Table Of ContentGalimkair Mutanov
Mathematical
Methods and Models
in Economic Planning,
Management
and Budgeting
Second Edition
Mathematical Methods and Models in Economic
Planning, Management and Budgeting
Galimkair Mutanov
Mathematical Methods
and Models in Economic
Planning, Management
and Budgeting
Second Edition
GalimkairMutanov
Al-FarabiKazakhNationalUniversity
Almaty,Kazakhstan
ISBN978-3-662-45141-0 ISBN978-3-662-45142-7(eBook)
DOI10.1007/978-3-662-45142-7
SpringerHeidelbergNewYorkDordrechtLondon
LibraryofCongressControlNumber:2014955682
1stedition:©Al-FarabiKazakhNationalUniversity2011
©Springer-VerlagBerlinHeidelberg2015
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Preface
A new qualitativestage of the market economy,defined as knowledgeeconomics,
differs considerably from the previous stage in terms of nonlinear trends in eco-
nomicdevelopment.Thoseresponsibleforreproductioncyclemanagementhaveto
makemanagerialdecisionsinconditionsofhighuncertaintyaffectingthedevelop-
mentofproductionprocesses,distribution,exchange,andconsumption.Itisimpos-
sibletoestimatetheeffectivenessofsuchprojectsandprocesseswithoutadequate
administrativeinstruments.
Economic-mathematical modeling is one of the most effective methods for de-
scribing complex socio-economic objects and processes in terms of mathematical
models in combination with new engineering decisions. Modeling thus becomes
partofeconomicsitself.Knowledgeeconomicsasacommonalbeitsomewhatab-
stractcategorymustbeexpressedinatangibleconcreteform.Thiscanbeachieved
bymeansofmathematicmodelingofitsprocessesasmanagerialobjects.
Thepresentworkpresentsaseriesofworksinthefieldofscientificandmethod-
ological bases of creation of information-analytical systems of management of fi-
nancialandeconomicprocessesandsystemsintheperiodfrom1995to2011years.
Thistextreflectsthecurrentleveloftheoreticalresearchanddevelopmentofthe
systemofmathematicalmodelsandmethodsthatcanbeusedtosolvereal,impor-
tanteconomicproblems:controlofdevelopmentandoperationsupportatanybud-
getlevel;qualityassessmentofeconomicsystemsmanagementintermsofenergy-
entropicapproach;andriskmanagementofinvestmentprocesses.
The proposed mathematical methods and models were tested on the example
ofKazakhstan’seconomy,anddevelopedsolutionsandmodelsmaybeusedinany
levelandinanyState.Inthecourseofthisresearchwereanalyzedanddevelopedthe
ideasofNobellaureatesandleadingscientists—V.Leontiev,Prigogine,G.Odum,
E. Odum, Harold Kuhn, John Keynes, Christopher Sims, principle of McKinsey
matrixandothers.
The reader will find presented here a complex of models used to analyze and
forecasttheflowofbudgetfinancialresources.Currentcalculationsandlong-term
forecasting of budget indicators are the instruments of realization of strategic de-
velopmentplans. Traditional methods of budget program planning are still widely
v
vi Preface
used; they include planning based on rated standards specified by administrative
bodiesorbythechangingdynamicsofpreviousperiods.However,thedevelopment
of information technologies (IT), the requirements of a market economy, and the
highpaceofdevelopmentnecessitatenew,highlyintellectualandpreciseanalytical
andplanningmodels.
The semantic and frame-based models suggested in this work create the math-
ematicalbasis for automatedsystem control.The authorpresents here his seminal
development of a mathematical budget model which with mathematical exactness
reflects properties and conditions at any budget level. Methods and mathematical
modelsforprogramcontrolofbudgetresourcesfocusedonendresultssuchascor-
rectplanningareutilizedaccordingtothestrategicplanofsocio-economicdevelop-
mentofthenationorregion.Benchmarksarethuscreatedagainstwhichtoestimate
the achievability of set goals under certain limitations in budget funds and budget
potentialasdeterminedintheprocessofmedium-termplanning.Thisworkdetails
aneffectivemethodforestimatingthestabilityofprogrammovementsdetermining
systemdecisions,basedonconstructionofLyapunov’sfunction,allowingplanners
toestimatetheefficiencyofbudgetmechanismsforresourcedistribution.Theprin-
ciplesgoverningthedesignofanintellectualsystemmodelingprogramcontrolof
budget resources, and permitting correction of the decision by adjustment of the
systemofindicators,areoutlined.
Newknowledgeoftenarisesattheintersectionofdifferentscientificfieldswhen
well-knownlawsofonescienceareadaptedtoandinterpretedbytheother,opening
upaphenomenonforapproachfromanotherangle,andtheresultscanbeexciting.
Anexampleisapplicationofthethermodynamicapproachtobusinesssystemman-
agement, through mathematicaldescriptions focused on a decrease in entropy and
increase in productiveefficiency.The theoreticalapproachproposed by the author
becomesevenmorevaluableasnationaltheoryandpracticeinKazakhstanhavenot
previously offered developments in the assessment of business system efficiency
based on the energy-entropic method. The universality of the proposed method is
based on the fact that all systems of the material world—from wildlife and inan-
imate nature to technology and production—are arenas of ever-present change in
amounts of energy and entropy, and studying this dynamic can give new knowl-
edgeofthelawsgoverningthefunctioninganddevelopmentofsuchsystems.This
research undertakes, therefore, the scientifically based application of the energy-
entropic method to assessment of the economic efficiency of any production pro-
cess.
Theworkfurthersuggestsmethodsandmathematicalmodelswhichcanbeused
to analyze currency purchase and sale, to make forecasts, to determine profitable
cycles,andtostructuredecision-makingintheforeignexchangemarket.Aninfor-
mationsystemisdevelopedonthefoundationofthesemethodsandisappliedtoa
moredetailedanalysisoftheforeignexchangemarket,leadingtopracticalrecom-
mendations for second-rank banks on correction of exchange rates. A description
is provided of the software, hardware, and instrumentation used in the proposed
system.
Inordertoprotectthesafetyoffinancialinvestmentsinconditionsofinformation
uncertainty,methods and mathematicalmodels are developedto assess innovation
Preface vii
projects. This is a strategically oriented approach which enables every project to
engagethehighestavailableexpertiselevelwithapplicationofadvancedinforma-
tiontechnologies.Theroleofrisk-managementandqualitativeprojectassessment
becomesevenmoreimportantiftheprojectinquestionisinnovative—anditmust
bestressedherethatinnovativenessofdevelopmentisoneofthemainprioritiesof
the economic program of our country. A richly complex method of assessment of
innovation projects and a graphic model based on such parameters as innovation,
competitiveness,andreducednetcostofaprojectfacilitatein-depthassessmentof
innovation projects on the basis of absolute positioning. The methods and mathe-
maticalmodelspresentedherecanbeusedbyexpertcommissionsofventurefunds,
developmentinstitutes,andotherpotentialinvestorstomeaningfullyassessinnova-
tionprojects.
Investmentinthedevelopmentofeconomicprocessesandsystemsalwaysentails
risk.Aninvestmentdecisionthatisnotadequatelyreasonedcancauseadverseeco-
nomic consequences for the investor. Making investment decisions becomes even
more complicated with the high degree of uncertainty surrounding economic con-
sequences of a given investment. The series of mathematical methods and models
proposed here represent an integrated methodology for making investment deci-
sionsthataimstoreduceriskbymoreobjectivelyestimatingprobabilityofinvest-
ment consequences, and thereby to equip the investor with a practical instrument
for scientifically-based forecasting. A review of a variety of methodological ap-
proaches to studying risk reveals that researchers tend to focus their attention on
entrepreneurialrisk—thatistosay,astheobjectofanalysistheyconsiderindivid-
ual enterprises, and the subjects of their investigations are statistical variations in
stochasticprobabilitydistributionsofallpossiblelossesanddamages.Meanwhile,
insufficient attention is given to the investigation of principles of functioning and
formsofmanifestationofnonstatisticalrisks,theirinfluenceontheentrepreneurial
activityandinteractionwithstatisticalrisks.Thisresearchsuggestsamethodologi-
calbaseforcreationofanintegralexpertsystemsupportingcoordinatedinvestment
decisionsthattakesintoaccountassessmentandcontrolofprojectrisks.
Themethodsandmodelsdevelopedbytheauthorhavebeenbroughttopractical
realizationintheformofsoftwaretools.Thesearereliableinstrumentstobeused
in solving problems of business forecasting, assessment, and management of the
developmentofeconomicprocessesandsystems.
I would like to acknowledge contributions to this book made by my assistants
I.G. Kurmashev, A.U. Shintemirova, Zh.D. Mamykova, E.S. Kutuzova, V.P. Ku-
likova.
Itismyhopethatthisworkwillbeofboththeoreticalandpracticalinteresttoits
readers,tothebenefitofall.
Contents
1 MathematicalMethodsofBudgetModeling . . . . . . . . . . . . . 1
1.1 BudgetasanObjectofModelingandManagement. . . . . . . . 2
1.1.1 BudgetStructureandContents . . . . . . . . . . . . . . 2
1.1.2 MainPrinciplesofBudgetFormation . . . . . . . . . . . 3
1.2 BudgetModels . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.2.1 ModelsofKnowledgeRepresentationandBudget
Functioning . . . . . . . . . . . . . . . . . . . . . . . . 6
1.2.2 SemanticModelofBudgetRepresentation . . . . . . . . 10
1.2.2.1 ObjectDomainModel . . . . . . . . . . . . . . 10
1.2.2.2 ABudgetStructureGraph . . . . . . . . . . . . 14
1.2.2.3 AGraphRepresentingBudgetValues . . . . . . 14
1.2.2.4 AnExampleoftheSemanticModel . . . . . . 17
1.2.3 Frame-BasedModelofBudgetKnowledge
Representation . . . . . . . . . . . . . . . . . . . . . . . 18
1.2.3.1 BudgetModel . . . . . . . . . . . . . . . . . . 18
1.2.3.2 BudgetItemModel . . . . . . . . . . . . . . . 20
1.2.3.3 AnExampleoftheFrame-BasedModel . . . . 21
1.3 MathematicalBudgetModels . . . . . . . . . . . . . . . . . . . 23
1.3.1 StaticMathematicalBudgetModel . . . . . . . . . . . . 24
1.3.2 MathematicalModelofInteractionofIncome
andExpenditureItems . . . . . . . . . . . . . . . . . . . 28
1.3.3 ModelofBudgetSensitivity . . . . . . . . . . . . . . . . 32
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
2 MethodsandMathematicalModelsofBudgetManagement . . . . 39
2.1 CurrentTrendsinBudgeting. . . . . . . . . . . . . . . . . . . . 39
2.2 CurrentStateofBudgetControlMethodsandMathematical
Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
2.3 GeneralConceptoftheProgrammableMethodofBudget
MechanismControl . . . . . . . . . . . . . . . . . . . . . . . . 43
ix
x Contents
2.3.1 GeneralStatementoftheProblemofBudgetMechanism
Control . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
2.3.2 CyberneticApproachtotheDescriptionofBudget
Mechanism. . . . . . . . . . . . . . . . . . . . . . . . . 44
2.3.3 SystemApproachtotheMathematicalModelofBudget
Mechanism. . . . . . . . . . . . . . . . . . . . . . . . . 47
2.4 MathematicalModelsofBudgetExpenditure . . . . . . . . . . . 50
2.4.1 ConstructionofProgramMovementsforBudget
Expenditure . . . . . . . . . . . . . . . . . . . . . . . . 50
2.4.2 AModelofProgramControloftheExpenditureBudget
Part . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
2.4.3 ModelofManagementAdjustment . . . . . . . . . . . . 57
2.4.4 DescriptionofAlgorithmsofBasicProcesses . . . . . . 59
2.5 MathematicalModelsofBudgetRevenuePart . . . . . . . . . . 61
2.5.1 BasicProvisionsDescribingInteractionsofBudget
Items . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
2.5.2 LearningElementsofBudgetSystem . . . . . . . . . . . 62
2.5.3 ModelofCorrectionofBudgetRevenueForecast . . . . 65
2.6 ModelofInformationSystemforProgramBudgetControl. . . . 66
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
3 Energy-EntropicMethodsinAssessmentandControlofEconomic
Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
3.1 ArgumentsinFavorofApplicationoftheThermodynamic
ApproachtoEconomicSystems . . . . . . . . . . . . . . . . . . 73
3.2 Energy-EntropyModelforAssessmentofEconomicSystem
Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
3.3 Energy-EntropyApproachastheBasisofSystemEstimation
ofProductionManagementQuality . . . . . . . . . . . . . . . . 83
3.3.1 UnitedMeasuringSystemofEnergyResources . . . . . 83
3.3.2 MethodsUsedtoEstimatePowerConsumption
(EfficiencyofPowerResourcesUsage)attheEnterprise
Level . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
3.3.3 EntropicEvaluationofProductionEfficiency . . . . . . . 86
3.3.4 UsageofEnergy-SavingCriteriontoAssessProduction
ControlQuality . . . . . . . . . . . . . . . . . . . . . . 92
3.3.4.1 AThermodynamicApproachtoConstructing
SystemsControllingProductionProcesses . . . 92
3.3.4.2 ComparisonofProductionProcessesinTerms
ofEnergy-Entropy . . . . . . . . . . . . . . . . 95
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
4 CurrencyTradingMethodsandMathematicalModels . . . . . . . 99
4.1 CurrencyMarketResearchandManagement . . . . . . . . . . . 99
4.2 MathematicalModelsofEquilibriumExchangeRates . . . . . . 102
4.2.1 ModelDevelopmentandAnalysis. . . . . . . . . . . . . 102
Contents xi
4.2.2 EquilibriumExchangeRate:StatementoftheProblem
andWaystoSolveIt . . . . . . . . . . . . . . . . . . . . 104
4.2.3 OptimalAdjustmentofCurrencyExchangeRates . . . . 106
4.2.4 BuildingaBalancedDirectedGraph . . . . . . . . . . . 108
4.2.5 EquilibriumExchangeRates:Problem-Solving
Procedures . . . . . . . . . . . . . . . . . . . . . . . . . 111
4.2.5.1 StatementoftheAssignmentProblem . . . . . 111
4.2.5.2 AssignmentProblemasaLinearProgramming
Problem . . . . . . . . . . . . . . . . . . . . . 112
4.2.5.3 AssignmentProblemasaTransportation
Problem . . . . . . . . . . . . . . . . . . . . . 112
4.2.6 ExperimentalStudyoftheModelofEquilibrium . . . . . 115
4.3 MathematicalProjectionModelsforCurrencyTransactions . . . 119
4.3.1 ForecastProblemofRiskMinimization . . . . . . . . . . 119
4.3.2 ACollocationModelforForecastingOperations
ontheCurrencyMarket . . . . . . . . . . . . . . . . . . 121
4.3.2.1 BackgroundoftheCollocationModel . . . . . 121
4.3.2.2 DevelopmentofMathematicalModel
forForecastingExchangeRate . . . . . . . . . 122
4.4 InformationDecisionSupportSystemsinCurrencyOperations . 125
4.4.1 DevelopmentofInformationModelforDecisionSupport
SysteminCurrencyExchangeOperations . . . . . . . . 125
4.4.2 ISSoftware . . . . . . . . . . . . . . . . . . . . . . . . 127
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
5 MethodsandMathematicalModelsofInnovationProject
Appraisal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
5.1 CurrentStatusofInnovationProjectReviewandAppraisal . . . 131
5.1.1 InnovationProjectasaSubjectofAnalysisandAppraisal 131
5.1.2 ExistingMethodsandToolsofEvaluatingInnovation
Projects . . . . . . . . . . . . . . . . . . . . . . . . . . 132
5.2 DevelopmentofMethodsandModelsforAssessing
InnovativenessandCompetitivenessofInnovativeProjects. . . . 138
5.2.1 TheEssenceofInnovationandCompetitiveness . . . . . 138
5.2.2 InnovativenessCriteriaforInnovativeProjects . . . . . . 139
5.2.3 CompetitivenessCriteriaforInnovativeProjects . . . . . 140
5.2.4 MethodandGraphicModelforAssessingInnovativeness
andCompetitivenessofInnovativeProjects . . . . . . . . 145
5.3 DevelopmentofMethodsandModelsforAssessingFeasibility
andCost-EffectivenessofInnovativeProjects . . . . . . . . . . . 157
5.3.1 BasicStepsinDesigninganInnovativeProject . . . . . . 157
5.3.2 BasicLifeCyclesofInnovationProjects . . . . . . . . . 160
5.3.3 TheMethodandGraphicModelforAssessingFeasibility
andEconomicEffectsofInnovationProjects . . . . . . . 166
5.3.4 MethodandGraphicModelforInnovationProject
Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . 175
