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64Review of Business and Economics Studies 2021, Vol. 9, No. 2, 6-15
DOi: 10.26794/2308-944X-2021-9-2-6-15
Impact of Raising Tax Rates in GDP Growth:
The Case of Nepal
Sanjaya Acharya ABSTRACT
This study is an effort to examine whether there is a potential of variations in tax efforts of different types in making a positive impact on economic growth in a typical developing economy. We take the case of Nepal and analyse 44 years (1975-2018) of time series data of growth and fiscal variables. We conclude that Nepal has already reached its optimal tax GDP ratio. Additional efforts to collect more tax revenue are counter-productive; rather, it should take some other structural measures for higher GDP growth. implementation of several scenarios of revenue replacement does not have a significant positive impact on GDP; however, minimising the contribution by excise duties but replacing its contribution by income tax has minimal positive impact on GDP. It refers to the need to protect Nepalese infant industries at this juncture of the fiscal-growth discourse of this small developing economy.
Keywords: tax rates; public sector revenue; GDP growth JEL Classifications: G18, H21, H25, H71, E62 © Sanjaya Acharya, 2021
1 General Background
The impact of restructuring tax rates on GDP growth is crucial in the wake of economic reforms in different economies, more specifically after the mid-1980s that witnessed liberalisations in both factor and product markets. Three significant strands of analysis are existent in this regard so far. Many researchers analysed the impact using partial analysis with select macro variables; however, some followed general equilibrium analysis. The third group of analysis is exploratory in nature, before-after analysis and cross-country comparison. The conclusions of these studies are hardly consistent with each other. In the vast array of literature, evidence shows the growth enhancing and retarding effects of different tax systems and short-term and long-term impact on growth and other macro-economic performance of the economy. However, as Rimmler et al. (2017) remarks, tax revenue in various forms still dominates the public sector revenue in developed, developing, and underdeveloped economies.
The impact of tax structure on economic growth occurs through its effect on both labour and capital markets. More specifically, the level of capital and intermediate goods tax has a significant impact on economic growth; countries with lower
tax rates grow faster than those applying high tax rates (Gerson, 1998). Regarding the tax types, high direct taxes reduce consumer spending in the short-term and reduce economic efficiency and welfare in the long run, Gale and Samwick (2014). Analysing the relationship between taxes and the rate of economic growth among 23 OECD countries for the period 1965-1990, Widmalm (1999) demonstrated that taxes have a negative effect on economic growth. The econometric analysis also revealed that progressive taxation results in a more adverse effect on real GDP.
Romero-Avila and Strauch (2008) concluded with the negative impact of direct taxes on GDP growth rate per capita through the strong negative impact on capital accumulation. Ferede and Dahlby (2012) and Nechaev and Antipina (2016) also concluded with the overall negative impact of tax effort ratio on the GDP growth rate. However, Asllani and Statovci (2018) and Gasteratos et al. (2016) treated the impact differently to basic consumption products and luxury products with the conclusion that the reduction of the tax rate on the consumption of basic products and an increase in the tax rate on luxury products has a positive effect on the growth of GDP.
Contrary to the conclusions of the studies mentioned above, Arnold (2008) concluded with the
positive taxes in consumption and taxes on personal income. Furthermore, corporate income taxes have the most negative impact on GDP per capita, while real estate taxes and especially reuse tax on real estate has a more positive effect on growth. High corporate taxes discourage potential investors from realising investments in the given country because they reduce the return on invested capital and the capital structure or age of a company (Daniel and Jefferey 2013). Schraztenstaller and Kohler (2015) demonstrated a negative link between corporate tax and foreign direct investment (FDI).
Various studies conclude that public revenues affect economic growth more than public expenditures, given the other macroeconomic parameters.
The public financial system in Nepal has undergone significant changes for the last three and half decades. Several initiatives do have a significant impact on the Nepalese public sector revenue and consequent expenditure system. Liberalisation of health and education services began in the mid-eighties as a component of the structural adjustment program of the World Bank. Likewise, full convertibility of the current account and partial convertibility of the capital account and the relaxation of the price control in both factor and product markets appeared as a policy prescription of the Stabilization Program of the International Monetary Fund (IMF). Privatisation of state-owned enterprises initiated at the beginning of the 1990s. Furthermore, Nepal received the membership of the World Trade Organization, South Asian Free Trade Agreement (SAFTA) and the Bay of Bengal Initiative for Multi-Sectoral and Technical Cooperation (BIMSTEC) in the mid-2000s. Moreover, along with the adoption of the federal system of governance, revenue and expenditure flows have spread to three tiers of the government.
Several studies exist in measuring tax productivity in Nepal, VAT and other tax potentials. Examples include Acharya (2016a, 2016b, 2010). However, studies assessing the growth impact of these reform measures are absent, specifically the impact of tax rate changes on production and work incentives that eventually translate into the economy's growth performance. This study intends to fulfil this gap. The remainder of this paper runs as follows. Section 2 mentions the paper's objectives and methods, followed by data and observations in section 3. Section 4 presents the analysis and discusses the results. Section 5 concludes.
2 Objectives and Methods
This study reviews the budgetary reforms for the last three decades in light of the country's high growth potential. In this regard, it assesses the elasticity of various taxes in Nepal and explores the tax potentials of them. Furthermore, it explores the avenues that circumvent the combinations of tax and other variables that affect the economy's growth performance.
The major data used in this study are as follows:
a. Total revenue series by various tax categories from the 1980s to the latest available
b. Time series databases of various tax types
c. Reports of the public expenditure reviews of the government conducted in various periods
d. Consistent time series data of the major macroeconomic variables, i.e. GDP by sectors, growth rates, employment, domestic investment, capital formation, foreign direct investment, etc.
Broader methodological approach to this study has comprised:
A. Review of the available methods in measuring the impact of the tax rate changes on economic growth,
B. Include both short term dynamic relationship between revenue variables and GDP growth,
C. Include other variables that impact GDP along with the revenue variables, and
D. Keep revenue GDP ratio as a controlled variable while assessing the impact of the variations of different tax types on the economy's growth performance.
The study has conducted some econometric analysis that stemmed from the previous works by various researchers. Based on the best fit models on revenue vs growth diagnostics, the study has conducted some simulation analyses with the impact of an increase in public sector revenue on the overall growth performance of the economy. The government's revenue generation capacity is instrumental in funding priority investments and programs and institutes a simpler, fairer, and more efficient tax system in the developing economy.
Three methodological approaches exist in analysing the impact of tax rate changes on government revenue: tax multiplier approach, general equilibrium approach, and partial equilibrium approach. The tax multiplier approach uses the following model in assessing the impact of the tax rate change on Gross Domestic Product (GDP):
Y = a + b(1 -1)Y-b(1 -1)T0 + b(1 -1)tr +1 + G, (1)
where Y, G, and I refer to GDP, government expenditure, and total investment, respectively. a, b, t, and tr are the autonomous consumption, marginal propensity to consume (MPC), tax rate, and transfer payment, respectively. T0 is the fixed revenue.
Equation (1) can be solved as
a - b (1 -1 )Tn + b (1 -1) tr + G
Y =-^-(2)
1 - b (1 -1)
Based on this three-sector model, the tax impact on GDP is measured using the tax multiplier and this can be expressed as follows:
K
Kt 1 - b(l -1)
(3)
This multiplier approach in assessing the taxation impact on GDP concludes that taxation has a contractionary impact on output. The economic growth and revenue dynamics were initially modelled by Arnold et al. (2011).
AIny, _-0;.
my u-i -P/n4 -p2Mt + + P3n-t +SW -au
+
(4)
+bu Mnsk + b2i AMt +b3i An, +Ybji kVt + 8;.;
In equation 4, y refers to GDP, s the ratio of investment to accumulated capital, h the average number of schooling of the working-age population, n the population growth rate, and V the tax policy variables.
The present study follows this modular framework with slight modification in line with that of Acosta-Ormaechea and Yoo (2012) that essentially follows Arnold et al. (2011). More specifically, we study the relationship as follows:
g, _-0
gt-1 -aiI,-1 -a2Inh,-i -a3n,-i ■
m
-«4 T-i-Xaj TCj-i
j _5
+ P1AIt +p2Alnht +P3Ant +p4ATt -
m
-£Pj. .ATCj +Y.t + e,
j _5
+
(5)
In the given equation g is the GDP per capita growth, I is the investment ratio, and h is the number of years of schooling, n is the population growth, T is the tax revenue as a share of GDP. TC is the vector of tax-composition variables expressed as a share of total tax revenue. The subscript t refers to a time in years and s the error term.
The equation 5 has two broader components. The first, kept in the parenthesis that is also known as error correction term, captures the long-term relationship between growth and the explanatory variables. The variable T has been regarded as a control variable that is kept intact along with the variations of shares of different taxes in overall tax revenue. The second part, terms outside the parenthesis, measures short term dynamic effect of all the explanatory variables used in the model. This model measures the impact of tax policy change with revenue neutrality.
3 Data and Observations
This study uses the time series data for 44 years (1975/76-2017/18). The summary statistics of the variables used in the model are presented in Table 1. The average growth rate of the Nepalese economy has remained 4.5 per cent during this period, but it is fluctuating between -3 and almost 10 per cent. The population growth rate remained approximately 2.04 per cent.
Going to fiscal variables, the tax GDP ratio has been 9.5 per cent on average, but it was rather low (5.1 per cent) at the beginning but had been gradually increasing. It peaked up to almost 22 per cent in 2017/18. In the revenue composition, the share of VAT in total tax revenue is highest (31%); this was 20 per cent at the beginning but has reached almost 38 per cent now. Likewise, the share of income tax to total tax is also increasing from six to 28 per cent. Contrary to this, the contribution of excise duties in total tax revenue has remained almost stable, around 13 per cent, with minor fluctuation, the standard deviation being 0.02. The trend is opposite in the case of customs duties; its share in total revenue is gradually declining significantly from the mid-2000s, mainly due to Nepal's accession to the World Trade Organization (WTO), South Asia Free Trade Area (SAFTA), and Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Co-operation (BIMSTEC). During this period, contribution by import duties in total tax revenue declined from about 35 to 17 per cent.
Table 1
Summary of the major variables used in the study (1975/76-2017/18)
Variables No of observations Mean Std. deviation Minimum Maximum
GDP growth rate 43 4.715 4.539 -3.00 9.700
Population growth rate 44 2.036 0.405 1.350 2.660
Tax GDP ratio 44 0.095 0.041 0.051 0.219
VAT to total tax ratio 44 0.312 0.037 0.200 0.376
import tax to total tax ratio 44 0.251 0.049 0.170 0.346
Excise duties to total tax ratio 44 0.132 0.022 0.084 0.158
income tax to total tax ratio 44 0.159 0.065 0.056 0.278
Annual rate of inflation (%) 44 8.655 4.505 -0.700 21.10
Capital formation to GDP ratio 44 0.203 0.043 0.120 0.340
Rate of investment growth 44 0.254 0.088 0.134 0.518
In the 44 years covered by the study, the average inflation rate remained approximately nine per cent, ranging from 4.5 to 21 per cent. The capital formation to GDP ratio remained around 20 per cent, and the annual growth of investment around 25 per cent.
4 Results and Discussions
The results as presented in Table 5 show the relative effectiveness of different taxes on economic growth. We start with Arnold (2011) model (equation 4), more specifically, the version adopted by Acosta-Ormaechea and Yoo (2012) (equation 5) and make its extension/adjustment with the inclusion of some other variables that reveal more explanatory power in case of Nepal as presented in Table 2. Firstly, we develop a baseline scenario and make some simulation analysis. The variables used in the model belong to four different categories: dependent variable, independent variables, control variable, and policy variables. For the details regarding dependent, independent, control, and policy variables, please see Appendix A1.
The growth rate of GDP is the dependent variable in all the models used. Moreover, there are several independent, control, and policy variables in the model. Change in investment GDP ratio, change in capital expenditure to total expenditure ratio, change in population growth rate, change in tax GDP ratio, change in the share of income tax to total tax revenue, change in the share of
import duties to total tax revenue, change in the share of excise duties to total tax revenue, change in the share of VAT to total tax revenue, time variable, GDP growth rate, investment growth rate, capital expenditure to total expenditure ratio, population growth rate, the ratio of income tax revenue to total tax revenue, the share of import duties to total tax revenue, the share of excise duties to total tax revenue, and share of value-added tax to total tax revenue are the independent variables. Likewise, the tax revenue GDP ratio is the control variable in the simulation scenarios. We are trying to explore whether changes in the growth rate of revenue of a particular tax type, keeping the tax revenue ratio unchanged from the natural change, would contribute to higher economic growth. Three simulation scenarios are developed in this regard:
No change in the income tax and excise duties, but additional tax effort is from value-added tax. In this case, the trend of the growth of import duties is also expected from value-added tax (simulation 1)
No change in the import duties and value-added tax, but additional tax effort is from income tax. In this case, the trend of the growth of excise duties is also expected from the income tax (simulation 2)
Additional revenue generation is expected from value-added tax and income tax; the growth trends of import duties and excise duties are merged to that of VAT and income tax, respectively (simulation 1 + simulation 2).
Table 2
Growth and tax revenue composition correlates (Dependent variable GDP growth rate)
Independent variables
Arnold and Acosta/Yoo model
Baseline scenario (Present study model)
Simulation 1
Simulation 2
Simulation 3
AI
CapExTotExRtCh An
AT
AITs AImpDs AExcDs AVATs t
G(t-1) i(t-1)
CaExp/TotEx(t-1)
n(t-1) T(t-1)
its(t-1) impds(t-1)
ExcDs(M)
VATs(t-1)
Constant
Simulation policy variables
impToVAT
ExcToincTx
R2
Adjusted R2
-25.09 (-0.91)
-9.22 (-0.44)
-356.86 (-3.45)***
14.87 (0.32)
96.62 (1.94)*
108.07 (1.67)*
65.02 (1.28)
-0.187 (-0.61)
-0.406 (-3.43)***
39.1 (0.87)
6.94 (1.06)
86.56 (1.31)
-113.97 (-2.24)**
202.61 (-2.95)***
16.56 (1.17)
-1.53 (-0.08)
-386.1 (-4.24)***
45.17 (1.08)
114.83 (2.32)**
133.02 (2.04)**
91.47 (1.72)
-0.132 (-0.45)
-0.411 (-3.64)***
16.94 (1.61)* 0.58(0.11) 65.52 (1.11)
-148.16 (-2.18)**
-144.21 (-1.81)* -74.78 (-0.99)
95.66 (-1.75)* 98.11 (2.46)*
-29.41 (-0.54) 56.54 (1.27)
0.73 0.56
0.75 0.69
7.65 (0.52)
5.60 (0.26)
-360.35 (-3.68)***
-35.34 (-0.75)
53.23 (0.89)
-0.097 (-0.30)
-0.387 (-3.19)**
14.28 (1.26) 4.30 (0.76) 97.85 (1.59)
20.16 (1.41)
-13.53 (-0.73)
-387.17 (-4.16)***
109.62 (2.17)**
77.61 (1.45)
-0.27 (-0.95)
-0.369 (-3.31)***
14.83 (1.39) -0.196 (-0.04) 94.32 (1.67)*
7.40 (0.49) 5.28 (0.24)
95.07 (1.47)
253.45 (0.19)
344.81 (0.25) -0.105 (-0.32)
0.388 (-3.11)*
13.60 (1.15) 0.598 (0.11) 4.11 (0.71)
-27.36 (-0.43) -97.09 (-1.58) 30.57 (-0.46) -96.89 (-1.54)
-252.29 (-4.58)***
-159.23 (-2.22)**
-94.33 (-1.87)*
114.83 (2.89)**
11.63 (0.27)
0.69 0.52
-153.45 (-2.21)**
-108.38 (-1.47)
-39.08 (-0.71) 68.53 (1.53)
62.88 (1.42) 0.73 0.58
-250.30 (-4.42)**
-157.45 (-2.12)**
-91.44 (-1.73)*
114.34 (2.81)***
-331.03(-0.25) 53.96 (0.86) 0.70 0.51
Note: Figures in parentheses are corresponding t-values of the coefficient estimated. at 10, 5, and 1 per cent, respectively.
' refer to the level of significance
Control variable
T(t-1) = tax revenue GDP share of the previous year
Policy variables (introduced in simulations)
ImpToVAT = share of import duties to total tax revenue merged into VAT to total tax revenue share
ExcToIncTx = share of excise duties to total tax revenue merged into income tax to total tax revenue share
Even more significant variable affecting economic growth is investment growth. Moreover, the past year's investment also affects the overall GDP growth of the current year. Once the higher economic growth rate is attained, it supports the growth rate to go up in the following years as well, as shown by the solid positive time variable.
Among the tax variables, they are causing contraction in the economic growth rate. Only in the case of value-added tax, the impact on the growth rate is expansionary. It should be understood cautiously. The value-added tax may not directly contribute to raising the growth rate, but in a higher growth spiral, the VAT collection also rises due to increased turnover in the market.
The models presented are found accepted as the residuals left are found fully stochastic in nature. Please refer to Appendix 2A.
5 Conclusion
The study applied an econometric model in measuring the short-term dynamic relationship as well as the long-term association between revenue and growth performance of a typical developing economy. Taking the case of Nepal, additional tax revenue generation effort does
not prove to be growth-enhancing. Rather, it has a contractionary effect on GDP. However, to examine the effects of raising the revenue from a particular tax type on GDP growth, we made the tax revenue to GDP ratio intact and developed three different scenarios. To put it in other words, series of revenue replacement scenarios are developed. First, we implement a scenario of no change in the income tax and excise duties, but additional tax effort is from value-added tax. In this case, the trend of the growth of import duties is also expected from value-added tax. Second, we implement a scenario with no change in the import duties and value-added tax, but additional tax effort is from income tax. In this case, the trend of the growth of excise duties is also expected from the income tax. In the third effort, we combine the two scenarios, i. e. additional revenue generation is expected from value-added tax and income tax; the growth trends of import duties and excise duties are merged to that of VAT and income tax, respectively.
The study concludes that Nepal's tax GDP ratio is on a higher side; therefore, any further effort to raise additional tax generates contractionary effects. The three different scenarios of revenue replacement developed also do not prove to be productive in making a significant impact on GDP growth. However, raising the revenue share from import duties and revenue replacement of excise duties by additional income tax reveals some positive impact on economic growth. Raising the share of import duties might have worked positively to economic growth due to the import of capital goods and intermediate imports rather than the import of final consumption goods/services.
References
Acharya, S. (2010). Import Liberalisation and Revenue Replacement: Impacts in a Small Asian Developing Economy. European Journal of Development Research, 3(22), pp. 417-442.
Acharya, S. (2016). Reforming Value Added Tax System in Developing World: The Case of Nepal. Business and Management Studies, pp. 44-63.
Acharya, S. (2016). Role of Public Investment in Growth and Poverty Reduction in Transition Economies. Journal of Reviews on Global Economics, 5, 310-326.
Acosta-Ormaechea, S., & Yoo, J. (2012). Tax Composition and Growth: A Broad Cross-Country Perspective. IMF Working Paper WP/12/257, International Monetary Fund.
Arnold, J. (2008). Do Tax Structures Affect Aggregate Economic Growth? Empirical Evidence from Panel of OECD countries. OECD Working Paper EC0/WKP(2008)51, Paris: OECD.
Arnold, J. M., Brys, B., Heady, C., Johansson, A., Schwellnus, C., & Vartia, L. (2011). Tax Policy for Economic Recovery and Economic Growth. The Economic Journal, 121, pp. F59-F80,
Asllani, G., & Statovci, B. (2018). Effect of the Change in Value Added Tax on the Fiscal Stability of Kosovo. Croatian
Economic Association Zagreb, 65(6), 513-540. Daniel, B., & Jeffrey, P. 2013. Investment Taxation and Portfolio Performance. Journal of Public Economics, 97(1), pp. 245-257.
Frede, E., & Dahlyb, B. (2012). The Impact of Tax Cat on Economic Growth: Evidence Form Canadian Province. National Tax Journal, 65(3), pp. 563-594. Gale, W. G., & Samwick, A. A. (2014). Effects of Income Tax Changes on Economic Growth, SSRNElectronic Journal. Gasteratos, I., Karamalis, M., & Koutoupis, A. (2016). Shadow Economy Worsens Income Distribution. International
Journal of Economics & Business Administration, 4(3), pp. 80-92. Gerson, P. (1998). The Impact of Fiscal Policy Variables on Output Growth, IMF Working Paper WP/98/1, IMF. Nechaev, A., & Antipina, O. (2016). Analysis of the Impact of Taxation of Business Entities on the Innovative Development of the Country. European Research Studies Journal, 19(1), pp. 71-83. Rimmler, M., Rose, M., & Zöller, D. (2017). Tax Reform for Tax Competition: Which Alternatives should be Used?
Croatian Economic Association Zagreb, 56(11), pp. 1079-1100. Romero, D., & Strauch, R. (2008). Public Finance on Long-term Growth in Europe: Evidence from Panel Data Analysis.
European Journal of Political Economy, 24, pp. 172-191. Schraztenstaller, W., & Kohler, T. (2015). The Impact of Tax on Economic Growth. Case Study of OECD Countries. Paris: OECD.
Widmalm, F. (1999). Tax Structure and Growth. Are Some Tax Better than Others? Public Choice, 107, pp. 199-219. Appendix:
Appendix A1: Variables in the model
In the given linear regression models, the GDP growth rate is the dependent variable. The followings are the independent, control, and policy variables used in the model:
Independent variables:
AI = change in investment GDP ratio
CapExTotExRtCh = change in capital expenditure to total expenditure ratio An = change in population growth rate AT = change in tax GDP ratio
AITs = change in the share of income tax to total tax revenue AImpDs = change in the share of import duties to total tax revenue AExcDs = change in the share of excise duties to total tax revenue AVATs = change in the share of VAT to total tax revenue t = time variable
G(t-1) = GDP growth rate of previous year
I(t-1) = investment growth rate of the previous year
CaExp/TotEx(t-1) = capital expenditure share in total expenditure of the previous year n(t-1) = population growth rate of the previous year
Its(t-1) = income tax revenue share in total tax revenue of the previous year ImpDs(t-1) = Import duties share in total tax revenue of the previous year ExcDs(t-1) = Excise duties share in total tax revenue of the previous year VATs(t-1) = Value added tax share in total tax revenue of the previous year
Control variable
T(t-1) = tax revenue GDP share of the previous year Policy variables (introduced in simulations)
ImpToVAT = share of import duties to total tax revenue merged into VAT to total tax revenue share ExcToIncTx = share of excise duties to total tax revenue merged into income tax to total tax revenue share
Appendix A2: Residual Plots
5 ^ Growth rates vs. residuals (Baseline model)
• •
• • • . •
Res idu • * •
als • • • . ,
0 ^ * •
• • •
•
• •
•• :
• 9
-5
-10 i i 0 10 20 Fitted values
Growth rates vs. residuals (Simulation model 1)
5 J
-5
• •
•• •
Resdu als
0 J
• • •
. . a'
-10 -5 0 5 10 15
Fitted values
Growth rates vs. residuals (simulation model 2)
CD '
■t -
<2™ TO
"O
w 0£ °
OJ -
• •
•V. . • • •• •
• • •
.__
—I-1-1-1-1-1—
-10 -5 0 5 10 15
Fitted values
Growth rates vs. residuals (simulation model 3)
• •
• •• • • • . •
m -
<2
3 O
I-1-1-1-1-r~
-10 -5 0 5 10 15
Fitted values
aboutthe author
Sanjaya Acharya holds PhD in Economics, Erasmus University Rotterdam, The Netherlands (Nov. 2006, which received the best doctoral award in global competition), PhD in Economics from Hokkaido University, Sapporo, Japan (March 2006), JSPS Post-doctoral Research at Hokkaido University, Japan (2008). He is a Development Economist and free-lance consultant based in Kathmandu, Nepal. Previously, he worked as a Professor of Economics at Ritsumeikan University, Shiga, Japan and before that Associate Professor of Economics at Tribhuvan University, Kathmandu, Nepal. Sanjaya Acharya is a Visiting fellow at Southasia institute for Advanced Studies, Kathmandu. Sanjaya also led several research projects at New ERA, Kathmandu, from 1995 to 2011, along with several independent consulting assignments. He also holds a Master degree in Development Economics from
the International Institute of Social Studies (ISS), Netherlands. He is working on pro-poor growth in developing economies.
Correspondence: Dr Sanjaya Acharya, Department of Economics, Saraswati Campus, Tribuvan University, Kathmandu, Nepal. E-mail: sanjaya.acharya@gmail.com
Влияние повышения налоговых ставок на рост ВВП Непала
Санджая Ачарья
аннотация
Данная работа представляет собой проверку гипотезы существования вероятности того, что различия в налоговых условиях разных типов могут оказать положительное влияние на экономический рост в странах с развивающейся экономикой. Автор проанализировал данные временных рядов о росте и фискальных переменных за 44 года (1975-2018 гг.) в Непале. В результате исследования он пришел к выводу, что Непал уже достиг оптимального соотношения налогов к ВВП и дополнительные усилия по сбору налоговых поступлений будут в дальнейшем контрпродуктивны. Опираясь на результаты исследования, автор указывает на необходимость защиты этой небольшой развивающейся экономики и непальских зарождающихся отраслей от фискального роста и предлагает руководству Непала принять некоторые другие структурные меры для обеспечения более высоких темпов роста ВВП.
Ключевые слова: налоговые ставки; доходы государственного сектора; рост ВВП
об авторе
Санджая Ачарья - экономист по вопросам развития и внештатный консультант из Катманду (Непал); приглашенный научный сотрудник Южноазиатского института перспективных исследований (Катманду). Защитил докторскую диссертацию по экономике в Университете Хоккайдо (Саппоро, Япония, март 2006 г.). Имеет диплом Университета Эразма (Роттердам, Нидерланды, ноябрь 2006 г.). Его вторая докторская диссертация, защищенная в Роттердаме, была признана лучшей в рамках университетского конкурса. Имеет также звание магистра экономики развития Международного института социальных исследований (ISS, Нидерланды) и диплом о завершении постдокторского исследования JSPS в Университете Хоккайдо (Япония, 2008 г.).
