Integrated Household Survey 1993 DDI_ZAF_1993_IHS_v01_M

World Bank, Living Standard Measurement Study (LSMS)

Development Economics Data Group 2010-06-29 Metadata Editor Version 1.1 (March 2011) ZAF_1993_IHS_v01_M Integrated Household Survey 1993 IHS 1993 ZAF_1993_IHS_v01_M Southern Africa Labour and Development Research Unit The World Bank Metadata Editor Government of Denmark Government of the Netherlands Government of Norway LSMS Data Manager Living Standards Measurement Study [hh/lsms] v2.0 Edited anonymous dataset for public distribution poverty education demography housing health expenditure income consumption fertility agriculture land use literacy numeracy The Project for Statistics on Living standards and Development was a coutrywide World Bank Living Standards Measurement Survey. It covered approximately 9000 households, drawn from a representative sample of South African households. The fieldwork was undertaken during the nine months leading up to the country's first democratic elections at the end of April 1994. The purpose of the survey was to collect statistical information about the conditions under which South Africans live in order to provide policymakers with the data necessary for planning strategies. This data would aid the implementation of goals such as those outlined in the Government of National Unity's Reconstruction and Development Programme. South Africa National coverage - Households - Individuals - Community Sample survey data [ssd] Bureau of Market Research Data Research Africa Human Sciences Research Council Mark Data Mr. Sintu Mpambani Sample size is 9,000 households The sample design adopted for the study was a two-stage self-weightingdesign in which the first stage units were Census Enumerator Subdistricts (ESDs, or their equivalent) and the second stage were households. The advantage of using such a design is that it provides a representative sample that need not be based on accurate census population distribution.in the case of South Africa, the sample will automatically include many poor people, without the need to go beyond this and oversample the poor. Proportionate sampling as in such a self-weighting sample design offers the simplest possible data files for further analysis, as weights do not have to be added. However, in the end this advantage could not be retained and weights had to be added. The sampling frame was drawn up on the basis of small, clearly demarcated area units, each with a population estimate. The nature of the self-weighting procedure adopted ensured that this population estimate was not important for determining the final sample, however. For most of the country, census ESDs were used. Where some ESDs comprised relatively large populations as for instance in some black townships such as Soweto, aerial photographs were used to divide the areas into blocks of approximately equal population size. In other instances, particularly in some of the former homelands, the area units were not ESDs but villages or village groups. In the sample design chosen, the area stage units (generally ESDs) were selected with probability proportional to size, based on the census population. Systematic sampling was used throughout that is, sampling at fixed interval in a list of ESDs, starting at a randomly selected starting point. Given that sampling was self-weighting, the impact of stratification was expected to be modest. The main objective was to ensure that the racial and geographic breakdown approximated the national population distribution. This was done by listing the area stage units (ESDs) by statistical region and then within the statistical region by urban or rural. Within these sub-statistical regions, the ESDs were then listed in order of percentage African. The sampling interval for the selection of the ESDs was obtained by dividing the 1991 census population of 38,120,853 by the 300 clusters to be selected. This yielded 105,800. Starting at a randomly selected point, every 105,800th person down the cluster list was selected. This ensured both geographic and racial diversity (ESDs were ordered by statistical sub-region and proportion of the population African). In three or four instances, the ESD chosen was judged inaccessible and replaced with a similar one. In the second sampling stage the unit of analysis was the household. In each selected ESD a listing or enumeration of households was carried out by means of a field operation. From the households listed in an ESD a sample of households was selected by systematic sampling. Even though the ultimate enumeration unit was the household, in most cases "stands" were used as enumeration units. However, when a stand was chosen as the enumeration unit all households on that stand had to be interviewed. Census population data, however, was available only for 1991. An assumption on population growth was thus made to obtain an approximation of the population size for 1993, the year of the survey. The sampling interval at the level of the household was determined in the following way: Based on the decision to have a take of 125 individuals on average per cluster (i.e. assuming 5 members per household to give an average cluster size of 25 households), the interval of households to be selected was determined as the census population divided by 118.1, i.e. allowing for population growth since the census. It was subsequently discovered that population growth was slightly over-estimated but this had little effect on the findings of the survey. Individuals in hospitals, old age homes, hotels and hostels of educational institutions were not included in the sample. Migrant labour hostels were included. In addition to those that turned up in the selected ESDs, a sample of three hostels was chosen from a national list provided by the Human Sciences Research Council and within each of these hostels a representative sample was drawn on a similar basis as described abovefor the households in ESDs. Face-to-face [f2f] The main instrument used in the survey was a comprehensive household questionnaire. This questionnaire covered a wide range of topics but was not intended to provide exhaustive coverage of any single subject. In other words, it was an integrated questionnaire aimed at capturing different aspects of living standards. The topics covered included demography, household services, household expenditure, educational status and expenditure, remittances and marital maintenance, land access and use, employment and income, health status and expenditure and anthropometry (children under the age of six were weighed and their heights measured). This questionnaire was available to households in two languages, namely English and Afrikaans. In addition, interviewers had in their possession a translation in the dominant African language/s of the region. In addition to the detailed household questionnaire referred to above, a community questionnaire was administered in each cluster of the sample. The purpose of this questionnaire was to elicit information on the facilities available to the community in each cluster. Questions related primarily to the provision of education, health and recreational facilities. Furthermore there was a detailed section for the prices of a range of commodities from two retail sources in or near the cluster: a formal source such as a supermarket and a less formal one such as the "corner cafe" or a "spaza". The purpose of this latter section was to obtain a measure of regional price variation both by region and by retail source. These prices were obtained by the interviewer. For the questions relating to the provision of facilities, respondents were "prominent" members of the community such as school principals, priests and chiefs. The Bureau of Market Research was responsible for the rural and the predominantly non- African urban areas of the Transvaal excluding the homelands. Mark Data conducted surveys in the Orange Free State, Qwa-Qwa, Bophuthatswana and Lebowa. Social Surveys covered the African townships in the PWW as well as Venda, Gazankulu and Kwandebele. Data Research Africa from Natal was responsible for the field work in Kwazulu and Kangwane. The rest of Natal and the Ciskei was covered by the HSRC in Durban. The HSRC in Cape Town covered the Northern, Western and Eastern Cape. Finally, a team under Sintu Mpambani from the University of the Transkei covered the difficult terrain in the Transkei. Completed questionnaires were sent to Saldru where data entry management and cleaning were centralized. A self-weighting sample design should in principle eliminate the need for weighting. A number of factors intervened, however, which made it essential to use weights after all. Amongst these was violence, which prevented survey teams from conducting interviews in two clusters on the East Rand; failure to continue interviewing in a cluster until the required take had been interviewed; and systematic under-representation of whites in the sample. This last problem resulted both from systematic non-response (whites were found to be more likely to refuse to be interviewed, or to be absent than other groups) and from sampling problems themselves. The importance of race in determining living standards in South Africa is such that the racial distribution of the population has a major bearing on measures of living standards and inequality. It was thus regarded as essential that the problems mentioned above should be overcome by applying appropriate weights to the data. The most appropriate weights to apply would usually be the average values obtained in a cluster for the missing questionnaires from that cluster in order to capture the homogeneity usually inherent in residential contiguity. However, that presented some difficulty for the two clusters in which violence prevented surveying and for those clusters in which there were only a small number of questionnaires completed. It was felt that this method would therefore not be appropriate. Accordingly it was decided to use weights as far as possible at the level of the old provincial/homeland boundaries and race. The listing of households in each cluster combined with the sampling interval was used to determine how many households should have been interviewed. Where this deviated from the number actually interviewed, this was taken into account. The assumption was that the households left out were racially distributed in the same proportion as the actual households interviewed. When these numbers were then calculated at the provincial level, a weight could be calculated for each race group to rectify errors made in the field work. These errors typically resulted from the fact that most field work organizations involved had little experience of using anything but a weighted sample and were used to replacements that could easily be added ex post, not necessarily in the same area. When these mistakes were discovered, it was too late to go back to the field. The sample of 360 clusters of 25 households each based on an expected household size of 5 should have yielded a resident population of 45,000. In fact, a different household size should not affect the results. In any particular cluster, the expected take of individuals would remain the same if the census population were accurate, irrespective of household size, for a smaller household size (as in the case of whites) would only have yielded more households, of whom a given proportion would have been interviewed. If in a particular cluster the census population was 472, every fourth household should have been interviewed (based on a sampling interval calculated to produce 125 persons per cluster in 1993, the expected take based on the census data of 118.1 per duster divided into the same population size). Irrespective of household size, then, one quarter of the cluster population would have been included in the survey. An average household size of 5 would have given 94 households of whom 23 would have been interviewed, i.e. 115 resident household members would have been found. If the household size were only three, on the other hand, one-quarter of the 157 households would have been 39, representing 117 household members. Only small differences from the expected take of 118 should thus arise, due to rounding. Only if the estimate of population based on the census is wrong, however, would the actual number of households deviate substantially from the expected take. In such a case, one quarter of the actual (i.e. listed or enumerated) rather than of the census population would have been included in the survey, i.e. there would have been an automatic adjustment. This gives the sample design its self-weighting character. The census population for the survey data was estimated by applying Sadie's population growth rates to the adjusted 1991 census figures. The resultant racial and geographic distribution of the population of 40.1 million was presuming, of course, that no migration across provincial and homeland boundaries had occurred since the census. This implies that a raising factor of 891.4154 (40.1 million divided by an expected take of 45,000) should be applied to the results weighted by enumeration to obtain the population it represents. Applying the weights according to enumeration, 38.1 million people were covered by the survey, i.e. there was a 2 million under-enumeration amounting to about 5 per cent. Broken down by race, the under-enumeration was particularly large amongst whites, for whom the best census data exists, indicating that the problem did not lie so much with the census as with the survey. However, this is to be expected - a survey of this nature is better at capturing inequality and living standards than population size. Nevertheless, the margin of error in aggregate population estimates is relatively small, considering the presence of some homeless people, uncertainties about ESD boundaries in some areas and the likelihood of incomplete listings of households for various reasons. These results are therefore encouraging regarding the accuracy of the survey and also confirm that the adjusted census does not deviate substantially from population estimates obtained in a different manner. However, the raised enumeration results deviate more from the census results where the provincial breakdown is concerned. The reason for this is not hard to find. The sample design introduced stratification only by geographic area (statistical regions) and proportion of the ESD population that was black. South African population clusters are still predominantly racially homogeneous, inter alia, because of past controls on residential patterns. It is therefore not surprising that in particular regions too few or too many clusters of a particular group were selected. In Natal, for instance, Coloureds and Indians are over represented in the data, even when weighted by enumeration, while Whites are under-represented. At the aggregate level, this should have little effect on the validity of the conclusions drawn, but it emphasizes the fact that care should be taken when drawing implications from the survey for Small populations. In small provinces (for instance, the new Northern Cape), only a small number of clusters has been included, with the result that little can be concluded about living standards there, even though these clusters are important in determining overall distribution. As a final comment on weights, the data provided for the user contains weights to correct for the enumeration difficulties discussed above as well as census based weights. If the user of the data wishes to use these weights they are found in the data file named "weight02". The variable name for the enumeration-based weight is "rsweight" and the name for the census-based weight is "rcweight". (Do not use the "sweight" and "cweight" variables.) All the questionnaires were checked when received. Where information was incomplete or appeared contradictory, the questionnaire was sent back to the relevant survey organization. As soon as the data was available, it was captured using local development platform ADE. This was completed in February 1994. Following this, a series of exploratory programs were written to highlight inconsistencies and outlier. For example, all person level files were linked together to ensure that the same person code reported in different sections of the questionnaire corresponded to the same person. The error reports from these programs were compared to the questionnaires and the necessary alterations made. This was a lengthy process, as several files were checked more than once, and completed at the beginning of August 1994. In some cases questionnaires would contain missing values, or comments that the respondent did not know, or refused to answer a question. These responses are coded in the data files with the following values: VALUE MEANING -1 : The data was not available on the questionnaire or form -2 : The field is not applicable -3 : Respondent refused to answer -4 : Respondent did not know answer to question The data collected in clusters 217 and 218 should be viewed as highly unreliable and therefore removed from the data set. The data currently available on the web site has been revised to remove the data from these clusters. Researchers who have downloaded the data in the past should revise their data sets. For information on the data in those clusters, contact SALDRU http://www.saldru.uct.ac.za/. World Bank LSMS Use of the dataset must be acknowledged by including a citation which would include: - Identification of the Primary Investigator - Title of the survey (including the year of implementation) - Survey reference number - Source and date of download Example: Southern Africa Labour and Development Research Unit. Integrated Household Survey (IHS) 1993 Ref. ZAF_1993_IHS_v01_M. Dataset downloaded from www.microdata.worldbank.org on [date] In receiving these data it is recognized that the data are supplied for use within my organization, and I agree to the following stipulations as conditions for the use of the data: 1. The data are supplied solely for the use described in this form and will not be made available to other organizations or individuals. Other organizations or individuals may request the data directly. 2. Three copies of all publications, conference papers, or other research reports based entirely or in part upon the requested data will be supplied to: SALDRU School of Economics University of Cape Town Private Bag, Rondebosch, 7700 SOUTH AFRICA info@data1st.org AND The World Bank Development Economics Research Group LSMS Database Administrator MSN MC3-306 1818 H Street, NW Washington, DC 20433, USA tel: (202) 473-9041 fax: (202) 522-1153 e-mail: lsms@worldbank.org 3. The researcher will refer to the 1993 South Africa Integrated Household Survey as the source of the information in all publications, conference papers, and manuscripts. At the same time, the World Bank is not responsable for the estimations reported by the analyst(s). 4. Users who download the data may not pass the data to third parties. 5. The database cannot be used for commercial ends, nor can it be sold. The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses. CFPRI01.NSDstat Cluster Food Prices 9667 4 Nesstar 200801 CFPRI03.NSDstat Cluster Food Prices with Imputed values 9464 11 Nesstar 200801 COMPRIV9.NSDstat 7: Shops and Commodity prices 18259 4 Nesstar 200801 FCODE1.NSDstat Food Conversion Table: Quantity & Calories 31 3 Nesstar 200801 FCODE2.NSDstat Food Conversion Table: Quan, Cal & Prices 31 7 Nesstar 200801 FOODEX01.NSDstat Food Expenditure - Total Values 151833 9 Nesstar 200801 FOODEX02.NSDstat Food Expenditure - Total Values with imputed 151833 9 Nesstar 200801 FOODEX10.NSDstat Food Consumption and Expenditure 151833 11 Nesstar 200801 HHEXPTL.NSDstat Total Monthly Expenditure 8811 42 Nesstar 200801 HHFEXP.NSDstat Monthly Food Expenditure and Shares 8810 21 Nesstar 200801 HHFEXPT.NSDstat Total Monthly Food Expenditure 8651 6 Nesstar 200801 HHINCTL.NSDstat Total Monthly Income 8810 33 Nesstar 200801 HHSIZE.NSDstat Household Size 8809 4 Nesstar 200801 HHSTX01.NSDstat Summary Expenditure 8810 13 Nesstar 200801 M1_AGR2.NSDstat 8.5.1.2 Livestock: cattle etc (1) 3014 12 Nesstar 200801 M1_AGR4.NSDstat 8.5.1.5 Other Farming Cost 1291 4 Nesstar 200801 M1_CASW2.NSDstat 8.3.5 Second casual job 30 12 Nesstar 200801 M1_ED2.NSDstat 5.2 Education Spending 17046 4 Nesstar 200801 M2_AGR1.NSDstat 8.5.1.1 Crop production 1409 9 Nesstar 200801 M2_NFS1.NSDstat 4.1 Regular Non food spending 43998 4 Nesstar 200801 M2_NFS3.NSDstat 4.3 Summary of Food And Non-Food Spending 29988 6 Nesstar 200801 M2_NFS4.NSDstat 4.4 Household items 35187 4 Nesstar 200801 M2_REM1.NSDstat 6.1 Remittances Income received from ..... 2729 11 Nesstar 200801 M2_REM2.NSDstat 6.2 People absent..who receive.... 1771 11 Nesstar 200801 M3_CASW1.NSDstat 8.3.1 Main casual job 937 12 Nesstar 200801 M3_HEA1.NSDstat 10.1 Health Spending/Incidence 3383 14 Nesstar 200801 M3_HSV4.NSDstat 2.5 Expenditure on Energy, Water, Rates Expenditure 18010 4 Nesstar 200801 M3_LAND2.NSDstat 7.2 Non-Farming land etc 484 6 Nesstar 200801 M3_NFS2.NSDstat 4.2 Occasional Non Food Spending 35749 4 Nesstar 200801 M3_NFS5.NSDstat 4.5 Household debt 5429 5 Nesstar 200801 M3_SEMP.NSDstat 8.6 Other forms of self employment 1135 12 Nesstar 200801 M4_ED1.NSDstat 5.1 Education Enrolment 16782 12 Nesstar 200801 M4_HEA2.NSDstat 10.2 Pregnancy and Child Health 10654 12 Nesstar 200801 M4_TRAN.NSDstat 8.4 Transport 8310 8 Nesstar 200801 M5_EDUC1.NSDstat 3.1: Education- FOR ALL PRIMARY SCHOOLS 2673 5 Nesstar 200801 M5_EDUC2.NSDstat 3.2: Education- FOR ALL SECONDARY SCHOOLS 4009 5 Nesstar 200801 M5_HEAL1.NSDstat 4.1: health - PERSONNEL 2338 4 Nesstar 200801 M5_HEAL2.NSDstat 4.2: health - FACILITIES 2005 5 Nesstar 200801 M5_INES.NSDstat 8.7 Income: Non-Employment 3344 6 Nesstar 200801 M5_RECR.NSDstat 6: Recreational Facilities 2673 5 Nesstar 200801 M6_ANTH.NSDstat 11 Anthropometry 5993 27 Nesstar 200801 M6_ECON1.NSDstat 2: Economy and Infrastructure 2339 5 Nesstar 200801 M6_REMP.NSDstat 8.2 Regular Employment 7513 20 Nesstar 200801 M8_EMPS.NSDstat 8.1 Employment Status 24296 18 Nesstar 200801 M8_HROST.NSDstat 1.0 Household Roster 43687 18 Nesstar 200801 M10_FSC.NSDstat 3.0 Food spending and consumption 151027 11 Nesstar 200801 METRO.NSDstat Metropolitan Classification 358 2 Nesstar 200801 NF1X01.NSDstat Non Food Regular: Monthly Expenditure 8809 17 Nesstar 200801 NF2X02.NSDstat Non Food Occational: Year Expenditure 8809 17 Nesstar 200801 PSAMPLE4.NSDstat Sampling frame 358 13 Nesstar 200801 S0_AGR5.NSDstat 8.5.2 Agriculture-Large Scale, Commercial 35 20 Nesstar 200801 S0_AGRC.NSDstat 5: Agriculture 207 22 Nesstar 200801 S1_AGR2.NSDstat 8.5.1.2 Livestock: Cattle etc (2) 1442 13 Nesstar 200801 S1_AGR3.NSDstat 8.5.1.3 Other Farming Income 1141 13 Nesstar 200801 S1_ED2.NSDstat 5.3 Bursaries.scholarships + meals 5971 6 Nesstar 200801 S1_EDUC3.NSDstat 3.2: Education - LITERACY PROGRAMS 299 10 Nesstar 200801 S1_HEAL1.NSDstat 4 : OTHER HEALTH SERVICES 299 15 Nesstar 200801 S3_DEMOG.NSDstat 1: Demographic Information 334 15 Nesstar 200801 S3_ECON2.NSDstat 2: Economy and Infrastructure 335 6 Nesstar 200801 S3_EDUC2.NSDstat 3.2: Education - SECONDARY SCHOOLS 334 4 Nesstar 200801 S3_HSV2.NSDstat 2.2/2.3 Water and Sanitation 8808 21 Nesstar 200801 S3_HSV3.NSDstat 2.4 Energy 8808 20 Nesstar 200801 S4_EDUC1.NSDstat 3.1: Education - PRIMARY SCHOOLS 334 4 Nesstar 200801 S4_HDEF.NSDstat 0.0 Household definition : Cover Page 8809 22 Nesstar 200801 S4_HSV1.NSDstat 2.1 Housing 8796 21 Nesstar 200801 S4_LAND1.NSDstat 7.1 Agricultural land 1302 34 Nesstar 200801 S5_ECON1.NSDstat 2: Economy and Infrastructure 334 8 Nesstar 200801 S5_PQL.NSDstat 9 Perceived quality of life 8804 21 Nesstar 200801 SAMPLE04.NSDstat Information on Sample 358 14 Nesstar 200801 STRATA2.NSDstat Basic Cross Variables 8809 11 Nesstar 200801 WEIGHT02.NSDstat Weighting Information 31 11 Nesstar 200801 9667 0 0 360 180.275 104.192 9667 0 1 28 14.519 8.225 Cluster Food Price source 1 7178 2489 -1 37 5.093 4.998 Cluster Food Price source 2 5122 4545 -1 32.8 5.178 5.082 9464 0 1 360 178.747 104.133 1a:Food code 9464 0 1 28 14.535 8.108 Num. Commodities Observed by Cl 9464 0 1 114 15.483 10.478 Cluster Food Price source 1 7028 2436 -1 37 5.046 4.919 Cluster Food Price source 2 4948 4516 -1 32.8 5.05 4.933 Cluster Food Price 9464 0 0.5 37 5.405 5.094 Missing Values 9464 0 0 7453 2 729 3 985 4 79 5 218 Median Implicit Cluster Price 704 8760 0.05 100 4.551 7.141 Province 9464 0 1 1576 2 623 3 2354 4 563 5 1350 6 194 7 77 8 238 9 676 10 109 11 787 12 565 13 135 14 217 New Magesterial Code 9464 0 1 4006 651.469 756.183 Metro - Urban - Rural 9464 0 1 4793 2 2167 3 2504 :Cluster Number 18259 0 3.69e-40 360 180.278 104.19 18259 0 3.69e-40 51 25.999 14.721 12284 5975 3.69e-40 37 4.615 5.116 8861 9398 3.69e-40 36.8 4.717 5.183 31 0 1 31 16 9.092 Kilogram conversion 31 0 0 1 0.805 0.366 Calories per Kilogram 31 0 0 8340 2053.871 2046.217 31 0 1 31 16 9.092 Kilogram conversion 31 0 0 1 0.805 0.366 Calories per Kilogram 31 0 0 8340 2053.871 2046.217 Imputed Median Kg Price 28 3 1 18 4.703 4.102 Imputed Mean Kg Price 28 3 1.369 18.3 5.628 4.314 Imputed Standard deviation 28 3 0.548 25.007 5.266 5.716 Number of Observations 31 0 0 199 64.71 56.642 Household identification No 151833 0 1001 360017 168160.724 101743.057 1a:Food code 151833 0 1 31 14.772 8.448 Missing ? 151833 0 2 150476 4 1357 2 :Weekly/Monthly? 146789 5044 -2 38 -1 764 1 51667 2 94320 Sysmiss 5044 Monthly value purchased 146789 5044 0 3826 29.943 50.622 Monthly value received 3480 148353 0.166 5281.34 35.666 110.849 Monthly value produced 1230 150603 0.5 4114.023 51.905 144.503 Monthly expenditure consumed 150476 1357 0.109 5307.945 30.458 54.742 Cluster number 151833 0 1 360 168.136 101.75 Household identification No 151833 0 1001 360017 168160.724 101743.057 1a:Food code 151833 0 1 31 14.772 8.448 Missing ? 151833 0 2 150476 4 1357 2 :Weekly/Monthly? 146789 5044 -2 38 -1 764 1 51667 2 94320 Sysmiss 5044 Monthly value purchased 146789 5044 0 3826 29.943 50.622 Monthly value received 3480 148353 0.166 5281.34 35.666 110.849 Monthly value produced 1230 150603 0.5 4114.023 51.905 144.503 Monthly expenditure consumed 151833 0 0.109 5307.945 30.506 54.704 Cluster number 151833 0 1 360 168.136 101.75 Household identification No 151833 0 1001 360017 168160.724 101743.057 1a:Food code 151833 0 1 31 14.772 8.448 2 :Weekly/Monthly? 151833 0 -2 43 -1 1042 1 53709 2 97039 3a:Value of food 151833 0 -4 3500 10.109 31.613 3b:Quantity 151833 0 -4 320 3.765 10.317 4a:Value of food received 151833 0 -4 500 0.119 4.212 4b:Amount of food received 151833 0 -4 397 0.183 3.528 5a:Value of food produced 151833 0 -4 300 0.0471 1.968 5b:Amount of food produced 151833 0 -4 240 0.093 2.15 Missing ? 151833 0 2 150476 4 1357 Cluster number 151833 0 1 360 168.136 101.75 Household identification No 8811 0 1001 360017 179756.647 102407.773 Marker 8809 2 1 1553 2 817 3 4754 4 1644 5 41 Sysmiss 2 Total Housing Expenditure 8810 1 0.0118 100000 263.59 1142.49 Tot exp: energy, water, rates 8809 2 0 4643 122.426 155.919 Marker 8809 2 1 8510 2 299 Sysmiss 2 Total Monthly Food exp. 8773 38 4 5807.105 549.417 398.036 Marker 8810 1 0 159 1 8651 Sysmiss 1 Vehicle Exp. 8809 2 0 4000 71.951 202.63 Transportation Exp. 8809 2 0 27300 99.976 456.581 Marker 8809 2 1 8482 2 327 Sysmiss 2 Personal Items 8809 2 0 5400 131.729 201.487 Other NonFood 1 8809 2 0 3520 84.741 188.918 Marker 8809 2 1 8382 2 427 Sysmiss 2 Household Exp. 8809 2 0 1215.833 15.1 46.949 Clothing Exp. 8809 2 0 3083.333 70.071 107.341 Health Care Exp. 8809 2 0 3791.667 28.673 125.332 Other NonFood 2 8809 2 0 10000 43.352 253.333 Insurance. 8809 2 0 12000 90.799 283.422 Saving. 8809 2 0 16666 62.32 304.513 Marker 8809 2 0 32 1 8204 2 573 Sysmiss 2 Total School Expenditure 8808 3 0 4458.332 54.766 187.007 Marker 8809 2 0 1 1 8576 2 232 Sysmiss 2 Tot Month Remittance Expenditur 8783 28 0 5416.664 36.133 154.287 Marker 8809 2 1 8783 2 26 Sysmiss 2 HH Size All 8809 2 1 31 4.959 3.297 HH Size Memebers 8809 2 1 30 4.548 2.973 Household Housing Subsidy 8811 0 0 100000 56.756 1083.41 Total Month Food Received 8811 0 0 3000 22.804 79.4 Tot Month Food Received Value 8811 0 0 5301.637 14.087 81.938 Flag Food Received Wage 8811 0 0 7815 1 996 Flag Food Received Remittances 8811 0 0 8057 1 754 Flag Food Received F.O.S 8811 0 0 7835 1 976 1b:Value of bursaries 8811 0 0 50000 57.046 940.47 sum 7 :Transport costs 8811 0 0 400 2.902 13.826 Marker 5328 3483 1 5256 2 72 Sysmiss 3483 sum 4 :Transport cost 8811 0 0 160 3.664 7.618 Marker 5722 3089 1 5602 2 120 Sysmiss 3089 8811 0 0 405 6.567 16.765 Household Travel Subsidy 691 8120 1 6450 574.227 872.66 Total Monthy Expenditure 8770 41 44.079 103536.813 1688.934 2253.712 Total Monthy Exp. w/ remittance 8744 67 45.337 103536.813 1721.602 2270.598 Cluster number 8811 0 1 360 179.733 102.413 Household identification No 8810 0 1001 360017 179765.696 102410.063 max HH Size Memebers 8809 1 1 30 4.548 2.973 Per capita grain month exp. 8651 159 0 323 33.799 23.366 Per capita meat & fish month ex 8651 159 0 987.926 39.652 45.211 Per capita dairy month exp. 8650 160 0 888.241 16.8 26.067 Per capita fru. and veg. month 8651 159 0 346.85 23.298 21.584 Per capita oil month exp. 8651 159 0 164.905 7.144 7.621 Per capita sugar month exp. 8651 159 0 160.713 5.523 5.233 Per capita meals month exp. 8650 160 0 1775 13.392 49.978 Per capita other month exp. 8651 159 0 430 12.3 21.566 Per capita tot food month exp. 8650 160 0.571 1915.965 151.922 126.568 Household tot food month exp. 8651 159 2.173 5807.105 535.404 392.351 Share grain month exp. 8650 160 0 100 30.246 18.814 Share meat & fish month exp. 8650 160 0 100 23.222 13.751 Share dairy month exp. 8650 160 0 94.356 9.298 9.961 Share fru. and veg. month exp. 8650 160 0 100 15.944 8.649 Share oil month exp. 8650 160 0 100 4.987 4.06 Share sugar month exp. 8650 160 0 100 5.211 5.051 Share meals month exp. 8650 160 0 100 4.606 11.253 Share other month exp. 8650 160 0 100 6.485 8.67 Cluster number 8810 0 1 360 179.742 102.416 Household identification No 8651 0 1001 360017 181176.424 102634.107 Tot Month Food Purchase Value 8651 0 0 5109.723 508.067 384.023 Tot Month Food Received Value 8651 0 0 5301.637 14.347 82.669 Tot Month Food Produced Value 8651 0 0 4570.473 7.38 67.384 Tot Month Food Value 8651 0 2.173 5807.105 535.404 392.351 Cluster number 8651 0 1 360 181.153 102.64 Rental Income 8809 1 0 64933.414 37.059 836.286 Household Net Wage 8784 26 0 93971.508 1207.07 2264.57 Household Gross Wage 8784 26 0 183250 1445.014 3695.227 Imp house prop value - 5.0% 8809 1 0 5150 99.283 257.138 Crop Rental Income 8809 1 0 15000 5.345 220.866 Grazing Rental Income 8809 1 0 8036 2.751 129.385 Total Yearly Cash received 2127 6683 0 2000 28.296 77.09 Total Monthly in kind 8809 1 0 2000 6.832 39.763 Total Monthly received 8809 1 0 5301.637 65.166 184.722 Household Travel Subsidy 8784 26 0 6450 45.58 291.1 Household Food Subsidy 8806 4 0 3000 22.928 80.584 Household Housing Subsidy 8787 23 0 6450 48.831 204.96 Household Cas 1 Wage 8758 52 0 19000 44.141 322.933 Household Cas 1 Food Subsidy 8758 52 0 1000 1.485 22.028 Household Cas 1 subsidy 8758 52 0 2905 0.759 33.612 Household Cas 2 Wage 8808 2 0 1900 1.134 30.542 Household Cas 2 Food Subsidy 8808 2 0 600 0.109 6.839 Household Cas 2 subsidy 8808 2 0 8806 5 1 16 1 Sysmiss 2 Valid Large Farmers ? 35 8775 0 4 1 31 Sysmiss 8775 Value of Ag. Income 8808 2 -8541.664 124733.313 84.464 2370.596 Value of Ag. Subsidy 8809 1 0 14416.664 5.53 218.58 Household profit value 8704 106 0 100000 129.949 1730.95 Household other income 8809 1 0 75711 211.378 1166.606 Household identification No 8810 0 1001 360017 179765.696 102410.063 Missing Wage value 8809 1 0 8784 1 24 2 1 Sysmiss 1 With missing Cas 1 Wage value 8809 1 0 8758 1 45 2 6 Sysmiss 1 With missing Cas 2 Wage value 8809 1 0 8808 1 1 Sysmiss 1 Missing profit data 8809 1 0 8704 1 104 2 1 Sysmiss 1 Missing Values 8809 1 0 8809 Sysmiss 1 Tot Month Food Received Value 8651 159 0 5301.637 14.347 82.669 9c:Monthly rent (mkt) 936 7874 2 2000 105.203 230.035 Total Monthy Income 8634 176 -4375.449 207979.813 2016.904 4613.719 Cluster number 8810 0 1 360 179.742 102.416 Household identification No 8809 0 1001 360017 179767.71 102415.701 HH Size All 8809 0 1 31 4.959 3.297 HH Size Memebers 8809 0 1 30 4.548 2.973 Cluster number 8809 0 1 360 179.744 102.421 Household identification No 8810 0 3.69e-40 360017 179747.305 102427.796 Groceries. 8808 2 0 6000 320.475 321.098 Food eaten out. 8809 1 0 3500 26.875 94.477 Holidays. 8809 1 0 10000 35.58 236.946 Cars, etc. 8805 5 0 88523 121.205 1644.329 Furniture. 8809 1 0 7550 58.587 184.044 Clothing. 8809 1 0 2500 73.693 117.316 domestic workers. 8809 1 0 5000 37.775 128.666 Insurance. 8805 5 0 12000 90.84 283.48 Saving. 8788 22 0 16666 62.469 304.861 Summary Exp: total 8778 32 0 92530 826.675 2081.302 Marker 8810 0 0 32 3.68782519453291e-40 1 1 8204 2 573 Cluster number 8810 0 0 360 179.723 102.434 Household identification No 3014 0 2024 360012 274058.11 61611.277 :Livestock Code 3014 0 1 670 2 186 3 592 4 356 5 1210 2a:No of livestock owned now 3014 0 -4 2000 9.947 42.078 2b:No of livestock born 3014 0 -4 200 1.371 7.381 2c:No of livestock sold 3014 0 -4 200 0.607 6.375 2d:Value of livestock sales 3014 0 -4 30000 84.338 799.846 2e:No of livestock bought 3014 0 -4 300 0.578 7.647 2f:No of livestock slaughtered 3014 0 -4 280 2.167 7.236 2g:No of livestock lost 3014 0 -4 50 1.944 4.492 2h:No of livestock loaned 3014 0 -4 50 0.0876 1.123 2i:No of livestock borrowed 3014 0 -4 1 -1 2 0 2919 1 38 2 18 3 9 4 10 5 5 6 3 7 2 8 1 10 4 11 1 13 1 Cluster number 3014 0 2 360 274.039 61.609 Household identification No 1291 0 2024 360012 244301.361 66374.143 2 :Code 1291 0 1 86 2 451 3 47 4 358 5 18 6 18 7 36 8 253 9 8 10 16 3 :Amt paid in cash and credit 1291 0 -4 150000 957.74 7533.767 Cluster number 1291 0 2 360 244.283 66.373 Household identification No 30 0 2027 341036 140050.133 93959.728 2b:Person code 30 0 1 12 2 7 3 6 4 2 5 2 7 1 3a:Code - Occupation 30 0 -1 1 1 3 3 6 4 3 5 4 9 1 10 11 11 1 3b:Code of employer 30 0 -1 1 3 1 5 16 7 2 8 9 9 1 3c:Sector code 30 0 -1 1 1 1 2 1 3 1 4 1 6 3 7 1 8 6 10 2 11 1 13 9 15 2 16 1 3d:Hours worked on average day 30 0 -1 20 6.483 4.114 3e:Overtime hours past week 30 0 -2 1 -1 1 0 28 4c:Cash pay last month 30 0 -4 1900 336.233 408.747 4e:Value of food subsidy 30 0 0 600 28.8 114.038 4e:Value of other benefits 30 0 0 29 5 1 4f:Value of equipment 30 0 -2 10000 333.267 1825.754 Cluster number 30 0 2 341 140.033 93.958 Household identification No 17046 0 1009 360016 192182.169 101394.423 2 :Code 17046 0 1 3000 5.551 29.143 3 :Amount 17046 0 -4 35000 304.164 969.276 Cluster number 17046 0 1 360 192.16 101.4 Household identification No 1409 0 8001 346016 250329.101 65984.592 1b:Crop code 1409 0 1 22 6.402 5.642 1c:Units - qty harvested 1409 0 -4 11 -1 18 0 1 1 239 2 133 3 112 4 195 5 315 6 26 7 74 8 88 9 24 10 86 11 65 12 22 1d:Amount harvested 1409 0 -4 3700 26.765 161.933 1e:Price per unit 1409 0 -4 6000 9.816 169.453 1e:Units sold 1409 0 -4 3700 7.973 128.853 1f:Payments to workers 1409 0 -4 75 0.35 3.519 1g:No of units paid - rent 1409 0 -4 2 -1 11 0 1389 0.5 1 2 3 3 1 5 2 Cluster number 1409 0 8 346 250.313 65.983 Household identification No 43998 0 1001 360017 162626.79 99228.314 2 :Code 43998 0 1 4093 2 3449 3 1643 4 7621 5 3361 6 2465 7 2063 8 4417 9 8343 10 1169 11 3098 12 938 13 1338 3 :Amount 43998 0 -4 25000 67.949 190.799 Cluster number 43998 0 1 360 162.601 99.235 Household identification No 29988 0 1001 360017 161016.355 98510.024 1a:Code 29988 0 1 250 4.435 3.126 2 :Actual Mthly Exp 29983 5 -4 200000 237.035 1559.674 3 :Usual Mthly Exp 29982 6 -4 15000 197.264 343.201 4 :Annual Exp 29960 28 -4 200000 1021.985 3306.107 Cluster number 29988 0 1 360 160.99 98.517 Household identification No 35187 0 1001 360017 149837.028 97791.281 2 :Code 35187 0 1 2249 2 1877 3 6914 4 3273 5 1227 6 4651 7 3489 8 4031 9 2226 10 3044 11 2206 3 :No of durables 35187 0 -4 8 -3 1 0 1 1 29197 2 4425 3 1030 4 357 5 95 6 46 7 15 8 6 9 4 10 1 14 1 Cluster number 35187 0 1 360 149.811 97.798 Household identification No 2729 0 1008 360017 236835.767 87068.296 3 :Residence of recipient 2729 0 -4 20 6.07 5.807 4a:Relationship code to member 2729 0 -1 20 1 886 2 480 3 931 4 260 5 121 6 28 7 1 13 2 4c:Person code of relation 2729 0 -1 30 2.163 1.931 5a:No of times sent cash to abs 2729 0 -4 120 8.593 4.851 5b:Cash sent in past year 2729 0 -4 30000 2086.001 2428.925 5c:Cash sent in past month 2729 0 -4 5000 218.835 291.65 6a:No of times sent in kind 2729 0 -4 2400 3.596 47.42 6b:Value in kind sent in past y 2709 20 -4 24000 265.908 783.612 6c:Value in kind sent in past m 2705 24 -4 3000 28.61 91.176 Cluster number 2729 0 1 360 236.813 87.073 Household identification No 1771 0 1001 360005 155285.207 85302.759 2 :Residence of absent member 1771 0 -4 20 11.766 6.426 4a:Relationship code 1771 0 -3 2 -1 1 1 289 2 548 3 605 4 135 5 95 6 20 7 76 4c:Person code of relation 1771 0 -1 2 1 1383 2 311 3 44 4 15 5 8 6 2 7 2 10 2 11 1 12 1 5a:No of times 1771 0 -4 52 8.623 4.374 5b:Cash in the past year 1771 0 -4 60000 1822.112 2836.623 5c:Cash in past month 1771 0 -4 5000 174.828 236.047 6a:No of times in past year - k 1771 0 -4 267 2.456 15.618 6b:Value in kind in past year 1771 0 -4 35000 219.727 1034.157 6c:Value in kind in past month 1771 0 -4 2000 22.283 91.402 Cluster number 1771 0 1 360 155.26 85.31 Household identification No 937 0 1008 359013 163300.348 100721.616 2b:Person code 937 0 0 1 1 379 2 242 3 151 4 86 5 42 6 11 7 14 8 3 9 3 11 2 12 2 17 1 3a:Code - Occupation 937 0 -3 2 1 43 2 12 3 110 4 30 5 180 6 41 7 88 8 11 9 43 10 367 11 10 3b:Code of employer 937 0 -3 2 1 18 2 16 3 26 4 28 5 516 6 12 7 43 8 270 9 6 3c:Sector code 937 0 -3 2 1 79 2 6 3 92 4 15 5 123 6 152 7 55 8 38 9 14 10 25 11 14 12 3 13 255 14 2 15 56 16 6 3d:Hours worked average day 937 0 -4 17 7.216 2.946 3e:Overtime hours past week 937 0 -4 36 0.289 2.041 4c:Cash pay last month 937 0 -4 16000 414.542 826.481 4e:Value of food subsidy 937 0 -4 400 10.691 43.467 4e:Value of other benefits 937 0 -4 2905 6.984 102.394 4f:Value of equipment 937 0 -4 100000 224.014 3468.132 Cluster number 937 0 1 359 163.277 100.725 Household identification No 3383 0 1001 360006 179363.868 100031.1 3 :Person code 3383 0 1 1087 2 845 3 389 4 312 5 251 6 163 7 108 8 75 9 49 10 29 11 23 12 20 13 9 14 9 15 8 16 2 17 3 19 1 3a:Still sick? 3383 0 1 742 2 2641 4 :1st sick code 3383 0 -4 23 13.354 7.007 5 :2nd sick code 3383 0 -1 23 2.371 6.094 6 :No of days sick 3383 0 -4 30 7.718 5.046 7 :Days out of work 3383 0 -4 30 4.849 5.131 8 :Consultation 3383 0 -4 3 -1 13 1 596 2 14 3 1428 4 69 5 452 6 724 7 4 8 42 9 14 10 3 11 21 9a:Time taken to get there 3383 0 -4 530 30.837 45.582 9b:Time taken to get treat 3383 0 -4 720 32.899 55.605 9c:Amount charged 3383 0 -4 55000 90.495 1357.539 9d:Cost of medicine 3383 0 -4 2000 12.141 74.622 10 :Reason for not consulting 3383 0 -2 2787 -1 5 1 214 2 228 3 69 4 5 5 1 6 3 7 3 10 68 Cluster number 3383 0 1 360 179.339 100.039 Household identification No 18010 0 1001 360017 193847.798 102231.67 1b:Expenditure code 18010 0 1 940 2 4598 3 862 4 2107 5 4275 6 713 7 805 8 61 9 112 10 1178 11 749 12 1610 1c:Amount spent 18010 0 -4 4500 54.758 111.266 Cluster number 18010 0 1 360 193.825 102.236 Household identification No 484 0 1010 353015 130317.165 77725.763 2a:List of properties 484 0 -1 18 01 1 1 BLACK SHACK 1 1 EXTRA ROOM 1 1 ROOM 1 1 SHACK 4 100 HECT STILBAAI 1 12 BACKROOMS 1 2 BACK ROOMS 1 2 BACK SHACKS 1 2 HOUSES 2 2 ROOMED HOUSE 1 2 ROOMS AND GARAGE 1 2 SHACKS 3 2ND HOUSE 2 3 FLATS 1 3 HOUSES 1 3 OUTBUILDING 1 3 ROOM 1 3 ROOM HOUSE 1 3 ROOM OUT BUILDING 1 3 SHACKS 1 3X CLUSTER HOME 1 4 HOUSES 1 4 HUTS, 1 HOUSE 1 4 OUTBUILDING 1 4 OUTBUILDINGS 1 4 ROOM HOUSE 1 5 ROOM HOUSE 2 5 ROOMS 1 6 ROOMS RENTED 1 7 SHACKS 1 8 SHACKS 1 ANOTHER HOUSE 1 APARTMENT 1 AT MAGALIESPARK 1 BEACH COTTAGE 1 BESIGHEID 1 BLOCK OF FLATS 1 BUILDING CONSTRUCT 1 BUILDING SITE 1 BUS & BUILDING 1 BUSINESS 4 BUSINESS HOUSE 1 BUSINESS PROP 1 BUSINESS PROPERTY 1 BUTCHER 1 CABANA BEACH 1 CAFE 1 COLONSO INDUSTRIAL 1 COTTAGE 2 CRYSTAL SPRINGS 1 DEEL VAN HUIS 1 DURBAN 1 EMPANGENI 1 ERF 6 ERF GEKOOP 1 ERF-BOSVELD 1 EZAKHANI 1 FALCON GLEN 1 FARM 5 FARMING LAND 1 FLAT 9 FLAT GABLE 1 FOUR SHACKS 1 GARAGE 2 GENERAL DEALER 1 GETHLONE LODGE 1 GRANNY FLAT 1 GROND 1 HAZELWOOD 1 HOLIDAY FLAT 1 HOLIDAY HOUSE 6 HOME 10 HOMESTEAD 1 HOUSE 142 HOUSE (ALBERTON) 1 HOUSE MESINA 1 HOUSES 2 HOUSE[4] 1 HUIS 9 HUT 1 HUTS/ROUNDAVAL 1 INWONER 1 INWONERS 1 KAIA 1 KAMER 1 KLEINMOND 1 LAND 10 LODGER 3 LOSEERDER 1 MABULA 1 MAKULA TIMES 1 MARGATE TYDDEEL 1 MEENTHUIS SKEMA 1 MOTORHAWE 1 OESTESEE 1 OFFICE BLOCK 1 ONE EXTRA H 1 ONE HOME 1 OUT BUILDING 4 OUTBUILDING 3 OUTSIDE ROOM 1 PANDOK 1 PARODYSSTRAND 1 PIET RETIEF 1 PLAAS 1 PLETT HOMES 1 PLOT 9 PLOT OF LAND 1 PLOT ON VAAL 1 PROPERTY 1 PROPERTY IN TRANSKEI 1 PROPERTY SHARE 1 PROTEARIF 1 QUARTER OF HOUSE 1 RENT 2 RENTS ONE ROOM 1 RONDAVEL 1 ROOM 13 ROOM (TENNANT) 1 ROOM [TENNANT] 1 ROOMS 3 SECOND HOME 2 SECOND HOUSE 5 SHACK 30 SHACK 1 1 SHACK 2 1 SHACK 3 1 SHACKS 1 SHARE HOLD 7 SHOP 5 SITE 1 SITE-LAND 1 SMALL HOLDING 1 STAND 2 STAND - PLOT 1 STAND NO 2 1 STAND-75 1 STOCK 1 STRANDHUIS 1 T/H & GABLE 1 TENANT 4 TENNANT 2 TENNANTS 2 TIME SHARE 5 TIME-SHARE 1 TIMESHARE 9 TIMESHARE UMHLANGA 1 TOWNHOUSE 2 TRADITIONAL HOUSE 1 TRADITIONAL HOUSES 1 TRADITIONAL HUT 1 TROPICANA 1 TWEEDE PLOT 1 TWO ROOMS 1 TWO SHACKS 1 TYDDEEL 3 UMHLANGA SANDS 1 VACANT LAND 1 VACANT PLOT 1 VAKANSIEHUIS 1 WENDY HOUSE 2 WOONSTEL 3 XANADU 1 house 1 2b:Value of property 484 0 -4 3000000 65012.543 222913.912 2c:Rent recieved? 484 0 -1 6 1 197 2 281 2d:Rent (last 12 months) 484 0 -4 132000 3643.128 14835.197 Cluster number 484 0 1 353 130.285 77.733 Household identification No 35749 0 1001 360017 165640.963 98516.668 2 :Code 35749 0 1 2326 2 1899 3 2843 4 2609 5 6660 6 6642 7 1253 8 3624 9 2505 10 1683 11 594 12 1797 13 1314 3 :Amount spent 35749 0 -14 120000 730.595 2459.121 Cluster number 35749 0 1 360 165.616 98.524 Household identification No 5429 0 1001 360015 164857.374 104306.021 2a:Code for lender 5429 0 1 712 2 50 3 84 4 399 5 18 6 79 7 52 8 146 9 99 10 1672 11 1865 12 253 2b:Amount owed 5429 0 -4 900000 4143.407 21787.748 2c:Amount repaid 5429 0 -4 75000 238.974 1155.681 Cluster number 5429 0 1 360 164.83 104.314 Household identification No 1135 0 1024 360005 183293.404 97160.19 2 :Activity code 1135 0 -3 22 7.54 6.187 3 :Code:member 1 1135 0 1 623 2 374 3 77 4 32 5 12 6 9 7 2 8 1 9 1 10 2 12 1 13 1 4 :Code member 2 1135 0 -2 742 -1 129 1 26 2 104 3 69 4 31 5 16 6 10 7 6 8 2 5 :Code member 3 1135 0 -2 901 -1 152 1 8 2 5 3 22 4 19 5 9 6 7 7 6 8 2 9 3 10 1 6 :Gross time-activity 1 1135 0 -4 840 148.938 132.497 7 :Gross sales-activity 1 1135 0 -4 1500000 2906.549 44902.253 8 :Ave monthly profit - activit 1135 0 -4 100000 873.357 3968.864 8 :Total expenses - activity 1 1135 0 -4 1000000 1770.769 29997.933 9 :Value of equipment/stocks 1 1135 0 -4 3000000 11814.964 112579.843 10 :No of others inv excl hh me 1135 0 -4 160 0.792 5.576 Cluster number 1135 0 1 360 183.27 97.169 Household identification No 16782 0 3.69e-40 360017 204982.065 100987.178 2 :Person code 16782 0 3.69e-40 30 5.132 2.582 3 :Enrolled(formal Education) ? 16782 0 -1 2 3.68782519453291e-40 1 1 13062 2 3717 4 :Reason not in school 16782 0 -4 16 -2 13065 -1 35 3.68782519453291e-40 1 1 628 2 543 3 198 4 471 5 63 6 432 7 37 8 42 9 619 10 120 11 512 5 :Last year enrolled 16782 0 -4 1993 333.215 745.149 6 :Time taken(to and fro) 16782 0 -4 480 26.103 32.061 7 :Transport costs 16773 9 -4 400 1.376 8.252 8a:1st transport 16782 0 -4 17 -2 3712 -1 130 0 7 3.68782519453291e-40 1 1 474 2 532 3 65 4 130 5 572 6 11009 7 93 8 40 8b:2nd transport 16782 0 -2 16564 -1 130 0 7 3.68782519453291e-40 1 1 8 2 24 3 5 4 3 5 12 6 25 7 3 8c:3rd transport 16782 0 -2 16642 -1 130 0 7 3.68782519453291e-40 1 3 1 5 1 5 :Age in years 16782 0 3.69e-40 24 14.736 5.127 Cluster number 16782 0 0 360 204.96 100.992 Household identification No 10654 0 1001 360017 189572.867 103273.027 2 :Person code 10654 0 1 29 3.15 2.011 3 :No of pregnancies 10654 0 -3 1 -2 2 -1 5 0 3269 1 2012 2 1706 3 1213 4 902 5 529 6 428 7 239 8 155 9 92 10 50 11 25 12 12 13 7 14 5 15 2 4 :No of births 10654 0 -3 1 -2 3271 -1 5 0 130 1 1986 2 1726 3 1209 4 860 5 515 6 398 7 222 8 151 9 88 10 46 11 25 12 12 13 5 14 3 15 1 5 :No stillborn 10654 0 -3 1 -2 3271 -1 11 0 6502 1 591 2 180 3 61 4 20 5 8 6 6 7 3 6 :No alive now 10654 0 -3 1 -2 3271 -1 6 0 303 1 2096 2 1832 3 1239 4 842 5 467 6 312 7 159 8 70 9 39 10 12 11 5 7 :No died before 1yr 10654 0 -3 1 -2 3274 -1 11 0 6462 1 645 2 179 3 52 4 16 5 7 6 4 8 2 9 1 7 :No died between age 1 + 5 10654 0 -4 1 -3 1 -2 3275 -1 12 0 6863 1 386 2 86 3 20 4 5 5 2 6 2 7 1 8 :Pregnant now ? 10654 0 -3 1 -2 3272 -1 19 1 347 2 7015 9 :Breast feeding ? 10654 0 -3 1 -2 3273 -1 44 1 1236 2 6100 10 :Age of youngest child 10653 1 -4 51 3.927 6.59 Cluster number 10654 0 1 360 189.551 103.278 Household identification No 8310 0 1001 360016 145157.638 94608.439 2 :Person code 8310 0 1 4495 2 2150 3 874 4 399 5 190 6 96 7 45 8 24 9 14 10 5 11 5 12 5 13 1 14 1 15 2 16 1 17 1 18 1 19 1 3 :Time taken to get to work 8305 5 -4 220 35.075 30.998 4 :Transport cost 8303 7 -4 80 3.753 5.82 5 :First mode of transport 8308 2 -4 2 -1 14 0 32 1 964 2 2055 3 303 4 102 5 2416 6 2386 7 34 Sysmiss 2 6 :2nd mode of transport 8303 7 -2 7499 -1 15 0 32 1 1 2 113 3 170 5 54 6 417 7 2 Sysmiss 7 7 :3rd Mode of transport 8303 7 -2 8235 -1 15 0 32 1 1 3 3 5 4 6 13 Sysmiss 7 Cluster number 8310 0 1 360 145.133 94.614 cluster number 2673 0 3.69e-40 360 179.684 105.43 4 : Service\facility code 2673 0 3.68782519453291e-40 1 1 334 2 334 3 334 4 334 5 334 6 334 7 334 8 334 4 : primary school type- one 2673 0 -4 1800 37.655 169.889 4 : primary school type- two 2673 0 -2 1478 8.865 87.078 4 : primary school type- three 2673 0 -2 1500 4.94 77.588 cluster number 4009 0 3.69e-40 360 179.707 105.411 4 : Service\facility code 4009 0 3.68782519453291e-40 1 1 334 2 334 3 334 4 334 5 334 6 334 7 334 8 334 9 334 10 334 11 334 12 334 4 : secondary school type- one 4009 0 -4 3000 26.743 165.675 4 : secondary school type- two 4009 0 -4 1953 4.867 81.372 4 : secondary school type- thre 4009 0 -20 1583 1.214 52.973 cluster number 2338 0 1 360 179.751 105.395 1 : personnel code 2338 0 1 334 2 334 3 334 4 334 5 334 6 334 7 334 1 : respondent code 2338 0 -1 87 1 712 2 1539 2 : distance of personnel 2338 0 -2 275 7.744 19.861 cluster number 2005 0 3.69e-40 360 179.662 105.449 3 : facility code 2005 0 3.68782519453291e-40 1 1 334 2 334 3 334 4 334 5 334 6 334 3 : hospital 2005 0 -1 40 0 3 3.68782519453291e-40 1 1 453 2 1508 4 : number of hospitals 2005 0 -2 1514 -1 116 3.68782519453291e-40 1 1 328 2 23 3 14 4 8 5 1 5 : distance of hospital 2005 0 -2 275 11.712 21.925 Household identification No 3344 0 1002 360017 193307.497 106597.718 1a:Code - Source of income - 3344 0 1 2094 2 237 3 139 4 320 5 23 6 37 7 235 8 96 9 21 10 4 11 14 12 62 13 55 14 2 15 5 1c:Receive income? 3344 0 -1 1 1 3342 7 1 2b:Person code 3343 1 1 2250 2 690 3 210 4 69 5 39 6 36 7 23 8 9 9 6 10 4 11 2 12 1 15 2 16 1 17 1 Sysmiss 1 2c:Amount received 3344 0 -4 52416 559.898 1520.997 Cluster number 3344 0 1 360 193.283 106.604 2673 0 3.69e-40 360 179.684 105.43 6 : Code of facility used 2673 0 3.68782519453291e-40 1 1 334 2 334 3 334 4 334 5 334 6 334 7 334 8 334 6.1: Number of recreational fac 2673 0 -1 224 0 1954 3.68782519453291e-40 1 1 339 2 102 3 25 4 12 5 8 6 1 7 1 8 2 9 1 15 3 6.2: Acces to the facility 2612 61 -2 1954 -1 224 0 17 3.68782519453291e-40 1 1 396 2 20 Sysmiss 61 6.3: Distance of the facility 2673 0 -2 503 23.771 43.21 Household identification No 5993 0 1005 360017 209556.989 99273.609 2 :Person code 5993 0 1 31 7.269 3.532 New Measurement data 5991 2 0 5788 1 97 2 106 Sysmiss 2 3 :Gender 5993 0 -1 30 F 2939 M 3024 4 :Date of Birth 5976 0 . 3 01/01/01 2 01/01/86 1 01/01/87 7 01/01/88 70 01/01/89 79 01/01/90 84 01/01/91 92 01/01/92 81 01/01/93 88 01/02/90 2 01/02/91 1 01/07/91 1 01/14/89 1 01/14/93 1 01/18/88 1 01/19/91 1 01/20/87 1 01/23/88 1 01/24/90 1 01/26/91 1 01/26/93 1 01/30/88 1 01012001 186 02/01/87 11 02/01/88 51 02/01/89 70 02/01/90 60 02/01/91 60 02/01/92 65 02/01/93 59 02/02/89 1 02/05/89 1 02/08/93 1 02/12/89 1 02/16/89 1 02/18/91 1 02/22/91 1 02/22/93 1 02/26/89 1 02/26/93 1 02012001 1 03/01/86 1 03/01/87 15 03/01/88 66 03/01/89 80 03/01/90 89 03/01/91 80 03/01/92 66 03/01/93 86 03/03/88 1 03/10/89 1 03/15/90 1 03/17/91 1 03/20/93 1 03/23/90 1 03/28/91 1 03/31/91 1 04/01/87 14 04/01/88 72 04/01/89 94 04/01/90 91 04/01/91 65 04/01/92 84 04/01/93 79 04/04/93 1 04/11/90 1 04/12/90 1 04/17/89 1 04/19/88 1 04/20/89 2 04/20/91 1 04/24/92 1 05/01/87 10 05/01/88 62 05/01/89 62 05/01/90 84 05/01/91 78 05/01/92 62 05/01/93 68 05/03/89 1 05/07/88 1 05/10/88 1 05/12/89 1 05/14/93 1 05/20/90 1 05/25/91 1 05/30/92 2 06/01/87 13 06/01/88 70 06/01/89 91 06/01/90 96 06/01/91 91 06/01/92 76 06/01/93 76 06/03/93 1 06/06/88 2 06/06/92 1 06/08/92 1 06/08/93 1 06/13/89 1 06/17/91 1 06/20/90 1 06/21/93 1 06/23/92 1 06/25/91 1 06012001 2 07/01/87 12 07/01/88 55 07/01/89 77 07/01/90 90 07/01/91 95 07/01/92 80 07/01/93 87 07/04/91 1 07/05/93 1 07/06/92 1 07/07/91 1 07/13/91 1 07/15/88 1 07/18/92 1 07/21/92 1 07/22/93 1 07/26/88 1 07/26/90 1 07/26/93 1 08/01/87 10 08/01/88 74 08/01/89 81 08/01/90 73 08/01/91 73 08/01/92 76 08/01/93 85 08/03/91 1 08/06/92 1 08/08/90 1 08/09/93 1 08/12/91 1 08/13/87 1 08/14/90 1 08/15/91 1 08/25/92 1 08/26/91 1 08/27/90 1 08012001 1 09/01/86 2 09/01/87 21 09/01/88 87 09/01/89 90 09/01/90 93 09/01/91 121 09/01/92 102 09/01/93 63 09/03/88 1 09/03/91 1 09/10/87 1 09/11/93 1 09/15/90 1 09/17/90 1 09/19/87 1 09/23/90 1 09/23/93 1 09/24/88 1 09/25/90 1 09/28/88 1 10/01/86 3 10/01/87 30 10/01/88 73 10/01/89 91 10/01/90 72 10/01/91 64 10/01/92 91 10/01/93 47 10/03/92 1 10/07/90 1 10/15/92 1 10/16/92 1 10/19/91 1 10/22/89 1 10/22/92 1 10/25/88 1 11/01/86 3 11/01/87 30 11/01/88 57 11/01/89 67 11/01/90 78 11/01/91 80 11/01/92 85 11/01/93 15 11/17/89 1 11/21/91 1 11/23/88 1 11012001 1 12/01/86 6 12/01/87 34 12/01/88 59 12/01/89 90 12/01/90 87 12/01/91 80 12/01/92 75 12/04/90 1 12/11/87 1 12/13/91 1 12/16/87 1 12/17/87 1 12/22/91 1 12/22/92 1 12/25/87 1 12/29/92 1 5 :Source of birth info 5993 0 -4 19 -3 20 -1 214 1 2345 2 786 3 20 4 1274 5 853 6 364 7 55 8 43 6 :Clinic Card 5993 0 -4 1 -3 4 -1 141 1 3989 2 1858 7a:Vaccinated(Measles) 5993 0 -4 20 -3 22 -2 1826 -1 341 0 731 1 2221 2 756 3 60 4 14 5 1 6 1 7b:Vaccinated(DPT) 5993 0 -4 18 -3 22 -2 1826 -1 307 0 309 1 316 2 390 3 1334 4 1395 5 69 6 6 7 1 7c:Vaccinated(Polio) 5993 0 -4 18 -3 22 -2 1826 -1 295 0 203 1 367 2 347 3 1153 4 1406 5 329 6 21 7 4 8 2 7d:Vaccinated(TB) 5993 0 -4 18 -3 22 -2 1826 -1 279 0 208 1 2597 2 933 3 83 4 21 5 5 6 1 8 :Child Breast Feeding 5993 0 -4 2 -3 19 -1 128 1 1321 2 4523 9 :Age Breast Feeding Stopped 5993 0 -4 99 18.163 28.472 10 :No. x Child Fed per Day 5993 0 -4 17 -3 22 -1 242 0 2 1 22 2 261 3 2865 4 1219 5 629 6 258 7 55 8 36 9 6 10 354 12 4 13 1 11 :Weight 5993 0 -4 96.1 10.415 6.684 12 :Height 5993 0 -4 192 72.172 37.436 13 :Reason Not Measured 5993 0 -3 6 -2 4917 -1 70 1 650 2 159 3 58 4 133 14 :Age start solids 5992 1 -4 99 0.366 2.931 Year of birth 5779 214 86 16 87 214 88 812 89 986 90 1015 91 1004 92 960 93 772 Sysmiss 214 Month of birth 5779 214 1 517 2 386 3 491 4 508 5 435 6 525 7 507 8 483 9 591 10 479 11 417 12 440 Sysmiss 214 Year of remeasuring 106 5887 93 51 94 55 Sysmiss 5887 Month of remeasuring 106 5887 2 6 3 49 11 44 12 7 Sysmiss 5887 Age in Months 5779 214 0 91 35.188 20.801 Height for Age Z score 4851 1142 -9.98 9.99 -1.063 2.201 Weight for Age Z score 4853 1140 -7.01 9.99 -0.611 1.807 Weight for Height Z score 4905 1088 -9.89 9.99 0.242 2.289 Cluster number 5993 0 1 360 209.535 99.277 cluster number 2339 0 3.69e-40 360 179.675 105.438 5 : Service\facility code 2339 0 3.68782519453291e-40 1 1 334 2 334 3 334 4 334 5 334 6 334 7 334 5a: number of facilities 2339 0 -1 100 0.528 2.623 5b: access to facility 2339 0 -2 1796 -1 31 -0.199999988079071 1 3.68782519453291e-40 1 1 499 2 11 5c: distance of facility 2339 0 -4 700 12.962 33.435 Household identification No 7513 0 1001 360016 143643.296 93503.131 2b:Person code 7513 0 1 4185 2 1939 3 726 4 329 5 159 6 84 7 37 8 22 9 13 10 6 11 3 12 3 13 1 14 1 15 2 16 1 18 1 19 1 3a:Code:occupation 7507 6 -4 5 -3 1 -1 1 1 1068 2 446 3 1076 4 404 5 1141 6 321 7 519 8 238 9 749 10 1524 11 14 Sysmiss 6 3b:Code:employer 7507 6 -4 7 -3 3 -1 7 1 777 2 450 3 304 4 401 5 4793 6 58 7 121 8 579 9 7 Sysmiss 6 3c:Code:economic sector 7507 6 -4 10 -3 4 -1 2 1 936 2 547 3 1262 4 145 5 421 6 812 7 191 8 486 9 289 10 589 11 417 12 145 13 647 14 177 15 404 16 23 Sysmiss 6 3d:Hours per day 7507 6 -4 48 8.541 2.095 3e:Overtime in past week 7507 6 -4 96 0.802 3.895 4c:Pay period type 7470 43 -4 7 -3 4 -2 2 -1 38 1 1340 2 372 3 5707 Sysmiss 43 4d:Take home pay 7487 26 -4 25000 934.9 1338.307 4e:Deductions (not taxes) 7487 26 -4 10000 232.44 514.555 4f:Gross pay 7487 26 -4 180000 1350.833 3315.544 4g:Bonus in the last year 7487 26 -4 80000 865.322 2259.846 4h:Profit share in past year 7487 26 -4 50000 65.839 1261.47 4i:Contribute to pension ? 7470 43 -4 58 -3 20 -2 5 -1 73 1 4193 2 3121 Sysmiss 43 5c:Value of transport 7459 54 -4 5000 51.675 288.158 5d:Value of food subsidy 7459 54 -4 3000 15.956 63.661 5e:Value of house subsidy 7459 54 -43 4000 50.442 187.997 5f:Paid-up member of a trade un 7452 61 -4 47 -3 16 -2 4 -1 55 1 2099 2 5231 Sysmiss 61 5g:Value of equipment 7459 54 -4 11000000 5260.845 190692.949 Cluster number 7513 0 1 360 143.618 93.509 Household identification No 24296 0 1001 360017 186196.253 103273.614 2b:Person code 24296 0 0 29 2.679 1.988 3 :Currently Employed ? 24296 0 -2 1 -1 3 1 9406 2 14886 4 :Job desription 24294 2 -2 14884 -1 6 1 7452 2 851 3 61 4 1037 5 3 Sysmiss 2 5 :Hours worked last week 24295 1 -4 168 16.185 22.845 6 :Liked more work last week 24294 2 -1 155 1 4118 2 20021 Sysmiss 2 7 :Look for work? 24296 0 -1 42 1.906 0.445 8 :Reason not look for work 24296 0 -4 1 -2 1766 -1 88 1 8275 2 3216 3 478 4 222 5 139 6 2906 7 4393 8 2515 9 297 10 :Job seeking method 24295 1 -2 22524 -1 13 1 231 2 85 3 991 4 398 5 53 Sysmiss 1 11 : Time spent(hrs) 24296 0 -4 90 -1.049 4.913 12 :Lowest weekly wage 24296 0 -4 600 1.336 16.869 13 :Lowest monthly wage 24296 0 -4 10000 58.565 304.487 14 :Paid job for 1 mth 24295 1 -2 22527 -1 16 1 849 2 903 Sysmiss 1 15a: Code recent job 24295 1 -4 2 -2 23189 -1 15 1 36 2 39 3 115 4 297 5 104 6 25 7 61 8 13 9 92 10 274 11 33 Sysmiss 1 15b:Current Employer 24295 1 -4 4 -2 23430 -1 16 1 21 2 24 3 13 4 40 5 588 6 3 7 23 8 126 9 7 Sysmiss 1 15c:Sector 24295 1 -4 4 -2 23430 -1 17 1 62 2 45 3 170 4 17 5 100 6 99 7 49 8 62 9 15 10 14 11 16 12 9 13 126 14 7 15 32 16 21 Sysmiss 1 24296 0 0 24028 1 268 Cluster number 24296 0 1 360 186.174 103.279 Household identification No 43687 0 1001 360017 198851.334 101637.147 1 :Person code 43687 0 -1 42 4.078 3.056 1a: Circled member / Resident 43687 0 1 40060 2 3627 1b: Is person respondent 43687 0 -1 2 1 8652 2 35033 3 :Relationship to head 43687 0 -1 1 1 7994 2 791 3 5258 4 18924 5 327 6 6643 7 52 8 87 9 507 10 223 11 65 12 911 13 915 14 171 15 10 16 184 17 27 18 407 19 190 4 :Gender code 43687 0 -1 11 F 22575 M 21101 5 :Age in years 43687 0 -4 110 25.343 18.884 6 :Education code 43687 0 -4 19 4.352 4.241 7 :Spouse present ? 43687 0 -4 99 12.017 32.77 8 :Father present ? 43687 0 -4 99 60.905 44.041 9 :Mother present ? 43687 0 -4 99 43.837 45.817 10 :Absence in last 12 mths 43687 0 -4 99 0.791 2.74 11 :Code -Reason for absence 43687 0 -4 1 -2 37090 -1 48 1 2345 2 330 3 384 4 147 5 148 6 21 7 1270 8 71 9 94 10 29 11 1432 12 50 13 52 14 21 15 154 12 :15 days out of last 30 days 43687 0 -2 1 -1 24 1 40119 2 3543 13 :Migrated during past 5 yrs 43687 0 -2 1 -1 96 0 1 1 3360 2 40229 14 :Last place of residence 43687 0 -2 20 -1.109 3.623 4 :Gender code 43687 0 1 11 2 22576 3 21100 Cluster number 43687 0 1 360 198.829 101.642 Household identification No 151027 0 1001 360017 168165.916 102078.855 1a:Food code 151027 0 -1 31 14.779 8.45 1b:Eat or Bought? 151026 1 -1 124 1 150765 2 136 7 1 Sysmiss 1 2 :Weekly/Monthly? 151027 0 -2 120 -1 1067 1 52725 2 97111 3 2 4 1 7 1 3a:Value of food 150999 28 -4 3500 10.163 31.691 3b:Quantity 150987 40 -4 320 3.788 10.348 4a:Value of food received 150965 62 -4 500 0.119 4.224 4b:Amount of food received 150965 62 -4 397 0.18 3.538 5a:Value of food produced 150967 60 -4 300 0.0471 1.973 5b:Amount of food produced 150968 59 -4 240 0.0939 2.158 Cluster number 151027 0 1 360 168.141 102.086 358 0 1 360 180.293 104.321 Metro - Urban - Rural 358 0 1 187 2 76 3 95 Household identification No 8809 0 1001 360017 179767.71 102415.701 Cigarettes and Tobacco Exp. 8736 73 0 2000 23.644 52.447 Spirits Exp. 8725 84 0 2000 24.66 58.178 Entertainment Exp. 8800 9 0 3000 13.523 66.971 Personal Care Exp. 8752 57 0 800 30.96 46.173 Newspapers Etc. Exp. 8792 17 0 1800 8.906 34.661 Telephone Exp. 8789 20 0 1600 29.68 74.393 Vehicle Exp. 8770 39 0 4000 71.435 202.81 Transportation Exp. 8734 75 0 25000 51.736 330.421 Washing Supplies Exp. 8771 38 0 800 14.502 19.119 Day Care Exp. 8801 8 0 700 11.884 51.568 Dues Exp. 8766 43 0 3000 20.394 73.183 Donations Exp. 8800 9 0 1500 4.286 38.496 Household Help Exp. 8800 9 0 2400 35.676 115.974 With Missing Values 8745 64 0 8418 1 220 2 80 3 15 4 6 5 3 6 1 10 1 13 1 Sysmiss 64 Tot Non Food Month Exp 8482 327 0 27055 340.862 603.208 Cluster number 8809 0 1 360 179.744 102.421 Household identification No 8809 0 1001 360017 179767.71 102415.701 Kitchen equipments 8767 42 0 13000 87.517 417.148 Home rep/maint. 8778 31 0 80000 447.296 3218.98 Bedding/Towels etc. 8774 35 0 6000 92.914 295.743 Furniture/Appliance 8780 29 0 60000 666.228 1951.438 Shoes 8619 190 0 6000 250.361 354.39 Clothes 8607 202 0 16000 533.161 892.66 cloth materials. 8793 16 0 30000 61.341 432.31 Dentists/Doctors/Nurses 8721 88 0 30000 177.688 921.369 Hospital Fees 8738 71 0 45000 75.106 829.371 Medical Supplies 8770 39 0 17000 70.597 446.755 Traditional Healer 8796 13 0 4400 13.979 99.638 Holidays 8796 13 0 120000 413.053 2749 Luxury Goods 8802 7 0 40000 101.618 860.294 With Missing Values 8061 748 0 7634 1 178 2 179 3 33 4 16 5 9 6 6 7 2 8 3 13 1 Sysmiss 748 Tot Non Food Yearly Exp 8382 427 0 156700 2992.809 6987.577 Cluster number 8809 0 1 360 179.744 102.421 :Cluster Number 358 0 1 360 180.293 104.321 2:Statistical Region 358 0 0 97 50.296 36.91 3:Province Code 358 0 0 67 1 58 2 23 3 90 4 21 6 50 7 9 9 26 10 3 11 7 13 4 4:Province Name 358 0 BOPHUTHATSWANA 21 CAPE 58 CISKEI 8 GAZANKULU 9 KANGWANE 7 KWA ZULU 50 KWANDEBELE 4 LEBOWA 26 NATAL 23 ORANGE FREE STATE 21 QWA-QWA 3 TRANSKEI 33 TRANSVAAL 90 VENDA 5 5:Magesterial District - Code 358 0 001 1 003 3 004 2 005 1 006 12 007 2 010 1 015 2 017 2 022 1 024 1 027 1 032 1 034 1 043 1 045 1 046 1 049 1 051 6 052 2 053 1 060 1 074 1 081 1 088 1 093 3 094 1 097 2 099 1 105 1 107 1 108 1 201 1 203 1 210 2 211 1 212 1 219 3 220 5 221 2 222 1 223 1 225 1 227 1 231 1 232 1 237 1 300 13 302 1 303 4 304 4 305 4 306 5 307 2 308 1 309 1 310 1 311 3 312 3 313 1 314 1 316 7 317 1 318 2 319 1 320 3 321 4 323 1 324 2 325 1 334 4 339 1 341 1 344 1 346 1 349 1 350 1 354 1 355 1 357 1 358 1 360 2 362 1 364 1 365 2 367 1 402 1 410 3 413 2 421 1 422 1 424 4 429 1 433 1 434 2 439 1 441 2 442 1 447 1 500 2 501 2 503 3 504 2 505 3 506 3 507 2 508 3 509 4 512 2 513 2 515 2 516 3 517 5 519 1 520 2 523 1 524 6 525 2 600 1 601 3 602 3 633 2 636 1 700 3 800 1 801 2 803 3 804 2 805 1 900 1 901 5 903 2 904 4 905 2 906 3 907 2 908 3 909 1 910 3 950 2 951 2 B01 1 B02 1 B03 1 B04 1 B05 1 B06 1 B07 1 B08 1 B09 1 B10 1 B11 1 B12 1 B13 1 B14 1 B15 1 B16 1 B17 1 B18 1 B19 1 B20 1 B21 1 C01 1 C02 1 C03 2 C04 1 C05 2 C06 1 T01 2 T03 1 T04 1 T05 2 T06 1 T07 1 T08 1 T09 2 T10 2 T12 2 T13 1 T14 1 T15 1 T16 1 T17 1 T18 1 T19 1 T20 1 T21 1 T22 1 T23 2 T24 2 T25 1 T26 1 T27 1 T28 1 V01 1 V02 3 V03 1 6:Magesterial District - Name 358 0 ALFRED 1 BAFOKENG 1 BALFOUR 1 BARBETON 1 BEDFORD/ADELAIDE 1 BELLVILLE 3 BENONI 4 BETHULIE 1 BIZANA 2 BLOEMFONTEIN 3 BOCHUM 2 BOKSBURG 4 BOLOBEDU 5 BOTHAVILLE 1 BOTSHABELO 2 BRAKPAN 3 BRITS 1 BUTTERWORTH 1 CALEDON 2 CAPE TOWN 1 CERES 1 CHATSWORTH 1 COFIMVABA 1 CULLINAN 1 DE AAR 1 DITSOBOTLA 1 DUNDEE 1 DURBAN 3 DZANANI 1 EAST LONDON 3 EERSTEHOEK 1 ELLIOTDALE 1 EMBUMBULU 3 EMNAMBITHI 3 EMPUMALANGA 3 EMZUMBE 2 ENGCOBO 1 ENSELENI 5 ERMELO 1 EXCELSIOR 1 EZINGOLWENI 2 FICKSBURG 2 FLAGSTAFF 2 GERMISTON 1 GOODWOOD 2 GORDONIA 1 HARRISMITH 1 HEWU 1 HLANGANANI 4 HOEVELDRIF 1 HOFMEYR 1 HOOPSTAD 1 HUMANSDORP 1 IDUTYWA 1 INANDA 5 INKANYEZI 2 JOHANNESBURG 13 KEMPTON PARK 4 KENTANI 1 KIESKAMMA HOEK 1 KIMBERLEY 2 KIRKWOOD 1 KLERKSDORP 3 KLIPRIVER 1 KNYSNA 1 KROONSTAD 2 KRUGERSDORP 3 KUILS RIVER 1 LADY FRERE 1 LEHURUTSHE 2 LIBODE 1 LICHTENBURG 1 LIONS RIVER 1 LOWER TUGELA 1 LOWER UMFOLOZI 1 LULEKANI 2 LUSIKISIKI 2 LYDENBURG 1 MACLEAR 1 MADADENI 6 MADIKWE 1 MAHLABATINI 1 MALAMULELE 3 MALUTI 2 MANKWE 1 MAPULANENG 3 MARICO 1 MDANTSANE 2 MDUTJANA 2 MHALA 1 MKOBOLA 2 MOKERONG 4 MOLOPO 2 MORETELE 3 MOUTSE 1 MPOFU 1 MQANDULI 1 MSINGA 2 MT. FLETCHER 2 MT. FRERE 1 NAMAKGALE 1 NAMAKWALAND 1 NAPHUNO 1 NDWEDWE 3 NEBO 2 NEW HANOVER 1 NEWCASTLE 1 NGOTSHE 1 NGQELENI 1 NIGEL 1 NKANDLA 2 NKOMAZI 3 NONGOMA 2 NQAMAKWE 1 NSIKAZI 3 NTUZUMA 4 OBERHOLZER 1 ODENDAALSRUS 1 ODI 5 OKHAHLAMBA 1 OKHLAHLAMBA 1 OUDTSHOORN 1 PAARL 1 PEDDIE 1 PHALABORWA 1 PIET RETIEF 1 PIETERMARITZBURG 2 PIETERSBURG 1 PINETOWN 2 PORT ELIZABETH 6 PORT ST. JOHNS 1 POSTMASBURG 1 POTCHEFSTROOM 1 POTGIETERSRUS 1 PRETORIA 7 PRINCE ALBERT 1 QUEENSTOWN 1 QUMBU 1 RANDBURG 5 RANDFONTEIN 1 RITAVI 2 RIVERSDALE 1 ROODEPOORT 2 SASOLBURG 1 SCHWEIZER RENEKE 1 SEKHUKHUNELAND 3 SENEKAL 1 SESHEGO 2 SIMDLANGENTSHA 1 SOMERSET WEST 2 SOSHANGUVE 2 SPRINGS 1 STANDERTON 2 STERKSPRUIT 1 SWARTRUGGENS 1 TABANKULU 1 TAUNG 3 THABA-NCHU 1 THABAMOOPO 3 THOHOYANDOU 3 TLHAPING - TLHARO 1 TSOLO 1 TSOMO 1 UITENHAGE 2 UMLAZI 2 UMTATA 2 UMZIMKHULU 2 UMZINTO 1 VANDERBIJLPARK 3 VANRHYNSDORP 1 VENTERSDORP 2 VEREENIGING 4 VREDENBURG 2 VRYBURG 1 VULINDLELA 2 VUWANI/TSHITALE 1 WARMBAD 1 WARRENTON 1 WELKOM 3 WESSELSBRON 1 WESTONARIA 1 WILLOWVALE 1 WITBANK 4 WITSIESHOEK 3 WONDERBOOM 1 WORCESTER 1 WYNBERG 12 ZWELITSHE 2 7:ESD Name 358 0 ACTONVILLE 1 ADRIAANSE 1 ALEXANDER BAY 1 ALEXANDRA 2 ALFRED NU/NS 1 ATTERIDGEVILLE 1 BALFOUR NU/NS 1 BARBETON NU/NS 1 BEACON VALLEY 1 BEDFORD/ADELAIDE 1 BELHAR 1 BENONI 1 BETHELSDORP 2 BIESIESVLEI 1 BISHOP LAVIS 1 BLOCK X 1 BOCHUM NU/NS 2 BOLOBEDU NU/NS 4 BOTHAVILLE NU/NS 1 BOTSHABELO 2 BRACKENFELL 1 BRITS NU/NS/CULLINAN 1 CALEDON NS/NU 1 CERES NU/NS 1 CHURCHILL 1 CLAREMONT 1 CLERKILLE 1 COMET 1 CONSTANTIA PARK 1 CORANA 1 CROSSMOOR 1 DALVIEW 1 DAVEYTON 2 DE AAR 1 DESPATCH 1 DIEPMEADOW 3 DIHIBIDUNG 1 DOBSONVILLE 1 DUDMENI 1 DUDUZA 1 DUMSI 1 DURBANVILLE PROPER 1 EAST LONDON NU/NS 1 EASTWOOD 1 EDENDALE 1 EERSTEHOEK NU/NS 1 ELARDUSPARK 1 EMBALENHLE 1 EMBUMBULU NU/NS 2 EMNABITHI NU/NS 1 EMNAMBITHI 1 EMPUMALANGA NU/NS 2 EMZUMBE NU/NS 2 ENNERDALE 1 ENSELENI NU/NS 5 EVATON 1 EXCELSIOR NU/NS 1 EZAKHENI 1 EZINGOLWENI NU/NS 2 FAMA 1 FORT MALAN 1 GA-KGAPANE 1 GALESHEWE 1 GAQANGANA/NOKGOHLOKO 1 GELUKSDAL 1 GERMISTON REST 1 GLENMARAIS 1 GLENMORE 1 GRABOUW 1 GRASSY PARK 1 GRASSY PARK/MONTAGU'S GIFT 1 GREENFIELD 1 GROSVENOR/JACOBS/BONELA 1 GUGULETHU 1 HARRISMITH NU/NS 1 HAYI/MNGAZI/NDITA 1 HEIDEDAL 1 HLANGANANI NU/NS 4 HOFMEYR NS/NU 1 HOMEVALE 1 HOOPSTAD NU/NS 1 HOWICK 1 IBHAYI 2 IMBALI 1 INKANYEZI NU/NS 2 IPELENGENG 1 ITSOSENG 1 JEFFREYS BAY 1 JOBERTON 1 JOHANNESBURG & CLAREMONT 1 KAGISO 1 KALANA 1 KEMPTON PARK RES. 1 KENSINGTON 2 KGABOESELE 1 KHAYELITSA/LINGELETHU WEST 2 KHUTSONG 1 KIRKWOOD NS/NU 1 KLAWER 1 KLERKSDORP NU/NS 1 KOEQANA 1 KOKOMENG 1 KROONSTAD 1 KRUGERSDORP NORTH 1 KUTLWANONG 1 KWAMAKUTA 1 KWAMASHU 2 KWANO-BUHLE 1 KWATHEMA 1 KWAZANELE 1 KWELERA/NEWLANDS/MOOIPLAAS 1 LADYSMITH 1 LAMTHOLE 1 LANGA 1 LENTEGEUR 1 LEPHOI 1 LOWER TUGELA NU/NS 1 LUGENGELENI/GXENI 1 LULEKANI NU/NS 1 LULEKANI/NKOWAKIWA 1 LUYENGWENI 1 LYDENBURG NU/NS 1 MACASSAR 1 MACLEAR NS/NU 1 MADADENI 1 MADADENI NU/NS 3 MADINKGWANA 1 MAGWACA 1 MAHANGWE 1 MAHLABATINI NU/NS 1 MALAMULELE NU/NS 3 MAMELODI 1 MANGAUNG 2 MAOKENG 1 MAPULANENG NU/NS 3 MAQANYENI 1 MARICO NU/NS 1 MATHEKO 1 MATLOU 1 MATOLONG 1 MATSA 1 MATSULU 1 MAUMONG 1 MAUTSE 1 MDANTSANE 2 MDUTJANA NU/NS 1 MENLO PARK 1 MEQHELENG 1 MFOLOZI 1 MHALA NU/NS 1 MIDRAND 1 MIER 1 MKHAMBA 1 MKOBOLA NU/NS 2 MMAKAU 1 MNGQOSINI 1 MODIMOLA 1 MOEDING 1 MOEMA 1 MOHLAKENG 1 MOKERONG NU/NS 4 MOKWENA 1 MOLELEMA 1 MONYAKENG 1 MOTHERWELL 1 MOTLHABENG 1 MOUNT ROAD/CANNONVILLE 1 MOUTSE NU/NS 1 MPUMALANGA 1 MSINGA NU/NS 2 MSOBOMVU 1 MVOLOZANE 1 NAMAKGALE 1 NAPHUNO NU/NS 1 NBUQWINI 1 NDWEDWE NU/NS 3 NEBO NU/NS 2 NEW HANOVER NU/NS 1 NEWCASTLE NU/NS 1 NEWLANDS WEST 1 NGANGELIZWE 1 NGAPHESHEYA/MISSION/NKENCEZI 1 NGOTSHE NU/NS 1 NGQUBA 1 NKANDLA NU/NS 2 NKOMAZI NU/NS 3 NONGOMA NU/NS 2 NORKEM PARK 1 NSIKAZI NU/NS 2 NTABA KANDODA FOREST 1 NTUZUMA 1 NTUZUMA NU/NS 1 OKHAHLAMBA NU/NS 2 ORANGEFARM EN OMGEWING 1 OSIZWENI 2 OUDTSHOORN 1 PAARL 1 PARKDENE 2 PERCY 1 PHALABORWA NU/NS 1 PHOLA 1 PHUMLO 1 PIET RETIEF 1 PIETERSBURG 1 PINETOWN 1 PLETTENBERG BAY 1 POSTMASBURG NS/NU 1 POTCHEFSTROOM NU/NS 1 POTGIETERSRUS NU/NS 1 PRETORIA CENTRAL 1 PRINCE ALBERT NS/NU 1 PROTEA RIDGE A.H. 1 QADINI/RHINI/MDENI 1 QUEENSTOWN 1 RAMANYAPELO A RAMOLE 1 RANDPARKRIF 1 RANDVAAL 1 REFILWE 1 RETREAT 1 RHEEDERPARK 1 RICHARDS BAY 1 RITAVI NU/NS 2 RIVERSDALE 1 RIVONIA 1 ROBERTSHAM 1 ROCKFORD 1 ROCKLANDS 1 SASOLBURG NU/NS 1 SEA POINT 1 SEBOKENG 1 SEKHUKHUNELAND NU/NS 2 SEKHUKHUNELAND/NEBO 1 SENEKAL NU/NS 1 SESHEGO NU/NS 2 SHAYANDIMA 1 SIBONGILE 1 SIDIKIDIKI 1 SILVERTON 1 SIMDLANGENTSHA NU/NS 1 SITHEBE 1 SIYABUSWA 1 SOMERSET WEST 1 SOSHANGUVE 2 SOWETO 5 SPARKS 1 ST. WENDOLINS, SAVANNAH PARK 1 STANDERTON NU/NS 2 STILFONTEIN 1 SUNFORD 1 SWARTRUGGENS NU/NS 1 TAFELSIG 1 TEMBISA 1 THABAMOOPO NU/NS 3 THABONG 1 TLHABANE 1 TONGAAT 1 TSAKANE 1 TSHITEREKE, DONALD FRASER 1 TSITSONG 1 TYUTYU 1 UMLAZI 2 UMZINTO NORTH 1 UPPER BLINKWATER/TIDBURY'S TOLL 1 VANDERBIJLPARK 1 VENTERSDORP NU/NS 2 VEREENIGING NU/NS 1 VERULAM 1 VHANGANI 1 VHUTALU, MUDZIDZIDAI 1 VOSLOOSRUS 1 VREDENBURG/SALDAHNA 2 VRYBURG NS/NU 1 VULINDLELA NU/NS 1 WARD 6 1 WARD F 1 WARD H 1 WARMBAD 1 WARRENTON 1 WELBEDACHT 1 1 WELKOM NS/NU 1 WELTEVREDEN PARK 1 WESTCLIFF 1 WESTONARIA/DISCOVERY 1 WESTRIDGE 1 WINDERMERE 1 WITBANK 1 WITBANK NU/NS 2 WITSIESHOEK NU/NS 3 WONDERBOOM SUID 1 WORCESTER 1 ZIZANA 1 8:Population 358 0 0 596632 33989.52 95618.327 9:Type 358 0 0 186 1 170 3 2 10:Survey Organisation 358 0 1 41 2 33 3 23 4 57 5 51 6 57 7 71 8 8 9 17 Province 358 0 1 58 2 23 3 90 4 21 5 50 6 7 7 3 8 9 9 26 10 4 11 33 12 21 13 5 14 8 New Province 358 0 1 33 2 7 3 58 4 73 5 25 6 29 7 39 8 32 9 62 New Magesterial Code 358 0 1 4006 654.251 749.983 Household identification No 35 0 34006 336011 145300.914 68202.606 1a:Partnership ? 35 0 1 5 2 30 1b:Percentage of Farm 35 0 -4 51 2.486 13.921 2 :(1) Field crop products 35 0 -4 2433612 202740.2 494962.364 2 :(2) Value of hortic product 35 0 -1 51000 2485.686 9882.765 2 :(3) Value of animal products 35 0 -4 800000 93620.114 180114.168 2 :(4) Forestry products 35 0 -1 202816 6423.286 34284.398 2 :(5) Other farm income 35 0 -1 240000 26228.543 53454.825 3 :(1) Capital expenses 35 0 -4 1000000 76696.514 192408.672 3 :(2) Cost of new equipment 35 0 -4 288000 29599.857 62595.592 3 :(3) New building cost 35 0 -4 300000 22057.057 63962.309 3 :(4) Development work 35 0 -4 100000 4859.829 17444.957 3 :(5) Other expenses 35 0 -4 465000 44422.829 116362.192 3 :(6) Running cost 35 0 -4 1218076 88806.571 211612.132 4a:No of permanent workers 35 0 -1 64 9.714 13.522 4b:No of seasonal workers 35 0 -1 300 20.829 53.648 5 :(1) Tractors other farm vehi 35 0 -4 3000000 336041.343 578694.541 5 :(2) Mechanised farm equipmen 35 0 -4 800000 86264.914 167623.988 5 :(3) Other farm tools 35 0 -4 510000 39645.057 98002.496 Cluster number 35 0 34 336 145.286 68.201 clustnum 207 0 1 360 220.449 100.737 agricultural centre service 195 12 1 76 2 119 Sysmiss 12 distance of centre service 92 115 0 200 30.804 32.832 agricultural agent service visi 1 206 1 1 Sysmiss 206 farming agencies 66 141 0 1 1 51 2 6 3 5 4 3 Sysmiss 141 farming agencies 6 201 0 1 1 1 3 4 Sysmiss 201 service provided by agencies 60 147 1 20 2 13 3 10 4 7 6 9 8 1 Sysmiss 147 service provided by agencies 37 170 0 1 1 11 2 12 3 5 4 5 6 3 Sysmiss 170 service provided by agencies 15 192 1 7 2 3 3 2 4 2 6 1 Sysmiss 192 service provided by agencies 9 198 0 2 1 1 2 3 3 2 6 1 Sysmiss 198 cooperative service 184 23 1 32 2 150 6 2 Sysmiss 23 cooperative service code1 7 200 0 3 1 1 2 3 Sysmiss 200 cooperative service code2 5 202 0 1 1 1 2 2 4 1 Sysmiss 202 cooperative service code3 0 207 Sysmiss 207 cooperative service code4 0 207 Sysmiss 207 number of tractors availability 73 134 0 500 19.644 61.26 are fertilizers used? 176 31 1 83 2 93 Sysmiss 31 use insecticides or herbicides? 180 27 1 67 2 113 Sysmiss 27 rain during the past twelve mon 186 21 1 41 2 118 3 27 Sysmiss 21 buy or sell land? 190 17 1 34 2 156 Sysmiss 17 are there any sharecroppers? 189 18 1 32 2 157 Sysmiss 18 sharecroppers proportion 38 169 1 3 2 14 3 6 4 15 Sysmiss 169 Household identification No 1442 0 2024 360012 269177.318 65960.6 3a:Litres milk last month 1442 0 -4 4900 8.023 162.964 3b:Litres of milk used 1442 0 -4 100 0.556 6.492 3c:Litres of milk sold 1442 0 -4 4865 5.748 154.067 3d:Value of milk sold 1442 0 -4 3892 4.739 123.277 4a:No of eggs produced 1442 0 -4 326 8.721 16.481 4b:No of eggs used 1442 0 -4 100 2.856 8.204 4c:Qty eggs sold 1442 0 -4 290 -0.119 8.082 4d:Value off eggs sold 1442 0 -4 240 -0.0573 6.784 5 :Value of sale of wool 1442 0 -4 1600 1.415 52.393 6 :Value of skins/hides sold 1442 0 -3 144 -0.275 5.782 7 :Cost of vet services 1442 0 -4 1800 8.494 75.632 Cluster number 1442 0 2 360 269.159 65.959 Household identification No 1141 0 2024 360010 263464.18 64280.682 3.1a:Subsidies or drought relie 1141 0 -1 17 1 16 2 1108 3.1b:Value of subsidies 1141 0 -2 240000 369.465 7522.782 3.2a:Services to other farmers 1141 0 -1 21 1 13 2 1107 3.2b:Value of services to other 1141 0 -2 400 -0.588 17.275 3.3 :Other income from farming 1141 0 -1 19 1 8 2 1114 4.1a:Own tractors etc ? 1141 0 -1 13 1 35 2 1093 4.1b:Value of vehicles 1141 0 -4 1000000 1814.428 31871.642 4.2a:Own mechanised Equipment? 1141 0 -1 14 1 49 2 1078 4.2b:Value of mechanised equip 1141 0 -4 100000 381.884 4722.665 4.3a:Own non mechanised equip 1141 0 -1 17 1 857 2 267 4.3b:Value of non mech. equip 1141 0 -4 60000 187.126 1932.736 Cluster number 1141 0 2 360 263.445 64.278 Household identification No 5971 0 1009 360016 194353.301 104051.583 1a:Bursaries ? 5971 0 -1 96 1 147 2 5728 1b:Value of bursaries 5953 18 -4 50000 84.42 1143.189 2a:Free school meals? 5971 0 -1 98 0 18 1 114 2 5741 2b:Value of free meals 5971 0 -4 3000 3.517 63.749 Cluster number 5971 0 1 360 194.331 104.057 cluster number 299 0 3.69e-40 341 162.174 95.265 adult literacy programme 291 8 3.69e-40 2 1.739 0.448 programme start 80 219 0 1993 1912.913 379.996 programme end 22 277 0 1993 904.318 1013.945 number of men attended 52 247 0 250 43.788 49.668 number of women attended 55 244 0 600 69.855 106.805 schooling problem one 220 79 0 8 3.359 2.698 schooling problem two 155 144 0 9 3.484 2.607 schooling problem three 91 208 0 10 2.736 2.25 schooling problem four 47 252 3.69e-40 8 2.468 2.009 cluster number 299 0 1 341 162.709 95.333 traditional birth attendant 246 53 0 1 1 78 2 167 Sysmiss 53 distance of traditional birth a 82 217 0 160 13.205 23.282 health services or personnel 285 14 0 2 1 42 2 241 Sysmiss 14 specify services 22 0 0 2 2 3 AMBULANCE SERVICES 1 DENTIST 1 FIRST AID 1 FIRST AIDERS 1 HERBALISTS, SANGOMAS 1 HOMEOPATH 1 MOBILE CLINIC 1 PRIVATE DOCTOR 1 PROPHETS 1 SATELITE COMBI 1 TRAD. DOCTORS 1 TRAD. HEALERS 4 TRADITIONAL HEALERS 1 WITCH DOCTORS 1 health problem one 212 87 0 1 1 22 2 16 3 90 4 13 5 38 6 28 7 2 8 2 Sysmiss 87 health problem two 148 151 0 2 1 21 2 16 3 44 4 15 5 22 6 27 8 1 Sysmiss 151 health problem three 79 220 0 2 1 8 2 10 3 21 4 8 5 16 6 11 7 3 Sysmiss 220 health problem four 48 251 0 11 1 7 2 6 3 7 4 3 5 1 6 12 7 1 Sysmiss 251 health service one 184 115 0 1 1 125 2 7 3 10 4 3 5 36 6 1 9 1 Sysmiss 115 health service two 100 199 0 1 1 52 2 4 3 16 5 25 6 1 8 1 Sysmiss 199 health service three 51 248 0 3 1 23 2 5 3 10 4 1 5 8 6 1 Sysmiss 248 health service four 23 276 0 3 1 12 2 3 3 2 5 2 6 1 Sysmiss 276 birth place in community 292 7 0 1 1 25 2 51 3 192 4 23 Sysmiss 7 immunisation campaign 291 8 0 2 1 206 2 83 Sysmiss 8 cluster number 334 0 1 360 179.751 105.531 date began 332 0 01/29/1994 1 04/01/1994 1 04/10/1993 1 07/26/1993 1 07/27/1993 1 08/01/1993 2 08/10/1993 1 08/11/1993 1 08/14/1993 1 08/16/1993 2 08/17/1993 2 08/18/1993 4 08/19/1993 2 08/20/1993 1 08/23/1993 5 08/24/1993 3 08/25/1993 2 08/26/1993 1 08/27/1993 5 08/29/1993 3 08/30/1993 2 08/31/1993 3 09/01/1993 1 09/02/1993 1 09/03/1993 2 09/04/1993 2 09/06/1993 4 09/07/1993 5 09/08/1993 2 09/09/1993 5 09/10/1993 4 09/11/1993 5 09/13/1993 2 09/14/1993 1 09/15/1993 1 09/16/1993 4 09/17/1993 3 09/18/1993 2 09/20/1993 4 09/21/1993 9 09/22/1993 6 09/23/1993 7 09/24/1993 7 09/25/1993 1 09/26/1993 1 09/27/1993 5 09/28/1993 8 09/29/1993 5 10/01/1993 5 10/02/1993 1 10/03/1993 3 10/04/1993 3 10/05/1993 6 10/06/1993 3 10/07/1993 4 10/08/1993 8 10/10/1993 1 10/11/1993 2 10/12/1993 4 10/13/1993 5 10/14/1993 8 10/15/1993 6 10/16/1993 4 10/18/1993 1 10/19/1993 5 10/20/1993 7 10/21/1993 5 10/22/1993 3 10/23/1993 1 10/25/1993 1 10/26/1993 3 10/27/1993 1 10/28/1993 4 10/29/1993 2 10/30/1993 1 11/01/1993 6 11/02/1993 4 11/03/1993 4 11/04/1993 3 11/05/1993 2 11/07/1993 2 11/08/1993 3 11/09/1993 3 11/10/1993 4 11/11/1993 5 11/12/1993 4 11/13/1993 1 11/14/1993 2 11/15/1993 3 11/16/1993 5 11/17/1993 2 11/18/1993 6 11/19/1993 5 11/20/1993 1 11/21/1993 2 11/23/1993 5 11/24/1993 1 11/25/1993 6 11/27/1993 3 11/29/1993 2 11/30/1993 2 12/02/1993 1 12/07/1993 1 12/09/1993 1 12/10/1993 1 15/10/1993 1 29/09/1993 1 31/08/1993 1 date completed 320 0 01/31/1994 1 04/01/1994 1 05/10/1993 1 05/11/1993 1 08/01/1993 1 08/10/1993 1 08/11/1993 1 08/15/1993 1 08/16/1993 1 08/17/1993 2 08/18/1993 3 08/19/1993 3 08/23/1993 3 08/24/1993 1 08/25/1993 3 08/26/1993 2 08/27/1993 5 08/28/1993 1 08/30/1993 1 08/31/1993 4 09/02/1993 1 09/04/1993 1 09/05/1993 1 09/06/1993 3 09/07/1993 4 09/08/1993 2 09/09/1993 3 09/10/1993 5 09/11/1993 4 09/12/1993 2 09/13/1993 2 09/14/1993 3 09/15/1993 1 09/16/1993 1 09/17/1993 3 09/18/1993 3 09/20/1993 4 09/21/1993 6 09/22/1993 3 09/23/1993 6 09/24/1993 3 09/25/1993 1 09/26/1993 3 09/27/1993 8 09/28/1993 6 09/29/1993 3 09/30/1993 3 10/01/1993 3 10/03/1993 5 10/04/1993 1 10/05/1993 5 10/06/1993 5 10/07/1993 3 10/08/1993 4 10/09/1993 1 10/10/1993 2 10/11/1993 3 10/12/1993 5 10/13/1993 4 10/14/1993 8 10/15/1993 7 10/16/1993 2 10/17/1993 1 10/18/1993 3 10/19/1993 3 10/20/1993 2 10/21/1993 4 10/22/1993 3 10/23/1993 4 10/24/1993 1 10/25/1993 2 10/26/1993 3 10/27/1993 1 10/28/1993 1 10/29/1993 6 10/31/1993 1 11/02/1993 6 11/03/1993 5 11/04/1993 2 11/05/1993 4 11/07/1993 1 11/08/1993 1 11/09/1993 5 11/10/1993 2 11/11/1993 7 11/12/1993 7 11/15/1993 3 11/16/1993 4 11/17/1993 4 11/18/1993 10 11/19/1993 9 11/20/1993 2 11/21/1993 2 11/23/1993 2 11/24/1993 2 11/25/1993 4 11/26/1993 5 11/27/1993 3 11/29/1993 1 11/30/1993 3 12/01/1993 3 12/02/1993 2 12/08/1993 1 12/12/1993 1 12/13/1993 1 15/10/1993 1 29/09/1993 1 31/08/1993 1 type of community 322 12 -1 1 1 149 2 21 3 151 Sysmiss 12 population group- a 332 2 0 1 1 240 2 29 3 10 4 51 5 1 Sysmiss 2 population group- b 83 251 0 1 1 23 2 22 3 5 4 31 5 1 Sysmiss 251 population group- c 197 137 0 170 1 3 2 9 3 6 4 8 5 1 Sysmiss 137 population group- d 13 321 -1 1 0 5 1 2 2 3 3 2 Sysmiss 321 religion- a 328 6 0 6 1 2 2 301 3 11 5 1 6 7 Sysmiss 6 religion- b 231 103 0 151 2 20 3 2 4 28 5 2 6 28 Sysmiss 103 religion- c 193 141 0 178 2 5 3 1 4 7 6 2 Sysmiss 141 religion- d 184 150 0 183 6 1 Sysmiss 150 people moved too or away from c 327 7 0 1 1 164 2 30 3 67 4 65 Sysmiss 7 homeless people 326 8 0 2 1 96 2 228 Sysmiss 8 amount of homeless people 97 237 -31072 5200 171.186 3398.95 cluster number 335 0 1 360 179.224 105.814 6 : public transport 332 3 0 2 1 259 2 71 Sysmiss 3 7 : mode of transport 277 58 -1 1 0 7 1 46 2 9 3 86 4 3 5 19 6 105 7 1 Sysmiss 58 8 : distance of public transpor 87 248 0 160 7.439 21.315 9a: frequency code 250 85 -1 1 1 245 2 4 Sysmiss 85 9b: frequency number 132 203 -1 80 5.894 12.639 cluster number 334 0 1 360 179.751 105.531 1 : secondary school 334 0 -1 1 0 1 1 165 2 167 2 : number of secondary school 334 0 -2 163 -1 13 0 1 1 122 2 20 3 9 4 3 5 1 6 1 7 1 3 : distance of secondary schoo 334 0 -2 120 3.459 12.316 Household identification No 8808 0 1001 360017 179777.902 102417.049 1 :Drinking + other water sourc 8808 0 -1 14 1 8217 2 298 3 279 2 :Code:main water source 8808 0 -1 6 1 3263 2 1740 3 150 4 1425 5 169 6 869 7 45 8 590 9 96 10 219 11 173 12 63 3 :Get all water needed? 8808 0 -2 5156 -1 19 1 2598 2 618 3 417 4 :Fetch water daily? 8808 0 -2 5158 -1 27 1 3502 2 121 5 :Code:distance to water 8808 0 -2 5169 -1 98 1 1615 2 1211 3 468 4 227 5 20 6a:Person 1 (fetch) 8808 0 -2 88 0.135 4.989 6a:Person 2 (fetch) 8808 0 -2 77 -0.503 3.925 6a:Person 3 (fetch) 8808 0 -2 77 -1.225 3.135 6c:Person 1:no of trips 8808 0 -4 25 -0.178 2.299 6c:Person 2:no of trips 8808 0 -4 25 -0.82 1.822 6c:Person 3:no of trips per 8808 0 -4 25 -1.21 1.38 6d:Person 1:time taken (min) 8808 0 -4 720 15.711 38.71 6d:Person 2:time taken (min) 8808 0 -4 720 8.446 31.854 6d:Person 3:time taken (min) 8808 0 -4 720 2.741 21.586 6e:Person 1:qty carried per 8808 0 -4 525 20.625 39.768 6e:Person 2:qty carried per 8808 0 -4 500 9.081 27.453 6e:Person 3:qty carried 8808 0 -4 225 2.474 16.711 10a:Code:toilet type 8808 0 -1 8 1 4363 2 102 3 2732 4 471 5 30 6 1102 11a:Code:location of toilet 8808 0 -2 1019 -1 111 1 3093 2 4315 3 270 Cluster number 8808 0 1 360 179.754 102.423 Household identification No 8808 0 1001 360017 179777.902 102417.049 1 :Connected to electricity sup 8808 0 -1 20 1 4514 2 4274 2a:Cooking:main source 8808 0 -2 18 -1 5 1 2360 2 1922 3 421 4 3723 5 42 7 242 8 8 11 58 12 9 2a:Cooking:second source 8808 0 -4 1 -2 5063 -1 50 1 607 2 2185 3 296 4 59 5 5 7 442 8 4 11 59 12 37 2b:Lighting:main source 8808 0 -2 17 -1 9 1 45 2 1661 3 4 4 4271 5 85 6 2692 7 16 9 3 11 1 12 4 2b:Lighting:second source 8808 0 -2 5621 -1 44 1 35 2 968 3 8 4 22 5 11 6 2012 7 60 9 4 10 5 12 18 2c:Heating-water:main source 8808 0 -2 36 -1 10 1 2189 2 2127 3 333 4 3802 5 46 7 198 8 3 11 55 12 9 2c:Heating-water:second source 8808 0 -2 6183 -1 72 1 502 2 1345 3 238 4 45 5 7 7 328 8 4 11 48 12 36 2d:Heating-home:main source 8808 0 -4 2 -2 1036 -1 44 1 2202 2 1303 3 528 4 3482 5 40 7 72 8 3 11 67 12 29 2d:Heating-home:second source 8808 0 -4 2 -2 7371 -1 121 1 322 2 513 3 212 4 44 5 4 7 115 8 2 11 63 12 39 3b:Code:Person 1 (collects wood 8808 0 -2 77 -0.785 2.719 3b:Code:Person 2 (collects wood 8808 0 -2 88 -1.255 2.504 3b:Code:Person 3 (collects wood 8808 0 -2 19 -1.673 1.641 3c:Person 1:no of trips 8808 0 -4 19 0.595 1.344 3c:Person 2:no of trips 8808 0 -2 45 0.235 0.962 3c:Person 3:no of trips 8808 0 -4 1 -2 17 0 8424 1 190 2 94 3 40 4 7 5 18 6 7 7 8 10 1 14 1 3d:Person 1:time taken 8808 0 -4 2880 40.146 94.053 3d:Person 2:time taken 8808 0 -2 780 18.59 65.777 3d:Person 3:time taken 8808 0 -2 600 7.06 42.027 Cluster number 8808 0 1 360 179.754 102.423 cluster number 334 0 1 360 179.751 105.531 1 : primary school 334 0 1 236 2 98 2 : number of primary school 334 0 -2 96 -1 4 0 2 1 145 2 39 3 24 4 6 5 5 6 2 7 4 9 1 10 1 11 2 12 1 13 1 14 1 3 : distance of primary school 334 0 -2 55 0.0402 5.574 Household identification No 8809 0 1001 360017 179767.71 102415.701 7a:No of listing unit selected 8809 0 -1 3813 110.179 240.506 7b:Total Household per Unit 8809 0 1 28 1.922 3.218 7c:Sequantial No. per Unit 8809 0 -1 28 1.456 1.894 8 :Replace/original 8809 0 -1 250 1 7528 2 1031 9 :Interviewer 1 code 8745 64 -2 9073 670.203 2183.85 10 :Interviewer 2 code 121 8688 -1 9013 1047.785 2677.248 11 :Date of visit 1 8762 0 01/01/90 1 01/01/93 5 01012001 3 04/13/93 1 05/07/93 1 05/25/93 1 05/26/93 1 05/30/93 1 06/26/93 1 06/29/93 2 07/02/93 1 07/04/93 1 07/10/93 2 07/17/93 1 08/01/93 1 08/02/93 4 08/03/93 7 08/04/93 4 08/05/93 4 08/06/93 28 08/07/93 3 08/08/93 4 08/09/93 2 08/10/93 4 08/11/93 29 08/12/93 36 08/13/93 49 08/14/93 52 08/15/93 27 08/16/93 64 08/17/93 74 08/18/93 56 08/19/93 84 08/20/93 60 08/21/93 45 08/22/93 26 08/23/93 78 08/24/93 79 08/25/93 105 08/26/93 145 08/27/93 100 08/28/93 68 08/29/93 45 08/30/93 77 08/31/93 60 09/01/93 88 09/02/93 93 09/03/93 64 09/04/93 107 09/05/93 52 09/06/93 59 09/07/93 91 09/08/93 78 09/09/92 1 09/09/93 77 09/10/93 79 09/11/93 61 09/12/93 37 09/13/93 75 09/14/93 91 09/15/93 113 09/16/93 126 09/17/93 140 09/18/91 1 09/18/93 105 09/19/93 25 09/20/93 112 09/21/93 184 09/22/93 167 09/23/93 127 09/24/93 89 09/25/93 68 09/26/93 45 09/27/93 120 09/28/93 121 09/29/93 113 09/30/93 95 09222003 1 10/01/93 66 10/02/93 51 10/03/93 22 10/04/93 72 10/05/93 87 10/06/93 132 10/07/93 127 10/08/93 79 10/09/93 105 10/10/93 38 10/11/93 42 10/12/93 131 10/13/93 109 10/14/93 104 10/15/93 130 10/16/93 123 10/17/93 29 10/18/93 108 10/19/93 119 10/20/93 130 10/21/93 145 10/22/93 68 10/23/93 71 10/24/93 16 10/25/93 79 10/26/93 82 10/27/93 89 10/28/93 111 10/29/93 39 10/30/93 47 10/31/93 15 10072000 1 10122000 1 11/01/93 26 11/02/93 101 11/03/93 97 11/04/93 91 11/05/93 54 11/06/93 40 11/07/93 31 11/08/93 55 11/09/93 127 11/10/93 124 11/11/93 92 11/12/93 44 11/13/93 43 11/14/93 18 11/15/93 50 11/16/93 65 11/17/89 1 11/17/93 82 11/18/93 65 11/19/93 82 11/20/93 57 11/21/93 17 11/22/93 29 11/23/93 73 11/24/93 91 11/25/93 76 11/26/93 45 11/27/93 33 11/28/93 15 11/29/93 61 11/30/93 45 12/01/93 25 12/02/93 15 12/03/93 10 12/07/93 9 12/08/93 16 12/09/93 4 12/10/93 6 12/11/93 12 12/13/93 1 12/20/93 18 12/30/93 1 11 :Date of visit 2 281 0 08/04/93 1 08/06/93 1 08/09/93 1 08/11/93 1 08/12/93 1 08/13/93 4 08/14/93 6 08/15/93 5 08/16/93 4 08/17/93 3 08/18/93 4 08/19/93 4 08/20/93 2 08/21/93 3 08/23/93 6 08/24/93 3 08/25/93 5 08/26/93 4 08/27/93 4 08/28/93 14 08/29/93 3 08/30/93 7 08/31/93 6 09/01/93 5 09/02/93 9 09/03/93 6 09/04/93 4 09/05/93 1 09/06/93 3 09/07/93 2 09/08/93 3 09/09/93 4 09/11/93 3 09/13/93 1 09/14/93 4 09/15/93 2 09/16/93 2 09/17/93 5 09/18/93 7 09/19/93 3 09/20/93 7 09/21/93 1 09/22/93 2 09/23/93 1 09/24/93 2 09/25/93 2 09/26/93 1 09/27/93 7 09/28/93 6 09/29/93 2 09/30/93 7 10/01/93 5 10/02/93 2 10/03/93 3 10/04/93 2 10/10/93 2 10/11/93 1 10/12/93 4 10/13/93 1 10/14/93 1 10/15/93 3 10/16/93 6 10/19/93 6 10/20/93 7 10/21/93 2 10/22/93 4 10/23/93 6 10/24/93 2 10/25/93 2 10/26/93 1 10/27/93 2 10/28/93 3 10/29/93 3 10/30/93 2 11/01/93 1 11/02/93 1 11/03/93 3 11/04/93 1 11/07/93 1 11/09/93 5 11/11/93 1 11/13/93 1 11/15/93 1 11/17/93 1 11/24/93 1 12a:Time Visit1 495 8314 1 67 2 63 3 67 4 51 5 40 6 51 7 26 8 40 9 90 Sysmiss 8314 12b:Time Visit 23 8786 1 3 2 1 3 4 4 3 5 1 6 3 7 2 8 2 9 4 Sysmiss 8786 14 :Anthropometrist Code 8762 47 -23 9014 262.658 1487.294 16 :Supervisor code 8752 57 -2 902 51.268 106.633 16 :Verified by supervisor 8809 0 -1 11 1 6889 2 1909 19 :Population Group 8809 0 1 6494 2 690 3 258 4 1367 20 :Gender 8809 0 -1 19 1 2975 2 5815 21 :Language code 8809 0 1 963 2 1360 3 1463 4 1597 5 825 6 949 7 744 8 127 9 395 10 246 11 96 12 44 SS :Date of Capture 8809 0 01/03/94 57 01/04/94 91 01/05/94 128 01/06/94 106 01/07/94 138 01/10/94 194 01/11/94 139 01/12/94 123 01/13/94 135 01/14/94 107 01/17/94 94 01/18/94 79 01/19/94 113 01/20/94 129 01/21/94 80 01/24/94 97 01/25/94 27 09/06/93 21 09/07/93 28 09/08/93 17 09/09/93 41 09/10/93 34 09/13/93 32 09/14/93 17 09/15/93 45 09/16/93 31 09/17/93 31 09/20/93 44 09/21/93 42 09/22/93 89 09/23/93 75 09/24/93 88 09/27/93 78 09/28/93 78 09/29/93 89 09/30/93 43 10/01/93 93 10/04/93 81 10/05/93 41 10/06/93 95 10/07/93 95 10/08/93 66 10/11/93 93 10/12/93 69 10/13/93 52 10/14/93 104 10/15/93 111 10/18/93 120 10/19/93 110 10/20/93 133 10/21/93 86 10/22/93 36 10/25/93 77 10/26/93 111 10/27/93 110 10/28/93 138 10/29/93 112 11/01/93 66 11/03/93 55 11/04/93 125 11/05/93 107 11/08/93 121 11/09/93 138 11/10/93 130 11/11/93 91 11/12/93 4 11/16/93 49 11/17/93 114 11/18/93 81 11/19/93 103 11/22/93 138 11/23/93 137 11/24/93 109 11/25/93 82 11/26/93 85 11/29/93 101 11/30/93 114 12/01/93 143 12/02/93 187 12/03/93 80 12/06/93 115 12/07/93 191 12/08/93 196 12/09/93 197 12/10/93 125 12/13/93 165 12/14/93 153 12/15/93 77 12/16/93 101 12/20/93 56 12/21/93 106 12/22/93 134 12/23/93 112 12/24/93 28 Date year1 8809 0 93 8809 Date month1 8809 0 8 1434 9 2827 10 2588 11 1838 12 122 Date day1 8809 0 1 31 16.537 8.4 Cluster number 8809 0 1 360 179.744 102.421 Household identification No 8796 0 1001 360017 179745.285 102449.457 1 :Code:Type of house 8796 0 -1 7 1 964 2 4721 3 940 4 117 5 409 6 443 7 196 8 984 9 15 2a:Code:1st roof material 8796 0 -1 25 1 45 2 95 3 59 4 4908 5 94 6 2 7 21 8 14 9 25 10 1382 13 10 14 621 15 1447 16 48 2a:Code:2nd roof material 8796 0 -2 7658 -1 25 2 56 3 1 4 17 5 163 6 4 7 12 8 5 9 115 10 22 13 10 14 639 15 63 16 6 2a:Code:3rd roof material 8796 0 -2 8697 -1 25 2 2 5 1 7 1 8 1 9 1 10 5 14 56 15 6 16 1 2b:Code:1st wall material 8796 0 -1 20 1 4165 2 1411 3 51 4 696 5 166 6 5 7 71 8 862 9 267 10 10 13 1026 14 18 15 13 16 15 2b:Code:2nd wall material 8796 0 -2 7542 -1 20 1 2 2 63 3 12 4 24 5 44 6 1 7 31 8 632 9 96 10 17 13 286 14 15 15 1 16 10 2b:Code:3rd wall material 8796 0 -2 8684 -1 21 3 1 5 1 8 13 9 11 10 12 13 45 14 2 16 6 2c:Code:1st floor material 8796 0 -1 32 1 53 2 503 3 44 4 19 5 225 6 27 7 15 8 2904 9 140 10 1580 11 1564 12 507 13 1124 14 20 15 2 16 37 2c:Code:2nd floor material 8796 0 -2 6700 -1 31 1 10 2 18 3 5 5 6 6 1 8 66 9 29 10 213 11 1006 12 408 13 272 14 6 16 25 2c:Code:3rd floor material 8796 0 -2 8586 -1 31 1 1 3 1 10 7 11 57 12 63 13 43 16 7 3 :Total no of rooms 8796 0 -3 30 4.146 2.547 4 :No of rooms used 8796 0 -1 20 3.908 2.345 5 :Ownership 8796 0 -1 15 1 5737 2 3044 6 :Bonded or loan? 8796 0 -2 3044 -1 53 1 1248 2 4451 7 :Amt owed on bond or loan 8796 0 -4 1058000 7637.105 28901.761 8 :Resale value of house 8796 0 -4 1500000 29821.418 74827.831 9a:Pay rent (Y/N)? 8796 0 -2 5737 -1 32 1 1887 2 1140 9b:Monthly rent (actual) 8796 0 -4 3600 37.668 178.493 9c:Monthly rent (mkt) 8796 0 -4 2000 9.386 81.97 Cluster number 8796 0 1 360 179.721 102.455 :Household number 1302 0 6006 360002 258361.412 60799.792 1a:Crop land ownerhip type 1302 0 1 1177 2 125 1b:Crop land ownerhip type 1302 0 -2 125 -1 27 1 818 2 288 3 34 4 10 2a:Graze land ownership type 1302 0 1 932 2 370 2b:Graze land ownership type 1302 0 -2 370 -1 8 1 791 2 112 3 12 4 9 3 :Land use 1302 0 -1 19 1 683 2 75 3 192 4 154 5 111 6 25 7 20 8 23 4 :Use of land for crops 1302 0 -4 8986 16.334 264.503 5a:Crops:land use last year 1302 0 -4 2 -2 128 -1 26 1 41 2 128 3 24 4 619 5 334 5b:Crops:land use in 1993 1302 0 -4 7 -2 128 -1 33 1 32 2 90 3 31 4 733 5 247 6 1 6a:Crops: water source (1) 1302 0 -2 135 -1 54 1 41 2 17 3 31 4 1 5 12 6 998 7 3 8 10 6a:Crops:water source (2) 1302 0 -2 1205 -1 54 2 3 3 4 4 2 5 1 6 32 7 1 6a:Crops:water source (3) 1302 0 -2 1241 -1 54 6 6 8 1 6b:Main source of water 1302 0 -2 134 -1 40 1 26 2 16 3 32 4 2 5 13 6 1024 7 5 8 10 6c:Irrigation for crops 1302 0 -4 1 -2 137 -1 63 1 36 2 29 3 6 4 108 5 922 7 :Crops:rights to sell land 1302 0 -4 1 -2 137 -1 11 1 81 2 1072 8a:Crops:size of saleable land 1297 5 -4 8986 8.995 252.663 8b:Crops:value of saleable land 1302 0 -4 1820000 6448.281 67905.343 9a:Crops:rent land to others 1302 0 -2 133 -1 5 1 18 2 1146 9b:Crops:rent received 1302 0 -4 15000 34.187 573.836 10a:Crops:rent land from others 1302 0 -2 133 -1 8 1 88 2 1073 10b:Crops:rent paid 1302 0 -4 56000 112.419 1780.744 11a:Grazing:water source (2) 1302 0 -2 377 -1 56 1 151 2 56 3 38 4 8 5 1 6 611 8 4 11a:Grazing:water source(1) 1302 0 -2 1170 -1 56 2 12 3 17 4 1 5 1 6 43 8 2 11a:Grazing:water source(3) 1302 0 -2 1228 -1 56 3 1 4 2 6 14 8 1 11b:Grazing: main water source 1302 0 -2 377 -1 71 1 110 2 39 3 48 4 7 5 1 6 642 7 1 8 6 12a:Grazing-rights to sell 1302 0 -2 377 -1 10 1 48 2 867 12b:Grazing:size of saleable la 1302 0 -4 8986 11.693 264.245 12c:Grazing:value of saleable l 1302 0 -4 1000000 3736.29 37389.665 13a:Grazing:rent land to others 1302 0 -2 377 -1 11 1 8 2 906 13b:Grazing:rent received 1302 0 -4 8036 16.63 336.325 14a:Grazing:rent land from othe 1302 0 -2 378 -1 12 1 15 2 897 14b Grazing:rent paid 1299 3 -4 18000 38.824 798.144 Same Household ? 1302 0 0 1302 Cluster number 1302 0 6 360 258.343 60.798 cluster number 334 0 1 360 179.751 105.531 1a: economic activity- one 328 6 0 5 1 99 2 39 3 74 4 3 5 10 6 15 8 6 9 12 10 21 11 3 12 1 13 15 14 2 15 10 16 13 Sysmiss 6 1b: economic activity- two 285 49 0 13 1 12 2 19 3 31 4 5 5 27 6 35 7 7 8 11 9 3 10 36 11 10 12 10 13 53 14 2 15 5 16 6 Sysmiss 49 1c: economic activity- three 241 93 0 16 1 8 2 2 3 23 4 5 5 16 6 33 7 9 8 19 9 5 10 29 11 8 12 7 13 32 14 5 15 19 16 5 Sysmiss 93 1d: economic activity- four 187 147 -1 1 0 28 1 6 3 5 4 4 5 11 6 20 7 3 8 11 9 2 10 25 11 7 12 3 13 15 14 8 15 26 16 12 Sysmiss 147 2 : tarred or dirt roads 333 1 1 94 2 173 3 59 4 5 5 2 Sysmiss 1 3 : impassable roads 331 3 0 1 1 143 2 187 Sysmiss 3 4 : duration of impassable road 128 206 0 12 2.771 2.649 Household identification No 8804 0 1001 360017 179773.479 102409.355 :Person code of respondent 8804 0 -3 18 1.818 1.202 1 :Level of satisfaction 8804 0 -3 1 -1 79 1 666 2 2312 3 815 4 2882 5 2049 3a:Code:1st choice 8804 0 -4 26 5.041 5.972 3a:Rank 1 8804 0 -1 90 1 5063 2 1832 3 1819 3b:Code:2nd choice 8804 0 -4 27 8.82 5.844 3b:Rank 2 8804 0 -1 147 1 1815 2 4805 3 2037 3c:Code:3rd choice 8804 0 -4 27 12.049 6.629 3c:RANK 3 8804 0 -1 251 1 1849 2 2007 3 4697 4 :Safety inside home 8804 0 -4 8 -3 1 -1 14 1 1361 2 2363 3 5057 5 :Safety outside home 8804 0 -4 8 -3 1 -1 16 1 878 2 2185 3 5716 6a:Victim of crime 8804 0 -1 14 1 915 2 7875 6b:(1) Assault 8804 0 -2 7875 -1 20 1 266 2 643 6b:(2) Robbery 8804 0 -2 7875 -1 20 1 582 2 327 6b:(3) Rape 8804 0 -2 7875 -1 20 1 22 2 887 6b:(4) Murder 8804 0 -2 7875 -1 20 1 60 2 849 6b:(5) Abduction 8804 0 -2 7875 -1 20 1 18 2 891 6b:(6) Other 8804 0 -2 7875 -1 33 1 63 2 833 7 :Compared with parents 8804 0 -4 27 -1 21 1 2142 2 2012 3 4602 8 :Effect of new government 8804 0 -4 673 -3 22 -1 29 1 4619 2 1420 3 2041 Cluster number 8804 0 1 360 179.75 102.415 :Cluster Number 358 0 1 360 180.293 104.321 8:Population 358 0 0 596632 33989.52 95618.327 9:Type 358 0 0 186 1 170 3 2 Metro - Urban - Rural 358 0 1 187 2 76 3 95 10:Survey Organisation 358 0 1 41 2 33 3 23 4 57 5 51 6 57 7 71 8 8 9 17 Province 358 0 1 58 2 23 3 90 4 21 5 50 6 7 7 3 8 9 9 26 10 4 11 33 12 21 13 5 14 8 New Province 358 0 1 33 2 7 3 58 4 73 5 25 6 29 7 39 8 32 9 62 New Magesterial Code 358 0 1 4006 654.251 749.983 Total number of People 355 3 3 120 24.814 11.991 Total number of Residents 355 3 3 120 24.814 11.991 Total number of Households 355 3 8 346 123.062 52.335 Total number of Resident Househ 355 3 8 294 112.845 45.447 Average Household Size All 355 3 1 11.842 5.331 1.92 Average Household Size Resident 355 3 1 9.316 4.871 1.553 Household identification No 8809 0 1001 360017 179767.71 102415.701 19 :Population Group 8809 0 1 6494 2 690 3 258 4 1367 21 :Language code 8809 0 1 963 2 1360 3 1463 4 1597 5 825 6 949 7 744 8 127 9 395 10 246 11 96 12 44 9:Type 8809 0 0 4328 1 4398 3 83 Metro - Urban - Rural 8809 0 1 4332 2 1953 3 2524 Province 8809 0 1 1189 2 560 3 2648 4 630 5 959 6 161 7 54 8 205 9 685 10 92 11 767 12 552 13 113 14 194 New Province 8809 0 1 770 2 120 3 1247 4 1519 5 721 6 755 7 1000 8 859 9 1818 Enumeration Weights 8809 0 1 8520 2 289 Enumeration Raised Weights 8809 0 824 1532 964.47 132.861 Census Reaised Weights 8809 0 465 7833 1032.278 250.34 Cluster number 8809 0 1 360 179.744 102.421 31 0 1 5 2 4 3 5 4 3 5 2 6 1 7 1 8 1 9 1 10 1 11 2 12 2 13 2 14 1 31 0 1 14 2 5 3 4 4 6 5 2 Census Population 31 0 0 6647448 1293987.097 1690687.929 Enumeration Number of Household 31 0 0 1898 308.742 421.187 Enumeration Number of raised In 31 0 0 5904753 1232568.387 1628898.679 Number of Actual Households 31 0 1 1652 284.258 380.085 Number of Actual Raised Individ 31 0 3566 5804610 1158428.226 1543955.607 Enumeration Weights 31 0 1 30 2 1 Enumeration Raised Weights 31 0 824 1532 953.871 156.873 Census Weights 31 0 1 25 2 5 9 1 Census Reaised Weights 31 0 465 7833 1269.71 1260.089