities are carried out, te extent of fixed capital used, te duration of te enterprise and its operation as main or secondary activity of te owner. Tis survey includes questions to identify te sector of economy in wic employed persons are engaged as teir main activity. Te information collected refers to only part of te employed population. Te figures ere were not referring to te wole employed population. Tus, according to te 15 t ICLS recommendations, tose employed persons wo were engaged in subsistence farming and work in private ouseolds were exempted from te analysis of te formal and informal sectors of te economic activity. Employed persons wose employment status was government employee, government parastatal employee, NGOs employee and members of cooperatives were treated as being working in te formal sector. Oter employed persons wose employment status of main activity were employer, private organization employee, self-employed, and apprentice were asked weter te business/enterprise tey were engaged in: a) is keeping book of account tat sow te montly income statement and balance seet; or b) as business/enterprise license. Based on te response to tese two conditions, classification on te sector of economy was made as: formal, informal, or not-identified. Employed persons wo satisfy at least one of te above conditions were considered as employed in te formal sector. For tose wo respond no for te two questions, te activity was taken as informal. Person wo doesn t know te situation about teir main activity/business/ enterprise wit respect to te above questions, were labeled as not-identified.

66 Summary Table 5.6 Proportion of Urban Employed Population Aged Ten Years and over Wo Were Working in te Informal Sector by Region and Sex During te Five Survey Periods Region Total Working Population of May Proportion of Working Population in te Informal Sector 2010 Bot Sexes Male Female Total Male Female October 2003 April 2004 May 2009 May 2010 October 2003 April 2004 May 2009 May 2010 October 2003 Country Total 4,236,521 2,497,679 1,738, Tigray 291, , , Affar 46,071 28,627 17, Amara 817, , , Oromia 1,223, , , Somali 134,238 81,705 52, BeniSangul- Gumuz 41,574 24,292 17, S.N.N.P. 550, , , Gambella 24,572 12,700 11, Harari 39,534 22,516 17, Addis Ababa 1,002, , , Dire Dawa 65,254 39,753 25, Note: Subsistence farmers and domestic workers are not included in te above figures. April 2004 May 2009 May 2010

67 Summary Table 5.6 presents te proportion of urban employed population of te country wo were engaged in te informal sector by region, sex during te four survey periods. According to te May 2010 survey result, in urban areas of te country out of te total 4,236,521 working population 1,445,967 people were engaged in te informal sector, making up about 34 percent of te total employment. Te proportion of employed persons working in te informal sector as been declining witin six years i.e. from 48 percent in October 2003 declined to 46 in April 2004 and furter went down to 34 percent in te year In te four survey periods, te proportions of females wo participate in te informal sector were significantly iger tan tat of males. In May 2010, te proportion of employed population wo were working in te informal sector was recorded te igest percentage sare for Somali Region (46.5 percent) closely followed by Gambella Region (42.1 percent). Te lowest proportion of employed population wo were working in te informal sector was found in Addis Ababa City Administration (20.5 percent). Te decline trend is observed in all regions except in Benisangul-Gumuz and SNNP regions as compared to te previous survey of May 2009.

68 As sown from Figure 5.5 at national urban level, te proportion of working population in te informal sector as declined from 48.3 percent in October 2003 to 45.8 percent in April 2004 and ten to 37 percent in May 2009 and furter decline to 34 percent in 2010 survey periods. During te four survey periods, depicts significantly iger proportion of female participation in te informal sector tan tat of male counterparts.

69 CHAPTER VI SIZE, RATE AND CHARACTERISTICS OF THE CURRENTLY URBAN 6.1. Introduction UNEMPLOYED POPULATION Tis capter presents te size, caracteristics of unemployed population and rate of unemployment by age, sex, educational level at national and regional urban levels. In addition, te percentage distribution of unemployed population in relation to marital status, previous work experience, te type of problem faced to establis own business and duration of unemployment are sown in detail. Even toug, information regarding unemployment was collected based on te current and usual status approaces, te results presented in tis capter refers only to te current activity status approac i.e. te information tat obtained from te last seven days prior to te survey date Measurement of Unemployment According to (ILO, 1990) Unemployment is measured based on te following tree criteria: i) witout work ii) available for work and iii) seeking for work. However, tis definition varies in te context of developing and developed countries. In te developed countries were te labour market is largely organized and te labour absorption is adequate, terefore, te standard definition of unemployment relies on te seeking work criteria. Te standard definition of unemployment tat is based on te "seeking work" criterion can be interpreted as activity or efforts searcing for job by non-working persons during a specified reference period. On te contrary, in developing countries like Etiopia, were tere is no strong labour market information and limited scope, labour absorption is inadequate or were te labour force is dominantly self employed, it was felt tat te above standard definition wit its empasis on seeking work criteria migt ave ad limited relevance, somewat restrictive and migt not fully capture te prevailing employment situation. Hence, te International standard introduced provisions, wic allows for te relaxation of te seeking work criterion in certain situations. Te provisions are two types, namely, partial relaxed and complete relaxed definition of unemployment.

70 In tis survey, Unemployment data was collected in te standard, partially relaxed and completely relaxed options of measurements. After toroug evaluation and assessment of te results obtained using te tree alternative measures; te rates obtained using te completely relaxed definition was found most plausible and ence selected for reporting. Te treatment of eac option was described in detail in te Statistical Report on Urban Employment and Unemployment Survey, November In Etiopia context, were te completely relaxed definition suits, unemployment includes persons witout work and tose wo are available for work, including tose wo were or were not seeking work or discouraged job seekers. Te discouraged job seekers refers to tose unemployed persons wo want a job but did not take any active step to searc for work because tey tougt tat job was not found in te market. Te seeking work criterion ere is completely relaxed and unemployment is based on te witout work and availability criterion only. In tis survey, tose persons aged ten years and over wo did not work or did not ave job were asked to respond weter tey were available or willing to work if job was found during te coming one mont. Te coming one mont refers to te survey week and te subsequent tree weeks after te survey date. Tose wo responded Yes answer to tis question were furter tested weter tey were ready to take a job under prevailing conditions. Based on tese inquires te following results were obtained. 6.3 Size and Rate of Unemployment As described in Capter IV, data on te current unemployment was collected by asking a series of filtering questions to all unemployed persons aged ten years and over. Te unemployment rate is computed as te proportion of te unemployed persons to tat of te total economically active population. Tis can be used to measure te level of unemployed population in a specified area and reference period. Te unemployment rate can also be used to make studies about te differentials among sub groups of te population. Summary Table 6.1 presents te rate of unemployment for October 2003, April 2004, April 2006, May 2009 and te size togeter wit te rate of unemployment for te latest survey of May 2010 by sex and age group at national urban level.

71 Summary Table 6.1 Distribution of Unemployment Rate of Population of Urban Areas Aged Ten Years and Over by Sex, and Age Group, During te Five Survey Periods - Country Total Unemployment Rate Bot Sexes Male Female Age Group October 2003 April 2004 April 2006 May 2009 Rate Size May 2010 May 2010 May 2010 October April April May October April April May Rate Size Rate Size All Ages ,116, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and Over , , , and Over ,107, , , /Yout/ , , ,355 Unemployment Rate Under Different definitions Completely Relaxed ,116, , ,696 Partially relaxed , , ,832 Standard , , ,937

72 Te survey results of te May 2010 reveals tat te overall unemployment rate was 18.9 percent and te corresponding unemployment rates for male and female were 11.0 percent and 27.4 percent, respectively. Tis indicates tat unemployment rate for females are more tan two times iger tan tat of males. One sould note tat te lowest unemployment rate in April 2006 was observed due to te difference in te definition of unemployment. Te 2006 survey result was obtained based on te partially relaxed definition of unemployment. Tis was not similar to te rest of oter surveys tat used te completely relaxed definition of unemployment. Terefore, care sould be taken wen comparing tis survey result to tat of te oter corresponding survey results. Te rate of unemployment in October 2004 and April 2006 are excluded from te grap below due to te difference in te season survey monts and te definition of unemployment, respectively. For te purpose of comparison, tose surveys conducted in te same season of survey monts and te same definition of unemployment used were taken ere below i.e. April 2004, May 2009 and May Te unemployment rate as registered in te Urban Employment and Unemployment surveys sow a down ward trend during te six years period. In April 2004 registered 22.9 percent and tere after went down to 20.4 percent in te year In May 2010, te rate ad furter declined to 18.9 percent. Te comparison of tis rate to tat of April 2004 sows a decline of 4.0 percentage point, wile comparing wit tat of May 2009 survey results, declined by 1.5 percentage point. During te tree survey periods, females were more affected wit te incidence of unemployment tan males. However, te decline of female unemployment rate was relatively iger tan tat of males (See Figure 6.1).

73 6.4 Urban Yout Unemployment Rate and Sex In April 2004 survey periods, unemployment rate for yout aged years was found to be iger and reported one-tird of te total urban unemployed population. However, te decline was observed after five years to 26.0 percent in 2009 and furter went down to 24.5 percent in te year In tis age group younger females were more affected by te incidence of unemployment tan teir male counterparts (See Figure 6.2). 6.5 Unemployment Rate, Literacy Status and educational Level As can be seen from Figure 6.3, trougout te four survey periods te overall unemployment rate for literate is iger tan illiterate persons. Also, te figure sows a continuous decline of unemployment rate for literate during te six years period, wile te decline for illiterate sows some fluctuations.

74 Summary Table 6.2 Distribution of Unemployment Rate of Urban Population Aged Ten Years and Over by Sex, Literacy Status and educational Level, During te Five Survey Periods - Country Total Literacy status and Level of Education Literacy Status Illiterate Literate Educational Level October 2003 April 2004 Unemployment Rate Bot Sexes Male Female April 2006 May 2009 Rate Size May 2010 May 2010 May 2010 October April April October April April May Rate Size May 2009 Rate Size , , , , , ,459 Non Formal Grades 1-8 Hig Scool/ Secondary Education not Completed* Hig Scool/ Secondary , , , , , , , , ,975 Education Completed ** , , ,214 Certificate , , ,984 Diploma or Degree not Completed*** , , ,867 Diploma & Above , , ,423 Not Stated *Include tose wo completed grade 9 in te new devised curriculum and grades 9-11 in old curriculum. **Include tose wo completed grade 10 in te new devised curriculum and grade 12 in old curriculum. *** TVET, Preparatory are included in Diploma or degree not completed.

75 Among te literate group, te rate of unemployment is relatively iger among tose wo did not complete ig scool and ig scool education completed reported equally about (25.0 percent) followed by Diploma or Degree not completed (23.4 percent). In all educational levels, unemployment rate is more pronounced among te females tan males. Te incidence of unemployment was relatively lower for tose wit Diploma and above (11.6 percent) and Non-formal education (12.4 percent) (See Summary Table 6.2 and Figure 6.4). 6.6 Urban Unemployment Rate of Regions Summary Table 6.3 sows distribution of unemployment rate by region and sex for all te five survey periods. Te result of te May 2010 survey depicts ig unemployment rate in Dire Dawa Administration (30.2 percent) and Addis Ababa City Administration (26.9 percent). In te previous surveys, te igest unemployment rate was also recorded for Dire Dawa Administration and Addis Ababa City Administration. Te lowest unemployment rate reported to be 10.1 percent and 12.7 percent, wic is registered for Benisangul- Gumuz and Gambella regions, respectively. Te rates of unemployment for te rest of oter regions fall witin te range of 13 percent to 18 percent. In all Urban Employment and Unemployment Surveys conducted so far and for all regions, te unemployment rates among females were muc iger tan tat of te males.

76 Summary Table 6.3 Distribution of Unemployment Rate for Urban Population Aged Ten Years and Over by Region and Sex, During te Six Survey Periods Unemployment Rate Region Sex October 2003 April 2004 April 2005 /NLFS/ April 2006 May 2009 May 2010 Rate Size Country Total Bot Sexes ,116,512 Male ,816 Female ,696 Tigray Bot Sexes ,472 Male ,639 Female ,832 Affar Bot Sexes ,503 Male ,236 Female ,267 Amara Bot Sexes ,985 Male ,125 Female ,859 Oromia Bot Sexes ,754 Male ,555 Female ,199 Somali Bot Sexes ,643 Male ,784 Female ,859 Benisangul-Gumuz Bot Sexes ,485 Male Female ,595 S.N.N.P. Bot Sexes ,571 Male ,016 Female ,556 Gambella Bot Sexes ,170 Male ,321 Female ,850 Harari Bot Sexes ,661 Male ,831 Female ,830 Addis Ababa City Administration Bot Sexes ,492 Male ,989 Female ,503 Dire Dawa Administration Bot Sexes ,777 Male ,431 Female ,347 Note: 1) Te survey was not conducted in Gamebella Region in te year ) Te rate of unemployment tat obtained from te April 2005 National Labour Force Survey /NLFS/ results was included in te above table for comparison at regional levels.

77 6.7 Problems of Establising Own Business Te unemployed persons were asked about weter tey ave tried to establis teir own business and te type of problems tey faced. From Summary Table 6.4 one can easily see tat te percentage distribution of urban unemployed population wo wanted to establis teir own business reported tat sortage of finance as te main problem tey ave faced wic accounted for 58.1 percent. Te next problem cited by te respondent was lack of working place (land), wic constituted about 12.3 percent. Te five consecutively conducted surveys seem to indicate similarity of te problem but te percentage especially tat of sortage of finance sows a significant sare. In almost all surveys, no significant differences ave been noticed between male and female wit respect to te type of problems tey ave mentioned.

78

79 Summary Table 6.4 Percentage Distribution of Unemployed Population of Urban Areas Aged Ten Years and Over Wo Wants to Establis Own Business by Sex and Type of Problems Faced, During te Five Survey Periods - Country Total All Persons Type of Problems Faced Sex and Survey Period Bot Sexes No % I ave no Problem Sortage of Finance Lack of Training Problem Working of Place/land Lack of Lack of Lack/ Sortage Finance Working Absence Absence & Place & of of Training land License Equipment Do not Know Oters Not Stated October ,010, April , April , May , May , Male October , April , April , May , May Female October , April , April , May , May

80 6.8 Unemployment and Marital Status of Urban Population Te percentage distribution of unemployed persons by marital status is also sown in Summary Table 6.5. In May 2010, te single unemployed persons were 40.8 percent, married 47.8 percent and widowed, divorced and separated togeter covered about 11.0 percent of te total unemployed population. Wit regard to sex, about 66.7 percent of male unemployed and (29.4 percent) of female unemployed were single. Among te married unemployed, 28.4 percent were males and 56.3 percent were females. Te percentage sare of unemployment is iger for female tan males in widowed, divorced and separated category (13.6 percent against 4.5 percent). Regarding te proportion of unemployed by region and marital status, Addis Ababa City Administration reported to ave te igest never married (single) unemployed (50.0 percent), wile te lowest found in Harari Region (23.3 percent) and followed by Somali region (25.9 percent). In te married category, te igest proportion of unemployed population was recorded for in Somali Region (60.7 percent) and te lowest in Addis Ababa City Administration (39.4 percent). Summary Table 6.5 Percentage Distribution of Urban Unemployed Population Aged Ten years and Over by Sex, Region and Marital Status : 2010 Total Unemployed Persons Marital Status Sex and Region Never All Persons % Married Married Divorced Widowed Separated Country Total Live Togeter Bot sexes 1,116, Male 339, Female 776, Regions Tigray 71, Afar 9, Amara 168, Oromiya 263, Somali 24, Benisangul- Gumuz 5, SNNP 100, Gambella 4, Harari 7, Addis Ababa 429, Dire Dawa 30,

81 6.9 Previous Work Experience In tis survey, unemployed persons were asked about teir previous work experience. Summary Table 6.6 presents te percentage distribution of urban unemployed population by sex and previous work experience. Out of te total 1,116,512 urban unemployed persons in te country, 560,548 persons or about 50.2 percent ad no work experience, wile 49.4 percent ave ad previous work experience prior to te survey date. Among tose wo ad work experience more tan alf of were females and two-fift of were males. On te oter and, 57.6 percent of male unemployed and 47.0 percent of female unemployed were first time job seekers. Te latest survey results sowed tat tose unemployed wit pervious work experience were reported iger proportions as compared to te 2009 survey results. Te reverse is true for tose unemployed wit first time job seekers. Summary Table 6.6 Percentage Distribution of Urban Unemployed Population Aged Ten Years and Over by Sex, Previous Work Experience, During te Five Survey Periods - Country Total Previous Work Experience Sex October 2003 April 2004 April 2006 May 2009 percent May 2010 Size Unemployed Wit Work Experience Unemployed Wit Out Work Experience Not Stated Bot Sexes ,078 Male ,366 Female ,712 Bot Sexes ,548 Male ,796 Female ,752 Bot Sexes ,887 Male Female ,233 As it as been sown from Figure 6.6 tat tere was a sift in te size of work experience, tat is, te percentage sare of unemployed wit previous work experience wic previously ad te largest sare was lowered down after te year 2006 as compared to tat of te first time job seekers.

82 6.10 Duration of Unemployment As sown in Summary Table 6.7 below, te majority 28.2 percent of te unemployed persons ave been witout work for 1-6 monts and 24.1 percent for less tan one mont and 17.8 percent for 7-12 monts. Altogeter about 70 percent of te unemployed persons ave been witout work for 12 monts or during te survey period of May Te percentage distribution of urban unemployed population (10.1 percent) remained jobless for monts and 8.4 percent for 96 or more monts. Te rest of tose unemployed remained jobless for monts are accounted for 11.3 percent. Tis olds true for te previous tree surveys. Tere is no significance distinction between te two sexes wit respect to duration of unemployment.

83 Summary Table 6.7 Percentage Distribution of Unemployed Population of Urban Areas Aged Ten Years and Over by Sex and Duration of Unemployment, During te Five Survey Periods- Country Total Duration of Unemployment Survey Periods Sex <1 Monts October 2003 April 2004 April 2006 May Monts 7-12 Monts Monts Monts Monts Monts Monts Monts Monts Bot Sexes Male Female Bot Sexes Male Female Bot Sexes Male Female Bot Sexes Male Female or More Monts May 2010 Percent Total Unemployed Persons Bot Sexes Male Female Bot Sexes 269, , , ,274 50,603 29,725 22,186 14,033 6,744 2,540 93,961 Male 51, ,998 67,905 34,666 14,315 8,609 5,012 4,480 1, ,423 Female 217, , ,790 77,609 36,288 21,116 17,174 9,553 5,412 1,966 70,538

84 Annex I- III Annex I Annex II Survey Questionnaire Estimation Procedures of Total Ratio and Sampling Errors Annex II Estimates of CV s for selected Tables

85 ANNEX III ANNEX TABLE 1. Urban Population Aged Ten Years And Over By Age Group, Sex and Activity Status during te Last Six Monts (Usual Status Approac) - Country Total: 2010 Age Group and Sex All Persons CV Active CV Non Active CV All Ages Total 9,961, ,594, ,367, Male 4,686, ,001, ,684, Female 5,275, ,592, ,683, Total 1,487, , ,343, Male 718, , , Female 769, , , Total 1,678, , ,182, Male 729, , , Female 949, , , Total 1,501, , , Male 673, , , Female 828, , , Total 1,393, ,125, , Male 659, , , Female 733, , , Total 895, , , Male 443, , , Female 451, , , Total 792, , , Male 385, , , Female 407, , , Total 499, , , Male 262, , , Female 237, , , Total 448, , , Male 228, , , Female 220, , , Total 338, , , Male 155, , , Female 182, , , Total 240, , , Male 110, , , Female 129, , , Total 216, , , Male 96, , , Female 120, , , Total 468, , , Male 223, , , Female 245, , ,

86 ANNEX TABLE 2. Urban Population Aged Ten Years And Over By Age Group, Sex and Activity Status During Te Last Seven Days (Current Status Approac) Country Total: 2010 Age Group and Sex All Persons CV Active CV Non-Active CV All Ages Total 9,961, ,914, ,046, Male 4,686, ,079, ,606, Female 5,275, ,835, ,440, Total 1,487, , ,340, Male 718, , , Female 769, , , Total 1,678, , ,139, Male 729, , , Female 949, , , Total 1,501, ,065, , Male 673, , , Female 828, , , Total 1,393, ,195, , Male 659, , , Female 733, , , Total 895, , , Male 443, , , Female 451, , , Total 792, , , Male 385, , , Female 407, , , Total 499, , , Male 262, , , Female 237, , , Total 448, , , Male 228, , , Female 220, , , Total 338, , , Male 155, , , Female 182, , , Total 240, , , Male 110, , , Female 129, , , Total 216, , , Male 96, , , Female 120, , , Total 468, , , Male 223, , , Female 245, , ,

87 ANNEX TABLE 3. Economically Active Urban Population of Major Towns Aged Ten Years and Over by Age Group, Sex, Weter Employed or Not During te Last Six Monts (Usual Status Approac): 2010 Age Group and Sex All Persons CV Active CV Non Active CV All Ages Total 2,373, ,872, , Male 1,254, ,070, , Female 1,118, , , Total 24, , , Male 7, , , Female 17, , , Total 194, , , Male 60, , , Female 133, , , Total 441, , , Male 209, , , Female 231, , , Total 511, , , Male 266, , , Female 245, , , Total 341, , , Male 192, , , Female 148, , , Total 289, , , Male 162, , , Female 127, , , Total 157, , , Male 93, , , Female 63, , , Total 154, , , Male 95, , , Female 58, , , Total 97, , , Male 56, , , Female 40, , , Total 61, , , Male 37, , , Female 23, , , Total 48, , , Male 32, , , Female 15, , , Total 51, , , Male 38, , , Female 12, , ,

88 ANNEX TABLE 4. Economically Active Urban Population of Major Towns Aged Ten Years And Over By Age Group, Sex, Weter Employed or Not During te Last Seven Days (Current Status Approac): 2009 Age Group and Sex All Persons CV Active CV Non -Active CV All Ages Total 2,521, ,894, , Male 1,285, ,082, , Female 1,236, , , Total 24, , , Male 7, , , Female 17, , , Total 211, , , Male 66, , , Female 144, , , Total 476, , , Male 217, , , Female 258, , , Total 547, , , Male 272, , , Female 274, , , Total 359, , , Male 194, , , Female 165, , , Total 300, , , Male 163, , , Female 137, , , Total 166, , , Male 96, , , Female 70, , , Total 162, , , Male 97, , , Female 64, , , Total 104, , , Male 58, , , Female 45, , , Total 64, , , Male 38, , , Female 25, , , Total 51, , , Male 33, , , Female 17, , , Total 52, , , Male 37, , , Female 15, , ,

89 Period of Payment Total Hourly Daily Weekly Fortnigt ANNEX TABLE 5 Paid Employees of Urban Population Urban Areas Aged Ten Years and Over by Sex, Period of Payment and Amount of Total Payment Country Total: Amount of Total Payment (in Birr) Total Paid Employees CV <50 CV CV CV CV CV CV CV Not Stated CV Total 2,438, , , , , , , , , Male 1,432, , , , , , , , , Female 1,005, , , , , , , , , Total 12, , , , , , , Male 9, , , , , Female 2, , Total 107, , , , , , , , , Male 84, , , , , , , Female 23, , , , , , , Total 91, , , , , , , , , Male 72, , , , , , , , Female 18, , , , , , Total 90, , , , , , Male 62, , , , , , Female 27, , , , ,

90 ANNEX TABLE 5 Cont d Period of Payment Amount of Total Payment (in Birr) Total Paid Employees CV <50 CV CV CV CV CV CV CV Not Stated CV Montly Yearly Total 2,099, , , , , , , , , Male 1,180, , , , , , , , , Female 919, , , , , , , , , Total 9, , , , Male 6, , , , Female 3, , Oter/ specify Not Stated Total 25, , , , , , , , Male 16, , , , , , , Female 9, , , , , Total 1, , Male 1, , Female

91 SECTION 4: UNEMPLOYMENT AND CHARACTERISTICS OF UNEMPLOYED PERSONS (For tose aged 10 years and above) SECTION 5: ECONOMIC ACTIVITY DURING THE LAST 6 MONTHS (For members age 5 years and abo Wat step ave For tose wo If opportunities Are you willing to take up Wy are you not For tose wo answered For tose wo Have you For ow For tose coded 4 In Col. 306 you taken mainlyanswered to work exist work for wage or salary on available for Code "2-6" in Col. 405 answered ever done many mo- ACTIVITY STATUS Did you look in searc code "2" in te coming locally prevailing terms or ready a work? Code 1 in Col.407 work in te nts ave Enumerator:- Ask respondents te following questions for work or of work or to sta in Col. 401 one mont are to undertake self-employment Wat type of job past for pay or you been separatelyand mark code "1" and list te activity (ies) Durig te last Interviewer :- Col.506 try to your own business? you willing activity given te necessary are you looking for? Wat are/were te profit? unem- if te respondent was engaged in at least one of te 6 monts ave Ceck in Col. 505 Wat was te main Full Name establis your Wat was te and ready to resources and facility? If te 0= Home maker problems you faced ployed? activities.mark code 2 if participated in 'none of te activity ave you ever total number of weeks reason for not working own business Alternative reason tat work for answer is "Yes" were do you 1= Pregnancy/ Enumerator: to establis your During te last 6 monts, did you engage in any work looked for work economically not active is or not being availabe (Transfer from page1, Col.202) during te last answers are you didn't seek income/ prefer te place of job to be? delivery Read te alternative own Business/ or in any work for pay or profit or family gain or been for work for 3 monts? indicated or try to earning? 2= Student answers if need Enterprise? 1. No available to work weeks or more most of te below establis 3= Disabled arises. 2. Yes, as employee - Did you work as an employee for Government/ in some last 6 monts? All ouseold members are 1= Yes your own 1. Not available 4= Illness/ Injury 1. Self employment 3. Yes, for family Private enterprise? productive transferred in tis column business? 1= Yes 5= Too young 4. Yes, for own - Did you work as mercant? (including petty trade) activity? 2. Less tan 12 weeks 0= Pregnancy/ Line number (Transfer form page1, Col. 201) but Col sall be 2= No 2. Witin tis dwelling. 6=Remmitance 2. Paid employment-private - Did you work as service giving agent be it private or delivery marked " " for members 3. Witin residence village/ 7= Old age/ 3. Paid employment-gov't See alternatives If more tan salaried (suc as barber, soe sining,...etc.)? 1. Home maker aged below 10 years. Alternative 2= No town only Pensioned 4. Any available work answer below one,refers to - Did you work in Agriculture privately/salaried (suc as 1= Yes 2. Student END answers are 4. Only in Urban areas of tis 8= Oters 5. Oters te recent one. plowing and, Cattle rearing, poultry,...etc.)? 3. Disablity Go to indicated country ( Specify) - Did you produce goods for sale (suc as "injera", "Tella"..etc) Go to Col Illness Col. 403 All go to below Go to Col Any were in te country - Did you produce permanent goods for your family? 5. Too young col Overseas only Go to - Did you engage in productive activity for your family 2=No 6. Remittance Col.501 Skip to Col. 409 witout payment? 7. Pensioned/old age - Oter productive activity not mentioned above? 8. Oter /Specify skip to Col. 407 Go to Col.505 Weeks Weeks Weeks 1. Yes Go to No Worked Unemployed Inactive END Column 403 Column 408 Column Pregnancy/delivery 00. I ave no problem 07. Sortage/absence of 1. Searcing vacancy advertising boards 02. Illness/Injury previous work 01. Sortage of finance equipment 2. Troug News paper, Radio and TV 03. Personal/family responsibili09. Tougt no work available 02. Lack of training 08. Don't know 3. I ave unemployment card 04. Responsibility of ome activ10. To start private work, I tougt tere will 03. Problem of working place/land 09. Lack of information 4. Seeking assistance of friends, relatives, etc. 05. Old age/pension be sortage of money, raw material...etc. 04. Lack of finance and training 10. Oters /Specify/ 5. Trying to establis own enterprise 06. Education/Training 11. Too young 05. Lack of working place & finance 6. Direct application to employers 07. Already found/made an 12. Remittance 06. Lack/absence of License 7. Cecking at work sites arrangement for work 13. Culture/believing tat it is te role of Men 8. Oters 08. Possiblity to rejoin my 14. Oters/Specify During te last 6 monts for ow many weeks were you During te last 12 monts for ow many weeks employed? working? During te last 6 monts for ow many weeks were you not working? During te last 6 monts for ow many weeks were you economically not active? If code 1 is filled in

92 ANNEX II Estimation Procedures of Total, Ratio and Sampling Errors Te following formulas were used to estimate te required variables by reporting levels. 1. Estimate of Total Ŷ in Major Urban Domain (Category I) Ŷ Were, = n i W i= 1 j= 1 i M Y ij H i W i = is te basic sampling weigt nm ii 2. Estimate of Total Ŷ in Oter Urban Domain (Category II) Yˆ = n i= 1 n M n i n i j= 1 M H ij ij ij ij k = 1 Y ijk n n i ij = i= 1 j= 1 k = 1 W ij Y ijk Were, W ij = n M n i H M ij ij ij is basic sampling weigt Te following notations were used in te formula: M = Total number of ouseolds in stratum obtained from te sampling frame. M i = Total number of ouseolds in EA/PSU i for major urban domain or in urban center/psu i for oter urban domain, stratum obtained from te sampling frame. H i = Total number of ouseolds obtained from te survey listing in sample EA/PSU i stratum for major urban domain.

93 i = Total number of ouseolds successfully covered in EA/PSU i stratum for major urban domain. M = Total number of ouseolds of te domain in stratum obtained from te n sampling frame = Number of successfully covered urban centers for oter urban domain / covered EAs for major urban domain in stratum. M = Total number of ouseolds in EA/PSUi in stratum obtained from te i sampling frame = Total number of sampled and covered ouseolds in sampled EA/PSU i, and i= stratum Yˆ = Te observed value of caracteristic y for ouseold j, in EA/PSUi, stratum of ij M ij n i = Major Urban Domain = Total number of ouseolds in EA/SSU j, urban centers/psu i and stratum obtained from te sampling frame for oter urban center domain. Number of sample EAs successfully covered in urban center/psu i and stratum for oter urban center domain. H ij = Total number of ouseolds obtained from te survey listing in EA/SSU j, urban ij Y ijk center/psu i and stratum for oter urban center domain = Number of sample ouseolds successfully covered in EA /SSU j, urban center/psu i and stratum for oter urban center domain. = Te observed value of a caracteristic y for ouseold k in EA/SSUj, urban center/psu i and Note: Estimate of total at country level, stratum/domain total estimates. stratum for oter urban domain. Y ˆ, is obtained by summing up Yˆ = ˆ Y

94 4. Sampling Variance of te Estimates: Sampling variance of estimate of stratum total are given by te following formulas: Te variance of domain or reporting total estimate is: = = = + = i j i i ij n i i i i n i i Y Y f f n Y Y n n f Y Var ) (1 1 ) (1 ) ( in wic for major urban centers domains, = = i j ij i i Y W Y 1 ˆ and for oter urban center domain. = = = i ij k ijk n j ij i y W Y 1 1 ˆ = Y V Y V ) ˆ ( ˆ) ( ) ˆ ( ) ˆ ( Y Var Y SE = 5. Coefficient of Variation (CV) and Confidence Interval (CI) Te following formulas were used to calculate CV and CI of te domain (reporting level) total. Te coefficient of variation (CV) of domain total in percentage is: *100 ) ( ) ˆ ( = Y Y VAR Y CV and Ninety-five percent confidence interval (CI) of domain total: ) ˆ ( 1.96* ˆ Y SE Y ± 6. Ratio Estimates: X Y and R X Y R ˆ ˆ ˆ ˆ ˆ ˆ = = Were te numerator and te denominator are estimates of domain totals of caracteristic y and x, respectively. ( ) ( ) ( ) ( ) [ ] X Y Cov R X Var R Y Var X R Var ˆ ˆ ˆ 2 ˆ ˆ ˆ ˆ 1 ˆ, = In wic + = = = = i i ij j i i ij n i i i i i n i i X X Y Y f f n X X n Y Y n n f X Y Cov i ) (1 1 ) (1 ), (