Report No. 40048-MZ Mozambique Beating the Odds: Sustaining Inclusion in a Growing Economy A Mozambique Poverty, Gender, and Social Assessment (In Two Volumes) Volume II: Appendixes February 2008 Africa Region Poverty Reduction and Economic Management Document of the World Bank TABLE OF CONTENTS APPENDIX A.CHAPTER TABLES ......................................................................................................... 9 CHAPTER1................................................................................................................................................. 9 CHAPTER 2 CHAPTER3 ............................................................................................................................................... ............................................................................................................................................... 25 50 CHAPTER 4............................................................................................................................................... 70 CHAPTER5 ............................................................................................................................................... CHAPTER6 ............................................................................................................................................. 92 100 APPENDIX B METHODOLOGY . ......................................................................................................... 103 DESCRIPTIONOFHOUSEHOLD SOURCES SURVEY ................................................................................... HOUSEHOLD EQUIVALENTS AND CONSUMPTIONANDINCOME RURALANDURBANDEFINITIONS POVERTYLINES IAF 1997AND2003 COMPARISONS.........108 ADULT RANKINGS (QUINTILES) ............103 AND FOR 109 CONSTRUCTINGPOVERTYLINES FORPOVERTY ANALYSIS.................................................................... 110 iii LISTOFTABLES APPENDIXA TABLEAl.1. POVERTYMEASURES. BY AREA.1997 AND 2003 ....................................................................... 9 TABLEA1.2. POVERTYMEASURES. BY PROVINCE. 1997 AND 2003 ................................................................ 9 TABLEA1.3. ACCESS LAND. AREA.GENDER.AND WEALTHOFHEAD. TO BY 2006 ..................................... 10 TABLEAl.4. URBANHOUSEHOLD EMPLOYMENT HEAD SECTOR, BY GENDEROF HEADAND WEALTH TERCILE,2006 ............................................................................................................................................... 10 TABLEA1.5. RURALHOUSEHOLDHEADEMPLOYMENT TERCILE,2006............................................................................................................................................... SECTOR, BY GENDEROF HEAD WEALTH AND 10 TABLEAl.6. SHOCKSEXPERIENCEDURBANHOUSEHOLDS LAST 12MONTHS, BY GENDER BY DURING OF HEAD AND WEALTH TERCILE, 2006 ........................................................................................................ 11 TABLEA1.7 SHOCKS EXPERIENCED RURALHOUSEHOLDS LAST MONTHS, BY GENDER BY DURING 12 OF HEAD AND WEALTH TERCILE, 2006 ........................................................................................................ 11 TABLEA1.8. COPINGSTRATEGIESINRESPONSETO SHOCKS DURINGTHELAST MONTHS,AREA 12 BY AND INCOMEGROUP, 2006 ........................................................................................................................... 11 TABLEA1.9. COPINGSTRATEGIES INCOMMUNITIES VISITED, 2006............................................................. TABLEA1.10. SCHOOLATTENDANCEBY ORPHANSTATUS, AREA,AND WEALTHTERCILE,2006 ...............1212 TABLEA1.11.RATIOOF SCHOOL ATTENDANCEOF ORPHANS VERSUS NONORPHANS,10-14, 1997 AND 2003 ............................................................................................................................................. AGED 12 TABLEA1 12 PARTICIPATIONINDOMESTIC CHORESAND LEISURECHILDRENAGED0-17, BY . . OF ORPHANSTATUS, AREA,AND GENDER,2006 13 TABLEA1 13 HUMAN . . ............................................................................................... DEVELOPMENT AND GENDER-RELATED ............................................................................................................................. INDEX DEVELOPMENT INDEX-LEVELS 13 TABLEA1.14.SELF-ASSESSMENTOFWELFARERELATIVETO OTHERSINTHECOMMUNITY,2006 AND TRENDS, 1975-2004 .............. 14 TABLEA 1.15. HOUSEHOLDS THAT HAVEEXPERIENCED HUNGER DURINGTHELAST MONTHS, 12 BY HOUSEHOLDHEAD TERCILE, 2006 AND ........................................................................................................ 14 TABLEA1.16. NUMBERMEALS OF CONSUMED DURINGPREVIOUSDAY,2006 ............................................ 14 TABLEA 1.17. PERCEPTIONOF CHANGEINHOUSEHOLD YEARS, 2006 ................................................................................................................................................. POVERTY INRURALAREASOVERLAST FIVE 15 TABLEA 1.18. PERCEPTIONOFCHANGEINHOUSEHOLD POVERTYINURBANAREASOVERLAST FIVE YEARS,2006 ................................................................................................................................................. TABLEA1.19. PREDICTIONOF CHANGEINHOUSEHOLD WELL-BEING OVERNEXT FIVEYEARS, 2006 ........15 15 TABLEAl.20. POPULATIONDISTRIBUTION ACROSS CONSUMPTIONQUINTILES, BY AREAAND GENDER OFHOUSEHOLD 1997 AND 2003 HEAD, 16 TABLEA1.21 POPULATIONDISTRIBUTION . ........................................................................................................ ACROSS WEALTH TERCILES, BY AREAAND GENDEROF HOUSEHOLDHEAD, 2006 16 TABLEA1.22 HOUSEHOLD . .............................................................................................................................. CHARACTERISTICS, BY CONSUMPTION QUINTILE, 1997 AND 2003 17 TAB LEA^.^^. ACCESS SERVICESBY QUINTILE, REGION, AND AREA,1997AND 2003 TO ............................ .................... 18 TABLEAl.24. NETSECONDARY SCHOOLENROLLMENT, GENDERAND CONSUMPTIONQUINTILE, 1997 AND 2003 ............................................................................................................................................. BY 19 TABLEAl.25. EFFECT EDUCATIONANDINFORMATIONON CHILDCAREAND CHILDHEIGHT-FOR-AGE, OF 2003.............................................................................................................................................................. TABLEA1.26. CONSTRAINTS TO HEALTHCARE,2006 ................................................................................... 19 20 TABLEA1.27. FOODSHAREAND OWNERSHIPOF HOUSEHOLD BY QUINTILE AND AREA,1997 ASSETS AND 2003 ..................................................................................................................................................... 20 TABLEA1.28. KNOWLEDGE PRACTICESOFMOTHERS. AND 2003 ................................................................. 21 TABLEAl.29. CONSUMPTIONREGRESSIONSWITH DISTRICT FIXEDEFFECTS, AND 2003 1997 22 TABLEA1.30. CHARACTERISTICS OFHOUSEHOLD BY GENDEROF HOUSEHOLD 2003 HEAD, ....................... ..................... 24 TABLEA2.1. GDPBY EXPENDITURE ......................... 25 TABLEA2.2. ACCOUNTING FORGDPGROWTHBY FACTOR PRODUCTION............................................... CATEGORY, SHARE AND GROWTH RATE, 1996-2003 OF 25 TABLEA2.3 .INTERNATIONAL ANDDOMESTIC TERMS TRADE,1996-2003 ............................................. OF 26 AREA,1997-2003 ......................................................................................................................................... TABLEA2.4. AVERAGE ANNUALGROWTH RATE OF AVERAGE CONSUMPTION, BY QUINTILE AND 26 TABLEA2.5. MEASURES OFINEQUALITY, 1997AND 2003 ............................................................................ 26 TABLEA2.6. GINI COEFFICIENT FORVARIOUSCOUNTRIES .......................................................................... 27 iv TABLEA2.7. DECOMPOSITION 1997-2003 .................................................................................................................................................... OF CHANGEINPOVERTY. BY GROWTH AND INEQUALITY DIMENSIONS. TABLEA2.8. GDP,LABOR FORCE,PRODUCTIVITY, ANDPOVERTY, BY SECTOR, 1997-2003 ....................... 28 TABLEA2.9. DECOMPOSITION OF CHANGES INPOVERTY BY LOCATION SECTOR, 1997-2003 AND ..............29 30 TABLEA2.10. OCCUPATIONAL STATUSOFPOPULATION, BY GENDER,1997AND 2003 31 TABLEA2.11. TYPEOFEMPLOYMENT, AREA,1997-2003 BY ...................................................................... ................................ 31 TABLEA2.12A.DISTRIBUTIONTHELABOR AREA,2003 ................................................................................................................................................... OF FORCE SECTOR AND TYPE OFEMPLOYMENT, BY BY 32 EMPLOYMENT, AREA,1997-2003 ......................................................................................................... TABLEA2.12B. AVERAGE ANNUALGROWTH RATEOF THELABOR FORCE SECTOR, TYPEOF BY AND 32 TABLEA2.13. TYPEOF CONTRACT, BY INDUSTRYAND AREA,2003 ............................................................ 33 TABLEA2.14. AVERAGE NUMBERSECTORSANDINCOMESOURCESREPRESENTEDINTHE OF HOUSEHOLD, BY AREA,1997AND 2003 ....................................................................................................... 33 TABLEA2.15. HOUSEHOLD SOURCES OF INCOME AND INCOME SHARE, BY AREA,2003 .............................. 34 FIVEYEARS, BY TERCILEAND AREA,2006................................................................................................... TABLEA2.16. REASONSBEHINDPERCEIVEDIMPROVEMENTINHOUSEHOLD WELL-BEINGDURINGLAST 35 TABLEA2.17. REASONSBEHINDPERCEIVEDWORSENINGINHOUSEHOLD WELL-BEINGDURINGLAST FIVEYEARS, BYRRCILEAND AREA,2006 .................................................................................................. 36 TABLEA2.18A. INDEXAND GROWTH EMPLOYMENT, 1997-2003 ............................................................................................................................ RATEOF AVERAGE EARNINGS URBANAREAS,BY SECTOROF IN 36 TABLEA2.18B. INDEXAND GROWTH EMPLOYMENT, 1997-2003 ............................................................................................................................ RATEOF AVERAGEEARNINGS RURALAREAS, BY SECTOROF IN TABLEA2.19. EARNINGS INEQUALITYINURBANAREAS,BY TYPEOFEMPLOYMENT, TABLEA2.20. EARNINGS INEQUALITYINRURALAREAS,BY TYPEOFEMPLOYMENT, 1997-2003 ....... 38 AND 1997-2003 ......37 AND 39 TABLEA2.21. HIGHEST LEVEL EDUCATION OF COMPLETED, BY TYPEAND SECTOR OF EMPLOYMENT, 1997 AND 2003 ............................................................................................................................................. 40 TABLEA2.22. REGRESSIONRESULTS:DETERMINANTSWAGES, 2003, WITH DISTRICTFIXED OF EFFECTS ........................................................................................................................................................ 41 TABLEA2.23. WAGEREGRESSIONMEANSVARIABLES OF ........................................................................... 42 TABLEA2.24. AVERAGE BY QUINTILES, 1997 AND 2003 ..................................................................................................................... NUMBERSECTORSANDINCOMESOURCESREPRESENTEDINHOUSEHOLD, OF 43 TABLEA2.25. HOUSEHOLD SOURCE, BY QUINTILE, 2003 INCOME ............................................................... 43 TABLEA2.26. TYPEOF EMPLOYMENT SECTOR, BY QUINTILE, 1997 AND 2003 ............................................ 44 TAB LEA^.^^. POVERTYRATESBY SECTOROF ACTIVITY OFHEAD AND SPOUSE, 2003 ............................... 44 TABLEA2.28. CONTRIBUTIONTO GROWTH TYPEOFLABOR, BY 1999-2004 TABLEA2.29. EDUCATION LEVEL ECONOMICALLY OF ACTIVE POPULATIONBY GENDER,1980-2004.......................................................44 TABLEA2.30. TYPEOFEMPLOYMENTURBANAREAS,BY GENDERAND SECTOR, 1997AND 2003 IN ..........45 TABLEA2.3 1.TYPEOFEMPLOYMENTALLAREAS,BYGENDERAND SECTOR, 1997AND 2003 IN ...............45 46 RURALMOZAMBIQUE, AND 2004......................................................................................................... TABLEA2.32. GENDERRATIOOFEDUCATION LEVEL ECONOMICALLY OF ACTIVE POPULATION IN 1997 46 TABLEA2.33. SECTOROFEMPLOYMENTHEAD OF VERSUS SPOUSE, 2003 ................................................... 47 TABLEA2.34. HOUSEHOLD PARTICIPATIONINAGRICULTURE,BY AREA,2003 ............................................ 48 TABLEA2.35. RURALHOUSEHOLD DIVERSIFICATION NONFARM INTO SELF-EMPLOYMENT, BY GENDER OF THE HEAD, 1996 AND 2002 ...................................................................................................................... 48 TABLEA2.36. INCOMESHARES BY TYPE OFEMPLOYMENT, GENDERAND AREA,2003 ............................... 49 TABLEA2.37. ANNUALGROWTHRATES OF GDP, CONSUMPTION,INVESTMENT,EXPORTS, AND IMPORTS, 2000-08 ........................................................................................................................................ 49 TABLEA3.1. RURALHOUSEHOLD PERADULTEQUIVALENTAND ANNUAL GROWTH INCOME RATES, BY QUINTILE, LOCATION, GENDER,1996-2002 AND ......................................................................................... 50 TABLE A3.2. PERCENTAGEOF FEMALE 1996 AND 2002 ............................................................................................................................................. HEAD WIDOW HEADOFHOUSEHOLDSBYINCOME AND QUINTILE, 51 TABLEA3.3. PROVINCIAL CHANGESINCROPPRODUCTION, 1996-2002 ...................................................... TAB LEA^.^.NUMBEROF GROWN,BY TYPE OF CROPAND INCOMEQUINTILE, 1996 AND 2002 CROPS 52 TABLEA3.5. AVERAGEANNUALGROWTH RATES INLAND UTILIZATION, 1993-2003 ................................ .......51 52 TABLEA3.6. ESTIMATED ACTUALAND POTENTIAL CROPYIELDS, 1998 ...................................................... 52 TABLEA3.7. CONDITIONSOF THECLASSIFIEDROADNETWORK, 1995 AND 2005 ........................................ 53 V TABLEA3.8. DETERMINANTS CENTRALAND NORTHERN MOZAMBIQUE. ........................................................................................... OFPARTICIPATION AND PERFORMANCEINRURALMAIZEMARKETS IN 2002 54 TABLEA3.9. DETERMINANTS OFPARTICIPATIONAND PERFORMANCEINRURALCOTTON MARKETS IN CENTRAL AND NORTHERN MOZAMBIQUE. 2002 ........................................................................................... 55 TABLEA3.10. DETERMINANTSPARTICIPATIONANDPERFORMANCEINTOBACCO OF MARKETS IN CENTRAL AND NORTHERNMOZAMBIQUE. TABLEA3.11. SOURCES OF GROWTH RURALHOUSEHOLD BY QUINTILE. 1996-2002 ................ 56 2002 ........................................................................................... IN INCOME 57 TABLEA3.12. RURALINCOME POVERTYINCIDENCEAND TRANSITIONMATRIX. 2002 AND 2005 ................ TABLEA3.13. RURALHOUSEHOLD POVERTY TRANSITIONSTATUS. BY GEOGRAPHIC AREA.2002-05 ....... 58 57 TABLEA3.14A. RURALINCOMEPOVERTYINCIDENCEANDPOVERTYTRANSITIONMATRIX. 2002 AND 2005 ............................................................................................................................................................. 58 TABLEA3.14B. RURALPOVERTYSTATUSAND POVERTY TRANSITIONMATRIX: EXTREMELY NONPOOR.WEALTHY. BYREGION. 2002AND2005 .............................................................................. POOR. TABLEA3.15. RURALPOVERTYDYNAMICS PERCEPTIONSOFWELFARECHANGES. 2002-05 .............. 60 AND 59 AND TABLEA3.16. DETERMINANTS OF HOUSEHOLD TRANSITIONS OUT OF AND INTORURALPOVERTY. 2002-05 ........................................................................................................................................................ 61 TABLEA3.17. RURALPOVERTYTRANSITION AND HOUSEHOLD CHARACTERISTICS. 2005 ........................... 63 TABLEA3.18. RURALPOVERTY AND CROPINCOME DIVERSIFICATION DYNAMICS. 2002-05 ...................... 64 TABLEA3.19. RURALHOUSEHOLDMARKET TRANSITIONSTATUS. 2002 AND2005 ........................................................................................................... CROP PARTICIPATIONAND OUTCOMES. BY POVERTY TABLEA3.20. RURALPOVERTYDYNAMICS OFF-FARMINCOMEDIVERSIFICATION. AND 2002-05 .............. 64 65 TABLEA3.21. RURALHOUSEHOLDS WITH INCOMEFROMSOURCE. BY POVERTY TRANSITION STATUS. 2002 AND 2005 ............................................................................................................................................. 65 TABLEA3.22. CHANGESINMAJOR SOURCES OF RURALINCOME. BY POVERTYTRANSITIONSTATUS. 2002 AND 2005 ............................................................................................................................................. 66 TABLEA3.23. RURALPOVERTYTRANSITIONS AND DIVERSIFICATION VARIOUS TYPESOFWAGE INTO LABOR. AND2005 2002 ................................................................................................................................ 67 TABLEA3.24. RURALPOVERTY TRANSITIONSAND DIVERSIFICATION VARIOUS TYPESOF INTO NONFARM BUSINESSES. 2002 AND 2005 ....................................................................................................... 68 TABLEA3.25. STRUCTUREOF RURALHOUSEHOLD BY QUINTILE AND ZONE. 1996.2002. AND INCOME. 2005 .............................................................................................................................................................. 69 TABLEA4.1. SECTORAL EXPENDITURES A PERCENTAGEOF TOTALEXPENDITURES. TABLEA4.2. GOVERNMENT EXPENDITURESEDUCATION.BY TYPE.2002-04 .......................................... AS 1999-2006 ............70 IN 71 TABLEA4.3. NUMBEREP1-2 SCHOOLS BY AREAINMOZAMBIQUE. OF 1996-2005 TABLEA4.4. NUMBERTEACHERS AND PROPORTIONOFUNQUALIFIEDTEACHERS. OF ............................................ 71 1997 AND 2003 72 TABLEA4.5. PUPIL-TEACHERRATIOTRENDSAT THENATIONALLEVEL. 1992-2005 .................................. 72 TABLEA4.6. PUPIL-TEACHERRATIOSINEP1SCHOOLSBY PROVINCE. 1996-2005 ..................................... 73 2003 .............................................................................................................................................................. TABLEA4.7. NET ENROLLMENT RATESBY SELECTEDGROUPS AND LEVEL EDUCATION.1997 AND OF 73 TABLEA4.8. NET PRIMARY SCHOOL ENROLLMENT. GENDERAND CONSUMPTION QUINTILE. BY 1997 AND 2003 ..................................................................................................................................................... 74 TABLEA4.9. GROSS NETENROLLMENT AND RATIOS. BY GENDER.2005 ..................................................... 74 TABLEA4.10. GROSS ENROLLMENT RATES. BY GENDERAND AREAOF RESIDENCE.2003 .......................... TABLEA4.11. ENROLLMENTSCHOOLBYAGE. CONSUMPTIONQUINTILE AND GENDER.2003 IN ................75 75 TABLEA4.12. GROSS NET AND ENROLLMENT RATES. BY EDUCATIONLEVEL. 1996-2005 .......................... 76 2003 .............................................................................................................................................................. TABLEA4.13. PRIMARY SCHOOL (EP1) COMPLETIONAND DROPOUTRATESBY PROVINCE. 1997 AND 77 TABLEA4.14. BENEFITINCIDENCE:EDUCATIONEXPENDITURE ALLOCATIONBY QUINTILE. 2003 ..............77 TABLEA4.15 BENEFITINCIDENCE:EXPENDITURE ALLOCATION. QUINTILE AND GENDER.2003 ............77 BY TABLEA4.16. PERCEPTIONS OF CHANGESINEDUCATION. AREAOF RESIDENCEAND GENDEROF BY THEHOUSEHOLD 2006 HEAD. ...................................................................................................................... 78 TABLEA4.17. PERCEPTIONSOF CHANGESINEDUCATION. AREAOF RESIDENCEAND ASSET BY TERCILE. 2006 .............................................................................................................................................................. 78 TABLEA4.18. REASONSFORIMPROVEMENTSAND WORSENINGINEDUCATION. AREAOFRESIDENCE. 2006 .............................................................................................................................................................. 79 BY TABLEA4.19. SELECTEDINDICATORS OF GOVERNMENTHEALTHEXPENDITURE. 1999-2003 ..................... 79 vi TABLEA4.20. REASONSFORNOT ACCESSING HEALTHCARE. WOMEN.2003 ............................................... 80 TABLEA4.21. NUMBER OFLIVEBIRTHSATTENDED HEALTHFACILITYAND VACCINATION AT COVERAGE. BY PROVINCE. 1997-2003 ......................................................................................................... 80 TABLEA4.22.REGIONAL COMPARISONOFWELFARE INDICATORS .............................................................. 81 TABLEA4.23. SELECTED SOCIAL OUTCOMEINDICATORS ............................................................................ 82 TABLEA4.24. CHANGESINPREVENTIVECARE AND HOME-BASED 1997-2003 CARE. ................................ 82 TABLEA4.25.PREVENTIVECAREBY WEALTH QUINTILE AND BY AREA OFRESIDENCE. 2003 .................... TABLEA4.26. TREATMENT WHEN SHOWINGILLNESS SYMPTOMS: CURATIVECARE. 1997AND 2003 .........83 83 TABLEA4.27. STUNTINGBYPROVINCE. 1997AND 2003 .............................................................................. 84 TABLEA4.28. PERCEPTIONS OF CHANGES INHEALTH SERVICES. BY AREA OF RESIDENCEAND ASSET TERCILE. 2006 ............................................................................................................................................... 84 TABLEA4.29. REASONSFORCHANGES INHEALTH SERVICES. BY AREAOF RESIDENCE. 2006 .................... 85 TABLEA4.30. PERCEPTIONSOF CHANGESINHEALTHSERVICES.BY AREAOFRESIDENCEAND GENDEROFTHEHOUSEHOLD 2006 HEAD. .................................................................................................... 85 TABLEA4.31.PROAGRIINTOTALAGRICULTURESECTORBUDGET. 86 TABLEA4.32. STRUCTUREOFPROAGRIBUDGET. CURRENT AND INVESTMENT. 2000-05 ......................... 1999-2005 ...................................... 86 TABLEA4.33. PROAGRIBUDGET EXPENDITURE BY COMPONENT.1999-2005 .......................................... 86 TABLEA4.34. DISTRICT COVERAGE FOR EXTENSION SERVICESINMOZAMBIQUE. 2004 .............................. 87 TABLEA4.35. RURALHOUSEHOLDS RECEIVINGEXTENSIONINFORMATION. BY LOCATION AND GENDEROFTHEHEAD. 2002 AND 2005 ....................................................................................................... 87 TABLEA4.36. RURALHOUSEHOLDS RECEIVING EXTENSIONINFORMATION. BY INCOMEQUINTILE. 2005 ............................................................................................................................................................. 88 TABLEA4.37.RURALHOUSEHOLDS RECEIVING EXTENSION INFORMATION. BY INCOMEQUINTILE AND POVERTY TRANSITION STATUS. 2002 AND 2005 ................................................................................... 89 TABLE4.A38. EXTENSION ......................................................... TABLEA4.39. ACCESS SAFEWATERIN MOZAMBIQUE BY AREA.1990.2005. AND 2015........................ WORKERDENSITY MOZAMBIQUE. IN 2004 89 TO 90 TABLEA4.40. OVERVIEW OFWORKING AND PLANNEDWATER POINT SOURCE. BY PROVINCE. 2001-03 ........................................................................................................................................................ 90 TABLEA4.41. DISTRIBUTION TYPESOF WATER USED. BYPROVINCE. QUINTILE AND AREA. OF 1997AND2003 ............................................................................................................................................. 91 TABLEA5.1. HOUSEHOLD CONSTRAINTS TO ACCESS JUSTICE TO ................................................................. 92 TABLEA5.2. ASSESSMENTTHEJUSTICE SYSTEMBY HOUSEHOLD OF ........................................................... 92 TABLEA5.3.RESOLUTIONOFPROBLEMSBY ENTITYINURBAN AREAS.BY GENDEROFHEAD AND WEALTH TERCILE.2006 ........................................................................................................................ 92 TABLE A5.4. RESOLUTIONOF PROBLEMS BY ENTITYINRURAL AREAS. GENDEROF HEAD BY AND WEALTH TERCILE.2006 ........................................................................................................................ 93 TABLEA5.5. URBANPERCEPTIONSOFCHANGEINPOWEROR RIGHTSOFHOUSEHOLDS OVER LAST FIVEYEARS. BY GENDEROF HEADAND WEALTH TERCILE.2006 ...................................................... 93 TABLEA5.6. RURALPERCEPTIONSOF CHANGEINPOWERORRIGHTSOFHOUSEHOLDS OVER LAST YEARS. GENDEROFHEADANDWEALTH TERCILE.2006 FIVE BY ....................................................... 93 TABLE A5.7. AWARENESSHOW TO OBTAIN LAND OF TITLE. BY AREA.GENDEROFHOUSEHOLD HEAD. TERCILE. 2006 TABLEA5.8. REASONSFORLACK TITLE. BY AREAAND GENDEROFHOUSEHOLD 2006 ..............94 AND ............................................................................................................................ OF HEAD. 94 TABLEA5.9.ALLOCATION OFPUBLICSECTORRESOURCESTO COMMUNITY LAND THROUGH PAAO SPGCBUDGETS: 2001-03 ................................................................................................ DELIMITATION 94 TABLEA5.10.DELIMITATION COMMUNITY LAND. PROVINCE. 2003 OF BY 95 TABLEA5.11 HOUSEHOLDSTITLE TO LAND. AREA.2006 TABLEA5 12 HOUSEHOLDPURCHASESAND LAND . .. .................................................. WITH BY ............................................................. 95 LAND TITLE HOLDINGRURALAREAS.BY IN REGION. 1996. 2002 AND 2005 ..................................................................................................................... 96 TABLEA5.13. HOUSEHOLD PURCHASESAND LAND LAND TITLEHOLDING STATUS. BY INCOME QUINTILE. 1996. 2002 AND 2005 .................................................................................................................. 97 TABLEA5.14. DECISIONMAKING RESPONSIBILITYON KEY HOUSEHOLD EXPENDIWRES. HEAD'S RESPONSE. 2006 ............................................................................................................................................ 98 TABLEA5.15. DECISIONMAKING RESPONSIBILITYON KEY URBANHOUSEHOLD EXPENDITURES. BY WEALTH TERCILE. 2006 .......................................................................................................................... 98 TABLEA5.16. DECISIONMAKING RESPONSIBILITYON KEYRURALHOUSEHOLD EXPENDITURES. vii BY WEALTH TERCILE. 2006 .......................................................................................................................... 98 TABLEA5.17. DECISIONMAKING RESPONSIBILITY ON KEYURBANHOUSEHOLD EXPENDITURES, BY RELIGION(MUSLIWNON-MUSLIM), 2006 ..................................................................................................... 98 TABLEA5.18. DECISIONMAKING RESPONSIBILITYON KEYRURALHOUSEHOLD RELIGION(MUSLIM/NON-MUSLIM), 2006 ..................................................................................................... EXPENDITURES, BY TABLEA5.19. DECISIONMAKING RESPONSIBILITY ON KEYHOUSEHOLD TABLEA6.1. AWARENESSHIV/AIDS AND PREVENTIONMETHODS. 2003 ............................................EXPENDITURES, ................... 99 99 2006 OF 100 TABLEA6.2. RATIOOF CURRENT SCHOOLATTENDANCE ORPHANS VERSUSNONORPHANS, OF BY TYPE OF ORPHAN, 2003 .............................................................................................................................. 100 TABLEA6.3. DIFFERENCE-IN-DIFFERENCES OFRURALHOUSEHOLD ANALYSIS COMPOSITIONBY GENDEROFDECEASED PRIME-AGEADULTSIN MOZAMBIQUE, 2002-05 .................................................... 101 TABLEA6.4. PERCENTAGERECEIVINGANTIRETROVIRALCOMBINATIONTHERAPY (HAART) IN MOZAMBIQUE,GENDERAND BYREGION, OCTOBER2005 BY ..................................................................... 102 TABLEA6.5. NUMBERPEOPLERECEIVINGANTIRETROVIRALCOMBINATIONTHERAPY(HAART)IN OF MOZAMBIQUE, 2006 .................................................................................................................................... TABLEA6.6. ANTIRETROVIRAL COVERAGEINMOZAMBIQUENEIGHBORING AND COUNTRIES, 2005 ........102 102 APPENDIX B TABLEB 1 IAFSURVEY SAMPLEBYPROVINCE. 1997AND 2003 104 TABLEB 2 TIA SURVEY SAMPLEBY PROVINCE. 1996. 2002. 2005. AND 2002-05 PANEL ......................... TABLEB 3 SAMPLEFORPOVERTY AND VULNERABILITY ASSESSMENT. ............................................ ... ............................................................... 105 2006 TABLEB 4.POPULATIONDISTRIBUTION ............. 107 110 TABLEB 5.FOODPOVERTYLINES UNDERALTERNATIVERURALAND URBANDEFINITIONS 112 TABLEB 6 POVERTY HEADCOUNT FIXEDAND FLEXIBLEBUNDLE . USINGBASICNEEDSFOODBUNDLES 1997 AND 2003 FOR ................... USING APPROACHES ............................ 113 TABLEB 7.FOOD AND NONFOOD POVERTY LINES. 2003 ............................................................................ 115 ... Vlll AppendixA. ChaDter Tables APPENDIX A. CHAPTER TABLES CHAPTER1 Table Al.l. Poverty Measures,by Area, 1997 and 2003 @ercent) Area Headcount Poverty Gap Squared Poverty Gap 1997 2003 Change 1997 2003 Change 1997 2003 Change All 69.4 54.1 -22.0 29.2 19.9 -31.8 15.5 9.9 -36.1 Urban 63.9 51.6 -19.2 27.2 18.9 -30.5 14.8 9.0 -39.1 Rural 71.6 55.2 -22.9 30.0 20.4 -32.0 15.8 10.3 -34.8 Source: IAF data for 1997 and 2003. Note: Consistentwith the 2003 urbanand rural definitions Table A1.2. PovertyMeasures, by Province, 1997 and2003 (percent) Headcount Poverty Gap Squared Poverty Gap 1997 2003 Change 1997 2003 Change 1997 2003 Change All 69.4 54.1 -22.0 29.2 19.9 -31.8 15.5 9.9 -36.1 Area Urban 63.9 51.6 -19.2 27.2 18.9 -30.5 14.8 9.0 -39.1 Rural 71.6 55.2 -22.9 30.0 20.4 -32.0 15.8 10.3 -34.8 Province Niassa 69.9 49.5 -29.2 29.1 14.5 -50.2 15.3 6.2 -59.5 Cab0 Delgado 56.8 62.8 10.6 19.2 20.8 8.3 8.8 8.9 1.1 Nampula 68.7 53.6 -22.0 28 18.7 -33.2 14.7 8.6 -41.5 Zambezia 68 45 -33.8 25.2 13.4 -46.8 11.7 5.6 -52.1 Tete 80.3 58.7 -26.9 38.5 25.7 -33.2 22.2 14.9 -32.9 Manica 62.3 44.4 -28.7 23.3 16.8 -27.9 11.1 9.1 -18.0 Sofala 88.2 34.1 -61.3 48.9 10.1 -79.3 31.8 4.1 -87.1 Inhambane 83.8 81.1 -3.2 37.4 42.1 12.6 20.2 25.8 27.7 Gaza 65.4 59.7 -8.7 23.2 19.9 -14.2 11.1 8.8 -20.7 Maputo 64.8 71 9.6 27.4 30.9 12.8 14.5 16.9 16.6 Maputo city 47.3 53.2 12.5 15.7 20.1 28.0 7.3 9.8 34.2 Source: IAF data for 1997 and 2003 data. Note: Consistent with 2003 urbanand rural definitions. 9 Amendix A. ChaDter Tables Table A1.3. Access to Land, by Area, Gender,and Wealth of Head, 2006 (percent) Urban Rural Male Female Male Female Tercile All Head Head All Head Head All 54.6 55.5 52.8 80.4 80.9 79.2 Poorest 53.2 50.0 57.1 74.7 77.1 72.1 Richest 49.6 54.2 38.2 86.7 85.7 92.3 Source: Authors' calculations basedon PVS data for 2006. Note; Sample not representative. Table A1.4. UrbanHouseholdHeadEmploymentSector, by Gender of Head and Wealth Tercile, 2006 (percent) All Household Heads Male Household Head Female Household Head 1st 1st 1st Sector All Tercile 3rd Tercile All Tercile 3rd Tercile All Tercile 3rd Tercile Agriculture 42.2 55.6 21.8 37.1 54.0 19.7 54.0 58.1 28.0 Mining 0.0 0.0 0.0 0.0 0.0 0.o 0.0 0.o 0.0 Manufacturing 0.7 1.2 1.o 1.o 2.0 1.3 0.0 0.0 0.0 Construction 0.7 1.2 0.0 1 .o 2.0 0.0 0.0 0.0 0.0 Transport 3.8 1.2 5.9 5.4 2.0 7.9 0.0 0.0 0.0 Trade 25.6 24.7 23.8 22.8 18.0 18.4 32.2 35.5 40.0 Services 14.9 13.6 19.8 19.3 20.0 22.4 4.6 3.2 12.0 Education 6.6 1.2 15.8 6.9 2.0 17.1 5.7 0.0 12.0 Health 3.1 1.2 5.9 3.O 0.0 5.3 3.4 3.2 8.O Public administration 2.4 0.0 5.9 3.5 0.0 7.9 0.0 0.0 0.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Source: Authors' calculations based on PVS data for 2006. Note: Sample not representative. Table A1.5. RuralHouseholdHead EmploymentSector, by Genderof Head and Wealth Tercile, 2006 (percent) All Male Head Female Head 1st 1st Sector All Tercile 3rd Tercile All 1st Tercile 3rd Tercile All Tercile 3rd Tercile Agriculture 73.3 82.3 61.6 65.0 71.1 56.2 96.9 97.1 92.3 Mining 0.0 0.0 0.0 0.o 0.0 0.0 0.0 0.0 0.o Manufacturing 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.o Construction 0.4 0.0 1.2 0.5 0.0 1.4 0.0 0.0 0.0 Transport 0.4 0.o 0.0 0.5 0.0 0.0 0.o 0.0 0.0 Trade 13.4 7.6 20.9 18.0 13.3 24.7 0.0 0.0 0.0 Services 6.5 3.8 8.1 8.7 6.7 9.6 0.0 0.0 0.0 Education 4.9 5.1 5.8 6.6 8.9 6.8 0.0 0.0 0.0 Health 0.4 1.3 0.0 0.0 0.0 0.0 1.6 2.9 0.0 Public administration 0.8 0.0 2.3 0.5 0.0 1.4 1.6 0.0 7.7 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Source: Authors' calculations basedon PVS data for 2006. Note: Sample not representative. 10 AppendixA. Chapter Tables Table A1.6. Shocks Experienced by Urban HouseholdsduringLast 12 Months,by Gender of Headand Wealth Tercile, 2006 (percent) All Male Head Female Head Shock All Terciles Poorest Tercile All Terciles Poorest Tercile All Terciles Poorest Tercile Drought 17.7 17.1 22.5 24.2 8.8 8.2 Floods 0.3 0.9 0.0 0.0 0.8 2.0 Insectsand animalsdestroyed crops 10.5 12.6 12.7 14.5 6.4 10.2 Illness of family member 31.9 36.9 35.6 38.7 24.8 34.7 Deathof family member 16.3 17.1 14.4 12.9 20.0 22.4 Loss o f work 2.2 1.8 3.O 0.8 0.8 0.0 Other 0.6 0.0 0.4 0.0 0.8 0.0 Source: Authors' calculations based on PVS data for 2006. Note: Sample not representative. Table A1.7 Shocks Experienced by Rural Householdsduring Last 12 months, by Gender of Headand Wealth Tercile, 2006 (percent) All Male Head Female Head All Shock Terciles Poorest Tercile All Terciles Poorest Tercile All Terciles Poorest Tercile Drought 26.1 34.1 25.6 27.1 27.3 41.9 Floods 0.4 1.1 0.0 0.0 1.3 2.3 Insectsand animals destroyed crops 22.5 25.3 27.1 33.3 10.4 16.3 Illness offamily member 45.3 53.8 46.7 47.9 41.6 60.5 Deathof family member 16.7 9.9 14.6 0.0 22.1 20.9 Loss of work 0.4 0.0 0.5 0.0 0.0 0.0 Other 0.0 0.0 0.0 0.0 0.0 0.0 Source: Authors' calculations based on PVS data for 2006. Note: Sample not representative. Table A1.8. Coping Strategies in Responseto Shocks duringthe Last 12 Months, by Area and Income Group,2006 (percent) Urban Household Rural Household Coping strategies All Terciles Poorest Tercile All Terciles Poorest Tercile Sale of goods 5.9 2.7 9.0 9.0 Remove children from school 0.0 0.0 0.0 0.0 Put children to work 0.0 0.0 0.o 0.0 Help from family and friends (within community) 61.3 68.5 48.4 44.8 Helpfrom family and friends (outside community) 40.2 37.0 23.4 29.9 Helpfrom NGOs 0.5 1.4 0.5 0.0 Helpfrom local government 0.0 0.0 1.1 1.5 Helpfrom central government 0.5 0.0 0.0 0.0 Casualwagejob 2.5 3.6 5.4 7.7 Petty trade 0.8 0.9 2.5 0.0 Do nothing 9.7 10.8 18.5 20.9 Other (includingfishing) 0.3 0.9 0.7 0.0 Source: Authors' calculations basedon PVS data for 2006. Note: Sample not representative. 11 Appendix A. Chapter Tables TableA1.9. Coping Strategiesin Communities Visited, 2006 Coping Strategy Social Group Casualday labor (on farms of others, also includesnonagriculturalwork) All, but predominantlymen and maleyouth Collectionofwild fruits, roots, and vegetables (mainly for consumption) Women and children Collection, preparation, and sale of firewood and charcoal Male youth Relying on remittances All Selling, consuming, or drawing down existinghouseholdassets All Borrowing from friends and family All (those likely to reciprocate) Begging All (those with few assets left) Early marriage Young girls Prostitution Women, female youth, young girls Social networks All (limited to thosewith ability to reciprocate) Source: Authors' calculations basedon PVS data for 2006. Note: Sample not representative. Table A1.10. SchoolAttendance by Orphan Status, Area, andWealth Tercile, 2006 (percentageof children, aged 6-1 7) Urban Household Rural Household Orphans status All 1st Tercile 3rd Tercile All 1st Tercile 3rd Tercile All nonorphans 96.5 95.2 98.7 91.6 87.5 94.5 All orphans 89.7 75.0 96.0 79.2 75.0 83.3 Male nonorphans 97.7 96.3 98.4 91.5 86.2 93.8 Male orphans 91.4 88.9 92.9 78.3 75.0 80.0 Female nonorphans 95.2 94.4 99.0 91.7 89.5 95.3 Female orphans 87.8 63.6 100.0 80.0 75.0 85.7 Source: Authors' calculations basedon PVS data for 2006. Note: Sample not representative. Table Al.ll. Ratio of SchoolAttendance of Orphansversus Nonorphans,Aged 10-14,1997 and 2003 (percent) Gender 1997 2003 All 0.47 0.80 Male 0.44 0.89 Female 0.50 0.73 Source: GoM (2006) basedon DHS data. 12 Amendix A. ChaDter Tables Table A1.12. Participationin DomesticChoresand Leisureof ChildrenAged 0-17, by Orphan Status, Area, and Gender,2006 (percent) Activities Urban Household Rural Household Nonorphan Orphan Nonorphan Orphan All Male Female All Male Female All Male Female All Male Female Cooking 35.7 19.5 53.4 40.0 17.2 66.1 21.5 3.9 38.3 51.0 26.9 76.0 Washing 50.0 36.7 64.4 63.3 50.0 78.6 29.9 19.5 39.8 51.0 38.5 64.0 Cleaning 52.3 43.4 62.0 61.7 48.4 76.8 35.6 30.5 40.6 47.1 42.3 52.0 Shopping 30.9 27.9 34.1 37.5 29.7 46.4 13.4 14.1 12.8 25.5 30.8 20.0 Caring for the elderly and children 14.3 7.1 22.1 18.3 4.7 33.9 13.4 9.4 17.3 9.8 3.8 16.0 Rearing of animals 6.7 9.3 3.8 5.8 9.4 1.8 8.0 14.8 1.5 7.8 3.8 12.0 Agricultural work 5.1 4.4 5.8 6.7 3.1 10.7 12.6 12.5 12.8 21.6 19.2 24.0 Collection of firewood 13.8 14.6 13.0 11.7 12.5 10.7 33.0 28.1 37.6 54.9 53.8 56.0 Fetching of water 53.7 47.8 60.1 56.7 43.8 71.4 58.6 41.4 76.0 80.4 69.2 92.0 Community work 0.5 0.9 0.0 0.0 0.0 0.0 0.4 0.0 0.8 0.0 0.0 0.0 House maintenance 6.7 5.8 7.7 19.2 23.4 14.3 0.8 1.6 0.0 3.9 7.7 0.0 Food processing 36.2 24.3 49.0 35.0 20.3 51.8 32.6 22.7 42.1 47.1 38.5 56.0 Leisure 30.6 31.0 30.3 55.0 56.3 53.6 28.7 28.9 28.6 25.5 19.2 32.0 Source: Authors' calculations basedon PVS data for 2006. Note: Sample not representative. Table A1.13. Human Development Index and Gender-RelatedDevelopmentIndex-Levels and Trends, 1975-2004 (percent) Gender- Related Development Country 1975 1980 I985 1990 1995 2000 2004 2004 Malawi 0.327 0.357 0.368 0.372 0.414 0.398 0.400 0.394 Mozambique - 0.302 0.290 0.316 0.330 0.364 0.390 0.387 South Africa 0.653 0.673 0.703 0.735 0.741 0.691 0.653 0.646 Tanzania - - - 0.437 0.423 0.420 0.430 0.426 Uganda - - 0.414 0.411 0.413 0.474 0.502 0.498 Zambia 0.470 0.477 0.486 0.464 0.425 0.409 0.407 0.396 Zimbabwe 0.548 0.576 0.642 0.639 0.591 0.525 0.491 0.483 Source: UNDP 2006a. -isnotavailable. 13 AppendixA. Chapter Tables TableA1.14. Self-Assessmentof Welfare Relativeto Others in the Community,2006 (percent) Urban Rural Male Female Male Female Self-assessment All Head Head All Head Head 1-Poorer 31.3 24.6 44.0 39.9 33.2 57.1 2 28.8 31.8 23.2 22.5 22.6 22.1 3 19.1 17.8 21.6 16.3 17.1 14.3 4 8.6 10.2 5.6 12.3 15.1 5.2 5 8.3 10.6 4.0 4.7 6.5 0.0 6 3.0 3.8 1.6 2.2 2.5 1.3 7 0.3 0.4 0.0 0.4 0.5 0.0 8 0.3 0.4 0.0 0.7 1.0 0.0 9 0.3 0.4 0.0 1.1 1.5 0.0 10-Less poor 0.0 0.0 0.0 0.0 0.0 0.0 Source:Authors' calculations based on PVS data for 2006. Note: Sample not representative. Table A1.15. Householdsthat Have ExperiencedHunger duringthe Last 12 Months,by HouseholdHead and Tercile, 2006 (percent) Urban Rural Householh All Terciles Poorest Tercile All Terciles Poorest Tercile All 43.2 58.6 52.5 67.0 Male head 48.3 61.3 54.3 64.6 Female head 33.6 55.1 48.1 69.8 Source: Authors' calculations basedon PVS data for 2006. Note: Sample not representative. Table A1.16. Number of Meals ConsumedduringPrevious Day, 2006 (percent) Urban Rural Number of Male Female Male Female meals All Head Head All Head Head One 12.2 8.1 20.0 9.8 8.0 14.3 Two 51.0 54.2 44.8 58.7 57.3 62.3 Three 36.8 37.7 35.2 31.5 34.7 23.4 Total 100 100 100 100 100 100 Source:Authors' calculations basedon PVS data for 2006. Note: Sample not representative. 14 Appendix A. Chapter Tables Table A1.17. Perceptionof Change in HouseholdPovertyin RuralAreas over Last Five Years, 2006 (percent) Perception All Household Heads Male Household Heads Female Household Heads 1st 3rd 1st 3rd 1st 3rd All Tercile Tercile All Tercile Tercile All Tercile Tercile Improved 26.8 11.0 45.6 32.2 16.7 48.1 13.0 4.7 30.8 Worse 40.6 61.5 24.4 37.2 54.2 54.2 49.4 69.8 30.8 No change 32.6 27.5 30.0 30.7 29.2 28.6 37.7 25.6 38.5 Total 100 100 100 100 100 100 100 100 100 Source:Authors' calculations basedon PVS data for 2006. Note: Sample not representative. Table A1.18. Perceptionof Change in HouseholdPovertyin Urban Areas over Last Five Years, 2006 (percent) Perception All Household Heads Male Household Heads Female Household Heads 1st 1st 3rd 3rd All Tercile 3rd Tercile All Tercile Tercile All 1st Tercile Tercile Improved 25.2 11.7 42.7 28.4 17.7 43.4 19.2 4.1 41.2 Worse 37.7 51.4 23.9 37.3 45.2 25.3 38.4 59.2 20.6 No change 37.1 36.9 33.3 34.3 37.1 31.3 42.4 36.7 38.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Source:Authors' calculations basedon PVS data for 2006. Note: Sample not representative. Table A1.19. Predictionof Change in HouseholdWell-Being over Next Five Years, 2006 Urban Households Rural Households Male Female Male Female Prediction All Head Head All Head Head It will improve 37.4 39.8 32.8 21.7 26.1 10.4 It will worsen 11.9 12.7 10.4 14.5 13.1 18.2 It will remain unchanged 50.7 47.5 56.8 63.8 60.8 71.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 Source:Authors' calculationsbasedon PVS data for 2006. Note: Sample not representative. 15 Appendix A. Chapter Tables Table A1.20. PopulationDistributionacross Consumption Quintiles, by Area and Gender of HouseholdHead, 1997 and 2003 (percent) Lowest 2nd 3rd 4th Highest Quintile Quintile Quintile Quintile Quintile Total Area Urban 1997 19.1 16.6 19.4 18.5 26.2 100.0 2003 19.3 19.6 18.5 17.1 25.2 100.0 Rural 1997 20.3 21.5 20.5 20.4 17.7 100.0 2003 20.3 20.1 20.6 21.3 17.4 100.0 Gender of head Male 1997 20.2 20.1 20.3 19.5 19.8 100.0 2003 19.0 19.6 20.0 20.6 20.8 100.0 Female 1997 19.0 19.6 18.2 22.2 20.7 100.0 2003 23.8 21.2 20.1 18.1 16.8 100.0 All 20.0 20.0 20.0 20.0 20.0 100.0 Source: IAF data for 1997 and 2003. Note: The quintiles are inMeticais per day (in2003 realterms). Consistent with 2003 urban and rural definitions. Table A1.21. PopulationDistributionacross Wealth Terciles, by Area and Gender of HouseholdHead,2006 (percent) 1st Tercile 2nd Tercile 3rd Tercile Total Urban All 30.7 36.8 32.4 100.0 Male head 26.3 38.6 35.2 100.0 Female head 39.2 33.6 27.2 100.0 Rural All 33.0 35.8 32.5 100.0 Male head 24.1 37.2 38.7 100.0 Female head 46.7 33.3 27.7 100.0 Source: Authors' calculations based on PVS data for 2006. Note: Sample not representative. 16 AtmendixA. ChaDter Tables Table A1.22. HouseholdCharacteristics, by ConsumptionQuintile, 1997and 2003 (percent) Characteristic anddate Lowest 2nd 3rd 4th Highest All Demographics Household size 1997 6.4 5.7 5.0 4.3 3.5 4.8 2003 6.0 5.4 4.8 4.3 4.0 4.8 Disabled adult(s) 1997 9 8 8 6 6 7 2003 10 8 6 6 5 7 Number o f children 0-5 1997 1.2 1.1 0.9 0.8 0.6 0.9 2003 1.4 1.2 1.o 0.9 0.8 1.o Number of children 6-9 1997 0.9 0.9 0.7 0.6 0.4 0.6 2003 0.8 0.7 0.6 0.5 0.4 0.6 Number o f children 10-14 1997 1.1 0.9 0.8 0.6 0.4 0.7 2003 0.9 0.8 0.6 0.5 0.4 0.6 Dependency ratioa 1997 1.14 1.16 1.08 0.97 0.77 0.99 2003 1.54 1.43 1.21 1.08 1.04 1.23 Head characteristics Age of household head 1997 46 43 42 41 40 42 2003 46 43 42 42 41 43 Female head 1997 20 20 19 24 23 21 2003 27 25 23 25 25 25 Head no education 1997 50 48 41 41 32 41 2003 38 32 29 31 21 29 Head in agriculture 1997 87 86 82 84 74 82 2003 80 80 82 79 60 75 Rural population 1997 81 84 80 83 70 80 2003 69 68 71 73 59 68 Source: IAF data for 1997 and2003. a. Economic dependency ratio (number of people not working divided by the number ofpeople working). b. Rural population is calculated at the individual level. It counts the percentageof individuals (rather than household heads) living inruralareas. Consistentwith 2003 urban andrural definitions. 17 Amendix A. ChaDter Tables Table A1.23. Access to Services by Quintile, Region, and Area, 1997 and 2003 (percent) All Lowest 2nd 3rd 4th Highest Service I997 2003 1997 2003 I997 2003 1997 2003 1997 2003 1997 2003 Water Use safe water 24 37 24 38 20 32 20 35 22 34 30 45 <30' to water 69 90 71 85 69 89 69 91 68 90 71 94 Sanitation Latrinea 35 45 29 47 33 46 33 41 35 38 41 52 Electricity Used inhouseholdb 4 7 1 1 1 3 1 4 4 5 11 18 Health Recently ill' 11 16 9 14 11 15 11 16 13 18 14 17 Seeking helpd 51 56 46 53 49 53 49 56 54 53 54 66 <30' health postd - 35 - 33 - 30 - 35 - 32 - 42 Education Enrolled 7-12 51 71 39 65 48 68 50 69 58 72 62 79 Enrolled 12-18 3 6 1 3 1 4 2 6 4 7 8 13 <30' primarye 73 72 73 72 - 73 - 74 <30' secondary - 15 - 14 - 14 - 12 - 12 - 23 North Central South Urban Rural 1997 2003 1997 2003 I997 2003 1997 2003 I997 2003 Water Use safe water 18 34 19 69 45 47 51 64 13 27 <30' to water 72 93 67 89 67 86 84 97 62 87 Sanitation Latrinea 33 39 18 29 72 78 57 72 26 33 Electricity Used inhouseholdb 2 4 2 4 12 15 15 22 0.5 0 Health Recently ill' 14 18 10 16 7 11 10 14 12 17 Seeking helpd 49 50 47 55 63 69 67 74 44 50 <30' health postd - 35 - 25 - 50 71 68 52 21 Education Enrolled 7-12 45 60 41 69 69 87 64 82 43 65 Enrolled 13-18 0.5 3 2 4 6 12 7.5 15 0.6 1 <30' primary' - 77 - 66 - 77 - 91 - 65 <30' secondary - 8 - 10 - 34 - 41 - 4 Source: IAF data for 1997 and2003. Note: Consistentwith 2003 urbanandruraldefinitions. a.Use of latrine includes latrines, improved latrines, andbetter sanitation types, such as toilet and bathroom. b. Electricityused for cooking and lighting. c. Incidenceillis not fully comparable betweenboth survey years: recall period 1997 was one month while recall period 2003 was two weeks. d. Went for medicaladvice when sick, seeking help from traditional healers excluded. e. Distance (time) to sanitary post and school: only available at the householdlevel for 2003 (in 1997 the question was included inthe communityquestionnaire). f.The significance ofthe differencebetweenbothyears was testedfor the fullsample andsignificantat the 1percentlevelfor all variables. -isnotavailable. 18 Appendix A. Chapter Tables Table A1.24. Net Secondary SchoolEnrollment,by Gender and Consumption Quintile, 1997 and 2003 (percent) All Girls Boys 1997 2003 1997 2003 1997 2003 Quintile National Lowest 1.1 3.4 0.4 3.1 1.8 3.7 Highest 8.1 12.5 8.0 9.6 8.4 15.6 All 3.0 6.4 2.8 5.4 3.2 7.3 Rural Lowest 0.7 1.5 0.2 1.3 1.1 1.6 Highest 0.4 0.6 0.3 0.5 0.5 0.8 All 0.6 1.0 0.3 0.9 0.9 1.0 Urban Lowest 2.1 7.4 1.2 6.3 2.8 8.4 Highest 15.8 23.5 15.7 19.8 16.0 26.8 All 7.5 15.4 7.3 12.8 7.7 17.8 Region North 0.5 3.7 0.1 2.5 0.9 4.6 Central 1.8 4.3 1.5 2.8 2.0 5.8 South 6.6 12.0 6.1 11.1 7.0 12.8 Source: Authors' calculations basedon IAF data for 1997and 2003. Note: Consistent with 2003 urbanandrural definitions. Table A1.25. Effect of Educationand Informationon Childcareand Child Height- for-Age, 2003 (percent) Variables Effects on Childcare Effects on Child Height- Practices Indexa for-Age All Rural Urban All Rural Urban Childcare index (predicted) ++ ++ Mother's years of education +++ +++ +++ +++ Years o f education squared +++ +++ +++ ++ Household owns radiob +++ +++ ++ Household owns bicycleb +++ Source: DHS data for 2003. Note: The childcare practices index was constructed including whether the mother knows or practices the following: giving vitamin-A-rich fruit or supplements to increase resistance to diseases; putting children to sleep under mosquito nets to protect the child against malaria; giving more liquids when a child has diarrhea to prevent dehydration; feeding the child breast milk to strengthen the child's immunization system; breastfeeding for first six months to provide the child with the necessary foods andto increaseprotection;vaccinatingthe child to protectit againsteasily preventable diseases, suchas polio or measles; or that prenatal care, or alack of care, can already affect the child's nutritional status. a.The first three columns representthe effects the variables have on estimatingthe index on childcare practices; the result of this estimation is a predictedchildcare practice variable, which is then included inthe analysis ofthe determinantsof child height-for-agerepresentedinthe last three columns. b.0wnership of radio and bicycles are assumed not to affect child height-for-age directly but only affectthe childcarebehavior. +++ is highly significantly positive at the 1percent level. ++is moderately significantly positive at the 5 percent level. + is weakly significantly positive at the 10percent. 19 Appendix A. Chapter Tables Table A1.26. Constraintsto Healthcare,2006 (percent) Urban Rural Constraint All Terciles Poorest Tercile Richest Tercile All Terciles Poorest Tercile Richest Tercile Lack o fhealth posts 2.3 0.0 9.1 8.3 13.3 11.1 Distance 0.0 0.0 0.0 35.0 13.3 44.4 Quality o ftreatment 60.5 68.8 54.5 21.7 33.3 5.6 Waiting time 14.0 12.5 27.3 0.0 0.0 0.0 Lack of medications 18.6 12.5 9.1 35.0 40.0 38.9 costs 2.3 6.3 0.0 0.0 0.0 0.o Lack of rooms 2.3 0.0 0.0 0.0 0.0 0.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 Source: Authors' calculationsbasedon PVS data for 2006. Note: Sample not representative. TableA1.27. Food Share and Ownershipof HouseholdAssets by Quintile and Area, 1997 and 2003 hercent) Asset All Lowest 2nd 3rd 4th Highest Urban Rural 1997 2003 1997 2003 1997 2003 1997 2003 1997 2003 1997 2003 2003 2003 Foodshare 68 61 67 60 70 63 70 64 69 64 63 52 50 66 Durable goods Radio 29 65 20 59 26 63 25 65 28 66 38 68 65 65 TV 5 9 1 4 2 5 3 5 4 7 11 19 23 1 Clock 24 43 14 34 21 38 24 35 23 41 32 58 60 34 Motorbike 1 2 0 0 0 1 1 1 1 1 3 4 3 1 Bicycle 13 40 10 28 15 35 12 39 14 44 15 47 23 50 Housinga Durablewall 31 85 23 74 24 83 31 88 32 87 39 90 87 85 Durableroof 16 25 11 27 12 25 16 19 15 18 23 34 56 11 Source:IAF data for 1997 and2003. a. Durable wall includes stone and wood walls; durable roofincludes concrete, tile, halite, andzinc roofs. The nondurablewalls or roofs consist of naturalmaterials, suchas reedand leaves. They also includethe category "other." 20 Appendix A. Chapter Tables Table A1.28. Knowledge and Practices of Mothers, 2003 (percent,, All under Knowledge Knows to Age Five and Heard of Ever Used Give More Sleeping Vitamin-A Practice Children Oral Oral Liquid under Fruit Last Score under age Rehydration Rehydration during Mosquito 24 Hours (between-5 Jive" 'Salts Salts Diarrhea Net (lastborn) and IO) All 88 10 51 2 21 3.2 Area Rural 86 8 44 1 21 2.6 Urban 96 14 70 4 20 4.6 Quintile Lowest 79 7 40 1 19 1.9 2nd 86 8 40 1 20 2.6 3rd 90 13 49 2 22 3.2 4th 95 12 59 3 25 4.2 Highest 98 12 78 6 20 5.1 Source: DHS data for 2003. Note: Mothers o f children under age five only. a. Base for percentage calculations are children under age five. 21 ** ** ** ** * * * * ** ** ** ** ** * m ;8 8 8 ; W P- 00 2 drc) ea 00 N c c hl hl m o o s m c c - ? 9 9 8 - m m c c ? ? 0 ? -0 00 70 ** ** * * ** * c 8 ? Nm 9 rc) 2 m c hl 4 9 4 2 a9 8 ** ** ** **1 ** * ** 1 ** ** * * 1 * ** ** ** ** ** * c m 8 8 m 00 -4: 2 c 8 8 7 QI z m ea *m c 0 * * ** ** ** ** 8 rc) c ? cc W 3 0 00 0 m d hl ? 4 ? 8 9 0 * : : : : ; ** * * * * * ::::: *** * * * * * ** *** * * * * I * ** *E: : : : * * * * *** * * * ** ** ** *** ** ** * * * :: *:: E : : * * * * *** * * * * * * * ** *I* * * * * * * * * * I\ a ? Appendix A. Chapter Tables Table A1.30. Characteristics of Household by Gender of Household Head, 2003 (percent) Characteristic Female Head Male Head Total Poor 62.5 51.9 54.1 Disabled adult(s) 6.0 7.4 7.0 Head no education 51.9 22 29 Dependencyrates 1.44 1.16 1.23 Rural 68.9 70.6 70.2 Head in agriculture 86.2 71.5 75.2 Source: IAF data for 2003. 24 Annendix A. Chanter Tables CHAPTER 2 TableA2.1. GDP by ExpenditureCategory, Share and Growth Rate, 1996- 2003 (percent) AverageAnnual Share of GDP GrowthRate I996 2003 1996-2003 GDP 100.0 100.0 8.9 Consumption 97.0 89.4 7.6 Private 89.9 79.0 6.9 Public 7.1 10.3 14.9 Investment 21.8 27.4 12.5 Private 10.6 15.7 15.1 Public 11.2 11.7 9.6 Exports-imports -18.8 -16.8 7.2 Source: World Bank staff estimates. Table A2.2. Accounting for GDP Growth by Factor of Production (actual share of GDP growth) Total Factor Fixed Capital Human Capital Real GDP Productivity (r) (A) Government Private Unskilled Skilled 1993-2004 Actual 7.5 2.6 1.o 2.5 0.0 1.3 Share 100.0 34.6 13.5 33.6 0.6 17.8 1993-98 Actual 7.6 3.4 1.o 2.1 0.4 0.7 Share 100.0 44.8 12.9 28.3 5.1 8.9 1999-2004 Actual 7.4 1.8 1.o 2.9 -0.3 2.0 Share 100.0 24.0 14.1 39.1 -4.1 27.0 I981-2004 Actual 2.6 0.3 0.5 0.7 0.1 0.9 Share 100.0 10.6 20.4 28.3 5.8 35.0 Source: Jones 2006. 25 Appendix A. ChapterTables TableA2.3. International and DomesticTerms of Trade, 1996-2003 (percent) Year Domestic International 1996 1.oo 1.oo 1997 1.oo 1.07 1998 0.90 0.98 1999 0.85 0.94 2000 0.82 1.03 2001 0.79 1.oo 2002 0.78 0.96 2003 0.75 0.94 Source: World Bank staffestimates. Note: Domesticterms oftrade equals agriculturalprice index divided by nonagricultural price index. Table A2.4. Average Annual Growth Rate ofAverage Consumption, by Quintile and Area, 1997-2003 (percent) Quintile Total Rural Urban Lowest 4.3 4.4 4.1 2nd 3.9 4.3 3.0 3rd 4.4 4.6 4.0 4th 4.8 5.3 3.4 Highest 6.2 6.3 5.7 Source: IAF data for 1997 and2003. Note: Consistent with 2003 urbanand rural definitions. Table A2.5. Measures of Inequality, 1997 and 2003 (percent) Gini Theil Area 1997 2003 1997 2003 Urban 0.47 0.48 0.373 0.462 Rural 0.37 0.37 0.231 0.256 All 0.40 0.42 0.286 0.343 Decomposition of Inequality: Rural and Urban (percent of total inequality) 1997 2003 Inequality within rural and urban areas 97.9 97.7 Rural-urban gap 2.1 2.3 Source: IAF data for 1997 and2003. Gini data comes from GoM (2005). Note: Consistent with 2003 urbanand rural definitions. Gini coefficient basedon consumptionper capita andtheil basedon consumptionper adult equivalent. 26 Appendix A. Chapter Tables Table A2.6. GiniCoefficientfor Various Countries (uercenti Survey Country Year Gini Ethiopia 2000 0.300 India Rural 2004 0.305 Urban 2004 0.376 Pakistan 2004 0.312 Bangladesh 2000 0.334 China Urban 2004 0.340 Rural 2004 0.381 United Republic of Tanzania 2000 0.346 Indonesia (Urban) 1990 0.347 Malawi 2004 0.390 Morocco 1998 0.395 Burkina Faso 2003 0.396 Kenya 1997 0.425 Cameroon 2001 0.446 Uganda 2002 0.458 Mozambique 2002 0.420 Zambia 2004 0.507 El Salvador 2002 0.523 Brazil 2004 0.570 South Africa 2000 0.578 Source: World Bank,http://www.worldbank.org/lsms/tools/povcatl.Datafor Mozambique comes from GoM (2005). 27 Appendix A. Chapter Tables Table A2.7. Decompositionof Changein Poverty, by Growth and Inequality Dimensions,1997-2003 (percentagepoints ofpoverty reduction) Total Change in Change Change in Mean in Poverty Consumption Inequality Residual Total change inpoverty (national) -15.3 -16.9 1.3 0.5 Urban-rural Urban poverty -12.5 -15.8 3.7 -0.4 Rural poverty -16.3 -15.7 -0.6 -0.02 Share of Population by Total Change in Change Sector of Change in Mean in Employment of the Poverty Consumption Inequality Residual Head 1997-2003 Household headsector of activity Agriculture -14.4 -13.0 -0.7 -0.7 78.7 71.3 Industry -8.9 -19.3 6.9 3.5 7.6 5.3 Service (private) -9.2 -1 1.2 -0.8 2.7 9.4 17.5 Service (public) -19.9 -22.6 0.8 1.9 4.1 5.8 Source: IAF data for 1997 and2003. Note: A negative number representsthe percentagepoint fall inthe incidence of poverty; a positive number is the percentage point increase in poverty. Householdhead sector of activity is determined by the sector where the household head is employed. Ifthe head is not employed, the sector of employment of the oldest adult is used. If nobody works (less than 5 percent of all cases) they are assignedto agriculture. Service (private) includestrade, transport, and services. Service (public) includes health, education, and public administration. Consistent with 2003 urban andrural definitions. 28 Amendix A. ChaDter Tables Table A2.8. GDP, Labor Force, Productivity, and Poverty, by Sector, 1997-2003 (percent) Annual Average Growth Share of GDP (percent) Rate 1997 2003 1997-2003 GDP 100.0 100.0 9.0 Agriculture 34.4 27.3 5.4 Industry 16.0 26.9 17.4 Services(private) 40.9 37.2 7.5 Services (public) 8.7 8.6 8.8 Share of Labor Force 1997 2003 1997-2003 Laborforce 100.0 100.0 0.8 Agriculture 89.7 81.7 -0.8 Industry 3.4 3.1 -0.6 Services (private) 5.0 12.3 17.1 Services (public) 1.8 2.9 8.7 Average Productivitf Annual Average Growth rate 1997 2003 1997-2003 All 4.0 6.5 8.4 Agriculture 1.5 2.1 5.6 Industry 18.2 54.1 19.9 Services (private) 31.6 20.2 -7.2 Services (public) 19.3 19.8 0.4 Annual Change Poverty Headcount in Poverty Rate 1997 2003 1997-2003 All 69.2 54.1 -4.0 Agriculture 72.6 58.2 -3.6 Industry 65.4 54.0 -3.1 Services (private) 54.6 44.4 -3.4 Services (public) 56.0 32.9 -8.5 Source: World Bank staffestimatesand IAF data for 1997 and 2003. Note: Service (private) includes trade, transports, and services. Service (public) includeshealth, education, and public administration. a. Average productivity equals sector GDPdivided by sector employment. 29 Appendix A. Chapter Tables Table A2.9. Decomposition of Changes in Poverty by Location and Sector, 1997 and 2003 (percent) Decomposition Level and Population Share Change 1997 2003 Mozambique Poverty in 1997 69.4 Poverty in2003 54.1 Total change inpoverty 1997-2003 -15.3 Regional By Region Change inpoverty inthe north -3.7 North 32.3 32.3 Change inpoverty inthe central -1 1.7 Central 41.9 41.9 Change inpoverty inthe south 0.12 South 25.7 25.7 Total intraregionalcomponent -15.3 Populationshift (regional migration) 0.0 Interactioncomponent(residual) -0.0 Urban-rural By Area of Residence Change inurbanpoverty -3.6 Urban 29.0 32.0 Change inruralpoverty -1 1.6 Rural 71.0 68.0 Total intrasectoralcomponent 15.2 Populationshift (urban-ruralmigration) -0.22 Interaction component (residual) 0.11 Aggregate sectors (by head of household) By Sector ofEmployment of the Head Change inagriculturepoverty -11.1 Headinagriculture 78.7 71.3 Change in industry poverty -0.8 Headinindustry 7.6 5.3 Change inservice (private) poverty Headin services (private) 9.4 17.5 Change inservice (public) poverty -0.9 Head inservices (public) 4.1 5.8 Total intrasectoralcomponent -13.9 Populationshift (sector shift) -1.5 Interactioncomponent(residual) 0.10 Source: Authors' calculationsbasedon IAF data from 1997 and 2003. Note: Consistent with 2003 urban and rural definitions. Individuals are assigned to the sector where the householdheadis employed. Ifthe head is not employed, they are assignedto the sector ofemployment of the oldest adult. If nobody works (less than 5 percent o f all cases), they are assigned to agriculture. Service (private) includes trade, transport, and services. Service (public) includes health, education, and public administration. North includes Niassa, Cab0 Delgado, and Nampula; center includes Sofala, Tete, Manica, andZambezia; and south includesGaza, Inhambane, Maputo province, andMaputo city. 30 Appendix A. ChapterTables Table A2.10. OccupationalStatus of Population,by Gender, 1997 and2003 (percent) Status 1997 2003 Working 69.2 68.5 Male 32.9 31.5 Female 36.2 37.0 Unemployed 0.9 2.6 Male 0.7 1.4 Female 0.2 1.2 Stu4ing 16.9 21.8 Male 10.2 12.2 Female 6.6 9.7 Domestic 7.6 2.5 Male 1.9 0.4 Female 5.7 2.1 Other 5.5 4.6 Male 2.6 1.9 Female 2.8 2.7 Total 100.0 100.0 Source: IAF data for 1997 and2003. Note: Populationconsists o f people aged 10years andhigher. Table A2.11. Type of Employment,by Area, 1997 and 2003 (percent) Share of AN Workers Rural Urban Typeof employment 1997 2003 Growth Rate 1997 2003 GrowthRate 1997 2003 Growth Rate Agriculture (all) 88.8 81.5 -0.6 94.8 93.1 -0.3 71.3 53.5 -1.9 Self-employed (nonagriculture) 3.8 8.1 14.3 2.0 3.6 10.6 9.0 19.0 16.5 Wage employment 7.3 7.5 1.2 3.2 2.5 -3.9 19.2 19.6 3.3 Private 2.5 3.7 7.8 1.1 1.1 0.6 6.4 9.9 10.8 Public 4.8 3.8 -3.2 2.1 1.3 -6.8 12.8 9.7 -1.7 Employers 0.1 2.9 66.1 0.0 0.9 65.0 0.4 7.9 66.6 All economically active 100.0 100.0 0.8 100.0 100.0 0.0 100.0 100.0 2.9 Source: IAF data for 1997 and 2003. 31 Appendix A. Chapter Tables Table A2.12a. Distributionof the Labor Force by Sector and Type of Employment,by Area, 2003 (percent) Agriculture Self-employed WageEmployment Employer Nonagriculture Private Public Urban (29percent of the labor force) Agriculture 100 0 0 1.5 0 Industry 0 5.2 33.1 3.1 30.6 Service (private) 0 94.3 63.8 29.2 69.0 Service (public) 0 0.6 3.1 66.8 0.4 Total 100 100 100 100 100 Rural (71 percent of the laborforce) Agriculture 100 0 0 4.9 0 Industry 0 15.8 49.5 4.4 42.4 Service (private) 0 80.5 48.0 13.7 57.6 Service (public) 0 3.7 2.5 77.0 0 Total 100 100 loo 100 100 Source: IAF data for 2003. Note: Service (private) includes trade, transports, and services. Service (public) includeshealth, education, andpublic administration. TableA2.12b. Average Annual Growth Rate of the Labor Force by Sector, Type of Employment,and Area, 1997-2003 (percent) Agriculture Self-Employed WageEmployment Nonagriculture Private Public Urban Agriculture -1.9 -28.3 Industry -11.1 6.7 -11.1 Service (private) 22.1 14.9 -5.6 Service (public) -9.3 -1.1 11.8 Total -1.9 16.5 10.8 -1.7 Rural Agriculture -0.3 -34.8 Industry -9.5 -0.2 -22.3 Service (private) 24.2 2.3 -6.3 Service (public) -1.9 0.9 7.6 Total -0.3 10.6 0.6 -6.9 Source: IAF data for 1997 and2003. Note: Service (private) includes trade, transports, and services. Service (public) includeshealth, education, andpublic administration.Wage (private) includes private sector, cooperatives, and employers. Wage (public) includes public administrationandpublic firms. Excludes "employers" category. ..is negligible. 32 Appendix A. Chapter Tables Table A2.13. Type of Contract,by Industryand Area, 2003 (percent) Receiving Casual Industry a Wage Workers All Agriculture 77.3 22.7 100.0 Industry 78.6 21.4 100.0 Services(private) 88.1 11.9 100.0 Services (public) 99.7 0.3 100.o Source: IAF data for 2003. Note: Does not includefamily workers or self-employed. Service (private) includes trade, transports, and services.Service(public) includes health,education, and public administration. Table A2.14. Average Number of Sectorsand Income Sources Represented in the Household,by Area, 1997 and 2003 (percent) Number of sectorsa All Rural Urban 1997 2003 1997 2003 1997 2003 1 67.9 62.1 82.7 78.0 40.9 36.2 2 28.3 33.3 16.6 21.0 49.5 53.3 3 3.7 4.3 0.6 0.9 9.2 9.7 4 0.1 0.3 0.0 0.0 0.3 0.7 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of income All Rural Urban sources, 2002~ 2003 2003 2003 0 0.8 0.1 2.4 1 18.5 13.0 31.6 2 61.7 67.0 49.4 3 17.0 17.9 14.7 4 2.0 2.0 2.0 Total 100.0 100.0 100.0 Source: IAF data for 1997 and 2003. Note: Consistent with 2003 urbanand rural definitions. a. Sectors are: agriculture, industry, services (private) and services (public). Service (private) includes trade, transports, and services. Service (public) includes health, education, and public administration. b. Sourcesof income are from: employment, self-employment, selling products, occasional income (incl. insurancepayment), auto-consumption, capital, pension, and alimony. 33 AppendixA. Chapter Tables Table A2.15. Household Sources of Income and Income Share, by Area, 2003 (percent) Households EarningIncomefrom Source Employee Sev- Income Revenue Revenuefrom Rental and Other Income employment in Kind from Selling Other Income, (nonagricult Agriculture Home-Produced Pensions, and Area ure) Products Products" Alimony Urban 51.6 28.1 63.O 16.7 11.0 12.9 Rural 19.3 12.5 99.3 58.9 19.6 8.1 All 29.0 17.7 88.5 46.3 17.0 9.5 Income Shares Total Self- em&come loyment Total Incomefrom Incomefrom Employee (nonagricult Income Selling Selling Other Other Income ure) in Kind AEriculture Products Income Total Urban 54 18 12 3 3 10 100 Rural 13 9 52 14 6 6 100 All 27 12 38 11 5 7 100 Source: IAF data for 2003. a. For example, leather, clothes, small articles, and so on. 34 AppendixA. ChaDter Tables Table A2.16. Reasonsbehind PerceivedImprovementin HouseholdWell-beingduring Last Five Years, by Tercileand Area, 2006 (percent) All Household Heads in Urban areas All Household Heads in Rural areas Reason All 1st Tercile 3rd Tercile All 1st Tercile 3rd Tercile Morehouseholdmembers with work 36.3 15.4 42 14.9 20 19.5 Higher salaries ofhousehold members 23.1 0.o 34 1.4 0.0 2.4 Goodharvests 15.4 30.8 12 58.1 50 56.1 Improvededucationsystem 1.1 0.0 2 4.1 10 2.4 Improvedroads 4.4 15.4 2 8.1 0.0 4.9 Crime dropped 2.2 0.0 2 0.0 0.0 0.0 Improvedhealthcare 6.6 0.0 2 4.1 10 2.4 Currently studying 1.1 7.7 0.0 0.0 0.o 0.0 Businessimproving 4.4 15.4 0.0 8.1 0.0 12.2 Other 5.5 15.4 4 1.4 10 0.0 Total 100 100 100 100 100 100 Source:PVS data from 2006. Note: Sample not representative. 35 Amendix A. ChaDter Tables Table A2.17. ReasonsbehindPerceivedWorseningin HouseholdWell-being during Last Five Years, by Tercile and Area, 2006 (percent) All Household Heads Urban All Household Heads Rural Reason All 1st 3rd Tercile All 1st Tercile 3rd Tercile Tercile More household members without work 33.8 22.8 42.9 12.5 7.1 22.7 Poor harvests 8.1 7 17.9 24.1 21.4 36.4 Increase in crime 0.7 1.8 Cost of living increased 46.3 54.4 32.1 51.8 60.7 31.8 Natural disasters 4.4 5.3 7.1 7.1 4.5 Nonprofitable business 0.7 Age 0.7 1.8 0.9 Divorce, separation, widowhood 2.2 5.3 0.9 1.8 N o money 0.9 1.8 Illness 0.9 Other 0.7 3.6 N o reason 2.2 1.8 3.6 Total 100.0 100.0 100.0 100.0 100.0 100.0 Source:PVS data for 2006. Note: Sample not representative. Table A2.18a. Index and Growth Rate ofAverage Earningsin Urban Areas, by Sector of Employment,1997-2003 (percent) GrowthRate Index Gini Theil Sector of Employment 1997-2003 1997 2003 1997 2003 1997 2003 Agriculture 5.3 100 100 0.447 0.418 0.426 0.354 Industry 5.4 160 161 0.458 0.486 0.370 0.481 Services (private) 4.7 211 203 0.516 0.497 0.526 0.466 Services (public) 9.5 208 263 0.480 0.496 0.414 0.431 Total (mean) 7.3 130 135 0.506 0.504 0.511 0.490 Decomposition of the TheilIndex in Within- and Between-group Inequality (groups defned by typeof employment)' 1997 2003 Within-group inequality 94.1 94.6 Between-group inequality 5.9 5.4 Source: IAF data for 1997 and 2003. Note: Service (private) includes trade, transports, and services. Service (public) includeshealth, education, andpublic administration. a. Type of employment refers to the type of employment of the headofthe household.Householdsthat havethe headin wage employment are highly likely to also to have someone working inagriculture, as most householdshave some participation inagriculture. Therefore, for these heterogeneoushouseholds(as opposed to more homogeneousagricultural households), inequality might be higher because two sectors(agricultureand nonagriculture) are beingcombined, increasing the variance. Householdsthat have the headinthe "employer" category are not included. 36 AppendixA. ChaDter Tables TableA2.18b. Index and Growth Rate of Average Earningsin Rural Areas, by Sector of Employment,1997-2003 (percent) Growth Rate Index Gini Theil Sector of employment 1997-2003 1997 2003 1997 2003 1997 2003 Agriculture 6.2 100 100 0.372 0.370 0.247 0.249 Industry 12.0 125 172 0.384 0.499 0.261 0.582 Services (private) 6.1 172 170 0.432 0.470 0.327 0.396 Services (public) 7.4 182 195 0.442 0.351 0.346 0.228 Total (mean) 6.8 104 108 0.384 0.396 0.266 0.299 Decomposition of the TheilIndex in Within- and Between-group Inequality (groups defined by typeof employment)a 1997 2003 Within-group inequality 98.9 97.8 Between-group inequality 1.1 2.2 Source: IAF data for 1997 and 2003. Note: Service (private) includestrade, transports, and services. Service (public) includeshealth, education, and public administration.Agriculture does not include public sector. a. Type of employment refers to the type of employmentof the headofthe household. Households with ahead inwage employment are highly likely to also to have someone working inagriculture, as most households have some participation in agriculture.Therefore, for these heterogeneoushouseholds(as opposedto more homogeneousagricultural households), inequality might be higherbecausetwo sectors(agriculture andnonagriculture)are being combined, increasing the variance. Householdsthat have the head inthe "employer" category are not included. 37 AppendixA. Chapter Tables Table A2.19. Earningsand Inequality in UrbanAreas, by Type of Employment, 1997-2003 (percent) Growth Rate Index Gini Theil Type of employment 1997-2003 I997 2003 I997 2003 I997 2003 Agriculture (all) 5.3 100 100 0.444 0.416 0.410 0.351 Self-employed, nonagriculture 5.6 195 198 0.525 0.508 0.569 0.501 Wage employment Private 5.4 180 182 0.483 0.501 0.438 0.516 Public 10.0 197 257 0.478 0.492 0.422 0.420 Total (mean) 7.3 149 167 0.500 0.506 0.499 0.500 Decomposition of the Theil Index in Within- and Between-group Inequality (groups defined by type of employment)' I997 2003 Within-group inequality 95.0 94.3 Behveen-group inequality 5.0 5.7 Source: IAF data for 1997 and 2003. a. Type of employment refers to the type of employment of the head ofthe household. Householdsthat havethe headinwage employment are highly likely to also to havesomeone working in agriculture, as most householdshave some participation in agriculture. Therefore, for these heterogeneoushouseholds(as opposedto more homogeneousagricultural households), inequality might be higher becausetwo sectors (agricultureand nonagriculture)are being combined, increasing the variance. Householdsthat have the head in the "employer" category are not included. 38 Amendix A. CharderTables Table A2.20. Earningsand Inequality in Rural Areas, by Type of Employment, 1997-2003 (percent) Growth rate Index Gini Theil TvDe of emDlovment 1997-2003 1997 2003 1997 2003 1997 2003 Agriculture (all) 6.2 100 100 0.373 0.370 0.248 0.249 Self-employed, nonagriculture 10.0 134 165 0.398 0.464 0.268 0.405 Wage employment Private 4.2 166 148 0.444 0.518 0.374 0.711 Public 13.0 148 214 0.423 0.388 0.324 0.274 Total (mean) 6.8 104 108 0.384 0.395 0.267 0.299 Decomposition of the Theil Index in Within- and Between-group Inequality (groups defined by type of employment)' 1997 2003 Within-group inequality 99.0 97.9 Between-group inequality 1.o 2.1 Source: IAF data for 1997 and 2003. a. Type o f employment refers to the type o f employment o f the heado fthe household.Householdsthat have the headinwage employment are highly likely to also to have someone working inagriculture, as mosthouseholdshave some participation in agriculture.Therefore, for these heterogeneoushouseholds (as opposed to more homogeneousagricultural households), inequality mightbe higherbecausetwo sectors(agricultureandnonagriculture) are beingcombined, increasingthe variance. Householdsthat havethe headinthe "employer" category are not included. 39 k c c hl h 0. 0. 4 k c c h h 0. ? k c 4 h 0. ? k e 4 h 0. ? k e 4 0 d 0. h ? c rr 4 h 0. ? c k e h h 0. 2 c* e c ru h 0. ? Appendix A. Chapter Tables Table A2.22. RegressionResults:DeterminantsofWages, 2003, with District FixedEffects All Men Women Coeficient Significance Coeficient Significance Coeflcient SigniJcance *** Significance of Difference Age 0.060 *** 0.063 *** 0.055 Age squared -0.001 *** -0.001 *** -0.001 ** Female (1=J -0.280 *** Marital status Married 0.254 *** 0.329 *** 0.137 Polygamous 0.215 *** 0.267 *** -0.029 Cohabiting 0.117 *** 0.155 *** 0.142 * Divorced 0.095 0.153 0.081 Widowed 0.113 0.326 *** 0.154 Education CompletedEP1 0.221 *** 0.206 *** 0.224 *** CompletedEP2 0.510 *** 0.473 *** 0.666 *** * CompletedESl 0.842 *** 0.786 *** 1.074 *** ** CompletedES2 1.132 *** 1.066 *** 1.412 *** ** CompletedET1 1.001 *** 0.929 *** 1.235 *** Completed ET2 1.484 *** 1.406 *** 1.605 *** Teacher education 0.929 *** 0.961 *** 1.086 *** Higher education 2.412 *** 2.333 *** 2.636 *** Industrial sector Agriculture -0.532 *** -0.488 *** -0.630 *** Mining 0.768 *** 0.783 *** 0.342 Construction 0.132 * 0.113 0.836 *** ** Transport 0.182 ** 0.191 ** -0.030 Trade -0.095 -0.142 0.004 Services -0.031 -0.023 -0.038 Education 0.096 0.098 -0.012 Health 0.098 0.03 1 0.164 Public administration 0.044 0.068 -0.155 Type contract Casual -0.298 *** -0.255 *** -0.760 *** ** Constant 10.366 *** 10.298 *** 10.126 *** District effects Yes Yes Yes Observations 2810 2218 592 Adjusted R Squared 0.559 0.532 0.665 Source: IAF data for 1997 and2003. Note: The dependent variable is the logarithm ofthe weekly wage inthe mainjob (including fringe benefits). EPl: Primary grades 1-5. EP2: Primary grades 6-7. ESl: Secondary grades 8-10. ES2: Secondary grades 11-12. ET1: Technicaltraining 1. ET2: Technicaltraining 2. *Significant at the 10 percent level. ** Significanceat the 5 percentlevel. ***Significance at the 1 percentlevel. 41 Amendix A. ChaDter Tables Table A2.23. Wage Regression Means of Variables (percent) A l l Men Women Age (Mean) 26.6 26.3 26.9 Female 53.0 na na Single 35.1 43.5 27.8 Married 12.0 11.9 12.1 Polygamous 8.1 6.1 9.9 Cohabitation 35.7 35.5 35.8 Divorced or separated 6.4 2.5 9.8 Widow 2.7 0.5 4.6 No formal education 74.5 66.5 81.6 Completed EP1 15.5 19.6 11.8 Completed EP2 6.7 8.8 4.8 Completed ESl 1.9 2.9 1.o Completed ES2 1.o 1.5 0.5 Completed technical schooling 0.4 0.7 0.2 Completed postsecondary schooling 0.1 0.1 0.1 Agriculture 79.9 68.2 89.4 Mining 0.5 1.1 0.1 Manufacturing 0.8 1.5 0.1 Construction 2.1 4.6 0.1 Transport 1.o 2.2 0.1 Trade 7.4 9.8 5.4 Services 5.2 7.5 3.3 Education 1.6 2.6 0.7 Health 0.5 0.5 0.4 Public administration 1.1 2.1 0.3 Source: IAF data for 2003. na is not applicable. EP1: Primary grades 1-5. EP2: Primary grades 6-7. ES1: Secondary grades 8-10, ES2: Secondary grades 11-12. 42 Appendix A. Chapter Tables Table A2.24. Average Number of Sectorsand IncomeSourcesRepresentedin Household,by Quintiles, 1997 and 2003 (percent) Number of sectorsa All Lowest 2nd Quintile 3rd Quintile 4th Quintile Highest 1997 2003 1997 2003 1997 2003 1997 2003 1997 2003 1997 2003 1 67.9 62.1 72.7 61.7 73.4 62.1 66.9 68.1 69.5 67.1 61.4 53.9 2 28.3 33.3 23.8 31.8 23.4 31.8 28.7 27.1 25.9 29.6 35.2 42.9 3 3.7 4.3 3.5 6.1 3.0 5.3 4.2 4.6 4.5 3.2 3.1 3.O 4 0.1 0.3 0.0 0.4 0.1 0.7 0.1 0.2 0.0 0.1 0.3 0.2 Total 100.0 100.0 100. 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of income sources 2003b 0 0.8 1.o 0.7 0.8 0.6 1.6 1 18.5 21.1 18.9 17.7 17.0 24 2 61.7 61.5 64.1 65.1 65.5 55 3 17.0 15.4 14.7 14.5 15.2 18 4 2.0 1.o 1.6 1.8 1.6 1 Total 100.0 100.0 100.0 100.0 100.0 100.0 Source: IAF data for 1997 and 2003. a. Sectors are: agriculture, industry, services (private), and services (public). Service (private) includestrade, transports, and services. Service (public) includes health, education, andpublic administration. b. Sourcesof income are: employment, self-employment, sellingproducts, occasionalincome (incl. insurancepayment), auto- consumption, capital, pension, andalimony. Table A2.25. HouseholdIncomeSource, by Quintile, 2003 (percent) Revenuefrom Selling Other Home- Produced Products Sev- (clothes, Quintiles of adult employment Revenuefrom wood, arts Rental and Other equivalent Employee (nonagricult Income Agricultural craft, and so Income, Pensions, consumption Income ure) in Kind Products on) andAlimony Lowest 28.0 12.8 90.5 43.O 16.3 12.5 2nd 26.6 17.3 89.4 47.4 16.6 10.0 3rd 26.0 14.5 91.8 47.7 18.4 9.2 4th 24.77 16.4 91.7 52.6 19.7 6.7 Highest 37.5 23.0 80.6 40.5 14.3 10.1 Source: IAF data for 2003. 43 Appendix A. Chapter Tables Table A2.26. Type of EmploymentSector, by Quintile, 1997 and 2003 (percent) Self-employed WageEmployment Quintile Agriculture (all) Nonagriculture Private Public 1997 2003 1997 1997 1997 2003 1997 2003 Lowest 20.5 19.8 11.0 13.8 13.8 10.1 11.0 16.7 2nd 19.9 19.7 16.1 13.5 13.5 9.9 16.1 17.6 3rd 19.9 21.2 20.9 16.8 16.8 11.1 20.9 17.0 4th 20.0 21.6 20.7 17.8 17.8 18.0 20.7 19.3 Highest 19.7 17.7 31.2 38.0 38.0 50.7 31.2 29.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Source: IAF data for 1997 and2003. Table A2.27. PovertyRates by Sector ofActivity of Head and Spouse, 2003 (percent) Head in Agriculture Head in Nonagriculture Spouse inagriculture 57 46 Spouse innonagriculture 61 42 Source: IAF data for 1997 and2003. TableA2.28. Contributionto Growth by Type of Labor, 1999-2004 (percent) Real GDP (annual) Rural Urban Total Women Men Women Men Women Men Women Men Primary Primary Secondary Secondary Primary Primary Secondary Secondary Y School School School School School School School School 1999-2004 7.4 0.1 0.3 0.0 0.1 0.4 0.3 0.3 0.6 2.1 S na 6.4 12.2 0.4 6.7 18.4 12.2 14.2 29.5 100.0 Y 100.0 1.8 3.4 0.1 1.9 5.2 3.5 4.0 8.3 28.3 Source:Jones 2006. S: Share o f labor force. Y: Contribution to GDP growth. na is not applicable. 44 Appendix A. Chapter Tables Table A2.29. EducationLevelof Economically ActivePopulationby Gender, 1980-2004 (estimated thousands) EconomicallyActive No Education Primary Education Secondary Education Year Women Men Women Men Women Men Women Men 1980 2,999.7 2,692.5 2,s 17.0 2,246.4 119.8 388.4 23.3 65.5 1985 3,112.8 2,866.6 2,947.4 2,255.6 169.7 518.3 20.4 68.0 1990 3,230.1 3,119.0 3,102.5 2,277.5 222.2 641.8 24.3 80.9 1995 3,633.5 3,290.9 3,366.4 2,369.3 280.6 765.2 30.5 112.4 2000 3,910.5 3,548.1 3 3 3 1.2 2,355.9 376.9 969.1 43.8 181.7 2001 3,976.9 3,556.8 3,507.3 2,340.4 400.9 1,031.5 49.3 204.3 2002 4,116.5 3,492.5 3,560.0 2,233.8 535.5 991.7 66.2 221.8 2003 4,186.3 3,498.6 3,515.4 2,205.2 572.7 1,060.6 76.1 254.9 2004 4,257.3 3,508.0 3,45 8.4 2,168.9 615.3 1,139.5 88.2 295.2 Total change 141.9 130.3 122.8 96.5 513.5 293.4 378.4 450.7 Source: World Bank staff estimate. Table A2.30. Type of Employmentin Urban Areas, by Genderand Sector, 1997and 2003 (percent) Number of Employed Percentage Type of employment Share (thousands) Change 1997 2003 1997 2003 1997-2003 Agriculture 100.0 100.0 1,500 1,300 -1 3.3 Female 66.3 70.2 995 913 -8.2 Male 33.7 29.8 505 387 -23.5 Self-employment 100.0 100.0 475 284 147.8 Female 41.8 51.3 80 244 204.4 Male 58.2 48.7 112 231 107.1 Wageprivate 100.0 100.0 145 445 208.0 Female 11.8 18.4 17 82 381.1 Male 88.2 81.6 127 363 184.9 Wagepublic 100.0 100.0 273 244 -10.5 Female 16.2 23.4 44 57 29.8 Male 83.8 76.6 229 187 -18.2 All economically active 100.0 100.0 2,100 2,500 19.0 Female 54.7 55.1 1,148 1,377 19.9 Male 45.3 44.9 952 1,123 18.0 Source: IAF data for 1997 and 2003. 45 Appendix A. Chapter Tables Table A2.31. Type of Employmentin All Areas, by Genderand Sector, 1997 and 2003 (percent) Number of Employed Percentage Type of employment Share (thousands) Change 1997 2003 1997 2003 1997-2003 Agriculture 100.0 100.0 7,400 7,000 -5.4 Female 58.7 61.2 4,344 4,283 -1.4 Male 41.3 38.8 3,056 2,717 -11.1 Self-employment 100.0 100.0 310 692 122.7 Female 31.9 41.5 99 287 189.4 Male 68.1 58.5 212 405 91.4 Wageprivate 100.0 100.0 214 567 164.7 Female 11.8 16.8 25 95 276.8 Male 88.2 83.2 189 472 149.7 Wagepublic 100.0 100.0 321 319 -0.5 Female 15.4 20.7 50 66 34.0 Male 84.6 79.3 272 254 -6.7 All economically active 100.0 100.0 8,200 8,600 4.9 Female 54.8 55.1 4,492 4,737 5.5 Male 45.2 44.9 3,708 3,863 4.2 Source:IAF data for 1997 and 2003. Table A2.32. Gender Ratio of EducationLevelof Economically Active Populationin RuralMozambique, 1997 and 2004 (percent) Ratio of Men to Women Year No Education Primary School Secondary School 1997 0.7 2.7 4.7 2004 0.6 2.2 7.7 Source: World Bank staff estimate. 46 sc U p 8 p rl 8 Bi Y Amendix A. ChaDter Tables Table A2.34. Household Participation in Agriculture, by Area, 2003 (percent) Urban Rural Male head Headandspouse inagriculture 38.3 86.6 Only spouse inagriculture 32.3 12.0 Only headinagriculture 3.0 0.6 Neitherheador spouse inagriculture 26.4 0.7 Total 100.0 100.0 Female head Headinagriculture 64.0 97.7 Headnot inagriculture 36.0 2.3 Total 100.0 100.0 Source:IAF data for 2003. Table A2.35. Rural Household Diversificationinto Nonfarm Self-Employment, by Gender of the Head, 1996 and 2002 Diversijkationinto Nonfarm Self-Employmentand its Importance in TotalIncome Households with Share of Non-Farm Nonfarm Household Earning Enterprise Income Enterprise Nonfarm Enterprise as MA4 Source of Income in Total Survey Income Income Income Gender of head Year 1996 37.4 12.9 13.9 Male head 2002 46.1 16.8 17.6 1996 23.5 11.5 10.6 Femalehead 2002 29.1 11.2 11.7 Source:TIA data for 1996 and2002. Note: Major source is definedas the source with the highest contribution. Other sources include crop income, livestock income, andwage-labor income. 48 Amendix A. ChaDter Tables Table A2.36. IncomeShares by Type of Employment,Gender and Area, 2003 (percent) Income category Urban Rural Total Employment male 46.3 11.7 23.4 Employment female 7.8 0.9 3.2 Self-employment male 14.0 8.4 10.3 Self-employment female 3.9 0.7 1.8 Selling products male 4.5 18.1 13.5 Selling products female 1.5 2.8 2.4 Self-consumption (household) 12.2 51.6 38.3 Pension and alimony (household) 4.5 1.o 2.2 Income from capital (household) 2.1 2.4 2.3 Occasional income (household) 3.2 2.5 2.7 Total 100.0 100.0 100.0 Source:IAF data for 2003. Note: Separate contribution by gender for individualincome sources. Table A2.37. Annual Growth Rates of GDP, Consumption, Investment,Exports,and Imports,2000-08 (volume,percent change) 2000 2001 2002 2003 2004 2005 2006 2007 Estimated Projected GDP,total 1.9 13.1 8.2 7.9 7.5 7.8 8.5 6.8 Consumption 0.9 3.3 0.6 14.8 4.5 12.1 -3.7 11.1 Government 11.7 17.2 3.6 16.2 8.6 12.0 25.1 17.3 Nongovernment -0.3 1.5 0.2 14.6 3.9 14.6 -3.7 12.6 Grossdomestic investment -8.7 -15.2 38.0 3.2 34.6 -6.4 16.6 27.0 Exports of goods and services Exports 31.9 51.6 21.0 30.2 13.1 9.4 13.7 8.0 Imports -2.4 -20.7 21.4 13.1 -7.5 29.1 31.7 29.4 Source: World Bank staffestimates. 49 Appendix A. Chapter Tables CHAPTER3 TableA3.1. Rural HouseholdIncome per Adult Equivalentand Annual Growth Rates, by Quintile, Location,and Gender, 1996-2002 I996 2002 ~Incomeper Incomeper Adult Adult Equivalent Equivalent Annual Growth (Meticais) (Meticais) 19962002 Quintile Lowest 161.0 234.8 6.5 2nd 502.0 596.9 2.9 3rd 879.6 1,040.5 2.8 4th 1,467.5 1,872.5 4.1 Highest 3,3 58.7 6,788.3 12.4 Rural region North 1,645.6 1,912.0 2.5 Central 947.6 1,893 .O 12.2 South 1,236.4 3,058.2 16.3 Province (rural) Niassa 1,053.4 2,560.0 16.0 Cab0 Delgado 1,453.9 1,858.6 4.2 Nampula 1,895.8 1,773.4 -1.1 Zambkzia 986.8 1,789.8 10.4 Tete 646.8 2,412.2 24.5 Manica 1,489.9 1,781.6 3.0 Sofala 894.7 1,634.3 10.6 Inhambane 1,411.2 3,288.7 15.1 Gaza 870.1 2,344.7 18.0 Maputo 1,266.9 4,415.5 23.1 Gender of the head of household (rural) Male head 1,3 13.0 2,300.0 9.8 Female head 1,039.0 1,516.0 6.5 All Rural 1,273.6 2,106.2 8.7 Source; TIA data for 1996 and 2002. 50 Appendix A. ChaDter Tables Table A3.2. Percentage of FemaleHead andWidow Head of Householdsby Income Quintile, 1996 and 2002 hercent) Quintiles of total net household income per adult equivalent Female Head Widow Head I996 2002 1996 2002 Lowest 20.4 34.3 8.9 13.4 2nd 16.4 27.1 8.3 11.1 3rd 12.2 22.1 5.1 8.2 4th 12.2 22.2 6.1 8.6 Highest 10.8 15.7 5.4 4.0 Total 14.4 24.3 6.8 9.0 Source: TIA data for 1996 and 2002. Table A3.3. ProvincialChanges in Crop Production,19962002 (mean annual average changepercent) Province Maize Sorghum Millet Pad& Beans Groundnuts Cassava ~ ~ Cab0 Delgado 4.5 12.9 12.2 11.3 10.8 9.1 8.7 Niassa 1.6 4.7 5.3 17.2 3.3 0.6 5.1 Nampula 1.7 1.3 2.7 4.8 2.7 -1.9 -0.3 Zambkzia 6.0 5.7 8.5 1.5 4.4 2.4 7.6 Tete 11.5 11.6 7.5 12.2 16.7 8.6 13.4 Manica 5.1 3.1 0.5 30.6 5.4 -5.6 16.4 Sofala 1.5 -0.5 10.0 3.1 -1.6 -3.6 3.6 Inhambane -7.9 -6.7 -4.8 0.4 -5.7 -9.1 1.2 Gaza 11.6 14.9 13.8 4.9 4.3 3.5 9.9 Maputo 13.5 -1.8 0.0 -15.3 -3.2 -1.6 8.4 Total 4.5 4.1 5.4 3.2 4.0 -1.1 3.8 ~ Source: World Bank 2006a. Note: Estimatesbasedon unpublisheddata from Aviso Previo, Ministry of Agriculture. 51 Amendix A. Chauter Tables Table A3.4. Number of Crops Grown, by Type of Crop and IncomeQuintile, 1996 and 2002 (percent) Quintiles of total net Field Cash Perennial household income All Crops Food Cropsa Cropsb Crops' Horticulture per adultequivalent I996 2002 1996 2002 I996 2002 I996 2002 I996 2002 Lowest 3.0 6.1 2.2 2.9 0.0 0.1 0.6 1.9 0.1 1.3 2nd 4.2 7.4 3.0 3.8 0.0 0.2 0.9 2.1 0.2 1.4 3rd 4.7 7.9 3.3 4.2 0.1 0.2 1.1 2.1 0.3 1.4 4th 5.2 8.8 3.6 4.4 0.1 0.3 1.3 2.3 0.3 1.8 Highest 5.7 9.2 3.9 4.2 0.2 0.3 1.4 2.5 0.3 2.2 Total 4.6 7.9 3.2 3.9 0.1 0.2 1.1 2.1 0.2 1.6 Source: Boughton and others 2006. a. Food crops are cereals, pulses, roots, andtubers. b. Field cash crops are cotton, tobacco, sisal, tea, soybeans, paprika, sunflower, and sesame. c. Perennial crops are fruit trees, cashew, cocoa, and sugar cane. Table A3.5. Average Annual Growth Rates in LandUtilization, 1993-2003 (percent) Area Region Time Total Smallholder Commercial North 1993-200 1 2.5 2.9 -8.2 Central 1993-200 1 6.8 7.2 -5.0 South 1993-2001 2.7 2.7 7.0 Total 1993-2001 3.3 3.6 -4.2 Total 2000-03 3.9 - - -i Source: World Bank 2006a, basedon data from CAP 1999/2000. s not available. Table A3.6. EstimatedActual and PotentialCrop Yields, 1998 Average Potential Yield Crop Average Actual Yield (t/ha) (t/ha) Maize 0.9 5.0-6.5 Sorghum 0.4 0.8-2 .O Rice 1.o 2.5-6.0 Beans 0.5 5-0- 10.o 0.5-2.5 Cassava 6.0 Cotton 0.5 1.o-2.0 Source: Howard and others 1998. 52 Amendix A. ChaDter Tables Table A3.7. Conditions of the Classified RoadNetwork, 1995 and 2005 (percent) PavedRoads UnpavedRoads Year Good Fair Poor Good Fair Poor 1995 11 20 69 1 19 80 2000 41 39 20 21 30 48 Source: Benito-Spinetto and Moll 2005, basedon a recompilation o f secondary sources. 53 Appendix A. Chapter Tables Table A3.8. Determinantsof Participationand Performance in Rural Maize Markets in Central and Northern Mozambique,2002 Parameter Estimates Ordinary Least Squares Probitfor Market Participation withSelection Correction Dependent Variable: 1IfHousehold Dependent Variable: Log Sold Maize (maize sales value) Coeficient CoefJkient Explanatory variables Estimate p-value Estimate p-value Female headof household Educationofthe head (years) Educationof head squared Age of householdhead(years) -0.181 0.031 -0.254 0.089 Age of householdheadSquared -0.037 0.292 0.046 0.234 0.001 0.890 -0.004 0.446 Householdheadreceived -0.018 0.147 0.006 0.704 information from extension agent 0.000 0.367 0.000 0.654 Householdheadmembersin 0.143 0.109 0.067 0.497 association 0.046 0.792 0.119 0.601 Householdheadhas pump or gravity irrigation Householdheadreports yield loss in maize 0.036 0.946 -0.272 0.702 Householdheadowns animal -0.253 0.001 -0.148 0.262 traction 0.189 0.490 0.674 0.002 Householdheadowns atractor 1.099 0.180 0.221 0.844 District medianmaize farmgate price 0.111 0.460 0.951 0.000 Distance from village to Sede (kms) 0.003 0.165 -0.001 0.799 Householdhead owns bike 0.056 0.436 0.268 0.002 Householdhead owns radio -0.060 0.506 0.163 0.101 Village received price information -0.016 0.880 -0.056 0.659 Householdhead owns radio 0.151 0.188 -0.063 0.683 Total area (ha) Total area squared 0.118 0.000 0.196 0.000 Numberof adults inhousehold(aged -0.002 0.000 -0.003 0.000 15-59) -0.032 0.681 0.024 0.814 Numberof adults inhouseholdsquared -0.005 0.556 0.003 0.812 Household headhas skilled wage income Householdheadhas nonfarm microenterprise income Householdheadhas nonfarm -0.055 0.706 microenterprise income-resource -0.055 0.371 extraction 0.141 0.141 Household headhas livestock income 0.181 0.003 Inverse Millsratio -0.134 0.785 constant -1.483 0.001 1.331 0.322 Numberof observations 896 Log likelihood 2.867 R-squared -473.00 0.408 Source: Boughtonandothers, forthcoming. Note: Because maize, tobacco, and cotton sales are only observed for a subset of the sample population, the potential exists for the sample selection problem referredto as incidental truncation. That is, households with sales observations are likely not to be a random subsample of the population. In other words, there may be factors associated with their likelihood of participation that are also explaining their performance as participants. To address this concern, we employ the standard Heckman Two-step sample selection model. The first step estimatesa probit model of participation inthe relevant market-the determinantsof participation (variables that likely also determine crop sales volumes, conditional on market participation) as well as exclusion restriction variables (those assumed to affect participation but not outcome). Our exclusion restriction variables focus on factors affecting a household's level of dependence on crop income as an income source and factors that might affect perceptions of risk relating to market participation. The second step is an OLS regressionof the log of net crop sales value on the reduced form regressorsplus the inverse Mills ratio (IMR) derived from the first-stage probit regression, which controls for unobservedfactors that affect the probability of marketparticipation. 54 Appendix A. Chapter Tables Table A3.9. Determinantsof Participationand Performancein RuralCotton Markets in Central and Northern Mozambique,2002 Parameter Estimates Probitfor Cotton Market Ordinary Least Squares Participation with Selection Correction Dependent Variable: I If Dependent Variable: Log (cotton Household Sold Cotton sales value) Coeficient Explanatory variables Estimate p-value Coeficient Estimate p-value Female heado f household Education o f the head (years) -0.580 0.000 -0.103 0.589 Education o f head squared -0.018 0.808 -0.152 0.091 Age ofhousehold head (years) 0.021 0.077 0.030 0.077 Age of household head squared -0.002 0.929 0,010 0.625 Household head members in 0.000 0.764 0.000 0.652 association 0.257 0.274 -0.125 0.292 Household head owns animal traction Distance from village to Sede (kms) Household headowns bike -0,180 0.647 0.820 0.096 Total area (ha) 0.011 0.000 -0.009 0.044 Total area squared 0.252 0.047 0.325 0.033 Numberof adults inhousehold(aged 0.403 0.000 0.087 -0.499 15-59) -0.013 0.000 -0.008 0.113 Number of adults inhousehold -0.036 0.737 0.107 0.214 squared 0.001 0.892 0.007 0.149 Household headhas skilledwage income Household headhas nonfarm microenterprise income Household headhas nonfarm -0.390 0.195 microenterprise income-resource -0.088 0.490 extraction -0.418 0.006 Household headhas livestock income -0.291 0.012 Inverse Millsratio -0.757 0.061 constant -7.439 0.000 8.975 0.000 Number o f observations 275 Log likelihood 1,574 R-squared -496.65 0.772 Source: Boughtonand others 2007. Note: Because maize, tobacco, and cotton sales are only observed for a subset of the sample population, the potential exists for the sample selection problem referredto as incidentaltruncation.That is, households with sales observationsare likely not to be a random subsample of the population. In other words, there may be factors associated with their likelihood of participation that are also explaining their performance as participants.To address this concern, we employ the standard HeckmanTwo-step sample selection model. The first step estimatesa probit modelofparticipation inthe relevantmarket-the determinants of participation (variables that likely also determine crop sales volumes, conditionalon market participation) as well as exclusionrestriction variables (those assumed to affect participation but not outcome). Our exclusion restriction variables focus on factors affecting a household's level of dependenceon crop income as an income source and factors that might affect perceptions of risk relating to market participation. The second step is an OLS regressionof the log of net crop sales value on the reduced form regressorsplus the inverse Mills ratio (IMR) derivedfrom the first-stageprobit regression, which controlsfor unobservedfactors that affect the probability ofmarketparticipation. 55 AuuendixA. Chauter Tables TableA3.10. Determinants ofParticipationand Performance in Tobacco Markets in Central and Northern Mozambique,2002 Parameter Estimates Probitfor Tobacco Market Ordinary Least Squares Participation with Selection Correction Dependent Variable: I IfHousehold Dependent Variable: Log (tobacco Sold Tobacco sales value) Explanatory variables Coeflcient Estimate p-value Coefficient Estimate p-value Female headof household Education of the head (years) -0.431 0.001 -0.242 0.632 Education o f head squared 0.016 0.785 0.213 0.091 Age o f household head(years) -0.008 0.313 -0.026 0.098 Age of householdheadsquared -0.010 0.635 -0.028 0.509 Householdhead members in 0.000 0.631 0.000 0.266 association 0.331 0.110 0.275 0.600 Householdhead owns animal traction Distance from village to Sede (kms) Household headowns bike 0.917 0.016 -0.442 0.614 Total area (ha) 0.004 0.198 -0.005 0.429 Total area squared 0.069 0.509 0.294 0.378 Number of adults in household (aged 0.276 0.000 0.095 0.684 15-59) -0.019 0.018 0.006 0.720 Number of adults in household 0.310 0.066 0.155 0.803 squared -0.049 0.050 -0.009 0.934 Household headhas skilled wage income Household headhas nonfarm microenterprise income Household headhas nonfarm microenterprise income-resource 0.033 0.873 extraction -0.047 0.672 Householdheadhas livestock 0.250 0.052 income 0.199 0.062 InverseMillsratio -0.471 0.662 constant -2.516 0.000 2.096 0.579 Number o f observations 160 Log likelihood 2,346 R-squared 423.82 0.7 19 Source: Boughtonand others 2007. Note: Because maize, tobacco, andcotton sales are only observedfor asubset of the sample population,the potential exists for the sample selection problemreferredto as incidentaltruncation.That is, householdswith sales observationsare likely not to be arandom subsample ofthe population.Inother words, there may be factors associated with their likelihood of participationthat are also explaining their performanceas participants. To addressthis concern, we employ the standard HeckmanTwo-step sample selection model. The first step estimatesaprobitmodel of participation inthe relevantmarket- the determinantsofparticipation(variables that likely also determinecrop salesvolumes, conditional onmarket participation) as well as exclusionrestriction variables (those assumedto affect participationbut not outcome). Our exclusion restriction variables focus on factors affecting ahousehold's levelof dependenceon crop income as an income source and factors that might affect perceptionsofrisk relatingto marketparticipation. The second step is an OLS regressionofthe log of net crop sales value onthe reducedform regressorsplus the inverseMills ratio (IMR) derivedfrom the first-stageprobit regression, which controls for unobservedfactors that affect the probability ofmarket participation. These regressions also control for agroecological zones anddistrict fixed effects. 56 Appendix A. Chapter Tables Table A3.11. Sourcesof Growth in RuralHouseholdIncomeby Quintile, 1996-2002 (percent) Change in Mean TotalIncomeAttributable to Each Source Quintiles of net Annual (1996-2002) household GrowthRate incomeper in Income Crop Livestock Wage Nonfarm adult equivalent (19962002) Income Sales Income Enterprise Total Lowest 6.5 77.2 5.0 -3 .O 20.0 100.0 2nd 2.9 77.0 6.0 5.0 12.0 100.0 3rd 2.8 79.2 7.9 13.9 -1 .o 100.0 4th 4.1 39.4 9.1 38.4 13.1 100.0 Highest 12.4 -8.0 4.0 55.0 49.0 100.0 All households 8.7 9.9 5.o 46.5 38.6 100.0 Source: TIA data for 2002 andBoughton andothers 2004. Note: Percentof the total change attributableto the source, calculated as a share o f each source change inthe total change. Table A3.12. Rural IncomePovertyIncidence and TransitionMatrix, 2002 and 2005 (percent) Household Poverty Status Group Source: TIA data for 2002 and2005. Note: The numbers inparenthesis are transitionprobabilities given the initial status. 57 Amendix A. Chanter Tables Table A3.13. Rural HouseholdPoverty Transition Status, by Geographic Area, 2002-05 (percent) Poverty Transition Status Stayed Escaped Stayed Geographic dimensions Poor Became Poor Poverty Nonpoor South 54.1 12.4 19.6 13.8 Region Centra 50.4 15.4 17.6 16.6 North 53.9 15.0 16.4 14.7 Niassa 48.3 16.2 15.9 19.6 Cab0 Delgado 56.7 8.2 22.2 12.9 Nampula 53.8 18.0 13.7 14.4 Zambezia 51.2 18.1 17.0 13.7 Province Tete 47.2 15.0 15.7 22.2 Manica 59.9 9.8 15.2 15.1 Sofala 38.9 11.2 27.2 22.8 Inhambane 46.4 14.2 21.0 18.4 Gaza 59.8 10.8 19.5 9.9 Maputo 63.9 11.0 15.3 9.8 National 52.4 14.7 17.5 15.4 Source: TIA 2002-05 Panel data. Table A3.14a. Rural IncomePoverty Incidence and PovertyTransition Matrix, 2002 and 2005 (percent) Poverty Household Group Survey year Extremely Poor Poor Nonpoor Wealthy All 2002 42.8 27.1 12.9 17.2 100.0 2005 43.1 23.7 11.1 22.1 100.0 Poverty Transitions 2002-05 Poverty Status in 2005 Poverty status in 2002 Extremely Poor Poor Nonpoor Wealthy All Extremely Poor 56.4 22.8 7.6 13.3 100.0 Poor 40.9 27.4 12.4 19.4 100.0 Nonpoor 33.0 24.1 14.4 28.5 100.0 Wealthy 22.6 20.2 15.9 41.4 100.0 Source: TIA data for 2002 and2005. Note: Extremelypoor is definedas 0.5 pointsbelow the poverty line andwealthy, 1.5 above the poverty line. 58 AppendixA. Chapter Tables Table A3.14b. Rural Poverty Status and Poverty Transition Matrix: Extremely Poor, Nonpoor, and Wealthy, by Region, 2002 and 2005 (percent) Poverty Household Group Surveyyear Extremely Poor Poor Nonpoor Wealthy All South 51.9 21.9 10.3 16.0 100.0 Central 43.8 24.1 12.5 19.5 100.0 North 37.3 33.0 14.7 15.1 100.0 2002 Mozambique 42.8 27.1 12.9 17.2 100.0 South 44.2 22.3 9.0 24.5 100.0 Central 43.3 22.5 10.3 23.8 100.0 North 43.0 25.8 13.2 18.0 100.0 2005 Mozambique 43.1 23.7 11.1 22.1 100.0 Poverty Transitions 2002-05 Poverty Status in 2005 Poverty status in 2002 Extremely Poor Poor Nonpoor Wealthy All South 53.7 22.7 7.1 16.4 100.0 Central 56.3 21.3 7.6 14.8 100.0 Extremely North 58.3 24.8 7.8 9.1 100.0 poor Mozambique 56.4 22.8 7.6 13.3 100.0 South 40.1 26.0 10.6 23.3 100.0 Central 39.6 28.2 11.5 20.7 100.0 North 42.1 27.1 13.7 17.1 100.0 Poor Mozambique 40.9 27.4 12.4 19.4 100.0 South 35.0 19.9 9.5 35.6 100.0 Central 36.0 21.7 12.1 30.3 100.0 North .4 27.9 18.3 24.4 100.0 Nonpoor Mozambique 33.0 24.1 14.4 28.5 100.0 South 25.0 17.5 12.5 45.1 100.0 Central 23.3 18.9 13.9 43.9 100.0 North 20.2 23.6 20.5 35.7 100.0 Wealthy Mozambique 22.6 20.2 15.9 41.4 100.0 Source: TIA data for 2002 and2005. Note: Exfremelypoor is defined as 0.5 points below the poverty line and wealthy, 1.5 abovethe poverty line. 59 Amendix A. ChaDter Tables Table A3.15. RuralPovertyDynamicsand PerceptionsofWelfare Changes,2002-05 (percent) Perception of living Poverty TransitionStatus conditionsoverprevious 3 Became Escaped Stayed All years Stayedpoor Poor Poverty Nonpoor Households Improved 24.6 37.3 29.9 46.1 30.7 DidNot Change 29.6 37.6 29.7 25.0 30.1 Worsened 45.8 25.6 40.4 28.9 39.2 2002 100.0 100.0 100.0 100.0 100.0 Improved 12.8 15.9 25.3 31.1 18.3 DidNot Change 31.2 32.8 31.8 31.6 31.6 Worsened 56.0 51.3 42.9 37.3 50.1 Total 100.0 100.o 100.0 100.0 100.0 Source: TIA 2002-05 Panel data 60 Appendix A. Chapter Tables transitions cient Z Level cient t-stat P I t I SigniJicance level Demographics Gender o f the head -0.01 -0.11 0.91 -0.00 -0.01 0.99 Age o f the head 0.02 1.71 0.09 -0.02 -1.08 0.28 Age o f the head squared -0.00 -1.81 0.07 ** 0.00 1.00 0.32 Head's education 0.04 0.84 0.40 0.05 0.93 0.35 Head's education squared 0.01 0.83 0.40 -0.02 -2.61 0.01 *** Labor adult equivalents -0.10 -4.97 0.00 *** 0.11 3.50 0.00 *** Numbero fwaged members 0.12 2.31 0.02 *** ** -0.14 -1.45 -0.34 Numberof memberswith 0.15 3.45 0.00 -0.14 -1.69 0.09 * MSE Household assets Owns bicycle 0.21 2.38 0.02 *** ** -0.20 -1.58 0.12 Owns radio 0.20 2.53 0.01 -0.49 -4.10 0.00 *** Owns improved silos 0.18 1.79 0.07 *** * -0.18 -1.28 0.20 Total area 0.07 3.09 0.00 -0.14 -4.26 0.00 *** Access to services Extension information 0.07 0.66 0.51 -0.33 -2.09 0.04 ** Price information 0.14 1.80 0.07 * 0.00 0.01 0.99 Belongs to association -0.10 -0.69 0.49 0.02 0.10 0.92 Use of Technologies Used irrigation -0.18 -1.16 0.25 0.01 0.03 0.98 Used improvedmaize seed 0.18 1.29 0.20 -0.17 -0.70 0.48 Used fertilizer 0.25 1.29 0.20 0.04 0.18 0.86 Used pesticide 0.16 0.91 0.36 0.07 0.25 0.80 Mobility in access to sources Lost food crop market -0.16 -1.58 0.11 0.16 1.17 0.24 Entered food crop market 0.25 2.73 0.01 *** 0.04 0.28 0.78 Lost cash crop market -0.08 -0.75 0.45 -0.03 -0.19 0.85 Entered cash crop market 0.18 1.71 0.09 -0.51 -0.30 0.76 Lost wage labor income -0.34 1.87 0.06 ** 0.54 2.80 0.01 *** Entered wage labor market 0.09 0.83 0.41 0.21 1.21 0.23 Lost nonfarm MSE -0.21 -1.69 0.09 * 0.43 2.98 0.00 *** income Entered nonfarm MSE 0.17 1.99 0.05 * 0.03 0.22 0.83 income Districtfued-effects Yes Yes Included Constant -1.30 -3.03 0.00 *** 0.38 0.65 0.31 Number o f observations 2,4 12 1,059 Wald chi2 (105):(101) 273.5 253.2 Prob > chi2 ' 0.000 0.000 PseudoR2 0.13 0.21 Log pseudo-likelihood -1,207.2 -580.1 Source:TIA data for 2002 and 2005. 61 Appendix A. Chapter Tables a. Probit estimationfor escapingpoverty, basedonthe numberof householdsthat were poor in 2002. The dependent variable is 1ifhouseholdescapedpoverty in2005, 0 otherwise. b. Probit estimationfor entering poverty, basedonthe number ofhouseholdsthat were nonpoor in2002. The dependent variable is 1ifhouseholdfell into poverty in2005,O otherwise. MSE: Micro o small enterprise. * Significant at the 10percent level. **Significant at the 5 percent level. *** Significant at the 1percent level. 62 AppendixA. Chapter Tables Table A3.17. RuralPovertyTransition and HouseholdCharacteristics,2005 (percent) Povertv TransitionStatus Stayed Became Escaped Stayed All Selected characteristics Poor Poor Poverty Nonpoor Householch Household demographics Gender ofthe head(percent male) 68.4 75.0 75.7 83.6 73.O Age ofthe head(years) 45.4 44.6 43.7 44.5 44.8 Years of schoolingof head 1.6 1.9 2.4 3.O 2.0 Householdsize 5.7 4.6 5.5 4.9 5.4 Labor adult equivalents 4.2 3.5 4.2 3.8 4.0 Consumptionadult equivalents 4.0 3.3 4.0 3.5 3.8 Dependency ratio 1.4 1.1 1.2 1.o 1.2 Economic activity Head in agriculturalactivity 90.5 92.4 83.9 85.1 88.8 Headwith agriculture as primary 86.9 86.8 76.7 72.7 82.9 Headwith wage labor 22.3 23.8 28.8 30.1 24.9 Headwith nonfarmrural microenterprise 38.1 37.6 52.2 48.1 42.1 Number of peoplewith wage 0.4 0.4 0.6 0.5 0.4 Number of peoplewith nonfarmrural microenterprise 0.6 0.6 0.9 0.8 0.7 Household assets Householdowns bike 26.0 31.0 36.0 43.0 31.0 Householdowns radio 46.0 51.0 62.0 73.0 53.0 Householdhas improvedstorage 11.0 12.0 16.0 18.0 13.0 Number of fields 4.3 4.2 4.5 4.3 4.3 Total area "owned" 1.7 1.9 2.0 2.7 2.0 Area cultivatedwith field crops 1.6 1.7 1.9 2.3 1.8 Access topublic services Receivedextension info 13.4 13.7 18.7 21.7 15.7 Receivedprice information 35.8 38.5 49.2 47.6 40.4 Technology Cultivatedtobacco 1.7 2.2 3.2 5.8 2.7 Cultivated cotton 5.3 5.5 4.6 8.7 5.7 Used irrigation (any) 6.0 4.0 6.0 8.0 6.0 Used improvedseeds (maize) 5.O 4.0 7.0 8.0 5.0 Usedchemicalfertilizers 2.0 4.0 4.0 7.0 4.0 Usedpesticides 4.0 5.0 6.0 8.0 5.0 Usedanimaltraction 8.0 9.0 11.2 11.1 9.2 Household belongs to an association 5.8 7.1 7.2 10.3 6.9 Source: TIA 2002-05 Panel data. 63 AppendixA. Chapter Tables Table A3.18. RuralPovertyand Crop IncomeDiversification Dynamics,2002-05 (percent) Poverty Transition Status Crop income diversijkation Stayed Became Escaped Stayed All dynamics, 2002-05 Poor Poor Poverty Nonpoor Households Inand out food marketing Never had food sales 36.5 24.4 28.5 25.8 31.6 Lost food sales market 19.4 23.3 12.3 16.5 18.3 Entered food market 15.5 12.4 24.4 15.8 16.7 Maintained food market 28.6 39.9 34.8 41.9 33.5 100.0 100.0 100.0 100.0 100.0 Inandout ofcashcrops Never had a cash crop 54.0 44.4 48.9 38.5 49.3 Lost cash crop 18.8 22.1 14.6 18.7 18.6 Entered cash crops 11.7 13.0 17.4 14.0 13.3 Maintained cash crops 15.5 20.4 19.2 28.8 18.9 Source; TIA 2002-05 Panel data. Table A3.19. RuralHouseholdCrop Market Participationand Outcomes,by Poverty Transition Status, 2002 and 2005 Poverty Food Crop Markets Cash Crop Markets transition status Survey Percent of Gross Sales Net Sales Percent of Gross Sales Net sales 2002-05 Year Households (Mts) (Mts) Householh (Mts) (Mts) 2002 48.0 208.5 206.4 34.3 236.1 230.6 Stayed poor 2005 44.1 266.6 261.2 27.5 267.4 255.3 2002 63.2 708.6 700.9 42.5 638.0 625.6 Became poor 2005 52.3 344.0 -925.3 33.4 291.4 254.4 2002 47.1 228.9 225.3 33.7 250.4 240.1 Escapedpoverty 2005 59.2 890.2 876.9 36.5 973.6 971.5 2002 58.4 952.4 916.8 47.5 1404.3 1345.6 Stayed nonpoor 2005 57.7 1365.2 1330.3 42.8 1804.6 1782.0 2002 51.7 400.0 391.7 37.4 477.3 461.8 All households 2005 50.1 556.2 358.9 32.1 631.O 615.4 Source:TIA 2002-05 Paneldata. 64 Appendix A. Chapter Tables Table A3.20. Rural PovertyDynamics and Off-farm IncomeDiversification,2002-05 Poverty TransitionStatus Offarm income diversi3cation Stayed Became Escaped Stayed All dynamics Poor Poor Poverty Nonpoor Households Wageincome status Never hadwage income 66.1 58.9 58.6 57.3 62.4 Lost wage income 7.4 13.8 3.4 6.5 7.5 Enteredwage market 21.0 17.5 30.3 15.5 21.3 Maintained wage income 5.5 9.7 7.7 20.8 8.8 Nonfarm MSE income status Never had MSE income 39.9 30.0 27.6 25.3 34.1 Lost MSE income 14.8 27.2 8.6 16.0 15.7 Entered MSE activity 23.2 18.1 34.1 21.1 24.1 Maintained MSE income 23.2 24.6 29.7 37.5 26.1 Source:TIA 2002-05 Panel data. MSE: Micro or small enterprise. Table A3.21. RuralHouseholdswith Income from Source, by Poverty Transition Status, 2002 and 2005 (percent) Households with Incomefrom Source Poverty transition status Survey Crop Livestock Wage Nonfarm Migration 2002-05 Year Income Sales Labor Enterprise Income 2002 100.0 28.1 12.9 36.9 19.7 Stayed poor 2005 100.0 25.7 26.5 45.3 23.1 2002 100.0 40.3 23.6 51.8 22.0 Became poor 2005 100.0 23.7 27.2 42.7 20.5 2002 100.0 28.3 11.1 38.3 17.5 Escaped poverty 2005 100.0 29.4 38.0 63.8 27.4 2002 100.o 37.3 27.2 53.5 24.1 Stayed nonpoor 2005 100.0 27.1 36.3 58.6 24.6 2002 100.0 31.4 16.3 41.9 20.3 All households 2005 100.0 26.3 30.1 50.2 23.7 Source: TIA 2002-05 Panel data. 65 AppendixA. Chapter Tables Table A3.22. Changes in Major Sources of RuralIncome, by PovertyTransition Status, 2002 and 2005 (percent) Major Sources of Income Poverty transition status Survey Crop Livestock Wage Nonfarm Migration 2002-05 Year Income Sales Labor Enterprise Income Total 2002 77.7 2.2 5.5 11.4 3.2 100.0 Stayedpoor 2005 65.9 2.3 9.9 11.4 5.3 100.0 2002 54.5 1.9 14.1 25.5 3.9 100.0 Became poor 2005 69.7 1.3 9.8 15.2 3.9 100.0 2002 74.5 2.7 7.3 11.6 3.8 100.0 Escapedpoverty 2005 47.0 1.2 20.3 28.0 3.6 100.0 2002 52.7 1.3 20.5 21.5 3.9 100.0 Stayednonpoor 2005 51.1 1.2 19.9 23.9 4.0 100.0 2002 69.9 2.1 9.4 15.0 3.5 100.0 All households 2005 60.9 1.8 13.3 19.4 4.6 100.0 Source: TIA2002-05 Panel data. 66 S o q " 9 S f ? " W b N O Q \ b l o O cW? 1 c ? 9 b N O 0 3 0 3 0 0 2 2 3 0 '-1999 W W N O - " ! q 0 & l o - 0 Auuendix A. Chauter Tables Table A3.24. Rural Poverty Transitions and Diversification into Various Types of Nonfarm Businesses, 2002 and 2005 (percent) Poverty Transition Status Escaped Stayed All StayedPoor Became Poor Poverty Nonpoor Households 2002 2005 2002 2005 2002 2005 2002 2005 2002 2005 Typesof Nonfarm activities Natural resource extraction 15.0 17.6 15.3 14.8 13.3 21.7 14.9 17.9 14.7 17.7 Firewoodcollection 2.8 2.8 2.7 2.0 2.4 4.3 1.9 3.6 2.6 3.1 Charcoal production 2.9 2.9 2.4 1.8 2.0 3.6 1.6 3.0 2.4 2.9 Grass cane 3.6 5.5 3.9 4.4 1.4 8.4 3.1 4.3 3.2 5.6 Wood collection 1.1 1.7 2.2 1.3 1.2 2.8 1.o 1.8 1.3 1.8 Collectionofwild fruits 0.5 0.3 1.9 0.6 1.0 1.5 0.7 1.1 0.8 0.7 Hunting 0.7 1.2 1.0 1.0 0.5 2.0 1.4 1.2 0.8 1.3 Fishing 5.7 5.6 9.0 5.5 6.2 7.1 8.0 7.6 6.6 6.2 Total 15.0 17.6 15.3 14.8 13.3 21.7 14.9 17.9 14.7 17.7 Manufacturinghervices Carpenter 2.9 7.8 6.6 6.5 3.0 6.4 4.2 7.4 3.7 7.3 Taylor 1.3 1.1 1.3 2.2 1.5 2.3 2.9 2.0 1.6 1.6 Brickmaking/blacksmith 1.7 1.4 1.6 1.1 1.2 3.8 2.7 3.7 1.8 2.1 Grainmilling 0.3 0.1 0.7 0.4 0.4 0.3 0.3 0.3 0.4 0.2 Bicycle/radiorepairing 0.5 1.3 0.7 1.6 0.6 2.7 0.1 2$4 0.5 1.8 Other manufacturing 3.3 3.7 6.6 2.1 2.9 5.6 4.1 5.8 3.9 4.1 Total 9.8 14.8 16.9 13.5 9.4 19.7 13.7 20.1 11.4 16.3 Trading (buyhell) Buyinglselling beverages 2.6 3.9 6.8 4.8 5.2 13.1 7.8 15.4 4.5 7.4 Foodproducts 3.1 1.3 7.2 2.4 4.6 8.3 11.8 6.9 5.3 3.6 Nonfoodproducts 1.9 3.0 5.8 1.9 2.8 9.4 3.6 7.5 2.9 4.6 Largelivestockand products 0.3 0.5 0.5 0.4 0.8 1.5 1.3 2.0 0.5 0.9 Small livestockand products - 0.9 - 1.3 - 2.8 - 2.2 - 1.5 Total 7.3 8.1 19.1 9.3 12.9 24.6 22.8 26.8 12.4 14.1 Source: TIA 2002-05 Panel data. 68 Amendix A. ChaDter Tables Table A3.25. Structure of RuralHouseholdIncome, by Quintile and Zone, 1996,2002, and 2005 Quintiles of net Incomefrom Source by Quintile and Year household incomeper adult equivalent and Survey Crop Livestock Wage Nonfarm region Year Income Sales Labor Enterprise Total Quintile 1996 92.5 1.6 2.8 3.1 100.0 2002 85.3 4.4 2.1 8.3 100.0 Lowest 2005 77.8 3.5 8.0 10.7 100.0 1996 87.5 2.0 1.7 8.8 100.0 2002 84.4 3.6 1.8 10.2 100.0 2nd 2005 72.8 4.3 7.2 15.6 100.o 1996 81.9 1.4 1.8 14.9 100.0 2002 75.8 3.8 6.3 14.1 100.0 3rd 2005 63.8 3.4 11.1 21.7 100.0 1996 78.2 1.1 2.4 18.4 100.0 2002 61.0 3.9 14.6 20.5 100.0 4th 2005 54.1 3.1 18.2 24.6 100.0 1996 74.8 1.o 2.1 22.0 100.0 2002 38.7 2.9 25.9 32.5 100.0 Hiehest 2005 42.4 1.9 26.8 28.9 100.0 Rural region 1996 89.6 0.9 1.9 7.6 100.0 2002 77.2 2.9 5.6 14.3 100.o North 2005 64.5 2.5 11.2 21.8 100.0 1996 79.0 1.8 1.6 17.6 100.0 2002 68.7 4.6 9.9 16.8 100.0 Central 2005 63.1 3.5 13.9 19.4 100.o 1996 78.6 1.6 3.7 16.1 100.0 2002 63.0 3.5 15.0 18.5 100.0 South 2005 54.6 3.8 20.1 21.4 100.0 1996 83.0 1.4 2.1 13.4 100.0 2002 70.9 3.8 9.1 16.2 100.0 All rural households 2005 63.4 3.3 13.6 19.7 100.0 Source: TIAdata for 1996,2002, and 2005. 69 AuuendixA. Chauter Tables CHAPTER4 Table A4.1. Sectoral Expenditures as a Percentage of Total Expenditures, 1999-2006 1999 2000 2001 2002 2003 2004 2005 2006 General administration 16.9 15.3 7.2 8.8 13.7 9.2 10.2 19.2 Education 14.4 21.7 21.7 15.9 21.5 21.8 20.4 19.9 Primarylsecondaryltechnical 11.3 18.8 17.2 13.9 18.4 18.6 17.8 16.8 Higher education 3.1 2.9 4.4 2.0 3.2 3.2 2.6 3.1 Health 12.0 14.1 9.7 10.3 11.5 11.9 13.1 15.8 HealtWgeneral 12.0 14.1 9.2 9.5 11.2 11.5 12.1 14.3 HIV/AIDS 0.0 0.0 0.5 0.8 0.4 0.4 1.o 1.4 Infrastructure development 11.9 17.2 10.6 11.9 13.5 11.5 17.2 15.7 Roads 0.0 0.0 2.7 8.8 10.3 9.2 12.4 9.8 Water, sanitation, and public works 0.0 0.0 7.8 3.1 3.2 2.3 4.8 5.9 Agriculture and rural development 4.7 6.9 3.1 4.6 4.1 4.5 4.8 3.5 Governance andjudicial system 7.9 8.6 7.2 8.0 9.4 10.1 8.8 9.2 Security and public order 5.8 5.8 4.7 4.9 5.6 5.9 4.9 4.2 Governance 0.5 1.o 1.1 1.4 1.4 1.5 1.5 2.8 Judicial system 1.7 1.8 1.4 1.7 2.4 2.7 2.4 2.3 Energy and mineral resources 3.4 4.4 2.1 2.4 2.9 2.4 2.3 0.4 Social action and labor and employment 1.o 1.7 1.2 1.2 1.2 1.1 0.9 1.1 Social actions 0.6 1.3 0.9 0.9 0.8 0.7 0.6 0.7 Labor and employment 0.4 0.4 0.3 0.3 0.4 0.4 0.4 0.4 Other sectorsa 27.9 10.2 37.2 36.9 22.2 27.5 22.3 15.2 Total expenditureb 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Total expenditure as apercent of GDP 24.1 25.5 31.7 27.5 23.6 22.2 24.6 28.8 Expenditure in PARPA priority areas aspercent of total expenditure 55.2 74.5 61.2 65.3 63.9 65.0 63.0 66.3 Source:MPF 1999-2006. a. This is a group of sectors that includes communications; recreation, culture, and religion; housing and community development; tourism; construction; and nonspecifiedexpenditures. Given the difficulty of systematically reporting on these itemsindividually, they are lumpedinto a single category. b. Total expenditure excluding bankrestructuringcosts, net lending, and interest payments. 70 AppendixA. Chapter Tables Table A4.2. GovernmentExpendituresin Education,by Type, 2002-04 (percent) Education level 2002 2003 2004 Primary 63.2 63.9 61.0 Secondary general 15.4 11.5 13.5 Technical and vocational 2.3 3.0 3.8 Higher education 17.5 18.7 17.3 Other educationa 1.6 2.9 4.6 Source: Relutdrios de Execup7o Orpmental (mapa 4), 2002,2003, and2004. a. Other education includes adult education, teacher training, andthe like. Table A4.3. Number of EP1-2 Schools by Area in Mozambique, 1996-2005 Region 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 EP1 Rural North 1,536 1,715 1,962 2,122 2,256 2,406 2,502 2,605 2,752 2,811 Central 1,878 2,011 2,060 2,528 2,709 2,628 3,103 3,221 3,571 3,773 South 915 999 1,090 1,214 1,308 1,390 1,436 1,442 1,539 1,578 Total 4,329 4,725 5,112 5,864 6,273 6,424 7,041 7,268 7,862 8,162 EPl Urban North 110 122 118 120 105 133 147 147 160 163 Central 103 85 64 109 116 116 116 128 132 135 South 191 189 197 203 211 218 221 227 234 236 Total 404 396 379 432 432 467 484 502 526 534 EP2 Rural North 59 59 76 97 99 156 196 208 283 340 Central 71 71 93 153 180 238 296 321 434 522 South 88 91 117 124 135 188 251 236 306 349 Total 218 221 286 374 414 582 743 765 1,023 1,211 EP2 Urban North 13 19 18 22 28 42 42 46 68 75 Central 16 20 21 33 41 55 63 73 106 113 South 65 67 81 87 94 114 123 125 177 195 Total 94 106 120 142 163 211 228 244 351 383 Source: Ministry o f Educationand Culture (MEC) database. EPl: Primary grades 1-5. EP2: Primary grades 6 7 . 71 Amendix A. Chauter Tables Table A4.4. Number of Teachers and Proportion of Unqualified Teachers, 1997 and 2003 Number of Teachers Proportion UnqualiJied School level 1997 2003 1997 2003 EP1 28,715 42,847 29.6 42.2 EP2 3,982 9,139 21.1 34.6 ES1 1,308 3,523 18.0 37.2 ES2 219 657 12.3 16.8 Source: MEC database. EP1:Primary grades 1-5. EP2: Primary grades 6-7. ESI:Secondary grades 8-10. ES2: Secondary grades 11-12. Table A4.5. Pupil-Teacher Ratio Trends at the National Level, 1992-2005 School Pupil-Teacher Ratios year EP1 EP2 1992 53.9 17.4 1993 54.5 18.0 1994 56.9 19.3 1995 57.4 18.6 1996 58.7 20.3 1997 58.1 34.6 1998 58.4 30.8 1999 59.0 29.9 2000 61.2 29.8 2001 62.7 34.5 2002 63.7 38.5 2003 61.1 47.4 2004 65.8 30.5 2005 74.0 32.2 Source: MEC database. EP1:Primary grades 1-5. EP2: Primary grades 6-7. 72 Appendix A. Chapter Tables Table A4.6. Pupil-Teacher Ratios in EP1Schools by Province, 1996-2005 Province 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 Niassa 46.1 44.7 44.7 40.7 43.1 44.3 49.3 46.0 44.1 61.3 Cab0 Delgado 47.1 52.8 53.8 54.0 65.3 72.4 71.8 68.7 71.2 77.2 Nampula 47.4 51.1 51.6 53.6 60.3 62.8 65.2 59.3 86.3 75.6 Zambezia 65.2 63.6 66.7 70.9 72.8 75.4 80.3 84.9 72.8 103.0 Tete 50.6 46.5 45.7 47.3 48.7 51.7 50.9 52.3 59.9 69.9 Manica 54.0 57.1 59.3 60.5 57.0 58.9 63.3 57.6 60.5 65.5 Sofala 54.2 53.5 59.2 63.4 69.2 67.2 71.7 67.8 74.5 86.3 Inhambane 63.8 65.6 66.2 69.7 65.9 67.6 62.8 59.2 59.3 66.0 Gaza 78.7 74.8 73.9 69.5 67.1 64.4 58.6 54.4 56.0 59.6 Maputo 78.8 74.9 70.6 58.2 58.4 55.0 54.5 52.2 55.6 58.6 Maputo city 64.0 57.5 54.2 56.0 55.0 57.3 58.1 55.2 60.4 64.7 Total 58.7 58.1 58.4 59.0 61.2 62.7 63.7 61.1 65.8 74.0 Source: MEC database. Table A4.7. Net EnrollmentRates by SelectedGroups and Levelof Education,1997 and 2003 (percent) Group EPI (age 6 1I) EP2 (age 12-13) ESI (age 14-1 6) ES2 (age I7-1 8) 1997 2003 1997 2003 1997 2003 1997 2003 Area Rural 34.9 57.7 2.6 4.0 0.8 0.6 - 0.1 Urban 56.8 75.9 18.9 19.9 9.6 13.9 2.5 2.9 Gender Male 42.3 65.1 5.9 9.6 2.8 5.1 0.9 1.7 Female 36.4 61.2 6.9 8.6 3.0 5.9 0.4 0.7 Quintile Lowest 29.9 58.9 3.1 7.0 1.7 1.8 - 0.6 2nd 36.0 59.6 2.0 8.2 0.5 4.8 0.3 0.5 3rd 40.4 60.6 6.6 6.0 1.6 4.6 0.9 0.9 4th 44.5 66.3 6.5 10.0 4.1 7.0 0.8 0.6 Highest 50.1 72.8 17.4 15.3 8.6 10.0 1.2 3.6 Province Niassa 32.4 49.7 5.1 4.7 0.6 2.2 - 0.3 Cab0 28.0 60.9 0.7 9.1 0.7 2.5 - 2.6 Delgado Nampula 38.6 50.7 0.3 4.4 0.02 3.5 1.2 - Zambezia 32.4 61.5 2.4 3.2 1.9 2.9 0.2 1.1 Tete 34.5 54.8 3.9 5.0 1.4 2.9 - - Manica 38.7 68.6 5.0 15.8 0.4 5.2 - 0.8 Sofala 28.7 61.7 8.3 13.9 3.6 5.o - 1.1 Inhambane 41.4 76.6 12.9 13.4 1.6 7.1 2.1 2.0 Gaza 58.8 79.2 3.2 13.2 2.2 5.5 - 0.4 Maputo 58.0 85.9 9.8 17.3 5.5 12.2 0.1 0.8 Maputo 69.6 83.4 22.3 27.6 15.7 17.9 2.6 4.9 city .... All 39.3 63.1 6.4 9.1 2.9 5.5 0.6 1.2 Source: IAF data for 1997 and 2003. EPl: Primary grades 1-5. EP2: Primary grades 6-7. ES1: Secondary grades 8-10. ES2:Secondary grades 11-12. -isnotavailable 73 Appendix A. Chauter Tables TableA4.8. Net Primary School Enrollment,by Gender and ConsumptionQuintile, 1997 and 2003 (percent) All Girls Boys 1997 2003 1997 2003 1997 2003 Quintile National Lowest 39.0 65.4 34.1 65.2 42.3 65.6 Highest 62.0 79.4 55.8 79.0 66.4 80.0 All 51.0 70.5 45.1 69.0 54.1 71.8 Rural Lowest 35.0 63.5 30.8 63.8 39.2 63.3 Highest 45.4 72.1 39.0 70.4 53.5 73.6 All 43.6 65.3 38.5 63.5 48.7 67.0 Urban Lowest 46.4 70.1 42.8 68.8 49.5 71.3 Highest 80.6 90.8 78.9 90.6 82.3 91.0 All 64.4 82.5 61.2 81.4 67.8 83.6 Region North 45.3 60.0 40.2 58.8 50.7 61.0 Central 41.8 69.4 35.7 66.3 47.8 72.4 South 69.4 87.2 67.3 88.1 71.8 86.4 Source: IAF data for 1997 and 2003. Note: Consistent with 2003 urban and rural definitions. Table A4.9. Gross and Net EnrollmentRatios,by Gender, 2005 GrossEnrollment Ratio Net Enrollment Ratio Province Male Female Gender Gap Male Female Gender Gap Niassa 145 125 20 94 88 6 Cab0 Delgado 145 119 26 84 75 9 Nampula 128 105 23 73 67 6 Zambezia 141 116 25 88 78 10 Tete 140 124 16 92 88 4 Manica 151 128 23 87 81 6 Sofala 135 111 24 82 73 9 Inhambane 139 137 2 84 89 -5 Gaza 144 143 1 87 92 -5 Maputo 159 160 -1 103 108 -5 Maputo city 140 143 -3 94 100 -6 Total 140 123 17 86 81 5 Source: MEC database. 74 Amendix A. ChaPter Tables TableA4.10. Gross EnrollmentRates, by Gender and Area ofResidence,2003 School level Urban Rural Boys Girls Boys Girls EP1 113.1 109.7 104.8 86.3 EP2 120.6 110.1 37.2 19.5 ES1 63.7 49.4 4.1 2.2 ES2 22.1 14.4 - 0.3 Source: IAF data for 2003. EP1: Primary grades 1-5. EP2: Primary grades 6-7. ESI: Secondary grades 8-10. ES2: Secondary grades 11-12. -isnotavailable Table A4.11. Enrollmentin Schoolby Age, ConsumptionQuintileand Gender,2003 (percent) Lowest 2nd Quintile 3rd Quintile 4th Quintile Highest Age Boys Girls Boys Girls Boys Girls Boys Girls Boys Girls 6 30.5 34.8 38.1 31.3 41.8 25.8 51.1 35.9 58.7 53.4 7 49.8 46.4 49.1 56.5 47.7 49.0 62.8 47.2 59.8 68.7 8 68.7 58.5 67.8 56.2 65.2 60.5 69.0 69.5 81.8 75.3 9 72.0 67.5 70.4 68.2 78.4 67.5 83.9 80.1 88.0 89.5 10 58.5 78.0 74.2 68.4 82.3 76.8 76.3 84.2 80.8 79.5 11 85.7 77.0 84.4 79.0 76.8 81.6 81.8 80.0 92.6 83.4 12 73.6 75.4 80.4 67.2 80.9 80.1 78.0 74.1 78.1 80.9 13 77.7 68.8 72.3 69.2 71.9 78.3 90.9 72.9 94.3 87.7 14 71.1 52.8 59.5 73.0 85.0 75.0 67.7 68.8 79.2 77.1 15 58.8 62.2 77.3 68.0 63.3 55.1 72.7 48.4 66.8 67.2 16 64.1 59.9 48.4 38.2 64.8 59.2 58.8 39.1 62.7 27.8 17 51.7 36.1 61.2 27.1 65.8 27.7 58.5 43.2 68.4 41.8 18 47.1 28.6 46.3 15.3 43.4 11.5 37.1 17.0 59.9 25.0 19 40.5 9.8 32.6 14.7 54.2 16.1 37.4 11.1 37.2 26.7 Source: IAF data for 2003. 75 Amendix A. ChaPter Tables Table A4.12. Gross and Net Enrollment Rates, by Education Level, 1996-2005 (percent) Gross Enrollment Rates EPI EP2 ESI e52 Schoolyear (age 6-1 I) (age 12-1 3) (age 14-1 6) (age 17-1 8) 1996 67.5 18.5 5.9 1.6 1997 73.8 19.6 5.8 0.7 1998 78.6 21.0 6.0 1.6 1999 85.3 22.4 6.3 1.4 2000 92.1 25.3 7.6 1.5 2001 101.2 29.2 8.5 2 2002 106.5 32.9 10.6 2.4 2003 112.7 36.9 12 2.9 2004 121.2 42.7 13.8 3.4 2005 131.3 47.0 17.0 3.7 Net Enrolment Rates EPI EP2 ESI e52 1996 39.3 2.2 1.3 0.3 1997 42.5 2.2 1.4 0.2 1998 45.1 2.5 1.3 0.5 1999 50.1 2.5 1.4 0.2 2000 54.7 2.7 1.7 0.2 2001 61.1 3.3 1.9 0.3 2002 64.1 3.6 2.3 0.4 2003 69.4 4.5 2.7 0.5 2004 75.6 5.6 3 0.5 2005 83.4 6.7 3.9 0.6 Source: MEC database. EP1: Primary grades 1-5. EP2: Primary grades 6-7. ESl: Secondary grades 8-10, ES2: Secondary grades 11-12. 76 Atmendix A. ChaDter Tables Table A4.13. Primary School(EP1) Completionand DropoutRatesby Province,1997 and 2003 Primary School Primary School (EPI) Completiona Dropout Province 1997 2003 1997 2003 Niassa 62.0 61.7 17.9 19.5 Cab0 Delgado 57.9 64.5 19.6 19.1 Nampula 59.1 64.9 18.7 17.0 Zambezia 51.0 57.3 26.8 20.5 Tete 61.0 68.7 24.1 14.8 Manica 62.7 67.9 14.3 11.8 Sofala 67.8 73.2 11.0 10.7 Inhambane 63.5 68.0 14.2 10.7 Gaza 60.1 67.7 16.6 13.2 Maputo province 60.6 75.3 15.5 8.8 Maputo city 64.2 76.3 11.3 5.9 Total 60.6 67.5 17.1 13.8 Source: MECdatabase. a. Primary school (primary grades 1-5) completion: the data presentmodified completion rates, meaning the enrollment inthe final year ofthe cycle, regardlessof age, expressedas a percentageofthe segment of the population that is at the age correspondingto the official age for graduation. Table A4.14. BenefitIncidence:EducationExpenditureAllocation by Quintile, 2003 (percent) DistributionAcross Ruintiles &om householdsurvey) Education Lowest 2nd 3rd 4th Highest Primary education 21.8 20.6 19.6 19.5 18.5 Secondary education 12.8 13.6 17.2 17.8 38.6 TVE 5.2 6.0 14.7 13.6 60.4 Adult literacy 18.1 17.8 26.3 21.1 16.8 Teachertraining 5.3 16.2 10.3 5.4 62.8 Higher education 5.O 3.1 4.2 2.2 85.5 Total education 2003 16.7 16.0 16.1 15.6 35.6 Source:IAF data for 2003. Table A4.15 BenefitIncidence: ExpenditureAllocation,by Quintile and Gender,2003 Primary School Secondary School All Public Schools (EPI + EP2) (ESI + ES2) Boys Girls Difference Boys Girls Difference Boys Girls Diflerence Quintile (I) (2) (3) (4) (5) (6) (7) (8) (9) Lowest 11.3 9.6 1.7 11.9 9.9 2.0 7.7 5.1 2.6 2nd 11.0 8.8 2.2 11.6 9.1 2.5 8.3 5.2 3.1 3rd 10.6 9.0 1.6 10.8 8.8 2.0 10.6 6.6 4.0 4th 10.3 9.1 1.2 10.5 9.1 1.4 10.7 7.0 3.7 Highest 10.7 9.6 1.1 9.6 8.8 0.8 22.5 16.1 6.4 All 53.9 46.1 7.8 54.4 45.7 8.7 59.8 40.0 19.8 Source:IAF data for 2003. 77 Annendix A. Chanter Tables Table A4.16. Perceptions of Changes in Education, by Area of Residence and Gender of the HouseholdHead, 2006 (percent) Gender of the Household Head Changes in perception of All education Male Head Female Head Household Urban areas Improved 70.3 72.8 71.2 Didnot change 24.2 18.4 22.2 Worsened 5.5 8.8 6.6 Total 100.0 100.0 100.0 Rural areas Improved 57.3 44.2 53.6 Did not change 21.6 24.6 22.5 Worsened 21.1 31.2 23.9 Source: PVS data 2006. Note: Sample not representative. Table A4.17. Perceptions of Changes in Education,by Area of Residence and Asset Tercile, 2006 (percent) HouseholdAsset Tercile Changes inperception of All education Low Medium High Households Urban areas Improved 64.9 72.2 76.1 71.2 Didnot change 26.1 24.1 16.2 22.2 Worsened 9.0 3.8 7.7 6.6 Total 100.0 100.0 100.0 100.0 Rural areas Improved 62.6 49.5 48.9 53.6 Did not change 20.9 23.2 23.3 22.5 Worsened 16.5 27.4 27.8 23.9 Source: PVS data for 2006. Note: Sample not representative. 78 Amendix A. ChaDter Tables TableA4.18. Reasonsfor ImprovementsandWorseningin Education, by Area of Residence, 2006 (percent) Area of Residence Reasonfor change Urban Rural Reasonsfor improvement Expansion o f the school network 66.9 61.5 Increase in school teachers 19.5 8.8 Improved curricula 12.8 25.7 Other 0.8 4.1 Reasonfor worsening Lack of schools 8.3 36.4 Distance 0.o 37.9 Lack o f teachers 8.3 12.1 Lack of books 29.2 0.0 Lack o f desks 16.7 10.6 Curmptionhribes 37.5 1.5 Other 0.0 1.5 Source: PVS data for 2006. Note: Sample not representative Table A4.19. SelectedIndicatorsof GovernmentHealth Expenditure,1999-2003 Government Health Expenditure as Percent Per Capita Government Expenditure on Countries of Total Government Expenditure Health" 1999 2000 2001 2002 2003 1999 2000 2001 2002 2003 Mozambiwe 12.0 14.1 9.7 10.3 11.5 7 8 6 7 7 South Africa 10.7 10.9 11.2 11.6 10.2 105 100 89 80 114 Tanzania 12.4 12.6 12.8 12.8 12.7 5 6 6 6 7 Uganda 9.4 9.0 9.6 10.8 10.7 5 4 5 5 5 Zambia 9.5 9.1 10.2 10.6 11.8 8 9 11 11 11 Zimbabwe 10.0 7.4 9.3 9.8 9.2 17 21 25 50 14 Source: WHO 2006. Note: For Mozambique, CGE (1999-2000) BudgetExecutionReports.(2001-03). a. At average exchange rateUSD; computedby WHO for comparability, not necessarily the same as the official statistics, which may have usedalternative methods. 79 Amendix A. Chanter Tables Table A4.20. Reasons for not AccessingHealthcare,Women, 2003 (percent) Concern Knowing Getting ThereMay Where to Permission Getting Distance to Having to Not not Be a Quintile Gofor to Gofor Moneyfor Health Take Wanting to Female Treatment Treatment Treatment Facility Transport GoAlone Provider Lowest 22.0 13.1 73.7 79.0 76.5 28.4 12.7 2nd 15.3 12.3 69.6 68.4 66.6 24.0 10.4 3rd 11.5 7.9 60.3 58.3 55.6 21.4 9.2 4th 6.6 5.8 50.0 35.9 34.8 15.1 8.0 Highest 5.7 5.7 34.4 18.9 18.0 10.7 7.0 Residence Rural 15.3 10.2 65.6 68.1 64.6 24.4 10.6 Urban 7.2 6.8 42.6 23.1 24.3 12.0 7.5 Total 12.3 9.0 57.1 51.6 49.8 19.8 9.5 Source: DHS 2003. Table A4.21. Number of Live Births Attended at Health Facility and Vaccination Coverage, by Province, 1997-2003 (percent) Live Births Attended at Public Children 12-23 Months Fully Provinces Health Facility Vaccinated 1997 2003 Change 1997 2003 Change Niassa 44.4 45.9 1.5 48.2 46.6 -1.6 Cab0 Delgado 31.O 29.6 -1.4 25.4 57.9 32.5 Nampula 28.5 36.8 8.3 34.4 53.9 19.5 Zambezia 23.5 32.6 9.1 23.2 44.7 21.5 Tete 41.0 47.4 6.4 48.0 55.0 7.0 Manica 43.0 55.7 12.7 46.5 61.6 15.1 Sofala 35.4 51.4 16 49.6 63.9 14.3 Inhambane 56.3 49.6 -6.7 71.7 90.6 18.9 Gaza 65.7 62.6 -3.1 63.0 82.3 19.3 Maputo province 75.7 84.8 9.1 61.9 92.5 30.6 Maputo city 86.5 88.2 1.7 82.0 91.3 9.3 Rural 33.3 33.8 0.5 36.4 56.0 19.6 Urban 81.3 80.6 -0.7 85.0 80.5 -4.5 Total 43.7 47.4 3.7 47.3 63.3 16.0 Source: DHS 1997 and 2003. 80 Appendix A. Chapter Tables Table A4.22. Regional Comparison of Welfare Indicators (percent) Infant Severe Female HIVAIDS Region Mortality Stunting Malnutrition Prevalence Malawi (2002) Average 112.5 24.4 8.8 14.1 Rural-urban ratio 1.4 1.9 1.7 - Low-high ratio 1.5 2.9 1.7 - Mozambique (2003) Average 123.6 17.9 8.1 16.2 Rural-urban ratio 1.4 2.2 1.6 - Low-high ratio 2.0 4.2 2.0 - Tanzania (2004) Average 82.5 12.3 9.4 6.5 Rural-urban ratio 1.2 1.8 1.3 - Low-high ratio 1.4 4.7 1.6 - Uganda (2002) Average 89.4 23.8 10.4 6.7 Rural-urban ratio 1.7 2.2 2.5 - Low-high ratio 1.8 . 1.4 3.1 - Zambia (2002) Average 93.9 22.1 15.0 17.0 Rural-urban ratio 1.3 1.7 1.54 - Low-high ratio 2.0 2.2 2.1 - Source: World Bank 2007, Socio-Economic Differences in Health, Nutrition, and Population, Country Reports; HIV/AIDS data are from UNAIDS/WHO(2006b) andare for 2005. Note: Infant mortality is the number of deaths to children under 12 months per 1,000 live births, based on experience during the 10years precedingthe survey. Severe stunting(height-for-age) i s the percentageof children aged 3 years (varies by survey), with a height-for-ageZ- score of below-3 standarddeviationsof the median reference standardfor their age. Female malnutrition is the percentageof women aged 15-29 years with a body mass index of less than 18.5, defined as weight inkilograms divided by square ofheight in meters. The low-highratio is highest quintile/lowest quintile. -is not available. 81 Amendix A. ChaDter Tables Table A4.23. Selected SocialOutcome Indicators (percent) Lfe HIV/AIDS Infant Under 5 Stunting Wasting Expectancy Prevalence Mortality Mortality (under (under age5) age5) 1997 2005 2000 2004 1997 2003 1997 2003 2003 2003 All 42.3 47.1 11.0 16.2 147 124 219 178 41.0 4.0 Area Urban 48.8 50.8 - - 101 95 150 143 29.2 3.1 Rural 40.2 45.7 - - 160 135 237 192 45.7 4.3 Province Niassa 42.2 45.1 6.2 11.1 134 140 213 206 47.0 1.3 CaboDelgado 37.9 42.4 7.5 8.6 123 177 165 240 55.6 4.1 Nampula 39.9 44.4 4.8 9.2 216 164 319 220 42.1 6.0 Zambezia 37.0 48.6 10.0 18.4 129 89 183 123 47.3 5.2 Tete 43.8 44.3 16.3 16.6 160 125 283 206 45.6 1.6 Manica 42.7 46.5 17.3 19.7 91 128 159 184 39.0 2.8 Sofala 42.2 44.8 20.6 26.5 173 149 242 206 42.3 7.6 Inhambane 46.0 49.6 7.8 11.7 151 91 193 149 33.1 1.3 Gaza 45.6 49.0 12.6 19.9 135 92 208 156 33.6 6.7 Maputoprovince 50.6 54.0 14.4 20.7 92 61 147 108 23.9 0.5 Maputo city 58.3 58.6 13.5 20.7 49 51 97 89 20.6 0.8 Quintile Poorest - - - - 188 143 278 196 49.3 5.6 Poorer - - - - 136 147 214 200 46.7 4.3 Middle - - - - 144 128 216 203 46.2 3.0 Richer - - - - 134 106 187 155 35.2 3.9 Richest - - - - 95 71 145 108 20.0 2.5 Source: Healthdata are taken from DHS, 1997 and2003; andIAF data for 1997 and 2003. Note: HIV/AIDS prevalence is the percentageof adults, ages 15-49, with HIV/AIDS. Stunting (height-for-age) is the percentage of children under age five who are below -2 standard deviations from the median of the InternationalReferencePopulation(not comparablewith 1997). Wasting(weight-for-height) is the percentage below-2 standarddeviations (not comparable with 1997). -isnotavailable. Table A4.24. Changesin Preventive Care and Home-BasedCare, 1997-2003 (percent) Lowest Quintile Highest Quintile Indicator 1997 2003 Change 1997 2003 Change Measles immunizationrate 33 61 84 94 96 3 DPT3 immunization rate 32 52 63 94 96 2 Fully immunized 20 45 129 85 90 6 Antenatal care at health provider 47 67 44 98 98 0 Use o f ORT at home 42 61 44 83 88 6 Source: DHS data for 1997and2003 data from World Bank 2005b. ORT: Oral rehydrationtherapy. 82 AppendixA. Chapter Tables Table A4.25. Preventive Care by Wealth Quintile and by Area ofResidence,2003 (percent) WomenFormaP Women Tetanus Children 12-23 Children 12-23 Antenatal Care ToxoidInjectionb Months withNo Months withAlF Quintile Last Birth Last Birth Vaccinations Vaccinations Lowest 67.1 60.5 19.9 45.2 2nd 82.5 73.2 7.9 53.6 3rd 86.0 79.2 7.4 60.9 4th 96.9 86.6 2.3 78.7 Highest 98.3 85.6 0.2 90.3 Residence Rural 78.9 70.9 11.5 56.0 Urban 97.0 86.4 2.2 80.5 Total 84.5 75.7 8.7 63.3 Source: DHS data for 2003. a. Formal: doctor, nurse, midwife, or auxiliary midwife (excluding traditional birthattendantdother). b. One, two, or more injections receivedduring most recent pregnancy. c. All vaccinations: BCG, measles, three doses each of DPT andpolio vaccine. Table A4.26. TreatmentWhen ShowingIllness Symptoms: Curative Care, 1997 and 2003 (percent) Children Treated Children Treated Quintile for A M for Diarrhea Sickb WhoSought Treatment Year 2003 2003 1997 2003 Lowest 42.4 41.6 46.4 53.4 2nd 44.7 45.0 50.8 53.2 3rd 48.9 60.0 50.8 56.9 4th 62.0 52.0 56.4 53.6 Highest 64.5 48.1 53.0 66.5 Pesidence Rural 46.6 46.3 47.1 50.1 Urban 62.4 53.1 72.9 75.1 rota1 51.4 48.5 51.9 57.0 Source:DHS data for 2003 (columns 1-2), IAF data for 1997 (column 3), and IAF data for 2003 (column 4). ARI=Acute respiratory infection. a. Percentage of children under age five with ARI symptoms (coughing, accompanied by short rapid breathing) for whom treatment was sought from a health facility or provider (excluding pharmacy, shops, and traditional practitioners). b. In IAF data for 1997 the recall period was last month whereas in IAF data for 2003 the recall period was last two weeks. 83 Appendix A. Chapter Tables Table A4.27. Stunting by Province, 1997 and 2003 Province 1997 2003 Change Niassa 54.9 40.9 -14.0 Cab0 Delgado 56.8 50.2 -6.6 Nampula 38.4 37.1 -1.3 Zambezia 37.3 41.1 2.8 Tete 45.7 41.7 -4.0 Manica 40.8 35.4 -5.4 Sofala 38.7 42.1 3.4 Inhambane 26.0 29.8 3.8 Gaza 30.0 31.3 1.3 Maputo 16.0 23.9 7.9 Maputo city 22.6 21.9 -0.7 Average 36.2 33.9 -2.3 Source: Simler and Ibrahimo 2005. Note: Stunting(low height-for-age): percentageof children under age three who are below-2 standarddeviations from the medianheight-for-ageofthe International 1 ReferencePopulation. Table A4.28. Perceptions of Changes in Health Services, by Area of Residence and Asset Tercile, 2006 (percent) HouseholdAsset Tercile Changes inperception of health All services Low Medium High Households Urban areas Improved 61.3 69.2 69.2 66.8 Didnot change 24.3 18.8 21.4 21.3 Worsened 14.4 12.0 9.4 11.9 Rural areas Improved 62.6 60.0 66.7 63.0 Didnot change 20.9 11.6 13.3 15.5 Worsened 16.5 28.4 20.0 21.7 Source: PVS data for 2006. Note: Sample not representative. 84 Amendix A. ChaDter Tables Table A4.29. Reasons for Changes in Health Services, by Area of Residence, 2006 bercent) Area of Residence Reasonfor the change Urban Rural Reasonsfor improvement Expansion ofthe health network 16.2 28.2 Increase instaff 14.1 4.0 Better service 69.3 66.7 Other 0.4 1.1 Reasonsfor worsening Lack of health facilities 2.3 8.3 Distance 0.0 35 Bad quality of service 60.5 21.7 Waiting time 14.0 0.0 Lack o f medicines 18.6 35 costs 2.3 0.o Lack o f professionals 2.3 0.0 Source: PVS data for 2006. Note: Sample not representative. Table A4.30. Perceptions of Changes in Health Services, by Area of Residence and Gender of the Household Head, 2006 (percent) Gender of the Household Head Changes inperception of health services Male Head Female Head All Households Urban areas Improved 68.6 63.2 66.8 Did not change 20.8 22.4 21.3 Worsened 10.6 14.4 11.9 Total 100.0 100.0 100.0 RuralAreas Improved 65.3 57.1 63.0 Did not change 15.1 15.6 15.5 Worsened 19.6 27.3 21.7 Total 100.0 100.0 100.0 Source: PVS 2006. Note; Sample not representative. 85 Appendix A. Chapter Tables Table A4.31. PROAGRI in TotalAgricultureSector Budget, 1999-2005 (percent) 1999 2000 2001 2002 2003 2004 2005 Components Expenditure in Agriculture PROAGRI 16.3 15.0 36.2 58.3 83.0 49.1 35.8 Institutionaldevelopment 6.1 6.6 16.7 37.6 58.4 8.6 7.2 Livestock 1.8 0.6 1.4 2.2 2.5 0.5 0.4 Extension 2.4 2.0 1.8 4.4 3.5 1.1 0.6 Crop production 1.2 0.6 3.7 5.O 2.9 2.2 2.4 Forestry and wildlife 3.9 1.1 2.7 1.5 1.7 0.7 0.5 Land management 0.6 1.5 3.2 3.3 3.4 1.4 1.o Research 0.4 1.6 4.0 3.2 5.8 5.7 9.9 Irrigation 0.0 1.o 1.o 1.1 1.4 0.5 0.3 Others 0.o 0.0 1.8 0.o 3.5 28.4 13.4 Source: Ministry of Agriculture, PROAGRI database 2006. Table A4.32. Structureof PROAGRI Budget, Current and Investment, 2000-05 (percent) 2000 2001 2002 2003 2004 2005 Recurrent expenditures 67.1 57.9 62.4 71.5 78.9 89.2 Wages and remunerations 4.7 3.2 4.5 7.1 8.8 7.O Other expenditureswith personnel 15.0 11.9 12.3 8.7 9.7 11.3 Goods 15.9 12.1 15.1 17.8 21.6 23.0 Services 30.2 28.9 29.0 36.8 37.4 44.6 Transfers to households 1.3 1.7 1.5 1.2 1.4 3.3 Capital expenditures 32.9 42.1 37.6 28.5 21.1 10.8 Constructions 2.9 8.5 5.9 6.4 6.8 2.6 Machinery and equipment 26.4 32.2 29.3 19.5 13.1 7.4 Other capital expenditures 3.5 1.4 2.5 2.6 1.1 0.8 Total 100.0 100.0 100.0 100.0 100.0 100.0 Source: Ministry of Agriculture, PROAGRI database 2006. Table A4.33. PROAGRIBudget by ExpenditureComponent, 1999-2005 (percent) Component 1999 2000 2001 2002 2003 2004 2005 Institutional development 37.3 43.8 46.2 64.5 70.4 17.6 20.2 Livestock 11.0 3.7 3.8 3.7 3.0 1.0 1.2 Rural extension 14.4 13.3 5.0 7.6 4.2 2.2 1.5 Support to agricultural production 7.1 4.3 10.1 8.6 3.5 4.4 6.8 Forestry and wildlife 24.1 7.5 7.5 2.6 2.1 1.4 1.5 Land management 3.8 10.2 8.8 5.7 4.0 2.8 2.8 Research 2.3 10.6 10.9 5.5 6.9 11.6 27.7 Irrigation 0.0 6.6 2.6 1.9 1.7 1.1 0.8 Other 0.0 0.o 5.O 0.0 4.2 58.0 37.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Source: Ministry of Agriculture, PROAGRI database, 1999-2005. 86 Appendix A. Chapter Tables Table A4.34. District Coverage for Extension Services in Mozambique, 2004 Number of Districts Districts Having At Least Some Extension Region Province ReceivingAt Least WorkersSupplied by Some Extension Services MINAG NGOS" Private Companiesb s Cab0 Delgado 14 7 16 12 Nampula 19 11 20 15 2 Niassa 13 5 14 6 - Manica 6 6 6 5 Sofala 10 9 9 0 Tete 10 5 7 10 0 2 Zambkzia 16 6 15 6 Gaza 11 5 11 0 5 Inhambane 11 6 13 0 Maputo 7 6 7 0 Total 117 66 111 72 Source: Coughlin 2006, derived from tables by Gemo, Eicher, and Teclemariam 2005 (pp. 53, 113-1 16), after minor adjustments and updates for the information about where the private cotton companies with extension workers are operating. The table above differs from that presented by Perumalpillai-Essex (2005, pS), which shows 143 districts (more than the country has, unless it also includedurbandistricts). Note: Total excludes the seven districts ofMaputo city. a. Whereas the statistics for MADER (Ministry for Agriculture and Rural Development) only report the districts with an extensionofice, the NGOs count any district where they render serviceswhether or not they have an office there. b. Whereas MINAG has had a strict definition of the qualifications for a person to be classified as an extension worker the NGOs and private companies use variable definitions and may well class some employees as extension workerswho would not qualify as such under MINAG's definition. Table A4.35. Rural Households Receiving Extension Information, by Location and Gender of the Head, 2002 and 2005 Householdr Receiving Extension Information 2002 2005 Rural region North 16.0 17.1 Central 13.6 12.8 South 7.8 14.2 Gender of head (rural) Male head 14.8 16.0 Female head 9.7 10.9 Source: TIA data for 2002 and 2005. 87 AuuendixA. Chauter Tables Table A4.36. RuralHouseholdsReceivingExtensionInformation,by Income Quintile, 2005 (percent) Use of Specific Techniques Intercropping Crop Rotation Line Planting Extension Extension Extension Recipients Nonrecipients Recipients Nonrecipients Recipients Nonrecipients Quintile Lowest 89.3 83.5 39.9 31.6 61.3 34.3 2nd 90.3 87.3 57.5 37.1 56.9 35.9 3rd 84.7 86.6 51.3 34.3 53.4 38.6 4th 90.9 85.3 54.9 37.3 64.6 40.6 Highest 91.8 86.1 39.9 34.4 62.1 46.5 Rural region North 85.7 82.4 63.3 36.8 62.0 31.5 Central 90.5 84.6 42.7 34.4 63.1 42.6 South 90.7 89.6 32.7 32.3 47.2 45.3 Gender of head (rural) Male head 88.2 85.4 52.9 37.0 60.2 41.3 Femalehead 93.8 86.7 34.4 28.6 55.8 30.6 All rural 88.4 84.7 50.1 34.9 59.8 39.0 Source: TIA data for 2005. 88 Amendix A. Chaoter Tables Table A4.37. RuralHouseholdsReceivingExtension Information, by Income Quintile and PovertyTransitionStatus, 2002 and 2005 (percent) Households Receiving ExtensionInformation DistributionAcross Groups 2002 2005 2002 2005 Quintile Lowest 8.7 12.2 13.6 16.4 2nd 12.2 15.6 19.9 22.1 3rd 15.5 17.3 24.3 22.3 4th 15.9 16.7 22.7 21.1 Highest 16.5 17.5 19.4 18.1 Poverty transitions (rural)" Stayedpoor 11.6 13.4 43.9 45.0 Becamepoor 18.4 13.7 19.6 12.9 Escapedpoverty 15.0 18.7 19.0 20.9 Stayednonpoor 15.8 21.6 17.5 21.1 All rural 13.5 15.7 100.0 100.0 Source: TIA data for 2002 and 2005. a. Only 2002-05 Panel Households. Table 4.A38. ExtensionWorker Density in Mozambique,2004 (percent) Extension Workers Region Province Population Extension Workers per 10,000Inhabitants Government NGOs Private Province Zone e Niassa 966,579 58 135 68 2.7 Cab0 Delgado 1,588,741 91 183 - 1.7 Nampula 3,563,224 121 291 - 1.2 1.3 Zambkzia 3,645,630 55 213 19 0.8 Tete 1,461,650 56 54 172 1.9 Manica 1,280,829 62 71 - 1.o 028 Sofala 1,582,256 86 26 - 0.7 1.2 Inhambane 1,401,2 16 54 95 - 1.1 Gaza 1,333,540 73 177 - 1.9 1 Maputo 1,074,793 52 64 - 1.1 1.4 Total 17,898,458 708 1,309 259 1.3 Source: Coughlin (2006) usingdata from Ministryo f Agriculture. -is not available. 89 Amendix A. ChaDter Tables Table A4.39. Access to Safe Water in Mozambique by Area, 1990,2005, and 2015 (percent) Area 1990 2005 MDG Target (2015) Urban 33 37 70 Rural 30 41 70 Total 31 40 70 Source: GoM, FIPAG, DNA databases. MDG: MillenniumDevelopmentGoal. Table A4.40. Overview of Working and PlannedWater Point Source, by Province,2001-03 Point Sources in 2001 Constructed Estimated Number Number not Percent not Number or Number Province Existing Working Working Functioning Rehabilitated Workingin 2002-03 2003 (a) (b) (c)=@)/(a) (d)=(a)+) (e) &I761-I =(d) (e) Niassa 745 219 29 526 235 Cab0 Delgado 1,225 409 33 816 240 1,056 Nampula 1,533 811 53 722 343 1,065 Zambezia 1,574 499 32 1,075 702 1,777 Tete 1,444 470 33 974 190 1,164 Manica 1,152 357 31 795 123 918 Sofala 1,226 253 21 973 105 1,078 Inhambane 1,533 770 50 763 515 1,278 Gaza 1,492 468 31 1,024 71 1,095 Maputo 566 136 24 430 72 502 Total 12,490 4,392 35 8,098 2,596 10,694 Source: Finney andKleemeier 2003. 90 0 r n v l d - m m 0 ddhldv, z m d m m m l f l ch m m hl o z u 0 d d m d vl 30 d 3 l- Appendix A. Chapter Tables CHAPTER5 TableA5.1. HouseholdConstraints to Access to Justice (percent) Not Important Not Very Somewhat Constraint at All Important Important Important Very Important costs 24.1 16.6 18.8 18.0 22.5 Bribes 26.6 16.3 27.6 13.3 16.2 Corruption 19.1 17.6 23.7 18.1 21.4 Incompetence 23.0 17.4 25.4 15.8 18.4 Waiting time/delays 20.2 17.1 22.9 20.1 19.6 Complexity 20.9 17.8 26.2 19.0 16.1 Execution 17.9 16.6 26.3 19.1 20.2 Distance 25.1 15.3 17.1 13.8 28.6 Source: Austral 2005, table 18.3. TableA5.2. Assessment ofthe Justice Systemby Household (percent) Disagree Disagree D o not Agree Agree Agree Assessment Completely Partially or Disagree Partially Completely Thejustice system does not deserve any trust whatsoever 19.0 17.7 24.2 19.6 19.5 The courts are entirely dependent on the government 8.8 14.5 30.0 19.6 27.1 Only the weak and poorwho are unable to evadethe law 9.5 9.7 20.0 22.2 38.6 Thejustice system is unfair 9.8 12.7 34.4 23.6 19.5 Thejustice system is manipulatedby economic interests 10.9 14.2 31.1 21.7 22.1 Thejustice system is more corrupt than the government 14.9 14.9 36.1 14.4 19.8 Source: Austral 2005, table 18.1. Table A5.3. Resolutionof Problemsby Entity in Urban Areas, by Gender ofHeadand Wealth Tercile, 2006 (percent) Male Head Female Head Item All Poorest Richest All Poorest Richest Family 16.5 19.4 9.6 11.2 16.3 11.8 Traditional authorities 7.6 6.5 4.8 7.2 12.2 0.0 Local authorities 57.2 58.1 60.2 65.6 51.0 70.6 Community police 4.7 3.2 3.6 4.0 10.2 0.0 State police 12.3 11.3 19.3 11.2 8.2 17.6 court 0.8 0.0 2.4 0.0 0.0 0.0 Church 0.4 0.o 0.0 0.8 2.0 0.0 Do not seek help 0.4 1.6 0.0 0.0 0.0 0.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 Source: PVS data for 2006. Note: Samplenot representative. 92 Amendix A. ChaDter Tables Table A5.4. ResolutionofProblemsby Entityin RuralAreas, by Gender ofHeadand Wealth Tercile, 2006 (percent) Male Head Female Head Item All Poorest Richest All Poorest Richest Family 16.6 18.8 14.3 9.1 11.6 15.4 Traditional authorities 32.2 29.2 33.8 33.8 53.5 7.7 Local authorities 44.2 47.9 41.6 54.5 32.6 76.9 Community police 1.5 0.0 3.9 2.6 2.3 0.0 State police 4.0 4.2 5.2 0.0 0.0 0.0 court 1.5 0.o 1.3 0.0 0.0 0.0 Church 0.0 0.0 0.0 0.o 0.0 0.0 Did not seek help 0.0 0.0 0.0 0.0 0.0 0.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 Source: PVS data for 2006. Note: Sample not representative. Table A5.5. UrbanPerceptionsof Change in Power or Rights of Householdsover Last Five Years, by Gender of HeadandWealth Tercile, 2006 (percent) Male Head Female Head Status All Poorest Richest All Poorest Richest Improved 42.8 25.8 53.0 39.2 32.7 52.9 Worsened 10.2 11.3 8.4 12.8 14.3 14.7 Not changed 47.0 62.9 38.6 48.0 53.1 32.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 Source: PVS data for 2006. Note: Sample not representative. Table A5.6. RuralPerceptionsof Change inPower or Rights ofHouseholdsover Last Five Years, by Gender of Head andWealth Tercile, 2006 (percent) Male Head Female Head Status All Poorest Richest All Poorest Richest Improved 43.7 35.4 45.5 33.8 41.9 30.8 Worsened 6.0 4.2 9.1 10.4 7.0 0.0 Not changed 50.3 60.4 45.5 55.8 51.2 69.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 Source: PVS data for 2006. Note: Sample not representative. 93 AppendixA. Chaoter Tables Table A5.7. Awareness of How to Obtain Land Title, by Area, Gender of Household Head, and Tercile, 2006 (percent) Urban Rural Head of household All Terciles Poorest Richest All Poorest Richest All 15.2 0.0 30.0 10.5 10.4 11.5 Male heads of household 18.2 0.0 32.5 11.9 10.8 12.1 Female headsof household 8.8 0.0 20.0 6.7 10.0 8.3 Source: PVS data for 2006. Note: Sample not representative. TableA5.8. Reasonsfor Lack of Title, by Area and Gender of HouseholdHead, 2006 (percent) Urban Rural Male Female Male Female Reason All Head Head All Head Head Lack of interest 22.5 26.4 14.0 27.9 32.7 15.0 It is complicated 6.2 5.O 8.8 5.0 6.3 1.7 Lack o f knowledge 57.9 52.9 68.4 62.1 55.3 80.0 Lack o f money 3.9 4.1 3.5 4.6 5.0 3.3 Land is borrowed 9.0 10.7 5.3 0.5 0.6 0.0 Other 0.6 0.8 0.0 0.0 0.0 0.0 Source; PVS data for 2006. Note: Sample not representative. Table A5.9. Allocationof Public Sector Resourcesto Community LandDelimitation through PAAO SPGC Budgets:2001-03 Resourcesfor Community Land Resourcesfor Community consultations Province Registration (1000 Mts) (I000 Mts) 2001 2002 2003 2001 2002 2003 Niassa 142,520 28,080 116,400 0 88,000 0 Cab0 Delgado 67,920 0 23,500 34,060 14,000 0 Nampula 301,040 57,600 0 71,832 41,800 42,600 Zambezia 335,080 73,800 83,260 62,000 130,500 42,720 Tete 36,432 90,000 37,260 0 25,380 0 Manica 27,504 22,680 83,425 79,200 37,900 8 1,700 Sofala 147,488 0 0 26,720 0 0 Inhambane 0 47,520 20,184 0 176,400 0 Gaza 80,000 11,520 5,800 0 0 0 Maputo 10,836 118,700 42,840 7,224 0 0 Total (1000 Mts) 1,148,820 449,900 412,669 281,036 513,980 167,020 Source: CTC Consulting2003, p. 44, using data from the sector program PROAGRI, cited in Tanner 2005, p. 8. 94 AppendixA. Chapter Tables Table A5.10. Delimitationof CommunityLand, by Province,2003 (percent) Province Land Delimited Issued Certificates Issued Land Titles Niassa 5 3 ' 0 Cab0 Delgado 11 0 0 Nampula 56 19 24 ZambCzia 48 39 0 Tete 3 0 0 Manica 18 5 0 Sofala 17 5 0 Inhambane 5 0 0 Gaza 13 10 0 Maputo 9 7 0 Total 185 88 24 Source: Chilundo and others 2005, updating data from CTC Consulting 2003. Cited in Norfolk and Tanner 2006, p.12, table 1. TableA5.11. Householdswith Title to Land, by Area, 2006 (percent) Area Urban Rural Yes 9.6 1.4 No 90.4 98.6 Source: PVS data for 2006. Note; Samplenot representative. 95 Amendix A. ChaPter Tables Table A5.12. Household Land Purchasesand Land Title Holding in RuralAreas, by Region, 1996,2002 and 2005 (percent) UnweightedResults Weighted Results Households that Report Households that Report Purchasing Land Purchasing Land Survey With Without Households With Without Households Region Year Title Title All with Title Title Title All with Title 1996 0.7 4.6 5.3 - 0.8 4.8 5.7 - 2002 0.4 6.4 6.7 1.4 0.3 6.6 6.7 0.8 South 2005 1.2 13.1 14.0 1.2 1.1 14.1 14.8 0.9 1996 0.5 2.3 2.8 - 0.4 2.3 2.7 - 2002 0.1 5.0 5.1 1.1 0.2 5.1 5.3 0.9 Central 2005 1.1 6.7 7.5 2.2 1.2 8.7 9.5 2.7 1996 0.7 2.5 3.2 - 0.8 3.2 4.0 - 2002 0.5 5.2 5.7 5.1 0.7 7.4 8.1 2.8 North 2005 2.4 7.5 9.7 7.6 2.6 11.0 13.2 6.O 1996 0.6 3.1 3.7 - 0.6 3.4 4.1 - All rural 2002 0.3 5.4 5.7 2.3 0.3 6.1 6.4 1.2 households 2o05 1.5 8.7 10.0 3.6 1.4 11.2 12.2 2.6 Source: TIA data for 1996,2002, and 2005. -is not available 96 Appendix A. Chapter Tables Table A5.13. Household Land Purchasesand Land Title Holding Status, by Income Quintile, 1996,2002 and 2005 hercent) Quintile of UnweightedResults WeightedResults net Households that household Households that Report Report Purchasing incomeper Purchasing Land Land adult Survey With Without Households With Without Households equivalent Year Title Title All with Title Title Title All with Title 1996 0.5 1.6 2.1 - 0.6 1.8 2.3 - 2002 0.2 3.9 4.1 1.6 0.3 4.6 4.9 1.2 Lowest 2005 1.2 7.5 8.5 3.1 1.4 10.6 11.8 3.O 1996 0.6 3.3 3.9 - 0.6 4.1 4.7 - 2002 0.1 3.9 4.0 1.3 0.2 4.2 4.3 1.o 2nd 2005 0.9 7.1 7.8 2.5 1.o 9.1 9.9 2.2 1996 1.3 2.9 4.3 - 1.4 3.1 4.4 - 2002 0.5 4.8 5.2 2.1 0.3 5.2 5.2 1.1 3rd 2005 1.o 7.1 7.8 3.1 1.o 9.0 9.5 2.6 1996 0.6 4.7 5.3 - 0.7 5.1 5.8 - 2002 0.3 6.2 6.5 1.7 0.5 7.3 7.7 0.9 4th 2005 1.4 8.6 9.8 3.2 1.2 11.8 12.8 1.9 1996 0.o 3.2 3.2 - 0.0 3.3 3.3 - 2002 0.5 8.5 9.0 4.6 0.5 10.3 10.8 1.9 Highest 2005 3.3 13.3 16.0 6.1 2.8 17.2 19.3 3.3 1996 0.6 3.1 3.7 - 0.6 3.4 4.1 - All rural 2002 0.3 5.4 5.7 2.3 0.3 6.1 6.4 1.2 households 2005 1.5 8.7 10.0 3.6 1.4 11.2 12.2 2.6 Source: TIA data for 1996,2002, and 2005. -is not available. 97 Appendix A. Chapter Tables Table A5.14. DecisionmakingResponsibilityon Key HouseholdExpenditures,Head's Response,2006 (percent) Urban Rural Male Female Male Female Item Head Spouse Both Others Head Spouse Both Others Education 88.5 2.6 9.0 0.0 100.0 0.0 0.0 0.o Health 78.2 10.3 11.5 0.0 96.2 0.0 3.8 0.0 Food 65.4 19.2 15.4 0.0 64.2 20.8 15.1 0.0 Source: PVS data for 2006. Note: Sample not representative. Table A5.15. DecisionmakingResponsibilityon Key Urban HouseholdExpenditures, by Wealth Tercile, 2006 (percent) Lower Tercile Upper Tercile Male Female Male Female Item Head Spouse Both Others Head Spouse Both Others Education 96.9 0.0 3.1 0.0 80.8 3.8 15.4 0.0 Health 90.6 0.0 9.4 0.0 65.4 15.4 19.2 0.0 Food 71.9 18.8 9.4 0.0 46.2 26.9 26.9 0.0 Source: PVS data for 2006. Note:Sample not representative.Responsescome from heads of household inurbanareas. Table A5.16. DecisionmakingResponsibility on Key Rural HouseholdExpenditures, by Wealth Tercile, 2006 (percent) Lower Tercile Upper Tercile Male Female Male Female Item Head Spouse Both Others Head Spouse Both Others Education 100.0 0.0 0.o 0.0 100.0 0.0 0.0 0.0 Health 100.0 0.0 0.0 0.0 100.0 0.0 0.0 0.0 Food 55.0 25.0 20.0 0.0 64.3 21.4 14.3 0.0 Source: PVS data for 2006. Note: Sample not representative.Responsescome from heads of householdinrural areas. Table A5.17. DecisionmakingResponsibilityon Key Urban HouseholdExpenditures, by Religion(Muslimhon-Muslim), 2006 (percent) Non-Muslim Muslim Male Female Male Female Item Head Spouse Both Others Head Spouse Both Others Education 76.0 5.5 18.5 0.0 92.2 1.1 4.4 2.2 Health 71.9 8.9 19.2 0.0 90.0 3.3 5.6 1.1 Food 50.7 30.1 19.2 0.0 62.2 18.9 18.9 0.0 Source: PVS data for 2006. Note: Sample not representative.Responsescome from heads of household inurbanareas. 98 AppendixA. Chapter Tables Table A5.18. DecisionmakingResponsibilityon Key RuralHouseholdExpenditures, by Religion(Muslimhon-Muslim), 2006 (percent) Non-Muslim Muslim Male Female Male Female Item Head Spouse Both Others Head Spouse Both Others Education 91.8 2.0 6.1 0.0 96.7 0.0 2.7 0.7 Health 83.7 2.0 12.2 2.0 96.0 0.0 4.0 0.0 Food 65.3 18.4 14.3 2.0 68.0 16.0 16.0 0.0 Source: PVS data for 2006. Note: Samplenot representative.Responsescome from heads ofhousehold inrural areas. Table A5.19. DecisionmakingResponsibilityon Key HouseholdExpenditures,2006 (percent) Urban Rural Item Head Spouse Both Others Head Spouse Both Others Education 81.0 6.1 11.3 1.6 97.8 0.3 1.5 0.3 Health 75.9 6.7 15.8 1.6 92.5 0.8 6.7 0.0 Food 48.6 28.5 22.9 0.0 59.5 21.3 19.2 0.0 Source: PVS data for 2006. Note: Sample not representative.Responsescome from the spouse o fthe headof household. 99 Appendix A. Chapter Tables CHAPTER6 Table A6.1. Awareness ofHIV/AIDS and PreventionMethods,2003 Knows Using Condoms and Limiting Sex to One Has Discussed Has Heard of Uninfected Partner HIV/AIDS Prevention Characteristic HIV/AIDS Reduces Risk with Partner Area Rural 93.7 38.0 45.1 Urban 99.1 57.6 60.3 Education No education 91.7 31.1 39.3 Primary 98.2 51.4 56.8 Secondary 100.0 78.5 82.1 Wealthquintile Lowest 90.5 29.5 38.5 2nd 93.7 34.3 41.9 3rd 95.9 43.1 50.6 4th 98.7 51.4 53.5 Highest 99.7 65.8 69.2 Total 95.7 45.2 49.5 Source: DHS datafor 2003. Table A6.2. Ratio of Current SchoolAttendanceof Orphansversus Nonorphans,by Type of Orphan, 2003 (percent) Type of orphan 2003 Maternal 0.81 Paternal 0.97 Both parentsdied 0.80 Source: GoM 2006, basedon DHS data 100 AppendixA. Chapter Tables Table A6.3. Difference-in-DifferencesAnalysis of RuralHouseholdComposition by Gender of DeceasedPrime-ageAdults in Mozambique,2002-05 (percent) Households with Male Households with Households without Prime-age Death, 2002- Female Prime-age Prime-age Death, Difference-in- 05 Death, 2002-05 2002-05 Differences Male Female Prime-age Prime-age Death Death x2002 x.005 A X x.002 x2005 Af x.002 x2005 Ax0 AX- AX0 AY- AX0 Household composition Household size 6.48 5.24 -1.23 5.69 5.52 -0.17 4.91 5.29 0.37 -1.61 -0.54 Male adults 1.89 1.12 -0.78 1.32 1.54 0.22 1.23 1.31 0.09 -0.86 0.13 Female adults 1.90 1.77 -0.13 1.93 1.57 -0.36 1.38 1.47 0.09 -0.21 -0.45 BOYS 5-14 0.93 0.83 -0.10 0.85 0.77 -0.08 0.76 0.87 0.11 -0.21 -0.19 Girls 5-14 0.80 0.81 0.01 0.85 0.82 -0.03 0.71 0.83 0.12 -0.11 -0.15 Young children 0 4 0.96 0.68 -0.28 0.74 0.83 0.09 0.83 0.80 -0.03 -0.25 0.12 Household size (adult equivalent) 5.04 4.01 -1.02 4.40 4.23 -0.17 3.68 3.95 0.28 -1.30 -0.44 Prime-age adults 3.52 2.59 -0.93 2.93 2.77 -0.16 2.38 2.51 0.14 -1.07 -0.30 Elderly adults 0.27 0.29 0.03 0.32 0.33 0.01 0.23 0.27 0.04 -0.01 -0.02 Dependency ratioa 0.90 1.25 0.35 1.10 1.11 0.01 1.19 1.29 0.09 0.26 -0.08 caies 115 115 121 121 3,806 3,806 Source: TIA 2002-05 Paneldata. Note: Households with more than one prime-agedeath are excluded(N=23). a. Dependency ratio is effective dependency ratio: (children+ adults over 60 + prime-age adults with chronic illness)/ prime-ageadults without chronic illness. 101 Auuendix A. ChaDter Tables Table A6.4. PercentageReceivingAntiretroviral CombinationTherapy (HAART) in Mozambique, by Gender and by Region, October 2005 Region Male Female Total South 17.9 17.4 17.6 Central 4.6 4.4 4.5 North 1.6 1.3 1.4 Total 7.4 7.4 7.4 Source: GoM 2006, basedon DHSdata. Table A6.5. Number of PeopleReceivingAntiretroviral CombinationTherapy (HAART) in Mozambique,2006 September October November December 2006 2006 2006 2006 Number receiving HAART 34,184 37,133 40,475 44,100 Estimated number in needo f HAART 270,3 17 Percentagereceiving HAART 16 Source: MISAUandGoM 2007. Table A6.6. Antiretroviral Coveragein Mozambiqueand NeighboringCountries, 2005 Reported Number of Sites Estimated Number of Providing ART People, Age &49, ART Coverage, December September to December Country and region NeedingART, 2005 2005 2005 Mozambique 216,000 9 32 Tanzania 315,000 7 96 Malawi 169,000 20 60 Zambia 183,000 27 >110 Zimbabwe 321,000 8 48 South Africa 983,000 21 183 Sub-SaharanAfrica 4,700,000 17 Source: UNAIDSand WHO 2006. 102 APPENDIX B. METHODOLOGY Much o f the analysis presented in this poverty assessment uses data at the household level from sample surveys undertaken inMozambique inthe past 10 years. The aim o f this appendix is twofold. First, it describes the key sources o f household-level data used in the assessment. Second, it defines some key concepts used in the analysis o f those surveys. Third, it explains some technical issues related to the comparability o f the two national expenditure surveys, particularly as it relates to the definition o f rural and urban areas. And finally, it discusses the methodology used in the construction o f poverty lines for poverty analysis in Mozambique for the period 1997-2003 and the rural poverty dynamics in 2002-05. DESCRIPTION OFHOUSEHOLD SOURCES SURVEY In this assessment we use data from various household surveys undertaken in the country over the past decade. They include: the National Household Survey on Living Conditions o f 1997 and 2003; the National AgriculturalRural Income Survey of 1996, 2002, and 2005; and the 2006 Poverty, Social, and Gender Assessment Household Survey commissioned for this assessment (conducted inNiassa, ZambCzia, Nampula, and Gaza).' Each o f these surveys i s described below. National Household Surveys on Living Conditions(LAF) The National Household Survey on Living Conditions in Mozambique, also known as IAF (lnque'rito aos Agregados Familiares), i s the main data source for the official poverty estimates. There have been two such surveys, one in 1997 and another in 2003. Both surveys had nationwide coverage-covering Mozambique's rural and urban areas and the city o f Maputo as a separate stratum. The IAF survey samples are stratified random samples designed to be representative at the national, provincial, and area of residence (urban and rural) levels. The IAF surveys are designed and implemented by Mozambique's National Instituteo f Statistics (NE). The sample for the 1997 survey consisted o f 8,274 households, and the 2003 covered about 8,700 households. The sample frame for the 1997 survey was the 1980 population census with adjustments and other data, such as the 1994 electoral census. For the 2003 survey, the sampling frame was the 1997 population census. The universe from which the sample was selected covers the population o f Mozambique residing in households, excluding those residing in prisons, army camps, hotels, collective housing, the homeless, and so on. ' Anotherimportantsource of informationusedinthis document, but not discussedhere, is the Demographicand HealthSurveysof 1997 and 2003 undertakenby INE in collaborationwith the Ministryof Healthof Mozambique (MISAU). 103 Table B1 shows the distribution o f households by province in each year and the rural and urban distribution according to the definitions used in the 2003 survey (consistent with the population census o f 1997).2 Table B1. IAF Survey Sample by Province,1997 and 2003 1997Survey 2003 Survey Province Urban Rural Total Urban Rural Total Niassa 225 432 657 456 360 816 Cab0 Delgado 152 594 746 144 594 738 Nampula 417 539 956 216 540 756 Zambezia 348 540 888 132 601 733 Tete 159 453 612 216 540 756 Manica 204 458 662 456 360 816 Sofala 468 297 765 372 423 795 Inhambane 216 513 729 214 539 753 Gaza 180 459 639 336 450 786 Maputo province 423 297 720 540 288 828 Maputo city 900 0 900 923 - 0 ___.___I-_ 923 -I___ Mozambique 3,692 4,582 8,274 4,005 4,695 8,700 Source IAF data for 1997 and2003. The surveys included information about consumption patterns, income, health, nutrition, education, agriculture, and numerous other aspects o f Mozambicans' living conditions. Each participating household was visited three times within a seven-day period. At the household level, there were three instruments used for interviews: a principal survey questionnaire, a daily household expenditure questionnaire, and a daily personal expenditure questionnaire administered to all income-earning members within the household. Inaddition to data collected at individual and household levels, there were two instruments administered once during the survey period at higher levels of aggregation. First, within each village (aldeia), a community-level survey o f available infrastructure, access to services, and general community characteristics was collected. These data were not collected in any urban areas. Second, detailed market-price information was collected in the major market for each sampled bairro (urban areas) and localidade (rural areas). National AgriculturallRural Income Surveys (TU) The National AgriculturalRural Income Survey, also known as Trabalho de Inque`rito Agrz'cola (TIA), is a household-level survey implemented nationally by the Ministry o f Agriculture o f Mozambique employing standards from the INE.The first such survey was implemented in 1992/93, and since then it has been systematically * Theoriginal definition of urban areas used inthe 1997 survey included only capital cities. Inthe next sectiono f this appendix, we discuss the issue of rural and urban definitions and the course o f action followed to undertakeconsistent comparisonsby area o fresidence over the period. 104 implemented, in 1996, 2002, and 2005. Inthis assessment we make use o f the consistent data from these last three surveys. All TIA survey samples are exclusively rural and selected using stratified, clustered sample design methods. The samples are representative at the provincial, regional, and national levels. The 1996 TIA collected data from 3,889 households in 66 districts, while the 2002 TIA collected data from 4,908 households in 80 districts, and the 2005 TIA covered 6,149 households in 96 districts. While the 2006 TIA was drawn from the updated sampling frame from the 1980 census and electoral census of 1994, the 2002 TIA and 2005 TIA samples were drawn from the sampling frame prepared for the 2000 agricultural census that covered over 22,000 households. The 2005 survey includes the households from the 80 districts covered in 2002 that could be reinterviewed (4,104 households), thus constituting a panel dataset. Attrition between these two surveys was about 16 percent. Replacement households were included in the 2005 sample, and it also added households in another 16 districts, extending the number to 96. The panel dataset i s used in chapter 4 for the analysis o f rural household poverty dynamics. Table B 2 summarizes the distribution o f households across provinces for three years, includingthe panel households from 2002-05. Table B2. TIA Survey Sample by Province, 1996,2002,2005, and 2002-05 Panel Number of SampledHouseholds by Survey Year 2002-05 Province 1996 2002 2005 Panel Niassa 256 277 337 222 Cab0 Delgado 320 500 591 406 Nampula 702 604 785 513 Zambezia 830 724 781 620 Tete 320 587 721 486 Manica 253 478 505 395 Sofala 319 416 531 308 Inhambane 378 426 586 377 Gaza 319 552 865 476 Maputo province 192 344 447 301 Mozambique 3,889 4,908 6,149 4,104 Source: TIA data for 1996,2002, and2005. The rural survey includes instruments both at the household and the village level. Multilevel survey questionnaire design techniques are used for appropriate treatment o f the data collected in the various parts o f the surveys at different levels (household, field, crop, activity, and so on). At the household level it includes information on smallholder household demographics, land use and cropping patterns, use and sources o f farm nonlabor inputs, labor allocation on farm and nonfarm activities, production and marketing o f crops, ownership o f production and marketing assets, ownership and marketing o f livestock, income diversification into micro and small enterprises and wage labor, remittances from (and to) rural smallholder households, and pensions and other 105 transfers. The village level questionnaire collects data on village infrastructure, including roads (distance to main and secondary roads), water sources, electricity, economic activities, history o f the village, and other aspects relevant to understanding the context in which the households live. Poverty and VulnerabilitySurvey (PVS)-Qualitative/Quantitative (Q2) Assessment To ensure that the assessment was informed by poor people's own perceptions, a survey was fielded to supplement existingsources o f primary and secondary information. It employed participatory and qualitative research methods and quantitative data collection and analysis. The ultimate aim was to explore: The principal livelihood strategies o f the poor-women and men's access to, and perceptions of, key rights, resources, and services. Sex-disaggregated consequences o f public action and policy, with a particular focus on anticipated major reforms and investments, including in the areas o f infrastructure, service delivery, and land and family reform. Issues and mechanisms for participation, representation, influence, and accountability in policy making and local governance, with particular reference to processes o f decentralization reform. Social exclusion, vulnerability to shocks, and seasonality o f risks as faced by different social groups. The impact of economic growth on local institutions and social relations. The survey covered the rural and urban areas in four provinces o f the country, namely Niassa, ZambCzia, Nampula, and Gaza. Sixteen research sites were selected-four per province-based on a purposive clustering sample methodology drawing on a mix o f preidentified criteria, including: Rural-urban characteristics. Social diversity and ethnic group. Predominant livelihoods and agroecological zones. Levels o f access to infrastructure and services. Relative decentralization impact. The participatory/qualitative survey data collection was done in rural and urban areas usingthe following tools: Mapping (resource, asset mapping, wealth ranking, and institutional diagrams). 106 Focus groups, PRA (participatory Rural Appraisal), and PUA (Participatory Urban Appraisal)-in mixed groups (women and men), women and men separately, and youth (mixed). Key informant interviews (conversational and semistructured) for more in- depth discussion o f key topics. These included: leaders and nonleaders, women and men, and youth and older community members. Overall, the qualitative survey included 16 mapping exercises (in each o f the four research sites, in each o f the four provinces), 128 semistructured household interviews, 90 with key informants, and 36 focus group interviews. Intotal, 648 people (of which 43.7 percent were women) were interviewed inthe four provinces. The household level/quantitative survey also covered the 16 rural and urban areas selected in the four provinces. Within each o f these four research sites, approximately 40 households were randomly selected to be interviewed (amounting to about 160 per province). The provincial sample was not designed to be statistically representative but to provide indicative results and support the qualitative assessment undertaken in those areas. Table B3 summarizes the distribution o f households by area o f residence in province. Table B3. Sample for Poverty andVulnerabilityAssessment, 2006 Area of Residence Province Urban Rural Total Niassa 40 120 160 Nampula 80 80 160 Zambkzia 118 39 157 Gaza 123 37 160 Mozambique 361 276 637 Source: PVS data for 2006. The interviews took place preferably with the household head, but any other adult member present could act as the main respondent and attend the interview. As a gender study, where there was a male head of household, there were specific sections designed to be answered by female spouses in order to assess their perceptions and perspectives as compared with those o f male respondents. The survey instrument included the following main sections: Household demographics, health, education, and employment. Housing characteristics and conditions. Poverty and vulnerability profile. Access to services. Decisionmaking inthe household. Land access, ownership, and use. Ownership o f household and productive assets. While the PVS as a whole has been used to provide an indication o f trends since the nationally representative data from 1997 and 2003, the main focus o f the 107 quantitative/qualitative survey has been on documenting people's perceptions o f poverty, the livelihoods of the poor, shocks, and vulnerability and on people's sense of empowerment regarding their rights and responsibilities as well as their interactions with the state and public institutions. For the analysis o f the quantitative survey data, in addition to the rural-urban breakdown, a simple Household Asset Ownership Index was created to rank households in each of those areas. The asset index was created as a simple (unweighted) count of individual asset types owned by households, in such a way that households with more diversified assets were considered asset rich. In each area households were then divided into asset-ownership tercile categories, each composed o f one-third o f the households, with the bottom group composed by the one-third that had less diversification o f assets and the top group composed by one-third o f the asset-rich households. HOUSEHOLD EQUIVALENTS ANDCONSUMPTIONANDINCOMERANKINGS ADULT (QUINTILES) In most of the analysis that uses household consumption expenditure and household income data, we use the concept o f household consumption (and income) per adult equivalent and break the households into quintiles o f those variables to compare group variables. The concept o f adult equivalent (AE) is widely used in the socioeconomic literature and is similar to the concept o fper capita but i s based on the observation that not all members o f a household need the same number o f calories to remain healthy. For example, an adult woman or child does not need to consume as much as an adult male. Thus they are not counted as heavily as an adult male. This consumption adult equivalent i s based on calorie requirements for "normal" activity levels. Adult equivalents are: males aged 10 or older = 1; females aged 20 or older = 0.84; females aged 10-19 = 0.72; and children under age 10 = 0.60. Thus, for the average household, consumption (or income) per adult equivalent is higher than consumption (or income) per capita. Household quintile groups are created from the ranking o f all households based on the level of the variable of interest, in this case household consumption or income per adult equivalent. In the case o f quintiles, we create five groups o f equal size, each comprising 20 percent o f the total number o f sampled households. The first 20 percent o f household in the ranking (those with the lowest level of consumption or income or adult equivalent) are in quintile 1, the second 20 percent in quintile 2, and so on, with the top quintile includingthe richest 20 percent o f households. 108 RURAL AND URBANDEFINITIONS AND POVERTY LINES FOR IAF 1997AND 2003 COMPARISONS A great deal o f the analysis in this report uses data from the two national expenditure surveys (IAF) implemented in 1997 and 2003 and described above. In this report we often analyze differences across the two survey years for a number o f indicators, across space (provinces, regions, or rural and urban areas) and over time. In this section we cover two issues that are important for the comparability of results: consistency o f the definitions o f urban and rural areas over the period and methodology for the construction o f poverty lines for the poverty analysis. Consistent Urban andRural Definitions for 1997and 2003 This issue is of importance both for the poverty analysis and the more general statistical analysis that compares urban and rural areas over the sample period. The fundamental point here is that the two IAF surveys used a different definition o f area o f residence (rural and urban). While the 1997 survey considered only the provincial capital cities (including Maputo city) urban, the 2003 survey used the new definition based on the 1997 census and the New Administrative Division (Nova DivisLio Administrativa) that included another 23 cities and 68 small towns. Previous comparative analyses that use these two datasets for comparative though recognizing that these differences in definitions can potentially affect the comparability o f the results, do not attempt to correct it. The definitional disparity does not affect the provincial and national estimates. But the aggregate rural-urban comparisons are affected. Using inconsistent definitions biases the results, as the urban subset is much bigger in2002. Thus the results give a false sense o f rapid urbanization. To correct for this problem and get genuinely comparable sets, we follow a three step process. First, we recode the sites consistently across the two surveys by identifying in the 1997 dataset the sites (cities and towns) that were selected in the 1997 IAF and coded as urban according to the new definition. We recode them consistently with the 1997 census and 2003 IAF. This way, the two datasets have the same sets o f rural and urban populations. Second, we regenerate the populations and test the weights for 1996.Then we generate the population with the new consistent urban and rural definitions applied to the 1997 IAF dataset using the original weights (based on the original sample design and definitions) and the household sizes recorded in the database. The results are then assessed interms of: replication o f total population, provincial totals, and shares o f rural and urban population. Then they are compared against the original (based on the old definition) and the census numbers (based on the new definition). See table B4 for an illustration. 'INE2004; MPF, IFPRI, and the Purdue University 2004. 109 Table B4. PopulationDistributionunderAlternativeRural and UrbanDefinitions Distribution of Population Generatedby Weight Factor by Area of Residence (percent) Surveysand census Survey Weights Urban Rural 1997IAF Urban= 11provincial capitals Original 1996 20 80 Urban=23 cities + 68 towns Original 1996 38 62 Urban=23 cities +68 towns Adjusteda 29 71 Populationcensus 1997 Definition consistentwith 2002 29 71 2003 IAF Rural-urbanand weights of 2002 Original 2002 32 68 Source: IAF data for 1997 and2003 and INEpopulationcensus data a. The adjustment consisted ingeneratingaunique set of weights that replicatedthe nationalandprovincialpopulation sizes with an urban-ruralstructure (percent) similar to the one inthe 1997 census. The results found suggested that usingthe original weights tends to overstate the urban population-the resulting urban population is about 38 percent o f the total population, a figure well above the estimated 29 percent in the 1997 census that uses the same definiti~n.~ The reason for that is that, given the sample design,the rural weights are typically higher than the urban ones, and all the newly coded urban (previously rural) households carry those weights in the calculation while they are in fact representing a much smaller universe. For this reason, in the final, third step we adjusted the 1996 weights to reflect the new consistent definition. It is clear that along with the alignment of location codes we needed an adjustment in the weighting factors to reflect the new definition. The new set o f weights should pass the assessment criteria above-replicating the national and provincial populations estimated for 1996 and reflecting an urban-rural composition that i s consistent with the 1997 census that uses a definition consistent with the 2003 IAF.Table B4 summarizes these results. Thus for consistency we use the original set of weights inthe 2003 dataset. For the 1997 dataset, we use the adjusted set o f weights that corresponds to the consistent 2003 rural and urban definitions based on the 1997 census and replicate the population structure inthat year usingthe 1997 IAF dataset. CONSTRUCTINGPOVERTYLINES FORPOVERTY ANALYSIS Our poverty lines were developed by the Government o f Mozambique. Detailed explanations o f the methodology for consistently constructing the poverty lines are available in MPF and UEM (1998) and MPF, IFPRI, and Purdue University (2004). In this section, we briefly explain the methodology. We first explain the issues in creating ~~~~ As expected, this figure is higher thanthe 20 percentobserved with the original urbandefinition. It is evenhigher than the 32 percent found inthe 2003 IAF, which obviates the needfor correction. 110 consistent poverty lines over time and the method adopted to solve this problem. Then we provide details on the construction o f boththe food poverty line and the total poverty line. Mozambique's first and second national poverty assessments use the cost o f basic needs (CBN)' methodology to construct region-specific poverty lines (Ravallion 1994, 1998).6 In the C B N approach, the total poverty line i s constructed as the sum o f a food and a nonfood poverty line (see sections below for explanation on the construction o f these poverty lines). The poverty lines are set in terms o f a level o f per capita consumption expenditure that i s deemed consistent with meeting these basic needs. Spatial differences need to be taken into account because in Mozambique, where markets are not always well integrated and transaction costs are high, prices vary across regions. Thus, one single poverty line for the whole country would not be appropriate, as it would generate inconsistent poverty comparisons. Spatial differences were accommodated by (a) defining 13 region-specific consumption bundles (see table B5 for a list o f regions) by the consumption bundle in each region, reflecting consumption patterns o f the poor in that region and the cost o f the bundle calculated using the prices prevailing inthat region; and then by (b) estimating a total poverty line, includingnonfood costs, once the poverty line has been constructed. Households that spend less on a per capita basis than the poverty line are deemed poor.7 The Ravallion methodology uses this same basic needs consumption bundle (with adjustments for changes inprices) for analysis overtime, as this provides a fixed standard to measure changes in welfare. But if the relative prices o f items in the basic needs consumption bundle change over time, consumers will substitute these items for less expensive ones, thus changing the composition o f the relevant basic needs consumption bundle. As reported in MPF, IFPRI, and Purdue University (2004) over the period 1997 and 2003, significant changes in relative prices o f basic food commodities occurred, and the thus expected substitution inconsumption took place. For example, the depreciation of the exchange rate raised the price of imported food (and domestically produced import substitutes). Analysis shows that substitution in consumption did occur in response to these changes in relative prices resulting in changes in the basic needs consumption bundle. It was decided, therefore, that for the poverty lines for the 2003 data, the food consumption bundle for each region would be changed to reflect the consumption patterns o f the poor in 2003.8 Thus, different bundles than those used in 1997 analysis were The CBN approachshouldnot be confused with asimilarly namedapproach, NecessidadesBdsicas Insatisfeitas, which hasbeenusedat times inLatin America. Ravallion(1994, 1998) and Ravallion andBidani(1994), among others, have shownthat the CBN approachdoes not suffer from the problem of inconsistent poverty comparisons that often arise when the food energy intake methodis usedto set poverty lines. UsingIAF data for 1997, Tarp andothers (2002) have shownthat the food energy intake approachyields inconsistent poverty lines and estimatesfor Mozambique. 'Complete details of the criteria for defining regions are given inMPF, UEM, andIFPRI (1998) andTarp andothers (2002). For adetailed presentation ofthe fixed and flexible food bundle approaches see MPF, IFPFU, and Purdue University (2004). 111 created for the 2003 poverty lines. To find adjusted bundles that satisfy revealed preferences, an information theoretic approach (minimum cross entropy) is used.' It results in bundles that meet coherency requirements and reflect the actual consumption patterns o f the poor in each region. With this methodology, consistent food poverty lines were found and added to the nonfood poverty lines to generate total poverty lines in each spatial domain for our analysis. Table B5. FoodPovertyLines Using Basic Needs Food Bundlesfor 1997 and 2003 2003 Fixed Bundle 2003 Unadjusted 1997Food Poverty Poverty Line (1997 Food Poverty Line Line (1997 bundle at bundle at 2003 (2003 bundle at Spatial domain 1997prices) prices) 2003prices) 1Niassa and Cab0 Delgado (rural) 3,011 6,246 4,756 2 Niassa and Cab0 Delgado (urban) 3,687 7,857 7,717 3 Nampula(rural) 2,742 5,277 2,752 4 Nampula(urban) 3,642 8,275 3,749 5 Sofala and Zambezia (rural) 3,719 5,175 3,548 6 Sofala and Zambezia (urban) 5,370 7,483 5,902 7 Manica and Tete (rural) 3,845 6,838 6,937 8 Manica and Tete (urban) 5,548 11,176 9,656 9 Gazaand Inhambane(rural) 4,971 6,858 5,438 10 Gaza and Inhambane(urban) 5,714 7,461 6,613 11Maputo province (rural) 5,418 11,801 12,584 12 Maputo province (urban) 6,047 11,898 13,741 13 Maputo city 6,192 12,224 13,211 Source:MPF, IFPRI,andPurdueUniversityusingIAFdata for 2003. Note:All figuresinMeticais per personper day. A comparison o f the poverty impact of usingthe fixed versus the flexible bundles i s shown in table B5 and table B6. The new bundles generally resulted in a lower cost o f basic food needs in the rural areas o f Niassa and Cab0 Delgado, Nampula, Sofala and Zambezia, and in the urban areas o f Nampula, Sofala, Zambezia Manica, Tete, and Maputo. This adjustment meant that the national poverty rate in 2003 was 9 percentage points lower under the flexible bundle than the fixed bundle (from 63.2 to 54.1 in 2003, see table B6)." The effect on the poverty rates varied across the regions, reflecting the Mozambique's heterogeneity. In the north and center, poverty rates under the flexible bundle approach decreased by 12 and 13 percentage points, while in the south, where the capital i s located, the poverty rate increased because o f flexible bundles (from 63.6 to 66.5 in 2003). The biggest effect on the poverty rate was in Manica, where the poverty headcount was almost 17 percentage points lower under the flexible than fixed bundle (from 60.2 to 43.6 in2003). See MPF, IFPRI, andPurdueUniversity(2004) for more detail. lo Ibid. 112 Table B6. Poverty HeadcountUsingFixed and FlexibleBundleApproaches Difference in Poverty Poverty Headcount Using Headcount Poverty Headcount Using the the Flexible Bundle between Flexible Fixed Bundle Approach Approach and Fixed Bundle Region 1997 2003 1997 2003 2003 National 69.4 63.2 69.4 54.1 -9.1 Urban 62.0 61.3 62.0 51.5 -9.8 Rural 71.3 64.1 71.3 55.3 -8.8 North 66.3 68.1 66.3 55.3 -12.8 Center 73.8 59.2 73.8 45.5 -1 3.7 South 65.8 63.6 65.8 66.5 2.9 Niassa 70.6 61.2 70.6 52.1 -9.1 Cab0 Delgado 57.4 72.3 57.4 63.2 -9.1 Nampula 68.9 68.1 68.9 52.6 -15.5 Zambezia 68.1 58.6 68.1 44.6 -14 Tete 82.3 71.6 82.3 59.8 -11.8 Manica 62.6 60.2 62.6 43.6 -16.6 Sofala 87.9 48.4 87.9 36.1 -12.3 Inhambane 82.6 80.1 82.6 80.7 0.6 Gaza 64.6 58.6 64.6 60.1 1.5 Maputo province 65.6 66.9 65.6 69.3 2.4 Maputo city 47.8 45.5 47.8 53.6 8.1 Source: MPF, IFPRI, and Purdue University 2004. The flexible bundles approach has obviously affected the overall analysis of poverty in this report in areas where a major adjustment was made. However, given the extensive research underlying the choice o f poverty lines for 2003 and that this methodology has been adopted by the Government o f Mozambique, we did not pursue the question o f how our analysis might have changed had we used the more traditional fixed bundlepoverty line methodology. Food Poverty Lines For each poverty line region, the food poverty line is constructed by determining the food energy (caloric) intake requirements for the reference population (the poor), the caloric content o f the typical diet o f the poor in that region, and the average cost (at local prices) o f a calorie when consuming that diet. The food poverty line-expressed in monetary cost per person per day-is the region-specific cost o f meeting the minimum caloric requirements when consuming a food bundle comprised o f goods that the poor in the regionactually consume.'' "Thetypical foodbundleofthepoorcould,ofcourse, containmoreorlesscaloriesthantherequirementforthat region. This bundle is then proportionally scaled up or down until it yields exactly the preestablishedcaloric requirement, andthe cost ofthis rescaledbundle at region-specificprices determinesthe food poverty line for that region. 113 Food poverty lines are tied to the notion o f basic food needs, which in turn are typically anchored to minimum energy requirements.12 In the Mozambique poverty analysis, in the absence o f adequate data on physical activity levels or body weight, we estimate caloric requirements using age and gender.13 Thus, average per capita requirements in a given region will vary with the average household composition in that region. In both the 1997 IAF and the 2003 IAF the average daily caloric requirementper person per day was approximately 2,150 kilocalories in each o f the 13 poverty line regions. Nonfood Poverty Lines and TotalPoverty Lines Whereas physiological needs provide the conceptual underpinning o f the food poverty lines, no similar basis i s readily available for defining nonfood needs. A plausible way o f assessing basic nonfood needs i s to look at how much households who are barely in a position to meet their food needs spend on nonfood items.14This approach was used inthe 1997 study and for the development ofthe flexible bundlepoverty line for 2003. We examine households whose per capita total consumption is inthe neighborhood poverty line. Usingthese households, the cost o f the minimumnonfood bundle, 3,i s then o f the food poverty line-with the neighborhood defined as 80 to 120 percent o f the food estimated as the wei hted average nonfood expenditure where observations closer to the food poverty line, 1,aregiven a higher weight." We calculate the weighted average nonfood consumption per capita in each o f the 13 poverty line regions, weighting household-level observations by the product o f these triangular weights, the household expansion factor, and household size. Table B 7 presents the nonfood and food poverty lines, as well as the total poverty line, which is obtained as their sum. Poverty Linesfor the Rural Poverty Dynamics To undertake the poverty dynamics analysis in chapter 5, especially the derivation o f poverty status each year and transition groups over time, poverty lines had to be calculated. For 2002 we used the 2003 IAF food poverty lines, derived above for rural sites in the various provinces o f the country. Itis well understoodandappreciatedthat foodenergy is only one facet ofhumannutritionandthat adequate consumptionof other nutrients, such as protein, iron, vitamin A, and so forth, is also essential for ahealthy and active life. But like most multipurposehouseholdsurveys, the information on food consumptionin the IAF dataset is not sufficiently detailed to permit estimationof the intake andabsorption of other nutrients.Use of energy requirements alone is also well establishedinthe poverty measurement literature(Greer and Thorbecke 1986; Ravallion 1994, 1998; Deaton 1997). l3For bothyears, caloric requirements for moderatelyactive individuals by demographicandcharacteristicswere obtained from the World Health Organization(WHO 1985). l4 For details of an alternativeapproachthat permits amore generous basic nonfood allowance, see Ravallion (1994) andMPF, UEM, andIFPRI(1998). IsHardle (1990), MPF, UEM, andIFPRI(1998), and Datt, Jolliffe, and Sharma(2001). 114 Table B7. Food andNonfoodPoverty Lines, 2003 Food Total Food Poverty Share Nonfood Poverty Spatial domain Line (percent) Poverty Line Line 1Niassa and Cab0 Delgado (rural) 5,434 77 1,665 7,099 2 Niassa and Cab0 Delgado (urban) 7,540 74 2,690 10,23 1 3 Nampula (rural) 4,471 75 1,501 5,972 4 Nampula (urban) 4,853 73 1,807 6,661 5 Sofala and Zambezia(rural) 4,155 76 1,318 5,473 6 Sofala andZambezia (urban) 6,591 75 2,183 8,775 7 Manicaand Tete (rural) 5,629 81 1,304 6,933 8 Manicaand Tete (urban) 7,145 74 2,545 9,690 9 Gaza and Inhambane(rural) 6,6 14 73 2,394 9,008 10 Gaza and Inhambane (urban) 7,264 68 3,457 10,72 1 11Maputo province (rural) 11,801 70 4,963 16,764 12 Maputo province (urban) 11,898 65 6,398 18,296 13 Maputo city 12,224 63 7,29 1 19,515 Source:MPF, IFPRI,andPurdueUniversityusingIAF data for 2003. Note: Poverty line figures inMeticais per personper day. 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