Tarun Das ADB Nepal Macro Economic Model

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    Nepal Macroeconomic Model- Inception Report

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    INCEPTION R EPORT (F INAL ):NEPAL M ACROECONOMIC M ODEL (NMEM) AND

    DYNAMIC STOCHASTIC G ENERAL EQUILIBRIUM (DSGE) M ODEL -M ODEL STRUCTURES , D ATA BASE , AND SOFTWARE -H ARDWARE R EQUIREMENTS

    PART-I: MAIN REPORT

    DR . TARUN DAS 1,2 (F ORMERLY , E CONOMIC ADVISER , M INISTRY OF F INANCE , I NDIA )

    IN ASSOCIATION WITH P ROFESSOR DURGA L AL SHRESTHA 3

    DR . V IKASH R AJ SATYAL 4

    M R . R OJAN BAJRACHARYA 5

    12 O CTOBER 2009

    Executing Agency:The Nepal Rastra Bank,Baluwater, Kathmandu.

    For any clarifications, write to : [email protected]

    1 Macroeconomic Modeling Specialist/ Team Leader (International), Formerly Economic Adviser, Ministry

    of Finance, and Adviser (Modeling and Policy Planning), Planning Commission, India.2 Authors would like to express their sincere thanks to Mr. Shahid Parwez, ADB Project/ ProgramImplementation Officer and Dr. Nephil Matangi Maskay, Director (Research), Nepal Rastra Bank, andFocal Officer, Technical Committee on Modeling, for overall guidance, valuable discussions andcomments on an earlier draft. However, the Report expresses personal views of the authors and does notnecessarily imply the views of the ADB Nepal Resident Mission, NRB, MOF and the CBS, Nepal.

    3 Macroeconomic Modeling Specialist (National)4 Econometrician (National)5 Information Technology Specialist (National)

    1

    mailto:[email protected]://flagspot.net/images/n/np)2006.gifmailto:[email protected]
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    NEPAL G EOGRAPHIC M AP

    Location : 26 22' N to 30 27' North, 80 4'E to 88 12' East

    Political and Administrative StructureNepal ( ), officially known as the Federal Democratic Republic of Nepal , is alandlocked country in South Asia and the world's youngest republic. It is divided into fivedevelopment regions ( Eastern, Central, Western, Mid-Western and Far-Western ), and threeecological regions ( Mountain, Hill and Terai ). For administrative purpose, it is divided into 75districts (Zilla) and each district is divided into municipalities and Village DevelopmentCommittees that are further divided into wards.

    Basic Facts about Nepal:Fiscal year: 16 th July to 15 th July of the following year Items (Year) Units Value Rank in the World

    from topin descending order

    Area (2009) Sq. km. 147,181 98 out of 248 countriesPopulation (2008) Million 29.5 41 out of 241 countriesGDP PPP (2004) Billion US$ 29.3 103 out of 229 countriesGDP Nominal (2006) Billion US$ 8.1 122 out of 229 countriesGDP PPP per capita (2004) US$ 1,352 141 out of 163 countries

    GDP per capita (2006) US$ 291 195 out of 207 countriesPoverty Ratio (% of people belowOne-US$) (2000)

    Percent 37.7 14 out of 59 countries

    External debt (2006) Billion US $ 3.1 116 out of 196Debt service ratio (2006) Percentage 4.9 105 out of 128

    Source: http://www.nationmaster.com

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    http://en.wikipedia.org/wiki/Landlockedhttp://en.wikipedia.org/wiki/South_Asiahttp://en.wikipedia.org/wiki/Republichttp://www.nationmaster.com/http://en.wikipedia.org/wiki/Landlockedhttp://en.wikipedia.org/wiki/South_Asiahttp://en.wikipedia.org/wiki/Republichttp://www.nationmaster.com/
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    Table of Contents

    Table of Contents Pages

    Contents 3-4

    Acronyms and Abbreviations 5Project Team 6Acknowledgements 7

    Nepal at a Glance by the World Bank 8-91. I NTRODUCTION - B ACKGROUND AND O UTLINE

    1.1 Background of the project1.2 Implementation and Institutional Arrangements1.3 An Outline of the Report

    10-12101111

    2. D EVELOPMENT C HALLENGES AND ISSUES 2.1 S TRENGTHS , WEAKNESS , OPPORTUNITIES , THREATS

    13-1414

    3. A NALYTICAL F RAMEWORK OF A G ENERAL M ACROECONOMIC M ODEL FOR NEPAL

    3.1 B ASIC OBJECTIVES3.2 M ODEL STRUCTURE AND A NALYTICAL FRAMEWORK 3.3 S PECIFICATION OF THE MODEL AND THE WORK PLAN3.4 D ATA BASE

    15-19

    15161919

    4. W ORK P LAN M ILESTONES AND DESCRIPTIONS OF W ORKS4.1 W ORK PLAN MILESTONES4.2 B RIEF DESCRIPTION OF WORKS

    4.2.1 UPDATING ADB MACROECOMIC MODEL4.2.2 BUILDNG UP DSGE MODEL 4.2.3 CAPACITY BUILDING AND TRANING4.2.4 H ELP IT GROUP FOR SOFTWARE /HARDWARE SELECTION4.2.5 P REPARING MANUALS A ND ORGANIZING WORKSHOPS 4.2.6 P REPARATION OF THE INCEPTION R EPORT4.2.7 P REPARATION OF QUARTERLY PROGRESS R EPORTS

    4.2.8 P REPARATION OF TERMINAL R EPORT

    20-232021

    2121212223232323

    5. R EVIEW AND UPGRADING THE NEPAL M ACROECONOMIC M ODEL DEVELOPED BY ADB IN 2005

    24-40

    6. D EVELOPMENT OF AN O PERATIONAL DYNAMIC STOCHASTIC G ENERAL E QUILIBRIUM M ODEL (DSGE) FOR NEPAL

    41-48

    7. R ECOMMENDATION FOR C HOICE OF H ARDWARE AND SOFTWARE R EQUIREMENTS TO R UN THE M ODELS

    49-54

    REFERENCES 55-59

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    P ART -II: A NNEXES 1-55

    TABLE OF CONTENTS 3

    A NNEX -1: E CONOMIC CONTEXT OF MODELING 4-13

    ANNEX -2: B UILDING UP OF A N OPERATIONAL MACROECONOMIC MODEL FOR NEPAL

    14-17

    A NNEX -3: S COPE , CHARACTERISTICS AND TYPES OF MACROECONOMIC MODELS

    18-32

    ANNEX -4: D ATA BASE REQUIRED FOR TEST AND CALIBRATIONS OF THE NMEM AND DSGE-TYPE MODELS FOR NEPAL

    33-37

    ANNEX -5: TERMS OF REFERENCE OF THE CONSULTANTS 38-39

    A NNEX -6: BRIEF CV OF THE CONSULTANTS

    40-43

    A NNEX -7: W ORK PLAN MATRIX OF CONSULTANTS

    44-48

    A NNEX -8A: B ROAD FEATURES OF E-V IEWS 6 SOFTWARE 49-52

    A NNEX -8B: EV IEWS COMMERCIAL AND GOVERNMENT VOLUME LICENSING CONDITIONS AND PRICES

    53-54

    A NNEX -9: L IST OF OFFICERS CONSULTED 55

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    Acronyms and Abbreviations

    ANA: Annual National AccountsCBS: Central Bureau of StatisticsCNSP: Consolidated National Statistical PlanDSGE: Dynamic Stochastic General EquilibriumEA: Executing AgencyEDPs : External Development PartnersEFA : Education for AllEU : European UnionFAO : Food and Agriculture OrganizationFDI : Foreign Direct InvestmentFTA : Free Trade AreaFY : Fiscal Year GDI : Gender Development IndexGDP : Gross Domestic ProductGNP : Gross National ProductHDI : Human Development IndexHDR: Human Development Report/ UNDPHHs : House HoldsHIPC : Heavily Indebted Poor CountriesHIV : Human Immuno-deficiency VirusHRD : Human Resource DevelopmentILO : International Labor OrganizationIMF : International Monetary FundLDCs : Least Developed CountriesMDGs : Millennium Development GoalsMOF : Ministry of Finance/NepalMTEF : Medium Term Expenditure Framework

    NGOs : Non-Governmental Organizations NMEM : Nepal Macro Economic Model NPC : National Planning Commission/Nepal NRB : Nepal Rastra Bank ODA : Official Development AssistancePPP : Purchasing Power ParityPRGF : Poverty Reduction and Growth Facility/IMFPRSP : Poverty Reduction Strategy Paper Rs. : Rupees/NepaleseTA technical assistanceUK : United KingdomUN : United NationsUNDP : United Nation's Development ProgramWB : World Bank WDR : World Development Report/WBWFP : World Food ProgramWHO : World Health OrganizationWTO : World Trade Organization

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    ADB Project on Macroeconomic Modeling for Nepal

    Project Team and Supervisors

    Program/ Project Implementation Officer Mr. Shahid Parwez,

    ADB Nepal Residence Office

    Executive Agency Nepal Rastra Bank

    Overall Guidance andStrategic Direction

    Steering Committee, chaired by therelevant NPC Member and comprisingrepresentatives of MOF, NRB, and other relevant line ministries and departments.

    Technical Advice and Supervision Technical Committee, chaired byMr. Ravindra Prasad Pandey, the

    Executive Director of the ResearchDepartment of NRB, and comprisingrepresentatives of MOF, NPC, and other relevant agencies.

    Focal Officer responsible for day-to-daysupervision, coordination and overseeingthe implementation of the TA activities

    Dr. Nephil Matangi MaskayDirector (Research)

    Project Facilitators Dr. Bama Dev SigdelDeputy Director (Research)

    Dr. Ram Sharan KharelAssistant Director (Research)

    Consultants Prof. Tarun Das, Ph.D., Team Leader andMacroeconomic Modeling Specialist.

    Prof. Durga Lal Shrestha, Ph.D.,Macroeconomic Modeling Specialist,

    Dr. Vikas Raj Satyal, Econometrician

    Mr. Rojan Bajracharya, IT Specialist

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    Acknowledgements

    This Inception Report summarizes the basic objectives and scope of the project and themajor duties, responsibilities, Terms of Reference (TOR) and detailed work plan of theConsultants viz. the International Macroeconomic Modeling Specialist Dr. Tarun Das,

    National Macroeconomic Modeling Specialist Dr. Durga Lal Shrestha, NationalEconometrician Dr. Vikash Raj Satyal and National Information Technology (IT)Specialist Mr. Rojan Bajracharya.

    The Report has been produced on the basis of consultations and discussions with the principal stakeholders and the information and advice provided by them. I express mysincere gratitude to everyone (a List of officers met is given in Annex-9 in Part-II) whohas given their valuable time for discussions.

    First of all, I am grateful to Mr. Shahid Parwez, Program/ Project ImplementationOfficer, ADB Nepal Resident Mission for providing all possible support, guidance,

    briefing and encouragements at every stage of my works and even before my joining theProject at Kathmandu. I would like to thank Mr. Trilochan Pangeni, the then Executive Director, ResearchDepartment for proving valuable backgrounds of the modeling works at the NRB. Iwould also like to thank Mr. Ravindra Prasad Pandey, the present Executive Director,Research Department and the Chairman of the Technical Committee for setting themotion for modeling works under the project.

    I would like to express my sincere gratitude and thanks to Dr. Nephil Matangi Maskay,Director (Research), Nepal Rastra Bank and Focal Officer, Technical Committee onModeling, for overall guidance and valuable discussions and comments on an earlier draft. I would like to express my thanks to Facilitators Dr. Bama Dev Sigdel, DeputyDirector and Dr. Ram Sharan Kharel, Assistant Director, Research Department, NRB, for their enthusiastic cooperation, keen interest, useful discussions and providing relevantdata and documents.

    Finally, I would like to thank my colleagues- the national consultants Prof. Durga LalShrestha, Macroeconomic Modeling Specialist; Dr. Vikash Raj Satyal, Econometricianand Mr. Rojan Bajracharya, Information Technology (IT) Specialist for providing vitalinputs for preparation of this report.

    It is needless to mention that the report expresses my personal views and I am solelyresponsible for any errors and omissions.

    Kathmandu. Nepal Tarun Das12 th October 2009. Team Leader

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    Source: Nepal at a Glance, by the World Bank, dated the 24 th Sept 2008.

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    INCEPTION R EPORT (F INAL ):NEPAL M ACROECONOMIC M ODEL (NMEM) AND

    DYNAMIC STOCHASTIC G ENERAL EQUILIBRIUM (DSGE) M ODEL -

    M ODEL STRUCTURES , D ATA BASE , AND SOFTWARE -H ARDWARE R EQUIREMENTS

    DR . TARUN DAS

    IN ASSOCIATION WITH

    P ROFESSOR DURGA L AL SHRESTHADR . V IKASH R AJ SATYAL

    M R . R OJAN BAJRACHARYA

    1. Introduction- Scope, Background and Outline

    Would you tell me please, which way I ought to go from here? asked Alice.That depends a great deal on where you want to get to. said the cat.I dont much care where . said Alice.Then it does not matter which way you go. said the cat.

    --- Extract from Alice in Wonderland, Lewis B. Carrol

    Eventually Alice in Wonderland realized that it does matter a great deal to know whereto go and how to get there . Similarly, in budgeting, planning and monetary programming, it is important to know the vision, mission and basic goals of an agency;the scope of its activities in terms of exact inputs, outputs and outcomes in the mediumterm, and how to achieve these activities with least resources. Modeling and projectionshelp to have a clear vision by the planners and facilitate preparation of sound strategic

    business and financial plans by a budgetary or monetary agency.

    1.1 Background of the Project

    The present project is a part of a wider project called Nepal: Strengthening Capacityfor Macroeconomic Analysis - TA-7165 (NEP), which is being funded by the AsianDevelopment Bank (ADB). The TA will enhance the Governments capacity for economic policy formulation based on reliable macroeconomic data and sound policyanalysis. The TA has two distinct parts viz. (a) to further improve the national statisticalsystem and (b) to develop and use macroeconomic models for policy simulations,forecasting and economic planning. While component-A of the TA deals with part (a)and is being executed by the Central Bureau of Statistics (CBS), Component-B deals with

    part (b) and is being executed by the Nepal Rastra Bank (NRB).

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    This Inception Report deals with Component-B of the Project i.e. to build upmacroeconomic models for Nepal which can provide vital inputs for planning,

    preparation of the budget and formulation of monetary policy. Desirable characteristicsand scope of an ideal macroeconomic model, factors affecting its formulation, test and

    calibration; types of various macroeconomic models and their relative merits anddemerits are discussed in details in Annex-3 .

    Modeling Team comprises Prof. Tarun Das, Macroeconomic Modeling Specialist/ TeamLeader; Prof Durga Lal Shrestha, Macroeconomic Modeling Specialist; Dr. Vikas LalSatyal, Econometrician and Mr. Rojan Bajracharya, IT Specialist. The basic task of theModeling Group is to review and upgrade the Nepal Macroeconomic Model (NMEM)

    built by ADB in 2005 and to build an alternative Model in the framework of a DynamicStochastic General Equilibrium (DSGE) Model. The respective Terms of References(TOR) of the consultants are reproduced in Annex-5, the respective brief CVs of theconsultants are given in Annex-6.1 to Annes-6.4 and the respective Work Plan Matrices

    are given in Annex-7.1 to Annes-7.4.1.2 Implementation and Institutional Arrangements

    CBS is the Executing Agency (EA) for component A of the TA and NRB for componentB. Both components of the TA are being implemented under the overall direction of aSteering Committee chaired by the relevant NPC Member and comprising representativesof MOF, NRB, CBS, and other relevant line ministries. In addition, two TechnicalCommittees (TCs) have been formed to provide technical advice and guidance on therespective TA activities. The TC for component-B on Modeling is chaired by Mr.Ravindra Prasad Pandey, Executive Director (Research), NRB and compriserepresentatives of MOF, NPC, and other agencies. Dr. Nephil Matangi Maskay, Director (Research Department), Nepal Rastra Bank, is the Focal Officer with the responsibilityfor overall supervision and coordination.

    1.3 An Outline of the Report

    With this brief introduction on modeling and project background, the rest of the reporthas 6 additional sections and 9 Annexes.

    Section-2 discusses briefly the development challenges, problems and prospects of Nepal,and its inherent strengths, weakness, opportunities and threats (SWOT).

    Section-3 describes an analytical framework of an operational general macroeconomicmodel for Nepal.

    Section-4 deals with specific work plans and brief descriptions of the activities of theconsultants during the project period.

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    Section-5 makes a critical review of the Nepal Macroeconomic Model (NMEM)developed by the ADB in 2005 and provides the upgraded structure of the NMEM, whichwill be calibrated and tested by the consultants.

    Section-6 provides a tentative structure for an operational Dynamic Stochastic General

    Equilibrium (DSGE) Model for Nepal, which will be fully developed, tested andcalibrated by the consultants with available data and computer algorithms.

    Section-7 recommends hardware and software requirements for estimation, test,calibration, projection and simulations of the models.

    The report is then followed by selected references and nine Annexes. Annex-1 deals with both global and domestic economic context of modeling, and makes a critical appraisal of the current state of the Nepalese economy.

    Annex-2 describes alternative macroeconomic models and building blocks for an

    operational macroeconomic model for Nepal. Annex-3 makes a critical review of basic characteristics, types and technical structures of various macroeconomic models.

    Annex-4 provides the complete list of variables and data requirements for thespecification, test and calibration of the upgraded Macroeconomic Model and theDynamic Stochastic General Equilibrium type of model for Nepal.

    Annex-5 reproduces the respective Terms of Reference (TOR) of the consultants asspecified under the ADB Project (TA-7165-NEP) on Nepal: Strengthening Capacity for Macroeconomic Analysis.

    Annex-6 provides brief curriculum vitae of the consultants, while Annex-7 provides therespective Work Plan Matrices of the Consultants.

    Annex-8 has two parts and presents the broad features (Annex-8A) and licensingconditions for commercial and government volume contracts (Annex-8B) for the E-Views6 Software which is recommended by the modeling team for estimation, test, calibration,forecasting and simulation the Nepal macroeconomic models.

    Annex-9 provides a list of officers who were consulted to prepare this report.

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    2. Development Challenges and Issues

    During the last five years the Nepalese economy had performed reasonably well withmoderate and stable economic growth, increasing per capita income, buoyant investment,moderate inflation, low fiscal deficit and favorable balance of payments situation. But,

    these favorable trends have not led to commensurate reduction of poverty in rural andhilly areas. This implies that the so-called trickle down effects of growth had beendelayed, slow and uneven. The domestic political transition might have further exacerbated the economic conditions in Nepal.

    These trends have led to various development challenges such as how to sustaineconomic growth with fiscal prudence, monetary discipline and price stability, how to

    promote equitable growth and to raise the levels of living of all citizens, how to eradicate poverty, hunger and disease and to attain other Millennium Development Goals (MDGs)at a faster speed, and how to create enabling environment for public-private partnershipand international cooperation in the development process for improving quality and

    delivery of basic public goods and services.The core challenge for the government budget is how to adopt long-term MDG targetswithin the annual and medium-term national budget constraints and priorities. MDGstrategies are both needs based and resource constrained . The national budget musttake care of poverty reduction strategies as a guide to MDG action, and set out clear

    priorities for pro-poor public expenditure and investment plans based on a realisticassessment of the available resources and the needs of other sectors.

    The countrys economic growth has remained low and needs to be reinvigorated byincreasing agriculture production and productivity and improving environment for privateinvestments including foreign investment. There is also need to improve institutional setup and governance, liberalize labor laws, and improve investment climate and physicalinfrastructure. Nepals road density is one of the lowest even among the least developedcountries. Similarly the country suffers from severe electricity shortage.

    Population pressure on natural resources is increasing. Over-population is alreadystraining the "carrying capacity" of the middle hill areas, particularly the KathmanduValley, resulting in the depletion of forest cover for crops, fuel, and fodder andcontributing to erosion and flooding and other environmental hazards.

    The challenge is not only of accelerating growth, but also of sharing the growth and prosperity more broadly across the population. Building social and human capital,creating employment opportunities and implementing affirmative actions to the excludedgroups are probably the best ways for reducing poverty and inequality in the country. If all Nepalese people are healthy, educated, skilled and live longer, they can participatefully, contribute more and gain from the development process..

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    2.1 SWOT Analysis for the Nepalese Economy

    On the basis of above discussion, a SWOT analysis of the Nepalese economy is presentedin the following table.

    Table-2.1 SWOT Analysis of the Nepalese Macro-economy

    I n t e r n a l e n v

    i r o n m e n

    t

    Strengths

    1. Sustainable moderate economic growth in recent years2. Good performance by services sectors.3. Rising trend of tax/ GDP ratio;4. Manageable fiscal deficit, with surplus in overall fiscal balance

    in 2008/09.5. Rising trend of gross domestic investment ratio6. Rising trend of national savings ratio7. Good performance of major social development indicators

    including reduction of poverty8. Country is on track on most of the MDG targets

    Weaknesses

    1. Growth rate remains vulnerable to weather shocks;2. Low productivity of agriculture;3. Industrial sector remains week due to political uncertainty,

    labor unrest, and constraints on electricity supply and other infrastructure facilities;

    4. Inflation pressures in 20095. Low levels of domestic savings6. Large proportion of current expenditure and low levels of

    investment in public expenditure7. Although overall poverty ratio is declining, poverty incidence

    remains high in rural and hilly areas8. Degradation of environment in cities

    E x t e r n a l e n v i r o n m e n

    t

    Opportunities 1. Located between two giant economies and fast growingneighbors (China and India) with positive pulls and pushes onthe Nepalese economy

    2. Surplus in the external current account during 2004-2009except for marginal deficit in 2007

    3. Comfortable foreign exchange reserves (equivalent to 7.5months of imports during 2006-2009)

    4. Declining ratios of external debt to GDP ratio5. Very low external debt service ratios indicating sustainability

    of external debt over time (and possibility of no debt trap)Threats Overall economic growth and government revenue remain

    vulnerable to terms of trade shocks triggered by possible sharp

    declines in international prices of Nepalese exportsBalance of payments remains vulnerable to future risk of hardening of global oil prices

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    3. Analytical Framework of a General Macroeconomic Model for Nepal3.1 Basic Objectives

    The basic purpose is to build an appropriate and stable model, depicting the underlyingstructure of the Nepalese economy, which can be used to forecast major macro economic

    variables for both the short-term (one year) and medium term (five years) for preparationof budget and national plan and formulation of monetary and fiscal policies. The projections will also form the basis for preparing the macroeconomic and fiscal envelope by the Nepal Rastra Bank to be provided to the Ministry of Finance for pre-budgetconsultations and requirements.

    Here we present a general framework for a macroeconomic model, which is consistentwith the concepts under the UN System of National Accounts (UN-SNA), and the IMFGovernment Finance Statistics (GFS), Balance of Payments (BOP) Statistics and theMonetary-Financial Statistics (MFS). This model produces the baseline scenario of themacro economy disaggregated into the five inter-related accounts as indicated below:

    (i) Real Sector and National Accounts(ii) Government Sector (Fiscal Account)(iii) Monetary and Financial Sectors(iv)External Sector (v) Prices, Interest Rates and Exchange Rate and

    3.2 Model Structure and Analytical Framework

    The basic structures of these sub-models and their interrelations are depicted in the formof a flow diagram in Box-3.1. The linkages between key aggregates of the nationalaccounts and the balance of payments flows can, by the use of symbols, be summarizedalgebraically within a savings/investment framework.

    National Accounts System (NAS)GDPFC = Real GDP at constant FC

    = GDPAG + GDPIND + GDPSER GDPAG = Agricultural GDPFCGDPIND = Industrial GDPFCGDPSER = Services GDPFCC = private consumption expenditureG = government consumption expenditureI = gross domestic investmentS = gross savingX = exports of goods and (non-factor) servicesM = imports of goods and (non-factor) servicesNFY = net factor income from abroadGDP = gross domestic productGNP = gross national productGNDY = gross national disposable income

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    Balance of Payments (BOP)

    CAB = current account balance in the balance of paymentsNCT = net current transfersNKT = net capital transfers

    NPNNA = net purchases of non-produced, non-financial assetsNFI = net foreign investment or net lending/ net borrowing vis--vis the rest of the worldNKA = net capital and financial account (i.e., all capital and financial transactionsexcluding reserve assets )RT = reserve asset transactions

    Government Finance Statistics (GFS)

    R = Revenue = T + NTT = Tax revenueNT = Nontax revenue

    GR = GrantsGEXP = Government expenditure and net lending = G + GK G = government consumption expenditureGK = GCE + NDGCE = Government capital expenditureND = Net lendingGFD = Gross Fiscal Deficit

    = (R+GR) - GEXP

    Monetary-Financial Statistics (MFS)

    MD = Demand for money = NFA+CRG + CRP + OIMS = Supply of money = DD + TD + CNCRG = Credits to the government and public enterprisesCRP = Credits to the private sector NFA = Net foreign assetsOI = Other itemsDD = Demand depositsTD = Time depositsCN = Currency and notes in circulation

    Prices, Interest Rates and Exchange RatesCPI = Consumer Price IndexWPI = Wholesale Price IndexGDPDF = GDP Deflator INT = Rate of interestPLR = Prime lending rateFDR = Fixed deposit rateER = Exchange rate of Nepalese Rupee

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    Box-3.1: Basic Structures of Macroeconomic Sub-models and Inter-linkages

    NMEMs

    17

    National AccountsReal Sector (Supply Side)GDP = GDPi

    Where GDPi = GDP of i-th sector

    Demand/ Expenditure Side Private consumption Gen. govt. consumption Gen. govt. investment

    Private investment Exports of goods and

    non-factor services Imports of goods and

    non-factor services

    CENTRAL GOVERNMENT Revenues

    Taxes and non-taxes Grants

    Expenditures Current Capital

    Overall balanceFinancing

    Domestic financing (net) Banking system Nonbanking sector

    Balance of PaymentsCURRENT ACCOUNT Exports of goods and

    non-factor services Imports of goods and

    non-factor services Factor services (net) Transfers (net)

    Official Private grants Remittances

    MONETARY SECTOR Monetary Authorities Net Foreign Assets

    Net domestic assets: Net credit to central govt. Credit to banks Other items (net)

    Reserve money

    CAPITAL ACCOUNT Direct investment

    Medium/ long-termcapital flow (net)

    Short-term capital (net)Overall balance

    Change in net foreign assets

    Deposit Money Banks Banks' reserves

    Net Foreign AssetsNet domestic assets: Net credit to govt. Credit to private sector Other items (net)

    Liabilities to monetaryauthorities

    Private sector deposits

    CPI Inflation, GDP Deflator,Interest Rates and Exchange Rate

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    The Macroeconomic Balance Equations stand as follow:GDP = C + G + I + X M (1)( X M = balance on goods and services in the balance of payments)GNP = GDP + NFY (2)CAB = X M + NFY+NCT (3)

    GNDY = C + G + I + CAB (4)GNDY = C + G + S (5)

    Equating (4) and (5) we get:S I = CAB i.e. saving-investment gap (resource gap) equals CAB (6)S I + (NKT NPNNA) = CAB + ( NKT NPNNA) = NFI (7)( NKT NPNNA) = balance on the capital account of the balance of payments.

    Interrelationship between the internal and external sectors of an economy can be seen ingreater detail by distinguishing between the private and government sectors. Privatesaving and investment ( Sp and Ip ) and government saving and investment ( Sg and Ig )

    are identified as:SI = Sp+SgIpIg (8)

    Use of the definition of the external current account from equation (1) then gives:CAB = (SpIp) + (SgIg) = SI (9)

    Equation (9) shows that the private savings-investment balance plus the governmentfiscal balance equals the current account balance. It also implies that, if governmentsector dissaving is not offset by net saving of the private sector, the current account will

    be in deficit. More specifically, the equation shows that the budgetary position of thegovernment ( Sg-Ig ) may be an important factor influencing the current account balance.

    Government deficit is financed by borrowing from the domestic sector, borrowing fromthe external sector and borrowing from the central bank. All these factors have influenceson the domestic capital and financial markets and also on the balance of payments.

    Economists generally agree that a persistent fiscal deficit may ultimately spill over thecurrent account deficit in the balance of payments. On the converse, a sustained currentaccount deficit may reflect persistent government spending in excess of receipts, andsuch excess spending may suggest that fiscal tightening is the appropriate policy action totackle both fiscal and balance of payments problems.

    We also know thatCAB = NKA+RT = SI (10)Equation (10) shows that the current account balance is necessarily equal (with signreversed) to the net capital and financial account balance plus reserve asset transactions.This relationship shows that the net provision, as measured by the current account

    balance, of resources to or from the rest of the world mustby definitionbe matched by a change in net claims on the rest of the world.

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    It may be useful to rewrite CAB as:SI = CAB = TB+SB+FIB+TRANB = NKA+RT , where (11TB = Merchandise trade balance = Merchandise Exports Merchandise ImportsSB = Non-factor service balance (travel, tourism, financial, business, ICT etc.)FIB = Factor income balance (interest, dividends, wages, rent, royalties etc.)

    TRANB = current transfer balance ( official grants, private grants, remittances )For Nepal, in general, TB and SB are negative, while FIB and TRANB are positive.

    3.3 Specification of the Model

    While keeping these basic identities and macroeconomic balance equations intact,various variables in the model will be categorized either as exogenous variables or endogenous variables. While exogenous variables will be determined outside the model,suitable econometric relations will be specified for the endogenous variables on the basisof standard economic theories. Items in different sub-models will be estimated andcalibrated by econometric techniques and tested on the basis of standard goodness of fit

    statistics. In this Inception Report, Model Structures of an Operational Nepal Macroeconomic Model and an Operational Dynamic Stochastic General EquilibriumModels are presented.

    It may please be kept in view that the Inception Report is only the beginning of modeling works and not the end product on modeling. But, we are confident thatthe proposed models are in the right directions as judged by availability of basicinputs. The models will be fully developed and documented in the subsequentreports. In addition to these Models, as desired by various Departments of NRB, a

    Short Term Forecasting Model will be developed to estimate and forecast majorvariables for the current and next budget year on the basis of past five years

    fortnightly/ monthly/ quarterly data available for the concerned variables .

    3.4 Data Base

    Sample period for NMEM update and DSGE Model will be from FY1984/85 toFY2006/07 since the data for 2007/8 is not final. There will be thus 23 years of timeseries data. Modeling exercise based on the actual data is more realistic and reliable thanthat on estimated data, and large number of observations in a time series will be better for obtaining more robust and reliable estimates. We are aware that the complete seriesare not available for all the variables. In those cases, instead of fitting econometricrelations, suitable time series analysis or elasticity approach will be adopted.

    The major sources of the data are the Government of Nepal, MOF, NRB and CBS. Thedata for final demand, prices, Balance of payment, government budget, and money can beobtained from the Economic Survey and budget speech of MOF, Quarterly EconomicBulletin of NRB, and Statistical year books of CBS. But due care will be taken in usingsome data because of the fiscal year of the Government of Nepal which starts from the16 th July of a year and ends on the 15 th July of next year. The unique dating conventionmakes it necessary to adjust external variables to maintain data coherence.

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    4. Work Plan Milestones and Brief Description of Works

    4.1 Work Plan Milestones

    The proposed Work Plan Matrices of the Consultants are presented in Annex-7.1 to

    Annex-7.4. Major Work Plan Milestones are summarized below:Work Plan Milestones:

    1. Preparation of the First Draft of the Inception Report by 10 September 20092. Review the NMEM and identify deficiencies and their causes by 15 September 20093. Conduct research, identify data base and upgrade the NMEM by 22 September 20094. Develop an operational DSGE Model for Nepal by 08 October 2009 .5. Prepare a Report on the choice of software and hardware by 08 October 20096. Preparation of the Second Draft of the Inception Report by 08 October 2009 .7. Submission of the Final Inception Report incorporating all works until date- by the

    16 October 20098. Installation of Software/ hardware Testing by 31 st January 20109. Test, calibrate and simulate the upgraded NMEM by 15 March 201010. Undertake research and finalize a DSGE-type model for Nepal by 31 March 201011. Test, calibrate and simulate the DSGE-type model by 30 April 2010.12. Conduct multi-stakeholders seminars/ workshops on the features of the two models by

    15 May 201013. Develop and calibrate short-term forecasting model for major variables of interest to

    NRB by the 31 May 201014. Preparation of macroeconomic and fiscal envelope for the Ministry of Finance to provide

    pre-budget inputs to MOF for preparation of the 2010-2011 Budget by 31 May 201015. Develop a user manual, including calibration methodology, to undertake quantitative

    macroeconomic analysis using the DSGE model by 31 May 201016. Conduct seminars/ workshops on the features of the two models by 30 Sep 201017. Provide on-the-job training to three staff from each of the agencies NRB, CBS, NPC,

    MOF and the Department of Economics, Tribhuvan University, and other relevantagencies (staff will be selected in close coordination with the executing agency, SteeringCommittee, and the Technical Committee) by 30 Sep 2010.

    18. Prepare Terminal Report by 4 October 2010.

    Proposed Phases Period Number of workingdays (Total Days)

    Total Working daysand (Total Days of

    Stay at Kathmandu)First Phase 23 Aug 2009 to

    16 Oct 200933 (48) 33 (48)

    Leave of Absence 17 Oct 2009 to15 Feb 2010

    0 (121) 33 (48))

    Second Phase 16 Feb 2010 to31 May 2010

    75(105) 108 (153)

    Leave of Absence 1 June 2010 to31 Aug 2010

    0 (67) 108 (153)

    Third Phase 1 Sept 2010 to 24 (33) 132 (186)

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    04 Oct 2010

    4.2. Brief Descriptions of Works

    4.2.1 Updating the Nepal Macroeconomic Model developed by ADB

    In 2005 ADB ( Ra, Sungsup and Chang Young Rhee 2005) developed the NepalMacro-economic Model (NMEM) and simulated the model to carry out alternativescenario analysis. The model was also calibrated to measure the economic costs of conflict in terms of the effect of declining development expenditures on economic growth( Ra, Sungsup and Bipul Singh 2005) .

    The NMEM will be reviewed critically and an upgraded model structure will be built upin the next section. While doing so, due consideration will be given to the availabilitydata base, statistical test and calibration techniques, computer algorithms, and availablehardware and software capabilities, and technical manpower in the NRB, MOF and other

    budgetary agencies which are likely to use the updated NMEM for budgeting, planningand monetary and financial programming.

    4.2.2 Building up of a Dynamic Stochastic General Equilibrium Model

    The model has been described fully with its relative merits and demerits in terms of objectives, data requirements and test and calibration techniques in section 3.13 in theAnnex-3. As the name indicates, DSGE models are dynamic, studying how the economyevolves over time. They are also stochastic, taking into account the fact that the economyis affected by random shocks such as technological change, fluctuations in the price of oil, or errors in macroeconomic policy-making.

    International best practices like the ECB Model and the USA Model will be studied andsuitable model will be formulated and estimated for forecasting and planning by the

    NRB, NPC and the Ministry of Finance.

    4.2.3 Capacity Building and Training

    The consultants shall work in close collaboration with the concerned authorities in thegovernment department viz. MOF, CBS, NPC and the National Rasta Bank with a viewto transferring knowledge and equipping the staff with the skill required to manage andmaintain the models in future. Consultants will demonstrate the use of the models bysimulating actual policy questions raised by the authorities.

    After the Models have been fully developed, macroeconomic modeling experts shallcarry out a series of simulations to check for consistency, predictability and reliability of

    both the models, and shall validate both the models at multi-stakeholders workshop.Macroeconomic modeling experts will also advise the authorities on the most appropriatehardware and user-friendly software package for the purpose of maintaining the models.

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    4.2.4 Support the IT Group for Software and Hardware Selection

    In consultation with the Team Leader, local econometrician and the local IT Specialist

    jointly made a Rapid Survey on the current status of ICT capabilities in the MOF, CBS, NPC and NRA. As per their assessment, all the four agencies have rich database, welldeveloped website, and reasonable hardware and software capabilities. However, licensesof major software have expired and the software is outdated and need upgrading.Agencies do not have uniform operating systems and software capabilities. The mainobservations of the Consultants drawn from the Rapid Survey are summarized below:

    a) Data Bank and Warehouse: All four agencies regularly update their database andmaintain soft version of data in various software depending on the size and nature of thedatabase. CBS maintains database mostly in MS-Excel, Oracle, STATA and SPSS; NRBin MS-Excel and SPSS; MoF in Oracle and MS-Excel; and NPC in SPSS, Oracle and

    MS-Excel. For time-series data on major Macro variables, all four agencies use MS-Excel and share their data via emails. However, time interval and frequency of data publication varies from agency to agency depending on the nature of data. There is nouniformity in the storage and software format among the agencies.

    b) Capacity for Data Analysis: Capacities of agencies differ in terms of data analysisskill. CBS is very competent in statistical analysis but lags in macro-econometricforecasting. NRB is equipped with both statistical techniques and limited macro-econometric modeling skills. NRB staffs are technically competent and use econometricmethods in course of their researches, but such activities are not systematically followeddue to pressures from routine works. NPC has limited capacity on statistical analysis buthas experience of modeling exercises that were discontinued due to work pressures andlimited designated staffs. MOF is less competent in statistical analysis and econometricmodeling skills as compared to other agencies.

    c) Capacity for Data Retrieval: Capacities of the four agencies differ in terms of dataretrieval. While four agencies have capacity to retrieve data from MS-Excel, CBS, NRBand NPC are partially equipped to retrieve data from SPSS and Eviews. They also havesome knowledge on how to transfer the database from one software to another software.

    d) Data Availability in Web: All four agencies have their own websites, which areupdated on regular basis to upload new data. The data are generally uploaded either inMS-Excel format or in Adobe Reader files.

    e) Hardware Capacity : All four agencies do have sufficient computers of good qualitythat are sufficient to run software programs like EXCEL, SPSS, STATA and Eview andto use the facility of internet/ emails.

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    f) Availability of Software: The status of the four agencies is mixed in terms of availability of software as indicated below. It is observed that most of the softwareversions are outdated and in many cases the licenses have expired.

    Agencies Available Software

    CBS STATA, SPSS and MS- Excel NRB Eviews 3.1, SPSS and MS- Excel NPC Eviews, SPSS and MS- ExcelMOF MS- Excel and Eviews 4.1

    g) Human Resource: CBS staffs have very good statistical skill but very few of themhave the experience of modeling. NRB staffs, in general, possess very good statistical andmodeling skill. NPC has very limited human resource but the available few are verycompetent in statistical and modeling shill. MOF has a very small pool of humanresource having sufficient statistical and modeling skills.

    4.2.5 Preparation of Manuals and Organizing Workshops

    As discussed earlier, substantial time will be spent to prepare manuals and fulldocumentation on basic concepts, structure of the models, data base, computer algorithms, test and calibration techniques. portion, so that any other group can test,calibrate and run the model, even after the present modelers and consultants have left themodeling project. Once the Models are fully developed and calibrated, results will be

    presented in the multi- stakeholders Workshops.

    4.2.6 Preparation of the Inception Report

    This is the Final Inception Report being submitted by the International ModelingSpecialist in consultation with the major stakeholders and vital inputs from the localconsultant. The First Draft of the Inception Report was submitted on the 10 th September,2009, well before the stipulated time of one month as envisaged under the Terms of Reference. List of officers consulted for preparation of this report is giver in Annex-8.

    4.2.7 Preparation of the Quarterly Progress Report

    The modeling works with all its components are required to be completed in six personmonths (132 working days) on intermittent basis in four phases during 15 months fromAugust 2009 to October 2010. The Work Plan Matrices of the Consultants presented inAnnerx-6.1 to Annex-6.4 clearly indicate the distinct four phases of the work which will

    be completed within stipulated time. The Progress Report will be submitted after completion of each phase of works.

    4.2.8 Preparation of the Terminal Report

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    At the end of the Project, a Terminal Report will be prepared indicating the overall scopeand achievements of the project, constraints faced, lessons learnt, issues and challengesfor way forward, and suggested roll out plan so that the project comes to a logical end.

    5. Review and Upgrading the Nepal Macroeconomic Model5.1 A brief review of the past economic modeling exercises in Nepal

    Since 1980s, individual researchers had attempted to use statistical techniques andeconometric models for economic analysis and forecasting in Nepal.

    1) In 1985, a multi-sector, economy-wide model was first introduced by Khanal,Thapa and Elbers (1987) 6.

    2) In 1987, the Water and Energy Commission developed a macro model for forecasting energy demand.

    3) In 1989, a macro-economic model in the Leontief input-output framework comprising 39 sectors was also developed to prepare long-term industrial plansand to formulate alternative development strategies for the economy 7. The basicobjective of the model was to determine the optimum volume of investment under an acceptable rate of inflation, acceptable fiscal deficit, realistic level of foreignassistance, and a stipulated growth rate for per capita consumption.

    4) A similar version of the macroeconomic model was also used in the formulationof the Eighth Plan.

    5) In 1992 another macro model was developed as a part of the link model for theSouth Asian Association for Regional Cooperation (SAARC) countries 8 toexamine the impact of regional trade on its member economies.

    6) A slightly different model in the framework of the standard flow-of-fundsaccounting, commonly used by the World Bank and the International MonetaryFund, was developed for the National Planning Commission Secretariat Project.In the model, different building blocks viz. the national accounts; the budget and

    pubic sector account; the balance of payments (BOP) or the rest of the worldaccount; the monetary sector account; and the private sector account; wasintegrated into a consistent accounting framework.

    6 Khanal, D. R., P. J. Thapa, and C. Elbers. 1987. A Regionally Disaggregated Planning Models for Nepal .Kathmandu: NPC/ESCAP/IDS/ISI.7 Development Study Consultants. 1990. Policy Planning Models for the Nepalese Economy with SpecialReference to the Industrial Sector. Mimeo. Kathmandu: DSC/MOI/UNIDO.8 Khanal, D. R. and G. N. Sharma. 1992. A Macroeconometric Model of Nepal in SAARC Link. Nagvi,S.N.H. and S.A. Samad, eds. New Delhi: Oxford and IBH Publishing Co. Pvt. Ltd.

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    7) In 1990, a simple macroeconomic accounting framework was employed toexamine the possibility of policy coordination between exchange rate policy andfiscal policy for more effective management of the economy 9.

    8) While the Tenth Plan was being formulated, the integrated macro and input-

    output model was used to set the growth rates and the investment levels at boththe sectoral and aggregate level without disrupting macroeconomic stability.

    9) Special attention should be drawn to two other macroeconomic models: Alamgir and Ra (2001) 10 and Sharma (1989). The Alamgir and Ra (2001) model projectsGDP growth by major economic sectors on the basis of growth elasticity derivedfrom historical data and adjusted for structural changes.

    10) A common feature of the two models is that GDP is predetermined or stipulated before estimating individual equations. These models implicitly assume that thesupply side determines aggregate output, and they predict each endogenous

    variable in a way that is consistent with the given output level.11) There had recent attempts under technical assistance by ADB to develop a

    medium a medium size Macroeconomic Model (MEM). A part of TA for Strengthening Institutional Capacity for Public Debt Management, ADB (Ra andRhee 2005) supported the Government in developing a MEM in 2005 known as

    Nepal Macroeconomic Model (NMEM) on the basis of the standard Keynesianincomeexpenditure approach in which gross domestic product (GDP) isdetermined endogenously.

    12) Apart from being used by the Government for debt sustainability analyses, NepalRasta Bank (NRB) has also been using the NMEM for economic forecasting.

    13) Subsequently to that Khanal and Kane (2005) had utilized a MEM to analyzereduction of domestic poverty, and

    14) Bhattarai (2007) had produced an applied dynamic general equilibrium model for Nepal.

    15) In recent years Nepal Rastra Bank has engaged itself actively for developing itsown MEM which would be consistent with the vision and mission of the Bank.The model was developed by the Macroeconomic Modeling Unit (MMU) of the

    NRB (2007), Research Departments Economic Analysis Division as a part of itsmacroeconomic modeling activities.

    9 Cruikshank, E.D. and R.H. Nord. 1990. The Role of Exchange Rate Policy: The Case of Nepal . Mimeo.Kathmandu.

    10 Alamgir, M., and S. Ra. 2001. Nepal: Debt Sustainability and Country Risk Analysis . Manila:ADB.

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    From the above review it follows that the state of the macroeconomic modeling in Nepalis still at an experimental and learning stage. There are a few examples of macroeconomic modeling for the purpose of policy planning and formulation of economic plan. But these were not done on a sustainable, comprehensive and continual

    basis. There was also lack of adequate capacity building in the respective agencies.

    Besides, the utility of NMEM has become limited due to major structural changes in the Nepals economy, and major revisions of key macroeconomic data (such as NationalAccounts, Price Statistics, Government Finance Statistics and the Balance of Paymentsover the years) due to changes in base period and basic concepts. Therefore, the NMEMdeveloped by ADB needs to be reviewed and upgraded. In addition, other econometricmodels such as the Dynamic Stochastic General Equilibrium (DSGE) model need to bedeveloped to examine the relative merits and demerits of both these models.

    Considerable efforts are, therefore, required for the development of new modelingtechniques with a focus on the direct and practical policy applications by the Nepal

    Rastra Bank, Ministry of Finance and the National Planning Commission (NPC).The basic purpose of the present technical assistance of the ADB is to remove thesedeficiencies in macroeconomic modeling and to strengthen technical capability in the

    NRB, MOF, NPC and CBS for model building and its use for policy planning.

    5.2 Review of the Nepal Macroeconomic Model developed by ADB

    As mentioned in the previous section, ADB supported the Government of Nepal indeveloping a comprehensive macroeconomic model in 2005Nepal MacroeconomicModel (NMEM)as a part of TA for Strengthening Institutional Capacity for PublicDebt Management. Apart from being used by the Government for public debtsustainability analyses, Nepal Rasta Bank (NRB)the central bank of Nepalhas also

    been using the NMEM for economic forecasting. However, the NMEMs utility has become limited due to some major developments in recent years.

    The major characteristics of the NMEM are:

    (a) The NMEM is a basically Keynesian income-expenditure model in which thedemand side determines GDP.

    (b) The supply side is not explicitly specified as the aggregate productionfunction is not estimated.

    (c) Its basic features are drawn from the Korea Development Institute (KDI)macro model that had been used to design successive 5-year economicdevelopment plans in Korea. Due to the lack of quarterly data in Nepal the

    NMEM is an annual model while the KDI used a quarterly macro-econometric model.

    (d) There are 5 building blocks in the NMEM viz. final demand, prices, credit andmoney, government, and the balance of payments blocks. Final demand is the

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    sum of private consumption, government consumption, private fixedinvestment, government fixed investment, increase in stock or inventory, andnet exports. In NMEM, development expenditure is a determinant for the

    private fixed investment, public fixed investment and public consumption.

    (e) The NMEM is a mid-sized model with 37 equations. A medium-sized modelhas an advantage in policy analysis as it incorporates more detail of thestructure of the economy.

    (f) The NMEM consists of 20 behavioral equations and 17 identities. Of the 59variables in the system, 37 are endogenous and 22 are exogenous. The NMEMdistinguishes policy variables from simple exogenous variables since these

    policy variables are different from simple exogenous variables that aredetermined by non-economic forces or foreign sectors. Taxes, regular expenditures, development expenditures, foreign borrowing, and the exchangerate were taken as policy variables in the NMEM. Table-5.1 lists theexogenous, endogenous and policy variables and Table-5.2 presents the set of

    best fitted equations for the model.

    (g) Given the peg of the Nepalese rupee to the Indian Rupee, monetary variablesare not considered as policy variables.

    (h) The NMM attempts to incorporate Nepals strong economic ties with India ininternational transactions although economic relationships with other countries are also becoming important.

    (i) The impact of the exchange rate on trade in Nepal is quite limited since the Nepalese rupee is pegged to the Indian rupee and India is the major trading partner of Nepal. The exchange rate variables were incorporated in the tradeequations since the changes in the exchange rate with respect to the US dollar

    can affect trade with the rest of world by changing the relative prices withother countries.

    The Nepal Macro-economic Model (NMEM) was tested and calibrated on the basis of time series data for the sample period from FY1975 to FY2004. Then the model wassimulated to carry out alternative scenario analysis for formulation of the Tenth Plan. Themodel was also calibrated to measure the economic costs of conflict in terms of the effectof declining development expenditures on economic growth (Ra, Sungsup and BipulSingh 2005).

    5.3 Limitations of the Model of the Model

    A critical review of the model leads to the following limitations:

    (a) Model considers only the demand side of GDP, but does not consider the supplyside of the real sectors.

    (b) Similarly, money, credit and price blocks were not fully developed and did notconsider the supply side and the role of expectations.

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    (c) The Government block was the weakest block with only equation for the non-taxrevenue and all other variables were defined by simple accounting identities.Basically, all the fiscal variables such as taxes, current and capital expenditure aretreated as policy variables and left to be decided by the policy makers. This is nota very convincing assumption because taxes and government expenditures also

    depend on economic prospects, composition of GDP and many other variables.(d) Similarly, balance of payments block were not well developed. It consideredonly merchandise exports and merchandised imports but did not endogenize theother components in the current account (such as services and remittances). In thecapital account, loans and amortization was endogenized, but the underlyingeconometric relations are less convincing.

    (e) The model also needs to be updated and upgraded on the basis of new dataavailable for the national accounts and balance of payments.

    The utility of NMEM in the national polity analysis has been limited due to thefollowing reasons:

    (a) The structure of Nepals economy has changed significantly. Agriculturescontribution to GDP has declined fast whereas the services sectorscontribution has grown rapidly compared to other sectors of non-agriculturesectors. It is interesting to note that the industrys share of GDP has remainedmore or less unchanged. The national accounts also underestimate certainincomes, such as migrant workers remittances, which have grown sharplysince 2004.

    (b) There have been some major revisions of basic concepts and standards of keymacroeconomic variables such as national accounts, government finance,

    balance of payments and prices since the NMEM was developed.

    (c) In view of these changes, it is necessary to upgrade the NMEM for analyticalwork and macroeconomic forecasting.

    In the following sub-section, we specify a modified and upgraded macroeconomic modelfor Nepal. While doing so, due consideration has been given to the availability new data

    base, up-to-date statistical test and calibration techniques, computer algorithms, andavailable hardware and software capabilities, and technical manpower in the NRB, MOFand other budgetary agencies which are likely to use the updated NMEM for budgeting,

    planning and monetary and financial programming.

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    Table 5.1: List of Variables in ADB NMEM (2005)

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    Table-5 .2

    The Structure of the ADB Nepal Macroeconomic Model (NMEM)

    Independent

    Variables

    Fitted Equations

    1. PrivateConsumption

    2. GovernmentConsumption

    3. PrivateFixedInvestment

    4. GovernmentFixedInvestment

    5. Exports of goods andservices

    6. Imports of goods andservices

    7. Consumer

    Price Index8. GDP

    Deflator

    9. Net ForeignAssets

    10.PrivateDomesticCredit

    11.GovernmentDomesticCredit

    12.Non-taxRevenue

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    13.Merchandise Exports

    14.Merchandis

    e Imports

    15.ForeignLoans andOfficialGrants

    16.Amorti-zation

    17.ForeignLoanDisburse-mint

    18.GrantDisbursement

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    5.4 An Upgraded Macroeconomic Model for Nepal

    As described in Section 3 earlier the proposed model has the following blocks:

    (1) National Accounts System (NAS) - Supply and Demand Side

    (2) Government Finance (GF)(3) Balance of Payments (BOP)(4) Monetary-Financial Sectors (MFS)(5) Prices, Interest Rates and Exchange Rates

    5.4.1 National Accounts Block

    (a) Supply Side of GDP

    Real GDP at constant factor cost will be projected for the broad sectorsof the economy. List of variables, their types and notations are

    indicated in the following table:List of Variables Type of Variable Notation

    A. Population (million, as on 2 July Exogenous POPPopulation growth rate (% per annum) Exogenous POPGR B. GDP: Supply Side1. GDP const FC (Mill. NR) =1.1+1.2+1.3 Identity GDP1.1 Agriculture and allied (1.1.1+1.1.2) Identity GDPAG

    1.1.1 Agriculture, forestry andlogging

    Endogenous GDPAFL

    1.1.2 Fishing Endogenous GDPF1.2 Industry = 1.2.1+1.2.2+1.2.3+1.2.4 Identity GDPIND

    1.2.1 Manufacturing Endogenous GDPMANF1.2.2 Mining and quarrying Endogenous GDPMINQ1.2.3 Electricity, gas, water supply Endogenous GDPELEC1.2.4 Construction Endogenous GDPCONST

    1.3 Services = 1.3.1+1.3.2+. +1.3.9 Identity GDPSER 1.3.1 Trade Endogenous GDPTR 1.3.2 Hotels and restaurants Endogenous GDPHT1.3.3 Transport, storage, commn. Endogenous GDPTRANS1.3.4 Financial intermediation Endogenous GDPFIN1.3.5 Real estate, renting, business activities Endogenous GDPRE1.3.6 Public administration and defense Endogenous GDPPAD1.3.7 Education Endogenous GDPED

    1.3.8 Health Endogenous GDPHL1.3.9 Other community, social and personal Endogenous GDPCSL

    1. GDP const FC (Mill. NR) =1.1+1.2+1.3 Identity GDP2. (Plus) Indirect taxes less subsidies Endogenous INDT3. GDP at cons mp (Mill. NR) = 1 + 2 Identity GDPMP4. GDP at current mp (Mln NR) Endogenous GDPN

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    Data Base

    The basic data on selected variables for the period from the fiscal year1984/1985 (annual data the year 1984/1985 ending 15 July 1985) tothe fiscal year 2007/2008 (annual data for the year 2007/2008 ending

    15 July 2008) will be obtained from the respective primary sources i.e.national accounts from the CBS, balance of payments and monetaryand financial statistics from the NRB and the public finance statisticsfrom the MOF.

    Methodology

    Basic methodology used is the time series analysis and to estimatehistorical growth rates on the basis of three kinds of time trendsgrowth rates viz., least squares time trend growth rate, exponentialgrowth rate and simple average annual growth rate.

    Historical Growth Rates

    To start with, we estimate the average historical growth rate for eachof 15 sub-sectors of GDP viz. GDPAFL, GDPF, GDPMANF, GDPMINQ, GDPELEC,GDPCONST, GDPTR, GDPHT, GDPTRANS, GDPFIN, GDPRE, GDPPAD, GDPED, GDPHLand GDPCSL . The following three kinds of growth rates will be estimatedon the basis of the past time series data obtained from the CBS for theyears for which consistent estimates are available.

    (a) Least-squares time trend growth rate

    The IMF uses the Least-squares growth rates to forecast the countrygrowth rates in their World Economic Outlook (WEO) published twice ina year, wherever their is past data for at least 9 years to permit areliable calculation. The least-squares growth rate, r , is estimated byfitting a linear regression trend line to the logarithmic annual values of the variable in the relevant period. The regression equation takes theform

    Ln Y t = a + bt

    which is equivalent to the logarithmic transformation of the compoundgrowth equation,

    Y t = Yo (1 + r ) t

    In this equation, Y is the variable, t is time, r is the trend growth rate,Ln is the natural logarithm operator, and a = log Yo and b = Ln (1 + r )are the parameters to be estimated.

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    If b* is the least-squares estimate of b, the average annual growthrate, r, is obtained as

    r = [exp( b* ) 1] and is multiplied by 100 to express it as a percentage.

    The calculated growth rate is an average rate that is representative of the available observations over the entire period. It does notnecessarily match the actual growth rate between any two years.

    (b) Exponential growth rate

    The exponential growth rate between two points in time for a variableis calculated from the following equation

    r = Ln ( Y n /Y 1)/ n

    where Y n and Y 1 are the last and first observations in the period, n isthe number of years in the period, and Ln is the natural logarithmoperator. This growth rate is based on a model of continuous andexponential growth between two points in time. It does not take intoaccount the intermediate values of the series.

    (c) Average of Annual Growth rates

    Average Annual Growth Rate () = GR i /nGR i = 100 * (Y i / Y i-1 -1) for i=1, 2, n for the years 1985, 1986, ..... 2008.

    CV = 100 * SD/ SD = (GR i - ) / nWhere Ln stands for natural logarithm, GRi for growth rate for the i-th year, CV for coefficient of variation and SD for standard deviation.

    (d) Base Line Time Trend Projections

    The projections of sectoral value added for the years 2009-2015 are done on the basis of the trend growth rate, which happens to be the minimum of these three types of growthrates. In general, the least squares trend growth rate is expected to be lower than theexponential growth rate, which in turn is expected to be lower than the average annualgrowth rates for most of the variables. It may also be possible that annual growth ratesare highly volatile with high standard deviation (SD) and co-efficient of variation (CV),and therefore the average annual growth rate cannot hold good for the medium and longterm. If for any variable, there is high CV (say exceeding 100%), the projected growthrate is modified on the basis of the following formula:

    Projected growth rate = Trend growth rate minus 25 percent of SD.

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    The same methodology is used to project net indirect taxes (i.e. indirect taxes lesssubsidies and transfers). Thus we have,

    GDP = GDPAG + GDPIND + GDPSER GDPAG = GDPAFL + GDPF

    GDPIND = GDPMANF+GDPMINQ+GDPELEC+GDPCONSTGDPSER= GDPTR + GDPHT + GDPTRANS + GDPFIN + GDPRE + GDPPAD + GDPED +GDPHL + GDPCSL GDPMP = GDP + INDT

    Projections for future

    In general, we use the following equation for forecasting:

    Yt = Yo (1 + r) t

    Where Y = GDPAG and other sectors0 = Base year 2008/09T = 1, 2, 3 for years 2009/10, 2010/11, 2011/12

    Nominal GDP at current market prices is projected by the following equation:GDPN t = GDP t (1 + 0.01 * INFGDPt)Where INFPGDPt is the projected inflation in terms of GDP deflator forthe year t.

    (b) Demand Side of GDP

    Demand side is projected at current market prices because decisions by economic agentsare always made on the basis of current market prices. List of variables, their typesand notations are indicated in the following table:

    GDP at current mp (Mln NR)=a+b+c+d+e-f+g

    Identity GDPN

    (a) Private consumption Endogenous CP(b) Government consumption Endogenous CG(c) Gross fixed capital formation = (i)+(ii) Identity FC

    (i) Gross fixed cap. Formation by govt. Endogenous FCG(ii) Gross fixed cap. Formation by private Endogenous FCP

    (d) Change in stocks Endogenous ST(e) Exports of goods and services Endogenous XGS

    (f) Imports of goods and services Endogenous MGS(g) Statistical error in GDPN estimation Endogenous SDGDP

    Investment (at current prices)=a+b+c Identity INV(a) Agriculture and allied Endogenous INVAG(b) Industry Endogenous INVIND(c) Services Endogenous INVSER

    Other explanatory variables (current prices)Tax revenues of the government Exogenous TAX

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    Total revenues of the government Exogenous REVTime = 1, 2, .. for the years 1984/85, Exogenous TimeInflation rare in terms of WPI Exogenous INFWPIBank credits to the private sector Exogenous BCPBank credits to the public sector Exogenous BCG

    Fixed ratio of stocks/ inventories to totalgross fixed capital on the basis of past data

    Exogenous K

    R eal exchange rate of Nepalese Rupee interms of US dollar

    Exogenous REXR

    Nominal GDP from the demand side (GDPNN t) is determined by the usual balanceequation. The other equations are specified below.

    GDPNN t = CP t + CG t + FCP t + FCG t + ST t + XGS t MGS t + SEGDP t

    Ln(CP t) = + 1 Ln(GDPN t-TAX t) + 2 Ln(POP t) + 3 Ln(CP t-1) + 4 Time

    Ln(CG t) = + 1 Ln(REV t) + 2 Ln(GDPN t) + 3 Ln(CG t-1) + 4 Time

    Ln(FCP t) = + 1 Ln(GDPN t-TAX t) + 2 Ln(INT t-INFWPI t) + 3 Ln(BCP t)+ 4 Ln(FCP t-1) + 5 Time

    Ln(FCG t) = + 1 Ln(GDPN t-TAX t) + 2 Ln(INT t-INFWPI t) + 3 Ln(BCG t)+ 4 Ln(FCG t-1) + 5 Time

    FC t = FCGt + FCPtSTt = k. FCt

    Ln (XGSt) = + 1 Ln(GDPN t) + 2 Ln(REXR t) + 3 Ln(XGS t-1) + 4 TimeLn (MGSt) = + 1 Ln(GDPN t) + 2 Ln(REXR t) + 3 Ln(MGS t-1) + 4 Time

    SEGDP t = GDPN t [CP t + CG t + FCP t + FCG t + ST t + XGS t MGS t]

    5.4.2 Government Finance Block

    List of variables, their types and notations are indicated in thefollowing table:

    Central Govt Operations (Billion NR)1.Total Revenue and grants = 1.1+1.2 Identity TRG

    1.1 Total revenue = (a) + (b) Identity R (i) Tax revenue = DT + IDT Identity T

    -- Direct taxes Endogenous DT-- Indirect taxes Endogenous IDT

    (ii) Nontax revenue Endogenous NT1.2 Grants Exogenous GR

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    2. Total Exp and net lending = 2.1+2.2 Identity GEXP2.1 Current expenditure = (a) + (b) Endogenous CG

    (a) Wages and salaries Endogenous WS(b) Other charges (OC) Identity CG-WS-INT

    (c) Interest payments Endogenous INT2.2 Capital expenditure and net lending = a+b Identity GK

    (a) Capital expenditure Endogenous FCG(b) Net lending Endogenous ND

    3. Current A/C Balance =1.1 - 2.1 (a) Identity CABGF4. Gross Fiscal Balance = 1-2 Identity GFB5. Primary Balance = 4 - Interest payments Identity PB

    The proposed equations stand as follow:

    Ln(DT t) = + 1 Ln(GDPN t-GDPNAG t) + 2 Ln(PGDP t) + 3 Ln(DT t-1) + 4Time

    Ln(IDT t) = + 1 Ln(GDPN t) + 2 Ln(PGDP t) + 3 Ln(IDT t-1) + 4 Time

    Ln(NT t) = + 1 Ln(GDPN t) + 2 Ln(PGDP t) + 3 Ln(NT t-1) + 4 Time

    GR t = Grants are estimates on the basis of historical growth rates as described in earlier section adjusted by current information by the government

    Ln(CG t) = + 1 Ln(REV t) + 2 Ln(GDPN t) + 3 Ln(CG t-1) + 4 Time

    Ln(WS t) = + 1 Ln(REV t) + 2 Ln(WS t-1) + 3 Time

    INT = Interest payments are estimated on the basis of projected profile of domestic andexternal public debt and negotiated terms and conditions for interest payments

    OC = CG-WS-INTLn(ND t) = + 1 Ln(R t) + 2 Ln(GDPN t) + 3 Ln(ND t-1) + 4 TimeCABGF = Current account balance in government finance = TRG-CGGFD = TRG- GEXPPB = GFD-IINT

    5.4.3 Balance of Payments Block

    List of variables, their types and notations are indicated in thefollowing table:Balance of Payments (Million US$) Type of Variables NotationGoods balance = XG-MG Identity GBExports of goods f.o.b.=XGIND+XGCH+XGR Endogenous XG

    (a) Exports of goods to India Endogenous XGIND(b) Exports of goods to others Endogenous XGR

    Imports of goods c.i.f.=MGIND+MGCH+MGR Identity MG(a) Imports of goods from India Endogenous MGIND

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    (b) Imports of goods from China Endogenous MGCH(c) Imports of goods from other countries Endogenous MGR

    Services balance= SCR-SDB Identity SB(a) Credits Endogenous SCR (b) Debits Endogenous SDB

    Services and incomes balance= SICR-SIDB Identity SIB(a) Credits Endogenous SICR (b) Debits Endogenous SIDB

    Transfers Balance = (a)+(b) Identity TRB(a) Official grants, net Exogenous GR (b) Remittances Endogenous REM

    Current account balance (CAB)=GB+SB+TRB Identity CAB

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    Exports of goods & services Identity XGSImports of goods & services Identity MGSCapital and financial account

    Official loans, net = DISB-AMORT Identity DISB-AMORTDisbursement Exogenous DISB

    Amortization (AMORT) Exogenous AMORTPrivate capital inflow Identity PRCAP

    FDI, net Endogenous FDIOther investment, net Endogenous OINV

    Errors and omissions Endogenous EBOPCapital and Financial Balance Identity CAPBOverall balance = OB Identity CAB+CAPBForeign Exch reserve at the end period Identity FER Equivalent to months of imports Identity MM

    The equations stand as follow:

    Ln(XG t) = + 1 Ln(GDPN t) + 2 Ln(XGIND t) + 3 Ln(XGCH t) + 4Ln(REXR t)

    + 5 Ln(XG t-1) + 6 TimeLn(MG t) = + 1 Ln(GDPN t) + 2 Ln(MGIND t) + 3 Ln(MGCH t) + 4Ln(REXR t)

    + 5 Ln(MG t-1) + 6 TimeXG t = Exp(Ln(XG t))MG t = Exp(Ln(MG t))GB t = XG t - MG t

    Ln (XGSt) = + 1 Ln(GDPN t) + 2 Ln(REXR t) + 3 Ln(XGS t-1) + 4 TimeLn (MGSt) = + 1 Ln(GDPN t) + 2 Ln(REXR t) + 3 Ln(MGS t-1) + 4 Time

    SCR t = XGSt XGtSDBt = MGSt MGtSB t = SCRt - SDBt

    Ln(SICR t) = + 1 Ln(GDPN t) + 2 Ln(SICR t-1) + 3 TimeLn(SIDB t) = + 1 Ln(GDPN t) + 2 Ln(SIDB t-1) + 3 TimeSICR t = Exp(Ln(SICR t))SIDB t = Exp(Ln(SIDB t))SIB t = SICR t - SIDB t

    GR t = Grants are estimates on the basis of historical growth rates as described in section8.2.1 adjusted by current information by the governmentLn (REMt) = + 1 Ln(GDPN t) + 2 Ln(REM t-1) + 3 TimeTRB t = GRt + REMt

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    CAB t = GBt + SBt + FIBt + TRBt

    DISB t and AMORTt are estimated on the basis of projected profile of external publicdebt and negotiated terms and conditions for disbursement and repayments of principal.

    Ln (FDIt) = + 1 Ln(GDPN t) + 2 Ln(FDI t-1) + 3 TimeLn (OINVt) = + 1 Ln(GDPN t) + 2 Ln(OINV t-1) + 3 TimePRCAP t = FDIt + OINVt

    EBOP t is determined on the basis of past trends.

    CAPB t = DISB t AMORT t + PRCAP t + EBOP t

    OB t = CAB t +CAPB t

    FER t = FER t-1 + OB t

    MM t = 12 * FER t / MGSt +1

    5.4.4 Monetary and Financial Sectors

    List of variables, their types and notations are indicated in thefollowing table:

    List of Variables Type of Variable NotationMonetary survey (Billion NR)

    Net foreign assets Endogenous NFA Net domestic assets = DC + OIN Identity NDA

    Domestic credits = BCG + BCP + BCF Identity DCCredits to the public sector, net Endogenous BCGCredits to the private sector, net Endogenous BCPClaims on financial institutions Endogenous BCF

    Other items, net (OIN) Endogenous OINBroad money (M2) demand Identity M2Broad money (M2) supply =M1+Time Deposits

    Identity M2

    Quasi Money (M1) = (a) +(b) Identity M1(a) Currency outside banks Endogenous CUR (b) Demand Deposits Endogenous DD

    Time Deposits Endogenous TDInterest Rates (% per annum) Endogenous INTTerm deposit rate (one year) TDR Bank lending rate (medium term) LR Treasury Bill (364 day) rate TBR

    NRB Bank rate BR Cash Reserve Ratio (CRR)

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    Ln (CURt) = + 1 Ln(GDPN t) + 2 Ln(CUR t-1) + 3 TimeLn (DDt) = + 1 Ln(GDPN t) + 2 Ln(DD t-1) + 3 TimeLn (TDt) = + 1 Ln(GDPN t) + 2 Ln(TDR t-INF t) + 3 Ln(TD t-1) + 4 TimeM1 t = CURt + DDtM3t = M1 + TDt

    Ln (NFA t) = + 1 Ln(OB t) + 2 Time where OB = overall BOP balanceLn (BCG t) = + 1 Ln(GFD t) + 2 Ln(BCG t-1) + 3 TimeLn (BCPt) = + 1 Ln(GFD t) + 2 Ln(PLR t-INFT) + 3 Ln(BCP t-1) + 4 TimeLn (BCF t) = + 1 Ln(DD t) + 2 Ln(BCF t-1) + 3 TimeOIN t = M3 t NFAt [BCGt + BCPt + BCPt]

    NDA t = BCGt + BCPt + BCPt + OINtM3 t = NFA t + NDAt

    5.4.5 Prices, Interest Rates and Exchange Rates

    PLR t = + 1 Ln(M3 t) + 2 INF t + 3 BR + 4 CRR + 5 Exchange Rate + 6TimeDeposit rate = f(WPI inflation, exchange rate in terms of US$, Bank rate, Time)Exchange Rate in terms of US$ = f(Overall BOP, Domestic Inflation/ World inflation)WPI inflation = f(Real GDP growth rate, M3 growth rate, PLR, exchange rate)CPI inflation = f(Indian CPI inflation)GDP deflator inflation = f(WPI inflation, real GDP growth rate)

    List of Variables for Prices, interest rate, exchange rate

    List of Variables Type of Variable NotationAve Exchange Rate (NR/US$) Endogenous EXR GDP at current mp (mn US$) Identity GDPMP$Percapita GDP current mp (US$) Identity PCGDP$Consumer (Urban) Price Index (1995/96=100) Identity CPI

    Food Endogenous CPIFNon-Food Endogenous CPINF

    CPI Inflation (Annual % change) Identity INFCPIFood Endogenous INFCPIFNon-Food Endogenous INFCPINF

    Implicit GDP Deflator Identity INFGDPDeposit rate (annual in percentage) Exogenous DR

    NRB discount rate (annual in percentage) Exogenous BR Prime lending rate (annual in percentage) Exogenous PLR

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    6. An Operational Dynamic Stochastic General Equilibrium Model for Nepal

    6.1 Basic Characteristics of DSGE Model

    In recent decades, academic research has emphasized the development of DynamicStochastic General Equilibrium (DSGE) models, whose basic characteristic is to usemicroeconomic foundations for modeling macroeconomic behavior. The model hasseveral advantages. First, micro foundations allow avoiding Lucas critique (1976).Second, the individual rationality behind the aggregate behavior is useful to analyze theimpact of fiscal and monetary policies on private agents expectations. Moreover, rationalexpectations differentiate effects between permanent and transitory shocks. Third, thegeneral equilibrium structure maintains the consistency between flow and stock variables,such as investment and capital stock, the current account balance and the net foreignassets reserve, fiscal deficit and the total stock of public debt etc. Fourth, there is recentempirical evidence showing that DSGE models can have a better forecasting performancethan purely econometric models 11.

    The main objective of the model is to conduct policy analysis and to forecast majormacroeconomic variables for the immediate future and the mediumterm which can be used to prepare the government budget,macroeconomic plan, monetary program, and to formulate budgetary,fiscal, monetary and real sector policies by the Ministry of Finance,Nepal Rastra Bank and the National Planning Commission. T he model canalso decompose macroeconomic variables for explaining their fluctuations (shocks), bothin history and forecast. Because of its designs, such as micro-foundations, dynamics,uncertainty and rational expectations, a potential use of the model is the evaluation of the

    impact of fiscal and monetary policy on social welfare (such as inflation, poverty etc.).Other uses of the model include the estimation of non-observable variables such as thenatural interest rate, the potential output, the real exchange rate equilibrium and thenatural unemployment rate for the Nepalese economy. The main advantage of the modelis its ability to estimate all the variables simultaneously.

    For operational purpose, such a model generally considers five majoragents viz. the households, the firms, the financial institutions, thegovernment with its agencies, and the rest of the world. The behaviorof the economic agents is not only decided by economic theories, butalso is estimated on the basis of historical time series data after

    satisfying the standard econometric techniques on specification,identification, estimation, test and calibration.

    As discussed in details in Annex-3.13 in Part-II of this report, the DSGE methodologyattempts to explain macro economic phenomena, such as economic growth and the

    11 Del Negro, M. F. Schorfheide, F. Smets, and R.Wouters (2006). On the Fit of New KeynesianModels, Journal of Business of Economic and Statistics .

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    effects of monetary and fiscal policies, on the basis of macroeconomic models derivedfrom microeconomic principles. Unlike traditional macro-econometric forecastingmodels, DSGE macroeconomic models are not subject to Lucas critique ( Woodford,2003, p. 11; Tovar, 2008, p. 15 ).

    As the name indicates, DSGE models are dynamic , studying how the economy evolvesover time. They are also stochastic, taking into account the fact that the economy isaffected by random shocks such as technological change, fluctuations in the price of oil,or errors in macroeconomic policy-making. Traditional macro-econometric forecastingmodels used by central banks in the 1970s estimated the dynamic correlations between

    prices and quantities in different sectors, and often included hundreds of variables.

    Since DSGE models are technically more difficult to solve and analyze, they cannot dealwith sectoral details as given in the previous section, and would include limited number of variables. DSGE models provide logical consistency and spell out the essential aspectsof the economy viz. preferences of e conomic agents, technology used for production ,

    and institutional framework for monetary, fiscal and external sector policies .The best example of DGSE models include the Smets-Wouters model, developed by theEuropean Central Bank (ECB), to analyzes the economy of the Eurozone as a whole(without analyzing individual European countries separately). Another partial DGSEmodel is used by the staff of the Joint Committee on Taxation to model themacroeconomic effects of proposed tax legislation in the United States of America.

    With limited database and resources (in terms of technical manpower, hardware andsoftware requirements, and Finance) and no previous experience of DGSE modeling sucha leapfrogging may not be feasible for Nepal. So we make an attempt to develop a simpleDGSE Model for Nepal. Here we present the basic structure of an operational DSGEModel for Nepal. The Model will be fully developed in the course of the modelingexercises by the consultants after examining fully the available data base, estimationtechniques and computer algorithms for test, calibration, projections and simulations.

    6.2 Model Specification

    The model is a simple macro-econometric one with a combination of supply and demand factors influencing economic growth. An increasein aggregate demand leads to increase in output and prices 12 which inturn influence the supply. Output (GDPR) of the economy is determinedby domestic demand (DR) and external demand. As in the case of NMEM, domestic demand (DR) is determined as sum of privateconsumption (CP), government consumption (CG), total investment(INV) and Stocks (ST). External demand equals exports of goods andservices (XGS) less imports of goods and services (MGS).

    12

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    As in the case of NMEM described in the previous section, the DSGEM will have fiveinterrelated blocks as follows. However, unlike in the NMEM, demand equations in thismodel will take into account the behavior, preferences and expectations of the economicagents and the production side will consider technological equations.

    (1) National Accounts System (NAS) - Supply and Demand Side(2) Government Finance (GF)(3) Balance of Payments (BOP)(4) Monetary-Financial Sectors (MFS)(5) Prices, Interest Rates and Exchange Rates

    6.3 Data system, estimation procedure and software used in model

    The model would use annual time series data for the period from 1985to 2008 obtained from the CBS, MOF and NRB. The model will becalibrated and tested by EVIEWS 6.0.

    Methods of estimation

    A DSGE model comprises a set of equations that jointly describe therelationship between a set of variables. The equations consist of simultaneous and single equations and simple identities. There are twoapproaches to estimate the model equations. One approach is toestimate each equation in the system separately. A second approach isto estimate, simultaneously, the complete set of parameters of theequations in the system. In reality, single equation estimation methodis easier and more flexible for adjusting and selecting the form of

    equation13

    . There are some advanced techniques to estimate system of simultaneous equations such as Two Stage Least Squares (TSLS) or Three Stage Least Squares (3SLS). However these methods are notonly complex but also require large sets of data.

    So we would apply first the ordinary least squares (OLS) method toestimate the single equations and to identify the form of eachequation. And then we would apply the SUR model for estimatingsystem of equations.

    A common finding in time series regressions is that the residuals are

    correlated with theirown lagged values. This serial correlation violates the standardassumption of classical regression theory that disturbances are not

    13 If one of the equations in the system is miss-specified and estimate the parametersusing single equation methods, only the miss-specified equation will be poorlyestimated. If system estimation techniques are employed, the poor estimates for themisspecification equation may "contaminate" estimates for other equations.

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    correlated with other disturbances. In this case, we could apply autoregressive model (RAM) to correct the serial correlation error. Thesimplest and most widely used model of serial correlation is the first-order autoregressive, or AR(1), model, which stands as follows:

    Yt = X t + U t (1)Ut = U t-1 + V t (2) The parameter is the first-order serial correlation coefficient. Ineffect, the AR(1) modelincorporates the residual from the past observation into the regressionmodel for the current observation. For example, the EVIEWS softwareautomatically uses the following equation to transform the linearmodel into a nonlinear model:

    Yt = Y t-1 + (X t X t-1 ) + V t (3)

    which is obtained by substituting equation (2) into equation (1), andrearranging terms. The coefficients and are estimatedsimultan