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I I I I I I I I I I I I I I I I I I I I

18866 '

lJN ..L DO UN1-"TED NArr.CONS ..LNDUSrrR_l:AL

DEVELOPMENT ORGANIZATION

1_4~INAL REPORT

ON

PC>I...._CCV PJ ..... ANNING MOJ>ELS J4"0H. "'rllE NJ~PALESE .HCONOMY W_l:"'rH

SPECJAL REFERENCE TO THE ..LNDUSTRIAL SECTOR

..LNDUS"'rRIAL PLANNING AND MON L rroR. I NG

PROJECT NO. DP/NEP/86/005

SlJBMl:TTF.I> BY DEVHLC>PMJ~N"'I" S"'rUDV CC.>NSUL"'rAN"'rs

KATHMANDU. NEPAL

,· ·-·1 l_,.-1 , I\:

NOVHMBRR 1990

I . f J ' l ~ I ~ :'f _, . I

,.: . ·' -.


Preface ...................................................... .

CHAP1'ER l : INTRODUCTION • ••..•.••.••.•.••.••.••.•....•••.•.•..

I.I Need for the Study ...•••••.••••••••••••.•••••••••••••••• 1.2 Objectives ............................................. . I.3 Scope of the Study •••••••••••••.•••••••••••••••••••••••• I.4 Structure of the Report •••••••••••••••••••••••••••••••••

CHAPTER 2: NBPALBSB ECONOMY AND THB INDUSTRIAL STRUCTURE •••••

2.I 2.2 2.3

Nepalese Economic Structure ••••••••••••••••••••••••••••• ferformance of the Manufacturing Sector ••••••••••••••••• Policy Issues for Industrial Planning ••••••••••••••••••

CHAPTER 3: POLICY PLANNING HODBLS FOR N.KPALBSB BCONottY

3. I 3.2 3.3

3.4 3.5

WITH SPECIAL RBFBRBNCB TO TH.K INDUSTRIAL SBCTOR ••.

Macro r--1ode l .••.•••.••••••••.•••••••••••••••••••••••••••• Input/Output l'-1odel .......... ........................... . Integration of the Macro Hodel with the Input/Output ~lode! ........ ............................. . Sequencing of Models' Integration ••••••.•••••••••••••••• Simulations ............................................ . 3.5.1 Reference Run ••••••••••••••••••••••••••••••••••••• 3.5.2 Alternative Simulations •••••••••••••••.•.•••••••••

CHAPTER 4: DATA BASK OF TUB MACRO HOD.KL •..•••••••••.••••••.••

4.I 4.2 4.3

Introduction Data Sources and the Time Period Covered by the Study ••. Methods used to Minimize the Data Gap Problems •••••••••• 4.3.1 Production Functions and Capital Stock

Variables ..................................... ···· 4.3.2 Estimation of Sectoral Employment Series •••••••••• 4.3.3 Trade Statistics and Foreign Trade Sub-model •••••• 4.3.4 Government Accounts ••.•.•••.••••.•...•••.••.•.•••• 4.3.5 Price Indices and Time Series Data at constant

Prices····•••••••••••••••••••••••••••••••••••••••

CHAPTER 5: DATA BASH OF TH.K INPUT/OUTPUT MODEL ••••••••••••.••

5.1 Introduction ........................................... . 5.2 Input/Output Table at Producer's Prices and Data

Requ i remen l . ...•••.••••••••••••.•••••••••••.••.•••••.••• 5.3 Sources of Dato ........................................ .

5.3.1 Agriculture, Livestock and Fisheries ••..••••••••.

( i )

Page

viii

1

I 2 3 6

7

7 IO I8

20

20 31

34 36 37 37 38

f

39

39 40 40

41 41 42 43

43

46

46

48 49 50


5.4

5.3.2 5.3.3 5.3.4 5.3.5 5.3.6 5.3.7 5.3.8 5.3.9 5.3.10 5.3.11

Industrial Sector •..•..•••.••••.••..•••••••••••.. Mining and Quarrying .••.••••••••••••••••••••••••• Construction .................................... . Electricity, Gas and Water .••••••••...•..•••••••• Trade, Hotel and kes tau rant ••••••••••••.•.•••.••• Transport and Communication ••••••••••••••••.•••.• Banking, Real Estate and Dwelling •••••••••••••••• Indirect Taxes and Government Services .•••••••••. Pr i vale Services ..... ........................... . Foreign Trade ................................... .

Consolidation of Data Base and Estiaation of Input/Output Table ..... ................................. .

50 51 5I 52 52 52 52 53 54 54

54

CHAPTER 6: VALIDATION OF THK MACRO HODEL AND

6. 1 6.2

6.3

POLICY SIH~LATION..... . . . . • • • . • • • • • • • . • • . . • • • . . • • • 66

Hodel Validation ....................................... . Pol icy Simula lion ...................................... . 6.2.1 Base Run Scenario •••.••••••••••••••••••••••••••••• 6.2.2 Alternative Scenarios ••••••••••••••••••••••••••••• Policy Implications •••••.••••.•••••••••••••••••••••••••.

66 7!, 76 78 82

CHAPTER 7: INPUT/OUTPUT MODEL AND POLICY SIMULATION •••••••••• 84

7.1 Reference Run Solutio, ••••.••••••••.••••••.••••.•••••••• 85 7.2 Sensitivity Analysis and Alternative Policy

Simulations............................................. 86 7.2.1 Import Substitution Strategy and Industrial

[.2velopment....................................... 90 7.2.2 Export Led Strategy and Industrial Development •••• 92 7.2.3 Combined StrateY,y: Export Promotion and Import

Subs ti tut ion on the !Jc.sis of Comparative Advnnlnge and Industrial Development .•.•••.••••.•• 99

7.2.4 Poverty Alleviation Strategy and Its lmpl icalions...................................... 103

7.3 Intersectornl Linkages and Investment Planning •••••••••• 10~ 7.4 Employment Effect of Alternative Strategies •••.••.•••••• 109

CHAPTER 8: CONCLUSIONS and RKCOHHBNDATIONS •••.••.••.••.•••••• 111

8. 1 Cone 1 us ions . . . . . . . • . • . . • . . . . . . . . . . • • . • . • • • • • • • . • • • • • • • • • 111 8.1.1 The Macro-Economic Scenario ••••••••••••••••••••••• 112 8.1.2 The Inter-Sectoral Scenario ••••••••••••••••••••••• 114

8. 2 Recommendations... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117

Bibliography ................................................ 122

(ii)

I I I LIST OF TABLES

I Table 2. 1 Selected Indicators of Nepal (1980-88) •••••••••. 8

I Table 2.2 Principle Indicators of Manufacturing

Establishments ................................. 12

I Table 2.3

Table 2.4

Total Exports and Its Coaposition .••.•••••••••.• 13

Export of Major Commodities to Third Countries ................................. ..... 14

I Table 2.5 Export of Major Commodities to India •.••.•••••• 15

I Table 2.6

Table 2.7

Total Import and Its Composition •.•••.•.•.••••. 16

Capacity Utilization of Selectert Industries .................................... . 16

I Table 2.8 Gross Fixed Capital Formation in Private Sector ••••••••••••••••••.•••••••••••••• 17

I Table 5.1 Input/Output Table ••••••••••••••••••••••.••••.• 62

I Table 6. 1 Root Mean Square Percent Error

of Selected Variables •••••••••.•.•••••••••••••• 75

I Table 6.2

Table 6.3

Basic Assumptions .....•...•....•...•......•.•.. 76

Sectoral Allocation of Invest•ent ••••••••••••.• 7~

I Table 6.4 Base Run Results on Major Macro Variables ••••••••••••.••••••.••••••.••••• 78

I Table 6.5

Table 6.6

Sectoral ICORs Derived •••••••••••••••••••••.••• 79

Results of Alternative Scenarios ••••••••..•.••• 80

I Table 7. 1 Growth Rate Implication of Reference Run Results ..•.•••••••••••••••••.•..••••.•••..• 87

I Table 7.2a Reference Run Results on Employment ••••••••.•.• 88

Table 7.2b Reference Run Results on Invemstment ••••.••.••• 89

I Table 7.3 Basic Assumptions •••••••••••.•.••.••..•••••••.• 91

I Table 7.4 Growth Rate Implication of Import

Substitution Strategy I •.••.•.••••••.••...•.•.• 94

I (iii)

I


Table 7.5

Table 7.6

Table 7.7

Table 7.8

Table 7.9

Table 7.10

Table 7 .11

Table 7.12

Table 7.13

Table 8.1

Growth Rate Implication of Import Substitution Strategy II ••••••••.•••••••....•.. 95

Growth Rate Implication of Export Promotion Strategy I ••.••••••••••••.••••.••.••. 97

Grwoth Rate Implication of Export Promotion Strategy II ••••••••••••.•••••••••••• 98

Growth Rate Implication of Export Promotion and Import Substitution Strategy I •••.••..•.•• 101

Growth Rate Implication of Export Promotion and Import Substitutioin Strategy II •••••••.•• 102

Gro~th Rate Implication of Poverty Alleviating Strategy •••••••••••••••••••••••••• 105

Investment Implications of Alternative Strategies ................................... . 106

Ranking of Industries in Terms of Backward and Forward Linkages ••••••••••••••••• 108

Employment Implication of Alternative Scenarios ..................................... 110

Plan Targeted Scenario ••••••••••••.••••••••••• 119

f i v )

I I i I I I I I I I I I I I I I I I I I I

1.

2.

3.

4.

5.

6.

7.

8.

LIST OF FIGURES

Flow Chart of the Macro Model •.••••••••.••••..•..•••• 22

Integration of Macro and Input Output Models ••••••••• 35

Gross Domestic Product

Gro~s National Product

. ............................. .

............................... 69

70

Government Savings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1

Govt Fiscal Deficit...... ••••••••••••••••••••••••••• 72

Import of Goods

Current Account

...................................... Balance ............................. .

( v;

73

74


LIST OF APPKNDICHS

Appendix Table l: Time Series Data Used in the Estimation of Macro Hodel •••••••••••••••••••••••••

Appendix Table 2: Simulated Data Series •••••.••••••••••••

Appendix Table 3: Base Run Forecast of the Macro Model •••

Appendix Table 4: Macro Model Forecast - Alt. 1

Appendix Table 5: Macro Model Forecast Alt. 2

Appendix.Table 6: Macro Model Forecast - Alt. 3

Appendix Table 7: Macro Hodel Forecast - Alt. 4 .......... Appendix Table 8: Aij Matri.iC ••••.••••••••••.•••••••••••••

Appendix Table 9: [l-A)-1 - Inverted Matrix •••.••••••••••

Appendix Table 10: Sectoral ICORs and Employment Coefficients ......................... .

Appendix Table 11: Results on Import Substitution Strategy 2 ........................... .

Appendix Table 12: Results on Export Promotion Strategy 2 ...................... ~ .... .

Appendix Table 13: Results on Export Promotion and Import Substitution Strategy 2 ••••••.•

(vi)

1

124

126

128

130

131

133

135

137

141

145

146

147

148

I I I I

Abbreviations and Acronyas

I APROSC Agricultural Projects Services Centre

CBS

I CD

Central Bureau of Statistics

Customs Department

I CTA Chief Technical Adviser

HMG I - His Majesty's Government of Nepal '

I ICOR Incremental Capital Output Ratio

IDS

I 1/0

Integrated Development Systems

Input Output

I LES Linear Expenditure Syst~m

MOF Ministry of Finance/HHG

I .MO! Ministry of lndustry/HMG

NRB

I SITC

Nepal Rastra Bank

Standard International Trade C.lassification

I TPC Trade Promotion Centre

UNDP United Nations Development Programme

I UNI DO United Nations Industrial Development Organization

I I I I I (vii)

I


PREFACE

This modelling exercide was undertaken by a team of local

experts with the support of LJnited Nations Development Programme

(UNDP) and United Nations Industrial Development Organization

(UNIDO). The primary objective of this exercise was to develop a

quantitative framework for medium and long term industrial

planning whereby the macro-economic and sectoral impacts of

alternative inv"estment and other policy decisions could be

assessed. For this purpose, a macro model and an input/output

model were separately developed and linked together to undertake

various sensitivity analyses.

As far as we know, this is the first comprehensive exercise

of its nature in Nepal in which a macro-economic and an

input/output planning model have been constructed separately and

integrateci. subsequently with special focus on a long term

industrial plan. It had been a challenging task in many ways. The

poor <lnt~ base nnd the very limited experience in Nepal in model

building were considered by many as ~nsuperable difficulties in

undertaking this exercise. Doubts had also been expressed in some

quarters about the validity of the models constructed on the 1

basis of data series built up on various assumptions. However, it

is needless to point out that unless a beginning is made now, it

may be impossible to introduce quanti ta wive t~chniques in our

planning and policy analysis in the near future. One ~Jditional

advantage of such an exercise is that it facilitates to pinpoint

the nreas where the data gtLp is more severe and further survey

and research work is required. From these broad perspectives,,

therefore, we hope that this effort undertaken by us to construct

the macro nnd input/output models and their subsequent

integration, consistent with both the theory and economic reality

(viii)

I I I I I I I I I I I I I I I I I I I I I

of Nepal, will make a significant ccntribution in the field of

research, policy analysis and planning. To us, it has been a very

satisfying and rewarding experience.

Because it is in the nature of an initial effort, we ~laim

no perfection to the models 2onstructed by us. We are conscious

of several limitations arising from inadequate data base and

other infirmities. But we hope this exercise provides a stimulus

to further work in this direction, leading to updating,

improvement and refinement of these models. We would welcome

suggestions and critic isms which could he!.p to improve the

models. After all, the construction of models should become a

regular feature of economic planning in future years.

During the course of model construction, sensitivity

analysis and policy simulation, the study team benefited

considerably from valuable suggestions provided by the Advisory

Committee chaired by Dr. B.P. Dhital, Vice-Chairman of the

National Planning Commission. Through the entire period of the

modelling exercise, the study team received sustained help and

support from Dr. B.N. Chalise, Joint Secretary, Ministry of

Industry, Mr. M. Satyapal, CTA and Mr. Arjun Upadhya of UNIDO.

Dr. S.H. Park of UNIDO and Dr. S.P. Gupta, International

Consultant provided valuable guidance to the s+-,udy team during

the course of model construction, policy simulation and

finalization of the report. The study team is very grateful to

all of them. We are also grateful to a number of national and

international experts for their constructive comments and

suggestions during the period of model construction.

The project team would also like to thank the Nepalese and

international experts who participated in various seminars

organized during the course of the study. The study team also

( ix)

·1


expresses its gratitude to the various institutions for supplying

necessary data and valuable information. Finally, we would like

to put 011 record our appreciation to the UNIDO headquarters for

entrusting us with this pioneering task which was also aimed at

developing and enhancing local expertise in the

of model building.

technical area

November 1990 Kathmandu

( x)

Dr. Dilli Raj Khnnal (Project Coordinator)

I I I I I I I I I I I I

MODELLING TEAM*

Dr. D.R. Khanal Froject Coordinator/Modelling Expert

Dr. Sharad Sharma

Mr. Ram Krishna Neupane,

Mr. Pra4ash Sapkota

Mr. Hari Bol Shrestha

Mr. Kapil Lohani

Research Assistants

Mr. Dinesh Khanal

Mr. Rabi Lal Bhusal

Mr. Babu Ram Khanal

FCA

Developm£at Economist

Financial and Cost Accounting Expert

Trade/Industry Expert

National Accounts Expert

Computer Specialist

Mr. Sushi! Dahal

I Mr. Bimal Banjade

I I I I I I I I

~~~~~~-~~--·~~~~-

Dr. G.N. Sharma (Macro Economist), Dr. Kiahore Gurugharana * (Modelling Expert) and Mr. Hem Raj Khare! (Computer Specialist) were also associated with the modelling team in the early phase of the project work.

(xi)


Chapter I

INTRO;JUCTION

1.1 Need fo!: the Study

Industrialization has been historically a well-trodden path

to economic development. Its vital role in the structural

transformation of developing econoaies has found general

acceptance among econoaic planners. Industry contributes in aany

ways to the accelerated growth of the econoay. It produces a

wide array of goods and ~ervices for consumers. It supplies a

vast range of intermediate goods and capital goods to other

sectors of the economy such as agriculture, aining, construction,

public utilities and services, as well as numerous manufacturing

industries within its own sector. Also, the most dvnar.ic

technological changes usually originate in the manufacturing

sector and sp!"ead to the rest of the econoay. Because of

symbiotic relationships between industry and the rest of the

economy, it seems almost impossible to consider industrialization

issues in general and industrial planning in particular in

isolation from the macro-economic context.

It is in this context that the construction and uEe of a

macro-econometric and an input/output model were considered

essential for long term industrial planning within the overall

macro-economic framework. Such modelling exercises would enable

us to derive policy implications of alternative industrial

development strategies and to check and ensure the overall

consistency and feasibility of each alternative strategy in the

light of various macro-economic constraints imposed by both

external and internal conditions.

In the past, some modelling exercises of the Nepalese

e~onomy had been attempted. For instance, an input/output table

for the country was constructed in 1981/82 by local experts which

1


was the first attempt in this direction (Khanal D.R., Thapa.

P.J., Elbers. c.; 1988). But the sectoral breakdown was too

aggregative to be useful for the purpose of industrial planning.

Though subsequently ~his was updated on the basis of 1986/87 data

(Khanal, D.R., Bade, J., Elbers, C.; 1989), the proble• of

disaggregation and data gap still reaained. At the saae tiae,

efforts were also made to develop a aacro-econoaetric model, but

these were mainly in the form of single equation aodels and hence

of limited utility for intersectoral analysis.

This study is the first of its kind in that both a

comprehensive 51-simultaneous eq~ation macro-econoaetric aodel

and 39-sector input/output aodel were join~ly developed and

linked together to derive policy implications of alternative

development strategies at the detailed individual industry levels

as well as at the overall economy level.

1.2 Objectives

The main objective ~f this modelling exercise is to identify

the policy measures to accelerate and sustain the

industrialization process consistent with the overall development

objectives of Nepal. The development objectives of Nepal entails

(a) rapid economic growth, fully exploiting Nepal's compa1·ative

advantages; (b) to generate high employment; (c) to develop a

viable foreign trade sector and earn sufficient foreign exchange

and (d) to alleviate poverty.

Accordingly, the modelling exercise aims to identify and

quantify the kind of industrial and aacro-economic policies

needed to attain these development goals.

This modelling exerrise may prove to be highly useful not

only for mapping out a viable long-term industrial development

strategy, but also to expand and improve the existing data base

and information network on which policy-making decisions

critically depend.

2


1.3 Scope of the Study

i. To develop and iaprove the data base for the aodelling

exercises.

ii. To construc-t a 39-sector disaggregated

table for the econo•y for 1986/87.

input/output

iii. To develop a 51-si•ultaneous equation •aero-

econo•etric model.

iv. To link the econoaetric aodel with the input/output

aodel.

v. With the aid of a •acro-econo•etric aodel linked to an

input/output table, to run si•ulation exercises under

alternative policy scenarios to assess the overall

aggregative and sectoral iaplications of alternative

development strategies.

vi. Based on simulation exercises, to foraulate a set of

policy recommendations for a long-term viable

industrial developaent strategy.

The scope of the study as set out above would entaii the

following major tasks.

Historical Analysis: Analysis of various macroeconoaic data

on the sectoral output shares, employment, trade etc. for

manufacturing and non-manufacturing sectors to capture the

historical trend of economic and industrial growth and change.

Co•pilation of Data: Compilation and reconciliation of data

on manufacturing census, exports, balance of payments over time,

inter-sectoral investment, household expenditure surveys,

national income accounts, profit and loss accounts of different

enterprises etc. for the construction of the aodels coverinl the

pe~iod of at least 14 to 15 years. Also to undertake small

surveys, where data gap is more severe.

lnpul-Output Table: As an essential p~e~equisite to the

construction of the model, preparation of 39 sector inpu~-output

3

I I I table taking latest aanufacturing census data as a basis for

I I I I I I I I I I I I I I I I I

detailed sectoral disaggregation of the aanufa~turing sector.

Modelling: The developaent of a 39 sector input-output aodel

with detailed breakdown of the aanufacturing sector into 23

subsectors in order to ensure a reasonably detailed analysis of

the changing patterns of industrial developaent for a historical

period, and further to project the sectoral developaents and

changes into lhe future.

The sectoral classifications of the aanufacturing sector

adopted for projection and historical analysis are as follows:

t. Dairy Products 13. Footwear and Leather Goods

2. Canning 14. Ceaent

3. Other Food Products 15. Structural Clay

4. Grain Hill Products 16. Pharaaceuticals

5. Tobacco Manufacture 17. Chemicals

6. Beverages 18. Wood and Furniture

7. Tea 19. Paper and Printing

8. Sugar and Confectionery 20. Plastic and Rubber Products

9. Carpet.s 21. Basic & Fabricated Metals

10. Textiles 22. Electric and Electronic Goods

11. Garments 23. Industries N.S.B.

12. Jute Goods

The non-manufacturing sectors include

1. Food crops

2. Jute

3. Tobacco

4. Sugarcane

5. Other cash crops

6. Livestock ~ Fisheries

7. Forestry

8. Mining and Quarrying

4

9. Construction

10. Gas, Electricity and Water

11. Hotel & Restaurants

12. Transport & Communication

13. Wholesale & Retail Trade

14. Banking, Real Estate and

Dwelling

15. Governments services

16. Other services


Forward Projections: The developaent of forward projections

for a period of ter- years (1990-95 and 1995-2000) as representin~

the •ini•um time period required for exaaining a long tera viable

industrial development strategy.

For the projection of industrial growth, several si•ulation

runs need to be carried out under the following scenarios:

With respect to the growth of GDP: • a. Base run

b. Moder&.te growth rate (Alternative I)

c. Medium growth rate (Alternative II)

d. Minimum acceptable growth rate (Alternative Ill)

e. High growth rate (Alternative IV)

With respect to industrial developaent stra!egies:

a. Export-oriented develop•ent

b. l•port substitution oriented developaent

c. Combination of both.

Consistency Checks and Macro-adjustaents: To develop the

macro model in such a way as would facilitate the generation of

key macro-econnmic parameters such as consuaption, investaent,

money supply, prices, trade and current account balance for the

period 1990-95 and 1995-2000. This would help in selecting that

scenario which provides an acceptable growth rate within aoderate

rates of inflation and trade and current account deficits. The

final demand vectors of this scenario are then fed into the

input-output model fgr ensuring both inter-sectoral consistency

and overall macro-economic stability.

Derivation of Policy laplications: Based on the results of

the simulation runs, derivation of policy iaplications of

different development strategies.

5


1.4 Structure of the Report

Thia study has been divided into eight Chapters. The

present Chapter describes the objective, scope and rationale for

the study. The next Chapter characterizes the aajor features of

the Nt:palese econo~y along with an evaluation of the overaJ l

performance of the industrial sector and specific poli~y i~sues

related to industrial develop•ent. The structure of both aacro

econoaetric and input. ~utput aodels is described in the Third

Chapter including the linking of the two aodels. ThP. aethods

adopted fpr conslrucLing data bases required for the aacro

econoaetric aodel and the input/output table along with data

problems encountered in the •~delling exercise are explcined ih

Chapter Four and Five respectively. Chapter Six is concerned

with the validation of the aacro-econometric aodel to assess its

capacity lo replicate the past data and its predictive power.

Moreover, this Chapter also presents various alternati~e

development scenarios derived through the macro model. The

latter enables one to examine the broad policy iaplications of

alternative development strategies on various macro-economic

variables such as output, employment, consumption, savings, money

supply, prices, trade and balance of payaents as well as

differential sectoral and industry impacts. In Chapter Seven

reference run solution and sensitivity analysis of the

input/output model are presented. Conclusions and major policy

recommendations are given in the last Chapter.

6 ·I


CHAPTKR 2

NKPALKSK KCONOHY AND THB INDUSTRIAL STRUCTURE

2.1 Nepalese Kcono•ic Structure

There exists no general •odel that will apply universally to

all developing countries. Ee.ch country •odel has to take into

account the special socio-econo•ic conditions unique to

individual countries. Therefore, a brief review of the Nepalese

econoay is useful to define the context of the •odels atte•pted

in this exercise.

The Nepalese econoay today is confronted with severe

probleas of both long tera and short ter• nature. The econoay

bas stagnated at a very low historical growth rates of per

capita income, estimated at 0.5 percent per year in the period of

1965-1987 with a current estiaated per capita incoae of USS 170

(1). In terms of per capita incoae, Nepal is ranked today as

the second poorest country in the world. Not surprisingly, the

country is als~ equally lagging in social developaent as shown by

its unfavourable social indicators such as a low life expectancy

of 51 years, a high fertility rate of 5.9 percent and an adult

literacy rate of only 35 percent.

The ~tructure of production has shown little change in the

past three decades as the econo•y has been dominated by

agriculture whose share in GDP ranged between 57 and 65 percent

during the same period. Industry is still at a very early stage

of development mainly dominated by cottage and small industries,

and accounting for only about 6 percent of GDP.

Nepal covers an area of 147181 sq. km. with an estimated

population of about 18.5 million in 1989. ll is densely populated

and has a re la ti vely unfavourable ratio of cultivable land to

population, mainly because only 17 percent of the land is

( l) World Bnnk; Wor'ld Development Report, 1989

7


suitable for cultivation.

Economic growth in the 1980s was reasonably good, with an

average reoJ ~rowth rate of about 5 percent (Table 2.1). These

overall growth rates, however, tend to conceal certain basic

weaknesses of the Nepalese econoay. Several sources of the

underlyin~ weaknesses in the Nepalese economy can be identified.

Table 2.1: Selected Indicators of Nepal (1980-1988)

1.

2.

3.

GDP Growth rate per annua (percentage)

Current Cbnstant

GDP at current prices In million Rupees In million US S

GDP per capita (in US $)

1980-85

13.70 4.90

1979/80

4. Sectoral Share of GDP at Current Prices (percentage)

5.

6.

a. Agriculture b. Mining & Manufacturing c. Construction d. Transport & Communication e. Trade & Services

Expenditure Share of GDP at Current Prices (percentag~) a. Government Consumption b. Private Consum~tion c. Gross Investment d. Exports of Gcods & Services e. Imports of Goods & Services

Sectoral Percentage Share of Gross Domestic Fixed Investment (at Current Prices) a. Agriculture b. Mining & Manufacturing c. Transport & Communication d. Construction e. Trade und Services

* Revised Estimate

8

61. 80 4.50 7.20 7.00

19.50

6.70 82.20 18.30 11.50 18.70

30.30 1. 60

14.60 2.85

50.65

1980-88

14.61 5.10

1984/85

56.60 5.10 8.60 6.70

23.00

:).80 76. 10 22.90 13.60 21. 00

26.60 3.40

12.60 3.05

54.35

1987-88

17.23* 7.83•

69513* 2958•

164

1987/88

55.51 5.84 9.28 6.64

22.73

10.20 83.29 20.49 12. 19 22.25

28.90 5.60

14.60 4. 21

46.69

')


7.

8.

9.

10.

1979/80 1984/85 1987/88

Sa~·ing & Investment Share iPercentagc)

of GDP

a. Domestic Saving b. Gross Domestic ~ixed

Investment c. Rescurce Balance

Public Finance (Rs. in •illion) Government Deficit

11.80

15.80 - 4.00

150.00

14.00

21.10 - 7.90

1799.90

10.83

17.87 - 7.04

807.1

Consumer Price Index (1972 = 100) 177.60 280.90 409.30

Balance of Payments (Rs. in million) a. Commodity Trade Falance b. Services (net) c. Trade Balance d. Transfers e. Current A/C Balance f. Capital Flows (netJ

Official Private

g. Change in Reserve

- 2403.00 873.20

- 5022.20 1079.50

- 3942.70 760.90

- 9765.50 2211.70

- 1529.80 426.50

- 1103. 30 1129.70 1339.00 209.30 -26.10 -

- 3181. 80 -2315.80 2603.00

287.20 866.00

- 7553.80 1652.30 5901.50 8174.50 5646.70 2527.80 2273.00

Source: Economic Survey 1989/90; Ministry of Finance

The Nepalese economy is dominated by agriculture, and trade

ard services. The two sectors together accounted for almost 80

percent of GDP in 1988. The activities in trade and services are

mainly concel1trated in informal sector while those in

agriculture are of subsistence type. They together contribute

little to both the growth of tax base and export potential of the

economy, thus aggravating government deficits and balance of

payments problems.

Second, the government budgetary deficit which grew very

rapidJy in the 1980s is a matter of serious concern. Government

deficit al current prices rose over ten fold from Rs. 150 million

in 1980 lo almost Rs. 1800 million in 1985, and then declined

somewhat to the level of around Rs. 800 million (Table 2.1) in

1988. Undoubtedly this excessive demand induced by rapid

expansion of overall government deficits has created serious

inflationcry pressures. For instance, the consumer price index


(1972 = lCO) surged sharply from 178 to about 410 during the

period of 1980 to 1988, roughly an increase of over 200 points.

The growing budgetary deficit has been increasingly financed by

both domestic and external sources, particularly from easy credit

expansion of the banking system.

Third, the economy has experienced severe current account

deficit which increased almost six-fold from Rs. 1103 million in

1980 to Rs. 5902 million in 1988. This sharp increase in current

account deficit was caused by the unprecedented upsurge in import

demand coupled with a sharp escalation in public expenditure

during the same period. Fu~thermore, the large and widening

resource gap has been financed primarily by foreign grants and

loans. This aspect of financing the mounting import bill through

grants and loans underscored the balance of payment dificulties.

Finally, despite the steady growth in aggregate investment

accompanied by reasonable overall economic growth rates observed

in recent years, the economy has yet to show strong evidence of

structural transformation, bringing about perceptible change in

the sectoral share of GDP. In contrast, investment in

agriculLure was somewhat reduced in recent years in terms of its

sectoral share in gross fixed investment. Yet agriculture has

borne the brunt of employment creation supporting over 90 percent

of labour force.

In the light of the preceding discussions, the major macro

economic imbalances of the Nepalese economy may be summarised as

follows:

1. worsening trade imbalance;

2. growing government deficits; I

3. inflationary pressure building up; and

4. widespread unemployment and under-employment

(aggravated by high population growth).

2.2 Performance of the Manufacturing Sector

The manufacturing sector in Nepal is composed chiefly of

10


light industries with very little intermediate and capital goods

prcduction. The latest Manufact•.iring Census ( 1987) shows that

only about 137,000 workers are employed in the manufacturing

sector in the co~ntry. Also latest information reveals that 246

industries operating in 10 industcial districts throughout the

country employ less than 11000 workers in total (2). This means

despite the establishment of industrial districts, industries

have generated little employment.

Turning to individual industries within the manufacturing

sector, food and allied industries which have been dominated by

milling activities, notwithstanding their steadily decline over

time, still contribute by far the largest share in total output,

value added and employment (see Table 2. 2). Notably, the

reduction in the share of milling activities has been compensated

by textile, leather, non-metallic, tobacco and beverages

industries. But given the insignificant share of manufacturing

sector in total output and employment, the expansion that has

taken place has not contributed to any significant extent

either in self-sufficiency or in promoting diversified export-• oriented industries in the country. Though the share of

manufactured goods in total exports has remarkably increased to

the level of 63.2 percent in 1987/88 from as low as 9.7 percent

in 1974/75, this growth has largely been explained by the rapid

increase in the volume of readymade garments during the 1980s

based on imported cloth and other raw materials from India,

adding little to the value added of the Nepalese industrial

sector (Table 2.3).

(2) Ministry of Finance, Economic Survey, 1988/89.

11

I Ii I I I I I I I I I I I I I I I I I I

Table 2. 2: Principal Indicators Q.f. Manufacturing Establishmnets

(R&. i.n '0001 ----------------------------·----------------------------------------

1976177 ---------------------------------------------------------------------

Total Fi1ed Value Output I Capital I Added I Blp loJlelll I

-------- ·--------------------------------·--------------------------------------------------------------1. Food l Allied 3313048 84.09 7ZZ953 75.BZ 314698 59.11 10159 40.ZZ

Of Which Grain !!ills (3199887) (650607) 68.13 (273916) (15171) z. Tobacco l 11everages 59037 1.50 7496 0.79 14558 2.73 5158 10.29 3. Ttrtile, LeaUer l Allied 74431 1.89 4036% 4.%3 27305 5.ll mo 7.61 4. Vood I Furniture mm 1.97 ll911 l.Z5 33388 5.17 3094 &.17 5. Paper, Printing l Allied 14747 0.37 13940 1.46 4608 0.87 m1 4.01 6. Chemical, Plutic l Rubl:er 15489 0.39 JZ77 0.34 6%47 1.17 874 ) • 74 7. Phamceuticals 6961 0.18 zm 0.26 m& 0.75 m 0.51 8. Non-lletallic llineral Products 20!60 0.53 98ZZ 1.03 9303 ), 75 6019 11.01 9. lletal P!'Oducts 40053 I.OZ 14375 ).51 9791 1.84 990 ).98 10. Klectric l Blectronice 0 0 0 0 0 0 0 0 11. lliscellaneous 278117 7.06 IZ6873 13.31 10855d 20.39 7739 15.41

Total 3939955 100 mm 100 mm 100 50119 100

..................... _____________________________________________________________

1981/82 --------·----------------·---·---------------------------------------

Total Fi1ed Ytlue Output I Capital I Added I BlploJ1ent I

-------------------... -------... -----------------------------------------... -------------------·--... -----------I. food l Allied 4217746 59.42 638504 CO.ST 11Z6003 47.69 21761 Z!.52

or Which Grain !!ills (35856841 1mso41 (789154) m::o1 z. Tobacco l Beverages 986689 13.90 137519 8.80 523313 22.16 10986 J(.90 3. Tertile, Leather l Allied 657956 9.27 mm 13.80 mm 11.45 13569 18.41 4. Vood l Furniture 508347 7.16 50143 3.21 mm &.99 3705 5.03 5. Paper, Printing l Allied 79480 1.12 37104 Z.37 39900 1.69 zm 3.U 6. Che1ical, Pl11tic l Rubber 204068 Z.87 87543 5.60 79100 3.35 1330 1.80 1. Phar1aceuticals 16326 0.23 10209 0.65 4343 0.18 79 0.11 8. Non-lletall ic Mineral Products 130478 1.84 mm 10.34 49480 z.10 15156 20.56 9. lletal Products 185304 Z.61 75732 4.85 56155 2.38 3171 4.30 IO. Blectric l Klectronics 0 0 0 0 0 0 0 0 11. lliscellaneous 111775 1.57 148543 9.51 47544 Z.01 1589 Z.16

Total 7098169 100 1mm 100 zmm 100 73718 100

12


---------------------------------------------------------------------1986/87

---- -----------...... ------------------- ......... ------------------------------Total Fi1ed Value

Output s Capital s Added s llaploJlellt s ----------... ------... -------------- ... -----... -·---------------------------------------------------------------1. Food l Allied 6677915 49.33 1513146 32.6Z !453757 JZ.38 %4050 17.57

Of Which Grain llills 5Z95687 (341005) (9447821 1mo z. Tobacco l Beverages IZZ6Z55 9.06 381580 8.13 788750 17.57 10501 7.b7 3. Te1ti le, ~ather l Allied 2159489 15.!5 816672 17.61 877546 19.55 mza Zt.78 4. Vood l furn i lure 347100 Z.56 19Z403 4.15 135059 3.01 6004 4.3! 5. Paper, Print inc l Allied mm 1.90 ZZZ067 4.79 IOll6Z us 3953 1.89 6. Cbetical, Plastic l Kubber 807179 5.96 367616 7 .93 247637 5.5! 59Z3 4.33 7. Pbaruceuticals 55597 0.41 61311 1.32 18964 o.u 1086 0.79 8. No11-lletallic llineral Products 937984 i.93 713698 15.39 554930 11.36 44416 32.H 9. lletal Products 770990 5.70 261830 5.65 2ZZ490 t.95 5Z87 3.86 10. Klectric l Blectro11ics mm 1.58 7718% 1.66 63516 1.41 806 0.59 II. lliscell11.Deous 83935 0.6Z 306ZO 0.66 25686 0.57 957 0.70 -------------------------------------------------------------------------------------------------------

Total 13537599 100 4638185 100 1489497 100 136911 100

SolllCe: llanufacturing Census ![ 1976/77, 198l[82 and 1986/87

Tnble 2.3: Total Export & Its Composition

Year Tote! Raw Manufact. Export Materials Goods

(In. Rs. Million)

Raw Manufact. Materials Goods

8hare (Percentage) ---------------------------------------------------------1974/75 889.60 215.70 86.40 24.25 9.71 1979/80 1150.50 490.00 345.80 42.59 30.06 1984/85 2740.60 543.90 1162.50 19.85 42.42 1985/86 3078.00 474.20 1726.40 15.41 56.09 1986/87 2991. 42 608.17 1671.03 20.33 55.86 1987/88 4114.50 685.17 2598.50 16.65 63. 15


Turning to the composition of commodities exported to third

countries, it is worth noting that the importance of jute has

sharply declined from a sizable share of 27 .6 percent in total

exports in 1974/75 to a negligible ~.~ ~~rcent in 1987/88, while

the export of rcadymade garments has soared steeply in recent

years, from 0.8 percent to 36 percent during the same period (see

fable 2. 4) . The expor l growth of carpets was al so e'}ua 11 y

impressive, increasing its share sharply from 4.7 percent to 48

perccnL during the same period. In contrast, the export share of


handicrafts declined markedly from 10.5 percent to 2.1 percent,

during tne same p~riod, ralthough its value of export has grown

steadily from Rs. 17.5 million in 1974/75 to Rs. 53.8 million in

1987/88.

The only export item of manufactured goods to India has been

jute goods whose export value has been highly erratic as shown in

Table 2.5. Its share rose from 3.9 percent in 1979/80 to as high

as 36 percent in 1984/85, only to drop to 15. 2 percent in

1987/88.

Though the export trend shows the replacement of primary

agricultural goods by industrial goods, it also clearly reveals

the fragile base of the export sector, as it is dominated by one

or two principal commodities.

Table 2.4 Exports of Major Commodities to Third Countries

(Ks. in Killionl ... ------·------------·-------·-----------------------------------------·-------------------------- ... ·----------·

Total Kaw Jute Hide l ReadJl8de CarJeaua Vollen Year Bx port Pulses Jute Goods Carpets Skin Garaents Bandicraf t ( Lar1e I Herbs Goods -----·------ --------·----------·-------------------------------------------- .. ----------·------------------ ... ---lm/75 166.60 8.00 45.90 34.30 7.90 6.o: 1.30 17.50 6.70 9.90 6.70 1979/80 780.60 81.90 119.60 115.00 55.40 rn.60 7.80 43.00 16.40 1.50 6.70 1984/85 1119.00 108.60 249.40 m.9o 470.90 12. 70 14.60 0.80 4.60 1985/86 1762.50 240.40 28.90 376.40 233.20 803. 70 18.40 25. 70 0.30 3.80 1986/87 1668.80 100.60 21.60 627 .50 161.00 611.20 32.40 43.30 0.10 5.30 1987 /88 2546. 70 4.00 30.30 0.40 1223.00 165.40 916.00 53.80 20.00 0.20 9.00

Percentage Share of Major Commodities Exported to Third Countries

..... ---.... -......... -..... --.. -........... -- .. ---.. ----.. ---.. ---.... ------.. -·- .. ---- ............. -- ...... ---.. ----...... ----------...... -.... ---... ------- ........ -- ...

Raw Jute Hide l Read11ade Carde1u1 Voll en Year Pulses Jute Goods Carr~ts Skin Gar1ents Handicraft (Largel Herbs Goods .................................... ------ .......... -................ ---- .................... --- ................................................. --- ...... ---- ..................... -------------------------1974/75 4.80 Z1 .55 20.59 4. 74 3.60 c.78 10.50 4.02 5 .94 4.02 1979/80 I0.4S 15.32 14.73 1.10 27. II J.00 5.51 2.10 0.19 0.86 1984/85 9. 71 o.oo 0.00 22.29 21. 71 42.08 J.13 1.30 0.07 0.41 1985/86 13.64 1.64 0.00 21 .36 13.23 45.60 1.04 J.46 0.02 0.22 1986/87 6.05 1.30 o.oo 37. 71 9.68 36. 74 1.95 2.60 0.01 0.32 1987 /88 0.16 1.19 0.02 48.02 6.49 35.99 2. ll o. 79 0.01 0.35

--·--------·-·---·----Source . ~conomic Survey t988L89; Ministry of Finance .

I I I I I I I I I I I I I I I I

Table 2.5 Exports of Major Commodities to lndia

(is. in Billion) -------------------------------------------------------------------------------------------

Total llustard l Haw Jute Dried Year Kxporl Linseed Jute r.oods Gincer Ti1ber Rice Herbs !lee ----------------------------------------------------·---------------------------------------1974175 m.5o 29.40 29.00 Z83.ZO ll&.70 2.10 52.00 1979/80 1.]3.10 Zl.90 8.30 uo 136.10 Z.90 13.50 Zl.ZO 1984/85 m.zo Z5.70 43.90 Z60.00 38.10 25.70 ZS0..00 27.90 39.40 1985/86 m.10 58.ZO ".JO 167 .40 44.30 93.ZO l&.60 47.10 1986/87 498.ZO 103.10 14.50 164.00 47.50 14.40 8.10 46.60 1987/88 1241.40 141.JO 44.10 188.70 71.30 15.40 46.70

Percentage Share of Major Commodities Exported to India

1974/75 5.74 0.00 o.oo 5.66 55.%6 1277 0.45 10.15 1979/80 o.oo 10.z5 3.88 4.0Z 63.69 1.36 5.3Z 9.!Z 1984/85 3.56 6.08 36.00 5.36 3.56 34.62 3.86 5.46 1985/86 7 .69 0.30 ZZ.11 5.85 o.oo IZ.31 Z.19 6.ZZ !986/87 20.69 Z.91 . 3Z.91 11.54 0.00 2.89 1 .63 9.35 1987 /88 11.38 3.55 15.ZO 5.74 o.oo 0.00 l.32 3.76

Source: Kcono1ic Survey 1988/89; Kinistr1 of Finance

Similarly, the composition of imports reveals the very early

stages of industrialization in which the Nepalese P.conomy finds

itself. The share of manufactured goods in the total imports is

still considerable although it steadily declined from 39 percent

in 1974/75 to 29.5 percent in 1987/88. In contrast, the share of

raw materials has increased remarkably from 3.9 percent to 10

percent during the same period (see Table 2. 6) • It should be

noted, however, that the "raw materials" imports largely

represent the imports of semi-finished or nearly-finished goo<ls

which are used only at the very final stages of production, in

most cases, thus adding very little to domestic value added. Some

examples arc the imported steel sheets used for manufacture of

steel utensils, imported readymade foam cut into different sizes

of plastic slippers, transistor assembly parts, imported cloth to

I manufacture readymade garments etc.

I I I 15

I


Table 2.6: Total laport and Its Coaposition

Total Raw Manufact. Year Import Materials Goods

(Rs. in Million)

Raw Manufact. Materials Goods Share (Percentage)

---------------------------------------------------------1974/75 1814.60 70.80 707.60 3.90 38.99 1979/80 3480.10 126.90 1378.20 3.65 39.60 1984/85 7742.10 547.20 2827.50 7.07 36.52 1985/86 9341.17 494.89 3396.68 5.30 36.36 1986/87 10905.22 833.09 3890.80 7.64 35.68 1987/88 13869.60 1389.50 4098.30 10.02 29.55


The capacity uti lizat.ion of soae selected industries also

presents a very erratic movement over the years as shown in table

2.7. By and large, the capacity utilization in a nuaber of

industries has been low mainly Jue to poor management, lack of

investment planning, shortages of raw materials and inefficiency

in production.

Table 2.7: Capacity Utilization of Selected Industries

Name of the Industry

Bansbari Leather & Shoe Factory Shoes (150,000 Pairs) Processed Leather (1800000 Sq. Semi-Processed Leather (900000

Janakpur Cigarette Factory (5.25 Billion Sticks)

Brick & Tile Factory (Harisiddhi 20 Million)

Hetauda Textile Industry (11 Million Metres)

Himal Cement Company (128,400 MT)

Agriculture Tools Factory (260,000 MT)

(Percentage)

1980/81 1984/85 1987/88

98.76 Ft.) 96.85 Sq.Ft.) 52.87

39.00

49.20

28.70

70.71

19. 11

78.00 90.00 81.89

92.00

60.00

54.00

66.00

99.00

68.00 105.83

98.29

67.79

59.07

44.50

90.00

Note: Figures in brackets indicate installed capacity.

Source: ~co~Qmic SurVlU: 1988/89; Ministry of Finance

If)

I I I I I I I

The share of private sector aanufacturing in gross capital

for•ation has been growing very slowly and rose to 8.9 percen~ of

the total in 1985/86 fro• 2.6 percent in 1974/75, but declined

to 7.6 in 1987/88 (Table 2.8). The low gross capital formation

in private manufacturing sector is rartly explained by the fact

that investment in the services sector and particularly in real

estate ard dwelling continues to be aore attractive than

investment in manufacturing industries.

Table 2.8: Gross Fixed Capital Foraation in Private Sector

I I I I

Gross 8-ttic Piied CapiW

1. A&ricsltm, lunlill(, Foreatr7 l Piai1& Shre it Total

z. 111111ractarinc Am ii Total

3. Fiuace, hi lstate l Due Iliac am i1 Total

1!74/15 1919/IO 1914/15 1915/15 lSU/IT 1911/11

mz.oo mo. llO nn .ao 5%11.00 57"·'° 5'11.IO

aoo.oo m.oo muo ms.oo izos.oo mo.ao 47.ZI 34.11 20.Ui U.51 20.90 U.41

44.DO 47.00 214.00 m.oo 415.00 511.00 uo 2.14 4.91 U4 7.37 7.55

526.00 1025.00 1995.00 238'.00 %111.00 32'7.00 31.09 U.59 34.99 45.11 5U9 41.91

JU.DO m.oo zm.oo ll71.00 ma.oo mz.oo 19.03 11.09 Jt.97 U.31 Zl.'4 U.03 I 4. OOers

Am ii Total

I I I

Source: Central Bureau of Statistics

The low share of manufacturing in GDP can be attributed to a

number of factors. First, there is a chronic imbalance in the

external sector and the consequent foreign exchange squeeze,

while the absorptive capacity of the economy to impleaen~ foreign

I aided projects is qui le limited. Second, whercna the financial

institutions are sufficiently endowed with resources, the rural

poor which constitutes the target population for developing

I potential industrial entrepreneurs has very limited access to

industrial credit facilities. Third, despite the rapid

'population gr0wth, the shortage of trained manpower has impeded

the implementation of a number of development projects. Fourth,

'

heavy reliance o imported finished or semi-finished manufactured

goods in export8 has contributed little to the development of the

I I

I 7


industrial linkages in the econoay. Fifth, significant capacity

underutilization has prevailed in aanufacturing establ ishaents,

particularly in public enterprises. Finally, inappropriate and

conflicting policies pertaining to industrial, trade, fiscal,

foreign exchange and aonetary aanageaent have been detriaental lo

the rapid structural transforaation of the econoay in general and

the industrial sector in particular.

As a result, increase in output has not been comaensurate

with large increases in investaent, reflecting the aisallocation

of scarce resources.

2.3 Policy Issues for Industrial Planning

As of 1984/85 over 42 percent of Nepal's population is in •

absolute poverty, while rapid population growth, put at 2.66

percent per year, is worsening the already alaraing situation

every year. Against this background of widespread poverty, there

would be little prospects of alleviating it, if the present trend

continues. What is urgently needed is a substantially higher

economic growth rate than has been observed in the past. This is

possible only in the context of a higher level of investment and

towards this end, additional resources have to be mobilized both

internally and externally, while utilizing them more efficiently

and productively.

By and large, investment programs in the past were drawn up

and implemented without regard to considerations of overall

macro-economic implications and intersectoral consistency. They

also lacked the framework of medium and long term perspectives of

the Nepalese economy. Only within a broad national economic

framework, priority industries for development can be identified

and their feasibilities can be assessed. This is precisely what

this modelling exercise proposes to accomplish. It will attempt

to demarcate the role of manufacturing industries in a longer

term perspective of economic development, examine alternate

development strategies and policies, establish inter-sectoral and

intru-scctornJ linkages and indicate desirable investment and

IR


output targets and suggest the path to follow in the realisation

of these targets. This aodelling exercise will particularly help

to identify:

i. those industries with aaxi•u• backward and forward linkages

ii. those industries which are relatively labour intensive

iii. those industries showing lower ICOR i.e., high capital

productivity, and

iv. those industries which have co•parative advantages in teras

of export proaotion and iaport substitution.

19

I I I I I I I I I I I I I I I I I I I I , I

Chapter 3

POLICY PLANNING HODBLS FOR NBPALBSB RBFBRBNCB TO TUB INDUSTRIAL SBCTOR

3.1 Macro Hodel

BCONOHY WITH SPBCIAL

Models are quantitative tools generally used by national

planners to find solutions to a wide variety of econoaic planning

and policy issues. The nature of the problea is an iaportant

determinant in formulating the structure of the aodels and its

variables. Whether the problea is of short, aediu• or long tera

nature makes a significant difference to the characteristics of

the model.

Macro models are often influenced by Keynesian Incoae

Exper.di ture theory and, therefore, are applied to address short

term stabilization problems. Such aodels tend to ignore the

supply side of the econoay. However, the structural supply

oriented factors together with external factors are critically

important to a small country like Nepal. Hence, it is necessary

to take them into account in constructing the macro-model for

Nepal. Another important aspect which cannot be overlooked in

drawing up the model specification is the nature and availability

of time series data required for model estimation.

Since the model estimation primarily relies on national

income accounts and international trade statistics, its

specification is largely dictated by the way such statistics are

compiled.

The main objective of the macro model is to find out the

optimum size of investment in conformity with:

i. a tolerable rate of inflation;

ii. an acceptable ratio of deficit;

iii. a realistic level of foreign assistance;

iv. a stipulated rate of growth of per capita consumption

in order to increase the consumption level of poor

people; and

20


v. the ' fulfillaent of an acceptable level of eaployaent

generation.

The •aero aodel has been constructed based on data

pertaining to the period of fourteen years (fro• 1974/75 to

1987/88) and consists of the following aajor blocks:

1. Production and Expenditure Block

2. Money and Prices

3. Labour Market and Eaployaent

4. Foreign Trade

5. Government Revenue

6. External Balance

The model has been utilized to derive the following

important co-efficients; these are necessary for the Input/Output

model too:

1. Consumption propensity

2. Import propensity of aajor SITC coaaodities

3. Buoyancy of various taxP.s

4. Money supply

5. Prices . 6. Employment.

7. IGOR

8. Money-price deficit financing relationship

The basic concept of the model is given in the attached flow

chart. The flow chart explicitly brings out the possible trade

offs between a higher investment size and a lesser degree of

self-reliance from more external assistance, a more crowding out

of private investment, a lesser control on inflation and increase

in money supply. The key trade off can be illustrated by the

following identity:

Government Overall Budget Deficit = (Government borrowing +

Grants + Changes in Reserves) + (Private Sector Saving -

Private Sector Investment).

:l I

---------------------

"' ""

(~- •> _.

FLOW CHART OF THE MACRO MODEL

f GOP ( FC)) - ( IND'T) ~ flJDP -to ( mp>)

+ -------...~

+{8>+@

...... ,, --+ GNP

!IC

Tl•---- Kr* I ~ t::="\ ( IC + r1) '-!!./ ----,. 'a.I -R 1

IC • Copttol Stotll INDT• ln•eot TH 119 • ..,,.,.,. aevtn9 !IC • llrlvote C9M41n!pt I• Git • GO'tt· fttv1n111 GC • Govt. Col\h111ptlon GS • Govt. lovlnt

,. • ,.,.,," '°"'"' GI • Govt. lorrowlnt 0119 • Dtflilt ""9"°' GI • Govt,_,vtl't " . ,,,.,,,. " llP • loton u of flor Ml • Meney Su pply

I I

TT • ftot• of lnflOtlon M • ll111port1 E • lxperf'I

CTA • CurNnt Trontftr


Algebra of lhe Model

1. VAA

R-2

= 20914.777 + 0.359968 AGRIC(-1) (13.45)

: .93:DW = l.3l:F = 95

= Value Added in Agriculture Where, VAA

ARRIC(-1 > = One Year Lagged Cumulative Investment in Agriculture

2. VMM = 1643.242+0.5472033 MMIC(-1) (17.65)

R-1 = .96; DW = 0.73; F = 160.24

Value Added in Manufacturing and Mining Where, VMM =

MMIC(-1): One Year Lagged Cumulative Investment in Manufacturing and Mining.

3. VAC = 2729.9284 + 0.7373775 CONSIC(-2) (8.34)

R-2 = 0.87 DW = 1.50; F = 38.39 Where, VAC = Value Added in Construction

CONSIC(-2) = Two Year Lagged Cumulative InveRtment in Construction.

4. VASS = 25-1.8974 + 0.3133943 SSIC(-1) (22.65)

R-2 = 0.95; OW = 0.98; F = 261 Where, VASS = Value Added in Social Services

SSIC(-1)= One Year Lagged Investment Cumulative Investment in Social Services

5. VATC = 2899.2342 + 0.0190629 TCIC(-3) (4.37)

R-2 = 0.71; OW= 1.22; F = 13.12 Where, VATC = Value Added in Transport and Communication

TCIC(-3)= Three Years Lagged Cumulative Investment in Transport a:.d Communication.

6. VAFRD = 3268.2777 + 0.0466488 REDIC(-1) (9.65)

R-2 : 0.89; DW = 1.46 F = 51.07 Where, VAFRD = ~dlue Added in Finance, Real Estate and Dwolling REDIC = One Year Lagged Cumulative Investment in Finance,

Estate.and Dwelling

7. VAEG = 67.413964 + 0.032941 ELECIC(-3)

(9.42) R-2 = 0.90; OW= 1.31; F = 47.96

23

Real


Where, VAEG = Value Added in Electricity and Gas ELECIC(-3) = Three Years Lagged Cumulative Investment in

Electricity and Gas

8. VATR = 1308.4556 + 0.3786615 TRRADEIC(-1) (8.32)

R-2 = 0.86; DW = O.~g; F = 39.08 Where, VATR = Value Added in Trade, Hotel and Restaurant

TRADEIC(-1) =One Year Lagged Cumulative Investment in Trade, Hotel and Restaurant

9. PRVCR = 2066.8250 + 0.7442635 GNP (38.00)

R-2 = 0.99; DW = 1.57; F = 727.04 Where, PRVCR = Private Consumption GNP = Gross National Product

10. MS = -2065.7569 + 0.5386110 GFD(-1) + 1.3449761 PSCR (2.66) (15.60)

R-2 = 0.96;· DW = 0.85; F = 89.51

::: Money Supply Where, MS

GDF(-1) PSCR

::: 0ne Year Lagged Government Fiscal Deficit = Credit to the Private Sector

11. GDPDA = 8.1019040 + 0.0027294 (2.36)

0.6262734 GDPDA(-1) (3.63)

MS + 0.1219092 IMPI (2.19)

R-2 = 0.99; DW = 2.24; F = 309.12 Where, GDPDA = GDP Deflator, Agriculture MS = Money Supply IMPI ~ Import Price Index

GDPDA(-1)= One Year Lagged GDP Deflator, Agriculture

12. GDP,DNA = 38.343038 + 0.0104376 MS ( 7. 40•)

+ 0.0014734 NAGDP + 0.1926548 ( 1. 56)

R-2 = 0.98; DW = 0.96; F = 186.82 Where, GDPDNA = GDP Deflator, Non-Agriculture MS = Money Supply NACDP = Non-Agricultural GDP

lMPI(-1) (2.33)

IMPI(-1) = ~ne Year Lagged Import Price Index

13. CPI = -9.6270262 + 0.4722221 GDPDA + 0.6229494 GDPDNA

R-2 = 0.99; DW: 1.04; F: 1013.09 Where,


CPI GDPDA GDPDNA

14. LA

R-2 Where, LA VAA

15. LMM

R-2 Where, LMM VMM

16. LC

R-,2 Where, LC VAC

17. LTC

R-2 Where, LTC VATC

18. LTR

R-2 Where, LTR VATR

19. LEG

R-2 Where, LEG VAEG

20. LFRD

R-2 Where, LFRD

VAFRD

= = =

=

=

= =

=

=

= =

=

=

= = =

=

= = = = = =

=

=

= =

=

=

=

=

Consumer Price Index GDP Deflator, Agriculture GDP Deflator, Non-Agriculture

2.5204286 + 0.0001403 VAA (7.18)

0.82; DW 0.41; F = 30.72

Employment in Agriculture Value Added in Agriculture

-0.0137839 + 4.360E - 05 VHM (20.78)

0.97; DW = 1.007; F = 220.92

Employment in Manufacturing & Mining Value Added in Manufacturing & Mining

-0.0504756 + 2.722E - 05 VAC (8.87)

0.87; DW = 0.61; F = 44.28

Employment in Construction Value Added in Construction

-0.1695132 + 8.9111 E - 05 VATC (4.81)

0.70; DW = 0.27; F = 16.49

Employment in Transport and Communication Value Added in Transport and Communication

0.0065683 + 5.623E - 05 VATR (12.25)

0.92; DW + 0.65; F : 79.93

Employment in Trade, Hotel & Restaurant Value Added in Trade, Hotel & Restaurant

0.0018554 + 7.241E 06 VAEG (12.64)

0.93; DW = 0.73; F = 84.85

Employment in Electricity & Gas Value Added in Electricity and Gas

- 0.0219223 + 8.708E - 06 VAFRD (10.21)

0.90; DW: 0.84; F = 57.03

Employment in Finance, Real Estate and Dwelling

Value Added in Finance, Re~l Estate and Dwelling

25


21. LSS

R-2 Where, LSS VASS

22. MFS

R-2 Where, MFS GDP

23. MR

R-2 Where, MR VMM MR(-1)

24. MK

R-2 Where, MK FA MK(-1)

25. MMG

R-2 Where, MMG GDP GFD

2o. DT

R-2 Where, DT GDP

27, EXU

R-2

Whnrc, EXU

= =

= = = =

= =

=

=

= = =

=

=

= = = =

=

= = =

=

=

= =

=

=

=

- 0.1384708 + 0.0001340 VASS (25.35)

0.98; DW = 1.69; F = 326.17

Emplyment in Social Services Value Added in Social Services

- 1096.2734 + 0.0413758 GDP (9.29)

0.88; DW = 1.98; F : 48.10

Imports of 0 and 1 SITC Group Gross Domestic Product

- 588.01485 + 0.3521733 VMM + 0.4278029 MR(-1)

(3.07) (1.31) 0.94; DW = 2.49; F = 66.11

Imports of Raw Materials (2+4 SITC Group) Value Added in Manufacturing ~ Mining Lagged Import of Raw Materials

- 182.26349 + 0.4821908FA + 0.4050333 MK(-1) (5.76) (2.58)

0.98; DW = 1.10; F = 229.67

Import of Capital Imports (7 SITC Group) Foreign Aid Capital Imports, Lagged

3697.29 + 0.1203725 GDP+ 0.384129 GFD (4.31) (3.84)

+ 0.2516453 MMG(-1) (1.53)

0.96; DW = 2.07; F = 78.42

Imports of 5, 6, 8 and 9 SITC Group Gross Domestic Product Government Fiscal Deficit

-204.73266 + 0.0122368 GDP (8.16)

0.85; OW = 1.09; F = 38.24

Direct Tax Gross Domestic Product

- 25.735904 + 0.2077930 VMM (9.47)

0.88; DW = 0.49; F = 49.76

Excise Duty

I I I I I I I I I I I

VMM

28. ST

R-2 Where, ST GDP

29. AGT

R-2 Where, AGT TCA

30. TAF

R-2 Where, TAF IMPG

31. NTR

R-2 Where, NTR GDP

I Id~ntities 32. TVA

I I I I I I I I I

33. GDP

34. GNP

35. LD

36. !MPG

37. GR

38. GE

39_ GOVTS

40. GFD

41. INDT

42. CJ\B

=

=

=

= = =

=

= =

=

= = =

= =

= =

=

=

=

=

=

= =

=

=

Value Ad1ed in Manufacturing & Mining

- 497.34882 + 0.0289424 GDP (8.42)

0.86; DW = 0.56; F = 40.40

Sales Tax Gross Domestic Product

421.64242 - 0.0448668 TCA (-1.45)

0.43; DW = 1.44; F = 5.998

Agricultural Tax Total Cultivated Area

862.09407 + 0.0613430 IMPG (4.33)

0.67; DW = 0.95; F : 14.32

Tariff Revenue Imports ou Goods

- 912.00533 + 0.0336274 GDP (8.63)

0.86; DW = 1.65; F: 42.16

Non-Tax Revenue Gross Domestic Product

VAA + VMM + VAC + VATC + VATR + VAEG + VAFRD v VASS

TVA + INDT

GDP + NFI

LA + LMM + LC + LTC + LTR + LEG + LFRD + LSS

MFS + MR + MFL + MK + MMG

INDT + DT + NTR

GOVC + GOVGFI + GOVTRS

GR GOVC - GOVTRS

GE GR - FA

AGT + EXD + ST + TAE + OTR

EXPG + EXPS - IMPG - IMPS + NFD + CTA

'2 7

I


43.

44.

45.

46.

47.

48.

49.

50.

51.

TIR =

NS =

PRVS =

ISGR =

FA =

NAG DP =

AGDP =

PRVGFIR =

cs =

PRVS + GOVTS + "i<'A

GNP - PRVCR - GCVC

NS - GOVTS

TIR NS

GFB + GFG

GDP AGDP

VAA + AGT

TIR GOVGFI

GNP PRVCR - GOVC - PRVGFIR - GOVGFI - EXPG - EXPS + IMPG ,+ IMPS

28

I


~xogenous ~n~ fuadqgenous Variables of the Model

Endogenous Variables

1. VAA Value Added in Agriculture 2. VMM Vnluc Added in Manufacturing 3. VATC Value Added in Transport and Coaaunication 4. VAEG Value Added in Electricity and Gas 5. VASS Value Added in Social Service 6. VAFRO Value Added in Finance, Real Estate and Dwelling 7. VAC Value Added in Construction 8. PRV:R Private Consumption 9. VATR Value Added in Trade, Restaurant and Hotel 10. GDPDA Agricultural GDP Deflator 11. GDPDNA Non-Agricultural GDP Deflator 12. CPI Consumer Price Index 13. MS Money Supply 14. LA Labour Absorption in Agriculture 15. LMM Labour Absorption in Manufacturing and Mining 16. LC Labour Absorption in Construction 17. LMM Labour Absorption in Transport and Communication 18. LTR Labour Absorption in Trade 19. LEG Labour Absorption in Electricity and Gas 20. LFRD Labour Absorption in Real Estate and Dwelling 21. LSS Labour Absorption in Social Services 22. MFS Imports of 0 and 1 SITC Group 23. MR Imports of 2 and 4 SITC Group 24. MK Imports of Capital Goods 25. MMG Impo~ts of Manufactured Goods 26. DT Direct Tax 27. EXD Exci8e 28. ST Sales Tax 29. AGT Agricultural Tax 30. TAF Tariffs 31. NTR Non-Tax Revenue 32. GDP Gross Domestic Product 33. GNP Gross National Product 34. LO Total Labour Absorption 35. IMPG Total Imports 36. GR Governme11t Total Revenue 37. GE Government Total Expenditure 38. TVA Total Value Added at Factor Cost 39. GOVTS Government Saving 40. GFD Government Fiscal Deficit 41. INDT Indirect Tax 42. CAB Current Account Balance 43. PRYS Private Sector Saving 44. NS Nn tiorrnl Saving 45; ISGR Investment Saving Gap 46. FA Foreign Aid 47. NAGDP•Non-Agricultural GDP 48. AGDP Agriculturnl GDP 49. TTH Total Investment 50. PHVGFIR Private Sector Gross Fixed Investment 51. CS Cha11gc in Stocks

I


Rxogcnous Variables

1. IMPI Import Price Index 2. PSCR Private Sector Credit from Banking Systea 3. TCA Total Cultivated Area 4. NFI Net Factor Incoae 5. HFI Fuel Import 6. GOVC Government Consumption 7. GOVGFI Governm~nt Investment 8. GOVTRS Government Transfers 9. OTR Other Tax Revenue 10. EXPG Export of Goods 11. EXPS Export of Services 12. IMPS Import of Services 13. GFB Government Foreign Borrowing 14. GFG Government Foreign Grants 15. CTA Current Transfer from Abroad

Predeterained Yariablcs

1. AGRFC(-1) One Year Lagged Cumulative Investment in Agriculture

2. MMFC(-1) One Year Lagged Cumulative Investment in Mining & Manufacturing

3. TCFC(-1) One Year Lagged Cumulative Investment in Transport and Communication

4. ELECIC(-3) Three Year Lagged Cumulative Investment in Electricity

5. SSIC(-1) One Year Lagged Cumulative Investment in Social and Community Services

6. REDIC(-1) One Year Lagged Cumulative Investment in Finance, Real Estate and Dwelling

7. CONSFC(-2l Two Year Lagged Cumulalive Investment in Construction

8. TRADEIC(-1) One Year Lagged Cumulative Investment in Trade 9. GDPDAC-ll One Year Lagged GDP Deflntor, Agriculture 10. GDPDNA(-1) One Year Lagged GDP Dcflator, Non-Agriculture 11. GFD(-1) Government Fiscal Deficit, Lagged 12. MR(-1) Raw Material Import 13. MK(-ll CapiLnl Goods Import 14. MMGC-1) Manufactured Goods Import

The structure of the model is given above in the form of

behavioural equations and identities along with both endogenous and exogenous variables. In the model, there are 31 behavioural

equations against 15 exogenous and 14 predetermined variables. In

the model, production functions and other equations have been

specified in such u way as to facilitate the derivation of key

macro parameters such as output, money supply, prices, trade and current account balance. Likewise, in the model employment

:w

1

I


equations arc related to sectoral value added. On the whole,

macro model has been specified in such a way that i l helps to

examine various imbalances of the economy besides the implication

of key policy parameters and exogenous variables on major

endogenous variables such as output and employment.

3 • 2 !!!.l!_u I. Ou L pu L Model

A comparative "Static, Open Input-Output Hodel" has been

chosen in this exercise instead of a dynamic one mainly on

account of paucity of sectoral investment data in Nepal. The

model, however, has been closed in an indirect way by integrating

it with a macro econometric model when consistent relationships

among the outputs, consumption, investments, exports and imports

have been reached between major aggregate sectors and over the

projection period.

The basic message of a static input-output model is: given a

pattern of consumption, investments, exports and imports, there ' is always a consistent pattern of gross outputs which satisfy the

"demand-supply" balances in every sector of the economy at the

prevalent prices (i.e. base period prices).

Gross output plus imports (which constitutes supply)is equal

lo private consumption plus public consumption plus private and

public investments plus exports (which constitutes total demand:

both domestic and foreign)*. This balance is achieved in each

sector. This is an identity in which the import-export balance

is satisfied. In Prof. Chenery's "two gap" concept, this

relation automatically satisfies the "saving-investment" gap with

the "export-import" (i.e. trade) gap and, therefore, ensures an

equilibrium situation.

This type of models have become now a strong planning Looi

in most LIJC 's because by using such models, the planners could

* when Hlock changes have been merged with private

COJl8UR1ption.

:J I

I

I I I I I I I I I

ensure the necessary supply of domestic output and imports, given

the foreco.sted demand and, therefore, guarantee price stability

and an absence of any shortages and surpluses in every sector of

the economy. In terms of algebra:

X + M =AX+ C +I+ E ••.•••••••••••••••••••••• (1) or X AX = C + I + E M

or X = ( 1 - A)_ l [ C + I + E - HJ • • ( 2)

when C + I + E - M = F

Notations: x = c = I = E = M =

F --,

gross output vector of n sectors ( in the present exercise n = 39) consumption vector, both public and private investment vector, both public and private Export vector, both public and private Total import vector including consumption, investments, and intermediates, when Fino.I demand vector.

If however, the Matrix [A) is gross of imports then the

aij's will give only the total input (taking both domestic and

I foreign input to gross outputs), but if matrix [A] is net of

imports it will give only the domestic input to outputs.

I I I I I I I I I I

[A] matrix is the coefficient matrix of the actual

input/output flows. This has been explained in Chapter 5

(construction of the input output table).

matrix is that~aij < 1 and all aij < 1; ,.., This gives:

[l-AJ- 1 = 1 +A+ A2 + A3 ••• An,

when An -> 0

The property of [A]

When equation (2) is used, it would mean that in estimating

output for production of the stipulated demand, all the needs

for both direct and indirect inputs have been considered. This

means, the matrix ( l-A)- 1 gives the multipller i.e. express the

ratio of total/direct needs of production to meet certain demand

levels. Any column of the inverted matrix [i.e. (i (1-A)- 1 1 will

give the production needed in all sectors of the economy for

producing one unit of final demand for that production. The

I

I • I I I I I I I I I I I I I I I I I I I

diagt.•nal values will give the production needs in all the

secto1s, for producing one unit of final demand of the same

sector i~c!uding self consumption.

Alsebrl4 of the Input-Output Model:

In matrix r~rm, with n sectors:

X = (l-AR)- 1 (~cPC+,\iPI +,\giGI +,\eio<.TE +~eni(l-c()TE -4mc

6 TFM - mi J T FM ) .....•..•.••.•.•..••.••.•..•••••.••• l

When,

6.

( 2) Xkv

X = Gross output of any year (Endogenous Variable)

[A) = Input output coefficient matrix net of imported intermediate imports.

" (R] = A diagonal matrix given the ratio of import intermediate sector along the substitution in the

diagonal. ~ ... ~ -PC, PI, GI, TE, TFM are Private consumption, private

investments, government investments, total exports and total final demand imports (consumption and capital goods imports including net services) derived for any year fro~ the Macro econometric model.

c, i, gi, ei, eni, me, mi are normalized allocation vectors for private consumption, private investments, Government Investments, Exports to India, Exports to Non-India, imports of consumer goods & imports of capital goods respectively.

o(, is the ratio of total exports going to India, e is the ratio of consumer goods imports to total

final goods import; ~ is therefore ratio allocated to the capital goods imports at the bas~ year (in the

=

input output table year).

Gi..r at When x =

k = \' =

GDP =

factor cost ••.•• (2) Gross output vector transposed (Row) scalar parameter (endogenous) value added to gross output vector GDP estimated at factor cost in the Macro-econometric model.

(3) GDP mk : GDP + INDT ......... ( 3)

( 4) Intcrmcdinlc import vector = [M)X •.. ( 4)

33

I


3. 3 !_!!_L~~rulior! of Lhc Macro Hodel with the lnput-Oulpul Hodel

A Schematic Diagram is presented below to explain the inter

relationships between the macro and input/output model used. The

macro model focusses more on the supply side of the economy and

therefore, it throws light on whether stipulated targets in

aggregative term can be achie~ed given aac~o supply constraints

of the economy. On the other hand, the input/output model gives

in more detail, the implications of various demand components on

39 sectors of the economy. It particularly focusses on the

implications of adopting iaport subs ti tut ion and/or export

promotion strategies taking into account simultaneously their

implications on long term investment planning. The main

advantage of such simultaneous exercises is that they help to

bring together both supply side and deaand side to ensure

necessary equilibrium in the economic plan. To achieve this, the

macro-economic scenario developed through the macro model is fed

into input/output model so that overall consistency between

demand and supply could be established.

I


Policy Regime

nl

R (Technology ChongesJ

APC IV

4GC

ofM

INTEGRATION OF MACRO

AND INPUT OUTPUT MODELS

Model lnler--action

lnpul-Oulpul

Model

Ml (RI

60

--"II ICOR ...__. INU

m>T

·----6£

35

MACRO MODEL

GOP LAGGED •YEST HE NT

I

I I Notations

I I I I I I I I I I I I I I I I I I

I I I I

( ) GDP INV PC GC PI GI TFH TF A

= = = = = = = = = = = = =

ml = ICOR = VA = GO = INDT = NFI = R = Exo =

Signifies Parameters Signifies Scalar Values Sig~ifies Vectors Signifies Matrix (n * n) Gross Domestic Product Investments Privnte Consuaption Government Consuaption Private Investments Government Investaents Final Demand Iaports Exports Input/Output Ratios Intermediate Imports Incremental Capital Output Ratio Value Added Gross Outputs Indirect Taxes Net Factor Income Technology Exogenous

3.4 Sequencing of Models' Integration

The macro model (which has already been described) throws

out private and government consumption, private and government

investments, exports and imports, GDP as some of the many

endogenous variables, all in scalar terms.

These variables then enter ~he Final Demand Model which, in

simple language, means a conversion mechanism of the macro scalar

variables •into \'eetors, covering 39 s,ectors of the Input-Output

classifications adopted. These conversions can be done by

sophisticated methods using extended Linear Expenditure Systell'

(LES) or by simply adopting base period normalized allocation coefficients. In the present exercise, the second method has been adopted so far as the reference run is concerned. In the

alternative pol icy runs, given different policy regimes, these

allocation coefficients have been exogenously changed. The

details of these changes are explained in Chapter 7.

These vectors then enter into the Input Output model. In the

present exercise, the (A] is an import matrix net of intermediate

demand which Repnrntr.ly interacts with [ml] matrix. The input-

3£;

I


output model is e;ssentially a Leonticf inverse anrl works as n

reduced form equation structure.

The outputs of this model come out as a set of gross output

vectors. These then get transformed into a vector of value added

by passing through value added (VA) paraaeter matrix (diagonal).

Similarly these derived value added vectors pass through another

diagonal [ ICOR] matrix to provide estimate of gross and fixed

investment vectors. A similar •ethod has been applied to derive

employment vectors.

The derived value added (VA) generates revised GD~ and GNP.

If this derived GDP differs significantly from the GDP obtained

through the macro model, then it enters back into the macro model

and the whole interaction continues until the GDP derived from

macro model and that from input - output model almost converge.

In the convergence process, the value added ratios can also be

used as endogenous equilibirating variables.

3.5 Simulations

In the macro model, various alternative scenarios have been

developed. The results of one likely scenario which shows 4. 5

percent GDP (at factor cost) growth rate over the period 1990 to

1995 has been used as inputs to compute the reference run in the • input/output model. The techniq'ue followed to make various

alternative runs in the input/output model is presented below for

the purpose of illustration.

3.5.1 Reference Run

i. First of all, it is necessary to take reference run

simulation from macro model (growth of GDP = 4.5 percent at

factor cost). It gives PC, PI, GI, TE, TFM. Subsequently,

the X's (gross outputu), V's (value added), intermediate

consumption and capital goods imports, exports to India and

non-India arc calculated into detailed 3::1 sector basis by

sourccH over the years.

:n

I


ii. For seven sectors ICORs derived from macro model have been

used to derive investment basket.

iii. Taking the ICORs derived from detailed manufacturing sector

[eslimnted as It/Ot multiplied by (l+r)/r for any sector,

whc\1 I = total investments, 0 = gross outputs, r is the rate I

of growth ~ver observed historical period], the detailed

manufacturing investment growth over the projection period

has been estimated.

iv. Based on employment co-efficients calculated from

input/output table, the detailed sectoral employment figures

have also been obtained.

3.5.2 Alternative Simulations Al tcrnati ve simulation runs were run against the reference

run solutions. It was necessary to do so for examining the

precise implications of alternative policies on total output,

value added, investment, employment, trade etL. The input/output

model has been presently employed to undertake sensi ti vi ty

analysis on four alternate development strategies: (a) import

substitution (b) export promotion (c) a combination of both and

(d) poverty alleviation. These exercises have helped in assessing

the outward vis-a-vis inward looking development strategies in

the light uf comparative advantages of the Nepalese economy.

38

I


Chapter 4

DATA BASR OF THR MACRO HODEL

4.1 Introduction

The most important prerequisite to any modelling exercise is

an adequate data base which provides the different parameters of

the national economy. The poor data base and lack of sufficient

experience and expertise have been serious deterrents in the past • lo the construction of macro models of the Nepalese economy.

This, coupled with ad hoc procedures adopted in decision making

wi tho · t any rigorous analysis, did not provide the stimulus to

take up modelling exercises. Nonetheless some individual efforts

were made in the past to construct such quantitative models

( Khannl, 1988, Khanal and Sharma, 1989). They, however, lacked

sufficient disaggregation and detailed simulation exercise.

The macro model presented in the previous chapter was

specified broadly taking into account the availability of data.

Therefore, in most of the equations only one or two explanatory

variables were included. In some cases, suitable proxy variables

were considered in the absence of data of reliable quality.

In spite of these limitations, it has been possible to cover

both the demand and supply side of the economy at a reasonably

disaggregate level and over time. The latter was achieved by the

construction of necessary time series data.

The trade data were disaggrated in such a way that they

could brundly represent the consumption, intermediate and capital

goods separately. Besides appropriate export and import price

indices were constructed in order to use them in deriving trade

and foreign aid figures at constant prices.

As employment plays a significant role in alleviating

poverty as well as raising living standards of the pooplc, an

attempt wns also made to construct employment series. For this

:rn

-I


purpose, rt~course had to be made to a variety of data sources.

Indeed, this was found to be one of the areas where d~ta base is

extremely poor. Though it has not been possible to examine the

exter.t of underemployment, the series constructed made it

possible to derive average employment co-efficients for the major

sectors of the economy. These data series, thus, have helped not

only to identify the sectors where the data gap on employment is

serious but olso to compare the likely growth of employment vis

a-vis the addition to labour force.

Some salient aspects of the procedures adopted for data

assembly for the macro model are discussed in the following

paragraphs.

4.2 Dala Sources and the Tiae Period Covered ~ the Study

The main sources of data for modelling are generally the

secondary data resources. Thus, for the purpose of this study

data hss been derived largely from Central Bureau of Statistics,

Nepal Rastra Bank, National Planning Commission, Ministry of

Finance, Agriculture Marketing Department, Trade Promotion Center

and other national and international institutions.

For the construction of macro model, time series data over a

auff iciently long period are always preferred. Such data series

are necessary especially for unbiased and efficient estimation.

But because national accounts data estimated before 1975 had poor

coverage and also the methods used before 1975 and after 1975

were not compar~ble, no long time series data on foreign trade,

prices, labor force and employment etc. could be generated.

Therefore, the model had to limit itself to only the period 1975

through 1988.

4. 3 Methods usc_i.I. lo Minimize the Data Gap Problems

In spite of more recent data l . in the construction of

macro modr.l, Rome data gaps still rem, .· when the strt.~turc of

the macro model was finalized. The ~roblcm& manifested

them s c? 1 v c R i n L h c course o f e s t i ma t i n g prod u c t i o n as we 11 as

I 0

I


employment functions. The data on prices available from secondary

sources aJso could not fulfill the data requirements. This was

also true in case of government accounts and trade statistics.

The methods used to construct some important data series are

briefly explained below.

4.3.l Production Functions and Capilal Stock variables

The model has a pronounced supply orientation and hence it

specifies eight production functions on lines similar to sectoral

value added estimates in national accounts. At the same time,

care has been taken to specify the production functio~s in such a

wey that would facilitate the estimation of sectoral incremental

capital output ratios. However, because of the inadequacies of

the existing data base, it was not possible to derive sectoral

capital stock variab~es. To get over this problem, cumulat5.ve

investme:1t variables have been estimated as proxies to capital

stock variables by assuming certain life time of assets in each

sector. This method has been Jmmonly utilized by model builders

in other developing countries. From these series, it becomes

possible to estimate the capital productivity fairly easily.

I

However, these data are stil1 insufficient for the purpose

of forecasting and simulation exercises. In order to examine the

implications of different patterns of sectoral investments, it is

necessary to take into account the life of the existin~ capital

stock in different sectors and to construct replacement capital

series for each year. In the absence of data on existing capital

stocks in different sectors, the sectoral investment variables

for forecasting purpose were derived by subslracting the

replacement values from sectoral investment figures obtained from

the model.

4. 3. 2 F.s limn Lion of Sectoral Employment Series

An earlier mentioned, data base was found lo be extremely

poor in t.hc nrea of employment. In the absence of systematic

periocic RurvcyR,

avniJublc. The

no time series dutn on sectorwisc employment is

only source which is commonly used is the

I J

I


-I I

periodic population census data. But even in this case, no

consistent and comparable data series are available. For

instance, a comparison of population census of 1971 and 1981

indicates a declining trend in construction and industrial

employment. However, it is generally known that these are the

sectors in which there has been a significant increase in

empluyme11t. Therefore, the census results on sectoral employmeLt

du not alwa~·s provide a correct assessment of the factual

situation and therefore, cannot be made the sole basis of

computing inter censal growth rates. The discrepancy appears to

be due to different classifications adopted in 1971 and 1981

censuses. For instance, contrary to 1971 census, 1981 census

gives a non-classified employment figure which is comparatively

very high. Therefore, some sectoral adjustments were made on the

basis of IDS study and recent NRB household survey. Although

these series enabled estimation of preliminary employment co

efficients but they need further revision and updating.

Particularly for the purpose of preparing long term human

resource development and manpower planning, a detailed employment

survey will be found necessary.

4.3.3 Trade Statistics and Foreign Trade Sub-model

Nepal Ras lra Bank regularly pub! ishes trade s ta tis tics on

the basis of SITC classifications. However, these

classifications do not exactly match with the consumption,

intermediate and capital goods categories. Classification along

these categories is necessary to examine both short and long term

implicutiu11s of foreign trade on the e.:!onomy. In order to make

SITC classifications conform to these categories, suitable

classification converters were generated. For instance, 0 to 1

calegor i cs were considered as consumption goods, 2 and 4 were

treated as intermediate goods and SITC group 7 was considered as

capital goods category. Altogether all SITC groups were brought

into five categories including fuel and manufacturing goods.

• I I I I I I I I I I I I I I I I I I I I

4.3.4 Government Accounts

Thou;.!h nulionul accounts datu give information on government

consumption and invest.menl, they do not exactly match wi Lh

economic classification of the government expenditure. The

problem emerges because of non-availability of up-to-date

information on government transfers. Therefore, an indirect

approach was fol lowed to derive those transfers which ·•ere

estimated by substracting consumption and investment components

from lolul government expenditure. This also faciliatcd

estimation of aggregate saving of the government.

4.3.5 l~ice Indices nnd Time Series Data al Conslanl Prices

National accounts data provide only GDP deflators for

various years. Additionally, separate estimates of both

agricultural and non-agricult.ural dcflalors arc furnished in

national account estimates. Nepal Rastra Bank, on the other

hand, publishes Urban Consumer price index regularly. These

indices are nut sufficient to construct time series data at

constant prices. For instance, for building up investment series

at constant prices it is necessary to have a separate price index

for investment goods. No such index exists and therefore, it has

not been possible to derive the investment deflator.

agricultural and non-agricultural def la tors had to be

estimating sectoral value added and investment figures.

Hence,

used for

Likewise

for saving and consumption series, Urban Consumer price index was

utilized.

In Nepnl, no attempt has been made to construct export and

import price indices. But such indices are available from World

Bank publications. No detailed information, however, is

available from those documents regarding the methods followed to

compute them. In tli.e absence of other sources, these indices

have been utiliu~d to deflate foreign aid and trade data. All

the dulu series arc at 1986/87 prices. They have been brought ut

198fi/87 prices mainly to mukc macro model data comparable with

ltw i 11pul/output. .model.


The discussions in the previous paragraphs also suggest the

direct ions in which improvements would need to be made in data

coll eel iun and presentation by different authorities, so as to

impro\'C data availability and reliability for future macro

modelling exercises. More sepcifically, for time series analysis

and macro modelling, data base and its reliability should be

enhanced in the following areas:

a. For identifying Government savings, detailed analysis of

Government expenditure on the basis of economic

classification is needed. This task falls within the scope

of CBS activities.

b.

c.

d.

e.

r.

g.

h.

To facilitate resource planning, analysis of flow of funds

in the economy is essential. For this purpose, consumption

and savings by sector have to be estimated. This should be

done jointly by Central Bank and CBS.

Also, computation of investment by both destination and

origin is an essential requirement for realistic estimation

of lCOR. It also significantly helps the construction of

dynamic models. CBS should attempt to estimate time series

data on these lines.

CBS should attempt to work out realistic GDP deflators,

particularly investment deflators.

A reliable set of Export-Import Price indices needs to be

prepared to examine the price behaviour and terms of trade

in the economy. For this purpose, it is necessary that

Customs Oata are compiled by the Customs Department both in

physical and monetary terms.

IL ie also recommended that per unit prices arc compiled by

U~c concerned ministries for agricultural and industrial I

products (both wholesale and retail).

A comprehensive perodic survey is needed on employment by

sector with detailed classifications in terms of unskilled,

semiskilJeJ, skilled and profPssional catagories involved in

production and service industries in order to assess the

employm~nt trends in the economy.

Export - import data series should be developed by Customs

Department unJ/or Trade Promotion Centre and/or Central Bank


in a manner as to provide clearly the required data on

exports and imports of consumption, intermediate and capital

goods separately. To reduce the discrepency between data

furnished by NRB, TPC and CD, a uniform methodology of data

collection and presentation is highly recommended.

·15

1

• I I I I I I I I I I I I I

Chapter 5

DATA BASE 01'' THE INPUT /OUTPUT MODEL

5.1 lnlroducliun -·- -------

\\hi le the poor da tn base and non-aYai la bi l i ty of rel inble

t.inir• seri1~s dala presented se,·eral difficulties, as mentioned i11

the pre\· i uus Chapter, in the construction of the macro model,

they "'ere nol less daunting in the construction of the

iupu t/ou l.pu t mudc l. ln fact the se,·eri ty of the problem explains

why Nepal has not been able to construct an operationally useful

input/output. table in the past for planning purposes. Though a

small ant.I hi~h ly aggrcgath·e input/output table was prepared in

thr. past ( l\hanal ct al 1988), n number of estimation problems

werP .-111:011nl.1:r1·c1 and therefore, the model could not reproduce the

historical dul.a satisfactorily.

It has, therefore, not been an easy task to construct n 39 x

39 input/output table as a part of the present exercise. To do so

has meant ~ot only a great deal of examination of the available

secondary data sources, but also conducting mini-surveys lo

generate primary data to the extent possible.

Si11cc the main objective of this exercise is lo apply the

model for the purpose of industrial planning, efforts were

in the co11slruetion of the Input/Output table lo make

industrial sector more disaggregativc. l ll \' i CW 0 f

ma<lc

the

the I a\·nilubiliLy of ~uccessive manufacturing census results, this in

itself 1:as 11ot thought to present any major problr.ms. In deciding

I I I

Uw lcve I of di!'rng~rcgation in other sectors, a number of fuctors

w c: re I.' 011 s i d e r r~ d . U b v i o us l y , on c fa c to r t ha t c o u l d no t b c

ovcrloolwd was data availability. The other factors taken into

account. lH~re homo~cncity of output and input, the scope for

export oriP11Led urid import substitution activities und the

Jiul(a.l.(r> (both lmclo•ard and forward> llf one activit~· with another.

For p~;;un 1 >1f·, h'it.h r1 view Lo cxnrninc· t..hc Jir1kaJi!c be~'•ccn n1nJor

I c: a H h c r ops I as r· a"' nm t c r in l s I u n d mun u f n c tu r i n st i n c.l us t r i cs ,

I I

-I I I I I I I I I I I I I I I I I I I I

imporlanl eash crops were separated from other non-food

commodities.

In lhc nbs~nce of sufficient and reliable data to estimate

the cost structure of various sectors, several sources had to be

utilized including the results obtained through small surveys

undertake11 by the study team. To supplement, the Profit and Loss

accounts as well as balance sheets of both private and public

enterprises were analyzed with a view to arriving at the cost

structure of certain sectors. Because of the varied sources from

which data has been collected, the results should be regarded as

preliminary and far from conclusive. Consequently, these need to

be further updated and revised. For instance, the cost structure

of important sectors such as construction, transportation, real

estate, dwelling, social and personal services of private non

profit institutions, trade, hotel and restaurants which was

estimated partly on the basis of the results of such surveys do

need a second look.

Likewise, lhe study team faced considerable difficulty in

deriving tax rates and reclassifying data on imports of goods and

services to conform to selected sectors of the economy. In

particular, problems were encountered in separating intermediate

inputs from consumption and capital goods. The computation of

consumption separately for each commodity has not been possible • since national account estimates on consumption are derived

residually by subslracting investment from gross national product

and net imports. This procedure makes it virtually impossible to

estimate the consumption coefficient of each sector by origin

and hence, lhe discrepancy between output and input of each

sector could not al·so be examined. In the absence of such

detailed information from national accounts data, the private

consumption figures had to be derived residually for the purpose

of lhc input/output table. This is not an altogether

satisfactory approach. However, in the absence of other better

alternatives, this procedure had to be adopted, cross checked lo

some ex len l 1.1 i th Uw Nepal Ras trn Bnnk Household Survey dn la.

·17


5.2 lnpuVO_!!..lpul Table at Producer•s Prices I. Related Data

R_~qui rc•cnls

Il is possible to construct the input/output table at both

purchasers' prices :lnd producers' prices. Since all monetary

transactions arc valued at either the prices received by the

producers or lhc prices paid by the purchasers, the lablc can be

conslruclcd either way. In the nor•al course, however,

transactions are recorded in teras of prices paid by the

purchasers and therefore, input/output tables can be constructed

•ore easily al purchasers' prices. The difference between

purchaser's price and producer's price co•es fro• trade and

transpurlalion margin. As these margins differ significantly from

time to time, input/output tables based on producers' prices are

preferred lo lhosc based on purchasers' prices. Input-Output

tables prepared at purchasers' prices suffer in general from the

following drawbacks:

i. The input/output table prepared at purchasers' prices

portrays the trade and transport cost twice; once as the

output of lhe producing industry and again the input of the

same industry from trade and transport sector. The

input./oulpul table constructed at producers' prices is free

frbm this drawback.

ii. The input structure quoted in value terms can be directly

iratcrlinlu"!d with lhe physical units under producers' pricing

sys t.i"!m.

iii. As st.at.cd above ir1pul coefficients which are estimated at

purchasers' prices vary significantly. Therefore, only by

segregating marketing and transportation costs can input

coefficients remain stable, reflecting primarily the

prevailing te>chnology thus facilitating more realistic

projections.

In view of lhcse salient features, the study team

prcpurPrJ I.he: i nput-oulput laulc n.t producers' pr ices. For

Hect.oral r:1wfficie11ts of both trade and transport margins

c:alculutcd in standard matrix form.

·IH

has

this

were


5.3 ~_<,>ur_~~~ of !Jnlu:

In view of lhe availability of aanufacturing census, the

year 1986/87 has been chosen as the base year of the input/output

table. Alsu some information on construction and transport

acth·itics is a\·ailnble from CBS surveys. Moreover, studies on

produeliun cusls and returns in agriculture se~tor are also

avni lahle for various years from Marketing Department. Further,

lhr. ex tens i \"C household survey carried out by the Nepal Ras tra

Dani{ in 1983-8-1 also provides considerable information on income,

employment and consumption pattern.

All thes•.! sources were made the main basis for obtaining

ncccssar) data for the construction of the input/output table.

But as llw worl{ proceeded, the team quickly realized that there

were several data gaps. Thus, for exaaple, the manufacturing

census could not fully meet the data requirements of the input

oulput table with respect to industrial activities. A significant

lacuna is that the census has not covered the detailed cost

structure of different industries. Cost information pertaining to

private services, transportation, trade and other similar non

industrial costs such as rent, audit fee, advertisement etc. were

not available in the census data.

H c n c 4! , non - i n dust r i a 1 cos ts had to be es ti mated

independently on the basis of Profit and Loss accounts of various

enterprises and subsequently verified with the results of Annual

Survey of Industries of 1987 /88 which fortunately includes daln

on 11011-inc..luslriat costs.

For other sectors of the economy, there are not even census

data (as for th~ manufacturing sector) to fall back upon. Hence,

totals as reported in national accounts have been utilized so as

tu reconcile estimated figures on cost structure of different

sectors with th1! national account value added figures. For the

govcrrnncnt. scc:tor, dato. o.vo.iluble from Ministry of Finance and

Auditor· li!:111:ral'H Jlcport were analyzed, which were by anc..I large

l!l

1


sufficienl tu obtain the cost structure of government activities.

A brief (!Xplanation ol'l data sources and methods of

estimation is gi \"Cn in the following paragraphs:

5.3.1 Agriculture, Livestock and Fisheries

IJ1! I.a i lcr.J eos t data on agricul lure sector are avai !able from

Farm Ma11ugement and Annual Production and Cost Surveys undertakrn

by Agriculture Marketing Department. Latest information (1986/87)

available ira cost and production surveys has been fully utilized.

Cost and production surveys data together with Farm Management

Studies were found sufficient to examine the cost structure of

the agriculture sector. On the other hand, an analysis of cost

data pertaining to forestry and livestock showed that available

data was insufficient to make realistic estimates of cost

coefficients. The Master Plan on Forestry and Energy sector also

could not satisfy the data requirements. Therefore, for these two

sub-sectors (forestry and livestock), information from various

olher sources had to be assembled. Information available from

Agricultural Projects Services Centre (APROSC) and Integrated

Development Systems (IDS) studies were analyzed. In addition, a

small survey was also undertaken.

5.3.2 Industrial Sector

Dula for the· various industrial sub-sectors were mainly

obtained from tlae manufacturing census of 1986/87. Infor1&a ti on

relating to output, return to labour, gross fixed investment by

source and capital stock by major industrial activities was

available from this census. As mentioned above, this was not,

howcv~r, adequate lo derive the complete input and output . structure. The census excludes management and admi~islrative

cosLH viz. advertisement, audit and legal fees, telex and

tc I cphone chnrges, off ice rent and also depreciation and saJ cs

and r.Ji~it.ribution ct>sls. Further, census results have generally

proved incompl~te in view of the fact that non-industrial income

is also f!Xcludcd from the output. To fill this gap, data

co11t.ai11f!d in ,\nnual Survey of 1987/88 and balance sheets, and

50

I


Profit and Loss accounts of various industries operating both in

pri\•atc and public sector were utilized. Some difficulty was also

cxperieueed i11 the computation of tax rates as per input/output

sectors. This information is not readily available from the

manufacturiug ecnsus. Hence, a detailed exercise was undertaken

to estimate them from data collected from the Finance Ministry on

tax rates and revenue collection. This helped to meet broadly the

data requirements and to derive value added at factor cost.

5.3.3 Mining and Quarrying

The contribution of mining to the total economy is as yet

insignificant. At the same time, mining and quarrying activities

are scattered across the country in an unorganized manner.

Therefore, it has not been possible to collect consistent output

and input structure data from a single source. Necessary

information was collected from various sources and they were

reconciled with national accounts data.

5.3.4 Construction

Construction sector also consists of heterogeneous

activiiies ranging from constructdon of residential and non

residential buildings to engineering works, repairs and

demolition, coustruction of dams, roads and airports. The cost

structure of one activity is significantly different from that of

other activities. Further, in view of the fact that n substantial

share of building construction is undertaken in rural areas, the

cost structure of building constructio~ is also not uniform.

Hence, a uniform procedure for all construction activitieL cannot

be followed. Based on the same methodology as adopted in national

nccouut.s, a smnl 1 sample survey was carried out to derive the

cost structure uf different construction activities and this

information was further verified with CBS. The cost structure

thus derived js slightly different from national accounts

estimates. This is to be quite expected in view of the fact that

CBS has continurd lo base its estimates on cost structure data

developed more than a decade ago in 1976-77.

5 I

I


5.3.5 Electricity, Gas ~ Water

Data 011 input structure of electricity: gas and waler were

obtained from the balance sheets, Profit and Loss accounts of

Nepal Electricity Authority, Drinking Water Corporation and Gas

Compauies.

5.3.6 Trade, Hotel and Restaurant

In the input/output table, 1-\holesale and retail trade has

been separated from hotel and restaurant sector. Cost structures

of these activities were analyzed from balance sheets, Profit and

Loss accounts and other financial statements of trade and hotel

establishments operating in public and private sector. Cost

structure of a number of small hotels, restaurants, travel and

trekking agencies was also examined. For hotel and restaurant

sector the tourism study conducted by Nepal Rastra Bank (NRB) was

also utilized.

5.3.7 Transport and Communication

Various sources of information were used to estimate the

input structure of transport and communication sectors. At first,

balance sheets, Profit and Loss accounts and other information on

transport and communication sectors operating both in public and

private sectors were examined. The data so collected was still

insufficient to provide detailed cost data for taxis, rickshaws,

etc. Therefore, additional information from CBS survey was drawn

upon lo estimate cost structure of various modes of transport. In

spite of this, it was not possible to derive the cost structure

of pull-earls and portering. Further, the detailed cost

structure of other modes of transport e.g. horse, yak etc. used

in different parts of i,he country could not be estimated

sepurulely. Therefore, these activities have been excluded

though in aggregate they are captured in the total value added

eslimntes given ih national accounts.

5.3.8 rrnn~in~ Real Estate and Dwelling

For the banking sector relevant information from Nepal

Rast.rn Bani\ and other commercial banks, Securities Exchange

r:: ') ,,..,


Center and insurance companies was obtained and examined. Since

finance and insurance business is operating with a strong

institutional base in the public sector, no major data problem

for t.hese sub-activities was encountered. Some di ff icul ty was,

however, faced in the course of estimating cost data of real

estate and dwelling activities. This was natural in view of the

scattered nature of these activities all over the cuuntry. Data

problem in real estate and dwelling sector was resolved through

small surveys conducted by the study team in both rural and urban

ureas.

5.3.9 Indirect Taxes and Govcrnaent Services

In both macro and input/output models, government sector has

been treated separately in order to delineate the critical role

of govcrnmcn t in Nepal's future development. Al though the

expendi lure estimates are presented in the budget broadly in

conformity with economic classification, actual expenditure is

accounted and reported only on the functional besis in government,

documents. This makes the economic analysis of government

expenditure very difficult. Though the Central Bureau of

Statistics (CBS) estimates on government accounts are available,

they do not provide detailed information on government purchases.

Therefore, n detailed analysis of the budgetary rstimates of

Ministry of Finance (MOF) and Auditor General's report was

undertaken. This analysis helped to separate both current and

capital expenditures. As a result, not only intermediate inputs

purchased from various industries could be estimated but gross

fixecJ investment by source could also be derived. Ucsidcs, this

analysis also helped to examine the saving position. of lhe

government in addition to facilitating the separation of the

transfer component from other current expenses which have been

rising fast, in recent years. To present tax rates of both

inlerme<linte inputs and final demand components in lhe

input/output table, necessary information from lax, excise and

tariff departments were col.lectcd and analyzed. This analysis

made it. possil>lc t.o derive tax rates by each industry included in

the input./oulput lnble.


5.3.10 Private Services

Private services comprise heterogeneous activities such ns

privately run educational and health institutions, individual

mcdieul prncl i l i one rs, tutors, professional and legal services,

household domestic servacts, dry cleaning and laundry services,

hair dressers, tailors, blacksmiths etc. The input structure of

these diverse activities is not identical. Information regarding

the educational institutions was collected from the institutions

concerned. The input structure cf most of the service industries

was collectec from the tax department. Also for some activities,

small surveys were conducted.

5.3.11 foreign Trude

llcliable data on foreign trade is necessary to analyze in

detail not only the cost structure but also to explore the

possibilities of promoting export oriented and import

substitution industries ir. the country.

producing intermediate goods as well as

Such industries may be

final products. Also

from tl•c point of \·iew of separating domestic and foreign cost

components a detailed analysis of foreign trade is necessary.

Taking all lhcsc factors into account, a detailed analysis of

trade statistics obtained from Custom Department was undertaken.

This has hclpe<l le identify imported input components. For

i n d us t r i a l a c t i \' i t i es , the imp o r t co e f f i c i en t s de r i "'e d f r om

annual survey was also utilized lo make data comparable and

consistent. For. other sectors, information available from trade

' statistics was ut.il ized.

5. '1 ~~rn~o I idation of Data Base ~nd Estimation of J_nput/Output

Table --- ----·----

The i nput./output table has been disaggregated into 39

sectors of the economy. This disaggregative table has been

const.ruelf'd on tlw basis of cost structure duta computed on lines

di HCUH!·Wd aboVf!. Except for industrial sector whose intermediate

arid \'a I 1H: added components arc bnsed on census results, other

Hect.ors' r·o11trol totals i.e. value udded have been taken from

I

I I I I I I I I I I • • I I I I I I I I I

nationaJ aceounts data. The cost structuret on the other handt

has been inuepcndently estimated. Likewise, among the final

demand componentst investmentt exports and imports have been

derived frum national accounts data and foreign trade and balance

of payments statistics. As noted above, private consumption

figures fur cuch sector have been obtained residually i.e.

substrnc:tlng intermediate input and other final demand components

from total output of each row. In this way, the total output and

input of each ruw and column match one another, a prerequisite

to ensuring input/output balances. In most casest it has been

found that the cost structure data is comparable to similar

estimates made for other developing countries by national and

international organizations.

The first part 39 x 39 matrix - represents the flow of

domestic materials and services i.e. inter-industry transactions

between specified economic activities (Table 5. 1). The second

part of the table represents the import of raw materials and

serv_ces made by each economic activity. The import of materi&ls

and services from India is separated from imports from third

countries, as the two streams have different economic

implications. The third part of the table deals with the

absorpli 011 of primary factors in production process i.e. value

added components comprising compensation of employees, indirect

taxes net of subsidy (domestic, India and third countries

presented separ~tely), depreciation and operating surplus. The

final demand in the table represents private consumption,

governmer1t consumption, private fixed investment, government

fixed investment and exports (shown separately to India and third

countries). The last rows and columns of the table represent the

total output of each sector. In a nutshell, the input/output

table has been presented in rows and columns in the following

manner.

TotuJ intermediate demand + f'rivate consumption +

Governmcr1t consumption + Private capital formation +

G0Vf!rr1mc!11l capital formation + Exports (net of firrnl demand I

imports) = Total domestic inp1•t purchase + lnl.ermediate

• I I I I I

imports + Value added.

Pul differenll.'·,

Puymenls for lotal input for materials and ser\'ices + Wage

payme11L fur labour services + Indirect taxes net of subsidy

+ Depreciation on fixed investment and operating surplus = Tolal gross output

As nuled above, the input/output table is presented at

I producers' prices.#

I I I I I I I I I I I I I

The input/output table comprises 39 sectors; 7 for

agriculture and forestry, 24 for mining and manufacturing

industries, and one each for construction, gas, electricity and

waler, hotel and restaurant, transport and communication,

wholesale and retail trade, banking, real estate and dwelling,

government services and other services. The broad composition of

above sectors is as follows:

1.

2.

3.

4.

5.

6.

7.

#

F1Jo<1 Crop;;

Jule Crops

Tobacco Cr ups

Sugarcane

Other Cash Crops

Liveslocl{ and Fisheries

Fores tr~·

Pa~dy, Wheat, Barley and All Types of Food grains

Jute

Tobacco

Sugarcane

Pulses, Spi~es, Fruit and Vegetables etc.

All Livestock and Fisheries Products

Forest

TtH~ va J uc added figures for manufacturing sec lor given in inpul/oulpul table (Table 5.1) for the base year 1986/87 wi 11 11ot lH! found idcnlicnl lo the Manufacturin~ Census datn f'ul"n i Hh<!d b.v the CBS. The di fferencc arises on account of th(~ fa<;L that the value added figures reported by the CBS exc l udP non- i ndus trial i ncomc and expen9es. In some cases th<~Y do not ulso capture the unorganized sector fully because lhe coverage of the census excludes enterprises emplo~·i11f;{ lc~<.i than 10 persons and not using power.

fj fj

I

I I

_l ________ ~~~~--1

•


8. Mining & Quarrying

9. Dairy Products

10. Canning

11. Other Food Products

12. Grain Nill

13. Tobacco Manufacture

14. Beverages

15. Tea and Coffee

16. Sugar and Confectionery

17. Carpels

18. Textiles

19. Garments

20. Jute Goods

21. Footwear and Leather Products

22. Cement

57

All Mining and Quarrying Acth·i ties

Dairy

Canning and Preserving of Fruits and Vegetables

Bakery, Animal Feed Products, Vegetable Ghee, Noodles, Spices Grinding, Dalmoth and Snacks Products and All Other Food Products

All Grain Milling Activities of Food, Oil etc.

Cigarette and Bidi Products, Chewing Tobacco and Allied Products

Distillery, Rectifying and Blending Spirit, Alcoholic ar.d Wine Products, Beer Products, Soft Drinks and Carbonated Water

Tea and Coffee Packing and Processing Industries

Sugar and refineries, biscuits, Cocoa and Confectionery Products

Carpets and Rugs

Cotton Spinning, Weaving Processing and Finishing, Textiles, Knitting Mills, Other Textiles

Non Wearing Textile Goods, Wearing Apparels, Readymade Garments

Jute Processing, Jute and Other Coarse Fibres

Footwear Products of all types, Leather and Leather Products

Cement, Lime and Plaster


23. Mineral and Fuel Products

24. Phnrmacculiculs

25. Chemicals

26. Wood and Furniture

27. Paper and Printing

28. Plastic and Rubber Products

29. Basic and Fabricated Metals

30. Electric and Electronic Goods

31. Industries Not Specified Elsewhere

32. Construction

33. Gas, Electricity and Water

34. Hotel and Restaurant

35. TranHporl und Communication

36. Whol1~su1': and Rf!l,uil Trade

58

Structural Clay Products, Bricks, Roofing Tiles, Wall Tiles and Other Mineral Products Including Fuel

Drugs and Medicines of All Types Including Herbs Proce~sing and Ayu~vedic Medicine

Soaps and Detergents, Chemical Products Including Lubricating Oil, Bitumen, Fertilizer, Paints, Batteries etc.

Wood Furniture and Fixtures, Saw Mills and Wood Mills, Wood Cork Products

Paper and Paper Products, Printing, Publishing and Allied Industries

All Plastic and Rubber Products including PVC Cables, Household Plastic Utensils, Plastic Pipes, Galvanized Rubber Sheets, Foam Mattresses etc.

Metal Furniture and Fixtures, Structural Metal Products, Utensils Made of Brass, Copper, Stainless Steel, Aluminum Products etc.

Consumer Electronic Goods such as Television and VCR Sets, Radio, Communication and Office Equipment and All Electric Apparatus

All Industries Not Falling in the Above Categories

All Construction Activities

Gas, Electri~ity and Water

Hotel and Restaurants Including Trcltking and Tourism Activities

All Modes of Transportation and Communication A~livitics

All Types of Trading Activities

• I I I I

3 'i. Bural• i 11~, Real Es ta le & Dwelling

38. Government Services

39. Other Services

Banking, Real Estate & Dwelling Activities

Service A~tivities of General Government

Private and Personal Services Activities

I 5.5 Data Gaps

I I I I

In spite of continuous efforts made to expand the data base

and update lhc information, the estimates in some sectors are

based on weak data base. For example, this is true in the case

of forestry sector. Although information available from APROSC

and IDS studies was partly used, it is still necessary to obtain

more detailed info~mation on this sector. Similarly, it has

not been possible to get adequate information on livestock,

mining and quarrying activities. Surprisingly, even in sectors

like construction, transport and communication adequate

information on cost structure is not available. Likewise,

I information on trade, real estate, dwelling, pr·ivate services,

hotel and restaurants is also not available to an adequate

I I I

extent. Even the national accounts data are prepared on the

basis of a number of bold assumptions. In some cases the

estimates arc made on decade old cost coefficients. No attempt

has been made so far to estimate the tax rates by sectors.

It is not possible to derive 'investment data by source on

the basis of existing national accounts data. As a result,

I investment by source could be estimated only at the aggregate

I I I I I I

level. Conscqucnt.ly, the capital flow matrix could not be

constructed and the model had to remain static.

Major data gaps could be identified when an attempt was made

lo estimate separately the input components of various sectors in

Lerma of Jomcstic and imported inputs. Though the trade figures

are availnbJc in some great detail, these could not be readily

brou,l(ht into an input/output framework. Likewise, n major dntn

gup wus 1:xpcrieneed in estimutin.l( the consumption vectors for

each !iector of I.he economy. In the absence of these data, it is

;; !}


not possible to estimate the saving generated by each sector and

to crvss check the flow of funds from one sector to another. This

information is of particular importance to a c•luntry like Nepal

needing rigorous resource planning. For further re'\·ision,

updating and standardization of input/output table, it is

essential to fill the gaps in information as pointed out above.

This should be systematically attempted through central

statistical organizations such as CBS to ensure better planning

and policy analysis in future. Specifically, this task is

suggesle<l lo be performed in the following ways. I

a. CBS should attempt to estimat~ both output and value added

b.

c.

d.

for sectors other than manufacturing industries with a

reasonable degree of disaggregation so that the

construction of 1/0 table can be institutionalized. For this

purpose CBS should try to update cost structure of various

sectors regularly by undertaking periodic mini surveys.

Also from the point of view of estimation of 1/0 table at

producers' prices reliable iraformaticn on transport and

trade margin for different sectors is required. Such

information should also be collected and updated by CBS

regularly.

There arc certain sectors which need immediate attention,

especially for updating their cost structure. These sectors

include Mining, Forestry, Livestock, Transportation.

Construction, Hotel, Trade, Real Estat.e, IJwelling and

Pr i vale Services. Separate mini surveys for all these

sectors arc needed before attempting to update 1/0 table. In

such surveys special consideration should be given to

acquire information on domestic and imported inputs

separately.

CBS should also try to estimate tax rates by sector. For

thi~, a regular flow of infcrmation from Customs Department

i H 1u!1~d1·d. ~pcciully the physical uni ls of both exported and

imported commodities have to be regularly recorded by

Customs Department. Also a scientific method of data

pr·esf?rvalion should be devised so thut the information

col lcctr.d could be utilized not only to compute effective

60


e.

f.

tax r.i te b~· commodity but also to compute export - import price indices.

For the purpose of developing consumption sub-models and to

be able to follow standard methods such as LESt CBS should

make n beginning in analysing the information contained in

Household Surveys conducted by NRB. This may help to

identify the discrepency between CBS estimates made •

residually and actual information gathered through field

surveys. It will also help to update the 1/0 table which at

the momenlt is based on residual method adopted by the CBS.

Last but not leasLt a system has to be developed by CBS to

undertake periodic surveys specially taking into account the

data gaps as noted above for data reliability and adequate coverage.

fi 1


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63

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I I ~~~~~~~~~~~~~

64

• I Tible 5.1: lnrJti'?rtp!t hH~

-- ---------I &.se l~ar 1~~5: e7 l · · --------· ---· · --· -------------------- ---- ----- ---- --- -- --- ---- ----------------------- --- ----- --- ------- ----------- ------e~~ii!' C"".1!r~:!at ~~h~r Sub- rrinte ~rt. Frirate C11vt. ~·~! Smim Smices Tota! Cmutf. Cmuap. fixed fixed bl'Ortl l1~i1 Thid Sub-Total T~t•I !•'.!'.! ~ !amt. !amt. CouatrJ Outr.it I [,;~!I i~l

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I I

65


Chapter 6

VALIDATION OF THE MACRO MODEL AND POLICY SIMULATION

6 l Model Validation

The structure of the macro model has been briefly discussed

in Chapter 3. The parameters estimated separately for each

equation is also presented there. The model consists of various

blocl{s representing vroduction, demand, foreign trade,

employment, money supply and prices. In spite of model's

simplicity, statistical test such as R2, DW, F and t-Statistics

show that the individual equations and the parameters estimated

are statistically significant. But in the simultaneous systew,

it is necessary to test the overall fitness of the multi-equation

model, which is a precondition for examining the forecasting

ability of the model. This is needed mainly due to the following

reasons:

(a) the multi-equation model having the dynamic property has

strong feedback mechanism and hence even if all the

individual equations fit the data well and are statistically

significant, it is not guaranteed that this will lead to

replication of the same data when the model is historically sim1 lated;

(b) the tracking performance may not be uniformly consistent

among variables and may vary considerably from one variable

to another.

Due lo these reasons, the behaviour of the dynamic multi

equation simultaneous model may be completely different from the

single equation model. It is in this context the total

mathemctical solution of the simultaneous model is needed. This

is done through the simulation of the whole model. Given the

initial vu..i.ues of endogenous variables and time series for the

exogenous variables, the model is sequentially solved over sample

period lo obtain solutions for a set of endogenous variables

(both behavioural and identities).


There has been no prior attempt in Nepal at such detailed

simulalion exercise. A number of problems was encountered in the

beginning partly because of lack of sufficient experience and

party because of non-availability of an appropriate software.

Eventually, micro TSP package was used to undertake both

simulation and forecasting exercises.

Tai< ing into account the sample period of both endogenous and

pre-determined variables, a historical simulation of the model

was curried out covering the period of 1978 to 1988 to validate

the model. The validation exercise generated new data series

which were then compared with the original data. Interestingly,

in spite of model's simplicity and poor data base, the tracking

ability of the model was found to be extremely good. In dynamic

simulation, there is always a danger of large gap manifesting

over time among actual and simulated values due to (a) inability

of the model in tracking fully the turning pointR in the

movements of endogenous variables; and (b) the errors cumulated

over time and through successive substitutions of equations for •

the model solution because of the use of the lagged endogenous

variables generated by the model(!).

To begin with, the simulated and actual values of the

endogenous variables were graphically compared. Subsequently,

root mean square percent errors (RMSPE) were also derived to

measure the <lcvialion of the simulated variables from their

actual time path. Such errors were estimated using the following

formula:

RMSPE =

(1) For detnils see Economic Commission for West Asia: A Macro

Economclric Planning Model of the Syrian Arab Republic,

Lebanon, 1980 and also see R.S. Pindyck and D.L. Rubinfeld;

Economc_lric Models !lncl Economic Ft recasts, (McGraw-Hill Koga

KuHI in Lt.d.), 1976.

Ii 7


Where,

ys = the simulated value

ya = the actual value

T = the number of years in the simulation

It is possible to assess the overall fore~asting ability of

the model from this statistic. It not only reveals the accuracy

of simulation fit but also demonstrates whether the model under

consideration for policy simulation is fairly good to capture t~e

turning points.

The graphs showing both actual and simulated series of some

key endogenous variables are presented below. From the graphs it

can be seen that the erratic trends of some variables such as

government savi-ng, budgetary and current account deficit have

been fairly well captured by the model. It indicates that the

tracking performance of even the external balance sector has been

satisfactory. As expected, in many cases aggregate variables

track historical pattern better than their disaggregated

components. This is possible because of cancellation of errors

in the aggregation process.

Likewise, the RMSPE calculated for some of the important

variables clearly indicate that the errors are reasonably small

(Table 6. 1). A model designed for forecasting purposes should

have standard errors as small as possible. Thes~ results again

confirm that the model has a good forecasting ability. It is

worth mentioning that it is only seldom that the results show low

RMPSE in such exercises. Low Root Mean Square Error (RMSE) is far

more common because of cancellation of errors in the calculation

procc~s.

Ii 8

• I I I I I CD

CD

en Q.. 0 I ,.._ C>

a>

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0 ·~ a ~

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(!) I

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in 0 in 0 in ~ It"! 0 ~ N N - 0 0 0 - -

I I I I

I I 69

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lo :::> a 0 0:: a. -' <( z 0 -~ z (/) (/) 0 a:: (!)

"' 0 I() 0 N N - -

\ \ \ \ \ \ \ \ \ \

0 I{} 0 "' "' 0 0 -0

70

CD CD

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'<t CD

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-(J)

0 (l)

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UJ

- - - - ·- - - - - - - - - - - - - - - - :-

....,, ,.

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2·0

1·5

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/

BO

GOVERNMENT . SAVINGS . '··....;

Bl 92 83 84

, ....

85

.... ,,.

86 87 88 ~~~~~~~~~~~~YEAR

[-- GOVTS - - - - - - -GOVTSS j

S• SIMULATED

•

- - - - ·- - - - - - - - - - - - - - ·- - -

-..J

"'

GOVERNMENT FISCAL DEFICIT

2.0--~~~~~~~~~~~~~~~~~~~~~~~--~~~~..,

1.5

1.0

0.5

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- - - -.........

-1.or-----

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-2.0 78 79 80

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82 83 84

I

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I \ \ \ \ ,,, \ I \ \ I \ \ I \ \ I \

' \ \ I \

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86 87

\

' \ '

ea YEAR~~~~~~~~~~~~

I- GFD - - -GFOS I S • S IMUl..ATED

I

I· I I 1,

·I CD CD

(/)

I " 0.. I'- ~ CD

I U> 0 en CD Ill

·I 0 C> ~ ..J

0 0.. ::> I{) ~ :E

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I I 73

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-·

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" ...

1·5

l·O

0·5

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-0·5

-1·0

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-2·0 78 79

CURRENT A~C BALANCE

' .... - ' '

80 81

', ' \

82

\

' \ \ \

' ' ,. ' '-----,

83 84

.... .... ,

' ',·

85 86 87 88

~~--~~~~~~~YEAR~~~~~~~~~~~~~~~

[-CAB -----CABS I S• SIMULATED

I

I I I I I I I I I I I I I I I

Table 6. 1 ~_!>-~>-~ Hean Sgua_r_g Percent Error of Selected Variables

\'ariables

Vt\A

VMM

V:\FIW

VASS

PRVCH

MS

CPc

LD

IMPG

GR

GDP

GNP

(Agricultural Value Added)

{Value Added in Manufacturing)

{Value Added in Finance, Real Estate & Dwelling) {Value added in Social Service Sector) (Private Consumption)

Money Supply

(Consumer Price Index)

(Total Labour Demand)

(Import of Goods)

(Government Revenue)

(Gross Domestic Product)

(Gross Natipnal Product)

RMS PE

3.93

6.42

3.55

4.20

2.83

3.19

4.58

1. 77

8.76

5.44

2.95

2.88 ---- .. ---------------- -------------------------

6.2 Policy Simulali~~

Encouraged by lhe good fit of the model, various alternative

policy simulations were carried out. Essentially the model was

used tu examine the impact of exogenous policy variables on

crucial macro-economic variables such as output, employment,

money supply, prices, trade as well as current account balance.

As noted in Chapter 3, the major exogenous policy variables used

in the model were government investment, government consumption,

foreign a i cl, cxpor ls of goods and services, importsi of services

and external prices. In addition to base run, four al ternati vc

I scc11arios were developed on the basis of exogenously determined

lim<! path for· pol icy variables.

I I I I

Ttu: purpose of developing these alternative dccnarios was lo

cxumi111: Ltlf! possihl.c trade offs betwf'en fust<~r growth und

inflation and hetw1!<!n self-reliance and cxternuJ d<!JH!11dr.nc1:,

7 fj

I


II I

between labour intensive and capital intensi\·e in\·estmenl.

It may be seen from both equations and identities thal lhe

lolal irn·eslmcnl outlay is constrained by the le\·eJ of domestic

sa\·ings unu external resources. The internal savings arc in lurn

directly affected by the ~aving propensity of private as well as

go\·crnment sector. The model has attempted several sensilivily

analyses on lhe basis of exogenously determined sectoral

in\•eslmcnt distribvtion coefficients. They show lhe likely

impli<.:at.ions of lhe distribution parameters on capital

productivi ly and output in the various SP.ctors of the economy.

The policy issues are, thus, examined through changing the time

palh of exogenous variables or re11llocating the investment among

sectors.

6. 2. I Base Run Scenario

[n tables 6.2 and 6.3 the alternative growth rules as well

us sectoral allocation of investment assumed lo construct . exogenous variables are presented.

Table 6.2: Basic Assumptions

(Growth Rates Per Annum) Exo~enous Base Run Alternate Alternate Alternate Allcrnal~ Varjablcs I !.!. III lV -------

PSCH 9.89 8.00 10.00 12.00 12.00 GOVGFI 7.50 10.00 10.00 10.00 12.00 c;ovc 6.00 6.00 6.00 6.00 6.00 GOVT RS 9.00 9.00 9.00 9.00 9.00 GF<i 6.88 8.00 10.00 12.00 15.00 c:FB 7. 00 9.00 12.00 14. 00 18.00 NFJ 2.82 2.82 2.82 2.82 2.82 EXPG 6.00 6.00 7.00 8.00 10.00 EXPS 9.00 9.00 9.00 9.00 10.00 IMl'S 6.00 6.00 6.00 6.00 6. 00 MFL 9. 31 9. 3 1 9. 31 9. 31 9. :n I Ml' l 5.75 5.75 5.75 5.75 5.75 C'T/\ .00 .00 . 00 .00 .oo OTH 6.00 6. ()(} 6.00 G.00 6.00 TC:A 1. 22 j • 22 I. 22 I. 22 I. 22

I

I I I I I I I I

Table 6.3: Sectoral Allocation of Investment IFercentacel

------------ ... --- --- --- --- --- .... ----------------------- ...... --- ------------------------ ... ---------------________ ...... _ Altl Alt H Alt III Alt lY Alt H Alt HI Alt IV

Base ---------------- ------------------ --------------- ... ·---·-------Run 1990/95 1990/95 19951:000

-... -- ------ -- -- ---- -- ......... -------- -------·--- -·------------------·---... ---------------- ............. ---------------------A~ricdture .3018 .JZOO .m~ .JWO .3%00 .J:ou .noo .JZOO Mining l lndustu .cm .1000 .mo .1500 .1800 .1500 .1800 .:900 Electrici t; .1405 .1405 .1405 .1405 .1405 .1400 .1400 .1400 Construction .om .0400 .mo .0450 .0500 .0500 .0500 .0500 Trade .om .OZ55 .OZ55 .om .om .OJOO .0300 .0300 Transfcrt .1346 .1346 .1346 .1346 .1346 .1300 .1300 .1300 Rell.I Estat.e l Dwellir.g .Z499 .mo .1490 .1!90 .0840 .1100 .0800 .0600 Social l Ccuuni ty Services .om .om .om .am .0654 .0700 .0700 .0700 .................................................................................................................................................................... __________________________________________________

Total 1.0000 1.0000 l.0000 1.0000 l.OOOG [ .0000 1.0000 l.0000 --------- - - --------------------------------------------------------------------------------------------------

In the base run, past trends of most of the exogenous

variables were retained and the investment shares were derived

taking the average share of the recent past five years. A

I notable change, howev~r, was made in case of external borrowing.

I I I I I I I I I I

Ii

I l had shown an average growth rate of more than 20 percen l

during the period of 1975 to 1987; this high percentage was made

possible because of the initial low base to start with. It was

considered unrealistic that s~ch high rat~ could be maintained in

the future. The annual growth rate was therefore brought down to

7 percent for the period 1990 to 1995.

The base run resJlts are presented in table 6.4.

77

I

I


6.4: Base Run Results on Major Macro Variables

Endo(cnous V:i.ri11blcs

Rs in 1illicn (At 1986/87 prices)

1989/90 1990/91 1991/92 199Z/93 1993/94 mt/95 1990-95 Growth Rate

----------... --- ---------- -----------------------· --------------------------------------- -------------------------GNP 67787.84 69883.05 iZlll .74 ?4Z49.4Z 76619.Z7 79113.17 3.14 Priva' c Conmption 5Z518.85 54078.Z3 55736.97 573Z7 .9Z 59091.75 60947 .86 3.oz Pri vale lnvest1ent 8543.ZZ 8649.32 8761.46 88Z0.38 8960.11 8990.66 I.OJ Gcvern1ent Total Revenue 7027 .91 7363 .16 7716.56 8070.04 8457 .ZS 8868.24 4.76 l1ports of Goods 15099.41 16296.24 17543.88 18831.99 20Zl4.84 21691.73 7.5Z Current Account Balance -6196.89 -6755.36 -7313.10 -7855.86 -8431.75 -9038.11 1.84 Honer Supply 10534.30 11897 .60 13338.88 149ZZ.4Z 16672.44 18586. 73 11.90 Consumer Price lnder m.oz 137 .57 ISZ.18 167.99 185.41 204.Sl 10.35 Govern1ent Fiscal Deficit llZl.61 IJ44.Z4 1588.3Z 1874.85 2173.32 zm .o4 17 .37 Total ln1esllent 14351.@7 14893.62 15474.08 16036.45 16663.98 17329. 73 3.84 National Saving 7S86.8Z 8085. 7Z 8192.53 8248.Z8 8333.94 8420.13 1.06 Toltll Eaplo11ent 8.51 8.67 8.86 9.04 9.Z4 9.46 2.IC ------------------------.. ------ ... ----------------------- .. ---------------------------·----------------------------

It is evident from table 6.4 that if the exogenous variables

grow at the historical rate, the overall growth of GNP will be no

more than 3.14 percent during 1990 to 1995. At the same time,

the budgetary deficit will increase substantially over the 1987-

88 level an<l will reach around 3 percent of GNP by 1995. With

the increase in money supply by arour,d lZ percent, the rise :in

prices will also be around 10 percent per annum (Table 6.4). The

resul til also indicate that the overall employment can increase '

only at a rate below the population growth. This exercise thus

highlights that in a condition of neutral policy regime the

prospects cf the ~epalese economy are far from satisfactory and

in fact, likely to deteriorate.

6.2.2 Allcrnulivc Scenarios

The base run scenario waR obviously unacceptable. It was,

therefore, considered necessary to examine the effect of policy

intervention to stimulate economic growth to a more acceptable

level. J\ccorcJingly, four alternative simulation exercises were

carried out.

Thf! hjsturical trend is assumed to be modified by a

deliberate pol icy Jccision in two main directions uncJcr the

78

I

I

I I I I I I I I I I I I I I I I I I I

I I

alternative scenarios: firstly, in terms of aggregate investment

in the ecnnomy and secondly, by way of a reallocation of

investment among different sectors.

The basic assumptions underlying the alternate simulation

runs have already been set out in Table 6.2 and 6.3.

As will be seen from table 6.2, Government investment and

private sector credit are progressively increased from one

al ternatl ve to the other. To support these larger investments,

foreign grants and borrowings are also assumed to be stepped up

progr~ssively. A significant growth in exports of goods and I

services is also assumed. Most of the other variables are assumed

to remain constant at the historical trend rate.

The shifts in the allocation of investment will be evident

from Table 6.3. The most significant change is a progressive

increase in the mining and industry sector and a sharp decline in

investment in the real estate and dwelling sector. A moderate

increase i u the construction sector is also assumed. The trend

rate has been maintained more or less constant in other sectors.

The significant changes in sectoral allocations were

~onsidercd necessary in view of the predominance of investment in

real estate and dwelling activities within non-agricultural

sector. Obviously, this trend was sustained due to the

prevalence of policies which encouraged and attracted private

sector investment in less productive but quick yielding

activities. This is corroborated by the incremental 1.Japital

output ratios derived from the macro model (see table 6.5).

Table 6.5: Sectoral ICORs Derived

J\~riculture Miniug & Industry Construction F.lcclricily Transport & Communication Trade, Hotel & Restaurant Finance, Real Estate & Dwelling Private & Community Services

79

2.78 1. 84 1. 36

33.0J 20.38 2.67

21. 4 3 3. 19

I


The results obtuined from the macro model show that with the

exccplion of lhe electricity sector, the real estate and dwelling

scclur hud lhe highest ICOR. Surprisingly, mining and industry

scclur has u very low

i nves tmcn t has been

ICOR and it is also the sector in which

very low in the past. This anomalous

siluuliu11 did indicate the need for a drastic correction.

Accordingly, it was decided to increase the level of investment

in ind us try and to reduce it substantially in real estate and

dwelling. As will be seen from table 6.3, the share of real

es ta Le has been decreased to 6. 4 percent in 2000 in the last

scenario from us high as 25 percent in 1990. On the other

hand, the share of industry has been increased substantially to

r~ach 20 percent in 2000.

The results of alternate simulation runs in terms of major

economic indicators are ~resented in Table 6.6. A comprehensive

set of forecasts obtained for endogenous variables arc given in

tables al the appendix.

Table 6.6: Results of Alternative Scenarios (Growth Rates Per annum)

. ----- --- - --- - - - --- - --------.. -...... --·------.. ___ ........ -........ -------·--- .. -........ ------------· ...... -........................... -.. --- .............................. ALT I ALT II ALT II ALT III ALT Ill ALT IV ALT IV -------·----·--------·-·--------------·------------·-------------··------------

fofow.ous Variabl~s 1990-95 1990-95 1995-2000 1990-95 1995-2000 1990-95 1995-2000 --.. -------------------------- - ----- ------ ........ ------- .. ---.... -- .... ----- ...... ------------- --- -- ---.. ---- -.. -.... -....................... -.... ---r;~;p 3. 967 4.25 5.7Z 4.75 7. 49 5 .48 8.66 Private Consumption 3.822 4.09 5 .56 4.57 7 .29 5.29 8. 43 rriv:itc lnvest~cnt 9.857 6 .16 8.7Z 9. 75 13 .39 13 .94 17 .25 GomM~nt Total Revenue 6.503 7 .08 8.49 8.12 10.51 9.55 12.27 foporls of Goods 9.287 10.34 10.45 11.32 12.04 13 .28 14.01 Current Ace0unt Balance I I. 930 Jj,42 12.99 14. 74 15. 53 16 .35 17. 93 Konry Supp If 9 .648 10.87 9 .89 IJ.06 11.0 I 11.83 9 .05 Cnns1111~r f'rir1: lri·lcx 8.322 9.17 8.59 JO. 79 9.28 9 .57 7 .15 Tot:il lnv•·sl,mrrit 5. 643 8.23 9.31 10.27 12.0Z 13.92 15.24 N:itin11.1l Sa'lin~ 2. 973 J.60 6.54 4.70 10.12 6.Z9 12.12 Tot..11 Emplo1mt 2.m 2.62 3.72 2.84 4 .66 3.19 5. 73 . -- -. --- --------------------.............................................. -·- -- ............................................................ ------------ .........................................................

Th!~ altcrnalivc simulation runs throw up some interesting

resultH whi"h have a decisive influence on the economy. The

80

I

I

I

I I I I I I I I I I I I I I I I I I I •

I

salient points may be summarized as follows:

1. The rate of investment in the economy will have to be

significantly stepped up even to attain moderately

respectable rates of growth of GNP. For example investment

rate has to be stepped up to 14 percent to secure a growth

of 5.5 percent in national income (Alt. 4). The latter is by '

no means high when compared' to the growth rates actually

achieved by other developing countries.

2. An appreciable increase in national savings is essential to

support the larger level of investment (notwithstanding

substantially higher inflows of foreign and). The saving

rate has to be stepped upto 5 to 6 percent (as compared to 1

percent in the base run) for the next five year period

(1990-95).

3.

4.

5.

6.

7.

8.

Even so, growth in employment will be only at the rate of

about 3 percent per annum. In other words, it will take a

long lime before the employment problem can be adequately

dealt with.

However, a significant upward trend in investment and

national income over the next five years will have a

multiplier effect in the following quinquinium. In all the

alternatives, it will be noted that the national income

grows much faster during the period 1995-2000.

The country will continue to need substantial foreign aid

for the foreseeable future. This will have to be in the form

of grants and soft loans, as otherwise balance of payments

situation may turn out to be unsunstainable due to rising

debt service ·obligations.

This is highlighted by •~e fact that in spite of u growing

quantum of foreign aid and significant step JP in exports

assumed in the simulation runs, thr current account deficit

tends to grow at a fairly fast rate.

l!nder al 1 the four scenarios, the rate of inflation seems to

be clos'i to 10 percent. Money supply will therefore need to

be kept cla .y under watch.

A 1·1~1.ll I <1c· on of inveBtment in favour of industry appears

1.o haV(l ;1 .ignificant positive impact on national income and

HI

I


employment.

As tu lhc choice to be made among the different alternatives

examined in lhe model, it is primarily a matter to be considered

in the light of socio-political considerations. While a higher

rule of savings and investments are desirable from a longer term

point of \' iew, there are short term considerations to be taken

into account e.g. the limits of austerity that the general public

would tolerably accept and the extent of foreign aid that can

reasonably be expected to be available within the existing

international economic environment.

Subject to these considerations, it would, however, seem

that Alternatives I and II seem to fall below minimum acceptable

rates uf growth ir1 national income and employment; Alternative IV

is perhaps somewhat unrealistic in terms of foreign aid

requirements und sectoral allocation parameters. Viewed from this

angle, Alternative III appears to be close to a feasible

alternative and at the same time, perhaps the minimum to be

attempted. Even this alternative, however, has disturbing

elements, particularly by way of a widening current account

deficit as a result of a sharp rise in the level of imports. The

correction of this drawback will need to be further analyzed by

examining the possibilities of achieving a higher level of

exports and a greater measure of import substitution.

6.3 Policy Implications

ThP purpose of the explanatory remarks in the preceding

section is not to argue strongly in favour of one scenario or the

othP.r. The ultimate decision is obviously that of planners and

pol icy makers. I l may nevertheless be reasonable Lo argue that

the construction of this macro model now makes it possible to

mal<P dcLai 1,~d policy analysis in the context of Nepal's economic

development. The implications and broad dimensions of the

Nepalc!se <!conomy can be assessed by making policy choices out of

several pol icy al lcrnnlives under r:!Onsideration.

<I '' ,, ..


At a broader plane, the model results indicate that there

are el~rln in ureas where special consideration is warranted in

order lu sustain Nepal's development efforts. First of all, an

ambitious programme by the government will be necessary

parliculnrly to release many of the country's infrastructural

growth constraints by increased public investments. A strong

case also could be made for additional external assistance in

certain specific individual sub-sectors. Likewise the

productivity in labor and capital use has to be increased by new

incentives, an improvement in manageaent, better technology

absorption and allocation of investaent in areas where the

capital use is comparatively low. In this connection, the

results clearly indicate that industrial sector is the one which

deserves special consideration (See Table 6.3) so as not only to

accclcralc the industrialization process in the country but also

to expedite the growth process, and thereby to raise the living

standards of the common people within a reasonable period of

time.


Chapter 7

INPUT/OUTPUT MODEL AND POLICY SIMULATION

As discussed in the previous chapter, the macro model

prJvidcs lite broad dimensions of the Nepalese economy in terms of

GDP, consumption, investments, exports and imports in the

background of \·arious levels of prices, deficit financing,

dependency on foreign assistance and changes in the behaviour and

technological constraints. The input/output model, on the other

hand, attempts to bring balance between supply and demand in the

consumption market, the investment market, the labour market and

inlcrmcdialc goods market at a disaggregated operational level.

To give an example, all industrial and mining activities are

clubted together under one sector - industry and mining - in the

mt;.cro model. Different sub-sectors within industry and mining

sector arc not disaggregated and, therefore, the implications of

policy changes al the sub-sectoral level cannot be discerned.

Further, inter-industry comparisons are also not possible. At the

aggregate level, it is also impossible to undertake a policy

analysis of allocation of resources among different indust.ries

within the industrial sector which constitutes a key policy

decision in industrial planning. The input/output model is used

to cover these gaps. Besides, it can also help to di~tinguishe

the priority sectors of the economy on the basis of forward and

backward linkages of various industries. An input/output model

is thus an important planning tool in ensuring utilization of

factor endowments and dynamic comparative advantages of the

economy und in es ta bl ish ing the f eas i bi 1 i ty of pl an targets

without generating sectoral disequilibrium.

Gencrully an input/output model is utilized to examine the

intcrsccloral <'ansistency, considering only the fina.1 demand

componenlH. Though this helps to examine the additional output

demand generated in the process us a result of an increase in the

finnl df~mand, such analysis overlool(s the supply side constraint

and hence, J.tivcs little policy direction on the likely

deslubi I izution effects. Jn order lo overcome these

I I I shorlcomin~s. the alternutive III scenario of the macro model

(givin~ aJ!gregale growth rate of 4.5 percent) has been taken as a

I I I

basis for reference run solution of the input/output model. To • put. it diffcr1~nt.Jy, the final demand components of the macro

model ( 1.Jh i ch ar·e supported by supply cons ide rn ti on under the

macro mudel I ha\·c been utilized to get "reference" solution of

Lhc iupul./oulpul model. The salient feature of such integrated

araalys1s is lhul given almost same aggregate size of the fir~al

demand components as considered in the macro-reference run, it

I tries lo work out Lhe detaile~ sectoral implication in terms of

consumplior1, production, investment, export and import.

I I I

7.1 Reference Run Solution --- ------The macru model gives GDP and other variables in scalar

terms. AL first, all the variables related lo final demand

componr.n ts were converted into \"ectors by using normalized

al location co- »fficicnt computed from the base year input/output

table of 1986/87. Then the model solution was achieved with the

I help of ~9 sector inverted matrix by using the final demand

vcc tors on pr i vu le consumption and i nves tmcn t, government

I I I I I I I I I

consumptiu11 and investment, exports of goods and services as

well as imports of ·goods and se&vices as estimated above. This,

however, could give only the total output level that had to be

produced by each sector for s'.ltisfying the additional demand

ge11craled through the new final demand vectors. Again, given

the share of value added at factor cost in total output derived

from lhc input/output table the value added figures for each

sector were ublaincd. As shown in table 7.1, this gave exactly

the same growlh rate as given by the macro model thereby helping

us to satisfy Lhe Lest of complete integration.##

The input/output model gives interesting results in many

---·· - . ## The vnltw 1.uJdcd figures adopted in various tables in Chapter

i and i11 Appendix Tables 11, 12 and 13 reJJresenting future proJ1~ct.io11s to 1990 - 95 and 1995 - 2000 arc estimated nl fac l.o r cos I.. There fore, these figures wou J d not be comparafil,. to thP vaJuc nc.1dcd figures presented in Tnblc 5.1 wh i d1 i rw I 11d1· 1 nd i rec t I.axes n I so.

-, I I I I I I I I I I I I I I I I I I I

respects. From table 7.1 it can be seen that gi\•en the

interscctoral linkages, sectors like canning, sugar, tea, basic

and fabricated metal, and pharmaceutical industries have to grow

at n faster rate than others for satisfying the growth in the

aggregate demand vector. This implies that to meet either a

substantial increase in consumption and investment demand or a

gruwiug export demand, these industries need special

cousidcration in the process of industrial development.

The input/output model is also utilized for investment and

employr;ient planning by examining the impact on investment and

employment at disaggregative level& For this purpose, as noted in

Chapter 3, sectoral ICORs and employment coefficients for all 39

sectors were derived by employing various techniques.

The reference run results on sectoral investment and

em pl oymcn t arc presented in table 7. 2 (a) and 7. 2 ( b) • The

input/output model gave substantially higher implicit aggregate

ICOR than the histo!.ical ICOR derived from t~e macro model.

For instance in the input/output ·.iodel t.he ICOR at the

aggregate lev~l comes to around 5 whereas in the macro model it

was only around -I • This is b'O?cause the macro model with it: s

aggretativc nature cannot take into account the changes in the

activity/production mix taking place over time. Indeed it shows

that over time the production-mix of the industrial sector is

moving towards higher ICOR activities. This is not surprising, as

the diversification of industries tend to increase the capital

intensity cf the sector.

7.2 Scr:Hi~ivity Analysis and Altccnativc Pol._cy Simulations

Based on reference run aoluticn, sensitivity analyses were

undcrtaltrn l.o <:xaminc the overall as wcJ 1 as sectoral

implications on output, value added, investment and

under different growth strategics. The alternate

cousider1!d wr!r1!: (I) export - oriented development,

employment,

strategics

( 2) import -

substitutio11 oriented development and (3) n combi:mtion of both.

81i

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Emp. 1&9u

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up. 1992

61311120

2168 2130 365

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5li3E 15&2 4655 777~

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up. 1993

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inYest. inYest.

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Invest. lnYeat. laves•.

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89

'

I I I I I I I I I I

Finally, a scenario was also developed to investigate the

likely consequences on sectoral in\•estment planning arising from

pove~ty alleviation programmes leading to an enlarged consumption

basl{cl for some essential goods and services. The various

ul lernal i \"e assumptions made, in this connection are presented in

table 7.3.

7.2.1 Import Substitution Strategy and Industrial Development

In this sensitivity analysis, two types of substitution

strategies were considered.

In Alternate I, the substitution of final import (both

consumption and investment) by locally produced goods was assumed

to grow rather slowly among the thirteen import substitution

industrial products considered. Inter ~ among these products,

import substitution was assumed to take place at a higher level

in cement industry followed by paper and printing. A lower level

of si.bst i tut ion was assumed in basic and fabricated industrial

I products. In view of the limited scope for promoting capital

I I I I I I I I I

goods industries in the country in the immediate future, this

assumption may not be unrealistic.

The results of the sensitivity analysis under Alternative I

are presented in table 7.4. It is interesting to note from table

7. 4 that in spite of a substantial measure of import

substitution, the overall gain in output and value added is not

significant. Fur example, in comparison lo the "reference run",

only a 0.2 percent additional growth in aggregate value added

could be achieved for the period of 1990 to 1995. This is

because the income (value added) multiplier for import

subslitut.ing indu~tries is seen to be only around 1.2 to 1.3. A

similar trend is also observed for the period 1995 to 2000 also.

To examine the impli~ations of pursuing a more aggressive

import substitution strategy, another scenario, Alternative II,

was dcvelopt!d by aHsuming the attainment of 100 percent self

suffic:im1cy b~· t.hP year :moo in certain commodities 1 ikc sugar,

!JO


Table 7.3: Basic Assuaptions

1. lmµurl SuLstilution Strategy

1. Tobacco n Dairy Products L. •

3. Canning 4. Sugar 5. Textile 6. Footwear 7. Cement 8. Mineral &. Fuel 9. Pharmaceuticals 10. Chemicals 11. Paper and Print 12. Basic and Fabricated 13. Electric & Electronic 14 . Plastic and Rubber

II. Export Promotion Strategy

l. Other Cash Crop 2. Livestock 3. Tea 4 . Carpets 5. Garrr.cnts 6. Ju tr. Goods 7' Footwear 8. Hotel and Restaurant 9. TranRport and Communication l 0. 01.h'~ r Services

!I I

Annual Additional Percentage Reduction in Import Demand 1990-2000 Alternate

( I )

4 3 3 4 3 4 6 3 4 3 5 1 3 0

Annual Additional Percentage Reduction in Import Demand 1990-2000 Alternate

(II)

4 0 3

100 100 100 100

3 75

3 100

1 50 50

Annual Additional Percentage Increase in Exports 1990-2000 Alternate

Annual Additional Percentage Increase in Exports 1990-2000 Alternate

(I ) (II)

.J 15 2 10 3 10 8 20 6 10 4 0 3 8 4 10 3 10 0 10


III. Combination of I & II - - - -

Table 7.3: Basic Assumptions (continued)

IV. E_~_sc;~1_l.i_u_t Q_oods Strutcu:

1. 2. 3. 4 • 5.

Food Crops Textile Leather & Goods Real Estate and Dwelling Other Services

Annual Additional Percentage Increase Rate

1 4 2 2 3

textiles, footwear, cement and paper and printing, 75 percent

self sufficiency in pharmaceuticals and 50 percent in electric

and electronic goods as well as plastic and rubber products.

This scenario gave the average value added growth rate of 4. 9

percent for the period of 1990 to 1995 and 7.29 percent for 1995

to 2000 (table 7.5).

' Even under a vigorous import substitution policy, the gains ' are not very impressive. But more importantly, this scenario is

not considered feasible in view of the possible supply

constraints and the nature of non-competitive import

substitution.

7.2.2 Export Led Strat~ and Industrial Development

As iu the case of import substitution strategy, two

alternative possibilities were considered under the export

oriented d(!\'elopmcnt strategy.

To beg i 11 w i t.h, Len exportable i terns which P.!:!_mu facic seem

Lo hold considerable potential were identified. These inclt•ic

other cash crops, livestock, tea, carpets, garn:.ents, jute goods,

footwear, hotel and restaurant, transport and ~ommunication and

other services. The lust three items have been included as export

it.c?ms in Uu! sPnsc! t.hnt these contribute greatly to foreign


i-·.1·ha11!.'." ··:11·11111!!s 1"1·om the !!rowth of tourism. Thus lht>y

111:1.1111· sn111..--: or for·ei~n cxchn!1~c- earnings jusl as cummudily

1·:.1'111·ts :11·•·. l.i\f'c->1111·1;. and ensh crops were considered i11 \·icw or llwrr· st1·n11!! li11ha!!r- Hilh 0L!1er seelors and ulsc tlt!e Lo their

f'l"""l"''"' s f"nr· a11'.!111t•11I ing exports.

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Table 7 .5: Grovtll hte l1pliction of l1port Substitution Strateu II ___ . _____________ --------------- _____________ -------------------------------- _ . ______________ 1E, ,~ .. : · .

:m _____ mi__ ______ Jm __________ lm __________ mL _______ J~~L __ Avr Grth £t. A;·. :-·

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iota[ Value Total Value Totd Value Total Value Tot.\[ Val•1~ ~·J-95 g~-95 ~5-!i,,, 1 ;:

i":t 1·11t M4~~--Q~~e~U4~~L:~!t~LH~~LQ!!tm_~g~~LQ~~euLM~~L~~~£~L~~U~L"ut 21: _ ·'

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95


Under Alternative I, the 'export growth of these ten

commudi lies was exogenously increased by minimum 2 percent to

maximum 8 percent above the reference run growth. The results of

the sensitivity analysis as presented iu table 7.6 indicalc a

rcspceLaiJlc gru1•lh rule of 5 percent of GDP during 1990-95. Also

in this context it is seen that the income multiplier in the case

of cxpurl led strategy is around 2.0, much higher than the case

of impurl ~u~slitution strategy.

The implications of adopting a strategy of placing even

greater emphasis on exports were examined in Alternative II.

Under this Alternative, except assuming a zero increase in the

growth rate of jute goods, the growth rate in other goods and

sen· ices (Table 7. 2) were increased by 8 to 20 percent. The

highcs t annual growth ratP. was assumed for carpets ( 20 percent)

followed by cash crops and livestock, t~a, garments etc. In thi~

scenario the export of services plays a crucial role in export

promotion, and reflects a faster growth of tourism sector in

Nepal's development. In table 7.7 the results of this

Alternative arc presented. This scenario gives very high growth

rate of both value added (5.9 percent and 8.69 percent) and

output (7.2 percent and 9.99 percent) for the period of 1990-95

and 1995-2000.

From the foregoing analysis, it is evident that if a choice

were lo be made between import substitution and export led

strategies, the latter is clearly more beneficial for the

economic development of Nepal. This underlines the validity of

promoting an outward looking economy in Nepal. It also brings out

clearly the importance of tourism provided, however, its

multiplier effects are fully harnessed through its linkage effect

with other sectors of the economy.

96


T&b!e 7.6: Growth i.ate !1plic1tioa of i1porl Pro1otio1 Strate'' I

:!.H ________ !~!~ _________ 1~~~---------l~~! __________ i~~~- ___ A::r. '~!'~~ i: .. !·;~. ~

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97

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Tablt 7. T: Gra11tll late l1plicatiu of ilpo&l Pro1atioa Strateu II

. __ _!H! ______ J!~L ________ !HL _______ Jrn _______ __ ,~!~ \or. 1;rth i.~. h~ .

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I.! L~

5.5

i ! . j

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u i.; 2.7

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IU i. 7

IU u u IU

7 .J .. [ u 1. c J. ~

f_O

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u i. 8 u

I I. 5 u u u u u

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!2.9 3.1 u

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12.9 u u

4.1 u u lU u &.7 5.4 u

la.1 14.9 6 .8 5 .o 5.0 5.9

l?.5 11.Z 2U 5.8

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11.5 u u u u

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ll .5 4.l u

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•.; ____ u ____ u ____ 1, • ___ -~ J ____ u ____ 1J ___ J) ____ • . .: 4.8 6.7 ~.7 7.1 5.7 7.8 6.4

98

4.1 5.l

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7.2.3 Combined Strategy of Export Proaotion nnd Iaport

~ub~lilulion on the Basis of Coaparntive Advnntnge and

!!t_dlJ~-~r iul Qcvelopsent

IwJeed a country like Nepal cannot follow exclusively either

an export I cd or import subs ti tut ion development s•.rategy. ln a

more fundamental sense, these are not mutually exclusive. Several

industries which export also meet growing domestic demand. In a

pract ieaJ sense, there is no reason not lo proaole import

substitution of products which can be coapetitively manufactured

in the country while pursuing exports exclusively or

substantially in certain other products. In the real world, both

import subs ti tut ion and export possibilities are simultaneously

explored, no doubt with a greater emphasis on one or the other •

depending on the resource endowments and comparative advantages

enjoyed by n country. And this applies to Nepal too.

There arc, of course, other valid reasons why an exclusive

allcntion to one or the other strategy would not be advantageous

to Nepals' growth prospects. Given the low per capita income and

relatively small population, the aggregate domestic dema11d for

manufactured products is modest and can be expected grow only at

a slow pace. As such, industrial development based on domestic

demand can only have a limited scope. It will soon exhaust itself

and will be hardly sufficient to maintain the momentum of growth

of the national economy. This apart, the lack of natural

resources and the diseconomies of scale and the consequent high

cost of production will rule out import substitution of several

products. On the other hand, exports cannot be s trelched to ad

infinitum. The changes in the global economic situation,

fluctuations in demand and trade restrictions of various kinds

adopt.ell by importing countries set limits to the quantum of

exports which a country may aspire to, even assuming that it

enjoys 1Jistinct comparative advantages i~ factor costs.

Undoub,1.erlly the export led strategy exhibits several ,'istinct

udvant.a~cs. ft. has a larger valu~ added multiplier !i.e. more

f a v o u r a h I ,. < • f f 1~ c t. o n G D P g r o w t h ) , and l e s s e r n e c d f o r

i ll\'1•:-d.rnc11l.s, compared to import substitution strut.cl(~·· Also the

99


\"aluc added for labour is high in export oriented industries.

Thus from all uccounts export orientulion lo induslrinl

development seems lo give better econoaic

reasons, industrial strategy aust have a

rewara. For lhcsc

pronounced export

uricnlalion, but, as earli:!r mentioned, it docs not exclude

import substitution where it is econoaically advantageous to do

so.

The basic principle underlying such an a~-iroach is to

promo le ·1 l l such industries in which Nepal enjoys a comparati \'C

advantage irrespective of the aarkets for which these are

intended, whether they be domestic or foreign. Viewed in this

light, it would be more appropriate to designate this alternative

as the Strategy of Comparative Advantage rather than merely as a

combined strategy of Export Promotion and laport Substitution.

The results of the sensitivity analysis under this combined

strategy on the basis of the assumptions set out in table 7.3 arc

presented in tables 7. 8 and 7. 9. It suggests that a GDP growth

rate of 5.2 percent is achievable over the next five years even

under •moderate assumptions of import substitution and export '

promotion. The rates of import substitution and exports assumed

arc reasonable and attainable. Hence the results validate the

general hypothesis that the strategy of comparative advantage

maximizes the growth prospects and offers perhaps the best

approach lo Ncpals' economic development.

Vir~wPd from t.his angle, the Study Team considers this an

acccplahle l.argel (or plan) scenario. As noted above, this

scenario is suitable from a number of other considerations also.

Jl ha~ a .:omparut.ively low ICOR, thus enabling the attainment of

a rensonably high growth rate within available investment

rcsourc•cs. Also this alternative has high income, employment and

export. mul lip I ir.r in cnmparison with other scenarios.

100

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One more scenario was developed by extending impore

substitution and export promotion to higher levels (Table 7.9).

As is expected~ the growth rate is even better under these

assumpl ions. Huwe ver, it may be di ff icul t to realize these

assumptions in practice. The purpose of developing this scenario

was merely lo show that the strategy was basicall; sound and that

the more inlensuly it can be followed the aore rewarding the

outcome.

7.2.4 Poverty Alleviation Strategy and Its Implications

A sensitivity analysis was also carried out to examine in a

very broad way the implications on the overall economy of putting

more emphasis on expanding the production of some essential

consumer goods and services for the benefit of the poor. But it

should be noted that iu such an analysis the essential

prerequisite is to identify the share of population living below

the subsistence level, to examine the se~ of measures to be taken

to increase their income and to relate the incremental demands

generated from the altered income pattern to additional

prorluction of goods and services to meet them. Such a detailed

analysis will require a separate study. Here, an attempt has

been 'made lo derive broad impl ica,tions at the aggregate level, by

increasing in an ad hoc manner the avai la bi 1 i ty of some of the

essential consumer goods.

ln this exercise, consumption n( food crops, texti:c goods,

real estate, dwelling and services (which include education and

heal t.h) was increased arbitrarily above the reference run level

by one to four percent (table 7.3). This gives the output and

va 1 uc added growth rate of 6. 1 and 5. l percent for 1990-95 and

8.07 and 7.17 percent for 1995-2000 (table 7.10). A further

implication is lh11t it necessitates a sizable investment.

7.3 Jntcrs,!clornJ "-'inkagcs and Investacnt Planning

On1! advnntnge of input/output modelling exercise is that it

provides I.he broad d imcns ion of in tersectoral l inknges in outpu.l

~1!nPrati1H1 in l.<!rmH of both forwnrd and backward li.nl<agcs by

103


1•hich it. is possible to identify the sectors demanding higher

priority fur generating growth momentum. Although such analysis

is Lasc<l on prc~·ui ling technological considerations, it also can

be made lo examine the likely eff.ct of technological changes on

the listing of priurilies. Such an examination can be carried out

by introducing new technology coefficients in the model,

depending on the technolog) proposed to be adopted.

First of all with the help of inverted matrix both backward

and forward linkages coefficients in 39 sectors were calculated

and then totals were obtained by simply adding these two.

In the table 7 .12 the industries ranked on these lines arc

presented. From the table it can be observed that in general the

forward linkage co-efficients are higher than the backward ones.

Among lh~ industries, the grain milling industry has the highest

backward linkage effect followed by tea, footwear, sugar, dairy,

wood & furniture, other food, cement and chemical industries, in

that order. On the other hand, only few industries such as paper,

electric and electronic goods industries show a high level of

forward linkage effect, followed by cement, jute and canning

industries. These results are to be anticipated in view of low industrial base on the one hand and almost total absence of

intermediate industries on the other. When total linkage coefficients are closely examined, only two industries paper and

electronics show relatively high values followed by tea and cement.

Tt:is backward and forward linkage analysis, thus, clearly highUghlP tl1<• fuel th t - d -' · '" - - · a in esigning long term investment planning it is neccssa.r.y to gi"ve adequate tt t' t · d -a en ion o in ustr1al divcrsi fical.ion and overall restructuring.

104

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2. 7 !~7::: ~ . 7 4 ~ i ;·,.;

,, ... ,..,..., , ...... ,,, .. "'•'· ·.J ... ·1

l,1)(111 ri:10 Too1c·:o Har.ufadur-~ 2.In. ··1

i.-'tl ~~r_·;~~1Ll _I)'. ~·)Q~ .u~~u~-L~i!~t~Lt!Q1:1~ ~~---·::' l '.i~: ~ -

108

I I I I I I I I I i

,, I

I I I I I I I I I I

7. 4 l~pj._oymcr!1_ Er reel of Al ternati vc Strategies

ruriuus ullcrnali\·c scenarios covering 1990-95 and 1995-2000

is gin~n in lhe Lahle 7.13. From all alternative scenarios il

SCl!ntS l ha l the inc reuse in em pl oymen t in the economy w i 11 be

sulist.aulially hi~hl'r lhu11 population growth. Although Lhe

combined cmploymcnl effect of export promotion with import

substilution slratcgy is much more pronounced, the effect of the

export promotion strategy is almost as strong as that of import

substitution strategy. Since this sensitivity analysis provides

only an nn~rall piclurc, it is necessary to undertake u more in

dep Lh una l ~-sis u f lhe working labour force classified on the

basis of occupational pattern to prepare a detailed manpower

plan. ,

I 1 J ~ I


'..!::L 1 .": 1;,,_:i1 r. iu11,-·i ica r.ion or Ai r.ernat.i ve

Av. 1..irt.. hate

t\··.t. : _1 !"' ..

--. ': •:- u -., L' i ,_, ___ l_;._·1 ;_~:,_,_·, ____ l_9_8_5 ___ l_d_8_Q_-_;;t_. _0 ___ ;_,_-\}~- _ __:.;;.'.;,;' ;_, _-_.., ': . .' .'

l •lT18087 4. tJ

5.1

4.8 ...... -

· - - ! ., ', : i ii1r · rL - ":. . [t ___ ;,;~·:l.:..~!..;_:,_J;:...;1;)56:.:.8 5. "{ L .: -

110


8. 1 C_o_!lc l us j.~n-~

Chapter 8

CONCLUSIONS AND RKCOHMHNDATIONS

The purpose of the present exercise was two fold:

a. DeYeloping an industrial planning model as a tool for

industrial planning; and

b. To inil~ate a debate on specific industrial development

scenarios, which are consistent, feasible, and at the

same lime confirm to the goals of development chosen by

the society, and provide corresponding suitable policy

recommendations.

The first purpose has been reasonably fulfilled. An

integrated macro-econometric and input/output model has been

formulated. The macro-econometric model has been designed to

ensure the feasibility of a selected development program within

the country's macro-economic constraints and the input/output

model to provide the test of detailed sectoral consistency and

the demand needs of the economy in conformity with its multiple

goals of dcvc_lopment.

c; i ...- e n t h c s ma 11 s i z e o f t h e i n du s t r i a l s e c t o r i n t h c

Nepal esc economy and its heavy interdependence on the growth of

other sectors, setting up of a suitable macro-economic scenario

was regarded as u prerequisite for formulating any detailed

industrial development strategy.

Setting up of a development strategy needs proper

id c n t i f i ca t i <HI o f th c ..I eve lo pm en t obj e c t i v es and a re o. l i s t i c

assessment of the resources base and factor endowment of the

economy, not necessarily in a static but in a dynamic sense,

tul{irt~ into Ponsideration a long-term view of changes in

technolo~y and international environment. For a small and poor

economy I ilu~ Nepa!, with skewed resource distribution, a proper

<:l1<>ic1! of iriduHLrial structure conforming to her comparative

111


ad\·antage and making her fully internationally price competitive

is a must. lndcecl this asked for an exercise combining pragmatism

with imagination.

8.1.1 1'hc Hue~~ Econoaic Scenario

The present model simulation ,warns that if no positive and

prmlenl pol icy packages are introduced in near term, the economy

in ils pasl tempo will not grow beyond 3 ~o 3.5 percent per

annum. This ~rm1th rate may not e\·en absorb the growing labour

force, uot t.o lnJk of absorbing back log of unemployment or under

employment. The per capita consumption growth will be almost

stagnant. Then~ will be mounting trade iabalance. All these may

prove to be socially and politically unacceptable and throw the

country into complete disequillibrium.

The major policy instrument identified for accelerating this

low growth is increase in aggregate investments and their more

efficient. use by choosing both better technology and appropriate

sectoral allocations. In the macro scenario emphasis has been

given lo the aggregate increase in the investible resources. In

the sectoral scenario C input/output approach), their allocation

and efficiency consideration~ have been mainly explored.

The investiblc resource base of the country has been divided

inlo l.wo: foreign and domestic. Any atteDlpt to increase these

resources has a price <i.e. a sacrifice) to pay. The external

resources can be increased either by more aid (borrow\ng or

grant), or by more exports (and in soae way less imports).

Al I.hough grant. has nu economic pr ice to pay (it may have some

political price>, borrowing has to be paid back in principal and

interest. Besides, in many cases it has explicit or implicit

conditiunolity. The availability of external grant is not

inf in i le and the present prospect of more grants arc nol very

rosy. The debt service ratio in Nepal is now not very high; al

lhc snmc Lime it ca .. not be stretched ver'J much. Taking c.11 these

fncl.orH 1u1 upper limit t.o growth of grants and borrowings hove

bePn pla•:1:d al. 12 and 14 percent per annum, respectively.

112


Similarly a growth in exports both in v.oods and services

(ncU l>i ll ~i\·c additional foreign saving. But aore exports will

need ti) •cneruting more export surplus in the doaestic market,

and Ciil more export demand abroad, aainly by iaproving on the

price competitiveness. In this context, it has been assumed that

an export growth maximum of around 8 percent will be possible,

rais1~cl from lhc long-term trend of 6 percent, over the next five

~·ear horizon.

Coming lo domestic resources, two areas are located (i)

private sector and lii) government sector. In the private sector

-by heller operations of financial interaediaries, the credit

availability could be raised from a trend growth of 9.89 percent

to a growth of 12 percent. This will entail an increase in

savings propensity by more than two to three points: given the

structure of the Nepalese society, and low per capita income, and

the stick i ncss of. private savings behaviour, this proposed

increase of savings can be regarded as already on the high side.

The publir sector increase in financial resources arise

primarily from government's tax and non-tax revenue (net of

expenditures) und deficit financing. Deficit financing indeed

adds lo the resource base as long as it is non-inflationary. In

less developing countries, with large unused physical resources,

deficit finnnec has indeed act~d as one of the powerful tools for

resource mobilization.

ln lhc present exercise a deficit of upto 2.4 percent of GDP

has been found acceptable containing the rate of inflation below

10 lo 11 percent. The growth of public saving has been stipulated

to come 1i1ainly from Ii) economizing subsidies (ii) improving tax

collection, and !iii) increasing efficiency in budgetary

ma111.igcm1!fl l.

113


The resultant increase in public sector investment came to

10 perce11l per annum ns compared to a trend growth of 7.5 percent

given in lhe base run.

Against this policy inputs, a growth rate of as high as 4.5

percent \"alue added over the next five years and a long term

growth of near l~· 6 percent have been seen feasible by the

simulation of the macro-model. This will give an employment

growth of 2.8 percent and consumption growth of 4.6 percent

during the period 1990 to 1995. On the other hand the current

account deficit will reach almost 14.7 percent of GDP by the end

of 1994/95. This scenariQ has been regarded as a minimum, given

the compulsions of development objectives of the country. In the

input/output scenario, n further exploration has been made in

order lo enhance the growth potential of the country by a

restructuring of industry by intersectoral investment

adjustments.

8.1.2 The Inter-Sectoral Scenario

While the macro-economic scenario has shown the need for

increasing investment resources in aggregate, the sectoral

(input-output) analysis has attempted to deal with the issue of

sectoral allocation as well as efficiency considerations.

Within the limits set by the 'J.Vailability of resources

(given through the macro-model), areas of thrust for future

growth as wej l as restructuration requirements have therefore

beer1 assessed in the input-output model. Particular attention has

been given to identify an optimal allocation of resources within

the manufacturing sector, in line with the country's comparative

advantages. Main criteria which have been kept in view in the

analysis include: growth of value added, employment growth,

soeiuJ rclurns (direct and indirect), elasticity of resource

base, demand level and economies of scale.

114


Ir• designing the future industrial development strategy, it

musl be l{ept in mind that Nepal is still at a very early stage of

industrial development, with the manufacturing sector ha,·ing a

share of only slightly more than 6 percent in the o\·erall GDP. In

nddiliur1, lhe major part of the overall manufacturing value added

is produced by cottage and s~all industries. Therefore,

significant c~anges in the existing industrial structure a1e

required lo accelerate growth and development of the industrial

sector. A basic precondition is to promote improved linkages with

the agricultural resource base and sectors producing intermediate

goods. A rapid development of the tourism sector and of the

hydro-power base will put industrial development on a sustainable

basis and enhan~e Nepal's comparative advantages, while at the

same time, industrial growth will have a significant impact in

accelerating lhc development of other sectors.

The input-output model very clearly shows, first of all,

that in order lo attain a modest minimum level of growth the

pattern of investment needs to be changed considerably, with a

much greater emphasis on the manufacturing industry. This is also

essential lo increase the consumption standards of the people, to

meet the wide range of requirements of other sectors, and to

improve lhc situation of the balance of payments.

Secondly, different industrial development strategies have

bce11 considered and evaluated. Major development alternatives for

lhc industrial sector in Nepal exist between a reliance on

capital- or employment-intensive industrialization, and an

oulwar<l-looking strategy versus fo~us on import substitution.

As shown b.\·

terms of overal 1

the sensitivity analysis,

~rowth of income and

the highest impact

employment could

in

be

uct1icvc<l by concentrating on those industries which contribute lo

an overal I incrmuw in capital productivity, and at the same time

generntc a si11.nificnnt level of employment. An export promotion

str11t.1~~.~· HHS fou11d to have better results in terms of growth Lha11

1rn in1-1arrl-lool<i11~ approach. In actual practice, however, ~rowth

115


has '-" '!" 1111 111 a parallel manner on the external and internal

m:1rh.•·I li:1s•·tl •Ill Utt• pri1wipl1' of comparative ad\·antage. lmpurl

s11hsl i I 111 irn! indusl ri('S should be developed only if they arc

····n1p1111i1·al I.\· \·ialde, a11d lhey ean be made aore viable if t.l1cy

!', ... ,, ...... ~;i11111ll:l111·tH1sly for lh1: internal and the external murkcl.

.\lso, !.!i\·1·11 the pour lcn•l of linkages of light industries with

lh•· ln•·al 1·Psour1·1~ bas .. , ~~·~pal should focus on industries h'hi·~h

pr'lil11•·,. inl•:rmedial.t• :>roduels, thus contribulin~ lo a

subs Ii I 111 in11 ot' imports.

ThPrPfore, in analyziru! three scenarios, i.e. reliance on

1•:;p11rt prnmolion, focus on import substitution, an~ lastly a • c11111bi1ll'rl 0111:, i I was lh1: last• scenario which was most in line

1:it.l1 ~< .. pal's eomparali\·e arh'anlages. Only in the last scenario, a

1;111· t~l'tll·:lh ral.t> or 5.2 pcre1:nt. could be achieved.

1111 t.his o\·crall basis, thirdly, the main areas which should

r .. ,.,. i \ ,. major t:mphas is 111 the future i ndus trial development

sl.r·al•~l!,\' !1an~ l>e<'n identified as f·_llows:

I I I E ~; po r I i n du s t r i cs , w hr- r c N c pa 1 , due to i ts cheap l ab o u r ,

p11ss•·ss1·g g i J.!11 if i cau t eumparali ve advantages. This includes

s•·1:t11rs lil~e carpPts production, fruit and veitctable

1·;11111i111!, .i11tr., tea and footwear manufacture. These

i11rl11sl.rics will nlso create significant emplo~·ment

I :! I

I :~ I

nppn1·t.1111i tir•s.

l11rl11sl.1·if~s 1.+ich posses'.~ important

I i111\:u!Ps; in particular paper and

1•IPr·l1·i1· and eleelronic J!oods, tea,

backward and forwurd

printing industries,

cement. Except for lea,

!hr"''.' at·f· al I import. substitution sectors.

"\·::11~·· i.:oorls" SP('f.or:~, ·''• industries which are important

1'1·""' !.lw point of \'it!W of increasing inl~rnal consumption

lt·,···ls. Thr·sr· an~ i11 part.icular textile, sugar, drugs and

pharm:wr~111.i<'1.1ls, food crops, grain milling.

.\~; ,.,,11,·r·r11s hr~a\·y arid ha~:ic industr:r sectors, product.ion

1.ilhir1 ~lr·p:il r·a1111ol. Ill' r·r·r·ommPIHJed in the immediate future in

\·11•1. 111' hit.!h 1·apil.al ""'l'lin~.nr-11!.s implied, management expert.is<!

I L 1,


r···qu i r•·rl. as ,..;c 11 as the need for significant economies of scale.

H. L! Ike ~o•u••~~'~~i_!-j_t~ns

lhc• aho\·c anal :rs is shows the importance of the criterion of

.. rri,·i·~ney and lhc principle of coaparative advantage for

incn·asiu!{ productivity and redilcing costs in the industrial

spc· I or. Jn how far the future growth potential can be realized I

w i I I I :1 r~e J :r depend on wheth'er the external aarke t can be

caplurc~d on the basis of price competitiveness. Any major price

ii is I ., ,. , i 1111!> Lh rouJ!h inn ppropr i ate taxes or subsidies should be

avuidl'rl. :\t lhe same lime, attention must be given to fulfilling

lhc• .l1·111a11ils i11 I.he national economy.

Tlw .-:1pid industrial development of Nepal will depend on how

far i I s1wcr.ecls in c\·ol\'ing and implementing an appropriate

i udus lr i a I pol icy in a speed:r manner and at restructuring its

industrial sector in the abo\·c sense. Only then can the modest

anl i1~ipal.1•d ~rowlh le\·el of 5.Z p::L·cent be achieved.

.\ rip I.a i l c!d layout of the proposed sectoral i nves tmen t

pal.l.,.1·11, including anticipated levels of output and employment is

j>1'0\·id,:d i11 n tabular form in Table 8.1.

Tl11• speei fie !Jolicy instruments in terms of taxes,

~.;uhsidir?s, licensing, tariff rates etc. for achieving the

rccom111Pr11J1?d rl!sourcc al location can be worked out only by more

dr~t.ai l(:d micro study which we understand is now in progress in a

sPparal.1~ Sf'<·tor st.ud~· i11itiatcd by UNIDO.

B<-1"01·" 1.·orwluding, il is !lecessary to point out that the

11111rl1· Is rl1~\"f: I l)f'"d arc basr-cl on weak data base and therefore need

co11I in11ous rc\'ision and updating. First of all, it is necessary

t.o broadr-11 the coverage of national accounts and improve the

q11.1lit.\· ,,,. "~:isl.i11g c..lnta. Separate estimation of government and

pr· i ,.a l.1: sn\· i 11~H is cssent. ial for examining either the crowding

""' phr·r111m1~r1C>r1 or thr J{rowing inefficiency in government.

l.il\r•1.:i~:r·, t'r-nl.r·al lJ11rPn11 of Statistics should devote immediate

J l .,


ul.tt>11t i1111 In 1·0111put.iH!! sccloral sa\·ings and consumption figures,

apart fn1111 1>1·11,·itli11!! reliable estimates of sectoral investment

fi1!11r-•·s f.y linl.h uril!in and destination for facilitating the

rcs1·:tn·lwrs aud puli1·~· planners in analyzing the flow of funds

h1•l.1-:1·P11 ~:•!•·tors as also drri\"ing capital flow matrix necessary

for 1.l•·\· .. t11pi11l! clelailcd resource plans and policy oriented

d,y11ami1· modr•ls. BP,..id1~s, the t!Xisling information and data arc

not. s111"fi1·il'1tl l.o r·onstrucl a reliable input/output table.

Specially, llw sectors lil<e forestry, livestock, construction and

pri,·at,,. spr·,·ic1!s ha\"c poor data base pertaining to their cosl

compositio11 a11d delailed input structure, both domestic and

import.Pr.I. No rPl iablc information on employment by sector is also

a\·ai lablP. Tltt!rcforc, a system for undertaking periodic mini

sur\"cys in arras where data gaps are severe has to be developed

so I hat. 1·1111' i nuous updating of cost structure of various sectors

cou Id be! mad1• as and i.rhcn necessary.

I I i ... t' i·~· , ·!·-",·~-r.·· l .. :·:etlitf"J•J tf_! .. ~.' .. G1'owt.h Rate)

.. · · · .. ··n·~::i i :::.i ... H1 t'iu.": E:-.:p1Jrt Promotion

I 1-----·· ..

F~), .. .:

T<_1t•F.1C:1

.:";ugarc ,, r. · OthP-r · ·;,. :: Livesr.. · · .:. I fore:::tt .. _..

Agricu i '.::··•

I Minin~ .• l.'llh"t·\1"'.

L•c1.iry fr-._,,iu. t •.

I Cannino: t)ther i..-, .. .- .. i l 1 ·

Gr"iin Hi.•: f-:.·:· :,_1·r:: . " ' ~ . r .. -.

To ba.cc;,__ r !.=-"\ t1~ 1!..;-1 1 ~: ~-· :.i !·~~

I Bever.::1g•·:~:

Te.i;,. Sugar.:, , ··111.· .·t.j.-'w°'r:.'

I Carpet::: 1·~:-:t i l.•'7:· G."i rmen t..'·

I .jute 1_;.:;.,r_i:·

FootwF,::;. t· '' \;ement.

I Chemic::, i _..,. Wood.:• ~·:;~·r:i·.;:?····

! 1·~11'.l!I" ; i 'Ill : ... t·

! _j.-.c,~:i~:

l: :· 1 ~· Jl_](: t.f:

. . : c · .. :11::1.•1n1,;r1t.l•.·n

r;,·}t~!i .... :· . ...,J,'i -~;;! 't:l~

Emp. L .. :i::10

756465:)

198~ 1820

285 43715

14:3t3:=i 8841 1806

784 '3(J01

11157 10274 1081u 795ti 1385 3245

4705::: 1340 4604 6t32lj 4.1au 19313 789::.: 104P. 101~;

12860·* 499::;

257513

Emp. 1995

9683037

2986 3687

604 5993

17889 12223

2229 1364

13481 38321 23485 23375• 11664

2554 5438

66990 3669 5940 9778 6448 2388

14820 1757 1149

202216 6540

46499

Growth Rate

5.06

8.44 15.16 15.39 6.49 4.48 4.43 4.30

11. 71 17.57 27.99 17.98 16.46 7.95

13.02 10.88 7.32

22.31 5.23 8.09 8.04 4.29

13.43 10.89 2.50 9.47 5.54

12.54 ..

Emp. 2000

14294t.74

5671 s2:1 1330 8707

251t)-i 17274

3110 2819

32238 110822

57307 49137 17'278

4848 10482

105231 88v::: 6887

15611 ll0b2

3354 36787

3506 16~~b

33lt'"1:Yi 872.3

89488

I Wti.)i.e.::·,.;:··

;:;1Ji'"J I.(>'·': , 922086 9.38 152874-i

I E :J 111-: i.. r. •

I I I

; ~I l ~ J T', .' : • I ,

I ' ',

· · ,, [.-.·:·,!.ling 27081 5.28 38 l'i~

119

t. ~t t..··:

:.:.: . l i.)

j_;j. t3~:1

17. •H) 17. u

.... . 7·~:. I

7. :._: j 7. Jr)

t} • i~,.'j

!5. 1:.:3 1.::"l .U5 ~~~. t'·t~ l: ! • :";.~

ll). tJ:::

b. ie. 14.1.-.i 14. 0:::

!~1. 45 .·,, ---:··· - ~. t ....

~:· • f ,.~;

:j. ;j _j

l J.:14 ·;. u;j

1!:1. :1-i 14. ;3~·: 6.L·

J.•.>. 4•.• ~ ···t-'-IJ • t..J.}

10. ::i::i

• j. ,.


........... ~- .. :'." .......... :"'"

T::;:r ·: 5t:!a!'~~~= O:h!r ~~·~ :!':::

Hini~g ~ ~J~~r:ng

[rair:: ~:-ci::::s

Ctr.~!": .. -: ~r~~·~:~: ~ra:n ~ii: fr::~~:!

i'::i

~u~~r 1 ~:=:~~~::=~~7

1:.:ip•,Q, .. ~ :' , ........ ..

- . ~r.;·::s·~~!' ·~ _:~:;;.:;~ ·.

.... - . -.. ~ ;::- ~ ·; .. :-.~

:::.~ :.:: ::1e::~~r.~ ?ia:: 2ian iargetted Scenario t5.Zl Grovtni ::;~r~ ~1~::it~ticn ilus nxport Pro1otion

-··r-;,n .... ::.: 5ii.lli Inve3t. :n7est. invest. Invest. iN icve~~. !S

:~5~6 156~~

~7ij ·.;,·;; .. ----~ :i':~:j

::,; j

.. ~ -.~ J: - : .. '1 ......... ,

.~:: 'J ....

> ·_.j

zmo Zl214 mfi

005~6

Iii464

1179 5iiSi l(~jl3

&::n

11570~

j&ll5

"".••;"': __ ,,.

:~~3 1~~4 19~5 l~~0-~5 TOTAL

4J5oii5 5~vv~68 5685444 21634~97

2:gsz ::m;

•"ic.· 1vvU

J•j64i ~jci&i

UjSJ lf:S~ m~

65~5·i

SJio6 13ivi5

15451 12J6jl j~o45

5jBiO :ooov !7J54 ~:;Ho

~00~ 149494 :•j56S ~H

16919 27817 . 1539

33959 10i047 13113 1~62 1571

iiv4i 149425 ,ll~li47 156640 j65Jl li464

143729 4i104 64345 J216J 1~962 27350 lll40

l~i603 ~:4756 ~osa

35273 32297 1825

37061 119058 14651 1411 1845

90243 173755 132568 . 178527 40969 19621

164173 54568 7ci344 36•i4il 22515 31245 12450

255870 29456 2457

134900 120749

ci651 155176 463246 50249 5451 6830

333570 65S476 4763~ 703616 166173 79159

665838 225271 277546 146:96 95011

122135 47i42

681816 1123~1 10115

l1:5i91. 13344i9. 1564246. 5951660 .

tloJ50i 53~115 656916 3106035 6i646o4 iil4a60 8526634 35313556

120

0.14 32666: 0.13 265625 0.01 I54oJ 0.16 Z605ritl 0.46 949j25 v.06 119m 0.01 1101~ O.ill Ili9Sj li.35 ii0495 0.69 ll~ZOJ6 0.50 940342 0.73 119Zill O.li 23iliil 0.06 W245 0.70 107J:5ti 0.24 423941 0.29 7Jlio9S 0.15 lDiS:i ·o.1v ns13:; O. lJ 1651i84 0.05 1'ili66 o.n 27iioo6 0.1: 2jij4!1 O.lil ~91ii~

J.Z4 6j42olii as.a; 44j9Zou4

'J. 'J!

Ii.·:~ ~.01 •j.4~

Ii.~~ •i.55 0.7~ . . -II ,., ..•..

o.~o u.:c tj. 45 '} .·:,-, r. . "' r.:. ~.:.

!i.t;6 • -1 L.t.

0.I4

- . ' (. :,

,.._ '. .:.1 .~v

.j. _.;


----------------------------------------------------------------------------------------------------

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. ~; . ;. ; - - : _ ..

. .. .:-: : ~ ~ .. -

-------- -------- Grc•:h

., .... , ~ .. . .J.j:i~ .. · ··-;·":'·, MM, ... ,v

~ 117

>5~12 ;::~4

::::~'i

.~:9120 - .. , -~~~"I , ........

~ ! C"li·j~

...... : i'",

.. _ .. _ .. 1 ..

: :.JJO :;46:3

:T~4~~1

4;1;1~~

75~5(1 3

1~:ij7·~j

li·:~:6

113t~~:~£ j65!j~1

lt)i 4:5 m~:;;

Ii~:

.:.::~~-

Ji~56

~5~1

115315 J~tl4·)0

4~64.S l

1:65!,:~

2:45~·:'·j

li3!55.i3

5u~hi2 lj~vj~1j

';,, .,_..,., l~.:5

ll.'5 ... , .. "•""''

,, -; .1".Jt_,

~.~.;

4. ~.3 • .: j "I.:;.,.

1 ! . '17 ,. ,._ .. .. 1 • .:.:.

E.76

,,. --! .. • r -~

11.65 ~.H 7.~~

i.:: 1U5

c.':1 1 1L:~ 4. 31i

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J " ' w ••

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