LouisBéduneau
August21,2025
Report2025-007
1Introduction
Thebankingsectorplaysakeyroleinmoderneconomies,butitsrelativeweightcan vary,influencingeconomicstabilityandwealthcreation.Anoversizedbankingsectorcan generateriskssuchasexcessivespeculationorwealthcapture(illustratedbythe2008 LehmanBrotherscrisis),whileanundersizedsectormayreflectaneconomyunableto sustainacomplexfinancialsystem.Thisstudyanalyzestherelationshipsbetweenindustrialproduction,thebankingsector,andpublicdebtinthe30largestglobaleconomies, focusingontheircontributiontoGDPandimplicationsforwealthcreation.
Thestudyaddressesthecentralquestion:Isthereacorrelationbetweenindustryand thebankingsector?Italsoexaminesthelinksbetweenthebankingsectorandpublic debt,aswellastherelationshipsbetweenGDPandtheindustrialandbankingsectors, toproposeanoptimalbankingsectorweightmodel.Themethodology(section2)details thesourcesandanalyticalapproaches.Subsequentsectionsexplorespecificcorrelations (sections3to6)andproposeanoptimalmodel(section7),followedbyasynthesisand conclusion(section8).
2Methodology
ThisstudyusesofficialdatafromtheInternationalMonetaryFund(IMF,WorldEconomicOutlook,October2023)fornominalGDP(billionsUSD,2023)andpublicdebt (%ofGDP,2023),andfromtheWorldBankforindustrialproduction(valueaddedof industry,includingconstruction,%ofGDP,2022)andthebankingsector(valueadded offinancialservices,insurance,andrealestate,%ofGDP,2022).Theanalysiscovers the30largesteconomiesbynominalGDP.
Forcontext,thestudyconsiderseconomicevolutionsince1945,markedbypost-war industrialization,followedbytertiarizationindevelopedeconomiesandthepersistenceof industryinemergingeconomies.CorrelationsarecalculatedusingthePearsoncoefficient, measuringlinearrelationshipsbetween:
• Industrialproduction(%ofGDP)andbankingsector(%ofGDP).
• Bankingsector(%ofGDP)andpublicdebt(%ofGDP).
• NominalGDP(billionsUSD)andindustrialproduction(%ofGDP).
• NominalGDP(billionsUSD)andbankingsector(%ofGDP).
Calculationsaredetailedintheannex(section11).Resultsareanalyzedinthefollowing sections,withasynthesisintheconclusion(section8).
3CorrelationbetweenIndustrialProductionandBankingSector
Thissectionanalyzesthecorrelationbetweenindustrialproduction(valueaddedofindustry,includingconstruction,%ofGDP)andthebankingsector(valueaddedoffinancial services,insurance,andrealestate,%ofGDP)forthe30largestglobaleconomies(2022 data).Thefollowingtablepresentsthekeydata.
Table1:IndustrialProductionandBankingSector(2022)
Pearsoncorrelationcoefficient:-0.69
Thecoefficientof-0.69indicatesamoderatetostrongnegativecorrelation.Economies withhighindustrialproduction(e.g.,SaudiArabia:44.7%,Indonesia:41.4%)tendto havealowerbankingsectorweight.Conversely,countriesliketheUnitedStatesorthe UnitedKingdomtendtohaveahigherbankingsectorweight(7.8%,8.2%).
4CorrelationbetweenBankingSectorandPublic Debt
Thissectionexaminesthecorrelationbetweenthebankingsector(%ofGDP,2022)and publicdebt(%ofGDP,2023)forthe30largesteconomies.Thefollowingtablepresents thedata.
Table2:BankingSectorandPublicDebt(2022-2023)
Pearsoncorrelationcoefficient:0.18
Thecoefficientof0.18indicatesaveryweakpositivecorrelation.Thesizeofthe bankingsectorisnotstronglylinkedtopublicdebt.Forexample,Japan(254.6%debt, 6.2%banking)contrastswithSwitzerland(38.3%debt,9.8%banking).Thisweakrelationshipsuggeststhatdebtismoreinfluencedbyfiscalpoliciesthanbythebanking sector’sweight.Thefollowingsections(sections5,6)exploretheimpactofthesesectors onwealthcreation.
5CorrelationbetweenGDPandIndustrialProduction
ThissectionanalyzesthecorrelationbetweennominalGDP(billionsUSD,2023)and industrialproduction(%ofGDP,2022)toassesswhetherindustrydriveswealthcreation.
Table3:GDPandIndustrialProduction(2022-2023)
Pearsoncorrelationcoefficient:-0.54
Thecoefficientof-0.54indicatesamoderatenegativecorrelation.Economieswith highGDP(UnitedStates:25,463billion,China:18,321billion)donotnecessarilyhave strongindustrialproduction(17.9%,39.9%),whilesmallereconomieslikeSaudiArabia (1,069billion,44.7%)orIndonesia(1,317billion,41.4%)relyheavilyonindustry.Wealth creationofteninvolvesamixofindustry,services,andotherfactorsessentialforliving standardsandcountryattractiveness.
6CorrelationbetweenGDPandBankingSector
ThissectionanalyzesthecorrelationbetweennominalGDP(billionsUSD,2023)andthe bankingsector(%ofGDP,2022)todetermineifastrongbankingsectorislinkedtohigh wealthcreation.
Table4:GDPandBankingSector(2022-2023)
Pearsoncorrelationcoefficient:0.32
Thecoefficientof0.32indicatesaweakpositivecorrelation.High-GDPeconomies (UnitedStates,China)haveamoderatelydevelopedbankingsector(7.8%,8.0%),but smallereconomieslikeSwitzerland(9.8%)orAustralia(8.5%)showastrongbanking contribution.ThissuggeststhatthebankingsectorisnotaprimarydriverofGDPsize butplaysasupportiverole.Thenextsection(section7)proposesamodeltooptimize thisrole.
7OptimalBankingModel
Basedonthecorrelationsanalyzed(sections3to6),anoptimalbankingsectormodel aimstobalanceitsweighttosupportwealthcreationwithoutgeneratingsystemicrisks. EconomieslikeCanada(6.8%banking,24.0%industry,107.0%debt),SouthKorea
(6.7%banking,32.1%industry,49.3%debt),andtheNetherlands(6.0%banking,20.2% industry,50.1%debt)offerabalance:abankingsectorrepresenting5to7%ofGDP, moderateindustrialproduction(20-32%),andmanageabledebt(50-107%).
Thismodelavoidsextremes,suchasSwitzerland(9.8%banking,riskofover-financialization) orNigeria(3.8%banking,under-developedfinance).Abankingsectorof5to7%supportsindustrialinvestmentwhilelimitingspeculationrisks.Theconclusion(section8) synthesizesthesefindingstoguideeconomicpolicies.
8Conclusion
Thisstudyanalyzedtherelationshipsbetweenindustrialproduction,thebankingsector, publicdebt,andGDPinthe30largestglobaleconomies.Theresultsshow:
• Amoderatetostrongnegativecorrelation(-0.69)betweenindustrialproductionand thebankingsector(section3),reflectingspecializationbetweenindustrial(emerging)andtertiary(developed)economies.
• Averyweakpositivecorrelation(0.18)betweenthebankingsectorandpublicdebt (section4),indicatingthatdebtdependslittleonthebankingsector’ssize.
• Amoderatenegativecorrelation(-0.54)betweenGDPandindustrialproduction (section5),suggestingthatindustryisnottheprimarywealthdriverinlarge economies.
• Aweakpositivecorrelation(0.32)betweenGDPandthebankingsector(section 6),indicatingasupportiveroleforthebankingsector.
Synthesisforwealthcreation:Thebesteconomicsystemcombinesmoderateindustrial production(20-32%ofGDP)andabankingsectorof5to7%ofGDP(section7).This model,observedineconomieslikeCanadaorSouthKorea,fosterswealthcreationby supportingindustrialinvestmentwhilelimitingfinancialrisks.
Warningindicators:Abankingsectorexceeding8%ofGDP(e.g.,Switzerland:9.8%, Australia:8.5%)maysignalariskofover-financialization,increasingvulnerabilityto crises(e.g.,LehmanBrothers).Conversely,abankingsectorbelow4%(e.g.,Nigeria: 3.8%,Turkey:3.9%)maylimitindustrialfinancing,hinderinggrowth.
Nuances:Thebankingsectorisessentialforfinancingindustry,providingcapitalfor investmentandinnovation.However,rigorouspublicbudgetmanagementiscrucialto avoidexcessivedebt(e.g.,Japan:254.6%,Italy:140.6%),whichcanweakentheeconomy independentlyofthebankingsector’sweight.Economicpoliciesmustthereforebalance financialdevelopment,industrialsupport,andfiscaldiscipline.
9Limitations
• Temporality:Sectoraldata(2022)anddebt/GDPdata(2023)haveaslightlag.
• Definitions:Thebankingsectorsometimesincludesrealestateactivities,which mayskewcomparisons.
• Linearcorrelation:ThePearsoncoefficientdoesnotcapturenon-linearorcontextualrelationships.
• Historicalcontext:Theanalysisfocuseson2022-2023,limitingexplorationofevolutionsince1945.
10References
• InternationalMonetaryFund.(2023).WorldEconomicOutlook,October2023. Availableat: https://www.imf.org
• WorldBank.(2023).WorldDevelopmentIndicators.Availableat: https://data. worldbank.org
11Annexes
11.1CompleteDataTable
Table5:CompleteData(2022-2023)
Country GDP(billionsUSD,2023)%Industry(2022)%Banking(2022)
Table5:CompleteData(2022-2023)
11.2CorrelationCalculations
Correlationbetween%Industryand%Banking:
7 88
0 69
Correlationbetween%BankingandDebt:
CorrelationbetweenGDPand%Industry:
• MeanGDP:25,463+18,321+··· +374 ≈ 3, 028 3Mean%Industry :≈ 27 93
• Covariance: ∑(xi x)(yi y) ≈−37, 295 6StandarddeviationGDP : √∑(xi x)2 ≈ 5, 155.7
• Standarddeviation%Industry: √∑(yi y)2 ≈ 7.88Pearsoncoefficient : 37,295 6 5,155 7×7 88 ≈ 0.54
CorrelationbetweenGDPand%Banking:
• MeanGDP: ≈ 3, 028 3Mean%Banking :≈ 5 74
• Covariance: ∑(xi x)(yi y) ≈ 2, 683 9StandarddeviationGDP : √∑(xi x)2 ≈ 5, 155 7
• Standarddeviation%Banking: √∑(yi y)2 ≈ 1 64Pearsoncoefficient : 2,683 9 5,155 7×1 64 ≈ 0 32