Upload
others
View
1
Download
0
Embed Size (px)
Citation preview
The Elasticity of Corporate Taxable Income -Evidence from South Africa I
Collen Ledigaa, Nadine Riedela,b,∗, Kristina Strohmaierc
aUniversity of BochumbCESifo Munich
cUniversity of Tubingen
Abstract
How strongly do firms reduce their reported taxable income when corporate tax
rates increase? We add new evidence from an emerging economy to a so far
developed-country-dominated literature.
Keywords: Corporate taxation, developing countries, bunching
1. Introduction
While a growing empirical literature assesses behavioral responses to corporate
taxation in industrialized economies, limited access to corporate micro data has
largely prevented analogous analyses for less developed countries. Our study
helps filling this gap. We draw on the population of corporate tax returns in5
South Africa in 2009–2015 to determine the elasticity of corporate taxable in-
come by exploiting non-linearities in the corporate tax schedule. The analysis
yields large elasticities for firms with incomes around the first kink (∼70,000
South African Rand or e5,000 p.a.), while entities with incomes around the
second and third kink (∼R365,000 and ∼R550,000 p.a.) respond only moder-10
ately to marginal tax increases.
Two further insights emerge. Firstly, we show that firms bunch at zero cor-
porate taxable income. This supports Johannesen et al. (2016) who report a
∗Corresponding author: Nadine Riedel, Email: [email protected]
Preprint submitted to Elsevier 10th June 2018
similar pattern for multinational entities and interpret it as evidence for inter-
national income shifting. Our data suggests that zero is also a focal point for15
domestic tax avoidance and evasion - despite the fact that, for many firms, the
South African tax provisions imply no, or even disincentives, for bunching beha-
vior. This supports the notion of some taxpayers having imperfect information
on the tax code (Hoopes et al., 2015).
Finally, we follow prior papers and assess how firms manage to bunch at20
kink points. As total assets, sales, costs and other accounting measures show no
major discontinuities at our tax thresholds, bunching firms do not systematically
differ from other entities near the kinks. This contrasts prior findings (see,
e.g., Bachas and Soto, 2016), which suggest that corporate tax responses are
dominated by cost-overreporting.125
2. Institutional Background, Data and Methodology
South Africa is an upper-middle-income economy with a tax-to-GDP ratio of
29% in 2015 (compared to a 34%-OECD-average).2 It levies a “standard” tax
rate of 28% on corporate income and applies a progressive “Small Business
Corporations” (SBCs) tax scheme, where income of eligible businesses is taxed30
at lower rates. Kinks in the SBC-schedule will in the following be used to identify
the corporate taxable income elasticity. Figure 1 depicts the three kinks of the
marginal tax rate schedule for 2015.3
To quantify behavioral responses to taxation, we estimate the elasticity of
taxable income (ETI), which captures all kinds of behavioral responses including35
real production shifts, tax avoidance and tax evasion. We employ the nonpara-
metric approach of Saez (2010), which exploits clustering of firms around tax
1After finalizing the first working paper version, we became aware of Boonzaaier et al.(2017) who equally estimate corporate income elasticities in South Africa. Compared to theirstudy, our data offers the advantage that firms subject to SBC-taxation can be clearly iden-tified, which allows for more precise estimates and may explain differences in result patterns.Contrary to others (including Boonzaaier et al., 2017), we moreover assess bunching at zerocorporate taxable income.
2Information on tax-to-GDP ratios was obtained from OECD revenue statistics.3See http://www.sars.gov.za for tax schedules in all years and eligibility criteria.
2
Figure 1: SBC Tax Schedule 2015
Taxable income
Mar
gin
al
Tax
Rat
e
R70, 700 R365, 000 R550, 000
10%
20%
30%
kinks. To estimate the excess mass of firms around the kink, we determine the
counterfactual density by running a local polynomial regression on binned data,
while excluding bins within the bunching window. The latter is determined40
by an endogenous data-driven procedure (Dekker et al., 2016). To account for
increasing tax thresholds over time when pooling the tax years, the data is res-
caled relative to the threshold and a weighted average value is used. Finally, we
only pool years with identical changes in marginal tax rates at a given kink.
3. Results45
3.1. Bunching at Kinks in the Tax Schedule
Figure 2 shows the distribution of firms at the first kink in the SBC tax schedule.
The data is subdivided in two time periods, 2009–2012 and 2013–2016, as the
marginal tax jump differs between the intervals (being 0 to 10% in the former
case and 0 to 7% in the latter).50
For both time spans, we see clear bunching for firms under the SBC tax
schedule (and no bunching for Non-SBCs). For the years 2010–2012 (2013–
2016), we estimate a highly significant excess mass of taxpayers b = 6.62 (b =
7.48). Using a weighted average for the threshold value4, this translates into an
4We calculate this weighted average using the share of bunchers as weights.
3
Figure 2: Bunching at the First Threshold
050
010
0015
0020
00Fr
eque
ncy
-20000 -10000 0 10000 20000Distance First Threshold
SBCs, 2010-2012b: 6.6214 b_se: 0.2683 e: 0.7913 binwidth: 717
600
800
1000
1200
1400
Freq
uenc
y
-20000 -10000 0 10000 20000Distance First Threshold
Non-SBCs, 2010-2012b: 0.0594 b_se: 0.0646 e: 0.0095 binwidth: 964
050
010
0015
00Fr
eque
ncy
-20000 0 20000Distance First Threshold
SBCs, 2013-2016b: 7.4797 b_se: 0.3589 e: 1.3280 binwidth: 847
500
600
700
800
900
1000
Freq
uenc
y
-20000 0 20000Distance First Threshold
Non-SBCs, 2013-2016b: -0.0727 b_se: 0.0639 e: -0.0179 binwidth: 1176
Notes: Observed distribution: Blue dotted line; Estimated counterfactual: Grey dotted line.
ETI of e = 0.79 (e = 1.33).55
Table 1 reports the results for the other two thresholds. Firms respond
at both income levels. Compared to the lowest threshold, the bunching at
the second and third threshold translates into significantly smaller elasticity
estimates though (ranging between 0.08 and 0.15).
While existing papers report large tax elasticities in less developed country60
contexts (see, e.g., Waseem, 2018), we find mixed evidence for the corporate
income tax in South Africa. Specifically, our results point to moderate tax
elasticities—similar in size to developed country estimates—for larger SBCs at
the upper two kinks; the elasticities at the lower end of the income distribu-
tion are, in turn, sizable and well exceed their developed country counterparts,65
compare e.g. evidence for the UK in Devereux et al. (2014).5 This pattern may
5Devereux et al. (2014) report an ETI for the UK of 0.14–0.18 (0.54–0.57) for companieswith profits around the £300k kink (£10k kink).
4
root in differences in institutional and economic tax evasion constraints faced
by entities of different size.6
Table 1: Results Bunching Analyses
Bunching window binwidth excess mass se elasticity
Second threshold2010–2012 [ -10,362 ; 6,705 ] 1219 6.6147 0.5023 0.12052013 [ -6,090 ; 2,610 ] 1740 4.3389 0.3732 0.08432014–2016 [ -10,230 ; 930 ] 1860 3.8754 0.2484 0.1210
Third threshold2014–2016 [ -3,792 ; 1,264 ] 2528 2.9359 0.3142 0.1454
3.2. Bunching at Zero
On top, one of the most salient features of our corporate taxable income dis-70
tribution is that firms strongly bunch at a taxable income of zero, cf. Figure 3
for active7 SBCs and Non-SBCs in 2009–2015. Strikingly, this aspect has been
largely ignored in the existing literature - except for a recent paper by Johan-
nesen et al. (2016), who show that multinational firms bunch at zero income
and interpret the pattern as evidence for international tax avoidance.75
As SBCs are by definition domestic entities, the results in Johannesen et al.
(2016) are found to carry over to national entities in our analysis, despite the fact
that the South African tax schedule provides no or even disincentives for SBCs
to bunch at zero.8 One possible explanation for the pattern is that taxpayers
have incomplete information on the business tax schedule (see, e.g., Hoopes80
et al., 2015) and zero is a focal point for domestic evasion/avoidance strategies
based on these false perceptions.9
6We tested for differences in response rates along observed dimensions other than size,namely industry affiliation and host region and found no evidence of systematic variation.
7=firms with positive sales and deductions8Above zero, income is exempted from taxation; below zero, indefinite loss-carryforward
provisions in the South African tax schedule provide an implicit tax subsidy (see, e.g., Domarand Musgrave, 1944), making the budget set convex or linear. For Non-SBCs, the budget setis linear around zero if they expect positive future income.
9A quantitative interpretation (yielding an ETI) is not straightforward at zero, given that
5
Figure 3: Bunching at Zero
020
0040
0060
0080
00Fr
eque
ncy
-20000 0 20000Distance Zero Threshold
b: 11.8494 b_se: 0.4539 e: - binwidth: 446SBCs
050
000
1000
0015
0000
2000
0025
0000
Freq
uenc
y
-20000 0 20000Distance Zero Threshold
b: 29.7389 b_se: 1.0126 e: - binwidth: 471Non-SBCs
3.3. Anatomy of Response
Finally, we follow previous papers and plot the median of total assets, sales
and total costs of sales against taxable income around the kinks to determine85
how firms bunch (cf. Figure 4). We cannot detect any clear anomalies except
for a small jump in costs for the second threshold. These findings contrast
recent evidence (see, e.g., Bachas and Soto, 2016), which suggests that firms’
tax responses are dominated by tax evasion through cost-overreporting. Our
results are, in turn, consistent with evasion by a proportional underreporting of90
sales, deductions and assets (with evading firms “mimicking” taxpayers at the
threshold) and with real responses - hence underpinning that response margins
may differ across countries and institutional contexts.
4. Conclusion
Three conclusions follow: First, the pattern of identified tax elasticities suggests95
that progressive business taxation may be optimal from an efficiency perspective.
Second, if zero serves as a focal point for (domestic) tax evasion/avoidance
strategies, variation in “zero-bunching” across time and across firm-subgroups
may be used to identify correlates of evasion/avoidance behavior. Third, our
there are no (clear) jumps in the marginal tax rates and relative income responses cannot becalculated. The estimated excess mass for SBCs (Non-SBCs) is 11.8 (29.7).
6
Figure 4: Anatomy of Response
(a) Total Assets (log)
(b) Sales (log)
(c) Total Costs (log)
Notes: The panels show the medians of total assets, sales and costs around the first and secondthreshold for SBCs (filled, blue dots) and Non-SBCs (non-filled, grey dots).
7
analysis stresses that tax response margins may depend on institutional contexts100
and that findings for one country may not carry over to others.
References
Pierre Bachas and Mauricio Soto. Not(ch) your average tax system: Corporate
taxation under weak enforcement. mimeo, 2016.
Wian Boonzaaier, Jarkko Harju, Tuomas Matikka, and Jukka Pirttila. How105
do small firms respond to tax schedule discontinuities? Evidence from south
african tax registers. VATT Working Papers, 2017.
Vincent Dekker, Kristina Strohmaier, and Nicole Bosch. A data-driven proced-
ure to determine the bunching window - an application for the netherlands.
CPB Discussion Paper, 2016.110
Michael P. Devereux, Li Liu, and Simon Loretz. The elasticity of corporate
taxable income: New evidence from UK tax records. American Economic
Journal: Economic Policy, 6(2):19–53, May 2014.
E. Domar and R.A. Musgrave. Proportional income taxation and risk-taking.
Quarterly Journal of Economics, 58:388–422, 1944.115
Jeffrey L. Hoopes, Daniel Reck, and Joel Slemrod. Taxpayer search for inform-
ation: Implications for rational inattention. American Economic Journal:
Economic Policy, 7(3):177–208, 2015.
Niels Johannesen, Thomas Tørsløv, and Ludvig Wier. Are less developed coun-
tries more exposed to multinational tax avoidance? Method and evidence120
from micro-data. WIDER Working Paper, 2016.
Emmanuel Saez. Do taxpayers bunch at kink points? American Economic
Journal: Economic Policy, 2(3):180–212, 2010.
Mazhar Waseem. Taxes, informality and income shifting: Evidence from a
recent pakistani tax reform. Journal of Public Economics, 157:41–77, 2018.125
8