government expenditure and economic growth in bhutan, 1985
TRANSCRIPT
GOVERNMENT EXPENDITURE AND ECONOMIC
GROWTH IN BHUTAN, 1985-2015: A DISAGGREGATED
ANALYSIS
BY
MR. BAL BDR. KHARKA
A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF
THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF ECONOMICS
(INTERNATIONAL PROGRAM)
FACULTY OF ECONOMICS
THAMMASAT UNIVERSITY
ACADEMIC YEAR 2016
COPYRIGHT OF THAMMASAT UNIVERSITY
GOVERNMENT EXPENDITURE AND ECONOMIC
GROWTH IN BHUTAN, 1985-2015: A DISAGGREGATED
ANALYSIS
BY
MR. BAL BDR. KHARKA
A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF
THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF ECONOMICS
(INTERNATIONAL PROGRAM)
FACULTY OF ECONOMICS
THAMMASAT UNIVERSITY
ACADEMIC YEAR 2016
COPYRIGHT OF THAMMASAT UNIVERSITY
(1)
ABSTRACT
This thesis explores the effects of seven economic components of
government expenditure, namely, total expenditure, capital expenditure, current
expenditure, expenditure on agriculture and forest, information and communication,
economic affair and foreign affair on real GDP growth in Bhutan over the period 1985-
2015. In particular, it studies the effect of components of public expenditures that
contributes on a GDP growth in Bhutan. This research analyzed the impact of public
expenditure components on real GDP growth using annual data. We use Cointegration
and Error Correction Model (ECM) methods to examine long run and short run effects
on real GDP growth.
The empirical result showed that the total government expenditure,
capital expenditure, current expenditure, expenditure on agriculture and forest and
expenditure on information and communication are positive and statistically
significantly associated with the real GDP growth in the long run. The composition of
government spending on economic services showed positive but statistically
insignificant relationship with the real GDP growth. On contrary, government spending
on foreign affair has significantly adverse impression on the real GDP growth in the
long run. On the other hand ECM results revealed insignificant association between
expenditure and real GDP. However, ECM term in the GDP growth equation. It entails
that the real GDP will converge to long run equilibrium path when there is short run
deviation.
These research generalize the policy implication that the expenditure on
agriculture and forest and information and communication remains the most preferable
sector of the government to increase its expenditure within the economy.
Keywords: GDP, Government spending, Cointegration, ECM, and Bhutan
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ACKNOWLEDGEMENTS
First and foremost, my sincere thanks goes to the Ministry of Education,
Royal Government of Bhutan for giving me the opportunity to study master degree in
Thailand. And to TICA, I owe my genuine appreciation for providing me with all kind
of support including moral, spiritual and financial matters during the course of my
study.
Secondly, this thesis would not be successful without proper guidance from
my advisor, Dr. Chaleampong Kongcharoen. I would like to thank my advisor for his
constructive recommendations, suggestions, criticisms and advices which are
invaluable to complete this thesis. I also like to acknowledge my chairperson (Prof. Dr.
Pawin Siriprapanukul) and my external committee (Prof. Dr. Sumanee
Suppakomkosai) for all their support and guide to complete my research. I also
indebted to them for acquiescent to commit their precious time and for being so patient
with me all the time.
Thirdly, I exceptionally gratified to my Family, Parents, and Relatives who
have had encouraged and supported me for past two years until I completed my study.
I further acknowledge the support provided by Mr. Udhim Subba (Vice Principal) and
Mr. Jigme Dorji (Teacher) for making this thesis possible.
Last, but certainly not the least, I must thank our international program
coordinator Miss Wannah Vejbrahm. Without her support and encouragement, I would
not have accomplished my study productively within the prescribe time.
Mr. Bal Bdr. Kharka
Thammasat University
April, 2017
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TABLE OF CONTENT
PAGE
ABSTRACT ……………………………………………..……………….......… (1)
ACKNOWLEDGEMENTS …………………………………………….......…. (2)
TABLE OF CONTENT ………………………….…..……………..………........ (3)
LIST OF TABLES …………………………………………….…………......… (6)
LIST OF FIGURES ………………………………………………………....…. (7)
CHAPTER
1. INTRODUCTION …………………………...……………………….……1
1.1 Background of the study ……………………………………….……1
1.2 An overview of Bhutanese Economy …….............................................3
1.3 Gross Domestic Product by broad economic sectors………..................7
1.4 Annual GDP and economic growth rate of Bhutan………………...... 11
1.5 Trends and compositions of government expenditure in Bhutan…... 12
1.6 Composition of government spending by agencies (Ministry)…...... 14
1.7 Statement of the problem………………………................................. 16
1.8 Objectives of the Study ……………………………………….......... 17
1.9 Limitations, scope and organization of the research............................ 17
2. REVIEW OF LITERATURE …………………..………………….….. 19
2.1 Theories explaining the relationship between public expenditure
and economic growth …………………………..........………………... 19
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PAGE
2.2.1 Keynesian theory ………………………………………....…20
2.1.2 Classical theory……………………………………….……...22
2.1.3 The Neo-classical theory ………………………………….....23
2.1.4 Endogenous growth theory…………………………………...24
2.2 Review on past Empirical Studies…………………………………....25
3. RESEARCH DESIGN AND METHODOLOGY …..……………...….. 31
3.1 Theoretical Framework …………………………………….…...….. 31
3.1 The Econometric model and Estimation Techniques………..…...….. 34
3.1 Time Series Properties of the Data…………………………….....….. 37
3.3.1 Estimation issues……………………………………............... 37
3.3.2 Testing for Unit Roots………………………………............... 37
3.3.3 Error Correction Model………………………………............... 38
3.1 Data ……………………………………………………...……...….. 39
3.1 Definition and measurement of variables……………..………...….. 39
3.1 Working hypothesis ………………………………………………....41
4. RESULTS AND DISCUSSIONS..................................................................42
4.1 Descriptive study …………………….…………………………….....42
4.2 Descriptive Statistics……………………………………………….... 50
4.3 Diagnostic Testing... ………………..……………………….............. 52
4.3.1 Correlation Test……………………………………….............. 52
4.3.2 Multicollinearity Test ……………… ………..……….............. 54
4.4 Long run relationship and short run Adjustment ……………........... 55
4.4.1 Unit Root Test…………………………………………............. 55
4.4.2 Co-integration ………………………………..……….............. 56
4.4.3 Long run relationship estimation ……...……………………… 56
4.4.4 Short run adjustment ………..…………………………........... 62
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PAGE
5. CONCLUSIONS AND RECOMMENDATIONS ……………….……68
5.1 Conclusion ………………………………………………………...68
5.2 Policy Recommendations ..........................................................…...70
5.3 Suggestions for future research …………………………………..71
REFERENCES …………………………………………………………………72
APPENDICES ………………………………………………………………….80
A. Estimated result with different specification ……………………………….80
BIOGRAPHY…………………………………………………………………….86
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LIST OF TABLES
TABLES PAGE
1.2.1 Budget Summary of Overall Financial Position for the last five years….....6
1.3.1 Aggregate Outputs of national income ……………………………….......8
1.5.1 Classification of government expenditure by Ministry…………………....15
4.1 Descriptive Statistics…………….……………………………………….…..51
4.2 Model 1: Pair-wise Correlation Matrix………………………………………52
4.3 Model 2: Pair-wise Correlation Matrix……………………………………....53
4.4 Variance Inflation factor ….............................................................................54
4.5 Result of Unit Root Test…..............................................................................55
4.6 Residual Based Test for Co-integration (Stationary Test) …………………..56
4.7 Model 1: Long Run Estimation Result......……………………………….…..57
4.8 Model 2: Long Run Estimation Result......………………………….………..60
4.9 Model 1A: Short Run Estimation Result....…………………………….…….63
4.10 Model 1B: Short Run Estimation Result...…………………….…………....64
4.11 Model 1C: Short Run Estimation Result...………………….………………65
4.12 Model 2: Short Run Estimation Result...……………………….………...…66
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LIST OF FIGURES
FIGURES PAGE
1.3.1 Share of different Sectors to GDP ……………….………….…………….10
1.4.1 Overview of Annual GDP and Economic Growth in Bhutan …....................11
1.5.1 Trend of public expenditure growth in Bhutan .....................................…...13
4.1.1 Real Total Expenditure and real GDP of Bhutan, 1985-2015.........................42
4.1.2 Real capital expenditure and real GDP of Bhutan, 1985-2015.......................43
4.1.3 Real current expenditure and real GD of Bhutan, 1985-2015….....................44
4.1.4 Real agriculture expenditure and real GD of Bhutan, 1985-2015............…...45
4.1.5 Real information expenditure and real GD of Bhutan, 1985-2015.…….…...46
4.1.6 Real economic affair expenditure and real GD of Bhutan, 1985-2015….…..47
4.1.7 Real foreign affair expenditure and real GDP of Bhutan, 1985-2015...….....48
4.1.8 Real gross capital formation and real GDP of Bhutan, 1985-2015.…..….….49
4.1.9 Trend of real tourism revenue and real GDP of Bhutan, 1985-2015…..……50
1
CHAPTER 1
INTRODUCTION
1.1 Background of the study
The relationship between public expenditure and economic growth has
been a long-standing debate in public economic literature. Foundation with Robert Solo
and Trevor Swan, the Neo-Classical economists initiated to investigate how economies
grows (Harberger, 1978). Keynesian economists proposed the government role through
the budget management on the economy. Barro (1990) stated that only the productive
expenditures, such as public investments, can have a significant impact on economic
growth. However, government consumption expenditures would have adverse effects
on growth. Therefore, many developing countries have implemented the public
expenditure as a measure to promote economic prosperity. Moreover, researchers have
focused on the composition of public expenditure on the country’s growth. They
believed that spending on some sectors or types have a greater effect on growth than
the others (Olabisi & Oloni, 2012). Therefore, government expenditure is expected to
bring better economic growth by reducing adverse effects of market failure on economy
and by reducing unproductive use of public funds.
The relationship between economic growth and components of
government expenditure is a critical subject of analysis as these two are related (Stiglitz,
1998). Effective use of nation’s resources for enrichment of both human capital and
physical infrastructures would lead to improve productivity and income, so escalating
the choice for both private and public expenditure prospects (World Bank, 2007). Al-
Yousif (2000) and Abdullah (2000) viewed that enlargement of government
expenditure adds greatly on growth. Keynesian view also suggested that increasing
government expenditure leads to an expansion of outputs, which rises total demand
resulting to an increase in real GDP.
The economic growth based on mercantilism theory that sustenance
government participation in the economy was owing to externalities, failures of the
market and public goods as stated in some reported literature of development. Some
2
economists have seen that a rise in government expenditure can be an effective tool to
spur aggregate demand for a stagnant economy and to bring about crowd-in effects on
the private sector. This is consistent with Keynesian view that the government spending
can positively impact economic growth when the government borrow from the private
sector and inject back through various spending plans.
In general, government has to perform two major functions; country
security and supplies of some public good and services. Security function helps to
reduce the risk of crime, corruption, protect life and property and the country as a whole
from external violence. The second functions encompass roads, defense, health,
education, construction, hydropower, relation, etc. The general view is that expansion
of government expenditure on education, health, agriculture and advancement of
infrastructure improve growth. Ranjan et al. (2008) established that expansion of
government expenditure has significant positive effects on economic growth. Likewise,
a dynamic and resourceful primary sector would empower a nation to nourish its
population, solve unemployment problems, receive external currency and provide fresh
materials for businesses and productions (Mapfumo, Mushunje & Chidoko, 2012).
In reality, many emerging economics of developing countries, the
required expenditure always exceeds the available resources. Huge amount of funds is
spent on defense, administration, development, religion, relation, welfare project and
various other relief operations. Indeed, the position is made worse by limiting the option
of raising additional revenue nationally. Bhutan is one of them. These countries also
have large number of informal sectors to get fund but they lack effective instrument of
collecting taxes. High taxes and borrowing to finance public services may however,
impose excessive burden on individuals and private sector thus decreasing the
incentives to save and invest. At the same time, change in fiscal policy in this regard is
considered as disincentives for private investment growth. On the other hand, the
volume of debt of these nations is also very little and outside borrowing is least
attractive. The best way for the policy maker or government in general, involves
prioritizing government expenditure to the most important sectors of the economy.
Bhutan as a newly evolving economy in the world, the action of
government is significant in scope and significance to accelerate economic growth.
Mostly government’s fiscal policy includes taxation, government expenditure,
3
correcting market failure and providing varieties of public goods such as roads and
bridges, security of a nation and street lighting have become fundamental instruments
of economic growth of a nation. Of the various policy tools, this study concentrates on
government expenditures which are the essential instruments for economic growth. To
this fact, there is neither a general consensus nor consistent evidence found regarding
the meaningful relationship between government expenditures and economic growth
(Chipaumire, Ngirande & Ruswal, 2014). Bhutan has mixed economic performance
since the start of first five year plan in 1961 and this study will focus on the role of
government in term of allocation of its resources on an economy.
1.2 An overview of Bhutanese Economy
Bhutan’s economy is largely based on hydropower, agriculture and
forestry which provide the main livelihood for more than 55% of the total population
at present time. Till the beginning of first five year expansion plan in the nation, the
economic actions were essentially undertaken in classical way. The economic
transactions were made through batter form and taxes were being composed in the form
of kind and human force. The people were to send certain slice of their agricultural,
forest and livestock produce to government and obligatory to provide services of labour
to accomplish national expansion accomplishments.
Today, India contributes largely on Bhutanese economy through trade
and monetary relation, financial assistance, and laborers for development project such
as hydropower and road construction. Moreover, productions in the industrial sectors
are of cottage type. Hydropower potential and Bhutan’s attraction to tourists are main
source income in Bhutan. On an average, the hydropower sector contributes around
45% of its gross revenue to the government. This contribution accounts for about 30%
of the government’s total domestic revenue. However, the government has made some
progress in expanding the country’s productive base by improving social welfares.
Model education, infrastructure development, environmental programs are underway
with support from various multilateral development organizations. Multilateral
development organizations administer generally environmental, social and educational
4
programs. In addition, major investments in the hydropower sector, construction
sectors, training and basic by the government and development partners have critically
contributed to the overall progress of the economy. Eventually, the size and allocation
of government expenditure have transformed remarkably over the last three decades.
The state of public finance management is a matter of serious concern
as government expenditure is increasing faster than available income and external
revenue. Bhutan continues to make momentous and continuous improvement in
achieving the Millennium Development Goals, achievement of vision 20201 and
Bhutan’s goals of green socio-economic development and vision of self-reliance. The
MDGs concerning to poverty elimination, improvement in educational, maternal and
child health, high-risk diseases and environmental sustainability are the main
challenges discussed in any plan period.
Since the commencement of first five year plan and inaugural of the
economy to the external world, Bhutan would able to uphold an increasing trend of
investment. The investment rate in Bhutan has rose from 32% of GDP in the 1980s to
56% in 2015. According to World Bank, Bhutan’s gross domestic saving as a
percentage of GDP was 27.6% as of 2015. Its maximum rate over the past 36 years was
recorded 43.7% in 2012, while its lowest value was – 0.5 in 1981. Even if there was an
upward saving trend, the savings were always insufficient to finance the volume of
required investment, i.e. existence of investment saving gap which made Bhutan to rely
gradually on outside resources to finance its capital budget. In general, major cause of
widened gap in saving-investment is the result of huge budget discrepancies incurred
by the government. Meanwhile, government continues to depend greatly on overseas
grants to finance its gap. Grants finance was around 36% of the total spending in the
fiscal year 2012-2013. The total outstanding public debt as a percentage of gross
domestic product (GDP) was 98.3% as of 30th June, 2015 (National Budget Report,
2015). This is because capital expenditure remains dependent on external financing.
While current expenditure was fully meet through domestic revenues in the medium
term. ODA or grants remains a necessary development input to Bhutan’s aspiration of
1 See Bhutan 2020 guide book
5
Gross National Happiness in the near future. However, all these achievements and
progression have been guided by many important documents like seasonal papers,
Bhutan vision 2020, Mid-term plans, Gross National Happiness guidelines and the
constitution of kingdom of Bhutan for its smooth development.
In every fiscal year, as prerequisite by Public Finance Act, 2007,
Ministry of Finance is accountable for total administration of financial supervision
through effective and efficient use of public resources. As commanded for maintaining
healthy fiscal and macroeconomics policies, Ministry of Finance coordinates, organizes
and publish government financial statistics. Publication of the Budget and
Appropriation Bill are done after it has been passed by the Parliament. The outline of
the presentation contains four types of budget summary namely Resources, Outlay
(capital and current)2, Fiscal Balance and Financing. These budget estimates are
presented by Ministry of Finance taking into consideration the total government
expenditure ceiling. The statement of budget is made and presented according to the
rule and regulation prescribed in Public Finance Act of Bhutan 2007. The fiscal frame
work of government for last five fiscal years is shown in table 1.2.1.
2 As mandated by the constitution and the fiscal policy of the
government, the current expenditure is fully financed from the domestic revenue.
6
Table 1.2.1
Budget Summary of Overall Financial Position for the Last 5 Years
Figures in Millions Nu3.
Items 2010/11 2011/12 2012/13 2013/14 2014/15
Total Resources 30,990.7 28,171.76 32,646.36 30,656.12 36231.05
Domestic Revenue 15,638.4 17,458.80 20,354.46 21,101.61 25141.03
i. Tax 9,655.78 11,593.49 14,676.93 15,403.12 18387.34
ii. non-tax 5,982.65 5,865.311 5,677.533 5,698.573 6753.70
Grants 11,118.9 10,497.73 12,501.52 9,562.636 9955.02
i. India 7,306.39 7,882.77 9,003.442 4,693.402 2125
ii. others 3,812.49 2,614.96 3,498.078 4,869.234 52.50
Other Receipts 4,233.37 215.235 (209.627) (8.210) 1135.01
Outlay 29,888.9 29,842.45 33,688.01 34,900.81 34334.26
Total Expenditures 25,831.8 29,521.92 34,842.76 36,527.82 36475.85
i. Current 12,902.6 14,735.08 16,705.65 18,096.55 21032.04
ii. Capital 12,929.1 14,786.85 18,137.12 18,431.26 15443.81
Net Lending (400.37) (906.605) (1,036.57) (739.889) (2552.8)
Advance/ suspense 334.728 1,227.133 (118.180) (887.117) 411.156
Fiscal balance 1,101.69 (1,670.69) (1,041.65) (4,244.69) 1896.80
Financing (1,101.7) 1,670.69 1,041.654 4,244.692 (1896.8)
Net Borrowing 81.986 293.970 (1,007.15) 492.306 (1086.4)
Borrowing 2,817.51 3,110.01 6,212.866 16,463.46 1685.27
Repayments 2,735.53 2,816.04 7,220.013 15,971.15 2771.68
Resource Gap 1,183.67 (1,376.72) (2,048.80) (3,752.39) 810.39
Source: Annual Financial Statement (AFS), Bhutan
The fiscal year 2014-15 ended with a fiscal surplus of Nu. 1896.80
million (1.5% 0f GDP) comparing to fiscal deficit of Nu.4244.69 in the previous FY.
The total resource realized was Nu.36231.05 million as against the total outlay of Nu
3 Ngultrum (Nu.) is the name of Bhutanese Domestic currency
7
34334.26 million for the fiscal year. The total expenditure during the FY 2014-2015
was Nu 36475.85 million which is about 29% of the GDP. The overall expenditure
increased by 5.4% from the previous FY due to the increase in the current expenditure.
The realized domestic revenue for the FY 2014-15 was Nu 25141.030 million (20.1%
of GDP) which is an increase of 8.2% from the previous FY constituting Nu.18387.32
of tax revenue. The increase in domestic revenue was mainly contributed by tax
measures introduced by the government during the fiscal year.
1.3 Gross Domestics Product by Broad Economic Sectors
The economic growth experienced in the last two and half decades has
brought about significant quantitative and qualitative changes in every sphere of human
activity; the primary sector, the secondary sector and the service sector. Primary sector
embraces Crops, Livestock and Forestry activities. Secondary sector embraces
manufacturing, electricity, water supply, and construction. Service sector embraces
hotels, restaurants, whole sale trade, retail trade, finance, insurance, transport and
communication, real estate, etc. Faster growth in Bhutan is escorted by an improvement
of productivity of the factors of production. Increased per capita capital stock,
technological improvement, an increase in the education achievements and health
standards have contributed with substantial rise in the productivity of labour in
particular and other factors in general.
Household consumption expenditure remained the principle constituent
of GDP growth in the 1980s accounting for nearly 85 percentage, subsequently
decreased to 43.3% in 2012. From being consumption-led economy, the growth is now
largely driven by capital expenditure. Capital accumulation was around 10.7% in 1980
but now it contributes more than half to the share to GDP growth amounting to 57.7%.
Thus, Government expenditure is a key constituent of national total income as seen the
expenditure method to measuring national outputs. This tells us that government
expenditure is a key element of the magnitude of the economy and economic growth.
For more detail see Bhutan’s national income aggregate presented in the table 1.3.1
below
8
Table 1.3.1
Aggregate Outputs of National Income.
Figures in Million Nu.
Year Consumption Investment Government X-M
Private Public
1980 768.78 248.40 86.61 248.36 -197.75
1982 910.33 316.93 192.85 294.09 -390.82
1983 1234.12 411.16 250.15 398.69 -473.45
1985 1562.92 502.78 431.50 504.91 -614.63
1986 1605.83 361.48 680.08 518.77 -518.10
1987 1765.49 395.19 800.71 570.35 -98.52
1989 2449.28 506.05 950.17 791.26 -274.02
1990 2643.50 715.93 836.35 854.00 -267.00
1993 3791.00 1794.50 1575.58 1178.50 -898.40
1995 3977.00 2708.12 1710.81 1773.00 -477.70
1998 8646.00 3085.51 3029.97 3039.00 -2537.90
2000 9415.96 6785.52 3080.14 4330.96 -3732.11
2001 10281.28 9802.00 3564.38 4841.13 -4824.54
2002 11415.07 11709.19 4095.70 5390.43 -6645.85
2003 12994.88 14258.22 2647.95 5919.54 -7330.20
2004 13806.72 16927.44 3235.99 6649.72 -9915.72
2005 14586.17 15131.55 3669.72 7911.51 -9460.87
2006 15553.70 13682.56 5189.53 8644.25 -1935.42
2007 19372.88 9619.55 6302.45 9454.77 -1150.83
2008 21761.78 16150.76 6729.17 10372.57 -5019.45
2009 27202.22 21231.70 7038.24 13082.07 -10715.53
2010 31752.11 33986.68 10373.30 14487.85 -20501.25
2011 34927.33 46124.75 11660.59 17047.84 -24874.52
2012 42690.24 50256.60 15996.22 18691.15 -23693.89
2013 53362.80 36275.41 13070.39 18274.46 -22988.64
2014 55486.02 58106.60 11802.84 20194.04 -25168.39
Source: National Statistical Bureau, Bhutan
9
In 2014, the structure of Bhutan’s economy was mainly contributed by
private investment and household consumption (see table 1.3.1). The total export
mainly relied on agricultural products and accompanied by electricity in the recent time.
Despite being agriculture-centered, the Bhutanese economy has
increasingly been dominated by secondary and service sectors over the decades.
Economy has experienced vast structural changes that are usually considered to be a
major feature of modern economic growth; a shift of economic undertakings from the
primary sector to the secondary and service sectors activities. According to United
Nations analysts, such shift in the economy is principally due to significant growth in
the hydropower and construction sectors that have not yet been accompanied by
dynamic growth and progresses in the manufacturing and industrial based sectors in the
country. In particular, the expansion of hydro-power projects has become powerful
driver of economic growth and is now main source of income, accounting for about
one-fifth of GDP in Bhutan and about 30 percent of total government revenues
(International Monetary Fund 2014).
The service sector, especially tourism sector, is also the key source of
economic growth in Bhutan. In 2014, the number of tourists visited Bhutan was around
155,121 with the gross earning of USD 71.04 million. International arrival make up
37.09% while regional arrivals constitute 62.91%. These achievements of
transformation was mainly due to modernization and globalization of the Bhutanese
economy. However, government on its cautious expansion of the tourism, encourages
only environmental friendly tourists.
Furthermore, GDP estimates at three broad aggregate levels: Primary,
Secondary and service sector is presented in figure 1.3.1. The contribution of each of
the sectors varied greatly over the years.
10
Figure 1.3.1
Share of different sectors to GDP
Source: Author’s computation, data from NSB4
Notice in the above figure, in 1991, the contribution of primary sector
was 40.9% to the share of GDP which was declined to 16.77% in 2014. On the other
hand, the growth of primary sector was recorded 2.37% higher over the previous year
in 2014. With the decline in the share of primary sector over the year, the share of
secondary and service sectors increased steadily from 30.6% and 28.8% in 1991 to
about 40.55% and 42.68% respectively in 2014. In fact, the contribution of service
sector was recorded as highest to the share of GDP in recent times. These contributions
comprised mainly of tourism and services related to tourism. Its share stood at 42.68%
of the GDP in 2014 as compared to 41.55% in 2013. Passing over the decades has seen
bigger range of structural dynamism. These changes is notably contributed by an
upsurge in the adeptness of utilizing the existing resources, an increase in the quantity
of existing resources and technological advancement and innovation.
4 NSB stand for National Statistical Bureau of Bhutan
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
45.0
50.0
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
Per
cen
tage
sh
are
to G
DP
YearPrimary Sectors Secondary sectors Service Sectors
11
1.4 Annual GDP and economic Growth rate in Bhutan
Bhutan’s economic growth over the past three decades has averaged
more than a remarkable 7.0% until 2010 after which there was a decline in economic
growth, hitting a minimum of 2.14 percent in the fiscal year 2012-2013. However, the
economic growth was not consistent over the year. This challenges is due to High
trading costs lead to difficulties in diversifying the narrow economic base. Of the total
GDP, 27% is trade deficits and most of the export is hydropower.
The figure 1.4.1 depicts clearly that the annual real GDP was Nu
59240.01 million in the year 2015. The Gross Domestic Product worth of Bhutan
constitutes less than 0.01 percent of the global economy. Bhutan GDP averaged 0.67
Billion US dollars between 1990s and 2014, attaining to USD 873.22 million (Nominal
GDP=Nu.125880 million, 2015) in the year 2015 and USD 0.14 billion recorded in
1980 (World Bank).
Figure 1.4.1
Overview of annual GDP and economic growth in Bhutan
Figures in Million Nu.
Source: Author’s computation, data collected from NSB
0
10000
20000
30000
40000
50000
60000
70000
-5
0
5
10
15
20
25
30
35
1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015
Rea
l GD
P (
Mill
ion
s N
u.)
Eco
no
mic
Gro
wth
YearEconomic Growth (G%) Real GDP
12
Given a small size of the market and limited natural resource base,
Bhutan’s economic growth has primarily been driven by hydroelectricity, construction
and tourism sectors. Bhutan was identified as the second fastest-growing economy in
the world in 2007 (World Bank, 2007). This was mainly due to the commissioning of
the gigantic Tala Hydroelectric Power Station. The variance in growth rate over the
year was due to the high proportion of economic output pertaining to the hydropower
sector. And also the volatility of output in Bhutan is the result of highly non-diversified
economy that is comprised largely of the capital-intensive. Foreign direct investment is
not yet officially operationalized. Therefore, complicated controls and ambiguous
policies on industrial licensing, trade and commerce, migrant labour, and finance
continue to hinder foreign investment strategies and economic growth in general.
1.5 Trends and Composition of Government Expenditure in Bhutan.
The system of modern public finance in Bhutan is of very recent origin.
Ministry of Finance presented the first budget on contemporary lines in 1971. It was
called the Civil Budget as it covered the needs of the Ministry of Finance, Home affairs
and Agriculture and so on. The requirements of development oriented Ministries like
Communication and information, Trade and Industry, Foreign Affair were provided
under a separate development budget administered first by the Development Secretariat
and then by its successor, the Planning Commission. With the commencement of the
First Five Year Plan in 1961, the classification of the government budget into Civil and
Development was replaced by the concept of Maintenance and Development
Expenditures. Maintenance or Current Expenditures reflected mostly the current or
consumption expenditures of the government while development expenditures were
identified largely with the expenditures of the government on fixed capital formation.
The Royal Government of Bhutan has given almost equal priority to both capital and
recurrent expenditures in terms of budget allocation. Free education system, health care
facilities and frequent increase of civil servant salaries made current expenditure rise
up faster and because of rugged mountains dominated the terrain, made building of
roads and other infrastructure difficult. While planning its total expenditure, each sector
13
of the economy, depending on requirements, receives their own share of money.
Mostly, current expenditure of the country was meet through domestic revenue and
capital expenditure from external sources.
The trend and composition of public expenditure as total expenditure,
capital expenditure and current expenditure are presented in figure 1.5.1. These
expenditure are based on constant price.
Figure 1.5.1:
Trend of Public Expenditure Growth in Bhutan
Source: Author’s computation
From figure 1.5.1, the total public expenditure displayed an increasing
trend in most of the year since 1985, by the year 2008, the amount of total public
expenditure expanded more than four times. In 1985 it was Nu.3498 million. In 2015
the expenditure folded 8 times higher than 1985. The budget for 2013-14 projected a
decline of nearly 9% in nominal spending compared with the revised budget for the
0
5000
10000
15000
20000
25000
30000
35000
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
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2011
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2013
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2015
Go
vern
men
t Ex
pen
dit
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Year
Figure in millions Nu.
Capital Expenditure Current Expenditure Total Expenditure
14
previous fiscal year, 2012-13. This is because of the shortage of rupees (Indian currency
reserve). The government has tightened the country's expenditures to bring it in line
with the available resources. Another reason is the slow start of the budget year
following elections, the change of leadership, and delays in foreign grant
disbursements.
The link between planning, allocation and policy of public resources has
been strengthened through the Medium Term Review expenditure framework (MTR).
The purpose of the Medium Term Review assess the improvement of Plan in the first
two fiscal years of the five years plan period and identify issues that are likely to hamper
the successful implementation of the plan. This is intended at providing opportunities
for next three years of the plan period to use resources efficiently.
1.5 Composition of Government Spending by Agencies (Ministry)
With the infusion of modern financial system, government have created
different departments (Ministries) to look after different sectors of an economy. It has
eight Ministries until 1999 and created two additional ministries, totaling to 10
ministries in fiscal year 2000. The old Health and Education Ministry was segregated
into two different ministries, which makes two additional Ministry, namely, Ministry
of Health and Ministry of Education. Furthermore, Ministry of Labour and Human
resource and Ministry of Work and Human Settlement were additional new ministries
created making 10 ministry at present. So, today there are 10 Ministries in Bhutan to
receive their share of budget every year. All these 10 ministries (departments) receives
their own share of fund depending on request with maximum ceilings.
These departments (Ministries) are important components of public
expenditures allocations, which reveals public spending priorities. The public
expenditure strategies in Bhutan has focused their efforts on the affordability of the
current levels of public expenditure in which less emphasis has been given to where the
public fund is actually invested.
15
The government still faced big challenges in making a good choice
regarding the composition of its expenditure allocation in each sectors of Ministries.
However, each departments gets its annual budgets depending on availability of
resources and its priorities.
The table below gives quick glimpse of the allocation of public
expenditure by Ministries for the year 2010 to 2015.
Table 1.5.1
Classification of government expenditure by agencies (Ministry)
Figures in millions Nu.
Ministries (Agencies) 2015 2014 2013 2012 2011 2010
Agriculture and Forest 2737.2 2600.6 2570.3 2082.6 1787.3 1788.3
Infor. and Communication 917.62 698.3 1324.5 1583.6 1182.9 518.4
Economic Affairs 794.09 701.6 774.2 869.1 1890.3 1048.2
Foreign Affairs 555.8 566.7 537.9 639.6 416.2 353.2
Home and culture 2141.4 1765.1 1914.2 1957.9 1580 1305.4
Education 1798.7 886.8 1312.3 1124.1 729.1 798.5
Health 1526.4 1443.8 1799.8 1674 1422.4 1357.1
Finance 6180.6 7973.8 5829.8 4946.8 3928 3787.3
Works and Human
settlement
4273.1 4027 4664.7 4072.6 2776.6 3135.7
Labour and Human
Resource
515.4 427.6 421.9 465 343.6 324.6
Source: National Statistical Year Book, National Statistical Bureau, Bhutan
Table 1.5.1 shows the division of public expenditure amongst different
departments (Ministries). Expenditure data shows that Bhutan allocate a relatively
larger proportion of its available resources on Ministry of Finance, Work and Human
Settlement, Agriculture and Education. Economic Affair and Foreign Affair
expenditures amongst all departments show relatively smaller proportion of resource
allocation. Ministry of finance received highest spending since it deals with debt
16
management, civil servant salaries and so on. As mentioned earlier, the fall in
expenditure share in 2014 for some departments as compared to 2013 was due to
election and delay in received of external budget such as grants. In general, economic
and public services have been given the highest priority. This area includes agriculture,
housing and community, mining and manufacturing, communication, energy and road.
Similarly, social service such as health and education also receives huge share of
expenditure. This disbursement of revenue is organized in accordance with public fiscal
policy on the grounds of equity verses efficiency to achieve desired target.
1.7 Statement of the problem
The impact of public expenditures on economic growth needs to be
considered in newly emerging countries, especially in those countries anguish from
high poverty, unemployment, humble exploitation of existing resources, and the
hastened rates in budget deficit as a percent of the GDP’s of these countries. Bhutan is
one of them. Bhutan continuously suffer from a negative fiscal balance in the general
budget and a decline in the balance of payments, which confines its ability to stimulate
economic growth and delays critical development investment and the full achievement
of Millennium Development Goals and Bhutan’s vision of 2020 goals. The fiscal deficit
widened significantly in the fiscal year 2010/2011 reaching 4.8% of GDP, compared to
a surplus of about 1.7% in the fiscal year 2009/2010. This was mainly because of an
escalation in capital spending on infrastructure set-up coupled with sluggish in
revenues. The total outstanding public debt (internal and external) as of 30th June 2014
was accounting for 98.3% of GDP.
Nonetheless, Public expenditure in Bhutan has grown tremendously
over the years despite the government efforts to rationalize expenditure through
downsizing and other budgeting measures. Unfortunately, increasing expenditure has
not transformed into dynamic growth and development, as Bhutan is still a least
developed country (UNCTAD, 2014). As a result, the government is faced with hard
choices when undertaking public expenditure cuts since the question of which
departments of public expenditure should be reduced; whether Culture, Education,
17
Infrastructure or Agriculture depends on the role of these agencies to growth. Thus,
there is a cause of concern to policy makers on the implications of such expenditure
cuts to economic growth. Consequently, this research try to inspect the different
components of public spending in Bhutan and how they influence economic growth.
The finding from this paper will help the planner or the policy makers in prioritizing
most scared and limited public resources so as to achieve optimal economic growth
through budget rationalization.
1.8 Objectives of the study
The main objective of this study is to investigate the impact of public
expenditure on economic growth in Bhutan, focusing on the various components of
government spending. Specifically, the study seeks to answer following two questions:
1. What is the relationship between public spending and the economic
growth in Bhutan?
2. What are the most important components of public spending that
contributes on an economic growth in Bhutan?
1.9 Limitations, Scope and Organization of the research
This research have many shortcomings. One of the main limitation is the
reshuffle of Ministries in the fiscal year 20005, so collecting relevant data and choosing
main components or sectors in the study introduced big hurdles. Owing to the limited
availability of data, we could not include the most important sectors such as education
and health. The other obstacle is that no studies has conducted so far in relation to real
GDP growth and government expenditure in Bhutan. Therefore, referencing the
relevant literature posed further challenge. Thus, the study mostly used annual
documents like national statistical year books, seasonal papers besides many other
international journals and books.
5 See section 1.5 for more details.
18
Considering the limitations mentioned above, the study will focus on the
main four components of government spending which are Agriculture and Forestry,
Information and Communication, Economic Affairs and Foreign Affairs. This research
is ordered into five different chapters. The theoretical and empirical literature is
reviewed in the next chapter. Research design and methodology is outline in the chapter
three. Chapter four comprises of analysis and discussion of the finding. Conclusion and
recommendation are shown in chapter five.
19
CHAPTER 2
LITERATURE REVIEW
2.1 Theories explaining the relationship between public expenditure
and economic growth
There exists an extensive disagreement among planners regarding the
impact of increase in public spending on achieving economic growth. Government
expenditure includes all kinds of government consumptions, investments and transfer
payments made by a nation. Government spending can be financed by taxes,
government borrowing and foreign aids. Every country around the world tries to
maximize GDP growth rate by increasing government spending.
The issue of economics is best explained by Adam Smith in his book
“Wealth of Nation”, his incredible book published in 1976. Only examining the
economic growth can assist in identifying the cause why some countries are prosperous
and others poor. Many growth theories of deal with the long-run movements of an
economy (Branson, 2002). It states the features which affects economic growth over
time and analyzes the factors that permit some nations to grow very quickly, few gently
and others remain stagnant. In general, in many developing countries, national spending
has maintained a very crucial part in sinking district gaps through use of social services
activities, development of infrastructural amenities in connection to road and
telecommunication services, growth of commerce, health, education, training and so
on.
There are many well-known economic theories which elucidate the
impact of public expenditure on economic growth which also provides a solution in
order to redistribute available income or resources on most productive sectors.
20
2.1.1 Keynesian Theory
In the nineteenth century, economists commonly advocated a nation
with minimal economic function. This was a reaction to failures in the eighteenth
century due to heavy government alterations (Schuknecht, 1995). At the end of world
war 1, the perception about the function of government has changed quickly due to the
great influence of J.M Keynes who argue that the government still had many things to
do which were not yet been done.
The early step of the Keynesian uprising took place in the years after the
publication of Keynes' General Theory in 1936. The theory was based on spending in
the economy and its effects on output and inflation. Its analysis arrives at the conclusion
that aggregate demand managing procedures can be employed to boost economic
performance as demand is a prerequisite for growth. Harrod and Domar are the first to
develop macroeconomic model to formally analyze the problem of growth. Their
growth equation is the dominant model in the Keynesian framework which gives some
intuitions into the dynamics of growth. The model states that investment, saving,
technical progress and population growth as the main foundations of growth but
production is obtained only by means of labour and physical capital. So they focus in
goods market which assumes saving is identical to preferred investment.
The New Keynesian models argue that an expansion in government
expenditure increases demand and thus creates more economic activity that is output
through multiplier effect. He believes that aggregate demand is influenced by a host of
economic decisions, public and private and sometimes works both intermittently
(Blinder, 1986). This theory also suggests that fluctuations in total outputs, whether
expected/unexpected, have its paramount short period consequence on real income and
occupation (Blinder, 1988). Hence, an increase in the government expenditure is likely
to reduce unemployment and lead to increase profitability and investment through
multiplier effects on aggregated demand (Urban & Nordensvard, 2013). Subsequently,
Keynesian hypothesis is just opposite to the classical economist’s view in relation to
government expenditure and economic growth. The classical economists argue that
only final output will boost when there is an expansion in government spending. They
found that total expenditure as destabilizing mechanism on the development of an
output rather than dynamic force of economic growth as the Keynesian economists have
21
proposed. On other hand, Classical economists view in invisible hand to initiate full
employment equilibrium in the economy. Also they believe in government intervention
in the economy is not required because of the assumption that the invisible hand is the
best guide for the economy.
The new Keynesian models also argue that increase in government
expenditure will lift total output through crowding in effect. In contrary, increase in
government spending may also result in crowding out of private sector but if
government cut expenditure there may be decrease in private investment (Mudaki &
Masaviru, 2012). Keynes (1964) suggested that government expenditure should create
employment opportunities and exploit resource capital that has been underutilized
during the time when an economy is in a recession with high level of unemployment of
labor and capital. He believes that a severe down turn in economic activities may never
come to end if there is no government intervention. (Mitchell, 2005) stated that
government can improve economic declines by borrowing money from the private firm
and then returning the money to the private sector through various spending programs.
Barro (1990) argued that increase in expenditure will enhance output growth in the long
run. He demonstrated using Cobb-Douglas framework and viewed that government
expenditure has both steady state growth and output growth. Thus, it is clear that the
Keynesian views that public consumption affect the economy positively while the
classical economists assert that the effect is temporary since long run adjustment of
prices lead to optimal output and employment levels (Ocran, 2009).
Keynesian theory also states that spending of the government would
contribute immensely on economic growth. So, an increase in the government final
expenditure is likely to result in an up rise in employment, investment and productivity.
It means that government spending supplements increase in final outputs, escalating
that an additional output depended on expenditure multipliers effects. On the other
hand, opponents of this view stipulate that government consumption expenditure give
less room for private investor and adversely effects the short run growth and reduces
innovations in the long period (Diamond, 1989). Therefore, in Keynesian theory,
government expenditure is necessary to enhance economic growth. However,
Motivated by private sector and political parties, the government may misallocate
available limited public resources.
22
2.1.2 Classical Growth Theory
The groundwork of classical economics was laid by Smith (1723-1790) and
later evolved to its complete body in the nineteenth century. Featuring the process of
economic growth was the main idea in the work of the classical writers namely, Adam
Smith, Ricardo, and Malthus. Accordingly, it was felt the objectives of analysis to
identify the forces in the nation that promoted or deterred the economic development
and to provide a basis for policy and action to influence those forces (Harries, 1975).
The conventional theories of Smith and Malthus outline economic growth in terms of
immobile properties and growing populace. The supply of free land will ultimately
finish with an increasing number of population in case of absence of technological
changes. When available land became little to work then the marginal product of each
worker will also become lesser which will entail the decline in the reservation of real
wage. Malthusian equilibrium arises if real wages declines to the lower level, below
which the supply of labor will not produce outputs by itself. However, classical theorists
fail to consider the reality that technological change has retained economic
development continuing in industrial countries by persistently increasing the
productivity of labour onward (Samuelson & Nordhaus, 1989). In fact, the foundation
for classical growth model was laid by Adam Smith. He is one of the first economists
to develop a supply side driven growth model as a function of,
Y = f (L, K, R)
Where Y, L, K and R were output growth, labour supply, capital employed and land
respectively. Hence, the growth of output is the function of growth of land, labour and
capital and increase in overall productivity as highlighted below:
𝑔𝑌 = 𝑓(𝑔𝑃, 𝑔𝐾, 𝑔𝐿 , 𝑔𝑅),
Where small ‘g’ refers to the growth rate of all individual factors of production. In line
with this reasoning, Smith claimed that growth was self-enforcing as it demonstrates
increasing returns to scale. He explained economic growth endogenously, admitting
that the speed of output growth be contingent on the decisions and actions of every
23
agent with regard to saving-investment behaviors and innovations. Subsequently,
special focus is placed on the endogenous creation of new knowledge. New knowledge
and labour power is regarded as goods, which is in the long period tending to become
public goods. Diminishing returns to scale due to limited natural resources was
compensated by the increase in productivity due to the division of labor and
specialization.
To sum up, the conventional economists believed in an unseen hand, self-
interest, and a self-regulating economic system, as well as in the growth of monetary
institutions, capital accumulation and free trade. They also believed in division of labor and
specialization, the law of diminishing returns, and the ability of the economy to self-adjust
in a laissez-faire system lacking of government intervention. Malthus provided a new
dimension to Smith’s doctrine of growth by incorporating issues of population growth.
Classical economics logically leads to the creation of a capitalistic economic system.
2.1.3. The Neo-Classical growth model
The Neo-Classical growth theory is an economic theory that outlines
how a steady economic growth rate can be achieved. The theory suggests that
technological innovation takes central power on nation’s economy. It state that
economic growth will not have continuous progresses without better technology. In the
neo-classical theories, growth is measured in three different ways; increase in capital,
labour supply and productivity.
Robert Solow and TW Swan added labour in the production and capital
to output ratios are not fixed as they are like in Harrod function. According to Solow
model saving and growth of population rates are three central components of economic
growth. The function state that higher degree of investment leads to addition of higher
capital and output per individual worker. However, huge population growth creates
adverse effect on economic growth. It is because a higher fraction of saving in the
economy with high population growth has to maintain constant capital and labor ratio.
Hence in the absence of technological innovation and changes, an increase in capital
per each worker would not correspond to relative increase in output per worker because
of diminishing returns. Hence adding capital would diminishes the rate of return on
capital.
24
The main idea of Solow model is that the accumulation of physical
capital cannot account big growth in output per person over a time. The model
anticipated technological innovation and changes to grow at constant ‘steady state’
output growth. Other prediction of the model is that the growth may experience before
steady state output because growth slowdown and ceases as they approach to steady
state. This suggests that least developed countries with a lower value of capital and
output grow faster than rich countries and consequently the poor countries tend to catch
up with the rich countries.
In the Solow growth model, if an expansionary fiscal policy is continued
to adapt then the long-term consequences of growth may be a lower level of steady state
GDP. The intuition behind is that the government in budget deficit drives a wedge
between private saving and investment, as the government collects part of private
saving to finance the deficit. When this end up in lower saving being available for
private investment then it will lead to lower capital stock accumulation and lower steady
state GDP growth. Nonetheless, if government runs in deficit balance in order to finance
public investment on infrastructure and amenities, the negative effects could be reduced
on steady state income (Leach, 2002)
2.1.4 Endogenous Growth
Most endogenous growth models, principally the AK model and Lucas
(1988) model, stated that the higher domestic investment rate exerts a positive effect on
the economic growth rate in the long run. The endogenous growth model suggests that
economic growth is generated from within a system as a direct result of internal
mechanism. In brief, the theory state that the improvement of a country's human
resources will lead to economic growth by innovating new systems of technology and
efficient means of production. Additionally, Endogenous Growth model provides the
fact that to rise productivity; the work force must persistently be improved with
abundant inputs such like physical, human and knowledge capital. Thus, growth is
pushed by the capital accumulation and it is the outcome of private investment. The
endogenous growth model explains the association between government spending and
economic growth where public expenditure composition is taken as one of the
determinants of economic growth (Sanz & Velazquez, 2001). Within the endogenous
25
growth model, governments make policies aimed at improving the resource allocation
where market forces have failed to improve. The model makes a distinction between
nonproductive and productive public expenditure whereas productive public
expenditure is believed to be critical in complementing private sector production
(Barro, 1990). It means that the best way a government can affect economic growth in
the long run is through greater investment in human resource, health and education and
research and development.
Endogenous growth models consider public spending by linking it with
the economy‘s long-term growth rate (Devarajan, et al., 1996). Further, economic
forces explain the positive relation between technological progress and the
accumulation of human knowledge.
2.2 Review of Existing Empirical Evidence.
Many researchers already tried to find out the association ship between
government expenditure and economic growth around the glove. In the past empirical
studies, existence of relationship (Ram, 1986) explained about total government
expenditures and economic growth while others found public expenditure is negatively
linked with growth (Landau, 1986) and yet some have found insignificant relation
between public spending and economic growth (Kormendi, 1985). A study by
Aigheyisi (2013) using 32 years’ time series data establish that total expenditure and
current expenditure showed positive impacts on GDP growth which was also
statistically significant in long term.
In most of the unindustrialized countries, many research focuses on
examining the part of public investment in the context of growth. There is believe that
bigger investment in infrastructure and human resource accumulation can promote long
term economic growth of a nation. This types of investment will also encourage private
sector participation and enhance productivity. According to Khan and Kumar (1997)
on their study on relative return between public and private investment amongst 95
emerging countries, they found that private investment has more impact than public
investment on growth. However public investment provide complimentary to private
investment. However, low income country will feel greater return from investment than
26
high income country. Alshahrani et al. (1997) using VECM in Saudi Arabia conformed
that public investment has potential to boost long run economic growth.
Albatel (2000) studied the association ship between government
expenditure and economic growth in Saudi Arabia: The study states that government
expenditure exerts positive impact on economic growth. A study conducted by Dandan
(2011) found that the total government expenditure has positive impact on GDP growth
which is also consistent with the Keynesian's theory of fiscal policy. Similarly,
Gemmell, Kneller &Sanz (2015) used multiple regression models in Nigeria for the
period of 1970 and 2011. They have concluded positive relationship in the long run
between public expenditure and economic growth in Nigeria. Also, (Al-Obaid, 2004)
analyzed the long run relation between government expenditure and real GDP where
findings showed statistically positive long run relationship between share of
government expenditure and per capita income. Recently, Lahirushan and Gunasekara
(2015) studied using panel data amongst nine Asian countries using co-integration
technique; fixed effects and Causality test (These countries include China, Japan, South
Korea, Singapore, Thailand, Malaysia, Sri Lanka, India and Bhutan). The empirical
findings showed significant positive impact of government expenditure on GDP growth
in Asian region. Seemingly, government expenditure and economic growth revealed a
long-run relationship in Asian countries and found that there is a unidirectional
causality flowing from economic growth to government spending and government
spending to economic growth in Asian countries. These findings, in general, meet the
expectation of outcome of public spending on growth. In reality, every emerging or
industrialized country expects positive results of their spending on nation’s growth. In
contrary, Alshahrani & Alsadiq (2014) estimated using system equation model and
states that economic growth is positively related to private domestic and public
investments in the long run. Larger Spending on building houses can also lift short term
economic growth. However, some other economist like Barro (1990), he stated negative
impact of public expenditure on economic growth. In addition, Devarajan (1996) also
observed that government capital expenditure has negative relationship with per-capita
growth.
A few number of studies has also focused attention on causality between
government expenditure and growth. Lai and Cheng (1997) conducted study in Korea
27
applying a VAR econometric technique. They have concluded bi-directional causal
relationship between government expenditure and economic growth exists. Aigheyisi
(2013) also found bidirectional causation between total expenditure, capital expenditure
and GDP. It means causality runs from both the directions in Nigerian economy. A
recent study by Lui et al. (2008) on causality between gross domestic product & public
spending in United State, the study confirmed that government expenditure cause
growth of GDP. However, the growth of GDP does not cause expansion of government
expenditure. Similarly, Loizides & Vamvoukas (2005) examined if the relative size of
public total spending in GNP Granger cause the rate of economic growth by employing
the trivariate causality test using data set on Greece, United Kingdom and Ireland. They
have found that government size granger causes economic growth rate in all the three
countries. And also, economic growth granger cause public expenditure for Greece and
United Kingdom when they add inflation in the data set. It is also clear that the statistical
results were true for the United Kingdom and Ireland both in the long run and short run.
Similar type of studies was piloted by Bader and Qarn (2003) to state the causality
between growth and expenditure in three different countries. They confirm that the
government expenditures and economic growth reveal negative relationship from both
the direction in Israel and Syria and one sided negative short run causality running from
economic growth to government expenditure in Egypt. In similar way Ebaidalla (2013)
using Granger causality test in Sudan for the period of 1970 to 2008 found that the
government expenditure can cause national income but not national income causing
expenditure growth. This result also propagates the support of Keynesian proposition
of public spending stimulating economic growth.
In the recent times, the association ship between different departments
of expenditures components and economic growth has received a lot of attention
amongst researchers. For an instant, as per the finding of the effect of different
components of public expenditure on growth is concerned, (Devarajan, 1996) stated a
positive and significant association ship between current expenditure and real GDP and
negatively significant association ship between capital components spending and real
GDP for 43 countries. The study conducted by Ghosh and Gregoriou (2008) in 15
developed and developing countries confirms that current public spending has
positively significant effect on the growth while capital spending has adverse but
28
significant effect with growth. In contrary, statistically insignificant estimated results
was also confirmed by Chamorro-Narvaez (2012) and Al-Fawwaz (2016) between
development expenditure and growth in Jordan. On the other hand, (Nurudeen &
Usman, 2010) in Nigeria stated that development expenditure, current expenditure and
government expenditure on human development have an adverse impact on economic
growth. Similar idea is also evident from Nworji, Obiwuru, Okwu and Nworji (2012)
in which case they found that government capital expenditure was inversely related
with economic services. But government expenditure on transport and communication
and health resulted positive impact on economic growth. On the other hand (Joharji &
Starr, 2010) examined using annual time series data to find the relationship between
development and maintenance expenditures between GDP in Saudi Arabia. They
confirmed that increase in government spending on current expenditure have greater
positive impacts on economic growth than capital expenditure. On contrary, a study in
Gulf Cooperation Council (GCC) by Espinoza and Senhadji (2011) confirmed capital
expenditure has larger impacts. Maingi (2010) stated the impact of public spending on
real economic growth using annual time series data for the period 45 years in Kenya.
Researcher applied Vector Auto Regression (VAR) estimation technique. The findings
argued government spending on education and infrastructure enhances growth in the
long run. In Similar way, Ashaure (1989) examined the link between aggregate outputs
and some government spending variables in the United States over the period 1949 -
1985. It was found that expenditure on electricity and gas supply, highways and streets,
mass transit, water and sewage system displayed influential positive significant on
growth.
Recent study by Musaba, Chilonda and Matchaya (2013) using VECM,
found that sectorial government expenditure related to education, health, agriculture,
defense, social safety and transportation and communication has insignificant
relationship on economic growth in short run. However, the long run results postulated
that government expenditure on agriculture and defenses has significant positive
impacts on economic growth. Spending on agriculture was potentially strong in
promoting economic growth (Fan, Yu & Saurkar, 2008). In contrary, Saad and
Kalakech (2009) used the same method and concluded that government educational
expenditure of its citizen confirmed positive relationship to economic growth in the
29
long period and adverse association ship in the short period of time and agriculture
expenditure and defense has a negative impact on economic growth during the long
period and insignificant impact during the short period of time.
In the empirical findings it was noted that public expenditure on
education is positive significant determinant of economic growth while spending on
security reason were seen to be insignificant to drive economic growth (Mudaki &
Masaviru, 2012). Increased expenditure on agriculture showed significant but
negatively related to economic growth. It was also clear from the study that expenditure
on economic affairs, transport and communication were also significant but weakly
related to economic growth. Similar idea is also evident from (Vu, 2005), where
telecommunication network are very responsive to growth. Erhan (2012) also
concluded that information and communication paly very important role in promoting
economic growth. Amasoma et al (2011) in Nigeria, using same method for the period
ranging 1970 to 2010 found that expenditure on agriculture was strongly significant to
economic growth and spending on information and communication, education were
prove to be insignificant in short and long period of time. On contrary, Musibau &
Rasak (2005) found that education prevails long run relationship to build a nation. In
case of infrastructural expansion Albala et al. (2001) argued positively significant
association with economic growth.
Similarly, ARDL estimates in Nigerian economy reveals that forestry
expenditure promotes growth while spending on education, transport has neutral impact
on long term growth. For the short period, these sectors were insignificant and also
government expenditure on defense retards the economic growth (Aremu et. al, 2015).
However, ARDL test result found out by (Egbetunde & O Fasanya, 2013) in the same
countries using time series data (1970 to 2010) contradicts with the above finding in
which the researcher proclaims that the frameworks are bound together conforming
significant long run relationship.
Lastly as highlighted in the review above that some researchers believe
that government involvement in the economy will bring economic growth while others
strongly opposes believing that government involvement in activities inherently is
inefficient and bureaucratic which deter economic growth. Yet some studies still view
30
that government spending was indeterminate of economic growth (Najkamp & Poot,
2002)
While economic theory does not provide clear cut solution to the debate
of how different constituents of government expenditure affect economic growth. On
the other hand, empirical evidence provides conflicting results in this regard. Therefore,
more empirical analysis is required to capture the relationship between economic
growth and different components of government expenditure to bridge the research gap.
Especially, to situate the study within the context of particular economy would
determine the phenomenon specific to where the study is conducted. In Bhutan, having
no such study being undertaken, this study would add to the literature on the issue from
the Bhutanese perspective.
Furthermore, although there are many theoretical and empirical
literatures available around the world with regard to impact of different components of
public expenditure on economic growth but the researches lack to find the same for
foreign affairs and tourism. In fact, no research has been carried out in this field in
Bhutan. Therefore, this paper aims to add foreign affair to extend the study on the
influence of public expenditure on real GDP growth in Bhutan.
31
CHAPTER 3
RESEARCH DESIGH AND METHODOLOGY
3.1 Theoretical Framework
The theoretical framework designed in this paper is based on Keynesian
theory and endogenous growth theory constructed by Barro & Sala-i-Martin (1992).
Firstly, Keynesian theory help us to model short run relationship between government
expenditure and real GDP growth. It states that government expenditure will boost
economic growth in a short run. For instance, during economic downturn a policy of
budgetary expansion will increase or help to stabilize short run fluctuation in economic
activities (Ju-Haung, 2006). Keynesian confirmed how the government can adjust the
budgetary and monetary policy to avoid severe slump that happened in the 1930’s. Thus
following Keynesian theory, the model expresses economic growth (GDP) as a
dependent variable which is a function of government expenditures. Here, Jerono
(2009) defined gross domestic product as
RGDP=f (government expenditure) (1)
The mechanisms through which public spending may affect GDP
growth rate relates to the government capacity on dealing with goods and services that
increases the aggregate final demand in the economy. The basic concept of growth
implies periodical change in output from periodical changes in inputs (Banister, 2000).
Thus public expenditure changes over a time creating change in output.
The second model relates to long run relationship. According to neo-
classical theory, fiscal policy helps to determine the output level rather it failed to state
steady state economic growth rate. However, Barro (1990), Barro and Sala-i-Martin
(1992) and Mendoza et al. (1997) provides a theoretical as well as empirical evidence
supporting that fiscal policy does affects both the output level and steady state economic
growth rate. Model of endogenous growth by Romer (1986), Lucas (1988), Barro
32
(1990) and Rebelo (1991) also confirmed the government participation in the growth
process. The key message of the endogenous growth model with government fiscal
policy is that higher taxation explicitly decreases output. However, that unambiguously
decrease of output may be counterbalance by using proceeds for productive spending
(Barro, 1990).
Barro and Sala-i-Martin (1992)6 used the modified Cobb-Douglas
production function to establish the persistence influence of fiscal policy determinants
on economic growth. The production function takes the following form:
𝑌 = 𝐴𝐾1−𝛼𝑔𝛼 (2)
Where, 0 < 𝛼 < 1. Y represent for per capita output, K represent per capita capital, g
represents per capital input provided by the government and A represents total factor
productivity level.
Now assuming that the budget can be balanced through increase in
lump-sum tax (LST) and proportional tax (𝜏). Consider there are n producers in the
economy. Each producer produces output yi. Therefore, the budget constraint is written
as:
𝑛𝜏𝑦 + 𝐿𝑆𝑇 = 𝐶 + 𝑔𝑛 (3)
In the above equation (𝜏) represents distortionary taxes which influence the saving-
investment decision of the household (private agents). LST are the non-distortionary
taxes which never affect the saving and investment decision of the individuals. C is the
unproductive government expenditures. It defines those expenditures which are
included by private agents in their utility function. g represents for productive
expenditures and it incorporates those expenditures which are included in private
6 See details study of how fiscal policy influence economic growth in the
work of Barro and Sala-i-Martin (1992, 1995).
33
agent’s production function. Accordingly, from the above specification of utility
function, Barro and Sala-i-Martin (1992) derived the long run growth rate as:
Ψ = 𝜆(1-𝜏)(1-𝛼)𝐴1
(1−𝛼)(𝑔
𝑦⁄ )𝛼
1−∝-𝜇 (4)
Where (λ & μ) are the parameters in the supposed utility function. Equation (4) above
shows that distortionary taxes (τ) and government productive expenditure (g)
respectively will have either negative or positive impact on economic growth. However,
indirect taxes (LST) and government unproductive expenditure (C) have neutral impact
on long run growth rate. Hence, the supposition of balanced budget is impractical
particularly in the emerging countries like Bhutan, thus the equation (3) can now be
improved as:
𝜏𝑛𝑦 + 𝐿𝑆𝑇 = 𝐶 + 𝑔𝑛𝑦 + 𝑓 (5)
Where f constitute for surplus or deficit budget in a given period. g is predicted to be
positive as g is productive, but (𝜏) is negative as it distorts private agent’s incentives to
invest. Both LST and C are anticipated to have zero effects on equilibrium growth.
Henceforth, we will follows the growth formula of Kneller et al. (1999) to determine
the impact of fiscal policy on economic growth. They have empirically tested the public
policy endogenous growth model and predicted that composition of taxation and
government expenditure will affect the steady state growth rate7. They specified
economic growth as a function of some fiscal and non-fiscal variables. Now the
equation is written as
Ψt = 𝛽0 + ∑ 𝑀𝑖𝑡𝛽𝑖𝑘𝑖=1 + ∑ 𝑍𝑗𝑡𝛾𝑗
𝑚𝑖=1 + 휀𝑡 (6)
7 However, they used 26 years panel data for 20 OECD countries, which
is from 1970 to 1995.
34
Where Ψ represents real GDP growth, M represents vector of fiscal policy variables
(government expenditure variables), Z represents vector of the non-fiscal policy or
control variables and 휀𝑡 is the random error term.
3.2 The Econometric Model and Estimation Technique
For the purpose of estimating effects of the composition of government
expenditures equation (7), (8), (9) and (10) will be used. This setting will be done by
transferring equation (6) into logarithmic form in order to help the analysis using linear
regression model. This type of idea is also evident from Barro (1990), where he
confirmed the difference between productive and unproductive expenditures by how
they affect the aggregate production function of the economy. Empirical literature has
underlined the distinction between productive and unproductive spending, say,
Devarajan, et al, 1996). This study targets on the link between various components of
government expenditure and economic growth without pre-judging which components
should be productive or unproductive. Similar idea is also confirmed from Barro &
Sala-i-Martin (1992), where government fiscal policy have greater importance on
growth.
The main goal of this research is to find out the relationship between
components of government expenditure and real GDP growth in Bhutan. And also to
find out which components of government expenditure contribute better than other.
Eventually, we will first analyze the effect of total expenditure, capital expenditure and
current public expenditure on real GDP growth than we will pin down our focus
exclusively on components; expenditure on Agriculture and Forest, Information and
Communication, Economic Affair and Foreign Affair. For this purpose, we separated
our model into four equation. First three models (equations) consists of total, capital
expenditure and current expenditure with gross capital formation and tourism revenue
as control variables. Second model take into account of four components of government
expenditures.
Econometrically, the set up to investigate the relation between
government expenditure and economic growth follows the empirical study of Ghosh,
S., & Gregoriou, A. (2008) and Bose et al. (2007) as these studies were applicable to
35
my study. However, the current study includes some additional variables of government
expenditure like government expenditure on foreign affair, and capital Formation and
revenue from tourism as a control variables as
Model 1A.
The first regression model is the linear regression between real GDP
growth and total government expenditure (TExp) with gross capital formation and gross
revenue from tourism being control variables. The equation is given below:
Model 1A
𝑙𝑛𝑅𝐺𝐷𝑃 = 𝛽0 + 𝛽1𝑙𝑛𝑇𝐸𝑥𝑝𝑡 + 𝛽2𝑙𝑛𝐺𝐶𝐹𝑡 + 𝛽3𝑙𝑛𝑇𝑅𝑒𝑣𝑡 + 휀𝑡 (7)
Model 1B.
This linear regression model is the relationship between real GDP
(RGDP) and total current expenditure (CRExp). RGDP is the dependent variable and
CRExp is the explanatory variable with gross capital formation and revenue from
tourism as a control variable.
𝑙𝑛𝑅𝐺𝐷𝑃 = 𝛿0 + 𝛽1𝑙𝑛𝐶𝑅𝐸𝑥𝑝𝑡 + 𝛽2𝑙𝑛𝐺𝐶𝐹𝑡 + 𝛽3𝑙𝑛𝑇𝑅𝑒𝑣𝑡 + 휀𝑡 (8)
Model 1C.
This linear regression model is the relationship between real GDP
(RGDP) and total capital expenditure (CAPExp). RGDP is the dependent variable and
CAPExp is the explanatory variable with gross capital formation and revenue from
tourism as a control variable.
𝑙𝑛𝑅𝐺𝐷𝑃 = 𝛿0 + 𝛽1𝑙𝑛𝐶𝐴𝑃𝐸𝑥𝑝𝑡 + 𝛽2𝑙𝑛𝐺𝐶𝐹𝑡 + 𝛽3𝑙𝑛𝑇𝑅𝑒𝑣𝑡 + 휀𝑡 (9)
β1 β2 and β3 each for the model stated above are the parameter to be estimated. So that
the prior economic expectations are; β1 β2 and β3 are greater than zero.
Where, t represents time series dimension. RGDP is the real GDP growth rate, TExp is
government total expenditure, CRExp is government current expenditure, TRev is gross
36
revenue from tourism and GCF is the gross capital formation. All these variables are
expressed in logarithmic transformation.
Model 2.
This regression model is the linear regression between real GDP growth
and different components of government expenditure such as expenditure on
agriculture and forest (ExpAF), economic affair (ExpEA), information and
communication (ExpIC) and foreign affair (ExpFA) with gross capital formation and
gross revenue from tourism being control variables. Real GDP is the dependent
variable. The equation is given below:
𝑙𝑛𝑅𝐺𝐷𝑃𝑡 = 𝛽0 + 𝛽1𝑙𝑛(ExpAFt) + 𝛽2𝑙𝑛 (ExpEAt) + 𝛽3𝑙𝑛 (ExpICt) + 𝛽4𝑙𝑛
(ExpFAt) + 𝛽5𝑙𝑛 (GCFt) + 𝛽6 𝑙𝑛(TRevt) + 휀𝑡 (10)
Where,
Ln RGDPt = Natural logarithm of real Gross Domestic Product at time t
Ln (ExpAFt) = Natural logarithm of expenditure on agriculture and forest
Ln (ExpEAt) = Natural logarithm of expenditure on economic affair
Ln (ExpICt) = Natural logarithm of expenditure on information and
Communication
Ln (ExpFAt) = Natural logarithm of real expenditure on foreign affair
Ln (GCFt) = Natural logarithm of real gross capital formation at time t
Ln (RevTt) = Natural logarithm of net revenue from tourism.
휀𝑡 = Random Error term (is stochastic variable to accommodate
the influence of other determinants of economic growth
which were not included in the model)
The prior economic expectations are; βi (i=1, 2…... 7) are greater than
zero. It implies that the intercept and slope coefficient are expected to have positive
sign, indicating that each components of public spending is expected to correlate
positively with real GDP growth. The study explores the positive and negative impact
37
of public expenditure on real GDP growth. To achieve these objectives, our study would
employ least square regression model and error correction model to examine long run
and short rum effects respectively. Eventually, we will base our result based on the
frame work of Keynesian and Endogenous growth theory for short and long run result
validations.
3.3 Time Series Properties of the Data and Techniques of testing
3.3.1 Estimation issue
Many macroeconomic time series are usually non-stationary and
applying standard least regression method to non-stationary data series can give
nonsense correlation and spurious regression. Therefore, it is important to test and
correct various pitfalls of time series data before applying OLS regression on the data.
The first step in analyzing time series data involved testing for stationary of the series
to ensure that the series have a zero mean and constant variance. That is, the time series
data under consideration should be tested for stationary before we can attempt to fit a
suitable model. Spurious regression is, therefore, not desirable. Thus we need to test
the series for unit root.
3.3.2. Testing for Unit Root
Checking non stationarity of the data is the first step in analyzing time
series data. To escape from estimating spurious results, the study conduct stationarity
test. The Augmented Dickey Fuller (ADF) is employed to check the existence of unit
root. The ADF regression equation to test unit root in a series Y is in the form:
∆𝑌𝑡 = 𝛼0 + 𝛽𝑦𝑡−1 + 𝛼1𝑇 + ∑ 𝛾𝑗𝑘𝑗=1 ∆𝑦𝑡−𝑗 + 휀𝑡 (11)
Where ∆𝑦𝑡 referred to first difference of the data, T is the time trend variable. The k
lagged difference terms are added to remove serial correlation in the residual and
𝛼0, β,𝛼1 and γ are estimated parameters. 휀𝑡 is random error term.
38
Model (11) is developed since all the variables of interest at level are
assumed to have unit root which could produce inconsistent result if the variables were
run together in the multiple regression without taking first difference. If the computed
ADF test statistic is greater than the ADF critical value at a given level of significance,
we do not reject the null hypothesis rather fail to reject null hypothesis that unit root
exits. Thus we differentiate all the series once to make stationary. Therefore, these
series are said to be integrated of order one, i.e. I (1).
In fact, knowing the order of integration between GDP growth and
compositions of public expenditure is the first step that enables us to determine the next
step of estimation. When variables of interest considered in this paper are found to be
stationary, then the estimation of regression is possible.
3.3.3 Error Correction Model
Computing long run estimates of co-integration relations is only a first
steps to estimate complete model. Along with the long run estimation, the short run
adjustment of the model is also equally important as it conveys the short run correction
behavior of the economic variables. The estimation of short run dynamics is often
carried out by first eliminating trends in the variables, mostly by differencing. However,
this method will throws away some potential information about the long run
association. The better approach is to transform the dynamic approach into error
correction mechanism. Error correction method conveys information about both long
run and short run properties of the model, with disequilibrium as a process of
adjustment to the long run dynamic model. Specifically, the model take the following
general form for the short run relationship.
∆𝑌𝑡 = 𝛼𝑖�̂�𝑡−1 + 𝛽1 ∗ ∆𝑌𝑡−1 + 𝛽𝑖 ∑ ∆𝑋𝑡−𝑘
𝑘
𝑘=1
(12)
Where, α shows the degree of adjustment of the dependent variables to its long run
solution. Where α is expected to be negative and less than 1, it serves to influence the
short term movements in the dependent variables.
39
3.4 Data
This research aims to establish the impact of government expenditure on
economic growth in Bhutan for the period between 1985 and 2015 for various
departments of government expenditure. The data of Capital expenditure, Current
expenditure, expenditure on Agriculture and Forest, Information and Communication,
Foreign Affairs and Economic Affairs were collected from SYB8. Data pertaining to
CPI was extracted from International Financial Statistics (IFS). While data on real GDP
and Gross Capital Formation were collected from national account statistics of Bhutan.
Finally, the data on tourism revenue was collected from office of TCB9. In line with
this, the answer to the question posed in chapter 1(one) is based on secondary data form
the various annual reports of the Government.
3.5 Definition and measurement of variables
1. Real GDP growth rate
This is the rate of increase in gross domestic product at constant price.
It captures the change in value of final goods and services produced in an economy for
a particular period of time.
2. Total Government Expenditure
Total government expenditure comprises of expenditures allotted to all
Ministries, Judiciary, Constitutional Bodies, Dzongkhag Administration and Geog
Administration.
3. Total capital expenditure
Total expenditures allotted to all Ministries, Judiciary, Constitutional
Bodies, Dzongkhag Administration and Geog Administration for creation new capital
8 National Statistical Year Book, National statistical Bureau
9 TCB stand for Tourism Council of Bhutan
40
goods. Capital expenditure includes acquisition or creation of capital assets such as
buildings, roads, land, equipment and machinery.
4. Total current expenditure
Total expenditures allotted to all Ministries, Judiciary, Constitutional
Bodies, Dzongkhag Administration and Geog Administration to meet daily
maintenance and repairing expenses. It includes spending on recurrent expenditure that
are incurred each year such like wages, salaries, administration, interest payment,
welfare service, etc.
5. Public expenditure on Agriculture and Forest
This is the fractional part of total government expenditure. It includes
the expenditure on all types of agricultural activities, environmental conservation, and
livestock, such as buying modern agricultural equipment’s, agricultural inputs like high
yielding seeds, etc.
6. Public expenditure on information and Communication
This is the fractional part of total government expenditure. MoIC10
is
responsible for prompting the development of reliable and sustainable information,
communication and transport networks and systems. It also includes activities such as
national telecommunication network, fiber optic cable connection layouts, and postal
services.
7. Public expenditure on Foreign Affair
Public expenditure on Foreign Affair is the part of total expenditures
which includes expenses on development of foreign relations.
8. Public expenditures on Economic Affair
This is the fractional part of total government expenditure directed to
activities such as Trade, Industry, Intellectual Property, Geology and Mines, Hydro met
10 MoIC stand for Ministry of Information and Communication
41
services, Renewable Energy, Cottage and Small Industry. This sector is responsible for
proper management of economy in the country.
9. Gross Capital Formation
Gross capital accumulation during an accounting period in country, and
the term refers to additions of capital stock, such as equipment, tools, transportation
assets, and electricity.
10. Revenue from Tourism
Gross revenue earned by tourism sector in the form of royalties, fees and
other charges.
3.6 Working hypothesis
The main Hypotheses of this research includes the following
1. H01: Total public expenditure contributes negatively on real GDP growth in
Bhutan.
2. H02: Total capital expenditure contributes negatively on real GDP growth in
Bhutan
3. H03: Total current expenditure contributes negatively on real GDP growth in
Bhutan
4. H04: Government expenditure on Agriculture and Forest has no significant
contribution on real GDP growth in Bhutan.
5. H05: Government expenditure on Economic Affair has no significant
contribution on real GDP growth in Bhutan.
6. H06: Public expenditure on Information and Communication has no significant
contribution on real GDP growth in Bhutan.
7. H07: Public expenditure on Foreign Affair has no significant contribution on
real GDP growth in Bhutan.
42
CHAPTER 4
RESULTS AND DISCUSSIONS
4.1 Descriptive Study
In this section, descriptive and econometric analysis of the relationship
between government expenditure and real GDP growth are presented. First we present
the descriptive statistics to show the nature of the data. Secondly, we perform the
stationary test and then follow by regression analysis. The data are in real term (constant
price). The nominal values of each variables have been divided by consumer price index
(CPI) to generate real data.
A graphical representation of total government expenditure together
with real GDP indicates an increasing trend in the data over the time as shown in figure
4.1.1.
Figure.4.1.1
Real total expenditure and real GDP of Bhutan, 1985-2015
Source: National Statistical Year Book, National Statistical Bureau, Bhutan
0
5000
10000
15000
20000
25000
30000
35000
0
10000
20000
30000
40000
50000
60000
70000To
tal E
xpen
dit
ure
Rea
l GD
P
Year
Figures in million Nu.
Real GDP Total Expenditure
43
The graph 4.1.1 clearly states that government expenditure in Bhutan
accelerated over the year with much greater rate.
Similarly, the trend in the data of capital expenditure along with real
GDP also predicts increasing trend over the year. While the expenditure for fiscal year
2012/2014 projective to decline nominally by 9%. This is due to the shortage of rupee
reserve (Indian currency). In this case, government has tighten the country’s
expenditure to bring the shortage in line with available resources (see graph 4.1.2).
Figure. 4.1.2
Real capital expenditure and real GDP of Bhutan, 1985-2015
Source: National Statistical Year Book, National Statistical Bureau, Bhutan
0
2000
4000
6000
8000
10000
12000
14000
16000
0
10000
20000
30000
40000
50000
60000
70000
Cap
ital
Exp
end
itu
re
Rea
l GD
P
Year
Figures in million Nu.
Real GDP Capital Expenditure
44
A graphical representation of total current expenditure together with real
GDP indicated an increasing trend in data over the time as given below in figure 4.1.3.
Figure. 4.1.3
Real current expenditure and real GDP of Bhutan, 1985-2015
Source: National Statistical Year Book, National Statistical Bureau, Bhutan
Current expenditure shows increasing trend as it includes all general
public final consumption expenditures for buying of goods and services. It also
includes national defense and security. However, it excludes public military spending
which are portion of government capital formation.
0
2000
4000
6000
8000
10000
12000
14000
16000
0
10000
20000
30000
40000
50000
60000
70000
Cu
rren
t Ex
pen
dit
ure
Rea
l GD
P
Year
Figures in illion Nu.
RGDP Current Expenditure
45
A graphical representation of real expenditure on Agriculture and Forest
together with real GDP depicted that the two series has rising trend with some curvature
over some years.
Figure.4.1.4
Real Agriculture and Forest expenditure and real GDP of Bhutan, 1985-2015
Source: National Statistical Year Book, National Statistical Bureau, Bhutan
The figure 4.1.4 states that there was high public spending on
Agriculture and Forest. The increasing trend of public expenditure in this ministry was
due to free distribution of agricultural equipment and improved seeds to the farmers
which includes expenditure on utility van, power taller, seed and saplings, and other
livestock related services.
0
500
1000
1500
2000
2500
0
10000
20000
30000
40000
50000
60000
70000
Exp
. on
Agr
icu
ltu
re &
Fo
rest
Rea
l GD
P
Year
Figures in milliion Nu.
RGDP Exp Agriculture & Forest
46
The real expenditure on information and communication also showed
increasing trend along with the trend of real GDP with some curvature. This increase
in public spending pertains to government expenditure on installation of more new
modern telecommunication facilities and other services during some year.
Figure.4.1.5
Real Information and com. expenditure and real GDP of Bhutan, 1985-2015
Source: National Statistical Year Book, National Statistical Bureau, Bhutan
0
200
400
600
800
1000
1200
1400
1600
0
10000
20000
30000
40000
50000
60000
70000
Exp
. on
info
rmat
ion
Rea
l GD
P
Year
Figures in million Nu.
Real GDP Expenditure Information and Communication
47
The graphical representation of expenditure on economic affair
together with real GDP is presented in figure 4.1.6. The spending in this department
was mostly constant over the years.
Figure.4.1.6
Real economic affair expenditure and real GDP of Bhutan, 1985-2015
Source: National Statistical Year Book, National Statistical Bureau, Bhutan
The sharp increase in expenditure on ministry economic affair in the
fiscal year 2000-2002 was mainly due to privatization of Public sector activities.
0
500
1000
1500
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2500
3000
3500
4000
4500
0
10000
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30000
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60000
70000
Exp
. on
Eco
no
mic
Aff
air
Rea
l GD
P
Year
Figures in million Nu.
Real GDP Expenditure on Economic Affair
48
The graph of real foreign expenditure with real GDP indicates upward
trend between the years ranging from 1985 to 2015. This increasing trend of foreign
expenditure indicates the investment in creating better development of foreign
relations.
Figure.4.1.6
Real foreign expenditure and real GDP of Bhutan, 1985-2015
Source: National Statistical Year Book, National Statistical Bureau, Bhutan
Gross capital formation together with real GDP also revealed increasing
trend. It means that there was an increasing rate of new capital formation in Bhutan
over the year. The fluctuation over the year was mainly due to major investment in
mega Hydro power Plat beside other. Similarly, the fall in the domestic investment in
2007-2008 was due to global financial crisis.
0
100
200
300
400
500
600
0
10000
20000
30000
40000
50000
60000
70000
Exp
. on
Fo
reig
n A
ffai
r
Rea
l GD
P
Year
Figures in million Nu.
Real GDP Expenditure Foreign Affair
49
Figure.4.1.7
Real gross capital formation with and real GDP of Bhutan, 1985-2015
Source: National Account Statistics, National Statistical Bureau, Bhutan
Revenue from tourism together with real GDP also revealed increasing
trend in data. It means gross revenue received every year seems to be increasing along
with an increased in real GDP. This shows that the government obtains additional
amount of revenue from tourism each year to finance its expenditure. This is shown in
figure. 4.1.8
0
5000
10000
15000
20000
25000
30000
35000
0
10000
20000
30000
40000
50000
60000
70000
1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015
Gro
ss C
apit
al F
orm
atio
n
Rea
l GD
P
Year
Figures in milliion Nu.
Real GDP Gross Capital Formation
50
Figure.4.1.8
Real Gross revenue from tourism and real GDP of Bhutan, 1985-2015
Source: National Account Statistics and TCB11
4.2 Descriptive statistics
The descriptive statistics are presented in Table 4.1. This paper used
annual data covering the period 0f 31 years. The variables we include in our study
comprise of real gross domestic product (RGDP), total expenditure (TExp), total capital
expenditure (CAPExp), total current expenditure (CRExp), expenditures on
Agriculture and Forest (ExpAF), Information and Communication (ExpIC), Economic
Affair (ExpEA) and Foreign Affair (ExpFA) respectively. In addition, gross capital
formation (GCF) and revenue from tourism (TRev) are used as control variables. Real
GDP is considered as dependent variable whereas all other variables are explanatory
variables. All the variables were expressed in real term.
11 Tourism council of Bhutan
0
500
1000
1500
2000
2500
3000
3500
0
10000
20000
30000
40000
50000
60000
70000
1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015
Tou
rism
Rev
enu
e
Rea
l GD
p
Year
Figures in million Nu.
Real GDP Tourism Revenue
51
Table 4.1
Descriptive statistics
Measurement mean Std. Dev. Minimum Maximum skewness kurtosis
RGDP 25656.4 15942.63 6756.9 59240.0 .74568 2.2221
TExp 12905.8 8553.56 3498.4 28858.9 .64778 1.8862
CAPExp 6449.6 4202.52 1930.5 15022.2 .65147 2.0437
CRExp 6456.2 4409.2 1402.3 14393.8 .66635 1.8763
ExpAF 1145.60 471.21 384.5 1989.5 .13932 1.867
ExpEA 987.15 773.12 212.2 4104.3 2.2555 9.5641
ExpIC 714.97 413.16 105.2 1463.6 .19645 2.0791
ExpFA 249.81 137.22 2.9 539.4 .29382 2.4545
GCF 12623.3 9487.58 3403.63 32716.1 .93930 2.6188
TRev 938.02 967.03 82.67 3141.7 1.1119 2.9362
Source: Summarized by author
In the table 4.1, skewness coefficient depicts that real GDP, TExp,
CAPExp, CRExp, ExpAF, ExpIC, ExpFA, GCF were normal except ExpEA and TRev.
This conclusion was being reached as the skewness coefficient adjusted between -1 and
+1(Bulmer, 1979). If the skewness is positive, the data were positively skewed or
skewed right. If the skewness coefficient is negative, the data were negatively skewed
or skewed left. In fact, the distributions were positively skewed with expenditure on
economic affair distribution with longest tail. However, Kurtosis coefficient depicted
that GDP, TExp, CAPExp, CRExp, ExpAF, ExpIC and ExpFA have platykurtic
distribution. While ExpEA variables had a leptokurtic distribution while remaining
variables conformed platykurtic distribution. According to George and Mallery (2010)
the values for symmetry and Kurtosis ranging from -2 to +2 are considered satisfactory
in order to prove normal univariate distribution
52
4.3 Diagnostic Testing
Gujarati (2004) suggest that in order to have decent econometric models
for least square regression, it should qualify some assumptions. Some of these
assumptions includes that the data should be linear, the residual must be normally
distributed, no correlation between independent variables, no multicollinearity, etc.
Therefore, this study conduct correlation test, multicollinearity test and residual
diagnostic test as shown in the coming sections.
4.3.1 Correlation Test.
One of the important assumption of least square econometric analysis
on the time series data is that the independent variables should not have correlation to
each other. To test this important assumption, we used pair-wise correlation test. Many
literature mentioned that correlation should not be larger than of 0.8 in case of pair-
wise correlation matrix. This test is shown in tables 4.2 and 4.3 respectively.
Table 4.2
Model 1: Pair-Wise correlation matrix
lnTExp lnCAPExp lnCRExp lnGCF lnTRev
lnTExp 1
lnCAPExp 0.9872 1
lnCRExp 0.9879 0.9508 1
lnGCF 0.9564 0.9487 0.9419 1
lnTRev 0.9417 0.9364 0.9250 0.9390 1
Source: Author’s calculation
53
Table 4.3
Model 2: Pair-Wise correlation matrix
lnExpAF lnExpEA lnExpIC lnExpFA lnGCF lnRevT
lnExpAF 1
lnExpEA 0.2613 1
lnExpIC -0.0219 -0.0429 1
lnExpFA 0.7620 0.4578 -0.0190 1
lnGCF 0.8183 0.3128 0.0385 0.6583 1
lnRevT 0.7168 0.2013 -0.0027 0.6600 0.9390 1
Source: Author’s calculation
From the correlation results presented in table 4.2, we concluded that the
independent variables were highly correlated with each other in model 1. Many
literature suggested that correlation should not be larger than of 0.8 in case of pair-wise
correlation matrix. However, model 2 reflected some positive correlation between
expenditure on agriculture and forest and gross capital formation. And also gross capital
formation and tourism revenue were highly correlated. This type of correlation might
introduce multicollinearity in a way. So using least square regression in such a situation
might result in spurious regression.
As it is usually known that we face with autocorrelation with time series
data. We use regression with the Newey-West Standard Error regression technique. The
Newey-West (1987) variance estimator is an extension that yields consistent estimates
when there is autocorrelation in addition to possible heteroskedasticity.
The next steps is to check multicollinearity between explanatory
variables. From table 4.2, it is known that there is very high correlation between
independent variables. Owing to the high multicollinearity in the estimation, we
decided to drop gross capital formation from the model
54
4.3.2 Multicollinearity Test.
If there is a perfect linear relationship among the explanatory variables,
the estimates for a regression model cannot be BLUE. When two or more than two
variables are collinear, it is often called multicollinearity. Which means there should
not be multicollinearity among variables. To test this important assumption, we used
VIF. And the rule of thumb for VIF suggest that VIF of 10 or greater are cited as
symbolic of problematic collinearity. On the other hand, the tolerance value lower than
0.1 is cited as multicollinearity. In such a situation, one independent variable could be
considered as a linear combination of other independent variables. Table 4.4 below
represents the multicollinearity test.
Table: 4.4
Variance Inflation Factor
Model 1A Model 1B Model 1C Model 2
lnTExp 8.84
lnCAPExp 8.12
lnCRExp 6.93
lnExpAF 4.11
lnExpEA 1.31
lnExpIC 1.00
lnExpFA 2.92
lnTRev 8.84 8.12 6.93 3.05
Mean VIF 8.84 8.12 6.93 2.48
Source: Author’s calculation
Table 4.4 suggests that our regression model do not suffer from sever
multicollinearity or are not so worrisome. So we can proceed with the estimation using
simple least square method. But before we estimate the regression, the primary step is
to check the stationarity of the data under study. Therefore, we begin with testing unit
root of the series.
55
4.4 Long run relationship and short run adjustment
4.4.1 Unit Root Test
We performed Augmented Dickey Fuller unit root test and used the
critical values proposed by McKinnon (1991).
The unit root test results are presented in the table 4.5. We have included
trend in the test specification. The results suggests that variables from both the models
are not stationary at level with 5% significance level. However, all variables became
stationary after taking the first difference. This implies that the variables are integrated
of order one, say I (1). Therefore, we examine the existence of long run relationship
between the real GDP and components of government expenditure by using the two-
step Engle-Granger co-integration test.
Table: 4.5
Result of Unit Root Test
At level At first difference
variables ADF statistics ADF statistics Conclusion
lnRGDP -2.422 -4.825*** I(1)
lnTExp -1.980 -6.073*** I(1)
lnCAPExp -2.290 -6.638*** I(1)
lnCRExp -2.118 -5.011*** I(1)
lnExpAF -3.718 -6.652*** I(1)
lnExpEA -3.467 -7.366*** I(1)
lnExpIC -2.894 -5.605 *** I(1)
lnExpFA -3.564 -5.621*** I(1)
lnTRev -3.572 -4.558*** I(1)
**(***) denotes rejection of the hypothesis at 5%(1%) significance level
Source: Author’s calculation
Table 4.5 suggests that the variables we considered might be co-
integrated. Therefore, we will perform the co-integration test in the next section.
56
4.4.2 Co-integration
Because all variables are integrated of order 1, we examine the long run
association between real GDP and components of government expenditure. If the sets
of a variables are of the same order and if it have one or more linear combination of
these variables that is stationary, then the variables are cointegrated. We perform the
two-step Engle-Granger co-integration test. We have tested the residuals and found that
all equations are cointegrated.
The ADF test result of the unit root test with the residuals are presented
in the table 4.6.
Table 4.6
Residual Based Test for Co-integration (Stationary Test)
Models Test
Statistics
1% critical
value
5% critical
value
10% critical
value
Order of
Cointegration
Model 1A -3.568 -3.716 -2.986 -2.624 I(0)
Model 1B -4.042 -3.716 -2.986 -2.624 I(0)
Model 1C -4.135 -3.716 -2.986 -2.624 I(0)
Model 2 -4.872 -3.716 -2.986 -2.624 I(0)
Source: Author’s calculation
The cointegration in table 4.6 confirms that the residuals are stationary
at 1% significance level. Therefore, is stationary at level, say I(0). It means that there
exist a long run relationship between dependent variable (real GDP) and independent
variables (total expenditure, capital expenditure, current expenditure, expenditure on
agriculture and forest, information and communication, economic affair, foreign affair,
gross capital formation and tourism revenue). Thus, we can examine the long run
relationship between real GDP and components of government expenditure by using
the Ordinary Least Square method.
4.4.3 Long run relationship estimation
The first objective is to find out the effects of different components of
government expenditure on the real GDP growth. The long run relationship are
57
presented in tables 4.7 and 4.8 and short run adjustments are presented in tables 4.9,
4.10, 4.11 and 4.12. All the estimations are computed taking variables in their level
form in Stata.
The first long run relationship we considered is the association ship
between the real GDP and the total government expenditure. We also consider different
types of government expenditure which are capital and current expenditures. The
results in table 4.7 (model 1A, model 1B and model 1C) shows that the sign of the
coefficient (beta) corresponding to total expenditure (TExp), Capital expenditure
(CAPExp), current expenditure (CRExp) components and tourism revenue are
positively and statistically significant as expected in all models. This means that total
government expenditure, capital expenditure and current expenditure have positive
relationship with real GDP growth in the long run.
Table 4.7
Model 1: Long Run Estimated Result
Dependent variable: log of real GDP (lnRGDP)
Method: Least Square
Variables Model 1A Model 1B Model 1C
Coef. Coef. Coef.
lnTExp .550***
(.1025)
lnCAPExp .318***
(.1143)
lnCURExp .557***
(.0958)
lnTRev .224***
(.0612)
.353***
(.0676)
.213***
(.0518)
*[**](***) denotes rejection of the hypothesis at 10%[5%](1%) significance level.
Figure in the bracket () indicates newey-west standard error.
Source: Author’s calculation
58
In addition, the coefficient of individual variables is discussed hereafter.
The long run result indicated that the total government expenditure have positive and
statistically significant relationship with real GDP growth. The coefficient of 0.550 (p-
value=0.002) implies that one percentage increases in total government expenditure
will result in 0.55 percentage increase in the real GDP. This finding is in accordance
with the finding of Albatel (2000), Aigheyisi (2013), and Gemmell et.al (2015).
However, our finding is consistence with the theoretical frame work developed by
Barro and Sala-i-Martin (1992). Furthermore, the coefficient of tourism revenue of
0.224 suggests that one percentage increase in earning revenue from tourism will boost
growth of real GDP by 0.22 percentage. Thus, the study confirms to have long run
association between real GDP and stated independent variables.
As per the finding of the influence of different types of public
expenditure on growth is concerned, we have noted in the literature review that
Devarajan et al. (1996) found a positive and significant relationship between current
expenditure and real GDP growth and negative and significant relationship between
capital components expenditure and real GDP growth for 43 countries. Our long run
result indicates that government capital expenditure and current expenditure revealed
positively statistically significant association ship with the real GDP growth. From table
4.7, one percentage increase in government current expenditure will leads to 0.55
percentage increase of real GDP growth in the long run (p-value=0.000). Moreover,
one percentage increase in the capital expenditure results in an increases in the real
GDP growth by 0.318 percentage. These findings were consistent with Gemmell et.al
(2015), Al-Fawwaz (2016) and Dandan (2011) where they have stated that total capital
expenditure and current expenditure resulted positive and significant impacts on GDP
growth in the long run. Moreover, our findings signifies the productive use of Public
resources in Bhutan. On the other hand, our findings differ with those of Ghosh and
Gregoriou (2008) as they have found that capital expenditure is statistically
insignificant in the long run.
The coefficient associated with tourism revenue is positive and
statistically significance in the long run. This suggested that an increase in gross income
from tourism will boost real GDP growth in the long run. Which means that an increase
in the number of tourists visiting the country really matters in Bhutan. In particular, the
59
positive value in the long run coefficient imply that all other thing being equal, a rise in
tourism revenue promotes long term economic growth. The coefficient suggests that
one percentage increase in gross revenue from tourism leads to 0.22 percentage, 0.35
percentage and 0.21 percentage increase in real GDP growth respectively (see table 4.7
Model 1A, Model 1B & Model 1C). These finding suggests that income made from
tourism industry can boost economic growth in Bhutan. Therefore, government should
discover more tourism activities, spots with modern amenities. And also, revisit tourism
policy to address the high prevailing tourist tariff in order to receive more number of
dollar paying tourists in the country. Furthermore, the role of government should be
supportive in all case to allow tourism sectors to drive economic growth in Bhutan.
We also consider the relationship between the real GDP and government
expenditure from different departments (Ministries) as shown in model 2. The result
are presented in table 4.8. Based on R-square, the model performed well. The result
shows that the sign of the coefficient (beta) corresponding to expenditure on agriculture
and forest, information and communication, economic affair and tourism revenue turn
out to be positive as theoretically expected in the model. However, government
expenditure on Foreign Affair was significantly negative in the long run.
60
Table 4.8
Model 2: Long Run Estimated Result
Dependent variable: RGDP (Real GDP)
Method: Least Square
Variables Coefficients
lnExpAF .247**
(.1287)
lnExpEA .077
(.0528)
lnExpIC .090**
(.037)
lnExpFA -.095**
(.0465)
lnTRev .502***
(.0449)
R-Squared 0.9394
Prob(F-Stat) 0.0000
Durbin-Watson stat. 1.178835
*[**](***) denotes rejection of the hypothesis at 10%[5%](1%) significance level.
Figure in the bracket () indicates standard error.
Source: Author’s calculation.
The coefficient associated with expenditure on agriculture and forest is
statistically significant and accomplish positive value only in the long run. The long run
coefficient is positively significant at a 5% significant level. From table 4.8, a one
percentage increase in agriculture and forest expenditure will results to 0.24 percentage
rise in the real GDP growth (p-value=0.001). Moreover, a one percentage increase in
the expenditure on information and communication results in an increase in the real
GDP by 0.09 percentage (p-value=0.020). Similar findings were stated by (Vu, 2005),
Yu et.al (2008), Erhan (2012) and Musaba et.al (2013). They found that spending on
61
agriculture was potentially strong in promoting economic growth in the long term. In
contrary, Saad and Kalakech (2009) and Amasoma et al. (2011) found spending on
agriculture was insignificant in both long and short term.
Furthermore, the long run result indicated that the expenditure on
Economic Affair attached significant association with real GDP but insignificant in the
short run, which means that the expenditures on economic service was unproductive.
These types of statistically insignificant effects of government spending may be due to
disorganization. Perhaps, inefficiency of government expenditures has widely been
associated in the literature with bad governance and high corruption which happens
mostly in developing countries. It can be said that this sector should have significant
impact on economic growth as it is the main pillar of the economy.
Unexpectedly, government expenditure on Foreign Affair is found to be
negative although significant determinant of real GDP growth, which did not conform
to the expectation of a positive linkage between expenditure on Foreign Affair and real
GDP growth. From the table 4.8, a one percentage increase in government expenditure
on foreign affair will leads to 0.09 percentage decrease in the real GDP growth in the
long run. Our result could be generalized to the fact that the expenses on development
of foreign relations do not create any valuable economic activities. It means that
expenditure on foreign affair exert adverse effect on real GDP growth in Bhutanese
economy. So the excess use of government fund in this department (Ministry) become
unproductive. As (Devarajan, 1996) stated that seemingly productive expenditure,
when used more will became unproductive.
Finally, the statistical significant of the coefficient corresponding to
tourism revenue shows positive effects on real GDP growth in Bhutan. It is Significant
at 1% significance level. Unlike in model 1, when we conditions tourism revenue along
with government expenditure at disaggregate level, its impact increase drastically.
Tourism play key role in promoting long term growth in Bhutan. The coefficient of
0.502 suggest that one percentage increase in revenue generation from tourism
increases real GDP growth by 0.502 percentage in the long run. While the short run, it
is reported to exert negative impact on real GDP growth in Bhutan.
Nevertheless, our findings are consistent with endogenous growth
theory of fiscal policy laid down by Barro (1990) and Barro and Sala-i-Martin (1992).
62
The endogenous growth model explains the relationship between government spending
and economic growth where public expenditure composition is taken as one of the
determinants of economic growth (Sanz & Velazquez, 2001). However, in reality, we
cannot guarantee our findings. These findings may depend on various aspects like
methods or techniques adopted, type of country under study to analyze, assumptions,
etc. With the theoretical framework about the effects of public expenditure on economic
growth is concerned, Barro (1990), Bajo-Rubio (2000) and Milbourne et al. (2003)
reported that a positive effect is anticipated to be found where size of government is
smaller (like Bhutan) and negative effects to those countries where size is bigger than
a certain threshold, mostly developed countries. However, in general, the success of
public spending in intensifying the economy and fostering rapid economic growth
depends on whether the expenditure is productive or unproductive. All things being
equal, productive expenditure would have positive effect on the economy, while
unproductive expenditure would have negative effect or no effect in the nations’
economy.
4.4.4 Short-run Adjustment
By knowing that there exist a long run association between dependent
variable and independent variables then there will be error correction process is taking
place. It means that there could be deviations from the equilibrium relations in the short
term. This disequilibrium come from the short run fluctuations on the data series. ECM
methods predicts how quickly can real GDP adjust towards the long run equilibrium
after a short period shock. ECM includes using the previous value of residual to adjust
the short run deviations from the equilibrium. Therefore, the expected sign of the
coefficient of ECM should be negative and statistically different from zero. This
negative sign reports a return of the variables towards equilibrium. The complete value
of coefficient of the lagged value of residual denotes the speed of adjustment and
indicates how quickly equilibrium is restored in the event of short term shock.
The short run coefficient of single variables should be examine to find
out the relevant addition of each variables of government expenditure on real GDP
growth. We present our short run regression equations taking lagged value of real GDP,
lagged value of real total expenditure, lagged value current expenditure and lagged
63
value of revenue from tourism along with residual. All the variables in the short run do
not conform priori expectation. They are all negative and insignificant. However,
lagged value of capital expenditure is negative and significant at 10% significant level
(Table 4.10). This finding is consistent with the previous finding of Lheanacho (2016)
and Ghosh and Gregoriou (2008). On contrary, lagged value of tourism revenue is
reported to be negative determinant of real GDP growth (see tables no. 4.9, 4.10 and
4.11). The coefficients of the error correction (uhat-1) are as anticipated, negative and
statistically significant at 1% significant level. Such type of finding was also reported
by Aigheyisi (2013). Thus error correction will precisely act to restore equilibrium
when there is deviation in the short run. So we will consider only error correction in
our main analysis.
Table 4.9
Model 1A: Short Run Estimated Result
Dependent
variables
Independent variables
LD.lnRGDP LD.lnTExp LD.lnTRev Uhat(-1)
D.lnRGDP -.1699
(.1500)
-.07818
(.0621)
-.05906*
(.0322)
-.3524***
(.0811)
D.lnTExp 1.274**
(.5661)
.13154
(.2345)
.0373
(.1216)
.49101
(.3063)
D.lnTRev -.3136
(.79573)
.12725
(.32968)
.08470
(.1709)
1.265***
(.4305)
*[**](***) denotes rejection of the hypothesis at 10%[5%](1%) significance level
Figure in the bracket () indicates standard error.
R square - 53%
Source: Author’s calculation
The result of error correction model (see table 4.9, Model 1A) shows
that the previous growth value of lagged GDP is negative and insignificant. From the
64
result, lagged error correction value is negative and significant, which conforms the
error correction in the model. This means that the speed of adjustment of lnRGDP is
negative and significant. More essentially, the estimated coefficient of ECM term is -
0.352, which is significant at 1% significance level and has correct sign as expected,
suggests that approximately 0.35 percentage of deviations in previous year is corrected
in the current year. Table 4.9 suggests that though the lagged value of total expenditure
is not significant, error correction appeared to restore any short run deviations from the
long run equilibrium.
Table 4.10
Model 1B Short Run Estimated Result
Dependent
variables
Independent variables
LD.lnRGDP LD.lnCAPExp LD.lnTRev Uhat(-1)
D.lnRGDP -.1472
(.1516)
-.0722*
(.04124)
-.06104*
(.03307)
-.2832***
(.0607)
D.lnCAPExp .9673
(.87813)
-.2348
(.23890)
.19737
(.19158)
.05406
( .35215)
D.lnTRev -.2824
(.74916)
.0298
(.20381)
.1311
(.16344)
1.057***
(.3004)
*[**](***) denotes rejection of the hypothesis at 10%[5%](1%) significance level
Figure in the bracket () indicates standard error.
R square was 52%
Source: Author’s calculation
Similarly model 1B suggests that lagged value of real GDP is negative
and insignificant. However, lagged value of capital expenditure is negative and
significant. This means that previous value of government capital expenditure has
negative impact on current growth. On the other hand, lagged error correction value
(Uhat-1) is negative and significant. The coefficient of 0.283, significant at 5% level,
65
suggests that approximately 0.28 percentage of disequilibrium in previous year is
corrected by real GDP in the current year (Table 4.10).
Table 4.11
Model 1C Short Run Estimated Result
Dependent
variables
Independent variables
LD.lnRGDP LD.lnCRExp LD.lnTRev Uhat(-1)
D.lnRGDP -.04650
(.16267)
-.0078
(.06392)
-.081**
(.03613)
-.327***
(.10343)
D.lnCRExp 1.4053***
(.47846)
.31947*
(.1880)
-.0207
(.10628)
.803***
(.30424)
D.lnTRev -.86408
(.85861)
.14859
(.3374)
.15536
(.19072)
1.271**
(.5459)
*[**](***) denotes rejection of the hypothesis at 10%[5%](1%) significance level
Figure in the bracket () indicates standard error.
R square = 53%
Source: Author’s calculation
From table 4.11, the lagged value of error correction (Uhat-1) is negative
and significant. The coefficient of -0.327 explains that the disequilibrium in the
previous period will be corrected at the speed of 0.327 percentage annually in the
current period. It means that real GDP can be restore if there is any short run deviations
from the long run equilibrium. As mentioned earlier, tourism revenue have adverse
impact on real GDP.
Finally, in regard of model two, the analysis showed that all the variables
are negative and insignificant. Therefore, for our better analysis, we dropped all
independent variables as they were not significant in the short run. These variables
includes one period lagged value of real GDP, lagged value of expenditures on
agriculture and forest, information and communication, economic affairs, foreign
66
affair, tourism revenue and lagged value of error term. We try to examine only with
lagged value of residual on each dependent variables as shown below in table 4.12.
Table 4.12
Model 2 Short Run Estimated Result /ECM
Dependent Variables Coefficient
Uhat (-1)
D.lnRGDP -.107**
(.0553)
D.lnExpAF .457
(.3890)
D.lnExpEA -.893
(.8354)
D.lnExpIC .341
(.781)
D.lnExpFA -1.016
(1.183)
D. lnTRev .651***
(.242)
*[**](***) denotes rejection of the hypothesis at 10%[5%] (1%) significance
level. Figure in the bracket () indicates standard error.
Source: Author’s calculation
From table 4.12, lagged error correction value was negative and
significant with regard to real GDP growth as a dependent variable. The Uhat (-1)
coefficient is the speed of adjustment factor, ECM term. The ECM term is negative and
significant at 5% significant level as expected. This entails that 0.107 percentage of
disequilibrium in the previous year is restore in the current period.
Thus according to tables 4.9, 4.10, 4.11 and 4.12, real GDP appear to
respond to restore disequilibrium in Bhutanese economy. It entails that the real GDP
67
will converge to long run equilibrium path when there is any short run deviation.
Therefore, the real GDP is stable in the long run in Bhutan.
Notes: variables as previously defined, all the variables are in first difference for the
short run analysis. Uhat (-1) is the ECM term.
68
CHAPTER 5
CONCLUSION AND RECAMMENDATIONS
5.1 Conclusion
Many kinds of studies were carried out by different researchers of
diverse background in order to understand the impact of government spending at the
aggregated and disaggregated level on the economic growth using different techniques
and economic variables. Few of these studies involved to study the impact of public
spending on different sectors of the economy, say like percapita economic growth.
Many other advocates devoted their studies to examine the role of economic growth on
public spending. In this study, we narrow down our analysis to predict the influence of
public expenditure on real GDP in Bhutan.
Since economic theories provided no clear cut answer to how
government size affect economic growth, researchers mostly rely on existing empirical
studies. There has been mixed results on this issue. Ram(1986), Grossman(1988),
Aschauer(1989), Holmes and Hutton(1990) generally found positive association, while
other such like Landau (1986) & Bradley(1989) argued negative or insignificant
relationship between size of a government and growth. This research relied on
Keynesian theory and Endogenous Growth theory developed by Barro and Sala-i-
Martin (1992) as a basis to theoretically validate the findings (results).
The contribution of this research have two folds in existing literature.
Firstly, our findings complement the overall existing literature where most researcher
have had focused on panel cross country analysis. As we know that the effects of public
spending on growth are likely to be influenced by institutional factors and the quality
of bureaucratic systems, it is more appropriate to carryout time series analysis to tackle
such issues. Secondly, this research will immensely help planners in Bhutan as it is the
first research in
relation to public expenditure and real GDP growth. No studies has been conducted in
relation to public expenditure and real GDP growth in Bhutan.
69
Our analysis started with a discussion of pattern and trend of
government expenditure in Bhutan over the period of 31 years, starting from 1985. The
evidence from the graph and statistics showed that total government expenditure has
increased over the time. In other hand, we can see that relative increase in size of public
spending was not accompanied by robust economic growth in the recent times. In fact,
economic growth in Bhutan dropped to 2.14% in fiscal year 2012-2013. This shows
that over the past three decades, government spending grew at a faster rate than the
growth of real GDP. Thus, the rapid growth of Public expenditure caused a concern
among policy makers on its implication on growth. In such type of financial state, an
explanation requires studying the impact of public spending on real GDP growth. This
study is one which tries to investigate the effects of components of government
expenditure on real GDP growth in Bhutan.
The study used unit root test, Cointegration, Least Square regression and
error correction methods to answer the question set in chapter 1. Unlike most of the
studies that used panel or cross-sectional data, this paper take annual data into account
to evaluate the relationship between real GDP growth and components of government
expenditure. After using the stated methodology, the study found interesting results.
The study discovered that some types of government expenditure have potential to
promote real GDP growth. Firstly, the empirical finding pertaining to model 1
demonstrated a significant positive impact of government expenditure on real GDP
growth with current expenditure having greater impact on GDP growth. This suggest
that spending on repair and maintenance has a stronger impact on growth than capital
spending. Indeed, all variables stated in model 1A, 1B and 1C including control variable
showed statistically positive impact on real GDP growth. This tells us that total
government expenditure, capital expenditure, current expenditure, and revenue from
tourism have growth enhancing effects in long run in Bhutanese economy. However,
Model 2 predicted mixed findings.
Following are the main findings of this study. It state the presence of
long run equilibrium relationship exist among the variables. It is also known that
Productive government expenditure affects economic growth positively and
significantly (Barro, 1990). It means that, the success of public spending in intensifying
the economy and fostering rapid economic growth depends on whether the expenditure
70
is productive or unproductive. All things being equal, productive expenditure would
have positive effects on the economy, while unproductive expenditure would have
negative effects on the economy. Therefore, the findings from these fiscal variables
strongly support the prediction of public fiscal policy endogenous growth model. On
the other hand, expenditure on economic affair showed positive but insignificant result
in the long run. However, expenditure on foreign affair exert adverse effect on growth
of real GDP. It also crucial to state that the negative and significant coefficient of Uhat
(-1) indicates that Bhutan’s real GDP responds to restore disequilibrium in the long run.
It means that real GDP will converge to long run equilibrium path if there is any short
run deviation.
5.2 Policy Recommendation
Economic growth in Bhutan highlights volatility and registered very low
in some year. On the other hand, government spending as a fiscal policy tool failed to
play its expected role to stimulate the GDP growth in Bhutan. In this regard, we draw
some policy recommendation from the findings of our study, such as:
1. The study recommends that government should not waste its
available resources in order to finance non-productive expenditure since they have
neutral or no impact on GDP growth. Rather government should use available income
for Productive Purpose. Such type of policy will be helpful in improving infrastructure
facilities, education, agriculture, health that will in turn boost private sectors
investments.
2. Government should allocate higher percentage of resources to
spend on Agriculture sector and information and communication. Spending on
information and communication will improve the quality of linkage of road way, air
way, telecommunication network and IT park. While spending on agriculture and forest
will make Bhutan to meet food self-sufficiency and ensure food security of a nation.
3. Government should decrease the spending on Ministry of Foreign
Affair as it has adverse effect on real GDP growth both in long and short run.
4. Although public spending in economic affair is found to be
insignificant determinant of GDP growth, government should not cut allocation of
71
expenditure on this department as it remain important pillar of economic growth in
Bhutan. Increasing spending on economic affair improves Cottage and Small industries
which was indeed growing very slowly over the year accept hydro power sector.
5. Government should discover more tourism activities, spots with
modern amenities to encourage more inflow of foreign tourist in the country as it
contributes to GDP growth in Bhutan. And also, revisit tourism policy to address the
high prevailing tourist tariff in order to receive more number of dollar paying tourists
in the country. Finally, the role of government should be supportive in all case to allow
tourism sectors to drive economic growth in Bhutan and ensure sustainability of the
industry.
1.3. Suggestions for future research
One of the core macroeconomic indicator associated with fiscal policy
is government expenditure, which was covered in current paper. In this empirical study,
out of ten departments (Ministries) only four are included due to unavailability of data.
To evaluate the impact of government expenditure (fiscal policy) on economic growth
further in more detail, other important sector should be applied such as education,
health, etc. in order to check which sectors contributes the most. Moreover, tax revenue
should be included as it increases the government expenditure. Subsequently, increase
in government spending will then increases total GDP in a specific year.
Furthermore, different econometric techniques should be applied beside
what is used in this study. I suggest to use VECM which represent the system equations
model beside other good model. This model can explain the relation of all variables
together in the system.
72
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APPENDIX
Appendix 1. Estimated Result with gross capital formation and tourism revenue as
control variables.
Table 1.1
Model 1: Long Run Estimated Result
Dependent variable: log of real GDP (lnRGDP)
Method: Least Square
Variables Model 1A Model 1B Model 1C
Coef. Coef. Coef.
lnTExp .398***
(.1298)
lnCAPExp(-1)
.242***
(.0586)
lnCURExp .471 ***
(.1107)
lnGCF .214**
(.0854)
.229***
(.071)
.159**
(.071)
lnTRev .176***
(.0602)
.243***
(.0348)
.163***
(.0553)
*[**](***) denotes rejection of the hypothesis at 10%[5%](1%) significance level
Figure in the bracket () indicates newey-west standard error.
Source: Author’s calculation
81
Table 1.2
Model 2: Long Run Estimated Result
Dependent variable: RGDP
Method: Least Square
Variables Coefficient
lnExpAF .139
(.1088108)
lnExpEA .009
(.0434385)
lnExpIC .0710**
(.0306234)
lnExpFA -.0734*
(.0388867)
lnGCF .394***
(.1035404)
lnTRev .286***
(.0669194)
R-Squared 0.9670
Adj. R-Squared 0.9587
Prob(F-Stat) 0.0000
Durbin-Watson stat. 1.277282
Source: Author’s calculation
82
Table 1.3
Model 1A: Short Run Estimated Result
Dependent
variables
Independent variables
LD.lnRGDP LD.lnTExp LD.lnGCF LD.lnTRev Uhat(-1)
D.lnRGDP -.1767
(.1463)
-.08606
(.0604)
-.00925
(.0343)
-.06247**
(.03142)
-.405***
(.0863)
D.lnTExp 1.2289
(.5865)
.018413**
(.2423)
.13008
(.13769)
.03956
(.12593)
.3557
(.3460)
D.lnGCF -.36963
(.70870)
.61583**
(.29284)
.01830
(.1663)
-.4221***
(.15216)
1.123**
(.4180)
D.lnTRev -.41368
(.8484)
.01153
(.3505)
.10989
(.1821)
-.16751
(.19919)
1.073**
(.5005)
Figure in the bracket () indicates standard error.
*[**](***) denotes rejection of the hypothesis at 10%[5%](1%) significance level
Source: Author’s calculation
83
Table 1.4
Model 1B Short Run Estimated Result
Dependent
variables
Independent variables
LD.lnRGDP L2D.lnCAPE
xp
LD.lnGCF LD.lnTRev Uhat(-1)
D.lnRGDP -.0516
(.18965)
-.00150
(.012482)
-.00293
(.04568)
-.05215
(.04121)
-.198**
(.08150)
L1D.lnCAPEx
p
.64534
(.89901)
-.05275
(.05917)
.19321
(.21657)
.22963
(.19535)
-.21025
(.38638)
D.lnGCF -.479559
(.70310)
.00828
(.04627)
.070171
(.16937)
-.416**
(.15278)
.771***
(.30218)
D.lnTRev -.93163
(.95790)
.03349
(.06304)
-.24540
(.23075)
.06343
(.20815)
.21155*
(.41168)
Figure in the bracket () indicates standard error.
*[**](***) denotes rejection of the hypothesis at 10%[5%](1%) significance level
Source: Author’s calculation
84
Table 1.5
Model 1B Short Run Estimated Result
Dependent
variables
Independent variables
LD.lnRGDP LD.lnCRExp LD.lnGCF LD.lnTRev Uhat (-1)
D.lnRGDP -.06960
(.15220)
-.05064
(.0631)
.0051
(.03598)
-.0870**
(.03387)
-.447***
(.11273)
D.lnCRExp 1.442***
(.489)
.3067
(.2028)
.16868
(.11565)
-.0387
(.1088)
.810**
(.36230)
D.lnGCF -.60466
(.74222)
.37496
(.30782)
.00812
(.17549)
-.3265*
(.1652)
1.0397*
(.5497)
D.lnTRev -.7923
(.87008)
.16393
(.3608)
.1607
(.19365)
-.2279
(.20572)
1.3066*
(.64446)
Figure in the bracket () indicates standard error.
*[**](***) denotes rejection of the hypothesis at 10%[5%](1%) significance level
Source: Author’s calculation
85
Table 1.6
Model 2 Short Run Estimated Result
Dependent Variables Independent variable
Coefficient
Uhat (-1)
D.lnRGDP -.1395**
(.07007)
D.lnExpAF .2348
(.5042)
D.lnExpEA -1.861
(1.0975)
D.lnExpIC .51500
(.9919)
D.lnExpFA -.9514
(1.515)
D.lnGCF .7991***
(.2553)
D. lnTRev .5622*
(.32855)
Source: Author’s calculation
86
BIOGRAPHY
Name Bal Bdr. Kharka
Date of birth November 27, 1984
Educational Attainment 2005-2007: Bachelor of Commerce (Hons)
Sherubtse College, Kanglung Bhutan
2009: Post Graduate Diploma in Education
Samtse College of Education (NIE), Bhutan
Scholarship Thailand International Cooperation Agency
TICA (Agency)