Ethiopia ET: Population: Growth data was reported at 2.464 % in 2017. This records a decrease from the previous number of 2.502 % for 2016. Ethiopia ET: Population: Growth data is updated yearly, averaging 2.702 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 3.601 % in 1992 and a record low of 1.318 % in 1978. Ethiopia ET: Population: Growth data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ethiopia – Table ET.World Bank.WDI: Population and Urbanization Statistics. Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage . Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.; ; Derived from total population. Population source: (1) United Nations Population Division. World Population Prospects: 2017 Revision, (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;

Abstract

The presence of adequate and current statistical data in various economic sectors that are considered essential for development planning, socio-economic policy formulation and economic analysis is vital in promoting the economic development of a country. Based on this general objective, the Central Statistical Agency (CSA) has been conducting surveys of various economic activities, of which, the annual Large and Medium Scale Manufacturing Industries survey is one.

Manufacturing is defined here according to International Standard Industrial Classification (ISIC Revision-3.1) as “the physical or chemical transformation of materials or components into new products, whether the work is performed by power-driven machines or by hand, whether it is done in a factory or in the worker's home, and whether the products are sold at wholesale or retail. The assembly of the component parts of manufactured products is also considered as manufacturing activities.”

CSA has been publishing results of the survey of Manufacturing and Electricity Industries on annual basis since 1968 Ethiopian Calendar to provide users with reliable, comprehensive and timely statistical data on these sectors. In this respect, this survey, which is conducted on annual basis, is the principal source of industrial statistics on large and medium scale manufacturing industries in the country.

The main objectives of the annual survey of Large and Medium Scale Manufacturing and Electricity Industries are to: 1.Obtain basic statistical data that are essential for policy makers, planners and researchers by major industrial group. 2.Collect basic quantitative information on employment, volume of quantitative information on employment, volume of production and raw materials, structure and performance of the country's Large and Medium Scale Manufacturing and Electricity Industries. 3.Compile statistical data which will be an input to the System of National Accounts (SNA), on Large and Medium Scale Manufacturing and Electricity establishments as a whole and by major industrial group. 4.Obtain the number of proprietors engaged in these sectors and find out the major problems that create stumbling blocks for their activities.

Geographic coverage

National

Analysis unit

Establishment/ Enterprise

Universe

The universe of the large and medium scale manufacturing survey is confined to those establishments which engaged 10 persons and above and use power-driven machines and covers both public and private industries in all Regions of the country.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Not applicable - the survey enumerated all manufacturing industries/ enterprises that qualified as large and medium manufacturing industry category.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questinnaire contains the following sections/ items:

Item 1.1. Adress of the establishments: This section has varibles that identify the questionnaire uniquely. The variables are; Killil, Zone, Wereda, Town, Higher, Kebele, House no, Year, ISIC, Establishmnet no, Eelephone no and P.O.Box codes or numbers.

Item 1.2. Address of Head Office if Separated From Factory: In this section information about factory head office is collected (if the factory is separated from the head office). The varibles used to collect the information are; Killil, Zone, Wereda, Town, Higher, Kebele, House no, Telephone no and P.O.Box.

Item 2. Basic Information About The Establishment: This section has questions related to basic information about the establishment.

Item 3.1. Number of Persons Engaged: This section has variables (questions) that used to collect establishment's employees number by employees occupation.

Item 3.2. Number of Persons Engaged by Educational Status: This section has varabils (questions) that used to collect establishment's employees number by their educational status.

Item 3.3. Number of Persons Engaged by Age Group: Contains variables that used to collect information about employees number by employees age group.

Item 3.4. Wages and Salaries and Other Employee Benefits Paid: This section has variables related to wages and other employees benefits by employee occupation.

Item 3.5. Number of Permanent Employees by Basic Salary Group: This section has variables related to salary groups by sex of employees

Item 4.1. Products and By-products: This section has questions related to product produced, produced quantity and sales.

Item 4.2. Service and Other Receipts: Contains questions related to income from different source other than selling the products.

Item 5. Value of Stocks: Contains questions that related to information about materials in the stock.

Item 6.1. Cost and Quantity of Raw Materials, Parts and Containers Used: This section has questions related to principal raw materials, raw material type, quantity, value and source (local or imported).

Item 6.2. Other Industrial Costs: This sections has questions related to other industrial costs including cost of energy and other expenses.

Item 6.3. Other Non-industrial Expenses: Contains questions related to non-industrial expenses like license fee, advertising, stationary, etc.

Item 6.4. Taxes Paid: This section has questions related to taxes like indirect tax and income tax.

Item 7. Fixed Assets and Investment: This section has questions related to fixed assets and investment on fixed assests and working capital.

Item 8.1. Annual Production at Full Capacity: This section has questions about quantity and value of products if the establishment uses its full capacity.

Item 8.2. Estimated Value and Quantity of Raw Materials Needed, at Full Capacity: This section has questions about the estimate of quantity and value of raw materials that needed to function at full capacity.

Item 8.3. The three major problems that prevented the establishment from operating at full capacity.

Item 8.4. The three major problems that are facing the establishment at present.

Cleaning operations

Editing, Coding and Verification: A number of quality control steps were taken to ensure the quality of data. The first step taken in this direction was, to revise the questionnaire, to make it easier for internal consistency checking or editing, both at field and office level. Furthermore, based on this revised questionnaire, revised instruction manual with field editing procedures were prepared in Amharic for both enumerators and supervisors (field editors). Using this manual, some editing and coding were carried out by field editors during the data collection stage.

After the majority of the completed questionnaires were brought back to head office, final editing, coding and verification were performed by editors, statistical technicians and statisticians. Finally, the edited and coded questionnaires were checked and verified by other senior professionals.

Data Entry, Cleaning and Tabulation: The data were entered and verified on personal computers using CSpro (Census and Survey Processing System) Software. Fifteen CSA data entry staff and one data cleaner participated in this activity for fifteen days with close supervision of the activities by two professionals. Then, the data entered were cleaned hundred percent using personal computers in combination with manual cleaning for some serious errors. Finally, the tabulation of the results was processed using the same software by one programmer with technical assistance from Industry, Trade and Services Statistics Department staff.

Abstract

Agriculture is the major contributor to the Ethiopian economy. A majority of the Ethiopian populations are engaged in agriculture to earn their livelihood and most of the nation's exports are made up of agriculture produces. The collection of reliable, comprehensive and timely data on agriculture is, thus, essential for policy formulation, decision making and other uses. In this regard the Central Statistical Agency(CSA) has exerted effort to provide users and policy makers with reliable and timely agriculture data.

The general objectives of CSA's annual Agricultural Sample Survey (AgSS) is to collect basic quantitative information on the country's agriculture that is considered essential for development planning, socio-economic policy formulation, food assistance, etc.

The specific objectives of the Main (“Meher”) season area and production survey are: - To estimate the total cultivated land area, production and yield per hectare of major crops (temporary). - To estimate the total farm inputs applied area and quantity of inputs applied by type for major temporary and permanent crops.

Geographic coverage

The survey covered all sedentary rural agricultural population in all regions of the country except urban and nomadic areas which were not included in the survey.

Analysis unit

Agricultural household/ Holder/ Crop

Universe

Agricultural households

Kind of data

Sample survey data [ssd]

Sampling procedure

The 1998-1999 (1991 E.C) Main ("Mehere") season agricultural survey covered the rural part of the country except two zones in Afar region and six zones in Somalie region that are predominantly nomadic. A two-stage stratified sample design was used to select the sample EAs and the agricultural households. Each zone/ special wereda in the sampled population of Tigray, Afar, Amhara, Oromiya, Somalie, Benishangul_Gumuz, SNNP regions was adopted as stratum for which major finings of the survey are reported. But each of the four regions, namely; Gambela, Harari, Addis Ababa and Dire Dawa were considered as reporting levels. The primary sampling units (PSUs) were enumeration areas (EAs) and agricultural households were the secondary sampling units. The survey questionnaires were administered to all agricultural holders within the sample households. A fixed number of sample EAs was determined fro each stratum/reporting level based on precision of major estimates and cost considerations. Within each stratum EAs were selected using probability proportional to size; size being total number of households in the EAs as obtained form the 1994 population and housing census. From each sample EA, 25 agricultural households were systematically selected for the 'Meher" season survey from a fresh list of households prepared at the beginning of the fieldwork of the survey.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 1998-1999 annual Agricultural Sample Survey used structured questionnaires to collect agricultural information from selected sample households. List of forms in the questionnaire: - AgSS Form 91/0: Used to list all agricultural households and holders in the sample enumeration areas. - AgSS Form 91/1: Used to list selected households and agricultural holders in the sample enumeration areas. - AgSS Form 91/2: Used to collect information about crop condition. - AgSS Form 91/3A: Used to list fields and agricultural practices only pure stand temporary and permanent crops, list of fields and agricultural practices for mixed crops, other land use, quantity of improved and local seeds by type of crop and type and quantity of crop protection chemicals. - AgSS Form 91/3B: Used to collect information about quantity of production of crops. - AgSS Form 91/4A: Used to collect information about results of area measurement and field area measurement. - AgSS Form 91/4B: Used to collect information about results of area measurement and field area measurement. - AgSS Form 91/5: Used to list fields for selecting fields for crop cuttings and collect information about details of crop cutting. - AgSS Form 91/6: Used to collect information about cattle by sex, age and purpose.

Note: The questionnaires are provided as external resource.

Cleaning operations

Editing, Coding and Verification: In order to insure the quality of collected survey data an editing, coding and verification instruction manual was prepared and fifty editors/coders and ten verifiers were trained for two days to edit, code and verify the data using the aforementioned manual as a reference and teaching aid. The filled-in questionnaires were edited, coded and later verified by supervisors on a 100% basis before the questionnaires were sent to the data processing unit for data entry. The editing, coding and verification of all questionnaires was completed in fourty days.

Data Entry, Cleaning and Tabulation: Before starting data entry professional staffs of Agricultural Statistics Department of Central Statistical Authority prepared edit specification that used to developed data entry and cleaning computer programs by data processing staffs using Integrated Microcomputer Processing System (IMPS). The edited and coded questionnaires were captured into computers and later cleaned using cleaning program that was developed for this purpose earlier. Fifty data encoders were involved in this process and it took thirty-five days to complete the job. Finally, using tabulations format provided by the subject matter specialist computer program was developed and survey results were produced accordingly.

Response rate

A total of 1,450 EAs (2.9 % of total EAs in the rural areas of the country) were selected for the survey. However, 22 EAs were not covered by the survey due to various reasons that are beyond the control of the Agency. Thus, the survey succeeded in covering 1428 (98.48%) EAs. With respect to ultimate sampling units, it was planned to cover a total of 36,250 agricultural households for area measurement and 21,750 agricultural households for crop cutting (see Appendix III in the report which is provided as external resource). The response rate was found to be 98.94 % for area measurement and 95.50 % for crop cutting.

Sampling error estimates

Estimation procedures of parameters of interest (total and ratio) and their sampling error is presented in Appendix II of the 1998-1999 annual Agricultural Sample Survey, Volume I report which is provided in this documentation.

Abstract

The sound performance of agriculture warrants the availability of food crops. This accomplishment in agriculture does not only signify the adequate acquisition of food crops to attain food security, but also heralds a positive aspect of the economy. In regard to this, collective efforts are being geared to securing agricultural outputs of the desired level so that self reliance in food supply can be achieved and disaster caused food shortages be contained in the shortest possible time in Ethiopia. The prime role that agriculture plays in a country's political, economic and social stability makes measures of agricultural productions extremely sensitive. Statistics collected on agricultural productions are, therefore, fraught with questions of reliability by data users. To tackle these questions convincingly and dissipate the misgivings of users, information on agriculture has to be collected using standard procedures of data collection. Upholding this principle, the Central Statistical Agency (CSA) has been furnishing statistical information on the country's agriculture since 1980/81 to alert policy interventionists on the changes taking place in the agricultural sector. As part of this task the 2007-08 (2000E.C) Agricultural Sample Survey (AgSS) was conducted to provide data on crop area and production of crops within the private peasant holdings for Main (“Meher”) Season of the specified year.

The general objective of CSA's Agricultural Sample Survey (AgSS) is to collect basic quantitative information on the country's agriculture that is essential for planning, policy formulation, monitoring and evaluation of mainly food security and other agricultural activities.

The specific objectives of Main (“Meher”) Season Post Harvest Survey are: - To estimate the total crop area, volume of crop production and yield of crops for Main (“Meher”) Season agriculture in Ethiopia. - To estimate the total volume of inputs used, inputs applied area and number of holders using inputs. - To estimate the total cultivated area and other forms of land use.

Geographic coverage

The 2007-08 (2000 E.C) annual Agricultural Sample Survey (Meher season) covered the entire rural parts of the country except the non-sedentary population of three zones of Afar and six zones of Somali regions. Accordingly, the survey took into account all parts of Harari, Dire Dawa, and 68 additional Zones / Special weredas (that are treated as zones) of other regions.

Analysis unit

Agricultural household/ Holder/ Crop

Universe

Agricultural households

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame: The list containing EAs of all regions and their respective agricultural households obtained from the 2006/07 (1999 E.C) cartographic census frame was used as the sampling frame in order to select the primary sampling units (EAs). Consequently, all sample EAs were selected from this frame based on the design proposed for the 4 survey. The second stage sampling units, households, were selected from a fresh list of households that were prepared for each EA at the beginning of the survey.

Sample Design: In order to select the sample a stratified two-stage cluster sample design was implemented. Enumeration areas (EAs) were taken to be the primary sampling units (PSUs) and the secondary sampling units (SSUs) were agricultural households. The sample size for the 2007/08 (2000 E.C) agricultural sample survey was determined by taking into account both the required level of precision for the most important estimates within each domain and the amount of resources allocated to the survey. In order to reduce non-sampling errors, manageability of the survey in terms of quality and operational control was also considered. Except Harari and Dire Dawa, where each region as a whole was taken to be the domain of estimation; each zone of a region / special wereda was adopted as a stratum for which major findings of the survey are reported.

Selection Scheme: Enumeration areas from each stratum were selected systematically using probability proportional to size sampling technique; size being number of agricultural households. The sizes for EAs were obtained from the 2006/07 (1999 E.C) cartographic census frame. From the fresh list of households prepared at the beginning of the survey 20 agricultural households within each sample EA were selected systematically. Estimation procedure of totals, ratios, sampling error and the measurement of precision of estimates (CV) are given in Appendix I and II respectively.

Note: Distribution of sampling units (sampled and covered EAs) by stratum is also presented in Appendix III of 2007-2008 Agricultural Sample Survey, Volume I report.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2007-2008 annual Agricultural Sample Survey used structured questionnaires to collect agricultural information from selected sample households. List of forms in the questionnaires: - AgSS Form 2000/0: It contains forms that used to list all households in the sample areas. - AgSS Form 2000/1: It contains forms that used to list selected agricultural households and holders in the sample areas. - AgSS Form 2000/2A: It contains forms that used to collect information about crops, results of area measurements covered by crops and other land uses. - AgSS Form 2000/2B: It contains forms that used to collect information about miscellaneous questions for the holders. - AgSS Form 2000/4: It contains forms that used to collect information about list of temporary crop fields for selecting crop cutting plots. - AgSS Form 2000/5: It contains forms that used to collect information about list of temporary crop cutting results.

Note: The questionnaires are presented in the Appendix IV of the 2007-2008 Agricultural Sample Survey report Volume I.

Cleaning operations

a) Editing, Coding and Verification: Statistical data editing plays an important role in ensuring the quality of the collected survey data. It minimizes the effects of errors introduced while collecting data in the field, hence the need for data editing, coding and verification. Although coding and editing are done by the enumerators and supervisors in the field, respectively, verification of this task is done at the Head Office. An editing, coding and verification instruction manual was prepared and reproduced for this purpose. Then 34 editors-coders and verifiers were trained for two days in editing, coding and verification using the aforementioned manual as a reference and teaching aid. The completed questionnaires were edited, coded and later verified on a 100 % basis before the questionnaires were passed over to the data entry unit. The editing, coding and verification exercise of all questionnaires took 35 days.

b) Data Entry, Cleaning and Tabulation: Before data entry, the Natural Resources and Agricultural Statistics Department of the CSA prepared edit specification for the survey for use on personal computers for data consistency checking purposes. The data on the edited and coded questionnaires were then entered into personal computers. The data were then checked and cleaned using the edit specifications prepared earlier for this purpose. The data entry operation involved about 97 data encoders, 4 data encoder supervisors, 8 data cleaning operators and 57 personal computers. The data entered into the computers using the entry module of the CSPRO (Census and Survey Processing System) software, which is a software package developed by the United States Bureau of the Census. Following the data entry operations, the data was further reviewed for data inconsistencies, missing data … etc. by the regular professional staff from Natural Resources and Agricultural Statistics Department. The final stage of the data processing was to summarizing the cleaned data and produce statistical tables that present the results of the survey using the tabulation component of the PC based CSPRO software produced by professional staff from Data processing Department.

Response rate

To be covered by the survey, a total of 2,200 enumeration areas (EAs) were selected. However, due to various reasons that are beyond control, in 75 EAs the survey could not be successful and hence interrupted. Thus, all in all the survey succeeded to cover 2,125 EAs (96.59%) throughout the regions. The Annual Agricultural Sample survey (Meher season) was conducted on the basis of 20 agricultural households selected from each EA. Regarding the ultimate sampling units, it was intended to cover a total of 44,200 agricultural households, however, 42,523 (96.21%) were actually covered by the survey.

Sampling error estimates

Estimation procedure of totals, ratios, sampling error and the measurement of precision of estimates (CV) are given in Appendix I and II respectively of 2007-2008 Agricultural Sample Survey, Volume I report.

Abstract

The need for comprehensive economic statistics has been recently growing rapidly in most developing countries in view of the use of such statistics in formulating socio-economic development plans in general, and to assess the socio-economic situation at the household level such as the one obained from Household Income, Consumption and Expenditure Survey, on a regular basis are the major sources of these data. The survey provides valuable data, especially for assessment of the impact of policies on the conditions and levels of living of houeholds. It is a well known fact that surveys of Household Income, Consumption and Expenditure usually have the major goal of providing basic data needed for the purpose of designing socio-economic policy as well as other related issues that might arise at the micro level.

The major objectives of the survey are to: - Provide data on the levels, distribution and pattern of household income, consumption and expenditure that will be used for analysis of changes in the levels of living standards of households over time in various socio-economic groups and geographical areas. - Obtained information for the formulation of socio-economic plans and policies. - Furnish bench mark data for assessing the impact of existing or proposed socio-economic programs on household living conditions. - Provide data for compiling household accounts in the system of national accounts, especially in the estimation of private consumption expenditure. - Obtain weights and other useful information for the construction of consumer price indices at various levels.

Geographic coverage

The 1999-2000 Household Income, Consumption and Expenditure Survey covered all parts of the country on sample basis except the non sedentary population in Afar and Somali regions.

Analysis unit

• Households
• Individuals
• Consumption expenditure commodities/ services

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLE DESIGN

The 1999-2000 Household Income, Consumption, and Expenditure Survey covered both the urban the sedentary rural parts of the country. The survey has not covered six zones in Somalia Region and two zones in Afar Region that are inhabited mainly by nomadic population. For the purpose of the survey, the country was divided into three categories. That is, the rural parts of the country and the urban areas that were divided into two broad categories taking into account sizes of their population.

Category I: Rural parts of nine Regional States and two administrative regions were grouped in this category each of which was the survey domains (reporting levels). These regions are Tigray, Afar, Amhara, Oromia, Somalia, Benishangul-Gumuz, SNNPR, Gambela, Harari, Addis Ababa and Dire Dawa.

Category II: All regional capitals and five major urban centers of the country were grouped in this category. Each of the urban centers in this category was the survey domain (reporting level) for which separate survey results for major survey characteristics were reported.

Category III: Urban centers in the country other than the urban centers in category II were grouped in this category and formed a single reporting level.

Other than the reporting levels defined in the category II and category III one additional domain, namely total urban (country level) can be constructed by combining the basic domains defined in the two categories. All in all 35 basic rural and urban domains (reporting levels) were defined for the survey. In addition to the above urban and rural domains, survey results are to be reported at regional and country levels by aggregating the survey results for the corresponding urban and rural areas. Definition of the survey domains was based on both technical and resource considerations. More specifically, sample size for the domains were determined to enable provision of major indicators with reasonable precision subject to the resources that were available for the survey.

SELECTION SCHEME AND SAMPLE SIZE IN EACH CATEGORY: 1) Category I: A stratified two-stage sample design was used to select the sample in which the primary sampling units (PSUs) were EAs. Sample enumeration areas (EAs) from each domain were selected using systematic sampling that is probability proportional to size; size being number of households obtained from the rural parts of the country. Within each sample EA a fresh list of households was prepared at the beginning of the survey's field work and for the administration of the survey questionnaire 12 households per sample EA for rural areas were systematically selected.

2) Category II: In this category also, a stratified two-stage sample design was used to select the sample. Here a strata constitutes all the "Region State Capitals" and the five "Major Urban Centers" in the country and are grouped as a strata in this category. The primary sampling units (PSUs) are the EA's in the Regional State Capitals and the five major urban centers and excludes the special EAs (non-conventional households). Sample enumeration areas (EAs) from each stratum were selected using systematic sampling probability proportional to size, size being number of houesholds obtained from the 1994 population and housing census. A total of 373 EAs were selected from this domain of study. Within each sample EAs a fresh list of households was prepared at the beginning of the survey's field work and for the administration of the questionnaire 16 houeholds per sample EA were systematically selected.

3) Category III: Three-stage stratified sample design was adopted to select the sample from domains in category III. The PSUs were other urban centers selected using systematic sampling that is probability proportional to size; size begin number of households obtained from the 1994 population and housing census. The secondary sampling units (SSUs) were EAs which were selected using systematic sampling that is probability proportional to size; size being number of households obtained from the 1994 population and housing census. A total of 169 sample EAs were selected from the sample of other urban centers and was determined by proportional allocation to their size of households from the 1994 census. Ultimately, 16 households within each of the sample EAs were selected systematically from a fresh list of households prepared at the beginning of the survey's fieldwork for the administrator of the survey questionnaire.

Mode of data collection

Face-to-face [f2f]

Research instrument

The Household Income, Consumption and Expenditure Survey questionnaire contains the following forms: - Form 1: Area Identification and Household Characteristics - Form 2A: Quantity and value of weekly consumption of food and drinks consumed at home and tobacco/including quantity purchased, own produced, obtained, etc for first and second week. - Form 2B: Quantity and value of weekly consumption of food and drinks consumed at home and tobacco/including quantity purchased, own produced, obtained, etc for third and fourth week . - Form 3A: All transaction (income, expenditure and consumption) for the first and second weeks except what is collected in Forms 2A and 2B - Form 3B: All transaction (income, expenditure and consumption) for the third and fourth weeks except what is collected in Forms 2A and 2B - Form 4: All transaction (expenditure and consumption) for last 6 months for Household expenditure on some selected item groups - Form 5: Cash income and receipts received by household and type of tenure. The survey questionnaire is provided as external resource.

Cleaning operations

Due to complex nature and magnitude of the survey, CSA has given special attention to the data processing activity. Thus, a task force comprising of subject matter specialists and data processing experts was formed to oversee the data processing and analysis activities of the HIES starting from August 1999. After the completion of the first round of the survey data collected operation, the filled-in questionnaires were retrieved from the field, the task force embarked on the first stage of data processing activities, i.e. manual editing, coding and verification. Experienced editors-coders and verifiers have been deployed for this activities. Considering the complication of the data collected in this survey the editing, coding and verification of the questionnaires have taken the most part of the three months after which data entry was started.

For the data entry activity, the Integrated Microcomputer Processing System (IMPS) software was used throughout. To speed up this process, experienced data entry operators were used and the data entry activity was completed in December 1999. The survey data collected during the second round (January 1999 - February 2000) have also passed through all the data processing activities stated above for the first round.

After the data entry of both rounds of the survey has been completed, the next step in the data processing activity was to merge the data from the first and the second rounds of the survey. Unlike the 1995-1996 Household Income, Consumption and Expenditure Survey, which was done with the help of a short term consultancy services provided by Statistics Norway, the merging operation of these surveys was successfully completed in October 2000 by the programmers in the Data Processing Department of the CSA, after which data cleaning, detailed and through consistency checking were done. In fact, the data cleaning and the consistency

United States Imports from Ethiopia of Office machines not specified elsewhere was US$6.84 Thousand during 2014, according to the United Nations COMTRADE database on international trade. United States Imports from Ethiopia of Office machines not specified elsewhere - data, historical chart and statistics - was last updated on June of 2025.

Ethiopia ET: Population: Total data was reported at 104,957,438.000 Person in 2017. This records an increase from the previous number of 102,403,196.000 Person for 2016. Ethiopia ET: Population: Total data is updated yearly, averaging 45,695,488.500 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 104,957,438.000 Person in 2017 and a record low of 22,151,278.000 Person in 1960. Ethiopia ET: Population: Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ethiopia – Table ET.World Bank: Population and Urbanization Statistics. Total population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship. The values shown are midyear estimates.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Sum; Relevance to gender indicator: disaggregating the population composition by gender will help a country in projecting its demand for social services on a gender basis.

Abstract

The general objective of CSA's Agricultural Sample Survey (AgSS) is to collect basic quantitative information on the country's agriculture that is essential for planning, policy formulation, monitoring and evaluation of mainly food security and other agricultural activities. The AgSS is composed of four components: Crop Production Forecast Survey, Meher Season Post Harvest Survey, Livestock Survey and Belg Season Survey.

The specific objectives of Meher Season Post Harvest Survey are to estimate the total crop area, volume of crop production and yield of crops for Meher Season agriculture in Ethiopia. The report is based on private peasant holdings in rural sedentary areas of the country and part of companion reports on the performance of agriculture in the country. The report is compiled at regional and zonal level.

Geographic coverage

The 2008-2009 (2001 E.C) annual Agricultural Sample Survey ("Meher" season) covered the entire rural parts of the country except the non-sedentary population of three zones of Afar & six zones of Somali regions. Accordingly the survey took into account of all parts of Harari, Dire Dawa, and 68 Zones / special weredas (that are treated as zones) of other regions

Analysis unit

Agricultural household/ Holder/ Crop

Universe

Agricultural households

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING FRAME: The list containing EAs of all regions and their respective households obtained from the 1999 E.C cartographic census frame was used as the sampling frame in order to select the primary sampling units (EAs). Consequently, all sample EAs were selected from this frame based on the design proposed for the survey. The second stage sampling units, households, were selected from a fresh list of households that were prepared for each EA at the beginning of the survey.

SAMPLE DESIGN: In order to select the sample a stratified two-stage cluster sample design was implemented. Enumeration areas (EAs) were taken to be the primary sampling units (PSUs) and the secondary sampling units (SSUs) were agricultural households. The sample size for the 2008/09 agricultural sample survey was determined by taking into account of both the required level of precision for the most important estimates within each domain and the amount of resources allocated to the survey. In order to reduce non-sampling errors, manageability of the survey in terms of quality and operational control was also considered. Except Harari, and Dire Dawa, where each region as a whole was taken to be the domain of estimation; each zone of a region / special wereda was adopted as a stratum for which major findings of the survey are reported.

SELECTION SCHEME: Enumeration areas from each stratum were selected systematically using probability proportional to size sampling technique; size being number of agricultural households. The sizes for EAs were obtained from the 1999 E.C cartographic census frame. From the fresh list of households prepared at the beginning of the survey 20 agricultural households within each sample EA were selected systematically.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2008-2009 annual Agricultural Sample Survey used structured questionnaires to collect agricultural information from selected sample households. List of forms in the questionnaires: - AgSS Form 2001/0: It contains forms that used to list all households in the sample areas. - AgSS Form 2001/1: It contains forms that used to list selected agricultural households and holders in the sample areas. - AgSS Form 2001/2A: It contains forms that used to collect information about crops, results of area measurements covered by crops and other land uses. - AgSS Form 2001/2B: It contains forms that used to collect information about miscellaneous questions for the holders. - AgSS Form 2001/4: It contains forms that used to collect information about list of temporary crop fields for selecting crop cutting plots. - AgSS Form 2001/5: It contains forms that used to collect information about list of temporary crop cutting results.

Note: The questionnaires are presented in the Appendix IV of the 2008-2009 Agricultural Sample Survey report Volume I.

Cleaning operations

a) Editing, Coding and Verification Statistical data editing plays an important role in ensuring the quality of the collected survey data. It minimizes the effects of errors introduced while collecting data in the field, hence the need for data editing, coding and verification. Although coding and editing are done by the enumerators and supervisors in the field, respectively, verification of this task is done at the Head Office.

An editing, coding and verification instruction manual was prepared and reproduced for this purpose. Then 54 editors-coders and verifiers were trained for two days in editing, coding and verification using the aforementioned manual as a reference and teaching aid. The completed questionnaires were edited, coded and later verified on a 100 % basis before the questionnaires were passed over to the data entry unit. The editing, coding and verification exercise of all questionnaires took 21 days.

b) Data Entry, Cleaning and Tabulation Before data entry, the Natural Resources and Agricultural Statistics Department of the CSA prepared edit specification for the survey for use on personal computers for data consistency checking purposes. The data on the edited and coded questionnaires were then entered into personal computers. The data were then checked and cleaned using the edit specifications prepared earlier for this purpose. The data entry operation involved about 90 data encoders, 10 data encoder supervisors, 13 data cleaning operators and 55 personal computers. The data entered into the computers using the entry module of the CSPRO (Census and Survey Processing System) software, which is a software package developed by the United States Bureau of the Census. Following the data entry operations, the data was further reviewed for data inconsistencies, missing data ...etc. by the regular professional staff from Natural Resources and Agricultural Statistics Department. The final stage of the data processing was to summarizing the cleaned data and produce statistical tables that present the results of the survey using the tabulation component of the PC based CSPRO software produced by professional staff from Data processing Department.

Response rate

A total of 2,290 Enumeration Areas (EAs) were selected. However, due to various reasons that are beyond control, in 48 EAs the survey could not be successful and hence interrupted. Thus, all in all the survey succeeded to cover 2242 EAs (97 %) throughout the regions. The Annual Agricultural Sample survey (Meher season) was conducted on the basis of 20 agricultural households selected from each EA. Regarding the ultimate sampling units, it was intended to cover a total of 45,800 agricultural households, however, 44,922 (98 %) were actually covered by the survey.

Sampling error estimates

Estimation procedure of totals, ratios, sampling error and the measurement of precision of estimates (CV) are given in Appendix I and II of Agricultural Sample Survey 2008-2009 report. Distribution of sampling units (sampled and covered EAs and households) by stratum is also presented in Appendix III.

Ethiopia Imports from Indonesia of Office machines not specified elsewhere was US$778 during 2023, according to the United Nations COMTRADE database on international trade. Ethiopia Imports from Indonesia of Office machines not specified elsewhere - data, historical chart and statistics - was last updated on June of 2025.

Abstract

Food security has become a burring issue in Ethiopia since it is an absolute prerequisite for political and social stability. It received national prominence in the aftermath of the recurring drought and famine and obviously became an immediate domestic policy concern. The gap between the dire need for food supply is compounded by rapidly increasing population, depletion of natural resources and the existing traditional way of farming. It even requires sacrifice to provide adequate supply of food in such a situation where natural and human factors have negatively impacted in the agricultural production and resulted in recurrent droughts and sometimes in catastrophe. Pressed by these problems and other economic factors, the Ethiopian government has centered its agricultural policy on ensuring food security by allocating more resources to increase agricultural production so as to ward off food shortage and ensure continuous adequate supply of food. To monitor and evaluate the performance of the policy and the trends in the charging patterns in agricultural, statistical information on agriculture is required as an input since agriculture is a primary activity connected with food availability. The Central Statistical Agency (CSA) has been generating statistical information used as inputs in the formulation of agricultural policies by collecting processing and summarizing reliable, comprehensive and timely data on the country's agriculture. As part of this mission the 2003-2004 (1996 E.C) Annual Agricultural Sample Survey was conducted to furnish data on cropland area and production of crops within the private peasant holdings for Main (“Meher”) season of the quoted year.

The general objective of CSA's annual Agricultural Sample Survey (AgSS) is to collect basic quantitative information on the country's agriculture that is essential for planning, policy formulation, food security, etc. The survey is composed of four components: Crop production forecast survey. Main (“Meher”) season survey, Livestock survey and “Belg” season survey.

The specific objectives of Main (“Meher”) season survey are: - To estimate the total cultivated area, production and yield of crops. - To estimate the total volume of inputs used, inputs applied area and number of holders using inputs. - To estimate the total cultivated area and other forms of land use.

Geographic coverage

The 2003-2004 annual Agricultural Sample Survey covered the entire rural parts of the country except all zones of Gambella region, and the non-sedentary population of three zones of Afar and six zones of Somali regions.

Note: The crop cutting exercise part of the survey from November 2003 up to January 2004 was not done in Gambela regional state, therefore no production estimates for the region was computed for Meher (main) season.

Analysis unit

Agricultural household/ Holder/ Crop

Universe

Agricultural households

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame: The list containing EAs of all regions and their respective agricultural households obtained from the 2001/02 Ethiopian Agricultural Sample Enumeration (EASE) was used as the sampling frame in order to select the primary sampling units (EAs). Consequently, all sample EAs were selected from this frame based on the design proposed for the survey. Sample Design A stratified two-stage cluster sample design was used to select the sample. Enumeration Areas (EAs) were taken to be the primary sampling units (PSUs) and the secondary sampling units (SSUs) were agricultural households. Sample enumeration areas from each stratum were sub-samples of the 2001/02 (1994 E.C) Ethiopian Agricultural Sample Enumeration. They were selected using probability proportional to size systematic sampling; size being number of agricultural households obtained from the 1994 Population & Housing Census and adjusted for the sub-sampling effect. Within each sample EA a fresh list of households was prepared and 25 agricultural households from each sample EA were systematically selected at the second stage. The survey questionnaire was finally administered to the 25 agricultural households selected at the second stage. Information on area under crops and Meher season production of crops was obtained from the 25 households that were ultimately selected. It is important to note, however, that data on crop cutting were obtained only from fifteen sampled households (the 11th - 25th households selected).

The sample size for the 2003-04 agricultural sample survey was determined by taking into account both the required level of precision for the most important estimates within each domain and the amount of resources allocated to the survey. In order to reduce non- sampling errors, manageability of the survey in terms of quality and operational capability was also considered. Except Harari, Addis Ababa and Dire Dawa, where each region as a whole was taken to be the domain of estimation; each zone of a region / special wereda was adopted as a stratum for which major findings of the survey are reported.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2003-2004 annual Agricultural Sample Survey used structured questionnaires to collect agricultural information from selected sample households. List of forms in the questionnaires: - AgSS Form 96/0: Used to list all households and agricultural holders in the sample enumeration areas. - AgSS Form 96/1: Used to list selected households and agricultural holders in the sample enumeration areas. - AgSS Form 96/3A: Used to list fields under temporary crops and farm management practice. - AgSS Form 96/3B: Used to list fields under permanent crops and farm management practice. - AgSS Form 96/3C: Used to list fields under mixed crops and farm management practice. - AgSS Form 96/3D: Used to collect information about other land use type and area and other agricultural related questions. - AgSS Form 96/5: Used to list temporary crop fields for selecting crop fields for crop cutting. - AgSS Form 96/6: Used to collect information about temporary crop cutting results.

Cleaning operations

Editing, Coding and Verification: Statistical data editing plays an important role in ensuring the quality of the collected survey data. It minimizes the effects of errors introduced while collecting data in the field , hence the need for data editing, and verification. An editing, coding and verification instruction manual was perpared and reproduced. Then 65 editors-coders and verifiers were trained for two days in editing , coding and.verification using the aforementioned manual as a reference and teaching aid. The completed questionnaires were edited, coded and later verified on a 1OO % basis before the questioners were passed over to the data entry unit. The editlng, coding and verification exercise of all questionnaires took 40 days.

Data Entry, Cleaning and Tabulation: Before data entry, the Natural resource and Agricultural Statistics Department prepared edit specification for the survey for use on personal computers for data consistency checking purposes . The data on the edited and coded questionnaires were then entered into personal computers. The data were then checked and cleaned using the edit specification prepared earlier for this purpose. The data entry operation involved about 64 data encoders and it took 50 days to finsh the job. Finally, tabulation was done on personal computers to produce statistical tables as per the tabulation plan.

Response rate

A total of 2,072 enumeration areas were initially selected to be covered by the survey, however, due to various reasons 16 EA's were not covered and the survey was successfully carried out in 2,056 (99.23 %) EAs. As regards the ultimate sampling unit, it was planned to conduct the survey on 51,800 agricultural households and 51,300 (99.03 %) households were actually covered by the Meher season Agricultural Sample Survey.

Sampling error estimates

Estimation procedure of totals, ratios, sampling error and the measurement of precision of estimates (CV) are given in Appendix I and II of 2003-2004 Agricultural Sample Survey, Volume I report.

Data appraisal

As it was explained in the response rate under sampling section, the non response rate was minimal. There is no testing for bias made in this survey.

Ethiopia Exports of office machines not specified elsewhere to Oman was US$49 during 2017, according to the United Nations COMTRADE database on international trade. Ethiopia Exports of office machines not specified elsewhere to Oman - data, historical chart and statistics - was last updated on June of 2025.

Ethiopia Exports of office machines not specified elsewhere to Netherlands was US$916 during 2016, according to the United Nations COMTRADE database on international trade. Ethiopia Exports of office machines not specified elsewhere to Netherlands - data, historical chart and statistics - was last updated on June of 2025.

Geographic coverage

National

Analysis unit

• Schools

Kind of data

Administrative records data [adm]

Mode of data collection

Face-to-face [f2f]

The urban indicators data available here are analyzed, compiled and published by UN-Habitat’s Global Urban Observatory which supports governments, local authorities and civil society organizations to develop urban indicators, data and statistics. Urban statistics are collected through household surveys and censuses conducted by national statistics authorities. Global Urban Observatory team analyses and compiles urban indicators statistics from surveys and censuses. Additionally, Local urban observatories collect, compile and analyze urban data for national policy development. Population statistics are produced by the United Nations Department of Economic and Social Affairs, World Urbanization Prospects.

Ethiopia Imports from Ecuador of Office machines not specified elsewhere was US$689 during 2023, according to the United Nations COMTRADE database on international trade. Ethiopia Imports from Ecuador of Office machines not specified elsewhere - data, historical chart and statistics - was last updated on April of 2025.

Statistics illustrates consumption, production, prices, and trade of Base Metal Staples in Strips for Use in Offices in Ethiopia from 2007 to 2024.

United States Immigrants Admitted: Ethiopia data was reported at 14,637.000 Person in 2017. This records an increase from the previous number of 13,232.000 Person for 2016. United States Immigrants Admitted: Ethiopia data is updated yearly, averaging 6,359.500 Person from Sep 1986 (Median) to 2017, with 32 observations. The data reached an all-time high of 16,152.000 Person in 2006 and a record low of 2,156.000 Person in 1987. United States Immigrants Admitted: Ethiopia data remains active status in CEIC and is reported by US Department of Homeland Security. The data is categorized under Global Database’s United States – Table US.G087: Immigration.

Ethiopia ET: Death Rate: Crude: per 1000 People data was reported at 6.825 Ratio in 2016. This records a decrease from the previous number of 6.997 Ratio for 2015. Ethiopia ET: Death Rate: Crude: per 1000 People data is updated yearly, averaging 18.966 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 25.000 Ratio in 1960 and a record low of 6.825 Ratio in 2016. Ethiopia ET: Death Rate: Crude: per 1000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ethiopia – Table ET.World Bank.WDI: Population and Urbanization Statistics. Crude death rate indicates the number of deaths occurring during the year, per 1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;

Abstract

The Ethiopian Rural Socioeconomic Survey (ERSS) is a collaborative project between the Central Statistics Agency (CSA) of Ethiopia and the World Bank Living Standards Measurement Study- Integrated Surveys on Agriculture (LSMS-ISA) team. The objective of the LSMS-ISA is to collect multi-topic panel household level data with a special focus on improving agriculture statistics and the link between agriculture and other sectors of the economy. The project also aims to build capacity, share knowledge across countries, and improve survey methodologies and technology.

The specific objectives of the ERSS are: - Development of an innovative model for collecting agricultural data in conjunction with household data; - Strengthening the capacity to generate a sustainable system for producing accurate and timely information on agricultural households in Ethiopia; - Development of a model of inter-institutional collaboration between the CSA and relevant federal and local government agencies as well as national and international research and development partners; and - Comprehensive analysis of household income, well-being, and socio-economic characteristics of households in rural areas and small towns.

Geographic coverage

Regional Coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

The ERSS sample is designed to be representative of rural and small town areas of Ethiopia. The ERSS rural sample is a sub-sample of the AgSS while the small town sample comes from the universe of small town EAs. The ERSS sample size provides estimates at the national level for rural and small town households. At the regional level, it provides estimates for four regions including Amhara, Oromiya, SNNP, and Tigray.

The sample is a two-stage probability sample. The first stage of sampling entailed selecting primary sampling units , which are a sample of the CSA enumeration areas (EAs). For the rural sample, 290 EAs were selected from the AgSS EAs. The AgSS EAs were selected based on probability proportional to size of the total EAs in each region. For small town EAs, a total of 43 EAs were selected. In order to ensure sufficient sample in the most populous regions (Amhara, Oromiya, SNNP, and Tigray), quotas were set for the number of EAs in each region. The sample is not representative for each of the small regions including Afar, Benshangul Gumuz, Dire Dawa, Gambella, Harari, and Somalie regions. However, estimates can be produced for a combination of all smaller regions as one "other region" category.

The second stage of sampling was the selection of households to be interviewed in each EA. For rural EAs, a total of 12 households are sampled in each EA. Of these, 10 households were randomly selected from the sample of 30 AgSS households. The AgSS households are households which are involved in farming or livestock activities. Another 2 households were randomly selected from all other households in the rural EA (those not involved in agriculture or livestock). In some EAs, there is only one or no such households, in which case, less than two non-agricultural households were surveyed and more agricultural households were interviewed instead so that the total number of households per EA remains the same.

In the small town EAs, 12 households are selected randomly from the listing of each EA, with no stratification as to whether the household is engaged in agriculture/livestock. Households were not selected using replacement. Thus, the final number of household interviewed was slightly less than the 3,996 as planned in the design.

Mode of data collection

Face-to-face paper [f2f]

Cleaning operations

Most of the interviews were carried out using paper and pen interviewing method. The completed paper questionnaires were sent to the CSA headquarters in Addis Ababa. The questionnaires were first checked by editors for completeness and consistency. The editors checked completeness (taking inventory) and cross-checked the questionnaires with the EA codebook. Questionnaires with inconsistent responses or with errors were corrected by contacting the branch offices or, in some cases, by sending the questionnaires back to the field. Checked questionnaires were keyed by data entry clerks at the head office using CSPro data entry application software.

Computer assisted personal interviewing (CAPI) was implemented, as a pilot, in 33 of the 333 EAs using SurveyBe data collection software.

The data cleaning process was done in two stages. The first step was at the CSA head office using the CSA's data cleaning staff. The CSA data cleaning staff used the CSpro data cleaning application to capture out of range values, outliers, and skip inconsistencies from the batch error reports. Once the errors were flagged in the batch error report the hard copy of the original questionnaire was retrieved and checked if the errors were at the data collection, editing, or entry level. Editing and entry level errors were corrected at the head office. Field level errors were communicated with the branch offices in the regions. The second level of data cleaning was done using Stata program to check for inconsistencies.

Response rate

A total of 3,969 households were interviewed with a response rate of 99.3 percent.

Abstract

The presence of adequate and current statistical data in various economic sectors that are considered essential for development planning, socio-economic policy formulation and economic analysis is vital in promoting the economic development of a country. Based on this general objective, the Central Statistical Agency (CSA) has been conducting surveys of various economic activities, of which, the annual Large and Medium Scale Manufacturing Industries survey is one.

Manufacturing is defined here according to International Standard Industrial Classification (ISIC Revision-3) as “the physical or chemical transformation of materials or components into new products, whether the work is performed by power-driven machines or by hand, whether it is done in a factory or in the worker’s home, and whether the products are sold at wholesale or retail. The assembly of the component parts of manufactured products is also considered as manufacturing activities.”

CSA has been publishing results of the survey of Manufacturing and Electricity Industries on annual basis since 1968 E.C. to provide users with reliable, comprehensive and timely statistical data on these sectors. In this respect, this survey, which is conducted on annual basis, is the principal source of industrial statistics on large and medium scale manufacturing industries in the country. In this edition value added in the national account concept at factor cost is replaced with value added in the national account concept at basic price. So as to comply with the current practice of System of National Account (SNA). As a result, the time serious data for the previous four years have also been adjusted. In addition to this the concept and data in respect of census value added is withdrawn from the report because its application is no more used in practice.

The main objectives of the annual survey of Large and Medium Scale Manufacturing and Electricity Industries are to:- 1. Obtain basic statistical data that are essential for policy makers, planners and researchers by major industrial group. 2. Collect basic quantitative information on employment, volume of production and raw materials, structure and performance of the country’s Large and Medium Scale Manufacturing and Electricity Industries. 3. Compile statistical data which will be an input to the System of National Accounts (SNA), on Large and Medium Scale Manufacturing and Electricity establishments as a whole and by major industrial group. 4. Obtain the number of proprietors engaged in these sectors and find out the major problems that create stumbling blocks for their activities.

Geographic coverage

National

Analysis unit

Establishment/ Enterprise

Universe

The universe of the large and medium scale manufacturing survey is confined to those establishments which engaged 10 persons and above and use power-driven machines and covers both public and private industries in all Regions of the country.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Not applicable - the survey enumerated all manufacturing industries/ enterprises that qualified as large and medium manufacturing industry category.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questinnaire contains the following sections/ items:

Item 1.1. Adress of the establishments: This section has varibles that identify the questionnaire uniquely. The variables are; Killil, Zone, Wereda, Town, Higher, Kebele, House no, Year, ISIC, Establishmnet no, Eelephone no and P.O.Box codes or numbers.

Item 1.2. Address of Head Office if Separated From Factory: In this section information about factory head office is collected (if the factory is separated from the head office). The varibles used to collect the information are; Killil, Zone, Wereda, Town, Higher, Kebele, House no, Telephone no and P.O.Box.

Item 2. Basic Information About The Establishment: This section has questions related to basic information about the establishment.

Item 3.1. Number of Persons Engaged: This section has variables (questions) that used to collect establishment's employees number by employees occupation.

Item 3.2. Number of Persons Engaged by Educational Status: This section has varabils (questions) that used to collect establishment's employees number by their educational status.

Item 3.3. Number of Persons Engaged by Age Group: Contains variables that used to collect information about employees number by employees age group.

Item 3.4. Wages and Salaries and Other Employee Benefits Paid: This section has variables related to wages and other employees benefits by employee occupation.

Item 3.5. Number of Permanent Employees by Basic Salary Group: This section has variables related to salary groups by sex of employees

Item 4.1. Products and By-products: This section has questions related to product produced, produced quantity and sales.

Item 4.2. Service and Other Receipts: Contains questions related to income from different source other than selling the products.

Item 5. Value of Stocks: Contains questions that related to information about materials in the stock.

Item 6.1. Cost and Quantity of Raw Materials, Parts and Containers Used: This section has questions related to principal raw materials, raw material type, quantity, value and source (local or imported).

Item 6.2. Other Industrial Costs: This sections has questions related to other industrial costs including cost of energy and other expenses.

Item 6.3. Other Non-industrial Expenses: Contains questions related to non-industrial expenses like license fee, advertising, stationary, etc.

Item 6.4. Taxes Paid: This section has questions related to taxes like indirect tax and income tax.

Item 7. Fixed Assets and Investment: This section has questions related to fixed assets and investment on fixed assests and working capital.

Item 8.1. Annual Production at Full Capacity: This section has questions about quantity and value of products if the establishment uses its full capacity.

Item 8.2. Estimated Value and Quantity of Raw Materials Needed, at Full Capacity: This section has questions about the estimate of quantity and value of raw materials that needed to function at full capacity.

Item 8.3. The three major problems that prevented the establishment from operating at full capacity.

Item 8.4. The three major problems that are facing the establishment at present.

Cleaning operations

Editing, Coding and Verification: A number of quality control steps were taken to ensure the quality of data. The first step taken in this direction was, to revise the questionnaire, to make it easier for internal consistency checking or editing, both at field and office level. Furthermore, based on this revised questionnaire, revised instruction manual with field editing procedures was prepared in Amharic for both enumerators and supervisors (field editors). Using this manual, some editing and coding were carried out by field editors during the data collection stage. After the majority of the completed questionnaires were brought back to head office, final editing, coding and verification were performed by editors, statistical technicians and statisticians. Finally, the edited and coded questionnaires were checked and verified by other senior professionals.

Data Entry, Cleaning and Tabulation: The data were entered and verified on personal computers using CSpro (Census and Survey Processing System) Software. Twelve CSA data entry staff and one data cleaner participated in this activity for fifteen days with close supervision of the activities by two professionals. Then, the data entered were cleaned using personal computers in combination with manual cleaning for some serious errors. Finally, the tabulation of the results was processed using the same software by one programmer with technical assistance from Industry, Trade and Services Statistics Department staff.