Botswana Census-Based Poverty Map Report Republic of Botswana

District Level Results

July 2008

Price P25.00 BOTSWANA CENSUS-BASED POVERTY MAP District Level Results1

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July 2008

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1 This project was funded by the United Nations Development Programme (UNDP). The work was undertaken by Harold Coulombe and Thomas Otter (consultants), with full support from the Central Statistics Office (CSO) staff, in particular Ms. Anna Majelantle (Government statistician), Mr. Moffat Malepa (HIES statistician) and Mr. Daniel Magogwe (assistant statistician). Geographical Information System (GIS) issues were kindly resolved by Mr. Royal Chalashika, CSO Cartography Unit. We would also like to thank Ms. Constance Formson from UNDP who made this project possible. The authors can be reached at [email protected] Preface T Government Statistician A. N.Majelantle Coulombe forconstructingthePovertyMap. Dr.Harold and Otter Mr.Thomas consultants, the to appreciation extends consultancy.further It the funding in assistance for UNDP the thank to like would CSO The with thedistrictandsub-districtpovertyrates. calculate small area estimates of poverty, making use of the PDL estimates, to come to up undertook part second The sets. data two the HIES between linkages and establishing data, Census the of preparation involved part first The parts. two in done was consultancy The (UNDP). Programme Development Nations United the by funded consultancy a through undertaken was Map Poverty Disaggregated the on work The Survey (HIES)publishedintheBotswanaPovertyDatumLine. Expenditure and Income Household 2002/03 the from analysis poverty in-depth and 5 4 3 2 1 Figures /Tables /MapsAnnexes Contents Concluding Remarks Results Data Methodology Introduction use of the detailed information from the 2001 Population and Housing Census Housing and Population 2001 the from information detailed the of use (CSO). The report details poverty rates at district and sub-district levels, making his is the first Disaggregated Poverty Map report by the Central Statistics Office 9 4 2 2 1 ii

i CENSUS-BASED POVERTY MAP REPORT Figures / Tables / Maps / Annexes

FIGURES Figure 1: Poverty Headcount Accuracy, by Disaggregation (administrative) Level 7

TABLES Table 1: Descriptive Statistics on the Botswana Administrative Structure 4 Table 2: Poverty Rates based on HIES (actual) and Census 2001 (predicted), by Strata 6 Table 3: Poverty Indices, by District, Sub-District and Locality 10 Table 4: Comparison of Poverty Indicators between Locality, Sub-District and District 16 Table 5: Poverty Indices, by Sex of Household Head, District, Sub-District and Area 19

MAPS Map 1: District Level Poverty Headcount 13 Map 2: Sub-District-Level Poverty Headcount 14 Map 3: Locality-Level Poverty Headcount 15 Map 4: Gender Gap in Poverty Headcount by Sub-District 18

REFERENCES 22

ANNEXES Annex 1: Methodology 23

Annex 2: Data Predictors & Means Testing 26 Annex 2a: Definition of the Different Predictors 26 Annex 2b: Aligning the Data, Test on Equality of Means 28

Annex 3: Survey-Based Regression Models 33 Strata 1: Gaborone 33 Strata 2: Other Towns & Cities 33 Strata 3: Urban Villages 34 Strata 4: Rural Villages 34 1 Introduction 1.3 1.2 1.1 it should be seen as a natural extension to the poverty profile, and a way to way a and operationalise PovertyProfile results. profile, poverty the to extension natural a as seen be should it results, profile poverty with compatible fully is map poverty of type this Since poverty indicators. consistent fully of errors standard of computation is the permits and figures, profile poverty with expenditure, household on information methods, incorporates other it than as sophisticated more as seen be should and 2003) (2002, Lanjouw and Lanjouw Elbers, by developed been has used methodology The as spatialinequalitiescanbeimportantwithinagiven region. necessarily would level, local the at needed level are indicators Poverty schemes. anti-poverty and efficient effective local cost more permit the therefore and leakages at information minimise information better Having schemes. targeted poorly to lead would which districts, well-off relatively otherwise pockets in poverty of existence the hides often information district-level Using useful and convincing! more be would concentrated are households poorest the villages, and towns even or sub-districts, which in them informing However, known. well and general is information that as useful, or impressive too be not would areas rural the in are people neediest the that Botswana in policy-makers Informing such ascityneighbourhoods,townsorvillages. units, geographic small for information Typically,need schemes. they poverty and policy-makers particular, In planners constraints. need finely disaggregated information of in order to implement number their anti- a has approach the the welfare levels of households in general, and of the poorer ones in particular, of knowledge our improved greatly have studies household-based these While poverty levelsbetweenregions,groups,orovertime. compare and policies, some of effect reducing poverty the assessing in assist also profiles The living. of standard - non-monetary and - monetary of their levels to according population the of characteristics the present profiles these in collected information household surveys, on including detailed Based information poverty.on expenditures monitor and incomes, and assess characterise, In the past decade, poverty profiles poverty decade, past the In these impreciseestimates. too low. The very small was population of – most variation villages was of the the coefficient main the reason cases behind by measured as most – estimates in the of as precision retained, not were but computed, also were indicators level Village presented. are levels locality- and sub-district- district-, at Results information found in the HIES survey and the exhaustive coverage of the Census. Poverty indicators are calculated at low levels of aggregation, using the detailed and Income Household 2002/03 authors utilisedamethodologydevelopedbyElbersetal(2002,2003). the from The data 2001. Census Housing and Population the and (HIES) Survey Expenditure on Botswana based a of Map, results selected Poverty and construction the documents paper This 2

See CSO (2008)forthelatest povertyprofilein Botswana. 2 have been developed into useful tools to tools useful into developed been have

1 CENSUS-BASED POVERTY MAP REPORT 2 Central Statistics Office 2008 3 2 Data Methodology 3.1 2.2 2.1 1.4 3 index andthepovertylinefrom suchpovertyprofileswouldbeused. profile would have to be constructed from the survey. The household-level welfare as a population and housing census. If not already done, a monetary-based poverty utmost requirementisahousehold surveyhavinganexpendituremodule,aswell The data. of terms in demanding very is Map Poverty a such of construction The hr t so te iageain rcs. h mtoooy sd s further is used discussed inAnnex1. methodology The process. disaggregation the stop ustodecide to help where will errors standard ofthese computation The confidence. with used be to imprecise too become would indicators poverty estimated the decreases, and therefore yields less and less precise estimates. At a certain point, and lower levels, the number of households upon which the estimates are based can disaggregate the poverty indicators. As we welfare disaggregate our results at lower of we low how set us tell they each since important, for are errors standard errors These statistics. standard compute to willingness our predictions, does unbiased as ensures issues econometric these account into Taking in thedevelopmentofpredictivemodel. from households within the same cluster are correlated) and heteroskedasticity (expenditure auto-correlation spatial account into take to need the from arise mainly complexities These computations. complex requires implementation proper its simple, conceptually is methodology the behind idea the Although depth, severity,level, inequality)fordifferentgeographicalsubgroups. poverty (e.g. indicators welfare of series a construct to used are expenditures every household predicted finally, these of And Census. levels the in household expenditure the predict to set data Census the to applied are both the survey to and common the are latest which those Census. to Secondly,variables explanatory the of coefficientsset fromthe thatlimits model it data; a Firstly, straightforward. rather regression is model of adult methodology equivalent expenditure is the estimated using HIES behind survey idea basic The along withmoredetailedresults. 1, Annex in found be can methodology the of presentation technical more A 4/ 3/ 2/ 1/ The remainingsectionsofthispaperarestructuredasfollows: under considerationareundertaken. however, that the map should reach its full potential once a series of applications This report documents the construction of the Poverty Map. It should be noted,

h mtoooy a be apid o mra o dvlpn cutis icuig hs i Arc. For Africa. which 15 countries participated. in in those Initiative Map including Poverty Africa Central countries, and West the developing described (2007) Wodon of and Coulombe myriad example, a to applied been has methodology The Further worktobeundertaken. A discussionoftheresults–includinggender-specific data;and A descriptionofthedataused; A presentationofthemethodologyused,inlaymanterms; 3

HIES Survey Census Administrative Layers 3.5 3.4 3.3 3.2 Time-wise, itwasthemostappropriatesurveytouseinpovertymapping. level. household at data expenditure collected having survey national latest the is The third round of the Household Income and Expenditure Survey (HIES, 2002/03) fieldwork. However, theyarealsousefulforplanningpurposes. Census the ease to designed divisions territorial originally were They districts.’ The ten districts can be further divided into 26 sub-districts, often called ‘census than 557000individuals. different these District, with only of 16 547 people to the much larger Central size District, with more the on statistics administrative levels. The districts descriptive vary a lot in some terms of population, from Chobe presents 1 Table yield reliablepovertyestimates.We thereforegroupedtheminto53localities. to small too are villages the of some However, villages. ‘large’ considered are which towns and cities including ‘villages,’ 485 into divided also is Botswana Census fieldwork. the during used districts of a breakdown sub-districts, of definitions unofficial the as well as districts, the of definitions official study,the our use In we level. is composed of ten districts, whilst the villages comprise the lower administrative The administrative structure of Botswana is rather straightforward. The top tier at stratalevel,theloweststatisticallyrobustlevelachievableinHIES. or not the predicted poverty indicators match those found in the Poverty Profile the Poverty Profile and the new Poverty Map. It also permitted us to samehousehold-level test whether the Welfare Index Using and the associated poverty 2008). lines ensured (CSO, full consistency on HIES between based Profile Poverty Government-sponsored the in used one the as same the is terms) real in adult The Welfare Index (WI) used in our regression models (expenditure per equivalent on average. into approximately 4 150 Enumeration Areas (EAs) of about 97 households each, households grouped fieldwork Census The households. 000 into grouped individuals405 approximately million 1.7 covered. to well close out level, are turns database goods Census household The durable the of ownership At and characteristics activities. coversdwelling economic it level, and individual education the demography, At expenditures. and incomes household information on any contain not does but detailed, 2001. relatively August, is questionnaire in Its conducted was Census Housing and Population latest The some ofthatinformationwasavailableincompilingthedata. Botswana, of case the In terms. monetary in defined not or whether living, of and infrastructure, and other aspectsofpublicpolicy, canallleadtoimportantdifferencesinstandards services public markets, to access ethnicity, history, geography, in differences as map, poverty a of construction the in useful also are characteristics level community information, household-level from Apart

3 CENSUS-BASED POVERTY MAP REPORT 4 Central Statistics Office 2008 4 Source: Authors’calculationsbasedontheCensus2001. Table 1:DescriptiveStatisticsontheBotswanaAdministrative Structure Village Locality Sub-District District Unit Territorial Results Stage 1:Aligningthedata Stage 2:Survey-basedregressions Number of Units 485 53 26 10 4.3 4.2 4.1 The resultsarepresentedinAnnex2. errors. standard the of computation the in account into taken was HIES the of that comparison exercise was done at strata level. The two-stage sample design 4 almost all the coefficients are of expected sign. As said earlier, these models are based that confirmed results the of check A model. selection stepwise was backward a on variables independent the of choice ultimate The HIES. on based results Squares) Least (Ordinary regression strata-specific the presents 3 Annex welfare predicted Profile. the Poverty survey-based the that with consistent be would ensured figures variables these to ourselves Restricting (95%) confidenceinterval. variables and tested whether or not they were equal, using a ninety five percent isolate potential variables. We then compared the means of those to questionnaires (dichotomised) both in modalities and questions the compared we instance, Census and the HIES were really measuring the same characteristics. In the first The first task was to make sure that the variables deemed common to both the which arecommontoboththeHIESandCensus. expenditure level household variables explanatory using strata, these of A each for developed been has model Villages. Rural and Villages Urban Cities, & consists of sampling strata in the following categories: Gaborone, Other Towns model at the lowest geographical level for which the HIES is representative. This a created have we estimates, poverty the of accuracy the maximise to order In level village households, 242 only of estimates wouldclearlybeunreliable. median a At sub-districts. 19 of rural the areas and characteristics, urban having villages large seven 27 include cities, These and towns ‘localities.’ the is level disaggregated lower the Finally, Median

10,766 30,136 5,143 collinearity problemsinoureconometric models. multi- serious avoid to 0.97 than larger or 0.03 than less variables dichotomic redefined or deleted also We 242 Number ofHouseholds Minimum 4,600 979 979 1 Maximum 129,102 58,476 58,476 58,476 126,184 Median 20,920 49,037 1,132 Number ofIndividuals Minimum 16,547 2,726 2,726 6 Maximum 188,627 188,627 188,063 557,101 4 As noted, As Stage 3:Welfare Indicators

4.5 4.4 as determinants of welfare or poverty. The relatively lower R lower relatively The poverty. or welfare of determinants as models were purely predictive in the statistical sense and should not be viewed these that note to important is it ‘credible,’ look coefficients these While maps. poverty other from results with compared favourably be can cross-section and survey-based, regressions of typical are they side, low the on be to appear 4/ 3/ 2/ 1/ Villages aremainlyduetofourimportantfactors: ae idctr cno b rjce (t 95%). (at rejected be cannot indicators based For each stratum and poverty indicator, the equality of HIES-based and Census- them withactualfiguresfromthelatestsurvey-based povertyprofiles. (P2). Table 2 presents estimated poverty figures for each stratum, and compares index severity poverty the and (P1) index gap poverty the (P0), ratio headcount shown here – will be used in the last stage of analysis in order to correct for correct to heteroskedasticity.order in analysis not of stage – last the in results used be Those will – variables. here shown dependent as residuals model base regressions the of series using a ran also We variables. the of some of averages cluster variables. At that stage, we attempted to control location effect by the incorporating with concerned only were predictive power we of the Map, regressors without Poverty regards, for the example, for for endogenous used models the In poverty modelsthatcanbeanalysedintermsofcausalrelationships. of determinant not models, prediction exclusively are They discussion. for not ae o te eut fo te rvos tg, e ple te estimated the applied we stage, previous the from parameters results the on Based The R 8 7 6 5 than theones calculatedfrom HIES. the lower for systematically are figures census-based the of mean the of errors model standard the that noting worth is It a estimated we level, both errorterms.See themethodologicalannexforfurther details. welfare household explaining heteroskedasticity in the household component of the error. models We also estimated the parametric distributions of regression from Apart Zhao (2005). written to implement the methodology used here. We used the February 2005 version developed by Qinghua especially software a PovMap, to thanks eased, greatly been has indicators welfare the of computation The Elbers etal(2002,2003). corrected by modelising the error terms. Correcting for these two problems yields unbiased estimates. See also Areas Means some key variables. The heteroskedasticity (error terms are not constant across observations) is Enumeration regressions the in incorporating by minimised is effects) location are there i.e. correlated, surely Least Squares assumptions. Spatial autocorrelation (expenditure from households within the same cluster are As described in the Methodology Section and Annex 1, two statistical problems are likely to violate Ordinary predictive power. of terms in useless correlates potential many makes which correlates, the of quality the in variations wide account into take not do indicators Many their since stage, first the at distributions didnotappeartobeidentical. discarded been had predictors good Many using observable not simply are standard closed-questionnairedatacollectionmethods. correlates potential of number large A low R2. characteristics, even if their consumption habits vary. That necessarily yields observable of terms in homogeneous rather are households areas, many In 2 s of the different regressions vary from 0.44 to 0.57. Although they might 7 to the Census data to compute a series of poverty indicators: the indicators: poverty of series a compute to data Census the to 5 6 8 h cnu-ae headcount census-based The 2 s for the Rural the for s

5 CENSUS-BASED POVERTY MAP REPORT 6 Central Statistics Office 2008 Table 2:PovertyRatesbasedonHIES(actual)andCensus2001 (predicted),byStrata Note: Robuststandarderrorsareinparentheses. Sources: Authors’calculationsbasedonHIES2002/03andCensus2001. Rural Villages Urban Villages Other Towns &Cities Gaborone How lowcanwego? 4.6 4.7 (Actual) Headcount Incidence to be precise enough, it is legitimate to be interrogative for the locality-level the estimates. for interrogative be to legitimate is it enough, precise be to estimates poverty sub-district-level the expect we while example, For smaller. gets units administrative different the in households of number the as declines As discussed in the Methodology section, the precision of the poverty estimates we neededtodeterminewhetherornottheyarepreciseenoughbeuseful. results, actual the presenting Before locality. and sub-district district, in 1: Table described levels disaggregated three first the for figures poverty estimated we models, predictive different the of reliability the established having Once excellent reliabilitytestofthemethodologyusedhere. bythe an provided figures poverty onesprovided these of equality the level, stratum the at survey HIES with becompared only can figures poverty based ratio is at most 1.4 percent points different and often minute. Although census- oet etmts sne h dsrc-ee cre is n r eo te HIES the below or on lies curve district-level the since HIES-based estimates, the to poverty favourably compare estimates incidence headcount level locality- and sub-district- district-, our that show clearly 1 Figure in curves The with thedifferentstratums. step curve. These steps represent the different coefficients of variationthe by associated represented is which benchmark, a as incidence headcount HIES-based the of precision the use ofthe can we survey.Hence, HIES the from computed the ones to variation them compares of and estimates level coefficients locality- and incidence sub-district- district-, headcount the presents 1 Figure Profile. Poverty HIES-based the from estimates headcount the for as well as locality), and sub-district (district, levels three all for variation of coefficients computed we estimates, our of precision the on judgment ‘objective’ an make to order In 0.453 0.247 0.135 0.063 (0.032) (0.016) (0.018) (0.008) HIES (P 0 ) (Predicted) Census 0.455 0.258 0.149 0.076 (0.020) (0.012) (0.010) (0.008) (Actual) 0.183 0.043 0.018 Poverty GapIndex (0.018) (0.007) (0.006) (0.003) HIES 0.085 (P 1 ) (Predicted) Census 0.197 0.096 0.051 0.023 (0.013) (0.006) (0.005) (0.003) Poverty SeverityIndex (Actual) 0.097 0.040 0.019 0.009 (0.012) (0.004) (0.003) (0.002) HIES (P 2 ) (Predicted) Census 0.112 0.050 0.025 0.010 (0.009) (0.004) (0.003) (0.002) Sources: Authors’computationsonHIES 2002/03andCensus2001. Figure 1:PovertyHeadcountAccuracy, byDisaggregation(administrative)Level Ratio (s.e./point estimate) .05 .10 .15 .20 .25 .30 0 Strata (HIES) 4.8 vial i Btwn. s ih b epce, ua pvry s uh more be takenintoaccountinpovertyalleviatingpoliciesandprogrammes. much is poverty rural expected, prevalent than urban poverty, be and therefore the area of residence should clearly might As Botswana. in available reliable. quite figures poverty predicted These disaggregated estimates are the first the ever monetary-based poverty figures make which small, relatively – sub-districts 26 and 53 localities. The standard errors are also presented and are – in most districts, cases ten the of each for figures poverty presents 3 Table clearly misleading touse,sincemostarenotpreciseenough. be would here) shown (not estimates Village-level policy-makers. clear for is it guides good valid, be would as levels disaggregated benchmark three all HIES at estimates the poverty that takes one If go? we can low How of coefficient higher significantly variation. a has sub-district/locality North-East the why clear not is it However,Town). Sowa and (Orapa poverty of levels very low with sub-districts/localities two are exceptions three the Amongst one. Proportion ofHouseholds(rankedbys.e./pointestimate) .2 Sub-District (Census) .4 .6 Locality (Census) .8 1

7 CENSUS-BASED POVERTY MAP REPORT 8 Central Statistics Office 2008 How lowshouldwego? Gender 4.11 4.10 4.9 compared toonly twentysevenpercent (27%) ofmale-headedhouseholds. line, poverty the below lie (34%) their percent four than thirty since poorer counterparts, male also are they average, On worldwide. households headed forty six percent (46%), Botswana has one of the highest poverty percentages of female- than more At compute size. enough large a to having group population any for possible indicators is it outcomes, geographically-based towards geared mainly is maps poverty construct to used methodology the Although the as districts or appropriate levelstotargetpoverty. sub-districts of instead localities using by added shows value clearly the This indicators. poverty our as severity or depth poverty take we if similar very are figures The districts. own their than cases) (25 richer or cases) (16 poorer either are localities 53 of out 41 poverty, headcount at look we poverty.If of level national the to compared when or districts, or districts sub- own their than an richer or poorer statistically are is localities which us tells 4 levels poverty about locality,Tableto information sub-district to district from disaggregate we additional when advantage not or whether test To statistically not are localities different different fromeachotherintermsofmonetarypoverty. the that possible be might it district, figures do not yield much more information. Within a rather homogenous sub- locality poverty figures with some confidence, itand sub-district maydistrict, bethe thatuse can thesewe disaggregated that demonstrated have we Although quite are poor. localities rural neigbouring their poverty, of rates lowest the enjoy circles) have much lower poverty rates. While the capital and the mining towns more that fifty percent (50%). On the contrary, urban localities (represented by have localities rural four (40%); percent forty above figures headcount poverty Patterns from the locality-level map (Map 3) show that almost all rural areas have hencea pattern, poverty better targetingindicator. afiner provides figures how poverty striking the is it dissagregating maps, three all Comparing tables. the from see to difficult of aseries respectively. levels on locality- Using maps instead of and tables figures permits the user to establish geographical patterns sub-district- headcount district-, poverty at 3 maps Table geographical reproduce 3 to 1 Maps remain similar. patterns poverty the poverty, of measures as depth (P2) the severity take the we or (P1) If Map. Poverty the of localities usefulness the and for sub-districts argues strongly across headcounts poverty of heterogeneity The rural in found ones the areas. to closer (40%) percent forty approximately of rate headcount Sub- poverty urban Southern an have West) in Kweneng in Moshupa Letlhakeng and (notably District localities other some poverty, of level low very a enjoyed towns mining main the and Gaborone Whilst poor. being than in urban areas. However, having residence in urban areas does not exclude areas rural in higher much is rate poverty headcount the sub-district, each For 5 Concluding Remarks 5.3 5.2 5.1 etc. And finally, it can serve as a useful tool in the study of the relationships the of between povertydistributionandvarioussocio-economic outcomes. study the in tool useful a as serve can it finally, And etc. schemes (i.e. social funds, town/village development schemes), impact analysis, anti-poverty targeted locally of evaluation the include could uses Other tools. the merging targeting powerful yield particular,would maps health and education In with Map Poverty indicators. infrastructure or health education, on based alleviation poverty of measures alternative with conjunction in used be could taking indicators target monetary-based currently such Obviously,country. the processes in place decentralisation and administrative government the of support in tool important an become could Map Poverty Botswana The Government thecentral subdivisions, towards thedistricts,anddistrictstheirsub-districtslocalities. their towards offices administrative different the by applied be to regulations allocation budget design to used be potential full their can results the others, Amongst used. are they which acquire in ways the to according should they are, results the interesting However be used withconfidence. to unreliable too were level village at computations the villages, different the of size population small planners, rather the to to Due useful researchers. and policy-makers be to enough precise are levels locality- and sub-district- district-, at figures benchmark, a as Profile Poverty latest the of level precision to have an idea of the reliability therefore of these estimates. We observed and that by using the estimates poverty to different ability the for the errors is standard here compute used methodology the of advantages main the of One latest Botswana the Poverty Profile. with compatible fully are figures poverty disaggregated finely The presented. also is breakdown gender ever A first estimates. the poverty obtain reliable to researchers/authors the by used been has (2003) al et and sub-district- district-, a locality-level Poverty Map of for Botswana. The construction methodology developed the by Elbers documented has paper This in ruralareas. than areas urban in larger be to tends gap gender the sub-districts, and districts all for case the not illustrates is this if 4 Even level. sub-district Map at figures gap District. gender these Chobe in (10%) percent ten than more and to Town Orapa) (Sowa nonexistent from goes gap gender the level, sub-district at that shows table The head. household the of gender the by down broken also but sub-district, and district by indicators poverty usual the presents 5 Table

9 CENSUS-BASED POVERTY MAP REPORT 10 Central Statistics Office 2008 Table 3:PovertyIndices,byDistrict,Sub-DistrictandLocality SOUTHERN

SOUTH-EAST KWENENG Disaggregated Levels

Kweneng East South East Lobatse Gaborone Ngwaketse West Borolong Southern Jwaneng Kweneng West Tlokweng Ramotswa Rural Lobatse Gaborone Rural Rural Moshupa Kanye Rural Jwaneng Letlhakeng Rural Thamaga Mogoditshane Kopong Gabane Molepolole Rural Population 185,540 227,986 270,305 188,063 181,627 113,186 39,923 181,627 59,877 28,801 10,471 47,324 14,559 33,941 18,096 32,829 10,399 53,727 67,441 20,920 20,286 18,671 28,801 10,471 47,324 16,922 40,138 56,126 14,559 5,982 5,571 Headcount Poverty 0.407 0.332 0.111 0.175 0.191 0.481 0.434 0.088 0.300 0.076 0.430 0.485 (0.037) (0.037) (0.025) (0.025) (0.037) (0.030) (0.023) (0.027) (0.010) (0.010) (0.024) (0.035) (0.024) (0.026) (0.023) (0.011) (0.029) (0.022) (0.017) (0.022) (0.017) (0.017) (0.010) (0.021) (0.022) (0.016) (0.014) (0.014) (0.008) (0.008) (0.011) 0.093 0.199 0.242 0.191 0.076 0.481 0.434 0.432 0.369 0.473 0.088 0.419 0.496 0.281 0.117 0.336 0.203 0.287 0.416 (P0) Gap Index Poverty 0.037 0.211 0.184 0.187 0.031 0.176 0.211 0.117 0.134 0.063 0.070 0.023 (0.024) (0.024) (0.015) (0.015) (0.023) (0.018) (0.015) (0.017) (0.004) (0.004) (0.015) (0.021) (0.017) (0.017) (0.011) (0.004) (0.015) (0.010) (0.009) (0.014) (0.009) (0.010) (0.004) (0.008) (0.012) (0.008) (0.007) (0.007) (0.003) (0.003) (0.005) 0.211 0.184 0.191 0.161 0.205 0.031 0.164 0.219 0.099 0.039 0.121 0.069 0.104 0.178 0.031 0.065 0.097 0.070 0.023 (P1)

Severity Index Poverty 0.018 0.120 0.103 0.107 0.016 0.100 0.120 0.063 0.073 0.032 0.036 0.010 (0.017) (0.017) (0.011) (0.011) (0.016) (0.013) (0.010) (0.012) (0.003) (0.003) (0.010) (0.014) (0.012) (0.012) (0.006) (0.002) (0.009) (0.006) (0.006) (0.010) (0.006) (0.007) (0.002) (0.005) (0.005) (0.005) (0.004) (0.004) (0.002) (0.002) (0.003) 0.120 0.103 0.111 0.093 0.116 0.016 0.086 0.126 0.048 0.019 0.061 0.033 0.053 0.100 0.015 0.031 0.053 0.036 0.010 (P2) Individuals Number 19,363 56,419 75,691 of Poor 30,004 20,539 48,670 75,515 10,478 13,804 16,835 15,420 28,055 20,539 14,811 26,548 13,804 5,037 1,281 5,501 5,037 7,310 1,281 2,506 5,085 3,841 1,872 2,111 1,946 4,037 4,518 5,501 Table 3:PovertyIndices,byDistrict,Sub-DistrictandLocality (continued...) KGATLENG CENTRAL

Disaggregated Levels Selebi-Phikwe Kgatleng Central Tutume Central Boteti Central Bobonong Central Mahalapye Central Serowe Sowa Town Orapa Tutume Maitengwe Rural Letlhakane Rural Mmadinare Bobonong Rural Shoshong Mahalapye Rural Lerala Palapye Serowe Rural Sowa Town Orapa Selebi-Phikwe Mochudi Rural Population 557,101 122,696 108,324 151,884 73,199 48,825 73,199 47,738 66,602 13,671 88,200 14,881 32,857 10,857 14,529 41,216 38,414 62,439 26,085 41,811 78,241 48,825 36,674 36,525 2,726 8,306 5,221 7,471 5,747 2,726 8,306 Headcount Poverty 0.272 0.370 0.419 0.389 0.373 0.034 0.018 0.157 0.272 0.425 0.414 (0.010) (0.010) (0.005) (0.005) (0.012) (0.012) (0.018) (0.017) (0.020) (0.019) (0.019) (0.026) (0.038) (0.023) (0.022) (0.017) (0.026) (0.023) (0.025) (0.020) (0.025) (0.023) (0.032) (0.015) (0.026) (0.021) (0.034) (0.015) (0.013) (0.024) (0.018) 0.345 0.453 0.454 0.255 0.501 0.309 0.308 0.479 0.356 0.241 0.483 0.397 0.212 0.258 0.487 0.034 0.018 0.157 0.211 0.334 (P0) Gap Index Poverty 0.154 0.010 0.005 0.052 0.152 0.105 0.105 0.173 0.182 0.172 0.160 (0.003) (0.003) (0.002) (0.002) (0.005) (0.005) (0.011) (0.007) (0.012) (0.010) (0.010) (0.014) (0.023) (0.015) (0.014) (0.009) (0.018) (0.015) (0.012) (0.011) (0.016) (0.014) (0.016) (0.007) (0.017) (0.013) (0.018) (0.008) (0.007) (0.016) (0.012) 0.010 0.005 0.052 0.072 0.137 0.127 0.173 0.193 0.095 0.221 0.114 0.115 0.207 0.130 0.085 0.210 0.149 0.076 0.094 0.213 (P1) Severity Index Poverty 0.085 0.004 0.002 0.025 0.083 0.055 0.055 0.095 0.102 0.094 0.088 (0.002) (0.002) (0.001) (0.001) (0.003) (0.003) (0.008) (0.004) (0.008) (0.006) (0.006) (0.009) (0.015) (0.010) (0.009) (0.006) (0.013) (0.011) (0.008) (0.007) (0.012) (0.010) (0.010) (0.004) (0.012) (0.009) (0.012) (0.005) (0.005) (0.012) (0.008) 0.004 0.002 0.025 0.035 0.076 0.064 0.089 0.108 0.049 0.126 0.058 0.059 0.117 0.065 0.042 0.119 0.076 0.038 0.047 0.121 (P2) Individuals Number 206,127 56,653 19,910 19,910 51,410 20,289 42,138 of Poor 12,199 40,043 16,461 19,742 27,573 30,158 10,787 38,103 7,666 7,666 7,738 4,716 2,365 3,795 3,355 4,475 2,660 9,258 2,282 5,530 150 150 93 93 11 CENSUS-BASED POVERTY MAP REPORT 12 Central Statistics Office 2008 Note 3:Because ofthenature ofDeltaandCKGR sub-districts,they wereaggregated withNgamiland West and Ghanzirespectively. their respectivesub-districts. below shown are localities the and bold in listed are sub-districts associated The case. upper and bold in shown are districts The 2: Note Note 1:Robuststandard errorsareinparentheses. Sources: Authors’calculationsbasedon theHIES2002/03andCensus2001. Table 3:PovertyIndices,byDistrict,Sub-DistrictandLocality (continued...) NGAMILAND NORTH-EAST KGALAGADI GHANZI CHOBE

(Central Tutume continued) Disaggregated Levels Kgalagadi North Kgalagadi South Ghanzi Ngamiland East Chobe North East Francistown Tonota Ghanzi Rural Gumare Rural Ngamiland West Maun Rural Kasane Rural Rural Francistown Rural Tsabong Rural Population 122,115 130,252 41,684 32,704 16,547 16,067 25,617 32,704 50,746 71,369 16,547 49,249 81,003 15,604 23,176 44,729 43,392 27,977 49,249 81,003 16,067 19,348 9,528 6,017 7,352 9,195 6,269 Headcount Poverty 0.419 0.214 0.459 0.416 0.277 0.383 0.506 0.416 0.533 0.339 0.277 0.304 0.159 (0.027) (0.022) (0.036) (0.030) (0.030) (0.073) (0.073) (0.012) (0.012) (0.035) (0.021) (0.026) (0.026) (0.022) (0.097) (0.079) (0.051) (0.021) (0.031) (0.027) (0.027) (0.036) (0.031) (0.031) (0.031) (0.030) (0.031) 0.276 0.247 0.486 0.418 0.549 0.214 0.532 0.139 0.387 0.304 0.159 0.383 0.224 0.598 (P0) Gap Index Poverty 0.181 0.112 0.112 0.118 0.054 0.078 0.163 0.243 0.212 0.181 0.181 0.239 0.139 (0.016) (0.009) (0.020) (0.015) (0.015) (0.037) (0.037) (0.005) (0.005) (0.017) (0.010) (0.016) (0.016) (0.011) (0.072) (0.057) (0.036) (0.010) (0.021) (0.017) (0.017) (0.021) (0.021) (0.021) (0.014) (0.021) (0.016) 0.046 0.164 0.118 0.054 0.099 0.163 0.082 0.296 0.097 0.215 0.168 0.248 0.074 0.240 (P1) Severity Index Poverty 0.102 0.061 0.061 0.063 0.026 0.040 0.091 0.148 0.126 0.102 0.102 0.137 0.077 (0.011) (0.005) (0.013) (0.009) (0.009) (0.022) (0.022) (0.003) (0.003) (0.010) (0.006) (0.011) (0.011) (0.007) (0.054) (0.042) (0.027) (0.007) (0.015) (0.012) (0.012) (0.014) (0.016) (0.015) (0.008) (0.015) (0.010) 0.022 0.091 0.063 0.026 0.049 0.091 0.041 0.182 0.051 0.123 0.090 0.144 0.036 0.139 (P2) Individuals Number 51,166 14,972 12,879 27,874 12,962 19,133 13,605 13,605 27,048 24,194 of Poor 14,972 12,879 11,570 11,264 24,556 14,884 4,584 4,584 6,154 1,022 3,558 4,307 6,154 1,404 2,353 2,515 9,286 Map 1:DistrictLevelPovertyHeadcount Sources: Authors’calculationsbasedon theHIES2002/03andCensus2001. 13 CENSUS-BASED POVERTY MAP REPORT 14 Central Statistics Office 2008 Map 2:Sub-District-LevelPovertyHeadcount Sources: Authors’calculationsbasedon theHIES2002/03andCensus2001. Map 3:Locality-LevelPovertyHeadcount Sources: Authors’calculationsbasedon theHIES2002/03andCensus2001. 15 CENSUS-BASED POVERTY MAP REPORT 16 Central Statistics Office 2008 Table 4:ComparisonofPovertyIndicatorsbetweenLocality, Sub-DistrictandDistrict Poverty Headcount (P0) Poverty Gap Index (P1) Locality compared to ... Locality compared to ... District Sub-District Locality National District Sub-District National District Sub-District Southern Jwaneng Jwaneng Richer Richer Richer Richer Richer Richer Southern Ngwaketse Rural Poorer Poorer Poorer Southern Ngwaketse Kanye Poorer Richer Poorer Richer Southern Ngwaketse Moshupa Poorer Poorer Poorer Poorer Southern Borolong Rural Poorer Poorer Poorer Poorer Southern Ngwaketse West Rural Poorer Poorer Poorer Poorer Poorer South-East Gaborone Gaborone Richer Richer Richer Richer Richer Richer South-East Lobatse Lobatse Richer Poorer Richer Poorer South-East South East Rural Richer Poorer Poorer Poorer Poorer South-East South East Ramotswa Richer Poorer Poorer Richer Poorer Poorer South-East South East Tlokweng Richer Richer Richer Richer Kweneng Kweneng East Rural Poorer Poorer Richer Poorer Poorer Richer Kweneng Kweneng East Molepolole Richer Richer Richer Richer Kweneng Kweneng East Gabane Richer Richer Richer Richer Richer Richer Kweneng Kweneng East Kopong Kweneng Kweneng East Mogoditshane Richer Richer Richer Richer Richer Richer Kweneng Kweneng East Thamaga Richer Richer Richer Richer Kweneng Kweneng West Rural Poorer Poorer Poorer Poorer Kweneng Kweneng West Letlhakeng Poorer Poorer Poorer Richer Kgatleng Kgatleng Rural Poorer Poorer Poorer Poorer Kgatleng Kgatleng Mochudi Richer Richer Richer Richer Richer Richer Central Selebi-Phikwe Selebi-Phikwe Richer Richer Richer Richer Richer Richer Central Orapa Orapa Richer Richer Richer Richer Richer Richer Central Sowa Town Sowa Richer Richer Richer Richer Central Central Serowe/Palapye Rural Poorer Poorer Poorer Poorer Poorer Poorer Central Central Serowe/Palapye Serowe Richer Richer Richer Richer Richer Richer Central Central Serowe/Palapye Palapye Richer Richer Richer Richer Richer Richer Central Central Serowe/Palapye Lerala Poorer Poorer Poorer Table 4:ComparisonofPovertyIndicatorsbetweenLocality, Sub-DistrictandDistrict(Continued...) Poverty Headcount (P0) Poverty Gap Index (P1) Locality compared to ... Locality compared to ... District Sub-District Locality National District Sub-District National District Sub-District Central Central Mahalapye Rural Poorer Poorer Poorer Poorer Poorer Poorer Central Central Mahalapye Mahalapye Richer Richer Richer Richer Richer Richer Central Central Mahalapye Shoshong Richer Central Central Bobonong Rural Poorer Poorer Poorer Poorer Poorer Poorer Central Central Bobonong Bobonong Richer Richer Richer Richer Central Central Bobonong Mmadinare Richer Richer Richer Richer Central Central Boteti Rural Poorer Poorer Poorer Poorer Poorer Poorer Central Central Boteti Letlhakane Richer Richer Richer Richer Richer Richer Central Central Tutume Rural Poorer Poorer Poorer Poorer Poorer Poorer Central Central Tutume Maitengwe Poorer Poorer Poorer Central Central Tutume Tutume Richer Richer Central Central Tutume Tonota Richer Richer Richer Richer North-East Francistown Francistown Richer Richer Richer Richer North-East North East Rural Chobe Chobe Rural Poorer Poorer Poorer Poorer Poorer Poorer Chobe Chobe Kasane Richer Richer Richer Richer Richer Richer Ngamiland Ngamiland East Rural Poorer Poorer Poorer Poorer Poorer Poorer Ngamiland Ngamiland East Maun Richer Richer Richer Richer Richer Richer Ngamiland Ngamiland West Rural Poorer Poorer Poorer Poorer Poorer Poorer Ngamiland Ngamiland West Gumare Poorer Richer Poorer Richer Ghanzi Ghanzi Rural Poorer Poorer Poorer Poorer Ghanzi Ghanzi Ghanzi Richer Richer Richer Richer Richer Kgalagadi Kgalagadi South Rural Poorer Poorer Kgalagadi Kgalagadi South Tsabong Richer Richer Richer Richer Richer Richer Kgalagadi Kgalagadi North Rural Poorer Richer Poorer Richer

Sources: Authors’ calculations based on the HIES 2002/03 and Census 2001. Note: A Locality is deemed poorer (richer) than its own Sub-District/District if its poverty indicator is more (less) than two standard errors than its Sub-District/District poverty indicator. A blank cell signifying the hypothesis that the poverty indicators are equal cannot be rejected. The same logic applies to the comparison between Locality and national poverty. 17 CENSUS-BASED POVERTY MAP REPORT 18 Central Statistics Office 2008 Map 4:GenderGapinPovertyHeadcountbySub-District Sources: Authors’calculationsbasedon theHIES2002/03andCensus2001. Table 5:PovertyIndices,bySexofHouseholdHead,District,Sub-DistrictandArea District/ Sex of Urban Rural Total Sub-District Head Pop. P0 P1 P2 Pop. P0 P1 P2 Pop. P0 P1 P2 Southern Male 35,029 0.270 0.116 0.066 57,415 0.421 0.178 0.100 92,444 0.364 0.155 0.087 Female 36,617 0.379 0.167 0.097 56,479 0.495 0.217 0.123 93,096 0.450 0.197 0.113 Jwaneng Male 9,892 0.079 0.029 0.015 ...... 9,892 0.079 0.029 0.015 Female 4,667 0.107 0.035 0.017 ...... 4,667 0.107 0.035 0.017 Ngwaketse Male 25,137 0.346 0.150 0.086 29,455 0.442 0.190 0.107 54,592 0.398 0.171 0.097 Female 31,950 0.419 0.186 0.108 26,644 0.506 0.222 0.127 58,594 0.459 0.202 0.117 Borolong Male ...... 23,109 0.391 0.161 0.089 23,109 0.391 0.161 0.089 Female ...... 24,215 0.477 0.207 0.117 24,215 0.477 0.207 0.117 Ngwaketse West Male ...... 4,851 0.442 0.192 0.109 4,851 0.442 0.192 0.109 Female ...... 5,620 0.520 0.233 0.134 5,620 0.520 0.233 0.134 South-East Male 147,945 0.077 0.025 0.011 10,434 0.214 0.085 0.046 158,379 0.086 0.028 0.014 Female 103,911 0.135 0.043 0.020 8,015 0.287 0.116 0.063 111,926 0.146 0.049 0.023 Gaborone Male 111,294 0.057 0.016 0.007 ...... 111,294 0.057 0.016 0.007 Female 70,333 0.107 0.033 0.014 ...... 70,333 0.107 0.033 0.014 Lobatse Male 15,714 0.167 0.064 0.034 ...... 15,714 0.167 0.064 0.034 Female 13,087 0.220 0.077 0.038 ...... 13,087 0.220 0.077 0.038 South East Male 20,937 0.116 0.038 0.018 10,434 0.214 0.085 0.046 31,371 0.149 0.054 0.027 Female 20,491 0.176 0.059 0.028 8,015 0.287 0.116 0.063 28,506 0.207 0.075 0.038 Kweneng Male 63,394 0.194 0.068 0.034 53,634 0.426 0.184 0.104 117,028 0.300 0.121 0.066 Female 67,185 0.280 0.101 0.051 43,773 0.499 0.219 0.124 110,958 0.367 0.148 0.080 Kweneng East Male 61,310 0.189 0.066 0.033 35,220 0.408 0.174 0.098 96,530 0.269 0.106 0.056 Female 63,229 0.269 0.096 0.048 28,304 0.473 0.205 0.116 91,533 0.332 0.130 0.069 Kweneng West Male 2,084 0.344 0.131 0.067 18,414 0.460 0.203 0.116 20,498 0.448 0.195 0.111 Female 3,956 0.458 0.182 0.096 15,469 0.546 0.244 0.141 19,425 0.528 0.231 0.131 Kgatleng Male 16,823 0.183 0.062 0.030 19,224 0.297 0.120 0.065 36,047 0.244 0.093 0.049 Female 19,888 0.234 0.081 0.040 17,264 0.380 0.159 0.088 37,152 0.302 0.117 0.062 Kgatleng Male 16,823 0.183 0.062 0.030 19,224 0.297 0.120 0.065 36,047 0.244 0.093 0.049 Female 19,888 0.234 0.081 0.040 17,264 0.380 0.159 0.088 37,152 0.302 0.117 0.062 Central Male 115,735 0.186 0.066 0.033 143,588 0.440 0.188 0.106 259,323 0.327 0.134 0.073 Female 139,616 0.287 0.104 0.052 158,162 0.511 0.224 0.128 297,778 0.406 0.168 0.092 19 CENSUS-BASED POVERTY MAP REPORT 20 Central Statistics Office 2008 Table 5:PovertyIndices,bySexofHouseholdHead,District,Sub-DistrictandArea(continued...) District/ Sex of Urban Rural Total Sub-District Head Pop. P0 P1 P2 Pop. P0 P1 P2 Pop. P0 P1 P2 Selebi-Phikwe Male 28,881 0.141 0.049 0.024 ...... 28,881 0.141 0.049 0.024 Female 19,944 0.179 0.057 0.026 ...... 19,944 0.179 0.057 0.026 Orapa Male 5,889 0.017 0.005 0.002 ...... 5,889 0.017 0.005 0.002 Female 2,417 0.018 0.005 0.002 ...... 2,417 0.018 0.005 0.002 Sowa Town Male 1,905 0.035 0.010 0.005 ...... 1,905 0.035 0.010 0.005 Female 821 0.030 0.008 0.003 ...... 821 0.030 0.008 0.003 Central Male 29,065 0.192 0.068 0.034 37,441 0.451 0.194 0.110 66,506 0.338 0.139 0.076 Serowe/Palapye Female 44,778 0.290 0.107 0.054 40,600 0.523 0.232 0.133 85,378 0.401 0.166 0.092 Central Male 18,146 0.201 0.071 0.035 29,572 0.440 0.188 0.105 47,718 0.349 0.143 0.078 Mahalapye Female 27,742 0.297 0.107 0.054 32,864 0.520 0.229 0.131 60,606 0.418 0.174 0.096 Central Bobonong Male 9,816 0.252 0.090 0.045 18,667 0.429 0.182 0.102 28,483 0.368 0.150 0.082 Female 15,570 0.342 0.128 0.065 22,549 0.521 0.230 0.131 38,119 0.448 0.188 0.104 Central Boteti Male 7,810 0.189 0.070 0.036 17,119 0.478 0.210 0.120 24,929 0.387 0.166 0.094 Female 7,200 0.325 0.122 0.063 15,609 0.522 0.232 0.133 22,809 0.460 0.197 0.111 Central Tutume Male 14,223 0.290 0.106 0.053 40,789 0.418 0.176 0.098 55,012 0.385 0.158 0.087 Female 21,144 0.358 0.132 0.066 46,540 0.486 0.210 0.118 67,684 0.446 0.185 0.102 North-East Male 44,848 0.145 0.051 0.026 21,096 0.264 0.101 0.053 65,944 0.183 0.067 0.034 Female 36,155 0.176 0.056 0.026 28,153 0.334 0.131 0.070 64,308 0.245 0.089 0.046 Francistown Male 44,848 0.145 0.051 0.026 ...... 44,848 0.145 0.051 0.026 Female 36,155 0.176 0.056 0.026 ...... 36,155 0.176 0.056 0.026 North East Male ...... 21,096 0.264 0.101 0.053 21,096 0.264 0.101 0.053 Female ...... 28,153 0.334 0.131 0.070 28,153 0.334 0.131 0.070 Chobe Male 3,745 0.096 0.032 0.015 4,266 0.328 0.135 0.074 8,011 0.220 0.087 0.047 Female 3,676 0.178 0.061 0.029 4,860 0.452 0.195 0.110 8,536 0.334 0.137 0.075 Chobe Male 3,745 0.096 0.032 0.015 4,266 0.328 0.135 0.074 8,011 0.220 0.087 0.047 Female 3,676 0.178 0.061 0.029 4,860 0.452 0.195 0.110 8,536 0.334 0.137 0.075 Ngamiland Male 21,720 0.168 0.059 0.029 32,479 0.519 0.234 0.136 54,199 0.378 0.164 0.093 Female 29,354 0.300 0.111 0.056 38,562 0.572 0.261 0.152 67,916 0.455 0.196 0.111 Table 5:PovertyIndices,bySexofHouseholdHead,District,Sub-DistrictandArea(continued...) District/ Sex of Urban Rural Total Sub-District Head Pop. P0 P1 P2 Pop. P0 P1 P2 Pop. P0 P1 P2 Ngamiland East Male 18,501 0.140 0.046 0.022 13,991 0.498 0.222 0.128 32,492 0.294 0.122 0.068 Female 24,999 0.268 0.096 0.047 13,878 0.576 0.264 0.154 38,877 0.378 0.156 0.085 Ngamiland West Male 3,219 0.332 0.131 0.069 18,488 0.534 0.243 0.141 21,707 0.504 0.226 0.131 Female 4,355 0.482 0.198 0.106 24,684 0.570 0.259 0.151 29,039 0.557 0.250 0.144 Ghanzi Male 5,319 0.238 0.098 0.053 14,105 0.471 0.208 0.119 19,424 0.407 0.178 0.101 Female 5,067 0.316 0.125 0.066 8,213 0.508 0.226 0.130 13,280 0.435 0.188 0.106 Ghanzi Male 5,319 0.238 0.098 0.053 14,105 0.471 0.208 0.119 19,424 0.407 0.178 0.101 Female 5,067 0.316 0.125 0.066 8,213 0.508 0.226 0.130 13,280 0.435 0.188 0.106 Kgalagadi Male 3,157 0.163 0.058 0.029 19,434 0.463 0.213 0.126 22,591 0.421 0.191 0.112 Female 3,133 0.287 0.108 0.055 15,960 0.543 0.260 0.157 19,093 0.501 0.235 0.141 Kgalagadi South Male 3,157 0.163 0.058 0.029 10,870 0.552 0.266 0.161 14,027 0.465 0.219 0.131 Female 3,133 0.287 0.108 0.055 8,457 0.650 0.330 0.206 11,590 0.552 0.270 0.165 Kgalagadi North Male ...... 8,564 0.350 0.145 0.081 8,564 0.350 0.145 0.081 Female ...... 7,503 0.422 0.182 0.103 7,503 0.422 0.182 0.103

Sources: Authors’ calculations based on the HIES 2002/03 and Census 2001. Note 1: Robust standard errors associated with these figures are available on request. Note 2: The districts are shown in bold. The associated sub-districts are listed below each district. Note 3: Because of the nature of Delta and CKGR sub-districts, they were aggregated with Ngamiland West and Ghanzi respectively. Note 4: Population (Pop.) refers to the number of individuals having either a Male or a Female Household Head. 21 CENSUS-BASED POVERTY MAP REPORT 22 Central Statistics Office 2008 References Ue Mna fr oMp mmo Dvlpet eerh ru. 2005. Group. Research Development mimeo, PovMap, for Manual User Q. Zhao, Putting J. Razafindravonona. and Razafimanantena T. Ozler, B. J., Mistiaen, 2008. (CSO), Office Statistics Central Elbers, C., J. O. Lanjouw, and P. Lanjouw. “Micro-Level Estimation of Poverty and Towns:P.Villagesand Lanjouw,Micro and in Welfare O. Lanjouw. J. C., Elbers, Data Survey Household and Census Combining Wodon. Q. and H. Coulombe, World Bank,Washington, D.C. 2002. World Bank.Washington, D.C. Welfare on the Map in Madagascar, Africa Region Working Paper Series No. 34. Gaborone, Botswana. Inequality.” Econometrica.2003.71(1),355-364. 2911. 2002.DECRG-World Bank.Washington, D.C. Level Estimation of Poverty and Inequality. Policy Research Working Paper No. Bank. World 2007. 280. No. Washington, D.C. Series Paper Working Region Africa Findings, Initiative Mapping Poverty Africa Central and West The Targeting: Better for 2003. Botswana. for Line Datum Poverty Annex 1:Methodology Stage 2 Stage 1

papers ofElbers,LanjouwandaswellonMistiaenetal(2002). theoretical original the from borrows It Map. Poverty a of construction the in necessary stage each for one parts, three into divided is below discussion The methodology’s complexities. the increases tremendously errors standard and indicators welfare different the of and calculation proper Furthermore, autocorrelation model. regression the spatial in heteroskedasticity account into take to wants one if computations, Although the idea is rather simple, its proper implementation requires complex measures andGini). (Atkinson computed be poverty FGT index, inequalities class Entropy generalised measures, inequality can indicators inequality and poverty usual the but sample survey. In order to maximise accuracy, we estimated the model at the at model the estimated accuracy,we maximise to order survey.In sample presented inthisnote,butcan beobtaineduponrequest. not is results test means of equality their and variables potential all of list The the of comparability the including level, different variablesfromwhichthedefinitivemodels would bedetermined. strata the at performed be would analysis all models, second-stage the of power predictability order the In maximise to means. the only test to ourselves restrained we practice in variable, each of distribution entire the we of comparability the Although test to comparability.wanted have might for tested be would which built variables then of we series questions, a selected of set the From options. answer proposed the as well as questions different the of wording the checking by started We between theCensusandHIES. profile, it is important to restrict ourselves to variables that are fully comparable poverty associated the with consistent map poverty a reproduce to able be to variables order comparability.In set ofexplanatory of criteria a some meeting are that databases both from todetermine we needed instance, first the In We first modelled the per capita household expenditure household per capita the modelled first We h tr ‘efr idctr ebae a etr st f niaos ae on based (P headcount indicators poverty on of emphasis puts note set This expenditures. entire household an embraces indicator’ ‘welfare term The of welfareindicatorsareconstructedfordifferentgeographicalsubgroups. to predict expenditures for every household in the Census. And thirdly, a series data, survey using HIES the estimated survey and both the 2001 Census. Secondly,to is parameters from common the regression are used are expenditure that variables explanatory capita of set per a employing of log a of model and Lanjouw Elbers, by Lanjouw (2002, 2003) cannot be challenged for its accuracy. developed Firstly, a regression methodology the behind idea basic The 9

In our study we used the Welfare Index constructed for the HIES Poverty Profile. Although this Welfare this Although Profile. Index isdefined intermsof equivalent adults, the demonstrationremains unchanged. Poverty HIES the for constructed Index Welfare the used we study our In 9 sn te limited the using 0 ), 23 CENSUS-BASED POVERTY MAP REPORT 24 Central Statistics Office 2008 (3) (2) (1) ( 4)

u 1n y 1n y û

ch ch =ƞ

=ƞ ch ch n teeoe h hueod component household the therefore and Let us specify a household level expenditure level household a specify us Let Urban Villages andRuralVillages. Cities, Towns& Other Gaborone, strata: sampling the is level that HIES, the of case the In representative. is survey the which for level geographical lowest these residualsbetweenuncorrelatedhouseholdandlocation components: by given disturbances, overall the of estimate an as In practice we first estimated equation (2) by simple OLS and used the residuals term. where the errortermsas: specify first we so heteroskedasticity.Todo and correlated.) surely are cluster same the within households from (Expenditure autocorrelation spatial possible to matrix need variance-covariance error first the we estimate model this estimate To (GLS). Square Least Generalised by disturbances of vector The capita expenditureas: If we linearise the previous equation, we model the household’s logarithmic per areas, enumeration in both theHIESandCensus,needtobedefinedsimilarly.present census be to need represent variables explanatory The also so. necessarily not although usually They design. sampling The locations represent clusters as defined in the first stage of typical household The location term location c;x =x =E[1ny c c +e

ƞ + Ɛ c is the location effect and effect location the is ch ch β+u ch isasetofexplanatoryvariables,andu ch

( ƞ c ch ) is estimated as the cluster means of the overall residuals, ch |x

is distributed F (0, F distributed is u ch ]+u Ɛ ch is the individual component of the error the of component individual the is ch

( ( e in order to take into account into take to order in Σ ch y ). The model (2) is estimated is (2) model The Σ). ch s ipy eutd The deducted. simply is ) ) model for household for model µ ch ch istheresidual: . We then decomposed then We . in h ( 5)

Stage 3 ŷ

r ch =exp(x´ squared its regressing by modelled is component error latest the in heteroskedasticity model (2). The latest matrix allowed us to estimate the final set of coefficients of the main predicted valuesandthedisturbanceterms: eae u pit siae ad h sadr dvain f u wlae index welfare became thestandarderrorsofthesesimulatedestimates. our of deviation standard the and of estimate; point set our became full the redrawing time each index welfare simulated the of means The terms. disturbances and coefficients times, 100 repeated was process This index welfare of value a census the in found household have terms disturbance been drawn and from their corresponding distributions. We coefficients then simulated for each of series a stage, previous the From welfare imputed that of dispersion the index. of measure a get to used been techniques have bootstrapping intractable, index welfare imputed the of variance the of computation the made has structure disturbance complex very the Since simulated the and expenditure capita disturbances. per of log the predict to census the in found household each of characteristics corresponding the with stage second To complete the Poverty Map, we associated the estimated parameters from the sum of sum the then are which matrices two produce to used are computations error Both and interactionsaswelltheimputedwelfare.Alogisticmodelisused. ( , the estimated variance-covariance matrix of the original model (2). model original the of matrix variance-covariance estimated the , ) on a long list of independent variables of model (2), their squared ch

ß r + ῆ c r +Ɛ r ch ( ŷ r ch ) based on the on based 25 CENSUS-BASED POVERTY MAP REPORT 26 Central Statistics Office 2008 Annex 2a:DefinitionoftheDifferentPredictors Data Predictors&MeansTesting Annex 2: pip_out pip_in pubcomp_rent indiv_rent other_house self_built psch pocc agesp mothsurvsp fathsurvsp selfemplsp emplsp teresecsp secesecsp primesecsp tertiarysp secondarysp primarysp noneducsp no_spouse agehd mothsurv fathsurv selfempl empl teresec secesec primesec couple single tertiary secondary primary noneduc literate headmale sedu hedu elderly female male girl714 boy714 kid06 hhsize =1 ifhouseholduses pipedoutdoorasitsmainsource ofwater;0ifnot =1 ifhouseholduses pipedindoorasitsmainsource water;0ifnot =1 ifhouseholdrentsitsdwelling from apubliccorporation;0ifnot =1 ifhouseholdrentsitsdwelling from anindividual;0ifnot =1 ifhouseholdpurchaseditsown dwelling;0ifnot =1 ifhouseholdbuiltitsowndwelling; 0ifnot Proportion ofhouseholdmemberscurrentlygoingtoschool Proportion ofhouseholdmembersbeingoccupied(employed) Age ofspouse(inyears) =1 ifspouse’s motherisstillalive; 0ifnot =1 ifspouse’s fatherisstillalive; 0ifnot =1 ifspouseisself-employed;0not =1 ifspouseworksasanemployee;0not =1 ifspouseworksinthetertiarysector;0not =1 ifspouseworksinthesecondarysector;0not =1 ifspouseworksintheprimarysector;0not =1 ifspousewenttopostsecondaryschool;0not =1 ifspousewenttosecondaryschool(atmost);0not =1 ifspousewenttoprimaryschool(atmost);0not =1 ifspousehasnoformaleducation;0not =1 ifthereisnospouseinthehousehold;0not Age ofhouseholdhead(inyears) =1 ifhouseholdhead’s motherisstillalive;0ifnot =1 ifhouseholdhead’s fatherisstillalive;0ifnot =1 ifhouseholdheadisself-employed;0not =1 ifhouseholdheadworksasanemployee;0not =1 ifhouseholdheadworksinthetertiarysector;0not =1 ifhouseholdheadworksinthesecondarysector;0not =1 ifhouseholdheadworksintheprimarysector;0not =1 ifhouseholdheadisincouple;0not =1 ifhouseholdheadissingle;0not =1 ifhouseholdheadwenttopostsecondaryschool;0not =1 ifhouseholdheadwenttosecondaryschool(atmost);0not =1 ifhouseholdheadwenttoprimaryschool(atmost);0not =1 ifhouseholdheadhasnoformaleducation;0not =1 ifhouseholdheadisliterate;0not =1 ifhouseholdheadisamale;0not Spouse yearsofschooling Household headyearsofschooling Number ofelderlyaged65ormore Number ofadultfemalesagedbetween15and64 Number ofadultmalesagedbetween15and64 Number ofgirlsagedbetween7and14 Number ofboysagedbetween7and14 Number ofchildrenagedbetween0and6 Household size Annex 2a:DefinitionoftheDifferentPredictors(continued...) d90 d80 d72 d71 d70 d60 d54 d53 d52 d51 d50 d40 d31 d30 d20 d12 d11 d10 d7 d6 d5 d4 d3 d2 d1 tv radio pc phone barrow cart bike tractor car van room other_heat none_heat wood_heat elec_heat elec_light para_cook gas_cook wood_cook elec_cook other_toi lat_toi vip_toi flush_toi borehole com_tap hhsize =1 ifhousehold residesin KgalagadiSouth sub-district;0if not =1 ifhouseholdresides inGhanzisub-district;0if not =1 ifhouseholdresides inChobesub-district;0ifnot =1 ifhouseholdresides inNgamilandWest sub-district;0ifnot =1 ifhouseholdresidesinNgamiland Eastsub-district;0ifnot =1 ifhouseholdresidesinNorthEast sub-district;0ifnot =1 ifhouseholdresidesinCentral Tutume sub-district;0ifnot =1 ifhouseholdresidesinCentral Botetisub-district;0ifnot =1 ifhouseholdresidesinCentralBobonongsub-district;0not =1 ifhouseholdresidesinCentralMahalapyesub-district;0not =1 ifhouseholdresidesinCentralSerowe/Palapyesub-district;0not =1 ifhouseholdresidesinKgatlengsub-district;0not =1 ifhouseholdresidesinKwenengWest sub-district;0ifnot =1 ifhouseholdresidesinKwenengEastsub-district;0not =1 ifhouseholdresidesinSouthEastsub-district;0not =1 ifhouseholdresidesinNgwaketseWest sub-district;0ifnot =1 ifhouseholdresidesinBorolongsub-district;0not =1 ifhouseholdresidesinNgwaketsesub-district;0not =1 ifhouseholdresidesinSowaTown sub-district;0ifnot =1 ifhouseholdresidesinJwanengsub-district;0not =1 ifhouseholdresidesinOrapasub-district;0not =1 ifhouseholdresidesinSelebi-Phikwesub-district;0not =1 ifhouseholdresidesinLobatsesub-district;0not =1 ifhouseholdresidesinFrancistownsub-district;0not =1 ifhouseholdresidesinGaboronesub-district;0not =1 ifhouseholdownsatelevision;0not =1 ifhouseholdownsaradio;0not =1 ifhouseholdownsapersonalcomputer;0not =1 ifhouseholdownsaphone;0not =1 ifhouseholdownsabarrow;0not =1 ifhouseholdownsacart;0not =1 ifhouseholdownsabicycle;0not =1 ifhouseholdownsatractor;0not =1 ifhouseholdownsacar;0not =1 ifhouseholdownsavan;0not Number ofroomsindwelling =1 ifhouseholdusesothertypesofcombustibleforheating;0not =1 ifhouseholddoesnotuseanycombustibleforheating;0 =1 ifhouseholduseswoodforheating;0not =1 ifhouseholduseselectricityforheating;0not =1 ifhouseholduseselectricityforlighting;0not =1 ifhouseholdusesparaffinforcooking;0not =1 ifhouseholdusesgasforcooking;0not =1 ifhouseholduseswoodforcooking;0not =1 ifhouseholduseselectricityforcooking;0not =1 ifhouseholdusesothertypesoftoilet;0not =1 ifhouseholduseslatrine;0not =1 ifhouseholdusesventilatedimprovedpitlatrine;0not =1 ifhouseholdusesflushtoilet;0not =1 ifhouseholdusesboreholeasitsmainsourceofwater;0not =1 ifhouseholdusescommunaltapasitsmainsourceofwater;0not Household size 27 CENSUS-BASED POVERTY MAP REPORT 28 Central Statistics Office 2008 Annex 2b:AligningtheData,Test onEqualityofMeans Households kid06 pip_out boy714 com_tap girl714 male female elderly hedu sedu headmale literate noneduc primary secondary tertiary single couple primesec secesec teresec empl selfempl fathsurv mothsurv agehd no_spouse noneducsp primarysp secondarysp tertiarysp primesecsp secesecsp teresecsp emplsp selfemplsp fathsurvsp mothsurvsp agesp pocc psch self_built other_house pip_in Census Mean 3.106 0.359 0.276 0.202 0.230 0.231 1.115 1.157 0.041 9.971 3.462 0.610 0.880 0.097 0.249 0.519 0.135 0.469 0.509 0.006 0.203 0.643 0.772 0.085 0.498 0.773 0.661 0.020 0.073 0.197 0.048 0.002 0.041 0.169 0.186 0.028 0.179 0.268 0.609 0.149 0.128 0.179 0.492 35.8 11.7 Mean 3.185 0.370 0.403 0.232 0.108 0.251 1.078 1.227 0.027 9.993 3.678 0.605 0.883 0.100 0.252 0.483 0.165 0.465 0.502 0.005 0.237 0.641 0.793 0.091 0.470 0.737 0.644 0.023 0.072 0.195 0.066 0.003 0.054 0.176 0.200 0.032 0.190 0.276 0.591 0.167 0.155 0.134 0.460 37.6 12.6 Survey Gaborone 0.085 0.022 0.045 0.015 0.032 0.017 0.028 0.035 0.005 0.324 0.252 0.015 0.012 0.011 0.017 0.017 0.025 0.020 0.020 0.002 0.014 0.018 0.011 0.008 0.014 0.011 0.018 0.004 0.008 0.014 0.012 0.002 0.006 0.014 0.013 0.006 0.013 0.015 0.012 0.009 0.019 0.020 0.051 0.48 0.78 s.d. Means (95%) Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Equality of Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Test on Census Mean 3.341 0.405 0.473 0.306 0.257 0.281 0.294 1.085 1.174 0.059 8.729 2.850 0.598 0.839 0.123 0.329 0.490 0.058 0.415 0.550 0.007 0.318 0.479 0.718 0.087 0.457 0.735 0.679 0.032 0.103 0.170 0.016 0.002 0.049 0.123 0.140 0.034 0.161 0.246 0.551 0.171 0.199 0.141 36.9 11.2 Other Towns &Cities Mean 3.556 0.421 0.487 0.337 0.336 0.204 0.357 1.065 1.245 0.066 8.526 2.880 0.594 0.821 0.139 0.338 0.461 0.062 0.416 0.529 0.010 0.368 0.476 0.742 0.112 0.416 0.685 0.669 0.031 0.116 0.170 0.014 0.003 0.044 0.121 0.126 0.041 0.160 0.253 0.529 0.213 0.216 0.124 39.2 12.2 Survey 0.093 0.051 0.029 0.041 0.023 0.033 0.020 0.034 0.035 0.009 0.286 0.220 0.020 0.019 0.015 0.019 0.021 0.014 0.022 0.023 0.003 0.029 0.027 0.022 0.012 0.015 0.015 0.019 0.005 0.011 0.014 0.005 0.001 0.005 0.012 0.012 0.007 0.013 0.017 0.013 0.009 0.022 0.020 0.48 0.73 s.d. Means (95%) Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Equality of Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Test on Annex 2b:AligningtheData,Test onEqualityofMeans(continued...) borehole other_wate d51 flush_toi d52 vip_toi lat_toi other_toi elec_cook wood_cook gas_cook para_cook elec_light elec_heat wood_heat none_heat other_heat room indiv_rent ubcomp_rent van car tractor bike cart barrow phone pc radio tv d1 d2 d3 d4 d5 d6 d7 d10 d11 d12 d20 d30 d31 d40 d50 Census Mean 0.000 0.002 0.000 0.511 0.000 0.224 0.258 0.007 0.146 0.016 0.714 0.125 0.491 0.205 0.156 0.561 0.078 1.972 0.480 0.214 0.157 0.224 0.022 0.125 0.047 0.245 0.584 0.126 0.762 0.486 1.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Mean 0.000 0.028 0.000 0.457 0.000 0.303 0.234 0.006 0.114 0.004 0.785 0.098 0.488 0.219 0.087 0.664 0.030 2.240 0.512 0.198 0.175 0.432 0.009 0.119 0.019 0.255 0.613 0.152 0.752 0.500 1.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Survey Gaborone 0.000 0.007 0.000 0.051 0.000 0.039 0.036 0.002 0.023 0.002 0.022 0.015 0.045 0.031 0.014 0.031 0.007 0.114 0.039 0.036 0.019 0.046 0.003 0.012 0.004 0.017 0.036 0.024 0.017 0.037 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 s.d. Means (95%) Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Equality of Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Test on Census Mean 0.000 0.000 0.008 0.000 0.438 0.000 0.202 0.329 0.031 0.107 0.121 0.613 0.159 0.438 0.156 0.276 0.492 0.076 2.164 0.410 0.250 0.142 0.149 0.023 0.146 0.064 0.300 0.466 0.055 0.755 0.391 0.000 0.419 0.155 0.277 0.047 0.085 0.018 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Other Towns &Cities Mean 0.000 0.000 0.038 0.000 0.442 0.000 0.269 0.260 0.028 0.123 0.101 0.637 0.139 0.473 0.156 0.218 0.610 0.016 2.313 0.395 0.265 0.157 0.386 0.008 0.119 0.032 0.306 0.519 0.071 0.726 0.423 0.000 0.419 0.158 0.279 0.044 0.083 0.016 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Survey 0.000 0.000 0.011 0.000 0.050 0.000 0.035 0.038 0.008 0.026 0.016 0.027 0.017 0.045 0.024 0.025 0.025 0.005 0.087 0.036 0.048 0.021 0.052 0.003 0.012 0.005 0.018 0.034 0.015 0.018 0.033 0.000 0.059 0.043 0.053 0.024 0.032 0.016 0.000 0.000 0.000 0.000 0.000 0.000 0.000 s.d. Means (95%) Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Equality of Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Test on 29 CENSUS-BASED POVERTY MAP REPORT 30 Central Statistics Office 2008 Annex 2b:AligningtheData,Test onEqualityofMeans(continued...) d53 d54 d60 d70 d71 d72 d80 d90 hhsize kid06 boy714 girl714 male female elderly hedu sedu headmale literate noneduc primary secondary tertiary single couple primesec secesec teresec empl selfempl fathsurv mothsurv agehd no_spouse noneducsp primarysp secondarysp tertiarysp primesecsp secesecsp Census Census Mean Mean 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 4.356 0.717 0.388 0.444 1.138 1.428 0.241 6.631 1.901 0.479 0.663 0.271 0.347 0.343 0.039 0.380 0.520 0.022 0.129 0.389 0.450 0.094 0.360 0.602 0.719 0.065 0.110 0.096 0.010 0.005 0.025 44.0 Mean Mean 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 4.489 0.683 0.448 0.499 1.106 1.493 0.259 6.670 1.982 0.477 0.657 0.279 0.336 0.336 0.049 0.388 0.466 0.049 0.149 0.441 0.498 0.140 0.311 0.545 0.706 0.064 0.119 0.097 0.015 0.009 0.025 46.4 Urban Villages Survey Survey Gaborone 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.131 0.036 0.024 0.027 0.032 0.041 0.021 0.311 0.136 0.016 0.023 0.019 0.016 0.022 0.009 0.017 0.018 0.009 0.014 0.023 0.027 0.014 0.016 0.020 0.014 0.008 0.009 0.010 0.004 0.003 0.004 0.95 s.d. s.d. Means (95%) Means (95%) Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Equality of Equality of Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Test on Test on Census Census Mean Mean 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 4.496 0.848 0.554 0.499 1.104 1.177 0.315 4.271 1.114 0.538 0.464 0.457 0.338 0.193 0.013 0.345 0.546 0.156 0.079 0.214 0.339 0.122 0.319 0.536 0.712 0.138 0.105 0.042 0.003 0.021 0.016 47.0 Other Towns &Cities Mean Mean 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 4.394 0.899 0.531 0.494 1.003 1.151 0.317 3.786 1.155 0.535 0.424 0.507 0.327 0.158 0.008 0.357 0.480 0.307 0.080 0.215 0.328 0.273 0.270 0.489 0.692 0.147 0.117 0.043 0.002 0.055 0.016 49.3 Survey Survey Rural Villages 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.172 0.051 0.037 0.043 0.037 0.057 0.020 0.222 0.116 0.023 0.022 0.023 0.017 0.015 0.003 0.019 0.018 0.041 0.016 0.024 0.029 0.032 0.013 0.015 0.015 0.015 0.011 0.009 0.001 0.008 0.004 0.73 s.d. s.d. Means (95%) Means (95%) Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Equality of Equality of Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Test on Test on d53 d54 d60 d70 d71 d72 d80 d90 hhsize kid06 boy714 girl714 male female elderly hedu sedu headmale literate noneduc primary secondary tertiary single couple primesec secesec teresec empl selfempl fathsurv mothsurv agehd no_spouse noneducsp primarysp secondarysp tertiarysp primesecsp secesecsp Census Census Mean Mean 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 4.356 0.717 0.388 0.444 1.138 1.428 0.241 6.631 1.901 0.479 0.663 0.271 0.347 0.343 0.039 0.380 0.520 0.022 0.129 0.389 0.450 0.094 0.360 0.602 0.719 0.065 0.110 0.096 0.010 0.005 0.025 44.0 Mean Mean 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 4.489 0.683 0.448 0.499 1.106 1.493 0.259 6.670 1.982 0.477 0.657 0.279 0.336 0.336 0.049 0.388 0.466 0.049 0.149 0.441 0.498 0.140 0.311 0.545 0.706 0.064 0.119 0.097 0.015 0.009 0.025 46.4 Urban Villages Survey Survey Gaborone 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.131 0.036 0.024 0.027 0.032 0.041 0.021 0.311 0.136 0.016 0.023 0.019 0.016 0.022 0.009 0.017 0.018 0.009 0.014 0.023 0.027 0.014 0.016 0.020 0.014 0.008 0.009 0.010 0.004 0.003 0.004 0.95 s.d. s.d. Means (95%) Means (95%) Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Equality of Equality of Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Test on Test on Census Census Mean Mean 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 4.496 0.848 0.554 0.499 1.104 1.177 0.315 4.271 1.114 0.538 0.464 0.457 0.338 0.193 0.013 0.345 0.546 0.156 0.079 0.214 0.339 0.122 0.319 0.536 0.712 0.138 0.105 0.042 0.003 0.021 0.016 47.0 Other Towns &Cities Mean Mean 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 4.394 0.899 0.531 0.494 1.003 1.151 0.317 3.786 1.155 0.535 0.424 0.507 0.327 0.158 0.008 0.357 0.480 0.307 0.080 0.215 0.328 0.273 0.270 0.489 0.692 0.147 0.117 0.043 0.002 0.055 0.016 49.3 Survey Survey Rural Villages 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.172 0.051 0.037 0.043 0.037 0.057 0.020 0.222 0.116 0.023 0.022 0.023 0.017 0.015 0.003 0.019 0.018 0.041 0.016 0.024 0.029 0.032 0.013 0.015 0.015 0.015 0.011 0.009 0.001 0.008 0.004 0.73 s.d. s.d. Means (95%) Means (95%) Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Equality of Equality of Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Test on Test on Annex 2b:AligningtheData,Test onEqualityofMeans(continued...) teresecsp d3 emplsp d4 selfemplsp fathsurvsp mothsurvsp agesp pocc psch self_built other_house pip_in pip_out com_tap borehole other_wate flush_toi vip_toi lat_toi other_toi elec_cook wood_cook gas_cook para_cook elec_light elec_heat wood_heat none_heat other_heat room indiv_rent ubcomp_rent van car tractor bike cart barrow phone pc radio tv d1 d2 Census Mean 0.091 0.000 0.094 0.000 0.028 0.111 0.184 0.370 0.221 0.623 0.111 0.195 0.456 0.316 0.001 0.033 0.177 0.268 0.388 0.167 0.034 0.386 0.510 0.070 0.286 0.077 0.575 0.298 0.051 2.548 0.182 0.084 0.136 0.118 0.035 0.172 0.132 0.485 0.406 0.030 0.730 0.272 0.000 0.000 11.8 Mean 0.095 0.000 0.088 0.000 0.041 0.103 0.172 0.383 0.244 0.620 0.078 0.196 0.500 0.253 0.000 0.051 0.195 0.281 0.411 0.113 0.035 0.354 0.556 0.054 0.355 0.074 0.489 0.414 0.022 2.777 0.186 0.116 0.129 0.241 0.017 0.135 0.112 0.500 0.512 0.029 0.691 0.312 0.000 0.000 12.8 Urban Villages Survey 0.008 0.000 0.008 0.000 0.005 0.010 0.014 0.017 0.009 0.033 0.008 0.029 0.027 0.025 0.000 0.008 0.029 0.027 0.030 0.014 0.007 0.028 0.024 0.007 0.027 0.009 0.033 0.031 0.004 0.071 0.024 0.026 0.012 0.039 0.003 0.012 0.011 0.023 0.027 0.005 0.015 0.023 0.000 0.000 0.65 s.d. Means (95%) Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Equality of Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Test on Census Mean 0.000 0.045 0.000 0.058 0.000 0.028 0.096 0.163 0.304 0.237 0.773 0.139 0.067 0.160 0.506 0.123 0.144 0.068 0.141 0.241 0.550 0.011 0.785 0.170 0.035 0.080 0.022 0.834 0.113 0.031 2.264 0.033 0.055 0.086 0.064 0.029 0.174 0.224 0.420 0.153 0.010 0.579 0.109 0.000 13.2 Mean 0.000 0.055 0.000 0.056 0.000 0.069 0.092 0.172 0.391 0.196 0.762 0.150 0.051 0.162 0.446 0.050 0.291 0.073 0.136 0.221 0.571 0.009 0.809 0.168 0.014 0.070 0.014 0.847 0.126 0.012 2.441 0.033 0.055 0.050 0.266 0.013 0.156 0.250 0.405 0.153 0.011 0.504 0.062 0.000 14.4 Survey Rural Villages 0.000 0.010 0.000 0.009 0.000 0.010 0.010 0.013 0.029 0.015 0.027 0.024 0.012 0.032 0.049 0.022 0.046 0.021 0.024 0.032 0.046 0.007 0.033 0.028 0.006 0.015 0.006 0.027 0.025 0.003 0.083 0.011 0.011 0.007 0.055 0.004 0.020 0.026 0.033 0.024 0.003 0.019 0.013 0.000 0.69 s.d. Means (95%) Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Equality of Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Rejected Test on 31 CENSUS-BASED POVERTY MAP REPORT 32 Central Statistics Office 2008 Annex 2b:AligningtheData,Test onEqualityofMeans(continued...) d5 d6 d7 d10 d11 d12 d20 d30 d31 d40 d50 d51 d52 d53 d54 d60 d70 d71 d72 d80 d90 Census Mean 0.000 0.000 0.000 0.100 0.000 0.000 0.080 0.239 0.011 0.064 0.135 0.082 0.047 0.029 0.063 0.000 0.080 0.011 0.018 0.022 0.014 Mean 0.000 0.000 0.000 0.104 0.000 0.000 0.091 0.234 0.000 0.073 0.130 0.079 0.050 0.039 0.059 0.000 0.079 0.014 0.012 0.025 0.011 Urban Villages Survey 0.000 0.000 0.000 0.033 0.000 0.000 0.033 0.047 0.000 0.029 0.037 0.029 0.024 0.022 0.026 0.000 0.029 0.014 0.012 0.017 0.011 s.d. Means (95%) Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Equality of Rejected Test on Census Mean 0.000 0.000 0.000 0.073 0.062 0.014 0.029 0.085 0.044 0.055 0.103 0.081 0.055 0.040 0.116 0.065 0.034 0.052 0.014 0.030 0.024 Mean 0.000 0.000 0.000 0.079 0.053 0.014 0.033 0.082 0.038 0.062 0.097 0.085 0.054 0.050 0.114 0.048 0.031 0.070 0.015 0.018 0.033 Survey Rural Villages 0.000 0.000 0.000 0.035 0.030 0.014 0.023 0.036 0.027 0.030 0.038 0.036 0.031 0.028 0.042 0.028 0.022 0.034 0.015 0.018 0.023 s.d. Means (95%) Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Not Rejected Equality of Test on Survey-Based RegressionModels Annex 3: Strata 1:Gaborone Intercept LNHHSIZE Var Adj. R-square R-square Number ofobservations HEDU HEADMALE POCC LAT_TOI ELEC_COOK ELEC_LIGHT VAN PHONE PC RADIO TV -0.1701538 -0.1790979 0.2381769 0.0435303 0.1214941 0.3242945 0.3883621 0.3201606 0.1233106 0.3195958 0.1298748 0.3308698 0.404568 Coef. OLS Result 0.0425679 0.0052495 0.0440434 0.0813135 0.0531913 0.0725188 0.0625414 0.0616613 0.0490012 0.0691948 0.0501286 0.0587581 Std.Err. 0.098491 -3.997 -3.367 2.418 8.292 2.759 4.975 4.472 5.192 2.516 4.619 2.591 5.631 6.21 t 0.469399 0.473899 1416 Prob>|t| <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 0.0157 0.0059 0.0008 0.0097 0.012 Strata 2:OtherTowns &Cities MHEDU MEMPL MELEC_COOK MSECONDARY TV RADIO PC VAN ELEC_LIGHT PARA_COOK GAS_COOK PIP_IN POCC AGESP NO_SPOUSE COUPLE SINGLE TERTIARY HEADMALE SEDU HEDU MALE KID06 Intercept Var Adj. R-square R-square Number ofobservations -0.6346226 -1.2176457 -0.2278888 -0.2466743 -0.2527069 -0.0904476 -0.0625897 -0.8244724 0.1031643 0.6556504 0.1843409 0.1275051 0.2092166 0.4713308 0.3169513 0.0975748 0.3071151 0.6006978 0.0062617 0.4587054 0.1214278 0.1285616 0.0267959 Coef. 0.030794 OLS Result Std.Err. 0.0179735 0.1835715 0.1228846 0.2593629 0.0550807 0.0455006 0.0844879 0.0617177 0.0664221 0.0729658 0.0528421 0.0682209 0.0663344 0.1932194 0.0964106 0.0913556 0.0523431 0.0103214 0.0055096 0.0275977 0.2562724 0.003478 0.092037 0.024372 -5.164 -4.695 -3.123 -2.559 -2.268 -3.217 -2.746 -3.711 3.572 3.347 2.802 2.476 7.637 4.772 1.847 4.502 9.056 2.374 1.329 2.456 2.596 5.589 5.74 t 1.8 0.526916 0.534677 1403 Prob>|t| <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 0.0004 0.0008 0.0051 0.0134 0.0018 0.0177 0.0106 0.0142 0.0095 0.0235 0.0013 0.0061 0.0002 0.072 0.065 0.184 33 CENSUS-BASED POVERTY MAP REPORT 34 Central Statistics Office 2008 Strata 3:UrbanVillages Intercept LNHHSIZE Var Adj. R-square R-square Number ofobservations HEDU SEDU HEADMALE SINGLE EMPL NO_SPOUSE POCC PIP_IN PIP_OUT FLUSH_TOI VIP_TOI LAT_TOI ELEC_COOK GAS_COOK ELEC_HEAT VAN TV D10 D70 MELEC_LIGHT -0.3625015 -0.1701171 -0.2971803 -0.3766534 0.1481195 0.0269838 0.1739154 0.2895495 0.4861628 0.5912371 0.2482076 0.3142308 0.2165864 0.2494052 0.1504111 0.3308518 0.2785336 0.2896169 0.154624 0.476567 Coef. 0.02347 0.3752 OLS Result 0.1166024 0.0333901 0.0049296 0.0079738 0.0476143 0.0461512 0.0477392 0.0808339 0.0772172 0.1460227 0.0472407 0.1532707 0.0694489 0.0653801 0.1127903 0.0473082 0.0757218 0.0618234 0.0507411 0.0630257 0.0695317 0.1051625 Std.Err. -10.857 -3.686 -4.715 -3.582 5.474 2.943 3.653 3.239 3.582 6.296 4.049 5.254 3.109 4.525 3.313 3.327 5.272 1.986 5.352 5.489 4.165 1.27 t 0.573895 0.578988 1758 Prob>|t| <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 0.2041 0.0033 0.0003 0.0002 0.0012 0.0004 0.0019 0.0009 0.0009 0.0471 0.0004 Strata 4:RuralVillages D90 D60 PHONE ELEC_LIGHT GAS_COOK VIP_TOI FLUSH_TOI FATHSURVSP NONEDUCSP EMPL SINGLE LITERATE HEADMALE LNHHSIZE Intercept Var Adj. R-square R-square Number ofobservations -0.3780958 0.2573657 0.3828551 0.4471726 0.3681034 0.2592718 0.4023625 -0.2096494 -0.2701309 0.3594446 -0.1551154 0.1958288 0.1975546 -0.44441 0.6205013 Coef. OLS Result 0.123747 0.1041893 0.0710522 0.1197241 0.0761244 0.0660722 0.1272069 0.0824586 0.0727789 0.0543494 0.0512671 0.0504958 0.0505266 0.0324199 0.0668019 Std.Err. -3.055 2.47 5.388 3.735 4.836 3.924 3.163 -2.542 -3.712 6.614 -3.026 3.878 3.91 -13.708 9.289 t 0.0023 0.0136 <.0001 0.0002 <.0001 <.0001 0.0016 0.0111 0.0002 <.0001 0.0025 0.0001 <.0001 <.0001 <.0001 0.526916 0.534677 1403 Prob>|t|

Republic of Botswana Botswana Census-Based Poverty Map Report

July 2008