秘魯2023世行企業(yè)調(diào)查實(shí)施報(bào)告（英文）

1

ThePeru2023WorldBankEnterpriseSurveyImplementationReport

I.Introduction

ThisdocumentprovidesinformationontheWorldBankEnterpriseSurveys(WBES)implementedinPerubetweenAugust2022andAugust2023(baselinedatacollection)andbetweenMayandOctober2023(follow-updatacollection).TheWBEScollectbothobjectivedatabasedonfirms’day-to-dayexperiences,andperceptionsofenterprisesregardingthebusinessenvironmentinwhichtheyoperate.TheWBEScurrentlycoverover200,000firmsin155countrieswithatotalof340surveyssince2006.TheWBESarealsousedtobuildapanelofenterprisedatathatwillmakeitpossibletotrackchangesinthebusinessenvironmentovertime.1

Thisreportdescribesthesamplingdesignofthesurvey,thedatasetstructureaswellasadditionalinformationthatmaybeusefulwhenusingthedata,suchasinformationonsurveynon-responseandtheappropriateuseofthesamplingweights.

II.SamplingStructure

TheWBESusestratifiedrandomsampling,wherethepopulationofestablishmentsisfirstseparatedintonon-overlappinggroups,calledstrata,andthenrespondentsareselectedthroughsimplerandomsamplingfromeachstratum.ThedetailedmethodologyisprovidedintheSamplingNote.2Stratifiedrandomsamplinghasseveraladvantagesoversimplerandomsampling.Inparticular,it:

?producesunbiasedestimatesofthewholepopulationoruniverseofinference,aswellasatthelevelsofstratification

?ensuresrepresentativenessbyincludingobservationsinallofthosecategories

?producesmorepreciseestimatesforagivensamplesizeorbudgetallocation,and

?mayreduceimplementationcostsbysplittingthepopulationintoconvenientsubdivisions.

TheWBEStypicallyusethreelevelsofstratification:industryclassification,establishmentsize,andsubnationalregion(usedincombination).Startingin2022,theWBESbasestheindustryclassificationonISICRev.4(withearliersurveysusingISICRev.3.1).3Forregionalcoveragewithinacountry,theWBEShasnationalcoverage.

1A“panelinterview”referstoaninterviewwithabusinessthatwasalsointerviewedinthepreviousWBES.

2TheSamplingNoteisavailableat:

/content/dam/enterprisesurveys/documents/methodology/Sampling_Note-

Consolidated-2-16-22.pdf.

Forfurthermethodologicalbackgroundsee,RichardL.Scheaffer;Mendenhall,W.;

Lyman,R.,“ElementarySurveySampling”,FifthEdition,1996.

3TheWBESuniverseincludes:allmanufacturing(ISIC4.0codes10-32),services(ISIC4.0codes33,41-43,45-47,49-56,58,61,62,69-75,79,95).DetailsonsectoralcoverageandtheWBESuniverseofinferencecanbefoundintheEnterpriseSurveysManualandGuide(p.4).

2

II.1StratificationCategories

ThePeru2023WBESusesthefollowingstratificationcategories:

?Industry:7categories:

?Withinmanufacturing:Food,Textiles,Garments,Othermanufacturing

?Withinservices:Retail,Hotels,andOtherServices

?Size:3categories:Small(5to19employees),Medium(20to99employees),Large(100ormoreemployees)

?Region:5categories:Lima,Arequipa,Chiclayo,Trujillo,Piura.

Industrystrataforthemanufacturingsectorwereselectedbytheircontributiontoemployment,tototalnumberofestablishments,andtototalsalesvalue,usinginformationfromtheSUNAT(SuperintendenciaNacionaldeAduanasydeAdministraciónTributaria)databaseextractedinMarch2022.Themanufacturingsectorsstratifiedseparatelyrepresent53%oftotalemploymentoftheuniversecoveredbytheES,33%ofthenumberofestablishments,and33%ofsalesvalue,withtherestofsectorsgroupedintoaresidual“OtherManufacturing”stratum.

Thestratafortheservicessectorwereselectedbycontributiontothesameindicators(totalnumberofestablishments,employment,andtotalsalesvalue),alsousingthelistingfromSUNATextractedinMarch2022.Thesectorsstratifiedseparatelyrepresent17%ofthetotalnumberofestablishmentsintheservicessector,22%oftheworkforce,and20%ofthesalesvalue;therestofservicessectorsaregroupedintoaresidual“Otherservices”stratum.

RegionstrataofthePeru2023WBESwereselectedbasedonadministrativedivisions,withtheaimtoachieveminimumrequiredprecisionofestimatesatthelevelofeachstratificationregion.LimacoverstheregionofLima,ArequipacoverstheArequiparegion,TrujillocoversLaLibertadregion,ChiclayocoversLambayequeregion,andfinallyPiuracoversPiuraregion.ThemostremoteareasofthecountrywerenotpartoftheESuniverseforPeru.

II.2Universe

Theuniverseofinferenceincludesallformal(i.e.,registered)privatesectorbusinesses(withatleast1%privateownership)andwithatleastfiveemployees.Intermsofsectoralcriteria,allmanufacturingbusinesses(ISICRev4.codes10-33)areeligible;forservicesbusinesses,thosecorrespondingtotheISICRev4codes41-43,45-47,49-53,55-56,58,61-62,69-75,79,and95areincludedintheEnterpriseSurveys.CooperativesandcollectivesareexcludedfromtheEnterpriseSurveys.Alleligibleestablishmentsmustberegisteredwiththeregistrationagency.InthecaseofPeru,thelistingfromSUNAT,extractedinMarch2022,wasused.TheregistrationagencyisalsoSUNAT.Theuniversetableisthetotalnumberofeligibleestablishments,andthetableispartitionedbythestratificationgroups(industryclassification,establishmentsize,andsubnationalregion)inacountry.

ForthePeru2023WBES,theuniversetable,showninTable1below,wasobtainedfromSUNATinMarch2022.

3

II.3SamplingFrame

TheWBESrequiresthemostcompleteandup-to-dateSamplingFrame,thelistofeligibleestablishmentswithinformationonindustryclassification,size,addressandothercontactinformationthatwillbeusedtorandomlyselectthesample.IncountrieswhereapreviousroundoftheWBESexists,theSamplingFramealsoincludesthePanelSamplingFrame,whichprovidesinformationaboutalltheestablishmentsthatparticipatedinthepreviousroundoftheWBESinthecountry.

TheSamplingFrameforthePeru2023WBESwasconstructedfromthefollowingsources(seecountsofestablishmentsintheframeinTable2).ThePanelSamplingFramewasconstructedusinginformationonalltheestablishmentsthatparticipatedinthePeru2017WBES.TheFreshSamplingFrame,i.e.,listofestablishmentsthatareintheWBESuniverseandthathavenotparticipatedinthePeru2017WBES,forboththemanufacturingsector(ISIC4.0codes10-32)andtheservicessector(ISIC4.0codes41-43,45-47,49-56,58,61,62,69-75,79,95),wasobtainedfromSUNAT.

ForeveryWBES,necessarymeasuresaretakentoensurethequalityoftheframe;however,thesampleframesarenotimmunetothetypicalproblemsfoundinestablishmentsurveys:positiveratesofnon-eligibility,repetition,non-existentunits,etc.Giventheimpactthatnon-eligibleunitsincludedinthesampleuniversemayhaveontheresults,eligibilityadjustmentsmaybeneededwhencomputingtheappropriatesamplingweightsforindividualobservations(ifandonlyiftheweightsarecomputedthesamplingframethatisalsotheuniverse).Table4reportsresponseoutcomes.

II.4SampleDesign

TheWBESsampledesign,i.e.,targetnumberofinterviewsineachcombinationofstratificationcategories(cells),isgeneratedusingthetwoprimarycriteria:1)minimizethedifferencefromthepurelyproportionalsamplewithineachcell;and2)achieveasufficientsamplesizebystratificationcategorytoallowforestimatesofagivenlevelofprecision.4AdditionalinformationonthecriteriafordeterminingthesamplesizebystratificationcategoryisgivenintheSamplingNote,andadditionalinformationonthesampledesignisgivenintheEnterpriseSurveysManualandGuide.5TheoriginalsurveydesignforthePeru2023WBESisgiveninTable3.

III.DataCollection

ThedetailedinformationontheWBESmethodologyanddatacollectionisprovidedintheEnterpriseSurveysManualandGuide.TheinterviewsforthePeru2023WBESwereconductedbetweenAugust2022andAugust2023.TheinterviewswereconductedinSpanish.Formonetary

4Additionalconstraintsarealsoconsideredinthedesignstage.Thesearegenerallypracticalandinclude,forexample,havingasufficientnumberofavailablecontactsinthesample.

5TheEnterpriseSurveysManualandGuideisavailableat:

/content/dam/enterprisesurveys/documents/methodology/Enterprise-Surveys-

Manual-and-Guide.pdf

4

variables,thecurrencywasPEN(NuevoSoles).Aboutthirtyvariableswerecollectedthroughfollow-upphonesurveys,conductedbetweenMay2023andOctober2023;thesevariableshavethesuffix_BR.Althoughtherewasanattempttore-contactalltheestablishmentsthatparticipatedinthebaselinesurveystocollectthevariablesneededfortheB-readyreport,attritionoccurredinthefollow-upsurveys:830weresuccessfullyrecontacted(84%realizationrate);139refusedtoparticipate,and18wereunobtainable.

Apartfromthechallengeswithparticipationandcall-backsthatarestandardforallsurveys,thePeru2023WBESfacedchallengesduetopoliticalinstabilityinseveralregionsofthecountryinthefirsttrimesterof2023andadverseclimateeventsinMarch2023.Botheventscausedatemporarysuspensionoffieldworkintheaffectedareas.

III.1Questionnaire

ThestandardWBESquestionnairecoversseveraltopicsregardingthebusinessenvironmentandbusinessperformance.Thesetopicsincludegeneralfirmcharacteristics,infrastructure,salesandsupplies,managementpractices,competition,innovation,capacity,landandpermits,finance,business-governmentrelations,exposuretobribery,labor,andperformance.InformationaboutthegeneralstructureofthequestionnaireisavailableintheEnterpriseSurveysManualandGuide.

ThebaselinequestionnaireimplementedinthePeru2023WBESincludedadditionalquestionscoveringgreeneconomy.

Thefollow-upquestionnaireincludednewquestionsthatareaskedfortheBusinessReady(B-READY)project.

III.2Contractor

ThefieldworkforthePeru2023WBESwasimplementedbyDatumInternacionalSA.TheselectionfortheimplementingagencyfollowedthestandardWorldBankprocurementpracticesthataredescribedinmoredetailintheEnterpriseSurveysManualandGuide.

III.3Samplingandscreening

SamplesaredrawnbytheEnterpriseSurveysteaminbatches,followingthestratificationandsampledesign.ThecontractorconductedathoroughscreeningprocessbeforeschedulingtheESinterviews.ResultsofthescreeningareprovidedusingtheeligibilityandstatuscodesaslistedinTable4.Incasesofunitnon-response(eitherarefusaloraninabilitytoobtainaninterviewafterexhaustiveattempts),thecontractorproceededwiththecontactthatappearednextinthelistdrawnintherespectivecell.Theprocessofsamplingandscreeningisdescribedinmoredetailinthe

EnterpriseSurveysManualandGuide.

III.4Surveyresponse

Inallsurveys,includingtheWBES,somerespondentschoosenottoparticipate.TheEnterpriseAnalysisteamandthecontractortakeallnecessarymeasurestoboostparticipation,

5

throughvariousmethodsofrecruitment.Thepropermanagementofthescreeningprocessandsamplereplacementensuresthattheresultingsampleremainsrandom.

Themainmeasureofsurveyparticipationistheyield,whichistheratioofthetotalnumberofachievedinterviewstothetotalnumberofcontactedestablishments.Therearetwomainelementsthatboostyields.Firstisthesurveyparticipationrate,measuredastheshareofestablishmentsthatparticipatedamongthosethatcanbeassumedtohavebeeneligible.Thesecondelementisthequalityofframe.Ifonlyasmallfractionofthecontactedestablishmentsisactuallyeligibletoparticipateinthesurvey,thenthesamplingframeisfarfromideal.ThisqualityismeasuredbytheratioofthetotalnumberofestablishmentsthatcanbeassumedtobeeligiblefortheWBESwiththetotalnumberofcontactedestablishmentsintheframe.Inotherwords:

yield=surveyresponserate*Rateofqualityoftheframe

whichcanrewrittenasfollows:

Table5providesthesemeasuresforthePeru2023WBESandacrossitsstratificationlevels.

III.5AchievedSample

Tables6and7providecountoftheWBESinterviewscollectedforeachstratificationcell,i.e.,brokendownbyindustry,establishmentsize,andregion.Table6reportsfullsample,whileTable7showscountsofonlypanelinterviews.

III.6SamplingWeights

SincetheWBESusesstratifiedrandomsampling,individualobservationsshouldbeproperlyweightedwhenmakinginferencesaboutthepopulation,sinceunweightedestimatesarebiasedunlesssamplesizesareproportionaltothesizeofeachstratum.ForeachWBES,specialcareisgiventocorrectlycomputesamplingweights.WhenevertheUniverseisusedtodrawthesample(i.e.,SamplingFrameisthesameastheUniverse)itisimperativetoaccuratelyadjusttheuniversewithineachstratumtoaccountforthepresenceofineligibleestablishments(e.g.,thefirmdiscontinuedbusinesses,orisdeemedineligibleduetoitsbusinessactivityorhavingfewerthanfiveemployees).Propertreatmentofpanelestablishmentsisalsocrucial.DetailsabouthowtheWBESsamplingweightsarecalculatedaregivenintheSamplingNote.

Threeversionsofsamplingweightsarecalculated,dependingontheassumptionsthatdetermineeligibilityofestablishmentstobecountedtowardstheWBESuniverse.Theseassumptionsarecalledweak,medium,andstrong;andaredefinedasgiveninthetablebelow.PrevalenceofeachoftheseoutcomesforthePeru2023WBESisgiveninTable4.AllindicatorsandanalysisconductedbytheEnterpriseSurveysteamusethesamplingweightsbasedonthemedianassumption.Tables8-10reportestimateduniversebasedontherespectiveassumption.

6

Assumption

EligibilitycodesforinclusionintheWBESuniverse

Strict

1,2,3,4,16

Median

1,2,3,4,16,10,11,13

Weak

1,2,3,4,16,10,11,13,91,92,93,94,12

Fordescriptionsofeacheligibilitycode,seeTable4.

Twodifferentsetsofweightsarepresentedinthedataset.ThestandardweightsdiscussedaboveapplytothestandardEnterpriseSurveyquestionsthatwereadministeredinthebaselinesurveytoallrespondents.Thesecondsetofweightsaredenotedwiththesuffix_BRandtheyapplytothequestionsaskedinthefollow-upsurveys,i.e.,toallthevariablesdenotedwiththesuffix_BR.Bothsetsofweightsarescaledsuchthattheyarenationallyrepresentativeofthebusinessesoperatinginthecountry.Thisimpliesthatallvariableswiththesuffix_BRmustbeusedwiththeweightswithsuffix_BRwhereasvariableswithoutthesuffixmustusetheweightswithoutsuffixwhenmakinginferencestothepopulation.

III.7Itemresponserates

Itemresponseratemustbedifferentiatedfromsurveyresponserates.Thelatterreferstoparticipationinthesurveyitself(seeSectionIII.4)whereastheformerreferstotheabsenceofresponsestospecificsurveyquestions.6TheWBES,asanysurvey,sufferfromitemnon-response;anddifferentstrategiesareusedbythedatacollectionteamtoaddressthis.Inparticular:

?Forsensitivequestions,suchasoncorruptionortaxevasion,enumeratorswereinstructedtocollecttherefusaltorespond(-8)asaseparateresponsecategoryfromdon’tknow(-9).

?Establishmentswithincompleteinformationwerere-contactedtofillgaps.

Table11providesitemresponseratesforseveralkeyvariables,brokendownacrossthestratificationlevels.

III.8DatabaseStructure

TheWBESdatafilesareorganizedinwaysthatreflectthecorrespondingquestionnaire.Thevariablesthatarestandardacrosscountrieshavethefirstletterintheirnamecorrespondtothequestionnairesectionwherethevariablebelongsinthequestionnaire,i.e.,a1denotessectionA.Forthefollow-upsurvey,allthevariableshavethesuffix_BR,includingtheweights.Allvariablesarenumericwiththeexceptionofthosevariableswithan“x”attheendoftheirnames.Thesuffix“x”denotesthatthevariableisalpha-numeric.

TheWBESdatafilescontaintwoestablishmentidentifiers,idstdandid.Theformerisaglobaluniqueidentifierofeachestablishment,whilethelatterisuniqueidentifierwithineachsurvey.ThevariableidstdcanbeusedtomatchtheWBESestablishmentone-to-oneacross

6TheWBESquestionnaireisorganizedsothatthereisalwayssomeentryinthedatabasewhenthequestionwas

posed.Anemptyentrymeansthatthequestionwasnotaskedtothecorrespondingrespondent,typically,duetoskippatterns,orlackofapplicabilityofthatquestioningeneral.

7

databases.Thevariableswweak,wmedian,andwstrongcorrespondingtosamplingweightsbasedon,respectively,weak,median,andstrongassumptionsabouteligibility(seeSectionIII.6).Thevariablestratacorrespondstothestratumofeachobservation.

Additionally,theWBESdatafilescontainmanystandardvariables.Thevariabled1a2_v4denotesthemainactivityoftheestablishment,asobtainedduringtheWBESinterview,codedinthefour-digitISICRev.4.UsersshouldnotethatthisactivitymaydifferfromtheindustryclassificationgivenintheSamplingFrame,a4a.Usersaregenerallyadvisedtouseindustrycategoriesbasedontherealizedinformationind1a2_v4.Additionalsamplinginformationiscontainedinvariablesa2(region)anda6a(size).Thevariablepanelidentifiespanelestablishments,i.e.,thosethatparticipatedinthePeru2017WBES.Thecombinationofa4a,a2,a6a,andpanelformsstratumofeachestablishment,whichiscontainedinvariablestrata.

Thelastcompletefiscalyearforeachestablishmentiscontainedinvariablesa20m(lastmonthoflastcompletefiscalyear)anda20y(lastcompletefiscalyear).

NotethatwhenanentryintheWBESdatabaseisempty,thismeansthatthequestionwasnotaskedtothecorrespondingrespondent.Thishappenswhenthequestionisdeemedinapplicable,duetoskippatternsorotherreasons.Incaseswhenthequestionwasposed,someentryisprovided,includingdon'tknow,whichisanexampleofitemnon-response.

8

IV.UsefulLinks

TheusersoftheWBESdatamayfindthefollowinglinksuseful:

?SamplingNoteisavailableat:

/content/dam/enterprisesurveys/documents/methodolog

y/Sampling_Note-Consolidated-2-16-22.pdf

?TheEnterpriseSurveysManualandGuideisavailableat:

/content/dam/enterprisesurveys/documents/methodolog

y/Enterprise-Surveys-Manual-and-Guide.pdf

?TheWBESglobalquestionnairesareavailableat:

/en/methodology

?TheprojectsthatarecurrentlybeingimplementedbytheEnterpriseSurveysteamareavailableat:

/en/current-projects

?ThelistofallWBESdatabasesanddetailedinformationabouteachisavailablehere:

/content/dam/enterprisesurveys/documents/methodolog

y/DataDetails.xls

?ThedescriptionoftheWBESindicatorsisavailableat:

/content/dam/enterprisesurveys/documents/Indicator-

Description.pdf

9

FactSheet

SourceofUniverseTable

SUNATMarch2022

SourceofSamplingFrame

SUNATMarch2022

Stratificationsectors

Manufacturingof:Food,Textiles,Garments,Othermanufacturing;Retail,Hotels,andOtherServices

Stratificationsizes

Small(5to19employees),Medium(20to99employees),andLarge(100ormore)

Stratificationregions

Lima,Arequipa,Chiclayo,Trujillo,Piura

Contractor

DatumInternacionalSA

Fieldworkdates

August2022-August2023(Baseline)

Interviewlanguages

Spanish

Surveysoftware

SurveySolutions

Currencyfornominalvariables

PEN(NeuvoSoles)

Referencefiscalyear

2021(396obs.)and2022(591obs.)

SampleSize

Total:987Fresh:629Panel:358

Surveyresponserates

Yield:13.4%Responserate:25%Framequality:53.5%

Itemresponserates

d2:95.1%n2a:83.9%l1:100%allTFPvars.:71.2%

Additionaltopicscoveredinthe

questionnaire

Greeneconomy

Additionalsurveysavailable(ifany)

InformalSectorEnterpriseSurvey

10

Tables

11

Table1:Peru2023WBESUniverse

FoodTextilesGarmentsOtherMfgRetailHotels·OtherServicesGrandTotal

Lima

Small(5-19)

644

313

585

3,515

2,863

399

14,483

29,622

Lima

Medium(20-99)

215

82

109

786

375

93

3,395

Lima

Large(100ormore)

152

38

47

325

124

28

1,051

Arequipa

Small(5-19)

74

21

37

238

299

77

1,604

2,790

Arequipa

Medium(20-99)

23

1

2

53

23

8

230

Arequipa

Large(100ormore)

5

4

3

22

6

0

60

Chiclayo

Small(5-19)

64

0

2

88

151

35

645

1,136

Chiclayo

Medium(20-99)

9

0

0

15

10

4

80

Chiclayo

Large(100ormore)

9

0

0

5

2

0

17

Trujillo

Small(5-19)

54

3

4

177

259

59

1,562

2,515

Trujillo

Medium(20-99)

11

0

1

26

21

5

266

Trujillo

Large(100ormore)

10

0

0

6

5

0

46

Piura

Small(5-19)

63

1

4

97

229

52

841

1,551

Piura

Medium(20-99)

28

0

0

14

20

4

141

PiuraLarge(100ormore)190036029

1,380-

463

794

5,370

4,393-

764

24,450

37,614

Source:SUNATMarch2022

12

Table2:Peru2023WBESSampleFrame(FreshandPanelCombined)

Textiles

·Food·

Garments·OtherMfgRetail·HotelsOtherServicesGrandTotal

Lima

Small(5-19)

480

205

507

1507

1177

250

5105

14,436

Lima

Medium(20-99)

173

86

81

664

295

70

2252

Lima

Large(100ormore)

175

52

66

355

122

25

789

Arequipa

Small(5-19)

60

20

42

240

275

61

1304

2,508

Arequipa

Medium(20-99)

26

2

5

65

26

9

241

Arequipa

Large(100ormore)

8

7

5

29

9

0

74

Chiclayo

Small(5-19)

49

0

6

88

130

32

533

1,017

Chiclayo

Medium(20-99)

11

0

0

13

13

5

98

Chiclayo

Large(100ormore)

12

0

0

4

3

0

20

Trujillo

Small(5-19)

47

2

6

194

226

53

1201

2,141

Trujillo

Medium(20-99)

9

0

2

34

27

7

254

Trujillo

Large(100ormore)

11

0

0

8

3

1

56

Piura

Small(5-19)

48

1

2

77

148

36

592

1,137

Piura

Medium(20-99)

22

0

0

13

21

4

115

Piura

Large(100ormore)

19

0

0

2

6

0

31

1,150

-375

722

3,293

2,481

553

12,665

21,239

Source:TheframewasobtainedbyenrichingthedatasetfromtheUniverse.Universegenerallydidnotcontainanycontact

informationbutthevendor,usingtheinfoavailableintheuniverse(RUC,firmdenomination)diddeskresearchtoidentifythecontactinformation.Theenrichmenthappenedusingthefollowingsources:Top10mil(baseespecializada),TopPYME(baseespecializada),Redessociales(FacebookyLinkedIn),Páginawebdelasempresas,Internetengeneral).

13

Table3:OriginalSurveyDesign(FreshandPanelCombined)

FoodTextilesGarmentsOtherMfgRetailHotelsOtherServicesGrandTotal

Lima

Small(5-19)

7

25

25

25

19

16

17

435

Lima

Medium(20-99)

19

27

28

32

11

19

25

Lima

Large(100ormore)

25

17

24

28

26

7

13

Arequipa

Small(5-19)

8

6

14

10

11

17

20

180

Arequipa

Medium(20-99)

9

1

3

19

8

3

10

Arequipa

Large(100ormore)

3

3

3

10

4

0

18

Chiclayo

Small(5-19)

11

0

3

11

15

9

20

120

Chiclayo

Medium(20-99)

3

0

0

4

5

3

21

Chiclayo

Large(100ormore)

4

0

0

2

2

0

7

Trujillo

Small(5-19)

12

1

3

11

21

16

20

160

Trujillo

Medium(20-99)

3

0

1

11

9

2

24

Trujillo

Large(100ormore)

4

0

0

3

1

1

17

Piura

Small(5-19)

4

0

1

5

8

10

4

105

Piura

Medium(20-99)

7

0

0

5

8

2

33

Piura

Large(100ormore)

5

0

0

1

2

0

10

124

80

105

177

150

105

259

1,000

14

Table4:ResponseOutcomes

Totals

Ratesrelativetototalcontacted

Overall

Contactsavailableinframe

21,239

Issued

8,109

Screeningphase

Contacted

7,386

Eligibles

1,204

16.3%

Screenerrefusals

2,152

29.1%

Assumedeligibles

3,953

53.5%

Interviewphase(onlyifeligible)

Ineligible+outoftarget

627

8.5%

Unobtainables

3,403

46.1%

Interviewrefusals

217

2.9%

Completeinterviews

987

13.4%

Table5:SurveyYieldRates

Stratification

Yield

Surveyresponserate

Framequality

Panel

Fresh

9.9%

19.3%

51.2%

Panel

35.7%

52.1%

68.5%

Size

Small(5-19)

12.4%

25.6%

48.6%

Medium(20-99)

16.2%

29.6%

54.6%

Large(100+)

11.7%

18.9%

62.1%

Region

Lima

10.7%

19.3%

55.5%

Arequipa

16.6%

27.9%

59.4%

Chiclayo

20.2%

40.7%

49.6%

Trujillo

15.7%

34.1%

46.0%

Piura

15.0%

31.8%

47.2%

Sector

Food

13.9%

24.2%

57.3%

Textiles

11.8%

21.3%

55.5%

Garments

12.2%

25.9%

47.3%

OtherManufacturing

16.2%

30.4%

53.2%

Retail

12.9%

24.9%

51.9%

Hotels

16.1%

25.5%

63.1%

OtherServices

11.7%

22.4%

52.3%

Overall

Peru2023

13.4%

25.0%

53.5%

Notes:theratesarecalculatedasdefinedinSectionIII.4.

15

Table6:AchievedTotalSample(FreshandPanelCombined)

Garments

Textiles

OtherMfg

Retail

Hotels

OtherServices

GrandTotal

Food

Lima

Small(5-19)

8

18

25

23

11

25

16

436

Lima

Medium(20-99)Large(100or

25

11

12

44

28

13

21

Lima

more)

28

8

12

54

12

7

35

Arequipa

Small(5-19)

5

4

12

20

18

17

17

176

Arequipa

Medium(20-99)Large(100or

7

1

1

14

3

3

34

Arequipa

more)

1

2

2

5

0

0

10

Chiclayo

Small(5-19)

9

0

2

13

23

6

15

112

Chiclayo

Medium(20-99)Large(100or

4

0

0

4

6

2

23

Chiclayo

more)

0

0

0

1

1

0

3

Trujillo

Small(5-19)

6

0

2

25

26

7

19

155

Trujillo

Medium(20-99)Large(100or

2

0

0

9

5

1

41

Trujillo

more)

1

0

0

0

0

0

11

Piura

Small(5-19)

9

0

0

12

22

7

12

108

Piura

Medium(20-99)Large(100or

2

0

0

3

5

1

24

Piura

more)

2

0

0

0

0

0

9

109

44

68

227

160

89

290

987

16

Table7:AchievedPanelSample

·Food·TextilesGarments·OtherMfgRetailHotelsOtherServicesGrandTotal

Lima

Small(5-19)

6

3

13

18

8

0

1

189

Lima

Medium(20-99)

15

7

8

29

10

0

11

Lima

Large(100ormore)

13

6

8

25

3

1

4

Arequipa

Small(5-19)

1

0

4

5

5

0

10

49

Arequipa

Medium(20-99)

3

1

1

5

1

0

3

Arequipa

Large(100ormore)

0

2

2

2