Accelerated Economic Growth and Tax Effort: The case of an Economically Advanced State of India

Transcription

1 Accelerated Economic Growth and Tax Effort: The case of an Economically Advanced State of India By K. Pushpangadan Visiting Professor Rajiv Gandhi Institute for Development Studies Thiruvananthapuram and Sthanu R. Nair Associate Professor Indian Institute of Management Kozhikode Kozhikode Abstract To meet her developmental requirements Kerala requires sufficient tax revenue mobilisation. This paper attempts to empirically estimate the effort taken by Kerala in mobilising tax revenues in relation to its taxable capacity during two different phases of the state s economic growth trajectory: and. Whereas the first period has experienced stagnant to moderate economic growth, the second period saw rapid economic progress. The findings of the paper reveal that though Kerala was able to improve the tax effort with respect to land revenue, motor vehicle tax and passengers and goods tax, state excise duty and own tax revenue during the period of accelerated economic growth in the case sales tax, which contributes the lion s share of the tax revenue, the state s tax effort lowered significantly. The state has earned lowest ranking based on the tax effort for many taxes when compared to other comparable states. Keywords: Economic Growth, Tax effort, India, Kerala JEL Classification: H2, H71 We thank Indian Institute of Management for providing financial support for this work. Thanks are also due to Keerthana S for her excellent research assistance. The usual disclaimer applies. 0

2 1. Introduction Accelerated Economic Growth and Tax Effort: The case of an Economically Advanced State of India After facing economic stagnation over the first three decades of its formation, Kerala witnessed rapid economic growth since late-1980s. One of the important factors contributing to this economic turnaround was the high level of expenditures by the government on social sectors, public administration and welfare programme (GoK 2006; 2015). It has been argued that in order for Kerala to sustain its high growth performance, it is imperative to maintain high levels of public expenditure on these heads. However, this cannot be possible unless the revenue base of the government is widened. It is found that Kerala has been able to utilize only two third of it public revenue potential (GoK 2006). This situation calls for detailed studies to identify the gap between potential and realised public revenue sources and suggest measures to widen the revenue base. Apart from the need for sustaining government expenditure on social sector and welfare there are several other compelling reasons to strengthen public revenue mobilization in Kerala. First, Kerala has been facing several problems associated with the developed countries such as large and growing share of elderly population, higher level of educated unemployment, municipal waste management, and rapid environmental degradation, all due to its significant progress both on economic and human development front (George 2011). To tackle such problems the state needs to maintain fiscal stability, an important requirement of which is mobilisation of adequate public revenue. For instance, the growing graying population has added enormous pressure on government health infrastructure thereby requiring enhanced public expenditure on health services. 1

3 Second, the fiscal situation in Kerala is characterised by continuing high fiscal and revenue deficits which, in turn, has placed limits on government s budgetary priorities in favour of social sectors (George 2011). Concerted measures such as appropriate utilisation of revenue potential are therefore called for to correct the situation. Third, one of the important outcomes of the policies of economic liberalization followed in India since early 1990s is the some sort of independent status attained by the states in charting their economic growth trajectory. In contrast to the pattern of investment flows witnessed under the previous license-quota raj regime, where the direction and composition of investments across states were influenced by the policies and priorities of the central government, the post-economic reforms period has opened up the possibility of mobility of private investments, both domestic and foreign, between the states in pursuit of maximum returns (Ahluwalia 2000). 1 As a result, today the economic conditions and business environment at the state level play a very important role in attracting private investment to respective state jurisdiction. Since private investments exhibit the tendency to flow to those states that offer quality physical infrastructure such as road, water and power supply it is imperative that states mobilise adequate financial resources to shore up public investment in such critical areas. This is all the more important in Kerala because due to increased inter-state competition for private investment and weak physical infrastructure the inflow of private investment remains too small in Kerala (GoK 2015). Fourth, since early 1980s Kerala has been among the top three Indian states in terms of monthly per capita consumer expenditure (MPCE) (GoK 2015) and currently, as per National Sample Survey 68 th round ( ), the state is ranked first in MPCE in the rural area and 1 As Ahluwalia (2000) has pointed out, another important factor contributing to this scenario was the whittling down of the centre's ability to influence the direction and composition of private investment across states in the postliberalisation period. 2

4 second in the urban area. 2 Hence it is imperative to see whether this consumption boom, resulting mainly from large inflow of remittances, has benefited the state in terms of higher public revenues. In this context, the objective of this paper is to empirically estimate the effort taken by the state of Kerala in mobilizing a crucial source of public revenue namely taxes known as tax effort during the period, from a comparative perspective of other major Indian states. The paper is organised as follows. Section 2 provides a brief description on the economic and fiscal performance of Kerala. Section 3 delineates the methodology for computing tax capacity and tax effort and the data sources for the study. In Section 4, findings of the paper are presented. The summary and policy conclusion of the paper are provided in Section Kerala economy - Growth and Fiscal Performance: Kerala s economic growth trajectory since its formation in 1956 can be divided into three distinct phases: They are the (a) phase of economic stagnation ( to ), (b) phase of moderate economic growth ( to ) and (c) phase of accelerated economic growth ( to present) (GoK 2015). 3 Available growth analysis reveals that gross state domestic product (GSDP) of Kerala grew at the average annual rate of 1.12 per cent between and (GoK 2015). On the other hand, during the period to and to the same figure was 5.2 per cent and 8 per cent respectively (GoK 2015). Two factors have contributed to this remarkable turnaround in Kerala s economic growth from They are high level of public spending on the social sectors and large flow of remittances, in particular after 1991, and the resulting consumption boom. 2 See the data available in 3 Subrahmanian and Prasad (2008) through structural break analysis found that a significant break in Kerala s growth trajectory occurred in the late 1980s. 3

5 Despite the rapid economic growth achieved since the beginning of the last decade, Kerala economy today faces several challenges; chief among them is the deteriorating fiscal position of the state (George 2011, GoK 2015). 4 The fiscal edifice of Kerala has been diagnosed with several cracks. They mainly include continued high levels of fiscal and revenue deficits, low levels of public spending on capital works, utilisation of borrowed funds more to fund revenue expenditure, mounting debt liabilities, higher interest payment burden and falling own revenue mobilisation efforts (George and Krishnakumar 2012). Such a situation calls for serious reform efforts, both on expenditure and revenue side, to keep the fiscal house in order. On the revenue side, in the light of the rapid economic growth experienced during the last decade and top position in terms of MPCE, it can be safely argued that Kerala today has greater capacity to mobilise more public revenues than before through tax and non-tax sources and direct the same to fix its emerging development challenges highlighted earlier. Hence, it is important to examine how far Kerala was able to utilise its tax revenue potential emerging from the rapid economic growth since the beginning of the last decade. 3. Methodology and Data: In the literature several methodologies are available to empirically estimate tax effort of countries or sub-national governments. Major among them are per capita tax revenue, tax-gross Domestic Product (GDP) ratio, representative tax system (RTS) approach and regression method. Per capita tax revenue and tax-gdp ratio are the simplest definitions of tax effort. Large per capita tax revenue implies high tax effort and vice versa. In the case of tax-gdp ratio, GDP 4 The other major challenges are high unemployment rate for the educated; high dependence on external economy (other states and countries) for income in the form of remittances, employment and consumption needs; growing number of elderly population; environmental degradation; falling productive capacity of economy; rising economic inequality; and all challenges posed by rapid urbanization (GoK 2015, George 2011). 4

6 is considered as a proxy for taxable capacity and tax effort is measured by the share of tax revenue mobilised as a percentage of GDP. The larger the tax-gdp ratio the higher the tax effort and vice versa. Accordingly, countries or sub-national governments (hereafter governmental units) are ranked as per the values of tax-gdp obtained for each. Though tax-gdp ratio is the easiest method to measure tax effort, it suffers from two principle defects (Lotz and Morss 1967; Le et al 2012). First, this measure is not suitable for comparing tax effort of countries with varying economic structures, income levels demographic profile and institutional arrangements. For instance, countries with high levels of economic development and income have greater ability to collect taxes than otherwise. Second, the simple tax ratio does not take into account the influence of other social and economic factors in determining tax capacity of governments. The RTS approach of measuring tax effort involves four steps (Sobarzo 2004; Purohit 2006). In the first step, for each country (say i) and each tax revenue source (say j) an effective tax rate (ETR) is computed as the ratio between actual tax revenue collection from a given tax revenue source j and a sensible proxy measure of tax capacity (or) potential tax base value for tax source j. In the second step, an average effective tax rate (AETR) for tax revenue source j is calculated by summing the ETR of each country in which tax source j is utilised and dividing the sum by number of countries. This is regarded as representative tax rate. In the third step, the potential tax base value of source j for each country i is multiplied with the AETR computed in step two. This gives the absolute value of tax potential of country i with respect to tax source j, representing the amount of tax revenue country i would be able to mobilise from tax source j if it utilises its potential tax base to an average extent. In the fourth step, tax effort of each country is computed as the ratio between actual tax collection from tax source j and the absolute value of tax potential of each country with respect to tax source j (obtained in the third step). If the ratio is 5

7 more than one it implies that the country is making more than average effort to raise tax revenue and the opposite conclusion holds if the ratio is less than one. The two major shortcomings of RTS approach are (a) identifying an accurate measure of potential tax base for each individual tax source is a very demanding task; (b) like in the case of tax-gdp ratio measure of tax effort, RTS approach does not take into account the influence of broad socio-economic factors on tax potentials. The regression method of measuring tax effort is based the idea that tax performance of a governmental unit can be measured with more accuracy if the socio, economic and institutional characteristics of the governmental unit are taken into consideration for measuring its tax capacity. Accordingly, under the regression method, tax effort is measured as an index of the ratio between the actual tax revenue collection or tax-gdp ratio and the estimated taxable capacity or tax-gdp ratio (Le et al 2012). The estimated taxable capacity is nothing but the predicted tax revenue or tax-gdp ratio arrived from a regression model where tax revenue or tax-gdp ratio of a governmental unit is regressed on a set of social, economic and institutional characteristics associated with that governmental unit or tax handle. A tax effort index of more than one can be classified as high tax effort and less than one as low tax effort. A high tax effort implies that the concerned governmental unit makes good use of its tax base to mobilise tax revenues and low tax effort points to the fact that the governmental unit has substantial scope or potential to raise tax revenue. In the regression approach to measure tax effort, note that the tax performance of a governmental unit is judged against the average performance of its counterparts, after making due allowance for variations in socio, economic and institutional characteristics specific to each governmental unit. In this paper we employ regression method to estimate the tax effort of Kerala. Since 6

8 Kerala economy has gone through three varied growth phases, as explained above, it would be interesting to estimate the tax effort separately for the three phases and see whether the state was able to utilize its better growth performance overtime in terms of improving its tax effort. However, since the three phases of economic growth in Kerala may not coincide with similar growth phases of other Indian states, forcing a common set of periods across the states is inappropriate. Therefore, to identify a common period of analysis based on economic growth performance of the Indian states, we conducted a Chow structural breakpoint test in Net State Domestic Product (NSDP) (constant prices) of fourteen major Indian states for the period from. 5 It was found that for seven states namely Gujarat, Kerala, Madhya Pradesh, Maharashtra, Punjab, Tamil Nadu, and Uttar Pradesh, is the fiscal year which splits them into two statistically different economic growth regimes. Interestingly, this period closely coincides with the beginning of rapid economic growth in Kerala, as discussed in the background analysis in the previous section. Thus, based on structural break analysis, tax effort of Kerala was estimated for two separate periods namely and, and the whole period from and compared with tax efforts of other six major states namely Gujarat, Madhya Pradesh, Maharashtra, Punjab, Tamil Nadu, and Uttar Pradesh. Six individual taxes levied at the state level and states own tax revenue are taken up for tax effort analysis. The individual taxes are land revenue; stamp duty and registration fees; general sales tax excluding central sales tax; motor vehicles tax and passenger and goods tax; state excise duty; and electricity duty. A brief description of these tax sources are given in Table 1. As the estimation of taxable capacity under the regression methodology requires information on social and economic characteristics relevant for each tax and state, a set of variables 5 The states are Andhra Pradesh, Bihar, Gujarat, Haryana, Karnataka, Kerala, Madhya Pradesh, Maharashra, Orissa, Punjab, Rajasthan, Tamil Nadu, Uttar Pradesh, and West Bengal 7

9 representing such characteristic are identified for each tax and included in the regression analysis (see Table 2). Except share of agricultural NSDP in the states own tax revenue equation, all the other economic and social variables are expected to have a positive impact on the respective dependent variables. Since (a) it is relatively difficult to tax the agricultural income, (b) tax buoyancy in agricultural sector is low and (c) agriculture income has high tax exemption base (Garg et al 2014), it is expected that as the share of agricultural NSDP increases, states own tax collection drops. The data on tax revenues, per capita NSDP and sectoral composition of NSDP are collected from the India Time Series online data base published by EPW Research Foundation. State-wise information on population density and share of urban population in total population is compiled from Census of India. The data on number of registered motor vehicles, per capita power consumption and road density are obtained from the online data base namely Centre for Monitoring Indian Economy (CMIE) State Data Base. All monetary values are converted into prices using GDP deflator. The taxable capacity equations are estimated using the panel data methodology. All variables are expressed in logarithmic values in the estimation. 4. Taxable capacity and Tax effort: Empirical Results Table 3 reports the summary statistics for the study variables. Taxable capacity estimation results for each individual tax and states own tax revenues, using the specifications given in Table 2, are presented in Tables 4 to 10. The regressions capture the two sub-periods of and as well as the entire period of. As reported in Tables 4 to 10, for all the taxes, the estimated coefficients mostly have the expected signs and they are mostly statistically significant. The few exceptions are (a) incorrect sign for NSDP from agricultural sector variable in land revenue regression specification for the 8

10 period ; (b) insignificant coefficient for share of agricultural NSDP and road density variables in the own tax revenue regression specification for the period ; (c) unexpected sign for urban population share variable in the own tax revenue equation for. Tables 11 to 17 present tax effort index of the selected states for each tax category and ranking of the states according to their tax efforts. The tax effort index was measured based on the methodology described in the previous section. The following are the major findings from the tax effort analysis. Land Revenue: Except Kerala and Uttar Pradesh most states tax effort indexes are relatively stable over the sub-periods and. In case of Kerala, the tax effort index with respect to land revenue has increased dramatically from 0.79 in to 1.41 in. In the process, the state has moved from sixth rank to first. However, for the full period of study ( ) Kerala has the second lowest tax effort. The other states who have improved their land tax collection effort between the two sub-periods are Gujarat and Tamil Nadu. During the overall period Maharashtra has made maximum tax effort with respect to land revenue followed by Gujarat, Uttar Pradesh, and Madhya Pradesh. Stamp duty and registration fees: All the states under analysis were not able to tap the resources from this tax in all the periods of analysis. Kerala has the lowest tax effort scores in all the periods. Interestingly, the tax effort scores of all the states declined between and. During the period Uttar Pradesh ranked first, while Kerala ranked last. 9

11 Sales tax: The tax effort of all the study states with respect to sales tax has declined during the period compared to the period. Not only that during the whole period all the states have taken lower tax effort. In case of Kerala the drop in tax effort score was sharp from 1.01 to However, Kerala ranked second in all the periods of analysis. On the other hand, Uttar Pradesh recorded highest tax effort in all the periods. Motor vehicle tax and passengers and goods tax: Kerala is the only state which has made notable improvement in its effort to collect this tax during compared to to. 6 Consequently, the state s ranking has improved from sixth to fourth during the same period. However, during the whole period from to Kerala has got second lowest rank with Maharashtra topping the list. During this period the tax effort index was less than one for Kerala implying low tax effort. Except Uttar Pradesh and Maharashtra, tax effort indexes of all the other states remained more or less the same between the periods to and. State excise duty: Though Kerala has increased its effort in collecting this tax during compared to, the state has the lowest tax effort in all the periods of analysis. In fact, despite the improvement in the tax effort of all the states during period, their actual state excise tax revenues are much lower than taxable capacity in all the periods of analysis. The state of Uttar Pradesh ranked first in all the periods. Electricity duty: Kerala lowered its tax effort with respect to this tax after 2000 and it is the only state to experience such a trend. The state s ranking also dropped to the bottom of the list during compared to fifth position during. In the whole period as well, Kerala has the lowest tax effort (0.79). Madhya Pradesh and Maharashtra 6 Since data on number of motor vehicles is available only from , the analysis for motor vehicle tax and passengers and goods tax covers the period from

12 has made maximum tax efforts in all the periods of analysis followed by Gujarat. Own tax revenue: Kerala s overall tax effort increased from 0.64 to 0.80 between to and. However, during both the periods Kerala recorded the lowest tax effort. The same is the trend in the whole period of analysis. Uttar Pradesh ranked first in all the periods. One notable finding is that none of the states have not been able to fully utilize own tax revenue capacity though they have increased their tax effort between and. 5. Summary and Conclusions In estimating the tax effort of Kerala in relation to selected other states during the period, this paper adopts regression method. Using this method we computed tax effort as an index of the ratio between the actual tax revenue collection and the estimated taxable capacity from a regression model. Since Kerala s economic growth performance has improved over the years, in order to identify whether the state was able to increase its tax effort in accordance with better growth performance overtime, using structural break-analysis, we divided the study period into two sub-periods namely and. Of these the second period represents acceleration in the economic growth of Kerala as well as other study states namely Gujarat, Madhya Pradesh, Maharashtra, Punjab, Tamil Nadu, and Uttar Pradesh. Tax efforts with respect to six individual state-level taxes namely land revenue; stamp duty and registration fees; general sales tax excluding central sales tax; motor vehicles tax and passenger and goods tax; state excise duty, and electricity duty as well as states own tax revenue was calculated. The results of the study show that whereas Kerala has increased its tax effort with respect to land revenue, motor vehicle tax and passengers and goods tax, state excise duty and own tax 11

13 revenue during the period of rapid economic growth from , in case of stamp duty and registration fees, sales tax and electricity duty the state has lowered its tax effort. The sharp drop in the tax effort with respect to sales tax, the major tax revenue source of the states, is cause for serious concern. The ranking of Kerala based on the effort taken to collect stamp duty and registration fees, excise duty and own tax revenue was the lowest among all the seven states during all the periods of analysis. In case of electricity duty, the state s ranking slipped from fifth in to bottom in. Only in the case of land revenue and motor vehicle tax and passenger and goods tax, Kerala s ranking of tax effort improved over the years. Also, the state has the second highest tax effort index for sales tax consistently over the years. The findings of the study reveal that though, on its own, Kerala has improved its tax effort with respect to majority of the tax handles during the period of rapid economic growth, the sharp fall in the tax effort index of the most important tax source namely sales tax after is alarming. Such a trend is difficult to reconcile with the fact that Kerala ranks first among all the Indian states in terms of monthly per capita consumer expenditure. Another concern emerging from the study is the lowest ranking Kerala earned with respect to many taxes when compared to other states. This clearly points out that relative to other comparable states Kerala is placed far behind in tax effort, particularly considering its better economic status, and hence the state has to focus on improving its actual tax revenue on par with higher ranked states. 12

14 Table 1: Description of Individual Taxes Tax Land revenue Stamp duty and registration fees General sales tax Motor vehicle tax and passenger and goods tax Description Includes land tax, cesses on land tax, special crop cesses, and surcharge and betterment levy. Individual tax liability depends on the size of landholdings and land productivity Paid on the transfer or registration of movable and immovable financial instruments or deeds relating to financial transactions. Tax base is the value of financial instruments transacted Levied on sales and/or purchase of goods or commodities within a state. Motor vehicle tax is imposed on the registration of new motor vehicles; transfer of ownership of vehicles; issuance of trade certificates to vehicle manufacturers and dealers; issuance of vehicle fitness certificates; and for obtaining driving licence State excise duty Electricity duty Own tax revenue Source: Purohit (2006) Passenger and goods tax is levied on the movement of goods and persons from one place to another. It is either collected as a percentage of the gross revenues of transport companies from passenger fares and goods freight or as a lump sum tax calculated on the basis of the seating capacity of the vehicles and route length Though technically defined as a levy alcoholic liquors for human consumption and opium, Indian hemp and other narcotic drugs and narcotics, but not including medicinal and toilet preparations containing alcohol in practice revenue from this tax comes mainly from production and consumption of alcoholic liquor Levied on the consumption of electricity in each state Refers to revenue from all the taxes that states are entitled to levy within their territory as per Constitutional provision of sharing of tax handles between the central and state governments 13

15 Table 2: Variables used in Panel Regression Specifications for Estimating Tax Capacity Tax Dependent variable Independent variables Land revenue Revenue from land revenue Net state domestic product (NSDP) from agricultural sector Stamp duty and registration fees General sales tax Revenue from stamp duty and registration fees Revenue from general sales tax excluding central sales tax NSDP from construction and real estate; percentage of urban population to total population; and population density per square km Share of NSDP from manufacturing sector; percentage of urban population to total population Motor vehicle tax and passenger and goods tax Revenue from motor vehicle tad and passenger and goods tax Number of registered motor vehicles State excise duty Revenue from excise duty Per capita NSDP Electricity duty Revenue from electricity duty Per capita power consumption Own tax revenue Revenue from own tax revenue Per capita NSDP; share of NSDP from agricultural sector; percentage of urban population to total population; and road density Table 3: Descriptive Statistics, averages over Variable Mean Standard Deviation Minimum Maximum Count NSDP from Agricultural Sector NSDP from construction and real estate Percentage of urban population to total population Population density per square km Share of manufacturing NSDP Per capita Power Consumption Per capita NSDP Share of agricultural NSDP Road density Number of Registered Motor Vehicles

16 Table 4: Determinants of Taxable Capacity - Land Revenue Dependent Variable: : Ln Land revenue Constant *** *** *** (5.24) (-8.34) (-3.95) Ln NSDP from Agricultural Sector ** *** *** (-2.53) (9.65) (7.48) R-squared Hausman Test Statistics No of Observations Model Random effects Random effects Random effects Note: t statistics are in parentheses. *** indicates significant at 1% level; ** indicates significant at 5% level and * indicates significant at 10% level Table 5: Determinants of Taxable Capacity - Stamp Duty and Registration Fees Dependent Variable: : Ln Revenue from Stamp Duty and Registration fees Ln NSDP from construction and real estate **.24971*** (1.02) (2.1) (6.55) Ln Percentage of urban population to total population *** *** *** (11.89) (3.63) (19.68) Ln Population density per square km *** *** *** (20.72) (3.86) (22.7) R-squared Hausman Test Statistics No of Observations Model Fixed Effects Fixed Effects Fixed Effects Note: Same as Table 4 15

17 Table 6: Determinants of Taxable Capacity - Sales Tax Dependent Variable: : Ln Revenue from General Sales tax excluding Central Sales tax Ln Share of manufacturing NSDP *** *** *** (10.85) (4.03) (7.52) Ln Percentage of urban population to total population *** *** *** (5.38) (8.42) (17.66) R-squared Hausman Test Statistics No of Observations Model Fixed Effects Fixed Effects Fixed Effects Note: Same as Table 4 Table 7: Determinants of Taxable Capacity - Motor Vehicles Tax Dependent Variable: : Ln Revenue from Motor Vehicles Tax and Passenger and Goods Tax to to Constant *** *** * (4.34) (-7.02) (-1.95) Ln Number of Registered Motor Vehicles.34387***.73321*** *** (17.5) (17.96) (36.62) R-squared Hausman Test Statistics No of Observations Model Random Effects Random Effects Random Effects Note: Same as Table 4 16

18 Table 8: Determinants of Taxable Capacity - Excise Duty Dependent Variable: : Ln Revenue from State Excise Duty Ln Per capita NSDP *** *** *** R-squared Hausman Test Statistics No of Observations Model Fixed Effects Fixed Effects Fixed Effects Note: Same as Table 4 Table 9: Determinants of Taxable Capacity - Electricity Duty Dependent Variable: : Ln Revenue from Electricity Duty Constant (-0.56) (-1.04) (-0.57) Ln Per capita Power Consumption.95693*** ***.95407*** (12.35) (3.85) (14.89) R-squared Hausman Test Statistics No of Observations Model Random Effects Random Effects Random Effects Note: Same as Table 4 17

19 Table 10: Determinants of Taxable Capacity - States Own Tax Revenue Dependent Variable: : Ln States Own Tax Revenue Ln Per capita NSDP *** ***.98313*** (13.34) (15.61) (14.95) Ln Share of agricultural NSDP *** *** (-6.49) (-1.57) (-3.73) Ln Percentage of urban population to total population.29684*** *.29750*** (3.32) (-1.76) (3.76) Ln Road density.55156*** *** (9.34) (1.66) (14.03) R-squared Hausman Test Statistics No of Observations Model Fixed Effects Fixed Effects Fixed Effects Note: Same as Table 4 Table 11 : Index of Tax Effort - Land Revenue State Index Rank Index Rank Index Rank Gujarat Kerala Madhya Pradesh Maharashtra Punjab Tamil Nadu Uttar Pradesh

20 Table 12 : Index of Tax Effort - Stamp Duty and Registration Fees State Index Rank Index Rank Index Rank Gujarat Kerala Madhya Pradesh Maharashtra Punjab Tamil Nadu Uttar Pradesh Table 13 : Index of Tax Effort - Sales Tax State Index Rank Index Rank Index Rank Gujarat Kerala Madhya Pradesh Maharashtra Punjab Tamil Nadu Uttar Pradesh Table 14 : Index of Tax Effort - Motor Vehicles Tax and Passenger and Goods Tax State to to Index Rank Index Rank Index Rank Gujarat Kerala Madhya Pradesh Maharashtra Punjab Tamil Nadu Uttar Pradesh

21 Table 15 : Index of Tax Effort - State Excise Duty State Index Rank Index Rank Index Rank Kerala Madhya Pradesh Maharashtra Punjab Tamil Nadu Uttar Pradesh Table 16 : Index of Tax Effort - Electricity Duty State Index Rank Index Rank Index Rank Gujarat Kerala Madhya Pradesh Maharashtra Punjab Tamil Nadu Uttar Pradesh Table 17 : Index of Tax Effort - States Own Tax Revenue State Index Rank Index Rank Index Rank Gujarat Kerala Madhya Pradesh Maharashtra Punjab Tamil Nadu Uttar Pradesh

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