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SPECIAL ARTICLE

Economic & Political Weekly EPW march 10, 2012 vol xlvii no 10 55

This is an extensively revised and extended version of “A Preliminary

Evaluation of the Revenue Impact of the State Level VAT in India”

co-authored with Joy Chowdhury presented at the National Institute of

Public Finance and Policy, New Delhi in March 2011. For this paper data

have been corrected and updated, and the analysis has been altered

drawing largely on comments received from seminar part icipants.

Their suggestions are gratefully acknowledged individually where

appropriate. Thanks are due to Fernanda Andrade for excellent research

assistance. The usual disclaimers apply.

Arindam Das-Gupta ([email protected]) is at the Centre for Economic

Research, Goa Institute of Management, Goa.

An Assessment of the Revenue Impactof State-Level VAT in India

Arindam Das-Gupta

Revenue and GSDP data for 29 states for 1993-94 to

2008-09 are used to study the revenue performance of

the state value added tax in India. The direct revenue

impact was assessed by testing if VAT introduction

increased VAT or state’s own revenue buoyancies or the

VAT or SOR to GSDP ratios. The indirect impact of VAT

introduction on the VAT base (proxied by GSDP) and base

growth were also examined. No indirect impacts of the

VAT on its base was found. The direct revenue impact of

the VAT was found to be positive in two-thirds of sample

jurisdictions. A positive impact on SOR was however

found only in Orissa and Haryana among 11 major states

and 50% of other jurisdictions.

Limited VAT revenue performance can partly be traced

to large-scale evasion given weaknesses in VAT

administration identified in a 2009 performance audit

by the Comptroller and Auditor General. The

implications of this study for the planned move to a

goods and services VAT (from the current goods only VAT)

are drawn and a suggestion is made for a non-VAT

goods and services tax which should be less vulnerable

to tax evasion.

Introduction and Motivation

The revenue performance of the state-level value added

tax ( VAT) in India relative to the turnover-type sales

taxes it replaced is assessed here. Besides being the first

econometric assessment of sub-national VAT revenue perform-

ance, this assessment may serve as a benchmark for the pro-

posed national and state Goods and Services Tax (GST). Bar-

ring further consensus building or implementation problems,

the GST is to replace several central and state levies, includingthe central and state VATs over the next few years.

In developing countries the VAT is the consumption tax of

choice of most applied public economists.1 However, Stiglitz

and Dasgupta (1971) identified conditions under which VAT-

like exemption of productive intermediate inputs would not

ensure economic efficiency. Some recent theoretical papers on

the VAT also found it wanting when imperfect markets or

informal sectors exist in the economy.2 On the other hand by

granting input tax credits (ITC), the base of the VAT is narrower

than a consumption tax without ITC, thus violating a widely

accepted rule of thumb for practical design of general taxes,

broad bases permitting low tax rates.3 One justification for this

violation is that opposed interests of input suppliers (who ben-efit from evasion of VAT on their output) and buyers (who

would like to claim ITC) make the VAT partly “self-enforcing”.4

Whatever its merits or drawbacks, the VAT is now imple-

mented in at least 138 nations.5 In at least three of them

(Brazil, India and Quebec province of Canada) a sub-national

VAT is also in place. The empirical assessments of the revenue

impact of the VAT in Ebrill et al (2001) and also in Keen and

Table 1: Revenue Gain from VAT Adoption Region (% of GDP)

Region Ebrill et al (2001) Keen and Lockwood (2007)3, 4

Average Gain Number of: Average Gain (%)

over Predecessor Countries Gaining

Sales Tax (% of GDP)2, 4 Revenue from

the VAT (Countries

Losing Revenue)Sub-Saharan Africa 1.10 11 (14) -0.81

Asia and Pacific 0.70 19 (3) 2.10

Americas 1.42 14 (9) 0.51

Central Europe and BRO1 -1.88 Not studied Not studied

EU (plus Norway and Switzerland) 1.05 17(0) 4.15

North Africa and west Asia 0.10 3 (2) 0.45

Small Islands 1.96 8 (0) 4.03

(1) BRO: Baltic states, Russia and other states of the former Soviet Union.

(2) Figures based on IMF staff calculations.

(3) Illustrative calculations by the authors based on their equation 4 (of 7 equations) estimated

with panel data for 143 countries having at least 10 years of data between 1975 and 2000.The

authors also estimate predicted revenue gain from VAT adoption for countries not having a VAT.

(4) Revenue variables: Ebrill e t al (2001): VAT to GDP ratio over pre decessor sale s tax to GDP

ratio. Keen and Lockwood (2007): tax-GDP ratio pre- and post-VAT.



SPECIAL ARTICLE

march 10, 2012 vol xlvii no 10 EPW Economic & Political Weekly56

Lockwood (2006, 2007) were limited to national level VATs. So

an assessment of the VAT in India, which has had VATs on goods

at both national and sub-national levels for around six years, is

of interest. The revenue performance of the VAT reported in

Ebrill et al and in Keen and Lockwood (2007) are reproduced

in Table 1 (p 55).6 Clearly revenue gain from VAT adoption,

while fairly widespread, were not universal.

As Ebrill et al (2001) point out, these results need not reflect

poor VAT revenue potential. First, many countries intended a

revenue neutral replacement of their earlier consumption

taxes by the VAT, as in the Indian states. Second, design differ-

ences in VATs in different countries cause them to depart in

various ways from a textbook VAT, again as in the states. Third,

if the VAT causes less economic distortion than the tax it

replaces, this may lead to VAT base (proxied by GDP) gains,

increasing the denominator in Table 1’s revenue ratios. The VAT

fails on revenue grounds only if both the direct revenue impact

plus its indirect impact on the VAT base are negative.

Note that revenue is not the only performance criterion.

Administrative and cost efficiency, predictability, simplicity,impact on economic efficiency, evasion proneness, equity and

economic welfare as a whole are other important evaluation

criteria. Of these, only administrative efficiency and evasion

proneness are partly addressed below.

After describing Indian state VAT design features, modelling and

data issues are discussed, followed by the presentation of em-

pirical results. Two robustness tests of the main empirical find-

ings and a review of a recent performance audit by the Comp-

troller and Auditor General (CAG) in 2010 are then presented.

Policy suggestions based on the analysis conclude the paper.

The VAT in Indian States

Starting with Haryana and ending with Uttar Pradesh, between 2003-04 and 2007-08 VATs on goods were implemented

in all Indian states and several union territories.7 Implementa-

tion dates for the 29 states are in Table 2.

Though VAT designs differ across states, among major

widely prevailing design differences compared to a destina-

tion based consumption-type VAT are:8

• The continuing origin-based central sales tax (CST) on inter-

state sales.

• No VAT on imports from abroad.

• Thresholds (differing across states) for registration of VAT

dealers. Also in some states a simplified tax regime without

input crediting for dealers below the VAT threshold but above

a floor turnover.

• Exclusion of certain goods including basic necessities, petro-

leum, oil and lubricants from the VAT.

• Limits on VAT crediting for inputs and capital goods, and

disallowance or carry forward of refunds in excess of tax paid

on sales except for exports.

Consequently commodity taxes in the states continue to be

partly origin based, tax intermediate inputs, and result in dif-

ferential cascading across both goods and services. Even so,

there are fewer design differences across the states than, for

example, in the cross-country studies cited above. Further-

more, in India it is likely that the VAT was introduced to, inter

alia, improve revenue but indirectly by reducing economic dis-

tortions and increasing the tax base.9

Data and Modelling Issues

To assess the revenue impact of the state VAT, the (a) gross

state domestic product (GSDP) buoyancy of sales taxes (ST),

and (b) the revenue to GSDP ratio, before and after VAT are ex-

amined. GDP (here GSDP) is the standard proxy for the base of

general consumption taxes in most revenue performance stud-ies. Two issues are examined. First, has the VAT done better

than the sales tax it replaced? Second, has the VAT contributed

to an improved own revenue performance? The latter is not

assured if VAT gains are eroded by losses from other revenue

sources, unintended or intended.10

For the first question two equations, ST revenue pre- and

post VAT implementation were compared:

LNSTt = B0 + B1LNGt + B2(VATt.LNGt) ...(1)

(ST/G)t = B

0 + B

1 VAT

t ...(2)

In (1) LN prefixed to a variable name denotes its natural log-

arithm, GSDP t is abbreviated to G

t and the t is an annual time

period subscript ranging from 1993-94 to 2008-09. VAT t is a

dummy variable taking the value 1 for years in which the VAT prevailed and zero otherwise. Thus VAT

t.LNG

t is a slope dummy

variable. An increased coefficient of the VAT dummy in the

buoyancy equation (1) is consistent with higher secular reve-

nue productivity of the VAT compared to the earlier sales tax.

An increase only in the VAT /GSDP ratio may reflect a one time

increase in revenues due to the VAT, with no trend impact.

For the second question, the same two equations but with

state’s own revenue receipts (SORR ) replacing ST are estimated:

LNSORR t = B0 + B1LNGt + B2(VATt.LNGt), ...(3)

(SORR/G)t = B

0 + B

1 VAT

t ...(4)

An alternative to equations (1) and (3) with lagged Gt-1

replac-

ing current Gt, (equations 1a and 3a) is also reported.11

A fifth equation was estimated to check if, even if there was

no revenue increase, the VAT at least contributed a larger share

of state revenue:12

(ST/SORR)t = B0 + B1 VATt ...(5)

These models do not include other possible determinants of

revenue performance. Keen and Lockwood (2007), for example,

estimate pooled regressions and so include additional “tax

effort” determinants including a per capita income variable, a

trade openness variable and the share of agriculture in GDP.

These variables, which will vary little over the sample period

in Indian states, are unlikely to contribute to the explanatory

Table 2: Dates of VAT Implementation by States in India

Haryana 1st Apr 2003

Andhra Pradesh, Bihar, Haryana, Karnataka, Kerala, Maharashtra,Orissa, Punjab, West Bengal, Arunachal Pradesh, Assam,Himachal Pradesh, Goa, Jammu and Kashmir, Manipur,Meghalaya, Mizoram, Nagaland, NCT New Delhi, Sikkim, Tripura 1st Apr 2005

Uttarakhand 1st Oct 2005

Chhattisgarh, Madhya Pradesh, Gujarat, Rajasthan, Jharkhand 1st Apr 2006

Tamil Nadu 1st Jan 2007

Uttar Pradesh 1st Jan 2008

Source: Halakhan di (2007) except Tamil Nadu: Government of Tamil Nadu (no date), and

Uttar Pradesh: CA.inINDIA.Org (2011).



SPECIAL ARTICLE


Table 3: VAT Dummy Variable Signs a nd Significance s for Equations (1) to (5)

State ST GSDP ST Lagged ST/GSDP SORR GSDP SORR SORR/GSDP ST/SORR

Buoyancy GSDP Buoyancy (Eq 2) Buoyancy Lagged GSDP (Eq 4) (Eq 5)

(Eq 1) (Eq 1a) (Eq 3) Buoyancy

(Eq 3a)

Major states

Andhra Pradesh (AP) 0.000 0.003 0.004* 0.004 0.005 0.008 -0.003

Gujarat (Guj) 0.011* 0.011* -0.0 02 0.003 0.004 -0.015* 0.236*

Haryana (Har) 0.004 0.007 0.010* 0.019* 0.027* -0.023 0.142*

Karnataka (Kar) 0.008* 0.012* 0.001 0.008 0.013 0.010 -0.032

Kerala (Ker) -0.005* 0.000 0.003 0.002 0.007 0.003 0.01

Maharashtra (Mah) -0.004 0.002 0.001 0.001 0.006 0.003 -0.006

Orissa (Ori) 0.008 0.010 0.008* 0.011 0.014 0.017* 0.000

Punjab (Pun) 0.001 0.005 0.005* -0.005 0.004 -0.002 0.056*

Rajasthan (Raj) 0.004 0.009 0.008* 0.010 0.015* 0.005 0.067*

West Bengal (WB) 0.007* 0.011* 0.001 0.007 0.01 0.004 -0.025

Tamil Nadu (TN) 0.000 0.002 -0.008* 0.005 0.007 -0.008 -0.039*

Non-major states

Arunachal Pradesh (ArP) 0.007 -0.032 0.013* 0.077* 0.074* 0.074* 0.082*

Assam (Asm) 0.007 0.005 0.015* 0.013* 0.011* 0.025* 0.047

Himachal Pradesh (HP) 0.022* 0.024* 0.013* 0.024* 0.027 0.035* 0.034

Goa 0.018* 0.019* -0.014 -0.007 -0.003 -0.073* 0.065

Jammu and Kashmir (JK) 0.023* 0.019* 0.022* 0.014* 0.012 0.029* 0.166*

Manipur (Man) 0.029 0.018 0.007* 0.05* 0.053* 0.012* 0.215*

Meghalaya Meg) 0.019* 0.023* 0.01* 0.011 0.015 0.008* 0.138*

Mizoram (Miz) 0.026 0.015 0.011* 0.05* 0.051* 0.008 0.168*

Nagaland (Nag) 0.020* 0.018 0.005* 0.024* 0.028 0.005 0.098*

Sikkim (Sik) -0.020* -0.022 0.013* -0.041 0.004 -0.301 0.021

Tripura (Tri) 0.010 0.007 0.008* -0.008 -0.011 0.004 0.177

NCT Delhi (ND) -0.010 0.007 0.006 -0.011 0.007 0.014 -0.038*

of which combined states

Bihar+Jharkhand (BJ) 0.001 0.001 -0.002 0.007 0.005 -0.001 -0.021

Madhya Pradesh+

Chhattisgarh (MPC) 0.003 0.007 0.00 6* 0.001 0.004 0.007 0.039*

Uttar Pradesh+

Uttarakhand (UPU) 0.008* 0.013* 0.007* 0.017* 0.020* 0.012 0.01

(1) *: Significant at 95% or better. P-values are reported in the Appendix.

(2) Of the combined states, Bihar, Madhya Pradesh and Uttar Pradesh are major states.

power of the time series models analysed here. Furthermore

trade openness data are not available for Indian states.13 How-

ever, as in other Indian studies, states are classified as major

states and non-major states, the latter including the 10 special

category states. Special category states are officially held to

suffer from poor infrastructure, difficult terrain and in most

cases large tribal populations.14

The equations above neglect the indirect impact, if any, of

VAT introduction on the VAT base. To assess this, two more equa-

tions were estimated using pooled data for the jurisdictions

studied. The reason for data pooling was to take into account

possible cross-state economic spillovers on the VAT base.15 Using

the subscript j for the jth state, the estimated equations were:

LNGSDP jt

= Bo + B

1 VAT

jt + B

2Time

t + B

3State

j, ...(6)

ΔLNGSDP jt = Bo + B1 VAT jt + B2Timet + B3State j. ...(7)

There is little alternative to the admittedly weak methodo-

logy of using a VAT dummy variable to assess the impact of the

VAT. This methodology, with all its problems, is also used in ear-

lier VAT impact studies including Ebrill et al (2001) and Keen and

Lockwood (2006, 2007).16

However, this implies that differ-ences between VAT and pre- VAT periods rather than the impact

of the VAT are being studied. The technique cannot distinguish

between the VAT’s impact and the impact of other tax and fiscal

reforms during the period. For this detailed, state by state,

inquiries on the quality of VAT implementation

and also other reforms are needed. The quality of

VAT implementation is partly examined below by

drawing on a VAT performance audit.17 Two

other statistical exercises to check the robust-

ness of the basic results were carried out.

Current rupee data on GSDP, ST and SORR

are used for all 29 Indian states (clubbed into

26 jurisdictions as explained below) for 2003-04 to 2008-09. ST and SORR data were from

the website of the Reserve Bank of India (RBI)

and GSDP data were from the website of the

Ministry of Statistics and Programme Imple-

mentation (MOSPI).18 Four data problems and

the manner in which they were dealt with are

now described.

(a) Chhattisgarh, Jharkhand, and Uttarakhand

were carved respectively out of Madhya Pradesh,

Bihar and Uttar Pradesh in 2000. So com-

bined data for Bihar-Jharkhand (BJ), Madhya

Pradesh-Chhattisgarh (MPC), and Uttar Pradesh-

Uttarakhand (UPU) were used. This reduced

the number of jurisdictions to 26 instead of 29.

Since differences could arise after the split, an

additional dummy variable term, B3Split

t, was

added to equations (1) to (5) for these states,

with Splitt equalling one from the year of the

split (2000 in all three cases) and zero before

that. Furthermore, in BJ and UPU, Bihar and

Uttarakhand implemented the VAT before

their sibling states (Table 2). So additional

dummy variable terms, B4VAT 1

t , were added

for BJ and UPU in all equations. VAT 1t equals 1 for years in

which only one sibling state had the VAT and zero otherwise.

(b) Data for two states, Jammu and Kashmir and Karnataka

were only available to 2007-08.

(c) Tamil Nadu and Uttarakhand (then Uttaranchal) imple-

mented the VAT mid-year rather than on 1 April. A dummy

variable for mid-year implementation was tried but, being in-

significant, was dropped from the regressions reported here.

(d) GSDP data were from three different series: 1993-94, 1999-

2000 and 2004-05. A chained GSDP series was, estimated by

projecting the ratio of overlapping years of these series back-

ward using a linear projection equation fitted by ordinary least

squares. The resulting chained series thus has GSDP even for

years before 2004-05 to the base year 2004-05. Equations (1) to

(4) were estimated with both chained and unchained GSDP

series. With unchained GSDP data, VAT revenue performance

turns out to be worse than with chained GSDP. So only chained

series results are reported in the main text. Differences with

unchained GSDP series are footnoted.

Empirical Results

In Table 3, VAT dummy coefficients and their significances are

summarised from the detailed Appendix Tables A1 to A7 (pp 61-64).

Table 4 (p 58) reports the mean values of the GSDP and SORR



SPECIAL ARTICLE


Table 4: Buoyancies and Mean Values of Ratios

State ST GSDP ST Lagged ST/GSDP SORR GSDP SORR SORR/GSDP ST/SORR

Buoyancy GSDP Buoyancy (Eq 2) Buoyancy Lagged (Eq 4) (Eq 5)

(Eq 1) (Eq 1a) (Eq 3) GSDP

Buoyancy

(Eq 3a)

Major statesAndhra Pradesh 1.085 1.057 0.047 1.013 1.029 0.091 0.520

Gujarat 0.797 0.797 0.047 0.799 0.791 0.094 0.510

Hary ana 1.147 1.128 0.039 0.548 0.421 0.127 0.388

Karnataka 0.894 0.858 0.050 0.959 0.917 0.104 0.472

Kerala 1.154 1.073 0.051 1.005 0.931 0.080 0.643

Maharashtra 1.095 1.034 0.040 1.015 0.958 0.082 0.484

Orissa 1.117 1.119 0.027 1.061 1.062 0.062 0.440

Punjab 1.166 1.156 0.033 1.079 0.935 0.108 0.320

Rajasthan 1.171 1.141 0.032 0.893 0.836 0.082 0.401

West Bengal 0.894 0. 835 0.026 0.959 0.907 0.047 0.543

Tamil Nadu 0.875 0.835 0.062 0.865 0.826 0.105 0.580

Non-major statesArunachal Pradesh 4.510 5.476 0.003 0.856 0.984 0.050 0.080

Assam 1.467 1.53 0.025 1.214 1.294 0.054 0.475

Himachal Pradesh 1.288 1.267 0.017 1.103 1.052 0.064 0.284

Goa 0.643 0.607 0.064 0.756 0.673 0.203 0.335

Jammu and Kashmir 1.700 1.75 0.017 1.297 1.299 0.055 0.329

Manipur 1.353 1.519 0.009 0.634 0.561 0.033 0.304

Meghalaya 1.310 1.258 0.015 1.017 0.958 0.047 0.347

Mizoram 1.992 2.155 0.005 0.581 0.573 0.049 0.151

Nagaland 1.261 1.266 0.009 0.789 0.671 0.031 0.311

Sikkim 1.811 1.854 0.020 1.271 0.501 0.869 0.042

Tripura 1.372 1.349 0.014 1.223 1.212 0.037 0.412

New Delhi 1.294 0.974 0.047 1.367 1.029 0.071 0.655

of which combined statesBihar+Jhark hand 0.887 1.015 0.028 0.821 0.975 0.059 0.478

Madhya Pradesh+Chhatt isgarh 1.232 1.315 0.026 1.128 1.198 0.079 0.347

Uttar Pradesh+Uttarakhand 1.077 1.018 0.029 0.812 0.792 0.064 0.458

Averages major states 1.036 1.003 0.041 0.927 0.874 0.089 0.482

All states 1.330 1.361 0.030 0.964 0.899 0.106 0.396All buoyancies are significant at 99%: See Tables A1, A2, A4 and A5.

ratios and also the buoyancies to help interpretation of Table 3.19

State by state narrative assessments are in Table 5 (p 59).

Results for three states are difficult to interpret. In Andhra

Pradesh the three ratios in the table appear mutually contradic-

tory. They are, in any case, small. In Arunachal Pradesh, sales

tax/ VAT revenue grew 15,000% (in nominal terms) over the

sample period while SORR grew by 1,000% or over twice as

much as GSDP. Clearly, these gains cannot be attributed to VAT

introduction alone. In Sikkim ratios and buoyancies appear to

be mutually contradictory. In any case VAT appears to have no

impact on revenue performance in Sikkim, the negative VAT

buoyancy and ST /SORR may contradict this, implying question-

able results. Leaving aside these states, Table 5 suggests that VAT

revenue performance was positive in 15 of the remaining 23 ju-

risdictions including in six of 10 major states (excluding AP). Of

these, in Karnataka, Kerala and UPU revenue gains were small.20

Own revenue performance after VAT introduction improved

in only two major states (Haryana and Orissa) and seven non-

major states. Overall, even if VAT performance was positive in

two-thirds of the states, improved own revenue performance

after VAT introduction occurred in less than 40% of jurisdic-

tions including only two major states.21

The last column of Table 3 shows that the

share of ST in SORR increased in only 11 states

(excluding Arunachal), including four major

states, after VAT introduction and reduced in

one major and one non-major state. So reliance

on sales taxes did not increase in the majority

of states after the VAT reform.

On the indirect impact of VAT introduction,

coefficients of VAT dummies in pooled regres-

sions with LNGSDP and the GSDP growth rate

in Table 6 (p 59) are uniformly insignificant.

The conclusion is that VAT introduction did

not lead to any base expansion.22 So the direct

revenue impact of the VAT is also the total

revenue impact.23

Robustness Checks

Given the questionable data, especially for

GSDP, and methodological weakness, two

robustness checks are now presented. Fur-ther, in the next section findings of the per-

formance audit (CAG 2010), which also tend to

suggest negative or weak VAT revenue per-

formance are presented.

States Gaming the Centre: The centre agreed

to compensate states implementing the VAT in

2005 for any revenue loss in the initial years

relative to sales tax revenue in 2004-05. The

compensation would equal 100%, 75% and

50% of the revenue loss in the first, second

and third years of the VAT, respectively. Could

this have led to higher than normal state taxeffort in 2004-05 followed possibly by lower

than normal tax effort particularly in 2005-06?24 If so VAT

dummy coefficient estimates reported above would be biased

downward and could turn insignificant.25 To examine this aug-

mented versions of equations (1) and (2), equations (1b) and (2b)

were estimated for the 21 states which implemented the VAT in

2005. The additional variables included were dummy variables

for 2004-05 (Pre VAT) and 2005-06 (Post VAT). These were slope

dummies in (1b) and intercept dummies in (2b). The hypothesis

is confirmed if Pre VAT is positive and significant and, perhaps,

Post VAT is negative and significant. Results are summarised in

Table 7 (p 59). Further detail is in Tables A8 and A9 (p 64).

For both equations the first of the four columns for each

equation reports VAT dummy signs and significances from Table 3.

In equations (1b) and (2b) Pre VAT is positive and significant in

two and five states, respectively. In no case is Post VAT significant.

However, Pre VAT /Post VAT have the expected positive/negative

sign pattern in eight cases in (1b) and 10 cases in (2b). Thus the

hypothesis of gaming has weak support. What of VAT dummy

coefficients? In fact addition of Pre VAT and Post VAT robs some

VAT dummy coefficients (including two negative coefficients)

of their significance. In no case does addition of these dum-

mies cause an insignificant VAT dummy to become significant



SPECIAL ARTICLE


Table 5: Impact of VAT Introduction on Sales Tax and State's Own Revenues:State by State Assessment

State Assessment

Major states

Andhra Pradesh See discussion in the text

Gujarat VAT not a success but other revenue sources performed

even worse.

Haryana Improved revenue performance including of the VAT.

Karnataka VAT had no impact on revenue performance in Karnataka.

ST buoyancy improved but by under 1%.

Kerala VAT had no impact on revenue performance in Kerala. ST

buoyancy worsened but by under 1%.

Maharashtra VAT appears to have had no impact on revenue

performance in Maharashtra.

Orissa ST/GSDP and SORR/GSDP dummy coefficients are both

large relative to the mean. Suggests improved revenueperformance including of the VAT.

Punjab From ST/SORR and ST/GSDP, VAT was successful.

Other revenue sources eroded VAT gains.

Rajasthan From ST/SORR and ST/GSDP, VAT was successful.

Other revenue sources eroded VAT gains.

West Bengal VAT had no impact on revenue performance. ST buoyancy

improved but by under 1% leaving it below unit y.

Tamil Nadu VAT performance was worse than the sales tax it replaced,

but overall revenue performance is unchanged.

Non-major statesArunachal Pradesh See discussion in the text

Assam Improved revenue performance including of the VAT.

Himachal Pradesh Improved revenue performance including of the VAT.

Goa VAT appears to have had no impact on revenue performancein Goa. ST buoyancy may have improved by around 3% still

leaving it well below unity.

Jammu and Kashmir Improved revenue performance including of the VAT.

Manipur Improved revenue performance including of the VAT.

Meghalaya Improved revenue performance including of the VAT.

Mizoram Improved revenue performance including of the VAT.

Nagaland VAT performance is positive but overall SORR

performance has not improved.

Sikkim See discussion in the text.

Tripura ST/GSDP increased from a low level of 1%. No impact on

overall own revenue performance.

New Delhi VAT performance worse than the sales tax it replaced.

Overall revenue performance is unchanged.

of which combined statesBihar+Jharkhand VAT had no impact on revenue performance.

Madhya Pradesh+ VAT performance is positive but had no impact onChhattisgarh revenue performance.

Uttar Pradesh+ Improved revenue performance including of the VAT,

Uttarakhand though magnitude is small.

Table 6: Impact of VAT Introduction on GSDP (pooled regressions for all st ates on state dummy variables, a time trend, and VATperiod dummy variable)

LNGSDP (Eqn 6) ΔLNGSDP (Eqn 7)

Regression VAT Dummy Variable Regression VAT Dummy Variable

Signific ance Coeffici ent Significa nce Significa nce Coefficient Significa nce

Regression without combined states 0.000 0.024 0.484 0.000 -0.037 0.129

Regression with combined states 0.000 0.029 0.344 0.000 -0.030 0.178

Additional dummy variables for combined states are (a) from the year of states splitting, and (b) years during which only one of the

combined states implemented the VAT.

lost revenue so that the country as a whole gained. 26 To test

this, data were aggregated across all 29 states in the sample

and the following aggregate versions of equations (1) to (4)

were estimated:

LNST = B0+B

1LNG+B

2[VAT2003LNG]

+B3[VAT

2005LNG]+B

4[VAT

2006LNG]+B

5[VAT

2007LNG] (1c)

ST/G = B0+

B

1 VAT

2003+B

2 VAT

2005+B

4 VAT

2006

+B5 VAT

2007 (2c)

LNSORR = B0+B1LNG+B2[VAT2003LNG]+B3[VAT2005LNG]+B4[VAT2006LNG]+B5[VAT2007LNG] (3c)

SORR/G = B0+ B1 VAT2003+B2 VAT2005

+B4 VAT2006+B5 VAT2007 (4c)

Four VAT dummy variables were needed given that states

implemented the VAT in different years. For example, VAT2003

takes on the value 1 from 2003-04 onward to capture the VAT

effect of states implementing the VAT in 2003 (from Table 2

this was only Haryana). Results, including F-tests for the jointsignificance of the four VAT dummies are in Table 8 (p 60).

In Table 8, only the VAT dummies in equation (2c) are signifi-

cant. However, looking at the individual dummies in the equa-

tion only VAT2003, when Haryana alone introduced the VAT, is

significant. Furthermore states’ own revenues in equations

(3c) and (4c) were not significantly affected by the VAT. So it

may be concluded that revenue gainers from the VAT could not

compensate the losers.

Did Tax Evasion Reduce VAT Performance?

To what extent was VAT performance eroded by poor adminis-

tration permitting leakage through tax non-compliance? For this

the findings of the performance audit in CAG (2010) are revealing.The audit conducted during April-November 2009 covered 23

states27 and the post- VAT period 2005-06 to 2008-09, which is

precisely the VAT years included in the sample in this paper (bar-

ring Haryana’s early VAT years). Using the 2005 white paper of the

Empowered Committee of State Finance Ministers (ECSFM) which

set out desirable basic VAT design and tax administration (TA)

features as a benchmark, CAG (2010) assessed VAT performance.28

The main findings of importance for this paper were:

• Deficiencies in VAT acts and rules existed in many states.

• The large backlog of pending assessments under the prede-

cessor taxes burdened TAs.

• Incomplete automation, limited electronic return filing, and

differences in VAT returns and documents across states seri-

ously handicapped cross-verification of information in VAT

returns across VAT dealers within and across states.

• Inability or unwillingness to

cross-check information with

that available in other tax de-

partments like the central ex-

cise and customs departments.

• Ineffective procedures for veri-

fying ITC claims and detecting

fake ITC claims.

though they appear to cause downward bias in some cases.

Thus the hypothesis of VAT dummy coefficients being insignifi-

cant due to states gaming the centre can be safely rejected.

Downward bias of VAT dummy variables is, however, possible.

Can Winners Compensate Losers? Instead of counting states

with revenue improvements post VAT, an alternative is to see if

states gaining revenue from the VAT could compensate states that



SPECIAL ARTICLE


Table 7: Signs and Significances of VAT, PreVAT and PostVAT Dummy Variables

ST Buoyancy (eq 1b) ST/GSDP (eq 2b)

VAT - (eq 1) VAT PreVAT PostVAT VAT - (eq2) VAT PreVAT PostVAT

Andhra Pradesh 0.000 0.000 -0.020 -0.031 0.004* 0.005* 0.002 -0.003

Karnataka 0.008* 0.013* 0.173* -0.056 0.001 0.002 0.003 -0.001

Kerala -0.005 -0.004 0.008 -0.036 0.003 0.004 0.005 -0.004

Maharashtra -0.004 -0.002 0.114 0.033 0.001 0.001 0.006* 0.001

Orissa 0.008 0.009 0.126 0.077 0.008* 0.008* 0.005 0.001

Punjab 0.001 -0.001 0.127 0.207 0.005* 0.004 0.007 0.006

West Bengal 0.007* 0.012 0.163* -0.050 0.001 0.001 0.002 0.000

Arunachal

Pradesh 0.007 0.005 0.311 0.448 0.013* 0.015* 0.006 -0.004

Assam 0.007 0.010 0.263 0.164 0.015* 0.015* 0.015* 0.004

Himachal

Pradesh 0.022* 0.028* 0.164 -0.102 0.013* 0.015* 0.006* -0.0 05

Goa 0.018* 0.020* 0.041 -0.050 -0.014 -0.017 -0.021 0.002

Jammu

and Kashmir 0.023* 0.027* 0.243 0.039 0.022* 0.024* 0.013* -0.002

Manipur 0.029 0.038 0.120 -0.269 0.007* 0.009* 0.002 -0.005

Meghalaya 0.019* 0.021* 0.136 0.039 0.010* 0.011* 0.005 -0.001

Mizoram 0.026 0.031 0.299 0.099 0.011* 0.012* 0.006* -0.0 02

Nagaland 0.020* 0.021 0.024 0.008 0.005* 0.005* 0.002 0.000

Sikkim -0.020* -0.027 -0.208 0.022 0.013* 0.015* 0.009 -0.005

Tripura 0.010 0.011 0.035 -0.016 0.008* 0.009* 0.005 -0.002

New Delhi -0.010 -0.016 -0.114 0.179 0.006 0.006 0.006 0.004

(1) *: Significant at 95% or better. P-values are reported in the Appendix.

Table 8: Aggregate Regressi on Results for Equations (1c) to (4c)

Variable/Stati stic ST Buoyancy (Eqn 1c) ST/GSDP (Eqn 2c) SORR Buoyanc (Eqn 3c) SORR/GSDP (Eqn 4c)

Coeff P-Value Coeff P-Value Coeff P-Value Coeff P-Value

LNGSDP (Buoyancy) 1.050* 0.000 0.943* 0.000

VAT2003

*LNGSDP 0.003 0.227 0.003 0.197

VAT2005

*LNGSDP 0.002 0.550 0.002 0.501

VAT2006*LNGSDP 0.000 0.934 0.002 0.580VAT

2007*LNGSDP -0.002 0.569 0.000 0.968

VAT2003

0.004 0.028 0.002 0.467

VAT2005

0.002 0.402 0.003 0.598

VAT2006

0.001 0.809 0.003 0.638

VAT2007

-0.0 01 0.614 -0.0 01 0.876

R-Squared 0.996 0.712 0.995 0.393

F-Significance 0.000 0.009 0.000 0.244

F-Test: Joint significance of VATdummy variables 1.125 6.181* 1.800 2.037

F-test degrees of freedom (4.9) (4.10) (4.9) (4.10)

(1) Sample period was 1993-94 to 2007-08 due to missing 2008-09 data for two states.

(2) *: Significant at 99%.

• Most states were without tax administration procedure

manuals.

• Problems with VAT dealer registration procedures allowing non-

registration of some dealers and multiple registration of others.

• Penalties for VAT non-compliance were at the discretion of

TAs and often not levied.

On account of these TA deficiencies audit test checks of

around 1,00,000 dealers found widespread tax evasion and

avoidance through a variety of channels including (1) Under-declaration of sales and incorrect or false ITC claims by

50% of VAT dealers; (2) granting of incorrect VAT exemptions;

and (3) collection of VAT from customers which was not re-

mitted to state treasuries by some exempt dealers who con-

tinued to receive transitional benefits from earlier tax

incentive schemes.

These official performance audit findings, based on extensive

test checks, provide independent verification of the relatively

poor revenue performance of the VAT found in this paper. The

audit traces this to incomplete reforms and ineffective TAs.29 It

would be of interest to see if TA weakness can statistically ex-

plain poor revenue performance if state by state information

for the CAG report were made available. Note, however, that ad-

ministration of the predecessor sales taxes was also ineffective

as documented by several studies and o fficial reports.30 The

incapacity of TAs to successfully cope with administering a

new, sophisticated, tax like the VAT is strongly suggested by

the CAG performance audit.

Implications for Near Term Reform

Given the poor ability of states to cope with tax reforms docu-

mented by the CAG and the possible negative impact of this on

revenue is several states, further large-scale tax reform at this

stage appears premature, despite the three years of planning. TAs

will have to cope with a greatly expanded number of dealers

under the GST. Furthermore state TAs have no experience deal-ing with dealers providing services as there have been no gen-

eral state taxes on services. So while base broadening by

including services is desirable in due course, this should not be

attempted unless TAs expertise in taxing service providers.

Instead, performance benchmarks for TAs should be laid

down with respect to current TA weaknesses and procedures

in implementing the VAT on goods. Moving to a GST should

only be suggested if states can achieve the performance

benchmark as verified, for example, by another CAG perform-

ance audit.

For states which had a positive VAT revenue performance

but poor own revenue performance, attention should possi-

bly be diverted to other revenue sources. Such states includeChhattisgarh, Karnataka, Kerala, Madhya Pradesh, Naga-

land, Punjab and Rajasthan. For Goa and Gujarat causes of

apparently declining tax effort should be identified and

corrected. For Arunachal, Sikkim and Maharashtra further

assessment to identify causes of apparently contradictory or

insignificant revenue performance indicators is needed.

Are any base broadening (and conse-

quent tax rate lowering) options avail-

able for the existing VATs on goods?

One option is a move from 100% ITC to

partial ITC at, say, 20% of input taxes

paid by suppliers. As noted in the intro-

duction, there is no theoretical justifi-

cation of any efficiency benefit in coun-

tries like India from a 100% ITC. Evi-

dence in Table 6 also suggests the ab-

sence of efficiency benefits, though

data and methodological weaknesses

are present. Instead revenue loss due to

evasion and TA inability to administer

the ITC documented by the CAG will be

limited as will loss from a narrow base

with a partial ITC. Furthermore, “self



SPECIAL ARTICLE


Table A3: (ST/GSDP) = B1 + B2 VAT (Equation 2)

State R-Square F VAT Dummy Variable Dummy: Only Bihar/ Dummy: Years with

Signific ance (VAT) Uttarakhan d VAT Bifurcated States

Coeff P-Value Coeff Coeff P-Value Coeff

Andhra Pradesh 0.261 0.043 0.004* 0.043

Gujarat .0160 0.645 -0.002 0.645

Haryana 0.652 0.000 0.010* 0.000

Karnataka 0.032 0.526 0.001 0.526

Kerala 0.147 0.143 0.003 0.143Maharashtra 0.010 0.719 0.001 0.719

Orissa 0.607 0.000 0.008* 0.000

Punjab 0.247 0.050 0.005* 0.050

Rajasthan 0.418 0.007 0.008* 0.007

West Bengal 0.079 0.291 0.001 0.291

Tamil Nadu 0.299 0.028 -0.008* 0.028

Arunachal Pradesh 0.786 0.000 0.013* 0.000

Assam 0.588 0.001 0.015* 0.001

Himachal Pradesh 0.845 0.000 0.013* 0.000

Goa 0.146 0.144 -0.014 0.144

Jammu and Kashmir 0.749 0.000 0.022* 0.000

Manipur 0.592 0.000 0.007* 0.000

Meghalaya 0.817 0.000 0.010* 0.000

Mizoram 0.762 0.000 0.011* 0.000

Nagaland 0.752 0.000 0.005* 0.000

Sikkim 0.391 0.010 0.013* 0.010

Tripura 0.647 0.000 0.008* 0.000

New Delhi 0.107 0.216 0.006 0.216

Jharkhand+Bihar 0.065 0.839 -0.002 0.477 -0.002 0.657 0.001 0.437

Madhya Pradesh+

Chhattisgarh 0.884 0.000 0.006* 0.004 0.010 0.000

Uttar Pradesh+

Uttarakhand 0.982 0.000 0.007* 0.000 0.006 0.000 0.007 0.000

Table A4: LNSORR = B0+B1 LNGSDP+B2 [VAT.LNGSDP] (Equation 3)

State R-square F Buoyancy Slope Dummy Dummy for Only Bihar/ Dummy: Years

Signific ance Variable (VAT) Uttarakha nd VAT with Bifurcated

Implementati on States


Andhra Pradesh 0.987 0.000 1.013 0.000 0.004 0.315

Gujarat 0.986 0.000 0.799 0.000 0.003 0.373

Haryana 0.923 0.000 0.548 0.000 0.019 0.046

Karnataka 0.978 0.000 0.959 0.000 0.008 0.140

Kerala 0.994 0.000 1.005 0.000 0.002 0.394

Maharashtra 0.988 0.000 1.015 0.000 0.001 0.766

Orissa 0.979 0.000 1.061 0.000 0.011 0.097

Punjab 0.937 0.000 1.079 0.000 -0.005 0.533

Rajasthan 0.968 0.000 0.893 0.000 0.010 0.094

West Bengal 0.968 0.000 0.959 0.000 0.007 0.178

Tamil Nadu 0.995 0.000 0.865 0.000 0.005 0.063

Arunachal Pradesh 0.879 0.000 0.856 0.007 0.077 0.003

Assam 0.982 0.000 1.214 0.000 0.013 0.024

Himachal Pradesh 0.943 0.000 1.103 0.000 0.024 0.044

Goa 0.952 0.000 0.756 0.000 -0.007 0.428

Jammu and Kashmir 0.986 0.000 1.297 0.000 0.014 0.023Manipur 0.901 0.000 0.634 0.001 0.050 0.003

Meghalaya 0.971 0.000 1.017 0.000 0.011 0.146

Mizoram 0.965 0.000 0.581 0.000 0.050 0.000

Nagaland 0.914 0.000 0.789 0.000 0.024 0.040

Sikkim 0.462 0.018 1.271 0.016 -0.041 0.418

Tripura 0.986 0.000 1.223 0.000 -0.008 0.156

New Delhi 0.937 0.000 1.367 0.000 -0.011 0.383

Bihar+Jharkhand 0.932 0.000 0.821 0.001 0.007 0.537 0.095 0.628 0.057 0.728

Madhya Pradesh+

Chhattisgarh 0.983 0.000 1.128 0.000 0.001 0.875 0.085 0.297

Uttar Pradesh+

Uttarakhand 0.987 0.000 0.812 0.000 0.017 0.013 0.259 0.008 0.214 0.019

intercept dummies variables and both GSDPt-1

and GSDP

t were unreliable with high multicol-

linearity. These are not r eported here.

12 (5) also serves as a partial data consistencycheck by comparing its VAT

t coefficient sign

and significance with that of VATt coefficients

in (2) and (4).

13 Keen and Lockwood (2006, 2007) use log (reve-nue/GDP) as their dependent variable. This is

equivalent to a restricted regression with GDPbuoyancy constrained to have the value 1.

14 Special category states include ArunachalPradesh, Assam, Himachal Pradesh, Jammuand Kashmir, Manipur, Meghalaya, Mizoram,Nagaland, Tripura and Sikkim (Saxena 2009).

15 Given the poor estimation results from thismodel, a simultaneous model with VAT

t and

GSDPt as dependent variables and additional

GSDP determinants was not specified.

16 As Keen (2009) puts it “Such a dummy varia-ble, though, is a very noisy indicator…. VATsdiffer enormously amongst themselves: in t heextent of exemptions, threshold, number ofrates, ease of obtaining refunds, treatment ofserv ices …” (p 162).

17 Government of India, Comptroller and AuditorGeneral (2010) abbreviated CAG.

18 An Excel file with data used is available athttp://www.gim.ac.in/data/32 states chainedGSDP and RBI rev data 93-94 to 08-09.xls.

19 The very high VAT buoyancy in Arunachal andits low VAT/GSDP ratio, discussed later, shouldbe noted in interpreting results.

20 That Maharashtra already had partial ITCprior to 2005 could be the cause of the insigni-ficant dummies found here. This requires fur-ther study.

21 With unchained GSDP, major states with sig-nificant, positive VAT dummies decreased fromfour to two while states with significant, nega-tive VAT buoyancy dummies increased fromone to two. Significances of either buoyancy orratio dummies changed for Andhra Pradesh,Gujarat, Karnataka, Rajasthan and West Ben-gal. VAT buoyancy and GSDP shares were bothsignificantly positive for Rajasthan and both

significantly negative for Kerala. The buoyancydummy for Maharashtra was significantly neg-ative. For SORR, no major state had a positive significant VAT buoyancy dummy . The SORR/GSDP VAT dummy for Andhra Pradesh was in-significant. Thus VAT performance is worse with unchained GSDP. For non-major states,dummy signs and significances were identicalto those with chained GSDP except that theSORR/GSDP ratio VAT dummy for Mizoram was insignificant.

22 The average annual GSDP growth rate of sam-ple states fell from 12.3% in pre-VAT years to11.7% post -VAT implementation.

23 Significances of coefficients with unchainedGSDP were identical though estimated coeffi-cients were somewhat larger.

24 The Economic Times (2004): Describes the com-

pensation scheme. The possibility of statesgaming the centre is reported, 23 September,for example, in Gupta (2005), 16 September.

25 Thanks are due to Kavita Rao who flagged thispossibility, which led to this robustness check.

26 Grateful thanks are due to Pulin Nayak for sug-gesting this check.

27 That is all states studied here excludingHaryana, Uttar Pradesh, Uttarakhand, Punjab, Arunachal Pradesh and Tamil Nadu.

28 The ECSFM was set up by the centre in 1999 tocoordinate VAT designs across states and arriveat a consensus design. The consensus design was described in the white paper (CAG 2010).The ECSFM currently plays the same roleacross states with respect to the planned GST.



SPECIAL ARTICLE


29 It should be noted that administration of thepredecessor sales taxes was also ineffective as was documented by several studies and officialreports.

30 An example is Chapter 3 in World Bank (2005).

References

Bird, Richard (2011): “The BBLR Approach to TaxReform in Emerging Countries” in M G Raoand M Rakshit (ed.), Public Economics: Theoryand Policy (New Delhi: Sage Publishers).

Bird, Richard M and Pierre-Pascal Gendron (2007):The VAT in Developing and Transitional Coun-tries (Cambridge and New York: CambridgeUniversity P ress).

CA.inINDIA.Org (2011): e-bible for chartered ac-countants, available at http://www.cainindia.org/news/6_2008/vat_value_added_tax_2008_india_news_.html, accessed 8 March.

Chelliah, R J and Kavita Rao (1999): A Pr imer onthe Value Added Tax, National Institute ofPublic Finance and Policy, New Delhi.

Das-Gupta, Arindam (2005): “With Non-competi-tive Firms, a Turnover Tax Can Dominate the VAT”, Economics Bulletin , Vol 8, No 9, pp 1-6,available at http://www.economicsbulletin.com/

2005/volume8/EB−05H20003A.pdf, last ac-cessed March 2011.

Diamond, P and J Mirrlees (1971): “Optimal Taxa-tion and Public Production I: Production Effi-ciency”, American Economic Review, 61, 8-27.

Ebrill, L, M Keen, J Bodin and V Summers (2001):The Modern VAT (Washington DC: InternationalMonetary Fund).

Emran, M Shahe and Joseph E Stiglitz (2005): “OnSelective Indirect Tax Reform in DevelopingCountries”, Journal of Public Economics, El sevier, Vol 89(4), pp 599-623, April.

Government of India, Comptroller and AuditorGeneral (2010): “Implementation of Value Add-ed Tax in India – Lessons for Transition toGoods and Services Tax – A Study Report”,Comptroller and Auditor General, New Delhi,available at http://cag.gov.in/SRA-value-add-

ed-tax.pdf, accessed on 10 October 2011.Government of India, Ministry of Statistics andProgramme Implementation (MOSPI) (2007):“Statement: Gross State Domestic Product atCurrent Prices” available at http://mospi.nic.in/statewise_sdp1999_2000_8feb10.pdf on 11 Nov-ember 2009.

Government of Maharashtra (2000): “Report of theExpert Group to Review Value Added Tax inMaharashtra” (Valluri Narayan Committee),Government of Maharashtra, Mumbai.

Government of Tamil Nadu, Commercial TaxesDepartment (no date): “Tamil Nadu Value Added Tax”, http://www.tnvat.gov.in, ac-cessed on 8 March 2011.

Gupta, Monica (2005): “States Underplay VATGains to Get Aid”, 16 September, BusinessStandard online edition, available at http:// www.business -standard.com/india/news/

states-underplay-vat-gains-to-get-aid/220653/,accessed on 20 October 2011.

Halakhandi, Sudhir (2007): “CA Club India – Inter-active Platform for Finance Professionals andTax Payers”, http://www.caclubindia.com/ar-ticles/value-added-tax-for-students-1508.asp,accessed on 8 March 2011.

Jafari, Samimi, Ahmad and Fereshte Talesh Salehani(2010): “VAT and Governance: Evidence fromCountries around the World”, Australian Journalof Basic and Applied Sciences, 4(10): 4852-56,available at http://www.insipub.com/ajbas/2010/4852-4856.pdf, last accessed March 2011.

Keen, Michael (2009): “What Do (and Don’t) WeKnow about the Value Added Tax?”, A Reviewof Richard M Bird and Pierre-Pascal Gendron’s

Table A5: LNSORR = B0+B1 LNGSDP-1+B2 [VAT-1 LNGSDP-1] (Equation 3a)

State R-square F Buoyancy Slope Dummy Dummy for Only Bihar/ Dummy: Years

Signi ficance (lagged GSDP) Variable Uttarakha nd VAT with Bifurcated

(lagged VAT) Implementati on States


Andhra Pradesh 0.990 0.000 1.029 0.000 0.005 0.168

Gujarat 0.990 0.000 0.791 0.000 0.004 0.214

Haryana 0.908 0.000 0.421 0.006 0.027 0.013

Karnataka 0.960 0.000 0.917 0.000 0.013 0.086Kerala 0.987 0.000 0.931 0.000 0.007 0.066

Maharashtra 0.988 0.000 0.958 0.000 0.006 0.075

Orissa 0.965 0.000 1.062 0.000 0.014 0.111

Punjab 0.939 0.000 0.935 0.000 0.004 0.610

Rajasthan 0.957 0.000 0.836 0.000 0.015 0.030

West Bengal 0.959 0.000 0.907 0.000 0.010 0.074

Tamil Nadu 0.987 0.000 0.826 0.000 0.007 0.063

Arunachal Pradesh 0.873 0.000 0.984 0.011 0.074 0.009

Assam 0.986 0.000 1.294 0.000 0.011 0.043

Himachal Pradesh 0.930 0.000 1.052 0.000 0.027 0.041

Goa 0.948 0.000 0.673 0.000 -0.003 0.679

Jammu and Kashmir 0.982 0.000 1.299 0.000 0.012 0.068

Manipur 0.890 0.000 0.561 0.005 0.053 0.004

Meghalaya 0.962 0.000 0.958 0.000 0.015 0.080

Mizoram 0.958 0.000 0.573 0.000 0.051 0.000

Nagaland 0.918 0.000 0.671 0.000 0.028 0.015

Sikkim 0.399 0.047 0.501 0.109 0.004 0.902

Tripura 0.984 0.000 1.212 0.000 -0.011 0.075

Delhi 0.992 0.000 1.029 0.000 0.007 0.071

Bihar+Jharkhand 0.932 0.000 0.975 0.002 0.005 0.665 -0.005 0.980 -0.046 0.794

Madhya Pradesh+

Chhatt isgarh 0.976 0.000 1.198 0.000 0.004 0.520 0.010 0.920

Uttar Pradesh+

Uttarakhand 0.982 0.00 0 0.792 0.000 0.020 0.013 0.307 0.007 0.191 0.077

Table A6: (SORR/GSDP) = B1+B2 VAT (Equation 4)

State R-Square F VAT Dummy Variable Dummy: for Only Bihar/ Dummy: Years with

Signific ance Uttarakhand VAT Bifurcated States

Coeff P-Value Coeff P-Value Coeff P-Value

Andhra Pradesh 0.228 0.061 0.008 0.061

Gujarat 0.265 0.042 -0.015 0.042

Haryana 0.131 0.168 -0.023 0.168

Karnat aka 0.173 0.123 0.010 0.123

Kerala 0.150 0.138 0.003 0.138

Maharashtra 0.055 0.382 0.003 0.382

Orissa 0.579 0.001 0.017 0.001

Punjab 0.003 0.832 -0.002 0.832

Rajasthan 0.051 0.401 0.005 0.401

West Bengal 0.152 0.135 0.004 0.135

Tamil Nadu 0.124 0.180 -0.008 0.180

Arunachal Pradesh 0.634 0.000 0.074 0.000

Assam 0.749 0.000 0.025 0.000

Himachal Pradesh 0.522 0.002 0.035 0.002

Goa 0.397 0.009 -0.073 0.009

Jammu and Kashmir 0.669 0.000 0.029 0.000Manipur 0.280 0.035 0.012 0.035

Meghalaya 0.355 0.015 0.008 0.015

Mizoram 0.083 0.280 0.008 0.280

Nagaland 0.099 0.253 0.005 0.253

Sikkim 0.126 0.178 -0.301 0.178

Tripura 0.085 0.273 0.004 0.273

New Delhi 0.192 0.089 0.014 0.089

Jharkhand+Bihar 0.051 0.856 -0.001 0.895 0.002 0.868 -0.004 0.497

Madhya Pradesh+

Chhattisgarh 0.584 0.003 0.007 0.213 0.013 0.008

Uttar Pradesh+

Uttarakhand 0.709 0.002 0.012 0.027 0.014 0.014 0.007 0.079



SPECIAL ARTICLE


Table A7: ST/SORR = B1+ B2 VAT (Equation 5)

State R-Square F VAT Dummy Variable Dummy: for Only Bihar/ Dummy: Years with

Significa nce Uttarakha nd VAT Bifurcated States


Andhra Pradesh 0.002 0.865 -0.003 0.865

Gujarat 0.411 0.007 0.236 0.007

Hary ana 0.431 0.006 0.142 0.006

Karnataka 0.187 0.108 -0.032 0.108

Kerala 0.014 0.658 0.010 0.658

Maharashtra 0.008 0.740 -0.006 0.74

Orissa 0.000 0.996 0.000 0.996

Punjab 0.375 0.012 0.056 0.012

Rajasthan 0.249 0.049 0.067 0.049

West Bengal 0.089 0.262 -0.025 0.262

Tamil Nadu 0.543 0.001 -0.039 0.001Arunachal Pradesh 0.263 0.042 0.082 0.042

Assam 0.137 0.158 0.047 0.158

Himachal Pradesh 0.079 0.292 0.034 0.292

Goa 0.234 0.058 0.065 0.058

Jammu and Kashmir 0.596 0.001 0.166 0.001

Manipur 0.312 0.025 0.215 0.025

Meghalaya 0.661 0.000 0.138 0.000

Mizoram 0.493 0.002 0.168 0.002

Nagaland 0.325 0.027 0.098 0.027

Sikkim 0.089 0.262 0.021 0.262

Tripura 0.824 0.000 0.177 0.000

New Delhi 0.248 0.050 -0.038 0.050

Bihar+Jharkhand 0.283 0.247 -0.021 0.473 -0.042 0.353 0.049 0.055

Madhya Pradesh+

Chhattisgarh 0.872 0.000 0.039 0.008 0.067 0.000Uttar Pradesh+

Uttarakhand 0.443 0.063 0.010 0.751 -0.0 03 0.915 0.055 0.024

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Table A9: LNSORR = B0+B1 LNGSDP+B2 [VAT.LNGSDP]+B3 PreVAT+B4 PostVAT

State R-Square F VAT Slope PreVAT PostVAT

Significa nce Dummy


Andhra Pradesh 0.318 0.189 0.00 5 0.038 0.002 0.552 -0.003 0.441

Karnatak a 0.085 0.796 0.002 0.480 0.003 0.460 -0.001 0.817

Kerala 0.353 0.143 0.004 0.052 0.005 0.129 -0.004 0.303

Maharashtra 0.327 0.176 0.001 0.558 0.006 0.035 0.001 0.859

Orissa 0.707 0.002 0.008 0.001 0.005 0.072 0.001 0.659

Punjab 0.466 0.050 0.004 0.109 0.007 0.102 0.006 0.206

West Bengal 0.160 0.536 0.001 0.273 0.002 0.307 0.000 0.888

Arunachal Pradesh 0.853 0.000 0.015 0.000 0.006 0.077 -0.0 04 0.2 02

Assam 0.774 0.000 0.015 0.000 0.015 0.010 0.004 0.527

Himachal Pradesh 0.924 0.000 0.015 0.000 0.0 06 0.013 -0.005 0 .062

Goa 0.242 0.326 -0.017 0.143 -0.021 0.243 0.002 0.898

Jammu and Kashmir 0.855 0.000 0.024 0.000 0.013 0.017 -0.002 0.695

Manipur 0.672 0.003 0.009 0.000 0.002 0.486 -0.005 0.146

Meghalaya 0.883 0.000 0.011 0.000 0.005 0.026 -0.001 0.617

Mizoram 0.847 0.000 0.012 0.000 0.006 0.031 -0.002 0.422

Nagaland 0.784 0.001 0.005 0.000 0.002 0.236 0.000 0.824

Sikkim 0.464 0.051 0.015 0.010 0.009 0.289 -0.005 0.537

Tripura 0.718 0.001 0.009 0.000 0.005 0.130 -0.002 0.560

New Delhi 0.142 0.591 0.006 0.342 0.006 0.573 0.004 0.702

Table A8: LNST = B0+B1 LNGSDP+B2 [VAT.LNGSDP]+B3 PreVAT+B4 PostVAT

State R-Square F VAT Slope Dummy PreVAT PostVAT

Significa nce Variable


Andhra Pradesh 0.993 0.000 0.000 0.963 -0.020 0.801 -0.031 0.696

Karnatak a 0.997 0.000 0.013 0.000 0.173 0.003 -0.056 0.255

Kerala 0.998 0.000 -0.004 0.082 0.008 0.825 -0.036 0.362

Maharashtra 0.991 0.000 -0.002 0.609 0.114 0.161 0.033 0.673

Orissa 0.987 0.000 0.009 0.202 0.126 0.286 0.077 0.501

Punjab 0.972 0.000 -0.001 0.892 0.127 0.374 0.207 0.170

West Bengal 0.995 0.000 0.012 0.0 00 0.163 0.003 -0.050 0.286

Arunachal Pradesh 0.819 0.000 0.005 0.960 0.311 0.827 0.448 0.748

Assam 0.977 0.000 0.010 0.294 0.263 0.126 0.164 0.317

Himachal Pradesh 0.995 0.000 0.028 0.000 0.164 0.066 -0.102 0.234

Goa 0.991 0.000 0.020 0.001 0.041 0.629 -0.050 0.555

Jammu and Kashmir 0.988 0.000 0.027 0.009 0.243 0.122 0.039 0.801

Manipur 0.730 0.004 0.038 0.438 0.120 0.876 -0.269 0.723

Meghalaya 0.993 0.000 0.021 0.004 0.136 0.171 0.039 0.683

Mizoram 0.975 0.000 0.031 0.174 0.299 0.377 0.099 0.763

Nagaland 0.977 0.000 0.021 0.068 0.024 0.877 0.008 0.957

Sikkim 0.984 0.000 -0.027 0.061 -0.208 0.266 0.022 0.900

Tripura 0.991 0.000 0.011 0.126 0.035 0.766 -0.016 0.891

New Delhi 0.935 0.00 0 -0.016 0.328 -0.114 0.695 0.179 0.539

an assessment of revenue impact of state level vat in india.pdf

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